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eliseo salazar | https://en.wikipedia.org/wiki/Eliseo_Salazar | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1219773-2.html.csv | superlative | in 1989 eliseo salazar completed the highest number of laps in the 24 hours of le mans race than any other time he competed in that particular race . | {'scope': 'all', 'col_superlative': '6', 'row_superlative': '4', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'laps'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; laps }'}, 'year'], 'result': '1989', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; laps } ; year }'}, '1989'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; laps } ; year } ; 1989 } = true', 'tointer': 'select the row whose laps record of all rows is maximum . the year record of this row is 1989 .'} | eq { hop { argmax { all_rows ; laps } ; year } ; 1989 } = true | select the row whose laps record of all rows is maximum . the year record of this row is 1989 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'num_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'laps_5': 5, 'year_6': 6, '1989_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'num_hop_1': 'num_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'laps_5': 'laps', 'year_6': 'year', '1989_7': '1989'} | {'eq_2': [3], 'result_3': [], 'num_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'laps_5': [0], 'year_6': [1], '1989_7': [2]} | ['year', 'class', 'tyres', 'team', 'co - drivers', 'laps', 'pos', 'class pos'] | [['1982', 'c', 'd', 'dome co ltd', 'chris craft', '85', 'dnf', 'dnf'], ['1983', 'c', 'd', 'dome racing', 'chris craft nick mason', '75', 'dnf', 'dnf'], ['1988', 'c2', 'g', 'spice engineering', 'almo coppelli thorkild thyrring', '281', 'dnf', 'dnf'], ['1989', 'c1', 'd', 'silk cut jaguar tom walkinshaw racing', 'alain ferté michel ferté', '368', '8th', '7th'], ['1990', 'c1', 'g', 'silk cut jaguar tom walkinshaw racing', 'davy jones michel ferté', '282', 'dnf', 'dnf'], ['1997', 'lmp', 'p', 'pacific racing ltd', 'harri toivonen jesús pareja', '6', 'dnf', 'dnf']] |
2008 - 09 portland trail blazers season | https://en.wikipedia.org/wiki/2008%E2%80%9309_Portland_Trail_Blazers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17058178-8.html.csv | majority | the rose garden is where the portland trail blazers played the majority of their games in january , for the 2008-09 season . | {'scope': 'all', 'col': '7', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'rose garden', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'location attendance', 'rose garden'], 'result': True, 'ind': 0, 'tointer': 'for the location attendance records of all rows , most of them fuzzily match to rose garden .', 'tostr': 'most_eq { all_rows ; location attendance ; rose garden } = true'} | most_eq { all_rows ; location attendance ; rose garden } = true | for the location attendance records of all rows , most of them fuzzily match to rose garden . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'location attendance_3': 3, 'rose garden_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'location attendance_3': 'location attendance', 'rose garden_4': 'rose garden'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'location attendance_3': [0], 'rose garden_4': [0]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'location attendance', 'record'] | [['33', 'january 2', 'new orleans', 'l 77 - 92 ( ot )', 'rudy fernández ( 19 )', 'lamarcus aldridge ( 10 )', 'rose garden 20708', '20 - 13'], ['34', 'january 4', 'la lakers', 'l 86 - 100 ( ot )', 'lamarcus aldridge ( 22 )', 'lamarcus aldridge ( 11 )', 'staples center 18997', '20 - 14'], ['35', 'january 7', 'detroit', 'w 84 - 83 ( ot )', 'lamarcus aldridge ( 26 )', 'joel przybilla ( 7 )', 'rose garden 20644', '21 - 14'], ['36', 'january 10', 'golden state', 'w 113 - 100 ( ot )', 'lamarcus aldridge ( 26 )', 'greg oden ( 8 )', 'rose garden 20687', '22 - 14'], ['37', 'january 12', 'chicago', 'w 109 - 95 ( ot )', 'travis outlaw ( 33 )', 'greg oden ( 13 )', 'united center 18996', '23 - 14'], ['38', 'january 14', 'philadelphia', 'l 79 - 100 ( ot )', 'brandon roy ( 27 )', 'lamarcus aldridge , joel przybilla ( 9 )', 'wachovia center 14561', '23 - 15'], ['39', 'january 15', 'new jersey', 'w 105 - 99 ( ot )', 'brandon roy ( 29 )', 'joel przybilla ( 11 )', 'izod center 13824', '24 - 15'], ['40', 'january 17', 'charlotte', 'l 97 - 102 ( ot )', 'lamarcus aldridge ( 21 )', 'joel przybilla ( 10 )', 'time warner cable arena 17482', '24 - 16'], ['41', 'january 19', 'milwaukee', 'w 102 - 85 ( ot )', 'greg oden ( 24 )', 'greg oden ( 15 )', 'rose garden 20580', '25 - 16'], ['42', 'january 21', 'cleveland', 'l 98 - 104 ( ot )', 'brandon roy ( 23 )', 'joel przybilla ( 15 )', 'rose garden 20632', '25 - 17'], ['43', 'january 24', 'washington', 'w 100 - 87 ( ot )', 'brandon roy ( 22 )', 'greg oden ( 14 )', 'rose garden 20566', '26 - 17'], ['44', 'january 26', 'la clippers', 'w 113 - 88 ( ot )', 'brandon roy ( 33 )', 'joel przybilla ( 8 )', 'staples center 16570', '27 - 17'], ['45', 'january 28', 'charlotte', 'w 88 - 74 ( ot )', 'lamarcus aldridge ( 25 )', 'greg oden ( 14 )', 'rose garden 20380', '28 - 17'], ['46', 'january 31', 'utah', 'w 122 - 108 ( ot )', 'brandon roy ( 30 )', 'joel przybilla ( 17 )', 'rose garden 20593', '29 - 17']] |
1982 world series | https://en.wikipedia.org/wiki/1982_World_Series | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1218008-1.html.csv | aggregation | the average attendance for the 1982 world series was 54939 . | {'scope': 'all', 'col': '6', 'type': 'average', 'result': '54939', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'attendance'], 'result': '54939', 'ind': 0, 'tostr': 'avg { all_rows ; attendance }'}, '54939'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; attendance } ; 54939 } = true', 'tointer': 'the average of the attendance record of all rows is 54939 .'} | round_eq { avg { all_rows ; attendance } ; 54939 } = true | the average of the attendance record of all rows is 54939 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'attendance_4': 4, '54939_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'attendance_4': 'attendance', '54939_5': '54939'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'attendance_4': [0], '54939_5': [1]} | ['game', 'date', 'score', 'location', 'time', 'attendance'] | [['1', 'october 12', 'milwaukee brewers - 10 , st louis cardinals - 0', 'busch stadium ( ii )', '2:30', '53723'], ['2', 'october 13', 'milwaukee brewers - 4 , st louis cardinals - 5', 'busch stadium ( ii )', '2:54', '53723'], ['3', 'october 15', 'st louis cardinals - 6 , milwaukee brewers - 2', 'county stadium', '2:53', '56556'], ['4', 'october 16', 'st louis cardinals - 5 , milwaukee brewers - 7', 'county stadium', '3:04', '56560'], ['5', 'october 17', 'st louis cardinals - 4 , milwaukee brewers - 6', 'county stadium', '3:02', '56562'], ['6', 'october 19', 'milwaukee brewers - 1 , st louis cardinals - 13', 'busch stadium ( ii )', '2:21', '53723'], ['7', 'october 20', 'milwaukee brewers - 3 , st louis cardinals - 6', 'busch stadium ( ii )', '2:50', '53723']] |
united states house of representatives elections , 2010 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_2010 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-19753079-41.html.csv | unique | bob brady is the only candidate to be re-elected unopposed . | {'scope': 'all', 'row': '1', 'col': '6', 'col_other': '2', 'criterion': 'fuzzily_match', 'value': 'unopposed', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'candidates', 'unopposed'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose candidates record fuzzily matches to unopposed .', 'tostr': 'filter_eq { all_rows ; candidates ; unopposed }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; candidates ; unopposed } }', 'tointer': 'select the rows whose candidates record fuzzily matches to unopposed . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'candidates', 'unopposed'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose candidates record fuzzily matches to unopposed .', 'tostr': 'filter_eq { all_rows ; candidates ; unopposed }'}, 'incumbent'], 'result': 'bob brady', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; candidates ; unopposed } ; incumbent }'}, 'bob brady'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; candidates ; unopposed } ; incumbent } ; bob brady }', 'tointer': 'the incumbent record of this unqiue row is bob brady .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; candidates ; unopposed } } ; eq { hop { filter_eq { all_rows ; candidates ; unopposed } ; incumbent } ; bob brady } } = true', 'tointer': 'select the rows whose candidates record fuzzily matches to unopposed . there is only one such row in the table . the incumbent record of this unqiue row is bob brady .'} | and { only { filter_eq { all_rows ; candidates ; unopposed } } ; eq { hop { filter_eq { all_rows ; candidates ; unopposed } ; incumbent } ; bob brady } } = true | select the rows whose candidates record fuzzily matches to unopposed . there is only one such row in the table . the incumbent record of this unqiue row is bob brady . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'candidates_7': 7, 'unopposed_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'incumbent_9': 9, 'bob brady_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'candidates_7': 'candidates', 'unopposed_8': 'unopposed', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'incumbent_9': 'incumbent', 'bob brady_10': 'bob brady'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'candidates_7': [0], 'unopposed_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'incumbent_9': [2], 'bob brady_10': [3]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['pennsylvania 1', 'bob brady', 'democratic', '1998', 're - elected', 'bob brady ( d ) unopposed'], ['pennsylvania 2', 'chaka fattah', 'democratic', '1994', 're - elected', 'chaka fattah ( d ) 89.3 % rick hellberg ( r ) 10.7 %'], ['pennsylvania 3', 'kathy dahlkemper', 'democratic', '2008', 'lost re - election republican gain', 'mike kelly ( r ) 55.7 % kathy dahlkemper ( d ) 44.3 %'], ['pennsylvania 4', 'jason altmire', 'democratic', '2006', 're - elected', 'jason altmire ( d ) 50.8 % keith rothfuss ( r ) 49.2 %'], ['pennsylvania 6', 'jim gerlach', 'republican', '2002', 're - elected', 'jim gerlach ( r ) 57.1 % manan trivedi ( d ) 42.9 %'], ['pennsylvania 9', 'bill shuster', 'republican', '2001', 're - elected', 'bill shuster ( r ) 73.1 % tom conners ( d ) 26.9 %'], ['pennsylvania 10', 'chris carney', 'democratic', '2006', 'lost re - election republican gain', 'tom marino ( r ) 55.2 % chris carney ( d ) 44.8 %'], ['pennsylvania 11', 'paul kanjorski', 'democratic', '1984', 'lost re - election republican gain', 'lou barletta ( r ) 54.7 % paul kanjorski ( d ) 45.3 %'], ['pennsylvania 12', 'mark critz', 'democratic', '2010', 're - elected', 'mark critz ( d ) 50.8 % tim burns ( r ) 49.2 %'], ['pennsylvania 13', 'allyson schwartz', 'democratic', '2004', 're - elected', 'allyson schwartz ( d ) 56.3 % dee adcock ( r ) 43.7 %'], ['pennsylvania 16', 'joe pitts', 'republican', '1996', 're - elected', 'joe pitts ( r ) 65.4 % lois herr ( d ) 34.6 %'], ['pennsylvania 17', 'tim holden', 'democratic', '1992', 're - elected', 'tim holden ( d ) 55.5 % dave argall ( r ) 44.5 %']] |
no way out ( 2008 ) | https://en.wikipedia.org/wiki/No_Way_Out_%282008%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15325500-3.html.csv | unique | of all the contestants , triple h is the only contestant to have not been eliminated in wwe raw 's no way out in 2008 . | {'scope': 'all', 'row': '6', 'col': '4', 'col_other': '2', 'criterion': 'equal', 'value': 'n / a', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'eliminated by', 'n / a'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose eliminated by record fuzzily matches to n / a .', 'tostr': 'filter_eq { all_rows ; eliminated by ; n / a }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; eliminated by ; n / a } }', 'tointer': 'select the rows whose eliminated by record fuzzily matches to n / a . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'eliminated by', 'n / a'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose eliminated by record fuzzily matches to n / a .', 'tostr': 'filter_eq { all_rows ; eliminated by ; n / a }'}, 'wrestler'], 'result': 'triple h', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; eliminated by ; n / a } ; wrestler }'}, 'triple h'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; eliminated by ; n / a } ; wrestler } ; triple h }', 'tointer': 'the wrestler record of this unqiue row is triple h .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; eliminated by ; n / a } } ; eq { hop { filter_eq { all_rows ; eliminated by ; n / a } ; wrestler } ; triple h } } = true', 'tointer': 'select the rows whose eliminated by record fuzzily matches to n / a . there is only one such row in the table . the wrestler record of this unqiue row is triple h .'} | and { only { filter_eq { all_rows ; eliminated by ; n / a } } ; eq { hop { filter_eq { all_rows ; eliminated by ; n / a } ; wrestler } ; triple h } } = true | select the rows whose eliminated by record fuzzily matches to n / a . there is only one such row in the table . the wrestler record of this unqiue row is triple h . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'eliminated by_7': 7, 'n / a_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'wrestler_9': 9, 'triple h_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'eliminated by_7': 'eliminated by', 'n / a_8': 'n / a', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'wrestler_9': 'wrestler', 'triple h_10': 'triple h'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'eliminated by_7': [0], 'n / a_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'wrestler_9': [2], 'triple h_10': [3]} | ['eliminated', 'wrestler', 'entered', 'eliminated by', 'time'] | [['1', 'jbl', '4', 'jericho', '13:44'], ['2', 'umaga', '3', 'jericho', '19:45'], ['3', 'chris jericho', '1', 'hardy', '19:57'], ['4', 'shawn michaels', '2', 'triple h', '20:25'], ['5', 'jeff hardy', '6', 'triple h', '23:54'], ['winner', 'triple h', '5', 'n / a', 'n / a']] |
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 | count | joão sousa had a total of 9 wins across all editions . | {'scope': 'all', 'criterion': 'equal', 'value': 'win', 'result': '9', 'col': '7', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'w / l', 'win'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose w / l record fuzzily matches to win .', 'tostr': 'filter_eq { all_rows ; w / l ; win }'}], 'result': '9', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; w / l ; win } }', 'tointer': 'select the rows whose w / l record fuzzily matches to win . the number of such rows is 9 .'}, '9'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; w / l ; win } } ; 9 } = true', 'tointer': 'select the rows whose w / l record fuzzily matches to win . the number of such rows is 9 .'} | eq { count { filter_eq { all_rows ; w / l ; win } } ; 9 } = true | select the rows whose w / l record fuzzily matches to win . the number of such rows is 9 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'w / l_5': 5, 'win_6': 6, '9_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'w / l_5': 'w / l', 'win_6': 'win', '9_7': '9'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'w / l_5': [0], 'win_6': [0], '9_7': [2]} | ['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']] |
muhsin corbbrey | https://en.wikipedia.org/wiki/Muhsin_Corbbrey | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17624865-1.html.csv | aggregation | muhsin corbbrey 's fights lasted for a combined total of 37 rounds . | {'scope': 'all', 'col': '7', 'type': 'sum', 'result': '37', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'round'], 'result': '37', 'ind': 0, 'tostr': 'sum { all_rows ; round }'}, '37'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; round } ; 37 } = true', 'tointer': 'the sum of the round record of all rows is 37 .'} | round_eq { sum { all_rows ; round } ; 37 } = true | the sum of the round record of all rows is 37 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'round_4': 4, '37_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'round_4': 'round', '37_5': '37'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'round_4': [0], '37_5': [1]} | ['date', 'result', 'opponent', 'venue', 'location', 'method', 'round', 'time', 'record'] | [['2009 - 02 - 28', 'win', 'troy nelson', 'shoreline ball room', 'hilton head , south carolina , usa', 'decision', '6', '3:00', '6 - 2 - 1'], ['2006 - 09 - 15', 'win', 'ryan rayonec', 'omar shrine temple', 'mount pleasant , south carolina , usa', 'tko', '4', '0:54', '5 - 2 - 1'], ['2006 - 06 - 15', 'loss', 'tim coleman', "michael 's eighth avenue", 'glen burnie , maryland , usa', 'decision ( unanimous )', '6', '3:00', '4 - 2 - 1'], ['2006 - 04 - 21', 'win', 'shelton barnes', 'omar shrine temple', 'mount pleasant , south carolina , usa', 'tko', '1', '2:43', '4 - 1 - 1'], ['2006 - 03 - 09', 'win', 'kareem robinson', "michael 's eighth avenue", 'glen burnie , maryland , usa', 'decision ( unanimous )', '4', '3:00', '3 - 1 - 1'], ['2006 - 01 - 26', 'win', 'anthony abrams', "michael 's eighth avenue", 'glen burnie , maryland , usa', 'decision ( unanimous )', '4', '3:00', '2 - 1 - 1'], ['2005 - 11 - 26', 'win', 'ben lock', 'show place arena', 'upper marlboro , maryland , usa', 'decision ( unanimous )', '4', '3:00', '1 - 1 - 1'], ['2005 - 04 - 26', 'loss', 'emanuel gonzã ¡ lez', 'radisson hotel', 'miami , florida , usa', 'decision ( unanimous )', '4', '3:00', '0 - 1 - 1'], ['2005 - 04 - 08', 'draw', 'ricardo planter', 'club med sandpiper', 'port st lucie , florida , usa', 'draw ( majority )', '4', '3:00', '0 - 0 - 1']] |
world golf championships | https://en.wikipedia.org/wiki/World_Golf_Championships | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1458666-4.html.csv | comparative | south africa had more team wins in the world golf championships than northern ireland . | {'row_1': '4', 'row_2': '5', 'col': '3', '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', 'nation', 'south africa'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose nation record fuzzily matches to south africa .', 'tostr': 'filter_eq { all_rows ; nation ; south africa }'}, 'team wins'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; nation ; south africa } ; team wins }', 'tointer': 'select the rows whose nation record fuzzily matches to south africa . take the team wins record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'nation', 'northern ireland'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose nation record fuzzily matches to northern ireland .', 'tostr': 'filter_eq { all_rows ; nation ; northern ireland }'}, 'team wins'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; nation ; northern ireland } ; team wins }', 'tointer': 'select the rows whose nation record fuzzily matches to northern ireland . take the team wins record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; nation ; south africa } ; team wins } ; hop { filter_eq { all_rows ; nation ; northern ireland } ; team wins } } = true', 'tointer': 'select the rows whose nation record fuzzily matches to south africa . take the team wins record of this row . select the rows whose nation record fuzzily matches to northern ireland . take the team wins record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; nation ; south africa } ; team wins } ; hop { filter_eq { all_rows ; nation ; northern ireland } ; team wins } } = true | select the rows whose nation record fuzzily matches to south africa . take the team wins record of this row . select the rows whose nation record fuzzily matches to northern ireland . take the team wins 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, 'nation_7': 7, 'south africa_8': 8, 'team wins_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'nation_11': 11, 'northern ireland_12': 12, 'team wins_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', 'nation_7': 'nation', 'south africa_8': 'south africa', 'team wins_9': 'team wins', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'nation_11': 'nation', 'northern ireland_12': 'northern ireland', 'team wins_13': 'team wins'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'nation_7': [0], 'south africa_8': [0], 'team wins_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'nation_11': [1], 'northern ireland_12': [1], 'team wins_13': [3]} | ['nation', 'total wins', 'team wins', 'individual wins', 'individual winners'] | [['united states', '32', '1', '31', '12'], ['australia', '5', '0', '5', '3'], ['england', '5', '1', '4', '3'], ['south africa', '4', '2', '2', '1'], ['northern ireland', '2', '0', '2', '1'], ['germany', '2', '1', '1', '1'], ['canada', '1', '0', '1', '1'], ['fiji', '1', '0', '1', '1'], ['sweden', '1', '0', '1', '1'], ['italy', '1', '0', '1', '1'], ['japan', '1', '1', '0', '0'], ['wales', '1', '1', '0', '0']] |
television in italy | https://en.wikipedia.org/wiki/Television_in_Italy | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15887683-19.html.csv | majority | the majority of television services in italy provide programmi per adulti 24h / 24 content . | {'scope': 'all', 'col': '2', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'italy', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'country', 'italy'], 'result': True, 'ind': 0, 'tointer': 'for the country records of all rows , all of them fuzzily match to italy .', 'tostr': 'all_eq { all_rows ; country ; italy } = true'} | all_eq { all_rows ; country ; italy } = true | for the country records of all rows , all of them fuzzily match to italy . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'country_3': 3, 'italy_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'country_3': 'country', 'italy_4': 'italy'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'country_3': [0], 'italy_4': [0]} | ['television service', 'country', 'language', 'content', 'hdtv', 'package / option'] | [['contotv 1', 'italy', 'italian', 'general television', 'no', 'qualsiasi'], ['contotv 2', 'italy', 'italian', 'general television', 'no', 'qualsiasi'], ['contotv 3', 'italy', 'italian', 'general television', 'no', 'qualsiasi'], ['contotv 4', 'italy', 'italian', 'programmi per adulti 24h / 24', 'no', 'qualsiasi'], ['contotv 5', 'italy', 'italian', 'programmi per adulti 24h / 24', 'no', 'qualsiasi'], ['teleitalia', 'italy', 'italian', 'general television', 'no', 'qualsiasi ( fta )'], ['teleitalia spot', 'italy', 'italian', 'general television', 'no', 'qualsiasi ( fta )'], ['d - xtv', 'italy', 'italian', 'programmi per adulti 24h / 24', 'no', 'qualsiasi'], ['r - light', 'italy', 'italian', 'programmi per adulti 24h / 24', 'no', 'qualsiasi'], ['sct', 'italy', 'italian', 'programmi per adulti 24h / 24', 'no', 'qualsiasi'], ['boy & boy', 'italy', 'italian', 'programmi per adulti 24h / 24', 'no', 'qualsiasi'], ['privã', 'italy', 'italian', 'programmi per adulti 24h / 24', 'no', 'qualsiasi'], ['themex', 'italy', 'italian', 'programmi per adulti 24h / 24', 'no', 'qualsiasi'], ['satisfaction hd', 'italy', 'italian', 'programmi per adulti 24h / 24', 'yes', 'qualsiasi']] |
list of top association football goal scorers by country | https://en.wikipedia.org/wiki/List_of_top_association_football_goal_scorers_by_country | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1590321-78.html.csv | comparative | of the top association football goal scorers , yordanos abay scored 15 fewer goals than fathi jabir . | {'row_1': '5', 'row_2': '4', 'col': '4', 'col_other': '2', 'relation': 'diff', 'record_mentioned': 'no', 'diff_result': {'diff_value': '15', 'bigger': 'row2'}} | {'func': 'eq', 'args': [{'func': 'diff', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', 'yordanos abay'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose player record fuzzily matches to yordanos abay .', 'tostr': 'filter_eq { all_rows ; player ; yordanos abay }'}, 'goals'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; player ; yordanos abay } ; goals }', 'tointer': 'select the rows whose player record fuzzily matches to yordanos abay . take the goals record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', 'fathi jabir'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose player record fuzzily matches to fathi jabir .', 'tostr': 'filter_eq { all_rows ; player ; fathi jabir }'}, 'goals'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; player ; fathi jabir } ; goals }', 'tointer': 'select the rows whose player record fuzzily matches to fathi jabir . take the goals record of this row .'}], 'result': '-15', 'ind': 4, 'tostr': 'diff { hop { filter_eq { all_rows ; player ; yordanos abay } ; goals } ; hop { filter_eq { all_rows ; player ; fathi jabir } ; goals } }'}, '-15'], 'result': True, 'ind': 5, 'tostr': 'eq { diff { hop { filter_eq { all_rows ; player ; yordanos abay } ; goals } ; hop { filter_eq { all_rows ; player ; fathi jabir } ; goals } } ; -15 } = true', 'tointer': 'select the rows whose player record fuzzily matches to yordanos abay . take the goals record of this row . select the rows whose player record fuzzily matches to fathi jabir . take the goals record of this row . the second record is 15 larger than the first record .'} | eq { diff { hop { filter_eq { all_rows ; player ; yordanos abay } ; goals } ; hop { filter_eq { all_rows ; player ; fathi jabir } ; goals } } ; -15 } = true | select the rows whose player record fuzzily matches to yordanos abay . take the goals record of this row . select the rows whose player record fuzzily matches to fathi jabir . take the goals record of this row . the second record is 15 larger than the first record . | 6 | 6 | {'eq_5': 5, 'result_6': 6, 'diff_4': 4, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_7': 7, 'player_8': 8, 'yordanos abay_9': 9, 'goals_10': 10, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_11': 11, 'player_12': 12, 'fathi jabir_13': 13, 'goals_14': 14, '-15_15': 15} | {'eq_5': 'eq', 'result_6': 'true', 'diff_4': 'diff', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_7': 'all_rows', 'player_8': 'player', 'yordanos abay_9': 'yordanos abay', 'goals_10': 'goals', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_11': 'all_rows', 'player_12': 'player', 'fathi jabir_13': 'fathi jabir', 'goals_14': 'goals', '-15_15': '-15'} | {'eq_5': [6], 'result_6': [], 'diff_4': [5], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_7': [0], 'player_8': [0], 'yordanos abay_9': [0], 'goals_10': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_11': [1], 'player_12': [1], 'fathi jabir_13': [1], 'goals_14': [3], '-15_15': [5]} | ['rank', 'player', 'country', 'goals', 'years'] | [['1', 'ali al - nono', 'yemen', '146', "'99 -"], ['2', 'adel al - salimi', 'yemen', '136', "'97 - ' 11"], ['3', 'sharaf mahfood', 'yemen', '121', "'85 - ' 05"], ['4', 'fathi jabir', 'yemen', '108', "'97 - ' 08"], ['5', 'yordanos abay', 'ethiopia', '93', "'03 -"]] |
don freeland | https://en.wikipedia.org/wiki/Don_Freeland | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1236238-1.html.csv | aggregation | considering the participations of don freeland on indy 500 , on average he lasted in the race until the 164 lap . | {'scope': 'all', 'col': '6', 'type': 'average', 'result': '164', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'laps'], 'result': '164', 'ind': 0, 'tostr': 'avg { all_rows ; laps }'}, '164'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; laps } ; 164 } = true', 'tointer': 'the average of the laps record of all rows is 164 .'} | round_eq { avg { all_rows ; laps } ; 164 } = true | the average of the laps record of all rows is 164 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'laps_4': 4, '164_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'laps_4': 'laps', '164_5': '164'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'laps_4': [0], '164_5': [1]} | ['year', 'start', 'qual', 'rank', 'finish', 'laps'] | [['1953', '15', '136.867', '12', '27', '76'], ['1954', '6', '138.339', '17', '7', '200'], ['1955', '21', '139.866', '14', '15', '178'], ['1956', '26', '141.699', '22', '3', '200'], ['1957', '21', '139.649', '33', '17', '192'], ['1958', '13', '143.033', '17', '7', '200'], ['1959', '25', '143.056', '14', '22', '136'], ['1960', '11', '144.352', '14', '22', '129']] |
united states house of representatives elections , 2006 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_2006 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1805191-8.html.csv | comparative | nancy johnson has a first elected year which is earlier than that of chris shays . | {'row_1': '5', 'row_2': '4', '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', 'incumbent', 'nancy johnson'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose incumbent record fuzzily matches to nancy johnson .', 'tostr': 'filter_eq { all_rows ; incumbent ; nancy johnson }'}, 'first elected'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; incumbent ; nancy johnson } ; first elected }', 'tointer': 'select the rows whose incumbent record fuzzily matches to nancy johnson . take the first elected record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'incumbent', 'chris shays'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose incumbent record fuzzily matches to chris shays .', 'tostr': 'filter_eq { all_rows ; incumbent ; chris shays }'}, 'first elected'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; incumbent ; chris shays } ; first elected }', 'tointer': 'select the rows whose incumbent record fuzzily matches to chris shays . take the first elected record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; incumbent ; nancy johnson } ; first elected } ; hop { filter_eq { all_rows ; incumbent ; chris shays } ; first elected } } = true', 'tointer': 'select the rows whose incumbent record fuzzily matches to nancy johnson . take the first elected record of this row . select the rows whose incumbent record fuzzily matches to chris shays . take the first elected record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; incumbent ; nancy johnson } ; first elected } ; hop { filter_eq { all_rows ; incumbent ; chris shays } ; first elected } } = true | select the rows whose incumbent record fuzzily matches to nancy johnson . take the first elected record of this row . select the rows whose incumbent record fuzzily matches to chris shays . take the first elected record of this row . the first record is less than the second record . | 5 | 5 | {'less_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'incumbent_7': 7, 'nancy johnson_8': 8, 'first elected_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'incumbent_11': 11, 'chris shays_12': 12, 'first elected_13': 13} | {'less_4': 'less', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'incumbent_7': 'incumbent', 'nancy johnson_8': 'nancy johnson', 'first elected_9': 'first elected', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'incumbent_11': 'incumbent', 'chris shays_12': 'chris shays', 'first elected_13': 'first elected'} | {'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'incumbent_7': [0], 'nancy johnson_8': [0], 'first elected_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'incumbent_11': [1], 'chris shays_12': [1], 'first elected_13': [3]} | ['district', 'incumbent', 'party', 'first elected', 'results'] | [['connecticut 1', 'john larson', 'democratic', '1998', 're - elected'], ['connecticut 2', 'rob simmons', 'republican', '2000', 'lost re - election democratic gain'], ['connecticut 3', 'rosa delauro', 'democratic', '1990', 're - elected'], ['connecticut 4', 'chris shays', 'republican', '1987', 're - elected'], ['connecticut 5', 'nancy johnson', 'republican', '1982', 'lost re - election democratic gain']] |
rosi sexton | https://en.wikipedia.org/wiki/Rosi_Sexton | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18916132-2.html.csv | majority | the majority of rosi sexton 's mma fights ended in wins for rosi sexton . | {'scope': 'all', 'col': '1', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'win', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'res', 'win'], 'result': True, 'ind': 0, 'tointer': 'for the res records of all rows , most of them fuzzily match to win .', 'tostr': 'most_eq { all_rows ; res ; win } = true'} | most_eq { all_rows ; res ; win } = true | for the res records of all rows , most of them fuzzily match to win . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'res_3': 3, 'win_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'res_3': 'res', 'win_4': 'win'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'res_3': [0], 'win_4': [0]} | ['res', 'record', 'opponent', 'method', 'event', 'round', 'time', 'location'] | [['loss', '13 - 4', 'jessica andrade', 'decision ( unanimous )', 'ufc fight night : machida vs munoz', '3', '5:00', 'manchester , england'], ['loss', '13 - 3', 'alexis davis', 'decision ( unanimous )', 'ufc 161', '3', '5:00', 'winnipeg , manitoba , canada'], ['win', '13 - 2', 'aisling daly', 'decision ( unanimous )', 'cage warriors fighting championship 47', '3', '5:00', 'dublin , ireland'], ['win', '12 - 2', 'roxanne modafferi', 'decision ( unanimous )', 'cage warriors fighting championship 40', '3', '5:00', 'north london , england'], ['win', '11 - 2', 'sally krumdiack', 'tko ( punches )', 'cage warriors fighting championship 39', '2', '4:07', 'cork , ireland'], ['loss', '10 - 2', 'zoila frausto gurgel', 'ko ( knee and punches )', 'bellator 23', '1', '2:00', 'louisville , kentucky , united states'], ['win', '10 - 1', 'valerie coolbaugh', 'submission ( armbar )', 'bellator 12', '1', '3:40', 'hollywood , florida , united states'], ['win', '9 - 1', 'debi purcell', 'decision ( split )', 'shoxc : suganuma vs hamman ii', '3', '3:00', 'friant , california , united states'], ['win', '8 - 1', 'julia berezikova', 'submission ( armbar )', 'bodogfight - vancouver', '2', '1:49', 'vancouver , british columbia , canada'], ['win', '7 - 1', 'tomomi sunaba', 'technical decision ( unanimous )', 'bodogfight - costa rica', '2', '1:05', 'san josã , costa rica'], ['win', '6 - 1', 'carina damm', 'submission ( armbar )', 'bodogfight - st petersburg', '1', '4:15', 'saint petersburg , russia'], ['loss', '5 - 1', 'gina carano', 'ko ( punch )', 'world pro fighting championships', '2', '4:55', 'las vegas , nevada , united states'], ['win', '5 - 0', 'dina van den hooven', 'tko ( corner stoppage )', 'cwfc - strike force 4', '3', '5:00', 'english midlands , england'], ['win', '4 - 0', 'kelli salone', 'submission ( armbar )', 'p & g 1 - pride and glory 1', '1', '3:45', 'cardiff , wales'], ['win', '3 - 0', "carla o ' sullivan", 'submission ( rear - naked choke )', 'cwfc 3 - cage warriors 3', '1', 'n / a', 'hampshire , england'], ['win', '2 - 0', 'serena saunders', 'submission ( armbar )', 'cwfc 1 - armageddon', '1', '0:40', 'london , england'], ['win', '1 - 0', 'angela boyce', 'submission ( armbar )', 'g & s 5 - grapple & strike 5', '3', 'n / a', 'worcester , england']] |
2007 - 08 la liga | https://en.wikipedia.org/wiki/2007%E2%80%9308_La_Liga | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11834742-5.html.csv | majority | the majority of the averages are over 1 goal per match . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'greater_than', 'value': '1', 'subset': None} | {'func': 'most_greater', 'args': ['all_rows', 'average', '1'], 'result': True, 'ind': 0, 'tointer': 'for the average records of all rows , most of them are greater than 1 .', 'tostr': 'most_greater { all_rows ; average ; 1 } = true'} | most_greater { all_rows ; average ; 1 } = true | for the average records of all rows , most of them are greater than 1 . | 1 | 1 | {'most_greater_0': 0, 'result_1': 1, 'all_rows_2': 2, 'average_3': 3, '1_4': 4} | {'most_greater_0': 'most_greater', 'result_1': 'true', 'all_rows_2': 'all_rows', 'average_3': 'average', '1_4': '1'} | {'most_greater_0': [1], 'result_1': [], 'all_rows_2': [0], 'average_3': [0], '1_4': [0]} | ['goalkeeper', 'goals', 'matches', 'average', 'team'] | [['iker casillas', '32', '36', '0.89', 'real madrid'], ['víctor valdés', '35', '35', '1', 'fc barcelona'], ['toño', '31', '30', '1.03', 'racing de santander'], ['ricardo lópez felipe', '38', '36', '1.06', 'ca osasuna'], ['miguel ángel moyà', '34', '29', '1.17', 'rcd mallorca'], ['roberto abbondanzieri', '42', '34', '1.24', 'getafe cf'], ['carlos kameni', '38', '29', '1.31', 'rcd espanyol'], ['andrés palop', '41', '30', '1.37', 'sevilla fc'], ['stefano sorrentino', '60', '38', '1.58', 'recreativo de huelva'], ['césar sánchez', '56', '35', '1.6', 'zaragoza']] |
ivor bueb | https://en.wikipedia.org/wiki/Ivor_Bueb | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1233860-1.html.csv | count | ivor bueb competed in the british racing partnership twice between 1957 and 1959 . | {'scope': 'all', 'criterion': 'equal', 'value': 'british racing partnership', 'result': '2', 'col': '2', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'entrant', 'british racing partnership'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose entrant record fuzzily matches to british racing partnership .', 'tostr': 'filter_eq { all_rows ; entrant ; british racing partnership }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; entrant ; british racing partnership } }', 'tointer': 'select the rows whose entrant record fuzzily matches to british racing partnership . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; entrant ; british racing partnership } } ; 2 } = true', 'tointer': 'select the rows whose entrant record fuzzily matches to british racing partnership . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; entrant ; british racing partnership } } ; 2 } = true | select the rows whose entrant record fuzzily matches to british racing partnership . 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, 'entrant_5': 5, 'british racing partnership_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', 'entrant_5': 'entrant', 'british racing partnership_6': 'british racing partnership', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'entrant_5': [0], 'british racing partnership_6': [0], '2_7': [2]} | ['year', 'entrant', 'chassis', 'engine', 'points'] | [['1957', 'connaught engineering', 'connaught type b', 'alta straight - 4', '0'], ['1957', 'gilby engineering ltd', 'maserati 250f', 'maserati straight - 6', '0'], ['1958', 'bc ecclestone', 'connaught type b', 'alta straight - 4', '0'], ['1958', 'ecurie demi litre', 'lotus 12', 'climax straight - 4', '0'], ['1959', 'british racing partnership', 'cooper t51', 'climax straight - 4', '0'], ['1959', 'british racing partnership', 'cooper t51', 'borgward straight - 4', '0']] |
1980 - 81 segunda división | https://en.wikipedia.org/wiki/1980%E2%80%9381_Segunda_Divisi%C3%B3n | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12189375-2.html.csv | count | there are 4 clubs with 15 draws in the 1980-81 segunda division . | {'scope': 'all', 'criterion': 'equal', 'value': '15', 'result': '4', 'col': '6', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'draws', '15'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose draws record is equal to 15 .', 'tostr': 'filter_eq { all_rows ; draws ; 15 }'}], 'result': '4', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; draws ; 15 } }', 'tointer': 'select the rows whose draws record is equal to 15 . the number of such rows is 4 .'}, '4'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; draws ; 15 } } ; 4 } = true', 'tointer': 'select the rows whose draws record is equal to 15 . the number of such rows is 4 .'} | eq { count { filter_eq { all_rows ; draws ; 15 } } ; 4 } = true | select the rows whose draws record is equal to 15 . the number of such rows is 4 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_eq_0': 0, 'all_rows_4': 4, 'draws_5': 5, '15_6': 6, '4_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'draws_5': 'draws', '15_6': '15', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'draws_5': [0], '15_6': [0], '4_7': [2]} | ['position', 'club', 'played', 'points', 'wins', 'draws', 'losses', 'goals for', 'goals against', 'goal difference'] | [['1', 'cd castellón', '38', '45 + 7', '15', '15', '8', '45', '33', '+ 12'], ['2', 'cádiz cf', '38', '45 + 7', '19', '7', '12', '55', '37', '+ 18'], ['3', 'racing de santander', '38', '45 + 7', '18', '9', '11', '48', '40', '+ 8'], ['4', 'elche cf', '38', '45 + 7', '17', '11', '10', '55', '44', '+ 11'], ['5', 'rayo vallecano', '38', '45 + 7', '15', '15', '8', '37', '23', '+ 14'], ['6', 'cd málaga', '38', '42 + 4', '14', '14', '10', '47', '45', '+ 2'], ['7', 'ce sabadell fc', '38', '42 + 4', '16', '10', '12', '45', '44', '+ 1'], ['8', 'deportivo alavés', '38', '39 + 1', '15', '9', '14', '49', '35', '+ 14'], ['9', 'levante ud', '38', '38', '15', '8', '15', '36', '37', '- 1'], ['10', 'real oviedo', '38', '37 - 1', '11', '15', '12', '37', '39', '- 2'], ['11', 'castilla cf', '38', '36 - 2', '14', '8', '16', '50', '44', '+ 6'], ['12', 'linares', '38', '36 - 2', '13', '10', '15', '36', '42', '- 6'], ['13', 'getafe deportivo', '38', '35 - 3', '10', '15', '13', '41', '50', '- 9'], ['14', 'atlético madrileño', '38', '35 - 3', '13', '9', '16', '44', '55', '- 11'], ['15', 'burgos', '38', '35 - 3', '13', '9', '16', '47', '52', '- 5'], ['16', 'recreativo de huelva', '38', '35 - 3', '12', '11', '15', '33', '37', '- 4'], ['17', 'granada cf', '38', '33 - 5', '10', '13', '15', '33', '45', '- 12'], ['18', 'palencia cf', '38', '32 - 6', '12', '8', '18', '30', '37', '- 7'], ['19', 'barakaldo cf', '38', '31 - 7', '11', '9', '18', '34', '46', '- 12'], ['20', 'agd ceuta', '38', '29 - 9', '11', '7', '20', '33', '50', '- 17']] |
presidents ' athletic conference | https://en.wikipedia.org/wiki/Presidents%27_Athletic_Conference | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-262476-1.html.csv | superlative | the institution with the largest enrollment in the presidents ' athletic conference is grove city college . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '4', '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', 'enrollment'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; enrollment }'}, 'institution'], 'result': 'grove city college', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; enrollment } ; institution }'}, 'grove city college'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; enrollment } ; institution } ; grove city college } = true', 'tointer': 'select the row whose enrollment record of all rows is maximum . the institution record of this row is grove city college .'} | eq { hop { argmax { all_rows ; enrollment } ; institution } ; grove city college } = true | select the row whose enrollment record of all rows is maximum . the institution record of this row is grove city college . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'enrollment_5': 5, 'institution_6': 6, 'grove city college_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'enrollment_5': 'enrollment', 'institution_6': 'institution', 'grove city college_7': 'grove city college'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'enrollment_5': [0], 'institution_6': [1], 'grove city college_7': [2]} | ['institution', 'location', 'nickname', 'founded', 'enrollment', 'joined'] | [['bethany college', 'bethany , west virginia', 'bison', '1840', '1030', '1958'], ['chatham university', 'pittsburgh , pennsylvania', 'cougars', '1869', '2300', '2007'], ['geneva college', 'beaver falls , pennsylvania', 'golden tornadoes', '1848', '1791', '2007'], ['grove city college', 'grove city , pennsylvania', 'wolverines', '1876', '2500', '1984'], ['saint vincent college', 'latrobe , pennsylvania', 'bearcats', '1846', '1652', '2006'], ['thiel college', 'greenville , pennsylvania', 'tomcats', '1866', '1066', '1958'], ['thomas more college', 'crestview hills , kentucky', 'saints', '1921', '1900', '2005'], ['washington & jefferson college', 'washington , pennsylvania', 'presidents', '1781', '1519', '1958'], ['waynesburg university', 'waynesburg , pennsylvania', 'yellow jackets', '1849', '1500', '1990']] |
list of v ( 2009 tv series ) episodes | https://en.wikipedia.org/wiki/List_of_V_%282009_TV_series%29_episodes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-24938621-2.html.csv | aggregation | for episodes of the 2009 tv series v , the average us viewers ( in millions ) for episodes that originally aired in 2009 was 9.74 . | {'scope': 'subset', 'col': '7', 'type': 'average', 'result': '9.74', 'subset': {'col': '5', 'criterion': 'less_than', 'value': 'january 1 , 2010'}} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'original air date', 'january 1 , 2010'], 'result': None, 'ind': 0, 'tostr': 'filter_less { all_rows ; original air date ; january 1 , 2010 }', 'tointer': 'select the rows whose original air date record is less than january 1 , 2010 .'}, 'us viewers ( million )'], 'result': '9.74', 'ind': 1, 'tostr': 'avg { filter_less { all_rows ; original air date ; january 1 , 2010 } ; us viewers ( million ) }'}, '9.74'], 'result': True, 'ind': 2, 'tostr': 'round_eq { avg { filter_less { all_rows ; original air date ; january 1 , 2010 } ; us viewers ( million ) } ; 9.74 } = true', 'tointer': 'select the rows whose original air date record is less than january 1 , 2010 . the average of the us viewers ( million ) record of these rows is 9.74 .'} | round_eq { avg { filter_less { all_rows ; original air date ; january 1 , 2010 } ; us viewers ( million ) } ; 9.74 } = true | select the rows whose original air date record is less than january 1 , 2010 . the average of the us viewers ( million ) record of these rows is 9.74 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'avg_1': 1, 'filter_less_0': 0, 'all_rows_4': 4, 'original air date_5': 5, 'january 1, 2010_6': 6, 'us viewers (million)_7': 7, '9.74_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'avg_1': 'avg', 'filter_less_0': 'filter_less', 'all_rows_4': 'all_rows', 'original air date_5': 'original air date', 'january 1, 2010_6': 'january 1 , 2010', 'us viewers (million)_7': 'us viewers ( million )', '9.74_8': '9.74'} | {'eq_2': [3], 'result_3': [], 'avg_1': [2], 'filter_less_0': [1], 'all_rows_4': [0], 'original air date_5': [0], 'january 1, 2010_6': [0], 'us viewers (million)_7': [1], '9.74_8': [2]} | ['no', 'title', 'directed by', 'written by', 'original air date', 'production code', 'us viewers ( million )'] | [['2', 'there is no normal anymore', 'yves simoneau', 'scott peters & sam egan', 'november 10 , 2009', '3x5401', '10.70'], ['3', 'a bright new day', 'frederick e o toye', 'diego gutierrez & christine roum', 'november 17 , 2009', '3x5402', '9.32'], ['4', "it 's only the beginning", 'yves simoneau', 'cameron litvack & angela russo otstot', 'november 24 , 2009', '3x5403', '9.20'], ['5', 'welcome to the war', 'yves simoneau', 'scott rosenbaum', 'march 30 , 2010', '3x5404', '7.03'], ['6', 'pound of flesh', 'dean white', 'charles murray & natalie chaidez', 'april 6 , 2010', '3x5405', '5.79'], ['7', 'john may', 'jonathan frakes', 'gregg hurwitz', 'april 13 , 2010', '3x5406', '5.61'], ['8', "we ca n't win", 'david barrett', 'christine roum & cameron litvack', 'april 20 , 2010', '3x5407', '5.81'], ['9', "heretic 's fork", 'frederick e o toye', 'john wirth & angela russo otstot', 'april 27 , 2010', '3x5408', '4.87'], ['10', 'hearts and minds', 'bobby roth', 'gregg hurwitz', 'may 4 , 2010', '3x5409', '5.37'], ['11', 'fruition', 'bryan spicer', 'john wirth & natalie chaidez', 'may 11 , 2010', '3x5410', '5.69']] |
2006 - 07 tottenham hotspur f.c. season | https://en.wikipedia.org/wiki/2006%E2%80%9307_Tottenham_Hotspur_F.C._season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17583318-4.html.csv | aggregation | the players in the 2006 - 07 tottenham hotspur f.c. season had an average total of 51 appearances . | {'scope': 'all', 'col': '7', 'type': 'average', 'result': '51', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'total'], 'result': '51', 'ind': 0, 'tostr': 'avg { all_rows ; total }'}, '51'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; total } ; 51 } = true', 'tointer': 'the average of the total record of all rows is 51 .'} | round_eq { avg { all_rows ; total } ; 51 } = true | the average of the total record of all rows is 51 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'total_4': 4, '51_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'total_4': 'total', '51_5': '51'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'total_4': [0], '51_5': [1]} | ['player', 'position', 'premier league', 'fa cup', 'league cup', 'uefa cup', 'total'] | [['michael dawson', 'defender', '37', '6', '4', '10', '57'], ['paul robinson', 'goalkeeper', '38', '4', '3', '9', '54'], ['pascal chimbonda', 'defender', '33', '4', '4', '10', '51'], ['jermain defoe', 'forward', '33', '5', '5', '5', '48'], ['robbie keane', 'forward', '27', '5', '3', '9', '44']] |
2007 - 08 phoenix suns season | https://en.wikipedia.org/wiki/2007%E2%80%9308_Phoenix_Suns_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11965574-5.html.csv | ordinal | the 10 january 2008 game had the third highest location attendance . | {'row': '6', 'col': '7', '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', 'location attendance', '3'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; location attendance ; 3 }'}, 'date'], 'result': '10 january 2008', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; location attendance ; 3 } ; date }'}, '10 january 2008'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; location attendance ; 3 } ; date } ; 10 january 2008 } = true', 'tointer': 'select the row whose location attendance record of all rows is 3rd maximum . the date record of this row is 10 january 2008 .'} | eq { hop { nth_argmax { all_rows ; location attendance ; 3 } ; date } ; 10 january 2008 } = true | select the row whose location attendance record of all rows is 3rd maximum . the date record of this row is 10 january 2008 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'location attendance_5': 5, '3_6': 6, 'date_7': 7, '10 january 2008_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', 'location attendance_5': 'location attendance', '3_6': '3', 'date_7': 'date', '10 january 2008_8': '10 january 2008'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'location attendance_5': [0], '3_6': [0], 'date_7': [1], '10 january 2008_8': [2]} | ['date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record'] | [['date', 'visitor', 'score', 'home', 'ot', 'leading scorer', 'attendance', 'record'], ['3 january 2008', 'supersonics', '96 - 104', 'suns', 'na', "amar ' e stoudemire ( 34 )", '18422', '23 - 9'], ['5 january 2008', 'hornets', '118 - 113', 'suns', 'na', 'leandro barbosa ( 28 )', '18422', '23 - 10'], ['7 january 2008', 'nuggets', '115 - 137', 'suns', 'na', 'shawn marion ( 27 )', '18422', '24 - 10'], ['9 january 2008', 'pacers', '122 - 129', 'suns', '1', 'two - way tie ( 27 )', '18422', '25 - 10'], ['10 january 2008', 'suns', '86 - 108', 'jazz', 'na', 'leandro barbosa ( 25 )', '19911', '25 - 11'], ['12 january 2008', 'bucks', '114 - 122', 'suns', 'na', 'steve nash ( 35 )', '18422', '26 - 11'], ['15 january 2008', 'suns', '90 - 97', 'clippers', 'na', "amar ' e stoudemire ( 29 )", '16063', '26 - 12'], ['17 january 2008', 'suns', '106 - 98', 'lakers', 'na', 'leandro barbosa ( 22 )', '18997', '27 - 12'], ['18 january 2008', 'timberwolves', '95 - 115', 'suns', 'na', "amar ' e stoudemire ( 23 )", '18422', '28 - 12'], ['20 january 2008', 'nets', '92 - 116', 'suns', 'na', "amar ' e stoudemire ( 28 )", '18422', '29 - 12'], ['22 january 2008', 'suns', '114 - 105', 'bucks', 'na', 'steve nash ( 37 )', '14503', '30 - 12'], ['23 january 2008', 'suns', '107 - 117', 'timberwolves', 'na', "amar ' e stoudemire ( 33 )", '15101', '30 - 13'], ['25 january 2008', 'suns', '110 - 108', 'cavaliers', 'na', 'raja bell ( 27 )', '20562', '31 - 13'], ['27 january 2008', 'suns', '88 - 77', 'bulls', 'na', "amar ' e stoudemire ( 24 )", '22245', '32 - 13'], ['29 january 2008', 'hawks', '92 - 125', 'suns', 'na', "amar ' e stoudemire ( 24 )", '18422', '33 - 13'], ['31 january 2008', 'spurs', '84 - 81', 'suns', 'na', 'shawn marion ( 21 )', '18422', '33 - 14']] |
2007 - 08 cleveland cavaliers season | https://en.wikipedia.org/wiki/2007%E2%80%9308_Cleveland_Cavaliers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11960713-4.html.csv | unique | in the 2007 - 08 cleveland cavaliers season , when lebron james was the leading scorer , the only time the attendance was under 15000 was on february 20 . | {'scope': 'subset', 'row': '9', 'col': '6', 'col_other': '1', 'criterion': 'less_than', 'value': '15000', 'subset': {'col': '5', 'criterion': 'fuzzily_match', 'value': 'lebron james'}} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_less', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'leading scorer', 'lebron james'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; leading scorer ; lebron james }', 'tointer': 'select the rows whose leading scorer record fuzzily matches to lebron james .'}, 'attendance', '15000'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose leading scorer record fuzzily matches to lebron james . among these rows , select the rows whose attendance record is less than 15000 .', 'tostr': 'filter_less { filter_eq { all_rows ; leading scorer ; lebron james } ; attendance ; 15000 }'}], 'result': True, 'ind': 2, 'tostr': 'only { filter_less { filter_eq { all_rows ; leading scorer ; lebron james } ; attendance ; 15000 } }', 'tointer': 'select the rows whose leading scorer record fuzzily matches to lebron james . among these rows , select the rows whose attendance record is less than 15000 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_less', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'leading scorer', 'lebron james'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; leading scorer ; lebron james }', 'tointer': 'select the rows whose leading scorer record fuzzily matches to lebron james .'}, 'attendance', '15000'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose leading scorer record fuzzily matches to lebron james . among these rows , select the rows whose attendance record is less than 15000 .', 'tostr': 'filter_less { filter_eq { all_rows ; leading scorer ; lebron james } ; attendance ; 15000 }'}, 'date'], 'result': 'february 20', 'ind': 3, 'tostr': 'hop { filter_less { filter_eq { all_rows ; leading scorer ; lebron james } ; attendance ; 15000 } ; date }'}, 'february 20'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { filter_less { filter_eq { all_rows ; leading scorer ; lebron james } ; attendance ; 15000 } ; date } ; february 20 }', 'tointer': 'the date record of this unqiue row is february 20 .'}], 'result': True, 'ind': 5, 'tostr': 'and { only { filter_less { filter_eq { all_rows ; leading scorer ; lebron james } ; attendance ; 15000 } } ; eq { hop { filter_less { filter_eq { all_rows ; leading scorer ; lebron james } ; attendance ; 15000 } ; date } ; february 20 } } = true', 'tointer': 'select the rows whose leading scorer record fuzzily matches to lebron james . among these rows , select the rows whose attendance record is less than 15000 . there is only one such row in the table . the date record of this unqiue row is february 20 .'} | and { only { filter_less { filter_eq { all_rows ; leading scorer ; lebron james } ; attendance ; 15000 } } ; eq { hop { filter_less { filter_eq { all_rows ; leading scorer ; lebron james } ; attendance ; 15000 } ; date } ; february 20 } } = true | select the rows whose leading scorer record fuzzily matches to lebron james . among these rows , select the rows whose attendance record is less than 15000 . there is only one such row in the table . the date record of this unqiue row is february 20 . | 8 | 6 | {'and_5': 5, 'result_6': 6, 'only_2': 2, 'filter_less_1': 1, 'filter_str_eq_0': 0, 'all_rows_7': 7, 'leading scorer_8': 8, 'lebron james_9': 9, 'attendance_10': 10, '15000_11': 11, 'str_eq_4': 4, 'str_hop_3': 3, 'date_12': 12, 'february 20_13': 13} | {'and_5': 'and', 'result_6': 'true', 'only_2': 'only', 'filter_less_1': 'filter_less', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_7': 'all_rows', 'leading scorer_8': 'leading scorer', 'lebron james_9': 'lebron james', 'attendance_10': 'attendance', '15000_11': '15000', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'date_12': 'date', 'february 20_13': 'february 20'} | {'and_5': [6], 'result_6': [], 'only_2': [5], 'filter_less_1': [2, 3], 'filter_str_eq_0': [1], 'all_rows_7': [0], 'leading scorer_8': [0], 'lebron james_9': [0], 'attendance_10': [1], '15000_11': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'date_12': [3], 'february 20_13': [4]} | ['date', 'visitor', 'score', 'home', 'leading scorer', 'attendance', 'record'] | [['february 2', 'la clippers', '98 - 84', 'cleveland', 'lebron james ( 28 )', '20562', '26 - 20'], ['february 5', 'boston', '114 - 113', 'cleveland', 'lebron james ( 33 )', '20562', '27 - 20'], ['february 7', 'cleveland', '77 - 92', 'houston', 'lebron james ( 32 )', '18402', '27 - 21'], ['february 8', 'cleveland', '100 - 95', 'atlanta', 'lebron james ( 26 )', '19335', '28 - 21'], ['february 10', 'denver', '83 - 113', 'cleveland', 'lebron james ( 30 )', '20562', '28 - 22'], ['february 11', 'cleveland', '118 - 111', 'orlando', 'larry hughes ( 40 )', '17519', '29 - 22'], ['february 13', 'san antonio', '105 - 112', 'cleveland', 'lebron james ( 39 )', '20562', '29 - 23'], ['february 19', 'houston', '85 - 93', 'cleveland', 'lebron james ( 26 )', '20562', '29 - 24'], ['february 20', 'cleveland', '106 - 97', 'indiana', 'lebron james ( 31 )', '13096', '30 - 24'], ['february 22', 'washington', '90 - 89', 'cleveland', 'lebron james ( 33 )', '20562', '31 - 24'], ['february 24', 'memphis', '109 - 89', 'cleveland', 'lebron james ( 25 )', '20562', '32 - 24'], ['february 26', 'cleveland', '102 - 105', 'milwaukee', 'lebron james ( 35 )', '15346', '32 - 25'], ['february 27', 'cleveland', '87 - 92', 'boston', 'lebron james ( 26 )', '18624', '32 - 26'], ['february 29', 'minnesota', '92 - 84', 'cleveland', 'lebron james ( 30 )', '20562', '33 - 26']] |
northern europe | https://en.wikipedia.org/wiki/Northern_Europe | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-159865-1.html.csv | aggregation | the average area of countries in northern europe is 110,129 km square . | {'scope': 'all', 'col': '2', 'type': 'average', 'result': '110,129', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'area ( km square )'], 'result': '110,129', 'ind': 0, 'tostr': 'avg { all_rows ; area ( km square ) }'}, '110,129'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; area ( km square ) } ; 110,129 } = true', 'tointer': 'the average of the area ( km square ) record of all rows is 110,129 .'} | round_eq { avg { all_rows ; area ( km square ) } ; 110,129 } = true | the average of the area ( km square ) record of all rows is 110,129 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'area (km square)_4': 4, '110,129_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'area (km square)_4': 'area ( km square )', '110,129_5': '110,129'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'area (km square)_4': [0], '110,129_5': [1]} | ['country', 'area ( km square )', 'population ( 2011 est )', 'population density ( per km square )', 'gdp ( ppp ) m usd'] | [['country', 'area ( km square )', 'population ( 2011 est )', 'population density ( per km square )', 'gdp ( ppp ) m usd'], ['åland ( finland )', '1527', '28007', '18.1', '( finland )'], ['denmark', '43098', '5564219', '129', '204060'], ['faroe islands ( denmark )', '1399', '48917', '35.0', '( denmark )'], ['estonia', '45227', '1 286 479', '29', '29.944'], ['finland', '336897', '5374781', '16', '190862'], ['guernsey d', '78', '65573', '836.3', '2742'], ['iceland', '103001', '318452', '3.1', '12664'], ['ireland', '70273', '4581269', '65.2', '188112'], ['isle of man d', '572', '80085', '140', '2719'], ['jersey d', '116', '92500', '797', '5100'], ['latvia', '64589', '2067900', '34.3', '38764'], ['lithuania', '65200', '3221216', '50.3', '63625'], ['norway', '385252', '4905200', '15.1', '256523'], ['svalbard and jan mayen islands ( norway )', '61395', '2572', '0.042', '( norway )'], ['sweden', '449964', '9354462', '20.6', '381.719'], ['united kingdom', '243610', '62008048', '254.7', '2256830'], ['total', '1811176', '99230679', '54.8 / km square', '3591077']] |
1996 - 97 european challenge cup | https://en.wikipedia.org/wiki/1996%E2%80%9397_European_Challenge_Cup | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-16770037-3.html.csv | superlative | castres olympique was the best team playing at the european challenge cup in 96-97 . | {'scope': 'all', 'col_superlative': '12', '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', 'pts'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; pts }'}, 'team'], 'result': 'castres olympique', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; pts } ; team }'}, 'castres olympique'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; pts } ; team } ; castres olympique } = true', 'tointer': 'select the row whose pts record of all rows is maximum . the team record of this row is castres olympique .'} | eq { hop { argmax { all_rows ; pts } ; team } ; castres olympique } = true | select the row whose pts record of all rows is maximum . the team record of this row is castres olympique . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'pts_5': 5, 'team_6': 6, 'castres olympique_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'pts_5': 'pts', 'team_6': 'team', 'castres olympique_7': 'castres olympique'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'pts_5': [0], 'team_6': [1], 'castres olympique_7': [2]} | ['team', 'p', 'w', 'd', 'l', 'tries for', 'tries against', 'try diff', 'points for', 'points against', 'points diff', 'pts'] | [['castres olympique', '5', '5', '0', '0', '29', '6', '+ 23', '207', '71', '+ 136', '10'], ['narbonne', '5', '4', '0', '1', '21', '6', '+ 15', '161', '90', '+ 71', '8'], ['dinamo - bucureşti', '5', '2', '1', '2', '12', '32', '20', '109', '213', '104', '5'], ['bridgend', '4', '1', '1', '2', '10', '14', '4', '94', '120', '26', '3'], ['bristol shoguns', '5', '1', '0', '4', '11', '12', '1', '128', '99', '+ 29', '2'], ['treorchy', '4', '0', '0', '4', '10', '23', '13', '72', '178', '106', '0']] |
1983 - 84 houston rockets season | https://en.wikipedia.org/wiki/1983%E2%80%9384_Houston_Rockets_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17383465-1.html.csv | superlative | james campbell had the highest number of picks over the others . | {'scope': 'all', 'col_superlative': '2', 'row_superlative': '9', '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', 'pick'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; pick }'}, 'player'], 'result': 'james campbell', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; pick } ; player }'}, 'james campbell'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; pick } ; player } ; james campbell } = true', 'tointer': 'select the row whose pick record of all rows is maximum . the player record of this row is james campbell .'} | eq { hop { argmax { all_rows ; pick } ; player } ; james campbell } = true | select the row whose pick record of all rows is maximum . the player record of this row is james campbell . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'pick_5': 5, 'player_6': 6, 'james campbell_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'pick_5': 'pick', 'player_6': 'player', 'james campbell_7': 'james campbell'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'pick_5': [0], 'player_6': [1], 'james campbell_7': [2]} | ['round', 'pick', 'player', 'nationality', 'college'] | [['1', '1', 'ralph sampson', 'united states', 'virginia'], ['1', '3', 'rodney mccray', 'united states', 'louisville'], ['3', '48', 'craig ehlo', 'united states', 'washington state'], ['4', '71', 'darrell browder', 'united states', 'texas christian'], ['5', '94', 'chuck barnett', 'united states', 'oklahoma'], ['6', '117', 'jim stack', 'united states', 'northwestern'], ['7', '140', 'brian kellerman', 'united states', 'idaho'], ['8', '163', 'jeff bolding', 'united states', 'arkansas state'], ['9', '185', 'james campbell', 'united states', 'oklahoma city']] |
indiana high school athletics conferences : ohio river valley - western indiana | https://en.wikipedia.org/wiki/Indiana_High_School_Athletics_Conferences%3A_Ohio_River_Valley_%E2%80%93_Western_Indiana | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18974097-16.html.csv | superlative | northview school had the highest student enrollment of high schools in the ohio river valley - western indiana conference . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '3', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'enrollment'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; enrollment }'}, 'school'], 'result': 'northview', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; enrollment } ; school }'}, 'northview'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; enrollment } ; school } ; northview } = true', 'tointer': 'select the row whose enrollment record of all rows is maximum . the school record of this row is northview .'} | eq { hop { argmax { all_rows ; enrollment } ; school } ; northview } = true | select the row whose enrollment record of all rows is maximum . the school record of this row is northview . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'enrollment_5': 5, 'school_6': 6, 'northview_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'enrollment_5': 'enrollment', 'school_6': 'school', 'northview_7': 'northview'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'enrollment_5': [0], 'school_6': [1], 'northview_7': [2]} | ['school', 'location', 'mascot', 'enrollment', 'ihsaa class', 'ihsaa football class', 'county'] | [['brown county', 'nashville', 'eagles', '755', 'aaa', 'aaa', '7 brown'], ['edgewood', 'ellettsville', 'mustangs', '833', 'aaa', 'aaa', '53 monroe'], ['northview', 'brazil', 'knights', '1142', 'aaaa', 'aaaa', '11 clay'], ['owen valley', 'spencer', 'patriots', '908', 'aaa', 'aaaa', '60 owen'], ['south vermillion', 'clinton', 'wildcats', '583', 'aaa', 'aa', '83 vermillion'], ['sullivan', 'sullivan', 'golden arrows', '543', 'aaa', 'aa', '77 sullivan'], ['west vigo', 'west terre haute', 'vikings', '640', 'aaa', 'aaa', '84 vigo']] |
2008 in canadian music | https://en.wikipedia.org/wiki/2008_in_Canadian_music | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18382316-1.html.csv | majority | the majority of 2008 canadian albums had a certification of platinum . | {'scope': 'all', 'col': '6', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'platinum', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'certification', 'platinum'], 'result': True, 'ind': 0, 'tointer': 'for the certification records of all rows , most of them fuzzily match to platinum .', 'tostr': 'most_eq { all_rows ; certification ; platinum } = true'} | most_eq { all_rows ; certification ; platinum } = true | for the certification records of all rows , most of them fuzzily match to platinum . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'certification_3': 3, 'platinum_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'certification_3': 'certification', 'platinum_4': 'platinum'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'certification_3': [0], 'platinum_4': [0]} | ['rank', 'artist', 'album', 'peak position', 'sales', 'certification'] | [['1', 'nickelback', 'dark horse', '1', '480000', '6x platinum'], ['2', 'simple plan', 'simple plan', '2', '200000', 'platinum'], ['3', 'celine dion', 'my love : essential collection', '2', '160000', '2x platinum'], ['4', 'the canadian tenors', 'the canadian tenors', '22', '80000', 'platinum'], ['5', 'city and colour', 'bring me your love', '3', '80000', 'platinum'], ['6', 'cur de pirate', 'cur de pirate', 'n / a', '80000', 'platinum'], ['7', 'sarah mclachlan', 'closer : the best of sarah mclachlan', '3', '80000', 'platinum'], ['8', 'theory of a deadman', 'scars & souvenirs', '2', '80000', 'platinum'], ['9', 'sam roberts', 'love at the end of the world', '1', '50000', 'gold'], ['10', 'tara oram', 'chasing the sun', '8', '50000', 'gold']] |
list of state leaders in 820s bc | https://en.wikipedia.org/wiki/List_of_state_leaders_in_820s_BC | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17338083-13.html.csv | majority | all of the states in the 800s bc listed are of the sovereign type . | {'scope': 'all', 'col': '2', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'sovereign', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'type', 'sovereign'], 'result': True, 'ind': 0, 'tointer': 'for the type records of all rows , all of them fuzzily match to sovereign .', 'tostr': 'all_eq { all_rows ; type ; sovereign } = true'} | all_eq { all_rows ; type ; sovereign } = true | for the type records of all rows , all of them fuzzily match to sovereign . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'type_3': 3, 'sovereign_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'type_3': 'type', 'sovereign_4': 'sovereign'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'type_3': [0], 'sovereign_4': [0]} | ['state', 'type', 'name', 'title', 'royal house', 'from'] | [['cai', 'sovereign', 'yi', 'marquis', 'ji', '837 bc'], ['cao', 'sovereign', 'you', 'count', '-', '835 bc'], ['cao', 'sovereign', 'dai', 'count', '-', '826 bc'], ['chen', 'sovereign', 'li', 'duke', '-', '831 bc'], ['chu', 'sovereign', 'xiong yan the younger', 'viscount', 'mi', '837 bc'], ['chu', 'sovereign', 'xiong shuang', 'viscount', 'mi', '827 bc'], ['chu', 'sovereign', 'xiong xun', 'viscount', 'mi', '821 bc'], ['jin', 'sovereign', 'xi', 'marquis', 'ji', '840 bc'], ['jin', 'sovereign', 'xian', 'marquis', 'ji', '822 bc'], ['lu', 'sovereign', 'shen', 'duke', 'ji', '854 bc'], ['lu', 'sovereign', 'wu', 'duke', 'ji', '825 bc'], ['qi', 'sovereign', 'wu', 'duke', 'jiang', '850 bc'], ['qi', 'sovereign', 'li', 'duke', 'jiang', '824 bc'], ['qin', 'sovereign', 'qin zhong', 'ruler', 'ying', '845 bc'], ['qin', 'sovereign', 'zhuang', 'duke', 'ying', '822 bc'], ['song', 'sovereign', 'hui', 'duke', '-', '830 bc'], ['wey', 'sovereign', 'li', 'marquis', '-', '855 bc'], ['yan', 'sovereign', 'hui', 'marquis', '-', '864 bc'], ['yan', 'sovereign', 'li', 'marquis', '-', '826 bc']] |
2002 atlanta falcons season | https://en.wikipedia.org/wiki/2002_Atlanta_Falcons_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18856037-1.html.csv | aggregation | just under 200,000 people attended the first three falcons games in september of the 2002 season . | {'scope': 'subset', 'col': '5', 'type': 'sum', 'result': 'under 200,000', 'subset': {'col': '2', 'criterion': 'fuzzily_match', 'value': 'september'}} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', 'september'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; date ; september }', 'tointer': 'select the rows whose date record fuzzily matches to september .'}, 'attendance'], 'result': 'under 200,000', 'ind': 1, 'tostr': 'sum { filter_eq { all_rows ; date ; september } ; attendance }'}, 'under 200,000'], 'result': True, 'ind': 2, 'tostr': 'round_eq { sum { filter_eq { all_rows ; date ; september } ; attendance } ; under 200,000 } = true', 'tointer': 'select the rows whose date record fuzzily matches to september . the sum of the attendance record of these rows is under 200,000 .'} | round_eq { sum { filter_eq { all_rows ; date ; september } ; attendance } ; under 200,000 } = true | select the rows whose date record fuzzily matches to september . the sum of the attendance record of these rows is under 200,000 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'sum_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'date_5': 5, 'september_6': 6, 'attendance_7': 7, 'under 200,000_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'sum_1': 'sum', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'date_5': 'date', 'september_6': 'september', 'attendance_7': 'attendance', 'under 200,000_8': 'under 200,000'} | {'eq_2': [3], 'result_3': [], 'sum_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'date_5': [0], 'september_6': [0], 'attendance_7': [1], 'under 200,000_8': [2]} | ['week', 'date', 'opponent', 'result', 'attendance'] | [['1', 'september 8 , 2002', 'green bay packers', 'l 37 - 34', '63127'], ['2', 'september 15 , 2002', 'chicago bears', 'l 14 - 13', '68081'], ['3', 'september 22 , 2002', 'cincinnati bengals', 'w 30 - 3', '68129'], ['5', 'october 6 , 2002', 'tampa bay buccaneers', 'l 20 - 6', '68936'], ['6', 'october 13 , 2002', 'new york giants', 'w 17 - 10', '78728'], ['7', 'october 20 , 2002', 'carolina panthers', 'w 30 - 0', '68056'], ['8', 'october 27 , 2002', 'new orleans saints', 'w 37 - 35', '67883'], ['9', 'november 3 , 2002', 'baltimore ravens', 'w 20 - 17', '68532'], ['10', 'november 10 , 2002', 'pittsburgh steelers', 't 34 - 34', '62779'], ['11', 'november 17 , 2002', 'new orleans saints', 'w 24 - 17', '70382'], ['12', 'november 24 , 2002', 'carolina panthers', 'w 41 - 0', '72533'], ['13', 'december 1 , 2002', 'minnesota vikings', 'w 30 - 24', '63947'], ['14', 'december 8 , 2002', 'tampa bay buccaneers', 'l 34 - 10', '65648'], ['15', 'december 15 , 2002', 'seattle seahawks', 'l 30 - 24', '69551'], ['16', 'december 22 , 2002', 'detroit lions', 'w 36 - 15', '69307'], ['17', 'december 29 , 2002', 'cleveland browns', 'l 24 - 16', '73528']] |
2006 - 07 tottenham hotspur f.c. season | https://en.wikipedia.org/wiki/2006%E2%80%9307_Tottenham_Hotspur_F.C._season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17583318-4.html.csv | unique | paul robinson is the only player in the 2006 - 07 tottenham hotspur f.c. season to play the goalkeeper position . | {'scope': 'all', 'row': '2', 'col': '2', 'col_other': '1', 'criterion': 'equal', 'value': 'goalkeeper', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'position', 'goalkeeper'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose position record fuzzily matches to goalkeeper .', 'tostr': 'filter_eq { all_rows ; position ; goalkeeper }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; position ; goalkeeper } }', 'tointer': 'select the rows whose position record fuzzily matches to goalkeeper . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'position', 'goalkeeper'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose position record fuzzily matches to goalkeeper .', 'tostr': 'filter_eq { all_rows ; position ; goalkeeper }'}, 'player'], 'result': 'paul robinson', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; position ; goalkeeper } ; player }'}, 'paul robinson'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; position ; goalkeeper } ; player } ; paul robinson }', 'tointer': 'the player record of this unqiue row is paul robinson .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; position ; goalkeeper } } ; eq { hop { filter_eq { all_rows ; position ; goalkeeper } ; player } ; paul robinson } } = true', 'tointer': 'select the rows whose position record fuzzily matches to goalkeeper . there is only one such row in the table . the player record of this unqiue row is paul robinson .'} | and { only { filter_eq { all_rows ; position ; goalkeeper } } ; eq { hop { filter_eq { all_rows ; position ; goalkeeper } ; player } ; paul robinson } } = true | select the rows whose position record fuzzily matches to goalkeeper . there is only one such row in the table . the player record of this unqiue row is paul robinson . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'position_7': 7, 'goalkeeper_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'player_9': 9, 'paul robinson_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'position_7': 'position', 'goalkeeper_8': 'goalkeeper', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'player_9': 'player', 'paul robinson_10': 'paul robinson'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'position_7': [0], 'goalkeeper_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'player_9': [2], 'paul robinson_10': [3]} | ['player', 'position', 'premier league', 'fa cup', 'league cup', 'uefa cup', 'total'] | [['michael dawson', 'defender', '37', '6', '4', '10', '57'], ['paul robinson', 'goalkeeper', '38', '4', '3', '9', '54'], ['pascal chimbonda', 'defender', '33', '4', '4', '10', '51'], ['jermain defoe', 'forward', '33', '5', '5', '5', '48'], ['robbie keane', 'forward', '27', '5', '3', '9', '44']] |
australia at the rugby world cup | https://en.wikipedia.org/wiki/Australia_at_the_Rugby_World_Cup | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11942082-10.html.csv | aggregation | the average seating capacity for australian stadiums in the rugby world cup is 37730 . | {'scope': 'all', 'col': '5', 'type': 'average', 'result': '37730', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'capacity'], 'result': '37730', 'ind': 0, 'tostr': 'avg { all_rows ; capacity }'}, '37730'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; capacity } ; 37730 } = true', 'tointer': 'the average of the capacity record of all rows is 37730 .'} | round_eq { avg { all_rows ; capacity } ; 37730 } = true | the average of the capacity record of all rows is 37730 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'capacity_4': 4, '37730_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'capacity_4': 'capacity', '37730_5': '37730'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'capacity_4': [0], '37730_5': [1]} | ['stadium', 'games', 'city', 'state', 'capacity', 'best crowd'] | [['telstra stadium', '7', 'sydney', 'new south wales', '83500', '82957 ( final : australia vs england )'], ['aussie stadium', '5', 'sydney', 'new south wales', '41159', '37137 ( scotland vs fiji )'], ['central coast stadium', '3', 'gosford', 'new south wales', '20119', '19653 ( japan vs united states )'], ['win stadium', '2', 'wollongong', 'new south wales', '18484', '17833 ( france vs united states )'], ['suncorp stadium', '9', 'brisbane', 'queensland', '52500', '48778 ( australia vs romania )'], ['dairy farmers stadium', '3', 'townsville', 'queensland', '24843', '21309 ( france vs japan )'], ['telstra dome', '7', 'melbourne', 'victoria', '53371', '54206 ( australia vs ireland )'], ['subiaco oval', '5', 'perth', 'western australia', '42922', '38834 ( south africa vs england )'], ['canberra stadium', '4', 'canberra', 'australian capital territory', '24647', '22641 ( italy vs wales )'], ["adelaide oval '", '2', 'adelaide', 'south australia', '33597', '33000 ( australia vs namibia )'], ['york park', '1', 'launceston', 'tasmania', '19891', '15457 ( namibia vs romania )']] |
eurovision song contest 1965 | https://en.wikipedia.org/wiki/Eurovision_Song_Contest_1965 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-184806-1.html.csv | aggregation | in the 1965 eurovision song contest the songs sung in english achieved a total of 43 points . | {'scope': 'subset', 'col': '5', 'type': 'sum', 'result': '43', 'subset': {'col': '2', 'criterion': 'equal', 'value': 'english'}} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'language', 'english'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; language ; english }', 'tointer': 'select the rows whose language record fuzzily matches to english .'}, 'points'], 'result': '43', 'ind': 1, 'tostr': 'sum { filter_eq { all_rows ; language ; english } ; points }'}, '43'], 'result': True, 'ind': 2, 'tostr': 'round_eq { sum { filter_eq { all_rows ; language ; english } ; points } ; 43 } = true', 'tointer': 'select the rows whose language record fuzzily matches to english . the sum of the points record of these rows is 43 .'} | round_eq { sum { filter_eq { all_rows ; language ; english } ; points } ; 43 } = true | select the rows whose language record fuzzily matches to english . the sum of the points record of these rows is 43 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'sum_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'language_5': 5, 'english_6': 6, 'points_7': 7, '43_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'sum_1': 'sum', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'language_5': 'language', 'english_6': 'english', 'points_7': 'points', '43_8': '43'} | {'eq_2': [3], 'result_3': [], 'sum_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'language_5': [0], 'english_6': [0], 'points_7': [1], '43_8': [2]} | ['draw', 'language', 'artist', 'place', 'points'] | [['01', 'dutch', 'conny van den bos', '11', '5'], ['02', 'english', 'kathy kirby', '2', '26'], ['03', 'spanish', 'conchita bautista', '15', '0'], ['04', 'english', 'butch moore', '6', '11'], ['05', 'german', 'ulla wiesner', '15', '0'], ['06', 'german', 'udo jürgens', '4', '16'], ['07', 'norwegian', 'kirsti sparboe', '13', '1'], ['08', 'dutch', 'lize marke', '15', '0'], ['09', 'french', 'marjorie noël', '9', '7'], ['10', 'english', 'ingvar wixell', '10', '6'], ['11', 'french', 'guy mardel', '3', '22'], ['12', 'portuguese', 'simone de oliveira', '13', '1'], ['13', 'italian', 'bobby solo', '5', '15'], ['14', 'danish', 'birgit brüel', '7', '10'], ['15', 'french', 'france gall', '1', '32'], ['16', 'finnish', 'viktor klimenko', '15', '0'], ['17', 'croatian', 'vice vukov', '12', '2'], ['18', 'french', 'yovanna', '8', '8']] |
list of chicago blackhawks statistics and records | https://en.wikipedia.org/wiki/List_of_Chicago_Blackhawks_statistics_and_records | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16366700-2.html.csv | unique | out of the players listed in the chicago blackhawks ' records , only bobby hull played more than 600 regular season games . | {'scope': 'all', 'row': '1', 'col': '3', 'col_other': '1', 'criterion': 'greater_than', 'value': '600', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'regular season', '600'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose regular season record is greater than 600 .', 'tostr': 'filter_greater { all_rows ; regular season ; 600 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_greater { all_rows ; regular season ; 600 } }', 'tointer': 'select the rows whose regular season record is greater than 600 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'regular season', '600'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose regular season record is greater than 600 .', 'tostr': 'filter_greater { all_rows ; regular season ; 600 }'}, 'name'], 'result': 'bobby hull', 'ind': 2, 'tostr': 'hop { filter_greater { all_rows ; regular season ; 600 } ; name }'}, 'bobby hull'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_greater { all_rows ; regular season ; 600 } ; name } ; bobby hull }', 'tointer': 'the name record of this unqiue row is bobby hull .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_greater { all_rows ; regular season ; 600 } } ; eq { hop { filter_greater { all_rows ; regular season ; 600 } ; name } ; bobby hull } } = true', 'tointer': 'select the rows whose regular season record is greater than 600 . there is only one such row in the table . the name record of this unqiue row is bobby hull .'} | and { only { filter_greater { all_rows ; regular season ; 600 } } ; eq { hop { filter_greater { all_rows ; regular season ; 600 } ; name } ; bobby hull } } = true | select the rows whose regular season record is greater than 600 . there is only one such row in the table . the name record of this unqiue row is bobby hull . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_greater_0': 0, 'all_rows_6': 6, 'regular season_7': 7, '600_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'name_9': 9, 'bobby hull_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_greater_0': 'filter_greater', 'all_rows_6': 'all_rows', 'regular season_7': 'regular season', '600_8': '600', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'name_9': 'name', 'bobby hull_10': 'bobby hull'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_greater_0': [1, 2], 'all_rows_6': [0], 'regular season_7': [0], '600_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'name_9': [2], 'bobby hull_10': [3]} | ['name', 'years', 'regular season', 'playoffs', 'total'] | [['bobby hull', '1957 - 1972', '604', '62', '666'], ['stan mikita', '1959 - 1979', '541', '59', '600'], ['steve larmer', '1981 - 1993', '406', '45', '451'], ['denis savard', '1980 - 1990 1995 - 1997', '377', '61', '438'], ['dennis hull', '1964 - 1977', '298', '33', '331'], ['jeremy roenick', '1988 - 1996', '267', '35', '302'], ['tony amonte', '1994 - 2002', '268', '13', '281'], ['hubert pit martin', '1967 - 1977', '243', '26', '269'], ['bill mosienko', '1942 - 1955', '258', '10', '268'], ['ken wharram', '1952 - 1969', '252', '16', '268']] |
1995 pga tour | https://en.wikipedia.org/wiki/1995_PGA_Tour | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14611590-3.html.csv | majority | the majority of players in the 1995 pga tour were from the united states . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'united states', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'country', 'united states'], 'result': True, 'ind': 0, 'tointer': 'for the country records of all rows , most of them fuzzily match to united states .', 'tostr': 'most_eq { all_rows ; country ; united states } = true'} | most_eq { all_rows ; country ; united states } = true | for the country records of all rows , most of them fuzzily match to united states . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'country_3': 3, 'united states_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'country_3': 'country', 'united states_4': 'united states'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'country_3': [0], 'united states_4': [0]} | ['rank', 'player', 'country', 'earnings', 'events', 'wins'] | [['1', 'greg norman', 'australia', '1654959', '16', '3'], ['2', 'billy mayfair', 'united states', '1543192', '28', '2'], ['3', 'lee janzen', 'united states', '1378966', '28', '3'], ['4', 'corey pavin', 'united states', '1340079', '22', '2'], ['5', 'steve elkington', 'australia', '1254352', '21', '2']] |
american seafoods | https://en.wikipedia.org/wiki/American_Seafoods | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-15230458-1.html.csv | comparative | of the american seafoods ' ships , northern eagle was built 15 years before northern hawk . | {'row_1': '4', 'row_2': '5', 'col': '5', 'col_other': '1', 'relation': 'diff', 'record_mentioned': 'no', 'diff_result': {'diff_value': '15 years', 'bigger': 'row2'}} | {'func': 'eq', 'args': [{'func': 'diff', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'name', 'northern eagle'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose name record fuzzily matches to northern eagle .', 'tostr': 'filter_eq { all_rows ; name ; northern eagle }'}, 'year'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; name ; northern eagle } ; year }', 'tointer': 'select the rows whose name record fuzzily matches to northern eagle . take the year record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'name', 'northern hawk'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose name record fuzzily matches to northern hawk .', 'tostr': 'filter_eq { all_rows ; name ; northern hawk }'}, 'year'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; name ; northern hawk } ; year }', 'tointer': 'select the rows whose name record fuzzily matches to northern hawk . take the year record of this row .'}], 'result': '-15 years', 'ind': 4, 'tostr': 'diff { hop { filter_eq { all_rows ; name ; northern eagle } ; year } ; hop { filter_eq { all_rows ; name ; northern hawk } ; year } }'}, '-15 years'], 'result': True, 'ind': 5, 'tostr': 'eq { diff { hop { filter_eq { all_rows ; name ; northern eagle } ; year } ; hop { filter_eq { all_rows ; name ; northern hawk } ; year } } ; -15 years } = true', 'tointer': 'select the rows whose name record fuzzily matches to northern eagle . take the year record of this row . select the rows whose name record fuzzily matches to northern hawk . take the year record of this row . the second record is 15 years larger than the first record .'} | eq { diff { hop { filter_eq { all_rows ; name ; northern eagle } ; year } ; hop { filter_eq { all_rows ; name ; northern hawk } ; year } } ; -15 years } = true | select the rows whose name record fuzzily matches to northern eagle . take the year record of this row . select the rows whose name record fuzzily matches to northern hawk . take the year record of this row . the second record is 15 years larger than the first record . | 6 | 6 | {'str_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, 'northern eagle_9': 9, 'year_10': 10, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_11': 11, 'name_12': 12, 'northern hawk_13': 13, 'year_14': 14, '-15 years_15': 15} | {'str_eq_5': 'str_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', 'northern eagle_9': 'northern eagle', 'year_10': 'year', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_11': 'all_rows', 'name_12': 'name', 'northern hawk_13': 'northern hawk', 'year_14': 'year', '-15 years_15': '-15 years'} | {'str_eq_5': [6], 'result_6': [], 'diff_4': [5], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_7': [0], 'name_8': [0], 'northern eagle_9': [0], 'year_10': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_11': [1], 'name_12': [1], 'northern hawk_13': [1], 'year_14': [3], '-15 years_15': [5]} | ['name', 'length', 'tonnage', 'built by', 'year', 'engines', 'horsepowers', 'former names'] | [['american dynasty', '272.0 feet', '3471', 'mangone shipyard , houston , tx', '1974', '2 , bergen diesel , brm - 8', '8000', 'artabaze , bure , sea bure'], ['american triumph', '285.0 feet', '4294', 'ls baier & co , portland , or', '1961', '2 , w채rtsil채 , 8r32d', '7939', 'acona'], ['northern jaeger', '337 feet', '3732', 'levingston shipbuilding , orange , tx', '1969', '2 , mak m453c', '6322', 'jaeger , inagua ranger ii , wisco ranger'], ['northern eagle', '344.1 feet', '4437', 'ulstein hatlo norway', '1966', '2 , bergen diesel , brm - 8', '6590', 'mauna kea , hawaiian princess'], ['northern hawk', '310.1 feet', '3732', 'brount marine corp , warren , ri', '1981', '2 , bergen diesel , brm - 8', '8790', 'state trust'], ['ocean rover', '223.0 feet', '4345', 'mcdermott shipyards , amelia , la', '1973', '3 , w채rtsil채', '7080', 'enterprise']] |
list of doctor who audio plays by big finish | https://en.wikipedia.org/wiki/List_of_Doctor_Who_audio_plays_by_Big_Finish | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1620397-2.html.csv | ordinal | mission to magnus was the second earliest released doctor who audio play by big finish . | {'row': '2', 'col': '7', 'order': '2', 'col_other': '3', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'released', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; released ; 2 }'}, 'title'], 'result': 'mission to magnus', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; released ; 2 } ; title }'}, 'mission to magnus'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; released ; 2 } ; title } ; mission to magnus } = true', 'tointer': 'select the row whose released record of all rows is 2nd minimum . the title record of this row is mission to magnus .'} | eq { hop { nth_argmin { all_rows ; released ; 2 } ; title } ; mission to magnus } = true | select the row whose released record of all rows is 2nd minimum . the title record of this row is mission to magnus . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'released_5': 5, '2_6': 6, 'title_7': 7, 'mission to magnus_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', 'released_5': 'released', '2_6': '2', 'title_7': 'title', 'mission to magnus_8': 'mission to magnus'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'released_5': [0], '2_6': [0], 'title_7': [1], 'mission to magnus_8': [2]} | ['', 'series sorted', 'title', 'author', 'doctor', 'featuring', 'released'] | [['1', '6y / aa', 'the nightmare fair', 'graham williams ( adapted by john ainsworth )', '6th', 'peri , celestial toymaker', 'november 2009'], ['2', '6y / ab', 'mission to magnus', 'philip martin', '6th', 'peri , s ice warrior , sil', 'december 2009'], ['3', '6y / ac', 'leviathan', 'brian finch ( adapted by paul finch )', '6th', 'peri', 'january 2010'], ['5', '6y / ae', 'paradise 5', 'pj hammond and andy lane', '6th', 'peri', 'march 2010'], ['6', '6y / af', 'point of entry', 'barbara clegg and marc platt', '6th', 'peri', 'april 2010'], ['7', '6y / ag', 'the song of megaptera', 'pat mills', '6th', 'peri', 'may 2010']] |
list of tallest buildings in philadelphia | https://en.wikipedia.org/wiki/List_of_tallest_buildings_in_Philadelphia | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12587248-3.html.csv | count | two of the buildings that held the record for the tallest building in philadelphia before 1902 were under 200 feet . | {'scope': 'subset', 'criterion': 'less_than', 'value': '200', 'result': '2', 'col': '4', 'subset': {'col': '3', 'criterion': 'less_than', 'value': '1902'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_less', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'years as tallest', '1902'], 'result': None, 'ind': 0, 'tostr': 'filter_less { all_rows ; years as tallest ; 1902 }', 'tointer': 'select the rows whose years as tallest record is less than 1902 .'}, 'height ft ( m )', '200'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose years as tallest record is less than 1902 . among these rows , select the rows whose height ft ( m ) record is less than 200 .', 'tostr': 'filter_less { filter_less { all_rows ; years as tallest ; 1902 } ; height ft ( m ) ; 200 }'}], 'result': '2', 'ind': 2, 'tostr': 'count { filter_less { filter_less { all_rows ; years as tallest ; 1902 } ; height ft ( m ) ; 200 } }', 'tointer': 'select the rows whose years as tallest record is less than 1902 . among these rows , select the rows whose height ft ( m ) record is less than 200 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_less { filter_less { all_rows ; years as tallest ; 1902 } ; height ft ( m ) ; 200 } } ; 2 } = true', 'tointer': 'select the rows whose years as tallest record is less than 1902 . among these rows , select the rows whose height ft ( m ) record is less than 200 . the number of such rows is 2 .'} | eq { count { filter_less { filter_less { all_rows ; years as tallest ; 1902 } ; height ft ( m ) ; 200 } } ; 2 } = true | select the rows whose years as tallest record is less than 1902 . among these rows , select the rows whose height ft ( m ) record is less than 200 . 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, 'years as tallest_6': 6, '1902_7': 7, 'height ft (m)_8': 8, '200_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', 'years as tallest_6': 'years as tallest', '1902_7': '1902', 'height ft (m)_8': 'height ft ( m )', '200_9': '200', '2_10': '2'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_less_1': [2], 'filter_less_0': [1], 'all_rows_5': [0], 'years as tallest_6': [0], '1902_7': [0], 'height ft (m)_8': [1], '200_9': [1], '2_10': [3]} | ['name', 'street address', 'years as tallest', 'height ft ( m )', 'floors', 'architect'] | [['independence hall', '520 chestnut street', '1748 - 1754', '134 ( 41 )', '-', 'edmund woolley and andrew hamilton'], ['christ church', '20 north american street', '1754 - 1856', '196 ( 60 )', '-', 'robert smith'], ['tenth presbyterian church', '17th & spruce streets', '1856 - 1900', '250 ( 76 )', '-', 'john mcarthur , jr'], ['north american building', '121 south broad street', '1900 - 1901', '267 ( 81 )', '21', 'james h windrim'], ['philadelphia city hall', 'broad & market streets', '1901 - 1987', '548 ( 167 )', '9', 'john mcarthur , jr'], ['one liberty place', '1650 market street', '1987 - 2008', '945 ( 288 )', '61', 'helmut jahn'], ['comcast center', '1701 john f kennedy boulevard', '2008 - present', '975 ( 297 )', '57', 'robert a m stern architects']] |
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 | count | a total of five episodes of drop dead diva were originally aired in the month of august . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'august', 'result': '5', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'original air date', 'august'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose original air date record fuzzily matches to august .', 'tostr': 'filter_eq { all_rows ; original air date ; august }'}], 'result': '5', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; original air date ; august } }', 'tointer': 'select the rows whose original air date record fuzzily matches to august . the number of such rows is 5 .'}, '5'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; original air date ; august } } ; 5 } = true', 'tointer': 'select the rows whose original air date record fuzzily matches to august . the number of such rows is 5 .'} | eq { count { filter_eq { all_rows ; original air date ; august } } ; 5 } = true | select the rows whose original air date record fuzzily matches to august . 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, 'original air date_5': 5, 'august_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', 'original air date_5': 'original air date', 'august_6': 'august', '5_7': '5'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'original air date_5': [0], 'august_6': [0], '5_7': [2]} | ['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']] |
muhsin corbbrey | https://en.wikipedia.org/wiki/Muhsin_Corbbrey | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17624865-1.html.csv | majority | the majority of fights resulted in a win for muhsin corbbrey . | {'scope': 'all', 'col': '2', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'win', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'result', 'win'], 'result': True, 'ind': 0, 'tointer': 'for the result records of all rows , most of them fuzzily match to win .', 'tostr': 'most_eq { all_rows ; result ; win } = true'} | most_eq { all_rows ; result ; win } = true | for the result records of all rows , most of them fuzzily match to win . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'result_3': 3, 'win_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'result_3': 'result', 'win_4': 'win'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'result_3': [0], 'win_4': [0]} | ['date', 'result', 'opponent', 'venue', 'location', 'method', 'round', 'time', 'record'] | [['2009 - 02 - 28', 'win', 'troy nelson', 'shoreline ball room', 'hilton head , south carolina , usa', 'decision', '6', '3:00', '6 - 2 - 1'], ['2006 - 09 - 15', 'win', 'ryan rayonec', 'omar shrine temple', 'mount pleasant , south carolina , usa', 'tko', '4', '0:54', '5 - 2 - 1'], ['2006 - 06 - 15', 'loss', 'tim coleman', "michael 's eighth avenue", 'glen burnie , maryland , usa', 'decision ( unanimous )', '6', '3:00', '4 - 2 - 1'], ['2006 - 04 - 21', 'win', 'shelton barnes', 'omar shrine temple', 'mount pleasant , south carolina , usa', 'tko', '1', '2:43', '4 - 1 - 1'], ['2006 - 03 - 09', 'win', 'kareem robinson', "michael 's eighth avenue", 'glen burnie , maryland , usa', 'decision ( unanimous )', '4', '3:00', '3 - 1 - 1'], ['2006 - 01 - 26', 'win', 'anthony abrams', "michael 's eighth avenue", 'glen burnie , maryland , usa', 'decision ( unanimous )', '4', '3:00', '2 - 1 - 1'], ['2005 - 11 - 26', 'win', 'ben lock', 'show place arena', 'upper marlboro , maryland , usa', 'decision ( unanimous )', '4', '3:00', '1 - 1 - 1'], ['2005 - 04 - 26', 'loss', 'emanuel gonzã ¡ lez', 'radisson hotel', 'miami , florida , usa', 'decision ( unanimous )', '4', '3:00', '0 - 1 - 1'], ['2005 - 04 - 08', 'draw', 'ricardo planter', 'club med sandpiper', 'port st lucie , florida , usa', 'draw ( majority )', '4', '3:00', '0 - 0 - 1']] |
rowing at the 2008 summer olympics - women 's lightweight double sculls | https://en.wikipedia.org/wiki/Rowing_at_the_2008_Summer_Olympics_%E2%80%93_Women%27s_lightweight_double_sculls | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18662704-5.html.csv | ordinal | misaki kumakura and akiko iwamoto were the duo with the third fastest time in the 2008 summer olympics - women 's lightweight double sculls . | {'row': '3', 'col': '4', 'order': '3', 'col_other': '2', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'time', '3'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; time ; 3 }'}, 'rowers'], 'result': 'misaki kumakura , akiko iwamoto', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; time ; 3 } ; rowers }'}, 'misaki kumakura , akiko iwamoto'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; time ; 3 } ; rowers } ; misaki kumakura , akiko iwamoto } = true', 'tointer': 'select the row whose time record of all rows is 3rd minimum . the rowers record of this row is misaki kumakura , akiko iwamoto .'} | eq { hop { nth_argmin { all_rows ; time ; 3 } ; rowers } ; misaki kumakura , akiko iwamoto } = true | select the row whose time record of all rows is 3rd minimum . the rowers record of this row is misaki kumakura , akiko iwamoto . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'time_5': 5, '3_6': 6, 'rowers_7': 7, 'misaki kumakura , akiko iwamoto_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmin_0': 'nth_argmin', 'all_rows_4': 'all_rows', 'time_5': 'time', '3_6': '3', 'rowers_7': 'rowers', 'misaki kumakura , akiko iwamoto_8': 'misaki kumakura , akiko iwamoto'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'time_5': [0], '3_6': [0], 'rowers_7': [1], 'misaki kumakura , akiko iwamoto_8': [2]} | ['rank', 'rowers', 'country', 'time', 'notes'] | [['1', 'xu dongxiang , chen haixia', 'china', '6:57.58', 'sa / b'], ['2', 'katrin olsen , juliane rasmussen', 'denmark', '6:58.63', 'sa / b'], ['3', 'misaki kumakura , akiko iwamoto', 'japan', '7:05.67', 'r'], ['4', 'yaima velazquez , ismaray marrero', 'cuba', '7:13.35', 'r'], ['5', 'ko young - eun , ji yoo - jin', 'south korea', '7:39.70', 'r']] |
1980 world judo championships | https://en.wikipedia.org/wiki/1980_World_Judo_Championships | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15826103-2.html.csv | ordinal | france recorded the highest number of silver in the world judo championships of 1980 . | {'row': '2', 'col': '4', 'order': '1', 'col_other': '2', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'silver', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; silver ; 1 }'}, 'nation'], 'result': 'france', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; silver ; 1 } ; nation }'}, 'france'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; silver ; 1 } ; nation } ; france } = true', 'tointer': 'select the row whose silver record of all rows is 1st maximum . the nation record of this row is france .'} | eq { hop { nth_argmax { all_rows ; silver ; 1 } ; nation } ; france } = true | select the row whose silver record of all rows is 1st maximum . the nation record of this row is france . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'silver_5': 5, '1_6': 6, 'nation_7': 7, 'france_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', 'silver_5': 'silver', '1_6': '1', 'nation_7': 'nation', 'france_8': 'france'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'silver_5': [0], '1_6': [0], 'nation_7': [1], 'france_8': [2]} | ['rank', 'nation', 'gold', 'silver', 'bronze', 'total'] | [['1', 'austria', '3', '0', '0', '3'], ['2', 'france', '1', '3', '4', '8'], ['3', 'italy', '1', '2', '0', '3'], ['4', 'great britain', '1', '1', '3', '5'], ['5', 'belgium', '1', '0', '2', '3'], ['6', 'netherlands', '1', '0', '1', '2'], ['7', 'germany', '0', '1', '3', '4'], ['8', 'japan', '0', '1', '0', '1'], ['9', 'united states', '0', '0', '3', '3']] |
six flags magic mountain | https://en.wikipedia.org/wiki/Six_Flags_Magic_Mountain | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1017230-2.html.csv | count | in six flags magic mountain , 2 of those in baja ridge has a thrill / intensity rating of maximum . | {'scope': 'subset', 'criterion': 'equal', 'value': 'maximum', 'result': '2', 'col': '5', 'subset': {'col': '4', 'criterion': 'equal', 'value': 'baja ridge'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location in park', 'baja ridge'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; location in park ; baja ridge }', 'tointer': 'select the rows whose location in park record fuzzily matches to baja ridge .'}, 'thrill / intensity rating', 'maximum'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose location in park record fuzzily matches to baja ridge . among these rows , select the rows whose thrill / intensity rating record fuzzily matches to maximum .', 'tostr': 'filter_eq { filter_eq { all_rows ; location in park ; baja ridge } ; thrill / intensity rating ; maximum }'}], 'result': '2', 'ind': 2, 'tostr': 'count { filter_eq { filter_eq { all_rows ; location in park ; baja ridge } ; thrill / intensity rating ; maximum } }', 'tointer': 'select the rows whose location in park record fuzzily matches to baja ridge . among these rows , select the rows whose thrill / intensity rating record fuzzily matches to maximum . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_eq { filter_eq { all_rows ; location in park ; baja ridge } ; thrill / intensity rating ; maximum } } ; 2 } = true', 'tointer': 'select the rows whose location in park record fuzzily matches to baja ridge . among these rows , select the rows whose thrill / intensity rating record fuzzily matches to maximum . the number of such rows is 2 .'} | eq { count { filter_eq { filter_eq { all_rows ; location in park ; baja ridge } ; thrill / intensity rating ; maximum } } ; 2 } = true | select the rows whose location in park record fuzzily matches to baja ridge . among these rows , select the rows whose thrill / intensity rating record fuzzily matches to maximum . the number of such rows is 2 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_str_eq_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'location in park_6': 6, 'baja ridge_7': 7, 'thrill / intensity rating_8': 8, 'maximum_9': 9, '2_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_str_eq_1': 'filter_str_eq', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'location in park_6': 'location in park', 'baja ridge_7': 'baja ridge', 'thrill / intensity rating_8': 'thrill / intensity rating', 'maximum_9': 'maximum', '2_10': '2'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_str_eq_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'location in park_6': [0], 'baja ridge_7': [0], 'thrill / intensity rating_8': [1], 'maximum_9': [1], '2_10': [3]} | ['current name', 'year first opened', 'manufacturer', 'location in park', 'thrill / intensity rating', 'minimum height requirements'] | [['apocalypse : the ride', '2009', 'great coasters international', 'cyclone bay', 'moderate', '48'], ['batman : the ride', '1994', 'bolliger & mabillard', 'dc universe', 'maximum', '54'], ['canyon blaster', '1999', 'e & f miler industries', 'high sierra territory', 'mild', "33 to ride with an adult '36 to ride alone"], ['colossus', '1978', 'international amusement devices', 'colossus county fair', 'moderate', '48'], ['full throttle', '2013', 'premier rides', 'full throttle area', 'maximum', '54'], ['gold rusher', '1971', 'arrow development', 'the movie district', 'moderate', '48'], ['goliath', '2000', 'giovanola', 'colossus county fair', 'maximum', '48'], ['green lantern : first flight', '2011', 'intamin', 'dc universe', 'maximum', '52'], ['magic flyer', '1971', 'bradley and kaye', 'high sierra territory', 'mild', 'none , rider can not be taller than 54'], ['ninja', '1988', 'arrow dynamics', 'samurai summit', 'moderate', '42'], ['revolution', '1976', 'anton schwarzkopf', 'baja ridge', 'moderate', '48'], ["the riddler 's revenge", '1998', 'bolliger & mabillard', 'the movie district', 'maximum', '54'], ['road runner express', '2011', 'vekoma', 'high sierra territory', 'moderate', '36'], ['scream !', '2003', 'bolliger & mabillard', 'colossus county fair', 'maximum', '54'], ['superman : escape from krypton', '2011', 'intamin', 'samurai summit', 'maximum', '48'], ['tatsu', '2006', 'bolliger & mabillard', 'samurai summit', 'maximum', '54'], ['viper', '1990', 'arrow dynamics', 'baja ridge', 'maximum', '54'], ['x square', '2002', 'arrow dynamics', 'baja ridge', 'maximum', '48']] |
ranked list of norwegian counties | https://en.wikipedia.org/wiki/Ranked_list_of_Norwegian_counties | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1064198-3.html.csv | count | three counties are expected to have percentages higher than 10 % in 2040 . | {'scope': 'all', 'criterion': 'greater_than_eq', 'value': '10', 'result': '3', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater_eq', 'args': ['all_rows', '% ( 2040 )', '10'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose % ( 2040 ) record is greater than or equal to 10 .', 'tostr': 'filter_greater_eq { all_rows ; % ( 2040 ) ; 10 }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_greater_eq { all_rows ; % ( 2040 ) ; 10 } }', 'tointer': 'select the rows whose % ( 2040 ) record is greater than or equal to 10 . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_greater_eq { all_rows ; % ( 2040 ) ; 10 } } ; 3 } = true', 'tointer': 'select the rows whose % ( 2040 ) record is greater than or equal to 10 . the number of such rows is 3 .'} | eq { count { filter_greater_eq { all_rows ; % ( 2040 ) ; 10 } } ; 3 } = true | select the rows whose % ( 2040 ) record is greater than or equal to 10 . the number of such rows is 3 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_greater_eq_0': 0, 'all_rows_4': 4, '% (2040)_5': 5, '10_6': 6, '3_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_greater_eq_0': 'filter_greater_eq', 'all_rows_4': 'all_rows', '% (2040)_5': '% ( 2040 )', '10_6': '10', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_greater_eq_0': [1], 'all_rows_4': [0], '% (2040)_5': [0], '10_6': [0], '3_7': [2]} | ['rank', 'county', '% ( 1960 )', '% ( 2000 )', '% ( 2040 )'] | [['1', 'oslo', '13.2', '11.3', '12.8'], ['2', 'akershus', '6.3', '10.4', '11.9'], ['3', 'hordaland', '9.4', '9.7', '10.2'], ['4', 'rogaland', '6.6', '8.3', '9.9'], ['5', 'sør - trøndelag', '5.8', '5.8', '6.0'], ['6', 'østfold', '5.6', '5.5', '5.5'], ['7', 'buskerud', '4.6', '5.2', '5.4'], ['8', 'møre og romsdal', '5.9', '5.4', '4.8'], ['9', 'nordland', '6.6', '5.3', '3.9'], ['10', 'vestfold', '4.8', '4.7', '4.7'], ['11', 'hedmark', '4.9', '4.1', '3.4'], ['12', 'oppland', '4.6', '4.0', '3.3'], ['13', 'vest - agder', '3.0', '3.4', '3.6'], ['14', 'telemark', '4.1', '3.6', '3.0'], ['15', 'troms', '3.5', '3.3', '2.7'], ['16', 'nord - trøndelag', '3.2', '2.8', '2.4'], ['17', 'aust - agder', '2.1', '2.2', '2.3'], ['18', 'sogn og fjordane', '2.8', '2.4', '1.8'], ['19', 'finnmark', '2.0', '1.6', '1.2'], ['sum', 'norway', '100.0', '100.0', '100.0']] |
galatasaray s.k. ( superleague formula team ) | https://en.wikipedia.org/wiki/Galatasaray_S.K._%28Superleague_Formula_team%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-23293785-2.html.csv | majority | alessandro pier guidi was the driver for all of the races that the galatasaray s.k. superleague formula team participated in . | {'scope': 'all', 'col': '5', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'alessandro pier guidi', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'driver', 'alessandro pier guidi'], 'result': True, 'ind': 0, 'tointer': 'for the driver records of all rows , all of them fuzzily match to alessandro pier guidi .', 'tostr': 'all_eq { all_rows ; driver ; alessandro pier guidi } = true'} | all_eq { all_rows ; driver ; alessandro pier guidi } = true | for the driver records of all rows , all of them fuzzily match to alessandro pier guidi . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'driver_3': 3, 'alessandro pier guidi_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'driver_3': 'driver', 'alessandro pier guidi_4': 'alessandro pier guidi'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'driver_3': [0], 'alessandro pier guidi_4': [0]} | ['sf round', 'country', 'location', 'date', 'driver', 'race 1 ( pts )', 'race 2 ( pts )', 'race total ( pts )'] | [['1', 'england', 'donington park', '30 - 31 august 2008', 'alessandro pier guidi', '12', '12', '24'], ['2', 'germany', 'nürburgring', '20 - 21 september 2008', 'alessandro pier guidi', '40', '26', '90'], ['3', 'belgium', 'zolder', '4 - 5 october 2008', 'alessandro pier guidi', '10', '14', '114'], ['4', 'portugal', 'estoril circuit', '18 - 19 october 2008', 'alessandro pier guidi', '26', '40', '180'], ['5', 'italy', 'vallelunga circuit', '1 - 2 november 2008', 'alessandro pier guidi', '40', '16', '236']] |
1989 cleveland browns season | https://en.wikipedia.org/wiki/1989_Cleveland_Browns_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10650760-1.html.csv | count | during the 1989 cleveland browns season , the cleveland browns played five games during the month of october . | {'scope': 'subset', 'criterion': 'fuzzily_match', 'value': 'october', 'result': '5', 'col': '2', 'subset': {'col': '2', 'criterion': 'fuzzily_match', 'value': 'october'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', 'october'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; date ; october }', 'tointer': 'select the rows whose date record fuzzily matches to october .'}, 'date', 'october'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose date record fuzzily matches to october . among these rows , select the rows whose date record fuzzily matches to october .', 'tostr': 'filter_eq { filter_eq { all_rows ; date ; october } ; date ; october }'}], 'result': '5', 'ind': 2, 'tostr': 'count { filter_eq { filter_eq { all_rows ; date ; october } ; date ; october } }', 'tointer': 'select the rows whose date record fuzzily matches to october . among these rows , select the rows whose date record fuzzily matches to october . the number of such rows is 5 .'}, '5'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_eq { filter_eq { all_rows ; date ; october } ; date ; october } } ; 5 } = true', 'tointer': 'select the rows whose date record fuzzily matches to october . among these rows , select the rows whose date record fuzzily matches to october . the number of such rows is 5 .'} | eq { count { filter_eq { filter_eq { all_rows ; date ; october } ; date ; october } } ; 5 } = true | select the rows whose date record fuzzily matches to october . among these rows , select the rows whose date record fuzzily matches to october . the number of such rows is 5 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_str_eq_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'date_6': 6, 'october_7': 7, 'date_8': 8, 'october_9': 9, '5_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_str_eq_1': 'filter_str_eq', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'date_6': 'date', 'october_7': 'october', 'date_8': 'date', 'october_9': 'october', '5_10': '5'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_str_eq_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'date_6': [0], 'october_7': [0], 'date_8': [1], 'october_9': [1], '5_10': [3]} | ['week', 'date', 'opponent', 'result', 'attendance'] | [['1', 'september 10 , 1989', 'pittsburgh steelers', 'w 51 - 0', '57928'], ['2', 'september 17 , 1989', 'new york jets', 'w 38 - 24', '73516'], ['3', 'september 25 , 1989', 'cincinnati bengals', 'l 21 - 14', '55996'], ['4', 'october 1 , 1989', 'denver broncos', 'w 16 - 13', '78637'], ['5', 'october 8 , 1989', 'miami dolphins', 'l 13 - 10', '58444'], ['6', 'october 15 , 1989', 'pittsburgh steelers', 'l 17 - 7', '78840'], ['7', 'october 23 , 1989', 'chicago bears', 'w 27 - 7', '78722'], ['8', 'october 29 , 1989', 'houston oilers', 'w 28 - 17', '78765'], ['9', 'november 5 , 1989', 'tampa bay buccaneers', 'w 42 - 31', '69162'], ['10', 'november 12 , 1989', 'seattle seahawks', 'w 17 - 7', '58978'], ['11', 'november 19 , 1989', 'kansas city chiefs', 't 10 - 10', '77922'], ['12', 'november 23 , 1989', 'detroit lions', 'l 13 - 10', '65624'], ['13', 'december 3 , 1989', 'cincinnati bengals', 'l 21 - 0', '76236'], ['14', 'december 10 , 1989', 'indianapolis colts', 'l 23 - 17', '58550'], ['15', 'december 17 , 1989', 'minnesota vikings', 'w 23 - 17', '70777'], ['16', 'december 23 , 1989', 'houston oilers', 'w 24 - 20', '58852']] |
cbfx - fm | https://en.wikipedia.org/wiki/CBFX-FM | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1873425-1.html.csv | superlative | gaspe requires the least amount of power between all the various cities . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '2', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '1', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmin', 'args': ['all_rows', 'power'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; power }'}, 'city of license'], 'result': 'gaspé', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; power } ; city of license }'}, 'gaspé'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmin { all_rows ; power } ; city of license } ; gaspé } = true', 'tointer': 'select the row whose power record of all rows is minimum . the city of license record of this row is gaspé .'} | eq { hop { argmin { all_rows ; power } ; city of license } ; gaspé } = true | select the row whose power record of all rows is minimum . the city of license record of this row is gaspé . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'power_5': 5, 'city of license_6': 6, 'gaspé_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'power_5': 'power', 'city of license_6': 'city of license', 'gaspé_7': 'gaspé'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'power_5': [0], 'city of license_6': [1], 'gaspé_7': [2]} | ['city of license', 'identifier', 'frequency', 'power', 'class', 'recnet'] | [['amos', 'cbfx - fm - 3', '88.3 fm', '32400 s watt', 'b', 'query'], ['gaspé', 'cbfx - fm - 5', '90.1 fm', '4110 watts', 'b', 'query'], ['mont - laurier', 'cbfx - fm - 6', '91.1 fm', '72000 watts', 'c1', 'query'], ['rouyn - noranda', 'cbfx - fm - 4', '89.9 fm', '17200 watts', 'b', 'query'], ['sherbrooke 1', 'cbfx - fm - 2', '90.7 fm', '25000 watts', 'b', 'query'], ['trois - rivières 1', 'cbfx - fm - 1', '104.3 fm', '43000 watts', 'c1', 'query']] |
aalesunds fk | https://en.wikipedia.org/wiki/Aalesunds_FK | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1149273-1.html.csv | comparative | aalesunds fk had the same score and drawed during the 2011 - 2012 uefa europa league away game and the 2012 - 2013 uefa europa league away game . | {'row_1': '2', 'row_2': '6', 'col': '7', 'col_other': '1', 'relation': 'equal', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'season', '2011 - 12'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose season record fuzzily matches to 2011 - 12 .', 'tostr': 'filter_eq { all_rows ; season ; 2011 - 12 }'}, 'aggregate'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; season ; 2011 - 12 } ; aggregate }', 'tointer': 'select the rows whose season record fuzzily matches to 2011 - 12 . take the aggregate record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'season', '2012 - 13'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose season record fuzzily matches to 2012 - 13 .', 'tostr': 'filter_eq { all_rows ; season ; 2012 - 13 }'}, 'aggregate'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; season ; 2012 - 13 } ; aggregate }', 'tointer': 'select the rows whose season record fuzzily matches to 2012 - 13 . take the aggregate record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'eq { hop { filter_eq { all_rows ; season ; 2011 - 12 } ; aggregate } ; hop { filter_eq { all_rows ; season ; 2012 - 13 } ; aggregate } } = true', 'tointer': 'select the rows whose season record fuzzily matches to 2011 - 12 . take the aggregate record of this row . select the rows whose season record fuzzily matches to 2012 - 13 . take the aggregate record of this row . the first record fuzzily matches to the second record .'} | eq { hop { filter_eq { all_rows ; season ; 2011 - 12 } ; aggregate } ; hop { filter_eq { all_rows ; season ; 2012 - 13 } ; aggregate } } = true | select the rows whose season record fuzzily matches to 2011 - 12 . take the aggregate record of this row . select the rows whose season record fuzzily matches to 2012 - 13 . take the aggregate record of this row . the first record fuzzily matches to the second record . | 5 | 5 | {'str_eq_4': 4, 'result_5': 5, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'season_7': 7, '2011 - 12_8': 8, 'aggregate_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'season_11': 11, '2012 - 13_12': 12, 'aggregate_13': 13} | {'str_eq_4': 'str_eq', 'result_5': 'true', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'season_7': 'season', '2011 - 12_8': '2011 - 12', 'aggregate_9': 'aggregate', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'season_11': 'season', '2012 - 13_12': '2012 - 13', 'aggregate_13': 'aggregate'} | {'str_eq_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'season_7': [0], '2011 - 12_8': [0], 'aggregate_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'season_11': [1], '2012 - 13_12': [1], 'aggregate_13': [3]} | ['season', 'competition', 'round', 'club', 'home', 'away', 'aggregate'] | [['2010 - 11', 'uefa europa league', 'q3', 'motherwell', '1 - 1', '0 - 3', '1 - 4'], ['2011 - 12', 'uefa europa league', 'q1', 'neath', '4 - 1', '2 - 0', '6 - 1'], ['2011 - 12', 'uefa europa league', 'q2', 'ferencváros', '3 - 1 ( aet )', '1 - 2', '4 - 3'], ['2011 - 12', 'uefa europa league', 'q3', 'elfsborg', '4 - 0', '1 - 1', '5 - 1'], ['2011 - 12', 'uefa europa league', 'play - off', 'az', '2 - 1', '0 - 6', '2 - 7'], ['2012 - 13', 'uefa europa league', 'q2', 'tirana', '5 - 0', '1 - 1', '6 - 1'], ['2012 - 13', 'uefa europa league', 'q3', 'apoel', '0 - 1', '1 - 2', '1 - 3']] |
2007 - 08 utah jazz season | https://en.wikipedia.org/wiki/2007%E2%80%9308_Utah_Jazz_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11964263-5.html.csv | comparative | utah jazz had a game against the cavaliers earlier than the hornets in the 2007 - 08 season . | {'row_1': '4', 'row_2': '12', 'col': '1', 'col_other': '2', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'visitor', 'cavaliers'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose visitor record fuzzily matches to cavaliers .', 'tostr': 'filter_eq { all_rows ; visitor ; cavaliers }'}, 'date'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; visitor ; cavaliers } ; date }', 'tointer': 'select the rows whose visitor record fuzzily matches to cavaliers . take the date record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'visitor', 'hornets'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose visitor record fuzzily matches to hornets .', 'tostr': 'filter_eq { all_rows ; visitor ; hornets }'}, 'date'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; visitor ; hornets } ; date }', 'tointer': 'select the rows whose visitor record fuzzily matches to hornets . take the date record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; visitor ; cavaliers } ; date } ; hop { filter_eq { all_rows ; visitor ; hornets } ; date } } = true', 'tointer': 'select the rows whose visitor record fuzzily matches to cavaliers . take the date record of this row . select the rows whose visitor record fuzzily matches to hornets . take the date record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; visitor ; cavaliers } ; date } ; hop { filter_eq { all_rows ; visitor ; hornets } ; date } } = true | select the rows whose visitor record fuzzily matches to cavaliers . take the date record of this row . select the rows whose visitor record fuzzily matches to hornets . take the date record of this row . the first record is less than the second record . | 5 | 5 | {'less_4': 4, 'result_5': 5, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'visitor_7': 7, 'cavaliers_8': 8, 'date_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'visitor_11': 11, 'hornets_12': 12, 'date_13': 13} | {'less_4': 'less', 'result_5': 'true', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'visitor_7': 'visitor', 'cavaliers_8': 'cavaliers', 'date_9': 'date', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'visitor_11': 'visitor', 'hornets_12': 'hornets', 'date_13': 'date'} | {'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'visitor_7': [0], 'cavaliers_8': [0], 'date_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'visitor_11': [1], 'hornets_12': [1], 'date_13': [3]} | ['date', 'visitor', 'score', 'home', 'leading scorer', 'attendance', 'record'] | [['november 1', 'rockets', 'l 95 - 106 ( ot )', 'jazz', 'boozer ( 30 )', '19911', '1 - 1'], ['november 3', 'warriors', 'w 133 - 110 ( ot )', 'jazz', 'williams ( 30 )', '19911', '2 - 1'], ['november 4', 'jazz', 'l 109 - 119 ( ot )', 'lakers', 'williams ( 26 )', '18997', '2 - 2'], ['november 7', 'cavaliers', 'w 103 - 101 ( ot )', 'jazz', 'millsap ( 24 )', '19911', '3 - 2'], ['november 9', 'jazz', 'w 103 - 101 ( ot )', 'supersonics', 'boozer ( 27 )', '15980', '4 - 2'], ['november 10', 'grizzlies', 'w 118 - 94 ( ot )', 'jazz', 'boozer ( 31 )', '19771', '5 - 2'], ['november 12', 'kings', 'w 117 - 93 ( ot )', 'jazz', 'boozer ( 32 )', '19911', '6 - 2'], ['november 14', 'jazz', 'w 92 - 88 ( ot )', 'raptors', 'boozer ( 23 )', '17337', '7 - 2'], ['november 16', 'jazz', 'l 94 - 99 ( ot )', 'cavaliers', 'boozer ( 26 )', '19862', '7 - 3'], ['november 17', 'jazz', 'l 97 - 117 ( ot )', 'pacers', 'boozer ( 19 )', '12447', '7 - 4'], ['november 19', 'nets', 'w 102 - 75 ( ot )', 'jazz', 'williams ( 20 )', '19911', '8 - 4'], ['november 23', 'hornets', 'w 99 - 71 ( ot )', 'jazz', 'boozer ( 19 )', '19911', '9 - 4'], ['november 25', 'jazz', 'w 103 - 93 ( ot )', 'pistons', 'boozer ( 36 )', '22076', '10 - 4'], ['november 26', 'jazz', 'l 109 - 113 ( ot )', 'knicks', 'boozer ( 30 )', '18816', '10 - 5'], ['november 28', 'jazz', 'w 106 - 95 ( ot )', '76ers', 'boozer ( 26 )', '11006', '11 - 5'], ['november 30', 'lakers', 'w 120 - 96 ( ot )', 'jazz', 'williams ( 35 )', '19911', '12 - 5']] |
1966 american football league draft | https://en.wikipedia.org/wiki/1966_American_Football_League_Draft | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17706792-1.html.csv | unique | the houston oilers were the only team to draft a linebacker . | {'scope': 'all', 'row': '2', 'col': '4', 'col_other': 'n/a', 'criterion': 'equal', 'value': 'linebacker', 'subset': None} | {'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'position', 'linebacker'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose position record fuzzily matches to linebacker .', 'tostr': 'filter_eq { all_rows ; position ; linebacker }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; position ; linebacker } } = true', 'tointer': 'select the rows whose position record fuzzily matches to linebacker . there is only one such row in the table .'} | only { filter_eq { all_rows ; position ; linebacker } } = true | select the rows whose position record fuzzily matches to linebacker . there is only one such row in the table . | 2 | 2 | {'only_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, 'position_4': 4, 'linebacker_5': 5} | {'only_1': 'only', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'position_4': 'position', 'linebacker_5': 'linebacker'} | {'only_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'position_4': [0], 'linebacker_5': [0]} | ['pick', 'afl team', 'player', 'position', 'college'] | [['1', 'miami dolphins', 'jim grabowski', 'running back', 'illinois'], ['2', 'miami dolphins', 'rick norton', 'quarterback', 'kentucky'], ['3', 'boston patriots', 'karl singer', 'offensive tackle', 'purdue'], ['4', 'denver broncos', 'jerry shay', 'offensive tackle', 'purdue'], ['5', 'houston oilers', 'tommy nobis', 'linebacker', 'texas'], ['6', 'kansas city chiefs', 'aaron brown', 'end', 'minnesota'], ['7', 'san diego chargers', 'don davis', 'offensive tackle', 'cal state - la'], ['8', 'buffalo bills', 'mike dennis', 'running back', "ole ' miss"], ['9', 'new york jets', 'bill yearby', 'offensive tackle', 'michigan'], ['10', 'oakland raiders', 'rodger bird', 'running back', 'kentucky']] |
inxs ( album ) | https://en.wikipedia.org/wiki/INXS_%28album%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1689029-2.html.csv | unique | the initial australian lp release was the only one under the deluxe records label . | {'scope': 'all', 'row': '1', 'col': '3', 'col_other': '1,2', 'criterion': 'equal', 'value': 'deluxe records', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'label', 'deluxe records'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose label record fuzzily matches to deluxe records .', 'tostr': 'filter_eq { all_rows ; label ; deluxe records }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; label ; deluxe records } }', 'tointer': 'select the rows whose label record fuzzily matches to deluxe records . there is only one such row in the table .'}, {'func': 'and', 'args': [{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'label', 'deluxe records'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose label record fuzzily matches to deluxe records .', 'tostr': 'filter_eq { all_rows ; label ; deluxe records }'}, 'format'], 'result': 'lp', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; label ; deluxe records } ; format }'}, 'lp'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; label ; deluxe records } ; format } ; lp }', 'tointer': 'the format record of this unqiue row is lp .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'label', 'deluxe records'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose label record fuzzily matches to deluxe records .', 'tostr': 'filter_eq { all_rows ; label ; deluxe records }'}, 'country'], 'result': 'aus', 'ind': 4, 'tostr': 'hop { filter_eq { all_rows ; label ; deluxe records } ; country }'}, 'aus'], 'result': True, 'ind': 5, 'tostr': 'eq { hop { filter_eq { all_rows ; label ; deluxe records } ; country } ; aus }', 'tointer': 'the country record of this unqiue row is aus .'}], 'result': True, 'ind': 6, 'tostr': 'and { eq { hop { filter_eq { all_rows ; label ; deluxe records } ; format } ; lp } ; eq { hop { filter_eq { all_rows ; label ; deluxe records } ; country } ; aus } }', 'tointer': 'the format record of this unqiue row is lp . the country record of this unqiue row is aus .'}], 'result': True, 'ind': 7, 'tostr': 'and { only { filter_eq { all_rows ; label ; deluxe records } } ; and { eq { hop { filter_eq { all_rows ; label ; deluxe records } ; format } ; lp } ; eq { hop { filter_eq { all_rows ; label ; deluxe records } ; country } ; aus } } } = true', 'tointer': 'select the rows whose label record fuzzily matches to deluxe records . there is only one such row in the table . the format record of this unqiue row is lp . the country record of this unqiue row is aus .'} | and { only { filter_eq { all_rows ; label ; deluxe records } } ; and { eq { hop { filter_eq { all_rows ; label ; deluxe records } ; format } ; lp } ; eq { hop { filter_eq { all_rows ; label ; deluxe records } ; country } ; aus } } } = true | select the rows whose label record fuzzily matches to deluxe records . there is only one such row in the table . the format record of this unqiue row is lp . the country record of this unqiue row is aus . | 10 | 8 | {'and_7': 7, 'result_8': 8, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_9': 9, 'label_10': 10, 'deluxe records_11': 11, 'and_6': 6, 'str_eq_3': 3, 'str_hop_2': 2, 'format_12': 12, 'lp_13': 13, 'str_eq_5': 5, 'str_hop_4': 4, 'country_14': 14, 'aus_15': 15} | {'and_7': 'and', 'result_8': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_9': 'all_rows', 'label_10': 'label', 'deluxe records_11': 'deluxe records', 'and_6': 'and', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'format_12': 'format', 'lp_13': 'lp', 'str_eq_5': 'str_eq', 'str_hop_4': 'str_hop', 'country_14': 'country', 'aus_15': 'aus'} | {'and_7': [8], 'result_8': [], 'only_1': [7], 'filter_str_eq_0': [1, 2, 4], 'all_rows_9': [0], 'label_10': [0], 'deluxe records_11': [0], 'and_6': [7], 'str_eq_3': [6], 'str_hop_2': [3], 'format_12': [2], 'lp_13': [3], 'str_eq_5': [6], 'str_hop_4': [5], 'country_14': [4], 'aus_15': [5]} | ['format', 'country', 'label', 'catalogue no', 'date'] | [['lp', 'aus', 'deluxe records', 'vpl1 6529', '30 october 1980'], ['lp', 'eur', 'mercury records', '838 925 - 1', '1980'], ['lp', 'usa', 'atco records', '7 - 90184 - 1 - y', '1984'], ['mc', 'eur', 'mercury records', '838 925 - 4', '1980'], ['mc', 'usa', 'atco records', '7 - 90184 - 4', '1984'], ['cd', 'aus', 'mercury records', '838 925 - 2', '1989'], ['cd', 'eur', 'mercury records', '838 925 - 2', '1989'], ['cd', 'usa', 'atco records', '7 - 90184 - 2', '15 november 1987']] |
1994 group | https://en.wikipedia.org/wiki/1994_Group | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-142950-1.html.csv | superlative | of the members of the 1994 group , loughborough university received the largest amount of research funding . | {'scope': 'all', 'col_superlative': '7', 'row_superlative': '8', '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', 'research funding ( 000 )'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; research funding ( 000 ) }'}, 'institution'], 'result': 'loughborough university', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; research funding ( 000 ) } ; institution }'}, 'loughborough university'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; research funding ( 000 ) } ; institution } ; loughborough university } = true', 'tointer': 'select the row whose research funding ( 000 ) record of all rows is maximum . the institution record of this row is loughborough university .'} | eq { hop { argmax { all_rows ; research funding ( 000 ) } ; institution } ; loughborough university } = true | select the row whose research funding ( 000 ) record of all rows is maximum . the institution record of this row is loughborough university . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'research funding (000)_5': 5, 'institution_6': 6, 'loughborough university_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'research funding (000)_5': 'research funding ( 000 )', 'institution_6': 'institution', 'loughborough university_7': 'loughborough university'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'research funding (000)_5': [0], 'institution_6': [1], 'loughborough university_7': [2]} | ['institution', 'location', 'established', 'gained university status', 'vice - chancellor', 'total number of students', 'research funding ( 000 )'] | [['birkbeck , university of london', 'london', '1823', '1920', 'professor david latchman', '19020', '9985'], ['university of east anglia', 'norwich', '1963', '1963', 'professor edward acton', '19585', '16482'], ['university of essex', 'colchester', '1964', '1964', 'professor anthony forster', '11690', '9967'], ['goldsmiths , university of london', 'london', '1891', '1904', 'dr pat loughrey', '7615', '8539'], ['institute of education , university of london', 'london', '1902', '1932', 'professor chris husbands', '7215', '7734'], ['university of lancaster', 'lancaster', '1964', '1964', 'professor mark smith', '12695', '18640'], ['university of leicester', 'leicester', '1921', '1957', 'professor robert burgess', '16160', '22225'], ['loughborough university', 'loughborough', '1909', '1966', 'professor robert allison', '17825', '22398'], ['royal holloway , university of london', 'egham', '1849', '1900', 'professor paul layzell ( principal )', '7620', '13699'], ['soas , university of london', 'london', '1916', '1916', 'professor paul webley', '4525', '7238']] |
mexico national under - 20 football team | https://en.wikipedia.org/wiki/Mexico_national_under-20_football_team | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17736508-2.html.csv | count | two managers of the mexico national under - 20 football team have exactly 3 losses . | {'scope': 'all', 'criterion': 'equal', 'value': '3', 'result': '2', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'lost', '3'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose lost record is equal to 3 .', 'tostr': 'filter_eq { all_rows ; lost ; 3 }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; lost ; 3 } }', 'tointer': 'select the rows whose lost record is equal to 3 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; lost ; 3 } } ; 2 } = true', 'tointer': 'select the rows whose lost record is equal to 3 . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; lost ; 3 } } ; 2 } = true | select the rows whose lost record is equal to 3 . 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, 'lost_5': 5, '3_6': 6, '2_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'lost_5': 'lost', '3_6': '3', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'lost_5': [0], '3_6': [0], '2_7': [2]} | ['manager', 'mexico career', 'played', 'drawn', 'lost', 'win %'] | [['horacio casarin', '1977', '5', '4', '0', '20.0'], ['mario velarde', '1983', '3', '1', '2', '0.00'], ['jesús del muro', '1985 , 1998 - 1999', '12', '1', '2', '75.00'], ['alfonso portugal diaz', '1991', '4', '2', '1', '25.0'], ['juan de dios castillo', '1992 - 1993', '7', '2', '1', '60'], ['juan manuel alvarez', '1994', '3', '0', '1', '56.6'], ['josé luis real', '1996 - 1997 , 2001', '12', '3', '3', '50.00'], ['eduardo rergis', '2002 - 2003', '6', '1', '3', '33.3'], ['humberto grondona', '2005', '3', '0', '2', '33.3'], ['jesús ramírez', '2007 - 2009', '8', '1', '1', '75.00'], ['juan carlos chávez', '2009 - 2011', '19', '3', '4', '63.15'], ['sergio almaguer', '2011 -', '5', '0', '0', '100']] |
list of rampage killers | https://en.wikipedia.org/wiki/List_of_rampage_killers | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17794738-5.html.csv | count | there was a total of three rampage killing sprees in the country of france . | {'scope': 'all', 'criterion': 'equal', 'value': 'france', 'result': '3', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'france'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose country record fuzzily matches to france .', 'tostr': 'filter_eq { all_rows ; country ; france }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; country ; france } }', 'tointer': 'select the rows whose country record fuzzily matches to france . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; country ; france } } ; 3 } = true', 'tointer': 'select the rows whose country record fuzzily matches to france . the number of such rows is 3 .'} | eq { count { filter_eq { all_rows ; country ; france } } ; 3 } = true | select the rows whose country record fuzzily matches to france . 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, 'country_5': 5, 'france_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', 'country_5': 'country', 'france_6': 'france', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'country_5': [0], 'france_6': [0], '3_7': [2]} | ['perpetrator', 'date', 'year', 'location', 'country', 'killed', 'injured'] | [['grachev , peter', '07.31 july 31', '1925', 'ivankovo', 'soviet union', '17', '03 3'], ['ryan , michael robert , 27', '08.19 aug 19', '1987', 'hungerford', 'united kingdom', '16', '15'], ['borel , eric , 16', '09.23 sep 23 / 24', '1995', 'solliès - pont & cuers', 'france', '15', '04 4'], ['leibacher , friedrich , 57', '09.27 sep 27', '2001', 'zug', 'switzerland', '14', '18'], ['wagner , ernst august , 38', '09.04 sep 4', '1913', 'degerloch & mühlhausen / enz', 'german empire', '14', '11'], ['hz', '06.32', '1939.9', 'kz', 'fz', '100.9', '100.9'], ['unknown', '06.10 june 10 / 11', '1945', 'rouen', 'france', '14', '09 9'], ['dornier , christian , 31', '07.12 july 12', '1989', 'luxiol', 'france', '14', '08 8'], ['dembsky , vladimir', '02.15 feb 15', '1904', 'warsaw', 'russian empire', '13', '10'], ['bogdanović , ljubiša , 60', '04.09 april 9', '2013', 'velika ivanča', 'serbia', '13', '1'], ['bird , derrick , 52', '06.02 june 2', '2010', 'copeland , cumbria', 'united kingdom', '12', '11'], ['pz', '08.32', '1989.9', 'rz', 'soz', '100.9', '100.9'], ['marimon carles , jose , 26', '05.21 may 21', '1928', 'pobla de ferran', 'spain', '10', '02 2'], ['hedin , tore , 25', '08.22 aug 22', '1952', 'saxtorp & hurva', 'sweden', '9', '10 - 20'], ['izquierdo , antonio , 53 izquierdo , emilio , 58', '08.26 aug 26', '1990', 'puerto hurraco', 'spain', '9', '06.12 6 - 12'], ['palić , vinko , 28', '01.01 jan 1', '1993', 'zrinski topolovac', 'croatia', '9', '05.7 5 - 7'], ['tranchita , rosario', '09.25 june 25', '1925', 'librizzi', 'italy', '9', '04 4']] |
2008 - 09 indiana pacers season | https://en.wikipedia.org/wiki/2008%E2%80%9309_Indiana_Pacers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17326036-5.html.csv | aggregation | the average attendance in november for indiana pacers games at the conseco fieldhouse in the 2008 - 09 season was 14040 . | {'scope': 'all', 'col': '8', 'type': 'average', 'result': '14040', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'location attendance'], 'result': '14040', 'ind': 0, 'tostr': 'avg { all_rows ; location attendance }'}, '14040'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; location attendance } ; 14040 } = true', 'tointer': 'the average of the location attendance record of all rows is 14040 .'} | round_eq { avg { all_rows ; location attendance } ; 14040 } = true | the average of the location attendance record of all rows is 14040 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'location attendance_4': 4, '14040_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'location attendance_4': 'location attendance', '14040_5': '14040'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'location attendance_4': [0], '14040_5': [1]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record'] | [['2', 'november 1', 'boston', 'w 95 - 79 ( ot )', 'danny granger ( 20 )', 'marquis daniels ( 10 )', 'troy murphy ( 5 )', 'conseco fieldhouse 18165', '1 - 1'], ['3', 'november 5', 'phoenix', 'l 103 - 113 ( ot )', 't j ford , danny granger ( 23 )', 'troy murphy ( 10 )', 'troy murphy ( 4 )', 'conseco fieldhouse 11660', '1 - 2'], ['4', 'november 7', 'cleveland', 'l 107 - 111 ( ot )', 'danny granger ( 33 )', 'marquis daniels ( 11 )', 'marquis daniels ( 7 )', 'quicken loans arena 20562', '1 - 3'], ['5', 'november 8', 'new jersey', 'w 98 - 80 ( ot )', 'danny granger ( 23 )', 'jeff foster ( 13 )', 't j ford ( 9 )', 'conseco fieldhouse 14355', '2 - 3'], ['6', 'november 10', 'oklahoma city', 'w 107 - 99 ( ot )', 't j ford ( 24 )', 't j ford , danny granger ( 7 )', 't j ford ( 10 )', 'conseco fieldhouse 10165', '3 - 3'], ['7', 'november 12', 'new jersey', 'w 98 - 87 ( ot )', 't j ford ( 18 )', 't j ford ( 8 )', 't j ford ( 9 )', 'izod center 13551', '4 - 3'], ['8', 'november 14', 'philadelphia', 'l 92 - 94 ( ot )', 'danny granger ( 18 )', 'jeff foster ( 11 )', 't j ford ( 7 )', 'conseco fieldhouse 12742', '4 - 4'], ['9', 'november 15', 'chicago', 'l 91 - 104 ( ot )', 't j ford ( 16 )', 'troy murphy ( 13 )', 'troy murphy ( 5 )', 'united center 21759', '4 - 5'], ['10', 'november 18', 'atlanta', 'w 113 - 96 ( ot )', 'danny granger ( 34 )', 'troy murphy ( 19 )', 'radoslav nesterović , jarrett jack ( 5 )', 'conseco fieldhouse 13379', '5 - 5'], ['11', 'november 21', 'orlando', 'l 98 - 100 ( ot )', 'marquis daniels ( 25 )', 'troy murphy ( 10 )', 'radoslav nesterović ( 8 )', 'conseco fieldhouse 14699', '5 - 6'], ['12', 'november 22', 'miami', 'l 100 - 109 ( ot )', 'marquis daniels ( 25 )', 'troy murphy ( 11 )', 'danny granger , troy murphy ( 6 )', 'american airlines arena 18685', '5 - 7'], ['13', 'november 25', 'dallas', 'l 106 - 109 ( ot )', 'danny granger ( 22 )', 'troy murphy ( 14 )', 't j ford ( 7 )', 'american airlines center 19996', '5 - 8'], ['14', 'november 26', 'houston', 'w 91 - 90 ( ot )', 'troy murphy ( 21 )', 'troy murphy ( 14 )', 'danny granger ( 5 )', 'toyota center 18194', '6 - 8'], ['15', 'november 28', 'charlotte', 'l 108 - 115 ( ot )', 'danny granger ( 35 )', 'troy murphy ( 12 )', 't j ford ( 6 )', 'conseco fieldhouse 17160', '6 - 9'], ['16', 'november 29', 'orlando', 'l 96 - 110 ( ot )', 'danny granger ( 27 )', 'troy murphy ( 11 )', 't j ford , jarrett jack ( 5 )', 'amway arena 17172', '6 - 10']] |
upper grand district school board | https://en.wikipedia.org/wiki/Upper_Grand_District_School_Board | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1803594-1.html.csv | comparative | centennial collegiate vocational institute has a lower enrollment than john f ross collegiate vocational institute . | {'row_1': '1', 'row_2': '7', 'col': '3', 'col_other': '1', 'relation': 'diff', 'record_mentioned': 'no', 'diff_result': {'diff_value': '362', 'bigger': 'row2'}} | {'func': 'eq', 'args': [{'func': 'diff', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'name', 'centennial collegiate vocational institute'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose name record fuzzily matches to centennial collegiate vocational institute .', 'tostr': 'filter_eq { all_rows ; name ; centennial collegiate vocational institute }'}, 'enrollment'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; name ; centennial collegiate vocational institute } ; enrollment }', 'tointer': 'select the rows whose name record fuzzily matches to centennial collegiate vocational institute . take the enrollment record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'name', 'john f ross collegiate vocational institute'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose name record fuzzily matches to john f ross collegiate vocational institute .', 'tostr': 'filter_eq { all_rows ; name ; john f ross collegiate vocational institute }'}, 'enrollment'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; name ; john f ross collegiate vocational institute } ; enrollment }', 'tointer': 'select the rows whose name record fuzzily matches to john f ross collegiate vocational institute . take the enrollment record of this row .'}], 'result': '-362', 'ind': 4, 'tostr': 'diff { hop { filter_eq { all_rows ; name ; centennial collegiate vocational institute } ; enrollment } ; hop { filter_eq { all_rows ; name ; john f ross collegiate vocational institute } ; enrollment } }'}, '-362'], 'result': True, 'ind': 5, 'tostr': 'eq { diff { hop { filter_eq { all_rows ; name ; centennial collegiate vocational institute } ; enrollment } ; hop { filter_eq { all_rows ; name ; john f ross collegiate vocational institute } ; enrollment } } ; -362 } = true', 'tointer': 'select the rows whose name record fuzzily matches to centennial collegiate vocational institute . take the enrollment record of this row . select the rows whose name record fuzzily matches to john f ross collegiate vocational institute . take the enrollment record of this row . the second record is 362 larger than the first record .'} | eq { diff { hop { filter_eq { all_rows ; name ; centennial collegiate vocational institute } ; enrollment } ; hop { filter_eq { all_rows ; name ; john f ross collegiate vocational institute } ; enrollment } } ; -362 } = true | select the rows whose name record fuzzily matches to centennial collegiate vocational institute . take the enrollment record of this row . select the rows whose name record fuzzily matches to john f ross collegiate vocational institute . take the enrollment record of this row . the second record is 362 larger than the first record . | 6 | 6 | {'eq_5': 5, 'result_6': 6, 'diff_4': 4, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_7': 7, 'name_8': 8, 'centennial collegiate vocational institute_9': 9, 'enrollment_10': 10, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_11': 11, 'name_12': 12, 'john f ross collegiate vocational institute_13': 13, 'enrollment_14': 14, '-362_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', 'centennial collegiate vocational institute_9': 'centennial collegiate vocational institute', 'enrollment_10': 'enrollment', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_11': 'all_rows', 'name_12': 'name', 'john f ross collegiate vocational institute_13': 'john f ross collegiate vocational institute', 'enrollment_14': 'enrollment', '-362_15': '-362'} | {'eq_5': [6], 'result_6': [], 'diff_4': [5], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_7': [0], 'name_8': [0], 'centennial collegiate vocational institute_9': [0], 'enrollment_10': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_11': [1], 'name_12': [1], 'john f ross collegiate vocational institute_13': [1], 'enrollment_14': [3], '-362_15': [5]} | ['name', 'location', 'enrollment', '1 - year ranking of 727', '5 - year ranking of 693'] | [['centennial collegiate vocational institute', 'guelph', '1533', '63', '22'], ['centre dufferin district high school', 'shelburne', '998', '265', '281'], ['centre wellington district high school', 'fergus', '1459', '330', '246'], ['college heights secondary school', 'guelph', '649', '717', '688'], ['erin district high school', 'erin', '616', '197', '148'], ['guelph collegiate vocational institute', 'guelph', '1314', '16', '30'], ['john f ross collegiate vocational institute', 'guelph', '1895', '181', '165'], ['norwell district secondary school', 'palmerston', '795', '126', '343'], ['orangeville district secondary school', 'orangeville', '1574', '181', '194'], ['wellington heights secondary school', 'mount forest', '680', '371', '426'], ['westside secondary school', 'orangeville', '996', '478', '343']] |
united states house of representatives elections , 1988 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1988 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1341577-22.html.csv | unique | edward boland was the only united states house of representatives incumbent that retired . | {'scope': 'all', 'row': '2', 'col': '5', 'col_other': '2', 'criterion': 'equal', 'value': 'retired', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'result', 'retired'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose result record fuzzily matches to retired .', 'tostr': 'filter_eq { all_rows ; result ; retired }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; result ; retired } }', 'tointer': 'select the rows whose result record fuzzily matches to retired . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'result', 'retired'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose result record fuzzily matches to retired .', 'tostr': 'filter_eq { all_rows ; result ; retired }'}, 'incumbent'], 'result': 'edward boland', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; result ; retired } ; incumbent }'}, 'edward boland'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; result ; retired } ; incumbent } ; edward boland }', 'tointer': 'the incumbent record of this unqiue row is edward boland .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; result ; retired } } ; eq { hop { filter_eq { all_rows ; result ; retired } ; incumbent } ; edward boland } } = true', 'tointer': 'select the rows whose result record fuzzily matches to retired . there is only one such row in the table . the incumbent record of this unqiue row is edward boland .'} | and { only { filter_eq { all_rows ; result ; retired } } ; eq { hop { filter_eq { all_rows ; result ; retired } ; incumbent } ; edward boland } } = true | select the rows whose result record fuzzily matches to retired . there is only one such row in the table . the incumbent record of this unqiue row is edward boland . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'result_7': 7, 'retired_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'incumbent_9': 9, 'edward boland_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'result_7': 'result', 'retired_8': 'retired', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'incumbent_9': 'incumbent', 'edward boland_10': 'edward boland'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'result_7': [0], 'retired_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'incumbent_9': [2], 'edward boland_10': [3]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['massachusetts 1', 'silvio conte', 'republican', '1958', 're - elected', 'silvio conte ( r ) 82.7 % john r arden ( d ) 17.3 %'], ['massachusetts 2', 'edward boland', 'democratic', '1952', 'retired democratic hold', 'richard neal ( d ) 80.3 % louis r godena ( i ) 19.7 %'], ['massachusetts 3', 'joseph d early', 'democratic', '1974', 're - elected', 'joseph d early ( d ) unopposed'], ['massachusetts 4', 'barney frank', 'democratic', '1980', 're - elected', 'barney frank ( d ) 70.3 % debra r tucker ( r ) 29.7 %'], ['massachusetts 7', 'ed markey', 'democratic', '1976', 're - elected', 'ed markey ( d ) unopposed'], ['massachusetts 9', 'joe moakley', 'democratic', '1972', 're - elected', 'joe moakley ( d ) unopposed']] |
washington redskins draft history | https://en.wikipedia.org/wiki/Washington_Redskins_draft_history | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17100961-5.html.csv | majority | in the washington redskins draft history , all of the players were the 2nd pick in their round . | {'scope': 'all', 'col': '2', 'most_or_all': 'all', 'criterion': 'equal', 'value': '2', 'subset': None} | {'func': 'all_eq', 'args': ['all_rows', 'pick', '2'], 'result': True, 'ind': 0, 'tointer': 'for the pick records of all rows , all of them are equal to 2 .', 'tostr': 'all_eq { all_rows ; pick ; 2 } = true'} | all_eq { all_rows ; pick ; 2 } = true | for the pick records of all rows , all of them are equal to 2 . | 1 | 1 | {'all_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'pick_3': 3, '2_4': 4} | {'all_eq_0': 'all_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'pick_3': 'pick', '2_4': '2'} | {'all_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'pick_3': [0], '2_4': [0]} | ['round', 'pick', 'overall', 'name', 'position', 'college'] | [['1', '2', '2', 'riley smith', 'fb', 'alabama'], ['2', '2', '11', 'keith topping', 'e', 'stanford'], ['3', '2', '20', 'ed smith', 'fb', 'new york'], ['4', '2', '29', 'paul tangora', 'g', 'northwestern'], ['5', '2', '38', 'wilson groseclose', 'ot', 'texas christian'], ['6', '2', '47', 'larry lutz', 'ot', 'california'], ['7', '2', '56', 'don irwin', 'fb', 'colgate'], ['8', '2', '65', 'wayne millner', 'e', 'notre dame'], ['9', '2', '74', 'marcel saunders', 'g', 'loyola']] |
2008 victoria cup | https://en.wikipedia.org/wiki/2008_Victoria_Cup | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17058856-1.html.csv | ordinal | denis platonov scored the first goal during the 2008 victoria cup . | {'row': '1', 'col': '4', 'order': '1', 'col_other': '3', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'time', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; time ; 1 }'}, 'goal'], 'result': 'denis platonov ( 1 )', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; time ; 1 } ; goal }'}, 'denis platonov ( 1 )'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; time ; 1 } ; goal } ; denis platonov ( 1 ) } = true', 'tointer': 'select the row whose time record of all rows is 1st minimum . the goal record of this row is denis platonov ( 1 ) .'} | eq { hop { nth_argmin { all_rows ; time ; 1 } ; goal } ; denis platonov ( 1 ) } = true | select the row whose time record of all rows is 1st minimum . the goal record of this row is denis platonov ( 1 ) . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'time_5': 5, '1_6': 6, 'goal_7': 7, 'denis platonov (1)_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmin_0': 'nth_argmin', 'all_rows_4': 'all_rows', 'time_5': 'time', '1_6': '1', 'goal_7': 'goal', 'denis platonov (1)_8': 'denis platonov ( 1 )'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'time_5': [0], '1_6': [0], 'goal_7': [1], 'denis platonov (1)_8': [2]} | ['period', 'team', 'goal', 'time', 'score'] | [['1st', 'met', 'denis platonov ( 1 )', '1:28', '0 - 1 met'], ['1st', 'met', 'vladimir malenkikh ( 1 ) ( pp )', '18:27', '0 - 2 met'], ['2nd', 'met', 'nikolai zavarukhin ( 1 )', '30:20', '0 - 3 met'], ['2nd', 'nyr', 'chris drury ( 1 ) ( pp )', '39:37', '1 - 3 nyr'], ['3rd', 'nyr', 'dan fritsche ( 1 )', '45:45', '2 - 3 nyr'], ['3rd', 'nyr', 'chris drury ( 2 ) ( pp )', '50:13', '3 - 3 nyr'], ['3rd', 'nyr', 'ryan callahan ( 1 )', '59:40', '4 - 3 nyr']] |
karen walker ( footballer ) | https://en.wikipedia.org/wiki/Karen_Walker_%28footballer%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17150259-1.html.csv | aggregation | in total , karen walker scored 28 goals from 1993 to 2002 . | {'scope': 'all', 'col': '6', 'type': 'sum', 'result': '28', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'scored'], 'result': '28', 'ind': 0, 'tostr': 'sum { all_rows ; scored }'}, '28'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; scored } ; 28 } = true', 'tointer': 'the sum of the scored record of all rows is 28 .'} | round_eq { sum { all_rows ; scored } ; 28 } = true | the sum of the scored record of all rows is 28 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'scored_4': 4, '28_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'scored_4': 'scored', '28_5': '28'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'scored_4': [0], '28_5': [1]} | ['goal', 'date', 'venue', 'result', 'competition', 'scored'] | [['3', '25 september 1993', 'bežigrad stadium , ljubljana', '10 - 0', '1995 uefa championship qual', '3'], ['5', '6 november 1993', 'kvv coxyde , koksijde', '3 - 0', '1995 uefa championship qual', '2'], ['7', '13 march 1994', 'city ground , nottingham', '6 - 0', '1995 uefa championship qual', '2'], ['9', '17 april 1994', 'griffin park , brentford', '10 - 0', '1995 uefa championship qual', '2'], ['10', '8 june 1995', 'tingvalla ip , karlstad', '3 - 2', '1995 world cup', '1'], ['12', '19 november 1995', 'the valley , london', '5 - 0', '1997 uefa championship qual', '2'], ['13', '23 may 1998', 'sportpark olympia , waalwijk', '1 - 2', '1999 world cup qual', '1'], ['15', '13 september 1998', 'stadionul poiana , cmpina', '4 - 1', '1999 world cup qual', '2'], ['16', '11 october 1998', 'adams park , wycombe', '2 - 1', '1999 world cup qual', '1'], ['17', '26 may 1999', 'lugo , emilia - romagna', '1 - 4', 'friendly', '1'], ['18', '22 august 1999', 'odense stadion , odense', '1 - 0', 'friendly', '1'], ['19', '17 october 1999', 'sportanlagen trinermatten , zofingen', '3 - 0', '2001 uefa championship qual', '1'], ['20', '20 february 2000', 'oakwell , barnsley', '2 - 0', '2001 uefa championship qual', '1'], ['21', '30 october 2000', 'kolos stadium , boryspil', '2 - 1', '2001 uefa championship qual', '1'], ['22', '24 november 2001', 'complexo desportivo da gafanha , gafanha da nazaré', '1 - 1', '2003 world cup qual', '1'], ['24', '5 march 2002', 'estádio municipal , lagos', '3 - 6', 'algarve cup', '2'], ['25', '7 march 2002', 'estádio municipal , quarteira', '4 - 1', 'algarve cup', '1'], ['25', '23 march 2002', 'zuiderpark stadion , the hague', '4 - 0', '2003 world cup qual', '1'], ['27', '16 september 2002', 'laugardalsvöllur , reykjavík', '2 - 2', '2003 world cup qual', '2']] |
triple - a baseball national championship game | https://en.wikipedia.org/wiki/Triple-A_Baseball_National_Championship_Game | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13128203-2.html.csv | count | in the triple - a baseball national championship game , when the winning percentage was 1.0 , there were 2 times that there were 2 wins . | {'scope': 'subset', 'criterion': 'equal', 'value': '2', 'result': '2', 'col': '3', 'subset': {'col': '5', 'criterion': 'equal', 'value': '1'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'winning percentage', '1'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; winning percentage ; 1 }', 'tointer': 'select the rows whose winning percentage record is equal to 1 .'}, 'wins', '2'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose winning percentage record is equal to 1 . among these rows , select the rows whose wins record is equal to 2 .', 'tostr': 'filter_eq { filter_eq { all_rows ; winning percentage ; 1 } ; wins ; 2 }'}], 'result': '2', 'ind': 2, 'tostr': 'count { filter_eq { filter_eq { all_rows ; winning percentage ; 1 } ; wins ; 2 } }', 'tointer': 'select the rows whose winning percentage record is equal to 1 . among these rows , select the rows whose wins record is equal to 2 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_eq { filter_eq { all_rows ; winning percentage ; 1 } ; wins ; 2 } } ; 2 } = true', 'tointer': 'select the rows whose winning percentage record is equal to 1 . among these rows , select the rows whose wins record is equal to 2 . the number of such rows is 2 .'} | eq { count { filter_eq { filter_eq { all_rows ; winning percentage ; 1 } ; wins ; 2 } } ; 2 } = true | select the rows whose winning percentage record is equal to 1 . among these rows , select the rows whose wins record is equal to 2 . the number of such rows is 2 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_eq_1': 1, 'filter_eq_0': 0, 'all_rows_5': 5, 'winning percentage_6': 6, '1_7': 7, 'wins_8': 8, '2_9': 9, '2_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_eq_1': 'filter_eq', 'filter_eq_0': 'filter_eq', 'all_rows_5': 'all_rows', 'winning percentage_6': 'winning percentage', '1_7': '1', 'wins_8': 'wins', '2_9': '2', '2_10': '2'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_eq_1': [2], 'filter_eq_0': [1], 'all_rows_5': [0], 'winning percentage_6': [0], '1_7': [0], 'wins_8': [1], '2_9': [1], '2_10': [3]} | ['appearances', 'team', 'wins', 'losses', 'winning percentage', 'season ( s )'] | [['2', 'sacramento rivercats', '2', '0', '1.000', '2007 , 2008'], ['2', 'columbus clippers', '2', '0', '1.000', '2010 , 2011'], ['2', 'durham bulls', '1', '1', '500', '2009 , 2013'], ['2', 'omaha storm chasers', '1', '1', '500', '2011 , 2013'], ['1', 'tucson sidewinders', '1', '0', '1.000', '2006'], ['1', 'reno aces', '1', '0', '1.000', '2012'], ['1', 'toledo mud hens', '0', '1', '000', '2006'], ['1', 'richmond braves', '0', '1', '000', '2007'], ['1', 'scranton / wilkes - barre yankees', '0', '1', '000', '2008'], ['1', 'memphis redbirds', '0', '1', '000', '2009'], ['1', 'tacoma rainiers', '0', '1', '000', '2010'], ['1', 'pawtucket red sox', '0', '1', '000', '2012']] |
forest hill railway station | https://en.wikipedia.org/wiki/Forest_Hill_railway_station | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1569516-1.html.csv | majority | most of the the trains which come through the forest hill railway station is on the metro line . | {'scope': 'all', 'col': '6', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'metro', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'line', 'metro'], 'result': True, 'ind': 0, 'tointer': 'for the line records of all rows , most of them fuzzily match to metro .', 'tostr': 'most_eq { all_rows ; line ; metro } = true'} | most_eq { all_rows ; line ; metro } = true | for the line records of all rows , most of them fuzzily match to metro . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'line_3': 3, 'metro_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'line_3': 'line', 'metro_4': 'metro'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'line_3': [0], 'metro_4': [0]} | ['platform', 'frequency ( per hour )', 'destination', 'service pattern', 'operator', 'line'] | [['1', '4', 'highbury & islington', 'all stations via shoreditch high street', 'london overground', 'east london'], ['1', '4', 'dalston junction', 'all stations via shoreditch high street', 'london overground', 'east london'], ['1', '4', 'london bridge', 'all stations', 'southern', 'metro'], ['2', '4', 'crystal palace', 'all stations', 'london overground', 'east london'], ['2', '4', 'west croydon', 'all stations', 'london overground', 'east london'], ['2', '2', 'london victoria ( mon - sat )', 'all stations via clapham junction', 'southern', 'metro'], ['2', '2', 'caterham ( mon - sat )', 'all stations via east croydon', 'southern', 'metro'], ['2', '2', 'west croydon ( peaks & sun only )', 'sydenham then fast to norwood junction', 'southern', 'metro'], ['2', '2', 'tattenham corner ( sun only )', 'all stations via east croydon', 'southern', 'metro']] |
betty stöve | https://en.wikipedia.org/wiki/Betty_St%C3%B6ve | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2820584-3.html.csv | count | for the championships betty stöve participated in , when the surface was grass , there were 4 occasions when the championship was wimbledon . | {'scope': 'subset', 'criterion': 'equal', 'value': 'wimbledon', 'result': '4', 'col': '3', 'subset': {'col': '4', 'criterion': 'equal', 'value': 'grass'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'surface', 'grass'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; surface ; grass }', 'tointer': 'select the rows whose surface record fuzzily matches to grass .'}, 'championship', 'wimbledon'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose surface record fuzzily matches to grass . among these rows , select the rows whose championship record fuzzily matches to wimbledon .', 'tostr': 'filter_eq { filter_eq { all_rows ; surface ; grass } ; championship ; wimbledon }'}], 'result': '4', 'ind': 2, 'tostr': 'count { filter_eq { filter_eq { all_rows ; surface ; grass } ; championship ; wimbledon } }', 'tointer': 'select the rows whose surface record fuzzily matches to grass . among these rows , select the rows whose championship record fuzzily matches to wimbledon . the number of such rows is 4 .'}, '4'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_eq { filter_eq { all_rows ; surface ; grass } ; championship ; wimbledon } } ; 4 } = true', 'tointer': 'select the rows whose surface record fuzzily matches to grass . among these rows , select the rows whose championship record fuzzily matches to wimbledon . the number of such rows is 4 .'} | eq { count { filter_eq { filter_eq { all_rows ; surface ; grass } ; championship ; wimbledon } } ; 4 } = true | select the rows whose surface record fuzzily matches to grass . among these rows , select the rows whose championship record fuzzily matches to wimbledon . the number of such rows is 4 . | 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, 'surface_6': 6, 'grass_7': 7, 'championship_8': 8, 'wimbledon_9': 9, '4_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', 'surface_6': 'surface', 'grass_7': 'grass', 'championship_8': 'championship', 'wimbledon_9': 'wimbledon', '4_10': '4'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_str_eq_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'surface_6': [0], 'grass_7': [0], 'championship_8': [1], 'wimbledon_9': [1], '4_10': [3]} | ['outcome', 'year', 'championship', 'surface', 'partner', 'opponents in the final', 'score in the final'] | [['runner - up', '1971', 'us open', 'grass', 'bob maud', 'billie jean king owen davidson', '6 - 3 , 7 - 5'], ['runner - up', '1973', 'french open', 'clay', 'patrice dominguez', 'françoise dürr jean - claude barclay', '6 - 1 , 6 - 4'], ['runner - up', '1975', 'wimbledon', 'grass', 'allan stone', 'margaret court marty riessen', '6 - 4 , 7 - 5'], ['runner - up', '1976', 'us open', 'clay', 'frew mcmillan', 'billie jean king phil dent', '3 - 6 , 6 - 2 , 7 - 5'], ['runner - up', '1977', 'wimbledon', 'grass', 'frew mcmillan', 'greer stevens bob hewitt', '3 - 6 , 7 - 5 , 6 - 4'], ['winner', '1977', 'us open', 'clay', 'frew mcmillan', 'billie jean king vitas gerulaitis', '6 - 2 , 3 - 6 , 6 - 3'], ['winner', '1978', 'wimbledon', 'grass', 'frew mcmillan', 'billie jean king ray ruffels', '6 - 2 , 6 - 2'], ['winner', '1978', 'us open ( 2 )', 'hard', 'frew mcmillan', 'billie jean king ray ruffels', '6 - 3 , 7 - 6'], ['runner - up', '1979', 'wimbledon', 'grass', 'frew mcmillan', 'greer stevens bob hewitt', '7 - 5 , 7 - 6'], ['runner - up', '1979', 'us open', 'hard', 'frew mcmillan', 'greer stevens bob hewitt', '6 - 3 , 7 - 5'], ['runner - up', '1980', 'us open', 'hard', 'frew mcmillan', 'wendy turnbull marty riessen', '7 - 5 , 6 - 2'], ['runner - up', '1981', 'french open', 'clay', 'fred mcnair', 'andrea jaeger jimmy arias', '7 - 6 , 6 - 4']] |
1945 vfl season | https://en.wikipedia.org/wiki/1945_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10809271-16.html.csv | superlative | in the 1945 vfl season , the highest attendance for the games where home team scored more than 10 was in victoria park . | {'scope': 'subset', 'col_superlative': '6', 'row_superlative': '3', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '2,5', 'subset': {'col': '2', 'criterion': 'greater_than', 'value': '10'}} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'home team score', '10'], 'result': None, 'ind': 0, 'tostr': 'filter_greater { all_rows ; home team score ; 10 }', 'tointer': 'select the rows whose home team score record is greater than 10 .'}, 'crowd'], 'result': None, 'ind': 1, 'tostr': 'argmax { filter_greater { all_rows ; home team score ; 10 } ; crowd }'}, 'venue'], 'result': 'victoria park', 'ind': 2, 'tostr': 'hop { argmax { filter_greater { all_rows ; home team score ; 10 } ; crowd } ; venue }'}, 'victoria park'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { argmax { filter_greater { all_rows ; home team score ; 10 } ; crowd } ; venue } ; victoria park } = true', 'tointer': 'select the rows whose home team score record is greater than 10 . select the row whose crowd record of these rows is maximum . the venue record of this row is victoria park .'} | eq { hop { argmax { filter_greater { all_rows ; home team score ; 10 } ; crowd } ; venue } ; victoria park } = true | select the rows whose home team score record is greater than 10 . select the row whose crowd record of these rows is maximum . the venue record of this row is victoria park . | 4 | 4 | {'str_eq_3': 3, 'result_4': 4, 'str_hop_2': 2, 'argmax_1': 1, 'filter_greater_0': 0, 'all_rows_5': 5, 'home team score_6': 6, '10_7': 7, 'crowd_8': 8, 'venue_9': 9, 'victoria park_10': 10} | {'str_eq_3': 'str_eq', 'result_4': 'true', 'str_hop_2': 'str_hop', 'argmax_1': 'argmax', 'filter_greater_0': 'filter_greater', 'all_rows_5': 'all_rows', 'home team score_6': 'home team score', '10_7': '10', 'crowd_8': 'crowd', 'venue_9': 'venue', 'victoria park_10': 'victoria park'} | {'str_eq_3': [4], 'result_4': [], 'str_hop_2': [3], 'argmax_1': [2], 'filter_greater_0': [1], 'all_rows_5': [0], 'home team score_6': [0], '10_7': [0], 'crowd_8': [1], 'venue_9': [2], 'victoria park_10': [3]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['geelong', '7.14 ( 56 )', 'melbourne', '17.13 ( 115 )', 'kardinia park', '7000', '4 august 1945'], ['footscray', '7.13 ( 55 )', 'south melbourne', '8.8 ( 56 )', 'western oval', '27000', '4 august 1945'], ['collingwood', '16.8 ( 104 )', 'essendon', '10.15 ( 75 )', 'victoria park', '19000', '4 august 1945'], ['richmond', '15.15 ( 105 )', 'hawthorn', '19.7 ( 121 )', 'punt road oval', '13000', '4 august 1945'], ['north melbourne', '12.6 ( 78 )', 'fitzroy', '4.9 ( 33 )', 'arden street oval', '14000', '4 august 1945'], ['st kilda', '7.15 ( 57 )', 'carlton', '11.13 ( 79 )', 'junction oval', '10000', '4 august 1945']] |
list of sons of anarchy episodes | https://en.wikipedia.org/wiki/List_of_Sons_of_Anarchy_episodes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-20726262-2.html.csv | comparative | for the episodes of sons of anarchy , the one titled " capybara " aired 7 days before the episode titled " the sleep of babies . " . | {'row_1': '11', 'row_2': '12', 'col': '5', 'col_other': '2', 'relation': 'diff', 'record_mentioned': 'no', 'diff_result': {'diff_value': '7 days', 'bigger': 'row2'}} | {'func': 'eq', 'args': [{'func': 'diff', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'title', 'capybara'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose title record fuzzily matches to capybara .', 'tostr': 'filter_eq { all_rows ; title ; capybara }'}, 'originalairdate'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; title ; capybara } ; originalairdate }', 'tointer': 'select the rows whose title record fuzzily matches to capybara . take the originalairdate record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'title', 'the sleep of babies'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose title record fuzzily matches to the sleep of babies .', 'tostr': 'filter_eq { all_rows ; title ; the sleep of babies }'}, 'originalairdate'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; title ; the sleep of babies } ; originalairdate }', 'tointer': 'select the rows whose title record fuzzily matches to the sleep of babies . take the originalairdate record of this row .'}], 'result': '-7 days', 'ind': 4, 'tostr': 'diff { hop { filter_eq { all_rows ; title ; capybara } ; originalairdate } ; hop { filter_eq { all_rows ; title ; the sleep of babies } ; originalairdate } }'}, '-7 days'], 'result': True, 'ind': 5, 'tostr': 'eq { diff { hop { filter_eq { all_rows ; title ; capybara } ; originalairdate } ; hop { filter_eq { all_rows ; title ; the sleep of babies } ; originalairdate } } ; -7 days } = true', 'tointer': 'select the rows whose title record fuzzily matches to capybara . take the originalairdate record of this row . select the rows whose title record fuzzily matches to the sleep of babies . take the originalairdate record of this row . the second record is 7 days larger than the first record .'} | eq { diff { hop { filter_eq { all_rows ; title ; capybara } ; originalairdate } ; hop { filter_eq { all_rows ; title ; the sleep of babies } ; originalairdate } } ; -7 days } = true | select the rows whose title record fuzzily matches to capybara . take the originalairdate record of this row . select the rows whose title record fuzzily matches to the sleep of babies . take the originalairdate record of this row . the second record is 7 days larger than the first record . | 6 | 6 | {'str_eq_5': 5, 'result_6': 6, 'diff_4': 4, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_7': 7, 'title_8': 8, 'capybara_9': 9, 'originalairdate_10': 10, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_11': 11, 'title_12': 12, 'the sleep of babies_13': 13, 'originalairdate_14': 14, '-7 days_15': 15} | {'str_eq_5': 'str_eq', 'result_6': 'true', 'diff_4': 'diff', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_7': 'all_rows', 'title_8': 'title', 'capybara_9': 'capybara', 'originalairdate_10': 'originalairdate', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_11': 'all_rows', 'title_12': 'title', 'the sleep of babies_13': 'the sleep of babies', 'originalairdate_14': 'originalairdate', '-7 days_15': '-7 days'} | {'str_eq_5': [6], 'result_6': [], 'diff_4': [5], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_7': [0], 'title_8': [0], 'capybara_9': [0], 'originalairdate_10': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_11': [1], 'title_12': [1], 'the sleep of babies_13': [1], 'originalairdate_14': [3], '-7 days_15': [5]} | ['no in series', 'title', 'directedby', 'writtenby', 'originalairdate', 'production code'] | [['1', 'pilot', 'allen coulter & michael dinner', 'kurt sutter', 'september 3 , 2008', '1wab79'], ['2', 'seeds', 'charles haid', 'kurt sutter', 'september 10 , 2008', '1wab01'], ['3', 'fun town', 'stephen kay', 'kurt sutter', 'september 17 , 2008', '1wab02'], ['4', 'patch over', 'paris barclay', 'james d parriott', 'september 24 , 2008', '1wab03'], ['5', 'giving back', 'tim hunter', 'jack logiudice', 'october 1 , 2008', '1wab04'], ['6', 'ak - 51', 'seith mann', 'nichole beattie', 'october 8 , 2008', '1wab05'], ['7', 'old bones', 'gwyneth horder - payton', 'dave erickson', 'october 15 , 2008', '1wab06'], ['8', 'the pull', 'guy ferland', 'kurt sutter & jack logiudice', 'october 22 , 2008', '1wab07'], ['9', 'hell followed', 'billy gierhart', 'brett conrad', 'october 29 , 2008', '1wab08'], ['10', 'better half', 'mario van peebles', 'pat charles', 'november 5 , 2008', '1wab09'], ['11', 'capybara', 'stephen kay', 'kurt sutter & dave erickson', 'november 12 , 2008', '1wab10'], ['12', 'the sleep of babies', "terrence o'hara", 'kurt sutter', 'november 19 , 2008', '1wab11']] |
patiparn phetphun | https://en.wikipedia.org/wiki/Patiparn_Phetphun | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18046242-2.html.csv | unique | the game on march 21 , 2007 was the only patiparn phetphun game that ended in a 1-1 score . | {'scope': 'all', 'row': '2', 'col': '4', 'col_other': '1', 'criterion': 'equal', 'value': '1-1', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'score', '1-1'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose score record fuzzily matches to 1-1 .', 'tostr': 'filter_eq { all_rows ; score ; 1-1 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; score ; 1-1 } }', 'tointer': 'select the rows whose score record fuzzily matches to 1-1 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'score', '1-1'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose score record fuzzily matches to 1-1 .', 'tostr': 'filter_eq { all_rows ; score ; 1-1 }'}, 'date'], 'result': 'march 21 , 2007', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; score ; 1-1 } ; date }'}, 'march 21 , 2007'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; score ; 1-1 } ; date } ; march 21 , 2007 }', 'tointer': 'the date record of this unqiue row is march 21 , 2007 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; score ; 1-1 } } ; eq { hop { filter_eq { all_rows ; score ; 1-1 } ; date } ; march 21 , 2007 } } = true', 'tointer': 'select the rows whose score record fuzzily matches to 1-1 . there is only one such row in the table . the date record of this unqiue row is march 21 , 2007 .'} | and { only { filter_eq { all_rows ; score ; 1-1 } } ; eq { hop { filter_eq { all_rows ; score ; 1-1 } ; date } ; march 21 , 2007 } } = true | select the rows whose score record fuzzily matches to 1-1 . there is only one such row in the table . the date record of this unqiue row is march 21 , 2007 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'score_7': 7, '1-1_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'date_9': 9, 'march 21 , 2007_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'score_7': 'score', '1-1_8': '1-1', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'date_9': 'date', 'march 21 , 2007_10': 'march 21 , 2007'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'score_7': [0], '1-1_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'date_9': [2], 'march 21 , 2007_10': [3]} | ['date', 'venue', 'opponent', 'score', 'result'] | [['march 7 , 2007', 'bangkok , thailand', 'chunnam dragons', '0 - 0', 'draw'], ['march 21 , 2007', 'kawasaki , japan', 'kawasaki frontale', '1 - 1', 'draw'], ['april 11 , 2007', 'bangkok , thailand', 'arema malang', '0 - 0', 'draw'], ['april 25 , 2007', 'malang , indonesia', 'arema malang', '0 - 1', 'lost'], ['may 9 , 2007', 'gwangyang , south korea', 'chunnam dragons', '2 - 3', 'lost'], ['may 23 , 2007', 'bangkok , thailand', 'kawasaki frontale', '1 - 2', 'lost']] |
list of top association football goal scorers | https://en.wikipedia.org/wiki/List_of_top_association_football_goal_scorers | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11336844-1.html.csv | majority | a majority of the top association football goal scorers had more than 1000 goals . | {'scope': 'all', 'col': '6', 'most_or_all': 'most', 'criterion': 'greater_than', 'value': '1000', 'subset': None} | {'func': 'most_greater', 'args': ['all_rows', 'goals', '1000'], 'result': True, 'ind': 0, 'tointer': 'for the goals records of all rows , most of them are greater than 1000 .', 'tostr': 'most_greater { all_rows ; goals ; 1000 } = true'} | most_greater { all_rows ; goals ; 1000 } = true | for the goals records of all rows , most of them are greater than 1000 . | 1 | 1 | {'most_greater_0': 0, 'result_1': 1, 'all_rows_2': 2, 'goals_3': 3, '1000_4': 4} | {'most_greater_0': 'most_greater', 'result_1': 'true', 'all_rows_2': 'all_rows', 'goals_3': 'goals', '1000_4': '1000'} | {'most_greater_0': [1], 'result_1': [], 'all_rows_2': [0], 'goals_3': [0], '1000_4': [0]} | ['rank', 'name', 'country', 'years', 'matches', 'goals'] | [['1', 'josef bican', 'austria czech republic', '1931 - 1956', '918', '1468'], ['2', 'gerd mã ¼ ller', 'germany', '1962 - 1983', '1216', '1461'], ['3', 'arthur friedenreich', 'brazil', '1909 - 1935', '1239', '1329'], ['4', 'pele', 'brazil', '1956 - 1990', '1375', '1284'], ['5', 'franz binder', 'austria germany', '1930 - 1949', '756', '1006'], ['6', 'romario', 'brazil', '1985 - 2007', '1188', '968'], ['7', 'ferenc puskas', 'hungary spain', '1943 - 1966', '754', '746']] |
2004 molson indy montreal | https://en.wikipedia.org/wiki/2004_Molson_Indy_Montreal | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16838759-2.html.csv | aggregation | in the 2004 molson indy montreal , the average number of points is 14.56 . | {'scope': 'all', 'col': '6', 'type': 'average', 'result': '14.56', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'points'], 'result': '14.56', 'ind': 0, 'tostr': 'avg { all_rows ; points }'}, '14.56'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; points } ; 14.56 } = true', 'tointer': 'the average of the points record of all rows is 14.56 .'} | round_eq { avg { all_rows ; points } ; 14.56 } = true | the average of the points record of all rows is 14.56 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'points_4': 4, '14.56_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'points_4': 'points', '14.56_5': '14.56'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'points_4': [0], '14.56_5': [1]} | ['driver', 'team', 'laps', 'time / retired', 'grid', 'points'] | [['bruno junqueira', 'newman / haas racing', '69', '1:39:12.432', '4', '32'], ['patrick carpentier', 'forsythe racing', '69', '+ 6.382 secs', '6', '27'], ['mario domínguez', 'herdez competition', '69', '+ 11.142 secs', '3', '26'], ['paul tracy', 'forsythe racing', '69', '+ 16.874 secs', '5', '23'], ['a j allmendinger', 'rusport', '69', '+ 17.561 secs', '2', '22'], ['michel jourdain , jr', 'rusport', '69', '+ 32.256 secs', '12', '20'], ['alex tagliani', 'rocketsports racing', '69', '+ 32.300 secs', '7', '17'], ['jimmy vasser', 'pkv racing', '69', '+ 34.097 secs', '11', '15'], ['oriol servià', 'dale coyne racing', '69', '+ 42.654 secs', '10', '13'], ['roberto gonzález', 'pkv racing', '69', '+ 1:09.190', '15', '11'], ['rodolfo lavín', 'forsythe racing', '69', '+ 1:18.083', '14', '10'], ['gastón mazzacane', 'dale coyne racing', '67', '+ 2 laps', '18', '9'], ['mario haberfeld', 'walker racing', '65', '+ 4 laps', '17', '8'], ['justin wilson', 'mi - jack conquest racing', '55', 'gearbox', '8', '7'], ['sébastien bourdais', 'newman / haas racing', '42', 'contact', '1', '10'], ['guy smith', 'rocketsports racing', '27', 'engine', '16', '5'], ['nelson philippe', 'mi - jack conquest racing', '21', 'lost wheel', '13', '4'], ['ryan hunter - reay', 'herdez competition', '5', 'contact', '9', '3']] |
1970 arizona state sun devils football team | https://en.wikipedia.org/wiki/1970_Arizona_State_Sun_Devils_football_team | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-21034801-1.html.csv | aggregation | the average score for the sun devils during the 1970 season was 38.5 . | {'scope': 'all', 'col': '5', 'type': 'average', 'result': '38.5', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'sun devils points'], 'result': '38.5', 'ind': 0, 'tostr': 'avg { all_rows ; sun devils points }'}, '38.5'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; sun devils points } ; 38.5 } = true', 'tointer': 'the average of the sun devils points record of all rows is 38.5 .'} | round_eq { avg { all_rows ; sun devils points } ; 38.5 } = true | the average of the sun devils points record of all rows is 38.5 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'sun devils points_4': 4, '38.5_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'sun devils points_4': 'sun devils points', '38.5_5': '38.5'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'sun devils points_4': [0], '38.5_5': [1]} | ['game', 'date', 'opponent', 'result', 'sun devils points', 'opponents', 'record'] | [['1', 'sept 19', 'colorado state', 'win', '38', '9', '1 - 0'], ['2', 'sept 26', 'kansas state', 'win', '35', '13', '2 - 0'], ['3', 'oct 3', 'wyoming', 'win', '52', '3', '3 - 0'], ['4', 'oct 10', 'washington state', 'win', '37', '30', '4 - 0'], ['5', 'oct 17', 'brigham young', 'win', '27', '3', '5 - 0'], ['6', 'oct 24', 'texas el - paso', 'win', '42', '13', '6 - 0'], ['7', 'nov 7', 'san jose state', 'win', '46', '10', '7 - 0'], ['8', 'nov 14', 'utah', 'win', '37', '14', '8 - 0'], ['9', 'nov 21', 'new mexico', 'win', '33', '21', '9 - 0']] |
vitantonio liuzzi | https://en.wikipedia.org/wiki/Vitantonio_Liuzzi | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1393912-3.html.csv | count | a total of 6 entrants participated in the vitantonio liuzzi . | {'scope': 'all', 'criterion': 'all', 'value': 'n/a', 'result': '6', 'col': '2', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_all', 'args': ['all_rows', 'entrant'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose entrant record is arbitrary .', 'tostr': 'filter_all { all_rows ; entrant }'}], 'result': '6', 'ind': 1, 'tostr': 'count { filter_all { all_rows ; entrant } }', 'tointer': 'select the rows whose entrant record is arbitrary . the number of such rows is 6 .'}, '6'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_all { all_rows ; entrant } } ; 6 } = true', 'tointer': 'select the rows whose entrant record is arbitrary . the number of such rows is 6 .'} | eq { count { filter_all { all_rows ; entrant } } ; 6 } = true | select the rows whose entrant record is arbitrary . the number of such rows is 6 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_all_0': 0, 'all_rows_4': 4, 'entrant_5': 5, '6_6': 6} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_all_0': 'filter_all', 'all_rows_4': 'all_rows', 'entrant_5': 'entrant', '6_6': '6'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_all_0': [1], 'all_rows_4': [0], 'entrant_5': [0], '6_6': [2]} | ['year', 'entrant', 'chassis', 'engine', 'points'] | [['2005', 'red bull racing', 'red bull rb1', 'cosworth tj2005 3.0 v10', '1'], ['2006', 'scuderia toro rosso', 'toro rosso str1', 'cosworth tj2006 3.0 v10 14 series', '1'], ['2007', 'scuderia toro rosso', 'toro rosso str2', 'ferrari 056 2.4 v8', '3'], ['2009', 'force india f1 team', 'force india vjm02', 'mercedes fo 108w 2.4 l v8', '0'], ['2010', 'force india f1 team', 'force india vjm03', 'mercedes fo 108x 2.4 v8', '21'], ['2011', 'hispania racing f1 team', 'hispania f111', 'cosworth ca2011 v8', '0']] |
1996 - 97 european challenge cup | https://en.wikipedia.org/wiki/1996%E2%80%9397_European_Challenge_Cup | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-16770037-3.html.csv | count | there were two teams that won more than two games in the 96-97 european challenge cup . | {'scope': 'all', 'criterion': 'greater_than', 'value': '2', 'result': '2', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'w', '2'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose w record is greater than 2 .', 'tostr': 'filter_greater { all_rows ; w ; 2 }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_greater { all_rows ; w ; 2 } }', 'tointer': 'select the rows whose w record is greater than 2 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_greater { all_rows ; w ; 2 } } ; 2 } = true', 'tointer': 'select the rows whose w record is greater than 2 . the number of such rows is 2 .'} | eq { count { filter_greater { all_rows ; w ; 2 } } ; 2 } = true | select the rows whose w record is greater than 2 . the number of such rows is 2 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_greater_0': 0, 'all_rows_4': 4, 'w_5': 5, '2_6': 6, '2_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_greater_0': 'filter_greater', 'all_rows_4': 'all_rows', 'w_5': 'w', '2_6': '2', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_greater_0': [1], 'all_rows_4': [0], 'w_5': [0], '2_6': [0], '2_7': [2]} | ['team', 'p', 'w', 'd', 'l', 'tries for', 'tries against', 'try diff', 'points for', 'points against', 'points diff', 'pts'] | [['castres olympique', '5', '5', '0', '0', '29', '6', '+ 23', '207', '71', '+ 136', '10'], ['narbonne', '5', '4', '0', '1', '21', '6', '+ 15', '161', '90', '+ 71', '8'], ['dinamo - bucureşti', '5', '2', '1', '2', '12', '32', '20', '109', '213', '104', '5'], ['bridgend', '4', '1', '1', '2', '10', '14', '4', '94', '120', '26', '3'], ['bristol shoguns', '5', '1', '0', '4', '11', '12', '1', '128', '99', '+ 29', '2'], ['treorchy', '4', '0', '0', '4', '10', '23', '13', '72', '178', '106', '0']] |
united states house of representatives elections , 1996 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1996 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1341472-34.html.csv | count | the democratic party is represented by 4 individuals as incumbents . | {'scope': 'all', 'criterion': 'equal', 'value': 'democratic', 'result': '4', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'party', 'democratic'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose party record fuzzily matches to democratic .', 'tostr': 'filter_eq { all_rows ; party ; democratic }'}], 'result': '4', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; party ; democratic } }', 'tointer': 'select the rows whose party record fuzzily matches to democratic . the number of such rows is 4 .'}, '4'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; party ; democratic } } ; 4 } = true', 'tointer': 'select the rows whose party record fuzzily matches to democratic . the number of such rows is 4 .'} | eq { count { filter_eq { all_rows ; party ; democratic } } ; 4 } = true | select the rows whose party record fuzzily matches to democratic . 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, 'party_5': 5, 'democratic_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', 'party_5': 'party', 'democratic_6': 'democratic', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'party_5': [0], 'democratic_6': [0], '4_7': [2]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['new york 1', 'michael forbes', 'republican', '1994', 're - elected', 'michael forbes ( r ) 54.72 % nora bredes ( d ) 45.28 %'], ['new york 6', 'floyd flake', 'democratic', '1986', 're - elected', 'floyd flake ( d ) 84.85 % jorawar misir ( r ) 15.14 %'], ['new york 7', 'thomas manton', 'democratic', '1984', 're - elected', 'thomas manton ( d ) 71.07 % rose birtley ( r ) 28.93 %'], ['new york 11', 'major owens', 'democratic', '1982', 're - elected', 'major owens ( d ) 91.95 % claudette hayle ( r ) 8.04 %'], ['new york 22', 'gerald solomon', 'republican', '1978', 're - elected', 'gerald solomon ( r ) 60.48 % steve james ( d ) 39.52 %'], ['new york 25', 'jim walsh', 'republican', '1988', 're - elected', 'jim walsh ( r ) 55.11 % marty mack ( d ) 44.89 %'], ['new york 27', 'bill paxon', 'republican', '1988', 're - elected', 'bill paxon ( r ) 59.88 % thomas fricano ( d ) 40.12 %'], ['new york 29', 'john lafalce', 'democratic', '1974', 're - elected', 'john lafalce ( d ) 61.99 % david callard ( r ) 38.01 %']] |
1980 winter olympics | https://en.wikipedia.org/wiki/1980_Winter_Olympics | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-113360-1.html.csv | superlative | at the 1980 winter olympics , the team who won the largest number of medals was east germany . | {'scope': 'all', 'col_superlative': '6', 'row_superlative': '2', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '2', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'total'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; total }'}, 'nation'], 'result': 'east germany ( gdr )', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; total } ; nation }'}, 'east germany ( gdr )'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; total } ; nation } ; east germany ( gdr ) } = true', 'tointer': 'select the row whose total record of all rows is maximum . the nation record of this row is east germany ( gdr ) .'} | eq { hop { argmax { all_rows ; total } ; nation } ; east germany ( gdr ) } = true | select the row whose total record of all rows is maximum . the nation record of this row is east germany ( gdr ) . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'total_5': 5, 'nation_6': 6, 'east germany (gdr)_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'total_5': 'total', 'nation_6': 'nation', 'east germany (gdr)_7': 'east germany ( gdr )'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'total_5': [0], 'nation_6': [1], 'east germany (gdr)_7': [2]} | ['rank', 'nation', 'gold', 'silver', 'bronze', 'total'] | [['1', 'soviet union', '10', '6', '6', '22'], ['2', 'east germany ( gdr )', '9', '7', '7', '23'], ['3', 'united states', '6', '4', '2', '12'], ['4', 'austria', '3', '2', '2', '7'], ['5', 'sweden', '3', '0', '1', '4'], ['6', 'liechtenstein', '2', '2', '0', '4'], ['7', 'finland', '1', '5', '3', '9'], ['8', 'norway', '1', '3', '6', '10'], ['9', 'netherlands', '1', '2', '1', '4'], ['10', 'switzerland', '1', '1', '3', '5']] |
1965 buffalo bills season | https://en.wikipedia.org/wiki/1965_Buffalo_Bills_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16008156-2.html.csv | majority | the majority of games resulted in wins for the bills in the 1965 buffalo bills season . | {'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 11 , 1965', 'boston patriots', 'w 24 - 7', '45502'], ['2', 'september 19 , 1965', 'denver broncos', 'w 30 - 15', '30682'], ['3', 'september 26 , 1965', 'new york jets', 'w 33 - 21', '45056'], ['4', 'october 3 , 1965', 'oakland raiders', 'w 17 - 12', '41256'], ['5', 'october 10 , 1965', 'san diego chargers', 'l 34 - 3', '45260'], ['6', 'october 17 , 1965', 'kansas city chiefs', 'w 23 - 7', '26941'], ['7', 'october 24 , 1965', 'denver broncos', 'w 31 - 13', '45046'], ['8', 'october 31 , 1965', 'houston oilers', 'l 19 - 17', '44267'], ['9', 'november 7 , 1965', 'boston patriots', 'w 23 - 7', '24415'], ['10', 'november 14 , 1965', 'oakland raiders', 'w 17 - 14', '19352'], ['12', 'november 25 , 1965', 'san diego chargers', 't 20 - 20', '27473'], ['13', 'december 5 , 1965', 'houston oilers', 'w 29 - 18', '23087'], ['14', 'december 12 , 1965', 'kansas city chiefs', 'w 34 - 25', '40298'], ['15', 'december 19 , 1965', 'new york jets', 'l 14 - 12', '57396']] |
weightlifting at the 2008 summer olympics - men 's 85 kg | https://en.wikipedia.org/wiki/Weightlifting_at_the_2008_Summer_Olympics_%E2%80%93_Men%27s_85_kg | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18532579-2.html.csv | ordinal | the 2nd heaviest weight that was lifted for a record weighed 215 kg . | {'row': '4', 'col': '4', 'order': '2', 'col_other': '1', 'max_or_min': 'max_to_min', 'value_mentioned': 'yes', 'scope': 'all', 'subset': None} | {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'nth_max', 'args': ['all_rows', '187 kg', '2'], 'result': '215 kg', 'ind': 0, 'tostr': 'nth_max { all_rows ; 187 kg ; 2 }', 'tointer': 'the 2nd maximum 187 kg record of all rows is 215 kg .'}, '215 kg'], 'result': True, 'ind': 1, 'tostr': 'eq { nth_max { all_rows ; 187 kg ; 2 } ; 215 kg }', 'tointer': 'the 2nd maximum 187 kg record of all rows is 215 kg .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', '187 kg', '2'], 'result': None, 'ind': 2, 'tostr': 'nth_argmax { all_rows ; 187 kg ; 2 }'}, 'world record'], 'result': 'olympic record', 'ind': 3, 'tostr': 'hop { nth_argmax { all_rows ; 187 kg ; 2 } ; world record }'}, 'olympic record'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { nth_argmax { all_rows ; 187 kg ; 2 } ; world record } ; olympic record }', 'tointer': 'the world record record of the row with 2nd maximum 187 kg record is olympic record .'}], 'result': True, 'ind': 5, 'tostr': 'and { eq { nth_max { all_rows ; 187 kg ; 2 } ; 215 kg } ; eq { hop { nth_argmax { all_rows ; 187 kg ; 2 } ; world record } ; olympic record } } = true', 'tointer': 'the 2nd maximum 187 kg record of all rows is 215 kg . the world record record of the row with 2nd maximum 187 kg record is olympic record .'} | and { eq { nth_max { all_rows ; 187 kg ; 2 } ; 215 kg } ; eq { hop { nth_argmax { all_rows ; 187 kg ; 2 } ; world record } ; olympic record } } = true | the 2nd maximum 187 kg record of all rows is 215 kg . the world record record of the row with 2nd maximum 187 kg record is olympic record . | 6 | 6 | {'and_5': 5, 'result_6': 6, 'eq_1': 1, 'nth_max_0': 0, 'all_rows_7': 7, '187 kg_8': 8, '2_9': 9, '215 kg_10': 10, 'str_eq_4': 4, 'str_hop_3': 3, 'nth_argmax_2': 2, 'all_rows_11': 11, '187 kg_12': 12, '2_13': 13, 'world record_14': 14, 'olympic record_15': 15} | {'and_5': 'and', 'result_6': 'true', 'eq_1': 'eq', 'nth_max_0': 'nth_max', 'all_rows_7': 'all_rows', '187 kg_8': '187 kg', '2_9': '2', '215 kg_10': '215 kg', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'nth_argmax_2': 'nth_argmax', 'all_rows_11': 'all_rows', '187 kg_12': '187 kg', '2_13': '2', 'world record_14': 'world record', 'olympic record_15': 'olympic record'} | {'and_5': [6], 'result_6': [], 'eq_1': [5], 'nth_max_0': [1], 'all_rows_7': [0], '187 kg_8': [0], '2_9': [0], '215 kg_10': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'nth_argmax_2': [3], 'all_rows_11': [2], '187 kg_12': [2], '2_13': [2], 'world record_14': [3], 'olympic record_15': [4]} | ['world record', 'snatch', 'andrei rybakou ( blr )', '187 kg', 'chiang mai , thailand'] | [['clean & jerk', 'zhang yong ( chn )', '218 kg', 'ramat gan , israel', '25 april 1998'], ['total', 'andrei rybakou ( blr )', '393 kg', 'chiang mai , thailand', '22 september 2007'], ['olympic record', 'snatch', 'olympic standard', '180 kg', '-'], ['olympic record', 'clean & jerk', 'olympic standard', '215 kg', '-'], ['olympic record', 'total', 'olympic standard', '392 kg', '-']] |
1988 - 89 in argentine football | https://en.wikipedia.org/wiki/1988%E2%80%9389_in_Argentine_football | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-14489821-1.html.csv | aggregation | for the 1988 - 89 season in argentine football , teams that had less than 100 points had an average of 71.4 points . | {'scope': 'subset', 'col': '3', 'type': 'average', 'result': '71.4', 'subset': {'col': '3', 'criterion': 'less_than', 'value': '100'}} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'points', '100'], 'result': None, 'ind': 0, 'tostr': 'filter_less { all_rows ; points ; 100 }', 'tointer': 'select the rows whose points record is less than 100 .'}, 'points'], 'result': '71.4', 'ind': 1, 'tostr': 'avg { filter_less { all_rows ; points ; 100 } ; points }'}, '71.4'], 'result': True, 'ind': 2, 'tostr': 'round_eq { avg { filter_less { all_rows ; points ; 100 } ; points } ; 71.4 } = true', 'tointer': 'select the rows whose points record is less than 100 . the average of the points record of these rows is 71.4 .'} | round_eq { avg { filter_less { all_rows ; points ; 100 } ; points } ; 71.4 } = true | select the rows whose points record is less than 100 . the average of the points record of these rows is 71.4 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'avg_1': 1, 'filter_less_0': 0, 'all_rows_4': 4, 'points_5': 5, '100_6': 6, 'points_7': 7, '71.4_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'avg_1': 'avg', 'filter_less_0': 'filter_less', 'all_rows_4': 'all_rows', 'points_5': 'points', '100_6': '100', 'points_7': 'points', '71.4_8': '71.4'} | {'eq_2': [3], 'result_3': [], 'avg_1': [2], 'filter_less_0': [1], 'all_rows_4': [0], 'points_5': [0], '100_6': [0], 'points_7': [1], '71.4_8': [2]} | ['team', 'average', 'points', 'played', '1986 - 87', '1987 - 88', '1988 - 89'] | [['independiente', '1.219', '139', '114', '47', '37', '55'], ["newell 's old boys", '1.193', '136', '114', '48', '55', '33'], ['san lorenzo', '1.184', '135', '114', '44', '49', '42'], ['racing club', '1.158', '132', '114', '44', '48', '40'], ['boca juniors', '1.140', '130', '114', '46', '35', '49'], ['river plate', '1.140', '130', '114', '39', '46', '45'], ['rosario central', '1.079', '123', '114', '49', '40', '34'], ['deportivo español', '1.070', '122', '114', '36', '40', '46'], ['gimnasia de la plata', '1.018', '116', '114', '37', '43', '36'], ['vélez sársfield', '1.009', '115', '114', '41', '41', '33'], ['estudiantes de la plata', '0.974', '111', '114', '37', '32', '42'], ['argentinos juniors', '0.965', '110', '114', '28', '40', '42'], ['talleres de córdoba', '0.956', '109', '114', '38', '27', '44'], ['ferro carril oeste', '0.939', '107', '114', '44', '33', '30'], ['textil mandiyú', '0.868', '33', '38', 'n / a', 'n / a', '33'], ['platense', '0.860', '98', '114', '27', '38', '33'], ['instituto de córdoba', '0.851', '97', '114', '41', '33', '23'], ['racing de córdoba', '0.851', '97', '114', '33', '31', '33'], ['san martín de tucumán', '0.842', '32', '38', 'n / a', 'n / a', '32']] |
thiago alves ( tennis ) | https://en.wikipedia.org/wiki/Thiago_Alves_%28tennis%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14924949-3.html.csv | unique | thiago alves only played one game in the singles during the year 2007 . | {'scope': 'all', 'row': '5', 'col': '1', 'col_other': 'n/a', 'criterion': 'fuzzily_match', 'value': '2007', 'subset': None} | {'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', '2007'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose date record fuzzily matches to 2007 .', 'tostr': 'filter_eq { all_rows ; date ; 2007 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; date ; 2007 } } = true', 'tointer': 'select the rows whose date record fuzzily matches to 2007 . there is only one such row in the table .'} | only { filter_eq { all_rows ; date ; 2007 } } = true | select the rows whose date record fuzzily matches to 2007 . there is only one such row in the table . | 2 | 2 | {'only_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, 'date_4': 4, '2007_5': 5} | {'only_1': 'only', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'date_4': 'date', '2007_5': '2007'} | {'only_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'date_4': [0], '2007_5': [0]} | ['date', 'tournament', 'surface', 'opponent', 'score'] | [['august 15 , 2005', 'manta , ecuador', 'hard', 'lesley joseph', '6 - 4 , 6 - 1'], ['october 10 , 2005', 'quito , ecuador', 'clay', 'marcos daniel', '1 - 6 , 7 - 6 ( 7 - 1 ) , 6 - 2'], ['july 31 , 2006', 'belo horizonte , brazil', 'hard', 'andré sá', '6 - 3 , 0 - 6 , 6 - 4'], ['august 14 , 2006', 'manta , ecuador', 'hard', 'brian dabul', '6 - 2 , 6 - 2'], ['december 31 , 2007', 'são paulo , brazil', 'hard', 'carlos berlocq', '6 - 4 , 3 - 6 , 7 - 5'], ['january 8 , 2012', 'são paulo , brazil', 'hard', 'gastão elias', '7 - 6 ( 7 - 5 ) , 7 - 6 ( 7 - 1 )'], ['march 18 , 2012', 'guadalajara , mexico', 'hard', 'paolo lorenzi', '6 - 3 , 7 - 6 ( 6 - 4 )']] |
teo fabi | https://en.wikipedia.org/wiki/Teo_Fabi | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1218368-2.html.csv | aggregation | teo fabi earned 23 points in formula one races over the course of his career . | {'scope': 'all', 'col': '5', 'type': 'sum', 'result': '23', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'pts'], 'result': '23', 'ind': 0, 'tostr': 'sum { all_rows ; pts }'}, '23'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; pts } ; 23 } = true', 'tointer': 'the sum of the pts record of all rows is 23 .'} | round_eq { sum { all_rows ; pts } ; 23 } = true | the sum of the pts record of all rows is 23 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'pts_4': 4, '23_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'pts_4': 'pts', '23_5': '23'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'pts_4': [0], '23_5': [1]} | ['year', 'entrant', 'chassis', 'engine', 'pts'] | [['1982', 'candy toleman motorsport', 'toleman tg181c', 'hart straight - 4 ( t / c )', '0'], ['1984', 'mrd international', 'brabham bt53', 'bmw straight - 4 ( t / c )', '9'], ['1985', 'toleman group motorsport', 'toleman tg185', 'hart straight - 4 ( t / c )', '0'], ['1986', 'benetton formula ltd', 'benetton b186', 'bmw straight - 4 ( t / c )', '2'], ['1987', 'benetton formula ltd', 'benetton b187', 'ford v6 ( t / c )', '12']] |
yakushiji ryōko no kaiki jikenbo | https://en.wikipedia.org/wiki/Yakushiji_Ry%C5%8Dko_no_Kaiki_Jikenbo | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18443854-1.html.csv | count | two of the books were first published by shodensha non-novels . | {'scope': 'all', 'criterion': 'equal', 'value': 'shodensha non - novels', 'result': '2', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'first publisher', 'shodensha non - novels'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose first publisher record fuzzily matches to shodensha non - novels .', 'tostr': 'filter_eq { all_rows ; first publisher ; shodensha non - novels }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; first publisher ; shodensha non - novels } }', 'tointer': 'select the rows whose first publisher record fuzzily matches to shodensha non - novels . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; first publisher ; shodensha non - novels } } ; 2 } = true', 'tointer': 'select the rows whose first publisher record fuzzily matches to shodensha non - novels . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; first publisher ; shodensha non - novels } } ; 2 } = true | select the rows whose first publisher record fuzzily matches to shodensha non - novels . 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, 'first publisher_5': 5, 'shodensha non - novels_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', 'first publisher_5': 'first publisher', 'shodensha non - novels_6': 'shodensha non - novels', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'first publisher_5': [0], 'shodensha non - novels_6': [0], '2_7': [2]} | ['japanese title', 'english title', 'year', 'first publisher', 'isbn'] | [['魔天楼 ( matenrō )', 'demon skyscraper', '1996', 'kodansha bunko', 'isbn 4 - 06 - 263346 - 9'], ['東京ナイトメア ( tokyo nightmare )', 'tokyo nightmare', '1999', 'kodansha novels', 'isbn 4 - 06 - 182042 - 7'], ['巴里 ・ 妖都変 ( paris yōto - hen )', 'paris , the strange attractive capital', '2000', 'kobunsha kappa novels', 'isbn 4 - 334 - 07371 - 9'], ['クレオパトラの葬送 ( cleopatra no sōsō )', 'funeral of the cleopatra', '2001', 'kodansha novels', 'isbn 4 - 06 - 182197 - 0'], ['黒蜘蛛島 ( black spider island )', 'black spider island', '2003', 'kobunsha kappa novels', 'isbn 4 - 334 - 07541 - x'], ['夜光曲 ( yakōkyoku )', 'luminous song', '2005', 'shodensha non - novels', 'isbn 4 - 396 - 20793 - x'], ['霧の訪問者 ( kiri no hōmonsha )', "visitor 's fog", '2006', 'kodansha novels', 'isbn 4 - 06 - 182499 - 6'], ['水妖日にご用心 ( suiyō - bi ni goyōjin )', 'be careful on wednesday', '2007', 'shodensha non - novels', 'isbn 4 - 396 - 20840 - 5']] |
east surrey ( uk parliament constituency ) | https://en.wikipedia.org/wiki/East_Surrey_%28UK_Parliament_constituency%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1809923-1.html.csv | comparative | john ivatt briscoe was elected before peter john locke king was elected . | {'row_1': '1', 'row_2': '5', 'col': '1', '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', 'first member', 'john ivatt briscoe'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose first member record fuzzily matches to john ivatt briscoe .', 'tostr': 'filter_eq { all_rows ; first member ; john ivatt briscoe }'}, 'election'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; first member ; john ivatt briscoe } ; election }', 'tointer': 'select the rows whose first member record fuzzily matches to john ivatt briscoe . take the election record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'first member', 'peter john locke king'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose first member record fuzzily matches to peter john locke king .', 'tostr': 'filter_eq { all_rows ; first member ; peter john locke king }'}, 'election'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; first member ; peter john locke king } ; election }', 'tointer': 'select the rows whose first member record fuzzily matches to peter john locke king . take the election record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; first member ; john ivatt briscoe } ; election } ; hop { filter_eq { all_rows ; first member ; peter john locke king } ; election } } = true', 'tointer': 'select the rows whose first member record fuzzily matches to john ivatt briscoe . take the election record of this row . select the rows whose first member record fuzzily matches to peter john locke king . take the election record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; first member ; john ivatt briscoe } ; election } ; hop { filter_eq { all_rows ; first member ; peter john locke king } ; election } } = true | select the rows whose first member record fuzzily matches to john ivatt briscoe . take the election record of this row . select the rows whose first member record fuzzily matches to peter john locke king . take the election 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, 'first member_7': 7, 'john ivatt briscoe_8': 8, 'election_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'first member_11': 11, 'peter john locke king_12': 12, 'election_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', 'first member_7': 'first member', 'john ivatt briscoe_8': 'john ivatt briscoe', 'election_9': 'election', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'first member_11': 'first member', 'peter john locke king_12': 'peter john locke king', 'election_13': 'election'} | {'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'first member_7': [0], 'john ivatt briscoe_8': [0], 'election_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'first member_11': [1], 'peter john locke king_12': [1], 'election_13': [3]} | ['election', 'first member', '1st party', 'second member', '2nd party'] | [['1832', 'john ivatt briscoe', 'liberal', 'aubrey beauclerk', 'liberal'], ['1835', 'richard alsager', 'conservative', 'aubrey beauclerk', 'liberal'], ['1837', 'richard alsager', 'conservative', 'henry kemble', 'conservative'], ['1841 by - election', 'edmund antrobus', 'conservative', 'henry kemble', 'conservative'], ['1847', 'peter john locke king', 'liberal', 'thomas alcock', 'liberal'], ['1865', 'peter john locke king', 'liberal', 'charles buxton', 'liberal'], ['1871 by - election', 'peter john locke king', 'liberal', 'james watney', 'conservative'], ['1874', 'william grantham', 'conservative', 'james watney', 'conservative'], ['1885', 'constituency abolished', 'constituency abolished', 'constituency abolished', 'constituency abolished']] |
2009 world championships in athletics - women 's 20 kilometres walk | https://en.wikipedia.org/wiki/2009_World_Championships_in_Athletics_%E2%80%93_Women%27s_20_kilometres_walk | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-24002100-2.html.csv | comparative | the north american record time was faster than the south american record time . | {'row_1': '5', 'row_2': '6', 'col': '3', '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', 'world record', 'north american record'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose world record record fuzzily matches to north american record .', 'tostr': 'filter_eq { all_rows ; world record ; north american record }'}, '1:25:41'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; world record ; north american record } ; 1:25:41 }', 'tointer': 'select the rows whose world record record fuzzily matches to north american record . take the 1:25:41 record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'world record', 'south american record'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose world record record fuzzily matches to south american record .', 'tostr': 'filter_eq { all_rows ; world record ; south american record }'}, '1:25:41'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; world record ; south american record } ; 1:25:41 }', 'tointer': 'select the rows whose world record record fuzzily matches to south american record . take the 1:25:41 record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; world record ; north american record } ; 1:25:41 } ; hop { filter_eq { all_rows ; world record ; south american record } ; 1:25:41 } } = true', 'tointer': 'select the rows whose world record record fuzzily matches to north american record . take the 1:25:41 record of this row . select the rows whose world record record fuzzily matches to south american record . take the 1:25:41 record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; world record ; north american record } ; 1:25:41 } ; hop { filter_eq { all_rows ; world record ; south american record } ; 1:25:41 } } = true | select the rows whose world record record fuzzily matches to north american record . take the 1:25:41 record of this row . select the rows whose world record record fuzzily matches to south american record . take the 1:25:41 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, 'world record_7': 7, 'north american record_8': 8, '1:25:41_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'world record_11': 11, 'south american record_12': 12, '1:25:41_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', 'world record_7': 'world record', 'north american record_8': 'north american record', '1:25:41_9': '1:25:41', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'world record_11': 'world record', 'south american record_12': 'south american record', '1:25:41_13': '1:25:41'} | {'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'world record_7': [0], 'north american record_8': [0], '1:25:41_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'world record_11': [1], 'south american record_12': [1], '1:25:41_13': [3]} | ['world record', 'olimpiada ivanova ( rus )', '1:25:41', 'helsinki , finland', '7 august 2005'] | [['championship record', 'olimpiada ivanova ( rus )', '1:25:41', 'helsinki , finland', '7 august 2005'], ['world leading', 'olga kaniskina ( rus )', '1:24:56', 'adler , russia', '28 february 2009'], ['african record', 'susan vermeulen ( rsa )', '1:36:18', 'mézidon - canon , france', '2 may 1999'], ['asian record', 'wang yan ( chn )', '1:26:22', 'guangzhou , china', '19 november 2001'], ['north american record', 'graciela mendoza ( mex )', '1:30:03', 'mézidon - canon , france', '2 may 1999'], ['south american record', 'miriam ramón ( ecu )', '1:31:25', 'lima , peru', '7 may 2005'], ['european record', 'olimpiada ivanova ( rus )', '1:25:41', 'helsinki , finland', '7 august 2005']] |
list of are you afraid of the dark ? episodes | https://en.wikipedia.org/wiki/List_of_Are_You_Afraid_of_the_Dark%3F_episodes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-10470082-8.html.csv | superlative | the last episode of are you afraid of the dark to air in 2000 was the tale of many faces . | {'scope': 'all', 'col_superlative': '6', 'row_superlative': '12', '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', 'us air date'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; us air date }'}, 'title'], 'result': 'the tale of many faces', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; us air date } ; title }'}, 'the tale of many faces'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; us air date } ; title } ; the tale of many faces } = true', 'tointer': 'select the row whose us air date record of all rows is maximum . the title record of this row is the tale of many faces .'} | eq { hop { argmax { all_rows ; us air date } ; title } ; the tale of many faces } = true | select the row whose us air date record of all rows is maximum . the title record of this row is the tale of many faces . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'us air date_5': 5, 'title_6': 6, 'the tale of many faces_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'us air date_5': 'us air date', 'title_6': 'title', 'the tale of many faces_7': 'the tale of many faces'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'us air date_5': [0], 'title_6': [1], 'the tale of many faces_7': [2]} | ['no', '-', 'title', 'director', 'writer', 'us air date', 'storyteller', 'villains'] | [['79', '1', 'the tale of the silver sight , part 1', 'mark soulard', 'd j machale', 'april 2 , 2000', 'n / a', 'the evil spirit'], ['80', '2', 'the tale of the silver sight , part 2', 'mark soulard', 'd j machale', 'april 2 , 2000', 'n / a', 'the evil spirit'], ['81', '3', 'the tale of the silver sight , part 3', 'mark soulard', 'd j machale', 'april 2 , 2000', "gary and tucker 's grandfather , gene", 'the evil spirit'], ['82', '4', 'the tale of the lunar locusts', 'jim donovan', 'michael koegel', 'april 9 , 2000', 'megan', 'the unborn alien babies'], ['83', '5', 'the tale of the stone maiden', 'adam weissman', 'mark d perry', 'april 16 , 2000', 'megan', 'the maiden statue'], ['84', '6', 'the tale of highway 13', 'jim donovan', 'ted elrick', 'april 23 , 2000', 'quinn', 'none'], ['85', '7', 'the tale of the reanimator', 'adam weissman', 'kenny davis', 'april 30 , 2000', 'quinn', 'reanimated zombie'], ['86', '8', 'the tale of the time trap', 'jim donovan', 'jim morris', 'may 7 , 2000', 'tucker', 'bell the genie'], ['87', '9', 'the tale of the photo finish', 'mark soulard', 'alan kingsberg', 'may 14 , 2000', 'andy', 'jasper davis'], ['88', '10', 'the tale of the last dance', 'jim donovan', 'mark d perry', 'may 21 , 2000', 'andy', 'none'], ['89', '11', 'the tale of the laser maze', 'mark soulard', 'peggy sarlin', 'may 28 , 2000', 'tucker', 'drake'], ['90', '12', 'the tale of many faces', 'lorette leblanc', 'alan kingsberg', 'june 4 , 2000', 'vange', 'madame visage']] |
list of boston celtics broadcasters | https://en.wikipedia.org/wiki/List_of_Boston_Celtics_broadcasters | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14902507-9.html.csv | unique | cedric maxwell was the only color commentator for the wrko flagship station . | {'scope': 'all', 'row': '5', 'col': '2', 'col_other': '4', 'criterion': 'equal', 'value': 'wrko', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'flagship station', 'wrko'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose flagship station record fuzzily matches to wrko .', 'tostr': 'filter_eq { all_rows ; flagship station ; wrko }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; flagship station ; wrko } }', 'tointer': 'select the rows whose flagship station record fuzzily matches to wrko . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'flagship station', 'wrko'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose flagship station record fuzzily matches to wrko .', 'tostr': 'filter_eq { all_rows ; flagship station ; wrko }'}, 'color commentator ( s )'], 'result': 'cedric maxwell', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; flagship station ; wrko } ; color commentator ( s ) }'}, 'cedric maxwell'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; flagship station ; wrko } ; color commentator ( s ) } ; cedric maxwell }', 'tointer': 'the color commentator ( s ) record of this unqiue row is cedric maxwell .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; flagship station ; wrko } } ; eq { hop { filter_eq { all_rows ; flagship station ; wrko } ; color commentator ( s ) } ; cedric maxwell } } = true', 'tointer': 'select the rows whose flagship station record fuzzily matches to wrko . there is only one such row in the table . the color commentator ( s ) record of this unqiue row is cedric maxwell .'} | and { only { filter_eq { all_rows ; flagship station ; wrko } } ; eq { hop { filter_eq { all_rows ; flagship station ; wrko } ; color commentator ( s ) } ; cedric maxwell } } = true | select the rows whose flagship station record fuzzily matches to wrko . there is only one such row in the table . the color commentator ( s ) record of this unqiue row is cedric maxwell . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'flagship station_7': 7, 'wrko_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'color commentator (s)_9': 9, 'cedric maxwell_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'flagship station_7': 'flagship station', 'wrko_8': 'wrko', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'color commentator (s)_9': 'color commentator ( s )', 'cedric maxwell_10': 'cedric maxwell'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'flagship station_7': [0], 'wrko_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'color commentator (s)_9': [2], 'cedric maxwell_10': [3]} | ['year', 'flagship station', 'play - by - play', 'color commentator ( s )', 'studio host'] | [['1999 - 2000', 'weei', 'howard david', 'cedric maxwell', 'ted sarandis'], ['1998 - 99', 'weei', 'howard david', 'cedric maxwell', 'ted sarandis'], ['1997 - 98', 'weei', 'howard david', 'cedric maxwell', 'ted sarandis'], ['1996 - 97', 'weei', 'spencer ross', 'cedric maxwell', 'ted sarandis'], ['1995 - 96', 'wrko', 'spencer ross', 'cedric maxwell', 'ted sarandis'], ['1994 - 95', 'weei', 'glenn ordway', 'jerry sichting', 'craig mustard'], ['1993 - 94', 'weei', 'glenn ordway', 'jerry sichting', 'craig mustard'], ['1992 - 93', 'weei', 'glenn ordway', 'jerry sichting', 'craig mustard'], ['1991 - 92', 'weei', 'glenn ordway', 'jerry sichting', 'craig mustard'], ['1990 - 91', 'weei', 'glenn ordway', 'doug brown', 'craig mustard']] |
that 's so raven ( season 2 ) | https://en.wikipedia.org/wiki/That%27s_So_Raven_%28season_2%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27610775-1.html.csv | aggregation | that 's so raven ( season 2 ) had a combined total of 78.52 millions of us viewers . | {'scope': 'all', 'col': '8', 'type': 'sum', 'result': '78.52', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'us viewers ( millions )'], 'result': '78.52', 'ind': 0, 'tostr': 'sum { all_rows ; us viewers ( millions ) }'}, '78.52'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; us viewers ( millions ) } ; 78.52 } = true', 'tointer': 'the sum of the us viewers ( millions ) record of all rows is 78.52 .'} | round_eq { sum { all_rows ; us viewers ( millions ) } ; 78.52 } = true | the sum of the us viewers ( millions ) record of all rows is 78.52 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'us viewers (millions)_4': 4, '78.52_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'us viewers (millions)_4': 'us viewers ( millions )', '78.52_5': '78.52'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'us viewers (millions)_4': [0], '78.52_5': [1]} | ['series', 'season', 'title', 'directed by', 'written by', 'original air date', 'prod code', 'us viewers ( millions )'] | [['22', '1', 'out of control', 'gerren keith', 'sarah jane cunningham & suzie v freeman', 'october 3 , 2003', '203', '2.9'], ['23', '2', "do n't have a cow", 'rich correll', 'michael carrington', 'october 17 , 2003', '204', '4.5'], ['24', '3', 'run , raven , run', 'rich correll', 'marc warren', 'november 7 , 2003', '202', '4.1'], ['25', '4', 'clothes minded', 'sean mcnamara', 'edward c evans', 'january 1 , 2004', '207', '3.6'], ['26', '5', "four 's a crowd", 'rich correll', 'michael feldman', 'january 30 , 2004', '206', '5.5'], ['27', '6', 'hearts and minds', 'rich correll', 'michael feldman', 'february 6 , 2004', '212', '3.8'], ['28', '7', 'close encounters of the nerd kind', 'john tracy', 'josh lynn & danny warren', 'march 26 , 2004', '211', '2.4'], ['29', '8', "that 's so not raven", 'sean mcnamara', 'dennis rinsler', 'april 9 , 2004', '201', '7.1'], ['30', '9', 'blue in the face', 'sean mcnamara', 'maisha closson', 'april 16 , 2004', '208', '1.9'], ['31', '10', 'spa day afternoon', 'carl lauten', 'dava savel', 'may 21 , 2004', '209', '2.4'], ['32', '11', 'leave it to diva', 'donna pescow', 'marc warren', 'may 28 , 2004', '213', '2.9'], ['33', '12', 'there goes the bride', 'erma elzy - jones', 'sarah jane cunningham & suzie v freeman', 'june 11 , 2004', '216', '2.7'], ['34', '13', 'radio heads', 'rich correll', 'dennis rinsler', 'june 25 , 2004', '215', '3.7'], ['35', '14', "a goat 's tale", 'debbie allen', 'edward c evans', 'july 2 , 2004', '217', '4.3'], ['36', '15', "he 's got the power", 'john tracy', 'dava savel', 'july 9 , 2004', '205', '4.9'], ['37', '16', "skunk 'd", 'christopher b pearman', 'sarah jane cunningham & suzie v freeman', 'july 16 , 2004', '219', '5.0'], ['38', '17', 'the dating shame', 'sean mcnamara', 'edward c evans & michael feldman', 'july 23 , 2004', '218', '4.6'], ['39', '18', 'the road to audition', 'debbie allen', 'beth seriff & geoff tarson', 'july 30 , 2004', '214', '4.3'], ['40', '19', 'the lying game', 'rich correll', 'dennis rinsler & marc warren', 'august 6 , 2004', '220', '4.27'], ['41', '20', 'numb and number', 'rondell sheridan', 'michael feldman & dava savel', 'september 10 , 2004', '221', '3.65']] |
list of cities , towns and villages in vojvodina | https://en.wikipedia.org/wiki/List_of_cities%2C_towns_and_villages_in_Vojvodina | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2562572-53.html.csv | majority | orthodox christianity is the main religion in vojvodina . | {'scope': 'all', 'col': '6', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'orthodox christianity', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'dominant religion ( 2002 )', 'orthodox christianity'], 'result': True, 'ind': 0, 'tointer': 'for the dominant religion ( 2002 ) records of all rows , all of them fuzzily match to orthodox christianity .', 'tostr': 'all_eq { all_rows ; dominant religion ( 2002 ) ; orthodox christianity } = true'} | all_eq { all_rows ; dominant religion ( 2002 ) ; orthodox christianity } = true | for the dominant religion ( 2002 ) records of all rows , all of them fuzzily match to orthodox christianity . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'dominant religion (2002)_3': 3, 'orthodox christianity_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'dominant religion (2002)_3': 'dominant religion ( 2002 )', 'orthodox christianity_4': 'orthodox christianity'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'dominant religion (2002)_3': [0], 'orthodox christianity_4': [0]} | ['settlement', 'cyrillic name', 'type', 'population ( 2011 )', 'largest ethnic group ( 2002 )', 'dominant religion ( 2002 )'] | [['stara pazova', 'стара пазова', 'town', '18602', 'serbs', 'orthodox christianity'], ['belegiš', 'белегиш', 'village', '2973', 'serbs', 'orthodox christianity'], ['golubinci', 'голубинци', 'village', '4721', 'serbs', 'orthodox christianity'], ['krnješevci', 'крњешевци', 'village', '845', 'serbs', 'orthodox christianity'], ['nova pazova', 'нова пазова', 'village', '17105', 'serbs', 'orthodox christianity'], ['novi banovci', 'нови бановци', 'village', '9443', 'serbs', 'orthodox christianity'], ['stari banovci', 'стари бановци', 'village', '5954', 'serbs', 'orthodox christianity'], ['surduk', 'сурдук', 'village', '1397', 'serbs', 'orthodox christianity']] |
indiana high school athletics conferences : allen county - metropolitan | https://en.wikipedia.org/wiki/Indiana_High_School_Athletics_Conferences%3A_Allen_County_%E2%80%93_Metropolitan | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13986492-6.html.csv | unique | among the schools in the allen county - metropolitan division ( indiana high school athletics conference ) , the only one with an enrollment higher than 3000 is lake central . | {'scope': 'all', 'row': '4', 'col': '4', 'col_other': '1', 'criterion': 'greater_than', 'value': '3000', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'enrollment', '3000'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose enrollment record is greater than 3000 .', 'tostr': 'filter_greater { all_rows ; enrollment ; 3000 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_greater { all_rows ; enrollment ; 3000 } }', 'tointer': 'select the rows whose enrollment record is greater than 3000 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'enrollment', '3000'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose enrollment record is greater than 3000 .', 'tostr': 'filter_greater { all_rows ; enrollment ; 3000 }'}, 'school'], 'result': 'lake central', 'ind': 2, 'tostr': 'hop { filter_greater { all_rows ; enrollment ; 3000 } ; school }'}, 'lake central'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_greater { all_rows ; enrollment ; 3000 } ; school } ; lake central }', 'tointer': 'the school record of this unqiue row is lake central .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_greater { all_rows ; enrollment ; 3000 } } ; eq { hop { filter_greater { all_rows ; enrollment ; 3000 } ; school } ; lake central } } = true', 'tointer': 'select the rows whose enrollment record is greater than 3000 . there is only one such row in the table . the school record of this unqiue row is lake central .'} | and { only { filter_greater { all_rows ; enrollment ; 3000 } } ; eq { hop { filter_greater { all_rows ; enrollment ; 3000 } ; school } ; lake central } } = true | select the rows whose enrollment record is greater than 3000 . there is only one such row in the table . the school record of this unqiue row is lake central . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_greater_0': 0, 'all_rows_6': 6, 'enrollment_7': 7, '3000_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'school_9': 9, 'lake central_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_greater_0': 'filter_greater', 'all_rows_6': 'all_rows', 'enrollment_7': 'enrollment', '3000_8': '3000', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'school_9': 'school', 'lake central_10': 'lake central'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_greater_0': [1, 2], 'all_rows_6': [0], 'enrollment_7': [0], '3000_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'school_9': [2], 'lake central_10': [3]} | ['school', 'mascot', 'location', 'enrollment', 'ihsaa class', 'ihsaa football class', 'county'] | [['chesterton', 'trojans', 'chesterton', '1986', 'aaaa', 'aaaaa', '64 porter'], ['crown point', 'bulldogs', 'crown point', '2532', 'aaaa', 'aaaaa', '45 lake'], ['laporte', 'slicers', 'laporte', '1839', 'aaaa', 'aaaaa', '46 laporte'], ['lake central', 'indians', 'saint john', '3225', 'aaaa', 'aaaaa', '45 lake'], ['merrillville', 'pirates', 'merrillville', '2396', 'aaaa', 'aaaaa', '45 lake'], ['michigan city', 'wolves', 'michigan city', '1909', 'aaaa', 'aaaaa', '46 laporte'], ['portage', 'indians', 'portage', '2668', 'aaaa', 'aaaaa', '64 porter'], ['valparaiso', 'vikings', 'valparaiso', '2114', 'aaaa', 'aaaaa', '64 porter']] |
list of world number one male golfers | https://en.wikipedia.org/wiki/List_of_World_Number_One_male_golfers | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10753786-4.html.csv | comparative | fred couples was ranked as the world 's number one male golfer for more weeks than david duval was . | {'row_1': '11', 'row_2': '12', 'col': '4', 'col_other': '2', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', 'fred couples'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose player record fuzzily matches to fred couples .', 'tostr': 'filter_eq { all_rows ; player ; fred couples }'}, 'weeks'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; player ; fred couples } ; weeks }', 'tointer': 'select the rows whose player record fuzzily matches to fred couples . take the weeks record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', 'david duval'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose player record fuzzily matches to david duval .', 'tostr': 'filter_eq { all_rows ; player ; david duval }'}, 'weeks'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; player ; david duval } ; weeks }', 'tointer': 'select the rows whose player record fuzzily matches to david duval . take the weeks record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; player ; fred couples } ; weeks } ; hop { filter_eq { all_rows ; player ; david duval } ; weeks } } = true', 'tointer': 'select the rows whose player record fuzzily matches to fred couples . take the weeks record of this row . select the rows whose player record fuzzily matches to david duval . take the weeks record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; player ; fred couples } ; weeks } ; hop { filter_eq { all_rows ; player ; david duval } ; weeks } } = true | select the rows whose player record fuzzily matches to fred couples . take the weeks record of this row . select the rows whose player record fuzzily matches to david duval . take the weeks 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, 'player_7': 7, 'fred couples_8': 8, 'weeks_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'player_11': 11, 'david duval_12': 12, 'weeks_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', 'player_7': 'player', 'fred couples_8': 'fred couples', 'weeks_9': 'weeks', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'player_11': 'player', 'david duval_12': 'david duval', 'weeks_13': 'weeks'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'player_7': [0], 'fred couples_8': [0], 'weeks_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'player_11': [1], 'david duval_12': [1], 'weeks_13': [3]} | ['rank', 'player', 'country', 'weeks', 'order', 'majors'] | [['1', 'tiger woods', 'united states', '656', '9', '14'], ['2', 'greg norman', 'australia', '331', '3', '2'], ['3', 'nick faldo', 'england', '97', '4', '6'], ['4', 'seve ballesteros', 'spain', '61', '2', '5'], ['5', 'luke donald', 'england', '56', '15', '0'], ['6', 'ian woosnam', 'wales', '50', '5', '1'], ['7', 'nick price', 'zimbabwe', '44', '7', '3'], ['8', 'rory mcilroy', 'northern ireland', '39', '16', '2'], ['9', 'vijay singh', 'fiji', '32', '12', '3'], ['10', 'lee westwood', 'england', '22', '13', '0'], ['11', 'fred couples', 'united states', '16', '6', '1'], ['12', 'david duval', 'united states', '15', '11', '1'], ['13', 'ernie els', 'south africa', '9', '10', '4'], ['14', 'martin kaymer', 'germany', '8', '14', '1'], ['15', 'bernhard langer', 'west germany', '3', '1', '2'], ['16', 'tom lehman', 'united states', '1', '8', '1']] |
1947 european amateur boxing championships | https://en.wikipedia.org/wiki/1947_European_Amateur_Boxing_Championships | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14129554-2.html.csv | aggregation | the average number of gold medals won , was .667 . | {'scope': 'all', 'col': '3', 'type': 'average', 'result': '.667', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'gold'], 'result': '.667', 'ind': 0, 'tostr': 'avg { all_rows ; gold }'}, '.667'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; gold } ; .667 } = true', 'tointer': 'the average of the gold record of all rows is .667 .'} | round_eq { avg { all_rows ; gold } ; .667 } = true | the average of the gold record of all rows is .667 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'gold_4': 4, '.667_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'gold_4': 'gold', '.667_5': '.667'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'gold_4': [0], '.667_5': [1]} | ['rank', 'nation', 'gold', 'silver', 'bronze', 'total'] | [['1', 'france', '1', '3', '0', '4'], ['2', 'england', '1', '2', '1', '4'], ['3', 'ireland', '1', '1', '0', '2'], ['-', 'sweden', '1', '1', '0', '2'], ['5', 'belgium', '1', '0', '2', '3'], ['6', 'hungary', '1', '0', '0', '1'], ['-', 'netherlands', '1', '0', '0', '1'], ['-', 'spain', '1', '0', '0', '1'], ['9', 'scotland', '0', '1', '0', '1'], ['10', 'czechoslovakia', '0', '0', '2', '2'], ['-', 'italy', '0', '0', '2', '2'], ['12', 'denmark', '0', '0', '1', '1']] |
1984 u.s. open ( golf ) | https://en.wikipedia.org/wiki/1984_U.S._Open_%28golf%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17231267-6.html.csv | ordinal | in the 1984 u.s. open ( golf ) , the forth highest prize was won by player that scored 284 . | {'scope': 'all', 'row': '6', 'col': '6', 'order': '4', 'col_other': '4', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'money', '4'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; money ; 4 }'}, 'score'], 'result': '68 + 68 + 69 + 79 = 284', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; money ; 4 } ; score }'}, '68 + 68 + 69 + 79 = 284'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; money ; 4 } ; score } ; 68 + 68 + 69 + 79 = 284 } = true', 'tointer': 'select the row whose money record of all rows is 4th maximum . the score record of this row is 68 + 68 + 69 + 79 = 284 .'} | eq { hop { nth_argmax { all_rows ; money ; 4 } ; score } ; 68 + 68 + 69 + 79 = 284 } = true | select the row whose money record of all rows is 4th maximum . the score record of this row is 68 + 68 + 69 + 79 = 284 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'money_5': 5, '4_6': 6, 'score_7': 7, '68 + 68 + 69 + 79 = 284_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', 'money_5': 'money', '4_6': '4', 'score_7': 'score', '68 + 68 + 69 + 79 = 284_8': '68 + 68 + 69 + 79 = 284'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'money_5': [0], '4_6': [0], 'score_7': [1], '68 + 68 + 69 + 79 = 284_8': [2]} | ['place', 'player', 'country', 'score', 'to par', 'money'] | [['t1', 'fuzzy zoeller', 'united states', '71 + 66 + 69 + 70 = 276', '- 4', 'playoff'], ['t1', 'greg norman', 'australia', '70 + 68 + 69 + 69 = 276', '- 4', 'playoff'], ['3', 'curtis strange', 'united states', '69 + 70 + 74 + 68 = 281', '+ 1', '36000'], ['t4', 'johnny miller', 'united states', '74 + 68 + 70 + 70 = 282', '+ 2', '22335'], ['t4', 'jim thorpe', 'united states', '68 + 71 + 70 + 73 = 282', '+ 2', '22335'], ['6', 'hale irwin', 'united states', '68 + 68 + 69 + 79 = 284', '+ 4', '16238'], ['t7', 'peter jacobsen', 'united states', '72 + 73 + 73 + 67 = 285', '+ 5', '14237'], ['t7', "mark o'meara", 'united states', '71 + 74 + 71 + 69 = 285', '+ 5', '14237'], ['t9', 'fred couples', 'united states', '69 + 71 + 74 + 72 = 286', '+ 6', '12122'], ['t9', 'lee trevino', 'united states', '71 + 72 + 69 + 74 = 286', '+ 6', '12122']] |
shinichi ito | https://en.wikipedia.org/wiki/Shinichi_Ito | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12185077-3.html.csv | aggregation | shinichi ito scored a total number of 526 points in his motorcycle racing career . | {'scope': 'all', 'col': '5', 'type': 'sum', 'result': '526', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'points'], 'result': '526', 'ind': 0, 'tostr': 'sum { all_rows ; points }'}, '526'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; points } ; 526 } = true', 'tointer': 'the sum of the points record of all rows is 526 .'} | round_eq { sum { all_rows ; points } ; 526 } = true | the sum of the points record of all rows is 526 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'points_4': 4, '526_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'points_4': 'points', '526_5': '526'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'points_4': [0], '526_5': [1]} | ['year', 'class', 'team', 'machine', 'points', 'rank', 'wins'] | [['1988', '500cc', 'seed - honda', 'nsr500', '0', 'nc', '0'], ['1989', '500cc', 'hrc - honda', 'nsr500', '6', '32nd', '0'], ['1990', '500cc', 'pentax - honda', 'nsr500', '7', '26th', '0'], ['1991', '500cc', 'pentax - honda', 'nsr500', '0', 'nc', '0'], ['1992', '500cc', 'hrc - honda', 'nsr500', '10', '16th', '0'], ['1993', '500cc', 'rothmans - honda', 'nsr500', '119', '7th', '0'], ['1994', '500cc', 'hrc - honda', 'nsr500', '141', '7th', '0'], ['1995', '500cc', 'repsol - honda', 'nsr500', '127', '5th', '0'], ['1996', '500cc', 'repsol - honda', 'nsr500v', '77', '12th', '0'], ['1999', '500cc', 'lucky strike - honda', 'nsr500', '9', '21st', '0'], ['2002', 'motogp', 'repsol - honda', 'rc211v', '13', '21st', '0'], ['2002', 'motogp', 'kanemoto - honda', 'nsr500', '13', '21st', '0'], ['2005', 'motogp', 'marlboro - ducati', 'gp5', '0', 'nc', '0'], ['2007', 'motogp', "pramac d'antin ducati", 'gp7', '1', '26th', '0'], ['2011', 'motogp', 'repsol - honda', 'rc212v', '3', '22nd', '0']] |
1984 chicago cubs season | https://en.wikipedia.org/wiki/1984_Chicago_Cubs_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11800675-2.html.csv | aggregation | the average attendance for games in the 1984 chicago cubs season was 20240 . | {'scope': 'all', 'col': '5', 'type': 'average', 'result': '20240', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'attendance'], 'result': '20240', 'ind': 0, 'tostr': 'avg { all_rows ; attendance }'}, '20240'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; attendance } ; 20240 } = true', 'tointer': 'the average of the attendance record of all rows is 20240 .'} | round_eq { avg { all_rows ; attendance } ; 20240 } = true | the average of the attendance record of all rows is 20240 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'attendance_4': 4, '20240_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'attendance_4': 'attendance', '20240_5': '20240'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'attendance_4': [0], '20240_5': [1]} | ['date', 'opponent', 'score', 'loss', 'attendance', 'record'] | [['april 3', 'giants', '5 - 3', 'm davis ( 0 - 1 )', '52700', '1 - 0'], ['april 5', 'giants', '11 - 7', 'krukow ( 0 - 1 )', '8460', '2 - 0'], ['april 6', 'padres', '3 - 2', 'smith ( 0 - 1 )', '15835', '2 - 1'], ['april 7', 'padres', '7 - 6', 'trout ( 0 - 1 )', '27799', '2 - 2'], ['april 8', 'padres', '8 - 5', 'thurmond ( 0 - 1 )', '24285', '3 - 2'], ['april 9', 'dodgers', '4 - 2', 'rainey ( 1 - 1 )', '33284', '3 - 3'], ['april 11', 'dodgers', '2 - 1', 'sanderson ( 0 - 1 )', '38466', '3 - 4'], ['april 13', 'mets', '11 - 2', 'gooden ( 1 - 1 )', '33436', '4 - 4'], ['april 14', 'mets', '5 - 2', 'leary ( 1 - 1 )', '15789', '5 - 4'], ['april 18', 'cardinals', '5 - 0', 'rainey ( 1 - 2 )', '0', '5 - 5'], ['april 18', 'cardinals', '6 - 1', 'lapoint ( 1 - 2 )', '5816', '6 - 5'], ['april 19', 'cardinals', '6 - 1', 'cox ( 2 - 1 )', '8086', '7 - 5'], ['april 20', 'pirates', '5 - 4', 'tekulve ( 0 - 1 )', '22049', '8 - 5'], ['april 21', 'pirates', '8 - 5', 'noles ( 0 - 1 )', '21936', '8 - 6'], ['april 23', 'cardinals', '6 - 2', 'lapoint ( 1 - 3 )', '12468', '9 - 6'], ['april 24', 'cardinals', '3 - 2', 'sutter ( 0 - 1 )', '19639', '10 - 6'], ['april 25', 'cardinals', '7 - 5', 'ruthven ( 2 - 1 )', '24978', '10 - 7'], ['april 27', 'pirates', '3 - 2', 'rainey ( 1 - 3 )', '9057', '10 - 8'], ['april 28', 'pirates', '7 - 1', 'mcwilliams ( 0 - 3 )', '17317', '11 - 8'], ['april 29', 'pirates', '2 - 1', 'candelaria ( 3 - 2 )', '13397', '12 - 8']] |
dams | https://en.wikipedia.org/wiki/DAMS | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1029726-1.html.csv | count | among the dams drivers that raced in 2010 , two of them raced over 10 races . | {'scope': 'subset', 'criterion': 'greater_than', 'value': '10', 'result': '2', 'col': '3', 'subset': {'col': '1', 'criterion': 'equal', 'value': '2010'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'year', '2010'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; year ; 2010 }', 'tointer': 'select the rows whose year record is equal to 2010 .'}, 'races', '10'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose year record is equal to 2010 . among these rows , select the rows whose races record is greater than 10 .', 'tostr': 'filter_greater { filter_eq { all_rows ; year ; 2010 } ; races ; 10 }'}], 'result': '2', 'ind': 2, 'tostr': 'count { filter_greater { filter_eq { all_rows ; year ; 2010 } ; races ; 10 } }', 'tointer': 'select the rows whose year record is equal to 2010 . among these rows , select the rows whose races record is greater than 10 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_greater { filter_eq { all_rows ; year ; 2010 } ; races ; 10 } } ; 2 } = true', 'tointer': 'select the rows whose year record is equal to 2010 . among these rows , select the rows whose races record is greater than 10 . the number of such rows is 2 .'} | eq { count { filter_greater { filter_eq { all_rows ; year ; 2010 } ; races ; 10 } } ; 2 } = true | select the rows whose year record is equal to 2010 . among these rows , select the rows whose races record is greater than 10 . the number of such rows is 2 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_greater_1': 1, 'filter_eq_0': 0, 'all_rows_5': 5, 'year_6': 6, '2010_7': 7, 'races_8': 8, '10_9': 9, '2_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_greater_1': 'filter_greater', 'filter_eq_0': 'filter_eq', 'all_rows_5': 'all_rows', 'year_6': 'year', '2010_7': '2010', 'races_8': 'races', '10_9': '10', '2_10': '2'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_greater_1': [2], 'filter_eq_0': [1], 'all_rows_5': [0], 'year_6': [0], '2010_7': [0], 'races_8': [1], '10_9': [1], '2_10': [3]} | ['year', 'drivers', 'races', 'wins', 'poles', 'fl', 'points', 'dc', 'tc'] | [['2005', 'josé maría lópez', '23', '1', '0', '0', '36', '9th', '7th'], ['2005', 'fairuz fauzy', '23', '0', '0', '0', '0', '24th', '7th'], ['2006', 'ferdinando monfardini', '21', '0', '0', '0', '6', '21st', '12th'], ['2006', 'franck perera', '21', '0', '0', '0', '8', '17th', '12th'], ['2007', 'kazuki nakajima', '21', '0', '1', '3', '44', '5th', '5th'], ['2007', 'nicolas lapierre', '21', '2', '1', '2', '23', '12th', '5th'], ['2008', "jérôme d'ambrosio", '20', '0', '0', '0', '21', '11th', '8th'], ['2008', 'kamui kobayashi', '20', '1', '0', '2', '10', '16th', '8th'], ['2009', "jérôme d'ambrosio", '20', '0', '0', '0', '29', '9th', '6th'], ['2009', 'kamui kobayashi', '20', '0', '0', '0', '13', '16th', '6th'], ['2010', "jérôme d'ambrosio", '18', '1', '1', '0', '21', '12th', '6th'], ['2010', 'ho - pin tung', '14', '0', '0', '0', '0', '28th', '6th'], ['2010', 'romain grosjean', '8', '0', '0', '0', '14', '14th', '6th'], ['2011', 'romain grosjean', '18', '5', '1', '6', '89', '1st', '2nd'], ['2011', 'pål varhaug', '18', '0', '0', '0', '0', '23rd', '2nd'], ['2012', 'davide valsecchi', '24', '4', '2', '5', '247', '1st', '1st'], ['2012', 'felipe nasr', '24', '0', '0', '0', '95', '10th', '1st']] |
2004 japanese grand prix | https://en.wikipedia.org/wiki/2004_Japanese_Grand_Prix | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1054525-2.html.csv | superlative | zsolt baumgartner had the largest value position on the grid in the 2004 japanese grand prix . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '17', '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', 'grid'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; grid }'}, 'driver'], 'result': 'zsolt baumgartner', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; grid } ; driver }'}, 'zsolt baumgartner'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; grid } ; driver } ; zsolt baumgartner } = true', 'tointer': 'select the row whose grid record of all rows is maximum . the driver record of this row is zsolt baumgartner .'} | eq { hop { argmax { all_rows ; grid } ; driver } ; zsolt baumgartner } = true | select the row whose grid record of all rows is maximum . the driver record of this row is zsolt baumgartner . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'grid_5': 5, 'driver_6': 6, 'zsolt baumgartner_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'grid_5': 'grid', 'driver_6': 'driver', 'zsolt baumgartner_7': 'zsolt baumgartner'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'grid_5': [0], 'driver_6': [1], 'zsolt baumgartner_7': [2]} | ['driver', 'constructor', 'laps', 'time / retired', 'grid'] | [['michael schumacher', 'ferrari', '53', '1:24:26.985', '1'], ['ralf schumacher', 'williams - bmw', '53', '+ 14.098', '2'], ['jenson button', 'bar - honda', '53', '+ 19.662', '5'], ['takuma sato', 'bar - honda', '53', '+ 31.781', '4'], ['fernando alonso', 'renault', '53', '+ 37.767', '11'], ['kimi räikkönen', 'mclaren - mercedes', '53', '+ 39.362', '12'], ['juan pablo montoya', 'williams - bmw', '53', '+ 55.347', '13'], ['giancarlo fisichella', 'sauber - petronas', '53', '+ 56.276', '7'], ['felipe massa', 'sauber - petronas', '53', '+ 1:29.656', '19'], ['jacques villeneuve', 'renault', '52', '+ 1 lap', '9'], ['jarno trulli', 'toyota', '52', '+ 1 lap', '6'], ['christian klien', 'jaguar - cosworth', '52', '+ 1 lap', '14'], ['nick heidfeld', 'jordan - ford', '52', '+ 1 lap', '16'], ['olivier panis', 'toyota', '51', '+ 2 lap', '10'], ['timo glock', 'jordan - ford', '51', '+ 2 lap', '17'], ['gianmaria bruni', 'minardi - cosworth', '50', '+ 3 lap', '18'], ['zsolt baumgartner', 'minardi - cosworth', '41', 'spin', '20'], ['david coulthard', 'mclaren - mercedes', '38', 'collision', '8'], ['rubens barrichello', 'ferrari', '38', 'collision', '15'], ['mark webber', 'jaguar - cosworth', '20', 'overheating', '3']] |
list of jag episodes | https://en.wikipedia.org/wiki/List_of_JAG_episodes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-228973-3.html.csv | unique | the jag episode titled ' we the people ' was the only jag episode written by donald p bellisario . | {'scope': 'all', 'row': '1', 'col': '5', 'col_other': '3', 'criterion': 'equal', 'value': 'donald p bellisario', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'written by', 'donald p bellisario'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose written by record fuzzily matches to donald p bellisario .', 'tostr': 'filter_eq { all_rows ; written by ; donald p bellisario }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; written by ; donald p bellisario } }', 'tointer': 'select the rows whose written by record fuzzily matches to donald p bellisario . 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', 'donald p bellisario'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose written by record fuzzily matches to donald p bellisario .', 'tostr': 'filter_eq { all_rows ; written by ; donald p bellisario }'}, 'title'], 'result': 'we the people', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; written by ; donald p bellisario } ; title }'}, 'we the people'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; written by ; donald p bellisario } ; title } ; we the people }', 'tointer': 'the title record of this unqiue row is we the people .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; written by ; donald p bellisario } } ; eq { hop { filter_eq { all_rows ; written by ; donald p bellisario } ; title } ; we the people } } = true', 'tointer': 'select the rows whose written by record fuzzily matches to donald p bellisario . there is only one such row in the table . the title record of this unqiue row is we the people .'} | and { only { filter_eq { all_rows ; written by ; donald p bellisario } } ; eq { hop { filter_eq { all_rows ; written by ; donald p bellisario } ; title } ; we the people } } = true | select the rows whose written by record fuzzily matches to donald p bellisario . there is only one such row in the table . the title record of this unqiue row is we the people . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'written by_7': 7, 'donald p bellisario_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'title_9': 9, 'we the people_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', 'donald p bellisario_8': 'donald p bellisario', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'title_9': 'title', 'we the people_10': 'we the people'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'written by_7': [0], 'donald p bellisario_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'title_9': [2], 'we the people_10': [3]} | ['no in series', 'no in season', 'title', 'directed by', 'written by', 'original air date'] | [['23', '1', 'we the people', 'les landau', 'donald p bellisario', 'january 3 , 1997'], ['24', '2', 'secrets', 'ray austin', 'tom towler', 'january 10 , 1997'], ['25', '3', 'jinx', 'jerry jameson', 'jack orman', 'january 17 , 1997'], ['26', '4', 'heroes', 'tony wharmby', 'r scott gemmill', 'january 24 , 1997'], ['27', '5', 'crossing the line', 'tony wharmby', 'stephen zito', 'january 31 , 1997'], ['28', '6', 'trinity', 'alan j levi', 'jack orman', 'february 7 , 1997'], ['29', '7', 'ghosts', 'ray austin', 'r scott gemmill', 'february 7 , 1997'], ['30', '8', 'full engagement', 'alan j levi', 'jack orman', 'february 21 , 1997'], ['31', '9', 'washington holiday', 'joe napolitano', 'stephen zito', 'february 28 , 1997'], ['32', '10', 'the game of go', 'ray austin', 'tom towler', 'february 28 , 1997'], ['33', '11', 'force recon', 'alan j levi', 'tom towler & stephen zito', 'march 7 , 1997'], ['34', '12', 'the guardian', 'michael schultz', 'jack orman', 'march 28 , 1997'], ['35', '13', 'code blue', 'tony wharmby', 'r scott gemmill', 'april 4 , 1997'], ['36', '14', 'cowboys & cossacks', 'tony wharmby', 'r scott gemmill', 'april 11 , 1997']] |
1997 cfl draft | https://en.wikipedia.org/wiki/1997_CFL_Draft | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-28059992-6.html.csv | comparative | dan comiskey was picked earlier in the draft than kelly lochbaum . | {'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', 'player', 'dan comiskey'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose player record fuzzily matches to dan comiskey .', 'tostr': 'filter_eq { all_rows ; player ; dan comiskey }'}, 'pick'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; player ; dan comiskey } ; pick }', 'tointer': 'select the rows whose player record fuzzily matches to dan comiskey . take the pick record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', 'kelly lochbaum'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose player record fuzzily matches to kelly lochbaum .', 'tostr': 'filter_eq { all_rows ; player ; kelly lochbaum }'}, 'pick'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; player ; kelly lochbaum } ; pick }', 'tointer': 'select the rows whose player record fuzzily matches to kelly lochbaum . take the pick record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; player ; dan comiskey } ; pick } ; hop { filter_eq { all_rows ; player ; kelly lochbaum } ; pick } } = true', 'tointer': 'select the rows whose player record fuzzily matches to dan comiskey . take the pick record of this row . select the rows whose player record fuzzily matches to kelly lochbaum . take the pick record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; player ; dan comiskey } ; pick } ; hop { filter_eq { all_rows ; player ; kelly lochbaum } ; pick } } = true | select the rows whose player record fuzzily matches to dan comiskey . take the pick record of this row . select the rows whose player record fuzzily matches to kelly lochbaum . take the pick record of this row . the first record is less than the second record . | 5 | 5 | {'less_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'player_7': 7, 'dan comiskey_8': 8, 'pick_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'player_11': 11, 'kelly lochbaum_12': 12, 'pick_13': 13} | {'less_4': 'less', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'player_7': 'player', 'dan comiskey_8': 'dan comiskey', 'pick_9': 'pick', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'player_11': 'player', 'kelly lochbaum_12': 'kelly lochbaum', 'pick_13': 'pick'} | {'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'player_7': [0], 'dan comiskey_8': [0], 'pick_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'player_11': [1], 'kelly lochbaum_12': [1], 'pick_13': [3]} | ['pick', 'cfl team', 'player', 'position', 'college'] | [['42', 'saskatchewan', 'dan comiskey', 'ol', 'windsor'], ['43', 'bc', 'kelly lochbaum', 'lb', 'northern arizona'], ['44', 'winnipeg', 'wayne weathers', 'de', 'manitoba'], ['45', 'montreal', 'francis bellefroid', 'lb', "bishop 's"], ['46', 'calgary', 'paul donkersley', 'rb', 'acadia'], ['47', 'edmonton', 'chris hardy', 'qb', 'manitoba']] |
1988 england rugby union tour of australia and fiji | https://en.wikipedia.org/wiki/1988_England_rugby_union_tour_of_Australia_and_Fiji | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17058417-1.html.csv | unique | may 25th , 1988 was the only date when the venue was in toowoomba . | {'scope': 'all', 'row': '3', 'col': '4', 'col_other': '3', 'criterion': 'equal', 'value': 'toowoomba', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'venue', 'toowoomba'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose venue record fuzzily matches to toowoomba .', 'tostr': 'filter_eq { all_rows ; venue ; toowoomba }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; venue ; toowoomba } }', 'tointer': 'select the rows whose venue record fuzzily matches to toowoomba . 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', 'toowoomba'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose venue record fuzzily matches to toowoomba .', 'tostr': 'filter_eq { all_rows ; venue ; toowoomba }'}, 'date'], 'result': '25 may 1988', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; venue ; toowoomba } ; date }'}, '25 may 1988'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; venue ; toowoomba } ; date } ; 25 may 1988 }', 'tointer': 'the date record of this unqiue row is 25 may 1988 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; venue ; toowoomba } } ; eq { hop { filter_eq { all_rows ; venue ; toowoomba } ; date } ; 25 may 1988 } } = true', 'tointer': 'select the rows whose venue record fuzzily matches to toowoomba . there is only one such row in the table . the date record of this unqiue row is 25 may 1988 .'} | and { only { filter_eq { all_rows ; venue ; toowoomba } } ; eq { hop { filter_eq { all_rows ; venue ; toowoomba } ; date } ; 25 may 1988 } } = true | select the rows whose venue record fuzzily matches to toowoomba . there is only one such row in the table . the date record of this unqiue row is 25 may 1988 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'venue_7': 7, 'toowoomba_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'date_9': 9, '25 may 1988_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', 'toowoomba_8': 'toowoomba', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'date_9': 'date', '25 may 1988_10': '25 may 1988'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'venue_7': [0], 'toowoomba_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'date_9': [2], '25 may 1988_10': [3]} | ['opposing team', 'against', 'date', 'venue', 'status'] | [['queensland country', '9', '17 may 1988', 'quarry hill rugby park , mackay', 'tour match'], ['queensland', '19', '22 may 1988', 'ballymore , brisbane', 'tour match'], ["queensland ' b '", '7', '25 may 1988', 'gold park , toowoomba', 'tour match'], ['australia', '22', '29 may 1988', 'ballymore , brisbane', 'first test'], ['south australia invitation xv', '10', '1 june 1988', 'hindmarsh stadium , adelaide', 'tour match'], ['new south wales', '23', '5 june 1988', 'waratah stadium , sydney', 'tour match'], ["new south wales ' b '", '9', '8 june 1988', 'brandon park , wollongong', 'tour match'], ['australia', '28', '12 june 1988', 'waratah stadium , sydney', 'second test'], ['fiji', '12', '16 june 1988', 'national stadium , suva', 'test match']] |
concrete canoe | https://en.wikipedia.org/wiki/Concrete_canoe | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2331549-1.html.csv | count | for concrete canoe , there were 4 times when the champion was the university of california , berkeley . | {'scope': 'all', 'criterion': 'equal', 'value': 'university of california , berkeley', 'result': '4', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'champion', 'university of california , berkeley'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose champion record fuzzily matches to university of california , berkeley .', 'tostr': 'filter_eq { all_rows ; champion ; university of california , berkeley }'}], 'result': '4', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; champion ; university of california , berkeley } }', 'tointer': 'select the rows whose champion record fuzzily matches to university of california , berkeley . the number of such rows is 4 .'}, '4'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; champion ; university of california , berkeley } } ; 4 } = true', 'tointer': 'select the rows whose champion record fuzzily matches to university of california , berkeley . the number of such rows is 4 .'} | eq { count { filter_eq { all_rows ; champion ; university of california , berkeley } } ; 4 } = true | select the rows whose champion record fuzzily matches to university of california , berkeley . 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, 'champion_5': 5, 'university of california , berkeley_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', 'champion_5': 'champion', 'university of california , berkeley_6': 'university of california , berkeley', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'champion_5': [0], 'university of california , berkeley_6': [0], '4_7': [2]} | ['year', 'host city', 'host school', 'champion', 'second place', 'third place'] | [['1988', 'east lansing , michigan', 'michigan state university', 'university of california , berkeley', 'university of new hampshire', 'university of akron'], ['1989', 'lubbock , texas', 'texas tech university', 'university of california , berkeley', 'michigan state university', 'university of new hampshire'], ['1990', 'buffalo , new york', 'state university of new york', 'michigan state university', 'university of maryland', 'university of california , berkeley'], ['1991', 'orlando , florida', 'university of central florida', 'university of california , berkeley', 'university of maryland', 'university at buffalo'], ['1992', 'fort collins , colorado', 'colorado state university', 'university of california , berkeley', 'university of alabama , huntsville', 'university of new orleans'], ['1993', 'sacramento , california', 'california state university , sacramento', 'university of alabama , huntsville', 'michigan state university', 'university of california , berkeley'], ['1994', 'new orleans , louisiana', 'university of new orleans', 'university of alabama , huntsville', 'university of california , berkeley', 'university of new orleans'], ['1995', 'washington , dc', 'george washington university', 'south dakota school of mines & technology', 'california state university , sacramento', 'michigan state university'], ['1996', 'madison , wisconsin', 'university of wisconsin at madison', 'university of alabama , huntsville', 'michigan state university', 'university of california , berkeley'], ['1997', 'cleveland , ohio', 'cleveland state university', 'florida institute of technology', 'university of alabama , huntsville', 'university of california , berkeley'], ['1998', 'rapid city , south dakota', 'south dakota school of mines & technology', 'university of alabama , huntsville', 'california state university , sacramento', 'clemson university'], ['1999', 'melbourne , florida', 'florida institute of technology', 'clemson university', 'university of alabama , huntsville', 'oklahoma state university'], ['2000', 'golden , colorado', 'colorado school of mines', 'clemson university', 'oklahoma state university', 'florida institute of technology'], ['2001', 'san diego , california', 'san diego state university', 'university of alabama , huntsville', 'clemson university', 'oklahoma state university'], ['2002', 'madison , wisconsin', 'university of wisconsin', 'clemson university', 'université laval', 'oklahoma state university'], ['2003', 'philadelphia , pennsylvania', 'drexel university', 'university of wisconsin , madison', 'université laval', 'university of california , berkeley'], ['2004', 'washington , dc', 'the catholic university of america', 'university of wisconsin , madison', 'université laval', 'university of alabama , huntsville'], ['2005', 'clemson , south carolina', 'clemson university', 'university of wisconsin , madison', 'clemson university', 'michigan technological university'], ['2007', 'seattle , washington', 'university of washington', 'university of wisconsin , madison', 'university of florida', 'university of nevada , reno'], ['2008', 'montreal , quebec', 'école de technologie supérieure', 'university of nevada , reno', 'university of california , berkeley', 'école de technologie supérieure']] |
corruption in india | https://en.wikipedia.org/wiki/Corruption_in_India | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14496392-1.html.csv | aggregation | the average anti-corruption index in indian states for the years 1990-95 was 0.27 . | {'scope': 'all', 'col': '2', 'type': 'average', 'result': '0.27', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', '1990 - 95'], 'result': '0.27', 'ind': 0, 'tostr': 'avg { all_rows ; 1990 - 95 }'}, '0.27'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; 1990 - 95 } ; 0.27 } = true', 'tointer': 'the average of the 1990 - 95 record of all rows is 0.27 .'} | round_eq { avg { all_rows ; 1990 - 95 } ; 0.27 } = true | the average of the 1990 - 95 record of all rows is 0.27 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, '1990 - 95_4': 4, '0.27_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', '1990 - 95_4': '1990 - 95', '0.27_5': '0.27'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], '1990 - 95_4': [0], '0.27_5': [1]} | ['state', '1990 - 95', '1996 - 00', '2001 - 05', '2006 - 10'] | [['bihar', '0.41', '0.30', '0.43', '0.88'], ['gujarat', '0.48', '0.57', '0.64', '0.69'], ['andhra pradesh', '0.53', '0.73', '0.55', '0.61'], ['punjab', '0.32', '0.46', '0.46', '0.60'], ['jammu & kashmir', '0.13', '0.32', '0.17', '0.40'], ['haryana', '0.33', '0.60', '0.31', '0.37'], ['himachal pradesh', '0.26', '0.14', '0.23', '0.35'], ['tamil nadu', '0.19', '0.20', '0.24', '0.29'], ['madhya pradesh', '0.23', '0.22', '0.31', '0.29'], ['karnataka', '0.24', '0.19', '0.20', '0.29'], ['rajasthan', '0.27', '0.23', '0.26', '0.27'], ['kerala', '0.16', '0.20', '0.22', '0.27'], ['maharashtra', '0.45', '0.29', '0.27', '0.26'], ['uttar pradesh', '0.11', '0.11', '0.16', '0.21'], ['orissa', '0.22', '0.16', '0.15', '0.19'], ['assam', '0.21', '0.02', '0.14', '0.17'], ['west bengal', '0.11', '0.08', '0.03', '0.01']] |
1988 formula one season | https://en.wikipedia.org/wiki/1988_Formula_One_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1139087-2.html.csv | count | ayrton senna took pole position 13 times in the 1988 formula one season . | {'scope': 'all', 'criterion': 'equal', 'value': 'ayrton senna', 'result': '13', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'pole position', 'ayrton senna'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose pole position record fuzzily matches to ayrton senna .', 'tostr': 'filter_eq { all_rows ; pole position ; ayrton senna }'}], 'result': '13', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; pole position ; ayrton senna } }', 'tointer': 'select the rows whose pole position record fuzzily matches to ayrton senna . the number of such rows is 13 .'}, '13'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; pole position ; ayrton senna } } ; 13 } = true', 'tointer': 'select the rows whose pole position record fuzzily matches to ayrton senna . the number of such rows is 13 .'} | eq { count { filter_eq { all_rows ; pole position ; ayrton senna } } ; 13 } = true | select the rows whose pole position record fuzzily matches to ayrton senna . the number of such rows is 13 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'pole position_5': 5, 'ayrton senna_6': 6, '13_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'pole position_5': 'pole position', 'ayrton senna_6': 'ayrton senna', '13_7': '13'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'pole position_5': [0], 'ayrton senna_6': [0], '13_7': [2]} | ['grand prix', 'date', 'location', 'pole position', 'fastest lap', 'winning driver', 'constructor', 'report'] | [['brazilian grand prix', '3 april', 'jacarepaguá', 'ayrton senna', 'gerhard berger', 'alain prost', 'mclaren - honda', 'report'], ['san marino grand prix', '1 may', 'imola', 'ayrton senna', 'alain prost', 'ayrton senna', 'mclaren - honda', 'report'], ['monaco grand prix', '15 may', 'monaco', 'ayrton senna', 'ayrton senna', 'alain prost', 'mclaren - honda', 'report'], ['mexican grand prix', '29 may', 'hermanos rodríguez', 'ayrton senna', 'alain prost', 'alain prost', 'mclaren - honda', 'report'], ['canadian grand prix', '12 june', 'circuit gilles villeneuve', 'ayrton senna', 'ayrton senna', 'ayrton senna', 'mclaren - honda', 'report'], ['detroit grand prix', '19 june', 'detroit', 'ayrton senna', 'alain prost', 'ayrton senna', 'mclaren - honda', 'report'], ['french grand prix', '3 july', 'paul ricard', 'alain prost', 'alain prost', 'alain prost', 'mclaren - honda', 'report'], ['british grand prix', '10 july', 'silverstone', 'gerhard berger', 'nigel mansell', 'ayrton senna', 'mclaren - honda', 'report'], ['german grand prix', '24 july', 'hockenheimring', 'ayrton senna', 'alessandro nannini', 'ayrton senna', 'mclaren - honda', 'report'], ['hungarian grand prix', '7 august', 'hungaroring', 'ayrton senna', 'alain prost', 'ayrton senna', 'mclaren - honda', 'report'], ['belgian grand prix', '28 august', 'spa - francorchamps', 'ayrton senna', 'gerhard berger', 'ayrton senna', 'mclaren - honda', 'report'], ['italian grand prix', '11 september', 'monza', 'ayrton senna', 'michele alboreto', 'gerhard berger', 'ferrari', 'report'], ['portuguese grand prix', '25 september', 'estoril', 'alain prost', 'gerhard berger', 'alain prost', 'mclaren - honda', 'report'], ['spanish grand prix', '2 october', 'jerez', 'ayrton senna', 'alain prost', 'alain prost', 'mclaren - honda', 'report'], ['japanese grand prix', '30 october', 'suzuka', 'ayrton senna', 'ayrton senna', 'ayrton senna', 'mclaren - honda', 'report'], ['australian grand prix', '13 november', 'adelaide', 'ayrton senna', 'alain prost', 'alain prost', 'mclaren - honda', 'report']] |
list of tallest buildings in ottawa - gatineau | https://en.wikipedia.org/wiki/List_of_tallest_buildings_in_Ottawa%E2%80%93Gatineau | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1722347-2.html.csv | comparative | the richcraft - dow honda site tower i had more floors in its building than the claridge plaza iii . | {'row_1': '1', 'row_2': '10', 'col': '4', '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', 'building', 'richcraft - dow honda site tower i'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose building record fuzzily matches to richcraft - dow honda site tower i .', 'tostr': 'filter_eq { all_rows ; building ; richcraft - dow honda site tower i }'}, 'floors'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; building ; richcraft - dow honda site tower i } ; floors }', 'tointer': 'select the rows whose building record fuzzily matches to richcraft - dow honda site tower i . take the floors record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'building', 'claridge plaza iii'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose building record fuzzily matches to claridge plaza iii .', 'tostr': 'filter_eq { all_rows ; building ; claridge plaza iii }'}, 'floors'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; building ; claridge plaza iii } ; floors }', 'tointer': 'select the rows whose building record fuzzily matches to claridge plaza iii . take the floors record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; building ; richcraft - dow honda site tower i } ; floors } ; hop { filter_eq { all_rows ; building ; claridge plaza iii } ; floors } } = true', 'tointer': 'select the rows whose building record fuzzily matches to richcraft - dow honda site tower i . take the floors record of this row . select the rows whose building record fuzzily matches to claridge plaza iii . take the floors record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; building ; richcraft - dow honda site tower i } ; floors } ; hop { filter_eq { all_rows ; building ; claridge plaza iii } ; floors } } = true | select the rows whose building record fuzzily matches to richcraft - dow honda site tower i . take the floors record of this row . select the rows whose building record fuzzily matches to claridge plaza iii . take the floors 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, 'building_7': 7, 'richcraft - dow honda site tower i_8': 8, 'floors_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'building_11': 11, 'claridge plaza iii_12': 12, 'floors_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', 'building_7': 'building', 'richcraft - dow honda site tower i_8': 'richcraft - dow honda site tower i', 'floors_9': 'floors', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'building_11': 'building', 'claridge plaza iii_12': 'claridge plaza iii', 'floors_13': 'floors'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'building_7': [0], 'richcraft - dow honda site tower i_8': [0], 'floors_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'building_11': [1], 'claridge plaza iii_12': [1], 'floors_13': [3]} | ['building', 'location', 'height', 'floors', 'status'] | [['richcraft - dow honda site tower i', 'little italy', '-', '48', 'proposed'], ['richcraft - dow honda site tower ii', 'little italy', '-', '48', 'proposed'], ['claridge icon', 'little italy', '-', '45', 'approved'], ['lebreton mews tower a', 'bayview yards', '-', '32', 'approved'], ['claridge - 1040 somerset street', 'hintonburg', '-', '39', 'proposed'], ['lebreton mews tower b', 'bayview yards', '-', '29', 'approved'], ['soho italia', 'little italy', '-', '36', 'approved 30 stories / height increase proposed'], ['the rhombus', 'mechanicsville', '-', '32', 'approved'], ['150 elgin', 'downtown', '-', '23', 'under construction'], ['claridge plaza iii', 'sandy hill', '-', '28', 'under construction'], ['265 laurier avenue w', 'downtown', '-', '19', 'proposed'], ['claridge plaza iv', 'sandy hill', '-', '28', 'under construction'], ['tribeca i', 'centretown', '-', '27', 'under construction'], ['tribeca ii', 'centretown', '-', '27', 'under construction'], ['nepean tower', 'centretown', '-', '27', 'approved']] |
2000 indianapolis colts season | https://en.wikipedia.org/wiki/2000_Indianapolis_Colts_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14908721-2.html.csv | count | in the 2000 indianapolis colts season ten of the games resulted in a victory . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'w', 'result': '10', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'result', 'w'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose result record fuzzily matches to w .', 'tostr': 'filter_eq { all_rows ; result ; w }'}], 'result': '10', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; result ; w } }', 'tointer': 'select the rows whose result record fuzzily matches to w . the number of such rows is 10 .'}, '10'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; result ; w } } ; 10 } = true', 'tointer': 'select the rows whose result record fuzzily matches to w . the number of such rows is 10 .'} | eq { count { filter_eq { all_rows ; result ; w } } ; 10 } = true | select the rows whose result record fuzzily matches to w . the number of such rows is 10 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'result_5': 5, 'w_6': 6, '10_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'result_5': 'result', 'w_6': 'w', '10_7': '10'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'result_5': [0], 'w_6': [0], '10_7': [2]} | ['week', 'date', 'opponent', 'result', 'record', 'game site', 'tv time', 'attendance'] | [['1', 'september 3 , 2000', 'kansas city chiefs', 'w 27 - 14', '1 - 0', 'arrowhead stadium', 'cbs 1:00 pm', '78357'], ['2', 'september 10 , 2000', 'oakland raiders', 'l 31 - 38', '1 - 1', 'rca dome', 'cbs 1:00 pm', '56769'], ['3', '-', '-', '-', '-', '-', '-', ''], ['4', 'september 25 , 2000', 'jacksonville jaguars', 'w 43 - 14', '2 - 1', 'rca dome', 'abc 9:00 pm', '56816'], ['5', 'october 1 , 2000', 'buffalo bills', 'w 18 - 16', '3 - 1', 'ralph wilson stadium', 'cbs 1:00 pm', '72617'], ['6', 'october 8 , 2000', 'new england patriots', 'l 16 - 24', '3 - 2', 'foxboro stadium', 'cbs 1:00 pm', '60292'], ['7', 'october 15 , 2000', 'seattle seahawks', 'w 37 - 24', '4 - 2', 'husky stadium', 'cbs 4:15 pm', '63593'], ['8', 'october 22 , 2000', 'new england patriots', 'w 30 - 23', '5 - 2', 'rca dome', 'cbs 1:00 pm', '56828'], ['9', 'october 29 , 2000', 'detroit lions', 'w 30 - 18', '6 - 2', 'rca dome', 'fox 1:00 pm', '56971'], ['10', 'november 5 , 2000', 'chicago bears', 'l 24 - 27', '6 - 3', 'soldier field', 'cbs 1:00 pm', '66944'], ['11', 'november 12 , 2000', 'new york jets', 'w 23 - 15', '7 - 3', 'rca dome', 'cbs 1:00 pm', '56657'], ['12', 'november 19 , 2000', 'green bay packers', 'l 24 - 26', '7 - 4', 'lambeau field', 'cbs 1:00 pm', '59869'], ['13', 'november 26 , 2000', 'miami dolphins', 'l 14 - 17', '7 - 5', 'rca dome', 'cbs 4:15 pm', '56935'], ['14', 'december 3 , 2000', 'new york jets', 'l 17 - 27', '7 - 6', 'the meadowlands', 'cbs 4:15 pm', '78138'], ['15', 'december 11 , 2000', 'buffalo bills', 'w 44 - 20', '8 - 6', 'rca dome', 'abc 9:00 pm', '56671'], ['16', 'december 17 , 2000', 'miami dolphins', 'w 20 - 13', '9 - 6', 'pro player stadium', 'cbs 4:05 pm', '73884'], ['17', 'december 24 , 2000', 'minnesota vikings', 'w 31 - 10', '10 - 6', 'rca dome', 'fox 4:15 pm', '56672']] |
2007 - 08 rugby - bundesliga | https://en.wikipedia.org/wiki/2007%E2%80%9308_Rugby-Bundesliga | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-20877272-4.html.csv | majority | all of the rugby teams in the 2007 - 08 rugby - bundesliga played a total of 16 matches . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': '16', 'subset': None} | {'func': 'most_eq', 'args': ['all_rows', 'played', '16'], 'result': True, 'ind': 0, 'tointer': 'for the played records of all rows , most of them are equal to 16 .', 'tostr': 'most_eq { all_rows ; played ; 16 } = true'} | most_eq { all_rows ; played ; 16 } = true | for the played records of all rows , most of them are equal to 16 . | 1 | 1 | {'most_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'played_3': 3, '16_4': 4} | {'most_eq_0': 'most_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'played_3': 'played', '16_4': '16'} | {'most_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'played_3': [0], '16_4': [0]} | ['', 'club', 'played', 'won', 'drawn', 'lost', 'points for', 'points against', 'difference', 'points'] | [['1', 'asv köln rugby', '16', '12', '2', '2', '484', '118', '366', '41'], ['2', 'stuttgarter rc', '16', '13', '1', '2', '339', '190', '149', '39'], ['3', 'tsv handschuhsheim ii', '16', '10', '0', '6', '377', '276', '101', '35'], ['4', 'sc 1880 frankfurt ii', '16', '8', '1', '7', '415', '245', '170', '33'], ['5', 'münchen rfc', '16', '7', '2', '7', '261', '282', '- 21', '31'], ['6', 'stusta münchen', '16', '5', '1', '10', '238', '405', '- 167', '27'], ['7', 'heidelberger tv', '16', '5', '0', '11', '253', '377', '- 124', '26'], ['8', 'rg heidelberg ii', '16', '5', '0', '11', '274', '440', '- 166', '25']] |
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