Split (1)

test · 4.34k rows

context stringlengths 362 4.81k	question stringlengths 2.11k 2.25k	answer stringlengths 1 260	max_new_tokens int64 128 128	answer_prefix stringclasses 1 value
Table InputTable: [["Political lieutenant", "District\\n(Area)", "Took Office", "Left Office", "Party leader"], ["Georges-Henri Héon", "Argenteuil\\n(Laurentides)", "1949", "1949", "George A. Drew"], ["Claude Wagner", "Saint-Hyacinthe\\n(Montérégie)", "1972", "1978", "Robert Stanfield\\nJoe Clark"], ["Léon Balcer", "Trois-Rivières\\n(Mauricie)", "1957", "1965", "John George Diefenbaker"], ["Marcel Faribault", "none", "1967", "1968", "Robert Stanfield"], ["Lucien Bouchard", "Lac-Saint-Jean\\n(Saguenay-Lac-Saint-Jean)", "1988", "1990", "Brian Mulroney"], ["André Bachand", "Richmond—Arthabaska\\n(Centre-du-Québec &\\nEastern Townships)", "1998", "2004", "Joe Clark\\nPeter MacKay"], ["Benoît Bouchard", "Roberval\\n(Saguenay-Lac-Saint-Jean)", "1990", "1993", "Brian Mulroney"], ["Monique Landry", "Blainville—Deux-Montagnes\\n(Laurentides)", "1993", "1993", "Kim Campbell"]]	You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 0, 2, 2], [10, "France", 0, 0, 1, 1]] Question: name the countries that had at least 5 gold medals Answer: Netherlands, Italy Question:who was the first lieutenant to take office?	Georges-Henri Héon	128	Answer:
Table InputTable: [["Series #", "Season #", "Title", "Notes", "Original air date"], ["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"], ["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"], ["13", "1", "\"The Big Bully\"", "Dee Dee gets beat up at school and his friends try to teach him how to fight back. Goo, however, tells him to bluff, but the plan backfires and Dee Dee gets hit because of it. When Alfie confronts the bully, he learns that Dee Dee was picked on by a girl. Alfie and Goo decide to confront her. However, when some of their classmates, who happen to be the girls' siblings, learn they are bullying their sister, they intervene.", "February 2, 1995"], ["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"], ["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"], ["8", "1", "\"Dee Dee's Haircut\"", "Dee Dee wants to get a hair cut by Cool Doctor Money and have his name shaved in his head. His parents will not let him do this, but Goo offers to do it for five dollars. However, when Goo messes up Dee Dee's hair and spells his name wrong, his parents find out the truth and Dee Dee is forced to have his hair shaved off. In addition to that, his friends tease him about his bald head, causing a fight between the boys along with Goo and Alfie. In a b-story, Alfie and Goo try to play a practical joke on Dee Dee involving a jalapeño lollipop. It backfires when Roger is the unwitting victim and it leads to him chasing the boys around.", "December 20, 1994"], ["5", "1", "\"Basketball Tryouts\"", "Alfie tries out for the basketball team and doesn't make it even after showing off his basketball skills. However, Harry, Dee Dee and Donnell make the team. Alfie is depressed and doesn't want to attend the celebration party. However, Goo sets him straight by telling him it was his own fault for not being a team player and kept the ball to himself.", "November 30, 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"], ["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"]]	You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 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 previous episode before "robin hood play?"	"The Weekend Aunt Helen Came"	128	Answer:
Table InputTable: [["State", "Membership", "Parliament", "Membership status", "Represented since", "Members"], ["Iceland", "Full", "Alþingi", "Sovereign state", "1952", "7"], ["Finland", "Full", "Eduskunta", "Sovereign state", "1955", "18"], ["Faroe Islands", "Associate", "Løgting", "Self-governing region of the Danish Realm", "1970", "2"], ["Denmark", "Full", "The Folketing", "Sovereign state", "1952", "16"], ["Åland Islands", "Associate", "Lagting", "Self-governing region of Finland", "1970", "2"], ["Norway", "Full", "The Storting", "Sovereign state", "1952", "20"], ["Greenland", "Associate", "Landsting", "Self-governing region of the Danish Realm", "1984", "2"], ["Sweden", "Full", "The Riksdag", "Sovereign state", "1952", "20"], ["Latvia", "Observers", "", "", "", ""], ["Estonia", "Observers", "", "", "", ""], ["Lithuania", "Observers", "", "", "", ""]]	You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 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 state has a full membership and also has a membership status under sovereign state with only 7 members?	Iceland	128	Answer:
Table InputTable: [["Year", "Matches", "Winner", "Results", "Pakistan\\nCaptain", "Pakistan\\nCoach", "India\\nCaptain", "India\\nCoach"], ["1988", "6", "Draw", "2 - 2", "Nasir Ali", "Manzoor-ul-Hasan", "M. M. Somaya", "M. P. Ganesh"], ["1981", "4", "Pakistan win", "2 - 1", "Akhtar Rasool", "Zakauddin", "Surjeet Singh", "Harmeek Singh"], ["2006", "6", "Pakistan win", "3 - 1", "Mohammad Saqlain", "Asif Bajwa", "Ignace Tirkey", "Rajinder Singh Jr."], ["1986", "7", "India win", "3 - 2", "Hassan Sardar", "Anwar Ahmad Khan", "Mohmmad Shaheed", "M. P. Ganesh"], ["2004", "8", "Pakistan win", "4 - 2", "Waseem Ahmad", "Roelant Oltmans", "Dileep Tirkey", "Gehard Rach"], ["2013", "TBA", "TBA", "TBA", "TBA", "TBA", "TBA", "TBA"], ["1999", "9", "Pakistan win", "5 - 3", "Atif Bashir", "Shahnaz Shaikh", "Anil Aldrin", "V Bhaskaran"], ["1978", "4", "Pakistan win", "3 - 1", "Islahuddin Siddique", "Sayad A. Hussain", "V. J. Philips", "R. S. Gentle"], ["1998", "8", "Pakistan win", "4 - 3", "Tahir Zaman", "Islahuddin Siddique", "Dhanraj Pillay", "V Bhaskaran"]]	You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 0, 2, 2], [10, "France", 0, 0, 1, 1]] Question: name the countries that had at least 5 gold medals Answer: Netherlands, Italy Question:how many years were there more than 6 matches?	4	128	Answer:
Table InputTable: [["Model", "Volume", "Engine", "Fuel", "Power/Torque", "Years produced", "Produced"], ["735iL", "3.5L", "M62B35 V8", "Petrol", "173 kW (235 PS; 232 hp) / 320 N·m (236 lb·ft)", "1994–1997", "6963"], ["740d", "3.9L", "M67D40 turbocharged V8", "Diesel", "180 kW (245 PS; 241 hp) / 560 N·m (413 lb·ft)", "1998–2001", "3450"], ["740iL", "4.4L", "M62B44 V8", "Petrol", "210 kW (286 PS; 282 hp) / 420 N·m (310 lb·ft)", "1996–1998", "91431"], ["730d", "2.9L", "M57D30 turbocharged I6", "Diesel", "142 kW (193 PS; 190 hp) / 410 N·m (302 lb·ft)", "1998–2001", "12336"], ["728iL", "2.8L", "M52B28 I6", "Petrol", "142 kW (193 PS; 190 hp) / 280 N·m (207 lb·ft)", "1996–2001", "6816"], ["735i", "3.5L", "M62B35 V8", "Petrol", "173 kW (235 PS; 232 hp) / 320 N·m (236 lb·ft)", "1994–1997", "21481"], ["740i", "4.4L", "M62B44 V8", "Petrol", "210 kW (286 PS; 282 hp) / 420 N·m (310 lb·ft)", "1996–1998", "88853"], ["728i", "2.8L", "M52B28 I6", "Petrol", "142 kW (193 PS; 190 hp) / 280 N·m (207 lb·ft)", "1996–2001", "38947"], ["740iL", "4.4L", "M62TUB44 V8", "Petrol", "210 kW (286 PS; 282 hp) / 440 N·m (325 lb·ft)", "1998–2001", ""], ["735iL", "3.5L", "M62TUB35 V8", "Petrol", "174 kW (237 PS; 233 hp) / 345 N·m (254 lb·ft)", "1998–2001", ""], ["725tds", "2.5L", "M51D25 turbocharged I6", "Diesel", "105 kW (143 PS; 141 hp) / 280 N·m (207 lb·ft)", "1995–2001", "9053"], ["740i", "4.4L", "M62TUB44 V8", "Petrol", "210 kW (286 PS; 282 hp) / 440 N·m (325 lb·ft)", "1998–2001", ""], ["740iL", "4.0L", "M60B40 V8", "Petrol", "210 kW (286 PS; 282 hp) / 400 N·m (295 lb·ft)", "1994–1996", ""], ["735i", "3.5L", "M62TUB35 V8", "Petrol", "174 kW (237 PS; 233 hp) / 345 N·m (254 lb·ft)", "1998–2001", ""], ["730iL", "3.0L", "M60B30 V8", "Petrol", "160 kW (218 PS; 215 hp) / 290 N·m (214 lb·ft)", "1994–1996", "2137"], ["750i-iL", "5.4L", "M73B54 V12", "Petrol", "240 kW (326 PS; 322 hp) / 490 N·m (361 lb·ft)", "1995–1997", "15759"], ["730i", "3.0L", "M60B30 V8", "Petrol", "160 kW (218 PS; 215 hp) / 290 N·m (214 lb·ft)", "1994–1996", "20876"]]	You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 0, 2, 2], [10, "France", 0, 0, 1, 1]] Question: name the countries that had at least 5 gold medals Answer: Netherlands, Italy Question:what is the difference in number of petrol models and the number of diesel?	13	128	Answer:
Table InputTable: [["Team", "Chassis", "Engine", "Tires", "No", "Drivers"], ["Della Penna Motorsports", "Swift 009.c", "Ford XB", "Firestone", "10", "Richie Hearn"], ["Della Penna Motorsports", "Swift 009.c", "Ford XB", "Firestone", "43", "Hideshi Matsuda"], ["Chip Ganassi Racing", "Reynard 98i", "Honda", "Firestone", "1", "Alex Zanardi"], ["All American Racing", "Reynard 98i\\nEagle 987", "Toyota", "Goodyear", "98", "P. J. Jones\\n Vincenzo Sospiri"], ["Payton/Coyne Racing", "Reynard 98i", "Ford XB", "Firestone", "19", "Michel Jourdain, Jr."], ["Payton/Coyne Racing", "Reynard 98i", "Ford XB", "Firestone", "34", "Dennis Vitolo\\n Gualter Salles"], ["Walker Racing", "Reynard 98i", "Honda", "Goodyear", "5", "Gil de Ferran"], ["Newman-Haas Racing", "Swift 009.c", "Ford XB", "Goodyear", "6", "Michael Andretti"], ["Chip Ganassi Racing", "Reynard 98i", "Honda", "Firestone", "12", "Jimmy Vasser"], ["Arciero-Wells Racing", "Reynard 98i", "Toyota", "Firestone", "25", "Max Papis"], ["Arciero-Wells Racing", "Reynard 98i", "Toyota", "Firestone", "24", "Hiro Matsushita\\n Robby Gordon"], ["All American Racing", "Reynard 98i\\nEagle 987", "Toyota", "Goodyear", "36", "Alex Barron"], ["Hogan Racing", "Reynard 98i", "Mercedes", "Firestone", "9", "JJ Lehto"], ["Patrick Racing", "Reynard 98i", "Ford XB", "Firestone", "40", "Adrián Fernández"], ["Patrick Racing", "Reynard 98i", "Ford XB", "Firestone", "20", "Scott Pruett"], ["Newman-Haas Racing", "Swift 009.c", "Ford XB", "Goodyear", "11", "Christian Fittipaldi\\n Roberto Moreno"], ["Forsythe Racing", "Reynard 98i", "Mercedes", "Firestone", "99", "Greg Moore"], ["Forsythe Racing", "Reynard 98i", "Mercedes", "Firestone", "33", "Patrick Carpentier"], ["Project Indy", "Reynard 97i", "Ford XB", "Goodyear", "15", "Roberto Moreno\\n Domenico Schiattarella"], ["Davis Racing", "Lola T98/00", "Ford XB", "Goodyear", "77", "Arnd Meier"], ["Marlboro Team Penske", "Penske PC27-98", "Mercedes", "Goodyear", "2", "Al Unser, Jr."], ["Tasman Motorsports Group", "Reynard 98i", "Honda", "Firestone", "21", "Tony Kanaan"], ["Marlboro Team Penske", "Penske PC27-98", "Mercedes", "Goodyear", "3", "André Ribeiro"], ["Bettenhausen Racing", "Reynard 98i", "Mercedes", "Goodyear", "16", "Hélio Castroneves"], ["Team Rahal", "Reynard 98i", "Ford XB", "Firestone", "8", "Bryan Herta"], ["PacWest Racing Group", "Reynard 98i", "Mercedes", "Firestone", "17", "Maurício Gugelmin"], ["PacWest Racing Group", "Reynard 98i", "Mercedes", "Firestone", "18", "Mark Blundell"], ["Team KOOL Green", "Reynard 98i", "Honda", "Firestone", "26", "Paul Tracy"], ["Team KOOL Green", "Reynard 98i", "Honda", "Firestone", "27", "Dario Franchitti"], ["Team Rahal", "Reynard 98i", "Ford XB", "Firestone", "7", "Bobby Rahal"]]	You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 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 drives that della penna motorsports had?	2	128	Answer:
Table InputTable: [["Speed", "Date", "Country", "Train", "Arr.", "Power", "State", "Comments"], ["182.4 km/h (113 mph)", "1972-10-11", "Germany", "BR 18 201", "Loc", "Steam", "Unkn.", "The fastest operational steam locomotive as of 2011.[citation needed]"], ["164 km/h (102 mph)", "1904-05-09", "UK", "GWR 3700 Class 3440 City of Truro", "Loc", "Steam", "Unmod.", "Claimed[by whom?] to be the first steam locomotive to reach100 mph (161 km/h).[citation needed]"], ["185.07 km/h (115 mph)", "1905-06-11", "USA", "Pennsylvania Railroad E2 #7002", "Loc", "Steam", "Unmod.", "Claimed.[by whom?] Clocked at Crestline, Ohio at 127.1 mph (205 km/h) in 1905. However PRR Steam Locomotives did not carry speedometers at that time, speed was calculated by measuring time between mile markers, so this is not recognized as a speed record.[citation needed]"], ["161 km/h (100 mph)", "1934-11-30", "UK", "LNER Class A3 4472 Flying Scotsman", "Loc", "Steam", "Unmod.", "In 1934, Flying Scotsman achieved the first authenticated 100 mph (161 km/h) by a steam locomotive."], ["145 km/h (90 mph)", "1895-08-22", "UK", "LNWR No. 790 Hardwicke", "Loc", "Steam", "Unmod.", "Maximum speed claimed[by whom?], although average speed record was authenticated.[citation needed]"], ["131.6 km/h (82 mph)", "1854-06", "UK", "Bristol & Exeter Railway #41", "Loc", "Steam", "Unmod.", "Broad gauge[citation needed]"], ["8 km/h (5 mph)", "1804-02-21", "UK", "Richard Trevithick's world's first railway steam locomotive", "Loc", "Steam", "Unmod.", "[citation needed]"], ["180.3 km/h (112 mph)", "1935-09-29", "UK", "LNER Class A4 2509 Silver Link", "Loc", "Steam", "Unkn.", "Authenticated. Some sources say 112.5 mph.[citation needed]"], ["168.5 km/h (105 mph)", "1935-03-05", "UK", "LNER Class A3 No. 2750 Papyrus", "Loc", "Steam", "Unmod.", "First run at 100+ mph with complete, surviving documentation.[citation needed]"], ["200.4 km/h (125 mph)", "1936-05-11", "Germany", "Borsig DRG series 05 002", "Loc", "Steam", "Unkn.", "Level grade.[citation needed]"], ["131 km/h (81 mph)", "1893-05-10", "USA", "Empire State Express No. 999", "Loc", "Steam", "Unmod.", "112 mph (180 km/h) claimed[by whom?], which would make it the first wheeled vehicle to exceed 100 mph (161 km/h)."], ["202.6 km/h (126 mph)", "1938-07-03", "UK", "LNER Class A4 No. 4468 Mallard", "Loc", "Steam", "Unkn.", "Downhill grade. Data indicates peak speed 202.6 km/h (126 mph), mean speed (half-mile) 201.2 km/h (125 mph). Mallard suffered an overheated crankpin during the run, but was repaired and returned to traffic within 9 days."], ["96.6 km/h (60 mph)", "1848", "USA", "Boston and Maine Railroad Antelope", "Loc", "Steam", "Unmod.", "First authenticated 60 mph (97 km/h),26 miles (42 km) in 26 minutes.[citation needed]"], ["166.6 km/h (104 mph)", "1934-07-20", "USA", "Milwaukee Road class F6 #6402", "Loc", "Steam", "Unmod", "A point between Oakwood, Illinois and Lake, Wisconsin. Also averaged 75.5 mph (122 km/h) on 85 miles (137 km) from Chicago, Illinois to Milwaukee, and 89.92 mph (145 km/h) for a 68.9 miles (110.9 km) stretch"]]	You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 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 kind of train has been recorded going the top speed of any steam rail vehicle?	LNER Class A4 No. 4468 Mallard	128	Answer:
Table InputTable: [["Olympics", "Athlete", "Judge (Official)", "Coach", "Language"], ["1976 Summer Olympics", "Pierre St.-Jean", "Maurice Fauget", "-", "French (St.-Jean)/English (Fauget)"], ["1924 Summer Olympics", "Géo André", "-", "-", "French."], ["1948 Summer Olympics", "Donald Finlay", "-", "-", "English"], ["1968 Winter Olympics", "Léo Lacroix", "-", "-", "French"], ["1988 Winter Olympics", "Pierre Harvey", "Suzanna Morrow-Francis", "-", "English"], ["1932 Summer Olympics", "George Calnan", "-", "-", "English"], ["2010 Winter Olympics", "Hayley Wickenheiser", "Michel Verrault", "-", "English/French"], ["1992 Winter Olympics", "Surya Bonaly", "Pierre Bornat", "-", "French"], ["1996 Summer Olympics", "Teresa Edwards", "Hobie Billingsley", "-", "English"], ["1980 Winter Olympics", "Eric Heiden", "Terry McDermott", "-", "English"], ["1956 Summer Olympics", "John Landy (Melbourne)\\nHenri Saint Cyr (Stockholm)", "-", "-", "English/Swedish"], ["1984 Summer Olympics", "Edwin Moses", "Sharon Weber", "-", "English"], ["2012 Summer Olympics", "Sarah Stevenson", "Mik Basi", "Eric Farrell", "English"], ["2002 Winter Olympics", "Jimmy Shea", "Allen Church", "-", "English"], ["1994 Winter Olympics", "Vegard Ulvang", "Kari Kåring", "-", "English (Ulvang)/Norwegian (Kåring)"], ["1964 Winter Olympics", "Paul Aste", "-", "-", "German"], ["2000 Summer Olympics", "Rechelle Hawkes", "Peter Kerr", "-", "English"], ["1936 Summer Olympics", "Rudolf Ismayr", "-", "-", "-"], ["1920 Summer Olympics", "Victor Boin", "-", "-", "-"], ["1924 Winter Olympics", "Camille Mandrillon", "-", "-", "-"], ["1968 Summer Olympics", "Pablo Garrido", "-", "-", "Spanish"], ["1928 Summer Olympics", "Harry Dénis", "-", "-", "-"], ["2008 Summer Olympics", "Zhang Yining", "Huang Liping", "-", "Chinese"], ["1980 Summer Olympics", "Nikolai Andrianov", "Alexander Medved", "-", "Russian"], ["1960 Summer Olympics", "Adolfo Consolini", "-", "-", "-"], ["1972 Summer Olympics", "Heidi Schüller", "Heinz Pollay", "-", "German"], ["1952 Summer Olympics", "Heikki Savolainen", "-", "-", "-"], ["1932 Winter Olympics", "Jack Shea", "-", "-", "-"], ["1992 Summer Olympics", "Luis Doreste Blanco", "Eugeni Asensio", "-", "Spanish/Catalan"], ["1952 Winter Olympics", "Torbjørn Falkanger", "-", "-", "-"], ["1936 Winter Olympics", "Willy Bogner, Sr.", "-", "-", "-"], ["2004 Summer Olympics", "Zoi Dimoschaki", "Lazaros Voreadis", "-", "Greek"], ["1988 Summer Olympics", "Hur Jae\\nShon Mi-Na", "Lee Hak-Rae", "-", "Korean"], ["1964 Summer Olympics", "Takashi Ono", "-", "-", "Japanese"], ["1948 Winter Olympics", "Bibi Torriani", "-", "-", "-"], ["1928 Winter Olympics", "Hans Eidenbenz", "-", "-", "-"], ["1960 Winter Olympics", "Carol Heiss", "-", "-", "-"], ["1976 Winter Olympics", "Werner Delle Karth", "Willy Köstinger", "-", "German"], ["2006 Winter Olympics", "Giorgio Rocca", "Fabio Bianchetti", "-", "Italian"], ["1972 Winter Olympics", "Keiichi Suzuki", "Fumio Asaki", "-", "Japanese"], ["1998 Winter Olympics", "Kenji Ogiwara", "Junko Hiramatsu", "-", "Japanese"], ["1956 Winter Olympics", "Giuliana Minuzzo", "-", "-", "-"], ["2014 Winter Olympics", "Ruslan Zakharov", "Vyacheslav Vedenin, Jr", "Anastassia Popkova", "Russian"], ["1984 Winter Olympics", "Bojan Križaj", "Dragan Perovic", "-", "Serbo-Croatian"]]	You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 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 language has been spoken more during the olympic oath, english or french?	English	128	Answer:
Table InputTable: [["Name of place", "Number of counties", "Principal county", "Lower zip code", "Upper zip code"], ["Saegertown", "1", "Crawford County", "16433", ""], ["Saegersville", "1", "Lehigh County", "18053", ""], ["Saegers", "1", "Lycoming County", "", ""], ["Saville Township", "1", "Perry County", "", ""], ["Schuylkill", "1", "Philadelphia County", "19146", ""], ["Seipstown", "1", "Lehigh County", "18031", ""], ["Shoenersville", "2", "Lehigh County", "18103", ""], ["Shaft", "1", "Schuylkill County", "17976", ""], ["Saville", "1", "Perry County", "17074", ""], ["Sharps Hill", "1", "Allegheny County", "15215", ""], ["Schaefferstown", "1", "Lebanon County", "17088", ""], ["Scherersville", "1", "Lehigh County", "", ""], ["Scott Township", "1", "Allegheny County", "15106", ""], ["Schnecksville", "1", "Lehigh County", "18078", ""], ["Seiberlingville", "1", "Lehigh County", "", ""], ["Shimpstown", "1", "Franklin County", "17236", ""], ["Sharpe Hill", "1", "Allegheny County", "", ""], ["Shimerville", "1", "Lehigh County", "18049", ""], ["Shackamaxon", "1", "Philadelphia County", "", ""], ["Simmonstown", "1", "Lancaster County", "17527", ""], ["Shousetown", "1", "Allegheny County", "", ""], ["Schuylkill Township", "1", "Chester County", "", ""], ["Schoeneck", "1", "Lancaster County", "17578", ""], ["Scotia", "1", "Allegheny County", "15025", ""], ["Sewickley Hills", "1", "Allegheny County", "15143", ""], ["Shaler Township", "1", "Allegheny County", "", ""], ["Sewickley", "1", "Allegheny County", "15143", ""], ["Sawtown", "1", "Venango County", "16301", ""], ["St. Clair Acres", "1", "Allegheny County", "15241", ""], ["St. Joseph", "1", "Susquehanna County", "18818", ""], ["Seiple", "1", "Lehigh County", "", ""], ["Sample Heights", "1", "Allegheny County", "15209", ""], ["Sedgwick", "1", "Philadelphia County", "", ""], ["Sewickley Heights", "1", "Allegheny County", "15143", ""], ["Sconnelltown", "1", "Chester County", "19380", ""], ["Shadyside", "1", "Allegheny County", "15232", ""], ["Shepherdstown", "1", "Cumberland County", "17055", ""], ["Schuylkill Hills", "1", "Montgomery County", "19401", ""], ["Scarlan Hill", "1", "Cambria County", "", ""], ["Shalercrest", "1", "Allegheny County", "15223", ""], ["Sewickley Township", "1", "Allegheny County", "", ""], ["Savage", "1", "Somerset County", "", ""], ["Shaytown", "1", "Potter County", "", ""], ["Shenandoah Junction", "1", "Schuylkill County", "17976", ""], ["Sagon", "1", "Northumberland County", "17872", ""], ["Schoenersville", "1", "Northampton County", "", ""], ["Schuylkill Township", "1", "Schuylkill County", "", ""], ["Sabula", "1", "Clearfield County", "15801", ""], ["Sagon Junction", "1", "Northumberland County", "", ""], ["Shenandoah", "1", "Schuylkill County", "17976", ""], ["Shepherd Hills", "1", "Lehigh County", "", ""], ["Shingletown", "1", "Centre County", "16801", ""], ["Sewickley Heights Township", "1", "Allegheny County", "", ""]]	You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 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 counties in saegertown, pennsylvania?	1	128	Answer:
Table InputTable: [["Year", "Single", "Peak chart\\npositions\\nUS Country", "Peak chart\\npositions\\nCAN Country", "Album"], ["1969", "\"A World Called You\"", "23", "—", "A World Called You"], ["1970", "\"So Much in Love with You\"", "46", "—", "A World Called You"], ["1968", "\"You Touched My Heart\"", "37", "—", "A World Called You"], ["1967", "\"Forbidden Fruit\"", "—", "—", "A World Called You"], ["1968", "\"I'd Be Your Fool Again\"", "69", "—", "A World Called You"], ["1977", "\"I'm Gonna Love You Right Out of This World\"", "21", "38", "singles only"], ["1968", "\"I'm in Love with My Wife\"", "38", "—", "A World Called You"], ["1972", "\"All Heaven Breaks Loose\"", "35", "—", "single only"], ["1983", "\"You've Still Got Me\"", "71", "—", "singles only"], ["1979", "\"You're Amazing\"", "39", "—", "singles only"], ["1974", "\"Loving You Has Changed My Life\"", "9", "21", "Hey There Girl"], ["1976", "\"Mahogany Bridge\"", "84", "—", "singles only"], ["1979", "\"You Are My Rainbow\"", "36", "—", "singles only"], ["1977", "\"You and Me Alone\"", "24", "—", "Lovingly"], ["1971", "\"Ruby, You're Warm\"", "21", "16", "single only"], ["1982", "\"Crown Prince of the Barroom\"", "92", "—", "singles only"], ["1983", "\"Hold Me\"", "67", "—", "singles only"], ["1977", "\"I Love What My Woman Does to Me\"", "49", "33", "singles only"], ["1981", "\"Houston Blue\"", "88", "—", "singles only"], ["1983", "\"The Devil Is a Woman\"", "87", "—", "singles only"], ["1977", "\"Do You Hear My Heart Beat\"", "47", "—", "Lovingly"], ["1984", "\"I'm a Country Song\"", "72", "—", "singles only"], ["1969", "\"Dearly Beloved\"", "59", "—", "single only"], ["1979", "\"Darlin'\"", "18", "36", "singles only"], ["1976", "\"Whispers and Grins\"", "66", "—", "singles only"], ["1978", "\"I'll Be There (When You Get Lonely)\"", "22", "—", "Lovingly"], ["1978", "\"When a Woman Cries\"", "31", "—", "singles only"], ["1972", "\"Need You\"", "9", "9", "Need You"], ["1972", "\"Goodbye\"", "38", "—", "Need You"], ["1973", "\"It'll Be Her\"", "22", "16", "Just Thank Me"], ["1971", "\"She Don't Make Me Cry\"", "19", "9", "She Don't Make Me Cry"], ["1977", "\"The Lady and the Baby\"", "76", "—", "singles only"], ["1970", "\"I Wake Up in Heaven\"", "26", "—", "She Don't Make Me Cry"], ["1973", "\"Just Thank Me\"", "17", "18", "Just Thank Me"], ["1974", "\"Hey There Girl\"", "21", "42", "Hey There Girl"], ["1978", "\"Let's Try to Remember\"", "32", "—", "Lovingly"], ["1975", "\"It Takes a Whole Lot of Livin' in a House\"", "60", "—", "Whole Lotta Livin' in a House"], ["1974", "\"I Just Can't Help Believin'\"", "59", "—", "Hey There Girl"]]	You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 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 other albums are there besides a world called you?	6	128	Answer:
Table InputTable: [["Date", "Opponent", "Venue", "Result", "Attendance", "Scorers"], ["17 December 1960", "Aston Villa", "H", "2-4", "23,805", "Greaves (2)"], ["26 December 1960", "Manchester United", "A", "0-6", "50,213", ""], ["24 December 1960", "Manchester United", "H", "1-2", "37,601", "Brabrook"], ["21 January 1961", "West Ham United", "A", "1-3", "21,829", "Blunstone"], ["27 August 1960", "Wolverhampton Wanderers", "H", "3-3", "41,681", "Greaves (3)"], ["29 April 1961", "Nottingham Forest", "H", "4-3", "22,775", "Greaves (4)"], ["10 September 1960", "West Ham United", "H", "3-2", "37,873", "Greaves, Livesey, Blunstone"], ["25 March 1961", "Newcastle United", "A", "6-1", "28,975", "Greaves (4), Tindall (2)"], ["5 November 1960", "Newcastle United", "H", "4-2", "30,489", "Brabrook, Tindall (3)"], ["31 August 1960", "Leicester City", "A", "3-1", "21,087", "Sillett, Greaves, Brooks"], ["3 April 1961", "Tottenham Hotspur", "H", "2-3", "57,103", "Blunstone, Greaves"], ["3 September 1960", "Bolton Wanderers", "A", "1-4", "21,609", "Greaves"], ["12 November 1960", "Arsenal", "A", "4-1", "38,666", "Mortimore, Greaves, Tindall, Tambling"], ["3 December 1960", "West Bromwich Albion", "H", "7-1", "19,568", "Brabrook, Greaves (5), Tindall"], ["26 November 1960", "Nottingham Forest", "A", "1-2", "22,121", "Brabrook"], ["31 March 1961", "Tottenham Hotspur", "A", "2-4", "65,032", "Brabrook, Tindall"], ["19 November 1960", "Manchester City", "H", "6-3", "37,346", "Greaves (3), Tindall (2), Tambling"], ["18 February 1961", "Everton", "A", "1-1", "34,449", "Greaves"], ["7 September 1960", "Blackburn Rovers", "H", "5-2", "23,224", "Greaves (3), Livesey (2)"], ["17 September 1960", "Fulham", "A", "2-3", "37,423", "Livesey, Blunstone"], ["22 April 1961", "West Bromwich Albion", "A", "0-3", "17,691", ""], ["15 April 1961", "Arsenal", "H", "3-1", "38,233", "Tindall, Tambling, Neill (o.g.)"], ["19 September 1960", "Blackburn Rovers", "A", "1-3", "21,508", "Brabrook"], ["1 October 1960", "Everton", "H", "3-3", "31,457", "Greaves"], ["14 January 1961", "Bolton Wanderers", "H", "1-1", "20,461", "Livesey"], ["31 December 1960", "Wolverhampton Wanderers", "A", "1-6", "28,503", "Anderton"], ["4 February 1961", "Fulham", "H", "2-1", "39,185", "Greaves, Bridges"], ["10 December 1960", "Cardiff City", "A", "1-2", "21,840", "Greaves"], ["8 April 1961", "Manchester City", "A", "1-2", "27,720", "Tambling"], ["25 February 1961", "Sheffield Wednesday", "A", "0-1", "21,936", ""], ["20 August 1960", "Aston Villa", "A", "2-3", "43,776", "Brabrook, Gibbs"]]	You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 0, 2, 2], [10, "France", 0, 0, 1, 1]] Question: name the countries that had at least 5 gold medals Answer: Netherlands, Italy Question:which player scored the most in this season?	Greaves	128	Answer:
Table InputTable: [["Place", "Rider", "Country", "Team", "Points", "Wins"], ["16", "Gary Jones", "United States", "Yamaha", "439", "0"], ["12", "Andy Roberton", "United Kingdom", "Husqvarna", "810", "0"], ["10", "Dave Bickers", "United Kingdom", "ČZ", "1076", "0"], ["9", "Pierre Karsmakers", "Netherlands", "Husqvarna", "1110", "0"], ["8", "Gaston Rahier", "Belgium", "ČZ", "1112", "0"], ["11", "John Banks", "United Kingdom", "ČZ", "971", "0"], ["15", "Brad Lackey", "United States", "ČZ", "603", "0"], ["5", "Joel Robert", "Belgium", "Suzuki", "1730", "1"], ["18", "Chris Horsefield", "United Kingdom", "ČZ", "416", "0"], ["1", "Sylvain Geboers", "Belgium", "Suzuki", "3066", "3"], ["17", "John DeSoto", "United States", "Suzuki", "425", "0"], ["20", "Peter Lamppu", "United States", "Montesa", "309", "0"], ["3", "Torlief Hansen", "Sweden", "Husqvarna", "2052", "0"], ["19", "Uno Palm", "Sweden", "Husqvarna", "324", "0"], ["14", "Mark Blackwell", "United States", "Husqvarna", "604", "0"], ["4", "Roger De Coster", "Belgium", "Suzuki", "1865", "3"], ["7", "Willy Bauer", "Germany", "Maico", "1276", "0"], ["13", "Vlastimil Valek", "Czechoslovakia", "ČZ", "709", "0"], ["2", "Adolf Weil", "Germany", "Maico", "2331", "2"], ["6", "Heikki Mikkola", "Finland", "Husqvarna", "1680", "2"]]	You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 0, 2, 2], [10, "France", 0, 0, 1, 1]] Question: name the countries that had at least 5 gold medals Answer: Netherlands, Italy Question:what is the number of riders who scored at least 1000 points?	10	128	Answer:
Table InputTable: [["Year", "Competition", "Venue", "Position", "Event", "Notes"], ["2011", "World Championships", "Daegu, South Korea", "48th (h)", "200 m", "21.45"], ["2010", "Asian Games", "Guangzhou, China", "3rd", "200 m", "20.83"], ["2009", "World Championships", "Berlin, Germany", "25th (qf)", "200 m", "20.97"], ["2011", "Pan Arab Games", "Doha, Qatar", "3rd", "4x100 m", "40.15"], ["2008", "Olympic Games", "Beijing, China", "40th (h)", "200 m", "21.00"], ["2007", "Pan Arab Games", "Cairo, Egypt", "4th", "200 m", "20.94 (NR)"], ["2009", "Asian Championships", "Guangzhou, China", "1st", "200 m", "21.07"], ["2008", "Asian Indoor Championships", "Doha, Qatar", "4th", "60 m", "6.81"], ["2011", "Pan Arab Games", "Doha, Qatar", "5th", "100 m", "21.59"], ["2008", "World Indoor Championships", "Valencia, Spain", "28th (h)", "60 m", "6.88"], ["2009", "Asian Indoor Games", "Hanoi, Vietnam", "4th", "60 m", "6.72 (NR)"], ["2008", "World Junior Championships", "Bydgoszcz, Poland", "7th", "200 m", "21.10"], ["2011", "Asian Championships", "Kobe, Jpan", "3rd", "200 m", "20.97"]]	You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 0, 2, 2], [10, "France", 0, 0, 1, 1]] Question: name the countries that had at least 5 gold medals Answer: Netherlands, Italy Question:after the olympic games, what was the next competition he participated in?	Asian Indoor Games	128	Answer:
Table InputTable: [["Name", "Pennant", "Namesake", "Builder", "Ordered", "Laid down", "Launched", "Commissioned", "Fate"], ["Ajax", "22", "Ajax the Great", "Vickers Armstrong", "1 October 1932", "7 February 1933", "1 March 1934", "12 April 1935", "Broken up at Newport, 1949"], ["Achilles", "70", "Achilles", "Cammell Laird", "16 February 1931", "11 June 1931", "1 September 1932", "24 March 1936", "Transferred to Royal New Zealand Navy as HMNZS Achilles 1941-1946\\nSold to Indian Navy as HIMS Delhi 1948"], ["Sydney\\n(ex-Phaeton)", "48", "City of Sydney", "Swan Hunter", "10 February 1933", "8 July 1933", "22 September 1934", "24 September 1935", "Sunk in surface action, 19 November 1941"], ["Apollo", "63", "Apollo, God of Light", "HM Dockyard, Devonport", "1 March 1933", "15 August 1933", "9 October 1934", "13 January 1936", "Sold to Royal Australian Navy as HMAS Hobart, 1938\\nBroken up at Osaka, 1962"], ["Amphion", "29", "Amphion of Thebes", "HM Dockyard, Portsmouth", "1 December 1932", "22 June 1933", "27 July 1934", "15 June 1936", "Sold to Royal Australian Navy as HMAS Perth, 1939\\nSunk in torpedo attack, 1 March 1942"], ["Leander", "75", "Leander of Abydos", "HM Dockyard, Devonport", "18 February 1928", "1 August 1928", "13 July 1929", "23 July 1931", "Transferred to Royal New Zealand Navy as HMNZS Leander 1941-1945\\nBroken up at Blyth 1950"], ["Orion", "85", "Orion the Hunter", "HM Dockyard, Devonport", "24 March 1931", "26 September 1931", "24 November 1932", "18 January 1934", "Broken up at Dalmuir, 1949"], ["Neptune", "20", "Neptune, God of the Sea", "HM Dockyard, Portsmouth", "2 March 1931", "24 September 1931", "31 January 1933", "23 February 1934", "Sunk in minefield off Tripoli, 19 December 1941"]]	You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 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 previous name of ajax?	Ajax the Great	128	Answer:
Table InputTable: [["#", "Title", "Time", "Lyrics", "Music", "Producer(s)", "Performer(s)"], ["3", "\"Out Here\"", "3:18", "Boondox", "Mike E. Clark\\nTino Grosse", "Boondox", "Boondox"], ["4", "\"It Ain't A Thang\"", "3:45", "Boondox", "Mike E. Clark", "Boondox", "Boondox"], ["12", "\"Red Mist\"", "3:54", "Boondox", "Mike E. Clark", "Boondox", "Boondox\\nBlaze Ya Dead Homie\\nTwiztid"], ["8", "\"Rollin Hard\"", "4:07", "Boondox", "Mike E. Clark", "Boondox", "Boondox"], ["9", "\"The Harvest\"", "3:53", "Boondox\\nAMB", "Kuma", "Boondox\\nAMB", "Boondox\\nAxe Murder Boyz"], ["7", "\"They Pray with Snakes\"", "3:56", "Boondox", "Kuma", "Boondox", "Boondox"], ["13", "\"Angel Like\"", "3:42", "Boondox", "Mike E. Clark", "Boondox", "Boondox"], ["2", "\"Seven\"", "3:30", "Boondox", "Mike E. Clark", "Boondox", "Boondox"], ["10", "\"Sippin\"", "3:16", "Boondox", "Mike E. Clark", "Boondox", "Boondox"], ["6", "\"Lady In The Jaguar\"", "3:55", "Boondox\\nICP", "Mike E. Clark", "Boondox\\nICP", "Boondox\\nICP"], ["5", "\"Digging\"", "3:04", "Boondox", "Kuma", "Boondox", "Boondox"], ["11", "\"Lake of Fire\"", "4:12", "Boondox", "Mike E. Clark", "Boondox", "Boondox"], ["1", "\"Intro\"", "1:16", "", "", "", ""]]	You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 0, 2, 2], [10, "France", 0, 0, 1, 1]] Question: name the countries that had at least 5 gold medals Answer: Netherlands, Italy Question:all songs are over 3:00 but which song?	Intro	128	Answer:
Table InputTable: [["Round", "Pick", "Player", "Position", "Nationality", "School/Club Team"], ["1", "15", "Reggie Johnson", "PF/C", "United States", "Tennessee"], ["8", "172", "Bill Bailey", "", "United States", "Texas Pan-American"], ["6", "129", "Dean Uthoff", "", "United States", "Iowa State"], ["9", "192", "Al Williams", "", "United States", "North Texas State"], ["4", "83", "Calvin Roberts", "", "United States", "California State-Fullerton"], ["10", "209", "Steve Schall", "", "United States", "Arkansas"], ["5", "107", "Gib Hinz", "", "United States", "Wisconsin-Eau Claire"], ["3", "60", "Lavon Mercer", "", "United States", "Georgia"], ["3", "61", "Rich Yonakor", "", "United States", "North Carolina"], ["7", "153", "Allan Zahn", "", "United States", "Arkansas"], ["2", "39", "Michael Miley", "", "United States", "California State-Long Beach"]]	You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 0, 2, 2], [10, "France", 0, 0, 1, 1]] Question: name the countries that had at least 5 gold medals Answer: Netherlands, Italy Question:school attended of player picked next after bill bailey	Texas Pan-American	128	Answer:
Table InputTable: [["Contestant", "Original\\nTribe", "First\\nSwitch", "Second\\nSwitch", "Merged\\nTribe", "Finish", "Ghost\\nIsland", "Total\\nVotes"], ["Dušan Milisavljević\\n25, Zvečan", "Manobo", "Manobo", "Manobo", "Diwata", "Eliminated in Challenge\\n8th Jury Member\\nDay 53", "Locator of\\nHidden Immunity Idol\\n(Failed)\\nDay 37", "2"], ["Njegoš Arnautović\\n21, Bijeljina, Republika Srpska", "Manobo", "Ga 'dang", "Ga 'dang", "Diwata", "Eliminated in Challenge\\n7th Jury Member\\nDay 53", "Locator of\\nHidden Immunity Idol\\n(Successful)\\nDay 40", "1"], ["Vesna Đolović\\n38, Beograd", "Manobo", "Manobo", "Manobo", "Diwata", "2nd Runner-Up", "Locator of\\nHidden Immunity Idol\\n(Failed)\\nDay 46", "8"], ["Branislava Bogdanović\\n27, Kačarevo", "Manobo", "", "", "", "Eliminated in a twist\\nDay 17", "5th Eliminated\\nDay 18", "2"], ["Srđan Dinčić\\n25, Sremska Mitrovica", "Manobo", "Manobo", "Manobo", "Diwata", "15th Voted Out\\n6th Jury Member\\nDay 50", "", "7"], ["Ana Stojanovska\\n21, Skopje, Macedonia", "Manobo", "Manobo", "Manobo", "", "8th Voted Out\\nDay 28", "9th Eliminated\\nDay 30", "3"], ["Luka Rajačić\\n21, Belgrade", "Ga 'dang", "Manobo", "Manobo", "", "9th Voted Out\\nDay 31", "10th Eliminated\\nDay 32", "6"], ["Aleksandar Bošković\\n28, Belgrade", "Manobo", "Manobo", "", "", "7th Voted Out\\nDay 25", "8th Eliminated\\nDay 27", "4"], ["Gordana Berger\\n38, Belgrade", "Manobo", "", "", "", "1st Voted Out\\nDay 4", "2nd Eliminated\\nDay 12", "9"], ["Srđan Dinčić\\n25, Sremska Mitrovica", "Manobo", "Manobo", "Ga 'dang", "Diwata", "15th Voted Out\\n6th Jury Member\\nDay 50", "", "7"], ["Pece Kotevski\\n42, Bitola, Macedonia", "Ga 'dang", "Manobo", "", "", "6th Voted Out\\nDay 19", "6th Eliminated\\nDay 21", "7"], ["Nikola Kovačević\\n24, Kragujevac", "Ga 'dang", "", "", "Diwata", "11th Voted Out\\n2nd Jury Member\\nDay 38", "Ghost Island Winner\\nDay 32", "12"], ["Dina Berić\\n23, Ledinci, near Novi Sad", "Manobo", "Ga 'dang", "Manobo", "Diwata", "12th Voted Out\\n3rd Jury Member\\nDay 41", "", "6"], ["Teja Lapanja\\n30, Škofja Loka, Slovenija", "Ga 'dang", "Ga 'dang", "Ga 'dang", "Diwata", "Runner-Up", "Locator of\\nHidden Immunity Idol\\n(Failed)\\nDay 49", "1"], ["Aleksandar Krajišnik\\n19, Majur, near Šabac", "Ga 'dang", "Ga 'dang", "Ga 'dang", "Diwata", "Sole Survivor", "Locator of\\nHidden Immunity Idol\\n(Failed)\\nDay 43", "0"], ["Nemanja Vučetić\\n23, Novi Sad", "Manobo", "Ga 'dang", "Ga 'dang", "Diwata", "10th Voted Out\\n1st Jury Member\\nDay 35", "", "7"]]	You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 0, 2, 2], [10, "France", 0, 0, 1, 1]] Question: name the countries that had at least 5 gold medals Answer: Netherlands, Italy Question:how many contestants were on the original manobo tribe?	11	128	Answer:
Table InputTable: [["Year", "Title", "Role", "Notes"], ["1999", "Detention", "Orangejella LaBelle", "13 episodes"], ["1994–1999", "Sister, Sister", "Tamera Campbell", "119 episodes"], ["1995–1996", "The Adventures of Hyperman", "Emma C. Squared", "8 episodes"], ["2012", "Christmas Angel", "Daphney", ""], ["2000", "How I Loved a Macho Boy", "Jamal Santos", "3 episodes"], ["2004–2006", "Strong Medicine", "Dr. Kayla Thorton", "37 episodes"], ["1992", "True Colors", "Lorae", "1 episode"], ["2011", "Things We Do for Love", "Lourdes", "5 episodes"], ["1996", "All That", "Herself", ""], ["1991", "Flesh'n Blood", "Penelope", "1 episode"], ["1997", "Smart Guy", "Roxanne", "1 episode"], ["2006–2007", "Family Guy", "Esther", "Voice\\n3 episodes"], ["2013", "The Real", "Herself", "Host"], ["1998", "Blues Clues", "Herself", "1 episode"], ["2009", "The Super Hero Squad Show", "Misty Knight", "1 episode"], ["1995", "Are You Afraid of the Dark?", "Evil Chameleon", "1 episode"], ["2011–2013", "Tia & Tamera", "Herself", "Executive producer"], ["2009", "Roommates", "Hope", "13 episodes"], ["1994", "The All-New Mickey Mouse (MMC)", "Herself", "1 episode"], ["2011", "CHRISJayify", "Herself", "Episode: \"Drugs Are Bad\""], ["2011", "Access Hollywood Live", "Herself", "Co-host"], ["2014", "Melissa and Joey", "Gillian", "Season 3 Episode 24 'To Tell the Truth'"]]	You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 0, 2, 2], [10, "France", 0, 0, 1, 1]] Question: name the countries that had at least 5 gold medals Answer: Netherlands, Italy Question:which year had the most titles?	2011	128	Answer:
Table InputTable: [["Pick #", "Player", "Position", "Nationality", "NHL team", "College/junior/club team"], ["158", "Andy Suhy", "Defense", "United States", "Detroit Red Wings", "Western Michigan University (NCAA)"], ["163", "David Shute", "Left Wing", "United States", "Pittsburgh Penguins", "Victoria Cougars (WHL)"], ["159", "Sverre Sears", "Defense", "United States", "Philadelphia Flyers", "Princeton University (NCAA)"], ["151", "Jim Solly", "Left Wing", "Canada", "Winnipeg Jets", "Bowling Green State University (NCAA)"], ["161", "Derek Plante", "Center", "United States", "Buffalo Sabres", "Cloquet High School (USHS-MN)"], ["162", "Darcy Martini", "Defense", "Canada", "Edmonton Oilers", "Michigan Technological University (NCAA)"], ["168", "Kevin Wortman", "Defense", "United States", "Calgary Flames", "American International College (NCAA)"], ["165", "Sean Whyte", "Right Wing", "Canada", "Los Angeles Kings", "Guelph Platers (OHL)"], ["152", "Sergei Starikov", "Defense", "Soviet Union", "New Jersey Devils", "CSKA Moscow (USSR)"], ["149", "Phil Huber", "Center", "Canada", "New York Islanders", "Kamloops Blazers (WHL)"], ["160", "Greg Spenrath", "Defense", "Canada", "New York Rangers", "Tri-City Americans (WHL)"], ["153", "Milan Tichy", "Defense", "Czechoslovakia", "Chicago Blackhawks", "Prince Albert Raiders (WHL)"], ["164", "Rick Allain", "Defense", "Canada", "Boston Bruins", "Kitchener Rangers (OHL)"], ["155", "Rob Sangster", "Left Wing", "Canada", "Vancouver Canucks", "Kitchener Rangers (OHL)"], ["166", "Dean Holoien", "Right Wing", "Canada", "Washington Capitals", "Saskatoon Blades (WHL)"], ["167", "Patrick Lebeau", "Left Wing", "Canada", "Montreal Canadiens", "St-Jean Lynx (QMJHL)"], ["150", "Derek Langille", "Defense", "Canada", "Toronto Maple Leafs", "North Bay Centennials (OHL)"], ["157", "Raymond Saumier", "Right Wing", "Canada", "Hartford Whalers", "Trois Rivieres Draveurs (QMJHL)"], ["156", "Kevin Plager", "Right Wing", "United States", "St. Louis Blues", "Parkway North High School (USHS-MO)"], ["154", "Jon Pratt", "Left Wing", "United States", "Minnesota North Stars", "Pingree High School (USHS-MA)"], ["148", "Paul Krake", "Goalie", "Canada", "Quebec Nordiques", "University of Alaska Anchorage (NCAA)"]]	You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 0, 2, 2], [10, "France", 0, 0, 1, 1]] Question: name the countries that had at least 5 gold medals Answer: Netherlands, Italy Question:which position was drafted the most?	Defense	128	Answer:
Table InputTable: [["#", "Name", "Height", "Weight (lbs.)", "Position", "Class", "Hometown", "Previous Team(s)"], ["44", "Darnell Gant", "6'8\"", "215", "F", "Fr.", "Los Angeles, CA, U.S.", "Crenshaw HS"], ["21", "Artem Wallace", "6'8\"", "250", "C", "Jr.", "Toledo, WA, U.S.", "Toledo HS"], ["20", "Ryan Appleby", "6'3\"", "170", "G", "Sr.", "Stanwood, WA, U.S.", "Florida"], ["24", "Quincy Pondexter", "6'6\"", "210", "F", "So.", "Fresno, CA, U.S.", "San Joaquin Memorial HS"], ["40", "Jon Brockman", "6'7\"", "255", "F", "Jr.", "Snohomish, WA, U.S.", "Snohomish Sr. HS"], ["4", "Tim Morris", "6'4\"", "210", "G", "Sr.", "Spokane Wa, U.S.", "Central Valley HS"], ["1", "Venoy Overton", "5'11\"", "180", "G", "Fr.", "Seattle, WA, U.S.", "Franklin HS"], ["5", "Justin Dentmon", "5'11\"", "185", "G", "Jr.", "Carbondale, IL, U.S.", "Winchendon School"], ["22", "Justin Holiday", "6'6\"", "170", "F", "Fr.", "Chatsworth, CA, U.S.", "Campbell Hall School"], ["0", "Joel Smith", "6'4\"", "210", "G", "RS Jr.", "Lompoc, CA, U.S.", "Brewster Academy"], ["32", "Joe Wolfinger", "7'0\"", "255", "C", "RS So.", "Portland, OR, U.S.", "Northfield Mount Hermon School"], ["11", "Matthew Bryan-Amaning", "6'9\"", "235", "F", "Fr.", "London, England, U.K.", "South Kent School"]]	You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 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 players weigh at least 215 pounds?	5	128	Answer:
Table InputTable: [["Date", "Team", "Competition", "Round", "Leg", "Opponent", "Location", "Score"], ["August 29", "Anderlecht", "Champions League", "Qual. Round 3", "Leg 2, Home", "Fenerbahçe", "Constant Vanden Stock Stadium, Anderlecht", "0-2"], ["August 15", "Anderlecht", "Champions League", "Qual. Round 3", "Leg 1, Away", "Fenerbahçe", "Şükrü Saracoğlu Stadium, Istanbul", "0-1"], ["August 16", "Standard Liège", "UEFA Cup", "Qual. Round 2", "Leg 1, Away", "Käerjeng", "Stade Josy Barthel, Luxembourg", "3-0"], ["July 31", "Genk", "Champions League", "Qual. Round 2", "Leg 1, Home", "Sarajevo", "Cristal Arena, Genk", "1-2"], ["December 19", "Anderlecht", "UEFA Cup", "Group Stage", "Match 4, Away", "Getafe", "Coliseum Alfonso Pérez, Getafe", "1-2"], ["December 6", "Anderlecht", "UEFA Cup", "Group Stage", "Match 3, Home", "Tottenham Hotspur", "Constant Vanden Stock Stadium, Anderlecht", "1-1"], ["August 8", "Genk", "Champions League", "Qual. Round 2", "Leg 2, Away", "Sarajevo", "Asim Ferhatović Hase Stadium, Sarajevo", "1-0"], ["November 8", "Anderlecht", "UEFA Cup", "Group Stage", "Match 2, Away", "Aalborg", "Energi Nord Arena, Aalborg", "1-1"], ["February 21", "Anderlecht", "UEFA Cup", "Round of 32", "Leg 2, Away", "Bordeaux", "Stade Chaban-Delmas, Bordeaux", "1-1"], ["August 30", "Standard Liège", "UEFA Cup", "Qual. Round 2", "Leg 2, Home", "Käerjeng", "Stade Maurice Dufrasne, Liège", "1-0"], ["February 13", "Anderlecht", "UEFA Cup", "Round of 32", "Leg 1, Home", "Bordeaux", "Constant Vanden Stock Stadium, Anderlecht", "2-1"], ["March 12", "Anderlecht", "UEFA Cup", "Round of 16", "Leg 2, Away", "Bayern Munich", "Allianz Arena, Munich", "2-1"], ["March 6", "Anderlecht", "UEFA Cup", "Round of 16", "Leg 1, Home", "Bayern Munich", "Constant Vanden Stock Stadium, Anderlecht", "0-5"], ["September 20", "Club Brugge", "UEFA Cup", "Round 1", "Leg 1, Away", "Brann", "Brann Stadion, Bergen", "1-0"], ["October 25", "Anderlecht", "UEFA Cup", "Group Stage", "Match 1, Home", "Hapoel Tel Aviv", "Constant Vanden Stock Stadium, Anderlecht", "2-0"], ["September 20", "Anderlecht", "UEFA Cup", "Round 1", "Leg 1, Home", "Rapid Wien", "Constant Vanden Stock Stadium, Anderlecht", "1-1"], ["September 20", "Standard Liège", "UEFA Cup", "Round 1", "Leg 1, Away", "Zenit St. Petersburg", "Petrovsky Stadium, Saint Petersburg", "0-3"], ["October 4", "Anderlecht", "UEFA Cup", "Round 1", "Leg 2, Away", "Rapid Wien", "Gerhard Hanappi Stadium, Vienna", "1-0"], ["July 7", "Gent", "Intertoto Cup", "Round 2", "Leg 1, Home", "Cliftonville", "Jules Ottenstadion, Ghent", "2-0"], ["October 4", "Standard Liège", "UEFA Cup", "Round 1", "Leg 2, Home", "Zenit St. Petersburg", "Stade Maurice Dufrasne, Liège", "1-1"]]	You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 0, 2, 2], [10, "France", 0, 0, 1, 1]] Question: name the countries that had at least 5 gold medals Answer: Netherlands, Italy Question:how many of these games were part of the champions league competition?	4	128	Answer:
Table InputTable: [["Team", "City", "Years active", "Seasons played", "Win–loss record", "Win%", "Playoffs appearances"], ["Denver Nuggets", "Denver, Colorado", "1949–1950", "1", "11–51", ".177", "0"], ["Indianapolis Olympians", "Indianapolis, Indiana", "1949–1953", "4", "132–137", ".491", "4"], ["Indianapolis Jets", "Indianapolis, Indiana", "1948–1949", "1", "18–42", ".300", "0"], ["Pittsburgh Ironmen", "Pittsburgh, Pennsylvania", "1946–1947", "1", "15–45", ".250", "0"], ["Baltimore Bullets*", "Baltimore, Maryland", "1947–1954", "8", "158–292", ".351", "3"], ["Detroit Falcons", "Detroit, Michigan", "1946–1947", "1", "20–40", ".333", "0"], ["Anderson Packers", "Anderson, Indiana", "1949–1950", "1", "37–27", ".578", "1"], ["Cleveland Rebels", "Cleveland, Ohio", "1946–1947", "1", "30–30", ".500", "1"], ["Toronto Huskies", "Toronto, Ontario", "1946–1947", "1", "22–38", ".367", "0"], ["Waterloo Hawks", "Waterloo, Iowa", "1949–1950", "1", "19–43", ".306", "0"], ["Chicago Stags", "Chicago, Illinois", "1946–1950", "4", "145–92", ".612", "4"], ["St. Louis Bombers", "St. Louis, Missouri", "1946–1950", "4", "122–115", ".515", "3"], ["Providence Steamrollers", "Providence, Rhode Island", "1946–1949", "3", "46–122", ".274", "0"], ["BAA Indianapolis", "Indianapolis, Indiana", "Never Played", "0", "0–0", "N/A", "0"], ["BAA Buffalo", "Buffalo, New York", "Never Played", "0", "0–0", "N/A", "0"], ["Sheboygan Red Skins", "Sheboygan, Wisconsin", "1949–1950", "1", "22–40", ".355", "1"], ["Washington Capitols", "Washington, D.C.", "1946–1951", "5", "157–114", ".579", "4"]]	You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 0, 2, 2], [10, "France", 0, 0, 1, 1]] Question: name the countries that had at least 5 gold medals Answer: Netherlands, Italy Question:which defunct nba team played after 1953?	Baltimore Bullets	128	Answer:
Table InputTable: [["Year", "MVP", "Defensive Player of the Year", "Unsung Hero", "Newcomer of the Year"], ["2008", "Matt Jordan", "Nevio Pizzolitto", "Joey Gjertsen", "Stefano Pesoli"], ["2010", "Philippe Billy", "Philippe Billy", "Tony Donatelli", "Ali Gerba"], ["2011", "Hassoun Camara", "Evan Bush", "Simon Gatti", "Ian Westlake / Sinisa Ubiparipovic"], ["2007", "Leonardo Di Lorenzo", "Mauricio Vincello", "Simon Gatti", "Matt Jordan"], ["2003", "Greg Sutton", "Gabriel Gervais", "David Fronimadis", "Martin Nash"], ["2001", "Mauro Biello", "–", "–", "–"], ["1998", "Mauro Biello", "–", "–", "–"], ["2000", "Jim Larkin", "–", "–", "–"], ["2009", "David Testo", "Nevio Pizzolitto", "Adam Braz", "Stephen deRoux"], ["2002", "Eduardo Sebrango", "Gabriel Gervais", "Jason DiTullio", "Zé Roberto"], ["1997", "Mauro Biello", "–", "–", "–"], ["1993", "Patrice Ferri", "–", "–", "–"], ["2004", "Gabriel Gervais", "Greg Sutton", "Zé Roberto", "Sandro Grande"], ["2006", "Mauricio Vincello", "Gabriel Gervais", "Andrew Weber", "Leonardo Di Lorenzo"], ["1996", "Paolo Ceccarelli", "–", "–", "–"], ["1995", "Lloyd Barker", "–", "–", "–"], ["1999", "N/A", "–", "–", "–"], ["2005", "Mauro Biello", "Nevio Pizzolitto", "Mauricio Vincello", "Masahiro Fukazawa"], ["1994", "Jean Harbor", "–", "–", "–"]]	You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 0, 2, 2], [10, "France", 0, 0, 1, 1]] Question: name the countries that had at least 5 gold medals Answer: Netherlands, Italy Question:who is the player with the most mvp's?	Mauro Biello	128	Answer:
Table InputTable: [["Period", "Live births per year", "Deaths per year", "Natural change per year", "CBR", "CDR", "NC", "TFR", "IMR*"], ["1960-1965", "195 000", "89 000", "105 000", "55.5", "25.5", "30.1", "7.13", "167"], ["1950-1955", "139 000", "66 000", "74 000", "52.6", "24.8", "27.8", "6.86", "174"], ["1955-1960", "164 000", "76 000", "88 000", "53.8", "24.9", "29.0", "6.96", "171"], ["1965-1970", "229 000", "105 000", "124 000", "56.2", "25.8", "30.4", "7.32", "164"], ["1970-1975", "263 000", "121 000", "142 000", "55.8", "25.6", "30.2", "7.52", "162"], ["1990-1995", "471 000", "192 000", "279 000", "55.5", "22.7", "32.8", "7.78", "146"], ["1985-1990", "406 000", "179 000", "227 000", "55.9", "24.6", "31.3", "7.81", "155"], ["1975-1980", "301 000", "138 000", "164 000", "55.1", "25.1", "29.9", "7.63", "161"], ["1980-1985", "350 000", "157 000", "193 000", "55.4", "24.8", "30.6", "7.76", "159"], ["2005-2010", "705 000", "196 000", "509 000", "49.5", "13.8", "35.7", "7.19", "96"], ["2000-2005", "614 000", "194 000", "420 000", "51.3", "16.2", "35.1", "7.40", "113"], ["1995-2000", "538 000", "194 000", "344 000", "53.5", "19.3", "34.2", "7.60", "131"]]	You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 0, 2, 2], [10, "France", 0, 0, 1, 1]] Question: name the countries that had at least 5 gold medals Answer: Netherlands, Italy Question:number of deaths from 1950-1960	142,000	128	Answer:
Table InputTable: [["#", "Directed By", "Written By", "Original Air Date"], ["6", "John Reardon", "Neil McKay", "November 2, 1997"], ["5", "John Reardon", "Neil McKay", "October 26, 1997"], ["13", "John Reardon", "Simon J. Sharkey", "January 18, 1998"], ["11", "John Reardon", "Simon J. Sharkey", "January 4, 1998"], ["10", "John Reardon", "Simon J. Sharkey", "November 30, 1997"], ["18", "John Reardon", "Simon J. Sharkey", "February 22, 1998"], ["4", "Gerry Poulson", "David Humphries", "October 12, 1997"], ["3", "Gerry Poulson", "David Humphries", "October 5, 1997"], ["12", "Ken Horn", "David Humphries", "January 11, 1998"], ["8", "Douglas Mackinnon", "Neil McKay", "November 16, 1997"], ["9", "Douglas Mackinnon", "Neil McKay", "November 23, 1997"], ["14", "Ken Horn", "Neil McKay", "January 25, 1998"], ["16", "Douglas MacKinnon", "Neil McKay", "February 8, 1998"], ["2", "Frank W. Smith", "Simon J. Sharkey", "September 28, 1997"], ["1", "Frank W. Smith", "Simon J. Sharkey", "September 14, 1997"], ["15", "Frank W. Smith", "Dave Humphries", "February 1, 1998"], ["17", "Graham Moore", "Simon J. Sharkey", "February 15, 1998"], ["7", "Frank W. Smith", "Fran Carroll", "November 9, 1997"]]	You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 0, 2, 2], [10, "France", 0, 0, 1, 1]] Question: name the countries that had at least 5 gold medals Answer: Netherlands, Italy Question:who directed the series directly before john reardon?	Gerry Poulson	128	Answer:
Table InputTable: [["#", "Date", "Venue", "Opponent", "Score", "Result", "Competition"], ["2.", "27 March 1999", "Mestalla, Valencia, Spain", "Austria", "5–0", "9–0", "Euro 2000 qualifying"], ["1.", "27 March 1999", "Mestalla, Valencia, Spain", "Austria", "3–0", "9–0", "Euro 2000 qualifying"], ["4.", "8 September 1999", "Vivero, Badajoz, Spain", "Cyprus", "1–0", "8–0", "Euro 2000 qualifying"], ["6.", "8 September 1999", "Vivero, Badajoz, Spain", "Cyprus", "4–0", "8–0", "Euro 2000 qualifying"], ["5.", "8 September 1999", "Vivero, Badajoz, Spain", "Cyprus", "2–0", "8–0", "Euro 2000 qualifying"], ["3.", "31 March 1999", "Olimpico, Serravalle, San Marino", "San Marino", "0–3", "0–6", "Euro 2000 qualifying"], ["7.", "26 January 2000", "Cartagonova, Cartagena, Spain", "Poland", "2–0", "3–0", "Friendly"], ["8.", "26 January 2000", "Cartagonova, Cartagena, Spain", "Poland", "3–0", "3–0", "Friendly"]]	You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 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 euro 2000 qualifying competitions?	6	128	Answer:
Table InputTable: [["Year", "Award", "Film", "Result"], ["2006", "Best Supporting Actress", "Palais Royal!", "Nominated"], ["1988", "Best Actress", "Agent trouble", "Nominated"], ["1997", "Best Actress", "Les Voleurs", "Nominated"], ["1989", "Best Actress", "Drôle d'endroit pour une rencontre", "Nominated"], ["1994", "Best Actress", "Ma saison préférée", "Nominated"], ["1999", "Best Actress", "Place Vendôme", "Nominated"], ["1976", "Best Actress", "Le Sauvage", "Nominated"], ["1982", "Best Actress", "Hôtel des Amériques", "Nominated"], ["1981", "Best Actress", "Le Dernier métro", "Won"], ["1993", "Best Actress", "Indochine", "Won"], ["2011", "Best Actress", "Potiche", "Nominated"], ["2014", "Best Actress", "On My Way", "Pending"]]	You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 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 film was nominated for best supporting actress?	Palais Royal!	128	Answer:
Table InputTable: [["Number", "Name", "Term Started", "Term Ended", "Alma Mater", "Field(s)", "Educational Background"], ["7", "Dr Abdul Majid", "1997", "2001", "University of Wales", "Astrophysics", "Ph.D"], ["3", "Air Commodore K. M. Ahmad", "1979", "1980", "Pakistan Air Force Academy", "Flight Instructor", "Certificated Flight Instructor (CFI)"], ["5", "Dr M. Shafi Ahmad", "1989", "1990", "University of London", "Astronomy", "Ph.D"], ["1", "Dr Abdus Salam", "1961", "1967", "Imperial College", "Theoretical Physics", "Doctor of Philosophy (Ph.D)"], ["9", "Major General Ahmed Bilal", "2010", "Present", "Pakistan Army Corps of Signals Engineering", "Computer Engineering", "Master of Science (M.S)"], ["8", "Major General Raza Hussain", "2001", "2010", "Pakistan Army Corps of Electrical and Mechanical Engineers", "Electrical Engineering", "B.S."], ["4", "Dr Salim Mehmud", "1980", "1989", "Oak Ridge Institute for Science and Education and Oak Ridge National Laboratory", "Nuclear Engineering, Electrical engineering, Physics, Mathematics, Electronics engineering", "Ph.D"], ["2", "Air Commodore Dr Władysław Turowicz", "1967", "1979", "Warsaw University of Technology", "Aeronautical Engineering", "Ph.D"], ["6", "Engr.Sikandar Zaman", "1990", "1997", "University of Leeds", "Mechanical Engineering", "Bachelor of Science (B.S.)"]]	You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 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 previous administrator of suparco before dr. abdul majid?	Engr.Sikandar Zaman	128	Answer:
Table InputTable: [["Band", "Disc/Song", "Released", "Disc Description", "Disk Size", "Image"], ["Guns N' Roses", "Paradise City", "1989", "Shape of a Colt \"Peacemaker\"", "7\"", ""], ["The Coconuts (Side project of Kid Creole and the Coconuts)", "Did You Have To Love Me Like You Did", "1983", "In the shape of a coconut.", "7\"", ""], ["Gary Numan", "Warriors", "1983", "Shaped like a Jet Fighter.", "7\"", ""], ["Red Box", "Lean On Me b/w Stinging Bee", "1985", "Hexagonal red vinyl. Looks like a red box in 2D; flipside is a band photo.", "7\"", ""], ["OMD", "La Femme Accident", "1985", "", "", ""], ["Devo", "Beautiful World b/w Nu-Tra", "1981", "Shaped like an astronaut head", "", ""], ["The Enemy", "You're not alone", "2007", "Square shaped. Has the single cover art on the A-side and a black and white picture of the band on the B-side with track listing.", "7\"", ""], ["Kiss", "Lick It Up", "1983", "Shaped like an armored tank", "", ""], ["Men Without Hats", "I Got the Message", "1983", "", "", ""], ["Monster Magnet", "Dopes to Infinity", "1995", "Shaped like the lead singer Dave Wyndorf's head.", "12\"", ""], ["Guns N' Roses", "Nightrain", "1989", "Shape of a suitcase", "7\"", ""], ["Saxon", "Back on the Streets Again", "", "Shaped as an apple (as is printed on one side of the disk).", "7\"", ""], ["Yeah Yeah Yeahs", "Cheated Hearts", "2006", "Heart shaped.", "7\"", ""], ["Joe Strummer", "Love Kills", "", "Shaped like a gun", "7\"", "A gun"], ["Barnes & Barnes", "Fish Heads: Barnes & Barnes' Greatest Hits", "1982", "Shaped as a fish head", "12\"", ""], ["U2", "The Unforgettable Fire (single)", "1985", "Shaped as letter & number \"U2\" with various pictures of the band from the period.", "7\"", "U2"], ["Gary Numan", "Berserker", "1984", "Shaped like Numan's head.", "7\"", ""], ["Killing Joke", "Loose Cannon", "2003", "shaped yellow evil clown head image from the eponymous 2003 album sleeve", "", ""], ["The Mars Volta", "Mr. Muggs", "2008", "In the shape of a clear planchette.", "7\"", ""], ["Monster Magnet", "Negasonic Teenage Warhead", "", "Shaped like a mushroom cloud", "12\"", ""], ["Gangrene", "Sawblade EP", "2010", "In the shape of a circular sawblade.", "", ""], ["Less Than Jake", "Cheese", "1998", "Shaped like a piece of swiss cheese. 1000 pressed in yellow. 500 pressed in green (\"Moldy Version\").", "7\"", ""], ["Tangerine Dream", "Warsaw in the Sun", "1984", "The record is in the shape of Poland and has several images including Lech Wałęsa and Pope John Paul II.", "7\"", ""], ["Men Without Hats", "The Safety Dance", "1982", "Oddly shaped picture disc of a man and a woman dancing", "", ""], ["The Fat Boys", "Wipe Out", "", "Shaped like a Hamburger", "7\"", ""], ["Guns N' Roses", "Sweet Child o' Mine", "1988", "Shape of the classic logo of the cross and skulls of the five band members", "7\"", ""], ["Broken English", "Comin on Strong", "1987", "Shaped as the 3 band members wearing Ghostbusters outfits holding guitars.", "", ""]]	You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 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 released after paradise city?	Nightrain	128	Answer:
Table InputTable: [["Year", "Competition", "Venue", "Position", "Event", "Notes"], ["2006", "Commonwealth Games", "Melbourne, Australia", "4th", "Discus throw", "60.99 m"], ["2004", "Olympic Games", "Athens, Greece", "8th", "Discus throw", "62.58 m"], ["2000", "World Junior Championships", "Santiago, Chile", "1st", "Discus throw", "59.51 m"], ["2004", "African Championships", "Brazzaville, Republic of the Congo", "2nd", "Discus throw", "63.50 m"], ["2008", "African Championships", "Addis Ababa, Ethiopia", "2nd", "Discus throw", "56.98 m"], ["2003", "All-Africa Games", "Abuja, Nigeria", "2nd", "Discus throw", "62.86 m"], ["2007", "All-Africa Games", "Algiers, Algeria", "3rd", "Discus throw", "57.79 m"], ["2006", "Commonwealth Games", "Melbourne, Australia", "7th", "Shot put", "18.44 m"], ["2003", "All-Africa Games", "Abuja, Nigeria", "5th", "Shot put", "17.76 m"]]	You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 0, 2, 2], [10, "France", 0, 0, 1, 1]] Question: name the countries that had at least 5 gold medals Answer: Netherlands, Italy Question:how many events featured a distance of at least 60 in the discus throw?	4 events	128	Answer:
Table InputTable: [["#", "Player", "Goals", "Caps", "Career"], ["2", "Clint Dempsey", "36", "103", "2004–present"], ["9T", "DaMarcus Beasley", "17", "114", "2001–present"], ["1", "Landon Donovan", "57", "155", "2000–present"], ["8", "Eddie Johnson", "19", "62", "2004–present"], ["3", "Eric Wynalda", "34", "106", "1990–2000"], ["5", "Joe-Max Moore", "24", "100", "1992–2002"], ["4", "Brian McBride", "30", "95", "1993–2006"], ["6T", "Bruce Murray", "21", "86", "1985–1993"], ["9T", "Earnie Stewart", "17", "101", "1990–2004"], ["6T", "Jozy Altidore", "21", "67", "2007–present"]]	You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 0, 2, 2], [10, "France", 0, 0, 1, 1]] Question: name the countries that had at least 5 gold medals Answer: Netherlands, Italy Question:who had more caps, dempsey or beasley?	DaMarcus Beasley	128	Answer:
Table InputTable: [["Event", "Gold", "Time", "Silver", "Time", "Bronze", "Time"], ["K–2 200 m", "Hungary\\nKatalin Kovács\\nDanuta Kozák", "37.667", "Poland\\nKarolina Naja\\nMagdalena Krukowska", "38.165", "Australia\\nJoanne Brigden-Jones\\nHannah Davis", "38.369"], ["K–1 500 m", "Nicole Reinhardt (GER)", "1:47.066", "Danuta Kozák (HUN)", "1:47.396", "Inna Osypenko-Radomska (UKR)", "1:48.668"], ["K–4 500 m", "Hungary\\nGabriella Szabó\\nDanuta Kozák\\nKatalin Kovács\\nDalma Benedek", "1:36.339", "Germany\\nCarolin Leonhardt\\nSilke Hörmann\\nFranziska Weber\\nTina Dietze", "1:37.521", "Belarus\\nIryna Pamialova\\nNadzeya Papok\\nVolha Khudzenka\\nMaryna Paltaran", "1:37.887"], ["K–1 4x200 m Relay", "Germany\\nNicole Reinhardt\\nConny Wassmuth\\nTina Dietze\\nCarolin Leonhardt", "2:49.541", "Russia\\nNatalia Lobova\\nAnastasiya Sergeeva\\nNatalia Proskurina\\nSvetlana Kudinova", "2:50.207", "Poland\\nMarta Walczykiewicz\\nKarolina Naja\\nAneta Konieczna\\nEwelina Wojnarowska", "2:50.951"], ["K–1 1000 m", "Tamara Csipes (HUN)", "4:11.388", "Krisztina Fazekas Zur (USA)", "4:13.470", "Naomi Flood (AUS)", "4:14.124"], ["K–2 1000 m", "Germany\\nAnne Knorr\\nDebora Niche", "3:50.614", "Bulgaria\\nBerenike Faldum\\nDaniela Nedeva", "3:50.950", "Hungary\\nAlíz Sarudi\\nErika Medveczky", "3:53.416"], ["K–2 500 m", "Austria\\nYvonne Schuring\\nViktoria Schwarz", "1:37.071 WB", "Germany\\nFranziska Weber\\nTina Dietze", "1:37.275", "Poland\\nBeata Mikołajczyk\\nAneta Konieczna", "1:37.803"], ["K–1 200 m", "Lisa Carrington (NZL)", "39.998", "Marta Walczykiewicz (POL)", "40.472", "Inna Osypenko-Radomska (UKR)", "40.670"], ["K–1 5000 m", "Tamara Csipes (HUN)", "22:19.816", "Lani Belcher (GBR)", "22:26.572", "Maryna Paltaran (BLR)", "22:37.294"]]	You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 0, 2, 2], [10, "France", 0, 0, 1, 1]] Question: name the countries that had at least 5 gold medals Answer: Netherlands, Italy Question:what was the time for the first place medal finisher in the k-1500 m kayak event.	1:47.066	128	Answer:
Table InputTable: [["Date", "Opponents", "Venue", "Result", "Scorers", "Attendance"], ["13 Jan 1921", "Norwich City", "H", "2–0", "Wright, Cox", "4,000"], ["5 Mar 1921", "Brighton & Hove Albion", "A", "0–1", "", "8,000"], ["25 Dec 1920", "Southend United", "H", "1–1", "Dobson", "9,000"], ["30 Apr 1921", "Luton Town", "H", "2–0", "Devlin 2", "5,000"], ["9 Sep 1920", "Bristol Rovers", "H", "0–2", "", "8,000"], ["18 Sep 1920", "Plymouth Argyle", "H", "0–0", "", "8,000"], ["30 Oct 1920", "Portsmouth", "A", "2–0", "Devlin, Dobson", "13,679"], ["21 Oct 1920", "Swindon Town", "H", "0–1", "", "10,000"], ["27 Dec 1920", "Southend United", "A", "1–2", "Walker", "10,000"], ["27 Nov 1920", "Swindon Town", "A", "0–5", "", "7,000"], ["23 Oct 1920", "Portsmouth", "H", "1–0", "Devlin", "9,000"], ["26 Feb 1921", "Brighton & Hove Albion", "H", "0–4", "", "8,000"], ["2 Oct 1920", "Exeter City", "H", "2–0", "Wolstenholme 2", "8,000"], ["22 Jan 1921", "Norwich City", "A", "0–3", "", "5,000"], ["19 Mar 1921", "Grimsby Town", "A", "1–1", "Devlin", "9,000"], ["9 Apr 1921", "Swansea Town", "H", "1–1", "Walker", "6,000"], ["25 Sep 1920", "Exeter City", "A", "1–0", "Wolstenholme", "8,000"], ["23 Apr 1921", "Luton Town", "A", "2–2", "Walker, Devlin", "9,000"], ["26 Mar 1921", "Queens Park Rangers", "A", "0–2", "", "10,000"], ["5 Feb 1921", "Northampton Town", "A", "2–0", "Groves, Wright", "8,000"], ["1 Sep 1920", "Bristol Rovers", "A", "2–3", "Walker, Wolstenholme", "10,000"], ["4 Dec 1920", "Watford", "H", "0–2", "", "6,000"], ["12 Mar 1921", "Grimsby Town", "H", "2–1", "Devlin, Kelson", "8,000"], ["12 Feb 1921", "Crystal Palace", "H", "0–1", "", "12,000"], ["1 Jan 1921", "Brentford", "H", "3–1", "Dobson, Walker, Cox", "7,500"], ["2 May 1921", "Southampton", "A", "0–0", "", "6,000"], ["7 May 1921", "Southampton", "H", "0–0", "", "8,000"], ["11 Sep 1920", "Plymouth Argyle", "A", "1–5", "Wolstenholme", "12,000"], ["6 Nov 1920", "Gillingham", "H", "1–0", "Wolstenholme", "7,000"], ["19 Feb 1921", "Crystal Palace", "A", "0–2", "", "7,000"], ["18 Dec 1920", "Brentford", "A", "2–2", "Wright, Thompson", "6,000"], ["16 Apr 1921", "Swansea Town", "A", "2–1", "Dobson, Wolstenholme", "14,000"], ["11 Dec 1920", "Watford", "A", "1–5", "Wright", "7,000"], ["2 Apr 1921", "Queens Park Rangers", "H", "1–3", "Devlin", "7,500"]]	You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 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 this team's first opponent during this season?	Reading	128	Answer:
Table InputTable: [["Year", "Manufacturer", "Model", "Length (feet)", "Quantity", "Fleet Series", "Fuel Propulsion", "Powertrain"], ["1998", "NABI", "416", "40", "133", "3001-3067, 3101-3166", "Diesel", "Cummins M11E\\nAllison B400R"], ["2008", "Van Hool", "A300L", "40", "27", "1201-1227", "Diesel", "Cummins ISL\\nVoith D864.5"], ["2007", "Van Hool", "AG300", "60", "15", "2151-2165", "Diesel", "Cummins ISM\\nVoith D864.3E"], ["2008", "Van Hool", "A300K", "30", "39", "5101-5139", "Diesel", "Cummins ISB\\nVoith D854.5"], ["2003", "NABI", "40-LFW", "40", "46", "4051-4090", "Diesel", "Cummins ISL\\nAllison B400R"], ["2010", "Van Hool", "AG300", "60", "9", "2191-2199", "Diesel", "Cummins ISL\\nVoith D864.5"], ["2003", "Van Hool", "A330", "40", "110", "1001-1110", "Diesel", "Cummins ISM\\nVoith D864.3E"], ["2013", "Gillig", "Low-floor Advantage", "40", "55", "6101-6155", "Diesel", "Cummins ISL 280 HP\\nAllison B400 6-speed"], ["2003", "Van Hool", "AG300", "60", "57", "2001-2057", "Diesel", "Cummins ISM\\nVoith D864.3E"], ["2000", "NABI", "40-LFW", "40", "23", "7201-7223", "Diesel", "Cummins ISM\\nAllison B400R"], ["2007", "Van Hool", "AG300", "60", "10", "2101-2110", "Diesel", "Cummins ISL\\nVoith D864.3E"], ["2013", "Gillig", "Low-floor Advantage", "40", "65", "1301-1365", "Diesel", "Cummins ISL 280 HP \\nAllison B400 6-speed"], ["2006", "Van Hool", "A300K", "30", "50", "5001-5050", "Diesel", "Cummins ISB\\nVoith D864.3E"], ["2003", "MCI", "D4500", "45", "39", "6041-6079", "Diesel", ""], ["2005", "Van Hool", "A300FC", "40", "3", "FC1-FC3", "Hydrogen", ""], ["2013", "New Flyer", "Xcelsior D60", "60", "23", "2201-2223", "Diesel", "Cummins ISL 330 HP\\nAllison B400 6-speed"], ["1996", "New Flyer", "D60", "60 (articulated)", "30", "1901-1930", "Diesel", "Detroit Diesel Series 50\\nAllison B400R"], ["2000", "MCI", "D4500", "45", "30", "6001-6030", "Diesel", ""], ["2001", "MCI", "D4500", "45", "10", "6031-6040", "Diesel", ""], ["1999", "NABI", "40-LFW", "40", "44", "4001-4044", "Diesel", ""], ["2010", "Van Hool", "A300L FC", "40", "12", "FC4-FC16", "Hydrogen", ""], ["2008", "Van Hool", "A300K", "30", "1", "5099", "Diesel-electric hybrid", ""]]	You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 0, 2, 2], [10, "France", 0, 0, 1, 1]] Question: name the countries that had at least 5 gold medals Answer: Netherlands, Italy Question:what is the name of the last manufacturer on this chart?	Gillig	128	Answer:
Table InputTable: [["Pick #", "Player", "Position", "Nationality", "NHL team", "College/junior/club team"], ["163", "David Shute", "Left Wing", "United States", "Pittsburgh Penguins", "Victoria Cougars (WHL)"], ["167", "Patrick Lebeau", "Left Wing", "Canada", "Montreal Canadiens", "St-Jean Lynx (QMJHL)"], ["155", "Rob Sangster", "Left Wing", "Canada", "Vancouver Canucks", "Kitchener Rangers (OHL)"], ["158", "Andy Suhy", "Defense", "United States", "Detroit Red Wings", "Western Michigan University (NCAA)"], ["166", "Dean Holoien", "Right Wing", "Canada", "Washington Capitals", "Saskatoon Blades (WHL)"], ["165", "Sean Whyte", "Right Wing", "Canada", "Los Angeles Kings", "Guelph Platers (OHL)"], ["157", "Raymond Saumier", "Right Wing", "Canada", "Hartford Whalers", "Trois Rivieres Draveurs (QMJHL)"], ["151", "Jim Solly", "Left Wing", "Canada", "Winnipeg Jets", "Bowling Green State University (NCAA)"], ["153", "Milan Tichy", "Defense", "Czechoslovakia", "Chicago Blackhawks", "Prince Albert Raiders (WHL)"], ["159", "Sverre Sears", "Defense", "United States", "Philadelphia Flyers", "Princeton University (NCAA)"], ["149", "Phil Huber", "Center", "Canada", "New York Islanders", "Kamloops Blazers (WHL)"], ["168", "Kevin Wortman", "Defense", "United States", "Calgary Flames", "American International College (NCAA)"], ["164", "Rick Allain", "Defense", "Canada", "Boston Bruins", "Kitchener Rangers (OHL)"], ["156", "Kevin Plager", "Right Wing", "United States", "St. Louis Blues", "Parkway North High School (USHS-MO)"], ["162", "Darcy Martini", "Defense", "Canada", "Edmonton Oilers", "Michigan Technological University (NCAA)"], ["152", "Sergei Starikov", "Defense", "Soviet Union", "New Jersey Devils", "CSKA Moscow (USSR)"], ["160", "Greg Spenrath", "Defense", "Canada", "New York Rangers", "Tri-City Americans (WHL)"], ["150", "Derek Langille", "Defense", "Canada", "Toronto Maple Leafs", "North Bay Centennials (OHL)"], ["154", "Jon Pratt", "Left Wing", "United States", "Minnesota North Stars", "Pingree High School (USHS-MA)"], ["161", "Derek Plante", "Center", "United States", "Buffalo Sabres", "Cloquet High School (USHS-MN)"], ["148", "Paul Krake", "Goalie", "Canada", "Quebec Nordiques", "University of Alaska Anchorage (NCAA)"]]	You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 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 left wings were picked in the eighth round?	5	128	Answer:
Table InputTable: [["School", "Season", "Record", "Conference Record", "Place", "Postseason"], ["Illinois", "1917–18", "9–6", "6–6", "T4th", ""], ["Illinois", "1915–16", "13–3", "9–3", "T2nd", ""], ["Illinois", "1914–15", "16–0", "12–0", "T1st", "National Champions"], ["Illinois", "1919–20", "9–4", "8–4", "3rd", ""], ["Illinois", "1916–17", "13–3", "10–2", "T1st", "Big Ten Champions"], ["Illinois", "1912–20", "85–34", "64–31", "–", ""], ["Illinois", "1918–19", "6–8", "5–7", "5th", ""], ["Illinois", "1912–13", "10–6", "7–6", "5th", ""], ["Illinois", "1913–14", "9–4", "7–3", "3rd", ""]]	You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 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 they win more conference games, 1917-18 or 1915-16?	1915-16	128	Answer:
Table InputTable: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], ["2", "Austria", "4", "3", "4", "11"], ["9", "Germany", "1", "0", "1", "2"], ["1", "Soviet Union", "7", "3", "6", "16"], ["8", "Italy", "1", "2", "0", "3"], ["7", "Norway", "2", "1", "1", "4"], ["5", "Sweden", "2", "4", "4", "10"], ["4", "Switzerland", "3", "2", "1", "6"], ["3", "Finland", "3", "3", "1", "7"], ["6", "United States", "2", "3", "2", "7"], ["10", "Canada", "0", "1", "2", "3"]]	You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 0, 2, 2], [10, "France", 0, 0, 1, 1]] Question: name the countries that had at least 5 gold medals Answer: Netherlands, Italy Question:list each country that had 2 bronze medals.	United States, Canada	128	Answer:
Table InputTable: [["Season", "Conference", "Head Coach", "Total Wins", "Total Losses", "Total Ties", "Conference Wins", "Conference Losses", "Conference Ties", "Conference Standing", "Postseason Result"], ["2008", "Southern", "Kevin Higgins", "4", "8", "—", "2", "6", "—", "7", "—"], ["2012", "Southern", "Kevin Higgins", "7", "4", "—", "5", "3", "—", "T-4", "—"], ["2007", "Southern", "Kevin Higgins", "7", "4", "—", "4", "3", "—", "T-3", "—"], ["2009", "Southern", "Kevin Higgins", "4", "7", "—", "2", "6", "—", "7", "—"], ["2013", "Southern", "Kevin Higgins", "5", "7", "—", "4", "4", "—", "T-4", "—"], ["2010", "Southern", "Kevin Higgins", "3", "8", "—", "1", "7", "—", "T-8", "—"], ["2011", "Southern", "Kevin Higgins", "4", "7", "—", "2", "6", "—", "8", "—"], ["2006", "Southern", "Kevin Higgins", "5", "6", "—", "4", "3", "—", "4", "—"], ["1992", "Southern", "Charlie Taaffe", "11", "2", "0", "6", "1", "0", "1", "Quarterfinals"], ["2005", "Southern", "Kevin Higgins", "4", "7", "—", "2", "5", "—", "7", "—"], ["1999", "Southern", "Don Powers", "2", "9", "0", "1", "7", "0", "8", "—"], ["1996", "Southern", "Don Powers", "4", "7", "0", "3", "5", "0", "5", "—"], ["1998", "Southern", "Don Powers", "5", "6", "0", "4", "4", "0", "4", "—"], ["1988", "Southern", "Charlie Taaffe", "8", "4", "0", "5", "2", "0", "3", "First Round"], ["2000", "Southern", "Don Powers", "2", "9", "0", "1", "7", "0", "T-8", "—"], ["1997", "Southern", "Don Powers", "6", "5", "0", "4", "4", "0", "4", "—"], ["1990", "Southern", "Charlie Taaffe", "7", "5", "0", "4", "3", "0", "3", "First Round"], ["1962", "Southern", "Eddie Teague", "3", "7", "0", "1", "4", "0", "7", "—"], ["1965", "Southern", "Eddie Teague", "2", "8", "0", "2", "6", "0", "8", "—"], ["1960", "Southern", "Eddie Teague", "8", "2", "1", "4", "2", "0", "2", "Tangerine Bowl"], ["1963", "Southern", "Eddie Teague", "4", "6", "0", "2", "4", "0", "7", "—"], ["1964", "Southern", "Eddie Teague", "4", "6", "0", "4", "3", "0", "4", "—"], ["1961", "Southern", "Eddie Teague", "7", "3", "0", "5", "1", "0", "1", "—"], ["1989", "Southern", "Charlie Taaffe", "5", "5", "1", "1", "5", "1", "8", "—"], ["1958", "Southern", "Eddie Teague", "4", "6", "0", "2", "3", "0", "7", "—"], ["1959", "Southern", "Eddie Teague", "8", "2", "0", "5", "1", "0", "2", "—"], ["1942", "Southern", "Bo Rowland", "5", "2", "0", "2", "2", "0", "8", "—"]]	You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 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 coach served longer, higgins or powers?	Kevin Higgins	128	Answer:
Table InputTable: [["Season", "Age", "Overall", "Slalom", "Giant\\nSlalom", "Super G", "Downhill", "Combined"], ["2005", "18", "37", "–", "27", "18", "49", "—"], ["2013", "26", "37", "–", "17", "28", "30", "—"], ["2006", "19", "22", "–", "18", "37", "15", "—"], ["2007", "20", "33", "–", "50", "15", "23", "—"], ["2008", "21", "38", "–", "–", "35", "13", "—"], ["2004", "17", "112", "–", "–", "51", "–", "—"], ["2012", "25", "75", "–", "28", "–", "–", "—"], ["2010", "23", "28", "–", "–", "13", "23", "—"], ["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"], ["2009", "22", "9", "–", "40", "2", "5", "50"]]	You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 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 she place in the top 30 in the overall standings?	2	128	Answer:
Table InputTable: [["Year", "Rider", "Victories", "Bike", "Manufacturer's Championship"], ["2001", "Troy Bayliss", "6", "Ducati 996", "Ducati"], ["1996", "Troy Corser", "7", "Ducati 916", "Ducati"], ["1994", "Carl Fogarty", "11", "Ducati 916", "Ducati"], ["1995", "Carl Fogarty", "13", "Ducati 916", "Ducati"], ["1998", "Carl Fogarty", "3", "Ducati 916", "Ducati"], ["2000", "(Colin Edwards)", "(7)", "(Honda RC51)", "Ducati"], ["1999", "Carl Fogarty", "11", "Ducati 996", "Ducati"]]	You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 0, 2, 2], [10, "France", 0, 0, 1, 1]] Question: name the countries that had at least 5 gold medals Answer: Netherlands, Italy Question:which player has the most victories?	Carl Fogarty	128	Answer:
Table InputTable: [["Route", "Destinations", "Via", "Frequency\\n(minutes)", "Peak Hours Only", "Former"], ["16", "Train Station\\nBus Terminal", "Kingston Centre", "30", "", "(formerly Route C)"], ["14", "Train Station\\nCataraqui Town Centre / Midland Avenue", "Waterloo-Davis\\nMultiplex", "30", "", "(formerly Route A)"], ["11", "Kingston Centre\\nCataraqui Town Centre", "Bath Road\\nGardiners Town Centre", "30", "", "(formerly Route 71)"], ["7", "Dalton/Division\\nMidland/Gardiners", "Cataraqui Town Centre\\nTrain Station\\nBus Terminal", "30", "", ""], ["15", "Reddendale\\nCataraqui Town Centre - Woods", "Gardiners Town Centre", "30", "", "(formerly Route B)"], ["18", "Train Station\\nBus Terminal", "Downtown\\nQueen's University\\nSt. Lawrence College", "*", "", "Student Circuit"], ["12", "Kingston Centre\\nHighway 15", "Downtown\\nCFB Kingston (off-peak only)", "30", "", "-"], ["6", "Cataraqui Town Centre\\nSt. Lawrence College", "Gardiners Town Centre", "30", "", "Downtown"], ["4", "Princess Street", "Cataraqui Town Centre\\nDowntown", "30", "", ""], ["10", "Amherstview\\nCataraqui Town Centre", "Collins Bay Road", "30", "", "Kingston Centre"], ["9", "Downtown\\nCataraqui Town Centre", "Brock St. / Barrie St.\\nGardiners Town Centre", "20", "", ""], ["1", "Montreal Street\\nSt. Lawrence College", "Downtown", "30", "", "Cataraqui Town Centre-Woods"], ["19", "Montreal Street\\nQueen's University", "Downtown", "30", "X", ""], ["3", "Kingston Centre\\nDowntown", "Queen Mary Road\\nSt. Lawrence College\\nKing Street", "30", "", ""], ["12A", "CFB Kingston\\nDowntown", "", "30", "X", ""], ["2", "Kingston Centre\\nDivision Street", "St. Lawrence College\\nDowntown", "30", "", ""]]	You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 0, 2, 2], [10, "France", 0, 0, 1, 1]] Question: name the countries that had at least 5 gold medals Answer: Netherlands, Italy Question:what is the name of the last destination listed on this chart?	Bus Terminal	128	Answer:
Table InputTable: [["DATE", "OPPONENT", "SCORE", "TOP SCORER (Total points)", "VENUE"], ["July 13", "TANDUAY", "104-98", "", "PHILSPORTS ARENA"], ["March 9", "SHELL", "65-58", "", "PHILSPORTS ARENA"], ["October 24", "BRGY.GINEBRA", "93-72", "", "PHILSPORTS ARENA"], ["September 23 Governor's Cup", "TANDUAY", "108-93", "", "PHILSPORTS ARENA"], ["June 15", "BRGY.GINEBRA", "111-98", "", "PHILSPORTS ARENA"], ["February 28", "SAN MIGUEL", "78-76", "Lowell Briones (21)", "PHILSPORTS ARENA"], ["February 16", "ALASKA", "73-72", "Davonn Harp (20)", "PHILSPORTS ARENA"], ["April 4", "STA.LUCIA", "87-84", "", "PHILSPORTS ARENA"], ["June 10 Commissioner's Cup", "MOBILINE", "97-92", "Tony Lang (29)", "ARANETA COLISEUM"], ["February 7 All-Filipino Cup", "SHELL", "76-60", "", "PHILSPORTS ARENA"], ["June 24", "SHELL", "94-82", "", "ARANETA COLISEUM"], ["November 7", "SAN MIGUEL", "86-81", "", "ARANETA COLISEUM"], ["July 8", "STA.LUCIA", "95-88", "", "ARANETA COLISEUM"], ["July 1", "POP COLA", "95-79", "", "ARANETA COLISEUM"], ["February 11", "MOBILINE", "80-68", "", "ARANETA COLISEUM"], ["October 14", "SHELL", "68-62", "", "YNARES CENTER"], ["March 3", "BRGY.GINEBRA", "79-72", "", "ILOILO CITY"], ["October 19", "STA.LUCIA", "101-94", "", "CUNETA ASTRODOME"], ["September 29", "TALK 'N TEXT", "99-85", "", "DUMAGUETE CITY"]]	You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 0, 2, 2], [10, "France", 0, 0, 1, 1]] Question: name the countries that had at least 5 gold medals Answer: Netherlands, Italy Question:how many games were played at the philsports arena?	9	128	Answer:
Table InputTable: [["Name", "Location", "Date Formed", "Area", "Description"], ["Padre Island", "Texas\\n27°00′N 97°23′W / 27°N 97.38°W", "April 6, 1968", "130,434.27 acres (527.8 km2)", "Padre Island, the world's longest undeveloped barrier island, is a nesting ground for the Kemp's ridley sea turtle and a migratory site for Least Terns, Brown Pelicans, and Piping Plovers. Malaquite Beach provides a variety of recreational activities, and Novillo Line Camp has the remains of a cattle ranch. The military used part of the island as a bombing range during WWII."], ["Cumberland Island", "Georgia\\n30°50′N 81°27′W / 30.83°N 81.45°W", "October 23, 1972", "36,415.13 acres (147.4 km2)", "Cumberland Island is the site of the Plum Orchard estate, Thomas Carnegie's ruined Dungeness mansion, and an African Baptist church. The museum on the mainland preserves Timucua Indian history, Nathaniel Green and Eli Whitney's works, and War of 1812 battles."], ["Cape Hatteras", "North Carolina\\n35°18′N 75°31′W / 35.30°N 75.51°W", "January 12, 1953", "30,350.65 acres (122.8 km2)", "Located in the Outer Banks, Cape Hatteras is known for its Bodie Island and Cape Hatteras Lighthouses. Popular recreation activities include windsurfing, birdwatching, fishing, shell collecting, and kayaking. Constantly changing from ocean activity, this barrier island provides refuge for the endangered piping plover, seabeach amaranth, and sea turtles."], ["Point Reyes", "California\\n38°00′N 123°00′W / 38.00°N 123.00°W", "October 20, 1972", "71,067.78 acres (287.6 km2)", "Historic locations on Point Reyes Peninsula include the Point Reyes Lighthouse and Lifeboat Station and a recreated Coast Miwok village. Gray whales can be seen as they migrate near the seashore, and tule elk and elephant seals populate the wilderness area."], ["Canaveral", "Florida\\n28°46′N 80°47′W / 28.77°N 80.78°W", "January 3, 1975", "57,661.69 acres (233.3 km2)", "Adjacent to the Kennedy Space Center, this barrier island has a variety of recreational activities including hiking, boating, and fishing. The Seminole Rest features an ancient Native American mound, and Eldora Statehouse shows historic life on the lagoon. Florida's longest undeveloped Atlantic beach surrounds Mosquito Lagoon, which is home to dolphins, manatees, and sea turtles, along with a variety of sea grasses."], ["Gulf Islands", "Florida, Mississippi\\n30°22′N 86°58′W / 30.36°N 86.97°W", "January 8, 1971", "137,990.97 acres (558.4 km2)", "Seven main islands have four historic forts built by the Spanish, British, and Americans that were used for defense in the Civil War. Apache Indians once lived here, including Geronimo. There are nature trails for wildlife viewing and long beaches for snorkeling, biking, and other activities."], ["Fire Island", "New York\\n40°42′N 72°59′W / 40.70°N 72.98°W", "September 11, 1964", "19,579.47 acres (79.2 km2)", "Fire Island, a barrier island south of Long Island, has the historic William Floyd House and Fire Island Lighthouse. The beaches and dunes are complemented by a sunken forest, wetlands, and seventeen communities."], ["Cape Cod", "Massachusetts\\n41°57′N 70°00′W / 41.95°N 70.00°W", "August 7, 1961", "43,608.48 acres (176.5 km2)", "Beyond its nearly 40 miles of beaches, this historic area has Marconi Station, the Three Sisters Lighthouses, and the former North Truro Air Force Station. Cranberry bogs, marshes, and hiking trails provide a look into the flora and fauna of Cape Cod."], ["Cape Lookout", "North Carolina\\n34°37′N 76°32′W / 34.61°N 76.54°W", "March 10, 1966", "28,243.36 acres (114.3 km2)", "Cape Lookout National Seashore is made up of three islands of the Outer Banks. It is known for its wild horses and the Cape Lookout Lighthouse. Hiking, camping, fishing, and birdwatching are popular recreational activities. It is also home to two historic villages."]]	You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 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 locations are proclaim home to sea turtles?	3	128	Answer:
Table InputTable: [["Game", "Day", "Date", "Kickoff", "Opponent", "Results\\nScore", "Results\\nRecord", "Location", "Attendance"], ["2", "Sunday", "November 17", "1:05pm", "Monterrey Flash", "L 6–10", "0–2", "UniSantos Park", "363"], ["5", "Saturday", "December 14", "7:05pm", "at Sacramento Surge", "W 7–6 (OT)", "3–2", "Estadio Azteca Soccer Arena", "215"], ["14", "Friday", "February 7", "7:05pm", "at Turlock Express", "L 6–9", "7–7", "Turlock Soccer Complex", "673"], ["7", "Sunday", "December 22", "1:05pm", "Turlock Express", "W 16–8", "4–3", "UniSantos Park", "218"], ["4", "Sunday", "December 1", "1:05pm", "Ontario Fury", "W 18–4", "2–2", "UniSantos Park", "207"], ["1", "Sunday", "November 10", "3:05pm", "at Las Vegas Legends", "L 3–7", "0–1", "Orleans Arena", "1,836"], ["6", "Sunday", "December 15", "6:00pm", "at Bay Area Rosal", "L 8–9 (OT)", "3–3", "Cabernet Indoor Sports", "480"], ["15", "Saturday", "February 8", "7:05pm", "at Sacramento Surge", "W 10–6", "8–7", "Estadio Azteca Soccer Arena", "323"], ["8", "Saturday", "January 4", "7:05pm", "at Ontario Fury", "L 5–12", "4–4", "Citizens Business Bank Arena", "2,653"], ["9", "Sunday", "January 5", "1:05pm", "San Diego Sockers", "L 7–12", "4–5", "UniSantos Park", "388"], ["12", "Sunday", "January 26", "1:05pm", "Sacramento Surge", "W 20–6", "7–5", "UniSantos Park", "224"], ["13", "Saturday", "February 1", "7:05pm", "at San Diego Sockers", "L 5–6", "7–6", "Valley View Casino Center", "4,954"], ["3", "Saturday", "November 23", "7:05pm", "at Bay Area Rosal", "W 10–7", "1–2", "Cabernet Indoor Sports", "652"], ["11", "Sunday", "January 19", "1:05pm", "Bay Area Rosal", "W 17–7", "6–5", "UniSantos Park", "219"], ["16", "Saturday", "February 15♥", "5:05pm", "Bay Area Rosal", "W 27–2", "9–7", "UniSantos Park", "118"], ["10", "Sunday", "January 12", "1:05pm", "Las Vegas Legends", "W 10–7", "5–5", "UniSantos Park", "343"]]	You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 0, 2, 2], [10, "France", 0, 0, 1, 1]] Question: name the countries that had at least 5 gold medals Answer: Netherlands, Italy Question:what was the first team played against in the month of december?	Ontario Fury	128	Answer:
Table InputTable: [["name", "glyph", "C string", "Unicode", "Unicode name"], ["backspace", "", "\\\\b", "U+0008", "BACKSPACE (BS)"], ["W", "W", "W", "U+0057", "LATIN CAPITAL LETTER W"], ["alert", "", "\\\\a", "U+0007", "BELL (BEL)"], ["w", "w", "w", "U+0077", "LATIN SMALL LETTER W"], ["tab", "", "\\\\t", "U+0009", "CHARACTER TABULATION (HT)"], ["U", "U", "U", "U+0055", "LATIN CAPITAL LETTER U"], ["e", "e", "e", "U+0065", "LATIN SMALL LETTER E"], ["exclamation-mark", "!", "!", "U+0021", "EXCLAMATION MARK"], ["u", "u", "u", "U+0075", "LATIN SMALL LETTER U"], ["C", "C", "C", "U+0043", "LATIN CAPITAL LETTER C"], ["r", "r", "r", "U+0072", "LATIN SMALL LETTER R"], ["apostrophe", "'", "\\\\'", "U+0027", "APOSTROPHE"], ["K", "K", "K", "U+004B", "LATIN CAPITAL LETTER K"], ["R", "R", "R", "U+0052", "LATIN CAPITAL LETTER R"], ["c", "c", "c", "U+0063", "LATIN SMALL LETTER C"], ["X", "X", "X", "U+0058", "LATIN CAPITAL LETTER X"], ["E", "E", "E", "U+0045", "LATIN CAPITAL LETTER E"], ["v", "v", "v", "U+0076", "LATIN SMALL LETTER V"], ["L", "L", "L", "U+004C", "LATIN CAPITAL LETTER L"], ["x", "x", "x", "U+0078", "LATIN SMALL LETTER X"], ["backslash", "\\\\", "\\\\\\\\", "U+005C", "REVERSE SOLIDUS"], ["s", "s", "s", "U+0073", "LATIN SMALL LETTER S"], ["O", "O", "O", "U+004F", "LATIN CAPITAL LETTER O"], ["V", "V", "V", "U+0056", "LATIN CAPITAL LETTER V"], ["i", "i", "i", "U+0069", "LATIN SMALL LETTER I"], ["y", "y", "y", "U+0079", "LATIN SMALL LETTER Y"], ["a", "a", "a", "U+0061", "LATIN SMALL LETTER A"], ["Y", "Y", "Y", "U+0059", "LATIN CAPITAL LETTER Y"], ["A", "A", "A", "U+0041", "LATIN CAPITAL LETTER A"], ["k", "k", "k", "U+006B", "LATIN SMALL LETTER K"], ["quotation-mark", "\"", "\\\\\"", "U+0022", "QUOTATION MARK"], ["grave-accent", "`", "`", "U+0060", "GRAVE ACCENT"], ["circumflex", "^", "^", "U+005E", "CIRCUMFLEX ACCENT"], ["o", "o", "o", "U+006F", "LATIN SMALL LETTER O"], ["S", "S", "S", "U+0053", "LATIN CAPITAL LETTER S"], ["F", "F", "F", "U+0046", "LATIN CAPITAL LETTER F"], ["f", "f", "f", "U+0066", "LATIN SMALL LETTER F"], ["l", "l", "l", "U+006C", "LATIN SMALL LETTER L"], ["z", "z", "z", "U+007A", "LATIN SMALL LETTER Z"], ["t", "t", "t", "U+0074", "LATIN SMALL LETTER T"], ["J", "J", "J", "U+004A", "LATIN CAPITAL LETTER J"], ["M", "M", "M", "U+004D", "LATIN CAPITAL LETTER M"], ["I", "I", "I", "U+0049", "LATIN CAPITAL LETTER I"], ["q", "q", "q", "U+0071", "LATIN SMALL LETTER Q"], ["p", "p", "p", "U+0070", "LATIN SMALL LETTER P"], ["underscore", "_", "_", "U+005F", "LOW LINE"]]	You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 0, 2, 2], [10, "France", 0, 0, 1, 1]] Question: name the countries that had at least 5 gold medals Answer: Netherlands, Italy Question:is the unicode name for alert the same as the unicode name for backspace?	no	128	Answer:
Table InputTable: [["Year", "Single", "Peak chart\\npositions\\nUS Country", "Peak chart\\npositions\\nCAN Country", "Album"], ["1972", "\"All Heaven Breaks Loose\"", "35", "—", "single only"], ["1976", "\"Mahogany Bridge\"", "84", "—", "singles only"], ["1983", "\"Hold Me\"", "67", "—", "singles only"], ["1983", "\"You've Still Got Me\"", "71", "—", "singles only"], ["1979", "\"Darlin'\"", "18", "36", "singles only"], ["1977", "\"I'm Gonna Love You Right Out of This World\"", "21", "38", "singles only"], ["1979", "\"You Are My Rainbow\"", "36", "—", "singles only"], ["1981", "\"Houston Blue\"", "88", "—", "singles only"], ["1969", "\"Dearly Beloved\"", "59", "—", "single only"], ["1983", "\"The Devil Is a Woman\"", "87", "—", "singles only"], ["1976", "\"Whispers and Grins\"", "66", "—", "singles only"], ["1984", "\"I'm a Country Song\"", "72", "—", "singles only"], ["1979", "\"You're Amazing\"", "39", "—", "singles only"], ["1977", "\"I Love What My Woman Does to Me\"", "49", "33", "singles only"], ["1982", "\"Crown Prince of the Barroom\"", "92", "—", "singles only"], ["1978", "\"When a Woman Cries\"", "31", "—", "singles only"], ["1971", "\"Ruby, You're Warm\"", "21", "16", "single only"], ["1977", "\"The Lady and the Baby\"", "76", "—", "singles only"], ["1977", "\"You and Me Alone\"", "24", "—", "Lovingly"], ["1971", "\"She Don't Make Me Cry\"", "19", "9", "She Don't Make Me Cry"], ["1978", "\"I'll Be There (When You Get Lonely)\"", "22", "—", "Lovingly"], ["1970", "\"So Much in Love with You\"", "46", "—", "A World Called You"], ["1969", "\"A World Called You\"", "23", "—", "A World Called You"], ["1973", "\"It'll Be Her\"", "22", "16", "Just Thank Me"], ["1974", "\"Loving You Has Changed My Life\"", "9", "21", "Hey There Girl"], ["1977", "\"Do You Hear My Heart Beat\"", "47", "—", "Lovingly"], ["1970", "\"I Wake Up in Heaven\"", "26", "—", "She Don't Make Me Cry"], ["1968", "\"You Touched My Heart\"", "37", "—", "A World Called You"], ["1968", "\"I'm in Love with My Wife\"", "38", "—", "A World Called You"], ["1972", "\"Need You\"", "9", "9", "Need You"], ["1973", "\"Just Thank Me\"", "17", "18", "Just Thank Me"], ["1974", "\"Hey There Girl\"", "21", "42", "Hey There Girl"], ["1967", "\"Forbidden Fruit\"", "—", "—", "A World Called You"], ["1972", "\"Goodbye\"", "38", "—", "Need You"], ["1968", "\"I'd Be Your Fool Again\"", "69", "—", "A World Called You"], ["1978", "\"Let's Try to Remember\"", "32", "—", "Lovingly"], ["1975", "\"It Takes a Whole Lot of Livin' in a House\"", "60", "—", "Whole Lotta Livin' in a House"], ["1974", "\"I Just Can't Help Believin'\"", "59", "—", "Hey There Girl"]]	You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 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 singles are only a single and not apart of an album?	18	128	Answer:
Table InputTable: [["Pick #", "Player", "Position", "Nationality", "NHL team", "College/junior/club team"], ["158", "Andy Suhy", "Defense", "United States", "Detroit Red Wings", "Western Michigan University (NCAA)"], ["164", "Rick Allain", "Defense", "Canada", "Boston Bruins", "Kitchener Rangers (OHL)"], ["168", "Kevin Wortman", "Defense", "United States", "Calgary Flames", "American International College (NCAA)"], ["149", "Phil Huber", "Center", "Canada", "New York Islanders", "Kamloops Blazers (WHL)"], ["159", "Sverre Sears", "Defense", "United States", "Philadelphia Flyers", "Princeton University (NCAA)"], ["165", "Sean Whyte", "Right Wing", "Canada", "Los Angeles Kings", "Guelph Platers (OHL)"], ["162", "Darcy Martini", "Defense", "Canada", "Edmonton Oilers", "Michigan Technological University (NCAA)"], ["163", "David Shute", "Left Wing", "United States", "Pittsburgh Penguins", "Victoria Cougars (WHL)"], ["153", "Milan Tichy", "Defense", "Czechoslovakia", "Chicago Blackhawks", "Prince Albert Raiders (WHL)"], ["150", "Derek Langille", "Defense", "Canada", "Toronto Maple Leafs", "North Bay Centennials (OHL)"], ["166", "Dean Holoien", "Right Wing", "Canada", "Washington Capitals", "Saskatoon Blades (WHL)"], ["160", "Greg Spenrath", "Defense", "Canada", "New York Rangers", "Tri-City Americans (WHL)"], ["155", "Rob Sangster", "Left Wing", "Canada", "Vancouver Canucks", "Kitchener Rangers (OHL)"], ["151", "Jim Solly", "Left Wing", "Canada", "Winnipeg Jets", "Bowling Green State University (NCAA)"], ["157", "Raymond Saumier", "Right Wing", "Canada", "Hartford Whalers", "Trois Rivieres Draveurs (QMJHL)"], ["161", "Derek Plante", "Center", "United States", "Buffalo Sabres", "Cloquet High School (USHS-MN)"], ["152", "Sergei Starikov", "Defense", "Soviet Union", "New Jersey Devils", "CSKA Moscow (USSR)"], ["167", "Patrick Lebeau", "Left Wing", "Canada", "Montreal Canadiens", "St-Jean Lynx (QMJHL)"], ["148", "Paul Krake", "Goalie", "Canada", "Quebec Nordiques", "University of Alaska Anchorage (NCAA)"], ["156", "Kevin Plager", "Right Wing", "United States", "St. Louis Blues", "Parkway North High School (USHS-MO)"], ["154", "Jon Pratt", "Left Wing", "United States", "Minnesota North Stars", "Pingree High School (USHS-MA)"]]	You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 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 total picks in the eighth round?	21	128	Answer:
Table InputTable: [["Team", "No", "Driver", "Class", "Rounds"], ["Fortec Motorsport", "25", "George Katsinis", "", "All"], ["Fortec Motorsport", "26", "Christof von Grünigen", "", "All"], ["Mücke Motorsport", "8", "Timmy Hansen", "", "All"], ["Eifelland Racing", "18", "Facundo Regalia", "", "All"], ["Mücke Motorsport", "7", "Maciej Bernacik", "R", "All"], ["Fortec Motorsport", "24", "Jack Harvey", "", "All"], ["EuroInternational", "11", "Daniil Kvyat", "R", "All"], ["EuroInternational", "12", "Carlos Sainz, Jr.", "R", "All"], ["DAMS", "16", "Dustin Sofyan", "", "5"], ["Josef Kaufmann Racing", "4", "Robin Frijns", "", "All"], ["EuroInternational", "14", "Michael Lewis", "", "All"], ["DAMS", "17", "Fahmi Ilyas", "", "1–6"], ["DAMS", "17", "Dustin Sofyan", "", "8"], ["Eifelland Racing", "19", "Côme Ledogar", "", "All"], ["Eifelland Racing", "20", "Marc Coleselli", "R", "All"], ["Josef Kaufmann Racing", "5", "Hannes van Asseldonk", "R", "All"], ["Josef Kaufmann Racing", "6", "Petri Suvanto", "R", "All"], ["DAMS", "16", "Luciano Bacheta", "", "7–8"], ["DAMS", "15", "Javier Tarancón", "", "All"]]	You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 0, 2, 2], [10, "France", 0, 0, 1, 1]] Question: name the countries that had at least 5 gold medals Answer: Netherlands, Italy Question:what are the total number of times all appears under the rounds column?	15	128	Answer:
Table InputTable: [["Rank", "Diver", "Preliminary\\nPoints", "Preliminary\\nRank", "Final\\nPoints"], ["23", "Angela Ribeiro (BRA)", "370.68", "23", ""], ["20", "Kerstin Finke (FRG)", "393.93", "20", ""], ["24", "Rim Hassan (EGY)", "258.63", "24", ""], ["22", "Joana Figueiredo (POR)", "374.07", "22", ""], ["18", "Valerie McFarland-Beddoe (AUS)", "401.13", "18", ""], ["19", "Alison Childs (GBR)", "400.68", "19", ""], ["21", "Nicole Kreil (AUT)", "382.68", "21", ""], ["17", "Claire Izacard (FRA)", "403.17", "17", ""], ["13", "Ann Fargher (NZL)", "421.65", "13", ""], ["15", "Antonette Wilken (ZIM)", "414.66", "15", ""], ["", "Christina Seufert (USA)", "481.41", "5", "517.62"], ["11", "Anita Rossing (SWE)", "464.58", "7", "424.98"], ["14", "Tine Tollan (NOR)", "419.55", "14", ""], ["16", "Guadalupe Canseco (MEX)", "411.96", "16", ""], ["9", "Jennifer Donnet (AUS)", "432.78", "12", "443.13"], ["7", "Lesley Smith (ZIM)", "438.72", "10", "451.89"], ["6", "Elsa Tenorio (MEX)", "460.56", "8", "463.56"], ["", "Kelly McCormick (USA)", "516.75", "2", "527.46"], ["", "Sylvie Bernier (CAN)", "489.51", "3", "530.70"], ["4", "Li Yihua (CHN)", "517.92", "1", "506.52"], ["8", "Debbie Fuller (CAN)", "437.04", "11", "450.99"], ["10", "Daphne Jongejans (NED)", "487.95", "4", "437.40"], ["5", "Li Qiaoxian (CHN)", "466.83", "6", "487.68"], ["12", "Verónica Ribot (ARG)", "443.25", "9", "422.52"]]	You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 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 athlete had the least final points?	Verónica Ribot (ARG)	128	Answer:
Table InputTable: [["Name", "League", "FA Cup", "League Cup", "JP Trophy", "Total"], ["OWN GOALS", "0", "0", "0", "0", "0"], ["Scot Bennett", "5", "0", "0", "0", "5"], ["Danny Coles", "3", "0", "0", "0", "3"], ["Liam Sercombe", "1", "0", "0", "0", "1"], ["Alan Gow", "4", "0", "0", "0", "4"], ["Jamie Cureton", "20", "0", "0", "0", "20"], ["Arron Davies", "3", "0", "0", "0", "3"], ["Guillem Bauza", "2", "0", "0", "0", "2"], ["Pat Baldwin", "1", "0", "0", "0", "1"], ["Jimmy Keohane", "3", "0", "0", "0", "3"], ["John O'Flynn", "11", "0", "1", "0", "12"], ["Jake Gosling", "1", "0", "0", "0", "1"], ["Total", "0", "0", "0", "0", "0"]]	You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 0, 2, 2], [10, "France", 0, 0, 1, 1]] Question: name the countries that had at least 5 gold medals Answer: Netherlands, Italy Question:name a player that had more than 5 league goals but no other goals.	Jamie Cureton	128	Answer:
Table InputTable: [["District\\nbalance\\n[clarification needed]", "Area\\nkm2", "Area\\nsq mi", "Pop.\\n1998", "Pop.\\n2008", "Pop./km²\\n2008"], ["Saint Paul's", "11.4", "4.4", "908", "795", "69.7"], ["Blue Hill", "36.5", "14.1", "177", "153", "4.2"], ["Half Tree Hollow", "1.6", "0.6", "1,140", "901", "563.1"], ["Jamestown", "3.6", "1.4", "884", "714", "198.3"], ["Sandy Bay", "15.3", "5.9", "254", "205", "13.4"], ["Jamestown\\nHarbour", "–", "–", "20", "9", "–"], ["Total", "121.7", "47.0", "5,157", "4,255", "35.0"], ["Levelwood", "14.0", "5.4", "376", "316", "22.6"], ["Royal Mail Ship\\nSt. Helena[clarification needed]", "–", "–", "149", "171", "–"], ["Longwood", "33.4", "12.9", "960", "715", "21.4"], ["Alarm Forest", "5.9", "2.3", "289", "276", "46.8"]]	You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 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 district balance has the least 2008 population?	Jamestown Harbour	128	Answer:
Table InputTable: [["Rank", "Country", "Box Office", "Year", "Box office\\nfrom national films"], ["5", "France", "$1.7 billion", "2012", "33.3% (2013)"], ["11", "Italy", "$0.84 billion", "2013", "30% (2013)"], ["8", "Germany", "$1.3 billion", "2012", "–"], ["2", "China", "$3.6 billion", "2013", "59% (2013)"], ["12", "Brazil", "$0.72 billion", "2013", "17% (2013)"], ["4", "United Kingdom", "$1.7 billion", "2012", "36.1% (2011)"], ["9", "Russia", "$1.2 billion", "2012", "–"], ["-", "World", "$34.7 billion", "2012", "–"], ["3", "Japan", "$1.88 billion", "2013", "61% (2013)"], ["6", "South Korea", "$1.47 billion", "2013", "59.7% (2013)"], ["10", "Australia", "$1.2 billion", "2012", "4.1% (2011)"], ["7", "India", "$1.4 billion", "2012", "–"], ["1", "Canada/United States", "$10.8 billion", "2012", "–"]]	You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 0, 2, 2], [10, "France", 0, 0, 1, 1]] Question: name the countries that had at least 5 gold medals Answer: Netherlands, Italy Question:who ranks after france in the list of largest markets in the film industry by box office?	South Korea	128	Answer:
Table InputTable: [["#", "Massif", "Region", "Type of nature reserve", "Preserved area", "Buffer zone"], ["8", "Rožok", "Presov", "Presov Preserved areas", "67.1 ha", "41.4 ha"], ["10", "Havešová", "Presov", "Presov Preserved areas", "171.3 ha", "63.9 ha"], ["4", "Maramoros", "Zakarpattia", "Carpathian Biosphere Reserve", "2243.6 ha", "6230.4 ha"], ["13", "Grumsiner Forest", "Brandenburg", "Grumsiner Forest Nature Reserve", "590.1 ha", "274.3 ha"], ["11", "Jasmund", "Mecklenburg-Vorpommern", "Jasmund National Park", "492.5 ha", "2510.5 ha"], ["9", "Vihorlat", "Presov", "Presov Preserved areas", "2578 ha", "2413 ha"], ["3", "Svydovets", "Zakarpattia", "Carpathian Biosphere Reserve", "3030.5 ha", "5639.5 ha"], ["5", "Kuziy / Trybushany", "Zakarpattia", "Carpathian Biosphere Reserve", "1369.6 ha", "3163.4 ha"], ["14", "Hainich", "Thuringia", "Hainich National Park", "1573.4 ha", "4085.4 ha"], ["1", "Chornohora", "Zakarpattia", "Carpathian Biosphere Reserve", "2476.8 ha", "12925 ha"], ["15", "Kellerwald", "Hesse", "Kellerwald-Edersee National Park", "1467.1 ha", "4271.4 ha"], ["2", "Uholka / Wide Meadow", "Zakarpattia", "Carpathian Biosphere Reserve", "11860 ha", "3301 ha"], ["7", "Stužica / Bukovské vrchy", "Presov", "Poloniny National Park", "2950 ha", "11300 ha"], ["12", "Serrahn", "Mecklenburg-Vorpommern", "Müritz National Park", "268.1 ha", "2568 ha"], ["6", "Stuzhytsia / Uzhok", "Zakarpattia", "Uzh National Nature Park", "2532 ha", "3615 ha"]]	You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 0, 2, 2], [10, "France", 0, 0, 1, 1]] Question: name the countries that had at least 5 gold medals Answer: Netherlands, Italy Question:how many total massifs are there?	15	128	Answer:
Table InputTable: [["Outcome", "No.", "Date", "Tournament", "Surface", "Opponent", "Score"], ["Winner", "11.", "14 April 2013", "Grand Prix Hassan II, Casablanca, Morocco", "Clay", "Kevin Anderson", "7–6(8–6), 4–6, 6–3"], ["Runner-up", "6.", "16 September 2007", "China Open, Beijing, China", "Hard (i)", "Fernando González", "1–6, 6–3, 1–6"], ["Runner-up", "1.", "15 April 2001", "Grand Prix Hassan II, Casablanca, Morocco", "Clay", "Guillermo Cañas", "5–7, 2–6"], ["Runner-up", "5.", "14 January 2007", "Heineken Open, Auckland, New Zealand", "Hard", "David Ferrer", "4–6, 2–6"], ["Runner-up", "3.", "1 May 2005", "Estoril Open, Estoril, Portugal", "Clay", "Gastón Gaudio", "1–6, 6–2, 1–6"], ["Winner", "1.", "29 July 2001", "Orange Warsaw Open, Sopot, Poland", "Clay", "Albert Portas", "1–6, 7–5, 7–6(7–2)"], ["Runner-up", "4.", "30 April 2006", "Torneo Godó, Barcelona, Spain", "Clay", "Rafael Nadal", "4–6, 4–6, 0–6"], ["Runner-up", "2.", "20 July 2003", "Mercedes Cup, Stuttgart, Germany", "Clay", "Guillermo Coria", "2–6, 2–6, 1–6"], ["Winner", "6.", "7 October 2007", "Open de Moselle, Metz, France", "Hard (i)", "Andy Murray", "0–6, 6–2, 6–3"], ["Winner", "3.", "21 May 2006", "Hamburg Masters, Hamburg, Germany", "Clay", "Radek Štěpánek", "6–1, 6–3, 6–3"], ["Winner", "5.", "5 August 2007", "Orange Warsaw Open, Sopot, Poland (2)", "Clay", "José Acasuso", "7–5, 6–0"], ["Runner-up", "7.", "15 June 2008", "Orange Warsaw Open, Warsaw, Poland", "Clay", "Nikolay Davydenko", "3–6, 3–6"], ["Winner", "2.", "2 May 2004", "Torneo Godó, Barcelona, Spain", "Clay", "Gastón Gaudio", "6–3, 4–6, 6–2, 3–6, 6–3"], ["Winner", "4.", "16 July 2006", "Swedish Open, Båstad, Sweden", "Clay", "Nikolay Davydenko", "6–2, 6–1"], ["Winner", "10.", "6 February 2011", "Chile Open, Santiago, Chile", "Clay", "Santiago Giraldo", "6–2, 2–6, 7–6(7–5)"], ["Winner", "7.", "13 July 2008", "Swedish Open, Båstad, Sweden (2)", "Clay", "Tomáš Berdych", "6–4, 6–1"], ["Winner", "12.", "28 July 2013", "ATP Vegeta Croatia Open Umag, Umag, Croatia", "Clay", "Fabio Fognini", "6–0, 6–3"], ["Winner", "9.", "22 February 2009", "Copa Telmex, Buenos Aires, Argentina", "Clay", "Juan Mónaco", "7–5, 2–6, 7–6(7–5)"], ["Winner", "8.", "14 February 2009", "Brasil Open, Costa do Sauípe, Brazil", "Clay", "Thomaz Bellucci", "6–3, 3–6, 6–4"]]	You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 0, 2, 2], [10, "France", 0, 0, 1, 1]] Question: name the countries that had at least 5 gold medals Answer: Netherlands, Italy Question:how many days apart is the number 1 runner-up to the number 1 winner?	105	128	Answer:
Table InputTable: [["Wrestler:", "Reigns:", "Date:", "Place:", "Notes:"], ["Lanny Poffo", "1", "May 10, 1978", "San Francisco, California", "Defeated Joe Banek to become the first champion"], ["Lanny Poffo", "2", "July 21, 1979", "Lexington, Kentucky", ""], ["Lanny Poffo", "4", "January 1, 1984", "Springfield, Illinois", ""], ["Lanny Poffo", "3", "1981", "Unknown", ""], ["Paul Christy", "1", "November 13, 1983", "Springfield, Illinois", ""], ["Randy Savage", "2", "1981", "Unknown", ""], ["Randy Savage", "3", "1982", "Unknown", ""], ["Randy Savage", "1", "March 13, 1979", "Halifax, Nova Scotia", ""]]	You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 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 lanny poffo champion?	4	128	Answer:
Table InputTable: [["Episode", "Show #", "Iron Chef", "Challenger", "Challenger specialty", "Secret ingredient(s) or theme", "Winner", "Final score"], ["6", "IA0506", "Bobby Flay", "Kurt Boucher", "French-American", "Arctic char", "Bobby Flay", "46-39"], ["1", "IA0502", "Bobby Flay", "Ben Ford", "Regional American", "Blue foot chicken", "Bobby Flay", "44-35"], ["7", "IA0510", "Mario Batali", "Charles Clark", "New American", "Halibut", "Mario Batali", "51-50"], ["2", "IA0508", "Mario Batali", "Tony Liu", "Pan-European", "Opah", "Mario Batali", "55-47"], ["9", "IASP07", "Michael Symon", "Ricky Moore", "Contemporary American", "Traditional Thanksgiving", "Michael Symon", "51-43"], ["4", "IA0501", "Mario Batali", "Andrew Carmellini", "Urban Italian", "Parmigiano-Reggiano", "Mario Batali", "56-55"], ["10", "IASP08", "Cat Cora & Paula Deen", "Tyler Florence & Robert Irvine", "Southern (Deen), Contemporary American (Florence), International (Irvine)", "Sugar", "Cat Cora & Paula Deen", "49-47"], ["11", "IA0503", "Cat Cora", "Todd Richards", "Modern Southern", "Carrots", "Cat Cora", "48-46"], ["12", "IA0505", "Masaharu Morimoto", "Fortunato Nicotra", "Seasonal Italian", "Kampachi", "Masaharu Morimoto", "59-50"], ["8", "IA0507", "Cat Cora", "Mary Dumont", "French-American", "Milk and cream", "Cat Cora", "51-46"], ["3", "IA0509", "Cat Cora", "Alexandra Guarnaschelli", "French-American", "Farmers' Market", "Cat Cora", "45-41"], ["5", "IA0504", "Cat Cora", "Mark Tarbell", "Seasonal Organic", "Apples", "Mark Tarbell", "50-44"]]	You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 0, 2, 2], [10, "France", 0, 0, 1, 1]] Question: name the countries that had at least 5 gold medals Answer: Netherlands, Italy Question:how many episodes did bobby flay win?	2	128	Answer:
Table InputTable: [["Season", "Team", "Country", "Division", "Apps", "Goals"], ["2006", "Chengdu Wuniu", "China", "2", "1", "0"], ["2007", "Shandong Luneng", "China", "1", "0", "0"], ["2008", "Jiangsu Sainty", "China", "2", "24", "0"], ["2005", "Shandong Luneng", "China", "1", "0", "0"], ["2004", "Shandong Luneng", "China", "1", "0", "0"], ["2011", "Jiangsu Sainty", "China", "1", "9", "0"], ["2012", "Jiangsu Sainty", "China", "1", "0", "0"], ["2009", "Jiangsu Sainty", "China", "1", "15", "0"], ["2010", "Jiangsu Sainty", "China", "1", "17", "0"], ["2013", "Jiangsu Sainty", "China", "1", "11", "0"], ["2003", "Shandong Luneng", "China", "1", "4", "0"]]	You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 0, 2, 2], [10, "France", 0, 0, 1, 1]] Question: name the countries that had at least 5 gold medals Answer: Netherlands, Italy Question:what are the total combined apps of seasons 2006 and season 2007?	1	128	Answer:
Table InputTable: [["Season", "Age", "Overall", "Slalom", "Giant\\nSlalom", "Super G", "Downhill", "Combined"], ["2006", "19", "22", "–", "18", "37", "15", "—"], ["2005", "18", "37", "–", "27", "18", "49", "—"], ["2008", "21", "38", "–", "–", "35", "13", "—"], ["2004", "17", "112", "–", "–", "51", "–", "—"], ["2009", "22", "9", "–", "40", "2", "5", "50"], ["2012", "25", "75", "–", "28", "–", "–", "—"], ["2007", "20", "33", "–", "50", "15", "23", "—"], ["2013", "26", "37", "–", "17", "28", "30", "—"], ["2010", "23", "28", "–", "–", "13", "23", "—"], ["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"]]	You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 0, 2, 2], [10, "France", 0, 0, 1, 1]] Question: name the countries that had at least 5 gold medals Answer: Netherlands, Italy Question:how many total seasons are listed?	10	128	Answer:
Table InputTable: [["Place", "Player", "Country", "Score", "To par", "Money ($)"], ["T10", "Frank Nobilo", "New Zealand", "72-72-70-71=285", "+5", "44,184"], ["T4", "Phil Mickelson", "United States", "68-70-72-74=284", "+4", "66,633"], ["3", "Tom Lehman", "United States", "70-72-67-74=283", "+3", "131,974"], ["1", "Corey Pavin", "United States", "72-69-71-68=280", "E", "350,000"], ["T4", "Jeff Maggert", "United States", "69-72-77-66=284", "+4", "66,633"], ["T10", "Vijay Singh", "Fiji", "70-71-72-72=285", "+5", "44,184"], ["2", "Greg Norman", "Australia", "68-67-74-73=282", "+2", "207,000"], ["T4", "Neal Lancaster", "United States", "70-72-77-65=284", "+4", "66,633"], ["T4", "Bill Glasson", "United States", "69-70-76-69=284", "+4", "66,633"], ["T4", "Jay Haas", "United States", "70-73-72-69=284", "+4", "66,633"], ["T10", "Bob Tway", "United States", "69-69-72-75=285", "+5", "44,184"], ["T4", "Davis Love III", "United States", "72-68-73-71=284", "+4", "66,633"]]	You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 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 frank nobilo's total score?	285	128	Answer:
Table InputTable: [["Value", "Diameter", "Composition", "1975–1979\\nObverse", "1975–1979\\nReverse", "1981-\\nObverse", "1981-\\nReverse"], ["5 seniti", "19 mm", "Cupronickel", "Chicken with chicks", "Bananas", "Chicken with chicks", "Coconuts"], ["10 seniti", "24 mm", "Cupronickel", "King", "Grazing cattle", "King", "Bananas on tree"], ["50 seniti", "32–33 mm", "Cupronickel", "King", "Fishes around a vortex", "King", "Tomatoes"], ["20 seniti", "29 mm", "Cupronickel", "King", "Bees and hive", "King", "Yams"], ["2 seniti", "21 mm", "Bronze", "Marrows", "PLANNED FAMILIES FOOD FOR ALL, six people holding hands", "Taro", "PLANNED FAMILIES FOOD FOR ALL, six people holding hands"], ["1 seniti", "18 mm", "Bronze", "Maize", "Pig", "Maize", "Vanilla"]]	You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 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 tonga is the only one to feature chicken with chicks?	5 seniti	128	Answer:
Table InputTable: [["Wrestler:", "Times:", "Date:", "Location:", "Notes:"], ["Tigers Mask", "4", "May 19, 2013", "Osaka, Japan", "Defeated Billyken Kid in the finals of a four-man tournament to win the vacant title."], ["Billyken Kid", "2", "August 26, 2006", "Osaka, Japan", ""], ["Billyken Kid", "4", "February 11, 2010", "Osaka, Japan", ""], ["Billyken Kid", "1", "August 8, 2004", "Osaka, Japan", ""], ["Billyken Kid", "3", "February 15, 2009", "Osaka, Japan", ""], ["Billyken Kid", "5", "August 14, 2011", "Osaka, Japan", ""], ["Takehiro Murahama", "1", "May 7, 2000", "Tokyo, Japan", ""], ["Takehiro Murahama", "2", "July 6, 2003", "Osaka, Japan", ""], ["Super Delfin", "1", "January 4, 2000", "Tokyo, Japan", "Beat Dick Togo for the championship"], ["Daisuke Harada", "2", "July 22, 2012", "Osaka, Japan", ""], ["Asian Cougar / Kuuga", "1", "August 28, 2010", "Osaka, Japan", "Asian Cougar renamed himself Kuuga during his reign."], ["Dick Togo", "1", "July 25, 2009", "Osaka, Japan", ""], ["Daisuke Harada", "1", "February 26, 2012", "Osaka, Japan", ""], ["Black Buffalo", "1", "March 25, 2012", "Osaka, Japan", ""], ["Vacated", "N/A", "March 30, 2013", "Osaka, Japan", "Title vacated, after Harada announced that he was not re-signing with Osaka Pro after his contract ran out on April 29, 2013."], ["“Big Boss” MA-G-MA", "1", "October 2, 2004", "Osaka, Japan", ""], ["Super Delfin", "4", "February 26, 2006", "Osaka, Japan", ""], ["Super Delfin", "2", "June 18, 2000", "Osaka, Japan", ""], ["Tigers Mask", "1", "February 12, 2007", "Osaka, Japan", ""], ["Super Delfin", "3", "January 3, 2002", "Osaka, Japan", ""], ["Tigers Mask", "3", "April 29, 2011", "Osaka, Japan", ""], ["Hideyoshi", "1", "July 26, 2008", "Osaka, Japan", ""], ["Tigers Mask", "2", "July 29, 2010", "Osaka, Japan", ""], ["Quiet Storm", "1", "July 21, 2013", "Osaka, Japan", ""], ["Super Dolphin", "1", "February 13, 2005", "Osaka, Japan", ""], ["Zeus", "1", "January 19, 2014", "Osaka, Japan", ""], ["CIMA", "1", "June 18, 2010", "Osaka, Japan", ""], ["Daio QUALLT", "1", "April 17, 2004", "Osaka, Japan", ""], ["Gamma", "1", "June 24, 2001", "Osaka, Japan", ""]]	You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 0, 2, 2], [10, "France", 0, 0, 1, 1]] Question: name the countries that had at least 5 gold medals Answer: Netherlands, Italy Question:who won the title more times, murahama or billyken kid?	Billyken Kid	128	Answer:
Table InputTable: [["Binary", "Octal", "Decimal", "Hexadecimal", "Glyph"], ["0011 0001", "061", "49", "31", "1"], ["0011 0110", "066", "54", "36", "6"], ["0011 0100", "064", "52", "34", "4"], ["0011 0111", "067", "55", "37", "7"], ["0011 0101", "065", "53", "35", "5"], ["0011 0010", "062", "50", "32", "2"], ["0011 0000", "060", "48", "30", "0"], ["0011 0011", "063", "51", "33", "3"], ["0011 1001", "071", "57", "39", "9"], ["0011 1000", "070", "56", "38", "8"]]	You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 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 number is before 061?	060	128	Answer:
Table InputTable: [["Hull", "Type", "Original Name", "Original Operator", "Delivery", "Disposition (2012)", "2nd name", "2nd operator", "3rd Name", "3rd operator"], ["№ 5", "929-117", "Nagasaki", "JR Kyushu Jet Ferries", "Apr 1990", "Active", "Beetle 1", "JR Kyushu Jet Ferries", "", ""], ["№ 6", "929-117", "Beetle", "JR Kyushu Jet Ferries", "Jul 1990", "Active", "Rocket", "Cosmo Line", "Rocket 3", "Tane Yaku Jetfoils"], ["№ 8", "929-117", "Beetle 2", "JR Kyushu Jet Ferries", "Feb 1991", "Active", "", "", "", ""], ["№ 3", "929-117", "Toppy 1", "Tane Yaku Jetfoils", "Sep 1989", "Active", "Beetle 3", "JR Kyushu Jet Ferries", "", ""], ["№ 1", "929-117", "Tsubasa", "Sado Kisen", "Mar 1998", "Active", "", "", "", ""], ["№ 14", "929-117", "Crystal Wing", "Kaijo Access Co.", "Jun 1994", "Active", "2002 Beetle 5", "JR Kyushu Jet Ferries", "", ""], ["№ 10", "929-117", "Suisei", "Sado Kisen", "Apr 1991", "Active", "", "", "", ""], ["№ 9", "929-117", "Venus", "Kyushu Yusen", "Mar 1991", "Active", "", "", "", ""], ["№ 2", "929-117", "Pegasus", "Kyusyu Shosen Co. Ltd.", "Jun 1989", "Active", "Toppy 1", "Tane Yaku Jetfoils", "", ""], ["№ 7", "929-117", "Unicorn", "Kyusyu Shosen Co. Ltd.", "Oct 1990", "Active", "Pegasus 2", "Kyusyu Shosen Co. Ltd.", "", ""], ["№ 4", "929-117", "Princess Dacil", "Trasmediterranea", "Mar 1990", "Active", "Pegasus", "Kyusyu Shosen Co. Ltd.", "", ""], ["№ 15", "929-117", "Emerald Wing", "Kaijo Access Co.", "Jun 1994", "Active", "2004 Rocket 1", "Cosmo Line", "-", "Tane Yaku Jetfoil"], ["№ 12", "929-117", "Toppy 2", "Tane Yaku Jetfoils", "Apr 1992", "Active", "", "", "", ""], ["№ 13", "929-117", "Toppy 3", "Tane Yaku Jetfoils", "Mar 1995", "Active", "", "", "", ""], ["№ 11", "929-117", "Princess Teguise", "Trasmediterranea", "Jun 1991", "Active", "2007 Toppy 5", "Tane Yaku Jetfoils", "", ""]]	You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 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 original operators operate more boeing 929s: sado kisen or jr kyushu jet ferries?	JR Kyushu Jet Ferries	128	Answer:
Table InputTable: [["Route", "Name", "Fare Type", "Terminals", "Terminals", "Major streets", "Notes", "History"], ["34", "Naylor Rd Line", "Local", "Archives (10th St & Pennsylvania Av NW)", "Naylor Road station", "Pennsylvania Avenue SE\\nIndependence Avenue SE/SW\\nNaylor Road SE", "", "34 operated to Friendship Heights station until replaced by the M5, which operated from Naylor Road station to Eastern Market station in 2007; 34 replaced the M5 in 2008 with the extension to the Archives station, also see Pennsylvania Avenue Line"], ["32, 36", "Pennsylvania Avenue Line", "Local", "Friendship Heights station", "32 Southern Avenue station\\n36 Naylor Road station", "Wisconsin Avenue NW\\nPennsylvania Avenue SE/NW\\nBranch Avenue SE (36)\\nAlabama Avenue SE (32)", "Some weekday 32 and 36 trips terminate at:\\n\\nFarragut Square\\nFoggy Bottom – GWU station", "36 replaces a portion of the old 35 (see Pennsylvania Avenue Line)"], ["39", "Pennsylvania Avenue Metro Extra Line", "Limited Stop", "Naylor Road station", "Potomac Park (Virginia Av & 21st St NW)", "Pennsylvania Avenue SE/NW", "Weekday peak hour service only\\nAM to Potomac Park, PM to Naylor Road\\nLimited Stops Only", ""], ["60, 64", "Fort Totten-Petworth Line", "Local", "Fort Totten station", "60 Georgia Avenue – Petworth station\\n64 Federal Triangle (10th St & Constitution Av NW)", "Rock Creek Church Rd NW (60)\\nUpshur Street NW (60)\\nNew Hampshire Avenue NW (64)\\n11th Street NW (64)", "60: Monday-Friday service only", "64 was replaced by the 66 south of Georgia Avenue – Petworth station when it opened in 1999; it replaced the 66 in 2009\\n64 also runs on the old 11th Street Streetcar Line."], ["S9", "16th Street MetroExtra Line", "Limited Stop", "Silver Spring (Colesville Road & East-West Highway)", "McPherson Square station (Franklin Square Entrance)", "16th Street NW", "Weekday peak hour service only.", "S9 was introduced in 2009, replacing the former S3 & S5 lines that were discontinued in the late 1990s."], ["52, 53, 54", "14th Street Line", "Local", "Takoma station\\n14th Street & Colorado Ave NW", "52, 54 L'Enfant Plaza Metrorail Station (7th & D Streets SW)\\n53 McPherson Square station (Franklin Square Entrance)", "14th Street NW\\nPennsylvania Avenue NW (54)\\nIndependence Avenue SW (52)", "52 and 54: daily\\n53: Monday-Saturday only", "52 & 54 originally terminated at Navy Yard until the mid-1990s, when the 52 was truncated to L'Enfant Plaza station & 54 to Federal Triangle. 54 was later extended to L'Enfant Plaza station.\\nThe 53 was introduced several years after the former route 50 was discontinued, operating at first to Bureau Of Engraving before being shortened to Federal Triangle and now to Franklin Square.\\nAlso see 14th Street Line"], ["90, 92, 93", "U Street-Garfield Line", "Local*", "Duke Ellington Bridge or Frank D. Reeves Center (14th & U Streets NW)", "90 Anacostia station\\n92 Congress Heights station\\n93 Congress Heights station", "Calvert Street NW\\nU Street NW, Florida Avenue NW/NE\\n8th Street NE\\nGood Hope Road SE (92)\\nStanton Road SE (93)", "93: operates when Metrorail is not open, replacing the 90 & 94\\nFare: $1 (90 only, south of the 11th Street Bridge, unless transferring to another bus)", "90 replaced all portions of the 94 north of Anacostia station which became the 94's northern terminal after it opened in 1991; 90, 92, and 93 served McLean Gardens from the mid-1990s to the mid-2000s until replaced by the 96.\\nAlso see U Street Line, New Jersey Avenue Line and Florida Avenue Line"], ["62, 63", "Takoma-Petworth Line", "Local", "Takoma station", "62 Georgia Avenue – Petworth station\\n63 Federal Triangle (10th St & Constitution Av NW)", "5th Street NW, Kansas Avenue NW, Sherman Avenue NW (63)\\n13th Street NW (63)", "63: weekday peak & early weekend AM hours only", "63 operates through the portion of the 62 that operated to Federal Triangle until Georgia Avenue – Petworth station opened in 1999; it also replaces the 68, which operated from Georgia Avenue – Petworth station to Federal Triangle from 2001–2009"]]	You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 0, 2, 2], [10, "France", 0, 0, 1, 1]] Question: name the countries that had at least 5 gold medals Answer: Netherlands, Italy Question:tell me the number of lines that stop at the naylor road station.	3	128	Answer:
Table InputTable: [["Team", "City", "Venue", "Capacity", "Head Coach", "Team Captain", "Past Season"], ["Malavan", "Anzali", "Takhti Anzali", "8,000", "Mohammad Ahmadzadeh", "Masoud Gholamalizad", "16th"], ["Persepolis", "Tehran", "Azadi", "90,000", "Nelo Vingada", "Karim Bagheri", "Champion"], ["Foolad", "Ahvaz", "Takhti Ahvaz", "15,000", "Majid Jalali", "Ali Badavi", "Qualifier"], ["Saipa", "Karaj", "Enghelab Karaj", "15,000", "Mohammad Mayeli Kohan", "Ebrahim Sadeghi", "11th"], ["Payam", "Mashhad", "Samen", "35,000", "Kazem Ghiyasiyan", "Mehdi Hasheminasab", "Qualifier"], ["Rah Ahan", "Rey, Iran", "Rah Ahan", "15,000", "Mehdi Tartar", "Ahmad Taghavi", "12th"], ["Est. Ahvaz", "Ahvaz", "Takhti Ahvaz", "30,000", "Khodadad Azizi", "Afshin Komaei", "8th"], ["Aboomoslem", "Mashhad", "Samen", "35,000", "Ali Hanteh", "Saeed Khani", "4th"], ["Pas Hamedan", "Hamedan", "Ghods", "5,000", "Vinko Begovic", "Omid Khouraj", "5th"], ["Esteghlal", "Tehran", "Azadi", "90,000", "Amir Ghalenoei", "Farhad Majidi", "13th"], ["Mes Kerman", "Kerman", "Shahid Bahonar", "15,000", "Parviz Mazloomi", "Farzad Hosseinkhani", "10th"], ["Damash Gilan", "Rasht", "Sardar Jangal", "15,000", "Stanko Poklepović", "Mohammad Reza Mahdavi", "15th"], ["Bargh Shiraz", "Shiraz", "Hafezieh", "20,000", "Rasoul Korbekandi", "Sattar Zare", "7th"], ["Saba Qom", "Qom", "Yadegar Emam", "15,000", "Firouz Karimi", "Yahya Golmohammadi", "3rd"], ["Moghavemat", "Shiraz", "Hafezieh", "20,000", "Gholam Hossein Peyrovani", "Mostafa Sabri", "14th"], ["Paykan", "Qazvin", "Shahid Rajaei", "5,000", "Ali Asghar Modir Roosta", "Mohammad Reza Tahmasebi", "9th"], ["Zob Ahan", "Esfahan", "Foolad Shahr", "25,000", "Mansour Ebrahimzadeh", "Mohammad Salsali", "6th"], ["Sepahan", "Esfahan", "Foolad Shahr", "25,000", "Farhad Kazemi", "Moharram Navidkia", "2nd"]]	You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 0, 2, 2], [10, "France", 0, 0, 1, 1]] Question: name the countries that had at least 5 gold medals Answer: Netherlands, Italy Question:how many teams have at least 10000 capacity?	15	128	Answer:
Table InputTable: [["Season", "Team", "Record", "Head Coach", "Quarterback", "Leading Rusher", "Leading Receiver", "All-Pros", "Runner Up"], ["2005", "Seattle Seahawks", "13–3", "Mike Holmgren", "Matt Hasselbeck", "Shaun Alexander", "Bobby Engram", "Alexander, Hutchinson, Jones, Strong", "Carolina Panthers"], ["2002", "Tampa Bay Buccaneers†", "12–4", "Jon Gruden", "Brad Johnson", "Michael Pittman", "Keyshawn Johnson", "Brooks, Rice, Sapp", "Philadelphia Eagles"], ["2003", "Carolina Panthers", "11–5", "John Fox", "Jake Delhomme", "Stephen Davis", "Steve Smith", "Jenkins", "Philadelphia Eagles"], ["2006", "Chicago Bears", "13–3", "Lovie Smith", "Rex Grossman", "Thomas Jones", "Muhsin Muhammad", "Gould, Hester, Kreutz, Urlacher", "New Orleans Saints"], ["2013", "Seattle Seahawks†", "13–3", "Pete Carroll", "Russell Wilson", "Marshawn Lynch", "Golden Tate", "Sherman, Thomas", "San Francisco 49ers"], ["2004", "Philadelphia Eagles", "13–3", "Andy Reid", "Donovan McNabb", "Brian Westbrook", "Terrell Owens", "Dawkins, Owens, Sheppard", "Atlanta Falcons"], ["2000", "New York Giants", "12–4", "Jim Fassel", "Kerry Collins", "Tiki Barber", "Amani Toomer", "none", "Minnesota Vikings"], ["2011", "New York Giants†", "9–7", "Tom Coughlin", "Eli Manning", "Ahmad Bradshaw", "Victor Cruz", "Pierre-Paul", "San Francisco 49ers"], ["1998", "Atlanta Falcons", "14–2", "Dan Reeves", "Chris Chandler", "Jamal Anderson", "Tony Martin", "Anderson", "Minnesota Vikings"], ["1979", "Los Angeles Rams", "9–7", "Ray Malavasi", "Pat Haden", "Wendell Tyler", "Preston Dennard", "Brooks, Youngblood", "Tampa Bay Buccaneers"], ["1978", "Dallas Cowboys", "12–4", "Tom Landry", "Roger Staubach", "Tony Dorsett", "Tony Hill", "Harris, White", "Los Angeles Rams"], ["2009", "New Orleans Saints†", "13–3", "Sean Payton", "Drew Brees", "Pierre Thomas", "Marques Colston", "Evans", "Minnesota Vikings"], ["1975", "Dallas Cowboys", "10–4", "Tom Landry", "Roger Staubach", "Robert Newhouse", "Drew Pearson", "none", "Los Angeles Rams"], ["1977", "Dallas Cowboys†", "12–2", "Tom Landry", "Roger Staubach", "Tony Dorsett", "Drew Pearson", "Harris, Herrera, Martin, Pearson", "Minnesota Vikings"], ["1992", "Dallas Cowboys†", "13–3", "Jimmy Johnson", "Troy Aikman", "Emmitt Smith", "Michael Irvin", "Novacek, Smith", "San Francisco 49ers"], ["2001", "St. Louis Rams", "14–2", "Mike Martz", "Kurt Warner", "Marshall Faulk", "Torry Holt", "Faulk, Pace, Warner, Williams", "Philadelphia Eagles"], ["1984", "San Francisco 49ers†", "15–1", "Bill Walsh", "Joe Montana", "Wendell Tyler", "Dwight Clark", "Fahnhorst", "Chicago Bears"], ["2008", "Arizona Cardinals", "9–7", "Ken Whisenhunt", "Kurt Warner", "Edgerrin James", "Larry Fitzgerald", "Fitzgerald", "Philadelphia Eagles"], ["1999", "St. Louis Rams†", "13–3", "Dick Vermeil", "Kurt Warner", "Marshall Faulk", "Isaac Bruce", "Carter, Faulk, Pace, Warner", "Tampa Bay Buccaneers"], ["2012", "San Francisco 49ers", "11–4–1", "Jim Harbaugh", "Colin Kaepernick", "Frank Gore", "Michael Crabtree", "Bowman, Goldson, Iupati, Lee, Smith, Willis", "Atlanta Falcons"], ["1995", "Dallas Cowboys†", "12–4", "Barry Switzer", "Troy Aikman", "Emmitt Smith", "Michael Irvin", "Newton, Smith, Woodson", "Green Bay Packers"]]	You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 0, 2, 2], [10, "France", 0, 0, 1, 1]] Question: name the countries that had at least 5 gold medals Answer: Netherlands, Italy Question:which team was the latest runner-up?	San Francisco 49ers	128	Answer:
Table InputTable: [["Common name", "District", "Hebrew", "Arabic", "Population\\n(2009)", "Area\\n(km²)", "Mayor"], ["Afula", "North", "עפולה", "العفولة", "40,500", "26.909", "Avi Elkabetz"], ["Ashkelon", "South", "אשקלון", "عسقلان", "111,900", "47.788", "Benny Vaknin"], ["Eilat", "South", "אילת", "إيلات", "47,400", "84.789", "Meir Yitzhak Halevi"], ["Ramat HaSharon", "Tel Aviv", "רמת השרון", "رمات هشارون", "40,600", "16.792", "Yitzhak Rochberger"], ["Beit She'an", "North", "בית שאן", "بيسان", "16,900", "7.330", "Jacky Levi"], ["Modi'in Illit", "Judea & Samaria\\n(West Bank)", "מודיעין עילית", "موديعين عيليت", "46,200", "4.746", "Ya'akov Gutterman"], ["Kiryat Motzkin", "Haifa", "קריית מוצקין", "كريات موتسكين", "38,000", "3.778", "Haim Zuri"], ["Ramat Gan", "Tel Aviv", "רמת גן", "رمات غان", "145,000", "13.229", "Yisrael Zinger"], ["Yavne", "Center", "יבנה", "يبنة", "33,000", "10.700", "Zvi Gov-Ari"], ["Tayibe", "Center", "טייבה", "الطيبة", "36,500", "18.662", "Hemi Doron"], ["Ma'ale Adumim", "Judea & Samaria\\n(West Bank)", "מעלה אדומים", "معلي أدوميم", "34,300", "49.177", "Benny Kashriel"], ["Kiryat Bialik", "Haifa", "קריית ביאליק", "كريات بياليك", "37,300", "8.178", "Eli Dokursky"], ["Hod HaSharon", "Center", "הוד השרון", "هود هشارون", "47,200", "21.585", "Hai Adiv"], ["Beitar Illit", "Judea & Samaria\\n(West Bank)", "ביתר עילית", "بيتار عيليت", "35,000", "6.801", "Meir Rubenstein"], ["Giv'at Shmuel", "Center", "גבעת שמואל", "", "21,800", "2.579", "Yossi Brodny"], ["Beit Shemesh", "Jerusalem", "בית שמש", "بيت شيمش", "77,100", "34.259", "Moshe Abutbul"], ["Ashdod", "South", "אשדוד", "أشدود", "206,400", "47.242", "Yehiel Lasri"], ["Dimona", "South", "דימונה", "ديمونة", "32,400", "29.877", "Meir Cohen"], ["Hadera", "Haifa", "חדרה", "الخضيرة", "80,200", "49.359", "Haim Avitan"], ["Tel Aviv", "Tel Aviv", "תל אביב", "تل أبيب يافا", "403,700", "51.788", "Ron Huldai"], ["Modi'in-Maccabim-Re'ut", "Center", "מודיעין-מכבים-רעות", "موديعين-مكابيم-ريعوت", "72,700", "50.176", "Haim Beebas"], ["Rehovot", "Center", "רחובות", "رحوفوت", "112,700", "23.041", "Rahamim Malul"], ["Holon", "Tel Aviv", "חולון", "حولون", "184,700", "18.927", "Moti Sasson"]]	You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 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 mayor governs a larger population, levi or elkabetz?	Elkabetz	128	Answer:
Table InputTable: [["Episode no.", "Airdate", "Viewers", "BBC Three weekly ranking", "Multichannels rank"], ["3", "9 May 2013", "885,000", "1", "11"], ["9", "20 June 2013", "1,204,000", "6", "9"], ["8", "13 June 2013", "840,000", "5", "19"], ["1", "25 April 2013", "979,000", "2", "9"], ["6", "30 May 2013", "1,094,000", "1", "3"], ["10", "27 June 2013", "730,000", "N/A", "28"], ["4", "16 May 2013", "880,000", "1", "13"], ["2", "2 May 2013", "978,000", "1", "11"], ["11", "4 July 2013", "N/A", "N/A", "N/A"], ["12", "11 July 2013", "", "", ""], ["5", "23 May 2013", "1,092,000", "1", "5"], ["7", "6 June 2013", "975,000", "2", "6"]]	You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 0, 2, 2], [10, "France", 0, 0, 1, 1]] Question: name the countries that had at least 5 gold medals Answer: Netherlands, Italy Question:did episode 8 or episode 9 have a better bbc three weekly ranking?	8	128	Answer:
Table InputTable: [["Match no.", "Match Type", "Team Europe", "Score", "Team USA", "Progressive Total"], ["30", "Baker", "Team Europe", "202 - 203", "Team USA", "15 - 15"], ["28", "Singles", "Tore Torgersen", "206 - 275", "Doug Kent", "15 - 13"], ["29", "Singles", "Tomas Leandersson", "176 - 258", "Bill Hoffman", "15 - 14"], ["31", "Singles", "Tore Torgersen", "202 - 264", "Chris Barnes", "15 - 16"], ["25", "Singles", "Mika Koivuniemi", "217 - 279", "Chris Barnes", "14 - 11"], ["32", "Singles", "Osku Palermaa", "196 - 235", "Tommy Jones", "15 - 17"], ["26", "Singles", "Osku Palermaa", "217 - 244", "Tommy Jones", "14 - 12"], ["27", "Singles", "Paul Moor", "210 - 199", "Tim Mack", "15 - 12"]]	You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 0, 2, 2], [10, "France", 0, 0, 1, 1]] Question: name the countries that had at least 5 gold medals Answer: Netherlands, Italy Question:who was the first and only member of team europe to beat team usa during the evening session of the third day of the 2007 weber cup?	Paul Moor	128	Answer:
Table InputTable: [["ZOOM", "Cast Member 1", "Cast Member 2", "Cast Member 3", "Cast Member 4", "Cast Member 5", "Cast Member 6", "Cast Member 7"], ["Season 3 (2001)", "Frances Domond", "Kenneth \"Kenny\" Yates", "Rachel Redd", "Eric Rollins", "Kaleigh Cronin", "Kevin \"Buzz\" Barrette", "Caroline Botelho"], ["Season 7 (2005)", "W. Nick Henry", "Taylor Garron", "Francesco Tena", "Noreen Raja", "Emily Marshall", "Kyle Larrow", "Elena \"Shing Ying\" Shieh"], ["Season 2 (2000)", "Raymond \"Ray\" MacMore", "Caroline Botelho", "Claudio Schwartz", "Alisa Besher", "Jessica \"Jessie\" Ogungbadero", "Kenneth \"Kenny\" Yates", "Zoe Costello"], ["Season 6 (2004)", "Michael \"Mike\" Hansen", "Kortney Sumner", "Francesco Tena", "Cara Harvey", "Kyle Larrow", "Maya Morales", "Elena \"Shing Ying\" Shieh"], ["Season 5 (2003)", "Caroline Botelho", "Aline Toupi", "Estuardo Alvizures", "Garrett DiBona", "Michael \"Mike\" Hansen", "Kortney Sumner", "Elena \"Shing Ying\" Shieh"], ["Season 4 (2002)", "Aline Toupi", "Garrett DiBona", "Rachel Redd", "Matthew \"Matt\" Runyon", "Estuardo Alvizures", "Kaleigh Cronin", "Caroline Botelho"], ["Season 1 (1999)", "Zoe Costello", "Jared Nathan", "Keiko Yoshida", "Pablo Velez, Jr.", "Alisa Besher", "David Toropov", "Lynese Browder"]]	You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 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 cast member was killed in an accident?	Jared Nathan	128	Answer:
Table InputTable: [["Position", "Sail Number", "Yacht", "State/Country", "Yacht Type", "LOA\\n(Metres)", "Skipper", "Elapsed Time\\nd:hh:mm:ss"], ["8", "9090", "Industrial Quest", "QLD", "Nelson Marek 43", "13.11", "Kevin Miller", "3:14:58:46"], ["7", "6606", "Quest", "NSW", "Nelson Marek 46", "14.12", "Bob Steel", "3:14:41:28"], ["9", "4826", "Aspect Computing", "NSW", "Radford 16.5 Sloop", "16.50", "David Pescud", "3:15:28:24"], ["4", "AUS70", "Ragamuffin", "NSW", "Farr 50", "15.15", "Syd Fischer", "3:06:11:29"], ["3", "YC1000", "Ausmaid", "SA", "Farr 47", "14.24", "Kevan Pearce", "3:06:02:29"], ["2", "C1", "Brindabella", "NSW", "Jutson 79", "24.07", "George Snow", "2:21:55:06"], ["6", "SM1", "Fudge", "VIC", "Elliot 56", "17.07", "Peter Hansen", "3:11:00:26"], ["10", "8338", "AFR Midnight Rambler", "NSW", "Hick 35", "10.66", "Ed Psaltis\\nBob Thomas", "3:16:04:40"], ["1", "US17", "Sayonara", "USA", "Farr ILC Maxi", "24.13", "Larry Ellison", "2:19:03:32"], ["5", "COK1", "Nokia", "CI", "Farr Ketch Maxi", "25.20", "David Witt", "3:09:19:00"]]	You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 0, 2, 2], [10, "France", 0, 0, 1, 1]] Question: name the countries that had at least 5 gold medals Answer: Netherlands, Italy Question:how long did it take the industrial quest to complete the course?	3:14:58:46	128	Answer:
Table InputTable: [["#", "Title", "Featured guest(s)", "Producer(s)", "Time", "Sample (s)"], ["6", "\"Keep Hustlin\"", "E-40 & Too Short", "Young Tre", "3:39", "\"Yearning for Your Love\" by The Gap Band\\n\"Intimate Connection\" by Kleeer"], ["7", "\"Just Clownin'\"", "", "Battlecat", "3:59", "\"(Not Just) Knee Deep\" by Funkadelic\\n\"Too Tight for Light\" by Funkadelic"], ["16", "\"Better Days\"", "Ron Banks", "Barr Nine", "3:53", "\"It's Gonna Be Alright\" by Crimies"], ["12", "\"Rich Rollin'\"", "", "Dutch", "3:40", ""], ["5", "\"Can't Hold Back\"", "Ice Cube", "Skooby Doo", "3:34", "\"Ain't No Half-Steppin'\" by Big Daddy Kane"], ["11", "\"Call It What You Want\"", "", "Crazy Toones", "4:29", "\"Knucklehead\" by Grover Washington, Jr."], ["3", "\"Fuckin Wit uh House Party\"", "", "Battlecat", "4:49", "\"Hollywood Squares\" by Bootsy's Rubber Band\\n\"(Not Just) Knee Deep\" by Funkadelic"], ["15", "\"It's All Bad\"", "", "Battlecat", "4:15", "\"Chocolate City\" by Parliament"], ["17", "\"The Outcome\"", "", "Douglas Coleman", "2:45", ""], ["4", "\"The Shadiest One\"", "CJ Mac", "Ant Banks", "4:26", ""], ["13", "\"Cheddar\"", "Mack 10 & Ice Cube", "Mo-Suave-A", "4:12", "\"Gotta Get My Hands on Some (Money)\" by The Fatback Band"], ["10", "\"Like That\"", "Ice Cube, Daz Dillinger & CJ Mac", "Daz Dillinger", "4:29", "\"Just Rhymin' With Biz\" by Big Daddy Kane\\n\"West Up!\" by WC and the Maad Circle"], ["14", "\"Bank Lick\"", "", "WC", "0:49", ""], ["9", "\"Worldwide Gunnin'\"", "", "Skooby Doo", "3:25", ""], ["1", "\"Hog\"", "", "Battlecat", "4:24", "\"3 Time Felons\" by Westside Connection"], ["2", "\"Where Y'all From\"", "", "Battlecat", "1:11", ""], ["8", "\"The Autobiography\"", "", "Crazy Toones", "1:21", ""]]	You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 0, 2, 2], [10, "France", 0, 0, 1, 1]] Question: name the countries that had at least 5 gold medals Answer: Netherlands, Italy Question:how long is the shortest song?	0:49	128	Answer:
Table InputTable: [["Rank", "Lane", "Nation", "Swimmers", "Time", "Time behind", "Notes"], ["", "4", "United States", "Michael Phelps (1:46.49)\\nRyan Lochte (1:47.52)\\nPeter Vanderkaay (1:47.79)\\nKlete Keller (1:45.53)", "7:07.33", "", "AM"], ["", "5", "Australia", "Grant Hackett (1:47.50)\\nMichael Klim (1:47.62)\\nNicholas Sprenger (1:48.16)\\nIan Thorpe (1:44.18)", "7:07.46", "0.13", ""], ["5", "2", "Canada", "Brent Hayden (1:49.08)\\nBrian Johns (1:49.15)\\nAndrew Hurd (1:48.09)\\nRick Say (1:47.01)", "7:13.33", "6.00", ""], ["4", "6", "Great Britain", "Simon Burnett (1:47.90)\\nGavin Meadows (1:48.46)\\nDavid O'Brien (1:49.05)\\nRoss Davenport (1:47.19)", "7:12.60", "5.27", ""], ["", "7", "Italy", "Emiliano Brembilla (1:48.16)\\nMassimiliano Rosolino (1:46.24)\\nSimone Cercato (1:49.85)\\nFilippo Magnini (1:47.58)", "7:11.83", "4.50", ""], ["7", "8", "France", "Amaury Leveaux (1:48.57)\\nFabien Horth (1:48.67)\\nNicolas Kintz (1:50.01)\\nNicolas Rostoucher (1:50.18)", "7:17.43", "10.10", ""], ["6", "3", "Germany", "Jens Schreiber (1:49.08)\\nHeiko Hell (1:49.15)\\nLars Conrad (1:48.23)\\nChristian Keller (1:50.05)", "7:16.51", "9.18", ""], ["8", "1", "Greece", "Apostolos Antonopoulos (1:50.34)\\nDimitrios Manganas (1:51.33)\\nAndreas Zisimos (1:50.26)\\nNikolaos Xylouris (1:51.09)", "7:23.02", "15.67", ""]]	You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 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 swimmer has the fastest time?	Ian Thorpe	128	Answer:
Table InputTable: [["Year", "Single", "Peak chart positions\\nAUS", "Peak chart positions\\nAUT", "Peak chart positions\\nBEL\\n(Fl)", "Peak chart positions\\nBEL\\n(Wa)", "Peak chart positions\\nFIN", "Peak chart positions\\nFRA", "Peak chart positions\\nGER", "Peak chart positions\\nNED", "Peak chart positions\\nSWE", "Peak chart positions\\nSUI", "Certifications\\n(sales thresholds)", "Album"], ["2000", "\"My Heart Beats Like a Drum (Dam Dam Dam)\"", "76", "6", "11", "3", "12", "39", "3", "37", "38", "21", "GER: Gold", "Planet Pop"], ["2000", "\"Thinking of You\"", "—", "—", "—", "—", "—", "—", "46", "—", "—", "51", "", "Planet Pop"], ["2000", "\"Why Oh Why\"", "—", "16", "39", "15", "—", "—", "16", "—", "—", "—", "", "Planet Pop"], ["2001", "\"I'm In Heaven (When You Kiss Me)\"", "—", "27", "—", "—", "—", "—", "22", "—", "—", "31", "", "Touch the Sky"], ["2000", "\"Around the World (La La La La La)\"", "11", "1", "10", "10", "7", "12", "1", "5", "8", "1", "GER: Platinum\\nAUT: Gold\\nSWI: Gold\\nFRA: Silver", "Planet Pop"], ["2001", "\"Set Me Free\"", "—", "—", "—", "—", "—", "—", "44", "—", "—", "—", "", "Touch the Sky"], ["2001", "\"Call on Me\"", "—", "—", "—", "—", "—", "—", "—", "—", "—", "—", "", "Touch the Sky"], ["2001", "\"New York City\"", "—", "—", "—", "—", "—", "—", "—", "—", "—", "—", "", "Touch the Sky"]]	You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 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 album produced the best ranking songs?	Planet Pop	128	Answer:
Table InputTable: [["Represent", "Candidate", "in Russian", "Age", "Height", "Hometown"], ["Adygean Republic", "Alissa Joanndova", "Алисса Йоанндова", "19", "1.83 m (6 ft 0 in)", "Tulsky"], ["Jewish Autonomous Oblast", "Natalia Melckenberger", "Наталиа Мелцкенбергер", "20", "1.75 m (5 ft 9 in)", "Birobidzhan"], ["Tomsk Oblast", "Anastasija Tristova", "Анастасия Тристова", "23", "1.78 m (5 ft 10 in)", "Tomsk"], ["Chuvash Republic", "Martha Neosova", "Мартха Неосова", "19", "1.78 m (5 ft 10 in)", "Cheboksary"], ["Mordovian Republic", "Olga Stepančenko", "Олга Степанченко", "20", "1.75 m (5 ft 9 in)", "Saransk"], ["Tver Oblast", "Anastasija Prače’vysky", "Анастасия Прачеьвыскы", "19", "1.75 m (5 ft 9 in)", "Tver"], ["Moscow Oblast", "Anastasija Rodriguez", "Анастасия Родригуез", "20", "1.83 m (6 ft 0 in)", "Khimki"], ["Chechen Republic", "Carmen Jenockova", "Цармен Йеноцкова", "24", "1.80 m (5 ft 11 in)", "Urus-Martan"], ["Pskov Oblast", "Anastasija Germonova", "Анастасия Гермонова", "22", "1.75 m (5 ft 9 in)", "Pskov"], ["Tuva Republic", "Azida Levenok", "Азида Левенок", "18", "1.81 m (5 ft 11 1⁄2 in)", "Kyzyl"], ["Leningrad Oblast", "Mercedes Laplsjfda", "Мерцедес Лаплсйфда", "18", "1.79 m (5 ft 10 1⁄2 in)", "Leningrad"], ["Chelyabinsk Oblast", "Tatiana Abramenko", "Татиана Абраменко", "21", "1.74 m (5 ft 8 1⁄2 in)", "Chelyabinsk"], ["Saint Petersburg", "Maria Hernasova", "Мариа Хернасова", "20", "1.78 m (5 ft 10 in)", "Saint Petersburg"], ["Sakhalin Oblast", "Jeannette Menova", "Йеаннетте Менова", "18", "1.75 m (5 ft 9 in)", "Sakhalin"], ["Kamchatka Oblast", "Anastasija Jackson", "Анастасия Яцксон", "23", "1.76 m (5 ft 9 1⁄2 in)", "Petropavlovsk-Kamchatsky"], ["Capital City", "Natalia Varnakova", "Наталиа Варнакова", "19", "1.80 m (5 ft 11 in)", "Moscow"], ["Udmurt Republic", "Monica Zaharova", "Моница Захарова", "24", "1.81 m (5 ft 11 1⁄2 in)", "Izhevsk"], ["Buryatian Republic", "Loise Egiazarjan", "Лоисе Егиазарян", "20", "1.85 m (6 ft 1 in)", "Ulan-Ude"], ["North Ossetian Republic", "Emilianna Ninn", "Емилианна Нинн", "22", "1.76 m (5 ft 9 1⁄2 in)", "Vladikavkaz"], ["Volgograd Oblast", "Indhira Perlova", "Индхира Перлова", "21", "1.78 m (5 ft 10 in)", "Volgograd"], ["Penza Oblast", "Anna Milinzova", "Анна Милинзова", "20", "1.86 m (6 ft 1 in)", "Penza"], ["Yaroslavl Oblast", "Emely Androlevy", "Емелы Андролевы", "23", "1.73 m (5 ft 8 in)", "Yaroslavl"]]	You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 0, 2, 2], [10, "France", 0, 0, 1, 1]] Question: name the countries that had at least 5 gold medals Answer: Netherlands, Italy Question:who was the only candidate with the hometown of tulsky?	Alissa Joanndova	128	Answer:
Table InputTable: [["Year", "Competition", "Venue", "Position", "Event", "Notes"], ["2009", "Lusophony Games", "Lisbon, Portugal", "4th", "800 m", "2:07.48"], ["2011", "All-Africa Games", "Maputo, Mozambique", "12th (h)", "800 m", "2:06.72"], ["2006", "Lusophony Games", "Macau", "1st", "800 m", "2:07.34"], ["2006", "African Championships", "Bambous, Mauritius", "13th (h)", "800 m", "2:10.50"], ["2006", "Commonwealth Games", "Melbourne, Australia", "9th (sf)", "800 m", "2:01.84"], ["2009", "World Championships", "Berlin, Germany", "36th (h)", "800 m", "2:06.72"], ["2008", "African Championships", "Addis Ababa, Ethiopia", "6th", "800 m", "2:05.95"], ["2003", "All-Africa Games", "Abuja, Nigeria", "11th (h)", "800 m", "2:05.19"], ["2007", "All-Africa Games", "Algiers, Algeria", "1st", "800 m", "2:02.83"], ["2010", "African Championships", "Nairobi, Kenya", "7th", "800 m", "2:08.45"], ["2010", "Commonwealth Games", "Delhi, India", "–", "800 m", "DNF"]]	You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 0, 2, 2], [10, "France", 0, 0, 1, 1]] Question: name the countries that had at least 5 gold medals Answer: Netherlands, Italy Question:what is the last competition?	All-Africa Games	128	Answer:
Table InputTable: [["DATE", "OPPONENT", "SCORE", "TOP SCORER (Total points)", "VENUE"], ["October 24", "BRGY.GINEBRA", "93-72", "", "PHILSPORTS ARENA"], ["June 15", "BRGY.GINEBRA", "111-98", "", "PHILSPORTS ARENA"], ["February 28", "SAN MIGUEL", "78-76", "Lowell Briones (21)", "PHILSPORTS ARENA"], ["February 7 All-Filipino Cup", "SHELL", "76-60", "", "PHILSPORTS ARENA"], ["July 13", "TANDUAY", "104-98", "", "PHILSPORTS ARENA"], ["April 4", "STA.LUCIA", "87-84", "", "PHILSPORTS ARENA"], ["March 9", "SHELL", "65-58", "", "PHILSPORTS ARENA"], ["September 23 Governor's Cup", "TANDUAY", "108-93", "", "PHILSPORTS ARENA"], ["February 16", "ALASKA", "73-72", "Davonn Harp (20)", "PHILSPORTS ARENA"], ["March 3", "BRGY.GINEBRA", "79-72", "", "ILOILO CITY"], ["June 10 Commissioner's Cup", "MOBILINE", "97-92", "Tony Lang (29)", "ARANETA COLISEUM"], ["June 24", "SHELL", "94-82", "", "ARANETA COLISEUM"], ["November 7", "SAN MIGUEL", "86-81", "", "ARANETA COLISEUM"], ["July 8", "STA.LUCIA", "95-88", "", "ARANETA COLISEUM"], ["February 11", "MOBILINE", "80-68", "", "ARANETA COLISEUM"], ["October 19", "STA.LUCIA", "101-94", "", "CUNETA ASTRODOME"], ["October 14", "SHELL", "68-62", "", "YNARES CENTER"], ["July 1", "POP COLA", "95-79", "", "ARANETA COLISEUM"], ["September 29", "TALK 'N TEXT", "99-85", "", "DUMAGUETE CITY"]]	You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 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 of the top scorers listed scored the least?	Davonn Harp	128	Answer:
Table InputTable: [["#", "Date", "Venue", "Opponent", "Score", "Result", "Competition"], ["3", "September 17, 1989", "Tegucigalpa, Honduras", "El Salvador", "1–0", "1–0", "1990 World Cup qualifying"], ["2", "August 13, 1988", "St. Louis, Missouri", "Jamaica", "2–1", "5-1", "1990 World Cup qualifying"], ["8", "March 14, 1993", "Tokyo, Japan", "Japan", "1–0", "1–3", "Friendly"], ["11", "February 20, 1994", "Miami, Florida", "Sweden", "1–3", "1–0", "Friendly"], ["9", "October 16, 1993", "High Point, North Carolina", "Ukraine", "1–0", "1–2", "Friendly"], ["10", "December 5, 1993", "Los Angeles, California", "El Salvador", "5–0", "7–0", "Friendly"], ["5", "March 18, 1992", "Casablanca, Morocco", "Morocco", "1–2", "1–3", "Friendly"], ["4", "July 3, 1991", "Los Angeles, California", "Costa Rica", "2–2", "3–2", "1991 CONCACAF Gold Cup"], ["6", "April 4, 1992", "Palo Alto, California", "China PR", "1–0", "1-0", "Friendly"], ["7", "April 4, 1992", "Palo Alto, California", "China PR", "5–0", "1-0", "Friendly"], ["12", "March 26, 1994", "Dallas, Texas", "Bolivia", "1–1", "2–2", "Friendly"], ["1", "April 4, 1985", "Portland, Oregon", "Canada", "N/A", "1–1", "Friendly"]]	You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 0, 2, 2], [10, "France", 0, 0, 1, 1]] Question: name the countries that had at least 5 gold medals Answer: Netherlands, Italy Question:in what year did hugo perez score the most international goals?	1993	128	Answer:
Table InputTable: [["Year", "Car", "Start", "Qual", "Rank", "Finish", "Laps", "Led", "Retired"], ["1929", "23", "11", "112.146", "15", "17", "91", "0", "Supercharger"], ["1939", "62", "27", "121.749", "24", "11", "200", "0", "Running"], ["1928", "8", "4", "117.031", "4", "10", "200", "33", "Running"], ["1927", "27", "27", "107.765", "22", "3", "200", "0", "Running"], ["1937", "38", "7", "118.788", "16", "8", "200", "0", "Running"], ["1933", "34", "12", "113.578", "15", "7", "200", "0", "Running"], ["1931", "37", "19", "111.725", "6", "18", "167", "0", "Crash T4"], ["1938", "17", "4", "122.499", "6", "17", "130", "0", "Rod"], ["1934", "8", "7", "113.733", "13", "17", "94", "0", "Rod"], ["1930", "9", "20", "100.033", "18", "20", "79", "0", "Valve"], ["1932", "25", "20", "108.896", "34", "13", "184", "0", "Flagged"], ["1935", "44", "6", "115.459", "11", "21", "102", "0", "Magneto"], ["Totals", "Totals", "Totals", "Totals", "Totals", "Totals", "1989", "33", ""], ["1926", "31", "12", "102.789", "13", "11", "142", "0", "Flagged"]]	You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 0, 2, 2], [10, "France", 0, 0, 1, 1]] Question: name the countries that had at least 5 gold medals Answer: Netherlands, Italy Question:what is the average number of laps driven in the indianapolis 500 in tony gulotta's career?	153	128	Answer:
Table InputTable: [["Representative", "Years", "State", "Party", "Lifespan"], ["William Kent", "1911–1913", "California", "Progressive Republican", "1864–1928"], ["Ric Keller", "2001–2009", "Florida", "Republican", "1964–"], ["John Weinland Killinger", "1859–1863\\n1871–1875\\n1877–1881", "Pennsylvania", "Republican", "1824–1896"], ["Robert P. Kennedy", "1887–1891", "Ohio", "Republican", "1840–1918"], ["Julius Kahn", "1899–1903\\n1905–1924", "California", "Republican", "1861–1924"], ["Charles Edward Kiefner", "1925–1927\\n1929–1931", "Missouri", "Republican", "1869–1942"], ["John Henry Kyl", "1959–1965\\n1967–1973", "Iowa", "Republican", "1919–2002"], ["John A. Kasson", "1863–1867\\n1873–1877\\n1881–1884", "Iowa", "Republican", "1822–1910"], ["Peter H. Kostmayer", "1977–1981\\n1983–1993", "Pennsylvania", "Democratic", "1946–"], ["John Leeds Kerr", "1825–1829\\n1831–1833", "Maryland", "National Republican", "1780–1844"], ["Harrison Kelley", "1889–1891", "Kansas", "Republican", "1836–1897"], ["Bob Kasten", "1975–1979", "Wisconsin", "Republican", "1942–"], ["George Kremer", "1823–1825", "Pennsylvania", "Democratic-Republican", "1775–1854"], ["John C. Kunkel", "1939–1951\\n1961–1966", "Pennsylvania", "Republican", "1898–1970"], ["Snyder S. Kirkpatrick", "1895–1897", "Kansas", "Republican", "1848–1909"], ["Jim Kolbe", "1985–2007", "Arizona", "Republican", "1942–"], ["Arthur W. Kopp", "1909–1913", "Wisconsin", "Republican", "1874–1967"], ["Richard Kelly", "1975–1981", "Florida", "Republican", "1924–2005"], ["John H. Ketcham", "1865–1873\\n1877–1893\\n1897–1906", "New York", "Republican", "1832–1906"], ["John Kean", "1883–1885\\n1887–1889", "New Jersey", "Republican", "1852–1914"], ["Jacob Banks Kurtz", "1923–1935", "Pennsylvania", "Republican", "1867–1960"], ["Oscar Keller", "1919–1927", "Minnesota", "Republican", "1878–1927"], ["J. Warren Keifer", "1877–1885\\n1905–1911", "Ohio", "Republican", "1836–1932"], ["Daniel Kerr", "1887–1891", "Iowa", "Republican", "1836–1916"], ["Philip Knopf", "1903–1909", "Illinois", "Republican", "1847–1920"], ["William Huntington Kirkpatrick", "1921–1923", "Pennsylvania", "Republican", "1885–1970"], ["David Kilgore", "1857–1861", "Indiana", "Republican", "1804–1879"], ["Herman P. Kopplemann", "1933–1939\\n1941–1943\\n1945–1947", "Connecticut", "Democratic", "1880–1957"], ["Elva R. Kendall", "1929–1931", "Kentucky", "Republican", "1893–1968"], ["John Kasich", "1983–2001", "Ohio", "Republican", "1952–"], ["Ken Kramer", "1979–1987", "Colorado", "Republican", "1942–"], ["Karl C. King", "1951–1957", "Pennsylvania", "Republican", "1897–1974"], ["Joe Knollenberg", "1993–2009", "Michigan", "Republican", "1933–"], ["William P. Kellogg", "1883–1885", "Louisiana", "Republican", "1830–1918"]]	You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 0, 2, 2], [10, "France", 0, 0, 1, 1]] Question: name the countries that had at least 5 gold medals Answer: Netherlands, Italy Question:progressive republican is his party association.	William Kent	128	Answer:
Table InputTable: [["Place", "Code", "Area (km2)", "Population", "Most spoken language"], ["Remainder of the municipality", "91106", "2,944.04", "10,463", "Northern Sotho"], ["Sekgosese", "91108", "349.99", "46,749", "Northern Sotho"], ["Soekmekaar", "91110", "1.06", "217", "Northern Sotho"], ["Moletji", "91107", "11.66", "4,989", "Northern Sotho"], ["Bochum", "91102", "11.64", "4,142", "Northern Sotho"], ["Sekhokho", "91109", "1.24", "1,852", "Northern Sotho"], ["Ga-Ramokgopha", "91104", "11.22", "15,806", "Northern Sotho"], ["Dendron", "91103", "2.98", "1,885", "Northern Sotho"], ["Manthata", "91105", "12.24", "22,121", "Northern Sotho"], ["Backer", "91101", "0.34", "1,217", "Northern Sotho"]]	You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 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 places in this municipality have more than 10,000 people living there?	4	128	Answer:
Table InputTable: [["Rank", "Name", "Club", "Nationality", "Points"], ["13", "Ferenc Puskás", "Real Madrid", "Spain", "5"], ["17", "Amancio Amaro", "Real Madrid", "Spain", "2"], ["3", "Luis Suárez", "Internazionale", "Spain", "45"], ["17", "Mário Coluna", "Benfica", "Portugal", "2"], ["17", "Milan Galić", "Partizan Beograd", "Yugoslavia", "2"], ["5", "Bobby Charlton", "Manchester United", "England", "19"], ["1", "Eusébio", "Benfica", "Portugal", "67"], ["11", "Denis Law", "Manchester United", "Scotland", "8"], ["17", "Franz Beckenbauer", "Bayern Munich", "West Germany", "2"], ["25", "Sigfried Held", "Borussia Dortmund", "West Germany", "1"], ["25", "Ivor Allchurch", "Cardiff City", "Wales", "1"], ["17", "Philippe Gondet", "Nantes", "France", "2"], ["15", "Mario Corso", "Internazionale", "Italy", "3"], ["4", "Paul Van Himst", "Anderlecht", "Belgium", "25"], ["17", "Ferenc Bene", "Ujpest Dozsa", "Hungary", "2"], ["6", "Flórián Albert", "Ferencvárosi", "Hungary", "14"], ["7", "Gianni Rivera", "Milan", "Italy", "10"], ["8", "Alessandro Mazzola", "Internazionale", "Italy", "9"], ["8", "Georgi Asparuhov", "Levski Sofia", "Bulgaria", "9"], ["12", "Karl-Heinz Schnellinger", "Milan", "West Germany", "6"], ["13", "Jim Baxter", "Sunderland", "Scotland", "5"], ["2", "Giacinto Facchetti", "Internazionale", "Italy", "59"], ["15", "Lev Yashin", "Dynamo Moscow", "Soviet Union", "3"], ["17", "Slava Metreveli", "Dinamo Tbilisi", "Soviet Union", "2"], ["17", "Andrej Kvašňák", "Sparta Praha", "Czechoslovakia", "2"], ["25", "Jakob Kühn", "Zürich", "Switzerland", "1"], ["8", "Valery Voronin", "Torpedo Moskva", "Soviet Union", "9"]]	You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 0, 2, 2], [10, "France", 0, 0, 1, 1]] Question: name the countries that had at least 5 gold medals Answer: Netherlands, Italy Question:what are the total amount of points scored by all spain players?	52	128	Answer:
Table InputTable: [["No. in\\nseries", "No. in\\nseason", "Title", "Directed by", "Written by", "Original air date", "Prod.\\ncode"], ["3", "1", "\"So Long, Patrick Henry\"", "Leo Penn", "Robert Culp", "September 15, 1965", "101"], ["7", "5", "\"Dragon's Teeth\"", "Leo Penn", "Gilbert Ralston", "October 13, 1965", "105"], ["5", "2", "\"A Cup of Kindness\"", "Leo Penn", "Morton Fine & David Friedkin", "September 22, 1965", "102"], ["4", "7", "\"Danny was a Million Laughs\"", "Mark Rydell", "Arthur Dales", "October 27, 1965", "107"], ["9", "9", "\"No Exchange on Damaged Merchandise\"", "Leo Penn", "Gary Marshall & Jerry Belson", "November 10, 1965", "109"], ["18", "18", "\"Court of the Lion\"", "Robert Culp", "Robert Culp", "February 2, 1966", "118"], ["28", "27", "\"It's All Done with Mirrors\"", "Robert Butler", "Stephen Kandell", "April 13, 1966", "127"], ["26", "25", "\"My Mother, The Spy\"", "Richard Benedict", "Howard Gast", "March 30, 1966", "125"], ["8", "6", "\"The Loser\"", "Mark Rydell", "Robert Culp", "October 20, 1965", "106"], ["16", "15", "\"The Tiger\"", "Paul Wendkos", "Robert Culp", "January 5, 1966", "115"], ["2", "3", "\"Carry Me Back to Old Tsing-Tao\"", "Mark Rydell", "David Karp", "September 29, 1965", "103"], ["25", "24", "\"Crusade to Limbo\"", "Richard Sarafian", "Teleplay by: Morton Fine & David Freidkin & Jack Turley Story by: Jack Turley", "March 23, 1966", "124"], ["27", "26", "\"There was a Little Girl\"", "John Rich", "Teleplay by: Stephen Kandell Story by: Robert Bloch", "April 6, 1966", "126"], ["23", "23", "\"A Day Called 4 Jaguar\"", "Richard Sarafian", "Michael Zagar", "March 9, 1966", "123"], ["24", "28", "\"One Thousand Fine\"", "Paul Wendkos", "Eric Bercovici", "April 27, 1966", "128"], ["10", "8", "\"The Time of the Knife\"", "Paul Wendkos", "Gilbert Ralston", "November 3, 1965", "108"], ["21", "21", "\"Return to Glory\"", "Robert Sarafian", "David Friedkin & Morton Fine", "February 23, 1966", "121"], ["1", "14", "\"Affair in T'Sien Cha\"", "Sheldon Leonard", "Morton Fine & David Friedkin", "December 29, 1965", "114"], ["15", "17", "\"Always Say Goodbye\"", "Allen Reisner", "Robert C. Dennis & Earl Barrett", "January 26, 1966", "117"], ["19", "19", "\"Turkish Delight\"", "Paul Wendkos", "Eric Bercovici", "February 9, 1966", "119"], ["22", "22", "\"The Conquest of Maude Murdock\"", "Paul Wendkos", "Robert C. Dennis & Earl Barrett", "March 2, 1966", "122"], ["14", "12", "\"Three Hours on a Sunday\"", "Paul Wendkos", "Morton Fine & David Friedkin", "December 8, 1965", "112"], ["11", "10", "\"Tatia\"", "David Friedkin", "Robert Lewin", "November 17, 1965", "110"], ["12", "11", "\"Weight of the World\"", "Paul Wendkos", "Robert Lewin", "December 1, 1965", "111"], ["17", "16", "\"The Barter\"", "Allen Reisner", "Harvey Bullock & P.S. Allen", "January 12, 1966", "116"], ["13", "13", "\"Tigers of Heaven\"", "Allen Reisner", "Morton Fine & David Friedkin", "December 15, 1965", "113"]]	You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 0, 2, 2], [10, "France", 0, 0, 1, 1]] Question: name the countries that had at least 5 gold medals Answer: Netherlands, Italy Question:how many episodes were directed by leo penn?	4	128	Answer:
Table InputTable: [["Season", "Team", "Country", "Division", "Apps", "Goals"], ["2007/08", "Dnipro Dnipropetrovsk", "Ukraine", "1", "24", "0"], ["2008/09", "Dnipro Dnipropetrovsk", "Ukraine", "1", "22", "1"], ["2009/10", "Dnipro Dnipropetrovsk", "Ukraine", "1", "28", "0"], ["2012/13", "Dnipro Dnipropetrovsk", "Ukraine", "1", "10", "1"], ["2006/07", "Dnipro Dnipropetrovsk", "Ukraine", "1", "12", "0"], ["2010/11", "Dnipro Dnipropetrovsk", "Ukraine", "1", "23", "0"], ["2011/12", "Dnipro Dnipropetrovsk", "Ukraine", "1", "16", "0"], ["2006", "Spartak Nizhny Novgorod", "Russia", "2", "36", "1"], ["2004", "CSKA Moscow", "Russia", "1", "0", "0"], ["2005", "CSKA Moscow", "Russia", "1", "0", "0"], ["2013/14", "Lokomotiv Moscow", "Russia", "1", "14", "1"], ["2012/13", "Lokomotiv Moscow", "Russia", "1", "8", "0"]]	You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 0, 2, 2], [10, "France", 0, 0, 1, 1]] Question: name the countries that had at least 5 gold medals Answer: Netherlands, Italy Question:in what season did dnipro dnipropetrovsk had 28 appearances?	2009/10	128	Answer:
Table InputTable: [["Year", "Car", "Start", "Qual", "Rank", "Finish", "Laps", "Led", "Retired"], ["1927", "27", "27", "107.765", "22", "3", "200", "0", "Running"], ["1928", "8", "4", "117.031", "4", "10", "200", "33", "Running"], ["1939", "62", "27", "121.749", "24", "11", "200", "0", "Running"], ["1929", "23", "11", "112.146", "15", "17", "91", "0", "Supercharger"], ["1933", "34", "12", "113.578", "15", "7", "200", "0", "Running"], ["1931", "37", "19", "111.725", "6", "18", "167", "0", "Crash T4"], ["1937", "38", "7", "118.788", "16", "8", "200", "0", "Running"], ["1934", "8", "7", "113.733", "13", "17", "94", "0", "Rod"], ["1938", "17", "4", "122.499", "6", "17", "130", "0", "Rod"], ["1930", "9", "20", "100.033", "18", "20", "79", "0", "Valve"], ["1935", "44", "6", "115.459", "11", "21", "102", "0", "Magneto"], ["1926", "31", "12", "102.789", "13", "11", "142", "0", "Flagged"], ["1932", "25", "20", "108.896", "34", "13", "184", "0", "Flagged"], ["Totals", "Totals", "Totals", "Totals", "Totals", "Totals", "1989", "33", ""]]	You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 0, 2, 2], [10, "France", 0, 0, 1, 1]] Question: name the countries that had at least 5 gold medals Answer: Netherlands, Italy Question:how many indy 500 did tony gulotta finish in the top 3?	1	128	Answer:
Table InputTable: [["Team", "Stadium", "Capacity", "City/Area"], ["Bradford Bulls (2014 season)", "Provident Stadium", "27,000", "Bradford, West Yorkshire"], ["Wigan Warriors (2014 season)", "DW Stadium", "25,138", "Wigan, Greater Manchester"], ["Leeds Rhinos (2014 season)", "Headingley Carnegie Stadium", "22,250", "Leeds, West Yorkshire"], ["Huddersfield Giants (2014 season)", "John Smith's Stadium", "24,544", "Huddersfield, West Yorkshire"], ["Salford City Reds (2014 season)", "Salford City Stadium", "12,000", "Salford, Greater Manchester"], ["Widnes Vikings (2014 season)", "The Select Security Stadium", "13,500", "Widnes, Cheshire, England"], ["Wakefield Trinity Wildcats (2014 season)", "Rapid Solicitors Stadium", "11,000", "Wakefield, West Yorkshire"], ["Hull (2014 season)", "Kingston Communications Stadium", "25,404", "Kingston upon Hull, East Riding of Yorkshire"], ["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"], ["Warrington Wolves (2014 season)", "Halliwell Jones Stadium", "15,500", "Warrington, Cheshire"], ["Hull Kingston Rovers (2014 season)", "MS3 Craven Park", "9,471", "Kingston upon Hull, East Riding of Yorkshire"], ["Castleford Tigers (2014 season)", "The Wish Communications Stadium", "11,750", "Castleford, West Yorkshire"], ["London Broncos (2014 season)", "Twickenham Stoop", "12,700", "Twickenham, London"]]	You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 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 stadiums have a capacity above 25,000?	3	128	Answer:
Table InputTable: [["Title", "Year", "Peak chart positions\\nUS", "Peak chart positions\\nUS R&B", "Peak chart positions\\nUS Rap", "Album"], ["\"Pain In My Life\"\\n(featuring Trey Songz)", "2006", "—", "—", "—", "N/A"], ["\"Gotta Believe It\"\\n(featuring Just Blaze)", "2009", "—", "—", "—", "Warning Shots 2"], ["\"Not Like Them\"\\n(featuring Styles P)", "2012", "—", "—", "—", "The Greatest Story Never Told Chapter 2: Bread and Circuses"], ["\"Best Mistake\"\\n(featuring G. Martin)", "2013", "—", "—", "—", "The Greatest Story Never Told Chapter 3: The Troubled Times of Brian Carenard"], ["\"C'mon Baby\"\\n(featuring Swizz Beatz)", "2007", "—", "—", "—", "N/A"], ["\"Clap\"\\n(featuring Faith Evans)", "2011", "—", "—", "—", "The Greatest Story Never Told"], ["\"Bring Me Down\"", "2010", "—", "—", "—", "N/A"], ["\"Best Thing That I Found\"\\n(featuring Lecrae and Corbett)", "2012", "—", "—", "—", "The Greatest Story Never Told Chapter 2: Bread and Circuses"], ["\"Do You Know\"", "2002", "—", "—", "—", "N/A"], ["\"Favorite Things\"", "2004", "—", "—", "—", "N/A"], ["\"The Greatest Story Never Told\"", "2011", "—", "—", "—", "The Greatest Story Never Told"], ["\"Say Yes\"", "2001", "—", "—", "—", "N/A"]]	You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 0, 2, 2], [10, "France", 0, 0, 1, 1]] Question: name the countries that had at least 5 gold medals Answer: Netherlands, Italy Question:rapper saigon has had at least ____ albums released in the u.s.?	4	128	Answer:
Table InputTable: [["Player", "No.", "Nationality", "Position", "Years for Jazz", "School/Club Team"], ["Terry Furlow", "25", "United States", "Guard/Forward", "1979-80", "Michigan State"], ["Todd Fuller", "52", "United States", "Center", "1998-99", "North Carolina State"], ["Jim Farmer", "30", "United States", "Guard", "1988-89", "Alabama"], ["Derrick Favors", "15", "United States", "Forward", "2011-present", "Georgia Tech"], ["Bernie Fryer", "25", "United States", "Guard", "1975-76", "BYU"], ["Greg Foster", "44", "United States", "Center/Forward", "1995-99", "UTEP"], ["Derek Fisher", "2", "United States", "Guard", "2006-2007", "Arkansas-Little Rock"], ["Kyrylo Fesenko", "44", "Ukraine", "Center", "2007-11", "Cherkasy Monkeys (Ukraine)"]]	You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 0, 2, 2], [10, "France", 0, 0, 1, 1]] Question: name the countries that had at least 5 gold medals Answer: Netherlands, Italy Question:who was the only player not from the usa?	Kyrylo Fesenko	128	Answer:
Table InputTable: [["Parish", "Church name", "Location", "Year built"], ["Markabygd", "Markabygda Church", "Markabygd", "1887"], ["Alstadhaug", "Alstadhaug Church", "Alstadhaug", "1180"], ["Levanger", "Levanger Church", "Levanger", "1902"], ["Ekne", "Ekne Church", "Ekne", "1893"], ["Åsen", "Åsen Church", "Åsen", "1904"], ["Levanger", "Bamberg Church", "Levanger", "1998"], ["Ytterøy", "Ytterøy Church", "Ytterøya", "1890"], ["Okkenhaug", "Okkenhaug Chapel", "Okkenhaug", "1893"]]	You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 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 church name does not have the name of the parish in its name?	Bamberg Church	128	Answer:
Table InputTable: [["Goal", "Date", "Venue", "Opponent", "Score", "Result", "Competition"], ["6", "2012-2-29", "Tsirion Stadium, Limassol, Cyprus", "Canada", "1-1", "1-3", "Friendly match"], ["7", "2012-2-29", "Tsirion Stadium, Limassol, Cyprus", "Canada", "1-2", "1-3", "Friendly match"], ["3", "2011-6-4", "Petrovsky Stadium, Saint Petersburg, Russia", "Russia", "0-1", "3–1", "Euro 2012 Q"], ["2", "2010-10-12", "Hanrapetakan Stadium, Yerevan, Armenia", "Andorra", "4–0", "4–0", "Euro 2012 Q"], ["5", "2011-10-7", "Hanrapetakan Stadium, Yerevan, Armenia", "Macedonia", "1-0", "4-1", "Euro 2012 Q"], ["1", "2008-5-28", "Sheriff Stadium, Tiraspol, Moldova", "Moldova", "0-1", "2–2", "Friendly match"], ["4", "2011-9-2", "Estadi Comunal d'Aixovall, Andorra la Vella, Andorra", "Andorra", "0-1", "0-3", "Euro 2012 Q"]]	You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 0, 2, 2], [10, "France", 0, 0, 1, 1]] Question: name the countries that had at least 5 gold medals Answer: Netherlands, Italy Question:in how many international games did marcos pizzelli score at least one goal?	4	128	Answer:
Table InputTable: [["Date", "Competition", "Location", "Country", "Event", "Placing", "Rider", "Nationality"], ["1 November 2008", "2008–09 World Cup", "Manchester", "United Kingdom", "Sprint", "1", "Jason Kenny", "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", "Team sprint", "1", "Jason Kenny", "GBR"], ["1 November 2008", "2008–09 World Cup", "Manchester", "United Kingdom", "500 m time trial", "1", "Victoria Pendleton", "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", "Ross Edgar", "GBR"], ["30 October 2009", "2009–10 World Cup", "Manchester", "United Kingdom", "Sprint", "1", "Chris Hoy", "GBR"], ["1 November 2009", "2009–10 World Cup", "Manchester", "United Kingdom", "Team sprint", "1", "Chris Hoy", "GBR"], ["13 February 2009", "2008–09 World Cup", "Copenhagen", "Denmark", "Sprint", "1", "Victoria Pendleton", "GBR"], ["2 November 2008", "2008–09 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"], ["13 February 2009", "2008–09 World Cup", "Copenhagen", "Denmark", "Team sprint", "1", "Jason Kenny", "GBR"], ["30 October 2009", "2009–10 World Cup", "Manchester", "United Kingdom", "500 m time trial", "2", "Victoria Pendleton", "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", "Keirin", "1", "Victoria Pendleton", "GBR"], ["1 November 2009", "2009–10 World Cup", "Manchester", "United Kingdom", "Team sprint", "1", "Jamie Staff", "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", "Team sprint", "1", "Jamie Staff", "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"]]	You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 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 competition?	20	128	Answer:
Table InputTable: [["Single / EP", "Tracks", "Label", "Year", "Album"], ["Die Famous", "Die Famous", "Burn The Fire", "2011", "—"], ["Los Angeles", "Los Angeles\\nLos Angeles feat. Whiskey Pete (Clean Mix)\\nLos Angeles feat. Whiskey Pete (Dirty Mix)", "Burn The Fire", "2010", "The Agenda"], ["Doin' It Right", "Doin' It Right", "Burn The Fire", "2009", "—"], ["Your Love Is Electric", "Your Love Is Electric", "Burn The Fire", "2009", "—"], ["Hot & Cold", "Overdose", "Burn The Fire", "2010", "—"], ["Rave To The Grave", "Raver Booty\\nShuffle", "Burn The Fire", "2010", "—"], ["2012 – Remix Contest EP", "2012 (Remastered)", "Burn The Fire", "2012", "The Agenda"], ["Fresh Attire Vol. 3", "Crush Groovin'", "Wearhouse Music", "2009", "—"], ["Hyped", "Hyped", "Vicious", "2014", "—"], ["Still Smoking", "Nasty & Gaspar Still Smoking", "Burn The Fire", "2010", "—"], ["Louder Than Bombs", "Louder Than Bombs", "Burn The Fire", "2012", "The Agenda"], ["Dutchie", "Dutchie", "Burn The Fire", "2010", "—"], ["Ghetto Ass Bitches", "Ghetto Ass Bitches", "Burn The Fire", "2010", "—"], ["Breakdown", "Breakdown", "Burn The Fire", "2009", "—"], ["Those Who From Heaven To Earth Came", "The Lizard King\\nAnnunaki", "Burn The Fire", "2010", "—"], ["Drop Bears", "Drop Bears", "Burn The Fire", "2013", "—"], ["Onslaught", "Onslaught", "Burn The Fire", "2012", "The Agenda"], ["Redroid", "Redroid", "Temple Music Group", "2011", "—"], ["The Thirteenth Skull", "The Thirteenth Skull", "Burn The Fire", "2010", "—"], ["Ancient Psychic Tandem War Elephant", "Ancient Psychic Tandem War Elephant", "Burn The Fire", "2011", "—"], ["Deception", "Deception", "Burn The Fire", "2012", "The Agenda"], ["The Flying Cat", "The Flying Cat", "Burn The Fire", "2010", "—"], ["Left To Right", "Left To Right", "Destination?", "2009", "—"]]	You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 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 single/ep came next after die famous?	Redroid	128	Answer:
Table InputTable: [["Year", "Title", "Role", "Notes"], ["2013", "A Grande Família", "Bianca", "Cameo"], ["2004", "Casseta & Planeta, Urgente!", "Darlene Sampaio", "Cameo"], ["2006", "Dança no Gelo", "Herself", "Reality show of Domingão do Faustão"], ["2008", "Episódio Especial", "Herself", "Cameo"], ["2009", "Episódio Especial", "Herself", "Cameo"], ["1997", "Zazá", "Dora Dumont", ""], ["1999", "Mundo VIP", "Herself", "Cameo"], ["2010", "As Cariocas", "Alice", "Ep: \"A Suicida da Lapa\""], ["1999", "Terra Nostra", "Hannah", "Cameo"], ["2003", "Homem Objeto", "Eva", ""], ["2002", "Brava Gente", "Jane", "Ep: \"Loucos de Pedra\""], ["1999", "Você Decide", "Socorro", "Ep: \"A Filha de Maria\""], ["2002", "O Beijo do Vampiro", "Lara", ""], ["1994", "Confissões de Adolescente", "Carol", ""], ["2007", "Paraíso Tropical", "Betina Monteiro", "Cameo"], ["2006", "Pé na Jaca", "Elizabeth Aparecida Barra", ""], ["1996", "Vira-Lata", "Tatu / Bárbara", ""], ["2008", "A Favorita", "Maria do Céu / Pâmela Queiroz", ""], ["2001", "A Padroeira", "Cecília de Sá", ""], ["2012", "Louco por Elas", "Giovanna Bianchi", ""], ["1993", "Contos de Verão", "Fabíola", ""], ["2011", "Insensato Coração", "Natalie Lamour", ""], ["1998", "Era Uma Vez...", "Emilia Zanella", ""], ["1996", "Você Decide", "", "Ep: \"Justiça\""], ["2009", "Decamerão - A Comédia do Sexo", "Monna", ""], ["2003", "Celebridade", "Darlene Sampaio", ""], ["2002", "Festival de Desenhos", "Herself", "Hoster"], ["1990", "Meu Bem, Meu Mal", "", "Cameo"], ["2002", "Os Normais", "Kátia", "Ep: \"É Nojento, Mas é Normal\""], ["1992", "Você Decide", "", "Ep: \"Tabu\""], ["2009", "Ó Paí, Ó", "Keila Cristina", "Ep: \"A Outra\""], ["1990", "Mico Preto", "Denise Menezes Garcia", ""], ["1992", "Você Decide", "", "Ep: \"Mamãe Coragem\""], ["2001", "Sítio do Picapau Amarelo", "", "Ep: \"A Festa da Cuca\""], ["2000", "Laços de Família", "Íris Frank Lacerda", ""], ["2000", "A Invenção do Brasil", "Moema", ""], ["2005", "América", "Sol de Oliveira", ""], ["1992", "Escolinha do Professor Raimundo", "Capituzinha", ""], ["1995", "A Próxima Vítima", "Carina Carvalho Rossi", ""], ["1999", "Suave Veneno", "Marina Canhedo", ""]]	You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 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 show did deborah secco play the character eva?	Homem Objeto	128	Answer:
Table InputTable: [["Season", "Age", "Overall", "Slalom", "Giant\\nSlalom", "Super G", "Downhill", "Combined"], ["2010", "12 Mar 2010", "Garmisch, Germany", "Giant Slalom", "", "", "", ""], ["2009", "13 Dec 2008", "Val d'Isère, France", "Giant slalom", "", "", "", ""], ["2010", "6 Dec 2009", "Beaver Creek, USA", "Giant Slalom", "", "", "", ""], ["2011", "5 Mar 2011", "Kranjska Gora, Slovenia", "Giant Slalom", "", "", "", ""], ["2009", "16 Jan 2009", "Wengen, Switzerland", "Super Combined", "", "", "", ""], ["2010", "10 Mar 2010", "Garmisch, Germany", "Downhill", "", "", "", ""], ["2010", "16 Jan 2010", "Wengen, Switzerland", "Downhill", "", "", "", ""], ["2010", "4 Dec 2009", "Beaver Creek, USA", "Super Combined", "", "", "", ""], ["Season", "Date", "Location", "Race", "", "", "", ""], ["2007", "20", "130", "–", "40", "–", "–", "—"], ["2014", "27", "18", "–", "25", "14", "20", "11"], ["2013", "26", "48", "–", "48", "27", "38", "4"], ["2012", "25", "24", "–", "16", "28", "17", "19"], ["2010", "5 Dec 2009", "Beaver Creek, USA", "Downhill", "", "", "", ""], ["2008", "21", "64", "–", "28", "46", "46", "31"], ["2009", "22", "7", "–", "6", "16", "16", "1"], ["2010", "23", "1", "–", "2", "6", "2", "2"], ["2011", "24", "3", "–", "5", "6", "9", "6"]]	You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 0, 2, 2], [10, "France", 0, 0, 1, 1]] Question: name the countries that had at least 5 gold medals Answer: Netherlands, Italy Question:what season had more than 20 in giant slalom but not super g?	2014	128	Answer:
Table InputTable: [["Pos", "No", "Driver", "Constructor", "Laps", "Time/Retired", "Grid", "Points"], ["4", "9", "Denny Hulme", "McLaren-Ford", "80", "+ 1:06.7", "8", "3"], ["7", "22", "John Surtees", "Surtees-Ford", "79", "+ 1 Lap", "10", ""], ["8", "27", "Henri Pescarolo", "March-Ford", "77", "+ 3 Laps", "13", ""], ["1", "11", "Jackie Stewart", "Tyrrell-Ford", "80", "1:52:21.3", "1", "9"], ["Ret", "14", "Jo Siffert", "BRM", "58", "Oil Pipe", "3", ""], ["10", "8", "Tim Schenken", "Brabham-Ford", "76", "+ 4 Laps", "18", ""], ["6", "24", "Rolf Stommelen", "Surtees-Ford", "79", "+ 1 Lap", "16", "1"], ["Ret", "7", "Graham Hill", "Brabham-Ford", "1", "Accident", "9", ""], ["5", "1", "Emerson Fittipaldi", "Lotus-Ford", "79", "+ 1 Lap", "17", "2"], ["Ret", "10", "Peter Gethin", "McLaren-Ford", "22", "Accident", "14", ""], ["9", "15", "Pedro Rodríguez", "BRM", "76", "+ 4 Laps", "5", ""], ["DNQ", "18", "Alex Soler-Roig", "March-Ford", "", "", "", ""], ["Ret", "2", "Reine Wisell", "Lotus-Ford", "21", "Wheel bearing", "12", ""], ["3", "4", "Jacky Ickx", "Ferrari", "80", "+ 53.3", "2", "4"], ["DNQ", "28", "Skip Barber", "March-Ford", "", "", "", ""], ["Ret", "12", "François Cevert", "Tyrrell-Ford", "5", "Accident", "15", ""], ["Ret", "5", "Clay Regazzoni", "Ferrari", "24", "Accident", "11", ""], ["2", "17", "Ronnie Peterson", "March-Ford", "80", "+ 25.6", "6", "6"], ["DNQ", "19", "Nanni Galli*", "March-Alfa-Romeo", "", "", "", ""], ["DNQ", "6", "Mario Andretti", "Ferrari", "", "", "", ""], ["Ret", "21", "Jean-Pierre Beltoise", "Matra", "47", "Differential", "7", ""], ["Ret", "20", "Chris Amon", "Matra", "45", "Differential", "4", ""], ["DNQ", "16", "Howden Ganley", "BRM", "", "", "", ""]]	You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 0, 2, 2], [10, "France", 0, 0, 1, 1]] Question: name the countries that had at least 5 gold medals Answer: Netherlands, Italy Question:did denny hulme or jo siffert drive more laps?	Denny Hulme	128	Answer:
Table InputTable: [["Year", "Division", "League", "Reg. Season", "Playoffs", "National Cup"], ["1935/36", "N/A", "ASL", "1st", "Champion (no playoff)", "?"], ["1953/54", "N/A", "ASL", "1st", "Champion (no playoff)", "Champion"], ["1931", "1", "ASL", "6th (Fall)", "No playoff", "N/A"], ["Fall 1932", "1", "ASL", "3rd", "No playoff", "N/A"], ["1936/37", "N/A", "ASL", "5th, National", "Did not qualify", "Champion"], ["1934/35", "N/A", "ASL", "2nd", "No playoff", "?"], ["1952/53", "N/A", "ASL", "6th", "No playoff", "Semifinals"], ["Spring 1932", "1", "ASL", "5th?", "No playoff", "1st Round"], ["1933/34", "N/A", "ASL", "2nd", "No playoff", "?"], ["1942/43", "N/A", "ASL", "6th", "No playoff", "?"], ["1939/40", "N/A", "ASL", "4th", "No playoff", "?"], ["1940/41", "N/A", "ASL", "6th", "No playoff", "?"], ["1946/47", "N/A", "ASL", "6th", "No playoff", "?"], ["1947/48", "N/A", "ASL", "6th", "No playoff", "?"], ["1945/46", "N/A", "ASL", "5th", "No playoff", "?"], ["1943/44", "N/A", "ASL", "9th", "No playoff", "?"], ["1950/51", "N/A", "ASL", "5th", "No playoff", "?"], ["1941/42", "N/A", "ASL", "3rd", "No playoff", "?"], ["1954/55", "N/A", "ASL", "8th", "No playoff", "?"], ["1944/45", "N/A", "ASL", "9th", "No playoff", "?"], ["1949/50", "N/A", "ASL", "3rd", "No playoff", "?"], ["1951/52", "N/A", "ASL", "6th", "No playoff", "?"], ["1955/56", "N/A", "ASL", "6th", "No playoff", "?"], ["1937/38", "N/A", "ASL", "3rd(t), National", "1st Round", "?"], ["1938/39", "N/A", "ASL", "4th, National", "Did not qualify", "?"], ["1948/49", "N/A", "ASL", "1st(t)", "Finals", "?"], ["Spring 1933", "1", "ASL", "?", "?", "Final"]]	You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 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 other year other than 1935/36 were championships held without playoffs?	1953/54	128	Answer:
Table InputTable: [["No. in\\nseries", "No. in\\nseason", "Title", "Directed by", "Written by", "Original air date", "Prod.\\ncode"], ["16", "15", "\"The Tiger\"", "Paul Wendkos", "Robert Culp", "January 5, 1966", "115"], ["24", "28", "\"One Thousand Fine\"", "Paul Wendkos", "Eric Bercovici", "April 27, 1966", "128"], ["19", "19", "\"Turkish Delight\"", "Paul Wendkos", "Eric Bercovici", "February 9, 1966", "119"], ["10", "8", "\"The Time of the Knife\"", "Paul Wendkos", "Gilbert Ralston", "November 3, 1965", "108"], ["12", "11", "\"Weight of the World\"", "Paul Wendkos", "Robert Lewin", "December 1, 1965", "111"], ["27", "26", "\"There was a Little Girl\"", "John Rich", "Teleplay by: Stephen Kandell Story by: Robert Bloch", "April 6, 1966", "126"], ["22", "22", "\"The Conquest of Maude Murdock\"", "Paul Wendkos", "Robert C. Dennis & Earl Barrett", "March 2, 1966", "122"], ["25", "24", "\"Crusade to Limbo\"", "Richard Sarafian", "Teleplay by: Morton Fine & David Freidkin & Jack Turley Story by: Jack Turley", "March 23, 1966", "124"], ["14", "12", "\"Three Hours on a Sunday\"", "Paul Wendkos", "Morton Fine & David Friedkin", "December 8, 1965", "112"], ["8", "6", "\"The Loser\"", "Mark Rydell", "Robert Culp", "October 20, 1965", "106"], ["18", "18", "\"Court of the Lion\"", "Robert Culp", "Robert Culp", "February 2, 1966", "118"], ["11", "10", "\"Tatia\"", "David Friedkin", "Robert Lewin", "November 17, 1965", "110"], ["28", "27", "\"It's All Done with Mirrors\"", "Robert Butler", "Stephen Kandell", "April 13, 1966", "127"], ["3", "1", "\"So Long, Patrick Henry\"", "Leo Penn", "Robert Culp", "September 15, 1965", "101"], ["26", "25", "\"My Mother, The Spy\"", "Richard Benedict", "Howard Gast", "March 30, 1966", "125"], ["4", "7", "\"Danny was a Million Laughs\"", "Mark Rydell", "Arthur Dales", "October 27, 1965", "107"], ["7", "5", "\"Dragon's Teeth\"", "Leo Penn", "Gilbert Ralston", "October 13, 1965", "105"], ["17", "16", "\"The Barter\"", "Allen Reisner", "Harvey Bullock & P.S. Allen", "January 12, 1966", "116"], ["23", "23", "\"A Day Called 4 Jaguar\"", "Richard Sarafian", "Michael Zagar", "March 9, 1966", "123"], ["21", "21", "\"Return to Glory\"", "Robert Sarafian", "David Friedkin & Morton Fine", "February 23, 1966", "121"], ["5", "2", "\"A Cup of Kindness\"", "Leo Penn", "Morton Fine & David Friedkin", "September 22, 1965", "102"], ["2", "3", "\"Carry Me Back to Old Tsing-Tao\"", "Mark Rydell", "David Karp", "September 29, 1965", "103"], ["15", "17", "\"Always Say Goodbye\"", "Allen Reisner", "Robert C. Dennis & Earl Barrett", "January 26, 1966", "117"], ["6", "4", "\"Chrysanthemum\"", "David Friedkin", "Edward J. Lakso", "October 6, 1965", "104"], ["1", "14", "\"Affair in T'Sien Cha\"", "Sheldon Leonard", "Morton Fine & David Friedkin", "December 29, 1965", "114"], ["13", "13", "\"Tigers of Heaven\"", "Allen Reisner", "Morton Fine & David Friedkin", "December 15, 1965", "113"]]	You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 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 title of the first episode directed by paul wendkos?	"The Time of the Knife"	128	Answer:
Table InputTable: [["Rank", "Pair", "Country", "Athletes", "Time", "Deficit"], ["7", "4", "South Korea", "Lee Seung-hoon\\nJoo Hyong-jun\\nKo Byung-wook", "3:47.18", "+5.75"], ["5", "1", "Norway", "Sverre Lunde Pedersen\\nHåvard Bøkko\\nKristian Reistad Fredriksen", "3:46.33", "+4.90"], ["", "3", "Netherlands", "Sven Kramer\\nKoen Verweij\\nJan Blokhuijsen", "3:41.43", ""], ["", "2", "Russia", "Ivan Skobrev\\nDenis Yuskov\\nYevgeny Lalenkov", "3:43.62", "+2.19"], ["8", "2", "Poland", "Zbigniew Bródka\\nKonrad Niedźwiedzki\\nJan Szymański", "3:47.72", "+6.29"], ["", "4", "United States", "Shani Davis\\nBrian Hansen\\nJonathan Kuck", "3:43.42", "+1.99"], ["6", "3", "Germany", "Patrick Beckert\\nMarco Weber\\nRobert Lehmann", "3:46.48", "+5.05"], ["4", "1", "Canada", "Denny Morrison\\nMathieu Giroux\\nLucas Makowsky", "3:44.38", "+2.95"]]	You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 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 faster, norway or south korea?	Norway	128	Answer:
Table InputTable: [["Route", "Destinations", "Via", "Frequency\\n(minutes)", "Peak Hours Only", "Former"], ["11", "Kingston Centre\\nCataraqui Town Centre", "Bath Road\\nGardiners Town Centre", "30", "", "(formerly Route 71)"], ["12", "Kingston Centre\\nHighway 15", "Downtown\\nCFB Kingston (off-peak only)", "30", "", "-"], ["16", "Train Station\\nBus Terminal", "Kingston Centre", "30", "", "(formerly Route C)"], ["3", "Kingston Centre\\nDowntown", "Queen Mary Road\\nSt. Lawrence College\\nKing Street", "30", "", ""], ["10", "Amherstview\\nCataraqui Town Centre", "Collins Bay Road", "30", "", "Kingston Centre"], ["2", "Kingston Centre\\nDivision Street", "St. Lawrence College\\nDowntown", "30", "", ""], ["15", "Reddendale\\nCataraqui Town Centre - Woods", "Gardiners Town Centre", "30", "", "(formerly Route B)"], ["9", "Downtown\\nCataraqui Town Centre", "Brock St. / Barrie St.\\nGardiners Town Centre", "20", "", ""], ["7", "Dalton/Division\\nMidland/Gardiners", "Cataraqui Town Centre\\nTrain Station\\nBus Terminal", "30", "", ""], ["6", "Cataraqui Town Centre\\nSt. Lawrence College", "Gardiners Town Centre", "30", "", "Downtown"], ["14", "Train Station\\nCataraqui Town Centre / Midland Avenue", "Waterloo-Davis\\nMultiplex", "30", "", "(formerly Route A)"], ["1", "Montreal Street\\nSt. Lawrence College", "Downtown", "30", "", "Cataraqui Town Centre-Woods"], ["4", "Princess Street", "Cataraqui Town Centre\\nDowntown", "30", "", ""], ["12A", "CFB Kingston\\nDowntown", "", "30", "X", ""], ["18", "Train Station\\nBus Terminal", "Downtown\\nQueen's University\\nSt. Lawrence College", "*", "", "Student Circuit"], ["19", "Montreal Street\\nQueen's University", "Downtown", "30", "X", ""]]	You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 0, 2, 2], [10, "France", 0, 0, 1, 1]] Question: name the countries that had at least 5 gold medals Answer: Netherlands, Italy Question:where does the bus stop after kingston centre on route 11?	Cataraqui Town Centre	128	Answer:
Table InputTable: [["#", "Weekend End Date", "Film", "Box Office"], ["19", "May 10, 1998", "Scream 2", "£1,213,184"], ["18", "May 3, 1998", "Scream 2", "£2,493,950"], ["37", "September 13, 1998", "Saving Private Ryan", "£2,704,522"], ["44", "November 1, 1998", "The Exorcist", "£2,186,977"], ["29", "July 19, 1998", "Godzilla", "£4,176,960"], ["30", "July 26, 1998", "Godzilla", "£2,145,088"], ["43", "October 25, 1998", "Small Soldiers", "£1,137,725"], ["38", "September 20, 1998", "Saving Private Ryan", "£2,077,362"], ["41", "October 11, 1998", "The Truman Show", "£2,210,999"], ["33", "August 16, 1998", "Armageddon", "£2,243,095"], ["15", "April 12, 1998", "Titanic", "£1,373,363"], ["42", "October 18, 1998", "The Truman Show", "£1,687,037"], ["13", "March 29, 1998", "Titanic", "£2,223,046"], ["32", "August 9, 1998", "Armageddon", "£2,732,785"], ["31", "August 2, 1998", "Lost in Space", "£3,127,079"], ["1", "January 4, 1998", "Starship Troopers", "£2,221,631"], ["26", "June 28, 1998", "City of Angels", "£674,705"], ["25", "June 21, 1998", "City of Angels", "£1,141,654"], ["11", "March 15, 1998", "Titanic", "£2,469,191"], ["22", "May 31, 1998", "Deep Impact", "£1,070,805"], ["12", "March 22, 1998", "Titanic", "£1,953,082"], ["23", "June 7, 1998", "The Wedding Singer", "£1,031,660"], ["48", "November 29, 1998", "Antz", "£978,414"], ["5", "February 1, 1998", "Titanic", "£4,773,404"], ["14", "April 5, 1998", "Titanic", "£1,504,551"], ["51", "December 20, 1998", "Rush Hour", "£744,783"], ["9", "March 1, 1998", "Titanic", "£3,403,199"], ["20", "May 17, 1998", "Deep Impact", "£1,763,805"], ["50", "December 13, 1998", "Rush Hour", "£1,179,123"], ["49", "December 6, 1998", "Rush Hour", "£1,809,093"], ["46", "November 15, 1998", "Antz", "£1,737,782"], ["16", "April 19, 1998", "Titanic", "£981,940"], ["21", "May 24, 1998", "Deep Impact", "£1,601,651"], ["47", "November 22, 1998", "Antz", "£1,357,591"], ["7", "February 15, 1998", "Titanic", "£3,849,120"], ["24", "June 14, 1998", "The Wedding Singer", "£974,719"], ["36", "September 6, 1998", "Lock, Stock and Two Smoking Barrels", "£1,147,448"], ["2", "January 11, 1998", "The Jackal", "£1,422,193"], ["34", "August 23, 1998", "The X-Files", "£2,506,148"], ["3", "January 18, 1998", "The Devil's Advocate", "£1,300,773"], ["10", "March 8, 1998", "Titanic", "£3,010,921"]]	You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 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 week was the lowest box office total received?	June 28, 1998	128	Answer:

Subsets and Splits

No community queries yet

The top public SQL queries from the community will appear here once available.