context stringlengths 362 4.81k | question stringlengths 2.11k 2.25k | answer stringlengths 1 260 | max_new_tokens int64 128 128 | answer_prefix stringclasses 1
value |
|---|---|---|---|---|
Table InputTable: [["Place", "Player", "Country", "Score", "To par"], ["T7", "K. J. Choi", "South Korea", "69-70-74=213", "+3"], ["1", "Retief Goosen", "South Africa", "68-70-69=207", "–3"], ["T7", "Lee Westwood", "England", "68-72-73=213", "+3"], ["T7", "Tiger Woods", "United States", "70-71-72=213", "+3"], ["T2", "Jason Gore", "United States", "71-67-72=210", "E"], ["T4", "Michael Campbell", "New Zealand", "71-69-71=211", "+1"], ["T7", "Peter Hedblom", "Sweden", "77-66-70=213", "+3"], ["T2", "Olin Browne", "United States", "67-71-72=210", "E"], ["T4", "Mark Hensby", "Australia", "71-68-72=211", "+1"], ["6", "David Toms", "United States", "70-72-70=212", "+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 only competitor from south korea? | K. J. Choi | 128 | Answer: |
Table InputTable: [["Representative", "Title", "Presentation\\nof Credentials", "Termination\\nof Mission", "Appointed by"], ["Jeanette W. Hyde", "Ambassador Extraordinary and Plenipotentiary", "April 4, 1995", "January 31, 1998", "Bill Clinton"], ["Earl Norfleet Phillips", "Ambassador Extraordinary and Plenipotentiary", "March 26, 2002", "June 1, 2003", "George W. Bush"], ["Mary Kramer", "Ambassador Extraordinary and Plenipotentiary", "February 5, 2004", "October 30, 2006", "George W. Bush"], ["Theodore R. Britton, Jr.", "Ambassador Extraordinary and Plenipotentiary", "February 25, 1975", "April 22, 1977", "Gerald Ford"], ["Sally Shelton-Colby", "Ambassador Extraordinary and Plenipotentiary", "July 23, 1979", "February 24, 1981", "Jimmy Carter"], ["Frank V. Ortiz, Jr.", "Ambassador Extraordinary and Plenipotentiary", "July 29, 1977", "May 15, 1979", "Jimmy Carter"], ["Mary Martin Ourisman", "Ambassador Extraordinary and Plenipotentiary", "January 18, 2007", "2008", "George W. Bush"], ["Larry Leon Palmer", "Ambassador Extraordinary and Plenipotentiary", "2012", "incumbent", "Barack Obama"], ["James A. Daley", "Ambassador Extraordinary and Plenipotentiary", "October 17, 2000", "March 1, 2001", "Bill Clinton"], ["Loren E. Lawrence", "Chargé d'Affaires ad interim", "March 1984", "December 1984", "Ronald Reagan"], ["Roy T. Haverkamp", "Chargé d'Affaires ad interim", "December 1984", "March 1986", "Ronald Reagan"], ["Annette T. Veler", "Chargé d'Affaires", "July 1991", "July 1993", "George H. W. Bush"], ["Charles A. Gillespie", "Chargé d'Affaires ad interim", "February 2, 1984", "March 1984", "Ronald Reagan"], ["E. William Crotty", "Ambassador Extraordinary and Plenipotentiary", "January 30, 1999", "October 10, 1999", "Bill Clinton"], ["John C. Leary", "Chargé d'Affaires ad interim", "March 1986", "January 9, 1987", "Ronald Reagan"], ["Dennis F. Carter", "Chargé d'Affaires", "December 1994", "March 1995", "Bill Clinton"], ["John C. Leary", "Chargé d'Affaires", "January 9, 1987", "May 1988", "Ronald Reagan"], ["James Ford Cooper", "Chargé d'Affaires", "June 1988", "January 1991", "Ronald Reagan"], ["Ollie P. Anderson, Jr.", "Chargé d'Affaires", "September 1993", "September 1994", "Bill Clinton"], ["Christopher Sandrolini", "Chargé d'Affaires ad interim", "June 19, 2011", "2012", ""], ["Brent Hardt", "Chargé d'Affaires ad interim", "January 1, 2009", "June 19, 2011", ""]] | 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 us ambassador to grenada prior to jeanette w. hyde? | Dennis F. Carter | 128 | Answer: |
Table InputTable: [["Year", "Winner", "Jockey", "Trainer", "Owner", "Distance\\n(Miles)", "Time", "Win $"], ["2009", "Miss World", "Cornelio Velasquez", "Christophe Clement", "Waratah Thoroughbreds", "1-1/8", "1:53.55", "$180,000"], ["1978", "Late Bloomer", "Jorge Velasquez", "John M. Gaver, Jr.", "Greentree Stable", "1-1/16", "1:41.60", ""], ["1993", "Sky Beauty", "Mike E. Smith", "H. Allen Jerkens", "Georgia E. Hofmann", "1", "1:35.76", "$68,400"], ["1989", "Highest Glory", "Jose A. Santos", "D. Wayne Lukas", "H. Joseph Allen", "1", "1:37.20", "$70,440"], ["1995", "Perfect Arc", "John Velazquez", "Angel Penna, Jr.", "Brazil Stables", "1-1/16", "1:42.35", "$101,070"], ["1986", "Life At The Top", "Chris McCarron", "D. Wayne Lukas", "Lloyd R. French", "1", "1:34.40", "$51,210"], ["2001", "Voodoo Dancer", "Corey Nakatani", "Christophe Clement", "Green Hills Farms", "1-1/8", "1:47.69", "$150,000"], ["1979", "Danielle B.", "Ruben Hernandez", "John O. Hertler", "Our Precious Stable", "1-1/16", "1:45.40", "$33,000"], ["1988", "Topicount", "Angel Cordero, Jr.", "H. Allen Jerkens", "Centennial Farms", "1", "1:38.00", "$82,260"], ["2011", "Winter Memories", "Javier Castellano", "James J. Toner", "Phillips Racing Partnership", "1-1/8", "1:51.06", "$150,000"], ["1999", "Perfect Sting", "Pat Day", "Joseph Orseno", "Stronach Stable", "1-1/8", "1:49.41", "$129,900"], ["2002", "Wonder Again", "Edgar Prado", "James J. Toner", "Joan G. & John W. Phillips", "1-1/8", "1:47.33", "$150,000"], ["2010", "Check the Label", "Ramon Dominguez", "H. Graham Motion", "Lael Stables", "1-1/8", "1:51.41", "$150,000"], ["1991", "Dazzle Me Jolie", "Jose A. Santos", "Willard J. Thompson", "Jolie Stanzione", "1", "1:35.61", "$72,000"], ["1997", "Auntie Mame", "Jerry D. Bailey", "Angel Penna, Jr.", "Lazy F Ranch", "1-1/8", "1:48.49", "$128,040"], ["2003", "Indy Five Hundred", "Pat Day", "Robert Barbara", "Georgica Stable", "1-1/8", "1:48.44", "$150,000"], ["2006", "Magnificent Song", "Garrett Gomez", "Todd A. Pletcher", "Parrish,Malcolm,Edward", "1-1/8", "1:48.48", "$150,000"], ["2005", "Luas Line", "John Velazquez", "David Wachman", "Evelyn M. Stockwell", "1-1/8", "1:45.62", "$180,000"], ["1981", "Banner Gala", "Angel Cordero, Jr.", "Angel Penna, Sr.", "Ogden Phipps", "1", "1:35.60", "$33,900"], ["1983", "Pretty Sensible", "Alfredo Smith, Jr.", "George Travers", "John Zervas", "1", "1:37.80", "$33,600"], ["1980", "Mitey Lively", "Jorge Velasquez", "Douglas R. Peterson", "Tayhill Stable", "1", "1:36.40", "$33,480"], ["1992", "November Snow", "Chris Antley", "H. Allen Jerkens", "Earle I. Mack", "1", "1:35.91", "$66,480"]] | 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 won after miss world did? | Check the Label | 128 | Answer: |
Table InputTable: [["Date", "Team", "Competition", "Round", "Leg", "Opponent", "Location", "Score"], ["October 25", "Anderlecht", "UEFA Cup", "Group Stage", "Match 1, Home", "Hapoel Tel Aviv", "Constant Vanden Stock Stadium, Anderlecht", "2-0"], ["August 15", "Anderlecht", "Champions League", "Qual. Round 3", "Leg 1, Away", "Fenerbahçe", "Şükrü Saracoğlu Stadium, Istanbul", "0-1"], ["August 8", "Genk", "Champions League", "Qual. Round 2", "Leg 2, Away", "Sarajevo", "Asim Ferhatović Hase Stadium, Sarajevo", "1-0"], ["December 19", "Anderlecht", "UEFA Cup", "Group Stage", "Match 4, Away", "Getafe", "Coliseum Alfonso Pérez, Getafe", "1-2"], ["August 30", "Standard Liège", "UEFA Cup", "Qual. Round 2", "Leg 2, Home", "Käerjeng", "Stade Maurice Dufrasne, Liège", "1-0"], ["August 16", "Standard Liège", "UEFA Cup", "Qual. Round 2", "Leg 1, Away", "Käerjeng", "Stade Josy Barthel, Luxembourg", "3-0"], ["August 29", "Anderlecht", "Champions League", "Qual. Round 3", "Leg 2, Home", "Fenerbahçe", "Constant Vanden Stock Stadium, Anderlecht", "0-2"], ["March 12", "Anderlecht", "UEFA Cup", "Round of 16", "Leg 2, Away", "Bayern Munich", "Allianz Arena, Munich", "2-1"], ["September 20", "Club Brugge", "UEFA Cup", "Round 1", "Leg 1, Away", "Brann", "Brann Stadion, Bergen", "1-0"], ["December 6", "Anderlecht", "UEFA Cup", "Group Stage", "Match 3, Home", "Tottenham Hotspur", "Constant Vanden Stock Stadium, Anderlecht", "1-1"], ["October 4", "Anderlecht", "UEFA Cup", "Round 1", "Leg 2, Away", "Rapid Wien", "Gerhard Hanappi Stadium, Vienna", "1-0"], ["July 31", "Genk", "Champions League", "Qual. Round 2", "Leg 1, Home", "Sarajevo", "Cristal Arena, Genk", "1-2"], ["February 21", "Anderlecht", "UEFA Cup", "Round of 32", "Leg 2, Away", "Bordeaux", "Stade Chaban-Delmas, Bordeaux", "1-1"], ["March 6", "Anderlecht", "UEFA Cup", "Round of 16", "Leg 1, Home", "Bayern Munich", "Constant Vanden Stock Stadium, Anderlecht", "0-5"], ["September 20", "Anderlecht", "UEFA Cup", "Round 1", "Leg 1, Home", "Rapid Wien", "Constant Vanden Stock Stadium, Anderlecht", "1-1"], ["September 20", "Standard Liège", "UEFA Cup", "Round 1", "Leg 1, Away", "Zenit St. Petersburg", "Petrovsky Stadium, Saint Petersburg", "0-3"], ["February 13", "Anderlecht", "UEFA Cup", "Round of 32", "Leg 1, Home", "Bordeaux", "Constant Vanden Stock Stadium, Anderlecht", "2-1"], ["November 8", "Anderlecht", "UEFA Cup", "Group Stage", "Match 2, Away", "Aalborg", "Energi Nord Arena, Aalborg", "1-1"], ["October 4", "Standard Liège", "UEFA Cup", "Round 1", "Leg 2, Home", "Zenit St. Petersburg", "Stade Maurice Dufrasne, Liège", "1-1"], ["July 14", "Gent", "Intertoto Cup", "Round 2", "Leg 2, Away", "Cliftonville", "Windsor Park, Belfast", "4-0"]] | 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:who was the only team to play hapoel tel aviv? | Anderlecht | 128 | Answer: |
Table InputTable: [["Rank", "Pair", "Country", "Athletes", "Time", "Deficit"], ["", "3", "Netherlands", "Sven Kramer\\nKoen Verweij\\nJan Blokhuijsen", "3:41.43", ""], ["6", "3", "Germany", "Patrick Beckert\\nMarco Weber\\nRobert Lehmann", "3:46.48", "+5.05"], ["8", "2", "Poland", "Zbigniew Bródka\\nKonrad Niedźwiedzki\\nJan Szymański", "3:47.72", "+6.29"], ["", "2", "Russia", "Ivan Skobrev\\nDenis Yuskov\\nYevgeny Lalenkov", "3:43.62", "+2.19"], ["7", "4", "South Korea", "Lee Seung-hoon\\nJoo Hyong-jun\\nKo Byung-wook", "3:47.18", "+5.75"], ["5", "1", "Norway", "Sverre Lunde Pedersen\\nHåvard Bøkko\\nKristian Reistad Fredriksen", "3:46.33", "+4.90"], ["4", "1", "Canada", "Denny Morrison\\nMathieu Giroux\\nLucas Makowsky", "3:44.38", "+2.95"], ["", "4", "United States", "Shani Davis\\nBrian Hansen\\nJonathan Kuck", "3:43.42", "+1.99"]] | 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 country is previous in rank to germany? | Norway | 128 | Answer: |
Table InputTable: [["Round", "Date", "Circuit", "Winning driver (TA2)", "Winning vehicle (TA2)", "Winning driver (TA1)", "Winning vehicle (TA1)"], ["1", "May 21", "Sears Point", "Greg Pickett", "Chevrolet Corvette", "Gene Bothello", "Chevrolet Corvette"], ["8", "September 4", "Road America", "Greg Pickett", "Chevrolet Corvette", "Bob Tullius", "Jaguar XJS"], ["7", "August 19", "Mosport", "Greg Pickett", "Chevrolet Corvette", "Bob Tullius", "Jaguar XJS"], ["9", "October 8", "Laguna Seca", "Greg Pickett", "Chevrolet Corvette", "Bob Tullius", "Jaguar XJS"], ["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"], ["2", "June 4", "Westwood", "Ludwig Heimrath", "Porsche 935", "Nick Engels", "Chevrolet Corvette"], ["6", "August 13", "Brainerd", "Jerry Hansen", "Chevrolet Monza", "Bob Tullius", "Jaguar XJS"], ["4", "June 25", "Mont-Tremblant", "Monte Sheldon", "Porsche 935", "Bob Tullius", "Jaguar XJS"], ["10", "November 5", "Mexico City", "Ludwig Heimrath", "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:did greg pickett drve the same vehicle as gene bothello? | yes | 128 | Answer: |
Table InputTable: [["Ship", "Type of Vessel", "Lake", "Location", "Lives lost"], ["Leafield", "Steamer", "Lake Superior", "", "all hands"], ["Henry B. Smith", "Steamer", "Lake Superior", "", "all hands"], ["Plymouth", "Barge", "Lake Michigan", "", "7 lost"], ["Lightship No. 82", "Lightship", "Lake Erie", "Point Albino (near Buffalo)", "6 lost"], ["Charles S. Price", "Steamer", "Lake Huron", "near Port Huron, Michigan", "28 lost"], ["Hydrus", "Steamer", "Lake Huron", "near Lexington, Michigan", "28 lost"], ["Argus", "Steamer", "Lake Huron", "25 miles off Kincardine, Ontario", "25 lost"], ["Regina", "Steamer", "Lake Huron", "near Harbor Beach, Michigan", ""], ["Issac M. Scott", "Steamer", "Lake Huron", "near Port Elgin, Ontario", "28 lost"], ["John A. McGean", "Steamer", "Lake Huron", "near Goderich, Ontario", "28 lost"], ["Wexford", "Steamer", "Lake Huron", "north of Grand Bend, Ontario", "all hands"], ["James Carruthers", "Steamer", "Lake Huron", "near Kincardine", "18 lost"]] | 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 type of vessel listed? | Lightship | 128 | Answer: |
Table InputTable: [["#", "Title", "Time", "Lyrics", "Music", "Producer(s)", "Performer(s)"], ["4", "\"It Ain't A Thang\"", "3:45", "Boondox", "Mike E. Clark", "Boondox", "Boondox"], ["2", "\"Seven\"", "3:30", "Boondox", "Mike E. Clark", "Boondox", "Boondox"], ["8", "\"Rollin Hard\"", "4:07", "Boondox", "Mike E. Clark", "Boondox", "Boondox"], ["3", "\"Out Here\"", "3:18", "Boondox", "Mike E. Clark\\nTino Grosse", "Boondox", "Boondox"], ["12", "\"Red Mist\"", "3:54", "Boondox", "Mike E. Clark", "Boondox", "Boondox\\nBlaze Ya Dead Homie\\nTwiztid"], ["9", "\"The Harvest\"", "3:53", "Boondox\\nAMB", "Kuma", "Boondox\\nAMB", "Boondox\\nAxe Murder Boyz"], ["13", "\"Angel Like\"", "3:42", "Boondox", "Mike E. Clark", "Boondox", "Boondox"], ["10", "\"Sippin\"", "3:16", "Boondox", "Mike E. Clark", "Boondox", "Boondox"], ["6", "\"Lady In The Jaguar\"", "3:55", "Boondox\\nICP", "Mike E. Clark", "Boondox\\nICP", "Boondox\\nICP"], ["7", "\"They Pray with Snakes\"", "3:56", "Boondox", "Kuma", "Boondox", "Boondox"], ["11", "\"Lake of Fire\"", "4:12", "Boondox", "Mike E. Clark", "Boondox", "Boondox"], ["5", "\"Digging\"", "3:04", "Boondox", "Kuma", "Boondox", "Boondox"], ["1", "\"Intro\"", "1:16", "", "", "", ""]] | 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 only track shorter than 2:00? | Intro | 128 | Answer: |
Table InputTable: [["State\\n(linked to\\nsummaries below)", "Incumbent\\nSenator", "Incumbent\\nParty", "Incumbent\\nElectoral\\nhistory", "Most recent election results", "2018 intent", "Candidates"], ["State\\n(linked to\\nsummaries below)", "Incumbent", "Incumbent", "Incumbent", "Most recent election results", "2018 intent", "Candidates"], ["Maine", "Angus King", "Independent", "Angus King (I) 52.9%\\nCharles E. Summers, Jr. (R) 30.7%\\nCynthia Dill (D) 13.3%", "2012", "[Data unknown/missing. You can help!]", "[Data unknown/missing. You can help!]"], ["Vermont", "Bernie Sanders", "Independent", "Bernie Sanders (I) 71%\\nJohn MacGovern (R) 24.9%\\nCris Ericson (Marijuana Party) 2%", "2006\\n2012", "[Data unknown/missing. You can help!]", "[Data unknown/missing. You can help!]"], ["Virginia", "Tim Kaine", "Democratic", "Tim Kaine (D) 52.9%\\nGeorge Allen (R) 47%", "2012", "[Data unknown/missing. You can help!]", "[Data unknown/missing. You can help!]"], ["State\\n(linked to\\nsummaries below)", "Senator", "Party", "Electoral\\nhistory", "Most recent election results", "2018 intent", "Candidates"], ["New Mexico", "Martin Heinrich", "Democratic", "Martin Heinrich (D) 51.0%\\nHeather Wilson (R) 45.3%\\nJon Barrie (IAP) 3.6%", "2012", "[Data unknown/missing. You can help!]", "[Data unknown/missing. You can help!]"], ["Indiana", "Joe Donnelly", "Democratic", "Joe Donnelly (D) 50.0%\\nRichard Mourdock (R) 44.2%\\nAndrew Horning (L) 5.7%", "2012", "[Data unknown/missing. You can help!]", "[Data unknown/missing. You can help!]"], ["Massachusetts", "Elizabeth Warren", "Democratic", "Elizabeth Warren (D) 53.7%\\nScott Brown (R) 46.3%", "2012", "[Data unknown/missing. You can help!]", "[Data unknown/missing. You can help!]"], ["Washington", "Maria Cantwell", "Democratic", "Maria Cantwell (D) 60.5%\\nMichael Baumgartner (R) 39.5%", "2000\\n2006\\n2012", "[Data unknown/missing. You can help!]", "[Data unknown/missing. You can help!]"], ["California", "Dianne Feinstein", "Democratic", "Dianne Feinstein (D) 62.5%\\nElizabeth Emken (R) 37.5%", "1992 (special)\\n1994\\n2000\\n2006\\n2012", "Running", "[Data unknown/missing. You can help!]"], ["New York", "Kirsten Gillibrand", "Democratic", "Kirsten Gillibrand (D) 71.6%\\nWendy E. Long (R) 26.0%", "2010 (special)\\n2012", "[Data unknown/missing. You can help!]", "[Data unknown/missing. You can help!]"], ["Missouri", "Claire McCaskill", "Democratic", "Claire McCaskill (D) 54.8%\\nTodd Akin (R) 39.0%\\nJonathan Dine (L) 6.1%", "2006\\n2012", "[Data unknown/missing. You can help!]", "[Data unknown/missing. You can help!]"], ["Utah", "Orrin Hatch", "Republican", "Orrin Hatch (R) 65.3%\\nScott Howell (D) 30.0%\\nShaun McCausland (C) 3.2%", "1976\\n1982\\n1988\\n1994\\n2000\\n2006\\n2012", "Retiring", "[Data unknown/missing. You can help!]"], ["Florida", "Bill Nelson", "Democratic", "Bill Nelson (D) 55.2%\\nConnie Mack IV (R) 42.2%", "2000\\n2006\\n2012", "[Data unknown/missing. You can help!]", "[Data unknown/missing. You can help!]"]] | 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 independent incumbents are on the list? | 2 | 128 | Answer: |
Table InputTable: [["Client", "Years of Operation", "Area of Operation", "Country", "Services"], ["IPC-Dublin", "1997-97", "Kilwa", "Tanzania", "Drilling"], ["Fina", "1997", "El Hamada", "Libya", "Drilling, workover"], ["IPLL", "1999-current", "El Naka field", "Libya", "Drilling"], ["Waha", "1994", "El Zahra", "Libya", "Drilling, workover"], ["Khalda/Repsol", "1998-99", "West Desert", "Egypt", "Drilling"], ["Marathon", "1998", "Manzala field", "Egypt", "Drilling"], ["Zueitina", "2001-current", "Field 103", "Libya", "Drilling, workover"], ["Perenco Oil Co.", "2000-01", "EchiraX Concession", "Gabon", "Drilling"], ["Veba", "2000", "Different fields", "Libya", "Drilling, workover"], ["Lasmo", "1993-94", "Wadi Borjuj", "Libya", "Drilling, workover"], ["Agoco", "1991-current", "Sarir field", "Libya", "Drilling, workover"], ["Total", "1999-current", "El Mabrouk", "Libya", "Drilling"], ["Agiba-Agip", "1999", "West Desert", "Egypt", "Drilling"], ["OMV", "1997", "Field 103", "Libya", "Drilling, workover"], ["SOC", "2000-current", "SOC fields", "Libya", "Drilling"]] | 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:fina's drilling was not in kilwa but what other area of operation? | El Hamada | 128 | Answer: |
Table InputTable: [["Name", "Nation", "Position", "League Apps", "League Goals", "FA Cup Apps", "FA Cup Goals", "Total Apps", "Total Goals"], ["Ian Duthie", "Scotland", "MF", "1", "0", "0", "0", "1", "0"], ["Henry Stewart", "England", "DF", "15", "0", "0", "0", "15", "0"], ["Bill Hayes", "Republic of Ireland", "DF", "17", "0", "1", "0", "18", "0"], ["Harold Hassall", "England", "FW", "10", "4", "1", "0", "11", "4"], ["George Hepplewhite", "England", "DF", "36", "0", "1", "0", "37", "0"], ["Harry Mills", "England", "GK", "34", "0", "1", "0", "35", "0"], ["Bill Whittaker", "England", "DF", "16", "0", "0", "0", "16", "0"], ["Charlie Gallogly", "Northern Ireland", "DF", "15", "0", "0", "0", "15", "0"], ["Jimmy Glazzard", "England", "FW", "21", "5", "1", "0", "22", "5"], ["John Battye", "England", "DF", "22", "0", "0", "0", "22", "0"], ["Jack Howe", "England", "DF", "20", "1", "1", "0", "21", "1"], ["Vic Metcalfe", "England", "MF", "41", "11", "1", "0", "42", "11"], ["George Howe", "England", "DF", "5", "0", "0", "0", "5", "0"], ["Conway Smith", "England", "MF", "10", "0", "0", "0", "10", "0"], ["Eddie Boot", "England", "DF", "38", "0", "1", "0", "39", "0"], ["Donald Hunter", "England", "DF", "7", "0", "0", "0", "7", "0"], ["Johnny McKenna", "Northern Ireland", "MF", "40", "3", "1", "0", "41", "3"], ["Don McEvoy", "England", "DF", "5", "2", "0", "0", "5", "2"], ["Arnold Rodgers", "England", "FW", "4", "2", "0", "0", "4", "2"], ["Tom Briggs", "England", "DF", "4", "0", "0", "0", "4", "0"], ["Harry Yates", "England", "MF", "1", "0", "0", "0", "1", "0"], ["Jack Wheeler", "England", "GK", "2", "0", "0", "0", "2", "0"], ["Jack Percival", "England", "DF", "7", "0", "0", "0", "7", "0"], ["Bob Hesford", "England", "GK", "6", "0", "0", "0", "6", "0"], ["Albert Nightingale", "England", "MF", "39", "7", "1", "0", "40", "7"], ["Ronnie Burke", "England", "FW", "12", "5", "0", "0", "12", "5"], ["Jeff Taylor", "England", "FW", "21", "11", "0", "0", "21", "11"], ["Joe Lynn", "England", "MF", "5", "0", "0", "0", "5", "0"], ["Lol Morgan", "England", "DF", "6", "0", "0", "0", "6", "0"], ["Ray Taylor", "England", "MF", "2", "0", "0", "0", "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:what was the total number of representatives from scotland? | 1 | 128 | Answer: |
Table InputTable: [["Year", "Title", "Genre", "Publisher", "Notes"], ["1911", "The Young Pitcher", "Baseball", "Harper & Brothers", ""], ["1920", "The Redheaded Outfield and other Baseball Stories", "Baseball", "Harper & Brothers", ""], ["1909", "The ShortStop", "Baseball", "A. C. McClurg", ""], ["1951", "The Dude Ranger", "Western", "Harper & Brothers", ""], ["1952", "Adventures in Fishing", "Fishing", "Harper & Brothers", ""], ["1915", "The Lone Star Ranger", "Western", "Harper & Brothers", ""], ["1949", "The Deer Stalker", "Western", "Harper & Brothers", ""], ["1939", "Knights of the Range", "Western", "Harper & Brothers", ""], ["1935", "Thunder Mountain", "Western", "Harper & Brothers", ""], ["1920", "The Man of the Forest", "Western", "Grosset & Dunlap", ""], ["1957", "The Fugitive Trail", "Western", "Harper & Brothers", ""], ["1959", "Horse Heaven Hill", "Western", "Harper & Brothers", ""], ["1956", "Stranger from the Tonto", "Western", "Harper & Brothers", ""], ["1926", "Under the Tonto Rim", "Western", "Harper & Brothers", ""], ["1940", "Thirty thousand on the Hoof", "Western", "Harper & Brothers", ""], ["1912", "Ken Ward in the Jungle", "Western", "Harper & Brothers", ""], ["1953", "Wyoming", "Western", "Harper & Brothers", ""], ["1960", "The Ranger and other Stories", "Western", "Harper & Row", ""], ["1932", "Arizona Ames", "Western", "Harper & Brothers", ""], ["1936", "The Lost Wagon Train", "Western", "Harper & Brothers", ""], ["1914", "The Light of Western Stars", "Western", "Harper & Brothers", ""], ["1952", "Captives of the Desert", "Western", "Harper & Brothers", ""], ["1948", "Rogue River Feud", "Western", "Harper & Brothers", ""], ["1933", "The Drift Fence", "Western", "Harper & Brothers", ""], ["1910", "The Young Forester", "Western", "Harper & Brothers", ""], ["1958", "Arizona Clan", "Western", "Harper & Brothers", ""], ["1955", "Black Mesa", "Western", "Harper & Brothers", ""], ["1947", "Valley of Wild Horses", "Western", "Harper & Brothers", ""], ["1924", "Roping Lions in the Grand Canyon", "Adventure", "Harper & Brothers", ""], ["1932", "Robbers' Roost", "Western", "Harper & Brothers", ""], ["1946", "Shadow on the Trail", "Western", "Harper & Brothers", ""], ["1921", "To the Last Man", "Western", "Harper & Brothers", ""], ["1954", "Lost Pueblo", "Western", "Harper & Brothers", ""], ["1919", "Tales of Fishes", "Fishing", "Harper & Brothers", ""], ["1925", "The Thundering Herd", "Western", "Harper & Brothers", ""], ["1950", "The Maverick Queen", "Western", "Harper & Brothers", ""], ["1930", "The Shepherd of Guadaloupe", "Western", "Harper & Brothers", ""], ["1924", "The Call of the Canyon", "Western", "Harper & Brothers", ""], ["1911", "The Young Lion Hunter", "Western", "Harper & Brothers", ""], ["1979", "The Camp Robber and other Stories", "Western", "Walter J. Black", ""], ["1924", "Tales of Southern Rivers", "Fishing", "Harper & Brothers", ""], ["1942", "Majesty’s Rancho", "Western", "Harper & Brothers", "Sequel to Light of Western Stars"], ["1943", "Omnibus", "Western", "Harper & Brothers", ""], ["1930", "The Wolf Tracker", "Western", "Harper & Brothers", ""], ["1925", "The Vanishing American", "Western", "Harper & Brothers", ""], ["1996", "Last of the Duanes", "Western", "Gunsmoke Westerns", "Unabridged version of The Lone Star Ranger (1915)"]] | 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 baseball films did he appear in? | 3 | 128 | Answer: |
Table InputTable: [["Date", "Location", "Opponent", "Result", "Competition"], ["January 19, 2013", "Concepción, Chile", "Chile", "0–3", "F"], ["July 12, 2013", "Miami Gardens, United States", "Trinidad and Tobago", "2-0", "GC"], ["July 8, 2013", "Harrison, United States", "Honduras", "0–2", "GC"], ["March 24, 2013", "Santo Domingo, Dominican Republic", "Dominican Republic", "1–3", "F"], ["July 15, 2013", "Houston, United States", "El Salvador", "0-1", "GC"], ["June 11, 2013", "Rio de Janeiro, Brazil", "Italy", "2–2", "F"], ["March 20, 2013", "Muscat, Oman", "Oman", "0–3", "F"], ["June 8, 2013", "Miami, United States", "Spain", "1–2", "F"], ["February 6, 2013", "Santa Cruz de la Sierra, Bolivia", "Bolivia", "1–2", "F"], ["March 5, 2014", "Mitrovica, Kosovo", "Kosovo", "0–0", "F"], ["September 6, 2013", "Incheon, South Korea", "South Korea", "1-4", "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:did chile beat haiti by more or less than the margin by which haiti beat trinidad and tobago? | more | 128 | Answer: |
Table InputTable: [["Year", "Recipient", "Nationality", "Profession", "Speech"], ["2008", "David Be'eri, Mordechai Eliav, Rabbi Yehuda Maly", "Israel", "", ""], ["1997", "Elie Wiesel", "United States", "Professional writer\\nWinner of the Nobel Peace Prize (1986)", ""], ["2009", "Caroline Glick", "Israel", "Journalist", ""], ["2000", "Sir Martin Gilbert", "United Kingdom", "Historian and writer", ""], ["2005", "William Safire", "United States", "Author, journalist and speechwriter\\n1978 Pulitzer Prize winner", ""], ["2007", "Norman Podhoretz", "United States", "Author, columnist", ""], ["2006", "Daniel Pipes", "United States", "Author and historian", ""], ["1998", "Herman Wouk", "United States", "Professional writer and 1952 Pulitzer Prize winner", ""], ["2010", "Malcolm Hoenlein", "United States", "Executive Vice Chairman of the Conference of Presidents of Major American Jewish Organizations", ""], ["2004", "Arthur Cohn", "Switzerland", "Filmmaker and writer", ""], ["1999", "A.M. Rosenthal", "United States", "Former New York Times editor\\nFormer New York Daily News columnist", ""], ["2001", "Cynthia Ozick", "United States", "Professional writer", ""], ["2003", "Ruth Roskies Wisse", "United States", "Yiddish professor of Harvard University", "[2]"], ["2002", "Charles Krauthammer", "United States", "The Washington Post columnist", "[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:who was the first to receive the guardian of zion award? | Elie Wiesel | 128 | Answer: |
Table InputTable: [["Match no.", "Match Type", "Team Europe", "Score", "Team USA", "Progressive Total"], ["30", "Baker", "Team Europe", "202 - 203", "Team USA", "15 - 15"], ["31", "Singles", "Tore Torgersen", "202 - 264", "Chris Barnes", "15 - 16"], ["25", "Singles", "Mika Koivuniemi", "217 - 279", "Chris Barnes", "14 - 11"], ["28", "Singles", "Tore Torgersen", "206 - 275", "Doug Kent", "15 - 13"], ["32", "Singles", "Osku Palermaa", "196 - 235", "Tommy Jones", "15 - 17"], ["26", "Singles", "Osku Palermaa", "217 - 244", "Tommy Jones", "14 - 12"], ["29", "Singles", "Tomas Leandersson", "176 - 258", "Bill Hoffman", "15 - 14"], ["27", "Singles", "Paul Moor", "210 - 199", "Tim Mack", "15 - 12"]] | 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 did team europe win? | 1 | 128 | Answer: |
Table InputTable: [["Contestant", "Original\\nTribe", "First\\nSwitch", "Second\\nSwitch", "Merged\\nTribe", "Finish", "Ghost\\nIsland", "Total\\nVotes"], ["Aleksandar Krajišnik\\n19, Majur, near Šabac", "Ga 'dang", "Ga 'dang", "Ga 'dang", "Diwata", "Sole Survivor", "Locator of\\nHidden Immunity Idol\\n(Failed)\\nDay 43", "0"], ["Nikola Kovačević\\n24, Kragujevac", "Ga 'dang", "", "", "Diwata", "11th Voted Out\\n2nd Jury Member\\nDay 38", "Ghost Island Winner\\nDay 32", "12"], ["Dušan Milisavljević\\n25, Zvečan", "Manobo", "Manobo", "Manobo", "Diwata", "Eliminated in Challenge\\n8th Jury Member\\nDay 53", "Locator of\\nHidden Immunity Idol\\n(Failed)\\nDay 37", "2"], ["Njegoš Arnautović\\n21, Bijeljina, Republika Srpska", "Manobo", "Ga 'dang", "Ga 'dang", "Diwata", "Eliminated in Challenge\\n7th Jury Member\\nDay 53", "Locator of\\nHidden Immunity Idol\\n(Successful)\\nDay 40", "1"], ["Milena Vitanović\\n21, Paraćin", "Ga 'dang", "", "", "", "4th Voted Out\\nDay 13", "4th Eliminated\\nDay 18", "8"], ["Branka Čudanov\\n28, Kikinda", "Ga 'dang", "", "", "", "2nd Voted Out\\nDay 7", "1st Eliminated\\nDay 9", "10"], ["Vesna Đolović\\n38, Beograd", "Manobo", "Manobo", "Manobo", "Diwata", "2nd Runner-Up", "Locator of\\nHidden Immunity Idol\\n(Failed)\\nDay 46", "8"], ["Gordana Berger\\n38, Belgrade", "Manobo", "", "", "", "1st Voted Out\\nDay 4", "2nd Eliminated\\nDay 12", "9"], ["Nikola Kovačević\\nReturned to game from Ghost Island", "Ga 'dang", "", "", "", "5th Voted Out\\nDay 16", "Ghost Island Winner\\nDay 32", "6"], ["Aleksandar Bošković\\n28, Belgrade", "Manobo", "Manobo", "", "", "7th Voted Out\\nDay 25", "8th Eliminated\\nDay 27", "4"], ["Pece Kotevski\\n42, Bitola, Macedonia", "Ga 'dang", "Manobo", "", "", "6th Voted Out\\nDay 19", "6th Eliminated\\nDay 21", "7"], ["Branislava Bogdanović\\n27, Kačarevo", "Manobo", "", "", "", "Eliminated in a twist\\nDay 17", "5th Eliminated\\nDay 18", "2"], ["Luka Rajačić\\n21, Belgrade", "Ga 'dang", "Manobo", "Manobo", "", "9th Voted Out\\nDay 31", "10th Eliminated\\nDay 32", "6"], ["Ana Mitrić\\n23, Belgrade", "Ga 'dang", "", "", "", "3rd Voted Out\\nDay 10", "3rd Eliminated\\nDay 15", "7"], ["Srđan Dinčić\\n25, Sremska Mitrovica", "Manobo", "Manobo", "Manobo", "Diwata", "15th Voted Out\\n6th Jury Member\\nDay 50", "", "7"], ["Srđan Dinčić\\n25, Sremska Mitrovica", "Manobo", "Manobo", "Ga 'dang", "Diwata", "15th Voted Out\\n6th Jury Member\\nDay 50", "", "7"], ["Ana Stojanovska\\n21, Skopje, Macedonia", "Manobo", "Manobo", "Manobo", "", "8th Voted Out\\nDay 28", "9th Eliminated\\nDay 30", "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 only sole survivor? | Aleksandar Krajišnik | 128 | Answer: |
Table InputTable: [["Value", "Diameter", "Composition", "1975–1979\\nObverse", "1975–1979\\nReverse", "1981-\\nObverse", "1981-\\nReverse"], ["10 seniti", "24 mm", "Cupronickel", "King", "Grazing cattle", "King", "Bananas on tree"], ["2 seniti", "21 mm", "Bronze", "Marrows", "PLANNED FAMILIES FOOD FOR ALL, six people holding hands", "Taro", "PLANNED FAMILIES FOOD FOR ALL, six people holding hands"], ["1 seniti", "18 mm", "Bronze", "Maize", "Pig", "Maize", "Vanilla"], ["20 seniti", "29 mm", "Cupronickel", "King", "Bees and hive", "King", "Yams"], ["50 seniti", "32–33 mm", "Cupronickel", "King", "Fishes around a vortex", "King", "Tomatoes"], ["5 seniti", "19 mm", "Cupronickel", "Chicken with chicks", "Bananas", "Chicken with chicks", "Coconuts"]] | 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 coins are valued at more than 10 seniti? | 2 | 128 | Answer: |
Table InputTable: [["Season", "Tier", "Division", "Place"], ["1988/89", "4", "3ª", "3rd"], ["1993/94", "3", "2ªB", "15th"], ["1991/92", "3", "2ªB", "12th"], ["1992/93", "3", "2ªB", "4th"], ["1994/95", "3", "2ªB", "9th"], ["1995/96", "3", "2ªB", "19th"], ["1996/97", "4", "3ª", "2nd"], ["1989/90", "4", "3ª", "1st"], ["1990/91", "3", "2ªB", "6th"], ["1997/98", "4", "3ª", "1st"], ["1998/99", "4", "3ª", "6th"]] | 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 did tier 3 play? | 6 | 128 | Answer: |
Table InputTable: [["Position", "Driver", "No.", "Car", "Entrant", "Lak.", "Ora.", "San.", "Phi.", "Total"], ["9", "Ivan Mikac", "42", "Mazda RX-7", "Ivan Mikac", "-", "-", "25", "26", "51"], ["22", "Shane Eklund", "", "", "", "10", "-", "-", "-", "10"], ["", "Paul Barrett", "", "", "", "-", "-", "-", "12", "12"], ["1", "John Briggs", "9", "Honda Prelude Chevrolet", "John Briggs", "42", "42", "42", "42", "168"], ["19", "Chris Donnelly", "", "", "", "12", "-", "-", "-", "12"], ["17", "Phil Crompton", "49", "Ford EA Falcon", "Phil Crompton", "17", "-", "-", "-", "17"], ["15", "Gary Rowe", "47", "Nissan Stanza", "Gary Rowe", "-", "-", "21", "-", "21"], ["", "Domenic Beninca", "", "", "", "-", "-", "-", "21", "21"], ["10", "Des Wall", "", "Toyota Supra", "", "15", "32", "-", "-", "47"], ["18", "Allan McCarthy", "", "Alfa Romeo Alfetta", "", "14", "-", "-", "-", "14"], ["2", "Kerry Baily", "18", "Toyota Supra Chevrolet", "Kerry Baily", "38", "38", "36", "38", "150"], ["21", "Brett Francis", "", "", "", "11", "-", "-", "-", "11"], ["11", "Kevin Clark", "116", "Ford Mustang GT", "Kevin Clark", "-", "-", "23", "23", "46"], ["3", "James Phillip", "55", "Honda Prelude Chevrolet", "James Phillip", "26", "28", "28", "30", "112"], ["13", "Chris Fing", "", "Chevrolet Monza", "", "29", "-", "-", "-", "29"], ["4", "Mick Monterosso", "2", "Ford Escort RS2000", "Mick Monterosso", "-", "34", "36", "34", "104"], ["7", "Mike Imrie", "4", "Saab", "Imrie Motor Sport", "23", "11", "-", "28", "62"], ["", "Ron O'Brien", "", "", "", "-", "-", "-", "10", "10"], ["5", "Bob Jolly", "3", "Holden VS Commodore", "Bob Jolly", "-", "28", "16", "32", "76"], ["14", "Brian Smith", "", "Alfa Romeo GTV Chevrolet", "", "-", "28", "-", "-", "28"], ["12", "Peter O'Brien", "17", "Holden VL Commodore", "O'Brien Aluminium", "-", "11", "29", "-", "40"], ["", "Craig Wildridge", "", "", "", "-", "10", "-", "-", "10"], ["8", "Mark Trenoweth", "", "Jaguar", "", "33", "24", "-", "-", "57"], ["6", "Danny Osborne", "", "Mazda RX-7", "", "26", "10", "30", "-", "66'"]] | 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 not number 42, mikac or wall? | Des Wall | 128 | Answer: |
Table InputTable: [["isn", "name", "arrival\\ndate", "departure\\ndate", "notes"], ["82", "Rasul Kudayev", "", "2004-02-27", "Repatriated to Russia on January 3, 2004.[citation needed]\\nReported to have been repatriated on 24 February 2004 with six other Russian men.\\nAlso called \"Abdullah D. Kafkas\"."], ["211", "Ruslan Anatoloivich Odijev", "2002-06-14", "2004-02-27", "Reported to have been repatriated on 24 February 2004, as \"Ruslan Anatolovich Odijev\", with six other Russian men.\\nCharged with a role in bombing a gas pipeline in 2005.\\nShot by police in 2007.\\nHuman Rights advocates argue he was falsely accused.\\nDefense Intelligence Agency classifies him as a former detainee who \"returned to terrorism\"."], ["674", "Timur Ravilich Ishmurat", "2002-06-14", "2004-02-27", "Repatriated to Russia.\\nReported to have been repatriated on 24 February 2004, as \"Timur Ravilich Ismurat\", with six other Russian men.\\nAlleged to have played a role in a 2005 bombing."], ["203", "Ravil Shafeyavich Gumarov", "2002-01-21", "2004-02-27", "Repatriated to Russia on January 3, 2004.[citation needed]\\nReported to have been repatriated on 24 February 2004 with six other Russian men.\\nAlleged to have played a role in a 2005 bombing.\\nDefense Intelligence Agency classifies him as a former detainee who \"returned to terrorism\"."], ["702", "Ravil Mingazov", "2002-10-28", "", ""], ["492", "Aiat Nasimovich Vahitov", "2002-06-14", "2004-02-27", "Repatriated to Russia on January 3, 2004.[citation needed]\\nReported to have been repatriated on 24 February 2004 with six other Russian men."], ["209", "Almasm Rabilavich Sharipov", "2002-01-21", "2004-02-27", "Repatriated to Russia on January 3, 2004.[citation needed]\\nReported to have been repatriated on 24 February 2004 with six other Russian men.\\nGranted asylum by the Netherlands."], ["672", "Zakirjan Asam", "2002-06-08", "2006-11-17", "NLEC"], ["573", "Rustam Akhmyarov", "2002-05-01", "2004-02-27", "Reported to have been repatriated on 24 February 2004 with six other Russian men."]] | 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 called "abdullah d. kafkas"? | Rasul Kudayev | 128 | Answer: |
Table InputTable: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], ["1", "Soviet Union", "*7*", "3", "6", "16"], ["9", "Germany", "1", "0", "1", "2"], ["8", "Italy", "1", "2", "0", "3"], ["2", "Austria", "4", "3", "4", "11"], ["7", "Norway", "2", "1", "1", "4"], ["5", "Sweden", "2", "4", "4", "10"], ["4", "Switzerland", "3", "2", "1", "6"], ["3", "Finland", "3", "3", "1", "7"], ["10", "Canada", "0", "1", "2", "3"], ["6", "United States", "2", "3", "2", "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:which country had no gold medals? | Canada | 128 | Answer: |
Table InputTable: [["Single / EP", "Tracks", "Label", "Year", "Album"], ["2012 – Remix Contest EP", "2012 (Remastered)", "Burn The Fire", "2012", "The Agenda"], ["Louder Than Bombs", "Louder Than Bombs", "Burn The Fire", "2012", "The Agenda"], ["Hot & Cold", "Overdose", "Burn The Fire", "2010", "—"], ["Breakdown", "Breakdown", "Burn The Fire", "2009", "—"], ["Doin' It Right", "Doin' It Right", "Burn The Fire", "2009", "—"], ["Onslaught", "Onslaught", "Burn The Fire", "2012", "The Agenda"], ["Rave To The Grave", "Raver Booty\\nShuffle", "Burn The Fire", "2010", "—"], ["Still Smoking", "Nasty & Gaspar Still Smoking", "Burn The Fire", "2010", "—"], ["Die Famous", "Die Famous", "Burn The Fire", "2011", "—"], ["Los Angeles", "Los Angeles\\nLos Angeles feat. Whiskey Pete (Clean Mix)\\nLos Angeles feat. Whiskey Pete (Dirty Mix)", "Burn The Fire", "2010", "The Agenda"], ["Fresh Attire Vol. 3", "Crush Groovin'", "Wearhouse Music", "2009", "—"], ["Redroid", "Redroid", "Temple Music Group", "2011", "—"], ["Dutchie", "Dutchie", "Burn The Fire", "2010", "—"], ["Your Love Is Electric", "Your Love Is Electric", "Burn The Fire", "2009", "—"], ["Deception", "Deception", "Burn The Fire", "2012", "The Agenda"], ["The Thirteenth Skull", "The Thirteenth Skull", "Burn The Fire", "2010", "—"], ["Ghetto Ass Bitches", "Ghetto Ass Bitches", "Burn The Fire", "2010", "—"], ["Hyped", "Hyped", "Vicious", "2014", "—"], ["Left To Right", "Left To Right", "Destination?", "2009", "—"], ["Drop Bears", "Drop Bears", "Burn The Fire", "2013", "—"], ["Ancient Psychic Tandem War Elephant", "Ancient Psychic Tandem War Elephant", "Burn The Fire", "2011", "—"], ["Those Who From Heaven To Earth Came", "The Lizard King\\nAnnunaki", "Burn The Fire", "2010", "—"], ["The Flying Cat", "The Flying Cat", "Burn The Fire", "2010", "—"]] | 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 more tracks were in 2010 compared to 2012? | 5 | 128 | Answer: |
Table InputTable: [["Release date", "Album Title", "Record Company", "Song Title", "Certification"], ["October 8, 2006", "Hotsilog: The ASAP Hotdog Compilation", "ASAP Music", "\"Annie Batungbakal\"", "PARI: Platinum"], ["December 2007", "H.O.P.E. (Healing Of Pain and Enlightenment)", "Star Records", "\"Count On Me\"", "PARI: Gold"], ["March 5, 2011", "Kris Aquino: My Heart’s Journey", "Universal Records", "\"God Bless the Broken Road\"", "PARI: Platinum"], ["November 12, 2011", "Happy Yipee Yehey! Nananana!", "Star Records", "\"Mahalin Ka Ng Totoo\"", "PARI: Gold"], ["April 2009", "OPM Number 1's", "Star Records", "\"Can't Hurry Love\"", "PARI:"], ["January 2011", "OPM Number 1's Vol. 2", "Star Records", "\"All Me (Remix)\"", "PARI:"], ["July 25, 2007", "Nagmamahal, Kapamilya: Songs for Global Pinoys", "Star Records", "\"Super Pinoy\"", "PARI: 6X Platinum"], ["February 2011", "I Love You", "Star Records", "\"Catch Me I'm Falling\"", "PARI:"], ["January 17, 2013", "Himig Handog P-Pop Love Songs 2013", "Star Records", "\"Kahit Na\"", "PARI:"], ["June 24, 2009", "I Move, I Give, I Love", "Star Records", "\"Power of the Dream\", \"Bagong Umaga\" with Erik Santos & Yeng Constantino", "PARI: Gold"], ["June 2011", "Bida Best Hits Da Best", "Star Records", "\"Mahal Kita Kasi\", \"Catch Me I'm Falling\", \"You Are The One\" with Sam Milby", "PARI:"], ["November 18, 2011", "Da Best ang Pasko ng Pilipino", "Star Records", "\"Ganyan ang Pasko\", \"Ngayong Pasko Magniningning ang Pilipino\" (Solo) & with Gary Valenciano", "PARI:"], ["November 2010", "Ngayong Pasko Magniningning ang Pilipino: Christmas Songs Compilation", "Star Records", "\"Ganyan ang Pasko\", \"Ngayong Pasko Magniningning ang Pilipino\" (Solo) & with Gary Valenciano", "PARI:"], ["June 2010", "60 Taon ng Musika at Soap Opera", "Star Records", "\"Crazy For You\"", "PARI:"]] | 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 next release date listed after october 8, 2006? | July 25, 2007 | 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"], ["8", "6", "\"The Loser\"", "Mark Rydell", "Robert Culp", "October 20, 1965", "106"], ["25", "24", "\"Crusade to Limbo\"", "Richard Sarafian", "Teleplay by: Morton Fine & David Freidkin & Jack Turley Story by: Jack Turley", "March 23, 1966", "124"], ["27", "26", "\"There was a Little Girl\"", "John Rich", "Teleplay by: Stephen Kandell Story by: Robert Bloch", "April 6, 1966", "126"], ["28", "27", "\"It's All Done with Mirrors\"", "Robert Butler", "Stephen Kandell", "April 13, 1966", "127"], ["26", "25", "\"My Mother, The Spy\"", "Richard Benedict", "Howard Gast", "March 30, 1966", "125"], ["16", "15", "\"The Tiger\"", "Paul Wendkos", "Robert Culp", "January 5, 1966", "115"], ["18", "18", "\"Court of the Lion\"", "Robert Culp", "Robert Culp", "February 2, 1966", "118"], ["3", "1", "\"So Long, Patrick Henry\"", "Leo Penn", "Robert Culp", "September 15, 1965", "101"], ["7", "5", "\"Dragon's Teeth\"", "Leo Penn", "Gilbert Ralston", "October 13, 1965", "105"], ["21", "21", "\"Return to Glory\"", "Robert Sarafian", "David Friedkin & Morton Fine", "February 23, 1966", "121"], ["11", "10", "\"Tatia\"", "David Friedkin", "Robert Lewin", "November 17, 1965", "110"], ["2", "3", "\"Carry Me Back to Old Tsing-Tao\"", "Mark Rydell", "David Karp", "September 29, 1965", "103"], ["24", "28", "\"One Thousand Fine\"", "Paul Wendkos", "Eric Bercovici", "April 27, 1966", "128"], ["13", "13", "\"Tigers of Heaven\"", "Allen Reisner", "Morton Fine & David Friedkin", "December 15, 1965", "113"], ["23", "23", "\"A Day Called 4 Jaguar\"", "Richard Sarafian", "Michael Zagar", "March 9, 1966", "123"], ["15", "17", "\"Always Say Goodbye\"", "Allen Reisner", "Robert C. Dennis & Earl Barrett", "January 26, 1966", "117"], ["10", "8", "\"The Time of the Knife\"", "Paul Wendkos", "Gilbert Ralston", "November 3, 1965", "108"], ["17", "16", "\"The Barter\"", "Allen Reisner", "Harvey Bullock & P.S. Allen", "January 12, 1966", "116"], ["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"], ["1", "14", "\"Affair in T'Sien Cha\"", "Sheldon Leonard", "Morton Fine & David Friedkin", "December 29, 1965", "114"], ["5", "2", "\"A Cup of Kindness\"", "Leo Penn", "Morton Fine & David Friedkin", "September 22, 1965", "102"], ["12", "11", "\"Weight of the World\"", "Paul Wendkos", "Robert Lewin", "December 1, 1965", "111"], ["14", "12", "\"Three Hours on a Sunday\"", "Paul Wendkos", "Morton Fine & David Friedkin", "December 8, 1965", "112"], ["6", "4", "\"Chrysanthemum\"", "David Friedkin", "Edward J. Lakso", "October 6, 1965", "104"]] | 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 directed the greatest number of episodes in the first season? | Paul Wendkos | 128 | Answer: |
Table InputTable: [["Name", "Title", "Date from", "Date until", "Russian state", "Austrian state"], ["Mikhail Timofeyevich Yefremov", "Ambassador Extraordinary and Plenipotentiary", "10 March 1975", "24 October 1986", "Soviet Union", "Republic of Austria"], ["Andrey Kirillovich Razumovsky", "Ambassador", "5 October 1801", "7 September 1806", "Russian Empire", "Holy Roman Empire/Austrian Empire"], ["Andrey Andreyevich Smirnov", "Ambassador Extraordinary and Plenipotentiary", "31 March 1956", "14 October 1956", "Soviet Union", "Republic of Austria"], ["Valery Nikolayevich Popov", "Ambassador Extraordinary and Plenipotentiary", "24 May 1990", "30 August 1996", "Soviet Union/Russian Federation", "Republic of Austria"], ["Pyotr Alekseyevich Kapnist", "Ambassador", "9 April 1895", "1904", "Russian Empire", "Austria-Hungary"], ["Vladimir Mikhailovich Grinin", "Ambassador Extraordinary and Plenipotentiary", "30 August 1996", "29 April 2000", "Russian Federation", "Republic of Austria"], ["Boris Fedorovich Podtserob", "Ambassador Extraordinary and Plenipotentiary", "30 June 1965", "20 September 1971", "Soviet Union", "Republic of Austria"], ["Dmitry Pavlovich Tatishchev", "Ambassador", "22 August 1826", "11 September 1841", "Russian Empire", "Austrian Empire"], ["Averky Borisovich Aristov", "Ambassador Extraordinary and Plenipotentiary", "20 September 1971", "11 July 1973", "Soviet Union", "Republic of Austria"], ["Dmitry Mikhailovich Golitsyn", "Ambassador", "October 1761", "April 1792", "Russian Empire", "Holy Roman Empire"], ["Yevgeny Petrovich Novikov", "Ambassador", "2 March 1874", "22 December 1879", "Russian Empire", "Austria-Hungary"], ["Gennady Serafimovich Shikin", "Ambassador Extraordinary and Plenipotentiary", "24 October 1986", "24 May 1990", "Soviet Union", "Republic of Austria"], ["Lev Pavlovich Urusov", "Ambassador", "1905", "1910", "Russian Empire", "Austria-Hungary"], ["Pavel Petrovich Ubri", "Ambassador", "22 December 1879", "1 June 1882", "Russian Empire", "Austria-Hungary"], ["Gustav Ernst Graf von Stackelberg", "Ambassador", "14 May 1810", "9 November 1818", "Russian Empire", "Austrian Empire"], ["Peter von Meyendorff", "Envoy", "31 August 1850", "7 January 1854", "Russian Empire", "Austrian Empire"], ["Sergey Georgyevich Lapin", "Ambassador Extraordinary and Plenipotentiary", "19 October 1956", "16 June 1960", "Soviet Union", "Republic of Austria"], ["Aleksey Borisovich Lobanov-Rostovsky", "Ambassador", "13 July 1882", "6 January 1895", "Russian Empire", "Austria-Hungary"], ["Viktor Petrovich Balabin", "Envoy", "22 July 1864", "12 August 1864", "Russian Empire", "Austrian Empire"], ["Alexander Vasiliyevich Golovin", "Ambassador Extraordinary and Plenipotentiary", "4 August 2000", "6 August 2004", "Russian Federation", "Republic of Austria"], ["Yury Aleksandrovich Golovkin", "Envoy", "9 November 1818", "16 September 1822", "Russian Empire", "Austrian Empire"], ["Pavel Ivanovich Medem", "Envoy", "24 December 1848", "31 August 1850", "Russian Empire", "Austrian Empire"], ["Stanislav Viliorovich Osadchy", "Ambassador Extraordinary and Plenipotentiary", "14 September 2004", "Present", "Russian Federation", "Republic of Austria"], ["Ernest Gustavovich Stackelberg", "Envoy", "3 August 1864", "25 April 1868", "Russian Empire", "Austrian Empire/Austria-Hungary"]] | 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 ambassadors were there? | 34 | 128 | Answer: |
Table InputTable: [["#", "Title", "Featured guest(s)", "Producer(s)", "Time", "Sample (s)"], ["2", "\"Where Y'all From\"", "", "Battlecat", "1:11", ""], ["1", "\"Hog\"", "", "Battlecat", "4:24", "*\"3 Time Felons\" by Westside Connection"], ["4", "\"The Shadiest One\"", "CJ Mac", "Ant Banks", "4:26", ""], ["15", "\"It's All Bad\"", "", "Battlecat", "4:15", "*\"Chocolate City\" by Parliament"], ["16", "\"Better Days\"", "Ron Banks", "Barr Nine", "3:53", "*\"It's Gonna Be Alright\" by Crimies"], ["12", "\"Rich Rollin'\"", "", "Dutch", "3:40", ""], ["11", "\"Call It What You Want\"", "", "Crazy Toones", "4:29", "*\"Knucklehead\" by Grover Washington, Jr."], ["14", "\"Bank Lick\"", "", "WC", "0:49", ""], ["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"], ["3", "\"Fuckin Wit uh House Party\"", "", "Battlecat", "4:49", "*\"Hollywood Squares\" by Bootsy's Rubber Band\\n*\"(Not Just) Knee Deep\" by Funkadelic"], ["7", "\"Just Clownin'\"", "", "Battlecat", "3:59", "*\"(Not Just) Knee Deep\" by Funkadelic\\n*\"Too Tight for Light\" by Funkadelic"], ["9", "\"Worldwide Gunnin'\"", "", "Skooby Doo", "3:25", ""], ["13", "\"Cheddar\"", "Mack 10 & Ice Cube", "Mo-Suave-A", "4:12", "*\"Gotta Get My Hands on Some (Money)\" by The Fatback Band"], ["6", "\"Keep Hustlin\"", "E-40 & Too Short", "Young Tre", "3:39", "*\"Yearning for Your Love\" by The Gap Band\\n*\"Intimate Connection\" by Kleeer"], ["8", "\"The Autobiography\"", "", "Crazy Toones", "1:21", ""], ["5", "\"Can't Hold Back\"", "Ice Cube", "Skooby Doo", "3:34", "*\"Ain't No Half-Steppin'\" by Big Daddy Kane"], ["17", "\"The Outcome\"", "", "Douglas Coleman", "2:45", ""]] | 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 was longer "hog" or "where y'all from"? | Hog | 128 | Answer: |
Table InputTable: [["Route", "Destinations", "Via", "Frequency\\n(minutes)", "Peak Hours Only", "Former"], ["19", "Montreal Street\\nQueen's University", "Downtown", "30", "X", ""], ["1", "Montreal Street\\nSt. Lawrence College", "Downtown", "30", "", "Cataraqui Town Centre-Woods"], ["14", "Train Station\\nCataraqui Town Centre / Midland Avenue", "Waterloo-Davis\\nMultiplex", "30", "", "(formerly Route A)"], ["11", "Kingston Centre\\nCataraqui Town Centre", "Bath Road\\nGardiners Town Centre", "30", "", "(formerly Route 71)"], ["15", "Reddendale\\nCataraqui Town Centre - Woods", "Gardiners Town Centre", "30", "", "(formerly Route B)"], ["9", "Downtown\\nCataraqui Town Centre", "Brock St. / Barrie St.\\nGardiners Town Centre", "20", "", ""], ["7", "Dalton/Division\\nMidland/Gardiners", "Cataraqui Town Centre\\nTrain Station\\nBus Terminal", "30", "", ""], ["16", "Train Station\\nBus Terminal", "Kingston Centre", "30", "", "(formerly Route C)"], ["10", "Amherstview\\nCataraqui Town Centre", "Collins Bay Road", "30", "", "Kingston Centre"], ["12", "Kingston Centre\\nHighway 15", "Downtown\\nCFB Kingston (off-peak only)", "30", "", "-"], ["6", "Cataraqui Town Centre\\nSt. Lawrence College", "Gardiners Town Centre", "30", "", "Downtown"], ["4", "Princess Street", "Cataraqui Town Centre\\nDowntown", "30", "", ""], ["3", "Kingston Centre\\nDowntown", "Queen Mary Road\\nSt. Lawrence College\\nKing Street", "30", "", ""], ["2", "Kingston Centre\\nDivision Street", "St. Lawrence College\\nDowntown", "30", "", ""], ["18", "Train Station\\nBus Terminal", "Downtown\\nQueen's University\\nSt. Lawrence College", "*", "", "Student Circuit"], ["12A", "CFB Kingston\\nDowntown", "", "30", "X", ""]] | 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 routes that stops at montreal street? | 2 | 128 | Answer: |
Table InputTable: [["Contestant", "Original\\nTribe", "First\\nSwitch", "Second\\nSwitch", "Merged\\nTribe", "Finish", "Ghost\\nIsland", "Total\\nVotes"], ["Milena Vitanović\\n21, Paraćin", "Ga 'dang", "", "", "", "4th Voted Out\\nDay 13", "4th Eliminated\\nDay 18", "8"], ["Branka Čudanov\\n28, Kikinda", "Ga 'dang", "", "", "", "2nd Voted Out\\nDay 7", "1st Eliminated\\nDay 9", "10"], ["Njegoš Arnautović\\n21, Bijeljina, Republika Srpska", "Manobo", "Ga 'dang", "Ga 'dang", "Diwata", "Eliminated in Challenge\\n7th Jury Member\\nDay 53", "Locator of\\nHidden Immunity Idol\\n(Successful)\\nDay 40", "1"], ["Dušan Milisavljević\\n25, Zvečan", "Manobo", "Manobo", "Manobo", "Diwata", "Eliminated in Challenge\\n8th Jury Member\\nDay 53", "Locator of\\nHidden Immunity Idol\\n(Failed)\\nDay 37", "2"], ["Luka Rajačić\\n21, Belgrade", "Ga 'dang", "Manobo", "Manobo", "", "9th Voted Out\\nDay 31", "10th Eliminated\\nDay 32", "6"], ["Gordana Berger\\n38, Belgrade", "Manobo", "", "", "", "1st Voted Out\\nDay 4", "2nd Eliminated\\nDay 12", "9"], ["Ana Mitrić\\n23, Belgrade", "Ga 'dang", "", "", "", "3rd Voted Out\\nDay 10", "3rd Eliminated\\nDay 15", "7"], ["Nikola Kovačević\\n24, Kragujevac", "Ga 'dang", "", "", "Diwata", "11th Voted Out\\n2nd Jury Member\\nDay 38", "Ghost Island Winner\\nDay 32", "12"], ["Aleksandar Bošković\\n28, Belgrade", "Manobo", "Manobo", "", "", "7th Voted Out\\nDay 25", "8th Eliminated\\nDay 27", "4"], ["Vesna Đolović\\n38, Beograd", "Manobo", "Manobo", "Manobo", "Diwata", "2nd Runner-Up", "Locator of\\nHidden Immunity Idol\\n(Failed)\\nDay 46", "8"], ["Klemen Rutar\\n21, Ljubljana, Slovenija", "Manobo", "Ga 'dang", "Ga 'dang", "Diwata", "14th Voted Out\\n5th Jury Member\\nDay 47", "Locator of\\nHidden Immunity Idol\\n(Failed)\\nDay 34", "6"], ["Ana Stojanovska\\n21, Skopje, Macedonia", "Manobo", "Manobo", "Manobo", "", "8th Voted Out\\nDay 28", "9th Eliminated\\nDay 30", "3"], ["Pece Kotevski\\n42, Bitola, Macedonia", "Ga 'dang", "Manobo", "", "", "6th Voted Out\\nDay 19", "6th Eliminated\\nDay 21", "7"], ["Branislava Bogdanović\\n27, Kačarevo", "Manobo", "", "", "", "Eliminated in a twist\\nDay 17", "5th Eliminated\\nDay 18", "2"], ["Nikola Kovačević\\nReturned to game from Ghost Island", "Ga 'dang", "", "", "", "5th Voted Out\\nDay 16", "Ghost Island Winner\\nDay 32", "6"], ["Teja Lapanja\\n30, Škofja Loka, Slovenija", "Ga 'dang", "Ga 'dang", "Ga 'dang", "Diwata", "Runner-Up", "Locator of\\nHidden Immunity Idol\\n(Failed)\\nDay 49", "1"], ["Aleksandar Krajišnik\\n19, Majur, near Šabac", "Ga 'dang", "Ga 'dang", "Ga 'dang", "Diwata", "Sole Survivor", "Locator of\\nHidden Immunity Idol\\n(Failed)\\nDay 43", "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:who was the only contestant voted out on day 25? | Aleksandar Bošković | 128 | Answer: |
Table InputTable: [["Year", "Winners", "Runners-up", "Third", "Fourth"], ["1973", "Borussia Mönchengladbach", "PFC CSKA Sofia", "Real Zaragoza", "West Ham"], ["1974", "Real Zaragoza", "Eintracht Frankfurt", "FC Molenbeek Brussels Strombeek", "Partizan Belgrade"], ["1972", "Hamburg SV", "Sociedade Esportiva Palmeiras", "Real Zaragoza", "-"], ["1975", "Real Zaragoza", "Club Atlético Boca Juniors", "FK Vojvodina", "Boavista Futebol Clube"], ["1976", "Real Zaragoza", "Górnik Zabrze", "OFK Belgrade", "Olympiacos FC"], ["1979", "Real Zaragoza", "NK Dinamo Zagreb", "Vasas SC", "FK Sarajevo"], ["1977", "PFC CSKA Sofia", "Real Zaragoza", "FK Radnički Niš", "RCD Espanyol"], ["1978", "Real Zaragoza", "Club Nacional de Football", "PFC Sliven", "FK Trepca Mitrovica"], ["1981", "Real Zaragoza", "Nottingham Forest Football Club", "Tisza Volán SC", "Club Atlético Osasuna"], ["1971", "Cologne", "Royal Sporting Club Anderlecht", "Real Zaragoza", "-"], ["1982", "Manchester United F.C.", "Real Zaragoza", "MTK Hungária FC", "Budapest Honvéd FC"], ["1990", "FC Dinamo Moscow", "Real Zaragoza", "Real Betis Balompié", "-"], ["1983", "Real Zaragoza", "Club América", "Aston Villa Football Club", "Politehnica Timişoara"], ["1980", "RCD Espanyol", "Real Zaragoza", "Sporting Lisboa", "Partizan Belgrade"], ["2007", "Real Zaragoza", "Juventus Football Club", "-", "-"], ["1988", "Club Atlético Peñarol", "Real Zaragoza", "-", "-"], ["1991", "Real Zaragoza", "Dinamo Bucharest", "-", "-"], ["2004", "Club Atlético de Madrid", "Real Zaragoza", "-", "-"], ["1984", "Videoton SC", "Universidad Católica", "Real Zaragoza", "Defensor Sporting Club"], ["2001", "Real Zaragoza", "FC Twente", "-", "-"], ["1989", "Real Zaragoza", "Club de Fútbol Atlante", "Aragon", "-"], ["2005", "Real Zaragoza", "Real Madrid Club de Fútbol", "-", "-"], ["1995", "Real Zaragoza", "Club Nacional de Football", "-", "-"], ["1985", "Fútbol Club Barcelona", "Real Zaragoza", "-", "-"], ["2009", "Società Sportiva Lazio", "Real Zaragoza", "-", "-"], ["1992", "Real Zaragoza", "Fútbol Club Barcelona", "-", "-"], ["1997", "Società Sportiva Lazio", "Real Zaragoza", "-", "-"], ["2006", "Real Zaragoza", "Associazione Sportiva Livorno Calcio", "-", "-"], ["1994", "Real Zaragoza", "CSKA Moscow", "-", "-"], ["1996", "Real Zaragoza", "Hamburg SV", "-", "-"], ["2008", "Getafe Club de Fútbol", "Real Zaragoza", "-", "-"], ["2002", "Real Zaragoza", "Athletic Club", "-", "-"], ["1999", "Real Zaragoza", "Feyenoord Rotterdam", "-", "-"], ["1993", "Club de Regatas Vasco da Gama", "Real Zaragoza", "-", "-"], ["1998", "Parma", "Real Zaragoza", "-", "-"], ["2010", "Sociedad Deportiva Huesca", "Real Zaragoza", "CD Teruel", "-"], ["2003", "Real Zaragoza", "Chievo", "-", "-"], ["2000", "Real Zaragoza", "Parma", "-", "-"], ["1986", "Real Zaragoza", "Cologne", "-", "-"], ["1987", "Real Zaragoza", "Checoslovaquia", "-", "-"], ["2012", "Real Zaragoza", "RCD Espanyol", "-", "-"], ["2011", "Real Zaragoza", "RCD Espanyol", "-", "-"]] | 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 had the most winners in the 1970s? | Real Zaragoza | 128 | Answer: |
Table InputTable: [["Episode no.", "Airdate", "Viewers", "BBC Three weekly ranking", "Multichannels rank"], ["2", "2 May 2013", "978,000", "1", "11"], ["1", "25 April 2013", "979,000", "2", "9"], ["10", "27 June 2013", "730,000", "N/A", "28"], ["4", "16 May 2013", "880,000", "1", "13"], ["7", "6 June 2013", "975,000", "2", "6"], ["3", "9 May 2013", "885,000", "1", "11"], ["8", "13 June 2013", "840,000", "5", "19"], ["5", "23 May 2013", "1,092,000", "1", "5"], ["9", "20 June 2013", "1,204,000", "6", "9"], ["6", "30 May 2013", "1,094,000", "1", "3"], ["12", "11 July 2013", "", "", ""], ["11", "4 July 2013", "N/A", "N/A", "N/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:difference in viewers between episode 1 and episode 2 | 1000 | 128 | Answer: |
Table InputTable: [["Player", "No.", "Nationality", "Position", "Years for Jazz", "School/Club Team"], ["Todd Fuller", "52", "United States", "Center", "1998-99", "North Carolina State"], ["Bernie Fryer", "25", "United States", "Guard", "1975-76", "BYU"], ["Kyrylo Fesenko", "44", "Ukraine", "Center", "2007-11", "Cherkasy Monkeys (Ukraine)"], ["Greg Foster", "44", "United States", "Center/Forward", "1995-99", "UTEP"], ["Derek Fisher", "2", "United States", "Guard", "2006-2007", "Arkansas-Little Rock"], ["Terry Furlow", "25", "United States", "Guard/Forward", "1979-80", "Michigan State"], ["Jim Farmer", "30", "United States", "Guard", "1988-89", "Alabama"], ["Derrick Favors", "15", "United States", "Forward", "2011-present", "Georgia Tech"]] | 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 ranked last among this group? | Terry Furlow | 128 | Answer: |
Table InputTable: [["Year", "Competition", "Venue", "Position", "Event", "Notes"], ["2007", "All-Africa Games", "Algiers, Algeria", "3rd", "Discus throw", "57.79 m"], ["2003", "All-Africa Games", "Abuja, Nigeria", "5th", "Shot put", "17.76 m"], ["2003", "All-Africa Games", "Abuja, Nigeria", "2nd", "Discus throw", "62.86 m"], ["2004", "African Championships", "Brazzaville, Republic of the Congo", "2nd", "Discus throw", "63.50 m"], ["2008", "African Championships", "Addis Ababa, Ethiopia", "2nd", "Discus throw", "56.98 m"], ["2006", "Commonwealth Games", "Melbourne, Australia", "7th", "Shot put", "18.44 m"], ["2006", "Commonwealth Games", "Melbourne, Australia", "4th", "Discus throw", "60.99 m"], ["2004", "Olympic Games", "Athens, Greece", "8th", "Discus throw", "62.58 m"], ["2000", "World Junior Championships", "Santiago, Chile", "1st", "Discus throw", "59.51 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:what is the number of all-africa games hannes has competed in? | 2 | 128 | Answer: |
Table InputTable: [["#", "Title", "Featured guest(s)", "Producer(s)", "Time", "Sample (s)"], ["5", "\"Can't Hold Back\"", "Ice Cube", "Skooby Doo", "3:34", "*\"Ain't No Half-Steppin'\" by Big Daddy Kane"], ["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"], ["3", "\"Fuckin Wit uh House Party\"", "", "Battlecat", "4:49", "*\"Hollywood Squares\" by Bootsy's Rubber Band\\n*\"(Not Just) Knee Deep\" by Funkadelic"], ["13", "\"Cheddar\"", "Mack 10 & Ice Cube", "Mo-Suave-A", "4:12", "*\"Gotta Get My Hands on Some (Money)\" by The Fatback Band"], ["12", "\"Rich Rollin'\"", "", "Dutch", "3:40", ""], ["6", "\"Keep Hustlin\"", "E-40 & Too Short", "Young Tre", "3:39", "*\"Yearning for Your Love\" by The Gap Band\\n*\"Intimate Connection\" by Kleeer"], ["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"], ["4", "\"The Shadiest One\"", "CJ Mac", "Ant Banks", "4:26", ""], ["7", "\"Just Clownin'\"", "", "Battlecat", "3:59", "*\"(Not Just) Knee Deep\" by Funkadelic\\n*\"Too Tight for Light\" by Funkadelic"], ["9", "\"Worldwide Gunnin'\"", "", "Skooby Doo", "3:25", ""], ["15", "\"It's All Bad\"", "", "Battlecat", "4:15", "*\"Chocolate City\" by Parliament"], ["14", "\"Bank Lick\"", "", "WC", "0:49", ""], ["8", "\"The Autobiography\"", "", "Crazy Toones", "1:21", ""], ["17", "\"The Outcome\"", "", "Douglas Coleman", "2:45", ""], ["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:how many songs have featured guests? | 6 | 128 | Answer: |
Table InputTable: [["Clerk", "Started", "Finished", "School (year)", "Previous clerkship"], ["Heywood H. Davis", "1958", "1959", "Kansas (1958)", "none"], ["Jerome B. Libin", "1959", "1960", "Michigan (1959)", "none"], ["Kenneth W. Dam", "1957", "1958", "Chicago (1957)", "none"], ["William C. Canby, Jr.", "1958", "1959", "Minnesota (1956)", "none"], ["Alan C. Kohn", "1957", "1958", "Wash U (1955)", "none"], ["Patrick F. McCartan", "1959", "1960", "Notre Dame (1959)", "none"], ["D. Lawrence Gunnels", "1961", "1962", "Wash U (1960)", "none"]] | 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 clerks started in the years 1958-59? | 4 | 128 | Answer: |
Table InputTable: [["Year", "Competition", "Venue", "Position", "Event", "Notes"], ["1992", "Olympic Games", "Barcelona, Spain", "5th", "Marathon", "2:14:15"], ["1987", "World Championships", "Rome, Italy", "13th", "Marathon", "2:17:45"], ["1996", "Olympic Games", "Atlanta, United States", "20th", "Marathon", "2:17:27"], ["1991", "World Championships", "Tokyo, Japan", "6th", "Marathon", "2:15:58"], ["1993", "World Championships", "Stuttgart, Germany", "—", "Marathon", "DNF"], ["1990", "European Championships", "Split, FR Yugoslavia", "4th", "Marathon", "2:17:45"], ["1987", "Venice Marathon", "Venice, Italy", "1st", "Marathon", "2:10:01"], ["1986", "Venice Marathon", "Venice, Italy", "1st", "Marathon", "2:18:44"]] | 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 are the number of times olympic games is listed as the competition? | 2 | 128 | Answer: |
Table InputTable: [["Outcome", "No.", "Date", "Tournament", "Surface", "Opponent", "Score"], ["Winner", "2.", "2 May 2004", "Torneo Godó, Barcelona, Spain", "Clay", "Gastón Gaudio", "6–3, 4–6, 6–2, 3–6, 6–3"], ["Runner-up", "4.", "30 April 2006", "Torneo Godó, Barcelona, Spain", "Clay", "Rafael Nadal", "4–6, 4–6, 0–6"], ["Winner", "9.", "22 February 2009", "Copa Telmex, Buenos Aires, Argentina", "Clay", "Juan Mónaco", "7–5, 2–6, 7–6(7–5)"], ["Winner", "10.", "6 February 2011", "Chile Open, Santiago, Chile", "Clay", "Santiago Giraldo", "6–2, 2–6, 7–6(7–5)"], ["Winner", "11.", "14 April 2013", "Grand Prix Hassan II, Casablanca, Morocco", "Clay", "Kevin Anderson", "7–6(8–6), 4–6, 6–3"], ["Winner", "3.", "21 May 2006", "Hamburg Masters, Hamburg, Germany", "Clay", "Radek Štěpánek", "6–1, 6–3, 6–3"], ["Runner-up", "3.", "1 May 2005", "Estoril Open, Estoril, Portugal", "Clay", "Gastón Gaudio", "1–6, 6–2, 1–6"], ["Winner", "5.", "5 August 2007", "Orange Warsaw Open, Sopot, Poland (2)", "Clay", "José Acasuso", "7–5, 6–0"], ["Winner", "12.", "28 July 2013", "ATP Vegeta Croatia Open Umag, Umag, Croatia", "Clay", "Fabio Fognini", "6–0, 6–3"], ["Winner", "1.", "29 July 2001", "Orange Warsaw Open, Sopot, Poland", "Clay", "Albert Portas", "1–6, 7–5, 7–6(7–2)"], ["Winner", "7.", "13 July 2008", "Swedish Open, Båstad, Sweden (2)", "Clay", "Tomáš Berdych", "6–4, 6–1"], ["Winner", "4.", "16 July 2006", "Swedish Open, Båstad, Sweden", "Clay", "Nikolay Davydenko", "6–2, 6–1"], ["Runner-up", "6.", "16 September 2007", "China Open, Beijing, China", "Hard (i)", "Fernando González", "1–6, 6–3, 1–6"], ["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"], ["Runner-up", "7.", "15 June 2008", "Orange Warsaw Open, Warsaw, Poland", "Clay", "Nikolay Davydenko", "3–6, 3–6"], ["Winner", "6.", "7 October 2007", "Open de Moselle, Metz, France", "Hard (i)", "Andy Murray", "0–6, 6–2, 6–3"], ["Runner-up", "5.", "14 January 2007", "Heineken Open, Auckland, New Zealand", "Hard", "David Ferrer", "4–6, 2–6"]] | 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:how many tournaments are held in spain? | 2 | 128 | Answer: |
Table InputTable: [["Pos", "No", "Driver", "Constructor", "Laps", "Time/Retired", "Grid", "Points"], ["1", "1", "Alain Prost", "McLaren-TAG", "82", "1:54:20.388", "4", "9"], ["2", "6", "Nelson Piquet", "Williams-Honda", "82", "+ 4.205", "2", "6"], ["4", "3", "Martin Brundle", "Tyrrell-Renault", "81", "+ 1 Lap", "16", "3"], ["8", "26", "Philippe Alliot", "Ligier-Renault", "79", "+ 3 Laps", "8", ""], ["7", "25", "René Arnoux", "Ligier-Renault", "79", "+ 3 Laps", "5", ""], ["3", "28", "Stefan Johansson", "Ferrari", "81", "+ 1 Lap", "12", "4"], ["5", "4", "Philippe Streiff", "Tyrrell-Renault", "80", "Out of Fuel", "10", "2"], ["Ret", "20", "Gerhard Berger", "Benetton-BMW", "40", "Engine", "6", ""], ["Ret", "7", "Riccardo Patrese", "Brabham-BMW", "63", "Electrical", "19", ""], ["Ret", "27", "Michele Alboreto", "Ferrari", "0", "Collision", "9", ""], ["Ret", "5", "Nigel Mansell", "Williams-Honda", "63", "Tyre", "1", ""], ["6", "11", "Johnny Dumfries", "Lotus-Renault", "80", "+ 2 Laps", "14", "1"], ["Ret", "2", "Keke Rosberg", "McLaren-TAG", "62", "Tyre", "7", ""], ["9", "14", "Jonathan Palmer", "Zakspeed", "77", "+ 5 Laps", "21", ""], ["NC", "22", "Allen Berg", "Osella-Alfa Romeo", "61", "Not Classified", "26", ""], ["Ret", "29", "Huub Rothengatter", "Zakspeed", "29", "Suspension", "23", ""], ["Ret", "12", "Ayrton Senna", "Lotus-Renault", "43", "Engine", "3", ""], ["Ret", "18", "Thierry Boutsen", "Arrows-BMW", "50", "Engine", "22", ""], ["10", "19", "Teo Fabi", "Benetton-BMW", "77", "+ 5 Laps", "13", ""], ["Ret", "23", "Andrea de Cesaris", "Minardi-Motori Moderni", "40", "Mechanical", "11", ""], ["Ret", "8", "Derek Warwick", "Brabham-BMW", "57", "Brakes", "20", ""], ["Ret", "21", "Piercarlo Ghinzani", "Osella-Alfa Romeo", "2", "Transmission", "25", ""], ["NC", "16", "Patrick Tambay", "Lola-Ford", "70", "Not Classified", "17", ""], ["Ret", "24", "Alessandro Nannini", "Minardi-Motori Moderni", "10", "Accident", "18", ""], ["Ret", "17", "Christian Danner", "Arrows-BMW", "52", "Engine", "24", ""], ["Ret", "15", "Alan Jones", "Lola-Ford", "16", "Engine", "15", ""]] | 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 points for alain prost and nelson piquet? | 15 | 128 | Answer: |
Table InputTable: [["Rank", "Player Name", "No. of Titles", "Runner-up", "Final Appearances"], ["5", "Nick Matthew", "3", "0", "3"], ["8", "Peter Nicol", "1", "2", "3"], ["3", "Geoff Hunt", "4", "1", "5"], ["6", "David Palmer", "2", "1", "3"], ["14", "Chris Dittmar", "0", "5", "5"], ["9", "Ross Norman", "1", "1", "2"], ["17", "Lee Beachill", "0", "1", "1"], ["17", "James Willstrop", "0", "1", "1"], ["12", "Jonathon Power", "1", "0", "1"], ["9", "Rodney Eyles", "1", "1", "2"], ["15", "Grégory Gaultier", "0", "4", "4"], ["2", "Jahangir Khan", "6", "3", "9"], ["17", "Dean Williams", "0", "1", "1"], ["17", "Peter Marshall", "0", "1", "1"], ["6", "Ramy Ashour", "2", "1", "3"], ["17", "Ahmed Barada", "0", "1", "1"], ["15", "Qamar Zaman", "0", "4", "4"], ["1", "Jansher Khan", "8", "1", "9"], ["12", "Rodney Martin", "1", "0", "1"], ["9", "Thierry Lincou", "1", "1", "2"], ["17", "John White", "0", "1", "1"], ["4", "Amr Shabana", "4", "0", "4"], ["17", "Mohibullah Khan", "0", "1", "1"], ["17", "Karim Darwish", "0", "1", "1"], ["17", "Del Harris", "0", "1", "1"], ["17", "Mohamed El Shorbagy", "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:final apprentices did nick matthew have? | 3 | 128 | Answer: |
Table InputTable: [["", "Chronological\\nNo.", "Date\\n(New style)", "Water level\\ncm", "Peak hour"], ["2", "210", "23 September 1924", "380", "19:15"], ["46", "211", "3 January 1925", "225", "21:30"], ["39", "228", "14 September 1938", "233", "2:25"], ["24", "136", "20 October 1873", "242", "–"], ["20", "55", "20 November 1764", "244", "–"], ["27", "177", "26 November 1898", "240", "23:30"], ["41", "292", "1 January 1984", "231", "21:20"], ["43", "208", "24 November 1922", "228", "19:15"], ["23", "45", "29 September 1756", "242", ""], ["49", "202", "24 August 1918", "224", "9:10"], ["34", "171", "2 November 1895", "237", "3:00"], ["48", "122", "19 May 1865", "224", "9:10"], ["14", "25", "10 September 1736", "261", ""], ["8", "14", "1 November 1726", "270", "–"], ["29", "219", "8 January 1932", "239", "3:00"], ["32", "76", "29 September 1788", "237", "–"], ["42", "125", "19 January 1866", "229", "10:00"], ["28", "260", "20 December 1973", "240", "7:15"], ["30", "225", "8 October 1935", "239", "5:50"], ["19", "144", "29 October 1874", "252", "4:00"], ["47", "81", "6 September 1802", "224", "daytime"], ["25", "175", "4 November 1897", "242", "12:00"], ["13", "319", "30 November 1999", "262", "4:35"], ["21", "201", "17 November 1917", "244", "6:50"], ["16", "215", "15 October 1929", "258", "17:15"], ["9", "183", "13 November 1903", "269", "9:00"], ["1", "84", "19 November 1824", "421", "14:00"], ["18", "83", "24 January 1822", "254", "night"], ["50", "242", "14 October 1954", "222", "21:00"], ["44", "315", "12 October 1994", "228", "13:50"], ["6", "39", "22 October 1752", "280", "10:00"], ["22", "254", "18 October 1967", "244", "13:30"], ["31", "18", "12 October 1729", "237", "10:00"], ["26", "261", "17 November 1974", "242", "1:00"], ["4", "244", "15 October 1955", "293", "20:45"], ["37", "41", "26 October 1752", "234", "12:00"], ["35", "227", "9 September 1937", "236", "5:30"], ["40", "269", "7 September 1977", "231", "16:50"], ["38", "43", "11 December 1752", "234", "night"], ["11", "86", "20 August 1831", "264", "night"], ["36", "37", "17 October 1744", "234", "–"], ["15", "298", "6 December 1986", "260", "13:30"], ["33", "145", "26 November 1874", "237", "4:00"], ["45", "116", "8 October 1863", "227", "2:00"], ["5", "264", "29 September 1975", "281", "4:00"], ["10", "7", "5 November 1721", "265", "daytime"], ["7", "9", "2 October 1723", "272", "–"], ["12", "3", "9 September 1706", "262", "daytime"], ["3", "71", "9 September 1777", "321", "morning"]] | 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 1900 how many entries are there? | 22 | 128 | Answer: |
Table InputTable: [["Rnd", "Circuit", "GTP Winning Team\\nGTP Winning Drivers", "GTO Winning Team\\nGTO Winning Drivers", "GTU Winning Team\\nGTU Winning Drivers", "Results"], ["15", "Michigan", "#56 Blue Thunder Racing", "#91 Electrodyne", "#84 Dole Racing", "Results"], ["10", "Watkins Glen", "#14 Holbert Racing", "#91 Electrodyne", "#87 Performance Motorsports", "Results"], ["13", "Road America", "#14 Holbert Racing", "#91 Electrodyne", "#66 Mike Meyer Racing", "Results"], ["16", "Watkins Glen", "#57 Blue Thunder Racing", "#91 Electrodyne", "#84 Dole Racing", "Results"], ["9", "Mid-Ohio", "#14 Holbert Racing", "#91 Electrodyne", "#66 Mike Meyer Racing", "Results"], ["7", "Charlotte", "#56 Blue Thunder Racing", "#4 Stratagraph Inc.", "#99 All American Racers", "Results"], ["2", "Miami", "#04 Group 44", "#47 Dingman Bros. Racing", "#99 All American Racers", "Results"], ["1", "Daytona", "#00 Kreepy Krauly Racing", "#4 Stratagraph Inc.", "#76 Malibu Grand Prix", "Results"], ["2", "Miami", "Doc Bundy\\n Brian Redman", "Walt Bohren", "Chris Cord", "Results"], ["16", "Watkins Glen", "Dale Whittington\\n Randy Lanier", "Chester Vincentz\\n Jim Mullen", "Clay Young", "Results"], ["5", "Riverside", "#56 Blue Thunder Racing", "#38 Mandeville Auto Tech", "#87 Performance Motorsports", "Results"], ["3", "Sebring", "Mauricio DeNarvaez\\n Hans Heyer\\n Stefan Johansson", "Terry Labonte\\n Billy Hagan\\n Gene Felton", "Jack Baldwin\\n Bob Reed\\n Ira Young", "Results"], ["4", "Road Atlanta", "#16 Marty Hinze Racing", "#4 Stratagraph Inc.", "#76 Malibu Grand Prix", "Results"], ["7", "Charlotte", "Bill Whittington\\n Randy Lanier", "Billy Hagan\\n Gene Felton", "Chris Cord\\n Jim Adams", "Results"], ["10", "Watkins Glen", "Al Holbert\\n Jim Adams\\n Derek Bell", "Chester Vincentz\\n Jim Mullen", "Elliot Forbes-Robinson\\n John Schneider", "Results"], ["6", "Laguna Seca", "#56 Blue Thunder Racing", "#77 Brooks Racing", "#99 All American Racers", "Results"], ["6", "Laguna Seca", "Randy Lanier", "John Bauer", "Jim Adams", "Results"], ["14", "Pocono", "#14 Holbert Racing", "#65 English Enterprises", "#87 Performance Motorsports", "Results"], ["12", "Sears Point", "#56 Blue Thunder Racing", "#77 Brooks Racing", "#98 All American Racers", "Results"], ["8", "Lime Rock", "#00 Kreepy Krauly Racing", "#38 Mandeville Auto Tech", "#76 Malibu Grand Prix", "Results"], ["1", "Daytona", "Sarel van der Merwe\\n Graham Duxbury\\n Tony Martin", "Terry Labonte\\n Billy Hagan\\n Gene Felton", "Jack Baldwin\\n Jim Cook\\n Ira Young\\n Bob Reed", "Results"], ["11", "Portland", "#56 Blue Thunder Racing", "#51 Corvette", "#76 Malibu Grand Prix", "Results"], ["5", "Riverside", "Don Whittington\\n Randy Lanier", "Roger Mandeville\\n Amos Johnson", "Elliot Forbes-Robinson\\n John Schneider", "Results"], ["4", "Road Atlanta", "Don Whittington", "Billy Hagan\\n Gene Felton", "Jack Baldwin\\n Bob Reed", "Results"], ["17", "Daytona", "Al Holbert\\n Derek Bell", "Wally Dallenbach, Jr.\\n Willy T. Ribbs", "Elliot Forbes-Robinson\\n John Schneider", "Results"], ["8", "Lime Rock", "Sarel van der Merwe", "Roger Mandeville", "Jack Baldwin", "Results"], ["12", "Sears Point", "Bill Whittington", "John Bauer", "Dennis Aase", "Results"], ["17", "Daytona", "#14 Holbert Racing", "#67 Roush Racing", "#87 Performance Motorsports", "Results"], ["15", "Michigan", "Bill Whittington\\n Randy Lanier", "Chester Vincentz\\n Jim Mullen", "Clay Young", "Results"]] | 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 number of times electrodyne won? | 5 | 128 | Answer: |
Table InputTable: [["#", "Player", "Goals", "Caps", "Career"], ["1", "Landon Donovan", "57", "155", "2000–present"], ["2", "Clint Dempsey", "36", "103", "2004–present"], ["8", "Eddie Johnson", "19", "62", "2004–present"], ["6T", "Jozy Altidore", "21", "67", "2007–present"], ["6T", "Bruce Murray", "21", "86", "1985–1993"], ["9T", "DaMarcus Beasley", "17", "114", "2001–present"], ["5", "Joe-Max Moore", "24", "100", "1992–2002"], ["4", "Brian McBride", "30", "95", "1993–2006"], ["9T", "Earnie Stewart", "17", "101", "1990–2004"], ["3", "Eric Wynalda", "34", "106", "1990–2000"]] | 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 most goals? | Landon Donovan | 128 | Answer: |
Table InputTable: [["Date", "Opponent", "Venue", "Result", "Attendance", "Scorers"], ["17 April 2006", "Newcastle United", "Stadium of Light", "1–4", "40,032", "Hoyte"], ["14 April 2006", "Manchester United", "Old Trafford", "0–0", "72,519", ""], ["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"], ["3 December 2005", "Tottenham Hotspur", "White Hart Lane", "2–3", "36,244", "Whitehead, Le Tallec"], ["10 September 2005", "Chelsea", "Stamford Bridge", "0–2", "41,969", ""], ["4 February 2006", "West Ham United", "Boleyn Ground", "0–2", "34,745", ""], ["26 December 2005", "Bolton Wanderers", "Stadium of Light", "0–0", "32,232", ""], ["3 March 2006", "Manchester City", "City of Manchester Stadium", "1–2", "42,200", "Kyle"], ["26 November 2005", "Birmingham City", "Stadium of Light", "0–1", "32,442", ""], ["18 March 2006", "Bolton Wanderers", "Reebok Stadium", "0–2", "23,568", ""], ["1 April 2006", "Everton", "Goodison Park", "2–2", "38,093", "Stead, Delap"], ["25 September 2005", "Middlesbrough", "Riverside Stadium", "2–0", "29,583", "Miller, Arca"], ["12 February 2006", "Tottenham Hotspur", "Stadium of Light", "1–1", "34,700", "Murphy"], ["7 May 2006", "Aston Villa", "Villa Park", "1–2", "33,820", "D. Collins"], ["23 October 2005", "Newcastle United", "St James' Park", "2–3", "52,302", "Lawrence, Elliott"], ["25 February 2006", "Birmingham City", "St. Andrew's", "0–1", "29,257", ""], ["1 October 2005", "West Ham United", "Stadium of Light", "1–1", "31,212", "Miller"], ["31 January 2006", "Middlesbrough", "Stadium of Light", "0–3", "31,675", ""], ["20 August 2005", "Liverpool", "Anfield", "0–1", "44,913", ""], ["21 January 2006", "West Bromwich Albion", "The Hawthorns", "1–0", "26,464", "Watson (own goal)"], ["15 February 2006", "Blackburn Rovers", "Ewood Park", "0–2", "18,220", ""], ["11 March 2006", "Wigan Athletic", "Stadium of Light", "0–1", "31,194", ""], ["15 October 2005", "Manchester United", "Stadium of Light", "1–3", "39,085", "Elliott"], ["30 November 2005", "Liverpool", "Stadium of Light", "0–2", "32,697", ""], ["25 March 2006", "Blackburn Rovers", "Stadium of Light", "0–1", "29,593", ""], ["5 November 2005", "Arsenal", "Highbury", "1–3", "38,210", "Stubbs"], ["31 December 2005", "Everton", "Stadium of Light", "0–1", "30,567", ""], ["23 August 2005", "Manchester City", "Stadium of Light", "1–2", "33,357", "Le Tallec"], ["27 August 2005", "Wigan Athletic", "JJB Stadium", "0–1", "17,223", ""], ["4 May 2006", "Fulham", "Stadium of Light", "2–1", "28,226", "Le Tallec, Brown"], ["10 December 2005", "Charlton Athletic", "The Valley", "0–2", "26,065", ""]] | 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 did they play in their last game? | Aston Villa | 128 | Answer: |
Table InputTable: [["Name", "Topic", "Cost", "Target age", "Advertising"], ["Cut-the-Knot", "Maths", "Free", "8+", "Yes - extensive"], ["IXL", "Math", "$80/year", "4-12", "?"], ["Awesome Library", "All", "Free", "All", "Yes - large"], ["Archimedes-lab.org", "Mathematics", "Free", "10+", "Yes - limited"], ["WatchKnowLearn", "All", "Free", "2-17", "None"], ["Fact Monster", "World & News, U.S., People, English, Science, Math & Money, Sports", "Free", "4-14 (K-8)", "Yes"], ["Le Patron", "French", "Free", "12+", "Yes"], ["Ask A Biologist", "Biology", "Free", "5+", "None"], ["Geometry from the Land of the Incas", "Geometry", "Free", "12+", "Yes - extensive"], ["Starfall.com", "Reading", "Free", "2-9", "None"], ["HackMath.net", "Mathematics", "Free", "9-18", "None"], ["HyperPhysics", "Physics", "Free", "15+", "None"], ["BrainPop", "Science, Social studies, English, Maths, Art & Music, Health, Technology", "from US$75/year", "4-17", "None"], ["Smartygames.com", "Math Games, Reading, Art, Word Scramble, Spanish, Puzzles, Kids Sudoku and more", "Free", "2-9", "None"], ["LearnAlberta.ca", "Everything (mainly aimed at teachers)", "Free", "5-18", "No"], ["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"], ["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 names are there on the chart? | 17 | 128 | Answer: |
Table InputTable: [["Year", "MVP", "Defensive Player of the Year", "Unsung Hero", "Newcomer of the Year"], ["1993", "Patrice Ferri", "–", "–", "–"], ["2010", "Philippe Billy", "Philippe Billy", "Tony Donatelli", "Ali Gerba"], ["2008", "Matt Jordan", "Nevio Pizzolitto", "Joey Gjertsen", "Stefano Pesoli"], ["2011", "Hassoun Camara", "Evan Bush", "Simon Gatti", "Ian Westlake / Sinisa Ubiparipovic"], ["1994", "Jean Harbor", "–", "–", "–"], ["2003", "Greg Sutton", "Gabriel Gervais", "David Fronimadis", "Martin Nash"], ["2000", "Jim Larkin", "–", "–", "–"], ["1995", "Lloyd Barker", "–", "–", "–"], ["2002", "Eduardo Sebrango", "Gabriel Gervais", "Jason DiTullio", "Zé Roberto"], ["1996", "Paolo Ceccarelli", "–", "–", "–"], ["2001", "Mauro Biello", "–", "–", "–"], ["1998", "Mauro Biello", "–", "–", "–"], ["1999", "N/A", "–", "–", "–"], ["2007", "Leonardo Di Lorenzo", "Mauricio Vincello", "Simon Gatti", "Matt Jordan"], ["1997", "Mauro Biello", "–", "–", "–"], ["2009", "David Testo", "Nevio Pizzolitto", "Adam Braz", "Stephen deRoux"], ["2004", "Gabriel Gervais", "Greg Sutton", "Zé Roberto", "Sandro Grande"], ["2006", "Mauricio Vincello", "Gabriel Gervais", "Andrew Weber", "Leonardo Di Lorenzo"], ["2005", "Mauro Biello", "Nevio Pizzolitto", "Mauricio Vincello", "Masahiro Fukazawa"]] | 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 number of canadians who have won mvp from 1993 to 2011? | 9 | 128 | Answer: |
Table InputTable: [["Pos", "No.", "Driver", "Team", "Laps", "Time/Retired", "Grid", "Laps Led", "Points"], ["18", "98", "Richard Antinucci", "Team 3G", "83", "+ 2 Laps", "19", "0", "12"], ["19", "7", "Danica Patrick", "Andretti Green Racing", "83", "+ 2 Laps", "12", "0", "12"], ["1", "9", "Scott Dixon", "Chip Ganassi Racing", "85", "1:46:05.7985", "3", "51", "52"], ["3", "10", "Dario Franchitti", "Chip Ganassi Racing", "85", "+ 30.0551", "6", "0", "35"], ["15", "13", "E. J. Viso", "HVM Racing", "84", "+ 1 Lap", "9", "0", "15"], ["14", "33", "Robert Doornbos (R)", "HVM Racing", "85", "+ 1:10.0812", "18", "0", "16"], ["17", "20", "Ed Carpenter", "Vision Racing", "84", "+ 1 Lap", "21", "0", "13"], ["16", "4", "Dan Wheldon", "Panther Racing", "84", "+ 1 Lap", "17", "0", "14"], ["6", "26", "Marco Andretti", "Andretti Green Racing", "85", "+ 46.7669", "13", "0", "28"], ["5", "27", "Hideki Mutoh", "Andretti Green Racing", "85", "+ 34.1839", "11", "0", "30"], ["20", "24", "Mike Conway (R)", "Dreyer & Reinbold Racing", "69", "Mechanical", "16", "0", "12"], ["11", "06", "Oriol Servià", "Newman/Haas/Lanigan Racing", "85", "+ 52.6215", "14", "0", "19"], ["10", "11", "Tony Kanaan", "Andretti Green Racing", "85", "+ 52.0810", "8", "0", "20"], ["8", "02", "Graham Rahal", "Newman/Haas/Lanigan Racing", "85", "+ 50.4517", "4", "0", "24"], ["13", "18", "Justin Wilson", "Dale Coyne Racing", "85", "+ 53.5768", "2", "28", "17"], ["12", "3", "Hélio Castroneves", "Penske Racing", "85", "+ 53.2362", "5", "0", "18"], ["2", "6", "Ryan Briscoe", "Penske Racing", "85", "+ 29.7803", "1", "6", "41"], ["7", "5", "Paul Tracy", "KV Racing Technology", "85", "+ 49.7020", "10", "0", "26"], ["9", "2", "Raphael Matos (R)", "Luczo-Dragon Racing", "85", "+ 51.2286", "15", "0", "22"], ["21", "23", "Milka Duno", "Dreyer & Reinbold Racing", "56", "Handling", "20", "0", "12"], ["4", "14", "Ryan Hunter-Reay", "A. J. Foyt Enterprises", "85", "+ 33.7307", "7", "0", "32"]] | 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 driver has the same amount of laps as richard antinucci? | Danica Patrick | 128 | Answer: |
Table InputTable: [["Rank", "Country", "Box Office", "Year", "Box office\\nfrom national films"], ["4", "United Kingdom", "$1.7 billion", "2012", "36.1% (2011)"], ["8", "Germany", "$1.3 billion", "2012", "–"], ["1", "Canada/United States", "$10.8 billion", "2012", "–"], ["11", "Italy", "$0.84 billion", "2013", "30% (2013)"], ["5", "France", "$1.7 billion", "2012", "33.3% (2013)"], ["6", "South Korea", "$1.47 billion", "2013", "59.7% (2013)"], ["-", "World", "$34.7 billion", "2012", "–"], ["2", "China", "$3.6 billion", "2013", "59% (2013)"], ["3", "Japan", "$1.88 billion", "2013", "61% (2013)"], ["12", "Brazil", "$0.72 billion", "2013", "17% (2013)"], ["7", "India", "$1.4 billion", "2012", "–"], ["10", "Australia", "$1.2 billion", "2012", "4.1% (2011)"], ["9", "Russia", "$1.2 billion", "2012", "–"]] | 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 county made the most in box office revenue? | Canada/United States | 128 | Answer: |
Table InputTable: [["Pos", "Team", "Played", "Won", "Draw", "Lost", "Goals For", "Goals Against", "Goal Difference", "Points", "Notes"], ["4", "ÍBV", "18", "8", "5", "5", "29", "17", "+12", "29", "Inter-Toto Cup"], ["10", "Leiftur", "18", "3", "7", "8", "24", "39", "-15", "16", "Relegated"], ["9", "Stjarnan", "18", "4", "5", "9", "18", "31", "-13", "17", "Relegated"], ["5", "ÍA", "18", "7", "5", "6", "21", "17", "+4", "26", ""], ["8", "Fram", "18", "4", "5", "9", "22", "33", "-11", "17", ""], ["6", "Keflavík", "18", "4", "7", "7", "21", "35", "-14", "19", ""], ["7", "Breiðablik", "18", "5", "3", "10", "29", "35", "-6", "18", ""], ["2", "Fylkir", "18", "10", "5", "3", "39", "16", "+23", "35", "UEFA Cup"], ["3", "Grindavík", "18", "8", "6", "4", "25", "18", "+7", "30", "UEFA Cup"], ["1", "KR", "18", "11", "4", "3", "27", "14", "+13", "37", "UEFA Champions League"]] | 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 least number of points earned? | 16 | 128 | Answer: |
Table InputTable: [["Season", "Team", "Country", "Division", "Apps", "Goals"], ["2008/09", "Dnipro Dnipropetrovsk", "Ukraine", "1", "22", "1"], ["2007/08", "Dnipro Dnipropetrovsk", "Ukraine", "1", "24", "0"], ["2009/10", "Dnipro Dnipropetrovsk", "Ukraine", "1", "28", "0"], ["2010/11", "Dnipro Dnipropetrovsk", "Ukraine", "1", "23", "0"], ["2006/07", "Dnipro Dnipropetrovsk", "Ukraine", "1", "12", "0"], ["2012/13", "Dnipro Dnipropetrovsk", "Ukraine", "1", "10", "1"], ["2011/12", "Dnipro Dnipropetrovsk", "Ukraine", "1", "16", "0"], ["2004", "CSKA Moscow", "Russia", "1", "0", "0"], ["2006", "Spartak Nizhny Novgorod", "Russia", "2", "36", "1"], ["2005", "CSKA Moscow", "Russia", "1", "0", "0"], ["2012/13", "Lokomotiv Moscow", "Russia", "1", "8", "0"], ["2013/14", "Lokomotiv Moscow", "Russia", "1", "14", "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 were the number of apps that team dnipro dnipropetrovsk had in the season of 2008/09? | 22 | 128 | Answer: |
Table InputTable: [["Source", "Date", "Population\\nRomania", "Population\\nSerbia", "Notes"], ["Romanian census", "1930", "10,012", "", "Romanian Banat only"], ["Romanian census", "1939", "9,951", "", "Romanian Banat only"], ["Karol Telbizov", "1940", "12,000", "", "Romanian Banat only; estimated"], ["Romanian census", "1956", "12,040", "", "Romania only"], ["Mihail Georgiev", "1942", "", "up to 4,500", "Serbian Banat only; estimated"], ["Hungarian statistics", "1880", "18,298", "18,298", ""], ["Romanian census", "1977", "9,267", "", "Romania only"], ["Dimo Kazasov", "1936", "", "3,200", "Serbian Banat only; estimated"], ["Romanian census", "2002", "6,486", "", "Romania only"], ["Yugoslav census", "1971", "", "3,745", "Serbian Banat only"], ["Hungarian statistics", "1910", "13,536", "13,536", "\"evidently underestimated\""], ["Hungarian statistics", "1900", "19,944", "19,944", ""], ["Serbian census", "2002", "", "1,658", "Serbia only"], ["Jozu Rill", "1864", "30,000–35,000", "30,000–35,000", ""], ["Various authors", "second half\\nof the 19th century", "22,000–26,000", "22,000–26,000", "\"sometimes including the Krashovani\""]] | 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 average population of banat bulgarians in romania from 1880 to 1910? | 17,259 | 128 | Answer: |
Table InputTable: [["Player", "Friendlies", "FIFA Confederations Cup", "FIFA World Cup Qual.", "Total Goals"], ["Milicic", "2", "-", "-", "2"], ["Chipperfield", "1", "-", "1", "2"], ["Zdrilic", "1", "-", "-", "1"], ["Cahill", "-", "-", "1", "1"], ["Colosimo", "1", "-", "-", "1"], ["Bresciano", "2", "-", "1", "3"], ["Aloisi", "1", "4", "-", "5"], ["Elrich", "1", "-", "-", "1"], ["Skoko", "-", "1", "-", "1"], ["Griffiths", "1", "-", "-", "1"], ["Viduka", "1", "-", "2", "3"], ["Thompson", "1", "-", "2", "3"], ["Culina", "-", "-", "1", "1"], ["Emerton", "-", "-", "2", "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 had the highest number of total goals? | Aloisi | 128 | Answer: |
Table InputTable: [["Sr. No.", "Train No.", "Name of the Train", "Arrival", "Departure", "Day"], ["1.", "18238", "Chhatisgarh Express", "01:23", "01:25", "Daily"], ["29.", "51830", "Agra-Nagpur Pass", "18:04", "18:05", "Daily"], ["12.", "51829", "Nagpur-Agra Pass", "09:41", "09:42", "Daily"], ["33.", "18237", "Chhatisgarh Express", "23:09", "23:10", "Daily"], ["25.", "12722", "Dakshin Express", "16:00", "16:02", "Daily"], ["34.", "51152", "Narkhed-New Amravati Pass", "N/a", "18:00", "Daily"], ["26.", "51183", "Bhusaval-Narkhed Pass", "16:00", "N/a", "Daily"], ["30.", "51293", "Nagpur-Amla Pass", "19:55", "20:00", "Daily"], ["35.", "51184", "Bhusaval-Narkhed Pass", "N/a", "09:00", "Daily"], ["8.", "51151", "New Amravati-Narkhed Pass", "08:30", "N/a", "Daily"], ["3.", "51294", "Amla-Nagpur Pass", "06:39", "06:40", "Daily"], ["14.", "12721", "Dakshin Express", "10:43", "10:44", "Daily"], ["17.", "11203", "Nagpur-Jaipur Weekly Express", "13:03", "13:05", "T"], ["11.", "16359", "Ernakulam-Patna Exp", "08:53", "08:55", "M"], ["18.", "12615", "Grand Trunk(GT) Exp", "13:30", "13:32", "Daily"], ["32.", "12159", "Amravati-Jabalpur SF", "22:30", "22:32", "Daily"], ["16.", "19714", "Sec-Jaipur Exp", "11:58", "12:00", "Tu"], ["15.", "12616", "Grand Trunk(GT) Exp", "10:49", "10:51", "Daily"], ["2.", "12160", "Jabalpur-Amravati SF", "04:51", "04:53", "Daily"], ["27.", "11204", "Jaipur-Nagpur Exp", "17:24", "17:25", "St"], ["31.", "12914", "Nagpur-Indore Tri. Exp", "20:08", "20:10", "M"], ["24.", "19713", "Jaipur-Sec Exp", "15:48", "15:50", "Tu"], ["13.", "12861", "Visakapatnam-Nizamuddin", "10:43", "10:44", "Daily"], ["21.", "16360", "Patna-Ernakulam Exp", "14:08", "14:10", "W"], ["10.", "11045", "Dikshsabhoomi Exp", "08:53", "08:55", "St"], ["9.", "22112", "Nagpur-Bhusaval SF", "08:37", "08:39", "M,T,St"], ["4.", "12913", "Indore-Nag Tri. Exp", "06:49", "06:51", "M"], ["6.", "12406", "Nizamuddin-Bhusaval Gondwana Exp", "07:25", "07:27", "M,St"], ["5.", "19301", "Indore-Yashwantpur Exp", "07:20", "07:25", "M"], ["22.", "11046", "Dikshsabhoomi Exp", "14:09", "14:10", "Tu"], ["7.", "12410", "Nizamuddin-Raigarh Gondwana Exp", "07:25", "07:27", "S,M,Tu,W,T,F"], ["23.", "22111", "Bhusaval_Nagpur SF", "14:36", "14:38", "S,W,F"], ["28.", "19302", "Yashwantpur-Indore Exp", "17:35", "17:40", "W"], ["20.", "12409", "Raigarh-H.Nizamuddin- Gondwana Exp", "14:08", "14:10", "M,W,T,F,St"]] | 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 train leaves the earliest on mondays? | Chhatisgarh Express | 128 | Answer: |
Table InputTable: [["Character", "Real name", "Home world", "Membership notes", "Powers"], ["Karate Kid II", "Myg", "Lythyl", "Joined as a replacement for Val Armorr, as revealed in Final Crisis: Legion of 3 Worlds #1 (October 2008), unlike his counterpart who did not join the original team prior to Crisis on Infinite Earths.\\nKilled by Radiation Roy in Final Crisis: Legion of 3 Worlds #3 (April 2009).", "Mastery of all known martial arts."], ["Dragonwing", "Marya Pai", "Earth", "First appeared in Legion of Super-Heroes vol. 6, #6 (December 2010) as a student at the Legion Academy.\\nJoined between Legion of Super-Heroes vol. 6, #16 (October 2011) and Legion of Super-Heroes vol. 7, #1 (November 2011).", "Fire breath and acid absorption."], ["Glorith II", "Glorith", "Unknown", "First appeared in Adventure Comics #523 (April 2011) as a student at the Legion Academy.\\nJoined between Legion of Super-Heroes vol. 6, #16 (October 2011) and Legion of Super-Heroes vol. 7, #1 (November 2011).", "Manipulation of mystical energies."], ["Chemical Kid", "Hadru Jamik", "Phlon", "First appeared in Legion of Super-Heroes vol. 6, #6 (December 2010) as a student at the Legion Academy.\\nJoined between Legion of Super-Heroes vol. 6, #16 (October 2011) and Legion of Super-Heroes vol. 7, #1 (November 2011).", "Catalyze chemical reactions."], ["Gates", "Ti'julk Mr'asz", "Vyrga", "First appeared in Legion of Super-Heroes vol. 4, #66 (March 1995).\\nJoined the Earth-247 team in Legion of Super-Heroes vol. 4, #76 (January 1996).\\nJoined the post-Infinite Crisis team in Final Crisis: Legion of 3 Worlds #5 (September 2009).", "Creation of teleportation \"gates\"."], ["Night Girl", "Lydda Jath", "Kathoon", "Pre-Crisis version first appeared in Adventure Comics #306 (March 1963).\\nLegion membership first mentioned by Starman in Justice Society of America vol. 3, #6 (July 2007) and confirmed in Action Comics #860 (February 2008).", "Super-strength when not in direct sunlight."], ["XS", "Jenni Ognats", "Aarok", "First appeared in Legionnaires #0 (October 1994); granddaughter of Barry Allen and first cousin of Bart Allen.\\nNative of the same universe as the post-Infinite Crisis team, as revealed in Final Crisis: Legion of 3 Worlds #3 (April 2009).\\nJoined the Earth-247 team in Legion of Super-Heroes vol. 4, #62 (November 1994).\\nJoined the post-Infinite Crisis team in Final Crisis: Legion of 3 Worlds #5 (September 2009).\\nPost-Flashpoint no longer listed as a member of the Legion.", "Superspeed."], ["Harmonia", "Harmonia Li", "Earth", "First appeared in Legion of Super-Heroes vol. 6, #1 (July 2010).\\nJoined between Legion of Super-Heroes vol. 6, #16 (October 2011) and Legion of Super-Heroes vol. 7, #1 (November 2011).", "Elemental."], ["Chameleon Girl", "Yera Allon", "Durla", "Pre-Crisis version first appeared (impersonating Shrinking Violet) in Legion of Super-Heroes vol. 2, #286 (April 1982).\\nTrue form and identity revealed in Legion of Super-Heroes vol. 2, #305 (November 1983).\\nLegion membership first revealed in Action Comics #861 (March 2008).", "Shapeshifting."], ["Comet Queen", "Grava", "Extal Colony", "Pre-Crisis version first appeared in Legion of Super-Heroes vol. 2, #304 (October 1983) as a student at the Legion Academy.\\nJoined between Legion of Super-Heroes vol. 6, #16 (October 2011) and Legion of Super-Heroes vol. 7, #1 (November 2011).", "Space flight, comet gas extrusion."]] | 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 legion member has a mastery of a number of martial arts? | Karate Kid II | 128 | Answer: |
Table InputTable: [["Year", "Network", "NASCAR\\nCountdown", "Lap-by-lap", "Color commentator(s)", "Pit reporters", "Ratings", "Viewers"], ["2007", "ESPN", "Brent Musburger\\nSuzy Kolber\\nBrad Daugherty", "Jerry Punch", "Rusty Wallace\\nAndy Petree", "Dave Burns\\nJamie Little\\nAllen Bestwick\\nMike Massaro", "4.2 (4.9 cable)", "6.574 million"], ["2009", "ESPN", "Allen Bestwick\\nRusty Wallace\\nBrad Daugherty\\nRay Evernham", "Jerry Punch", "Dale Jarrett\\nAndy Petree", "Dave Burns\\nJamie Little\\nShannon Spake\\nVince Welch", "4.1 (4.8 cable)", "6.487 million"], ["2008", "ESPN", "Allen Bestwick\\nRusty Wallace\\nBrad Daugherty", "Jerry Punch", "Dale Jarrett\\nAndy Petree", "Dave Burns\\nJamie Little\\nShannon Spake\\nMike Massaro", "4.3 (5.1 cable)", "6.668 million"], ["2011", "ESPN", "Nicole Briscoe\\nRusty Wallace\\nBrad Daugherty", "Allen Bestwick", "Dale Jarrett\\nAndy Petree", "Dave Burns\\nJamie Little\\nJerry Punch\\nVince Welch", "4.0 (4.6 cable)", "6.337 million"], ["2010", "ESPN", "Allen Bestwick\\nRusty Wallace\\nBrad Daugherty\\nRay Evernham", "Marty Reid", "Dale Jarrett\\nAndy Petree", "Dave Burns\\nJamie Little\\nJerry Punch\\nVince Welch", "3.6 (4.2 cable)", "5.709 million"], ["2012", "ESPN", "Nicole Briscoe\\nRusty Wallace\\nBrad Daugherty\\nRay Evernham", "Allen Bestwick", "Dale Jarrett\\nAndy Petree", "Dave Burns\\nJamie Little\\nJerry Punch\\nVince Welch", "3.3", "5.1 million"], ["2014", "ESPN", "", "", "", "", "", ""], ["2013", "ESPN", "Nicole Briscoe\\nRusty Wallace\\nBrad Daugherty\\nRay Evernham", "Allen Bestwick", "Dale Jarrett\\nAndy Petree", "Dave Burns\\nJamie Little\\nJerry Punch\\nVince Welch", "3.6", "5.5 million"]] | 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 year had the most viewers? | 2008 | 128 | Answer: |
Table InputTable: [["#", "Weekend End Date", "Film", "Box Office"], ["9", "March 1, 1998", "Titanic", "£3,403,199"], ["7", "February 15, 1998", "Titanic", "£3,849,120"], ["11", "March 15, 1998", "Titanic", "£2,469,191"], ["8", "February 22, 1998", "Titanic", "£3,657,613"], ["15", "April 12, 1998", "Titanic", "£1,373,363"], ["10", "March 8, 1998", "Titanic", "£3,010,921"], ["13", "March 29, 1998", "Titanic", "£2,223,046"], ["12", "March 22, 1998", "Titanic", "£1,953,082"], ["16", "April 19, 1998", "Titanic", "£981,940"], ["6", "February 8, 1998", "Titanic", "£4,274,375"], ["4", "January 25, 1998", "Titanic", "£4,805,270"], ["14", "April 5, 1998", "Titanic", "£1,504,551"], ["5", "February 1, 1998", "Titanic", "£4,773,404"], ["32", "August 9, 1998", "Armageddon", "£2,732,785"], ["33", "August 16, 1998", "Armageddon", "£2,243,095"], ["29", "July 19, 1998", "Godzilla", "£4,176,960"], ["30", "July 26, 1998", "Godzilla", "£2,145,088"], ["31", "August 2, 1998", "Lost in Space", "£3,127,079"], ["22", "May 31, 1998", "Deep Impact", "£1,070,805"], ["49", "December 6, 1998", "Rush Hour", "£1,809,093"], ["18", "May 3, 1998", "Scream 2", "£2,493,950"], ["39", "September 27, 1998", "There's Something About Mary", "£2,076,411"], ["1", "January 4, 1998", "Starship Troopers", "£2,221,631"], ["21", "May 24, 1998", "Deep Impact", "£1,601,651"], ["2", "January 11, 1998", "The Jackal", "£1,422,193"], ["41", "October 11, 1998", "The Truman Show", "£2,210,999"], ["20", "May 17, 1998", "Deep Impact", "£1,763,805"], ["19", "May 10, 1998", "Scream 2", "£1,213,184"], ["37", "September 13, 1998", "Saving Private Ryan", "£2,704,522"], ["43", "October 25, 1998", "Small Soldiers", "£1,137,725"], ["51", "December 20, 1998", "Rush Hour", "£744,783"], ["3", "January 18, 1998", "The Devil's Advocate", "£1,300,773"], ["38", "September 20, 1998", "Saving Private Ryan", "£2,077,362"], ["23", "June 7, 1998", "The Wedding Singer", "£1,031,660"], ["42", "October 18, 1998", "The Truman Show", "£1,687,037"], ["27", "July 5, 1998", "Six Days Seven Nights", "£908,713"], ["24", "June 14, 1998", "The Wedding Singer", "£974,719"], ["46", "November 15, 1998", "Antz", "£1,737,782"], ["50", "December 13, 1998", "Rush Hour", "£1,179,123"], ["44", "November 1, 1998", "The Exorcist", "£2,186,977"], ["25", "June 21, 1998", "City of Angels", "£1,141,654"]] | 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 weeks titanic was the number one at the uk box office in 1998 | 13 | 128 | Answer: |
Table InputTable: [["Name", "Route number(s)", "Length (mi)", "Location", "Notes"], ["Massachusetts Turnpike", "*", "138.1", "West Stockbridge\\nto Boston", "The Mass Pike is a toll road running from the New York state border to downtown Boston. It serves as the main cross-state freeway connecting the western and eastern portions of the state. The \"Pike\" carries the easternmost 138 miles (222 km) of cross-country Interstate 90."], ["Worcester-Providence Turnpike", "*", "20.99", "Millville to Worcester", "Route 146 is a freeway that, along with Rhode Island's Route 146, serves to connect the metropolitan areas of Providence and Worcester. The entire route starts from I-95 in Providence, with the Massachusetts section picking up at the state line in Millville. The highway runs 21 miles (34 km) northward, intersecting the Mass Pike (I-90) in Worcester, and terminating at I-290 shortly thereafter.\\n- Route 122A runs along the highway between Exits 9 and 12, concurrently with Route 146."], ["Wilbur Cross Highway", "*", "8.0", "Sturbridge", "I-84 in Massachusetts is designated the Wilbur Cross Highway. It runs 8 miles (13 km) from the Connecticut state border to the Mass Pike at Exit 9."], ["Pilgrims Highway", "", "42.5", "Bourne to Braintree", "The Pilgrims Highway is the southern portion of Route 3, a 42-mile (68 km) long freeway which serves as a connector between Cape Cod (via U.S. Route 6) and the Boston metropolitan area (via I-93 and I-95).\\n- U.S. Route 44 runs along the highway between Exits 6 and 7."], ["East Boston Expressway", "", "1.2", "Boston", "The East Boston Expressway comprises the first 1.2 miles (1.9 km) of Route 1A's northern segment. It stretches from I-93 Exit 24 at the southern end of the Callahan Tunnel (northbound) and the Sumner Tunnel (southbound) to just northeast of the interchange with Route 145 in East Boston, near the eastern end of the Mass Pike."], ["Boston-Worcester Turnpike", "", "", "Worcester to Boston", "Route 9 between Worcester and Boston is mostly a divided full-access highway with traffic light-controlled intersections which serves as one of the main alternatives to the Massachusetts Turnpike. Many shopping centers, car dealers, full-service restaurants and businesses line the roadway on this stretch, especially in Framingham, such as Barnes & Noble, Marshalls, T.G.I. Fridays, Kohl's, Toys \"R\" Us, Best Buy, Olive Garden and Walmart. This stretch of the roadway is also encompassed in the Golden Triangle district of Massachusetts."], ["Lydia Taft Highway", "*", "3", "Uxbridge", "Route 146A in Massachusetts is designated as the Lydia Taft Highway, which runs from the Rhode Island state border to Route 122 in Uxbridge."], ["Taunton-New Bedford Expressway\\n(Alfred M. Bessette Memorial Highway)", "", "19.3", "New Bedford to Taunton", "The New Bedford Expressway comprises the southern 19 miles (31 km) of Route 140, and serves as a freeway connection between U.S. Route 6 in New Bedford and Route 24 (Exit 12) in Taunton, near I-495."], ["Northeast Expressway", "*", "4.1", "Boston,\\nChelsea,\\nRevere", "This section of U.S. Route 1 runs from I-93 Exit 27 (Tobin Bridge) to an interchange with Route 60 in Revere. This was originally supposed to be part of I-95, but I-95 was cancelled in Boston, with I-93 and US-1 taking its place."], ["Central Artery\\n(John F. Fitzgerald Expressway)", "", "3.18", "Boston", "The Central Artery is the portion of I-93 in downtown Boston, which runs from Massachusetts Ave. (just south of Exit 20) north to U.S. Route 1's departure at Exit 27.\\nRoute 3 leaves the Artery at Exit 26."], ["Memorial Drive", "", "4.12", "Cambridge", "U.S. Route 3 and MA Route 3 connect to each other on Memorial Drive, which runs from the Fresh Pond Parkway to Main Street.\\nRoute 2 travels along Memorial Drive with US-3 and leaves via the Boston University Bridge."], ["Mid-Cape Highway", "", "36.6", "Bourne to Orleans", "The Mid-Cape Highway is the main highway on Cape Cod, a 36-mile (58 km) long freeway running from Route 3 and the Sagamore Bridge east to the Orleans Rotary."]] | 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 massachusetts turnpike? | 138.1 | 128 | Answer: |
Table InputTable: [["Rank", "Player", "From", "Transfer Fee\\n(€ millions)", "Year"], ["1.", "Neymar", "Santos FC", "86.0", "2013"], ["3.", "Alexis Sánchez", "Udinese", "26+11(add ons)", "2011"], ["2.", "Cesc Fàbregas", "Arsenal", "29+5(variables)", "2011"], ["4.", "Javier Mascherano", "Liverpool", "26.8", "2010"], ["7.", "Adriano", "Sevilla", "13.5", "2010"], ["6.", "Jordi Alba", "Valencia", "14.0", "2012"], ["5.", "Alex Song", "Arsenal", "19.0", "2012"]] | 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 player had the most transfer fee amount? | Neymar | 128 | Answer: |
Table InputTable: [["Year", "Team Record\\nW", "Team Record\\nL", "Playoffs"], ["2010", "5", "5", "Did Not Make Playoffs"], ["2009", "5", "5", "Did Not Make Playoffs"], ["2005", "3", "5", "Did Not Make Playoffs"], ["2004", "7", "2", "2nd Qualifier, Region 2"], ["2008", "7", "4", "2nd Qualifier, Region 2"], ["2007", "13", "1", "1st Qualifier, Region 2"], ["2001", "7", "2", "3rd Qualifier, Region 2"], ["2003", "8", "1", "2nd Qualifier, Region 2"], ["2006", "5", "4", "4th Qualifier, Region 2"], ["2002", "8", "1", "2nd Qualifier, Region 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:name a season that had more than 7 wins but less than 10. | 2002 | 128 | Answer: |
Table InputTable: [["Date", "Opponent", "Venue", "Result", "Attendance", "Scorers"], ["29 August 1992", "Manchester City", "A", "3–3", "27,288", "Jobson, Milligan, Halle"], ["26 January 1993", "Manchester City", "H", "0–1", "14,903", ""], ["21 November 1992", "Manchester United", "A", "0–3", "33,497", ""], ["26 September 1992", "Blackburn Rovers", "A", "0–2", "18,393", ""], ["13 March 1993", "Norwich City", "A", "0–1", "19,597", ""], ["17 October 1992", "Sheffield Wednesday", "A", "1–2", "24,485", "Milligan"], ["24 October 1992", "Aston Villa", "H", "1–1", "13,457", "Olney"], ["5 September 1992", "Coventry City", "H", "0–1", "11,254", ""], ["23 January 1993", "Coventry City", "A", "0–3", "10,544", ""], ["15 August 1992", "Chelsea", "A", "1–1", "20,699", "Henry"], ["31 October 1992", "Southampton", "A", "0–1", "10,827", ""], ["22 February 1993", "Sheffield United", "A", "0–2", "14,628", ""], ["19 September 1992", "Ipswich Town", "H", "4–2", "11,150", "Marshall, Sharp, Halle, Henry"], ["26 August 1992", "Arsenal", "A", "0–2", "20,796", ""], ["5 May 1993", "Liverpool", "H", "3–2", "15,381", "Beckford, Olney (2)"], ["20 March 1993", "Queens Park Rangers", "H", "2–2", "10,946", "Henry, Adams"], ["22 March 1993", "Middlesbrough", "A", "3–2", "12,290", "Bernard, Olney, Ritchie"], ["9 March 1993", "Manchester United", "H", "1–0", "17,106", "Adams"], ["30 January 1993", "Nottingham Forest", "A", "0–2", "21,240", ""], ["16 January 1993", "Blackburn Rovers", "H", "0–1", "13,742", ""], ["9 January 1993", "Ipswich Town", "A", "2–1", "15,025", "Brennan, Bernard"], ["1 September 1992", "Leeds United", "H", "2–2", "13,848", "Olney (2)"], ["4 October 1992", "Everton", "H", "1–0", "13,013", "Jobson"], ["28 November 1992", "Middlesbrough", "H", "4–1", "12,401", "Halle, Pointon, Sharp, Adams"], ["5 December 1992", "Queens Park Rangers", "A", "2–3", "11,804", "Adams, Olney"], ["10 April 1993", "Liverpool", "A", "0–1", "36,129", ""], ["13 April 1993", "Sheffield United", "H", "1–1", "14,795", "Ritchie"], ["20 February 1993", "Arsenal", "H", "0–1", "12,311", ""], ["27 February 1993", "Everton", "A", "2–2", "18,025", "Adams (2, 1 pen)"], ["2 May 1993", "Aston Villa", "A", "1–0", "37,247", "Henry"], ["17 April 1993", "Tottenham Hotspur", "A", "1–4", "26,663", "Beckford"], ["13 February 1993", "Leeds United", "A", "0–2", "27,654", ""], ["9 November 1992", "Norwich City", "H", "2–3", "11,081", "Sharp, Marshall"], ["7 April 1993", "Sheffield Wednesday", "H", "1–1", "12,312", "Pointon"]] | 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 games were not attended by more than 15,000 people? | 26 | 128 | Answer: |
Table InputTable: [["District", "Incumbent", "Party", "First\\nelected", "Result", "Candidates"], ["Maryland 8", "Connie Morella", "Republican", "1986", "Lost re-election\\nDemocratic gain", "Chris Van Hollen (D) 51.71%\\nConnie Morella (R) 47.49%\\nStephen Bassett (UN) 0.73%"], ["Maryland 6", "Roscoe Bartlett", "Republican", "1992", "Re-elected", "Roscoe Bartlett (R) 66.11%\\nDonald DeArmon (D) 33.80%"], ["Maryland 4", "Albert Wynn", "Democratic", "1992", "Re-elected", "Albert Wynn (D) 78.57%\\nJohn Kimble (R) 20.82%"], ["Maryland 1", "Wayne Gilchrest", "Republican", "1990", "Re-elected", "Wayne Gilchrest (R) 76.67%\\nAnn Tamlyn (D) 23.16%"], ["Maryland 5", "Steny Hoyer", "Democratic", "1981", "Re-elected", "Steny Hoyer (D) 69.27%\\nJoseph Crawford (R) 30.52%"], ["Maryland 3", "Ben Cardin", "Democratic", "1986", "Re-elected", "Ben Cardin (D) 65.72%\\nScott Conwell (R) 34.18%"], ["Maryland 7", "Elijah Cummings", "Democratic", "1996", "Re-elected", "Elijah Cummings (D) 73.53%\\nJoseph Ward (R) 26.38%"], ["Maryland 2", "Robert Ehrlich", "Republican", "1994", "Retired to run for Governor\\nDemocratic gain", "Dutch Ruppersberger (D) 54.16%\\nHelen Bentley (R) 45.57%"]] | 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:connie morella was last elected in which year? | 1986 | 128 | Answer: |
Table InputTable: [["Represented", "Contestant", "Age", "Height", "Hometown"], ["Santiago", "Karina Luisa Betances Cabrera", "21", "1.80", "Santiago de los Caballeros"], ["Santo Domingo", "Yisney Lina Lagrange Méndez", "19", "1.82", "Pedro Brand"], ["Espaillat", "Angela María García Ruíz", "26", "1.77", "Moca"], ["Azua", "Alicia Fernández de la Cruz", "23", "1.69", "Santo Domingo"], ["Salcedo", "Rossemely Cruz Logroño", "26", "1.76", "Salcedo"], ["La Romana", "Alina Charlin Espinal Luna", "19", "1.81", "La Romana"], ["Independencia", "Joany Marleny Sosa Peralta", "20", "1.82", "Jimaní"], ["Com. Dom. EU", "Sandra Elisabeth Tavares Ruíz", "19", "1.80", "Newark"], ["Monte Cristi", "Grace Stephany Mota Grisanty", "18", "1.75", "San Fernando de Monte Cristi"], ["Distrito Nacional", "Aimeé Elaine Melo Hernández", "23", "1.73", "Santo Domingo"], ["Peravia", "Mariela Joselin Rosario Jiménez", "25", "1.86", "Santo Domingo"], ["Valverde", "Fania Miguelina Marte Lozada", "22", "1.73", "Mao"], ["Barahona", "Lucía Magdalena Alvarado Suarez", "20", "1.71", "Santo Domingo"], ["Duarte", "Paola Saint-Hilaire Arias", "20", "1.79", "Santiago de los Caballeros"], ["San Cristóbal", "Daniela Teresa Peguero Brito", "24", "1.74", "Santo Domingo"], ["Puerto Plata", "Sheila Massiel Castíllo Domínguez", "18", "1.83", "Altamira"], ["La Vega", "Catherine Mabel Ramírez Rosario", "21", "1.83", "Santiago de los Caballeros"], ["La Altagracia", "Ana Carolina Viñas Machado", "22", "1.84", "Santiago de los Caballeros"]] | 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 contestants are 1.80 meters tall or more? | 9 | 128 | Answer: |
Table InputTable: [["Speed", "Date", "Country", "Train", "Arr.", "Power", "State", "Comments"], ["202.6 km/h (126 mph)", "1938-07-03", "UK", "LNER Class A4 No. 4468 Mallard", "Loc", "Steam", "Unkn.", "Downhill grade. Data indicates peak speed 202.6 km/h (126 mph), mean speed (half-mile) 201.2 km/h (125 mph). Mallard suffered an overheated crankpin during the run, but was repaired and returned to traffic within 9 days."], ["182.4 km/h (113 mph)", "1972-10-11", "Germany", "BR 18 201", "Loc", "Steam", "Unkn.", "The fastest operational steam locomotive as of 2011.[citation needed]"], ["200.4 km/h (125 mph)", "1936-05-11", "Germany", "Borsig DRG series 05 002", "Loc", "Steam", "Unkn.", "Level grade.[citation needed]"], ["185.07 km/h (115 mph)", "1905-06-11", "USA", "Pennsylvania Railroad E2 #7002", "Loc", "Steam", "Unmod.", "Claimed.[by whom?] Clocked at Crestline, Ohio at 127.1 mph (205 km/h) in 1905. However PRR Steam Locomotives did not carry speedometers at that time, speed was calculated by measuring time between mile markers, so this is not recognized as a speed record.[citation needed]"], ["161 km/h (100 mph)", "1934-11-30", "UK", "LNER Class A3 4472 Flying Scotsman", "Loc", "Steam", "Unmod.", "In 1934, Flying Scotsman achieved the first authenticated 100 mph (161 km/h) by a steam locomotive."], ["164 km/h (102 mph)", "1904-05-09", "UK", "GWR 3700 Class 3440 City of Truro", "Loc", "Steam", "Unmod.", "Claimed[by whom?] to be the first steam locomotive to reach100 mph (161 km/h).[citation needed]"], ["180.3 km/h (112 mph)", "1935-09-29", "UK", "LNER Class A4 2509 Silver Link", "Loc", "Steam", "Unkn.", "Authenticated. Some sources say 112.5 mph.[citation needed]"], ["168.5 km/h (105 mph)", "1935-03-05", "UK", "LNER Class A3 No. 2750 Papyrus", "Loc", "Steam", "Unmod.", "First run at 100+ mph with complete, surviving documentation.[citation needed]"], ["166.6 km/h (104 mph)", "1934-07-20", "USA", "Milwaukee Road class F6 #6402", "Loc", "Steam", "Unmod", "A point between Oakwood, Illinois and Lake, Wisconsin. Also averaged 75.5 mph (122 km/h) on 85 miles (137 km) from Chicago, Illinois to Milwaukee, and 89.92 mph (145 km/h) for a 68.9 miles (110.9 km) stretch"], ["145 km/h (90 mph)", "1895-08-22", "UK", "LNWR No. 790 Hardwicke", "Loc", "Steam", "Unmod.", "Maximum speed claimed[by whom?], although average speed record was authenticated.[citation needed]"], ["131.6 km/h (82 mph)", "1854-06", "UK", "Bristol & Exeter Railway #41", "Loc", "Steam", "Unmod.", "Broad gauge[citation needed]"], ["8 km/h (5 mph)", "1804-02-21", "UK", "Richard Trevithick's world's first railway steam locomotive", "Loc", "Steam", "Unmod.", "[citation needed]"], ["125.6 km/h (78 mph)", "1850", "UK", "Great Britain", "Loc", "Steam", "Unmod.", "80 mph (129 km/h) claimed[by whom?][citation needed]"], ["181.1 km/h (113 mph)", "1935-04-05", "USA", "Milwaukee Road class A #2", "Loc", "Steam", "Unkn.", "Claimed[by whom?] to have sustained 112.5 mph (181 km/h) for 14 miles (23 km). Average speed for 136 miles (219 km) between Milwaukee and New Lisbon, Wisconsin was 74.9 mph (121 km/h)."]] | 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 much faster was the train lner class a4 no. 4468 mallard than borsig drg series 05 002 (in mph)? | 1 mph | 128 | Answer: |
Table InputTable: [["Outcome", "No.", "Date", "Tournament", "Surface", "Opponent", "Score"], ["Winner", "3.", "7 June 2011", "Campobasso, Italy", "Clay", "Alizé Lim", "6–2, 6–4"], ["Runner-up", "8.", "9 July 2007", "Biella, Italy", "Clay", "Agnieszka Radwańska", "6–3, 6–3"], ["Winner", "4.", "20 June 2011", "Rome, Italy", "Clay", "Laura Thorpe", "6–3, 6–0"], ["Runner-up", "12.", "27 August 2012", "Bagnatica, Italy", "Clay", "Maria-Elena Camerin", "7–6(5), 6–4"], ["Runner-up", "7.", "9 April 2007", "Civitavecchia, Italy", "Clay", "Darya Kustova", "3–6, 6–4, 6–4"], ["Runner-up", "11.", "14 June 2011", "Padova, Italy", "Clay", "Kristina Mladenovic", "3–6, 6–4, 6–0"], ["Winner", "2.", "18 October 2010", "Seville, Spain", "Clay", "Andrea Gámiz", "6–0, 6–1"], ["Winner", "5.", "4 September 2012", "Mestre, Italy", "Clay", "Estrella Cabeza Candela", "6–1, 3–6, 6–1"], ["Runner-up", "1.", "6 October 2003", "Bari, Italy", "Clay", "Bettina Pirker", "6–2, 7–5"], ["Runner-up", "9.", "11 October 2010", "Settimo San Pietro, Italy", "Clay", "Anastasia Grymalska", "4–6, 6–2, 7–5"], ["Runner-up", "3.", "1 May 2006", "Catania, Italy", "Clay", "María José Martínez Sánchez", "6–3, 4–6, 6–4"], ["Runner-up", "4.", "31 July 2006", "Martina Franca, Italy", "Clay", "Margalita Chakhnashvili", "6–3, 7–5"], ["Winner", "1.", "25 July 2006", "Monteroni D'Arbia, Italy", "Clay", "Edina Gallovits-Hall", "6–2, 6–1"], ["Runner-up", "2.", "14 June 2005", "Lenzerheide, Switzerland", "Clay", "Danica Krstajić", "6–2, 7–5"], ["Runner-up", "6.", "3 April 2007", "Dinan, France", "Clay (i)", "Maša Zec Peškirič", "6–4, 6–2"], ["Runner-up", "10.", "16 November 2010", "Mallorca, Spain", "Clay", "Diana Enache", "6–4, 6–2"], ["Runner-up", "13.", "12 May 2013", "Trnava, Slovakia", "Clay", "Barbora Záhlavová-Strýcová", "6–2, 6–4"], ["Runner-up", "5.", "13 March 2007", "Orange, USA", "Hard", "Naomi Cavaday", "6–1, 6–1"]] | 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 times did the tournament occur in italy before 2008? | 6 | 128 | Answer: |
Table InputTable: [["Year", "Film", "Role", "Language", "Notes"], ["2009", "Love Guru", "Kushi", "Kannada", "Filmfare Award for Best Actress - Kannada"], ["2012", "18th Cross", "Punya", "Kannada", ""], ["2010", "Krishnan Love Story", "Geetha", "Kannada", "Filmfare Award for Best Actress - Kannada\\nUdaya Award for Best Actress"], ["2013", "Dilwala", "Preethi", "Kannada", ""], ["2013", "Bahaddoor", "Anjali", "Kannada", "Filming"], ["2012", "Alemari", "Neeli", "Kannada", ""], ["2013", "Kaddipudi", "Uma", "Kannada", ""], ["2008", "Moggina Manasu", "Chanchala", "Kannada", "Filmfare Award for Best Actress - Kannada\\nKarnataka State Film Award for Best Actress"], ["2012", "Addhuri", "Poorna", "Kannada", "Udaya Award for Best Actress\\nNominated — SIIMA Award for Best Actress\\nNominated — Filmfare Award for Best Actress – Kannada"], ["2012", "Sagar", "Kajal", "Kannada", ""], ["2011", "Hudugaru", "Gayithri", "Kannada", "Nominated, Filmfare Award for Best Actress – Kannada"], ["2010", "Gaana Bajaana", "Radhey", "Kannada", ""], ["2012", "Drama", "Nandini", "Kannada", ""], ["2009", "Olave Jeevana Lekkachaara", "Rukmini", "Kannada", "Innovative Film Award for Best Actress"], ["2012", "Breaking News", "Shraddha", "Kannada", ""], ["2014", "Mr. & Mrs. Ramachari", "", "", "Announced"], ["2014", "Endendigu", "", "", "Filming"]] | 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 role of kushi was in 18th cross or love guru? | Love Guru | 128 | Answer: |
Table InputTable: [["Designation", "Keel Laid", "Launched", "Commissioned", "Fate"], ["PE-38", "30 January 1919", "29 March 1919", "30 July 1919", "In service during WWII\\nSold 3 March 1947"], ["PE-55", "17 March 1919", "22 July 1919", "10 October 1919", "In service during WWII\\nSold 3 March 1947"], ["PE-57", "25 March 1919", "29 July 1919", "15 October 1919", "In service during WWII\\nSold 5 March 1947"], ["PE-19", "6 August 1918", "30 January 1919", "25 June 1919", "In service during WWII\\nDestroyed 6 August 1946"], ["PE-32", "30 November 1918", "15 March 1919", "4 September 1919", "In service during WWII\\nSold 3 March 1947"], ["PE-27", "22 October 1918", "1 March 1919", "14 July 1919", "In service during WWII\\nSold 4 June 1946"], ["PE-56", "25 March 1919", "15 August 1919", "26 October 1919", "In service during WWII\\nTorpedoed by U-853 off Portland, Maine, on 23 April 1945"], ["PE-44", "20 February 1919", "24 May 1919", "30 September 1919", "Disposed of 14 May 1938"], ["PE-58", "25 March 1919", "2 August 1919", "20 October 1919", "Disposed of 30 June 1940"], ["PE-12", "13 July 1918", "12 November 1918", "6 November 1919", "Sold 30 December 1935"], ["PE-17", "3 August 1918", "1 February 1919", "3 July 1919", "Wrecked off Long Island, New York 22 May 1922"], ["PE-47", "3 March 1919", "19 June 1919", "4 October 1919", "Sold 30 December 1935"], ["PE-7", "8 June 1918", "5 October 1918", "24 November 1918", "Expended as target 30 November 1934"], ["PE-48", "3 March 1919", "24 May 1919", "8 October 1919", "Sold 10 October 1946"], ["PE-53", "17 March 1919", "13 August 1919", "20 October 1919", "Sold 26 August 1938"], ["PE-36", "22 January 1919", "22 March 1919", "20 August 1919", "Sold 27 February 1936"], ["PE-35", "13 January 1919", "22 March 1919", "22 August 1919", "Sold 7 June 1938"], ["PE-46", "24 February 1919", "24 May 1919", "3 October 1919", "Sold 10 December 1936"], ["PE-5", "28 May 1918", "28 September 1918", "19 November 1918", "Sold 11 June 1930"], ["PE-3", "16 May 1918", "11 September 1918", "11 November 1918", "Sold 11 June 1930"], ["PE-4", "21 May 1918", "15 September 1918", "14 November 1918", "Sold 11 June 1930"], ["PE-9", "17 June 1918", "8 November 1918", "27 October 1919", "Sold 26 May 1930"], ["PE-6", "3 June 1918", "16 October 1918", "21 November 1918", "Expended as target 30 November 1934"], ["PE-31", "19 November 1918", "8 March 1919", "14 August 1919", "Sold 18 May 1923"], ["PE-54", "17 March 1919", "17 July 1919", "10 October 1919", "Sold 26 May 1930"], ["PE-14", "20 July 1918", "23 January 1919", "17 June 1919", "Expended as target 22 November 1934"], ["PE-43", "17 February 1919", "17 May 1919", "2 October 1919", "Sold 26 May 1930"]] | 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 fate of the last ship on this chart? | Sold 29 August 1938 | 128 | Answer: |
Table InputTable: [["Position", "Officer", "current officers", "superseded by", "Royal Household"], ["1", "Lord High Steward", "vacant", "Justiciar", "Lord Steward"], ["7", "Lord High Constable", "vacant", "Earl Marshal", "Master of the Horse"], ["3", "Lord High Treasurer", "in commission", "", ""], ["6", "Lord Great Chamberlain", "The Marquess of Cholmondeley", "Lord High Treasurer", "Lord Chamberlain"], ["9", "Lord High Admiral", "HRH The Duke of Edinburgh", "", ""], ["2", "Lord High Chancellor", "The Rt Hon Chris Grayling, MP", "", ""], ["8", "Earl Marshal", "The Duke of Norfolk", "", "Master of the Horse"], ["4", "Lord President of the Council", "The Rt Hon Nick Clegg, MP", "", ""], ["5", "Lord Privy Seal", "The Rt Hon Andrew Lansley, CBE, MP", "", ""]] | 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 only officer superseded by justiciar? | Lord High Steward | 128 | Answer: |
Table InputTable: [["Week", "Date", "Result", "Record", "Opponent", "Points For", "Points Against", "First Downs", "Attendance"], ["2", "September 25", "Win", "2–0", "New York Giants", "41", "21", "25", "64,215"], ["7", "October 30", "Win", "7–0", "Detroit Lions", "37", "0", "20", "63,160"], ["9", "November 14", "Loss", "8–1", "St. Louis Cardinals", "17", "24", "16", "64,038"], ["12", "December 4", "Win", "10–2", "Philadelphia Eagles", "24", "14", "19", "60,289"], ["10", "November 20", "Loss", "8–2", "at Pittsburgh Steelers", "13", "28", "20", "49,761"], ["5", "October 16", "Win", "5–0", "Washington Redskins", "34", "16", "23", "62,115"], ["4", "October 9", "Win", "4–0", "at St. Louis Cardinals", "30", "24", "22", "50,129"], ["3", "October 2", "Win", "3–0", "Tampa Bay Buccaneers", "23", "7", "23", "55,316"], ["8", "November 6", "Win", "8–0", "at New York Giants", "24", "10", "13", "74,532"], ["11", "November 27", "Win", "9–2", "at Washington Redskins", "14", "7", "19", "55,031"], ["14", "December 18", "Win", "12–2", "Denver Broncos", "14", "6", "15", "63,752"], ["1", "September 18", "Win", "1–0", "at Minnesota Vikings", "16", "10", "16", "47,678"], ["13", "December 12", "Win", "11–2", "at San Francisco 49ers", "42", "35", "24", "55,851"], ["6", "October 23", "Win", "6–0", "at Philadelphia Eagles", "16", "10", "17", "65,507"]] | 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:name a month with no losses. | September | 128 | Answer: |
Table InputTable: [["Region", "Physician (GP & specialist)", "Physician : Population Ratio", "Health Officer", "HO : Population Ratio", "All Nurses", "Nurse : Population Ratio", "Mid-wives", "Mid Wife: Population Ratio", "HEW*", "HEW : Population Ratio"], ["Addis Ababa", "934", "1:3,056", "170", "1:16,791", "3,377", "1:845", "244", "1:11,699", "NA", "-"], ["Ben-Gumuz", "12", "1:59,309", "42", "1:16,945", "452", "1:1,575", "37", "1:19,235", "499", "1:1,426"], ["SNNPR", "242", "1:65,817", "220", "1:72,398", "3,980", "1:4,002", "316", "1:50,404", "7,915", "1:2,012"], ["Gambella", "13", "1:25,585", "13", "1:25,585", "91", "1:3,655", "4", "1:83,150", "457", "1:728"], ["Tigray", "101", "1:44,880", "188", "1:24,111", "2,332", "1:1,944", "185", "1:24,502", "1,433", "1:3,163"], ["Somalia", "71", "1:65,817", "12", "1:389,415", "314", "1:14,882", "45", "1:103,844", "1,427", "1:3,275"], ["Afar", "15", "1:98,258", "29", "1:50,823", "185", "1:7,967", "−", "−", "572", "1:2,577"], ["Oromia", "378", "1:76,075", "448", "1:64,189", "5,040", "1:5,706", "287", "1:100,197", "13856", "1:2,075"], ["Amhara", "304", "1:58,567", "434", "1:41,024", "3,790", "1:4,698", "212", "1:83,983", "7,471", "1:2,383"], ["Diredawa", "53", "1:6,796", "19", "1:18,957", "272", "1:1,324", "20", "1:18,009", "142", "1:2,537"], ["Harari", "29", "1:6,655", "31", "1:6,226", "276", "1:699", "29", "1:6,655", "47", "1:4,106"]] | 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 regions have more than 100 physicians (gp & specialist)? | 5 | 128 | Answer: |
Table InputTable: [["Season", "Winning Team", "Score", "Losing Team", "Score", "Location", "Stadium"], ["1970–71", "Baltimore Colts (1)", "27", "Oakland Raiders", "17", "Baltimore, Maryland", "Memorial Stadium"], ["2008–09", "Pittsburgh Steelers (7)", "23", "Baltimore Ravens", "14", "Pittsburgh, Pennsylvania", "Heinz Field"], ["2001–02", "New England Patriots (3)", "24", "Pittsburgh Steelers", "17", "Pittsburgh, Pennsylvania", "Heinz Field"], ["2004–05", "New England Patriots (5)", "41", "Pittsburgh Steelers", "27", "Pittsburgh, Pennsylvania", "Heinz Field"], ["1985–86", "New England Patriots (1)", "31", "Miami Dolphins", "14", "Miami, Florida", "Miami Orange Bowl"], ["1971–72", "Miami Dolphins (1)", "21", "Baltimore Colts", "0", "Miami, Florida", "Miami Orange Bowl"], ["1984–85", "Miami Dolphins (5)", "45", "Pittsburgh Steelers", "28", "Miami, Florida", "Miami Orange Bowl"], ["1973–74", "Miami Dolphins (3)", "27", "Oakland Raiders", "10", "Miami, Florida", "Miami Orange Bowl"], ["2006–07", "Indianapolis Colts (2)", "38", "New England Patriots", "34", "Indianapolis, Indiana", "RCA Dome"], ["1995–96", "Pittsburgh Steelers (5)", "20", "Indianapolis Colts", "16", "Pittsburgh, Pennsylvania", "Three Rivers Stadium"], ["2003–04", "New England Patriots (4)", "24", "Indianapolis Colts", "14", "Foxborough, Massachusetts", "Gillette Stadium"], ["1974–75", "Pittsburgh Steelers (1)", "24", "Oakland Raiders", "13", "Oakland, California", "Oakland Coliseum"], ["1994–95", "San Diego Chargers (1)", "17", "Pittsburgh Steelers", "13", "Pittsburgh, Pennsylvania", "Three Rivers Stadium"], ["1972–73", "Miami Dolphins (2)", "21", "Pittsburgh Steelers", "17", "Pittsburgh, Pennsylvania", "Three Rivers Stadium"], ["2011–12", "New England Patriots (7)", "23", "Baltimore Ravens", "20", "Foxborough, Massachusetts", "Gillette Stadium"], ["1997–98", "Denver Broncos (5)", "24", "Pittsburgh Steelers", "21", "Pittsburgh, Pennsylvania", "Three Rivers Stadium"], ["2010–11", "Pittsburgh Steelers (8)", "24", "New York Jets", "19", "Pittsburgh, Pennsylvania", "Heinz Field"], ["1975–76", "Pittsburgh Steelers (2)", "16", "Oakland Raiders", "10", "Pittsburgh, Pennsylvania", "Three Rivers Stadium"], ["1982–83", "Miami Dolphins (4)", "14", "New York Jets", "0", "Miami, Florida", "Miami Orange Bowl"], ["2012–13", "Baltimore Ravens (2)", "28", "New England Patriots", "13", "Foxborough, Massachusetts", "Gillette Stadium"], ["2005–06", "Pittsburgh Steelers (6)", "34", "Denver Broncos", "17", "Denver, Colorado", "Invesco Field at Mile High"], ["1996–97", "New England Patriots (2)", "20", "Jacksonville Jaguars", "6", "Foxborough, Massachusetts", "Foxboro Stadium"], ["2009–10", "Indianapolis Colts (3)", "30", "New York Jets", "17", "Indianapolis, Indiana", "Lucas Oil Stadium"], ["2000–01", "Baltimore Ravens (1)", "16", "Oakland Raiders", "3", "Oakland, California", "Oakland Coliseum"], ["2007–08", "New England Patriots (6)", "21", "San Diego Chargers", "12", "Foxborough, Massachusetts", "Gillette Stadium"], ["1980–81", "Oakland Raiders (2)", "34", "San Diego Chargers", "27", "San Diego, California", "Jack Murphy Stadium"], ["1979–80", "Pittsburgh Steelers (4)", "27", "Houston Oilers", "13", "Pittsburgh, Pennsylvania", "Three Rivers Stadium"], ["1989–90", "Denver Broncos (4)", "37", "Cleveland Browns", "21", "Denver, Colorado", "Mile High 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:which team has won the most afc championship games? | Pittsburgh Steelers | 128 | Answer: |
Table InputTable: [["Result", "Encrypted", "Result", "Encrypted", "Result", "Encrypted", "Result", "Encrypted", "Result", "Encrypted"], ["2", "60", "21", "82", "40", "121", "59", "92", "78", "49"], ["0", "57", "19", "108", "38", "113", "57", "91", "76", "79"], ["1", "109", "20", "125", "39", "116", "58", "37", "77", "65"], ["18", "68", "37", "103", "56", "44", "75", "104", "", ""], ["3", "46", "22", "69", "41", "102", "60", "51", "79", "67"], ["7", "99", "26", "58", "45", "119", "64", "81", "83", "94"], ["13", "75", "32", "64", "51", "41", "70", "74", "89", "56"], ["12", "77", "31", "105", "50", "80", "69", "112", "88", "47"], ["4", "84", "23", "111", "42", "114", "61", "100", "80", "66"], ["5", "86", "24", "107", "43", "36", "62", "76", "81", "54"], ["10", "89", "29", "71", "48", "123", "67", "85", "86", "95"], ["15", "88", "34", "122", "53", "45", "72", "55", "91", "106"], ["8", "96", "27", "35", "46", "101", "65", "59", "84", "61"], ["9", "117", "28", "63", "47", "52", "66", "62", "85", "73"], ["16", "126", "35", "93", "54", "90", "73", "50", "92", "115"], ["14", "39", "33", "53", "52", "72", "71", "83", "90", "124"], ["6", "97", "25", "78", "44", "40", "63", "43", "82", "118"], ["11", "42", "30", "34", "49", "87", "68", "33", "87", "48"], ["17", "120", "36", "38", "55", "110", "74", "70", "93", "98"]] | 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 number 60 is paired with an encrypted result of 2, give the other number given when 60 is the result. | 51 | 128 | Answer: |
Table InputTable: [["Round", "Round", "Race", "Date", "Pole Position", "Fastest Lap", "Winning Club", "Winning Team", "Report"], ["2", "R2", "Nürburgring", "September 21", "", "SC Corinthians", "PSV Eindhoven", "Azerti Motorsport", "Report"], ["6", "R2", "Jerez", "November 23", "", "Beijing Guoan", "Borussia Dortmund", "Zakspeed", "Report"], ["4", "R2", "Estoril", "October 19", "", "Borussia Dortmund", "Al Ain", "Azerti Motorsport", "Report"], ["5", "R1", "Vallelunga", "November 2", "Liverpool F.C.", "Beijing Guoan", "Beijing Guoan", "Zakspeed", "Report"], ["3", "R2", "Zolder", "October 5", "", "Atlético Madrid", "Beijing Guoan", "Zakspeed", "Report"], ["1", "R1", "Donington Park", "August 31", "Beijing Guoan", "Beijing Guoan", "Beijing Guoan", "Zakspeed", "Report"], ["2", "R1", "Nürburgring", "September 21", "A.C. Milan", "PSV Eindhoven", "A.C. Milan", "Scuderia Playteam", "Report"], ["1", "R2", "Donington Park", "August 31", "", "PSV Eindhoven", "Sevilla FC", "GTA Motor Competición", "Report"], ["3", "R1", "Zolder", "October 5", "Borussia Dortmund", "Liverpool F.C.", "Liverpool F.C.", "Hitech Junior Team", "Report"], ["6", "R1", "Jerez", "November 23", "Liverpool F.C.", "R.S.C. Anderlecht", "A.C. Milan", "Scuderia Playteam", "Report"], ["5", "R2", "Vallelunga", "November 2", "", "Atlético Madrid", "F.C. Porto", "Hitech Junior Team", "Report"], ["4", "R1", "Estoril", "October 19", "A.S. Roma", "Atlético Madrid", "Liverpool F.C.", "Hitech Junior Team", "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 did zakspeed win? | 4 | 128 | Answer: |
Table InputTable: [["Polling Firm", "Source", "Date Published", "N.Anastasiades", "G.Lillikas", "S.Malas", "Others"], ["Prime Consulting Ltd", "[20]", "9 February 2013", "40.6%", "19.6%", "20.4%", "2.9%"], ["Prime Consulting Ltd", "[19]", "4 February 2013", "39.8%", "19.3%", "20%", "3%"], ["Prime Consulting Ltd", "[9]", "18 November 2012", "35.9%", "18.7%", "19.6%", "0.6%"], ["RAI Consultants Ltd", "[21]", "9 February 2013", "42.1%", "19.4%", "21.1%", "4.4%"], ["Prime Consulting Ltd", "[17]", "27 January 2013", "39.2%", "18.8%", "19.8%", "4%"], ["Prime Consulting Ltd", "[12]", "3 December 2012", "35%", "19.1%", "18.6%", "1.4%"], ["Prime Consulting Ltd", "[4]", "7 October 2012", "34.7%", "17.4%", "18.5%", ""], ["RAI Consultants", "[1][dead link]", "16 September 2012", "37.2%", "14.2%", "21.9%", "1.5%"], ["RAI Consultants", "[7]", "4 November 2012", "38.8%", "19.8%", "21.1%", "2.3%"], ["RAI Consultants Ltd", "[15][dead link]", "13 January 2013", "40.3%", "17.9%", "20.5%", "6.1%"], ["Average (only valid votes)", "–", "–", "48.4%", "22.52%", "25.29%", "3.79%"], ["Evresis", "[10]", "27 November 2012", "37.1%", "19.6%", "20.8%", "0.6%"], ["Evresis", "[14]", "22 December 2012", "37.4%", "19.8%", "21.8%", "0.5%"], ["Evresis", "[6]", "2 November 2012", "36.9%", "17.7%", "20.6%", "1.4%"], ["Evresis", "[2]", "18 September 2012", "35.2%", "17.5%", "19.7%", "1.7%"], ["Evresis", "[18]", "1 February 2013", "40.8%", "19.9%", "22.2%", "2.5%"], ["CMR Cypronetwork / Cybc", "[22]", "9 February 2013", "39.9%", "20.2%", "24.2%", "3%"], ["CMR Cypronetwork / Cybc", "[8]", "15 November 2012", "36.8%", "18.9%", "22.8%", "1.6%"], ["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%"], ["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", "[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:which polling firm is listed the most? | Prime Consulting Ltd | 128 | Answer: |
Table InputTable: [["Designation", "Keel Laid", "Launched", "Commissioned", "Fate"], ["PE-19", "6 August 1918", "30 January 1919", "25 June 1919", "In service during WWII\\nDestroyed 6 August 1946"], ["PE-57", "25 March 1919", "29 July 1919", "15 October 1919", "In service during WWII\\nSold 5 March 1947"], ["PE-55", "17 March 1919", "22 July 1919", "10 October 1919", "In service during WWII\\nSold 3 March 1947"], ["PE-38", "30 January 1919", "29 March 1919", "30 July 1919", "In service during WWII\\nSold 3 March 1947"], ["PE-32", "30 November 1918", "15 March 1919", "4 September 1919", "In service during WWII\\nSold 3 March 1947"], ["PE-56", "25 March 1919", "15 August 1919", "26 October 1919", "In service during WWII\\nTorpedoed by U-853 off Portland, Maine, on 23 April 1945"], ["PE-27", "22 October 1918", "1 March 1919", "14 July 1919", "In service during WWII\\nSold 4 June 1946"], ["PE-17", "3 August 1918", "1 February 1919", "3 July 1919", "Wrecked off Long Island, New York 22 May 1922"], ["PE-10", "6 July 1918", "9 November 1918", "31 October 1919", "Destroyed 19 August 1937"], ["PE-7", "8 June 1918", "5 October 1918", "24 November 1918", "Expended as target 30 November 1934"], ["PE-6", "3 June 1918", "16 October 1918", "21 November 1918", "Expended as target 30 November 1934"], ["PE-25", "17 September 1918", "19 February 1919", "30 June 1919", "Capsized in Delaware Bay squall 11 June 1920"], ["PE-12", "13 July 1918", "12 November 1918", "6 November 1919", "Sold 30 December 1935"], ["PE-3", "16 May 1918", "11 September 1918", "11 November 1918", "Sold 11 June 1930"], ["PE-4", "21 May 1918", "15 September 1918", "14 November 1918", "Sold 11 June 1930"], ["PE-5", "28 May 1918", "28 September 1918", "19 November 1918", "Sold 11 June 1930"], ["PE-1", "7 May 1918", "11 July 1918", "27 October 1918", "Sold 11 June 1930"], ["PE-58", "25 March 1919", "2 August 1919", "20 October 1919", "Disposed of 30 June 1940"], ["PE-24", "13 September 1918", "24 February 1919", "12 July 1919", "Sold 11 June 1930"], ["PE-23", "11 September 1918", "20 February 1919", "19 June 1919", "Sold 11 June 1930"], ["PE-8", "10 June 1918", "11 November 1918", "31 October 1919", "Sold 1 April 1931"], ["PE-44", "20 February 1919", "24 May 1919", "30 September 1919", "Disposed of 14 May 1938"], ["PE-48", "3 March 1919", "24 May 1919", "8 October 1919", "Sold 10 October 1946"], ["PE-21", "31 August 1918", "15 February 1919", "31 July 1919", "Transferred to USCG late 1919"], ["PE-9", "17 June 1918", "8 November 1918", "27 October 1919", "Sold 26 May 1930"], ["PE-35", "13 January 1919", "22 March 1919", "22 August 1919", "Sold 7 June 1938"], ["PE-18", "5 August 1918", "10 February 1919", "7 August 1919", "Sold 11 June 1930"]] | 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 designation of the only ship listed as being torpedoed? | PE-56 | 128 | Answer: |
Table InputTable: [["Season", "Winning Team", "Score", "Losing Team", "Score", "Location", "Stadium"], ["1989–90", "Denver Broncos (4)", "37", "Cleveland Browns", "21", "Denver, Colorado", "Mile High Stadium"], ["1987–88", "Denver Broncos (3)", "38", "Cleveland Browns", "33", "Denver, Colorado", "Mile High Stadium"], ["2006–07", "Indianapolis Colts (2)", "38", "New England Patriots", "34", "Indianapolis, Indiana", "RCA Dome"], ["2005–06", "Pittsburgh Steelers (6)", "34", "Denver Broncos", "17", "Denver, Colorado", "Invesco Field at Mile High"], ["1977–78", "Denver Broncos (1)", "20", "Oakland Raiders", "17", "Denver, Colorado", "Mile High Stadium"], ["1978–79", "Pittsburgh Steelers (3)", "34", "Houston Oilers", "5", "Pittsburgh, Pennsylvania", "Three Rivers Stadium"], ["1979–80", "Pittsburgh Steelers (4)", "27", "Houston Oilers", "13", "Pittsburgh, Pennsylvania", "Three Rivers Stadium"], ["2013–14", "Denver Broncos (7)", "26", "New England Patriots", "16", "Denver, Colorado", "Sports Authority Field at Mile High"], ["1998–99", "Denver Broncos (6)", "23", "New York Jets", "10", "Denver, Colorado", "Mile High Stadium"], ["1970–71", "Baltimore Colts (1)", "27", "Oakland Raiders", "17", "Baltimore, Maryland", "Memorial Stadium"], ["1971–72", "Miami Dolphins (1)", "21", "Baltimore Colts", "0", "Miami, Florida", "Miami Orange Bowl"], ["1972–73", "Miami Dolphins (2)", "21", "Pittsburgh Steelers", "17", "Pittsburgh, Pennsylvania", "Three Rivers Stadium"], ["2001–02", "New England Patriots (3)", "24", "Pittsburgh Steelers", "17", "Pittsburgh, Pennsylvania", "Heinz Field"], ["1994–95", "San Diego Chargers (1)", "17", "Pittsburgh Steelers", "13", "Pittsburgh, Pennsylvania", "Three Rivers Stadium"], ["1997–98", "Denver Broncos (5)", "24", "Pittsburgh Steelers", "21", "Pittsburgh, Pennsylvania", "Three Rivers Stadium"], ["1973–74", "Miami Dolphins (3)", "27", "Oakland Raiders", "10", "Miami, Florida", "Miami Orange Bowl"], ["2008–09", "Pittsburgh Steelers (7)", "23", "Baltimore Ravens", "14", "Pittsburgh, Pennsylvania", "Heinz Field"], ["2004–05", "New England Patriots (5)", "41", "Pittsburgh Steelers", "27", "Pittsburgh, Pennsylvania", "Heinz Field"], ["1974–75", "Pittsburgh Steelers (1)", "24", "Oakland Raiders", "13", "Oakland, California", "Oakland Coliseum"], ["1982–83", "Miami Dolphins (4)", "14", "New York Jets", "0", "Miami, Florida", "Miami Orange Bowl"], ["1980–81", "Oakland Raiders (2)", "34", "San Diego Chargers", "27", "San Diego, California", "Jack Murphy Stadium"], ["2009–10", "Indianapolis Colts (3)", "30", "New York Jets", "17", "Indianapolis, Indiana", "Lucas Oil Stadium"], ["1984–85", "Miami Dolphins (5)", "45", "Pittsburgh Steelers", "28", "Miami, Florida", "Miami Orange Bowl"], ["2003–04", "New England Patriots (4)", "24", "Indianapolis Colts", "14", "Foxborough, Massachusetts", "Gillette Stadium"], ["1976–77", "Oakland Raiders (1)", "24", "Pittsburgh Steelers", "7", "Oakland, California", "Oakland Coliseum"], ["1985–86", "New England Patriots (1)", "31", "Miami Dolphins", "14", "Miami, Florida", "Miami Orange Bowl"], ["1983–84", "Los Angeles Raiders (3)", "30", "Seattle Seahawks", "14", "Los Angeles, California", "Los Angeles Memorial Coliseum"], ["2007–08", "New England Patriots (6)", "21", "San Diego Chargers", "12", "Foxborough, Massachusetts", "Gillette Stadium"], ["1975–76", "Pittsburgh Steelers (2)", "16", "Oakland Raiders", "10", "Pittsburgh, Pennsylvania", "Three Rivers 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:which team has the longest consecutive win streak in the championship game? | Buffalo Bills | 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"], ["Gerald Ford", "June 5, 2004", "December 26, 2006", "90 years, 327 days", "93 years, 165 days", "2 years, 204 days", "934 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)"], ["James Buchanan", "July 24, 1862", "June 1, 1868", "71 years, 92 days", "77 years, 39 days", "5 years, 313 days", "2,139 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"], ["Millard Fillmore", "June 1, 1868", "March 8, 1874", "68 years, 146 days", "74 years, 60 days", "5 years, 280 days", "2,106 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"], ["Herbert Hoover", "January 5, 1933", "October 20, 1964", "58 years, 148 days", "90 years, 71 days", "31 years, 289 days", "11,611 days"], ["Calvin Coolidge", "March 8, 1930", "January 5, 1933", "57 years, 247 days", "60 years, 185 days", "2 years, 303 days", "1,034 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"], ["Ronald Reagan", "January 20, 1981", "June 5, 2004", "69 years, 349 days", "93 years, 120 days", "23 years, 137 days", "8,537 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"], ["Woodrow Wilson", "March 4, 1913", "February 3, 1924", "56 years, 66 days", "67 years, 37 days", "10 years, 336 days", "3,988 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"], ["Benjamin Harrison", "January 17, 1893", "March 13, 1901", "59 years, 150 days", "67 years, 205 days", "8 years, 55 days", "2,976 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 was oldest living right before gerald ford? | Ronald Reagan | 128 | Answer: |
Table InputTable: [["Date", "Opponent", "Venue", "Result", "Attendance", "Scorers"], ["14 April 2006", "Manchester United", "Old Trafford", "0–0", "72,519", ""], ["1 October 2005", "West Ham United", "Stadium of Light", "1–1", "31,212", "Miller"], ["17 April 2006", "Newcastle United", "Stadium of Light", "1–4", "40,032", "Hoyte"], ["1 May 2006", "Arsenal", "Stadium of Light", "0–3", "44,003", ""], ["31 January 2006", "Middlesbrough", "Stadium of Light", "0–3", "31,675", ""], ["3 March 2006", "Manchester City", "City of Manchester Stadium", "1–2", "42,200", "Kyle"], ["25 February 2006", "Birmingham City", "St. Andrew's", "0–1", "29,257", ""], ["25 September 2005", "Middlesbrough", "Riverside Stadium", "2–0", "29,583", "Miller, Arca"], ["15 October 2005", "Manchester United", "Stadium of Light", "1–3", "39,085", "Elliott"], ["18 March 2006", "Bolton Wanderers", "Reebok Stadium", "0–2", "23,568", ""], ["1 April 2006", "Everton", "Goodison Park", "2–2", "38,093", "Stead, Delap"], ["12 February 2006", "Tottenham Hotspur", "Stadium of Light", "1–1", "34,700", "Murphy"], ["25 March 2006", "Blackburn Rovers", "Stadium of Light", "0–1", "29,593", ""], ["4 February 2006", "West Ham United", "Boleyn Ground", "0–2", "34,745", ""], ["21 January 2006", "West Bromwich Albion", "The Hawthorns", "1–0", "26,464", "Watson (own goal)"], ["26 November 2005", "Birmingham City", "Stadium of Light", "0–1", "32,442", ""], ["17 September 2005", "West Bromwich Albion", "Stadium of Light", "1–1", "31,657", "Breen"], ["23 October 2005", "Newcastle United", "St James' Park", "2–3", "52,302", "Lawrence, Elliott"], ["7 May 2006", "Aston Villa", "Villa Park", "1–2", "33,820", "D. Collins"], ["29 October 2005", "Portsmouth", "Stadium of Light", "1–4", "34,926", "Whitehead (pen)"], ["20 August 2005", "Liverpool", "Anfield", "0–1", "44,913", ""], ["23 August 2005", "Manchester City", "Stadium of Light", "1–2", "33,357", "Le Tallec"], ["15 February 2006", "Blackburn Rovers", "Ewood Park", "0–2", "18,220", ""], ["10 September 2005", "Chelsea", "Stamford Bridge", "0–2", "41,969", ""], ["19 November 2005", "Aston Villa", "Stadium of Light", "1–3", "39,707", "Whitehead (pen)"], ["11 March 2006", "Wigan Athletic", "Stadium of Light", "0–1", "31,194", ""], ["5 November 2005", "Arsenal", "Highbury", "1–3", "38,210", "Stubbs"], ["15 January 2006", "Chelsea", "Stadium of Light", "1–2", "32,420", "Lawrence"], ["26 December 2005", "Bolton Wanderers", "Stadium of Light", "0–0", "32,232", ""], ["30 November 2005", "Liverpool", "Stadium of Light", "0–2", "32,697", ""], ["2 January 2006", "Fulham", "Craven Cottage", "1–2", "19,372", "Lawrence"], ["3 December 2005", "Tottenham Hotspur", "White Hart Lane", "2–3", "36,244", "Whitehead, Le Tallec"]] | 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 opponent? | Charlton Athletic | 128 | Answer: |
Table InputTable: [["Team", "City", "Venue", "Capacity", "Head Coach", "Team Captain", "Past Season"], ["Mes Kerman", "Kerman", "Shahid Bahonar", "15,000", "Parviz Mazloomi", "Farzad Hosseinkhani", "10th"], ["Damash Gilan", "Rasht", "Sardar Jangal", "15,000", "Stanko Poklepović", "Mohammad Reza Mahdavi", "15th"], ["Persepolis", "Tehran", "Azadi", "90,000", "Nelo Vingada", "Karim Bagheri", "Champion"], ["Esteghlal", "Tehran", "Azadi", "90,000", "Amir Ghalenoei", "Farhad Majidi", "13th"], ["Bargh Shiraz", "Shiraz", "Hafezieh", "20,000", "Rasoul Korbekandi", "Sattar Zare", "7th"], ["Aboomoslem", "Mashhad", "Samen", "35,000", "Ali Hanteh", "Saeed Khani", "4th"], ["Rah Ahan", "Rey, Iran", "Rah Ahan", "15,000", "Mehdi Tartar", "Ahmad Taghavi", "12th"], ["Payam", "Mashhad", "Samen", "35,000", "Kazem Ghiyasiyan", "Mehdi Hasheminasab", "Qualifier"], ["Paykan", "Qazvin", "Shahid Rajaei", "5,000", "Ali Asghar Modir Roosta", "Mohammad Reza Tahmasebi", "9th"], ["Malavan", "Anzali", "Takhti Anzali", "8,000", "Mohammad Ahmadzadeh", "Masoud Gholamalizad", "16th"], ["Zob Ahan", "Esfahan", "Foolad Shahr", "25,000", "Mansour Ebrahimzadeh", "Mohammad Salsali", "6th"], ["Est. Ahvaz", "Ahvaz", "Takhti Ahvaz", "30,000", "Khodadad Azizi", "Afshin Komaei", "8th"], ["Foolad", "Ahvaz", "Takhti Ahvaz", "15,000", "Majid Jalali", "Ali Badavi", "Qualifier"], ["Moghavemat", "Shiraz", "Hafezieh", "20,000", "Gholam Hossein Peyrovani", "Mostafa Sabri", "14th"], ["Saba Qom", "Qom", "Yadegar Emam", "15,000", "Firouz Karimi", "Yahya Golmohammadi", "3rd"], ["Saipa", "Karaj", "Enghelab Karaj", "15,000", "Mohammad Mayeli Kohan", "Ebrahim Sadeghi", "11th"], ["Sepahan", "Esfahan", "Foolad Shahr", "25,000", "Farhad Kazemi", "Moharram Navidkia", "2nd"], ["Pas Hamedan", "Hamedan", "Ghods", "5,000", "Vinko Begovic", "Omid Khouraj", "5th"]] | 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 much more capacity does rasht have than kerman? | 0 | 128 | Answer: |
Table InputTable: [["Pos", "Name", "Team", "Laps", "Time/Retired", "Grid", "Points"], ["3", "Bruno Junqueira", "Dale Coyne Racing", "69", "+8.419", "11", "26"], ["7", "Sébastien Bourdais", "N/H/L Racing", "69", "+22.955", "1", "18"], ["16", "Alex Figge", "Pacific Coast Motorsports", "68", "+ 1 Lap", "16", "5"], ["4", "Tristan Gommendy", "PKV Racing", "69", "+9.037", "3", "23"], ["9", "Graham Rahal", "N/H/L Racing", "69", "+23.949", "6", "13"], ["12", "Katherine Legge", "Dale Coyne Racing", "69", "+44.860", "14", "9"], ["8", "Oriol Servià", "Forsythe Racing", "69", "+23.406", "13", "15"], ["5", "Neel Jani", "PKV Racing", "69", "+22.262", "4", "21"], ["2", "Jan Heylen", "Conquest Racing", "69", "+7.227", "7", "27"], ["10", "Ryan Dalziel", "Pacific Coast Motorsports", "69", "+29.554", "15", "11"], ["17", "Paul Tracy", "Forsythe Racing", "14", "Mechanical", "17", "4"], ["15", "Alex Tagliani", "Rocketsports", "68", "+ 1 Lap", "12", "6"], ["11", "Dan Clarke", "Minardi Team USA", "69", "+38.903", "10", "11"], ["13", "Robert Doornbos", "Minardi Team USA", "69", "+1:00.638", "9", "8"], ["6", "Simon Pagenaud", "Team Australia", "69", "+22.698", "5", "19"], ["1", "Justin Wilson", "RuSPORT", "69", "1:46:02.236", "2", "32"], ["14", "Will Power", "Team Australia", "69", "+1:01.204", "8", "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:the most points in the race | 32 | 128 | Answer: |
Table InputTable: [["Hull", "Type", "Original Name", "Original Operator", "Delivery", "Disposition (2012)", "2nd name", "2nd operator", "3rd Name", "3rd operator"], ["№ 14", "929-117", "Crystal Wing", "Kaijo Access Co.", "Jun 1994", "Active", "2002 Beetle 5", "JR Kyushu Jet Ferries", "", ""], ["№ 5", "929-117", "Nagasaki", "JR Kyushu Jet Ferries", "Apr 1990", "Active", "Beetle 1", "JR Kyushu Jet Ferries", "", ""], ["№ 7", "929-117", "Unicorn", "Kyusyu Shosen Co. Ltd.", "Oct 1990", "Active", "Pegasus 2", "Kyusyu Shosen Co. Ltd.", "", ""], ["№ 8", "929-117", "Beetle 2", "JR Kyushu Jet Ferries", "Feb 1991", "Active", "", "", "", ""], ["№ 15", "929-117", "Emerald Wing", "Kaijo Access Co.", "Jun 1994", "Active", "2004 Rocket 1", "Cosmo Line", "-", "Tane Yaku Jetfoil"], ["№ 6", "929-117", "Beetle", "JR Kyushu Jet Ferries", "Jul 1990", "Active", "Rocket", "Cosmo Line", "Rocket 3", "Tane Yaku Jetfoils"], ["№ 3", "929-117", "Toppy 1", "Tane Yaku Jetfoils", "Sep 1989", "Active", "Beetle 3", "JR Kyushu Jet Ferries", "", ""], ["№ 4", "929-117", "Princess Dacil", "Trasmediterranea", "Mar 1990", "Active", "Pegasus", "Kyusyu Shosen Co. Ltd.", "", ""], ["№ 2", "929-117", "Pegasus", "Kyusyu Shosen Co. Ltd.", "Jun 1989", "Active", "Toppy 1", "Tane Yaku Jetfoils", "", ""], ["№ 9", "929-117", "Venus", "Kyushu Yusen", "Mar 1991", "Active", "", "", "", ""], ["№ 12", "929-117", "Toppy 2", "Tane Yaku Jetfoils", "Apr 1992", "Active", "", "", "", ""], ["№ 13", "929-117", "Toppy 3", "Tane Yaku Jetfoils", "Mar 1995", "Active", "", "", "", ""], ["№ 10", "929-117", "Suisei", "Sado Kisen", "Apr 1991", "Active", "", "", "", ""], ["№ 11", "929-117", "Princess Teguise", "Trasmediterranea", "Jun 1991", "Active", "2007 Toppy 5", "Tane Yaku Jetfoils", "", ""], ["№ 1", "929-117", "Tsubasa", "Sado Kisen", "Mar 1998", "Active", "", "", "", ""]] | 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 operator built the vehicle under the crystal wing | Kaijo Access Co. | 128 | Answer: |
Table InputTable: [["Rank", "Diver", "Nationality", "Preliminary\\nPoints", "Preliminary\\nRank", "Final\\nPoints", "Final\\nRank"], ["5", "Nadezhda Bazhina", "Russia", "262.75", "7", "286.20", "5"], ["7", "Sharleen Stratton", "Australia", "282.45", "3", "281.65", "7"], ["30", "Alicia Blagg", "Great Britain", "212.50", "30", "", ""], ["27", "Marion Farissier", "France", "221.65", "27", "", ""], ["4", "Maria Marconi", "Italy", "264.25", "6", "290.15", "4"], ["35", "Sari Ambarwati", "Indonesia", "200.05", "35", "", ""], ["25", "Hannah Starling", "Great Britain", "226.40", "25", "", ""], ["36", "Lei Sio I", "Macau", "192.00", "36", "", ""], ["9", "Kelci Bryant", "United States", "257.00", "11", "274.25", "9"], ["29", "Yuka Mabuchi", "Japan", "219.50", "29", "", ""], ["16", "Uschi Freitag", "Germany", "247.70", "16", "", ""], ["10", "Olena Fedorova", "Ukraine", "258.30", "9", "274.15", "10"], ["33", "Tina Punzel", "Germany", "206.05", "33", "", ""], ["23", "Vianey Hernandez", "Mexico", "227.85", "23", "", ""], ["6", "Abby Johnston", "United States", "282.40", "4", "282.85", "6"], ["21", "Jennifer Benitez", "Spain", "232.50", "21", "", ""], ["26", "Choi Sut Ian", "Macau", "224.50", "26", "", ""], ["20", "Sayaka Shibusawa", "Japan", "240.80", "20", "", ""], ["32", "Diana Pineda", "Colombia", "209.60", "32", "", ""], ["17", "Sharon Chan", "Hong Kong", "245.10", "17", "", ""], ["12", "Anastasia Pozdniakova", "Russia", "260.00", "8", "251.70", "12"], ["15", "Sophie Somloi", "Austria", "249.45", "15", "", ""], ["28", "Julia Loennegren", "Sweden", "221.05", "28", "", ""], ["8", "Anna Lindberg", "Sweden", "276.05", "5", "279.55", "8"], ["", "Shi Tingmao", "China", "294.65", "2", "318.65", "1"], ["11", "Brittany Broben", "Australia", "257.10", "10", "267.20", "11"], ["", "Tania Cagnotto", "Italy", "253.15", "12", "295.45", "3"], ["14", "Jennifer Abel", "Canada", "250.95", "14", "", ""], ["34", "Maria Florencia Betancourt", "Venezuela", "204.90", "34", "", ""], ["18", "Inge Jansen", "Netherlands", "241.95", "18", "", ""], ["37", "Leyre Eizaguirre", "Spain", "189.95", "37", "", ""], ["13", "Hanna Pysmenska", "Ukraine", "251.40", "13", "", ""], ["39", "Carolina Murillo", "Colombia", "181.85", "39", "", ""], ["22", "Arantxa Chavez", "Mexico", "232.35", "22", "", ""], ["19", "Jun Hoong Cheong", "Malaysia", "241.95", "18", "", ""], ["", "Wang Han", "China", "306.60", "1", "310.20", "2"], ["40", "Hsu Shi-Han", "Chinese Taipei", "146.15", "40", "", ""], ["31", "Beannelys Velasquez", "Venezuela", "211.30", "31", "", ""]] | 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:does rank 5 have at least 290 points? | No | 128 | Answer: |
Table InputTable: [["Year", "Car", "Start", "Qual", "Rank", "Finish", "Laps", "Led", "Retired"], ["1928", "8", "4", "117.031", "4", "10", "200", "33", "Running"], ["1927", "27", "27", "107.765", "22", "3", "200", "0", "Running"], ["1939", "62", "27", "121.749", "24", "11", "200", "0", "Running"], ["1933", "34", "12", "113.578", "15", "7", "200", "0", "Running"], ["1929", "23", "11", "112.146", "15", "17", "91", "0", "Supercharger"], ["1937", "38", "7", "118.788", "16", "8", "200", "0", "Running"], ["1938", "17", "4", "122.499", "6", "17", "130", "0", "Rod"], ["1931", "37", "19", "111.725", "6", "18", "167", "0", "Crash T4"], ["1930", "9", "20", "100.033", "18", "20", "79", "0", "Valve"], ["1932", "25", "20", "108.896", "34", "13", "184", "0", "Flagged"], ["1934", "8", "7", "113.733", "13", "17", "94", "0", "Rod"], ["1926", "31", "12", "102.789", "13", "11", "142", "0", "Flagged"], ["1935", "44", "6", "115.459", "11", "21", "102", "0", "Magneto"], ["Totals", "Totals", "Totals", "Totals", "Totals", "Totals", "1989", "33", ""]] | 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 year had the least amount of laps listed? | 1930 | 128 | Answer: |
Table InputTable: [["Year", "Division", "League", "Reg. Season", "Playoffs"], ["2009", "1", "USL W-League", "7th, Western", "Did not qualify"], ["2007", "1", "USL W-League", "5th, Western", ""], ["2011", "1", "USL W-League", "7th, Western", "Did not qualify"], ["2008", "1", "USL W-League", "6th, Western", "Did not qualify"], ["2005", "1", "USL W-League", "6th, Western", ""], ["2006", "1", "USL W-League", "5th, Western", ""], ["2010", "1", "USL W-League", "6th, Western", "Did not qualify"], ["2012", "1", "USL W-League", "4th, Western", "Did not qualify"], ["2003", "2", "USL W-League", "5th, Western", ""], ["2013", "1", "USL W-League", "4th, Western", "Did not qualify"], ["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 was the total number of times the team placed 7th? | 2 | 128 | Answer: |
Table InputTable: [["Language", "2001 census[1]\\n(total population 1,004.59 million)", "1991 censusIndian Census [2]\\n(total population 838.14 million)", "1991 censusIndian Census [2]\\n(total population 838.14 million)", ""], ["Oriya", "33,017,446", "28,061,313", "3.35%", "32.3 M"], ["Tamil", "60,793,814", "53,006,368", "6.32%", "66.0 M"], ["Malayalam", "33,066,392", "30,377,176", "3.62%", "35.7 M"], ["Gujarati", "46,091,617", "40,673,814", "4.85%", "46.1 M"], ["Urdu", "51,536,111", "43,406,932", "5.18%", "60.3 M"], ["Kurukh", "1,751,489", "0.17%", "1,426,618", "0.170%"], ["Bhili/Bhilodi", "9,582,957", "5,572,308", "0.665%", ""], ["Punjabi", "130,000,000", "100,017,615", "20.87%", "113 M"], ["Kannada", "37,924,011", "32,753,676", "3.91%", "40.3 M"], ["Kashmiri", "5,527,698", "0.54%", "", ""], ["Marathi", "71,936,894", "62,481,681", "7.45%", "68.0 M"], ["Meitei (Manipuri)", "1,466,705*", "0.14%", "1,270,216", "0.151%"], ["Maithili", "12,179,122", "1.18%", "", ""], ["Nepali", "23,017,446", "28,061,313", "3.35%", "32.3 M"], ["Tulu", "1,722,768", "0.17%", "1,552,259", "0.185%"], ["Mundari", "1,061,352", "0.105%", "", ""], ["Khandeshi", "2,075,258", "0.21%", "", ""], ["Bengali", "230,000,000", "200,595,738", "28.30%", "320 M"], ["Santali", "6,469,600", "5,216,325", "0.622%", ""], ["Dogri", "2,282,589[dubious – discuss]", "0.22%", "", ""], ["Telugu", "70,002,856", "65,595,738", "8.30%", "70 M"], ["Assamese", "13,168,484", "13,079,696", "1.56%", "15.4 M"], ["Sinhalese", "19,017,446", "28,061,313", "3.35%", "32.3 M"], ["Konkani", "2,489,015", "1,760,607", "0.210%", ""], ["Khasi", "1,128,575", "0.112%", "", ""], ["Sindhi", "25,535,485", "25,122,848", "0.248%", "32.3 M"], ["Gondi", "2,713,790", "2,124,852", "0.253%", ""], ["Hindi", "422,048,642", "337,272,114", "40.0%", "336 M"], ["Bodo", "1,350,478", "0.13%", "1,221,881", "0.146%"], ["", "Speakers", "Speakers", "Percentage", ""], ["Ho", "1,042,724", "0.103%", "", ""]] | 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 number of oriya speakers as of the 1991 census? | 28,061,313 | 128 | Answer: |
Table InputTable: [["Name", "Owner", "Location", "Notes", "Transmission", "Website"], ["Radio Monte Carlo", "Gruppo Finelco", "Milan", "Commercial; It is also called RMC", "FM, DVB-S", "http://www.radiomontecarlo.net"], ["Radio 24", "Il Sole 24 Ore", "Milan", "Commercial; News/Talk", "FM, DAB, DVB-S", "http://www.radio24.it"], ["Radio Italia Solo Musica Italiana", "Gruppo Radio Italia", "Milan", "Commercial; Italian Hits", "FM, DAB, DVB-S", "http://www.radioitalia.it"], ["Radio 105 Network", "Gruppo Finelco", "Milan", "Commercial; Rock, Pop, Hip Hop", "FM, DVB-S", "http://www.105.net"], ["R101", "Monradio", "Milan", "Commercial; Classic hits", "FM, DAB, DAB+, DVB-S", "http://www.r101.it"], ["Radio Capital", "Elemedia", "Cusano Milanino", "Commercial; Classic hits", "FM, DAB, DVB-T, DVB-S", "http://www.capital.it"], ["Virgin Radio Italia", "Gruppo Finelco", "Milan", "Commercial; Rock", "FM, DAB, DAB+, DVB-S", "http://www.virginradioitaly.it"], ["Radio Maria", "Associazione Radio Maria", "Erba, (CO)", "Community; Catholic", "FM, DAB, DVB-S", "http://www.radiomaria.it"], ["Multiradio", "Multiradio srl", "Massafra, (TA)", "Local; Adult Contemporary", "FM", "http://www.multiradio.it"], ["Radio Dimensione Suono", "", "Rome", "Commercial; It is also called RDS", "FM, DAB, DAB+, DVB-S", "http://www.rds.it"], ["Radio Radicale", "Radical Party", "Rome", "Community; News/Talk", "FM, DAB, DVB-S", "http://www.radioradicale.it"], ["Radio Padania Libera", "Lega Nord", "Varese", "Community; News/Talk", "DAB, DVB-S", "http://www.radiopadania.info"], ["RadioRadio", "", "Rome", "Local; News/Talk", "DAB, DVB-S", "http://www.radioradio.it"], ["Radio Popolare", "cooperative", "Rome", "Community; News/Talk", "FM", "http://www.radiopopolare.it"], ["Rai Radio 1", "RAI", "Rome", "Public; News/Talk; Generalist", "FM, MW, DAB, DVB-T, DVB-S", "http://www.radio1.rai.it"], ["Rai Radio 3", "RAI", "Rome", "Public; Culture; Classical music", "FM, DAB, DVB-T, DVB-S", "http://www.radio3.rai.it"], ["Radio DeeJay", "Elemedia", "Milan", "Commercial;", "FM, DAB, DAB+, DVB-T, DVB-S", "http://www.deejay.it"], ["Radio Pianeta", "", "Cividate al piano. (BG)", "Local; News/Talk", "FM", "http://www.radiopianeta.it"], ["Rai Radio 2", "RAI", "Rome", "Public; Popular music; Entertainment", "FM, DAB, DVB-T, DVB-S", "http://www.radio2.rai.it"], ["Rai GR Parlamento", "RAI", "Rome", "Public; News/Talk", "FM, DVB-S", "http://www.grparlamento.rai.it"], ["Radio Bruno", "Radio Bruno", "Carpi (MO)", "Local; Pop, Contemporary", "FM, streaming online, Dvb-T", "http://www.radiobruno.it"], ["m2o", "Elemedia", "Rome", "Commercial; Electronic dance music", "FM, DAB, DAB+, DVB-T, DVB-S", "http://www.m2o.it"], ["RTL 102.5 Classic", "", "Milan", "Commercial; Classic hits", "DAB, DVB-S", "http://www.rtl.it"], ["Rai Isoradio", "RAI", "", "Public; Traffic and weather news", "FM, DAB, DVB-S", "http://www.isoradio.rai.it"]] | 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 radio stations does milan have? | 8 | 128 | Answer: |
Table InputTable: [["Material", "λ (nm)", "n"], ["Fused silica (also called Fused Quartz)", "589.29", "1.458"], ["Cubic zirconia", "", "2.15 - 2.18"], ["Pyrex (a borosilicate glass)", "", "1.470"], ["Acrylic glass", "", "1.490 - 1.492"], ["Silicon carbide", "", "2.65 - 2.69"], ["Polycarbonate", "", "1.584 - 1.586"], ["Cryolite", "", "1.338"], ["Titanium dioxide (Rutile phase )", "589.29", "2.496"], ["Strontium titanate", "589.29", "2.41"], ["Sylgard 184 (Polydimethylsiloxane)", "", "1.4118"], ["Zinc Oxide", "390", "2.4"], ["Potassium Niobate (KNbO3)", "", "2.28"], ["Germanium", "", "4.01"], ["Helium", "589.29", "1.000036"], ["Flint glass (pure)", "", "1.60 - 1.62"], ["Crown glass (pure)", "", "1.50 - 1.54"], ["Silicon", "590", "3.962"], ["Hydrogen", "589.29", "1.000132"], ["Liquid helium", "", "1.025"], ["Acetone", "", "1.36"], ["Teflon AF", "", "1.315"], ["Gallium(III) phosphide", "", "3.5"], ["Crown glass (impure)", "", "1.485 - 1.755"], ["Cinnabar (Mercury sulfide)", "", "3.02"], ["Flint glass (impure)", "", "1.523 - 1.925"], ["Carbon disulfide", "589.29", "1.628"], ["Carbon dioxide", "589.29", "1.00045"], ["Diamond", "589.29", "2.419"], ["Teflon", "", "1.35 - 1.38"], ["Silicone oil", "", "1.336-1.582"], ["Carbon tetrachloride", "589.29", "1.461"], ["Arsenic trisulfide and sulfur in methylene iodide", "", "1.9"], ["Gallium(III) arsenide", "", "3.927"], ["Cornea (human)", "", "1.373/1.380/1.401"], ["Amber", "589.29", "1.55"], ["Lens (human)", "", "1.386 - 1.406"], ["Air", "589.29", "1.000293"], ["Sodium chloride", "589.29", "1.544"], ["Benzene", "589.29", "1.501"], ["Air at STP", "", "1.000277"], ["Ethanol", "", "1.36"], ["Sapphire", "", "1.762–1.778"], ["Bromine", "", "1.661"], ["Water", "589.29", "1.3330"], ["PMMA", "", "1.4893 - 1.4899"], ["Rock salt", "", "1.516"], ["Vacuum", "", "1 (by definition)"], ["Cytop", "", "1.34"], ["Water ice", "", "1.31"], ["Glycerol", "", "1.4729"], ["PETg", "", "1.57"], ["Ethyl alcohol (ethanol)", "589.29", "1.361"], ["PLA", "", "1.46"], ["Sugar Solution, 50%", "", "1.4200"], ["Sugar Solution, 25%", "", "1.3723"], ["Sugar Solution, 75%", "", "1.4774"], ["60% Glucose solution in water", "589.29", "1.4394"], ["10% Glucose solution in water", "589.29", "1.3477"], ["PET", "", "1.5750"], ["20% Glucose solution in water", "589.29", "1.3635"]] | 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 material does not have a wavelength above 500nm? | Zinc Oxide | 128 | Answer: |
Table InputTable: [["Date of Incident", "Offender", "Team", "Offense", "Date of Action", "Length"], ["May 6, 2012", "Claude Giroux", "Philadelphia Flyers", "Illegal hit to the head of Dainius Zubrus.", "May 7, 2012", "1 game‡ (1 post-season)"], ["April 15, 2012", "Craig Adams", "Pittsburgh Penguins", "Instigator penalty in the last five minutes of a game.", "April 16, 2012", "1 game‡ (1 post-season)"], ["September 21, 2011", "Jody Shelley", "Philadelphia Flyers", "Boarding Darryl Boyce.", "September 22, 2011", "10 games† (5 pre-season, 5 regular season)"], ["October 17, 2011", "Kris Letang", "Pittsburgh Penguins", "Boarding Alexander Burmistrov.", "October 18, 2011", "2 games"], ["December 20, 2011", "Deryk Engelland", "Pittsburgh Penguins", "Illegal hit to the head of Marcus Kruger.", "December 22, 2011", "3 games"], ["February 12, 2012", "Zac Rinaldo", "Philadelphia Flyers", "Charging Jonathan Ericsson.", "February 13, 2012", "2 games"], ["April 15, 2012", "Arron Asham", "Pittsburgh Penguins", "Cross-checking Brayden Schenn.", "April 17, 2012", "4 games‡ (3 post-season)*"], ["April 15, 2012", "James Neal", "Pittsburgh Penguins", "Charging Claude Giroux.", "April 17, 2012", "1 game‡ (1 post-season)"], ["March 8, 2012", "Mike Green", "Washington Capitals", "Illegal hit to the head of Brett Connolly.", "March 9, 2012", "3 games"], ["September 26, 2011", "Tom Sestito", "Philadelphia Flyers", "Checking Andre Deveaux from behind.", "September 28, 2011", "4 games† (2 pre-season, 2 regular season)"], ["January 22, 2012", "Alex Ovechkin", "Washington Capitals", "Charging Zbynek Michalek.", "January 23, 2012", "3 games"], ["January 8, 2012", "Jean-Francois Jacques", "Anaheim Ducks", "Illegal hit to the head of R.J. Umberger.", "January 9, 2012", "3 games"], ["January 14, 2012", "Dane Byers", "Columbus Blue Jackets", "Illegal hit to the head of Andrew Desjardins.", "January 16, 2012", "3 games"], ["April 14, 2012", "Nicklas Backstrom", "Washington Capitals", "Cross-checking Rich Peverley.", "April 17, 2012", "1 game‡ (1 post-season)"], ["November 26, 2011", "Max Pacioretty", "Montreal Canadiens", "Illegal hit to the head of Kris Letang.", "November 28, 2011", "3 games"], ["January 21, 2012", "Andrew Ference", "Boston Bruins", "Boarding Ryan McDonagh.", "January 22, 2012", "3 games"], ["September 28, 2011", "Brendan Smith", "Detroit Red Wings", "Illegal hit to the head of Ben Smith.", "September 30, 2011", "8 games† (3 pre-season, 5 regular season)"], ["April 14, 2012", "Andrew Shaw", "Chicago Blackhawks", "Charging goaltender Mike Smith.", "April 17, 2012", "3 games‡ (3 post-season)"], ["November 23, 2011", "Andre Deveaux", "New York Rangers", "Illegal hit to the head of Tomas Fleischmann.", "November 23, 2011", "3 games"], ["April 1, 2012", "Kyle Quincey", "Detroit Red Wings", "Charging Tomas Kopecky.", "April 2, 2012", "1 game"], ["April 17, 2012", "Raffi Torres", "Phoenix Coyotes", "Late charge to the head of Marian Hossa.", "April 21, 2012", "25 games\\nreduced to 21 games‡ (13 post-season)*"], ["December 3, 2011", "Jordin Tootoo", "Nashville Predators", "Charging goaltender Ryan Miller.", "December 6, 2011", "2 games"]] | 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 had more players with suspensions: the pittsburgh penguins or the philadelphia flyers? | Pittsburgh Penguins | 128 | Answer: |
Table InputTable: [["Year", "MVP", "Defensive Player of the Year", "Unsung Hero", "Newcomer of the Year"], ["2003", "Greg Sutton", "Gabriel Gervais", "David Fronimadis", "Martin Nash"], ["2004", "Gabriel Gervais", "Greg Sutton", "Zé Roberto", "Sandro Grande"], ["2002", "Eduardo Sebrango", "Gabriel Gervais", "Jason DiTullio", "Zé Roberto"], ["2006", "Mauricio Vincello", "Gabriel Gervais", "Andrew Weber", "Leonardo Di Lorenzo"], ["2008", "Matt Jordan", "Nevio Pizzolitto", "Joey Gjertsen", "Stefano Pesoli"], ["2011", "Hassoun Camara", "Evan Bush", "Simon Gatti", "Ian Westlake / Sinisa Ubiparipovic"], ["2010", "Philippe Billy", "Philippe Billy", "Tony Donatelli", "Ali Gerba"], ["2009", "David Testo", "Nevio Pizzolitto", "Adam Braz", "Stephen deRoux"], ["2007", "Leonardo Di Lorenzo", "Mauricio Vincello", "Simon Gatti", "Matt Jordan"], ["1996", "Paolo Ceccarelli", "–", "–", "–"], ["1993", "Patrice Ferri", "–", "–", "–"], ["1994", "Jean Harbor", "–", "–", "–"], ["1998", "Mauro Biello", "–", "–", "–"], ["2001", "Mauro Biello", "–", "–", "–"], ["1995", "Lloyd Barker", "–", "–", "–"], ["1997", "Mauro Biello", "–", "–", "–"], ["2000", "Jim Larkin", "–", "–", "–"], ["2005", "Mauro Biello", "Nevio Pizzolitto", "Mauricio Vincello", "Masahiro Fukazawa"], ["1999", "N/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:in what year did gabriel gervais win his first defensive player of the year award? | 2002 | 128 | Answer: |
Table InputTable: [["Wrestler:", "Times:", "Date:", "Location:", "Notes:"], ["Tigers Mask", "4", "May 19, 2013", "Osaka, Japan", "Defeated Billyken Kid in the finals of a four-man tournament to win the vacant title."], ["Super Delfin", "1", "January 4, 2000", "Tokyo, Japan", "Beat Dick Togo for the championship"], ["Asian Cougar / Kuuga", "1", "August 28, 2010", "Osaka, Japan", "Asian Cougar renamed himself Kuuga during his reign."], ["Super Delfin", "2", "June 18, 2000", "Osaka, Japan", ""], ["Super Delfin", "3", "January 3, 2002", "Osaka, Japan", ""], ["Super Delfin", "4", "February 26, 2006", "Osaka, Japan", ""], ["Vacated", "N/A", "March 30, 2013", "Osaka, Japan", "Title vacated, after Harada announced that he was not re-signing with Osaka Pro after his contract ran out on April 29, 2013."], ["Tigers Mask", "3", "April 29, 2011", "Osaka, Japan", ""], ["Tigers Mask", "1", "February 12, 2007", "Osaka, Japan", ""], ["Tigers Mask", "2", "July 29, 2010", "Osaka, Japan", ""], ["Daisuke Harada", "2", "July 22, 2012", "Osaka, Japan", ""], ["Hideyoshi", "1", "July 26, 2008", "Osaka, Japan", ""], ["“Big Boss” MA-G-MA", "1", "October 2, 2004", "Osaka, Japan", ""], ["Super Dolphin", "1", "February 13, 2005", "Osaka, Japan", ""], ["Takehiro Murahama", "2", "July 6, 2003", "Osaka, Japan", ""], ["Takehiro Murahama", "1", "May 7, 2000", "Tokyo, Japan", ""], ["Daisuke Harada", "1", "February 26, 2012", "Osaka, Japan", ""], ["Dick Togo", "1", "July 25, 2009", "Osaka, Japan", ""], ["Black Buffalo", "1", "March 25, 2012", "Osaka, Japan", ""], ["Quiet Storm", "1", "July 21, 2013", "Osaka, Japan", ""], ["Gamma", "1", "June 24, 2001", "Osaka, Japan", ""], ["CIMA", "1", "June 18, 2010", "Osaka, Japan", ""], ["Daio QUALLT", "1", "April 17, 2004", "Osaka, Japan", ""], ["Zeus", "1", "January 19, 2014", "Osaka, Japan", ""], ["Billyken Kid", "3", "February 15, 2009", "Osaka, Japan", ""], ["Billyken Kid", "5", "August 14, 2011", "Osaka, Japan", ""], ["Billyken Kid", "4", "February 11, 2010", "Osaka, Japan", ""], ["Billyken Kid", "1", "August 8, 2004", "Osaka, Japan", ""], ["Billyken Kid", "2", "August 26, 2006", "Osaka, Japan", ""]] | 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 won the most titles? | Billyken Kid | 128 | Answer: |
Table InputTable: [["Season/Torneo", "Jornada or Other", "Home Team", "Result", "Away Team", "Stadium", "Date"], ["1983–1984 season", "21", "América", "1–1", "Chivas", "Estadio Azteca", "22 January 1984"], ["1984–1985 season", "13", "América", "0–0", "Chivas", "Estadio Azteca", "11 December 1984"], ["1988–1989 season", "31", "América", "3–1", "Chivas", "Estadio Azteca", "30 April 1989"], ["1990-1991 Season", "12", "Chivas", "1-1", "América", "Estadio Jalisco", "December 9, 1990"], ["1983–1984 season", "2", "Chivas", "1–1", "América", "Estadio Jalisco", "11 September 1983"], ["1987–1988 Season", "15", "América", "1–0", "Chivas", "Estadio Azteca", "20 December 1987"], ["1991-1992 Season", "21", "Chivas", "0-0", "América", "Estadio Jalisco", "January 19, 1992"], ["1993-1994 Season", "23", "América", "1-0", "Chivas", "Estadio Azteca", "January 5, 1994"], ["1988–1989 season", "12", "Chivas", "2–2", "América", "Estadio Jalisco", "29 December 1988"], ["1992-1993 Season", "22", "América", "2-1", "Chivas", "Estadio Azteca", "January 10, 1993"], ["1986–1987 season", "3", "América", "1–0", "Chivas", "Estadio Azteca", "17 August 1986"], ["1984–1985 season", "32", "Chivas", "0–0", "América", "Estadio Jalisco", "24 March 1985"], ["1992-1993 Season", "3", "Chivas", "1-0", "América", "Estadio Jalisco", "August 30, 1992"], ["1989-1990 Season", "22", "América", "2-2", "Chivas", "Estadio Azteca", "January 14, 1990"], ["1991-1992 Season", "2", "América", "1-1", "Chivas", "Estadio Azteca", "September 22, 1991"], ["1994-1995 Season", "30", "América", "0-0", "Chivas", "Estadio Azteca", "March 19, 1995"], ["1995-1996 Season", "9", "Chivas", "0-2", "América", "Estadio Jalisco", "October 22, 1995"], ["Invierno 1998", "8", "Chivas", "1-0", "América", "Estadio Jalisco", "September 20, 1998"], ["Clausura 2012", "14", "Chivas", "0-1", "America", "Estadio Omnilife", "April 8, 2012"], ["1986–1987 season", "24", "Chivas", "2–2", "América", "Estadio Jalisco", "11 January 1987"], ["Clausura 2004", "17", "Chivas", "0-1", "América", "Estadio Jalisco", "May 1, 2004"], ["1993-1994 Season", "4", "Chivas", "0-0", "América", "Estadio Jalisco", "September 5, 1993"], ["Clausura 2009", "14", "Chivas", "1-0", "América", "Estadio Jalisco", "April 19, 2009"], ["1988-1989 Season", "Liquilla", "Chivas", "1-2", "América", "Estadio Jalisco", "June 25, 1989"], ["Clausura 2006", "7", "Chivas", "1-0", "América", "Estadio Jalisco", "February 26, 2006"], ["Bicentenario 2010", "13", "Chivas", "1-0", "America", "Estadio Jalisco", "April 4, 2010"]] | 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 result of the first season listed on the table? | 11 | 128 | Answer: |
Table InputTable: [["Year", "Chassis", "Engine", "Start", "Finish", "Team"], ["2007", "Dallara", "Honda", "1", "3", "Team Penske"], ["2009", "Dallara", "Honda", "1", "1", "Team Penske"], ["2013", "Dallara", "Chevrolet", "8", "6", "Team Penske"], ["2001", "Dallara", "Oldsmobile", "11", "1", "Team Penske"], ["2006", "Dallara", "Honda", "2", "25", "Team Penske"], ["2011", "Dallara", "Honda", "16", "17", "Team Penske"], ["2008", "Dallara", "Honda", "4", "4", "Team Penske"], ["2010", "Dallara", "Honda", "1", "9", "Team Penske"], ["2003", "Dallara", "Toyota", "1", "2", "Team Penske"], ["2002", "Dallara", "Chevrolet", "13", "1", "Team Penske"], ["2004", "Dallara", "Toyota", "8", "9", "Team Penske"], ["2012", "Dallara", "Chevrolet", "6", "10", "Team Penske"], ["2005", "Dallara", "Toyota", "5", "9", "Team Penske"]] | 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 first place finishes did team penske have between 2001 and 2013? | 3 | 128 | Answer: |
Table InputTable: [["Year", "Car", "Start", "Qual", "Rank", "Finish", "Laps", "Led", "Retired"], ["1928", "8", "4", "117.031", "4", "10", "200", "33", "Running"], ["1933", "34", "12", "113.578", "15", "7", "200", "0", "Running"], ["1934", "8", "7", "113.733", "13", "17", "94", "0", "Rod"], ["1930", "9", "20", "100.033", "18", "20", "79", "0", "Valve"], ["1939", "62", "27", "121.749", "24", "11", "200", "0", "Running"], ["1938", "17", "4", "122.499", "6", "17", "130", "0", "Rod"], ["1927", "27", "27", "107.765", "22", "3", "200", "0", "Running"], ["1926", "31", "12", "102.789", "13", "11", "142", "0", "Flagged"], ["1932", "25", "20", "108.896", "34", "13", "184", "0", "Flagged"], ["1937", "38", "7", "118.788", "16", "8", "200", "0", "Running"], ["1931", "37", "19", "111.725", "6", "18", "167", "0", "Crash T4"], ["1929", "23", "11", "112.146", "15", "17", "91", "0", "Supercharger"], ["1935", "44", "6", "115.459", "11", "21", "102", "0", "Magneto"], ["Totals", "Totals", "Totals", "Totals", "Totals", "Totals", "1989", "33", ""]] | 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:was the finish in 1930 above/below 12? | above | 128 | Answer: |
Table InputTable: [["Subject", "Robot's Name", "Who?", "When?", "Where?", "Occupation"], ["Writing", "Eraser-Bot", "Sumerians", "3,500 B.C.", "Middle East", "Pencil Man"], ["Sausage", "Sock-Bot", "Babylonians", "3,000 B.C.", "Middle East", "Sock Man"], ["Boomerang", "Oswald the Mailman Robot", "Aborigines", "40,000 years ago", "Australia", "Mailman"], ["Olympics", "Rhonda Robot", "Greeks", "776 B.C.", "Greece", "Beauty queen"], ["Wheel", "Rollin' Road-Bot", "Sumerians", "3,000 B.C.", "Middle East", "Race Starter"], ["Round Earth", "Vasco da Robot", "Ferdinand Magellan", "1522", "Spain", "Early Sailor"], ["Tools", "Hank the Handyman Robot", "Stone-Age Humans", "2½ million years ago", "Africa", "Mechanic"], ["Painting", "Pierro-Bot", "Stone-Age Humans", "35,000 B.C.", "Europe", "Clown/Artist"], ["Saxophone", "Bongo-Bot the Six-Armed Robot", "Antoine-Joseph Sax", "1846", "France", "Six-Armed Drum Player"], ["Toilet", "Brunwella the Bombshell", "Minoans", "2000 B.C.", "Crete", "Demolisher"], ["Germs", "Roast-Bot", "Louis Pasteur", "1865", "France", "Firefighter"], ["Dynamite", "Robby Robot", "Alfred Nobel", "1866", "Sweden", "Prankster"], ["Nursing", "Dr. Bug-Bot", "Florence Nightengale", "1860", "England", "Doctor"], ["Coins", "Verna the Vend-Bot", "Lydians", "600 B.C.", "Turkey", "Vending Machine"], ["Solar System", "Cosmo-Bot", "Copernicus", "1531", "Poland", "Cosmonaut"], ["Chewing Gum", "Bubble-Bot", "Mayans", "400", "Mexico", "Bubble Man"], ["Helicopter", "Amelia Air-Bot", "Leonardo da Vinci", "1483", "Italy", "Pilot"], ["Basketball", "Danny Defrost-Bot", "James Naismith", "1891", "United States", "Snowman"], ["Radium", "Miss Battery-Bot", "Marie Curie", "1898", "France", "Battery Lady"], ["Bicycle", "Booster-Bot", "Karl von Drais", "1816", "Germany", "Rocket Man"], ["Microscope", "Slobot", "Antonie van Leeuwenhoek", "1674", "The Netherlands", "Dirty Person"], ["Paper", "Noshi Origami", "Ts'ai Lun", "105", "China", "Origami Maker"], ["Scuba Gear", "Flip the High-Diving Robot", "Jacques Cousteau", "1946", "France", "Diver"], ["Corn Flakes", "Chef Boy-Robot", "William Kellogg", "1894", "Battle Creek, Michigan", "Cook"], ["Phonograph", "Slide the Heavy-Metal Robot", "Thomas Edison", "1877", "New Jersey", "Rock Star"]] | 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 there more robtos from the middle east or africa? | Middle East | 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", "–", "–"], ["Southeastern", "6", "10–6", ".625", "5", "3", "1", "1", "–"], ["Big Eight", "4", "3–4", ".429", "2", "1", "–", "–", "–"], ["Western Athletic", "1", "1–1", ".500", "1", "–", "–", "–", "–"], ["Southwest", "4", "5–4", ".556", "3", "2", "–", "–", "–"], ["Mid-Continent", "2", "0–2", "–", "–", "–", "–", "–", "–"], ["West Coast", "2", "0–2", "–", "–", "–", "–", "–", "–"], ["Colonial", "1", "1–1", ".500", "1", "–", "–", "–", "–"], ["Metro", "2", "2–2", ".500", "1", "1", "–", "–", "–"], ["Pacific-10", "5", "8–5", ".615", "4", "2", "2", "–", "–"], ["Big Ten", "5", "9–5", ".643", "4", "2", "2", "1", "–"], ["Great Midwest", "2", "0–2", "–", "–", "–", "–", "–", "–"], ["Sun Belt", "2", "6–2", ".750", "2", "1", "1", "1", "1"], ["Missouri Valley", "2", "2–2", ".500", "2", "–", "–", "–", "–"], ["Atlantic 10", "3", "1–3", ".250", "1", "–", "–", "–", "–"], ["Atlantic Coast", "3", "9–2", ".818", "3", "2", "1", "1", "1"], ["Big Sky", "2", "1–2", ".333", "1", "–", "–", "–", "–"], ["Big West", "2", "0–2", "–", "–", "–", "–", "–", "–"]] | 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:which conference has the most number of bids? | Southeastern | 128 | Answer: |
Table InputTable: [["Model", "Volume", "Engine", "Fuel", "Power/Torque", "Years produced", "Produced"], ["740d", "3.9L", "M67D40 turbocharged V8", "Diesel", "180 kW (245 PS; 241 hp) / 560 N·m (413 lb·ft)", "1998–2001", "3450"], ["730d", "2.9L", "M57D30 turbocharged I6", "Diesel", "142 kW (193 PS; 190 hp) / 410 N·m (302 lb·ft)", "1998–2001", "12336"], ["735iL", "3.5L", "M62TUB35 V8", "Petrol", "174 kW (237 PS; 233 hp) / 345 N·m (254 lb·ft)", "1998–2001", ""], ["735i", "3.5L", "M62TUB35 V8", "Petrol", "174 kW (237 PS; 233 hp) / 345 N·m (254 lb·ft)", "1998–2001", ""], ["740iL", "4.4L", "M62TUB44 V8", "Petrol", "210 kW (286 PS; 282 hp) / 440 N·m (325 lb·ft)", "1998–2001", ""], ["740i", "4.4L", "M62TUB44 V8", "Petrol", "210 kW (286 PS; 282 hp) / 440 N·m (325 lb·ft)", "1998–2001", ""], ["750i-iL", "5.4L", "M73TUB54 V12", "Petrol", "240 kW (326 PS; 322 hp) / 490 N·m (361 lb·ft)", "1998–2001", "1032"], ["740i", "4.4L", "M62B44 V8", "Petrol", "210 kW (286 PS; 282 hp) / 420 N·m (310 lb·ft)", "1996–1998", "88853"], ["740iL", "4.4L", "M62B44 V8", "Petrol", "210 kW (286 PS; 282 hp) / 420 N·m (310 lb·ft)", "1996–1998", "91431"], ["735iL", "3.5L", "M62B35 V8", "Petrol", "173 kW (235 PS; 232 hp) / 320 N·m (236 lb·ft)", "1994–1997", "6963"], ["725tds", "2.5L", "M51D25 turbocharged I6", "Diesel", "105 kW (143 PS; 141 hp) / 280 N·m (207 lb·ft)", "1995–2001", "9053"], ["735i", "3.5L", "M62B35 V8", "Petrol", "173 kW (235 PS; 232 hp) / 320 N·m (236 lb·ft)", "1994–1997", "21481"], ["728i", "2.8L", "M52B28 I6", "Petrol", "142 kW (193 PS; 190 hp) / 280 N·m (207 lb·ft)", "1996–2001", "38947"], ["728iL", "2.8L", "M52B28 I6", "Petrol", "142 kW (193 PS; 190 hp) / 280 N·m (207 lb·ft)", "1996–2001", "6816"], ["730i", "3.0L", "M60B30 V8", "Petrol", "160 kW (218 PS; 215 hp) / 290 N·m (214 lb·ft)", "1994–1996", "20876"], ["740iL", "4.0L", "M60B40 V8", "Petrol", "210 kW (286 PS; 282 hp) / 400 N·m (295 lb·ft)", "1994–1996", ""], ["730iL", "3.0L", "M60B30 V8", "Petrol", "160 kW (218 PS; 215 hp) / 290 N·m (214 lb·ft)", "1994–1996", "2137"]] | 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:list each of the models with diesel fuel produced from 1998-2001. | M57D30 turbocharged I6, M67D40 turbocharged V8 | 128 | Answer: |
Table InputTable: [["#", "Date", "Location", "Winner", "Score\\nJSU", "Score\\nTU", "Series"], ["8", "November 11, 1938", "Jacksonville, AL", "Tied", "6", "6", "TSU 4–3–1"], ["6", "November 10, 1933", "Jacksonville, AL", "Troy State", "7", "18", "Tied 3–3"], ["38", "November 11, 1972", "Jacksonville, AL", "Tied", "14", "14", "JSU 22–14–2"], ["21", "October 15, 1955", "Troy, AL", "Jacksonville State", "12", "0", "Tied 10–10–1"], ["3", "November 16, 1928", "Troy, AL", "Jacksonville State", "20", "0", "JSU 3–0"], ["62", "November 18, 2000", "Jacksonville, AL", "Troy State", "0", "28", "JSU 32–28–2"], ["17", "October 13, 1951", "Troy, AL", "Jacksonville State", "13", "7", "Tied 8–8–1"], ["5", "November 12, 1932", "Montgomery, AL", "Troy State", "0", "20", "JSU 3–2"], ["34", "October 19, 1968", "Jacksonville, AL", "Troy State", "0", "31", "JSU 21–12–1"], ["59", "November 22, 1997", "Troy, AL", "Troy State", "0", "49", "JSU 32–25–2"], ["9", "November 11, 1939", "Troy, AL", "Troy State", "0", "27", "TSU 5–3–1"], ["7", "October 26, 1934", "Troy, AL", "Troy State", "0", "32", "TSU 4–3"], ["2", "October 28, 1927", "?", "Jacksonville State", "26", "12", "JSU 2–0"], ["54", "November 5, 1988", "Jacksonville, AL", "Jacksonville State", "31", "3", "JSU 30–22–2"], ["1", "November 27, 1924", "Jacksonville, AL", "Jacksonville State", "14", "9", "JSU 1–0"], ["10", "November 8, 1940", "Troy, AL", "Troy State", "0", "7", "TSU 6–3–1"], ["14", "December 18, 1948", "Pensacola, FL", "Jacksonville State", "19", "0", "TSU 7–6–1"], ["12", "October 17, 1947", "Troy, AL", "Jacksonville State", "14", "0", "TSU 7–4–1"], ["11", "October 17, 1946", "Anniston, AL", "Troy State", "0", "12", "TSU 7–3–1"], ["61", "November 20, 1999", "Troy, AL", "Troy State", "16", "35", "JSU 32–27–2"], ["50", "November 10, 1984", "Jacksonville, AL", "Troy State", "39", "42", "JSU 29–19–2"], ["60", "November 21, 1998", "Jacksonville, AL", "Troy State", "7", "31", "JSU 32–26–2"], ["49", "November 12, 1983", "Troy, AL", "Troy State", "3", "45", "JSU 29–18–2"], ["48", "November 13, 1982", "Jacksonville, AL", "Jacksonville State", "49", "14", "JSU 29–17–2"], ["4", "October 3, 1931", "Jacksonville, AL", "Troy State", "6", "24", "JSU 3–1"], ["30", "October 3, 1964", "Jacksonville, AL", "Jacksonville State", "38", "0", "JSU 19–10–1"]] | 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 is the least amount of points scored in a tie game? | 6 | 128 | Answer: |
Table InputTable: [["Team", "City", "Venue", "Capacity", "Head Coach", "Team Captain", "Past Season"], ["Persepolis", "Tehran", "Azadi", "90,000", "Nelo Vingada", "Karim Bagheri", "Champion"], ["Aboomoslem", "Mashhad", "Samen", "35,000", "Ali Hanteh", "Saeed Khani", "4th"], ["Foolad", "Ahvaz", "Takhti Ahvaz", "15,000", "Majid Jalali", "Ali Badavi", "Qualifier"], ["Payam", "Mashhad", "Samen", "35,000", "Kazem Ghiyasiyan", "Mehdi Hasheminasab", "Qualifier"], ["Rah Ahan", "Rey, Iran", "Rah Ahan", "15,000", "Mehdi Tartar", "Ahmad Taghavi", "12th"], ["Saba Qom", "Qom", "Yadegar Emam", "15,000", "Firouz Karimi", "Yahya Golmohammadi", "3rd"], ["Esteghlal", "Tehran", "Azadi", "90,000", "Amir Ghalenoei", "Farhad Majidi", "13th"], ["Malavan", "Anzali", "Takhti Anzali", "8,000", "Mohammad Ahmadzadeh", "Masoud Gholamalizad", "16th"], ["Paykan", "Qazvin", "Shahid Rajaei", "5,000", "Ali Asghar Modir Roosta", "Mohammad Reza Tahmasebi", "9th"], ["Damash Gilan", "Rasht", "Sardar Jangal", "15,000", "Stanko Poklepović", "Mohammad Reza Mahdavi", "15th"], ["Pas Hamedan", "Hamedan", "Ghods", "5,000", "Vinko Begovic", "Omid Khouraj", "5th"], ["Bargh Shiraz", "Shiraz", "Hafezieh", "20,000", "Rasoul Korbekandi", "Sattar Zare", "7th"], ["Mes Kerman", "Kerman", "Shahid Bahonar", "15,000", "Parviz Mazloomi", "Farzad Hosseinkhani", "10th"], ["Zob Ahan", "Esfahan", "Foolad Shahr", "25,000", "Mansour Ebrahimzadeh", "Mohammad Salsali", "6th"], ["Est. Ahvaz", "Ahvaz", "Takhti Ahvaz", "30,000", "Khodadad Azizi", "Afshin Komaei", "8th"], ["Moghavemat", "Shiraz", "Hafezieh", "20,000", "Gholam Hossein Peyrovani", "Mostafa Sabri", "14th"], ["Sepahan", "Esfahan", "Foolad Shahr", "25,000", "Farhad Kazemi", "Moharram Navidkia", "2nd"], ["Saipa", "Karaj", "Enghelab Karaj", "15,000", "Mohammad Mayeli Kohan", "Ebrahim Sadeghi", "11th"]] | 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:ali hanteh is the head coach, but for what team? | Aboomoslem | 128 | Answer: |
Table InputTable: [["Year", "Division", "League", "Reg. Season", "Playoffs"], ["2006", "1", "USL W-League", "5th, Western", ""], ["2007", "1", "USL W-League", "5th, Western", ""], ["2005", "1", "USL W-League", "6th, Western", ""], ["2013", "1", "USL W-League", "4th, Western", "Did not qualify"], ["2008", "1", "USL W-League", "6th, Western", "Did not qualify"], ["2009", "1", "USL W-League", "7th, Western", "Did not qualify"], ["2011", "1", "USL W-League", "7th, Western", "Did not qualify"], ["2012", "1", "USL W-League", "4th, Western", "Did not qualify"], ["2003", "2", "USL W-League", "5th, Western", ""], ["2004", "1", "USL W-League", "8th, Western", ""], ["2010", "1", "USL W-League", "6th, Western", "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 many times have the colorado rapids women finished outside of the top 5 teams in the usl w-league western division 1? | 6 | 128 | Answer: |
Table InputTable: [["Year", "Competition", "Venue", "Position", "Event", "Notes"], ["2006", "Commonwealth Games", "Melbourne, Australia", "4th", "Discus throw", "60.99 m"], ["2003", "All-Africa Games", "Abuja, Nigeria", "2nd", "Discus throw", "62.86 m"], ["2004", "African Championships", "Brazzaville, Republic of the Congo", "2nd", "Discus throw", "63.50 m"], ["2000", "World Junior Championships", "Santiago, Chile", "1st", "Discus throw", "59.51 m"], ["2003", "All-Africa Games", "Abuja, Nigeria", "5th", "Shot put", "17.76 m"], ["2008", "African Championships", "Addis Ababa, Ethiopia", "2nd", "Discus throw", "56.98 m"], ["2004", "Olympic Games", "Athens, Greece", "8th", "Discus throw", "62.58 m"], ["2006", "Commonwealth Games", "Melbourne, Australia", "7th", "Shot put", "18.44 m"], ["2007", "All-Africa Games", "Algiers, Algeria", "3rd", "Discus throw", "57.79 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:what was hopley's best throw for the discuss? | 63.50 m | 128 | Answer: |
Table InputTable: [["Year", "Network", "NASCAR\\nCountdown", "Lap-by-lap", "Color commentator(s)", "Pit reporters", "Ratings", "Viewers"], ["2010", "ESPN", "Allen Bestwick\\nRusty Wallace\\nBrad Daugherty\\nRay Evernham", "Marty Reid", "Dale Jarrett\\nAndy Petree", "Dave Burns\\nJamie Little\\nJerry Punch\\nVince Welch", "3.6 (4.2 cable)", "5.709 million"], ["2012", "ESPN", "Nicole Briscoe\\nRusty Wallace\\nBrad Daugherty\\nRay Evernham", "Allen Bestwick", "Dale Jarrett\\nAndy Petree", "Dave Burns\\nJamie Little\\nJerry Punch\\nVince Welch", "3.3", "5.1 million"], ["2008", "ESPN", "Allen Bestwick\\nRusty Wallace\\nBrad Daugherty", "Jerry Punch", "Dale Jarrett\\nAndy Petree", "Dave Burns\\nJamie Little\\nShannon Spake\\nMike Massaro", "4.3 (5.1 cable)", "6.668 million"], ["2009", "ESPN", "Allen Bestwick\\nRusty Wallace\\nBrad Daugherty\\nRay Evernham", "Jerry Punch", "Dale Jarrett\\nAndy Petree", "Dave Burns\\nJamie Little\\nShannon Spake\\nVince Welch", "4.1 (4.8 cable)", "6.487 million"], ["2013", "ESPN", "Nicole Briscoe\\nRusty Wallace\\nBrad Daugherty\\nRay Evernham", "Allen Bestwick", "Dale Jarrett\\nAndy Petree", "Dave Burns\\nJamie Little\\nJerry Punch\\nVince Welch", "3.6", "5.5 million"], ["2011", "ESPN", "Nicole Briscoe\\nRusty Wallace\\nBrad Daugherty", "Allen Bestwick", "Dale Jarrett\\nAndy Petree", "Dave Burns\\nJamie Little\\nJerry Punch\\nVince Welch", "4.0 (4.6 cable)", "6.337 million"], ["2007", "ESPN", "Brent Musburger\\nSuzy Kolber\\nBrad Daugherty", "Jerry Punch", "Rusty Wallace\\nAndy Petree", "Dave Burns\\nJamie Little\\nAllen Bestwick\\nMike Massaro", "4.2 (4.9 cable)", "6.574 million"], ["2014", "ESPN", "", "", "", "", "", ""]] | 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 only year that allen bestwick a pit reporter? | 2007 | 128 | Answer: |
Table InputTable: [["Eps #", "Prod #", "Title", "Summary", "Air Date"], ["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"], ["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"], ["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"], ["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"], ["14", "15", "Galactus", "The Watcher has made strange events in hope of preventing the Silver Surfer from coming but the plan fails and the Surfer summons Galactus. Susan assists the unconscious Surfer and he begins to think differently. The Watcher has a plan only Johnny can undergo. Reed and Ben sabotage Galactus' Earth draining machine and the Silver Surfer arrives to battle Galactus. This angers Galactus, but Johnny gets back with the weapon that makes Galactus see reason not to destroy the Earth. NOTE: In the episode \"Galactus\", Susan Richards (The Invisible Girl) has the role originated by Alicia Masters (explaining to the Silver Surfer about humanity).", "12/16/1967"], ["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"]] | 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 episode has the same episode and production numbers? | Danger In The Depths | 128 | Answer: |
Table InputTable: [["Event", "Record", "Athlete", "Date", "Meet", "Place"], ["Half marathon", "1:00:28 #", "Germán Silva", "24 September 1994", "World Half Marathon Championships", "Oslo, Norway"], ["20 km (road)", "58:26+ #", "Juan Carlos Romero", "11 October 2009", "World Half Marathon Championships", "Birmingham, United Kingdom"], ["Half marathon", "1:00:14 a #", "Armando Quintanilla", "21 January 1996", "Tokyo Half Marathon", "Tokyo, Japan"], ["110 m hurdles", "13.81 (+0.8 m/s)", "Roberto Carmona", "22 July 1988", "Ibero-American Championships", "Mexico City, Mexico"], ["25 km (road)", "1:14:54+ #", "Juan Luis Barrios", "6 March 2011", "Lala Marathon", "Torreón, Mexico"], ["Marathon", "2:08:30 #", "Dionicio Cerón Pizarro", "2 April 1995", "London Marathon", "London, United Kingdom"], ["30 km (road)", "1:30:19+", "Juan Luis Barrios", "6 March 2011", "Lala Marathon", "Torreón, Mexico"], ["Long jump", "8.46 m (+1.3 m/s)", "Luis Rivera", "12 July 2013", "Universiade", "Kazan, Russia"], ["Decathlon", "10.2 (+0.1 m/s) (100 m), 7.72 m (+1.3 m/s) (long jump), 12.55 m (shot put), 1.74 m (high jump), 46.33 (400 m) /\\n15.73 (0.0 m/s) (110 m hurdles), 38.32 m (discus), 4.40 m (pole vault), 57.28 m (javelin), 4:52.35 (1500 m)", "10.2 (+0.1 m/s) (100 m), 7.72 m (+1.3 m/s) (long jump), 12.55 m (shot put), 1.74 m (high jump), 46.33 (400 m) /\\n15.73 (0.0 m/s) (110 m hurdles), 38.32 m (discus), 4.40 m (pole vault), 57.28 m (javelin), 4:52.35 (1500 m)", "10.2 (+0.1 m/s) (100 m), 7.72 m (+1.3 m/s) (long jump), 12.55 m (shot put), 1.74 m (high jump), 46.33 (400 m) /\\n15.73 (0.0 m/s) (110 m hurdles), 38.32 m (discus), 4.40 m (pole vault), 57.28 m (javelin), 4:52.35 (1500 m)", "10.2 (+0.1 m/s) (100 m), 7.72 m (+1.3 m/s) (long jump), 12.55 m (shot put), 1.74 m (high jump), 46.33 (400 m) /\\n15.73 (0.0 m/s) (110 m hurdles), 38.32 m (discus), 4.40 m (pole vault), 57.28 m (javelin), 4:52.35 (1500 m)", "10.2 (+0.1 m/s) (100 m), 7.72 m (+1.3 m/s) (long jump), 12.55 m (shot put), 1.74 m (high jump), 46.33 (400 m) /\\n15.73 (0.0 m/s) (110 m hurdles), 38.32 m (discus), 4.40 m (pole vault), 57.28 m (javelin), 4:52.35 (1500 m)"], ["4x400 m relay", "3:03.19", "Mexico\\nAlejandro Cárdenas\\nOscar Juanz\\nRoberto Carvajal\\nJuan Pedro Toledo", "11 August 2001", "World Championships", "Edmonton, Canada"], ["Marathon", "2:07:19 a", "Andrés Espinosa", "18 April 1994", "Boston Marathon", "Boston, United States"], ["4x100 m relay", "39.32", "Mexico\\nGenaro Rojas\\nEduardo Nava\\nHerman Adam\\nAlejandro Cárdenas", "21 June 1992", "", "Mexico City, Mexico"]] | 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 it take for silva to finish the half marathon? | 1:00:28 | 128 | Answer: |
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