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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/2-10966926-8.html.csv | superlative | chris cooley recorded the most receptions for the 2008 washington redskins . | {'scope': 'all', 'col_superlative': '2', 'row_superlative': '2', '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', 'rec'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; rec }'}, 'player'], 'result': 'chris cooley', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; rec } ; player }'}, 'chris cooley'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; rec } ; player } ; chris cooley } = true', 'tointer': 'select the row whose rec record of all rows is maximum . the player record of this row is chris cooley .'} | eq { hop { argmax { all_rows ; rec } ; player } ; chris cooley } = true | select the row whose rec record of all rows is maximum . the player record of this row is chris cooley . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'rec_5': 5, 'player_6': 6, 'chris cooley_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'rec_5': 'rec', 'player_6': 'player', 'chris cooley_7': 'chris cooley'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'rec_5': [0], 'player_6': [1], 'chris cooley_7': [2]} | ['player', 'rec', 'yards', 'avg', 'long'] | [['santana moss', '79', '1044', '13.2', '67'], ['chris cooley', '83', '849', '10.2', '28'], ['antwaan randle el', '53', '593', '11.2', '31'], ['clinton portis', '28', '218', '7.8', '29'], ['ladell betts', '22', '200', '9.1', '27'], ['devin thomas', '15', '120', '8.0', '18'], ['mike sellers', '12', '98', '8.2', '20'], ['james thrash', '9', '81', '9.0', '29'], ['todd yoder', '8', '50', '6.3', '14'], ['fred davis', '3', '27', '9.0', '15'], ['malcolm kelly', '3', '18', '6.0', '7'], ['shaun alexander', '1', '9', '9.0', '9'], ['rock cartwright', '1', '- 7', '- 7.0', '- 7'], ['pete kendall', '1', '- 9', '- 9.0', '- 9']] |
mid - southern conference of indiana | https://en.wikipedia.org/wiki/Mid-Southern_Conference_of_Indiana | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18833029-1.html.csv | aggregation | the average enrollment for schools that joined in the 1950s is below 800 . | {'scope': 'all', 'col': '4', 'type': 'average', 'result': '651.8', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'enrollment'], 'result': '651.8', 'ind': 0, 'tostr': 'avg { all_rows ; enrollment }'}, '651.8'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; enrollment } ; 651.8 } = true', 'tointer': 'the average of the enrollment record of all rows is 651.8 .'} | round_eq { avg { all_rows ; enrollment } ; 651.8 } = true | the average of the enrollment record of all rows is 651.8 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'enrollment_4': 4, '651.8_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'enrollment_4': 'enrollment', '651.8_5': '651.8'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'enrollment_4': [0], '651.8_5': [1]} | ['school', 'location', 'mascot', 'enrollment', 'ihsaa class', 'county', 'year joined'] | [['austin', 'austin', 'eagles', '437', 'aa', '72 scott', '1958'], ['brownstown central', 'brownstown', 'braves', '611', 'aaa', '36 jackson', '1965'], ['charlestown', 'charlestown', 'pirates', '702', 'aaa', '10 clark', '1958'], ['clarksville', 'clarksville', 'generals', '530', 'aa', '10 clark', '1958'], ['corydon central', 'corydon', 'panthers', '819', 'aaa', '31 harrison', '1958'], ['eastern ( pekin )', 'new pekin', 'musketeers', '552', 'aa', '88 washington', '2003'], ['north harrison', 'ramsey', 'cougars', '702', 'aaa', '31 harrison', '1978'], ['salem', 'salem', 'lions', '656', 'aaa', '88 washington', '1958'], ['scottsburg', 'scottsburg', 'warriors', '865', 'aaa', '72 scott', '1958'], ['silver creek', 'sellersburg', 'dragons', '644', 'aaa', '10 clark', '1958']] |
2007 - 08 birmingham city f.c. season | https://en.wikipedia.org/wiki/2007%E2%80%9308_Birmingham_City_F.C._season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15120038-1.html.csv | ordinal | 1 . fc heidenheim was the 2nd earliest opponent in the 2007-08 birmingham city f.c. season . | {'row': '2', 'col': '1', 'order': '2', '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', 'date', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; date ; 2 }'}, 'opponents'], 'result': '1 . fc heidenheim', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; date ; 2 } ; opponents }'}, '1 . fc heidenheim'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; date ; 2 } ; opponents } ; 1 . fc heidenheim } = true', 'tointer': 'select the row whose date record of all rows is 2nd minimum . the opponents record of this row is 1 . fc heidenheim .'} | eq { hop { nth_argmin { all_rows ; date ; 2 } ; opponents } ; 1 . fc heidenheim } = true | select the row whose date record of all rows is 2nd minimum . the opponents record of this row is 1 . fc heidenheim . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'date_5': 5, '2_6': 6, 'opponents_7': 7, '1. fc heidenheim_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', 'date_5': 'date', '2_6': '2', 'opponents_7': 'opponents', '1. fc heidenheim_8': '1 . fc heidenheim'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'date_5': [0], '2_6': [0], 'opponents_7': [1], '1. fc heidenheim_8': [2]} | ['date', 'opponents', 'venue', 'result', 'score f - a'] | [['16 july 2007', 'hollenbach / hohenlohe auswahl', 'a', 'w', '2 - 0'], ['18 july 2007', '1 . fc heidenheim', 'a', 'w', '2 - 0'], ['23 july 2007', 'fc schweinfurt 05', 'a', 'w', '5 - 2'], ['28 july 2007', 'walsall', 'a', 'w', '2 - 0'], ['31 july 2007', 'peterborough united', 'a', 'w', '3 - 0'], ['4 august 2007', 'sheffield wednesday', 'a', 'w', '3 - 0']] |
2008 - 09 memphis grizzlies season | https://en.wikipedia.org/wiki/2008%E2%80%9309_Memphis_Grizzlies_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17121262-6.html.csv | aggregation | for the 2008-09 memphis grizzlies season the games against new orleans had a total combined attendance of 27053 . | {'scope': 'subset', 'col': '8', 'type': 'sum', 'result': '27053', 'subset': {'col': '3', 'criterion': 'equal', 'value': 'new orleans'}} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'team', 'new orleans'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; team ; new orleans }', 'tointer': 'select the rows whose team record fuzzily matches to new orleans .'}, 'location attendance'], 'result': '27053', 'ind': 1, 'tostr': 'sum { filter_eq { all_rows ; team ; new orleans } ; location attendance }'}, '27053'], 'result': True, 'ind': 2, 'tostr': 'round_eq { sum { filter_eq { all_rows ; team ; new orleans } ; location attendance } ; 27053 } = true', 'tointer': 'select the rows whose team record fuzzily matches to new orleans . the sum of the location attendance record of these rows is 27053 .'} | round_eq { sum { filter_eq { all_rows ; team ; new orleans } ; location attendance } ; 27053 } = true | select the rows whose team record fuzzily matches to new orleans . the sum of the location attendance record of these rows is 27053 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'sum_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'team_5': 5, 'new orleans_6': 6, 'location attendance_7': 7, '27053_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'sum_1': 'sum', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'team_5': 'team', 'new orleans_6': 'new orleans', 'location attendance_7': 'location attendance', '27053_8': '27053'} | {'eq_2': [3], 'result_3': [], 'sum_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'team_5': [0], 'new orleans_6': [0], 'location attendance_7': [1], '27053_8': [2]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record'] | [['18', 'december 3', 'atlanta', 'l 95 - 105 ( ot )', 'hakim warrick ( 20 )', 'rudy gay ( 10 )', 'mike conley , jr , kyle lowry ( 4 )', 'philips arena 12088', '4 - 14'], ['19', 'december 5', 'la clippers', 'w 93 - 81 ( ot )', 'rudy gay ( 25 )', 'darko miličić ( 9 )', 'kyle lowry ( 5 )', 'fedexforum 10484', '5 - 14'], ['20', 'december 6', 'new orleans', 'l 87 - 106 ( ot )', 'marc gasol ( 21 )', 'marc gasol ( 7 )', 'o j mayo ( 5 )', 'new orleans arena 16822', '5 - 15'], ['21', 'december 8', 'houston', 'w 109 - 97 ( ot )', 'rudy gay ( 20 )', 'hakim warrick , marc gasol ( 8 )', 'kyle lowry ( 5 )', 'fedexforum 10691', '6 - 15'], ['22', 'december 10', 'oklahoma city', 'w 108 - 102 ( ot )', 'rudy gay ( 22 )', 'rudy gay , hakim warrick , marc gasol ( 6 )', 'o j mayo , kyle lowry ( 5 )', 'ford center 18009', '7 - 15'], ['23', 'december 12', 'chicago', 'w 103 - 96 ( ot )', 'rudy gay ( 29 )', 'darko miličić ( 11 )', 'mike conley , jr ( 7 )', 'fedexforum 17132', '8 - 15'], ['24', 'december 14', 'miami', 'w 102 - 86 ( ot )', 'o j mayo ( 28 )', 'marc gasol ( 7 )', 'kyle lowry ( 5 )', 'fedexforum 12271', '9 - 15'], ['25', 'december 16', 'new orleans', 'l 84 - 91 ( ot )', 'rudy gay ( 28 )', 'marc gasol ( 11 )', 'o j mayo , mike conley , jr ( 4 )', 'fedexforum 10231', '9 - 16'], ['26', 'december 19', 'charlotte', 'l 83 - 112 ( ot )', 'rudy gay ( 17 )', 'marc gasol ( 6 )', 'o j mayo ( 4 )', 'fedexforum 11869', '9 - 17'], ['27', 'december 22', 'la lakers', 'l 96 - 105 ( ot )', 'rudy gay ( 23 )', 'darko miličić ( 8 )', 'kyle lowry ( 7 )', 'fedexforum 17456', '9 - 18'], ['28', 'december 23', 'dallas', 'l 82 - 100 ( ot )', 'hakim warrick ( 17 )', 'rudy gay ( 9 )', 'kyle lowry ( 4 )', 'american airlines center 20200', '9 - 19'], ['29', 'december 26', 'indiana', 'w 108 - 105 ( ot )', 'hakim warrick ( 21 )', 'o j mayo ( 8 )', 'o j mayo ( 7 )', 'fedexforum 12346', '10 - 19'], ['30', 'december 27', 'san antonio', 'l 103 - 106 ( 2ot )', 'o j mayo ( 29 )', 'rudy gay ( 11 )', 'kyle lowry ( 8 )', 'at & t center 18797', '10 - 20'], ['31', 'december 29', 'minnesota', 'l 98 - 108 ( ot )', 'o j mayo ( 23 )', 'hakim warrick ( 8 )', 'kyle lowry ( 12 )', 'target center 12207', '10 - 21'], ['32', 'december 30', 'phoenix', 'l 89 - 101 ( ot )', 'hakim warrick ( 25 )', 'marc gasol ( 13 )', 'kyle lowry ( 6 )', 'fedexforum 14471', '10 - 22']] |
list of active indonesian navy ships | https://en.wikipedia.org/wiki/List_of_active_Indonesian_Navy_ships | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-12232526-2.html.csv | count | four ships are reportedly still active as of 2009 . | {'scope': 'all', 'criterion': 'equal', 'value': 'reportedly still active as of 2009', 'result': '4', 'col': '7', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'note', 'reportedly still active as of 2009'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose note record fuzzily matches to reportedly still active as of 2009 .', 'tostr': 'filter_eq { all_rows ; note ; reportedly still active as of 2009 }'}], 'result': '4', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; note ; reportedly still active as of 2009 } }', 'tointer': 'select the rows whose note record fuzzily matches to reportedly still active as of 2009 . the number of such rows is 4 .'}, '4'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; note ; reportedly still active as of 2009 } } ; 4 } = true', 'tointer': 'select the rows whose note record fuzzily matches to reportedly still active as of 2009 . the number of such rows is 4 .'} | eq { count { filter_eq { all_rows ; note ; reportedly still active as of 2009 } } ; 4 } = true | select the rows whose note record fuzzily matches to reportedly still active as of 2009 . the number of such rows is 4 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'note_5': 5, 'reportedly still active as of 2009_6': 6, '4_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'note_5': 'note', 'reportedly still active as of 2009_6': 'reportedly still active as of 2009', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'note_5': [0], 'reportedly still active as of 2009_6': [0], '4_7': [2]} | ['class', 'ship name', 'origin', 'hull numbers', 'service years', 'previously', 'note'] | [['ahmad yani class ( ffghm )', 'kri ahmad yani', 'netherlands', '351', '1986 - present', 'rnn hnlms tjerk hiddes ( f804 )', 'reportedly still active as of 2009'], ['ahmad yani class ( ffghm )', 'kri slamet riyadi', 'netherlands', '352', '1986 - present', 'rnn hnlms van speijk ( f802 )', 'reportedly still active as of 2009'], ['ahmad yani class ( ffghm )', 'kri yos sudarso', 'netherlands', '353', '1987 - present', 'rnn hnlms van galen ( f803 )', 'reportedly still active as of 2009'], ['ahmad yani class ( ffghm )', 'kri oswald siahaan', 'netherlands', '354', '1987 - present', 'rnn hnlms van nes ( f805 )', 'reportedly still active as of 2012'], ['ahmad yani class ( ffghm )', 'kri halim perdanakususma', 'netherlands', '355', '1989 - present', 'rnn hnlms evertsen ( f815 )', 'reportedly still active as of 2009']] |
1974 vfl season | https://en.wikipedia.org/wiki/1974_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10869646-17.html.csv | superlative | in the games of 1974 vfl season listed the most points were scored by collingwood . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '4', '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', 'away team score'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; away team score }'}, 'home team score'], 'result': '15.21 ( 111 )', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; away team score } ; home team score }'}, '15.21 ( 111 )'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; away team score } ; home team score } ; 15.21 ( 111 ) } = true', 'tointer': 'select the row whose away team score record of all rows is maximum . the home team score record of this row is 15.21 ( 111 ) .'} | eq { hop { argmax { all_rows ; away team score } ; home team score } ; 15.21 ( 111 ) } = true | select the row whose away team score record of all rows is maximum . the home team score record of this row is 15.21 ( 111 ) . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'away team score_5': 5, 'home team score_6': 6, '15.21 (111)_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'away team score_5': 'away team score', 'home team score_6': 'home team score', '15.21 (111)_7': '15.21 ( 111 )'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'away team score_5': [0], 'home team score_6': [1], '15.21 (111)_7': [2]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['essendon', '9.10 ( 64 )', 'footscray', '13.15 ( 93 )', 'windy hill', '16250', '27 july 1974'], ['st kilda', '10.13 ( 73 )', 'north melbourne', '11.16 ( 82 )', 'moorabbin oval', '15954', '27 july 1974'], ['hawthorn', '13.28 ( 106 )', 'fitzroy', '8.10 ( 58 )', 'princes park', '6198', '27 july 1974'], ['melbourne', '15.21 ( 111 )', 'collingwood', '17.13 ( 115 )', 'mcg', '22893', '27 july 1974'], ['south melbourne', '14.17 ( 101 )', 'carlton', '11.14 ( 80 )', 'lake oval', '14114', '27 july 1974'], ['richmond', '13.15 ( 93 )', 'geelong', '8.9 ( 57 )', 'vfl park', '15578', '27 july 1974']] |
1976 usac championship car season | https://en.wikipedia.org/wiki/1976_USAC_Championship_Car_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-22673872-1.html.csv | majority | a. j. foyt had pole position for most of the races in 1976 . | {'scope': 'all', 'col': '7', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'a j foyt', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'pole position', 'a j foyt'], 'result': True, 'ind': 0, 'tointer': 'for the pole position records of all rows , most of them fuzzily match to a j foyt .', 'tostr': 'most_eq { all_rows ; pole position ; a j foyt } = true'} | most_eq { all_rows ; pole position ; a j foyt } = true | for the pole position records of all rows , most of them fuzzily match to a j foyt . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'pole position_3': 3, 'a j foyt_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'pole position_3': 'pole position', 'a j foyt_4': 'a j foyt'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'pole position_3': [0], 'a j foyt_4': [0]} | ['rnd', 'date', 'race name', 'length', 'track', 'location', 'pole position', 'winning driver'] | [['1', 'march 14', 'jimmy bryan 150', '-', 'phoenix international raceway', 'avondale , arizona', 'al unser', 'bobby unser'], ['2', 'may 2', 'trenton 200', '-', 'trenton international speedway', 'trenton , new jersey', 'a j foyt', 'johnny rutherford'], ['3', 'may 30', 'international 500 mile sweepstakes', '-', 'indianapolis motor speedway', 'speedway , indiana', 'johnny rutherford', 'johnny rutherford'], ['4', 'june 13', 'rex mays classic', '-', 'wisconsin state fair park speedway', 'west allis , wisconsin', 'gordon johncock', 'mike mosley'], ['5', 'june 27', 'schaefer 500', '-', 'pocono international raceway', 'long pond , pennsylvania', 'johnny parsons', 'al unser'], ['6', 'july 18', 'norton twin 200s', '-', 'michigan international speedway', 'brooklyn , michigan', 'a j foyt', 'gordon johncock'], ['7', 'august 1', 'texas 150', '-', 'texas world speedway', 'college station , texas', 'a j foyt', 'a j foyt'], ['8', 'august 15', 'trenton 200', '-', 'trenton international speedway', 'trenton , new jersey', 'a j foyt', 'gordon johncock'], ['9', 'august 22', 'tony bettenhausen 200', '-', 'wisconsin state fair park speedway', 'west allis , wisconsin', 'johnny rutherford', 'al unser'], ['10', 'september 5', 'california 500', '-', 'ontario motor speedway', 'ontario , california', 'a j foyt', 'bobby unser'], ['11', 'september 18', 'michigan 150', '-', 'michigan international speedway', 'brooklyn , michigan', 'a j foyt', 'a j foyt'], ['12', 'october 31', 'benihana world series of auto racing', '-', 'texas world speedway', 'college station , texas', 'a j foyt', 'johnny rutherford']] |
ulrikke eikeri | https://en.wikipedia.org/wiki/Ulrikke_Eikeri | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27877656-7.html.csv | majority | ulrikke eikeri won most of her tournaments from 2008 to 2011 . | {'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', 'edition', 'opponent team', 'surface', 'opponent', 'score'] | [['winner', '2008 europe / africa group iiia', 'mauritius', 'clay', 'astrid tixier', '6 - 1 , 6 - 2'], ['winner', '2008 europe / africa group iiia', 'zimbabwe', 'clay', 'denise atzinger', '6 - 0 , 6 - 0'], ['winner', '2008 europe / africa group iiia', 'latvia', 'clay', 'trīna šlapeka', '6 - 1 , 6 - 3'], ['winner', '2008 europe / africa group iiia', 'iceland', 'clay', 'rebekka pétursdóttir', '6 - 0 , 6 - 0'], ['winner', '2009 europe / africa group iiib', 'liechtenstein', 'hard', 'kathinka von deichmann', '6 - 1 , 6 - 4'], ['winner', '2009 europe / africa group iiib', 'iceland', 'hard', 'sandra kristjánsdóttir', '6 - 0 , 6 - 1'], ['loser', '2009 europe / africa group iiib', 'armenia', 'hard', 'anna movsisyan', '6 - 4 , 6 - 1'], ['winner', '2009 europe / africa group iiib', 'moldova', 'hard', 'olga terteac', '6 - 1 , 6 - 2'], ['winner', '2009 europe / africa group iiib', 'egypt', 'hard', 'may el wardany', '6 - 0 , 6 - 0'], ['loser', '2010 europe / africa group iib', 'armenia', 'clay', 'ani amiraghyan', '4 - 6 , 6 - 3 , 6 - 2'], ['loser', '2010 europe / africa group iib', 'finland', 'clay', 'emma laine', '6 - 1 , 6 - 2'], ['loser', '2010 europe / africa group iib', 'georgia', 'clay', 'anna tatishvili', '6 - 2 , 6 - 3'], ['loser', '2010 europe / africa group ii playoff', 'liechtenstein', 'clay', 'stephanie vogt', '6 - 4 , 7 - 5'], ['winner', '2011 europe / africa group iiib', 'ireland', 'clay', 'julia moriarty', '6 - 4 , 6 - 1'], ['winner', '2011 europe / africa group iiib', 'moldova', 'clay', 'julia helbet', '1 - 6 , 7 - 5 , 6 - 3'], ['winner', '2011 europe / africa group iiib', 'tunisia', 'clay', 'ons jabeur', '7 - 6 ( 7 - 3 ) , 6 - 4']] |
northeast delta dental international | https://en.wikipedia.org/wiki/Northeast_Delta_Dental_International | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-15315276-1.html.csv | unique | jessica shepley was the only champion from the country of canada in the northeast delta dental international . | {'scope': 'all', 'row': '3', 'col': '4', 'col_other': '3', 'criterion': 'equal', 'value': 'canada', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'canada'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose country record fuzzily matches to canada .', 'tostr': 'filter_eq { all_rows ; country ; canada }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; country ; canada } }', 'tointer': 'select the rows whose country record fuzzily matches to canada . 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', 'canada'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose country record fuzzily matches to canada .', 'tostr': 'filter_eq { all_rows ; country ; canada }'}, 'champion'], 'result': 'jessica shepley', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; country ; canada } ; champion }'}, 'jessica shepley'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; country ; canada } ; champion } ; jessica shepley }', 'tointer': 'the champion record of this unqiue row is jessica shepley .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; country ; canada } } ; eq { hop { filter_eq { all_rows ; country ; canada } ; champion } ; jessica shepley } } = true', 'tointer': 'select the rows whose country record fuzzily matches to canada . there is only one such row in the table . the champion record of this unqiue row is jessica shepley .'} | and { only { filter_eq { all_rows ; country ; canada } } ; eq { hop { filter_eq { all_rows ; country ; canada } ; champion } ; jessica shepley } } = true | select the rows whose country record fuzzily matches to canada . there is only one such row in the table . the champion record of this unqiue row is jessica shepley . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'country_7': 7, 'canada_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'champion_9': 9, 'jessica shepley_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', 'canada_8': 'canada', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'champion_9': 'champion', 'jessica shepley_10': 'jessica shepley'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'country_7': [0], 'canada_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'champion_9': [2], 'jessica shepley_10': [3]} | ['year', 'dates', 'champion', 'country', 'score', 'tournament location', 'purse', 'winners share'] | [['2013', 'jul 19 - 21', 'pk kongkraphan', 'thailand', '207 ( 9 )', 'beaver meadow golf course', '100000', '15000'], ['2012', 'jul 20 - 22', 'jenny gleason', 'united states', '211 ( 5 )', 'beaver meadow golf course', '100000', '15000'], ['2011', 'jul 22 - 24', 'jessica shepley', 'canada', '203 ( 13 )', 'beaver meadow golf course', '100000', '14000'], ['2010', 'jul 19 - 25', 'jenny shin', 'united states', '205 ( 11 )', 'beaver meadow golf course', '110000', '15400'], ['2009', 'jul 24 - 26', 'misun cho', 'south korea', '207 ( 9 )', 'beaver meadow golf course', '90000', '12600'], ['2008', 'jul 25 - 27', 'mo martin', 'united states', '204 ( 12 )', 'beaver meadow golf course', '80000', '11200'], ['2007', 'aug 3 - 5', 'ji min jeong', 'south korea', '209 ( 7 )', 'beaver meadow golf course', '75000', '10500'], ['2006', 'aug 4 - 6', 'charlotte mayorkas', 'united states', '207 ( 9 )', 'beaver meadow golf course', '70000', '9800'], ['2005', 'jul 22 - 24', 'kyeong bae', 'south korea', '209 ( 7 )', 'beaver meadow golf course', '65000', '9100']] |
germany | https://en.wikipedia.org/wiki/Germany | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11867-3.html.csv | aggregation | the average profit of all of the largest companies in germany is 121.66 . | {'scope': 'all', 'col': '5', 'type': 'average', 'result': '121.66', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'profit ( mil )'], 'result': '121.66', 'ind': 0, 'tostr': 'avg { all_rows ; profit ( mil ) }'}, '121.66'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; profit ( mil ) } ; 121.66 } = true', 'tointer': 'the average of the profit ( mil ) record of all rows is 121.66 .'} | round_eq { avg { all_rows ; profit ( mil ) } ; 121.66 } = true | the average of the profit ( mil ) record of all rows is 121.66 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'profit (mil)_4': 4, '121.66_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'profit (mil)_4': 'profit ( mil )', '121.66_5': '121.66'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'profit (mil)_4': [0], '121.66_5': [1]} | ['rank', 'name', 'headquarters', 'revenue ( mil )', 'profit ( mil )', 'employees ( world )'] | [['0 1', 'volkswagen ag', 'wolfsburg', '159.000', '15.800', '502 ,000'], ['0 2', 'eon se', 'düsseldorf', '113.000', '1.900', '79 ,000'], ['0 3', 'daimler ag', 'stuttgart', '107.000', '6.000', '271 ,000'], ['0 4', 'siemens ag', 'berlin , münchen', '74.000', '6.300', '360 ,000'], ['0 5', 'basf se', 'ludwigshafen am rhein', '73.000', '6.600', '111 ,000'], ['0 6', 'bmw ag', 'münchen', '69.000', '4.900', '100 ,000'], ['0 7', 'metro ag', 'düsseldorf', '67.000', '740', '288 ,000'], ['0 8', 'schwarz - gruppe ( lidl / kaufland )', 'neckarsulm', '63.000', 'n / a', '315 ,000'], ['0 9', 'deutsche telekom ag', 'bonn', '59.000', '670', '235 ,000'], ['0 10', 'deutsche post ag', 'bonn', '53.000', '1.300', '471 ,000'], ['-', 'allianz se', 'münchen', '104.000', '2.800', '141 ,000'], ['-', 'deutsche bank ag', 'frankfurt am main', '2.160.000', '4.300', '101 ,000']] |
houston rockets all - time roster | https://en.wikipedia.org/wiki/Houston_Rockets_all-time_roster | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11734041-3.html.csv | count | the number of players of height 7 feet or over is 2 . | {'scope': 'all', 'criterion': 'greater_than_eq', 'value': '7 - 0', 'result': '2', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater_eq', 'args': ['all_rows', 'height in ft', '7 - 0'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose height in ft record is greater than or equal to 7 - 0 .', 'tostr': 'filter_greater_eq { all_rows ; height in ft ; 7 - 0 }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_greater_eq { all_rows ; height in ft ; 7 - 0 } }', 'tointer': 'select the rows whose height in ft record is greater than or equal to 7 - 0 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_greater_eq { all_rows ; height in ft ; 7 - 0 } } ; 2 } = true', 'tointer': 'select the rows whose height in ft record is greater than or equal to 7 - 0 . the number of such rows is 2 .'} | eq { count { filter_greater_eq { all_rows ; height in ft ; 7 - 0 } } ; 2 } = true | select the rows whose height in ft record is greater than or equal to 7 - 0 . the number of such rows is 2 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_greater_eq_0': 0, 'all_rows_4': 4, 'height in ft_5': 5, '7 - 0_6': 6, '2_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_greater_eq_0': 'filter_greater_eq', 'all_rows_4': 'all_rows', 'height in ft_5': 'height in ft', '7 - 0_6': '7 - 0', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_greater_eq_0': [1], 'all_rows_4': [0], 'height in ft_5': [0], '7 - 0_6': [0], '2_7': [2]} | ['player', 'no ( s )', 'height in ft', 'position', 'years for rockets', 'school / club team / country'] | [['caldwell , adrian adrian caldwell', '44', '6 - 8', 'forward', '1989 - 91 , 1994 - 95', 'lamar'], ['carr , antoine antoine carr', '55', '6 - 9', 'forward', '1998 - 99', 'wichita state'], ['carroll , joe barry joe barry carroll', '2', '7 - 1', 'center / forward', '1987 - 88', 'purdue'], ['cassell , sam sam cassell', '10', '6 - 3', 'guard', '1993 - 96', 'florida state'], ['cato , kelvin kelvin cato', '13', '6 - 11', 'center', '1999 - 2004', 'iowa state'], ['chievous , derrick derrick chievous', '3', '6 - 7', 'guard / forward', '1988 - 90', 'missouri'], ['chilcutt , pete pete chilcutt', '32', '6 - 10', 'forward', '1994 - 96', 'north carolina'], ['coleman , ec ec coleman', '12 , 44', '6 - 8', 'forward', '1973 - 74 , 1978 - 79', 'houston baptist'], ['collier , jason jason collier', '52', '7 - 0', 'forward / center', '2000 - 03', 'georgia tech'], ['colson , sean sean colson', '20', '6 - 0', 'guard', '2000 - 01', 'unc - charlotte'], ['conner , lester lester conner', '7', '6 - 4', 'guard', '1987 - 88', 'oregon state'], ['cook , brian brian cook', '43', '6 - 9', 'forward', '2009 - 10', 'illinois'], ['cunningham , dick dick cunningham', '34', '6 - 10', 'center', '1971 - 72', 'murray state'], ['cureton , earl earl cureton', '35', '6 - 9', 'forward / center', '1993 - 94', 'detroit , robert morris'], ['curley , bill bill curley', '15', '6 - 9', 'forward', '1999 - 2000', 'boston college']] |
houston rockets all - time roster | https://en.wikipedia.org/wiki/Houston_Rockets_all-time_roster | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-11734041-15.html.csv | aggregation | all players in the houston rockets all - time roster have an average of 6 - 9 . | {'scope': 'all', 'col': '3', 'type': 'average', 'result': '6 - 9', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'height in ft'], 'result': '6 - 9', 'ind': 0, 'tostr': 'avg { all_rows ; height in ft }'}, '6 - 9'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; height in ft } ; 6 - 9 } = true', 'tointer': 'the average of the height in ft record of all rows is 6 - 9 .'} | round_eq { avg { all_rows ; height in ft } ; 6 - 9 } = true | the average of the height in ft record of all rows is 6 - 9 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'height in ft_4': 4, '6 - 9_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'height in ft_4': 'height in ft', '6 - 9_5': '6 - 9'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'height in ft_4': [0], '6 - 9_5': [1]} | ['player', 'no ( s )', 'height in ft', 'position', 'years for rockets', 'school / club team / country'] | [['padgett , scott scott padgett', '35', '6 - 9', 'forward', '2003 - 05 , 2006 - 07', 'kentucky'], ['patterson , patrick patrick patterson', '54', '6 - 9', 'forward', '2010 - 2013', 'kentucky'], ['paultz , billy billy paultz', '5', '6 - 11', 'center', '1979 - 83', "st john 's"], ['perry , curtis curtis perry', '54', '6 - 7', 'forward', '1970 - 71', 'sw missouri state'], ['petersen , jim jim petersen', '43', '6 - 10', 'forward / center', '1984 - 88', 'minnesota'], ['petruska , richard richard petruska', '3', '6 - 10', 'center', '1993 - 94', 'ucla'], ['piatkowski , eric eric piatkowski', '52', '6 - 7', 'guard', '2003 - 04', 'nebraska'], ['pippen , scottie scottie pippen', '33', '6 - 8', 'forward', '1998 - 99', 'central arkansas'], ['posey , james james posey', '55', '6 - 8', 'forward', '2002 - 03', 'xavier ( ohio )']] |
the magician ( 2006 film ) | https://en.wikipedia.org/wiki/The_Magician_%282006_film%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14674285-1.html.csv | unique | turkey was the only territory that had more than 100 screens showing the 2006 film , the magician . | {'scope': 'all', 'row': '1', 'col': '3', 'col_other': '2', 'criterion': 'greater_than', 'value': '100', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'screens', '100'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose screens record is greater than 100 .', 'tostr': 'filter_greater { all_rows ; screens ; 100 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_greater { all_rows ; screens ; 100 } }', 'tointer': 'select the rows whose screens record is greater than 100 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'screens', '100'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose screens record is greater than 100 .', 'tostr': 'filter_greater { all_rows ; screens ; 100 }'}, 'territory'], 'result': 'turkey', 'ind': 2, 'tostr': 'hop { filter_greater { all_rows ; screens ; 100 } ; territory }'}, 'turkey'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_greater { all_rows ; screens ; 100 } ; territory } ; turkey }', 'tointer': 'the territory record of this unqiue row is turkey .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_greater { all_rows ; screens ; 100 } } ; eq { hop { filter_greater { all_rows ; screens ; 100 } ; territory } ; turkey } } = true', 'tointer': 'select the rows whose screens record is greater than 100 . there is only one such row in the table . the territory record of this unqiue row is turkey .'} | and { only { filter_greater { all_rows ; screens ; 100 } } ; eq { hop { filter_greater { all_rows ; screens ; 100 } ; territory } ; turkey } } = true | select the rows whose screens record is greater than 100 . there is only one such row in the table . the territory record of this unqiue row is turkey . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_greater_0': 0, 'all_rows_6': 6, 'screens_7': 7, '100_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'territory_9': 9, 'turkey_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_greater_0': 'filter_greater', 'all_rows_6': 'all_rows', 'screens_7': 'screens', '100_8': '100', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'territory_9': 'territory', 'turkey_10': 'turkey'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_greater_0': [1, 2], 'all_rows_6': [0], 'screens_7': [0], '100_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'territory_9': [2], 'turkey_10': [3]} | ['date', 'territory', 'screens', 'rank', 'gross'] | [['october 20 , 2006', 'turkey', '378', '1', '1462608'], ['october 25 , 2006', 'belgium', '6', '19', '38916'], ['october 26 , 2006', 'germany', '52', '12', '198149'], ['october 26 , 2006', 'austria', '4', '13', '41780'], ['october 26 , 2006', 'netherlands', '17', '14', '53749'], ['october 27 , 2006', 'united kingdom', '4', '24', '34704']] |
1972 - 73 atlanta flames season | https://en.wikipedia.org/wiki/1972%E2%80%9373_Atlanta_Flames_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14038705-1.html.csv | majority | all of the players drafted by the atlanta flames were from canada . | {'scope': 'all', 'col': '4', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'canada', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'nationality', 'canada'], 'result': True, 'ind': 0, 'tointer': 'for the nationality records of all rows , all of them fuzzily match to canada .', 'tostr': 'all_eq { all_rows ; nationality ; canada } = true'} | all_eq { all_rows ; nationality ; canada } = true | for the nationality records of all rows , all of them fuzzily match to canada . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'nationality_3': 3, 'canada_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'nationality_3': 'nationality', 'canada_4': 'canada'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'nationality_3': [0], 'canada_4': [0]} | ['round', 'pick', 'player', 'nationality', 'college / junior / club team'] | [['1', '2', 'jacques richard', 'canada', 'quebec remparts ( qmjhl )'], ['2', '18', 'dwight bialowas', 'canada', 'regina pats ( wcjhl )'], ['3', '34', 'jean lemieux', 'canada', 'sherbrooke castors ( qmjhl )'], ['4', '50', 'don martineau', 'canada', 'new westminster royals ( wcjhl )'], ['5', '78', 'john martin', 'canada', 'shawinigan bruins ( qmjhl )'], ['6', '82', 'frank blum', 'canada', 'sarnia sting ( sojhl )'], ['7', '98', 'scott smith', 'canada', 'regina pats ( wcjhl )'], ['8', '114', 'dave murphy', 'canada', 'hamilton red wings ( oha )'], ['9', '130', 'pierre roy', 'canada', 'quebec remparts ( qmjhl )']] |
statistics relating to enlargement of the european union | https://en.wikipedia.org/wiki/Statistics_relating_to_enlargement_of_the_European_Union | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1307842-7.html.csv | comparative | malta has a higher gdp per capita than the czech republic does . | {'row_1': '7', 'row_2': '2', 'col': '5', 'col_other': '1', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'member countries', 'malta'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose member countries record fuzzily matches to malta .', 'tostr': 'filter_eq { all_rows ; member countries ; malta }'}, 'gdp per capita ( us )'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; member countries ; malta } ; gdp per capita ( us ) }', 'tointer': 'select the rows whose member countries record fuzzily matches to malta . take the gdp per capita ( us ) record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'member countries', 'czech republic'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose member countries record fuzzily matches to czech republic .', 'tostr': 'filter_eq { all_rows ; member countries ; czech republic }'}, 'gdp per capita ( us )'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; member countries ; czech republic } ; gdp per capita ( us ) }', 'tointer': 'select the rows whose member countries record fuzzily matches to czech republic . take the gdp per capita ( us ) record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; member countries ; malta } ; gdp per capita ( us ) } ; hop { filter_eq { all_rows ; member countries ; czech republic } ; gdp per capita ( us ) } } = true', 'tointer': 'select the rows whose member countries record fuzzily matches to malta . take the gdp per capita ( us ) record of this row . select the rows whose member countries record fuzzily matches to czech republic . take the gdp per capita ( us ) record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; member countries ; malta } ; gdp per capita ( us ) } ; hop { filter_eq { all_rows ; member countries ; czech republic } ; gdp per capita ( us ) } } = true | select the rows whose member countries record fuzzily matches to malta . take the gdp per capita ( us ) record of this row . select the rows whose member countries record fuzzily matches to czech republic . take the gdp per capita ( us ) 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, 'member countries_7': 7, 'malta_8': 8, 'gdp per capita (us)_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'member countries_11': 11, 'czech republic_12': 12, 'gdp per capita (us)_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', 'member countries_7': 'member countries', 'malta_8': 'malta', 'gdp per capita (us)_9': 'gdp per capita ( us )', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'member countries_11': 'member countries', 'czech republic_12': 'czech republic', 'gdp per capita (us)_13': 'gdp per capita ( us )'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'member countries_7': [0], 'malta_8': [0], 'gdp per capita (us)_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'member countries_11': [1], 'czech republic_12': [1], 'gdp per capita (us)_13': [3]} | ['member countries', 'population', 'area ( km square )', 'gdp ( billion us )', 'gdp per capita ( us )'] | [['cyprus', '775927', '9250', '11.681', '15054'], ['czech republic', '10246178', '78866', '105.248', '10272'], ['estonia', '1341664', '45226', '22.384', '16684'], ['hungary', '10032375', '93030', '102183', '10185'], ['latvia', '2306306', '64589', '24.826', '10764'], ['lithuania', '3607899', '65200', '31.971', '8861'], ['malta', '396851', '316', '5.097', '12843'], ['poland', '38580445', '311904', '316.438', '8202'], ['slovakia', '5423567', '49036', '42.800', '7810'], ['slovenia', '2011473', '20273', '29.633', '14732'], ['accession countries', '74722685', '737690', '685.123', '9169'], ['existing members ( 2004 )', '381781620', '3367154', '7711.871', '20200']] |
united states house of representatives elections , 1952 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1952 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1342149-24.html.csv | superlative | john e rankin was the first incumbent to be first elected before the 1952 united states house of representatives elections . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '2', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '2', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmin', 'args': ['all_rows', 'first elected'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; first elected }'}, 'incumbent'], 'result': 'john e rankin', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; first elected } ; incumbent }'}, 'john e rankin'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmin { all_rows ; first elected } ; incumbent } ; john e rankin } = true', 'tointer': 'select the row whose first elected record of all rows is minimum . the incumbent record of this row is john e rankin .'} | eq { hop { argmin { all_rows ; first elected } ; incumbent } ; john e rankin } = true | select the row whose first elected record of all rows is minimum . the incumbent record of this row is john e rankin . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'first elected_5': 5, 'incumbent_6': 6, 'john e rankin_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'first elected_5': 'first elected', 'incumbent_6': 'incumbent', 'john e rankin_7': 'john e rankin'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'first elected_5': [0], 'incumbent_6': [1], 'john e rankin_7': [2]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['mississippi 1', 'thomas abernethy redistricted from 4th', 'democratic', '1942', 're - elected', 'thomas abernethy ( d ) unopposed'], ['mississippi 1', 'john e rankin', 'democratic', '1920', 'lost renomination democratic loss', 'thomas abernethy ( d ) unopposed'], ['mississippi 2', 'jamie l whitten', 'democratic', '1941', 're - elected', 'jamie l whitten ( d ) unopposed'], ['mississippi 3', 'frank e smith', 'democratic', '1950', 're - elected', 'frank e smith ( d ) 87.2 % paul clark ( r ) 12.8 %'], ['mississippi 4', 'john bell williams redistricted from 7th', 'democratic', '1946', 're - elected', 'john bell williams ( d ) unopposed']] |
wpar | https://en.wikipedia.org/wiki/WPAR | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12840409-2.html.csv | superlative | the wpar radio channel with the call sign w246bz operates with the highest erp wattage . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '3', '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', 'erp w'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; erp w }'}, 'call sign'], 'result': 'w246bz', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; erp w } ; call sign }'}, 'w246bz'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; erp w } ; call sign } ; w246bz } = true', 'tointer': 'select the row whose erp w record of all rows is maximum . the call sign record of this row is w246bz .'} | eq { hop { argmax { all_rows ; erp w } ; call sign } ; w246bz } = true | select the row whose erp w record of all rows is maximum . the call sign record of this row is w246bz . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'erp w_5': 5, 'call sign_6': 6, 'w246bz_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'erp w_5': 'erp w', 'call sign_6': 'call sign', 'w246bz_7': 'w246bz'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'erp w_5': [0], 'call sign_6': [1], 'w246bz_7': [2]} | ['call sign', 'frequency mhz', 'city of license', 'erp w', 'class', 'fcc info'] | [['w294aj', '106.7', 'charlottesville , virginia', '21', 'd', 'fcc'], ['w236ad', '95.1', 'lawrenceville , virginia', '25', 'd', 'fcc'], ['w246bz', '97.1', 'crewe , virginia', '38', 'd', 'fcc'], ['w254ah', '98.7', 'farmville , virginia', '27', 'd', 'fcc'], ['w272cc', '102.3', 'smithfield , virginia', '10', 'd', 'fcc'], ['w273aa', '102.5', 'blacksburg , virginia', '10', 'd', 'fcc'], ['w274ab', '102.7', 'petersburg , virginia', '30', 'd', 'fcc'], ['w291aj', '106.1', 'waverly , virginia', '27', 'd', 'fcc'], ['w292cu', '106.3', 'christiansburg , virginia', '10', 'd', 'fcc'], ['w295ai', '106.9', 'marion , virginia', '10', 'd', 'fcc']] |
list of most expensive ukrainian football transfers | https://en.wikipedia.org/wiki/List_of_most_expensive_Ukrainian_football_transfers | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12601456-1.html.csv | ordinal | matuzalém ranks 3rd in the most expensive ukrainian football transfers . | {'row': '3', 'col': '1', 'order': '3', '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', 'rank', '3'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; rank ; 3 }'}, 'name'], 'result': 'matuzalém', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; rank ; 3 } ; name }'}, 'matuzalém'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; rank ; 3 } ; name } ; matuzalém } = true', 'tointer': 'select the row whose rank record of all rows is 3rd minimum . the name record of this row is matuzalém .'} | eq { hop { nth_argmin { all_rows ; rank ; 3 } ; name } ; matuzalém } = true | select the row whose rank record of all rows is 3rd minimum . the name record of this row is matuzalém . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'rank_5': 5, '3_6': 6, 'name_7': 7, 'matuzalém_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', '3_6': '3', 'name_7': 'name', 'matuzalém_8': 'matuzalém'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'rank_5': [0], '3_6': [0], 'name_7': [1], 'matuzalém_8': [2]} | ['rank', 'year', 'name', 'moving from', 'moving to'] | [['1', '2007', 'nery castillo', 'olympiacos', 'shakhtar donetsk'], ['2', '2007', 'willian', 'corinthians', 'shakhtar donetsk'], ['3', '2004', 'matuzalém', 'brescia', 'shakhtar donetsk'], ['4', '2007', 'ilsinho', 'são paulo', 'shakhtar donetsk'], ['5', '2008', 'marcelo moreno', 'cruzeiro', 'shakhtar donetsk'], ['6', '2007', 'cristiano lucarelli', 'livorno', 'shakhtar donetsk'], ['7', '2005', 'fernandinho', 'atlético paranaense', 'shakhtar donetsk'], ['8', '2005', 'elano', 'santos', 'shakhtar donetsk'], ['9', '2007', 'pape diakhaté', 'nancy', 'dynamo kyiv'], ['10', '2007', 'ismaël bangoura', 'le mans', 'dynamo kyiv']] |
1960 - 61 segunda división | https://en.wikipedia.org/wiki/1960%E2%80%9361_Segunda_Divisi%C3%B3n | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17715861-2.html.csv | count | in the 1960 - 61 segunda división , when there were at least 40 goals against , there were 6 times when there were at least 40 goals for . | {'scope': 'subset', 'criterion': 'greater_than_eq', 'value': '40', 'result': '6', 'col': '8', 'subset': {'col': '9', 'criterion': 'greater_than_eq', 'value': '40'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater_eq', 'args': [{'func': 'filter_greater_eq', 'args': ['all_rows', 'goals against', '40'], 'result': None, 'ind': 0, 'tostr': 'filter_greater_eq { all_rows ; goals against ; 40 }', 'tointer': 'select the rows whose goals against record is greater than or equal to 40 .'}, 'goals for', '40'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose goals against record is greater than or equal to 40 . among these rows , select the rows whose goals for record is greater than or equal to 40 .', 'tostr': 'filter_greater_eq { filter_greater_eq { all_rows ; goals against ; 40 } ; goals for ; 40 }'}], 'result': '6', 'ind': 2, 'tostr': 'count { filter_greater_eq { filter_greater_eq { all_rows ; goals against ; 40 } ; goals for ; 40 } }', 'tointer': 'select the rows whose goals against record is greater than or equal to 40 . among these rows , select the rows whose goals for record is greater than or equal to 40 . the number of such rows is 6 .'}, '6'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_greater_eq { filter_greater_eq { all_rows ; goals against ; 40 } ; goals for ; 40 } } ; 6 } = true', 'tointer': 'select the rows whose goals against record is greater than or equal to 40 . among these rows , select the rows whose goals for record is greater than or equal to 40 . the number of such rows is 6 .'} | eq { count { filter_greater_eq { filter_greater_eq { all_rows ; goals against ; 40 } ; goals for ; 40 } } ; 6 } = true | select the rows whose goals against record is greater than or equal to 40 . among these rows , select the rows whose goals for record is greater than or equal to 40 . the number of such rows is 6 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_greater_eq_1': 1, 'filter_greater_eq_0': 0, 'all_rows_5': 5, 'goals against_6': 6, '40_7': 7, 'goals for_8': 8, '40_9': 9, '6_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_greater_eq_1': 'filter_greater_eq', 'filter_greater_eq_0': 'filter_greater_eq', 'all_rows_5': 'all_rows', 'goals against_6': 'goals against', '40_7': '40', 'goals for_8': 'goals for', '40_9': '40', '6_10': '6'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_greater_eq_1': [2], 'filter_greater_eq_0': [1], 'all_rows_5': [0], 'goals against_6': [0], '40_7': [0], 'goals for_8': [1], '40_9': [1], '6_10': [3]} | ['position', 'club', 'played', 'points', 'wins', 'draws', 'losses', 'goals for', 'goals against', 'goal difference'] | [['1', 'ca osasuna', '30', '46', '21', '4', '5', '83', '25', '+ 58'], ['2', 'rc celta de vigo', '30', '40', '17', '6', '7', '56', '30', '+ 26'], ['3', 'deportivo la coruña', '30', '36', '15', '6', '9', '68', '47', '+ 21'], ['4', 'cd orense', '30', '36', '14', '8', '8', '45', '36', '+ 9'], ['5', 'pontevedra cf', '30', '31', '11', '9', '10', '39', '40', '- 1'], ['6', 'cd sabadell cf', '30', '31', '11', '9', '10', '30', '40', '- 10'], ['7', 'cultural leonesa', '30', '30', '11', '8', '11', '39', '42', '- 3'], ['8', 'cd basconia', '30', '29', '14', '1', '15', '41', '57', '- 16'], ['9', 'san sebastián cf', '30', '29', '11', '7', '12', '51', '50', '+ 1'], ['10', 'ud salamanca', '30', '29', '11', '7', '12', '42', '36', '+ 6'], ['11', 'sd indauchu', '30', '27', '12', '3', '15', '46', '59', '- 13'], ['12', 'cd condal 1', '30', '26', '8', '10', '12', '44', '49', '- 5'], ['13', 'real gijón', '30', '25', '10', '5', '15', '41', '53', '- 12'], ['14', 'club sestao', '30', '24', '8', '8', '14', '35', '51', '- 16'], ['15', 'baracaldo ah', '30', '22', '7', '8', '15', '33', '51', '- 18'], ['16', 'cd tarrasa', '30', '19', '5', '9', '16', '33', '60', '- 27']] |
1966 british grand prix | https://en.wikipedia.org/wiki/1966_British_Grand_Prix | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1122355-1.html.csv | count | three drivers in the 1966 british grand prix dropped out due to engine problems . | {'scope': 'all', 'criterion': 'equal', 'value': 'engine', 'result': '3', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'time / retired', 'engine'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose time / retired record fuzzily matches to engine .', 'tostr': 'filter_eq { all_rows ; time / retired ; engine }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; time / retired ; engine } }', 'tointer': 'select the rows whose time / retired record fuzzily matches to engine . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; time / retired ; engine } } ; 3 } = true', 'tointer': 'select the rows whose time / retired record fuzzily matches to engine . the number of such rows is 3 .'} | eq { count { filter_eq { all_rows ; time / retired ; engine } } ; 3 } = true | select the rows whose time / retired record fuzzily matches to engine . 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, 'time / retired_5': 5, 'engine_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', 'time / retired_5': 'time / retired', 'engine_6': 'engine', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'time / retired_5': [0], 'engine_6': [0], '3_7': [2]} | ['driver', 'constructor', 'laps', 'time / retired', 'grid'] | [['jack brabham', 'brabham - repco', '80', '2:13:13.4', '1'], ['denny hulme', 'brabham - repco', '80', '+ 9.6', '2'], ['graham hill', 'brm', '79', '+ 1 lap', '4'], ['jim clark', 'lotus - climax', '79', '+ 1 lap', '5'], ['jochen rindt', 'cooper - maserati', '79', '+ 1 lap', '7'], ['bruce mclaren', 'mclaren - serenissima', '78', '+ 2 laps', '13'], ['chris irwin', 'brabham - climax', '78', '+ 2 laps', '12'], ['john taylor', 'brabham - brm', '76', '+ 4 laps', '16'], ['bob bondurant', 'brm', '76', '+ 4 laps', '14'], ['guy ligier', 'cooper - maserati', '75', '+ 5 laps', '17'], ['chris lawrence', 'cooper - ferrari', '73', '+ 7 laps', '19'], ['bob anderson', 'brabham - climax', '70', 'not classified', '10'], ['jo siffert', 'cooper - maserati', '70', 'not classified', '11'], ['john surtees', 'cooper - maserati', '67', 'transmission', '6'], ['jo bonnier', 'brabham - climax', '42', 'clutch', '15'], ['peter arundell', 'lotus - brm', '32', 'gearbox', '20'], ['jackie stewart', 'brm', '17', 'engine', '8'], ['mike spence', 'lotus - brm', '15', 'oil leak', '9'], ['dan gurney', 'eagle - climax', '9', 'engine', '3'], ['trevor taylor', 'shannon - climax', '0', 'engine', '18']] |
2002 grand national | https://en.wikipedia.org/wiki/2002_Grand_National | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-25429986-1.html.csv | ordinal | richard johnson got the highest position in those of sp 10/1 in the 2002 grand national . | {'scope': 'subset', 'row': '2', 'col': '1', 'order': '1', 'col_other': '4', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'subset': {'col': '7', 'criterion': 'equal', 'value': '10 / 1'}} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'sp', '10 / 1'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; sp ; 10 / 1 }', 'tointer': 'select the rows whose sp record fuzzily matches to 10 / 1 .'}, 'position', '1'], 'result': None, 'ind': 1, 'tostr': 'nth_argmin { filter_eq { all_rows ; sp ; 10 / 1 } ; position ; 1 }'}, 'jockey'], 'result': 'richard johnson', 'ind': 2, 'tostr': 'hop { nth_argmin { filter_eq { all_rows ; sp ; 10 / 1 } ; position ; 1 } ; jockey }'}, 'richard johnson'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { nth_argmin { filter_eq { all_rows ; sp ; 10 / 1 } ; position ; 1 } ; jockey } ; richard johnson } = true', 'tointer': 'select the rows whose sp record fuzzily matches to 10 / 1 . select the row whose position record of these rows is 1st minimum . the jockey record of this row is richard johnson .'} | eq { hop { nth_argmin { filter_eq { all_rows ; sp ; 10 / 1 } ; position ; 1 } ; jockey } ; richard johnson } = true | select the rows whose sp record fuzzily matches to 10 / 1 . select the row whose position record of these rows is 1st minimum . the jockey record of this row is richard johnson . | 4 | 4 | {'str_eq_3': 3, 'result_4': 4, 'str_hop_2': 2, 'nth_argmin_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'sp_6': 6, '10 / 1_7': 7, 'position_8': 8, '1_9': 9, 'jockey_10': 10, 'richard johnson_11': 11} | {'str_eq_3': 'str_eq', 'result_4': 'true', 'str_hop_2': 'str_hop', 'nth_argmin_1': 'nth_argmin', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'sp_6': 'sp', '10 / 1_7': '10 / 1', 'position_8': 'position', '1_9': '1', 'jockey_10': 'jockey', 'richard johnson_11': 'richard johnson'} | {'str_eq_3': [4], 'result_4': [], 'str_hop_2': [3], 'nth_argmin_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'sp_6': [0], '10 / 1_7': [0], 'position_8': [1], '1_9': [1], 'jockey_10': [2], 'richard johnson_11': [3]} | ['position', 'number', 'horse', 'jockey', 'age', 'handicap', 'sp', 'distance'] | [['1st', '21', 'bindaree', 'jim culloty', '8', '10 - 4', '20 / 1', 'won by 1 ¾ lengths'], ['2nd', '4', "what 's up boys", 'richard johnson', '8', '11 - 6', '10 / 1', '27 lengths'], ['3rd', '16', 'blowing wind', 'tony mccoy', '9', '10 - 6', '10 / 1', '9 lengths'], ['4th', '3', 'kingsmark', 'ruby walsh', '9', '11 - 9', '16 / 1', '17 lengths'], ['5th', '40', 'supreme charm', 'robert thornton', '10', '10 - 0', '28 / 1', '3 ½ lengths'], ['6th', '22', 'celibate', 'noel fehily', '11', '10 - 3', '66 / 1', '3 ½ lengths'], ['7th', '13', "you 're agoodun", 'johnny kavanagh', '10', '10 - 8', '50 / 1', '18 lengths'], ['8th', '14', 'royal predica', 'jimmy mccarthy', '8', '10 - 8', '80 / 1', '28 lengths'], ['9th', '12', 'streamstown', 'john mcnamara', '8', '10 - 8', '40 / 1', '13 lengths'], ['10th', '34', 'birkdale', 'jason maguire', '11', '10 - 2', '50 / 1', 'a distance']] |
asymmetric digital subscriber line | https://en.wikipedia.org/wiki/Asymmetric_digital_subscriber_line | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18934536-1.html.csv | aggregation | the average downstream rate of the asymmetric digital subscriber line is 14 mbit / s. | {'scope': 'all', 'col': '4', 'type': 'average', 'result': '14', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'downstream rate'], 'result': '14', 'ind': 0, 'tostr': 'avg { all_rows ; downstream rate }'}, '14'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; downstream rate } ; 14 } = true', 'tointer': 'the average of the downstream rate record of all rows is 14 .'} | round_eq { avg { all_rows ; downstream rate } ; 14 } = true | the average of the downstream rate record of all rows is 14 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'downstream rate_4': 4, '14_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'downstream rate_4': 'downstream rate', '14_5': '14'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'downstream rate_4': [0], '14_5': [1]} | ['version', 'standard name', 'common name', 'downstream rate', 'upstream rate'] | [['adsl', 'ansi t1 .413 - 1998 issue 2', 'adsl', '08.0 8.0 mbit / s', '1.0 mbit / s'], ['adsl', 'itu g992 .1', 'adsl ( gdmt )', '8.0 mbit / s', '1.3 mbit / s'], ['adsl', 'itu g992 .1 annex a', 'adsl over pots', '12.0 mbit / s', '1.3 mbit / s'], ['adsl', 'itu g992 .1 annex b', 'adsl over isdn', '12.0 mbit / s', '1.8 mbit / s'], ['adsl', 'itu g992 .2', 'adsl lite ( glite )', '01.5 1.5 mbit / s', '0.5 mbit / s'], ['adsl2', 'itu g992 .3', 'adsl2', '12.0 mbit / s', '1.3 mbit / s'], ['adsl2', 'itu g992 .3 annex j', 'adsl2', '12.0 mbit / s', '3.5 mbit / s'], ['adsl2', 'itu g992 .3 annex l', 're - adsl2', '05.0 5.0 mbit / s', '0.8 mbit / s'], ['adsl2', 'itu g992 .4', 'splitterless adsl2', '01.5 1.5 mbit / s', '0.5 mbit / s'], ['adsl2 +', 'itu g992 .5', 'adsl2 +', '20.0 mbit / s', '1.1 mbit / s'], ['adsl2 +', 'itu g992 .5 annex m', 'adsl2 + m', '24.0 mbit / s', '3.3 mbit / s'], ['adsl2 + +', '( up to 3.75 mhz )', 'adsl4', '52.0 mbit / s', '5.0 mbit / s']] |
list of nurse jackie episodes | https://en.wikipedia.org/wiki/List_of_Nurse_Jackie_episodes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-26961951-4.html.csv | count | 2 episodes of the nurse jackie drama were directed by steve buscemi . | {'scope': 'all', 'criterion': 'equal', 'value': 'steve buscemi', 'result': '2', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'directed by', 'steve buscemi'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose directed by record fuzzily matches to steve buscemi .', 'tostr': 'filter_eq { all_rows ; directed by ; steve buscemi }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; directed by ; steve buscemi } }', 'tointer': 'select the rows whose directed by record fuzzily matches to steve buscemi . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; directed by ; steve buscemi } } ; 2 } = true', 'tointer': 'select the rows whose directed by record fuzzily matches to steve buscemi . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; directed by ; steve buscemi } } ; 2 } = true | select the rows whose directed by record fuzzily matches to steve buscemi . 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, 'directed by_5': 5, 'steve buscemi_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', 'directed by_5': 'directed by', 'steve buscemi_6': 'steve buscemi', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'directed by_5': [0], 'steve buscemi_6': [0], '2_7': [2]} | ['no in series', 'no in season', 'title', 'directed by', 'written by', 'original air date', 'us viewers ( million )'] | [['25', '1', 'game on', 'steve buscemi', 'liz brixius & linda wallem', 'march 28 , 2011', '0.61'], ['26', '2', 'enough rope', 'steve buscemi', 'liz brixius', 'april 4 , 2011', '0.49'], ['27', '3', 'play me', 'michael lehmann', 'linda wallem', 'april 11 , 2011', '0.57'], ['28', '4', 'mitten', 'michael lehmann', 'liz flahive', 'april 18 , 2011', '0.60'], ['29', '5', 'rat falls', 'tristram shapeero', 'alison mcdonald', 'april 25 , 2011', '0.65'], ['30', '6', 'when the saints go', 'tristram shapeero', 'liz brixius', 'may 2 , 2011', '0.53'], ['31', '7', 'orchids and salami', 'bob balaban', 'ellen fairey', 'may 9 , 2011', '0.47'], ['32', '8', 'the astonishing', 'bob balaban', 'rajiv joseph', 'may 16 , 2011', '0.43'], ['33', '9', 'have you met ms jones', 'daisy von scherler mayer', 'liz brixius & wyndham lewis', 'may 23 , 2011', '0.60'], ['34', '10', 'fuck the lemurs', 'daisy von scherler mayer', 'liz brixius', 'june 6 , 2011', '0.56'], ['35', '11', 'batting practice', 'linda wallem', 'liz flahive', 'june 13 , 2011', '0.58']] |
1946 vfl season | https://en.wikipedia.org/wiki/1946_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10809368-5.html.csv | unique | in the 1946 vfl season , the only time the venue was punt road oval was when melbourne was the home team . | {'scope': 'all', 'row': '6', 'col': '5', 'col_other': '1', 'criterion': 'equal', 'value': 'punt road oval', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'venue', 'punt road oval'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose venue record fuzzily matches to punt road oval .', 'tostr': 'filter_eq { all_rows ; venue ; punt road oval }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; venue ; punt road oval } }', 'tointer': 'select the rows whose venue record fuzzily matches to punt road oval . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'venue', 'punt road oval'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose venue record fuzzily matches to punt road oval .', 'tostr': 'filter_eq { all_rows ; venue ; punt road oval }'}, 'home team'], 'result': 'melbourne', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; venue ; punt road oval } ; home team }'}, 'melbourne'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; venue ; punt road oval } ; home team } ; melbourne }', 'tointer': 'the home team record of this unqiue row is melbourne .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; venue ; punt road oval } } ; eq { hop { filter_eq { all_rows ; venue ; punt road oval } ; home team } ; melbourne } } = true', 'tointer': 'select the rows whose venue record fuzzily matches to punt road oval . there is only one such row in the table . the home team record of this unqiue row is melbourne .'} | and { only { filter_eq { all_rows ; venue ; punt road oval } } ; eq { hop { filter_eq { all_rows ; venue ; punt road oval } ; home team } ; melbourne } } = true | select the rows whose venue record fuzzily matches to punt road oval . there is only one such row in the table . the home team record of this unqiue row is melbourne . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'venue_7': 7, 'punt road oval_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'home team_9': 9, 'melbourne_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'venue_7': 'venue', 'punt road oval_8': 'punt road oval', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'home team_9': 'home team', 'melbourne_10': 'melbourne'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'venue_7': [0], 'punt road oval_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'home team_9': [2], 'melbourne_10': [3]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['geelong', '11.8 ( 74 )', 'st kilda', '13.17 ( 95 )', 'kardinia park', '9000', '18 may 1946'], ['essendon', '11.13 ( 79 )', 'fitzroy', '4.15 ( 39 )', 'windy hill', '17000', '18 may 1946'], ['collingwood', '2.16 ( 28 )', 'richmond', '14.10 ( 94 )', 'victoria park', '24000', '18 may 1946'], ['carlton', '11.15 ( 81 )', 'north melbourne', '9.11 ( 65 )', 'princes park', '19000', '18 may 1946'], ['south melbourne', '11.21 ( 87 )', 'hawthorn', '6.17 ( 53 )', 'junction oval', '10000', '18 may 1946'], ['melbourne', '12.13 ( 85 )', 'footscray', '22.14 ( 146 )', 'punt road oval', '18000', '18 may 1946']] |
cyrille diabaté | https://en.wikipedia.org/wiki/Cyrille_Diabat%C3%A9 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18722380-1.html.csv | majority | the majority of cyrille diabaté 's fights ended via the decision method . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'decision', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'method', 'decision'], 'result': True, 'ind': 0, 'tointer': 'for the method records of all rows , most of them fuzzily match to decision .', 'tostr': 'most_eq { all_rows ; method ; decision } = true'} | most_eq { all_rows ; method ; decision } = true | for the method records of all rows , most of them fuzzily match to decision . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'method_3': 3, 'decision_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'method_3': 'method', 'decision_4': 'decision'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'method_3': [0], 'decision_4': [0]} | ['result', 'opponent', 'method', 'event', 'round', 'location'] | [['win', 'michael bisping', 'decision ( unanimous )', 'cwfc : strike force 1', '4', 'coventry , west midlands , england'], ['loss', 'aleksandr pitchkounov', 'decision ( unanimous )', 'ichigeki paris 2005', '5', 'paris , france'], ['loss', 'alexey ignashov', 'decision', 'mt one', '5', 'saint - pierre , réunion'], ['loss', 'petar majstorović', 'decision ( unanimous )', 'k - 1 spain grand prix 2003 in barcelona', '3', 'barcelona , spain'], ['win', 'damián garcía', 'ko', 'k - 1 spain grand prix 2003 in barcelona', '1', 'barcelona , spain'], ['win', 'lee hasdell', 'tko ( doctor stoppage )', 'shoot boxing : s volume 1', '4', 'tokyo , japan'], ['win', 'rick roufus', 'tko ( doctor stoppage )', 'iska championship', '3', 'las vegas , nevada , united states']] |
looney tunes and merrie melodies filmography ( 1950 - 59 ) | https://en.wikipedia.org/wiki/Looney_Tunes_and_Merrie_Melodies_filmography_%281950%E2%80%9359%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18792948-9.html.csv | count | in 1958 , chuck jones directed 7 looney tunes or merrie melodies movies . | {'scope': 'all', 'criterion': 'equal', 'value': 'chuck jones', 'result': '7', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'director', 'chuck jones'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose director record fuzzily matches to chuck jones .', 'tostr': 'filter_eq { all_rows ; director ; chuck jones }'}], 'result': '7', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; director ; chuck jones } }', 'tointer': 'select the rows whose director record fuzzily matches to chuck jones . the number of such rows is 7 .'}, '7'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; director ; chuck jones } } ; 7 } = true', 'tointer': 'select the rows whose director record fuzzily matches to chuck jones . the number of such rows is 7 .'} | eq { count { filter_eq { all_rows ; director ; chuck jones } } ; 7 } = true | select the rows whose director record fuzzily matches to chuck jones . the number of such rows is 7 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'director_5': 5, 'chuck jones_6': 6, '7_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'director_5': 'director', 'chuck jones_6': 'chuck jones', '7_7': '7'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'director_5': [0], 'chuck jones_6': [0], '7_7': [2]} | ['title', 'series', 'director', 'production number', 'release date'] | [["do n't axe me", 'mm', 'robert mckimson', '1469', '1958 - 01 - 04'], ['tortilla flaps', 'lt', 'robert mckimson', '1449', '1958 - 01 - 18'], ['hare - less wolf', 'mm', 'friz freleng', '1478', '1958 - 02 - 01'], ['a pizza tweety pie', 'lt', 'friz freleng', '1479', '1958 - 02 - 22'], ['robin hood daffy', 'mm', 'chuck jones', '1470', '1958 - 03 - 08'], ['hare - way to the stars', 'lt', 'chuck jones', '1464', '1958 - 03 - 29'], ['whoa , be - gone !', 'mm', 'chuck jones', '1477', '1958 - 04 - 12'], ['a waggily tale', 'lt', 'friz freleng', '1486', '1958 - 04 - 26'], ['feather bluster', 'mm', 'robert mckimson', '1476', '1958 - 05 - 10'], ['now hare this', 'lt', 'robert mckimson', '1481', '1958 - 05 - 31'], ['to itch his own', 'mm', 'chuck jones', '1485', '1958 - 06 - 28'], ['dog tales', 'lt', 'robert mckimson', '1484', '1958 - 07 - 26'], ['knighty knight bugs', 'lt', 'friz freleng', '1483', '1958 - 08 - 23'], ['weasel while you work', 'mm', 'robert mckimson', '1489', '1958 - 09 - 06'], ['a bird in a bonnet', 'mm', 'friz freleng', '1490', '1958 - 09 - 27'], ['hook , line and stinker', 'lt', 'chuck jones', '1487', '1958 - 10 - 11'], ['pre - hysterical hare', 'lt', 'robert mckimson', '1491', '1958 - 11 - 01'], ['gopher broke', 'lt', 'robert mckimson', '1497', '1958 - 11 - 15'], ['hip hip - hurry !', 'mm', 'chuck jones', '1515', '1958 - 12 - 06'], ['cat feud', 'mm', 'chuck jones', '1474', '1958 - 12 - 20']] |
colin morgan | https://en.wikipedia.org/wiki/Colin_Morgan | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17973650-5.html.csv | count | colin morgan was nominated for outstanding actor three times . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'outstanding actor', 'result': '3', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'category', 'outstanding actor'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose category record fuzzily matches to outstanding actor .', 'tostr': 'filter_eq { all_rows ; category ; outstanding actor }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; category ; outstanding actor } }', 'tointer': 'select the rows whose category record fuzzily matches to outstanding actor . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; category ; outstanding actor } } ; 3 } = true', 'tointer': 'select the rows whose category record fuzzily matches to outstanding actor . the number of such rows is 3 .'} | eq { count { filter_eq { all_rows ; category ; outstanding actor } } ; 3 } = true | select the rows whose category record fuzzily matches to outstanding actor . 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, 'category_5': 5, 'outstanding actor_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', 'category_5': 'category', 'outstanding actor_6': 'outstanding actor', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'category_5': [0], 'outstanding actor_6': [0], '3_7': [2]} | ['year', 'award', 'category', 'role', 'result'] | [['2008', 'variety club showbiz awards', 'outstanding newcomer', 'merlin in merlin', 'won'], ['2009', 'monte carlo tv festival awards', 'outstanding actor ( drama )', 'merlin in merlin', 'nominated'], ['2010', 'monte carlo tv festival awards', 'outstanding actor ( drama )', 'merlin in merlin', 'nominated'], ['2011', 'monte carlo tv festival awards', 'outstanding actor ( drama )', 'merlin in merlin', 'nominated'], ['2012', 'virgin media tv awards', 'best actor', 'merlin in merlin', 'won'], ['2013', 'national television award', 'drama performance : male', 'merlin in merlin', 'won']] |
list of records in the national youth competition ( rugby league ) | https://en.wikipedia.org/wiki/List_of_records_in_the_National_Youth_Competition_%28rugby_league%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16802194-3.html.csv | count | two separate games ended with a total score of 24 . | {'scope': 'all', 'criterion': 'equal', 'value': '24', 'result': '2', 'col': '1', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'total', '24'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose total record is equal to 24 .', 'tostr': 'filter_eq { all_rows ; total ; 24 }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; total ; 24 } }', 'tointer': 'select the rows whose total record is equal to 24 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; total ; 24 } } ; 2 } = true', 'tointer': 'select the rows whose total record is equal to 24 . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; total ; 24 } } ; 2 } = true | select the rows whose total record is equal to 24 . 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, 'total_5': 5, '24_6': 6, '2_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'total_5': 'total', '24_6': '24', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'total_5': [0], '24_6': [0], '2_7': [2]} | ['total', 'score', 'winning team', 'losing team', 'venue', 'date'] | [['10', '6 - 4', 'st george illawarra dragons', 'cronulla sharks', 'anz stadium', '5 april 2008 ( round 4 )'], ['17', '9 - 8', 'cronulla sharks', 'manly sea eagles', 'toyota park', '12 july 2008 ( round 18 )'], ['19', '19 - 0', 'new zealand warriors', 'st george illawarra dragons', 'mt smart stadium', '6 june 2010 ( round 13 )'], ['24', '14 - 10', 'sydney roosters', 'south sydney rabbitohs', 'anz stadium', '14 march 2008 ( round 1 )'], ['24', '14 - 10', 'north queensland cowboys', 'melbourne storm', 'olympic park', '21 june 2008 ( round 15 )']] |
brecht wallis | https://en.wikipedia.org/wiki/Brecht_Wallis | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11286695-1.html.csv | unique | the fight between brecht wallis and cătălin zmărăndescu is the only fight that ended in a draw result . | {'scope': 'all', 'row': '12', 'col': '2', 'col_other': '3', 'criterion': 'equal', 'value': 'draw', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'result', 'draw'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose result record fuzzily matches to draw .', 'tostr': 'filter_eq { all_rows ; result ; draw }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; result ; draw } }', 'tointer': 'select the rows whose result record fuzzily matches to draw . 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', 'draw'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose result record fuzzily matches to draw .', 'tostr': 'filter_eq { all_rows ; result ; draw }'}, 'opponent'], 'result': 'cătălin zmărăndescu', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; result ; draw } ; opponent }'}, 'cătălin zmărăndescu'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; result ; draw } ; opponent } ; cătălin zmărăndescu }', 'tointer': 'the opponent record of this unqiue row is cătălin zmărăndescu .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; result ; draw } } ; eq { hop { filter_eq { all_rows ; result ; draw } ; opponent } ; cătălin zmărăndescu } } = true', 'tointer': 'select the rows whose result record fuzzily matches to draw . there is only one such row in the table . the opponent record of this unqiue row is cătălin zmărăndescu .'} | and { only { filter_eq { all_rows ; result ; draw } } ; eq { hop { filter_eq { all_rows ; result ; draw } ; opponent } ; cătălin zmărăndescu } } = true | select the rows whose result record fuzzily matches to draw . there is only one such row in the table . the opponent record of this unqiue row is cătălin zmărăndescu . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'result_7': 7, 'draw_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'opponent_9': 9, 'cătălin zmărăndescu_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', 'draw_8': 'draw', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'opponent_9': 'opponent', 'cătălin zmărăndescu_10': 'cătălin zmărăndescu'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'result_7': [0], 'draw_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'opponent_9': [2], 'cătălin zmărăndescu_10': [3]} | ['date', 'result', 'opponent', 'location', 'method'] | [['2013 - 04 - 27', 'win', 'martinis knyzelis', 'vilnius , lithuania', 'decision'], ['2007 - 06 - 25', 'loss', 'björn bregy', 'amsterdam , netherlands', 'decision ( unanimous )'], ['2007 - 05 - 04', 'win', 'paula mataele', 'bucharest , romania', 'ko ( straight punch )'], ['2007 - 05 - 04', 'win', 'errol zimmerman', 'bucharest , romania', 'decision ( majority )'], ['2007 - 05 - 04', 'win', 'doug viney', 'bucharest , romania', 'ko ( left roundhouse kick )'], ['2007 - 04 - 07', 'loss', 'errol zimmerman', 'tilburg , netherlands', 'decision'], ['2006 - 03 - 26', 'loss', 'lloyd van dams', 'tilburg , netherlands', 'decision ( unanimous )'], ['2005 - 10 - 02', 'loss', 'alexander ustinov', 'arnhem , netherlands', 'ko'], ['2005 - 09 - 16', 'loss', 'daniel ghiță', 'cluj - napoca , romania', 'decision ( unanimous )'], ['2005 - 02 - 05', 'win', 'alexander ustinov', 'romania', 'decision'], ['2004 - 11 - 12', 'win', 'aziz khattou', '-', 'decision ( unanimous )'], ['2004 - 11 - 04', 'draw', 'cătălin zmărăndescu', 'brașov , romania', 'decision'], ['2004 - 08 - 07', 'loss', 'mighty mo', 'las vegas , nevada , usa', 'ko ( right overhand )'], ['2004 - 08 - 07', 'win', 'jörgen kruth', 'las vegas , nevada , usa', 'decision ( unanimous )'], ['2004 - 08 - 07', 'win', 'carter williams', 'las vegas , nevada , usa', 'ko ( high kick )'], ['2004 - 02 - 14', 'win', 'rickard nordstrand', 'stockholm , sweden', 'tko ( corner stoppage )'], ['2004 - 02 - 14', 'win', 'petri reima', 'stockholm , sweden', 'decision ( majority )'], ['2004 - 02 - 14', 'win', 'johan mparmpagiannis', 'stockholm , sweden', 'tko ( fighter gave up )'], ['2003 - 04 - 06', 'win', 'jörgen kruth', 'zoetermeer , netherlands', 'extr decision ( majority )']] |
el tamarugal | https://en.wikipedia.org/wiki/El_Tamarugal | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13764346-1.html.csv | aggregation | in el tamarugal , the average density , in kilometers squared , is .55 . | {'scope': 'all', 'col': '4', 'type': 'average', 'result': '.55', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'density ( km 2 )'], 'result': '.55', 'ind': 0, 'tostr': 'avg { all_rows ; density ( km 2 ) }'}, '.55'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; density ( km 2 ) } ; .55 } = true', 'tointer': 'the average of the density ( km 2 ) record of all rows is .55 .'} | round_eq { avg { all_rows ; density ( km 2 ) } ; .55 } = true | the average of the density ( km 2 ) record of all rows is .55 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'density (km 2 )_4': 4, '.55_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'density (km 2 )_4': 'density ( km 2 )', '.55_5': '.55'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'density (km 2 )_4': [0], '.55_5': [1]} | ['commune', 'area ( km 2 )', '2002 population', 'density ( km 2 )', 'government website'] | [['pozo almonte ( capital )', '13765.8', '10830', '0.8', 'link'], ['pica', '8934.3', '6178', '0.7', 'link'], ['huara', '10474.6', '2599', '0.2', 'link'], ['colchane', '4015.6', '1649', '0.4', 'link'], ['camiã ± a', '2200.2', '1275', '0.6', 'none'], ['province', '39390.5', '22531', '0.6', 'link']] |
list of tallest buildings and structures in london | https://en.wikipedia.org/wiki/List_of_tallest_buildings_and_structures_in_London | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-180342-8.html.csv | superlative | of the building and structures that have held the title for the tallest building in london at some point in time , the shared london bridge was taller than any other so far . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '10', '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', 'height metres / ft'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; height metres / ft }'}, 'name'], 'result': 'shard london bridge', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; height metres / ft } ; name }'}, 'shard london bridge'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; height metres / ft } ; name } ; shard london bridge } = true', 'tointer': 'select the row whose height metres / ft record of all rows is maximum . the name record of this row is shard london bridge .'} | eq { hop { argmax { all_rows ; height metres / ft } ; name } ; shard london bridge } = true | select the row whose height metres / ft record of all rows is maximum . the name record of this row is shard london bridge . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'height metres / ft_5': 5, 'name_6': 6, 'shard london bridge_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'height metres / ft_5': 'height metres / ft', 'name_6': 'name', 'shard london bridge_7': 'shard london bridge'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'height metres / ft_5': [0], 'name_6': [1], 'shard london bridge_7': [2]} | ['name', 'location', 'years as tallest', 'height metres / ft', 'floors'] | [['white tower', 'tower hill', '1098 - 1310', '01.0 27 / 90', '03.0 n / a'], ["old st paul 's cathedral", 'city of london', '1310 - 1666', '07.0 150 / 493', '08.0 n / a'], ['southwark cathedral', 'southwark', '1666 - 1677', '02.0 50 / 163', '04.0 n / a'], ['monument to the great fire of london', 'city of london', '1677 - 1683', '03.0 62 / 202', '05.0 n / a'], ['st mary - le - bow', 'city of london', '1683 - 1710', '04.0 72 / 236', '06.0 n / a'], ["st paul 's cathedral", 'city of london', '1710 - 1939', '05.0 111 / 365', '07.0 n / a'], ['battersea power station', 'kirtling street', '1939 - 1950', '06.0 113 / 370', '01.0 10'], ['crystal palace transmitting station', 'crystal palace park', '1950 - 1991', '08.0 219 / 720', '09.0 n / a'], ['one canada square', 'canary wharf', '1991 - 2010', '09.0 235 / 771', '02.0 50'], ['shard london bridge', 'southwark', '2010 -', '306 / 1004', '87']] |
1992 - 93 in argentine football | https://en.wikipedia.org/wiki/1992%E2%80%9393_in_Argentine_football | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-14371754-1.html.csv | majority | most of the teams which participated in the 1992 - 93 argentine football season games each played 114 matches . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'equal', 'value': '114', 'subset': None} | {'func': 'most_eq', 'args': ['all_rows', 'played', '114'], 'result': True, 'ind': 0, 'tointer': 'for the played records of all rows , most of them are equal to 114 .', 'tostr': 'most_eq { all_rows ; played ; 114 } = true'} | most_eq { all_rows ; played ; 114 } = true | for the played records of all rows , most of them are equal to 114 . | 1 | 1 | {'most_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'played_3': 3, '114_4': 4} | {'most_eq_0': 'most_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'played_3': 'played', '114_4': '114'} | {'most_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'played_3': [0], '114_4': [0]} | ['team', 'average', 'points', 'played', '1991 - 92', '1992 - 93', '1993 - 94'] | [['boca juniors', '1.307', '149', '114', '51', '50', '48'], ['river plate', '1.281', '146', '114', '45', '55', '46'], ['vélez sársfield', '1.237', '141', '114', '45', '48', '48'], ['san lorenzo', '1.088', '124', '114', '45', '45', '45'], ['huracán', '1.061', '121', '114', '40', '38', '43'], ['independiente', '1.026', '117', '114', '40', '36', '41'], ["newell 's old boys", '1.026', '117', '114', '48', '44', '25'], ['racing club', '1.009', '115', '114', '40', '39', '36'], ['deportivo español', '1.000', '114', '114', '28', '45', '41'], ['ferro carril oeste', '0.991', '113', '114', '38', '37', '38'], ['rosario central', '0.982', '112', '114', '39', '34', '39'], ['lanús', '0.974', '37', '38', 'n / a', 'n / a', '37'], ['belgrano de córdoba', '0.961', '73', '76', 'n / a', '35', '38'], ['textil mandiyú', '0.947', '108', '114', '38', '33', '37'], ['gimnasia de la plata', '0.947', '108', '114', '33', '41', '34'], ['estudiantes de la plata', '0.930', '106', '114', '39', '29', '38'], ['platense', '0.921', '105', '114', '35', '42', '28'], ['argentinos juniors', '0.912', '104', '114', '36', '35', '33'], ['talleres de córdoba', '0.851', '97', '114', '29', '37', '31']] |
ai miyazato | https://en.wikipedia.org/wiki/Ai_Miyazato | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2126093-3.html.csv | aggregation | ai miyazato 's average number of strokes for margin of victory is 3.23 . | {'scope': 'all', 'col': '6', 'type': 'average', 'result': '3.23', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'margin of victory'], 'result': '3.23', 'ind': 0, 'tostr': 'avg { all_rows ; margin of victory }'}, '3.23'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; margin of victory } ; 3.23 } = true', 'tointer': 'the average of the margin of victory record of all rows is 3.23 .'} | round_eq { avg { all_rows ; margin of victory } ; 3.23 } = true | the average of the margin of victory record of all rows is 3.23 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'margin of victory_4': 4, '3.23_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'margin of victory_4': 'margin of victory', '3.23_5': '3.23'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'margin of victory_4': [0], '3.23_5': [1]} | ['no', 'date', 'tournament', 'winning score', 'to par', 'margin of victory', 'runner ( s ) - up'] | [['1', '28 sep 2003', 'miyagi tv cup dunlop ladies open ( as an amateur )', '70 + 70 + 71 = 211', '- 5', '1 stroke', 'mari katayama hiroko yamaguchi'], ['2', '7 mar 2004', 'daikin orchid ladies', '70 + 66 + 70 = 206', '- 10', '3 strokes', 'kaori higo'], ['3', '13 jun 2004', 'suntory ladies open', '69 + 70 + 70 + 68 = 277', '- 11', '6 strokes', 'hiroko yamaguchi toshimi kimura'], ['4', '20 jun 2004', 'apita circle k sunkus ladies', '69 + 69 + 72 = 210', '- 6', '1 stroke', 'yuri fudoh'], ['5', '24 oct 2004', 'masters gc ladies', '69 + 68 + 68 = 205', '- 11', '1 stroke', 'miho koga'], ['6', '21 nov 2004', 'daio paper elleair ladies open', '66 + 67 + 69 = 202', '- 14', '3 strokes', 'chieko amanuma rui kitada'], ['7', '15 may 2005', 'vernal ladies', '69 + 64 + 70 = 203', '- 13', '8 strokes', 'akiko fukushima'], ['8', '22 may 2005', 'chukyo tv bridgestone ladies open', '65 + 74 + 70 = 209', '- 7', 'playoff', 'nikki campbell'], ['9', '21 aug 2005', 'new catapillar mitsubishi ladies', '66 + 75 + 68 = 209', '- 10', '3 strokes', 'mi - jeong jeon hiromi mogi'], ['10', '2 oct 2005', "japan women 's open golf championship", '69 + 69 + 72 + 73 = 283', '- 5', '5 strokes', 'akiko fukushima'], ['12', '20 nov 2005', 'daio paper elleair ladies open', '69 + 70 + 65 = 204', '- 12', '5 strokes', 'shiho oyama woo - soon ko kasumi fujii'], ['13', '10 sep 2006', 'jlpga championship konica minolta cup', '70 + 68 + 74 + 70 = 282', '- 6', '3 strokes', 'hyun - ju shin'], ['14', '24 sep 2006', 'miyagi tv cup dunlop ladies open', '70 + 73 + 71 = 214', '- 2', '3 strokes', 'shiho oyama']] |
2008 - 09 phoenix suns season | https://en.wikipedia.org/wiki/2008%E2%80%9309_Phoenix_Suns_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17340355-7.html.csv | ordinal | in the 2008-2009 phoenix suns season , in the fourth game at the us airways centre , shaquille o'neal scored the highest number of points . | {'scope': 'subset', 'row': '5', 'col': '2', 'order': '4', 'col_other': '5,8', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'subset': {'col': '8', 'criterion': 'fuzzily_match', 'value': 'us airways center'}} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location attendance', 'us airways center'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; location attendance ; us airways center }', 'tointer': 'select the rows whose location attendance record fuzzily matches to us airways center .'}, 'date', '4'], 'result': None, 'ind': 1, 'tostr': 'nth_argmin { filter_eq { all_rows ; location attendance ; us airways center } ; date ; 4 }'}, 'high points'], 'result': "shaquille o'neal ( 26 )", 'ind': 2, 'tostr': 'hop { nth_argmin { filter_eq { all_rows ; location attendance ; us airways center } ; date ; 4 } ; high points }'}, "shaquille o'neal ( 26 )"], 'result': True, 'ind': 3, 'tostr': "eq { hop { nth_argmin { filter_eq { all_rows ; location attendance ; us airways center } ; date ; 4 } ; high points } ; shaquille o'neal ( 26 ) } = true", 'tointer': "select the rows whose location attendance record fuzzily matches to us airways center . select the row whose date record of these rows is 4th minimum . the high points record of this row is shaquille o'neal ( 26 ) ."} | eq { hop { nth_argmin { filter_eq { all_rows ; location attendance ; us airways center } ; date ; 4 } ; high points } ; shaquille o'neal ( 26 ) } = true | select the rows whose location attendance record fuzzily matches to us airways center . select the row whose date record of these rows is 4th minimum . the high points record of this row is shaquille o'neal ( 26 ) . | 4 | 4 | {'str_eq_3': 3, 'result_4': 4, 'str_hop_2': 2, 'nth_argmin_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'location attendance_6': 6, 'us airways center_7': 7, 'date_8': 8, '4_9': 9, 'high points_10': 10, "shaquille o'neal (26)_11": 11} | {'str_eq_3': 'str_eq', 'result_4': 'true', 'str_hop_2': 'str_hop', 'nth_argmin_1': 'nth_argmin', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'location attendance_6': 'location attendance', 'us airways center_7': 'us airways center', 'date_8': 'date', '4_9': '4', 'high points_10': 'high points', "shaquille o'neal (26)_11": "shaquille o'neal ( 26 )"} | {'str_eq_3': [4], 'result_4': [], 'str_hop_2': [3], 'nth_argmin_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'location attendance_6': [0], 'us airways center_7': [0], 'date_8': [1], '4_9': [1], 'high points_10': [2], "shaquille o'neal (26)_11": [3]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record'] | [['31', 'january 2', 'la clippers', 'w 106 - 98 ( ot )', "amar ' e stoudemire ( 23 )", "shaquille o'neal ( 9 )", 'steve nash ( 11 )', 'us airways center 18422', '19 - 12'], ['32', 'january 7', 'indiana', 'l 110 - 113 ( ot )', "amar ' e stoudemire ( 23 )", 'louis amundson ( 14 )', 'steve nash ( 12 )', 'us airways center 18422', '19 - 13'], ['33', 'january 9', 'dallas', 'w 128 - 100 ( ot )', "shaquille o'neal ( 25 )", "shaquille o'neal ( 10 )", 'steve nash ( 12 )', 'us airways center 18422', '20 - 13'], ['34', 'january 11', 'la clippers', 'w 109 - 103 ( ot )', "amar ' e stoudemire ( 26 )", "shaquille o'neal ( 10 )", 'steve nash ( 12 )', 'staples center 17307', '21 - 13'], ['35', 'january 13', 'atlanta', 'w 107 - 102 ( ot )', "shaquille o'neal ( 26 )", "matt barnes , shaquille o'neal ( 10 )", 'steve nash ( 6 )', 'us airways center 18422', '22 - 13'], ['36', 'january 15', 'denver', 'l 113 - 119 ( ot )', 'grant hill ( 25 )', "grant hill , amar ' e stoudemire ( 8 )", 'steve nash ( 14 )', 'pepsi center 18073', '22 - 14'], ['37', 'january 16', 'minnesota', 'l 103 - 105 ( ot )', "shaquille o'neal , leandro barbosa ( 22 )", "shaquille o'neal ( 11 )", 'steve nash ( 6 )', 'us airways center 18422', '22 - 15'], ['38', 'january 18', 'toronto', 'w 117 - 113 ( ot )', "amar ' e stoudemire ( 31 )", 'grant hill ( 9 )', 'steve nash ( 18 )', 'air canada centre 19800', '23 - 15'], ['39', 'january 19', 'boston', 'l 87 - 104 ( ot )', "shaquille o'neal ( 16 )", "shaquille o'neal ( 11 )", 'steve nash ( 8 )', 'td banknorth garden 18624', '23 - 16'], ['40', 'january 21', 'new york', 'l 109 - 114 ( ot )', 'jason richardson ( 27 )', "shaquille o'neal ( 12 )", 'steve nash ( 19 )', 'madison square garden 19256', '23 - 17'], ['41', 'january 23', 'charlotte', 'l 76 - 98 ( ot )', "shaquille o'neal ( 20 )", "amar ' e stoudemire ( 9 )", 'steve nash ( 5 )', 'time warner cable arena 19104', '23 - 18'], ['42', 'january 25', 'atlanta', 'w 104 - 99 ( ot )', "amar ' e stoudemire ( 23 )", "shaquille o'neal ( 11 )", 'steve nash ( 13 )', 'philips arena 19153', '24 - 18'], ['43', 'january 26', 'washington', 'w 103 - 87 ( ot )', "shaquille o'neal ( 29 )", "amar ' e stoudemire ( 15 )", 'steve nash ( 15 )', 'verizon center 17344', '25 - 18'], ['44', 'january 29', 'san antonio', 'l 104 - 114 ( ot )', "amar ' e stoudemire ( 28 )", "amar ' e stoudemire , grant hill ( 10 )", 'steve nash ( 18 )', 'us airways center 18422', '25 - 19'], ['45', 'january 31', 'chicago', 'l 111 - 122 ( ot )', 'leandro barbosa ( 32 )', "shaquille o'neal ( 8 )", 'steve nash ( 10 )', 'us airways center 18422', '25 - 20']] |
2008 universitario de deportes season | https://en.wikipedia.org/wiki/2008_Universitario_de_Deportes_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17932930-3.html.csv | majority | all of the players that were moved in the 2008 universitario de deportes season were in the winter transfer window . | {'scope': 'all', 'col': '5', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'winter', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'transfer window', 'winter'], 'result': True, 'ind': 0, 'tointer': 'for the transfer window records of all rows , all of them fuzzily match to winter .', 'tostr': 'all_eq { all_rows ; transfer window ; winter } = true'} | all_eq { all_rows ; transfer window ; winter } = true | for the transfer window records of all rows , all of them fuzzily match to winter . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'transfer window_3': 3, 'winter_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'transfer window_3': 'transfer window', 'winter_4': 'winter'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'transfer window_3': [0], 'winter_4': [0]} | ['nat', 'name', 'moving to', 'type', 'transfer window'] | [['per', 'rivas', 'górnik zabrze', 'transfer', 'winter'], ['per', 'v zapata', 'alianza atlético', 'transfer', 'winter'], ['per', 'tragodara', 'atlético minero', 'loaned out', 'winter'], ['per', 'correa', 'melgar', 'loaned out', 'winter'], ['per', 'curiel', 'alianza atlético', 'transfer', 'winter']] |
mecklenburg - vorpommern state election , 2002 | https://en.wikipedia.org/wiki/Mecklenburg-Vorpommern_state_election%2C_2002 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1265214-1.html.csv | count | there were 7 parties which participated in the 2002 mecklenburg - vorpommern state election . | {'scope': 'all', 'criterion': 'not_equal', 'value': 'totals', 'result': '7', 'col': '1', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_not_eq', 'args': ['all_rows', 'party', 'totals'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose party record does not match to totals .', 'tostr': 'filter_not_eq { all_rows ; party ; totals }'}], 'result': '7', 'ind': 1, 'tostr': 'count { filter_not_eq { all_rows ; party ; totals } }', 'tointer': 'select the rows whose party record does not match to totals . the number of such rows is 7 .'}, '7'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_not_eq { all_rows ; party ; totals } } ; 7 } = true', 'tointer': 'select the rows whose party record does not match to totals . the number of such rows is 7 .'} | eq { count { filter_not_eq { all_rows ; party ; totals } } ; 7 } = true | select the rows whose party record does not match to totals . the number of such rows is 7 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_not_eq_0': 0, 'all_rows_4': 4, 'party_5': 5, 'totals_6': 6, '7_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_not_eq_0': 'filter_str_not_eq', 'all_rows_4': 'all_rows', 'party_5': 'party', 'totals_6': 'totals', '7_7': '7'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_not_eq_0': [1], 'all_rows_4': [0], 'party_5': [0], 'totals_6': [0], '7_7': [2]} | ['party', 'party list votes', 'vote percentage', 'total seats', 'seat percentage'] | [['social democratic party ( spd )', '394118', '40.6 %', '33', '46.5 %'], ['christian democratic union ( cdu )', '304125', '31.4 %', '25', '35.2 %'], ['party of democratic socialism ( pds )', '159065', '16.4 %', '13', '18.3 %'], ["alliance '90 / the greens", '25402', '2.6 %', '0', '0.0 %'], ['free democratic party ( fdp )', '45676', '4.7 %', '0', '0.0 %'], ['law and order offensive party', '16483', '1.7 %', '0', '0.0 %'], ['all others', '25162', '2.6 %', '0', '0.0 %'], ['totals', '970031', '100.0 %', '71', '100.0 %']] |
the general in his labyrinth | https://en.wikipedia.org/wiki/The_General_in_His_Labyrinth | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1162324-1.html.csv | aggregation | the books written in 1990 total over 800 pages together . | {'scope': 'subset', 'col': '6', 'type': 'sum', 'result': '1135', 'subset': {'col': '1', 'criterion': 'equal', 'value': '1990'}} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'year', '1990'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; year ; 1990 }', 'tointer': 'select the rows whose year record is equal to 1990 .'}, 'pages'], 'result': '1135', 'ind': 1, 'tostr': 'sum { filter_eq { all_rows ; year ; 1990 } ; pages }'}, '1135'], 'result': True, 'ind': 2, 'tostr': 'round_eq { sum { filter_eq { all_rows ; year ; 1990 } ; pages } ; 1135 } = true', 'tointer': 'select the rows whose year record is equal to 1990 . the sum of the pages record of these rows is 1135 .'} | round_eq { sum { filter_eq { all_rows ; year ; 1990 } ; pages } ; 1135 } = true | select the rows whose year record is equal to 1990 . the sum of the pages record of these rows is 1135 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'sum_1': 1, 'filter_eq_0': 0, 'all_rows_4': 4, 'year_5': 5, '1990_6': 6, 'pages_7': 7, '1135_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'sum_1': 'sum', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'year_5': 'year', '1990_6': '1990', 'pages_7': 'pages', '1135_8': '1135'} | {'eq_2': [3], 'result_3': [], 'sum_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'year_5': [0], '1990_6': [0], 'pages_7': [1], '1135_8': [2]} | ['year', 'language', 'title', 'translator', 'company', 'pages'] | [['1989', 'arabic', 'al - jiniral fi matahatihi', 'salih ilmani', 'nicosia : ibal', '287'], ['1989', 'german', 'der general in seinem labyrinth : roman', 'dagmar ploetz', 'cologne : kiepenheuer & witsch', '359'], ['1989', 'swedish', 'generalen i sin labyrint', 'jens nordenhök', 'stockholm : wahlström & widstrand', '267'], ['1989', 'portuguese', 'o general em seu labirinto', 'moacir werneck de castro', 'rio de janeiro : editora record', '281'], ['1990', 'english', 'the general in his labyrinth', 'edith grossman', 'new york city : alfred a knopf', '285'], ['1990', 'french', 'le général dans son labyrinthe', 'annie morvan', 'paris : b grasset', '318'], ['1990', 'turkish', 'labirentindeki general', 'inci kut', 'istanbul : can yayınları', '253'], ['1990', 'basque', 'jenerala bere laberintoan', 'xabier mendiguren', 'donostia - san sebastián , spain : eikar', '279'], ['1991', 'hebrew', 'general be - mavokh', 'ritah meltser and amatsyah porat', 'tel aviv : am oved', '205'], ['1991', 'japanese', 'meikyu no shogun', 'kimura eiichi', 'tokyo : shinchosha', '323'], ['1991', 'persian', 'zhiniral dar hazar tu - yi khvad', 'hushang asadi ( based on the english version )', 'tehran : kitab - i mahnaz', '237'], ['1992', 'hungarian', 'a tábornok útvesztője', 'tomcsányi zsuzsanna', 'budapest : magvető', '254'], ['1992 , 1996', 'italian', 'il generale nel suo labirinto', 'angelo morino', 'milan : mondadori', '286'], ['1993', 'polish', 'generał w labiryncie', 'zofia wasitowa', 'warsaw : pánstwowy instytut wydawniczy', '285'], ['1995', 'chinese', 'mi gong zhong di jiang jun', 'chengdong yin', 'taipei : yun chen wen hua shi ye', '321'], ['1996', 'dutch', 'de generaal in zijn labyrint', 'mieke westra', 'amsterdam : meulenhoff , 3rd ed', '317'], ['1996', 'romanian', 'generalul în labirintul său', 'mihaela dumitrescu', 'bucharest : rao', '256'], ['1999', 'vietnamese', 'tướng qun giữa mê hồn trận', 'nguyễn trung đức', 'hanoi : hội nhà văn', '394'], ['2000', 'albanian', 'gjenerali në labirintin e vet : roman', 'nasi lera', 'tirana : mësonjëtorja e parë', '305'], ['nm', 'greek', 'ο στρατηγός μες στο λαβύρινθό του', 'klaiti sotiriadou - barajas', 'athens : livanis publications', '309']] |
1994 group | https://en.wikipedia.org/wiki/1994_Group | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-142950-1.html.csv | majority | the majority of the institutions gained university status after 1920 . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'greater_than', 'value': '1920', 'subset': None} | {'func': 'most_greater', 'args': ['all_rows', 'gained university status', '1920'], 'result': True, 'ind': 0, 'tointer': 'for the gained university status records of all rows , most of them are greater than 1920 .', 'tostr': 'most_greater { all_rows ; gained university status ; 1920 } = true'} | most_greater { all_rows ; gained university status ; 1920 } = true | for the gained university status records of all rows , most of them are greater than 1920 . | 1 | 1 | {'most_greater_0': 0, 'result_1': 1, 'all_rows_2': 2, 'gained university status_3': 3, '1920_4': 4} | {'most_greater_0': 'most_greater', 'result_1': 'true', 'all_rows_2': 'all_rows', 'gained university status_3': 'gained university status', '1920_4': '1920'} | {'most_greater_0': [1], 'result_1': [], 'all_rows_2': [0], 'gained university status_3': [0], '1920_4': [0]} | ['institution', 'location', 'established', 'gained university status', 'vice - chancellor', 'total number of students', 'research funding ( 000 )'] | [['birkbeck , university of london', 'london', '1823', '1920', 'professor david latchman', '19020', '9985'], ['university of east anglia', 'norwich', '1963', '1963', 'professor edward acton', '19585', '16482'], ['university of essex', 'colchester', '1964', '1964', 'professor anthony forster', '11690', '9967'], ['goldsmiths , university of london', 'london', '1891', '1904', 'dr pat loughrey', '7615', '8539'], ['institute of education , university of london', 'london', '1902', '1932', 'professor chris husbands', '7215', '7734'], ['university of lancaster', 'lancaster', '1964', '1964', 'professor mark smith', '12695', '18640'], ['university of leicester', 'leicester', '1921', '1957', 'professor robert burgess', '16160', '22225'], ['loughborough university', 'loughborough', '1909', '1966', 'professor robert allison', '17825', '22398'], ['royal holloway , university of london', 'egham', '1849', '1900', 'professor paul layzell ( principal )', '7620', '13699'], ['soas , university of london', 'london', '1916', '1916', 'professor paul webley', '4525', '7238'], ['university of sussex', 'brighton', '1961', '1961', 'professor michael farthing', '12415', '16196']] |
1990 - 91 boston celtics season | https://en.wikipedia.org/wiki/1990%E2%80%9391_Boston_Celtics_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-17344582-11.html.csv | count | the boston celtics won 2 games played against the detroit pistons from may 7 to may 15 in the 1990 - 91 season . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'w', 'result': '2', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'score', 'w'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose score record fuzzily matches to w .', 'tostr': 'filter_eq { all_rows ; score ; w }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; score ; w } }', 'tointer': 'select the rows whose score record fuzzily matches to w . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; score ; w } } ; 2 } = true', 'tointer': 'select the rows whose score record fuzzily matches to w . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; score ; w } } ; 2 } = true | select the rows whose score record fuzzily matches to w . 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, 'score_5': 5, 'w_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', 'score_5': 'score', 'w_6': 'w', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'score_5': [0], 'w_6': [0], '2_7': [2]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'series'] | [['1', 'may 7', 'detroit pistons', 'l 75 - 86', 'r lewis ( 20 )', 'k mchale ( 10 )', 'b shaw ( 5 )', 'boston garden', '0 - 1'], ['2', 'may 9', 'detroit pistons', 'w 109 - 103', 'r lewis ( 23 )', 'r parish ( 13 )', 'd brown ( 8 )', 'boston garden', '1 - 1'], ['3', 'may 11', 'detroit pistons', 'w 115 - 83', 'r lewis ( 21 )', 'r parish ( 11 )', 'd brown , k mchale ( 6 )', 'the palace of auburn hills', '2 - 1'], ['4', 'may 13', 'detroit pistons', 'l 97 - 104', 'k mchale ( 28 )', 'r parish ( 10 )', 'b shaw ( 6 )', 'the palace of auburn hills', '2 - 2'], ['5', 'may 15', 'detroit pistons', 'l 111 - 116', 'r lewis ( 30 )', 'r lewis ( 11 )', 'd brown ( 10 )', 'boston garden', '2 - 3']] |
miss usa 1989 | https://en.wikipedia.org/wiki/Miss_USA_1989 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-16268026-3.html.csv | comparative | oklahoma had a higher interview score than new jersey in the miss usa 1989 pageant . | {'row_1': '4', 'row_2': '1', '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', 'state', 'oklahoma'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose state record fuzzily matches to oklahoma .', 'tostr': 'filter_eq { all_rows ; state ; oklahoma }'}, 'interview'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; state ; oklahoma } ; interview }', 'tointer': 'select the rows whose state record fuzzily matches to oklahoma . take the interview record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'state', 'new jersey'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose state record fuzzily matches to new jersey .', 'tostr': 'filter_eq { all_rows ; state ; new jersey }'}, 'interview'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; state ; new jersey } ; interview }', 'tointer': 'select the rows whose state record fuzzily matches to new jersey . take the interview record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; state ; oklahoma } ; interview } ; hop { filter_eq { all_rows ; state ; new jersey } ; interview } } = true', 'tointer': 'select the rows whose state record fuzzily matches to oklahoma . take the interview record of this row . select the rows whose state record fuzzily matches to new jersey . take the interview record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; state ; oklahoma } ; interview } ; hop { filter_eq { all_rows ; state ; new jersey } ; interview } } = true | select the rows whose state record fuzzily matches to oklahoma . take the interview record of this row . select the rows whose state record fuzzily matches to new jersey . take the interview 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, 'state_7': 7, 'oklahoma_8': 8, 'interview_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'state_11': 11, 'new jersey_12': 12, 'interview_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', 'state_7': 'state', 'oklahoma_8': 'oklahoma', 'interview_9': 'interview', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'state_11': 'state', 'new jersey_12': 'new jersey', 'interview_13': 'interview'} | {'greater_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'state_7': [0], 'oklahoma_8': [0], 'interview_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'state_11': [1], 'new jersey_12': [1], 'interview_13': [3]} | ['state', 'preliminary average', 'interview', 'swimsuit', 'evening gown', 'semifinal average'] | [['new jersey', '8.510 ( 7 )', '8.626 ( 5 )', '8.712 ( 6 )', '9.165 ( 3 )', '8.834 ( 3 )'], ['colorado', '8.388 ( 10 )', '8.638 ( 4 )', '8.432 ( 9 )', '8.786 ( 5 )', '8.618 ( 7 )'], ['louisiana', '8.829 ( 2 )', '8.600 ( 6 )', '8.820 ( 4 )', '8.710 ( 7 )', '8.710 ( 5 )'], ['oklahoma', '8.662 ( 3 )', '8.880 ( 2 )', '8.762 ( 5 )', '9.214 ( 2 )', '8.952 ( 2 )'], ['california', '8.659 ( 4 )', '8.313 ( 8 )', '8.977 ( 2 )', '8.774 ( 6 )', '8.688 ( 6 )'], ['illinois', '8.501 ( 8 )', '7.988 ( 9 )', '8.432 ( 9 )', '8.681 ( 9 )', '8.367 ( 10 )'], ['texas', '9.084 ( 1 )', '9.425 ( 1 )', '9.535 ( 1 )', '9.601 ( 1 )', '9.520 ( 1 )'], ['pennsylvania', '8.580 ( 5 )', '8.534 ( 7 )', '8.467 ( 8 )', '8.613 ( 10 )', '8.538 ( 8 )'], ['arizona', '8.529 ( 6 )', '7.792 ( 10 )', '8.833 ( 3 )', '8.703 ( 8 )', '8.442 ( 9 )']] |
list of sri lanka test wicket - keepers | https://en.wikipedia.org/wiki/List_of_Sri_Lanka_Test_wicket-keepers | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12397222-1.html.csv | aggregation | sri lanka wicket keepers achieved a total of 463 dismissals . | {'scope': 'all', 'col': '6', 'type': 'sum', 'result': '463', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'total dismissals'], 'result': '463', 'ind': 0, 'tostr': 'sum { all_rows ; total dismissals }'}, '463'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; total dismissals } ; 463 } = true', 'tointer': 'the sum of the total dismissals record of all rows is 463 .'} | round_eq { sum { all_rows ; total dismissals } ; 463 } = true | the sum of the total dismissals record of all rows is 463 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'total dismissals_4': 4, '463_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'total dismissals_4': 'total dismissals', '463_5': '463'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'total dismissals_4': [0], '463_5': [1]} | ['player', 'test career', 'tests', 'catches', 'stumpings', 'total dismissals'] | [['mahes goonatilleke', '1982 - 82', '5', '10', '3', '15'], ['guy de alwis', '1983 - 88', '11', '21', '1', '23'], ['amal silva', '1983 - 88', '9', '33', '1', '34'], ['asanka gurusinha', '1985 - 96', '41', '2', '0', '2'], ['brendon kuruppu', '1987 - 91', '4', '1', '0', '1'], ['gamini wickremasinghe', '1989 - 92', '3', '9', '1', '10'], ['hashan tillakaratne', '1989 - 2004', '83', '33', '2', '35'], ['romesh kaluwitharana', '1992 - 2004', '49', '93', '26', '119'], ['ashley de silva', '1993 - 93', '3', '4', '1', '5'], ['pubudu dassanayake', '1993 - 94', '11', '19', '5', '24'], ['chamara dunusinghe', '1995 - 95', '5', '13', '2', '15'], ['lanka de silva', '1997 - 97', '3', '1', '0', '1'], ['prasanna jayawardene', '2000 - 2007', '12', '26', '6', '32'], ['kumar sangakkara', '2000 - 2007', '67', '127', '20', '147']] |
media in north bay , ontario | https://en.wikipedia.org/wiki/Media_in_North_Bay%2C_Ontario | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16079851-1.html.csv | unique | of the media frequencies in north bay , ontario , the only frequency owned by eternacom is 103.5 fm . | {'scope': 'all', 'row': '8', 'col': '5', 'col_other': '1', 'criterion': 'equal', 'value': 'eternacom', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'owner', 'eternacom'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose owner record fuzzily matches to eternacom .', 'tostr': 'filter_eq { all_rows ; owner ; eternacom }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; owner ; eternacom } }', 'tointer': 'select the rows whose owner record fuzzily matches to eternacom . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'owner', 'eternacom'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose owner record fuzzily matches to eternacom .', 'tostr': 'filter_eq { all_rows ; owner ; eternacom }'}, 'frequency'], 'result': '103.5 fm', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; owner ; eternacom } ; frequency }'}, '103.5 fm'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; owner ; eternacom } ; frequency } ; 103.5 fm }', 'tointer': 'the frequency record of this unqiue row is 103.5 fm .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; owner ; eternacom } } ; eq { hop { filter_eq { all_rows ; owner ; eternacom } ; frequency } ; 103.5 fm } } = true', 'tointer': 'select the rows whose owner record fuzzily matches to eternacom . there is only one such row in the table . the frequency record of this unqiue row is 103.5 fm .'} | and { only { filter_eq { all_rows ; owner ; eternacom } } ; eq { hop { filter_eq { all_rows ; owner ; eternacom } ; frequency } ; 103.5 fm } } = true | select the rows whose owner record fuzzily matches to eternacom . there is only one such row in the table . the frequency record of this unqiue row is 103.5 fm . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'owner_7': 7, 'eternacom_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'frequency_9': 9, '103.5 fm_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'owner_7': 'owner', 'eternacom_8': 'eternacom', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'frequency_9': 'frequency', '103.5 fm_10': '103.5 fm'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'owner_7': [0], 'eternacom_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'frequency_9': [2], '103.5 fm_10': [3]} | ['frequency', 'call sign', 'branding', 'format', 'owner'] | [['600 am', 'ckat', 'country 600', 'country / news / sports', 'rogers communications'], ['95.1 fm', 'cbon - fm - 17', 'première chaîne', 'public news / talk', 'canadian broadcasting corporation'], ['96.1 fm', 'cbcn - fm', 'cbc radio one', 'public news / talk', 'canadian broadcasting corporation'], ['97.1 fm', 'chyq - fm', 'le loup fm', 'hot adult contemporary', 'le5 communications'], ['99.3 fm', 'cfsf - fm', 'moose fm', 'adult contemporary', 'vista broadcast group'], ['100.5 fm', 'chur - fm', 'kiss 100.5', 'hot adult contemporary', 'rogers communications'], ['101.9 fm', 'ckfx - fm', 'the fox', 'active rock', 'rogers communications'], ['103.5 fm', 'cjtk - fm', 'kfm', 'christian music', 'eternacom'], ['104.9 fm', 'cktr - fm', 'north bay radio 104.9', 'tourist information / community radio', '1311831 ontario limited'], ['106.3 fm', 'cfxn - fm', 'moose fm', 'classic hits', 'vista broadcast group']] |
2005 new zealand rugby union tour of britain and ireland | https://en.wikipedia.org/wiki/2005_New_Zealand_rugby_union_tour_of_Britain_and_Ireland | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18769154-1.html.csv | aggregation | the average points scored per game by new zealand during the 2005 new zealand rugby union tour of britain and ireland was 34.5 . | {'scope': 'all', 'col': '3', 'type': 'average', 'result': '34.5', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'score'], 'result': '34.5', 'ind': 0, 'tostr': 'avg { all_rows ; score }'}, '34.5'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; score } ; 34.5 } = true', 'tointer': 'the average of the score record of all rows is 34.5 .'} | round_eq { avg { all_rows ; score } ; 34.5 } = true | the average of the score record of all rows is 34.5 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'score_4': 4, '34.5_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'score_4': 'score', '34.5_5': '34.5'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'score_4': [0], '34.5_5': [1]} | ['date', 'opponent', 'score', 'venue', 'attendance'] | [['5 nov', 'wales', '41 - 3', 'millennium stadium , cardiff', '74402'], ['12 nov', 'ireland', '45 - 7', 'lansdowne road , dublin', '42000'], ['19 nov', 'england', '23 - 19', 'twickenham , london', '62000'], ['26 nov', 'scotland', '29 - 10', 'murrayfield , edinburgh', '47678'], ['new zealand scores in bold', 'new zealand scores in bold', 'new zealand scores in bold', 'new zealand scores in bold', 'new zealand scores in bold']] |
2008 - 09 new orleans hornets season | https://en.wikipedia.org/wiki/2008%E2%80%9309_New_Orleans_Hornets_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-17288861-5.html.csv | aggregation | in the ' 08 - '09 season of new orleans hornets , their total attendance at new orleans arena was 117,747 . | {'scope': 'subset', 'col': '8', 'type': 'sum', 'result': '117747', 'subset': {'col': '8', 'criterion': 'equal', 'value': 'new orleans arena'}} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location attendance', 'new orleans arena'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; location attendance ; new orleans arena }', 'tointer': 'select the rows whose location attendance record fuzzily matches to new orleans arena .'}, 'location attendance'], 'result': '117747', 'ind': 1, 'tostr': 'sum { filter_eq { all_rows ; location attendance ; new orleans arena } ; location attendance }'}, '117747'], 'result': True, 'ind': 2, 'tostr': 'round_eq { sum { filter_eq { all_rows ; location attendance ; new orleans arena } ; location attendance } ; 117747 } = true', 'tointer': 'select the rows whose location attendance record fuzzily matches to new orleans arena . the sum of the location attendance record of these rows is 117747 .'} | round_eq { sum { filter_eq { all_rows ; location attendance ; new orleans arena } ; location attendance } ; 117747 } = true | select the rows whose location attendance record fuzzily matches to new orleans arena . the sum of the location attendance record of these rows is 117747 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'sum_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'location attendance_5': 5, 'new orleans arena_6': 6, 'location attendance_7': 7, '117747_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'sum_1': 'sum', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'location attendance_5': 'location attendance', 'new orleans arena_6': 'new orleans arena', 'location attendance_7': 'location attendance', '117747_8': '117747'} | {'eq_2': [3], 'result_3': [], 'sum_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'location attendance_5': [0], 'new orleans arena_6': [0], 'location attendance_7': [1], '117747_8': [2]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record'] | [['3', 'november 1', 'cleveland', 'w 104 - 92 ( ot )', 'david west ( 25 )', 'james posey ( 6 )', 'chris paul ( 15 )', 'new orleans arena 18150', '3 - 0'], ['4', 'november 5', 'atlanta', 'l 79 - 87 ( ot )', 'chris paul ( 22 )', 'david west , tyson chandler ( 7 )', 'chris paul ( 11 )', 'new orleans arena 16030', '3 - 1'], ['5', 'november 7', 'charlotte', 'l 89 - 92 ( ot )', 'predrag stojaković , chris paul ( 20 )', 'predrag stojaković , tyson chandler ( 7 )', 'chris paul ( 10 )', 'time warner cable arena 13435', '3 - 2'], ['6', 'november 8', 'miami', 'w 100 - 89 ( ot )', 'david west , chris paul ( 21 )', 'tyson chandler ( 10 )', 'chris paul ( 13 )', 'new orleans arena 17701', '4 - 2'], ['7', 'november 12', 'la lakers', 'l 86 - 93 ( ot )', 'chris paul ( 30 )', 'david west ( 12 )', 'chris paul ( 13 )', 'new orleans arena 18239', '4 - 3'], ['8', 'november 14', 'portland', 'w 87 - 82 ( ot )', 'david west ( 18 )', 'tyson chandler ( 7 )', 'chris paul ( 9 )', 'new orleans arena 16071', '5 - 3'], ['9', 'november 15', 'houston', 'l 82 - 91 ( ot )', 'david west ( 18 )', 'david west ( 10 )', 'chris paul ( 12 )', 'toyota center 18303', '5 - 4'], ['10', 'november 19', 'sacramento', 'l 96 - 105 ( ot )', 'david west ( 22 )', 'tyson chandler ( 10 )', 'chris paul ( 15 )', 'new orleans arena 15533', '5 - 5'], ['11', 'november 21', 'oklahoma city', 'w 105 - 80 ( ot )', 'david west ( 19 )', 'david west ( 8 )', 'chris paul ( 6 )', 'ford center 19136', '6 - 5'], ['12', 'november 22', 'oklahoma city', 'w 109 - 97 ( ot )', 'david west ( 33 )', 'chris paul ( 10 )', 'chris paul ( 16 )', 'new orleans arena 16023', '7 - 5'], ['13', 'november 24', 'la clippers', 'w 99 - 87 ( ot )', 'david west ( 27 )', 'chris paul ( 10 )', 'chris paul ( 17 )', 'staples center 14956', '8 - 5'], ['14', 'november 27', 'denver', 'w 105 - 101 ( ot )', 'chris paul ( 22 )', 'david west ( 8 )', 'chris paul ( 10 )', 'pepsi center 15563', '9 - 5']] |
1978 vfl season | https://en.wikipedia.org/wiki/1978_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10887680-10.html.csv | count | there were 6 game venues used during the 1978 vfl season . | {'scope': 'all', 'criterion': 'all', 'value': 'n/a', 'result': '6', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_all', 'args': ['all_rows', 'venue'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose venue record is arbitrary .', 'tostr': 'filter_all { all_rows ; venue }'}], 'result': '6', 'ind': 1, 'tostr': 'count { filter_all { all_rows ; venue } }', 'tointer': 'select the rows whose venue record is arbitrary . the number of such rows is 6 .'}, '6'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_all { all_rows ; venue } } ; 6 } = true', 'tointer': 'select the rows whose venue record is arbitrary . the number of such rows is 6 .'} | eq { count { filter_all { all_rows ; venue } } ; 6 } = true | select the rows whose venue record is arbitrary . the number of such rows is 6 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_all_0': 0, 'all_rows_4': 4, 'venue_5': 5, '6_6': 6} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_all_0': 'filter_all', 'all_rows_4': 'all_rows', 'venue_5': 'venue', '6_6': '6'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_all_0': [1], 'all_rows_4': [0], 'venue_5': [0], '6_6': [2]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['hawthorn', '12.24 ( 96 )', 'geelong', '8.13 ( 61 )', 'princes park', '11066', '3 june 1978'], ['richmond', '12.14 ( 86 )', 'fitzroy', '11.14 ( 80 )', 'mcg', '21122', '3 june 1978'], ['north melbourne', '13.7 ( 85 )', 'essendon', '12.10 ( 82 )', 'arden street oval', '28828', '3 june 1978'], ['south melbourne', '24.18 ( 162 )', 'melbourne', '14.8 ( 92 )', 'lake oval', '15738', '5 june 1978'], ['footscray', '19.11 ( 125 )', 'carlton', '15.14 ( 104 )', 'western oval', '30197', '5 june 1978'], ['collingwood', '18.23 ( 131 )', 'st kilda', '14.13 ( 97 )', 'vfl park', '72669', '5 june 1978']] |
big brother ( albania ) | https://en.wikipedia.org/wiki/Big_Brother_%28Albania%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15984770-1.html.csv | majority | the majority of the seasons were shown in a span of exactly 99 days . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'equal', 'value': '99', 'subset': None} | {'func': 'most_eq', 'args': ['all_rows', 'days', '99'], 'result': True, 'ind': 0, 'tointer': 'for the days records of all rows , most of them are equal to 99 .', 'tostr': 'most_eq { all_rows ; days ; 99 } = true'} | most_eq { all_rows ; days ; 99 } = true | for the days records of all rows , most of them are equal to 99 . | 1 | 1 | {'most_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'days_3': 3, '99_4': 4} | {'most_eq_0': 'most_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'days_3': 'days', '99_4': '99'} | {'most_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'days_3': [0], '99_4': [0]} | ['series', 'host', 'launch date', 'finale date', 'days', 'winner', 'prize'] | [['season 1', 'arbana osmani', '23 february 2008', '31 may 2008', '100', 'arbër çepani', '50000'], ['season 2', 'arbana osmani', '7 february 2009', '16 may 2009', '99', 'qetsor ferunaj', '70000'], ['season 3', 'arbana osmani', '23 january 2010', '15 may 2010', '113', 'jetmir salaj', '75000'], ['season 4', 'arbana osmani', '25 december 2010', '2 april 2011', '99', 'ermela mezuraj', '75000'], ['season 5', 'arbana osmani', '18 february 2012', '26 may 2012', '99', 'arbër zeka', '100000'], ['season 6', 'arbana osmani', '23 february 2013', '1 june 2013', '99', 'anaid kaloti', '100000']] |
toney penna | https://en.wikipedia.org/wiki/Toney_Penna | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11475534-1.html.csv | count | for toney penna , when there are more than 10 events , there are 2 times when he was in the top-10 2 times . | {'scope': 'subset', 'criterion': 'equal', 'value': '2', 'result': '2', 'col': '3', 'subset': {'col': '5', 'criterion': 'greater_than', 'value': '10'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'events', '10'], 'result': None, 'ind': 0, 'tostr': 'filter_greater { all_rows ; events ; 10 }', 'tointer': 'select the rows whose events record is greater than 10 .'}, 'top - 10', '2'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose events record is greater than 10 . among these rows , select the rows whose top - 10 record is equal to 2 .', 'tostr': 'filter_eq { filter_greater { all_rows ; events ; 10 } ; top - 10 ; 2 }'}], 'result': '2', 'ind': 2, 'tostr': 'count { filter_eq { filter_greater { all_rows ; events ; 10 } ; top - 10 ; 2 } }', 'tointer': 'select the rows whose events record is greater than 10 . among these rows , select the rows whose top - 10 record is equal to 2 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_eq { filter_greater { all_rows ; events ; 10 } ; top - 10 ; 2 } } ; 2 } = true', 'tointer': 'select the rows whose events record is greater than 10 . among these rows , select the rows whose top - 10 record is equal to 2 . the number of such rows is 2 .'} | eq { count { filter_eq { filter_greater { all_rows ; events ; 10 } ; top - 10 ; 2 } } ; 2 } = true | select the rows whose events record is greater than 10 . among these rows , select the rows whose top - 10 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_greater_0': 0, 'all_rows_5': 5, 'events_6': 6, '10_7': 7, 'top - 10_8': 8, '2_9': 9, '2_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_eq_1': 'filter_eq', 'filter_greater_0': 'filter_greater', 'all_rows_5': 'all_rows', 'events_6': 'events', '10_7': '10', 'top - 10_8': 'top - 10', '2_9': '2', '2_10': '2'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_eq_1': [2], 'filter_greater_0': [1], 'all_rows_5': [0], 'events_6': [0], '10_7': [0], 'top - 10_8': [1], '2_9': [1], '2_10': [3]} | ['tournament', 'wins', 'top - 10', 'top - 25', 'events', 'cuts made'] | [['masters tournament', '0', '3', '8', '11', '10'], ['us open', '0', '2', '3', '12', '8'], ['the open championship', '0', '0', '0', '1', '0'], ['pga championship', '0', '2', '7', '11', '11'], ['totals', '0', '7', '18', '35', '29']] |
dominique sarron | https://en.wikipedia.org/wiki/Dominique_Sarron | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14881553-3.html.csv | aggregation | for dominique sarron from 1985-1992 the total number of wins was 4 . | {'scope': 'all', 'col': '7', 'type': 'sum', 'result': '4', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'wins'], 'result': '4', 'ind': 0, 'tostr': 'sum { all_rows ; wins }'}, '4'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; wins } ; 4 } = true', 'tointer': 'the sum of the wins record of all rows is 4 .'} | round_eq { sum { all_rows ; wins } ; 4 } = true | the sum of the wins record of all rows is 4 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'wins_4': 4, '4_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'wins_4': 'wins', '4_5': '4'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'wins_4': [0], '4_5': [1]} | ['year', 'class', 'team', 'machine', 'points', 'rank', 'wins'] | [['1985', '250cc', 'rothmans - honda france', 'rs250', '7', '21st', '0'], ['1986', '250cc', 'rothmans - honda france', 'nsr250', '72', '3rd', '1'], ['1987', '250cc', 'rothmans - honda france', 'nsr250', '97', '4th', '1'], ['1988', '250cc', 'rothmans - honda france', 'nsr250', '158', '4th', '2'], ['1989', '500cc', 'elf - honda', 'nsr500', '39', '15th', '0'], ['1990', '250cc', 'rothmans - honda', 'nsr250', '78', '10th', '0'], ['1991', '250cc', 'gallina - yamaha', 'tz250', '4', '30th', '0'], ['1992', '500cc', 'banco - yamaha', 'roc yamaha', '2', '23rd', '0']] |
rick cheek | https://en.wikipedia.org/wiki/Rick_Cheek | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18727616-3.html.csv | ordinal | gladiator challenge 87 : collision course was rick cheek 's second fastest match . | {'row': '2', 'col': '7', 'order': '2', 'col_other': '5', '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', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; time ; 2 }'}, 'event'], 'result': 'gladiator challenge 87 : collision course', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; time ; 2 } ; event }'}, 'gladiator challenge 87 : collision course'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; time ; 2 } ; event } ; gladiator challenge 87 : collision course } = true', 'tointer': 'select the row whose time record of all rows is 2nd minimum . the event record of this row is gladiator challenge 87 : collision course .'} | eq { hop { nth_argmin { all_rows ; time ; 2 } ; event } ; gladiator challenge 87 : collision course } = true | select the row whose time record of all rows is 2nd minimum . the event record of this row is gladiator challenge 87 : collision course . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'time_5': 5, '2_6': 6, 'event_7': 7, 'gladiator challenge 87: collision course_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', '2_6': '2', 'event_7': 'event', 'gladiator challenge 87: collision course_8': 'gladiator challenge 87 : collision course'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'time_5': [0], '2_6': [0], 'event_7': [1], 'gladiator challenge 87: collision course_8': [2]} | ['res', 'record', 'opponent', 'method', 'event', 'round', 'time', 'location'] | [['loss', '4 - 4', 'mike hayes', 'submission ( verbal )', 'palace fighting championship : best of both worlds', '2', '1:01', 'lemoore , california , united states'], ['loss', '4 - 3', 'dave huckaba', 'submission ( armbar )', 'gladiator challenge 87 : collision course', '1', '0:37', 'roseville , california , united states'], ['loss', '4 - 2', 'buddy roberts', 'submission ( rear naked choke )', 'cage combat fighting championships : mayhem', '1', '0:52', 'santa rosa , california , united states'], ['win', '4 - 1', 'richard blake', 'ko ( punches )', 'cage combat fighting championships : annihilation', '1', '2:05', 'santa rosa , california , united states'], ['loss', '3 - 1', 'chase gormley', 'submission ( keylock )', 'gladiator challenge 73 : high noon', '2', '2:20', 'sacramento , california , united states'], ['win', '3 - 0', 'thomas rosser', 'tko ( punches )', 'gladiator challenge 63 : crackdown', '1', '1:15', 'south lake tahoe , california , united states'], ['win', '2 - 0', 'joe abouata', 'ko ( punch )', 'gladiator challenge 62 : sprawl or brawl', '1', '0:31', 'lakeport , california , united states'], ['win', '1 - 0', 'dave huckaba', 'tko ( punches )', 'gladiator challenge 57 : holiday beatings', '2', '1:35', 'sacramento , california , united states']] |
1992 open championship | https://en.wikipedia.org/wiki/1992_Open_Championship | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18122130-3.html.csv | count | 2 players in the 1992 open championship finished with a +1 to par . | {'scope': 'all', 'criterion': 'equal', 'value': '+1', 'result': '2', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'to par', '+1'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose to par record fuzzily matches to +1 .', 'tostr': 'filter_eq { all_rows ; to par ; +1 }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; to par ; +1 } }', 'tointer': 'select the rows whose to par record fuzzily matches to +1 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; to par ; +1 } } ; 2 } = true', 'tointer': 'select the rows whose to par record fuzzily matches to +1 . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; to par ; +1 } } ; 2 } = true | select the rows whose to par record fuzzily matches to +1 . 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, 'to par_5': 5, '+1_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', 'to par_5': 'to par', '+1_6': '+1', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'to par_5': [0], '+1_6': [0], '2_7': [2]} | ['player', 'country', 'year ( s ) won', 'total', 'to par'] | [['seve ballesteros', 'spain', '1979 , 1984 , 1988', '145', '+ 1'], ['tom weiskopf', 'united states', '1973', '145', '+ 1'], ['gary player', 'south africa', '1959 , 1968 , 1974', '146', '+ 2'], ['jack nicklaus', 'united states', '1966 , 1970 , 1978', '148', '+ 4'], ['tom watson', 'united states', '1975 , 1977 , 1980 , 1982 , 1983', '148', '+ 4']] |
1998 - 99 chelsea f.c. season | https://en.wikipedia.org/wiki/1998%E2%80%9399_Chelsea_F.C._season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16924792-2.html.csv | count | during the 1998-99 season chelsea played copenhagen 2 times . | {'scope': 'all', 'criterion': 'equal', 'value': 'copenhagen', 'result': '2', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', 'copenhagen'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose opponent record fuzzily matches to copenhagen .', 'tostr': 'filter_eq { all_rows ; opponent ; copenhagen }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; opponent ; copenhagen } }', 'tointer': 'select the rows whose opponent record fuzzily matches to copenhagen . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; opponent ; copenhagen } } ; 2 } = true', 'tointer': 'select the rows whose opponent record fuzzily matches to copenhagen . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; opponent ; copenhagen } } ; 2 } = true | select the rows whose opponent record fuzzily matches to copenhagen . 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, 'opponent_5': 5, 'copenhagen_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', 'opponent_5': 'opponent', 'copenhagen_6': 'copenhagen', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'opponent_5': [0], 'copenhagen_6': [0], '2_7': [2]} | ['date', 'round', 'opponent', 'venue', 'result', 'attendance'] | [['17 september 1998', 'r1', 'helsingborg', 'h', '1 - 0', '17714'], ['1 october 1998', 'r1', 'helsingborg', 'a', '0 - 0', '12348'], ['22 october 1998', 'r2', 'copenhagen', 'h', '1 - 1', '21207'], ['5 november 1998', 'r2', 'copenhagen', 'a', '1 - 0', '24188'], ['4 march 1999', 'qf', 'vålerenga', 'h', '3 - 0', '34177'], ['18 march 1999', 'qf', 'vålerenga', 'a', '3 - 2', '17936'], ['8 april 1999', 'sf', 'mallorca', 'h', '1 - 1', '35524'], ['22 april 1999', 'sf', 'mallorca', 'a', '0 - 1', '18848']] |
tasmania cricket team first - class records | https://en.wikipedia.org/wiki/Tasmania_cricket_team_first-class_records | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14412861-4.html.csv | superlative | the team that tasmania has had the most success against is queensland . | {'scope': 'all', 'col_superlative': '2', 'row_superlative': '5', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '3', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'runs'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; runs }'}, 'opponent'], 'result': 'queensland', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; runs } ; opponent }'}, 'queensland'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; runs } ; opponent } ; queensland } = true', 'tointer': 'select the row whose runs record of all rows is maximum . the opponent record of this row is queensland .'} | eq { hop { argmax { all_rows ; runs } ; opponent } ; queensland } = true | select the row whose runs record of all rows is maximum . the opponent record of this row is queensland . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'runs_5': 5, 'opponent_6': 6, 'queensland_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'runs_5': 'runs', 'opponent_6': 'opponent', 'queensland_7': 'queensland'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'runs_5': [0], 'opponent_6': [1], 'queensland_7': [2]} | ['rank', 'runs', 'opponent', 'venue', 'season'] | [['1', '50', 'victoria', 'launceston cricket club ground , launceston', '1853 / 54'], ['2', '53', 'new south wales', 'bellerive oval , hobart', '2006 / 07'], ['3', '55', 'south australia', 'bellerive oval , hobart', '2010 / 11'], ['4', '57', 'victoria', 'launceston cricket club ground , launceston', '1850 / 51'], ['5', '62', 'queensland', 'gabba , brisbane', '2008 / 09']] |
1977 atlanta falcons season | https://en.wikipedia.org/wiki/1977_Atlanta_Falcons_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17183877-2.html.csv | unique | the crowd on october 30th was the only crowd that was over 59000 people . | {'scope': 'all', 'row': '7', 'col': '5', 'col_other': '2', 'criterion': 'greater_than', 'value': '59000', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'attendance', '59000'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose attendance record is greater than 59000 .', 'tostr': 'filter_greater { all_rows ; attendance ; 59000 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_greater { all_rows ; attendance ; 59000 } }', 'tointer': 'select the rows whose attendance record is greater than 59000 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'attendance', '59000'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose attendance record is greater than 59000 .', 'tostr': 'filter_greater { all_rows ; attendance ; 59000 }'}, 'date'], 'result': 'october 30 , 1977', 'ind': 2, 'tostr': 'hop { filter_greater { all_rows ; attendance ; 59000 } ; date }'}, 'october 30 , 1977'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_greater { all_rows ; attendance ; 59000 } ; date } ; october 30 , 1977 }', 'tointer': 'the date record of this unqiue row is october 30 , 1977 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_greater { all_rows ; attendance ; 59000 } } ; eq { hop { filter_greater { all_rows ; attendance ; 59000 } ; date } ; october 30 , 1977 } } = true', 'tointer': 'select the rows whose attendance record is greater than 59000 . there is only one such row in the table . the date record of this unqiue row is october 30 , 1977 .'} | and { only { filter_greater { all_rows ; attendance ; 59000 } } ; eq { hop { filter_greater { all_rows ; attendance ; 59000 } ; date } ; october 30 , 1977 } } = true | select the rows whose attendance record is greater than 59000 . there is only one such row in the table . the date record of this unqiue row is october 30 , 1977 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_greater_0': 0, 'all_rows_6': 6, 'attendance_7': 7, '59000_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'date_9': 9, 'october 30 , 1977_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_greater_0': 'filter_greater', 'all_rows_6': 'all_rows', 'attendance_7': 'attendance', '59000_8': '59000', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'date_9': 'date', 'october 30 , 1977_10': 'october 30 , 1977'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_greater_0': [1, 2], 'all_rows_6': [0], 'attendance_7': [0], '59000_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'date_9': [2], 'october 30 , 1977_10': [3]} | ['week', 'date', 'opponent', 'result', 'attendance'] | [['1', 'september 18 , 1977', 'los angeles rams', 'w 17 - 6', '55956'], ['2', 'september 25 , 1977', 'washington redskins', 'l 10 - 6', '55031'], ['3', 'october 2 , 1977', 'new york giants', 'w 17 - 3', '46374'], ['4', 'october 9 , 1977', 'san francisco 49ers', 'w 7 - 0', '38009'], ['5', 'october 16 , 1977', 'buffalo bills', 'l 3 - 0', '27348'], ['6', 'october 23 , 1977', 'chicago bears', 'w 16 - 10', '49407'], ['7', 'october 30 , 1977', 'minnesota vikings', 'l 14 - 7', '59257'], ['8', 'november 6 , 1977', 'san francisco 49ers', 'l 10 - 3', '46577'], ['9', 'november 13 , 1977', 'detroit lions', 'w 17 - 6', '47461'], ['10', 'november 20 , 1977', 'new orleans saints', 'l 21 - 20', '43135'], ['11', 'november 27 , 1977', 'tampa bay buccaneers', 'w 17 - 0', '43592'], ['12', 'december 4 , 1977', 'new england patriots', 'l 16 - 10', '57911'], ['13', 'december 11 , 1977', 'los angeles rams', 'l 23 - 7', '52574'], ['14', 'december 18 , 1977', 'new orleans saints', 'w 35 - 7', '36895']] |
2009 swedish touring car championship season | https://en.wikipedia.org/wiki/2009_Swedish_Touring_Car_Championship_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-20079931-4.html.csv | majority | robert dahlgren set the fatest lap at most of the races at mantorp park durin the 2009 swedish touring car championship season . | {'scope': 'subset', 'col': '4', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'robert dahlgren', 'subset': {'col': '2', 'criterion': 'equal', 'value': 'mantorp park'}} | {'func': 'most_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'circuit / location', 'mantorp park'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; circuit / location ; mantorp park }', 'tointer': 'select the rows whose circuit / location record fuzzily matches to mantorp park .'}, 'fastest lap', 'robert dahlgren'], 'result': True, 'ind': 1, 'tointer': 'select the rows whose circuit / location record fuzzily matches to mantorp park . for the fastest lap records of these rows , most of them fuzzily match to robert dahlgren .', 'tostr': 'most_eq { filter_eq { all_rows ; circuit / location ; mantorp park } ; fastest lap ; robert dahlgren } = true'} | most_eq { filter_eq { all_rows ; circuit / location ; mantorp park } ; fastest lap ; robert dahlgren } = true | select the rows whose circuit / location record fuzzily matches to mantorp park . for the fastest lap records of these rows , most of them fuzzily match to robert dahlgren . | 2 | 2 | {'most_str_eq_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, 'circuit / location_4': 4, 'mantorp park_5': 5, 'fastest lap_6': 6, 'robert dahlgren_7': 7} | {'most_str_eq_1': 'most_str_eq', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'circuit / location_4': 'circuit / location', 'mantorp park_5': 'mantorp park', 'fastest lap_6': 'fastest lap', 'robert dahlgren_7': 'robert dahlgren'} | {'most_str_eq_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'circuit / location_4': [0], 'mantorp park_5': [0], 'fastest lap_6': [1], 'robert dahlgren_7': [1]} | ['round', 'circuit / location', 'pole position', 'fastest lap', 'winning driver', 'winning team', 'highest scoring team', 'winning privateer'] | [['1', 'mantorp park', 'robert dahlgren', 'robert dahlgren', 'robert dahlgren', 'polestar racing', 'flash engineering', 'johan kristoffersson'], ['2', 'mantorp park', 'thomas schie', 'thed björk', 'richard göransson', 'westcoast racing', 'flash engineering', 'johan kristoffersson'], ['3', 'karlskoga motorstadion', 'robin rudholm', 'robin rudholm', 'robin rudholm', 'westcoast racing', 'westcoast racing', 'johan kristoffersson'], ['4', 'karlskoga motorstadion', 'roger eriksson', 'robin rudholm', 'robin rudholm', 'westcoast racing', 'westcoast racing', 'viktor hallrup'], ['5', 'göteborg city race', 'tommy rustad', 'robert dahlgren', 'tommy rustad', 'polestar racing', 'ma : gp / ips', 'andreas simonsen'], ['6', 'göteborg city race', 'fredrik ekblom', 'robert dahlgren', 'tomas engström', 'engström motorsport', 'ma : gp / ips', 'viktor hallrup'], ['7', 'ring knutstorp', 'robert dahlgren', 'robin rudholm', 'robert dahlgren', 'polestar racing', 'westcoast racing', 'dick sahlén'], ['8', 'ring knutstorp', 'roger eriksson', 'robin rudholm', 'jan nilsson', 'flash engineering', 'westcoast racing', 'dick sahlén'], ['9', 'falkenbergs motorbana', 'tommy rustad', 'tommy rustad', 'tommy rustad', 'polestar racing', 'westcoast racing', 'johan kristoffersson'], ['10', 'falkenbergs motorbana', 'tomas engström', 'thed björk', 'richard göransson', 'westcoast racing', 'westcoast racing', 'andreas simonsen'], ['11', 'karlskoga motorstadion', 'robert dahlgren', 'jan nilsson', 'jan nilsson', 'flash engineering', 'westcoast racing', 'tony johansson'], ['12', 'karlskoga motorstadion', 'patrik olsson', 'robert dahlgren', 'robert dahlgren', 'polestar racing', 'westcoast racing', 'dick sahlén'], ['13', 'vålerbanen', 'robert dahlgren', 'tommy rustad', 'tommy rustad', 'polestar racing', 'polestar racing', 'viktor hallrup'], ['14', 'vålerbanen', 'pontus mörth', 'thed björk', 'tommy rustad', 'polestar racing', 'polestar racing', 'dick sahlén'], ['15', 'ring knutstorp', 'robert dahlgren', 'robert dahlgren', 'richard göransson', 'westcoast racing', 'ma : gp / ips', 'viktor hallrup'], ['16', 'ring knutstorp', 'patrik olsson', 'thed björk', 'johan stureson', 'ips motorsport', 'ma : gp / ips', 'mikael ohlsson'], ['17', 'mantorp park', 'robin rudholm ♯', 'robert dahlgren', 'tommy rustad', 'polestar racing', 'polestar racing', 'johan kristoffersson']] |
silent witness | https://en.wikipedia.org/wiki/Silent_Witness | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-143678-3.html.csv | count | three characters in " silent witness " appeared in more than 80 episodes . | {'scope': 'all', 'criterion': 'greater_than', 'value': '80', 'result': '3', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'episode count', '80'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose episode count record is greater than 80 .', 'tostr': 'filter_greater { all_rows ; episode count ; 80 }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_greater { all_rows ; episode count ; 80 } }', 'tointer': 'select the rows whose episode count record is greater than 80 . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_greater { all_rows ; episode count ; 80 } } ; 3 } = true', 'tointer': 'select the rows whose episode count record is greater than 80 . the number of such rows is 3 .'} | eq { count { filter_greater { all_rows ; episode count ; 80 } } ; 3 } = true | select the rows whose episode count record is greater than 80 . the number of such rows is 3 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_greater_0': 0, 'all_rows_4': 4, 'episode count_5': 5, '80_6': 6, '3_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_greater_0': 'filter_greater', 'all_rows_4': 'all_rows', 'episode count_5': 'episode count', '80_6': '80', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_greater_0': [1], 'all_rows_4': [0], 'episode count_5': [0], '80_6': [0], '3_7': [2]} | ['character', 'actor', 'years', 'series', 'episode count'] | [['dr nikki alexander', 'emilia fox', '2004 -', '8.5 -', '86'], ['dr jack hodgson', 'david caves', '2013 -', '16.1 -', '10'], ['dr clarissa mullery', 'liz carr', '2013 -', '16.1 -', '10'], ['dr thomas chamberlain', 'richard lintern', '2014 -', '17 . -', '0'], ['professor sam ryan', 'amanda burton', '1996 - 2004', '1.1 - 8.2', '54'], ['professor leo dalton', 'william gaminara', '2002 - 2013', '6.1 - 16.10', '106'], ['dr harry cunningham', 'tom ward', '2002 - 2012', '6.1 - 15.10', '96'], ['dr trevor stewart', 'william armstrong', '1996 - 1998', '1.1 - 3.8', '24']] |
2008 atlanta dream season | https://en.wikipedia.org/wiki/2008_Atlanta_Dream_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17103645-10.html.csv | count | the atlanta dream played against chicago two times in 2008 . | {'scope': 'all', 'criterion': 'equal', 'value': 'chicago', 'result': '2', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', 'chicago'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose opponent record fuzzily matches to chicago .', 'tostr': 'filter_eq { all_rows ; opponent ; chicago }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; opponent ; chicago } }', 'tointer': 'select the rows whose opponent record fuzzily matches to chicago . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; opponent ; chicago } } ; 2 } = true', 'tointer': 'select the rows whose opponent record fuzzily matches to chicago . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; opponent ; chicago } } ; 2 } = true | select the rows whose opponent record fuzzily matches to chicago . 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, 'opponent_5': 5, 'chicago_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', 'opponent_5': 'opponent', 'chicago_6': 'chicago', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'opponent_5': [0], 'chicago_6': [0], '2_7': [2]} | ['game', 'date', 'opponent', 'score', 'high points', 'high rebounds', 'high assists', 'location / attendance', 'record'] | [['16', 'july 1', 'phoenix', '79 - 97', 'lennox ( 18 )', 'lovelace , young ( 7 )', 'latta ( 5 )', 'philips arena 9795', '0 - 16'], ['17', 'july 3', 'houston', '65 - 72', 'lennox ( 15 )', 'feenstra ( 9 )', 'haynie , strother ( 3 )', 'philips arena 7430', '0 - 17'], ['18', 'july 5', 'chicago', '91 - 84', 'lacy , latta ( 18 )', 'young ( 8 )', 'haynie ( 11 )', 'philips arena 8468', '1 - 17'], ['19', 'july 9', 'minnesota', '73 - 67', 'lennox ( 24 )', 'bales ( 11 )', 'haynie ( 5 )', 'target center 5893', '2 - 17'], ['20', 'july 11', 'san antonio', '74 - 82', 'lennox ( 22 )', 'bales ( 9 )', 'lennox ( 4 )', 'at & t center 10943', '2 - 18'], ['21', 'july 13', 'chicago', '66 - 79', 'feenstra ( 21 )', 'feenstra ( 8 )', 'feenstra , haynie , lennox ( 2 )', 'uic pavilion 2907', '2 - 19'], ['22', 'july 16', 'indiana', '81 - 77', 'castro marques ( 24 )', 'bales ( 11 )', 'haynie ( 7 )', 'conseco fieldhouse 9303', '3 - 19'], ['23', 'july 18', 'sacramento', '73 - 77', 'haynie ( 12 )', 'feenstra ( 8 )', 'haynie ( 4 )', 'arco arena 7236', '3 - 20'], ['24', 'july 19', 'phoenix', '84 - 110', 'latta ( 18 )', 'terry ( 11 )', 'latta ( 3 )', 'us airways center 7913', '3 - 21'], ['25', 'july 22', 'sacramento', '66 - 79', 'terry , latta ( 15 )', 'terry ( 9 )', 'haynie ( 4 )', 'philips arena 10431', '3 - 22'], ['26', 'july 25', 'washington', '75 - 81', 'castro marques ( 23 )', 'bales ( 7 )', 'haynie ( 3 )', 'philips arena 8279', '3 - 23'], ['27', 'july 27', 'new york', '76 - 86', 'lennox ( 18 )', 'desouza ( 11 )', 'latta ( 5 )', 'philips arena 8759', '3 - 24']] |
colorado mountain passes | https://en.wikipedia.org/wiki/Colorado_mountain_passes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14926835-2.html.csv | count | the elevation of three colorado mountain passes is more than 12000 feet . | {'scope': 'all', 'criterion': 'greater_than', 'value': '12000 feet', 'result': '3', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'elevation', '12000 feet'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose elevation record is greater than 12000 feet .', 'tostr': 'filter_greater { all_rows ; elevation ; 12000 feet }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_greater { all_rows ; elevation ; 12000 feet } }', 'tointer': 'select the rows whose elevation record is greater than 12000 feet . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_greater { all_rows ; elevation ; 12000 feet } } ; 3 } = true', 'tointer': 'select the rows whose elevation record is greater than 12000 feet . the number of such rows is 3 .'} | eq { count { filter_greater { all_rows ; elevation ; 12000 feet } } ; 3 } = true | select the rows whose elevation record is greater than 12000 feet . the number of such rows is 3 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_greater_0': 0, 'all_rows_4': 4, 'elevation_5': 5, '12000 feet_6': 6, '3_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_greater_0': 'filter_greater', 'all_rows_4': 'all_rows', 'elevation_5': 'elevation', '12000 feet_6': '12000 feet', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_greater_0': [1], 'all_rows_4': [0], 'elevation_5': [0], '12000 feet_6': [0], '3_7': [2]} | ['rank', 'highway', 'elevation', 'surface', 'route'] | [['1', 'mount evans scenic byway', '14160 feet 4316 m', 'asphalt', '005'], ['2', 'pikes peak highway', '14115 feet 4302 m', 'asphalt', '999'], ['3', 'trail ridge road', '12183 feet 3713 m', 'asphalt', '034'], ['4', 'eisenhower tunnel', '11158 feet 3401 m', 'concrete', '070'], ['5', 'warrior mountain summit', '11140 feet 3395 m', 'asphalt', '103'], ['6', 'grand mesa summit', '10839 feet 3304 m', 'asphalt', '065'], ['7', 'battle mountain summit', '0 9267 feet 2825 m', 'asphalt', '024'], ['8', 'black mesa summit', '0 9121 feet 2780 m', 'asphalt', '092'], ['9', 'wondervu hill', '0 8660 feet 2640 m', 'asphalt', '072']] |
1986 - 87 football conference | https://en.wikipedia.org/wiki/1986%E2%80%9387_Football_Conference | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15559220-4.html.csv | ordinal | maidstone united had the third highest total in the 1986-1987 football conference . | {'row': '3', 'col': '7', 'order': '3', 'col_other': '2', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'total', '3'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; total ; 3 }'}, 'club'], 'result': 'maidstone united', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; total ; 3 } ; club }'}, 'maidstone united'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; total ; 3 } ; club } ; maidstone united } = true', 'tointer': 'select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .'} | eq { hop { nth_argmax { all_rows ; total ; 3 } ; club } ; maidstone united } = true | select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'total_5': 5, '3_6': 6, 'club_7': 7, 'maidstone united_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', '3_6': '3', 'club_7': 'club', 'maidstone united_8': 'maidstone united'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'total_5': [0], '3_6': [0], 'club_7': [1], 'maidstone united_8': [2]} | ['player', 'club', 'league', 'fa cup', 'fa trophy', 'league cup', 'total'] | [['kim casey', 'kidderminster harriers', '38', '4', '2', '0', '44'], ['mick carter', 'runcorn', '30', '2', '6', '3', '41'], ['steve butler', 'maidstone united', '24', '5', '3', '2', '34'], ['gary abbott', 'welling united', '23', '2', '3', '0', '28'], ['chris cook', 'boston united', '23', '0', '2', '2', '27'], ['ken mckenna', 'telford united', '23', '1', '0', '0', '24'], ['nicky evans', 'barnet', '22', '0', '4', '0', '26'], ['chris townsend', 'cheltenham town', '22', '1', '0', '0', '23'], ['mike doherty', 'weymouth', '16', '0', '1', '1', '18'], ['paul bodin', 'bath city', '16', '2', '2', '1', '21'], ['stewart mell', 'scarborough', '16', '0', '2', '0', '18'], ['john timmons', 'altrincham', '16', '0', '0', '1', '17']] |
1982 - 83 north west counties football league | https://en.wikipedia.org/wiki/1982%E2%80%9383_North_West_Counties_Football_League | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17716055-3.html.csv | majority | all teams which participated in the 1982 - 83 north west counties football league games each played 34 matches . | {'scope': 'all', 'col': '3', 'most_or_all': 'all', 'criterion': 'equal', 'value': '34', 'subset': None} | {'func': 'all_eq', 'args': ['all_rows', 'played', '34'], 'result': True, 'ind': 0, 'tointer': 'for the played records of all rows , all of them are equal to 34 .', 'tostr': 'all_eq { all_rows ; played ; 34 } = true'} | all_eq { all_rows ; played ; 34 } = true | for the played records of all rows , all of them are equal to 34 . | 1 | 1 | {'all_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'played_3': 3, '34_4': 4} | {'all_eq_0': 'all_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'played_3': 'played', '34_4': '34'} | {'all_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'played_3': [0], '34_4': [0]} | ['position', 'team', 'played', 'drawn', 'lost', 'goals for', 'goals against', 'goal difference', 'points 1'] | [['1', 'colne dynamoes', '34', '5', '4', '95', '37', '+ 58', '55'], ['2', 'warrington town', '34', '6', '4', '83', '33', '+ 50', '54'], ['3', 'clitheroe', '34', '7', '5', '87', '35', '+ 52', '51'], ['4', 'prestwich heys', '34', '11', '5', '70', '37', '+ 33', '47'], ['5', 'vulcan newton', '34', '10', '11', '70', '65', '+ 5', '36'], ['6', 'blackpool mechanics', '34', '13', '10', '67', '56', '+ 11', '35'], ['7', 'bacup borough', '34', '7', '13', '53', '45', '+ 8', '35'], ['8', 'atherton collieries', '34', '11', '11', '55', '57', '2', '35'], ['9', 'whitworth valley', '34', '9', '12', '54', '65', '11', '35'], ['10', 'nelson', '34', '16', '11', '49', '56', '7', '28'], ['11', 'daisy hill', '34', '10', '14', '47', '58', '11', '30'], ['12', 'maghull', '34', '9', '15', '56', '61', '5', '29'], ['13', 'ashton town', '34', '5', '17', '53', '73', '20', '29'], ['14', 'newton', '34', '12', '14', '59', '62', '3', '28'], ['15', 'oldham dew', '34', '8', '16', '48', '61', '13', '28'], ['16', 'bolton st', '34', '6', '19', '50', '84', '34', '24'], ['17', 'wigan rovers', '34', '7', '22', '35', '72', '37', '17'], ['18', 'ashton athletic', '34', '8', '23', '18', '92', '74', '14']] |
henlopen conference | https://en.wikipedia.org/wiki/Henlopen_Conference | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13054553-18.html.csv | majority | the majority of the teams at the henlopen conference failed to make the playoffs . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'failed to make playoffs', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'season outcome', 'failed to make playoffs'], 'result': True, 'ind': 0, 'tointer': 'for the season outcome records of all rows , most of them fuzzily match to failed to make playoffs .', 'tostr': 'most_eq { all_rows ; season outcome ; failed to make playoffs } = true'} | most_eq { all_rows ; season outcome ; failed to make playoffs } = true | for the season outcome records of all rows , most of them fuzzily match to failed to make playoffs . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'season outcome_3': 3, 'failed to make playoffs_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'season outcome_3': 'season outcome', 'failed to make playoffs_4': 'failed to make playoffs'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'season outcome_3': [0], 'failed to make playoffs_4': [0]} | ['school', 'team', 'division record', 'overall record', 'season outcome'] | [['indian river', 'indians', '6 - 0', '12 - 0', 'won div ii state championship'], ['delmar', 'wildcats', '5 - 1', '9 - 2', 'loss in first round of div ii playoffs'], ['laurel', 'bulldogs', '4 - 2', '4 - 6', 'failed to make playoffs'], ['lake forest', 'spartans', '3 - 3', '5 - 5', 'failed to make playoffs'], ['polytech', 'panthers', '2 - 4', '2 - 8', 'failed to make playoffs'], ['woodbridge', 'blue raiders', '1 - 5', '2 - 8', 'failed to make playoffs'], ['seaford', 'blue jays', '0 - 6', '0 - 10', 'failed to make playoffs']] |
1994 - 95 cleveland cavaliers season | https://en.wikipedia.org/wiki/1994%E2%80%9395_Cleveland_Cavaliers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16188254-3.html.csv | aggregation | the cleveland cavaliers scored a total of 1258 points in its 1994 to 1995 season . | {'scope': 'all', 'col': '3', 'type': 'sum', 'result': '1258', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'score'], 'result': '1258', 'ind': 0, 'tostr': 'sum { all_rows ; score }'}, '1258'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; score } ; 1258 } = true', 'tointer': 'the sum of the score record of all rows is 1258 .'} | round_eq { sum { all_rows ; score } ; 1258 } = true | the sum of the score record of all rows is 1258 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'score_4': 4, '1258_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'score_4': 'score', '1258_5': '1258'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'score_4': [0], '1258_5': [1]} | ['date', 'visitor', 'score', 'home', 'leading scorer', 'attendance', 'record'] | [['november 5', 'cleveland', '115 - 107', 'charlotte', 'mark price , 27 points', 'charlotte coliseum 23698', '1 - 0'], ['november 8', 'houston', '100 - 98', 'cleveland', 'terrell brandon , 19 points', 'gund arena 20562', '1 - 1'], ['november 10', 'milwaukee', '88 - 108', 'cleveland', 'mark price , 18 points', 'gund arena 19203', '2 - 1'], ['november 12', 'indiana', '93 - 86', 'cleveland', 'mark price , 15 points', 'gund arena 20401', '2 - 2'], ['november 15', 'charlotte', '86 - 89', 'cleveland', 'tyrone hill , 22 points', 'gund arena 19959', '3 - 2'], ['november 17', 'cleveland', '81 - 80', 'portland', 'mark price , 30 points', 'memorial coliseum 12888', '4 - 2'], ['november 18', 'cleveland', '80 - 82', 'la lakers', 'hot rod williams , 16 points', 'great western forum 10177', '4 - 3'], ['november 20', 'cleveland', '88 - 96', 'sacramento', 'hot rod williams , 17 points', 'arco arena 17317', '4 - 4'], ['november 22', 'minnesota', '79 - 112', 'cleveland', 'mark price , 17 points', 'gund arena 19125', '5 - 4'], ['november 23', 'cleveland', '87 - 100', 'miami', '2 way tie , 17 points', 'miami arena 14498', '5 - 5'], ['november 25', 'cleveland', '96 - 94', 'washington', 'tyrone hill , 25 points', 'usair arena 12756', '6 - 5'], ['november 26', 'golden state', '87 - 101', 'cleveland', 'mark price , 31 points', 'gund arena 20562', '7 - 5'], ['november 30', 'la lakers', '79 - 117', 'cleveland', '3 way tie , 16 points', 'gund arena 19014', '8 - 5']] |
1991 open championship | https://en.wikipedia.org/wiki/1991_Open_Championship | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18131508-5.html.csv | superlative | in the 1991 open championship , gary hallberg ranks the highest . | {'scope': 'all', 'col_superlative': '1', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '2', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmin', 'args': ['all_rows', 'place'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; place }'}, 'player'], 'result': 'gary hallberg', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; place } ; player }'}, 'gary hallberg'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmin { all_rows ; place } ; player } ; gary hallberg } = true', 'tointer': 'select the row whose place record of all rows is minimum . the player record of this row is gary hallberg .'} | eq { hop { argmin { all_rows ; place } ; player } ; gary hallberg } = true | select the row whose place record of all rows is minimum . the player record of this row is gary hallberg . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'place_5': 5, 'player_6': 6, 'gary hallberg_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'place_5': 'place', 'player_6': 'player', 'gary hallberg_7': 'gary hallberg'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'place_5': [0], 'player_6': [1], 'gary hallberg_7': [2]} | ['place', 'player', 'country', 'score', 'to par'] | [['t1', 'gary hallberg', 'united states', '68 + 70 = 138', '- 2'], ['t1', 'mike harwood', 'australia', '68 + 70 = 138', '- 2'], ['t1', 'andrew oldcorn', 'scotland', '71 + 67 = 138', '- 2'], ['t4', 'seve ballesteros', 'spain', '66 + 73 = 139', '- 1'], ['t4', 'steve elkington', 'australia', '71 + 68 = 139', '- 1'], ['t4', 'david gilford', 'england', '72 + 67 = 139', '- 1'], ['t4', 'wayne grady', 'australia', '69 + 70 = 139', '- 1'], ['t4', "mark o'meara", 'united states', '71 + 68 = 139', '- 1'], ['t4', 'mike reid', 'united states', '68 + 71 = 139', '- 1'], ['t10', 'richard boxall', 'england', '71 + 69 = 140', 'e'], ['t10', 'roger chapman', 'england', '74 + 66 = 140', 'e'], ['t10', 'howard clark', 'england', '71 + 69 = 140', 'e'], ['t10', 'mark james', 'england', '72 + 68 = 140', 'e'], ['t10', 'barry lane', 'england', '68 + 72 = 140', 'e'], ['t10', 'colin montgomerie', 'scotland', '71 + 69 = 140', 'e'], ['t10', 'vijay singh', 'fiji', '71 + 69 = 140', 'e']] |
1996 u.s. open ( golf ) | https://en.wikipedia.org/wiki/1996_U.S._Open_%28golf%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17162199-6.html.csv | count | in the 1996 u.s. open , 4 players made more than $ 100000 . | {'scope': 'all', 'criterion': 'greater_than', 'value': '100000', 'result': '4', 'col': '6', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'money', '100000'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose money record is greater than 100000 .', 'tostr': 'filter_greater { all_rows ; money ; 100000 }'}], 'result': '4', 'ind': 1, 'tostr': 'count { filter_greater { all_rows ; money ; 100000 } }', 'tointer': 'select the rows whose money record is greater than 100000 . the number of such rows is 4 .'}, '4'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_greater { all_rows ; money ; 100000 } } ; 4 } = true', 'tointer': 'select the rows whose money record is greater than 100000 . the number of such rows is 4 .'} | eq { count { filter_greater { all_rows ; money ; 100000 } } ; 4 } = true | select the rows whose money record is greater than 100000 . the number of such rows is 4 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_greater_0': 0, 'all_rows_4': 4, 'money_5': 5, '100000_6': 6, '4_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_greater_0': 'filter_greater', 'all_rows_4': 'all_rows', 'money_5': 'money', '100000_6': '100000', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_greater_0': [1], 'all_rows_4': [0], 'money_5': [0], '100000_6': [0], '4_7': [2]} | ['place', 'player', 'country', 'score', 'to par', 'money'] | [['1', 'steve jones', 'united states', '74 + 66 + 69 + 69 = 278', '- 2', '425000'], ['t2', 'tom lehman', 'united states', '71 + 72 + 65 + 71 = 279', '- 1', '204801'], ['t2', 'davis love iii', 'united states', '71 + 69 + 70 + 69 = 279', '- 1', '204801'], ['4', 'john morse', 'united states', '68 + 74 + 68 + 70 = 280', 'e', '111235'], ['t5', 'ernie els', 'south africa', '72 + 67 + 72 + 70 = 281', '+ 1', '84965'], ['t5', 'jim furyk', 'united states', '72 + 69 + 70 + 70 = 281', '+ 1', '84965'], ['t7', 'ken green', 'united states', '73 + 67 + 72 + 70 = 282', '+ 2', '66295'], ['t7', 'scott hoch', 'united states', '73 + 71 + 71 + 67 = 282', '+ 2', '66295'], ['t7', 'vijay singh', 'fiji', '71 + 72 + 70 + 69 = 282', '+ 2', '66295'], ['t10', 'lee janzen', 'united states', '68 + 75 + 71 + 69 = 283', '+ 3', '52591'], ['t10', 'colin montgomerie', 'scotland', '70 + 72 + 69 + 72 = 283', '+ 3', '52591'], ['t10', 'greg norman', 'australia', '73 + 66 + 74 + 70 = 283', '+ 3', '52591']] |
chung kyung - ho | https://en.wikipedia.org/wiki/Chung_Kyung-Ho | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1385043-2.html.csv | aggregation | chung kyung - ho scored a total of two goals in friendly matches in january 2005 . | {'scope': 'subset', 'col': '3', 'type': 'sum', 'result': '2', 'subset': {'col': '1', 'criterion': 'fuzzily_match', 'value': 'january'}} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', 'january'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; date ; january }', 'tointer': 'select the rows whose date record fuzzily matches to january .'}, 'score'], 'result': '2', 'ind': 1, 'tostr': 'sum { filter_eq { all_rows ; date ; january } ; score }'}, '2'], 'result': True, 'ind': 2, 'tostr': 'round_eq { sum { filter_eq { all_rows ; date ; january } ; score } ; 2 } = true', 'tointer': 'select the rows whose date record fuzzily matches to january . the sum of the score record of these rows is 2 .'} | round_eq { sum { filter_eq { all_rows ; date ; january } ; score } ; 2 } = true | select the rows whose date record fuzzily matches to january . the sum of the score record of these rows is 2 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'sum_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'date_5': 5, 'january_6': 6, 'score_7': 7, '2_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'sum_1': 'sum', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'date_5': 'date', 'january_6': 'january', 'score_7': 'score', '2_8': '2'} | {'eq_2': [3], 'result_3': [], 'sum_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'date_5': [0], 'january_6': [0], 'score_7': [1], '2_8': [2]} | ['date', 'venue', 'score', 'result', 'competition'] | [['september 29 , 2003', 'incheon', '1 goal', '16 - 0', '2004 afc asian cup qualification'], ['october 21 , 2003', 'muscat', '1 goal', '1 - 3', '2004 afc asian cup qualification'], ['october 24 , 2003', 'muscat', '1 goal', '7 - 0', '2004 afc asian cup qualification'], ['january 15 , 2005', 'los angeles', '1 goal', '1 - 2', 'friendly match'], ['january 22 , 2005', 'carson', '1 goal', '1 - 1', 'friendly match'], ['june 8 , 2005', 'kuwait city', '1 goal', '4 - 0', '2006 fifa world cup qualification']] |
list of sumo record holders | https://en.wikipedia.org/wiki/List_of_sumo_record_holders | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17634218-21.html.csv | majority | all of the sumo record holders hold a maegashira type rank . | {'scope': 'all', 'col': '5', 'most_or_all': 'all', 'criterion': 'fuzzily_match', 'value': 'maegashira', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'highest rank', 'maegashira'], 'result': True, 'ind': 0, 'tointer': 'for the highest rank records of all rows , all of them fuzzily match to maegashira .', 'tostr': 'all_eq { all_rows ; highest rank ; maegashira } = true'} | all_eq { all_rows ; highest rank ; maegashira } = true | for the highest rank records of all rows , all of them fuzzily match to maegashira . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'highest rank_3': 3, 'maegashira_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'highest rank_3': 'highest rank', 'maegashira_4': 'maegashira'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'highest rank_3': [0], 'maegashira_4': [0]} | ['name', 'tournaments', 'pro debut', 'top division debut', 'highest rank'] | [['hoshiiwato', '115', 'may 1970', 'july 1989', 'maegashira 14'], ['kyokunankai', '105', 'march 1993', 'september 2010', 'maegashira 16'], ['yoshiazuma', '93', 'january 1996', 'september 2011', 'maegashira 12'], ['kotokasuga', '91', 'march 1993', 'may 2008', 'maegashira 7'], ['kototsubaki', '89', 'march 1976', 'january 1991', 'maegashira 3'], ['toyozakura', '88', 'march 1989', 'november 2003', 'maegashira 5'], ['takanomine', '87', 'september 1974', 'march 1989', 'maegashira 12'], ['kitazakura', '86', 'march 1987', 'july 2001', 'maegashira 9'], ['daimanazuru', '85', 'may 1992', 'july 2006', 'maegashira 16'], ['ånohana', '84', 'march 1974', 'march 1988', 'maegashira 13']] |
1972 baltimore colts season | https://en.wikipedia.org/wiki/1972_Baltimore_Colts_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14959246-2.html.csv | superlative | the largest crowd occurred in the game on december 16 , 1972 . | {'scope': 'all', 'col_superlative': '7', 'row_superlative': '14', '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', 'attendance'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; attendance }'}, 'date'], 'result': 'december 16 , 1972', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; attendance } ; date }'}, 'december 16 , 1972'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; attendance } ; date } ; december 16 , 1972 } = true', 'tointer': 'select the row whose attendance record of all rows is maximum . the date record of this row is december 16 , 1972 .'} | eq { hop { argmax { all_rows ; attendance } ; date } ; december 16 , 1972 } = true | select the row whose attendance record of all rows is maximum . the date record of this row is december 16 , 1972 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'attendance_5': 5, 'date_6': 6, 'december 16 , 1972_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'attendance_5': 'attendance', 'date_6': 'date', 'december 16 , 1972_7': 'december 16 , 1972'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'attendance_5': [0], 'date_6': [1], 'december 16 , 1972_7': [2]} | ['week', 'date', 'opponent', 'result', 'record', 'game site', 'attendance'] | [['1', 'september 17 , 1972', 'st louis cardinals', 'l 3 - 10', '0 - 1', 'memorial stadium', '53562'], ['2', 'september 24 , 1972', 'new york jets', 'l 34 - 44', '0 - 2', 'memorial stadium', '56626'], ['3', 'october 1 , 1972', 'buffalo bills', 'w 17 - 0', '1 - 2', 'war memorial stadium', '46206'], ['4', 'october 8 , 1972', 'san diego chargers', 'l 20 - 23', '1 - 3', 'memorial stadium', '55459'], ['5', 'october 15 , 1972', 'dallas cowboys', 'l 0 - 21', '1 - 4', 'memorial stadium', '58992'], ['6', 'october 22 , 1972', 'new york jets', 'l 20 - 24', '1 - 5', 'shea stadium', '62948'], ['7', 'october 29 , 1972', 'miami dolphins', 'l 0 - 23', '1 - 6', 'memorial stadium', '60000'], ['8', 'november 6 , 1972', 'new england patriots', 'w 24 - 17', '2 - 6', 'schaefer stadium', '60999'], ['9', 'november 12 , 1972', 'san francisco 49ers', 'l 21 - 24', '2 - 7', 'candlestick park', '61214'], ['10', 'november 19 , 1972', 'cincinnati bengals', 'w 20 - 19', '3 - 7', 'riverfront stadium', '49512'], ['11', 'november 26 , 1972', 'new england patriots', 'w 31 - 0', '4 - 7', 'memorial stadium', '54907'], ['12', 'december 3 , 1972', 'buffalo bills', 'w 35 - 7', '5 - 7', 'memorial stadium', '55390'], ['13', 'december 10 , 1972', 'kansas city chiefs', 'l 10 - 24', '5 - 8', 'arrowhead stadium', '44175'], ['14', 'december 16 , 1972', 'miami dolphins', 'l 0 - 16', '5 - 9', 'miami orange bowl', '80010']] |
baie - comeau drakkar | https://en.wikipedia.org/wiki/Baie-Comeau_Drakkar | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1259985-1.html.csv | unique | the 1997-1998 season was the only one where baie - comeau drakkar had more than 300 goals against . | {'scope': 'all', 'row': '1', 'col': '6', 'col_other': '1', 'criterion': 'greater_than', 'value': '300', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'goalsagainst', '300'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose goalsagainst record is greater than 300 .', 'tostr': 'filter_greater { all_rows ; goalsagainst ; 300 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_greater { all_rows ; goalsagainst ; 300 } }', 'tointer': 'select the rows whose goalsagainst record is greater than 300 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'goalsagainst', '300'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose goalsagainst record is greater than 300 .', 'tostr': 'filter_greater { all_rows ; goalsagainst ; 300 }'}, 'season'], 'result': '1997 - 98', 'ind': 2, 'tostr': 'hop { filter_greater { all_rows ; goalsagainst ; 300 } ; season }'}, '1997 - 98'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_greater { all_rows ; goalsagainst ; 300 } ; season } ; 1997 - 98 }', 'tointer': 'the season record of this unqiue row is 1997 - 98 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_greater { all_rows ; goalsagainst ; 300 } } ; eq { hop { filter_greater { all_rows ; goalsagainst ; 300 } ; season } ; 1997 - 98 } } = true', 'tointer': 'select the rows whose goalsagainst record is greater than 300 . there is only one such row in the table . the season record of this unqiue row is 1997 - 98 .'} | and { only { filter_greater { all_rows ; goalsagainst ; 300 } } ; eq { hop { filter_greater { all_rows ; goalsagainst ; 300 } ; season } ; 1997 - 98 } } = true | select the rows whose goalsagainst record is greater than 300 . there is only one such row in the table . the season record of this unqiue row is 1997 - 98 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_greater_0': 0, 'all_rows_6': 6, 'goalsagainst_7': 7, '300_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'season_9': 9, '1997 - 98_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_greater_0': 'filter_greater', 'all_rows_6': 'all_rows', 'goalsagainst_7': 'goalsagainst', '300_8': '300', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'season_9': 'season', '1997 - 98_10': '1997 - 98'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_greater_0': [1, 2], 'all_rows_6': [0], 'goalsagainst_7': [0], '300_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'season_9': [2], '1997 - 98_10': [3]} | ['season', 'games', 'lost', 'points', 'goalsfor', 'goalsagainst'] | [['1997 - 98', '70', '47', '41', '215', '332'], ['1998 - 99', '70', '44', '44', '208', '297'], ['1999 - 2000', '72', '31', '72', '257', '285'], ['2000 - 01', '72', '23', '90', '283', '255'], ['2001 - 02', '72', '25', '85', '288', '231'], ['2002 - 03', '72', '14', '108', '319', '213'], ['2003 - 04', '70', '42', '49', '195', '285'], ['2004 - 05', '70', '37', '57', '208', '280'], ['2005 - 06', '70', '38', '62', '249', '285'], ['2006 - 07', '70', '26', '79', '304', '285'], ['2007 - 08', '70', '19', '96', '249', '210'], ['2008 - 09', '68', '37', '53', '206', '297'], ['2009 - 10', '68', '40', '49', '187', '297'], ['2010 - 11', '68', '46', '34', '151', '266'], ['2011 - 12', '68', '34', '63', '217', '241']] |
wru division five south east | https://en.wikipedia.org/wiki/WRU_Division_Five_South_East | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17625749-2.html.csv | aggregation | the average points in the wru division five south east for all clubs was 47.55 . | {'scope': 'all', 'col': '11', 'type': 'average', 'result': '47.55', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'points'], 'result': '47.55', 'ind': 0, 'tostr': 'avg { all_rows ; points }'}, '47.55'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; points } ; 47.55 } = true', 'tointer': 'the average of the points record of all rows is 47.55 .'} | round_eq { avg { all_rows ; points } ; 47.55 } = true | the average of the points record of all rows is 47.55 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'points_4': 4, '47.55_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'points_4': 'points', '47.55_5': '47.55'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'points_4': [0], '47.55_5': [1]} | ['club', 'played', 'drawn', 'lost', 'points for', 'points against', 'tries for', 'tries against', 'try bonus', 'losing bonus', 'points'] | [['club', 'played', 'drawn', 'lost', 'points for', 'points against', 'tries for', 'tries against', 'try bonus', 'losing bonus', 'points'], ['pontyclun rfc', '20', '0', '2', '694', '191', '104', '21', '12', '2', '86'], ['cilfynydd rfc', '20', '1', '4', '635', '330', '90', '37', '10', '2', '74'], ['barry rfc', '20', '2', '5', '515', '247', '64', '30', '5', '2', '63'], ['st albans rfc', '20', '0', '9', '504', '347', '68', '40', '7', '4', '55'], ['deri rfc', '20', '0', '9', '409', '349', '55', '45', '5', '3', '52'], ['hirwaun rfc', '20', '1', '8', '476', '421', '59', '57', '7', '2', '51'], ['penygraig rfc', '20', '1', '10', '283', '405', '41', '51', '4', '1', '43'], ['cowbridge rfc', '20', '1', '12', '337', '369', '33', '46', '3', '4', '37'], ['old penarthians rfc', '20', '0', '13', '318', '431', '39', '61', '2', '3', '33'], ['dinas powys rfc', '20', '0', '17', '291', '701', '44', '105', '4', '3', '19'], ['canton rfc', '20', '0', '18', '157', '828', '19', '123', '1', '1', '10']] |
sébastien bourdais | https://en.wikipedia.org/wiki/S%C3%A9bastien_Bourdais | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1019053-2.html.csv | majority | sebastian bourdais came in first place in the majority of these competitions . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': '1st', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'rank', '1st'], 'result': True, 'ind': 0, 'tointer': 'for the rank records of all rows , most of them fuzzily match to 1st .', 'tostr': 'most_eq { all_rows ; rank ; 1st } = true'} | most_eq { all_rows ; rank ; 1st } = true | for the rank records of all rows , most of them fuzzily match to 1st . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'rank_3': 3, '1st_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'rank_3': 'rank', '1st_4': '1st'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'rank_3': [0], '1st_4': [0]} | ['year', 'team', 'chassis', 'engine', 'rank', 'points'] | [['2003', 'newman / haas racing', 'lola b02 / 00', 'ford xfe', '4th', '159'], ['2004', 'newman / haas racing', 'lola b02 / 00', 'ford xfe', '1st', '369'], ['2005', 'newman / haas racing', 'lola b02 / 00', 'ford xfe', '1st', '348'], ['2006', 'newman / haas racing', 'lola b02 / 00', 'ford xfe', '1st', '387'], ['2007', 'newman / haas / lanigan racing', 'panoz dp01', 'cosworth xfe', '1st', '364']] |
henry cejudo | https://en.wikipedia.org/wiki/Henry_Cejudo | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18931507-2.html.csv | aggregation | in henry cejudo 's first five fights , cejudo 's average fight time for the five fights was 3:29 . | {'scope': 'all', 'col': '7', 'type': 'average', 'result': '3:29', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'time'], 'result': '3:29', 'ind': 0, 'tostr': 'avg { all_rows ; time }'}, '3:29'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; time } ; 3:29 } = true', 'tointer': 'the average of the time record of all rows is 3:29 .'} | round_eq { avg { all_rows ; time } ; 3:29 } = true | the average of the time record of all rows is 3:29 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'time_4': 4, '3:29_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'time_4': 'time', '3:29_5': '3:29'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'time_4': [0], '3:29_5': [1]} | ['res', 'record', 'opponent', 'method', 'event', 'round', 'time', 'location'] | [['win', '5 - 0', 'ryan hollis', 'decision ( unanimous )', 'lfc 24 - legacy fighting championship 24', '3', '5:00', 'dallas , texas , united states'], ['win', '4 - 0', 'miguelito marti', 'tko ( punches )', 'gladiator challenge : american dream', '1', '1:43', 'lincoln , california , united states'], ['win', '3 - 0', 'anthony sessions', 'tko ( punches )', 'wff 10 : cejudo v sessions', '1', '4:23', 'chandler , arizona , united states'], ['win', '2 - 0', 'sean henry barnett', 'tko ( punches )', 'gladiator challenge : battleground', '1', '4:55', 'san jacinto , california , united states'], ['win', '1 - 0', 'michael poe', 'submission ( punches )', 'wff mma : pascua yaqui fights 4', '1', '1:25', 'tucson , arizona , united states']] |
list of highest - grossing bollywood films | https://en.wikipedia.org/wiki/List_of_highest-grossing_Bollywood_films | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11872185-11.html.csv | majority | the majority of movies on the list of highest - grossing bollywood films were released after the year 2010 . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'greater_than', 'value': '2010', 'subset': None} | {'func': 'most_greater', 'args': ['all_rows', 'year', '2010'], 'result': True, 'ind': 0, 'tointer': 'for the year records of all rows , most of them are greater than 2010 .', 'tostr': 'most_greater { all_rows ; year ; 2010 } = true'} | most_greater { all_rows ; year ; 2010 } = true | for the year records of all rows , most of them are greater than 2010 . | 1 | 1 | {'most_greater_0': 0, 'result_1': 1, 'all_rows_2': 2, 'year_3': 3, '2010_4': 4} | {'most_greater_0': 'most_greater', 'result_1': 'true', 'all_rows_2': 'all_rows', 'year_3': 'year', '2010_4': '2010'} | {'most_greater_0': [1], 'result_1': [], 'all_rows_2': [0], 'year_3': [0], '2010_4': [0]} | ['rank', 'movie', 'year', 'studio ( s )', 'third week nett gross'] | [['1', '3 idiots', '2009', 'vinod chopra productions', '30 , 30 , 00000'], ['2', 'yeh jawaani hai deewani', '2013', 'dharma productions', '19 , 60 , 00000'], ['3', 'chennai express', '2013', 'red chillies entertainment', '18 , 31 , 00000'], ['4', 'dabangg', '2010', 'arbaaz khan productions', '17 , 21 , 00000'], ['5', 'barfi', '2012', 'utv motion pictures', '15 , 70 , 00000'], ['6', 'bhaag milkha bhaag', '2013', 'viacom 18', '15 , 49 , 00000'], ['7', 'rowdy rathore', '2012', 'utv motion pictures', '15 , 16 , 00000'], ['8', 'ghajini', '2008', 'reliance entertainment', '14 , 13 , 00000'], ['9', 'ready', '2010', 't - series', '13 , 61 , 00000'], ['10', 'omg ! oh my god', '2012', 'paresh rawal', '13 , 44 , 00000']] |
list of 10 metre air pistol records | https://en.wikipedia.org/wiki/List_of_10_metre_air_pistol_records | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18986934-4.html.csv | comparative | igor basinski 's 10 metre air pistol score in 1988 was higher than his score in 1986 . | {'row_1': '3', 'row_2': '1', 'col': '1', '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', 'date', '1988'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose date record fuzzily matches to 1988 .', 'tostr': 'filter_eq { all_rows ; date ; 1988 }'}, 'score'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; date ; 1988 } ; score }', 'tointer': 'select the rows whose date record fuzzily matches to 1988 . take the score record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', '1986'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose date record fuzzily matches to 1986 .', 'tostr': 'filter_eq { all_rows ; date ; 1986 }'}, 'score'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; date ; 1986 } ; score }', 'tointer': 'select the rows whose date record fuzzily matches to 1986 . take the score record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; date ; 1988 } ; score } ; hop { filter_eq { all_rows ; date ; 1986 } ; score } } = true', 'tointer': 'select the rows whose date record fuzzily matches to 1988 . take the score record of this row . select the rows whose date record fuzzily matches to 1986 . take the score record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; date ; 1988 } ; score } ; hop { filter_eq { all_rows ; date ; 1986 } ; score } } = true | select the rows whose date record fuzzily matches to 1988 . take the score record of this row . select the rows whose date record fuzzily matches to 1986 . take the score record of this row . the first record is greater than the second record . | 5 | 5 | {'greater_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'date_7': 7, '1988_8': 8, 'score_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'date_11': 11, '1986_12': 12, 'score_13': 13} | {'greater_4': 'greater', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'date_7': 'date', '1988_8': '1988', 'score_9': 'score', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'date_11': 'date', '1986_12': '1986', 'score_13': 'score'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'date_7': [0], '1988_8': [0], 'score_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'date_11': [1], '1986_12': [1], 'score_13': [3]} | ['score', 'shooter', 'date', 'comp', 'place'] | [['688.6', 'igor basinski ( urs )', '1986', 'wch', 'suhl , east germany'], ['689.7', 'aleksandr melentiev ( urs )', '1987', 'wc', 'seoul , south korea'], ['692.3', 'igor basinski ( urs )', '1988', 'ech', 'stavanger , norway'], ['new targets from 1989', 'new targets from 1989', 'new targets from 1989', 'new targets from 1989', 'new targets from 1989'], ['686.4', 'sorin babii ( rou )', '1989', 'ech', 'copenhagen , denmark'], ['690.3', 'sergei pyzhianov ( urs )', '1989', 'wch', 'sarajevo , yugoslavia'], ['695.1', 'sergei pyzhianov ( urs )', '13 oct 1989', 'wcf', 'munich , west germany']] |
telmex grand prix of monterrey | https://en.wikipedia.org/wiki/2004_Tecate/Telmex_Grand_Prix_of_Monterrey | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16326318-1.html.csv | count | forsythe racing had a total of three drivers in the telmex grand prix of monterrey . | {'scope': 'all', 'criterion': 'equal', 'value': 'forsythe racing', 'result': '3', 'col': '2', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'team', 'forsythe racing'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose team record fuzzily matches to forsythe racing .', 'tostr': 'filter_eq { all_rows ; team ; forsythe racing }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; team ; forsythe racing } }', 'tointer': 'select the rows whose team record fuzzily matches to forsythe racing . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; team ; forsythe racing } } ; 3 } = true', 'tointer': 'select the rows whose team record fuzzily matches to forsythe racing . the number of such rows is 3 .'} | eq { count { filter_eq { all_rows ; team ; forsythe racing } } ; 3 } = true | select the rows whose team record fuzzily matches to forsythe racing . 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, 'team_5': 5, 'forsythe racing_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', 'team_5': 'team', 'forsythe racing_6': 'forsythe racing', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'team_5': [0], 'forsythe racing_6': [0], '3_7': [2]} | ['name', 'team', 'qual 1', 'qual 2', 'best'] | [['sébastien bourdais', 'newman / haas racing', '1:15.978', '1:13.915', '1:13.915'], ['mario domínguez', 'herdez competition', '1:16.422', '1:14.343', '1:14.343'], ['justin wilson', 'mi - jack conquest racing', '1:16.087', '1:14.354', '1:14.354'], ['bruno junqueira', 'newman / haas racing', '1:15.834', '1:14.405', '1:14.405'], ['patrick carpentier', 'forsythe racing', '1:16.617', '1:14.625', '1:14.625'], ['paul tracy', 'forsythe racing', '1:16.417', '1:14.723', '1:14.723'], ['jimmy vasser', 'pkv racing', '1:16.620', '1:15.183', '1:15.183'], ['ryan hunter - reay', 'herdez competition', '1:17.637', '1:15.265', '1:15.265'], ['oriol servià', 'dale coyne racing', '1:17.890', '1:15.395', '1:15.395'], ['tarso marques', 'dale coyne racing', '1:18.100', '1:15.582', '1:15.582'], ['a j allmendinger', 'rusport', '1:17.644', '1:15.673', '1:15.673'], ['roberto gonzález', 'pkv racing', '1:18.154', '1:15.791', '1:15.791'], ['michel jourdain , jr', 'rusport', '1:17.873', '1:15.805', '1:15.805'], ['rodolfo lavín', 'forsythe racing', '1:18.553', '1:16.096', '1:16.096'], ['alex tagliani', 'rocketsports racing', '1:16.712', '1:16.103', '1:16.103'], ['mario haberfeld', 'walker racing', '1:16.491', '1:16.691', '1:16.491'], ['nelson philippe', 'rocketsports racing', '1:18.373', '1:17.191', '1:17.191'], ['alex sperafico', 'mi - jack conquest racing', '1:20.139', '1:17.736', '1:17.736']] |
erik fisher | https://en.wikipedia.org/wiki/Erik_Fisher | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16891410-1.html.csv | unique | 2009 was the only year where erik fisher competed in a super g. | {'scope': 'all', 'row': '1', 'col': '4', 'col_other': '1', 'criterion': 'equal', 'value': 'super g', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'race', 'super g'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose race record fuzzily matches to super g .', 'tostr': 'filter_eq { all_rows ; race ; super g }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; race ; super g } }', 'tointer': 'select the rows whose race record fuzzily matches to super g . there is only one such row in the table .'}, {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'race', 'super g'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose race record fuzzily matches to super g .', 'tostr': 'filter_eq { all_rows ; race ; super g }'}, 'season'], 'result': '2009', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; race ; super g } ; season }'}, '2009'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; race ; super g } ; season } ; 2009 }', 'tointer': 'the season record of this unqiue row is 2009 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; race ; super g } } ; eq { hop { filter_eq { all_rows ; race ; super g } ; season } ; 2009 } } = true', 'tointer': 'select the rows whose race record fuzzily matches to super g . there is only one such row in the table . the season record of this unqiue row is 2009 .'} | and { only { filter_eq { all_rows ; race ; super g } } ; eq { hop { filter_eq { all_rows ; race ; super g } ; season } ; 2009 } } = true | select the rows whose race record fuzzily matches to super g . there is only one such row in the table . the season record of this unqiue row is 2009 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'race_7': 7, 'super g_8': 8, 'eq_3': 3, 'num_hop_2': 2, 'season_9': 9, '2009_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'race_7': 'race', 'super g_8': 'super g', 'eq_3': 'eq', 'num_hop_2': 'num_hop', 'season_9': 'season', '2009_10': '2009'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'race_7': [0], 'super g_8': [0], 'eq_3': [4], 'num_hop_2': [3], 'season_9': [2], '2009_10': [3]} | ['season', 'date', 'location', 'race', 'place'] | [['2009', '19 dec 2008', 'val gardena , italy', 'super g', '20th'], ['2009', '20 dec 2008', 'val gardena , italy', 'downhill', '7th'], ['2009', '24 jan 2009', 'kitzbühel , austria', 'downhill', '11th'], ['2010', '18 dec 2009', 'val gardena , italy', 'downhill', '19th'], ['2010', '23 jan 2010', 'kitzbühel , austria', 'downhill', '18th'], ['2012', '3 feb 2012', 'chamonix , france', 'downhill', '12th'], ['2012', '4 feb 2012', 'chamonix , france', 'downhill', '12th']] |
86th united states congress | https://en.wikipedia.org/wiki/86th_United_States_Congress | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2159571-2.html.csv | ordinal | the first us representative in the 86th us congress to be replaced was george h. christopher . | {'row': '1', 'col': '3', 'order': '1', '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', 'reason for change', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; reason for change ; 1 }'}, 'vacator'], 'result': 'george h christopher ( d )', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; reason for change ; 1 } ; vacator }'}, 'george h christopher ( d )'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; reason for change ; 1 } ; vacator } ; george h christopher ( d ) } = true', 'tointer': 'select the row whose reason for change record of all rows is 1st minimum . the vacator record of this row is george h christopher ( d ) .'} | eq { hop { nth_argmin { all_rows ; reason for change ; 1 } ; vacator } ; george h christopher ( d ) } = true | select the row whose reason for change record of all rows is 1st minimum . the vacator record of this row is george h christopher ( d ) . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'reason for change_5': 5, '1_6': 6, 'vacator_7': 7, 'george h christopher (d)_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', 'reason for change_5': 'reason for change', '1_6': '1', 'vacator_7': 'vacator', 'george h christopher (d)_8': 'george h christopher ( d )'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'reason for change_5': [0], '1_6': [0], 'vacator_7': [1], 'george h christopher (d)_8': [2]} | ['district', 'vacator', 'reason for change', 'successor', 'date successor seated'] | [['missouri 4th', 'george h christopher ( d )', 'died january 23 , 1959', 'william j randall ( d )', 'march 3 , 1959'], ['new york 43rd', 'daniel a reed ( r )', 'died february 19 , 1959', 'charles goodell ( r )', 'may 26 , 1959'], ['ohio 6th', 'james g polk ( d )', 'died april 28 , 1959', 'ward miller ( r )', 'november 8 , 1960'], ['hawaii territory at - large', 'john a burns ( d )', 'hawaii achieved statehood', 'seat eliminated august 21 , 1959', 'seat eliminated august 21 , 1959'], ['hawaii at - large', 'new seat', 'hawaii achieved statehood august 21 , 1959', 'daniel inouye ( d )', 'august 21 , 1959'], ['illinois 12th', 'charles a boyle ( d )', 'died november 4 , 1959', 'vacant', 'not filled this term'], ['iowa 4th', 'steven v carter ( d )', 'died november 4 , 1959', 'john h kyl ( r )', 'december 15 , 1959'], ['pennsylvania 17th', 'alvin bush ( r )', 'died november 5 , 1959', 'herman t schneebeli ( r )', 'april 26 , 1960'], ['new york 23rd', 'isidore dollinger ( d )', 'resigned december 31 , 1959', 'jacob h gilbert ( d )', 'march 8 , 1960'], ['pennsylvania 18th', 'richard m simpson ( r )', 'died january 7 , 1960', 'douglas h elliott ( r )', 'april 26 , 1960'], ['north carolina 12th', 'david m hall ( d )', 'died january 29 , 1960', 'roy a taylor ( d )', 'june 25 , 1960'], ['washington 3rd', 'russell v mack ( r )', 'died march 28 , 1960', 'julia butler hansen ( d )', 'november 8 , 1960'], ['pennsylvania 18th', 'douglas h elliott ( r )', 'died june 19 , 1960', 'j irving whalley ( r )', 'november 8 , 1960'], ['north dakota at - large', 'quentin n burdick ( d )', 'resigned august 8 , 1960 after becoming us senator', 'vacant', 'not filled this term'], ['massachusetts 5th', 'edith nourse rogers ( r )', 'died september 10 , 1960', 'vacant', 'not filled this term']] |
1993 minnesota vikings season | https://en.wikipedia.org/wiki/1993_Minnesota_Vikings_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10362162-2.html.csv | majority | the minnesota vikings lost most games in the month of november during the 1993 season . | {'scope': 'subset', 'col': '4', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': 'l', 'subset': {'col': '2', 'criterion': 'fuzzily_match', 'value': 'november'}} | {'func': 'most_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', 'november'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; date ; november }', 'tointer': 'select the rows whose date record fuzzily matches to november .'}, 'result', 'l'], 'result': True, 'ind': 1, 'tointer': 'select the rows whose date record fuzzily matches to november . for the result records of these rows , most of them fuzzily match to l .', 'tostr': 'most_eq { filter_eq { all_rows ; date ; november } ; result ; l } = true'} | most_eq { filter_eq { all_rows ; date ; november } ; result ; l } = true | select the rows whose date record fuzzily matches to november . for the result records of these rows , most of them fuzzily match to l . | 2 | 2 | {'most_str_eq_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, 'date_4': 4, 'november_5': 5, 'result_6': 6, 'l_7': 7} | {'most_str_eq_1': 'most_str_eq', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'date_4': 'date', 'november_5': 'november', 'result_6': 'result', 'l_7': 'l'} | {'most_str_eq_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'date_4': [0], 'november_5': [0], 'result_6': [1], 'l_7': [1]} | ['week', 'date', 'opponent', 'result', 'attendance'] | [['1', 'september 5 , 1993', 'los angeles raiders', 'l 24 - 7', '44120'], ['2', 'september 12 , 1993', 'chicago bears', 'w 10 - 7', '57921'], ['4', 'september 26 , 1993', 'green bay packers', 'w 15 - 13', '61746'], ['5', 'october 3 , 1993', 'san francisco 49ers', 'l 38 - 19', '63071'], ['6', 'october 10 , 1993', 'tampa bay buccaneers', 'w 15 - 0', '54215'], ['8', 'october 25 , 1993', 'chicago bears', 'w 19 - 12', '64677'], ['9', 'october 31 , 1993', 'detroit lions', 'l 30 - 27', '53428'], ['10', 'november 7 , 1993', 'san diego chargers', 'l 30 - 17', '55527'], ['11', 'november 14 , 1993', 'denver broncos', 'w 26 - 23', '67329'], ['12', 'november 21 , 1993', 'tampa bay buccaneers', 'l 23 - 10', '40848'], ['13', 'november 28 , 1993', 'new orleans saints', 'l 17 - 14', '53030'], ['14', 'december 5 , 1993', 'detroit lions', 'w 13 - 0', '63216'], ['15', 'december 12 , 1993', 'dallas cowboys', 'l 37 - 20', '63321'], ['16', 'december 19 , 1993', 'green bay packers ( milw )', 'w 21 - 17', '54773'], ['17', 'december 26 , 1993', 'kansas city chiefs', 'w 30 - 10', '59236'], ['18', 'december 31 , 1993', 'washington redskins', 'w 14 - 9', '42836']] |
list of prime ministers of albania | https://en.wikipedia.org/wiki/List_of_Prime_Ministers_of_Albania | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-167235-8.html.csv | ordinal | sali berisha is the second earliest albanian prime minister to have been born . | {'row': '12', 'col': '2', 'order': '2', 'col_other': '1', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'born - died', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; born - died ; 2 }'}, 'name'], 'result': 'sali berisha', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; born - died ; 2 } ; name }'}, 'sali berisha'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; born - died ; 2 } ; name } ; sali berisha } = true', 'tointer': 'select the row whose born - died record of all rows is 2nd minimum . the name record of this row is sali berisha .'} | eq { hop { nth_argmin { all_rows ; born - died ; 2 } ; name } ; sali berisha } = true | select the row whose born - died record of all rows is 2nd minimum . the name record of this row is sali berisha . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'born - died_5': 5, '2_6': 6, 'name_7': 7, 'sali berisha_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', 'born - died_5': 'born - died', '2_6': '2', 'name_7': 'name', 'sali berisha_8': 'sali berisha'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'born - died_5': [0], '2_6': [0], 'name_7': [1], 'sali berisha_8': [2]} | ['name', 'born - died', 'term start', 'term end', 'political party'] | [['prime ministers 1991 onwards', 'prime ministers 1991 onwards', 'prime ministers 1991 onwards', 'prime ministers 1991 onwards', 'prime ministers 1991 onwards'], ['fatos nano ( 1st time )', '1952 -', '22 february 1991', '5 june 1991', 'party of labour of albania'], ['ylli bufi', '1948 -', '5 june 1991', '10 december 1991', 'socialist party of albania'], ['vilson ahmeti', '1951 -', '10 december 1991', '13 april 1992', 'non - party'], ['aleksandër meksi', '1939 -', '13 april 1992', '11 march 1997', 'democratic party of albania'], ['bashkim fino', '1962 -', '11 march 1997', '24 july 1997', 'socialist party of albania'], ['fatos nano ( 2nd time )', '1952 -', '24 july 1997', '2 october 1998', 'socialist party of albania'], ['pandeli majko ( 1st time )', '1967 -', '2 october 1998', '29 october 1999', 'socialist party of albania'], ['ilir meta', '1969 -', '29 october 1999', '22 february 2002', 'socialist party of albania'], ['pandeli majko ( 2nd time )', '1967 -', '22 february 2002', '31 july 2002', 'socialist party of albania'], ['fatos nano ( 3rd time )', '1952 -', '31 july 2002', '11 september 2005', 'socialist party of albania'], ['sali berisha', '1944 -', '11 september 2005', '15 september 2013', 'democratic party of albania'], ['edi rama', '1964 -', '15 september 2013', 'incumbent', 'socialist party of albania']] |
2007 - 08 segunda división | https://en.wikipedia.org/wiki/2007%E2%80%9308_Segunda_Divisi%C3%B3n | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11828307-4.html.csv | comparative | in the 2007-08 segunda division , bernardo had a better average than juan pablo . | {'row_1': '8', 'row_2': '9', 'col': '4', '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', 'goalkeeper', 'bernardo'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose goalkeeper record fuzzily matches to bernardo .', 'tostr': 'filter_eq { all_rows ; goalkeeper ; bernardo }'}, 'average'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; goalkeeper ; bernardo } ; average }', 'tointer': 'select the rows whose goalkeeper record fuzzily matches to bernardo . take the average record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'goalkeeper', 'javier varas'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose goalkeeper record fuzzily matches to javier varas .', 'tostr': 'filter_eq { all_rows ; goalkeeper ; javier varas }'}, 'average'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; goalkeeper ; javier varas } ; average }', 'tointer': 'select the rows whose goalkeeper record fuzzily matches to javier varas . take the average record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; goalkeeper ; bernardo } ; average } ; hop { filter_eq { all_rows ; goalkeeper ; javier varas } ; average } } = true', 'tointer': 'select the rows whose goalkeeper record fuzzily matches to bernardo . take the average record of this row . select the rows whose goalkeeper record fuzzily matches to javier varas . take the average record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; goalkeeper ; bernardo } ; average } ; hop { filter_eq { all_rows ; goalkeeper ; javier varas } ; average } } = true | select the rows whose goalkeeper record fuzzily matches to bernardo . take the average record of this row . select the rows whose goalkeeper record fuzzily matches to javier varas . take the average 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, 'goalkeeper_7': 7, 'bernardo_8': 8, 'average_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'goalkeeper_11': 11, 'javier varas_12': 12, 'average_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', 'goalkeeper_7': 'goalkeeper', 'bernardo_8': 'bernardo', 'average_9': 'average', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'goalkeeper_11': 'goalkeeper', 'javier varas_12': 'javier varas', 'average_13': 'average'} | {'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'goalkeeper_7': [0], 'bernardo_8': [0], 'average_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'goalkeeper_11': [1], 'javier varas_12': [1], 'average_13': [3]} | ['goalkeeper', 'goals', 'matches', 'average', 'team'] | [['carlos sánchez', '27', '33', '0.82', 'cd castellón'], ['jacobo', '29', '32', '0.91', 'cd numancia'], ['asier riesgo', '39', '42', '0.93', 'real sociedad'], ['roberto', '39', '41', '0.95', 'sporting de gijón'], ['iñaki goitia', '41', '40', '1.02', 'málaga cf'], ['pedro contreras', '37', '36', '1.03', 'cádiz cf'], ['wilfredo caballero', '41', '38', '1.08', 'elche cf'], ['bernardo', '42', '38', '1.11', 'deportivo alavés'], ['javier varas', '46', '41', '1.12', 'sevilla atlético'], ['juan pablo', '33', '29', '1.14', 'cd tenerife']] |
primera división de fútbol profesional apertura 2004 | https://en.wikipedia.org/wiki/Primera_Divisi%C3%B3n_de_F%C3%BAtbol_Profesional_Apertura_2004 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13018938-1.html.csv | superlative | the team that scored the highest number of goals in the 2004 primera división de fútbol profesional apertura was the san salvador fc . | {'scope': 'all', 'col_superlative': '6', 'row_superlative': '2', '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', 'goals scored'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; goals scored }'}, 'team'], 'result': 'san salvador fc', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; goals scored } ; team }'}, 'san salvador fc'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; goals scored } ; team } ; san salvador fc } = true', 'tointer': 'select the row whose goals scored record of all rows is maximum . the team record of this row is san salvador fc .'} | eq { hop { argmax { all_rows ; goals scored } ; team } ; san salvador fc } = true | select the row whose goals scored record of all rows is maximum . the team record of this row is san salvador fc . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'goals scored_5': 5, 'team_6': 6, 'san salvador fc_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'goals scored_5': 'goals scored', 'team_6': 'team', 'san salvador fc_7': 'san salvador fc'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'goals scored_5': [0], 'team_6': [1], 'san salvador fc_7': [2]} | ['place', 'team', 'played', 'draw', 'lost', 'goals scored', 'goals conceded', 'points'] | [['1', 'cd fas', '18', '5', '4', '26', '19', '32'], ['2', 'san salvador fc', '18', '5', '4', '30', '33', '32'], ['3', 'cd atlético balboa', '18', '9', '2', '26', '13', '30'], ['4', 'cd luis ángel firpo', '18', '8', '3', '26', '13', '29'], ['5', 'ad isidro metapán', '18', '5', '5', '25', '24', '29'], ['6', 'cd águila', '18', '8', '5', '24', '20', '23'], ['7', 'alianza fc', '18', '3', '9', '19', '25', '21'], ['8', 'once lobos', '18', '7', '7', '22', '21', '19'], ['9', 'once municipal', '18', '4', '9', '15', '26', '19'], ['10', 'municipal limeño', '18', '6', '12', '12', '31', '6']] |
athletics at the 1966 central american and caribbean games | https://en.wikipedia.org/wiki/Athletics_at_the_1966_Central_American_and_Caribbean_Games | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10139327-3.html.csv | count | only three countries have 10 or more total medals . | {'scope': 'all', 'criterion': 'greater_than_eq', 'value': '10', 'result': '3', 'col': '6', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater_eq', 'args': ['all_rows', 'total', '10'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose total record is greater than or equal to 10 .', 'tostr': 'filter_greater_eq { all_rows ; total ; 10 }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_greater_eq { all_rows ; total ; 10 } }', 'tointer': 'select the rows whose total record is greater than or equal to 10 . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_greater_eq { all_rows ; total ; 10 } } ; 3 } = true', 'tointer': 'select the rows whose total record is greater than or equal to 10 . the number of such rows is 3 .'} | eq { count { filter_greater_eq { all_rows ; total ; 10 } } ; 3 } = true | select the rows whose total record is greater than or equal to 10 . the number of such rows is 3 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_greater_eq_0': 0, 'all_rows_4': 4, 'total_5': 5, '10_6': 6, '3_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_greater_eq_0': 'filter_greater_eq', 'all_rows_4': 'all_rows', 'total_5': 'total', '10_6': '10', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_greater_eq_0': [1], 'all_rows_4': [0], 'total_5': [0], '10_6': [0], '3_7': [2]} | ['rank', 'nation', 'gold', 'silver', 'bronze', 'total'] | [['1', 'cuba', '9', '11', '12', '32'], ['2', 'jamaica', '7', '5', '4', '16'], ['3', 'colombia', '4', '2', '3', '9'], ['4', 'puerto rico', '4', '2', '1', '7'], ['5', 'mexico', '3', '3', '4', '10'], ['6', 'trinidad and tobago', '2', '5', '1', '8'], ['7', 'barbados', '1', '1', '1', '3'], ['8', 'guatemala', '1', '0', '0', '1'], ['8', 'bahamas', '1', '0', '0', '1'], ['10', 'venezuela', '0', '2', '5', '7'], ['11', 'us virgin islands', '0', '1', '1', '2']] |
1989 phoenix cardinals season | https://en.wikipedia.org/wiki/1989_Phoenix_Cardinals_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16642092-2.html.csv | ordinal | the phoenix cardinals ' game on september 24 recorded their highest attendance in the 1989 season . | {'row': '3', 'col': '5', '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', 'attendance', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; attendance ; 1 }'}, 'date'], 'result': 'september 24 , 1989', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; attendance ; 1 } ; date }'}, 'september 24 , 1989'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; attendance ; 1 } ; date } ; september 24 , 1989 } = true', 'tointer': 'select the row whose attendance record of all rows is 1st maximum . the date record of this row is september 24 , 1989 .'} | eq { hop { nth_argmax { all_rows ; attendance ; 1 } ; date } ; september 24 , 1989 } = true | select the row whose attendance record of all rows is 1st maximum . the date record of this row is september 24 , 1989 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'attendance_5': 5, '1_6': 6, 'date_7': 7, 'september 24 , 1989_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'attendance_5': 'attendance', '1_6': '1', 'date_7': 'date', 'september 24 , 1989_8': 'september 24 , 1989'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'attendance_5': [0], '1_6': [0], 'date_7': [1], 'september 24 , 1989_8': [2]} | ['week', 'date', 'opponent', 'result', 'attendance'] | [['1', 'september 10 , 1989', 'detroit lions', 'w 16 - 13', '36735'], ['2', 'september 17 , 1989', 'seattle seahawks', 'w 34 - 24', '60444'], ['3', 'september 24 , 1989', 'new york giants', 'l 35 - 7', '75742'], ['4', 'october 1 , 1989', 'san diego chargers', 'l 24 - 13', '44201'], ['5', 'october 8 , 1989', 'washington redskins', 'l 30 - 28', '53335'], ['6', 'october 15 , 1989', 'philadelphia eagles', 'l 17 - 5', '42620'], ['7', 'october 22 , 1989', 'atlanta falcons', 'w 34 - 20', '33894'], ['8', 'october 29 , 1989', 'dallas cowboys', 'w 19 - 10', '44431'], ['9', 'november 5 , 1989', 'new york giants', 'l 20 - 13', '46588'], ['10', 'november 12 , 1989', 'dallas cowboys', 'w 24 - 20', '49657'], ['11', 'november 19 , 1989', 'los angeles rams', 'l 37 - 14', '53176'], ['12', 'november 26 , 1989', 'tampa bay buccaneers', 'l 14 - 13', '33297'], ['13', 'december 3 , 1989', 'washington redskins', 'l 29 - 10', '38870'], ['14', 'december 10 , 1989', 'los angeles raiders', 'l 16 - 14', '41785'], ['15', 'december 16 , 1989', 'denver broncos', 'l 37 - 0', '56071'], ['16', 'december 24 , 1989', 'philadelphia eagles', 'l 31 - 14', '43287']] |
novi sad | https://en.wikipedia.org/wiki/Novi_Sad | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-113288-4.html.csv | superlative | in novi sad , the club with the earliest founding date is fk vojvodina . | {'scope': 'all', 'col_superlative': '3', 'row_superlative': '1', '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', 'founded'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; founded }'}, 'club'], 'result': 'fk vojvodina', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; founded } ; club }'}, 'fk vojvodina'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmin { all_rows ; founded } ; club } ; fk vojvodina } = true', 'tointer': 'select the row whose founded record of all rows is minimum . the club record of this row is fk vojvodina .'} | eq { hop { argmin { all_rows ; founded } ; club } ; fk vojvodina } = true | select the row whose founded record of all rows is minimum . the club record of this row is fk vojvodina . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'founded_5': 5, 'club_6': 6, 'fk vojvodina_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'founded_5': 'founded', 'club_6': 'club', 'fk vojvodina_7': 'fk vojvodina'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'founded_5': [0], 'club_6': [1], 'fk vojvodina_7': [2]} | ['club', 'sport', 'founded', 'league', 'venue'] | [['fk vojvodina', 'football', '1914', 'jelen superliga', 'karađorđe stadium'], ['fk proleter', 'football', '1951', 'first league', 'stadion slana bara'], ['fk novi sad', 'football', '1921', 'first league', 'detelinara stadium'], ['kk vojvodina', 'basketball', '2000', 'sinalco superleague', 'spens sports center'], ['kk novi sad', 'basketball', '1985', 'sinalco superleague', 'spens sports center'], ['ok vojvodina', 'volleyball', '1946', 'serbian volley league', 'spens sports center'], ['hk vojvodina', 'hockey', '1957', 'serbian hockey league', 'spens sports center'], ['hk novi sad', 'hockey', '1998', 'serbian hockey league', 'spens sports center']] |
southern league cup ( scotland ) | https://en.wikipedia.org/wiki/Southern_League_Cup_%28Scotland%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16880170-1.html.csv | majority | both teams scored goals in most of the games when rangers won the scottish southern league cup . | {'scope': 'subset', 'col': '3', 'most_or_all': 'most', 'criterion': 'greater_than', 'value': '0', 'subset': {'col': '2', 'criterion': 'equal', 'value': 'rangers'}} | {'func': 'most_greater', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'winner', 'rangers'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; winner ; rangers }', 'tointer': 'select the rows whose winner record fuzzily matches to rangers .'}, 'score', '0'], 'result': True, 'ind': 1, 'tointer': 'select the rows whose winner record fuzzily matches to rangers . for the score records of these rows , most of them are greater than 0 .', 'tostr': 'most_greater { filter_eq { all_rows ; winner ; rangers } ; score ; 0 } = true'} | most_greater { filter_eq { all_rows ; winner ; rangers } ; score ; 0 } = true | select the rows whose winner record fuzzily matches to rangers . for the score records of these rows , most of them are greater than 0 . | 2 | 2 | {'most_greater_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, 'winner_4': 4, 'rangers_5': 5, 'score_6': 6, '0_7': 7} | {'most_greater_1': 'most_greater', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'winner_4': 'winner', 'rangers_5': 'rangers', 'score_6': 'score', '0_7': '0'} | {'most_greater_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'winner_4': [0], 'rangers_5': [0], 'score_6': [1], '0_7': [1]} | ['season', 'winner', 'score', 'runner - up', 'venue'] | [['1940 - 41', 'rangers', '4 - 2 ( rep )', 'heart of midlothian', 'hampden park'], ['1941 - 42', 'rangers', '2 - 0', 'morton', 'hampden park'], ['1942 - 43', 'rangers', '1 - 1 ( 11 - 3 corners )', 'falkirk', 'hampden park'], ['1943 - 44', 'hibernian', '0 - 0 ( 6 - 5 corners )', 'rangers', 'hampden park'], ['1944 - 45', 'rangers', '2 - 1', 'motherwell', 'hampden park'], ['1945 - 46', 'aberdeen', '3 - 2', 'rangers', 'hampden park']] |
2002 honda indy 300 | https://en.wikipedia.org/wiki/2002_Honda_Indy_300 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15162303-2.html.csv | count | in the results for the 2002 honda indy 300 given , six cars finished less than ten seconds after the winner . | {'scope': 'all', 'criterion': 'less_than', 'value': '10 secs', 'result': '6', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'time / retired', '10 secs'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose time / retired record is less than 10 secs .', 'tostr': 'filter_less { all_rows ; time / retired ; 10 secs }'}], 'result': '6', 'ind': 1, 'tostr': 'count { filter_less { all_rows ; time / retired ; 10 secs } }', 'tointer': 'select the rows whose time / retired record is less than 10 secs . the number of such rows is 6 .'}, '6'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_less { all_rows ; time / retired ; 10 secs } } ; 6 } = true', 'tointer': 'select the rows whose time / retired record is less than 10 secs . the number of such rows is 6 .'} | eq { count { filter_less { all_rows ; time / retired ; 10 secs } } ; 6 } = true | select the rows whose time / retired record is less than 10 secs . the number of such rows is 6 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_less_0': 0, 'all_rows_4': 4, 'time / retired_5': 5, '10 secs_6': 6, '6_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_less_0': 'filter_less', 'all_rows_4': 'all_rows', 'time / retired_5': 'time / retired', '10 secs_6': '10 secs', '6_7': '6'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_less_0': [1], 'all_rows_4': [0], 'time / retired_5': [0], '10 secs_6': [0], '6_7': [2]} | ['driver', 'team', 'laps', 'time / retired', 'grid'] | [['mario domínguez', 'herdez competition', '40', '2:00:06.524', '18'], ['patrick carpentier', 'forsythe racing', '40', '+ 2.2 secs', '15'], ['paul tracy', 'team green', '40', '+ 2.5 secs', '5'], ['kenny bräck', 'chip ganassi racing', '40', '+ 2.7 secs', '4'], ['tony kanaan', 'mo nunn racing', '40', '+ 4.8 secs', '3'], ['alex tagliani', 'forsythe racing', '40', '+ 7.8 secs', '14'], ['dario franchitti', 'team green', '40', '+ 9.9 secs', '8'], ['cristiano da matta', 'newman - haas racing', '40', '+ 12.3 secs', '1'], ['michael andretti', 'team green', '40', '+ 13.5 secs', '16'], ['michel jourdain , jr', 'team rahal', '40', '+ 13.6 secs', '12'], ['christian fittipaldi', 'newman - haas racing', '40', '+ 14.8 secs', '13'], ['jimmy vasser', 'team rahal', '40', '+ 16.2 secs', '11'], ['shinji nakano', 'fernández racing', '40', '+ 17.6 secs', '7'], ['bruno junqueira', 'chip ganassi racing', '40', '+ 18.1 secs', '2'], ['scott dixon', 'chip ganassi racing', '24', 'mechanical', '6'], ['oriol servià', 'patrick racing', '11', 'mechanical', '9'], ['adrián fernández', 'fernández racing', '0', 'contact', '10'], ['tora takagi', 'walker racing', '0', 'contact', '17']] |
1957 vfl season | https://en.wikipedia.org/wiki/1957_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10774891-4.html.csv | aggregation | the average crowd for the 1957 vfl season was approximately 24,648 people . | {'scope': 'all', 'col': '6', 'type': 'average', 'result': '24,648', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'crowd'], 'result': '24,648', 'ind': 0, 'tostr': 'avg { all_rows ; crowd }'}, '24,648'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; crowd } ; 24,648 } = true', 'tointer': 'the average of the crowd record of all rows is 24,648 .'} | round_eq { avg { all_rows ; crowd } ; 24,648 } = true | the average of the crowd record of all rows is 24,648 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'crowd_4': 4, '24,648_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'crowd_4': 'crowd', '24,648_5': '24,648'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'crowd_4': [0], '24,648_5': [1]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['hawthorn', '6.15 ( 51 )', 'melbourne', '4.9 ( 33 )', 'glenferrie oval', '20000', '11 may 1957'], ['essendon', '11.14 ( 80 )', 'footscray', '4.14 ( 38 )', 'windy hill', '30000', '11 may 1957'], ['collingwood', '14.9 ( 93 )', 'south melbourne', '11.17 ( 83 )', 'victoria park', '32500', '11 may 1957'], ['carlton', '15.12 ( 102 )', 'geelong', '13.11 ( 89 )', 'princes park', '28888', '11 may 1957'], ['st kilda', '16.5 ( 101 )', 'north melbourne', '12.12 ( 84 )', 'junction oval', '20000', '11 may 1957'], ['richmond', '16.10 ( 106 )', 'fitzroy', '10.31 ( 91 )', 'punt road oval', '16500', '11 may 1957']] |
1975 in brazilian football | https://en.wikipedia.org/wiki/1975_in_Brazilian_football | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15172914-2.html.csv | majority | most of the games in 1975 brazilian football had a points score higher than 6 . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'greater_than', 'value': '6', 'subset': None} | {'func': 'most_greater', 'args': ['all_rows', 'points', '6'], 'result': True, 'ind': 0, 'tointer': 'for the points records of all rows , most of them are greater than 6 .', 'tostr': 'most_greater { all_rows ; points ; 6 } = true'} | most_greater { all_rows ; points ; 6 } = true | for the points records of all rows , most of them are greater than 6 . | 1 | 1 | {'most_greater_0': 0, 'result_1': 1, 'all_rows_2': 2, 'points_3': 3, '6_4': 4} | {'most_greater_0': 'most_greater', 'result_1': 'true', 'all_rows_2': 'all_rows', 'points_3': 'points', '6_4': '6'} | {'most_greater_0': [1], 'result_1': [], 'all_rows_2': [0], 'points_3': [0], '6_4': [0]} | ['position', 'team', 'points', 'played', 'won by 2 or more goals difference', 'drawn', 'lost', 'against', 'difference'] | [['1', 'fluminense', '14', '7', '3', '1', '1', '5', '9'], ['2', 'cruzeiro', '11', '7', '3', '2', '2', '5', '4'], ['3', 'america - rj', '10', '7', '1', '3', '1', '6', '2'], ['4', 'palmeiras', '10', '7', '3', '1', '3', '8', '2'], ['5', 'corinthians', '9', '7', '0', '1', '2', '8', '2'], ['6', 'guarani', '9', '7', '2', '1', '3', '9', '2'], ['7', 'guarani', '6', '7', '1', '1', '4', '10', '- 4'], ['8', 'nacional', '6', '7', '0', '0', '7', '17', '- 16']] |
1997 australian touring car championship | https://en.wikipedia.org/wiki/1997_Australian_Touring_Car_Championship | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15374407-2.html.csv | superlative | the calder park raceway was the first circuit used in the 1997 australian touring car championship . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '2', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmin', 'args': ['all_rows', 'date'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; date }'}, 'circuit'], 'result': 'calder park raceway', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; date } ; circuit }'}, 'calder park raceway'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmin { all_rows ; date } ; circuit } ; calder park raceway } = true', 'tointer': 'select the row whose date record of all rows is minimum . the circuit record of this row is calder park raceway .'} | eq { hop { argmin { all_rows ; date } ; circuit } ; calder park raceway } = true | select the row whose date record of all rows is minimum . the circuit record of this row is calder park raceway . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'date_5': 5, 'circuit_6': 6, 'calder park raceway_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'date_5': 'date', 'circuit_6': 'circuit', 'calder park raceway_7': 'calder park raceway'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'date_5': [0], 'circuit_6': [1], 'calder park raceway_7': [2]} | ['race title', 'circuit', 'city / state', 'date', 'winner', 'team'] | [['calder', 'calder park raceway', 'melbourne , victoria', '13 - 15 mar', 'wayne gardner', 'wayne gardner racing'], ['phillip island', 'phillip island grand prix circuit', 'phillip island , victoria', '11 - 13 apr', 'russell ingall', 'castrol perkins motorsport'], ['sandown', 'sandown international raceway', 'melbourne , victoria', '25 - 27 apr', 'glenn seton', 'glenn seton racing'], ['symmons plains', 'symmons plains raceway', 'launceston , tasmania', '2 - 4 may', 'greg murphy', 'holden racing team'], ['winton', 'winton motor raceway', 'benalla , victoria', '16 - 18 may', 'russell ingall', 'castrol perkins motorsport'], ['eastern creek', 'eastern creek raceway', 'sydney , new south wales', '23 - 25 may', 'glenn seton', 'glenn seton racing'], ['lakeside', 'lakeside international raceway', 'brisbane , queensland', '13 - 15 jun', 'john bowe', 'dick johnson racing'], ['wanneroo', 'barbagallo raceway', 'perth , western australia', '4 - 6 jul', 'peter brock', 'holden racing team'], ['mallala', 'mallala motor sport park', 'adelaide , south australia', '11 - 13 jul', 'greg murphy', 'holden racing team'], ['oran park', 'oran park raceway', 'sydney , new south wales', '1 - 3 aug', 'greg murphy', 'holden racing team']] |
2008 - 09 cleveland cavaliers season | https://en.wikipedia.org/wiki/2008%E2%80%9309_Cleveland_Cavaliers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17325580-10.html.csv | majority | for most of the games between april 2 and april 15 , lebron james had scored the most points . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'lebron james', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'high points', 'lebron james'], 'result': True, 'ind': 0, 'tointer': 'for the high points records of all rows , most of them fuzzily match to lebron james .', 'tostr': 'most_eq { all_rows ; high points ; lebron james } = true'} | most_eq { all_rows ; high points ; lebron james } = true | for the high points records of all rows , most of them fuzzily match to lebron james . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'high points_3': 3, 'lebron james_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'high points_3': 'high points', 'lebron james_4': 'lebron james'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'high points_3': [0], 'lebron james_4': [0]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record'] | [['75', 'april 2', 'washington', 'l 101 - 109 ( ot )', 'lebron james ( 31 )', 'lebron james ( 9 )', 'delonte west ( 7 )', 'verizon center 20173', '61 - 14'], ['76', 'april 3', 'orlando', 'l 87 - 116 ( ot )', 'lebron james ( 26 )', 'lebron james ( 9 )', 'lebron james ( 5 )', 'amway arena 17461', '61 - 15'], ['77', 'april 5', 'san antonio', 'w 101 - 81 ( ot )', 'lebron james ( 38 )', 'žydrūnas ilgauskas ( 10 )', 'lebron james ( 6 )', 'quicken loans arena 20562', '62 - 15'], ['78', 'april 8', 'washington', 'w 98 - 86 ( ot )', 'lebron james ( 21 )', 'žydrūnas ilgauskas ( 13 )', 'lebron james ( 7 )', 'quicken loans arena 20562', '63 - 15'], ['79', 'april 10', 'philadelphia', 'w 102 - 92 ( ot )', 'lebron james ( 27 )', 'žydrūnas ilgauskas ( 9 )', 'lebron james ( 10 )', 'wachovia center 20484', '64 - 15'], ['80', 'april 12', 'boston', 'w 107 - 76 ( ot )', 'lebron james ( 29 )', 'žydrūnas ilgauskas ( 10 )', 'lebron james ( 7 )', 'quicken loans arena 20562', '65 - 15'], ['81', 'april 13', 'indiana', 'w 117 - 109 ( ot )', 'lebron james ( 37 )', 'anderson varejão ( 11 )', 'maurice williams ( 8 )', 'conseco fieldhouse 18165', '66 - 15'], ['82', 'april 15', 'philadelphia', 'l 110 - 111 ( ot )', 'daniel gibson ( 28 )', 'darnell jackson , wally szczerbiak ( 8 )', 'wally szczerbiak ( 8 )', 'quicken loans arena 20562', '66 - 16']] |
list of holbyblue episodes | https://en.wikipedia.org/wiki/List_of_HolbyBlue_episodes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-12148018-2.html.csv | superlative | the first episode of holbyblue received the show 's most viewers . | {'scope': 'all', 'col_superlative': '6', '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', 'viewers'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; viewers }'}, 'episode'], 'result': 'episode 1', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; viewers } ; episode }'}, 'episode 1'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; viewers } ; episode } ; episode 1 } = true', 'tointer': 'select the row whose viewers record of all rows is maximum . the episode record of this row is episode 1 .'} | eq { hop { argmax { all_rows ; viewers } ; episode } ; episode 1 } = true | select the row whose viewers record of all rows is maximum . the episode record of this row is episode 1 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'viewers_5': 5, 'episode_6': 6, 'episode 1_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'viewers_5': 'viewers', 'episode_6': 'episode', 'episode 1_7': 'episode 1'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'viewers_5': [0], 'episode_6': [1], 'episode 1_7': [2]} | ['', 'episode', 'director', 'writer', 'original airdate', 'viewers'] | [['1', 'episode 1', 'martin hutchings', 'tony jordan', '8 may 2007', '5.46 m'], ['2', 'episode 2', 'martin hutchings', 'tony jordan', '15 may 2007', '5.16 m'], ['3', 'episode 3', 'bryn higgins', 'james payne', '22 may 2007', '4.42 m'], ['4', 'episode 4', 'bryn higgins', 'sarah phelps', '29 may 2007', 'n / a'], ['5', 'episode 5', 'barnaby southcombe', 'jeff povey', '5 june 2007', '4.1 m'], ['6', 'episode 6', 'barnaby southcombe', 'richard davidson', '12 june 2007', '4 m'], ['7', 'episode 7', 'martin hutchings', 'marc pye', '19 june 2007', '4.13 m']] |
emily hewson | https://en.wikipedia.org/wiki/Emily_Hewson | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15272495-4.html.csv | majority | most of the outcomes of emily hewson 's tennis career for doubles are runner-up . | {'scope': 'all', 'col': '1', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'runner - up', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'outcome', 'runner - up'], 'result': True, 'ind': 0, 'tointer': 'for the outcome records of all rows , most of them fuzzily match to runner - up .', 'tostr': 'most_eq { all_rows ; outcome ; runner - up } = true'} | most_eq { all_rows ; outcome ; runner - up } = true | for the outcome records of all rows , most of them fuzzily match to runner - up . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'outcome_3': 3, 'runner - up_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'outcome_3': 'outcome', 'runner - up_4': 'runner - up'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'outcome_3': [0], 'runner - up_4': [0]} | ['outcome', 'date', 'tournament', 'surface', 'partner', 'opponents in the final', 'score'] | [['runner - up', '13 may 2001', 'swansea , wales', 'clay', 'maria bobedova', 'natalia egorova ekaterina sysoeva', '6 - 4 6 - 7 ( 5 - 7 ) 0 - 6'], ['runner - up', '27 may 2001', 'tel aviv , israel', 'hard', 'natasha van der merwe', 'irina kornienko maria pavlidou', 'w / o'], ['runner - up', '5 august 2001', 'dublin , ireland', 'carpet', 'bree calderwood', 'yvonne doyle karen nugent', '4 - 6 2 - 6'], ['runner - up', '21 march 2004', 'wellington , new zealand', 'grass', 'nicole kriz', 'shelley bryce kristen van elden', '1 - 6 6 - 3 3 - 6'], ['runner - up', '21 march 2004', 'yarrawonga , australia', 'grass', 'nicole kriz', 'beti sekulovski cindy watson', '3 - 6 6 - 4 4 - 6'], ['winner', '28 march 2004', 'yarrawonga , australia', 'grass', 'nicole kriz', 'mirielle dittmann kristen van elden', '6 - 3 6 - 2'], ['runner - up', '20 march 2005', 'yarrawonga , australia', 'grass', 'nicole kriz', 'lara picone julia efremova', '4 - 6 3 - 6'], ['winner', '16 march 2007', 'perth , australia', 'hard', 'casey dellacqua', 'trudi musgrave christina wheeler', '6 - 4 4 - 6 6 - 2'], ['winner', '23 march 2007', 'kalgoorlie , australia', 'grass', 'christina wheeler', 'vivien silfany - tony lavinia tananta', '6 - 4 6 - 3'], ['runner - up', '9 november 2007', 'port pirie , australia', 'hard', 'daniella dominikovic', 'sarah borwell courtney nagle', '2 - 6 2 - 6'], ['winner', '23 august 2008', 'trecastagni , italy', 'hard', 'pemra özgen', 'valeria casillo lilly raffa', 'w / o']] |
media in the fraser valley | https://en.wikipedia.org/wiki/Media_in_the_Fraser_Valley | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18520022-1.html.csv | unique | fm 101.7 is the only university owned radio station in fraser valley . | {'scope': 'all', 'row': '10', 'col': '4', 'col_other': '1', 'criterion': 'fuzzily_match', 'value': 'university', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'owner', 'university'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose owner record fuzzily matches to university .', 'tostr': 'filter_eq { all_rows ; owner ; university }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; owner ; university } }', 'tointer': 'select the rows whose owner record fuzzily matches to university . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'owner', 'university'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose owner record fuzzily matches to university .', 'tostr': 'filter_eq { all_rows ; owner ; university }'}, 'frequency'], 'result': 'fm 101.7', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; owner ; university } ; frequency }'}, 'fm 101.7'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; owner ; university } ; frequency } ; fm 101.7 }', 'tointer': 'the frequency record of this unqiue row is fm 101.7 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; owner ; university } } ; eq { hop { filter_eq { all_rows ; owner ; university } ; frequency } ; fm 101.7 } } = true', 'tointer': 'select the rows whose owner record fuzzily matches to university . there is only one such row in the table . the frequency record of this unqiue row is fm 101.7 .'} | and { only { filter_eq { all_rows ; owner ; university } } ; eq { hop { filter_eq { all_rows ; owner ; university } ; frequency } ; fm 101.7 } } = true | select the rows whose owner record fuzzily matches to university . there is only one such row in the table . the frequency record of this unqiue row is fm 101.7 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'owner_7': 7, 'university_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'frequency_9': 9, 'fm 101.7_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'owner_7': 'owner', 'university_8': 'university', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'frequency_9': 'frequency', 'fm 101.7_10': 'fm 101.7'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'owner_7': [0], 'university_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'frequency_9': [2], 'fm 101.7_10': [3]} | ['frequency', 'call sign', 'format', 'owner', 'notes'] | [['fm 88.1', 'vf2522', 'tourist information', 'cameron bell consultancy', 'licensed to chilliwack'], ['fm 88.5', 'cbu - 1 - fm', 'news / talk', 'canadian broadcasting corporation', 'licensed to abbotsford'], ['fm 89.5', 'chwk - fm', 'active rock', 'fabmar communications', 'licensed to chilliwack'], ['fm 91.7', 'cbyf - fm', 'news / talk', 'canadian broadcasting corporation', 'licensed to chilliwack'], ['fm 92.5', 'cfun - fm - 1', 'contemporary hit radio', 'rogers media', 'licensed to abbotsford'], ['fm 96.7', 'cbyh - fm', 'news / talk', 'canadian broadcasting corporation', 'licensed to harrison hot springs'], ['fm 98.3', 'cksr - fm', 'adult contemporary', 'rogers media', 'licensed to chilliwack'], ['fm 99.9', 'cbu - fm - 7', 'public music', 'canadian broadcasting corporation', 'licensed to chilliwack'], ['fm 100.5', 'cfsr - fm', 'adult contemporary', 'rogers media', 'licensed to hope'], ['fm 101.7', 'civl - fm', 'campus radio', 'university of the fraser valley', 'licensed to abbotsford'], ['fm 101.7', 'cbue - fm', 'news / talk', 'canadian broadcasting corporation', 'licensed to hope'], ['fm 102.1', 'cbuf - fm - 1', 'news / talk', 'canadian broadcasting corporation', 'licensed to chilliwack'], ['fm 107.1', 'ckqc - fm', 'country', 'rogers media', 'licensed to abbotsford'], ['fm 107.5', 'cfun - fm', 'contemporary hit radio', 'rogers media', 'licensed to chilliwack']] |
2008 twenty20 cup | https://en.wikipedia.org/wiki/2008_Twenty20_Cup | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17900317-4.html.csv | count | three players in the 2008 twenty20 cup played in a total of exactly 10 matches . | {'scope': 'all', 'criterion': 'equal', 'value': '10', 'result': '3', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'matches', '10'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose matches record is equal to 10 .', 'tostr': 'filter_eq { all_rows ; matches ; 10 }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; matches ; 10 } }', 'tointer': 'select the rows whose matches record is equal to 10 . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; matches ; 10 } } ; 3 } = true', 'tointer': 'select the rows whose matches record is equal to 10 . the number of such rows is 3 .'} | eq { count { filter_eq { all_rows ; matches ; 10 } } ; 3 } = true | select the rows whose matches record is equal to 10 . the number of such rows is 3 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_eq_0': 0, 'all_rows_4': 4, 'matches_5': 5, '10_6': 6, '3_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'matches_5': 'matches', '10_6': '10', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'matches_5': [0], '10_6': [0], '3_7': [2]} | ['player', 'team', 'matches', 'inns', 'runs', 'balls', 's / rate', '100s', 'average'] | [['joe denly', 'kent spitfires', '13', '13', '451', '379', '118.99', '0', '34.69'], ['anthony mcgrath', 'yorkshire carnegie', '9', '9', '392', '296', '132.43', '0', '56.00'], ['murray goodwin', 'sussex sharks', '10', '10', '345', '273', '126.37', '0', '43.13'], ['robert key', 'kent spitfires', '13', '13', '345', '258', '133.72', '0', '26.53'], ['michael carberry', 'hampshire hawks', '10', '10', '334', '268', '124.62', '0', '37.11'], ['graham napier', 'essex eagles', '12', '11', '326', '167', '195.20', '1', '32.60'], ['michael lumb', 'hampshire hawks', '10', '10', '315', '209', '150.71', '0', '31.50'], ['marcus trescothick', 'somerset sabres', '8', '8', '306', '185', '165.40', '1', '38.25'], ['dawid malan', 'middlesex crusaders', '12', '10', '306', '220', '139.09', '1', '61.20'], ['phil mustard', 'durham dynamos', '11', '11', '303', '224', '135.26', '0', '27.54']] |
list of the busiest airports in the united states | https://en.wikipedia.org/wiki/List_of_the_busiest_airports_in_the_United_States | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-18047346-4.html.csv | majority | the majority of airports had a 4.5 % change or higher . | {'scope': 'all', 'col': '6', 'most_or_all': 'most', 'criterion': 'greater_than_eq', 'value': '4.5 %', 'subset': None} | {'func': 'most_greater_eq', 'args': ['all_rows', '% chg 2009 / 10', '4.5 %'], 'result': True, 'ind': 0, 'tointer': 'for the % chg 2009 / 10 records of all rows , most of them are greater than or equal to 4.5 % .', 'tostr': 'most_greater_eq { all_rows ; % chg 2009 / 10 ; 4.5 % } = true'} | most_greater_eq { all_rows ; % chg 2009 / 10 ; 4.5 % } = true | for the % chg 2009 / 10 records of all rows , most of them are greater than or equal to 4.5 % . | 1 | 1 | {'most_greater_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, '% chg 2009 / 10_3': 3, '4.5%_4': 4} | {'most_greater_eq_0': 'most_greater_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', '% chg 2009 / 10_3': '% chg 2009 / 10', '4.5%_4': '4.5 %'} | {'most_greater_eq_0': [1], 'result_1': [], 'all_rows_2': [0], '% chg 2009 / 10_3': [0], '4.5%_4': [0]} | ['rank', 'airport name', 'location', 'iata code', 'passengers', '% chg 2009 / 10'] | [['1', 'john f kennedy international airport', 'queens , new york', 'jfk', '22702882', '5.8 %'], ['2', 'miami international airport', 'miami , florida', 'mia', '16207353', '5.3 %'], ['3', 'los angeles international airport', 'los angeles , california', 'lax', '15505566', '4.7 %'], ['4', 'newark liberty international airport', 'newark , new jersey', 'ewr', '11372186', '6.6 %'], ['5', "o'hare international airport", 'chicago , illinois', 'ord', '10426287', '2.5 %'], ['6', 'hartsfield - jackson atlanta international airport', 'atlanta , georgia', 'atl', '9120974', '4.1 %'], ['7', 'san francisco international airport', 'san mateo county , california', 'sfo', '8476172', '7.4 %'], ['8', 'george bush intercontinental airport', 'houston , texas', 'iah', '8279513', '9.5 %'], ['9', 'washington dulles international airport', 'dulles , virginia', 'iad', '6167501', '9.5 %']] |
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/2-13599687-8.html.csv | majority | michael schumacher had most of the wins in the formula one races . | {'scope': 'all', 'col': '1', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'michael schumacher', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'driver', 'michael schumacher'], 'result': True, 'ind': 0, 'tointer': 'for the driver records of all rows , most of them fuzzily match to michael schumacher .', 'tostr': 'most_eq { all_rows ; driver ; michael schumacher } = true'} | most_eq { all_rows ; driver ; michael schumacher } = true | for the driver records of all rows , most of them fuzzily match to michael schumacher . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'driver_3': 3, 'michael schumacher_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'driver_3': 'driver', 'michael schumacher_4': 'michael schumacher'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'driver_3': [0], 'michael schumacher_4': [0]} | ['driver', 'season', 'wins', 'entries', 'percentage'] | [['michael schumacher', '2004', '13', '18', '72.22 %'], ['michael schumacher', '2002', '11', '17', '64.70 %'], ['sebastian vettel', '2011', '11', '19', '57.89 %'], ['sebastian vettel', '2013', '11', '17', '64.70 %'], ['nigel mansell', '1992', '9', '16', '56.25 %'], ['michael schumacher', '1995', '9', '17', '52.94 %'], ['michael schumacher', '2000', '9', '17', '52.94 %'], ['michael schumacher', '2001', '9', '17', '52.94 %'], ['ayrton senna', '1988', '8', '16', '50.00 %'], ['michael schumacher', '1994', '8', '14', '57.14 %'], ['damon hill', '1996', '8', '16', '50.00 %'], ['mika hã ¤ kkinen', '1998', '8', '16', '50.00 %']] |
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/2-15100419-3.html.csv | ordinal | james hamilton was the third highest overall player drafted by the jacksonville jaguars . | {'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': 'james hamilton', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; overall ; 3 } ; name }'}, 'james hamilton'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; overall ; 3 } ; name } ; james hamilton } = true', 'tointer': 'select the row whose overall record of all rows is 3rd minimum . the name record of this row is james hamilton .'} | eq { hop { nth_argmin { all_rows ; overall ; 3 } ; name } ; james hamilton } = true | select the row whose overall record of all rows is 3rd minimum . the name record of this row is james hamilton . | 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, 'james hamilton_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', 'james hamilton_8': 'james hamilton'} | {'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], 'james hamilton_8': [2]} | ['round', 'pick', 'overall', 'name', 'position', 'college'] | [['1', '21', '21', 'renaldo wynn', 'defensive tackle', 'notre dame'], ['2', '20', '50', 'mike logan', 'cornerback', 'west virginia'], ['3', '19', '79', 'james hamilton', 'linebacker', 'north carolina'], ['4', '18', '114', 'seth payne', 'defensive tackle', 'cornell'], ['5', '17', '147', 'damon jones', 'tight end', 'southern illinois'], ['6', '21', '184', 'daimon shelton', 'fullback', 'sacramento state'], ['7', '20', '221', 'jon hesse', 'linebacker', 'nebraska']] |
netflow | https://en.wikipedia.org/wiki/NetFlow | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1206114-2.html.csv | unique | enterasys switches are the only netflow supported routers that implements as dedicated hardware . | {'scope': 'all', 'row': '4', 'col': '4', 'col_other': '1', 'criterion': 'equal', 'value': 'dedicated hardware', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'implementation', 'dedicated hardware'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose implementation record fuzzily matches to dedicated hardware .', 'tostr': 'filter_eq { all_rows ; implementation ; dedicated hardware }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; implementation ; dedicated hardware } }', 'tointer': 'select the rows whose implementation record fuzzily matches to dedicated hardware . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'implementation', 'dedicated hardware'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose implementation record fuzzily matches to dedicated hardware .', 'tostr': 'filter_eq { all_rows ; implementation ; dedicated hardware }'}, 'vendor and type'], 'result': 'enterasys switches', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; implementation ; dedicated hardware } ; vendor and type }'}, 'enterasys switches'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; implementation ; dedicated hardware } ; vendor and type } ; enterasys switches }', 'tointer': 'the vendor and type record of this unqiue row is enterasys switches .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; implementation ; dedicated hardware } } ; eq { hop { filter_eq { all_rows ; implementation ; dedicated hardware } ; vendor and type } ; enterasys switches } } = true', 'tointer': 'select the rows whose implementation record fuzzily matches to dedicated hardware . there is only one such row in the table . the vendor and type record of this unqiue row is enterasys switches .'} | and { only { filter_eq { all_rows ; implementation ; dedicated hardware } } ; eq { hop { filter_eq { all_rows ; implementation ; dedicated hardware } ; vendor and type } ; enterasys switches } } = true | select the rows whose implementation record fuzzily matches to dedicated hardware . there is only one such row in the table . the vendor and type record of this unqiue row is enterasys switches . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'implementation_7': 7, 'dedicated hardware_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'vendor and type_9': 9, 'enterasys switches_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'implementation_7': 'implementation', 'dedicated hardware_8': 'dedicated hardware', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'vendor and type_9': 'vendor and type', 'enterasys switches_10': 'enterasys switches'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'implementation_7': [0], 'dedicated hardware_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'vendor and type_9': [2], 'enterasys switches_10': [3]} | ['vendor and type', 'models', 'netflow version', 'implementation', 'comments'] | [['cisco ios - xr routers', 'crs , asr9000 old 12000', 'v5 , v8 , v9', 'software running on line card cpu', 'comprehensive support for ipv6 and mpls'], ['alcatel - lucent routers', '7750sr', 'v5 , v8 , v9 , ipfix', 'software running on central processor module', 'ipv6 or mpls using iom3 line cards or better'], ['huawei routers', 'ne5000e ne40e / x ne80e', 'v5 , v9', 'software running on service cards', 'support for ipv6 or mpls is unknown'], ['enterasys switches', 's - serie and n - serie', 'v5 , v9', 'dedicated hardware', 'ipv6 support is unknown'], ['pc and servers', 'linux freebsd netbsd openbsd', 'v5 , v9 , ipfix', 'software like fprobe , ipt - netflow or pflow', 'ipv6 support depend on the software used'], ['vmware servers', 'vsphere 5 . x', 'v5', 'software', 'ipv6 support is unknown']] |
forbes global 2000 | https://en.wikipedia.org/wiki/Forbes_Global_2000 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1682026-3.html.csv | aggregation | the average banking industry company profits shown in the forbes global list in 2000 was 13.9 billion . | {'scope': 'subset', 'col': '6', 'type': 'average', 'result': '13.9 billion', 'subset': {'col': '4', 'criterion': 'equal', 'value': 'banking'}} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'industry', 'banking'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; industry ; banking }', 'tointer': 'select the rows whose industry record fuzzily matches to banking .'}, 'profits ( billion )'], 'result': '13.9 billion', 'ind': 1, 'tostr': 'avg { filter_eq { all_rows ; industry ; banking } ; profits ( billion ) }'}, '13.9 billion'], 'result': True, 'ind': 2, 'tostr': 'round_eq { avg { filter_eq { all_rows ; industry ; banking } ; profits ( billion ) } ; 13.9 billion } = true', 'tointer': 'select the rows whose industry record fuzzily matches to banking . the average of the profits ( billion ) record of these rows is 13.9 billion .'} | round_eq { avg { filter_eq { all_rows ; industry ; banking } ; profits ( billion ) } ; 13.9 billion } = true | select the rows whose industry record fuzzily matches to banking . the average of the profits ( billion ) record of these rows is 13.9 billion . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'avg_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'industry_5': 5, 'banking_6': 6, 'profits (billion )_7': 7, '13.9 billion_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'avg_1': 'avg', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'industry_5': 'industry', 'banking_6': 'banking', 'profits (billion )_7': 'profits ( billion )', '13.9 billion_8': '13.9 billion'} | {'eq_2': [3], 'result_3': [], 'avg_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'industry_5': [0], 'banking_6': [0], 'profits (billion )_7': [1], '13.9 billion_8': [2]} | ['rank', 'company', 'headquarters', 'industry', 'sales ( billion )', 'profits ( billion )', 'assets ( billion )', 'market value ( billion )'] | [['01', 'jpmorgan chase', 'usa', 'banking', '115.5', '17.4', '2117.6', '182.2'], ['02', 'hsbc', 'uk', 'banking', '103.3', '13.3', '2467.9', '186.5'], ['03', 'general electric', 'usa', 'conglomerate', '156.2', '11.6', '751.2', '216.2'], ['04', 'exxonmobil', 'usa', 'oil and gas', '341.6', '30.5', '302.5', '407.2'], ['05', 'royal dutch shell', 'netherlands', 'oil and gas', '369.1', '20.1', '317.2', '212.9'], ['06', 'petrochina', 'china', 'oil and gas', '222.3', '21.2', '251.3', '320.8'], ['07', 'industrial and commercial bank of china', 'china', 'banking', '69.2', '18.8', '1723.5', '239.5'], ['08', 'berkshire hathaway', 'usa', 'conglomerate', '136.2', '13', '372.2', '211'], ['08', 'petrobras', 'brazil', 'oil and gas', '121.3', '21.2', '313.2', '238.8'], ['10', 'citigroup', 'usa', 'banking', '111.5', '10.6', '1913.9', '132.8'], ['11', 'bnp paribas', 'france', 'banking', '130.4', '10.5', '2680.7', '88'], ['11', 'wells fargo', 'usa', 'banking', '93.2', '12.4', '1258.1', '170.6'], ['13', 'santander group', 'spain', 'banking', '109.7', '12.8', '1570.6', '94.7'], ['14', 'at & t inc', 'usa', 'telecommunications', '124.3', '19.9', '268.5', '168.2'], ['15', 'gazprom', 'russia', 'oil and gas', '98.7', '25.7', '275.9', '172.9'], ['16', 'chevron', 'usa', 'oil and gas', '189.6', '19', '184.8', '200.6'], ['17', 'china construction bank', 'china', 'banking', '58.2', '15.6', '1408', '224.8'], ['18', 'walmart', 'usa', 'retailing', '421.8', '16.4', '180.7', '187.3'], ['19', 'total', 'france', 'oil and gas', '188.1', '14.2', '192.8', '138'], ['20', 'allianz', 'germany', 'insurance', '142.9', '6.7', '838.4', '62.7']] |
list of ultras of oceania | https://en.wikipedia.org/wiki/List_of_Ultras_of_Oceania | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18946749-5.html.csv | aggregation | the average elevation of ultra summits of oceania is 1952 meters . | {'scope': 'all', 'col': '5', 'type': 'average', 'result': '1952', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'elevation ( m )'], 'result': '1952', 'ind': 0, 'tostr': 'avg { all_rows ; elevation ( m ) }'}, '1952'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; elevation ( m ) } ; 1952 } = true', 'tointer': 'the average of the elevation ( m ) record of all rows is 1952 .'} | round_eq { avg { all_rows ; elevation ( m ) } ; 1952 } = true | the average of the elevation ( m ) record of all rows is 1952 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'elevation (m)_4': 4, '1952_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'elevation (m)_4': 'elevation ( m )', '1952_5': '1952'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'elevation (m)_4': [0], '1952_5': [1]} | ['rank', 'peak', 'country', 'island', 'elevation ( m )', 'col ( m )'] | [['1', 'mount popomanaseu', 'solomon islands', 'guadalcanal', '2335', '0'], ['2', 'mont orohena', 'french polynesia', 'tahiti', '2241', '0'], ['3', 'mount tabwemasana', 'vanuatu', 'espiritu santo', '1879', '0'], ['4', 'silisili', 'samoa', "savai'i", '1858', '0'], ['5', 'mount veve', 'solomon islands', 'kolombangara', '1768', '0'], ['6', 'mont paniã', 'new caledonia', 'grande terre', '1628', '0']] |
gilbert aldana | https://en.wikipedia.org/wiki/Gilbert_Aldana | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17441930-2.html.csv | count | a total of two of gilbert aldana 's fights took place in nevada , united states . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'nevada , united states', 'result': '2', 'col': '8', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location', 'nevada , united states'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose location record fuzzily matches to nevada , united states .', 'tostr': 'filter_eq { all_rows ; location ; nevada , united states }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; location ; nevada , united states } }', 'tointer': 'select the rows whose location record fuzzily matches to nevada , united states . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; location ; nevada , united states } } ; 2 } = true', 'tointer': 'select the rows whose location record fuzzily matches to nevada , united states . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; location ; nevada , united states } } ; 2 } = true | select the rows whose location record fuzzily matches to nevada , united states . 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, 'location_5': 5, 'nevada, united states_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', 'location_5': 'location', 'nevada, united states_6': 'nevada , united states', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'location_5': [0], 'nevada, united states_6': [0], '2_7': [2]} | ['res', 'record', 'opponent', 'method', 'event', 'round', 'time', 'location'] | [['win', '6 - 2', 'rich beecroft', 'submission ( kimura )', 'ritc 90 - rage in the cage', '1', '0:26', 'arizona , united states'], ['loss', '5 - 2', 'cheick kongo', 'tko ( doctor stoppage )', 'ufc 61', '1', '4:13', 'nevada , united states'], ['loss', '5 - 1', 'paul buentello', 'tko ( strikes )', 'ufc 57', '2', '2:27', 'nevada , united states'], ['win', '5 - 0', 'chad armstrong', 'tko', 'ritc 75 - friday night fights', '1', '1:00', 'arizona , united states'], ['win', '4 - 0', 'melville calabaca', 'ko', 'ritc 70 - rage in the cage 70', '1', '0:30', 'arizona , united states'], ['win', '3 - 0', 'tim mcmullen', 'ko', 'ritc 65 - rage in the cage 65', '1', '0:15', 'arizona , united states'], ['win', '2 - 0', 'karl perkins', 'ko', 'ritc 62 - more punishment', '1', '1:55', 'arizona , united states'], ['win', '1 - 0', 'herb garcia', 'ko', 'ritc 61 - relentless', '1', '0:03', 'arizona , united states']] |
banking and insurance in iran | https://en.wikipedia.org/wiki/Banking_and_insurance_in_Iran | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16254980-5.html.csv | comparative | the assets score for mellat bank is lower than the bank of industry and mine . | {'row_1': '4', 'row_2': '3', 'col': '7', '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', 'bank', 'mellat bank'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose bank record fuzzily matches to mellat bank .', 'tostr': 'filter_eq { all_rows ; bank ; mellat bank }'}, 'total assets ( score )'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; bank ; mellat bank } ; total assets ( score ) }', 'tointer': 'select the rows whose bank record fuzzily matches to mellat bank . take the total assets ( score ) record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'bank', 'bank of industry and mine'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose bank record fuzzily matches to bank of industry and mine .', 'tostr': 'filter_eq { all_rows ; bank ; bank of industry and mine }'}, 'total assets ( score )'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; bank ; bank of industry and mine } ; total assets ( score ) }', 'tointer': 'select the rows whose bank record fuzzily matches to bank of industry and mine . take the total assets ( score ) record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; bank ; mellat bank } ; total assets ( score ) } ; hop { filter_eq { all_rows ; bank ; bank of industry and mine } ; total assets ( score ) } } = true', 'tointer': 'select the rows whose bank record fuzzily matches to mellat bank . take the total assets ( score ) record of this row . select the rows whose bank record fuzzily matches to bank of industry and mine . take the total assets ( score ) record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; bank ; mellat bank } ; total assets ( score ) } ; hop { filter_eq { all_rows ; bank ; bank of industry and mine } ; total assets ( score ) } } = true | select the rows whose bank record fuzzily matches to mellat bank . take the total assets ( score ) record of this row . select the rows whose bank record fuzzily matches to bank of industry and mine . take the total assets ( score ) 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, 'bank_7': 7, 'mellat bank_8': 8, 'total assets (score)_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'bank_11': 11, 'bank of industry and mine_12': 12, 'total assets (score)_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', 'bank_7': 'bank', 'mellat bank_8': 'mellat bank', 'total assets (score)_9': 'total assets ( score )', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'bank_11': 'bank', 'bank of industry and mine_12': 'bank of industry and mine', 'total assets (score)_13': 'total assets ( score )'} | {'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'bank_7': [0], 'mellat bank_8': [0], 'total assets (score)_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'bank_11': [1], 'bank of industry and mine_12': [1], 'total assets (score)_13': [3]} | ['bank', 'score ( iran )', 'score ( global )', 'banking power / capital base ( million )', 'banking power / capital base ( % change )', 'total assets ( million )', 'total assets ( score )', 'total assets ( % change )', 'credibility / capital to assets ratio ( % )', 'credibility / capital to assets ratio ( score )', 'performance / return on capital ( % )', 'performance / return on capital ( score )', 'return on assets ( % )', 'return on assets ( score )'] | [['bank saderat iran', '1', '259', '3109', '4.46', '54877', '3', '14.22', '5.66', '7', '25.63', '8', '1.45', '7'], ['pasargad bank', '2', '266', '3057', '147.7', '18057', '8', '47.41', '16.93', '3', '20.69', '9', '3.5', '2'], ['bank of industry and mine', '3', '310', '2550', '- 2.16', '9432', '10', '12.1', '27.04', '2', '3.2', '13', '0.87', '10'], ['mellat bank', '4', '320', '2402', 'nm', '68370', '2', 'nm', '3.51', '12', '32.59', '15', '1.14', '9'], ['tejarat bank', '5', '350', '2103', '13.6', '68370', '4', '18.65', '4.66', '9', '27.14', '7', '1.26', '8']] |
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