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2009 - 10 louisville cardinals men 's basketball team | https://en.wikipedia.org/wiki/2009%E2%80%9310_Louisville_Cardinals_men%27s_basketball_team | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-25118909-3.html.csv | majority | the majority of players on the 2009 - 10 louisville cardinals men 's basketball team play the guard position . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'guard', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'position', 'guard'], 'result': True, 'ind': 0, 'tointer': 'for the position records of all rows , most of them fuzzily match to guard .', 'tostr': 'most_eq { all_rows ; position ; guard } = true'} | most_eq { all_rows ; position ; guard } = true | for the position records of all rows , most of them fuzzily match to guard . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'position_3': 3, 'guard_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'position_3': 'position', 'guard_4': 'guard'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'position_3': [0], 'guard_4': [0]} | ['name', '-', 'position', 'height', 'weight', 'year', 'former school', 'hometown'] | [['chris brickley', '11', 'guard', '6 - 4', '175', 'senior', 'northeastern university', 'manchester , nh'], ['rakeem buckles', '4', 'forward', '6 - 8', '200', 'freshman', 'pace', 'miami , fl'], ['reginald delk', '12', 'guard', '6 - 4', '175', 'senior', 'mississippi state university', 'jackson , tn'], ['george goode', '... |
smallville ( season 10 ) | https://en.wikipedia.org/wiki/Smallville_%28season_10%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-26464364-1.html.csv | unique | the only episode directed by turi meyer was episode 6 which was called harvest . | {'scope': 'all', 'row': '6', 'col': '4', 'col_other': '2,3', 'criterion': 'equal', 'value': 'turi meyer', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'directed by', 'turi meyer'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose directed by record fuzzily matches to turi meyer .', 'tostr': 'filter_eq { all_rows ; directed by ; turi meyer }'}], 'result': True,... | and { only { filter_eq { all_rows ; directed by ; turi meyer } } ; and { eq { hop { filter_eq { all_rows ; directed by ; turi meyer } ; - } ; 6 } ; eq { hop { filter_eq { all_rows ; directed by ; turi meyer } ; title } ; harvest } } } = true | select the rows whose directed by record fuzzily matches to turi meyer . there is only one such row in the table . the - record of this unqiue row is 6 . the title record of this unqiue row is harvest . | 10 | 8 | {'and_7': 7, 'result_8': 8, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_9': 9, 'directed by_10': 10, 'turi meyer_11': 11, 'and_6': 6, 'eq_3': 3, 'num_hop_2': 2, '-_12': 12, '6_13': 13, 'str_eq_5': 5, 'str_hop_4': 4, 'title_14': 14, 'harvest_15': 15} | {'and_7': 'and', 'result_8': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_9': 'all_rows', 'directed by_10': 'directed by', 'turi meyer_11': 'turi meyer', 'and_6': 'and', 'eq_3': 'eq', 'num_hop_2': 'num_hop', '-_12': '-', '6_13': '6', 'str_eq_5': 'str_eq', 'str_hop_4': 'str_hop', 'title_14': '... | {'and_7': [8], 'result_8': [], 'only_1': [7], 'filter_str_eq_0': [1, 2, 4], 'all_rows_9': [0], 'directed by_10': [0], 'turi meyer_11': [0], 'and_6': [7], 'eq_3': [6], 'num_hop_2': [3], '-_12': [2], '6_13': [3], 'str_eq_5': [6], 'str_hop_4': [5], 'title_14': [4], 'harvest_15': [5]} | ['no', '-', 'title', 'directed by', 'written by', 'us air date', 'production code', 'us viewers ( million )'] | [['196', '1', 'lazarus', 'kevin g fair', 'don whitehead & holly henderson', 'september 24 , 2010', '3x6001', '2.98'], ['197', '2', 'shield', 'glen winter', 'jordan hawley', 'october 1 , 2010', '3x6002', '2.38'], ['198', '3', 'supergirl', 'mairzee almas', 'anne cofell saunders', 'october 8 , 2010', '3x6003', '2.30'], ['... |
1991 - 92 in argentine football | https://en.wikipedia.org/wiki/1991%E2%80%9392_in_Argentine_football | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-14390413-1.html.csv | superlative | the river plate team had the most points in the 1991 - 92 argentine football season . | {'scope': 'all', 'col_superlative': '3', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'points'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; points }'}, 'team'], 'result': 'river plate', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; points } ; team }'}, 'river plate'], 'result': True, 'ind': 2, '... | eq { hop { argmax { all_rows ; points } ; team } ; river plate } = true | select the row whose points record of all rows is maximum . the team record of this row is river plate . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'points_5': 5, 'team_6': 6, 'river plate_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'points_5': 'points', 'team_6': 'team', 'river plate_7': 'river plate'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'points_5': [0], 'team_6': [1], 'river plate_7': [2]} | ['team', 'average', 'points', 'played', '1989 - 90', '1990 - 91', '1991 - 1992'] | [['river plate', '1.342', '153', '114', '53', '45', '55'], ['boca juniors', '1.263', '144', '114', '43', '51', '50'], ['vélez sársfield', '1.184', '135', '114', '42', '45', '48'], ["newell 's old boys", '1.123', '128', '114', '36', '48', '44'], ['independiente', '1.070', '122', '114', '46', '40', '36'], ['racing club',... |
2008 detroit shock season | https://en.wikipedia.org/wiki/2008_Detroit_Shock_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17103729-10.html.csv | majority | all games of the detroit shock 's in the 2008 season were played in the month of september . | {'scope': 'all', 'col': '2', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'september', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'date', 'september'], 'result': True, 'ind': 0, 'tointer': 'for the date records of all rows , all of them fuzzily match to september .', 'tostr': 'all_eq { all_rows ; date ; september } = true'} | all_eq { all_rows ; date ; september } = true | for the date records of all rows , all of them fuzzily match to september . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'date_3': 3, 'september_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'date_3': 'date', 'september_4': 'september'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'date_3': [0], 'september_4': [0]} | ['game', 'date', 'opponent', 'score', 'high points', 'high rebounds', 'high assists', 'location / attendance', 'record'] | [['30', 'september 5', 'indiana', '90 - 68', 'pierson ( 20 )', 'pierson ( 6 )', 'mcwilliams - franklin , pierson ( 4 )', 'palace of auburn hills 9287', '18 - 12'], ['31', 'september 6', 'washington', '84 - 69', 'mcwilliams - franklin ( 21 )', 'nolan ( 10 )', 'smith ( 8 )', 'verizon center 9976', '19 - 12'], ['32', 'sep... |
united states house of representatives elections , 2006 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_2006 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1805191-4.html.csv | aggregation | the arizona incumbents in the 2006 united states house of representatives elections had an average first election year of 1996 . | {'scope': 'all', 'col': '4', 'type': 'average', 'result': '1996', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'first elected'], 'result': '1996', 'ind': 0, 'tostr': 'avg { all_rows ; first elected }'}, '1996'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; first elected } ; 1996 } = true', 'tointer': 'the average of the first elected record of... | round_eq { avg { all_rows ; first elected } ; 1996 } = true | the average of the first elected record of all rows is 1996 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'first elected_4': 4, '1996_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'first elected_4': 'first elected', '1996_5': '1996'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'first elected_4': [0], '1996_5': [1]} | ['district', 'incumbent', 'party', 'first elected', 'results'] | [['arizona 1', 'rick renzi', 'republican', '2002', 're - elected'], ['arizona 2', 'trent franks', 'republican', '2002', 're - elected'], ['arizona 3', 'john shadegg', 'republican', '1994', 're - elected'], ['arizona 4', 'ed pastor', 'democratic', '1990', 're - elected'], ['arizona 5', 'j d hayworth', 'republican', '199... |
you can dance : po prostu tańcz ! | https://en.wikipedia.org/wiki/You_Can_Dance%3A_Po_prostu_ta%C5%84cz%21 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17671150-9.html.csv | aggregation | on you can dance : po prostu tancz ! the total points were 235 . | {'scope': 'all', 'col': '4', 'type': 'sum', 'result': '235', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'points jury'], 'result': '235', 'ind': 0, 'tostr': 'sum { all_rows ; points jury }'}, '235'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; points jury } ; 235 } = true', 'tointer': 'the sum of the points jury record of all rows is 23... | round_eq { sum { all_rows ; points jury } ; 235 } = true | the sum of the points jury record of all rows is 235 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'points jury_4': 4, '235_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'points jury_4': 'points jury', '235_5': '235'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'points jury_4': [0], '235_5': [1]} | ['team', 'dance', 'music', 'points jury', 'place'] | [['rafał bryndal & diana staniszewska', 'jive', 'i get around - beach boys', '18 ( 5 , 5 , 4 , 4 )', '4 . place'], ['rafał bryndal & diana staniszewska', 'pop', 'thriller - michael jackson', '31 ( 5 , 6 , 10 , 10 )', '4 . place'], ['anna guzik & rafał kamiński', 'tango', 'libertango - ástor piazzolla', '24 ( 7 , 5 , 6 ... |
1933 vfl season | https://en.wikipedia.org/wiki/1933_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10790397-11.html.csv | ordinal | princes park venue recorded the highest crowd participation during the 1933 vfl season . | {'row': '3', 'col': '6', 'order': '1', 'col_other': '5', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'crowd', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; crowd ; 1 }'}, 'venue'], 'result': 'princes park', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; crowd ; 1 } ; venue }'}, 'princes park'], '... | eq { hop { nth_argmax { all_rows ; crowd ; 1 } ; venue } ; princes park } = true | select the row whose crowd record of all rows is 1st maximum . the venue record of this row is princes park . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'crowd_5': 5, '1_6': 6, 'venue_7': 7, 'princes park_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'crowd_5': 'crowd', '1_6': '1', 'venue_7': 'venue', 'princes park_8': 'princes park'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'crowd_5': [0], '1_6': [0], 'venue_7': [1], 'princes park_8': [2]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['north melbourne', '13.12 ( 90 )', 'south melbourne', '15.13 ( 103 )', 'arden street oval', '15000', '8 july 1933'], ['collingwood', '20.19 ( 139 )', 'essendon', '14.14 ( 98 )', 'victoria park', '8500', '8 july 1933'], ['carlton', '10.10 ( 70 )', 'richmond', '9.13 ( 67 )', 'princes park', '43000', '8 july 1933'], ['m... |
1988 open championship | https://en.wikipedia.org/wiki/1988_Open_Championship | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18139254-4.html.csv | unique | seve ballesteros was the only player from spain in the 1988 open championship . | {'scope': 'all', 'row': '1', 'col': '3', 'col_other': '2', 'criterion': 'equal', 'value': 'spain', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'spain'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose country record fuzzily matches to spain .', 'tostr': 'filter_eq { all_rows ; country ; spain }'}], 'result': True, 'ind': 1, 'tostr': 'only {... | and { only { filter_eq { all_rows ; country ; spain } } ; eq { hop { filter_eq { all_rows ; country ; spain } ; player } ; seve ballesteros } } = true | select the rows whose country record fuzzily matches to spain . there is only one such row in the table . the player record of this unqiue row is seve ballesteros . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'country_7': 7, 'spain_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'player_9': 9, 'seve ballesteros_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'country_7': 'country', 'spain_8': 'spain', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'player_9': 'player', 'seve ballesteros_10': 'seve ballesteros'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'country_7': [0], 'spain_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'player_9': [2], 'seve ballesteros_10': [3]} | ['place', 'player', 'country', 'score', 'to par'] | [['1', 'seve ballesteros', 'spain', '67', '4'], ['t2', 'brad faxon', 'united states', '69', '2'], ['t2', 'wayne grady', 'australia', '69', '2'], ['t4', 'don pooley', 'united states', '70', '1'], ['t4', 'nick price', 'zimbabwe', '70', '1'], ['t4', 'noel ratcliffe', 'australia', '70', '1'], ['t4', 'peter senior', 'austra... |
list of superfund sites in illinois | https://en.wikipedia.org/wiki/List_of_Superfund_sites_in_Illinois | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12769819-1.html.csv | ordinal | of the superfund sites in illinois , the one that has the third-latest list date is in lake county . | {'row': '9', 'col': '3', 'order': '3', 'col_other': '2', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'listed', '3'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; listed ; 3 }'}, 'county'], 'result': 'lake', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; listed ; 3 } ; county }'}, 'lake'], 'result': Tr... | eq { hop { nth_argmax { all_rows ; listed ; 3 } ; county } ; lake } = true | select the row whose listed record of all rows is 3rd maximum . the county record of this row is lake . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'listed_5': 5, '3_6': 6, 'county_7': 7, 'lake_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'listed_5': 'listed', '3_6': '3', 'county_7': 'county', 'lake_8': 'lake'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'listed_5': [0], '3_6': [0], 'county_7': [1], 'lake_8': [2]} | ['cerclis id', 'county', 'listed', 'construction completed', 'partially deleted', 'deleted'] | [['ild980607055', 'adams', '08 / 30 / 1990', '03 / 31 / 1999', 'n / a', 'n / a'], ['ild980996789', 'alexander', '10 / 04 / 1989', '09 / 28 / 1999', 'n / a', '01 / 08 / 2001'], ['ild980397079', 'cumberland', '09 / 08 / 1983', '09 / 24 / 1992', 'n / a', 'n / a'], ['il3210020803', 'jo daviess', '03 / 13 / 1989', 'n / a', ... |
yen plus | https://en.wikipedia.org/wiki/Yen_Plus | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18685750-2.html.csv | ordinal | ' time and again ' was the second latest manwha in the yen plus to have its first issue created . | {'row': '6', 'col': '3', 'order': '2', 'col_other': '1', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'first issue', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; first issue ; 2 }'}, 'title'], 'result': 'time and again', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; first issue ; 2 } ; title }'}... | eq { hop { nth_argmax { all_rows ; first issue ; 2 } ; title } ; time and again } = true | select the row whose first issue record of all rows is 2nd maximum . the title record of this row is time and again . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'first issue_5': 5, '2_6': 6, 'title_7': 7, 'time and again_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'first issue_5': 'first issue', '2_6': '2', 'title_7': 'title', 'time and again_8': 'time and again'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'first issue_5': [0], '2_6': [0], 'title_7': [1], 'time and again_8': [2]} | ['title', 'author', 'first issue', 'last issue', 'completed'] | [["aron 's absurd armada", 'misun kim', 'august 2010', 'ongoing', 'no'], ['jack frost', 'jinho ko', 'august 2008', 'ongoing', 'no'], ['one fine day', 'sirial', 'august 2008', 'july 2010', 'yes'], ['pig bride', 'kookhwa huh ( author ) , sujin kim ( artist )', 'august 2008', 'july 2010', 'yes'], ['sarasah', 'ryang ruy', ... |
2008 - 09 temple owls men 's basketball team | https://en.wikipedia.org/wiki/2008%E2%80%9309_Temple_Owls_men%27s_basketball_team | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-30054758-3.html.csv | unique | the december 6 game was the only game played at the bryce jordan center . | {'scope': 'all', 'row': '2', 'col': '8', 'col_other': '2', 'criterion': 'equal', 'value': 'bryce jordan center , state college , pa ( 9833 )', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location attendance', 'bryce jordan center , state college , pa ( 9833 )'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose location attendance record fuzzily matches to bryce jordan center , state college , p... | and { only { filter_eq { all_rows ; location attendance ; bryce jordan center , state college , pa ( 9833 ) } } ; eq { hop { filter_eq { all_rows ; location attendance ; bryce jordan center , state college , pa ( 9833 ) } ; date } ; december 6 } } = true | select the rows whose location attendance record fuzzily matches to bryce jordan center , state college , pa ( 9833 ) . there is only one such row in the table . the date record of this unqiue row is december 6 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'location attendance_7': 7, 'bryce jordan center , state college , pa (9833)_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'date_9': 9, 'december 6_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'location attendance_7': 'location attendance', 'bryce jordan center , state college , pa (9833)_8': 'bryce jordan center , state college , pa ( 9833 )', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'da... | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'location attendance_7': [0], 'bryce jordan center , state college , pa (9833)_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'date_9': [2], 'december 6_10': [3]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record'] | [['6', 'december 3', 'miami ( oh )', 'l 68 - 52', 'sergio olmos - 12', 'brooks - 6', 'inge - 5', 'liacouras center , philadelphia , pa ( 5029 )', '3 - 3'], ['7', 'december 6', 'penn state', 'w 65 - 59', 'inge - 19', 'allen - 10', 'inge - 6', 'bryce jordan center , state college , pa ( 9833 )', '4 - 3'], ['8', 'december... |
list of widows and widowers | https://en.wikipedia.org/wiki/List_of_widows_and_widowers | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-24143253-4.html.csv | unique | norris church mailer and norman mailer were the only widow and widowers with 1 son . | {'scope': 'all', 'row': '5', 'col': '6', 'col_other': '1,2', 'criterion': 'equal', 'value': '1 son', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'children together', '1 son'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose children together record fuzzily matches to 1 son .', 'tostr': 'filter_eq { all_rows ; children together ; 1 son }'}], 'result': Tr... | and { only { filter_eq { all_rows ; children together ; 1 son } } ; and { eq { hop { filter_eq { all_rows ; children together ; 1 son } ; name } ; norris church mailer } ; eq { hop { filter_eq { all_rows ; children together ; 1 son } ; deceased spouse } ; norman mailer } } } = true | select the rows whose children together record fuzzily matches to 1 son . there is only one such row in the table . the name record of this unqiue row is norris church mailer . the deceased spouse record of this unqiue row is norman mailer . | 10 | 8 | {'and_7': 7, 'result_8': 8, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_9': 9, 'children together_10': 10, '1 son_11': 11, 'and_6': 6, 'str_eq_3': 3, 'str_hop_2': 2, 'name_12': 12, 'norris church mailer_13': 13, 'str_eq_5': 5, 'str_hop_4': 4, 'deceased spouse_14': 14, 'norman mailer_15': 15} | {'and_7': 'and', 'result_8': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_9': 'all_rows', 'children together_10': 'children together', '1 son_11': '1 son', 'and_6': 'and', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'name_12': 'name', 'norris church mailer_13': 'norris church mailer', 'str_... | {'and_7': [8], 'result_8': [], 'only_1': [7], 'filter_str_eq_0': [1, 2, 4], 'all_rows_9': [0], 'children together_10': [0], '1 son_11': [0], 'and_6': [7], 'str_eq_3': [6], 'str_hop_2': [3], 'name_12': [2], 'norris church mailer_13': [3], 'str_eq_5': [6], 'str_hop_4': [5], 'deceased spouse_14': [4], 'norman mailer_15': ... | ['name', 'deceased spouse', 'cause of death', 'date of spouses death', 'length of marriage', 'children together', 'current marital status'] | [['samuel beckett', 'suzanne dãchevaux - dumesnil', 'unknown', 'july 17 , 1989 ( aged89 )', '28 years', 'none', 'deceased ( 1989 )'], ['jan berenstain', 'stan berenstain', 'unknown', 'november 26 , 2005 ( aged82 )', '59 years', '2 sons ( leo , michael )', 'deceased ( 2012 )'], ['ray bradbury', 'marguerite mcclure', 'no... |
1953 washington redskins season | https://en.wikipedia.org/wiki/1953_Washington_Redskins_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15123292-1.html.csv | aggregation | the average crowd attendance in the 1953 washington redskins season was 24652 . | {'scope': 'all', 'col': '5', 'type': 'average', 'result': '24652', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'attendance'], 'result': '24652', 'ind': 0, 'tostr': 'avg { all_rows ; attendance }'}, '24652'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; attendance } ; 24652 } = true', 'tointer': 'the average of the attendance record of all rows... | round_eq { avg { all_rows ; attendance } ; 24652 } = true | the average of the attendance record of all rows is 24652 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'attendance_4': 4, '24652_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'attendance_4': 'attendance', '24652_5': '24652'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'attendance_4': [0], '24652_5': [1]} | ['week', 'date', 'opponent', 'result', 'attendance'] | [['1', 'september 27 , 1953', 'chicago cardinals', 'w 24 - 13', '16055'], ['2', 'october 2 , 1953', 'philadelphia eagles', 't 21 - 21', '19099'], ['3', 'october 11 , 1953', 'new york giants', 'w 13 - 9', '26241'], ['4', 'october 18 , 1953', 'cleveland browns', 'l 30 - 14', '33963'], ['5', 'october 25 , 1953', 'baltimor... |
kingco athletic conference | https://en.wikipedia.org/wiki/Kingco_Athletic_Conference | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-13759592-2.html.csv | aggregation | the total sum of enrollments among the five institutions participating in the kingco athletic conference was 6339 individuals . | {'scope': 'all', 'col': '5', 'type': 'sum', 'result': '6339', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'enrollment'], 'result': '6339', 'ind': 0, 'tostr': 'sum { all_rows ; enrollment }'}, '6339'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; enrollment } ; 6339 } = true', 'tointer': 'the sum of the enrollment record of all rows is 633... | round_eq { sum { all_rows ; enrollment } ; 6339 } = true | the sum of the enrollment record of all rows is 6339 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'enrollment_4': 4, '6339_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'enrollment_4': 'enrollment', '6339_5': '6339'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'enrollment_4': [0], '6339_5': [1]} | ['institution', 'location', 'founded', 'affiliation', 'enrollment', 'nickname'] | [['bellevue', 'bellevue', '1923', 'public ( bellevue sd )', '1327', 'wolverines'], ['interlake', 'bellevue', '1968', 'public ( bellevue sd )', '1341', 's saint'], ['juanita', 'kirkland', '1971', 'public ( lake washington sd )', '1010', 'rebels'], ['liberty', 'renton', '1977', 'public ( issaquah sd )', '1237', 'patriots... |
concrete canoe | https://en.wikipedia.org/wiki/Concrete_canoe | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2331549-1.html.csv | ordinal | the 2nd to last y ear for concrete canoe was when the host city was seattle , washington . | {'row': '19', 'col': '1', 'order': '2', 'col_other': '2', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'year', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; year ; 2 }'}, 'host city'], 'result': 'seattle , washington', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; year ; 2 } ; host city }'}, 'seat... | eq { hop { nth_argmax { all_rows ; year ; 2 } ; host city } ; seattle , washington } = true | select the row whose year record of all rows is 2nd maximum . the host city record of this row is seattle , washington . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'year_5': 5, '2_6': 6, 'host city_7': 7, 'seattle , washington_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'year_5': 'year', '2_6': '2', 'host city_7': 'host city', 'seattle , washington_8': 'seattle , washington'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'year_5': [0], '2_6': [0], 'host city_7': [1], 'seattle , washington_8': [2]} | ['year', 'host city', 'host school', 'champion', 'second place', 'third place'] | [['1988', 'east lansing , michigan', 'michigan state university', 'university of california , berkeley', 'university of new hampshire', 'university of akron'], ['1989', 'lubbock , texas', 'texas tech university', 'university of california , berkeley', 'michigan state university', 'university of new hampshire'], ['1990'... |
1972 - 73 philadelphia flyers season | https://en.wikipedia.org/wiki/1972%E2%80%9373_Philadelphia_Flyers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14294324-15.html.csv | majority | all of the players that were drafted in the 1972-73 philadelphia flyers ' season were from canada . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'canada', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'nationality', 'canada'], 'result': True, 'ind': 0, 'tointer': 'for the nationality records of all rows , most of them fuzzily match to canada .', 'tostr': 'most_eq { all_rows ; nationality ; canada } = true'} | most_eq { all_rows ; nationality ; canada } = true | for the nationality records of all rows , most of them fuzzily match to canada . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'nationality_3': 3, 'canada_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'nationality_3': 'nationality', 'canada_4': 'canada'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'nationality_3': [0], 'canada_4': [0]} | ['round', 'player', 'position', 'nationality', 'college / junior / club team ( league )'] | [['1', 'bill barber', 'left wing', 'canada', 'kitchener rangers ( oha )'], ['2', 'tom bladon', 'defense', 'canada', 'edmonton oil kings ( wchl )'], ['3', 'jim watson', 'defense', 'canada', 'calgary centennials ( wchl )'], ['4', 'al macadam', 'right wing', 'canada', 'charlottetown islanders ( mjhl )'], ['5', 'darryl fed... |
1991 - 92 segunda división | https://en.wikipedia.org/wiki/1991%E2%80%9392_Segunda_Divisi%C3%B3n | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12097374-2.html.csv | unique | ce sabadell fc was the only team in the 1991-92 segunda division that had a goal difference of -1 . | {'scope': 'all', 'row': '9', 'col': '10', 'col_other': '2', 'criterion': 'equal', 'value': '-1', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'goal difference', '-1'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose goal difference record is equal to -1 .', 'tostr': 'filter_eq { all_rows ; goal difference ; -1 }'}], 'result': True, 'ind': 1, 'tostr': 'on... | and { only { filter_eq { all_rows ; goal difference ; -1 } } ; eq { hop { filter_eq { all_rows ; goal difference ; -1 } ; club } ; ce sabadell fc } } = true | select the rows whose goal difference record is equal to -1 . there is only one such row in the table . the club record of this unqiue row is ce sabadell fc . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'goal difference_7': 7, '-1_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'club_9': 9, 'ce sabadell fc_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'goal difference_7': 'goal difference', '-1_8': '-1', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'club_9': 'club', 'ce sabadell fc_10': 'ce sabadell fc'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'goal difference_7': [0], '-1_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'club_9': [2], 'ce sabadell fc_10': [3]} | ['position', 'club', 'played', 'points', 'wins', 'draws', 'losses', 'goals for', 'goals against', 'goal difference'] | [['1', 'celta de vigo', '38', '53 + 15', '22', '9', '7', '61', '26', '+ 35'], ['2', 'rayo vallecano', '38', '48 + 10', '20', '8', '10', '52', '27', '+ 25'], ['3', 'ue figueres', '38', '47 + 9', '16', '15', '7', '43', '27', '+ 16'], ['4', 'real betis', '38', '46 + 8', '18', '10', '10', '54', '43', '+ 11'], ['5', 'ue lle... |
list of free multiplayer online games | https://en.wikipedia.org/wiki/List_of_free_multiplayer_online_games | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17493675-2.html.csv | majority | all of the free multiplayer online games are available on the windows operating system . | {'scope': 'all', 'col': '3', 'most_or_all': 'all', 'criterion': 'fuzzily_match', 'value': 'windows', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'required os', 'windows'], 'result': True, 'ind': 0, 'tointer': 'for the required os records of all rows , all of them fuzzily match to windows .', 'tostr': 'all_eq { all_rows ; required os ; windows } = true'} | all_eq { all_rows ; required os ; windows } = true | for the required os records of all rows , all of them fuzzily match to windows . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'required os_3': 3, 'windows_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'required os_3': 'required os', 'windows_4': 'windows'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'required os_3': [0], 'windows_4': [0]} | ['developer ( s )', 'release date', 'required os', 'genre', 'type'] | [['robot entertainment , gas powered games', 'august 16 , 2011', 'windows', 'mmorts', '3d'], ['ea games', '2009', 'windows', 'first - person shooter', '3d'], ['stunlock studios', '2011', 'windows', 'moba', '3d'], ['thq', '2010 - 2011', 'windows', 'real - time strategy', '3d'], ['novel , inc', '2011', 'windows', 'mmorpg... |
utah jazz all - time roster | https://en.wikipedia.org/wiki/Utah_Jazz_all-time_roster | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-11545282-4.html.csv | ordinal | john drew is the third newest member on the utah jazz all - time roster , joining in 1982 . | {'row': '7', 'col': '5', 'order': '3', 'col_other': '1', 'max_or_min': 'max_to_min', 'value_mentioned': 'yes', 'scope': 'all', 'subset': None} | {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'nth_max', 'args': ['all_rows', 'years for jazz', '3'], 'result': '1982 - 85', 'ind': 0, 'tostr': 'nth_max { all_rows ; years for jazz ; 3 }', 'tointer': 'the 3rd maximum years for jazz record of all rows is 1982 - 85 .'}, '1982 - 85'], 'result': True, 'ind': 1,... | and { eq { nth_max { all_rows ; years for jazz ; 3 } ; 1982 - 85 } ; eq { hop { nth_argmax { all_rows ; years for jazz ; 3 } ; player } ; john drew } } = true | the 3rd maximum years for jazz record of all rows is 1982 - 85 . the player record of the row with 3rd maximum years for jazz record is john drew . | 6 | 6 | {'and_5': 5, 'result_6': 6, 'eq_1': 1, 'nth_max_0': 0, 'all_rows_7': 7, 'years for jazz_8': 8, '3_9': 9, '1982 - 85_10': 10, 'str_eq_4': 4, 'str_hop_3': 3, 'nth_argmax_2': 2, 'all_rows_11': 11, 'years for jazz_12': 12, '3_13': 13, 'player_14': 14, 'john drew_15': 15} | {'and_5': 'and', 'result_6': 'true', 'eq_1': 'eq', 'nth_max_0': 'nth_max', 'all_rows_7': 'all_rows', 'years for jazz_8': 'years for jazz', '3_9': '3', '1982 - 85_10': '1982 - 85', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'nth_argmax_2': 'nth_argmax', 'all_rows_11': 'all_rows', 'years for jazz_12': 'years for jazz'... | {'and_5': [6], 'result_6': [], 'eq_1': [5], 'nth_max_0': [1], 'all_rows_7': [0], 'years for jazz_8': [0], '3_9': [0], '1982 - 85_10': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'nth_argmax_2': [3], 'all_rows_11': [2], 'years for jazz_12': [2], '3_13': [2], 'player_14': [3], 'john drew_15': [4]} | ['player', 'no', 'nationality', 'position', 'years for jazz', 'school / club team'] | [['adrian dantley', '4', 'united states', 'guard - forward', '1979 - 86', 'notre dame'], ['brad davis', '12', 'united states', 'guard', '1979 - 80', 'maryland'], ['darryl dawkins', '45', 'united states', 'center', '1987 - 88', 'maynard evans hs'], ['paul dawkins', '31', 'united states', 'guard', '1979 - 80', 'northern ... |
1973 ohio state buckeyes football team | https://en.wikipedia.org/wiki/1973_Ohio_State_Buckeyes_football_team | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17824926-1.html.csv | comparative | the ohio state buckeyes team had a game against iowa earlier than michigan . | {'row_1': '9', 'row_2': '10', 'col': '1', 'col_other': '2', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', 'iowa'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose opponent record fuzzily matches to iowa .', 'tostr': 'filter_eq { all_rows ; opponent ; iowa }'}, 'date'], 'result': None, 'ind': 2, 'tos... | less { hop { filter_eq { all_rows ; opponent ; iowa } ; date } ; hop { filter_eq { all_rows ; opponent ; 4 michigan } ; date } } = true | select the rows whose opponent record fuzzily matches to iowa . take the date record of this row . select the rows whose opponent record fuzzily matches to 4 michigan . take the date record of this row . the first record is less than the second record . | 5 | 5 | {'less_4': 4, 'result_5': 5, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'opponent_7': 7, 'iowa_8': 8, 'date_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'opponent_11': 11, '4 michigan_12': 12, 'date_13': 13} | {'less_4': 'less', 'result_5': 'true', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'opponent_7': 'opponent', 'iowa_8': 'iowa', 'date_9': 'date', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'opponent_11': 'opponent', '4 michigan_12': '4... | {'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'opponent_7': [0], 'iowa_8': [0], 'date_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'opponent_11': [1], '4 michigan_12': [1], 'date_13': [3]} | ['date', 'opponent', 'rank', 'site', 'result', 'attendance'] | [['september 15', 'minnesota', '3', 'ohio stadium columbus , oh', 'w56 - 7', '86005'], ['september 29', 'tcu', '3', 'ohio stadium columbus , oh', 'w37 - 3', '87439'], ['october 6', 'washington state', '1', 'ohio stadium columbus , oh', 'w27 - 3', '87425'], ['october 13', 'wisconsin', '1', 'camp randall stadium madison ... |
united states house of representatives elections , 1800 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1800 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2668401-12.html.csv | majority | the majority of the representatives elected from pennsylvania were from the democratic - republican party . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'democratic - republican', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'party', 'democratic - republican'], 'result': True, 'ind': 0, 'tointer': 'for the party records of all rows , most of them fuzzily match to democratic - republican .', 'tostr': 'most_eq { all_rows ; party ; democratic - republican } = true'} | most_eq { all_rows ; party ; democratic - republican } = true | for the party records of all rows , most of them fuzzily match to democratic - republican . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'party_3': 3, 'democratic - republican_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'party_3': 'party', 'democratic - republican_4': 'democratic - republican'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'party_3': [0], 'democratic - republican_4': [0]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['pennsylvania 1', 'robert waln', 'federalist', '1798 ( special )', 'retired democratic - republican gain', 'william jones ( dr ) 50.2 % francis gurney ( f ) 49.8 %'], ['pennsylvania 2', 'michael leib', 'democratic - republican', '1798', 're - elected', 'michael leib ( dr ) 77.8 % john lardner ( f ) 22.2 %'], ['pennsy... |
2005 - 06 u.s. città di palermo season | https://en.wikipedia.org/wiki/2005%E2%80%9306_U.S._Citt%C3%A0_di_Palermo_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11361788-3.html.csv | ordinal | the 1st round - 1st leg of the 2005 - 06 u.s. città di palermo season had the 4th highest attendance . | {'row': '1', 'col': '6', 'order': '4', 'col_other': '2', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'attendance', '4'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; attendance ; 4 }'}, 'round'], 'result': '1st round - 1st leg', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; attendance ; 4 } ; round }... | eq { hop { nth_argmax { all_rows ; attendance ; 4 } ; round } ; 1st round - 1st leg } = true | select the row whose attendance record of all rows is 4th maximum . the round record of this row is 1st round - 1st leg . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'attendance_5': 5, '4_6': 6, 'round_7': 7, '1st round - 1st leg_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'attendance_5': 'attendance', '4_6': '4', 'round_7': 'round', '1st round - 1st leg_8': '1st round - 1st leg'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'attendance_5': [0], '4_6': [0], 'round_7': [1], '1st round - 1st leg_8': [2]} | ['date and time', 'round', 'opponent', 'venue', 'result', 'attendance'] | [['september 15 , 2005 - 20.30', '1st round - 1st leg', 'anorthosis famagusta', 'home', 'won 2 - 1', '13047'], ['september 29 , 2005 - 17.00', '1st round - 2nd leg', 'anorthosis famagusta', 'away', 'won 4 - 0', '12000'], ['october 20 , 2005 - 17.00', 'group stage - group b', 'maccabi petah tikva', 'away', 'won 2 - 1', ... |
1989 toronto blue jays season | https://en.wikipedia.org/wiki/1989_Toronto_Blue_Jays_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12207158-9.html.csv | aggregation | the 1989 toronto blue jays season had an average of about 49,849.4 attendees per game . | {'scope': 'all', 'col': '5', 'type': 'average', 'result': '49849.4', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'attendance'], 'result': '49849.4', 'ind': 0, 'tostr': 'avg { all_rows ; attendance }'}, '49849.4'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; attendance } ; 49849.4 } = true', 'tointer': 'the average of the attendance record of al... | round_eq { avg { all_rows ; attendance } ; 49849.4 } = true | the average of the attendance record of all rows is 49849.4 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'attendance_4': 4, '49849.4_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'attendance_4': 'attendance', '49849.4_5': '49849.4'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'attendance_4': [0], '49849.4_5': [1]} | ['date', 'opponent', 'score', 'loss', 'attendance', 'series'] | [['october 3', 'athletics', '7 - 3', 'stieb ( 0 - 1 )', '49435', '0 - 1'], ['october 4', 'athletics', '6 - 3', 'stottlemyre ( 0 - 1 )', '49444', '0 - 2'], ['october 6', 'athletics', '7 - 3', 'davis ( 0 - 1 )', '50268', '1 - 2'], ['october 7', 'athletics', '6 - 5', 'flanagan ( 0 - 1 )', '50076', '1 - 3'], ['october 8', ... |
2009 atp world tour masters 1000 | https://en.wikipedia.org/wiki/2009_ATP_World_Tour_Masters_1000 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17057363-1.html.csv | superlative | cincinnati masters is the first atp world tour masters 1000 tournament that took place in the united states . | {'scope': 'subset', 'col_superlative': '5', 'row_superlative': '7', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '1,2', 'subset': {'col': '2', 'criterion': 'equal', 'value': 'united states'}} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmin', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'united states'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; country ; united states }', 'tointer': 'select the rows whose country record fuzzily matches to unit... | eq { hop { argmin { filter_eq { all_rows ; country ; united states } ; began } ; tournament } ; cincinnati masters } = true | select the rows whose country record fuzzily matches to united states . select the row whose began record of these rows is minimum . the tournament record of this row is cincinnati masters . | 4 | 4 | {'str_eq_3': 3, 'result_4': 4, 'str_hop_2': 2, 'argmin_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'country_6': 6, 'united states_7': 7, 'began_8': 8, 'tournament_9': 9, 'cincinnati masters_10': 10} | {'str_eq_3': 'str_eq', 'result_4': 'true', 'str_hop_2': 'str_hop', 'argmin_1': 'argmin', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'country_6': 'country', 'united states_7': 'united states', 'began_8': 'began', 'tournament_9': 'tournament', 'cincinnati masters_10': 'cincinnati masters'} | {'str_eq_3': [4], 'result_4': [], 'str_hop_2': [3], 'argmin_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'country_6': [0], 'united states_7': [0], 'began_8': [1], 'tournament_9': [2], 'cincinnati masters_10': [3]} | ['tournament', 'country', 'location', 'current venue', 'began', 'court surface'] | [['indian wells masters', 'united states', 'indian wells', 'indian wells tennis garden', '1987', 'hard'], ['miami masters', 'united states', 'miami', 'tennis center at crandon park', '1987', 'hard'], ['monte carlo masters', 'monaco', 'roquebrune - cap - martin , france', 'monte carlo country club', '1897', 'clay'], ['r... |
portuguese legislative election , 2005 | https://en.wikipedia.org/wiki/Portuguese_legislative_election%2C_2005 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1463383-1.html.csv | majority | the majority of polls in 2005 showed at least 42 % support for the socialist party . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'greater_than_eq', 'value': '42 %', 'subset': None} | {'func': 'most_greater_eq', 'args': ['all_rows', 'socialist', '42 %'], 'result': True, 'ind': 0, 'tointer': 'for the socialist records of all rows , most of them are greater than or equal to 42 % .', 'tostr': 'most_greater_eq { all_rows ; socialist ; 42 % } = true'} | most_greater_eq { all_rows ; socialist ; 42 % } = true | for the socialist records of all rows , most of them are greater than or equal to 42 % . | 1 | 1 | {'most_greater_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'socialist_3': 3, '42%_4': 4} | {'most_greater_eq_0': 'most_greater_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'socialist_3': 'socialist', '42%_4': '42 %'} | {'most_greater_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'socialist_3': [0], '42%_4': [0]} | ['date released', 'polling institute', 'socialist', 'social democratic', 'peoples party', 'green - communist', 'left bloc', 'lead'] | [['february 20 , 2005', 'election results', '45.0 % 121 seats', '28.8 % 75 seats', '7.2 % 12 seats', '7.5 % 14 seats', '6.4 % 8 seats', '16.2 %'], ['february 18 , 2005', 'aximage', '46.8 %', '29.6 %', '7.3 %', '7.0 %', '5.5 %', '17.2 %'], ['february 18 , 2005', 'marktest', '46.0 %', '26.8 %', '7.5 %', '8.9 %', '7.7 %',... |
mack hellings | https://en.wikipedia.org/wiki/Mack_Hellings | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1252130-1.html.csv | aggregation | mack hellings drove a total number of 522 laps in his career . | {'scope': 'all', 'col': '6', 'type': 'sum', 'result': '522', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'laps'], 'result': '522', 'ind': 0, 'tostr': 'sum { all_rows ; laps }'}, '522'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; laps } ; 522 } = true', 'tointer': 'the sum of the laps record of all rows is 522 .'} | round_eq { sum { all_rows ; laps } ; 522 } = true | the sum of the laps record of all rows is 522 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'laps_4': 4, '522_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'laps_4': 'laps', '522_5': '522'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'laps_4': [0], '522_5': [1]} | ['year', 'start', 'qual', 'rank', 'finish', 'laps'] | [['1948', '21', '127.968', '6', '5', '200'], ['1949', '14', '128.260', '11', '16', '172'], ['1950', '26', '130.687', '20', '13', '132'], ['1951', '23', '132.925', '22', '31', '18']] |
the sunday night project | https://en.wikipedia.org/wiki/The_Sunday_Night_Project | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1590967-2.html.csv | majority | all of the episodes aired in the year 2006 . | {'scope': 'all', 'col': '2', 'most_or_all': 'all', 'criterion': 'fuzzily_match', 'value': '2006', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'air date', '2006'], 'result': True, 'ind': 0, 'tointer': 'for the air date records of all rows , all of them fuzzily match to 2006 .', 'tostr': 'all_eq { all_rows ; air date ; 2006 } = true'} | all_eq { all_rows ; air date ; 2006 } = true | for the air date records of all rows , all of them fuzzily match to 2006 . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'air date_3': 3, '2006_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'air date_3': 'air date', '2006_4': '2006'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'air date_3': [0], '2006_4': [0]} | ['episode number', 'air date', 'guest host', 'musical guest ( song performed )', 'who knows the most about the guest host panelists'] | [['1', '6 january 2006', 'billie piper', 'texas ( sleep )', 'jade goody and kenzie'], ['2', '13 january 2006', 'lorraine kelly', 'editors ( munich )', 'myleene klass and phil tufnell'], ['3', '20 january 2006', 'christian slater', "the kooks ( you do n't love me )", 'lady isabella hervey and fearne cotton'], ['4', '27 ... |
acc - big ten challenge | https://en.wikipedia.org/wiki/ACC%E2%80%93Big_Ten_Challenge | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1672976-1.html.csv | count | four teams in the acc - big ten challenge have recorded zero away losses . | {'scope': 'all', 'criterion': 'equal', 'value': '0', 'result': '4', 'col': '7', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'away losses', '0'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose away losses record is equal to 0 .', 'tostr': 'filter_eq { all_rows ; away losses ; 0 }'}], 'result': '4', 'ind': 1, 'tostr': 'count { filter_eq ... | eq { count { filter_eq { all_rows ; away losses ; 0 } } ; 4 } = true | select the rows whose away losses record is equal to 0 . the number of such rows is 4 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_eq_0': 0, 'all_rows_4': 4, 'away losses_5': 5, '0_6': 6, '4_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'away losses_5': 'away losses', '0_6': '0', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'away losses_5': [0], '0_6': [0], '4_7': [2]} | ['institution', 'wins', 'loss', 'home wins', 'home losses', 'away wins', 'away losses', 'neutral wins', 'neutral losses'] | [['boston college eagles', '6', '1', '3', '1', '3', '0', '0', '0'], ['clemson tigers', '9', '5', '4', '3', '5', '2', '0', '0'], ['duke blue devils', '12', '2', '5', '0', '3', '2', '4', '0'], ['florida state seminoles', '6', '8', '4', '3', '2', '5', '0', '0'], ['georgia tech yellow jackets', '4', '9', '3', '2', '1', '6'... |
1959 portuguese grand prix | https://en.wikipedia.org/wiki/1959_Portuguese_Grand_Prix | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1122212-1.html.csv | majority | the majority of drivers were at least 2 laps behind the leader at the end of the 1959 portuguese grand prix . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'greater_than_eq', 'value': '2', 'subset': None} | {'func': 'most_greater_eq', 'args': ['all_rows', 'time / retired', '2'], 'result': True, 'ind': 0, 'tointer': 'for the time / retired records of all rows , most of them are greater than or equal to 2 .', 'tostr': 'most_greater_eq { all_rows ; time / retired ; 2 } = true'} | most_greater_eq { all_rows ; time / retired ; 2 } = true | for the time / retired records of all rows , most of them are greater than or equal to 2 . | 1 | 1 | {'most_greater_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'time / retired_3': 3, '2_4': 4} | {'most_greater_eq_0': 'most_greater_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'time / retired_3': 'time / retired', '2_4': '2'} | {'most_greater_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'time / retired_3': [0], '2_4': [0]} | ['driver', 'constructor', 'laps', 'time / retired', 'grid'] | [['stirling moss', 'cooper - climax', '62', '2:11:55.41', '1'], ['masten gregory', 'cooper - climax', '61', '+ 1 lap', '3'], ['dan gurney', 'ferrari', '61', '+ 1 lap', '6'], ['maurice trintignant', 'cooper - climax', '60', '+ 2 laps', '4'], ['harry schell', 'brm', '59', '+ 3 laps', '9'], ['roy salvadori', 'aston martin... |
southern athletic conference of indiana | https://en.wikipedia.org/wiki/Southern_Athletic_Conference_of_Indiana | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18956862-1.html.csv | aggregation | on average , teams joined the southern athletic conference of indiana around 1977 . | {'scope': 'all', 'col': '7', 'type': 'average', 'result': '1977', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'year joined'], 'result': '1977', 'ind': 0, 'tostr': 'avg { all_rows ; year joined }'}, '1977'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; year joined } ; 1977 } = true', 'tointer': 'the average of the year joined record of all row... | round_eq { avg { all_rows ; year joined } ; 1977 } = true | the average of the year joined record of all rows is 1977 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'year joined_4': 4, '1977_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'year joined_4': 'year joined', '1977_5': '1977'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'year joined_4': [0], '1977_5': [1]} | ['school', 'location', 'mascot', 'county', 'enrollment', 'ihsaa class', 'year joined', 'previous conference'] | [['borden', 'borden', 'braves', '228', 'a', '10 clark', '1974', 'lost river'], ['crothersville', 'crothersville', 'tigers', '180', 'a', '36 jackson', '1974', 'mid - hoosier'], ['henryville', 'henryville', 'hornets', '347', 'aa', '10 clark', '1977', 'lost river'], ['lanesville', 'lanesville', 'eagles', '237', 'a', '31 h... |
2003 lexmark indy 300 | https://en.wikipedia.org/wiki/2003_Lexmark_Indy_300 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15080993-2.html.csv | majority | most of the drivers during the 2003 lexmark indy 300 did 47 laps . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': '47', 'subset': None} | {'func': 'most_eq', 'args': ['all_rows', 'laps', '47'], 'result': True, 'ind': 0, 'tointer': 'for the laps records of all rows , most of them are equal to 47 .', 'tostr': 'most_eq { all_rows ; laps ; 47 } = true'} | most_eq { all_rows ; laps ; 47 } = true | for the laps records of all rows , most of them are equal to 47 . | 1 | 1 | {'most_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'laps_3': 3, '47_4': 4} | {'most_eq_0': 'most_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'laps_3': 'laps', '47_4': '47'} | {'most_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'laps_3': [0], '47_4': [0]} | ['driver', 'team', 'laps', 'time / retired', 'grid', 'points'] | [['ryan hunter - reay', 'american spirit team johansson', '47', '1:49:02.803', '12', '20'], ['darren manning', 'walker racing', '47', '+ 1.546 secs', '14', '16'], ['jimmy vasser', 'american spirit team johansson', '47', '+ 3.792 secs', '15', '14'], ['michel jourdain , jr', 'team rahal', '47', '+ 5.315 secs', '9', '12']... |
1981 seattle seahawks season | https://en.wikipedia.org/wiki/1981_Seattle_Seahawks_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-13258972-2.html.csv | aggregation | the seattle seahawks scored an average of 21.8 points over the course of 7 home games during the 1981 season . | {'scope': 'subset', 'col': '4', 'type': 'average', 'result': '21.8', 'subset': {'col': '5', 'criterion': 'equal', 'value': 'kingdome'}} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'game site', 'kingdome'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; game site ; kingdome }', 'tointer': 'select the rows whose game site record fuzzily matches to kingdome .'}, 'result'], 'result': '21... | round_eq { avg { filter_eq { all_rows ; game site ; kingdome } ; result } ; 21.8 } = true | select the rows whose game site record fuzzily matches to kingdome . the average of the result record of these rows is 21.8 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'avg_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'game site_5': 5, 'kingdome_6': 6, 'result_7': 7, '21.8_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'avg_1': 'avg', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'game site_5': 'game site', 'kingdome_6': 'kingdome', 'result_7': 'result', '21.8_8': '21.8'} | {'eq_2': [3], 'result_3': [], 'avg_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'game site_5': [0], 'kingdome_6': [0], 'result_7': [1], '21.8_8': [2]} | ['week', 'date', 'opponent', 'result', 'game site', 'record', 'attendance'] | [['1', 'september 6 , 1981', 'cincinnati bengals', 'l 21 - 27', 'riverfront stadium', '0 - 1', '41177'], ['2', 'september 13 , 1981', 'denver broncos', 'w 13 - 10', 'kingdome', '1 - 1', '58513'], ['3', 'september 20 , 1981', 'oakland raiders', 'l 10 - 20', 'oakland - alameda county coliseum', '1 - 2', '45725'], ['4', '... |
orlando magic all - time roster | https://en.wikipedia.org/wiki/Orlando_Magic_all-time_roster | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-15621965-2.html.csv | count | two of the players had previously played for kentucky . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'kentucky', 'result': '2', 'col': '6', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'school / club team', 'kentucky'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose school / club team record fuzzily matches to kentucky .', 'tostr': 'filter_eq { all_rows ; school / club team ; kentucky }'}], ... | eq { count { filter_eq { all_rows ; school / club team ; kentucky } } ; 2 } = true | select the rows whose school / club team record fuzzily matches to kentucky . the number of such rows is 2 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'school / club team_5': 5, 'kentucky_6': 6, '2_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'school / club team_5': 'school / club team', 'kentucky_6': 'kentucky', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'school / club team_5': [0], 'kentucky_6': [0], '2_7': [2]} | ['player', 'no', 'nationality', 'position', 'years in orlando', 'school / club team'] | [['matt barnes', '22', 'united states', 'guard - forward', '2009 - 2010', 'ucla'], ['andre barrett', '11', 'united states', 'guard', '2005', 'seton hall'], ['brandon bass', '30', 'united states', 'forward', '2009 - 2011', 'louisiana state'], ['tony battie', '4', 'united states', 'forward - center', '2004 - 2009', 'texa... |
list of tvb series ( 2007 ) | https://en.wikipedia.org/wiki/List_of_TVB_series_%282007%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-11173827-1.html.csv | majority | the majority of tvb series in 2007 drew over 2 million hk viewers . | {'scope': 'all', 'col': '8', 'most_or_all': 'most', 'criterion': 'greater_than', 'value': '2', 'subset': None} | {'func': 'most_greater', 'args': ['all_rows', 'hk viewers', '2'], 'result': True, 'ind': 0, 'tointer': 'for the hk viewers records of all rows , most of them are greater than 2 .', 'tostr': 'most_greater { all_rows ; hk viewers ; 2 } = true'} | most_greater { all_rows ; hk viewers ; 2 } = true | for the hk viewers records of all rows , most of them are greater than 2 . | 1 | 1 | {'most_greater_0': 0, 'result_1': 1, 'all_rows_2': 2, 'hk viewers_3': 3, '2_4': 4} | {'most_greater_0': 'most_greater', 'result_1': 'true', 'all_rows_2': 'all_rows', 'hk viewers_3': 'hk viewers', '2_4': '2'} | {'most_greater_0': [1], 'result_1': [], 'all_rows_2': [0], 'hk viewers_3': [0], '2_4': [0]} | ['rank', 'english title', 'chinese title', 'average', 'peak', 'premiere', 'finale', 'hk viewers'] | [['1', 'the family link', '師奶兵團', '33', '42', '31', '33', '2.12 million'], ['2', 'fathers and sons', '爸爸閉翳', '32', '40', '31', '37', '2.11 million'], ['3', 'heart of greed', '溏心風暴', '32', '48', '29', '40', '2.08 million'], ['4', 'ten brothers', '十兄弟', '32', '39', '29', '36', '2.05 million'], ['5', 'on the first beat', ... |
flavio cipolla | https://en.wikipedia.org/wiki/Flavio_Cipolla | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16474033-9.html.csv | count | flavio cipolla played a total of three tennis tournaments on a hard surface . | {'scope': 'all', 'criterion': 'equal', 'value': 'hard', 'result': '3', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'surface', 'hard'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose surface record fuzzily matches to hard .', 'tostr': 'filter_eq { all_rows ; surface ; hard }'}], 'result': '3', 'ind': 1, 'tostr': 'count { fi... | eq { count { filter_eq { all_rows ; surface ; hard } } ; 3 } = true | select the rows whose surface record fuzzily matches to hard . the number of such rows is 3 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'surface_5': 5, 'hard_6': 6, '3_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'surface_5': 'surface', 'hard_6': 'hard', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'surface_5': [0], 'hard_6': [0], '3_7': [2]} | ['date', 'tournament', 'surface', 'opponent', 'score'] | [['29 august 2005', 'freudenstadt , germany', 'clay', 'sergio roitman', '7 - 5 , 6 - 4'], ['6 september 2005', 'genoa , italy', 'clay', 'potito starace', '6 - 3 , 7 - 6 ( 7 - 3 )'], ['3 april 2006', 'monza , italy', 'clay', 'nicolas devilder', '6 - 2 , 7 - 5'], ['28 july 2008', 'tampere , finland', 'clay', 'mathieu mon... |
1988 los angeles rams season | https://en.wikipedia.org/wiki/1988_Los_Angeles_Rams_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11157007-1.html.csv | ordinal | in the 1988 los angeles rams season , the 3rd highest crowd was on november 27 , 1988 . | {'row': '13', 'col': '5', 'order': '3', 'col_other': '2', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'attendance', '3'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; attendance ; 3 }'}, 'date'], 'result': 'november 27 , 1988', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; attendance ; 3 } ; date }'},... | eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; date } ; november 27 , 1988 } = true | select the row whose attendance record of all rows is 3rd maximum . the date record of this row is november 27 , 1988 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'attendance_5': 5, '3_6': 6, 'date_7': 7, 'november 27 , 1988_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'attendance_5': 'attendance', '3_6': '3', 'date_7': 'date', 'november 27 , 1988_8': 'november 27 , 1988'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'attendance_5': [0], '3_6': [0], 'date_7': [1], 'november 27 , 1988_8': [2]} | ['week', 'date', 'opponent', 'result', 'attendance'] | [['1', 'september 4 , 1988', 'green bay packers', 'w 34 - 7', '53769'], ['2', 'september 11 , 1988', 'detroit lions', 'w 17 - 10', '46262'], ['3', 'september 18 , 1988', 'los angeles raiders', 'w 22 - 17', '84870'], ['4', 'september 25 , 1988', 'new york giants', 'w 45 - 31', '75617'], ['5', 'october 2 , 1988', 'phoeni... |
2003 lexmark indy 300 | https://en.wikipedia.org/wiki/2003_Lexmark_Indy_300 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15080993-2.html.csv | unique | tiago monteiro id the only driver having mechanical issues during the 2003 lexmark indy 300 . | {'scope': 'all', 'row': '18', 'col': '4', 'col_other': '1', 'criterion': 'equal', 'value': 'mechanical', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'time / retired', 'mechanical'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose time / retired record fuzzily matches to mechanical .', 'tostr': 'filter_eq { all_rows ; time / retired ; mechanical }'}], 'resul... | and { only { filter_eq { all_rows ; time / retired ; mechanical } } ; eq { hop { filter_eq { all_rows ; time / retired ; mechanical } ; driver } ; tiago monteiro } } = true | select the rows whose time / retired record fuzzily matches to mechanical . there is only one such row in the table . the driver record of this unqiue row is tiago monteiro . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'time / retired_7': 7, 'mechanical_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'driver_9': 9, 'tiago monteiro_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'time / retired_7': 'time / retired', 'mechanical_8': 'mechanical', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'driver_9': 'driver', 'tiago monteiro_10': 'tiago monteiro'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'time / retired_7': [0], 'mechanical_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'driver_9': [2], 'tiago monteiro_10': [3]} | ['driver', 'team', 'laps', 'time / retired', 'grid', 'points'] | [['ryan hunter - reay', 'american spirit team johansson', '47', '1:49:02.803', '12', '20'], ['darren manning', 'walker racing', '47', '+ 1.546 secs', '14', '16'], ['jimmy vasser', 'american spirit team johansson', '47', '+ 3.792 secs', '15', '14'], ['michel jourdain , jr', 'team rahal', '47', '+ 5.315 secs', '9', '12']... |
list of kyle xy episodes | https://en.wikipedia.org/wiki/List_of_Kyle_XY_episodes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-11075747-4.html.csv | comparative | guy norman bee directed an episode of kyle xy before james head did . | {'row_1': '6', 'row_2': '7', 'col': '2', 'col_other': '4', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'directed by', 'guy norman bee'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose directed by record fuzzily matches to guy norman bee .', 'tostr': 'filter_eq { all_rows ; directed by ; guy norman bee }'}, ... | less { hop { filter_eq { all_rows ; directed by ; guy norman bee } ; episode } ; hop { filter_eq { all_rows ; directed by ; james head } ; episode } } = true | select the rows whose directed by record fuzzily matches to guy norman bee . take the episode record of this row . select the rows whose directed by record fuzzily matches to james head . take the episode record of this row . the first record is less than the second record . | 5 | 5 | {'less_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'directed by_7': 7, 'guy norman bee_8': 8, 'episode_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'directed by_11': 11, 'james head_12': 12, 'episode_13': 13} | {'less_4': 'less', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'directed by_7': 'directed by', 'guy norman bee_8': 'guy norman bee', 'episode_9': 'episode', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'directed by_1... | {'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'directed by_7': [0], 'guy norman bee_8': [0], 'episode_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'directed by_11': [1], 'james head_12': [1], 'episode_13': [3]} | ['series', 'episode', 'title', 'directed by', 'written by', 'original air date'] | [['34', '1', 'it happened one night', 'chris grismer', 'eric tuchman', 'january 12 , 2009'], ['35', '2', 'psychic friend', 'michael robison', 'julie plec', 'january 19 , 2009'], ['36', '3', 'electric kiss', 'chris grismer', 'gayle abrams', 'january 26 , 2009'], ['37', '4', 'in the company of men', 'guy norman bee', 'da... |
1991 national league championship series | https://en.wikipedia.org/wiki/1991_National_League_Championship_Series | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1742998-1.html.csv | aggregation | the average attendance at the 1991 national league championship games was just under 52,800 . | {'scope': 'all', 'col': '5', 'type': 'average', 'result': '52800', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'attendance'], 'result': '52800', 'ind': 0, 'tostr': 'avg { all_rows ; attendance }'}, '52800'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; attendance } ; 52800 } = true', 'tointer': 'the average of the attendance record of all rows... | round_eq { avg { all_rows ; attendance } ; 52800 } = true | the average of the attendance record of all rows is 52800 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'attendance_4': 4, '52800_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'attendance_4': 'attendance', '52800_5': '52800'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'attendance_4': [0], '52800_5': [1]} | ['game', 'date', 'location', 'time', 'attendance'] | [['1', 'october 9', 'three rivers stadium', '2:51', '57347'], ['2', 'october 10', 'three rivers stadium', '2:46', '57533'], ['3', 'october 12', 'atlanta - fulton county stadium', '3:21', '50905'], ['4', 'october 13', 'atlanta - fulton county stadium', '3:43', '51109'], ['5', 'october 14', 'atlanta - fulton county stadi... |
tomasz sikora | https://en.wikipedia.org/wiki/Tomasz_Sikora | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1269400-2.html.csv | ordinal | tomasz sikora 's second best finish in the individual event was in 2004 . | {'row': '10', 'col': '2', 'order': '2', 'col_other': '1', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'individual', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; individual ; 2 }'}, 'event'], 'result': '2004 oberhof', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; individual ; 2 } ; event }'}, '20... | eq { hop { nth_argmin { all_rows ; individual ; 2 } ; event } ; 2004 oberhof } = true | select the row whose individual record of all rows is 2nd minimum . the event record of this row is 2004 oberhof . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'individual_5': 5, '2_6': 6, 'event_7': 7, '2004 oberhof_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmin_0': 'nth_argmin', 'all_rows_4': 'all_rows', 'individual_5': 'individual', '2_6': '2', 'event_7': 'event', '2004 oberhof_8': '2004 oberhof'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'individual_5': [0], '2_6': [0], 'event_7': [1], '2004 oberhof_8': [2]} | ['event', 'individual', 'sprint', 'pursuit', 'mass start', 'relay'] | [['1995 antholz', '1st', '29th', '-', '-', '7th'], ['1996 ruhpolding', '6th', '15th', '-', '-', '7th'], ['1997 brezno - osrblie', '28th', '17th', '21st', '-', '6th'], ['1998 pokljuka', '-', '-', '14th', '-', '-'], ['1999 kontiolahti', '14th', '59th', '-', '-', '14th'], ['2000 oslo', '32nd', '21st', '47th', '18th', '11t... |
1940 vfl season | https://en.wikipedia.org/wiki/1940_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10807253-8.html.csv | aggregation | the vfl crowd size on 15 june 1940 averaged 12,600 across five venues . | {'scope': 'subset', 'col': '6', 'type': 'average', 'result': '12,600', 'subset': {'col': '7', 'criterion': 'equal', 'value': '15 june 1940'}} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', '15 june 1940'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; date ; 15 june 1940 }', 'tointer': 'select the rows whose date record fuzzily matches to 15 june 1940 .'}, 'crowd'], 'result': '12,600... | round_eq { avg { filter_eq { all_rows ; date ; 15 june 1940 } ; crowd } ; 12,600 } = true | select the rows whose date record fuzzily matches to 15 june 1940 . the average of the crowd record of these rows is 12,600 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'avg_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'date_5': 5, '15 june 1940_6': 6, 'crowd_7': 7, '12,600_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'avg_1': 'avg', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'date_5': 'date', '15 june 1940_6': '15 june 1940', 'crowd_7': 'crowd', '12,600_8': '12,600'} | {'eq_2': [3], 'result_3': [], 'avg_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'date_5': [0], '15 june 1940_6': [0], 'crowd_7': [1], '12,600_8': [2]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['collingwood', '6.13 ( 49 )', 'richmond', '10.15 ( 75 )', 'victoria park', '20000', '15 june 1940'], ['south melbourne', '12.9 ( 81 )', 'st kilda', '10.16 ( 76 )', 'lake oval', '12000', '15 june 1940'], ['north melbourne', '8.15 ( 63 )', 'geelong', '13.20 ( 98 )', 'arden street oval', '5000', '15 june 1940'], ['hawth... |
list of the busiest airports in the united states | https://en.wikipedia.org/wiki/List_of_the_busiest_airports_in_the_United_States | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-18047346-5.html.csv | ordinal | the second highest number of people go through the airport that is located in alaska . | {'row': '2', 'col': '5', 'order': '2', 'col_other': '3', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'tonnes', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; tonnes ; 2 }'}, 'location'], 'result': 'anchorage , alaska', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; tonnes ; 2 } ; location }'}, 'an... | eq { hop { nth_argmax { all_rows ; tonnes ; 2 } ; location } ; anchorage , alaska } = true | select the row whose tonnes record of all rows is 2nd maximum . the location record of this row is anchorage , alaska . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'tonnes_5': 5, '2_6': 6, 'location_7': 7, 'anchorage , alaska_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'tonnes_5': 'tonnes', '2_6': '2', 'location_7': 'location', 'anchorage , alaska_8': 'anchorage , alaska'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'tonnes_5': [0], '2_6': [0], 'location_7': [1], 'anchorage , alaska_8': [2]} | ['rank', 'airport name', 'location', 'iata code', 'tonnes', '% chg 2010 / 11'] | [['1', 'memphis international airport', 'memphis , tennessee', 'mem', '3916410', '0 0.0 %'], ['2', 'ted stevens anchorage international airport', 'anchorage , alaska', 'anc', '2543105', '0 3.9 %'], ['3', 'louisville international airport', 'louisville , kentucky', 'sdf', '2188422', '0 1.0 %'], ['4', 'miami internationa... |
1975 dallas cowboys season | https://en.wikipedia.org/wiki/1975_Dallas_Cowboys_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16767061-2.html.csv | comparative | more people attended the game on november 10 , 1975 than attended on december 7 , 1975 . | {'row_1': '8', 'row_2': '12', 'col': '5', 'col_other': '2', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', 'november 10 , 1975'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose date record fuzzily matches to november 10 , 1975 .', 'tostr': 'filter_eq { all_rows ; date ; november 10 , 1975 }'}, 'atten... | greater { hop { filter_eq { all_rows ; date ; november 10 , 1975 } ; attendance } ; hop { filter_eq { all_rows ; date ; december 7 , 1975 } ; attendance } } = true | select the rows whose date record fuzzily matches to november 10 , 1975 . take the attendance record of this row . select the rows whose date record fuzzily matches to december 7 , 1975 . take the attendance record of this row . the first record is greater than the second record . | 5 | 5 | {'greater_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'date_7': 7, 'november 10 , 1975_8': 8, 'attendance_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'date_11': 11, 'december 7 , 1975_12': 12, 'attendance_13': 13} | {'greater_4': 'greater', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'date_7': 'date', 'november 10 , 1975_8': 'november 10 , 1975', 'attendance_9': 'attendance', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'date_11... | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'date_7': [0], 'november 10 , 1975_8': [0], 'attendance_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'date_11': [1], 'december 7 , 1975_12': [1], 'attendance_13': [3]} | ['week', 'date', 'opponent', 'result', 'attendance'] | [['1', 'september 21 , 1975', 'los angeles rams', 'w 18 - 7', '49091'], ['2', 'september 28 , 1975', 'st louis cardinals', 'w 37 - 31', '52417'], ['3', 'october 6 , 1975', 'detroit lions', 'w 36 - 10', '79384'], ['4', 'october 12 , 1975', 'new york giants', 'w 13 - 7', '56511'], ['5', 'october 19 , 1975', 'green bay pa... |
1973 uefa cup final | https://en.wikipedia.org/wiki/1973_UEFA_Cup_Final | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15755354-2.html.csv | unique | fc koln was the only opposition team that did not score any goals . | {'scope': 'all', 'row': '3', 'col': '5', 'col_other': '2', 'criterion': 'fuzzily_match', 'value': '0', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'aggregate score', '0'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose aggregate score record fuzzily matches to 0 .', 'tostr': 'filter_eq { all_rows ; aggregate score ; 0 }'}], 'result': True, 'ind': 1, 'tos... | and { only { filter_eq { all_rows ; aggregate score ; 0 } } ; eq { hop { filter_eq { all_rows ; aggregate score ; 0 } ; opposition } ; fc köln } } = true | select the rows whose aggregate score record fuzzily matches to 0 . there is only one such row in the table . the opposition record of this unqiue row is fc köln . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'aggregate score_7': 7, '0_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'opposition_9': 9, 'fc köln_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'aggregate score_7': 'aggregate score', '0_8': '0', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'opposition_9': 'opposition', 'fc köln_10': 'fc köln'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'aggregate score_7': [0], '0_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'opposition_9': [2], 'fc köln_10': [3]} | ['round', 'opposition', 'first leg', 'second leg', 'aggregate score'] | [['1st', 'aberdeen', '3 - 2 ( a )', '6 - 3 ( h )', '9 - 5'], ['2nd', 'hvidovre', '3 - 0 ( h )', '3 - 1 ( a )', '6 - 1'], ['3rd', 'fc köln', '0 - 0 ( a )', '5 - 0 ( h )', '5 - 0'], ['quarter - final', 'kaiserslautern', '2 - 1 ( a )', '7 - 1 ( h )', '9 - 2'], ['semi - final', 'twente', '3 - 0 ( h )', '2 - 1 ( a )', '5 - ... |
face up ( album ) | https://en.wikipedia.org/wiki/Face_Up_%28album%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15845800-3.html.csv | count | three of the cd releases occurred during june of 2001 . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'june 2001', 'result': '3', 'col': '2', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', 'june 2001'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose date record fuzzily matches to june 2001 .', 'tostr': 'filter_eq { all_rows ; date ; june 2001 }'}], 'result': '3', 'ind': 1, 'tostr': 'coun... | eq { count { filter_eq { all_rows ; date ; june 2001 } } ; 3 } = true | select the rows whose date record fuzzily matches to june 2001 . the number of such rows is 3 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'date_5': 5, 'june 2001_6': 6, '3_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'date_5': 'date', 'june 2001_6': 'june 2001', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'date_5': [0], 'june 2001_6': [0], '3_7': [2]} | ['region', 'date', 'label', 'format', 'catalog'] | [['japan', '20 june 2001', 'arista', 'cd', 'bvca - 21087'], ['europe', '25 june 2001', 'arista', 'cd', '74321 86632 2'], ['united kingdom', '25 june 2001', 'arista', 'cd', '74321 86346 2'], ['united kingdom', '2 june 2003', 'arista', 'remastered cd', '82876 54377 2'], ['europe', '2 august 2004', 'arista', 'remastered c... |
miracle ( celine dion album ) | https://en.wikipedia.org/wiki/Miracle_%28Celine_Dion_album%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1097545-4.html.csv | count | the album was released eight times in october of 2004 . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'october', 'result': '8', 'col': '2', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', 'october'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose date record fuzzily matches to october .', 'tostr': 'filter_eq { all_rows ; date ; october }'}], 'result': '8', 'ind': 1, 'tostr': 'count { fi... | eq { count { filter_eq { all_rows ; date ; october } } ; 8 } = true | select the rows whose date record fuzzily matches to october . the number of such rows is 8 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'date_5': 5, 'october_6': 6, '8_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'date_5': 'date', 'october_6': 'october', '8_7': '8'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'date_5': [0], 'october_6': [0], '8_7': [2]} | ['region', 'date', 'label', 'format', 'catalog'] | [['europe', 'october 11 , 2004', 'sony bmg , columbia', 'cd', 'col 518748 9'], ['europe', 'october 11 , 2004', 'sony bmg , columbia', 'cd / dvd', 'col 518748 7'], ['united states', 'october 12 , 2004', 'epic', 'cd', '5187482'], ['united states', 'october 12 , 2004', 'epic', 'cd / dvd', '5187487'], ['canada', 'october 1... |
2008 - 09 west ham united f.c. season | https://en.wikipedia.org/wiki/2008%E2%80%9309_West_Ham_United_F.C._season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18539546-8.html.csv | superlative | ferdinand was the player in the 2008 - 09 west ham united f.c. season that received the highest transfer fee . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '6', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'transfer fee'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; transfer fee }'}, 'name'], 'result': 'ferdinand', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; transfer fee } ; name }'}, 'ferdinand'], 'result': Tru... | eq { hop { argmax { all_rows ; transfer fee } ; name } ; ferdinand } = true | select the row whose transfer fee record of all rows is maximum . the name record of this row is ferdinand . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'transfer fee_5': 5, 'name_6': 6, 'ferdinand_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'transfer fee_5': 'transfer fee', 'name_6': 'name', 'ferdinand_7': 'ferdinand'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'transfer fee_5': [0], 'name_6': [1], 'ferdinand_7': [2]} | ['name', 'country', 'status', 'moving to', 'transfer fee'] | [['solano', 'per', 'transferred', 'released', 'free'], ['zamora', 'eng', 'transferred', 'fulham', '4.8 m'], ['paintsil', 'gha', 'transferred', 'fulham', '1.5 m'], ['wright', 'eng', 'transferred', 'ipswich town', '0.5 m'], ['ljungberg', 'swe', 'transferred', 'released', 'free'], ['ferdinand', 'eng', 'transferred', 'sund... |
ian woosnam | https://en.wikipedia.org/wiki/Ian_Woosnam | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1034991-8.html.csv | unique | pga championship is the only tournament where ian woosnam never made it to the top 5 . | {'scope': 'all', 'row': '4', 'col': '3', 'col_other': '1', 'criterion': 'equal', 'value': '0', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'top - 5', '0'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose top - 5 record is equal to 0 .', 'tostr': 'filter_eq { all_rows ; top - 5 ; 0 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ;... | and { only { filter_eq { all_rows ; top - 5 ; 0 } } ; eq { hop { filter_eq { all_rows ; top - 5 ; 0 } ; tournament } ; pga championship } } = true | select the rows whose top - 5 record is equal to 0 . there is only one such row in the table . the tournament record of this unqiue row is pga championship . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'top - 5_7': 7, '0_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'tournament_9': 9, 'pga championship_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'top - 5_7': 'top - 5', '0_8': '0', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'tournament_9': 'tournament', 'pga championship_10': 'pga championship'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'top - 5_7': [0], '0_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'tournament_9': [2], 'pga championship_10': [3]} | ['tournament', 'wins', 'top - 5', 'top - 10', 'top - 25', 'events', 'cuts made'] | [['masters tournament', '1', '1', '1', '7', '25', '13'], ['us open', '0', '1', '2', '4', '10', '7'], ['the open championship', '0', '4', '5', '10', '23', '17'], ['pga championship', '0', '0', '2', '3', '18', '9'], ['totals', '1', '6', '10', '24', '76', '46']] |
b " grey 's anatomy ( season 4 ) " | https://en.wikipedia.org/wiki/Grey%27s_Anatomy_%28season_4%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-11058032-1.html.csv | count | shonda rhimes was one of the writers for four of the episodes in the season four series of grey 's anatomy . | {'scope': 'all', 'criterion': 'equal', 'value': 'shonda rhimes', 'result': '4', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'written by', 'shonda rhimes'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose written by record fuzzily matches to shonda rhimes .', 'tostr': 'filter_eq { all_rows ; written by ; shonda rhimes }'}], 'result':... | eq { count { filter_eq { all_rows ; written by ; shonda rhimes } } ; 4 } = true | select the rows whose written by record fuzzily matches to shonda rhimes . the number of such rows is 4 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'written by_5': 5, 'shonda rhimes_6': 6, '4_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'written by_5': 'written by', 'shonda rhimes_6': 'shonda rhimes', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'written by_5': [0], 'shonda rhimes_6': [0], '4_7': [2]} | ['no in series', 'no in season', 'title', 'directed by', 'written by', 'original air date', 'us viewers ( millions )'] | [['62', '1', 'a change is gon na come', 'rob corn', 'shonda rhimes', 'september 27 , 2007', '20.93'], ['63', '2', 'love / addiction', 'james frawley', 'debora cahn', 'october 4 , 2007', '18.51'], ['64', '3', 'let the truth sting', 'dan minahan', 'mark wilding', 'october 11 , 2007', '19.04'], ['65', '4', 'the heart of t... |
daniela hantuchová career statistics | https://en.wikipedia.org/wiki/Daniela_Hantuchov%C3%A1_career_statistics | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-23944006-4.html.csv | majority | daniela hantuchová was the runner-up in the majority of her tennis doubles tournaments . | {'scope': 'all', 'col': '1', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'runner - up', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'outcome', 'runner - up'], 'result': True, 'ind': 0, 'tointer': 'for the outcome records of all rows , most of them fuzzily match to runner - up .', 'tostr': 'most_eq { all_rows ; outcome ; runner - up } = true'} | most_eq { all_rows ; outcome ; runner - up } = true | for the outcome records of all rows , most of them fuzzily match to runner - up . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'outcome_3': 3, 'runner - up_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'outcome_3': 'outcome', 'runner - up_4': 'runner - up'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'outcome_3': [0], 'runner - up_4': [0]} | ['outcome', 'year', 'championship', 'surface', 'partner', 'opponents', 'score'] | [['runner - up', '2002', 'berlin', 'clay', 'arantxa sánchez vicario', 'elena dementieva janette husárová', '6 - 0 , 6 - 7 , 2 - 6'], ['runner - up', '2002', 'san diego', 'hard', 'ai sugiyama', 'conchita martínez virginia ruano pascual', '7 - 6 ( 9 - 7 ) , 1 - 6 , 5 - 7'], ['runner - up', '2005', 'zurich', 'hard ( i )',... |
indiana high school athletics conferences : allen county - metropolitan | https://en.wikipedia.org/wiki/Indiana_High_School_Athletics_Conferences%3A_Allen_County_%E2%80%93_Metropolitan | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13986492-17.html.csv | aggregation | average enrollment in marion county indiana high schools is 3,633 . | {'scope': 'subset', 'col': '4', 'type': 'average', 'result': '3,633', 'subset': {'col': '7', 'criterion': 'fuzzily_match', 'value': 'marion'}} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'county', 'marion'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; county ; marion }', 'tointer': 'select the rows whose county record fuzzily matches to marion .'}, 'enrollment'], 'result': '3,633', 'ind'... | round_eq { avg { filter_eq { all_rows ; county ; marion } ; enrollment } ; 3,633 } = true | select the rows whose county record fuzzily matches to marion . the average of the enrollment record of these rows is 3,633 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'avg_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'county_5': 5, 'marion_6': 6, 'enrollment_7': 7, '3,633_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'avg_1': 'avg', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'county_5': 'county', 'marion_6': 'marion', 'enrollment_7': 'enrollment', '3,633_8': '3,633'} | {'eq_2': [3], 'result_3': [], 'avg_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'county_5': [0], 'marion_6': [0], 'enrollment_7': [1], '3,633_8': [2]} | ['school', 'mascot', 'location', 'enrollment', 'ihsaa class', 'ihsaa football class', 'county'] | [['indianapolis ben davis', 'giants', 'indianapolis', '4892', 'aaaa', 'aaaaa', '49 marion'], ['carmel', 'greyhounds', 'carmel', '4443', 'aaaa', 'aaaaa', '29 hamilton'], ['center grove', 'trojans', 'greenwood', '2.366', 'aaaa', 'aaaaa', '41 johnson'], ['lawrence north', 'wildcats', 'lawrence', '2457', 'aaaa', 'aaaaa', '... |
nick park | https://en.wikipedia.org/wiki/Nick_Park | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-149052-1.html.csv | majority | the majority of nick park 's works are classified as short films . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'short film', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'notes', 'short film'], 'result': True, 'ind': 0, 'tointer': 'for the notes records of all rows , most of them fuzzily match to short film .', 'tostr': 'most_eq { all_rows ; notes ; short film } = true'} | most_eq { all_rows ; notes ; short film } = true | for the notes records of all rows , most of them fuzzily match to short film . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'notes_3': 3, 'short film_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'notes_3': 'notes', 'short film_4': 'short film'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'notes_3': [0], 'short film_4': [0]} | ['year', 'title', 'director', 'writer', 'notes'] | [['1989', 'creature comforts', 'yes', 'yes', 'short film'], ['1989', 'wallace & gromit : a grand day out', 'yes', 'yes', 'short film'], ['1993', 'wallace & gromit : the wrong trousers', 'yes', 'yes', 'short film'], ['1995', 'wallace & gromit : a close shave', 'yes', 'yes', 'short film'], ['2000', 'chicken run', 'yes', ... |
lukoil | https://en.wikipedia.org/wiki/Lukoil | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1027881-2.html.csv | unique | lukoil - permnefteorgsintez is the only one among those launched in 1958 that has a capacity , mln tpa of 12 , 0 . | {'scope': 'subset', 'row': '2', 'col': '5', 'col_other': '1,3', 'criterion': 'equal', 'value': '12 , 0', 'subset': {'col': '3', 'criterion': 'equal', 'value': '1958'}} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'launched', '1958'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; launched ; 1958 }', 'tointer': 'select the rows whose launched record is equal to 1958 .'}, 'capacity , mln tpa... | and { only { filter_eq { filter_eq { all_rows ; launched ; 1958 } ; capacity , mln tpa ; 12 , 0 } } ; eq { hop { filter_eq { filter_eq { all_rows ; launched ; 1958 } ; capacity , mln tpa ; 12 , 0 } ; name } ; lukoil - permnefteorgsintez } } = true | select the rows whose launched record is equal to 1958 . among these rows , select the rows whose capacity , mln tpa record fuzzily matches to 12 , 0 . there is only one such row in the table . the name record of this unqiue row is lukoil - permnefteorgsintez . | 8 | 6 | {'and_5': 5, 'result_6': 6, 'only_2': 2, 'filter_str_eq_1': 1, 'filter_eq_0': 0, 'all_rows_7': 7, 'launched_8': 8, '1958_9': 9, 'capacity , mln tpa_10': 10, '12 , 0_11': 11, 'str_eq_4': 4, 'str_hop_3': 3, 'name_12': 12, 'lukoil - permnefteorgsintez_13': 13} | {'and_5': 'and', 'result_6': 'true', 'only_2': 'only', 'filter_str_eq_1': 'filter_str_eq', 'filter_eq_0': 'filter_eq', 'all_rows_7': 'all_rows', 'launched_8': 'launched', '1958_9': '1958', 'capacity , mln tpa_10': 'capacity , mln tpa', '12 , 0_11': '12 , 0', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'name_12': 'nam... | {'and_5': [6], 'result_6': [], 'only_2': [5], 'filter_str_eq_1': [2, 3], 'filter_eq_0': [1], 'all_rows_7': [0], 'launched_8': [0], '1958_9': [0], 'capacity , mln tpa_10': [1], '12 , 0_11': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'name_12': [3], 'lukoil - permnefteorgsintez_13': [4]} | ['name', 'location', 'launched', 'acquired', 'capacity , mln tpa'] | [['lukoil - nizhegorodnefteorgsintez', 'kstovo', '1958', '2000', '15 , 0'], ['lukoil - permnefteorgsintez', 'perm', '1958', '1991', '12 , 0'], ['lukoil - volgogradneftepererabotka', 'volgograd', '1957', '1991', '9 , 9'], ['lukoil - ukhtaneftepererabotka', 'ukhta', '1934', '2000', '3 , 7'], ['lukoil - odessky nefteperer... |
1980 - 81 philadelphia flyers season | https://en.wikipedia.org/wiki/1980%E2%80%9381_Philadelphia_Flyers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14311305-4.html.csv | unique | game number 32 was the only game to have 47 points . | {'scope': 'all', 'row': '6', 'col': '6', 'col_other': '1', 'criterion': 'equal', 'value': '47', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'points', '47'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose points record is equal to 47 .', 'tostr': 'filter_eq { all_rows ; points ; 47 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ;... | and { only { filter_eq { all_rows ; points ; 47 } } ; eq { hop { filter_eq { all_rows ; points ; 47 } ; game } ; 32 } } = true | select the rows whose points record is equal to 47 . there is only one such row in the table . the game record of this unqiue row is 32 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'points_7': 7, '47_8': 8, 'eq_3': 3, 'num_hop_2': 2, 'game_9': 9, '32_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'points_7': 'points', '47_8': '47', 'eq_3': 'eq', 'num_hop_2': 'num_hop', 'game_9': 'game', '32_10': '32'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'points_7': [0], '47_8': [0], 'eq_3': [4], 'num_hop_2': [3], 'game_9': [2], '32_10': [3]} | ['game', 'december', 'opponent', 'score', 'record', 'points'] | [['27', '4', 'chicago black hawks', '7 - 5', '18 - 5 - 4', '40'], ['28', '6', 'detroit red wings', '2 - 4', '18 - 6 - 4', '40'], ['29', '7', 'colorado rockies', '4 - 2', '19 - 6 - 4', '42'], ['30', '10', 'chicago black hawks', '2 - 2', '19 - 6 - 5', '43'], ['31', '13', 'pittsburgh penguins', '6 - 5', '20 - 6 - 5', '45'... |
sebastián gonzález | https://en.wikipedia.org/wiki/Sebasti%C3%A1n_Gonz%C3%A1lez | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1257826-1.html.csv | count | there were six goals scored by sebastian gonzales . | {'scope': 'all', 'criterion': 'all', 'value': 'n/a', 'result': '6', 'col': '1', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_all', 'args': ['all_rows', 'goal'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose goal record is arbitrary .', 'tostr': 'filter_all { all_rows ; goal }'}], 'result': '6', 'ind': 1, 'tostr': 'count { filter_all { all_rows ; goal } }', 'toi... | eq { count { filter_all { all_rows ; goal } } ; 6 } = true | select the rows whose goal record is arbitrary . the number of such rows is 6 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_all_0': 0, 'all_rows_4': 4, 'goal_5': 5, '6_6': 6} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_all_0': 'filter_all', 'all_rows_4': 'all_rows', 'goal_5': 'goal', '6_6': '6'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_all_0': [1], 'all_rows_4': [0], 'goal_5': [0], '6_6': [2]} | ['goal', 'date', 'score', 'result', 'competition'] | [['1', '17 january 2001', '2 - 0', '2 - 0', 'friendly'], ['2', '20 january 2001', '1 - 0', '2 - 0', 'friendly'], ['3', '20 january 2001', '2 - 0', '2 - 0', 'friendly'], ['4', '15 march 2001', '3 - 1', '3 - 1', 'friendly'], ['5', '14 july 2004', '0 - 1', '1 - 1', '2004 copa américa'], ['6', '17 november 2004', '2 - 1', ... |
memphis grizzlies all - time roster | https://en.wikipedia.org/wiki/Memphis_Grizzlies_all-time_roster | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-16494599-4.html.csv | ordinal | terry dehere has the third highest player number on the memphis grizzlies all - time roster . | {'row': '5', 'col': '2', 'order': '3', 'col_other': '1', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'no', '3'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; no ; 3 }'}, 'player'], 'result': 'terry dehere', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; no ; 3 } ; player }'}, 'terry dehere'], 'result'... | eq { hop { nth_argmax { all_rows ; no ; 3 } ; player } ; terry dehere } = true | select the row whose no record of all rows is 3rd maximum . the player record of this row is terry dehere . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'no_5': 5, '3_6': 6, 'player_7': 7, 'terry dehere_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'no_5': 'no', '3_6': '3', 'player_7': 'player', 'terry dehere_8': 'terry dehere'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'no_5': [0], '3_6': [0], 'player_7': [1], 'terry dehere_8': [2]} | ['player', 'no', 'nationality', 'position', 'years for grizzlies', 'school / club team'] | [['antonio daniels', '33', 'united states', 'point guard', '1997 - 1998', 'bowling green'], ['ed davis', '32', 'united states', 'forward', '2013 - present', 'north carolina'], ['josh davis', '18', 'united states', 'forward', '2011 - 2012', 'wyoming'], ['austin daye', '5', 'united states', 'small forward', '2013 - prese... |
kairat nurdauletov | https://en.wikipedia.org/wiki/Kairat_Nurdauletov | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12706952-1.html.csv | count | kairat nurdauletov participated in 3 friendly competitions between 2007 and 2012 . | {'scope': 'all', 'criterion': 'equal', 'value': 'friendly', 'result': '3', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'competition', 'friendly'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose competition record fuzzily matches to friendly .', 'tostr': 'filter_eq { all_rows ; competition ; friendly }'}], 'result': '3', 'ind':... | eq { count { filter_eq { all_rows ; competition ; friendly } } ; 3 } = true | select the rows whose competition record fuzzily matches to friendly . the number of such rows is 3 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'competition_5': 5, 'friendly_6': 6, '3_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'competition_5': 'competition', 'friendly_6': 'friendly', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'competition_5': [0], 'friendly_6': [0], '3_7': [2]} | ['date', 'venue', 'score', 'result', 'competition'] | [['8 september 2007', 'central stadium , almaty , kazakhstan', '1 - 1', 'draw', 'friendly'], ['7 october 2011', 'king baudouin stadium , almaty , kazakhstan', '4 - 1', 'lost', 'friendly'], ['1 june 2012', 'central stadium , almaty , kazakhstan', '5 - 2', 'win', 'friendly'], ['7 september 2012', 'astana arena , astana ,... |
lara gut | https://en.wikipedia.org/wiki/Lara_Gut | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15556757-2.html.csv | unique | the only time lara gut was at a race in italy was on january 23 , 2011 . | {'scope': 'all', 'row': '6', 'col': '3', 'col_other': '2', 'criterion': 'fuzzily_match', 'value': 'italy', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location', 'italy'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose location record fuzzily matches to italy .', 'tostr': 'filter_eq { all_rows ; location ; italy }'}], 'result': True, 'ind': 1, 'tostr': 'onl... | and { only { filter_eq { all_rows ; location ; italy } } ; eq { hop { filter_eq { all_rows ; location ; italy } ; date } ; 23 jan 2011 } } = true | select the rows whose location record fuzzily matches to italy . there is only one such row in the table . the date record of this unqiue row is 23 jan 2011 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'location_7': 7, 'italy_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'date_9': 9, '23 jan 2011_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'location_7': 'location', 'italy_8': 'italy', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'date_9': 'date', '23 jan 2011_10': '23 jan 2011'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'location_7': [0], 'italy_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'date_9': [2], '23 jan 2011_10': [3]} | ['season', 'date', 'location', 'race', 'place'] | [['2008', '2 feb 2008', 'st moritz , switzerland', 'downhill', '3rd'], ['2009', '20 dec 2008', 'st moritz , switzerland', 'super - g', '1st'], ['2009', '28 dec 2008', 'semmering , austria', 'giant slalom', '3rd'], ['2011', '18 dec 2010', "val d'isère , france", 'downhill', '3rd'], ['2011', '9 jan 2011', 'altenmarkt - z... |
list of kraft nabisco championship champions | https://en.wikipedia.org/wiki/List_of_Kraft_Nabisco_Championship_champions | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27864661-6.html.csv | ordinal | the number one ranked nation on the list of kraft nabisco championship champions had the highest number of major wins among the other nations . | {'row': '1', 'col': '6', 'order': '1', 'col_other': '1', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'major winners', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; major winners ; 1 }'}, 'rank'], 'result': '1', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; major winners ; 1 } ; rank }'}, '1'], '... | eq { hop { nth_argmax { all_rows ; major winners ; 1 } ; rank } ; 1 } = true | select the row whose major winners record of all rows is 1st maximum . the rank record of this row is 1 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'major winners_5': 5, '1_6': 6, 'rank_7': 7, '1_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'major winners_5': 'major winners', '1_6': '1', 'rank_7': 'rank', '1_8': '1'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'major winners_5': [0], '1_6': [0], 'rank_7': [1], '1_8': [2]} | ['rank', 'nationality', 'non - major wins', 'non - major winners', 'major wins', 'major winners', 'total wins', 'total winners', 'first title', 'last title'] | [['1', 'united states', '8', '8', '19', '13', '27', '21', '1972', '2011'], ['2', 'sweden', '0', '0', '4', '2', '4', '2', '1993', '2005'], ['3', 'south korea', '0', '0', '3', '3', '3', '3', '2004', '2013'], ['t4', 'australia', '0', '0', '2', '1', '2', '1', '2000', '2006'], ['t4', 'canada', '2', '1', '0', '0', '2', '1', ... |
ranked lists of chilean regions | https://en.wikipedia.org/wiki/Ranked_lists_of_Chilean_regions | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-25042332-22.html.csv | comparative | the arica and parinacota chilean region has a higher tertiary education attainment than the maule region . | {'row_1': '1', 'row_2': '9', 'col': '5', 'col_other': '1', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'region', 'arica and parinacota'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose region record fuzzily matches to arica and parinacota .', 'tostr': 'filter_eq { all_rows ; region ; arica and parinacota... | greater { hop { filter_eq { all_rows ; region ; arica and parinacota } ; tertiary ( 18 - 24 years ) } ; hop { filter_eq { all_rows ; region ; maule } ; tertiary ( 18 - 24 years ) } } = true | select the rows whose region record fuzzily matches to arica and parinacota . take the tertiary ( 18 - 24 years ) record of this row . select the rows whose region record fuzzily matches to maule . take the tertiary ( 18 - 24 years ) record of this row . the first record is greater than the second record . | 5 | 5 | {'greater_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'region_7': 7, 'arica and parinacota_8': 8, 'tertiary (18 - 24 years)_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'region_11': 11, 'maule_12': 12, 'tertiary (18 - 24 years)_13': 13} | {'greater_4': 'greater', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'region_7': 'region', 'arica and parinacota_8': 'arica and parinacota', 'tertiary (18 - 24 years)_9': 'tertiary ( 18 - 24 years )', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq... | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'region_7': [0], 'arica and parinacota_8': [0], 'tertiary (18 - 24 years)_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'region_11': [1], 'maule_12': [1], 'tertiary (18 - 24 years)_13': [3]} | ['region', 'preschool ( 0 - 5 years )', 'primary ( 6 - 13 years )', 'secondary ( 14 - 17 years )', 'tertiary ( 18 - 24 years )'] | [['arica and parinacota', '42.92', '91.17', '76.65', '38.67'], ['tarapacá', '47.51', '94.52', '70.82', '28.16'], ['antofagasta', '38.13', '91.90', '70.78', '28.26'], ['atacama', '38.14', '94.13', '73.93', '23.01'], ['coquimbo', '47.43', '93.00', '68.95', '33.89'], ['valparaíso', '50.23', '91.37', '71.63', '42.96'], ['s... |
89th united states congress | https://en.wikipedia.org/wiki/89th_United_States_Congress | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1847180-3.html.csv | unique | ross bass was the only vacator of the 89th united states congress who had no successor . | {'scope': 'all', 'row': '6', 'col': '4', 'col_other': '2', 'criterion': 'fuzzily_match', 'value': 'vacant', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'successor', 'vacant'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose successor record fuzzily matches to vacant .', 'tostr': 'filter_eq { all_rows ; successor ; vacant }'}], 'result': True, 'ind': 1, 'tostr'... | and { only { filter_eq { all_rows ; successor ; vacant } } ; eq { hop { filter_eq { all_rows ; successor ; vacant } ; vacator } ; ross bass ( d ) } } = true | select the rows whose successor record fuzzily matches to vacant . there is only one such row in the table . the vacator record of this unqiue row is ross bass ( d ) . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'successor_7': 7, 'vacant_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'vacator_9': 9, 'ross bass (d)_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'successor_7': 'successor', 'vacant_8': 'vacant', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'vacator_9': 'vacator', 'ross bass (d)_10': 'ross bass ( d )'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'successor_7': [0], 'vacant_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'vacator_9': [2], 'ross bass (d)_10': [3]} | ['state ( class )', 'vacator', 'reason for change', 'successor', "date of successor 's formal installation"] | [['south carolina ( 3 )', 'olin d johnston ( d )', 'died april 18 , 1965', 'donald s russell ( d )', 'april 22 , 1965'], ['south carolina ( 3 )', 'donald s russell ( d )', 'successor elected november 8 , 1965', 'ernest hollings ( d )', 'november 9 , 1965'], ['virginia ( 1 )', 'harry f byrd ( d )', 'resigned november 10... |
2003 grand prix of monterey | https://en.wikipedia.org/wiki/2003_Grand_Prix_of_Monterey | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18805166-2.html.csv | count | 8 of the drivers completed 87 or more laps . | {'scope': 'all', 'criterion': 'greater_than_eq', 'value': '87', 'result': '8', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater_eq', 'args': ['all_rows', 'laps', '87'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose laps record is greater than or equal to 87 .', 'tostr': 'filter_greater_eq { all_rows ; laps ; 87 }'}], 'result': '8', 'ind': 1, 'tostr': 'coun... | eq { count { filter_greater_eq { all_rows ; laps ; 87 } } ; 8 } = true | select the rows whose laps record is greater than or equal to 87 . the number of such rows is 8 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_greater_eq_0': 0, 'all_rows_4': 4, 'laps_5': 5, '87_6': 6, '8_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_greater_eq_0': 'filter_greater_eq', 'all_rows_4': 'all_rows', 'laps_5': 'laps', '87_6': '87', '8_7': '8'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_greater_eq_0': [1], 'all_rows_4': [0], 'laps_5': [0], '87_6': [0], '8_7': [2]} | ['driver', 'team', 'laps', 'time / retired', 'grid', 'points'] | [['patrick carpentier', "team player 's", '87', '1:48:11.023', '1', '22'], ['bruno junqueira', 'newman / haas racing', '87', '+ 0.8 secs', '2', '17'], ['paul tracy', "team player 's", '87', '+ 28.6 secs', '3', '14'], ['michel jourdain , jr', 'team rahal', '87', '+ 40.8 secs', '13', '12'], ['mario haberfeld', 'mi - jack... |
fiba under - 19 world championship | https://en.wikipedia.org/wiki/FIBA_Under-19_World_Championship | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11383852-2.html.csv | aggregation | in fiba under - 19 world championship there are people got totally 25 medals that includes all the silver , gold and bronze medals . | {'scope': 'all', 'col': '5', 'type': 'sum', 'result': '25', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'total'], 'result': '25', 'ind': 0, 'tostr': 'sum { all_rows ; total }'}, '25'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; total } ; 25 } = true', 'tointer': 'the sum of the total record of all rows is 25 .'} | round_eq { sum { all_rows ; total } ; 25 } = true | the sum of the total record of all rows is 25 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'total_4': 4, '25_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'total_4': 'total', '25_5': '25'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'total_4': [0], '25_5': [1]} | ['rank', 'gold', 'silver', 'bronze', 'total'] | [['1', '5', '3', '0', '8'], ['2', '2', '2', '0', '4'], ['3', '1', '1', '1', '3'], ['5', '1', '1', '0', '2'], ['6', '1', '0', '1', '2'], ['8', '0', '1', '1', '2'], ['10', '0', '1', '0', '1'], ['11', '0', '0', '2', '2'], ['13', '0', '0', '1', '1']] |
1969 cleveland browns season | https://en.wikipedia.org/wiki/1969_Cleveland_Browns_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10652161-2.html.csv | count | there were two games in the browns season of 1969 with less than 35000 fans in attendance . | {'scope': 'all', 'criterion': 'less_than', 'value': '35000', 'result': '2', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'attendance', '35000'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose attendance record is less than 35000 .', 'tostr': 'filter_less { all_rows ; attendance ; 35000 }'}], 'result': '2', 'ind': 1, 'tostr': 'coun... | eq { count { filter_less { all_rows ; attendance ; 35000 } } ; 2 } = true | select the rows whose attendance record is less than 35000 . the number of such rows is 2 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_less_0': 0, 'all_rows_4': 4, 'attendance_5': 5, '35000_6': 6, '2_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_less_0': 'filter_less', 'all_rows_4': 'all_rows', 'attendance_5': 'attendance', '35000_6': '35000', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_less_0': [1], 'all_rows_4': [0], 'attendance_5': [0], '35000_6': [0], '2_7': [2]} | ['week', 'date', 'opponent', 'result', 'attendance'] | [['1', 'august 10 , 1969', 'san francisco 49ers at seattle', 'w 24 - 19', '32219'], ['2', 'august 16 , 1969', 'los angeles rams', 'w 10 - 3', '54937'], ['3', 'august 23 , 1969', 'san diego chargers', 't 19 - 19', '36005'], ['4', 'august 30 , 1969', 'green bay packers', 'l 27 - 17', '85532'], ['5', 'september 6 , 1969',... |
washington redskins draft history | https://en.wikipedia.org/wiki/Washington_Redskins_draft_history | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17100961-50.html.csv | superlative | in the washington redskins draft history , art monk ranks as the highest overall . | {'scope': 'all', 'col_superlative': '3', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '4', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmin', 'args': ['all_rows', 'overall'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; overall }'}, 'name'], 'result': 'art monk', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; overall } ; name }'}, 'art monk'], 'result': True, 'ind': 2, 'tos... | eq { hop { argmin { all_rows ; overall } ; name } ; art monk } = true | select the row whose overall record of all rows is minimum . the name record of this row is art monk . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'overall_5': 5, 'name_6': 6, 'art monk_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'overall_5': 'overall', 'name_6': 'name', 'art monk_7': 'art monk'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'overall_5': [0], 'name_6': [1], 'art monk_7': [2]} | ['round', 'pick', 'overall', 'name', 'position', 'college'] | [['1', '18', '18', 'art monk', 'wr', 'syracuse'], ['2', '27', '55', 'mat mendenhall', 'de', 'brigham young'], ['6', '17', '155', 'farley bell', 'lb', 'cincinnati'], ['7', '22', '187', 'melvin jones', 'g', 'houston'], ['9', '20', '241', 'lawrence mccullough', 'wr', 'illinois'], ['10', '19', '268', 'lewis walker', 'rb', ... |
list of bangladeshi submissions for the academy award for best foreign language film | https://en.wikipedia.org/wiki/List_of_Bangladeshi_submissions_for_the_Academy_Award_for_Best_Foreign_Language_Film | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-17156199-1.html.csv | ordinal | humayun ahmed is the director of the 2nd earliest best foreign language film for the bangladeshi submission award . | {'row': '2', 'col': '1', 'order': '2', 'col_other': '4', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'year ( ceremony )', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; year ( ceremony ) ; 2 }'}, 'director'], 'result': 'humayun ahmed', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; year ( ceremony... | eq { hop { nth_argmin { all_rows ; year ( ceremony ) ; 2 } ; director } ; humayun ahmed } = true | select the row whose year ( ceremony ) record of all rows is 2nd minimum . the director record of this row is humayun ahmed . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'year (ceremony)_5': 5, '2_6': 6, 'director_7': 7, 'humayun ahmed_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmin_0': 'nth_argmin', 'all_rows_4': 'all_rows', 'year (ceremony)_5': 'year ( ceremony )', '2_6': '2', 'director_7': 'director', 'humayun ahmed_8': 'humayun ahmed'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'year (ceremony)_5': [0], '2_6': [0], 'director_7': [1], 'humayun ahmed_8': [2]} | ['year ( ceremony )', 'film title used in nomination', 'original title', 'director', 'result'] | [['2002 ( 75th )', 'the clay bird', 'মাটির ময়না ( matir moyna )', 'tareque masud', 'not nominated'], ['2005 ( 78th )', 'shyamol chhaya', 'শ্যামল ছায়া ( shyamol chhaya )', 'humayun ahmed', 'not nominated'], ['2006 ( 79th )', 'forever flows', 'নিরন্তর ( nirontor )', 'abu sayeed', 'not nominated'], ['2007 ( 80th )', 'on... |
taylor dent | https://en.wikipedia.org/wiki/Taylor_Dent | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1551815-5.html.csv | ordinal | taylor dent 's second to last tournament was in adelaide , australia . | {'row': '6', 'col': '2', 'order': '2', 'col_other': '3', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'date ( final )', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; date ( final ) ; 2 }'}, 'tournament'], 'result': 'adelaide , australia', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; date ( final... | eq { hop { nth_argmax { all_rows ; date ( final ) ; 2 } ; tournament } ; adelaide , australia } = true | select the row whose date ( final ) record of all rows is 2nd maximum . the tournament record of this row is adelaide , australia . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'date (final)_5': 5, '2_6': 6, 'tournament_7': 7, 'adelaide , australia_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'date (final)_5': 'date ( final )', '2_6': '2', 'tournament_7': 'tournament', 'adelaide , australia_8': 'adelaide , australia'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'date (final)_5': [0], '2_6': [0], 'tournament_7': [1], 'adelaide , australia_8': [2]} | ['outcome', 'date ( final )', 'tournament', 'surface', 'opponent in the final', 'score'] | [['winner', 'july 7 2002', 'newport , united states', 'grass', 'james blake', '6 - 1 , 4 - 6 , 6 - 4'], ['winner', 'february 17 , 2003', 'memphis , united states', 'hard ( i )', 'andy roddick', '6 - 1 , 6 - 4'], ['winner', 'september 22 , 2003', 'bangkok , thailand', 'hard ( i )', 'juan carlos ferrero', '6 - 3 , 7 - 6 ... |
porsche boxster | https://en.wikipedia.org/wiki/Porsche_Boxster | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-24729-2.html.csv | majority | the majority of versions of the porsche boxster listed produce less than 200 g/km of carbon dioxide . | {'scope': 'all', 'col': '8', 'most_or_all': 'most', 'criterion': 'less_than_eq', 'value': '200 g/km', 'subset': None} | {'func': 'most_less_eq', 'args': ['all_rows', 'co2', '200 g/km'], 'result': True, 'ind': 0, 'tointer': 'for the co2 records of all rows , most of them are less than or equal to 200 g/km .', 'tostr': 'most_less_eq { all_rows ; co2 ; 200 g/km } = true'} | most_less_eq { all_rows ; co2 ; 200 g/km } = true | for the co2 records of all rows , most of them are less than or equal to 200 g/km . | 1 | 1 | {'most_less_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'co2_3': 3, '200 g/km_4': 4} | {'most_less_eq_0': 'most_less_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'co2_3': 'co2', '200 g/km_4': '200 g/km'} | {'most_less_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'co2_3': [0], '200 g/km_4': [0]} | ['year', 'engine', 'power', 'torque', 'transmission', '0 - 100 km / h ( 60 mph )', 'top speed', 'co2'] | [['2012', '2.7 l ( 2706 cc )', 'n / a', '', 'manual ( 6 )', '5.8 seconds ( 5.5 )', 'n / a', '192 g / km'], ['2012', '2.7 l ( 2706 cc )', 'n / a', '', 'pdk ( 7 )', '5.7 seconds ( 5.4 )', 'n / a', '180 g / km'], ['2012', '2.7 l ( 2706 cc ) sport chrono', 'n / a', '', 'pdk ( 7 )', '5.5 seconds ( 5.2 )', 'n / a', '180 g / ... |
blue ridge hockey conference | https://en.wikipedia.org/wiki/Blue_Ridge_Hockey_Conference | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16404837-5.html.csv | comparative | in the blue ridge hockey conference , high point university was founded 30 years before coastal carolina university . | {'row_1': '3', 'row_2': '2', 'col': '3', 'col_other': '1', 'relation': 'diff', 'record_mentioned': 'no', 'diff_result': {'diff_value': '30', 'bigger': 'row2'}} | {'func': 'eq', 'args': [{'func': 'diff', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'school', 'high point university'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose school record fuzzily matches to high point university .', 'tostr': 'filter_eq { all_rows ; school... | eq { diff { hop { filter_eq { all_rows ; school ; high point university } ; founded } ; hop { filter_eq { all_rows ; school ; coastal carolina university } ; founded } } ; -30 } = true | select the rows whose school record fuzzily matches to high point university . take the founded record of this row . select the rows whose school record fuzzily matches to coastal carolina university . take the founded record of this row . the second record is 30 larger than the first record . | 6 | 6 | {'eq_5': 5, 'result_6': 6, 'diff_4': 4, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_7': 7, 'school_8': 8, 'high point university_9': 9, 'founded_10': 10, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_11': 11, 'school_12': 12, 'coastal carolina university_13': 13, 'founded_14': 14, '-30_15': 15} | {'eq_5': 'eq', 'result_6': 'true', 'diff_4': 'diff', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_7': 'all_rows', 'school_8': 'school', 'high point university_9': 'high point university', 'founded_10': 'founded', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_11': 'all_ro... | {'eq_5': [6], 'result_6': [], 'diff_4': [5], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_7': [0], 'school_8': [0], 'high point university_9': [0], 'founded_10': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_11': [1], 'school_12': [1], 'coastal carolina university_13': [1], 'founded_14': [3], '-30_15'... | ['school', 'location', 'founded', 'affiliation', 'nickname'] | [['appalachian state university', 'boone , nc', '1899', 'public ( university of north carolina system )', 'mountaineers'], ['coastal carolina university', 'conway , sc', '1954', 'public', 'chanticleers'], ['high point university', 'high point , nc', '1924', 'private / methodist', 'panthers'], ['johnson & wales universi... |
1991 foster 's cup | https://en.wikipedia.org/wiki/1991_Foster%27s_Cup | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16387700-1.html.csv | superlative | carlton had the highest score of any home team at the 1991 foster 's cup . | {'scope': 'all', 'col_superlative': '2', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'home team score'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; home team score }'}, 'home team'], 'result': 'carlton', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; home team score } ; home team }'}, 'carlton']... | eq { hop { argmax { all_rows ; home team score } ; home team } ; carlton } = true | select the row whose home team score record of all rows is maximum . the home team record of this row is carlton . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'home team score_5': 5, 'home team_6': 6, 'carlton_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'home team score_5': 'home team score', 'home team_6': 'home team', 'carlton_7': 'carlton'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'home team score_5': [0], 'home team_6': [1], 'carlton_7': [2]} | ['home team', 'home team score', 'away team', 'away team score', 'ground', 'crowd', 'date'] | [['carlton', '27.9 ( 171 )', 'fitzroy', '13.8 ( 86 )', 'north hobart oval', '10100', 'sunday 3 february'], ['footscray', '9.6 ( 60 )', 'hawthorn', '19.25 ( 139 )', 'waverley park', '13196', 'wednesday 6 february'], ['collingwood', '11.17 ( 83 )', 'brisbane', '20.20 ( 140 )', 'gabba', '12461', 'saturday 10 february'], [... |
colonia ( a camp album ) | https://en.wikipedia.org/wiki/Colonia_%28A_Camp_album%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18908421-5.html.csv | count | colonia ( a camp album ) has reveal records as its label 3 times . | {'scope': 'all', 'criterion': 'equal', 'value': 'reveal records', 'result': '3', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'label', 'reveal records'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose label record fuzzily matches to reveal records .', 'tostr': 'filter_eq { all_rows ; label ; reveal records }'}], 'result': '3', 'ind':... | eq { count { filter_eq { all_rows ; label ; reveal records } } ; 3 } = true | select the rows whose label record fuzzily matches to reveal records . the number of such rows is 3 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'label_5': 5, 'reveal records_6': 6, '3_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'label_5': 'label', 'reveal records_6': 'reveal records', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'label_5': [0], 'reveal records_6': [0], '3_7': [2]} | ['region', 'date', 'label', 'format', 'catalog'] | [['scandinavia', '28 january 2009', 'universal', 'cd', '0 - 6025 - 17918 - 7 - 7'], ['ireland', '30 january 2009', 'reveal records', 'cd / lp', 'reveal50cd / lp'], ['united kingdom', '2 february 2009', 'reveal records', 'cd / lp', 'reveal50cd / lp'], ['mainland europe', '20 march 2009', 'reveal records', 'cd / lp', 're... |
tasmania cricket team first - class records | https://en.wikipedia.org/wiki/Tasmania_cricket_team_first-class_records | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14412861-4.html.csv | comparative | tasmania scored more runs against queensland than they did against victoria . | {'row_1': '5', 'row_2': '1', 'col': '2', 'col_other': '3', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', 'queensland'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose opponent record fuzzily matches to queensland .', 'tostr': 'filter_eq { all_rows ; opponent ; queensland }'}, 'runs'], 'result':... | greater { hop { filter_eq { all_rows ; opponent ; queensland } ; runs } ; hop { filter_eq { all_rows ; opponent ; victoria } ; runs } } = true | select the rows whose opponent record fuzzily matches to queensland . take the runs record of this row . select the rows whose opponent record fuzzily matches to victoria . take the runs record of this row . the first record is greater than the second record . | 5 | 5 | {'greater_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'opponent_7': 7, 'queensland_8': 8, 'runs_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'opponent_11': 11, 'victoria_12': 12, 'runs_13': 13} | {'greater_4': 'greater', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'opponent_7': 'opponent', 'queensland_8': 'queensland', 'runs_9': 'runs', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'opponent_11': 'opponent', '... | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'opponent_7': [0], 'queensland_8': [0], 'runs_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'opponent_11': [1], 'victoria_12': [1], 'runs_13': [3]} | ['rank', 'runs', 'opponent', 'venue', 'season'] | [['1', '50', 'victoria', 'launceston cricket club ground , launceston', '1853 / 54'], ['2', '53', 'new south wales', 'bellerive oval , hobart', '2006 / 07'], ['3', '55', 'south australia', 'bellerive oval , hobart', '2010 / 11'], ['4', '57', 'victoria', 'launceston cricket club ground , launceston', '1850 / 51'], ['5',... |
galatasaray s.k. ( men 's volleyball ) | https://en.wikipedia.org/wiki/Galatasaray_S.K._%28men%27s_volleyball%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18729570-2.html.csv | superlative | ferhat akdeniz is the tallest player on the galatasaray s.k. men 's volleyball team . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '5', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '3', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'height'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; height }'}, 'player'], 'result': 'ferhat akdeniz', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; height } ; player }'}, 'ferhat akdeniz'], 'result': True, '... | eq { hop { argmax { all_rows ; height } ; player } ; ferhat akdeniz } = true | select the row whose height record of all rows is maximum . the player record of this row is ferhat akdeniz . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'height_5': 5, 'player_6': 6, 'ferhat akdeniz_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'height_5': 'height', 'player_6': 'player', 'ferhat akdeniz_7': 'ferhat akdeniz'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'height_5': [0], 'player_6': [1], 'ferhat akdeniz_7': [2]} | ['shirt no', 'nationality', 'player', 'birth date', 'height', 'position'] | [['6', 'cuba', 'henry bell cisnero', 'july 27 , 1982 ( age31 )', '188', 'spiker'], ['7', 'turkey', 'tolgahan camgöz', 'january 27 , 1990 ( age24 )', '182', 'libero'], ['11', 'turkey', 'caner pekşen', 'june 9 , 1987 ( age26 )', '190', 'setter'], ['15', 'turkey', 'oğuzhan tarakçı', 'april 23 , 1993 ( age20 )', '195', 'ou... |
1940 world series | https://en.wikipedia.org/wiki/1940_World_Series | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1332360-1.html.csv | comparative | game 4 had drawn a larger crowd than game 1 drew . | {'row_1': '4', 'row_2': '1', 'col': '6', 'col_other': '1', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'game', '4'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose game record fuzzily matches to 4 .', 'tostr': 'filter_eq { all_rows ; game ; 4 }'}, 'attendance'], 'result': None, 'ind': 2, 'tostr': 'hop { ... | greater { hop { filter_eq { all_rows ; game ; 4 } ; attendance } ; hop { filter_eq { all_rows ; game ; 1 } ; attendance } } = true | select the rows whose game record fuzzily matches to 4 . take the attendance record of this row . select the rows whose game record fuzzily matches to 1 . take the attendance record of this row . the first record is greater than the second record . | 5 | 5 | {'greater_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'game_7': 7, '4_8': 8, 'attendance_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'game_11': 11, '1_12': 12, 'attendance_13': 13} | {'greater_4': 'greater', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'game_7': 'game', '4_8': '4', 'attendance_9': 'attendance', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'game_11': 'game', '1_12': '1', 'attendanc... | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'game_7': [0], '4_8': [0], 'attendance_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'game_11': [1], '1_12': [1], 'attendance_13': [3]} | ['game', 'date', 'score', 'location', 'time', 'attendance'] | [['1', 'october 2', 'detroit tigers - 7 , cincinnati reds - 2', 'crosley field', '2:09', '31793'], ['2', 'october 3', 'detroit tigers - 3 , cincinnati reds - 5', 'crosley field', '1:54', '30640'], ['3', 'october 4', 'cincinnati reds - 4 , detroit tigers - 7', 'briggs stadium', '2:08', '52877'], ['4', 'october 5', 'cinc... |
1968 vfl season | https://en.wikipedia.org/wiki/1968_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10808933-3.html.csv | ordinal | mcg venue recorded the highest crowd participation during the 1968 vfl season . | {'row': '2', 'col': '6', 'order': '1', 'col_other': '5', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'crowd', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; crowd ; 1 }'}, 'venue'], 'result': 'mcg', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; crowd ; 1 } ; venue }'}, 'mcg'], 'result': True, 'in... | eq { hop { nth_argmax { all_rows ; crowd ; 1 } ; venue } ; mcg } = true | select the row whose crowd record of all rows is 1st maximum . the venue record of this row is mcg . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'crowd_5': 5, '1_6': 6, 'venue_7': 7, 'mcg_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'crowd_5': 'crowd', '1_6': '1', 'venue_7': 'venue', 'mcg_8': 'mcg'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'crowd_5': [0], '1_6': [0], 'venue_7': [1], 'mcg_8': [2]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['carlton', '1.11 ( 17 )', 'essendon', '7.8 ( 50 )', 'princes park', '37406', '25 april 1968'], ['richmond', '10.15 ( 75 )', 'geelong', '17.21 ( 123 )', 'mcg', '52175', '25 april 1968'], ['footscray', '14.10 ( 94 )', 'hawthorn', '16.9 ( 105 )', 'western oval', '14054', '27 april 1968'], ['collingwood', '2.19 ( 31 )', ... |
credit union challenge | https://en.wikipedia.org/wiki/Credit_Union_Challenge | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15315816-1.html.csv | count | three winners had the same prize of 8400 during the credit union golf challenge . | {'scope': 'all', 'criterion': 'equal', 'value': '8400', 'result': '3', 'col': '8', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': ['all_rows', "winner 's share", '8400'], 'result': None, 'ind': 0, 'tointer': "select the rows whose winner 's share record is equal to 8400 .", 'tostr': "filter_eq { all_rows ; winner 's share ; 8400 }"}], 'result': '3', 'ind': 1, 'tostr'... | eq { count { filter_eq { all_rows ; winner 's share ; 8400 } } ; 3 } = true | select the rows whose winner 's share record is equal to 8400 . the number of such rows is 3 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_eq_0': 0, 'all_rows_4': 4, "winner 's share_5": 5, '8400_6': 6, '3_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', "winner 's share_5": "winner 's share", '8400_6': '8400', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], "winner 's share_5": [0], '8400_6': [0], '3_7': [2]} | ['year', 'dates', 'champion', 'country', 'score', 'tournament location', 'purse', "winner 's share"] | [['2013', 'jul 12 - 14', 'wei - ling hsu', 'taiwan', '202 ( - 11 )', 'capital hills at albany', '100000', '15000'], ['2012', 'aug 3 - 5', 'jaclyn sweeney', 'united states', '203 ( - 10 )', 'capital hills at albany', '100000', '15000'], ['2011', 'sep 9 - 11', 'sydnee michaels', 'united states', '202 ( - 8 )', 'capital h... |
list of rugby league stadiums by capacity | https://en.wikipedia.org/wiki/List_of_rugby_league_stadiums_by_capacity | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18735456-2.html.csv | superlative | of the rugby league stadiums , the one with the largest capacity is anz stadium . | {'scope': 'all', 'col_superlative': '2', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'capacity'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; capacity }'}, 'stadium'], 'result': 'anz stadium', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; capacity } ; stadium }'}, 'anz stadium'], 'result': True,... | eq { hop { argmax { all_rows ; capacity } ; stadium } ; anz stadium } = true | select the row whose capacity record of all rows is maximum . the stadium record of this row is anz stadium . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'capacity_5': 5, 'stadium_6': 6, 'anz stadium_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'capacity_5': 'capacity', 'stadium_6': 'stadium', 'anz stadium_7': 'anz stadium'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'capacity_5': [0], 'stadium_6': [1], 'anz stadium_7': [2]} | ['stadium', 'capacity', 'city', 'country', 'home team / s', 'closed ( as a rl stadium )'] | [['anz stadium', '59000', 'brisbane', 'australia', 'brisbane broncos', '2003'], ['sydney sports ground', '35000', 'sydney', 'australia', 'eastern suburbs', '1986'], ['redfern oval', '23000', 'sydney', 'australia', 'south sydney', '1987'], ['stade sébastien charléty', '20000', 'paris', 'france', 'paris saint - germain',... |
norwegian international | https://en.wikipedia.org/wiki/Norwegian_International | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12121208-1.html.csv | count | julienne schenk participated in the women 's singles a three times . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'juliane schenk', 'result': '3', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', "women 's singles", 'juliane schenk'], 'result': None, 'ind': 0, 'tointer': "select the rows whose women 's singles record fuzzily matches to juliane schenk .", 'tostr': "filter_eq { all_rows ; women 's singles ; juliane s... | eq { count { filter_eq { all_rows ; women 's singles ; juliane schenk } } ; 3 } = true | select the rows whose women 's singles record fuzzily matches to juliane schenk . the number of such rows is 3 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, "women 's singles_5": 5, 'juliane schenk_6': 6, '3_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', "women 's singles_5": "women 's singles", 'juliane schenk_6': 'juliane schenk', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], "women 's singles_5": [0], 'juliane schenk_6': [0], '3_7': [2]} | ['year', "men 's singles", "women 's singles", "men 's doubles", "women 's doubles", 'mixed doubles'] | [['2012', 'chou tien - chen', 'sashina vignes waran', 'ruud bosch koen ridder', 'samantha barning eefje muskens', 'jorrit de ruiter samantha barning'], ['2011', 'ville lang', 'linda zechiri', 'rasmus bonde anders kristiansen', 'eva lee paula lynn obanana', 'sam magee chloe magee'], ['2010', 'hans - kristian vittinghus'... |
1960 vfl season | https://en.wikipedia.org/wiki/1960_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10775890-6.html.csv | aggregation | the average away team score achieved was 8.75 on the 28th of may 1960 . | {'scope': 'all', 'col': '4', 'type': 'average', 'result': '8.75', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'away team score'], 'result': '8.75', 'ind': 0, 'tostr': 'avg { all_rows ; away team score }'}, '8.75'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; away team score } ; 8.75 } = true', 'tointer': 'the average of the away team score r... | round_eq { avg { all_rows ; away team score } ; 8.75 } = true | the average of the away team score record of all rows is 8.75 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'away team score_4': 4, '8.75_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'away team score_4': 'away team score', '8.75_5': '8.75'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'away team score_4': [0], '8.75_5': [1]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['melbourne', '17.22 ( 124 )', 'richmond', '4.8 ( 32 )', 'mcg', '27249', '28 may 1960'], ['footscray', '6.11 ( 47 )', 'st kilda', '10.5 ( 65 )', 'western oval', '22126', '28 may 1960'], ['north melbourne', '7.6 ( 48 )', 'hawthorn', '9.8 ( 62 )', 'arden street oval', '8600', '28 may 1960'], ['fitzroy', '8.7 ( 55 )', 'e... |
2009 - 10 alabama crimson tide men 's basketball team | https://en.wikipedia.org/wiki/2009%E2%80%9310_Alabama_Crimson_Tide_men%27s_basketball_team | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-25360865-1.html.csv | comparative | on the 2009-2010 alabama crimson tide men 's basketball team , justin knox was the same height as jamychal green . | {'row_1': '11', 'row_2': '10', 'col': '4', 'col_other': '2', 'relation': 'equal', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'name', 'justin knox'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose name record fuzzily matches to justin knox .', 'tostr': 'filter_eq { all_rows ; name ; justin knox }'}, 'height'], 'result': None, '... | eq { hop { filter_eq { all_rows ; name ; justin knox } ; height } ; hop { filter_eq { all_rows ; name ; jamychal green } ; height } } = true | select the rows whose name record fuzzily matches to justin knox . take the height record of this row . select the rows whose name record fuzzily matches to jamychal green . take the height record of this row . the first record fuzzily matches to the second record . | 5 | 5 | {'str_eq_4': 4, 'result_5': 5, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'name_7': 7, 'justin knox_8': 8, 'height_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'name_11': 11, 'jamychal green_12': 12, 'height_13': 13} | {'str_eq_4': 'str_eq', 'result_5': 'true', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'name_7': 'name', 'justin knox_8': 'justin knox', 'height_9': 'height', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'name_11': 'name', 'jamychal gre... | {'str_eq_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'name_7': [0], 'justin knox_8': [0], 'height_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'name_11': [1], 'jamychal green_12': [1], 'height_13': [3]} | ['', 'name', 'position', 'height', 'weight', 'year', 'home town', 'last school'] | [['1', 'anthony brock', 'guard', '5 - 9', '165', 'senior', 'little rock , ark', 'itawamba cc'], ['2', 'mikhail torrance', 'guard', '6 - 5', '210', 'senior', 'eight mile , ala', 'mary montgomery hs'], ['5', 'tony mitchell', 'forward', '6 - 6', '185', 'freshman', 'swainsboro , ga', 'central park christian hs'], ['10', 'b... |
list of the tudors episodes | https://en.wikipedia.org/wiki/List_of_The_Tudors_episodes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-10413597-5.html.csv | majority | all of the episodes of the tudors were written by michael hirst . | {'scope': 'all', 'col': '6', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'michael hirst', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'written by', 'michael hirst'], 'result': True, 'ind': 0, 'tointer': 'for the written by records of all rows , all of them fuzzily match to michael hirst .', 'tostr': 'all_eq { all_rows ; written by ; michael hirst } = true'} | all_eq { all_rows ; written by ; michael hirst } = true | for the written by records of all rows , all of them fuzzily match to michael hirst . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'written by_3': 3, 'michael hirst_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'written by_3': 'written by', 'michael hirst_4': 'michael hirst'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'written by_3': [0], 'michael hirst_4': [0]} | ['no in series', 'no in season', 'title', 'setting', 'directed by', 'written by', 'us viewers ( million )', 'original air date'] | [['29', '1', 'moment of nostalgia', 'summer 1540', 'dearbhla walsh', 'michael hirst', '0.88', 'april 11 , 2010'], ['30', '2', 'sister', 'winter 1540', 'dearbhla walsh', 'michael hirst', 'n / a', 'april 18 , 2010'], ['31', '3', 'something for you', 'spring 1541', 'dearbhla walsh', 'michael hirst', 'n / a', 'april 25 , 2... |
rowing at the 2008 summer olympics - women 's single sculls | https://en.wikipedia.org/wiki/Rowing_at_the_2008_Summer_Olympics_%E2%80%93_Women%27s_single_sculls | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18662695-9.html.csv | comparative | mayra gonzález had a faster time than camila vargas in the 2008 summer olympics - women 's single sculls . | {'row_1': '4', 'row_2': '5', 'col': '4', 'col_other': '2', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'athlete', 'mayra gonzález'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose athlete record fuzzily matches to mayra gonzález .', 'tostr': 'filter_eq { all_rows ; athlete ; mayra gonzález }'}, 'time'], 're... | less { hop { filter_eq { all_rows ; athlete ; mayra gonzález } ; time } ; hop { filter_eq { all_rows ; athlete ; camila vargas } ; time } } = true | select the rows whose athlete record fuzzily matches to mayra gonzález . take the time record of this row . select the rows whose athlete record fuzzily matches to camila vargas . take the time record of this row . the first record is less than the second record . | 5 | 5 | {'less_4': 4, 'result_5': 5, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'athlete_7': 7, 'mayra gonzález_8': 8, 'time_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'athlete_11': 11, 'camila vargas_12': 12, 'time_13': 13} | {'less_4': 'less', 'result_5': 'true', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'athlete_7': 'athlete', 'mayra gonzález_8': 'mayra gonzález', 'time_9': 'time', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'athlete_11': 'athlete', 'ca... | {'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'athlete_7': [0], 'mayra gonzález_8': [0], 'time_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'athlete_11': [1], 'camila vargas_12': [1], 'time_13': [3]} | ['rank', 'athlete', 'country', 'time', 'notes'] | [['1', 'miroslava knapková', 'czech republic', '7:30.33', 'sa / b'], ['2', 'sophie balmary', 'france', '7:37.01', 'sa / b'], ['3', 'iva obradović', 'serbia', '7:39.16', 'sa / b'], ['4', 'mayra gonzález', 'cuba', '7:45.75', 'sc / d'], ['5', 'camila vargas', 'el salvador', '8:11.79', 'sc / d'], ['6', 'latt shwe zin', 'my... |
1951 in brazilian football | https://en.wikipedia.org/wiki/1951_in_Brazilian_football | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15303773-1.html.csv | comparative | in 1951 brazilian football , palmeiras had fewer goals scored against them than flamengo . | {'row_1': '1', 'row_2': '4', 'col': '7', 'col_other': '2', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'team', 'palmeiras'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose team record fuzzily matches to palmeiras .', 'tostr': 'filter_eq { all_rows ; team ; palmeiras }'}, 'against'], 'result': None, 'ind': 2... | less { hop { filter_eq { all_rows ; team ; palmeiras } ; against } ; hop { filter_eq { all_rows ; team ; flamengo } ; against } } = true | select the rows whose team record fuzzily matches to palmeiras . take the against record of this row . select the rows whose team record fuzzily matches to flamengo . take the against record of this row . the first record is less than the second record . | 5 | 5 | {'less_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'team_7': 7, 'palmeiras_8': 8, 'against_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'team_11': 11, 'flamengo_12': 12, 'against_13': 13} | {'less_4': 'less', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'team_7': 'team', 'palmeiras_8': 'palmeiras', 'against_9': 'against', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'team_11': 'team', 'flamengo_12': 'fla... | {'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'team_7': [0], 'palmeiras_8': [0], 'against_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'team_11': [1], 'flamengo_12': [1], 'against_13': [3]} | ['position', 'team', 'points', 'played', 'drawn', 'lost', 'against', 'difference'] | [['1', 'palmeiras', '10', '7', '0', '2', '14', '11'], ['2', 'corinthians', '10', '7', '2', '1', '12', '8'], ['3', 'bangu', '7', '7', '1', '3', '18', '4'], ['4', 'flamengo', '7', '7', '1', '3', '19', '- 4'], ['5', 'américa', '7', '7', '3', '2', '19', '0'], ['6', 'portuguesa', '7', '7', '1', '3', '23', '- 6'], ['7', 'vas... |
1974 vfl season | https://en.wikipedia.org/wiki/1974_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10869646-17.html.csv | majority | in the games of 1974 vfl season listed the majority of crowds were over 15000 . | {'scope': 'all', 'col': '6', 'most_or_all': 'most', 'criterion': 'greater_than', 'value': '15000', 'subset': None} | {'func': 'most_greater', 'args': ['all_rows', 'crowd', '15000'], 'result': True, 'ind': 0, 'tointer': 'for the crowd records of all rows , most of them are greater than 15000 .', 'tostr': 'most_greater { all_rows ; crowd ; 15000 } = true'} | most_greater { all_rows ; crowd ; 15000 } = true | for the crowd records of all rows , most of them are greater than 15000 . | 1 | 1 | {'most_greater_0': 0, 'result_1': 1, 'all_rows_2': 2, 'crowd_3': 3, '15000_4': 4} | {'most_greater_0': 'most_greater', 'result_1': 'true', 'all_rows_2': 'all_rows', 'crowd_3': 'crowd', '15000_4': '15000'} | {'most_greater_0': [1], 'result_1': [], 'all_rows_2': [0], 'crowd_3': [0], '15000_4': [0]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['essendon', '9.10 ( 64 )', 'footscray', '13.15 ( 93 )', 'windy hill', '16250', '27 july 1974'], ['st kilda', '10.13 ( 73 )', 'north melbourne', '11.16 ( 82 )', 'moorabbin oval', '15954', '27 july 1974'], ['hawthorn', '13.28 ( 106 )', 'fitzroy', '8.10 ( 58 )', 'princes park', '6198', '27 july 1974'], ['melbourne', '15... |
list of animals of farthing wood characters | https://en.wikipedia.org/wiki/List_of_Animals_of_Farthing_Wood_characters | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11206371-1.html.csv | comparative | the rabbits appeared in more seasons of farthing wood than the mole did . | {'row_1': '10', 'row_2': '8', 'col': '6', 'col_other': '1', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'animal name', 'the rabbits'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose animal name record fuzzily matches to the rabbits .', 'tostr': 'filter_eq { all_rows ; animal name ; the rabbits }'}, 'tv se... | greater { hop { filter_eq { all_rows ; animal name ; the rabbits } ; tv seasons } ; hop { filter_eq { all_rows ; animal name ; mole } ; tv seasons } } = true | select the rows whose animal name record fuzzily matches to the rabbits . take the tv seasons record of this row . select the rows whose animal name record fuzzily matches to mole . take the tv seasons record of this row . the first record is greater than the second record . | 5 | 5 | {'greater_4': 4, 'result_5': 5, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'animal name_7': 7, 'the rabbits_8': 8, 'tv seasons_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'animal name_11': 11, 'mole_12': 12, 'tv seasons_13': 13} | {'greater_4': 'greater', 'result_5': 'true', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'animal name_7': 'animal name', 'the rabbits_8': 'the rabbits', 'tv seasons_9': 'tv seasons', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'animal ... | {'greater_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'animal name_7': [0], 'the rabbits_8': [0], 'tv seasons_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'animal name_11': [1], 'mole_12': [1], 'tv seasons_13': [3]} | ['animal name', 'species', 'books', 'tv series', 'gender', 'tv seasons'] | [['fox', 'fox', 'yes', 'yes', 'male', '1 , 2 , 3'], ['badger', 'badger', 'yes', 'yes', 'male', '1 , 2'], ['toad', 'toad', 'yes', 'yes', 'male', '1 , 2 , 3'], ['owl', 'owl', 'yes ( as tawny owl )', 'yes', 'female ( tv ) male ( books )', '1 , 2 , 3'], ['weasel', 'weasel', 'yes', 'yes', 'female ( tv ) male ( books )', '1 ... |
1963 in brazilian football | https://en.wikipedia.org/wiki/1963_in_Brazilian_football | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15244400-2.html.csv | unique | of the teams in the top 5 of the 1963 brazilian football season , only one had more than 3 drawn games . | {'scope': 'subset', 'row': '4', 'col': '5', 'col_other': 'n/a', 'criterion': 'greater_than', 'value': '3', 'subset': {'col': '1', 'criterion': 'less_than_eq', 'value': '5'}} | {'func': 'only', 'args': [{'func': 'filter_greater', 'args': [{'func': 'filter_less_eq', 'args': ['all_rows', 'position', '5'], 'result': None, 'ind': 0, 'tostr': 'filter_less_eq { all_rows ; position ; 5 }', 'tointer': 'select the rows whose position record is less than or equal to 5 .'}, 'drawn', '3'], 'result': None... | only { filter_greater { filter_less_eq { all_rows ; position ; 5 } ; drawn ; 3 } } = true | select the rows whose position record is less than or equal to 5 . among these rows , select the rows whose drawn record is greater than 3 . there is only one such row in the table . | 3 | 3 | {'only_2': 2, 'result_3': 3, 'filter_greater_1': 1, 'filter_less_eq_0': 0, 'all_rows_4': 4, 'position_5': 5, '5_6': 6, 'drawn_7': 7, '3_8': 8} | {'only_2': 'only', 'result_3': 'true', 'filter_greater_1': 'filter_greater', 'filter_less_eq_0': 'filter_less_eq', 'all_rows_4': 'all_rows', 'position_5': 'position', '5_6': '5', 'drawn_7': 'drawn', '3_8': '3'} | {'only_2': [3], 'result_3': [], 'filter_greater_1': [2], 'filter_less_eq_0': [1], 'all_rows_4': [0], 'position_5': [0], '5_6': [0], 'drawn_7': [1], '3_8': [1]} | ['position', 'team', 'points', 'played', 'drawn', 'lost', 'against', 'difference'] | [['1', 'santos', '13', '9', '1', '2', '15', '15'], ['2', 'corinthians', '12', '9', '0', '3', '9', '8'], ['3', 'fluminense', '11', '9', '3', '2', '12', '1'], ['4', 'botafogo', '10', '9', '4', '2', '14', '2'], ['5', 'palmeiras', '10', '9', '2', '3', '12', '0'], ['6', 'portuguesa', '9', '9', '3', '3', '21', '- 3'], ['7', ... |
political appointments system in hong kong | https://en.wikipedia.org/wiki/Political_Appointments_System_in_Hong_Kong | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17964087-1.html.csv | superlative | the oldest person to have been appointed to office in hong kong happened to have been a canadian . | {'scope': 'all', 'col_superlative': '3', 'row_superlative': '7', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '4', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'age at appointment'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; age at appointment }'}, 'foreign nationality'], 'result': 'canadian', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; age at appointment } ; forei... | eq { hop { argmax { all_rows ; age at appointment } ; foreign nationality } ; canadian } = true | select the row whose age at appointment record of all rows is maximum . the foreign nationality record of this row is canadian . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'age at appointment_5': 5, 'foreign nationality_6': 6, 'canadian_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'age at appointment_5': 'age at appointment', 'foreign nationality_6': 'foreign nationality', 'canadian_7': 'canadian'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'age at appointment_5': [0], 'foreign nationality_6': [1], 'canadian_7': [2]} | ['romanised name', 'chinese name', 'age at appointment', 'foreign nationality', 'portfolio attachment', 'govt salary'] | [['chen wei - on , kenneth', '陳維安', '43', 'n / a', 'education', 'hk223585'], ['hui hiu - fai , florence', '許曉暉', '34', 'n / a', 'home affairs', 'hk223585'], ['leung fung - yee , julia', '梁鳳儀', '48', 'british', 'financial services and the treasury', 'hk223585'], ['leung , gabriel matthew', '梁卓偉', '35', 'canadian', 'food... |
2010 fedex cup playoffs | https://en.wikipedia.org/wiki/2010_FedEx_Cup_Playoffs | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-28498999-4.html.csv | unique | england is the only country with only 1 player in the top 9 in the 2010 fedex cup playoffs . | {'scope': 'all', 'row': '3', 'col': '3', 'col_other': 'n/a', 'criterion': 'equal', 'value': 'england', 'subset': None} | {'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'england'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose country record fuzzily matches to england .', 'tostr': 'filter_eq { all_rows ; country ; england }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_ro... | only { filter_eq { all_rows ; country ; england } } = true | select the rows whose country record fuzzily matches to england . there is only one such row in the table . | 2 | 2 | {'only_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, 'country_4': 4, 'england_5': 5} | {'only_1': 'only', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'country_4': 'country', 'england_5': 'england'} | {'only_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'country_4': [0], 'england_5': [0]} | ['', 'player', 'country', 'score', 'to par', 'winnings', 'after', 'before'] | [['1', 'charley hoffman', 'united states', '64 + 67 + 69 + 62 = 262', '- 22', '1350000', '2', '59'], ['t2', 'jason day', 'australia', '63 + 67 + 66 + 71 = 267', '- 17', '560000', '4', '14'], ['t2', 'luke donald', 'england', '65 + 67 + 66 + 69 = 267', '- 17', '560000', '5', '17'], ['t2', 'geoff ogilvy', 'australia', '64... |
1941 vfl season | https://en.wikipedia.org/wiki/1941_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10807673-16.html.csv | majority | all games of the 1941 vfl season were played on the 16th of august . | {'scope': 'all', 'col': '7', 'most_or_all': 'all', 'criterion': 'fuzzily_match', 'value': '16 august', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'date', '16 august'], 'result': True, 'ind': 0, 'tointer': 'for the date records of all rows , all of them fuzzily match to 16 august .', 'tostr': 'all_eq { all_rows ; date ; 16 august } = true'} | all_eq { all_rows ; date ; 16 august } = true | for the date records of all rows , all of them fuzzily match to 16 august . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'date_3': 3, '16 august_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'date_3': 'date', '16 august_4': '16 august'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'date_3': [0], '16 august_4': [0]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['fitzroy', '14.15 ( 99 )', 'richmond', '12.16 ( 88 )', 'brunswick street oval', '11000', '16 august 1941'], ['essendon', '19.17 ( 131 )', 'hawthorn', '14.9 ( 93 )', 'windy hill', '7000', '16 august 1941'], ['carlton', '20.17 ( 137 )', 'st kilda', '11.14 ( 80 )', 'princes park', '8000', '16 august 1941'], ['south melb... |
rugby union at the 2002 asian games | https://en.wikipedia.org/wiki/Rugby_union_at_the_2002_Asian_Games | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14335046-1.html.csv | ordinal | during the rugby union at the 2002 asian games , japan ranked 3rd winning only 1 silver medal . | {'scope': 'all', 'row': '3', 'col': '1', 'order': '3', 'col_other': '2,4', 'max_or_min': 'min_to_max', 'value_mentioned': 'yes', 'subset': None} | {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'nth_min', 'args': ['all_rows', 'rank', '3'], 'result': '3', 'ind': 0, 'tostr': 'nth_min { all_rows ; rank ; 3 }', 'tointer': 'the 3rd minimum rank record of all rows is 3 .'}, '3'], 'result': True, 'ind': 1, 'tostr': 'eq { nth_min { all_rows ; rank ; 3 } ; 3 }'... | and { eq { nth_min { all_rows ; rank ; 3 } ; 3 } ; and { eq { hop { nth_argmin { all_rows ; rank ; 3 } ; nation } ; japan ( jpn ) } ; eq { hop { nth_argmin { all_rows ; rank ; 3 } ; silver } ; 1 } } } = true | the 3rd minimum rank record of all rows is 3 . the nation record of the row with 3rd minimum rank record is japan ( jpn ) . the silver record of the row with 3rd minimum rank record is 1 . | 10 | 9 | {'and_8': 8, 'result_9': 9, 'eq_1': 1, 'nth_min_0': 0, 'all_rows_10': 10, 'rank_11': 11, '3_12': 12, '3_13': 13, 'and_7': 7, 'str_eq_4': 4, 'str_hop_3': 3, 'nth_argmin_2': 2, 'all_rows_14': 14, 'rank_15': 15, '3_16': 16, 'nation_17': 17, 'japan (jpn)_18': 18, 'eq_6': 6, 'num_hop_5': 5, 'silver_19': 19, '1_20': 20} | {'and_8': 'and', 'result_9': 'true', 'eq_1': 'eq', 'nth_min_0': 'nth_min', 'all_rows_10': 'all_rows', 'rank_11': 'rank', '3_12': '3', '3_13': '3', 'and_7': 'and', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'nth_argmin_2': 'nth_argmin', 'all_rows_14': 'all_rows', 'rank_15': 'rank', '3_16': '3', 'nation_17': 'nation',... | {'and_8': [9], 'result_9': [], 'eq_1': [8], 'nth_min_0': [1], 'all_rows_10': [0], 'rank_11': [0], '3_12': [0], '3_13': [1], 'and_7': [8], 'str_eq_4': [7], 'str_hop_3': [4], 'nth_argmin_2': [3, 5], 'all_rows_14': [2], 'rank_15': [2], '3_16': [2], 'nation_17': [3], 'japan (jpn)_18': [4], 'eq_6': [7], 'num_hop_5': [6], 's... | ['rank', 'nation', 'gold', 'silver', 'bronze', 'total'] | [['1', 'south korea ( kor )', '2', '0', '0', '2'], ['2', 'chinese taipei ( tpe )', '0', '1', '1', '2'], ['3', 'japan ( jpn )', '0', '1', '0', '1'], ['4', 'thailand ( tha )', '0', '0', '1', '1'], ['total', 'total', '2', '2', '2', '6']] |
utah jazz all - time roster | https://en.wikipedia.org/wiki/Utah_Jazz_all-time_roster | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11545282-4.html.csv | ordinal | james donaldson is the player with the latest year record of playing for the utah jazz . | {'row': '6', 'col': '4', 'order': '1', 'col_other': '1', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'years for jazz', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; years for jazz ; 1 }'}, 'player'], 'result': 'james donaldson', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; years for jazz ; 1 } ... | eq { hop { nth_argmax { all_rows ; years for jazz ; 1 } ; player } ; james donaldson } = true | select the row whose years for jazz record of all rows is 1st maximum . the player record of this row is james donaldson . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'years for jazz_5': 5, '1_6': 6, 'player_7': 7, 'james donaldson_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'years for jazz_5': 'years for jazz', '1_6': '1', 'player_7': 'player', 'james donaldson_8': 'james donaldson'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'years for jazz_5': [0], '1_6': [0], 'player_7': [1], 'james donaldson_8': [2]} | ['player', 'nationality', 'position', 'years for jazz', 'school / club team'] | [['adrian dantley', 'united states', 'guard - forward', '1979 - 86', 'notre dame'], ['brad davis', 'united states', 'guard', '1979 - 80', 'maryland'], ['darryl dawkins', 'united states', 'center', '1987 - 88', 'maynard evans hs'], ['paul dawkins', 'united states', 'guard', '1979 - 80', 'northern illinois'], ['greg dean... |
albert county , new brunswick | https://en.wikipedia.org/wiki/Albert_County%2C_New_Brunswick | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-170958-2.html.csv | ordinal | the parish in albert county new brunswick with the second highest population is hillsborough . | {'row': '2', 'col': '4', 'order': '2', 'col_other': '1', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'population', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; population ; 2 }'}, 'official name'], 'result': 'hillsborough', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; population ; 2 } ; offici... | eq { hop { nth_argmax { all_rows ; population ; 2 } ; official name } ; hillsborough } = true | select the row whose population record of all rows is 2nd maximum . the official name record of this row is hillsborough . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'population_5': 5, '2_6': 6, 'official name_7': 7, 'hillsborough_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'population_5': 'population', '2_6': '2', 'official name_7': 'official name', 'hillsborough_8': 'hillsborough'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'population_5': [0], '2_6': [0], 'official name_7': [1], 'hillsborough_8': [2]} | ['official name', 'status', 'area km 2', 'population', 'census ranking'] | [['coverdale', 'parish', '236.15', '4401', '769 of 5008'], ['hillsborough', 'parish', '303.73', '1395', '1684 of 5008'], ['elgin', 'parish', '519.38', '968', '2124 of 5008'], ['hopewell', 'parish', '149.32', '643', '2689 of 5008'], ['harvey', 'parish', '276.84', '376', '3372 of 5008'], ['alma', 'parish', '222.79', '0',... |
1967 south african grand prix | https://en.wikipedia.org/wiki/1967_South_African_Grand_Prix | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1122362-1.html.csv | count | at the 1967 south african grand prix , there were 2 drivers who completed 80 laps . | {'scope': 'all', 'criterion': 'equal', 'value': '80', 'result': '2', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'laps', '80'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose laps record is equal to 80 .', 'tostr': 'filter_eq { all_rows ; laps ; 80 }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; laps ... | eq { count { filter_eq { all_rows ; laps ; 80 } } ; 2 } = true | select the rows whose laps record is equal to 80 . the number of such rows is 2 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_eq_0': 0, 'all_rows_4': 4, 'laps_5': 5, '80_6': 6, '2_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'laps_5': 'laps', '80_6': '80', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'laps_5': [0], '80_6': [0], '2_7': [2]} | ['driver', 'constructor', 'laps', 'time / retired', 'grid'] | [['pedro rodrã\xadguez', 'cooper - maserati', '80', '2:05:45.9', '4'], ['john love', 'cooper - climax', '80', '+ 26.4', '5'], ['john surtees', 'honda', '79', '+ 1 lap', '6'], ['denny hulme', 'brabham - repco', '78', '+ 2 laps', '2'], ['bob anderson', 'brabham - climax', '78', '+ 2 laps', '10'], ['jack brabham', 'brabha... |
cryengine | https://en.wikipedia.org/wiki/CryEngine | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1241866-2.html.csv | comparative | merchants of brooklyn was released after crysis warhead was released . | {'row_1': '5', 'row_2': '3', 'col': '2', 'col_other': '1', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'title', 'merchants of brooklyn'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose title record fuzzily matches to merchants of brooklyn .', 'tostr': 'filter_eq { all_rows ; title ; merchants of brooklyn... | greater { hop { filter_eq { all_rows ; title ; merchants of brooklyn } ; year } ; hop { filter_eq { all_rows ; title ; crysis warhead } ; year } } = true | select the rows whose title record fuzzily matches to merchants of brooklyn . take the year record of this row . select the rows whose title record fuzzily matches to crysis warhead . take the year record of this row . the first record is greater than the second record . | 5 | 5 | {'greater_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'title_7': 7, 'merchants of brooklyn_8': 8, 'year_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'title_11': 11, 'crysis warhead_12': 12, 'year_13': 13} | {'greater_4': 'greater', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'title_7': 'title', 'merchants of brooklyn_8': 'merchants of brooklyn', 'year_9': 'year', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'title_11': ... | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'title_7': [0], 'merchants of brooklyn_8': [0], 'year_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'title_11': [1], 'crysis warhead_12': [1], 'year_13': [3]} | ['title', 'year', 'developer', 'publisher', 'platform'] | [['blue mars', '2009 ( open beta )', 'avatar reality', 'avatar reality', 'microsoft windows'], ['crysis', '2007', 'crytek frankfurt', 'electronic arts', 'microsoft windows'], ['crysis warhead', '2008', 'crytek budapest', 'electronic arts', 'microsoft windows'], ['entropia universe', '2003 ( initial version ) 2009 ( cry... |
2010 - 11 atlanta thrashers season | https://en.wikipedia.org/wiki/2010%E2%80%9311_Atlanta_Thrashers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27537518-6.html.csv | majority | in the 2010 -11 atlanta thrashers season , most of the matches at philips arena had o pavelec with the decision . | {'scope': 'subset', 'col': '6', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'o pavelec', 'subset': {'col': '7', 'criterion': 'equal', 'value': 'philips arena'}} | {'func': 'most_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location', 'philips arena'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; location ; philips arena }', 'tointer': 'select the rows whose location record fuzzily matches to philips arena .'}, 'decision', 'o pavelec'], 'result'... | most_eq { filter_eq { all_rows ; location ; philips arena } ; decision ; o pavelec } = true | select the rows whose location record fuzzily matches to philips arena . for the decision records of these rows , most of them fuzzily match to o pavelec . | 2 | 2 | {'most_str_eq_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, 'location_4': 4, 'philips arena_5': 5, 'decision_6': 6, 'o pavelec_7': 7} | {'most_str_eq_1': 'most_str_eq', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'location_4': 'location', 'philips arena_5': 'philips arena', 'decision_6': 'decision', 'o pavelec_7': 'o pavelec'} | {'most_str_eq_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'location_4': [0], 'philips arena_5': [0], 'decision_6': [1], 'o pavelec_7': [1]} | ['game', 'date', 'opponent', 'score', 'first star', 'decision', 'location', 'attendance', 'record', 'points'] | [['26', 'december 2', 'pittsburgh penguins', '2 - 3', 's crosby', 'o pavelec', 'consol energy center', '18223', '13 - 10 - 3', '29'], ['27', 'december 4', 'washington capitals', '3 - 1', 'o pavelec', 'o pavelec', 'verizon center', '18398', '14 - 10 - 3', '31'], ['28', 'december 6', 'nashville predators', '3 - 2 ot', 'z... |
iran at the 1998 asian games | https://en.wikipedia.org/wiki/Iran_at_the_1998_Asian_Games | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10831471-37.html.csv | majority | most of the athletes did not advance to the final in iran at the 1998 asian games . | {'scope': 'all', 'col': '8', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'did not advance', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'final', 'did not advance'], 'result': True, 'ind': 0, 'tointer': 'for the final records of all rows , most of them fuzzily match to did not advance .', 'tostr': 'most_eq { all_rows ; final ; did not advance } = true'} | most_eq { all_rows ; final ; did not advance } = true | for the final records of all rows , most of them fuzzily match to did not advance . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'final_3': 3, 'did not advance_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'final_3': 'final', 'did not advance_4': 'did not advance'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'final_3': [0], 'did not advance_4': [0]} | ['athlete', 'event', 'round 1', 'round 2', 'round 3', 'round 4', 'round 5', 'final'] | [['ali ashkani', '54 kg', 'suwanna w 10 - 0', 'wang l 4 - 9', 'repechage aripov l 2 - 3', 'did not advance', 'did not advance', 'did not advance'], ['sardar pashaei', '58 kg', 'tumasis w 12 - 0', '-', 'khudaiberdiev l 5 - 8', 'repechage nishimi w 3 - 2', 'n / a', '3rd place match sheng l 0 - 3'], ['parviz zeidvand', '6... |
1954 vfl season | https://en.wikipedia.org/wiki/1954_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10773616-18.html.csv | count | there were 6 game venues used during the 1954 vfl season . | {'scope': 'all', 'criterion': 'all', 'value': 'n/a', 'result': '6', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_all', 'args': ['all_rows', 'venue'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose venue record is arbitrary .', 'tostr': 'filter_all { all_rows ; venue }'}], 'result': '6', 'ind': 1, 'tostr': 'count { filter_all { all_rows ; venue } }', ... | eq { count { filter_all { all_rows ; venue } } ; 6 } = true | select the rows whose venue record is arbitrary . the number of such rows is 6 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_all_0': 0, 'all_rows_4': 4, 'venue_5': 5, '6_6': 6} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_all_0': 'filter_all', 'all_rows_4': 'all_rows', 'venue_5': 'venue', '6_6': '6'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_all_0': [1], 'all_rows_4': [0], 'venue_5': [0], '6_6': [2]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['north melbourne', '19.15 ( 129 )', 'st kilda', '12.10 ( 82 )', 'arden street oval', '9500', '28 august 1954'], ['footscray', '17.15 ( 117 )', 'hawthorn', '5.4 ( 34 )', 'western oval', '22896', '28 august 1954'], ['south melbourne', '7.7 ( 49 )', 'melbourne', '14.17 ( 101 )', 'lake oval', '25000', '28 august 1954'], ... |
vilnius marathon | https://en.wikipedia.org/wiki/Vilnius_Marathon | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18564507-1.html.csv | aggregation | the number of gold medals awarded at the vilnius marathon totaled 27 . | {'scope': 'all', 'col': '3', 'type': 'sum', 'result': '27', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'gold'], 'result': '27', 'ind': 0, 'tostr': 'sum { all_rows ; gold }'}, '27'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; gold } ; 27 } = true', 'tointer': 'the sum of the gold record of all rows is 27 .'} | round_eq { sum { all_rows ; gold } ; 27 } = true | the sum of the gold record of all rows is 27 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'gold_4': 4, '27_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'gold_4': 'gold', '27_5': '27'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'gold_4': [0], '27_5': [1]} | ['rank', 'nation', 'gold', 'silver', 'bronze', 'total'] | [['1', 'lithuania', '20', '20', '22', '62'], ['2', 'belarus', '5', '3', '3', '11'], ['3', 'latvia', '1', '1', '2', '4'], ['4', 'kenya', '1', '1', '0', '2'], ['5', 'poland', '0', '1', '0', '1'], ['5', 'germany', '0', '1', '0', '1'], ['5', 'australia', '0', '1', '0', '1'], ['8', 'estonia', '0', '0', '1', '1'], ['8', 'uni... |
memphis grizzlies all - time roster | https://en.wikipedia.org/wiki/Memphis_Grizzlies_all-time_roster | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16494599-3.html.csv | superlative | pete chilcutt was the first of these players to join the grizzlies . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '5', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '1', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmin', 'args': ['all_rows', 'years for grizzlies'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; years for grizzlies }'}, 'player'], 'result': 'pete chilcutt', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; years for grizzlies } ; player }'}... | eq { hop { argmin { all_rows ; years for grizzlies } ; player } ; pete chilcutt } = true | select the row whose years for grizzlies record of all rows is minimum . the player record of this row is pete chilcutt . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'years for grizzlies_5': 5, 'player_6': 6, 'pete chilcutt_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'years for grizzlies_5': 'years for grizzlies', 'player_6': 'player', 'pete chilcutt_7': 'pete chilcutt'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'years for grizzlies_5': [0], 'player_6': [1], 'pete chilcutt_7': [2]} | ['player', 'nationality', 'position', 'years for grizzlies', 'school / club team'] | [['brian cardinal', 'united states', 'forward', '2004 - 2008', 'purdue'], ['rodney carney', 'united states', 'forward', '2011', 'memphis'], ['antoine carr', 'united states', 'forward / center', '1999 - 2000', 'wichita state'], ['demarre carroll', 'united states', 'forward', '2009 - 2012', 'missouri'], ['pete chilcutt',... |
eren derdiyok | https://en.wikipedia.org/wiki/Eren_Derdiyok | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12318000-2.html.csv | majority | most of the competitions for eren derdiyok were in the category of friendly competition . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'friendly', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'competition', 'friendly'], 'result': True, 'ind': 0, 'tointer': 'for the competition records of all rows , most of them fuzzily match to friendly .', 'tostr': 'most_eq { all_rows ; competition ; friendly } = true'} | most_eq { all_rows ; competition ; friendly } = true | for the competition records of all rows , most of them fuzzily match to friendly . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'competition_3': 3, 'friendly_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'competition_3': 'competition', 'friendly_4': 'friendly'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'competition_3': [0], 'friendly_4': [0]} | ['date', 'venue', 'score', 'result', 'competition'] | [['6 february 2008', 'london , england', '1 - 1', '2 - 1', 'friendly'], ['9 september 2009', 'riga , latvia', '2 - 2', '2 - 2', '2010 fifa world cup qualification'], ['10 august 2011', 'vaduz , liechtenstein', '1 - 0', '1 - 2', 'friendly'], ['11 october 2011', 'basel , switzerland', '1 - 0', '2 - 0', 'uefa euro 2012 qu... |
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