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1999 belarusian premier league | https://en.wikipedia.org/wiki/1999_Belarusian_Premier_League | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14746581-1.html.csv | unique | bate was the only team in the 1999 belarusian premier league to be located in borisov . | {'scope': 'all', 'row': '2', 'col': '2', 'col_other': '1', 'criterion': 'equal', 'value': 'borisov', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location', 'borisov'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose location record fuzzily matches to borisov .', 'tostr': 'filter_eq { all_rows ; location ; borisov }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; location ; borisov } }', 'tointer': 'select the rows whose location record fuzzily matches to borisov . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location', 'borisov'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose location record fuzzily matches to borisov .', 'tostr': 'filter_eq { all_rows ; location ; borisov }'}, 'team'], 'result': 'bate', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; location ; borisov } ; team }'}, 'bate'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; location ; borisov } ; team } ; bate }', 'tointer': 'the team record of this unqiue row is bate .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; location ; borisov } } ; eq { hop { filter_eq { all_rows ; location ; borisov } ; team } ; bate } } = true', 'tointer': 'select the rows whose location record fuzzily matches to borisov . there is only one such row in the table . the team record of this unqiue row is bate .'} | and { only { filter_eq { all_rows ; location ; borisov } } ; eq { hop { filter_eq { all_rows ; location ; borisov } ; team } ; bate } } = true | select the rows whose location record fuzzily matches to borisov . there is only one such row in the table . the team record of this unqiue row is bate . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'location_7': 7, 'borisov_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'team_9': 9, 'bate_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', 'borisov_8': 'borisov', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'team_9': 'team', 'bate_10': 'bate'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'location_7': [0], 'borisov_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'team_9': [2], 'bate_10': [3]} | ['team', 'location', 'venue', 'capacity', 'position in 1998'] | [['dnepr - transmash', 'mogilev', 'spartak , mogilev', '11200', '1'], ['bate', 'borisov', 'city stadium , borisov', '5500', '2'], ['belshina', 'bobruisk', 'spartak , bobruisk', '3550', '3'], ['lokomotiv - 96', 'vitebsk', 'central , vitebsk', '8300', '4'], ['gomel', 'gomel', 'central , gomel', '11800', '5'], ['slavia', 'mozyr', 'yunost , mozyr', '5500', '6'], ['torpedo - maz', 'minsk', 'torpedo , minsk', '5200', '7'], ['dinamo minsk', 'minsk', 'dinamo , minsk', '41040', '8'], ['dinamo brest', 'brest', 'dinamo , brest', '10080', '9'], ['neman - belcard', 'grodno', 'neman', '6300', '10'], ['shakhtyor', 'soligorsk', 'stroitel', '5000', '11'], ['torpedo - kadino', 'mogilev', 'torpedo , mogilev', '3500', '12'], ['naftan - devon', 'novopolotsk', 'atlant', '6500', '13'], ['molodechno', 'molodechno', 'city stadium , molodechno', '5500', '14'], ['lida', 'lida', 'city stadium , lida', '4000', 'first league , 1'], ['svisloch - krovlya', 'osipovichi', 'yunost , osipovichi', '4000', 'first league , 2']] |
1971 vfl season | https://en.wikipedia.org/wiki/1971_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10826072-12.html.csv | majority | the crowd was less than 20000 for most of the games on june 19 of the 71 vfl season . | {'scope': 'all', 'col': '6', 'most_or_all': 'most', 'criterion': 'less_than', 'value': '20000', 'subset': None} | {'func': 'most_less', 'args': ['all_rows', 'crowd', '20000'], 'result': True, 'ind': 0, 'tointer': 'for the crowd records of all rows , most of them are less than 20000 .', 'tostr': 'most_less { all_rows ; crowd ; 20000 } = true'} | most_less { all_rows ; crowd ; 20000 } = true | for the crowd records of all rows , most of them are less than 20000 . | 1 | 1 | {'most_less_0': 0, 'result_1': 1, 'all_rows_2': 2, 'crowd_3': 3, '20000_4': 4} | {'most_less_0': 'most_less', 'result_1': 'true', 'all_rows_2': 'all_rows', 'crowd_3': 'crowd', '20000_4': '20000'} | {'most_less_0': [1], 'result_1': [], 'all_rows_2': [0], 'crowd_3': [0], '20000_4': [0]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['carlton', '16.18 ( 114 )', 'north melbourne', '3.5 ( 23 )', 'princes park', '13300', '19 june 1971'], ['st kilda', '14.15 ( 99 )', 'geelong', '3.3 ( 21 )', 'moorabbin oval', '14181', '19 june 1971'], ['richmond', '6.11 ( 47 )', 'fitzroy', '8.17 ( 65 )', 'mcg', '24831', '19 june 1971'], ['hawthorn', '14.20 ( 104 )', 'essendon', '11.5 ( 71 )', 'glenferrie oval', '14181', '19 june 1971'], ['footscray', '8.15 ( 63 )', 'collingwood', '6.10 ( 46 )', 'western oval', '21188', '19 june 1971'], ['melbourne', '6.13 ( 49 )', 'south melbourne', '2.6 ( 18 )', 'vfl park', '12528', '19 june 1971']] |
sweeney todd : the demon barber of fleet street | https://en.wikipedia.org/wiki/Sweeney_Todd%3A_The_Demon_Barber_of_Fleet_Street | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1794747-8.html.csv | count | sweeney todd : the demon barber of fleet street won 3 awards in 2013 . | {'scope': 'subset', 'criterion': 'equal', 'value': 'won', 'result': '3', 'col': '5', 'subset': {'col': '1', 'criterion': 'equal', 'value': '2013'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'year', '2013'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; year ; 2013 }', 'tointer': 'select the rows whose year record is equal to 2013 .'}, 'result', 'won'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose year record is equal to 2013 . among these rows , select the rows whose result record fuzzily matches to won .', 'tostr': 'filter_eq { filter_eq { all_rows ; year ; 2013 } ; result ; won }'}], 'result': '3', 'ind': 2, 'tostr': 'count { filter_eq { filter_eq { all_rows ; year ; 2013 } ; result ; won } }', 'tointer': 'select the rows whose year record is equal to 2013 . among these rows , select the rows whose result record fuzzily matches to won . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_eq { filter_eq { all_rows ; year ; 2013 } ; result ; won } } ; 3 } = true', 'tointer': 'select the rows whose year record is equal to 2013 . among these rows , select the rows whose result record fuzzily matches to won . the number of such rows is 3 .'} | eq { count { filter_eq { filter_eq { all_rows ; year ; 2013 } ; result ; won } } ; 3 } = true | select the rows whose year record is equal to 2013 . among these rows , select the rows whose result record fuzzily matches to won . the number of such rows is 3 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_str_eq_1': 1, 'filter_eq_0': 0, 'all_rows_5': 5, 'year_6': 6, '2013_7': 7, 'result_8': 8, 'won_9': 9, '3_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_str_eq_1': 'filter_str_eq', 'filter_eq_0': 'filter_eq', 'all_rows_5': 'all_rows', 'year_6': 'year', '2013_7': '2013', 'result_8': 'result', 'won_9': 'won', '3_10': '3'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_str_eq_1': [2], 'filter_eq_0': [1], 'all_rows_5': [0], 'year_6': [0], '2013_7': [0], 'result_8': [1], 'won_9': [1], '3_10': [3]} | ['year', 'award ceremony', 'category', 'nominee', 'result'] | [['2012', 'evening standard award', 'best musical', 'best musical', 'won'], ['2013', 'laurence olivier award', 'best musical revival', 'best musical revival', 'won'], ['2013', 'laurence olivier award', 'best actor in a musical', 'michael ball', 'won'], ['2013', 'laurence olivier award', 'best actress in a musical', 'imelda staunton', 'won'], ['2013', 'laurence olivier award', 'best costume design', 'anthony ward', 'nominated'], ['2013', 'laurence olivier award', 'best lighting design', 'mark henderson', 'nominated'], ['2013', 'laurence olivier award', 'best sound design', 'paul groothuis', 'nominated']] |
gymnastics at the 2008 summer olympics - men 's pommel horse | https://en.wikipedia.org/wiki/Gymnastics_at_the_2008_Summer_Olympics_%E2%80%93_Men%27s_pommel_horse | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18662018-2.html.csv | aggregation | the average score by all the gymnasts in the 2008 summer olympics - men 's pommel horse was 15.419 . | {'scope': 'all', 'col': '5', 'type': 'average', 'result': '15.419', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'total'], 'result': '15.419', 'ind': 0, 'tostr': 'avg { all_rows ; total }'}, '15.419'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; total } ; 15.419 } = true', 'tointer': 'the average of the total record of all rows is 15.419 .'} | round_eq { avg { all_rows ; total } ; 15.419 } = true | the average of the total record of all rows is 15.419 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'total_4': 4, '15.419_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'total_4': 'total', '15.419_5': '15.419'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'total_4': [0], '15.419_5': [1]} | ['position', 'gymnast', 'a score', 'b score', 'total'] | [['1', 'xiao qin ( chn )', '6.400', '9.600', '16.000'], ['2', 'josã luis fuentes bustamante ( ven )', '6.500', '9.025', '15.525'], ['3', 'filip ude ( cro )', '6.400', '9.075', '15.475'], ['4', 'yang wei ( chn )', '6.100', '9.325', '15.425'], ['5', 'louis smith ( gbr )', '6.500', '8.825', '15.325'], ['6', 'alexander artemev ( usa )', '6.100', '9.150', '15.250'], ['7', 'hiroyuki tomita ( jpn )', '6.100', '9.075', '15.175'], ['8', 'kim ji - hoon ( kor )', '6.100', '9.075', '15.175']] |
list of argumental episodes | https://en.wikipedia.org/wiki/List_of_Argumental_episodes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-19930660-1.html.csv | count | jimmy carr was a guest on argumental season 1 two times . | {'scope': 'all', 'criterion': 'equal', 'value': 'jimmy carr', 'result': '1', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'rufus guest', 'jimmy carr'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose rufus guest record fuzzily matches to jimmy carr .', 'tostr': 'filter_eq { all_rows ; rufus guest ; jimmy carr }'}], 'result': '1', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; rufus guest ; jimmy carr } }', 'tointer': 'select the rows whose rufus guest record fuzzily matches to jimmy carr . the number of such rows is 1 .'}, '1'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; rufus guest ; jimmy carr } } ; 1 } = true', 'tointer': 'select the rows whose rufus guest record fuzzily matches to jimmy carr . the number of such rows is 1 .'} | eq { count { filter_eq { all_rows ; rufus guest ; jimmy carr } } ; 1 } = true | select the rows whose rufus guest record fuzzily matches to jimmy carr . the number of such rows is 1 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'rufus guest_5': 5, 'jimmy carr_6': 6, '1_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'rufus guest_5': 'rufus guest', 'jimmy carr_6': 'jimmy carr', '1_7': '1'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'rufus guest_5': [0], 'jimmy carr_6': [0], '1_7': [2]} | ['episode', 'first broadcast', 'rufus guest', 'marcus guest', 'winner'] | [['1x01', '27 october 2008', 'dara ó briain', 'mark watson', 'blue ( 3 - 2 )'], ['1x02', '3 november 2008', 'jimmy carr', 'ed byrne', 'blue ( 3 - 2 )'], ['1x03', '10 november 2008', 'johnny vegas', 'robin ince', 'red ( 3 - 1 )'], ['1x04', '17 november 2008', 'frankie boyle', 'phill jupitus', 'blue ( 3 - 2 )'], ['1x05', '24 november 2008', 'hugh dennis', 'richard herring', 'blue ( 3 - 2 )'], ['1x06', '1 december 2008', 'andrew maxwell', 'sue perkins', 'blue ( 2 - 2 )'], ['1x07', '8 december 2008', 'charlie higson', 'jimmy carr', 'red ( 2 - 2 )'], ['1x08', '15 december 2008', 'andy parsons', 'mark watson', 'red ( 3 - 2 )'], ['1x09', '5 january 2009', 'phill jupitus', 'frankie boyle', 'red ( 3 - 2 )'], ['1x10', '12 january 2009', 'patrick kielty', 'lucy porter', 'blue ( 3 - 1 )'], ['1x11', '19 january 2009', 'sue perkins', 'jason byrne', 'blue ( 4 - 1 )'], ['1x12', '26 january 2009', 'lucy porter', 'jarred christmas', 'red ( 3 - 2 )']] |
1960 cleveland browns season | https://en.wikipedia.org/wiki/1960_Cleveland_Browns_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10651740-2.html.csv | count | 3 of the games played in october in the 1960 cleveland brown season were wins . | {'scope': 'subset', 'criterion': 'fuzzily_match', 'value': 'w', 'result': '3', 'col': '4', 'subset': {'col': '2', 'criterion': 'fuzzily_match', 'value': 'october'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', 'october'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; date ; october }', 'tointer': 'select the rows whose date record fuzzily matches to october .'}, 'result', 'w'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose date record fuzzily matches to october . among these rows , select the rows whose result record fuzzily matches to w .', 'tostr': 'filter_eq { filter_eq { all_rows ; date ; october } ; result ; w }'}], 'result': '3', 'ind': 2, 'tostr': 'count { filter_eq { filter_eq { all_rows ; date ; october } ; result ; w } }', 'tointer': 'select the rows whose date record fuzzily matches to october . among these rows , select the rows whose result record fuzzily matches to w . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_eq { filter_eq { all_rows ; date ; october } ; result ; w } } ; 3 } = true', 'tointer': 'select the rows whose date record fuzzily matches to october . among these rows , select the rows whose result record fuzzily matches to w . the number of such rows is 3 .'} | eq { count { filter_eq { filter_eq { all_rows ; date ; october } ; result ; w } } ; 3 } = true | select the rows whose date record fuzzily matches to october . among these rows , select the rows whose result record fuzzily matches to w . the number of such rows is 3 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_str_eq_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'date_6': 6, 'october_7': 7, 'result_8': 8, 'w_9': 9, '3_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_str_eq_1': 'filter_str_eq', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'date_6': 'date', 'october_7': 'october', 'result_8': 'result', 'w_9': 'w', '3_10': '3'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_str_eq_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'date_6': [0], 'october_7': [0], 'result_8': [1], 'w_9': [1], '3_10': [3]} | ['week', 'date', 'opponent', 'result', 'attendance'] | [['1', 'september 25 , 1960', 'philadelphia eagles', 'w 41 - 24', '56303'], ['2', 'october 2 , 1960', 'pittsburgh steelers', 'w 28 - 20', '67692'], ['4', 'october 16 , 1960', 'dallas cowboys', 'w 48 - 7', '28500'], ['5', 'october 23 , 1960', 'philadelphia eagles', 'l 31 - 29', '64850'], ['6', 'october 30 , 1960', 'washington redskins', 'w 31 - 10', '32086'], ['7', 'november 6 , 1960', 'new york giants', 'l 17 - 13', '82872'], ['8', 'november 13 , 1960', 'st louis cardinals', 'w 28 - 27', '49192'], ['9', 'november 20 , 1960', 'pittsburgh steelers', 'l 14 - 10', '35215'], ['10', 'november 27 , 1960', 'st louis cardinals', 't 17 - 17', '26146'], ['11', 'december 4 , 1960', 'washington redskins', 'w 27 - 16', '35211'], ['12', 'december 11 , 1960', 'chicago bears', 'w 42 - 0', '38155'], ['13', 'december 18 , 1960', 'new york giants', 'w 48 - 34', '56517']] |
geoff lees | https://en.wikipedia.org/wiki/Geoff_Lees | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1228378-2.html.csv | majority | geoff lees drove cars with ford v8 engines in all of his formula one world championship races from 1978 to 1982 . | {'scope': 'all', 'col': '4', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'ford v8', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'engine', 'ford v8'], 'result': True, 'ind': 0, 'tointer': 'for the engine records of all rows , all of them fuzzily match to ford v8 .', 'tostr': 'all_eq { all_rows ; engine ; ford v8 } = true'} | all_eq { all_rows ; engine ; ford v8 } = true | for the engine records of all rows , all of them fuzzily match to ford v8 . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'engine_3': 3, 'ford v8_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'engine_3': 'engine', 'ford v8_4': 'ford v8'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'engine_3': [0], 'ford v8_4': [0]} | ['year', 'entrant', 'chassis', 'engine', 'points'] | [['1978', 'mario deliotti racing', 'ensign n175', 'ford v8', '0'], ['1979', 'candy tyrrell team', 'tyrrell 009', 'ford v8', '0'], ['1980', 'shadow cars', 'shadow dn11', 'ford v8', '0'], ['1980', 'shadow cars', 'shadow dn12', 'ford v8', '0'], ['1980', 'unipart racing team', 'ensign n180', 'ford v8', '0'], ['1980', 'ram theodore', 'williams fw07b', 'ford v8', '0'], ['1982', 'theodore racing team', 'theodore ty02', 'ford v8', '0'], ['1982', 'john player team lotus', 'lotus 91', 'ford v8', '0']] |
usa today all - usa high school basketball team | https://en.wikipedia.org/wiki/USA_Today_All-USA_high_school_basketball_team | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11677760-33.html.csv | majority | most of the all-usa high school basketball team players were not drafted into the nba . | {'scope': 'all', 'col': '6', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': 'has not yet declared for the nba draft', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'nba draft', 'has not yet declared for the nba draft'], 'result': True, 'ind': 0, 'tointer': 'for the nba draft records of all rows , most of them fuzzily match to has not yet declared for the nba draft .', 'tostr': 'most_eq { all_rows ; nba draft ; has not yet declared for the nba draft } = true'} | most_eq { all_rows ; nba draft ; has not yet declared for the nba draft } = true | for the nba draft records of all rows , most of them fuzzily match to has not yet declared for the nba draft . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'nba draft_3': 3, 'has not yet declared for the nba draft_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'nba draft_3': 'nba draft', 'has not yet declared for the nba draft_4': 'has not yet declared for the nba draft'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'nba draft_3': [0], 'has not yet declared for the nba draft_4': [0]} | ['player', 'height', 'school', 'hometown', 'college', 'nba draft'] | [['tyler lewis', "5 ' 11", 'oak hill academy', 'statesville , nc', 'nc state', 'has not yet declared for the nba draft'], ['kasey hill', "6 ' 1", 'montverde academy', 'eustis , fl', 'florida', 'not eligible for the draft until 2014'], ['amile jefferson', "6 ' 9", "friends ' central school", 'wynnewood , pa', 'duke', 'has not yet declared for the nba draft'], ['anthony bennett', "6 ' 8", 'findlay prep', 'brampton , on', 'unlv', '1st round - 1st pick of 2013 draft ( cavaliers )'], ['perry ellis', "6 ' 8", 'wichita heights high school', 'wichita , ks', 'kansas', 'has not yet declared for the nba draft']] |
strikeout | https://en.wikipedia.org/wiki/Strikeout | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-242813-2.html.csv | count | three of the major league baseball pitchers played in the aa league . | {'scope': 'all', 'criterion': 'equal', 'value': 'aa', 'result': '3', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'league', 'aa'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose league record fuzzily matches to aa .', 'tostr': 'filter_eq { all_rows ; league ; aa }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; league ; aa } }', 'tointer': 'select the rows whose league record fuzzily matches to aa . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; league ; aa } } ; 3 } = true', 'tointer': 'select the rows whose league record fuzzily matches to aa . the number of such rows is 3 .'} | eq { count { filter_eq { all_rows ; league ; aa } } ; 3 } = true | select the rows whose league record fuzzily matches to aa . 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, 'league_5': 5, 'aa_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', 'league_5': 'league', 'aa_6': 'aa', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'league_5': [0], 'aa_6': [0], '3_7': [2]} | ['pitcher', 'strikeouts', 'season', 'team', 'league', 'overall rank'] | [['matt kilroy', '513', '1886', 'baltimore orioles', 'aa', '1'], ['toad ramsey', '499', '1886', 'louisville colonels', 'aa', '2'], ['dupee shaw', '451', '1884', 'detroit wolverines / boston reds', 'nl / ua', '4'], ['old hoss radbourn', '441', '1884', 'providence grays', 'nl', '5'], ['charlie buffington', '417', '1884', 'boston beaneaters', 'nl', '6'], ['guy hecker', '385', '1884', 'louisville eclipse', 'aa', '7'], ['nolan ryan', '383', '1973', 'california angels', 'al', '8'], ['sandy koufax', '382', '1965', 'los angeles dodgers', 'nl', '9']] |
iowa corn cy - hawk series | https://en.wikipedia.org/wiki/Iowa_Corn_Cy-Hawk_Series | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14175075-8.html.csv | comparative | men 's cross country was played earlier than women 's gymnastics in the iowa corn cy - hawk series . | {'row_1': '4', 'row_2': '10', 'col': '1', 'col_other': '3', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'sport', 'm cross country'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose sport record fuzzily matches to m cross country .', 'tostr': 'filter_eq { all_rows ; sport ; m cross country }'}, 'date'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; sport ; m cross country } ; date }', 'tointer': 'select the rows whose sport record fuzzily matches to m cross country . take the date record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'sport', 'w gymnastics'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose sport record fuzzily matches to w gymnastics .', 'tostr': 'filter_eq { all_rows ; sport ; w gymnastics }'}, 'date'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; sport ; w gymnastics } ; date }', 'tointer': 'select the rows whose sport record fuzzily matches to w gymnastics . take the date record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; sport ; m cross country } ; date } ; hop { filter_eq { all_rows ; sport ; w gymnastics } ; date } } = true', 'tointer': 'select the rows whose sport record fuzzily matches to m cross country . take the date record of this row . select the rows whose sport record fuzzily matches to w gymnastics . take the date record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; sport ; m cross country } ; date } ; hop { filter_eq { all_rows ; sport ; w gymnastics } ; date } } = true | select the rows whose sport record fuzzily matches to m cross country . take the date record of this row . select the rows whose sport record fuzzily matches to w gymnastics . 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, 'sport_7': 7, 'm cross country_8': 8, 'date_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'sport_11': 11, 'w gymnastics_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', 'sport_7': 'sport', 'm cross country_8': 'm cross country', 'date_9': 'date', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'sport_11': 'sport', 'w gymnastics_12': 'w gymnastics', 'date_13': 'date'} | {'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'sport_7': [0], 'm cross country_8': [0], 'date_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'sport_11': [1], 'w gymnastics_12': [1], 'date_13': [3]} | ['date', 'site', 'sport', 'winning team', 'series'] | [['september 10 , 2010', 'iowa city', 'volleyball', 'iowa state', 'iowa state 2 - 0'], ['september 11 , 2010', 'iowa city', 'football', 'iowa', 'iowa 3 - 2'], ['september 17 , 2010', 'ames', 'w soccer', 'iowa', 'iowa 5 - 2'], ['november 13 , 2010', 'springfield', 'm cross country', 'iowa state', 'iowa 5 - 4'], ['november 13 , 2010', 'springfield', 'w cross country', 'iowa state', 'iowa state 6 - 5'], ['december 3 , 2010', 'iowa city', 'wrestling', 'iowa', 'iowa 7 - 6'], ['december 9 , 2010', 'iowa city', 'w basketball', 'iowa', 'iowa 9 - 6'], ['december 10 , 2010', 'iowa city', 'm basketball', 'iowa state', 'iowa 9 - 8'], ['december 10 , 2010', 'iowa city', 'w swimming', 'iowa', 'iowa 11 - 8'], ['february 18 , 2011', 'ames', 'w gymnastics', 'iowa state', 'iowa 11 - 10'], ['february 25 , 2011', 'iowa city', 'w gymnastics', 'iowa', 'iowa 13 - 10'], ['april 20 , 2011', 'iowa city', 'softball', 'iowa', 'iowa 15 - 10'], ['may 5 , 2011', 'iowa city', 'academics', 'iowa state', 'iowa 15 - 11']] |
intel core | https://en.wikipedia.org/wiki/Intel_Core | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-24538587-13.html.csv | majority | most of intel core cpus have an l3 cache of below 10 mb . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'less_than', 'value': '10', 'subset': None} | {'func': 'most_less', 'args': ['all_rows', 'l3 cache', '10'], 'result': True, 'ind': 0, 'tointer': 'for the l3 cache records of all rows , most of them are less than 10 .', 'tostr': 'most_less { all_rows ; l3 cache ; 10 } = true'} | most_less { all_rows ; l3 cache ; 10 } = true | for the l3 cache records of all rows , most of them are less than 10 . | 1 | 1 | {'most_less_0': 0, 'result_1': 1, 'all_rows_2': 2, 'l3 cache_3': 3, '10_4': 4} | {'most_less_0': 'most_less', 'result_1': 'true', 'all_rows_2': 'all_rows', 'l3 cache_3': 'l3 cache', '10_4': '10'} | {'most_less_0': [1], 'result_1': [], 'all_rows_2': [0], 'l3 cache_3': [0], '10_4': [0]} | ['codename ( main article )', 'brand name ( list )', 'cores', 'l3 cache', 'socket', 'tdp', 'process', 'i / o bus', 'release date'] | [['ivy bridge ( desktop )', 'core i7 - 37xx , i7 - 37xxk', '4', '8 mb', 'lga 1155', '77 w', '22 nm', 'direct media interface , integrated gpu', 'april 2012'], ['ivy bridge ( desktop )', 'core i7 - 37xxs', '4', '8 mb', 'lga 1155', '65 w', '22 nm', 'direct media interface , integrated gpu', 'april 2012'], ['ivy bridge ( desktop )', 'core i7 - 37xxt', '4', '8 mb', 'lga 1155', '45 w', '22 nm', 'direct media interface , integrated gpu', 'april 2012'], ['sandy bridge - e ( desktop )', 'core i7 - 39xxx', '6', '15 mb', 'lga 2011', '130 w', '32 nm', 'direct media interface', 'november 2011'], ['sandy bridge - e ( desktop )', 'core i7 - 39xxk', '6', '12 mb', 'lga 2011', '130 w', '32 nm', 'direct media interface', 'november 2011'], ['sandy bridge - e ( desktop )', 'core i7 - 38xx', '4', '10 mb', 'lga 2011', '130 w', '32 nm', 'direct media interface', 'november 2011'], ['sandy bridge ( desktop )', 'core i7 - 2xxxk , i7 - 2xxx', '4', '8 mb', 'lga 1155', '95 w', '32 nm', 'direct media interface , integrated gpu', 'january 2011'], ['sandy bridge ( desktop )', 'core i7 - 2xxxs', '4', '8 mb', 'lga 1155', '65 w', '32 nm', 'direct media interface , integrated gpu', 'january 2011'], ['ivy bridge ( mobile )', 'core i7 - 3xx9y', '2', '4 mb', 'rpga - 988b bga - 1023', '13 w', '22 nm', 'direct media interface , integrated gpu', 'january 2013'], ['ivy bridge ( mobile )', 'core i7 - 3xx7u , i7 - 3xx7ue', '2', '4 mb', 'rpga - 988b bga - 1023', '17 w', '22 nm', 'direct media interface , integrated gpu', 'april 2012'], ['ivy bridge ( mobile )', 'core i7 - 3xxxle', '2', '4 mb', 'rpga - 988b bga - 1023', '25 w', '22 nm', 'direct media interface , integrated gpu', 'april 2012'], ['ivy bridge ( mobile )', 'core i7 - 3xxxm', '2', '4 mb', 'rpga - 988b bga - 1023', '35 w', '22 nm', 'direct media interface , integrated gpu', 'april 2012'], ['ivy bridge ( mobile )', 'core i7 - 3xx2qm , i7 - 3xx2qe', '4', '6 mb', 'rpga - 988b bga - 1023', '35 w', '22 nm', 'direct media interface , integrated gpu', 'april 2012'], ['ivy bridge ( mobile )', 'core i7 - 38xxqm', '4', '8 mb', 'rpga - 988b bga - 1023', '45 w', '22 nm', 'direct media interface , integrated gpu', 'april 2012'], ['ivy bridge ( mobile )', 'core i7 - 3xxxxm', '4', '8 mb', 'rpga - 988b bga - 1023', '55 w', '22 nm', 'direct media interface , integrated gpu', 'april 2012'], ['sandy bridge ( mobile )', 'core i7 - 2xxxxm', '4', '8 mb', 'rpga - 988b bga - 1023', '55 w', '32 nm', 'direct media interface , integrated gpu', 'january 2011'], ['sandy bridge ( mobile )', 'core i7 - 28xxqm', '4', '8 mb', 'rpga - 988b bga - 1023', '45 w', '32 nm', 'direct media interface , integrated gpu', 'january 2011'], ['sandy bridge ( mobile )', 'core i7 - 2xxxqe , i7 - 26xxqm , i7 - 27xxqm', '4', '6 mb', 'rpga - 988b bga - 1023', '45 w', '32 nm', 'direct media interface , integrated gpu', 'january 2011'], ['sandy bridge ( mobile )', 'core i7 - 2xx0 m', '2', '4 mb', 'rpga - 988b bga - 1023', '35 w', '32 nm', 'direct media interface , integrated gpu', 'february 2011'], ['sandy bridge ( mobile )', 'core i7 - 2xx9 m', '2', '4 mb', 'bga - 1023', '25 w', '32 nm', 'direct media interface , integrated gpu', 'february 2011']] |
1986 - 87 north west counties football league | https://en.wikipedia.org/wiki/1986%E2%80%9387_North_West_Counties_Football_League | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17785973-2.html.csv | aggregation | in north west counties football league 's 1986-97 season , teams on average had 7.9 drawn matches . | {'scope': 'all', 'col': '4', 'type': 'average', 'result': '7.9', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'drawn'], 'result': '7.9', 'ind': 0, 'tostr': 'avg { all_rows ; drawn }'}, '7.9'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; drawn } ; 7.9 } = true', 'tointer': 'the average of the drawn record of all rows is 7.9 .'} | round_eq { avg { all_rows ; drawn } ; 7.9 } = true | the average of the drawn record of all rows is 7.9 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'drawn_4': 4, '7.9_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'drawn_4': 'drawn', '7.9_5': '7.9'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'drawn_4': [0], '7.9_5': [1]} | ['position', 'team', 'played', 'drawn', 'lost', 'goals for', 'goals against', 'goal difference', 'points 1'] | [['1', 'droylsden', '34', '8', '6', '79', '42', '+ 37', '48'], ['2', 'warrington town', '34', '13', '5', '48', '34', '+ 14', '45'], ['3', 'ashton united', '34', '6', '9', '73', '45', '+ 28', '44'], ['4', 'wren rovers', '34', '8', '8', '65', '39', '+ 26', '44'], ['5', 'colwyn bay', '34', '9', '8', '61', '43', '+ 18', '43'], ['6', 'darwen', '34', '8', '11', '45', '47', '2', '38'], ['7', 'chadderton', '34', '9', '11', '52', '47', '+ 5', '37'], ['8', 'colne dynamoes', '34', '8', '12', '57', '44', '+ 13', '36'], ['9', 'skelmersdale united', '34', '10', '11', '52', '53', '1', '36'], ['10', 'ellesmere port & neston', '34', '5', '14', '68', '54', '+ 14', '35'], ['11', 'formby', '34', '7', '14', '54', '55', '1', '33'], ['12', 'blackpool mechanics', '34', '8', '14', '56', '64', '8', '32'], ['13', 'lancaster city', '34', '7', '15', '55', '53', '+ 2', '31'], ['14', 'prescot cables', '34', '6', '16', '46', '48', '2', '28 2'], ['15', 'great harwood town', '34', '8', '17', '36', '59', '23', '24 2'], ['16', 'oldham town', '34', '9', '18', '38', '57', '19', '23'], ['17', 'atherton laburnum rovers', '34', '5', '21', '32', '61', '29', '21'], ['18', 'salford', '34', '8', '25', '17', '89', '72', '10']] |
merlin ( series 3 ) | https://en.wikipedia.org/wiki/Merlin_%28series_3%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-29106680-1.html.csv | count | there are 6 episodes of merlin , series 3 , that were written by julian jones . | {'scope': 'all', 'criterion': 'equal', 'value': 'julian jones', 'result': '6', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'written by', 'julian jones'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose written by record fuzzily matches to julian jones .', 'tostr': 'filter_eq { all_rows ; written by ; julian jones }'}], 'result': '6', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; written by ; julian jones } }', 'tointer': 'select the rows whose written by record fuzzily matches to julian jones . the number of such rows is 6 .'}, '6'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; written by ; julian jones } } ; 6 } = true', 'tointer': 'select the rows whose written by record fuzzily matches to julian jones . the number of such rows is 6 .'} | eq { count { filter_eq { all_rows ; written by ; julian jones } } ; 6 } = true | select the rows whose written by record fuzzily matches to julian jones . the number of such rows is 6 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'written by_5': 5, 'julian jones_6': 6, '6_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', 'julian jones_6': 'julian jones', '6_7': '6'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'written by_5': [0], 'julian jones_6': [0], '6_7': [2]} | ['no overall', 'no for series', 'title', 'directed by', 'written by', 'original air date', 'uk viewers ( million )'] | [['27', '1', 'the tears of uther pendragon ( part 1 )', 'jeremy webb', 'julian jones', '11 september 2010', '6.49'], ['28', '2', 'the tears of uther pendragon ( part 2 )', 'jeremy webb', 'julian jones', '18 september 2010', '6.06'], ['29', '3', "goblin 's gold", 'jeremy webb', 'howard overman', '25 september 2010', '6.22'], ['30', '4', 'gwaine', 'david moore', 'julian jones', '2 october 2010', '6.42'], ['31', '5', 'the crystal cave', 'alice troughton', 'julian jones', '9 october 2010', '6.36'], ['32', '6', 'the changeling', 'david moore', 'lucy watkins', '16 october 2010', '6.40'], ['33', '7', 'the castle of fyrien', 'david moore', 'jake michie', '23 october 2010', '6.82'], ['34', '8', 'the eye of the phoenix', 'alice troughton', 'julian jones', '30 october 2010', '6.92'], ['35', '9', 'love in the time of dragons', 'alice troughton', 'jake michie', '6 november 2010', '6.90'], ['36', '10', 'queen of hearts', 'ashley way', 'howard overman', '13 november 2010', '7.37'], ['37', '11', "the sorcerer 's shadow", 'ashley way', 'julian jones', '20 november 2010', '7.42'], ['38', '12', 'the coming of arthur ( part 1 )', 'jeremy webb', 'jake michie', '27 november 2010', '7.12']] |
margalita chakhnashvili | https://en.wikipedia.org/wiki/Margalita_Chakhnashvili | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12428755-2.html.csv | majority | the majority of these tournaments took place on a surface made of clay . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'clay', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'surface', 'clay'], 'result': True, 'ind': 0, 'tointer': 'for the surface records of all rows , most of them fuzzily match to clay .', 'tostr': 'most_eq { all_rows ; surface ; clay } = true'} | most_eq { all_rows ; surface ; clay } = true | for the surface records of all rows , most of them fuzzily match to clay . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'surface_3': 3, 'clay_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'surface_3': 'surface', 'clay_4': 'clay'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'surface_3': [0], 'clay_4': [0]} | ['date', 'tournament', 'surface', 'tier', 'partner', 'opponents in the final', 'score'] | [['may 8 , 2006', 'antalya - belek', 'clay', 'itf 10k', 'ipek şenoğlu', 'claire de gubernatis alexandra dulgheru', '6 - 4 , 6 - 3'], ['july 3 , 2006', 'mont de marson', 'clay', 'itf 25k', 'ioana raluca olaru', 'akgul amanmuradova nina bratchikova', '7 - 5 , 1 - 6 , 6 - 1'], ['august 21 , 2009', 'westende', 'hard', 'itf 25k', 'vasilisa davydova', 'emilie bacquet jasmin wöhr', '6 - 2 , 7 - 5'], ['june 12 , 2011', 'zlin', 'clay', 'itf 50k', 'yuliya beygelzimer', 'réka - luca jani katalin marosi', '3 - 6 , 6 - 1 ,'], ['june 3 , 2012', 'grado', 'clay', 'itf 25k', 'ekaterine gorgodze', 'claudia giovine anastasia grymalska', '7 - 6 ( 7 - 2 ) , 7 - 6 ( 7 - 1 )']] |
2008 - 09 football league championship | https://en.wikipedia.org/wiki/2008%E2%80%9309_Football_League_Championship | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-18784280-3.html.csv | count | there were two resignations that took place in the 2008-2009 football league championship . | {'scope': 'all', 'criterion': 'equal', 'value': 'resigned', 'result': '2', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'manner of departure', 'resigned'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose manner of departure record fuzzily matches to resigned .', 'tostr': 'filter_eq { all_rows ; manner of departure ; resigned }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; manner of departure ; resigned } }', 'tointer': 'select the rows whose manner of departure record fuzzily matches to resigned . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; manner of departure ; resigned } } ; 2 } = true', 'tointer': 'select the rows whose manner of departure record fuzzily matches to resigned . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; manner of departure ; resigned } } ; 2 } = true | select the rows whose manner of departure record fuzzily matches to resigned . 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, 'manner of departure_5': 5, 'resigned_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', 'manner of departure_5': 'manner of departure', 'resigned_6': 'resigned', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'manner of departure_5': [0], 'resigned_6': [0], '2_7': [2]} | ['team', 'outgoing manager', 'manner of departure', 'date of vacancy', 'replaced by', 'date of appointment', 'position in table'] | [['qpr', 'iain dowie', 'contract terminated', '24 october 2008', 'paulo sousa', '19 november 2008', '9th'], ['watford', 'aidy boothroyd', 'mutual consent', '3 november 2008', 'brendan rodgers', '24 november 2008', '21st'], ['charlton athletic', 'alan pardew', 'mutual consent', '22 november 2008', 'phil parkinson', '31 december 2008', '22nd'], ['blackpool', 'simon grayson', 'signed by leeds united ( mutual consent )', '23 december 2008', 'ian holloway', '21 may 2009', '16th'], ['nottingham forest', 'colin calderwood', 'contract terminated', '26 december 2008', 'billy davies', '1 january 2009', '22nd'], ['derby county', 'paul jewell', 'resigned', '28 december 2008', 'nigel clough', '6 january 2009', '18th'], ['norwich city', 'glenn roeder', 'contract terminated', '14 january 2009', 'bryan gunn', '21 january 2009', '21st'], ['southampton', 'jan poortvliet', 'resigned', '23 january 2009', 'mark wotte', '23 january 2009', '23rd'], ['qpr', 'paulo sousa', 'contract terminated', '9 april 2009', 'jim magilton', '3 june 2009', '10th'], ['ipswich town', 'jim magilton', 'contract terminated', '22 april 2009', 'roy keane', '23 april 2009', '9th']] |
viktor leonenko | https://en.wikipedia.org/wiki/Viktor_Leonenko | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11327303-2.html.csv | majority | all of viktor leonenko 's international goals were scored in friendly competitions . | {'scope': 'all', 'col': '5', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'friendly', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'competition', 'friendly'], 'result': True, 'ind': 0, 'tointer': 'for the competition records of all rows , all of them fuzzily match to friendly .', 'tostr': 'all_eq { all_rows ; competition ; friendly } = true'} | all_eq { all_rows ; competition ; friendly } = true | for the competition records of all rows , all of them fuzzily match to friendly . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'competition_3': 3, 'friendly_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'competition_3': 'competition', 'friendly_4': 'friendly'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'competition_3': [0], 'friendly_4': [0]} | ['date', 'venue', 'score', 'result', 'competition'] | [['18 may 1993', 'vilnius , lithuania', '1 - 1', '1 - 2', 'friendly'], ['16 october 1993', 'high point , united states', '1 - 1', '1 - 2', 'friendly'], ['16 october 1993', 'high point , united states', '1 - 2', '1 - 2', 'friendly'], ['25 may 1994', 'kyiv , ukraine', '1 - 1', '3 - 1', 'friendly'], ['13 august 1996', 'kyiv , ukraine', '1 - 1', '5 - 2', 'friendly'], ['13 august 1996', 'kyiv , ukraine', '3 - 1', '5 - 2', 'friendly']] |
2001 new york jets season | https://en.wikipedia.org/wiki/2001_New_York_Jets_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10768951-1.html.csv | unique | only the rca dome hosted a game with fewer than 60,000 people in attendance . | {'scope': 'all', 'row': '15', 'col': '6', 'col_other': '5', 'criterion': 'less_than', 'value': '60000', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'attendance', '60000'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose attendance record is less than 60000 .', 'tostr': 'filter_less { all_rows ; attendance ; 60000 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_less { all_rows ; attendance ; 60000 } }', 'tointer': 'select the rows whose attendance record is less than 60000 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'attendance', '60000'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose attendance record is less than 60000 .', 'tostr': 'filter_less { all_rows ; attendance ; 60000 }'}, 'game site'], 'result': 'rca dome', 'ind': 2, 'tostr': 'hop { filter_less { all_rows ; attendance ; 60000 } ; game site }'}, 'rca dome'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_less { all_rows ; attendance ; 60000 } ; game site } ; rca dome }', 'tointer': 'the game site record of this unqiue row is rca dome .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_less { all_rows ; attendance ; 60000 } } ; eq { hop { filter_less { all_rows ; attendance ; 60000 } ; game site } ; rca dome } } = true', 'tointer': 'select the rows whose attendance record is less than 60000 . there is only one such row in the table . the game site record of this unqiue row is rca dome .'} | and { only { filter_less { all_rows ; attendance ; 60000 } } ; eq { hop { filter_less { all_rows ; attendance ; 60000 } ; game site } ; rca dome } } = true | select the rows whose attendance record is less than 60000 . there is only one such row in the table . the game site record of this unqiue row is rca dome . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_less_0': 0, 'all_rows_6': 6, 'attendance_7': 7, '60000_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'game site_9': 9, 'rca dome_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_less_0': 'filter_less', 'all_rows_6': 'all_rows', 'attendance_7': 'attendance', '60000_8': '60000', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'game site_9': 'game site', 'rca dome_10': 'rca dome'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_less_0': [1, 2], 'all_rows_6': [0], 'attendance_7': [0], '60000_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'game site_9': [2], 'rca dome_10': [3]} | ['week', 'date', 'opponent', 'result', 'game site', 'attendance'] | [['1', '2001 - 09 - 09', 'indianapolis colts', 'l 45 - 24', 'the meadowlands', '78606'], ['2', '2001 - 09 - 23', 'new england patriots', 'w 10 - 3', 'foxboro stadium', '60292'], ['3', '2001 - 10 - 01', 'san francisco 49ers', 'l 19 - 17', 'the meadowlands', '78722'], ['4', '2001 - 10 - 07', 'buffalo bills', 'w 42 - 36', 'ralph wilson stadium', '72654'], ['5', '2001 - 10 - 14', 'miami dolphins', 'w 21 - 17', 'the meadowlands', '78823'], ['6', '2001 - 10 - 21', 'st louis rams', 'l 34 - 14', 'the meadowlands', '78766'], ['7', '2001 - 10 - 28', 'carolina panthers', 'w 13 - 12', 'bank of america stadium', '72642'], ['8', '2001 - 11 - 04', 'new orleans saints', 'w 16 - 9', 'louisiana superdome', '70020'], ['9', '2001 - 11 - 11', 'kansas city chiefs', 'w 27 - 7', 'the meadowlands', '78234'], ['10', '2001 - 11 - 18', 'miami dolphins', 'w 24 - 0', 'pro player stadium', '74259'], ['11', '-', '-', '-', '-', ''], ['12', '2001 - 12 - 02', 'new england patriots', 'l 17 - 16', 'the meadowlands', '78712'], ['13', '2001 - 12 - 09', 'pittsburgh steelers', 'l 18 - 7', 'heinz field', '62884'], ['14', '2001 - 12 - 16', 'cincinnati bengals', 'w 15 - 14', 'the meadowlands', '77745'], ['15', '2001 - 12 - 23', 'indianapolis colts', 'w 29 - 28', 'rca dome', '56302'], ['16', '2001 - 12 - 30', 'buffalo bills', 'l 14 - 9', 'the meadowlands', '78200'], ['17', '2002 - 01 - 06', 'oakland raiders', 'w 24 - 22', 'network associates coliseum', '62011']] |
zaur tagizade | https://en.wikipedia.org/wiki/Zaur_Tagizade | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17911639-1.html.csv | aggregation | of the competitions zaur tagizade participated in , the average score for his team was 1.67 . | {'scope': 'all', 'col': '3', 'type': 'average', 'result': '1.67', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'score'], 'result': '1.67', 'ind': 0, 'tostr': 'avg { all_rows ; score }'}, '1.67'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; score } ; 1.67 } = true', 'tointer': 'the average of the score record of all rows is 1.67 .'} | round_eq { avg { all_rows ; score } ; 1.67 } = true | the average of the score record of all rows is 1.67 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'score_4': 4, '1.67_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'score_4': 'score', '1.67_5': '1.67'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'score_4': [0], '1.67_5': [1]} | ['date', 'venue', 'score', 'result', 'competition'] | [['5 june 1999', 'tofiq bahramov stadium , baku', '3 - 0', '4 - 0', 'euro 2000 qualifying'], ['18 august 1999', 'dynamo samarkand stadium , samarkand', '3 - 1', '5 - 1', 'friendly'], ['4 september 1999', 'tofiq bahramov stadium , baku', '1 - 0', '1 - 1', 'euro 2000 qualifying'], ['26 february 2001', 'national sport base sportpalace , varna', '1 - 0', '1 - 0', 'friendly'], ['6 june 2001', 'tofiq bahramov stadium , baku', '2 - 0', '2 - 0', '2002 world cup qualification'], ['17 august 2005', 'qemal stafa stadium , tirana', '0 - 1', '2 - 1', 'friendly']] |
aleksandra wozniak | https://en.wikipedia.org/wiki/Aleksandra_Wozniak | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11307139-5.html.csv | majority | in most of aleksandra wozniak 's tournaments , she was the winner . | {'scope': 'all', 'col': '1', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'winner', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'outcome', 'winner'], 'result': True, 'ind': 0, 'tointer': 'for the outcome records of all rows , most of them fuzzily match to winner .', 'tostr': 'most_eq { all_rows ; outcome ; winner } = true'} | most_eq { all_rows ; outcome ; winner } = true | for the outcome records of all rows , most of them fuzzily match to winner . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'outcome_3': 3, 'winner_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'outcome_3': 'outcome', 'winner_4': 'winner'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'outcome_3': [0], 'winner_4': [0]} | ['outcome', 'date', 'tournament', 'surface', 'opponent', 'score'] | [['winner', 'june 30 , 2002', 'lachine , canada', 'hard', 'beier ko', '6 - 0 , 6 - 3'], ['winner', 'july 17 , 2005', 'hamilton , canada', 'clay', 'maría josé argeri', '6 - 1 , 6 - 2'], ['runner - up', 'october 2 , 2005', 'pelham , united states', 'clay', 'soledad esperón', '5 - 7 , 2 - 6'], ['winner', 'october 16 , 2005', 'victoria , mexico', 'hard', 'olga blahotová', '2 - 6 , 6 - 0 , 6 - 4'], ['runner - up', 'october 23 , 2005', 'mexico city , mexico', 'hard', 'maría josé argeri', '4 - 6 , 0 - 4 ret'], ['winner', 'november 13 , 2005', 'toronto , canada', 'hard ( i )', 'olena antypina', '6 - 4 , 6 - 3'], ['winner', 'july 23 , 2006', 'hamilton , canada', 'clay', 'valérie tétreault', '6 - 1 , 6 - 7 ( 5 - 7 ) , 6 - 2'], ['winner', 'october 1 , 2006', 'ashland , united states', 'hard', 'ágnes szávay', '6 - 1 , 7 - 6 ( 7 - 2 )'], ['winner', 'november 12 , 2006', 'pittsburgh , united states', 'hard ( i )', 'victoria azarenka', '6 - 2 , ret'], ['runner - up', 'march 23 , 2008', 'redding , united states', 'hard', 'barbora záhlavová - strýcová', '6 - 7 ( 4 - 7 ) , 3 - 6'], ['winner', 'august 7 , 2011', 'vancouver , canada', 'hard', 'jamie hampton', '6 - 3 , 6 - 1'], ['winner', 'march 17 , 2012', 'nassau , bahamas', 'hard', 'alizé cornet', '6 - 4 , 7 - 5']] |
co - operative commonwealth federation ( ontario section ) | https://en.wikipedia.org/wiki/Co-operative_Commonwealth_Federation_%28Ontario_Section%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1036175-1.html.csv | comparative | in co - operative commonwealth federation , candidates selected in the year 1951 is very low when compare with the year 1948 . | {'row_1': '6', 'row_2': '5', 'col': '2', 'col_other': '1', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'year of election', '1951'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose year of election record fuzzily matches to 1951 .', 'tostr': 'filter_eq { all_rows ; year of election ; 1951 }'}, 'candidates elected'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; year of election ; 1951 } ; candidates elected }', 'tointer': 'select the rows whose year of election record fuzzily matches to 1951 . take the candidates elected record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'year of election', '1948'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose year of election record fuzzily matches to 1948 .', 'tostr': 'filter_eq { all_rows ; year of election ; 1948 }'}, 'candidates elected'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; year of election ; 1948 } ; candidates elected }', 'tointer': 'select the rows whose year of election record fuzzily matches to 1948 . take the candidates elected record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; year of election ; 1951 } ; candidates elected } ; hop { filter_eq { all_rows ; year of election ; 1948 } ; candidates elected } } = true', 'tointer': 'select the rows whose year of election record fuzzily matches to 1951 . take the candidates elected record of this row . select the rows whose year of election record fuzzily matches to 1948 . take the candidates elected record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; year of election ; 1951 } ; candidates elected } ; hop { filter_eq { all_rows ; year of election ; 1948 } ; candidates elected } } = true | select the rows whose year of election record fuzzily matches to 1951 . take the candidates elected record of this row . select the rows whose year of election record fuzzily matches to 1948 . take the candidates elected 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, 'year of election_7': 7, '1951_8': 8, 'candidates elected_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'year of election_11': 11, '1948_12': 12, 'candidates elected_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', 'year of election_7': 'year of election', '1951_8': '1951', 'candidates elected_9': 'candidates elected', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'year of election_11': 'year of election', '1948_12': '1948', 'candidates elected_13': 'candidates elected'} | {'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'year of election_7': [0], '1951_8': [0], 'candidates elected_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'year of election_11': [1], '1948_12': [1], 'candidates elected_13': [3]} | ['year of election', 'candidates elected', 'of seats available', 'of votes', '% of popular vote'] | [['1934', '1', '90', 'na', '7.0 %'], ['1937', '0', '90', 'na', '5.6 %'], ['1943', '34', '90', 'na', '31.7 %'], ['1945', '8', '90', 'na', '22.4 %'], ['1948', '21', '90', 'na', '27.0 %'], ['1951', '2', '90', 'na', '19.1 %'], ['1955', '3', '98', 'na', '16.5 %'], ['1959', '5', '98', 'na', '16.7 %']] |
oldest football competitions | https://en.wikipedia.org/wiki/Oldest_football_competitions | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18050568-2.html.csv | count | according to the list of oldest football competitions , among the competitions located in sheffield , england , two of them had club trophy type . | {'scope': 'subset', 'criterion': 'equal', 'value': 'club trophy', 'result': '2', 'col': '2', 'subset': {'col': '5', 'criterion': 'equal', 'value': 'sheffield , england'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location', 'sheffield , england'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; location ; sheffield , england }', 'tointer': 'select the rows whose location record fuzzily matches to sheffield , england .'}, 'type', 'club trophy'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose location record fuzzily matches to sheffield , england . among these rows , select the rows whose type record fuzzily matches to club trophy .', 'tostr': 'filter_eq { filter_eq { all_rows ; location ; sheffield , england } ; type ; club trophy }'}], 'result': '2', 'ind': 2, 'tostr': 'count { filter_eq { filter_eq { all_rows ; location ; sheffield , england } ; type ; club trophy } }', 'tointer': 'select the rows whose location record fuzzily matches to sheffield , england . among these rows , select the rows whose type record fuzzily matches to club trophy . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_eq { filter_eq { all_rows ; location ; sheffield , england } ; type ; club trophy } } ; 2 } = true', 'tointer': 'select the rows whose location record fuzzily matches to sheffield , england . among these rows , select the rows whose type record fuzzily matches to club trophy . the number of such rows is 2 .'} | eq { count { filter_eq { filter_eq { all_rows ; location ; sheffield , england } ; type ; club trophy } } ; 2 } = true | select the rows whose location record fuzzily matches to sheffield , england . among these rows , select the rows whose type record fuzzily matches to club trophy . the number of such rows is 2 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_str_eq_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'location_6': 6, 'sheffield , england_7': 7, 'type_8': 8, 'club trophy_9': 9, '2_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_str_eq_1': 'filter_str_eq', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'location_6': 'location', 'sheffield , england_7': 'sheffield , england', 'type_8': 'type', 'club trophy_9': 'club trophy', '2_10': '2'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_str_eq_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'location_6': [0], 'sheffield , england_7': [0], 'type_8': [1], 'club trophy_9': [1], '2_10': [3]} | ['years', 'type', 'original code', 'current code', 'location'] | [['1860 -', 'interclub fixture', 'sheffield rules', 'defunct', 'sheffield , england'], ['1867 only', 'club trophy', 'sheffield rules', 'defunct', 'sheffield , england'], ['1868 only', 'club trophy', 'sheffield rules', 'defunct', 'sheffield , england'], ['1882 - 1883', 'club league', 'victorian rules', 'defunct', 'launceston , tasmania'], ['1884 - 1984', 'international challenge', 'association football', 'defunct', 'home nations ( uk )']] |
2008 - 09 florida panthers season | https://en.wikipedia.org/wiki/2008%E2%80%9309_Florida_Panthers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17360818-13.html.csv | unique | jacob markstrom is the only player from sweden drafted for the 2008 - 09 florida panthers season . | {'scope': 'all', 'row': '1', 'col': '4', 'col_other': '2', 'criterion': 'equal', 'value': 'sweden', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'nationality', 'sweden'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose nationality record fuzzily matches to sweden .', 'tostr': 'filter_eq { all_rows ; nationality ; sweden }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; nationality ; sweden } }', 'tointer': 'select the rows whose nationality record fuzzily matches to sweden . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'nationality', 'sweden'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose nationality record fuzzily matches to sweden .', 'tostr': 'filter_eq { all_rows ; nationality ; sweden }'}, 'player'], 'result': 'jacob markstrom', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; nationality ; sweden } ; player }'}, 'jacob markstrom'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; nationality ; sweden } ; player } ; jacob markstrom }', 'tointer': 'the player record of this unqiue row is jacob markstrom .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; nationality ; sweden } } ; eq { hop { filter_eq { all_rows ; nationality ; sweden } ; player } ; jacob markstrom } } = true', 'tointer': 'select the rows whose nationality record fuzzily matches to sweden . there is only one such row in the table . the player record of this unqiue row is jacob markstrom .'} | and { only { filter_eq { all_rows ; nationality ; sweden } } ; eq { hop { filter_eq { all_rows ; nationality ; sweden } ; player } ; jacob markstrom } } = true | select the rows whose nationality record fuzzily matches to sweden . there is only one such row in the table . the player record of this unqiue row is jacob markstrom . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'nationality_7': 7, 'sweden_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'player_9': 9, 'jacob markstrom_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'nationality_7': 'nationality', 'sweden_8': 'sweden', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'player_9': 'player', 'jacob markstrom_10': 'jacob markstrom'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'nationality_7': [0], 'sweden_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'player_9': [2], 'jacob markstrom_10': [3]} | ['round', 'player', 'position', 'nationality', 'college / junior / club team ( league )'] | [['2', 'jacob markstrom', '( g )', 'sweden', 'brynã ¤ s if ( sweden jr )'], ['2', 'colby robak', '( d )', 'canada', 'brandon wheat kings ( whl )'], ['3', 'adam comrie', '( d )', 'canada', 'saginaw spirit ( ohl )'], ['4', 'a j jenks', '( lw )', 'united states', 'plymouth whalers ( ohl )'], ['7', 'matthew bartkowski', '( d )', 'united states', 'lincoln stars ( ushl )']] |
2003 jacksonville jaguars season | https://en.wikipedia.org/wiki/2003_Jacksonville_Jaguars_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17983822-2.html.csv | aggregation | for the 2003 jacksonville jaguars the games against the indianapolis colts had a total combined attendance of 100807 . | {'scope': 'subset', 'col': '6', 'type': 'sum', 'result': '100807', 'subset': {'col': '3', 'criterion': 'equal', 'value': 'indianapolis colts'}} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', 'indianapolis colts'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; opponent ; indianapolis colts }', 'tointer': 'select the rows whose opponent record fuzzily matches to indianapolis colts .'}, 'attendance'], 'result': '100807', 'ind': 1, 'tostr': 'sum { filter_eq { all_rows ; opponent ; indianapolis colts } ; attendance }'}, '100807'], 'result': True, 'ind': 2, 'tostr': 'round_eq { sum { filter_eq { all_rows ; opponent ; indianapolis colts } ; attendance } ; 100807 } = true', 'tointer': 'select the rows whose opponent record fuzzily matches to indianapolis colts . the sum of the attendance record of these rows is 100807 .'} | round_eq { sum { filter_eq { all_rows ; opponent ; indianapolis colts } ; attendance } ; 100807 } = true | select the rows whose opponent record fuzzily matches to indianapolis colts . the sum of the attendance record of these rows is 100807 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'sum_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'opponent_5': 5, 'indianapolis colts_6': 6, 'attendance_7': 7, '100807_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'sum_1': 'sum', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'opponent_5': 'opponent', 'indianapolis colts_6': 'indianapolis colts', 'attendance_7': 'attendance', '100807_8': '100807'} | {'eq_2': [3], 'result_3': [], 'sum_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'opponent_5': [0], 'indianapolis colts_6': [0], 'attendance_7': [1], '100807_8': [2]} | ['week', 'date', 'opponent', 'result', 'kickoff time', 'attendance'] | [['1', 'september 7 , 2003', 'carolina panthers', 'l 23 - 24', 'cbs 1:00 pm', '72134'], ['2', 'september 14 , 2003', 'buffalo bills', 'l 17 - 38', 'cbs 1:00 pm', '58613'], ['3', 'september 21 , 2003', 'indianapolis colts', 'l 13 - 23', 'cbs 1:00 pm', '55770'], ['4', 'september 28 , 2003', 'houston texans', 'l 20 - 24', 'cbs 1:00 pm', '70041'], ['5', 'october 5 , 2003', 'san diego chargers', 'w 27 - 21', 'cbs 4:00 pm', '48954'], ['6', 'october 12 , 2003', 'miami dolphins', 'l 24 - 10', 'cbs 1:00 pm', '66437'], ['8', 'october 26 , 2003', 'tennessee titans', 'l 17 - 30', 'cbs 1:00 pm', '55918'], ['9', 'november 2 , 2003', 'baltimore ravens', 'l 17 - 24', 'cbs 1:00 pm', '69486'], ['10', 'november 9 , 2003', 'indianapolis colts', 'w 28 - 23', 'cbs 1:00 pm', '45037'], ['11', 'november 16 , 2003', 'tennessee titans', 'l 3 - 10', 'cbs 1:00 pm', '68809'], ['12', 'november 23 , 2003', 'new york jets', 'l 10 - 13', 'cbs 1:00 pm', '77614'], ['13', 'november 30 , 2003', 'tampa bay buccaneers', 'w 17 - 10', 'espn 8:30 pm', '60543'], ['14', 'december 7 , 2003', 'houston texans', 'w 27 - 0', 'cbs 1:00 pm', '43363'], ['15', 'december 14 , 2003', 'new england patriots', 'l 13 - 27', 'cbs 1:00 pm', '68436'], ['16', 'december 21 , 2003', 'new orleans saints', 'w 20 - 19', 'fox 1:00 pm', '49207'], ['17', 'december 28 , 2003', 'atlanta falcons', 'l 14 - 21', 'cbs 1:00 pm', '70266']] |
kslt | https://en.wikipedia.org/wiki/KSLT | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10044708-2.html.csv | aggregation | the kslt radio channels are broadcasted with an average erp wattage of 66 . | {'scope': 'all', 'col': '4', 'type': 'average', 'result': '66', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'erp w'], 'result': '66', 'ind': 0, 'tostr': 'avg { all_rows ; erp w }'}, '66'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; erp w } ; 66 } = true', 'tointer': 'the average of the erp w record of all rows is 66 .'} | round_eq { avg { all_rows ; erp w } ; 66 } = true | the average of the erp w record of all rows is 66 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'erp w_4': 4, '66_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'erp w_4': 'erp w', '66_5': '66'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'erp w_4': [0], '66_5': [1]} | ['call sign', 'frequency mhz', 'city of license', 'erp w', 'class', 'fcc info'] | [['k276dl', '103.1', 'hemingford , nebraska', '80', 'd', 'fcc'], ['k276dm', '103.1', 'chadron , nebraska', '5', 'd', 'fcc'], ['k292ec', '106.3', 'hot springs , south dakota', '68', 'd', 'fcc'], ['k292dn', '106.3', 'newcastle , wyoming', '31', 'd', 'fcc'], ['k292dz', '106.3', 'sheridan , wyoming', '135', 'd', 'fcc'], ['k296ds', '107.1', 'alliance , nebraska', '74', 'd', 'fcc']] |
1992 open championship | https://en.wikipedia.org/wiki/1992_Open_Championship | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18122130-4.html.csv | count | two players were tied with a score of 64 in the 1992 open championship . | {'scope': 'all', 'criterion': 'equal', 'value': '64', 'result': '2', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'score', '64'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose score record is equal to 64 .', 'tostr': 'filter_eq { all_rows ; score ; 64 }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; score ; 64 } }', 'tointer': 'select the rows whose score record is equal to 64 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; score ; 64 } } ; 2 } = true', 'tointer': 'select the rows whose score record is equal to 64 . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; score ; 64 } } ; 2 } = true | select the rows whose score record is equal to 64 . 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, 'score_5': 5, '64_6': 6, '2_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'score_5': 'score', '64_6': '64', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'score_5': [0], '64_6': [0], '2_7': [2]} | ['place', 'player', 'country', 'score', 'to par'] | [['t1', 'raymond floyd', 'united states', '64', '- 7'], ['t1', 'steve pate', 'united states', '64', '- 7'], ['t3', 'gordon brand , jnr', 'scotland', '65', '- 6'], ['t3', 'ian woosnam', 'wales', '65', '- 6'], ['t5', 'john cook', 'united states', '66', '- 5'], ['t5', 'ernie els', 'south africa', '66', '- 5'], ['t5', 'nick faldo', 'england', '66', '- 5'], ['t5', 'lee janzen', 'united states', '66', '- 5'], ['t9', 'per - ulrik johansson', 'sweden', '67', '- 4'], ['t9', 'andrew magee', 'united states', '67', '- 4'], ['t9', 'rocco mediate', 'united states', '67', '- 4'], ['t9', 'craig parry', 'australia', '67', '- 4'], ['t9', 'costantino rocca', 'italy', '67', '- 4'], ['t9', 'orrin vincent iii', 'united states', '67', '- 4']] |
list of intel core i7 microprocessors | https://en.wikipedia.org/wiki/List_of_Intel_Core_i7_microprocessors | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-18823880-10.html.csv | majority | all of the intel core i7 microprocessors have a total of 4 cores . | {'scope': 'all', 'col': '5', 'most_or_all': 'all', 'criterion': 'equal', 'value': '4', 'subset': None} | {'func': 'all_eq', 'args': ['all_rows', 'cores', '4'], 'result': True, 'ind': 0, 'tointer': 'for the cores records of all rows , all of them are equal to 4 .', 'tostr': 'all_eq { all_rows ; cores ; 4 } = true'} | all_eq { all_rows ; cores ; 4 } = true | for the cores records of all rows , all of them are equal to 4 . | 1 | 1 | {'all_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'cores_3': 3, '4_4': 4} | {'all_eq_0': 'all_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'cores_3': 'cores', '4_4': '4'} | {'all_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'cores_3': [0], '4_4': [0]} | ['model number', 'sspec number', 'frequency', 'turbo', 'cores', 'l2 cache', 'l3 cache', 'i / o bus', 'mult', 'memory', 'voltage', 'tdp', 'socket', 'release date', 'part number ( s )', 'release price ( usd )'] | [['core i7 - 720qm', 'slbly ( b1 )', '1.6 ghz', '1 / 1 / 6 / 9', '4', '4 256 kb', '6 mb', 'dmi', '12', '2 ddr3 - 1333', '0.65 - 1.4 v', '45 w', 'socketg1', 'september 2009', 'by80607002907ahbx80607i7720qm', '364'], ['core i7 - 740qm', 'slbqg ( b1 )', '1.73 ghz', '1 / 1 / 6 / 9', '4', '4 256 kb', '6 mb', 'dmi', '13', '2 ddr3 - 1333', '0.65 - 1.4 v', '45 w', 'socket g1', 'june 2010', 'by80607005259aabx80607i7740qm', '378'], ['core i7 - 820qm', 'slblx ( b1 )', '1.73 ghz', '1 / 1 / 8 / 10', '4', '4 256 kb', '8 mb', 'dmi', '13', '2 ddr3 - 1333', '0.65 - 1.4 v', '45 w', 'socket g1', 'september 2009', 'by80607002904ak', '546'], ['core i7 - 840qm', 'slbmp ( b1 )', '1.87 ghz', '1 / 1 / 8 / 10', '4', '4 256 kb', '8 mb', 'dmi', '14', '2 ddr3 - 1333', '0.65 - 1.4 v', '45 w', 'socket g1', 'june 2010', 'by80607002901aibx80607i7840qm', '568'], ['core i7 - 920xm', 'slblw ( b1 )', '2 ghz', '2 / 2 / 8 / 9', '4', '4 256 kb', '8 mb', 'dmi', '15', '2 ddr3 - 1333', '0.65 - 1.4 v', '55 w', 'socket g1', 'september 2009', 'by80607002529af', '1054']] |
list of australian football league pre - season and night series premiers | https://en.wikipedia.org/wiki/List_of_Australian_Football_League_pre-season_and_night_series_premiers | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1139835-8.html.csv | ordinal | the premier of 1993 recorded the highest attendance in the list of australian football league pre - season and night series premiers . | {'row': '13', 'col': '6', 'order': '1', 'col_other': '1', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'attendance', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; attendance ; 1 }'}, 'season'], 'result': '1993', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; attendance ; 1 } ; season }'}, '1993'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; attendance ; 1 } ; season } ; 1993 } = true', 'tointer': 'select the row whose attendance record of all rows is 1st maximum . the season record of this row is 1993 .'} | eq { hop { nth_argmax { all_rows ; attendance ; 1 } ; season } ; 1993 } = true | select the row whose attendance record of all rows is 1st maximum . the season record of this row is 1993 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'num_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'attendance_5': 5, '1_6': 6, 'season_7': 7, '1993_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'num_hop_1': 'num_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'attendance_5': 'attendance', '1_6': '1', 'season_7': 'season', '1993_8': '1993'} | {'eq_2': [3], 'result_3': [], 'num_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'attendance_5': [0], '1_6': [0], 'season_7': [1], '1993_8': [2]} | ['season', 'premier', 'runner up', 'score', 'venue', 'attendance', 'margin'] | [['1956', 'south melbourne', 'carlton', '13.16 ( 94 ) - 13.10 ( 88 )', 'lake oval', '32450', '6'], ['1957', 'south melbourne', 'geelong', '15.13 ( 103 ) - 8.4 ( 52 )', 'lake oval', '25000', '51'], ['1963', 'footscray', 'richmond', '10.9 ( 69 ) - 9.9 ( 63 )', 'lake oval', '25270', '6'], ['1964', 'footscray', 'st kilda', '11.12 ( 78 ) - 11.7 ( 73 )', 'lake oval', '36300', '5'], ['1965', 'north melbourne', 'carlton', '14.13 ( 97 ) - 9.3 ( 57 )', 'lake oval', '37750', '40'], ['1966', 'north melbourne', 'hawthorn', '20.12 ( 132 ) - 12.7 ( 79 )', 'lake oval', '22800', '53'], ['1968', 'hawthorn', 'north melbourne', '16.15 ( 111 ) - 6.14 ( 50 )', 'lake oval', '15650', '61'], ['1969', 'hawthorn', 'melbourne', '10.17 ( 77 ) - 9.18 ( 72 )', 'lake oval', '21067', '5'], ['1985', 'hawthorn', 'essendon', '11.11 ( 77 ) - 10.8 ( 68 )', 'waverley park', '24812', '9'], ['1986', 'hawthorn', 'carlton', '9.12 ( 66 ) - 5.6 ( 36 )', 'waverley park', '19627', '30'], ['1991', 'hawthorn', 'north melbourne', '14.19 ( 103 ) - 7.12 ( 54 )', 'waverley park', '46629', '49'], ['1992', 'hawthorn', 'fitzroy', '19.14 ( 128 ) - 8.15 ( 63 )', 'waverley park', '49453', '65'], ['1993', 'essendon', 'richmond', '14.18 ( 102 ) - 11.13 ( 79 )', 'waverley park', '75533', '23'], ['1994', 'essendon', 'adelaide', '15.12 ( 102 ) - 9.14 ( 68 )', 'waverley park', '43925', '34'], ['2001', 'port adelaide', 'brisbane lions', '17.9 ( 111 ) - 3.8 ( 26 )', 'football park', '35304', '85'], ['2002', 'port adelaide', 'richmond', '10.11 ( 71 ) - 9.8 ( 62 )', 'colonial stadium', '36481', '9']] |
2005 - 06 toronto raptors season | https://en.wikipedia.org/wiki/2005%E2%80%9306_Toronto_Raptors_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15873014-5.html.csv | aggregation | during the 2005 - 06 toronto raptors season , for games where chris bosh had the high points , his average number of points was 25.57 . | {'scope': 'subset', 'col': '5', 'type': 'average', 'result': '25.57', 'subset': {'col': '5', 'criterion': 'equal', 'value': 'chris bosh'}} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'high points', 'chris bosh'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; high points ; chris bosh }', 'tointer': 'select the rows whose high points record fuzzily matches to chris bosh .'}, 'high points'], 'result': '25.57', 'ind': 1, 'tostr': 'avg { filter_eq { all_rows ; high points ; chris bosh } ; high points }'}, '25.57'], 'result': True, 'ind': 2, 'tostr': 'round_eq { avg { filter_eq { all_rows ; high points ; chris bosh } ; high points } ; 25.57 } = true', 'tointer': 'select the rows whose high points record fuzzily matches to chris bosh . the average of the high points record of these rows is 25.57 .'} | round_eq { avg { filter_eq { all_rows ; high points ; chris bosh } ; high points } ; 25.57 } = true | select the rows whose high points record fuzzily matches to chris bosh . the average of the high points record of these rows is 25.57 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'avg_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'high points_5': 5, 'chris bosh_6': 6, 'high points_7': 7, '25.57_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'avg_1': 'avg', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'high points_5': 'high points', 'chris bosh_6': 'chris bosh', 'high points_7': 'high points', '25.57_8': '25.57'} | {'eq_2': [3], 'result_3': [], 'avg_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'high points_5': [0], 'chris bosh_6': [0], 'high points_7': [1], '25.57_8': [2]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record'] | [['31', 'january 3', 'atlanta', 'w 108 - 97 ( ot )', 'mike james ( 28 )', 'chris bosh ( 10 )', 'mike james ( 6 )', 'philips arena 10048', '9 - 22'], ['32', 'january 4', 'orlando', 'w 121 - 97 ( ot )', 'charlie villanueva ( 24 )', 'rafael araújo ( 9 )', 'mike james ( 7 )', 'air canada centre 14085', '10 - 22'], ['33', 'january 6', 'houston', 'w 112 - 92 ( ot )', 'mike james ( 30 )', 'chris bosh ( 16 )', 'mike james ( 8 )', 'air canada centre 17460', '11 - 22'], ['34', 'january 8', 'new jersey', 'l 104 - 105 ( ot )', 'chris bosh ( 27 )', 'matt bonner ( 8 )', 'mike james ( 7 )', 'air canada centre 18935', '11 - 23'], ['35', 'january 9', 'chicago', 'l 104 - 113 ( ot )', 'chris bosh ( 26 )', 'matt bonner ( 9 )', 'mike james ( 13 )', 'united center 21103', '11 - 24'], ['36', 'january 11', 'charlotte', 'w 95 - 86 ( ot )', 'chris bosh ( 29 )', 'morris peterson ( 11 )', 'mike james ( 7 )', 'air canada centre 14098', '12 - 24'], ['37', 'january 15', 'new york', 'w 129 - 103 ( ot )', 'jalen rose ( 31 )', 'chris bosh , charlie villanueva ( 6 )', 'josé calderón ( 10 )', 'air canada centre 17393', '13 - 24'], ['38', 'january 17', 'utah', 'l 98 - 111 ( ot )', 'chris bosh ( 27 )', 'matt bonner , chris bosh ( 6 )', 'josé calderón , mike james ( 3 )', 'delta center 17831', '13 - 25'], ['39', 'january 18', 'portland', 'l 94 - 96 ( ot )', 'jalen rose ( 23 )', 'chris bosh ( 9 )', 'mike james ( 7 )', 'rose garden 12315', '13 - 26'], ['40', 'january 20', 'seattle', 'w 121 - 113 ( ot )', 'chris bosh ( 29 )', 'chris bosh ( 13 )', 'jalen rose ( 7 )', 'keyarena 15261', '14 - 26'], ['41', 'january 22', 'la lakers', 'l 104 - 122 ( ot )', 'mike james ( 26 )', 'chris bosh ( 8 )', 'mike james ( 10 )', 'staples center 18997', '14 - 27'], ['42', 'january 23', 'denver', 'l 101 - 107 ( ot )', 'mike james ( 22 )', 'matt bonner ( 9 )', 'chris bosh , mike james ( 4 )', 'pepsi center 14826', '14 - 28'], ['43', 'january 25', 'chicago', 'l 88 - 104 ( ot )', 'chris bosh ( 20 )', 'chris bosh ( 7 )', 'mike james ( 7 )', 'air canada centre 14198', '14 - 29'], ['44', 'january 27', 'milwaukee', 'l 87 - 108 ( ot )', 'chris bosh ( 21 )', 'charlie villanueva ( 6 )', 'josé calderón ( 7 )', 'bradley center 14867', '14 - 30'], ['45', 'january 29', 'sacramento', 'w 124 - 123 ( ot )', 'morris peterson ( 23 )', 'morris peterson ( 10 )', 'josé calderón ( 5 )', 'air canada centre 16573', '15 - 30']] |
green party of british columbia | https://en.wikipedia.org/wiki/Green_Party_of_British_Columbia | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-168482-1.html.csv | majority | most of the time the green party of british columbia won 0 seats . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': '0', 'subset': None} | {'func': 'most_eq', 'args': ['all_rows', 'of seats won', '0'], 'result': True, 'ind': 0, 'tointer': 'for the of seats won records of all rows , most of them are equal to 0 .', 'tostr': 'most_eq { all_rows ; of seats won ; 0 } = true'} | most_eq { all_rows ; of seats won ; 0 } = true | for the of seats won records of all rows , most of them are equal to 0 . | 1 | 1 | {'most_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'of seats won_3': 3, '0_4': 4} | {'most_eq_0': 'most_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'of seats won_3': 'of seats won', '0_4': '0'} | {'most_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'of seats won_3': [0], '0_4': [0]} | ['election', 'candidates fielded', 'of seats won', 'total votes', '% of popular vote', 'place'] | [['1983', '4', '0', '3078', '0.19 %', '7th'], ['1986', '9', '0', '4660', '0.24 %', '5th'], ['1991', '42', '0', '12650', '0.86 %', '4th'], ['1996', '71', '0', '31511', '1.99 %', '5th'], ['2001', '72', '0', '197231', '12.39 %', '3rd'], ['2005', '79', '0', '161842', '9.17 %', '3rd'], ['2009', '85', '0', '134570', '8.21 %', '3rd'], ['2013', '61', '1', '146607', '8.13 %', '3rd']] |
eurozone | https://en.wikipedia.org/wiki/Eurozone | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-184391-1.html.csv | unique | the only country adopted into the eurozone in 1999 that has a population of less than 1 million is luxembourg . | {'scope': 'subset', 'row': '11', 'col': '3', 'col_other': '1,2', 'criterion': 'less_than', 'value': '1000000', 'subset': {'col': '2', 'criterion': 'fuzzily_match', 'value': '1999'}} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_less', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'adopted', '1999'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; adopted ; 1999 }', 'tointer': 'select the rows whose adopted record fuzzily matches to 1999 .'}, 'population ( 2011 - 01 - 01 )', '1000000'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose adopted record fuzzily matches to 1999 . among these rows , select the rows whose population ( 2011 - 01 - 01 ) record is less than 1000000 .', 'tostr': 'filter_less { filter_eq { all_rows ; adopted ; 1999 } ; population ( 2011 - 01 - 01 ) ; 1000000 }'}], 'result': True, 'ind': 2, 'tostr': 'only { filter_less { filter_eq { all_rows ; adopted ; 1999 } ; population ( 2011 - 01 - 01 ) ; 1000000 } }', 'tointer': 'select the rows whose adopted record fuzzily matches to 1999 . among these rows , select the rows whose population ( 2011 - 01 - 01 ) record is less than 1000000 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_less', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'adopted', '1999'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; adopted ; 1999 }', 'tointer': 'select the rows whose adopted record fuzzily matches to 1999 .'}, 'population ( 2011 - 01 - 01 )', '1000000'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose adopted record fuzzily matches to 1999 . among these rows , select the rows whose population ( 2011 - 01 - 01 ) record is less than 1000000 .', 'tostr': 'filter_less { filter_eq { all_rows ; adopted ; 1999 } ; population ( 2011 - 01 - 01 ) ; 1000000 }'}, 'state'], 'result': 'luxembourg', 'ind': 3, 'tostr': 'hop { filter_less { filter_eq { all_rows ; adopted ; 1999 } ; population ( 2011 - 01 - 01 ) ; 1000000 } ; state }'}, 'luxembourg'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { filter_less { filter_eq { all_rows ; adopted ; 1999 } ; population ( 2011 - 01 - 01 ) ; 1000000 } ; state } ; luxembourg }', 'tointer': 'the state record of this unqiue row is luxembourg .'}], 'result': True, 'ind': 5, 'tostr': 'and { only { filter_less { filter_eq { all_rows ; adopted ; 1999 } ; population ( 2011 - 01 - 01 ) ; 1000000 } } ; eq { hop { filter_less { filter_eq { all_rows ; adopted ; 1999 } ; population ( 2011 - 01 - 01 ) ; 1000000 } ; state } ; luxembourg } } = true', 'tointer': 'select the rows whose adopted record fuzzily matches to 1999 . among these rows , select the rows whose population ( 2011 - 01 - 01 ) record is less than 1000000 . there is only one such row in the table . the state record of this unqiue row is luxembourg .'} | and { only { filter_less { filter_eq { all_rows ; adopted ; 1999 } ; population ( 2011 - 01 - 01 ) ; 1000000 } } ; eq { hop { filter_less { filter_eq { all_rows ; adopted ; 1999 } ; population ( 2011 - 01 - 01 ) ; 1000000 } ; state } ; luxembourg } } = true | select the rows whose adopted record fuzzily matches to 1999 . among these rows , select the rows whose population ( 2011 - 01 - 01 ) record is less than 1000000 . there is only one such row in the table . the state record of this unqiue row is luxembourg . | 8 | 6 | {'and_5': 5, 'result_6': 6, 'only_2': 2, 'filter_less_1': 1, 'filter_str_eq_0': 0, 'all_rows_7': 7, 'adopted_8': 8, '1999_9': 9, 'population (2011 - 01 - 01)_10': 10, '1000000_11': 11, 'str_eq_4': 4, 'str_hop_3': 3, 'state_12': 12, 'luxembourg_13': 13} | {'and_5': 'and', 'result_6': 'true', 'only_2': 'only', 'filter_less_1': 'filter_less', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_7': 'all_rows', 'adopted_8': 'adopted', '1999_9': '1999', 'population (2011 - 01 - 01)_10': 'population ( 2011 - 01 - 01 )', '1000000_11': '1000000', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'state_12': 'state', 'luxembourg_13': 'luxembourg'} | {'and_5': [6], 'result_6': [], 'only_2': [5], 'filter_less_1': [2, 3], 'filter_str_eq_0': [1], 'all_rows_7': [0], 'adopted_8': [0], '1999_9': [0], 'population (2011 - 01 - 01)_10': [1], '1000000_11': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'state_12': [3], 'luxembourg_13': [4]} | ['state', 'adopted', 'population ( 2011 - 01 - 01 )', 'nominal gdp world bank , 2009 ( million usd )', 'relative gdp of total ( nominal )', 'gdp per capita world bank , 2009 nominal ( usd )'] | [['austria', '1999 - 01 - 01', '8404252', '384908', '3.09 %', '45799'], ['belgium', '1999 - 01 - 01', '10918405', '468522', '3.76 %', '42911'], ['cyprus ( incl uk military base )', '2008 - 01 - 01', '838896 14500', '24910', '0.20 %', '30966'], ['estonia', '2011 - 01 - 01', '1340194', '19120', '0.15 %', '14267'], ['finland', '1999 - 01 - 01', '5375276', '237512', '1.91 %', '44186'], ['france', '1999 - 01 - 01', '65075373', '2649390', '21.26 %', '40713'], ['germany', '1999 - 01 - 01', '81751602', '3330032', '26.73 %', '40734'], ['greece', '2001 - 01 - 01', '11325897', '329924', '2.65 %', '29130'], ['ireland', '1999 - 01 - 01', '4480858', '227193', '1.82 %', '50703'], ['italy', '1999 - 01 - 01', '60626442', '2112780', '16.96 %', '34849'], ['luxembourg', '1999 - 01 - 01', '511840', '52449', '0.42 %', '102471'], ['malta', '2008 - 01 - 01', '417617', '7449', '0.06 %', '17837'], ['netherlands', '1999 - 01 - 01', '16655799', '792128', '6.36 %', '47559'], ['portugal', '1999 - 01 - 01', '10636979', '227676', '1.83 %', '21404'], ['slovakia', '2009 - 01 - 01', '5435273', '87642', '0.70 %', '16125'], ['slovenia', '2007 - 01 - 01', '2050189', '48477', '0.39 %', '23645'], ['spain', '1999 - 01 - 01', '47190493', '1460250', '11.72 %', '30944'], ['eurozone', 'eurozone', '331963357', '12460362', '100 %', '37535']] |
zhang haijie | https://en.wikipedia.org/wiki/Zhang_Haijie | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18498470-1.html.csv | unique | for zhang haijie , when the result was a win , the only time the organization was star awards was 2012 . | {'scope': 'subset', 'row': '10', 'col': '2', 'col_other': '1', 'criterion': 'equal', 'value': 'star awards', 'subset': {'col': '5', 'criterion': 'equal', 'value': 'won'}} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'result', 'won'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; result ; won }', 'tointer': 'select the rows whose result record fuzzily matches to won .'}, 'organisation', 'star awards'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose result record fuzzily matches to won . among these rows , select the rows whose organisation record fuzzily matches to star awards .', 'tostr': 'filter_eq { filter_eq { all_rows ; result ; won } ; organisation ; star awards }'}], 'result': True, 'ind': 2, 'tostr': 'only { filter_eq { filter_eq { all_rows ; result ; won } ; organisation ; star awards } }', 'tointer': 'select the rows whose result record fuzzily matches to won . among these rows , select the rows whose organisation record fuzzily matches to star awards . there is only one such row in the table .'}, {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'result', 'won'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; result ; won }', 'tointer': 'select the rows whose result record fuzzily matches to won .'}, 'organisation', 'star awards'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose result record fuzzily matches to won . among these rows , select the rows whose organisation record fuzzily matches to star awards .', 'tostr': 'filter_eq { filter_eq { all_rows ; result ; won } ; organisation ; star awards }'}, 'year'], 'result': '2012', 'ind': 3, 'tostr': 'hop { filter_eq { filter_eq { all_rows ; result ; won } ; organisation ; star awards } ; year }'}, '2012'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { filter_eq { filter_eq { all_rows ; result ; won } ; organisation ; star awards } ; year } ; 2012 }', 'tointer': 'the year record of this unqiue row is 2012 .'}], 'result': True, 'ind': 5, 'tostr': 'and { only { filter_eq { filter_eq { all_rows ; result ; won } ; organisation ; star awards } } ; eq { hop { filter_eq { filter_eq { all_rows ; result ; won } ; organisation ; star awards } ; year } ; 2012 } } = true', 'tointer': 'select the rows whose result record fuzzily matches to won . among these rows , select the rows whose organisation record fuzzily matches to star awards . there is only one such row in the table . the year record of this unqiue row is 2012 .'} | and { only { filter_eq { filter_eq { all_rows ; result ; won } ; organisation ; star awards } } ; eq { hop { filter_eq { filter_eq { all_rows ; result ; won } ; organisation ; star awards } ; year } ; 2012 } } = true | select the rows whose result record fuzzily matches to won . among these rows , select the rows whose organisation record fuzzily matches to star awards . there is only one such row in the table . the year record of this unqiue row is 2012 . | 8 | 6 | {'and_5': 5, 'result_6': 6, 'only_2': 2, 'filter_str_eq_1': 1, 'filter_str_eq_0': 0, 'all_rows_7': 7, 'result_8': 8, 'won_9': 9, 'organisation_10': 10, 'star awards_11': 11, 'eq_4': 4, 'num_hop_3': 3, 'year_12': 12, '2012_13': 13} | {'and_5': 'and', 'result_6': 'true', 'only_2': 'only', 'filter_str_eq_1': 'filter_str_eq', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_7': 'all_rows', 'result_8': 'result', 'won_9': 'won', 'organisation_10': 'organisation', 'star awards_11': 'star awards', 'eq_4': 'eq', 'num_hop_3': 'num_hop', 'year_12': 'year', '2012_13': '2012'} | {'and_5': [6], 'result_6': [], 'only_2': [5], 'filter_str_eq_1': [2, 3], 'filter_str_eq_0': [1], 'all_rows_7': [0], 'result_8': [0], 'won_9': [0], 'organisation_10': [1], 'star awards_11': [1], 'eq_4': [5], 'num_hop_3': [4], 'year_12': [3], '2012_13': [4]} | ['year', 'organisation', 'award', 'nominated work title', 'result'] | [['2000', 'star awards', 'best news / current affairs presenter', 'news 8 at ten', 'nominated'], ['2001', 'star awards', 'best news / current affairs presenter', 'news 8 at ten', 'nominated'], ['2003', 'asian television awards', 'best current affairs presenter', 'inside out', 'runner - up'], ['2004', 'lianhe zaobao', 'top 50 most popular asian idol', 'n / a', 'won'], ['2008', 'the anniversary gala 2008', 'most memorable news presenter ( 2000s era )', 'n / a', 'won'], ['2009', 'star awards', 'best news / current affairs presenter', 'news 8 at ten', 'nominated'], ['2010', 'star awards', 'best news presenter', 'news 8 at ten', 'nominated'], ['2011', 'star awards', 'best news story', 'kallang slash', 'nominated'], ['2011', 'star awards', 'best news presenter', 'news tonight', 'nominated'], ['2012', 'star awards', 'best news presenter', 'news tonight', 'won'], ['2013', 'star awards', 'best news presenter', 'news tonight', 'nominated']] |
2008 manx grand prix | https://en.wikipedia.org/wiki/2008_Manx_Grand_Prix | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18649514-4.html.csv | count | only two drivers in the 2008 manx grand prix drove at an average speed of higher than 100 mph . | {'scope': 'all', 'criterion': 'greater_than', 'value': '100', 'result': '2', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'speed', '100'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose speed record is greater than 100 .', 'tostr': 'filter_greater { all_rows ; speed ; 100 }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_greater { all_rows ; speed ; 100 } }', 'tointer': 'select the rows whose speed record is greater than 100 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_greater { all_rows ; speed ; 100 } } ; 2 } = true', 'tointer': 'select the rows whose speed record is greater than 100 . the number of such rows is 2 .'} | eq { count { filter_greater { all_rows ; speed ; 100 } } ; 2 } = true | select the rows whose speed record is greater than 100 . the number of such rows is 2 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_greater_0': 0, 'all_rows_4': 4, 'speed_5': 5, '100_6': 6, '2_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_greater_0': 'filter_greater', 'all_rows_4': 'all_rows', 'speed_5': 'speed', '100_6': '100', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_greater_0': [1], 'all_rows_4': [0], 'speed_5': [0], '100_6': [0], '2_7': [2]} | ['rank', 'rider', 'team', 'speed', 'time'] | [['1', 'ryan farquhar', '498cc bic paton', '102.385 mph', '1:06.19.90'], ['2', 'alan oversby', '500cc norton manx', '101.863 mph', '1:06.40.30'], ['3', 'alan brew', 'seeley g50 496cc', '99.367 mph', '1:08.20.78'], ['4', 'wattie brown', '500cc petty manx', '98.118 mph', '1:09.12.98'], ['5', 'andy reynolds', '499cc bic paton', '97.152 mph', '1:09.54.28'], ['6', 'bob price', '500cc seeley g50', '96.890 mph', '1:10.05.64'], ['7', 'ken davis', '500cc norton manx', '95.948 mph', '1:10.46.92'], ['8', 'chris swallow', '476cc ducati', '95.664 mph', '1:10.59.52'], ['9', 'mark herbertson', '499cc matchless g50', '95.272 mph', '1:11.17.05'], ['10', 'dave madsen - mygdal', '499cc honda', '92.209 mph', '1:11.19.89']] |
mars hill network | https://en.wikipedia.org/wiki/Mars_Hill_Network | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12454334-1.html.csv | superlative | wmhu is the mars hill network call sign that has the highest number facility id . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '5', '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', 'facility id'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; facility id }'}, 'call sign'], 'result': 'wmhu', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; facility id } ; call sign }'}, 'wmhu'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; facility id } ; call sign } ; wmhu } = true', 'tointer': 'select the row whose facility id record of all rows is maximum . the call sign record of this row is wmhu .'} | eq { hop { argmax { all_rows ; facility id } ; call sign } ; wmhu } = true | select the row whose facility id record of all rows is maximum . the call sign record of this row is wmhu . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'facility id_5': 5, 'call sign_6': 6, 'wmhu_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'facility id_5': 'facility id', 'call sign_6': 'call sign', 'wmhu_7': 'wmhu'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'facility id_5': [0], 'call sign_6': [1], 'wmhu_7': [2]} | ['call sign', 'frequency', 'city of license', 'facility id', 'erp / power w', 'height m ( ft )', 'class'] | [['wmhi', '94.7 fm', 'cape vincent , ny', '40435', '5800', '-', 'a'], ['wmhn', '89.3 fm', 'webster , ny', '40430', '1000', '-', 'a'], ['wmhq', '90.1 fm', 'malone , ny', '89863', '2700', '-', 'a'], ['wmhr', '102.9 fm', 'syracuse , ny', '40432', '20000', '-', 'b'], ['wmhu', '91.1 fm', 'cold brook , ny', '174468', '560', '-', 'a']] |
1995 men 's world ice hockey championships | https://en.wikipedia.org/wiki/1995_Men%27s_World_Ice_Hockey_Championships | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13771649-3.html.csv | ordinal | 6 was the 4th highest amount of points in the 1995 men 's world ice hockey championships . | {'row': '4', 'col': '5', 'order': '4', 'col_other': 'n/a', 'max_or_min': 'max_to_min', 'value_mentioned': 'yes', 'scope': 'all', 'subset': None} | {'func': 'eq', 'args': [{'func': 'nth_max', 'args': ['all_rows', 'points', '4'], 'result': '6', 'ind': 0, 'tostr': 'nth_max { all_rows ; points ; 4 }', 'tointer': 'the 4th maximum points record of all rows is 6 .'}, '6'], 'result': True, 'ind': 1, 'tostr': 'eq { nth_max { all_rows ; points ; 4 } ; 6 } = true', 'tointer': 'the 4th maximum points record of all rows is 6 .'} | eq { nth_max { all_rows ; points ; 4 } ; 6 } = true | the 4th maximum points record of all rows is 6 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'nth_max_0': 0, 'all_rows_3': 3, 'points_4': 4, '4_5': 5, '6_6': 6} | {'eq_1': 'eq', 'result_2': 'true', 'nth_max_0': 'nth_max', 'all_rows_3': 'all_rows', 'points_4': 'points', '4_5': '4', '6_6': '6'} | {'eq_1': [2], 'result_2': [], 'nth_max_0': [1], 'all_rows_3': [0], 'points_4': [0], '4_5': [0], '6_6': [1]} | ['games', 'drawn', 'lost', 'points difference', 'points'] | [['5', '2', '0', '17 - 11', '8'], ['5', '1', '1', '22 - 14', '7'], ['5', '1', '1', '17 - 09', '7'], ['5', '0', '2', '14 - 09', '6'], ['5', '0', '4', '09 - 18', '2'], ['5', '0', '5', '09 - 27', '0']] |
united states house of representatives elections , 1928 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1928 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1342370-12.html.csv | aggregation | the average winning percentage for the incumbents from districts 6 , 8 , 11 , 12 , 17 , 19 , and 21 in illinois that ran in the 1928 united states house of representatives was just over 65 % . | {'scope': 'all', 'col': '6', 'type': 'average', 'result': '65 %', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'candidates'], 'result': '65 %', 'ind': 0, 'tostr': 'avg { all_rows ; candidates }'}, '65 %'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; candidates } ; 65 % } = true', 'tointer': 'the average of the candidates record of all rows is 65 % .'} | round_eq { avg { all_rows ; candidates } ; 65 % } = true | the average of the candidates record of all rows is 65 % . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'candidates_4': 4, '65%_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'candidates_4': 'candidates', '65%_5': '65 %'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'candidates_4': [0], '65%_5': [1]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['illinois 6', 'james t igoe', 'democratic', '1926', 're - elected', 'james t igoe ( d ) 60.3 % samuel l golan ( r ) 39.7 %'], ['illinois 8', 'stanley h kunz', 'democratic', '1920', 're - elected', 'stanley h kunz ( d ) 70.8 % edward walz ( r ) 29.2 %'], ['illinois 11', 'frank r reid', 'republican', '1922', 're - elected', 'frank r reid ( r ) 68.9 % edwin l wilson ( d ) 31.1 %'], ['illinois 12', 'john t buckbee', 'republican', '1926', 're - elected', 'john t buckbee ( r ) 73.8 % jules vallatt ( d ) 26.2 %'], ['illinois 17', 'homer w hall', 'republican', '1926', 're - elected', 'homer w hall ( r ) 65.0 % frank gillespie ( d ) 35.0 %'], ['illinois 19', 'charles adkins', 'republican', '1924', 're - elected', 'charles adkins ( r ) 66.2 % w w reeves ( d ) 33.8 %'], ['illinois 21', 'j earl major', 'democratic', '1926', 'lost re - election republican gain', 'frank m ramey ( r ) 50.1 % j earl major ( d ) 49.9 %']] |
myrtle beach 250 | https://en.wikipedia.org/wiki/Myrtle_Beach_250 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-23015396-1.html.csv | majority | most of the winners of the myrtle beach 250 race drove 250 laps . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'greater_than_eq', 'value': '250', 'subset': None} | {'func': 'most_greater_eq', 'args': ['all_rows', 'laps', '250'], 'result': True, 'ind': 0, 'tointer': 'for the laps records of all rows , most of them are greater than or equal to 250 .', 'tostr': 'most_greater_eq { all_rows ; laps ; 250 } = true'} | most_greater_eq { all_rows ; laps ; 250 } = true | for the laps records of all rows , most of them are greater than or equal to 250 . | 1 | 1 | {'most_greater_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'laps_3': 3, '250_4': 4} | {'most_greater_eq_0': 'most_greater_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'laps_3': 'laps', '250_4': '250'} | {'most_greater_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'laps_3': [0], '250_4': [0]} | ['year', 'date', 'driver', 'manufacturer', 'laps', '-', 'race time', 'average speed ( mph )'] | [['1988', 'july 2', 'rob moroso', 'oldsmobile', '200', '107.6 ( 173.165 )', '1:36:04', '66.971'], ['1989', 'july 4', 'jimmy spencer', 'buick', '200', '107.6 ( 173.165 )', '1:25:01', '75.938'], ['1990', 'june 30', 'mark martin', 'ford', '200', '107.6 ( 173.165 )', '1:24:52', '76.072'], ['1991', 'june 22', 'chuck bown', 'pontiac', '250', '134.5 ( 216.456 )', '1:49:15', '73.867'], ['1992', 'june 20', 'jimmy spencer', 'oldsmobile', '250', '134.5 ( 216.456 )', '2:21:14', '57.139'], ['1993', 'june 12', 'jeff burton', 'ford', '250', '134.5 ( 216.456 )', '1:56:59', '68.984'], ['1994', 'june 11', 'elton sawyer', 'ford', '250', '134.5 ( 216.456 )', '2:01:18', '66.529'], ['1995', 'june 10', 'larry pearson', 'chevrolet', '250', '134.5 ( 216.456 )', '1:41:23', '79.599'], ['1996', 'june 22', 'david green', 'chevrolet', '250', '134.5 ( 216.456 )', '1:53:35', '71.049'], ['1997', 'july 12', 'elliott sadler', 'chevrolet', '250', '134.5 ( 216.456 )', '1:39:07', '81.419'], ['1998', 'july 11', 'randy lajoie', 'chevrolet', '250', '134.5 ( 216.456 )', '1:36:56', '80.754'], ['1999', 'july 17', 'jeff green', 'chevrolet', '250', '134.5 ( 216.456 )', '1:35:52', '84.179']] |
art competitions at the 1924 summer olympics | https://en.wikipedia.org/wiki/Art_competitions_at_the_1924_Summer_Olympics | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16581439-2.html.csv | ordinal | france ( fra ) recorded the highest total in art competitions at the 1924 summer olympics . | {'row': '2', 'col': '6', 'order': '1', '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', 'total', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; total ; 1 }'}, 'nation'], 'result': 'france ( fra )', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; total ; 1 } ; nation }'}, 'france ( fra )'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; total ; 1 } ; nation } ; france ( fra ) } = true', 'tointer': 'select the row whose total record of all rows is 1st maximum . the nation record of this row is france ( fra ) .'} | eq { hop { nth_argmax { all_rows ; total ; 1 } ; nation } ; france ( fra ) } = true | select the row whose total record of all rows is 1st maximum . the nation record of this row is france ( fra ) . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'total_5': 5, '1_6': 6, 'nation_7': 7, 'france (fra)_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', 'total_5': 'total', '1_6': '1', 'nation_7': 'nation', 'france (fra)_8': 'france ( fra )'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'total_5': [0], '1_6': [0], 'nation_7': [1], 'france (fra)_8': [2]} | ['rank', 'nation', 'gold', 'silver', 'bronze', 'total'] | [['1', 'luxembourg ( lux )', '1', '1', '0', '2'], ['2', 'france ( fra )', '1', '0', '2', '3'], ['3', 'greece ( gre )', '1', '0', '0', '1'], ['4', 'denmark ( den )', '0', '1', '1', '2'], ['4', 'ireland ( irl )', '0', '1', '1', '2'], ['6', 'great britain ( gbr )', '0', '1', '0', '1'], ['6', 'hungary ( hun )', '0', '1', '0', '1'], ['8', 'monaco ( mon )', '0', '0', '1', '1'], ['8', 'netherlands ( ned )', '0', '0', '1', '1']] |
northeast hoosier conference | https://en.wikipedia.org/wiki/Northeast_Hoosier_Conference | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18936832-1.html.csv | ordinal | in the northeast hoosier conference , the school with the 2nd highest enrollment is fort wayne carroll . | {'row': '5', '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', 'enrollment', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; enrollment ; 2 }'}, 'school'], 'result': 'fort wayne carroll', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; enrollment ; 2 } ; school }'}, 'fort wayne carroll'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; enrollment ; 2 } ; school } ; fort wayne carroll } = true', 'tointer': 'select the row whose enrollment record of all rows is 2nd maximum . the school record of this row is fort wayne carroll .'} | eq { hop { nth_argmax { all_rows ; enrollment ; 2 } ; school } ; fort wayne carroll } = true | select the row whose enrollment record of all rows is 2nd maximum . the school record of this row is fort wayne carroll . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'enrollment_5': 5, '2_6': 6, 'school_7': 7, 'fort wayne carroll_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', 'enrollment_5': 'enrollment', '2_6': '2', 'school_7': 'school', 'fort wayne carroll_8': 'fort wayne carroll'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'enrollment_5': [0], '2_6': [0], 'school_7': [1], 'fort wayne carroll_8': [2]} | ['school', 'location', 'mascot', 'enrollment', 'ihsaa class', 'county'] | [['bellmont', 'decatur', 'braves', '927', 'aaa', '01 adams'], ['columbia city', 'columbia city', 'eagles', '1127', 'aaaa', '92 whitley'], ['dekalb', 'waterloo', 'barons', '1302', 'aaaa', '17 dekalb'], ['east noble', 'kendallville', 'knights', '1213', 'aaaa', '57 noble'], ['fort wayne carroll', 'fort wayne', 'chargers', '1889', 'aaaaa', '02 allen'], ['fort wayne homestead', 'fort wayne', 'spartans', '2141', 'aaaaa', '02 allen'], ['new haven', 'new haven', 'bulldogs', '985', 'aaaa', '02 allen'], ['norwell', 'ossian', 'knights', '876', 'aaaa', '90 wells']] |
list of formula one driver records | https://en.wikipedia.org/wiki/List_of_Formula_One_driver_records | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13599687-60.html.csv | superlative | michael schumacher ranked highest in terms of number of points earned in one season . | {'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', 'points'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; points }'}, 'driver'], 'result': 'michael schumacher', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; points } ; driver }'}, 'michael schumacher'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; points } ; driver } ; michael schumacher } = true', 'tointer': 'select the row whose points record of all rows is maximum . the driver record of this row is michael schumacher .'} | eq { hop { argmax { all_rows ; points } ; driver } ; michael schumacher } = true | select the row whose points record of all rows is maximum . the driver record of this row is michael schumacher . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'points_5': 5, 'driver_6': 6, 'michael schumacher_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', 'driver_6': 'driver', 'michael schumacher_7': 'michael schumacher'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'points_5': [0], 'driver_6': [1], 'michael schumacher_7': [2]} | ['driver', 'points', 'season', 'races', 'percentage of possible points'] | [['michael schumacher', '148', '2004', '18', '82.22 %'], ['michael schumacher', '144', '2002', '17', '84.71 %'], ['fernando alonso', '134', '2006', '18', '74.44 %'], ['fernando alonso', '133', '2005', '19', '70.00 %'], ['michael schumacher', '123', '2001', '17', '72.36 %'], ['michael schumacher', '121', '2006', '18', '67.22 %'], ['rubens barrichello', '114', '2004', '18', '63.33 %'], ['kimi räikkönen', '112', '2005', '19', '58.95 %'], ['kimi räikkönen', '110', '2007', '17', '64.71 %'], ['lewis hamilton', '109', '2007', '17', '64.12 %'], ['fernando alonso', '109', '2007', '17', '64.12 %']] |
trevor taylor | https://en.wikipedia.org/wiki/Trevor_Taylor | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1226576-1.html.csv | aggregation | from 1959 to 1966 , trevor taylor won a total of 16 points in formula one world championships . | {'scope': 'all', 'col': '5', 'type': 'sum', 'result': '16', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'points'], 'result': '16', 'ind': 0, 'tostr': 'sum { all_rows ; points }'}, '16'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; points } ; 16 } = true', 'tointer': 'the sum of the points record of all rows is 16 .'} | round_eq { sum { all_rows ; points } ; 16 } = true | the sum of the points record of all rows is 16 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'points_4': 4, '16_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'points_4': 'points', '16_5': '16'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'points_4': [0], '16_5': [1]} | ['year', 'entrant', 'chassis', 'engine', 'points'] | [['1959', 'ace garage ( rotherham )', 'cooper t51', 'climax straight - 4', '0'], ['1961', 'team lotus', 'lotus 18', 'climax straight - 4', '0'], ['1962', 'team lotus', 'lotus 24', 'climax v8', '6'], ['1962', 'team lotus', 'lotus 25', 'climax v8', '6'], ['1963', 'team lotus', 'lotus 25', 'climax v8', '1'], ['1964', 'british racing partnership', 'brp 1', 'brm v8', '1'], ['1964', 'british racing partnership', 'brp 2', 'brm v8', '1'], ['1964', 'british racing partnership', 'lotus 24', 'brm v8', '1'], ['1966', 'aiden jones / paul emery', 'shannon', 'climax v8', '0']] |
afl records | https://en.wikipedia.org/wiki/List_of_VFL/AFL_records | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12161422-9.html.csv | superlative | the highest margin for afl records was for the fitzroy club . | {'scope': 'all', 'col_superlative': '2', 'row_superlative': '1', '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', 'margin'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; margin }'}, 'club'], 'result': 'fitzroy', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; margin } ; club }'}, 'fitzroy'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; margin } ; club } ; fitzroy } = true', 'tointer': 'select the row whose margin record of all rows is maximum . the club record of this row is fitzroy .'} | eq { hop { argmax { all_rows ; margin } ; club } ; fitzroy } = true | select the row whose margin record of all rows is maximum . the club record of this row is fitzroy . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'margin_5': 5, 'club_6': 6, 'fitzroy_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'margin_5': 'margin', 'club_6': 'club', 'fitzroy_7': 'fitzroy'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'margin_5': [0], 'club_6': [1], 'fitzroy_7': [2]} | ['rank', 'margin', 'club', 'opponent', 'year', 'round', 'venue'] | [['1', '190', 'fitzroy', 'melbourne', '1979', '17', 'vfl park'], ['2', '186', 'geelong', 'melbourne', '2011', '19', 'kardinia park'], ['3', '178', 'collingwood', 'st kilda', '1979', '4', 'victoria park'], ['4', '171', 'south melbourne', 'st kilda', '1919', '12', 'lake oval'], ['5', '168', 'richmond', 'north melbourne', '1931', '2', 'punt road oval']] |
alien huang | https://en.wikipedia.org/wiki/Alien_Huang | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-23379776-6.html.csv | comparative | black tide was released after the film burn ! motorbike was released . | {'row_1': '5', 'row_2': '4', 'col': '1', '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', 'title of movie', 'black tide 《 黑潮 》'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose title of movie record fuzzily matches to black tide 《 黑潮 》 .', 'tostr': 'filter_eq { all_rows ; title of movie ; black tide 《 黑潮 》 }'}, 'year'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; title of movie ; black tide 《 黑潮 》 } ; year }', 'tointer': 'select the rows whose title of movie record fuzzily matches to black tide 《 黑潮 》 . take the year record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'title of movie', 'burn ! motorbike 《 燃燒吧 ！ 機車 》'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose title of movie record fuzzily matches to burn ! motorbike 《 燃燒吧 ！ 機車 》 .', 'tostr': 'filter_eq { all_rows ; title of movie ; burn ! motorbike 《 燃燒吧 ！ 機車 》 }'}, 'year'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; title of movie ; burn ! motorbike 《 燃燒吧 ！ 機車 》 } ; year }', 'tointer': 'select the rows whose title of movie record fuzzily matches to burn ! motorbike 《 燃燒吧 ！ 機車 》 . take the year record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; title of movie ; black tide 《 黑潮 》 } ; year } ; hop { filter_eq { all_rows ; title of movie ; burn ! motorbike 《 燃燒吧 ！ 機車 》 } ; year } } = true', 'tointer': 'select the rows whose title of movie record fuzzily matches to black tide 《 黑潮 》 . take the year record of this row . select the rows whose title of movie record fuzzily matches to burn ! motorbike 《 燃燒吧 ！ 機車 》 . take the year record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; title of movie ; black tide 《 黑潮 》 } ; year } ; hop { filter_eq { all_rows ; title of movie ; burn ! motorbike 《 燃燒吧 ！ 機車 》 } ; year } } = true | select the rows whose title of movie record fuzzily matches to black tide 《 黑潮 》 . take the year record of this row . select the rows whose title of movie record fuzzily matches to burn ! motorbike 《 燃燒吧 ！ 機車 》 . 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 of movie_7': 7, 'black tide 《黑潮》_8': 8, 'year_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'title of movie_11': 11, 'burn! motorbike 《燃燒吧！機車》_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 of movie_7': 'title of movie', 'black tide 《黑潮》_8': 'black tide 《 黑潮 》', 'year_9': 'year', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'title of movie_11': 'title of movie', 'burn! motorbike 《燃燒吧！機車》_12': 'burn ! motorbike 《 燃燒吧 ！ 機車 》', 'year_13': 'year'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'title of movie_7': [0], 'black tide 《黑潮》_8': [0], 'year_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'title of movie_11': [1], 'burn! motorbike 《燃燒吧！機車》_12': [1], 'year_13': [3]} | ['year', 'title of movie', 'name of role', 'nature of role', 'co - artists', 'location'] | [['2002', 'wild 《 狂放 》', 'lin yi - jie 林益捷', 'male lead', 'junior han , josephine anan xu', 'taiwan'], ['2002', 'holiday dreaming 《 夢遊夏威夷 》', 'xiao gui 小鬼', 'second male lead', 'tony yang , janine chang', 'taiwan'], ['2006', 'a flight to yesterday 《 飛往昨天的ci006 》', 'li zheng - fei 李正非', 'male lead', 'yuchen zhang', 'taiwan'], ['2007', 'burn ! motorbike 《 燃燒吧 ！ 機車 》', 'hu di - ni 胡迪尼', 'male lead', 'megan lai', 'taiwan'], ['2009', 'black tide 《 黑潮 》', 'xiao gui 小鬼', 'male lead', 'shaoxiang li , jiaqing chu', 'taiwan'], ['2011', 'already famous 《 一泡而紅 》', 'christopher 阿盛', 'male lead', 'michelle chong', 'singapore']] |
grand tour ( cycling ) | https://en.wikipedia.org/wiki/Grand_Tour_%28cycling%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1286819-7.html.csv | majority | most of the riders in the table competed earlier than the year 1960 . | {'scope': 'all', 'col': '2', 'most_or_all': 'most', 'criterion': 'less_than', 'value': '1960', 'subset': None} | {'func': 'most_less', 'args': ['all_rows', 'year', '1960'], 'result': True, 'ind': 0, 'tointer': 'for the year records of all rows , most of them are less than 1960 .', 'tostr': 'most_less { all_rows ; year ; 1960 } = true'} | most_less { all_rows ; year ; 1960 } = true | for the year records of all rows , most of them are less than 1960 . | 1 | 1 | {'most_less_0': 0, 'result_1': 1, 'all_rows_2': 2, 'year_3': 3, '1960_4': 4} | {'most_less_0': 'most_less', 'result_1': 'true', 'all_rows_2': 'all_rows', 'year_3': 'year', '1960_4': '1960'} | {'most_less_0': [1], 'result_1': [], 'all_rows_2': [0], 'year_3': [0], '1960_4': [0]} | ['rider', 'year', 'final position - giro', 'final position - tour', 'final position - vuelta'] | [['eduardo chozas', '1990', '11', '6', '33'], ['marino lejarreta ( 3 )', '1990', '7', '5', '55'], ['marino lejarreta ( 2 )', '1989', '10', '5', '20'], ['luis - javier lukin', '1988', '32', '82', '60'], ['marino lejarreta', '1987', '4', '10', '34'], ['philippe poissonier', '1985', '86', '90', '66'], ['jose luis uribezubia', '1971', '29', '50', '27'], ['jose manuel fuente', '1971', '39', '72', '54'], ['federico bahamontes', '1958', '17', '8', '6'], ['pierino baffi', '1958', '23', '63', '37'], ['mario baroni', '1957', '74', '53', '46'], ['gastone nencini', '1957', '1', '6', '9'], ['bernardo ruiz ( 3 )', '1957', '55', '24', '3'], ['arrigo padovan', '1956', '12', '26', '19'], ['bernardo ruiz ( 2 )', '1956', '38', '70', '31'], ['josã serra', '1956', '26', '81', '9'], ['raphael geminiani', '1955', '4', '6', '3'], ['bernardo ruiz', '1955', '28', '22', '14'], ['louis caput', '1955', '68', '54', '55']] |
catherine tanvier | https://en.wikipedia.org/wiki/Catherine_Tanvier | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1676921-5.html.csv | majority | most of catherine tanvier 's matches were played on a surface of clay . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'clay', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'surface', 'clay'], 'result': True, 'ind': 0, 'tointer': 'for the surface records of all rows , most of them fuzzily match to clay .', 'tostr': 'most_eq { all_rows ; surface ; clay } = true'} | most_eq { all_rows ; surface ; clay } = true | for the surface records of all rows , most of them fuzzily match to clay . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'surface_3': 3, 'clay_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'surface_3': 'surface', 'clay_4': 'clay'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'surface_3': [0], 'clay_4': [0]} | ['date', 'tournament', 'surface', 'partner', 'opponents in final', 'score in final'] | [['18 july 1982', 'monte carlo , monaco', 'clay', 'virginia ruzici', 'patricia medrado claudia monteiro', '7 - 6 , 6 - 2'], ['8 august 1982', 'us clay courts , usa', 'clay', 'ivanna madruga', 'joanne russell virginia ruzici', '7 - 5 , 7 - 6'], ['9 may 1983', 'perugia , italy', 'clay', 'ivanna madruga', 'virginia ruzici virginia wade', '3 - 6 , 6 - 2 , 1 - 6'], ['10 july 1983', 'hittfeld , germany', 'clay', 'ivanna madruga', 'bettina bunge claudia kohde - kilsch', '5 - 7 , 4 - 6'], ['30 october 1983', 'filderstadt , germany', 'carpet', 'virginia ruzici', 'martina navratilova candy reynolds', '2 - 6 , 1 - 6'], ['16 december 1984', 'tokyo pan pacific , japan', 'carpet', 'elizabeth smylie', 'claudia kohde - kilsch helena suková', '4 - 6 , 1 - 6'], ['19 may 1985', 'german open , germany', 'clay', 'steffi graf', 'claudia kohde - kilsch helena suková', '4 - 6 , 1 - 6'], ['11 november 1985', 'hilversum , netherlands', 'carpet', 'marcella mesker', 'sandra cecchini sabrina goleš', '6 - 2 , 6 - 2'], ['13 april 1986', 'hilton head , usa', 'clay', 'steffi graf', 'chris evert - lloyd anne white', '3 - 6 , 3 - 6'], ['20 april 1986', 'amelia island , usa', 'clay', 'gabriela sabatini', 'claudia kohde - kilsch helena suková', '2 - 6 , 7 - 5 , 6 - 7'], ['19 october 1986', 'hilversum , netherlands', 'carpet', 'tine scheuer - larsen', 'kathy jordan helena suková', '5 - 7 , 1 - 6'], ['24 may 1987', 'european open , switzerland', 'clay', 'laura gildemeister', 'betsy nagelsen liz smylie', '6 - 4 , 4 - 6 , 3 - 6'], ['17 july 1988', 'nice , france', 'clay', 'catherine suire', 'isabelle demongeot nathalie tauziat', '6 - 4 , 4 - 6 , 6 - 2'], ['24 july 1988', 'aix - en - provence , france', 'clay', 'nathalie herreman', 'sandra cecchini arantxa sánchez vicario', '6 - 4 , 7 - 5'], ['22 october 1989', 'bayonne , france', 'hard', 'manon bollegraf', 'elna reinach raffaella reggi', '7 - 6 , 7 - 5'], ['30 september 1990', 'bayonne , france', 'carpet', 'louise field', 'jo - anne faull rachel mcquillan', '7 - 6 , 6 - 7 , 7 - 6'], ['29 september 1991', 'bayonne , france', 'carpet', 'rachel mcquillan', 'patricia tarabini nathalie tauziat', '3 - 6 , ret'], ['23 february 1992', 'cesena , italy', 'carpet', 'catherine suire', 'sabina appelmans raffaella reggi', 'w / o']] |
desperate romantics | https://en.wikipedia.org/wiki/Desperate_Romantics | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-23705843-1.html.csv | ordinal | episode 5 had the second lowest ratings of all these episodes of desperate romantics . | {'row': '5', 'col': '5', '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', 'ratings ( millions )', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; ratings ( millions ) ; 2 }'}, 'episode'], 'result': 'episode 5', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; ratings ( millions ) ; 2 } ; episode }'}, 'episode 5'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; ratings ( millions ) ; 2 } ; episode } ; episode 5 } = true', 'tointer': 'select the row whose ratings ( millions ) record of all rows is 2nd minimum . the episode record of this row is episode 5 .'} | eq { hop { nth_argmin { all_rows ; ratings ( millions ) ; 2 } ; episode } ; episode 5 } = true | select the row whose ratings ( millions ) record of all rows is 2nd minimum . the episode record of this row is episode 5 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'ratings (millions)_5': 5, '2_6': 6, 'episode_7': 7, 'episode 5_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', 'ratings (millions)_5': 'ratings ( millions )', '2_6': '2', 'episode_7': 'episode', 'episode 5_8': 'episode 5'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'ratings (millions)_5': [0], '2_6': [0], 'episode_7': [1], 'episode 5_8': [2]} | ['episode', 'director', 'writer', 'original air date', 'ratings ( millions )'] | [['episode 1', 'paul gay', 'peter bowker', '21 july 2009', '2.61'], ['episode 2', 'paul gay', 'peter bowker', '28 july 2009', '2.13'], ['episode 3', 'paul gay', 'peter bowker', '4 august 2009', '2.15'], ['episode 4', 'diarmuid lawrence', 'peter bowker', '11 august 2009', '1.92'], ['episode 5', 'diarmuid lawrence', 'peter bowker', '18 august 2009', '1.96']] |
jacksonville jaguars draft history | https://en.wikipedia.org/wiki/Jacksonville_Jaguars_draft_history | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15100419-13.html.csv | unique | adam podlesh is the only punter that was drafted by the jacksonville jaguars . | {'scope': 'all', 'row': '4', 'col': '5', 'col_other': '4', 'criterion': 'equal', 'value': 'punter', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'position', 'punter'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose position record fuzzily matches to punter .', 'tostr': 'filter_eq { all_rows ; position ; punter }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; position ; punter } }', 'tointer': 'select the rows whose position record fuzzily matches to punter . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'position', 'punter'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose position record fuzzily matches to punter .', 'tostr': 'filter_eq { all_rows ; position ; punter }'}, 'name'], 'result': 'adam podlesh', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; position ; punter } ; name }'}, 'adam podlesh'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; position ; punter } ; name } ; adam podlesh }', 'tointer': 'the name record of this unqiue row is adam podlesh .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; position ; punter } } ; eq { hop { filter_eq { all_rows ; position ; punter } ; name } ; adam podlesh } } = true', 'tointer': 'select the rows whose position record fuzzily matches to punter . there is only one such row in the table . the name record of this unqiue row is adam podlesh .'} | and { only { filter_eq { all_rows ; position ; punter } } ; eq { hop { filter_eq { all_rows ; position ; punter } ; name } ; adam podlesh } } = true | select the rows whose position record fuzzily matches to punter . there is only one such row in the table . the name record of this unqiue row is adam podlesh . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'position_7': 7, 'punter_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'name_9': 9, 'adam podlesh_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'position_7': 'position', 'punter_8': 'punter', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'name_9': 'name', 'adam podlesh_10': 'adam podlesh'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'position_7': [0], 'punter_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'name_9': [2], 'adam podlesh_10': [3]} | ['round', 'pick', 'overall', 'name', 'position', 'college'] | [['1', '21', '21', 'reggie nelson', 'safety', 'florida'], ['2', '16', '48', 'justin durant', 'linebacker', 'hampton'], ['3', '15', '79', 'mike sims - walker', 'wide receiver', 'central florida'], ['4', '2', '101', 'adam podlesh', 'punter', 'maryland'], ['4', '14', '113', 'brian smith', 'defensive end', 'missouri'], ['5', '12', '149', 'uche nwaneri', 'guard', 'purdue'], ['5', '13', '150', 'josh gattis', 'safety', 'wake forest'], ['5', '29', '166', 'derek landri', 'defensive tackle', 'notre dame'], ['7', '19', '229', 'john broussard', 'wide receiver', 'san jose state'], ['7', '41', '251', 'chad nkang', 'defensive back', 'elon'], ['7', '42', '252', 'andrew carnahan', 'offensive tackle', 'arizona state']] |
locomotives of the great western railway | https://en.wikipedia.org/wiki/Locomotives_of_the_Great_Western_Railway | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1169521-14.html.csv | unique | 0 - 8 - 2t is the only type of great western railway locomotive manufactured by cooke locomotive & machine works . | {'scope': 'all', 'row': '7', 'col': '1', 'col_other': '2', 'criterion': 'equal', 'value': 'cooke locomotive & machine works', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'manufacturer', 'cooke locomotive & machine works'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose manufacturer record fuzzily matches to cooke locomotive & machine works .', 'tostr': 'filter_eq { all_rows ; manufacturer ; cooke locomotive & machine works }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; manufacturer ; cooke locomotive & machine works } }', 'tointer': 'select the rows whose manufacturer record fuzzily matches to cooke locomotive & machine works . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'manufacturer', 'cooke locomotive & machine works'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose manufacturer record fuzzily matches to cooke locomotive & machine works .', 'tostr': 'filter_eq { all_rows ; manufacturer ; cooke locomotive & machine works }'}, 'type'], 'result': '0 - 8 - 2t', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; manufacturer ; cooke locomotive & machine works } ; type }'}, '0 - 8 - 2t'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; manufacturer ; cooke locomotive & machine works } ; type } ; 0 - 8 - 2t }', 'tointer': 'the type record of this unqiue row is 0 - 8 - 2t .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; manufacturer ; cooke locomotive & machine works } } ; eq { hop { filter_eq { all_rows ; manufacturer ; cooke locomotive & machine works } ; type } ; 0 - 8 - 2t } } = true', 'tointer': 'select the rows whose manufacturer record fuzzily matches to cooke locomotive & machine works . there is only one such row in the table . the type record of this unqiue row is 0 - 8 - 2t .'} | and { only { filter_eq { all_rows ; manufacturer ; cooke locomotive & machine works } } ; eq { hop { filter_eq { all_rows ; manufacturer ; cooke locomotive & machine works } ; type } ; 0 - 8 - 2t } } = true | select the rows whose manufacturer record fuzzily matches to cooke locomotive & machine works . there is only one such row in the table . the type record of this unqiue row is 0 - 8 - 2t . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'manufacturer_7': 7, 'cooke locomotive & machine works_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'type_9': 9, '0 - 8 - 2t_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'manufacturer_7': 'manufacturer', 'cooke locomotive & machine works_8': 'cooke locomotive & machine works', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'type_9': 'type', '0 - 8 - 2t_10': '0 - 8 - 2t'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'manufacturer_7': [0], 'cooke locomotive & machine works_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'type_9': [2], '0 - 8 - 2t_10': [3]} | ['manufacturer', 'type', 'quantity', 'ptrd nos', 'gwr nos'] | [['robert stephenson & co', '0 - 6 - 2t', '7', '8 - 14', '183 - 187'], ['hudswell clarke', '0 - 6 - 0st', '6', '22 - 27', '808 - 809 , 811 - 814'], ['robert stephenson & co', '0 - 6 - 0st', '2', '3 , 15', '815 , 816'], ['sharp , stewart & co', '2 - 4 - 0t', '1', '37', '1189'], ['sharp , stewart & co', '2 - 4 - 2t', '1', '36', '1326'], ['sharp , stewart & co', '0 - 8 - 2t', '3', '17 - 19', '1358 - 1360'], ['cooke locomotive & machine works', '0 - 8 - 2t', '2', '20 - 21', '1378 - 1379']] |
united states house of representatives elections , 1948 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1948 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1342218-13.html.csv | unique | district 3 of illinois was the only district in the 1948 united states house of representative elections that lost the re-election resulting in a democratic gain . | {'scope': 'all', 'row': '1', 'col': '5', 'col_other': '1', 'criterion': 'fuzzily_match', 'value': 'lost', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'result', 'lost'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose result record fuzzily matches to lost .', 'tostr': 'filter_eq { all_rows ; result ; lost }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; result ; lost } }', 'tointer': 'select the rows whose result record fuzzily matches to lost . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'result', 'lost'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose result record fuzzily matches to lost .', 'tostr': 'filter_eq { all_rows ; result ; lost }'}, 'district'], 'result': 'illinois 3', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; result ; lost } ; district }'}, 'illinois 3'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; result ; lost } ; district } ; illinois 3 }', 'tointer': 'the district record of this unqiue row is illinois 3 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; result ; lost } } ; eq { hop { filter_eq { all_rows ; result ; lost } ; district } ; illinois 3 } } = true', 'tointer': 'select the rows whose result record fuzzily matches to lost . there is only one such row in the table . the district record of this unqiue row is illinois 3 .'} | and { only { filter_eq { all_rows ; result ; lost } } ; eq { hop { filter_eq { all_rows ; result ; lost } ; district } ; illinois 3 } } = true | select the rows whose result record fuzzily matches to lost . there is only one such row in the table . the district record of this unqiue row is illinois 3 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'result_7': 7, 'lost_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'district_9': 9, 'illinois 3_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'result_7': 'result', 'lost_8': 'lost', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'district_9': 'district', 'illinois 3_10': 'illinois 3'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'result_7': [0], 'lost_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'district_9': [2], 'illinois 3_10': [3]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['illinois 3', 'fred e busbey', 'republican', '1946', 'lost re - election democratic gain', 'neil j linehan ( d ) 52.9 % fred e busbey ( r ) 47.1 %'], ['illinois 5', 'martin gorski redistricted from 4th', 'democratic', '1942', 're - elected', 'martin gorski ( d ) 72.4 % john l waner ( r ) 27.6 %'], ['illinois 14', 'chauncey w reed redistricted from 11th', 'republican', '1934', 're - elected', 'chauncey w reed ( r ) 68.3 % richard plum ( d ) 31.7 %'], ['illinois 15', 'noah m mason redistricted from 12th', 'republican', '1936', 're - elected', 'noah m mason ( r ) 56.4 % g m wells ( d ) 43.6 %'], ['illinois 17', 'leslie c arends', 'republican', '1934', 're - elected', 'leslie c arends ( r ) 62.8 % carl vrooman ( d ) 37.2 %'], ['illinois 18', 'everett dirksen redistricted from 16th', 'republican', '1932', 'retired republican hold', 'harold h velde ( r ) 52.1 % dale e sutton ( d ) 47.9 %'], ['illinois 20', 'sid simpson', 'republican', '1942', 're - elected', 'sid simpson ( r ) 53.1 % henry d sullivan ( d ) 46.9 %'], ['illinois 20', 'anton j johnson redistricted from 14th', 'republican', '1938', 'retired republican loss', 'sid simpson ( r ) 53.1 % henry d sullivan ( d ) 46.9 %'], ['illinois 26', 'c w bishop', 'republican', '1940', 're - elected', 'c w bishop ( r ) 51.9 % kent e keller ( d ) 48.1 %']] |
corruption in india | https://en.wikipedia.org/wiki/Corruption_in_India | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14496392-1.html.csv | superlative | bihar is the indian state that has the highest anti-corruption index score for the years 2006-10 . | {'scope': 'all', 'col_superlative': '5', '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', '2006 - 10'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; 2006 - 10 }'}, 'state'], 'result': 'bihar', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; 2006 - 10 } ; state }'}, 'bihar'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; 2006 - 10 } ; state } ; bihar } = true', 'tointer': 'select the row whose 2006 - 10 record of all rows is maximum . the state record of this row is bihar .'} | eq { hop { argmax { all_rows ; 2006 - 10 } ; state } ; bihar } = true | select the row whose 2006 - 10 record of all rows is maximum . the state record of this row is bihar . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, '2006 - 10_5': 5, 'state_6': 6, 'bihar_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', '2006 - 10_5': '2006 - 10', 'state_6': 'state', 'bihar_7': 'bihar'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], '2006 - 10_5': [0], 'state_6': [1], 'bihar_7': [2]} | ['state', '1990 - 95', '1996 - 00', '2001 - 05', '2006 - 10'] | [['bihar', '0.41', '0.30', '0.43', '0.88'], ['gujarat', '0.48', '0.57', '0.64', '0.69'], ['andhra pradesh', '0.53', '0.73', '0.55', '0.61'], ['punjab', '0.32', '0.46', '0.46', '0.60'], ['jammu & kashmir', '0.13', '0.32', '0.17', '0.40'], ['haryana', '0.33', '0.60', '0.31', '0.37'], ['himachal pradesh', '0.26', '0.14', '0.23', '0.35'], ['tamil nadu', '0.19', '0.20', '0.24', '0.29'], ['madhya pradesh', '0.23', '0.22', '0.31', '0.29'], ['karnataka', '0.24', '0.19', '0.20', '0.29'], ['rajasthan', '0.27', '0.23', '0.26', '0.27'], ['kerala', '0.16', '0.20', '0.22', '0.27'], ['maharashtra', '0.45', '0.29', '0.27', '0.26'], ['uttar pradesh', '0.11', '0.11', '0.16', '0.21'], ['orissa', '0.22', '0.16', '0.15', '0.19'], ['assam', '0.21', '0.02', '0.14', '0.17'], ['west bengal', '0.11', '0.08', '0.03', '0.01']] |
ar - 15 variants | https://en.wikipedia.org/wiki/AR-15_variants | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12834315-5.html.csv | superlative | of the 4th generation ar-15 variants , the le6921sp model had the shortest barrel length . | {'scope': 'all', 'col_superlative': '6', 'row_superlative': '8', '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', 'barrel length'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; barrel length }'}, 'colt model no'], 'result': 'le6921sp', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; barrel length } ; colt model no }'}, 'le6921sp'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmin { all_rows ; barrel length } ; colt model no } ; le6921sp } = true', 'tointer': 'select the row whose barrel length record of all rows is minimum . the colt model no record of this row is le6921sp .'} | eq { hop { argmin { all_rows ; barrel length } ; colt model no } ; le6921sp } = true | select the row whose barrel length record of all rows is minimum . the colt model no record of this row is le6921sp . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'barrel length_5': 5, 'colt model no_6': 6, 'le6921sp_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'barrel length_5': 'barrel length', 'colt model no_6': 'colt model no', 'le6921sp_7': 'le6921sp'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'barrel length_5': [0], 'colt model no_6': [1], 'le6921sp_7': [2]} | ['colt model no', 'stock', 'fire control', 'rear sight', 'forward assist', 'barrel length', 'barrel profile', 'barrel twist', 'hand guards', 'bayonet lug', 'muzzle device'] | [['le1020', '4th generation', 's - 1', 'flattop', 'yes', '16 in', 'm4', '1:7', 'rail system', 'yes', 'a2'], ['le1033', '4th generation', 's - 1', 'flattop', 'yes', '11.5 in', 'a2', '1:7', 'rail system', 'yes', 'a2'], ['le6920', '4th generation', 's - 1', 'flattop', 'yes', '16 in', 'm4', '1:7', 'm4', 'yes', 'a2'], ['le6920hb', '4th generation', 's - 1', 'flattop', 'yes', '16 in', 'm4 hbar', '1:7', 'm4', 'yes', 'a2'], ['le6921', '4th generation', 's - 1', 'flattop', 'yes', '14.5 in', 'm4', '1:7', 'm4', 'yes', 'a2'], ['le6921cqb', '4th generation', 's - 1', 'flattop', 'yes', '10.5 in', 'm4 hbar', '1:7', 'm4', 'yes', 'a2'], ['le6921hb', '4th generation', 's - 1', 'flattop', 'yes', '14.5 in', 'm4 hbar', '1:7', 'm4', 'yes', 'a2'], ['le6921sp', '4th generation', 's - 1', 'flattop', 'yes', '10 in', 'm4 hbar', '1:7', 'm4', 'yes', 'a2'], ['le6933', '4th generation', 's - 1', 'flattop', 'yes', '11.5 in', 'a2', '1:7', 'short ribbed', 'yes', 'a2'], ['le6940', '4th generation', 's - 1', 'flattop', 'yes', '16 in', 'm4', '1:7', 'monolithic rail system', 'yes', 'a2'], ['le6941', '4th generation', 's - 1', 'flattop', 'yes', '16 in', 'm4', '1:7', 'rail system', 'yes', 'a2']] |
real salt lake | https://en.wikipedia.org/wiki/Real_Salt_Lake | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1053453-9.html.csv | comparative | for real salt lake , scott garlick played in 4 more games than dj countess . | {'row_1': '2', 'row_2': '3', 'col': '5', 'col_other': '2', 'relation': 'diff', 'record_mentioned': 'no', 'diff_result': {'diff_value': '4', 'bigger': 'row1'}} | {'func': 'eq', 'args': [{'func': 'diff', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', 'scott garlick'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose player record fuzzily matches to scott garlick .', 'tostr': 'filter_eq { all_rows ; player ; scott garlick }'}, 'games'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; player ; scott garlick } ; games }', 'tointer': 'select the rows whose player record fuzzily matches to scott garlick . take the games record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', 'dj countess'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose player record fuzzily matches to dj countess .', 'tostr': 'filter_eq { all_rows ; player ; dj countess }'}, 'games'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; player ; dj countess } ; games }', 'tointer': 'select the rows whose player record fuzzily matches to dj countess . take the games record of this row .'}], 'result': '4', 'ind': 4, 'tostr': 'diff { hop { filter_eq { all_rows ; player ; scott garlick } ; games } ; hop { filter_eq { all_rows ; player ; dj countess } ; games } }'}, '4'], 'result': True, 'ind': 5, 'tostr': 'eq { diff { hop { filter_eq { all_rows ; player ; scott garlick } ; games } ; hop { filter_eq { all_rows ; player ; dj countess } ; games } } ; 4 } = true', 'tointer': 'select the rows whose player record fuzzily matches to scott garlick . take the games record of this row . select the rows whose player record fuzzily matches to dj countess . take the games record of this row . the first record is 4 larger than the second record .'} | eq { diff { hop { filter_eq { all_rows ; player ; scott garlick } ; games } ; hop { filter_eq { all_rows ; player ; dj countess } ; games } } ; 4 } = true | select the rows whose player record fuzzily matches to scott garlick . take the games record of this row . select the rows whose player record fuzzily matches to dj countess . take the games record of this row . the first record is 4 larger than the second 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, 'player_8': 8, 'scott garlick_9': 9, 'games_10': 10, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_11': 11, 'player_12': 12, 'dj countess_13': 13, 'games_14': 14, '4_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', 'player_8': 'player', 'scott garlick_9': 'scott garlick', 'games_10': 'games', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_11': 'all_rows', 'player_12': 'player', 'dj countess_13': 'dj countess', 'games_14': 'games', '4_15': '4'} | {'eq_5': [6], 'result_6': [], 'diff_4': [5], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_7': [0], 'player_8': [0], 'scott garlick_9': [0], 'games_10': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_11': [1], 'player_12': [1], 'dj countess_13': [1], 'games_14': [3], '4_15': [5]} | ['rank', 'player', 'nation', 'shutouts', 'games', 'years'] | [['1', 'nick rimando', 'usa', '72', '201', '2007 - present'], ['2', 'scott garlick', 'usa', '4', '31', '2006 - 2007'], ['2', 'dj countess', 'usa', '4', '27', '2005'], ['2', 'kyle reynish', 'usa', '4', '8', '2007 - 2012'], ['5', 'chris seitz', 'usa', '1', '7', '2007 - 2009'], ['5', 'jeff attinella', 'usa', '1', '5', '2013 - present']] |
lubbock , texas | https://en.wikipedia.org/wiki/Lubbock%2C_Texas | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-136320-2.html.csv | ordinal | the smallest number of floors in buildings over 200ft in lubbock , texas is 12 . | {'scope': 'subset', 'row': '3', 'col': '4', 'order': '1', 'col_other': 'n/a', 'max_or_min': 'min_to_max', 'value_mentioned': 'yes', 'subset': {'col': '3', 'criterion': 'greater_than', 'value': '200'}} | {'func': 'eq', 'args': [{'func': 'nth_min', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'height ft ( m )', '200'], 'result': None, 'ind': 0, 'tostr': 'filter_greater { all_rows ; height ft ( m ) ; 200 }', 'tointer': 'select the rows whose height ft ( m ) record is greater than 200 .'}, 'floors ( stories )', '1'], 'result': '12', 'ind': 1, 'tostr': 'nth_min { filter_greater { all_rows ; height ft ( m ) ; 200 } ; floors ( stories ) ; 1 }', 'tointer': 'select the rows whose height ft ( m ) record is greater than 200 . the 1st minimum floors ( stories ) record of these rows is 12 .'}, '12'], 'result': True, 'ind': 2, 'tostr': 'eq { nth_min { filter_greater { all_rows ; height ft ( m ) ; 200 } ; floors ( stories ) ; 1 } ; 12 } = true', 'tointer': 'select the rows whose height ft ( m ) record is greater than 200 . the 1st minimum floors ( stories ) record of these rows is 12 .'} | eq { nth_min { filter_greater { all_rows ; height ft ( m ) ; 200 } ; floors ( stories ) ; 1 } ; 12 } = true | select the rows whose height ft ( m ) record is greater than 200 . the 1st minimum floors ( stories ) record of these rows is 12 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'nth_min_1': 1, 'filter_greater_0': 0, 'all_rows_4': 4, 'height ft (m)_5': 5, '200_6': 6, 'floors (stories)_7': 7, '1_8': 8, '12_9': 9} | {'eq_2': 'eq', 'result_3': 'true', 'nth_min_1': 'nth_min', 'filter_greater_0': 'filter_greater', 'all_rows_4': 'all_rows', 'height ft (m)_5': 'height ft ( m )', '200_6': '200', 'floors (stories)_7': 'floors ( stories )', '1_8': '1', '12_9': '12'} | {'eq_2': [3], 'result_3': [], 'nth_min_1': [2], 'filter_greater_0': [1], 'all_rows_4': [0], 'height ft (m)_5': [0], '200_6': [0], 'floors (stories)_7': [1], '1_8': [1], '12_9': [2]} | ['rank', 'name', 'height ft ( m )', 'floors ( stories )', 'year completed'] | [['1', 'metro tower', '274 ( 84 )', '20', '1955'], ['2', 'wells fargo building', '209 ( 64 )', '15', '1968'], ['3', 'ttu media and communication', '208 ( 63 )', '12', '1969'], ['4', 'overton hotel', '165 ( 50 )', '15', '2009'], ['5', 'park tower', '150 ( 46 )', '15', '1968'], ['6', 'bank of america tower', '143 ( 44 )', '12', '1940'], ['7', 'victory tower', '96 ( 29 )', '8', '1999']] |
melodifestivalen 2011 | https://en.wikipedia.org/wiki/Melodifestivalen_2011 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27994983-8.html.csv | aggregation | the average score given by viewers to artists in the melodifestivalen 2011 was 44 points . | {'scope': 'all', 'col': '6', 'type': 'average', 'result': '44', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'viewers'], 'result': '44', 'ind': 0, 'tostr': 'avg { all_rows ; viewers }'}, '44'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; viewers } ; 44 } = true', 'tointer': 'the average of the viewers record of all rows is 44 .'} | round_eq { avg { all_rows ; viewers } ; 44 } = true | the average of the viewers record of all rows is 44 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'viewers_4': 4, '44_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'viewers_4': 'viewers', '44_5': '44'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'viewers_4': [0], '44_5': [1]} | ['draw', 'artist', 'song ( english translation )', 'lyrics ( l ) / music ( m )', 'juries', 'viewers', 'total', 'place'] | [['1', 'danny saucedo', 'in the club', 'figge boström , peter boström , danny saucedo', '79', '70', '149', '2'], ['2', 'sara varga', 'spring för livet ( run for your life )', 'sara varga , figge boström', '23', '27', '50', '9'], ['3', 'the moniker', 'oh my god !', 'daniel karlsson', '55', '69', '124', '3'], ['4', 'brolle', '7 days and 7 nights', 'brolle ( m & l )', '8', '21', '29', '10'], ['9', 'the playtones', 'the king', 'fredrik kempe , peter kvint ( m & l )', '46', '33', '79', '6']] |
rowing at the 2008 summer olympics - men 's lightweight double sculls | https://en.wikipedia.org/wiki/Rowing_at_the_2008_Summer_Olympics_%E2%80%93_Men%27s_lightweight_double_sculls | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18662685-8.html.csv | ordinal | zsolt hirling and tamã ¡ s varga of hungary finished 4th in the 2008 olympics . | {'row': '4', 'col': '1', 'order': '4', 'col_other': '2', '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', 'rank', '4'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; rank ; 4 }'}, 'rowers'], 'result': 'zsolt hirling , tamã ¡ s varga', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; rank ; 4 } ; rowers }'}, 'zsolt hirling , tamã ¡ s varga'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; rank ; 4 } ; rowers } ; zsolt hirling , tamã ¡ s varga } = true', 'tointer': 'select the row whose rank record of all rows is 4th minimum . the rowers record of this row is zsolt hirling , tamã ¡ s varga .'} | eq { hop { nth_argmin { all_rows ; rank ; 4 } ; rowers } ; zsolt hirling , tamã ¡ s varga } = true | select the row whose rank record of all rows is 4th minimum . the rowers record of this row is zsolt hirling , tamã ¡ s varga . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'rank_5': 5, '4_6': 6, 'rowers_7': 7, 'zsolt hirling , tamã¡s varga_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', 'rank_5': 'rank', '4_6': '4', 'rowers_7': 'rowers', 'zsolt hirling , tamã¡s varga_8': 'zsolt hirling , tamã ¡ s varga'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'rank_5': [0], '4_6': [0], 'rowers_7': [1], 'zsolt hirling , tamã¡s varga_8': [2]} | ['rank', 'rowers', 'country', 'time', 'notes'] | [['1', 'pedro fraga , nuno mendes', 'portugal', '6:39.07', 'sa / b'], ['2', 'eyder batista , yunior perez', 'cuba', '6:40.15', 'sa / b'], ['3', 'kazushige ura , daisaku takeda', 'japan', '6:43.03', 'sc / d'], ['4', 'zsolt hirling , tamã ¡ s varga', 'hungary', '6:50.48', 'sc / d'], ['5', 'devender kumar khandwal , manjeet singh', 'india', '7:02.06', 'sc / d'], ['6', 'jang kang - eun , kim hong - kyun', 'south korea', '7:12.17', 'sc / d']] |
wru division four west | https://en.wikipedia.org/wiki/WRU_Division_Four_West | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-13758945-1.html.csv | unique | tumble rfc is the only club of the wru division four west with a lost of 2 . | {'scope': 'all', 'row': '2', 'col': '5', 'col_other': '1', 'criterion': 'equal', 'value': '2', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'lost', '2'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose lost record is equal to 2 .', 'tostr': 'filter_eq { all_rows ; lost ; 2 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; lost ; 2 } }', 'tointer': 'select the rows whose lost record is equal to 2 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'lost', '2'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose lost record is equal to 2 .', 'tostr': 'filter_eq { all_rows ; lost ; 2 }'}, 'club'], 'result': 'tumble rfc', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; lost ; 2 } ; club }'}, 'tumble rfc'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; lost ; 2 } ; club } ; tumble rfc }', 'tointer': 'the club record of this unqiue row is tumble rfc .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; lost ; 2 } } ; eq { hop { filter_eq { all_rows ; lost ; 2 } ; club } ; tumble rfc } } = true', 'tointer': 'select the rows whose lost record is equal to 2 . there is only one such row in the table . the club record of this unqiue row is tumble rfc .'} | and { only { filter_eq { all_rows ; lost ; 2 } } ; eq { hop { filter_eq { all_rows ; lost ; 2 } ; club } ; tumble rfc } } = true | select the rows whose lost record is equal to 2 . there is only one such row in the table . the club record of this unqiue row is tumble rfc . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'lost_7': 7, '2_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'club_9': 9, 'tumble rfc_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'lost_7': 'lost', '2_8': '2', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'club_9': 'club', 'tumble rfc_10': 'tumble rfc'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'lost_7': [0], '2_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'club_9': [2], 'tumble rfc_10': [3]} | ['club', 'played', 'won', 'drawn', 'lost', 'points for', 'points against', 'tries for', 'tries against', 'try bonus', 'losing bonus', 'points'] | [['club', 'played', 'won', 'drawn', 'lost', 'points for', 'points against', 'tries for', 'tries against', 'try bonus', 'losing bonus', 'points'], ['tumble rfc', '22', '20', '0', '2', '662', '291', '92', '38', '12', '0', '92'], ['pontarddulais rfc', '22', '16', '0', '6', '631', '375', '85', '43', '12', '3', '79'], ['tenby united rfc', '22', '16', '0', '6', '584', '388', '70', '47', '11', '2', '77'], ['cefneithin rfc', '22', '16', '0', '6', '534', '386', '71', '51', '9', '2', '75'], ['milford haven rfc', '22', '11', '0', '11', '571', '433', '82', '60', '9', '6', '59'], ['amman united rfc', '22', '11', '0', '11', '565', '567', '77', '78', '10', '3', '57'], ['betws rfc', '22', '11', '0', '11', '415', '521', '55', '67', '5', '4', '53'], ['hendy rfc', '22', '7', '0', '15', '398', '571', '50', '81', '4', '4', '36'], ['trimsaran rfc', '22', '5', '1', '16', '353', '493', '39', '68', '3', '10', '35'], ['pembroke dock harlequins rfc', '22', '7', '0', '15', '324', '578', '39', '76', '2', '3', '33'], ['pembroke rfc', '22', '6', '0', '16', '335', '576', '47', '73', '5', '3', '32'], ['burry port rfc', '22', '5', '1', '16', '380', '573', '47', '72', '3', '6', '31']] |
list of are you afraid of the dark ? episodes | https://en.wikipedia.org/wiki/List_of_Are_You_Afraid_of_the_Dark%3F_episodes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-10470082-3.html.csv | ordinal | of the first 12 episodes of the second season of are you afraid of the dark ? , the one of the third-earliest us air date has no villains . | {'row': '3', 'col': '6', 'order': '3', 'col_other': '6', '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', 'us air date', '3'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; us air date ; 3 }'}, 'us air date'], 'result': 'july 3 , 1993', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; us air date ; 3 } ; us air date }'}, 'july 3 , 1993'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; us air date ; 3 } ; us air date } ; july 3 , 1993 } = true', 'tointer': 'select the row whose us air date record of all rows is 3rd minimum . the us air date record of this row is july 3 , 1993 .'} | eq { hop { nth_argmin { all_rows ; us air date ; 3 } ; us air date } ; july 3 , 1993 } = true | select the row whose us air date record of all rows is 3rd minimum . the us air date record of this row is july 3 , 1993 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'us air date_5': 5, '3_6': 6, 'us air date_7': 7, 'july 3 , 1993_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', 'us air date_5': 'us air date', '3_6': '3', 'us air date_7': 'us air date', 'july 3 , 1993_8': 'july 3 , 1993'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'us air date_5': [0], '3_6': [0], 'us air date_7': [1], 'july 3 , 1993_8': [2]} | ['no', '-', 'title', 'director', 'writer', 'us air date', 'storyteller', 'villains'] | [['14', '1', 'the tale of the final wish', 'd j machale', 'chloe brown', 'june 19 , 1993', 'kristen', 'the sandman'], ['15', '2', 'the tale of the midnight madness', 'd j machale', 'chloe brown', 'june 26 , 1993', 'frank', 'nosferatu and dr vink'], ['16', '3', 'the tale of locker 22', 'david winning', 'chloe brown', 'july 3 , 1993', 'kristen', 'none'], ['17', '4', 'the tale of the thirteenth floor', 'michael keusch', 'anne appelton', 'july 10 , 1993', 'betty ann', 'leonid , olga , and raymond'], ['19', '6', 'the tale of the dark dragon', 'd j machale', 'allison lea bingeman', 'july 24 , 1993', "david ( for gary 's birthday , borrowing sardo )", 'the dark dragon potion'], ['20', '8', 'the tale of the whispering walls', 'd j machale', 'allison lea bingeman', 'july 31 , 1993', 'betty ann', 'master raymond'], ['21', '7', 'the tale of the frozen ghost', 'ron oliver', 'naomi janzen', 'august 14 , 1993', 'kristen', 'none'], ['22', '9', 'the tale of the full moon', 'ron oliver', 'ron oliver', 'august 21 , 1993', 'frank', 'gordon , the werewolf'], ['23', '10', 'the tale of the shiny red bicycle', 'david winning', 'cassandra schafhausen', 'august 28 , 1993', 'david', 'none'], ['24', '11', "the tale of the magician 's assistant", 'ron oliver', 'cassandra schafhausen', 'september 11 , 1993', 'gary', 'nazrak'], ['25', '12', 'the tale of the hatching', 'd j machale', 'chloe brown', 'september 25 , 1993', 'david', 'mr and mrs taylor']] |
2008 - 09 nbl season | https://en.wikipedia.org/wiki/2008%E2%80%9309_NBL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16653153-8.html.csv | aggregation | the home teams all scored around 100 points each during their match . | {'scope': 'all', 'col': '3', 'type': 'average', 'result': '100', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'score'], 'result': '100', 'ind': 0, 'tostr': 'avg { all_rows ; score }'}, '100'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; score } ; 100 } = true', 'tointer': 'the average of the score record of all rows is 100 .'} | round_eq { avg { all_rows ; score } ; 100 } = true | the average of the score record of all rows is 100 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'score_4': 4, '100_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'score_4': 'score', '100_5': '100'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'score_4': [0], '100_5': [1]} | ['date', 'home team', 'score', 'away team', 'venue', 'box score', 'report'] | [['13 september', 'cairns taipans', '98 - 92', 'south dragons', 'cairns convention centre', 'box score', '-'], ['14 september', 'sydney spirit', '102 - 112', 'melbourne tigers', 'state sports centre', 'box score', '-'], ['17 september', 'south dragons', '97 - 81', 'perth wildcats', 'hisense arena', 'box score', '-'], ['18 september', 'new zealand breakers', '114 - 93', 'wollongong hawks', 'north shore events centre', 'box score', '-'], ['19 september', 'gold coast blaze', '75 - 85', 'cairns taipans', 'gold coast convention centre', 'box score', '-'], ['19 september', 'adelaide 36ers', '109 - 82', 'townsville crocodiles', 'distinctive homes dome', 'box score', '-'], ['20 september', 'melbourne tigers', '92 - 76', 'gold coast blaze', 'state netball and hockey centre', 'box score', '-'], ['20 september', 'wollongong hawks', '111 - 99', 'sydney spirit', 'win entertainment centre', 'box score', '-'], ['21 september', 'perth wildcats', '87 - 91', 'south dragons', 'challenge stadium', 'box score', '-']] |
kslt | https://en.wikipedia.org/wiki/KSLT | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10044708-2.html.csv | comparative | the k276dm station broadcasts on a lower mhz frequency than the k296ds station . | {'row_1': '2', 'row_2': '6', 'col': '2', 'col_other': '1', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'call sign', 'k276dm'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose call sign record fuzzily matches to k276dm .', 'tostr': 'filter_eq { all_rows ; call sign ; k276dm }'}, 'frequency mhz'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; call sign ; k276dm } ; frequency mhz }', 'tointer': 'select the rows whose call sign record fuzzily matches to k276dm . take the frequency mhz record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'call sign', 'k296ds'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose call sign record fuzzily matches to k296ds .', 'tostr': 'filter_eq { all_rows ; call sign ; k296ds }'}, 'frequency mhz'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; call sign ; k296ds } ; frequency mhz }', 'tointer': 'select the rows whose call sign record fuzzily matches to k296ds . take the frequency mhz record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; call sign ; k276dm } ; frequency mhz } ; hop { filter_eq { all_rows ; call sign ; k296ds } ; frequency mhz } } = true', 'tointer': 'select the rows whose call sign record fuzzily matches to k276dm . take the frequency mhz record of this row . select the rows whose call sign record fuzzily matches to k296ds . take the frequency mhz record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; call sign ; k276dm } ; frequency mhz } ; hop { filter_eq { all_rows ; call sign ; k296ds } ; frequency mhz } } = true | select the rows whose call sign record fuzzily matches to k276dm . take the frequency mhz record of this row . select the rows whose call sign record fuzzily matches to k296ds . take the frequency mhz 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, 'call sign_7': 7, 'k276dm_8': 8, 'frequency mhz_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'call sign_11': 11, 'k296ds_12': 12, 'frequency mhz_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', 'call sign_7': 'call sign', 'k276dm_8': 'k276dm', 'frequency mhz_9': 'frequency mhz', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'call sign_11': 'call sign', 'k296ds_12': 'k296ds', 'frequency mhz_13': 'frequency mhz'} | {'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'call sign_7': [0], 'k276dm_8': [0], 'frequency mhz_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'call sign_11': [1], 'k296ds_12': [1], 'frequency mhz_13': [3]} | ['call sign', 'frequency mhz', 'city of license', 'erp w', 'class', 'fcc info'] | [['k276dl', '103.1', 'hemingford , nebraska', '80', 'd', 'fcc'], ['k276dm', '103.1', 'chadron , nebraska', '5', 'd', 'fcc'], ['k292ec', '106.3', 'hot springs , south dakota', '68', 'd', 'fcc'], ['k292dn', '106.3', 'newcastle , wyoming', '31', 'd', 'fcc'], ['k292dz', '106.3', 'sheridan , wyoming', '135', 'd', 'fcc'], ['k296ds', '107.1', 'alliance , nebraska', '74', 'd', 'fcc']] |
christian uflacker | https://en.wikipedia.org/wiki/Christian_Uflacker | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13044634-2.html.csv | ordinal | christian uflacker 's match against mark sinclair recorded the fastest participation time . | {'row': '4', 'col': '6', 'order': '1', 'col_other': '3', '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', 'time', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; time ; 1 }'}, 'opponent'], 'result': 'mark sinclair', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; time ; 1 } ; opponent }'}, 'mark sinclair'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; time ; 1 } ; opponent } ; mark sinclair } = true', 'tointer': 'select the row whose time record of all rows is 1st minimum . the opponent record of this row is mark sinclair .'} | eq { hop { nth_argmin { all_rows ; time ; 1 } ; opponent } ; mark sinclair } = true | select the row whose time record of all rows is 1st minimum . the opponent record of this row is mark sinclair . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'time_5': 5, '1_6': 6, 'opponent_7': 7, 'mark sinclair_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', 'time_5': 'time', '1_6': '1', 'opponent_7': 'opponent', 'mark sinclair_8': 'mark sinclair'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'time_5': [0], '1_6': [0], 'opponent_7': [1], 'mark sinclair_8': [2]} | ['res', 'record', 'opponent', 'method', 'round', 'time', 'location'] | [['win', '5 - 0', 'cliff wright', 'technical decision ( unanimous )', '3', '2:26', 'hammond , indiana , united states'], ['win', '4 - 0', 'lc davis', 'decision ( split )', '3', '5:00', 'valparaiso , united states'], ['win', '3 - 0', 'jonatas novaes', 'decision ( unanimous )', '3', '5:00', 'hoffman estates , illinois , united states'], ['win', '2 - 0', 'mark sinclair', 'submission ( rear naked choke )', '1', '1:22', 'hammond , indiana , united states'], ['win', '1 - 0', 'kori trussell', 'submission ( rear naked choke )', '1', '2:20', 'hammond , indiana , united states']] |
1969 buffalo bills season | https://en.wikipedia.org/wiki/1969_Buffalo_Bills_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16351004-2.html.csv | aggregation | the average attendance for the buffalo bills ' games in 1969 was 43,583 . | {'scope': 'all', 'col': '6', 'type': 'average', 'result': '43583', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'attendance'], 'result': '43583', 'ind': 0, 'tostr': 'avg { all_rows ; attendance }'}, '43583'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; attendance } ; 43583 } = true', 'tointer': 'the average of the attendance record of all rows is 43583 .'} | round_eq { avg { all_rows ; attendance } ; 43583 } = true | the average of the attendance record of all rows is 43583 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'attendance_4': 4, '43583_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'attendance_4': 'attendance', '43583_5': '43583'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'attendance_4': [0], '43583_5': [1]} | ['date', 'opponent', 'score', 'result', 'record', 'attendance'] | [['september 14', 'new york jets', '33 - 19', 'loss', '0 - 1', '46165'], ['september 21', 'houston oilers', '21 - 17', 'loss', '0 - 2', '40146'], ['september 28', 'denver broncos', '41 - 28', 'win', '1 - 2', '40302'], ['october 5', 'houston oilers', '28 - 14', 'loss', '1 - 3', '46485'], ['october 11', 'boston patriots', '23 - 16', 'win', '2 - 3', '46201'], ['october 19', 'oakland raiders', '50 - 21', 'loss', '2 - 4', '54418'], ['october 26', 'miami dolphins', '24 - 6', 'loss', '2 - 5', '39837'], ['november 2', 'kansas city chiefs', '29 - 7', 'loss', '2 - 6', '45844'], ['november 9', 'new york jets', '16 - 6', 'loss', '2 - 7', '62680'], ['november 16', 'miami dolphins', '28 - 3', 'win', '3 - 7', '32686'], ['november 23', 'boston patriots', '35 - 21', 'loss', '3 - 8', '25584'], ['november 30', 'cincinnati bengals', '16 - 13', 'win', '4 - 8', '35122'], ['december 7', 'kansas city chiefs', '22 - 19', 'loss', '4 - 9', '47112'], ['december 14', 'san diego chargers', '45 - 6', 'loss', '4 - 10', '47582']] |
ewen leslie | https://en.wikipedia.org/wiki/Ewen_Leslie | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15292215-3.html.csv | unique | only , the war of the roses , in which ewen leslie appeared , had benedict andrews as the director . | {'scope': 'all', 'row': '8', 'col': '4', 'col_other': '2', 'criterion': 'equal', 'value': 'benedict andrews', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'director', 'benedict andrews'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose director record fuzzily matches to benedict andrews .', 'tostr': 'filter_eq { all_rows ; director ; benedict andrews }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; director ; benedict andrews } }', 'tointer': 'select the rows whose director record fuzzily matches to benedict andrews . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'director', 'benedict andrews'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose director record fuzzily matches to benedict andrews .', 'tostr': 'filter_eq { all_rows ; director ; benedict andrews }'}, 'production'], 'result': 'the war of the roses', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; director ; benedict andrews } ; production }'}, 'the war of the roses'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; director ; benedict andrews } ; production } ; the war of the roses }', 'tointer': 'the production record of this unqiue row is the war of the roses .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; director ; benedict andrews } } ; eq { hop { filter_eq { all_rows ; director ; benedict andrews } ; production } ; the war of the roses } } = true', 'tointer': 'select the rows whose director record fuzzily matches to benedict andrews . there is only one such row in the table . the production record of this unqiue row is the war of the roses .'} | and { only { filter_eq { all_rows ; director ; benedict andrews } } ; eq { hop { filter_eq { all_rows ; director ; benedict andrews } ; production } ; the war of the roses } } = true | select the rows whose director record fuzzily matches to benedict andrews . there is only one such row in the table . the production record of this unqiue row is the war of the roses . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'director_7': 7, 'benedict andrews_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'production_9': 9, 'the war of the roses_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'director_7': 'director', 'benedict andrews_8': 'benedict andrews', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'production_9': 'production', 'the war of the roses_10': 'the war of the roses'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'director_7': [0], 'benedict andrews_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'production_9': [2], 'the war of the roses_10': [3]} | ['year', 'production', 'role', 'director', 'company'] | [['2013', 'rosencrantz and guildenstern are dead', 'the player', 'simon philips', 'sydney theatre company'], ['2013', 'cat on a hot tin roof', 'brick pollitt', 'simon stone', 'belvoir st theatre'], ['2011', 'hamlet', 'hamlet', 'simon phillips', 'melbourne theatre company'], ['2011', 'the wild duck', 'hjalmar ekdal', 'simon stone', 'belvoir st theatre'], ['2010', 'the trial', 'josef k', 'matthew lutton', 'malthouse theatre / sydney theatre company'], ['2010', 'richard iii', 'richard iii', 'simon phillips', 'melbourne theatre company'], ['2009', 'the promise', 'marat', 'simon stone', 'belvoir st theatre'], ['2009', 'the war of the roses', 'prince hal / henry v', 'benedict andrews', 'sydney theatre company'], ['2008', 'gallipoli', 'billy hughes / ataturk', 'nigel jamieson', 'sydney theatre company'], ['2008', "the serpent 's teeth", 'sam lewis', 'pamela rabe and tim maddock', 'sydney theatre company'], ['2007', 'riflemind', 'lee', 'philip seymour hoffman', 'sydney theatre company'], ['2007', 'dead caesar', 'cassius', 'tamara cook', 'sydney theatre company'], ['2007', 'paul', 'yeshua', 'wesley enoch', 'belvoir st theatre'], ['2005', 'shakesperealism', 'lewis', 'tamara cook', 'tamarama rock surfers'], ['2004', 'this blasted earth', 'father / scarlett', 'leland kean', 'tamarama rock surfers'], ['2004', 'cross sections', 'aaron', 'chris mead', 'tamarama rock surfers'], ['2003', 'chicks will dig you !', 'seb', 'tamara cook', 'belvoir st theatre - downstairs']] |
2005 buffalo bills season | https://en.wikipedia.org/wiki/2005_Buffalo_Bills_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18695319-1.html.csv | comparative | eric king was picked in an earlier round than lionel gates in the 2005 buffalo bills season . | {'row_1': '4', 'row_2': '6', 'col': '1', 'col_other': '3', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', 'eric king'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose player record fuzzily matches to eric king .', 'tostr': 'filter_eq { all_rows ; player ; eric king }'}, 'round'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; player ; eric king } ; round }', 'tointer': 'select the rows whose player record fuzzily matches to eric king . take the round record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', 'lionel gates'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose player record fuzzily matches to lionel gates .', 'tostr': 'filter_eq { all_rows ; player ; lionel gates }'}, 'round'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; player ; lionel gates } ; round }', 'tointer': 'select the rows whose player record fuzzily matches to lionel gates . take the round record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; player ; eric king } ; round } ; hop { filter_eq { all_rows ; player ; lionel gates } ; round } } = true', 'tointer': 'select the rows whose player record fuzzily matches to eric king . take the round record of this row . select the rows whose player record fuzzily matches to lionel gates . take the round record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; player ; eric king } ; round } ; hop { filter_eq { all_rows ; player ; lionel gates } ; round } } = true | select the rows whose player record fuzzily matches to eric king . take the round record of this row . select the rows whose player record fuzzily matches to lionel gates . take the round 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, 'player_7': 7, 'eric king_8': 8, 'round_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'player_11': 11, 'lionel gates_12': 12, 'round_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', 'player_7': 'player', 'eric king_8': 'eric king', 'round_9': 'round', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'player_11': 'player', 'lionel gates_12': 'lionel gates', 'round_13': 'round'} | {'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'player_7': [0], 'eric king_8': [0], 'round_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'player_11': [1], 'lionel gates_12': [1], 'round_13': [3]} | ['round', 'pick', 'player', 'position', 'college'] | [['2', '5', 'roscoe parrish', 'wide receiver', 'miami ( fla )'], ['3', '86', 'kevin everett', 'tight end', 'miami ( fla )'], ['4', '122', 'duke preston', 'center', 'illinois'], ['5', '156', 'eric king', 'cornerback', 'wake forest'], ['6', '197', 'justin geisinger', 'offensive guard', 'vanterbilt'], ['7', '236', 'lionel gates', 'running back', 'louisville']] |
chicago throwbacks | https://en.wikipedia.org/wiki/Chicago_Throwbacks | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-10595672-1.html.csv | majority | imari sawyer had the majority of high assists performances for the chicago throwbacks . | {'scope': 'all', 'col': '7', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'imari sawyer', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'high assists', 'imari sawyer'], 'result': True, 'ind': 0, 'tointer': 'for the high assists records of all rows , most of them fuzzily match to imari sawyer .', 'tostr': 'most_eq { all_rows ; high assists ; imari sawyer } = true'} | most_eq { all_rows ; high assists ; imari sawyer } = true | for the high assists records of all rows , most of them fuzzily match to imari sawyer . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'high assists_3': 3, 'imari sawyer_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'high assists_3': 'high assists', 'imari sawyer_4': 'imari sawyer'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'high assists_3': [0], 'imari sawyer_4': [0]} | ['date', 'opponent', 'home / away', 'score', 'high points', 'high rebounds', 'high assists', 'location / attendance', 'record'] | [['january 2', 'battle creek knights', 'away', '113 - 120', 'stanley thomas ( 23 )', "michael o'neal ( 8 )", 'imari sawyer ( 7 )', 'kellogg arena ( 1257 )', '0 - 1'], ['january 4', 'detroit panthers', 'away', '110 - 106', 'stanley thomas ( 24 )', 'stanley thomas & marcus jackson ( 9 )', 'imari sawyer ( 8 )', 'groves high school', '1 - 1'], ['january 10', 'battle creek knights', 'home', '106 - 94', 'imari sawyer ( 18 )', 'dameon mason ( 7 )', 'imari sawyer ( 5 )', 'attack athletics', '1 - 2'], ['january 12', 'quebec kebs', 'home', '91 - 92', 'dameon mason ( 19 )', 'stanley thomas & michael herman ( 7 )', 'imari sawyer ( 10 )', 'attack athletics', '2 - 2'], ['january 18', 'detroit panthers', 'home', '107 - 119', 'stanley thomas ( 21 )', 'james booyer ( 11 )', "michael o'neal ( 3 )", 'attack athletics', '3 - 2'], ['january 23', 'mid - michigan destroyers', 'away', '105 - 116', 'anthony simmons ( 27 )', 'anthony simmons ( 10 )', 'stanley thomas ( 3 )', 'bay city western high school', '3 - 3'], ['january 24', 'rochester razorsharks', 'home', '112 - 83', 'dameon mason ( 22 )', 'james booyer ( 12 )', 'stanley thomas & michael herman ( 3 )', 'attack athletics', '3 - 4'], ['january 26', 'mid - michigan destroyers', 'home', '117 - 104', 'michael herman ( 28 )', 'amir major ( 16 )', 'imari sawyer ( 10 )', 'attack athletics', '3 - 5'], ['february 6', 'battle creek knights', 'away', '112 - 117', 'stanley thomas ( 29 )', 'anthony simmons ( 11 )', 'michael herman ( 6 )', 'kellogg arena', '3 - 6'], ['february 8', 'detroit panthers', 'away', '114 - 113', 'dameon mason ( 24 )', 'casey love ( 13 )', 'imari sawyer ( 8 )', 'groves high school', '4 - 6'], ['february 13', 'mid - michigan destroyers', 'home', '108 - 121', 'stanley thomas ( 32 )', 'stanley thomas ( 9 )', 'imari sawyer ( 9 )', 'attack athletics', '5 - 6'], ['february 20', 'quebec kebs', 'away', '109 - 104', 'imari sawyer ( 28 )', 'anthony simmons ( 8 )', 'imari sawyer ( 11 )', 'pavillon de la jeunesse', '6 - 6'], ['february 22', 'augusta groove', 'away', '105 - 119', 'willie mitchell ( 25 )', 'imari sawyer ( 9 )', "michael o'neal ( 4 )", 'richmond academy', '6 - 7'], ['february 27', 'manchester millrats', 'away', '105 - 124', 'dameon mason ( 22 )', 'casey love ( 12 )', 'imari sawyer & michael herman ( 7 )', 'southern new hampshire fieldhouse', '6 - 8'], ['march 6', 'detroit panthers', 'home', '123 - 116', 'dameon mason ( 28 )', 'willie mitchell & dameon mason ( 4 )', 'imari sawyer ( 10 )', 'attack athletics', '6 - 9'], ['march 8', 'battle creek knights', 'home', '114 - 109', 'casey love ( 22 )', 'willie mitchell ( 8 )', 'imari sawyer ( 11 )', 'attack athletics', '6 - 10'], ['march 13', 'battle creek knights', 'home', '120 - 123', 'stanley thomas ( 46 )', 'casey love ( 15 )', 'imari sawyer ( 10 )', 'attack athletics', '6 - 11'], ['march 15', 'manchester millrats', 'home', '122 - 99', 'stanley thomas ( 25 )', 'stanley thomas ( 11 )', 'imari sawyer ( 8 )', 'attack athletics', '6 - 12'], ['march 27', 'battle creek knights', 'home', '121 - 95', 'casey love ( 28 )', 'casey love ( 11 )', 'imari sawyer ( 10 )', 'attack athletics', '6 - 13']] |
finland 's next top model | https://en.wikipedia.org/wiki/Finland%27s_Next_Top_Model | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16805656-1.html.csv | comparative | in finland 's next top model , cycle 2 had one less contestant than cycle 1 . | {'row_1': '2', 'row_2': '1', 'col': '5', 'col_other': '1', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'cycle', '2'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose cycle record fuzzily matches to 2 .', 'tostr': 'filter_eq { all_rows ; cycle ; 2 }'}, 'number of contestants'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; cycle ; 2 } ; number of contestants }', 'tointer': 'select the rows whose cycle record fuzzily matches to 2 . take the number of contestants record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'cycle', '1'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose cycle record fuzzily matches to 1 .', 'tostr': 'filter_eq { all_rows ; cycle ; 1 }'}, 'number of contestants'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; cycle ; 1 } ; number of contestants }', 'tointer': 'select the rows whose cycle record fuzzily matches to 1 . take the number of contestants record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; cycle ; 2 } ; number of contestants } ; hop { filter_eq { all_rows ; cycle ; 1 } ; number of contestants } } = true', 'tointer': 'select the rows whose cycle record fuzzily matches to 2 . take the number of contestants record of this row . select the rows whose cycle record fuzzily matches to 1 . take the number of contestants record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; cycle ; 2 } ; number of contestants } ; hop { filter_eq { all_rows ; cycle ; 1 } ; number of contestants } } = true | select the rows whose cycle record fuzzily matches to 2 . take the number of contestants record of this row . select the rows whose cycle record fuzzily matches to 1 . take the number of contestants 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, 'cycle_7': 7, '2_8': 8, 'number of contestants_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'cycle_11': 11, '1_12': 12, 'number of contestants_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', 'cycle_7': 'cycle', '2_8': '2', 'number of contestants_9': 'number of contestants', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'cycle_11': 'cycle', '1_12': '1', 'number of contestants_13': 'number of contestants'} | {'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'cycle_7': [0], '2_8': [0], 'number of contestants_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'cycle_11': [1], '1_12': [1], 'number of contestants_13': [3]} | ['cycle', 'premiere date', 'winner', 'runner - up', 'number of contestants', 'international destinations'] | [['1', 'april 6 , 2008', 'ani alitalo', 'darina shved', '12', 'stockholm turkey'], ['2', 'april 13 , 2009', 'nanna grundfeldt', 'anna - kaisa tyrväinen', '11', 'paris gran canaria'], ['3', 'april 12 , 2010', 'jenna kuokkanen', 'saara sihvonen', '11', 'milan egypt'], ['4', 'september 12 , 2011', 'anna - sofia ali - sisto', 'helen preis', '12', 'london lisbon'], ['5', 'september 3 , 2012', 'meri ikonen', 'matleena helander', '11', 'reykjavík kenya'], ['6', 'tba', 'tba', 'tba', 'tba', 'tba']] |
2008 washington redskins season | https://en.wikipedia.org/wiki/2008_Washington_Redskins_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-10966926-2.html.csv | count | in the 2008 washington redskins season , among the players with height 6 ' 4 , 2 of them were picked during the 2nd round . | {'scope': 'subset', 'criterion': 'equal', 'value': '2', 'result': '2', 'col': '1', 'subset': {'col': '5', 'criterion': 'equal', 'value': "6 ' 4"}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'height', "6 ' 4"], 'result': None, 'ind': 0, 'tostr': "filter_eq { all_rows ; height ; 6 ' 4 }", 'tointer': "select the rows whose height record fuzzily matches to 6 ' 4 ."}, 'round', '2'], 'result': None, 'ind': 1, 'tointer': "select the rows whose height record fuzzily matches to 6 ' 4 . among these rows , select the rows whose round record is equal to 2 .", 'tostr': "filter_eq { filter_eq { all_rows ; height ; 6 ' 4 } ; round ; 2 }"}], 'result': '2', 'ind': 2, 'tostr': "count { filter_eq { filter_eq { all_rows ; height ; 6 ' 4 } ; round ; 2 } }", 'tointer': "select the rows whose height record fuzzily matches to 6 ' 4 . among these rows , select the rows whose round record is equal to 2 . the number of such rows is 2 ."}, '2'], 'result': True, 'ind': 3, 'tostr': "eq { count { filter_eq { filter_eq { all_rows ; height ; 6 ' 4 } ; round ; 2 } } ; 2 } = true", 'tointer': "select the rows whose height record fuzzily matches to 6 ' 4 . among these rows , select the rows whose round record is equal to 2 . the number of such rows is 2 ."} | eq { count { filter_eq { filter_eq { all_rows ; height ; 6 ' 4 } ; round ; 2 } } ; 2 } = true | select the rows whose height record fuzzily matches to 6 ' 4 . among these rows , select the rows whose round record is equal to 2 . the number of such rows is 2 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_eq_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'height_6': 6, "6'4_7": 7, 'round_8': 8, '2_9': 9, '2_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_eq_1': 'filter_eq', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'height_6': 'height', "6'4_7": "6 ' 4", 'round_8': 'round', '2_9': '2', '2_10': '2'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_eq_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'height_6': [0], "6'4_7": [0], 'round_8': [1], '2_9': [1], '2_10': [3]} | ['round', 'choice', 'player name', 'position', 'height', 'weight', 'college'] | [['2', '34', 'devin thomas', 'wide receiver', "6 ' 2", '215', 'michigan state'], ['2', '48', 'fred davis', 'tight end', "6 ' 4", '250', 'southern cal'], ['2', '51', 'malcolm kelly', 'wide receiver', "6 ' 4", '219', 'oklahoma'], ['3', '96', 'chad rinehart', 'offensive guard', "6 ' 5", '320', 'northern iowa'], ['4', '124', 'justin tryon', 'cornerback', "5 ' 9", '180', 'arizona state'], ['6', '168', 'durant brooks', 'punter', "6 ' 0", '204', 'georgia tech'], ['6', '180', 'kareem moore', 'safety', "5 ' 11", '213', 'nicholls state'], ['6', '186', 'colt brennan', 'quarterback', "6 ' 2", '205', 'hawaii'], ['7', '242', 'rob jackson', 'defensive end', "6 ' 4", '257', 'kansas state']] |
2007 abc supply company a.j. foyt 225 | https://en.wikipedia.org/wiki/2007_ABC_Supply_Company_A.J._Foyt_225 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-17330069-1.html.csv | comparative | in the 2007 abc supply company a.j. foyt 225 jeff simmons completed more laps than sarah fisher . | {'row_1': '10', 'row_2': '14', 'col': '5', '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', 'driver', 'jeff simmons'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose driver record fuzzily matches to jeff simmons .', 'tostr': 'filter_eq { all_rows ; driver ; jeff simmons }'}, 'laps'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; driver ; jeff simmons } ; laps }', 'tointer': 'select the rows whose driver record fuzzily matches to jeff simmons . take the laps record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'driver', 'sarah fisher'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose driver record fuzzily matches to sarah fisher .', 'tostr': 'filter_eq { all_rows ; driver ; sarah fisher }'}, 'laps'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; driver ; sarah fisher } ; laps }', 'tointer': 'select the rows whose driver record fuzzily matches to sarah fisher . take the laps record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; driver ; jeff simmons } ; laps } ; hop { filter_eq { all_rows ; driver ; sarah fisher } ; laps } } = true', 'tointer': 'select the rows whose driver record fuzzily matches to jeff simmons . take the laps record of this row . select the rows whose driver record fuzzily matches to sarah fisher . take the laps record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; driver ; jeff simmons } ; laps } ; hop { filter_eq { all_rows ; driver ; sarah fisher } ; laps } } = true | select the rows whose driver record fuzzily matches to jeff simmons . take the laps record of this row . select the rows whose driver record fuzzily matches to sarah fisher . take the laps 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, 'driver_7': 7, 'jeff simmons_8': 8, 'laps_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'driver_11': 11, 'sarah fisher_12': 12, 'laps_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', 'driver_7': 'driver', 'jeff simmons_8': 'jeff simmons', 'laps_9': 'laps', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'driver_11': 'driver', 'sarah fisher_12': 'sarah fisher', 'laps_13': 'laps'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'driver_7': [0], 'jeff simmons_8': [0], 'laps_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'driver_11': [1], 'sarah fisher_12': [1], 'laps_13': [3]} | ['fin pos', 'car no', 'driver', 'team', 'laps', 'time / retired', 'grid', 'laps led', 'points'] | [['1', '11', 'tony kanaan', 'andretti green', '225', '1:47:42.4393', '3', '25', '50'], ['2', '27', 'dario franchitti', 'andretti green', '225', '+ 2.5707', '10', '0', '40'], ['3', '10', 'dan wheldon', 'target chip ganassi', '225', '+ 3.1149', '4', '37', '35'], ['4', '9', 'scott dixon', 'target chip ganassi', '225', '+ 3.4026', '2', '0', '32'], ['5', '4', 'vitor meira', 'panther racing', '225', '+ 5.2684', '9', '0', '30'], ['6', '8', 'scott sharp', 'rahal letterman', '225', '+ 6.8359', '11', '0', '28'], ['7', '20', 'ed carpenter', 'vision racing', '225', '+ 7.0360', '8', '0', '26'], ['8', '7', 'danica patrick', 'andretti green', '225', '+ 8.0205', '17', '0', '24'], ['9', '6', 'sam hornish , jr', 'team penske', '224', '+ 1 lap', '5', '0', '22'], ['10', '17', 'jeff simmons', 'rahal letterman', '224', '+ 1 lap', '18', '0', '20'], ['11', '14', 'darren manning', 'aj foyt racing', '224', '+ 1 lap', '15', '0', '19'], ['12', '55', 'kosuke matsuura', 'panther racing', '223', '+ 2 laps', '6', '0', '18'], ['13', '22', 'a j foyt iv', 'vision racing', '222', '+ 3 laps', '12', '0', '17'], ['14', '5', 'sarah fisher', 'dreyer & reinbold racing', '221', '+ 4 laps', '16', '0', '16'], ['15', '26', 'marco andretti', 'andretti green', '209', 'accident', '19', '0', '15'], ['16', '3', 'hãlio castroneves', 'team penske', '201', 'rear wing', '1', '126', '14 + 3'], ['17', '2', 'tomas scheckter', 'vision racing', '159', 'mechanical', '13', '0', '13'], ['18', '15', 'buddy rice', 'dreyer & reinbold racing', '156', 'accident', '7', '37', '12']] |
bulgaria in the eurovision song contest 2009 | https://en.wikipedia.org/wiki/Bulgaria_in_the_Eurovision_Song_Contest_2009 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18593648-14.html.csv | aggregation | all artists in the bulgaria in the eurovision song contest of 2009 received an average of 8.33 % of the televotes . | {'scope': 'all', 'col': '4', 'type': 'average', 'result': '8.33', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'televote / sms'], 'result': '8.33', 'ind': 0, 'tostr': 'avg { all_rows ; televote / sms }'}, '8.33'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; televote / sms } ; 8.33 } = true', 'tointer': 'the average of the televote / sms record of all rows is 8.33 .'} | round_eq { avg { all_rows ; televote / sms } ; 8.33 } = true | the average of the televote / sms record of all rows is 8.33 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'televote / sms_4': 4, '8.33_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'televote / sms_4': 'televote / sms', '8.33_5': '8.33'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'televote / sms_4': [0], '8.33_5': [1]} | ['draw', 'artist', 'song', 'televote / sms', 'place'] | [['1', 'stefan ilchev', 'get up', '2.95 %', '7'], ['2', 'moto', 'razstoyaniya', '0.37 %', '12'], ['3', 'poli genova', 'one lifetime is not enough', '11.74 %', '2'], ['4', 'danny milev', 'nyama vreme', '2.39 %', '9'], ['5', 'ivelina', 'ready for love', '2.53 %', '8'], ['6', 'grafa', 'vrag', '3.91 %', '5'], ['7', 'sahara', "do n't kiss for the money", '3.20 %', '6'], ['8', 'mariana popova', 'crazy', '8.45 %', '3'], ['9', 'jura tone feat lady b', 'chance to love you', '2.03 %', '10'], ['10', 'stefan dobrev', 'everlasting', '1.16 %', '11'], ['11', 'krassimir avramov', 'illusion', '55.52 %', '1'], ['12', 'nora', "it 's not right", '5.75 %', '4']] |
louis armstrong | https://en.wikipedia.org/wiki/Louis_Armstrong | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18313-2.html.csv | majority | most of louis armstrong 's records were recorded before 1960 . | {'scope': 'all', 'col': '1', 'most_or_all': 'most', 'criterion': 'less_than', 'value': '1960', 'subset': None} | {'func': 'most_less', 'args': ['all_rows', 'year recorded', '1960'], 'result': True, 'ind': 0, 'tointer': 'for the year recorded records of all rows , most of them are less than 1960 .', 'tostr': 'most_less { all_rows ; year recorded ; 1960 } = true'} | most_less { all_rows ; year recorded ; 1960 } = true | for the year recorded records of all rows , most of them are less than 1960 . | 1 | 1 | {'most_less_0': 0, 'result_1': 1, 'all_rows_2': 2, 'year recorded_3': 3, '1960_4': 4} | {'most_less_0': 'most_less', 'result_1': 'true', 'all_rows_2': 'all_rows', 'year recorded_3': 'year recorded', '1960_4': '1960'} | {'most_less_0': [1], 'result_1': [], 'all_rows_2': [0], 'year recorded_3': [0], '1960_4': [0]} | ['year recorded', 'title', 'genre', 'label', 'year inducted'] | [['year recorded', 'title', 'genre', 'label', 'year inducted'], ['1929', 'st louis blues', 'jazz ( single )', 'okeh', '2008'], ['1928', 'weather bird', 'jazz ( single )', 'okeh', '2008'], ['1930', 'blue yodel no9 ( standing on the corner )', 'country ( single )', 'victor', '2007'], ['1932', 'all of me', 'jazz ( single )', 'columbia', '2005'], ['1958', 'porgy and bess', 'jazz ( album )', 'verve', '2001'], ['1964', 'hello dolly !', 'pop ( single )', 'kapp', '2001'], ['1926', 'heebie jeebies', 'jazz ( single )', 'okeh', '1999'], ['1967', 'what a wonderful world', 'jazz ( single )', 'abc', '1999'], ['1955', 'mack the knife', 'jazz ( single )', 'columbia', '1997'], ['1925', 'st louis blues', 'jazz ( single )', 'columbia', '1993'], ['1928', 'west end blues', 'jazz ( single )', 'okeh', '1974']] |
2008 in paraguayan football | https://en.wikipedia.org/wiki/2008_in_Paraguayan_football | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17334827-6.html.csv | aggregation | the average scores for paraguay across all paraguayan football in 2008 was around 1.4 . | {'scope': 'all', 'col': '3', 'type': 'average', 'result': '1.4', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'score'], 'result': '1.4', 'ind': 0, 'tostr': 'avg { all_rows ; score }'}, '1.4'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; score } ; 1.4 } = true', 'tointer': 'the average of the score record of all rows is 1.4 .'} | round_eq { avg { all_rows ; score } ; 1.4 } = true | the average of the score record of all rows is 1.4 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'score_4': 4, '1.4_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'score_4': 'score', '1.4_5': '1.4'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'score_4': [0], '1.4_5': [1]} | ['date', 'venue', 'score', 'comp', 'paraguay scorers', 'report'] | [['june 15 , 2008', 'defensores del chaco asunción , paraguay', '2 - 0', 'wcq 2010', "santa cruz 26 ' cabañas 49 '", 'report'], ['june 18 , 2008', 'estadio hernando siles la paz , bolivia', '4 - 2', 'wcq 2010', "santa cruz 66 ' haedo valdez 82 '", 'report'], ['september 6 , 2008', 'estadio monumental buenos aires , argentina', '1 - 1', 'wcq2010', "heinze 13 ' ( og )", 'report'], ['september 9 , 2008', 'defensores del chaco asunción , paraguay', '2 - 0', 'wcq2010', "riveros 28 ' haedo valdez 45 '", 'report'], ['october 11 , 2008', 'el campín bogotá , colombia', '0 - 1', 'wcq2010', "cabañas 9 '", 'report'], ['october 15 , 2008', 'defensores del chaco asunción , paraguay', '1 - 0', 'wcq2010', "cardozo 81 '", 'report'], ['november 19 , 2008', 'sultan qaboos sports complex muscat , oman', '0 - 1', 'f', "vera 37 '", 'n / a']] |
1933 vfl season | https://en.wikipedia.org/wiki/1933_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10790397-15.html.csv | aggregation | in 1933 vfl season their games drew a combined total of 80962 peoples . | {'scope': 'all', 'col': '6', 'type': 'sum', 'result': '80962', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'crowd'], 'result': '80962', 'ind': 0, 'tostr': 'sum { all_rows ; crowd }'}, '80962'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; crowd } ; 80962 } = true', 'tointer': 'the sum of the crowd record of all rows is 80962 .'} | round_eq { sum { all_rows ; crowd } ; 80962 } = true | the sum of the crowd record of all rows is 80962 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'crowd_4': 4, '80962_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'crowd_4': 'crowd', '80962_5': '80962'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'crowd_4': [0], '80962_5': [1]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['st kilda', '8.19 ( 67 )', 'south melbourne', '13.15 ( 93 )', 'junction oval', '20000', '5 august 1933'], ['footscray', '16.14 ( 110 )', 'hawthorn', '9.18 ( 72 )', 'western oval', '8000', '5 august 1933'], ['collingwood', '15.16 ( 106 )', 'richmond', '10.8 ( 68 )', 'victoria park', '15000', '5 august 1933'], ['carlton', '14.22 ( 106 )', 'essendon', '9.9 ( 63 )', 'princes park', '15000', '5 august 1933'], ['north melbourne', '9.7 ( 61 )', 'geelong', '15.10 ( 100 )', 'arden street oval', '8000', '5 august 1933'], ['melbourne', '9.15 ( 69 )', 'fitzroy', '13.8 ( 86 )', 'mcg', '14962', '5 august 1933']] |
list of yugoslav submissions for the academy award for best foreign language film | https://en.wikipedia.org/wiki/List_of_Yugoslav_submissions_for_the_Academy_Award_for_Best_Foreign_Language_Film | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16080300-2.html.csv | ordinal | labyrinth is the most recent film on the list of yugoslav submissions for the academy awards for best foreign language film . | {'scope': 'all', 'row': '9', 'col': '1', 'order': '1', 'col_other': '2', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'year ( ceremony )', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; year ( ceremony ) ; 1 }'}, 'film title used in nomination'], 'result': 'labyrinth', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; year ( ceremony ) ; 1 } ; film title used in nomination }'}, 'labyrinth'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; year ( ceremony ) ; 1 } ; film title used in nomination } ; labyrinth } = true', 'tointer': 'select the row whose year ( ceremony ) record of all rows is 1st maximum . the film title used in nomination record of this row is labyrinth .'} | eq { hop { nth_argmax { all_rows ; year ( ceremony ) ; 1 } ; film title used in nomination } ; labyrinth } = true | select the row whose year ( ceremony ) record of all rows is 1st maximum . the film title used in nomination record of this row is labyrinth . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'year (ceremony)_5': 5, '1_6': 6, 'film title used in nomination_7': 7, 'labyrinth_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 (ceremony)_5': 'year ( ceremony )', '1_6': '1', 'film title used in nomination_7': 'film title used in nomination', 'labyrinth_8': 'labyrinth'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'year (ceremony)_5': [0], '1_6': [0], 'film title used in nomination_7': [1], 'labyrinth_8': [2]} | ['year ( ceremony )', 'film title used in nomination', 'serbian title', 'director', 'result'] | [['1994 ( 67th )', 'vukovar poste restante', 'вуковар , једна прича', 'boro drašković', 'not nominated'], ['1995 ( 68th )', 'underground', 'подземље', 'emir kusturica', 'not nominated'], ['1996 ( 69th )', 'pretty village , pretty flame', 'лепа села лепо горе', 'srđan dragojević', 'not nominated'], ['1997 ( 70th )', 'three summer days', 'три летња дана', 'mirjana vukomanović', 'not nominated'], ['1998 ( 71st )', 'powder keg', 'буре барута', 'goran paskaljević', 'not nominated'], ['1999 ( 72nd )', 'the white suit', 'бело одело', 'lazar ristovski', 'not nominated'], ['2000 ( 73rd )', 'sky hook', 'небеска удица', 'ljubiša samardžić', 'not nominated'], ['2001 ( 74th )', 'war live', 'рат уживо', 'darko bajić', 'not nominated'], ['2002 ( 75th )', 'labyrinth', 'лавиринт', 'miroslav lekić', 'not nominated']] |
united states house of representatives elections , 1974 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1974 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1341690-18.html.csv | majority | most of the incumbent from louisiana were re-elected during the united states house of representatives elections of 1974 . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'equal', 'value': 're - elected', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'result', 're - elected'], 'result': True, 'ind': 0, 'tointer': 'for the result records of all rows , most of them fuzzily match to re - elected .', 'tostr': 'most_eq { all_rows ; result ; re - elected } = true'} | most_eq { all_rows ; result ; re - elected } = true | for the result records of all rows , most of them fuzzily match to re - elected . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'result_3': 3, 're - elected_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'result_3': 'result', 're - elected_4': 're - elected'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'result_3': [0], 're - elected_4': [0]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['louisiana 1', 'f edward hebert', 'democratic', '1940', 're - elected', 'f edward hebert ( d ) unopposed'], ['louisiana 4', 'joe waggonner', 'democratic', '1961', 're - elected', 'joe waggonner ( d ) unopposed'], ['louisiana 5', 'otto passman', 'democratic', '1946', 're - elected', 'otto passman ( d ) unopposed'], ['louisiana 6', 'john rarick', 'democratic', '1966', 'lost renomination republican gain', 'henson moore ( r ) 54.1 % jeff la caze ( d ) 45.9 %'], ['louisiana 7', 'john breaux', 'democratic', '1972', 're - elected', 'john breaux ( d ) 89.3 % jeremy j millett ( i ) 10.7 %']] |
cumann na ngaedheal | https://en.wikipedia.org/wiki/Cumann_na_nGaedheal | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-147622-1.html.csv | aggregation | the cumann na ngaedheal political party won an average of 55 per election . | {'scope': 'all', 'col': '4', 'type': 'average', 'result': '55', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'seats'], 'result': '55', 'ind': 0, 'tostr': 'avg { all_rows ; seats }'}, '55'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; seats } ; 55 } = true', 'tointer': 'the average of the seats record of all rows is 55 .'} | round_eq { avg { all_rows ; seats } ; 55 } = true | the average of the seats record of all rows is 55 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'seats_4': 4, '55_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'seats_4': 'seats', '55_5': '55'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'seats_4': [0], '55_5': [1]} | ['election', 'dáil', 'share of votes', 'seats', 'government'] | [['1923', '4th', '28.9 %', '63', 'cumann na ngaedheal government'], ['1927 ( jun )', '5th', '27.0 %', '46', 'cumann na ngaedheal government'], ['1927 ( sep )', '6th', '38.7 %', '61', 'cumann na ngaedheal government'], ['1932', '7th', '35.3 %', '57', 'fianna fáil government'], ['1933', '8th', '30.1 %', '48', 'fianna fáil government']] |
choi moon - sik | https://en.wikipedia.org/wiki/Choi_Moon-Sik | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11871805-3.html.csv | unique | the match played on september 27 , 1993 was the only friendly match that choi moon - sik scored in . | {'scope': 'all', 'row': '4', 'col': '5', 'col_other': '1', 'criterion': 'equal', 'value': 'friendly match', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'competition', 'friendly match'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose competition record fuzzily matches to friendly match .', 'tostr': 'filter_eq { all_rows ; competition ; friendly match }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; competition ; friendly match } }', 'tointer': 'select the rows whose competition record fuzzily matches to friendly match . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'competition', 'friendly match'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose competition record fuzzily matches to friendly match .', 'tostr': 'filter_eq { all_rows ; competition ; friendly match }'}, 'date'], 'result': 'september 27 , 1993', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; competition ; friendly match } ; date }'}, 'september 27 , 1993'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; competition ; friendly match } ; date } ; september 27 , 1993 }', 'tointer': 'the date record of this unqiue row is september 27 , 1993 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; competition ; friendly match } } ; eq { hop { filter_eq { all_rows ; competition ; friendly match } ; date } ; september 27 , 1993 } } = true', 'tointer': 'select the rows whose competition record fuzzily matches to friendly match . there is only one such row in the table . the date record of this unqiue row is september 27 , 1993 .'} | and { only { filter_eq { all_rows ; competition ; friendly match } } ; eq { hop { filter_eq { all_rows ; competition ; friendly match } ; date } ; september 27 , 1993 } } = true | select the rows whose competition record fuzzily matches to friendly match . there is only one such row in the table . the date record of this unqiue row is september 27 , 1993 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'competition_7': 7, 'friendly match_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'date_9': 9, 'september 27 , 1993_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'competition_7': 'competition', 'friendly match_8': 'friendly match', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'date_9': 'date', 'september 27 , 1993_10': 'september 27 , 1993'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'competition_7': [0], 'friendly match_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'date_9': [2], 'september 27 , 1993_10': [3]} | ['date', 'venue', 'score', 'result', 'competition'] | [['may 13 , 1993', 'beirut', '1 goal', '3 - 0', '1994 fifa world cup qualification'], ['may 15 , 1993', 'beirut', '1 goal', '3 - 0', '1994 fifa world cup qualification'], ['june 5 , 1993', 'seoul', '1 goal', '4 - 1', '1994 fifa world cup qualification'], ['september 27 , 1993', 'seoul', '1 goal', '1 - 0', 'friendly match'], ['august 5 , 1996', 'ho chi minh city', '1 goal', '9 - 0', '1996 afc asian cup qualification'], ['february 22 , 1997', 'hong kong', '1 goal', '2 - 0', '1998 fifa world cup qualification'], ['march 2 , 1997', 'bangkok', '1 goal', '3 - 1', '1998 fifa world cup qualification'], ['june 12 , 1997', 'seoul', '1 goal', '3 - 1', '1997 korea cup'], ['june 14 , 1997', 'suwon', '1 goal', '3 - 0', '1997 korea cup']] |
b " water polo at the 2004 summer olympics - men 's team rosters " | https://en.wikipedia.org/wiki/Water_polo_at_the_2004_Summer_Olympics_%E2%80%93_Men%27s_team_rosters | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17759945-12.html.csv | count | for men 's water polo at the 2004 summer olympics , two men were born in 1968 . | {'scope': 'all', 'criterion': 'equal', 'value': '1968', 'result': '2', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'date of birth', '1968'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose date of birth record is equal to 1968 .', 'tostr': 'filter_eq { all_rows ; date of birth ; 1968 }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; date of birth ; 1968 } }', 'tointer': 'select the rows whose date of birth record is equal to 1968 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; date of birth ; 1968 } } ; 2 } = true', 'tointer': 'select the rows whose date of birth record is equal to 1968 . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; date of birth ; 1968 } } ; 2 } = true | select the rows whose date of birth record is equal to 1968 . 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, 'date of birth_5': 5, '1968_6': 6, '2_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'date of birth_5': 'date of birth', '1968_6': '1968', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'date of birth_5': [0], '1968_6': [0], '2_7': [2]} | ['name', 'pos', 'height', 'weight', 'date of birth', 'club'] | [['jesús rollán', 'gk', 'm ( ft 2in )', '-', '1968 - 04 - 04', 'cn sabadell'], ['ángel andreo', 'gk', 'm ( ft 3in )', '-', '1972 - 12 - 03', 'cn atlètic - barceloneta'], ['sergi pedrerol', 'd', 'm ( ft 3in )', '-', '1969 - 12 - 16', 'cn sabadell'], ['gustavo marcos', 'cb', 'm ( ft 11in )', '-', '1972 - 12 - 23', 'cn sabadell'], ['guillermo molina', 'cb', 'm ( ft 0in )', '-', '1984 - 03 - 16', 'cn barcelona'], ['xavier garcía', 'cb', 'm ( ft 2in )', '-', '1984 - 01 - 05', 'cn atlètic - barceloneta'], ['gabriel hernández paz', 'd', 'm ( ft 1in )', '-', '1975 - 01 - 02', 'cn atlètic - barceloneta'], ['iván moro', 'cb', 'm ( ft 1in )', '-', '1974 - 12 - 25', 'cn atlètic - barceloneta'], ['daniel ballart', 'cb', 'm ( ft 10in )', '-', '1973 - 03 - 17', 'cn sabadell'], ['salvador gómez', 'cb', 'm ( ft 4in )', '-', '1968 - 03 - 11', 'wp valencia'], ['iván pérez', 'cf', 'm ( ft 3in )', '-', '1971 - 06 - 29', 'cn barcelona'], ['javier sanchez toril', 'cf', 'm ( ft 4in )', '-', '1975 - 06 - 16', 'cn atlètic - barceloneta'], ['daniel moro', 'd', 'm ( ft 2in )', '-', '1973 - 08 - 08', 'cn atlètic - barceloneta']] |
1985 - 86 utah jazz season | https://en.wikipedia.org/wiki/1985%E2%80%9386_Utah_Jazz_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17371779-1.html.csv | majority | in the 1985 - 86 utah jazz season , all of the players are from the united states . | {'scope': 'all', 'col': '4', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'united states', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'nationality', 'united states'], 'result': True, 'ind': 0, 'tointer': 'for the nationality records of all rows , all of them fuzzily match to united states .', 'tostr': 'all_eq { all_rows ; nationality ; united states } = true'} | all_eq { all_rows ; nationality ; united states } = true | for the nationality records of all rows , all of them fuzzily match to united states . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'nationality_3': 3, 'united states_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'nationality_3': 'nationality', 'united states_4': 'united states'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'nationality_3': [0], 'united states_4': [0]} | ['round', 'pick', 'player', 'nationality', 'college'] | [['1', '13', 'karl malone', 'united states', 'louisiana tech'], ['2', '37', 'carey scurry', 'united states', 'long island'], ['4', '83', 'delaney rudd', 'united states', 'wake forest'], ['5', '105', 'ray hall', 'united states', 'canisius'], ['6', '129', 'jim miller', 'united states', 'virginia'], ['7', '151', 'mike wacker', 'united states', 'texas - san antonio']] |
2006 japanese television dramas | https://en.wikipedia.org/wiki/2006_Japanese_television_dramas | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18540022-3.html.csv | superlative | the highest average rating for 2006 japanese television dramas is for the show titled my ☆ boss my ☆ hero . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '11', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '2', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'average ratings'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; average ratings }'}, 'romaji title'], 'result': 'my ☆ boss my ☆ hero', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; average ratings } ; romaji title }'}, 'my ☆ boss my ☆ hero'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; average ratings } ; romaji title } ; my ☆ boss my ☆ hero } = true', 'tointer': 'select the row whose average ratings record of all rows is maximum . the romaji title record of this row is my ☆ boss my ☆ hero .'} | eq { hop { argmax { all_rows ; average ratings } ; romaji title } ; my ☆ boss my ☆ hero } = true | select the row whose average ratings record of all rows is maximum . the romaji title record of this row is my ☆ boss my ☆ hero . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'average ratings_5': 5, 'romaji title_6': 6, 'my☆boss my☆hero_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'average ratings_5': 'average ratings', 'romaji title_6': 'romaji title', 'my☆boss my☆hero_7': 'my ☆ boss my ☆ hero'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'average ratings_5': [0], 'romaji title_6': [1], 'my☆boss my☆hero_7': [2]} | ['japanese title', 'romaji title', 'tv station', 'episodes', 'average ratings'] | [['サプリ', 'sapuri', 'fuji tv', '11', '14.2 %'], ['不信のとき ～ ウーマン ・ ウォーズ ～', 'fushin no toki ~ woman wars ~', 'fuji tv', '12', '12.9 %'], ['結婚できない男', 'kekkon dekinai otoko', 'fuji tv', '12', '17.1 %'], ['ダンドリ 。 ～ dance ☆ drill ～', 'dandori ~ dance ☆ drill ~', 'fuji tv', '11', '8.9 %'], ['誰よりもママを愛す', 'dare yorimo mama wo ai su', 'tbs', '11', '10.4 %'], ['花嫁は厄年ッ !', 'hanayome wa yakudoshi !', 'tbs', '12', '12.0 %'], ['タイヨウのうた', 'taiyou no uta', 'tbs', '10', '10.3 %'], ['レガッタ ～ 君といた永遠 ～', 'regatta ~ kimi to ita eien ~', 'tv - asahi', '9', '5.4 %'], ['下北サンデーズ', 'shimokita sundays', 'tv - asahi', '9', '7.3 %'], ['caとお呼びっ !', 'ca to oyobbi !', 'ntv', '11', '9.5 %'], ['マイ ☆ ボス マイ ☆ ヒーロー', 'my ☆ boss my ☆ hero', 'ntv', '10', '18.9 %']] |
fai world grand prix 2008 | https://en.wikipedia.org/wiki/FAI_World_Grand_Prix_2008 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17277703-1.html.csv | unique | thomas gostner was the only pilot from italy . | {'scope': 'all', 'row': '5', 'col': '3', 'col_other': '2', 'criterion': 'equal', 'value': 'italy', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'italy'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose country record fuzzily matches to italy .', 'tostr': 'filter_eq { all_rows ; country ; italy }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; country ; italy } }', 'tointer': 'select the rows whose country record fuzzily matches to italy . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'italy'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose country record fuzzily matches to italy .', 'tostr': 'filter_eq { all_rows ; country ; italy }'}, 'pilot'], 'result': 'thomas gostner', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; country ; italy } ; pilot }'}, 'thomas gostner'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; country ; italy } ; pilot } ; thomas gostner }', 'tointer': 'the pilot record of this unqiue row is thomas gostner .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; country ; italy } } ; eq { hop { filter_eq { all_rows ; country ; italy } ; pilot } ; thomas gostner } } = true', 'tointer': 'select the rows whose country record fuzzily matches to italy . there is only one such row in the table . the pilot record of this unqiue row is thomas gostner .'} | and { only { filter_eq { all_rows ; country ; italy } } ; eq { hop { filter_eq { all_rows ; country ; italy } ; pilot } ; thomas gostner } } = true | select the rows whose country record fuzzily matches to italy . there is only one such row in the table . the pilot record of this unqiue row is thomas gostner . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'country_7': 7, 'italy_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'pilot_9': 9, 'thomas gostner_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', 'italy_8': 'italy', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'pilot_9': 'pilot', 'thomas gostner_10': 'thomas gostner'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'country_7': [0], 'italy_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'pilot_9': [2], 'thomas gostner_10': [3]} | ['position', 'pilot', 'country', 'glider', 'points'] | [['1', 'sebastian kawa', 'poland', 'diana sailplanes - diana 2', '69'], ['2', 'carlos rocca vidal', 'chile', 'schempp - hirth flugzeugbau gmbh - ventus 2b', '55'], ['3', 'mario kiessling', 'germany', 'schempp - hirth flugzeugbau gmbh - ventus 2ax', '47'], ['4', 'uli schwenk', 'germany', 'schempp - hirth flugzeugbau gmbh - ventus 2ax', '40'], ['5', 'thomas gostner', 'italy', 'diana sailplanes - diana 2', '43'], ['6', 'tilo holighaus', 'germany', 'schempp - hirth flugzeugbau gmbh - ventus 2ax', '24'], ['7', 'wolfgang janowitsch', 'austria', 'schempp - hirth flugzeugbau gmbh - ventus 2cxa', '15'], ['8', 'rene vidal', 'chile', 'schempp - hirth flugzeugbau gmbh - ventus 2c', '14'], ['8', 'stanislaw wujczak', 'poland', 'alexander schleicher gmbh & co - asg 29', '14'], ['10', 'eduard supersperger', 'austria', 'schempp - hirth flugzeugbau gmbh - ventus 2b', '12'], ['11', 'heimo demmerer', 'austria', 'schempp - hirth flugzeugbau gmbh - ventus 2b', '11'], ['12', 'patrick puskeiler', 'germany', 'schempp - hirth flugzeugbau gmbh - discus 2ax', '8'], ['13', 'petr krejcirik', 'czech republic', 'schempp - hirth flugzeugbau gmbh - ventus 2ax', '4'], ['13', 'graham parker', 'australia', 'alexander schleicher gmbh & co - asg 29', '4'], ['15', 'olli teronen', 'finland', 'alexander schleicher gmbh & co - asg 29', '2']] |
honor oak park railway station | https://en.wikipedia.org/wiki/Honor_Oak_Park_railway_station | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1132489-1.html.csv | count | among the trains that go through honor oak park railway station and operated by london overground , two of them stop at platform 1 . | {'scope': 'subset', 'criterion': 'equal', 'value': '1', 'result': '2', 'col': '1', 'subset': {'col': '4', 'criterion': 'equal', 'value': 'london overground'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'operator', 'london overground'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; operator ; london overground }', 'tointer': 'select the rows whose operator record fuzzily matches to london overground .'}, 'platform', '1'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose operator record fuzzily matches to london overground . among these rows , select the rows whose platform record is equal to 1 .', 'tostr': 'filter_eq { filter_eq { all_rows ; operator ; london overground } ; platform ; 1 }'}], 'result': '2', 'ind': 2, 'tostr': 'count { filter_eq { filter_eq { all_rows ; operator ; london overground } ; platform ; 1 } }', 'tointer': 'select the rows whose operator record fuzzily matches to london overground . among these rows , select the rows whose platform record is equal to 1 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_eq { filter_eq { all_rows ; operator ; london overground } ; platform ; 1 } } ; 2 } = true', 'tointer': 'select the rows whose operator record fuzzily matches to london overground . among these rows , select the rows whose platform record is equal to 1 . the number of such rows is 2 .'} | eq { count { filter_eq { filter_eq { all_rows ; operator ; london overground } ; platform ; 1 } } ; 2 } = true | select the rows whose operator record fuzzily matches to london overground . among these rows , select the rows whose platform record is equal to 1 . the number of such rows is 2 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_eq_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'operator_6': 6, 'london overground_7': 7, 'platform_8': 8, '1_9': 9, '2_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_eq_1': 'filter_eq', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'operator_6': 'operator', 'london overground_7': 'london overground', 'platform_8': 'platform', '1_9': '1', '2_10': '2'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_eq_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'operator_6': [0], 'london overground_7': [0], 'platform_8': [1], '1_9': [1], '2_10': [3]} | ['platform', 'frequency ( per hour )', 'destination', 'operator', 'line'] | [['1', '4', 'highbury & islington', 'london overground', 'east london'], ['1', '4', 'dalston junction', 'london overground', 'east london'], ['1', '4', 'london bridge', 'southern', 'metro'], ['2', '4', 'crystal palace', 'london overground', 'east london'], ['2', '4', 'west croydon', 'london overground', 'east london'], ['2', '2', 'london victoria ( mon - sat )', 'southern', 'metro'], ['2', '2', 'caterham ( mon - sat )', 'southern', 'metro'], ['2', '2', 'west croydon ( peaks & sun only )', 'southern', 'metro'], ['2', '2', 'tattenham corner ( sun only )', 'southern', 'metro']] |
2007 - 08 cleveland cavaliers season | https://en.wikipedia.org/wiki/2007%E2%80%9308_Cleveland_Cavaliers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11960713-5.html.csv | aggregation | the average crowd attendance of games in the 2007 - 08 cleveland cavaliers season was 19893 . | {'scope': 'all', 'col': '6', 'type': 'average', 'result': '19893', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'attendance'], 'result': '19893', 'ind': 0, 'tostr': 'avg { all_rows ; attendance }'}, '19893'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; attendance } ; 19893 } = true', 'tointer': 'the average of the attendance record of all rows is 19893 .'} | round_eq { avg { all_rows ; attendance } ; 19893 } = true | the average of the attendance record of all rows is 19893 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'attendance_4': 4, '19893_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'attendance_4': 'attendance', '19893_5': '19893'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'attendance_4': [0], '19893_5': [1]} | ['date', 'visitor', 'score', 'home', 'leading scorer', 'attendance', 'record'] | [['march 2', 'chicago', '95 - 86', 'cleveland', 'lebron james ( 37 )', '20562', '34 - 26'], ['march 5', 'cleveland', '119 - 105', 'ny knicks', 'lebron james ( 50 )', '18760', '35 - 26'], ['march 6', 'cleveland', '96 - 107', 'chicago', 'lebron james ( 39 )', '22097', '35 - 27'], ['march 8', 'indiana', '103 - 95', 'cleveland', 'lebron james ( 38 )', '20562', '36 - 27'], ['march 10', 'portland', '88 - 80', 'cleveland', 'lebron james ( 24 )', '20213', '37 - 27'], ['march 12', 'cleveland', '99 - 104', 'new jersey', 'lebron james ( 42 )', '18287', '37 - 28'], ['march 13', 'cleveland', '99 - 101', 'washington', 'lebron james ( 25 )', '20173', '37 - 29'], ['march 16', 'charlotte', '98 - 91', 'cleveland', 'lebron james ( 33 )', '20562', '38 - 29'], ['march 17', 'cleveland', '90 - 104', 'orlando', 'lebron james ( 30 )', '17519', '38 - 30'], ['march 19', 'detroit', '89 - 73', 'cleveland', 'lebron james ( 30 )', '20562', '39 - 30'], ['march 21', 'toronto', '90 - 83', 'cleveland', 'lebron james ( 29 )', '20562', '40 - 30'], ['march 22', 'cleveland', '98 - 108', 'milwaukee', 'lebron james ( 29 )', '15337', '40 - 31'], ['march 26', 'new orleans', '99 - 100', 'cleveland', 'žydrūnas ilgauskas ( 29 )', '20562', '40 - 32'], ['march 29', 'cleveland', '71 - 85', 'detroit', 'lebron james ( 13 )', '22076', '40 - 33'], ['march 30', 'philadelphia', '91 - 88', 'cleveland', 'lebron james ( 26 )', '20562', '41 - 33']] |
indianapolis colts draft history | https://en.wikipedia.org/wiki/Indianapolis_Colts_draft_history | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13312898-47.html.csv | ordinal | brandon burlsworth was the third highest overall draft pick by the indianapolis colts . | {'row': '3', 'col': '3', 'order': '3', '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', 'overall', '3'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; overall ; 3 }'}, 'name'], 'result': 'brandon burlsworth', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; overall ; 3 } ; name }'}, 'brandon burlsworth'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; overall ; 3 } ; name } ; brandon burlsworth } = true', 'tointer': 'select the row whose overall record of all rows is 3rd minimum . the name record of this row is brandon burlsworth .'} | eq { hop { nth_argmin { all_rows ; overall ; 3 } ; name } ; brandon burlsworth } = true | select the row whose overall record of all rows is 3rd minimum . the name record of this row is brandon burlsworth . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'overall_5': 5, '3_6': 6, 'name_7': 7, 'brandon burlsworth_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', 'overall_5': 'overall', '3_6': '3', 'name_7': 'name', 'brandon burlsworth_8': 'brandon burlsworth'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'overall_5': [0], '3_6': [0], 'name_7': [1], 'brandon burlsworth_8': [2]} | ['round', 'pick', 'overall', 'name', 'position', 'college'] | [['1', '4', '4', 'edgerrin james', 'running back', 'miami ( fl )'], ['2', '5', '36', 'mike peterson', 'linebacker', 'florida'], ['3', '2', '63', 'brandon burlsworth', 'guard', 'arkansas'], ['4', '1', '96', 'paul miranda', 'cornerback', 'central florida'], ['5', '5', '138', 'brad scioli', 'defensive end', 'penn state'], ['7', '4', '210', 'hunter smith', 'punter', 'notre dame'], ['7', '44', '250', 'corey terry', 'linebacker', 'tennessee']] |
papal conclave , 1378 | https://en.wikipedia.org/wiki/Papal_conclave%2C_1378 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18868987-1.html.csv | majority | most of the electors in the papal conclave of 1378 were french . | {'scope': 'all', 'col': '2', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'french', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'nationality', 'french'], 'result': True, 'ind': 0, 'tointer': 'for the nationality records of all rows , most of them fuzzily match to french .', 'tostr': 'most_eq { all_rows ; nationality ; french } = true'} | most_eq { all_rows ; nationality ; french } = true | for the nationality records of all rows , most of them fuzzily match to french . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'nationality_3': 3, 'french_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'nationality_3': 'nationality', 'french_4': 'french'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'nationality_3': [0], 'french_4': [0]} | ['elector', 'nationality', 'cardinalatial order and title', 'elevated', 'elevator'] | [['pietro corsini', 'florentine', 'cardinal - bishop of porto e santa rufina', '1370 , june 7', 'urban v'], ['jean du cros', 'french', 'cardinal - bishop of palestrina', '1371 , may 30', 'gregory xi'], ["guillaume d'aigrefeuille , iuniore , osb", 'french', 'cardinal - priest of s stefano al monte celio', '1367 , may 12', 'urban v'], ['francesco tebaldeschi', 'roman', 'cardinal - priest of s sabina', '1368 , september 22', 'urban v'], ['bertrand lagier , ofm', 'french', 'cardinal - priest of s cecilia', '1371 , may 30', 'gregory xi'], ['robert de genève', 'french', 'cardinal - priest of ss xii apostoli', '1371 , may 30', 'gregory xi'], ['simone borsano', 'milanese', 'cardinal - priest of ss giovanni e paolo', '1375 , december 20', 'gregory xi'], ['hugues de montelais , le jeune', 'french', 'cardinal - priest of ss iv coronati', '1375 , december 20', 'gregory xi'], ['gui de maillesec', 'french', 'cardinal - priest of s croce in gerusalemme', '1375 , december 20', 'gregory xi'], ['pierre de sortenac', 'french', 'cardinal - priest of s lorenzo in lucina', '1375 , december 20', 'gregory xi'], ['gérard du puy , osb', 'french', 'cardinal - priest of s clemente', '1375 , december 20', 'gregory xi'], ['giacomo orsini', 'roman', 'cardinal - deacon of s giorgio in velabro', '1371 , may 30', 'gregory xi'], ['pierre flandrin', 'french', 'cardinal - deacon of s eustachio', '1371 , may 30', 'gregory xi'], ['guillaume noellet', 'french', 'cardinal - deacon of s angelo in pescheria', '1371 , may 30', 'gregory xi'], ['pierre de vergne', 'french', 'cardinal - deacon of s maria in via lata', '1371 , may 30', 'gregory xi'], ['pedro martínez de luna y gotor', 'aragonese', 'cardinal - deacon of s maria in cosmedin', '1375 , december 20', 'gregory xi']] |
1993 new york jets season | https://en.wikipedia.org/wiki/1993_New_York_Jets_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10918196-1.html.csv | count | in the 1993 new york jets season , there were 8 wins . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'w', 'result': '8', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'result', 'w'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose result record fuzzily matches to w .', 'tostr': 'filter_eq { all_rows ; result ; w }'}], 'result': '8', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; result ; w } }', 'tointer': 'select the rows whose result record fuzzily matches to w . the number of such rows is 8 .'}, '8'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; result ; w } } ; 8 } = true', 'tointer': 'select the rows whose result record fuzzily matches to w . the number of such rows is 8 .'} | eq { count { filter_eq { all_rows ; result ; w } } ; 8 } = true | select the rows whose result record fuzzily matches to w . 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, 'result_5': 5, 'w_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', 'result_5': 'result', 'w_6': 'w', '8_7': '8'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'result_5': [0], 'w_6': [0], '8_7': [2]} | ['week', 'date', 'opponent', 'result', 'game site', 'attendance'] | [['1', '1993 - 09 - 05', 'denver broncos', 'l 26 - 20', 'the meadowlands', '68130'], ['2', '1993 - 09 - 12', 'miami dolphins', 'w 24 - 14', 'joe robbie stadium', '70314'], ['4', '1993 - 09 - 26', 'new england patriots', 'w 45 - 7', 'the meadowlands', '64836'], ['5', '1993 - 10 - 03', 'philadelphia eagles', 'l 35 - 30', 'the meadowlands', '72593'], ['6', '1993 - 10 - 10', 'los angeles raiders', 'l 24 - 20', 'los angeles memorial coliseum', '41627'], ['8', '1993 - 10 - 24', 'buffalo bills', 'l 19 - 10', 'the meadowlands', '71541'], ['9', '1993 - 10 - 31', 'new york giants', 'w 10 - 6', 'giants stadium', '71659'], ['10', '1993 - 11 - 07', 'miami dolphins', 'w 27 - 10', 'the meadowlands', '71306'], ['11', '1993 - 11 - 14', 'indianapolis colts', 'w 31 - 17', 'rca dome', '47351'], ['12', '1993 - 11 - 21', 'cincinnati bengals', 'w 17 - 12', 'the meadowlands', '64264'], ['13', '1993 - 11 - 28', 'new england patriots', 'w 6 - 0', 'foxboro stadium', '42810'], ['14', '1993 - 12 - 05', 'indianapolis colts', 'l 9 - 6', 'the meadowlands', '45799'], ['15', '1993 - 12 - 11', 'washington redskins', 'w 3 - 0', 'robert f kennedy memorial stadium', '47970'], ['16', '1993 - 12 - 18', 'dallas cowboys', 'l 28 - 7', 'the meadowlands', '73233'], ['17', '1993 - 12 - 26', 'buffalo bills', 'l 16 - 14', 'rich stadium', '70817'], ['18', '1994 - 01 - 02', 'houston oilers', 'l 24 - 0', 'houston astrodome', '61040']] |
thawatchai damrong - ongtrakul | https://en.wikipedia.org/wiki/Thawatchai_Damrong-Ongtrakul | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18458106-1.html.csv | majority | thawatchai damrong - ongtrakul won the majority of the events from 1994 to 2001 . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'won', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'result', 'won'], 'result': True, 'ind': 0, 'tointer': 'for the result records of all rows , most of them fuzzily match to won .', 'tostr': 'most_eq { all_rows ; result ; won } = true'} | most_eq { all_rows ; result ; won } = true | for the result records of all rows , most of them fuzzily match to won . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'result_3': 3, 'won_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'result_3': 'result', 'won_4': 'won'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'result_3': [0], 'won_4': [0]} | ['date', 'venue', 'score', 'result', 'competition'] | [['october 7 , 1994', 'hiroshima , japan', '4 - 5', 'lost', '1994 asian games'], ['february 16 , 1996', 'bangkok , thailand', '5 - 2', 'win', "king 's cup 1996"], ['june 29 , 1996', 'bangkok , thailand', '5 - 1', 'won', '1996 asian cup qualification'], ['december 4 , 1998', 'bangkok , thailand', '2 - 0', 'won', '1998 asian games'], ['december 14 , 1998', 'bangkok , thailand', '2 - 1', 'won', '1998 asian games'], ['august 12 , 1999', 'bandar seri begawan , brunei', '2 - 0', 'won', '1999 southeast asian games'], ['august 14 , 1999', 'bandar seri begawan , brunei', '2 - 0', 'won', '1999 southeast asian games'], ['april 4 , 2000', 'bangkok , thailand', '5 - 3', 'won', '2000 asian cup qualification'], ['april 6 , 2000', 'bangkok , thailand', '1 - 0', 'won', '2000 asian cup qualification'], ['may 13 , 2001', 'bangkok , thailand', '4 - 2', 'won', '2002 world cup qualification']] |
casey martin | https://en.wikipedia.org/wiki/Casey_Martin | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1697190-2.html.csv | aggregation | casey martin 's total earnings on the pga tour were 206874 . | {'scope': 'all', 'col': '6', 'type': 'sum', 'result': '206874', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'earnings'], 'result': '206874', 'ind': 0, 'tostr': 'sum { all_rows ; earnings }'}, '206874'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; earnings } ; 206874 } = true', 'tointer': 'the sum of the earnings record of all rows is 206874 .'} | round_eq { sum { all_rows ; earnings } ; 206874 } = true | the sum of the earnings record of all rows is 206874 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'earnings_4': 4, '206874_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'earnings_4': 'earnings', '206874_5': '206874'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'earnings_4': [0], '206874_5': [1]} | ['year', 'tournaments played', 'cuts made', 'wins', 'best finish', 'earnings', 'money list rank'] | [['1998', '3', '2', '0', 't - 23', '37221', '221'], ['2000', '29', '14', '0', 't - 17', '143248', '179'], ['2001', '2', '0', '0', 'cut', '0', 'n / a'], ['2002', '3', '0', '0', 'cut', '0', 'n / a'], ['2003', '1', '0', '0', 'cut', '0', 'n / a'], ['2004', '2', '2', '0', 't - 69', '15858', 'n / a'], ['2005', '1', '1', '0', 't - 65', '10547', 'n / a']] |
2007 - 08 san antonio spurs season | https://en.wikipedia.org/wiki/2007%E2%80%9308_San_Antonio_Spurs_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11963601-10.html.csv | comparative | parker scored more points for the san antonio spurs on april 25 than on april 27 . | {'row_1': '3', 'row_2': '4', 'col': '5', 'col_other': '2', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', 'april 25'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose date record fuzzily matches to april 25 .', 'tostr': 'filter_eq { all_rows ; date ; april 25 }'}, 'high points'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; date ; april 25 } ; high points }', 'tointer': 'select the rows whose date record fuzzily matches to april 25 . take the high points record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', 'april 27'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose date record fuzzily matches to april 27 .', 'tostr': 'filter_eq { all_rows ; date ; april 27 }'}, 'high points'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; date ; april 27 } ; high points }', 'tointer': 'select the rows whose date record fuzzily matches to april 27 . take the high points record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; date ; april 25 } ; high points } ; hop { filter_eq { all_rows ; date ; april 27 } ; high points } } = true', 'tointer': 'select the rows whose date record fuzzily matches to april 25 . take the high points record of this row . select the rows whose date record fuzzily matches to april 27 . take the high points record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; date ; april 25 } ; high points } ; hop { filter_eq { all_rows ; date ; april 27 } ; high points } } = true | select the rows whose date record fuzzily matches to april 25 . take the high points record of this row . select the rows whose date record fuzzily matches to april 27 . take the high points 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, 'date_7': 7, 'april 25_8': 8, 'high points_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'date_11': 11, 'april 27_12': 12, 'high points_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', 'date_7': 'date', 'april 25_8': 'april 25', 'high points_9': 'high points', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'date_11': 'date', 'april 27_12': 'april 27', 'high points_13': 'high points'} | {'greater_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'date_7': [0], 'april 25_8': [0], 'high points_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'date_11': [1], 'april 27_12': [1], 'high points_13': [3]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'series'] | [['1', 'april 19', 'phoenix', '117 - 115 ( 2ot )', 'duncan ( 40 )', 'duncan ( 15 )', 'duncan , ginóbili , parker ( 5 )', 'at & t center 18797', '1 - 0'], ['2', 'april 22', 'phoenix', '102 - 96', 'parker ( 32 )', 'duncan ( 17 )', 'parker ( 7 )', 'at & t center 18797', '2 - 0'], ['3', 'april 25', 'phoenix', '115 - 99', 'parker ( 41 )', 'duncan ( 10 )', 'parker ( 12 )', 'us airways center 18422', '3 - 0'], ['4', 'april 27', 'phoenix', '86 - 105', 'parker ( 18 )', 'duncan ( 10 )', 'parker ( 3 )', 'us airways center 18422', '3 - 1'], ['5', 'april 29', 'phoenix', '92 - 87', 'parker ( 31 )', 'duncan ( 17 )', 'parker ( 8 )', 'at & t center 18797', '4 - 1']] |
2005 games of the small states of europe | https://en.wikipedia.org/wiki/2005_Games_of_the_Small_States_of_Europe | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11149631-1.html.csv | superlative | at the 2005 games of the small states of europe , cyprus won the highest number of silver medals . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '2', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'silver'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; silver }'}, 'nation'], 'result': 'cyprus', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; silver } ; nation }'}, 'cyprus'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; silver } ; nation } ; cyprus } = true', 'tointer': 'select the row whose silver record of all rows is maximum . the nation record of this row is cyprus .'} | eq { hop { argmax { all_rows ; silver } ; nation } ; cyprus } = true | select the row whose silver record of all rows is maximum . the nation record of this row is cyprus . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'silver_5': 5, 'nation_6': 6, 'cyprus_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'silver_5': 'silver', 'nation_6': 'nation', 'cyprus_7': 'cyprus'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'silver_5': [0], 'nation_6': [1], 'cyprus_7': [2]} | ['rank', 'nation', 'gold', 'silver', 'bronze', 'total'] | [['1', 'cyprus', '39', '28', '24', '91'], ['2', 'iceland', '26', '23', '27', '76'], ['3', 'luxembourg', '18', '21', '23', '62'], ['4', 'monaco', '11', '8', '18', '37'], ['5', 'andorra', '8', '14', '9', '31'], ['6', 'malta', '7', '13', '18', '38'], ['7', 'san marino', '6', '9', '7', '22'], ['8', 'liechtenstein', '5', '5', '3', '13']] |
2008 - 09 rugby - bundesliga | https://en.wikipedia.org/wiki/2008%E2%80%9309_Rugby-Bundesliga | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-20989972-7.html.csv | majority | in 2008 -- 2009 rugby-bundesliga 's 2nd . category south/west , most of the clubs had a negative points difference . | {'scope': 'all', 'col': '9', 'most_or_all': 'most', 'criterion': 'less_than', 'value': '0', 'subset': None} | {'func': 'most_less', 'args': ['all_rows', 'difference', '0'], 'result': True, 'ind': 0, 'tointer': 'for the difference records of all rows , most of them are less than 0 .', 'tostr': 'most_less { all_rows ; difference ; 0 } = true'} | most_less { all_rows ; difference ; 0 } = true | for the difference records of all rows , most of them are less than 0 . | 1 | 1 | {'most_less_0': 0, 'result_1': 1, 'all_rows_2': 2, 'difference_3': 3, '0_4': 4} | {'most_less_0': 'most_less', 'result_1': 'true', 'all_rows_2': 'all_rows', 'difference_3': 'difference', '0_4': '0'} | {'most_less_0': [1], 'result_1': [], 'all_rows_2': [0], 'difference_3': [0], '0_4': [0]} | ['', 'club', 'played', 'won', 'drawn', 'lost', 'points for', 'points against', 'difference', 'points'] | [['1', 'sc 1880 frankfurt ii', '18', '16', '0', '2', '778', '217', '561', '77'], ['2', 'asv köln rugby', '18', '15', '0', '3', '515', '166', '349', '72'], ['3', 'rg heidelberg ii', '18', '11', '1', '6', '445', '357', '88', '57'], ['4', 'münchen rfc', '18', '8', '1', '9', '451', '350', '91', '48'], ['5', 'tsv handschuhsheim ii', '18', '7', '0', '11', '334', '442', '- 108', '37'], ['6', 'stusta münchen', '18', '8', '0', '10', '270', '393', '- 123', '37'], ['7', 'rc mainz', '18', '6', '0', '12', '343', '513', '- 170', '33'], ['8', 'heidelberger rk ii', '18', '6', '2', '10', '265', '472', '- 207', '31'], ['9', 'stuttgarter rc', '18', '5', '1', '12', '256', '380', '- 124', '30']] |
synchronized swimming at the 2008 summer olympics - women 's duet | https://en.wikipedia.org/wiki/Synchronized_swimming_at_the_2008_Summer_Olympics_%E2%80%93_Women%27s_duet | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18789596-2.html.csv | superlative | the highest total in the women 's duet in synchronized swimming at the 2008 summer olympics was for anastasia davydova & anastasiya yermakova . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '2', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'total'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; total }'}, 'athlete'], 'result': 'anastasia davydova & anastasiya yermakova', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; total } ; athlete }'}, 'anastasia davydova & anastasiya yermakova'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; total } ; athlete } ; anastasia davydova & anastasiya yermakova } = true', 'tointer': 'select the row whose total record of all rows is maximum . the athlete record of this row is anastasia davydova & anastasiya yermakova .'} | eq { hop { argmax { all_rows ; total } ; athlete } ; anastasia davydova & anastasiya yermakova } = true | select the row whose total record of all rows is maximum . the athlete record of this row is anastasia davydova & anastasiya yermakova . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'total_5': 5, 'athlete_6': 6, 'anastasia davydova & anastasiya yermakova_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'total_5': 'total', 'athlete_6': 'athlete', 'anastasia davydova & anastasiya yermakova_7': 'anastasia davydova & anastasiya yermakova'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'total_5': [0], 'athlete_6': [1], 'anastasia davydova & anastasiya yermakova_7': [2]} | ['country', 'athlete', 'technical', 'free', 'total'] | [['russia', 'anastasia davydova & anastasiya yermakova', '49.334', '49.917', '99.251'], ['spain', 'andrea fuentes & gemma mengual', '48.834', '49.500', '98.334'], ['japan', 'saho harada & emiko suzuki', '48.250', '48.917', '97.167'], ['china', 'jiang tingting & jiang wenwen', '48.084', '48.250', '96.334'], ['united states', 'christina jones & andrea nott', '47.750', '47.750', '95.500'], ['canada', 'marie - pier boudreau gagnon & isabelle rampling', '47.417', '47.667', '95.084'], ['italy', 'beatrice adelizzi & giulia lapi', '46.834', '46.917', '93.751'], ['ukraine', 'darya yushko & kseniya sydorenko', '46.084', '46.584', '92.668'], ['netherlands', 'bianca van der velden & sonja van der velden', '45.584', '46.083', '91.667'], ['greece', 'evanthia makrygianni & despoina solomou', '45.834', '45.667', '91.501'], ['france', 'apolline dreyfuss & lila meesseman - bakir', '44.750', '45.583', '90.333'], ['switzerland', 'magdalena brunner & ariane schneider', '44.250', '45.000', '89.250']] |
teen angels | https://en.wikipedia.org/wiki/Teen_Angels | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18073917-17.html.csv | majority | most of the time that teen angels was nominated , it won the award . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'won', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'result', 'won'], 'result': True, 'ind': 0, 'tointer': 'for the result records of all rows , most of them fuzzily match to won .', 'tostr': 'most_eq { all_rows ; result ; won } = true'} | most_eq { all_rows ; result ; won } = true | for the result records of all rows , most of them fuzzily match to won . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'result_3': 3, 'won_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'result_3': 'result', 'won_4': 'won'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'result_3': [0], 'won_4': [0]} | ['year', 'award', 'category', 'nominated', 'result'] | [['2009', 'capif awards', 'best album by a film / television band', 'teen angels', 'won'], ['2009', 'premios carlos gardel 2009', 'best album by a film / television band', 'teen angels', 'won'], ['2009', 'premios 40 principales', 'best argentine act', 'teen angels', 'won'], ['2010', 'premios carlos gardel 2010', 'best album by a film / television band', 'teen angels', 'won'], ['2010', 'premios 40 principales', 'best argentine act', 'teen angels', 'won'], ['2011', "kids ' choice awards argentina 2011", 'favorite music group', 'teen angels', 'won'], ['2011', 'premios carlos gardel', 'mejor álbum infantil / juvenil por teenangels 4', 'teen angels', 'pending']] |
pirveli liga | https://en.wikipedia.org/wiki/Pirveli_Liga | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18009885-2.html.csv | count | eight of the teams in the pirveli liga are located in the imereti region . | {'scope': 'all', 'criterion': 'equal', 'value': 'imereti', 'result': '8', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'region', 'imereti'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose region record fuzzily matches to imereti .', 'tostr': 'filter_eq { all_rows ; region ; imereti }'}], 'result': '8', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; region ; imereti } }', 'tointer': 'select the rows whose region record fuzzily matches to imereti . the number of such rows is 8 .'}, '8'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; region ; imereti } } ; 8 } = true', 'tointer': 'select the rows whose region record fuzzily matches to imereti . the number of such rows is 8 .'} | eq { count { filter_eq { all_rows ; region ; imereti } } ; 8 } = true | select the rows whose region record fuzzily matches to imereti . 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, 'region_5': 5, 'imereti_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', 'region_5': 'region', 'imereti_6': 'imereti', '8_7': '8'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'region_5': [0], 'imereti_6': [0], '8_7': [2]} | ['clubs', 'position 2010 - 11', 'region', 'stadium', 'capacity'] | [['samtredia', 'umaglesi liga', 'imereti', 'erosi manjgaladze stadium', '15000'], ['chikhura sachkhere', '4', 'imereti', 'tsentral stadium ( sachkhere )', '2000'], ['dinamo batumi', '5', 'adjara', 'batumi stadium', '30000'], ['guria lanchkhuti', '6', 'guria', 'evgrapi shevardnadze stadium', '22000'], ['kolkheti khobi', '7', 'samegrelo', 'tsentral stadium ( khobi )', '12000'], ['imereti khoni', '8', 'imereti', 'tsentral stadium ( khoni )', '2000'], ['meshakhte tkibuli', '9', 'imereti', 'vladimer bochorishvili stadium', '11700'], ['norchi dinamoeli tbilisi', '10', 'tbilisi', 'sport - kompleksi shatili', '2000'], ['chkherimela kharagauli', '11', 'imereti', 'kharagauli stadium', '6000'], ['adeli batumi', '12', 'adjara', 'tsentral stadium ( batumi )', '15000'], ['mertskhali ozurgeti', '13', 'guria', 'megobroba stadium', '3500'], ['samgurali tskhaltubo', '14', 'imereti', '26 may stadium', '12000'], ['skuri tsalenjikha', '15', 'samegrelo', 'sasha kvaratskhelia stadium', '4000'], ['chiatura sachkhere', '16', 'imereti', 'temur maghradze stadium', '11700'], ['lokomotivi tbilisi', '17', 'tbilisi', 'mikheil meskhi stadium', '24680'], ['sulori vani', 'meore liga', 'imereti', 'grigol nikoleishvili stadium', '2500'], ['stu tbilisi', 'meore liga', 'tbilisi', 'sport - kompleksi shatili', '2000'], ['meskheri akhaltsikhe', 'meore liga', 'samtskhe - javakheti', 'tsentral stadium ( akhaltsikhe )', '4000'], ['aeti sokhumi', 'meore liga', 'abkhazia', 'sport - kompleksi shatili', '2000'], ['zooveti tbilisi', 'meore liga', 'tbilisi', 'sportis akademiis stadioni', '1000']] |
2000 tennessee titans season | https://en.wikipedia.org/wiki/2000_Tennessee_Titans_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16025613-2.html.csv | count | 16 games total were played by the tennessee titans during the 2000 season . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': '2000', 'result': '16', 'col': '2', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', '2000'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose date record fuzzily matches to 2000 .', 'tostr': 'filter_eq { all_rows ; date ; 2000 }'}], 'result': '16', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; date ; 2000 } }', 'tointer': 'select the rows whose date record fuzzily matches to 2000 . the number of such rows is 16 .'}, '16'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; date ; 2000 } } ; 16 } = true', 'tointer': 'select the rows whose date record fuzzily matches to 2000 . the number of such rows is 16 .'} | eq { count { filter_eq { all_rows ; date ; 2000 } } ; 16 } = true | select the rows whose date record fuzzily matches to 2000 . the number of such rows is 16 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'date_5': 5, '2000_6': 6, '16_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', '2000_6': '2000', '16_7': '16'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'date_5': [0], '2000_6': [0], '16_7': [2]} | ['week', 'date', 'tv time', 'opponent', 'result'] | [['1', 'september 3 , 2000', 'espn 7:30 pm cdt', 'buffalo bills', 'l 13 - 16'], ['2', 'september 10 , 2000', 'cbs 12:00 pm cdt', 'kansas city chiefs', 'w 17 - 14'], ['3', '-', '-', '-', 'none'], ['4', 'september 24 , 2000', 'cbs 12:00 pm cdt', 'pittsburgh steelers', 'w 23 - 20'], ['5', 'october 1 , 2000', 'fox 12:00 pm cdt', 'new york giants', 'w 28 - 14'], ['6', 'october 8 , 2000', 'cbs 12:00 pm cdt', 'cincinnati bengals', 'w 23 - 14'], ['7', 'october 16 , 2000', 'abc 8:00 pm cdt', 'jacksonville jaguars', 'w 27 - 13'], ['8', 'october 22 , 2000', 'cbs 12:00 pm cdt', 'baltimore ravens', 'w 14 - 6'], ['9', 'october 30 , 2000', 'abc 8:00 pm cdt', 'washington redskins', 'w 27 - 21'], ['10', 'november 5 , 2000', 'cbs 12:00 pm cdt', 'pittsburgh steelers', 'w 9 - 7'], ['11', 'november 12 , 2000', 'cbs 12:00 pm cdt', 'baltimore ravens', 'l 23 - 24'], ['12', 'november 19 , 2000', 'cbs 12:00 pm cdt', 'cleveland browns', 'w 24 - 10'], ['13', 'november 26 , 2000', 'cbs 3:15 pm cdt', 'jacksonville jaguars', 'l 13 - 16'], ['14', 'december 3 , 2000', 'cbs 12:00 pm cdt', 'philadelphia eagles', 'w 15 - 13'], ['15', 'december 10 , 2000', 'cbs 12:00 pm cdt', 'cincinnati bengals', 'w 35 - 3'], ['16', 'december 17 , 2000', 'cbs 12:00 pm cdt', 'cleveland browns', 'w 24 - 0'], ['17', 'december 25 , 2000', 'abc 8:00 pm cdt', 'dallas cowboys', 'w 31 - 0']] |
north state conference | https://en.wikipedia.org/wiki/North_State_Conference | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-16168849-1.html.csv | ordinal | in the north state conference , the school that was founded 2nd to last was high point university . | {'row': '8', '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', 'founded', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; founded ; 2 }'}, 'institution'], 'result': 'high point university', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; founded ; 2 } ; institution }'}, 'high point university'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; founded ; 2 } ; institution } ; high point university } = true', 'tointer': 'select the row whose founded record of all rows is 2nd maximum . the institution record of this row is high point university .'} | eq { hop { nth_argmax { all_rows ; founded ; 2 } ; institution } ; high point university } = true | select the row whose founded record of all rows is 2nd maximum . the institution record of this row is high point university . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'founded_5': 5, '2_6': 6, 'institution_7': 7, 'high point university_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', 'founded_5': 'founded', '2_6': '2', 'institution_7': 'institution', 'high point university_8': 'high point university'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'founded_5': [0], '2_6': [0], 'institution_7': [1], 'high point university_8': [2]} | ['institution', 'location', 'founded', 'type', 'enrollment', 'nickname', 'joined', 'left', 'current conference'] | [['anderson university', 'anderson , south carolina', '1911', 'private', '2907', 'trojans', '1998', '2010', 'sac'], ['appalachian state university', 'boone , north carolina', '1899', 'public', '17589', 'mountaineers', '1930', '1967', 'socon ( sun belt in 2014 ) ( ncaa division i )'], ['catawba college', 'salisbury , north carolina', '1851', 'private', '1300', 'indians', '1930', '1989', 'sac'], ['coker college', 'hartsville , south carolina', '1908', 'private', '1200', 'cobras', '1991', '2013', 'sac'], ['east carolina university', 'greenville , north carolina', '1907', 'public', '27386', 'pirates', '1947', '1962', 'c - usa ( the american in 2014 ) ( ncaa division i )'], ['elon university', 'elon , north carolina', '1889', 'private', '6720', 'phoenix', '1930', '1989', 'socon ( caa in 2014 ) ( ncaa division i )'], ['guilford college', 'greensboro , north carolina', '1837', 'private', '2706', 'quakers', '1930', '1988', 'odac ( ncaa division iii )'], ['high point university', 'high point , north carolina', '1924', 'private', '4519', 'panthers', '1930', '1997', 'big south ( ncaa division i )'], ['lenoirrhyne university', 'hickory , north carolina', '1891', 'private', '1983', 'bears', '1930 , 1985', '1974 , 1989', 'sac'], ['longwood university', 'farmville , virginia', '1839', 'public', '4800', 'lancers', '1995', '2003', 'big south ( ncaa division i )'], ['mars hill college', 'mars hill , north carolina', '1856', 'private', '1370', 'lions', '1973', '1975', 'sac'], ['newberry college', 'newberry , south carolina', '1856', 'private', '949', 'wolves', '1961', '1972', 'sac'], ['university of north carolina at pembroke', 'pembroke , north carolina', '1887', 'public', '6433', 'braves', '1976', '1992', 'peach belt ( pbc )'], ['presbyterian college', 'clinton , south carolina', '1880', 'private', '1300', 'blue hose', '1965', '1972', 'big south ( ncaa division i )'], ['queens university of charlotte', 'charlotte , north carolina', '1857', 'private', '2386', 'royals', '1995', '2013', 'sac'], ['st andrews university', 'laurinburg , north carolina', '1958', 'private', '600', 'knights', '1988', '2012', 'aac ( naia )'], ['western carolina university', 'cullowhee , north carolina', '1889', 'public', '9608', 'catamounts', '1933', '1976', 'socon ( ncaa division i )']] |
cho jae - jin | https://en.wikipedia.org/wiki/Cho_Jae-Jin | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1385081-3.html.csv | comparative | cho jae-jin scored more goals in an international game in september 2006 than in october 2006 . | {'row_1': '6', 'row_2': '7', 'col': '3', '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', 'date', '6 september 2006'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose date record fuzzily matches to 6 september 2006 .', 'tostr': 'filter_eq { all_rows ; date ; 6 september 2006 }'}, 'score'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; date ; 6 september 2006 } ; score }', 'tointer': 'select the rows whose date record fuzzily matches to 6 september 2006 . take the score record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', '11 october 2006'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose date record fuzzily matches to 11 october 2006 .', 'tostr': 'filter_eq { all_rows ; date ; 11 october 2006 }'}, 'score'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; date ; 11 october 2006 } ; score }', 'tointer': 'select the rows whose date record fuzzily matches to 11 october 2006 . take the score record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; date ; 6 september 2006 } ; score } ; hop { filter_eq { all_rows ; date ; 11 october 2006 } ; score } } = true', 'tointer': 'select the rows whose date record fuzzily matches to 6 september 2006 . take the score record of this row . select the rows whose date record fuzzily matches to 11 october 2006 . take the score record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; date ; 6 september 2006 } ; score } ; hop { filter_eq { all_rows ; date ; 11 october 2006 } ; score } } = true | select the rows whose date record fuzzily matches to 6 september 2006 . take the score record of this row . select the rows whose date record fuzzily matches to 11 october 2006 . take the score 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, 'date_7': 7, '6 september 2006_8': 8, 'score_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'date_11': 11, '11 october 2006_12': 12, 'score_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', 'date_7': 'date', '6 september 2006_8': '6 september 2006', 'score_9': 'score', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'date_11': 'date', '11 october 2006_12': '11 october 2006', 'score_13': 'score'} | {'greater_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'date_7': [0], '6 september 2006_8': [0], 'score_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'date_11': [1], '11 october 2006_12': [1], 'score_13': [3]} | ['date', 'venue', 'score', 'result', 'competition'] | [['25 september 2003', 'incheon', '1 goal', '5 - 0', '2004 afc asian cup qualification'], ['24 october 2003', 'muscat', '1 goal', '7 - 0', '2004 afc asian cup qualification'], ['19 december 2004', 'busan', '1 goal', '3 - 1', 'friendly match'], ['1 february 2006', 'hong kong', '1 goal', '1 - 3', '2006 carlsberg cup'], ['26 may 2006', 'seoul', '1 goal', '2 - 0', 'friendly match'], ['6 september 2006', 'suwon', '2 goals', '8 - 0', '2007 afc asian cup qualification'], ['11 october 2006', 'seoul', '1 goal', '2 - 1', '2007 afc asian cup qualification'], ['5 july 2007', 'seoul', '2 goals', '2 - 1', 'friendly match']] |
calgary united f.c | https://en.wikipedia.org/wiki/Calgary_United_F.C. | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12042534-3.html.csv | comparative | calgary united had more losses in 2009 than they did in 2011 . | {'row_1': '3', 'row_2': '5', 'col': '4', 'col_other': '1', 'relation': 'greater', 'record_mentioned': 'yes', 'diff_result': None} | {'func': 'and', 'args': [{'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'team', '2009'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose team record fuzzily matches to 2009 .', 'tostr': 'filter_eq { all_rows ; team ; 2009 }'}, 'losses'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; team ; 2009 } ; losses }', 'tointer': 'select the rows whose team record fuzzily matches to 2009 . take the losses record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'team', '2011'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose team record fuzzily matches to 2011 .', 'tostr': 'filter_eq { all_rows ; team ; 2011 }'}, 'losses'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; team ; 2011 } ; losses }', 'tointer': 'select the rows whose team record fuzzily matches to 2011 . take the losses record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; team ; 2009 } ; losses } ; hop { filter_eq { all_rows ; team ; 2011 } ; losses } }', 'tointer': 'select the rows whose team record fuzzily matches to 2009 . take the losses record of this row . select the rows whose team record fuzzily matches to 2011 . take the losses record of this row . the first record is greater than the second record .'}, {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'team', '2009'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose team record fuzzily matches to 2009 .', 'tostr': 'filter_eq { all_rows ; team ; 2009 }'}, 'losses'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; team ; 2009 } ; losses }', 'tointer': 'select the rows whose team record fuzzily matches to 2009 . take the losses record of this row .'}, '8'], 'result': True, 'ind': 5, 'tostr': 'eq { hop { filter_eq { all_rows ; team ; 2009 } ; losses } ; 8 }', 'tointer': 'the losses record of the first row is 8 .'}, {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'team', '2011'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose team record fuzzily matches to 2011 .', 'tostr': 'filter_eq { all_rows ; team ; 2011 }'}, 'losses'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; team ; 2011 } ; losses }', 'tointer': 'select the rows whose team record fuzzily matches to 2011 . take the losses record of this row .'}, '4'], 'result': True, 'ind': 6, 'tostr': 'eq { hop { filter_eq { all_rows ; team ; 2011 } ; losses } ; 4 }', 'tointer': 'the losses record of the second row is 4 .'}], 'result': True, 'ind': 7, 'tostr': 'and { eq { hop { filter_eq { all_rows ; team ; 2009 } ; losses } ; 8 } ; eq { hop { filter_eq { all_rows ; team ; 2011 } ; losses } ; 4 } }', 'tointer': 'the losses record of the first row is 8 . the losses record of the second row is 4 .'}], 'result': True, 'ind': 8, 'tostr': 'and { greater { hop { filter_eq { all_rows ; team ; 2009 } ; losses } ; hop { filter_eq { all_rows ; team ; 2011 } ; losses } } ; and { eq { hop { filter_eq { all_rows ; team ; 2009 } ; losses } ; 8 } ; eq { hop { filter_eq { all_rows ; team ; 2011 } ; losses } ; 4 } } } = true', 'tointer': 'select the rows whose team record fuzzily matches to 2009 . take the losses record of this row . select the rows whose team record fuzzily matches to 2011 . take the losses record of this row . the first record is greater than the second record . the losses record of the first row is 8 . the losses record of the second row is 4 .'} | and { greater { hop { filter_eq { all_rows ; team ; 2009 } ; losses } ; hop { filter_eq { all_rows ; team ; 2011 } ; losses } } ; and { eq { hop { filter_eq { all_rows ; team ; 2009 } ; losses } ; 8 } ; eq { hop { filter_eq { all_rows ; team ; 2011 } ; losses } ; 4 } } } = true | select the rows whose team record fuzzily matches to 2009 . take the losses record of this row . select the rows whose team record fuzzily matches to 2011 . take the losses record of this row . the first record is greater than the second record . the losses record of the first row is 8 . the losses record of the second row is 4 . | 13 | 9 | {'and_8': 8, 'result_9': 9, 'greater_4': 4, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_10': 10, 'team_11': 11, '2009_12': 12, 'losses_13': 13, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_14': 14, 'team_15': 15, '2011_16': 16, 'losses_17': 17, 'and_7': 7, 'eq_5': 5, '8_18': 18, 'eq_6': 6, '4_19': 19} | {'and_8': 'and', 'result_9': 'true', 'greater_4': 'greater', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_10': 'all_rows', 'team_11': 'team', '2009_12': '2009', 'losses_13': 'losses', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_14': 'all_rows', 'team_15': 'team', '2011_16': '2011', 'losses_17': 'losses', 'and_7': 'and', 'eq_5': 'eq', '8_18': '8', 'eq_6': 'eq', '4_19': '4'} | {'and_8': [9], 'result_9': [], 'greater_4': [8], 'num_hop_2': [4, 5], 'filter_str_eq_0': [2], 'all_rows_10': [0], 'team_11': [0], '2009_12': [0], 'losses_13': [2], 'num_hop_3': [4, 6], 'filter_str_eq_1': [3], 'all_rows_14': [1], 'team_15': [1], '2011_16': [1], 'losses_17': [3], 'and_7': [8], 'eq_5': [7], '8_18': [5], 'eq_6': [7], '4_19': [6]} | ['team', 'games played', 'wins', 'losses', 'winning percentage', 'points for', 'points against', 'point differential'] | [['2007', '4', '2', '2', '500', '9', '6', '+ 3'], ['2008', '10', '8', '2', '800', '72', '38', '+ 34'], ['2009', '16', '8', '8', '500', '109', '84', '+ 21'], ['2010', '10', '8', '2', '800', '79', '32', '+ 47'], ['2011', '12', '8', '4', '667', '68', '52', '+ 16']] |
1992 in spaceflight | https://en.wikipedia.org/wiki/1992_in_spaceflight | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17621896-3.html.csv | unique | there was only one space flight that was timed in july of 1992 . | {'scope': 'all', 'row': '6', 'col': '1', 'col_other': 'n/a', 'criterion': 'fuzzily_match', 'value': 'july', 'subset': None} | {'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'start date / time', 'july'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose start date / time record fuzzily matches to july .', 'tostr': 'filter_eq { all_rows ; start date / time ; july }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; start date / time ; july } } = true', 'tointer': 'select the rows whose start date / time record fuzzily matches to july . there is only one such row in the table .'} | only { filter_eq { all_rows ; start date / time ; july } } = true | select the rows whose start date / time record fuzzily matches to july . 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, 'start date / time_4': 4, 'july_5': 5} | {'only_1': 'only', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'start date / time_4': 'start date / time', 'july_5': 'july'} | {'only_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'start date / time_4': [0], 'july_5': [0]} | ['start date / time', 'duration', 'end time', 'spacecraft', 'crew'] | [['20 february 20:09', '4 hours 12 minutes', '21 february 00:21', 'mir eo - 10 kvant - 2', 'aleksandr volkov sergei krikalyov'], ['10 may 20:40', '3 hours 43 minutes', '11 may 00:23', 'sts - 49 endeavour', 'pierre j thuot richard hieb'], ['11 may 21:05', '5 hours 30 minutes', '12 may 02:35', 'sts - 49 endeavour', 'pierre j thuot richard hieb'], ['13 may 21:17', '8 hours 29 minutes', '14 may 05:46', 'sts - 49 endeavour', 'pierre j thuot richard hieb thomas akers'], ['14 may ~ 21:00', '7 hours 44 minutes', '15 may ~ 04:45', 'sts - 49 endeavour', 'thomas akers kathryn c thornton'], ['8 july 12:38', '2 hours 3 minutes', '14:41', 'mir eo - 11 kvant - 2', 'aleksandr viktorenko aleksandr kaleri'], ['3 september 13:32', '3 hours 56 minutes', '17:28', 'mir eo - 12 kvant - 2', 'sergei avdeyev anatoly solovyev'], ['7 september 11:47', '5 hours 8 minutes', '16:55', 'mir eo - 12 kvant - 2', 'sergei avdeyev anatoly solovyev'], ['11 september 10:06', '5 hours 44 minutes', '15:50', 'mir eo - 12 kvant - 2', 'sergei avdeyev anatoly solovyev'], ['15 september 07:49', '3 hours 33 minutes', '11:22', 'mir eo - 12 kvant - 2', 'sergei avdeyev anatoly solovyev']] |
wisconsin intercollegiate athletic conference | https://en.wikipedia.org/wiki/Wisconsin_Intercollegiate_Athletic_Conference | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-262495-1.html.csv | majority | most of the schools belonging to the wisconsin intercollegiate conference were founded prior to 1900 . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'less_than', 'value': '1900', 'subset': None} | {'func': 'most_less', 'args': ['all_rows', 'founded', '1900'], 'result': True, 'ind': 0, 'tointer': 'for the founded records of all rows , most of them are less than 1900 .', 'tostr': 'most_less { all_rows ; founded ; 1900 } = true'} | most_less { all_rows ; founded ; 1900 } = true | for the founded records of all rows , most of them are less than 1900 . | 1 | 1 | {'most_less_0': 0, 'result_1': 1, 'all_rows_2': 2, 'founded_3': 3, '1900_4': 4} | {'most_less_0': 'most_less', 'result_1': 'true', 'all_rows_2': 'all_rows', 'founded_3': 'founded', '1900_4': '1900'} | {'most_less_0': [1], 'result_1': [], 'all_rows_2': [0], 'founded_3': [0], '1900_4': [0]} | ['institution', 'nickname', 'location ( population )', 'founded', 'type', 'undergraduate enrollment', 'joined'] | [['university of wisconsin - eau claire', 'blugolds', 'eau claire , wisconsin ( 65883 )', '1916', 'public', '9799', '1917 - 18'], ['university of wisconsin - la crosse', 'eagles', 'la crosse , wisconsin ( 52485 )', '1909', 'public', '8324', '1913 - 14'], ['university of wisconsin - oshkosh', 'titans', 'oshkosh , wisconsin ( 66083 )', '1871', 'public', '9386', '1913 - 14'], ['university of wisconsin - platteville', 'pioneers', 'platteville , wisconsin ( 11224 )', '1866', 'public', '6498', '1913 - 14'], ['university of wisconsin - river falls', 'falcons', 'river falls , wisconsin ( 15000 )', '1874', 'public', '5801', '1913 - 14'], ['university of wisconsin - stevens point', 'pointers', 'stevens point , wisconsin ( 26717 )', '1894', 'public', '8481', '1913 - 14'], ['university of wisconsin - stout', 'blue devils', 'menomonie , wisconsin ( 16264 )', '1891', 'public', '6874', '1914 - 15'], ['university of wisconsin - superior', 'yellowjackets', 'superior , wisconsin ( 26960 )', '1893', 'public', '2114', '1913 - 14']] |
1972 vfl season | https://en.wikipedia.org/wiki/1972_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10826385-15.html.csv | superlative | vfl park had the largest crowd of any venue of the 1972 vfl season . | {'scope': 'all', 'col_superlative': '6', 'row_superlative': '6', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '5', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'crowd'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; crowd }'}, 'venue'], 'result': 'vfl park', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; crowd } ; venue }'}, 'vfl park'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; crowd } ; venue } ; vfl park } = true', 'tointer': 'select the row whose crowd record of all rows is maximum . the venue record of this row is vfl park .'} | eq { hop { argmax { all_rows ; crowd } ; venue } ; vfl park } = true | select the row whose crowd record of all rows is maximum . the venue record of this row is vfl park . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'crowd_5': 5, 'venue_6': 6, 'vfl park_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'crowd_5': 'crowd', 'venue_6': 'venue', 'vfl park_7': 'vfl park'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'crowd_5': [0], 'venue_6': [1], 'vfl park_7': [2]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['footscray', '14.7 ( 91 )', 'st kilda', '9.11 ( 65 )', 'western oval', '18655', '15 july 1972'], ['fitzroy', '16.14 ( 110 )', 'north melbourne', '9.12 ( 66 )', 'junction oval', '7007', '15 july 1972'], ['essendon', '13.12 ( 90 )', 'richmond', '17.9 ( 111 )', 'windy hill', '22251', '15 july 1972'], ['carlton', '20.8 ( 128 )', 'south melbourne', '8.15 ( 63 )', 'princes park', '14465', '15 july 1972'], ['hawthorn', '19.14 ( 128 )', 'geelong', '15.8 ( 98 )', 'glenferrie oval', '12425', '15 july 1972'], ['collingwood', '10.13 ( 73 )', 'melbourne', '8.10 ( 58 )', 'vfl park', '30883', '15 july 1972']] |
gary mcallister | https://en.wikipedia.org/wiki/Gary_McAllister | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1586620-1.html.csv | majority | gary mcallister played most of his games in the year of 1992 than any other year . | {'scope': 'all', 'col': '1', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': '1992', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'date', '1992'], 'result': True, 'ind': 0, 'tointer': 'for the date records of all rows , most of them fuzzily match to 1992 .', 'tostr': 'most_eq { all_rows ; date ; 1992 } = true'} | most_eq { all_rows ; date ; 1992 } = true | for the date records of all rows , most of them fuzzily match to 1992 . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'date_3': 3, '1992_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'date_3': 'date', '1992_4': '1992'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'date_3': [0], '1992_4': [0]} | ['date', 'venue', 'score', 'result', 'competition'] | [['17 october 1990', 'hampden park , glasgow , scotland', '2 - 1', 'win', 'uefa euro 1992 qualifying'], ['20 may 1992', 'varsity stadium , toronto , canada', '1 - 3', 'win', 'friendly'], ['18 june 1992', 'idrottsparken , norrköping , sweden', '0 - 3', 'win', 'uefa euro 1992'], ['8 june 1997', 'dynama stadium , minsk , belarus', '0 - 1', 'win', '1998 world cup qualification']] |
moses ndiema masai | https://en.wikipedia.org/wiki/Moses_Ndiema_Masai | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16682451-1.html.csv | majority | the majority of the events were solo , non-team competitions . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'not_equal', 'value': 'team competitions', 'subset': None} | {'func': 'most_str_not_eq', 'args': ['all_rows', 'event', 'team competitions'], 'result': True, 'ind': 0, 'tointer': 'for the event records of all rows , most of them do not match to team competitions .', 'tostr': 'most_not_eq { all_rows ; event ; team competitions } = true'} | most_not_eq { all_rows ; event ; team competitions } = true | for the event records of all rows , most of them do not match to team competitions . | 1 | 1 | {'most_str_not_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'event_3': 3, 'team competitions_4': 4} | {'most_str_not_eq_0': 'most_str_not_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'event_3': 'event', 'team competitions_4': 'team competitions'} | {'most_str_not_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'event_3': [0], 'team competitions_4': [0]} | ['year', 'competition', 'venue', 'position', 'event'] | [['2004', 'world junior championships', 'grosseto , italy', '10th', '10000 m'], ['2005', 'african junior championships', 'radès , tunisia', '1st', '5000 m'], ['2005', 'african junior championships', 'radès , tunisia', '1st', '10000 m'], ['2007', 'world athletics final', 'stuttgart , germany', '3rd', '5000 m'], ['2008', 'world cross country championships', 'edinburgh , scotland', '5th', 'senior race'], ['2008', 'world cross country championships', 'edinburgh , scotland', '1st', 'team competition'], ['2009', 'world championships', 'berlin , germany', '3rd', '10000 m'], ['2013', 'okpekpe international road race', 'okpekpe , nigeria', '1st', '10 kilometres']] |
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