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test · 4.34k rows

question stringlengths 2.11k 2.25k	context stringlengths 344 4.57k	answer stringlengths 1 260	answer_prefix stringclasses 1 value	max_new_tokens int64 128 128	tuple_count int64 5 60	token_count int64 137 1.11k
You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 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

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