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toronto raptors all - time roster | https://en.wikipedia.org/wiki/Toronto_Raptors_all-time_roster | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-10015132-21.html.csv | ordinal | corliss williamson wore the fourth highest number on the toronto raptors all - time roster . | {'row': '12', 'col': '2', 'order': '4', 'col_other': '1', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'no', '4'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; no ; 4 }'}, 'player'], 'result': 'corliss williamson', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; no ; 4 } ; player }'}, 'corliss williamson'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; no ; 4 } ; player } ; corliss williamson } = true', 'tointer': 'select the row whose no record of all rows is 4th maximum . the player record of this row is corliss williamson .'} | eq { hop { nth_argmax { all_rows ; no ; 4 } ; player } ; corliss williamson } = true | select the row whose no record of all rows is 4th maximum . the player record of this row is corliss williamson . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'no_5': 5, '4_6': 6, 'player_7': 7, 'corliss williamson_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'no_5': 'no', '4_6': '4', 'player_7': 'player', 'corliss williamson_8': 'corliss williamson'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'no_5': [0], '4_6': [0], 'player_7': [1], 'corliss williamson_8': [2]} | ['player', 'no', 'nationality', 'position', 'years in toronto', 'school / club team'] | [['john wallace', '44', 'united states', 'forward', '1997 - 99', 'syracuse'], ['sonny weems', '24', 'united states', 'guard', '2009 - 2011', 'arkansas'], ['donald whiteside', '12', 'united states', 'guard', '1996 - 97', 'northern illinois'], ['dwayne whitfield', '23', 'united states', 'forward', '1995 - 96', 'jackson state'], ['aaron williams', '34', 'united states', 'forward - center', '2004 - 05', 'xavier ( ohio )'], ['alvin williams', '20', 'united states', 'guard', '1998 - 2006', 'villanova'], ['eric williams', '17', 'united states', 'forward', '2004 - 06', 'providence'], ['herb williams', '32', 'united states', 'forward - center', '1996', 'ohio state'], ['jerome williams', '13', 'united states', 'forward', '2001 - 03', 'georgetown'], ['micheal williams', '14', 'united states', 'guard', '1998 - 99', 'baylor'], ['walt williams', '42', 'united states', 'guard - forward', '1996 - 98', 'maryland'], ['corliss williamson', '35', 'united states', 'forward', '2000 - 01', 'arkansas'], ['kevin willis', '42', 'united states', 'center', '1998 - 2001', 'michigan state'], ['loren woods', '3', 'united states', 'center', '2004 - 06', 'arizona'], ['haywoode workman', '3', 'united states', 'guard', '2000', 'oral roberts'], ['antoine wright', '21', 'united states', 'guard - forward', '2009 - 10', 'texas a & m'], ['julian wright', '14', 'united states', 'small forward', '2010 - 2011', 'kansas']] |
2001 lff lyga | https://en.wikipedia.org/wiki/2001_LFF_Lyga | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18018214-1.html.csv | majority | all of the teams in the 2001 lff lyga played 36 games in the league . | {'scope': 'all', 'col': '3', 'most_or_all': 'all', 'criterion': 'equal', 'value': '36', 'subset': None} | {'func': 'all_eq', 'args': ['all_rows', 'games played', '36'], 'result': True, 'ind': 0, 'tointer': 'for the games played records of all rows , all of them are equal to 36 .', 'tostr': 'all_eq { all_rows ; games played ; 36 } = true'} | all_eq { all_rows ; games played ; 36 } = true | for the games played records of all rows , all of them are equal to 36 . | 1 | 1 | {'all_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'games played_3': 3, '36_4': 4} | {'all_eq_0': 'all_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'games played_3': 'games played', '36_4': '36'} | {'all_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'games played_3': [0], '36_4': [0]} | ['position', 'club', 'games played', 'wins', 'draws', 'loses', 'goals scored', 'goals conceded', 'points'] | [['1', 'fbk kaunas', '36', '26', '7', '3', '76', '13', '85'], ['2', 'fk atlantas', '36', '19', '12', '5', '66', '29', '69'], ['3', 'fk žalgiris vilnius', '36', '20', '9', '7', '64', '39', '69'], ['4', 'fk ekranas', '36', '15', '10', '11', '58', '38', '55'], ['5', 'inkaras kaunas', '36', '11', '12', '13', '50', '44', '45'], ['6', 'geležinis vilkas vilnius', '36', '10', '6', '20', '42', '69', '36'], ['7', 'nevėžis kėdainiai', '36', '8', '11', '17', '33', '54', '35'], ['8', 'sakalas šiauliai', '36', '7', '13', '16', '32', '61', '34'], ['9', 'vėtra rūdiškės', '36', '7', '11', '18', '32', '57', '32'], ['10', 'dainava alytus', '36', '7', '9', '20', '34', '83', '30']] |
lark rise to candleford ( tv series ) | https://en.wikipedia.org/wiki/Lark_Rise_to_Candleford_%28TV_series%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-15026994-2.html.csv | majority | bill gallagher wrote most of the episodes of lark rise to candleford . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'bill gallagher', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'writer', 'bill gallagher'], 'result': True, 'ind': 0, 'tointer': 'for the writer records of all rows , most of them fuzzily match to bill gallagher .', 'tostr': 'most_eq { all_rows ; writer ; bill gallagher } = true'} | most_eq { all_rows ; writer ; bill gallagher } = true | for the writer records of all rows , most of them fuzzily match to bill gallagher . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'writer_3': 3, 'bill gallagher_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'writer_3': 'writer', 'bill gallagher_4': 'bill gallagher'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'writer_3': [0], 'bill gallagher_4': [0]} | ['', 'episode', 'writer', 'director', 'original air date', 'viewing figure'] | [['1', 'episode 1', 'bill gallagher', 'charles palmer', '13 january 2008', '7.27 million'], ['2', 'episode 2', 'bill gallagher', 'charles palmer', '20 january 2008', '7.01 million'], ['3', 'episode 3', 'bill gallagher', 'charles palmer', '27 january 2008', '6.66 million'], ['4', 'episode 4', 'paul rutman', 'john greening', '3 february 2008', '6.72 million'], ['5', 'episode 5', 'bill gallagher', 'charles palmer', '10 february 2008', '6.85 million'], ['6', 'episode 6', 'bill gallagher', 'john greening', '17 february 2008', '6.68 million'], ['7', 'episode 7', 'carolyn bonnyman', 'marc jobst', '24 february 2008', '6.70 million'], ['8', 'episode 8', 'gaby chiappe', 'marc jobst', '2 march 2008', '6.48 million'], ['9', 'episode 9', 'bill gallagher', 'john greening', '9 march 2008', '6.21 million']] |
iran at the asian games | https://en.wikipedia.org/wiki/Iran_at_the_Asian_Games | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10882501-1.html.csv | superlative | the most gold medals iran won was at the 1974 games . | {'scope': 'all', 'col_superlative': '2', 'row_superlative': '7', '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', 'gold'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; gold }'}, 'gold'], 'result': '36', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; gold } ; gold }'}, '36'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; gold } ; gold } ; 36 } = true', 'tointer': 'select the row whose gold record of all rows is maximum . the gold record of this row is 36 .'} | eq { hop { argmax { all_rows ; gold } ; gold } ; 36 } = true | select the row whose gold record of all rows is maximum . the gold record of this row is 36 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'gold_5': 5, 'gold_6': 6, '36_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'gold_5': 'gold', 'gold_6': 'gold', '36_7': '36'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'gold_5': [0], 'gold_6': [1], '36_7': [2]} | ['games', 'gold', 'silver', 'bronze', 'total', 'rank'] | [['1951 new delhi', '8', '6', '2', '16', '3'], ['1954 manila', 'did not participate', 'did not participate', 'did not participate', 'did not participate', 'did not participate'], ['1958 tokyo', '7', '14', '11', '32', '4'], ['1962 jakarta', 'did not participate', 'did not participate', 'did not participate', 'did not participate', 'did not participate'], ['1966 bangkok', '6', '8', '17', '31', '6'], ['1970 bangkok', '9', '7', '7', '23', '4'], ['1974 tehran', '36', '28', '17', '81', '2'], ['1978 bangkok', 'did not participate', 'did not participate', 'did not participate', 'did not participate', 'did not participate'], ['1982 new delhi', '4', '4', '4', '12', '7'], ['1986 seoul', '6', '6', '10', '22', '4'], ['1990 beijing', '4', '6', '8', '18', '5'], ['1994 hiroshima', '9', '9', '8', '26', '6'], ['1998 bangkok', '10', '11', '13', '34', '7'], ['2002 busan', '8', '14', '14', '36', '10'], ['2006 doha', '11', '15', '22', '48', '6'], ['2010 guangzhou', '20', '15', '24', '59', '4'], ['total', '138', '143', '157', '438', '4']] |
united states house of representatives elections , 1868 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1868 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1434788-5.html.csv | count | 3 incumbents were re - elected during the 1868 united states house of representatives elections . | {'scope': 'all', 'criterion': 'equal', 'value': 're - elected', 'result': '3', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'result', 're - elected'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose result record fuzzily matches to re - elected .', 'tostr': 'filter_eq { all_rows ; result ; re - elected }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; result ; re - elected } }', 'tointer': 'select the rows whose result record fuzzily matches to re - elected . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; result ; re - elected } } ; 3 } = true', 'tointer': 'select the rows whose result record fuzzily matches to re - elected . the number of such rows is 3 .'} | eq { count { filter_eq { all_rows ; result ; re - elected } } ; 3 } = true | select the rows whose result record fuzzily matches to re - elected . 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, 'result_5': 5, 're - elected_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', 'result_5': 'result', 're - elected_6': 're - elected', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'result_5': [0], 're - elected_6': [0], '3_7': [2]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['ohio 7', 'samuel shellabarger', 'republican', '1864', 'retired republican hold', 'james j winans ( r ) 50.2 % john h thomas ( d ) 49.8 %'], ['ohio 8', 'john beatty', 'republican', '1868 ( s )', 're - elected', 'john beatty ( r ) 52.0 % john h benson ( d ) 48.0 %'], ['ohio 10', 'james m ashley', 'republican', '1862', 'lost re - election democratic gain', 'truman h hoag ( d ) 51.5 % james m ashley ( d ) 48.5 %'], ['ohio 11', 'john thomas wilson', 'republican', '1866', 're - elected', 'john thomas wilson ( r ) 54.2 % john sands ( d ) 45.8 %'], ['ohio 16', 'john bingham', 'republican', '1864', 're - elected', 'john bingham ( r ) 50.8 % josiah m estep ( d ) 49.2 %']] |
athletics at the 2008 summer olympics - women 's 200 metres | https://en.wikipedia.org/wiki/Athletics_at_the_2008_Summer_Olympics_%E2%80%93_Women%27s_200_metres | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18569021-5.html.csv | unique | emily freeman was the only athlete in the women 's 200 metres at the 2008 summer olympics to come from great britain . | {'scope': 'all', 'row': '7', 'col': '4', 'col_other': '3', 'criterion': 'equal', 'value': 'great britain', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'great britain'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose country record fuzzily matches to great britain .', 'tostr': 'filter_eq { all_rows ; country ; great britain }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; country ; great britain } }', 'tointer': 'select the rows whose country record fuzzily matches to great britain . 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', 'great britain'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose country record fuzzily matches to great britain .', 'tostr': 'filter_eq { all_rows ; country ; great britain }'}, 'athlete'], 'result': 'emily freeman', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; country ; great britain } ; athlete }'}, 'emily freeman'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; country ; great britain } ; athlete } ; emily freeman }', 'tointer': 'the athlete record of this unqiue row is emily freeman .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; country ; great britain } } ; eq { hop { filter_eq { all_rows ; country ; great britain } ; athlete } ; emily freeman } } = true', 'tointer': 'select the rows whose country record fuzzily matches to great britain . there is only one such row in the table . the athlete record of this unqiue row is emily freeman .'} | and { only { filter_eq { all_rows ; country ; great britain } } ; eq { hop { filter_eq { all_rows ; country ; great britain } ; athlete } ; emily freeman } } = true | select the rows whose country record fuzzily matches to great britain . there is only one such row in the table . the athlete record of this unqiue row is emily freeman . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'country_7': 7, 'great britain_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'athlete_9': 9, 'emily freeman_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', 'great britain_8': 'great britain', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'athlete_9': 'athlete', 'emily freeman_10': 'emily freeman'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'country_7': [0], 'great britain_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'athlete_9': [2], 'emily freeman_10': [3]} | ['rank', 'lane', 'athlete', 'country', 'time', 'react'] | [['1', '7', 'allyson felix', 'united states', '22.33', '0.181'], ['2', '9', 'marshevet hooker', 'united states', '22.50', '0.196'], ['3', '5', 'sherone simpson', 'jamaica', '22.50', '0.175'], ['4', '3', 'cydonie mothersille', 'cayman islands', '22.61', '0.212'], ['5', '4', 'muriel hurtis - houairi', 'france', '22.71', '0.188'], ['6', '6', 'roqaya al - gassra', 'bahrain', '22.72', '0.259'], ['7', '8', 'emily freeman', 'great britain', '22.83', '0.201'], ['8', '2', 'aleksandra fedoriva', 'russia', '23.22', '0.202']] |
1957 vfl season | https://en.wikipedia.org/wiki/1957_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10774891-12.html.csv | aggregation | in the 1957 vfl season , the average home team score was 13.47 . | {'scope': 'all', 'col': '2', 'type': 'average', 'result': '13.47', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'home team score'], 'result': '13.47', 'ind': 0, 'tostr': 'avg { all_rows ; home team score }'}, '13.47'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; home team score } ; 13.47 } = true', 'tointer': 'the average of the home team score record of all rows is 13.47 .'} | round_eq { avg { all_rows ; home team score } ; 13.47 } = true | the average of the home team score record of all rows is 13.47 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'home team score_4': 4, '13.47_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'home team score_4': 'home team score', '13.47_5': '13.47'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'home team score_4': [0], '13.47_5': [1]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['north melbourne', '17.15 ( 117 )', 'richmond', '10.13 ( 73 )', 'arden street oval', '21000', '6 july 1957'], ['footscray', '9.11 ( 65 )', 'geelong', '9.10 ( 64 )', 'western oval', '23578', '6 july 1957'], ['south melbourne', '11.15 ( 81 )', 'st kilda', '9.17 ( 71 )', 'lake oval', '18000', '6 july 1957'], ['melbourne', '24.14 ( 158 )', 'fitzroy', '10.14 ( 74 )', 'mcg', '21370', '6 july 1957'], ['essendon', '12.16 ( 88 )', 'collingwood', '10.13 ( 73 )', 'windy hill', '26500', '6 july 1957'], ['hawthorn', '7.10 ( 52 )', 'carlton', '8.13 ( 61 )', 'glenferrie oval', '26000', '6 july 1957']] |
carsten jancker | https://en.wikipedia.org/wiki/Carsten_Jancker | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1834853-3.html.csv | ordinal | of the competitions that carsten jancker has participated in , the 2nd to last was when the venue was vasil levski national stadium . | {'row': '9', 'col': '1', 'order': '2', 'col_other': '2', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'date', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; date ; 2 }'}, 'venue'], 'result': 'vasil levski national stadium , sofia', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; date ; 2 } ; venue }'}, 'vasil levski national stadium , sofia'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; date ; 2 } ; venue } ; vasil levski national stadium , sofia } = true', 'tointer': 'select the row whose date record of all rows is 2nd maximum . the venue record of this row is vasil levski national stadium , sofia .'} | eq { hop { nth_argmax { all_rows ; date ; 2 } ; venue } ; vasil levski national stadium , sofia } = true | select the row whose date record of all rows is 2nd maximum . the venue record of this row is vasil levski national stadium , sofia . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'date_5': 5, '2_6': 6, 'venue_7': 7, 'vasil levski national stadium , sofia_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'date_5': 'date', '2_6': '2', 'venue_7': 'venue', 'vasil levski national stadium , sofia_8': 'vasil levski national stadium , sofia'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'date_5': [0], '2_6': [0], 'venue_7': [1], 'vasil levski national stadium , sofia_8': [2]} | ['date', 'venue', 'score', 'result', 'competition'] | [['3 june 2000', 'easycredit - stadion , nuremberg', '1 - 0', '3 - 2', 'friendly'], ['7 june 2000', 'dreisamstadion , freiburg', '6 - 2', '8 - 2', 'friendly'], ['7 june 2000', 'dreisamstadion , freiburg', '8 - 2', '8 - 2', 'friendly'], ['2 june 2001', 'helsinki olympic stadium , helsinki', '2 - 2', '2 - 2', '2002 world cup qualifier'], ['15 august 2001', 'ferenc puskás stadium , budapest', '3 - 0', '5 - 2', 'friendly'], ['1 september 2001', 'olympiastadion , munich', '1 - 0', '1 - 5', '2002 world cup qualifier'], ['9 may 2002', 'dreisamstadion , freiburg', '7 - 0', '7 - 0', 'friendly'], ['1 june 2002', 'sapporo dome , sapporo', '4 - 0', '8 - 0', '2002 world cup'], ['21 august 2002', 'vasil levski national stadium , sofia', '2 - 2', '2 - 2', 'friendly'], ['11 october 2002', 'asim ferhatović hase stadium , sarajevo', '1 - 1', '1 - 1', 'friendly']] |
1964 st. louis cardinals ( nfl ) season | https://en.wikipedia.org/wiki/1964_St._Louis_Cardinals_%28NFL%29_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16678127-1.html.csv | majority | in the 1964 regular season , the st. louis cardinals won more games than they lost or tied . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': 'w', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'result', 'w'], 'result': True, 'ind': 0, 'tointer': 'for the result records of all rows , most of them fuzzily match to w .', 'tostr': 'most_eq { all_rows ; result ; w } = true'} | most_eq { all_rows ; result ; w } = true | for the result records of all rows , most of them fuzzily match to w . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'result_3': 3, 'w_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'result_3': 'result', 'w_4': 'w'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'result_3': [0], 'w_4': [0]} | ['week', 'date', 'opponent', 'result', 'attendance'] | [['1', 'september 12 , 1964', 'dallas cowboys', 'w 16 - 6', '36605'], ['2', 'september 20 , 1964', 'cleveland browns', 't 33 - 33', '76954'], ['3', 'september 27 , 1964', 'san francisco 49ers', 'w 23 - 13', '30969'], ['4', 'october 4 , 1964', 'washington redskins', 'w 23 - 17', '49219'], ['5', 'october 12 , 1964', 'baltimore colts', 'l 47 - 27', '60213'], ['6', 'october 18 , 1964', 'washington redskins', 'w 38 - 24', '23748'], ['7', 'october 25 , 1964', 'dallas cowboys', 'l 31 - 13', '28253'], ['8', 'november 1 , 1964', 'new york giants', 'l 34 - 17', '63072'], ['9', 'november 8 , 1964', 'pittsburgh steelers', 'w 34 - 30', '28245'], ['10', 'november 15 , 1964', 'new york giants', 't 10 - 10', '29608'], ['11', 'november 22 , 1964', 'philadelphia eagles', 'w 38 - 13', '60671'], ['12', 'november 29 , 1964', 'pittsburgh steelers', 'w 21 - 20', '27807'], ['13', 'december 6 , 1964', 'cleveland browns', 'w 28 - 19', '31585'], ['14', 'december 13 , 1964', 'philadelphia eagles', 'w 36 - 34', '24636']] |
henlopen conference | https://en.wikipedia.org/wiki/Henlopen_Conference | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13054553-8.html.csv | superlative | delmar was the school with the most wins in the overall record . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'overall record'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; overall record }'}, 'school'], 'result': 'delmar', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; overall record } ; school }'}, 'delmar'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; overall record } ; school } ; delmar } = true', 'tointer': 'select the row whose overall record record of all rows is maximum . the school record of this row is delmar .'} | eq { hop { argmax { all_rows ; overall record } ; school } ; delmar } = true | select the row whose overall record record of all rows is maximum . the school record of this row is delmar . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'overall record_5': 5, 'school_6': 6, 'delmar_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'overall record_5': 'overall record', 'school_6': 'school', 'delmar_7': 'delmar'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'overall record_5': [0], 'school_6': [1], 'delmar_7': [2]} | ['school', 'team', 'division record', 'overall record', 'season outcome'] | [['delmar', 'wildcats', '6 - 0', '11 - 1', 'loss in div ii championship game'], ['indian river', 'indians', '5 - 1', '8 - 3', 'loss in first round of div ii playoffs'], ['woodbridge', 'blue raiders', '4 - 2', '6 - 4', 'failed to make playoffs'], ['laurel', 'bulldogs', '3 - 3', '6 - 4', 'failed to make playoffs'], ['smyrna', 'eagles', '2 - 4', '3 - 7', 'failed to make playoffs'], ['seaford', 'blue jays', '1 - 5', '2 - 8', 'failed to make playoffs'], ['lake forest', 'spartans', '1 - 5', '1 - 9', 'failed to make playoffs']] |
los angeles lakers all - time roster | https://en.wikipedia.org/wiki/Los_Angeles_Lakers_all-time_roster | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10560886-13.html.csv | aggregation | the los angeles lakers - all time roster began their time with the lakers at an average year of 1976 . | {'scope': 'all', 'col': '4', 'type': 'average', 'result': '1976', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'from'], 'result': '1976', 'ind': 0, 'tostr': 'avg { all_rows ; from }'}, '1976'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; from } ; 1976 } = true', 'tointer': 'the average of the from record of all rows is 1976 .'} | round_eq { avg { all_rows ; from } ; 1976 } = true | the average of the from record of all rows is 1976 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'from_4': 4, '1976_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'from_4': 'from', '1976_5': '1976'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'from_4': [0], '1976_5': [1]} | ['player', 'nationality', 'position', 'from', 'school / country'] | [['bo lamar', 'united states', 'guard', '1977', 'louisiana - lafayette'], ['jeff lamp', 'united states', 'guard / forward', '1987', 'virginia'], ['mark landsberger', 'united states', 'forward / center', '1979', 'arizona state'], ['stu lantz', 'united states', 'guard', '1974', 'nebraska'], ['rudy larusso', 'united states', 'forward / center', '1959', 'dartmouth'], ['butch lee', 'united states', 'guard', '1979', 'marquette'], ['slick leonard', 'united states', 'guard', '1956', 'indiana'], ['ronnie lester', 'united states', 'guard', '1984', 'iowa'], ['stan love', 'united states', 'forward', '1973', 'oregon'], ['clyde lovellette', 'united states', 'forward / center', '1953', 'kansas'], ['maurice lucas', 'united states', 'forward / center', '1985', 'marquette'], ['tyronn lue', 'united states', 'guard', '1998', 'nebraska'], ['george lynch', 'united states', 'forward', '1993', 'north carolina'], ['mike lynn', 'united states', 'forward', '1969', 'ucla']] |
g and h - class destroyer | https://en.wikipedia.org/wiki/G_and_H-class_destroyer | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1210297-2.html.csv | majority | most of the g and h destroyer ships were laid down in february 1935 . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': 'february 1935', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'laid down', 'february 1935'], 'result': True, 'ind': 0, 'tointer': 'for the laid down records of all rows , most of them fuzzily match to february 1935 .', 'tostr': 'most_eq { all_rows ; laid down ; february 1935 } = true'} | most_eq { all_rows ; laid down ; february 1935 } = true | for the laid down records of all rows , most of them fuzzily match to february 1935 . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'laid down_3': 3, 'february 1935_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'laid down_3': 'laid down', 'february 1935_4': 'february 1935'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'laid down_3': [0], 'february 1935_4': [0]} | ['ship', 'pennant number', 'laid down', 'launched', 'completed'] | [['hardy', '( h87 ) flotilla leader', '30 may 1935', '7 april 1936', '11 december 1936'], ['hasty', 'h24', '15 april 1935', '5 may 1936', '11 november 1936'], ['havock', 'h43', '15 may 1935', '7 july 1936', '16 january 1937'], ['hereward', 'h93', '28 february 1935', '10 march 1936', '9 december 1936'], ['hero', 'h99', '28 february 1935', '10 march 1936', '21 october 1936'], ['hostile', 'h55', '27 february 1935', '24 january 1936', '10 september 1936'], ['hotspur', 'h01', '27 february 1935', '23 march 1936', '29 december 1936'], ['hunter', 'h35', '27 march 1935', '25 february 1936', '30 september 1936'], ['hyperion', 'h97', '27 march 1935', '8 april 1936', '3 december 1936']] |
elvis ' gold records volume 5 | https://en.wikipedia.org/wiki/Elvis%27_Gold_Records_Volume_5 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15582798-4.html.csv | comparative | elvis 's song " big boss man " is eight seconds longer than " us male . " . | {'row_1': '1', 'row_2': '3', 'col': '6', 'col_other': '5', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'song title', 'big boss man'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose song title record fuzzily matches to big boss man .', 'tostr': 'filter_eq { all_rows ; song title ; big boss man }'}, 'time'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; song title ; big boss man } ; time }', 'tointer': 'select the rows whose song title record fuzzily matches to big boss man . take the time record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'song title', 'us male'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose song title record fuzzily matches to us male .', 'tostr': 'filter_eq { all_rows ; song title ; us male }'}, 'time'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; song title ; us male } ; time }', 'tointer': 'select the rows whose song title record fuzzily matches to us male . take the time record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; song title ; big boss man } ; time } ; hop { filter_eq { all_rows ; song title ; us male } ; time } } = true', 'tointer': 'select the rows whose song title record fuzzily matches to big boss man . take the time record of this row . select the rows whose song title record fuzzily matches to us male . take the time record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; song title ; big boss man } ; time } ; hop { filter_eq { all_rows ; song title ; us male } ; time } } = true | select the rows whose song title record fuzzily matches to big boss man . take the time record of this row . select the rows whose song title record fuzzily matches to us male . take the time 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, 'song title_7': 7, 'big boss man_8': 8, 'time_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'song title_11': 11, 'us male_12': 12, 'time_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', 'song title_7': 'song title', 'big boss man_8': 'big boss man', 'time_9': 'time', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'song title_11': 'song title', 'us male_12': 'us male', 'time_13': 'time'} | {'greater_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'song title_7': [0], 'big boss man_8': [0], 'time_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'song title_11': [1], 'us male_12': [1], 'time_13': [3]} | ['track', 'recorded', 'catalogue', 'release date', 'song title', 'time'] | [['1', '9 / 10 / 67', '47 - 9341', '9 / 26 / 67', 'big boss man', '2:50'], ['2', '9 / 10 / 67', '47 - 9425', '1 / 9 / 68', 'guitar man', '2:12'], ['3', '1 / 16 / 68', '47 - 9465', '2 / 28 / 68', 'us male', '2:42'], ['4', '6 / 6 / 70', '47 - 9916', '10 / 6 / 70', "you do n't have to say you love me", '2:30'], ['5', '3 / 7 / 68', '47 - 9670b', '11 / 5 / 68', 'edge of reality', '3:33'], ['6', '6 / 23 / 68', '47 - 9731', '2 / 25 / 69', 'memories', '3:06']] |
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/2-13599687-35.html.csv | ordinal | michael schumacher has the highest number of entries in the formula one driver records . | {'row': '9', 'col': '4', 'order': '1', 'col_other': '1', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'entries', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; entries ; 1 }'}, 'driver'], 'result': 'michael schumacher', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; entries ; 1 } ; driver }'}, 'michael schumacher'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; entries ; 1 } ; driver } ; michael schumacher } = true', 'tointer': 'select the row whose entries record of all rows is 1st maximum . the driver record of this row is michael schumacher .'} | eq { hop { nth_argmax { all_rows ; entries ; 1 } ; driver } ; michael schumacher } = true | select the row whose entries record of all rows is 1st maximum . the driver record of this row is michael schumacher . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'entries_5': 5, '1_6': 6, 'driver_7': 7, 'michael schumacher_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', 'entries_5': 'entries', '1_6': '1', 'driver_7': 'driver', 'michael schumacher_8': 'michael schumacher'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'entries_5': [0], '1_6': [0], 'driver_7': [1], 'michael schumacher_8': [2]} | ['driver', 'front row starts', 'pole positions', 'entries', 'percentage'] | [['juan manuel fangio', '48', '29', '52', '92.31 %'], ['jim clark', '48', '33', '73', '65.75 %'], ['ayrton senna', '87', '65', '162', '53.70 %'], ['sebastian vettel', '62', '43', '118', '52.54 %'], ['lewis hamilton', '57', '31', '127', '44.81 %'], ['alain prost', '86', '33', '202', '42.57 %'], ['jackie stewart', '42', '17', '100', '42.00 %'], ['damon hill', '47', '20', '122', '38.52 %'], ['michael schumacher', '116', '68', '308', '37.66 %'], ['nigel mansell', '56', '32', '191', '29.32 %']] |
1985 tampa bay buccaneers season | https://en.wikipedia.org/wiki/1985_Tampa_Bay_Buccaneers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11449311-2.html.csv | majority | most of the tampa bay buccaneers games ended in losses for the buccaneers . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': 'l', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'result', 'l'], 'result': True, 'ind': 0, 'tointer': 'for the result records of all rows , most of them fuzzily match to l .', 'tostr': 'most_eq { all_rows ; result ; l } = true'} | most_eq { all_rows ; result ; l } = true | for the result records of all rows , most of them fuzzily match to l . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'result_3': 3, 'l_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'result_3': 'result', 'l_4': 'l'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'result_3': [0], 'l_4': [0]} | ['week', 'date', 'opponent', 'result', 'kickoff', 'game site', 'attendance', 'record'] | [['week', 'date', 'opponent', 'result', 'kickoff', 'game site', 'attendance', 'record'], ['1', 'september 8 , 1985', 'chicago bears', 'l 38 - 28', '1:00', 'soldier field', '57828', '0 - 1'], ['2', 'september 15 , 1985', 'minnesota vikings', 'l 31 - 16', '4:00', 'tampa stadium', '46188', '0 - 2'], ['3', 'september 22 , 1985', 'new orleans saints', 'l 20 - 13', '1:00', 'louisiana superdome', '45320', '0 - 3'], ['4', 'september 29 , 1985', 'detroit lions', 'l 30 - 9', '1:00', 'pontiac silverdome', '45023', '0 - 4'], ['5', 'october 6 , 1985', 'chicago bears', 'l 27 - 19', '1:00', 'tampa stadium', '51795', '0 - 5'], ['6', 'october 13 , 1985', 'los angeles rams', 'l 31 - 27', '1:00', 'tampa stadium', '39607', '0 - 6'], ['7', 'october 20 , 1985', 'miami dolphins', 'l 41 - 38', '4:00', 'orange bowl', '62335', '0 - 7'], ['8', 'october 27 , 1985', 'new england patriots', 'l 32 - 14', '1:00', 'tampa stadium', '34661', '0 - 8'], ['9', 'november 3 , 1985', 'new york giants', 'l 22 - 20', '1:00', 'giants stadium', '72031', '0 - 9'], ['10', 'november 10 , 1985', 'st louis cardinals', 'w 16 - 0', '1:00', 'tampa stadium', '34736', '1 - 9'], ['11', 'november 17 , 1985', 'new york jets', 'l 62 - 28', '1:00', 'the meadowlands', '65344', '1 - 10'], ['12', 'november 24 , 1985', 'detroit lions', 'w 19 - 16 ot', '1:00', 'tampa stadium', '43471', '2 - 10'], ['13', 'december 1 , 1985', 'green bay packers', 'l 21 - 0', '1:00', 'lambeau field', '19856', '2 - 11'], ['14', 'december 8 , 1985', 'minnesota vikings', 'l 26 - 7', '4:00', 'hubert h humphrey metrodome', '51593', '2 - 12'], ['15', 'december 15 , 1985', 'indianapolis colts', 'l 31 - 23', '1:00', 'tampa stadium', '25577', '2 - 13'], ['16', 'december 22 , 1985', 'green bay packers', 'l 20 - 17', '1:00', 'tampa stadium', '33992', '2 - 14']] |
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 | count | the los angeles rams were the opponent on two different occasions . | {'scope': 'all', 'criterion': 'equal', 'value': 'los angeles rams', 'result': '2', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', 'los angeles rams'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose opponent record fuzzily matches to los angeles rams .', 'tostr': 'filter_eq { all_rows ; opponent ; los angeles rams }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; opponent ; los angeles rams } }', 'tointer': 'select the rows whose opponent record fuzzily matches to los angeles rams . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; opponent ; los angeles rams } } ; 2 } = true', 'tointer': 'select the rows whose opponent record fuzzily matches to los angeles rams . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; opponent ; los angeles rams } } ; 2 } = true | select the rows whose opponent record fuzzily matches to los angeles rams . 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, 'los angeles rams_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', 'los angeles rams_6': 'los angeles rams', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'opponent_5': [0], 'los angeles rams_6': [0], '2_7': [2]} | ['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']] |
octagonal | https://en.wikipedia.org/wiki/Octagonal | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1284347-3.html.csv | ordinal | octagonal had the highest distance covered in the mercedes classic race . | {'row': '11', 'col': '6', 'order': '1', 'col_other': '3', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'distance', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; distance ; 1 }'}, 'race'], 'result': 'mercedes classic', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; distance ; 1 } ; race }'}, 'mercedes classic'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; distance ; 1 } ; race } ; mercedes classic } = true', 'tointer': 'select the row whose distance record of all rows is 1st maximum . the race record of this row is mercedes classic .'} | eq { hop { nth_argmax { all_rows ; distance ; 1 } ; race } ; mercedes classic } = true | select the row whose distance record of all rows is 1st maximum . the race record of this row is mercedes classic . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'distance_5': 5, '1_6': 6, 'race_7': 7, 'mercedes classic_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', 'distance_5': 'distance', '1_6': '1', 'race_7': 'race', 'mercedes classic_8': 'mercedes classic'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'distance_5': [0], '1_6': [0], 'race_7': [1], 'mercedes classic_8': [2]} | ['result', 'date', 'race', 'venue', 'group', 'distance', 'weight ( kg )', 'jockey', 'winner / 2nd'] | [['6th', '17 aug 1996', 'manikato stakes', 'moonee valley', 'g1', '1200 m', '57', 'd gauci', '1st - poetic king'], ['7th', '31 aug 1996', 'memsie stakes', 'caulfield', 'g2', '1400 m', '57', 'd gauci', '1st - sir boom'], ['5th', '14 sep 1996', 'feehan stakes', 'moonee valley', 'g2', '1600 m', '57', 'd gauci', '1st - toil'], ['won', '22 sep 1996', 'underwood stakes', 'caulfield', 'g1', '1800 m', '57', 'd beadman', '2nd - seascay'], ['4th', '12 oct 1996', 'caulfield stakes', 'caulfield', 'g1', '2000 m', '57', 'd beadman', '1st - juggler'], ['5th', '26 oct 1996', 'cox plate', 'moonee valley', 'g1', '2040 m', '57', 'd gauci', '1st - saintly'], ['9th', '2 nov 1996', 'mackinnon stakes', 'flemington', 'g1', '2000 m', '57', 'd beadman', '1st - all our mob'], ['2nd', '15 feb 1997', 'apollo stakes', 'warwick farm', 'g2', '1400 m', '57', 'd beadman', '1st - juggler'], ['won', '22 feb 1997', 'chipping norton stakes', 'warwick farm', 'g1', '1600 m', '57', 's dye', '2nd - juggler'], ['won', '10 mar 1997', 'australia cup', 'flemington', 'g1', '2000 m', '57', 's dye', '2nd - gold city'], ['won', '22 mar 1997', 'mercedes classic', 'rosehill', 'g1', '2400 m', '57', 's dye', '2nd - arkady'], ['2nd', '12 apr 1997', 'queen elizabeth stakes', 'randwick', 'g1', '2000 m', '57', 's dye', '1st - intergaze']] |
gerry rafferty | https://en.wikipedia.org/wiki/Gerry_Rafferty | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1068160-1.html.csv | unique | 1979 is the only year that gerry rafferty received gold riaa certification . | {'scope': 'all', 'row': '3', 'col': '4', 'col_other': '1', 'criterion': 'equal', 'value': 'gold', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'riaa certification', 'gold'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose riaa certification record fuzzily matches to gold .', 'tostr': 'filter_eq { all_rows ; riaa certification ; gold }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; riaa certification ; gold } }', 'tointer': 'select the rows whose riaa certification record fuzzily matches to gold . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'riaa certification', 'gold'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose riaa certification record fuzzily matches to gold .', 'tostr': 'filter_eq { all_rows ; riaa certification ; gold }'}, 'year'], 'result': '1979', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; riaa certification ; gold } ; year }'}, '1979'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; riaa certification ; gold } ; year } ; 1979 }', 'tointer': 'the year record of this unqiue row is 1979 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; riaa certification ; gold } } ; eq { hop { filter_eq { all_rows ; riaa certification ; gold } ; year } ; 1979 } } = true', 'tointer': 'select the rows whose riaa certification record fuzzily matches to gold . there is only one such row in the table . the year record of this unqiue row is 1979 .'} | and { only { filter_eq { all_rows ; riaa certification ; gold } } ; eq { hop { filter_eq { all_rows ; riaa certification ; gold } ; year } ; 1979 } } = true | select the rows whose riaa certification record fuzzily matches to gold . there is only one such row in the table . the year record of this unqiue row is 1979 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'riaa certification_7': 7, 'gold_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'year_9': 9, '1979_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'riaa certification_7': 'riaa certification', 'gold_8': 'gold', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'year_9': 'year', '1979_10': '1979'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'riaa certification_7': [0], 'gold_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'year_9': [2], '1979_10': [3]} | ['year', 'us 200', 'uk albums', 'riaa certification', 'bpi certification'] | [['1971', '-', '-', '-', '-'], ['1978', '1', '6', 'platinum', 'gold'], ['1979', '29', '9', 'gold', 'gold'], ['1980', '61', '15', '-', 'silver'], ['1982', '-', '39', '-', '-'], ['1988', '-', '43', '-', '-'], ['1992', '-', '73', '-', '-'], ['1994', '-', '-', '-', '-'], ['2000', '-', '-', '-', '-'], ['compilations', 'compilations', 'compilations', 'compilations', 'compilations'], ['1974', '-', '-', '-', '-'], ['1984', '-', '-', '-', '-'], ['1989', '-', '-', '-', '-'], ['1995', '-', '17', '-', '-'], ['2006', '-', '-', '-', '-'], ['2009', '-', '-', '-', '-'], ['2011', '-', '-', '-', '-'], ['as guest or supporting musician', 'as guest or supporting musician', 'as guest or supporting musician', 'as guest or supporting musician', 'as guest or supporting musician'], ['1979', '-', '-', '-', '-']] |
iran at the asian games | https://en.wikipedia.org/wiki/Iran_at_the_Asian_Games | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10882501-12.html.csv | unique | for iran at the asian games , of the athletes that won silver medals , the only one who won 4 gold medals is mohammad nassiri . | {'scope': 'subset', 'row': '1', 'col': '4', 'col_other': '5,1', 'criterion': 'equal', 'value': '4', 'subset': {'col': '5', 'criterion': 'greater_than', 'value': '0'}} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'silver', '0'], 'result': None, 'ind': 0, 'tostr': 'filter_greater { all_rows ; silver ; 0 }', 'tointer': 'select the rows whose silver record is greater than 0 .'}, 'gold', '4'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose silver record is greater than 0 . among these rows , select the rows whose gold record is equal to 4 .', 'tostr': 'filter_eq { filter_greater { all_rows ; silver ; 0 } ; gold ; 4 }'}], 'result': True, 'ind': 2, 'tostr': 'only { filter_eq { filter_greater { all_rows ; silver ; 0 } ; gold ; 4 } }', 'tointer': 'select the rows whose silver record is greater than 0 . among these rows , select the rows whose gold record is equal to 4 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_eq', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'silver', '0'], 'result': None, 'ind': 0, 'tostr': 'filter_greater { all_rows ; silver ; 0 }', 'tointer': 'select the rows whose silver record is greater than 0 .'}, 'gold', '4'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose silver record is greater than 0 . among these rows , select the rows whose gold record is equal to 4 .', 'tostr': 'filter_eq { filter_greater { all_rows ; silver ; 0 } ; gold ; 4 }'}, 'athlete'], 'result': 'mohammad nassiri', 'ind': 3, 'tostr': 'hop { filter_eq { filter_greater { all_rows ; silver ; 0 } ; gold ; 4 } ; athlete }'}, 'mohammad nassiri'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { filter_eq { filter_greater { all_rows ; silver ; 0 } ; gold ; 4 } ; athlete } ; mohammad nassiri }', 'tointer': 'the athlete record of this unqiue row is mohammad nassiri .'}], 'result': True, 'ind': 5, 'tostr': 'and { only { filter_eq { filter_greater { all_rows ; silver ; 0 } ; gold ; 4 } } ; eq { hop { filter_eq { filter_greater { all_rows ; silver ; 0 } ; gold ; 4 } ; athlete } ; mohammad nassiri } } = true', 'tointer': 'select the rows whose silver record is greater than 0 . among these rows , select the rows whose gold record is equal to 4 . there is only one such row in the table . the athlete record of this unqiue row is mohammad nassiri .'} | and { only { filter_eq { filter_greater { all_rows ; silver ; 0 } ; gold ; 4 } } ; eq { hop { filter_eq { filter_greater { all_rows ; silver ; 0 } ; gold ; 4 } ; athlete } ; mohammad nassiri } } = true | select the rows whose silver record is greater than 0 . among these rows , select the rows whose gold record is equal to 4 . there is only one such row in the table . the athlete record of this unqiue row is mohammad nassiri . | 8 | 6 | {'and_5': 5, 'result_6': 6, 'only_2': 2, 'filter_eq_1': 1, 'filter_greater_0': 0, 'all_rows_7': 7, 'silver_8': 8, '0_9': 9, 'gold_10': 10, '4_11': 11, 'str_eq_4': 4, 'str_hop_3': 3, 'athlete_12': 12, 'mohammad nassiri_13': 13} | {'and_5': 'and', 'result_6': 'true', 'only_2': 'only', 'filter_eq_1': 'filter_eq', 'filter_greater_0': 'filter_greater', 'all_rows_7': 'all_rows', 'silver_8': 'silver', '0_9': '0', 'gold_10': 'gold', '4_11': '4', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'athlete_12': 'athlete', 'mohammad nassiri_13': 'mohammad nassiri'} | {'and_5': [6], 'result_6': [], 'only_2': [5], 'filter_eq_1': [2, 3], 'filter_greater_0': [1], 'all_rows_7': [0], 'silver_8': [0], '0_9': [0], 'gold_10': [1], '4_11': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'athlete_12': [3], 'mohammad nassiri_13': [4]} | ['athlete', 'sport', 'asian games', 'gold', 'silver', 'bronze', 'total'] | [['mohammad nassiri', 'weightlifting', '1966 - 1974', '4', '1', '0', '5'], ['moslem eskandar - filabi', 'wrestling', '1966 - 1974', '4', '0', '0', '4'], ['reza soukhteh - saraei', 'wrestling', '1974 - 1990', '3', '1', '0', '4'], ['houshang kargarnejad', 'weightlifting', '1970 - 1974', '3', '0', '1', '4'], ['alireza heidari', 'wrestling', '1998 - 2006', '3', '0', '0', '3'], ['jalal keshmiri', 'athletics', '1966 - 1974', '2', '3', '1', '6'], ['hassan arianfard', 'cycling', '1970 - 1974', '2', '1', '0', '3'], ['jasem vishgahi', 'karate', '2002 - 2010', '2', '1', '0', '3'], ['akbar shokrollahi', 'weightlifting', '1974', '2', '1', '0', '3'], ['ali vali', 'weightlifting', '1974', '2', '1', '0', '3'], ['teymour ghiasi', 'athletics', '1966 - 1974', '2', '0', '1', '3'], ['hossein rezazadeh', 'weightlifting', '1998 - 2006', '2', '0', '1', '3']] |
1969 army cadets football team | https://en.wikipedia.org/wiki/1969_Army_Cadets_football_team | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-21091162-1.html.csv | aggregation | the 1969 army cadets football team , the black knights , scored a total sum of 85 points in their victories . | {'scope': 'subset', 'col': '5', 'type': 'sum', 'result': '85', 'subset': {'col': '4', 'criterion': 'fuzzily_match', 'value': 'win'}} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'result', 'win'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; result ; win }', 'tointer': 'select the rows whose result record fuzzily matches to win .'}, 'black knights points'], 'result': '85', 'ind': 1, 'tostr': 'sum { filter_eq { all_rows ; result ; win } ; black knights points }'}, '85'], 'result': True, 'ind': 2, 'tostr': 'round_eq { sum { filter_eq { all_rows ; result ; win } ; black knights points } ; 85 } = true', 'tointer': 'select the rows whose result record fuzzily matches to win . the sum of the black knights points record of these rows is 85 .'} | round_eq { sum { filter_eq { all_rows ; result ; win } ; black knights points } ; 85 } = true | select the rows whose result record fuzzily matches to win . the sum of the black knights points record of these rows is 85 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'sum_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'result_5': 5, 'win_6': 6, 'black knights points_7': 7, '85_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'sum_1': 'sum', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'result_5': 'result', 'win_6': 'win', 'black knights points_7': 'black knights points', '85_8': '85'} | {'eq_2': [3], 'result_3': [], 'sum_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'result_5': [0], 'win_6': [0], 'black knights points_7': [1], '85_8': [2]} | ['game', 'date', 'opponent', 'result', 'black knights points', 'opponents', 'record'] | [['1', 'sept 20', 'new mexico', 'win', '31', '14', '1 - 0 - 0'], ['2', 'sept 27', 'vanderbilt', 'win', '16', '6', '2 - 0 - 0'], ['3', 'oct 4', 'texas a & m', 'loss', '13', '20', '2 - 1 - 0'], ['4', 'oct 11', 'notre dame', 'loss', '0', '45', '2 - 2 - 0'], ['5', 'oct 18', 'utah state', 'loss', '7', '23', '2 - 3 - 0'], ['6', 'oct 25', 'boston college', 'win', '38', '7', '3 - 3 - 0'], ['7', 'nov 1', 'air force', 'loss', '6', '13', '3 - 4 - 0'], ['8', 'nov 8', 'oregon', 'tie', '17', '17', '3 - 4 - 1'], ['9', 'nov 15', 'pittsburgh', 'loss', '6', '15', '3 - 5 - 1']] |
list of the largest trading partners of india | https://en.wikipedia.org/wiki/List_of_the_largest_trading_partners_of_India | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-26160007-1.html.csv | ordinal | iran has the lowest amount of total trade among the largest trading partners of india . | {'row': '14', 'col': '4', 'order': '1', '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', 'total trade', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; total trade ; 1 }'}, 'country'], 'result': 'iran', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; total trade ; 1 } ; country }'}, 'iran'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; total trade ; 1 } ; country } ; iran } = true', 'tointer': 'select the row whose total trade record of all rows is 1st minimum . the country record of this row is iran .'} | eq { hop { nth_argmin { all_rows ; total trade ; 1 } ; country } ; iran } = true | select the row whose total trade record of all rows is 1st minimum . the country record of this row is iran . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'total trade_5': 5, '1_6': 6, 'country_7': 7, 'iran_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', 'total trade_5': 'total trade', '1_6': '1', 'country_7': 'country', 'iran_8': 'iran'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'total trade_5': [0], '1_6': [0], 'country_7': [1], 'iran_8': [2]} | ['country', 'exports', 'imports', 'total trade', 'trade balance'] | [['united arab emirates', '36265.15', '38436.47', '74701.61', '- 2171.32'], ['china', '13503.00', '54324.04', '67827.04', '- 40821.04'], ['united states', '36152.30', '24343.73', '60496.03', '11808.57'], ['saudi arabia', '9783.81', '34130.50', '43914.31', '- 24346.69'], ['switzerland', '1116.98', '29915.78', '31032.76', '- 28798.80'], ['singapore', '13608.65', '7754.38', '21363.03', '5854.27'], ['germany', '7244.63', '14373.91', '21618.54', '- 7129.28'], ['hong kong', '12278.31', '8078.58', '20356.89', '4199.74'], ['indonesia', '5331.47', '14774.27', '20105.75', '- 9442.80'], ['iraq', '1278.13', '20155.94', '21434.07', '- 18877.81'], ['japan', '6099.06', '12514.07', '18613.14', '- 6415.01'], ['belgium', '5506.63', '10087.16', '15593.80', '- 4580.53'], ['kuwait', '1060.80', '16569.63', '17630.43', '- 15508.83'], ['iran', '3351.07', '11603.79', '14954.86', '- 8252.72']] |
1990 african cup of champions clubs | https://en.wikipedia.org/wiki/1990_African_Cup_of_Champions_Clubs | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16163549-1.html.csv | count | two games in the 1990 african cup of champions 1st leg ended with a score of 0-0 . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': '0 - 0', 'result': '2', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', '1st leg', '0 - 0'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose 1st leg record fuzzily matches to 0 - 0 .', 'tostr': 'filter_eq { all_rows ; 1st leg ; 0 - 0 }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; 1st leg ; 0 - 0 } }', 'tointer': 'select the rows whose 1st leg record fuzzily matches to 0 - 0 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; 1st leg ; 0 - 0 } } ; 2 } = true', 'tointer': 'select the rows whose 1st leg record fuzzily matches to 0 - 0 . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; 1st leg ; 0 - 0 } } ; 2 } = true | select the rows whose 1st leg record fuzzily matches to 0 - 0 . 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, '1st leg_5': 5, '0 - 0_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', '1st leg_5': '1st leg', '0 - 0_6': '0 - 0', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], '1st leg_5': [0], '0 - 0_6': [0], '2_7': [2]} | ['team 1', 'agg', 'team 2', '1st leg', '2nd leg'] | [['as sotema', '( a ) 2 - 2', 'defence force xi', '1 - 0', '1 - 2'], ['as kaloum star', '3 - 0', 'benfica de bissau', '2 - 0', '1 - 0'], ['asko kara', '3 - 0', 'asfa yennenga', '1 - 0', '2 - 0'], ['al - ittihad', '6 - 3', 'olympic fc de niamey', '6 - 1', '0 - 2'], ['arsenal', '4 - 0', 'denver sundowns', '1 - 0', '3 - 0'], ["dragons de l'ouémé", '0 - 3', 'mighty barolle', '0 - 0', '0 - 3'], ['fc inter - star', '2 - 3', 'petro atlético', '2 - 0', '0 - 3'], ['mogadishu municipality', '3 - 4', 'saint louis', '1 - 0', '2 - 4'], ['malindi', '1 - 2', 'mukungwa', '0 - 0', '1 - 2'], ['renaissance', '2 - 3', 'scaf tocages', '2 - 2', '0 - 1']] |
television in italy | https://en.wikipedia.org/wiki/Television_in_Italy | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-15887683-1.html.csv | majority | the vast majority of the package/options are no ( fta ) . | {'scope': 'all', 'col': '8', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'no ( fta )', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'package / option', 'no ( fta )'], 'result': True, 'ind': 0, 'tointer': 'for the package / option records of all rows , most of them fuzzily match to no ( fta ) .', 'tostr': 'most_eq { all_rows ; package / option ; no ( fta ) } = true'} | most_eq { all_rows ; package / option ; no ( fta ) } = true | for the package / option records of all rows , most of them fuzzily match to no ( fta ) . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'package / option_3': 3, 'no ( fta )_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'package / option_3': 'package / option', 'no ( fta )_4': 'no ( fta )'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'package / option_3': [0], 'no ( fta )_4': [0]} | ['n degree', 'television service', 'country', 'language', 'content', 'dar', 'hdtv', 'package / option'] | [['100', 'sky tg 24', 'italy', 'italian', 'all news', '16:9', 'no', 'any combination'], ['100', 'sky tg 24 active', 'italy', 'italian', 'all news', '16:9', 'no', 'any combination'], ['101', 'rai 1', 'italy', 'italian', 'general television', '16:9', 'no', 'no ( fta )'], ['102', 'rai 2', 'italy', 'italian', 'general television', '16:9', 'no', 'no ( fta )'], ['103', 'rai 3', 'italy', 'italian', 'general television', '16:9', 'no', 'no ( fta )'], ['104', 'rete 4', 'italy', 'italian', 'general television', '16:9', 'no', 'no ( fta )'], ['105', 'canale 5', 'italy', 'italian', 'general television', '16:9', 'no', 'no ( fta )'], ['106', 'italia 1', 'italy', 'italian', 'general television', '16:9', 'no', 'no ( fta )'], ['107', 'la7', 'italy', 'italian', 'general television', '16:9', 'no', 'no ( ftv )']] |
1975 oakland raiders season | https://en.wikipedia.org/wiki/1975_Oakland_Raiders_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18207285-2.html.csv | superlative | the nov 9 game against the saints was the only game where the raiders scored more than 45 points . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '8', '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', 'raiders points'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; raiders points }'}, 'date'], 'result': 'nov 9', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; raiders points } ; date }'}, 'nov 9'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; raiders points } ; date } ; nov 9 } = true', 'tointer': 'select the row whose raiders points record of all rows is maximum . the date record of this row is nov 9 .'} | eq { hop { argmax { all_rows ; raiders points } ; date } ; nov 9 } = true | select the row whose raiders points record of all rows is maximum . the date record of this row is nov 9 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'raiders points_5': 5, 'date_6': 6, 'nov 9_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'raiders points_5': 'raiders points', 'date_6': 'date', 'nov 9_7': 'nov 9'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'raiders points_5': [0], 'date_6': [1], 'nov 9_7': [2]} | ['game', 'date', 'opponent', 'result', 'raiders points', 'opponents', 'raiders first downs', 'record', 'attendance'] | [['1', 'sept 22', 'miami dolphins', 'win', '31', '21', '17', '1 - 0', '78744'], ['2', 'sept 28', 'baltimore colts', 'win', '31', '20', '18', '2 - 0', '40657'], ['3', 'oct 5', 'san diego chargers', 'win', '6', '0', '17', '3 - 0', '31095'], ['4', 'oct 12', 'kansas city chiefs', 'loss', '10', '42', '23', '3 - 1', '60425'], ['5', 'oct 19', 'cincinnati bengals', 'loss', '10', '14', '18', '3 - 2', '48122'], ['6', 'oct 26', 'san diego chargers', 'win', '25', '0', '23', '4 - 2', '42796'], ['7', 'nov 2', 'denver broncos', 'win', '42', '17', '21', '5 - 2', '52505'], ['8', 'nov 9', 'new orleans saints', 'win', '48', '10', '34', '6 - 2', '51267'], ['9', 'nov 16', 'cleveland browns', 'win', '38', '17', '22', '7 - 2', '50461'], ['10', 'nov 23', 'washington redskins', 'win', '26', '23', '26', '8 - 2', '53582'], ['11', 'nov 30', 'atlanta falcons', 'win', '37', '34', '33', '9 - 2', '50860'], ['12', 'dec 8', 'denver broncos', 'win', '17', '10', '16', '10 - 2', '51075'], ['13', 'dec 14', 'houston oilers', 'loss', '26', '27', '23', '10 - 3', '50719'], ['14', 'dec 21', 'kansas city chiefs', 'win', '28', '20', '24', '11 - 3', '48604']] |
champ car mont - tremblant 07 | https://en.wikipedia.org/wiki/Champ_Car_Mont-Tremblant_07 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12032042-1.html.csv | majority | most of the racers in the champ car mont had a first qualifying time of under 1:18:000 . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'less_than', 'value': '1:18:000', 'subset': None} | {'func': 'most_less', 'args': ['all_rows', 'qual 1', '1:18:000'], 'result': True, 'ind': 0, 'tointer': 'for the qual 1 records of all rows , most of them are less than 1:18:000 .', 'tostr': 'most_less { all_rows ; qual 1 ; 1:18:000 } = true'} | most_less { all_rows ; qual 1 ; 1:18:000 } = true | for the qual 1 records of all rows , most of them are less than 1:18:000 . | 1 | 1 | {'most_less_0': 0, 'result_1': 1, 'all_rows_2': 2, 'qual 1_3': 3, '1:18:000_4': 4} | {'most_less_0': 'most_less', 'result_1': 'true', 'all_rows_2': 'all_rows', 'qual 1_3': 'qual 1', '1:18:000_4': '1:18:000'} | {'most_less_0': [1], 'result_1': [], 'all_rows_2': [0], 'qual 1_3': [0], '1:18:000_4': [0]} | ['name', 'team', 'qual 1', 'qual 2', 'best'] | [['tristan gommendy', 'pkv racing', '1:16.776', 'no time', '1:16.776'], ['will power', 'team australia', '1:16.841', '1:20.943', '1:16.841'], ['sãbastien bourdais', 'n / h / l racing', '1:16.783', '1:21.380', '1:16.783'], ['justin wilson', 'rsports', '1:16.843', '1:20.981', '1:16.843'], ['robert doornbos', 'minardi team usa', '1:16.850', '1:22.093', '1:16.850'], ['neel jani', 'pkv racing', '1:16.931', '1:22.604', '1:16.931'], ['simon pagenaud', 'team australia', '1:16.944', '1:21.671', '1:16.944'], ['alex tagliani', 'rsports', '1:17.256', '1:21.610', '1:17.256'], ['graham rahal', 'n / h / l racing', '1:17.475', '1:21.350', '1:17.475'], ['dan clarke', 'minardi team usa', '1:17.481', '1:23.093', '1:17.481'], ['paul tracy', 'forsythe racing', '1:17.629', '1:22.266', '1:17.629'], ['jan heylen', 'conquest racing', '1:17.832', '1:21.611', '1:17.832'], ['ryan dalziel', 'pacific coast motorsports', '1:17.965', '1:22.804', '1:17.965'], ['oriol servia', 'forsythe racing', '1:17.965', '1:21.579', '1:17.965'], ['alex figge', 'pacific coast motorsports', '1:18.067', 'no time', '1:18.067'], ['bruno junqueira', 'dale coyne racing', '1:18.127', '1:21.699', '1:18.127'], ['katherine legge', 'dale coyne racing', '1:18.989', '1:26.259', '1:18.989']] |
2008 german motorcycle grand prix | https://en.wikipedia.org/wiki/2008_German_motorcycle_Grand_Prix | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16878651-1.html.csv | count | 4 competitors had accidents in the 2008 german motorcycle grand prix . | {'scope': 'all', 'criterion': 'equal', 'value': 'accident', 'result': '4', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'time', 'accident'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose time record fuzzily matches to accident .', 'tostr': 'filter_eq { all_rows ; time ; accident }'}], 'result': '4', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; time ; accident } }', 'tointer': 'select the rows whose time record fuzzily matches to accident . the number of such rows is 4 .'}, '4'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; time ; accident } } ; 4 } = true', 'tointer': 'select the rows whose time record fuzzily matches to accident . the number of such rows is 4 .'} | eq { count { filter_eq { all_rows ; time ; accident } } ; 4 } = true | select the rows whose time record fuzzily matches to accident . 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, 'time_5': 5, 'accident_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', 'time_5': 'time', 'accident_6': 'accident', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'time_5': [0], 'accident_6': [0], '4_7': [2]} | ['rider', 'manufacturer', 'laps', 'time', 'grid'] | [['casey stoner', 'ducati', '30', '47:30.057', '1'], ['valentino rossi', 'yamaha', '30', '+ 3.708', '7'], ['chris vermeulen', 'suzuki', '30', '+ 14.002', '14'], ['alex de angelis', 'honda', '30', '+ 14.124', '10'], ['andrea dovizioso', 'honda', '30', '+ 42.022', '4'], ['sylvain guintoli', 'ducati', '30', '+ 46.648', '15'], ['loris capirossi', 'suzuki', '30', '+ 1:04.483', '13'], ['randy de puniet', 'honda', '30', '+ 1:04.588', '6'], ['shinya nakano', 'honda', '30', '+ 1:16.773', '9'], ['anthony west', 'kawasaki', '30', '+ 1:29.275', '17'], ['james toseland', 'yamaha', '29', '+ 1 lap', '11'], ['toni elias', 'ducati', '29', '+ 1 lap', '12'], ['nicky hayden', 'honda', '28', '+ 2 laps', '8'], ['colin edwards', 'yamaha', '20', 'accident', '3'], ['marco melandri', 'ducati', '9', 'accident', '16'], ['dani pedrosa', 'honda', '5', 'accident', '2'], ['jorge lorenzo', 'yamaha', '2', 'accident', '5']] |
list of romanian counties by foreign trade | https://en.wikipedia.org/wiki/List_of_Romanian_counties_by_foreign_trade | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-24239748-2.html.csv | count | a total of seven counties are included for romanian foreign trade . | {'scope': 'all', 'criterion': 'all', 'value': 'n/a', 'result': '7', 'col': '1', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_all', 'args': ['all_rows', 'county'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose county record is arbitrary .', 'tostr': 'filter_all { all_rows ; county }'}], 'result': '7', 'ind': 1, 'tostr': 'count { filter_all { all_rows ; county } }', 'tointer': 'select the rows whose county record is arbitrary . the number of such rows is 7 .'}, '7'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_all { all_rows ; county } } ; 7 } = true', 'tointer': 'select the rows whose county record is arbitrary . the number of such rows is 7 .'} | eq { count { filter_all { all_rows ; county } } ; 7 } = true | select the rows whose county record is arbitrary . the number of such rows is 7 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_all_0': 0, 'all_rows_4': 4, 'county_5': 5, '7_6': 6} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_all_0': 'filter_all', 'all_rows_4': 'all_rows', 'county_5': 'county', '7_6': '7'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_all_0': [1], 'all_rows_4': [0], 'county_5': [0], '7_6': [2]} | ['county', 'exports ( us mil )', 'percent of total exports', 'imports ( us mil )', 'percent of total imports'] | [['bucharest - ilfov', '8001.2', '19.2 %', '26557.8', '39.8 %'], ['sud - muntenia', '6300 , 7', '15.1 %', '6785.5', '10.2 %'], ['vest', '6270.2', '15.0 %', '6597.6', '9.9 %'], ['sud - est', '5762', '13.8 %', '7501.9', '11.2 %'], ['centru', '5338', '12.8 %', '7.879.4', '11.8 %'], ['nord - vest', '4726.6', '11.3 %', '6999.1', '10.5 %'], ['sud - vest oltenia', '3226.2', '7.7 %', '2007.8', '3.0 %']] |
the apprentice australia | https://en.wikipedia.org/wiki/The_Apprentice_Australia | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-24501530-1.html.csv | comparative | on the apprentice australia , the candidate blake chandler was fired earlier than the candidate mary - anne lowe . | {'row_1': '9', 'row_2': '4', 'col': '6', 'col_other': '1', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'candidate', 'blake chandler'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose candidate record fuzzily matches to blake chandler .', 'tostr': 'filter_eq { all_rows ; candidate ; blake chandler }'}, 'result'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; candidate ; blake chandler } ; result }', 'tointer': 'select the rows whose candidate record fuzzily matches to blake chandler . take the result record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'candidate', 'mary - anne lowe'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose candidate record fuzzily matches to mary - anne lowe .', 'tostr': 'filter_eq { all_rows ; candidate ; mary - anne lowe }'}, 'result'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; candidate ; mary - anne lowe } ; result }', 'tointer': 'select the rows whose candidate record fuzzily matches to mary - anne lowe . take the result record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; candidate ; blake chandler } ; result } ; hop { filter_eq { all_rows ; candidate ; mary - anne lowe } ; result } } = true', 'tointer': 'select the rows whose candidate record fuzzily matches to blake chandler . take the result record of this row . select the rows whose candidate record fuzzily matches to mary - anne lowe . take the result record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; candidate ; blake chandler } ; result } ; hop { filter_eq { all_rows ; candidate ; mary - anne lowe } ; result } } = true | select the rows whose candidate record fuzzily matches to blake chandler . take the result record of this row . select the rows whose candidate record fuzzily matches to mary - anne lowe . take the result record of this row . the first record is less than the second record . | 5 | 5 | {'less_4': 4, 'result_5': 5, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'candidate_7': 7, 'blake chandler_8': 8, 'result_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'candidate_11': 11, 'mary - anne lowe_12': 12, 'result_13': 13} | {'less_4': 'less', 'result_5': 'true', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'candidate_7': 'candidate', 'blake chandler_8': 'blake chandler', 'result_9': 'result', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'candidate_11': 'candidate', 'mary - anne lowe_12': 'mary - anne lowe', 'result_13': 'result'} | {'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'candidate_7': [0], 'blake chandler_8': [0], 'result_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'candidate_11': [1], 'mary - anne lowe_12': [1], 'result_13': [3]} | ['candidate', 'background', 'original team', 'age', 'hometown', 'result'] | [['andrew morello morello', 'auctioneer', 'pinnacle', '23', 'melbourne , victoria', 'hired by bouris'], ['heather williams', 'advertising sales consultant', 'eventus', '31', 'maylands , western australia', 'fired 2nd in finale'], ['gavin mcinnes', 'lawyer', 'pinnacle', '33', 'brisbane , queensland', 'fired 1st in finale'], ['mary - anne lowe', 'business owner', 'eventus', '30', 'melbourne , victoria', 'fired in week 9'], ['sabrina houssami', 'university student and miss world australia 2006', 'eventus', '23', 'sydney , new south wales', 'fired in week 8'], ['samuel sam hooper', 'law student', 'pinnacle', '19', 'adelaide , south australia', 'fired in week 7'], ['carmen parnos', 'bankrupt former entrepreneur', 'eventus', '44', 'melbourne , victoria', 'fired in week 6'], ['john van yzerloo', 'unemployed', 'pinnacle', '44', 'romsey , victoria', 'fired in week 5'], ['blake chandler', 'customer service manager', 'pinnacle', '28', 'central coast , new south wales', 'fired in week 4'], ['amy cato', 'business owner', 'eventus', '25', 'adelaide , south australia', 'fired in week 3'], ['lynton pipkorn', 'marketing consultant', 'pinnacle', '30', 'melbourne , victoria', 'fired in week 2']] |
catriona matthew | https://en.wikipedia.org/wiki/Catriona_Matthew | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2167226-3.html.csv | ordinal | the second highest winner share that catriona matthew has received in a ladies european tour was in 2007 . | {'row': '2', 'col': '8', 'order': '2', 'col_other': '2', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'winners share', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; winners share ; 2 }'}, 'date'], 'result': '12 aug 2007', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; winners share ; 2 } ; date }'}, '12 aug 2007'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; winners share ; 2 } ; date } ; 12 aug 2007 } = true', 'tointer': 'select the row whose winners share record of all rows is 2nd maximum . the date record of this row is 12 aug 2007 .'} | eq { hop { nth_argmax { all_rows ; winners share ; 2 } ; date } ; 12 aug 2007 } = true | select the row whose winners share record of all rows is 2nd maximum . the date record of this row is 12 aug 2007 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'winners share_5': 5, '2_6': 6, 'date_7': 7, '12 aug 2007_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', 'winners share_5': 'winners share', '2_6': '2', 'date_7': 'date', '12 aug 2007_8': '12 aug 2007'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'winners share_5': [0], '2_6': [0], 'date_7': [1], '12 aug 2007_8': [2]} | ['no', 'date', 'tournament', 'winning score', 'to par', 'margin of victory', 'runner ( s ) - up', 'winners share'] | [['1', '9 aug 1998', "mcdonald 's wpga championship", '71 + 69 + 67 + 69 = 276', '- 12', '5 strokes', 'helen alfredsson laura davies', '45000'], ['2', '12 aug 2007', 'scandinavian tpc hosted by annika', '71 + 74 + 66 + 68 = 279', '- 10', '3 strokes', 'sophie gustafson laura diaz', '78750'], ['3', '2 aug 2009', "ricoh women 's british open 1", '74 + 67 + 71 + 73 = 285', '- 3', '3 strokes', 'karrie webb', '235036'], ['4', '20 aug 2011', 'aberdeen ladies scottish open', '70 + 65 + 76 = 201', '- 15', '10 strokes', 'hannah jun', '33000'], ['5', '5 aug 2012', 'ladies irish open', '67 + 71 + 71 = 209', '- 7', '1 stroke', 'suzann pettersen', '52500']] |
1969 vfl season | https://en.wikipedia.org/wiki/1969_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10809157-6.html.csv | superlative | mcg was the first venue to be used during the 1969 vfl season . | {'scope': 'all', 'col_superlative': '7', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '5', '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 }'}, 'venue'], 'result': 'mcg', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; date } ; venue }'}, 'mcg'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmin { all_rows ; date } ; venue } ; mcg } = true', 'tointer': 'select the row whose date record of all rows is minimum . the venue record of this row is mcg .'} | eq { hop { argmin { all_rows ; date } ; venue } ; mcg } = true | select the row whose date record of all rows is minimum . the venue record of this row is mcg . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'date_5': 5, 'venue_6': 6, 'mcg_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', 'venue_6': 'venue', 'mcg_7': 'mcg'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'date_5': [0], 'venue_6': [1], 'mcg_7': [2]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['melbourne', '13.15 ( 93 )', 'richmond', '16.25 ( 121 )', 'mcg', '26848', '10 may 1969'], ['collingwood', '17.13 ( 115 )', 'footscray', '8.14 ( 62 )', 'victoria park', '19025', '10 may 1969'], ['south melbourne', '14.9 ( 93 )', 'st kilda', '7.14 ( 56 )', 'lake oval', '17536', '10 may 1969'], ['north melbourne', '13.9 ( 87 )', 'hawthorn', '14.12 ( 96 )', 'arden street oval', '15338', '10 may 1969'], ['fitzroy', '13.12 ( 90 )', 'essendon', '17.13 ( 115 )', 'princes park', '13028', '10 may 1969'], ['geelong', '18.16 ( 124 )', 'carlton', '13.7 ( 85 )', 'kardinia park', '32025', '10 may 1969']] |
merlin ( series 3 ) | https://en.wikipedia.org/wiki/Merlin_%28series_3%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-29106680-1.html.csv | aggregation | the average number of viewers in the uk for merlin series 3 , in millions , is 6.71 . | {'scope': 'all', 'col': '7', 'type': 'average', 'result': '6.71', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'uk viewers ( million )'], 'result': '6.71', 'ind': 0, 'tostr': 'avg { all_rows ; uk viewers ( million ) }'}, '6.71'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; uk viewers ( million ) } ; 6.71 } = true', 'tointer': 'the average of the uk viewers ( million ) record of all rows is 6.71 .'} | round_eq { avg { all_rows ; uk viewers ( million ) } ; 6.71 } = true | the average of the uk viewers ( million ) record of all rows is 6.71 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'uk viewers (million)_4': 4, '6.71_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'uk viewers (million)_4': 'uk viewers ( million )', '6.71_5': '6.71'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'uk viewers (million)_4': [0], '6.71_5': [1]} | ['no overall', 'no for series', 'title', 'directed by', 'written by', 'original air date', 'uk viewers ( million )'] | [['27', '1', 'the tears of uther pendragon ( part 1 )', 'jeremy webb', 'julian jones', '11 september 2010', '6.49'], ['28', '2', 'the tears of uther pendragon ( part 2 )', 'jeremy webb', 'julian jones', '18 september 2010', '6.06'], ['29', '3', "goblin 's gold", 'jeremy webb', 'howard overman', '25 september 2010', '6.22'], ['30', '4', 'gwaine', 'david moore', 'julian jones', '2 october 2010', '6.42'], ['31', '5', 'the crystal cave', 'alice troughton', 'julian jones', '9 october 2010', '6.36'], ['32', '6', 'the changeling', 'david moore', 'lucy watkins', '16 october 2010', '6.40'], ['33', '7', 'the castle of fyrien', 'david moore', 'jake michie', '23 october 2010', '6.82'], ['34', '8', 'the eye of the phoenix', 'alice troughton', 'julian jones', '30 october 2010', '6.92'], ['35', '9', 'love in the time of dragons', 'alice troughton', 'jake michie', '6 november 2010', '6.90'], ['36', '10', 'queen of hearts', 'ashley way', 'howard overman', '13 november 2010', '7.37'], ['37', '11', "the sorcerer 's shadow", 'ashley way', 'julian jones', '20 november 2010', '7.42'], ['38', '12', 'the coming of arthur ( part 1 )', 'jeremy webb', 'jake michie', '27 november 2010', '7.12']] |
list of public sector undertakings in india | https://en.wikipedia.org/wiki/List_of_public_sector_undertakings_in_India | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15221362-8.html.csv | superlative | the most recent public sector to be incorporated in india was in the year of 2006 . | {'scope': 'all', 'col_superlative': '3', 'row_superlative': '3', 'value_mentioned': 'yes', 'max_or_min': 'max', 'other_col': 'n/a', 'subset': None} | {'func': 'eq', 'args': [{'func': 'max', 'args': ['all_rows', 'incorporated'], 'result': '2006', 'ind': 0, 'tostr': 'max { all_rows ; incorporated }', 'tointer': 'the maximum incorporated record of all rows is 2006 .'}, '2006'], 'result': True, 'ind': 1, 'tostr': 'eq { max { all_rows ; incorporated } ; 2006 } = true', 'tointer': 'the maximum incorporated record of all rows is 2006 .'} | eq { max { all_rows ; incorporated } ; 2006 } = true | the maximum incorporated record of all rows is 2006 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'max_0': 0, 'all_rows_3': 3, 'incorporated_4': 4, '2006_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'max_0': 'max', 'all_rows_3': 'all_rows', 'incorporated_4': 'incorporated', '2006_5': '2006'} | {'eq_1': [2], 'result_2': [], 'max_0': [1], 'all_rows_3': [0], 'incorporated_4': [0], '2006_5': [1]} | ['sno', 'company', 'incorporated', 'ministry', 'sector'] | [['1', 'air india air transport services ltd', '2003', 'ministry of civil aviation', 'services'], ['2', 'air india charters', '1972', 'ministry of civil aviation', 'services'], ['3', 'air india engineering services ltd', '2006', 'ministry of civil aviation', 'enterprises under construction'], ['4', 'airline allied services ltd', '1983', 'ministry of civil aviation', 'services'], ['5', 'airports authority of india ltd', '1996', 'ministry of civil aviation', 'services']] |
walter martínez ( footballer ) | https://en.wikipedia.org/wiki/Walter_Mart%C3%ADnez_%28footballer%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11982701-1.html.csv | majority | walter martinez was in division 1 for the majority of seasons listed here . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'equal', 'value': '1', 'subset': None} | {'func': 'most_eq', 'args': ['all_rows', 'division', '1'], 'result': True, 'ind': 0, 'tointer': 'for the division records of all rows , most of them are equal to 1 .', 'tostr': 'most_eq { all_rows ; division ; 1 } = true'} | most_eq { all_rows ; division ; 1 } = true | for the division records of all rows , most of them are equal to 1 . | 1 | 1 | {'most_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'division_3': 3, '1_4': 4} | {'most_eq_0': 'most_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'division_3': 'division', '1_4': '1'} | {'most_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'division_3': [0], '1_4': [0]} | ['season', 'team', 'country', 'division', 'apps', 'goals'] | [['00 / 01', 'club deportivo victoria', 'honduras', '1', '19', '1'], ['01 / 02', 'club deportivo victoria', 'honduras', '1', '14', '2'], ['02 / 03', 'club deportivo victoria', 'honduras', '1', '10', '4'], ['03 / 04', 'club deportivo victoria', 'honduras', '1', '10', '2'], ['03 / 04', 'club deportivo marathón', 'honduras', '1', '10', '2'], ['04 / 05', 'club deportivo marathón', 'honduras', '1', '10', '1'], ['05 / 06', 'club deportivo y social vida', 'honduras', '1', '8', '3'], ['06 / 07', 'club deportivo marathón', 'honduras', '1', '18', '9'], ['2007', 'beijing guoan', 'china', '1', '28', '7'], ['2008', 'beijing guoan', 'china', '1', '16', '7'], ['08 / 09', 'deportivo alavés', 'spain', '2', '3', '0'], ['09 / 10', 'club deportivo marathón', 'honduras', '1', '23', '7'], ['2010', 'beijing guoan', 'china', '1', '12', '4'], ['2011', 'beijing guoan', 'china', '1', '25', '9'], ['2012', 'chongqing fc', 'china', '2', '29', '3'], ['2013', 'san jose earthquakes', 'usa', '1', '11', '2']] |
formula one engines | https://en.wikipedia.org/wiki/Formula_One_engines | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11034903-1.html.csv | count | for formula one engines , when the number of wins was over 90 , there were two times that the first win was the french grand prix . | {'scope': 'subset', 'criterion': 'fuzzily_match', 'value': 'french grand prix', 'result': '2', 'col': '4', 'subset': {'col': '3', 'criterion': 'greater_than', 'value': '90'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'wins', '90'], 'result': None, 'ind': 0, 'tostr': 'filter_greater { all_rows ; wins ; 90 }', 'tointer': 'select the rows whose wins record is greater than 90 .'}, 'first win', 'french grand prix'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose wins record is greater than 90 . among these rows , select the rows whose first win record fuzzily matches to french grand prix .', 'tostr': 'filter_eq { filter_greater { all_rows ; wins ; 90 } ; first win ; french grand prix }'}], 'result': '2', 'ind': 2, 'tostr': 'count { filter_eq { filter_greater { all_rows ; wins ; 90 } ; first win ; french grand prix } }', 'tointer': 'select the rows whose wins record is greater than 90 . among these rows , select the rows whose first win record fuzzily matches to french grand prix . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_eq { filter_greater { all_rows ; wins ; 90 } ; first win ; french grand prix } } ; 2 } = true', 'tointer': 'select the rows whose wins record is greater than 90 . among these rows , select the rows whose first win record fuzzily matches to french grand prix . the number of such rows is 2 .'} | eq { count { filter_eq { filter_greater { all_rows ; wins ; 90 } ; first win ; french grand prix } } ; 2 } = true | select the rows whose wins record is greater than 90 . among these rows , select the rows whose first win record fuzzily matches to french grand prix . the number of such rows is 2 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_str_eq_1': 1, 'filter_greater_0': 0, 'all_rows_5': 5, 'wins_6': 6, '90_7': 7, 'first win_8': 8, 'french grand prix_9': 9, '2_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_str_eq_1': 'filter_str_eq', 'filter_greater_0': 'filter_greater', 'all_rows_5': 'all_rows', 'wins_6': 'wins', '90_7': '90', 'first win_8': 'first win', 'french grand prix_9': 'french grand prix', '2_10': '2'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_str_eq_1': [2], 'filter_greater_0': [1], 'all_rows_5': [0], 'wins_6': [0], '90_7': [0], 'first win_8': [1], 'french grand prix_9': [1], '2_10': [3]} | ['rank', 'engine', 'wins', 'first win', 'latest win'] | [['1', 'ferrari', '222', '1951 british grand prix', '2013 spanish grand prix'], ['2', 'ford', '176', '1967 dutch grand prix', '2003 brazilian grand prix'], ['3', 'renault', '162', '1979 french grand prix', '2013 indian grand prix'], ['4', 'mercedes - benz', '99', '1954 french grand prix', '2013 hungarian grand prix'], ['5', 'honda', '72', '1965 mexican grand prix', '2006 hungarian grand prix'], ['6', 'coventry climax', '40', '1958 argentine grand prix', '1965 german grand prix'], ['7', 'tag', '25', '1984 brazilian grand prix', '1987 portuguese grand prix'], ['8', 'bmw', '20', '1982 canadian grand prix', '2008 canadian grand prix'], ['9', 'brm', '18', '1959 dutch grand prix', '1972 monaco grand prix'], ['10', 'alfa romeo', '12', '1950 british grand prix', '1978 italian grand prix'], ['11', 'maserati', '11', '1953 italian grand prix', '1967 south african grand prix'], ['11', 'offenhauser', '11', '1950 indianapolis 500', '1960 indianapolis 500'], ['13', 'vanwall', '9', '1957 british grand prix', '1958 morocco grand prix'], ['14', 'repco', '8', '1966 french grand prix', '1967 canadian grand prix'], ['15', 'mugen honda', '4', '1996 monaco grand prix', '1999 italian grand prix'], ['16', 'matra', '3', '1977 swedish grand prix', '1981 canadian grand prix'], ['17', 'porsche', '1', '1962 french grand prix', '1962 french grand prix'], ['17', 'weslake', '1', '1967 belgian grand prix', '1967 belgian grand prix']] |
american dad ! ( season 7 ) | https://en.wikipedia.org/wiki/American_Dad%21_%28season_7%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-26409328-1.html.csv | ordinal | in american dad ! season 7 , the episode with the 2nd highest number of viewers is the one titled " for whom the sleigh bell tolls . " . | {'row': '8', 'col': '8', 'order': '2', 'col_other': '3', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'us viewers ( millions )', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; us viewers ( millions ) ; 2 }'}, 'title'], 'result': 'for whom the sleigh bell tolls', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; us viewers ( millions ) ; 2 } ; title }'}, 'for whom the sleigh bell tolls'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; us viewers ( millions ) ; 2 } ; title } ; for whom the sleigh bell tolls } = true', 'tointer': 'select the row whose us viewers ( millions ) record of all rows is 2nd maximum . the title record of this row is for whom the sleigh bell tolls .'} | eq { hop { nth_argmax { all_rows ; us viewers ( millions ) ; 2 } ; title } ; for whom the sleigh bell tolls } = true | select the row whose us viewers ( millions ) record of all rows is 2nd maximum . the title record of this row is for whom the sleigh bell tolls . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'us viewers (millions)_5': 5, '2_6': 6, 'title_7': 7, 'for whom the sleigh bell tolls_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', 'us viewers (millions)_5': 'us viewers ( millions )', '2_6': '2', 'title_7': 'title', 'for whom the sleigh bell tolls_8': 'for whom the sleigh bell tolls'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'us viewers (millions)_5': [0], '2_6': [0], 'title_7': [1], 'for whom the sleigh bell tolls_8': [2]} | ['no in series', 'no in season', 'title', 'directed by', 'written by', 'original air date', 'production code', 'us viewers ( millions )'] | [['97', '1', '100 ad ( part 1 )', 'tim parsons', 'keith heisler', 'october 3 , 2010', '5ajn14', '6.16'], ['98', '2', 'son of stan ( part 2 )', 'chris bennett', 'erik sommers', 'october 10 , 2010', '5ajn17', '5.36'], ['99', '3', 'best little horror house in langley falls', 'john aoshima & jansen yee', 'eric weinberg', 'november 7 , 2010', '5ajn19', '6.30'], ['100', '4', "stan 's food restaurant", 'josue cervantes', 'brian boyle', 'november 14 , 2010', '5ajn16', '5.38'], ['101', '5', 'white rice', 'bob bowen', 'rick wiener & kenny schwartz', 'november 21 , 2010', '5ajn15', '4.86'], ['102', '6', 'there will be bad blood', 'joe daniello', 'murray miller & judah miller', 'november 28 , 2010', '5ajn20', '6.13'], ['103', '7', 'the people vs martin sugar', 'pam cooke', 'jonathan fener', 'december 5 , 2010', '5ajn05', '5.31'], ['104', '8', 'for whom the sleigh bell tolls', 'bob bowen', 'erik durbin', 'december 12 , 2010', '5ajn22', '6.22'], ['105', '9', 'fart - break hotel', 'rodney clouden', 'chris mckenna & matt mckenna', 'january 16 , 2011', '5ajn18', '3.54'], ['106', '10', 'stanny boy and frantastic', 'pam cooke', 'laura mccreary', 'january 23 , 2011', '5ajn13', '4.81'], ['107', '11', 'a piã ± ata named desire', 'bob bowen', 'chris mckenna & matt mckenna', 'february 13 , 2011', '5ajn07', '3.93'], ['108', '12', 'you debt your life', 'chris bennett', 'erik sommers', 'february 20 , 2011', '5ajn09', '4.25'], ['109', '13', 'i am the walrus', 'tim parsons', 'keith heisler', 'march 27 , 2011', '5ajn21', '4.99'], ['110', '14', 'school lies', 'rodney clouden', 'brian boyle', 'april 3 , 2011', '6ajn03', '3.59'], ['111', '15', 'license to till', 'john aoshima & jansen yee', 'matt fusfeld & alex cuthbertson', 'april 10 , 2011', '6ajn04', '3.35'], ['112', '16', 'jenny fromdabloc', 'bob bowen', 'laura mccreary', 'april 17 , 2011', '6ajn08', '4.74'], ['113', '17', 'home wrecker', 'joe daniello', 'alan r cohen & alan freedland', 'may 8 , 2011', '6ajn05', '3.29'], ['114', '18', 'flirting with disaster', 'pam cooke', 'keith heisler', 'may 15 , 2011', '6ajn06', '3.89']] |
list of manchester united f.c. records and statistics | https://en.wikipedia.org/wiki/List_of_Manchester_United_F.C._records_and_statistics | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12783587-1.html.csv | ordinal | bill foulkes has the third highest league score of any player listed . | {'row': '4', 'col': '3', 'order': '3', 'col_other': '1', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'league', '3'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; league ; 3 }'}, 'name'], 'result': 'bill foulkes', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; league ; 3 } ; name }'}, 'bill foulkes'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; league ; 3 } ; name } ; bill foulkes } = true', 'tointer': 'select the row whose league record of all rows is 3rd maximum . the name record of this row is bill foulkes .'} | eq { hop { nth_argmax { all_rows ; league ; 3 } ; name } ; bill foulkes } = true | select the row whose league record of all rows is 3rd maximum . the name record of this row is bill foulkes . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'league_5': 5, '3_6': 6, 'name_7': 7, 'bill foulkes_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', 'league_5': 'league', '3_6': '3', 'name_7': 'name', 'bill foulkes_8': 'bill foulkes'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'league_5': [0], '3_6': [0], 'name_7': [1], 'bill foulkes_8': [2]} | ['name', 'years', 'league', 'fa cup', 'league cup', 'europe', 'other', 'total'] | [['ryan giggs', '1991 - present', '664 ( 113 )', '0 74 ( 12 )', '0 40 0 ( 6 )', '152 ( 23 )', '0 19 0 ( 3 )', '949 ( 157 )'], ['bobby charlton', '1956 - 1973', '606 0 ( 2 )', '0 78 0 ( 0 )', '0 24 0 ( 0 )', '0 45 0 ( 0 )', '00 5 0 ( 0 )', '758 00 ( 2 )'], ['paul scholes', '1994 - 2011 2012 - 2013', '499 ( 95 )', '0 49 ( 17 )', '0 21 0 ( 7 )', '134 ( 21 )', '0 15 0 ( 1 )', '718 ( 141 )'], ['bill foulkes', '1952 - 1970', '566 0 ( 3 )', '0 61 0 ( 0 )', '00 3 0 ( 0 )', '0 52 0 ( 0 )', '00 6 0 ( 0 )', '688 00 ( 3 )'], ['gary neville', '1992 - 2011', '400 ( 21 )', '0 47 0 ( 3 )', '0 25 0 ( 2 )', '117 0 ( 8 )', '0 13 0 ( 2 )', '602 0 ( 36 )'], ['alex stepney', '1966 - 1978', '433 0 ( 0 )', '0 44 0 ( 0 )', '0 35 0 ( 0 )', '0 23 0 ( 0 )', '00 4 0 ( 0 )', '539 00 ( 0 )'], ['tony dunne', '1960 - 1973', '414 0 ( 0 )', '0 55 0 ( 1 )', '0 21 0 ( 0 )', '0 40 0 ( 0 )', '00 5 0 ( 0 )', '535 00 ( 1 )'], ['denis irwin', '1990 - 2002', '368 ( 12 )', '0 43 0 ( 1 )', '0 31 0 ( 3 )', '0 75 0 ( 2 )', '0 12 0 ( 0 )', '529 0 ( 18 )'], ['joe spence', '1919 - 1933', '481 0 ( 0 )', '0 29 0 ( 0 )', '00 0 0 ( 0 )', '00 0 0 ( 0 )', '00 0 0 ( 0 )', '510 00 ( 0 )'], ['arthur albiston', '1974 - 1988', '379 ( 15 )', '0 36 0 ( 0 )', '0 40 0 ( 2 )', '0 27 0 ( 1 )', '00 3 0 ( 0 )', '485 0 ( 18 )']] |
alona bondarenko | https://en.wikipedia.org/wiki/Alona_Bondarenko | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1498593-2.html.csv | unique | the event in india was the only event where alona bondarenko had sania mirza as an opponent in the final . | {'scope': 'all', 'row': '1', 'col': '5', 'col_other': '3', 'criterion': 'equal', 'value': 'sania mirza', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent in the final', 'sania mirza'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose opponent in the final record fuzzily matches to sania mirza .', 'tostr': 'filter_eq { all_rows ; opponent in the final ; sania mirza }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; opponent in the final ; sania mirza } }', 'tointer': 'select the rows whose opponent in the final record fuzzily matches to sania mirza . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent in the final', 'sania mirza'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose opponent in the final record fuzzily matches to sania mirza .', 'tostr': 'filter_eq { all_rows ; opponent in the final ; sania mirza }'}, 'championship'], 'result': 'hyderabad , india', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; opponent in the final ; sania mirza } ; championship }'}, 'hyderabad , india'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; opponent in the final ; sania mirza } ; championship } ; hyderabad , india }', 'tointer': 'the championship record of this unqiue row is hyderabad , india .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; opponent in the final ; sania mirza } } ; eq { hop { filter_eq { all_rows ; opponent in the final ; sania mirza } ; championship } ; hyderabad , india } } = true', 'tointer': 'select the rows whose opponent in the final record fuzzily matches to sania mirza . there is only one such row in the table . the championship record of this unqiue row is hyderabad , india .'} | and { only { filter_eq { all_rows ; opponent in the final ; sania mirza } } ; eq { hop { filter_eq { all_rows ; opponent in the final ; sania mirza } ; championship } ; hyderabad , india } } = true | select the rows whose opponent in the final record fuzzily matches to sania mirza . there is only one such row in the table . the championship record of this unqiue row is hyderabad , india . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'opponent in the final_7': 7, 'sania mirza_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'championship_9': 9, 'hyderabad , india_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'opponent in the final_7': 'opponent in the final', 'sania mirza_8': 'sania mirza', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'championship_9': 'championship', 'hyderabad , india_10': 'hyderabad , india'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'opponent in the final_7': [0], 'sania mirza_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'championship_9': [2], 'hyderabad , india_10': [3]} | ['outcome', 'date', 'championship', 'surface', 'opponent in the final', 'score in the final'] | [['runner - up', '12 february 2005', 'hyderabad , india', 'hard', 'sania mirza', '4 - 6 , 7 - 5 , 3 - 6'], ['winner', '25 sep 2006', 'luxembourg city , luxembourg', 'hard ( i )', 'francesca schiavone', '6 - 3 , 6 - 2'], ['runner - up', '6 may 2007', 'warsaw , poland', 'clay', 'justine henin', '1 - 6 , 3 - 6'], ['runner - up', '23 may 2009', 'warsaw , poland', 'clay', 'alexandra dulgheru', '6 - 7 , 6 - 3 , 0 - 6'], ['winner', '16 january 2010', 'hobart , australia', 'hard', "shahar pe'er", '6 - 2 , 6 - 4']] |
1971 all - ireland senior hurling championship | https://en.wikipedia.org/wiki/1971_All-Ireland_Senior_Hurling_Championship | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13052263-3.html.csv | count | four of the players come from the county of kilkenny . | {'scope': 'all', 'criterion': 'equal', 'value': 'kilkenny', 'result': '4', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'county', 'kilkenny'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose county record fuzzily matches to kilkenny .', 'tostr': 'filter_eq { all_rows ; county ; kilkenny }'}], 'result': '4', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; county ; kilkenny } }', 'tointer': 'select the rows whose county record fuzzily matches to kilkenny . the number of such rows is 4 .'}, '4'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; county ; kilkenny } } ; 4 } = true', 'tointer': 'select the rows whose county record fuzzily matches to kilkenny . the number of such rows is 4 .'} | eq { count { filter_eq { all_rows ; county ; kilkenny } } ; 4 } = true | select the rows whose county record fuzzily matches to kilkenny . 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, 'county_5': 5, 'kilkenny_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', 'county_5': 'county', 'kilkenny_6': 'kilkenny', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'county_5': [0], 'kilkenny_6': [0], '4_7': [2]} | ['rank', 'player', 'county', 'tally', 'total', 'opposition'] | [['1', "michael ' babs ' keating", 'tipperary', '2 - 12', '18', 'galway'], ['2', 'eddie keher', 'kilkenny', '2 - 11', '17', 'tipperary'], ['3', 'eddie keher', 'kilkenny', '0 - 14', '14', 'london'], ['4', "michael ' babs ' keating", 'tipperary', '3 - 4', '13', 'limerick'], ['4', 'des coen', 'galway', '3 - 4', '13', 'antrim'], ['4', 'eddie keher', 'kilkenny', '2 - 7', '13', 'dublin'], ['7', 'richie bennis', 'limerick', '0 - 12', '12', 'tipperary'], ['8', 'richie bennis', 'limerick', '1 - 8', '11', 'cork'], ['8', 'eddie keher', 'kilkenny', '0 - 11', '11', 'wexford'], ['10', 'christy kehoe', 'wexford', '1 - 7', '10', 'kilkenny'], ['10', 'tom ryan', 'galway', '1 - 7', '10', 'antrim']] |
list of transformers : prime episodes | https://en.wikipedia.org/wiki/List_of_Transformers%3A_Prime_episodes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-29475589-3.html.csv | count | 1 transformers : prime episodes written by joseph kuhr was first aired in the us in march 2011 . | {'scope': 'subset', 'criterion': 'fuzzily_match', 'value': 'march', 'result': '1', 'col': '6', 'subset': {'col': '5', 'criterion': 'equal', 'value': 'joseph kuhr'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'writer ( s )', 'joseph kuhr'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; writer ( s ) ; joseph kuhr }', 'tointer': 'select the rows whose writer ( s ) record fuzzily matches to joseph kuhr .'}, 'us original airdate', 'march'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose writer ( s ) record fuzzily matches to joseph kuhr . among these rows , select the rows whose us original airdate record fuzzily matches to march .', 'tostr': 'filter_eq { filter_eq { all_rows ; writer ( s ) ; joseph kuhr } ; us original airdate ; march }'}], 'result': '1', 'ind': 2, 'tostr': 'count { filter_eq { filter_eq { all_rows ; writer ( s ) ; joseph kuhr } ; us original airdate ; march } }', 'tointer': 'select the rows whose writer ( s ) record fuzzily matches to joseph kuhr . among these rows , select the rows whose us original airdate record fuzzily matches to march . the number of such rows is 1 .'}, '1'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_eq { filter_eq { all_rows ; writer ( s ) ; joseph kuhr } ; us original airdate ; march } } ; 1 } = true', 'tointer': 'select the rows whose writer ( s ) record fuzzily matches to joseph kuhr . among these rows , select the rows whose us original airdate record fuzzily matches to march . the number of such rows is 1 .'} | eq { count { filter_eq { filter_eq { all_rows ; writer ( s ) ; joseph kuhr } ; us original airdate ; march } } ; 1 } = true | select the rows whose writer ( s ) record fuzzily matches to joseph kuhr . among these rows , select the rows whose us original airdate record fuzzily matches to march . the number of such rows is 1 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_str_eq_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'writer (s)_6': 6, 'joseph kuhr_7': 7, 'us original airdate_8': 8, 'march_9': 9, '1_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_str_eq_1': 'filter_str_eq', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'writer (s)_6': 'writer ( s )', 'joseph kuhr_7': 'joseph kuhr', 'us original airdate_8': 'us original airdate', 'march_9': 'march', '1_10': '1'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_str_eq_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'writer (s)_6': [0], 'joseph kuhr_7': [0], 'us original airdate_8': [1], 'march_9': [1], '1_10': [3]} | ['no', '-', 'episode title', 'director', 'writer ( s )', 'us original airdate', 'prod code'] | [['6', '1', 'masters and students', 'todd waterman', 'david slack', 'february 11 , 2011', '106'], ['7', '2', 'scrapheap', 'shaunt nigoghossian', 'marsha griffin', 'february 18 , 2011', '107'], ['8', '3', 'con job', 'vinton heuck', 'steven melching', 'february 25 , 2011', '108'], ['9', '4', 'convoy', 'todd waterman', 'joseph kuhr', 'march 4 , 2011', '109'], ['10', '5', 'deus ex machina', 'shaunt nigoghossian', 'nicole dubuc', 'march 11 , 2011', '110'], ['11', '6', 'speed metal', 'vinton heuck', 'dean stefan', 'april 9 , 2011', '111'], ['12', '7', 'predatory', 'todd waterman kirk van wormer ( co - director )', 'marsha griffin', 'april 16 , 2011', '112'], ['13', '8', 'sick mind', 'shaunt nigoghossian', 'steven melching', 'april 30 , 2011', '113'], ['14', '9', 'out of his head', 'vinton heuck', 'nicole dubuc', 'may 7 , 2011', '114'], ['15', '10', 'shadowzone', 'todd waterman', 'marsha griffin', 'may 14 , 2011', '115'], ['16', '11', 'operation : breakdown', 'shaunt nigoghossian', 'steven melching', 'june 18 , 2011', '116'], ['17', '12', 'crisscross', 'vinton heuck', 'joseph kuhr', 'june 25 , 2011', '117'], ['18', '13', 'metal attraction', 'todd waterman', 'nicole dubuc', 'july 9 , 2011', '118'], ['19', '14', 'rock bottom', 'shaunt nigoghossian', 'tim jones', 'july 16 , 2011', '119'], ['20', '15', 'partners', 'vinton heuck', 'mike johnson', 'july 23 , 2011', '120'], ['21', '16', 'tmi', 'todd waterman', 'joseph kuhr', 'september 10 , 2011', '121'], ['22', '17', 'stronger , faster', 'shaunt nigoghossian', 'mairghread scott', 'september 17 , 2011', '122'], ['23', '18', 'one shall fall', 'vinton heuck', 'duane capizzi joseph kuhr', 'september 24 , 2011', '123'], ['24', '19', 'one shall rise , part 1', 'todd waterman', 'nicole dubuc duane capizzi', 'october 1 , 2011', '124'], ['25', '20', 'one shall rise , part 2', 'shaunt nigoghossian', 'marsha griffin', 'october 8 , 2011', '125']] |
list of australia one day international cricket records | https://en.wikipedia.org/wiki/List_of_Australia_One_Day_International_cricket_records | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-21100348-11.html.csv | superlative | the highest number of runs for australia in an one day international cricket game was attributed to the player adam gilchrist . | {'scope': 'all', 'col_superlative': '6', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '3', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'runs'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; runs }'}, 'player'], 'result': 'adam gilchrist', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; runs } ; player }'}, 'adam gilchrist'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; runs } ; player } ; adam gilchrist } = true', 'tointer': 'select the row whose runs record of all rows is maximum . the player record of this row is adam gilchrist .'} | eq { hop { argmax { all_rows ; runs } ; player } ; adam gilchrist } = true | select the row whose runs record of all rows is maximum . the player record of this row is adam gilchrist . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'runs_5': 5, 'player_6': 6, 'adam gilchrist_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', 'player_6': 'player', 'adam gilchrist_7': 'adam gilchrist'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'runs_5': [0], 'player_6': [1], 'adam gilchrist_7': [2]} | ['rank', 'strike rate', 'player', 'innings', 'balls faced', 'runs', 'period'] | [['1', '96.89', 'adam gilchrist', '278', '9902', '9595', '1996 - 2008'], ['2', '96.12', 'mitchell johnson', '64', '749', '720', '2005 -'], ['3', '95.40', 'shane lee', '35', '500', '477', '1995 - 2001'], ['4', '93.71', 'james hopes', '61', '1415', '1326', '2005 - 2010'], ['5', '92.44', 'andrew symonds', '161', '5504', '5088', '1998 - 2009'], ['6', '91.67', 'david hussey', '57', '1885', '1728', '2008 -'], ['7', '88.27', 'shane watson', '134', '5169', '4563', '2002 -'], ['8', '88.16', 'ian harvey', '51', '811', '715', '1997 - 2004'], ['9', '87.51', 'brad hodge', '21', '657', '575', '2005 - 2007']] |
political appointments system in hong kong | https://en.wikipedia.org/wiki/Political_Appointments_System_in_Hong_Kong | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17964087-1.html.csv | comparative | the person appointed to the food and health department was younger than the person appointed to the position in environment . | {'row_1': '4', 'row_2': '5', 'col': '3', 'col_other': '5', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'portfolio attachment', 'food and health'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose portfolio attachment record fuzzily matches to food and health .', 'tostr': 'filter_eq { all_rows ; portfolio attachment ; food and health }'}, 'age at appointment'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; portfolio attachment ; food and health } ; age at appointment }', 'tointer': 'select the rows whose portfolio attachment record fuzzily matches to food and health . take the age at appointment record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'portfolio attachment', 'environment'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose portfolio attachment record fuzzily matches to environment .', 'tostr': 'filter_eq { all_rows ; portfolio attachment ; environment }'}, 'age at appointment'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; portfolio attachment ; environment } ; age at appointment }', 'tointer': 'select the rows whose portfolio attachment record fuzzily matches to environment . take the age at appointment record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; portfolio attachment ; food and health } ; age at appointment } ; hop { filter_eq { all_rows ; portfolio attachment ; environment } ; age at appointment } } = true', 'tointer': 'select the rows whose portfolio attachment record fuzzily matches to food and health . take the age at appointment record of this row . select the rows whose portfolio attachment record fuzzily matches to environment . take the age at appointment record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; portfolio attachment ; food and health } ; age at appointment } ; hop { filter_eq { all_rows ; portfolio attachment ; environment } ; age at appointment } } = true | select the rows whose portfolio attachment record fuzzily matches to food and health . take the age at appointment record of this row . select the rows whose portfolio attachment record fuzzily matches to environment . take the age at appointment 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, 'portfolio attachment_7': 7, 'food and health_8': 8, 'age at appointment_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'portfolio attachment_11': 11, 'environment_12': 12, 'age at appointment_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', 'portfolio attachment_7': 'portfolio attachment', 'food and health_8': 'food and health', 'age at appointment_9': 'age at appointment', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'portfolio attachment_11': 'portfolio attachment', 'environment_12': 'environment', 'age at appointment_13': 'age at appointment'} | {'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'portfolio attachment_7': [0], 'food and health_8': [0], 'age at appointment_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'portfolio attachment_11': [1], 'environment_12': [1], 'age at appointment_13': [3]} | ['romanised name', 'chinese name', 'age at appointment', 'foreign nationality', 'portfolio attachment', 'govt salary'] | [['chen wei - on , kenneth', '陳維安', '43', 'n / a', 'education', 'hk223585'], ['hui hiu - fai , florence', '許曉暉', '34', 'n / a', 'home affairs', 'hk223585'], ['leung fung - yee , julia', '梁鳳儀', '48', 'british', 'financial services and the treasury', 'hk223585'], ['leung , gabriel matthew', '梁卓偉', '35', 'canadian', 'food and health', 'hk208680'], ['poon kit , kitty', '潘潔', '45', 'us', 'environment', 'hk208680'], ['tam chi - yuen , raymond', '譚志源', '44', 'british', 'constitutional and mainland affairs', 'hk208680'], ['so kam - leung , gregory', '蘇錦樑', '49', 'canadian', 'commerce and economic development', 'hk223585'], ['yau shing - mu', '邱誠武', '48', 'n / a', 'transport and housing', 'hk 208680']] |
2004 cleveland browns season | https://en.wikipedia.org/wiki/2004_Cleveland_Browns_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10652530-2.html.csv | count | in the 2004 season , the cleveland browns played against the baltimore ravens 2 times . | {'scope': 'all', 'criterion': 'equal', 'value': 'baltimore ravens', 'result': '2', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', 'baltimore ravens'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose opponent record fuzzily matches to baltimore ravens .', 'tostr': 'filter_eq { all_rows ; opponent ; baltimore ravens }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; opponent ; baltimore ravens } }', 'tointer': 'select the rows whose opponent record fuzzily matches to baltimore ravens . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; opponent ; baltimore ravens } } ; 2 } = true', 'tointer': 'select the rows whose opponent record fuzzily matches to baltimore ravens . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; opponent ; baltimore ravens } } ; 2 } = true | select the rows whose opponent record fuzzily matches to baltimore ravens . 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, 'baltimore ravens_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', 'baltimore ravens_6': 'baltimore ravens', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'opponent_5': [0], 'baltimore ravens_6': [0], '2_7': [2]} | ['week', 'date', 'opponent', 'result', 'stadium', 'record', 'attendance'] | [['1', 'september 12 , 2004', 'baltimore ravens', 'w 20 - 3', 'cleveland browns stadium', '1 - 0', '73068'], ['2', 'september 19 , 2004', 'dallas cowboys', 'l 12 - 19', 'texas stadium', '1 - 1', '63119'], ['3', 'september 26 , 2004', 'new york giants', 'l 10 - 27', 'giants stadium', '1 - 2', '78521'], ['4', 'october 3 , 2004', 'washington redskins', 'w 17 - 13', 'cleveland browns stadium', '2 - 2', '73348'], ['5', 'october 10 , 2004', 'pittsburgh steelers', 'l 23 - 34', 'heinz field', '2 - 3', '63609'], ['6', 'october 17 , 2004', 'cincinnati bengals', 'w 34 - 17', 'cleveland browns stadium', '3 - 3', '73263'], ['7', 'october 24 , 2004', 'philadelphia eagles', 'l 31 - 34', 'cleveland browns stadium', '3 - 4', '73394'], ['8', '-', '-', '-', '-', '-', ''], ['9', 'november 7 , 2004', 'baltimore ravens', 'l 13 - 27', 'm & t bank stadium', '3 - 5', '69781'], ['10', 'november 14 , 2004', 'pittsburgh steelers', 'l 10 - 24', 'cleveland browns stadium', '3 - 6', '73703'], ['11', 'november 21 , 2004', 'new york jets', 'l 7 - 10', 'cleveland browns stadium', '3 - 7', '72547'], ['12', 'november 28 , 2004', 'cincinnati bengals', 'l 48 - 58', 'paul brown stadium', '3 - 8', '65677'], ['13', 'december 5 , 2004', 'new england patriots', 'l 15 - 42', 'cleveland browns stadium', '3 - 9', '73028'], ['14', 'december 12 , 2004', 'buffalo bills', 'l 7 - 37', 'ralph wilson stadium', '3 - 10', '72330'], ['15', 'december 19 , 2004', 'san diego chargers', 'l 0 - 21', 'cleveland browns stadium', '3 - 11', '72489'], ['16', 'december 26 , 2004', 'miami dolphins', 'l 7 - 10', 'pro player stadium', '3 - 12', '73169'], ['17', 'january 2 , 2005', 'houston texans', 'w 22 - 14', 'reliant stadium', '4 - 12', '70724']] |
nature of america | https://en.wikipedia.org/wiki/Nature_of_America | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-15635768-1.html.csv | majority | for nature of america , when the printer was avery dennison , the face value was always over 35 . | {'scope': 'subset', 'col': '5', 'most_or_all': 'all', 'criterion': 'greater_than', 'value': '35', 'subset': {'col': '6', 'criterion': 'equal', 'value': 'avery dennison'}} | {'func': 'all_greater', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'printer', 'avery dennison'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; printer ; avery dennison }', 'tointer': 'select the rows whose printer record fuzzily matches to avery dennison .'}, 'face value', '35'], 'result': True, 'ind': 1, 'tointer': 'select the rows whose printer record fuzzily matches to avery dennison . for the face value records of these rows , all of them are greater than 35 .', 'tostr': 'all_greater { filter_eq { all_rows ; printer ; avery dennison } ; face value ; 35 } = true'} | all_greater { filter_eq { all_rows ; printer ; avery dennison } ; face value ; 35 } = true | select the rows whose printer record fuzzily matches to avery dennison . for the face value records of these rows , all of them are greater than 35 . | 2 | 2 | {'all_greater_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, 'printer_4': 4, 'avery dennison_5': 5, 'face value_6': 6, '35_7': 7} | {'all_greater_1': 'all_greater', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'printer_4': 'printer', 'avery dennison_5': 'avery dennison', 'face value_6': 'face value', '35_7': '35'} | {'all_greater_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'printer_4': [0], 'avery dennison_5': [0], 'face value_6': [1], '35_7': [1]} | ['ecosystem', 'date of issue', 'place of issue', 'no stamps in sheet', 'face value', 'printer'] | [['sonoran desert', 'april 6 , 1999', 'tucson , arizona', '10', '33', 'banknote corporation of america'], ['pacific coast rain forest', 'march 28 , 2000', 'seattle , washington', '10', '33', 'banknote corporation of america'], ['great plains prairie', 'march 29 , 2001', 'lincoln , nebraska', '10', '34', 'ashton - potter ( usa ) ltd'], ['longleaf pine forest', 'april 26 , 2002', 'tallahassee , florida', '10', '34', 'american packaging corp for sennet security'], ['arctic tundra', 'july 1 , 2003', 'fairbanks , alaska', '10', '37', 'banknote corporation of america'], ['pacific coral reef', 'jan 2 , 2004', 'honolulu , hawaii', '10', '37', 'avery dennison'], ['northeast deciduous forest', 'march 3 , 2005', 'new york , new york', '10', '37', 'avery dennison'], ['southern florida wetland', 'october 5 , 2006', 'naples , florida', '10', '39', 'avery dennison'], ['alpine tundra', 'august 28 , 2007', 'estes park , colorado', '10', '41', 'sennett security products'], ['great lakes dunes', 'october 2 , 2008', 'empire , michigan', '10', '42', 'avery dennison'], ['kelp forest', 'october 1 , 2009', 'monterey , california', '10', '44', 'avery dennison']] |
1957 ohio state buckeyes football team | https://en.wikipedia.org/wiki/1957_Ohio_State_Buckeyes_football_team | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17998617-1.html.csv | count | the 1957 ohio state buckeyes football team played 4 games in the month of november . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'november', 'result': '4', 'col': '1', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', 'november'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose date record fuzzily matches to november .', 'tostr': 'filter_eq { all_rows ; date ; november }'}], 'result': '4', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; date ; november } }', 'tointer': 'select the rows whose date record fuzzily matches to november . the number of such rows is 4 .'}, '4'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; date ; november } } ; 4 } = true', 'tointer': 'select the rows whose date record fuzzily matches to november . the number of such rows is 4 .'} | eq { count { filter_eq { all_rows ; date ; november } } ; 4 } = true | select the rows whose date record fuzzily matches to november . 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, 'date_5': 5, 'november_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', 'date_5': 'date', 'november_6': 'november', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'date_5': [0], 'november_6': [0], '4_7': [2]} | ['date', 'opponent', 'site', 'result', 'attendance'] | [['september 28', 'tcu', 'ohio stadium columbus , oh', 'l14 - 18', '81784'], ['october 5', 'washington', 'husky stadium seattle , wa', 'w35 - 7', '37500'], ['october 12', 'illinois', 'ohio stadium columbus , oh', 'w21 - 7', '82239'], ['october 19', 'indiana', 'ohio stadium columbus , oh', 'w56 - 0', '78348'], ['october 26', 'wisconsin', 'camp randall stadium madison , wi', 'w16 - 13', '51051'], ['november 2', 'northwestern', 'ohio stadium columbus , oh', 'w47 - 6', '79635'], ['november 9', 'purdue', 'ohio stadium columbus , oh', 'w20 - 7', '79177'], ['november 16', '5 iowa', 'ohio stadium columbus , oh', 'w17 - 13', '82935'], ['november 23', '19 michigan', 'michigan stadium ann arbor , mi', 'w31 - 14', '101001'], ['january 1', 'oregon', 'rose bowl pasadena , ca ( rose bowl )', 'w10 - 7', '98202']] |
julian bailey | https://en.wikipedia.org/wiki/Julian_Bailey | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1235920-4.html.csv | aggregation | julian bailey drove a total number of 535 laps in his races . | {'scope': 'all', 'col': '6', 'type': 'sum', 'result': '535', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'laps'], 'result': '535', 'ind': 0, 'tostr': 'sum { all_rows ; laps }'}, '535'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; laps } ; 535 } = true', 'tointer': 'the sum of the laps record of all rows is 535 .'} | round_eq { sum { all_rows ; laps } ; 535 } = true | the sum of the laps record of all rows is 535 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'laps_4': 4, '535_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'laps_4': 'laps', '535_5': '535'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'laps_4': [0], '535_5': [1]} | ['year', 'class', 'tyres', 'team', 'co - drivers', 'laps', 'pos'] | [['1989', 'c1', 'd', 'nissan motorsports', 'mark blundell martin donnelly', '5', 'dnf'], ['1990', 'c1', 'd', 'nissan motorsports international', 'mark blundell gianfranco brancatelli', '142', 'dnf'], ['1997', 'gt1', 'd', 'newcastle united lister', 'thomas erdos mark skaife', '77', 'dnf'], ['2001', 'lmp675', 'm', 'mg sport & racing ltd', 'mark blundell kevin mcgarrity', '92', 'dnf'], ['2002', 'lmp675', 'm', 'mg sport & racing ltd', 'mark blundell kevin mcgarrity', '219', 'dnf']] |
list of true jackson , vp episodes | https://en.wikipedia.org/wiki/List_of_True_Jackson%2C_VP_episodes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-20046379-3.html.csv | majority | of the true jackson , vp episodes that took place in may , most of the time the director was gary halvorson . | {'scope': 'subset', 'col': '4', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'gary halvorson', 'subset': {'col': '6', 'criterion': 'fuzzily_match', 'value': 'may'}} | {'func': 'most_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'original air date', 'may'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; original air date ; may }', 'tointer': 'select the rows whose original air date record fuzzily matches to may .'}, 'directed by', 'gary halvorson'], 'result': True, 'ind': 1, 'tointer': 'select the rows whose original air date record fuzzily matches to may . for the directed by records of these rows , most of them fuzzily match to gary halvorson .', 'tostr': 'most_eq { filter_eq { all_rows ; original air date ; may } ; directed by ; gary halvorson } = true'} | most_eq { filter_eq { all_rows ; original air date ; may } ; directed by ; gary halvorson } = true | select the rows whose original air date record fuzzily matches to may . for the directed by records of these rows , most of them fuzzily match to gary halvorson . | 2 | 2 | {'most_str_eq_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, 'original air date_4': 4, 'may_5': 5, 'directed by_6': 6, 'gary halvorson_7': 7} | {'most_str_eq_1': 'most_str_eq', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'original air date_4': 'original air date', 'may_5': 'may', 'directed by_6': 'directed by', 'gary halvorson_7': 'gary halvorson'} | {'most_str_eq_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'original air date_4': [0], 'may_5': [0], 'directed by_6': [1], 'gary halvorson_7': [1]} | ['no in series', 'no in season', 'title', 'directed by', 'written by', 'original air date', 'production code', 'us viewers ( millions )'] | [['27', '1', 'true concert', 'gary halvorson', 'dan kopelman', 'november 14 , 2009', '204', '3.8'], ['30', '4', 'true parade', 'gary halvorson', 'andy gordon', 'december 12 , 2009', '210', 'n / a'], ['31', '5', 'true drama', 'roger christiansen', 'steve joe', 'january 9 , 2010', '211', '3.3'], ['32', '6', 'my boss ate my homework', 'roger christiansen', 'diana sproveri', 'january 16 , 2010', '203', 'n / a'], ['33', '7', 'little buddies', 'adam weissman', 'sib ventress', 'january 30 , 2010', '208', 'n / a'], ['34', '8', 'true valentine', 'gary halvorson', 'sebastian jones', 'february 6 , 2010', '206', 'n / a'], ['35', '9', 'true date', 'dennie gordon', 'steve joe', 'february 20 , 2010', '212', 'n / a'], ['36', '10', 'the hunky librarian', 'roger christiansen', 'sarah jane cunningham & suzie v freeman', 'march 13 , 2010', '209', 'n / a'], ['37', '11', 'saving snackleberry', 'roger christiansen', 'stacey cantwell', 'march 20 , 2010', '213', 'n / a'], ['38', '12', 'pajama party', 'gary halvorson', 'steve joe', 'april 3 , 2010', '207', 'n / a'], ['39', '13', 'the gift', 'roger christiansen', 'andy gordon', 'april 17 , 2010', '205', 'n / a'], ['40', '14', 'true royal', 'roger christiansen', 'sarah jane cunningham & suzie v freeman', 'may 1 , 2010', '214', '3.7'], ['41', '15', 'true fear', 'gary halvorson', 'sib ventress', 'may 8 , 2010', '216', 'n / a'], ['42', '16', 'the reject room', 'gary halvorson', 'dan kopelman', 'may 15 , 2010', '215', 'n / a'], ['43 - 44', '17 - 18', 'mission gone bad trapped in paris', 'gary halvorson', 'andy gordon', 'may 22 , 2010', '218 - 219', '3.4'], ['45', '19', 'heatwave', 'gregg heschong', 'steve joe', 'june 26 , 2010', '217', 'n / a']] |
yanina wickmayer | https://en.wikipedia.org/wiki/Yanina_Wickmayer | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15100199-8.html.csv | majority | the majority of yanina wickmayer 's tournaments were played on a hard surface . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'hard', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'surface', 'hard'], 'result': True, 'ind': 0, 'tointer': 'for the surface records of all rows , most of them fuzzily match to hard .', 'tostr': 'most_eq { all_rows ; surface ; hard } = true'} | most_eq { all_rows ; surface ; hard } = true | for the surface records of all rows , most of them fuzzily match to hard . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'surface_3': 3, 'hard_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'surface_3': 'surface', 'hard_4': 'hard'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'surface_3': [0], 'hard_4': [0]} | ['outcome', 'date', 'tournament', 'surface', 'opponent', 'score'] | [['runner - up', '14 may 2006', 'edinburgh , united kingdom', 'clay', 'mari andersson', '6 - 0 , 1 - 6 , 3 - 6'], ['winner', '20 august 2006', 'koksijde , belgium', 'clay', 'kristina steiert', '6 - 4 , 6 - 1'], ['winner', '19 november 2006', 'florianópolis , brazil', 'clay', 'estefania craciún', '6 - 1 , 6 - 0'], ['winner', '26 november 2006', 'córdoba , argentina', 'clay', 'teliana pereira', '6 - 1 , 6 - 7 ( 4 - 7 ) , 6 - 0'], ['runner - up', '15 april 2007', 'torhout , belgium', 'hard', 'claire feuerstein', '4 - 6 , 4 - 6'], ['winner', '29 july 2007', 'les contamines , france', 'hard', 'julie coin', '6 - 2 , 7 - 6 ( 7 - 3 )'], ['winner', '28 october 2007', 'hamanako , japan', 'carpet', 'junri namigata', '4 - 6 , 6 - 4 , 6 - 2'], ['runner - up', '4 november 2007', 'taoyuan city , taiwan', 'hard', 'akiko morigami', '4 - 6 , 6 - 7 ( 5 - 7 )'], ['winner', '11 november 2007', 'taizhou , china', 'hard', 'han xinyun', '6 - 2 , 6 - 2'], ['winner', '18 november 2007', 'kunming , china', 'hard', 'urszula radwańska', '7 - 5 , 6 - 4'], ['runner - up', '15 march 2008', 'new delhi , india', 'hard', 'ekaterina dzehalevich', '6 - 2 , 3 - 6 , 2 - 6'], ['runner - up', '13 april 2008', 'monzón , spain', 'hard', 'petra kvitová', '6 - 2 , 4 - 6 , 5 - 7'], ['winner', '11 may 2008', 'indian harbour beach , usa', 'clay', 'bethanie mattek', '6 - 4 , 7 - 5'], ['winner', '22 february 2009', 'surprise , usa', 'hard', 'julia vakulenko', '6 - 7 ( 0 - 7 ) , 6 - 3 , 4 - 3 , retired'], ['runner - up', '1 march 2009', 'clearwater , united states', 'hard', 'julie coin', '6 - 3 , 1 - 1 retired'], ['runner - up', '17 march 2009', 'saint - gaudens , france', 'clay', 'anastasiya yakimova', '5 - 7 , 6 - 7 ( 0 - 7 )'], ['winner', '17 october 2010', 'torhout , belgium', 'hard', 'simona halep', '6 - 3 , 6 - 2']] |
tourism | https://en.wikipedia.org/wiki/Tourism | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-29789-3.html.csv | count | three of the top 9 countries has a change in expenditure percentage higher than 10 % . | {'scope': 'all', 'criterion': 'greater_than', 'value': '10 %', 'result': '3', 'col': '6', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater', 'args': ['all_rows', '% change', '10 %'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose % change record is greater than 10 % .', 'tostr': 'filter_greater { all_rows ; % change ; 10 % }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_greater { all_rows ; % change ; 10 % } }', 'tointer': 'select the rows whose % change record is greater than 10 % . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_greater { all_rows ; % change ; 10 % } } ; 3 } = true', 'tointer': 'select the rows whose % change record is greater than 10 % . the number of such rows is 3 .'} | eq { count { filter_greater { all_rows ; % change ; 10 % } } ; 3 } = true | select the rows whose % change record is greater than 10 % . 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, '% change_5': 5, '10%_6': 6, '3_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_greater_0': 'filter_greater', 'all_rows_4': 'all_rows', '% change_5': '% change', '10%_6': '10 %', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_greater_0': [1], 'all_rows_4': [0], '% change_5': [0], '10%_6': [0], '3_7': [2]} | ['rank 2012', 'country', 'unwto region', 'international tourism expenditure 2011', 'international tourism expenditure 2012', '% change'] | [['1', 'china', 'asia', '72.3 billion', '102.0 billion', '40.5'], ['2', 'germany', 'europe', '85.9 billion', '83.8 billion', '2.4'], ['3', 'united states', 'north america', '78.7 billion', '83.7 billion', '6.6'], ['4', 'united kingdom', 'europe', '51.0 billion', '52.3 billion', '2.5'], ['5', 'russia', 'europe', '32.5 billion', '42.8 billion', '31.6'], ['6', 'france', 'europe', '44.1 billion', '38.1 billion', '13.6'], ['7', 'canada', 'north america', '33.3 billion', '35.2 billion', '5.7'], ['8', 'japan', 'asia', '27.2 billion', '28.1 billion', '3.3'], ['9', 'australia', 'oceania', '26.7 billion', '27.6 billion', '3.4']] |
joão sousa | https://en.wikipedia.org/wiki/Jo%C3%A3o_Sousa | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-23563375-11.html.csv | majority | most of the games took place on hard surfaces . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'hard', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'surface', 'hard'], 'result': True, 'ind': 0, 'tointer': 'for the surface records of all rows , most of them fuzzily match to hard .', 'tostr': 'most_eq { all_rows ; surface ; hard } = true'} | most_eq { all_rows ; surface ; hard } = true | for the surface records of all rows , most of them fuzzily match to hard . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'surface_3': 3, 'hard_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'surface_3': 'surface', 'hard_4': 'hard'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'surface_3': [0], 'hard_4': [0]} | ['edition', 'round', 'date', 'against', 'surface', 'opponent', 'w / l', 'result'] | [['2008 davis cup europe / africa group ii', 'qf', '18 - 20 july 2008', 'cyprus', 'clay', 'eleftherios christou', 'win', '6 - 3 , 6 - 3'], ['2008 davis cup europe / africa group ii', 'sf', '19 - 21 september 2008', 'ukraine', 'hard', 'illya marchenko', 'loss', '3 - 6 , 3 - 6'], ['2009 davis cup europe / africa group ii', '1r', '6 - 8 march 2009', 'cyprus', 'hard', 'philippos tsangaridis', 'win', '6 - 3 , 6 - 1'], ['2009 davis cup europe / africa group ii', 'gii po', '10 - 12 july 2009', 'algeria', 'clay', 'sid - ali akkal', 'win', '6 - 3 , 6 - 0'], ['2010 davis cup europe / africa group ii', 'qf', '9 - 11 july 2010', 'cyprus', 'clay', 'eleftherios christou', 'win', '6 - 1 , 6 - 0'], ['2010 davis cup europe / africa group ii', 'sf', '17 - 19 september 2010', 'bosnia and herzegovina', 'clay', 'damir džumhur', 'loss', '6 - 4 , 4 - 6 , 1 - 6'], ['2011 davis cup europe / africa group i', '1r', '4 - 6 march 2011', 'slovakia', 'clay', 'martin kližan', 'win', '6 - 2 , 4 - 1 , ret'], ['2011 davis cup europe / africa group i', '2r', '8 - 10 july 2011', 'switzerland', 'hard', 'marco chiudinelli', 'loss', '3 - 6 , 4 - 6'], ['2012 davis cup europe / africa group i', '2r', '6 - 8 april 2012', 'israel', 'hard', 'andy ram', 'win', '7 - 5 , 6 - 0'], ['2012 davis cup europe / africa group i', 'gi po', '14 - 16 september 2012', 'slovakia', 'hard', 'lukas lacko', 'win', '6 - 4 , 6 - 4 , 6 - 3'], ['2012 davis cup europe / africa group i', 'gi po', '14 - 16 september 2012', 'slovakia', 'hard', 'martin kližan', 'loss', '2 - 6 , 5 - 7 , 7 - 6 ( 11 - 9 ) , 1 - 6'], ['2013 davis cup europe / africa group ii', '1r', '1 - 3 february 2013', 'benin', 'clay', 'loic didavi', 'win', '6 - 1 , 6 - 3 , 6 - 0'], ['2013 davis cup europe / africa group ii', '3r', '13 - 15 september 2013', 'moldova', 'hard', 'maxim dubarenco', 'win', '6 - 7 ( 4 - 7 ) , 7 - 6 ( 7 - 4 ) , 6 - 1 , 6 - 4']] |
list of new jersey transit stations | https://en.wikipedia.org/wiki/List_of_New_Jersey_Transit_stations | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1051326-3.html.csv | comparative | the great notch transit station was closed after the finderne station . | {'row_1': '6', 'row_2': '5', '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', 'station', 'great notch'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose station record fuzzily matches to great notch .', 'tostr': 'filter_eq { all_rows ; station ; great notch }'}, 'closed'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; station ; great notch } ; closed }', 'tointer': 'select the rows whose station record fuzzily matches to great notch . take the closed record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'station', 'finderne'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose station record fuzzily matches to finderne .', 'tostr': 'filter_eq { all_rows ; station ; finderne }'}, 'closed'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; station ; finderne } ; closed }', 'tointer': 'select the rows whose station record fuzzily matches to finderne . take the closed record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; station ; great notch } ; closed } ; hop { filter_eq { all_rows ; station ; finderne } ; closed } } = true', 'tointer': 'select the rows whose station record fuzzily matches to great notch . take the closed record of this row . select the rows whose station record fuzzily matches to finderne . take the closed record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; station ; great notch } ; closed } ; hop { filter_eq { all_rows ; station ; finderne } ; closed } } = true | select the rows whose station record fuzzily matches to great notch . take the closed record of this row . select the rows whose station record fuzzily matches to finderne . take the closed 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, 'station_7': 7, 'great notch_8': 8, 'closed_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'station_11': 11, 'finderne_12': 12, 'closed_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', 'station_7': 'station', 'great notch_8': 'great notch', 'closed_9': 'closed', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'station_11': 'station', 'finderne_12': 'finderne', 'closed_13': 'closed'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'station_7': [0], 'great notch_8': [0], 'closed_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'station_11': [1], 'finderne_12': [1], 'closed_13': [3]} | ['station', 'municipality', 'county', 'former railroad', 'closed'] | [['ampere', 'east orange', 'essex , nj', 'lackawanna', '1991'], ['arlington', 'kearney', 'hudson , nj', 'erie', '2002'], ['benson street', 'glen ridge', 'essex , nj', 'erie', '2002'], ['fairmount avenue', 'hackensack', 'bergen , nj', 'erie', '1983'], ['finderne', 'finderne', 'somerset , nj', 'jersey central', '2006'], ['great notch', 'great notch', 'passaic , nj', 'erie', '2010'], ['grove street', 'east orange', 'essex , nj', 'lackawanna', '1991'], ['harmon cove', 'secaucus', 'hudson , nj', 'erie', '2003'], ['harrison', 'harrison', 'hudson , nj', 'lackawanna', '1984'], ['north newark', 'newark', 'essex , nj', 'lackawanna', '1984'], ['north rahway', 'rahway', 'fairfield , nj', 'pennsylvania', '1993'], ['roseville avenue', 'newark', 'essex , nj', 'lackawanna', '1984'], ['rowe street', 'bloomfield township', 'essex , nj', 'erie', '2002']] |
2008 tour of missouri | https://en.wikipedia.org/wiki/2008_Tour_of_Missouri | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15502952-15.html.csv | count | mark cavendish won 3 stages in the 2008 tour of missouri . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'mark cavendish', 'result': '3', 'col': '1', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'stage ( winner )', 'mark cavendish'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose stage ( winner ) record fuzzily matches to mark cavendish .', 'tostr': 'filter_eq { all_rows ; stage ( winner ) ; mark cavendish }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; stage ( winner ) ; mark cavendish } }', 'tointer': 'select the rows whose stage ( winner ) record fuzzily matches to mark cavendish . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; stage ( winner ) ; mark cavendish } } ; 3 } = true', 'tointer': 'select the rows whose stage ( winner ) record fuzzily matches to mark cavendish . the number of such rows is 3 .'} | eq { count { filter_eq { all_rows ; stage ( winner ) ; mark cavendish } } ; 3 } = true | select the rows whose stage ( winner ) record fuzzily matches to mark cavendish . 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, 'stage (winner)_5': 5, 'mark cavendish_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', 'stage (winner)_5': 'stage ( winner )', 'mark cavendish_6': 'mark cavendish', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'stage (winner)_5': [0], 'mark cavendish_6': [0], '3_7': [2]} | ['stage ( winner )', 'general classification', 'young classification', 'mountains classification', 'sprint classification', 'team classification'] | [['0 stage 1 ( mark cavendish )', 'mark cavendish', 'mark cavendish', 'dominique rollin', 'mark cavendish', 'team columbia'], ['0 stage 2 ( mark cavendish )', 'mark cavendish', 'mark cavendish', 'dominique rollin', 'mark cavendish', 'garmin - chipotle - h30'], ['0 stage 3 ( christian vande velde )', 'christian vande velde', 'steven cozza', 'dominique rollin', 'mark cavendish', 'garmin - chipotle - h30'], ['0 stage 4 ( michael barry )', 'christian vande velde', 'roman kreuziger', 'dominique rollin', 'eric baumann', 'team columbia'], ['0 stage 5 ( boy van poppel )', 'christian vande velde', 'roman kreuziger', 'dominique rollin', 'mark cavendish', 'team columbia'], ['0 stage 6 ( mark cavendish )', 'christian vande velde', 'roman kreuziger', 'dominique rollin', 'mark cavendish', 'team columbia'], ['0 stage 7 ( francesco chicchi )', 'christian vande velde', 'roman kreuziger', 'dominique rollin', 'mark cavendish', 'team columbia'], ['0 final', 'christian vande velde', 'roman kreuziger', 'dominique rollin', 'mark cavendish', 'team columbia']] |
2003 cricket world cup statistics | https://en.wikipedia.org/wiki/2003_Cricket_World_Cup_statistics | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11611293-10.html.csv | aggregation | in 2003 cricket world cup statistics the average catches were 3.125 . | {'scope': 'all', 'col': '1', 'type': 'average', 'result': '3.125', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'catches'], 'result': '3.125', 'ind': 0, 'tostr': 'avg { all_rows ; catches }'}, '3.125'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; catches } ; 3.125 } = true', 'tointer': 'the average of the catches record of all rows is 3.125 .'} | round_eq { avg { all_rows ; catches } ; 3.125 } = true | the average of the catches record of all rows is 3.125 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'catches_4': 4, '3.125_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'catches_4': 'catches', '3.125_5': '3.125'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'catches_4': [0], '3.125_5': [1]} | ['catches', 'player', 'versus', 'venue', 'date'] | [['4', 'm kaif', 'sri lanka', 'johannesburg', '10 - 03 - 2003'], ['3', 'v sehwag', 'netherlands', 'paarl', '12 - 02 - 2003'], ['3', 'lj burger', 'england', 'port elizabeth', '19 - 02 - 2003'], ['3', 'jp maher', 'netherlands', 'potchefstroom', '20 - 02 - 2003'], ['3', 'hh dippenaar', 'bangladesh', 'bloemfontein', '22 - 02 - 2003'], ['3', 'd mongia', 'namibia', 'pietermaritzburg', '23 - 02 - 2003'], ['3', 'v sehwag', 'england', 'durban', '26 - 02 - 2003'], ['3', 'af giles', 'australia', 'port elizabeth', '02 - 03 - 2003']] |
aveiro district | https://en.wikipedia.org/wiki/Aveiro_District | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1794599-1.html.csv | majority | the majority of municipalities in the aveiro district are in the baixo vouga subregion . | {'scope': 'all', 'col': '7', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'baixo vouga', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'subregion', 'baixo vouga'], 'result': True, 'ind': 0, 'tointer': 'for the subregion records of all rows , most of them fuzzily match to baixo vouga .', 'tostr': 'most_eq { all_rows ; subregion ; baixo vouga } = true'} | most_eq { all_rows ; subregion ; baixo vouga } = true | for the subregion records of all rows , most of them fuzzily match to baixo vouga . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'subregion_3': 3, 'baixo vouga_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'subregion_3': 'subregion', 'baixo vouga_4': 'baixo vouga'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'subregion_3': [0], 'baixo vouga_4': [0]} | ['name', 'area ( km square )', 'pop', 'pop / area ( 1 / km square )', 'no p', 'no c / no t', 'subregion'] | [['águeda', '335.3', '47729', '148', '20', '1', 'baixo vouga'], ['albergaria - a - velha', '155.4', '25497', '164', '8', '0', 'baixo vouga'], ['anadia', '216.6', '31671', '146', '15', '1', 'baixo vouga'], ['arouca', '329.1', '24019', '73', '20', '0', 'entre douro e vouga'], ['aveiro', '199.9', '73626', '368', '14', '1', 'baixo vouga'], ['castelo de paiva', '115.0', '17089', '149', '9', '0 / 2', 'tmega'], ['espinho', '21.1', '31703', '1503', '5', '1 / 1', 'grande porto'], ['estarreja', '108.4', '28279', '261', '7', '1 / 3', 'baixo vouga'], ['ílhavo', '73.5', '39247', '534', '4', '2', 'baixo vouga'], ['mealhada', '110.7', '20496', '194', '8', '1', 'baixo vouga'], ['murtosa', '73.3', '9657', '132', '4', '0 / 1', 'baixo vouga'], ['oliveira de azeméis', '163.5', '71243', '436', '19', '1 / 9', 'entre douro e vouga'], ['oliveira do bairro', '87.3', '22365', '256', '6', '1', 'baixo vouga'], ['ovar', '147.4', '56715', '385', '8', '2 / 3', 'baixo vouga'], ['santa maria da feira', '215.1', '142295', '662', '31', '3 / 13', 'entre douro e vouga'], ['são joão da madeira', '7.9', '21538', '2726', '1', '1 / 0', 'entre douro e vouga'], ['sever do vouga', '129.6', '12940', '100', '9', '0', 'baixo vouga'], ['vagos', '169.9', '23205', '137', '11', '0 / 2', 'baixo vouga'], ['vale de cambra', '146.5', '22864', '169', '9', '1', 'entre douro e vouga']] |
2007 - 08 oakland golden grizzlies men 's basketball team | https://en.wikipedia.org/wiki/2007%E2%80%9308_Oakland_Golden_Grizzlies_men%27s_basketball_team | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15748977-1.html.csv | comparative | keith benson weighs 10 pounds more than tim williams . | {'row_1': '13', 'row_2': '12', 'col': '4', 'col_other': '1', 'relation': 'diff', 'record_mentioned': 'no', 'diff_result': {'diff_value': '10', 'bigger': 'row1'}} | {'func': 'eq', 'args': [{'func': 'diff', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'name', 'keith benson'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose name record fuzzily matches to keith benson .', 'tostr': 'filter_eq { all_rows ; name ; keith benson }'}, 'weight'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; name ; keith benson } ; weight }', 'tointer': 'select the rows whose name record fuzzily matches to keith benson . take the weight record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'name', 'tim williams'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose name record fuzzily matches to tim williams .', 'tostr': 'filter_eq { all_rows ; name ; tim williams }'}, 'weight'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; name ; tim williams } ; weight }', 'tointer': 'select the rows whose name record fuzzily matches to tim williams . take the weight record of this row .'}], 'result': '10', 'ind': 4, 'tostr': 'diff { hop { filter_eq { all_rows ; name ; keith benson } ; weight } ; hop { filter_eq { all_rows ; name ; tim williams } ; weight } }'}, '10'], 'result': True, 'ind': 5, 'tostr': 'eq { diff { hop { filter_eq { all_rows ; name ; keith benson } ; weight } ; hop { filter_eq { all_rows ; name ; tim williams } ; weight } } ; 10 } = true', 'tointer': 'select the rows whose name record fuzzily matches to keith benson . take the weight record of this row . select the rows whose name record fuzzily matches to tim williams . take the weight record of this row . the first record is 10 larger than the second record .'} | eq { diff { hop { filter_eq { all_rows ; name ; keith benson } ; weight } ; hop { filter_eq { all_rows ; name ; tim williams } ; weight } } ; 10 } = true | select the rows whose name record fuzzily matches to keith benson . take the weight record of this row . select the rows whose name record fuzzily matches to tim williams . take the weight record of this row . the first record is 10 larger than the second record . | 6 | 6 | {'eq_5': 5, 'result_6': 6, 'diff_4': 4, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_7': 7, 'name_8': 8, 'keith benson_9': 9, 'weight_10': 10, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_11': 11, 'name_12': 12, 'tim williams_13': 13, 'weight_14': 14, '10_15': 15} | {'eq_5': 'eq', 'result_6': 'true', 'diff_4': 'diff', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_7': 'all_rows', 'name_8': 'name', 'keith benson_9': 'keith benson', 'weight_10': 'weight', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_11': 'all_rows', 'name_12': 'name', 'tim williams_13': 'tim williams', 'weight_14': 'weight', '10_15': '10'} | {'eq_5': [6], 'result_6': [], 'diff_4': [5], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_7': [0], 'name_8': [0], 'keith benson_9': [0], 'weight_10': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_11': [1], 'name_12': [1], 'tim williams_13': [1], 'weight_14': [3], '10_15': [5]} | ['name', 'pos', 'height', 'weight', 'year', 'hometown ( previous school )'] | [['derick nelson', 'f', "6 ' 5", '226', 'jr', 'lansing , mi ( bridgton academy )'], ['peter bunn', 'g', "6 ' 1", '165', 'fr', 'lansing , mi ( lansing christian )'], ['will hudson', 'f', "6 ' 9", '220', 'fr', 'verona , wi ( middleton )'], ['b - jay walker', 'g', "5 ' 8", '149', 'so', 'lathrup village , mi ( shrine catholic )'], ['brandon cassise', 'g', "6 ' 3", '207', 'sr', "walled lake , mi ( st mary 's preparatory )"], ['shane lawal', 'c', "6 ' 10", '225', 'jr', 'southfield , mi ( lathrup )'], ['ricky bieszki', 'g', "6 ' 2", '186', 'jr', 'shelby township , mi ( notre dame preparatory )'], ['ray goodson', 'g', "6 ' 1", '195', 'fr', 'detroit , mi ( pershing )'], ['johnathon jones', 'g', "5 ' 11", '160', 'so', 'okemos , mi ( okemos )'], ['erik kangas', 'g', "6 ' 3", '210', 'jr', 'dewitt , mi ( dewitt )'], ['john kast', 'g', "6 ' 2", '190', 'fr - r', 'clarkston , mi ( clarkston )'], ['tim williams', 'g', "6 ' 2", '200', 'fr', 'pontiac , mi ( pontiac northern )'], ['keith benson', 'c', "6 ' 11", '210', 'fr - r', 'farmington hills , mi ( country day )'], ['patrick mccloskey', 'f', "6 ' 8", '229', 'sr', 'marshall , mi ( marshall )'], ['dan waterstradt', 'c', "6 ' 10", '240', 'jr', 'dearborn heights , mi ( rutgers )']] |
1996 grand national | https://en.wikipedia.org/wiki/1996_Grand_National | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-29562161-1.html.csv | comparative | the horse ' over the deel ' was younger than the horse ' captain dibble ' in the 1996 grand national . | {'row_1': '9', 'row_2': '11', 'col': '4', 'col_other': '2', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'name', 'over the deel'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose name record fuzzily matches to over the deel .', 'tostr': 'filter_eq { all_rows ; name ; over the deel }'}, 'age'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; name ; over the deel } ; age }', 'tointer': 'select the rows whose name record fuzzily matches to over the deel . take the age record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'name', 'captain dibble'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose name record fuzzily matches to captain dibble .', 'tostr': 'filter_eq { all_rows ; name ; captain dibble }'}, 'age'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; name ; captain dibble } ; age }', 'tointer': 'select the rows whose name record fuzzily matches to captain dibble . take the age record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; name ; over the deel } ; age } ; hop { filter_eq { all_rows ; name ; captain dibble } ; age } } = true', 'tointer': 'select the rows whose name record fuzzily matches to over the deel . take the age record of this row . select the rows whose name record fuzzily matches to captain dibble . take the age record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; name ; over the deel } ; age } ; hop { filter_eq { all_rows ; name ; captain dibble } ; age } } = true | select the rows whose name record fuzzily matches to over the deel . take the age record of this row . select the rows whose name record fuzzily matches to captain dibble . take the age 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, 'name_7': 7, 'over the deel_8': 8, 'age_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'name_11': 11, 'captain dibble_12': 12, 'age_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', 'name_7': 'name', 'over the deel_8': 'over the deel', 'age_9': 'age', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'name_11': 'name', 'captain dibble_12': 'captain dibble', 'age_13': 'age'} | {'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'name_7': [0], 'over the deel_8': [0], 'age_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'name_11': [1], 'captain dibble_12': [1], 'age_13': [3]} | ['position', 'name', 'jockey', 'age', 'weight ( st , lb )', 'starting price', 'distance'] | [['1st', 'rough quest', 'mick fitzgerald', '10', '10 - 07', '7 / 1 f', 'won by 1 ¼ lengths'], ['2nd', 'encore un peu ( fra )', 'david bridgwater', '9', '10 - 00', '14 / 1', '16 lengths'], ['3rd', 'superior finish', 'richard dunwoody', '10', '10 - 03', '9 / 1', 'short head'], ['4th', 'sir peter lely', 'mr chris bonner', '9', '10 - 00', '33 / 1', '¾ length'], ['5th', 'young hustler', 'chris maude', '9', '11 - 07', '8 / 1', '4 lengths'], ['6th', 'three brownies', 'paul carberry', '9', '10 - 00', '100 / 1', '14 lengths'], ['7th', 'life of a lord', 'charlie swan', '10', '11 - 06', '10 / 1', '13 lengths'], ['8th', 'antonin ( fra )', 'john burke', '8', '10 - 00', '28 / 1', '2 ½ lengths'], ['9th', 'over the deel', 'mr tim mccarthy', '10', '10 - 00', '33 / 1', '15 lengths'], ['10th', 'vicompt de valmont', 'philip hide', '11', '10 - 01', '22 / 1', '4 lengths'], ['11th', 'captain dibble', 'tom jenks', '11', '10 - 00', '40 / 1', '2 lengths'], ['12th', 'riverside boy', 'david walsh', '13', '10 - 00', '66 / 1', '14 lengths'], ['13th', 'over the stream', 'andrew thornton', '10', '10 - 00', '50 / 1', '14 lengths'], ['14th', 'greenhill raffles', 'martin foster', '10', '10 - 00', '100 / 1', '3 lengths'], ['15th', 'into the red', 'richard guest', '12', '10 - 00', '33 / 1', 'a distance'], ['16th', 'lusty light', 'warren marston', '10', '10 - 11', '14 / 1', 'a distance']] |
nick price | https://en.wikipedia.org/wiki/Nick_Price | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1132021-7.html.csv | count | nick price made less than 20 cuts in three of the pga tournaments he played in . | {'scope': 'all', 'criterion': 'less_than', 'value': '20', 'result': '3', 'col': '7', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'cuts made', '20'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose cuts made record is less than 20 .', 'tostr': 'filter_less { all_rows ; cuts made ; 20 }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_less { all_rows ; cuts made ; 20 } }', 'tointer': 'select the rows whose cuts made record is less than 20 . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_less { all_rows ; cuts made ; 20 } } ; 3 } = true', 'tointer': 'select the rows whose cuts made record is less than 20 . the number of such rows is 3 .'} | eq { count { filter_less { all_rows ; cuts made ; 20 } } ; 3 } = true | select the rows whose cuts made record is less than 20 . the number of such rows is 3 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_less_0': 0, 'all_rows_4': 4, 'cuts made_5': 5, '20_6': 6, '3_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_less_0': 'filter_less', 'all_rows_4': 'all_rows', 'cuts made_5': 'cuts made', '20_6': '20', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_less_0': [1], 'all_rows_4': [0], 'cuts made_5': [0], '20_6': [0], '3_7': [2]} | ['tournament', 'wins', 'top - 5', 'top - 10', 'top - 25', 'events', 'cuts made'] | [['masters tournament', '0', '1', '4', '11', '20', '13'], ['us open', '0', '3', '5', '12', '20', '15'], ['the open championship', '1', '3', '5', '8', '27', '20'], ['pga championship', '2', '5', '7', '10', '20', '16'], ['totals', '3', '12', '21', '41', '87', '64']] |
simon whitlock | https://en.wikipedia.org/wiki/Simon_Whitlock | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10254961-3.html.csv | count | simon whitlock played against phil taylor in 3 championships and was runner up all 3 times . | {'scope': 'all', 'criterion': 'equal', 'value': 'phil taylor', 'result': '3', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent in the final', 'phil taylor'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose opponent in the final record fuzzily matches to phil taylor .', 'tostr': 'filter_eq { all_rows ; opponent in the final ; phil taylor }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; opponent in the final ; phil taylor } }', 'tointer': 'select the rows whose opponent in the final record fuzzily matches to phil taylor . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; opponent in the final ; phil taylor } } ; 3 } = true', 'tointer': 'select the rows whose opponent in the final record fuzzily matches to phil taylor . the number of such rows is 3 .'} | eq { count { filter_eq { all_rows ; opponent in the final ; phil taylor } } ; 3 } = true | select the rows whose opponent in the final record fuzzily matches to phil taylor . 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, 'opponent in the final_5': 5, 'phil taylor_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', 'opponent in the final_5': 'opponent in the final', 'phil taylor_6': 'phil taylor', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'opponent in the final_5': [0], 'phil taylor_6': [0], '3_7': [2]} | ['outcome', 'year', 'championship', 'opponent in the final', 'score ( l ) = score in legs , ( s ) = score in sets'] | [['runner - up', '2010', 'world darts championship', 'phil taylor', '3 - 7 ( s )'], ['runner - up', '2012', 'premier league darts', 'phil taylor', '7 - 10 ( l )'], ['winner', '2012', 'european championship', 'wes newton', '11 - 5 ( l )'], ['runner - up', '2012', 'championship league darts', 'phil taylor', '4 - 6 ( l )'], ['runner - up', '2013', 'european championship', 'adrian lewis', '6 - 11 ( l )']] |
hiroshi izumi | https://en.wikipedia.org/wiki/Hiroshi_Izumi | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12149929-2.html.csv | count | three of the fights in hiroshi izumi 's mixed martial arts record took place in tokyo , japan . | {'scope': 'all', 'criterion': 'equal', 'value': 'tokyo , japan', 'result': '3', 'col': '7', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location', 'tokyo , japan'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose location record fuzzily matches to tokyo , japan .', 'tostr': 'filter_eq { all_rows ; location ; tokyo , japan }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; location ; tokyo , japan } }', 'tointer': 'select the rows whose location record fuzzily matches to tokyo , japan . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; location ; tokyo , japan } } ; 3 } = true', 'tointer': 'select the rows whose location record fuzzily matches to tokyo , japan . the number of such rows is 3 .'} | eq { count { filter_eq { all_rows ; location ; tokyo , japan } } ; 3 } = true | select the rows whose location record fuzzily matches to tokyo , japan . 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, 'location_5': 5, 'tokyo, japan_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', 'location_5': 'location', 'tokyo, japan_6': 'tokyo , japan', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'location_5': [0], 'tokyo, japan_6': [0], '3_7': [2]} | ['res', 'record', 'opponent', 'method', 'round', 'time', 'location'] | [['loss', '4 - 2', 'gegard mousasi', 'tko ( punches )', '1', '3:28', 'tokyo , japan'], ['win', '4 - 1', 'ikuhisa minowa', 'tko ( punches )', '3', '2:50', 'saitama , saitama , japan'], ['win', '3 - 1', 'james zikic', 'decision ( split )', '3', '5:00', 'tokyo , japan'], ['win', '2 - 1', 'chang seob lee', 'tko ( punches )', '1', '4:37', 'tokyo , japan'], ['win', '1 - 1', 'katsuyori shibata', 'decision ( unanimous )', '3', '5:00', 'saitama , saitama , japan'], ['loss', '0 - 1', 'antz nansen', 'tko ( punches )', '1', '2:56', 'saitama , saitama , japan']] |
vivian girls | https://en.wikipedia.org/wiki/Vivian_Girls | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18710512-3.html.csv | count | 3 of the singles included involvement from the record label wild world . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'wild world', 'result': '3', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'record label', 'wild world'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose record label record fuzzily matches to wild world .', 'tostr': 'filter_eq { all_rows ; record label ; wild world }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; record label ; wild world } }', 'tointer': 'select the rows whose record label record fuzzily matches to wild world . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; record label ; wild world } } ; 3 } = true', 'tointer': 'select the rows whose record label record fuzzily matches to wild world . the number of such rows is 3 .'} | eq { count { filter_eq { all_rows ; record label ; wild world } } ; 3 } = true | select the rows whose record label record fuzzily matches to wild world . 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, 'record label_5': 5, 'wild world_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', 'record label_5': 'record label', 'wild world_6': 'wild world', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'record label_5': [0], 'wild world_6': [0], '3_7': [2]} | ['date', 'single', 'backed with', 'record label', 'format', 'other details'] | [['2008', 'wild eyes', 'my baby wants me dead', 'plays with dolls / wild world', '7 single', '4000 copies'], ['2008', 'tell the world', 'i believe in nothing & damaged', 'woodsist', '7 single', '3000 copies'], ['2008', "i ca n't stay", 'blind spot', 'in the red', '7 single', '2000 copies'], ['2008', 'surfin away & second date', "girl do n't tell me ( wilson )", 'wild world', '7 single', '1000 copies'], ['2009', 'moped girls', 'death', 'for us', '7 single', '1500 copies'], ['2010', 'my love will follow me', "he 's gone ( the chantels cover )", 'wild world', '7 single', '2000 copies'], ['2011', 'i heard you say', "i wo n't be long", 'polyvinyl', '7 single', 'rsd 2000 copies']] |
2008 - 09 philadelphia 76ers season | https://en.wikipedia.org/wiki/2008%E2%80%9309_Philadelphia_76ers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17323042-6.html.csv | aggregation | during the 2008-09 philadelphia 76ers season , the total attendance at games held at the wachovia center was 89767 . | {'scope': 'subset', 'col': '7', 'type': 'sum', 'result': '89767', 'subset': {'col': '7', 'criterion': 'equal', 'value': 'wachovia center'}} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location attendance', 'wachovia center'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; location attendance ; wachovia center }', 'tointer': 'select the rows whose location attendance record fuzzily matches to wachovia center .'}, 'location attendance'], 'result': '89767', 'ind': 1, 'tostr': 'sum { filter_eq { all_rows ; location attendance ; wachovia center } ; location attendance }'}, '89767'], 'result': True, 'ind': 2, 'tostr': 'round_eq { sum { filter_eq { all_rows ; location attendance ; wachovia center } ; location attendance } ; 89767 } = true', 'tointer': 'select the rows whose location attendance record fuzzily matches to wachovia center . the sum of the location attendance record of these rows is 89767 .'} | round_eq { sum { filter_eq { all_rows ; location attendance ; wachovia center } ; location attendance } ; 89767 } = true | select the rows whose location attendance record fuzzily matches to wachovia center . the sum of the location attendance record of these rows is 89767 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'sum_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'location attendance_5': 5, 'wachovia center_6': 6, 'location attendance_7': 7, '89767_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', 'wachovia center_6': 'wachovia center', 'location attendance_7': 'location attendance', '89767_8': '89767'} | {'eq_2': [3], 'result_3': [], 'sum_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'location attendance_5': [0], 'wachovia center_6': [0], 'location attendance_7': [1], '89767_8': [2]} | ['game', 'date', 'team', 'score', 'high points', 'high assists', 'location attendance', 'record'] | [['18', 'december 2', 'chicago', 'w 103 - 95 ( ot )', 'andre miller ( 28 )', 'andre iguodala ( 5 )', 'united center 20485', '8 - 10'], ['19', 'december 3', 'la lakers', 'l 102 - 114 ( ot )', 'andre miller ( 26 )', 'andre miller , andre iguodala ( 5 )', 'wachovia center 19119', '8 - 11'], ['20', 'december 5', 'detroit', 'w 96 - 91 ( ot )', 'andre miller ( 19 )', 'andre iguodala ( 5 )', 'the palace of auburn hills 22076', '9 - 11'], ['21', 'december 6', 'new jersey', 'l 84 - 95 ( ot )', 'andre iguodala ( 20 )', 'andre miller ( 5 )', 'wachovia center 13096', '9 - 12'], ['22', 'december 10', 'cleveland', 'l 93 - 101 ( ot )', 'andre iguodala ( 27 )', 'andre miller ( 8 )', 'wachovia center 15550', '9 - 13'], ['23', 'december 12', 'cleveland', 'l 72 - 88 ( ot )', 'willie green ( 19 )', 'andre miller ( 7 )', 'quicken loans arena 20562', '9 - 14'], ['24', 'december 13', 'washington', 'w 104 - 89 ( ot )', 'elton brand ( 27 )', 'andre miller ( 12 )', 'wachovia center 15865', '10 - 14'], ['25', 'december 17', 'milwaukee', 'w 93 - 88 ( ot )', 'louis williams ( 25 )', 'andre iguodala ( 7 )', 'wachovia center 11538', '11 - 14'], ['26', 'december 19', 'washington', 'w 109 - 103 ( ot )', 'louis williams ( 26 )', 'andre miller ( 6 )', 'verizon center 18323', '12 - 14'], ['27', 'december 20', 'indiana', 'l 94 - 95 ( ot )', 'andre iguodala ( 26 )', 'andre miller ( 12 )', 'wachovia center 14599', '12 - 15'], ['28', 'december 23', 'boston', 'l 91 - 110 ( ot )', 'louis williams , marreese speights ( 16 )', 'louis williams , andre miller ( 8 )', 'td banknorth garden 18624', '12 - 16'], ['29', 'december 26', 'denver', 'l 101 - 105 ( ot )', 'andre iguodala ( 24 )', 'andre miller ( 8 )', 'pepsi center 19155', '12 - 17'], ['30', 'december 29', 'utah', 'l 95 - 112 ( ot )', 'andre iguodala , thaddeus young ( 17 )', 'andre miller ( 8 )', 'energysolutions arena 19911', '12 - 18'], ['31', 'december 31', 'la clippers', 'w 100 - 92 ( ot )', 'andre iguodala ( 28 )', 'andre miller ( 9 )', 'staples center 14021', '13 - 18']] |
kevin mirocha | https://en.wikipedia.org/wiki/Kevin_Mirocha | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-25369796-1.html.csv | aggregation | kevin mirocha participated in a total of 65 races during his career . | {'scope': 'all', 'col': '4', 'type': 'sum', 'result': '65', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'races'], 'result': '65', 'ind': 0, 'tostr': 'sum { all_rows ; races }'}, '65'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; races } ; 65 } = true', 'tointer': 'the sum of the races record of all rows is 65 .'} | round_eq { sum { all_rows ; races } ; 65 } = true | the sum of the races record of all rows is 65 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'races_4': 4, '65_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'races_4': 'races', '65_5': '65'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'races_4': [0], '65_5': [1]} | ['season', 'series', 'team', 'races', 'wins', 'poles', 'f / laps', 'podiums', 'points', 'position'] | [['2007', 'formula bmw adac', 'adac berlin - brandenburg', '18', '0', '0', '0', '1', '389', '8th'], ['2007', 'formula bmw world final', 'josef kaufmann racing', '1', '0', '0', '0', '0', 'n / a', '22nd'], ['2008', 'ats formel 3 cup', 'josef kaufmann racing', '18', '0', '0', '0', '4', '56', '6th'], ['2009', 'formula 3 euro series', 'hbr motorsport', '6', '0', '0', '0', '0', '0', '29th'], ['2010', 'formula renault 2.0 nec', 'sl formula racing', '8', '1', '0', '2', '3', '137', '9th'], ['2011', 'gp2 series', 'ocean racing technology', '14', '0', '0', '0', '0', '0', '22nd']] |
wbfj - fm | https://en.wikipedia.org/wiki/WBFJ-FM | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10711725-1.html.csv | unique | w267 am is the only call sign radio channel that uses an erp w of 33 . | {'scope': 'all', 'row': '2', 'col': '5', 'col_other': '1', 'criterion': 'equal', 'value': '33', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'erp w', '33'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose erp w record is equal to 33 .', 'tostr': 'filter_eq { all_rows ; erp w ; 33 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; erp w ; 33 } }', 'tointer': 'select the rows whose erp w record is equal to 33 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'erp w', '33'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose erp w record is equal to 33 .', 'tostr': 'filter_eq { all_rows ; erp w ; 33 }'}, 'call sign'], 'result': 'w267 am', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; erp w ; 33 } ; call sign }'}, 'w267 am'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; erp w ; 33 } ; call sign } ; w267 am }', 'tointer': 'the call sign record of this unqiue row is w267 am .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; erp w ; 33 } } ; eq { hop { filter_eq { all_rows ; erp w ; 33 } ; call sign } ; w267 am } } = true', 'tointer': 'select the rows whose erp w record is equal to 33 . there is only one such row in the table . the call sign record of this unqiue row is w267 am .'} | and { only { filter_eq { all_rows ; erp w ; 33 } } ; eq { hop { filter_eq { all_rows ; erp w ; 33 } ; call sign } ; w267 am } } = true | select the rows whose erp w record is equal to 33 . there is only one such row in the table . the call sign record of this unqiue row is w267 am . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'erp w_7': 7, '33_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'call sign_9': 9, 'w267 am_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'erp w_7': 'erp w', '33_8': '33', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'call sign_9': 'call sign', 'w267 am_10': 'w267 am'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'erp w_7': [0], '33_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'call sign_9': [2], 'w267 am_10': [3]} | ['call sign', 'frequency mhz', 'city of license', 'facility id', 'erp w', 'height m ( ft )', 'class', 'fcc info'] | [['w267ag', '101.3', 'salisbury , north carolina', '67830', '38', '-', 'd', 'fcc'], ['w267 am', '101.3', 'mocksville , north carolina', '87027', '33', '-', 'd', 'fcc'], ['w267an', '101.3', 'wilkesboro , north carolina', '87078', '10', '-', 'd', 'fcc'], ['w274al', '102.7', 'high point , north carolina', '87044', '10', '-', 'd', 'fcc'], ['w276ba', '103.1', 'fancy gap , virginia', '87029', '10', '-', 'd', 'fcc'], ['w278 am', '103.5', 'sedalia , north carolina', '87023', '10', '-', 'd', 'fcc'], ['w285dj', '104.9', 'mount airy , north carolina', '67829', '10', '-', 'd', 'fcc']] |
1928 vfl season | https://en.wikipedia.org/wiki/1928_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10766119-6.html.csv | aggregation | 114870 people attended vfl games that were played on may 26 , 1928 . | {'scope': 'all', 'col': '6', 'type': 'sum', 'result': '114870', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'crowd'], 'result': '114870', 'ind': 0, 'tostr': 'sum { all_rows ; crowd }'}, '114870'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; crowd } ; 114870 } = true', 'tointer': 'the sum of the crowd record of all rows is 114870 .'} | round_eq { sum { all_rows ; crowd } ; 114870 } = true | the sum of the crowd record of all rows is 114870 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'crowd_4': 4, '114870_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'crowd_4': 'crowd', '114870_5': '114870'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'crowd_4': [0], '114870_5': [1]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['melbourne', '13.8 ( 86 )', 'st kilda', '11.8 ( 74 )', 'mcg', '16870', '26 may 1928'], ['footscray', '17.19 ( 121 )', 'hawthorn', '7.3 ( 45 )', 'western oval', '14000', '26 may 1928'], ['essendon', '10.8 ( 68 )', 'richmond', '7.19 ( 61 )', 'windy hill', '20000', '26 may 1928'], ['collingwood', '12.12 ( 84 )', 'north melbourne', '6.9 ( 45 )', 'victoria park', '25000', '26 may 1928'], ['geelong', '19.8 ( 122 )', 'fitzroy', '2.27 ( 39 )', 'corio oval', '11000', '26 may 1928'], ['south melbourne', '12.10 ( 82 )', 'carlton', '12.13 ( 85 )', 'lake oval', '28000', '26 may 1928']] |
fox television stations | https://en.wikipedia.org/wiki/Fox_Television_Stations | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1353096-2.html.csv | unique | wcvb - tv 1 is the only fox television station that is an abc affiliate owned by hearst television . | {'scope': 'all', 'row': '6', 'col': '5', 'col_other': '2', 'criterion': 'equal', 'value': 'abc affiliate owned by hearst television', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'current status', 'abc affiliate owned by hearst television'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose current status record fuzzily matches to abc affiliate owned by hearst television .', 'tostr': 'filter_eq { all_rows ; current status ; abc affiliate owned by hearst television }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; current status ; abc affiliate owned by hearst television } }', 'tointer': 'select the rows whose current status record fuzzily matches to abc affiliate owned by hearst television . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'current status', 'abc affiliate owned by hearst television'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose current status record fuzzily matches to abc affiliate owned by hearst television .', 'tostr': 'filter_eq { all_rows ; current status ; abc affiliate owned by hearst television }'}, 'station'], 'result': 'wcvb - tv 1', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; current status ; abc affiliate owned by hearst television } ; station }'}, 'wcvb - tv 1'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; current status ; abc affiliate owned by hearst television } ; station } ; wcvb - tv 1 }', 'tointer': 'the station record of this unqiue row is wcvb - tv 1 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; current status ; abc affiliate owned by hearst television } } ; eq { hop { filter_eq { all_rows ; current status ; abc affiliate owned by hearst television } ; station } ; wcvb - tv 1 } } = true', 'tointer': 'select the rows whose current status record fuzzily matches to abc affiliate owned by hearst television . there is only one such row in the table . the station record of this unqiue row is wcvb - tv 1 .'} | and { only { filter_eq { all_rows ; current status ; abc affiliate owned by hearst television } } ; eq { hop { filter_eq { all_rows ; current status ; abc affiliate owned by hearst television } ; station } ; wcvb - tv 1 } } = true | select the rows whose current status record fuzzily matches to abc affiliate owned by hearst television . there is only one such row in the table . the station record of this unqiue row is wcvb - tv 1 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'current status_7': 7, 'abc affiliate owned by hearst television_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'station_9': 9, 'wcvb - tv 1_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'current status_7': 'current status', 'abc affiliate owned by hearst television_8': 'abc affiliate owned by hearst television', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'station_9': 'station', 'wcvb - tv 1_10': 'wcvb - tv 1'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'current status_7': [0], 'abc affiliate owned by hearst television_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'station_9': [2], 'wcvb - tv 1_10': [3]} | ['city of license / market', 'station', 'channel tv ( dt )', 'years owned', 'current status'] | [['birmingham - tuscaloosa - anniston', 'wbrc - tv', '6 ( 50 )', '1995 - 2008', 'fox affiliate owned by raycom media'], ['san francisco - oakland - san jose', 'kbhk - tv ¤ ¤ ( now kbcw )', '44 ( 45 )', '2001 - 2002', 'cw affiliate owned by cbs corporation'], ['denver', 'kdvr', '31 ( 32 )', '1995 - 2008', 'fox affiliate owned by local tv'], ['fort collins , colorado', 'kfct ( satellite of kdvr )', '22 ( 21 )', '1995 - 2008', 'fox affiliate owned by local tv'], ['atlanta', 'watl - tv', '36 ( 25 )', '1993 - 1995', 'mynetworktv affiliate owned by gannett company'], ['boston', 'wcvb - tv 1', '5 ( 20 )', '1986', 'abc affiliate owned by hearst television'], ['kansas city , missouri', 'wdaf - tv + +', '4 ( 34 )', '1997 - 2008', 'fox affiliate owned by local tv'], ['saint louis', 'ktvi + +', '2 ( 43 )', '1997 - 2008', 'fox affiliate owned by local tv'], ['high point - greensboro - winston - salem', 'wghp', '8 ( 35 )', '1995 - 2008', 'fox affiliate owned by local tv'], ['cleveland - akron', 'wjw - tv + +', '8 ( 8 )', '1997 - 2008', 'fox affiliate owned by local tv'], ['portland , oregon', 'kptv ¤ ¤', '12 ( 12 )', '2001 - 2002', 'fox affiliate owned by meredith corporation'], ['dallas - fort worth', 'kdaf', '33 ( 32 )', '1986 - 1995', 'cw affiliate owned by tribune broadcasting'], ['san antonio', 'kmol - tv ¤ ¤ ( now woai - tv )', '4 ( 48 )', '2001', 'nbc affiliate owned by sinclair broadcast group'], ['salt lake city', 'kstu', '13 ( 28 )', '1990 - 2008', 'fox affiliate owned by local tv'], ['salt lake city', 'ktvx ¤ ¤', '4 ( 40 )', '2001', 'abc affiliate owned by nexstar broadcasting group']] |
1973 uefa cup final | https://en.wikipedia.org/wiki/1973_UEFA_Cup_Final | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15755354-2.html.csv | majority | in most first leg games one team scored 0 goals . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': '0', 'subset': None} | {'func': 'most_eq', 'args': ['all_rows', 'first leg', '0'], 'result': True, 'ind': 0, 'tointer': 'for the first leg records of all rows , most of them are equal to 0 .', 'tostr': 'most_eq { all_rows ; first leg ; 0 } = true'} | most_eq { all_rows ; first leg ; 0 } = true | for the first leg records of all rows , most of them are equal to 0 . | 1 | 1 | {'most_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'first leg_3': 3, '0_4': 4} | {'most_eq_0': 'most_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'first leg_3': 'first leg', '0_4': '0'} | {'most_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'first leg_3': [0], '0_4': [0]} | ['round', 'opposition', 'first leg', 'second leg', 'aggregate score'] | [['1st', 'aberdeen', '3 - 2 ( a )', '6 - 3 ( h )', '9 - 5'], ['2nd', 'hvidovre', '3 - 0 ( h )', '3 - 1 ( a )', '6 - 1'], ['3rd', 'fc köln', '0 - 0 ( a )', '5 - 0 ( h )', '5 - 0'], ['quarter - final', 'kaiserslautern', '2 - 1 ( a )', '7 - 1 ( h )', '9 - 2'], ['semi - final', 'twente', '3 - 0 ( h )', '2 - 1 ( a )', '5 - 1']] |
toronto and nipissing railway | https://en.wikipedia.org/wiki/Toronto_and_Nipissing_Railway | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15339242-1.html.csv | unique | engine number 11 was the only engine built in 1872 . | {'scope': 'all', 'row': '11', 'col': '4', 'col_other': '1', 'criterion': 'equal', 'value': '1872', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'date', '1872'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose date record is equal to 1872 .', 'tostr': 'filter_eq { all_rows ; date ; 1872 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; date ; 1872 } }', 'tointer': 'select the rows whose date record is equal to 1872 . there is only one such row in the table .'}, {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'date', '1872'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose date record is equal to 1872 .', 'tostr': 'filter_eq { all_rows ; date ; 1872 }'}, 'number'], 'result': '11', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; date ; 1872 } ; number }'}, '11'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; date ; 1872 } ; number } ; 11 }', 'tointer': 'the number record of this unqiue row is 11 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; date ; 1872 } } ; eq { hop { filter_eq { all_rows ; date ; 1872 } ; number } ; 11 } } = true', 'tointer': 'select the rows whose date record is equal to 1872 . there is only one such row in the table . the number record of this unqiue row is 11 .'} | and { only { filter_eq { all_rows ; date ; 1872 } } ; eq { hop { filter_eq { all_rows ; date ; 1872 } ; number } ; 11 } } = true | select the rows whose date record is equal to 1872 . there is only one such row in the table . the number record of this unqiue row is 11 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'date_7': 7, '1872_8': 8, 'eq_3': 3, 'num_hop_2': 2, 'number_9': 9, '11_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'date_7': 'date', '1872_8': '1872', 'eq_3': 'eq', 'num_hop_2': 'num_hop', 'number_9': 'number', '11_10': '11'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'date_7': [0], '1872_8': [0], 'eq_3': [4], 'num_hop_2': [3], 'number_9': [2], '11_10': [3]} | ['number', 'builder', 'type', 'date', 'works number'] | [['1', 'avonside engine company', '4 - 4 - 0', 'september 1870', '808'], ['2', 'canadian engine & machinery company', '4 - 4 - 0', 'november 1870', '83'], ['3', 'canadian engine & machinery company', '4 - 4 - 0', 'december 1870', '84'], ['4', 'canadian engine & machinery company', '4 - 4 - 0', 'early 1871', '85'], ['5', 'canadian engine & machinery company', '4 - 4 - 0', 'march 1871', '86'], ['6', 'canadian engine & machinery company', '4 - 4 - 0', 'may 1871', '87'], ['7', 'canadian engine & machinery company', '4 - 4 - 0', 'may 1871', '88'], ['8', 'avonside engine company', '4 - 6 - 0', 'december 1871', '867'], ['9', 'avonside engine company', '0 - 6 - 6 - 0 fairlie', 'december 1871', '864 & 865'], ['10', 'avonside engine company', '4 - 6 - 0', 'early 1873', 'uncertain but probably one of 931 - 934'], ['11', 'avonside engine company', '4 - 6 - 0', '1872', 'uncertain but probably one of 935 - 939'], ['12', 'avonside engine company', '4 - 6 - 0', 'early 1873', 'uncertain but probably one of 935 - 939']] |
2007 - 08 san antonio spurs season | https://en.wikipedia.org/wiki/2007%E2%80%9308_San_Antonio_Spurs_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11963601-10.html.csv | majority | parker was the high point scorer for the majority of the san antonio spurs games . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': 'parker', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'high points', 'parker'], 'result': True, 'ind': 0, 'tointer': 'for the high points records of all rows , most of them fuzzily match to parker .', 'tostr': 'most_eq { all_rows ; high points ; parker } = true'} | most_eq { all_rows ; high points ; parker } = true | for the high points records of all rows , most of them fuzzily match to parker . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'high points_3': 3, 'parker_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'high points_3': 'high points', 'parker_4': 'parker'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'high points_3': [0], 'parker_4': [0]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'series'] | [['1', 'april 19', 'phoenix', '117 - 115 ( 2ot )', 'duncan ( 40 )', 'duncan ( 15 )', 'duncan , ginóbili , parker ( 5 )', 'at & t center 18797', '1 - 0'], ['2', 'april 22', 'phoenix', '102 - 96', 'parker ( 32 )', 'duncan ( 17 )', 'parker ( 7 )', 'at & t center 18797', '2 - 0'], ['3', 'april 25', 'phoenix', '115 - 99', 'parker ( 41 )', 'duncan ( 10 )', 'parker ( 12 )', 'us airways center 18422', '3 - 0'], ['4', 'april 27', 'phoenix', '86 - 105', 'parker ( 18 )', 'duncan ( 10 )', 'parker ( 3 )', 'us airways center 18422', '3 - 1'], ['5', 'april 29', 'phoenix', '92 - 87', 'parker ( 31 )', 'duncan ( 17 )', 'parker ( 8 )', 'at & t center 18797', '4 - 1']] |
2009 masters tournament | https://en.wikipedia.org/wiki/2009_Masters_Tournament | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18812411-8.html.csv | aggregation | in the 2009 masters tournament , united states players averaged a total score of 279.4 . | {'scope': 'subset', 'col': '4', 'type': 'average', 'result': '279.4', 'subset': {'col': '3', 'criterion': 'equal', 'value': 'united states'}} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'united states'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; country ; united states }', 'tointer': 'select the rows whose country record fuzzily matches to united states .'}, 'score'], 'result': '279.4', 'ind': 1, 'tostr': 'avg { filter_eq { all_rows ; country ; united states } ; score }'}, '279.4'], 'result': True, 'ind': 2, 'tostr': 'round_eq { avg { filter_eq { all_rows ; country ; united states } ; score } ; 279.4 } = true', 'tointer': 'select the rows whose country record fuzzily matches to united states . the average of the score record of these rows is 279.4 .'} | round_eq { avg { filter_eq { all_rows ; country ; united states } ; score } ; 279.4 } = true | select the rows whose country record fuzzily matches to united states . the average of the score record of these rows is 279.4 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'avg_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'country_5': 5, 'united states_6': 6, 'score_7': 7, '279.4_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'avg_1': 'avg', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'country_5': 'country', 'united states_6': 'united states', 'score_7': 'score', '279.4_8': '279.4'} | {'eq_2': [3], 'result_3': [], 'avg_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'country_5': [0], 'united states_6': [0], 'score_7': [1], '279.4_8': [2]} | ['place', 'player', 'country', 'score', 'to par', 'money'] | [['t1', 'ángel cabrera', 'argentina', '68 + 68 + 69 + 71 = 276', '- 12', 'playoff'], ['t1', 'chad campbell', 'united states', '65 + 70 + 72 + 69 = 276', '- 12', 'playoff'], ['t1', 'kenny perry', 'united states', '68 + 67 + 70 + 71 = 276', '- 12', 'playoff'], ['4', 'shingo katayama', 'japan', '67 + 73 + 70 + 68 = 278', '- 10', '360000'], ['5', 'phil mickelson', 'united states', '73 + 68 + 71 + 67 = 279', '- 9', '300000'], ['t6', 'john merrick', 'united states', '68 + 72 + 74 + 66 = 280', '- 8', '242813'], ['t6', 'steve flesch', 'united states', '71 + 74 + 68 + 67 = 280', '- 8', '242813'], ['t6', 'tiger woods', 'united states', '70 + 72 + 70 + 68 = 280', '- 8', '242813'], ['t6', 'steve stricker', 'united states', '72 + 69 + 68 + 71 = 280', '- 8', '242813'], ['t10', 'hunter mahan', 'united states', '66 + 75 + 71 + 69 = 281', '- 7', '187500'], ['t10', "sean o'hair", 'united states', '68 + 76 + 68 + 69 = 281', '- 7', '187500'], ['t10', 'jim furyk', 'united states', '66 + 74 + 68 + 73 = 281', '- 7', '187500']] |
12th united states congress | https://en.wikipedia.org/wiki/12th_United_States_Congress | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-225095-4.html.csv | unique | thomas blount was the only vacator who died in office . | {'scope': 'all', 'row': '3', 'col': '3', 'col_other': '2', 'criterion': 'fuzzily_match', 'value': 'died', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'reason for change', 'died'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose reason for change record fuzzily matches to died .', 'tostr': 'filter_eq { all_rows ; reason for change ; died }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; reason for change ; died } }', 'tointer': 'select the rows whose reason for change record fuzzily matches to died . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'reason for change', 'died'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose reason for change record fuzzily matches to died .', 'tostr': 'filter_eq { all_rows ; reason for change ; died }'}, 'vacator'], 'result': 'thomas blount ( dr )', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; reason for change ; died } ; vacator }'}, 'thomas blount ( dr )'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; reason for change ; died } ; vacator } ; thomas blount ( dr ) }', 'tointer': 'the vacator record of this unqiue row is thomas blount ( dr ) .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; reason for change ; died } } ; eq { hop { filter_eq { all_rows ; reason for change ; died } ; vacator } ; thomas blount ( dr ) } } = true', 'tointer': 'select the rows whose reason for change record fuzzily matches to died . there is only one such row in the table . the vacator record of this unqiue row is thomas blount ( dr ) .'} | and { only { filter_eq { all_rows ; reason for change ; died } } ; eq { hop { filter_eq { all_rows ; reason for change ; died } ; vacator } ; thomas blount ( dr ) } } = true | select the rows whose reason for change record fuzzily matches to died . there is only one such row in the table . the vacator record of this unqiue row is thomas blount ( dr ) . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'reason for change_7': 7, 'died_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'vacator_9': 9, 'thomas blount (dr)_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'reason for change_7': 'reason for change', 'died_8': 'died', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'vacator_9': 'vacator', 'thomas blount (dr)_10': 'thomas blount ( dr )'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'reason for change_7': [0], 'died_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'vacator_9': [2], 'thomas blount (dr)_10': [3]} | ['district', 'vacator', 'reason for change', 'successor', 'date successor seated'] | [['massachusetts 4th', 'joseph b varnum ( dr )', 'resigned june 29 , 1811 to become us senator', 'william m richardson ( dr )', 'seated november 4 , 1811'], ['virginia 8th', 'john hungerford ( dr )', 'lost contested election november 29 , 1811', 'john taliaferro ( dr )', 'seated november 29 , 1811'], ['north carolina 3rd', 'thomas blount ( dr )', 'died february 7 , 1812', 'william kennedy ( dr )', 'seated january 30 , 1813'], ['new york 6th', 'robert le roy livingston ( f )', 'resigned may 6 , 1812', 'thomas p grosvenor ( f )', 'seated january 29 , 1813'], ['missouri territory', 'territory delegate seat established', 'territory delegate seat established', 'edward hempstead', 'seated november 9 , 1812'], ['illinois territory', 'territory delegate seat established', 'territory delegate seat established', 'shadrach bond', 'seated december 3 , 1812']] |
list of tallest buildings in the halifax regional municipality | https://en.wikipedia.org/wiki/List_of_tallest_buildings_in_the_Halifax_Regional_Municipality | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11339545-1.html.csv | comparative | in the list of tallest buildings in the halifax regional municipality duke tower is taller than summer gardens . | {'row_1': '11', 'row_2': '15', 'col': '3', 'col_other': '2', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'building', 'duke tower ( office )'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose building record fuzzily matches to duke tower ( office ) .', 'tostr': 'filter_eq { all_rows ; building ; duke tower ( office ) }'}, 'height'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; building ; duke tower ( office ) } ; height }', 'tointer': 'select the rows whose building record fuzzily matches to duke tower ( office ) . take the height record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'building', 'summer gardens ( residential )'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose building record fuzzily matches to summer gardens ( residential ) .', 'tostr': 'filter_eq { all_rows ; building ; summer gardens ( residential ) }'}, 'height'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; building ; summer gardens ( residential ) } ; height }', 'tointer': 'select the rows whose building record fuzzily matches to summer gardens ( residential ) . take the height record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; building ; duke tower ( office ) } ; height } ; hop { filter_eq { all_rows ; building ; summer gardens ( residential ) } ; height } } = true', 'tointer': 'select the rows whose building record fuzzily matches to duke tower ( office ) . take the height record of this row . select the rows whose building record fuzzily matches to summer gardens ( residential ) . take the height record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; building ; duke tower ( office ) } ; height } ; hop { filter_eq { all_rows ; building ; summer gardens ( residential ) } ; height } } = true | select the rows whose building record fuzzily matches to duke tower ( office ) . take the height record of this row . select the rows whose building record fuzzily matches to summer gardens ( residential ) . take the height 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, 'building_7': 7, 'duke tower (office)_8': 8, 'height_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'building_11': 11, 'summer gardens (residential)_12': 12, 'height_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', 'building_7': 'building', 'duke tower (office)_8': 'duke tower ( office )', 'height_9': 'height', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'building_11': 'building', 'summer gardens (residential)_12': 'summer gardens ( residential )', 'height_13': 'height'} | {'greater_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'building_7': [0], 'duke tower (office)_8': [0], 'height_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'building_11': [1], 'summer gardens (residential)_12': [1], 'height_13': [3]} | ['rank', 'building', 'height', 'floors', 'completed'] | [['1', 'fenwick tower ( residential )', '98 m ( 322ft )', '32', '1971'], ['2', "purdy 's wharf tower 2 ( office )", '88 m ( 289ft )', '22', '1990'], ['3', '1801 hollis street ( office )', '87 m ( 285ft )', '22', '1985'], ['4', 'barrington tower ( office )', '84 m ( 276ft )', '20', '1975'], ['5', 'cogswell tower ( office )', '79 m ( 259ft )', '20', '1975'], ['6', 'maritime centre ( office )', '78 m ( 256ft )', '21', '1974'], ['7', 'queen square ( office )', '75 m ( 246ft )', '19', '1975'], ['8', "purdy 's wharf tower 1 ( office )", '74 m ( 243ft )', '18', '1985'], ['9', 'bank of montreal building ( office )', '73 m ( 240ft )', '18', '1971'], ['10', 'td tower ( office )', '73 m ( 240ft )', '18', '1974'], ['11', 'duke tower ( office )', '71 m ( 233ft )', '16', '1970'], ['12', 'founders square ( office )', '71 m ( 233ft )', '15', '1970'], ['13', 'tupper building ( educational )', '70 m ( 233ft )', '16', '1967'], ['14', 'park victoria ( residential )', '70 m ( 233ft )', '21', '1969'], ['15', 'summer gardens ( residential )', '70 m ( 233ft )', '21', '1990'], ['16', 'loyola residence tower ( residential )', '67 m ( 220ft )', '22', '1971'], ['17', 'metropolitan place ( office )', '67 m ( 218ft )', '16', '1987'], ['18', 'bank of commerce ( office )', '66 m ( 217ft )', '16', '1977'], ['19', 'the trillium ( residential )', '65 m ( 213ft )', '19', '2011']] |
united states house of representatives elections , 1966 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1966 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1341843-15.html.csv | majority | the majority of incumbent representatives in indiana in 1966 were democratic . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'democratic', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'party', 'democratic'], 'result': True, 'ind': 0, 'tointer': 'for the party records of all rows , most of them fuzzily match to democratic .', 'tostr': 'most_eq { all_rows ; party ; democratic } = true'} | most_eq { all_rows ; party ; democratic } = true | for the party records of all rows , most of them fuzzily match to democratic . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'party_3': 3, 'democratic_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'party_3': 'party', 'democratic_4': 'democratic'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'party_3': [0], 'democratic_4': [0]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['indiana 1', 'ray j madden', 'democratic', '1942', 're - elected', 'ray j madden ( d ) 58.3 % albert harrigan ( r ) 41.7 %'], ['indiana 3', 'john brademas', 'democratic', '1958', 're - elected', 'john brademas ( d ) 55.8 % robert a ehlers ( r ) 44.2 %'], ['indiana 4', 'e ross adair', 'republican', '1950', 're - elected', 'e ross adair ( r ) 63.5 % j byron hayes ( d ) 36.5 %'], ['indiana 5', 'j edward roush', 'democratic', '1958', 're - elected', 'j edward roush ( d ) 51.1 % kenneth bowman ( r ) 48.9 %'], ['indiana 7', 'none ( district created )', 'none ( district created )', 'none ( district created )', 'new seat republican gain', 'john t myers ( r ) 54.3 % elden c tipton ( d ) 45.7 %']] |
midwest athletic conference ( ihsaa ) | https://en.wikipedia.org/wiki/Midwest_Athletic_Conference_%28IHSAA%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12393831-2.html.csv | count | in the midwest athletic conference , for the teams that joined in the 1970s , there were two that joined the hoosier heartland . | {'scope': 'subset', 'criterion': 'equal', 'value': 'hoosier heartland', 'result': '2', 'col': '7', 'subset': {'col': '6', 'criterion': 'greater_than_eq', 'value': '1970'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_greater_eq', 'args': ['all_rows', 'year left', '1970'], 'result': None, 'ind': 0, 'tostr': 'filter_greater_eq { all_rows ; year left ; 1970 }', 'tointer': 'select the rows whose year left record is greater than or equal to 1970 .'}, 'conference joined', 'hoosier heartland'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose year left record is greater than or equal to 1970 . among these rows , select the rows whose conference joined record fuzzily matches to hoosier heartland .', 'tostr': 'filter_eq { filter_greater_eq { all_rows ; year left ; 1970 } ; conference joined ; hoosier heartland }'}], 'result': '2', 'ind': 2, 'tostr': 'count { filter_eq { filter_greater_eq { all_rows ; year left ; 1970 } ; conference joined ; hoosier heartland } }', 'tointer': 'select the rows whose year left record is greater than or equal to 1970 . among these rows , select the rows whose conference joined record fuzzily matches to hoosier heartland . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_eq { filter_greater_eq { all_rows ; year left ; 1970 } ; conference joined ; hoosier heartland } } ; 2 } = true', 'tointer': 'select the rows whose year left record is greater than or equal to 1970 . among these rows , select the rows whose conference joined record fuzzily matches to hoosier heartland . the number of such rows is 2 .'} | eq { count { filter_eq { filter_greater_eq { all_rows ; year left ; 1970 } ; conference joined ; hoosier heartland } } ; 2 } = true | select the rows whose year left record is greater than or equal to 1970 . among these rows , select the rows whose conference joined record fuzzily matches to hoosier heartland . the number of such rows is 2 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_str_eq_1': 1, 'filter_greater_eq_0': 0, 'all_rows_5': 5, 'year left_6': 6, '1970_7': 7, 'conference joined_8': 8, 'hoosier heartland_9': 9, '2_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_str_eq_1': 'filter_str_eq', 'filter_greater_eq_0': 'filter_greater_eq', 'all_rows_5': 'all_rows', 'year left_6': 'year left', '1970_7': '1970', 'conference joined_8': 'conference joined', 'hoosier heartland_9': 'hoosier heartland', '2_10': '2'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_str_eq_1': [2], 'filter_greater_eq_0': [1], 'all_rows_5': [0], 'year left_6': [0], '1970_7': [0], 'conference joined_8': [1], 'hoosier heartland_9': [1], '2_10': [3]} | ['school', 'location', 'mascot', 'county', 'year joined', 'year left', 'conference joined'] | [['brook', 'brook', 'aces', '56 newton', '1955', '1966', 'none ( consolidated into south newton )'], ['brookston', 'brookston', 'bombers', '91 white', '1955', '1965', 'none ( consolidated into frontier )'], ['camden', 'camden', 'red devils', '08 carroll', '1955', '1965', 'none ( consolidated into delphi'], ['fowler', 'fowler', 'bulldogs', '04 benton', '1955', '1968', 'none ( consolidated into benton central )'], ['kentland', 'kentland', 'blue devils', '56 newton', '1955', '1966', 'none ( consolidated into south newton )'], ['monon', 'monon', 'railroaders', '91 white', '1955', '1963', 'none ( consolidated into north white )'], ['royal center', 'royal center', 'bulldogs', '09 cass', '1955', '1963', 'none ( consolidated into pioneer )'], ['wolcott', 'wolcott', 'wildcats', '91 white', '1955', '1971', 'none ( consolidated into tri - county )'], ['francesville', 'francesville', 'zebras', '66 pulaski', '1957', '1965', 'none ( consolidated into west central )'], ['klondike', 'west lafayette', 'nuggets', '79 tippecanoe', '1961', '1970', 'none ( consolidated into harrison )'], ['demotte', 'demotte', 'indians', '37 jasper', '1967', '1970', 'none ( consolidated into kankakee valley )'], ['north newton', 'morocco', 'spartans', '56 newton', '1967', '1975', 'northwest hoosier'], ['west central', 'medaryville', 'trojans', '66 pulaski', '1967', '1975', 'northwest hoosier'], ['kankakee valley', 'wheatfield', 'kougars', '37 jasper', '1970', '1972', 'northwest hoosier'], ['carroll', 'flora', 'cougars', '08 carroll', '1977', '1992', 'hoosier heartland'], ['rossville', 'rossville', 'hornets', '12 clinton', '1977', '1989', 'hoosier heartland']] |
rowing at the 2008 summer olympics - men 's lightweight double sculls | https://en.wikipedia.org/wiki/Rowing_at_the_2008_Summer_Olympics_%E2%80%93_Men%27s_lightweight_double_sculls | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18662685-8.html.csv | comparative | portugal ranked higher than cuba in rowing in the 2008 olympics . | {'row_1': '1', 'row_2': '2', 'col': '1', 'col_other': '3', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'portugal'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose country record fuzzily matches to portugal .', 'tostr': 'filter_eq { all_rows ; country ; portugal }'}, 'rank'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; country ; portugal } ; rank }', 'tointer': 'select the rows whose country record fuzzily matches to portugal . take the rank record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'cuba'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose country record fuzzily matches to cuba .', 'tostr': 'filter_eq { all_rows ; country ; cuba }'}, 'rank'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; country ; cuba } ; rank }', 'tointer': 'select the rows whose country record fuzzily matches to cuba . take the rank record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; country ; portugal } ; rank } ; hop { filter_eq { all_rows ; country ; cuba } ; rank } } = true', 'tointer': 'select the rows whose country record fuzzily matches to portugal . take the rank record of this row . select the rows whose country record fuzzily matches to cuba . take the rank record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; country ; portugal } ; rank } ; hop { filter_eq { all_rows ; country ; cuba } ; rank } } = true | select the rows whose country record fuzzily matches to portugal . take the rank record of this row . select the rows whose country record fuzzily matches to cuba . take the rank 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, 'country_7': 7, 'portugal_8': 8, 'rank_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'country_11': 11, 'cuba_12': 12, 'rank_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', 'country_7': 'country', 'portugal_8': 'portugal', 'rank_9': 'rank', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'country_11': 'country', 'cuba_12': 'cuba', 'rank_13': 'rank'} | {'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'country_7': [0], 'portugal_8': [0], 'rank_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'country_11': [1], 'cuba_12': [1], 'rank_13': [3]} | ['rank', 'rowers', 'country', 'time', 'notes'] | [['1', 'pedro fraga , nuno mendes', 'portugal', '6:39.07', 'sa / b'], ['2', 'eyder batista , yunior perez', 'cuba', '6:40.15', 'sa / b'], ['3', 'kazushige ura , daisaku takeda', 'japan', '6:43.03', 'sc / d'], ['4', 'zsolt hirling , tamã ¡ s varga', 'hungary', '6:50.48', 'sc / d'], ['5', 'devender kumar khandwal , manjeet singh', 'india', '7:02.06', 'sc / d'], ['6', 'jang kang - eun , kim hong - kyun', 'south korea', '7:12.17', 'sc / d']] |
emfuleni local municipality | https://en.wikipedia.org/wiki/Emfuleni_Local_Municipality | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18891012-1.html.csv | majority | sotho is the most commonly spoken language in the areas that make up the emfuleni local municipality . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'sotho', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'most spoken language', 'sotho'], 'result': True, 'ind': 0, 'tointer': 'for the most spoken language records of all rows , most of them fuzzily match to sotho .', 'tostr': 'most_eq { all_rows ; most spoken language ; sotho } = true'} | most_eq { all_rows ; most spoken language ; sotho } = true | for the most spoken language records of all rows , most of them fuzzily match to sotho . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'most spoken language_3': 3, 'sotho_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'most spoken language_3': 'most spoken language', 'sotho_4': 'sotho'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'most spoken language_3': [0], 'sotho_4': [0]} | ['place', 'code', 'area ( km 2 )', 'population', 'most spoken language'] | [['boipatong', '70401', '1.62', '16867', 'sotho'], ['bophelong', '70402', '5.97', '37782', 'sotho'], ['evaton', '70404', '35.20', '143157', 'sotho'], ['orange farm', '70405', '3.79', '16720', 'zulu'], ['sebokeng', '70406', '32.80', '222045', 'sotho'], ['sharpeville', '70407', '5.04', '41032', 'sotho'], ['tshepiso', '70408', '5.26', '22952', 'sotho'], ['vanderbijlpark', '70409', '207.69', '80205', 'afrikaans'], ['vereeniging', '70410', '191.33', '73283', 'afrikaans'], ['remainder of the municipality', '70403', '498.77', '4378', 'sotho']] |
2005 - 06 toronto raptors season | https://en.wikipedia.org/wiki/2005%E2%80%9306_Toronto_Raptors_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-15873014-5.html.csv | majority | chris bosh led the toronto raptors in rebounds for the majority of the games listed . | {'scope': 'all', 'col': '6', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': 'chris bosh', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'high rebounds', 'chris bosh'], 'result': True, 'ind': 0, 'tointer': 'for the high rebounds records of all rows , most of them fuzzily match to chris bosh .', 'tostr': 'most_eq { all_rows ; high rebounds ; chris bosh } = true'} | most_eq { all_rows ; high rebounds ; chris bosh } = true | for the high rebounds records of all rows , most of them fuzzily match to chris bosh . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'high rebounds_3': 3, 'chris bosh_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'high rebounds_3': 'high rebounds', 'chris bosh_4': 'chris bosh'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'high rebounds_3': [0], 'chris bosh_4': [0]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record'] | [['31', 'january 3', 'atlanta', 'w 108 - 97 ( ot )', 'mike james ( 28 )', 'chris bosh ( 10 )', 'mike james ( 6 )', 'philips arena 10048', '9 - 22'], ['32', 'january 4', 'orlando', 'w 121 - 97 ( ot )', 'charlie villanueva ( 24 )', 'rafael araújo ( 9 )', 'mike james ( 7 )', 'air canada centre 14085', '10 - 22'], ['33', 'january 6', 'houston', 'w 112 - 92 ( ot )', 'mike james ( 30 )', 'chris bosh ( 16 )', 'mike james ( 8 )', 'air canada centre 17460', '11 - 22'], ['34', 'january 8', 'new jersey', 'l 104 - 105 ( ot )', 'chris bosh ( 27 )', 'matt bonner ( 8 )', 'mike james ( 7 )', 'air canada centre 18935', '11 - 23'], ['35', 'january 9', 'chicago', 'l 104 - 113 ( ot )', 'chris bosh ( 26 )', 'matt bonner ( 9 )', 'mike james ( 13 )', 'united center 21103', '11 - 24'], ['36', 'january 11', 'charlotte', 'w 95 - 86 ( ot )', 'chris bosh ( 29 )', 'morris peterson ( 11 )', 'mike james ( 7 )', 'air canada centre 14098', '12 - 24'], ['37', 'january 15', 'new york', 'w 129 - 103 ( ot )', 'jalen rose ( 31 )', 'chris bosh , charlie villanueva ( 6 )', 'josé calderón ( 10 )', 'air canada centre 17393', '13 - 24'], ['38', 'january 17', 'utah', 'l 98 - 111 ( ot )', 'chris bosh ( 27 )', 'matt bonner , chris bosh ( 6 )', 'josé calderón , mike james ( 3 )', 'delta center 17831', '13 - 25'], ['39', 'january 18', 'portland', 'l 94 - 96 ( ot )', 'jalen rose ( 23 )', 'chris bosh ( 9 )', 'mike james ( 7 )', 'rose garden 12315', '13 - 26'], ['40', 'january 20', 'seattle', 'w 121 - 113 ( ot )', 'chris bosh ( 29 )', 'chris bosh ( 13 )', 'jalen rose ( 7 )', 'keyarena 15261', '14 - 26'], ['41', 'january 22', 'la lakers', 'l 104 - 122 ( ot )', 'mike james ( 26 )', 'chris bosh ( 8 )', 'mike james ( 10 )', 'staples center 18997', '14 - 27'], ['42', 'january 23', 'denver', 'l 101 - 107 ( ot )', 'mike james ( 22 )', 'matt bonner ( 9 )', 'chris bosh , mike james ( 4 )', 'pepsi center 14826', '14 - 28'], ['43', 'january 25', 'chicago', 'l 88 - 104 ( ot )', 'chris bosh ( 20 )', 'chris bosh ( 7 )', 'mike james ( 7 )', 'air canada centre 14198', '14 - 29'], ['44', 'january 27', 'milwaukee', 'l 87 - 108 ( ot )', 'chris bosh ( 21 )', 'charlie villanueva ( 6 )', 'josé calderón ( 7 )', 'bradley center 14867', '14 - 30']] |
great midwest conference | https://en.wikipedia.org/wiki/Great_Midwest_Conference | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2419754-1.html.csv | aggregation | the schools in the great midwest conference have an average enrollment of 20944 . | {'scope': 'all', 'col': '6', 'type': 'average', 'result': '20944', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'enrollment'], 'result': '20944', 'ind': 0, 'tostr': 'avg { all_rows ; enrollment }'}, '20944'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; enrollment } ; 20944 } = true', 'tointer': 'the average of the enrollment record of all rows is 20944 .'} | round_eq { avg { all_rows ; enrollment } ; 20944 } = true | the average of the enrollment record of all rows is 20944 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'enrollment_4': 4, '20944_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'enrollment_4': 'enrollment', '20944_5': '20944'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'enrollment_4': [0], '20944_5': [1]} | ['institution', 'nickname', 'location', 'founded', 'type', 'enrollment', 'joined', 'left'] | [['university of cincinnati', 'bearcats', 'cincinnati , ohio', '1819', 'public', '41357', '1991', '1995'], ['university of dayton', 'flyers', 'dayton , ohio', '1850', 'private', '11186', '1993', '1995'], ['depaul university', 'blue demons', 'chicago , illinois', '1898', 'private', '24966', '1991', '1995'], ['marquette university', 'golden eagles', 'milwaukee , wisconsin', '1881', 'private', '12002', '1991', '1995'], ['university of memphis', 'tigers', 'memphis , tennessee', '1912', 'public', '22365', '1991', '1995'], ['saint louis university', 'billikens', 'st louis , missouri', '1818', 'private', '13785', '1991', '1995']] |
2008 - 09 ue lleida season | https://en.wikipedia.org/wiki/2008%E2%80%9309_UE_Lleida_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-19018191-5.html.csv | majority | all of the players in the 2008 - 09 ue lleida season had 0 cup appearances . | {'scope': 'all', 'col': '6', 'most_or_all': 'all', 'criterion': 'equal', 'value': '0', 'subset': None} | {'func': 'all_eq', 'args': ['all_rows', 'c apps', '0'], 'result': True, 'ind': 0, 'tointer': 'for the c apps records of all rows , all of them are equal to 0 .', 'tostr': 'all_eq { all_rows ; c apps ; 0 } = true'} | all_eq { all_rows ; c apps ; 0 } = true | for the c apps records of all rows , all of them are equal to 0 . | 1 | 1 | {'all_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'c apps_3': 3, '0_4': 4} | {'all_eq_0': 'all_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'c apps_3': 'c apps', '0_4': '0'} | {'all_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'c apps_3': [0], '0_4': [0]} | ['player', 'nat', 'pos', 'l apps', 'l g', 'c apps', 'total apps', 'total g'] | [['gabernet', 'esp', 'mf', '15', '1', '0', '15', '1'], ['galán', 'esp', 'df', '32', '2', '0', '32', '2'], ['jerson', 'esp', 'df', '34', '1', '0', '34', '1'], ['urrea', 'esp', 'mf', '16', '0', '0', '16', '0'], ['dani marín', 'esp', 'df', '30', '1', '0', '30', '1'], ['campabadal', 'esp', 'mf', '32', '1', '0', '32', '1'], ['parra', 'esp', 'fw', '37', '4', '0', '37', '4'], ['figuerola', 'esp', 'mf', '25', '0', '0', '25', '0'], ['mikel álvaro', 'esp', 'mf', '36', '13', '0', '36', '13'], ['ermengol', 'esp', 'fw', '24', '0', '0', '24', '0'], ['miki', 'esp', 'mf', '36', '1', '0', '36', '1'], ['benet', 'esp', 'mf', '4', '0', '0', '4', '0'], ['moya', 'esp', 'df', '31', '5', '0', '31', '5'], ['david giménez', 'esp', 'mf', '36', '6', '0', '36', '6'], ['casado', 'esp', 'df', '27', '1', '0', '27', '1'], ['jaume', 'esp', 'mf', '35', '0', '0', '35', '0'], ['sellarés', 'esp', 'fw', '37', '8', '0', '37', '8']] |
greater rio de janeiro | https://en.wikipedia.org/wiki/Greater_Rio_de_Janeiro | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14986292-1.html.csv | count | among administrative divisions of greater rio de janeiro with area below 100.00 km square , two of them had population 2000 census of less than 100,000 . | {'scope': 'subset', 'criterion': 'less_than', 'value': '100000', 'result': '2', 'col': '3', 'subset': {'col': '2', 'criterion': 'less_than', 'value': '100'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_less', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'area ( km square )', '100'], 'result': None, 'ind': 0, 'tostr': 'filter_less { all_rows ; area ( km square ) ; 100 }', 'tointer': 'select the rows whose area ( km square ) record is less than 100 .'}, 'population 2000 census', '100000'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose area ( km square ) record is less than 100 . among these rows , select the rows whose population 2000 census record is less than 100000 .', 'tostr': 'filter_less { filter_less { all_rows ; area ( km square ) ; 100 } ; population 2000 census ; 100000 }'}], 'result': '2', 'ind': 2, 'tostr': 'count { filter_less { filter_less { all_rows ; area ( km square ) ; 100 } ; population 2000 census ; 100000 } }', 'tointer': 'select the rows whose area ( km square ) record is less than 100 . among these rows , select the rows whose population 2000 census record is less than 100000 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_less { filter_less { all_rows ; area ( km square ) ; 100 } ; population 2000 census ; 100000 } } ; 2 } = true', 'tointer': 'select the rows whose area ( km square ) record is less than 100 . among these rows , select the rows whose population 2000 census record is less than 100000 . the number of such rows is 2 .'} | eq { count { filter_less { filter_less { all_rows ; area ( km square ) ; 100 } ; population 2000 census ; 100000 } } ; 2 } = true | select the rows whose area ( km square ) record is less than 100 . among these rows , select the rows whose population 2000 census record is less than 100000 . the number of such rows is 2 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_less_1': 1, 'filter_less_0': 0, 'all_rows_5': 5, 'area (km square)_6': 6, '100_7': 7, 'population 2000 census_8': 8, '100000_9': 9, '2_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_less_1': 'filter_less', 'filter_less_0': 'filter_less', 'all_rows_5': 'all_rows', 'area (km square)_6': 'area ( km square )', '100_7': '100', 'population 2000 census_8': 'population 2000 census', '100000_9': '100000', '2_10': '2'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_less_1': [2], 'filter_less_0': [1], 'all_rows_5': [0], 'area (km square)_6': [0], '100_7': [0], 'population 2000 census_8': [1], '100000_9': [1], '2_10': [3]} | ['administrative division', 'area ( km square )', 'population 2000 census', 'population ( 2010 census )', 'population density 2010 ( / km square )'] | [['belford roxo', '79', '434474', '469261', '5940'], ['duque de caxias', '464.5', '775456', '855046', '1840'], ['guapimirim', '361', '37952', '51487', '143'], ['itaboraí', '424.2', '187479', '218090', '514'], ['japeri', '82.9', '83278', '95391', '1151'], ['magé', '386.6', '205830', '228150', '590'], ['mesquita', '34.8', '0', '168403', '4839'], ['nilópolis', '19.4', '153712', '157483', '8118'], ['niterói', '129.3', '459451', '487327', '3769'], ['nova iguaçu', '523.8', '920599', '797212', '1518'], ['queimados', '77', '121993', '137938', '1791'], ['rio de janeiro', '1260', '5857904', '6323037', '5018'], ['são gonçalo', '249.1', '891119', '1013901', '4014'], ['são joão de meriti', '34.8', '449476', '459356', '13200'], ['seropédica', '284', '65260', '78183', '275'], ['tanguá', '147', '26057', '30731', '209'], ['metropolitan rio janeiro', '4557.4', '10670040', '12603936', '2535']] |
list of asian academy award winners and nominees | https://en.wikipedia.org/wiki/List_of_Asian_Academy_Award_winners_and_nominees | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11296015-5.html.csv | majority | most of the films have an asian academy award status of nominated . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'nominated', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'status', 'nominated'], 'result': True, 'ind': 0, 'tointer': 'for the status records of all rows , most of them fuzzily match to nominated .', 'tostr': 'most_eq { all_rows ; status ; nominated } = true'} | most_eq { all_rows ; status ; nominated } = true | for the status records of all rows , most of them fuzzily match to nominated . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'status_3': 3, 'nominated_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'status_3': 'status', 'nominated_4': 'nominated'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'status_3': [0], 'nominated_4': [0]} | ['year', 'name', 'film', 'role', 'status'] | [['year', 'name', 'film', 'role', 'status'], ['1957', 'miyoshi umeki', 'sayonara', 'katsumi kelly', 'won'], ['1985', 'meg tilly', 'agnes of god', 'sister agnes', 'nominated'], ['1994', 'jennifer tilly', 'bullets over broadway', 'olive neal', 'nominated'], ['2003', 'shohreh aghdashloo', 'house of sand and fog', 'nadereh behrani', 'nominated'], ['2006', 'rinko kikuchi', 'babel', 'chieko wataya', 'nominated'], ['2010', 'hailee steinfeld', 'true grit', 'mattie ross', 'nominated']] |
british formula one series | https://en.wikipedia.org/wiki/British_Formula_One_Series | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10628119-1.html.csv | aggregation | the average margin in british formula one series events between 1978 and 1982 was 27.25 . | {'scope': 'all', 'col': '10', 'type': 'average', 'result': '27.25', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'margin ( pts )'], 'result': '27.25', 'ind': 0, 'tostr': 'avg { all_rows ; margin ( pts ) }'}, '27.25'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; margin ( pts ) } ; 27.25 } = true', 'tointer': 'the average of the margin ( pts ) record of all rows is 27.25 .'} | round_eq { avg { all_rows ; margin ( pts ) } ; 27.25 } = true | the average of the margin ( pts ) record of all rows is 27.25 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'margin (pts)_4': 4, '27.25_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'margin (pts)_4': 'margin ( pts )', '27.25_5': '27.25'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'margin (pts)_4': [0], '27.25_5': [1]} | ['season', 'series name', 'champion', 'races', 'pole positions', 'wins', 'podiums', 'fastest laps', 'points', 'margin ( pts )'] | [['1978', 'shellsport f1 series', 'tony trimmer', '8 / 12', '4', '5', '8', '5', '149', '56'], ['1979', 'aurora f1 series', 'rupert keegan', '13 / 15', '5', '6', '6', '4', '65', '2'], ['1980', 'aurora f1 series', 'emilio de villota', '12 / 12', '6', '5', '9', '4', '85', '33'], ['1981', 'no series', 'no series', 'no series', 'no series', 'no series', 'no series', 'no series', 'no series', 'no series'], ['1982', 'british f1 series', 'jim crawford', '4 / 5', '3', '3', '3', '4', '34', '18']] |
amy alcott | https://en.wikipedia.org/wiki/Amy_Alcott | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1629086-4.html.csv | superlative | amy alcott had the highest number of strokes among all of her major championships in 1980 . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '2', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'margin'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; margin }'}, 'year'], 'result': '1980', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; margin } ; year }'}, '1980'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; margin } ; year } ; 1980 } = true', 'tointer': 'select the row whose margin record of all rows is maximum . the year record of this row is 1980 .'} | eq { hop { argmax { all_rows ; margin } ; year } ; 1980 } = true | select the row whose margin record of all rows is maximum . the year record of this row is 1980 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'num_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'margin_5': 5, 'year_6': 6, '1980_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'num_hop_1': 'num_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'margin_5': 'margin', 'year_6': 'year', '1980_7': '1980'} | {'eq_2': [3], 'result_3': [], 'num_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'margin_5': [0], 'year_6': [1], '1980_7': [2]} | ['year', 'championship', 'winning score', 'margin', 'runner ( s ) - up'] | [['1979', 'peter jackson classic', '7 ( 75 + 70 + 70 + 70 = 285 )', '3 strokes', 'nancy lopez'], ['1980', "us women 's open", '4 ( 70 + 70 + 68 + 72 = 280 )', '9 strokes', 'hollis stacy'], ['1983', 'nabisco dinah shore', '6 ( 70 + 70 + 70 + 72 = 282 )', '2 strokes', 'beth daniel , kathy whitworth'], ['1988', 'nabisco dinah shore', '14 ( 71 + 66 + 66 + 71 = 274 )', '2 strokes', 'colleen walker'], ['1991', 'nabisco dinah shore', '15 ( 67 + 70 + 68 + 68 = 273 )', '8 strokes', 'dottie mochrie']] |
cleethorpes coast light railway | https://en.wikipedia.org/wiki/Cleethorpes_Coast_Light_Railway | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1158066-2.html.csv | count | there are five diesel-based locomotives in the cleethorpes coast light railway . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'diesel', 'result': '5', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'fuel / trans', 'diesel'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose fuel / trans record fuzzily matches to diesel .', 'tostr': 'filter_eq { all_rows ; fuel / trans ; diesel }'}], 'result': '5', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; fuel / trans ; diesel } }', 'tointer': 'select the rows whose fuel / trans record fuzzily matches to diesel . the number of such rows is 5 .'}, '5'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; fuel / trans ; diesel } } ; 5 } = true', 'tointer': 'select the rows whose fuel / trans record fuzzily matches to diesel . the number of such rows is 5 .'} | eq { count { filter_eq { all_rows ; fuel / trans ; diesel } } ; 5 } = true | select the rows whose fuel / trans record fuzzily matches to diesel . the number of such rows is 5 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'fuel / trans_5': 5, 'diesel_6': 6, '5_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'fuel / trans_5': 'fuel / trans', 'diesel_6': 'diesel', '5_7': '5'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'fuel / trans_5': [0], 'diesel_6': [0], '5_7': [2]} | ['name', 'built', 'wheels', 'fuel / trans', 'status', 'colour'] | [['ted', 'lister 1944', '0 - 4 - 0', 'diesel - mechanical', 'under rebuild', 'brown'], ['the cub / john', 'minirail 1954', '0 - 4 - 0 bo', 'diesel - hydraulic', 'stored', 'grey undercoat'], ['battison', 'battison 1958', '2 - 6 - 4de', 'diesel - electric', 'out of service', 'lner black'], ['dudley', 'g & s light engineering 1946', 'bo - bo', '4 petrol - mechanical', 'on display', 'grey & red'], ['da1', 'bush mill railway 1986', '0 - 4 - 0', 'diesel - mechanical', 'in service', 'royal blue with white linings'], ['kd1', 'unknown', 'articulated', 'diesel electric', 'long term restoration , stored', 'ran in a red livery previously']] |
drop dead diva ( season 1 ) | https://en.wikipedia.org/wiki/Drop_Dead_Diva_%28season_1%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27504682-1.html.csv | unique | the episode " dead model walking " was the only episode written by amy engelberg & wendy engelberg . | {'scope': 'all', 'row': '12', 'col': '4', 'col_other': '2', 'criterion': 'equal', 'value': 'amy engelberg & wendy engelberg', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'written by', 'amy engelberg & wendy engelberg'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose written by record fuzzily matches to amy engelberg & wendy engelberg .', 'tostr': 'filter_eq { all_rows ; written by ; amy engelberg & wendy engelberg }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; written by ; amy engelberg & wendy engelberg } }', 'tointer': 'select the rows whose written by record fuzzily matches to amy engelberg & wendy engelberg . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'written by', 'amy engelberg & wendy engelberg'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose written by record fuzzily matches to amy engelberg & wendy engelberg .', 'tostr': 'filter_eq { all_rows ; written by ; amy engelberg & wendy engelberg }'}, 'title'], 'result': 'dead model walking', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; written by ; amy engelberg & wendy engelberg } ; title }'}, 'dead model walking'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; written by ; amy engelberg & wendy engelberg } ; title } ; dead model walking }', 'tointer': 'the title record of this unqiue row is dead model walking .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; written by ; amy engelberg & wendy engelberg } } ; eq { hop { filter_eq { all_rows ; written by ; amy engelberg & wendy engelberg } ; title } ; dead model walking } } = true', 'tointer': 'select the rows whose written by record fuzzily matches to amy engelberg & wendy engelberg . there is only one such row in the table . the title record of this unqiue row is dead model walking .'} | and { only { filter_eq { all_rows ; written by ; amy engelberg & wendy engelberg } } ; eq { hop { filter_eq { all_rows ; written by ; amy engelberg & wendy engelberg } ; title } ; dead model walking } } = true | select the rows whose written by record fuzzily matches to amy engelberg & wendy engelberg . there is only one such row in the table . the title record of this unqiue row is dead model walking . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'written by_7': 7, 'amy engelberg & wendy engelberg_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'title_9': 9, 'dead model walking_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'written by_7': 'written by', 'amy engelberg & wendy engelberg_8': 'amy engelberg & wendy engelberg', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'title_9': 'title', 'dead model walking_10': 'dead model walking'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'written by_7': [0], 'amy engelberg & wendy engelberg_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'title_9': [2], 'dead model walking_10': [3]} | ['no in series', 'title', 'directed by', 'written by', 'original air date', 'us viewers ( millions )'] | [['1', 'pilot', 'james hayman', 'josh berman', 'july 12 , 2009', '2.8'], ['2', 'the f word', 'ron underwood', 'carla kettner & josh berman', 'july 19 , 2009', '2.46'], ['3', 'do over', 'michael lange', 'alex taub', 'july 26 , 2009', '2.80'], ['4', 'the chinese wall', 'lawrence trilling', 'thania st john', 'august 2 , 2009', 'n / a'], ['5', 'lost and found', 'david petrarca', 'jeanette collins & mimi friedman', 'august 9 , 2009', '2.44'], ['6', 'second chances', 'michael schultz', 'jeffrey lippman', 'august 16 , 2009', '3.06'], ['7', 'the magic bullet', 'jamie babbit', 'shawn schepps', 'august 23 , 2009', '2.90'], ['8', 'crazy', 'melanie mayron', 'maurissa tancharoen', 'august 30 , 2009', '3.41'], ['9', 'the dress', 'david petrarca', 'josh berman', 'september 13 , 2009', '3.08'], ['10', 'make me a match', 'matt hastings', 'thania st john', 'september 20 , 2009', '3.06'], ['11', 'what if', 'bethany rooney', 'jeanette collins & mimi friedman', 'september 27 , 2009', 'n / a'], ['12', 'dead model walking', 'ron underwood', 'amy engelberg & wendy engelberg', 'october 4 , 2009', 'n / a']] |
2007 detroit indy grand prix | https://en.wikipedia.org/wiki/2007_Detroit_Indy_Grand_Prix | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17242268-2.html.csv | superlative | dario franchitti was the driver who led the most laps in the 2007 detroit indy grand prix . | {'scope': 'all', 'col_superlative': '6', 'row_superlative': '6', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'laps led'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; laps led }'}, 'driver'], 'result': 'dario franchitti', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; laps led } ; driver }'}, 'dario franchitti'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; laps led } ; driver } ; dario franchitti } = true', 'tointer': 'select the row whose laps led record of all rows is maximum . the driver record of this row is dario franchitti .'} | eq { hop { argmax { all_rows ; laps led } ; driver } ; dario franchitti } = true | select the row whose laps led record of all rows is maximum . the driver record of this row is dario franchitti . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'laps led_5': 5, 'driver_6': 6, 'dario franchitti_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'laps led_5': 'laps led', 'driver_6': 'driver', 'dario franchitti_7': 'dario franchitti'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'laps led_5': [0], 'driver_6': [1], 'dario franchitti_7': [2]} | ['driver', 'team', 'laps', 'time / retired', 'grid', 'laps led', 'points'] | [['tony kanaan', 'andretti green', '89', '2:11:50.5097', '4', '20', '50'], ['danica patrick', 'andretti green', '89', '+ 0.4865', '11', '9', '40'], ['dan wheldon', 'target chip ganassi', '89', '+ 1.2207', '16', '0', '35'], ['darren manning', 'aj foyt racing', '89', '+ 1.9217', '8', '0', '32'], ['kosuke matsuura', 'panther racing', '88', '+ 1 lap', '14', '0', '30'], ['dario franchitti', 'andretti green', '88', '+ 1 lap', '2', '27', '31'], ['buddy rice', 'dreyer & reinbold racing', '87', 'contact', '15', '7', '26'], ['scott dixon', 'target chip ganassi', '87', 'contact', '3', '0', '24'], ['a j foyt iv', 'vision racing', '87', 'mechanical', '13', '0', '22'], ['ed carpenter', 'vision racing', '86', '+ 3 laps', '12', '0', '20'], ['scott sharp', 'rahal letterman', '82', '+ 7 laps', '17', '0', '19'], ['sam hornish , jr', 'team penske', '75', '+ 14 laps', '7', '0', '18'], ['tomas scheckter', 'vision racing', '67', 'contact', '9', '0', '17'], ['hãlio castroneves', 'team penske', '67', 'contact', '1', '26', '16'], ['vitor meira', 'panther racing', '31', 'contact', '10', '0', '15'], ['sarah fisher', 'dreyer & reinbold racing', '29', 'contact', '18', '0', '14'], ['marco andretti', 'andretti green', '27', 'mechanical', '6', '0', '13'], ['ryan hunter - reay', 'rahal letterman', '24', 'mechanical', '5', '0', '12']] |
helmut bradl | https://en.wikipedia.org/wiki/Helmut_Bradl | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14860663-4.html.csv | majority | the majority of the teams helmut raced motorcycles for were hb-honda . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'hb - honda', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'team', 'hb - honda'], 'result': True, 'ind': 0, 'tointer': 'for the team records of all rows , most of them fuzzily match to hb - honda .', 'tostr': 'most_eq { all_rows ; team ; hb - honda } = true'} | most_eq { all_rows ; team ; hb - honda } = true | for the team records of all rows , most of them fuzzily match to hb - honda . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'team_3': 3, 'hb - honda_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'team_3': 'team', 'hb - honda_4': 'hb - honda'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'team_3': [0], 'hb - honda_4': [0]} | ['year', 'class', 'team', 'points', 'wins'] | [['1986', '250cc', 'honda', '0', '0'], ['1987', '250cc', 'honda', '0', '0'], ['1988', '250cc', 'honda', '27', '0'], ['1989', '250cc', 'hb - honda', '88', '0'], ['1990', '250cc', 'hb - honda', '150', '0'], ['1991', '250cc', 'hb - honda', '220', '5'], ['1992', '250cc', 'hb - honda', '89', '0'], ['1993', '250cc', 'hb - honda', '126', '0']] |
1984 senior pga tour | https://en.wikipedia.org/wiki/1984_Senior_PGA_Tour | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11622840-4.html.csv | count | there were two players in the 1984 pga tour that had 14 wins each . | {'scope': 'all', 'criterion': 'equal', 'value': '14', 'result': '2', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'wins', '14'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose wins record is equal to 14 .', 'tostr': 'filter_eq { all_rows ; wins ; 14 }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; wins ; 14 } }', 'tointer': 'select the rows whose wins record is equal to 14 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; wins ; 14 } } ; 2 } = true', 'tointer': 'select the rows whose wins record is equal to 14 . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; wins ; 14 } } ; 2 } = true | select the rows whose wins record is equal to 14 . 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, 'wins_5': 5, '14_6': 6, '2_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'wins_5': 'wins', '14_6': '14', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'wins_5': [0], '14_6': [0], '2_7': [2]} | ['rank', 'player', 'country', 'earnings', 'wins'] | [['1', 'don january', 'united states', '791990', '14'], ['2', 'miller barber', 'united states', '720134', '14'], ['3', 'arnold palmer', 'united states', '442974', '8'], ['4', 'billy casper', 'united states', '395386', '4'], ['5', 'gene littler', 'united states', '358770', '3']] |
yankee small college conference | https://en.wikipedia.org/wiki/Yankee_Small_College_Conference | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10720390-1.html.csv | ordinal | unity college had the 2nd lowest enrollment among institutions in the yankee small college conference . | {'row': '14', 'col': '5', 'order': '2', 'col_other': '1', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'enrollment', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; enrollment ; 2 }'}, 'institution'], 'result': 'unity college', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; enrollment ; 2 } ; institution }'}, 'unity college'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; enrollment ; 2 } ; institution } ; unity college } = true', 'tointer': 'select the row whose enrollment record of all rows is 2nd minimum . the institution record of this row is unity college .'} | eq { hop { nth_argmin { all_rows ; enrollment ; 2 } ; institution } ; unity college } = true | select the row whose enrollment record of all rows is 2nd minimum . the institution record of this row is unity college . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'enrollment_5': 5, '2_6': 6, 'institution_7': 7, 'unity college_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', 'enrollment_5': 'enrollment', '2_6': '2', 'institution_7': 'institution', 'unity college_8': 'unity college'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'enrollment_5': [0], '2_6': [0], 'institution_7': [1], 'unity college_8': [2]} | ['institution', 'location', 'founded', 'affiliation', 'enrollment', 'team nickname'] | [['central maine community college', 'auburn , maine', '1963', 'public junior college', '2720', 'mustangs'], ['college of st joseph', 'rutland , vermont', '1956', 'private', '500', 'saints'], ['eastern maine community college', 'bangor , maine', '1966', 'public junior college', '2099', 'golden eagles'], ['great bay community college', 'portsmouth , new hampshire', '1945', 'public junior college', '1850', 'herons'], ['hampshire college', 'amherst , massachusetts', '1965', 'private', '1463', 'frogs'], ['nashua community college', 'nashua , new hampshire', '1970', 'public junior college', '2147', 'jaguars'], ['new hampshire technical institute', 'concord , new hampshire', '1961', 'public junior college', '4127', 'capitals'], ['northern maine community college', 'presque isle , maine', '1961', 'public junior college', '1129', 'falcons'], ["paul smith 's college", 'paul smiths , new york', '1946', 'private', '1000', 'bobcats'], ['southern maine community college', 'south portland , maine', '1946', 'public junior college', '6261', 'seawolves'], ['university of maine at machias', 'machias , maine', '1909', 'public', '1200', 'clippers'], ['university of maine at augusta', 'augusta , maine', '1965', 'public', '5054', 'moose'], ['university of new hampshire club sports', 'durham , new hampshire', '1866', 'public', '15253', 'wildcats'], ['unity college', 'unity , maine', '1965', 'private', '564', 'rams'], ['vermont technical college', 'randolph , vermont', '1866', 'public', '1453', 'green knights']] |
galina voskoboeva | https://en.wikipedia.org/wiki/Galina_Voskoboeva | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15272585-8.html.csv | majority | galina voskoboeva had a runner - up outcome in most tournaments of year 2003 . | {'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', 'opponent', 'score'] | [['runner - up', '28 january 2003', 'tipton', 'hard ( i )', 'matea mezak', '6 - 4 , 4 - 6 , 4 - 6'], ['winner', '29 june 2003', 'mont - de - marsan', 'hard ( i )', 'oleksandra kravets', '6 - 4 , 6 - 2'], ['runner - up', '3 october 2003', 'latina', 'clay', 'roberta vinci', '3 - 6 , 4 - 6'], ['runner - up', '8 november 2005', 'pittsburgh', 'hard', 'lilia osterloh', '6 - 7 , 4 - 6'], ['winner', '6 june 2006', 'cuneo , italy', 'clay', 'alice canepa', '6 - 1 , 6 - 2']] |
1963 detroit lions season | https://en.wikipedia.org/wiki/1963_Detroit_Lions_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16983245-2.html.csv | superlative | in the 1963 season , the detroit lions ' highest winning score was 45 . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '8', 'value_mentioned': 'yes', 'max_or_min': 'max', 'other_col': 'n/a', 'subset': None} | {'func': 'eq', 'args': [{'func': 'max', 'args': ['all_rows', 'result'], 'result': 'w 45 - 7', 'ind': 0, 'tostr': 'max { all_rows ; result }', 'tointer': 'the maximum result record of all rows is w 45 - 7 .'}, 'w 45 - 7'], 'result': True, 'ind': 1, 'tostr': 'eq { max { all_rows ; result } ; w 45 - 7 } = true', 'tointer': 'the maximum result record of all rows is w 45 - 7 .'} | eq { max { all_rows ; result } ; w 45 - 7 } = true | the maximum result record of all rows is w 45 - 7 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'max_0': 0, 'all_rows_3': 3, 'result_4': 4, 'w 45 - 7_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'max_0': 'max', 'all_rows_3': 'all_rows', 'result_4': 'result', 'w 45 - 7_5': 'w 45 - 7'} | {'eq_1': [2], 'result_2': [], 'max_0': [1], 'all_rows_3': [0], 'result_4': [0], 'w 45 - 7_5': [1]} | ['week', 'date', 'opponent', 'result', 'attendance'] | [['1', 'september 14 , 1963', 'los angeles rams', 'w 23 - 2', '49342'], ['2', 'september 22 , 1963', 'green bay packers', 'l 31 - 10', '45912'], ['3', 'september 29 , 1963', 'chicago bears', 'l 37 - 21', '55400'], ['4', 'october 6 , 1963', 'san francisco 49ers', 'w 26 - 3', '44088'], ['5', 'october 13 , 1963', 'dallas cowboys', 'l 17 - 14', '27264'], ['6', 'october 20 , 1963', 'baltimore colts', 'l 25 - 21', '51901'], ['7', 'october 27 , 1963', 'minnesota vikings', 'w 28 - 10', '44509'], ['8', 'november 3 , 1963', 'san francisco 49ers', 'w 45 - 7', '33511'], ['9', 'november 10 , 1963', 'baltimore colts', 'l 24 - 21', '59758'], ['10', 'november 17 , 1963', 'los angeles rams', 'l 28 - 21', '44951'], ['11', 'november 24 , 1963', 'minnesota vikings', 'l 34 - 31', '28763'], ['12', 'november 28 , 1963', 'green bay packers', 't 13 - 13', '54016'], ['13', 'december 8 , 1963', 'cleveland browns', 'w 38 - 10', '51382'], ['14', 'december 15 , 1963', 'chicago bears', 'l 24 - 14', '45317']] |
list of schools in the hawke 's bay region | https://en.wikipedia.org/wiki/List_of_schools_in_the_Hawke%27s_Bay_Region | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12195931-4.html.csv | aggregation | the average decile for the schools in the hawke 's bay region is around 5 . | {'scope': 'all', 'col': '6', 'type': 'average', 'result': '5', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'decile'], 'result': '5', 'ind': 0, 'tostr': 'avg { all_rows ; decile }'}, '5'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; decile } ; 5 } = true', 'tointer': 'the average of the decile record of all rows is 5 .'} | round_eq { avg { all_rows ; decile } ; 5 } = true | the average of the decile record of all rows is 5 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'decile_4': 4, '5_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'decile_4': 'decile', '5_5': '5'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'decile_4': [0], '5_5': [1]} | ['name', 'years', 'gender', 'area', 'authority', 'decile', 'roll'] | [['argyll east school', '1 - 8', 'coed', 'otane', 'state', '4', '51'], ["central hawke 's bay college", '9 - 15', 'coed', 'waipukurau', 'state', '4', '557'], ['elsthorpe school', '1 - 8', 'coed', 'elsthorpe', 'state', '9', '42'], ['flemington school', '1 - 8', 'coed', 'waipukurau', 'state', '8', '71'], ['mangaorapa school', '1 - 8', 'coed', 'porangahau', 'state', '3', '19'], ['omakere school', '1 - 8', 'coed', 'waipawa', 'state', '8', '30'], ['ongaonga school', '1 - 8', 'coed', 'ongaonga', 'state', '6', '111'], ['otane school', '1 - 8', 'coed', 'otane', 'state', '3', '43'], ['porangahau school', '1 - 8', 'coed', 'porangahau', 'state', '4', '31'], ['pukehou school', '1 - 8', 'coed', 'pukehou', 'state', '5', '108'], ['sherwood school', '1 - 8', 'coed', 'takapau', 'state', '6', '30'], ["st joseph 's school", '1 - 8', 'coed', 'waipukurau', 'state integrated', '5', '95'], ['takapau school', '1 - 8', 'coed', 'takapau', 'state', '5', '141'], ['te aute college', '9 - 15', 'boys', 'pukehou', 'state integrated', '3', '86'], ['the terrace school', '1 - 8', 'coed', 'waipukurau', 'state', '2', '214'], ['tikokino school', '1 - 8', 'coed', 'waipawa', 'state', '7', '42'], ['tkkm o takapau', '1 - 8', 'coed', 'takapau', 'state', '3', '37'], ['waipawa school', '1 - 8', 'coed', 'waipawa', 'state', '3', '139'], ['waipukurau school', '1 - 8', 'coed', 'waipukurau', 'state', '3', '243']] |
north state conference | https://en.wikipedia.org/wiki/North_State_Conference | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-16168849-1.html.csv | count | in the north state conference , twelve of the institutions are private . | {'scope': 'all', 'criterion': 'equal', 'value': 'private', 'result': '12', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'type', 'private'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose type record fuzzily matches to private .', 'tostr': 'filter_eq { all_rows ; type ; private }'}], 'result': '12', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; type ; private } }', 'tointer': 'select the rows whose type record fuzzily matches to private . the number of such rows is 12 .'}, '12'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; type ; private } } ; 12 } = true', 'tointer': 'select the rows whose type record fuzzily matches to private . the number of such rows is 12 .'} | eq { count { filter_eq { all_rows ; type ; private } } ; 12 } = true | select the rows whose type record fuzzily matches to private . the number of such rows is 12 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'type_5': 5, 'private_6': 6, '12_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'type_5': 'type', 'private_6': 'private', '12_7': '12'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'type_5': [0], 'private_6': [0], '12_7': [2]} | ['institution', 'location', 'founded', 'type', 'enrollment', 'nickname', 'joined', 'left', 'current conference'] | [['anderson university', 'anderson , south carolina', '1911', 'private', '2907', 'trojans', '1998', '2010', 'sac'], ['appalachian state university', 'boone , north carolina', '1899', 'public', '17589', 'mountaineers', '1930', '1967', 'socon ( sun belt in 2014 ) ( ncaa division i )'], ['catawba college', 'salisbury , north carolina', '1851', 'private', '1300', 'indians', '1930', '1989', 'sac'], ['coker college', 'hartsville , south carolina', '1908', 'private', '1200', 'cobras', '1991', '2013', 'sac'], ['east carolina university', 'greenville , north carolina', '1907', 'public', '27386', 'pirates', '1947', '1962', 'c - usa ( the american in 2014 ) ( ncaa division i )'], ['elon university', 'elon , north carolina', '1889', 'private', '6720', 'phoenix', '1930', '1989', 'socon ( caa in 2014 ) ( ncaa division i )'], ['guilford college', 'greensboro , north carolina', '1837', 'private', '2706', 'quakers', '1930', '1988', 'odac ( ncaa division iii )'], ['high point university', 'high point , north carolina', '1924', 'private', '4519', 'panthers', '1930', '1997', 'big south ( ncaa division i )'], ['lenoirrhyne university', 'hickory , north carolina', '1891', 'private', '1983', 'bears', '1930 , 1985', '1974 , 1989', 'sac'], ['longwood university', 'farmville , virginia', '1839', 'public', '4800', 'lancers', '1995', '2003', 'big south ( ncaa division i )'], ['mars hill college', 'mars hill , north carolina', '1856', 'private', '1370', 'lions', '1973', '1975', 'sac'], ['newberry college', 'newberry , south carolina', '1856', 'private', '949', 'wolves', '1961', '1972', 'sac'], ['university of north carolina at pembroke', 'pembroke , north carolina', '1887', 'public', '6433', 'braves', '1976', '1992', 'peach belt ( pbc )'], ['presbyterian college', 'clinton , south carolina', '1880', 'private', '1300', 'blue hose', '1965', '1972', 'big south ( ncaa division i )'], ['queens university of charlotte', 'charlotte , north carolina', '1857', 'private', '2386', 'royals', '1995', '2013', 'sac'], ['st andrews university', 'laurinburg , north carolina', '1958', 'private', '600', 'knights', '1988', '2012', 'aac ( naia )'], ['western carolina university', 'cullowhee , north carolina', '1889', 'public', '9608', 'catamounts', '1933', '1976', 'socon ( ncaa division i )']] |
helmut bradl | https://en.wikipedia.org/wiki/Helmut_Bradl | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14860663-4.html.csv | aggregation | the average points helmut bradl scored per year was 87.5 . | {'scope': 'all', 'col': '4', 'type': 'average', 'result': '87.5', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'points'], 'result': '87.5', 'ind': 0, 'tostr': 'avg { all_rows ; points }'}, '87.5'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; points } ; 87.5 } = true', 'tointer': 'the average of the points record of all rows is 87.5 .'} | round_eq { avg { all_rows ; points } ; 87.5 } = true | the average of the points record of all rows is 87.5 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'points_4': 4, '87.5_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'points_4': 'points', '87.5_5': '87.5'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'points_4': [0], '87.5_5': [1]} | ['year', 'class', 'team', 'points', 'wins'] | [['1986', '250cc', 'honda', '0', '0'], ['1987', '250cc', 'honda', '0', '0'], ['1988', '250cc', 'honda', '27', '0'], ['1989', '250cc', 'hb - honda', '88', '0'], ['1990', '250cc', 'hb - honda', '150', '0'], ['1991', '250cc', 'hb - honda', '220', '5'], ['1992', '250cc', 'hb - honda', '89', '0'], ['1993', '250cc', 'hb - honda', '126', '0']] |
acc - big ten challenge | https://en.wikipedia.org/wiki/ACC%E2%80%93Big_Ten_Challenge | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1672976-5.html.csv | count | 11 acc teams competed against the big ten teams in the acc - big ten challenge . | {'scope': 'all', 'criterion': 'all', 'value': 'n/a', 'result': '11', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_all', 'args': ['all_rows', 'acc team'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose acc team record is arbitrary .', 'tostr': 'filter_all { all_rows ; acc team }'}], 'result': '11', 'ind': 1, 'tostr': 'count { filter_all { all_rows ; acc team } }', 'tointer': 'select the rows whose acc team record is arbitrary . the number of such rows is 11 .'}, '11'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_all { all_rows ; acc team } } ; 11 } = true', 'tointer': 'select the rows whose acc team record is arbitrary . the number of such rows is 11 .'} | eq { count { filter_all { all_rows ; acc team } } ; 11 } = true | select the rows whose acc team record is arbitrary . the number of such rows is 11 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_all_0': 0, 'all_rows_4': 4, 'acc team_5': 5, '11_6': 6} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_all_0': 'filter_all', 'all_rows_4': 'all_rows', 'acc team_5': 'acc team', '11_6': '11'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_all_0': [1], 'all_rows_4': [0], 'acc team_5': [0], '11_6': [2]} | ['date', 'time', 'acc team', 'big ten team', 'location', 'television', 'attendance', 'winner', 'challenge leader'] | [['tue , nov 29', '7:00 pm', 'virginia', '15 michigan', 'john paul jones arena charlottesville , va', 'espn2', '10564', 'virginia ( 70 - 58 )', 'acc ( 1 - 0 )'], ['tue , nov 29', '7:15 pm', 'georgia tech', 'northwestern', 'philips arena atlanta , ga', 'espnu', '5619', 'northwestern ( 76 - 60 )', 'tied ( 1 - 1 )'], ['tue , nov 29', '7:30 pm', 'maryland', 'illinois', 'comcast center college park , md', 'espn', '13187', 'illinois ( 71 - 62 )', 'big ten ( 2 - 1 )'], ['tue , nov 29', '9:00 pm', 'miami', 'purdue', 'mackey arena west lafayette , in', 'espn2', '13927', 'purdue ( 76 - 65 )', 'big ten ( 3 - 1 )'], ['tue , nov 29', '9:15 pm', 'clemson', 'iowa', 'carver - hawkeye arena iowa city , ia', 'espnu', '10449', 'clemson ( 71 - 55 )', 'big ten ( 3 - 2 )'], ['tue , nov 29', '9:30 pm', '4 duke', '2 ohio state', 'value city arena columbus , oh', 'espn', '18809', 'ohio state ( 85 - 63 )', 'big ten ( 4 - 2 )'], ['wed , nov 30', '7:15 pm', 'nc state', 'indiana', 'rbc center raleigh , nc', 'espn2', '16597', 'indiana ( 86 - 75 )', 'big ten ( 5 - 2 )'], ['wed , nov 30', '7:15 pm', 'boston college', 'penn state', 'conte forum chestnut hill , ma', 'espnu', '4326', 'penn state ( 62 - 54 )', 'big ten ( 6 - 2 )'], ['wed , nov 30', '7:30 pm', 'florida state', 'michigan state', 'breslin student events center east lansing , mi', 'espn', '14797', 'michigan state ( 65 - 49 )', 'big ten ( 7 - 2 )'], ['wed , nov 30', '9:15 pm', 'virginia tech', 'minnesota', 'williams arena minneapolis , mn', 'espn2', '10487', 'minnesota ( 58 - 55 )', 'big ten ( 8 - 2 )'], ['wed , nov 30', '9:15 pm', 'wake forest', 'nebraska', 'bob devaney sports center lincoln , ne', 'espnu', '9769', 'wake forest ( 55 - 53 )', 'big ten ( 8 - 3 )']] |
canada post stamp releases ( 2005 - 09 ) | https://en.wikipedia.org/wiki/Canada_Post_stamp_releases_%282005%E2%80%9309%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11900773-1.html.csv | majority | most of the canada post stamp releases were on tullis russell coatings paper . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'tullis russell coatings', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'paper type', 'tullis russell coatings'], 'result': True, 'ind': 0, 'tointer': 'for the paper type records of all rows , most of them fuzzily match to tullis russell coatings .', 'tostr': 'most_eq { all_rows ; paper type ; tullis russell coatings } = true'} | most_eq { all_rows ; paper type ; tullis russell coatings } = true | for the paper type records of all rows , most of them fuzzily match to tullis russell coatings . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'paper type_3': 3, 'tullis russell coatings_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'paper type_3': 'paper type', 'tullis russell coatings_4': 'tullis russell coatings'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'paper type_3': [0], 'tullis russell coatings_4': [0]} | ['date of issue', 'denomination', 'design', 'paper type', 'first day cover cancellation'] | [['7 january 2005', '50 cents', 'hélène lheureux', 'tullis russell coatings', 'vancouver , bc'], ['7 january 2005', '1.45', 'hélène lheureux', 'tullis russell coatings', 'vancouver , bc'], ['29 january 2005', '0.50', 'stéphane huot', 'tullis russell coatings', 'edmonton , alberta'], ['4 february 2005', '0.50', 'circle design inc', 'tullis russell coatings', 'granby , qc'], ['14 february 2005', '0.50', 'denis lallier', 'fasson', 'truro , nova scotia'], ['4 march 2005', '0.50', 'hm & e design', 'tullis russell coatings', 'vancouver , bc'], ['10 march 2005', '0.50', 'isabelle toussaint', 'fasson', 'vancouver , bc'], ['23 march 2005', '0.50', 'rolf harder', 'tullis russell coatings', 'fredericton , new brunswick'], ['2 april 2005', '0.50', 'designwerke inc , andrew perro', 'tullis russell coatings', 'montreal , qc and halifax , ns'], ['12 april 2005', '0.50', '52 pick - up inc', 'tullis russell coatings', 'toronto , on'], ['22 april 2005', '0.50', 'xerxes irani', 'tullis russell coatings', 'waterton park , ab'], ['29 april 2005', '0.50', 'derek sarty', 'tullis russell coatings', 'halifax , ns'], ['6 may 2005', '0.50', 'tilt telmet and marko barac', 'tullis russell coatings', 'ottawa , on'], ['27 may 2005', '0.50', 'hélène lheureux', 'tullis russell coatings', 'kitchener , on'], ['13 june 2005', '0.50', 'françois dallaire', 'tullis russell coatings', 'victoria , bc'], ['13 june 2005', '0.50', 'françois dallaire', 'tullis russell coatings', 'victoria , bc'], ['21 june 2005', '0.50', 'katalin kovats', 'tullis russell coatings', 'hamilton , ontario']] |
carsten jancker | https://en.wikipedia.org/wiki/Carsten_Jancker | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1834853-3.html.csv | unique | of the competitions that carsten jancker has participated in , the only one in nuremberg was on june 3 , 2000 . | {'scope': 'all', 'row': '1', 'col': '2', 'col_other': '1', 'criterion': 'fuzzily_match', 'value': 'nuremberg', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'venue', 'nuremberg'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose venue record fuzzily matches to nuremberg .', 'tostr': 'filter_eq { all_rows ; venue ; nuremberg }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; venue ; nuremberg } }', 'tointer': 'select the rows whose venue record fuzzily matches to nuremberg . 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', 'nuremberg'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose venue record fuzzily matches to nuremberg .', 'tostr': 'filter_eq { all_rows ; venue ; nuremberg }'}, 'date'], 'result': '3 june 2000', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; venue ; nuremberg } ; date }'}, '3 june 2000'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; venue ; nuremberg } ; date } ; 3 june 2000 }', 'tointer': 'the date record of this unqiue row is 3 june 2000 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; venue ; nuremberg } } ; eq { hop { filter_eq { all_rows ; venue ; nuremberg } ; date } ; 3 june 2000 } } = true', 'tointer': 'select the rows whose venue record fuzzily matches to nuremberg . there is only one such row in the table . the date record of this unqiue row is 3 june 2000 .'} | and { only { filter_eq { all_rows ; venue ; nuremberg } } ; eq { hop { filter_eq { all_rows ; venue ; nuremberg } ; date } ; 3 june 2000 } } = true | select the rows whose venue record fuzzily matches to nuremberg . there is only one such row in the table . the date record of this unqiue row is 3 june 2000 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'venue_7': 7, 'nuremberg_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'date_9': 9, '3 june 2000_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', 'nuremberg_8': 'nuremberg', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'date_9': 'date', '3 june 2000_10': '3 june 2000'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'venue_7': [0], 'nuremberg_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'date_9': [2], '3 june 2000_10': [3]} | ['date', 'venue', 'score', 'result', 'competition'] | [['3 june 2000', 'easycredit - stadion , nuremberg', '1 - 0', '3 - 2', 'friendly'], ['7 june 2000', 'dreisamstadion , freiburg', '6 - 2', '8 - 2', 'friendly'], ['7 june 2000', 'dreisamstadion , freiburg', '8 - 2', '8 - 2', 'friendly'], ['2 june 2001', 'helsinki olympic stadium , helsinki', '2 - 2', '2 - 2', '2002 world cup qualifier'], ['15 august 2001', 'ferenc puskás stadium , budapest', '3 - 0', '5 - 2', 'friendly'], ['1 september 2001', 'olympiastadion , munich', '1 - 0', '1 - 5', '2002 world cup qualifier'], ['9 may 2002', 'dreisamstadion , freiburg', '7 - 0', '7 - 0', 'friendly'], ['1 june 2002', 'sapporo dome , sapporo', '4 - 0', '8 - 0', '2002 world cup'], ['21 august 2002', 'vasil levski national stadium , sofia', '2 - 2', '2 - 2', 'friendly'], ['11 october 2002', 'asim ferhatović hase stadium , sarajevo', '1 - 1', '1 - 1', 'friendly']] |
somerset county cricket club in 2009 | https://en.wikipedia.org/wiki/Somerset_County_Cricket_Club_in_2009 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27922491-8.html.csv | unique | of the players in the somerset county cricket club , charl willoughby is the only player to have three 5wi . | {'scope': 'all', 'row': '1', 'col': '8', 'col_other': '1', 'criterion': 'equal', 'value': '3', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', '5wi', '3'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose 5wi record is equal to 3 .', 'tostr': 'filter_eq { all_rows ; 5wi ; 3 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; 5wi ; 3 } }', 'tointer': 'select the rows whose 5wi record is equal to 3 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_eq', 'args': ['all_rows', '5wi', '3'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose 5wi record is equal to 3 .', 'tostr': 'filter_eq { all_rows ; 5wi ; 3 }'}, 'player'], 'result': 'charl willoughby', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; 5wi ; 3 } ; player }'}, 'charl willoughby'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; 5wi ; 3 } ; player } ; charl willoughby }', 'tointer': 'the player record of this unqiue row is charl willoughby .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; 5wi ; 3 } } ; eq { hop { filter_eq { all_rows ; 5wi ; 3 } ; player } ; charl willoughby } } = true', 'tointer': 'select the rows whose 5wi record is equal to 3 . there is only one such row in the table . the player record of this unqiue row is charl willoughby .'} | and { only { filter_eq { all_rows ; 5wi ; 3 } } ; eq { hop { filter_eq { all_rows ; 5wi ; 3 } ; player } ; charl willoughby } } = true | select the rows whose 5wi record is equal to 3 . there is only one such row in the table . the player record of this unqiue row is charl willoughby . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, '5wi_7': 7, '3_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'player_9': 9, 'charl willoughby_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', '5wi_7': '5wi', '3_8': '3', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'player_9': 'player', 'charl willoughby_10': 'charl willoughby'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], '5wi_7': [0], '3_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'player_9': [2], 'charl willoughby_10': [3]} | ['player', 'matches', 'innings', 'wickets', 'average', 'bbi', 'bbm', '5wi'] | [['charl willoughby', '16', '26', '54', '30.03', '5 / 56', '7 / 170', '3'], ['david stiff', '10', '18', '31', '36.12', '5 / 91', '5 / 93', '1'], ['alfonso thomas', '14', '22', '35', '37.62', '5 / 53', '8 / 152', '1'], ['ben phillips', '7', '11', '12', '38.00', '4 / 46', '4 / 73', '0'], ['arul suppiah', '16', '19', '15', '45.46', '3 / 58', '5 / 85', '0'], ['peter trego', '16', '25', '19', '46.78', '3 / 53', '3 / 74', '0'], ['andrew caddick', '5', '8', '10', '52.50', '3 / 53', '4 / 95', '0']] |
south london derby | https://en.wikipedia.org/wiki/South_London_derby | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-28611996-3.html.csv | aggregation | in the south london derby , charlton scored a total of 178 goals . | {'scope': 'all', 'col': '6', 'type': 'sum', 'result': '178', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'charlton goals'], 'result': '178', 'ind': 0, 'tostr': 'sum { all_rows ; charlton goals }'}, '178'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; charlton goals } ; 178 } = true', 'tointer': 'the sum of the charlton goals record of all rows is 178 .'} | round_eq { sum { all_rows ; charlton goals } ; 178 } = true | the sum of the charlton goals record of all rows is 178 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'charlton goals_4': 4, '178_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'charlton goals_4': 'charlton goals', '178_5': '178'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'charlton goals_4': [0], '178_5': [1]} | ['', 'played', 'charlton wins', 'drawn', 'millwall wins', 'charlton goals', 'millwall goals'] | [['the football league', '67', '11', '23', '33', '62', '111'], ['anglo - italian cup', '2', '1', '1', '0', '4', '3'], ['sub - total', '69', '12', '24', '33', '66', '114'], ['kent fa challenge cup finals', '18', '9', '5', '4', '36', '31'], ['london challenge cup', '1', '1', '0', '0', '1', '0'], ['football league jubilee fund', '2', '1', '1', '0', '2', '1'], ['london pfa charity fund', '5', '2', '1', '2', '7', '5']] |
jeff andretti | https://en.wikipedia.org/wiki/Jeff_Andretti | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1617211-2.html.csv | unique | the only year that jeff andretti drove a chevrolet was in 1992 . | {'scope': 'all', 'row': '3', 'col': '3', 'col_other': '1', 'criterion': 'equal', 'value': 'chevrolet', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'engine', 'chevrolet'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose engine record fuzzily matches to chevrolet .', 'tostr': 'filter_eq { all_rows ; engine ; chevrolet }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; engine ; chevrolet } }', 'tointer': 'select the rows whose engine record fuzzily matches to chevrolet . there is only one such row in the table .'}, {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'engine', 'chevrolet'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose engine record fuzzily matches to chevrolet .', 'tostr': 'filter_eq { all_rows ; engine ; chevrolet }'}, 'year'], 'result': '1992', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; engine ; chevrolet } ; year }'}, '1992'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; engine ; chevrolet } ; year } ; 1992 }', 'tointer': 'the year record of this unqiue row is 1992 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; engine ; chevrolet } } ; eq { hop { filter_eq { all_rows ; engine ; chevrolet } ; year } ; 1992 } } = true', 'tointer': 'select the rows whose engine record fuzzily matches to chevrolet . there is only one such row in the table . the year record of this unqiue row is 1992 .'} | and { only { filter_eq { all_rows ; engine ; chevrolet } } ; eq { hop { filter_eq { all_rows ; engine ; chevrolet } ; year } ; 1992 } } = true | select the rows whose engine record fuzzily matches to chevrolet . there is only one such row in the table . the year record of this unqiue row is 1992 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'engine_7': 7, 'chevrolet_8': 8, 'eq_3': 3, 'num_hop_2': 2, 'year_9': 9, '1992_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'engine_7': 'engine', 'chevrolet_8': 'chevrolet', 'eq_3': 'eq', 'num_hop_2': 'num_hop', 'year_9': 'year', '1992_10': '1992'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'engine_7': [0], 'chevrolet_8': [0], 'eq_3': [4], 'num_hop_2': [3], 'year_9': [2], '1992_10': [3]} | ['year', 'chassis', 'engine', 'start', 'finish'] | [['1990', 'lola', 'cosworth', 'failed to qualify', 'failed to qualify'], ['1991', 'lola', 'cosworth', '11th', '15th'], ['1992', 'lola', 'chevrolet', '20th', '18th'], ['1993', 'lola', 'buick', '16th', '29th'], ['1994', 'lola', 'buick', 'failed to qualify', 'failed to qualify']] |
patty schnyder | https://en.wikipedia.org/wiki/Patty_Schnyder | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1547798-2.html.csv | count | patty schynder played only two matches using a carpeted surface . | {'scope': 'all', 'criterion': 'equal', 'value': 'carpet ( i )', 'result': '2', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'surface', 'carpet ( i )'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose surface record fuzzily matches to carpet ( i ) .', 'tostr': 'filter_eq { all_rows ; surface ; carpet ( i ) }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; surface ; carpet ( i ) } }', 'tointer': 'select the rows whose surface record fuzzily matches to carpet ( i ) . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; surface ; carpet ( i ) } } ; 2 } = true', 'tointer': 'select the rows whose surface record fuzzily matches to carpet ( i ) . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; surface ; carpet ( i ) } } ; 2 } = true | select the rows whose surface record fuzzily matches to carpet ( i ) . 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, 'surface_5': 5, 'carpet (i)_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', 'surface_5': 'surface', 'carpet (i)_6': 'carpet ( i )', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'surface_5': [0], 'carpet (i)_6': [0], '2_7': [2]} | ['date', 'tournament', 'surface', 'opponent in the final', 'score'] | [['18 january 1998', 'hobart , australia', 'hard', 'dominique van roost', '6 - 3 , 6 - 2'], ['22 february 1998', 'hannover , germany', 'carpet ( i )', 'jana novotná', '6 - 0 , 3 - 6 , 7 - 5'], ['24 may 1998', 'madrid , spain', 'clay', 'dominique van roost', '3 - 6 , 6 - 4 , 6 - 0'], ['12 july 1998', 'maria lankowitz , austria', 'clay', 'gala león garcía', '6 - 2 , 4 - 6 , 6 - 3'], ['19 july 1998', 'palermo , italy', 'clay', 'barbara schett', '6 - 1 , 5 - 7 , 6 - 2'], ['10 january 1999', 'gold coast , australia', 'hard', 'mary pierce', '4 - 6 , 7 - 6 ( 5 ) , 6 - 2'], ['11 november 2001', 'pattaya city , thailand', 'hard', 'henrieta nagyová', '6 - 0 , 6 - 4'], ['20 october 2002', 'zürich , switzerland', 'carpet ( i )', 'lindsay davenport', '6 - 7 ( 5 ) , 7 - 6 ( 8 ) , 6 - 3'], ['8 january 2005', 'gold coast , australia', 'hard', 'samantha stosur', '1 - 6 , 6 - 3 , 7 - 5'], ['24 july 2005', 'cincinnati , usa', 'hard', 'akiko morigami', '6 - 4 , 6 - 0'], ['8 september 2008', 'bali , indonesia', 'hard', 'tamira paszek', '6 - 3 , 6 - 0']] |
list of schools in the wellington region | https://en.wikipedia.org/wiki/List_of_schools_in_the_Wellington_Region | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12214488-5.html.csv | majority | most of the schools in the wellington region are under state authority . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'state', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'authority', 'state'], 'result': True, 'ind': 0, 'tointer': 'for the authority records of all rows , most of them fuzzily match to state .', 'tostr': 'most_eq { all_rows ; authority ; state } = true'} | most_eq { all_rows ; authority ; state } = true | for the authority records of all rows , most of them fuzzily match to state . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'authority_3': 3, 'state_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'authority_3': 'authority', 'state_4': 'state'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'authority_3': [0], 'state_4': [0]} | ['name', 'years', 'gender', 'area', 'authority', 'decile', 'roll'] | [['kapanui school', '1 - 8', 'coed', 'waikanae', 'state', '8', '532'], ['kapiti college', '9 - 13', 'coed', 'raumati beach', 'state', '8', '1223'], ['kapiti school', '1 - 8', 'coed', 'paraparaumu', 'state', '5', '242'], ['kenakena school', '1 - 8', 'coed', 'paraparaumu beach', 'state', '8', '555'], ['otaki college', '7 - 13', 'coed', 'otaki', 'state', '4', '426'], ['otaki school', '1 - 6', 'coed', 'otaki', 'state', '3', '196'], ['paekakariki school', '1 - 8', 'coed', 'paekakariki', 'state', '7', '174'], ['paraparaumu beach school', '1 - 8', 'coed', 'paraparaumu beach', 'state', '9', '629'], ['paraparaumu college', '9 - 13', 'coed', 'paraparaumu', 'state', '8', '1215'], ['paraparaumu school', '1 - 8', 'coed', 'paraparaumu', 'state', '6', '164'], ['raumati beach school', '1 - 8', 'coed', 'raumati beach', 'state', '9', '655'], ['raumati south school', '1 - 8', 'coed', 'raumati south', 'state', '8', '418'], ["st patrick 's school", '1 - 8', 'coed', 'paraparaumu', 'integrated', '8', '121'], ['st peter chanel school', '1 - 8', 'coed', 'otaki', 'integrated', '3', '17'], ['te horo school', '1 - 6', 'coed', 'te horo', 'state', '9', '206'], ['te kura - a - iwi o whakatupuranga rua mano', '1 - 13', 'coed', 'otaki', 'state', '3', '158'], ['te ra school', '1 - 8', 'coed', 'raumati south', 'integrated', '9', '167'], ['tkkm o te rito', '1 - 13', 'coed', 'otaki', 'state', '3', '57'], ['waikanae school', '1 - 8', 'coed', 'waikanae', 'state', '8', '451'], ['waitohu school', '1 - 6', 'coed', 'otaki', 'state', '4', '254']] |
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