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stringlengths 2.11k
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Table InputTable: [["Player", "No.", "Nationality", "Position", "Years for Jazz", "School/Club Team"], ["Greg Foster", "44", "United States", "Center/Forward", "1995-99", "UTEP"], ["Jim Farmer", "30", "United States", "Guard", "1988-89", "Alabama"], ["Todd Fuller", "52", "United States", "Center", "1998-99", "North Carolina State"], ["Derek Fisher", "2", "United States", "Guard", "2006-2007", "Arkansas-Little Rock"], ["Derrick Favors", "15", "United States", "Forward", "2011-present", "Georgia Tech"], ["Terry Furlow", "25", "United States", "Guard/Forward", "1979-80", "Michigan State"], ["Bernie Fryer", "25", "United States", "Guard", "1975-76", "BYU"], ["Kyrylo Fesenko", "44", "Ukraine", "Center", "2007-11", "Cherkasy Monkeys (Ukraine)"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:who has the same number as greg foster?
|
Kyrylo Fesenko
| 128
|
Answer:
|
Table InputTable: [["Year", "Single", "Chart Positions\\nUS Country", "Chart Positions\\nUS", "Album"], ["1964", "\"Th' Wife\"", "45", "—", "singles only"], ["1963", "\"Bad News\" (b/w \"Guitar Player(Her and Him)\")", "23", "—", "singles only"], ["1965", "\"That Ain't All\"", "20", "—", "singles only"], ["1968", "\"Odd Folks of Okracoke\"", "—", "—", "single only"], ["1957", "\"Sittin' in the Balcony\"", "—", "38", "single only"], ["1964", "\"Blue Train (Of the Heartbreak Line)\"", "44", "132", "singles only"], ["1962", "\"Thou Shalt Not Steal\"", "—", "73", "singles only"], ["1962", "\"Callin' Dr. Casey\"", "—", "83", "singles only"], ["1966", "\"You're the Guilty One\"", "—", "—", "single only"], ["1962", "\"Road Hog\"", "—", "65", "Twelve Sides"], ["1967", "\"It's My Time\"", "51", "—", "Suburban Attitudes in Country Verse"], ["1966", "\"Silver Cloud Talkin' Blues\"", "—", "—", "A Bizarre Collection of the Most Unusual Songs"], ["1961", "\"Language of Love\"", "—", "32", "Language of Love"], ["1979", "\"Every Day I Learn a Little More About Love\"", "—", "—", "Just Passing Through"], ["1969", "\"Brown Girl\"", "—", "—", "The Open Mind of John D. Loudermilk"], ["1971", "\"Lord Have Mercy\"", "—", "—", "Volume 1-Elloree"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:besides "th' wife", what other single came out in 1964?
|
"Blue Train (Of the Heartbreak Line)"
| 128
|
Answer:
|
Table InputTable: [["Contestant", "Original Tribe", "Switched Tribe", "Merged Tribe", "Finish", "Total Votes"], ["Kris Kelmi\\n47.the singer", "Barracudas", "", "", "2nd Voted Out\\nDay 6", "1"], ["Aleksandr Pashutin\\n60.the actor", "Barracudas", "", "", "3rd Voted Out\\nDay 9", "7"], ["Aleksandr Byalko\\n50.the physicist", "Pelicans", "Barracudas", "", "5th Voted Out\\nDay 15", "6"], ["Aleksandr Lykov\\n41.the actor", "Barracudas", "Barracudas", "Crocodiles", "13th Voted Out\\n8th Jury Member\\nDay 37", "6"], ["Vera Glagoleva\\n46.the actress", "", "", "Crocodiles", "11th Voted Out\\n6th Jury Member\\nDay 33", "4"], ["Larisa Verbitskaya\\n43.the TV presenter", "Barracudas", "Pelicans", "Crocodiles", "12th Voted Out\\n7th Jury Member\\nDay 36", "11"], ["Yelena Proklova\\n49.the TV presenter", "Pelicans", "Barracudas", "Crocodiles", "8th Voted Out\\n3rd Jury Member\\nDay 24", "4"], ["Olga Orlova\\n25.the singer", "Barracudas", "Baracudas", "Crocodiles", "Eliminated\\n9th Jury Member\\nDay 38", "10"], ["Yelena Kondulaynen\\n44.the actress", "Pelicans", "", "", "1st Voted Out\\nDay 3", "5"], ["Viktor Gusev\\n47.the sport commentator", "Pelicans", "Pelicans", "Crocodiles", "7th Voted Out\\n1st Jury Member\\nDay 21", "6"], ["Ivar Kalnynsh\\n54.the actor", "", "", "Crocodiles", "10th Voted Out\\n5th Jury Member\\nDay 30", "3"], ["Ivan Demidov\\n39.the TV presenter", "Barracudas", "Pelicans", "Crocodiles", "Eliminated\\n2nd Jury Member\\nDay 23", "3"], ["Tatyana Dogileva\\n45.the actress", "Pelicans", "Barracudas", "", "6th Voted Out\\nDay 18", "3"], ["Marina Aleksandrova\\n20.the actress", "Barracudas", "Pelicans", "Crocodiles", "9th Voted Out\\n4th Jury Member\\nDay 27", "6"], ["Dana Borisova\\n26.the TV presenter", "Pelicans", "Barracudas", "", "4th Voted Out\\nDay 12", "5"], ["Igor' Livanov\\n49.the actor", "Pelicans", "", "", "Eliminated\\nDay 11", "0"], ["Tat'yana Ovsiyenko\\n36.the singer", "Barracudas", "Pelicans", "", "Eliminated\\nDay 19", "1"], ["Vladimir Presnyakov, Jr.\\n34.the singer", "Pelicans", "Pelicans", "Crocodiles", "Sole Survivor", "6"], ["Yelena Perova\\n26.the singer", "Pelicans", "Pelicans", "Crocodiles", "Runner-Up", "2"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:who was the first voted out?
|
Yelena Kondulaynen
| 128
|
Answer:
|
Table InputTable: [["Round", "Date", "Circuit", "Winning driver (TA2)", "Winning vehicle (TA2)", "Winning driver (TA1)", "Winning vehicle (TA1)"], ["3", "June 11", "Portland", "Tuck Thomas", "Chevrolet Monza", "Bob Matkowitch", "Chevrolet Corvette"], ["5", "July 8", "Watkins Glen‡", "Hal Shaw, Jr.\\n Monte Shelton", "Porsche 935", "Brian Fuerstenau\\n Bob Tullius", "Jaguar XJS"], ["7", "August 19", "Mosport", "Greg Pickett", "Chevrolet Corvette", "Bob Tullius", "Jaguar XJS"], ["1", "May 21", "Sears Point", "Greg Pickett", "Chevrolet Corvette", "Gene Bothello", "Chevrolet Corvette"], ["4", "June 25", "Mont-Tremblant", "Monte Sheldon", "Porsche 935", "Bob Tullius", "Jaguar XJS"], ["8", "September 4", "Road America", "Greg Pickett", "Chevrolet Corvette", "Bob Tullius", "Jaguar XJS"], ["6", "August 13", "Brainerd", "Jerry Hansen", "Chevrolet Monza", "Bob Tullius", "Jaguar XJS"], ["9", "October 8", "Laguna Seca", "Greg Pickett", "Chevrolet Corvette", "Bob Tullius", "Jaguar XJS"], ["10", "November 5", "Mexico City", "Ludwig Heimrath", "Porsche 935", "Bob Tullius", "Jaguar XJS"], ["2", "June 4", "Westwood", "Ludwig Heimrath", "Porsche 935", "Nick Engels", "Chevrolet Corvette"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what is the name of the circuit listed before portland?
|
Westwood
| 128
|
Answer:
|
Table InputTable: [["Tour", "Official title", "Venue", "City", "Date\\nStart", "Date\\nFinish", "Prize money\\nUSD", "Report"], ["4", "Swiss Open Super Series", "St. Jakobshalle", "Basel", "March 12", "March 18", "200,000", "Report"], ["11", "China Open Super Series", "Tianhe Gymnasium", "Guangzhou", "November 20", "November 25", "250,000", "Report"], ["9", "Denmark Super Series", "Arena Fyn", "Odense", "October 23", "October 28", "200,000", "Report"], ["10", "French Super Series", "Stade Pierre de Coubertin", "Paris", "October 30", "November 4", "200,000", "Report"], ["13", "Super Series Finals", "Cancelled", "Cancelled", "Cancelled", "Cancelled", "500,000", "Report"], ["12", "Hong Kong Super Series", "Ma On Shan Sports Centre\\nQueen Elizabeth Stadium", "Ma On Shan\\nWan Chai", "November 26", "December 2", "200,000", "Report"], ["7", "China Masters Super Series", "Sichuan Provincial Gymnasium", "Chengdu", "July 10", "July 15", "250,000", "Report"], ["2", "Korea Open Super Series", "Seoul National University Gymnasium", "Seoul", "January 23", "January 28", "300,000", "Report"], ["1", "Malaysia Super Series", "Stadium Badminton Kuala Lumpur", "Kuala Lumpur", "January 16", "January 21", "200,000", "Report"], ["5", "Singapore Super Series", "Singapore Indoor Stadium", "Singapore", "May 1", "May 6", "200,000", "Report"], ["3", "All England Super Series", "National Indoor Arena", "Birmingham", "March 6", "March 11", "200,000", "Report"], ["6", "Indonesia Super Series", "Bung Karno Stadium", "Jakarta", "May 7", "May 13", "250,000", "Report"], ["8", "Japan Super Series", "Tokyo Metropolitan Gymnasium", "Tokyo", "September 11", "September 16", "200,000", "Report"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how long does the swiss open series run for?
|
6 days
| 128
|
Answer:
|
Table InputTable: [["Pos", "Rider", "Manufacturer", "Time/Retired", "Points"], ["24", "Henk Van De Lagemaat", "Honda", "+1 Lap", ""], ["Ret", "Andre Romein", "Honda", "Retirement", ""], ["2", "Valentino Rossi", "Aprilia", "+0.180", "20"], ["1", "Loris Capirossi", "Honda", "38:04.730", "25"], ["8", "Stefano Perugini", "Honda", "+20.891", "8"], ["16", "Luca Boscoscuro", "TSR-Honda", "+56.432", ""], ["18", "Julien Allemand", "TSR-Honda", "+1:16.347", ""], ["Ret", "Maurice Bolwerk", "TSR-Honda", "Retirement", ""], ["20", "Lucas Oliver Bulto", "Yamaha", "+1:25.758", ""], ["11", "Alex Hofmann", "TSR-Honda", "+26.933", "5"], ["15", "Jarno Janssen", "TSR-Honda", "+56.248", "1"], ["12", "Sebastian Porto", "Yamaha", "+27.054", "4"], ["9", "Jason Vincent", "Honda", "+21.310", "7"], ["21", "David Garcia", "Yamaha", "+1:33.867", ""], ["19", "Fonsi Nieto", "Yamaha", "+1:25.622", ""], ["17", "Johann Stigefelt", "Yamaha", "+1:07.433", ""], ["Ret", "Roberto Rolfo", "Aprilia", "Retirement", ""], ["7", "Franco Battaini", "Aprilia", "+20.889", "9"], ["Ret", "Marcellino Lucchi", "Aprilia", "Retirement", ""], ["10", "Anthony West", "TSR-Honda", "+26.816", "6"], ["14", "Masaki Tokudome", "TSR-Honda", "+33.161", "2"], ["4", "Tohru Ukawa", "Honda", "+0.537", "13"], ["22", "Rudie Markink", "Aprilia", "+1:40.280", ""], ["13", "Tomomi Manako", "Yamaha", "+27.903", "3"], ["23", "Arno Visscher", "Aprilia", "+1:40.635", ""], ["3", "Jeremy McWilliams", "Aprilia", "+0.534", "16"], ["5", "Shinya Nakano", "Yamaha", "+0.742", "11"], ["6", "Ralf Waldmann", "Aprilia", "+7.019", "10"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:which racer was the only one not to finish on the final lap?
|
Henk Van De Lagemaat
| 128
|
Answer:
|
Table InputTable: [["Year", "Competition", "Venue", "Position", "Event", "Notes"], ["2008", "African Championships", "Addis Ababa, Ethiopia", "6th", "800 m", "2:05.95"], ["2006", "African Championships", "Bambous, Mauritius", "13th (h)", "800 m", "2:10.50"], ["2009", "World Championships", "Berlin, Germany", "36th (h)", "800 m", "2:06.72"], ["2010", "African Championships", "Nairobi, Kenya", "7th", "800 m", "2:08.45"], ["2009", "Lusophony Games", "Lisbon, Portugal", "4th", "800 m", "2:07.48"], ["2011", "All-Africa Games", "Maputo, Mozambique", "12th (h)", "800 m", "2:06.72"], ["2007", "All-Africa Games", "Algiers, Algeria", "1st", "800 m", "2:02.83"], ["2006", "Lusophony Games", "Macau", "1st", "800 m", "2:07.34"], ["2006", "Commonwealth Games", "Melbourne, Australia", "9th (sf)", "800 m", "2:01.84"], ["2003", "All-Africa Games", "Abuja, Nigeria", "11th (h)", "800 m", "2:05.19"], ["2010", "Commonwealth Games", "Delhi, India", "–", "800 m", "DNF"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:when did leonor piuza last compete in a race?
|
2011
| 128
|
Answer:
|
Table InputTable: [["Naturalisations by origin", "2000", "2005", "2009", "% Total 2009"], ["Africa", "84 182", "98 453", "85 144", "62.7"], ["South-East Asia", "7 265", "4 069", "2 475", "1.8"], ["South and Central America", "4 620", "5 498", "5 930", "4.4"], ["South Asia", "4 246", "4 436", "3 660", "2.7"], ["East Asia", "1 139", "1 280", "1 622", "1.2"], ["Asia", "27 941", "26 286", "19 494", "14.4"], ["Europe (not including CIS )", "22 085", "18 072", "14 753", "10.9"], ["Other Asia", "15 291", "16 501", "11 737", "8.6"], ["Other Africa", "5 375", "7 605", "6 906", "5.1"], ["Sub-Saharan Africa", "10 622", "15 624", "22 214", "16.4"], ["Oceania", "87", "127", "108", "0.1"], ["North America", "1 048", "854", "747", "0.5"], ["CIS (Asia)", "181", "573", "250", "0.2"], ["America", "5 668", "6 352", "6 677", "4.9"], ["CIS (Europe)", "1 000", "1 535", "4 454", "3.3"], ["Maghreb", "68 185", "75 224", "56 024", "41.2"], ["Total", "150 026", "154 643", "135 842", "100"], ["CIS", "1 181", "2 108", "4 704", "3.5"], ["Others", "8 882", "3 245", "4 962", "3.7"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what continent is listed at the top of the table?
|
Africa
| 128
|
Answer:
|
Table InputTable: [["Year", "Division", "League", "Reg. Season", "Playoffs", "National Cup"], ["1939/40", "N/A", "ASL", "2nd(t)", "No playoff", "Co-champion"], ["1945/46", "N/A", "ASL", "1st", "Champion (no playoff)", "?"], ["1935/36", "N/A", "ASL", "2nd", "No playoff", "?"], ["1934/35", "N/A", "ASL", "6th", "No playoff", "?"], ["1946/47", "N/A", "ASL", "4th", "No playoff", "?"], ["1947/48", "N/A", "ASL", "4th", "No playoff", "?"], ["1942/43", "N/A", "ASL", "5th", "No playoff", "?"], ["1941/42", "N/A", "ASL", "5th", "No playoff", "?"], ["1940/41", "N/A", "ASL", "3rd", "No playoff", "?"], ["1943/44", "N/A", "ASL", "3rd", "No playoff", "?"], ["1944/45", "N/A", "ASL", "4th", "No playoff", "?"], ["1948/49", "N/A", "ASL", "Withdrew after 3 games", "N/A", "N/A"], ["1936/37", "N/A", "ASL", "2nd, American", "1st Round", "?"], ["1937/38", "N/A", "ASL", "4th, American", "Did not qualify", "?"], ["1938/39", "N/A", "ASL", "5th, American", "Did not qualify", "?"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what year was the only year in which the team won the co-championship title?
|
1939/40
| 128
|
Answer:
|
Table InputTable: [["Year", "Injuries (US $000)", "Deaths (age <15)", "CPSC toy safety funding\\n(US$ Millions)", "Toy sales\\n(US $ Billions)"], ["2003", "206", "11", "12.8", "20.7"], ["1998", "153", "14", "", ""], ["1994", "154", "", "", ""], ["1995", "139", "", "", ""], ["1996", "130", "", "", ""], ["1997", "141", "", "", ""], ["2008", "no data", "19", "no data", ""], ["2009", "no data", "12", "no data", ""], ["2007", "no data", "22", "no data", ""], ["2001", "255", "25", "12.4", ""], ["2006", "no data", "22", "no data†", "22.3"], ["2004", "210", "16", "11.5", "22.4"], ["2005", "202 (estimate)", "20", "11.0", "22.2"], ["2002", "212", "13", "12.2", "21.3"], ["1999", "152", "16", "13.6", ""], ["2000", "191", "17", "12.0", ""]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what were the total number of deaths in 2003?
|
11
| 128
|
Answer:
|
Table InputTable: [["Outcome", "No.", "Date", "Tournament", "Surface", "Opponent", "Score"], ["Winner", "3.", "21 May 2006", "Hamburg Masters, Hamburg, Germany", "Clay", "Radek Štěpánek", "6–1, 6–3, 6–3"], ["Winner", "10.", "6 February 2011", "Chile Open, Santiago, Chile", "Clay", "Santiago Giraldo", "6–2, 2–6, 7–6(7–5)"], ["Runner-up", "5.", "14 January 2007", "Heineken Open, Auckland, New Zealand", "Hard", "David Ferrer", "4–6, 2–6"], ["Winner", "1.", "29 July 2001", "Orange Warsaw Open, Sopot, Poland", "Clay", "Albert Portas", "1–6, 7–5, 7–6(7–2)"], ["Winner", "11.", "14 April 2013", "Grand Prix Hassan II, Casablanca, Morocco", "Clay", "Kevin Anderson", "7–6(8–6), 4–6, 6–3"], ["Winner", "4.", "16 July 2006", "Swedish Open, Båstad, Sweden", "Clay", "Nikolay Davydenko", "6–2, 6–1"], ["Winner", "7.", "13 July 2008", "Swedish Open, Båstad, Sweden (2)", "Clay", "Tomáš Berdych", "6–4, 6–1"], ["Runner-up", "7.", "15 June 2008", "Orange Warsaw Open, Warsaw, Poland", "Clay", "Nikolay Davydenko", "3–6, 3–6"], ["Runner-up", "6.", "16 September 2007", "China Open, Beijing, China", "Hard (i)", "Fernando González", "1–6, 6–3, 1–6"], ["Winner", "12.", "28 July 2013", "ATP Vegeta Croatia Open Umag, Umag, Croatia", "Clay", "Fabio Fognini", "6–0, 6–3"], ["Runner-up", "4.", "30 April 2006", "Torneo Godó, Barcelona, Spain", "Clay", "Rafael Nadal", "4–6, 4–6, 0–6"], ["Winner", "6.", "7 October 2007", "Open de Moselle, Metz, France", "Hard (i)", "Andy Murray", "0–6, 6–2, 6–3"], ["Winner", "5.", "5 August 2007", "Orange Warsaw Open, Sopot, Poland (2)", "Clay", "José Acasuso", "7–5, 6–0"], ["Runner-up", "3.", "1 May 2005", "Estoril Open, Estoril, Portugal", "Clay", "Gastón Gaudio", "1–6, 6–2, 1–6"], ["Winner", "2.", "2 May 2004", "Torneo Godó, Barcelona, Spain", "Clay", "Gastón Gaudio", "6–3, 4–6, 6–2, 3–6, 6–3"], ["Runner-up", "2.", "20 July 2003", "Mercedes Cup, Stuttgart, Germany", "Clay", "Guillermo Coria", "2–6, 2–6, 1–6"], ["Winner", "8.", "14 February 2009", "Brasil Open, Costa do Sauípe, Brazil", "Clay", "Thomaz Bellucci", "6–3, 3–6, 6–4"], ["Runner-up", "1.", "15 April 2001", "Grand Prix Hassan II, Casablanca, Morocco", "Clay", "Guillermo Cañas", "5–7, 2–6"], ["Winner", "9.", "22 February 2009", "Copa Telmex, Buenos Aires, Argentina", "Clay", "Juan Mónaco", "7–5, 2–6, 7–6(7–5)"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many hard surface courts are there?
|
3
| 128
|
Answer:
|
Table InputTable: [["Season", "Class", "Moto", "Races", "Win", "Podiums", "Pole", "Pts", "Position"], ["2005", "125cc", "Derbi", "13", "0", "0", "0", "1", "36th"], ["2004", "125cc", "Aprilia", "1", "0", "0", "0", "0", "NC"], ["2007", "125cc", "Derbi", "17", "0", "0", "0", "19", "22nd"], ["2009", "125cc", "Aprilia", "16", "1", "4", "0", "179.5", "3rd"], ["2006", "125cc", "Derbi", "16", "0", "0", "0", "53", "14th"], ["2008", "125cc", "Aprilia", "17", "1", "5", "0", "176", "5th"], ["2010", "125cc", "Aprilia", "16", "3", "14", "1", "296", "2nd"], ["Total", "", "", "147", "16", "39", "9", "1213.5", ""], ["2011", "125cc", "Aprilia", "16", "8", "11", "7", "302", "1st"], ["2012", "Moto2", "Suter", "17", "0", "1", "0", "37", "17th"], ["2014", "Moto2", "Suter", "1", "0", "0", "0", "0*", "NC*"], ["2013", "Moto2", "Suter", "17", "3", "4", "1", "150", "7th"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what was the least amount of points scored in a season?
|
0
| 128
|
Answer:
|
Table InputTable: [["Specifications", "Foundation", "Essentials", "Standard", "Datacenter"], ["Active Directory Federation Services", "Yes", "No", "Yes", "Yes"], ["Active Directory Domain Services", "Must be root of forest and domain", "Must be root of forest and domain", "Yes", "Yes"], ["Active Directory Certificate Services", "Certificate Authorities only", "Certificate Authorities only", "Yes", "Yes"], ["Active Directory Lightweight Directory Services", "Yes", "Yes", "Yes", "Yes"], ["Active Directory Rights Management Services", "Yes", "Yes", "Yes", "Yes"], ["File Services limits", "1 standalone DFS root", "1 standalone DFS root", "Unlimited", "Unlimited"], ["Licensing model", "Per server", "Per server", "Per CPU pair + CAL", "Per CPU pair + CAL"], ["Network Policy and Access Services limits", "50 RRAS connections and 10 IAS connections", "250 RRAS connections, 50 IAS connections, and 2 IAS Server Groups", "Unlimited", "Unlimited"], ["Fax server role", "Yes", "Yes", "Yes", "Yes"], ["DHCP role", "Yes", "Yes", "Yes", "Yes"], ["Remote Desktop Services limits", "50 Remote Desktop Services connections", "Gateway only", "Unlimited", "Unlimited"], ["Distribution", "OEM only", "Retail, volume licensing, OEM", "Retail, volume licensing, OEM", "Volume licensing and OEM"], ["Application server role", "Yes", "Yes", "Yes", "Yes"], ["UDDI Services", "Yes", "Yes", "Yes", "Yes"], ["Server Core mode", "No", "No", "Yes", "Yes"], ["Windows Deployment Services", "Yes", "Yes", "Yes", "Yes"], ["Web Services (Internet Information Services)", "Yes", "Yes", "Yes", "Yes"], ["Virtualization rights", "N/A", "Either in 1 VM or 1 physical server, but not both at once", "2 VMs", "Unlimited"], ["DNS server role", "Yes", "Yes", "Yes", "Yes"], ["Server Manager", "Yes", "Yes", "Yes", "Yes"], ["Print and Document Services", "Yes", "Yes", "Yes", "Yes"], ["Windows Server Update Services", "No", "Yes", "Yes", "Yes"], ["User limit", "15", "25", "Unlimited", "Unlimited"], ["Windows Powershell", "Yes", "Yes", "Yes", "Yes"], ["Memory limit", "32 GB", "64 GB", "4 TB", "4 TB"], ["Processor chip limit", "1", "2", "64", "64"], ["Hyper-V", "No", "No", "Yes", "Yes"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many specifications have no active directory federation services?
|
1
| 128
|
Answer:
|
Table InputTable: [["Year", "Competition", "Venue", "Position", "Event"], ["2000", "Grand Prix Final", "Doha, Qatar", "4th", "100 m hurdles"], ["2003", "World Athletics Final", "Monaco", "6th", "100 m hurdles"], ["2002", "Grand Prix Final", "Paris, France", "7th", "100 m hurdles"], ["1997", "USA Outdoor Championships", "Indianapolis, United States", "1st", "100 m hurdles"], ["2000", "Olympic Games", "Sydney, Australia", "3rd", "100 m hurdles"], ["1998", "Grand Prix Final", "Moscow, Russia", "2nd", "100 m hurdles"], ["1998", "USA Indoor Championships", "", "1st", "60 m hurdles"], ["2002", "USA Indoor Championships", "", "1st", "60 m hurdles"], ["1997", "World Indoor Championships", "Paris, France", "5th", "60 m hurdles"], ["2004", "Olympic Games", "Athens, Greece", "3rd", "100 m hurdles"], ["2003", "World Indoor Championships", "Birmingham, England", "3rd", "60 m hurdles"], ["1999", "World Indoor Championships", "Maebashi, Japan", "6th", "60 m hurdles"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many total major races has melissa morrison-howard placed first in?
|
3
| 128
|
Answer:
|
Table InputTable: [["Distribution", "x86", "x86-64", "ia64", "ppc", "ppc64", "sparc32", "sparc64", "arm", "hppa", "mips", "sh", "s390", "s390x", "alpha", "m68k"], ["Distribution", "x86", "x86-64", "ia64", "ppc", "ppc64", "sparc32", "sparc64", "arm", "hppa", "mips", "sh", "s390", "s390x", "alpha", "m68k"], ["Arch Linux", "Yes (>=i686)", "Yes", "No", "Discontinued unofficial port", "No", "No", "No", "Yes\\nUnofficial", "No", "No", "No", "No", "No", "No", "No"], ["CentOS", "Yes", "Yes", "Discontinued\\n3.5-3.8\\n4.1-4.7", "Beta\\n4.0", "No", "Beta\\n4.2", "No", "No", "No", "No", "No", "Discontinued\\n3.5-3.8\\n4.1-4.7", "Discontinued\\n3.5-3.8\\n4.1-4.7", "Discontinued\\n4.2-4.3", "No"], ["Ubuntu/Kubuntu/Xubuntu/Lubuntu", "Yes", "Yes", "No", "Yes", "No", "No", "No", "Yes", "No", "No", "No", "No", "No", "No", "No"], ["Debian", "Yes", "Yes\\n4.0+", "Discontinued\\n3.0-7.0", "Yes\\n2.2+", "Yes", "Discontinued on Lenny", "Yes", "Yes\\n2.2+", "Discontinued\\n3.0-5.0", "Yes\\n3.0+", "In progress", "Discontinued\\n3.0-7", "Yes\\n7+", "Discontinued\\n2.1-5.0", "Discontinued\\n2.0-3.1"], ["Source Mage GNU/Linux", "Yes", "Yes", "No", "Yes", "No", "No", "No", "No", "No", "No", "No", "No", "No", "No", "No"], ["Red Hat Linux", "Yes", "No", "Discontinued\\n7.1-7.2", "Test release\\n5.1", "No", "Discontinued\\n4.0-4.2\\n5.1-6.2", "Test release\\n5.1", "No", "No", "Test release\\n5.1", "No", "Discontinued\\n7.2", "Discontinued\\n7.1", "Discontinued\\n2.1-7.1", "Test release\\n5.1"], ["SUSE Linux Enterprise Server", "Yes", "Yes", "Yes", "Yes", "Yes", "No", "No", "No", "No", "No", "No", "No", "Yes", "No", "No"], ["OES2-Linux", "Yes", "Yes", "No", "No", "No", "No", "No", "No", "No", "No", "No", "No", "No", "No", "No"], ["XBMC", "Yes", "No", "No", "No", "No", "No", "No", "Yes", "No", "No", "No", "No", "No", "No", "No"], ["Red Hat Enterprise Linux", "Discontinued\\n2.1-6", "Yes\\n3+", "Discontinued\\n2.1-5", "Yes\\n3+", "Yes\\n3+", "No", "No", "No", "No", "No", "No", "Discontinued\\n3-4", "Yes\\n3+", "No", "No"], ["Slackware", "Yes", "Yes", "No", "No", "No", "Discontinued\\n?", "No", "Yes", "No", "No", "No", "Discontinued\\n?", "Discontinued\\n?", "Discontinued\\n8.1", "No"], ["Scientific Linux", "Yes", "Yes", "Discontinued\\n3-4", "No", "No", "No", "No", "No", "No", "No", "No", "No", "No", "No", "No"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many distributions support the x86 architecture?
|
29
| 128
|
Answer:
|
Table InputTable: [["Rank", "Player", "County", "Tally", "Total", "Opposition"], ["9", "John Byrne", "Carlow", "2–2", "8", "Westmeath"], ["6", "Seán McLoughlin", "Westmeath", "1–6", "9", "Carlow"], ["9", "Paul Flynn", "Waterford", "1–5", "8", "Tipperary"], ["3", "Gary Kirby", "Limerick", "0–10", "10", "Tipperary"], ["6", "Gary Kirby", "Limerick", "0–9", "9", "Antrim"], ["2", "Niall English", "Carlow", "1–9", "12", "Westmeath"], ["9", "John Leahy", "Tipperary", "2–2", "8", "Kerry"], ["3", "Gary Kirby", "Limerick", "1–7", "10", "Tipperary"], ["6", "David Martin", "Meath", "1–6", "9", "Offaly"], ["9", "Tom Dempsey", "Wexford", "1–5", "8", "Offaly"], ["9", "John Troy", "Offaly", "2–2", "8", "Laois"], ["3", "Kevin Broderick", "Galway", "3–1", "10", "New York"], ["1", "Francis Forde", "Galway", "2–8", "14", "Roscommon"], ["9", "Francis Forde", "Galway", "1–5", "8", "New York"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:who was the only player to come from westmeath county?
|
Seán McLoughlin
| 128
|
Answer:
|
Table InputTable: [["Wrestler:", "Reigns:", "Date:", "Place:", "Notes:"], ["Pulgarcito", "1", "November 11, 1995", "", ""], ["B.J.", "2", "March 15, 2008", "Lares, Puerto Rico", ""], ["Rex King", "1", "1995", "", ""], ["Sean Morley", "1", "1995", "", ""], ["Mighty Koadiak", "2", "November 26, 1995", "", ""], ["Vengador Boricua", "1", "July 19, 2003", "Carolina, Puerto Rico", "title becomes inactive when Vengador Boricua leaves the company."], ["Ron Starr", "2", "June 25, 1988", "Carolina, Puerto Rico", ""], ["Rex King", "2", "1995", "", ""], ["TNT", "5", "October 26, 1991", "Carolina, Puerto Rico", ""], ["Dick Murdoch", "1", "November 23, 1991", "Arroyo, Puerto Rico", ""], ["Mighty Koadiak", "1", "1994", "", ""], ["Rico Suave", "2", "March 17, 2007", "Bayamon, Puerto Rico", ""], ["Rex King", "3", "March 19, 2000", "Cabo Rojo, Puerto Rico", ""], ["TNT", "3", "March 30, 1991", "Bayamon, Puerto Rico", ""], ["Invader I", "2", "September 18, 1987", "San Juan, Puerto Rico", ""], ["Rico Suave", "1", "April 6, 2002", "Caguas, Puerto Rico", ""], ["Glamour Boy Shane", "1", "April 2, 1999", "Guaynabo, Puerto Rico", "Defeated \"Jungle\" Jim Steele for vacant title."], ["Invader I", "5", "December 25, 1991", "San Juan, Puerto Rico", ""], ["Glamour Boy Shane", "3", "January 6, 2000", "Caguas, Puerto Rico", ""], ["Invader I", "4", "April 2, 1988", "Bayamon, Puerto Rico", ""], ["Jason The Terrible", "2", "January 28, 1989", "Carolina, Puerto Rico", ""], ["Ray Gonzalez", "1", "April 27, 2002", "San Lorenzo, Puerto Rico", ""], ["Alex Porteau", "1", "July 7, 2001", "Carolina, Puerto Rico", ""], ["Fidel Sierra", "2", "August 24, 2002", "Coamo, Puerto Rico", ""], ["Super Gladiator", "1", "October 6, 2001", "Caguas, Puerto Rico", ""], ["Vacant", "", "", "", "Chris Joel Jumps to IWA"], ["Crazy Rudy", "1", "April 28, 2007", "Bayamon, Puerto Rico", ""], ["Invader I", "1", "November 5, 1986", "San Juan, Puerto Rico", ""], ["Fidel Sierra", "1", "October 19, 1991", "Bayamon, Puerto Rico", ""], ["TNT", "4", "June 1, 1991", "Bayamon, Puerto Rico", ""], ["Hammett", "1", "March 1, 2008", "Tao Baja, Puerto Rico", ""], ["Ricky Santana", "1", "1995", "", ""], ["Carlos Colon", "1", "August 20, 1988", "Bayamon, Puerto Rico", ""], ["Sweet Brown Sugar (Skip Young)", "1", "January 6, 1996", "Caguas, Puerto Rico", ""], ["Chicky Starr", "1", "November 13, 1999", "Naguabo, Puerto Rico", ""], ["\"Jungle\" Jim Steele", "1", "April 20, 1996", "Caguas, Puerto Rico", ""], ["Glamour Boy Shane", "2", "September 19, 1999", "Guaynabo, Puerto Rico", ""], ["Grizzly Boone", "1", "October 24, 1987", "Bayamon, Puerto Rico", ""], ["Chris Candido", "1", "June 6, 2003", "Cayey, Puerto Rico", ""], ["Bad Boy Bradley", "1", "September 8, 2001", "Bayamón, Puerto Rico", ""]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:are the dates in a consecutive order?
|
yes
| 128
|
Answer:
|
Table InputTable: [["#", "Name", "Height", "Weight (lbs.)", "Position", "Class", "Hometown", "Previous Team(s)"], ["40", "Jon Brockman", "6'7\"", "255", "F", "Jr.", "Snohomish, WA, U.S.", "Snohomish Sr. HS"], ["1", "Venoy Overton", "5'11\"", "180", "G", "Fr.", "Seattle, WA, U.S.", "Franklin HS"], ["11", "Matthew Bryan-Amaning", "6'9\"", "235", "F", "Fr.", "London, England, U.K.", "South Kent School"], ["20", "Ryan Appleby", "6'3\"", "170", "G", "Sr.", "Stanwood, WA, U.S.", "Florida"], ["32", "Joe Wolfinger", "7'0\"", "255", "C", "RS So.", "Portland, OR, U.S.", "Northfield Mount Hermon School"], ["5", "Justin Dentmon", "5'11\"", "185", "G", "Jr.", "Carbondale, IL, U.S.", "Winchendon School"], ["22", "Justin Holiday", "6'6\"", "170", "F", "Fr.", "Chatsworth, CA, U.S.", "Campbell Hall School"], ["24", "Quincy Pondexter", "6'6\"", "210", "F", "So.", "Fresno, CA, U.S.", "San Joaquin Memorial HS"], ["44", "Darnell Gant", "6'8\"", "215", "F", "Fr.", "Los Angeles, CA, U.S.", "Crenshaw HS"], ["0", "Joel Smith", "6'4\"", "210", "G", "RS Jr.", "Lompoc, CA, U.S.", "Brewster Academy"], ["4", "Tim Morris", "6'4\"", "210", "G", "Sr.", "Spokane Wa, U.S.", "Central Valley HS"], ["21", "Artem Wallace", "6'8\"", "250", "C", "Jr.", "Toledo, WA, U.S.", "Toledo HS"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what is the first name on the chart?
|
Joel Smith
| 128
|
Answer:
|
Table InputTable: [["Date", "Opponent#", "Rank#", "Site", "TV", "Result", "Attendance"], ["October 31", "at Illinois", "#16", "Memorial Stadium • Champaign, IL", "", "L 7-24", "66,877"], ["October 17", "at #5 Michigan", "#12", "Michigan Stadium • Ann Arbor, MI", "", "W 9-7", "105,915"], ["September 26", "#6 UCLA*", "", "Kinnick Stadium • Iowa City, IA", "", "W 20-7", "60,004"], ["November 14", "at Wisconsin", "", "Camp Randall Stadium • Madison, WI", "ABC", "W 17-7", "78,731"], ["October 10", "Indiana", "#15", "Kinnick Stadium • Iowa City, IA", "", "W 42-28", "60,000"], ["November 7", "Purdue", "", "Kinnick Stadium • Iowa City, IA", "", "W 33-7", "60,114"], ["September 12", "#7 Nebraska*", "", "Kinnick Stadium • Iowa City, IA", "", "W 10-7", "60,160"], ["November 21", "Michigan State", "#19", "Kinnick Stadium • Iowa City, IA", "", "W 36-7", "60,103"], ["October 24", "Minnesota", "#6", "Kinnick Stadium • Iowa City, IA (Floyd of Rosedale)", "ABC", "L 10-12", "60,000"], ["January 1", "vs. #12 Washington*", "#13", "Rose Bowl • Pasadena, CA (Rose Bowl)", "NBC", "L 0-28", "105,611"], ["October 3", "at Northwestern", "#18", "Dyche Stadium • Evanston, IL", "", "W 64-0", "30,113"], ["September 19", "at Iowa State*", "", "Cyclone Stadium • Ames, IA (Cy-Hawk Trophy)", "", "L 12-23", "53,922"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:which date had the most attendance?
|
October 17
| 128
|
Answer:
|
Table InputTable: [["Tie no", "Home team", "Score", "Away team", "Date", "Attendance"], ["16", "Stoke City", "3 – 0", "Bournemouth", "26 January 2003", "12,004"], ["10", "Fulham", "3 – 0", "Charlton Athletic", "26 January 2003", "12,203"], ["3", "Watford", "1 – 0", "West Bromwich Albion", "25 January 2003", "16,975"], ["13", "Norwich City", "1 – 0", "Dagenham & Redbridge", "25 January 2003", "21,164"], ["1", "Rochdale", "2 – 0", "Coventry City", "25 January 2003", ""], ["12", "Manchester United", "6 – 0", "West Ham United", "26 January 2003", "67,181"], ["9", "Sheffield United", "4 – 3", "Ipswich Town", "25 January 2003", "12,757"], ["5", "Gillingham", "1 – 1", "Leeds United", "25 January 2003", "11,093"], ["14", "Crystal Palace", "0 – 0", "Liverpool", "26 January 2003", "26,054"], ["Replay", "Leeds United", "2 – 1", "Gillingham", "4 February 2003", "29,359"], ["11", "Brentford", "0 – 3", "Burnley", "25 January 2003", "9,563"], ["7", "Wolverhampton Wanderers", "4 – 1", "Leicester City", "25 January 2003", "28,164"], ["Replay", "Liverpool", "0 – 2", "Crystal Palace", "5 February 2003", "35,109"], ["6", "Blackburn Rovers", "3 – 3", "Sunderland", "25 January 2003", "14,315"], ["8", "Shrewsbury Town", "0 – 4", "Chelsea", "26 January 2003", "7,950"], ["Replay", "Sunderland", "2 – 2", "Blackburn Rovers", "5 February 2003", "15,745"], ["2", "Southampton", "1 – 1", "Millwall", "25 January 2003", "23,809"], ["4", "Walsall", "2 – 0", "Wimbledon", "25 January 2003", "6,693"], ["Replay", "Millwall", "1 – 2", "Southampton", "5 February 2003", "10,197"], ["15", "Farnborough Town", "1 – 5", "Arsenal", "25 January 2003", "35,108"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:fulham and stoke city both won with how many points?
|
3
| 128
|
Answer:
|
Table InputTable: [["Year", "Division", "League", "Reg. Season", "Playoffs"], ["2008", "1", "USL W-League", "6th, Western", "Did not qualify"], ["2009", "1", "USL W-League", "7th, Western", "Did not qualify"], ["2012", "1", "USL W-League", "4th, Western", "Did not qualify"], ["2011", "1", "USL W-League", "7th, Western", "Did not qualify"], ["2010", "1", "USL W-League", "6th, Western", "Did not qualify"], ["2013", "1", "USL W-League", "4th, Western", "Did not qualify"], ["2005", "1", "USL W-League", "6th, Western", ""], ["2003", "2", "USL W-League", "5th, Western", ""], ["2007", "1", "USL W-League", "5th, Western", ""], ["2006", "1", "USL W-League", "5th, Western", ""], ["2004", "1", "USL W-League", "8th, Western", ""]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what is the total number of times the team did not qualify for playoffs?
|
6
| 128
|
Answer:
|
Table InputTable: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], ["1", "France", "11", "5", "3", "19"], ["8", "Tunisia", "0", "1", "0", "1"], ["3", "Yugoslavia", "3", "2", "1", "6"], ["2", "Greece", "6", "7", "6", "19"], ["5", "Morocco", "1", "1", "0", "2"], ["7", "Egypt", "0", "1", "7", "8"], ["4", "Spain", "1", "5", "5", "11"], ["5", "Turkey", "1", "1", "0", "2"], ["Totaal", "Totaal", "23", "23", "22", "68"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:which country placed first the most?
|
France
| 128
|
Answer:
|
Table InputTable: [["Year", "Designer(s)", "Brief description", "Selected by:", "Associated publication"], ["1974", "Ottavio and Rosita Missoni\\nPasquali (shoes)", "Male & female ensembles in knitted wool & rayon", "Jennifer Hocking", "Harper's Bazaar and Queen magazine"], ["1965", "John Bates for Jean Varon\\nAnello & Davide (shoes)", "Printed linen dress with mesh midriff", "Members of The Fashion Writers' Association", ""], ["1964", "Jean Muir for Jane & Jane\\nCharles Jourdan for Dior (shoes)", "Dress in printed Liberty silk", "Members of The Fashion Writers' Association", ""], ["1973", "Female: Marc Bohan for Christian Dior London\\nMale: Yves Saint Laurent Rive Gauche", "Female: White wool coat & hat\\nMale: Wool jacket, trousers & sweater", "Alison Adburgham", "The Guardian"], ["2003", "Marni", "Colorful printed dress", "Lucinda Chambers", "Vogue"], ["1983", "Sheridan Barnett\\nManolo Blahnik (shoes)", "Linen dress and coat", "Sally Brampton", "The Observer"], ["1963", "Mary Quant\\nReed Crawford (hat)\\nAnello & Davide (boots)", "Grey wool 'Rex Harrison' pinafore dress & cream blouse", "Members of The Fashion Writers' Association", ""], ["1997", "Female: Hussein Chalayan\\nFemale: Julien MacDonald\\nFemale: Lainey Keogh\\nFemale: Deborah Milner\\nPhilip Treacy (bonnet)", "Female: Purple evening dress with sunburst bead embroidery (Chalayan)\\nFemale: 'Mermaid' evening dress, gold knitted rayon & horsehair (MacDonald)\\nFemale: Evening dress and coat, black knit with beading (Keogh)\\nFemale: Evening coat, purple velvet, with fur collar (Milner)\\nSculptural black bonnet", "Isabella Blow", "The Sunday Times"], ["1968", "Jean Muir\\nBally (shoes)", "Black-spotted white cotton voile dress", "Ailsa Garland", "Fashion Magazine"], ["1979", "Jean Muir\\nManolo Blahnik for Zapata (shoes)", "Black rayon jersey dress & beret with black leather jacket", "Geraldine Ranson", "The Sunday Telegraph"], ["1980", "Calvin Klein\\nDiego della Valle (sandals)", "Red & brown striped silk dress with leather belt & wooden jewellery", "Michael Roberts", "The Sunday Times"], ["1986", "Giorgio Armani", "Female: Checked wool jacket, skirt, and black suede shoes\\nMale: Jacket, trousers, shirt and brogues", "Colin McDowell", "Country Life"], ["1978", "Female: Gordon Luke Clarke\\nMale: Cerruti", "Female: Printed cotton & polyester jersey tunic, skirt and trousers worn with black leather skirt and coat\\nMale: Coat, jacket, waistcoat & trousers, knitted wool and wool tweed", "Barbara Griggs", "The Daily Mail"], ["1981", "Karl Lagerfeld for Chloé\\nWalter Steiger (shoes)\\nUgo Correani (necklace)", "Printed white silk dress", "Vanessa de Lisle", "Harper's & Queen"], ["1976", "Female: Kenzo Takada of Jungle Jap\\nMale: Fiorucci", "Female: Two printed cotton ensembles with wooden jewellery\\nMale: Hand-knitted sweater, two shirts and jeans", "Helena Matheopoulos", "The Daily Express"], ["1982", "Margaret Howell\\nNigel Preston of Maxfield Parrish (leather wear)\\nMulberry (belt)\\nManolo Blahnik for Zapata (shoes)", "Two women's ensembles, a linen skirt, shirt and waistcoat and a blue suede and fawn chamois leather skirt & jacket with cotton shirt", "Grace Coddington", "UK Vogue"], ["1985", "Female: Bruce Oldfield\\nCharles Jourdan (shoes)\\nMaria Buck (jewellery)\\nMale: Scott Crolla", "Female: Black silk & gold lamé evening dress\\nMale: Shirt, crushed velvet trousers and ikat mules", "Suzy Menkes", "The Times"], ["1987", "John Galliano\\nPatrick Cox (shoes)", "Checked cotton coat, skirt, shirt & hat", "Debbi Mason", "Elle"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many designers do not have an associated publication?
|
6
| 128
|
Answer:
|
Table InputTable: [["Year", "Name", "Label", "Hot Black Singles", "Club Play Singles"], ["1987", "\"Send It C.O.D.\"", "New Image", "―", "―"], ["1982", "\"Thanks to You\"", "Becket", "#44", "#1"], ["1984", "\"Thin Line\"", "Power House", "―", "―"], ["1986", "\"Say It Again\"", "Spring", "―", "―"], ["1986", "\"Say It Again\"", "Spring", "―", "―"], ["1983", "\"I Need You Now\"", "Jive", "―", "―"], ["1982", "\"He's Gonna Take You Home\"", "Becket", "―", "―"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what were the most labels?
|
Becket
| 128
|
Answer:
|
Table InputTable: [["Season", "Club", "Competition", "Games", "Goals"], ["2002/03", "RAEC Mons", "Jupiler League", "19", "0"], ["2003/04", "RAEC Mons", "Jupiler League", "23", "0"], ["2006/07", "KSV Roeselare", "Jupiler League", "29", "1"], ["2005/06", "KSV Roeselare", "Jupiler League", "26", "0"], ["2008/09", "Excelsior Mouscron", "Jupiler League", "31", "1"], ["2007/08", "KSV Roeselare", "Jupiler League", "25", "0"], ["2004/05", "KSV Roeselare", "Belgian Second Division", "29", "1"], ["2009/10", "Excelsior Mouscron", "Jupiler League", "14", "1"], ["2010/11", "Kortrijk", "Jupiler League", "0", "0"], ["2009/10", "Győri ETO FC", "Soproni Liga", "1", "0"], ["", "", "Totaal", "278", "4"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many seasons were played ?
|
10
| 128
|
Answer:
|
Table InputTable: [["#", "Name", "Took office", "Left office", "Party", "Governor", "Notes"], ["50", "Sue Ellspermann", "January 14, 2013", "Incumbent", "Republican", "Mike Pence", ""], ["46", "Frank O'Bannon", "January 9, 1989", "January 13, 1997", "Democrat", "Evan Bayh", ""], ["45", "John Mutz", "January 12, 1981", "January 9, 1989", "Republican", "Robert D. Orr", ""], ["11", "James Henry Lane", "December 5, 1849", "January 10, 1853", "Democrat", "Joseph A. Wright", ""], ["32", "Edgar D. Bush", "January 14, 1929", "January 9, 1933", "Republican", "Harry G. Leslie", ""], ["4", "John H. Thompson", "January 30, 1824", "December 3, 1828", "Democratic-Republican", "William Hendricks", ""], ["42", "Robert L. Rock", "January 11, 1965", "January 13, 1969", "Democrat", "Roger D. Branigin", ""], ["47", "Joe E. Kernan", "January 13, 1997", "September 13, 2003", "Democrat", "Frank O'Bannon", ""], ["35", "Charles M. Dawson", "January 13, 1941", "January 8, 1945", "Democrat", "Henry F. Schricker", ""], ["29", "Edgar D. Bush", "January 8, 1917", "January 10, 1921", "Republican", "James P. Goodrich", ""], ["48", "Kathy Davis", "October 20, 2003", "January 10, 2005", "Democrat", "Joe E. Kernan", ""], ["19", "Thomas Hanna", "January 10, 1881", "November 12, 1885", "Republican", "Albert G. Porter", ""], ["8", "Samuel Hall", "December 9, 1840", "December 6, 1843", "Whig", "Samuel Bigger", ""], ["1", "Christopher Harrison", "November 7, 1816", "December 17, 1818", "Democratic-Republican", "Jonathan Jennings", ""], ["36", "Richard T. James", "January 8, 1945", "January 10, 1948", "Republican", "Ralph F. Gates", ""], ["44", "Robert D. Orr", "January 8, 1973", "January 12, 1981", "Republican", "Otis R. Bowen", ""], ["21", "Robert S. Robertson", "January 10, 1887", "January 13, 1889", "Republican", "Isaac P. Gray", ""], ["17", "Leonidas Sexton", "January 13, 1873", "January 13, 1877", "Republican", "Thomas A. Hendricks", ""], ["12", "Ashbel P. Willard", "January 10, 1853", "January 12, 1857", "Democrat", "Joseph A. Wright", ""], ["16", "William Cumback", "January 11, 1869", "January 13, 1873", "Republican", "Conrad Baker", ""], ["38", "John A. Watkins", "January 10, 1949", "January 12, 1953", "Democrat", "Henry F. Schricker", ""], ["9", "Jesse D. Bright", "December 6, 1843", "December 6, 1845", "Democrat", "James Whitcomb", ""], ["28", "William P. O'Neill", "January 13, 1913", "January 8, 1917", "Democrat", "Samuel M. Ralston", ""], ["27", "Frank J. Hall", "January 11, 1909", "January 13, 1913", "Democrat", "Thomas R. Marshall", ""], ["31", "F. Harold Van Orman", "January 12, 1925", "January 14, 1929", "Republican", "Edward L. Jackson", ""], ["14", "Oliver P. Morton", "January 14, 1861", "January 16, 1861", "Republican", "Henry Smith Lane", ""]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:which party was in office the most?
|
Republican
| 128
|
Answer:
|
Table InputTable: [["Rank", "Lane", "Nation", "Swimmers", "Time", "Time behind", "Notes"], ["6", "3", "Germany", "Jens Schreiber (1:49.08)\\nHeiko Hell (1:49.15)\\nLars Conrad (1:48.23)\\nChristian Keller (1:50.05)", "7:16.51", "9.18", ""], ["4", "6", "Great Britain", "Simon Burnett (1:47.90)\\nGavin Meadows (1:48.46)\\nDavid O'Brien (1:49.05)\\nRoss Davenport (1:47.19)", "7:12.60", "5.27", ""], ["7", "8", "France", "Amaury Leveaux (1:48.57)\\nFabien Horth (1:48.67)\\nNicolas Kintz (1:50.01)\\nNicolas Rostoucher (1:50.18)", "7:17.43", "10.10", ""], ["", "7", "Italy", "Emiliano Brembilla (1:48.16)\\nMassimiliano Rosolino (1:46.24)\\nSimone Cercato (1:49.85)\\nFilippo Magnini (1:47.58)", "7:11.83", "4.50", ""], ["", "5", "Australia", "Grant Hackett (1:47.50)\\nMichael Klim (1:47.62)\\nNicholas Sprenger (1:48.16)\\nIan Thorpe (1:44.18)", "7:07.46", "0.13", ""], ["8", "1", "Greece", "Apostolos Antonopoulos (1:50.34)\\nDimitrios Manganas (1:51.33)\\nAndreas Zisimos (1:50.26)\\nNikolaos Xylouris (1:51.09)", "7:23.02", "15.67", ""], ["5", "2", "Canada", "Brent Hayden (1:49.08)\\nBrian Johns (1:49.15)\\nAndrew Hurd (1:48.09)\\nRick Say (1:47.01)", "7:13.33", "6.00", ""], ["", "4", "United States", "Michael Phelps (1:46.49)\\nRyan Lochte (1:47.52)\\nPeter Vanderkaay (1:47.79)\\nKlete Keller (1:45.53)", "7:07.33", "", "AM"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what nation comes first?
|
United States
| 128
|
Answer:
|
Table InputTable: [["Season", "Footballer", "Club", "Position", "Nationality"], ["2001-02", "Jabu Pule", "Kaizer Chiefs", "MF", "South Africa"], ["2003-04", "Tinashe Nengomasha", "Kaizer Chiefs", "MF", "Zimbabwe"], ["2008-09", "Teko Modise", "Orlando Pirates", "MF", "South Africa"], ["2006-07", "Godfrey Sapula", "Mamelodi Sundowns", "MF", "South Africa"], ["1998-99", "Roger Feutmba", "Mamelodi Sundowns", "MF", "Cameroon"], ["2010-11", "Thulani Serero", "Ajax Cape Town", "MF", "South Africa"], ["2005-06", "Surprise Moriri", "Mamelodi Sundowns", "MF", "South Africa"], ["1996-97", "Wilfred Mugeyi", "Bush Bucks", "FW", "Zimbabwe"], ["1997-98", "Raphael Chukwu", "Mamelodi Sundowns", "FW", "Nigeria"], ["2004-05", "Sandile Ndlovu", "Dynamos", "FW", "South Africa"], ["2000-01", "Benjani Mwaruwari", "Jomo Cosmos", "FW", "Zimbabwe"], ["2002-03", "Moeneeb Josephs", "Ajax Cape Town", "GK", "South Africa"], ["2011-12", "Siyabonga Nomvethe", "Moroka Swallows", "FW", "South Africa"], ["2009-10", "Katlego Mphela", "Mamelodi Sundowns", "FW", "South Africa"], ["1999-00", "Siyabonga Nomvethe", "Kaizer Chiefs", "FW", "South Africa"], ["2012-13", "Itumeleng Khune", "Kaizer Chiefs", "GK", "South Africa"], ["2007-08", "Itumeleng Khune", "Kaizer Chiefs", "GK", "South Africa"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:last year a mf won?
|
2010-11
| 128
|
Answer:
|
Table InputTable: [["Date", "Opponent", "Venue", "Result", "Attendance", "Scorers"], ["3 March 2006", "Manchester City", "City of Manchester Stadium", "1–2", "42,200", "Kyle"], ["31 January 2006", "Middlesbrough", "Stadium of Light", "0–3", "31,675", ""], ["30 November 2005", "Liverpool", "Stadium of Light", "0–2", "32,697", ""], ["14 April 2006", "Manchester United", "Old Trafford", "0–0", "72,519", ""], ["22 April 2006", "Portsmouth", "Fratton Park", "1–2", "20,078", "Miller"], ["29 October 2005", "Portsmouth", "Stadium of Light", "1–4", "34,926", "Whitehead (pen)"], ["1 May 2006", "Arsenal", "Stadium of Light", "0–3", "44,003", ""], ["17 April 2006", "Newcastle United", "Stadium of Light", "1–4", "40,032", "Hoyte"], ["25 February 2006", "Birmingham City", "St. Andrew's", "0–1", "29,257", ""], ["19 November 2005", "Aston Villa", "Stadium of Light", "1–3", "39,707", "Whitehead (pen)"], ["26 November 2005", "Birmingham City", "Stadium of Light", "0–1", "32,442", ""], ["4 May 2006", "Fulham", "Stadium of Light", "2–1", "28,226", "Le Tallec, Brown"], ["7 May 2006", "Aston Villa", "Villa Park", "1–2", "33,820", "D. Collins"], ["23 August 2005", "Manchester City", "Stadium of Light", "1–2", "33,357", "Le Tallec"], ["15 January 2006", "Chelsea", "Stadium of Light", "1–2", "32,420", "Lawrence"], ["31 December 2005", "Everton", "Stadium of Light", "0–1", "30,567", ""], ["5 November 2005", "Arsenal", "Highbury", "1–3", "38,210", "Stubbs"], ["2 January 2006", "Fulham", "Craven Cottage", "1–2", "19,372", "Lawrence"], ["15 October 2005", "Manchester United", "Stadium of Light", "1–3", "39,085", "Elliott"], ["25 March 2006", "Blackburn Rovers", "Stadium of Light", "0–1", "29,593", ""], ["10 September 2005", "Chelsea", "Stamford Bridge", "0–2", "41,969", ""], ["11 March 2006", "Wigan Athletic", "Stadium of Light", "0–1", "31,194", ""], ["12 February 2006", "Tottenham Hotspur", "Stadium of Light", "1–1", "34,700", "Murphy"], ["3 December 2005", "Tottenham Hotspur", "White Hart Lane", "2–3", "36,244", "Whitehead, Le Tallec"], ["23 October 2005", "Newcastle United", "St James' Park", "2–3", "52,302", "Lawrence, Elliott"], ["26 December 2005", "Bolton Wanderers", "Stadium of Light", "0–0", "32,232", ""], ["17 September 2005", "West Bromwich Albion", "Stadium of Light", "1–1", "31,657", "Breen"], ["10 December 2005", "Charlton Athletic", "The Valley", "0–2", "26,065", ""], ["1 October 2005", "West Ham United", "Stadium of Light", "1–1", "31,212", "Miller"], ["1 April 2006", "Everton", "Goodison Park", "2–2", "38,093", "Stead, Delap"], ["13 August 2005", "Charlton Athletic", "Stadium of Light", "1–3", "34,446", "Gray"], ["20 August 2005", "Liverpool", "Anfield", "0–1", "44,913", ""]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what date had the least number of attendees?
|
27 August 2005
| 128
|
Answer:
|
Table InputTable: [["Week", "Date", "Opponent", "Result", "Attendance"], ["8", "October 26, 1981", "at Pittsburgh Steelers", "L 26–13", "52,732"], ["11", "November 15, 1981", "at Kansas City Chiefs", "L 23–10", "73,984"], ["16", "December 20, 1981", "Pittsburgh Steelers", "W 21–20", "41,056"], ["6", "October 11, 1981", "Seattle Seahawks", "W 35–17", "42,671"], ["12", "November 22, 1981", "New Orleans Saints", "L 27–24", "49,581"], ["2", "September 13, 1981", "at Cleveland Browns", "W 9–3", "79,483"], ["7", "October 18, 1981", "at New England Patriots", "L 38–10", "60,474"], ["3", "September 20, 1981", "Miami Dolphins", "L 16–10", "47,379"], ["15", "December 13, 1981", "at San Francisco 49ers", "L 28–6", "55,707"], ["5", "October 4, 1981", "Cincinnati Bengals", "W 17–10", "44,350"], ["9", "November 1, 1981", "at Cincinnati Bengals", "L 34–21", "54,736"], ["1", "September 6, 1981", "at Los Angeles Rams", "W 27–20", "63,198"], ["10", "November 8, 1981", "Oakland Raiders", "W 17–16", "45,519"], ["14", "December 3, 1981", "Cleveland Browns", "W 17–13", "44,502"], ["13", "November 29, 1981", "Atlanta Falcons", "L 31–27", "40,201"], ["4", "September 27, 1981", "at New York Jets", "L 33–17", "50,309"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how may away games did they win?
|
7
| 128
|
Answer:
|
Table InputTable: [["Subject", "Robot's Name", "Who?", "When?", "Where?", "Occupation"], ["Nursing", "Dr. Bug-Bot", "Florence Nightengale", "1860", "England", "Doctor"], ["Olympics", "Rhonda Robot", "Greeks", "776 B.C.", "Greece", "Beauty queen"], ["Painting", "Pierro-Bot", "Stone-Age Humans", "35,000 B.C.", "Europe", "Clown/Artist"], ["Solar System", "Cosmo-Bot", "Copernicus", "1531", "Poland", "Cosmonaut"], ["Helicopter", "Amelia Air-Bot", "Leonardo da Vinci", "1483", "Italy", "Pilot"], ["Writing", "Eraser-Bot", "Sumerians", "3,500 B.C.", "Middle East", "Pencil Man"], ["Microscope", "Slobot", "Antonie van Leeuwenhoek", "1674", "The Netherlands", "Dirty Person"], ["Wheel", "Rollin' Road-Bot", "Sumerians", "3,000 B.C.", "Middle East", "Race Starter"], ["Bicycle", "Booster-Bot", "Karl von Drais", "1816", "Germany", "Rocket Man"], ["Sausage", "Sock-Bot", "Babylonians", "3,000 B.C.", "Middle East", "Sock Man"], ["Saxophone", "Bongo-Bot the Six-Armed Robot", "Antoine-Joseph Sax", "1846", "France", "Six-Armed Drum Player"], ["Radium", "Miss Battery-Bot", "Marie Curie", "1898", "France", "Battery Lady"], ["Germs", "Roast-Bot", "Louis Pasteur", "1865", "France", "Firefighter"], ["Chewing Gum", "Bubble-Bot", "Mayans", "400", "Mexico", "Bubble Man"], ["Dynamite", "Robby Robot", "Alfred Nobel", "1866", "Sweden", "Prankster"], ["Basketball", "Danny Defrost-Bot", "James Naismith", "1891", "United States", "Snowman"], ["Tools", "Hank the Handyman Robot", "Stone-Age Humans", "2½ million years ago", "Africa", "Mechanic"], ["Phonograph", "Slide the Heavy-Metal Robot", "Thomas Edison", "1877", "New Jersey", "Rock Star"], ["Toilet", "Brunwella the Bombshell", "Minoans", "2000 B.C.", "Crete", "Demolisher"], ["Corn Flakes", "Chef Boy-Robot", "William Kellogg", "1894", "Battle Creek, Michigan", "Cook"], ["Coins", "Verna the Vend-Bot", "Lydians", "600 B.C.", "Turkey", "Vending Machine"], ["Paper", "Noshi Origami", "Ts'ai Lun", "105", "China", "Origami Maker"], ["Boomerang", "Oswald the Mailman Robot", "Aborigines", "40,000 years ago", "Australia", "Mailman"], ["Round Earth", "Vasco da Robot", "Ferdinand Magellan", "1522", "Spain", "Early Sailor"], ["Scuba Gear", "Flip the High-Diving Robot", "Jacques Cousteau", "1946", "France", "Diver"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many total subjects are listed?
|
25
| 128
|
Answer:
|
Table InputTable: [["Pos", "Rider", "Manufacturer", "Time/Retired", "Points"], ["11", "Alex Hofmann", "TSR-Honda", "+26.933", "5"], ["Ret", "Andre Romein", "Honda", "Retirement", ""], ["Ret", "Maurice Bolwerk", "TSR-Honda", "Retirement", ""], ["1", "Loris Capirossi", "Honda", "38:04.730", "25"], ["18", "Julien Allemand", "TSR-Honda", "+1:16.347", ""], ["16", "Luca Boscoscuro", "TSR-Honda", "+56.432", ""], ["24", "Henk Van De Lagemaat", "Honda", "+1 Lap", ""], ["15", "Jarno Janssen", "TSR-Honda", "+56.248", "1"], ["8", "Stefano Perugini", "Honda", "+20.891", "8"], ["20", "Lucas Oliver Bulto", "Yamaha", "+1:25.758", ""], ["9", "Jason Vincent", "Honda", "+21.310", "7"], ["21", "David Garcia", "Yamaha", "+1:33.867", ""], ["2", "Valentino Rossi", "Aprilia", "+0.180", "20"], ["10", "Anthony West", "TSR-Honda", "+26.816", "6"], ["12", "Sebastian Porto", "Yamaha", "+27.054", "4"], ["19", "Fonsi Nieto", "Yamaha", "+1:25.622", ""], ["14", "Masaki Tokudome", "TSR-Honda", "+33.161", "2"], ["17", "Johann Stigefelt", "Yamaha", "+1:07.433", ""], ["13", "Tomomi Manako", "Yamaha", "+27.903", "3"], ["4", "Tohru Ukawa", "Honda", "+0.537", "13"], ["5", "Shinya Nakano", "Yamaha", "+0.742", "11"], ["Ret", "Roberto Rolfo", "Aprilia", "Retirement", ""], ["7", "Franco Battaini", "Aprilia", "+20.889", "9"], ["Ret", "Marcellino Lucchi", "Aprilia", "Retirement", ""], ["3", "Jeremy McWilliams", "Aprilia", "+0.534", "16"], ["23", "Arno Visscher", "Aprilia", "+1:40.635", ""], ["22", "Rudie Markink", "Aprilia", "+1:40.280", ""], ["6", "Ralf Waldmann", "Aprilia", "+7.019", "10"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:which manufacturer did the top racer use?
|
Honda
| 128
|
Answer:
|
Table InputTable: [["", "Chronological\\nNo.", "Date\\n(New style)", "Water level\\ncm", "Peak hour"], ["8", "14", "1 November 1726", "270", "–"], ["2", "210", "23 September 1924", "380", "19:15"], ["23", "45", "29 September 1756", "242", ""], ["24", "136", "20 October 1873", "242", "–"], ["14", "25", "10 September 1736", "261", ""], ["43", "208", "24 November 1922", "228", "19:15"], ["21", "201", "17 November 1917", "244", "6:50"], ["28", "260", "20 December 1973", "240", "7:15"], ["27", "177", "26 November 1898", "240", "23:30"], ["25", "175", "4 November 1897", "242", "12:00"], ["34", "171", "2 November 1895", "237", "3:00"], ["46", "211", "3 January 1925", "225", "21:30"], ["32", "76", "29 September 1788", "237", "–"], ["16", "215", "15 October 1929", "258", "17:15"], ["20", "55", "20 November 1764", "244", "–"], ["41", "292", "1 January 1984", "231", "21:20"], ["48", "122", "19 May 1865", "224", "9:10"], ["10", "7", "5 November 1721", "265", "daytime"], ["47", "81", "6 September 1802", "224", "daytime"], ["39", "228", "14 September 1938", "233", "2:25"], ["13", "319", "30 November 1999", "262", "4:35"], ["42", "125", "19 January 1866", "229", "10:00"], ["12", "3", "9 September 1706", "262", "daytime"], ["26", "261", "17 November 1974", "242", "1:00"], ["49", "202", "24 August 1918", "224", "9:10"], ["33", "145", "26 November 1874", "237", "4:00"], ["35", "227", "9 September 1937", "236", "5:30"], ["15", "298", "6 December 1986", "260", "13:30"], ["29", "219", "8 January 1932", "239", "3:00"], ["7", "9", "2 October 1723", "272", "–"], ["18", "83", "24 January 1822", "254", "night"], ["37", "41", "26 October 1752", "234", "12:00"], ["4", "244", "15 October 1955", "293", "20:45"], ["1", "84", "19 November 1824", "421", "14:00"], ["40", "269", "7 September 1977", "231", "16:50"], ["19", "144", "29 October 1874", "252", "4:00"], ["44", "315", "12 October 1994", "228", "13:50"], ["22", "254", "18 October 1967", "244", "13:30"], ["36", "37", "17 October 1744", "234", "–"], ["31", "18", "12 October 1729", "237", "10:00"], ["5", "264", "29 September 1975", "281", "4:00"], ["6", "39", "22 October 1752", "280", "10:00"], ["50", "242", "14 October 1954", "222", "21:00"], ["38", "43", "11 December 1752", "234", "night"], ["30", "225", "8 October 1935", "239", "5:50"], ["45", "116", "8 October 1863", "227", "2:00"], ["9", "183", "13 November 1903", "269", "9:00"], ["3", "71", "9 September 1777", "321", "morning"], ["11", "86", "20 August 1831", "264", "night"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many have a water level under 240cm?
|
22
| 128
|
Answer:
|
Table InputTable: [["Date", "Venue", "Opponent", "Result", "Scoreline", "China scorers"], ["April 16", "Seattle", "Mexico", "Lost", "0-1", "—"], ["April 23", "Los Angeles", "El Salvador", "Drawn", "2-2", "Xiao Zhanbo 62' pen\\nQu Bo 63'"], ["January 10", "Dubai", "United Arab Emirates", "Drawn", "0-0", "—"], ["Dec 21", "Amman", "Jordan", "Won", "1-0", "Cao Yang 77'"], ["Dec 17", "Muscat", "Oman", "Lost", "1-3", "Qu Bo 58'"], ["January 20", "Zhongshan", "Lebanon", "Drawn", "0-0", "—"], ["Dec 19", "Muscat", "Iran", "Lost", "0-2", ""], ["January 27", "Zhongshan", "Syria", "Won", "2-1", "Qu Bo 64'\\nZhu Ting 90'"], ["May 25", "Kunshan", "Jordan", "Won", "2-0", "Hao Junmin 23' pen\\nLi Weifeng 48'"], ["March 15", "Kunming", "Thailand", "Drawn", "3-3", "Qu Bo 34'\\nHan Peng 67'\\nZhu Ting 90'"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:besides seattle what other american city was a venue?
|
Los Angeles
| 128
|
Answer:
|
Table InputTable: [["Cellulose ethers", "Reagent", "Example", "Reagent", "Group R = H or", "Water solubility", "Application", "E number"], ["Alkyl", "Halogenoalkanes", "Methylcellulose", "Chloromethane", "-CH3", "Cold water soluble", "", "E461"], ["Hydroxyalkyl", "Epoxides", "Hydroxyethyl cellulose", "Ethylene oxide", "-CH2CH2OH", "Cold/hot water soluble", "Gelling and thickening agent", ""], ["", "", "Ethyl hydroxyethyl cellulose", "Chloroethane and ethylene oxide", "-CH2CH3 or—CH2CH2OH", "", "", "E467"], ["", "", "Hydroxypropyl methyl cellulose (HPMC)", "Chloromethane and propylene oxide", "-CH3 or -CH2CH(OH)CH3", "Cold water soluble", "Viscosity modifier, gelling, foaming and binding agent", "E464"], ["Carboxyalkyl", "Halogenated carboxylic acids", "Carboxymethyl cellulose (CMC)", "Chloroacetic acid", "-CH2COOH", "Cold/Hot water soluble", "Often used as its sodium salt, sodium carboxymethyl cellulose (NaCMC)", "E466"], ["", "", "Hydroxypropyl cellulose (HPC)", "Propylene oxide", "-CH2CH(OH)CH3", "Cold water soluble", "", "E463"], ["", "", "Ethyl methyl cellulose", "Chloromethane and chloroethane", "-CH3 or -CH2CH3", "", "", "E465"], ["", "", "Hydroxyethyl methyl cellulose", "Chloromethane and ethylene oxide", "-CH3 or -CH2CH2OH", "Cold water soluble", "Production of cellulose films", ""], ["", "", "Ethylcellulose", "Chloroethane", "-CH2CH3", "Water insoluble", "A commercial thermoplastic used in coatings, inks, binders, and controlled-release drug tablets", "E462"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:is the first reagent for a hydroxyalkyl usually a halogenoalkane or an epoxide?
|
Epoxides
| 128
|
Answer:
|
Table InputTable: [["Match Day", "Date", "Opponent", "H/A", "Score", "Aberdeen Scorer(s)", "Attendance"], ["5", "12 September", "Ayr United", "A", "0–1", "", "2,000"], ["24", "9 January", "Ayr United", "H", "1–1", "Cail", "4,500"], ["8", "28 September", "Queen's Park", "H", "1–1", "Main", "5,000"], ["2", "22 August", "Rangers", "H", "0–2", "", "15,000"], ["23", "2 January", "Raith Rovers", "A", "1–5", "Cail", "6,000"], ["6", "19 September", "Motherwell", "H", "3–1", "J. Wyllie, MacLachlan, Walker", "7,000"], ["4", "5 September", "Clyde", "H", "2–0", "MacLachlan, Archibald", "6,000"], ["29", "13 February", "St. Mirren", "A", "2–0", "Cail, Walker", "3,000"], ["28", "6 February", "Morton", "H", "2–0", "Brewster, Archibald", "2,000"], ["14", "7 November", "Raith Rovers", "H", "1–3", "Main", "6,000"], ["31", "27 February", "Third Lanark", "A", "1–0", "Walker", "5,000"], ["34", "20 March", "Airdrieonians", "H", "3–0", "Brewster, Cail, Main", "5,500"], ["13", "31 October", "Hibernian", "A", "2–1", "Chatwin, Main", "4,000"], ["22", "1 January", "Dundee", "H", "2–1", "Walker, J. Wyllie", "7,000"], ["18", "5 December", "Celtic", "H", "0–1", "", "7,000"], ["12", "24 October", "Falkirk", "A", "1–1", "J. Wyllie", "5,500"], ["35", "27 March", "Rangers", "A", "1–1", "W. Wylie", "10,000"], ["30", "20 February", "Hibernian", "H", "0–0", "", "8,500"], ["10", "10 October", "Airdrieonians", "A", "0–3", "", "7,000"], ["26", "23 January", "Falkirk", "H", "1–2", "Walker", "4,000"], ["16", "21 November", "Dumbarton", "H", "0–0", "", "5,000"], ["1", "15 August", "Dundee", "A", "3–1", "Soye, Walker, Cail", "10,000"], ["19", "12 December", "Partick Thistle", "A", "0–3", "", "6,000"], ["32", "6 March", "Partick Thistle", "H", "0–0", "", "6,000"], ["21", "26 December", "Motherwell", "A", "1–1", "Walker", "3,000"], ["20", "19 December", "Kilmarnock", "H", "3–0", "MacLachlan, Cail, Main", "4,000"], ["7", "26 September", "Heart of Midlothian", "A", "0–2", "", "14,000"], ["37", "10 April", "Celtic", "A", "0–1", "", "10,000"], ["33", "13 March", "Queen's Park", "A", "1–3", "Cail", "6,000"], ["17", "28 November", "Kilmarnock", "A", "2–5", "MacLachlan, McLeod", "2,500"], ["27", "30 January", "Dumbarton", "A", "2–3", "Cail, Walker", "3,000"], ["38", "17 April", "Hamilton Academical", "H", "1–0", "J. Wyllie", "4,000"], ["9", "3 October", "St. Mirren", "H", "0–0", "", "6,000"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many matches were attended by at least 8,000 people?
|
6
| 128
|
Answer:
|
Table InputTable: [["Chord", "Root", "Minor Third", "Perfect Fifth", "Major Seventh"], ["CmM7", "C", "E♭", "G", "B"], ["EmM7", "E", "G", "B", "D♯"], ["AmM7", "A", "C", "E", "G♯"], ["E♭mM7", "E♭", "G♭", "B♭", "D"], ["A♭mM7", "A♭", "C♭ (B)", "E♭", "G"], ["FmM7", "F", "A♭", "C", "E"], ["C♯mM7", "C♯", "E", "G♯", "B♯ (C)"], ["D♭mM7", "D♭", "F♭ (E)", "A♭", "C"], ["A♯mM7", "A♯", "C♯", "E♯ (F)", "G (A)"], ["F♯mM7", "F♯", "A", "C♯", "E♯ (F)"], ["B♭mM7", "B♭", "D♭", "F", "A"], ["G♭mM7", "G♭", "B (A)", "D♭", "F"], ["GmM7", "G", "B♭", "D", "F♯"], ["D♯mM7", "D♯", "F♯", "A♯", "C (D)"], ["G♯mM7", "G♯", "B", "D♯", "F (G)"], ["DmM7", "D", "F", "A", "C♯"], ["BmM7", "B", "D", "F♯", "A♯"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:the chords e minor major seventh and a minor major seventh have which note in common?
|
E
| 128
|
Answer:
|
Table InputTable: [["Rank", "Diver", "Preliminary\\nPoints", "Preliminary\\nRank", "Final\\nPoints"], ["18", "Valerie McFarland-Beddoe (AUS)", "401.13", "18", ""], ["23", "Angela Ribeiro (BRA)", "370.68", "23", ""], ["24", "Rim Hassan (EGY)", "258.63", "24", ""], ["17", "Claire Izacard (FRA)", "403.17", "17", ""], ["13", "Ann Fargher (NZL)", "421.65", "13", ""], ["11", "Anita Rossing (SWE)", "464.58", "7", "424.98"], ["7", "Lesley Smith (ZIM)", "438.72", "10", "451.89"], ["21", "Nicole Kreil (AUT)", "382.68", "21", ""], ["", "Christina Seufert (USA)", "481.41", "5", "517.62"], ["4", "Li Yihua (CHN)", "517.92", "1", "506.52"], ["19", "Alison Childs (GBR)", "400.68", "19", ""], ["9", "Jennifer Donnet (AUS)", "432.78", "12", "443.13"], ["20", "Kerstin Finke (FRG)", "393.93", "20", ""], ["22", "Joana Figueiredo (POR)", "374.07", "22", ""], ["10", "Daphne Jongejans (NED)", "487.95", "4", "437.40"], ["5", "Li Qiaoxian (CHN)", "466.83", "6", "487.68"], ["", "Kelly McCormick (USA)", "516.75", "2", "527.46"], ["15", "Antonette Wilken (ZIM)", "414.66", "15", ""], ["14", "Tine Tollan (NOR)", "419.55", "14", ""], ["", "Sylvie Bernier (CAN)", "489.51", "3", "530.70"], ["8", "Debbie Fuller (CAN)", "437.04", "11", "450.99"], ["12", "Verónica Ribot (ARG)", "443.25", "9", "422.52"], ["16", "Guadalupe Canseco (MEX)", "411.96", "16", ""], ["6", "Elsa Tenorio (MEX)", "460.56", "8", "463.56"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many individuals had at least 460+ points their final score?
|
6
| 128
|
Answer:
|
Table InputTable: [["Name", "Country", "Town", "Height\\nmetres / ft", "Structural type", "Held record", "Notes"], ["Great Pyramid of Giza", "Egypt", "Giza", "146 / 480", "Mausoleum", "2570 BC–1311", "Due to erosion today it stands at the height of 138.8 metres (455 ft)."], ["Eiffel Tower", "France", "Paris", "300.6 / 986", "Tower", "1889–1930", "Currently stands at a height of 324 metres (1,063 ft)."], ["Lincoln Cathedral", "England", "Lincoln", "159.7 / 524", "Church", "1311–1549", "Spire collapsed in 1549; today, stands at a height of 83 metres (272 ft)."], ["Ostankino Tower", "Russia", "Moscow", "540 / 1,772", "Tower", "1967–1976", ""], ["St. Mary's Church", "Germany", "Stralsund", "151 / 500", "Church", "1549–1647", "Spire destroyed by lightning in 1647; today stands at a height of 104 metres (341 ft)."], ["Burj Khalifa", "United Arab Emirates", "Dubai", "829.8 / 2,722", "Skyscraper", "2007–present", "Topped-out on 17 January 2009"], ["CN Tower", "Canada", "Toronto", "553 / 1,815", "Tower", "1976–2007", ""], ["Empire State Building", "United States", "New York City", "448 / 1,472", "Skyscraper", "1931–1967", ""], ["Chrysler Building", "United States", "New York City", "319 / 1,046", "Skyscraper", "1930–1931", ""], ["Notre-Dame Cathedral", "France", "Rouen", "151 / 500", "Church", "1876–1880", ""], ["Washington Monument", "United States", "Washington, D.C.", "169.3 / 555", "Monument", "1884–1889", ""], ["Strasbourg Cathedral", "Germany and/or France (today France)", "Strasbourg", "142 / 470", "Church", "1647–1874", ""], ["Cologne Cathedral", "Germany", "Cologne", "157.4 / 516", "Church", "1880–1884", ""], ["St Nikolai", "Germany", "Hamburg", "147.3 / 483", "Church", "1874–1876", "Due to aerial bombing in World War II the nave was demolished; only the spire remains."]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how long did the great pyramid of giza hold the record for tallest freestanding structure?
|
3881
| 128
|
Answer:
|
Table InputTable: [["Name", "Topic", "Cost", "Target age", "Advertising"], ["Starfall.com", "Reading", "Free", "2-9", "None"], ["LearnAlberta.ca", "Everything (mainly aimed at teachers)", "Free", "5-18", "No"], ["Awesome Library", "All", "Free", "All", "Yes - large"], ["IXL", "Math", "$80/year", "4-12", "?"], ["Archimedes-lab.org", "Mathematics", "Free", "10+", "Yes - limited"], ["Bitesize by the BBC", "Art & Design, Business Studies, Design & Technology, DiDA, Drama, English, English Literature, French, Geography, German, History, ICT, Irish, Maths, Music, Physical Education, Religious Studies, Science, Spanish", "Free", "5-16", "None"], ["BrainPop", "Science, Social studies, English, Maths, Art & Music, Health, Technology", "from US$75/year", "4-17", "None"], ["Le Patron", "French", "Free", "12+", "Yes"], ["HackMath.net", "Mathematics", "Free", "9-18", "None"], ["Fact Monster", "World & News, U.S., People, English, Science, Math & Money, Sports", "Free", "4-14 (K-8)", "Yes"], ["Smartygames.com", "Math Games, Reading, Art, Word Scramble, Spanish, Puzzles, Kids Sudoku and more", "Free", "2-9", "None"], ["WatchKnowLearn", "All", "Free", "2-17", "None"], ["Cut-the-Knot", "Maths", "Free", "8+", "Yes - extensive"], ["Ask A Biologist", "Biology", "Free", "5+", "None"], ["Geometry from the Land of the Incas", "Geometry", "Free", "12+", "Yes - extensive"], ["HyperPhysics", "Physics", "Free", "15+", "None"], ["Nafham", "Multidisciplinary 5-20min K-12 school video lessons for Arabic students", "Free", "6-18", "Yes"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many websites are free of advertising?
|
9
| 128
|
Answer:
|
Table InputTable: [["Pos", "No", "Driver", "Constructor", "Laps", "Time/Retired", "Grid", "Points"], ["DNPQ", "34", "Claudio Langes", "EuroBrun-Judd", "", "", "", ""], ["DNPQ", "33", "Roberto Moreno", "EuroBrun-Judd", "", "", "", ""], ["DNPQ", "31", "Bertrand Gachot", "Coloni-Subaru", "", "", "", ""], ["DNQ", "14", "Olivier Grouillard", "Osella-Ford", "", "", "", ""], ["2", "5", "Thierry Boutsen", "Williams-Renault", "64", "+ 39.092", "4", "6"], ["Ret", "2", "Nigel Mansell", "Ferrari", "55", "Gearbox", "1", ""], ["Ret", "6", "Riccardo Patrese", "Williams-Renault", "26", "Chassis", "7", ""], ["1", "1", "Alain Prost", "Ferrari", "64", "1:18:30.999", "5", "9"], ["Ret", "19", "Alessandro Nannini", "Benetton-Ford", "15", "Collision", "13", ""], ["13", "26", "Philippe Alliot", "Ligier-Ford", "61", "+ 3 Laps", "22", ""], ["5", "20", "Nelson Piquet", "Benetton-Ford", "64", "+ 1:24.003", "11", "2"], ["12", "24", "Paolo Barilla", "Minardi-Ford", "62", "+ 2 Laps", "24", ""], ["Ret", "3", "Satoru Nakajima", "Tyrrell-Ford", "20", "Electrical", "12", ""], ["Ret", "22", "Andrea de Cesaris", "Dallara-Ford", "12", "Fuel System", "23", ""], ["DNQ", "35", "Gregor Foitek", "Onyx-Ford", "", "", "", ""], ["DNPQ", "18", "Yannick Dalmas", "AGS-Ford", "", "", "", ""], ["14", "28", "Gerhard Berger", "McLaren-Honda", "60", "Throttle", "3", ""], ["11", "21", "Emanuele Pirro", "Dallara-Ford", "62", "+ 2 Laps", "19", ""], ["DNQ", "7", "David Brabham", "Brabham-Judd", "", "", "", ""], ["9", "8", "Stefano Modena", "Brabham-Judd", "62", "+ 2 Laps", "20", ""], ["DNQ", "36", "JJ Lehto", "Onyx-Ford", "", "", "", ""], ["Ret", "12", "Martin Donnelly", "Lotus-Lamborghini", "48", "Engine", "14", ""], ["3", "27", "Ayrton Senna", "McLaren-Honda", "64", "+ 43.088", "2", "4"], ["Ret", "9", "Michele Alboreto", "Arrows-Ford", "37", "Engine", "25", ""], ["Ret", "16", "Ivan Capelli", "Leyton House-Judd", "48", "Fuel Leak", "10", ""], ["Ret", "11", "Derek Warwick", "Lotus-Lamborghini", "46", "Engine", "16", ""], ["10", "25", "Nicola Larini", "Ligier-Ford", "62", "+ 2 Laps", "21", ""], ["DNPQ", "39", "Bruno Giacomelli", "Life", "", "", "", ""], ["Ret", "17", "Gabriele Tarquini", "AGS-Ford", "41", "Engine", "26", ""], ["DNS", "15", "Maurício Gugelmin", "Leyton House-Judd", "0", "Fuel Pump", "15", ""], ["7", "10", "Alex Caffi", "Arrows-Ford", "63", "+ 1 Lap", "17", ""], ["8", "4", "Jean Alesi", "Tyrrell-Ford", "63", "+ 1 Lap", "6", ""], ["4", "29", "Éric Bernard", "Lola-Lamborghini", "64", "+ 1:15.302", "8", "3"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:which country had the most competitors?
|
Italy
| 128
|
Answer:
|
Table InputTable: [["Season", "Conference", "Head Coach", "Total Wins", "Total Losses", "Total Ties", "Conference Wins", "Conference Losses", "Conference Ties", "Conference Standing", "Postseason Result"], ["1908", "Southern Intercollegiate", "Ralph Foster", "4", "1", "1", "—", "—", "—", "—", "—"], ["Totals:\\n105 Seasons", "2 Conferences", "23 Head Coaches", "Total\\nWins\\n473", "Total\\nLosses\\n536", "Total\\nTies\\n32", "239 Conference Wins\\n55 SIAA\\n184 SoCon", "379 Conference Losses\\n58 SIAA\\n321 SoCon", "13 Conference Ties\\n8 SIAA\\n5 SoCon", "Regular Season\\nChampions\\n2 times", "1–0 Bowl Record\\n1–3 Playoff Record"], ["1918", "Southern Intercollegiate", "Harvey O'Brien", "0", "2", "1", "0", "1", "1", "—", "—"], ["1920", "Southern Intercollegiate", "Harvey O'Brien", "2", "6", "0", "1", "5", "0", "—", "—"], ["1988", "Southern", "Charlie Taaffe", "8", "4", "0", "5", "2", "0", "3", "First Round"], ["1916", "Southern Intercollegiate", "Harvey O'Brien", "6", "1", "1", "4", "1", "0", "—", "—"], ["1911", "Southern Intercollegiate", "L. S. LeTellier", "5", "2", "2", "1", "2", "0", "—", "—"], ["1912", "Southern Intercollegiate", "L. S. LeTellier", "3", "4", "0", "0", "3", "0", "—", "—"], ["1931", "Southern Intercollegiate", "Johnny Floyd", "5", "4", "1", "4", "1", "0", "—", "—"], ["1917", "Southern Intercollegiate", "Harvey O'Brien", "3", "3", "0", "1", "3", "0", "—", "—"], ["1914", "Southern Intercollegiate", "George C. Rogers", "2", "5", "0", "0", "3", "0", "—", "—"], ["1930", "Southern Intercollegiate", "Johnny Floyd", "4", "5", "2", "3", "0", "1", "—", "—"], ["1925", "Southern Intercollegiate", "Carl Prause", "6", "4", "0", "4", "2", "0", "—", "—"], ["1910", "Southern Intercollegiate", "Sam Costen", "3", "4", "0", "1", "3", "0", "—", "—"], ["1929", "Southern Intercollegiate", "Carl Prause", "5", "4", "1", "4", "0", "1", "—", "—"], ["1909", "Southern Intercollegiate", "Sam Costen", "4", "3", "2", "0", "1", "1", "—", "—"], ["1924", "Southern Intercollegiate", "Carl Prause", "6", "4", "0", "4", "2", "0", "—", "—"], ["1992", "Southern", "Charlie Taaffe", "11", "2", "0", "6", "1", "0", "1", "Quarterfinals"], ["1926", "Southern Intercollegiate", "Carl Prause", "7", "3", "0", "4", "3", "0", "—", "—"], ["1932", "Southern Intercollegiate", "Tatum Gressette", "4", "5", "0", "2", "2", "0", "—", "—"], ["1927", "Southern Intercollegiate", "Carl Prause", "3", "6", "1", "2", "3", "1", "—", "—"], ["1922", "Southern Intercollegiate", "Carl Prause", "3", "5", "0", "1", "2", "0", "—", "—"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many total wins did the citadel bulldogs have before 1908?
|
6
| 128
|
Answer:
|
Table InputTable: [["Date introduced", "Class 1 (e.g. Motorbike)", "Class 2 (e.g. Car)", "Class 3 (e.g. Car with trailer)", "Class 4 (e.g. Van)", "Class 5 (e.g. HGV)"], ["1 January 2008", "£2.50", "£4.50", "£8.00", "£9.00", "£9.00"], ["1 March 2012", "£3.00", "£5.50", "£10.00", "£11.00", "£11.00"], ["9 December 2003", "£1.00", "£2.00", "£5.00", "£5.00", "£10.00"], ["1 January 2009", "£2.70", "£4.70", "£8.40", "£9.40", "£9.40"], ["1 March 2011", "£3.00", "£5.30", "£9.60", "£10.60", "£10.60"], ["1 March 2010", "£2.70", "£5.00", "£9.00", "£10.00", "£10.00"], ["23 July 2004", "£1.00", "£2.00", "£5.00", "£5.00", "£6.00"], ["14 June 2005", "£2.50", "£3.50", "£7.00", "£7.00", "£7.00"], ["16 August 2004", "£2.00", "£3.00", "£6.00", "£6.00", "£6.00"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:on what date did the toll for class 1 first go above 2.00?
|
14 June 2005
| 128
|
Answer:
|
Table InputTable: [["Conference", "# of Bids", "Record", "Win %", "Round\\nof 32", "Sweet\\nSixteen", "Elite\\nEight", "Final\\nFour", "Championship\\nGame"], ["Big East", "2", "5–2", ".714", "2", "2", "1", "–", "–"], ["Big Eight", "4", "3–4", ".429", "2", "1", "–", "–", "–"], ["West Coast", "2", "0–2", "–", "–", "–", "–", "–", "–"], ["Colonial", "1", "1–1", ".500", "1", "–", "–", "–", "–"], ["Metro", "2", "2–2", ".500", "1", "1", "–", "–", "–"], ["Mid-Continent", "2", "0–2", "–", "–", "–", "–", "–", "–"], ["Sun Belt", "2", "6–2", ".750", "2", "1", "1", "1", "1"], ["Southeastern", "6", "10–6", ".625", "5", "3", "1", "1", "–"], ["Southwest", "4", "5–4", ".556", "3", "2", "–", "–", "–"], ["Missouri Valley", "2", "2–2", ".500", "2", "–", "–", "–", "–"], ["Big Ten", "5", "9–5", ".643", "4", "2", "2", "1", "–"], ["Pacific-10", "5", "8–5", ".615", "4", "2", "2", "–", "–"], ["Atlantic Coast", "3", "9–2", ".818", "3", "2", "1", "1", "1"], ["Big Sky", "2", "1–2", ".333", "1", "–", "–", "–", "–"], ["Western Athletic", "1", "1–1", ".500", "1", "–", "–", "–", "–"], ["Great Midwest", "2", "0–2", "–", "–", "–", "–", "–", "–"], ["Big West", "2", "0–2", "–", "–", "–", "–", "–", "–"], ["Atlantic 10", "3", "1–3", ".250", "1", "–", "–", "–", "–"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many number of conferences had 2 bids?
|
9
| 128
|
Answer:
|
Table InputTable: [["", "Name on the Register", "Date listed", "Location", "City or town", "Summary"], ["32", "Strafford Union Academy", "September 22, 1983\\n(#83001155)", "NH 126 and NH 202A\\n43°16′07″N 71°07′23″W / 43.268611°N 71.123056°W", "Strafford", ""], ["31", "Strafford County Farm", "February 25, 1981\\n(#81000100)", "County Farm Rd.\\n43°13′03″N 70°56′31″W / 43.2175°N 70.941944°W", "Dover", ""], ["33", "Gen. John Sullivan House", "November 28, 1972\\n(#72000089)", "23 Newmarket Rd.\\n43°07′48″N 70°55′05″W / 43.13°N 70.918056°W", "Durham", "Home of American Revolutionary War General John Sullivan, elected President of New Hampshire."], ["18", "Plumer-Jones Farm", "March 23, 1979\\n(#79000212)", "North of Milton on NH 125\\n43°27′44″N 70°59′37″W / 43.462222°N 70.993611°W", "Milton", ""], ["27", "Salmon Falls Mill Historic District", "February 29, 1980\\n(#80000315)", "Front St.\\n43°14′10″N 70°49′05″W / 43.236111°N 70.818056°W", "Rollinsford", ""], ["15", "Milton Town House", "November 26, 1980\\n(#80000311)", "NH 125 and Town House Rd.\\n43°26′27″N 70°59′05″W / 43.440833°N 70.984722°W", "Milton", ""], ["34", "Thompson Hall", "December 6, 1996\\n(#96001468)", "Off Main St., University of New Hampshire campus\\n43°08′09″N 70°55′59″W / 43.135833°N 70.933056°W", "Durham", ""], ["3", "County Farm Bridge", "May 21, 1975\\n(#75000237)", "Northwest of Dover on County Farm Rd.\\n43°13′14″N 70°56′38″W / 43.220556°N 70.943889°W", "Dover", "Over Cocheco River"], ["7", "First Parish Church Site-Dover Point", "May 27, 1983\\n(#83001153)", "Dover Point Rd.\\n43°08′26″N 70°50′21″W / 43.140556°N 70.839167°W", "Dover", ""], ["11", "William Hale House", "November 18, 1980\\n(#80000309)", "5 Hale St.\\n43°11′36″N 70°52′29″W / 43.193376°N 70.874858°W", "Dover", ""], ["29", "Sawyer Woolen Mills", "September 13, 1989\\n(#89001208)", "1 Mill St.\\n43°10′44″N 70°52′35″W / 43.178889°N 70.876389°W", "Dover", ""], ["26", "St. Thomas Episcopal Church", "June 7, 1984\\n(#84003241)", "5 Hale St.\\n43°11′37″N 70°52′30″W / 43.193611°N 70.875°W", "Dover", ""], ["6", "First Parish Church", "March 11, 1982\\n(#82001696)", "218 Central Ave.\\n43°10′56″N 70°52′27″W / 43.182222°N 70.874167°W", "Dover", ""], ["40", "Samuel Wyatt House", "December 2, 1982\\n(#82000626)", "7 Church St.\\n43°11′30″N 70°52′31″W / 43.191667°N 70.875278°W", "Dover", ""], ["25", "Rollinsford Town Hall", "March 5, 1999\\n(#99000268)", "667 Main St.\\n43°14′08″N 70°49′17″W / 43.235556°N 70.821389°W", "Rollinsford", ""]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what was the last listed historical place in strafford county, new hampshire?
|
Samuel Wyatt House
| 128
|
Answer:
|
Table InputTable: [["Player", "League", "Cup", "Europa\\nLeague", "Total"], ["Gregory Nelson", "3", "0", "1", "4"], ["Stanislav Kostov", "1", "0", "0", "1"], ["Tomislav Kostadinov", "0", "0", "1", "1"], ["Kostadin Stoyanov", "1", "0", "0", "1"], ["Christian Tiboni", "0", "0", "1", "1"], ["Pavel Vidanov", "0", "0", "1", "1"], ["Aleksandar Tonev", "2", "0", "0", "2"], ["Rumen Trifonov", "2", "0", "1", "3"], ["Giuseppe Aquaro", "3", "0", "2", "5"], ["Emil Gargorov", "2", "0", "0", "2"], ["Michel Platini", "10", "0", "0", "10"], ["Spas Delev", "13", "7", "2", "22"], ["Cillian Sheridan", "4", "2", "1", "7"], ["Boris Galchev", "1", "0", "0", "1"], ["Marquinhos", "9", "1", "3", "13"], ["Todor Yanchev", "0", "1", "1", "2"], ["Apostol Popov", "2", "0", "0", "2"], ["Total", "53", "11", "14", "78"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:who scored the same number of league goals this season as gregory nelson?
|
Giuseppe Aquaro
| 128
|
Answer:
|
Table InputTable: [["#", "Title", "Featured guest(s)", "Producer(s)", "Time", "Sample (s)"], ["10", "\"Like That\"", "Ice Cube, Daz Dillinger & CJ Mac", "Daz Dillinger", "4:29", "*\"Just Rhymin' With Biz\" by Big Daddy Kane\\n*\"West Up!\" by WC and the Maad Circle"], ["7", "\"Just Clownin'\"", "", "Battlecat", "3:59", "*\"(Not Just) Knee Deep\" by Funkadelic\\n*\"Too Tight for Light\" by Funkadelic"], ["11", "\"Call It What You Want\"", "", "Crazy Toones", "4:29", "*\"Knucklehead\" by Grover Washington, Jr."], ["16", "\"Better Days\"", "Ron Banks", "Barr Nine", "3:53", "*\"It's Gonna Be Alright\" by Crimies"], ["6", "\"Keep Hustlin\"", "E-40 & Too Short", "Young Tre", "3:39", "*\"Yearning for Your Love\" by The Gap Band\\n*\"Intimate Connection\" by Kleeer"], ["3", "\"Fuckin Wit uh House Party\"", "", "Battlecat", "4:49", "*\"Hollywood Squares\" by Bootsy's Rubber Band\\n*\"(Not Just) Knee Deep\" by Funkadelic"], ["12", "\"Rich Rollin'\"", "", "Dutch", "3:40", ""], ["15", "\"It's All Bad\"", "", "Battlecat", "4:15", "*\"Chocolate City\" by Parliament"], ["13", "\"Cheddar\"", "Mack 10 & Ice Cube", "Mo-Suave-A", "4:12", "*\"Gotta Get My Hands on Some (Money)\" by The Fatback Band"], ["5", "\"Can't Hold Back\"", "Ice Cube", "Skooby Doo", "3:34", "*\"Ain't No Half-Steppin'\" by Big Daddy Kane"], ["4", "\"The Shadiest One\"", "CJ Mac", "Ant Banks", "4:26", ""], ["14", "\"Bank Lick\"", "", "WC", "0:49", ""], ["9", "\"Worldwide Gunnin'\"", "", "Skooby Doo", "3:25", ""], ["17", "\"The Outcome\"", "", "Douglas Coleman", "2:45", ""], ["8", "\"The Autobiography\"", "", "Crazy Toones", "1:21", ""], ["2", "\"Where Y'all From\"", "", "Battlecat", "1:11", ""], ["1", "\"Hog\"", "", "Battlecat", "4:24", "*\"3 Time Felons\" by Westside Connection"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:which track comes after "like that"?
|
"Call It What You Want"
| 128
|
Answer:
|
Table InputTable: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], ["6", "South Korea", "0", "0", "2", "2"], ["5", "North Korea", "1", "0", "1", "2"], ["2", "Japan", "7", "10", "7", "24"], ["3", "Uzbekistan", "1", "2", "3", "6"], ["1", "China", "13", "9", "13", "35"], ["4", "Kazakhstan", "2", "2", "0", "4"], ["Total", "Total", "24", "23", "26", "73"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many gold medals did south korea win?
|
0
| 128
|
Answer:
|
Table InputTable: [["Year", "Competition", "Venue", "Position", "Notes"], ["2006", "World Junior Championships", "Beijing, China", "5th", "5.30 m"], ["2011", "World Championships", "Daegu, South Korea", "9th", "5.65 m"], ["2008", "Olympic Games", "Beijing, China", "10th", "5.45 m"], ["2009", "World Championships", "Berlin, Germany", "22nd (q)", "5.40 m"], ["2005", "World Youth Championships", "Marrakech, Morocco", "6th", "5.05 m"], ["2014", "World Indoor Championships", "Sopot, Poland", "3rd", "5.80 m"], ["2012", "European Championships", "Helsinki, Finland", "6th", "5.60 m"], ["2012", "Olympic Games", "London, United Kingdom", "8th", "5.65 m"], ["2013", "European Indoor Championships", "Gothenburg, Sweden", "5th", "5.71 m"], ["2010", "European Championships", "Barcelona, Spain", "10th", "5.60 m"], ["2009", "European U23 Championships", "Kaunas, Lithuania", "8th", "5.15 m"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:after the 2006 world junior championships what was the other competition held in beijing?
|
Olympic Games
| 128
|
Answer:
|
Table InputTable: [["Pos", "Team", "Played", "Won", "Draw", "Lost", "Goals For", "Goals Against", "Goal Difference", "Points", "Notes"], ["8", "Fram", "18", "4", "5", "9", "22", "33", "-11", "17", ""], ["4", "ÍBV", "18", "8", "5", "5", "29", "17", "+12", "29", "Inter-Toto Cup"], ["7", "Breiðablik", "18", "5", "3", "10", "29", "35", "-6", "18", ""], ["3", "Grindavík", "18", "8", "6", "4", "25", "18", "+7", "30", "UEFA Cup"], ["10", "Leiftur", "18", "3", "7", "8", "24", "39", "-15", "16", "Relegated"], ["2", "Fylkir", "18", "10", "5", "3", "39", "16", "+23", "35", "UEFA Cup"], ["1", "KR", "18", "11", "4", "3", "27", "14", "+13", "37", "UEFA Champions League"], ["6", "Keflavík", "18", "4", "7", "7", "21", "35", "-14", "19", ""], ["9", "Stjarnan", "18", "4", "5", "9", "18", "31", "-13", "17", "Relegated"], ["5", "ÍA", "18", "7", "5", "6", "21", "17", "+4", "26", ""]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many total points did fram have?
|
17
| 128
|
Answer:
|
Table InputTable: [["President", "Became Oldest Living President", "Ceased to Be Oldest Living President", "Age at Start Date", "Age at End Date", "Duration (Years, Days)", "Duration (Days)"], ["George H. W. Bush", "December 26, 2006", "Current oldest living president", "82 years, 197 days", "Current oldest living president", "7 years, 173 days", "2,730 days"], ["President", "Became Oldest Living President", "Ceased to Be Oldest Living President", "Age at Start Date", "Age at End Date", "Duration (Years, Days)", "Duration (Days)"], ["John Quincy Adams", "June 8, 1845", "February 23, 1848", "77 years, 332 days", "80 years, 227 days", "2 years, 260 days", "990 days"], ["William Howard Taft", "March 4, 1909", "March 4, 1913", "51 years, 170 days", "55 years, 170 days", "4 years, 0 days", "1,461 days"], ["John Adams", "December 14, 1799", "July 4, 1826", "64 years, 45 days", "90 years, 247 days", "26 years, 202 days", "9,698 days"], ["William Howard Taft", "February 3, 1924", "March 8, 1930", "66 years, 141 days", "72 years, 174 days", "6 years, 33 days", "2,225 days"], ["Andrew Johnson", "March 8, 1874", "July 31, 1875", "65 years, 69 days", "66 years, 214 days", "1 year, 145 days", "510 days"], ["George Washington", "April 30, 1789", "December 14, 1799", "57 years, 67 days", "67 years, 295 days", "10 years, 228 days", "3,880 days"], ["Rutherford B. Hayes", "July 23, 1885", "January 17, 1893", "62 years, 292 days", "70 years, 105 days", "7 years, 178 days", "2,735 days"], ["Theodore Roosevelt", "June 24, 1908", "March 4, 1909", "49 years, 241 days", "50 years, 128 days", "0 years, 253 days", "253 days"], ["Martin Van Buren", "February 23, 1848", "July 24, 1862", "65 years, 80 days", "79 years, 231 days", "14 years, 151 days", "5,265 days"], ["James Buchanan", "July 24, 1862", "June 1, 1868", "71 years, 92 days", "77 years, 39 days", "5 years, 313 days", "2,139 days"], ["Harry S. Truman", "October 20, 1964", "December 26, 1972", "80 years, 165 days", "88 years, 232 days", "8 years, 67 days", "2,989 days"], ["Calvin Coolidge", "March 8, 1930", "January 5, 1933", "57 years, 247 days", "60 years, 185 days", "2 years, 303 days", "1,034 days"], ["Grover Cleveland", "March 13, 1901", "June 24, 1908", "63 years, 360 days", "71 years, 98 days", "7 years, 103 days", "2,660 days"], ["Lyndon B. Johnson", "December 26, 1972", "January 22, 1973", "64 years, 121 days", "64 years, 148 days", "0 years, 27 days", "27 days"], ["Ronald Reagan", "January 20, 1981", "June 5, 2004", "69 years, 349 days", "93 years, 120 days", "23 years, 137 days", "8,537 days"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:who became the oldest living president before john adams?
|
George Washington
| 128
|
Answer:
|
Table InputTable: [["Parish", "Church name", "Location", "Year built"], ["Levanger", "Bamberg Church", "Levanger", "1998"], ["Levanger", "Levanger Church", "Levanger", "1902"], ["Alstadhaug", "Alstadhaug Church", "Alstadhaug", "1180"], ["Markabygd", "Markabygda Church", "Markabygd", "1887"], ["Okkenhaug", "Okkenhaug Chapel", "Okkenhaug", "1893"], ["Ytterøy", "Ytterøy Church", "Ytterøya", "1890"], ["Ekne", "Ekne Church", "Ekne", "1893"], ["Åsen", "Åsen Church", "Åsen", "1904"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many years after the levanger church was built was the bamberg church built?
|
96
| 128
|
Answer:
|
Table InputTable: [["Player", "Friendlies", "FIFA Confederations Cup", "FIFA World Cup Qual.", "Total Goals"], ["Milicic", "2", "-", "-", "2"], ["Zdrilic", "1", "-", "-", "1"], ["Cahill", "-", "-", "1", "1"], ["Griffiths", "1", "-", "-", "1"], ["Bresciano", "2", "-", "1", "3"], ["Elrich", "1", "-", "-", "1"], ["Colosimo", "1", "-", "-", "1"], ["Chipperfield", "1", "-", "1", "2"], ["Viduka", "1", "-", "2", "3"], ["Aloisi", "1", "4", "-", "5"], ["Thompson", "1", "-", "2", "3"], ["Skoko", "-", "1", "-", "1"], ["Emerton", "-", "-", "2", "2"], ["Culina", "-", "-", "1", "1"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:number of players who scored at least 1 friendly
|
10
| 128
|
Answer:
|
Table InputTable: [["Polling Firm", "Source", "Date Published", "N.Anastasiades", "G.Lillikas", "S.Malas", "Others"], ["Evresis", "[2]", "18 September 2012", "35.2%", "17.5%", "19.7%", "1.7%"], ["Evresis", "[10]", "27 November 2012", "37.1%", "19.6%", "20.8%", "0.6%"], ["Evresis", "[6]", "2 November 2012", "36.9%", "17.7%", "20.6%", "1.4%"], ["Evresis", "[18]", "1 February 2013", "40.8%", "19.9%", "22.2%", "2.5%"], ["Evresis", "[14]", "22 December 2012", "37.4%", "19.8%", "21.8%", "0.5%"], ["Prime Consulting Ltd", "[9]", "18 November 2012", "35.9%", "18.7%", "19.6%", "0.6%"], ["Prime Consulting Ltd", "[12]", "3 December 2012", "35%", "19.1%", "18.6%", "1.4%"], ["Prime Consulting Ltd", "[17]", "27 January 2013", "39.2%", "18.8%", "19.8%", "4%"], ["Prime Consulting Ltd", "[4]", "7 October 2012", "34.7%", "17.4%", "18.5%", ""], ["Prime Consulting Ltd", "[19]", "4 February 2013", "39.8%", "19.3%", "20%", "3%"], ["RAI Consultants", "[7]", "4 November 2012", "38.8%", "19.8%", "21.1%", "2.3%"], ["Prime Consulting Ltd", "[20]", "9 February 2013", "40.6%", "19.6%", "20.4%", "2.9%"], ["Average (only valid votes)", "–", "–", "48.4%", "22.52%", "25.29%", "3.79%"], ["RAI Consultants", "[1][dead link]", "16 September 2012", "37.2%", "14.2%", "21.9%", "1.5%"], ["Noverna", "[3]", "23 September 2012", "35.02%", "15.81%", "17.78%", ""], ["Noverna", "[11]", "2 December 2012", "35.6%", "17.2%", "18.1%", "4.1%"], ["CMR Cypronetwork / Cybc", "[8]", "15 November 2012", "36.8%", "18.9%", "22.8%", "1.6%"], ["RAI Consultants Ltd", "[15][dead link]", "13 January 2013", "40.3%", "17.9%", "20.5%", "6.1%"], ["RAI Consultants Ltd", "[21]", "9 February 2013", "42.1%", "19.4%", "21.1%", "4.4%"], ["CMR Cypronetwork / Cybc", "[22]", "9 February 2013", "39.9%", "20.2%", "24.2%", "3%"], ["CMR Cypronetwork / Cybc", "[16]", "17 January 2013", "38%", "19.7%", "23.7%", "2.7%"], ["CMR Cypronetwork / Cybc", "[13][dead link]", "17 December 2012", "37.1%", "20.4%", "23.1%", "3.1%"], ["CMR Cypronetwork / Cybc", "[5][dead link]", "18 October 2012", "36.9%", "17%", "23.8%", "1.2%"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:calculate the average percentage of each selection.
|
48.4%, 22.52%, 25.29%, 3.79%
| 128
|
Answer:
|
Table InputTable: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], ["5", "Macau (MAC)", "11", "16", "17", "44"], ["1", "China (CHN)", "127", "63", "33", "223"], ["7", "Hong Kong (HKG)", "2", "2", "9", "13"], ["4", "Chinese Taipei (TPE)", "12", "34", "26", "72"], ["3", "South Korea (KOR)", "32", "48", "65", "145"], ["2", "Japan (JPN)", "46", "56", "77", "179"], ["8", "Mongolia (MGL)", "1", "1", "6", "8"], ["Total", "Total", "237", "230", "254", "721"], ["9", "Guam (GUM)", "0", "0", "1", "1"], ["6", "North Korea (PRK)", "6", "10", "20", "36"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many silver medals did macau earn?
|
16
| 128
|
Answer:
|
Table InputTable: [["#", "Weekend End Date", "Film", "Box Office"], ["30", "July 26, 1998", "Godzilla", "£2,145,088"], ["29", "July 19, 1998", "Godzilla", "£4,176,960"], ["1", "January 4, 1998", "Starship Troopers", "£2,221,631"], ["18", "May 3, 1998", "Scream 2", "£2,493,950"], ["7", "February 15, 1998", "Titanic", "£3,849,120"], ["44", "November 1, 1998", "The Exorcist", "£2,186,977"], ["19", "May 10, 1998", "Scream 2", "£1,213,184"], ["41", "October 11, 1998", "The Truman Show", "£2,210,999"], ["13", "March 29, 1998", "Titanic", "£2,223,046"], ["8", "February 22, 1998", "Titanic", "£3,657,613"], ["4", "January 25, 1998", "Titanic", "£4,805,270"], ["9", "March 1, 1998", "Titanic", "£3,403,199"], ["31", "August 2, 1998", "Lost in Space", "£3,127,079"], ["3", "January 18, 1998", "The Devil's Advocate", "£1,300,773"], ["11", "March 15, 1998", "Titanic", "£2,469,191"], ["37", "September 13, 1998", "Saving Private Ryan", "£2,704,522"], ["34", "August 23, 1998", "The X-Files", "£2,506,148"], ["15", "April 12, 1998", "Titanic", "£1,373,363"], ["32", "August 9, 1998", "Armageddon", "£2,732,785"], ["6", "February 8, 1998", "Titanic", "£4,274,375"], ["10", "March 8, 1998", "Titanic", "£3,010,921"], ["35", "August 30, 1998", "The X-Files", "£1,192,131"], ["25", "June 21, 1998", "City of Angels", "£1,141,654"], ["42", "October 18, 1998", "The Truman Show", "£1,687,037"], ["33", "August 16, 1998", "Armageddon", "£2,243,095"], ["38", "September 20, 1998", "Saving Private Ryan", "£2,077,362"], ["12", "March 22, 1998", "Titanic", "£1,953,082"], ["14", "April 5, 1998", "Titanic", "£1,504,551"], ["23", "June 7, 1998", "The Wedding Singer", "£1,031,660"], ["43", "October 25, 1998", "Small Soldiers", "£1,137,725"], ["16", "April 19, 1998", "Titanic", "£981,940"], ["26", "June 28, 1998", "City of Angels", "£674,705"], ["2", "January 11, 1998", "The Jackal", "£1,422,193"], ["24", "June 14, 1998", "The Wedding Singer", "£974,719"], ["5", "February 1, 1998", "Titanic", "£4,773,404"], ["39", "September 27, 1998", "There's Something About Mary", "£2,076,411"], ["27", "July 5, 1998", "Six Days Seven Nights", "£908,713"], ["40", "October 4, 1998", "There's Something About Mary", "£2,026,662"], ["50", "December 13, 1998", "Rush Hour", "£1,179,123"], ["52", "December 27, 1998", "Enemy of the State", "£1,420,216"], ["51", "December 20, 1998", "Rush Hour", "£744,783"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many different movies are on the list?
|
23
| 128
|
Answer:
|
Table InputTable: [["Pos", "No", "Driver", "Constructor", "Laps", "Time/Retired", "Grid", "Points"], ["9", "2", "Rubens Barrichello", "Ferrari", "65", "+1 lap", "16", ""], ["12", "18", "Tiago Monteiro", "Jordan-Toyota", "63", "+3 laps", "18", ""], ["Ret", "1", "Michael Schumacher", "Ferrari", "46", "Puncture", "8", ""], ["2", "5", "Fernando Alonso", "Renault", "66", "+27.652", "3", "8"], ["10", "8", "Nick Heidfeld", "Williams-BMW", "65", "+1 lap", "17", ""], ["11", "12", "Felipe Massa", "Sauber-Petronas", "63", "Wheel rim", "10", ""], ["8", "14", "David Coulthard", "Red Bull-Cosworth", "65", "+1 lap", "9", "1"], ["Ret", "11", "Jacques Villeneuve", "Sauber-Petronas", "51", "Engine", "12", ""], ["13", "19", "Narain Karthikeyan", "Jordan-Toyota", "63", "+3 laps", "13", ""], ["1", "9", "Kimi Räikkönen", "McLaren-Mercedes", "66", "1:27:16.830", "1", "10"], ["7", "10", "Juan Pablo Montoya", "McLaren-Mercedes", "65", "+1 lap", "7", "2"], ["Ret", "15", "Vitantonio Liuzzi", "Red Bull-Cosworth", "9", "Spun off", "11", ""], ["6", "7", "Mark Webber", "Williams-BMW", "66", "+1:08.542", "2", "3"], ["4", "17", "Ralf Schumacher", "Toyota", "66", "+46.719", "4", "5"], ["5", "6", "Giancarlo Fisichella", "Renault", "66", "+57.936", "6", "4"], ["Ret", "20", "Patrick Friesacher", "Minardi-Cosworth", "11", "Spun off", "15", ""], ["Ret", "21", "Christijan Albers", "Minardi-Cosworth", "19", "Gearbox", "14", ""], ["3", "16", "Jarno Trulli", "Toyota", "66", "+45.947", "5", "6"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:who was the last place driver to complete at least 50 laps?
|
Jacques Villeneuve
| 128
|
Answer:
|
Table InputTable: [["Pos", "No", "Driver", "Team", "Laps", "Time/Retired", "Grid", "Points"], ["2", "1", "Bruno Junqueira", "Newman/Haas Racing", "87", "+0.8 secs", "2", "17"], ["17", "2", "Sébastien Bourdais", "Newman/Haas Racing", "77", "Mechanical", "4", "0"], ["11", "27", "Bryan Herta", "PK Racing", "86", "+ 1 Lap", "12", "2"], ["9", "7", "Tiago Monteiro", "Fittipaldi-Dingman Racing", "86", "+ 1 Lap", "15", "4"], ["13", "19", "Joël Camathias", "Dale Coyne Racing", "85", "+ 2 Laps", "18", "0"], ["14", "33", "Alex Tagliani", "Rocketsports Racing", "85", "+ 2 Laps", "14", "0"], ["16", "11", "Geoff Boss", "Dale Coyne Racing", "83", "Mechanical", "19", "0"], ["7", "51", "Adrian Fernández", "Fernández Racing", "87", "+1:01.4", "5", "6"], ["15", "4", "Roberto Moreno", "Herdez Competition", "85", "+ 2 Laps", "9", "0"], ["10", "55", "Mario Domínguez", "Herdez Competition", "86", "+ 1 Lap", "11", "3"], ["6", "20", "Oriol Servià", "Patrick Racing", "87", "+1:00.2", "10", "8"], ["18", "15", "Darren Manning", "Walker Racing", "12", "Mechanical", "7", "0"], ["12", "31", "Ryan Hunter-Reay", "American Spirit Team Johansson", "86", "+ 1 Lap", "17", "1"], ["19", "5", "Rodolfo Lavín", "Walker Racing", "10", "Mechanical", "16", "0"], ["5", "34", "Mario Haberfeld", "Mi-Jack Conquest Racing", "87", "+42.1 secs", "6", "10"], ["1", "32", "Patrick Carpentier", "Team Player's", "87", "1:48:11.023", "1", "22"], ["3", "3", "Paul Tracy", "Team Player's", "87", "+28.6 secs", "3", "14"], ["4", "9", "Michel Jourdain, Jr.", "Team Rahal", "87", "+40.8 secs", "13", "12"], ["8", "12", "Jimmy Vasser", "American Spirit Team Johansson", "87", "+1:01.8", "8", "5"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many drivers earned more than 2 points at the 2003 grand prix of monterey?
|
10
| 128
|
Answer:
|
Table InputTable: [["Comet", "Discoverer(s) or namesake(s)", "Orbital period (years)", "Spacecraft encounter(s)"], ["1P/Halley", "Halley", "75.32", "Giotto (flyby 1986), Vega 1 (flyby 1986), Vega 2 (flyby 1986), Suisei (flyby 1986) ICE (distant flyby 1986), Sakigake (distant flyby 1986)"], ["250P/Larson", "Larson (Catalina Sky Survey)", "7.20", ""], ["19P/Borrelly", "Borrelly", "6.85", "Deep Space 1 (flyby 2001)"], ["9P/Tempel (Tempel 1)", "Tempel", "5.58", "Deep Impact (impactor/flyby 2005), Stardust (flyby 2011)"], ["107P/Wilson–Harrington = minor planet 4015 Wilson–Harrington", "Helin & Wilson & Harrington", "4.29", ""], ["67P/Churyumov–Gerasimenko", "Churyumov & Gerasimenko", "6.45", "Rosetta (orbiter 2014)"], ["21P/Giacobini–Zinner", "Giacobini & Zinner", "6.60", "ICE (distant flyby 1985)"], ["103P/Hartley (Hartley 2)", "Hartley", "6.47", "Deep Impact (flyby 2010)"], ["26P/Grigg–Skjellerup", "Grigg & Skjellerup", "5.31", "Giotto (flyby 1992)"], ["174P/Echeclus = minor planet 60558 Echeclus", "Spacewatch", "35.02", ""], ["211P/Hill", "Hill (Catalina Sky Survey) IAUC 9001", "6.71", ""], ["46P/Wirtanen", "Wirtanen", "5.44", "ICE (distant flyby 2018 – proposed), CHopper (lander 2022—proposed)"], ["133P/Elst–Pizarro = minor planet 7968 Elst–Pizarro", "Elst & Pizarro", "5.62", ""], ["95P/Chiron = minor planet 2060 Chiron", "Kowal", "50.50", ""], ["232P/Hill", "Hill (Catalina Sky Survey)", "9.49", ""], ["248P/Gibbs", "Gibbs (Catalina Sky Survey)", "14.63", ""], ["229P/Gibbs", "Gibbs (Catalina Sky Survey)", "7.78", ""], ["288P/Spacewatch = minor planet (300163) 2006 VW139", "Spacewatch", "5.32", ""], ["198P/ODAS", "OCA-DLR Asteroid Survey (ODAS)[2], IAUC 8929", "6.78", ""], ["274P/Tombaugh–Tenagra", "Tombaugh & Tenagra II Observatory", "9.12", ""], ["227P/Catalina–LINEAR", "Catalina Sky Survey & LINEAR", "6.79", ""], ["271P/van Houten–Lemmon", "C. van Houten & I. van Houten-Groeneveld & Mount Lemmon Survey", "18.42", ""], ["281P/MOSS", "Morocco Oukaimeden Sky Survey (MOSS)", "10.69", ""], ["263P/Gibbs", "Gibbs (Catalina Sky Survey)", "5.36", ""], ["176P/LINEAR = minor planet 118401 LINEAR", "LINEAR", "5.71", ""], ["279P/La Sagra", "La Sagra Sky Survey", "6.78", ""], ["81P/Wild (Wild 2)", "Wild", "6.41", "Stardust (flyby/sample return 2004)"], ["261P/Larson", "Larson (Mount Lemmon Survey)", "6.80", ""], ["233P/La Sagra", "La Sagra Sky Survey", "5.29", ""], ["22P/Kopff", "Kopff", "6.43", "CRAF (rendezvous/lander 2000 – cancelled)"], ["257P/Catalina", "Catalina Sky Survey", "7.27", ""]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many different flyby's have been done for the halley comet?
|
6
| 128
|
Answer:
|
Table InputTable: [["Year", "Division", "League", "Regular Season", "Playoffs", "Open Cup"], ["1998", "4", "USISL PDSL", "4th, Central", "Division Finals", "1st Round"], ["2003", "4", "USL PDL", "5th, Heartland", "Did not qualify", "Did not qualify"], ["1999", "4", "USL PDL", "5th, Heartland", "Did not qualify", "Did not qualify"], ["2004", "4", "USL PDL", "6th, Heartland", "Did not qualify", "Did not qualify"], ["2005", "4", "USL PDL", "3rd, Heartland", "Did not qualify", "Did not qualify"], ["2009", "4", "USL PDL", "6th, Heartland", "Did not qualify", "Did not qualify"], ["2002", "4", "USL PDL", "5th, Heartland", "Did not qualify", "Did not qualify"], ["2010", "4", "USL PDL", "7th, Heartland", "Did not qualify", "Did not qualify"], ["2008", "4", "USL PDL", "5th, Heartland", "Did not qualify", "Did not qualify"], ["2007", "4", "USL PDL", "3rd, Heartland", "Did not qualify", "1st Round"], ["2006", "4", "USL PDL", "3rd, Heartland", "Did not qualify", "Did not qualify"], ["2013", "4", "USL PDL", "4th, Heartland", "Did not qualify", "Did not qualify"], ["2012", "4", "USL PDL", "5th, Heartland", "Did not qualify", "Did not qualify"], ["2000", "4", "USL PDL", "4th, Rocky Mountain", "Did not qualify", "Did not qualify"], ["2001", "4", "USL PDL", "5th, Rocky Mountain", "Did not qualify", "Did not qualify"], ["2011", "4", "USL PDL", "4th, Heartland", "Did not qualify", "Did not qualify"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how long is the time frame in years of the table?
|
16
| 128
|
Answer:
|
Table InputTable: [["Date", "Rnd", "Race Name", "Circuit", "City/Location", "Pole position", "Winning driver", "Winning team", "Report"], ["10", "August 5", "Marlboro 500", "Michigan International Speedway", "Brooklyn, Michigan", "Emerson Fittipaldi", "Al Unser, Jr.", "Galles-Kraco Racing", "Report"], ["11", "August 26", "Texaco/Havoline Grand Prix of Denver", "Streets of Denver", "Denver, Colorado", "Teo Fabi", "Al Unser, Jr.", "Galles-Kraco Racing", "Report"], ["12", "September 2", "Molson Indy Vancouver", "Streets of Vancouver", "Vancouver, British Columbia", "Michael Andretti", "Al Unser, Jr.", "Galles-Kraco Racing", "Report"], ["3", "May 27", "74th Indianapolis 500", "Indianapolis Motor Speedway", "Speedway, Indiana", "Emerson Fittipaldi", "Arie Luyendyk", "Doug Shierson Racing", "Report"], ["14", "September 23", "Texaco/Havoline 200", "Road America", "Elkhart Lake, Wisconsin", "Danny Sullivan", "Michael Andretti", "Newman/Haas Racing", "Report"], ["2", "April 22", "Toyota Long Beach Grand Prix", "Streets of Long Beach", "Long Beach, California", "Al Unser, Jr.", "Al Unser, Jr.", "Galles-Kraco Racing", "Report"], ["8", "July 15", "Marlboro Grand Prix at the Meadowlands", "Meadowlands Sports Complex", "East Rutherford, New Jersey", "Michael Andretti", "Michael Andretti", "Newman/Haas Racing", "Report"], ["16", "October 21", "Champion Spark Plug 300K", "Laguna Seca Raceway", "Monterey, California", "Danny Sullivan", "Danny Sullivan", "Team Penske", "Report"], ["5", "June 17", "Valvoline Grand Prix of Detroit", "Streets of Detroit", "Detroit, Michigan", "Michael Andretti", "Michael Andretti", "Newman/Haas Racing", "Report"], ["13", "September 16", "Red Roof Inns 200", "Mid-Ohio Sports Car Course", "Lexington, Ohio", "Michael Andretti", "Michael Andretti", "Newman/Haas Racing", "Report"], ["NC", "October 6", "Marlboro Challenge", "Nazareth Speedway", "Nazareth, Pennsylvania", "Michael Andretti", "Rick Mears", "Team Penske", "Report"], ["9", "July 22", "Molson Indy Toronto", "Exhibition Place", "Toronto, Ontario", "Danny Sullivan", "Al Unser, Jr.", "Galles-Kraco Racing", "Report"], ["1", "April 8", "Autoworks 200", "Phoenix International Raceway", "Phoenix, Arizona", "Rick Mears", "Rick Mears", "Team Penske", "Report"], ["6", "June 24", "Budweiser/G.I.Joe's 200", "Portland International Raceway", "Portland, Oregon", "Danny Sullivan", "Michael Andretti", "Newman/Haas Racing", "Report"], ["4", "June 3", "Miller Genuine Draft 200", "Milwaukee Mile", "West Allis, Wisconsin", "Rick Mears", "Al Unser, Jr.", "Galles-Kraco Racing", "Report"], ["15", "October 7", "Bosch Spark Plug Grand Prix", "Nazareth Speedway", "Nazareth, Pennsylvania", "Bobby Rahal", "Emerson Fittipaldi", "Team Penske", "Report"], ["7", "July 8", "Budweiser Grand Prix of Cleveland", "Cleveland Burke Lakefront Airport", "Cleveland, Ohio", "Rick Mears", "Danny Sullivan", "Team Penske", "Report"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many races took place after august?
|
6
| 128
|
Answer:
|
Table InputTable: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], ["3", "Korea", "1", "1", "2", "4"], ["7", "Japan", "0", "0", "2", "2"], ["1", "Malaysia", "3", "0", "1", "4"], ["2", "Indonesia", "1", "3", "2", "6"], ["8", "India", "0", "0", "1", "1"], ["4", "Thailand", "1", "0", "0", "1"], ["5", "Chinese Taipei", "0", "1", "2", "3"], ["6", "Denmark", "0", "1", "0", "1"], ["9", "Spain", "0", "0", "1", "1"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what nation has won more gold medals than korea?
|
Malaysia
| 128
|
Answer:
|
Table InputTable: [["District", "Location", "Communities served"], ["Saint Mary's School", "Chardon, Ohio", "Roman Catholic Diocese of Cleveland preschool - 8th grade; parishioners and non-parishioners"], ["Saint Helen's School", "Newbury, Ohio", "Roman Catholic Diocese of Cleveland K - 8th grade; parishioners and non-parishioners"], ["Notre Dame-Cathedral Latin", "Munson Township, Ohio", "Roman Catholic Diocese of Cleveland: open to 8th grade students who have attended a Catholic elementary school and others who have not"], ["Saint Anselm School", "Chester Township, Ohio", "Roman Catholic Diocese of Cleveland K - 8th grade; preschool"], ["Hawken School", "Gates Mills, Ohio", "College preparatory day school: online application, site visit and testing"], ["Solon/Bainbridge Montessori School of Languages", "Bainbridge Township, Ohio", "nonsectarian Montessori School: quarterly enrollment periods"], ["Hershey Montessori Farm School", "Huntsburg Township, Ohio", "parent-owned, and chartered by Ohio Department of Education: application deadline January each year"], ["Agape Christian Academy", "Burton Township, Ohio and Troy Township, Ohio", "Accepts applications prior to the start of each school year"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many of the schools serve the roman catholic diocese of cleveland?
|
4
| 128
|
Answer:
|
Table InputTable: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], ["8", "Guyana", "0", "1", "0", "1"], ["9", "Netherlands Antilles", "0", "0", "1", "1"], ["9", "Panama", "0", "0", "1", "1"], ["1", "Brazil", "7", "5", "3", "15"], ["9", "Uruguay", "0", "0", "1", "1"], ["2", "Venezuela", "3", "2", "8", "13"], ["5", "Argentina", "1", "2", "5", "8"], ["7", "Ecuador", "0", "2", "2", "4"], ["3", "Colombia", "2", "3", "4", "9"], ["6", "Peru", "1", "1", "2", "4"], ["Total", "Total", "16", "16", "30", "62"], ["9", "Aruba", "0", "0", "1", "1"], ["4", "Chile", "2", "0", "2", "4"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many total medals did guyana win in the competition?
|
1
| 128
|
Answer:
|
Table InputTable: [["Opus", "Title", "Subdivisions", "Compo-sition", "Première date", "Place, theatre"], ["15", "Die heilige Linde", "3 acts", "1927", "2001", "Keulen (prelude only)"], ["14", "Rainulf und Adelasia", "3 acts", "1922", "1923", "Rostock (prelude only)"], ["3", "Der Kobold", "3 acts", "1903", "29 January 1904", "Hamburg, Stadttheater"], ["18", "Das Flüchlein, das Jeder mitbekam", "3 acts", "1929", "29 April 1984", "Kiel (completed by Hans Peter Mohr)"], ["17", "Walamund (libretto only, no music completed)", "3 acts", "1928", "", ""], ["5", "Sternengebot", "prologue and 3 acts", "1906", "21 January 1908", "Hamburg, Stadttheater"], ["12a", "Das Liebesopfer (libretto only, no music completed)", "4 acts", "1917", "", ""], ["4", "Bruder Lustig", "3 acts", "1904", "13 October 1905", "Hamburg, Stadttheater"], ["9", "Der Heidenkönig", "prologue and 3 acts", "1913", "16 December 1933", "Cologne, Städtische Bühnen"], ["16", "Wahnopfer", "3 acts", "1928", "1994", "Rudolstadt, Heidecksburg only libretto and Act 1 finished"], ["2", "Herzog Wildfang", "3 acts", "1900", "23 March 1901", "Munich, Hofopera"], ["8", "Sonnenflammen", "3 acts", "1912", "30 October 1918", "Darmstadt, Hoftheater"], ["1", "Der Bärenhäuter", "3 acts", "1898", "22 January 1899", "Munich, Hofopera"], ["11", "An allem ist Hütchen Schuld!", "3 acts", "1915", "6 December 1917", "Stuttgart, Hofopera"], ["6", "Banadietrich", "3 acts", "1909", "23 January 1910", "Karlsruhe, Hoftheater"], ["13", "Der Schmied von Marienburg", "3 acts", "1920", "16 December 1920", "Rostock, Städtische Bühnen"], ["7", "Schwarzschwanenreich", "3 acts", "1910", "5 November 1918", "Karlsruhe, Hoftheater"], ["10", "Der Friedensengel", "3 acts", "1914", "4 March 1926", "Karlsruhe, Badisches Landestheater"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many titles were listed as having 3 acts and a prologue?
|
2
| 128
|
Answer:
|
Table InputTable: [["Rank", "Cyclist", "Team", "Time", "UCI ProTour\\nPoints"], ["1", "Alejandro Valverde (ESP)", "Caisse d'Epargne", "5h 29' 10\"", "40"], ["2", "Alexandr Kolobnev (RUS)", "Team CSC Saxo Bank", "s.t.", "30"], ["8", "Stéphane Goubert (FRA)", "Ag2r-La Mondiale", "+ 2\"", "5"], ["10", "David Moncoutié (FRA)", "Cofidis", "+ 2\"", "1"], ["7", "Samuel Sánchez (ESP)", "Euskaltel-Euskadi", "s.t.", "7"], ["6", "Denis Menchov (RUS)", "Rabobank", "s.t.", "11"], ["4", "Paolo Bettini (ITA)", "Quick Step", "s.t.", "20"], ["3", "Davide Rebellin (ITA)", "Gerolsteiner", "s.t.", "25"], ["5", "Franco Pellizotti (ITA)", "Liquigas", "s.t.", "15"], ["9", "Haimar Zubeldia (ESP)", "Euskaltel-Euskadi", "+ 2\"", "3"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:who was the first cyclist to finish?
|
Alejandro Valverde
| 128
|
Answer:
|
Table InputTable: [["Year", "Title", "Genre", "Publisher", "Notes"], ["1923", "Tappan's Burro", "Western", "Harper & Brothers", ""], ["1930", "The Wolf Tracker", "Western", "Harper & Brothers", ""], ["1910", "The Young Forester", "Western", "Harper & Brothers", ""], ["1930", "The Shepherd of Guadaloupe", "Western", "Harper & Brothers", ""], ["1919", "The Desert of Wheat", "Western", "Harper & Brothers", ""], ["1923", "Wanderer of the Wasteland", "Western", "Harper & Brothers", ""], ["1913", "Desert Gold", "Western", "Harper & Brothers", ""], ["1912", "Riders of the Purple Sage", "Western", "Harper & Brothers", ""], ["1933", "The Drift Fence", "Western", "Harper & Brothers", ""], ["1928", "Avalanche", "Western", "Harper & Brothers", ""], ["1927", "Forlorn River", "Western", "Harper & Brothers", ""], ["1933", "The Hash Knife Outfit", "Western", "Harper & Brothers", "Sequel to The Drift Fence"], ["1916", "The Border Legion", "Western", "Harper & Brothers", ""], ["1932", "Arizona Ames", "Western", "Harper & Brothers", ""], ["1929", "Fighting Caravans", "Western", "Harper & Brothers", ""], ["1921", "The Mysterious Rider", "Western", "Harper & Brothers", ""], ["1929", "Stairs of Sand", "Western", "Harper & Brothers", ""], ["1925", "The Thundering Herd", "Western", "Harper & Brothers", ""], ["1943", "Omnibus", "Western", "Harper & Brothers", ""], ["1934", "The Code of the West", "Western", "Harper & Brothers", ""], ["1928", "Wild Horse Mesa", "Western", "Harper & Brothers", ""], ["1920", "The Redheaded Outfield and other Baseball Stories", "Baseball", "Harper & Brothers", ""], ["1914", "The Light of Western Stars", "Western", "Harper & Brothers", ""], ["1925", "The Vanishing American", "Western", "Harper & Brothers", ""], ["1928", "Tales of Fresh Water Fishing", "Fishing", "Harper & Brothers", ""], ["1910", "The Heritage of the Desert", "Western", "Harper & Brothers", ""], ["1924", "The Call of the Canyon", "Western", "Harper & Brothers", ""], ["1911", "The Young Lion Hunter", "Western", "Harper & Brothers", ""], ["1921", "To the Last Man", "Western", "Harper & Brothers", ""], ["1903", "Betty Zane", "Historical", "Charles Francis Press", ""], ["1927", "Tales of Swordfish and Tuna", "Fishing", "Harper & Brothers", ""], ["1928", "Don, the Story of a Lion Dog", "Western", "Harper & Brothers", ""], ["1932", "Robbers' Roost", "Western", "Harper & Brothers", ""], ["1912", "Ken Ward in the Jungle", "Western", "Harper & Brothers", ""], ["1911", "The Young Pitcher", "Baseball", "Harper & Brothers", ""], ["1922", "The Day of the Beast", "Fiction", "Harper & Brothers", ""], ["1953", "Wyoming", "Western", "Harper & Brothers", ""], ["1922", "Tales of Lonely Trails", "Adventure", "Harper & Brothers", ""], ["1917", "Wildfire", "Western", "Harper & Brothers", ""], ["1924", "Tales of Southern Rivers", "Fishing", "Harper & Brothers", ""], ["1958", "Arizona Clan", "Western", "Harper & Brothers", ""], ["1915", "The Rainbow Trail", "Western", "Harper & Brothers", "Sequel to Riders of the Purple Sage"], ["1919", "Tales of Fishes", "Fishing", "Harper & Brothers", ""], ["1939", "Western Union", "Western", "Harper & Brothers", ""], ["1946", "Shadow on the Trail", "Western", "Harper & Brothers", ""], ["1918", "The UP Trail", "Western", "Harper & Brothers", ""]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what was the first book published by harper & brothers between 1903-1923?
|
The Heritage of the Desert
| 128
|
Answer:
|
Table InputTable: [["Year", "Name", "Label", "Hot Black Singles", "Club Play Singles"], ["1983", "\"I Need You Now\"", "Jive", "―", "―"], ["1982", "\"Thanks to You\"", "Becket", "#44", "#1"], ["1982", "\"He's Gonna Take You Home\"", "Becket", "―", "―"], ["1984", "\"Thin Line\"", "Power House", "―", "―"], ["1987", "\"Send It C.O.D.\"", "New Image", "―", "―"], ["1986", "\"Say It Again\"", "Spring", "―", "―"], ["1986", "\"Say It Again\"", "Spring", "―", "―"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:which song topped the club play singles list?
|
"Thanks to You"
| 128
|
Answer:
|
Table InputTable: [["Olympics", "Athlete", "Judge (Official)", "Coach", "Language"], ["1984 Summer Olympics", "Edwin Moses", "Sharon Weber", "-", "English"], ["1932 Summer Olympics", "George Calnan", "-", "-", "English"], ["1980 Winter Olympics", "Eric Heiden", "Terry McDermott", "-", "English"], ["1980 Summer Olympics", "Nikolai Andrianov", "Alexander Medved", "-", "Russian"], ["1936 Summer Olympics", "Rudolf Ismayr", "-", "-", "-"], ["1924 Summer Olympics", "Géo André", "-", "-", "French."], ["1976 Summer Olympics", "Pierre St.-Jean", "Maurice Fauget", "-", "French (St.-Jean)/English (Fauget)"], ["1972 Summer Olympics", "Heidi Schüller", "Heinz Pollay", "-", "German"], ["1952 Summer Olympics", "Heikki Savolainen", "-", "-", "-"], ["1928 Summer Olympics", "Harry Dénis", "-", "-", "-"], ["1996 Summer Olympics", "Teresa Edwards", "Hobie Billingsley", "-", "English"], ["1988 Winter Olympics", "Pierre Harvey", "Suzanna Morrow-Francis", "-", "English"], ["1956 Summer Olympics", "John Landy (Melbourne)\\nHenri Saint Cyr (Stockholm)", "-", "-", "English/Swedish"], ["1920 Summer Olympics", "Victor Boin", "-", "-", "-"], ["2000 Summer Olympics", "Rechelle Hawkes", "Peter Kerr", "-", "English"], ["1968 Winter Olympics", "Léo Lacroix", "-", "-", "French"], ["1998 Winter Olympics", "Kenji Ogiwara", "Junko Hiramatsu", "-", "Japanese"], ["1948 Summer Olympics", "Donald Finlay", "-", "-", "English"], ["1936 Winter Olympics", "Willy Bogner, Sr.", "-", "-", "-"], ["1932 Winter Olympics", "Jack Shea", "-", "-", "-"], ["1964 Winter Olympics", "Paul Aste", "-", "-", "German"], ["1928 Winter Olympics", "Hans Eidenbenz", "-", "-", "-"], ["1924 Winter Olympics", "Camille Mandrillon", "-", "-", "-"], ["1960 Summer Olympics", "Adolfo Consolini", "-", "-", "-"], ["2012 Summer Olympics", "Sarah Stevenson", "Mik Basi", "Eric Farrell", "English"], ["2006 Winter Olympics", "Giorgio Rocca", "Fabio Bianchetti", "-", "Italian"], ["1992 Winter Olympics", "Surya Bonaly", "Pierre Bornat", "-", "French"], ["1948 Winter Olympics", "Bibi Torriani", "-", "-", "-"], ["2002 Winter Olympics", "Jimmy Shea", "Allen Church", "-", "English"], ["1976 Winter Olympics", "Werner Delle Karth", "Willy Köstinger", "-", "German"], ["1968 Summer Olympics", "Pablo Garrido", "-", "-", "Spanish"], ["2008 Summer Olympics", "Zhang Yining", "Huang Liping", "-", "Chinese"], ["1952 Winter Olympics", "Torbjørn Falkanger", "-", "-", "-"], ["1960 Winter Olympics", "Carol Heiss", "-", "-", "-"], ["1972 Winter Olympics", "Keiichi Suzuki", "Fumio Asaki", "-", "Japanese"], ["1994 Winter Olympics", "Vegard Ulvang", "Kari Kåring", "-", "English (Ulvang)/Norwegian (Kåring)"], ["1964 Summer Olympics", "Takashi Ono", "-", "-", "Japanese"], ["1988 Summer Olympics", "Hur Jae\\nShon Mi-Na", "Lee Hak-Rae", "-", "Korean"], ["2010 Winter Olympics", "Hayley Wickenheiser", "Michel Verrault", "-", "English/French"], ["1992 Summer Olympics", "Luis Doreste Blanco", "Eugeni Asensio", "-", "Spanish/Catalan"], ["1984 Winter Olympics", "Bojan Križaj", "Dragan Perovic", "-", "Serbo-Croatian"], ["1956 Winter Olympics", "Giuliana Minuzzo", "-", "-", "-"], ["2014 Winter Olympics", "Ruslan Zakharov", "Vyacheslav Vedenin, Jr", "Anastassia Popkova", "Russian"], ["2004 Summer Olympics", "Zoi Dimoschaki", "Lazaros Voreadis", "-", "Greek"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what year did a judge or official first start officiating the olympic oath?
|
1972
| 128
|
Answer:
|
Table InputTable: [["Round", "Date", "Circuit", "Winning driver (TA2)", "Winning vehicle (TA2)", "Winning driver (TA1)", "Winning vehicle (TA1)"], ["7", "August 19", "Mosport", "Greg Pickett", "Chevrolet Corvette", "Bob Tullius", "Jaguar XJS"], ["8", "September 4", "Road America", "Greg Pickett", "Chevrolet Corvette", "Bob Tullius", "Jaguar XJS"], ["1", "May 21", "Sears Point", "Greg Pickett", "Chevrolet Corvette", "Gene Bothello", "Chevrolet Corvette"], ["4", "June 25", "Mont-Tremblant", "Monte Sheldon", "Porsche 935", "Bob Tullius", "Jaguar XJS"], ["3", "June 11", "Portland", "Tuck Thomas", "Chevrolet Monza", "Bob Matkowitch", "Chevrolet Corvette"], ["6", "August 13", "Brainerd", "Jerry Hansen", "Chevrolet Monza", "Bob Tullius", "Jaguar XJS"], ["5", "July 8", "Watkins Glen‡", "Hal Shaw, Jr.\\n Monte Shelton", "Porsche 935", "Brian Fuerstenau\\n Bob Tullius", "Jaguar XJS"], ["9", "October 8", "Laguna Seca", "Greg Pickett", "Chevrolet Corvette", "Bob Tullius", "Jaguar XJS"], ["10", "November 5", "Mexico City", "Ludwig Heimrath", "Porsche 935", "Bob Tullius", "Jaguar XJS"], ["2", "June 4", "Westwood", "Ludwig Heimrath", "Porsche 935", "Nick Engels", "Chevrolet Corvette"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many circuits are there total?
|
10
| 128
|
Answer:
|
Table InputTable: [["Year", "Competition", "Venue", "Position", "Event", "Notes"], ["2007", "Universiade", "Bangkok, Thailand", "1st", "400 m", ""], ["2006", "Asian Games", "Doha, Qatar", "1st", "400 m", ""], ["2001", "World Youth Championships", "Debrecen, Hungary", "4th", "400 m", ""], ["2006", "Asian Games", "Doha, Qatar", "2nd", "4x400 m relay", ""], ["2005", "Asian Championships", "Incheon, South Korea", "2nd", "4x400 m relay", ""], ["2002", "Asian Games", "Busan, South Korea", "2nd", "4x400 m relay", ""], ["2005", "Universiade", "Izmir, Turkey", "6th", "4x400 m relay", ""], ["2011", "Universiade", "Shenzhen, China", "–", "400 m", "DQ"], ["2006", "World Cup", "Athens, Greece", "7th", "400 m", ""]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:where did she achieve first place for the first time
|
Doha, Qatar
| 128
|
Answer:
|
Table InputTable: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], ["1", "Australia (AUS)", "2", "1", "0", "3"], ["7", "Great Britain (GBR)", "0", "0", "1", "1"], ["3", "Germany (EUA)", "1", "0", "1", "2"], ["7", "France (FRA)", "0", "0", "1", "1"], ["5", "Switzerland (SUI)", "0", "2", "1", "3"], ["2", "Italy (ITA)", "1", "1", "1", "3"], ["4", "Soviet Union (URS)", "1", "0", "0", "1"], ["6", "United States (USA)", "0", "1", "0", "1"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what was the total number of medals won by australia?
|
3
| 128
|
Answer:
|
Table InputTable: [["Year", "Class", "No", "Tyres", "Car", "Team", "Co-Drivers", "Laps", "Pos.", "Class\\nPos."], ["1993", "GT", "71", "D", "Venturi 500LM\\nRenault PRV 3.0 L Turbo V6", "Jacadi Racing", "Michel Maisonneuve\\n Christophe Dechavanne", "210", "DNF", "DNF"], ["1996", "GT1", "38", "M", "McLaren F1 GTR\\nBMW S70 6.1L V12", "Team Bigazzi SRL", "Steve Soper\\n Marc Duez", "318", "11th", "9th"], ["1994", "GT2", "49", "P", "Porsche 911 Carrera RSR\\nPorsche 3.8 L Flat-6", "Larbre Compétition", "Jacques Alméras\\n Jean-Marie Alméras", "94", "DNF", "DNF"], ["1990", "C1", "6", "G", "Porsche 962C\\nPorsche Type-935 3.0L Turbo Flat-6", "Joest Porsche Racing", "Henri Pescarolo\\n Jean-Louis Ricci", "328", "14th", "14th"], ["1978", "S\\n+2.0", "10", "", "Mirage M9\\nRenault 2.0L Turbo V6", "Grand Touring Cars Inc.", "Vern Schuppan\\n Sam Posey", "293", "10th", "5th"], ["1977", "S\\n+2.0", "8", "", "Renault Alpine A442\\nRenault 2.0L Turbo V6", "Renault Sport", "Patrick Depailler", "289", "DNF", "DNF"], ["1974", "S\\n3.0", "15", "", "Ligier JS2\\nMaserati 3.0L V6", "Automobiles Ligier", "Alain Serpaggi", "310", "8th", "5th"], ["1972", "S\\n3.0", "22", "", "Ligier JS2\\nMaserati 3.0L V6", "Automobiles Ligier", "Pierre Maublanc", "195", "DNF", "DNF"], ["1973", "S\\n3.0", "62", "", "Ligier JS2\\nMaserati 3.0L V6", "Automobiles Ligier", "Guy Ligier", "24", "DSQ", "DSQ"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many times did this racer not finish the race?
|
4
| 128
|
Answer:
|
Table InputTable: [["Poll Source", "Sample Size", "Margin of Error", "Date", "Democrat", "%", "Republican", "%"], ["Rasmussen Reports", "500", "4.5", "Mar 31, 2008", "Hillary Clinton", "36", "John McCain", "51"], ["Rasmussen Reports", "500", "", "Feb 18, 2008", "Hillary Clinton", "37", "John McCain", "47"], ["Survey USA", "517", "4.4", "Mar 14-16, 2008", "Hillary Clinton", "44", "John McCain", "48"], ["Rasmussen Reports", "500", "4.5", "Mar 31, 2008", "Barack Obama", "46", "John McCain", "42"], ["Survey USA", "563", "4.2", "Feb 15-17, 2008", "Hillary Clinton", "41", "John McCain", "52"], ["Rasmussen Reports", "500", "", "Feb 18, 2008", "Barack Obama", "44", "John McCain", "41"], ["Survey USA", "543", "4.3", "Jan 4-6, 2008", "Hillary Clinton", "44", "John McCain", "48"], ["Survey USA", "502", "4.5", "Oct 12-14, 2007", "Hillary Clinton", "49", "John McCain", "44"], ["Survey USA", "546", "4.3", "Nov 9-11, 2007", "Hillary Clinton", "44", "John McCain", "48"], ["Survey USA", "563", "4.2", "Feb 15-17, 2008", "Barack Obama", "51", "John McCain", "41"], ["Survey USA", "517", "4.4", "Mar 14-16, 2008", "Barack Obama", "50", "John McCain", "44"], ["Survey USA", "543", "4.3", "Jan 4-6, 2008", "Barack Obama", "55", "John McCain", "38"], ["Survey USA", "543", "4.3", "Jan 4-6, 2008", "Hillary Clinton", "51", "Rudy Giuliani", "35"], ["Survey USA", "498", "4.5", "Oct 12-14, 2007", "Hillary Clinton", "52", "Ron Paul", "36"], ["Survey USA", "543", "4.3", "Jan 4-6, 2008", "Hillary Clinton", "48", "Mitt Romney", "40"], ["Survey USA", "506", "4.3", "Oct 12-14, 2007", "Hillary Clinton", "51", "Mike Huckabee", "41"], ["Survey USA", "543", "4.3", "Jan 4-6, 2008", "Hillary Clinton", "47", "Mike Huckabee", "45"], ["Survey USA", "506", "4.4", "Oct 12-14, 2007", "Hillary Clinton", "50", "Mitt Romney", "42"], ["Survey USA", "513", "4.4", "Oct 12-14, 2007", "Hillary Clinton", "48", "Rudy Giuliani", "43"], ["Survey USA", "546", "4.3", "Nov 9-11, 2007", "Barack Obama", "50", "John McCain", "42"], ["Survey USA", "509", "4.4", "Oct 12-14, 2007", "Hillary Clinton", "50", "Fred Thompson", "42"], ["Survey USA", "546", "4.3", "Nov 9-11, 2007", "Hillary Clinton", "49", "Mitt Romney", "43"], ["Survey USA", "546", "4.3", "Nov 9-11, 2007", "Hillary Clinton", "49", "Mike Huckabee", "43"], ["Survey USA", "", "", "Dec. 17, 2007", "Hillary Clinton", "46", "Mike Huckabee", "45"], ["Survey USA", "543", "4.3", "Jan 4-6, 2008", "Barack Obama", "59", "Mitt Romney", "33"], ["Survey USA", "546", "4.3", "Nov 9-11, 2007", "Hillary Clinton", "47", "Rudy Giuliani", "43"], ["Survey USA", "543", "4.3", "Jan 4-6, 2008", "Barack Obama", "58", "Mike Huckabee", "35"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:did hillary clinton or john mccain win 51% of the vote in the march 31, 2008 rasmussen reports poll?
|
John McCain
| 128
|
Answer:
|
Table InputTable: [["Nation", "Date", "Quantity", "Type", "Notes"], ["Venezuela", "2014", "6", "5009", "The Bolivarian Armada of Venezuela ordered 6 vessels together with 6 Damen Stan Patrol 4207 in March 2014. They are being built in UCOCAR shipyard with the assistance of DAMEX Shipbuilding & Engineering, Cuba."], ["Netherlands", "2001", "2", "4207", "In 2001 the Netherlands ordered two vessels to serve in the Dutch customs' service. Visarend commissioned in 2001, Zeearend in 2002. now operated by the Dutch Coast Guard"], ["Venezuela", "2014", "6", "4207", "The Bolivarian Armada of Venezuela ordered 6 vessels together with 6 Damen Ocean Patrol 5007 in March 2014. They are being built in UCOCAR shipyard with the assistance of DAMEX Shipbuilding & Engineering, Cuba."], ["Mexico", "2012", "6", "4207", "The Mexican Navy – Armada de México – inducted the first two of what could be several Tenochtitlan-class coastal patrol boats.[citation needed] The two StanPatrol 4207 patrol boats – ARM Tenochtitlan (PC-331) and ARM Teotihuacan (PC-332) were built at a cost of $9 million USD each at ASTIMAR 1 in Tampico, Tamaulipas and completed in April and May 2012."], ["Jamaica", "2005", "3", "4207", "The three vessels which form the County-class are HMJS Surrey, HMJS Cornwall and HMJS Middlesex. They were built in the Netherlands, and the last vessel was delivered in December 2006."], ["Qatar", "2014", "6", "5009", "The Qatar Armed Forces ordered 6 vessels together with 1 x 52 meter Diving Support Vessel on March 31st 2014. The vessels are to be build by Nakilat Damen Shipyard Qatar"], ["Canada", "2009", "9", "4207", "In 2009 the Department of Fisheries and Oceans announced it would be purchasing 9 patrol vessels for the Canadian Coast Guard. The Hero-class patrol vessels began entering service in 2011."], ["Barbados", "2007", "3", "4207", "Built for the Barbados Coast Guard. HMBS Leonard C Banfield and HMBS Rudyard Lewis were scheduled to be delivered in 2008. HMBS Trident was scheduled for delivery in 2009."], ["Albania", "2007", "4", "4207", "The Iliria and three other vessels: Oriku, Lisus and Butrindi operated by the Albanian Naval Defense Forces"], ["United States", "2012", "", "4708", "The United States Coast Guard is proposing the purchase of 24-34 cutters as the Sentinel class."], ["United Kingdom", "2001", "4", "4207", "the UKBA 42m Customs Cutters Seeker, Searcher, Vigilant and Valiant are operated by the United Kingdom Border Agency."], ["Netherlands Antilles & Aruba", "1998", "3", "4100", "Jaguar, Panter and Poema employed by the Netherlands Antilles & Aruba Coast Guard."], ["Honduras", "2013", "2", "4207", "Honduran Navy 2 patrol vessels 4207 (FNH 1401 Lempira and FNH 1402 Morazan) and 6 Damen Interceptor 1102 in service 2013"], ["Bahama's", "2013", "4", "4207", "The Royal Bahamas Defence Forces ordered 4 vessels together with 4 x Sea Axe 3007 Patrols and 1 x Stan Lander 5612 Logistics Support and Landing Craft in April 2013."], ["Bulgaria", "2010", "1", "4207", "The Bulgarian Border Police accepted delivery of the Obzor on July 16, 2010."], ["South Africa", "2004", "3", "4708", "Lillian Ngoyi-class environmental inshore patrol vessels: Lillian Ngoyi, Ruth First and Victoria Mxenge are employed by the Department of Agriculture, Forestry and Fisheries."], ["Vietnam", "2004", "3", "4100", "SAR-411, SAR-412 and SAR-413 employed by Vietnam Coast Guard search and rescue service."]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:who has the most quantity of all nations?
|
Canada
| 128
|
Answer:
|
Table InputTable: [["Place", "Shooter", "5 pts", "4 pts", "3 pts", "2 pts", "1 pts", "0 pts", "Total", "Rank"], ["2", "Sweden (SWE)", "8", "19", "12", "1", "-", "-", "154", ""], ["1", "Norway (NOR)", "12", "16", "12", "-", "-", "-", "160", ""], ["5", "Finland (FIN)", "7", "10", "15", "5", "-", "3", "130", ""], ["1", "Harald Natvig", "2", "4", "4", "-", "-", "-", "38", "8"], ["–", "Miloslav Hlaváč", "1", "2", "6", "1", "-", "-", "33", "15"], ["2", "Mauritz Johansson", "2", "4", "3", "1", "-", "-", "37", "11"], ["1", "Einar Liberg", "5", "2", "3", "-", "-", "-", "42", "2"], ["6", "Hungary (HUN)", "1", "8", "17", "4", "1", "9", "97", ""], ["–", "Czechoslovakia (TCH)", "1", "2", "6", "1", "-", "-", "33", ""], ["6", "Elemér Takács", "1", "2", "3", "-", "1", "3", "23", "23"], ["6", "Gusztáv Szomjas", "-", "4", "4", "1", "-", "1", "30", "20"], ["1", "Otto Olsen", "1", "5", "4", "-", "-", "-", "37", "11"], ["5", "Toivo Tikkanen", "1", "1", "5", "1", "-", "2", "26", "22"], ["1", "Ole Lilloe-Olsen", "4", "5", "1", "-", "-", "-", "43", "1"], ["5", "Karl Magnus Wegelius", "2", "6", "2", "-", "-", "-", "40", "5"], ["6", "László Szomjas", "-", "1", "5", "1", "-", "3", "21", "25"], ["4", "John Faunthorpe", "-", "5", "4", "-", "-", "1", "32", "16"], ["2", "Otto Hultberg", "1", "6", "3", "-", "-", "-", "38", "8"], ["5", "Jalo Autonen", "1", "1", "5", "2", "-", "1", "28", "21"], ["3", "Dennis Fenton", "1", "2", "5", "2", "-", "-", "32", "16"], ["4", "Great Britain (GBR)", "8", "9", "18", "3", "-", "2", "136", ""], ["2", "Alfred Swahn", "3", "4", "3", "-", "-", "-", "40", "5"], ["2", "Fredric Landelius", "2", "5", "3", "-", "-", "-", "39", "7"], ["4", "Cyril Mackworth-Praed", "6", "-", "3", "1", "-", "-", "41", "3"], ["3", "United States (USA)", "7", "17", "13", "3", "-", "-", "148", ""], ["4", "John O'Leary", "1", "2", "6", "-", "-", "1", "31", "19"], ["3", "John Boles", "3", "5", "2", "-", "-", "-", "41", "3"], ["4", "Alexander Rogers", "1", "2", "5", "2", "-", "-", "32", "16"], ["5", "Martti Liuttula", "3", "2", "3", "2", "-", "-", "36", "14"], ["3", "Walter Stokes", "1", "6", "3", "-", "-", "-", "38", "8"], ["6", "Rezső Velez", "-", "1", "5", "2", "-", "2", "23", "23"], ["3", "Raymond Coulter", "2", "4", "3", "1", "-", "-", "37", "11"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what is the difference in points scored between norway and sweden?
|
6
| 128
|
Answer:
|
Table InputTable: [["Conference", "# of Bids", "Record", "Win %", "Round\\nof 32", "Sweet\\nSixteen", "Elite\\nEight", "Final\\nFour", "Championship\\nGame"], ["Western Athletic", "1", "1–1", ".500", "1", "–", "–", "–", "–"], ["West Coast", "2", "0–2", "–", "–", "–", "–", "–", "–"], ["Big Ten", "5", "9–5", ".643", "4", "2", "2", "1", "–"], ["Big Eight", "4", "3–4", ".429", "2", "1", "–", "–", "–"], ["Big West", "2", "0–2", "–", "–", "–", "–", "–", "–"], ["Big East", "2", "5–2", ".714", "2", "2", "1", "–", "–"], ["Mid-Continent", "2", "0–2", "–", "–", "–", "–", "–", "–"], ["Great Midwest", "2", "0–2", "–", "–", "–", "–", "–", "–"], ["Southeastern", "6", "10–6", ".625", "5", "3", "1", "1", "–"], ["Atlantic Coast", "3", "9–2", ".818", "3", "2", "1", "1", "1"], ["Sun Belt", "2", "6–2", ".750", "2", "1", "1", "1", "1"], ["Southwest", "4", "5–4", ".556", "3", "2", "–", "–", "–"], ["Big Sky", "2", "1–2", ".333", "1", "–", "–", "–", "–"], ["Missouri Valley", "2", "2–2", ".500", "2", "–", "–", "–", "–"], ["Pacific-10", "5", "8–5", ".615", "4", "2", "2", "–", "–"], ["Colonial", "1", "1–1", ".500", "1", "–", "–", "–", "–"], ["Metro", "2", "2–2", ".500", "1", "1", "–", "–", "–"], ["Atlantic 10", "3", "1–3", ".250", "1", "–", "–", "–", "–"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many teams played in a championship game?
|
2
| 128
|
Answer:
|
Table InputTable: [["Eps #", "Prod #", "Title", "Summary", "Air Date"], ["13", "19", "Rama-Tut", "After coming back from vacation Reed tells Ben an interesting theory on attempting to restore him. They head to Dr. Doom’s deserted castle to use the time machine the doctor left behind. In 2000 B.C the four weaken during a fight and are taken by Pharaoh Rama-Tut, who is a lot more than he would seem at first sight. Susan is to be Rama-Tut’s queen while the other three are put to work with some mind control. Ben turns back to his former self. As he rescues Susan, he is once again the Thing. The four battle Rama-Tut to his sphinx. Finally, they destroy his sphinx and return to their own time.", "12/9/1967"], ["12", "13", "Return Of the Mole Man", "The Mole Man is creating earthquakes and causing buildings to sink deep into the Earth. In addition, he and his Moloids kidnap Susan. The Mole Man as usual has been expecting the other three and sends them back to the surface to tell the Army not to get involved. They manage to halt them and seek an alternate entrance in the underworld. Johnny rescues Susan, then they penetrate the laboratory. They all return the buildings to the surface and escape the exploding caves.", "11/25/1967"], ["6", "9", "Prisoners Of Planet X", "A UFO has been sighted. The pilot abducts the Fantastic Four from the Science Center and is setting course for Planet X. There, their dictator Kurrgo requests the Fantastic Four save their planet from another planet knocked off its orbit. Reed manages to formulate a working plan to save the population. While the plan is in process, Kurrgo has other ideas. However, Reed tricks Kurrgo and leaves him on the exploding planet while the micro-sized population and the Fantastic Four get away to safety.", "10/14/1967"], ["3", "7", "The Way It All Began", "While on a television show, Reed recalls the time he first met Victor von Doom before he became Dr. Doom. He had Ben as his roommate at university. Victor was working on dangerous experiments, especially a test that brought him to the hospital and got him expelled from university. Worse than that, the test altered his face and he swore revenge on Reed having to hide his work from him. Ben and Reed became soldiers in World War II. Ben, Susan, Johnny and Reed all went aboard a space rocket for space exploration. And so the origin of the Fantastic Four began. Dr. Doom confronts the Fantastic Four on the television show and briefs them on his origin. After that Dr. Doom attempts to get his revenge, but fails and escapes only to crash.", "9/23/1967"], ["5a", "1", "Klaws", "Klaw is here to vanquish the Fantastic 4 with his solidifying sonic waves. Johnny is on vacation or so it would seem and arrives in the nick of time to assist Mr. Fantastic in catching The Klaw.", "10/7/1967"], ["18", "18", "The Terrible Tribunal", "The Fantastic Four are taken to another planet where they are regarded as criminals against evil, charged by three old enemies. Reed is forced to recall his memories on Klaw, Molecule, Man and Blastaar’s defeat. Meanwhile the other three escape and they rescue Reed just as the verdict is given. At the surface, they have to battle the court judge before they are able to leave the planet for Earth.", "9/14/1968"], ["7", "14", "It Started On Yancy Street", "The Fantastic Four face a bunch of old rivals in Yancy Street, but their old enemy Red Ghost and his primates show up and capture them. During their voyage to the moon, the four turn the tables, but Red Ghost gets away and the four are dumped on the moon. They barely manage to get to a source of oxygen which is the Watcher’s laboratory. Using one of the Watcher’s machines, Reed brings down Red Ghost’s ship. Susan gets Dr. Kragoff banished into a trans-nitron machine. Reed uses that machine to get back to Earth.", "10/21/1967"], ["15", "16", "The Micro World Of Dr. Doom", "The Fantastic Four have been shrunken to small size. Dr. Doom is after them and takes them to the Micro World. Dr. Doom briefs them on his micro genius experiments involving a king and a princess from the micro world. The four battle the giant guards but Dr. Doom catches them and imprisons them with the King and Princess. They all escape and enlarge themselves. Ben puts a stop to the Lizard Men, then the four return to their own world.", "12/30/1967"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:were more episodes aired in 1967 or 1968?
|
1967
| 128
|
Answer:
|
Table InputTable: [["Pick #", "Player", "Position", "Nationality", "NHL team", "College/junior/club team"], ["160", "Kari Kanervo", "Centre", "Finland", "Minnesota North Stars", "TPS (Finland)"], ["157", "Petri Skriko", "Right Wing", "Finland", "Vancouver Canucks", "Saipa (Finland)"], ["151", "Denis Dore", "Right Wing", "Canada", "Hartford Whalers", "Chicoutimi Saguenéens (QMJHL)"], ["161", "Armel Parisee", "Defence", "Canada", "Boston Bruins", "Chicoutimi Saguenéens (QMJHL)"], ["162", "Dale DeGray", "Defence", "Canada", "Calgary Flames", "Oshawa Generals (OMJHL)"], ["150", "Tony Arima", "Left Wing", "Finland", "Colorado Rockies", "Jokerit (Finland)"], ["154", "Mitch Lamoureux", "Centre", "Canada", "Pittsburgh Penguins", "Oshawa Generals (OMJHL)"], ["167", "Alain Vigneault", "Defence", "Canada", "St. Louis Blues", "Trois-Rivières Draveurs (QMJHL)"], ["149", "Rick Zombo", "Defence", "United States", "Detroit Red Wings", "Austin Mavericks (USHL)"], ["155", "Mike Sturgeon", "Defence", "Canada", "Edmonton Oilers", "Kelowna Buckaroos (BCJHL)"], ["159", "Johan Mellstrom", "Left Wing", "Sweden", "Chicago Black Hawks", "Falun (Sweden)"], ["148", "Dan McFall", "Defence", "United States", "Winnipeg Jets", "Buffalo Jr. Sabres (NAJHL)"], ["168", "Bill Dowd", "Defence", "Canada", "New York Islanders", "Ottawa 67's (OMJHL)"], ["153", "Richard Turmel", "Defence", "Canada", "Toronto Maple Leafs", "Shawinigan Cataractes (QMJHL)"], ["152", "Gaetan Duchesne", "Left Wing", "Canada", "Washington Capitals", "Quebec Remparts (QMJHL)"], ["156", "Ari Lahteenmaki", "Right Wing", "Finland", "New York Rangers", "HIFK (Finland)"], ["164", "Gates Orlando", "Centre", "Canada", "Buffalo Sabres", "Providence College (ECAC)"], ["163", "Steve Taylor", "Left Wing", "United States", "Philadelphia Flyers", "Providence College (ECAC)"], ["158", "Andre Cote", "Right Wing", "Canada", "Quebec Nordiques", "Quebec Remparts (QMJHL)"], ["165", "Dan Brennan", "Left Wing", "Canada", "Los Angeles Kings", "University of North Dakota (WCHA)"], ["166", "Paul Gess", "Left Wing", "United States", "Montreal Canadiens", "Bloomington Jefferson High School (USHS-MN)"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what is the position of the player above kari kanervo?
|
Left Wing
| 128
|
Answer:
|
Table InputTable: [["#", "Episode", "Air date", "Rating", "Share", "18-49 (Rating/Share)", "Viewers (m)", "Rank (night)", "Rank (timeslot)", "Rank (overall)"], ["7", "\"The Past Comes Back to Haunt You\"", "November 16, 2007", "6.2", "11", "1.7/5", "8.94", "#4", "#1", "#41"], ["8", "\"No Opportunity Necessary\"", "November 23, 2007", "5.3", "9", "1.6/5", "7.76", "#3", "#1", "#45"], ["6", "\"Play Through the Pain\"", "November 15, 2007", "6.1", "10", "3.3/9", "8.93", "#8", "#3", "#45"], ["4", "\"Grannies, Guns, Love Mints\"", "November 2, 2007", "6.4", "11", "1.9/6", "9.47", "#1", "#1", "#35"], ["1", "\"Welcome to the Club\"", "October 12, 2007", "7.3", "13", "2.5/8", "10.82", "#1", "#1", "#26"], ["2", "\"Train In Vain\"", "October 19, 2007", "6.5", "12", "2.0/6", "9.69", "#2", "#1", "#37"], ["11", "\"Father's Day\"", "April 29, 2008", "5.8", "9", "1.9/5", "8.14", "#7", "#2", "#42"], ["3", "\"Blind Dates and Bleeding Hearts\"", "October 26, 2007", "6.1", "11", "1.9/6", "8.90", "#1", "#1", "#41"], ["9", "\"To Drag & To Hold\"", "December 7, 2007", "5.8", "10", "1.8/5", "8.58", "#2", "#1", "#32"], ["10", "\"FBI Guy\"", "January 4, 2008", "5.2", "9", "1.8/5", "7.68", "#2", "#1", "#36"], ["5", "\"Maybe, Baby\"", "November 9, 2007", "6.5", "11", "2.0/6", "9.70", "#1", "#1", "#36"], ["13", "\"Never Tell\"", "May 13, 2008", "5.8", "10", "2.1/6", "8.46", "", "#2", ""], ["12", "\"And the Truth Will (Sometimes) Set You Free\"", "May 6, 2008", "6.1", "10", "2.2/6", "8.68", "#8", "#2", ""]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:previous to november 15, 2007 how often was the overall rank in the 30s?
|
3
| 128
|
Answer:
|
Table InputTable: [["Atomic\\nno.", "Name", "Symbol", "Group", "Period", "Block", "State at\\nSTP", "Occurrence", "Description"], ["88", "Radium", "Ra", "2", "7", "s", "Solid", "Transient", "Alkaline earth metal"], ["45", "Rhodium", "Rh", "9", "5", "d", "Solid", "Primordial", "Transition metal"], ["90", "Thorium", "Th", "3", "7", "f", "Solid", "Primordial", "Actinide"], ["38", "Strontium", "Sr", "2", "5", "s", "Solid", "Primordial", "Alkaline earth metal"], ["59", "Praseodymium", "Pr", "3", "6", "f", "Solid", "Primordial", "Lanthanide"], ["104", "Rutherfordium", "Rf", "4", "7", "d", "", "Synthetic", "Transition metal"], ["44", "Ruthenium", "Ru", "8", "5", "d", "Solid", "Primordial", "Transition metal"], ["108", "Hassium", "Hs", "8", "7", "d", "", "Synthetic", "Transition metal"], ["92", "Uranium", "U", "3", "7", "f", "Solid", "Primordial", "Actinide"], ["21", "Scandium", "Sc", "3", "4", "d", "Solid", "Primordial", "Transition metal"], ["102", "Nobelium", "No", "3", "7", "f", "Solid", "Synthetic", "Actinide"], ["75", "Rhenium", "Re", "7", "6", "d", "Solid", "Primordial", "Transition metal"], ["107", "Bohrium", "Bh", "7", "7", "d", "", "Synthetic", "Transition metal"], ["69", "Thulium", "Tm", "3", "6", "f", "Solid", "Primordial", "Lanthanide"], ["63", "Europium", "Eu", "3", "6", "f", "Solid", "Primordial", "Lanthanide"], ["67", "Holmium", "Ho", "3", "6", "f", "Solid", "Primordial", "Lanthanide"], ["96", "Curium", "Cm", "3", "7", "f", "Solid", "Transient", "Actinide"], ["93", "Neptunium", "Np", "3", "7", "f", "Solid", "Transient", "Actinide"], ["46", "Palladium", "Pd", "10", "5", "d", "Solid", "Primordial", "Transition metal"], ["77", "Iridium", "Ir", "9", "6", "d", "Solid", "Primordial", "Transition metal"], ["33", "Arsenic", "As", "15", "4", "p", "Solid", "Primordial", "Metalloid"], ["32", "Germanium", "Ge", "14", "4", "p", "Solid", "Primordial", "Metalloid"], ["62", "Samarium", "Sm", "3", "6", "f", "Solid", "Primordial", "Lanthanide"], ["70", "Ytterbium", "Yb", "3", "6", "f", "Solid", "Primordial", "Lanthanide"], ["80", "Mercury", "Hg", "12", "6", "d", "Liquid", "Primordial", "Transition metal"], ["23", "Vanadium", "V", "5", "4", "d", "Solid", "Primordial", "Transition metal"], ["58", "Cerium", "Ce", "3", "6", "f", "Solid", "Primordial", "Lanthanide"], ["118", "(Ununoctium)", "Uuo", "18", "7", "p", "", "Synthetic", ""], ["68", "Erbium", "Er", "3", "6", "f", "Solid", "Primordial", "Lanthanide"], ["97", "Berkelium", "Bk", "3", "7", "f", "Solid", "Transient", "Actinide"], ["4", "Beryllium", "Be", "2", "2", "s", "Solid", "Primordial", "Alkaline earth metal"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what element is after radium?
|
Actinium
| 128
|
Answer:
|
Table InputTable: [["Date", "Opponent", "Venue", "Result", "Attendance", "Scorers"], ["17 April 2006", "Newcastle United", "Stadium of Light", "1–4", "40,032", "Hoyte"], ["12 February 2006", "Tottenham Hotspur", "Stadium of Light", "1–1", "34,700", "Murphy"], ["26 November 2005", "Birmingham City", "Stadium of Light", "0–1", "32,442", ""], ["23 August 2005", "Manchester City", "Stadium of Light", "1–2", "33,357", "Le Tallec"], ["4 May 2006", "Fulham", "Stadium of Light", "2–1", "28,226", "Le Tallec, Brown"], ["13 August 2005", "Charlton Athletic", "Stadium of Light", "1–3", "34,446", "Gray"], ["15 October 2005", "Manchester United", "Stadium of Light", "1–3", "39,085", "Elliott"], ["30 November 2005", "Liverpool", "Stadium of Light", "0–2", "32,697", ""], ["15 January 2006", "Chelsea", "Stadium of Light", "1–2", "32,420", "Lawrence"], ["1 May 2006", "Arsenal", "Stadium of Light", "0–3", "44,003", ""], ["17 September 2005", "West Bromwich Albion", "Stadium of Light", "1–1", "31,657", "Breen"], ["25 March 2006", "Blackburn Rovers", "Stadium of Light", "0–1", "29,593", ""], ["11 March 2006", "Wigan Athletic", "Stadium of Light", "0–1", "31,194", ""], ["31 January 2006", "Middlesbrough", "Stadium of Light", "0–3", "31,675", ""], ["26 December 2005", "Bolton Wanderers", "Stadium of Light", "0–0", "32,232", ""], ["31 December 2005", "Everton", "Stadium of Light", "0–1", "30,567", ""], ["29 October 2005", "Portsmouth", "Stadium of Light", "1–4", "34,926", "Whitehead (pen)"], ["1 October 2005", "West Ham United", "Stadium of Light", "1–1", "31,212", "Miller"], ["19 November 2005", "Aston Villa", "Stadium of Light", "1–3", "39,707", "Whitehead (pen)"], ["3 March 2006", "Manchester City", "City of Manchester Stadium", "1–2", "42,200", "Kyle"], ["7 May 2006", "Aston Villa", "Villa Park", "1–2", "33,820", "D. Collins"], ["25 September 2005", "Middlesbrough", "Riverside Stadium", "2–0", "29,583", "Miller, Arca"], ["27 August 2005", "Wigan Athletic", "JJB Stadium", "0–1", "17,223", ""], ["23 October 2005", "Newcastle United", "St James' Park", "2–3", "52,302", "Lawrence, Elliott"], ["1 April 2006", "Everton", "Goodison Park", "2–2", "38,093", "Stead, Delap"], ["18 March 2006", "Bolton Wanderers", "Reebok Stadium", "0–2", "23,568", ""], ["10 September 2005", "Chelsea", "Stamford Bridge", "0–2", "41,969", ""], ["14 April 2006", "Manchester United", "Old Trafford", "0–0", "72,519", ""], ["3 December 2005", "Tottenham Hotspur", "White Hart Lane", "2–3", "36,244", "Whitehead, Le Tallec"], ["25 February 2006", "Birmingham City", "St. Andrew's", "0–1", "29,257", ""], ["20 August 2005", "Liverpool", "Anfield", "0–1", "44,913", ""], ["15 February 2006", "Blackburn Rovers", "Ewood Park", "0–2", "18,220", ""]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what was the total number of games played at stadium of light?
|
19
| 128
|
Answer:
|
Table InputTable: [["Year", "Date", "Winner", "Result", "Loser", "Location"], ["2003", "November 16", "Philadelphia Eagles", "28-10", "New York Giants", "Lincoln Financial Field"], ["2005", "December 11", "New York Giants", "26-23 (OT)", "Philadelphia Eagles", "Lincoln Financial Field"], ["2008", "November 9", "New York Giants", "36-31", "Philadelphia Eagles", "Lincoln Financial Field"], ["2004", "September 12", "Philadelphia Eagles", "31-17", "New York Giants", "Lincoln Financial Field"], ["2009", "November 1", "Philadelphia Eagles", "40-17", "New York Giants", "Lincoln Financial Field"], ["2007", "December 9", "New York Giants", "16-13", "Philadelphia Eagles", "Lincoln Financial Field"], ["2006", "September 17", "New York Giants", "30-24 (OT)", "Philadelphia Eagles", "Lincoln Financial Field"], ["2007", "January 7", "Philadelphia Eagles", "23-20", "New York Giants", "Lincoln Financial Field"], ["2001", "December 30", "Philadelphia Eagles", "24-21", "New York Giants", "Veterans Stadium"], ["2001", "October 22", "Philadelphia Eagles", "10-9", "New York Giants", "Giants Stadium"], ["2001", "January 7", "New York Giants", "20-10", "Philadelphia Eagles", "Giants Stadium"], ["2009", "December 13", "Philadelphia Eagles", "45-38", "New York Giants", "Giants Stadium"], ["2006", "December 17", "Philadelphia Eagles", "36-22", "New York Giants", "Giants Stadium"], ["2004", "November 28", "Philadelphia Eagles", "27-6", "New York Giants", "Giants Stadium"], ["2002", "December 28", "New York Giants", "10-7", "Philadelphia Eagles", "Giants Stadium"], ["2003", "October 19", "Philadelphia Eagles", "14-10", "New York Giants", "Giants Stadium"], ["2009", "January 11", "Philadelphia Eagles", "23-11", "New York Giants", "Giants Stadium"], ["2005", "November 20", "New York Giants", "27-17", "Philadelphia Eagles", "Giants Stadium"], ["2008", "December 7", "Philadelphia Eagles", "20-14", "New York Giants", "Giants Stadium"], ["2000", "September 10", "New York Giants", "33-18", "Philadelphia Eagles", "Veterans Stadium"], ["2007", "September 30", "New York Giants", "16-3", "Philadelphia Eagles", "Giants Stadium"], ["2000", "October 29", "New York Giants", "24-7", "Philadelphia Eagles", "Giants Stadium"], ["2002", "October 28", "Philadelphia Eagles", "17-3", "New York Giants", "Veterans Stadium"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what year had the highest results?
|
2009
| 128
|
Answer:
|
Table InputTable: [["Match Day", "Date", "Opponent", "H/A", "Score", "Aberdeen Scorer(s)", "Attendance"], ["5", "12 September", "Ayr United", "A", "0–1", "", "2,000"], ["24", "9 January", "Ayr United", "H", "1–1", "Cail", "4,500"], ["32", "6 March", "Partick Thistle", "H", "0–0", "", "6,000"], ["19", "12 December", "Partick Thistle", "A", "0–3", "", "6,000"], ["30", "20 February", "Hibernian", "H", "0–0", "", "8,500"], ["20", "19 December", "Kilmarnock", "H", "3–0", "MacLachlan, Cail, Main", "4,000"], ["23", "2 January", "Raith Rovers", "A", "1–5", "Cail", "6,000"], ["2", "22 August", "Rangers", "H", "0–2", "", "15,000"], ["4", "5 September", "Clyde", "H", "2–0", "MacLachlan, Archibald", "6,000"], ["18", "5 December", "Celtic", "H", "0–1", "", "7,000"], ["37", "10 April", "Celtic", "A", "0–1", "", "10,000"], ["34", "20 March", "Airdrieonians", "H", "3–0", "Brewster, Cail, Main", "5,500"], ["14", "7 November", "Raith Rovers", "H", "1–3", "Main", "6,000"], ["35", "27 March", "Rangers", "A", "1–1", "W. Wylie", "10,000"], ["13", "31 October", "Hibernian", "A", "2–1", "Chatwin, Main", "4,000"], ["10", "10 October", "Airdrieonians", "A", "0–3", "", "7,000"], ["29", "13 February", "St. Mirren", "A", "2–0", "Cail, Walker", "3,000"], ["28", "6 February", "Morton", "H", "2–0", "Brewster, Archibald", "2,000"], ["26", "23 January", "Falkirk", "H", "1–2", "Walker", "4,000"], ["31", "27 February", "Third Lanark", "A", "1–0", "Walker", "5,000"], ["7", "26 September", "Heart of Midlothian", "A", "0–2", "", "14,000"], ["16", "21 November", "Dumbarton", "H", "0–0", "", "5,000"], ["12", "24 October", "Falkirk", "A", "1–1", "J. Wyllie", "5,500"], ["1", "15 August", "Dundee", "A", "3–1", "Soye, Walker, Cail", "10,000"], ["25", "16 January", "Clyde", "A", "0–3", "", "3,000"], ["9", "3 October", "St. Mirren", "H", "0–0", "", "6,000"], ["6", "19 September", "Motherwell", "H", "3–1", "J. Wyllie, MacLachlan, Walker", "7,000"], ["36", "3 April", "Heart of Midlothian", "H", "0–0", "", "6,000"], ["22", "1 January", "Dundee", "H", "2–1", "Walker, J. Wyllie", "7,000"], ["8", "28 September", "Queen's Park", "H", "1–1", "Main", "5,000"], ["17", "28 November", "Kilmarnock", "A", "2–5", "MacLachlan, McLeod", "2,500"], ["21", "26 December", "Motherwell", "A", "1–1", "Walker", "3,000"], ["38", "17 April", "Hamilton Academical", "H", "1–0", "J. Wyllie", "4,000"], ["27", "30 January", "Dumbarton", "A", "2–3", "Cail, Walker", "3,000"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what is the total attendance of the first 10 games this season?
|
76,000
| 128
|
Answer:
|
Table InputTable: [["#", "Player", "Goals", "Caps", "Career"], ["1", "Landon Donovan", "57", "155", "2000–present"], ["8", "Eddie Johnson", "19", "62", "2004–present"], ["2", "Clint Dempsey", "36", "103", "2004–present"], ["6T", "Jozy Altidore", "21", "67", "2007–present"], ["6T", "Bruce Murray", "21", "86", "1985–1993"], ["3", "Eric Wynalda", "34", "106", "1990–2000"], ["9T", "DaMarcus Beasley", "17", "114", "2001–present"], ["4", "Brian McBride", "30", "95", "1993–2006"], ["5", "Joe-Max Moore", "24", "100", "1992–2002"], ["9T", "Earnie Stewart", "17", "101", "1990–2004"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:who is the only goalscorer to score between 18 and 20 goals?
|
Eddie Johnson
| 128
|
Answer:
|
Table InputTable: [["Player", "No.", "Nationality", "Position", "Years for Jazz", "School/Club Team"], ["Greg Foster", "44", "United States", "Center/Forward", "1995-99", "UTEP"], ["Todd Fuller", "52", "United States", "Center", "1998-99", "North Carolina State"], ["Terry Furlow", "25", "United States", "Guard/Forward", "1979-80", "Michigan State"], ["Derrick Favors", "15", "United States", "Forward", "2011-present", "Georgia Tech"], ["Kyrylo Fesenko", "44", "Ukraine", "Center", "2007-11", "Cherkasy Monkeys (Ukraine)"], ["Bernie Fryer", "25", "United States", "Guard", "1975-76", "BYU"], ["Jim Farmer", "30", "United States", "Guard", "1988-89", "Alabama"], ["Derek Fisher", "2", "United States", "Guard", "2006-2007", "Arkansas-Little Rock"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:which nationality has the most forward position players?
|
United States
| 128
|
Answer:
|
Table InputTable: [["Year", "Competition", "Venue", "Position", "Event"], ["1997", "USA Outdoor Championships", "Indianapolis, United States", "1st", "100 m hurdles"], ["2000", "Olympic Games", "Sydney, Australia", "3rd", "100 m hurdles"], ["1997", "World Indoor Championships", "Paris, France", "5th", "60 m hurdles"], ["2004", "Olympic Games", "Athens, Greece", "3rd", "100 m hurdles"], ["2002", "Grand Prix Final", "Paris, France", "7th", "100 m hurdles"], ["1998", "Grand Prix Final", "Moscow, Russia", "2nd", "100 m hurdles"], ["2000", "Grand Prix Final", "Doha, Qatar", "4th", "100 m hurdles"], ["2003", "World Athletics Final", "Monaco", "6th", "100 m hurdles"], ["1999", "World Indoor Championships", "Maebashi, Japan", "6th", "60 m hurdles"], ["2003", "World Indoor Championships", "Birmingham, England", "3rd", "60 m hurdles"], ["1998", "USA Indoor Championships", "", "1st", "60 m hurdles"], ["2002", "USA Indoor Championships", "", "1st", "60 m hurdles"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:where did the only 100 m hurdle take place in 1997?
|
Indianapolis, United States
| 128
|
Answer:
|
Table InputTable: [["No. in\\nseries", "No. in\\nseason", "Title", "Directed by", "Written by", "Original air date", "Prod.\\ncode"], ["4", "7", "\"Danny was a Million Laughs\"", "Mark Rydell", "Arthur Dales", "October 27, 1965", "107"], ["12", "11", "\"Weight of the World\"", "Paul Wendkos", "Robert Lewin", "December 1, 1965", "111"], ["1", "14", "\"Affair in T'Sien Cha\"", "Sheldon Leonard", "Morton Fine & David Friedkin", "December 29, 1965", "114"], ["8", "6", "\"The Loser\"", "Mark Rydell", "Robert Culp", "October 20, 1965", "106"], ["11", "10", "\"Tatia\"", "David Friedkin", "Robert Lewin", "November 17, 1965", "110"], ["14", "12", "\"Three Hours on a Sunday\"", "Paul Wendkos", "Morton Fine & David Friedkin", "December 8, 1965", "112"], ["7", "5", "\"Dragon's Teeth\"", "Leo Penn", "Gilbert Ralston", "October 13, 1965", "105"], ["26", "25", "\"My Mother, The Spy\"", "Richard Benedict", "Howard Gast", "March 30, 1966", "125"], ["2", "3", "\"Carry Me Back to Old Tsing-Tao\"", "Mark Rydell", "David Karp", "September 29, 1965", "103"], ["27", "26", "\"There was a Little Girl\"", "John Rich", "Teleplay by: Stephen Kandell Story by: Robert Bloch", "April 6, 1966", "126"], ["25", "24", "\"Crusade to Limbo\"", "Richard Sarafian", "Teleplay by: Morton Fine & David Freidkin & Jack Turley Story by: Jack Turley", "March 23, 1966", "124"], ["10", "8", "\"The Time of the Knife\"", "Paul Wendkos", "Gilbert Ralston", "November 3, 1965", "108"], ["3", "1", "\"So Long, Patrick Henry\"", "Leo Penn", "Robert Culp", "September 15, 1965", "101"], ["9", "9", "\"No Exchange on Damaged Merchandise\"", "Leo Penn", "Gary Marshall & Jerry Belson", "November 10, 1965", "109"], ["13", "13", "\"Tigers of Heaven\"", "Allen Reisner", "Morton Fine & David Friedkin", "December 15, 1965", "113"], ["16", "15", "\"The Tiger\"", "Paul Wendkos", "Robert Culp", "January 5, 1966", "115"], ["21", "21", "\"Return to Glory\"", "Robert Sarafian", "David Friedkin & Morton Fine", "February 23, 1966", "121"], ["28", "27", "\"It's All Done with Mirrors\"", "Robert Butler", "Stephen Kandell", "April 13, 1966", "127"], ["15", "17", "\"Always Say Goodbye\"", "Allen Reisner", "Robert C. Dennis & Earl Barrett", "January 26, 1966", "117"], ["5", "2", "\"A Cup of Kindness\"", "Leo Penn", "Morton Fine & David Friedkin", "September 22, 1965", "102"], ["23", "23", "\"A Day Called 4 Jaguar\"", "Richard Sarafian", "Michael Zagar", "March 9, 1966", "123"], ["18", "18", "\"Court of the Lion\"", "Robert Culp", "Robert Culp", "February 2, 1966", "118"], ["22", "22", "\"The Conquest of Maude Murdock\"", "Paul Wendkos", "Robert C. Dennis & Earl Barrett", "March 2, 1966", "122"], ["19", "19", "\"Turkish Delight\"", "Paul Wendkos", "Eric Bercovici", "February 9, 1966", "119"], ["20", "20", "\"Bet Me a Dollar\"", "Richard Sarafian", "David Friedkin & Morton Fine", "February 16, 1966", "120"], ["17", "16", "\"The Barter\"", "Allen Reisner", "Harvey Bullock & P.S. Allen", "January 12, 1966", "116"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many episodes aired before december 1st, 1965?
|
10
| 128
|
Answer:
|
Table InputTable: [["Date", "Location", "Opponent", "Result", "Competition"], ["September 6, 2013", "Incheon, South Korea", "South Korea", "1-4", "F"], ["March 24, 2013", "Santo Domingo, Dominican Republic", "Dominican Republic", "1–3", "F"], ["July 12, 2013", "Miami Gardens, United States", "Trinidad and Tobago", "2-0", "GC"], ["July 8, 2013", "Harrison, United States", "Honduras", "0–2", "GC"], ["July 15, 2013", "Houston, United States", "El Salvador", "0-1", "GC"], ["January 19, 2013", "Concepción, Chile", "Chile", "0–3", "F"], ["June 11, 2013", "Rio de Janeiro, Brazil", "Italy", "2–2", "F"], ["February 6, 2013", "Santa Cruz de la Sierra, Bolivia", "Bolivia", "1–2", "F"], ["June 8, 2013", "Miami, United States", "Spain", "1–2", "F"], ["March 20, 2013", "Muscat, Oman", "Oman", "0–3", "F"], ["March 5, 2014", "Mitrovica, Kosovo", "Kosovo", "0–0", "F"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what was the total number of goals scored in the game between haiti and south korea on september 6, 2013?
|
5
| 128
|
Answer:
|
Table InputTable: [["Season", "League\\nPos.", "League\\nCompetition", "League\\nTop scorer", "Danish Cup", "Europe", "Others"], ["1987-88", "1", "1988 1st Division", "Bent Christensen (21)", "Finalist", "EC3 2nd round", ""], ["1988-89", "2", "1989 1st Division", "Bent Christensen (10)", "Winner", "EC1 1st round", ""], ["1989-90", "1", "1990 1st Division", "Bent Christensen (17)", "Quarter-final", "EC1 1st round", ""], ["1990-91", "1", "1991 Superliga", "Bent Christensen (11)", "Semi-final", "EC3 semi-final", ""], ["1999-00", "2", "1999-00 Superliga", "Bent Christensen (13)", "Semi-final", "EC1 qual 3rd round\\nEC3 1st round", ""], ["1982-83", "4", "1983 1st Division", "Brian Chrøis (12)", "4th round", "", ""], ["2001-02", "1", "2001-02 Superliga", "Peter Madsen (22)", "5th round", "EC3 3rd round", ""], ["1995-96", "1", "1995-96 Superliga", "Peter Møller (15)", "Finalist", "EC3 3rd round", ""], ["2008-09", "3", "2008-09 Superliga", "Morten Rasmussen (9)\\nAlexander Farnerud (9)\\nOusman Jallow (9)", "Semi-final", "EC3 1st round", ""], ["2007-08", "8", "2007-08 Superliga", "Morten Rasmussen (7)\\nMartin Ericsson (7)", "Winner", "", ""], ["2003-04", "2", "2003-04 Superliga", "Thomas Kahlenberg (11)", "Semi-final", "EC3 3rd round", ""], ["1983-84", "4", "1984 1st Division", "Jens Kolding (11)", "3rd round", "", ""], ["2011-12", "9", "2011-12 Superliga", "Simon Makienok Christoffersen (10)", "", "", ""], ["1996-97", "1", "1996-97 Superliga", "Peter Møller (22)", "Semi-final", "EC1 qualification round\\nEC3 quarter-final", "Danish Supercup winner"], ["2010-11", "3", "2010-11 Superliga", "Michael Krohn-Dehli (11)", "", "", ""], ["2000-01", "2", "2000-01 Superliga", "Peter Graulund (21)", "Quarter-final", "EC1 qual 3rd round\\nEC3 1st round", ""], ["1981-82", "4", "1982 1st Division", "Michael Laudrup (15)", "4th round", "", ""], ["2002-03", "2", "2002-03 Superliga", "Mattias Jonson (11)", "Winner", "EC1 qual 3rd round\\nEC3 1st round", "Danish Supercup winner"], ["1991-92", "7", "1991-92 Superliga", "Kim Vilfort (9)", "4th round", "EC1 2nd round", ""], ["1997-98", "1", "1997-98 Superliga", "Ebbe Sand (28)", "Winner", "EC1 qual 2nd round\\nEC3 1st round", "Danish Supercup winner"], ["1993-94", "3", "1993-94 Superliga", "Mark Strudal (13)", "Winner", "EC3 3rd round", ""], ["2006-07", "6", "2006-07 Superliga", "Morten Rasmussen (15)", "4th round", "EC3 1st round", "Royal League winner\\nDanish League Cup winner"], ["2004-05", "1", "2004-05 Superliga", "Thomas Kahlenberg (13)", "Winner", "EC3 qual 2nd round", "Royal League group stage"], ["2009-10", "3", "2009-10 Superliga", "Morten Rasmussen (12)", "4th round", "EC3 qual play-off round", ""]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many times did brent christensen make it to europe?
|
5
| 128
|
Answer:
|
Table InputTable: [["Year", "Film", "Rotten Tomatoes", "Metacritic", "IMDb"], ["2000", "Dancer in the Dark", "68%", "61%", "8.0/10"], ["2009", "Antichrist", "48%", "49%", "6.6/10"], ["2013", "Nymphomaniac: Volume I", "77%", "63%", "7.5/10"], ["2013", "Nymphomaniac: Volume II", "79%", "76%", "7.2/10"], ["1998", "The Idiots", "70%", "47%", "6.9/10"], ["1984", "The Element of Crime", "77%", "N/A", "6.9/10"], ["1991", "Europa", "85%", "66%", "7.7/10"], ["2011", "Melancholia", "77%", "80%", "7.1/10"], ["2006", "The Boss of It All", "74%", "71%", "6.7/10"], ["2003", "Dogville", "70%", "59%", "8.0/10"], ["1996", "Breaking the Waves", "86%", "76%", "7.9/10"], ["1982", "Images of Liberation", "N/A", "N/A", "5.1/10"], ["2005", "Manderlay", "51%", "46%", "7.4/10"], ["1987", "Epidemic", "33%", "66%", "6.1/10"], ["2003", "The Five Obstructions", "88%", "79%", "7.5/10"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what is the last film that lars von trier made?
|
Nymphomaniac: Volume II
| 128
|
Answer:
|
Table InputTable: [["Rank", "Mountain Peak", "Nation", "Province", "Elevation", "Prominence", "Isolation"], ["8", "Montañas Peña Blanca High Point PB", "Guatemala", "Huehuetenango", "3518 m\\n11,542 ft", "1858 m\\n6,096 ft", "42 km\\n26 mi"], ["14", "Montaña San Ildefonso PB", "Honduras", "Cortés", "2242 m\\n7,356 ft", "1702 m\\n5,584 ft", "68 km\\n42 mi"], ["3", "Montaña de Santa Bárbara PB", "Honduras", "Santa Bárbara", "2744 m\\n9,003 ft", "2084 m\\n6,837 ft", "74 km\\n46 mi"], ["15", "Volcán San Cristóbal PB", "Nicaragua", "Chinandega", "1745 m\\n5,725 ft", "1665 m\\n5,463 ft", "134 km\\n83 mi"], ["4", "Cerro las Minas PB", "Honduras", "Lempira", "2849 m\\n9,347 ft", "2069 m\\n6,788 ft", "130 km\\n81 mi"], ["11", "Cerro Tacarcuna PB", "Panama", "Darién", "1875 m\\n6,152 ft", "1770 m\\n5,807 ft", "99 km\\n61 mi"], ["9", "Volcán Acatenango PB", "Guatemala", "Chimaltenango\\nSacatepéquez", "3975 m\\n13,041 ft", "1835 m\\n6,020 ft", "126 km\\n78 mi"], ["7", "Volcán Irazú PB", "Costa Rica", "Cartago\\nSan José", "3402 m\\n11,161 ft", "1872 m\\n6,142 ft", "48 km\\n30 mi"], ["2", "Chirripó Grande PB", "Costa Rica", "Cartago\\nLimón\\nSan José", "3819 m\\n12,530 ft", "3726 m\\n12,224 ft", "864 km\\n537 mi"], ["5", "Volcán de Agua PB", "Guatemala", "Escuintla\\nSacatepéquez", "3761 m\\n12,339 ft", "1981 m\\n6,499 ft", "16 km\\n10 mi"], ["1", "Volcán Tajumulco PB", "Guatemala", "San Marcos", "4220 m\\n13,845 ft", "3980 m\\n13,058 ft", "722 km\\n448 mi"], ["13", "Pico Bonito PB", "Honduras", "Atlántida", "2450 m\\n8,038 ft", "1710 m\\n5,610 ft", "152 km\\n95 mi"], ["12", "Volcán Atitlán PB", "Guatemala", "Sololá", "3537 m\\n11,604 ft", "1754 m\\n5,755 ft", "35 km\\n21 mi"], ["6", "Alto Cuchumatanes PB", "Guatemala", "Huehuetenango", "3837 m\\n12,589 ft", "1877 m\\n6,158 ft", "65 km\\n40 mi"], ["10", "Volcán San Miguel PB", "El Salvador", "San Miguel", "2131 m\\n6,991 ft", "1831 m\\n6,007 ft", "64 km\\n40 mi"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:which mountain peak has the most elevation in feet?
|
Volcán Tajumulco PB
| 128
|
Answer:
|
Table InputTable: [["Date", "Rnd", "Race Name", "Circuit", "City/Location", "Pole position", "Winning driver", "Winning team", "Report"], ["NC", "October 6", "Marlboro Challenge", "Nazareth Speedway", "Nazareth, Pennsylvania", "Michael Andretti", "Rick Mears", "Team Penske", "Report"], ["15", "October 7", "Bosch Spark Plug Grand Prix", "Nazareth Speedway", "Nazareth, Pennsylvania", "Bobby Rahal", "Emerson Fittipaldi", "Team Penske", "Report"], ["3", "May 27", "74th Indianapolis 500", "Indianapolis Motor Speedway", "Speedway, Indiana", "Emerson Fittipaldi", "Arie Luyendyk", "Doug Shierson Racing", "Report"], ["1", "April 8", "Autoworks 200", "Phoenix International Raceway", "Phoenix, Arizona", "Rick Mears", "Rick Mears", "Team Penske", "Report"], ["2", "April 22", "Toyota Long Beach Grand Prix", "Streets of Long Beach", "Long Beach, California", "Al Unser, Jr.", "Al Unser, Jr.", "Galles-Kraco Racing", "Report"], ["9", "July 22", "Molson Indy Toronto", "Exhibition Place", "Toronto, Ontario", "Danny Sullivan", "Al Unser, Jr.", "Galles-Kraco Racing", "Report"], ["12", "September 2", "Molson Indy Vancouver", "Streets of Vancouver", "Vancouver, British Columbia", "Michael Andretti", "Al Unser, Jr.", "Galles-Kraco Racing", "Report"], ["16", "October 21", "Champion Spark Plug 300K", "Laguna Seca Raceway", "Monterey, California", "Danny Sullivan", "Danny Sullivan", "Team Penske", "Report"], ["10", "August 5", "Marlboro 500", "Michigan International Speedway", "Brooklyn, Michigan", "Emerson Fittipaldi", "Al Unser, Jr.", "Galles-Kraco Racing", "Report"], ["11", "August 26", "Texaco/Havoline Grand Prix of Denver", "Streets of Denver", "Denver, Colorado", "Teo Fabi", "Al Unser, Jr.", "Galles-Kraco Racing", "Report"], ["14", "September 23", "Texaco/Havoline 200", "Road America", "Elkhart Lake, Wisconsin", "Danny Sullivan", "Michael Andretti", "Newman/Haas Racing", "Report"], ["5", "June 17", "Valvoline Grand Prix of Detroit", "Streets of Detroit", "Detroit, Michigan", "Michael Andretti", "Michael Andretti", "Newman/Haas Racing", "Report"], ["6", "June 24", "Budweiser/G.I.Joe's 200", "Portland International Raceway", "Portland, Oregon", "Danny Sullivan", "Michael Andretti", "Newman/Haas Racing", "Report"], ["8", "July 15", "Marlboro Grand Prix at the Meadowlands", "Meadowlands Sports Complex", "East Rutherford, New Jersey", "Michael Andretti", "Michael Andretti", "Newman/Haas Racing", "Report"], ["7", "July 8", "Budweiser Grand Prix of Cleveland", "Cleveland Burke Lakefront Airport", "Cleveland, Ohio", "Rick Mears", "Danny Sullivan", "Team Penske", "Report"], ["13", "September 16", "Red Roof Inns 200", "Mid-Ohio Sports Car Course", "Lexington, Ohio", "Michael Andretti", "Michael Andretti", "Newman/Haas Racing", "Report"], ["4", "June 3", "Miller Genuine Draft 200", "Milwaukee Mile", "West Allis, Wisconsin", "Rick Mears", "Al Unser, Jr.", "Galles-Kraco Racing", "Report"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:which team(s)did not win more than once?
|
Doug Shierson Racing
| 128
|
Answer:
|
Table InputTable: [["Episode", "Show #", "Iron Chef", "Challenger", "Challenger specialty", "Secret ingredient(s) or theme", "Winner", "Final score"], ["7", "IA0510", "Mario Batali", "Charles Clark", "New American", "Halibut", "Mario Batali", "51-50"], ["6", "IA0506", "Bobby Flay", "Kurt Boucher", "French-American", "Arctic char", "Bobby Flay", "46-39"], ["1", "IA0502", "Bobby Flay", "Ben Ford", "Regional American", "Blue foot chicken", "Bobby Flay", "44-35"], ["2", "IA0508", "Mario Batali", "Tony Liu", "Pan-European", "Opah", "Mario Batali", "55-47"], ["11", "IA0503", "Cat Cora", "Todd Richards", "Modern Southern", "Carrots", "Cat Cora", "48-46"], ["9", "IASP07", "Michael Symon", "Ricky Moore", "Contemporary American", "Traditional Thanksgiving", "Michael Symon", "51-43"], ["4", "IA0501", "Mario Batali", "Andrew Carmellini", "Urban Italian", "Parmigiano-Reggiano", "Mario Batali", "56-55"], ["8", "IA0507", "Cat Cora", "Mary Dumont", "French-American", "Milk and cream", "Cat Cora", "51-46"], ["3", "IA0509", "Cat Cora", "Alexandra Guarnaschelli", "French-American", "Farmers' Market", "Cat Cora", "45-41"], ["5", "IA0504", "Cat Cora", "Mark Tarbell", "Seasonal Organic", "Apples", "Mark Tarbell", "50-44"], ["12", "IA0505", "Masaharu Morimoto", "Fortunato Nicotra", "Seasonal Italian", "Kampachi", "Masaharu Morimoto", "59-50"], ["10", "IASP08", "Cat Cora & Paula Deen", "Tyler Florence & Robert Irvine", "Southern (Deen), Contemporary American (Florence), International (Irvine)", "Sugar", "Cat Cora & Paula Deen", "49-47"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:number of first episode in which the iron chef did not win
|
5
| 128
|
Answer:
|
Table InputTable: [["Year", "Result", "Award", "Film"], ["2008", "Nominated", "People's Choice Award Favorite Male TV Star", ""], ["2008", "Nominated", "Outstanding Lead Actor - Comedy Series", "Two and a Half Men"], ["2007", "Nominated", "People's Choice Award Favorite Male TV Star", ""], ["2008", "Nominated", "Teen Choice Awards Choice TV Actor: Comedy", "Two and a Half Men"], ["2007", "Nominated", "Teen Choice Award Choice TV Actor: Comedy", "Two and a Half Men"], ["2002", "Nominated", "Kids' Choice Awards Favorite Television Actor", "Two and a Half Men"], ["2007", "Nominated", "Emmy Award for Outstanding Lead Actor - Comedy Series", "Two and a Half Men"], ["2006", "Nominated", "Golden Globe Award for Best Actor – Television Series Musical or Comedy", "Two and a Half Men"], ["2008", "Won", "ALMA Award Outstanding Actor in a Comedy Television Series", "Two and a Half Men"], ["2006", "Nominated", "Emmy Award for Outstanding Lead Actor - Comedy Series", "Two and a Half Men"], ["2001", "Nominated", "ALMA Award Outstanding Actor in a Television Series", "Spin City"], ["2006", "Won", "Golden Icon Award Best Actor - Comedy Series", "Two and a Half Men"], ["2002", "Nominated", "ALMA Award Outstanding Actor in a Television Series", "Spin City"], ["2010", "Nominated", "SAG Award Outstanding Performance by a Male Actor in a Comedy Series", "Two and a Half Men"], ["2012", "Won", "WWE Slammy Award Top Social Media Ambassador", "WWE Raw"], ["2005", "Nominated", "Golden Globe Award for Best Actor – Television Series Musical or Comedy", "Two and a Half Men"], ["2005", "Nominated", "SAG Award Outstanding Performance by a Male Actor in a Comedy Series", "Two and a Half Men"], ["1999", "Nominated", "SAG Award Outstanding Performance by a Cast in a Theatrical Motion Picture", "Being John Malkovich"], ["2002", "Won", "Golden Globe Award Best Performance by an Actor in a Television Series - Musical or Comedy", "Spin City"], ["1989", "Won", "Bronze Wrangler Theatrical Motion Picture", "Young Guns"], ["1999", "Nominated", "Online Film Critics Society Award for Best Cast", "Being John Malkovich"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how long did charlie sheen go without a nomination after 2008?
|
2 years
| 128
|
Answer:
|
Table InputTable: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], ["2", "Austria", "4", "3", "4", "11"], ["1", "Soviet Union", "*7*", "3", "6", "16"], ["9", "Germany", "1", "0", "1", "2"], ["7", "Norway", "2", "1", "1", "4"], ["8", "Italy", "1", "2", "0", "3"], ["4", "Switzerland", "3", "2", "1", "6"], ["3", "Finland", "3", "3", "1", "7"], ["5", "Sweden", "2", "4", "4", "10"], ["6", "United States", "2", "3", "2", "7"], ["10", "Canada", "0", "1", "2", "3"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:which nation earned more medals than austria?
|
Soviet Union
| 128
|
Answer:
|
Table InputTable: [["Round", "Date", "Circuit", "Winning driver (TA2)", "Winning vehicle (TA2)", "Winning driver (TA1)", "Winning vehicle (TA1)"], ["5", "July 8", "Watkins Glen‡", "Hal Shaw, Jr.\\n Monte Shelton", "Porsche 935", "Brian Fuerstenau\\n Bob Tullius", "Jaguar XJS"], ["7", "August 19", "Mosport", "Greg Pickett", "Chevrolet Corvette", "Bob Tullius", "Jaguar XJS"], ["8", "September 4", "Road America", "Greg Pickett", "Chevrolet Corvette", "Bob Tullius", "Jaguar XJS"], ["3", "June 11", "Portland", "Tuck Thomas", "Chevrolet Monza", "Bob Matkowitch", "Chevrolet Corvette"], ["9", "October 8", "Laguna Seca", "Greg Pickett", "Chevrolet Corvette", "Bob Tullius", "Jaguar XJS"], ["1", "May 21", "Sears Point", "Greg Pickett", "Chevrolet Corvette", "Gene Bothello", "Chevrolet Corvette"], ["10", "November 5", "Mexico City", "Ludwig Heimrath", "Porsche 935", "Bob Tullius", "Jaguar XJS"], ["6", "August 13", "Brainerd", "Jerry Hansen", "Chevrolet Monza", "Bob Tullius", "Jaguar XJS"], ["2", "June 4", "Westwood", "Ludwig Heimrath", "Porsche 935", "Nick Engels", "Chevrolet Corvette"], ["4", "June 25", "Mont-Tremblant", "Monte Sheldon", "Porsche 935", "Bob Tullius", "Jaguar XJS"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:who is the only winning driver not from the us?
|
Ludwig Heimrath
| 128
|
Answer:
|
Table InputTable: [["Goal", "Date", "Venue", "Opponent", "Score", "Result", "Competition"], ["1", "2008-5-28", "Sheriff Stadium, Tiraspol, Moldova", "Moldova", "0-1", "2–2", "Friendly match"], ["6", "2012-2-29", "Tsirion Stadium, Limassol, Cyprus", "Canada", "1-1", "1-3", "Friendly match"], ["3", "2011-6-4", "Petrovsky Stadium, Saint Petersburg, Russia", "Russia", "0-1", "3–1", "Euro 2012 Q"], ["7", "2012-2-29", "Tsirion Stadium, Limassol, Cyprus", "Canada", "1-2", "1-3", "Friendly match"], ["2", "2010-10-12", "Hanrapetakan Stadium, Yerevan, Armenia", "Andorra", "4–0", "4–0", "Euro 2012 Q"], ["5", "2011-10-7", "Hanrapetakan Stadium, Yerevan, Armenia", "Macedonia", "1-0", "4-1", "Euro 2012 Q"], ["4", "2011-9-2", "Estadi Comunal d'Aixovall, Andorra la Vella, Andorra", "Andorra", "0-1", "0-3", "Euro 2012 Q"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:where did marcos pizzelli score his only international goal in 1008?
|
Sheriff Stadium, Tiraspol, Moldova
| 128
|
Answer:
|
Table InputTable: [["Year", "Organization", "Award", "Work", "Result"], ["2007", "16th Hashida Awards", "Newcomer Award", "Hana Yori Dango 2", "Won"], ["2012", "16th Nikkan Sport Grand Prix", "Best Actress", "Tokkan", "Nominated"], ["2011", "35th Fumiko Yamaji Award Film Awards", "Newcomer Actress", "Youkame no Semi", "Won"], ["2011", "TV Navi", "Best Actress", "Ohisama", "Won"], ["2011", "26th Nikkan Sport Film Awards", "Best Newcomer", "Youkame no Semi, Miracle in the Pacific", "Won"], ["2012", "Japan Film Festival Theater Staff", "Best Actress", "Youkame no Semi", "Won"], ["2012", "35th Japan Academy Awards", "Best Starring Actress", "Youkame no Semi", "Won"], ["2011", "3rd TAMA Film Award", "Best Emerging Actress", "Miracle in the Pacific", "Won"], ["2007", "10th Nikkan Sports Drama Grand Prix", "Best Actress", "Hana Yori Dango 2", "Won"], ["2010", "Nikkan Sports Grand Prix (Fall)", "Best Supporting Actress", "Veterinarian Dolittle", "Nominated"], ["2011", "70th The Television Drama Academy Awards", "Best Actress", "Ohisama", "Won"], ["2008", "Nickelodeon Kids' Choice Awards", "Best Actress", "Hana Yori Dango 2", "Won"], ["2007", "2007 MTV Student Voice Awards", "Best Actress", "Hana Yori Dango 2", "Won"], ["2005", "47th The Television Drama Academy Awards", "Best Actress", "Hana Yori Dango", "Won"], ["2007", "54th The Television Academy Drama Awards", "Best Actress", "First Kiss", "Nominated"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:in the 16th hashida awards, did inoue win best actress or the newcomer award?
|
Newcomer Award
| 128
|
Answer:
|
Table InputTable: [["Year", "State/Territory Men's Division", "State/Territory Women's Division", "Major Centres Division", "Community Division", "Women's Division"], ["2001", "Tasmania", "", "", "", ""], ["2009", "Queensland", "", "Alkupitja", "Tangentyere", "New South Wales"], ["2002", "Northern Territory", "", "Darwin", "", ""], ["2012", "New South Wales", "New South Wales", "Darwin", "Brothers in Arms", "Bush Potatoes"], ["2005", "Queensland", "", "Alice Springs", "Alkupitja", "Darwin"], ["2003", "New South Wales", "", "Darwin", "", ""], ["2006", "Queensland", "", "Alice Springs", "Melville Island", "Darwin"], ["2012", "Queensland", "New South Wales", "", "", ""], ["2004", "Queensland", "", "Alice Springs", "Normanton", "Tennant Creek"], ["2007", "New South Wales", "", "Alkupitja", "Cat Tigers", "CGA Cougars"], ["2008", "Queensland", "", "Katherine", "Cooktown", "New South Wales"], ["2010", "Western Australia", "", "", "", ""], ["2011", "New South Wales", "New South Wales", "Maranoa Murris", "Gap Angels", "Bush Potatoes"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what year was the only year tasmania won the sate/ territory men's division?
|
2001
| 128
|
Answer:
|
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