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You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:which country had the most cyclists finish within the top 10? | [['Rank', 'Cyclist', 'Team', 'Time', 'UCI ProTour\\nPoints'], ['8', 'Stéphane Goubert\xa0(FRA)', 'Ag2r-La Mondiale', '+ 2"', '5'], ['4', 'Paolo Bettini\xa0(ITA)', 'Quick Step', 's.t.', '20'], ['3', 'Davide Rebellin\xa0(ITA)', 'Gerolsteiner', 's.t.', '25'], ['9', 'Haimar Zubeldia\xa0(ESP)', 'Euskaltel-Euskadi', '+ 2"', '3'], ['6', 'Denis Menchov\xa0(RUS)', 'Rabobank', 's.t.', '11'], ['7', 'Samuel Sánchez\xa0(ESP)', 'Euskaltel-Euskadi', 's.t.', '7'], ['10', 'David Moncoutié\xa0(FRA)', 'Cofidis', '+ 2"', '1'], ['5', 'Franco Pellizotti\xa0(ITA)', 'Liquigas', 's.t.', '15'], ['1', 'Alejandro Valverde\xa0(ESP)', "Caisse d'Epargne", '5h 29\' 10"', '40'], ['2', 'Alexandr Kolobnev\xa0(RUS)', 'Team CSC Saxo Bank', 's.t.', '30']] | Italy | Answer: | 128 | 10 | 310 |
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 people were murdered in 1940/41? | [['Description Losses', '1939/40', '1940/41', '1941/42', '1942/43', '1943/44', '1944/45', 'Total'], ['Deaths other countries', '', '', '', '', '', '', '2,000'], ['Total', '504,000', '352,000', '407,000', '541,000', '681,000', '270,000', '2,770,000'], ['Murdered in Eastern Regions', '', '', '', '', '', '100,000', '100,000'], ['Deaths Outside of Prisons & Camps', '', '42,000', '71,000', '142,000', '218,000', '', '473,000'], ['Murdered', '75,000', '100,000', '116,000', '133,000', '82,000', '', '506,000'], ['Deaths In Prisons & Camps', '69,000', '210,000', '220,000', '266,000', '381,000', '', '1,146,000'], ['Direct War Losses', '360,000', '', '', '', '', '183,000', '543,000']] | 100,000 | Answer: | 128 | 7 | 263 |
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 the new york americans to win the national cup after 1936? | [['Year', 'Division', 'League', 'Reg. Season', 'Playoffs', 'National Cup'], ['1944/45', 'N/A', 'ASL', '9th', 'No playoff', '?'], ['1949/50', 'N/A', 'ASL', '3rd', 'No playoff', '?'], ['1955/56', 'N/A', 'ASL', '6th', 'No playoff', '?'], ['1943/44', 'N/A', 'ASL', '9th', 'No playoff', '?'], ['1940/41', 'N/A', 'ASL', '6th', 'No playoff', '?'], ['1950/51', 'N/A', 'ASL', '5th', 'No playoff', '?'], ['1954/55', 'N/A', 'ASL', '8th', 'No playoff', '?'], ['1939/40', 'N/A', 'ASL', '4th', 'No playoff', '?'], ['1935/36', 'N/A', 'ASL', '1st', 'Champion (no playoff)', '?'], ['1933/34', 'N/A', 'ASL', '2nd', 'No playoff', '?'], ['1937/38', 'N/A', 'ASL', '3rd(t), National', '1st Round', '?'], ['Fall 1932', '1', 'ASL', '3rd', 'No playoff', 'N/A'], ['Spring 1932', '1', 'ASL', '5th?', 'No playoff', '1st Round'], ['1953/54', 'N/A', 'ASL', '1st', 'Champion (no playoff)', 'Champion'], ['1947/48', 'N/A', 'ASL', '6th', 'No playoff', '?'], ['1952/53', 'N/A', 'ASL', '6th', 'No playoff', 'Semifinals'], ['1948/49', 'N/A', 'ASL', '1st(t)', 'Finals', '?'], ['1931', '1', 'ASL', '6th (Fall)', 'No playoff', 'N/A'], ['1938/39', 'N/A', 'ASL', '4th, National', 'Did not qualify', '?'], ['1936/37', 'N/A', 'ASL', '5th, National', 'Did not qualify', 'Champion'], ['1941/42', 'N/A', 'ASL', '3rd', 'No playoff', '?'], ['1934/35', 'N/A', 'ASL', '2nd', 'No playoff', '?'], ['Spring 1933', '1', 'ASL', '?', '?', 'Final'], ['1951/52', 'N/A', 'ASL', '6th', 'No playoff', '?'], ['1946/47', 'N/A', 'ASL', '6th', 'No playoff', '?'], ['1945/46', 'N/A', 'ASL', '5th', 'No playoff', '?'], ['1942/43', 'N/A', 'ASL', '6th', 'No playoff', '?']] | 17 years | Answer: | 128 | 27 | 694 |
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:alfie's birthday party aired on january 19. what was the airdate of the next episode? | [['Series #', 'Season #', 'Title', 'Notes', 'Original air date'], ['9', '1', '"Dee Dee Runs Away"', "Dee Dee has been waiting to go to a monster truck show all week. But Alfie and Goo's baseball team makes it to the tournament and everyone forgets about the monster truck show. Dee Dee feels ignored and runs away from home with Harry and Donnell. It's up to Alfie and Goo to try and convince him to come home.", 'December 28, 1994'], ['12', '1', '"Candy Sale"', "Alfie and Goo are selling candy to make money for some expensive jackets, but they are not having any luck. However, when Dee Dee start helping them sell candy, they start to make money and asks him to help them out. Soon Goo and Alfie finds themselves confronted by Melanie, Deonne, Harry and Donnell for Dee Dee's share of the money. They soon learn the boys have used the money to buy three expensive jackets for themselves and Dee Dee as a token of their gratitude. They quickly apologize to Alfie and Goo for their quick judgment.", 'January 26, 1995'], ['11', '1', '"Alfie\'s Birthday Party"', "Goo and Melanie pretend they are dating and they leave Alfie out of everything. He ends up bored and starts hanging out with Dee Dee and his friends. However, it just isn't the same without Goo. Later on, Alfie learns about the surprise birthday party that Goo and Melanie had been planning with everyone else (except for Dee Dee, who couldn't know since he would've told).", 'January 19, 1995'], ['4', '1', '"Robin Hood Play"', "Alfie's school is performing the play Robin Hood and Alfie is chosen to play the part of Robin Hood. Alfie is excited at this prospect, but he does not want to wear tights because he feels that tights are for girls. However, he reconsiders his stance on tights when Dee Dee wisely tells him not to let that affect his performance as Robin Hood.", 'November 9, 1994'], ['6', '1', '"Where\'s the Snake?"', "Dee Dee gets a snake, but he doesn't want his parents to know about it. However, things get complicated when he loses the snake in the house. Meanwhile, Melanie and Deonne are assigned by their teacher to take care of her beloved pet rabbit, Duchess for the weekend. This causes both Alfie and Dee Dee to be concerned for Duchess when they learn from Goo that snakes eat rabbits.", 'December 6, 1994'], ['1', '1', '"The Charity"', "Alfie, Dee Dee, and Melanie are supposed to be helping their parents at a carnival by working the dunking booth. When Goo arrives and announces their favorite basketball player, Kendall Gill, is at the Comic Book Store signing autographs, the boys decide to ditch the carnival. This leaves Melanie and Jennifer to work the booth and both end up soaked. But the Comic Book Store is packed and much to Alfie and Dee Dee's surprise their father has to interview Kendall Gill. Goo comes up with a plan to get Alfie and Dee Dee, Gill's signature before getting them back at the local carnival, but are caught by Roger. All ends well for everyone except Alfie and Goo, who must endure being soaked at the dunking booth.", 'October 15, 1994'], ['3', '1', '"The Weekend Aunt Helen Came"', "The boy's mother, Jennifer, leaves for the weekend and she leaves the father, Roger, in charge. However, he lets the kids run wild. Alfie and Dee Dee's Aunt Helen then comes to oversee the house until Jennifer gets back. Meanwhile, Alfie throws a basketball at Goo, which hits him in the head, giving him temporary amnesia. In this case of memory loss, Goo acts like a nerd, does homework on a weekend, wants to be called Milton instead of Goo, and he even calls Alfie Alfred. He is much nicer to Deonne and Dee Dee, but is somewhat rude to Melanie. The only thing that will reverse this is another hit in the head.", 'November 1, 1994']] | January 26, 1995 | Answer: | 128 | 7 | 908 |
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 1st place finishes across all events? | [['Date', 'Competition', 'Location', 'Country', 'Event', 'Placing', 'Rider', 'Nationality'], ['30 October 2009', '2009–10 World Cup', 'Manchester', 'United Kingdom', 'Keirin', '1', 'Chris Hoy', 'GBR'], ['30 October 2009', '2009–10 World Cup', 'Manchester', 'United Kingdom', 'Sprint', '1', 'Chris Hoy', 'GBR'], ['1 November 2008', '2008–09 World Cup', 'Manchester', 'United Kingdom', '500 m time trial', '1', 'Victoria Pendleton', 'GBR'], ['1 November 2009', '2009–10 World Cup', 'Manchester', 'United Kingdom', 'Team sprint', '1', 'Jamie Staff', 'GBR'], ['30 October 2009', '2009–10 World Cup', 'Manchester', 'United Kingdom', 'Sprint', '1', 'Victoria Pendleton', 'GBR'], ['30 October 2009', '2009–10 World Cup', 'Manchester', 'United Kingdom', '500 m time trial', '2', 'Victoria Pendleton', 'GBR'], ['2 November 2008', '2008–09 World Cup', 'Manchester', 'United Kingdom', 'Team sprint', '1', 'Jamie Staff', 'GBR'], ['13 February 2009', '2008–09 World Cup', 'Copenhagen', 'Denmark', 'Team sprint', '1', 'Jason Kenny', 'GBR'], ['2 November 2008', '2008–09 World Cup', 'Manchester', 'United Kingdom', 'Team sprint', '1', 'Jason Kenny', 'GBR'], ['1 November 2009', '2009–10 World Cup', 'Manchester', 'United Kingdom', 'Team sprint', '1', 'Ross Edgar', 'GBR'], ['13 February 2009', '2008–09 World Cup', 'Copenhagen', 'Denmark', 'Team sprint', '1', 'Jamie Staff', 'GBR'], ['31 October 2008', '2008–09 World Cup', 'Manchester', 'United Kingdom', 'Sprint', '1', 'Victoria Pendleton', 'GBR'], ['1 November 2009', '2009–10 World Cup', 'Manchester', 'United Kingdom', 'Team sprint', '1', 'Chris Hoy', 'GBR'], ['2 November 2008', '5th International Keirin Event', 'Manchester', 'United Kingdom', 'International keirin', '2', 'Ross Edgar', 'GBR'], ['13 February 2009', '2008–09 World Cup', 'Copenhagen', 'Denmark', 'Team sprint', '1', 'Chris Hoy', 'GBR'], ['2 November 2008', '2008–09 World Cup', 'Manchester', 'United Kingdom', 'Team sprint', '1', 'Ross Edgar', 'GBR'], ['2 November 2008', '2008–09 World Cup', 'Manchester', 'United Kingdom', 'Keirin', '1', 'Victoria Pendleton', 'GBR'], ['31 October 2008', '2008–09 World Cup', 'Manchester', 'United Kingdom', 'Keirin', '2', 'Jason Kenny', 'GBR'], ['13 February 2009', '2008–09 World Cup', 'Copenhagen', 'Denmark', 'Sprint', '1', 'Victoria Pendleton', 'GBR'], ['1 November 2008', '2008–09 World Cup', 'Manchester', 'United Kingdom', 'Sprint', '1', 'Jason Kenny', 'GBR']] | 17 | Answer: | 128 | 20 | 788 |
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 which competition did hopley finish fist? | [['Year', 'Competition', 'Venue', 'Position', 'Event', 'Notes'], ['2000', 'World Junior Championships', 'Santiago, Chile', '1st', 'Discus throw', '59.51 m'], ['2008', 'African Championships', 'Addis Ababa, Ethiopia', '2nd', 'Discus throw', '56.98 m'], ['2007', 'All-Africa Games', 'Algiers, Algeria', '3rd', 'Discus throw', '57.79 m'], ['2003', 'All-Africa Games', 'Abuja, Nigeria', '2nd', 'Discus throw', '62.86 m'], ['2006', 'Commonwealth Games', 'Melbourne, Australia', '4th', 'Discus throw', '60.99 m'], ['2004', 'Olympic Games', 'Athens, Greece', '8th', 'Discus throw', '62.58 m'], ['2004', 'African Championships', 'Brazzaville, Republic of the Congo', '2nd', 'Discus throw', '63.50 m'], ['2003', 'All-Africa Games', 'Abuja, Nigeria', '5th', 'Shot put', '17.76 m'], ['2006', 'Commonwealth Games', 'Melbourne, Australia', '7th', 'Shot put', '18.44 m']] | World Junior Championships | Answer: | 128 | 9 | 299 |
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 films with the language of kannada listed? | [['Year', 'Film', 'Role', 'Language', 'Notes'], ['2014', 'Endendigu', '', '', 'Filming'], ['2013', 'Dilwala', 'Preethi', 'Kannada', ''], ['2012', 'Breaking News', 'Shraddha', 'Kannada', ''], ['2012', '18th Cross', 'Punya', 'Kannada', ''], ['2008', 'Moggina Manasu', 'Chanchala', 'Kannada', 'Filmfare Award for Best Actress - Kannada\\nKarnataka State Film Award for Best Actress'], ['2011', 'Hudugaru', 'Gayithri', 'Kannada', 'Nominated, Filmfare Award for Best Actress – Kannada'], ['2009', 'Olave Jeevana Lekkachaara', 'Rukmini', 'Kannada', 'Innovative Film Award for Best Actress'], ['2009', 'Love Guru', 'Kushi', 'Kannada', 'Filmfare Award for Best Actress - Kannada'], ['2012', 'Alemari', 'Neeli', 'Kannada', ''], ['2010', 'Krishnan Love Story', 'Geetha', 'Kannada', 'Filmfare Award for Best Actress - Kannada\\nUdaya Award for Best Actress'], ['2013', 'Kaddipudi', 'Uma', 'Kannada', ''], ['2014', 'Mr. & Mrs. Ramachari', '', '', 'Announced'], ['2013', 'Bahaddoor', 'Anjali', 'Kannada', 'Filming'], ['2012', 'Drama', 'Nandini', 'Kannada', ''], ['2012', 'Addhuri', 'Poorna', 'Kannada', 'Udaya Award for Best Actress\\nNominated — SIIMA Award for Best Actress\\nNominated — Filmfare Award for Best Actress\xa0– Kannada'], ['2010', 'Gaana Bajaana', 'Radhey', 'Kannada', ''], ['2012', 'Sagar', 'Kajal', 'Kannada', '']] | 15 | Answer: | 128 | 17 | 474 |
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 number of people attending the toros mexico vs. monterrey flash game? | [['Game', 'Day', 'Date', 'Kickoff', 'Opponent', 'Results\\nScore', 'Results\\nRecord', 'Location', 'Attendance'], ['5', 'Saturday', 'December 14', '7:05pm', 'at Sacramento Surge', 'W 7–6 (OT)', '3–2', 'Estadio Azteca Soccer Arena', '215'], ['8', 'Saturday', 'January 4', '7:05pm', 'at Ontario Fury', 'L 5–12', '4–4', 'Citizens Business Bank Arena', '2,653'], ['4', 'Sunday', 'December 1', '1:05pm', 'Ontario Fury', 'W 18–4', '2–2', 'UniSantos Park', '207'], ['13', 'Saturday', 'February 1', '7:05pm', 'at San Diego Sockers', 'L 5–6', '7–6', 'Valley View Casino Center', '4,954'], ['16', 'Saturday', 'February 15♥', '5:05pm', 'Bay Area Rosal', 'W 27–2', '9–7', 'UniSantos Park', '118'], ['12', 'Sunday', 'January 26', '1:05pm', 'Sacramento Surge', 'W 20–6', '7–5', 'UniSantos Park', '224'], ['14', 'Friday', 'February 7', '7:05pm', 'at Turlock Express', 'L 6–9', '7–7', 'Turlock Soccer Complex', '673'], ['10', 'Sunday', 'January 12', '1:05pm', 'Las Vegas Legends', 'W 10–7', '5–5', 'UniSantos Park', '343'], ['1', 'Sunday', 'November 10', '3:05pm', 'at Las Vegas Legends', 'L 3–7', '0–1', 'Orleans Arena', '1,836'], ['11', 'Sunday', 'January 19', '1:05pm', 'Bay Area Rosal', 'W 17–7', '6–5', 'UniSantos Park', '219'], ['9', 'Sunday', 'January 5', '1:05pm', 'San Diego Sockers', 'L 7–12', '4–5', 'UniSantos Park', '388'], ['15', 'Saturday', 'February 8', '7:05pm', 'at Sacramento Surge', 'W 10–6', '8–7', 'Estadio Azteca Soccer Arena', '323'], ['2', 'Sunday', 'November 17', '1:05pm', 'Monterrey Flash', 'L 6–10', '0–2', 'UniSantos Park', '363'], ['7', 'Sunday', 'December 22', '1:05pm', 'Turlock Express', 'W 16–8', '4–3', 'UniSantos Park', '218'], ['6', 'Sunday', 'December 15', '6:00pm', 'at Bay Area Rosal', 'L 8–9 (OT)', '3–3', 'Cabernet Indoor Sports', '480'], ['3', 'Saturday', 'November 23', '7:05pm', 'at Bay Area Rosal', 'W 10–7', '1–2', 'Cabernet Indoor Sports', '652']] | 363 | Answer: | 128 | 16 | 763 |
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 time period had no shirt sponsor? | [['Year', 'Kit Manufacturer', 'Shirt Sponsor', 'Back of Shirt Sponsor', 'Short Sponsor'], ['1985–1986', 'Umbro', 'Whitbread', '', ''], ['1993–1994', 'Club Sport', 'Gulf Oil', '', ''], ['2004–2008', 'Errea', 'Bence Building Merchants', '', ''], ['1977–1978', '', 'National Express', '', ''], ['1988–1989', '', 'Gulf Oil', '', ''], ['2008–', 'Errea', 'Mira Showers', '', ''], ['2013–', 'Errea', 'Mira Showers', 'Gloucestershire College', 'Gloucestershire Echo'], ['1996–1997', 'UK', 'Endsleigh Insurance', '', ''], ['1982–1985', 'Umbro', '', '', ''], ['2009–2011', 'Errea', 'Mira Showers', 'PSU Technology Group', ''], ['1994–1995', 'Klūb Sport', 'Empress', '', ''], ['1999–2004', 'Errea', 'Towergate Insurance', '', ''], ['1986–1988', 'Henson', 'Duraflex', '', ''], ['1997–1999', 'Errea', 'Endsleigh Insurance', '', ''], ['1991–1993', 'Technik', 'Gulf Oil', '', ''], ['1995–1996', 'Matchwinner', 'Empress', '', ''], ['2011–2013', 'Errea', 'Mira Showers', 'Barr Stadia', 'Gloucestershire Echo']] | 1982-1985 | Answer: | 128 | 17 | 366 |
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:when was his first 1st place record? | [['Year', 'Competition', 'Venue', 'Position', 'Event', 'Notes'], ['1999', 'European Junior Championships', 'Riga, Latvia', '4th', '400 m hurdles', '52.17'], ['2003', 'European U23 Championships', 'Bydgoszcz, Poland', '1st', '400 m hurdles', '48.45'], ['2000', 'World Junior Championships', 'Santiago, Chile', '1st', '400 m hurdles', '49.23'], ['2006', 'European Championships', 'Gothenburg, Sweden', '2nd', '400 m hurdles', '48.71'], ['2001', 'World Championships', 'Edmonton, Canada', '18th (sf)', '400 m hurdles', '49.80'], ['2003', 'World Indoor Championships', 'Birmingham, United Kingdom', '3rd', '4x400 m relay', '3:06.61'], ['2003', 'European U23 Championships', 'Bydgoszcz, Poland', '1st', '4x400 m relay', '3:03.32'], ['2008', 'Olympic Games', 'Beijing, China', '7th', '4x400 m relay', '3:00.32'], ['2007', 'World Championships', 'Osaka, Japan', '3rd', '400 m hurdles', '48.12 (NR)'], ['2004', 'Olympic Games', 'Athens, Greece', '6th', '400 m hurdles', '49.00'], ['2002', 'European Championships', 'Munich, Germany', '4th', '400 m', '45.40'], ['2002', 'European Indoor Championships', 'Vienna, Austria', '1st', '400 m', '45.39 (CR, NR)'], ['2003', 'World Indoor Championships', 'Birmingham, United Kingdom', '7th (sf)', '400 m', '46.82'], ['2001', 'Universiade', 'Beijing, China', '8th', '400 m hurdles', '49.68'], ['2004', 'Olympic Games', 'Athens, Greece', '10th (h)', '4x400 m relay', '3:03.69'], ['2012', 'European Championships', 'Helsinki, Finland', '18th (sf)', '400 m hurdles', '50.77'], ['2002', 'European Indoor Championships', 'Vienna, Austria', '1st', '4x400 m relay', '3:05.50 (CR)'], ['2008', 'Olympic Games', 'Beijing, China', '6th', '400 m hurdles', '48.42'], ['2007', 'World Championships', 'Osaka, Japan', '3rd', '4x400 m relay', '3:00.05'], ['2002', 'European Championships', 'Munich, Germany', '8th', '4x400 m relay', 'DQ']] | 2000 | Answer: | 128 | 20 | 650 |
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 which three consecutive years was the record the same? | [['Season', 'Team', 'Record', 'Head Coach', 'Quarterback', 'Leading Rusher', 'Leading Receiver', 'All-Pros', 'Runner Up'], ['1997', 'Green Bay Packers', '13–3', 'Mike Holmgren', 'Brett Favre', 'Dorsey Levens', 'Antonio Freeman', 'Butler, Favre', 'San Francisco 49ers'], ['2004', 'Philadelphia Eagles', '13–3', 'Andy Reid', 'Donovan McNabb', 'Brian Westbrook', 'Terrell Owens', 'Dawkins, Owens, Sheppard', 'Atlanta Falcons'], ['2011', 'New York Giants†', '9–7', 'Tom Coughlin', 'Eli Manning', 'Ahmad Bradshaw', 'Victor Cruz', 'Pierre-Paul', 'San Francisco 49ers'], ['2012', 'San Francisco 49ers', '11–4–1', 'Jim Harbaugh', 'Colin Kaepernick', 'Frank Gore', 'Michael Crabtree', 'Bowman, Goldson, Iupati, Lee, Smith, Willis', 'Atlanta Falcons'], ['1988', 'San Francisco 49ers†', '10–6', 'Bill Walsh*', 'Joe Montana*', 'Roger Craig', 'Jerry Rice*', 'Craig, Rice*', 'Chicago Bears'], ['2003', 'Carolina Panthers', '11–5', 'John Fox', 'Jake Delhomme', 'Stephen Davis', 'Steve Smith', 'Jenkins', 'Philadelphia Eagles'], ['1974', 'Minnesota Vikings', '10–4', 'Bud Grant*', 'Fran Tarkenton*', 'Chuck Foreman', 'Jim Lash', 'Page*, Yary*', 'Los Angeles Rams'], ['2010', 'Green Bay Packers†', '10–6', 'Mike McCarthy', 'Aaron Rodgers', 'Brandon Jackson', 'Greg Jennings', 'Clifton, Collins, Jennings, Matthews, Woodson', 'Chicago Bears'], ['2005', 'Seattle Seahawks', '13–3', 'Mike Holmgren', 'Matt Hasselbeck', 'Shaun Alexander', 'Bobby Engram', 'Alexander, Hutchinson, Jones*, Strong', 'Carolina Panthers'], ['1983', 'Washington Redskins', '14–2', 'Joe Gibbs*', 'Joe Theismann', 'John Riggins*', 'Charlie Brown', 'Butz, Grimm*, Jacoby, Murphy, Nelms, Riggins*, Theismann', 'San Francisco 49ers'], ['1995', 'Dallas Cowboys†', '12–4', 'Barry Switzer', 'Troy Aikman*', 'Emmitt Smith*', 'Michael Irvin*', 'Newton, Smith*, Woodson', 'Green Bay Packers'], ['1979', 'Los Angeles Rams', '9–7', 'Ray Malavasi', 'Pat Haden', 'Wendell Tyler', 'Preston Dennard', 'Brooks, Youngblood*', 'Tampa Bay Buccaneers'], ['1994', 'San Francisco 49ers†', '13–3', 'George Seifert', 'Steve Young*', 'Ricky Watters', 'Jerry Rice*', 'Rice*, Sanders*, Young*', 'Dallas Cowboys'], ['2001', 'St. Louis Rams', '14–2', 'Mike Martz', 'Kurt Warner', 'Marshall Faulk*', 'Torry Holt', 'Faulk*, Pace, Warner, Williams*', 'Philadelphia Eagles'], ['1976', 'Minnesota Vikings', '11–2–1', 'Bud Grant*', 'Fran Tarkenton*', 'Chuck Foreman', 'Sammy White', 'Yary*', 'Los Angeles Rams'], ['1986', 'New York Giants†', '14–2', 'Bill Parcells*', 'Phil Simms', 'Joe Morris', 'Mark Bavaro', 'Bavaro, Landeta, Morris, Taylor*', 'Washington Redskins'], ['1989', 'San Francisco 49ers†', '14–2', 'George Seifert', 'Joe Montana*', 'Roger Craig', 'Jerry Rice*', 'Cofer, Lott*, Montana*, Rice*,', 'Los Angeles Rams'], ['2006', 'Chicago Bears', '13–3', 'Lovie Smith', 'Rex Grossman', 'Thomas Jones', 'Muhsin Muhammad', 'Gould, Hester, Kreutz, Urlacher', 'New Orleans Saints'], ['2009', 'New Orleans Saints†', '13–3', 'Sean Payton', 'Drew Brees', 'Pierre Thomas', 'Marques Colston', 'Evans', 'Minnesota Vikings'], ['1985', 'Chicago Bears†', '15–1', 'Mike Ditka*', 'Jim McMahon', 'Walter Payton*', 'Willie Gault', 'Covert, Dent*, McMichael, Payton*, Singletary*', 'Los Angeles Rams']] | 2004, 2005, 2006 | Answer: | 128 | 20 | 1,026 |
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 pat or john have the highest total? | [['Name', 'League', 'FA Cup', 'League Cup', 'JP Trophy', 'Total'], ['Liam Sercombe', '1', '0', '0', '0', '1'], ['Danny Coles', '3', '0', '0', '0', '3'], ['Jimmy Keohane', '3', '0', '0', '0', '3'], ["John O'Flynn", '11', '0', '1', '0', '12'], ['Scot Bennett', '5', '0', '0', '0', '5'], ['OWN GOALS', '0', '0', '0', '0', '0'], ['Total', '0', '0', '0', '0', '0'], ['Guillem Bauza', '2', '0', '0', '0', '2'], ['Jake Gosling', '1', '0', '0', '0', '1'], ['Jamie Cureton', '20', '0', '0', '0', '20'], ['Pat Baldwin', '1', '0', '0', '0', '1'], ['Alan Gow', '4', '0', '0', '0', '4'], ['Arron Davies', '3', '0', '0', '0', '3']] | John | Answer: | 128 | 13 | 283 |
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 combined score of year end rankings before 2009? | [['Tournament', '2004', '2005', '2006', '2007', '2008', '2009', '2010', '2011', '2012', '2013', '2014', 'W–L'], ['Year End Ranking', '129', '91', '68', '90', '62', '41', '33', '39', '76', '62', '', ''], ['Rome Masters', 'A', 'A', 'A', 'A', 'A', 'LQ', '3R', '1R', '2R', 'A', '', '3–3'], ['Wimbledon', 'A', '2R', '2R', '1R', '3R', '2R', '1R', '2R', '2R', '1R', '', '7–9'], ['Canada Masters', 'A', 'A', 'A', 'A', 'A', '1R', 'A', 'A', 'A', 'A', '', '0–1'], ['Australian Open', 'A', '2R', '2R', '2R', '3R', '2R', '1R', '3R', '1R', '1R', '2R', '9–10'], ['French Open', '2R', '1R', '1R', '2R', '2R', '1R', '2R', '3R', '1R', '1R', '', '6–10'], ['Win–Loss', '0–0', '0–1', '1–1', '4–4', '1–2', '2–6', '11–6', '5–8', '5–5', '0–2', '', '29–35'], ['Cincinnati Masters', 'A', 'A', 'A', 'LQ', 'A', '3R', 'A', '1R', 'A', 'A', '', '2–2'], ['Shanghai Masters', 'Not Masters Series', 'Not Masters Series', 'Not Masters Series', 'Not Masters Series', 'Not Masters Series', '1R', 'QF', '2R', 'Q2', 'A', '', '4–3'], ['Indian Wells Masters', 'A', 'A', 'A', '3R', '2R', '1R', '4R', '2R', '3R', 'A', 'A', '8–6'], ['Paris Masters', 'A', 'A', 'A', 'LQ', 'LQ', 'A', 'A', '2R', '1R', '1R', '', '1–3'], ['US Open', 'A', '1R', '1R', '1R', '2R', '2R', '2R', '2R', '2R', '1R', '', '5–9'], ['Miami Masters', 'A', 'A', 'A', '2R', '1R', '1R', '2R', '2R', '2R', 'A', '', '3–6'], ['Titles–Finals', '0–0', '0–0', '0–0', '0–0', '0–0', '1–1', '1–2', '0–0', '0–0', '0–2', '', '2–5'], ['Monte-Carlo Masters', 'A', '1R', 'A', '3R', 'LQ', 'A', '1R', '2R', 'A', 'A', '', '2–3'], ['Madrid Masters', 'A', 'A', 'A', 'LQ', 'LQ', '1R', '3R', '3R', '2R', '1R', '', '5–5'], ['Hamburg Masters', 'A', 'A', '2R', '1R', 'A', 'Not Masters Series', 'Not Masters Series', 'Not Masters Series', 'Not Masters Series', 'Not Masters Series', '', '1–2'], ['Win–Loss', '1–1', '2–4', '2–4', '2–4', '6–4', '3–4', '2–4', '6–4', '2–4', '0–4', '1–1', '27–38']] | 440 | Answer: | 128 | 18 | 953 |
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 ships were wrecked in lake huron than in erie? | [['Ship', 'Type of Vessel', 'Lake', 'Location', 'Lives lost'], ['Wexford', 'Steamer', 'Lake Huron', 'north of Grand Bend, Ontario', 'all hands'], ['Issac M. Scott', 'Steamer', 'Lake Huron', 'near Port Elgin, Ontario', '28 lost'], ['Charles S. Price', 'Steamer', 'Lake Huron', 'near Port Huron, Michigan', '28 lost'], ['Argus', 'Steamer', 'Lake Huron', '25 miles off Kincardine, Ontario', '25 lost'], ['Henry B. Smith', 'Steamer', 'Lake Superior', '', 'all hands'], ['Regina', 'Steamer', 'Lake Huron', 'near Harbor Beach, Michigan', ''], ['Plymouth', 'Barge', 'Lake Michigan', '', '7 lost'], ['Lightship No. 82', 'Lightship', 'Lake Erie', 'Point Albino (near Buffalo)', '6 lost'], ['John A. McGean', 'Steamer', 'Lake Huron', 'near Goderich, Ontario', '28 lost'], ['Hydrus', 'Steamer', 'Lake Huron', 'near Lexington, Michigan', '28 lost'], ['Leafield', 'Steamer', 'Lake Superior', '', 'all hands'], ['James Carruthers', 'Steamer', 'Lake Huron', 'near Kincardine', '18 lost']] | 7 | Answer: | 128 | 12 | 312 |
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 character with a blank c string? | [['name', 'glyph', 'C string', 'Unicode', 'Unicode name'], ['c', 'c', 'c', 'U+0063', 'LATIN SMALL LETTER C'], ['backslash', '\\\\', '\\\\\\\\', 'U+005C', 'REVERSE SOLIDUS'], ['i', 'i', 'i', 'U+0069', 'LATIN SMALL LETTER I'], ['H', 'H', 'H', 'U+0048', 'LATIN CAPITAL LETTER H'], ['left-square-bracket', '[', '[', 'U+005B', 'LEFT SQUARE BRACKET'], ['K', 'K', 'K', 'U+004B', 'LATIN CAPITAL LETTER K'], ['asterisk', '*', '*', 'U+002A', 'ASTERISK'], ['n', 'n', 'n', 'U+006E', 'LATIN SMALL LETTER N'], ['E', 'E', 'E', 'U+0045', 'LATIN CAPITAL LETTER E'], ['X', 'X', 'X', 'U+0058', 'LATIN CAPITAL LETTER X'], ['colon', ':', ':', 'U+003A', 'COLON'], ['U', 'U', 'U', 'U+0055', 'LATIN CAPITAL LETTER U'], ['F', 'F', 'F', 'U+0046', 'LATIN CAPITAL LETTER F'], ['v', 'v', 'v', 'U+0076', 'LATIN SMALL LETTER V'], ['form-feed', '', '\\\\f', 'U+000C', 'FORM FEED (FF)'], ['O', 'O', 'O', 'U+004F', 'LATIN CAPITAL LETTER O'], ['comma', ',', ',', 'U+002C', 'COMMA'], ['exclamation-mark', '!', '!', 'U+0021', 'EXCLAMATION MARK'], ['x', 'x', 'x', 'U+0078', 'LATIN SMALL LETTER X'], ['A', 'A', 'A', 'U+0041', 'LATIN CAPITAL LETTER A'], ['carriage-return', '', '\\\\r', 'U+000D', 'CARRIAGE RETURN (CR)'], ['ampersand', '&', '&', 'U+0026', 'AMPERSAND'], ['period', '.', '.', 'U+002E', 'FULL STOP'], ['quotation-mark', '"', '\\\\"', 'U+0022', 'QUOTATION MARK'], ['newline', '', '\\\\n', 'U+000A', 'LINE FEED (LF)'], ['y', 'y', 'y', 'U+0079', 'LATIN SMALL LETTER Y'], ['four', '4', '4', 'U+0034', 'DIGIT FOUR'], ['right-brace', '}', '}', 'U+007D', 'RIGHT CURLY BRACKET'], ['hyphen', '-', '-', 'U+002D', 'HYPHEN-MINUS'], ['apostrophe', "'", "\\\\'", 'U+0027', 'APOSTROPHE'], ['e', 'e', 'e', 'U+0065', 'LATIN SMALL LETTER E'], ['u', 'u', 'u', 'U+0075', 'LATIN SMALL LETTER U'], ['Q', 'Q', 'Q', 'U+0051', 'LATIN CAPITAL LETTER Q'], ['question-mark', '?', '?', 'U+003F', 'QUESTION MARK'], ['six', '6', '6', 'U+0036', 'DIGIT SIX'], ['D', 'D', 'D', 'U+0044', 'LATIN CAPITAL LETTER D'], ['zero', '0', '0', 'U+0030', 'DIGIT ZERO'], ['w', 'w', 'w', 'U+0077', 'LATIN SMALL LETTER W'], ['h', 'h', 'h', 'U+0068', 'LATIN SMALL LETTER H'], ['N', 'N', 'N', 'U+004E', 'LATIN CAPITAL LETTER N'], ['vertical-line', '\\p', '\\p', 'U+007C', 'VERTICAL LINE'], ['L', 'L', 'L', 'U+004C', 'LATIN CAPITAL LETTER L'], ['less-than-sign', '<', '<', 'U+003C', 'LESS-THAN SIGN'], ['V', 'V', 'V', 'U+0056', 'LATIN CAPITAL LETTER V'], ['J', 'J', 'J', 'U+004A', 'LATIN CAPITAL LETTER J'], ['equals-sign', '=', '=', 'U+003D', 'EQUALS SIGN'], ['left-brace', '{', '{', 'U+007B', 'LEFT CURLY BRACKET'], ['S', 'S', 'S', 'U+0053', 'LATIN CAPITAL LETTER S']] | space | Answer: | 128 | 48 | 1,035 |
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 scored by the tide in the last 3 games combined. | [['Date', 'Opponent#', 'Rank#', 'Site', 'TV', 'Result', 'Attendance'], ['November 5', 'at\xa0LSU', '#6', 'Tiger Stadium • Baton Rouge, LA (Rivalry)', 'ESPN', 'W\xa035–17', '75,453'], ['October 15', 'at\xa0Tennessee', '#10', 'Neyland Stadium • Knoxville, TN (Third Saturday in October)', 'ESPN', 'W\xa017–13', '96,856'], ['September 10', 'Vanderbilt', '#11', 'Bryant–Denny Stadium • Tuscaloosa, AL', 'JPS', 'W\xa017–7', '70,123'], ['December 3', 'vs.\xa0#6\xa0Florida', '#3', 'Georgia Dome • Atlanta, GA (SEC Championship Game)', 'ABC', 'L\xa023–24', '74,751'], ['October 22', 'Ole Miss', '#8', 'Bryant–Denny Stadium • Tuscaloosa, AL (Rivalry)', 'ABC', 'W\xa021–10', '70,123'], ['September 17', 'at\xa0Arkansas', '#12', 'Razorback Stadium • Fayetteville, AR', 'ABC', 'W\xa013–6', '52,089'], ['October 1', 'Georgia', '#11', 'Bryant–Denny Stadium • Tuscaloosa, AL', 'ESPN', 'W\xa029–28', '70,123'], ['September 24', 'Tulane*', '#11', 'Legion Field • Birmingham, AL', '', 'W\xa020–10', '81,421'], ['January 2, 1995', 'vs.\xa0#13\xa0Ohio State*', '#6', 'Citrus Bowl • Orlando, FL (Florida Citrus Bowl)', 'ABC', 'W\xa024–17', '71,195'], ['November 19', '#6\xa0Auburn', '#4', 'Legion Field • Birmingham, AL (Iron Bowl)', 'ABC', 'W\xa021–14', '83,091'], ['November 12', 'at\xa0#20\xa0Mississippi State', '#6', 'Scott Field • Starkville, MS (Rivalry)', 'ABC', 'W\xa029–25', '41,358'], ['October 8', 'Southern Miss*', '#11', 'Bryant–Denny Stadium • Tuscaloosa, AL', '', 'W\xa014–6', '70,123'], ['September 3', 'Tennessee–Chattanooga*', '#11', 'Legion Field • Birmingham, AL', '', 'W\xa042–13', '82,109']] | 68 | Answer: | 128 | 13 | 593 |
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 came immediately after sebastian porto in the race? | [['Pos', 'Rider', 'Manufacturer', 'Time/Retired', 'Points'], ['11', 'Alex Hofmann', 'TSR-Honda', '+26.933', '5'], ['3', 'Jeremy McWilliams', 'Aprilia', '+0.534', '16'], ['6', 'Ralf Waldmann', 'Aprilia', '+7.019', '10'], ['20', 'Lucas Oliver Bulto', 'Yamaha', '+1:25.758', ''], ['18', 'Julien Allemand', 'TSR-Honda', '+1:16.347', ''], ['16', 'Luca Boscoscuro', 'TSR-Honda', '+56.432', ''], ['4', 'Tohru Ukawa', 'Honda', '+0.537', '13'], ['1', 'Loris Capirossi', 'Honda', '38:04.730', '25'], ['22', 'Rudie Markink', 'Aprilia', '+1:40.280', ''], ['14', 'Masaki Tokudome', 'TSR-Honda', '+33.161', '2'], ['5', 'Shinya Nakano', 'Yamaha', '+0.742', '11'], ['Ret', 'Maurice Bolwerk', 'TSR-Honda', 'Retirement', ''], ['17', 'Johann Stigefelt', 'Yamaha', '+1:07.433', ''], ['Ret', 'Marcellino Lucchi', 'Aprilia', 'Retirement', ''], ['8', 'Stefano Perugini', 'Honda', '+20.891', '8'], ['9', 'Jason Vincent', 'Honda', '+21.310', '7'], ['10', 'Anthony West', 'TSR-Honda', '+26.816', '6'], ['12', 'Sebastian Porto', 'Yamaha', '+27.054', '4'], ['13', 'Tomomi Manako', 'Yamaha', '+27.903', '3'], ['15', 'Jarno Janssen', 'TSR-Honda', '+56.248', '1'], ['23', 'Arno Visscher', 'Aprilia', '+1:40.635', ''], ['2', 'Valentino Rossi', 'Aprilia', '+0.180', '20'], ['Ret', 'Andre Romein', 'Honda', 'Retirement', ''], ['21', 'David Garcia', 'Yamaha', '+1:33.867', ''], ['24', 'Henk Van De Lagemaat', 'Honda', '+1 Lap', ''], ['Ret', 'Roberto Rolfo', 'Aprilia', 'Retirement', ''], ['7', 'Franco Battaini', 'Aprilia', '+20.889', '9'], ['19', 'Fonsi Nieto', 'Yamaha', '+1:25.622', '']] | Tomomi Manako | Answer: | 128 | 28 | 627 |
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's the total number of festivals that occurred in october? | [['Date', 'Festival', 'Location', 'Awards', 'Link'], ['Nov 16–18', 'AFF', 'Wrocław, Lower Silesia\\n\xa0Poland', '', 'AFF Poland'], ['Oct 1, Oct 15', 'Gwacheon International SF Festival', 'Gwacheon, Gyeonggi-do\\n\xa0South Korea', '', 'gisf.org'], ['Nov 12, Nov 18', 'Indonesia Fantastic Film Festival', 'Jakarta, Bandung\\n\xa0Indonesia', '', 'inaff.com'], ['Oct 9', 'London Int. Festival of Science Fiction Film', 'London, England\\n\xa0UK', 'Closing Night Film', 'Sci-Fi London'], ['Nov 11', 'Les Utopiales', 'Nantes, Pays de la Loire\\n\xa0France', '', 'utopiales.org'], ['Oct 17, Oct 20', 'Icon TLV', 'Tel Aviv, Central\\n\xa0Israel', '', 'icon.org.il'], ['Sep 28', 'Fantastic Fest', 'Austin, Texas\\n\xa0USA', '', 'FantasticFest.com'], ['Sep 19', 'Lund International Fantastic Film Festival', 'Lund, Skåne\\n\xa0Sweden', '', 'fff.se'], ['Jul 18, Jul 25', 'Fantasia Festival', 'Montreal, Quebec \xa0Canada', 'Special Mention\\n"for the resourcefulness and unwavering determination by a director to realize his unique vision"', 'FanTasia'], ['Feb 2–5, Feb 11', 'Santa Barbara International Film Festival', 'Santa Barbara, California \xa0USA', 'Top 11 "Best of the Fest" Selection', 'sbiff.org'], ['Oct 9, Oct 11', 'Sitges Film Festival', 'Sitges, Catalonia\\n\xa0Spain', '', 'Sitges Festival'], ['Oct 23', 'Toronto After Dark', 'Toronto, Ontario\\n\xa0Canada', 'Best Special Effects\\nBest Musical Score', 'torontoafterdark.com'], ['May 21–22, Jun 11', 'Seattle International Film Festival', 'Seattle, Washington \xa0USA', '', 'siff.net'], ['Sep 16', 'Athens International Film Festival', 'Athens, Attica\\n\xa0Greece', 'Best Director', 'aiff.gr']] | 5 | Answer: | 128 | 14 | 514 |
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 hospital to have 6 hospital beds? | [['Name', 'City', 'Hospital beds', 'Operating rooms', 'Total', 'Trauma designation', 'Affiliation', 'Notes'], ['Wilkes Regional Medical Center', 'North Wilkesboro', '144', '9', '153', '-', 'CHS', '-'], ['Memorial Mission Hospital and Asheville Surgery Center', 'Asheville', '730', '36', '766', 'Level II', 'Mission', '-'], ['North Carolina Specialty Hospital', 'Durham', '18', '4', '22', '-', '-', '-'], ['New Hanover Regional Medical Center', 'Wilmington', '769', '37', '806', 'Level II', 'NHRMC', '-'], ['CarePartners Rehabilitation Hospital', 'Asheville', '80', '0', '80', '-', '-', '-'], ['Vidant Beaufort Hospital', 'Washington', '142', '7', '149', '-', 'Vidant', '-'], ['Frye Regional Medical Center', 'Hickory', '355', '23', '378', '-', 'Tenet', '-'], ['Blowing Rock Hospital', 'Blowing Rock', '100', '2', '102', '-', 'ARHS', '-'], ['Vidant Duplin Hospital', 'Kenansville', '101', '3', '104', '-', 'Vidant', '-'], ['Novant Health Huntersville Medical Center', 'Huntersville', '60', '8', '68', '-', 'Novant', '-'], ['University of North Carolina Hospitals', 'Chapel Hill', '778', '48', '826', 'Level I', 'UNC', 'Primary teaching hospital of University of North Carolina at Chapel Hill School of Medicine'], ['Wake Forest Baptist Medical Center', 'Winston-Salem', '885', '50', '935', 'Level I', 'WFU', 'Primary teaching hospital of Wake Forest School of Medicine'], ['Rex Healthcare', 'Raleigh', '665', '38', '703', '-', 'UNC', '-'], ['Johnston Health', 'Smithfield', '177', '10', '187', '-', 'UNC', '-'], ['Novant Health Brunswick Medical Center', 'Supply', '60', '6', '66', '-', 'Novant', '-'], ['Vidant Edgecombe Hospital', 'Tarboro', '117', '8', '125', '-', 'Vidant', '-'], ['Carolinas Medical Center-NorthEast', 'Concord', '457', '25', '482', 'Level III', 'CHS', '-'], ['Alleghany Memorial Hospital', 'Sparta', '41', '2', '43', '-', 'QHR', '-'], ['Stanly Regional Medical Center', 'Albemarle', '119', '8', '127', '-', 'CHS', '-'], ['Alamance Regional Medical Center', 'Burlington', '238', '15', '253', '-', 'Cone', '-'], ['Kindred Hospital - Greensboro', 'Greensboro', '124', '1', '125', '-', '-', '-'], ['Highlands-Cashiers Hospital', 'Highlands', '108', '4', '112', '-', 'Mission', '-'], ['Granville Health System', 'Oxford', '142', '4', '146', '-', '-', '-'], ['Novant Health Medical Park Hospital', 'Winston-Salem', '22', '13', '35', '-', 'Novant', '-'], ['Lake Norman Regional Medical Center', 'Mooresville', '123', '11', '134', '-', 'HMA', '-'], ['Haywood Regional Medical Center', 'Clyde', '189', '10', '199', '-', '-', '-'], ['Cape Fear Valley-Bladen County Hospital', 'Elizabethtown', '58', '2', '60', '-', 'Cape Fear', '-'], ['Northern Hospital of Surry County', 'Mount Airy', '133', '7', '140', '-', 'QHR', '-'], ['Central Carolina Hospital', 'Sanford', '137', '8', '145', '-', 'Tenet', '-'], ['Novant Health Charlotte Orthopaedic Hospital', 'Charlotte', '156', '12', '168', '-', 'Novant', '-'], ['Carolinas Rehabilitation Mt. Holly', 'Belmont', '40', '0', '40', '-', 'CHS', '-'], ['Ashe Memorial Hospital', 'Jefferson', '136', '3', '139', '-', 'Novant', '-'], ['Margaret R. Pardee Memorial Hospital', 'Hendersonville', '222', '13', '235', '-', 'UNC', '-'], ['Vidant Pungo Hospital', 'Belhaven', '49', '2', '51', '-', 'Vidant', '-'], ['Wayne Memorial Hospital', 'Goldsboro', '316', '15', '331', '-', '-', '-']] | Vidant Bertie Hospital | Answer: | 128 | 35 | 1,042 |
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 skoda cars sold in the year 2005? | [['Model', '1991', '1995', '1996', '1997', '1998', '1999', '2000', '2001', '2002', '2003', '2004', '2005', '2006', '2007', '2008', '2009', '2010', '2011', '2012', '2013'], ['Škoda Superb', '−', '−', '−', '−', '−', '−', '−', '177', '16,867', '23,135', '22,392', '22,091', '20,989', '20,530', '25,645', '44,548', '98,873', '116,700', '106,847', '94,400'], ['Škoda Felicia', '172,000', '210,000', '', '288,458', '261,127', '241,256', '148,028', '44,963', '−', '−', '−', '−', '−', '−', '−', '−', '−', '−', '−', '−'], ['Škoda Yeti', '−', '−', '−', '−', '−', '−', '−', '−', '−', '−', '−', '−', '−', '−', '−', '11,018', '52,604', '70,300', '90,952', '82,400'], ['Škoda Rapid', '−', '−', '−', '−', '−', '−', '−', '−', '−', '−', '−', '−', '−', '−', '−', '−', '−', '1,700', '9,292', '103,800'], ['Total', '172,000', '210,000', '261,000', '336,334', '363,500', '385,330', '435,403', '460,252', '445,525', '449,758', '451,675', '492,111', '549,667', '630,032', '674,530', '684,226', '762,600', '879,200', '949,412', '920,800'], ['Škoda Octavia', '−', '−', '', '47,876', '102,373', '143,251', '158,503', '164,134', '164,017', '165,635', '181,683', '233,322', '270,274', '309,951', '344,857', '317,335', '349,746', '387,200', '409,360', '359,600'], ['Škoda Roomster', '−', '−', '−', '−', '−', '−', '−', '−', '−', '−', '−', '−', '14,422', '66,661', '57,467', '47,152', '32,332', '36,000', '39,249', '33,300'], ['Škoda Fabia', '−', '−', '−', '−', '−', '823', '128,872', '250,978', '264,641', '260,988', '247,600', '236,698', '243,982', '232,890', '246,561', '264,173', '229,045', '266,800', '255,025', '202,000'], ['Škoda Citigo', '−', '−', '−', '−', '−', '−', '−', '−', '−', '−', '−', '−', '−', '−', '−', '−', '−', '509', '36,687', '45,200']] | 492,111 | Answer: | 128 | 9 | 853 |
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 number of times won on grass? | [['Outcome', 'No.', 'Date', 'Championship', 'Surface', 'Opponent in the final', 'Score in the final'], ['Winner', '2.', 'February 14, 1994', 'Memphis, Tennessee, USA', 'Hard', 'Brad Gilbert', '6–4, 7–5'], ['Winner', '6.', 'April 20, 1998', 'Barcelona, Spain', 'Clay', 'Alberto Berasategui', '6–2, 1–6, 6–3, 6–2'], ['Runner-up', '3.', 'August 2, 1993', 'Montreal, Canada', 'Hard', 'Mikael Pernfors', '6–2, 2–6, 5–7'], ['Winner', '7.', 'November 16, 1998', 'Stockholm, Sweden', 'Hard', 'Thomas Johansson', '6–3, 6–4, 6–4'], ['Winner', '1.', 'May 17, 1993', 'Coral Springs, Florida, USA', 'Clay', 'David Wheaton', '6–3, 6–4'], ['Winner', '5.', 'January 15, 1996', 'Sydney, Australia', 'Hard', 'Goran Ivanišević', '5–7, 6–3, 6–4'], ['Runner-up', '9.', 'February 26, 1996', 'Memphis, Tennessee, USA', 'Hard (i)', 'Pete Sampras', '4–6, 6–7(2–7)'], ['Runner-up', '1.', 'February 15, 1993', 'Memphis, Tennessee, USA', 'Hard (i)', 'Jim Courier', '7–5, 6–7(4–7), 6–7(4–7)'], ['Winner', '3.', 'June 13, 1994', "London (Queen's Club), UK", 'Grass', 'Pete Sampras', '7–6(7–4), 7–6(7–4)'], ['Runner-up', '8.', 'December 18, 1995', 'Grand Slam Cup, Munich, Germany', 'Carpet', 'Goran Ivanišević', '6–7(4–7), 3–6, 4–6'], ['Runner-up', '7.', 'May 9, 1994', 'Pinehurst, USA', 'Clay', 'Jared Palmer', '4–6, 6–7(5–7)'], ['Winner', '8.', 'January 18, 1999', 'Sydney, Australia', 'Hard', 'Àlex Corretja', '6–3, 7–6(7–5)'], ['Runner-up', '12.', 'September 12, 1999', 'US Open, New York City, USA', 'Hard', 'Andre Agassi', '4–6, 7–6(7–5), 7–6(7–2), 3–6, 2–6'], ['Winner', '4.', 'February 20, 1995', 'Memphis, Tennessee, USA', 'Hard', 'Paul Haarhuis', '7–6(7–2), 6–4'], ['Runner-up', '4.', 'October 18, 1993', 'Tokyo, Japan', 'Carpet', 'Ivan Lendl', '4–6, 4–6'], ['Runner-up', '10.', 'August 22, 1996', 'Stockholm, Sweden', 'Hard (i)', 'Thomas Enqvist', '5–7, 4–6, 6–7(0–7)'], ['Runner-up', '6.', 'May 2, 1994', 'Atlanta, Georgia, USA', 'Clay', 'Michael Chang', '7–6(7–4), 6–7(4–7), 0–6'], ['Runner-up', '2.', 'July 26, 1993', 'Washington D.C., USA', 'Hard', 'Amos Mansdorf', '6–7(3–7), 5–7'], ['Runner-up', '5.', 'January 31, 1994', 'Australian Open, Melbourne, Australia', 'Hard', 'Pete Sampras', '6–7(4–7), 4–6, 4–6'], ['Runner-up', '11.', 'April 12, 1999', 'Estoril, Portugal', 'Clay', 'Albert Costa', '6–7(4–7), 6–2, 3–6']] | 1 | Answer: | 128 | 20 | 1,027 |
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 gold medals? | [['Rank', 'Nation', 'Gold', 'Silver', 'Bronze', 'Total'], ['9', 'Aruba', '0', '0', '1', '1'], ['7', 'Ecuador', '0', '2', '2', '4'], ['3', 'Colombia', '2', '3', '4', '9'], ['9', 'Netherlands Antilles', '0', '0', '1', '1'], ['1', 'Brazil', '7', '5', '3', '15'], ['6', 'Peru', '1', '1', '2', '4'], ['4', 'Chile', '2', '0', '2', '4'], ['2', 'Venezuela', '3', '2', '8', '13'], ['9', 'Uruguay', '0', '0', '1', '1'], ['9', 'Panama', '0', '0', '1', '1'], ['5', 'Argentina', '1', '2', '5', '8'], ['Total', 'Total', '16', '16', '30', '62'], ['8', 'Guyana', '0', '1', '0', '1']] | Brazil | Answer: | 128 | 13 | 267 |
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:total wins by belgian riders | [['Place', 'Rider', 'Country', 'Team', 'Points', 'Wins'], ['10', 'Dave Bickers', 'United Kingdom', 'ČZ', '1076', '0'], ['8', 'Gaston Rahier', 'Belgium', 'ČZ', '1112', '0'], ['6', 'Heikki Mikkola', 'Finland', 'Husqvarna', '1680', '2'], ['15', 'Brad Lackey', 'United States', 'ČZ', '603', '0'], ['17', 'John DeSoto', 'United States', 'Suzuki', '425', '0'], ['9', 'Pierre Karsmakers', 'Netherlands', 'Husqvarna', '1110', '0'], ['14', 'Mark Blackwell', 'United States', 'Husqvarna', '604', '0'], ['20', 'Peter Lamppu', 'United States', 'Montesa', '309', '0'], ['2', 'Adolf Weil', 'Germany', 'Maico', '2331', '2'], ['3', 'Torlief Hansen', 'Sweden', 'Husqvarna', '2052', '0'], ['19', 'Uno Palm', 'Sweden', 'Husqvarna', '324', '0'], ['11', 'John Banks', 'United Kingdom', 'ČZ', '971', '0'], ['18', 'Chris Horsefield', 'United Kingdom', 'ČZ', '416', '0'], ['12', 'Andy Roberton', 'United Kingdom', 'Husqvarna', '810', '0'], ['5', 'Joel Robert', 'Belgium', 'Suzuki', '1730', '1'], ['7', 'Willy Bauer', 'Germany', 'Maico', '1276', '0'], ['1', 'Sylvain Geboers', 'Belgium', 'Suzuki', '3066', '3'], ['13', 'Vlastimil Valek', 'Czechoslovakia', 'ČZ', '709', '0'], ['4', 'Roger De Coster', 'Belgium', 'Suzuki', '1865', '3'], ['16', 'Gary Jones', 'United States', 'Yamaha', '439', '0']] | 7 | Answer: | 128 | 20 | 503 |
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 yacht had the next best time (smaller time is better) than ausmaid? | [['Position', 'Sail Number', 'Yacht', 'State/Country', 'Yacht Type', 'LOA\\n(Metres)', 'Skipper', 'Elapsed Time\\nd:hh:mm:ss'], ['1', 'US17', 'Sayonara', 'USA', 'Farr ILC Maxi', '24.13', 'Larry Ellison', '2:19:03:32'], ['6', 'SM1', 'Fudge', 'VIC', 'Elliot 56', '17.07', 'Peter Hansen', '3:11:00:26'], ['3', 'YC1000', 'Ausmaid', 'SA', 'Farr 47', '14.24', 'Kevan Pearce', '3:06:02:29'], ['10', '8338', 'AFR Midnight Rambler', 'NSW', 'Hick 35', '10.66', 'Ed Psaltis\\nBob Thomas', '3:16:04:40'], ['4', 'AUS70', 'Ragamuffin', 'NSW', 'Farr 50', '15.15', 'Syd Fischer', '3:06:11:29'], ['2', 'C1', 'Brindabella', 'NSW', 'Jutson 79', '24.07', 'George Snow', '2:21:55:06'], ['8', '9090', 'Industrial Quest', 'QLD', 'Nelson Marek 43', '13.11', 'Kevin Miller', '3:14:58:46'], ['9', '4826', 'Aspect Computing', 'NSW', 'Radford 16.5 Sloop', '16.50', 'David Pescud', '3:15:28:24'], ['5', 'COK1', 'Nokia', 'CI', 'Farr Ketch Maxi', '25.20', 'David Witt', '3:09:19:00'], ['7', '6606', 'Quest', 'NSW', 'Nelson Marek 46', '14.12', 'Bob Steel', '3:14:41:28']] | Brindabella | Answer: | 128 | 10 | 466 |
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 match comes after gl-b-5? | [['Match', 'Date', 'Venue', 'Opponents', 'Score'], ['GL-B-1', '2008..', '[[]]', '[[]]', '-'], ['Quarterfinals-1', '2008..', '[[]]', '[[]]', '-'], ['GL-B-5', '2008..', '[[]]', '[[]]', '-'], ['GL-B-6', '2008..', '[[]]', '[[]]', '-'], ['Quarterfinals-2', '2008..', '[[]]', '[[]]', '-'], ['GL-B-4', '2008..', '[[]]', '[[]]', '-'], ['GL-B-3', '2008..', '[[]]', '[[]]', '-'], ['GL-B-2', '2008..', '[[]]', '[[]]', '-']] | GL-B-6 | Answer: | 128 | 8 | 170 |
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 was amanda on the judging panel? | [['Series', 'Premiere', 'Finale', 'Winner', 'Runner-up', 'Third place', 'Host(s)', 'Judging panel', 'Guest judge(s)'], ['One', '9 June 2007', '17 June 2007', 'Paul Potts', 'Damon Scott', 'Connie Talbot', 'Ant & Dec', 'Simon Cowell\\nAmanda Holden\\nPiers Morgan', 'N/A'], ['Three', '11 April 2009', '30 May 2009', 'Diversity', 'Susan Boyle', 'Julian Smith', 'Ant & Dec', 'Simon Cowell\\nAmanda Holden\\nPiers Morgan', 'Kelly Brook'], ['Eight', '12 April 2014', '31 May 2014', 'TBA', 'TBA', 'TBA', 'Ant & Dec', 'Simon Cowell\\nAmanda Holden\\nAlesha Dixon\\nDavid Walliams', 'Ant & Dec'], ['Five', '16 April 2011', '4 June 2011', 'Jai McDowall', 'Ronan Parke', 'New Bounce', 'Ant & Dec', 'Simon Cowell\\nAmanda Holden\\nDavid Hasselhoff\\nMichael McIntyre', 'Louis Walsh'], ['Six', '24 March 2012', '12 May 2012', 'Ashleigh and Pudsey', 'Jonathan and Charlotte', 'Only Boys Aloud', 'Ant & Dec', 'Simon Cowell\\nAmanda Holden\\nAlesha Dixon\\nDavid Walliams', 'Carmen Electra'], ['Four', '17 April 2010', '5 June 2010', 'Spelbound', 'Twist and Pulse', 'Kieran Gaffney', 'Ant & Dec', 'Simon Cowell\\nAmanda Holden\\nPiers Morgan', 'Louis Walsh'], ['Seven', '13 April 2013', '8 June 2013', 'Attraction', 'Jack Carroll', 'Richard & Adam', 'Ant & Dec', 'Simon Cowell\\nAmanda Holden\\nAlesha Dixon\\nDavid Walliams', 'N/A'], ['Nine', '2015', '2015', 'TBA', 'TBA', 'TBA', 'Ant & Dec', 'TBA', 'TBA'], ['Two', '12 April 2008', '31 May 2008', 'George Sampson', 'Signature', 'Andrew Johnston', 'Ant & Dec', 'Simon Cowell\\nAmanda Holden\\nPiers Morgan', 'N/A']] | 3 | Answer: | 128 | 9 | 546 |
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 awards has leona lewis won? | [['Year', 'Award', 'Nominated work', 'Category', 'Result'], ['2009', 'APRA Awards', '"Bleeding Love"', 'Most Played Foreign Work', 'Won'], ['2007', 'The Record of the Year', '"Bleeding Love"', 'The Record of the Year', 'Won'], ['2008', 'NME Best Album', '"Spirit"', 'Best Album', 'Nominated'], ['2008', 'Nickelodeon UK Kids Choice Awards', '"Bleeding Love"', 'Favourite Song', 'Won'], ['2007', 'Cosmopolitan Ultimate Woman of the Year', 'Leona Lewis', 'Newcomer of the Year', 'Won'], ['2008', 'New Music Weekly Awards', 'Leona Lewis', 'Top 40 New Artist of the Year', 'Won'], ['2009', 'Cosmopolitan Awards', 'Leona Lewis', 'Ultimate Music Star', 'Won'], ['2008', 'Capital Awards', 'Leona Lewis', 'Favourite UK Female Artist', 'Won'], ['2009', 'BEFFTA Awards', 'Leona Lewis', 'Best Female Act', 'Won'], ['2008', 'Bambi Award', 'Leona Lewis', 'Shooting Star', 'Won'], ['2009', 'HITO Pop Music Awards', '"Bleeding Love"', 'Best Western Song', 'Won'], ['2008', 'Glamour Woman Of The Year Awards', 'Leona Lewis', 'UK Solo Artist', 'Won'], ['2008', 'Billboard 2008 Year End Award', 'Leona Lewis', 'Best New Artist', 'Won'], ['2008', 'Vh1 Video of the Year', '"Bleeding Love"', 'Best Video', 'Won'], ['2008', 'NewNowNext Awards', 'Leona Lewis', 'The Kylie Award: Next International Crossover', 'Won'], ['2009', 'Swiss Music Awards', 'Leona Lewis', 'Best International Newcomer', 'Won'], ['2008', 'PETA', 'Leona Lewis', 'Person Of The Year', 'Won'], ['2008', 'UK Music Video Awards', '"Bleeding Love"', "People's Choice Award", 'Won'], ['2009', 'PETA - Sexiest Vegetarian Alive Awards', 'Leona Lewis', 'Sexiest Vegetarian Celebrity 2009', 'Won'], ['2008', "Britain's Best", 'Leona Lewis', 'Music Award', 'Won'], ['2009', 'Japan Gold Disc Awards', 'Leona Lewis', 'New Artist Of The Year', 'Won'], ['2009', 'NAACP Image Awards', 'Leona Lewis', 'Outstanding New Artist', 'Nominated']] | 20 | Answer: | 128 | 22 | 576 |
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 top scorer in the last season? | [['Season', 'League\\nPos.', 'League\\nCompetition', 'League\\nTop scorer', 'Danish Cup', 'Europe', 'Others'], ['2007-08', '8', '2007-08 Superliga', 'Morten Rasmussen (7)\\nMartin Ericsson (7)', 'Winner', '', ''], ['1999-00', '2', '1999-00 Superliga', 'Bent Christensen (13)', 'Semi-final', 'EC1 qual 3rd round\\nEC3 1st round', ''], ['1981-82', '4', '1982 1st Division', 'Michael Laudrup (15)', '4th round', '', ''], ['1985-86', '2', '1986 1st Division', 'Claus Nielsen (16)', 'Quarter-final', '', ''], ['2004-05', '1', '2004-05 Superliga', 'Thomas Kahlenberg (13)', 'Winner', 'EC3 qual 2nd round', 'Royal League group stage'], ['1996-97', '1', '1996-97 Superliga', 'Peter Møller (22)', 'Semi-final', 'EC1 qualification round\\nEC3 quarter-final', 'Danish Supercup winner'], ['2009-10', '3', '2009-10 Superliga', 'Morten Rasmussen (12)', '4th round', 'EC3 qual play-off round', ''], ['2010-11', '3', '2010-11 Superliga', 'Michael Krohn-Dehli (11)', '', '', ''], ['1990-91', '1', '1991 Superliga', 'Bent Christensen (11)', 'Semi-final', 'EC3 semi-final', ''], ['1987-88', '1', '1988 1st Division', 'Bent Christensen (21)', 'Finalist', 'EC3 2nd round', ''], ['2008-09', '3', '2008-09 Superliga', 'Morten Rasmussen (9)\\nAlexander Farnerud (9)\\nOusman Jallow (9)', 'Semi-final', 'EC3 1st round', ''], ['1988-89', '2', '1989 1st Division', 'Bent Christensen (10)', 'Winner', 'EC1 1st round', ''], ['1993-94', '3', '1993-94 Superliga', 'Mark Strudal (13)', 'Winner', 'EC3 3rd round', ''], ['2011-12', '9', '2011-12 Superliga', 'Simon Makienok Christoffersen (10)', '', '', ''], ['1989-90', '1', '1990 1st Division', 'Bent Christensen (17)', 'Quarter-final', 'EC1 1st round', ''], ['2003-04', '2', '2003-04 Superliga', 'Thomas Kahlenberg (11)', 'Semi-final', 'EC3 3rd round', ''], ['1997-98', '1', '1997-98 Superliga', 'Ebbe Sand (28)', 'Winner', 'EC1 qual 2nd round\\nEC3 1st round', 'Danish Supercup winner'], ['2005-06', '2', '2005-06 Superliga', 'Johan Elmander (13)', 'Semi-final', 'EC1 qual 3rd round\\nEC3 group stage', 'Royal League group stage\\nDanish League Cup winner'], ['2001-02', '1', '2001-02 Superliga', 'Peter Madsen (22)', '5th round', 'EC3 3rd round', ''], ['1995-96', '1', '1995-96 Superliga', 'Peter Møller (15)', 'Finalist', 'EC3 3rd round', ''], ['1994-95', '2', '1994-95 Superliga', 'Mark Strudal (12)', 'Quarter-final', 'EC2 2nd round', 'Danish Supercup winner'], ['1998-99', '2', '1998-99 Superliga', 'Ebbe Sand (19)', 'Semi-final', 'EC1 group stage', ''], ['1991-92', '7', '1991-92 Superliga', 'Kim Vilfort (9)', '4th round', 'EC1 2nd round', ''], ['1992-93', '3', '1992-93 Superliga', 'Kim Vilfort (10)', '5th round', '', '']] | Simon Makienok Christoffersen | Answer: | 128 | 24 | 1,020 |
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 jury members were there? | [['Contestant', 'Original Tribe', 'Switched Tribe', 'Merged Tribe', 'Finish', 'Total Votes'], ['Dana Borisova\\n26.the TV presenter', 'Pelicans', 'Barracudas', '', '4th Voted Out\\nDay 12', '5'], ['Yelena Kondulaynen\\n44.the actress', 'Pelicans', '', '', '1st Voted Out\\nDay 3', '5'], ['Marina Aleksandrova\\n20.the actress', 'Barracudas', 'Pelicans', 'Crocodiles', '9th Voted Out\\n4th Jury Member\\nDay 27', '6'], ['Vera Glagoleva\\n46.the actress', '', '', 'Crocodiles', '11th Voted Out\\n6th Jury Member\\nDay 33', '4'], ['Ivar Kalnynsh\\n54.the actor', '', '', 'Crocodiles', '10th Voted Out\\n5th Jury Member\\nDay 30', '3'], ['Viktor Gusev\\n47.the sport commentator', 'Pelicans', 'Pelicans', 'Crocodiles', '7th Voted Out\\n1st Jury Member\\nDay 21', '6'], ["Tat'yana Ovsiyenko\\n36.the singer", 'Barracudas', 'Pelicans', '', 'Eliminated\\nDay 19', '1'], ['Tatyana Dogileva\\n45.the actress', 'Pelicans', 'Barracudas', '', '6th Voted Out\\nDay 18', '3'], ['Vladimir Presnyakov, Jr.\\n34.the singer', 'Pelicans', 'Pelicans', 'Crocodiles', 'Sole Survivor', '6'], ['Yelena Perova\\n26.the singer', 'Pelicans', 'Pelicans', 'Crocodiles', 'Runner-Up', '2'], ['Yelena Proklova\\n49.the TV presenter', 'Pelicans', 'Barracudas', 'Crocodiles', '8th Voted Out\\n3rd Jury Member\\nDay 24', '4'], ['Aleksandr Lykov\\n41.the actor', 'Barracudas', 'Barracudas', 'Crocodiles', '13th Voted Out\\n8th Jury Member\\nDay 37', '6'], ['Kris Kelmi\\n47.the singer', 'Barracudas', '', '', '2nd Voted Out\\nDay 6', '1'], ['Aleksandr Byalko\\n50.the physicist', 'Pelicans', 'Barracudas', '', '5th Voted Out\\nDay 15', '6'], ['Aleksandr Pashutin\\n60.the actor', 'Barracudas', '', '', '3rd Voted Out\\nDay 9', '7'], ['Olga Orlova\\n25.the singer', 'Barracudas', 'Baracudas', 'Crocodiles', 'Eliminated\\n9th Jury Member\\nDay 38', '10'], ['Larisa Verbitskaya\\n43.the TV presenter', 'Barracudas', 'Pelicans', 'Crocodiles', '12th Voted Out\\n7th Jury Member\\nDay 36', '11'], ['Ivan Demidov\\n39.the TV presenter', 'Barracudas', 'Pelicans', 'Crocodiles', 'Eliminated\\n2nd Jury Member\\nDay 23', '3'], ["Igor' Livanov\\n49.the actor", 'Pelicans', '', '', 'Eliminated\\nDay 11', '0']] | 9 | Answer: | 128 | 19 | 808 |
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 was the val d'lsere, france location used? | [['Season', 'Age', 'Overall', 'Slalom', 'Giant\\nSlalom', 'Super G', 'Downhill', 'Combined'], ['Season', 'Date', 'Location', 'Race', '', '', '', ''], ['2012', '25', '24', '–', '16', '28', '17', '19'], ['2010', '6 Dec 2009', 'Beaver Creek, USA', 'Giant Slalom', '', '', '', ''], ['2014', '27', '18', '–', '25', '14', '20', '11'], ['2013', '26', '48', '–', '48', '27', '38', '4'], ['2009', '13 Dec 2008', "Val d'Isère, France", 'Giant slalom', '', '', '', ''], ['2011', '5 Mar 2011', 'Kranjska Gora, Slovenia', 'Giant Slalom', '', '', '', ''], ['2010', '10 Mar 2010', 'Garmisch, Germany', 'Downhill', '', '', '', ''], ['2010', '4 Dec 2009', 'Beaver Creek, USA', 'Super Combined', '', '', '', ''], ['2008', '21', '64', '–', '28', '46', '46', '31'], ['2010', '16 Jan 2010', 'Wengen, Switzerland', 'Downhill', '', '', '', ''], ['2010', '23', '1', '–', '2', '6', '2', '2'], ['2010', '5 Dec 2009', 'Beaver Creek, USA', 'Downhill', '', '', '', ''], ['2009', '22', '7', '–', '6', '16', '16', '1'], ['2011', '24', '3', '–', '5', '6', '9', '6'], ['2007', '20', '130', '–', '40', '–', '–', '—'], ['2010', '12 Mar 2010', 'Garmisch, Germany', 'Giant Slalom', '', '', '', ''], ['2009', '16 Jan 2009', 'Wengen, Switzerland', 'Super Combined', '', '', '', '']] | 1 | Answer: | 128 | 18 | 505 |
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what is the name listed before mount pleasant line? | [['Route', 'Name', 'Fare Type', 'Terminals', 'Terminals', 'Major streets', 'Notes', 'History'], ['H2, H3, H4', 'Crosstown Line', 'Local', 'Tenleytown-AU station', 'Brookland-CUA station', 'Wisconsin Avenue\\nPorter Street NW\\nVan Ness/Veazey Street NW (H2)\\nConnecticut Avenue (H2)\\nColumbia Road NW/Irving Street NW\\nMichigan Avenue NW/NE', 'H3: weekday peak hour service only\\nH3: Skips Washington Hospital Center', "H2 & H4 operated to Fort Lincoln (east of Brookland station) until replaced by H6 in the late 1990s. They also operated to Westmoreland Circle & Western Avenue NW (west of Tenleytown station) until replaced by the N8 in the late 1990s. H3's route west of Porter Street & Connecticut Avenue NW was served by H2 until it was rerouted to serve and terminate at Van Ness Station in the early 2000s. H2 was later rerouted back to its Tenleytown terminus, replacing the N8 route east of Tenleytown and rerouting the H3 to serve exactly the same route as the H4 with the exception of Washington Hospital Center."], ['W2, W3', 'United Medical Center-Anacostia Line', 'Local', 'United Medical Center', 'Washington Overlook (Mellon St & Martin Luther King Av SE)\\nAnacostia station', 'Southern Avenue\\nAlabama Avenue SE\\nMorris Road SE\\nMartin Luther King Avenue SE', 'W3: Monday-Friday service only.\\n\\nFare: $1 (unless transferring to another bus)', '(Portions of the W2 & W3 operate on the old M18 & M20 (Metro "Mini-Bus") routes'], ['W1', 'Shipley Terrace-Fort Drum Line', 'Local', 'Fort Drum', 'Southern Avenue station', 'Alabama Avenue SE\\nMartin Luther King Jr Avenue', 'W1: Monday-Friday service only.', 'W1 replace the M8, M9 on March 3, 2014.'], ['U8', 'Capitol Heights-Benning Heights Line', 'Local', 'Capitol Heights station and Benning Heights (H St & 45th Place SE)', 'Minnesota Avenue station', 'Nannie Helen Burroughs Avenue NE\\nBenning Road NE/SE', 'order of terminals (east to west): Capitol Heights to Minnesota Avenue then Minnesota Avenue to Benning Heights, then reverse.', 'U8 was created to replace the former X2, X4 & X6 routes east of Minnesota Avenue station in the late 1990s (X2 to Capitol Heights station, X4 then X6 to Benning Heights)'], ['D5', 'MacArthur Boulevard-Georgetown Line', 'Local', 'Little Flower Church (Bethesda, MD)', 'Farragut Square', 'MacArthur Boulevard NW\\nM Street NW\\nPennsylvania Avenue NW', 'Operates weekday peak hours only (AM to Farragut Square, PM to Little Flower Church).', 'Formerly known as the MacArthur Boulevard-M Street Line (with the former D9, which was discontinued in the mid-1990s)'], ['74', 'Convention Center-Southwest Waterfront Line', 'Local', 'Mount Vernon Square (K & 6th Streets NW)', 'Half & O Streets SW, or Buzzard Point (2nd & V Streets SW)', '7th Street NW/SW', 'Serves Buzzard Point during rush hour only', "Introduced September 24, 2011 as a replacement of DC Circulator's discontinued Convention Center-Southwest Waterfront route, and to also serve the southern portion of the 70 and 71 routes."], ['80', 'North Capitol Street Line', 'Local', 'Fort Totten station', 'Kennedy Center', '12th Street NE\\nMichigan Avenue NE\\nNorth Capitol Street\\nH Street NW\\nK Street NW', 'some peak hour and early AM/late night trips terminate at McPherson Square station', '80 operates on the old North Capitol Street Streetcar Line, which operated from Washington Circle to Brookland until 1958\\nIt operated to Potomac Park until it replaced the portion of the old Route 81 south of Pennsylvania Avenue NW to Kennedy Center after it was discontinued in the mid-1990s']] | Pennsylvania Avenue Metro Extra Line | Answer: | 128 | 7 | 958 |
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 stadium listed on this chart? | [['Team', 'Stadium', 'Capacity', 'City/Area'], ['Leeds Rhinos (2014 season)', 'Headingley Carnegie Stadium', '22,250', 'Leeds, West Yorkshire'], ['Hull Kingston Rovers (2014 season)', 'MS3 Craven Park', '9,471', 'Kingston upon Hull, East Riding of Yorkshire'], ['Widnes Vikings (2014 season)', 'The Select Security Stadium', '13,500', 'Widnes, Cheshire, England'], ['Huddersfield Giants (2014 season)', "John Smith's Stadium", '24,544', 'Huddersfield, West Yorkshire'], ['Bradford Bulls (2014 season)', 'Provident Stadium', '27,000', 'Bradford, West Yorkshire'], ['Wigan Warriors (2014 season)', 'DW Stadium', '25,138', 'Wigan, Greater Manchester'], ['Warrington Wolves (2014 season)', 'Halliwell Jones Stadium', '15,500', 'Warrington, Cheshire'], ['Wakefield Trinity Wildcats (2014 season)', 'Rapid Solicitors Stadium', '11,000', 'Wakefield, West Yorkshire'], ['Catalans Dragons (2014 season)', 'Stade Gilbert Brutus', '14,000', 'Perpignan, Pyrénées-Orientales, France'], ['St Helens RLFC (2014 season)', 'Langtree Park', '18,000', 'St Helens, Merseyside'], ['London Broncos (2014 season)', 'Twickenham Stoop', '12,700', 'Twickenham, London'], ['Salford City Reds (2014 season)', 'Salford City Stadium', '12,000', 'Salford, Greater Manchester'], ['Castleford Tigers (2014 season)', 'The Wish Communications Stadium', '11,750', 'Castleford, West Yorkshire'], ['Hull (2014 season)', 'Kingston Communications Stadium', '25,404', 'Kingston upon Hull, East Riding of Yorkshire']] | DW Stadium | Answer: | 128 | 14 | 432 |
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 salvatore bettiol win first place across competitions? | [['Year', 'Competition', 'Venue', 'Position', 'Event', 'Notes'], ['1991', 'World Championships', 'Tokyo, Japan', '6th', 'Marathon', '2:15:58'], ['1990', 'European Championships', 'Split, FR Yugoslavia', '4th', 'Marathon', '2:17:45'], ['1992', 'Olympic Games', 'Barcelona, Spain', '5th', 'Marathon', '2:14:15'], ['1996', 'Olympic Games', 'Atlanta, United States', '20th', 'Marathon', '2:17:27'], ['1993', 'World Championships', 'Stuttgart, Germany', '—', 'Marathon', 'DNF'], ['1986', 'Venice Marathon', 'Venice, Italy', '1st', 'Marathon', '2:18:44'], ['1987', 'Venice Marathon', 'Venice, Italy', '1st', 'Marathon', '2:10:01'], ['1987', 'World Championships', 'Rome, Italy', '13th', 'Marathon', '2:17:45']] | 2 | Answer: | 128 | 8 | 253 |
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 did illinois not have any losses during the conference? | [['School', 'Season', 'Record', 'Conference Record', 'Place', 'Postseason'], ['Illinois', '1917–18', '9–6', '6–6', 'T4th', ''], ['Illinois', '1913–14', '9–4', '7–3', '3rd', ''], ['Illinois', '1914–15', '16–0', '12–0', 'T1st', 'National Champions'], ['Illinois', '1912–20', '85–34', '64–31', '–', ''], ['Illinois', '1916–17', '13–3', '10–2', 'T1st', 'Big Ten Champions'], ['Illinois', '1912–13', '10–6', '7–6', '5th', ''], ['Illinois', '1915–16', '13–3', '9–3', 'T2nd', ''], ['Illinois', '1918–19', '6–8', '5–7', '5th', ''], ['Illinois', '1919–20', '9–4', '8–4', '3rd', '']] | 1914-15 | Answer: | 128 | 9 | 262 |
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:natalia varnakova is the same height as which other contestant(s)? | [['Represent', 'Candidate', 'in Russian', 'Age', 'Height', 'Hometown'], ['Saratov Oblast', 'Anastasija Marnolova', 'Анастасия Марнолова', '21', '1.74\xa0m (5\xa0ft 8\xa01⁄2\xa0in)', 'Saratov'], ['Capital City', 'Natalia Varnakova', 'Наталиа Варнакова', '19', '1.80\xa0m (5\xa0ft 11\xa0in)', 'Moscow'], ['Chelyabinsk Oblast', 'Tatiana Abramenko', 'Татиана Абраменко', '21', '1.74\xa0m (5\xa0ft 8\xa01⁄2\xa0in)', 'Chelyabinsk'], ['Oryol Oblast', 'Natalia Pavšukova', 'Наталиа Павшукова', '19', '1.79\xa0m (5\xa0ft 10\xa01⁄2\xa0in)', 'Oryol'], ['Novgorod Oblast', 'Ekaterina Žuravleva', 'Екатерина Журавлева', '20', '1.81\xa0m (5\xa0ft 11\xa01⁄2\xa0in)', 'Novgorod'], ['Sakha Republic', 'Sardana Syromyatnikova', 'Сардана Сыромыатникова', '19', '1.82\xa0m (5\xa0ft 11\xa01⁄2\xa0in)', 'Yakutia'], ['Mari El Republic', 'Anna Il’ina', 'Анна Ильина', '19', '1.88\xa0m (6\xa0ft 2\xa0in)', 'Medvedevo'], ['Chukotka Okrug', 'Mariesea Mnesiču', 'Мариесеа Мнесичу', '19', '1.80\xa0m (5\xa0ft 11\xa0in)', 'Anadyr'], ['Belgorod Oblast', 'Jahaira Novgorodova', 'Яхаира Новгородова', '25', '1.80\xa0m (5\xa0ft 11\xa0in)', 'Belgorod'], ['Nenets Okrug', 'Sofia Meldemendev', 'Софиа Мелдемендев', '25', '1.85\xa0m (6\xa0ft 1\xa0in)', 'Naryan-Mar'], ['Kostroma Oblast', 'Ekaterina Protod’jakonova', 'Екатерина Протодьяконова', '18', '1.84\xa0m (6\xa0ft 1⁄2\xa0in)', 'Kostroma'], ['Irkutsk Oblast', 'Yulia Samoylova', 'Ыулиа Самоылова', '21', '1.77\xa0m (5\xa0ft 9\xa01⁄2\xa0in)', 'Irkutsk'], ['Leningrad Oblast', 'Mercedes Laplsjfda', 'Мерцедес Лаплсйфда', '18', '1.79\xa0m (5\xa0ft 10\xa01⁄2\xa0in)', 'Leningrad'], ['Tatarstan Republic', 'Anastasija Muhammad', 'Анастасия Мухаммад', '19', '1.84\xa0m (6\xa0ft 1⁄2\xa0in)', 'Kazan'], ['Karachay-Cherkess Republic', 'Stephanie Drjagina', 'Степхание Дрягина', '24', '1.81\xa0m (5\xa0ft 11\xa01⁄2\xa0in)', 'Kaluga'], ['Yaroslavl Oblast', 'Emely Androlevy', 'Емелы Андролевы', '23', '1.73\xa0m (5\xa0ft 8\xa0in)', 'Yaroslavl'], ['Pskov Oblast', 'Anastasija Germonova', 'Анастасия Гермонова', '22', '1.75\xa0m (5\xa0ft 9\xa0in)', 'Pskov'], ['Sakhalin Oblast', 'Jeannette Menova', 'Йеаннетте Менова', '18', '1.75\xa0m (5\xa0ft 9\xa0in)', 'Sakhalin']] | Jahaira Novgorodova, Carmen Jenockova, Mariesea Mnesiču, Patricia Valiahmetova, Anastasija Larkova | Answer: | 128 | 18 | 1,004 |
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 candidates belong to a party other than republican or democrat? | [['District', 'Incumbent', '2008 Status', 'Democratic', 'Republican'], ['4', 'Marilyn Musgrave', 'Re-election', 'Betsy Markey', 'Marilyn Musgrave'], ['5', 'Doug Lamborn', 'Re-election', 'Hal Bidlack', 'Doug Lamborn'], ['1', 'Diana DeGette', 'Re-election', 'Diana DeGette', 'George Lilly'], ['2', 'Mark Udall', 'Open', 'Jared Polis', 'Scott Starin'], ['6', 'Tom Tancredo', 'Open', 'Hank Eng', 'Mike Coffman'], ['3', 'John Salazar', 'Re-election', 'John Salazar', 'Wayne Wolf'], ['7', 'Ed Perlmutter', 'Re-election', 'Ed Perlmutter', 'John W. Lerew']] | 0 | Answer: | 128 | 7 | 185 |
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 competitions were not in the united kingdom? | [['Date', 'Competition', 'Location', 'Country', 'Event', 'Placing', 'Rider', 'Nationality'], ['1 November 2009', '2009–10 World Cup', 'Manchester', 'United Kingdom', 'Team sprint', '1', 'Ross Edgar', 'GBR'], ['2 November 2008', '2008–09 World Cup', 'Manchester', 'United Kingdom', 'Team sprint', '1', 'Jason Kenny', 'GBR'], ['13 February 2009', '2008–09 World Cup', 'Copenhagen', 'Denmark', 'Team sprint', '1', 'Jamie Staff', 'GBR'], ['31 October 2008', '2008–09 World Cup', 'Manchester', 'United Kingdom', 'Keirin', '2', 'Jason Kenny', 'GBR'], ['30 October 2009', '2009–10 World Cup', 'Manchester', 'United Kingdom', 'Sprint', '1', 'Chris Hoy', 'GBR'], ['2 November 2008', '2008–09 World Cup', 'Manchester', 'United Kingdom', 'Team sprint', '1', 'Ross Edgar', 'GBR'], ['30 October 2009', '2009–10 World Cup', 'Manchester', 'United Kingdom', '500 m time trial', '2', 'Victoria Pendleton', 'GBR'], ['2 November 2008', '2008–09 World Cup', 'Manchester', 'United Kingdom', 'Keirin', '1', 'Victoria Pendleton', 'GBR'], ['1 November 2009', '2009–10 World Cup', 'Manchester', 'United Kingdom', 'Team sprint', '1', 'Chris Hoy', 'GBR'], ['1 November 2009', '2009–10 World Cup', 'Manchester', 'United Kingdom', 'Team sprint', '1', 'Jamie Staff', 'GBR'], ['13 February 2009', '2008–09 World Cup', 'Copenhagen', 'Denmark', 'Sprint', '1', 'Victoria Pendleton', 'GBR'], ['1 November 2008', '2008–09 World Cup', 'Manchester', 'United Kingdom', 'Sprint', '1', 'Jason Kenny', 'GBR'], ['13 February 2009', '2008–09 World Cup', 'Copenhagen', 'Denmark', 'Team sprint', '1', 'Jason Kenny', 'GBR'], ['31 October 2008', '2008–09 World Cup', 'Manchester', 'United Kingdom', 'Sprint', '1', 'Victoria Pendleton', 'GBR'], ['30 October 2009', '2009–10 World Cup', 'Manchester', 'United Kingdom', 'Sprint', '1', 'Victoria Pendleton', 'GBR'], ['30 October 2009', '2009–10 World Cup', 'Manchester', 'United Kingdom', 'Keirin', '1', 'Chris Hoy', 'GBR'], ['2 November 2008', '5th International Keirin Event', 'Manchester', 'United Kingdom', 'International keirin', '2', 'Ross Edgar', 'GBR'], ['13 February 2009', '2008–09 World Cup', 'Copenhagen', 'Denmark', 'Team sprint', '1', 'Chris Hoy', 'GBR'], ['1 November 2008', '2008–09 World Cup', 'Manchester', 'United Kingdom', '500 m time trial', '1', 'Victoria Pendleton', 'GBR'], ['2 November 2008', '2008–09 World Cup', 'Manchester', 'United Kingdom', 'Team sprint', '1', 'Jamie Staff', 'GBR']] | 4 | Answer: | 128 | 20 | 788 |
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 domestic routes out of houston intercontinental have united as a carrier? | [['Rank', 'City', 'Passengers', 'Top Carriers'], ['1', 'Los Angeles, CA', '700,000', 'American, Spirit, United'], ['4', 'San Francisco, CA', '492,000', 'United'], ['10', 'Phoenix, AZ', '393,000', 'United, US Airways'], ['7', 'Las Vegas, NV', '442,000', 'Spirit, United'], ['9', 'Atlanta, GA', '400,000', 'Delta, United'], ['2', 'Chicago, IL', '673,000', 'American, Spirit, United'], ['5', 'Dallas/Fort Worth, TX', '488,000', 'American, United'], ['6', 'Newark, NJ', '480,000', 'United'], ['8', 'Charlotte, NC', '441,000', 'United, US Airways'], ['3', 'Denver, CO', '654,000', 'Frontier, Spirit, United']] | 10 | Answer: | 128 | 10 | 207 |
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 total, how many germans are listed? | [['Place', 'Rider', 'Country', 'Team', 'Points', 'Wins'], ['10', 'Dave Bickers', 'United Kingdom', 'ČZ', '1076', '0'], ['3', 'Torlief Hansen', 'Sweden', 'Husqvarna', '2052', '0'], ['16', 'Gary Jones', 'United States', 'Yamaha', '439', '0'], ['2', 'Adolf Weil', 'Germany', 'Maico', '2331', '2'], ['8', 'Gaston Rahier', 'Belgium', 'ČZ', '1112', '0'], ['11', 'John Banks', 'United Kingdom', 'ČZ', '971', '0'], ['5', 'Joel Robert', 'Belgium', 'Suzuki', '1730', '1'], ['4', 'Roger De Coster', 'Belgium', 'Suzuki', '1865', '3'], ['19', 'Uno Palm', 'Sweden', 'Husqvarna', '324', '0'], ['17', 'John DeSoto', 'United States', 'Suzuki', '425', '0'], ['1', 'Sylvain Geboers', 'Belgium', 'Suzuki', '3066', '3'], ['15', 'Brad Lackey', 'United States', 'ČZ', '603', '0'], ['7', 'Willy Bauer', 'Germany', 'Maico', '1276', '0'], ['20', 'Peter Lamppu', 'United States', 'Montesa', '309', '0'], ['6', 'Heikki Mikkola', 'Finland', 'Husqvarna', '1680', '2'], ['12', 'Andy Roberton', 'United Kingdom', 'Husqvarna', '810', '0'], ['14', 'Mark Blackwell', 'United States', 'Husqvarna', '604', '0'], ['18', 'Chris Horsefield', 'United Kingdom', 'ČZ', '416', '0'], ['13', 'Vlastimil Valek', 'Czechoslovakia', 'ČZ', '709', '0'], ['9', 'Pierre Karsmakers', 'Netherlands', 'Husqvarna', '1110', '0']] | 2 | Answer: | 128 | 20 | 503 |
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 are there the first results for giant slalom? | [['Season', 'Age', 'Overall', 'Slalom', 'Giant\\nSlalom', 'Super G', 'Downhill', 'Combined'], ['2005', '18', '37', '–', '27', '18', '49', '—'], ['2006', '19', '22', '–', '18', '37', '15', '—'], ['2004', '17', '112', '–', '–', '51', '–', '—'], ['2013', '26', '37', '–', '17', '28', '30', '—'], ['2007', '20', '33', '–', '50', '15', '23', '—'], ['2010', '23', '28', '–', '–', '13', '23', '—'], ['2008', '21', '38', '–', '–', '35', '13', '—'], ['2009', '22', '9', '–', '40', '2', '5', '50'], ['2011', '24', 'Injured, did not compete', 'Injured, did not compete', 'Injured, did not compete', 'Injured, did not compete', 'Injured, did not compete', 'Injured, did not compete'], ['2012', '25', '75', '–', '28', '–', '–', '—']] | 2005 | Answer: | 128 | 10 | 312 |
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 cycle 4 of austria's next top model,how many contestants were older than 20? | [['Contestant', 'Age', 'Height', 'Home City', 'Rank'], ['Alina Chlebecek', '18', '170\xa0cm (5\xa0ft 7 in)', 'Deutsch-Wagram', 'Eliminated in Episode 1'], ['Michaela Schopf', '21', '172\xa0cm (5\xa0ft 7.5 in)', 'Salzburg (originally from Germany)', 'Quit in Episode 4'], ['Melisa Popanicić', '16', '175\xa0cm (5\xa0ft 9 in)', 'Wörgl', '2nd Eliminated in Episode 10'], ['Gina Zeneb Adamu', '17', '175\xa0cm (5\xa0ft 9 in)', 'Bad Vöslau', 'Runner-Up'], ['Katharina Mihalović', '23', '179\xa0cm (5\xa0ft 10.5 in)', 'Vienna', 'Eliminated in Episode 2'], ['Isabelle Raisa', '16', '170\xa0cm (5\xa0ft 7 in)', 'Vienna', 'Eliminated in Episode 1'], ['Christine Riener', '20', '181\xa0cm (5\xa0ft 11.25 in)', 'Bludenz', 'Eliminated in Episode 4'], ['Izabela Pop Kostić', '20', '170\xa0cm (5\xa0ft 7 in)', 'Vienna (originally from Bosnia)', 'Eliminated in Episode 8'], ['Nadine Trinker', '21', '183\xa0cm (6\xa0ft 0 in)', 'Bodensdorf', 'Eliminated in Episode 9'], ['Bianca Ebelsberger', '24', '179\xa0cm (5\xa0ft 10.5 in)', 'Aurach am Hongar', 'Eliminated in Episode 9'], ['Sabrina Angelika Rauch †', '21', '175\xa0cm (5\xa0ft 9 in)', 'Graz', 'Eliminated in Episode 2'], ['Antonia Maria Hausmair', '16', '175\xa0cm (5\xa0ft 9 in)', 'Siegendorf', 'Winner'], ['Yemisi Rieger', '17', '177\xa0cm (5\xa0ft 9.5 in)', 'Vienna', 'Eliminated in Episode 7'], ['Teodora-Mădălina Andreica', '17', '177\xa0cm (5\xa0ft 9.5 in)', 'Romania', 'Eliminated in Episode 6'], ['Dzejlana "Lana" Baltić', '20', '179\xa0cm (5\xa0ft 10.5 in)', 'Graz (originally from Bosnia)', '1st Eliminated in Episode 10'], ['Nataša Marić', '16', '175\xa0cm (5\xa0ft 9 in)', 'Liefering (originally from Serbia)', 'Eliminated in Episode 3']] | 5 | Answer: | 128 | 16 | 665 |
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 more goals: clint dempsey or eric wynalda? | [['#', 'Player', 'Goals', 'Caps', 'Career'], ['6T', 'Bruce Murray', '21', '86', '1985–1993'], ['6T', 'Jozy Altidore', '21', '67', '2007–present'], ['3', 'Eric Wynalda', '34', '106', '1990–2000'], ['5', 'Joe-Max Moore', '24', '100', '1992–2002'], ['1', 'Landon Donovan', '57', '155', '2000–present'], ['4', 'Brian McBride', '30', '95', '1993–2006'], ['9T', 'Earnie Stewart', '17', '101', '1990–2004'], ['2', 'Clint Dempsey', '36', '103', '2004–present'], ['9T', 'DaMarcus Beasley', '17', '114', '2001–present'], ['8', 'Eddie Johnson', '19', '62', '2004–present']] | Clint Dempsey | Answer: | 128 | 10 | 229 |
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 building had the least height in germany? | [['Name', 'Country', 'Town', 'Height\\nmetres / ft', 'Structural type', 'Held record', 'Notes'], ['Chrysler Building', 'United States', 'New York City', '319 / 1,046', 'Skyscraper', '1930–1931', ''], ['Empire State Building', 'United States', 'New York City', '448 / 1,472', 'Skyscraper', '1931–1967', ''], ["St. Mary's Church", 'Germany', 'Stralsund', '151 / 500', 'Church', '1549–1647', 'Spire destroyed by lightning in 1647; today stands at a height of 104 metres (341\xa0ft).'], ['CN Tower', 'Canada', 'Toronto', '553 / 1,815', 'Tower', '1976–2007', ''], ['Strasbourg Cathedral', 'Germany and/or France (today France)', 'Strasbourg', '142 / 470', 'Church', '1647–1874', ''], ['Lincoln Cathedral', 'England', 'Lincoln', '159.7 / 524', 'Church', '1311–1549', 'Spire collapsed in 1549; today, stands at a height of 83 metres (272\xa0ft).'], ['Cologne Cathedral', 'Germany', 'Cologne', '157.4 / 516', 'Church', '1880–1884', ''], ['Notre-Dame Cathedral', 'France', 'Rouen', '151 / 500', 'Church', '1876–1880', ''], ['Eiffel Tower', 'France', 'Paris', '300.6 / 986', 'Tower', '1889–1930', 'Currently stands at a height of 324 metres (1,063\xa0ft).'], ['Burj Khalifa', 'United Arab Emirates', 'Dubai', '829.8 / 2,722', 'Skyscraper', '2007–present', 'Topped-out on 17 January 2009'], ['Washington Monument', 'United States', 'Washington, D.C.', '169.3 / 555', 'Monument', '1884–1889', ''], ['Great Pyramid of Giza', 'Egypt', 'Giza', '146 / 480', 'Mausoleum', '2570 BC–1311', 'Due to erosion today it stands at the height of 138.8 metres (455\xa0ft).'], ['St Nikolai', 'Germany', 'Hamburg', '147.3 / 483', 'Church', '1874–1876', 'Due to aerial bombing in World War II the nave was demolished; only the spire remains.'], ['Ostankino Tower', 'Russia', 'Moscow', '540 / 1,772', 'Tower', '1967–1976', '']] | St. Mary's Church | Answer: | 128 | 14 | 623 |
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:besides republican (r) and democrat (d), what other party was represented in the maine election? | [['State\\n(linked to\\nsummaries below)', 'Incumbent\\nSenator', 'Incumbent\\nParty', 'Incumbent\\nElectoral\\nhistory', 'Most recent election results', '2018 intent', 'Candidates'], ['Connecticut', 'Chris Murphy', 'Democratic', 'Chris Murphy (D) 54.8%\\nLinda McMahon (R) 43.1%\\nPaul Passarelli (L) 1.7%', '2012', '[Data unknown/missing. You\xa0can\xa0help!]', '[Data unknown/missing. You\xa0can\xa0help!]'], ['Wyoming', 'John Barrasso', 'Republican', 'John Barrasso (R) 75.7%\\nTim Chestnut (D) 21.7%\\nJoel Otto (Wyoming Country) 2.6%', '2008 (special)\\n2012', '[Data unknown/missing. You\xa0can\xa0help!]', '[Data unknown/missing. You\xa0can\xa0help!]'], ['Nebraska', 'Deb Fischer', 'Republican', 'Deb Fischer (R) 57.8%\\nBob Kerrey (D) 42.2%', '2012', '[Data unknown/missing. You\xa0can\xa0help!]', '[Data unknown/missing. You\xa0can\xa0help!]'], ['Florida', 'Bill Nelson', 'Democratic', 'Bill Nelson (D) 55.2%\\nConnie Mack IV (R) 42.2%', '2000\\n2006\\n2012', '[Data unknown/missing. You\xa0can\xa0help!]', '[Data unknown/missing. You\xa0can\xa0help!]'], ['Nevada', 'Dean Heller', 'Republican', 'Dean Heller (R) 45.9%\\nShelley Berkley (D) 44.7%\\nDavid Lory VanderBeek (C) 4.9%\\nNone of These Candidates 4.5%', '2012', '[Data unknown/missing. You\xa0can\xa0help!]', '[Data unknown/missing. You\xa0can\xa0help!]'], ['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\xa0can\xa0help!]'], ['Hawaii', 'Mazie Hirono', 'Democratic', 'Mazie Hirono (D) 62.6%\\nLinda Lingle (R) 37.4%', '2012', '[Data unknown/missing. You\xa0can\xa0help!]', '[Data unknown/missing. You\xa0can\xa0help!]'], ['Pennsylvania', 'Bob Casey, Jr.', 'Democratic', 'Bob Casey, Jr. (D) 53.7%\\nTom Smith (R) 44.6%\\nRayburn Douglas Smith (L) 1.7%', '2006\\n2012', '[Data unknown/missing. You\xa0can\xa0help!]', '[Data unknown/missing. You\xa0can\xa0help!]'], ['Massachusetts', 'Elizabeth Warren', 'Democratic', 'Elizabeth Warren (D) 53.7%\\nScott Brown (R) 46.3%', '2012', '[Data unknown/missing. You\xa0can\xa0help!]', '[Data unknown/missing. You\xa0can\xa0help!]'], ['New York', 'Kirsten Gillibrand', 'Democratic', 'Kirsten Gillibrand (D) 71.6%\\nWendy E. Long (R) 26.0%', '2010 (special)\\n2012', '[Data unknown/missing. You\xa0can\xa0help!]', '[Data unknown/missing. You\xa0can\xa0help!]'], ['State\\n(linked to\\nsummaries below)', 'Incumbent', 'Incumbent', 'Incumbent', 'Most recent election results', '2018 intent', 'Candidates'], ['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\xa0can\xa0help!]']] | Independent | Answer: | 128 | 12 | 1,023 |
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 did the team have their most total wins? | [['Season', 'Conference', 'Head Coach', 'Total Wins', 'Total Losses', 'Total Ties', 'Conference Wins', 'Conference Losses', 'Conference Ties', 'Conference Standing', 'Postseason Result'], ['1993', 'Southern', 'Charlie Taaffe', '5', '6', '0', '4', '4', '0', '4', '—'], ['1939', 'Southern', 'Tatum Gressette', '3', '8', '0', '0', '4', '0', '15', '—'], ['1988', 'Southern', 'Charlie Taaffe', '8', '4', '0', '5', '2', '0', '3', 'First Round'], ['1924', 'Southern Intercollegiate', 'Carl Prause', '6', '4', '0', '4', '2', '0', '—', '—'], ['1926', 'Southern Intercollegiate', 'Carl Prause', '7', '3', '0', '4', '3', '0', '—', '—'], ['1986', 'Southern', 'Tom Moore', '3', '8', '0', '0', '6', '0', '8', '—'], ['1923', 'Southern Intercollegiate', 'Carl Prause', '5', '3', '1', '2', '1', '1', '—', '—'], ['Totals:\\n105 Seasons', '2 Conferences', '23 Head Coaches', 'Total\\nWins\\n473', 'Total\\nLosses\\n536', 'Total\\nTies\\n32', '239 Conference Wins\\n55 SIAA\\n184 SoCon', '379 Conference Losses\\n58 SIAA\\n321 SoCon', '13 Conference Ties\\n8 SIAA\\n5 SoCon', 'Regular Season\\nChampions\\n2 times', '1–0 Bowl Record\\n1–3 Playoff Record'], ['1909', 'Southern Intercollegiate', 'Sam Costen', '4', '3', '2', '0', '1', '1', '—', '—'], ['1998', 'Southern', 'Don Powers', '5', '6', '0', '4', '4', '0', '4', '—'], ['1925', 'Southern Intercollegiate', 'Carl Prause', '6', '4', '0', '4', '2', '0', '—', '—'], ['1907', 'Independent', 'Ralph Foster', '1', '5', '1', '—', '—', '—', '—', '—'], ['1935', 'Southern Intercollegiate', 'Tatum Gressette', '4', '3', '1', '3', '1', '0', '—', '—'], ['2007', 'Southern', 'Kevin Higgins', '7', '4', '—', '4', '3', '—', 'T-3', '—'], ['1956', 'Southern', 'John Sauer', '3', '5', '1', '1', '3', '0', '8', '—'], ['2014', 'Southern', 'Mike Houston', 'Upcoming', 'Upcoming', 'Upcoming', 'Upcoming', 'Upcoming', 'Upcoming', 'Upcoming', 'Upcoming'], ['1934', 'Southern Intercollegiate', 'Tatum Gressette', '3', '5', '1', '2', '2', '0', '—', '—'], ['1920', 'Southern Intercollegiate', "Harvey O'Brien", '2', '6', '0', '1', '5', '0', '—', '—'], ['2001', 'Southern', 'Ellis Johnson', '3', '7', '0', '2', '6', '0', '7', '—'], ['1996', 'Southern', 'Don Powers', '4', '7', '0', '3', '5', '0', '5', '—'], ['1971', 'Southern', 'Red Parker', '8', '3', '0', '4', '2', '0', '3', '—'], ['1914', 'Southern Intercollegiate', 'George C. Rogers', '2', '5', '0', '0', '3', '0', '—', '—'], ['1970', 'Southern', 'Red Parker', '5', '6', '0', '4', '2', '0', '2', '—'], ['1949', 'Southern', 'J. Quinn Decker', '4', '5', '0', '2', '2', '0', '7', '—']] | 1992 | Answer: | 128 | 24 | 1,049 |
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's the total of deaths that happened in 1939/1940? | [['Description Losses', '1939/40', '1940/41', '1941/42', '1942/43', '1943/44', '1944/45', 'Total'], ['Deaths Outside of Prisons & Camps', '', '42,000', '71,000', '142,000', '218,000', '', '473,000'], ['Deaths In Prisons & Camps', '69,000', '210,000', '220,000', '266,000', '381,000', '', '1,146,000'], ['Murdered in Eastern Regions', '', '', '', '', '', '100,000', '100,000'], ['Direct War Losses', '360,000', '', '', '', '', '183,000', '543,000'], ['Total', '504,000', '352,000', '407,000', '541,000', '681,000', '270,000', '2,770,000'], ['Deaths other countries', '', '', '', '', '', '', '2,000'], ['Murdered', '75,000', '100,000', '116,000', '133,000', '82,000', '', '506,000']] | 504,000 | Answer: | 128 | 7 | 263 |
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 models covered in the table? | [['Year', 'Manufacturer', 'Model', 'Length (feet)', 'Quantity', 'Fleet Series', 'Fuel Propulsion', 'Powertrain'], ['2008', 'Van Hool', 'A300K', '30', '1', '5099', 'Diesel-electric hybrid', ''], ['2006', 'Van Hool', 'A300K', '30', '50', '5001-5050', 'Diesel', 'Cummins ISB\\nVoith D864.3E'], ['2008', 'Van Hool', 'A300L', '40', '27', '1201-1227', 'Diesel', 'Cummins ISL\\nVoith D864.5'], ['2013', 'New Flyer', 'Xcelsior D60', '60', '23', '2201-2223', 'Diesel', 'Cummins ISL 330 HP\\nAllison B400 6-speed'], ['2003', 'Van Hool', 'AG300', '60', '57', '2001-2057', 'Diesel', 'Cummins ISM\\nVoith D864.3E'], ['2003', 'Van Hool', 'A330', '40', '110', '1001-1110', 'Diesel', 'Cummins ISM\\nVoith D864.3E'], ['2000', 'MCI', 'D4500', '45', '30', '6001-6030', 'Diesel', ''], ['2013', 'Gillig', 'Low-floor Advantage', '40', '55', '6101-6155', 'Diesel', 'Cummins ISL 280 HP\\nAllison B400 6-speed'], ['1998', 'NABI', '416', '40', '133', '3001-3067, 3101-3166*', 'Diesel', 'Cummins M11E\\nAllison B400R'], ['2000', 'NABI', '40-LFW', '40', '23', '7201-7223', 'Diesel', 'Cummins ISM\\nAllison B400R'], ['1999', 'NABI', '40-LFW', '40', '44', '4001-4044', 'Diesel', ''], ['2003', 'NABI', '40-LFW', '40', '46', '4051-4090', 'Diesel', 'Cummins ISL\\nAllison B400R'], ['2013', 'Gillig', 'Low-floor Advantage', '40', '65', '1301-1365', 'Diesel', 'Cummins ISL 280 HP \\nAllison B400 6-speed'], ['2010', 'Van Hool', 'A300L FC', '40', '12', 'FC4-FC16', 'Hydrogen', ''], ['2007', 'Van Hool', 'AG300', '60', '15', '2151-2165', 'Diesel', 'Cummins ISM\\nVoith D864.3E'], ['2010', 'Van Hool', 'AG300', '60', '9', '2191-2199', 'Diesel', 'Cummins ISL\\nVoith D864.5'], ['2008', 'Van Hool', 'A300K', '30', '39', '5101-5139', 'Diesel', 'Cummins ISB\\nVoith D854.5'], ['1996', 'New Flyer', 'D60', '60 (articulated)', '30', '1901-1930*', 'Diesel', 'Detroit Diesel Series 50\\nAllison B400R'], ['2001', 'MCI', 'D4500', '45', '10', '6031-6040', 'Diesel', ''], ['2005', 'Van Hool', 'A300FC', '40', '3', 'FC1-FC3', 'Hydrogen', ''], ['2003', 'MCI', 'D4500', '45', '39', '6041-6079', 'Diesel', ''], ['2007', 'Van Hool', 'AG300', '60', '10', '2101-2110', 'Diesel', 'Cummins ISL\\nVoith D864.3E']] | 20 | Answer: | 128 | 22 | 954 |
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 wins by jaguar xjs? | [['Round', 'Date', 'Circuit', 'Winning driver (TA2)', 'Winning vehicle (TA2)', 'Winning driver (TA1)', 'Winning vehicle (TA1)'], ['7', 'August 19', 'Mosport', 'Greg Pickett', 'Chevrolet Corvette', 'Bob Tullius', 'Jaguar XJS'], ['6', 'August 13', 'Brainerd', 'Jerry Hansen', 'Chevrolet Monza', 'Bob Tullius', 'Jaguar XJS'], ['9', 'October 8', 'Laguna Seca', 'Greg Pickett', 'Chevrolet Corvette', 'Bob Tullius', 'Jaguar XJS'], ['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'], ['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'], ['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']] | 7 | Answer: | 128 | 10 | 426 |
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:other nations besides peru to earn 2 bronze medals | [['Rank', 'Nation', 'Gold', 'Silver', 'Bronze', 'Total'], ['1', 'Brazil', '7', '5', '3', '15'], ['9', 'Netherlands Antilles', '0', '0', '1', '1'], ['9', 'Panama', '0', '0', '1', '1'], ['3', 'Colombia', '2', '3', '4', '9'], ['9', 'Aruba', '0', '0', '1', '1'], ['Total', 'Total', '16', '16', '30', '62'], ['7', 'Ecuador', '0', '2', '2', '4'], ['6', 'Peru', '1', '1', '2', '4'], ['5', 'Argentina', '1', '2', '5', '8'], ['8', 'Guyana', '0', '1', '0', '1'], ['2', 'Venezuela', '3', '2', '8', '13'], ['9', 'Uruguay', '0', '0', '1', '1'], ['4', 'Chile', '2', '0', '2', '4']] | Chile, Ecuador | Answer: | 128 | 13 | 267 |
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 were consecutive games played against millwall? | [['Date', 'Opponents', 'Venue', 'Result', 'Scorers', 'Attendance'], ['11 Sep 1920', 'Plymouth Argyle', 'A', '1–5', 'Wolstenholme', '12,000'], ['28 Aug 1920', 'Reading', 'H', '0–1', '', '14,500'], ['2 Oct 1920', 'Exeter City', 'H', '2–0', 'Wolstenholme 2', '8,000'], ['18 Dec 1920', 'Brentford', 'A', '2–2', 'Wright, Thompson', '6,000'], ['6 Nov 1920', 'Gillingham', 'H', '1–0', 'Wolstenholme', '7,000'], ['9 Sep 1920', 'Bristol Rovers', 'H', '0–2', '', '8,000'], ['1 Sep 1920', 'Bristol Rovers', 'A', '2–3', 'Walker, Wolstenholme', '10,000'], ['7 May 1921', 'Southampton', 'H', '0–0', '', '8,000'], ['27 Dec 1920', 'Southend United', 'A', '1–2', 'Walker', '10,000'], ['26 Mar 1921', 'Queens Park Rangers', 'A', '0–2', '', '10,000'], ['9 Oct 1920', 'Millwall', 'H', '3–1', 'Devlin 2, Walker', '14,000'], ['23 Apr 1921', 'Luton Town', 'A', '2–2', 'Walker, Devlin', '9,000'], ['25 Mar 1921', 'Merthyr Town', 'H', '0–3', '', '12,600'], ['2 Apr 1921', 'Queens Park Rangers', 'H', '1–3', 'Devlin', '7,500'], ['22 Jan 1921', 'Norwich City', 'A', '0–3', '', '5,000'], ['19 Feb 1921', 'Crystal Palace', 'A', '0–2', '', '7,000'], ['13 Jan 1921', 'Norwich City', 'H', '2–0', 'Wright, Cox', '4,000'], ['16 Oct 1920', 'Millwall', 'A', '0–1', '', '20,000'], ['11 Dec 1920', 'Watford', 'A', '1–5', 'Wright', '7,000'], ['13 Nov 1920', 'Gillingham', 'A', '4–1', 'Dobson, Wolstenholme, Blott, Devlin', '8,000'], ['1 Jan 1921', 'Brentford', 'H', '3–1', 'Dobson, Walker, Cox', '7,500'], ['4 Sep 1920', 'Reading', 'A', '0–4', '', '10,000'], ['30 Oct 1920', 'Portsmouth', 'A', '2–0', 'Devlin, Dobson', '13,679'], ['29 Jan 1921', 'Northampton Town', 'H', '1–1', 'Dobson', '8,000'], ['12 Mar 1921', 'Grimsby Town', 'H', '2–1', 'Devlin, Kelson', '8,000'], ['19 Mar 1921', 'Grimsby Town', 'A', '1–1', 'Devlin', '9,000'], ['2 May 1921', 'Southampton', 'A', '0–0', '', '6,000'], ['30 Apr 1921', 'Luton Town', 'H', '2–0', 'Devlin 2', '5,000'], ['12 Feb 1921', 'Crystal Palace', 'H', '0–1', '', '12,000'], ['25 Dec 1920', 'Southend United', 'H', '1–1', 'Dobson', '9,000'], ['25 Sep 1920', 'Exeter City', 'A', '1–0', 'Wolstenholme', '8,000'], ['27 Nov 1920', 'Swindon Town', 'A', '0–5', '', '7,000'], ['4 Dec 1920', 'Watford', 'H', '0–2', '', '6,000'], ['28 Mar 1921', 'Merthyr Town', 'A', '2–1', 'Gaughan, Devlin', '6,000']] | 1 | Answer: | 128 | 34 | 1,026 |
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:besides angola racing team, what other team is listed in the 23rd position? | [['Season', 'Series', 'Team', 'Races', 'Wins', 'Poles', 'F/Laps', 'Podiums', 'Points', 'Position'], ['2008', 'Asian Formula Renault Challenge', 'Champ Motorsports', '13', '0', '0', '0', '3', '193', '4th'], ['2009', 'Asian Formula Renault Challenge', 'Asia Racing Team', '12', '6', '2', '4', '7', '287', '2nd'], ['2012', 'Formula 3 Euro Series', 'Angola Racing Team', '21', '0', '0', '0', '0', '14', '14th'], ['2009', 'Formula Renault 2.0 Northern European Cup', 'Krenek Motorsport', '14', '0', '0', '0', '0', '44', '21st'], ['2007', 'Asian Formula Renault Challenge', 'Champ Motorsports', '12', '0', '0', '0', '1', '64', '14th'], ['2010', 'Austria Formula 3 Cup', 'Sonangol Motopark', '4', '1', '2', '3', '2', '35', '9th'], ['2013', 'GP3 Series', 'Carlin', '16', '0', '0', '0', '0', '0', '23rd'], ['2010', 'ATS Formel 3 Cup', 'China Sonangol', '5', '0', '0', '0', '0', '0', '19th'], ['2012', 'British Formula 3 Championship', 'Angola Racing Team', '5', '0', '0', '0', '0', '—', '—'], ['2012', 'Masters of Formula 3', 'Angola Racing Team', '1', '0', '0', '0', '0', '—', '18th'], ['2012', '59th Macau Grand Prix Formula 3', 'Angola Racing Team', '2', '0', '0', '0', '0', '—', '23rd'], ['2011', 'Formula Pilota China', 'Asia Racing Team', '12', '2', '0', '0', '3', '124', '2nd']] | Carlin | Answer: | 128 | 12 | 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:how many countries had at least $1 billion in box office? | [['Rank', 'Country', 'Box Office', 'Year', 'Box office\\nfrom national films'], ['-', 'World', '$34.7 billion', '2012', '–'], ['3', 'Japan', '$1.88 billion', '2013', '61% (2013)'], ['5', 'France', '$1.7 billion', '2012', '33.3% (2013)'], ['1', 'Canada/United States', '$10.8 billion', '2012', '–'], ['4', 'United Kingdom', '$1.7 billion', '2012', '36.1% (2011)'], ['7', 'India', '$1.4 billion', '2012', '–'], ['9', 'Russia', '$1.2 billion', '2012', '–'], ['11', 'Italy', '$0.84 billion', '2013', '30% (2013)'], ['12', 'Brazil', '$0.72 billion', '2013', '17% (2013)'], ['2', 'China', '$3.6 billion', '2013', '59% (2013)'], ['6', 'South Korea', '$1.47 billion', '2013', '59.7% (2013)'], ['10', 'Australia', '$1.2 billion', '2012', '4.1% (2011)'], ['8', 'Germany', '$1.3 billion', '2012', '–']] | 10 | Answer: | 128 | 13 | 321 |
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 city has a radio station called the wolf? | [['Frequency', 'Call sign', 'Name', 'Format', 'Owner', 'Target city/market', 'City of license'], ['94.3 FM', 'KDAM', 'The Dam', 'Mainstream Rock', 'Riverfront Broadcasting LLC', 'Yankton/Vermillion', 'Hartington'], ['104.1 FM', 'WNAX-FM', 'The Wolf 104.1', 'Country', 'Saga Communications', 'Yankton/Vermillion', 'Yankton'], ['89.7 FM', 'KUSD', 'South Dakota Public Broadcasting', 'NPR', 'SD Board of Directors for Educational Telecommunications', 'Yankton/Vermillion', 'Vermillion'], ['93.1 FM', 'KKYA', 'KK93', 'Country', 'Riverfront Broadcasting LLC', 'Yankton/Vermillion', 'Yankton'], ['106.3 FM', 'KVHT', 'Classic Hits 106.3', 'Classic Hits', 'Cullhane Communications, Inc.', 'Yankton/Vermillion', 'Vermillion']] | Yankton | Answer: | 128 | 5 | 228 |
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 earliest date kodak made 16mm film? | [['Film', 'Film', 'Date'], ['Kodachrome 64', '110 format, daylight', '1974–1987'], ['Kodachrome-X film', '35\xa0mm (ASA 64)', '1962–1974'], ['Kodachrome II film', '35\xa0mm and 828, daylight (ASA 25/early) (ASA 64/late)', '1961–1974'], ['Kodachrome 64', '35\xa0mm, daylight', '1974–2009'], ['Kodachrome-X film', '126 format', '1963–1974'], ['Kodachrome II film', '16\xa0mm, daylight (ASA 25) and Type A (ASA 40)', '1961–1974'], ['Kodachrome 200', 'Professional film, 35\xa0mm, daylight', '1986–2004'], ['Kodachrome 40 film', 'Movie film, S-8, Type A', '1974–2005'], ['Kodachrome II film', 'S-8, Type A (ASA 40)', '1965–1974'], ['Kodachrome 40 film', 'Movie film, 8\xa0mm, Type A', '1974–1992'], ['Kodachrome-X film', '110 format', '1972–1974'], ['Kodachrome 25 film', 'Movie film, 8\xa0mm, daylight', '1974–1992'], ['Kodachrome II film', 'Professional, 35\xa0mm, Type A (ASA 40)', '1962–1978'], ['Kodachrome 64', 'Professional film, 35\xa0mm, daylight', '1983–2009'], ['Kodachrome Professional film', '35\xa0mm, Type A (ASA 16)', '1956–1962'], ['Kodachrome Professional film (sheets)', 'daylight (ASA 8) and Type B (ASA 10)', '1938–1951'], ['Kodachrome 40 film', 'Sound Movie film, S-8, Type A', '1974–1998'], ['Kodachrome 25 film', 'Movie film, 16\xa0mm, daylight', '1974–2002'], ['Kodachrome 25 film', 'Professional film, 35\xa0mm, daylight', '1983–1999'], ['Kodachrome film', '8\xa0mm, daylight (ASA 10) & Type A (ASA 16)', '1936–1962'], ['Kodak Color Print Material', 'Type D (slide duping film)', '1955–1957'], ['Cine-Chrome 40A', 'Double Regular 8\xa0mm, tungsten', '2003–2006'], ['Kodachrome 40 film', 'Movie film, 16\xa0mm, Type A', '1974–2006'], ['Kodachrome film', '35\xa0mm and 828, daylight & Type A', '1936–1962'], ['Kodachrome 40 film', '35\xa0mm, Type A', '1978–1997'], ['Kodachrome 64', 'Professional film, daylight, 120 format', '1986–1996'], ['Kodachrome 64', '126 format, daylight', '1974–1993'], ['Kodachrome film', '35\xa0mm and 828, Type F (ASA 12)', '1955–1962'], ['Kodachrome film', '16\xa0mm, daylight (ASA 10) & Type A (ASA 16)', '1935–1962'], ['Kodachrome 25 film', '35\xa0mm, daylight', '1974–2001'], ['Kodachrome 200', '35\xa0mm, daylight', '1988–2007'], ['Kodachrome II film', '8\xa0mm, daylight (ASA 25) and Type A (ASA 40)', '1961–1974']] | 1935 | Answer: | 128 | 32 | 891 |
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 win during the 2009 fujitsu v8 supercar season? | [['Rd.', 'Event', 'Circuit', 'Location', 'Date', 'Winner'], ['6', 'Supercheap Auto Bathurst 1000', 'Mount Panorama Circuit', 'Bathurst, New South Wales', '8-11 Oct', 'Jonathon Webb'], ['5', 'Queensland House & Land 300', 'Queensland Raceway', 'Ipswich, Queensland', '21-23 Aug', 'Jonathon Webb'], ['1', 'Clipsal 500', 'Adelaide Street Circuit', 'Adelaide, South Australia', '19-22 Mar', 'David Russell'], ['2', 'Winton', 'Winton Motor Raceway', 'Benalla, Victoria', '1-3 May', 'Jonathon Webb'], ['4', 'Norton 360 Sandown Challenge', 'Sandown Raceway', 'Melbourne, Victoria', '31 Jul-Aug 2', 'David Russell'], ['7', 'Sydney Telstra 500', 'Homebush Street Circuit', 'Sydney, New South Wales', '4-6 Dec', 'Jonathon Webb'], ['3', 'Dunlop Townsville 400', 'Townsville Street Circuit', 'Townsville, Queensland', '10-12 Jul', 'James Moffat']] | David Russell | Answer: | 128 | 7 | 268 |
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 competition was held in berlin and daegu? | [['Year', 'Competition', 'Venue', 'Position', 'Notes'], ['2008', 'Olympic Games', 'Beijing, China', '10th', '5.45 m'], ['2006', 'World Junior Championships', 'Beijing, China', '5th', '5.30 m'], ['2014', 'World Indoor Championships', 'Sopot, Poland', '3rd', '5.80 m'], ['2012', 'Olympic Games', 'London, United Kingdom', '8th', '5.65 m'], ['2013', 'European Indoor Championships', 'Gothenburg, Sweden', '5th', '5.71 m'], ['2012', 'European Championships', 'Helsinki, Finland', '6th', '5.60 m'], ['2009', 'World Championships', 'Berlin, Germany', '22nd (q)', '5.40 m'], ['2005', 'World Youth Championships', 'Marrakech, Morocco', '6th', '5.05 m'], ['2010', 'European Championships', 'Barcelona, Spain', '10th', '5.60 m'], ['2011', 'World Championships', 'Daegu, South Korea', '9th', '5.65 m'], ['2009', 'European U23 Championships', 'Kaunas, Lithuania', '8th', '5.15 m']] | World Championships | Answer: | 128 | 11 | 296 |
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:total number of cars sold in 2001? | [['Model', '1991', '1995', '1996', '1997', '1998', '1999', '2000', '2001', '2002', '2003', '2004', '2005', '2006', '2007', '2008', '2009', '2010', '2011', '2012', '2013'], ['Škoda Rapid', '−', '−', '−', '−', '−', '−', '−', '−', '−', '−', '−', '−', '−', '−', '−', '−', '−', '1,700', '9,292', '103,800'], ['Škoda Roomster', '−', '−', '−', '−', '−', '−', '−', '−', '−', '−', '−', '−', '14,422', '66,661', '57,467', '47,152', '32,332', '36,000', '39,249', '33,300'], ['Škoda Octavia', '−', '−', '', '47,876', '102,373', '143,251', '158,503', '164,134', '164,017', '165,635', '181,683', '233,322', '270,274', '309,951', '344,857', '317,335', '349,746', '387,200', '409,360', '359,600'], ['Total', '172,000', '210,000', '261,000', '336,334', '363,500', '385,330', '435,403', '460,252', '445,525', '449,758', '451,675', '492,111', '549,667', '630,032', '674,530', '684,226', '762,600', '879,200', '949,412', '920,800'], ['Škoda Citigo', '−', '−', '−', '−', '−', '−', '−', '−', '−', '−', '−', '−', '−', '−', '−', '−', '−', '509', '36,687', '45,200'], ['Škoda Superb', '−', '−', '−', '−', '−', '−', '−', '177', '16,867', '23,135', '22,392', '22,091', '20,989', '20,530', '25,645', '44,548', '98,873', '116,700', '106,847', '94,400'], ['Škoda Fabia', '−', '−', '−', '−', '−', '823', '128,872', '250,978', '264,641', '260,988', '247,600', '236,698', '243,982', '232,890', '246,561', '264,173', '229,045', '266,800', '255,025', '202,000'], ['Škoda Felicia', '172,000', '210,000', '', '288,458', '261,127', '241,256', '148,028', '44,963', '−', '−', '−', '−', '−', '−', '−', '−', '−', '−', '−', '−'], ['Škoda Yeti', '−', '−', '−', '−', '−', '−', '−', '−', '−', '−', '−', '−', '−', '−', '−', '11,018', '52,604', '70,300', '90,952', '82,400']] | 460,252 | Answer: | 128 | 9 | 853 |
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 type of plane was encountered the least? | [['Date', 'Location', 'Air/Ground', 'Number', 'Type', 'Status'], ['24 April 1944', 'South of Munich, Germany', 'Air', '3', 'Me-110', 'Destroyed'], ['27 May 1944', 'North of Strasbourg, France', 'Air', '1', 'Me-109', 'Damaged'], ['13 September 1944', 'South of Nordhausen, Germany', 'Air', '2.5', 'Me-109', 'Destroyed'], ['6 October 1944', '20 miles northwest of Berlin, Germany', 'Air', '1', 'Me-109', 'Damaged'], ['8 March 1944', 'Near Steinhuder Meer (Lake), Germany', 'Air', '1', 'Me-109', 'Destroyed'], ['14 January 1945', '20 miles northwest of Berlin, Germany', 'Air', '1', 'Me-109', 'Destroyed'], ['16 March 1944', '20 miles south of Stuttgart, Germany', 'Air', '1', 'Me-110', 'Destroyed'], ['27 November 1944', 'South of Magdeburg, Germany', 'Air', '4', 'FW-190', 'Destroyed'], ['11 April 1944', '20 miles northeast of Magdeburg, Germany', 'Air', '0.5', 'Me-109', 'Destroyed'], ['6 October 1944', '20 miles northwest of Berlin, Germany', 'Air', '2', 'Me-109', 'Destroyed'], ['13 April 1944', 'West of Mannheim, Germany', 'Air', '1', 'FW-190', 'Destroyed'], ['25 January 1952', 'Korea', 'Air', '1', 'Mig-15', 'Damaged'], ['18 August 1944', '20 miles northeast of Paris, France', 'Air', '0.5', 'Me-109', 'Destroyed']] | Mig-15 | Answer: | 128 | 13 | 414 |
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 top placing competitor? | [['Name', 'Sport', 'Event', 'Placing', 'Performance'], ["Ze'ev Friedman", 'Weightlifting', 'Bantamweight <56 kg', '12', 'J:102.5 C:102.5 S:125 T:330'], ['Zelig Stroch', 'Shooting', '50 metre rifle prone', '57', '589/600'], ['Henry Hershkowitz', 'Shooting', '50 metre rifle prone', '23', '593/600'], ['Dan Alon', 'Fencing', "Men's foil", 'Second round', 'W5–L5 (1R 3-2, 2R 2-3)'], ['Shlomit Nir', 'Swimming', "Women's 100 m breaststroke", 'Heats (8th)', '1:20.90'], ['Shaul Ladani', 'Athletics', "Men's 50 km walk", '19', '4:24:38.6\\n(also entered for 20 km walk, but did not start)'], ['Mark Slavin', 'Wrestling', 'Greco-Roman — Middleweight <82 kg', '—', '(taken hostage before his scheduled event)'], ['Esther Shahamorov', 'Athletics', "Women's 100 m", 'Semifinal (5th)', '11.49'], ['Henry Hershkowitz', 'Shooting', '50 metre rifle three positions', '46', '1114/1200'], ['Gad Tsobari', 'Wrestling', 'Freestyle — Light Flyweight <48 kg', 'Group stage', '0W–2L'], ['Yair Michaeli', 'Sailing', 'Flying Dutchman', '23', '28-22-22-19-25-19-DNS = 171 pts\\n(left Kiel before 7th race)'], ['Itzhak Nir', 'Sailing', 'Flying Dutchman', '23', '28-22-22-19-25-19-DNS = 171 pts\\n(left Kiel before 7th race)'], ['Shlomit Nir', 'Swimming', "Women's 200 m breaststroke", 'Heats (6th)', '2:53.60'], ['Esther Shahamorov', 'Athletics', "Women's 100 m hurdles", 'Semifinal', 'Did not start (left Munich before the semifinal)'], ['David Berger', 'Weightlifting', 'Light-heavyweight <82.5 kg', '—', 'J:132.5 C:122.5 S:— T:—'], ['Eliezer Halfin', 'Wrestling', 'Freestyle — Lightweight <68 kg', 'Group stage', '1W–2L'], ['Yossef Romano', 'Weightlifting', 'Middleweight <75 kg', '—', '(retired injured on third attempt to press 137.5kg)'], ['Yehuda Weissenstein', 'Fencing', "Men's foil", 'Second round', 'W2–L8 (1R 2-3, 2R 0-5)']] | Esther Shahamorov | Answer: | 128 | 18 | 674 |
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:is the price money for 23 january 1984 more than that of 23 april 1984? | [['Result', 'Date', 'Category', 'Tournament', 'Surface', 'Partnering', 'Opponents', 'Score'], ['Runner-up', '22 April 1984', '$250,000', 'Amelia Island, United States', 'Clay', 'Mima Jaušovec', 'Kathy Jordan\\n Anne Smith', '4–6, 6–3, 4–6'], ['Runner-up', '30 August 1987', '$150,000', 'Mahwah, United States', 'Hard', 'Liz Smylie', 'Gigi Fernández\\n Lori McNeil', '3–6, 2–6'], ['Runner-up', '9 September 1984', 'Grand Slam', 'US Open, United States', 'Hard', 'Wendy Turnbull', 'Martina Navrátilová\\n Pam Shriver', '2–6, 4–6'], ['Runner-up', '23 April 1984', '$200,000', 'Orlando, United States', 'Clay', 'Wendy Turnbull', 'Claudia Kohde-Kilsch\\n Hana Mandlíková', '0–6, 6–1, 3–6'], ['Winner', '13 June 1982', '$100,000', 'Birmingham, Great Britain', 'Grass', 'Jo Durie', 'Rosie Casals\\n Wendy Turnbull', '6–3, 6–2'], ['Runner-up', '8 November 1981', '$50,000', 'Hong Kong', 'Clay', 'Susan Leo', 'Ann Kiyomura\\n Sharon Walsh', '3–6, 4–6'], ['Winner', '21 August 1983', '$200,000', 'Toronto, Canada', 'Hard', 'Andrea Jaeger', 'Rosalyn Fairbank\\n Candy Reynolds', '6–4, 5–7, 7–5'], ['Winner', '27 November 1983', '$150,000', 'Sydney, Australia', 'Grass', 'Wendy Turnbull', 'Hana Mandlíková\\n Helena Suková', '6–4, 6–3'], ['Runner-up', '19 June 1983', '$150,000', 'Eastbourne, Great Britain', 'Grass', 'Jo Durie', 'Martina Navrátilová\\n Pam Shriver', '1–6, 0–6'], ['Runner-up', '20 May 1985', '$75,000', 'Melbourne, Australia', 'Carpet', 'Kathy Jordan', 'Pam Shriver\\n Liz Smylie', '2–6, 7–5, 1–6'], ['Winner', '23 January 1984', '$50,000', 'Denver, United States', 'Hard', 'Marcella Mesker', 'Sherry Acker\\n Candy Reynolds', '6–2, 6–3'], ['Winner', '23 May 1983', '$150,000', 'Berlin, Germany', 'Carpet', 'Jo Durie', 'Claudia Kohde-Kilsch\\n Eva Pfaff', '6–4, 7–6(7–2)'], ['Runner-up', '12 December 1983', 'Grand Slam', 'Australian Open, Australia', 'Grass', 'Wendy Turnbull', 'Martina Navrátilová\\n Pam Shriver', '4–6, 7–6, 2–6'], ['Runner-up', '29 January 1984', '$100,000', 'Marco Island, United States', 'Clay', 'Andrea Jaeger', 'Hana Mandlíková\\n Helena Suková', '6–3, 2–6, 2–6'], ['Runner-up', '10 December 1978', '$75,000', 'Sydney, Australia', 'Grass', 'Judy Chaloner', 'Kerry Reid\\n Wendy Turnbull', '2–6, 6–4, 2–6'], ['Winner', '20 May 1984', '$150,000', 'Berlin, Germany', 'Clay', 'Candy Reynolds', 'Kathy Horvath\\n Virginia Ruzici', '6–3, 4–6, 7–6(13–11)'], ['Runner-up', '16 April 1984', '$200,000', 'Hilton Head, United States', 'Clay', 'Sharon Walsh', 'Claudia Kohde-Kilsch\\n Hana Mandlíková', '5–7, 2–6'], ['Winner', '15 December 1985', '$50,000', 'Auckland, New Zealand', 'Grass', 'Candy Reynolds', 'Lea Antonoplis\\n Adriana Villagrán', '6–1, 6–3']] | no | Answer: | 128 | 18 | 1,044 |
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 race in 2011? | [['Season', 'Age', 'Overall', 'Slalom', 'Giant\\nSlalom', 'Super G', 'Downhill', 'Combined'], ['2010', '10 Mar 2010', 'Garmisch, Germany', 'Downhill', '', '', '', ''], ['2010', '23', '1', '–', '2', '6', '2', '2'], ['2010', '5 Dec 2009', 'Beaver Creek, USA', 'Downhill', '', '', '', ''], ['2008', '21', '64', '–', '28', '46', '46', '31'], ['2007', '20', '130', '–', '40', '–', '–', '—'], ['2014', '27', '18', '–', '25', '14', '20', '11'], ['2010', '16 Jan 2010', 'Wengen, Switzerland', 'Downhill', '', '', '', ''], ['2010', '6 Dec 2009', 'Beaver Creek, USA', 'Giant Slalom', '', '', '', ''], ['2011', '5 Mar 2011', 'Kranjska Gora, Slovenia', 'Giant Slalom', '', '', '', ''], ['2013', '26', '48', '–', '48', '27', '38', '4'], ['2009', '22', '7', '–', '6', '16', '16', '1'], ['2009', '13 Dec 2008', "Val d'Isère, France", 'Giant slalom', '', '', '', ''], ['2009', '16 Jan 2009', 'Wengen, Switzerland', 'Super Combined', '', '', '', ''], ['2010', '12 Mar 2010', 'Garmisch, Germany', 'Giant Slalom', '', '', '', ''], ['Season', 'Date', 'Location', 'Race', '', '', '', ''], ['2012', '25', '24', '–', '16', '28', '17', '19'], ['2010', '4 Dec 2009', 'Beaver Creek, USA', 'Super Combined', '', '', '', ''], ['2011', '24', '3', '–', '5', '6', '9', '6']] | Giant Slalom | Answer: | 128 | 18 | 505 |
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 position was listed the most on this chart? | [['Round', 'Pick', 'Name', 'Position', 'College'], ['7', '254', 'Michael Green', 'S', 'Northwestern State'], ['2', '39', 'Mike Brown', 'S', 'Nebraska'], ['3', '69', 'Dez White', 'WR', 'Georgia Tech'], ['6', '174', 'Paul Edinger', 'K', 'Michigan State'], ['4', '125', 'Reggie Austin', 'DB', 'Wake Forest'], ['1', '9', 'Brian Urlacher', 'S', 'New Mexico'], ['6', '170', 'Frank Murphy', 'WR', 'Kansas State'], ['3', '87', 'Dustin Lyman', 'TE', 'Wake Forest'], ['7', '223', 'James Cotton', 'DE', 'Ohio State']] | S | Answer: | 128 | 9 | 175 |
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:m. shafi ahmad and absdul majid both had what type of degree? | [['Number', 'Name', 'Term Started', 'Term Ended', 'Alma Mater', 'Field(s)', 'Educational Background'], ['7', 'Dr Abdul Majid', '1997', '2001', 'University of Wales', 'Astrophysics', 'Ph.D'], ['5', 'Dr M. Shafi Ahmad', '1989', '1990', 'University of London', 'Astronomy', 'Ph.D'], ['9', 'Major General Ahmed Bilal', '2010', 'Present', 'Pakistan Army Corps of Signals Engineering', 'Computer Engineering', 'Master of Science (M.S)'], ['3', 'Air Commodore K. M. Ahmad', '1979', '1980', 'Pakistan Air Force Academy', 'Flight Instructor', 'Certificated Flight Instructor (CFI)'], ['8', 'Major General Raza Hussain', '2001', '2010', 'Pakistan Army Corps of Electrical and Mechanical Engineers', 'Electrical Engineering', 'B.S.'], ['2', 'Air Commodore Dr Władysław Turowicz', '1967', '1979', 'Warsaw University of Technology', 'Aeronautical Engineering', 'Ph.D'], ['6', 'Engr.Sikandar Zaman', '1990', '1997', 'University of Leeds', 'Mechanical Engineering', 'Bachelor of Science (B.S.)'], ['4', 'Dr Salim Mehmud', '1980', '1989', 'Oak Ridge Institute for Science and Education and Oak Ridge National Laboratory', 'Nuclear Engineering, Electrical engineering, Physics, Mathematics, Electronics engineering', 'Ph.D'], ['1', 'Dr Abdus Salam', '1961', '1967', 'Imperial College', 'Theoretical Physics', 'Doctor of Philosophy (Ph.D)']] | Ph.D | Answer: | 128 | 9 | 380 |
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 photos total are listed? | [['Ship', 'Hull No.', 'Status', 'Years Active', 'NVR\\nPage'], ['Guadalupe', 'T-AO-200', 'Active', '1992–present', 'AO200'], ['Rappahannock', 'T-AO-204', 'Active', '1995–present', 'AO204'], ['John Ericsson', 'T-AO-194', 'Active', '1991–present', 'AO194'], ['Laramie', 'T-AO-203', 'Active', '1996–present', 'AO203'], ['Yukon', 'T-AO-202', 'Active', '1994–present', 'AO202'], ['Walter S. Diehl', 'T-AO-193', 'Active', '1988–present', 'AO193'], ['Joshua Humphreys', 'T-AO-188', 'Inactivated 1996, returned to service 2005', '1987-1996; 2005-2006; 2010-present', 'AO188'], ['Pecos', 'T-AO-197', 'Active', '1990–present', 'AO197'], ['John Lenthall', 'T-AO-189', 'Active', '1987-1996; 1998–present', 'AO189'], ['Patuxent', 'T-AO-201', 'Active', '1995–present', 'AO201'], ['Henry Eckford', 'T-AO-192', 'Cancelled when 84% complete,\\ntransferred to the Maritime Administration,\\nlaid up in the James River Reserve Fleet,\\nscrapped in 2011', 'Launched 1989, never in service', 'AO192'], ['Kanawha', 'T-AO-196', 'Active', '1991–present', 'AO196'], ['Tippecanoe', 'T-AO-199', 'Active', '1993–present', 'AO199'], ['Leroy Grumman', 'T-AO-195', 'Active', '1989–present', 'AO195'], ['Benjamin Isherwood', 'T-AO-191', 'Cancelled when 95.3% complete,\\ntransferred to the Maritime Administration,\\nlaid up in the James River Reserve Fleet,\\nscrapped in 2011', 'Launched 1988, christened 1991, never in service', 'AO191'], ['Henry J. Kaiser', 'T-AO-187', 'Active—Southern California Duty Oiler', '1986–present', 'AO187'], ['Andrew J. Higgins', 'T-AO-190', 'Inactivated May 1996. Sold to the Chilean Navy May 2009. Towed to Atlantic Marine Alabama shipyard, Mobile, Alabama, September 2009 for three-month refit. Commissioned in Chilean Navy on 10 February 2010 and renamed Almirante Montt.[1]', '1987-1996 (USA); 2010–present (Chile)', 'AO190'], ['Big Horn', 'T-AO-198', 'Active', '1992–present', 'AO198']] | 18 | Answer: | 128 | 18 | 686 |
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 was first listed as the position according to this chart? | [['Year', 'Competition', 'Venue', 'Position', 'Event', 'Notes'], ['2006', 'European Championships', 'Gothenburg, Sweden', '2nd', '400 m hurdles', '48.71'], ['2003', 'World Indoor Championships', 'Birmingham, United Kingdom', '3rd', '4x400 m relay', '3:06.61'], ['2004', 'Olympic Games', 'Athens, Greece', '10th (h)', '4x400 m relay', '3:03.69'], ['2003', 'European U23 Championships', 'Bydgoszcz, Poland', '1st', '4x400 m relay', '3:03.32'], ['2001', 'World Championships', 'Edmonton, Canada', '18th (sf)', '400 m hurdles', '49.80'], ['2003', 'World Indoor Championships', 'Birmingham, United Kingdom', '7th (sf)', '400 m', '46.82'], ['2003', 'European U23 Championships', 'Bydgoszcz, Poland', '1st', '400 m hurdles', '48.45'], ['2002', 'European Championships', 'Munich, Germany', '4th', '400 m', '45.40'], ['2002', 'European Indoor Championships', 'Vienna, Austria', '1st', '4x400 m relay', '3:05.50 (CR)'], ['2002', 'European Championships', 'Munich, Germany', '8th', '4x400 m relay', 'DQ'], ['2001', 'Universiade', 'Beijing, China', '8th', '400 m hurdles', '49.68'], ['2000', 'World Junior Championships', 'Santiago, Chile', '1st', '400 m hurdles', '49.23'], ['2002', 'European Indoor Championships', 'Vienna, Austria', '1st', '400 m', '45.39 (CR, NR)'], ['2004', 'Olympic Games', 'Athens, Greece', '6th', '400 m hurdles', '49.00'], ['2008', 'Olympic Games', 'Beijing, China', '7th', '4x400 m relay', '3:00.32'], ['2012', 'European Championships', 'Helsinki, Finland', '18th (sf)', '400 m hurdles', '50.77'], ['2007', 'World Championships', 'Osaka, Japan', '3rd', '4x400 m relay', '3:00.05'], ['2008', 'Olympic Games', 'Beijing, China', '6th', '400 m hurdles', '48.42'], ['1999', 'European Junior Championships', 'Riga, Latvia', '4th', '400 m hurdles', '52.17'], ['2007', 'World Championships', 'Osaka, Japan', '3rd', '400 m hurdles', '48.12 (NR)']] | 5 | Answer: | 128 | 20 | 650 |
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 the candidate before anastasija nindova? | [['Represent', 'Candidate', 'in Russian', 'Age', 'Height', 'Hometown'], ['Tver Oblast', 'Anastasija Prače’vysky', 'Анастасия Прачеьвыскы', '19', '1.75\xa0m (5\xa0ft 9\xa0in)', 'Tver'], ['Saratov Oblast', 'Anastasija Marnolova', 'Анастасия Марнолова', '21', '1.74\xa0m (5\xa0ft 8\xa01⁄2\xa0in)', 'Saratov'], ['Magadan Oblast', 'Ekaterina Filimonova', 'Екатерина Филимонова', '20', '1.83\xa0m (6\xa0ft 0\xa0in)', 'Magadan'], ['North Ossetian Republic', 'Emilianna Ninn', 'Емилианна Нинн', '22', '1.76\xa0m (5\xa0ft 9\xa01⁄2\xa0in)', 'Vladikavkaz'], ['Mordovian Republic', 'Olga Stepančenko', 'Олга Степанченко', '20', '1.75\xa0m (5\xa0ft 9\xa0in)', 'Saransk'], ['Tomsk Oblast', 'Anastasija Tristova', 'Анастасия Тристова', '23', '1.78\xa0m (5\xa0ft 10\xa0in)', 'Tomsk'], ['Altai Krai', 'Anastasija Nindova', 'Анастасия Ниндова', '22', '1.74\xa0m (5\xa0ft 8\xa01⁄2\xa0in)', 'Barnaul'], ['Chelyabinsk Oblast', 'Tatiana Abramenko', 'Татиана Абраменко', '21', '1.74\xa0m (5\xa0ft 8\xa01⁄2\xa0in)', 'Chelyabinsk'], ['Penza Oblast', 'Anna Milinzova', 'Анна Милинзова', '20', '1.86\xa0m (6\xa0ft 1\xa0in)', 'Penza'], ['Adygean Republic', 'Alissa Joanndova', 'Алисса Йоанндова', '19', '1.83\xa0m (6\xa0ft 0\xa0in)', 'Tulsky'], ['Sakhalin Oblast', 'Jeannette Menova', 'Йеаннетте Менова', '18', '1.75\xa0m (5\xa0ft 9\xa0in)', 'Sakhalin'], ['Saint Petersburg', 'Maria Hernasova', 'Мариа Хернасова', '20', '1.78\xa0m (5\xa0ft 10\xa0in)', 'Saint Petersburg'], ['Leningrad Oblast', 'Mercedes Laplsjfda', 'Мерцедес Лаплсйфда', '18', '1.79\xa0m (5\xa0ft 10\xa01⁄2\xa0in)', 'Leningrad'], ['Kurgan Oblast', 'Irina Mondroe', 'Ирина Мондрое', '25', '1.79\xa0m (5\xa0ft 10\xa01⁄2\xa0in)', 'Kurgan'], ['Oryol Oblast', 'Natalia Pavšukova', 'Наталиа Павшукова', '19', '1.79\xa0m (5\xa0ft 10\xa01⁄2\xa0in)', 'Oryol'], ['Khanty–Mansi Okrug', 'Alba Šaršakova', 'Алба Шаршакова', '18', '1.76\xa0m (5\xa0ft 9\xa01⁄2\xa0in)', 'Kogalym'], ['Ryazan Oblast', 'Julia Sandrova', 'Юлиа Сандрова', '20', '1.74\xa0m (5\xa0ft 8\xa01⁄2\xa0in)', 'Ryazan'], ['Samara Oblast', 'Nadia Gurina', 'Надиа Гурина', '20', '1.78\xa0m (5\xa0ft 10\xa0in)', 'Samara'], ['Irkutsk Oblast', 'Yulia Samoylova', 'Ыулиа Самоылова', '21', '1.77\xa0m (5\xa0ft 9\xa01⁄2\xa0in)', 'Irkutsk']] | Alissa Joanndova | Answer: | 128 | 19 | 1,031 |
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what date is next listed after june 14, 2010. | [['Season', 'Episodes', 'Season Premiere', 'Season Finale'], ['5', '40', 'October 12, 2009', 'June 14, 2010'], ['7', '8', 'October 29, 2013', 'December 17, 2013'], ['3', '44', 'October 15, 2007', 'June 2, 2008'], ['4', '48', 'October 13, 2008', 'May 11, 2009'], ['1', '20', 'March 4, 2006', 'May 13, 2006'], ['6', '20', 'September 6, 2010', 'December 6, 2010'], ['2', '52', 'October 7, 2006', 'July 16, 2007']] | December 6, 2010 | Answer: | 128 | 7 | 184 |
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 was a tournament held in the united states? | [['Outcome', 'No.', 'Date', 'Tournament', 'Surface', 'Partner', 'Opponents', 'Score'], ['Winner', '2.', '7 August 2011', 'Vancouver, Canada', 'Hard', 'Karolína Plíšková', 'Jamie Hampton\\n N. Lertcheewakarn', '5–7, 6–2, 6–4'], ['Winner', '1.', '13 February 2011', 'Rancho Mirage, United States', 'Hard', 'Karolína Plíšková', 'Nadejda Guskova\\n Sandra Zaniewska', '6–7(6–8), 6–1, 6–4'], ['Winner', '4.', '30 January 2012', 'Grenoble, France', 'Hard (i)', 'Karolína Plíšková', 'Valentyna Ivakhnenko\\n Maryna Zanevska', '6–1, 6–3'], ['Winner', '3.', '23 January 2012', 'Andrézieux-Bouthéon, France', 'Hard (i)', 'Karolína Plíšková', 'Julie Coin\\n Eva Hrdinová', '6–4, 4–6, [10–5]'], ['Runner-up', '1.', '16 May 2010', 'Kurume, Japan', 'Clay', 'Karolína Plíšková', 'Sun Shengnan\\n Xu Yifan', '0–6, 3–6'], ['Winner', '6.', '28 October 2013', 'Barnstaple, United Kingdom', 'Hard (i)', 'Naomi Broady', 'Raluca Olaru\\n Tamira Paszek', '6–3, 3–6, [10–5]'], ['Winner', '5.', '12 November 2012', 'Zawada, Poland', 'Carpet (i)', 'Karolína Plíšková', 'Kristina Barrois\\n Sandra Klemenschits', '6–3, 6–1'], ['Runner-up', '4.', '17 September 2012', 'Shrewsbury, United Kingdom', 'Hard (i)', 'Karolína Plíšková', 'Vesna Dolonc\\n Stefanie Vögele', '1–6, 7–6(7–3), [13–15]'], ['Runner-up', '2.', '6 November 2011', 'Taipei 5, Taiwan', 'Hard', 'Karolína Plíšková', 'Chan Yung-jan\\n Zheng Jie', '6–7(5–7), 7–5, 3–6'], ['Runner-up', '3.', '20 November 2011', 'Bratislava, Slovakia', 'Hard', 'Karolína Plíšková', 'Naomi Broady\\n Kristina Mladenovic', '7–5, 4–6, [2–10]']] | 1 | Answer: | 128 | 10 | 652 |
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many drivers have no laps led? | [['Pos', 'No.', 'Driver', 'Team', 'Laps', 'Time/Retired', 'Grid', 'Laps Led', 'Points'], ['3', '10', 'Dario Franchitti', 'Chip Ganassi Racing', '85', '+ 30.0551', '6', '0', '35'], ['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'], ['5', '27', 'Hideki Mutoh', 'Andretti Green Racing', '85', '+ 34.1839', '11', '0', '30'], ['10', '11', 'Tony Kanaan', 'Andretti Green Racing', '85', '+ 52.0810', '8', '0', '20'], ['1', '9', 'Scott Dixon', 'Chip Ganassi Racing', '85', '1:46:05.7985', '3', '51', '52'], ['19', '7', 'Danica Patrick', 'Andretti Green Racing', '83', '+ 2 Laps', '12', '0', '12'], ['6', '26', 'Marco Andretti', 'Andretti Green Racing', '85', '+ 46.7669', '13', '0', '28'], ['15', '13', 'E. J. Viso', 'HVM Racing', '84', '+ 1 Lap', '9', '0', '15'], ['7', '5', 'Paul Tracy', 'KV Racing Technology', '85', '+ 49.7020', '10', '0', '26'], ['18', '98', 'Richard Antinucci', 'Team 3G', '83', '+ 2 Laps', '19', '0', '12'], ['2', '6', 'Ryan Briscoe', 'Penske Racing', '85', '+ 29.7803', '1', '6', '41'], ['12', '3', 'Hélio Castroneves', 'Penske Racing', '85', '+ 53.2362', '5', '0', '18'], ['17', '20', 'Ed Carpenter', 'Vision Racing', '84', '+ 1 Lap', '21', '0', '13'], ['11', '06', 'Oriol Servià', 'Newman/Haas/Lanigan Racing', '85', '+ 52.6215', '14', '0', '19'], ['9', '2', 'Raphael Matos (R)', 'Luczo-Dragon Racing', '85', '+ 51.2286', '15', '0', '22'], ['16', '4', 'Dan Wheldon', 'Panther Racing', '84', '+ 1 Lap', '17', '0', '14'], ['14', '33', 'Robert Doornbos (R)', 'HVM Racing', '85', '+ 1:10.0812', '18', '0', '16'], ['8', '02', 'Graham Rahal', 'Newman/Haas/Lanigan Racing', '85', '+ 50.4517', '4', '0', '24'], ['20', '24', 'Mike Conway (R)', 'Dreyer & Reinbold Racing', '69', 'Mechanical', '16', '0', '12'], ['13', '18', 'Justin Wilson', 'Dale Coyne Racing', '85', '+ 53.5768', '2', '28', '17']] | 18 | Answer: | 128 | 21 | 823 |
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 superceded lord high steward? | [['Position', 'Officer', 'current officers', 'superseded by', 'Royal Household'], ['8', 'Earl Marshal', 'The Duke of Norfolk', '', 'Master of the Horse'], ['1', 'Lord High Steward', 'vacant', 'Justiciar', 'Lord Steward'], ['3', 'Lord High Treasurer', 'in commission', '', ''], ['5', 'Lord Privy Seal', 'The Rt Hon Andrew Lansley, CBE, MP', '', ''], ['7', 'Lord High Constable', 'vacant', 'Earl Marshal', 'Master of the Horse'], ['2', 'Lord High Chancellor', 'The Rt Hon Chris Grayling, MP', '', ''], ['9', 'Lord High Admiral', 'HRH The Duke of Edinburgh', '', ''], ['6', 'Lord Great Chamberlain', 'The Marquess of Cholmondeley', 'Lord High Treasurer', 'Lord Chamberlain'], ['4', 'Lord President of the Council', 'The Rt Hon Nick Clegg, MP', '', '']] | Justiciar | Answer: | 128 | 9 | 222 |
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 kristyna pliskova's partner in her first professional doubles tournament? | [['Outcome', 'No.', 'Date', 'Tournament', 'Surface', 'Partner', 'Opponents', 'Score'], ['Winner', '4.', '30 January 2012', 'Grenoble, France', 'Hard (i)', 'Karolína Plíšková', 'Valentyna Ivakhnenko\\n Maryna Zanevska', '6–1, 6–3'], ['Winner', '5.', '12 November 2012', 'Zawada, Poland', 'Carpet (i)', 'Karolína Plíšková', 'Kristina Barrois\\n Sandra Klemenschits', '6–3, 6–1'], ['Runner-up', '1.', '16 May 2010', 'Kurume, Japan', 'Clay', 'Karolína Plíšková', 'Sun Shengnan\\n Xu Yifan', '0–6, 3–6'], ['Winner', '2.', '7 August 2011', 'Vancouver, Canada', 'Hard', 'Karolína Plíšková', 'Jamie Hampton\\n N. Lertcheewakarn', '5–7, 6–2, 6–4'], ['Winner', '1.', '13 February 2011', 'Rancho Mirage, United States', 'Hard', 'Karolína Plíšková', 'Nadejda Guskova\\n Sandra Zaniewska', '6–7(6–8), 6–1, 6–4'], ['Winner', '3.', '23 January 2012', 'Andrézieux-Bouthéon, France', 'Hard (i)', 'Karolína Plíšková', 'Julie Coin\\n Eva Hrdinová', '6–4, 4–6, [10–5]'], ['Runner-up', '2.', '6 November 2011', 'Taipei 5, Taiwan', 'Hard', 'Karolína Plíšková', 'Chan Yung-jan\\n Zheng Jie', '6–7(5–7), 7–5, 3–6'], ['Winner', '6.', '28 October 2013', 'Barnstaple, United Kingdom', 'Hard (i)', 'Naomi Broady', 'Raluca Olaru\\n Tamira Paszek', '6–3, 3–6, [10–5]'], ['Runner-up', '3.', '20 November 2011', 'Bratislava, Slovakia', 'Hard', 'Karolína Plíšková', 'Naomi Broady\\n Kristina Mladenovic', '7–5, 4–6, [2–10]'], ['Runner-up', '4.', '17 September 2012', 'Shrewsbury, United Kingdom', 'Hard (i)', 'Karolína Plíšková', 'Vesna Dolonc\\n Stefanie Vögele', '1–6, 7–6(7–3), [13–15]']] | Karolína Plíšková | Answer: | 128 | 10 | 652 |
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 fullback positions were picked? | [['Pick #', 'NFL Team', 'Player', 'Position', 'College'], ['3', 'Baltimore Colts', 'Alan Ameche', 'Fullback', 'Wisconsin'], ['9', 'Philadelphia Eagles', 'Dick Bielski', 'Fullback', 'Maryland'], ['7', 'Los Angeles Rams', 'Larry Morris', 'Center', 'Georgia Tech'], ['12', 'Detroit Lions', 'Dave Middleton', 'Halfback', 'Auburn'], ['10', 'San Francisco 49ers', 'Dickey Moegle', 'Halfback', 'Rice'], ['4', 'Washington Redskins', 'Ralph Guglielmi', 'Quarterback', 'Notre Dame'], ['2', 'Chicago Cardinals', 'Max Boydston', 'End', 'Oklahoma'], ['6', 'Pittsburgh Steelers', 'Frank Varrichione', 'Tackle', 'Notre Dame'], ['8', 'New York Giants', 'Joe Heap', 'Halfback', 'Notre Dame'], ['13', 'Cleveland Browns', 'Kurt Burris', 'Center', 'Oklahoma'], ['5', 'Green Bay Packers', 'Tom Bettis', 'Guard', 'Purdue'], ['11', 'Chicago Bears', 'Ron Drzewiecki', 'Halfback', 'Marquette'], ['1', 'Baltimore Colts (Lottery bonus pick)', 'George Shaw', 'Quarterback', 'Oregon']] | 2 | Answer: | 128 | 13 | 304 |
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 toy sales? | [['Year', 'Injuries (US $000)', 'Deaths (age <15)', 'CPSC toy safety funding\\n(US$ Millions)', 'Toy sales\\n(US $ Billions)'], ['2007', 'no data', '22', 'no data', ''], ['2002', '212', '13', '12.2', '21.3'], ['2005', '202 (estimate)', '20', '11.0', '22.2'], ['2009', 'no data', '12', 'no data', ''], ['2006', 'no data', '22', 'no data†', '22.3'], ['2000', '191', '17', '12.0', ''], ['1998', '153', '14', '', ''], ['1996', '130', '', '', ''], ['1994', '154', '', '', ''], ['2008', 'no data', '19', 'no data', ''], ['1997', '141', '', '', ''], ['2004', '210', '16', '11.5', '22.4'], ['1999', '152', '16', '13.6', ''], ['1995', '139', '', '', ''], ['2003', '206', '11', '12.8', '20.7'], ['2001', '255', '25', '12.4', '']] | 2003 | Answer: | 128 | 16 | 305 |
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 affiliates does tv azteca have all together? | [['Network name', 'Flagship', 'Programming type', 'Owner', 'Affiliates'], ['Galavisión', 'XEQ 9', 'retro programming and sports', 'Televisa', '1'], ['Independent', '', 'varies', 'Independent', '3'], ['Azteca 13', 'XHDF 13', 'news, soap operas, and sports', 'TV Azteca', '4'], ['TV 10 Chiapas', 'XHTTG', 'educational', 'Gobierno del Estado de Chiapas', '7'], ['Canal de las Estrellas', 'XEW 2', 'soap operas, retro movies and sports', 'Televisa', '10'], ['Canal 5', 'XHGC 5', 'cartoons, movies, and series', 'Televisa', '4'], ['Azteca 7', 'XHIMT 7', 'sports, series, and movies', 'TV Azteca', '5']] | 9 | Answer: | 128 | 7 | 209 |
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 number of times that the team placed 5th? | [['Year', 'Division', 'League', 'Reg. Season', 'Playoffs'], ['2013', '1', 'USL W-League', '4th, Western', 'Did not qualify'], ['2005', '1', 'USL W-League', '6th, Western', ''], ['2006', '1', 'USL W-League', '5th, Western', ''], ['2004', '1', 'USL W-League', '8th, Western', ''], ['2010', '1', 'USL W-League', '6th, Western', 'Did not qualify'], ['2008', '1', 'USL W-League', '6th, Western', 'Did not qualify'], ['2009', '1', 'USL W-League', '7th, Western', 'Did not qualify'], ['2003', '2', 'USL W-League', '5th, Western', ''], ['2007', '1', 'USL W-League', '5th, Western', ''], ['2011', '1', 'USL W-League', '7th, Western', 'Did not qualify'], ['2012', '1', 'USL W-League', '4th, Western', 'Did not qualify']] | 3 | Answer: | 128 | 11 | 267 |
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 did the team score at least 30 points? | [['Week', 'Date', 'Opponent', 'Score', 'Result', 'Record'], ['7', 'Oct 9', 'vs. Montreal Alouettes', '25–11', 'Loss', '1–7'], ['9', 'Oct 23', 'at Hamilton Tiger-Cats', '25–17', 'Loss', '1–10'], ['2', 'Sept 4', 'at Montreal Alouettes', '21–2', 'Loss', '0–2'], ['7', 'Oct 11', 'at Montreal Alouettes', '24–6', 'Loss', '1–8'], ['4', 'Sept 18', 'vs. Toronto Argonauts', '34–6', 'Loss', '1–4'], ['1', 'Aug 28', 'at Toronto Argonauts', '13–6', 'Loss', '0–1'], ['5', 'Sept 25', 'vs. Hamilton Tiger-Cats', '38–12', 'Loss', '1–5'], ['8', 'Oct 16', 'vs. Toronto Argonauts', '27–11', 'Loss', '1–9'], ['10', 'Oct 30', 'vs. Hamilton Tiger-Cats', '30–9', 'Loss', '1–11'], ['6', 'Oct 2', 'at Hamilton Tiger-Cats', '45–0', 'Loss', '1–6'], ['12', 'Nov 13', 'vs. Montreal Alouettes', '14–12', 'Win', '2–12'], ['11', 'Nov 6', 'at Toronto Argonauts', '18–12', 'Loss', '1–12'], ['2', 'Sept 6', 'vs. Montreal Alouettes', '20–11', 'Loss', '0–3'], ['3', 'Sept 11', 'at Toronto Argonauts', '12–5', 'Win', '1–3']] | 4 | Answer: | 128 | 14 | 418 |
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 he race more laps in 1926 or 1938? | [['Year', 'Car', 'Start', 'Qual', 'Rank', 'Finish', 'Laps', 'Led', 'Retired'], ['1929', '23', '11', '112.146', '15', '17', '91', '0', 'Supercharger'], ['1935', '44', '6', '115.459', '11', '21', '102', '0', 'Magneto'], ['1934', '8', '7', '113.733', '13', '17', '94', '0', 'Rod'], ['1933', '34', '12', '113.578', '15', '7', '200', '0', 'Running'], ['Totals', 'Totals', 'Totals', 'Totals', 'Totals', 'Totals', '1989', '33', ''], ['1926', '31', '12', '102.789', '13', '11', '142', '0', 'Flagged'], ['1932', '25', '20', '108.896', '34', '13', '184', '0', 'Flagged'], ['1939', '62', '27', '121.749', '24', '11', '200', '0', 'Running'], ['1931', '37', '19', '111.725', '6', '18', '167', '0', 'Crash T4'], ['1927', '27', '27', '107.765', '22', '3', '200', '0', 'Running'], ['1930', '9', '20', '100.033', '18', '20', '79', '0', 'Valve'], ['1928', '8', '4', '117.031', '4', '10', '200', '33', 'Running'], ['1937', '38', '7', '118.788', '16', '8', '200', '0', 'Running'], ['1938', '17', '4', '122.499', '6', '17', '130', '0', 'Rod']] | 1926 | Answer: | 128 | 14 | 460 |
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's the total attendance for gamestorm 11? | [['Iteration', 'Dates', 'Location', 'Attendance', 'Notes'], ['GameStorm 15', 'March 21–24, 2013', 'Hilton - Vancouver, WA', '1188', ''], ['GameStorm 16', 'March 20–23, 2014', 'Hilton - Vancouver, WA', 'tba', 'Guests: Mike Selinker, Shane Lacy Hensley, Lisa Steenson, Zev Shlasinger of Z-Man Games'], ['GameStorm 10', 'March 2008', 'Red Lion - Vancouver, WA', '750', '-'], ['GameStorm 13', 'March 24–27, 2011', 'Hilton - Vancouver, WA', '984', 'Guests: Lisa Steenson, Michael A. Stackpole'], ['GameStorm 14', 'March 22–25, 2012', 'Hilton - Vancouver, WA', '1072', 'Boardgame:Andrew Hackard and Sam Mitschke of Steve Jackson Games - RPG: Jason Bulmahn'], ['GameStorm 11', 'March 26–29, 2009', 'Hilton - Vancouver, WA', '736', 'debut of Video games, first-ever Artist Guest of Honor, Rob Alexander'], ['GameStorm 12', 'March 25–28, 2010', 'Hilton - Vancouver, WA', '802', 'Board games Guest of Honor: Tom Lehmann']] | 736 | Answer: | 128 | 7 | 309 |
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:who is the next driver listed after scott dixon? | [['Pos', 'No.', 'Driver', 'Team', 'Engine', 'Laps', 'Time/Retired', 'Grid', 'Laps Led', 'Points'], ['18', '28', 'Ryan Hunter-Reay', 'Andretti Autosport', 'Chevrolet', '84', '+ 1 lap', '7', '1', '12'], ['4', '8', 'Rubens Barrichello', 'KV Racing Technology', 'Chevrolet', '85', '+ 8.8529', '11', '0', '32'], ['1', '2', 'Ryan Briscoe', 'Team Penske', 'Chevrolet', '85', '2:07:02.8248', '2', '27', '50'], ['27', '15', 'Takuma Sato', 'Rahal Letterman Lanigan Racing', 'Honda', '2', 'Mechanical', '26', '0', '10'], ['16', '5', 'E.J. Viso', 'KV Racing Technology', 'Chevrolet', '84', '+ 1 lap', '17', '0', '14'], ['23', '67', 'Josef Newgarden (R)', 'Sarah Fisher Hartman Racing', 'Honda', '62', 'Contact', '22', '0', '12'], ['10', '11', 'Tony Kanaan', 'KV Racing Technology', 'Chevrolet', '84', '+ 1 lap', '16', '0', '20'], ['5', '38', 'Graham Rahal', 'Chip Ganassi Racing', 'Honda', '85', '+ 9.4667', '13', '0', '30'], ['13', '9', 'Scott Dixon', 'Chip Ganassi Racing', 'Honda', '84', '+ 1 lap', '5', '0', '17'], ['2', '12', 'Will Power', 'Team Penske', 'Chevrolet', '85', '+ 0.4408', '1', '57', '43'], ['20', '20', 'Ed Carpenter', 'Ed Carpenter Racing', 'Chevrolet', '84', '+ 1 lap', '25', '0', '12'], ['24', '6', 'Katherine Legge (R)', 'Dragon Racing', 'Chevrolet', '48', 'Mechanical', '19', '0', '12'], ['14', '14', 'Mike Conway', 'A.J. Foyt Enterprises', 'Honda', '84', '+ 1 lap', '14', '0', '16'], ['6', '3', 'Hélio Castroneves', 'Team Penske', 'Chevrolet', '85', '+ 11.2575', '4', '0', '28'], ['12', '19', 'James Jakes', 'Dale Coyne Racing', 'Honda', '84', '+ 1 lap', '24', '0', '18'], ['9', '98', 'Alex Tagliani', 'Team Barracuda – BHA', 'Honda', '85', '+ 39.6868', '8', '0', '22'], ['26', '27', 'James Hinchcliffe', 'Andretti Autosport', 'Chevrolet', '35', 'Mechanical', '10', '0', '10'], ['25', '26', 'Marco Andretti', 'Andretti Autosport', 'Chevrolet', '46', 'Mechanical', '12', '0', '10'], ['11', '18', 'Justin Wilson', 'Dale Coyne Racing', 'Honda', '84', '+ 1 lap', '20', '0', '19'], ['3', '10', 'Dario Franchitti', 'Chip Ganassi Racing', 'Honda', '85', '+ 1.0497', '6', '0', '35'], ['15', '17', 'Sebastián Saavedra', 'Andretti Autosport', 'Chevrolet', '84', '+ 1 lap', '23', '0', '15'], ['22', '7', 'Sebastien Bourdais', 'Dragon Racing', 'Chevrolet', '63', 'Contact', '3', '0', '12'], ['19', '22', 'Oriol Servià', 'Panther/Dreyer & Reinbold Racing', 'Chevrolet', '84', '+ 1 lap', '18', '0', '12'], ['21', '83', 'Charlie Kimball', 'Chip Ganassi Racing', 'Honda', '82', '+ 3 laps', '21', '0', '12'], ['7', '77', 'Simon Pagenaud (R)', 'Schmidt Hamilton Motorsports', 'Honda', '85', '+ 12.3087', '9', '0', '26']] | Mike Conway | Answer: | 128 | 25 | 1,031 |
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 venue did melissa morrison compete at in 2004? | [['Year', 'Competition', 'Venue', 'Position', 'Event'], ['2003', 'World Athletics Final', 'Monaco', '6th', '100 m hurdles'], ['1997', 'World Indoor Championships', 'Paris, France', '5th', '60 m hurdles'], ['2000', 'Olympic Games', 'Sydney, Australia', '3rd', '100 m hurdles'], ['2002', 'Grand Prix Final', 'Paris, France', '7th', '100 m hurdles'], ['2004', 'Olympic Games', 'Athens, Greece', '3rd', '100 m hurdles'], ['2002', 'USA Indoor Championships', '', '1st', '60 m hurdles'], ['1999', 'World Indoor Championships', 'Maebashi, Japan', '6th', '60 m hurdles'], ['1998', 'Grand Prix Final', 'Moscow, Russia', '2nd', '100 m hurdles'], ['2000', 'Grand Prix Final', 'Doha, Qatar', '4th', '100 m hurdles'], ['2003', 'World Indoor Championships', 'Birmingham, England', '3rd', '60 m hurdles'], ['1998', 'USA Indoor Championships', '', '1st', '60 m hurdles'], ['1997', 'USA Outdoor Championships', 'Indianapolis, United States', '1st', '100 m hurdles']] | Athens, Greece | Answer: | 128 | 12 | 294 |
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 is professional writer listed as the profession according to this chart? | [['Year', 'Recipient', 'Nationality', 'Profession', 'Speech'], ['1999', 'A.M. Rosenthal', 'United States', 'Former New York Times editor\\nFormer New York Daily News columnist', ''], ['2003', 'Ruth Roskies Wisse', 'United States', 'Yiddish professor of Harvard University', '[2]'], ['1997', 'Elie Wiesel', 'United States', 'Professional writer\\nWinner of the Nobel Peace Prize (1986)', ''], ['2008', "David Be'eri, Mordechai Eliav, Rabbi Yehuda Maly", 'Israel', '', ''], ['2007', 'Norman Podhoretz', 'United States', 'Author, columnist', ''], ['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', ''], ['2009', 'Caroline Glick', 'Israel', 'Journalist', ''], ['2002', 'Charles Krauthammer', 'United States', 'The Washington Post columnist', '[1]'], ['1998', 'Herman Wouk', 'United States', 'Professional writer and 1952 Pulitzer Prize winner', ''], ['2001', 'Cynthia Ozick', 'United States', 'Professional writer', ''], ['2006', 'Daniel Pipes', 'United States', 'Author and historian', ''], ['2000', 'Sir Martin Gilbert', 'United Kingdom', 'Historian and writer', ''], ['2005', 'William Safire', 'United States', 'Author, journalist and speechwriter\\n1978 Pulitzer Prize winner', '']] | 3 | Answer: | 128 | 14 | 377 |
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 listings from barrington, farmington, and rochester combined? | [['', 'Name on the Register', 'Date listed', 'Location', 'City or town', 'Summary'], ['19', 'Plummer Homestead', 'June 14, 2002\\n(#02000638)', '1273 White Mountain Highway\\n43°27′35″N 70°59′33″W\ufeff / \ufeff43.459722°N 70.9925°W', 'Milton', ''], ['35', 'US Post Office-Dover Main', 'July 17, 1986\\n(#86002273)', '133-137 Washington St.\\n43°11′42″N 70°52′39″W\ufeff / \ufeff43.195°N 70.8775°W', 'Dover', ''], ['37', 'Wiswall Falls Mills Site', 'March 18, 1988\\n(#88000184)', 'John Hatch Park\\nSouth of Wiswall Road just east of the Lamprey River\\n43°06′15″N 70°57′44″W\ufeff / \ufeff43.1043°N 70.9621°W', 'Durham', ''], ['40', 'Samuel Wyatt House', 'December 2, 1982\\n(#82000626)', '7 Church St.\\n43°11′30″N 70°52′31″W\ufeff / \ufeff43.191667°N 70.875278°W', 'Dover', ''], ['17', 'New Durham Town Hall', 'November 13, 1980\\n(#80000313)', 'Main St. and Ridge Rd.\\n43°26′02″N 71°09′55″W\ufeff / \ufeff43.433889°N 71.165278°W', 'New Durham', ''], ['10', 'Green Street School', 'March 7, 1985\\n(#85000481)', '104 Green St.\\n43°15′23″N 70°51′50″W\ufeff / \ufeff43.256389°N 70.863889°W', 'Somersworth', ''], ['9', 'Garrison Hill Park and Tower', 'September 11, 1987\\n(#87001413)', 'Abbie Sawyer Memorial Dr.\\n43°12′34″N 70°52′13″W\ufeff / \ufeff43.209444°N 70.870278°W', 'Dover', ''], ['16', 'New Durham Meetinghouse and Pound', 'December 8, 1980\\n(#80000312)', 'Old Bay Rd.\\n43°25′25″N 71°07′42″W\ufeff / \ufeff43.423611°N 71.128333°W', 'New Durham', ''], ['24', 'Rochester Commercial and Industrial District', 'April 8, 1983\\n(#83001154)', 'N. Main, Wakefield, Hanson, and S. Main Sts. and Central Square\\n43°18′11″N 70°58′34″W\ufeff / \ufeff43.303056°N 70.976111°W', 'Rochester', ''], ['15', 'Milton Town House', 'November 26, 1980\\n(#80000311)', 'NH 125 and Town House Rd.\\n43°26′27″N 70°59′05″W\ufeff / \ufeff43.440833°N 70.984722°W', 'Milton', ''], ['29', 'Sawyer Woolen Mills', 'September 13, 1989\\n(#89001208)', '1 Mill St.\\n43°10′44″N 70°52′35″W\ufeff / \ufeff43.178889°N 70.876389°W', 'Dover', ''], ['32', 'Strafford Union Academy', 'September 22, 1983\\n(#83001155)', 'NH 126 and NH 202A\\n43°16′07″N 71°07′23″W\ufeff / \ufeff43.268611°N 71.123056°W', 'Strafford', ''], ['12', 'Richard Hayes House', 'February 27, 1986\\n(#86000283)', '184 Gonic Rd.\\n43°15′38″N 70°58′44″W\ufeff / \ufeff43.260556°N 70.978889°W', 'Rochester', '']] | 5 | Answer: | 128 | 13 | 1,005 |
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many teams did not score any goals in the 2006 season? | [['Season', 'Team', 'Country', 'Division', 'Apps', 'Goals'], ['2013/14', 'Lokomotiv Moscow', 'Russia', '1', '14', '1'], ['2009/10', 'Dnipro Dnipropetrovsk', 'Ukraine', '1', '28', '0'], ['2005', 'CSKA Moscow', 'Russia', '1', '0', '0'], ['2010/11', 'Dnipro Dnipropetrovsk', 'Ukraine', '1', '23', '0'], ['2008/09', 'Dnipro Dnipropetrovsk', 'Ukraine', '1', '22', '1'], ['2012/13', 'Lokomotiv Moscow', 'Russia', '1', '8', '0'], ['2006/07', 'Dnipro Dnipropetrovsk', 'Ukraine', '1', '12', '0'], ['2012/13', 'Dnipro Dnipropetrovsk', 'Ukraine', '1', '10', '1'], ['2006', 'Spartak Nizhny Novgorod', 'Russia', '2', '36', '1'], ['2004', 'CSKA Moscow', 'Russia', '1', '0', '0'], ['2011/12', 'Dnipro Dnipropetrovsk', 'Ukraine', '1', '16', '0'], ['2007/08', 'Dnipro Dnipropetrovsk', 'Ukraine', '1', '24', '0']] | 1 | Answer: | 128 | 12 | 350 |
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 came in first? | [['Pos', 'Rider', 'Manufactuer', 'Time/Retired', 'Points'], ['8', 'Jean-Philippe Ruggia', 'Aprilia', '+3.985', '8'], ['Ret', 'Jean-Pierre Jeandat', 'Aprilia', 'Retirement', ''], ['Ret', 'Wilco Zeelenberg', 'Aprilia', 'Retirement', ''], ['Ret', 'Andreas Preining', 'Aprilia', 'Retirement', ''], ['13', 'Jochen Schmid', 'Yamaha', '+47.065', '3'], ['Ret', 'Eskil Suter', 'Aprilia', 'Retirement', ''], ['4', 'Max Biaggi', 'Honda', '+2.346', '13'], ['18', 'Bernd Kassner', 'Aprilia', '+1:16:464', ''], ['21', 'Adrian Bosshard', 'Honda', '+1:47.492', ''], ['17', 'Adi Stadler', 'Honda', '+1:16.349', ''], ['2', 'Loris Capirossi', 'Honda', '+0.090', '20'], ['14', 'Jean-Michel Bayle', 'Aprilia', '+1:15.546', '2'], ['7', 'Pierfrancesco Chili', 'Yamaha', '+3.845', '9'], ['11', 'Alberto Puig', 'Honda', '+25.136', '5'], ['9', 'Carlos Cardús', 'Honda', '+4.893', '7'], ['DNS', 'Nobuatsu Aoki', 'Honda', 'Did not start', ''], ['23', 'Bernard Haenggeli', 'Aprilia', '+2:41.806', ''], ['3', 'Helmut Bradl', 'Honda', '+0.384', '16'], ['1', 'Doriano Romboni', 'Honda', '33:53.776', '25'], ['22', 'Massimo Pennacchioli', 'Honda', '+1:59.498', ''], ['Ret', 'Luis Maurel', 'Aprilia', 'Retirement', ''], ['Ret', 'Patrick van den Goorbergh', 'Aprilia', 'Retirement', ''], ['5', 'Loris Reggiani', 'Aprilia', '+2.411', '11'], ['12', 'John Kocinski', 'Suzuki', '+25.463', '4'], ['6', 'Tetsuya Harada', 'Yamaha', '+2.537', '10'], ['24', 'Alessandro Gramigni', 'Gilera', '+1 Lap', ''], ['19', 'Paolo Casoli', 'Gilera', '+1:26.061', ''], ['10', "Luis d'Antin", 'Honda', '+25.044', '6'], ['20', 'Gabriele Debbia', 'Honda', '+1:40.049', ''], ['Ret', 'Volker Bähr', 'Honda', 'Retirement', ''], ['Ret', 'Jurgen van den Goorbergh', 'Aprilia', 'Retirement', ''], ['15', 'Juan Borja', 'Honda', '+1:15.769', '1'], ['16', 'Frédéric Protat', 'Aprilia', '+1:15.858', '']] | Doriano Romboni | Answer: | 128 | 33 | 731 |
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 team listed after widnes vikings? | [['Team', 'Stadium', 'Capacity', 'City/Area'], ['Hull Kingston Rovers (2014 season)', 'MS3 Craven Park', '9,471', 'Kingston upon Hull, East Riding of Yorkshire'], ['Widnes Vikings (2014 season)', 'The Select Security Stadium', '13,500', 'Widnes, Cheshire, England'], ['Wakefield Trinity Wildcats (2014 season)', 'Rapid Solicitors Stadium', '11,000', 'Wakefield, West Yorkshire'], ['Hull (2014 season)', 'Kingston Communications Stadium', '25,404', 'Kingston upon Hull, East Riding of Yorkshire'], ['Castleford Tigers (2014 season)', 'The Wish Communications Stadium', '11,750', 'Castleford, West Yorkshire'], ['Leeds Rhinos (2014 season)', 'Headingley Carnegie Stadium', '22,250', 'Leeds, West Yorkshire'], ['Salford City Reds (2014 season)', 'Salford City Stadium', '12,000', 'Salford, Greater Manchester'], ['Catalans Dragons (2014 season)', 'Stade Gilbert Brutus', '14,000', 'Perpignan, Pyrénées-Orientales, France'], ['Huddersfield Giants (2014 season)', "John Smith's Stadium", '24,544', 'Huddersfield, West Yorkshire'], ['London Broncos (2014 season)', 'Twickenham Stoop', '12,700', 'Twickenham, London'], ['Warrington Wolves (2014 season)', 'Halliwell Jones Stadium', '15,500', 'Warrington, Cheshire'], ['Wigan Warriors (2014 season)', 'DW Stadium', '25,138', 'Wigan, Greater Manchester'], ['Bradford Bulls (2014 season)', 'Provident Stadium', '27,000', 'Bradford, West Yorkshire'], ['St Helens RLFC (2014 season)', 'Langtree Park', '18,000', 'St Helens, Merseyside']] | Wigan Warriors | Answer: | 128 | 14 | 432 |
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 festivals was the film shown at? | [['Date', 'Festival', 'Location', 'Awards', 'Link'], ['Oct 9, Oct 11', 'Sitges Film Festival', 'Sitges, Catalonia\\n\xa0Spain', '', 'Sitges Festival'], ['Oct 9', 'London Int. Festival of Science Fiction Film', 'London, England\\n\xa0UK', 'Closing Night Film', 'Sci-Fi London'], ['Sep 19', 'Lund International Fantastic Film Festival', 'Lund, Skåne\\n\xa0Sweden', '', 'fff.se'], ['Sep 28', 'Fantastic Fest', 'Austin, Texas\\n\xa0USA', '', 'FantasticFest.com'], ['Sep 16', 'Athens International Film Festival', 'Athens, Attica\\n\xa0Greece', 'Best Director', 'aiff.gr'], ['Oct 23', 'Toronto After Dark', 'Toronto, Ontario\\n\xa0Canada', 'Best Special Effects\\nBest Musical Score', 'torontoafterdark.com'], ['Jul 18, Jul 25', 'Fantasia Festival', 'Montreal, Quebec \xa0Canada', 'Special Mention\\n"for the resourcefulness and unwavering determination by a director to realize his unique vision"', 'FanTasia'], ['Oct 1, Oct 15', 'Gwacheon International SF Festival', 'Gwacheon, Gyeonggi-do\\n\xa0South Korea', '', 'gisf.org'], ['Nov 16–18', 'AFF', 'Wrocław, Lower Silesia\\n\xa0Poland', '', 'AFF Poland'], ['May 21–22, Jun 11', 'Seattle International Film Festival', 'Seattle, Washington \xa0USA', '', 'siff.net'], ['Nov 11', 'Les Utopiales', 'Nantes, Pays de la Loire\\n\xa0France', '', 'utopiales.org'], ['Nov 12, Nov 18', 'Indonesia Fantastic Film Festival', 'Jakarta, Bandung\\n\xa0Indonesia', '', 'inaff.com'], ['Oct 17, Oct 20', 'Icon TLV', 'Tel Aviv, Central\\n\xa0Israel', '', 'icon.org.il'], ['Feb 2–5, Feb 11', 'Santa Barbara International Film Festival', 'Santa Barbara, California \xa0USA', 'Top 11 "Best of the Fest" Selection', 'sbiff.org']] | 14 | Answer: | 128 | 14 | 514 |
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many drivers completed 80 laps? | [['Pos', 'No', 'Driver', 'Constructor', 'Laps', 'Time/Retired', 'Grid', 'Points'], ['4', '9', 'Denny Hulme', 'McLaren-Ford', '80', '+ 1:06.7', '8', '3'], ['DNQ', '28', 'Skip Barber', 'March-Ford', '', '', '', ''], ['2', '17', 'Ronnie Peterson', 'March-Ford', '80', '+ 25.6', '6', '6'], ['3', '4', 'Jacky Ickx', 'Ferrari', '80', '+ 53.3', '2', '4'], ['Ret', '10', 'Peter Gethin', 'McLaren-Ford', '22', 'Accident', '14', ''], ['7', '22', 'John Surtees', 'Surtees-Ford', '79', '+ 1 Lap', '10', ''], ['DNQ', '19', 'Nanni Galli*', 'March-Alfa-Romeo', '', '', '', ''], ['DNQ', '6', 'Mario Andretti', 'Ferrari', '', '', '', ''], ['DNQ', '18', 'Alex Soler-Roig', 'March-Ford', '', '', '', ''], ['10', '8', 'Tim Schenken', 'Brabham-Ford', '76', '+ 4 Laps', '18', ''], ['Ret', '5', 'Clay Regazzoni', 'Ferrari', '24', 'Accident', '11', ''], ['Ret', '7', 'Graham Hill', 'Brabham-Ford', '1', 'Accident', '9', ''], ['9', '15', 'Pedro Rodríguez', 'BRM', '76', '+ 4 Laps', '5', ''], ['Ret', '14', 'Jo Siffert', 'BRM', '58', 'Oil Pipe', '3', ''], ['6', '24', 'Rolf Stommelen', 'Surtees-Ford', '79', '+ 1 Lap', '16', '1'], ['DNQ', '16', 'Howden Ganley', 'BRM', '', '', '', ''], ['1', '11', 'Jackie Stewart', 'Tyrrell-Ford', '80', '1:52:21.3', '1', '9'], ['Ret', '2', 'Reine Wisell', 'Lotus-Ford', '21', 'Wheel bearing', '12', ''], ['5', '1', 'Emerson Fittipaldi', 'Lotus-Ford', '79', '+ 1 Lap', '17', '2'], ['Ret', '21', 'Jean-Pierre Beltoise', 'Matra', '47', 'Differential', '7', ''], ['Ret', '12', 'François Cevert', 'Tyrrell-Ford', '5', 'Accident', '15', ''], ['Ret', '20', 'Chris Amon', 'Matra', '45', 'Differential', '4', ''], ['8', '27', 'Henri Pescarolo', 'March-Ford', '77', '+ 3 Laps', '13', '']] | 4 | Answer: | 128 | 23 | 713 |
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what was the first interval of five years to have more than 100,000 deaths? | [['Period', 'Live births per year', 'Deaths per year', 'Natural change per year', 'CBR*', 'CDR*', 'NC*', 'TFR*', 'IMR*'], ['1965-1970', '229 000', '105 000', '124 000', '56.2', '25.8', '30.4', '7.32', '164'], ['2005-2010', '705 000', '196 000', '509 000', '49.5', '13.8', '35.7', '7.19', '96'], ['2000-2005', '614 000', '194 000', '420 000', '51.3', '16.2', '35.1', '7.40', '113'], ['1985-1990', '406 000', '179 000', '227 000', '55.9', '24.6', '31.3', '7.81', '155'], ['1960-1965', '195 000', '89 000', '105 000', '55.5', '25.5', '30.1', '7.13', '167'], ['1955-1960', '164 000', '76 000', '88 000', '53.8', '24.9', '29.0', '6.96', '171'], ['1975-1980', '301 000', '138 000', '164 000', '55.1', '25.1', '29.9', '7.63', '161'], ['1980-1985', '350 000', '157 000', '193 000', '55.4', '24.8', '30.6', '7.76', '159'], ['1950-1955', '139 000', '66 000', '74 000', '52.6', '24.8', '27.8', '6.86', '174'], ['1970-1975', '263 000', '121 000', '142 000', '55.8', '25.6', '30.2', '7.52', '162'], ['1990-1995', '471 000', '192 000', '279 000', '55.5', '22.7', '32.8', '7.78', '146'], ['1995-2000', '538 000', '194 000', '344 000', '53.5', '19.3', '34.2', '7.60', '131']] | 1965-1970 | Answer: | 128 | 12 | 580 |
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:kremlin cup and st petersburg open are in what country? | [['Outcome', 'No.', 'Date', 'Tournament', 'Surface', 'Opponent', 'Score'], ['Runner-up', '7.', '22 July 2012', 'Swiss Open, Switzerland', 'Clay', 'Thomaz Bellucci', '7–6(8–6), 4–6, 2–6'], ['Runner-up', '2.', '19 June 2010', 'UNICEF Open, Netherlands', 'Grass', 'Sergiy Stakhovsky', '3–6, 0–6'], ['Winner', '4.', '6 January 2013', 'Chennai Open, India', 'Hard', 'Roberto Bautista-Agut', '3–6, 6–1, 6–3'], ['Runner-up', '3.', '27 February 2011', 'International Tennis Championships, United States', 'Hard', 'Juan Martín del Potro', '4–6, 4–6'], ['Runner-up', '1.', '25 October 2009', 'Kremlin Cup, Russia', 'Hard (i)', 'Mikhail Youzhny', '7–6(7–5), 0–6, 4–6'], ['Runner-up', '4.', '18 June 2011', 'Aegon International, United Kingdom', 'Grass', 'Andreas Seppi', '6–7(5–7), 6–3, 3–5 ret.'], ['Winner', '2.', '23 October 2011', 'Kremlin Cup, Russia', 'Hard (i)', 'Viktor Troicki', '6–4, 6–2'], ['Runner-up', '6.', '8 January 2012', 'Chennai Open, India', 'Hard', 'Milos Raonic', '7–6(7–4), 6–7(4–7), 6–7(4–7)'], ['Winner', '1.', '2 October 2011', 'Malaysian Open, Malaysia', 'Hard (i)', 'Marcos Baghdatis', '6–4, 7–5'], ['Runner-up', '5.', '30 October 2011', 'St. Petersburg Open, Russia', 'Hard (i)', 'Marin Čilić', '3–6, 6–3, 2–6'], ['Winner', '3.', '15 July 2012', 'Stuttgart Open, Germany', 'Clay', 'Juan Mónaco', '6–4, 5–7, 6–3']] | Russia | Answer: | 128 | 11 | 555 |
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many gold medals did australia and switzerland total? | [['Rank', 'Nation', 'Gold', 'Silver', 'Bronze', 'Total'], ['7', 'Great Britain\xa0(GBR)', '0', '0', '1', '1'], ['7', 'France\xa0(FRA)', '0', '0', '1', '1'], ['2', 'Italy\xa0(ITA)', '1', '1', '1', '3'], ['4', 'Soviet Union\xa0(URS)', '1', '0', '0', '1'], ['1', 'Australia\xa0(AUS)', '2', '1', '0', '3'], ['5', 'Switzerland\xa0(SUI)', '0', '2', '1', '3'], ['3', 'Germany\xa0(EUA)', '1', '0', '1', '2'], ['6', 'United States\xa0(USA)', '0', '1', '0', '1']] | 2 | Answer: | 128 | 8 | 203 |
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 sizes that has an inner diameter above 50 mm? | [['Thread\\nnominal size', 'Outer diameter\\n[mm (in)]', 'Threads per inch\\n(TPI)', 'Pitch\\n[in (mm)]', 'Inner diameter\\n[mm (in)]', 'Cable diameter\\n[mm (in)]'], ['PG21', '28.3 (1.114)', '16', '0.0625 (1.5875)', '26.78 (1.054)', '13 to 18 (0.512 to 0.709)'], ['PG13.5', '20.4 (0.803)', '18', '0.05556 (1.4112)', '19.06 (0.750)', '6 to 12 (0.236 to 0.472)'], ['PG16', '22.5 (0.886)', '18', '0.05556 (1.4112)', '21.16 (0.833)', '10 to 14 (0.394 to 0.551)'], ['PG42', '54.0 (2.126)', '16', '0.0625 (1.5875)', '52.48 (2.066)', ''], ['PG36', '47.0 (1.850)', '16', '0.0625 (1.5875)', '45.48 (1.791)', ''], ['PG9', '15.5 (0.610)', '18', '0.05556 (1.4112)', '13.86 (0.546)', '4 to 8 (0.157 to 0.315)'], ['PG7', '12.5 (0.492)', '20', '0.05 (1.270)', '11.28 (0.444)', '3 to 6.5 (0.118 to 0.256)'], ['PG48', '59.3 (2.335)', '16', '0.0625 (1.5875)', '57.78 (2.275)', ''], ['PG11', '18.6 (0.732)', '18', '0.05556 (1.4112)', '17.26 (0.680)', '5 to 10 (0.197 to 0.394)'], ['PG29', '37.0 (1.457)', '16', '0.0625 (1.5875)', '35.48 (1.397)', '18 to 25 (0.709 to 0.984)']] | 2 | Answer: | 128 | 10 | 540 |
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 has the larger number of circuits? | [['Round', 'Date', 'Circuit', 'Winning driver (TA2)', 'Winning vehicle (TA2)', 'Winning driver (TA1)', 'Winning vehicle (TA1)'], ['2', 'June 4', 'Westwood', 'Ludwig Heimrath', 'Porsche 935', 'Nick Engels', 'Chevrolet Corvette'], ['4', 'June 25', 'Mont-Tremblant', 'Monte Sheldon', 'Porsche 935', 'Bob Tullius', 'Jaguar XJS'], ['9', 'October 8', 'Laguna Seca', 'Greg Pickett', 'Chevrolet Corvette', 'Bob Tullius', 'Jaguar XJS'], ['1', 'May 21', 'Sears Point', 'Greg Pickett', 'Chevrolet Corvette', 'Gene Bothello', 'Chevrolet Corvette'], ['7', 'August 19', 'Mosport', 'Greg Pickett', 'Chevrolet Corvette', 'Bob Tullius', 'Jaguar XJS'], ['5', 'July 8', 'Watkins Glen‡', 'Hal Shaw, Jr.\\n Monte Shelton', 'Porsche 935', 'Brian Fuerstenau\\n Bob Tullius', 'Jaguar XJS'], ['3', 'June 11', 'Portland', 'Tuck Thomas', 'Chevrolet Monza', 'Bob Matkowitch', 'Chevrolet Corvette'], ['10', 'November 5', 'Mexico City', 'Ludwig Heimrath', 'Porsche 935', 'Bob Tullius', 'Jaguar XJS'], ['6', 'August 13', 'Brainerd', 'Jerry Hansen', 'Chevrolet Monza', 'Bob Tullius', 'Jaguar XJS'], ['8', 'September 4', 'Road America', 'Greg Pickett', 'Chevrolet Corvette', 'Bob Tullius', 'Jaguar XJS']] | USA | Answer: | 128 | 10 | 426 |
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 brazil and the united states have the highest gold count? | [['Rank', 'Nation', 'Gold', 'Silver', 'Bronze', 'Total'], ['12.', 'Austria', '0', '0', '1', '1'], ['4.', 'Netherlands', '1', '1', '1', '3'], ['2.', 'United States', '9', '3', '6', '18'], ['7.', 'Germany', '0', '5', '1', '6'], ['10.', 'Switzerland', '0', '1', '1', '2'], ['6.', 'Estonia', '1', '0', '0', '1'], ['1.', 'Brazil', '21', '9', '12', '42'], ['3.', 'China', '1', '9', '8', '18'], ['11.', 'Norway', '0', '1', '0', '1'], ['4.', 'Australia', '1', '1', '1', '3'], ['9.', 'Argentina', '0', '2', '0', '2'], ['8.', 'Russia', '0', '2', '3', '5']] | Yes | Answer: | 128 | 12 | 242 |
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 he lead the most laps in? | [['Year', 'Car', 'Start', 'Qual', 'Rank', 'Finish', 'Laps', 'Led', 'Retired'], ['1932', '25', '20', '108.896', '34', '13', '184', '0', 'Flagged'], ['1934', '8', '7', '113.733', '13', '17', '94', '0', 'Rod'], ['1927', '27', '27', '107.765', '22', '3', '200', '0', 'Running'], ['1929', '23', '11', '112.146', '15', '17', '91', '0', 'Supercharger'], ['1926', '31', '12', '102.789', '13', '11', '142', '0', 'Flagged'], ['1939', '62', '27', '121.749', '24', '11', '200', '0', 'Running'], ['1928', '8', '4', '117.031', '4', '10', '200', '33', 'Running'], ['1933', '34', '12', '113.578', '15', '7', '200', '0', 'Running'], ['1930', '9', '20', '100.033', '18', '20', '79', '0', 'Valve'], ['1935', '44', '6', '115.459', '11', '21', '102', '0', 'Magneto'], ['1938', '17', '4', '122.499', '6', '17', '130', '0', 'Rod'], ['Totals', 'Totals', 'Totals', 'Totals', 'Totals', 'Totals', '1989', '33', ''], ['1931', '37', '19', '111.725', '6', '18', '167', '0', 'Crash T4'], ['1937', '38', '7', '118.788', '16', '8', '200', '0', 'Running']] | 1928 | Answer: | 128 | 14 | 460 |
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 played after october 1st? | [['Date', 'Team', 'Competition', 'Round', 'Leg', 'Opponent', 'Location', 'Score'], ['August 29', 'Anderlecht', 'Champions League', 'Qual. Round 3', 'Leg 2, Home', 'Fenerbahçe', 'Constant Vanden Stock Stadium, Anderlecht', '0-2'], ['September 20', 'Standard Liège', 'UEFA Cup', 'Round 1', 'Leg 1, Away', 'Zenit St. Petersburg', 'Petrovsky Stadium, Saint Petersburg', '0-3'], ['November 8', 'Anderlecht', 'UEFA Cup', 'Group Stage', 'Match 2, Away', 'Aalborg', 'Energi Nord Arena, Aalborg', '1-1'], ['August 8', 'Genk', 'Champions League', 'Qual. Round 2', 'Leg 2, Away', 'Sarajevo', 'Asim Ferhatović Hase Stadium, Sarajevo', '1-0'], ['February 21', 'Anderlecht', 'UEFA Cup', 'Round of 32', 'Leg 2, Away', 'Bordeaux', 'Stade Chaban-Delmas, Bordeaux', '1-1'], ['March 12', 'Anderlecht', 'UEFA Cup', 'Round of 16', 'Leg 2, Away', 'Bayern Munich', 'Allianz Arena, Munich', '2-1'], ['February 13', 'Anderlecht', 'UEFA Cup', 'Round of 32', 'Leg 1, Home', 'Bordeaux', 'Constant Vanden Stock Stadium, Anderlecht', '2-1'], ['July 29', 'Gent', 'Intertoto Cup', 'Round 3', 'Leg 2, Away', 'Aalborg', 'Energi Nord Arena, Aalborg', '1-2'], ['August 30', 'Standard Liège', 'UEFA Cup', 'Qual. Round 2', 'Leg 2, Home', 'Käerjeng', 'Stade Maurice Dufrasne, Liège', '1-0'], ['September 20', 'Club Brugge', 'UEFA Cup', 'Round 1', 'Leg 1, Away', 'Brann', 'Brann Stadion, Bergen', '1-0'], ['October 4', 'Club Brugge', 'UEFA Cup', 'Round 1', 'Leg 2, Home', 'Brann', 'Jan Breydel Stadium, Bruges', '1-2'], ['July 7', 'Gent', 'Intertoto Cup', 'Round 2', 'Leg 1, Home', 'Cliftonville', 'Jules Ottenstadion, Ghent', '2-0'], ['August 16', 'Standard Liège', 'UEFA Cup', 'Qual. Round 2', 'Leg 1, Away', 'Käerjeng', 'Stade Josy Barthel, Luxembourg', '3-0'], ['September 20', 'Anderlecht', 'UEFA Cup', 'Round 1', 'Leg 1, Home', 'Rapid Wien', 'Constant Vanden Stock Stadium, Anderlecht', '1-1'], ['July 21', 'Gent', 'Intertoto Cup', 'Round 3', 'Leg 1, Home', 'Aalborg', 'Jules Ottenstadion, Ghent', '1-1'], ['July 31', 'Genk', 'Champions League', 'Qual. Round 2', 'Leg 1, Home', 'Sarajevo', 'Cristal Arena, Genk', '1-2'], ['December 19', 'Anderlecht', 'UEFA Cup', 'Group Stage', 'Match 4, Away', 'Getafe', 'Coliseum Alfonso Pérez, Getafe', '1-2'], ['August 15', 'Anderlecht', 'Champions League', 'Qual. Round 3', 'Leg 1, Away', 'Fenerbahçe', 'Şükrü Saracoğlu Stadium, Istanbul', '0-1'], ['October 4', 'Standard Liège', 'UEFA Cup', 'Round 1', 'Leg 2, Home', 'Zenit St. Petersburg', 'Stade Maurice Dufrasne, Liège', '1-1'], ['March 6', 'Anderlecht', 'UEFA Cup', 'Round of 16', 'Leg 1, Home', 'Bayern Munich', 'Constant Vanden Stock Stadium, Anderlecht', '0-5']] | 11 | Answer: | 128 | 20 | 1,017 |
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 wins listed for the united states? | [['Golfer', 'Country', 'Wins', 'Match Play', 'Championship', 'Invitational', 'Champions'], ['Phil Mickelson', 'United States', '2', '—', '1: 2009', '—', '1: 2009'], ['Hunter Mahan', 'United States', '2', '1: 2012', '—', '1: 2010', '—'], ['Ian Poulter', 'England', '2', '1: 2010', '—', '—', '1: 2012'], ['Darren Clarke', 'Northern Ireland', '2', '1: 2000', '—', '1: 2003', '—'], ['Ernie Els', 'South Africa', '2', '—', '2: 2004, 2010', '—', '—'], ['Geoff Ogilvy', 'Australia', '3', '2: 2006, 2009', '1: 2008', '—', '—'], ['Tiger Woods', 'United States', '18', '3: 2003, 2004, 2008', '7: 1999, 2002, 2003,\\n2005, 2006, 2007, 2013', '8: 1999, 2000, 2001, 2005,\\n2006, 2007, 2009, 2013', '—']] | 22 | Answer: | 128 | 7 | 323 |
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:if italy and brazil combined box office revenues, what would be their new total? | [['Rank', 'Country', 'Box Office', 'Year', 'Box office\\nfrom national films'], ['3', 'Japan', '$1.88 billion', '2013', '61% (2013)'], ['11', 'Italy', '$0.84 billion', '2013', '30% (2013)'], ['1', 'Canada/United States', '$10.8 billion', '2012', '–'], ['9', 'Russia', '$1.2 billion', '2012', '–'], ['6', 'South Korea', '$1.47 billion', '2013', '59.7% (2013)'], ['12', 'Brazil', '$0.72 billion', '2013', '17% (2013)'], ['2', 'China', '$3.6 billion', '2013', '59% (2013)'], ['10', 'Australia', '$1.2 billion', '2012', '4.1% (2011)'], ['-', 'World', '$34.7 billion', '2012', '–'], ['5', 'France', '$1.7 billion', '2012', '33.3% (2013)'], ['8', 'Germany', '$1.3 billion', '2012', '–'], ['7', 'India', '$1.4 billion', '2012', '–'], ['4', 'United Kingdom', '$1.7 billion', '2012', '36.1% (2011)']] | $1.56 billion | Answer: | 128 | 13 | 321 |
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:when did the restaurant "verre" at the hilton dubai creek close? | [['Restaurant', 'Location', 'Date Opened', 'Date Closed'], ['Maze by Gordon Ramsay', 'The Pearl-Qatar, Doha, Qatar', '2010', 'March 2012'], ['Maze / Maze Grill by Gordon Ramsay', 'Crown Metropol, Melbourne, Australia', 'March 2010', 'August 2011'], ['Cerise by Gordon Ramsay', 'Minato, Tokyo, Japan', '', '-'], ['Gordon Ramsay at Conrad Tokyo', 'Conrad Tokyo, Tokyo, Japan', '', '-'], ['Maze by Gordon Ramsay', 'One and Only Hotel, Cape Town, South Africa', 'April 2009', 'July 2010'], ['Verre at the Hilton Dubai Creek', 'Dubai, United Arab Emirates', '', 'October 2011']] | October 2011 | Answer: | 128 | 6 | 174 |
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 finished immediately after danny osborne? | [['Position', 'Driver', 'No.', 'Car', 'Entrant', 'Lak.', 'Ora.', 'San.', 'Phi.', 'Total'], ['22', 'Shane Eklund', '', '', '', '10', '-', '-', '-', '10'], ['10', 'Des Wall', '', 'Toyota Supra', '', '15', '32', '-', '-', '47'], ['6', 'Danny Osborne', '', 'Mazda RX-7', '', '26', '10', '30', '-', "66'"], ['15', 'Gary Rowe', '47', 'Nissan Stanza', 'Gary Rowe', '-', '-', '21', '-', '21'], ['', 'Paul Barrett', '', '', '', '-', '-', '-', '12', '12'], ['19', 'Chris Donnelly', '', '', '', '12', '-', '-', '-', '12'], ['13', 'Chris Fing', '', 'Chevrolet Monza', '', '29', '-', '-', '-', '29'], ['', "Ron O'Brien", '', '', '', '-', '-', '-', '10', '10'], ['3', 'James Phillip', '55', 'Honda Prelude Chevrolet', 'James Phillip', '26', '28', '28', '30', '112'], ['17', 'Phil Crompton', '49', 'Ford EA Falcon', 'Phil Crompton', '17', '-', '-', '-', '17'], ['5', 'Bob Jolly', '3', 'Holden VS Commodore', 'Bob Jolly', '-', '28', '16', '32', '76'], ['14', 'Brian Smith', '', 'Alfa Romeo GTV Chevrolet', '', '-', '28', '-', '-', '28'], ['11', 'Kevin Clark', '116', 'Ford Mustang GT', 'Kevin Clark', '-', '-', '23', '23', '46'], ['', 'Domenic Beninca', '', '', '', '-', '-', '-', '21', '21'], ['12', "Peter O'Brien", '17', 'Holden VL Commodore', "O'Brien Aluminium", '-', '11', '29', '-', '40'], ['7', 'Mike Imrie', '4', 'Saab', 'Imrie Motor Sport', '23', '11', '-', '28', '62'], ['21', 'Brett Francis', '', '', '', '11', '-', '-', '-', '11'], ['8', 'Mark Trenoweth', '', 'Jaguar', '', '33', '24', '-', '-', '57'], ['2', 'Kerry Baily', '18', 'Toyota Supra Chevrolet', 'Kerry Baily', '38', '38', '36', '38', '150'], ['18', 'Allan McCarthy', '', 'Alfa Romeo Alfetta', '', '14', '-', '-', '-', '14'], ['', 'Craig Wildridge', '', '', '', '-', '10', '-', '-', '10'], ['9', 'Ivan Mikac', '42', 'Mazda RX-7', 'Ivan Mikac', '-', '-', '25', '26', '51'], ['1', 'John Briggs', '9', 'Honda Prelude Chevrolet', 'John Briggs', '42', '42', '42', '42', '168'], ['4', 'Mick Monterosso', '2', 'Ford Escort RS2000', 'Mick Monterosso', '-', '34', '36', '34', '104']] | Mike Imrie | Answer: | 128 | 24 | 713 |
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:where is saint anslem school located? | [['District', 'Location', 'Communities served'], ['Hershey Montessori Farm School', 'Huntsburg Township, Ohio', 'parent-owned, and chartered by Ohio Department of Education: application deadline January each year'], ["Saint Helen's School", 'Newbury, Ohio', 'Roman Catholic Diocese of Cleveland K - 8th grade; parishioners and non-parishioners'], ["Saint Mary's School", 'Chardon, Ohio', 'Roman Catholic Diocese of Cleveland preschool - 8th grade; parishioners and non-parishioners'], ['Saint Anselm School', 'Chester Township, Ohio', 'Roman Catholic Diocese of Cleveland K - 8th grade; preschool'], ['Hawken School', 'Gates Mills, Ohio', 'College preparatory day school: online application, site visit and testing'], ['Notre Dame-Cathedral Latin', 'Munson Township, Ohio', 'Roman Catholic Diocese of Cleveland: open to 8th grade students who have attended a Catholic elementary school and others who have not'], ['Solon/Bainbridge Montessori School of Languages', 'Bainbridge Township, Ohio', 'nonsectarian Montessori School: quarterly enrollment periods'], ['Agape Christian Academy', 'Burton Township, Ohio and Troy Township, Ohio', 'Accepts applications prior to the start of each school year']] | Chester Township, Ohio | Answer: | 128 | 8 | 288 |
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