question
stringlengths 2.11k
2.25k
| context
stringlengths 265
2.3k
| answer
stringlengths 1
260
| answer_prefix
stringclasses 1
value | max_new_tokens
int64 128
128
| tuple_count
int64 2
33
| token_count
int64 95
601
|
|---|---|---|---|---|---|---|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:which country had the most cyclists finish within the top 10?
|
[['Rank', 'Cyclist', 'Team', 'Time', 'UCI ProTour\\nPoints'], ['8', 'StΓ©phane Goubert\xa0(FRA)', 'Ag2r-La Mondiale', '+ 2"', '5'], ['4', 'Paolo Bettini\xa0(ITA)', 'Quick Step', 's.t.', '20'], ['3', 'Davide Rebellin\xa0(ITA)', 'Gerolsteiner', 's.t.', '25'], ['9', 'Haimar Zubeldia\xa0(ESP)', 'Euskaltel-Euskadi', '+ 2"', '3'], ['6', 'Denis Menchov\xa0(RUS)', 'Rabobank', 's.t.', '11'], ['7', 'Samuel SΓ‘nchez\xa0(ESP)', 'Euskaltel-Euskadi', 's.t.', '7'], ['10', 'David MoncoutiΓ©\xa0(FRA)', 'Cofidis', '+ 2"', '1'], ['5', 'Franco Pellizotti\xa0(ITA)', 'Liquigas', 's.t.', '15'], ['1', 'Alejandro Valverde\xa0(ESP)', "Caisse d'Epargne", '5h 29\' 10"', '40'], ['2', 'Alexandr Kolobnev\xa0(RUS)', 'Team CSC Saxo Bank', 's.t.', '30']]
|
Italy
|
Answer:
| 128
| 10
| 310
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many people were murdered in 1940/41?
|
[['Description Losses', '1939/40', '1940/41', '1941/42', '1942/43', '1943/44', '1944/45', 'Total'], ['Deaths other countries', '', '', '', '', '', '', '2,000'], ['Total', '504,000', '352,000', '407,000', '541,000', '681,000', '270,000', '2,770,000'], ['Murdered in Eastern Regions', '', '', '', '', '', '100,000', '100,000'], ['Deaths Outside of Prisons & Camps', '', '42,000', '71,000', '142,000', '218,000', '', '473,000'], ['Murdered', '75,000', '100,000', '116,000', '133,000', '82,000', '', '506,000'], ['Deaths In Prisons & Camps', '69,000', '210,000', '220,000', '266,000', '381,000', '', '1,146,000'], ['Direct War Losses', '360,000', '', '', '', '', '183,000', '543,000']]
|
100,000
|
Answer:
| 128
| 7
| 263
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how long did it take for the new york americans to win the national cup after 1936?
|
[['Year', 'Division', 'League', 'Reg. Season', 'Playoffs', 'National Cup'], ['1944/45', 'N/A', 'ASL', '9th', 'No playoff', '?'], ['1949/50', 'N/A', 'ASL', '3rd', 'No playoff', '?'], ['1955/56', 'N/A', 'ASL', '6th', 'No playoff', '?'], ['1943/44', 'N/A', 'ASL', '9th', 'No playoff', '?'], ['1940/41', 'N/A', 'ASL', '6th', 'No playoff', '?'], ['1950/51', 'N/A', 'ASL', '5th', 'No playoff', '?'], ['1954/55', 'N/A', 'ASL', '8th', 'No playoff', '?'], ['1939/40', 'N/A', 'ASL', '4th', 'No playoff', '?'], ['1935/36', 'N/A', 'ASL', '1st', 'Champion (no playoff)', '?'], ['1933/34', 'N/A', 'ASL', '2nd', 'No playoff', '?'], ['1937/38', 'N/A', 'ASL', '3rd(t), National', '1st Round', '?'], ['Fall 1932', '1', 'ASL', '3rd', 'No playoff', 'N/A'], ['Spring 1932', '1', 'ASL', '5th?', 'No playoff', '1st Round'], ['1953/54', 'N/A', 'ASL', '1st', 'Champion (no playoff)', 'Champion'], ['1947/48', 'N/A', 'ASL', '6th', 'No playoff', '?'], ['1952/53', 'N/A', 'ASL', '6th', 'No playoff', 'Semifinals'], ['1948/49', 'N/A', 'ASL', '1st(t)', 'Finals', '?'], ['1931', '1', 'ASL', '6th (Fall)', 'No playoff', 'N/A'], ['1938/39', 'N/A', 'ASL', '4th, National', 'Did not qualify', '?'], ['1936/37', 'N/A', 'ASL', '5th, National', 'Did not qualify', 'Champion']]
|
17 years
|
Answer:
| 128
| 20
| 530
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:alfie's birthday party aired on january 19. what was the airdate of the next episode?
|
[['Series #', 'Season #', 'Title', 'Notes', 'Original air date'], ['9', '1', '"Dee Dee Runs Away"', "Dee Dee has been waiting to go to a monster truck show all week. But Alfie and Goo's baseball team makes it to the tournament and everyone forgets about the monster truck show. Dee Dee feels ignored and runs away from home with Harry and Donnell. It's up to Alfie and Goo to try and convince him to come home.", 'December 28, 1994'], ['12', '1', '"Candy Sale"', "Alfie and Goo are selling candy to make money for some expensive jackets, but they are not having any luck. However, when Dee Dee start helping them sell candy, they start to make money and asks him to help them out. Soon Goo and Alfie finds themselves confronted by Melanie, Deonne, Harry and Donnell for Dee Dee's share of the money. They soon learn the boys have used the money to buy three expensive jackets for themselves and Dee Dee as a token of their gratitude. They quickly apologize to Alfie and Goo for their quick judgment.", 'January 26, 1995'], ['11', '1', '"Alfie\'s Birthday Party"', "Goo and Melanie pretend they are dating and they leave Alfie out of everything. He ends up bored and starts hanging out with Dee Dee and his friends. However, it just isn't the same without Goo. Later on, Alfie learns about the surprise birthday party that Goo and Melanie had been planning with everyone else (except for Dee Dee, who couldn't know since he would've told).", 'January 19, 1995'], ['4', '1', '"Robin Hood Play"', "Alfie's school is performing the play Robin Hood and Alfie is chosen to play the part of Robin Hood. Alfie is excited at this prospect, but he does not want to wear tights because he feels that tights are for girls. However, he reconsiders his stance on tights when Dee Dee wisely tells him not to let that affect his performance as Robin Hood.", 'November 9, 1994']]
|
January 26, 1995
|
Answer:
| 128
| 4
| 461
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what is the number of 1st place finishes across all events?
|
[['Date', 'Competition', 'Location', 'Country', 'Event', 'Placing', 'Rider', 'Nationality'], ['30 October 2009', '2009β10 World Cup', 'Manchester', 'United Kingdom', 'Keirin', '1', 'Chris Hoy', 'GBR'], ['30 October 2009', '2009β10 World Cup', 'Manchester', 'United Kingdom', 'Sprint', '1', 'Chris Hoy', 'GBR'], ['1 November 2008', '2008β09 World Cup', 'Manchester', 'United Kingdom', '500 m time trial', '1', 'Victoria Pendleton', 'GBR'], ['1 November 2009', '2009β10 World Cup', 'Manchester', 'United Kingdom', 'Team sprint', '1', 'Jamie Staff', 'GBR'], ['30 October 2009', '2009β10 World Cup', 'Manchester', 'United Kingdom', 'Sprint', '1', 'Victoria Pendleton', 'GBR'], ['30 October 2009', '2009β10 World Cup', 'Manchester', 'United Kingdom', '500 m time trial', '2', 'Victoria Pendleton', 'GBR'], ['2 November 2008', '2008β09 World Cup', 'Manchester', 'United Kingdom', 'Team sprint', '1', 'Jamie Staff', 'GBR'], ['13 February 2009', '2008β09 World Cup', 'Copenhagen', 'Denmark', 'Team sprint', '1', 'Jason Kenny', 'GBR'], ['2 November 2008', '2008β09 World Cup', 'Manchester', 'United Kingdom', 'Team sprint', '1', 'Jason Kenny', 'GBR'], ['1 November 2009', '2009β10 World Cup', 'Manchester', 'United Kingdom', 'Team sprint', '1', 'Ross Edgar', 'GBR'], ['13 February 2009', '2008β09 World Cup', 'Copenhagen', 'Denmark', 'Team sprint', '1', 'Jamie Staff', 'GBR'], ['31 October 2008', '2008β09 World Cup', 'Manchester', 'United Kingdom', 'Sprint', '1', 'Victoria Pendleton', 'GBR'], ['1 November 2009', '2009β10 World Cup', 'Manchester', 'United Kingdom', 'Team sprint', '1', 'Chris Hoy', 'GBR']]
|
17
|
Answer:
| 128
| 13
| 520
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:in which competition did hopley finish fist?
|
[['Year', 'Competition', 'Venue', 'Position', 'Event', 'Notes'], ['2000', 'World Junior Championships', 'Santiago, Chile', '1st', 'Discus throw', '59.51 m'], ['2008', 'African Championships', 'Addis Ababa, Ethiopia', '2nd', 'Discus throw', '56.98 m'], ['2007', 'All-Africa Games', 'Algiers, Algeria', '3rd', 'Discus throw', '57.79 m'], ['2003', 'All-Africa Games', 'Abuja, Nigeria', '2nd', 'Discus throw', '62.86 m'], ['2006', 'Commonwealth Games', 'Melbourne, Australia', '4th', 'Discus throw', '60.99 m'], ['2004', 'Olympic Games', 'Athens, Greece', '8th', 'Discus throw', '62.58 m'], ['2004', 'African Championships', 'Brazzaville, Republic of the Congo', '2nd', 'Discus throw', '63.50 m'], ['2003', 'All-Africa Games', 'Abuja, Nigeria', '5th', 'Shot put', '17.76 m'], ['2006', 'Commonwealth Games', 'Melbourne, Australia', '7th', 'Shot put', '18.44 m']]
|
World Junior Championships
|
Answer:
| 128
| 9
| 299
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what is the total number of films with the language of kannada listed?
|
[['Year', 'Film', 'Role', 'Language', 'Notes'], ['2014', 'Endendigu', '', '', 'Filming'], ['2013', 'Dilwala', 'Preethi', 'Kannada', ''], ['2012', 'Breaking News', 'Shraddha', 'Kannada', ''], ['2012', '18th Cross', 'Punya', 'Kannada', ''], ['2008', 'Moggina Manasu', 'Chanchala', 'Kannada', 'Filmfare Award for Best Actress - Kannada\\nKarnataka State Film Award for Best Actress'], ['2011', 'Hudugaru', 'Gayithri', 'Kannada', 'Nominated, Filmfare Award for Best Actress β Kannada'], ['2009', 'Olave Jeevana Lekkachaara', 'Rukmini', 'Kannada', 'Innovative Film Award for Best Actress'], ['2009', 'Love Guru', 'Kushi', 'Kannada', 'Filmfare Award for Best Actress - Kannada'], ['2012', 'Alemari', 'Neeli', 'Kannada', ''], ['2010', 'Krishnan Love Story', 'Geetha', 'Kannada', 'Filmfare Award for Best Actress - Kannada\\nUdaya Award for Best Actress'], ['2013', 'Kaddipudi', 'Uma', 'Kannada', ''], ['2014', 'Mr. & Mrs. Ramachari', '', '', 'Announced'], ['2013', 'Bahaddoor', 'Anjali', 'Kannada', 'Filming'], ['2012', 'Drama', 'Nandini', 'Kannada', ''], ['2012', 'Addhuri', 'Poorna', 'Kannada', 'Udaya Award for Best Actress\\nNominated β SIIMA Award for Best Actress\\nNominated β Filmfare Award for Best Actress\xa0β Kannada'], ['2010', 'Gaana Bajaana', 'Radhey', 'Kannada', ''], ['2012', 'Sagar', 'Kajal', 'Kannada', '']]
|
15
|
Answer:
| 128
| 17
| 474
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what was the number of people attending the toros mexico vs. monterrey flash game?
|
[['Game', 'Day', 'Date', 'Kickoff', 'Opponent', 'Results\\nScore', 'Results\\nRecord', 'Location', 'Attendance'], ['5', 'Saturday', 'December 14', '7:05pm', 'at Sacramento Surge', 'W 7β6 (OT)', '3β2', 'Estadio Azteca Soccer Arena', '215'], ['8', 'Saturday', 'January 4', '7:05pm', 'at Ontario Fury', 'L 5β12', '4β4', 'Citizens Business Bank Arena', '2,653'], ['4', 'Sunday', 'December 1', '1:05pm', 'Ontario Fury', 'W 18β4', '2β2', 'UniSantos Park', '207'], ['13', 'Saturday', 'February 1', '7:05pm', 'at San Diego Sockers', 'L 5β6', '7β6', 'Valley View Casino Center', '4,954'], ['16', 'Saturday', 'February 15β₯', '5:05pm', 'Bay Area Rosal', 'W 27β2', '9β7', 'UniSantos Park', '118'], ['12', 'Sunday', 'January 26', '1:05pm', 'Sacramento Surge', 'W 20β6', '7β5', 'UniSantos Park', '224'], ['14', 'Friday', 'February 7', '7:05pm', 'at Turlock Express', 'L 6β9', '7β7', 'Turlock Soccer Complex', '673'], ['10', 'Sunday', 'January 12', '1:05pm', 'Las Vegas Legends', 'W 10β7', '5β5', 'UniSantos Park', '343'], ['1', 'Sunday', 'November 10', '3:05pm', 'at Las Vegas Legends', 'L 3β7', '0β1', 'Orleans Arena', '1,836'], ['11', 'Sunday', 'January 19', '1:05pm', 'Bay Area Rosal', 'W 17β7', '6β5', 'UniSantos Park', '219'], ['9', 'Sunday', 'January 5', '1:05pm', 'San Diego Sockers', 'L 7β12', '4β5', 'UniSantos Park', '388']]
|
363
|
Answer:
| 128
| 11
| 536
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what time period had no shirt sponsor?
|
[['Year', 'Kit Manufacturer', 'Shirt Sponsor', 'Back of Shirt Sponsor', 'Short Sponsor'], ['1985β1986', 'Umbro', 'Whitbread', '', ''], ['1993β1994', 'Club Sport', 'Gulf Oil', '', ''], ['2004β2008', 'Errea', 'Bence Building Merchants', '', ''], ['1977β1978', '', 'National Express', '', ''], ['1988β1989', '', 'Gulf Oil', '', ''], ['2008β', 'Errea', 'Mira Showers', '', ''], ['2013β', 'Errea', 'Mira Showers', 'Gloucestershire College', 'Gloucestershire Echo'], ['1996β1997', 'UK', 'Endsleigh Insurance', '', ''], ['1982β1985', 'Umbro', '', '', ''], ['2009β2011', 'Errea', 'Mira Showers', 'PSU Technology Group', ''], ['1994β1995', 'KlΕ«b Sport', 'Empress', '', ''], ['1999β2004', 'Errea', 'Towergate Insurance', '', ''], ['1986β1988', 'Henson', 'Duraflex', '', ''], ['1997β1999', 'Errea', 'Endsleigh Insurance', '', ''], ['1991β1993', 'Technik', 'Gulf Oil', '', ''], ['1995β1996', 'Matchwinner', 'Empress', '', ''], ['2011β2013', 'Errea', 'Mira Showers', 'Barr Stadia', 'Gloucestershire Echo']]
|
1982-1985
|
Answer:
| 128
| 17
| 366
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:when was his first 1st place record?
|
[['Year', 'Competition', 'Venue', 'Position', 'Event', 'Notes'], ['1999', 'European Junior Championships', 'Riga, Latvia', '4th', '400 m hurdles', '52.17'], ['2003', 'European U23 Championships', 'Bydgoszcz, Poland', '1st', '400 m hurdles', '48.45'], ['2000', 'World Junior Championships', 'Santiago, Chile', '1st', '400 m hurdles', '49.23'], ['2006', 'European Championships', 'Gothenburg, Sweden', '2nd', '400 m hurdles', '48.71'], ['2001', 'World Championships', 'Edmonton, Canada', '18th (sf)', '400 m hurdles', '49.80'], ['2003', 'World Indoor Championships', 'Birmingham, United Kingdom', '3rd', '4x400 m relay', '3:06.61'], ['2003', 'European U23 Championships', 'Bydgoszcz, Poland', '1st', '4x400 m relay', '3:03.32'], ['2008', 'Olympic Games', 'Beijing, China', '7th', '4x400 m relay', '3:00.32'], ['2007', 'World Championships', 'Osaka, Japan', '3rd', '400 m hurdles', '48.12 (NR)'], ['2004', 'Olympic Games', 'Athens, Greece', '6th', '400 m hurdles', '49.00'], ['2002', 'European Championships', 'Munich, Germany', '4th', '400 m', '45.40'], ['2002', 'European Indoor Championships', 'Vienna, Austria', '1st', '400 m', '45.39 (CR, NR)'], ['2003', 'World Indoor Championships', 'Birmingham, United Kingdom', '7th (sf)', '400 m', '46.82'], ['2001', 'Universiade', 'Beijing, China', '8th', '400 m hurdles', '49.68'], ['2004', 'Olympic Games', 'Athens, Greece', '10th (h)', '4x400 m relay', '3:03.69'], ['2012', 'European Championships', 'Helsinki, Finland', '18th (sf)', '400 m hurdles', '50.77']]
|
2000
|
Answer:
| 128
| 16
| 522
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:in which three consecutive years was the record the same?
|
[['Season', 'Team', 'Record', 'Head Coach', 'Quarterback', 'Leading Rusher', 'Leading Receiver', 'All-Pros', 'Runner Up'], ['1997', 'Green Bay Packers', '13β3', 'Mike Holmgren', 'Brett Favre', 'Dorsey Levens', 'Antonio Freeman', 'Butler, Favre', 'San Francisco 49ers'], ['2004', 'Philadelphia Eagles', '13β3', 'Andy Reid', 'Donovan McNabb', 'Brian Westbrook', 'Terrell Owens', 'Dawkins, Owens, Sheppard', 'Atlanta Falcons'], ['2011', 'New York Giantsβ ', '9β7', 'Tom Coughlin', 'Eli Manning', 'Ahmad Bradshaw', 'Victor Cruz', 'Pierre-Paul', 'San Francisco 49ers'], ['2012', 'San Francisco 49ers', '11β4β1', 'Jim Harbaugh', 'Colin Kaepernick', 'Frank Gore', 'Michael Crabtree', 'Bowman, Goldson, Iupati, Lee, Smith, Willis', 'Atlanta Falcons'], ['1988', 'San Francisco 49ersβ ', '10β6', 'Bill Walsh*', 'Joe Montana*', 'Roger Craig', 'Jerry Rice*', 'Craig, Rice*', 'Chicago Bears'], ['2003', 'Carolina Panthers', '11β5', 'John Fox', 'Jake Delhomme', 'Stephen Davis', 'Steve Smith', 'Jenkins', 'Philadelphia Eagles'], ['1974', 'Minnesota Vikings', '10β4', 'Bud Grant*', 'Fran Tarkenton*', 'Chuck Foreman', 'Jim Lash', 'Page*, Yary*', 'Los Angeles Rams'], ['2010', 'Green Bay Packersβ ', '10β6', 'Mike McCarthy', 'Aaron Rodgers', 'Brandon Jackson', 'Greg Jennings', 'Clifton, Collins, Jennings, Matthews, Woodson', 'Chicago Bears'], ['2005', 'Seattle Seahawks', '13β3', 'Mike Holmgren', 'Matt Hasselbeck', 'Shaun Alexander', 'Bobby Engram', 'Alexander, Hutchinson, Jones*, Strong', 'Carolina Panthers'], ['1983', 'Washington Redskins', '14β2', 'Joe Gibbs*', 'Joe Theismann', 'John Riggins*', 'Charlie Brown', 'Butz, Grimm*, Jacoby, Murphy, Nelms, Riggins*, Theismann', 'San Francisco 49ers']]
|
2004, 2005, 2006
|
Answer:
| 128
| 10
| 525
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:does pat or john have the highest total?
|
[['Name', 'League', 'FA Cup', 'League Cup', 'JP Trophy', 'Total'], ['Liam Sercombe', '1', '0', '0', '0', '1'], ['Danny Coles', '3', '0', '0', '0', '3'], ['Jimmy Keohane', '3', '0', '0', '0', '3'], ["John O'Flynn", '11', '0', '1', '0', '12'], ['Scot Bennett', '5', '0', '0', '0', '5'], ['OWN GOALS', '0', '0', '0', '0', '0'], ['Total', '0', '0', '0', '0', '0'], ['Guillem Bauza', '2', '0', '0', '0', '2'], ['Jake Gosling', '1', '0', '0', '0', '1'], ['Jamie Cureton', '20', '0', '0', '0', '20'], ['Pat Baldwin', '1', '0', '0', '0', '1'], ['Alan Gow', '4', '0', '0', '0', '4'], ['Arron Davies', '3', '0', '0', '0', '3']]
|
John
|
Answer:
| 128
| 13
| 283
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what is the combined score of year end rankings before 2009?
|
[['Tournament', '2004', '2005', '2006', '2007', '2008', '2009', '2010', '2011', '2012', '2013', '2014', 'WβL'], ['Year End Ranking', '129', '91', '68', '90', '62', '41', '33', '39', '76', '62', '', ''], ['Rome Masters', 'A', 'A', 'A', 'A', 'A', 'LQ', '3R', '1R', '2R', 'A', '', '3β3'], ['Wimbledon', 'A', '2R', '2R', '1R', '3R', '2R', '1R', '2R', '2R', '1R', '', '7β9'], ['Canada Masters', 'A', 'A', 'A', 'A', 'A', '1R', 'A', 'A', 'A', 'A', '', '0β1'], ['Australian Open', 'A', '2R', '2R', '2R', '3R', '2R', '1R', '3R', '1R', '1R', '2R', '9β10'], ['French Open', '2R', '1R', '1R', '2R', '2R', '1R', '2R', '3R', '1R', '1R', '', '6β10'], ['WinβLoss', '0β0', '0β1', '1β1', '4β4', '1β2', '2β6', '11β6', '5β8', '5β5', '0β2', '', '29β35'], ['Cincinnati Masters', 'A', 'A', 'A', 'LQ', 'A', '3R', 'A', '1R', 'A', 'A', '', '2β2'], ['Shanghai Masters', 'Not Masters Series', 'Not Masters Series', 'Not Masters Series', 'Not Masters Series', 'Not Masters Series', '1R', 'QF', '2R', 'Q2', 'A', '', '4β3'], ['Indian Wells Masters', 'A', 'A', 'A', '3R', '2R', '1R', '4R', '2R', '3R', 'A', 'A', '8β6']]
|
440
|
Answer:
| 128
| 10
| 537
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many more ships were wrecked in lake huron than in erie?
|
[['Ship', 'Type of Vessel', 'Lake', 'Location', 'Lives lost'], ['Wexford', 'Steamer', 'Lake Huron', 'north of Grand Bend, Ontario', 'all hands'], ['Issac M. Scott', 'Steamer', 'Lake Huron', 'near Port Elgin, Ontario', '28 lost'], ['Charles S. Price', 'Steamer', 'Lake Huron', 'near Port Huron, Michigan', '28 lost'], ['Argus', 'Steamer', 'Lake Huron', '25 miles off Kincardine, Ontario', '25 lost'], ['Henry B. Smith', 'Steamer', 'Lake Superior', '', 'all hands'], ['Regina', 'Steamer', 'Lake Huron', 'near Harbor Beach, Michigan', ''], ['Plymouth', 'Barge', 'Lake Michigan', '', '7 lost'], ['Lightship No. 82', 'Lightship', 'Lake Erie', 'Point Albino (near Buffalo)', '6 lost'], ['John A. McGean', 'Steamer', 'Lake Huron', 'near Goderich, Ontario', '28 lost'], ['Hydrus', 'Steamer', 'Lake Huron', 'near Lexington, Michigan', '28 lost'], ['Leafield', 'Steamer', 'Lake Superior', '', 'all hands'], ['James Carruthers', 'Steamer', 'Lake Huron', 'near Kincardine', '18 lost']]
|
7
|
Answer:
| 128
| 12
| 312
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what is the only character with a blank c string?
|
[['name', 'glyph', 'C string', 'Unicode', 'Unicode name'], ['c', 'c', 'c', 'U+0063', 'LATIN SMALL LETTER C'], ['backslash', '\\\\', '\\\\\\\\', 'U+005C', 'REVERSE SOLIDUS'], ['i', 'i', 'i', 'U+0069', 'LATIN SMALL LETTER I'], ['H', 'H', 'H', 'U+0048', 'LATIN CAPITAL LETTER H'], ['left-square-bracket', '[', '[', 'U+005B', 'LEFT SQUARE BRACKET'], ['K', 'K', 'K', 'U+004B', 'LATIN CAPITAL LETTER K'], ['asterisk', '*', '*', 'U+002A', 'ASTERISK'], ['n', 'n', 'n', 'U+006E', 'LATIN SMALL LETTER N'], ['E', 'E', 'E', 'U+0045', 'LATIN CAPITAL LETTER E'], ['X', 'X', 'X', 'U+0058', 'LATIN CAPITAL LETTER X'], ['colon', ':', ':', 'U+003A', 'COLON'], ['U', 'U', 'U', 'U+0055', 'LATIN CAPITAL LETTER U'], ['F', 'F', 'F', 'U+0046', 'LATIN CAPITAL LETTER F'], ['v', 'v', 'v', 'U+0076', 'LATIN SMALL LETTER V'], ['form-feed', '', '\\\\f', 'U+000C', 'FORM FEED (FF)'], ['O', 'O', 'O', 'U+004F', 'LATIN CAPITAL LETTER O'], ['comma', ',', ',', 'U+002C', 'COMMA'], ['exclamation-mark', '!', '!', 'U+0021', 'EXCLAMATION MARK'], ['x', 'x', 'x', 'U+0078', 'LATIN SMALL LETTER X'], ['A', 'A', 'A', 'U+0041', 'LATIN CAPITAL LETTER A'], ['carriage-return', '', '\\\\r', 'U+000D', 'CARRIAGE RETURN (CR)'], ['ampersand', '&', '&', 'U+0026', 'AMPERSAND'], ['period', '.', '.', 'U+002E', 'FULL STOP'], ['quotation-mark', '"', '\\\\"', 'U+0022', 'QUOTATION MARK']]
|
space
|
Answer:
| 128
| 24
| 525
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what was the total number of points scored by the tide in the last 3 games combined.
|
[['Date', 'Opponent#', 'Rank#', 'Site', 'TV', 'Result', 'Attendance'], ['November 5', 'at\xa0LSU', '#6', 'Tiger Stadium β’ Baton Rouge, LA (Rivalry)', 'ESPN', 'W\xa035β17', '75,453'], ['October 15', 'at\xa0Tennessee', '#10', 'Neyland Stadium β’ Knoxville, TN (Third Saturday in October)', 'ESPN', 'W\xa017β13', '96,856'], ['September 10', 'Vanderbilt', '#11', 'BryantβDenny Stadium β’ Tuscaloosa, AL', 'JPS', 'W\xa017β7', '70,123'], ['December 3', 'vs.\xa0#6\xa0Florida', '#3', 'Georgia Dome β’ Atlanta, GA (SEC Championship Game)', 'ABC', 'L\xa023β24', '74,751'], ['October 22', 'Ole Miss', '#8', 'BryantβDenny Stadium β’ Tuscaloosa, AL (Rivalry)', 'ABC', 'W\xa021β10', '70,123'], ['September 17', 'at\xa0Arkansas', '#12', 'Razorback Stadium β’ Fayetteville, AR', 'ABC', 'W\xa013β6', '52,089'], ['October 1', 'Georgia', '#11', 'BryantβDenny Stadium β’ Tuscaloosa, AL', 'ESPN', 'W\xa029β28', '70,123'], ['September 24', 'Tulane*', '#11', 'Legion Field β’ Birmingham, AL', '', 'W\xa020β10', '81,421'], ['January 2, 1995', 'vs.\xa0#13\xa0Ohio State*', '#6', 'Citrus Bowl β’ Orlando, FL (Florida Citrus Bowl)', 'ABC', 'W\xa024β17', '71,195'], ['November 19', '#6\xa0Auburn', '#4', 'Legion Field β’ Birmingham, AL (Iron Bowl)', 'ABC', 'W\xa021β14', '83,091'], ['November 12', 'at\xa0#20\xa0Mississippi State', '#6', 'Scott Field β’ Starkville, MS (Rivalry)', 'ABC', 'W\xa029β25', '41,358']]
|
68
|
Answer:
| 128
| 11
| 514
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:who came immediately after sebastian porto in the race?
|
[['Pos', 'Rider', 'Manufacturer', 'Time/Retired', 'Points'], ['11', 'Alex Hofmann', 'TSR-Honda', '+26.933', '5'], ['3', 'Jeremy McWilliams', 'Aprilia', '+0.534', '16'], ['6', 'Ralf Waldmann', 'Aprilia', '+7.019', '10'], ['20', 'Lucas Oliver Bulto', 'Yamaha', '+1:25.758', ''], ['18', 'Julien Allemand', 'TSR-Honda', '+1:16.347', ''], ['16', 'Luca Boscoscuro', 'TSR-Honda', '+56.432', ''], ['4', 'Tohru Ukawa', 'Honda', '+0.537', '13'], ['1', 'Loris Capirossi', 'Honda', '38:04.730', '25'], ['22', 'Rudie Markink', 'Aprilia', '+1:40.280', ''], ['14', 'Masaki Tokudome', 'TSR-Honda', '+33.161', '2'], ['5', 'Shinya Nakano', 'Yamaha', '+0.742', '11'], ['Ret', 'Maurice Bolwerk', 'TSR-Honda', 'Retirement', ''], ['17', 'Johann Stigefelt', 'Yamaha', '+1:07.433', ''], ['Ret', 'Marcellino Lucchi', 'Aprilia', 'Retirement', ''], ['8', 'Stefano Perugini', 'Honda', '+20.891', '8'], ['9', 'Jason Vincent', 'Honda', '+21.310', '7'], ['10', 'Anthony West', 'TSR-Honda', '+26.816', '6'], ['12', 'Sebastian Porto', 'Yamaha', '+27.054', '4'], ['13', 'Tomomi Manako', 'Yamaha', '+27.903', '3'], ['15', 'Jarno Janssen', 'TSR-Honda', '+56.248', '1'], ['23', 'Arno Visscher', 'Aprilia', '+1:40.635', ''], ['2', 'Valentino Rossi', 'Aprilia', '+0.180', '20'], ['Ret', 'Andre Romein', 'Honda', 'Retirement', '']]
|
Tomomi Manako
|
Answer:
| 128
| 23
| 522
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what's the total number of festivals that occurred in october?
|
[['Date', 'Festival', 'Location', 'Awards', 'Link'], ['Nov 16β18', 'AFF', 'WrocΕaw, Lower Silesia\\n\xa0Poland', '', 'AFF Poland'], ['Oct 1, Oct 15', 'Gwacheon International SF Festival', 'Gwacheon, Gyeonggi-do\\n\xa0South Korea', '', 'gisf.org'], ['Nov 12, Nov 18', 'Indonesia Fantastic Film Festival', 'Jakarta, Bandung\\n\xa0Indonesia', '', 'inaff.com'], ['Oct 9', 'London Int. Festival of Science Fiction Film', 'London, England\\n\xa0UK', 'Closing Night Film', 'Sci-Fi London'], ['Nov 11', 'Les Utopiales', 'Nantes, Pays de la Loire\\n\xa0France', '', 'utopiales.org'], ['Oct 17, Oct 20', 'Icon TLV', 'Tel Aviv, Central\\n\xa0Israel', '', 'icon.org.il'], ['Sep 28', 'Fantastic Fest', 'Austin, Texas\\n\xa0USA', '', 'FantasticFest.com'], ['Sep 19', 'Lund International Fantastic Film Festival', 'Lund, SkΓ₯ne\\n\xa0Sweden', '', 'fff.se'], ['Jul 18, Jul 25', 'Fantasia Festival', 'Montreal, Quebec \xa0Canada', 'Special Mention\\n"for the resourcefulness and unwavering determination by a director to realize his unique vision"', 'FanTasia'], ['Feb 2β5, Feb 11', 'Santa Barbara International Film Festival', 'Santa Barbara, California \xa0USA', 'Top 11 "Best of the Fest" Selection', 'sbiff.org'], ['Oct 9, Oct 11', 'Sitges Film Festival', 'Sitges, Catalonia\\n\xa0Spain', '', 'Sitges Festival'], ['Oct 23', 'Toronto After Dark', 'Toronto, Ontario\\n\xa0Canada', 'Best Special Effects\\nBest Musical Score', 'torontoafterdark.com'], ['May 21β22, Jun 11', 'Seattle International Film Festival', 'Seattle, Washington \xa0USA', '', 'siff.net'], ['Sep 16', 'Athens International Film Festival', 'Athens, Attica\\n\xa0Greece', 'Best Director', 'aiff.gr']]
|
5
|
Answer:
| 128
| 14
| 514
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what is the only hospital to have 6 hospital beds?
|
[['Name', 'City', 'Hospital beds', 'Operating rooms', 'Total', 'Trauma designation', 'Affiliation', 'Notes'], ['Wilkes Regional Medical Center', 'North Wilkesboro', '144', '9', '153', '-', 'CHS', '-'], ['Memorial Mission Hospital and Asheville Surgery Center', 'Asheville', '730', '36', '766', 'Level II', 'Mission', '-'], ['North Carolina Specialty Hospital', 'Durham', '18', '4', '22', '-', '-', '-'], ['New Hanover Regional Medical Center', 'Wilmington', '769', '37', '806', 'Level II', 'NHRMC', '-'], ['CarePartners Rehabilitation Hospital', 'Asheville', '80', '0', '80', '-', '-', '-'], ['Vidant Beaufort Hospital', 'Washington', '142', '7', '149', '-', 'Vidant', '-'], ['Frye Regional Medical Center', 'Hickory', '355', '23', '378', '-', 'Tenet', '-'], ['Blowing Rock Hospital', 'Blowing Rock', '100', '2', '102', '-', 'ARHS', '-'], ['Vidant Duplin Hospital', 'Kenansville', '101', '3', '104', '-', 'Vidant', '-'], ['Novant Health Huntersville Medical Center', 'Huntersville', '60', '8', '68', '-', 'Novant', '-'], ['University of North Carolina Hospitals', 'Chapel Hill', '778', '48', '826', 'Level I', 'UNC', 'Primary teaching hospital of University of North Carolina at Chapel Hill School of Medicine'], ['Wake Forest Baptist Medical Center', 'Winston-Salem', '885', '50', '935', 'Level I', 'WFU', 'Primary teaching hospital of Wake Forest School of Medicine'], ['Rex Healthcare', 'Raleigh', '665', '38', '703', '-', 'UNC', '-'], ['Johnston Health', 'Smithfield', '177', '10', '187', '-', 'UNC', '-'], ['Novant Health Brunswick Medical Center', 'Supply', '60', '6', '66', '-', 'Novant', '-'], ['Vidant Edgecombe Hospital', 'Tarboro', '117', '8', '125', '-', 'Vidant', '-'], ['Carolinas Medical Center-NorthEast', 'Concord', '457', '25', '482', 'Level III', 'CHS', '-']]
|
Vidant Bertie Hospital
|
Answer:
| 128
| 17
| 538
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what is the total number of skoda cars sold in the year 2005?
|
[['Model', '1991', '1995', '1996', '1997', '1998', '1999', '2000', '2001', '2002', '2003', '2004', '2005', '2006', '2007', '2008', '2009', '2010', '2011', '2012', '2013'], ['Ε koda Superb', 'β', 'β', 'β', 'β', 'β', 'β', 'β', '177', '16,867', '23,135', '22,392', '22,091', '20,989', '20,530', '25,645', '44,548', '98,873', '116,700', '106,847', '94,400'], ['Ε koda Felicia', '172,000', '210,000', '', '288,458', '261,127', '241,256', '148,028', '44,963', 'β', 'β', 'β', 'β', 'β', 'β', 'β', 'β', 'β', 'β', 'β', 'β'], ['Ε koda Yeti', 'β', 'β', 'β', 'β', 'β', 'β', 'β', 'β', 'β', 'β', 'β', 'β', 'β', 'β', 'β', '11,018', '52,604', '70,300', '90,952', '82,400'], ['Ε koda Rapid', 'β', 'β', 'β', 'β', 'β', 'β', 'β', 'β', 'β', 'β', 'β', 'β', 'β', 'β', 'β', 'β', 'β', '1,700', '9,292', '103,800'], ['Total', '172,000', '210,000', '261,000', '336,334', '363,500', '385,330', '435,403', '460,252', '445,525', '449,758', '451,675', '492,111', '549,667', '630,032', '674,530', '684,226', '762,600', '879,200', '949,412', '920,800']]
|
492,111
|
Answer:
| 128
| 5
| 505
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what was the number of times won on grass?
|
[['Outcome', 'No.', 'Date', 'Championship', 'Surface', 'Opponent in the final', 'Score in the final'], ['Winner', '2.', 'February 14, 1994', 'Memphis, Tennessee, USA', 'Hard', 'Brad Gilbert', '6β4, 7β5'], ['Winner', '6.', 'April 20, 1998', 'Barcelona, Spain', 'Clay', 'Alberto Berasategui', '6β2, 1β6, 6β3, 6β2'], ['Runner-up', '3.', 'August 2, 1993', 'Montreal, Canada', 'Hard', 'Mikael Pernfors', '6β2, 2β6, 5β7'], ['Winner', '7.', 'November 16, 1998', 'Stockholm, Sweden', 'Hard', 'Thomas Johansson', '6β3, 6β4, 6β4'], ['Winner', '1.', 'May 17, 1993', 'Coral Springs, Florida, USA', 'Clay', 'David Wheaton', '6β3, 6β4'], ['Winner', '5.', 'January 15, 1996', 'Sydney, Australia', 'Hard', 'Goran IvaniΕ‘eviΔ', '5β7, 6β3, 6β4'], ['Runner-up', '9.', 'February 26, 1996', 'Memphis, Tennessee, USA', 'Hard (i)', 'Pete Sampras', '4β6, 6β7(2β7)'], ['Runner-up', '1.', 'February 15, 1993', 'Memphis, Tennessee, USA', 'Hard (i)', 'Jim Courier', '7β5, 6β7(4β7), 6β7(4β7)'], ['Winner', '3.', 'June 13, 1994', "London (Queen's Club), UK", 'Grass', 'Pete Sampras', '7β6(7β4), 7β6(7β4)'], ['Runner-up', '8.', 'December 18, 1995', 'Grand Slam Cup, Munich, Germany', 'Carpet', 'Goran IvaniΕ‘eviΔ', '6β7(4β7), 3β6, 4β6']]
|
1
|
Answer:
| 128
| 10
| 523
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:who won the most gold medals?
|
[['Rank', 'Nation', 'Gold', 'Silver', 'Bronze', 'Total'], ['9', 'Aruba', '0', '0', '1', '1'], ['7', 'Ecuador', '0', '2', '2', '4'], ['3', 'Colombia', '2', '3', '4', '9'], ['9', 'Netherlands Antilles', '0', '0', '1', '1'], ['1', 'Brazil', '7', '5', '3', '15'], ['6', 'Peru', '1', '1', '2', '4'], ['4', 'Chile', '2', '0', '2', '4'], ['2', 'Venezuela', '3', '2', '8', '13'], ['9', 'Uruguay', '0', '0', '1', '1'], ['9', 'Panama', '0', '0', '1', '1'], ['5', 'Argentina', '1', '2', '5', '8'], ['Total', 'Total', '16', '16', '30', '62'], ['8', 'Guyana', '0', '1', '0', '1']]
|
Brazil
|
Answer:
| 128
| 13
| 267
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:total wins by belgian riders
|
[['Place', 'Rider', 'Country', 'Team', 'Points', 'Wins'], ['10', 'Dave Bickers', 'United Kingdom', 'ΔZ', '1076', '0'], ['8', 'Gaston Rahier', 'Belgium', 'ΔZ', '1112', '0'], ['6', 'Heikki Mikkola', 'Finland', 'Husqvarna', '1680', '2'], ['15', 'Brad Lackey', 'United States', 'ΔZ', '603', '0'], ['17', 'John DeSoto', 'United States', 'Suzuki', '425', '0'], ['9', 'Pierre Karsmakers', 'Netherlands', 'Husqvarna', '1110', '0'], ['14', 'Mark Blackwell', 'United States', 'Husqvarna', '604', '0'], ['20', 'Peter Lamppu', 'United States', 'Montesa', '309', '0'], ['2', 'Adolf Weil', 'Germany', 'Maico', '2331', '2'], ['3', 'Torlief Hansen', 'Sweden', 'Husqvarna', '2052', '0'], ['19', 'Uno Palm', 'Sweden', 'Husqvarna', '324', '0'], ['11', 'John Banks', 'United Kingdom', 'ΔZ', '971', '0'], ['18', 'Chris Horsefield', 'United Kingdom', 'ΔZ', '416', '0'], ['12', 'Andy Roberton', 'United Kingdom', 'Husqvarna', '810', '0'], ['5', 'Joel Robert', 'Belgium', 'Suzuki', '1730', '1'], ['7', 'Willy Bauer', 'Germany', 'Maico', '1276', '0'], ['1', 'Sylvain Geboers', 'Belgium', 'Suzuki', '3066', '3'], ['13', 'Vlastimil Valek', 'Czechoslovakia', 'ΔZ', '709', '0'], ['4', 'Roger De Coster', 'Belgium', 'Suzuki', '1865', '3'], ['16', 'Gary Jones', 'United States', 'Yamaha', '439', '0']]
|
7
|
Answer:
| 128
| 20
| 503
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what yacht had the next best time (smaller time is better) than ausmaid?
|
[['Position', 'Sail Number', 'Yacht', 'State/Country', 'Yacht Type', 'LOA\\n(Metres)', 'Skipper', 'Elapsed Time\\nd:hh:mm:ss'], ['1', 'US17', 'Sayonara', 'USA', 'Farr ILC Maxi', '24.13', 'Larry Ellison', '2:19:03:32'], ['6', 'SM1', 'Fudge', 'VIC', 'Elliot 56', '17.07', 'Peter Hansen', '3:11:00:26'], ['3', 'YC1000', 'Ausmaid', 'SA', 'Farr 47', '14.24', 'Kevan Pearce', '3:06:02:29'], ['10', '8338', 'AFR Midnight Rambler', 'NSW', 'Hick 35', '10.66', 'Ed Psaltis\\nBob Thomas', '3:16:04:40'], ['4', 'AUS70', 'Ragamuffin', 'NSW', 'Farr 50', '15.15', 'Syd Fischer', '3:06:11:29'], ['2', 'C1', 'Brindabella', 'NSW', 'Jutson 79', '24.07', 'George Snow', '2:21:55:06'], ['8', '9090', 'Industrial Quest', 'QLD', 'Nelson Marek 43', '13.11', 'Kevin Miller', '3:14:58:46'], ['9', '4826', 'Aspect Computing', 'NSW', 'Radford 16.5 Sloop', '16.50', 'David Pescud', '3:15:28:24'], ['5', 'COK1', 'Nokia', 'CI', 'Farr Ketch Maxi', '25.20', 'David Witt', '3:09:19:00'], ['7', '6606', 'Quest', 'NSW', 'Nelson Marek 46', '14.12', 'Bob Steel', '3:14:41:28']]
|
Brindabella
|
Answer:
| 128
| 10
| 466
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what match comes after gl-b-5?
|
[['Match', 'Date', 'Venue', 'Opponents', 'Score'], ['GL-B-1', '2008..', '[[]]', '[[]]', '-'], ['Quarterfinals-1', '2008..', '[[]]', '[[]]', '-'], ['GL-B-5', '2008..', '[[]]', '[[]]', '-'], ['GL-B-6', '2008..', '[[]]', '[[]]', '-'], ['Quarterfinals-2', '2008..', '[[]]', '[[]]', '-'], ['GL-B-4', '2008..', '[[]]', '[[]]', '-'], ['GL-B-3', '2008..', '[[]]', '[[]]', '-'], ['GL-B-2', '2008..', '[[]]', '[[]]', '-']]
|
GL-B-6
|
Answer:
| 128
| 8
| 170
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many times was amanda on the judging panel?
|
[['Series', 'Premiere', 'Finale', 'Winner', 'Runner-up', 'Third place', 'Host(s)', 'Judging panel', 'Guest judge(s)'], ['One', '9 June 2007', '17 June 2007', 'Paul Potts', 'Damon Scott', 'Connie Talbot', 'Ant & Dec', 'Simon Cowell\\nAmanda Holden\\nPiers Morgan', 'N/A'], ['Three', '11 April 2009', '30 May 2009', 'Diversity', 'Susan Boyle', 'Julian Smith', 'Ant & Dec', 'Simon Cowell\\nAmanda Holden\\nPiers Morgan', 'Kelly Brook'], ['Eight', '12 April 2014', '31 May 2014', 'TBA', 'TBA', 'TBA', 'Ant & Dec', 'Simon Cowell\\nAmanda Holden\\nAlesha Dixon\\nDavid Walliams', 'Ant & Dec'], ['Five', '16 April 2011', '4 June 2011', 'Jai McDowall', 'Ronan Parke', 'New Bounce', 'Ant & Dec', 'Simon Cowell\\nAmanda Holden\\nDavid Hasselhoff\\nMichael McIntyre', 'Louis Walsh'], ['Six', '24 March 2012', '12 May 2012', 'Ashleigh and Pudsey', 'Jonathan and Charlotte', 'Only Boys Aloud', 'Ant & Dec', 'Simon Cowell\\nAmanda Holden\\nAlesha Dixon\\nDavid Walliams', 'Carmen Electra'], ['Four', '17 April 2010', '5 June 2010', 'Spelbound', 'Twist and Pulse', 'Kieran Gaffney', 'Ant & Dec', 'Simon Cowell\\nAmanda Holden\\nPiers Morgan', 'Louis Walsh'], ['Seven', '13 April 2013', '8 June 2013', 'Attraction', 'Jack Carroll', 'Richard & Adam', 'Ant & Dec', 'Simon Cowell\\nAmanda Holden\\nAlesha Dixon\\nDavid Walliams', 'N/A'], ['Nine', '2015', '2015', 'TBA', 'TBA', 'TBA', 'Ant & Dec', 'TBA', 'TBA'], ['Two', '12 April 2008', '31 May 2008', 'George Sampson', 'Signature', 'Andrew Johnston', 'Ant & Dec', 'Simon Cowell\\nAmanda Holden\\nPiers Morgan', 'N/A']]
|
3
|
Answer:
| 128
| 9
| 546
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many awards has leona lewis won?
|
[['Year', 'Award', 'Nominated work', 'Category', 'Result'], ['2009', 'APRA Awards', '"Bleeding Love"', 'Most Played Foreign Work', 'Won'], ['2007', 'The Record of the Year', '"Bleeding Love"', 'The Record of the Year', 'Won'], ['2008', 'NME Best Album', '"Spirit"', 'Best Album', 'Nominated'], ['2008', 'Nickelodeon UK Kids Choice Awards', '"Bleeding Love"', 'Favourite Song', 'Won'], ['2007', 'Cosmopolitan Ultimate Woman of the Year', 'Leona Lewis', 'Newcomer of the Year', 'Won'], ['2008', 'New Music Weekly Awards', 'Leona Lewis', 'Top 40 New Artist of the Year', 'Won'], ['2009', 'Cosmopolitan Awards', 'Leona Lewis', 'Ultimate Music Star', 'Won'], ['2008', 'Capital Awards', 'Leona Lewis', 'Favourite UK Female Artist', 'Won'], ['2009', 'BEFFTA Awards', 'Leona Lewis', 'Best Female Act', 'Won'], ['2008', 'Bambi Award', 'Leona Lewis', 'Shooting Star', 'Won'], ['2009', 'HITO Pop Music Awards', '"Bleeding Love"', 'Best Western Song', 'Won'], ['2008', 'Glamour Woman Of The Year Awards', 'Leona Lewis', 'UK Solo Artist', 'Won'], ['2008', 'Billboard 2008 Year End Award', 'Leona Lewis', 'Best New Artist', 'Won'], ['2008', 'Vh1 Video of the Year', '"Bleeding Love"', 'Best Video', 'Won'], ['2008', 'NewNowNext Awards', 'Leona Lewis', 'The Kylie Award: Next International Crossover', 'Won'], ['2009', 'Swiss Music Awards', 'Leona Lewis', 'Best International Newcomer', 'Won'], ['2008', 'PETA', 'Leona Lewis', 'Person Of The Year', 'Won'], ['2008', 'UK Music Video Awards', '"Bleeding Love"', "People's Choice Award", 'Won'], ['2009', 'PETA - Sexiest Vegetarian Alive Awards', 'Leona Lewis', 'Sexiest Vegetarian Celebrity 2009', 'Won'], ['2008', "Britain's Best", 'Leona Lewis', 'Music Award', 'Won']]
|
20
|
Answer:
| 128
| 20
| 526
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:who was the top scorer in the last season?
|
[['Season', 'League\\nPos.', 'League\\nCompetition', 'League\\nTop scorer', 'Danish Cup', 'Europe', 'Others'], ['2007-08', '8', '2007-08 Superliga', 'Morten Rasmussen (7)\\nMartin Ericsson (7)', 'Winner', '', ''], ['1999-00', '2', '1999-00 Superliga', 'Bent Christensen (13)', 'Semi-final', 'EC1 qual 3rd round\\nEC3 1st round', ''], ['1981-82', '4', '1982 1st Division', 'Michael Laudrup (15)', '4th round', '', ''], ['1985-86', '2', '1986 1st Division', 'Claus Nielsen (16)', 'Quarter-final', '', ''], ['2004-05', '1', '2004-05 Superliga', 'Thomas Kahlenberg (13)', 'Winner', 'EC3 qual 2nd round', 'Royal League group stage'], ['1996-97', '1', '1996-97 Superliga', 'Peter MΓΈller (22)', 'Semi-final', 'EC1 qualification round\\nEC3 quarter-final', 'Danish Supercup winner'], ['2009-10', '3', '2009-10 Superliga', 'Morten Rasmussen (12)', '4th round', 'EC3 qual play-off round', ''], ['2010-11', '3', '2010-11 Superliga', 'Michael Krohn-Dehli (11)', '', '', ''], ['1990-91', '1', '1991 Superliga', 'Bent Christensen (11)', 'Semi-final', 'EC3 semi-final', ''], ['1987-88', '1', '1988 1st Division', 'Bent Christensen (21)', 'Finalist', 'EC3 2nd round', ''], ['2008-09', '3', '2008-09 Superliga', 'Morten Rasmussen (9)\\nAlexander Farnerud (9)\\nOusman Jallow (9)', 'Semi-final', 'EC3 1st round', ''], ['1988-89', '2', '1989 1st Division', 'Bent Christensen (10)', 'Winner', 'EC1 1st round', '']]
|
Simon Makienok Christoffersen
|
Answer:
| 128
| 12
| 528
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many jury members were there?
|
[['Contestant', 'Original Tribe', 'Switched Tribe', 'Merged Tribe', 'Finish', 'Total Votes'], ['Dana Borisova\\n26.the TV presenter', 'Pelicans', 'Barracudas', '', '4th Voted Out\\nDay 12', '5'], ['Yelena Kondulaynen\\n44.the actress', 'Pelicans', '', '', '1st Voted Out\\nDay 3', '5'], ['Marina Aleksandrova\\n20.the actress', 'Barracudas', 'Pelicans', 'Crocodiles', '9th Voted Out\\n4th Jury Member\\nDay 27', '6'], ['Vera Glagoleva\\n46.the actress', '', '', 'Crocodiles', '11th Voted Out\\n6th Jury Member\\nDay 33', '4'], ['Ivar Kalnynsh\\n54.the actor', '', '', 'Crocodiles', '10th Voted Out\\n5th Jury Member\\nDay 30', '3'], ['Viktor Gusev\\n47.the sport commentator', 'Pelicans', 'Pelicans', 'Crocodiles', '7th Voted Out\\n1st Jury Member\\nDay 21', '6'], ["Tat'yana Ovsiyenko\\n36.the singer", 'Barracudas', 'Pelicans', '', 'Eliminated\\nDay 19', '1'], ['Tatyana Dogileva\\n45.the actress', 'Pelicans', 'Barracudas', '', '6th Voted Out\\nDay 18', '3'], ['Vladimir Presnyakov, Jr.\\n34.the singer', 'Pelicans', 'Pelicans', 'Crocodiles', 'Sole Survivor', '6'], ['Yelena Perova\\n26.the singer', 'Pelicans', 'Pelicans', 'Crocodiles', 'Runner-Up', '2'], ['Yelena Proklova\\n49.the TV presenter', 'Pelicans', 'Barracudas', 'Crocodiles', '8th Voted Out\\n3rd Jury Member\\nDay 24', '4'], ['Aleksandr Lykov\\n41.the actor', 'Barracudas', 'Barracudas', 'Crocodiles', '13th Voted Out\\n8th Jury Member\\nDay 37', '6']]
|
9
|
Answer:
| 128
| 12
| 525
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many times was the val d'lsere, france location used?
|
[['Season', 'Age', 'Overall', 'Slalom', 'Giant\\nSlalom', 'Super G', 'Downhill', 'Combined'], ['Season', 'Date', 'Location', 'Race', '', '', '', ''], ['2012', '25', '24', 'β', '16', '28', '17', '19'], ['2010', '6 Dec 2009', 'Beaver Creek, USA', 'Giant Slalom', '', '', '', ''], ['2014', '27', '18', 'β', '25', '14', '20', '11'], ['2013', '26', '48', 'β', '48', '27', '38', '4'], ['2009', '13 Dec 2008', "Val d'IsΓ¨re, France", 'Giant slalom', '', '', '', ''], ['2011', '5 Mar 2011', 'Kranjska Gora, Slovenia', 'Giant Slalom', '', '', '', ''], ['2010', '10 Mar 2010', 'Garmisch, Germany', 'Downhill', '', '', '', ''], ['2010', '4 Dec 2009', 'Beaver Creek, USA', 'Super Combined', '', '', '', ''], ['2008', '21', '64', 'β', '28', '46', '46', '31'], ['2010', '16 Jan 2010', 'Wengen, Switzerland', 'Downhill', '', '', '', ''], ['2010', '23', '1', 'β', '2', '6', '2', '2'], ['2010', '5 Dec 2009', 'Beaver Creek, USA', 'Downhill', '', '', '', ''], ['2009', '22', '7', 'β', '6', '16', '16', '1'], ['2011', '24', '3', 'β', '5', '6', '9', '6'], ['2007', '20', '130', 'β', '40', 'β', 'β', 'β'], ['2010', '12 Mar 2010', 'Garmisch, Germany', 'Giant Slalom', '', '', '', ''], ['2009', '16 Jan 2009', 'Wengen, Switzerland', 'Super Combined', '', '', '', '']]
|
1
|
Answer:
| 128
| 18
| 505
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what is the name listed before mount pleasant line?
|
[['Route', 'Name', 'Fare Type', 'Terminals', 'Terminals', 'Major streets', 'Notes', 'History'], ['H2, H3, H4', 'Crosstown Line', 'Local', 'Tenleytown-AU station', 'Brookland-CUA station', 'Wisconsin Avenue\\nPorter Street NW\\nVan Ness/Veazey Street NW (H2)\\nConnecticut Avenue (H2)\\nColumbia Road NW/Irving Street NW\\nMichigan Avenue NW/NE', 'H3: weekday peak hour service only\\nH3: Skips Washington Hospital Center', "H2 & H4 operated to Fort Lincoln (east of Brookland station) until replaced by H6 in the late 1990s. They also operated to Westmoreland Circle & Western Avenue NW (west of Tenleytown station) until replaced by the N8 in the late 1990s. H3's route west of Porter Street & Connecticut Avenue NW was served by H2 until it was rerouted to serve and terminate at Van Ness Station in the early 2000s. H2 was later rerouted back to its Tenleytown terminus, replacing the N8 route east of Tenleytown and rerouting the H3 to serve exactly the same route as the H4 with the exception of Washington Hospital Center."], ['W2, W3', 'United Medical Center-Anacostia Line', 'Local', 'United Medical Center', 'Washington Overlook (Mellon St & Martin Luther King Av SE)\\nAnacostia station', 'Southern Avenue\\nAlabama Avenue SE\\nMorris Road SE\\nMartin Luther King Avenue SE', 'W3: Monday-Friday service only.\\n\\nFare: $1 (unless transferring to another bus)', '(Portions of the W2 & W3 operate on the old M18 & M20 (Metro "Mini-Bus") routes'], ['W1', 'Shipley Terrace-Fort Drum Line', 'Local', 'Fort Drum', 'Southern Avenue station', 'Alabama Avenue SE\\nMartin Luther King Jr Avenue', 'W1: Monday-Friday service only.', 'W1 replace the M8, M9 on March 3, 2014.']]
|
Pennsylvania Avenue Metro Extra Line
|
Answer:
| 128
| 3
| 478
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what is the last stadium listed on this chart?
|
[['Team', 'Stadium', 'Capacity', 'City/Area'], ['Leeds Rhinos (2014 season)', 'Headingley Carnegie Stadium', '22,250', 'Leeds, West Yorkshire'], ['Hull Kingston Rovers (2014 season)', 'MS3 Craven Park', '9,471', 'Kingston upon Hull, East Riding of Yorkshire'], ['Widnes Vikings (2014 season)', 'The Select Security Stadium', '13,500', 'Widnes, Cheshire, England'], ['Huddersfield Giants (2014 season)', "John Smith's Stadium", '24,544', 'Huddersfield, West Yorkshire'], ['Bradford Bulls (2014 season)', 'Provident Stadium', '27,000', 'Bradford, West Yorkshire'], ['Wigan Warriors (2014 season)', 'DW Stadium', '25,138', 'Wigan, Greater Manchester'], ['Warrington Wolves (2014 season)', 'Halliwell Jones Stadium', '15,500', 'Warrington, Cheshire'], ['Wakefield Trinity Wildcats (2014 season)', 'Rapid Solicitors Stadium', '11,000', 'Wakefield, West Yorkshire'], ['Catalans Dragons (2014 season)', 'Stade Gilbert Brutus', '14,000', 'Perpignan, PyrΓ©nΓ©es-Orientales, France'], ['St Helens RLFC (2014 season)', 'Langtree Park', '18,000', 'St Helens, Merseyside'], ['London Broncos (2014 season)', 'Twickenham Stoop', '12,700', 'Twickenham, London'], ['Salford City Reds (2014 season)', 'Salford City Stadium', '12,000', 'Salford, Greater Manchester'], ['Castleford Tigers (2014 season)', 'The Wish Communications Stadium', '11,750', 'Castleford, West Yorkshire'], ['Hull (2014 season)', 'Kingston Communications Stadium', '25,404', 'Kingston upon Hull, East Riding of Yorkshire']]
|
DW Stadium
|
Answer:
| 128
| 14
| 432
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many times did salvatore bettiol win first place across competitions?
|
[['Year', 'Competition', 'Venue', 'Position', 'Event', 'Notes'], ['1991', 'World Championships', 'Tokyo, Japan', '6th', 'Marathon', '2:15:58'], ['1990', 'European Championships', 'Split, FR Yugoslavia', '4th', 'Marathon', '2:17:45'], ['1992', 'Olympic Games', 'Barcelona, Spain', '5th', 'Marathon', '2:14:15'], ['1996', 'Olympic Games', 'Atlanta, United States', '20th', 'Marathon', '2:17:27'], ['1993', 'World Championships', 'Stuttgart, Germany', 'β', 'Marathon', 'DNF'], ['1986', 'Venice Marathon', 'Venice, Italy', '1st', 'Marathon', '2:18:44'], ['1987', 'Venice Marathon', 'Venice, Italy', '1st', 'Marathon', '2:10:01'], ['1987', 'World Championships', 'Rome, Italy', '13th', 'Marathon', '2:17:45']]
|
2
|
Answer:
| 128
| 8
| 253
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:which year did illinois not have any losses during the conference?
|
[['School', 'Season', 'Record', 'Conference Record', 'Place', 'Postseason'], ['Illinois', '1917β18', '9β6', '6β6', 'T4th', ''], ['Illinois', '1913β14', '9β4', '7β3', '3rd', ''], ['Illinois', '1914β15', '16β0', '12β0', 'T1st', 'National Champions'], ['Illinois', '1912β20', '85β34', '64β31', 'β', ''], ['Illinois', '1916β17', '13β3', '10β2', 'T1st', 'Big Ten Champions'], ['Illinois', '1912β13', '10β6', '7β6', '5th', ''], ['Illinois', '1915β16', '13β3', '9β3', 'T2nd', ''], ['Illinois', '1918β19', '6β8', '5β7', '5th', ''], ['Illinois', '1919β20', '9β4', '8β4', '3rd', '']]
|
1914-15
|
Answer:
| 128
| 9
| 262
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:natalia varnakova is the same height as which other contestant(s)?
|
[['Represent', 'Candidate', 'in Russian', 'Age', 'Height', 'Hometown'], ['Saratov Oblast', 'Anastasija Marnolova', 'ΠΠ½Π°ΡΡΠ°ΡΠΈΡ ΠΠ°ΡΠ½ΠΎΠ»ΠΎΠ²Π°', '21', '1.74\xa0m (5\xa0ft 8\xa01β2\xa0in)', 'Saratov'], ['Capital City', 'Natalia Varnakova', 'ΠΠ°ΡΠ°Π»ΠΈΠ° ΠΠ°ΡΠ½Π°ΠΊΠΎΠ²Π°', '19', '1.80\xa0m (5\xa0ft 11\xa0in)', 'Moscow'], ['Chelyabinsk Oblast', 'Tatiana Abramenko', 'Π’Π°ΡΠΈΠ°Π½Π° ΠΠ±ΡΠ°ΠΌΠ΅Π½ΠΊΠΎ', '21', '1.74\xa0m (5\xa0ft 8\xa01β2\xa0in)', 'Chelyabinsk'], ['Oryol Oblast', 'Natalia PavΕ‘ukova', 'ΠΠ°ΡΠ°Π»ΠΈΠ° ΠΠ°Π²ΡΡΠΊΠΎΠ²Π°', '19', '1.79\xa0m (5\xa0ft 10\xa01β2\xa0in)', 'Oryol'], ['Novgorod Oblast', 'Ekaterina Ε½uravleva', 'ΠΠΊΠ°ΡΠ΅ΡΠΈΠ½Π° ΠΡΡΠ°Π²Π»Π΅Π²Π°', '20', '1.81\xa0m (5\xa0ft 11\xa01β2\xa0in)', 'Novgorod'], ['Sakha Republic', 'Sardana Syromyatnikova', 'Π‘Π°ΡΠ΄Π°Π½Π° Π‘ΡΡΠΎΠΌΡΠ°ΡΠ½ΠΈΠΊΠΎΠ²Π°', '19', '1.82\xa0m (5\xa0ft 11\xa01β2\xa0in)', 'Yakutia'], ['Mari El Republic', 'Anna Ilβina', 'ΠΠ½Π½Π° ΠΠ»ΡΠΈΠ½Π°', '19', '1.88\xa0m (6\xa0ft 2\xa0in)', 'Medvedevo'], ['Chukotka Okrug', 'Mariesea MnesiΔu', 'ΠΠ°ΡΠΈΠ΅ΡΠ΅Π° ΠΠ½Π΅ΡΠΈΡΡ', '19', '1.80\xa0m (5\xa0ft 11\xa0in)', 'Anadyr'], ['Belgorod Oblast', 'Jahaira Novgorodova', 'Π―Ρ
Π°ΠΈΡΠ° ΠΠΎΠ²Π³ΠΎΡΠΎΠ΄ΠΎΠ²Π°', '25', '1.80\xa0m (5\xa0ft 11\xa0in)', 'Belgorod']]
|
Jahaira Novgorodova, Carmen Jenockova, Mariesea MnesiΔu, Patricia Valiahmetova, Anastasija Larkova
|
Answer:
| 128
| 9
| 506
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many candidates belong to a party other than republican or democrat?
|
[['District', 'Incumbent', '2008 Status', 'Democratic', 'Republican'], ['4', 'Marilyn Musgrave', 'Re-election', 'Betsy Markey', 'Marilyn Musgrave'], ['5', 'Doug Lamborn', 'Re-election', 'Hal Bidlack', 'Doug Lamborn'], ['1', 'Diana DeGette', 'Re-election', 'Diana DeGette', 'George Lilly'], ['2', 'Mark Udall', 'Open', 'Jared Polis', 'Scott Starin'], ['6', 'Tom Tancredo', 'Open', 'Hank Eng', 'Mike Coffman'], ['3', 'John Salazar', 'Re-election', 'John Salazar', 'Wayne Wolf'], ['7', 'Ed Perlmutter', 'Re-election', 'Ed Perlmutter', 'John W. Lerew']]
|
0
|
Answer:
| 128
| 7
| 185
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many competitions were not in the united kingdom?
|
[['Date', 'Competition', 'Location', 'Country', 'Event', 'Placing', 'Rider', 'Nationality'], ['1 November 2009', '2009β10 World Cup', 'Manchester', 'United Kingdom', 'Team sprint', '1', 'Ross Edgar', 'GBR'], ['2 November 2008', '2008β09 World Cup', 'Manchester', 'United Kingdom', 'Team sprint', '1', 'Jason Kenny', 'GBR'], ['13 February 2009', '2008β09 World Cup', 'Copenhagen', 'Denmark', 'Team sprint', '1', 'Jamie Staff', 'GBR'], ['31 October 2008', '2008β09 World Cup', 'Manchester', 'United Kingdom', 'Keirin', '2', 'Jason Kenny', 'GBR'], ['30 October 2009', '2009β10 World Cup', 'Manchester', 'United Kingdom', 'Sprint', '1', 'Chris Hoy', 'GBR'], ['2 November 2008', '2008β09 World Cup', 'Manchester', 'United Kingdom', 'Team sprint', '1', 'Ross Edgar', 'GBR'], ['30 October 2009', '2009β10 World Cup', 'Manchester', 'United Kingdom', '500 m time trial', '2', 'Victoria Pendleton', 'GBR'], ['2 November 2008', '2008β09 World Cup', 'Manchester', 'United Kingdom', 'Keirin', '1', 'Victoria Pendleton', 'GBR'], ['1 November 2009', '2009β10 World Cup', 'Manchester', 'United Kingdom', 'Team sprint', '1', 'Chris Hoy', 'GBR'], ['1 November 2009', '2009β10 World Cup', 'Manchester', 'United Kingdom', 'Team sprint', '1', 'Jamie Staff', 'GBR'], ['13 February 2009', '2008β09 World Cup', 'Copenhagen', 'Denmark', 'Sprint', '1', 'Victoria Pendleton', 'GBR'], ['1 November 2008', '2008β09 World Cup', 'Manchester', 'United Kingdom', 'Sprint', '1', 'Jason Kenny', 'GBR'], ['13 February 2009', '2008β09 World Cup', 'Copenhagen', 'Denmark', 'Team sprint', '1', 'Jason Kenny', 'GBR']]
|
4
|
Answer:
| 128
| 13
| 519
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many domestic routes out of houston intercontinental have united as a carrier?
|
[['Rank', 'City', 'Passengers', 'Top Carriers'], ['1', 'Los Angeles, CA', '700,000', 'American, Spirit, United'], ['4', 'San Francisco, CA', '492,000', 'United'], ['10', 'Phoenix, AZ', '393,000', 'United, US Airways'], ['7', 'Las Vegas, NV', '442,000', 'Spirit, United'], ['9', 'Atlanta, GA', '400,000', 'Delta, United'], ['2', 'Chicago, IL', '673,000', 'American, Spirit, United'], ['5', 'Dallas/Fort Worth, TX', '488,000', 'American, United'], ['6', 'Newark, NJ', '480,000', 'United'], ['8', 'Charlotte, NC', '441,000', 'United, US Airways'], ['3', 'Denver, CO', '654,000', 'Frontier, Spirit, United']]
|
10
|
Answer:
| 128
| 10
| 207
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:in total, how many germans are listed?
|
[['Place', 'Rider', 'Country', 'Team', 'Points', 'Wins'], ['10', 'Dave Bickers', 'United Kingdom', 'ΔZ', '1076', '0'], ['3', 'Torlief Hansen', 'Sweden', 'Husqvarna', '2052', '0'], ['16', 'Gary Jones', 'United States', 'Yamaha', '439', '0'], ['2', 'Adolf Weil', 'Germany', 'Maico', '2331', '2'], ['8', 'Gaston Rahier', 'Belgium', 'ΔZ', '1112', '0'], ['11', 'John Banks', 'United Kingdom', 'ΔZ', '971', '0'], ['5', 'Joel Robert', 'Belgium', 'Suzuki', '1730', '1'], ['4', 'Roger De Coster', 'Belgium', 'Suzuki', '1865', '3'], ['19', 'Uno Palm', 'Sweden', 'Husqvarna', '324', '0'], ['17', 'John DeSoto', 'United States', 'Suzuki', '425', '0'], ['1', 'Sylvain Geboers', 'Belgium', 'Suzuki', '3066', '3'], ['15', 'Brad Lackey', 'United States', 'ΔZ', '603', '0'], ['7', 'Willy Bauer', 'Germany', 'Maico', '1276', '0'], ['20', 'Peter Lamppu', 'United States', 'Montesa', '309', '0'], ['6', 'Heikki Mikkola', 'Finland', 'Husqvarna', '1680', '2'], ['12', 'Andy Roberton', 'United Kingdom', 'Husqvarna', '810', '0'], ['14', 'Mark Blackwell', 'United States', 'Husqvarna', '604', '0'], ['18', 'Chris Horsefield', 'United Kingdom', 'ΔZ', '416', '0'], ['13', 'Vlastimil Valek', 'Czechoslovakia', 'ΔZ', '709', '0'], ['9', 'Pierre Karsmakers', 'Netherlands', 'Husqvarna', '1110', '0']]
|
2
|
Answer:
| 128
| 20
| 503
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:in what year are there the first results for giant slalom?
|
[['Season', 'Age', 'Overall', 'Slalom', 'Giant\\nSlalom', 'Super G', 'Downhill', 'Combined'], ['2005', '18', '37', 'β', '27', '18', '49', 'β'], ['2006', '19', '22', 'β', '18', '37', '15', 'β'], ['2004', '17', '112', 'β', 'β', '51', 'β', 'β'], ['2013', '26', '37', 'β', '17', '28', '30', 'β'], ['2007', '20', '33', 'β', '50', '15', '23', 'β'], ['2010', '23', '28', 'β', 'β', '13', '23', 'β'], ['2008', '21', '38', 'β', 'β', '35', '13', 'β'], ['2009', '22', '9', 'β', '40', '2', '5', '50'], ['2011', '24', 'Injured, did not compete', 'Injured, did not compete', 'Injured, did not compete', 'Injured, did not compete', 'Injured, did not compete', 'Injured, did not compete'], ['2012', '25', '75', 'β', '28', 'β', 'β', 'β']]
|
2005
|
Answer:
| 128
| 10
| 312
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:in cycle 4 of austria's next top model,how many contestants were older than 20?
|
[['Contestant', 'Age', 'Height', 'Home City', 'Rank'], ['Alina Chlebecek', '18', '170\xa0cm (5\xa0ft 7 in)', 'Deutsch-Wagram', 'Eliminated in Episode 1'], ['Michaela Schopf', '21', '172\xa0cm (5\xa0ft 7.5 in)', 'Salzburg (originally from Germany)', 'Quit in Episode 4'], ['Melisa PopaniciΔ', '16', '175\xa0cm (5\xa0ft 9 in)', 'WΓΆrgl', '2nd Eliminated in Episode 10'], ['Gina Zeneb Adamu', '17', '175\xa0cm (5\xa0ft 9 in)', 'Bad VΓΆslau', 'Runner-Up'], ['Katharina MihaloviΔ', '23', '179\xa0cm (5\xa0ft 10.5 in)', 'Vienna', 'Eliminated in Episode 2'], ['Isabelle Raisa', '16', '170\xa0cm (5\xa0ft 7 in)', 'Vienna', 'Eliminated in Episode 1'], ['Christine Riener', '20', '181\xa0cm (5\xa0ft 11.25 in)', 'Bludenz', 'Eliminated in Episode 4'], ['Izabela Pop KostiΔ', '20', '170\xa0cm (5\xa0ft 7 in)', 'Vienna (originally from Bosnia)', 'Eliminated in Episode 8'], ['Nadine Trinker', '21', '183\xa0cm (6\xa0ft 0 in)', 'Bodensdorf', 'Eliminated in Episode 9'], ['Bianca Ebelsberger', '24', '179\xa0cm (5\xa0ft 10.5 in)', 'Aurach am Hongar', 'Eliminated in Episode 9'], ['Sabrina Angelika Rauch β ', '21', '175\xa0cm (5\xa0ft 9 in)', 'Graz', 'Eliminated in Episode 2'], ['Antonia Maria Hausmair', '16', '175\xa0cm (5\xa0ft 9 in)', 'Siegendorf', 'Winner'], ['Yemisi Rieger', '17', '177\xa0cm (5\xa0ft 9.5 in)', 'Vienna', 'Eliminated in Episode 7']]
|
5
|
Answer:
| 128
| 13
| 528
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:who scored more goals: clint dempsey or eric wynalda?
|
[['#', 'Player', 'Goals', 'Caps', 'Career'], ['6T', 'Bruce Murray', '21', '86', '1985β1993'], ['6T', 'Jozy Altidore', '21', '67', '2007βpresent'], ['3', 'Eric Wynalda', '34', '106', '1990β2000'], ['5', 'Joe-Max Moore', '24', '100', '1992β2002'], ['1', 'Landon Donovan', '57', '155', '2000βpresent'], ['4', 'Brian McBride', '30', '95', '1993β2006'], ['9T', 'Earnie Stewart', '17', '101', '1990β2004'], ['2', 'Clint Dempsey', '36', '103', '2004βpresent'], ['9T', 'DaMarcus Beasley', '17', '114', '2001βpresent'], ['8', 'Eddie Johnson', '19', '62', '2004βpresent']]
|
Clint Dempsey
|
Answer:
| 128
| 10
| 229
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what building had the least height in germany?
|
[['Name', 'Country', 'Town', 'Height\\nmetres / ft', 'Structural type', 'Held record', 'Notes'], ['Chrysler Building', 'United States', 'New York City', '319 / 1,046', 'Skyscraper', '1930β1931', ''], ['Empire State Building', 'United States', 'New York City', '448 / 1,472', 'Skyscraper', '1931β1967', ''], ["St. Mary's Church", 'Germany', 'Stralsund', '151 / 500', 'Church', '1549β1647', 'Spire destroyed by lightning in 1647; today stands at a height of 104 metres (341\xa0ft).'], ['CN Tower', 'Canada', 'Toronto', '553 / 1,815', 'Tower', '1976β2007', ''], ['Strasbourg Cathedral', 'Germany and/or France (today France)', 'Strasbourg', '142 / 470', 'Church', '1647β1874', ''], ['Lincoln Cathedral', 'England', 'Lincoln', '159.7 / 524', 'Church', '1311β1549', 'Spire collapsed in 1549; today, stands at a height of 83 metres (272\xa0ft).'], ['Cologne Cathedral', 'Germany', 'Cologne', '157.4 / 516', 'Church', '1880β1884', ''], ['Notre-Dame Cathedral', 'France', 'Rouen', '151 / 500', 'Church', '1876β1880', ''], ['Eiffel Tower', 'France', 'Paris', '300.6 / 986', 'Tower', '1889β1930', 'Currently stands at a height of 324 metres (1,063\xa0ft).'], ['Burj Khalifa', 'United Arab Emirates', 'Dubai', '829.8 / 2,722', 'Skyscraper', '2007βpresent', 'Topped-out on 17 January 2009'], ['Washington Monument', 'United States', 'Washington, D.C.', '169.3 / 555', 'Monument', '1884β1889', ''], ['Great Pyramid of Giza', 'Egypt', 'Giza', '146 / 480', 'Mausoleum', '2570 BCβ1311', 'Due to erosion today it stands at the height of 138.8 metres (455\xa0ft).']]
|
St. Mary's Church
|
Answer:
| 128
| 12
| 538
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:besides republican (r) and democrat (d), what other party was represented in the maine election?
|
[['State\\n(linked to\\nsummaries below)', 'Incumbent\\nSenator', 'Incumbent\\nParty', 'Incumbent\\nElectoral\\nhistory', 'Most recent election results', '2018 intent', 'Candidates'], ['Connecticut', 'Chris Murphy', 'Democratic', 'Chris Murphy (D) 54.8%\\nLinda McMahon (R) 43.1%\\nPaul Passarelli (L) 1.7%', '2012', '[Data unknown/missing. You\xa0can\xa0help!]', '[Data unknown/missing. You\xa0can\xa0help!]'], ['Wyoming', 'John Barrasso', 'Republican', 'John Barrasso (R) 75.7%\\nTim Chestnut (D) 21.7%\\nJoel Otto (Wyoming Country) 2.6%', '2008 (special)\\n2012', '[Data unknown/missing. You\xa0can\xa0help!]', '[Data unknown/missing. You\xa0can\xa0help!]'], ['Nebraska', 'Deb Fischer', 'Republican', 'Deb Fischer (R) 57.8%\\nBob Kerrey (D) 42.2%', '2012', '[Data unknown/missing. You\xa0can\xa0help!]', '[Data unknown/missing. You\xa0can\xa0help!]'], ['Florida', 'Bill Nelson', 'Democratic', 'Bill Nelson (D) 55.2%\\nConnie Mack IV (R) 42.2%', '2000\\n2006\\n2012', '[Data unknown/missing. You\xa0can\xa0help!]', '[Data unknown/missing. You\xa0can\xa0help!]'], ['Nevada', 'Dean Heller', 'Republican', 'Dean Heller (R) 45.9%\\nShelley Berkley (D) 44.7%\\nDavid Lory VanderBeek (C) 4.9%\\nNone of These Candidates 4.5%', '2012', '[Data unknown/missing. You\xa0can\xa0help!]', '[Data unknown/missing. You\xa0can\xa0help!]']]
|
Independent
|
Answer:
| 128
| 5
| 480
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:which year did the team have their most total wins?
|
[['Season', 'Conference', 'Head Coach', 'Total Wins', 'Total Losses', 'Total Ties', 'Conference Wins', 'Conference Losses', 'Conference Ties', 'Conference Standing', 'Postseason Result'], ['1993', 'Southern', 'Charlie Taaffe', '5', '6', '0', '4', '4', '0', '4', 'β'], ['1939', 'Southern', 'Tatum Gressette', '3', '8', '0', '0', '4', '0', '15', 'β'], ['1988', 'Southern', 'Charlie Taaffe', '8', '4', '0', '5', '2', '0', '3', 'First Round'], ['1924', 'Southern Intercollegiate', 'Carl Prause', '6', '4', '0', '4', '2', '0', 'β', 'β'], ['1926', 'Southern Intercollegiate', 'Carl Prause', '7', '3', '0', '4', '3', '0', 'β', 'β'], ['1986', 'Southern', 'Tom Moore', '3', '8', '0', '0', '6', '0', '8', 'β'], ['1923', 'Southern Intercollegiate', 'Carl Prause', '5', '3', '1', '2', '1', '1', 'β', 'β'], ['Totals:\\n105 Seasons', '2 Conferences', '23 Head Coaches', 'Total\\nWins\\n473', 'Total\\nLosses\\n536', 'Total\\nTies\\n32', '239 Conference Wins\\n55 SIAA\\n184 SoCon', '379 Conference Losses\\n58 SIAA\\n321 SoCon', '13 Conference Ties\\n8 SIAA\\n5 SoCon', 'Regular Season\\nChampions\\n2 times', '1β0 Bowl Record\\n1β3 Playoff Record'], ['1909', 'Southern Intercollegiate', 'Sam Costen', '4', '3', '2', '0', '1', '1', 'β', 'β'], ['1998', 'Southern', 'Don Powers', '5', '6', '0', '4', '4', '0', '4', 'β'], ['1925', 'Southern Intercollegiate', 'Carl Prause', '6', '4', '0', '4', '2', '0', 'β', 'β']]
|
1992
|
Answer:
| 128
| 11
| 552
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what's the total of deaths that happened in 1939/1940?
|
[['Description Losses', '1939/40', '1940/41', '1941/42', '1942/43', '1943/44', '1944/45', 'Total'], ['Deaths Outside of Prisons & Camps', '', '42,000', '71,000', '142,000', '218,000', '', '473,000'], ['Deaths In Prisons & Camps', '69,000', '210,000', '220,000', '266,000', '381,000', '', '1,146,000'], ['Murdered in Eastern Regions', '', '', '', '', '', '100,000', '100,000'], ['Direct War Losses', '360,000', '', '', '', '', '183,000', '543,000'], ['Total', '504,000', '352,000', '407,000', '541,000', '681,000', '270,000', '2,770,000'], ['Deaths other countries', '', '', '', '', '', '', '2,000'], ['Murdered', '75,000', '100,000', '116,000', '133,000', '82,000', '', '506,000']]
|
504,000
|
Answer:
| 128
| 7
| 263
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what is the total number of models covered in the table?
|
[['Year', 'Manufacturer', 'Model', 'Length (feet)', 'Quantity', 'Fleet Series', 'Fuel Propulsion', 'Powertrain'], ['2008', 'Van Hool', 'A300K', '30', '1', '5099', 'Diesel-electric hybrid', ''], ['2006', 'Van Hool', 'A300K', '30', '50', '5001-5050', 'Diesel', 'Cummins ISB\\nVoith D864.3E'], ['2008', 'Van Hool', 'A300L', '40', '27', '1201-1227', 'Diesel', 'Cummins ISL\\nVoith D864.5'], ['2013', 'New Flyer', 'Xcelsior D60', '60', '23', '2201-2223', 'Diesel', 'Cummins ISL 330 HP\\nAllison B400 6-speed'], ['2003', 'Van Hool', 'AG300', '60', '57', '2001-2057', 'Diesel', 'Cummins ISM\\nVoith D864.3E'], ['2003', 'Van Hool', 'A330', '40', '110', '1001-1110', 'Diesel', 'Cummins ISM\\nVoith D864.3E'], ['2000', 'MCI', 'D4500', '45', '30', '6001-6030', 'Diesel', ''], ['2013', 'Gillig', 'Low-floor Advantage', '40', '55', '6101-6155', 'Diesel', 'Cummins ISL 280 HP\\nAllison B400 6-speed'], ['1998', 'NABI', '416', '40', '133', '3001-3067, 3101-3166*', 'Diesel', 'Cummins M11E\\nAllison B400R'], ['2000', 'NABI', '40-LFW', '40', '23', '7201-7223', 'Diesel', 'Cummins ISM\\nAllison B400R'], ['1999', 'NABI', '40-LFW', '40', '44', '4001-4044', 'Diesel', '']]
|
20
|
Answer:
| 128
| 11
| 503
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what is the number of wins by jaguar xjs?
|
[['Round', 'Date', 'Circuit', 'Winning driver (TA2)', 'Winning vehicle (TA2)', 'Winning driver (TA1)', 'Winning vehicle (TA1)'], ['7', 'August 19', 'Mosport', 'Greg Pickett', 'Chevrolet Corvette', 'Bob Tullius', 'Jaguar XJS'], ['6', 'August 13', 'Brainerd', 'Jerry Hansen', 'Chevrolet Monza', 'Bob Tullius', 'Jaguar XJS'], ['9', 'October 8', 'Laguna Seca', 'Greg Pickett', 'Chevrolet Corvette', 'Bob Tullius', 'Jaguar XJS'], ['4', 'June 25', 'Mont-Tremblant', 'Monte Sheldon', 'Porsche 935', 'Bob Tullius', 'Jaguar XJS'], ['10', 'November 5', 'Mexico City', 'Ludwig Heimrath', 'Porsche 935', 'Bob Tullius', 'Jaguar XJS'], ['1', 'May 21', 'Sears Point', 'Greg Pickett', 'Chevrolet Corvette', 'Gene Bothello', 'Chevrolet Corvette'], ['8', 'September 4', 'Road America', 'Greg Pickett', 'Chevrolet Corvette', 'Bob Tullius', 'Jaguar XJS'], ['3', 'June 11', 'Portland', 'Tuck Thomas', 'Chevrolet Monza', 'Bob Matkowitch', 'Chevrolet Corvette'], ['5', 'July 8', 'Watkins Glenβ‘', 'Hal Shaw, Jr.\\n Monte Shelton', 'Porsche 935', 'Brian Fuerstenau\\n Bob Tullius', 'Jaguar XJS'], ['2', 'June 4', 'Westwood', 'Ludwig Heimrath', 'Porsche 935', 'Nick Engels', 'Chevrolet Corvette']]
|
7
|
Answer:
| 128
| 10
| 426
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:other nations besides peru to earn 2 bronze medals
|
[['Rank', 'Nation', 'Gold', 'Silver', 'Bronze', 'Total'], ['1', 'Brazil', '7', '5', '3', '15'], ['9', 'Netherlands Antilles', '0', '0', '1', '1'], ['9', 'Panama', '0', '0', '1', '1'], ['3', 'Colombia', '2', '3', '4', '9'], ['9', 'Aruba', '0', '0', '1', '1'], ['Total', 'Total', '16', '16', '30', '62'], ['7', 'Ecuador', '0', '2', '2', '4'], ['6', 'Peru', '1', '1', '2', '4'], ['5', 'Argentina', '1', '2', '5', '8'], ['8', 'Guyana', '0', '1', '0', '1'], ['2', 'Venezuela', '3', '2', '8', '13'], ['9', 'Uruguay', '0', '0', '1', '1'], ['4', 'Chile', '2', '0', '2', '4']]
|
Chile, Ecuador
|
Answer:
| 128
| 13
| 267
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many times were consecutive games played against millwall?
|
[['Date', 'Opponents', 'Venue', 'Result', 'Scorers', 'Attendance'], ['11 Sep 1920', 'Plymouth Argyle', 'A', '1β5', 'Wolstenholme', '12,000'], ['28 Aug 1920', 'Reading', 'H', '0β1', '', '14,500'], ['2 Oct 1920', 'Exeter City', 'H', '2β0', 'Wolstenholme 2', '8,000'], ['18 Dec 1920', 'Brentford', 'A', '2β2', 'Wright, Thompson', '6,000'], ['6 Nov 1920', 'Gillingham', 'H', '1β0', 'Wolstenholme', '7,000'], ['9 Sep 1920', 'Bristol Rovers', 'H', '0β2', '', '8,000'], ['1 Sep 1920', 'Bristol Rovers', 'A', '2β3', 'Walker, Wolstenholme', '10,000'], ['7 May 1921', 'Southampton', 'H', '0β0', '', '8,000'], ['27 Dec 1920', 'Southend United', 'A', '1β2', 'Walker', '10,000'], ['26 Mar 1921', 'Queens Park Rangers', 'A', '0β2', '', '10,000'], ['9 Oct 1920', 'Millwall', 'H', '3β1', 'Devlin 2, Walker', '14,000'], ['23 Apr 1921', 'Luton Town', 'A', '2β2', 'Walker, Devlin', '9,000'], ['25 Mar 1921', 'Merthyr Town', 'H', '0β3', '', '12,600'], ['2 Apr 1921', 'Queens Park Rangers', 'H', '1β3', 'Devlin', '7,500'], ['22 Jan 1921', 'Norwich City', 'A', '0β3', '', '5,000'], ['19 Feb 1921', 'Crystal Palace', 'A', '0β2', '', '7,000'], ['13 Jan 1921', 'Norwich City', 'H', '2β0', 'Wright, Cox', '4,000']]
|
1
|
Answer:
| 128
| 17
| 520
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:besides angola racing team, what other team is listed in the 23rd position?
|
[['Season', 'Series', 'Team', 'Races', 'Wins', 'Poles', 'F/Laps', 'Podiums', 'Points', 'Position'], ['2008', 'Asian Formula Renault Challenge', 'Champ Motorsports', '13', '0', '0', '0', '3', '193', '4th'], ['2009', 'Asian Formula Renault Challenge', 'Asia Racing Team', '12', '6', '2', '4', '7', '287', '2nd'], ['2012', 'Formula 3 Euro Series', 'Angola Racing Team', '21', '0', '0', '0', '0', '14', '14th'], ['2009', 'Formula Renault 2.0 Northern European Cup', 'Krenek Motorsport', '14', '0', '0', '0', '0', '44', '21st'], ['2007', 'Asian Formula Renault Challenge', 'Champ Motorsports', '12', '0', '0', '0', '1', '64', '14th'], ['2010', 'Austria Formula 3 Cup', 'Sonangol Motopark', '4', '1', '2', '3', '2', '35', '9th'], ['2013', 'GP3 Series', 'Carlin', '16', '0', '0', '0', '0', '0', '23rd'], ['2010', 'ATS Formel 3 Cup', 'China Sonangol', '5', '0', '0', '0', '0', '0', '19th'], ['2012', 'British Formula 3 Championship', 'Angola Racing Team', '5', '0', '0', '0', '0', 'β', 'β'], ['2012', 'Masters of Formula 3', 'Angola Racing Team', '1', '0', '0', '0', '0', 'β', '18th'], ['2012', '59th Macau Grand Prix Formula 3', 'Angola Racing Team', '2', '0', '0', '0', '0', 'β', '23rd'], ['2011', 'Formula Pilota China', 'Asia Racing Team', '12', '2', '0', '0', '3', '124', '2nd']]
|
Carlin
|
Answer:
| 128
| 12
| 507
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many countries had at least $1 billion in box office?
|
[['Rank', 'Country', 'Box Office', 'Year', 'Box office\\nfrom national films'], ['-', 'World', '$34.7 billion', '2012', 'β'], ['3', 'Japan', '$1.88 billion', '2013', '61% (2013)'], ['5', 'France', '$1.7 billion', '2012', '33.3% (2013)'], ['1', 'Canada/United States', '$10.8 billion', '2012', 'β'], ['4', 'United Kingdom', '$1.7 billion', '2012', '36.1% (2011)'], ['7', 'India', '$1.4 billion', '2012', 'β'], ['9', 'Russia', '$1.2 billion', '2012', 'β'], ['11', 'Italy', '$0.84 billion', '2013', '30% (2013)'], ['12', 'Brazil', '$0.72 billion', '2013', '17% (2013)'], ['2', 'China', '$3.6 billion', '2013', '59% (2013)'], ['6', 'South Korea', '$1.47 billion', '2013', '59.7% (2013)'], ['10', 'Australia', '$1.2 billion', '2012', '4.1% (2011)'], ['8', 'Germany', '$1.3 billion', '2012', 'β']]
|
10
|
Answer:
| 128
| 13
| 321
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what city has a radio station called the wolf?
|
[['Frequency', 'Call sign', 'Name', 'Format', 'Owner', 'Target city/market', 'City of license'], ['94.3 FM', 'KDAM', 'The Dam', 'Mainstream Rock', 'Riverfront Broadcasting LLC', 'Yankton/Vermillion', 'Hartington'], ['104.1 FM', 'WNAX-FM', 'The Wolf 104.1', 'Country', 'Saga Communications', 'Yankton/Vermillion', 'Yankton'], ['89.7 FM', 'KUSD', 'South Dakota Public Broadcasting', 'NPR', 'SD Board of Directors for Educational Telecommunications', 'Yankton/Vermillion', 'Vermillion'], ['93.1 FM', 'KKYA', 'KK93', 'Country', 'Riverfront Broadcasting LLC', 'Yankton/Vermillion', 'Yankton'], ['106.3 FM', 'KVHT', 'Classic Hits 106.3', 'Classic Hits', 'Cullhane Communications, Inc.', 'Yankton/Vermillion', 'Vermillion']]
|
Yankton
|
Answer:
| 128
| 5
| 228
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what is the earliest date kodak made 16mm film?
|
[['Film', 'Film', 'Date'], ['Kodachrome 64', '110 format, daylight', '1974β1987'], ['Kodachrome-X film', '35\xa0mm (ASA 64)', '1962β1974'], ['Kodachrome II film', '35\xa0mm and 828, daylight (ASA 25/early) (ASA 64/late)', '1961β1974'], ['Kodachrome 64', '35\xa0mm, daylight', '1974β2009'], ['Kodachrome-X film', '126 format', '1963β1974'], ['Kodachrome II film', '16\xa0mm, daylight (ASA 25) and Type A (ASA 40)', '1961β1974'], ['Kodachrome 200', 'Professional film, 35\xa0mm, daylight', '1986β2004'], ['Kodachrome 40 film', 'Movie film, S-8, Type A', '1974β2005'], ['Kodachrome II film', 'S-8, Type A (ASA 40)', '1965β1974'], ['Kodachrome 40 film', 'Movie film, 8\xa0mm, Type A', '1974β1992'], ['Kodachrome-X film', '110 format', '1972β1974'], ['Kodachrome 25 film', 'Movie film, 8\xa0mm, daylight', '1974β1992'], ['Kodachrome II film', 'Professional, 35\xa0mm, Type A (ASA 40)', '1962β1978'], ['Kodachrome 64', 'Professional film, 35\xa0mm, daylight', '1983β2009'], ['Kodachrome Professional film', '35\xa0mm, Type A (ASA 16)', '1956β1962'], ['Kodachrome Professional film (sheets)', 'daylight (ASA 8) and Type B (ASA 10)', '1938β1951'], ['Kodachrome 40 film', 'Sound Movie film, S-8, Type A', '1974β1998'], ['Kodachrome 25 film', 'Movie film, 16\xa0mm, daylight', '1974β2002']]
|
1935
|
Answer:
| 128
| 18
| 503
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:who was the first to win during the 2009 fujitsu v8 supercar season?
|
[['Rd.', 'Event', 'Circuit', 'Location', 'Date', 'Winner'], ['6', 'Supercheap Auto Bathurst 1000', 'Mount Panorama Circuit', 'Bathurst, New South Wales', '8-11 Oct', 'Jonathon Webb'], ['5', 'Queensland House & Land 300', 'Queensland Raceway', 'Ipswich, Queensland', '21-23 Aug', 'Jonathon Webb'], ['1', 'Clipsal 500', 'Adelaide Street Circuit', 'Adelaide, South Australia', '19-22 Mar', 'David Russell'], ['2', 'Winton', 'Winton Motor Raceway', 'Benalla, Victoria', '1-3 May', 'Jonathon Webb'], ['4', 'Norton 360 Sandown Challenge', 'Sandown Raceway', 'Melbourne, Victoria', '31 Jul-Aug 2', 'David Russell'], ['7', 'Sydney Telstra 500', 'Homebush Street Circuit', 'Sydney, New South Wales', '4-6 Dec', 'Jonathon Webb'], ['3', 'Dunlop Townsville 400', 'Townsville Street Circuit', 'Townsville, Queensland', '10-12 Jul', 'James Moffat']]
|
David Russell
|
Answer:
| 128
| 7
| 268
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:which competition was held in berlin and daegu?
|
[['Year', 'Competition', 'Venue', 'Position', 'Notes'], ['2008', 'Olympic Games', 'Beijing, China', '10th', '5.45 m'], ['2006', 'World Junior Championships', 'Beijing, China', '5th', '5.30 m'], ['2014', 'World Indoor Championships', 'Sopot, Poland', '3rd', '5.80 m'], ['2012', 'Olympic Games', 'London, United Kingdom', '8th', '5.65 m'], ['2013', 'European Indoor Championships', 'Gothenburg, Sweden', '5th', '5.71 m'], ['2012', 'European Championships', 'Helsinki, Finland', '6th', '5.60 m'], ['2009', 'World Championships', 'Berlin, Germany', '22nd (q)', '5.40 m'], ['2005', 'World Youth Championships', 'Marrakech, Morocco', '6th', '5.05 m'], ['2010', 'European Championships', 'Barcelona, Spain', '10th', '5.60 m'], ['2011', 'World Championships', 'Daegu, South Korea', '9th', '5.65 m'], ['2009', 'European U23 Championships', 'Kaunas, Lithuania', '8th', '5.15 m']]
|
World Championships
|
Answer:
| 128
| 11
| 296
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:total number of cars sold in 2001?
|
[['Model', '1991', '1995', '1996', '1997', '1998', '1999', '2000', '2001', '2002', '2003', '2004', '2005', '2006', '2007', '2008', '2009', '2010', '2011', '2012', '2013'], ['Ε koda Rapid', 'β', 'β', 'β', 'β', 'β', 'β', 'β', 'β', 'β', 'β', 'β', 'β', 'β', 'β', 'β', 'β', 'β', '1,700', '9,292', '103,800'], ['Ε koda Roomster', 'β', 'β', 'β', 'β', 'β', 'β', 'β', 'β', 'β', 'β', 'β', 'β', '14,422', '66,661', '57,467', '47,152', '32,332', '36,000', '39,249', '33,300'], ['Ε koda Octavia', 'β', 'β', '', '47,876', '102,373', '143,251', '158,503', '164,134', '164,017', '165,635', '181,683', '233,322', '270,274', '309,951', '344,857', '317,335', '349,746', '387,200', '409,360', '359,600'], ['Total', '172,000', '210,000', '261,000', '336,334', '363,500', '385,330', '435,403', '460,252', '445,525', '449,758', '451,675', '492,111', '549,667', '630,032', '674,530', '684,226', '762,600', '879,200', '949,412', '920,800'], ['Ε koda Citigo', 'β', 'β', 'β', 'β', 'β', 'β', 'β', 'β', 'β', 'β', 'β', 'β', 'β', 'β', 'β', 'β', 'β', '509', '36,687', '45,200']]
|
460,252
|
Answer:
| 128
| 5
| 511
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what type of plane was encountered the least?
|
[['Date', 'Location', 'Air/Ground', 'Number', 'Type', 'Status'], ['24 April 1944', 'South of Munich, Germany', 'Air', '3', 'Me-110', 'Destroyed'], ['27 May 1944', 'North of Strasbourg, France', 'Air', '1', 'Me-109', 'Damaged'], ['13 September 1944', 'South of Nordhausen, Germany', 'Air', '2.5', 'Me-109', 'Destroyed'], ['6 October 1944', '20 miles northwest of Berlin, Germany', 'Air', '1', 'Me-109', 'Damaged'], ['8 March 1944', 'Near Steinhuder Meer (Lake), Germany', 'Air', '1', 'Me-109', 'Destroyed'], ['14 January 1945', '20 miles northwest of Berlin, Germany', 'Air', '1', 'Me-109', 'Destroyed'], ['16 March 1944', '20 miles south of Stuttgart, Germany', 'Air', '1', 'Me-110', 'Destroyed'], ['27 November 1944', 'South of Magdeburg, Germany', 'Air', '4', 'FW-190', 'Destroyed'], ['11 April 1944', '20 miles northeast of Magdeburg, Germany', 'Air', '0.5', 'Me-109', 'Destroyed'], ['6 October 1944', '20 miles northwest of Berlin, Germany', 'Air', '2', 'Me-109', 'Destroyed'], ['13 April 1944', 'West of Mannheim, Germany', 'Air', '1', 'FW-190', 'Destroyed'], ['25 January 1952', 'Korea', 'Air', '1', 'Mig-15', 'Damaged'], ['18 August 1944', '20 miles northeast of Paris, France', 'Air', '0.5', 'Me-109', 'Destroyed']]
|
Mig-15
|
Answer:
| 128
| 13
| 414
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:who was the top placing competitor?
|
[['Name', 'Sport', 'Event', 'Placing', 'Performance'], ["Ze'ev Friedman", 'Weightlifting', 'Bantamweight <56 kg', '12', 'J:102.5 C:102.5 S:125 T:330'], ['Zelig Stroch', 'Shooting', '50 metre rifle prone', '57', '589/600'], ['Henry Hershkowitz', 'Shooting', '50 metre rifle prone', '23', '593/600'], ['Dan Alon', 'Fencing', "Men's foil", 'Second round', 'W5βL5 (1R 3-2, 2R 2-3)'], ['Shlomit Nir', 'Swimming', "Women's 100 m breaststroke", 'Heats (8th)', '1:20.90'], ['Shaul Ladani', 'Athletics', "Men's 50 km walk", '19', '4:24:38.6\\n(also entered for 20 km walk, but did not start)'], ['Mark Slavin', 'Wrestling', 'Greco-Roman β Middleweight <82 kg', 'β', '(taken hostage before his scheduled event)'], ['Esther Shahamorov', 'Athletics', "Women's 100 m", 'Semifinal (5th)', '11.49'], ['Henry Hershkowitz', 'Shooting', '50 metre rifle three positions', '46', '1114/1200'], ['Gad Tsobari', 'Wrestling', 'Freestyle β Light Flyweight <48 kg', 'Group stage', '0Wβ2L'], ['Yair Michaeli', 'Sailing', 'Flying Dutchman', '23', '28-22-22-19-25-19-DNS = 171 pts\\n(left Kiel before 7th race)'], ['Itzhak Nir', 'Sailing', 'Flying Dutchman', '23', '28-22-22-19-25-19-DNS = 171 pts\\n(left Kiel before 7th race)'], ['Shlomit Nir', 'Swimming', "Women's 200 m breaststroke", 'Heats (6th)', '2:53.60'], ['Esther Shahamorov', 'Athletics', "Women's 100 m hurdles", 'Semifinal', 'Did not start (left Munich before the semifinal)']]
|
Esther Shahamorov
|
Answer:
| 128
| 14
| 521
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:is the price money for 23 january 1984 more than that of 23 april 1984?
|
[['Result', 'Date', 'Category', 'Tournament', 'Surface', 'Partnering', 'Opponents', 'Score'], ['Runner-up', '22 April 1984', '$250,000', 'Amelia Island, United States', 'Clay', 'Mima JauΕ‘ovec', 'Kathy Jordan\\n Anne Smith', '4β6, 6β3, 4β6'], ['Runner-up', '30 August 1987', '$150,000', 'Mahwah, United States', 'Hard', 'Liz Smylie', 'Gigi FernΓ‘ndez\\n Lori McNeil', '3β6, 2β6'], ['Runner-up', '9 September 1984', 'Grand Slam', 'US Open, United States', 'Hard', 'Wendy Turnbull', 'Martina NavrΓ‘tilovΓ‘\\n Pam Shriver', '2β6, 4β6'], ['Runner-up', '23 April 1984', '$200,000', 'Orlando, United States', 'Clay', 'Wendy Turnbull', 'Claudia Kohde-Kilsch\\n Hana MandlΓkovΓ‘', '0β6, 6β1, 3β6'], ['Winner', '13 June 1982', '$100,000', 'Birmingham, Great Britain', 'Grass', 'Jo Durie', 'Rosie Casals\\n Wendy Turnbull', '6β3, 6β2'], ['Runner-up', '8 November 1981', '$50,000', 'Hong Kong', 'Clay', 'Susan Leo', 'Ann Kiyomura\\n Sharon Walsh', '3β6, 4β6'], ['Winner', '21 August 1983', '$200,000', 'Toronto, Canada', 'Hard', 'Andrea Jaeger', 'Rosalyn Fairbank\\n Candy Reynolds', '6β4, 5β7, 7β5'], ['Winner', '27 November 1983', '$150,000', 'Sydney, Australia', 'Grass', 'Wendy Turnbull', 'Hana MandlΓkovΓ‘\\n Helena SukovΓ‘', '6β4, 6β3'], ['Runner-up', '19 June 1983', '$150,000', 'Eastbourne, Great Britain', 'Grass', 'Jo Durie', 'Martina NavrΓ‘tilovΓ‘\\n Pam Shriver', '1β6, 0β6']]
|
no
|
Answer:
| 128
| 9
| 524
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what was the only race in 2011?
|
[['Season', 'Age', 'Overall', 'Slalom', 'Giant\\nSlalom', 'Super G', 'Downhill', 'Combined'], ['2010', '10 Mar 2010', 'Garmisch, Germany', 'Downhill', '', '', '', ''], ['2010', '23', '1', 'β', '2', '6', '2', '2'], ['2010', '5 Dec 2009', 'Beaver Creek, USA', 'Downhill', '', '', '', ''], ['2008', '21', '64', 'β', '28', '46', '46', '31'], ['2007', '20', '130', 'β', '40', 'β', 'β', 'β'], ['2014', '27', '18', 'β', '25', '14', '20', '11'], ['2010', '16 Jan 2010', 'Wengen, Switzerland', 'Downhill', '', '', '', ''], ['2010', '6 Dec 2009', 'Beaver Creek, USA', 'Giant Slalom', '', '', '', ''], ['2011', '5 Mar 2011', 'Kranjska Gora, Slovenia', 'Giant Slalom', '', '', '', ''], ['2013', '26', '48', 'β', '48', '27', '38', '4'], ['2009', '22', '7', 'β', '6', '16', '16', '1'], ['2009', '13 Dec 2008', "Val d'IsΓ¨re, France", 'Giant slalom', '', '', '', ''], ['2009', '16 Jan 2009', 'Wengen, Switzerland', 'Super Combined', '', '', '', ''], ['2010', '12 Mar 2010', 'Garmisch, Germany', 'Giant Slalom', '', '', '', ''], ['Season', 'Date', 'Location', 'Race', '', '', '', ''], ['2012', '25', '24', 'β', '16', '28', '17', '19'], ['2010', '4 Dec 2009', 'Beaver Creek, USA', 'Super Combined', '', '', '', ''], ['2011', '24', '3', 'β', '5', '6', '9', '6']]
|
Giant Slalom
|
Answer:
| 128
| 18
| 505
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:which position was listed the most on this chart?
|
[['Round', 'Pick', 'Name', 'Position', 'College'], ['7', '254', 'Michael Green', 'S', 'Northwestern State'], ['2', '39', 'Mike Brown', 'S', 'Nebraska'], ['3', '69', 'Dez White', 'WR', 'Georgia Tech'], ['6', '174', 'Paul Edinger', 'K', 'Michigan State'], ['4', '125', 'Reggie Austin', 'DB', 'Wake Forest'], ['1', '9', 'Brian Urlacher', 'S', 'New Mexico'], ['6', '170', 'Frank Murphy', 'WR', 'Kansas State'], ['3', '87', 'Dustin Lyman', 'TE', 'Wake Forest'], ['7', '223', 'James Cotton', 'DE', 'Ohio State']]
|
S
|
Answer:
| 128
| 9
| 175
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:m. shafi ahmad and absdul majid both had what type of degree?
|
[['Number', 'Name', 'Term Started', 'Term Ended', 'Alma Mater', 'Field(s)', 'Educational Background'], ['7', 'Dr Abdul Majid', '1997', '2001', 'University of Wales', 'Astrophysics', 'Ph.D'], ['5', 'Dr M. Shafi Ahmad', '1989', '1990', 'University of London', 'Astronomy', 'Ph.D'], ['9', 'Major General Ahmed Bilal', '2010', 'Present', 'Pakistan Army Corps of Signals Engineering', 'Computer Engineering', 'Master of Science (M.S)'], ['3', 'Air Commodore K. M. Ahmad', '1979', '1980', 'Pakistan Air Force Academy', 'Flight Instructor', 'Certificated Flight Instructor (CFI)'], ['8', 'Major General Raza Hussain', '2001', '2010', 'Pakistan Army Corps of Electrical and Mechanical Engineers', 'Electrical Engineering', 'B.S.'], ['2', 'Air Commodore Dr WΕadysΕaw Turowicz', '1967', '1979', 'Warsaw University of Technology', 'Aeronautical Engineering', 'Ph.D'], ['6', 'Engr.Sikandar Zaman', '1990', '1997', 'University of Leeds', 'Mechanical Engineering', 'Bachelor of Science (B.S.)'], ['4', 'Dr Salim Mehmud', '1980', '1989', 'Oak Ridge Institute for Science and Education and Oak Ridge National Laboratory', 'Nuclear Engineering, Electrical engineering, Physics, Mathematics, Electronics engineering', 'Ph.D'], ['1', 'Dr Abdus Salam', '1961', '1967', 'Imperial College', 'Theoretical Physics', 'Doctor of Philosophy (Ph.D)']]
|
Ph.D
|
Answer:
| 128
| 9
| 380
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many photos total are listed?
|
[['Ship', 'Hull No.', 'Status', 'Years Active', 'NVR\\nPage'], ['Guadalupe', 'T-AO-200', 'Active', '1992βpresent', 'AO200'], ['Rappahannock', 'T-AO-204', 'Active', '1995βpresent', 'AO204'], ['John Ericsson', 'T-AO-194', 'Active', '1991βpresent', 'AO194'], ['Laramie', 'T-AO-203', 'Active', '1996βpresent', 'AO203'], ['Yukon', 'T-AO-202', 'Active', '1994βpresent', 'AO202'], ['Walter S. Diehl', 'T-AO-193', 'Active', '1988βpresent', 'AO193'], ['Joshua Humphreys', 'T-AO-188', 'Inactivated 1996, returned to service 2005', '1987-1996; 2005-2006; 2010-present', 'AO188'], ['Pecos', 'T-AO-197', 'Active', '1990βpresent', 'AO197'], ['John Lenthall', 'T-AO-189', 'Active', '1987-1996; 1998βpresent', 'AO189'], ['Patuxent', 'T-AO-201', 'Active', '1995βpresent', 'AO201'], ['Henry Eckford', 'T-AO-192', 'Cancelled when 84% complete,\\ntransferred to the Maritime Administration,\\nlaid up in the James River Reserve Fleet,\\nscrapped in 2011', 'Launched 1989, never in service', 'AO192'], ['Kanawha', 'T-AO-196', 'Active', '1991βpresent', 'AO196'], ['Tippecanoe', 'T-AO-199', 'Active', '1993βpresent', 'AO199'], ['Leroy Grumman', 'T-AO-195', 'Active', '1989βpresent', 'AO195'], ['Benjamin Isherwood', 'T-AO-191', 'Cancelled when 95.3% complete,\\ntransferred to the Maritime Administration,\\nlaid up in the James River Reserve Fleet,\\nscrapped in 2011', 'Launched 1988, christened 1991, never in service', 'AO191']]
|
18
|
Answer:
| 128
| 15
| 530
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many times was first listed as the position according to this chart?
|
[['Year', 'Competition', 'Venue', 'Position', 'Event', 'Notes'], ['2006', 'European Championships', 'Gothenburg, Sweden', '2nd', '400 m hurdles', '48.71'], ['2003', 'World Indoor Championships', 'Birmingham, United Kingdom', '3rd', '4x400 m relay', '3:06.61'], ['2004', 'Olympic Games', 'Athens, Greece', '10th (h)', '4x400 m relay', '3:03.69'], ['2003', 'European U23 Championships', 'Bydgoszcz, Poland', '1st', '4x400 m relay', '3:03.32'], ['2001', 'World Championships', 'Edmonton, Canada', '18th (sf)', '400 m hurdles', '49.80'], ['2003', 'World Indoor Championships', 'Birmingham, United Kingdom', '7th (sf)', '400 m', '46.82'], ['2003', 'European U23 Championships', 'Bydgoszcz, Poland', '1st', '400 m hurdles', '48.45'], ['2002', 'European Championships', 'Munich, Germany', '4th', '400 m', '45.40'], ['2002', 'European Indoor Championships', 'Vienna, Austria', '1st', '4x400 m relay', '3:05.50 (CR)'], ['2002', 'European Championships', 'Munich, Germany', '8th', '4x400 m relay', 'DQ'], ['2001', 'Universiade', 'Beijing, China', '8th', '400 m hurdles', '49.68'], ['2000', 'World Junior Championships', 'Santiago, Chile', '1st', '400 m hurdles', '49.23'], ['2002', 'European Indoor Championships', 'Vienna, Austria', '1st', '400 m', '45.39 (CR, NR)'], ['2004', 'Olympic Games', 'Athens, Greece', '6th', '400 m hurdles', '49.00'], ['2008', 'Olympic Games', 'Beijing, China', '7th', '4x400 m relay', '3:00.32'], ['2012', 'European Championships', 'Helsinki, Finland', '18th (sf)', '400 m hurdles', '50.77']]
|
5
|
Answer:
| 128
| 16
| 528
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:who was the the candidate before anastasija nindova?
|
[['Represent', 'Candidate', 'in Russian', 'Age', 'Height', 'Hometown'], ['Tver Oblast', 'Anastasija PraΔeβvysky', 'ΠΠ½Π°ΡΡΠ°ΡΠΈΡ ΠΡΠ°ΡΠ΅ΡΠ²ΡΡΠΊΡ', '19', '1.75\xa0m (5\xa0ft 9\xa0in)', 'Tver'], ['Saratov Oblast', 'Anastasija Marnolova', 'ΠΠ½Π°ΡΡΠ°ΡΠΈΡ ΠΠ°ΡΠ½ΠΎΠ»ΠΎΠ²Π°', '21', '1.74\xa0m (5\xa0ft 8\xa01β2\xa0in)', 'Saratov'], ['Magadan Oblast', 'Ekaterina Filimonova', 'ΠΠΊΠ°ΡΠ΅ΡΠΈΠ½Π° Π€ΠΈΠ»ΠΈΠΌΠΎΠ½ΠΎΠ²Π°', '20', '1.83\xa0m (6\xa0ft 0\xa0in)', 'Magadan'], ['North Ossetian Republic', 'Emilianna Ninn', 'ΠΠΌΠΈΠ»ΠΈΠ°Π½Π½Π° ΠΠΈΠ½Π½', '22', '1.76\xa0m (5\xa0ft 9\xa01β2\xa0in)', 'Vladikavkaz'], ['Mordovian Republic', 'Olga StepanΔenko', 'ΠΠ»Π³Π° Π‘ΡΠ΅ΠΏΠ°Π½ΡΠ΅Π½ΠΊΠΎ', '20', '1.75\xa0m (5\xa0ft 9\xa0in)', 'Saransk'], ['Tomsk Oblast', 'Anastasija Tristova', 'ΠΠ½Π°ΡΡΠ°ΡΠΈΡ Π’ΡΠΈΡΡΠΎΠ²Π°', '23', '1.78\xa0m (5\xa0ft 10\xa0in)', 'Tomsk'], ['Altai Krai', 'Anastasija Nindova', 'ΠΠ½Π°ΡΡΠ°ΡΠΈΡ ΠΠΈΠ½Π΄ΠΎΠ²Π°', '22', '1.74\xa0m (5\xa0ft 8\xa01β2\xa0in)', 'Barnaul'], ['Chelyabinsk Oblast', 'Tatiana Abramenko', 'Π’Π°ΡΠΈΠ°Π½Π° ΠΠ±ΡΠ°ΠΌΠ΅Π½ΠΊΠΎ', '21', '1.74\xa0m (5\xa0ft 8\xa01β2\xa0in)', 'Chelyabinsk'], ['Penza Oblast', 'Anna Milinzova', 'ΠΠ½Π½Π° ΠΠΈΠ»ΠΈΠ½Π·ΠΎΠ²Π°', '20', '1.86\xa0m (6\xa0ft 1\xa0in)', 'Penza']]
|
Alissa Joanndova
|
Answer:
| 128
| 9
| 498
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what date is next listed after june 14, 2010.
|
[['Season', 'Episodes', 'Season Premiere', 'Season Finale'], ['5', '40', 'October 12, 2009', 'June 14, 2010'], ['7', '8', 'October 29, 2013', 'December 17, 2013'], ['3', '44', 'October 15, 2007', 'June 2, 2008'], ['4', '48', 'October 13, 2008', 'May 11, 2009'], ['1', '20', 'March 4, 2006', 'May 13, 2006'], ['6', '20', 'September 6, 2010', 'December 6, 2010'], ['2', '52', 'October 7, 2006', 'July 16, 2007']]
|
December 6, 2010
|
Answer:
| 128
| 7
| 184
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many times was a tournament held in the united states?
|
[['Outcome', 'No.', 'Date', 'Tournament', 'Surface', 'Partner', 'Opponents', 'Score'], ['Winner', '2.', '7 August 2011', 'Vancouver, Canada', 'Hard', 'KarolΓna PlΓΕ‘kovΓ‘', 'Jamie Hampton\\n N. Lertcheewakarn', '5β7, 6β2, 6β4'], ['Winner', '1.', '13 February 2011', 'Rancho Mirage, United States', 'Hard', 'KarolΓna PlΓΕ‘kovΓ‘', 'Nadejda Guskova\\n Sandra Zaniewska', '6β7(6β8), 6β1, 6β4'], ['Winner', '4.', '30 January 2012', 'Grenoble, France', 'Hard (i)', 'KarolΓna PlΓΕ‘kovΓ‘', 'Valentyna Ivakhnenko\\n Maryna Zanevska', '6β1, 6β3'], ['Winner', '3.', '23 January 2012', 'AndrΓ©zieux-BouthΓ©on, France', 'Hard (i)', 'KarolΓna PlΓΕ‘kovΓ‘', 'Julie Coin\\n Eva HrdinovΓ‘', '6β4, 4β6, [10β5]'], ['Runner-up', '1.', '16 May 2010', 'Kurume, Japan', 'Clay', 'KarolΓna PlΓΕ‘kovΓ‘', 'Sun Shengnan\\n Xu Yifan', '0β6, 3β6'], ['Winner', '6.', '28 October 2013', 'Barnstaple, United Kingdom', 'Hard (i)', 'Naomi Broady', 'Raluca Olaru\\n Tamira Paszek', '6β3, 3β6, [10β5]'], ['Winner', '5.', '12 November 2012', 'Zawada, Poland', 'Carpet (i)', 'KarolΓna PlΓΕ‘kovΓ‘', 'Kristina Barrois\\n Sandra Klemenschits', '6β3, 6β1'], ['Runner-up', '4.', '17 September 2012', 'Shrewsbury, United Kingdom', 'Hard (i)', 'KarolΓna PlΓΕ‘kovΓ‘', 'Vesna Dolonc\\n Stefanie VΓΆgele', '1β6, 7β6(7β3), [13β15]']]
|
1
|
Answer:
| 128
| 8
| 527
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many drivers have no laps led?
|
[['Pos', 'No.', 'Driver', 'Team', 'Laps', 'Time/Retired', 'Grid', 'Laps Led', 'Points'], ['3', '10', 'Dario Franchitti', 'Chip Ganassi Racing', '85', '+ 30.0551', '6', '0', '35'], ['21', '23', 'Milka Duno', 'Dreyer & Reinbold Racing', '56', 'Handling', '20', '0', '12'], ['4', '14', 'Ryan Hunter-Reay', 'A. J. Foyt Enterprises', '85', '+ 33.7307', '7', '0', '32'], ['5', '27', 'Hideki Mutoh', 'Andretti Green Racing', '85', '+ 34.1839', '11', '0', '30'], ['10', '11', 'Tony Kanaan', 'Andretti Green Racing', '85', '+ 52.0810', '8', '0', '20'], ['1', '9', 'Scott Dixon', 'Chip Ganassi Racing', '85', '1:46:05.7985', '3', '51', '52'], ['19', '7', 'Danica Patrick', 'Andretti Green Racing', '83', '+ 2 Laps', '12', '0', '12'], ['6', '26', 'Marco Andretti', 'Andretti Green Racing', '85', '+ 46.7669', '13', '0', '28'], ['15', '13', 'E. J. Viso', 'HVM Racing', '84', '+ 1 Lap', '9', '0', '15'], ['7', '5', 'Paul Tracy', 'KV Racing Technology', '85', '+ 49.7020', '10', '0', '26'], ['18', '98', 'Richard Antinucci', 'Team 3G', '83', '+ 2 Laps', '19', '0', '12'], ['2', '6', 'Ryan Briscoe', 'Penske Racing', '85', '+ 29.7803', '1', '6', '41'], ['12', '3', 'HΓ©lio Castroneves', 'Penske Racing', '85', '+ 53.2362', '5', '0', '18']]
|
18
|
Answer:
| 128
| 13
| 520
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:who superceded lord high steward?
|
[['Position', 'Officer', 'current officers', 'superseded by', 'Royal Household'], ['8', 'Earl Marshal', 'The Duke of Norfolk', '', 'Master of the Horse'], ['1', 'Lord High Steward', 'vacant', 'Justiciar', 'Lord Steward'], ['3', 'Lord High Treasurer', 'in commission', '', ''], ['5', 'Lord Privy Seal', 'The Rt Hon Andrew Lansley, CBE, MP', '', ''], ['7', 'Lord High Constable', 'vacant', 'Earl Marshal', 'Master of the Horse'], ['2', 'Lord High Chancellor', 'The Rt Hon Chris Grayling, MP', '', ''], ['9', 'Lord High Admiral', 'HRH The Duke of Edinburgh', '', ''], ['6', 'Lord Great Chamberlain', 'The Marquess of Cholmondeley', 'Lord High Treasurer', 'Lord Chamberlain'], ['4', 'Lord President of the Council', 'The Rt Hon Nick Clegg, MP', '', '']]
|
Justiciar
|
Answer:
| 128
| 9
| 222
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:who was kristyna pliskova's partner in her first professional doubles tournament?
|
[['Outcome', 'No.', 'Date', 'Tournament', 'Surface', 'Partner', 'Opponents', 'Score'], ['Winner', '4.', '30 January 2012', 'Grenoble, France', 'Hard (i)', 'KarolΓna PlΓΕ‘kovΓ‘', 'Valentyna Ivakhnenko\\n Maryna Zanevska', '6β1, 6β3'], ['Winner', '5.', '12 November 2012', 'Zawada, Poland', 'Carpet (i)', 'KarolΓna PlΓΕ‘kovΓ‘', 'Kristina Barrois\\n Sandra Klemenschits', '6β3, 6β1'], ['Runner-up', '1.', '16 May 2010', 'Kurume, Japan', 'Clay', 'KarolΓna PlΓΕ‘kovΓ‘', 'Sun Shengnan\\n Xu Yifan', '0β6, 3β6'], ['Winner', '2.', '7 August 2011', 'Vancouver, Canada', 'Hard', 'KarolΓna PlΓΕ‘kovΓ‘', 'Jamie Hampton\\n N. Lertcheewakarn', '5β7, 6β2, 6β4'], ['Winner', '1.', '13 February 2011', 'Rancho Mirage, United States', 'Hard', 'KarolΓna PlΓΕ‘kovΓ‘', 'Nadejda Guskova\\n Sandra Zaniewska', '6β7(6β8), 6β1, 6β4'], ['Winner', '3.', '23 January 2012', 'AndrΓ©zieux-BouthΓ©on, France', 'Hard (i)', 'KarolΓna PlΓΕ‘kovΓ‘', 'Julie Coin\\n Eva HrdinovΓ‘', '6β4, 4β6, [10β5]'], ['Runner-up', '2.', '6 November 2011', 'Taipei 5, Taiwan', 'Hard', 'KarolΓna PlΓΕ‘kovΓ‘', 'Chan Yung-jan\\n Zheng Jie', '6β7(5β7), 7β5, 3β6'], ['Winner', '6.', '28 October 2013', 'Barnstaple, United Kingdom', 'Hard (i)', 'Naomi Broady', 'Raluca Olaru\\n Tamira Paszek', '6β3, 3β6, [10β5]']]
|
KarolΓna PlΓΕ‘kovΓ‘
|
Answer:
| 128
| 8
| 519
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many fullback positions were picked?
|
[['Pick #', 'NFL Team', 'Player', 'Position', 'College'], ['3', 'Baltimore Colts', 'Alan Ameche', 'Fullback', 'Wisconsin'], ['9', 'Philadelphia Eagles', 'Dick Bielski', 'Fullback', 'Maryland'], ['7', 'Los Angeles Rams', 'Larry Morris', 'Center', 'Georgia Tech'], ['12', 'Detroit Lions', 'Dave Middleton', 'Halfback', 'Auburn'], ['10', 'San Francisco 49ers', 'Dickey Moegle', 'Halfback', 'Rice'], ['4', 'Washington Redskins', 'Ralph Guglielmi', 'Quarterback', 'Notre Dame'], ['2', 'Chicago Cardinals', 'Max Boydston', 'End', 'Oklahoma'], ['6', 'Pittsburgh Steelers', 'Frank Varrichione', 'Tackle', 'Notre Dame'], ['8', 'New York Giants', 'Joe Heap', 'Halfback', 'Notre Dame'], ['13', 'Cleveland Browns', 'Kurt Burris', 'Center', 'Oklahoma'], ['5', 'Green Bay Packers', 'Tom Bettis', 'Guard', 'Purdue'], ['11', 'Chicago Bears', 'Ron Drzewiecki', 'Halfback', 'Marquette'], ['1', 'Baltimore Colts (Lottery bonus pick)', 'George Shaw', 'Quarterback', 'Oregon']]
|
2
|
Answer:
| 128
| 13
| 304
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:which year had the least amount of toy sales?
|
[['Year', 'Injuries (US $000)', 'Deaths (age <15)', 'CPSC toy safety funding\\n(US$ Millions)', 'Toy sales\\n(US $ Billions)'], ['2007', 'no data', '22', 'no data', ''], ['2002', '212', '13', '12.2', '21.3'], ['2005', '202 (estimate)', '20', '11.0', '22.2'], ['2009', 'no data', '12', 'no data', ''], ['2006', 'no data', '22', 'no dataβ ', '22.3'], ['2000', '191', '17', '12.0', ''], ['1998', '153', '14', '', ''], ['1996', '130', '', '', ''], ['1994', '154', '', '', ''], ['2008', 'no data', '19', 'no data', ''], ['1997', '141', '', '', ''], ['2004', '210', '16', '11.5', '22.4'], ['1999', '152', '16', '13.6', ''], ['1995', '139', '', '', ''], ['2003', '206', '11', '12.8', '20.7'], ['2001', '255', '25', '12.4', '']]
|
2003
|
Answer:
| 128
| 16
| 305
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many affiliates does tv azteca have all together?
|
[['Network name', 'Flagship', 'Programming type', 'Owner', 'Affiliates'], ['GalavisiΓ³n', 'XEQ 9', 'retro programming and sports', 'Televisa', '1'], ['Independent', '', 'varies', 'Independent', '3'], ['Azteca 13', 'XHDF 13', 'news, soap operas, and sports', 'TV Azteca', '4'], ['TV 10 Chiapas', 'XHTTG', 'educational', 'Gobierno del Estado de Chiapas', '7'], ['Canal de las Estrellas', 'XEW 2', 'soap operas, retro movies and sports', 'Televisa', '10'], ['Canal 5', 'XHGC 5', 'cartoons, movies, and series', 'Televisa', '4'], ['Azteca 7', 'XHIMT 7', 'sports, series, and movies', 'TV Azteca', '5']]
|
9
|
Answer:
| 128
| 7
| 209
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what was the number of times that the team placed 5th?
|
[['Year', 'Division', 'League', 'Reg. Season', 'Playoffs'], ['2013', '1', 'USL W-League', '4th, Western', 'Did not qualify'], ['2005', '1', 'USL W-League', '6th, Western', ''], ['2006', '1', 'USL W-League', '5th, Western', ''], ['2004', '1', 'USL W-League', '8th, Western', ''], ['2010', '1', 'USL W-League', '6th, Western', 'Did not qualify'], ['2008', '1', 'USL W-League', '6th, Western', 'Did not qualify'], ['2009', '1', 'USL W-League', '7th, Western', 'Did not qualify'], ['2003', '2', 'USL W-League', '5th, Western', ''], ['2007', '1', 'USL W-League', '5th, Western', ''], ['2011', '1', 'USL W-League', '7th, Western', 'Did not qualify'], ['2012', '1', 'USL W-League', '4th, Western', 'Did not qualify']]
|
3
|
Answer:
| 128
| 11
| 267
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many games did the team score at least 30 points?
|
[['Week', 'Date', 'Opponent', 'Score', 'Result', 'Record'], ['7', 'Oct 9', 'vs. Montreal Alouettes', '25β11', 'Loss', '1β7'], ['9', 'Oct 23', 'at Hamilton Tiger-Cats', '25β17', 'Loss', '1β10'], ['2', 'Sept 4', 'at Montreal Alouettes', '21β2', 'Loss', '0β2'], ['7', 'Oct 11', 'at Montreal Alouettes', '24β6', 'Loss', '1β8'], ['4', 'Sept 18', 'vs. Toronto Argonauts', '34β6', 'Loss', '1β4'], ['1', 'Aug 28', 'at Toronto Argonauts', '13β6', 'Loss', '0β1'], ['5', 'Sept 25', 'vs. Hamilton Tiger-Cats', '38β12', 'Loss', '1β5'], ['8', 'Oct 16', 'vs. Toronto Argonauts', '27β11', 'Loss', '1β9'], ['10', 'Oct 30', 'vs. Hamilton Tiger-Cats', '30β9', 'Loss', '1β11'], ['6', 'Oct 2', 'at Hamilton Tiger-Cats', '45β0', 'Loss', '1β6'], ['12', 'Nov 13', 'vs. Montreal Alouettes', '14β12', 'Win', '2β12'], ['11', 'Nov 6', 'at Toronto Argonauts', '18β12', 'Loss', '1β12'], ['2', 'Sept 6', 'vs. Montreal Alouettes', '20β11', 'Loss', '0β3'], ['3', 'Sept 11', 'at Toronto Argonauts', '12β5', 'Win', '1β3']]
|
4
|
Answer:
| 128
| 14
| 418
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:did he race more laps in 1926 or 1938?
|
[['Year', 'Car', 'Start', 'Qual', 'Rank', 'Finish', 'Laps', 'Led', 'Retired'], ['1929', '23', '11', '112.146', '15', '17', '91', '0', 'Supercharger'], ['1935', '44', '6', '115.459', '11', '21', '102', '0', 'Magneto'], ['1934', '8', '7', '113.733', '13', '17', '94', '0', 'Rod'], ['1933', '34', '12', '113.578', '15', '7', '200', '0', 'Running'], ['Totals', 'Totals', 'Totals', 'Totals', 'Totals', 'Totals', '1989', '33', ''], ['1926', '31', '12', '102.789', '13', '11', '142', '0', 'Flagged'], ['1932', '25', '20', '108.896', '34', '13', '184', '0', 'Flagged'], ['1939', '62', '27', '121.749', '24', '11', '200', '0', 'Running'], ['1931', '37', '19', '111.725', '6', '18', '167', '0', 'Crash T4'], ['1927', '27', '27', '107.765', '22', '3', '200', '0', 'Running'], ['1930', '9', '20', '100.033', '18', '20', '79', '0', 'Valve'], ['1928', '8', '4', '117.031', '4', '10', '200', '33', 'Running'], ['1937', '38', '7', '118.788', '16', '8', '200', '0', 'Running'], ['1938', '17', '4', '122.499', '6', '17', '130', '0', 'Rod']]
|
1926
|
Answer:
| 128
| 14
| 460
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what's the total attendance for gamestorm 11?
|
[['Iteration', 'Dates', 'Location', 'Attendance', 'Notes'], ['GameStorm 15', 'March 21β24, 2013', 'Hilton - Vancouver, WA', '1188', ''], ['GameStorm 16', 'March 20β23, 2014', 'Hilton - Vancouver, WA', 'tba', 'Guests: Mike Selinker, Shane Lacy Hensley, Lisa Steenson, Zev Shlasinger of Z-Man Games'], ['GameStorm 10', 'March 2008', 'Red Lion - Vancouver, WA', '750', '-'], ['GameStorm 13', 'March 24β27, 2011', 'Hilton - Vancouver, WA', '984', 'Guests: Lisa Steenson, Michael A. Stackpole'], ['GameStorm 14', 'March 22β25, 2012', 'Hilton - Vancouver, WA', '1072', 'Boardgame:Andrew Hackard and Sam Mitschke of Steve Jackson Games - RPG: Jason Bulmahn'], ['GameStorm 11', 'March 26β29, 2009', 'Hilton - Vancouver, WA', '736', 'debut of Video games, first-ever Artist Guest of Honor, Rob Alexander'], ['GameStorm 12', 'March 25β28, 2010', 'Hilton - Vancouver, WA', '802', 'Board games Guest of Honor: Tom Lehmann']]
|
736
|
Answer:
| 128
| 7
| 309
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:who is the next driver listed after scott dixon?
|
[['Pos', 'No.', 'Driver', 'Team', 'Engine', 'Laps', 'Time/Retired', 'Grid', 'Laps Led', 'Points'], ['18', '28', 'Ryan Hunter-Reay', 'Andretti Autosport', 'Chevrolet', '84', '+ 1 lap', '7', '1', '12'], ['4', '8', 'Rubens Barrichello', 'KV Racing Technology', 'Chevrolet', '85', '+ 8.8529', '11', '0', '32'], ['1', '2', 'Ryan Briscoe', 'Team Penske', 'Chevrolet', '85', '2:07:02.8248', '2', '27', '50'], ['27', '15', 'Takuma Sato', 'Rahal Letterman Lanigan Racing', 'Honda', '2', 'Mechanical', '26', '0', '10'], ['16', '5', 'E.J. Viso', 'KV Racing Technology', 'Chevrolet', '84', '+ 1 lap', '17', '0', '14'], ['23', '67', 'Josef Newgarden (R)', 'Sarah Fisher Hartman Racing', 'Honda', '62', 'Contact', '22', '0', '12'], ['10', '11', 'Tony Kanaan', 'KV Racing Technology', 'Chevrolet', '84', '+ 1 lap', '16', '0', '20'], ['5', '38', 'Graham Rahal', 'Chip Ganassi Racing', 'Honda', '85', '+ 9.4667', '13', '0', '30'], ['13', '9', 'Scott Dixon', 'Chip Ganassi Racing', 'Honda', '84', '+ 1 lap', '5', '0', '17'], ['2', '12', 'Will Power', 'Team Penske', 'Chevrolet', '85', '+ 0.4408', '1', '57', '43'], ['20', '20', 'Ed Carpenter', 'Ed Carpenter Racing', 'Chevrolet', '84', '+ 1 lap', '25', '0', '12'], ['24', '6', 'Katherine Legge (R)', 'Dragon Racing', 'Chevrolet', '48', 'Mechanical', '19', '0', '12'], ['14', '14', 'Mike Conway', 'A.J. Foyt Enterprises', 'Honda', '84', '+ 1 lap', '14', '0', '16']]
|
Mike Conway
|
Answer:
| 128
| 13
| 545
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:which venue did melissa morrison compete at in 2004?
|
[['Year', 'Competition', 'Venue', 'Position', 'Event'], ['2003', 'World Athletics Final', 'Monaco', '6th', '100 m hurdles'], ['1997', 'World Indoor Championships', 'Paris, France', '5th', '60 m hurdles'], ['2000', 'Olympic Games', 'Sydney, Australia', '3rd', '100 m hurdles'], ['2002', 'Grand Prix Final', 'Paris, France', '7th', '100 m hurdles'], ['2004', 'Olympic Games', 'Athens, Greece', '3rd', '100 m hurdles'], ['2002', 'USA Indoor Championships', '', '1st', '60 m hurdles'], ['1999', 'World Indoor Championships', 'Maebashi, Japan', '6th', '60 m hurdles'], ['1998', 'Grand Prix Final', 'Moscow, Russia', '2nd', '100 m hurdles'], ['2000', 'Grand Prix Final', 'Doha, Qatar', '4th', '100 m hurdles'], ['2003', 'World Indoor Championships', 'Birmingham, England', '3rd', '60 m hurdles'], ['1998', 'USA Indoor Championships', '', '1st', '60 m hurdles'], ['1997', 'USA Outdoor Championships', 'Indianapolis, United States', '1st', '100 m hurdles']]
|
Athens, Greece
|
Answer:
| 128
| 12
| 294
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many times is professional writer listed as the profession according to this chart?
|
[['Year', 'Recipient', 'Nationality', 'Profession', 'Speech'], ['1999', 'A.M. Rosenthal', 'United States', 'Former New York Times editor\\nFormer New York Daily News columnist', ''], ['2003', 'Ruth Roskies Wisse', 'United States', 'Yiddish professor of Harvard University', '[2]'], ['1997', 'Elie Wiesel', 'United States', 'Professional writer\\nWinner of the Nobel Peace Prize (1986)', ''], ['2008', "David Be'eri, Mordechai Eliav, Rabbi Yehuda Maly", 'Israel', '', ''], ['2007', 'Norman Podhoretz', 'United States', 'Author, columnist', ''], ['2010', 'Malcolm Hoenlein', 'United States', 'Executive Vice Chairman of the Conference of Presidents of Major American Jewish Organizations', ''], ['2004', 'Arthur Cohn', 'Switzerland', 'Filmmaker and writer', ''], ['2009', 'Caroline Glick', 'Israel', 'Journalist', ''], ['2002', 'Charles Krauthammer', 'United States', 'The Washington Post columnist', '[1]'], ['1998', 'Herman Wouk', 'United States', 'Professional writer and 1952 Pulitzer Prize winner', ''], ['2001', 'Cynthia Ozick', 'United States', 'Professional writer', ''], ['2006', 'Daniel Pipes', 'United States', 'Author and historian', ''], ['2000', 'Sir Martin Gilbert', 'United Kingdom', 'Historian and writer', ''], ['2005', 'William Safire', 'United States', 'Author, journalist and speechwriter\\n1978 Pulitzer Prize winner', '']]
|
3
|
Answer:
| 128
| 14
| 377
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what is the number of listings from barrington, farmington, and rochester combined?
|
[['', 'Name on the Register', 'Date listed', 'Location', 'City or town', 'Summary'], ['19', 'Plummer Homestead', 'June 14, 2002\\n(#02000638)', '1273 White Mountain Highway\\n43Β°27β²35β³N 70Β°59β²33β³W\ufeff / \ufeff43.459722Β°N 70.9925Β°W', 'Milton', ''], ['35', 'US Post Office-Dover Main', 'July 17, 1986\\n(#86002273)', '133-137 Washington St.\\n43Β°11β²42β³N 70Β°52β²39β³W\ufeff / \ufeff43.195Β°N 70.8775Β°W', 'Dover', ''], ['37', 'Wiswall Falls Mills Site', 'March 18, 1988\\n(#88000184)', 'John Hatch Park\\nSouth of Wiswall Road just east of the Lamprey River\\n43Β°06β²15β³N 70Β°57β²44β³W\ufeff / \ufeff43.1043Β°N 70.9621Β°W', 'Durham', ''], ['40', 'Samuel Wyatt House', 'December 2, 1982\\n(#82000626)', '7 Church St.\\n43Β°11β²30β³N 70Β°52β²31β³W\ufeff / \ufeff43.191667Β°N 70.875278Β°W', 'Dover', ''], ['17', 'New Durham Town Hall', 'November 13, 1980\\n(#80000313)', 'Main St. and Ridge Rd.\\n43Β°26β²02β³N 71Β°09β²55β³W\ufeff / \ufeff43.433889Β°N 71.165278Β°W', 'New Durham', ''], ['10', 'Green Street School', 'March 7, 1985\\n(#85000481)', '104 Green St.\\n43Β°15β²23β³N 70Β°51β²50β³W\ufeff / \ufeff43.256389Β°N 70.863889Β°W', 'Somersworth', '']]
|
5
|
Answer:
| 128
| 6
| 470
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many teams did not score any goals in the 2006 season?
|
[['Season', 'Team', 'Country', 'Division', 'Apps', 'Goals'], ['2013/14', 'Lokomotiv Moscow', 'Russia', '1', '14', '1'], ['2009/10', 'Dnipro Dnipropetrovsk', 'Ukraine', '1', '28', '0'], ['2005', 'CSKA Moscow', 'Russia', '1', '0', '0'], ['2010/11', 'Dnipro Dnipropetrovsk', 'Ukraine', '1', '23', '0'], ['2008/09', 'Dnipro Dnipropetrovsk', 'Ukraine', '1', '22', '1'], ['2012/13', 'Lokomotiv Moscow', 'Russia', '1', '8', '0'], ['2006/07', 'Dnipro Dnipropetrovsk', 'Ukraine', '1', '12', '0'], ['2012/13', 'Dnipro Dnipropetrovsk', 'Ukraine', '1', '10', '1'], ['2006', 'Spartak Nizhny Novgorod', 'Russia', '2', '36', '1'], ['2004', 'CSKA Moscow', 'Russia', '1', '0', '0'], ['2011/12', 'Dnipro Dnipropetrovsk', 'Ukraine', '1', '16', '0'], ['2007/08', 'Dnipro Dnipropetrovsk', 'Ukraine', '1', '24', '0']]
|
1
|
Answer:
| 128
| 12
| 350
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:who came in first?
|
[['Pos', 'Rider', 'Manufactuer', 'Time/Retired', 'Points'], ['8', 'Jean-Philippe Ruggia', 'Aprilia', '+3.985', '8'], ['Ret', 'Jean-Pierre Jeandat', 'Aprilia', 'Retirement', ''], ['Ret', 'Wilco Zeelenberg', 'Aprilia', 'Retirement', ''], ['Ret', 'Andreas Preining', 'Aprilia', 'Retirement', ''], ['13', 'Jochen Schmid', 'Yamaha', '+47.065', '3'], ['Ret', 'Eskil Suter', 'Aprilia', 'Retirement', ''], ['4', 'Max Biaggi', 'Honda', '+2.346', '13'], ['18', 'Bernd Kassner', 'Aprilia', '+1:16:464', ''], ['21', 'Adrian Bosshard', 'Honda', '+1:47.492', ''], ['17', 'Adi Stadler', 'Honda', '+1:16.349', ''], ['2', 'Loris Capirossi', 'Honda', '+0.090', '20'], ['14', 'Jean-Michel Bayle', 'Aprilia', '+1:15.546', '2'], ['7', 'Pierfrancesco Chili', 'Yamaha', '+3.845', '9'], ['11', 'Alberto Puig', 'Honda', '+25.136', '5'], ['9', 'Carlos CardΓΊs', 'Honda', '+4.893', '7'], ['DNS', 'Nobuatsu Aoki', 'Honda', 'Did not start', ''], ['23', 'Bernard Haenggeli', 'Aprilia', '+2:41.806', ''], ['3', 'Helmut Bradl', 'Honda', '+0.384', '16'], ['1', 'Doriano Romboni', 'Honda', '33:53.776', '25'], ['22', 'Massimo Pennacchioli', 'Honda', '+1:59.498', ''], ['Ret', 'Luis Maurel', 'Aprilia', 'Retirement', ''], ['Ret', 'Patrick van den Goorbergh', 'Aprilia', 'Retirement', ''], ['5', 'Loris Reggiani', 'Aprilia', '+2.411', '11']]
|
Doriano Romboni
|
Answer:
| 128
| 23
| 514
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what is the next team listed after widnes vikings?
|
[['Team', 'Stadium', 'Capacity', 'City/Area'], ['Hull Kingston Rovers (2014 season)', 'MS3 Craven Park', '9,471', 'Kingston upon Hull, East Riding of Yorkshire'], ['Widnes Vikings (2014 season)', 'The Select Security Stadium', '13,500', 'Widnes, Cheshire, England'], ['Wakefield Trinity Wildcats (2014 season)', 'Rapid Solicitors Stadium', '11,000', 'Wakefield, West Yorkshire'], ['Hull (2014 season)', 'Kingston Communications Stadium', '25,404', 'Kingston upon Hull, East Riding of Yorkshire'], ['Castleford Tigers (2014 season)', 'The Wish Communications Stadium', '11,750', 'Castleford, West Yorkshire'], ['Leeds Rhinos (2014 season)', 'Headingley Carnegie Stadium', '22,250', 'Leeds, West Yorkshire'], ['Salford City Reds (2014 season)', 'Salford City Stadium', '12,000', 'Salford, Greater Manchester'], ['Catalans Dragons (2014 season)', 'Stade Gilbert Brutus', '14,000', 'Perpignan, PyrΓ©nΓ©es-Orientales, France'], ['Huddersfield Giants (2014 season)', "John Smith's Stadium", '24,544', 'Huddersfield, West Yorkshire'], ['London Broncos (2014 season)', 'Twickenham Stoop', '12,700', 'Twickenham, London'], ['Warrington Wolves (2014 season)', 'Halliwell Jones Stadium', '15,500', 'Warrington, Cheshire'], ['Wigan Warriors (2014 season)', 'DW Stadium', '25,138', 'Wigan, Greater Manchester'], ['Bradford Bulls (2014 season)', 'Provident Stadium', '27,000', 'Bradford, West Yorkshire'], ['St Helens RLFC (2014 season)', 'Langtree Park', '18,000', 'St Helens, Merseyside']]
|
Wigan Warriors
|
Answer:
| 128
| 14
| 432
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many festivals was the film shown at?
|
[['Date', 'Festival', 'Location', 'Awards', 'Link'], ['Oct 9, Oct 11', 'Sitges Film Festival', 'Sitges, Catalonia\\n\xa0Spain', '', 'Sitges Festival'], ['Oct 9', 'London Int. Festival of Science Fiction Film', 'London, England\\n\xa0UK', 'Closing Night Film', 'Sci-Fi London'], ['Sep 19', 'Lund International Fantastic Film Festival', 'Lund, SkΓ₯ne\\n\xa0Sweden', '', 'fff.se'], ['Sep 28', 'Fantastic Fest', 'Austin, Texas\\n\xa0USA', '', 'FantasticFest.com'], ['Sep 16', 'Athens International Film Festival', 'Athens, Attica\\n\xa0Greece', 'Best Director', 'aiff.gr'], ['Oct 23', 'Toronto After Dark', 'Toronto, Ontario\\n\xa0Canada', 'Best Special Effects\\nBest Musical Score', 'torontoafterdark.com'], ['Jul 18, Jul 25', 'Fantasia Festival', 'Montreal, Quebec \xa0Canada', 'Special Mention\\n"for the resourcefulness and unwavering determination by a director to realize his unique vision"', 'FanTasia'], ['Oct 1, Oct 15', 'Gwacheon International SF Festival', 'Gwacheon, Gyeonggi-do\\n\xa0South Korea', '', 'gisf.org'], ['Nov 16β18', 'AFF', 'WrocΕaw, Lower Silesia\\n\xa0Poland', '', 'AFF Poland'], ['May 21β22, Jun 11', 'Seattle International Film Festival', 'Seattle, Washington \xa0USA', '', 'siff.net'], ['Nov 11', 'Les Utopiales', 'Nantes, Pays de la Loire\\n\xa0France', '', 'utopiales.org'], ['Nov 12, Nov 18', 'Indonesia Fantastic Film Festival', 'Jakarta, Bandung\\n\xa0Indonesia', '', 'inaff.com'], ['Oct 17, Oct 20', 'Icon TLV', 'Tel Aviv, Central\\n\xa0Israel', '', 'icon.org.il'], ['Feb 2β5, Feb 11', 'Santa Barbara International Film Festival', 'Santa Barbara, California \xa0USA', 'Top 11 "Best of the Fest" Selection', 'sbiff.org']]
|
14
|
Answer:
| 128
| 14
| 514
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many drivers completed 80 laps?
|
[['Pos', 'No', 'Driver', 'Constructor', 'Laps', 'Time/Retired', 'Grid', 'Points'], ['4', '9', 'Denny Hulme', 'McLaren-Ford', '80', '+ 1:06.7', '8', '3'], ['DNQ', '28', 'Skip Barber', 'March-Ford', '', '', '', ''], ['2', '17', 'Ronnie Peterson', 'March-Ford', '80', '+ 25.6', '6', '6'], ['3', '4', 'Jacky Ickx', 'Ferrari', '80', '+ 53.3', '2', '4'], ['Ret', '10', 'Peter Gethin', 'McLaren-Ford', '22', 'Accident', '14', ''], ['7', '22', 'John Surtees', 'Surtees-Ford', '79', '+ 1 Lap', '10', ''], ['DNQ', '19', 'Nanni Galli*', 'March-Alfa-Romeo', '', '', '', ''], ['DNQ', '6', 'Mario Andretti', 'Ferrari', '', '', '', ''], ['DNQ', '18', 'Alex Soler-Roig', 'March-Ford', '', '', '', ''], ['10', '8', 'Tim Schenken', 'Brabham-Ford', '76', '+ 4 Laps', '18', ''], ['Ret', '5', 'Clay Regazzoni', 'Ferrari', '24', 'Accident', '11', ''], ['Ret', '7', 'Graham Hill', 'Brabham-Ford', '1', 'Accident', '9', ''], ['9', '15', 'Pedro RodrΓguez', 'BRM', '76', '+ 4 Laps', '5', ''], ['Ret', '14', 'Jo Siffert', 'BRM', '58', 'Oil Pipe', '3', ''], ['6', '24', 'Rolf Stommelen', 'Surtees-Ford', '79', '+ 1 Lap', '16', '1'], ['DNQ', '16', 'Howden Ganley', 'BRM', '', '', '', ''], ['1', '11', 'Jackie Stewart', 'Tyrrell-Ford', '80', '1:52:21.3', '1', '9']]
|
4
|
Answer:
| 128
| 17
| 528
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what was the first interval of five years to have more than 100,000 deaths?
|
[['Period', 'Live births per year', 'Deaths per year', 'Natural change per year', 'CBR*', 'CDR*', 'NC*', 'TFR*', 'IMR*'], ['1965-1970', '229 000', '105 000', '124 000', '56.2', '25.8', '30.4', '7.32', '164'], ['2005-2010', '705 000', '196 000', '509 000', '49.5', '13.8', '35.7', '7.19', '96'], ['2000-2005', '614 000', '194 000', '420 000', '51.3', '16.2', '35.1', '7.40', '113'], ['1985-1990', '406 000', '179 000', '227 000', '55.9', '24.6', '31.3', '7.81', '155'], ['1960-1965', '195 000', '89 000', '105 000', '55.5', '25.5', '30.1', '7.13', '167'], ['1955-1960', '164 000', '76 000', '88 000', '53.8', '24.9', '29.0', '6.96', '171'], ['1975-1980', '301 000', '138 000', '164 000', '55.1', '25.1', '29.9', '7.63', '161'], ['1980-1985', '350 000', '157 000', '193 000', '55.4', '24.8', '30.6', '7.76', '159'], ['1950-1955', '139 000', '66 000', '74 000', '52.6', '24.8', '27.8', '6.86', '174'], ['1970-1975', '263 000', '121 000', '142 000', '55.8', '25.6', '30.2', '7.52', '162'], ['1990-1995', '471 000', '192 000', '279 000', '55.5', '22.7', '32.8', '7.78', '146']]
|
1965-1970
|
Answer:
| 128
| 11
| 535
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:kremlin cup and st petersburg open are in what country?
|
[['Outcome', 'No.', 'Date', 'Tournament', 'Surface', 'Opponent', 'Score'], ['Runner-up', '7.', '22 July 2012', 'Swiss Open, Switzerland', 'Clay', 'Thomaz Bellucci', '7β6(8β6), 4β6, 2β6'], ['Runner-up', '2.', '19 June 2010', 'UNICEF Open, Netherlands', 'Grass', 'Sergiy Stakhovsky', '3β6, 0β6'], ['Winner', '4.', '6 January 2013', 'Chennai Open, India', 'Hard', 'Roberto Bautista-Agut', '3β6, 6β1, 6β3'], ['Runner-up', '3.', '27 February 2011', 'International Tennis Championships, United States', 'Hard', 'Juan MartΓn del Potro', '4β6, 4β6'], ['Runner-up', '1.', '25 October 2009', 'Kremlin Cup, Russia', 'Hard (i)', 'Mikhail Youzhny', '7β6(7β5), 0β6, 4β6'], ['Runner-up', '4.', '18 June 2011', 'Aegon International, United Kingdom', 'Grass', 'Andreas Seppi', '6β7(5β7), 6β3, 3β5 ret.'], ['Winner', '2.', '23 October 2011', 'Kremlin Cup, Russia', 'Hard (i)', 'Viktor Troicki', '6β4, 6β2'], ['Runner-up', '6.', '8 January 2012', 'Chennai Open, India', 'Hard', 'Milos Raonic', '7β6(7β4), 6β7(4β7), 6β7(4β7)'], ['Winner', '1.', '2 October 2011', 'Malaysian Open, Malaysia', 'Hard (i)', 'Marcos Baghdatis', '6β4, 7β5'], ['Runner-up', '5.', '30 October 2011', 'St. Petersburg Open, Russia', 'Hard (i)', 'Marin ΔiliΔ', '3β6, 6β3, 2β6']]
|
Russia
|
Answer:
| 128
| 10
| 510
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many gold medals did australia and switzerland total?
|
[['Rank', 'Nation', 'Gold', 'Silver', 'Bronze', 'Total'], ['7', 'Great Britain\xa0(GBR)', '0', '0', '1', '1'], ['7', 'France\xa0(FRA)', '0', '0', '1', '1'], ['2', 'Italy\xa0(ITA)', '1', '1', '1', '3'], ['4', 'Soviet Union\xa0(URS)', '1', '0', '0', '1'], ['1', 'Australia\xa0(AUS)', '2', '1', '0', '3'], ['5', 'Switzerland\xa0(SUI)', '0', '2', '1', '3'], ['3', 'Germany\xa0(EUA)', '1', '0', '1', '2'], ['6', 'United States\xa0(USA)', '0', '1', '0', '1']]
|
2
|
Answer:
| 128
| 8
| 203
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what is the number of sizes that has an inner diameter above 50 mm?
|
[['Thread\\nnominal size', 'Outer diameter\\n[mm (in)]', 'Threads per inch\\n(TPI)', 'Pitch\\n[in (mm)]', 'Inner diameter\\n[mm (in)]', 'Cable diameter\\n[mm (in)]'], ['PG21', '28.3 (1.114)', '16', '0.0625 (1.5875)', '26.78 (1.054)', '13 to 18 (0.512 to 0.709)'], ['PG13.5', '20.4 (0.803)', '18', '0.05556 (1.4112)', '19.06 (0.750)', '6 to 12 (0.236 to 0.472)'], ['PG16', '22.5 (0.886)', '18', '0.05556 (1.4112)', '21.16 (0.833)', '10 to 14 (0.394 to 0.551)'], ['PG42', '54.0 (2.126)', '16', '0.0625 (1.5875)', '52.48 (2.066)', ''], ['PG36', '47.0 (1.850)', '16', '0.0625 (1.5875)', '45.48 (1.791)', ''], ['PG9', '15.5 (0.610)', '18', '0.05556 (1.4112)', '13.86 (0.546)', '4 to 8 (0.157 to 0.315)'], ['PG7', '12.5 (0.492)', '20', '0.05 (1.270)', '11.28 (0.444)', '3 to 6.5 (0.118 to 0.256)'], ['PG48', '59.3 (2.335)', '16', '0.0625 (1.5875)', '57.78 (2.275)', ''], ['PG11', '18.6 (0.732)', '18', '0.05556 (1.4112)', '17.26 (0.680)', '5 to 10 (0.197 to 0.394)'], ['PG29', '37.0 (1.457)', '16', '0.0625 (1.5875)', '35.48 (1.397)', '18 to 25 (0.709 to 0.984)']]
|
2
|
Answer:
| 128
| 10
| 540
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:which country has the larger number of circuits?
|
[['Round', 'Date', 'Circuit', 'Winning driver (TA2)', 'Winning vehicle (TA2)', 'Winning driver (TA1)', 'Winning vehicle (TA1)'], ['2', 'June 4', 'Westwood', 'Ludwig Heimrath', 'Porsche 935', 'Nick Engels', 'Chevrolet Corvette'], ['4', 'June 25', 'Mont-Tremblant', 'Monte Sheldon', 'Porsche 935', 'Bob Tullius', 'Jaguar XJS'], ['9', 'October 8', 'Laguna Seca', 'Greg Pickett', 'Chevrolet Corvette', 'Bob Tullius', 'Jaguar XJS'], ['1', 'May 21', 'Sears Point', 'Greg Pickett', 'Chevrolet Corvette', 'Gene Bothello', 'Chevrolet Corvette'], ['7', 'August 19', 'Mosport', 'Greg Pickett', 'Chevrolet Corvette', 'Bob Tullius', 'Jaguar XJS'], ['5', 'July 8', 'Watkins Glenβ‘', 'Hal Shaw, Jr.\\n Monte Shelton', 'Porsche 935', 'Brian Fuerstenau\\n Bob Tullius', 'Jaguar XJS'], ['3', 'June 11', 'Portland', 'Tuck Thomas', 'Chevrolet Monza', 'Bob Matkowitch', 'Chevrolet Corvette'], ['10', 'November 5', 'Mexico City', 'Ludwig Heimrath', 'Porsche 935', 'Bob Tullius', 'Jaguar XJS'], ['6', 'August 13', 'Brainerd', 'Jerry Hansen', 'Chevrolet Monza', 'Bob Tullius', 'Jaguar XJS'], ['8', 'September 4', 'Road America', 'Greg Pickett', 'Chevrolet Corvette', 'Bob Tullius', 'Jaguar XJS']]
|
USA
|
Answer:
| 128
| 10
| 426
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:did brazil and the united states have the highest gold count?
|
[['Rank', 'Nation', 'Gold', 'Silver', 'Bronze', 'Total'], ['12.', 'Austria', '0', '0', '1', '1'], ['4.', 'Netherlands', '1', '1', '1', '3'], ['2.', 'United States', '9', '3', '6', '18'], ['7.', 'Germany', '0', '5', '1', '6'], ['10.', 'Switzerland', '0', '1', '1', '2'], ['6.', 'Estonia', '1', '0', '0', '1'], ['1.', 'Brazil', '21', '9', '12', '42'], ['3.', 'China', '1', '9', '8', '18'], ['11.', 'Norway', '0', '1', '0', '1'], ['4.', 'Australia', '1', '1', '1', '3'], ['9.', 'Argentina', '0', '2', '0', '2'], ['8.', 'Russia', '0', '2', '3', '5']]
|
Yes
|
Answer:
| 128
| 12
| 242
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:in what year did he lead the most laps in?
|
[['Year', 'Car', 'Start', 'Qual', 'Rank', 'Finish', 'Laps', 'Led', 'Retired'], ['1932', '25', '20', '108.896', '34', '13', '184', '0', 'Flagged'], ['1934', '8', '7', '113.733', '13', '17', '94', '0', 'Rod'], ['1927', '27', '27', '107.765', '22', '3', '200', '0', 'Running'], ['1929', '23', '11', '112.146', '15', '17', '91', '0', 'Supercharger'], ['1926', '31', '12', '102.789', '13', '11', '142', '0', 'Flagged'], ['1939', '62', '27', '121.749', '24', '11', '200', '0', 'Running'], ['1928', '8', '4', '117.031', '4', '10', '200', '33', 'Running'], ['1933', '34', '12', '113.578', '15', '7', '200', '0', 'Running'], ['1930', '9', '20', '100.033', '18', '20', '79', '0', 'Valve'], ['1935', '44', '6', '115.459', '11', '21', '102', '0', 'Magneto'], ['1938', '17', '4', '122.499', '6', '17', '130', '0', 'Rod'], ['Totals', 'Totals', 'Totals', 'Totals', 'Totals', 'Totals', '1989', '33', ''], ['1931', '37', '19', '111.725', '6', '18', '167', '0', 'Crash T4'], ['1937', '38', '7', '118.788', '16', '8', '200', '0', 'Running']]
|
1928
|
Answer:
| 128
| 14
| 460
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many games were played after october 1st?
|
[['Date', 'Team', 'Competition', 'Round', 'Leg', 'Opponent', 'Location', 'Score'], ['August 29', 'Anderlecht', 'Champions League', 'Qual. Round 3', 'Leg 2, Home', 'FenerbahΓ§e', 'Constant Vanden Stock Stadium, Anderlecht', '0-2'], ['September 20', 'Standard LiΓ¨ge', 'UEFA Cup', 'Round 1', 'Leg 1, Away', 'Zenit St. Petersburg', 'Petrovsky Stadium, Saint Petersburg', '0-3'], ['November 8', 'Anderlecht', 'UEFA Cup', 'Group Stage', 'Match 2, Away', 'Aalborg', 'Energi Nord Arena, Aalborg', '1-1'], ['August 8', 'Genk', 'Champions League', 'Qual. Round 2', 'Leg 2, Away', 'Sarajevo', 'Asim FerhatoviΔ Hase Stadium, Sarajevo', '1-0'], ['February 21', 'Anderlecht', 'UEFA Cup', 'Round of 32', 'Leg 2, Away', 'Bordeaux', 'Stade Chaban-Delmas, Bordeaux', '1-1'], ['March 12', 'Anderlecht', 'UEFA Cup', 'Round of 16', 'Leg 2, Away', 'Bayern Munich', 'Allianz Arena, Munich', '2-1'], ['February 13', 'Anderlecht', 'UEFA Cup', 'Round of 32', 'Leg 1, Home', 'Bordeaux', 'Constant Vanden Stock Stadium, Anderlecht', '2-1'], ['July 29', 'Gent', 'Intertoto Cup', 'Round 3', 'Leg 2, Away', 'Aalborg', 'Energi Nord Arena, Aalborg', '1-2'], ['August 30', 'Standard LiΓ¨ge', 'UEFA Cup', 'Qual. Round 2', 'Leg 2, Home', 'KΓ€erjeng', 'Stade Maurice Dufrasne, LiΓ¨ge', '1-0'], ['September 20', 'Club Brugge', 'UEFA Cup', 'Round 1', 'Leg 1, Away', 'Brann', 'Brann Stadion, Bergen', '1-0']]
|
11
|
Answer:
| 128
| 10
| 520
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what is the total number of wins listed for the united states?
|
[['Golfer', 'Country', 'Wins', 'Match Play', 'Championship', 'Invitational', 'Champions'], ['Phil Mickelson', 'United States', '2', 'β', '1: 2009', 'β', '1: 2009'], ['Hunter Mahan', 'United States', '2', '1: 2012', 'β', '1: 2010', 'β'], ['Ian Poulter', 'England', '2', '1: 2010', 'β', 'β', '1: 2012'], ['Darren Clarke', 'Northern Ireland', '2', '1: 2000', 'β', '1: 2003', 'β'], ['Ernie Els', 'South Africa', '2', 'β', '2: 2004, 2010', 'β', 'β'], ['Geoff Ogilvy', 'Australia', '3', '2: 2006, 2009', '1: 2008', 'β', 'β'], ['Tiger Woods', 'United States', '18', '3: 2003, 2004, 2008', '7: 1999, 2002, 2003,\\n2005, 2006, 2007, 2013', '8: 1999, 2000, 2001, 2005,\\n2006, 2007, 2009, 2013', 'β']]
|
22
|
Answer:
| 128
| 7
| 323
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:if italy and brazil combined box office revenues, what would be their new total?
|
[['Rank', 'Country', 'Box Office', 'Year', 'Box office\\nfrom national films'], ['3', 'Japan', '$1.88 billion', '2013', '61% (2013)'], ['11', 'Italy', '$0.84 billion', '2013', '30% (2013)'], ['1', 'Canada/United States', '$10.8 billion', '2012', 'β'], ['9', 'Russia', '$1.2 billion', '2012', 'β'], ['6', 'South Korea', '$1.47 billion', '2013', '59.7% (2013)'], ['12', 'Brazil', '$0.72 billion', '2013', '17% (2013)'], ['2', 'China', '$3.6 billion', '2013', '59% (2013)'], ['10', 'Australia', '$1.2 billion', '2012', '4.1% (2011)'], ['-', 'World', '$34.7 billion', '2012', 'β'], ['5', 'France', '$1.7 billion', '2012', '33.3% (2013)'], ['8', 'Germany', '$1.3 billion', '2012', 'β'], ['7', 'India', '$1.4 billion', '2012', 'β'], ['4', 'United Kingdom', '$1.7 billion', '2012', '36.1% (2011)']]
|
$1.56 billion
|
Answer:
| 128
| 13
| 321
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:when did the restaurant "verre" at the hilton dubai creek close?
|
[['Restaurant', 'Location', 'Date Opened', 'Date Closed'], ['Maze by Gordon Ramsay', 'The Pearl-Qatar, Doha, Qatar', '2010', 'March 2012'], ['Maze / Maze Grill by Gordon Ramsay', 'Crown Metropol, Melbourne, Australia', 'March 2010', 'August 2011'], ['Cerise by Gordon Ramsay', 'Minato, Tokyo, Japan', '', '-'], ['Gordon Ramsay at Conrad Tokyo', 'Conrad Tokyo, Tokyo, Japan', '', '-'], ['Maze by Gordon Ramsay', 'One and Only Hotel, Cape Town, South Africa', 'April 2009', 'July 2010'], ['Verre at the Hilton Dubai Creek', 'Dubai, United Arab Emirates', '', 'October 2011']]
|
October 2011
|
Answer:
| 128
| 6
| 174
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:who finished immediately after danny osborne?
|
[['Position', 'Driver', 'No.', 'Car', 'Entrant', 'Lak.', 'Ora.', 'San.', 'Phi.', 'Total'], ['22', 'Shane Eklund', '', '', '', '10', '-', '-', '-', '10'], ['10', 'Des Wall', '', 'Toyota Supra', '', '15', '32', '-', '-', '47'], ['6', 'Danny Osborne', '', 'Mazda RX-7', '', '26', '10', '30', '-', "66'"], ['15', 'Gary Rowe', '47', 'Nissan Stanza', 'Gary Rowe', '-', '-', '21', '-', '21'], ['', 'Paul Barrett', '', '', '', '-', '-', '-', '12', '12'], ['19', 'Chris Donnelly', '', '', '', '12', '-', '-', '-', '12'], ['13', 'Chris Fing', '', 'Chevrolet Monza', '', '29', '-', '-', '-', '29'], ['', "Ron O'Brien", '', '', '', '-', '-', '-', '10', '10'], ['3', 'James Phillip', '55', 'Honda Prelude Chevrolet', 'James Phillip', '26', '28', '28', '30', '112'], ['17', 'Phil Crompton', '49', 'Ford EA Falcon', 'Phil Crompton', '17', '-', '-', '-', '17'], ['5', 'Bob Jolly', '3', 'Holden VS Commodore', 'Bob Jolly', '-', '28', '16', '32', '76'], ['14', 'Brian Smith', '', 'Alfa Romeo GTV Chevrolet', '', '-', '28', '-', '-', '28'], ['11', 'Kevin Clark', '116', 'Ford Mustang GT', 'Kevin Clark', '-', '-', '23', '23', '46'], ['', 'Domenic Beninca', '', '', '', '-', '-', '-', '21', '21'], ['12', "Peter O'Brien", '17', 'Holden VL Commodore', "O'Brien Aluminium", '-', '11', '29', '-', '40'], ['7', 'Mike Imrie', '4', 'Saab', 'Imrie Motor Sport', '23', '11', '-', '28', '62'], ['21', 'Brett Francis', '', '', '', '11', '-', '-', '-', '11'], ['8', 'Mark Trenoweth', '', 'Jaguar', '', '33', '24', '-', '-', '57']]
|
Mike Imrie
|
Answer:
| 128
| 18
| 518
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:where is saint anslem school located?
|
[['District', 'Location', 'Communities served'], ['Hershey Montessori Farm School', 'Huntsburg Township, Ohio', 'parent-owned, and chartered by Ohio Department of Education: application deadline January each year'], ["Saint Helen's School", 'Newbury, Ohio', 'Roman Catholic Diocese of Cleveland K - 8th grade; parishioners and non-parishioners'], ["Saint Mary's School", 'Chardon, Ohio', 'Roman Catholic Diocese of Cleveland preschool - 8th grade; parishioners and non-parishioners'], ['Saint Anselm School', 'Chester Township, Ohio', 'Roman Catholic Diocese of Cleveland K - 8th grade; preschool'], ['Hawken School', 'Gates Mills, Ohio', 'College preparatory day school: online application, site visit and testing'], ['Notre Dame-Cathedral Latin', 'Munson Township, Ohio', 'Roman Catholic Diocese of Cleveland: open to 8th grade students who have attended a Catholic elementary school and others who have not'], ['Solon/Bainbridge Montessori School of Languages', 'Bainbridge Township, Ohio', 'nonsectarian Montessori School: quarterly enrollment periods'], ['Agape Christian Academy', 'Burton Township, Ohio and Troy Township, Ohio', 'Accepts applications prior to the start of each school year']]
|
Chester Township, Ohio
|
Answer:
| 128
| 8
| 288
|
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.