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jack mcgrath | https://en.wikipedia.org/wiki/Jack_McGrath | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1236208-1.html.csv | majority | the majority of the time jake started in the # 3 position . | {'scope': 'all', 'col': '2', 'most_or_all': 'most', 'criterion': 'equal', 'value': '3', 'subset': None} | {'func': 'most_eq', 'args': ['all_rows', 'start', '3'], 'result': True, 'ind': 0, 'tointer': 'for the start records of all rows , most of them are equal to 3 .', 'tostr': 'most_eq { all_rows ; start ; 3 } = true'} | most_eq { all_rows ; start ; 3 } = true | for the start records of all rows , most of them are equal to 3 . | 1 | 1 | {'most_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'start_3': 3, '3_4': 4} | {'most_eq_0': 'most_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'start_3': 'start', '3_4': '3'} | {'most_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'start_3': [0], '3_4': [0]} | ['year', 'start', 'qual', 'rank', 'finish', 'laps'] | [['1948', '13', '124.580', '16', '21', '70'], ['1949', '3', '128.884', '8', '26', '39'], ['1950', '6', '131.868', '10', '14', '131'], ['1951', '3', '134.303', '8', '3', '200'], ['1952', '3', '136.664', '5', '11', '200'], ['1953', '3', '136.602', '13', '5', '200'], ['1954', '1', '141.033', '1', '3', '200'], ['1955', '3', '142.580', '1', '26', '54']] |
melissa reid | https://en.wikipedia.org/wiki/Melissa_Reid | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-29506171-2.html.csv | unique | the only year that melissa reid had 0 wins and played in more than 15 tournaments is 2008 . | {'scope': 'subset', 'row': '3', 'col': '2', 'col_other': '1', 'criterion': 'greater_than', 'value': '15', 'subset': {'col': '4', 'criterion': 'equal', 'value': '0'}} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_greater', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'wins', '0'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; wins ; 0 }', 'tointer': 'select the rows whose wins record is equal to 0 .'}, 'tournaments played', '15'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose wins record is equal to 0 . among these rows , select the rows whose tournaments played record is greater than 15 .', 'tostr': 'filter_greater { filter_eq { all_rows ; wins ; 0 } ; tournaments played ; 15 }'}], 'result': True, 'ind': 2, 'tostr': 'only { filter_greater { filter_eq { all_rows ; wins ; 0 } ; tournaments played ; 15 } }', 'tointer': 'select the rows whose wins record is equal to 0 . among these rows , select the rows whose tournaments played record is greater than 15 . there is only one such row in the table .'}, {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_greater', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'wins', '0'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; wins ; 0 }', 'tointer': 'select the rows whose wins record is equal to 0 .'}, 'tournaments played', '15'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose wins record is equal to 0 . among these rows , select the rows whose tournaments played record is greater than 15 .', 'tostr': 'filter_greater { filter_eq { all_rows ; wins ; 0 } ; tournaments played ; 15 }'}, 'year'], 'result': '2008', 'ind': 3, 'tostr': 'hop { filter_greater { filter_eq { all_rows ; wins ; 0 } ; tournaments played ; 15 } ; year }'}, '2008'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { filter_greater { filter_eq { all_rows ; wins ; 0 } ; tournaments played ; 15 } ; year } ; 2008 }', 'tointer': 'the year record of this unqiue row is 2008 .'}], 'result': True, 'ind': 5, 'tostr': 'and { only { filter_greater { filter_eq { all_rows ; wins ; 0 } ; tournaments played ; 15 } } ; eq { hop { filter_greater { filter_eq { all_rows ; wins ; 0 } ; tournaments played ; 15 } ; year } ; 2008 } } = true', 'tointer': 'select the rows whose wins record is equal to 0 . among these rows , select the rows whose tournaments played record is greater than 15 . there is only one such row in the table . the year record of this unqiue row is 2008 .'} | and { only { filter_greater { filter_eq { all_rows ; wins ; 0 } ; tournaments played ; 15 } } ; eq { hop { filter_greater { filter_eq { all_rows ; wins ; 0 } ; tournaments played ; 15 } ; year } ; 2008 } } = true | select the rows whose wins record is equal to 0 . among these rows , select the rows whose tournaments played record is greater than 15 . there is only one such row in the table . the year record of this unqiue row is 2008 . | 8 | 6 | {'and_5': 5, 'result_6': 6, 'only_2': 2, 'filter_greater_1': 1, 'filter_eq_0': 0, 'all_rows_7': 7, 'wins_8': 8, '0_9': 9, 'tournaments played_10': 10, '15_11': 11, 'eq_4': 4, 'num_hop_3': 3, 'year_12': 12, '2008_13': 13} | {'and_5': 'and', 'result_6': 'true', 'only_2': 'only', 'filter_greater_1': 'filter_greater', 'filter_eq_0': 'filter_eq', 'all_rows_7': 'all_rows', 'wins_8': 'wins', '0_9': '0', 'tournaments played_10': 'tournaments played', '15_11': '15', 'eq_4': 'eq', 'num_hop_3': 'num_hop', 'year_12': 'year', '2008_13': '2008'} | {'and_5': [6], 'result_6': [], 'only_2': [5], 'filter_greater_1': [2, 3], 'filter_eq_0': [1], 'all_rows_7': [0], 'wins_8': [0], '0_9': [0], 'tournaments played_10': [1], '15_11': [1], 'eq_4': [5], 'num_hop_3': [4], 'year_12': [3], '2008_13': [4]} | ['year', 'tournaments played', 'cuts made', 'wins', '2nd', '3rd', 'top 10s', 'best finish', 'earnings', 'money list rank', 'scoring average', 'scoring rank', 'rolex ranking'] | [['2006', '1', '1', '0', '0', '0', '0', 't12', 'n / a', 'n / a', '72.33', 'n / a', '658'], ['2007', '3', '3', '0', '0', '0', '1', '9', '4050 1', 'n / a', '73.18', 'n / a', '307'], ['2008', '16', '12', '0', '3', '1', '7', '2', '136606', '12', '71.96', '26', '169'], ['2009', '14', '13', '0', '1', '2', '8', '2', '168749', '7', '71.12', '6', '128'], ['2010', '21', '20', '1', '2', '1', '10', '1', '270871', '3', '71.21', '7', '58'], ['2011', '19', '19', '2', '1', '3', '10', '1', '286578', '2', '70.83', '11', '45']] |
1928 vfl season | https://en.wikipedia.org/wiki/1928_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10766119-9.html.csv | majority | all games of the 1928 vfl season were played on the 9th of june . | {'scope': 'all', 'col': '7', 'most_or_all': 'all', 'criterion': 'equal', 'value': '9 june 1928', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'date', '9 june 1928'], 'result': True, 'ind': 0, 'tointer': 'for the date records of all rows , all of them fuzzily match to 9 june 1928 .', 'tostr': 'all_eq { all_rows ; date ; 9 june 1928 } = true'} | all_eq { all_rows ; date ; 9 june 1928 } = true | for the date records of all rows , all of them fuzzily match to 9 june 1928 . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'date_3': 3, '9 june 1928_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'date_3': 'date', '9 june 1928_4': '9 june 1928'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'date_3': [0], '9 june 1928_4': [0]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['richmond', '21.16 ( 142 )', 'south melbourne', '9.12 ( 66 )', 'punt road oval', '21000', '9 june 1928'], ['collingwood', '13.14 ( 92 )', 'melbourne', '11.14 ( 80 )', 'victoria park', '27000', '9 june 1928'], ['carlton', '9.7 ( 61 )', 'footscray', '8.14 ( 62 )', 'princes park', '25000', '9 june 1928'], ['st kilda', '14.13 ( 97 )', 'geelong', '10.6 ( 66 )', 'junction oval', '17000', '9 june 1928'], ['hawthorn', '10.12 ( 72 )', 'fitzroy', '15.16 ( 106 )', 'glenferrie oval', '8000', '9 june 1928'], ['north melbourne', '9.5 ( 59 )', 'essendon', '10.10 ( 70 )', 'arden street oval', '13000', '9 june 1928']] |
rowing at the 2008 summer olympics - women 's coxless pair | https://en.wikipedia.org/wiki/Rowing_at_the_2008_Summer_Olympics_%E2%80%93_Women%27s_coxless_pair | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18662697-3.html.csv | unique | canada is the only country that had a boat under water during the women 's coxless pair at the 2008 summer olympics . | {'scope': 'all', 'row': '5', 'col': '4', 'col_other': '3', 'criterion': 'equal', 'value': 'boat under weight', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'time', 'boat under weight'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose time record fuzzily matches to boat under weight .', 'tostr': 'filter_eq { all_rows ; time ; boat under weight }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; time ; boat under weight } }', 'tointer': 'select the rows whose time record fuzzily matches to boat under weight . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'time', 'boat under weight'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose time record fuzzily matches to boat under weight .', 'tostr': 'filter_eq { all_rows ; time ; boat under weight }'}, 'country'], 'result': 'canada', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; time ; boat under weight } ; country }'}, 'canada'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; time ; boat under weight } ; country } ; canada }', 'tointer': 'the country record of this unqiue row is canada .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; time ; boat under weight } } ; eq { hop { filter_eq { all_rows ; time ; boat under weight } ; country } ; canada } } = true', 'tointer': 'select the rows whose time record fuzzily matches to boat under weight . there is only one such row in the table . the country record of this unqiue row is canada .'} | and { only { filter_eq { all_rows ; time ; boat under weight } } ; eq { hop { filter_eq { all_rows ; time ; boat under weight } ; country } ; canada } } = true | select the rows whose time record fuzzily matches to boat under weight . there is only one such row in the table . the country record of this unqiue row is canada . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'time_7': 7, 'boat under weight_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'country_9': 9, 'canada_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'time_7': 'time', 'boat under weight_8': 'boat under weight', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'country_9': 'country', 'canada_10': 'canada'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'time_7': [0], 'boat under weight_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'country_9': [2], 'canada_10': [3]} | ['rank', 'rowers', 'country', 'time', 'notes'] | [['1', 'yuliya bichyk , natallia helakh', 'belarus', '7:24.47', 'fa'], ['2', 'juliette haigh , nicola coles', 'new zealand', '7:31.45', 'r'], ['3', 'wu you , gao yulan', 'china', '7:32.50', 'r'], ['4', 'kim crow , sarah cook', 'australia', '7:44.04', 'r'], ['5', 'zoe hoskins , sabrina kolker', 'canada', 'boat under weight', 'r']] |
wru division four west | https://en.wikipedia.org/wiki/WRU_Division_Four_West | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13758945-2.html.csv | superlative | the highest number of points against is for cwmgors rfc . | {'scope': 'all', 'col_superlative': '6', 'row_superlative': '13', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'points against'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; points against }'}, 'club'], 'result': 'cwmgors rfc', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; points against } ; club }'}, 'cwmgors rfc'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; points against } ; club } ; cwmgors rfc } = true', 'tointer': 'select the row whose points against record of all rows is maximum . the club record of this row is cwmgors rfc .'} | eq { hop { argmax { all_rows ; points against } ; club } ; cwmgors rfc } = true | select the row whose points against record of all rows is maximum . the club record of this row is cwmgors rfc . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'points against_5': 5, 'club_6': 6, 'cwmgors rfc_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'points against_5': 'points against', 'club_6': 'club', 'cwmgors rfc_7': 'cwmgors rfc'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'points against_5': [0], 'club_6': [1], 'cwmgors rfc_7': [2]} | ['club', 'played', 'drawn', 'lost', 'points for', 'points against', 'tries for', 'tries against', 'try bonus', 'losing bonus', 'points'] | [['club', 'played', 'drawn', 'lost', 'points for', 'points against', 'tries for', 'tries against', 'try bonus', 'losing bonus', 'points'], ['llandeilo rfc', '22', '1', '0', '917', '119', '136', '14', '19', '0', '105'], ['brynamman rfc', '22', '1', '2', '821', '210', '116', '27', '16', '2', '96'], ['tenby united rfc', '22', '0', '8', '562', '461', '78', '61', '10', '1', '67'], ['pembroke dock harlequins rfc', '22', '0', '8', '423', '351', '56', '40', '7', '3', '66'], ['pontarddulais rfc', '22', '1', '9', '550', '503', '79', '68', '11', '5', '66'], ['betws rfc', '22', '1', '9', '528', '440', '72', '63', '9', '0', '59'], ['trimsaran rfc', '22', '0', '12', '471', '540', '68', '77', '7', '1', '48'], ['pembroke rfc', '22', '0', '13', '467', '500', '69', '66', '8', '4', '48'], ['burry port rfc', '22', '1', '14', '373', '688', '47', '99', '3', '2', '31'], ['hendy rfc', '22', '0', '17', '292', '707', '38', '109', '1', '6', '27'], ['tycroes rfc', '22', '0', '18', '267', '645', '35', '89', '3', '3', '18'], ['cwmgors rfc', '22', '1', '19', '211', '718', '28', '109', '2', '3', '15']] |
ivana abramovi \ xc4 \ x87 | https://en.wikipedia.org/wiki/Ivana_Abramovi%C4%87 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14851245-3.html.csv | count | four of the tournaments that abramovic entered were in 2002 . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': '2002', 'result': '4', 'col': '2', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', '2002'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose date record fuzzily matches to 2002 .', 'tostr': 'filter_eq { all_rows ; date ; 2002 }'}], 'result': '4', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; date ; 2002 } }', 'tointer': 'select the rows whose date record fuzzily matches to 2002 . the number of such rows is 4 .'}, '4'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; date ; 2002 } } ; 4 } = true', 'tointer': 'select the rows whose date record fuzzily matches to 2002 . the number of such rows is 4 .'} | eq { count { filter_eq { all_rows ; date ; 2002 } } ; 4 } = true | select the rows whose date record fuzzily matches to 2002 . the number of such rows is 4 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'date_5': 5, '2002_6': 6, '4_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'date_5': 'date', '2002_6': '2002', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'date_5': [0], '2002_6': [0], '4_7': [2]} | ['outcome', 'date', 'tournament', 'surface', 'partner', 'opponents', 'score'] | [['runner - up', '15 - oct - 2001', 'makarska', 'clay', 'raffaella bindi', 'petra raclavska blanka kumbarova', '4 - 6 , 5 - 7'], ['winner', '03 - dec - 2001', 'bangkok', 'hard', 'kim jin - hee', 'mi - ra jeon manisha malhotra', '6 - 1 7 - 5'], ['runner - up', '08 - jan - 2002', 'tallahassee', 'hard', 'jacqueline trail', 'jessica lehnhoff vanessa webb', '4 - 6 , 3 - 6'], ['runner - up', '04 - mar - 2002', 'makarska', 'clay', 'lenka tvaroskova', 'tina hergold yevgenia savranska', '7 - 5 , 3 - 6 , 5 - 7'], ['winner', '27 - may - 2002', 'makarska', 'clay', 'jenny belobrajdic', 'zsuzsanna fodor dorottya magas', '6 - 4 6 - 0'], ['winner', '01 - dec - 2002', 'nonthaburi province', 'hard', 'remi tezuka', 'amanda augustus debby haak', '6 - 2 6 - 1'], ['runner - up', '22 - nov - 2004', 'san luis potosã\xad', 'hard', 'maria abramovic', 'hannah collin karen paterson', '4 - 6 6 - 2 2 - 6'], ['runner - up', '21 - mar - 2005', 'rome', 'clay', 'stefanie haidner', 'valentina sulpizio sandra zahlavova', '5 - 7 , 7 - 5 , 1 - 6'], ['winner', '15 - nov - 2005', 'puebla', 'hard', 'maria abramovic', 'betina jozami veronica spiegel', '6 - 4 , 4 - 6 , 6 - 7'], ['runner - up', '03 - apr - 2006', 'putignano', 'hard', 'maria abramovic', 'anastasia rodionova arina rodionova', '6 - 1 , 1 - 6 , 5 - 7'], ['winner', '15 - may - 2006', 'saint gaudens', 'clay', 'alla kudryavtseva', 'maria jose argeri leticia sobral', '6 - 2 6 - 0'], ['winner', '31 - jul - 2006', 'martina franca', 'clay', 'aurelie vedy', 'edina gallovits - hall mervana jugic - salkic', '6 - 3 6 - 2'], ['runner - up', '14 - nov - 2006', 'mexico city', 'clay', 'maria abramovic', 'larissa carvalho joana cortez', '5 - 7 , 2 - 6'], ['runner - up', '21 - nov - 2006', 'puebla', 'hard', 'maria abramovic', 'maria fernanda alves hana sromova', '4 - 6 , 3 - 6'], ['winner', '29 - nov - 2006', 'san diego', 'hard', 'hana sromova', 'christina fusano aleke tsoubanos', '6 - 4 6 - 3'], ['runner - up', '16 - jul - 2007', 'dnipropetrovsk', 'clay', 'maria abramovic', 'amina rakhim arina rodionova', '5 - 7 , 6 - 4 , 2 - 6'], ['runner - up', '24 - sep - 2007', 'podgorica', 'clay', 'maria abramovic', 'danica krstajic sandra martinovic', '1 - 6 , 2 - 6'], ['runner - up', '22 - oct - 2007', 'mexico city', 'hard', 'maria abramovic', 'arantxa rus nicole thyssen', '0 - 6 , 1 - 6']] |
international formula master | https://en.wikipedia.org/wiki/International_Formula_Master | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11292165-3.html.csv | unique | the only time the 3000 pro series took place was in 2005 . | {'scope': 'all', 'row': '1', 'col': '2', 'col_other': '1', 'criterion': 'equal', 'value': '3000 pro series', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'series name', '3000 pro series'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose series name record fuzzily matches to 3000 pro series .', 'tostr': 'filter_eq { all_rows ; series name ; 3000 pro series }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; series name ; 3000 pro series } }', 'tointer': 'select the rows whose series name record fuzzily matches to 3000 pro series . there is only one such row in the table .'}, {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'series name', '3000 pro series'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose series name record fuzzily matches to 3000 pro series .', 'tostr': 'filter_eq { all_rows ; series name ; 3000 pro series }'}, 'season'], 'result': '2005', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; series name ; 3000 pro series } ; season }'}, '2005'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; series name ; 3000 pro series } ; season } ; 2005 }', 'tointer': 'the season record of this unqiue row is 2005 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; series name ; 3000 pro series } } ; eq { hop { filter_eq { all_rows ; series name ; 3000 pro series } ; season } ; 2005 } } = true', 'tointer': 'select the rows whose series name record fuzzily matches to 3000 pro series . there is only one such row in the table . the season record of this unqiue row is 2005 .'} | and { only { filter_eq { all_rows ; series name ; 3000 pro series } } ; eq { hop { filter_eq { all_rows ; series name ; 3000 pro series } ; season } ; 2005 } } = true | select the rows whose series name record fuzzily matches to 3000 pro series . there is only one such row in the table . the season record of this unqiue row is 2005 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'series name_7': 7, '3000 pro series_8': 8, 'eq_3': 3, 'num_hop_2': 2, 'season_9': 9, '2005_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'series name_7': 'series name', '3000 pro series_8': '3000 pro series', 'eq_3': 'eq', 'num_hop_2': 'num_hop', 'season_9': 'season', '2005_10': '2005'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'series name_7': [0], '3000 pro series_8': [0], 'eq_3': [4], 'num_hop_2': [3], 'season_9': [2], '2005_10': [3]} | ['season', 'series name', 'champion', 'team champion', 'secondary class champion'] | [['2005', '3000 pro series', 'norbert siedler / max busnelli', 'draco junior team', 'iago rego rosende ( master junior formula )'], ['2006', 'f3000 international masters', 'jan charouz', 'charouz racing system', 'daniel campos - hull ( master junior formula )'], ['2007', 'international formula master', "jérôme d'ambrosio", 'cram competition', 'isaac lópez navarro ( master junior formula )'], ['2008', 'international formula master', 'chris van der drift', 'jd motorsport', 'marcello puglisi ( formula master italia )'], ['2009', 'international formula master', 'fabio leimer', 'jd motorsport', 'alexander rossi ( rookie of the year )']] |
1974 world ice hockey championships | https://en.wikipedia.org/wiki/1974_World_Ice_Hockey_Championships | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14271063-1.html.csv | superlative | in the 1974 world ice hockey championships the soviet union had the most points . | {'scope': 'all', 'col_superlative': '6', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'points'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; points }'}, 'team'], 'result': 'soviet union', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; points } ; team }'}, 'soviet union'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; points } ; team } ; soviet union } = true', 'tointer': 'select the row whose points record of all rows is maximum . the team record of this row is soviet union .'} | eq { hop { argmax { all_rows ; points } ; team } ; soviet union } = true | select the row whose points record of all rows is maximum . the team record of this row is soviet union . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'points_5': 5, 'team_6': 6, 'soviet union_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'points_5': 'points', 'team_6': 'team', 'soviet union_7': 'soviet union'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'points_5': [0], 'team_6': [1], 'soviet union_7': [2]} | ['team', 'games', 'drawn', 'lost', 'points difference', 'points'] | [['soviet union', '10', '0', '1', '64 - 18', '18'], ['czechoslovakia', '10', '0', '3', '57 - 20', '14'], ['sweden', '10', '1', '4', '38 - 24', '11'], ['finland', '10', '2', '4', '34 - 39', '10'], ['poland', '10', '2', '7', '22 - 64', '4'], ['east germany', '10', '1', '8', '19 - 82', '3']] |
asean club championship | https://en.wikipedia.org/wiki/ASEAN_Club_Championship | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-12303563-1.html.csv | majority | all of the clubs in the asean club championship had 0 finishes in 4th place . | {'scope': 'all', 'col': '6', 'most_or_all': 'all', 'criterion': 'equal', 'value': '0', 'subset': None} | {'func': 'all_eq', 'args': ['all_rows', '4th place', '0'], 'result': True, 'ind': 0, 'tointer': 'for the 4th place records of all rows , all of them are equal to 0 .', 'tostr': 'all_eq { all_rows ; 4th place ; 0 } = true'} | all_eq { all_rows ; 4th place ; 0 } = true | for the 4th place records of all rows , all of them are equal to 0 . | 1 | 1 | {'all_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, '4th place_3': 3, '0_4': 4} | {'all_eq_0': 'all_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', '4th place_3': '4th place', '0_4': '0'} | {'all_eq_0': [1], 'result_1': [], 'all_rows_2': [0], '4th place_3': [0], '0_4': [0]} | ['', 'nation', 'winners', 'runners - up', '3rd place', '4th place'] | [['1', 'kingfisher east bengal fc', '1', '0', '0', '0'], ['2', 'tampines rovers fc', '1', '0', '0', '0'], ['3', 'bec tero sasana', '0', '1', '0', '0'], ['4', 'pahang fa', '0', '1', '0', '0'], ['5', 'dpmm fc ( duli pengiran muda mahkota fc )', '0', '0', '1', '0'], ['6', 'hoang anh gia lai', '0', '0', '1', '0'], ['7', 'petrokimia putra fc', '0', '0', '1', '0']] |
list of sports teams in nebraska | https://en.wikipedia.org/wiki/List_of_sports_teams_in_Nebraska | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-14115168-4.html.csv | comparative | doane college was founded earlier than college of saint mary . | {'row_1': '4', 'row_2': '2', 'col': '5', 'col_other': '1', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'school', 'doane college'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose school record fuzzily matches to doane college .', 'tostr': 'filter_eq { all_rows ; school ; doane college }'}, 'founded'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; school ; doane college } ; founded }', 'tointer': 'select the rows whose school record fuzzily matches to doane college . take the founded record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'school', 'college of saint mary'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose school record fuzzily matches to college of saint mary .', 'tostr': 'filter_eq { all_rows ; school ; college of saint mary }'}, 'founded'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; school ; college of saint mary } ; founded }', 'tointer': 'select the rows whose school record fuzzily matches to college of saint mary . take the founded record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; school ; doane college } ; founded } ; hop { filter_eq { all_rows ; school ; college of saint mary } ; founded } } = true', 'tointer': 'select the rows whose school record fuzzily matches to doane college . take the founded record of this row . select the rows whose school record fuzzily matches to college of saint mary . take the founded record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; school ; doane college } ; founded } ; hop { filter_eq { all_rows ; school ; college of saint mary } ; founded } } = true | select the rows whose school record fuzzily matches to doane college . take the founded record of this row . select the rows whose school record fuzzily matches to college of saint mary . take the founded 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, 'school_7': 7, 'doane college_8': 8, 'founded_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'school_11': 11, 'college of saint mary_12': 12, 'founded_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', 'school_7': 'school', 'doane college_8': 'doane college', 'founded_9': 'founded', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'school_11': 'school', 'college of saint mary_12': 'college of saint mary', 'founded_13': 'founded'} | {'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'school_7': [0], 'doane college_8': [0], 'founded_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'school_11': [1], 'college of saint mary_12': [1], 'founded_13': [3]} | ['school', 'mascot', 'conference', 'national titles', 'founded'] | [['bellevue university', 'bellevue bruins', 'midlands', '14', '1966'], ['college of saint mary', 'saint mary flames', 'midlands', '0', '1923'], ['concordia university', 'concordia bulldogs', 'great plains', '1', '1894'], ['doane college', 'doane tigers', 'great plains', '10', '1872'], ['hastings college', 'hastings broncos', 'great plains', '3', '1882'], ['midland university', 'midland warriors', 'great plains', '2', '1883'], ['nebraska wesleyan university', 'nw prairie wolves', 'great plains', '19', '1887'], ['peru state college', 'peru state bobcats', 'midlands', '2', '1865']] |
hisar ( lok sabha constituency ) | https://en.wikipedia.org/wiki/Hisar_%28Lok_Sabha_constituency%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17922483-1.html.csv | majority | the majority of hisar 's constituencies are located in the hisar district . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'hisar', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'district', 'hisar'], 'result': True, 'ind': 0, 'tointer': 'for the district records of all rows , most of them fuzzily match to hisar .', 'tostr': 'most_eq { all_rows ; district ; hisar } = true'} | most_eq { all_rows ; district ; hisar } = true | for the district records of all rows , most of them fuzzily match to hisar . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'district_3': 3, 'hisar_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'district_3': 'district', 'hisar_4': 'hisar'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'district_3': [0], 'hisar_4': [0]} | ['constituency number', 'name', 'reserved for ( sc / st / none )', 'district', 'number of electorates ( 2009 )'] | [['37', 'uchana kalan', 'none', 'jind', '154284'], ['47', 'adampur', 'none', 'hisar', '123558'], ['48', 'uklana', 'sc', 'hisar', '147491'], ['49', 'narnaund', 'none', 'hisar', '152958'], ['50', 'hansi', 'none', 'hisar', '133581'], ['51', 'barwala', 'none', 'hisar', '119790'], ['52', 'hisar', 'none', 'hisar', '101595'], ['53', 'nalwa', 'none', 'hisar', '115472'], ['59', 'bawani khera', 'sc', 'bhiwani', '145965'], ['total :', 'total :', 'total :', 'total :', '1194694']] |
1925 vfl season | https://en.wikipedia.org/wiki/1925_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10746200-17.html.csv | ordinal | brunswick street oval venue recorded the highest crowd participation during the 1925 vfl season . | {'row': '6', 'col': '6', 'order': '1', 'col_other': '5', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'crowd', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; crowd ; 1 }'}, 'venue'], 'result': 'brunswick street oval', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; crowd ; 1 } ; venue }'}, 'brunswick street oval'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; crowd ; 1 } ; venue } ; brunswick street oval } = true', 'tointer': 'select the row whose crowd record of all rows is 1st maximum . the venue record of this row is brunswick street oval .'} | eq { hop { nth_argmax { all_rows ; crowd ; 1 } ; venue } ; brunswick street oval } = true | select the row whose crowd record of all rows is 1st maximum . the venue record of this row is brunswick street oval . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'crowd_5': 5, '1_6': 6, 'venue_7': 7, 'brunswick street oval_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'crowd_5': 'crowd', '1_6': '1', 'venue_7': 'venue', 'brunswick street oval_8': 'brunswick street oval'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'crowd_5': [0], '1_6': [0], 'venue_7': [1], 'brunswick street oval_8': [2]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['melbourne', '9.9 ( 63 )', 'richmond', '2.12 ( 24 )', 'mcg', '16989', '12 september 1925'], ['hawthorn', '7.13 ( 55 )', 'north melbourne', '4.6 ( 30 )', 'glenferrie oval', '8000', '12 september 1925'], ['essendon', '10.7 ( 67 )', 'st kilda', '8.10 ( 58 )', 'windy hill', '15000', '12 september 1925'], ['geelong', '14.16 ( 100 )', 'footscray', '9.7 ( 61 )', 'corio oval', '10800', '12 september 1925'], ['south melbourne', '4.6 ( 30 )', 'collingwood', '14.11 ( 95 )', 'lake oval', '12000', '12 september 1925'], ['fitzroy', '7.24 ( 66 )', 'carlton', '9.10 ( 64 )', 'brunswick street oval', '20000', '12 september 1925']] |
cbo - fm | https://en.wikipedia.org/wiki/CBO-FM | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1585163-1.html.csv | comparative | the station in kingston uses a higher frequency than the one in pembroke . | {'row_1': '4', 'row_2': '6', 'col': '3', 'col_other': '1', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'city of license', 'kingston'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose city of license record fuzzily matches to kingston .', 'tostr': 'filter_eq { all_rows ; city of license ; kingston }'}, 'frequency'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; city of license ; kingston } ; frequency }', 'tointer': 'select the rows whose city of license record fuzzily matches to kingston . take the frequency record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'city of license', 'pembroke'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose city of license record fuzzily matches to pembroke .', 'tostr': 'filter_eq { all_rows ; city of license ; pembroke }'}, 'frequency'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; city of license ; pembroke } ; frequency }', 'tointer': 'select the rows whose city of license record fuzzily matches to pembroke . take the frequency record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; city of license ; kingston } ; frequency } ; hop { filter_eq { all_rows ; city of license ; pembroke } ; frequency } } = true', 'tointer': 'select the rows whose city of license record fuzzily matches to kingston . take the frequency record of this row . select the rows whose city of license record fuzzily matches to pembroke . take the frequency record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; city of license ; kingston } ; frequency } ; hop { filter_eq { all_rows ; city of license ; pembroke } ; frequency } } = true | select the rows whose city of license record fuzzily matches to kingston . take the frequency record of this row . select the rows whose city of license record fuzzily matches to pembroke . take the frequency record of this row . the first record is greater than the second record . | 5 | 5 | {'greater_4': 4, 'result_5': 5, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'city of license_7': 7, 'kingston_8': 8, 'frequency_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'city of license_11': 11, 'pembroke_12': 12, 'frequency_13': 13} | {'greater_4': 'greater', 'result_5': 'true', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'city of license_7': 'city of license', 'kingston_8': 'kingston', 'frequency_9': 'frequency', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'city of license_11': 'city of license', 'pembroke_12': 'pembroke', 'frequency_13': 'frequency'} | {'greater_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'city of license_7': [0], 'kingston_8': [0], 'frequency_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'city of license_11': [1], 'pembroke_12': [1], 'frequency_13': [3]} | ['city of license', 'identifier', 'frequency', 'power', 'class', 'recnet'] | [['brockville', 'cbob - fm', '91.9 fm', '1080 s watt', 'a', 'query'], ['cornwall', 'cboc - fm', '95.5 fm', '3000 watts', 'a', 'query'], ['deep river', 'cbli', '1110 am', '40 watts', 'lp', 'query'], ['kingston', 'cbck - fm', '107.5 fm', '100000 watts', 'c1', 'query'], ['maniwaki , quebec', 'cbom', '710 am', '40 watts', 'lp', 'query'], ['pembroke', 'cbcd - fm', '92.5 fm', '100000 watts', 'c1', 'query'], ['whitney', 'cbcw - fm', '98.5 fm', '162 watts', 'a1', 'query']] |
ireland in the eurovision song contest 1989 | https://en.wikipedia.org/wiki/Ireland_in_the_Eurovision_Song_Contest_1989 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16956150-1.html.csv | superlative | for irish singers in the 1989 eurovision song contest , the performer with the highest number of points is kiev connolly & the missing passengers . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '3', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'points'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; points }'}, 'performer'], 'result': 'kiev connolly & the missing passengers', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; points } ; performer }'}, 'kiev connolly & the missing passengers'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; points } ; performer } ; kiev connolly & the missing passengers } = true', 'tointer': 'select the row whose points record of all rows is maximum . the performer record of this row is kiev connolly & the missing passengers .'} | eq { hop { argmax { all_rows ; points } ; performer } ; kiev connolly & the missing passengers } = true | select the row whose points record of all rows is maximum . the performer record of this row is kiev connolly & the missing passengers . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'points_5': 5, 'performer_6': 6, 'kiev connolly & the missing passengers_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'points_5': 'points', 'performer_6': 'performer', 'kiev connolly & the missing passengers_7': 'kiev connolly & the missing passengers'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'points_5': [0], 'performer_6': [1], 'kiev connolly & the missing passengers_7': [2]} | ['draw', 'song', 'performer', 'points', 'rank'] | [['1', 'the real me', 'kiev connolly & the missing passengers', '104', '1st'], ['2', 'easy', 'honor heffernan', '97', '2nd'], ['3', "this is n't war ( it 's revolution )", 'nicola kerr', '79', '3rd'], ['4', 'uaigneach', 'barry ronan', '48', '8th'], ['5', 'here we go', 'linda martin', '71', '6th'], ['6', 'angel eyes', 'jenny newman', '77', '5th'], ['7', 'song for you', 'dave lalor', '68', '7th'], ['8', 'it was meant to be', 'noelle', '79', '3rd']] |
1986 - 87 segunda división | https://en.wikipedia.org/wiki/1986%E2%80%9387_Segunda_Divisi%C3%B3n | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12109851-2.html.csv | ordinal | the club castilla cf had the second largest number of losses in the 1986 - 87 segunda división . | {'row': '17', 'col': '7', 'order': '2', 'col_other': '2', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'losses', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; losses ; 2 }'}, 'club'], 'result': 'castilla cf', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; losses ; 2 } ; club }'}, 'castilla cf'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; losses ; 2 } ; club } ; castilla cf } = true', 'tointer': 'select the row whose losses record of all rows is 2nd maximum . the club record of this row is castilla cf .'} | eq { hop { nth_argmax { all_rows ; losses ; 2 } ; club } ; castilla cf } = true | select the row whose losses record of all rows is 2nd maximum . the club record of this row is castilla cf . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'losses_5': 5, '2_6': 6, 'club_7': 7, 'castilla cf_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', 'losses_5': 'losses', '2_6': '2', 'club_7': 'club', 'castilla cf_8': 'castilla cf'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'losses_5': [0], '2_6': [0], 'club_7': [1], 'castilla cf_8': [2]} | ['position', 'club', 'played', 'points', 'wins', 'draws', 'losses', 'goals for', 'goals against', 'goal difference'] | [['1', 'valencia cf', '34', '46 + 12', '19', '8', '7', '53', '26', '+ 27'], ['2', 'deportivo de la coruña', '34', '43 + 9', '16', '11', '7', '46', '33', '+ 13'], ['3', 'cd logroñés', '34', '41 + 7', '16', '9', '9', '46', '33', '+ 13'], ['4', 'celta de vigo', '34', '40 + 6', '17', '6', '11', '56', '35', '+ 21'], ['5', 'recreativo de huelva', '34', '39 + 5', '18', '3', '13', '53', '44', '+ 9'], ['6', 'sestao', '34', '38 + 4', '13', '12', '9', '38', '23', '+ 15'], ['7', 'elche cf', '34', '36 + 2', '12', '12', '10', '31', '28', '+ 3'], ['8', 'rayo vallecano', '34', '35 + 1', '10', '15', '9', '28', '28', '0'], ['9', 'bilbao athletic', '34', '35 + 1', '12', '11', '11', '51', '54', '- 3'], ['10', 'cd castellón', '34', '34', '13', '8', '13', '38', '42', '- 4'], ['11', 'hércules cf', '34', '32 - 2', '12', '8', '14', '38', '43', '- 5'], ['12', 'cd málaga', '34', '32 - 2', '10', '12', '12', '43', '39', '+ 4'], ['13', 'barcelona atlètic', '34', '32 - 2', '11', '10', '13', '42', '46', '- 4'], ['14', 'real oviedo', '34', '30 - 4', '9', '12', '13', '33', '46', '- 13'], ['15', 'ue figueres', '34', '29 - 5', '9', '11', '14', '39', '40', '- 1'], ['16', 'cartagena fc', '34', '27 - 7', '7', '13', '14', '34', '51', '- 17'], ['17', 'castilla cf', '34', '24 - 10', '7', '10', '17', '30', '51', '- 21'], ['18', 'jerez deportivo', '34', '19 - 15', '4', '11', '19', '21', '58', '- 37']] |
brazil national football team | https://en.wikipedia.org/wiki/Brazil_national_football_team | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-149286-9.html.csv | count | for the brazil national football team , when the caps were under 100 , there were 2 times that there were 3 goals . | {'scope': 'subset', 'criterion': 'equal', 'value': '3', 'result': '2', 'col': '3', 'subset': {'col': '2', 'criterion': 'less_than', 'value': '100'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'caps', '100'], 'result': None, 'ind': 0, 'tostr': 'filter_less { all_rows ; caps ; 100 }', 'tointer': 'select the rows whose caps record is less than 100 .'}, 'goals', '3'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose caps record is less than 100 . among these rows , select the rows whose goals record is equal to 3 .', 'tostr': 'filter_eq { filter_less { all_rows ; caps ; 100 } ; goals ; 3 }'}], 'result': '2', 'ind': 2, 'tostr': 'count { filter_eq { filter_less { all_rows ; caps ; 100 } ; goals ; 3 } }', 'tointer': 'select the rows whose caps record is less than 100 . among these rows , select the rows whose goals record is equal to 3 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_eq { filter_less { all_rows ; caps ; 100 } ; goals ; 3 } } ; 2 } = true', 'tointer': 'select the rows whose caps record is less than 100 . among these rows , select the rows whose goals record is equal to 3 . the number of such rows is 2 .'} | eq { count { filter_eq { filter_less { all_rows ; caps ; 100 } ; goals ; 3 } } ; 2 } = true | select the rows whose caps record is less than 100 . among these rows , select the rows whose goals record is equal to 3 . the number of such rows is 2 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_eq_1': 1, 'filter_less_0': 0, 'all_rows_5': 5, 'caps_6': 6, '100_7': 7, 'goals_8': 8, '3_9': 9, '2_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_eq_1': 'filter_eq', 'filter_less_0': 'filter_less', 'all_rows_5': 'all_rows', 'caps_6': 'caps', '100_7': '100', 'goals_8': 'goals', '3_9': '3', '2_10': '2'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_eq_1': [2], 'filter_less_0': [1], 'all_rows_5': [0], 'caps_6': [0], '100_7': [0], 'goals_8': [1], '3_9': [1], '2_10': [3]} | ['name', 'caps', 'goals', 'first cap', 'latest cap'] | [['cafu', '142', '5', 'september 12 , 1990', 'july 1 , 2006'], ['roberto carlos', '125', '11', 'february 26 , 1992', 'july 1 , 2006'], ['lúcio', '105', '4', 'november 15 , 2000', 'september 5 , 2011'], ['cláudio taffarel', '101', '0', 'july 7 , 1988', 'july 12 , 1998'], ['djalma santos', '98', '3', 'april 10 , 1952', 'june 9 , 1968'], ['ronaldo', '98', '62', 'march 23 , 1994', 'june 7 , 2011'], ['ronaldinho', '97', '33', 'june 26 , 1999', 'april 24 , 2013'], ['gilmar', '94', '0', 'march 1 , 1953', 'june 12 , 1969'], ['gilberto silva', '93', '3', 'november 7 , 2001', 'july 2 , 2010'], ['pelé', '92', '77', 'july 7 , 1957', 'july 18 , 1971'], ['rivelino', '92', '26', 'november 16 , 1965', 'june 24 , 1978']] |
fiba eurobasket 2007 squads | https://en.wikipedia.org/wiki/FIBA_EuroBasket_2007_squads | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12962773-8.html.csv | count | there are a total of three players that were born in the year 1978 who held a center position in the 2007 fiba eurobasket squads . | {'scope': 'subset', 'criterion': 'equal', 'value': '1978', 'result': '3', 'col': '4', 'subset': {'col': '4', 'criterion': 'equal', 'value': '1978'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'year born', '1978'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; year born ; 1978 }', 'tointer': 'select the rows whose year born record is equal to 1978 .'}, 'year born', '1978'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose year born record is equal to 1978 . among these rows , select the rows whose year born record is equal to 1978 .', 'tostr': 'filter_eq { filter_eq { all_rows ; year born ; 1978 } ; year born ; 1978 }'}], 'result': '3', 'ind': 2, 'tostr': 'count { filter_eq { filter_eq { all_rows ; year born ; 1978 } ; year born ; 1978 } }', 'tointer': 'select the rows whose year born record is equal to 1978 . among these rows , select the rows whose year born record is equal to 1978 . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_eq { filter_eq { all_rows ; year born ; 1978 } ; year born ; 1978 } } ; 3 } = true', 'tointer': 'select the rows whose year born record is equal to 1978 . among these rows , select the rows whose year born record is equal to 1978 . the number of such rows is 3 .'} | eq { count { filter_eq { filter_eq { all_rows ; year born ; 1978 } ; year born ; 1978 } } ; 3 } = true | select the rows whose year born record is equal to 1978 . among these rows , select the rows whose year born record is equal to 1978 . the number of such rows is 3 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_eq_1': 1, 'filter_eq_0': 0, 'all_rows_5': 5, 'year born_6': 6, '1978_7': 7, 'year born_8': 8, '1978_9': 9, '3_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', 'year born_6': 'year born', '1978_7': '1978', 'year born_8': 'year born', '1978_9': '1978', '3_10': '3'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_eq_1': [2], 'filter_eq_0': [1], 'all_rows_5': [0], 'year born_6': [0], '1978_7': [0], 'year born_8': [1], '1978_9': [1], '3_10': [3]} | ['player', 'height', 'position', 'year born', 'current club'] | [['miguel minhava', '1 , 97', 'guard', '1983', "cb l'hospitalet"], ['mário gil fernandes', '1 , 74', 'guard', '1982', 'cb plasencia'], ['sérgio ramos', '2 , 00', 'forward', '1975', 'drac inca'], ['paulo cunha', '1 , 99', 'forward', '1980', 'fc porto'], ['francisco jordão', '2 , 00', 'center', '1979', '1 de agosto'], ['filipe da silva', '1 , 93', 'guard', '1979', 'cb villa de los barrios'], ['joão betinho gomes', '1 , 99', 'forward', '1985', 'fc barreirense'], ['jorge coelho', '2 , 00', 'center', '1978', 'cb palencia'], ['paulo simão', '1 , 98', 'forward', '1976', 'cf belenenses'], ['elvis évora', '2 , 05', 'center', '1978', 'ovarense aerosoles'], ['miguel miranda', '2 , 05', 'center', '1978', 'ovarense aerosoles'], ['joão santos', '2 , 03', 'forward', '1979', 'grupo capitol valladolid']] |
emergency shipbuilding program | https://en.wikipedia.org/wiki/Emergency_Shipbuilding_program | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11552751-4.html.csv | unique | the great lakes engineering co shipbuilding yard is the only yard in the state of michigan . | {'scope': 'all', 'row': '8', 'col': '2', 'col_other': '1', 'criterion': 'equal', 'value': 'michigan', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location ( city , state )', 'michigan'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose location ( city , state ) record fuzzily matches to michigan .', 'tostr': 'filter_eq { all_rows ; location ( city , state ) ; michigan }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; location ( city , state ) ; michigan } }', 'tointer': 'select the rows whose location ( city , state ) record fuzzily matches to michigan . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location ( city , state )', 'michigan'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose location ( city , state ) record fuzzily matches to michigan .', 'tostr': 'filter_eq { all_rows ; location ( city , state ) ; michigan }'}, 'yard name'], 'result': 'great lakes engineering co', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; location ( city , state ) ; michigan } ; yard name }'}, 'great lakes engineering co'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; location ( city , state ) ; michigan } ; yard name } ; great lakes engineering co }', 'tointer': 'the yard name record of this unqiue row is great lakes engineering co .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; location ( city , state ) ; michigan } } ; eq { hop { filter_eq { all_rows ; location ( city , state ) ; michigan } ; yard name } ; great lakes engineering co } } = true', 'tointer': 'select the rows whose location ( city , state ) record fuzzily matches to michigan . there is only one such row in the table . the yard name record of this unqiue row is great lakes engineering co .'} | and { only { filter_eq { all_rows ; location ( city , state ) ; michigan } } ; eq { hop { filter_eq { all_rows ; location ( city , state ) ; michigan } ; yard name } ; great lakes engineering co } } = true | select the rows whose location ( city , state ) record fuzzily matches to michigan . there is only one such row in the table . the yard name record of this unqiue row is great lakes engineering co . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'location (city , state)_7': 7, 'michigan_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'yard name_9': 9, 'great lakes engineering co_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'location (city , state)_7': 'location ( city , state )', 'michigan_8': 'michigan', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'yard name_9': 'yard name', 'great lakes engineering co_10': 'great lakes engineering co'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'location (city , state)_7': [0], 'michigan_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'yard name_9': [2], 'great lakes engineering co_10': [3]} | ['yard name', 'location ( city , state )', '1st ship delivery date', 'ship types delivered', 'total number of ways'] | [['cargill inc', 'savage , minnesota', 'november 1941', 't1 type', 'number'], ['leatham d smith shipbuilding co', 'sturgeon bay , wisconsin', 'november 1942', 'c1 - m type , n3 type , s2 ( frigate ) type', 'number'], ['walter butler shipbuilders', 'superior , wisconsin', 'december 1942', 'c1 - m type , n3 type , s2 ( frigate ) type', 'number'], ['froemming brothers', 'milwaukee , wisconsin', 'april 1943', 'c1 - m type , v4 type , s2 ( frigate ) type', 'number'], ['american shipbuilding', 'lorain , ohio', 'may 1943', 'l6 type , s2 ( frigate ) type', 'number'], ['walter butler shipbuilders inc', 'duluth , minnesota', 'may 1943', 'c1 - m type , n3 type , t1 type', 'number'], ['globe shipbuilding co', 'superior , wisconsin', 'may 1943', 'c1 - m type , v4 type , s2 ( frigate ) type', 'number'], ['great lakes engineering co', 'ecorse , michigan', 'may 1943', 'l6 type', 'number'], ['great lakes engineering co', 'ashtabula , ohio', 'may 1943', 'l6 type', 'number'], ['american shipbuilding', 'cleveland , ohio', 'june 1943', 'l6 type , s2 ( frigate ) type', 'number']] |
81st united states congress | https://en.wikipedia.org/wiki/81st_United_States_Congress | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1694492-2.html.csv | count | a total of four vacated seats were not filled for the remainder of the term . | {'scope': 'all', 'criterion': 'equal', 'value': 'vacant', 'result': '4', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'successor', 'vacant'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose successor record fuzzily matches to vacant .', 'tostr': 'filter_eq { all_rows ; successor ; vacant }'}], 'result': '4', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; successor ; vacant } }', 'tointer': 'select the rows whose successor record fuzzily matches to vacant . the number of such rows is 4 .'}, '4'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; successor ; vacant } } ; 4 } = true', 'tointer': 'select the rows whose successor record fuzzily matches to vacant . the number of such rows is 4 .'} | eq { count { filter_eq { all_rows ; successor ; vacant } } ; 4 } = true | select the rows whose successor record fuzzily matches to vacant . 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, 'successor_5': 5, 'vacant_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', 'successor_5': 'successor', 'vacant_6': 'vacant', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'successor_5': [0], 'vacant_6': [0], '4_7': [2]} | ['district', 'vacator', 'reason for change', 'successor', 'date successor seated'] | [['new york 7th', 'vacant', 'rep john j delaney died during previous congress', 'louis b heller ( d )', 'february 15 , 1949'], ['new york 20th', 'sol bloom ( d )', 'died march 7 , 1949', 'franklin delano roosevelt , jr ( lib )', 'may 17 , 1949'], ['new york 10th', 'andrew l somers ( d )', 'died april 6 , 1949', 'edna f kelly ( d )', 'november 8 , 1949'], ['pennsylvania 26th', 'robert l coffey ( d )', 'died april 20 , 1949', 'john p saylor ( r )', 'september 13 , 1949'], ['california 5th', 'richard j welch ( r )', 'died september 10 , 1949', 'john shelley ( d )', 'november 8 , 1949'], ['massachusetts 6th', 'george j bates ( r )', 'died november 1 , 1949', 'william h bates ( r )', 'february 14 , 1950'], ['illinois 5th', 'martin gorski ( d )', 'died december 4 , 1949', 'vacant', 'not filled for the remainder of this term'], ['virginia 1st', 's otis bland ( d )', 'died february 16 , 1950', 'edward j robeson , jr ( d )', 'may 2 , 1950'], ['illinois 13th', 'ralph e church ( r )', 'died march 21 , 1950', 'vacant', 'not filled for the remainder of this term'], ['michigan 16th', 'john lesinski , sr ( d )', 'died may 27 , 1950', 'vacant', 'not filled for the remainder of this term'], ['north dakota at - large', 'william lemke ( r )', 'died may 30 , 1950', 'vacant', 'not filled for the remainder of this term'], ['north carolina 11th', 'alfred l bulwinkle ( d )', 'died august 31 , 1950', 'woodrow w jones ( d )', 'november 7 , 1950']] |
wang shi - ting | https://en.wikipedia.org/wiki/Wang_Shi-ting | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15340120-1.html.csv | count | a total of two tournaments that wang shi - ting played in were located in taipei , taiwan . | {'scope': 'all', 'criterion': 'equal', 'value': 'taipei , taiwan', 'result': '2', 'col': '2', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'tournament', 'taipei , taiwan'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose tournament record fuzzily matches to taipei , taiwan .', 'tostr': 'filter_eq { all_rows ; tournament ; taipei , taiwan }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; tournament ; taipei , taiwan } }', 'tointer': 'select the rows whose tournament record fuzzily matches to taipei , taiwan . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; tournament ; taipei , taiwan } } ; 2 } = true', 'tointer': 'select the rows whose tournament record fuzzily matches to taipei , taiwan . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; tournament ; taipei , taiwan } } ; 2 } = true | select the rows whose tournament record fuzzily matches to taipei , taiwan . 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, 'tournament_5': 5, 'taipei, taiwan_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', 'tournament_5': 'tournament', 'taipei, taiwan_6': 'taipei , taiwan', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'tournament_5': [0], 'taipei, taiwan_6': [0], '2_7': [2]} | ['date', 'tournament', 'surface', 'opponent in the final', 'score'] | [['september 13 , 1993', 'hong kong', 'hard', 'marianne witmeyer', '6 - 4 , 3 - 6 , 7 - 5'], ['october 4 , 1993', 'taipei , taiwan', 'hard', 'linda wild', '6 - 1 , 7 - 6 ( 4 )'], ['november 14 , 1994', 'taipei , taiwan', 'hard', 'kyoko nagatsuka', '6 - 1 , 6 - 3'], ['october 2 , 1995', 'surabaya , indonesia', 'hard', 'yi jingqian', '6 - 1 , 6 - 1'], ['october 7 , 1996', 'surabaya , indonesia', 'hard', 'nana miyagi', '6 - 4 , 6 - 0'], ['october 14 , 1996', 'beijing , china', 'hard ( i )', 'chen li', '6 - 3 , 6 - 4']] |
eurovision song contest 1966 | https://en.wikipedia.org/wiki/Eurovision_Song_Contest_1966 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-184807-1.html.csv | unique | in the eurovision song contest in 1966 , when the language was french , the only time there were 14 points was when the artist was tonia . | {'scope': 'subset', 'row': '3', 'col': '7', 'col_other': '3', 'criterion': 'equal', 'value': '14', 'subset': {'col': '2', 'criterion': 'equal', 'value': 'french'}} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'language', 'french'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; language ; french }', 'tointer': 'select the rows whose language record fuzzily matches to french .'}, 'points', '14'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose language record fuzzily matches to french . among these rows , select the rows whose points record is equal to 14 .', 'tostr': 'filter_eq { filter_eq { all_rows ; language ; french } ; points ; 14 }'}], 'result': True, 'ind': 2, 'tostr': 'only { filter_eq { filter_eq { all_rows ; language ; french } ; points ; 14 } }', 'tointer': 'select the rows whose language record fuzzily matches to french . among these rows , select the rows whose points record is equal to 14 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'language', 'french'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; language ; french }', 'tointer': 'select the rows whose language record fuzzily matches to french .'}, 'points', '14'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose language record fuzzily matches to french . among these rows , select the rows whose points record is equal to 14 .', 'tostr': 'filter_eq { filter_eq { all_rows ; language ; french } ; points ; 14 }'}, 'artist'], 'result': 'tonia', 'ind': 3, 'tostr': 'hop { filter_eq { filter_eq { all_rows ; language ; french } ; points ; 14 } ; artist }'}, 'tonia'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { filter_eq { filter_eq { all_rows ; language ; french } ; points ; 14 } ; artist } ; tonia }', 'tointer': 'the artist record of this unqiue row is tonia .'}], 'result': True, 'ind': 5, 'tostr': 'and { only { filter_eq { filter_eq { all_rows ; language ; french } ; points ; 14 } } ; eq { hop { filter_eq { filter_eq { all_rows ; language ; french } ; points ; 14 } ; artist } ; tonia } } = true', 'tointer': 'select the rows whose language record fuzzily matches to french . among these rows , select the rows whose points record is equal to 14 . there is only one such row in the table . the artist record of this unqiue row is tonia .'} | and { only { filter_eq { filter_eq { all_rows ; language ; french } ; points ; 14 } } ; eq { hop { filter_eq { filter_eq { all_rows ; language ; french } ; points ; 14 } ; artist } ; tonia } } = true | select the rows whose language record fuzzily matches to french . among these rows , select the rows whose points record is equal to 14 . there is only one such row in the table . the artist record of this unqiue row is tonia . | 8 | 6 | {'and_5': 5, 'result_6': 6, 'only_2': 2, 'filter_eq_1': 1, 'filter_str_eq_0': 0, 'all_rows_7': 7, 'language_8': 8, 'french_9': 9, 'points_10': 10, '14_11': 11, 'str_eq_4': 4, 'str_hop_3': 3, 'artist_12': 12, 'tonia_13': 13} | {'and_5': 'and', 'result_6': 'true', 'only_2': 'only', 'filter_eq_1': 'filter_eq', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_7': 'all_rows', 'language_8': 'language', 'french_9': 'french', 'points_10': 'points', '14_11': '14', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'artist_12': 'artist', 'tonia_13': 'tonia'} | {'and_5': [6], 'result_6': [], 'only_2': [5], 'filter_eq_1': [2, 3], 'filter_str_eq_0': [1], 'all_rows_7': [0], 'language_8': [0], 'french_9': [0], 'points_10': [1], '14_11': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'artist_12': [3], 'tonia_13': [4]} | ['draw', 'language', 'artist', 'song', 'english translation', 'place', 'points'] | [['01', 'german', 'margot eskens', 'die zeiger der uhr', 'the hands of the clock', '10', '7'], ['02', 'danish', 'ulla pia', "stop - mens legen er go '", "stop while the going 's good", '14', '4'], ['03', 'french', 'tonia', 'un peu de poivre , un peu de sel', 'a bit of pepper , a bit of salt', '4', '14'], ['04', 'french', 'michèle torr', "ce soir je t ' attendais", 'tonight , i waited for you', '10', '7'], ['05', 'slovene', 'berta ambrož', 'brez besed', 'without words', '7', '9'], ['06', 'norwegian', 'åse kleveland', 'intet er nytt under solen', 'nothing is new under the sun', '3', '15'], ['07', 'finnish', 'ann christine', 'playboy', '-', '10', '7'], ['08', 'portuguese', 'madalena iglésias', 'ele e ela', 'he and she', '13', '6'], ['09', 'german', 'udo jürgens', 'merci , chérie', 'thank you , darling', '1', '31'], ['10', 'swedish', 'lill lindfors & svante thuresson', 'nygammal vals', 'new , yet familiar , waltz', '2', '16'], ['11', 'spanish', 'raphael', 'yo soy aquél', "i 'm that one", '7', '9'], ['12', 'french', 'madeleine pascal', 'ne vois - tu pas', "do n't you see", '6', '12'], ['13', 'french', 'tereza kesovija', 'bien plus fort', 'altogether stronger', '17', '0'], ['14', 'italian', 'domenico modugno', 'dio , come ti amo', 'god , how i love you', '17', '0'], ['15', 'french', 'dominique walter', 'chez nous', 'our place', '16', '1'], ['16', 'dutch', 'milly scott', 'fernando en filippo', 'fernando and filippo', '15', '2'], ['17', 'english', 'dickie rock', 'come back to stay', '-', '4', '14'], ['18', 'english', 'kenneth mckellar', 'a man without love', '-', '9', '8']] |
united states house of representatives elections , 1954 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1954 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1342013-12.html.csv | majority | the majority of incumbents in the united states house of representatives elections of 1954 from illinois were with the republican party . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'republican', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'party', 'republican'], 'result': True, 'ind': 0, 'tointer': 'for the party records of all rows , most of them fuzzily match to republican .', 'tostr': 'most_eq { all_rows ; party ; republican } = true'} | most_eq { all_rows ; party ; republican } = true | for the party records of all rows , most of them fuzzily match to republican . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'party_3': 3, 'republican_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'party_3': 'party', 'republican_4': 'republican'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'party_3': [0], 'republican_4': [0]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['illinois 2', "barratt o'hara", 'democratic', '1952', 're - elected', "barratt o'hara ( d ) 61.6 % richard b vail ( r ) 38.4 %"], ['illinois 3', 'fred e busbey', 'republican', '1950', 'lost re - election democratic gain', 'james c murray ( d ) 53.8 % fred e busbey ( r ) 46.2 %'], ['illinois 14', 'chauncey w reed', 'republican', '1934', 're - elected', 'chauncey w reed ( r ) 72.4 % richard plum ( d ) 27.6 %'], ['illinois 15', 'noah m mason', 'republican', '1936', 're - elected', 'noah m mason ( r ) 62.8 % richard a mohan ( d ) 37.2 %'], ['illinois 16', 'leo e allen', 'republican', '1932', 're - elected', 'leo e allen ( r ) unopposed'], ['illinois 20', 'sid simpson', 'republican', '1942', 're - elected', 'sid simpson ( r ) 62.9 % james a barry ( d ) 37.1 %'], ['illinois 24', 'melvin price', 'democratic', '1944', 're - elected', 'melvin price ( d ) 69.2 % john t thomas ( r ) 30.8 %']] |
american dad ! ( season 7 ) | https://en.wikipedia.org/wiki/American_Dad%21_%28season_7%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-26409328-1.html.csv | superlative | the episode of american dad ! in season 7 that had the highest number of viewers is the one that aired on november 7 , 2010 . | {'scope': 'all', 'col_superlative': '8', 'row_superlative': '3', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '6', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'us viewers ( millions )'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; us viewers ( millions ) }'}, 'original air date'], 'result': 'november 7 , 2010', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; us viewers ( millions ) } ; original air date }'}, 'november 7 , 2010'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; us viewers ( millions ) } ; original air date } ; november 7 , 2010 } = true', 'tointer': 'select the row whose us viewers ( millions ) record of all rows is maximum . the original air date record of this row is november 7 , 2010 .'} | eq { hop { argmax { all_rows ; us viewers ( millions ) } ; original air date } ; november 7 , 2010 } = true | select the row whose us viewers ( millions ) record of all rows is maximum . the original air date record of this row is november 7 , 2010 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'us viewers (millions)_5': 5, 'original air date_6': 6, 'november 7 , 2010_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'us viewers (millions)_5': 'us viewers ( millions )', 'original air date_6': 'original air date', 'november 7 , 2010_7': 'november 7 , 2010'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'us viewers (millions)_5': [0], 'original air date_6': [1], 'november 7 , 2010_7': [2]} | ['no in series', 'no in season', 'title', 'directed by', 'written by', 'original air date', 'production code', 'us viewers ( millions )'] | [['97', '1', '100 ad ( part 1 )', 'tim parsons', 'keith heisler', 'october 3 , 2010', '5ajn14', '6.16'], ['98', '2', 'son of stan ( part 2 )', 'chris bennett', 'erik sommers', 'october 10 , 2010', '5ajn17', '5.36'], ['99', '3', 'best little horror house in langley falls', 'john aoshima & jansen yee', 'eric weinberg', 'november 7 , 2010', '5ajn19', '6.30'], ['100', '4', "stan 's food restaurant", 'josue cervantes', 'brian boyle', 'november 14 , 2010', '5ajn16', '5.38'], ['101', '5', 'white rice', 'bob bowen', 'rick wiener & kenny schwartz', 'november 21 , 2010', '5ajn15', '4.86'], ['102', '6', 'there will be bad blood', 'joe daniello', 'murray miller & judah miller', 'november 28 , 2010', '5ajn20', '6.13'], ['103', '7', 'the people vs martin sugar', 'pam cooke', 'jonathan fener', 'december 5 , 2010', '5ajn05', '5.31'], ['104', '8', 'for whom the sleigh bell tolls', 'bob bowen', 'erik durbin', 'december 12 , 2010', '5ajn22', '6.22'], ['105', '9', 'fart - break hotel', 'rodney clouden', 'chris mckenna & matt mckenna', 'january 16 , 2011', '5ajn18', '3.54'], ['106', '10', 'stanny boy and frantastic', 'pam cooke', 'laura mccreary', 'january 23 , 2011', '5ajn13', '4.81'], ['107', '11', 'a piã ± ata named desire', 'bob bowen', 'chris mckenna & matt mckenna', 'february 13 , 2011', '5ajn07', '3.93'], ['108', '12', 'you debt your life', 'chris bennett', 'erik sommers', 'february 20 , 2011', '5ajn09', '4.25'], ['109', '13', 'i am the walrus', 'tim parsons', 'keith heisler', 'march 27 , 2011', '5ajn21', '4.99'], ['110', '14', 'school lies', 'rodney clouden', 'brian boyle', 'april 3 , 2011', '6ajn03', '3.59'], ['111', '15', 'license to till', 'john aoshima & jansen yee', 'matt fusfeld & alex cuthbertson', 'april 10 , 2011', '6ajn04', '3.35'], ['112', '16', 'jenny fromdabloc', 'bob bowen', 'laura mccreary', 'april 17 , 2011', '6ajn08', '4.74'], ['113', '17', 'home wrecker', 'joe daniello', 'alan r cohen & alan freedland', 'may 8 , 2011', '6ajn05', '3.29'], ['114', '18', 'flirting with disaster', 'pam cooke', 'keith heisler', 'may 15 , 2011', '6ajn06', '3.89']] |
colts - patriots rivalry | https://en.wikipedia.org/wiki/Colts%E2%80%93Patriots_rivalry | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13342861-6.html.csv | count | during the colts - patriots rivalry , there were five games where the location was the rca dome . | {'scope': 'all', 'criterion': 'equal', 'value': 'rca dome', 'result': '5', 'col': '6', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location', 'rca dome'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose location record fuzzily matches to rca dome .', 'tostr': 'filter_eq { all_rows ; location ; rca dome }'}], 'result': '5', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; location ; rca dome } }', 'tointer': 'select the rows whose location record fuzzily matches to rca dome . the number of such rows is 5 .'}, '5'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; location ; rca dome } } ; 5 } = true', 'tointer': 'select the rows whose location record fuzzily matches to rca dome . the number of such rows is 5 .'} | eq { count { filter_eq { all_rows ; location ; rca dome } } ; 5 } = true | select the rows whose location record fuzzily matches to rca dome . 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, 'location_5': 5, 'rca dome_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', 'location_5': 'location', 'rca dome_6': 'rca dome', '5_7': '5'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'location_5': [0], 'rca dome_6': [0], '5_7': [2]} | ['year', 'date', 'winner', 'result', 'loser', 'location'] | [['2000', 'october 8', 'new england patriots', '24 - 16', 'indianapolis colts', 'foxboro stadium'], ['2000', 'october 22', 'indianapolis colts', '30 - 23', 'new england patriots', 'rca dome'], ['2001', 'september 30', 'new england patriots', '44 - 13', 'indianapolis colts', 'foxboro stadium'], ['2001', 'october 21', 'new england patriots', '38 - 17', 'indianapolis colts', 'rca dome'], ['2003', 'november 30', 'new england patriots', '38 - 34', 'indianapolis colts', 'rca dome'], ['2004', 'january 18', 'new england patriots', '24 - 14', 'indianapolis colts', 'gillette stadium'], ['2004', 'september 9', 'new england patriots', '27 - 24', 'indianapolis colts', 'gillette stadium'], ['2005', 'january 16', 'new england patriots', '20 - 3', 'indianapolis colts', 'gillette stadium'], ['2005', 'november 7', 'indianapolis colts', '40 - 21', 'new england patriots', 'gillette stadium'], ['2006', 'november 5', 'indianapolis colts', '27 - 20', 'new england patriots', 'gillette stadium'], ['2007', 'january 21', 'indianapolis colts', '38 - 34', 'new england patriots', 'rca dome'], ['2007', 'november 4', 'new england patriots', '24 - 20', 'indianapolis colts', 'rca dome'], ['2008', 'november 2', 'indianapolis colts', '18 - 15', 'new england patriots', 'lucas oil stadium'], ['2009', 'november 15', 'indianapolis colts', '35 - 34', 'new england patriots', 'lucas oil stadium']] |
2007 bc lions season | https://en.wikipedia.org/wiki/2007_BC_Lions_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11994830-20.html.csv | comparative | ian smart had a lower rating than dave dickenson during the 2007 bc lions season . | {'row_1': '5', 'row_2': '3', 'col': '5', 'col_other': '1', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', 'ian smart'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose player record fuzzily matches to ian smart .', 'tostr': 'filter_eq { all_rows ; player ; ian smart }'}, 'rating'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; player ; ian smart } ; rating }', 'tointer': 'select the rows whose player record fuzzily matches to ian smart . take the rating record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', 'dave dickenson'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose player record fuzzily matches to dave dickenson .', 'tostr': 'filter_eq { all_rows ; player ; dave dickenson }'}, 'rating'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; player ; dave dickenson } ; rating }', 'tointer': 'select the rows whose player record fuzzily matches to dave dickenson . take the rating record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; player ; ian smart } ; rating } ; hop { filter_eq { all_rows ; player ; dave dickenson } ; rating } } = true', 'tointer': 'select the rows whose player record fuzzily matches to ian smart . take the rating record of this row . select the rows whose player record fuzzily matches to dave dickenson . take the rating record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; player ; ian smart } ; rating } ; hop { filter_eq { all_rows ; player ; dave dickenson } ; rating } } = true | select the rows whose player record fuzzily matches to ian smart . take the rating record of this row . select the rows whose player record fuzzily matches to dave dickenson . take the rating 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, 'ian smart_8': 8, 'rating_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'player_11': 11, 'dave dickenson_12': 12, 'rating_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', 'ian smart_8': 'ian smart', 'rating_9': 'rating', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'player_11': 'player', 'dave dickenson_12': 'dave dickenson', 'rating_13': 'rating'} | {'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'player_7': [0], 'ian smart_8': [0], 'rating_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'player_11': [1], 'dave dickenson_12': [1], 'rating_13': [3]} | ['player', 'att', 'comp', 'yards', 'rating'] | [['jarious jackson', '304', '167', '2553', '88.9'], ['buck pierce', '127', '81', '1013', '91.7'], ['dave dickenson', '87', '56', '740', '88.3'], ['gino guidugli', '11', '6', '138', '92.2'], ['ian smart', '1', '0', '0', '2.1']] |
list of collaborative software | https://en.wikipedia.org/wiki/List_of_collaborative_software | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1779657-2.html.csv | majority | the majority of the software programs do not allow faxing . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': 'no', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'faxing', 'no'], 'result': True, 'ind': 0, 'tointer': 'for the faxing records of all rows , most of them fuzzily match to no .', 'tostr': 'most_eq { all_rows ; faxing ; no } = true'} | most_eq { all_rows ; faxing ; no } = true | for the faxing records of all rows , most of them fuzzily match to no . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'faxing_3': 3, 'no_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'faxing_3': 'faxing', 'no_4': 'no'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'faxing_3': [0], 'no_4': [0]} | ['name', 'e - mail server', 'faxing', 'instant messaging', 'telephony', 'videoconferencing', 'web conferencing', 'data conferencing', 'application sharing', 'electronic meeting system', 'synchronous conferencing'] | [['ibm sametime', 'no , integrated with lotus domino', 'no', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes'], ['ibm lotus domino', 'yes', 'yes', 'yes with integrated sametime', 'yes with integrated sametime', 'yes with integrated sametime', 'yes with integrated sametime', 'no', 'yes with integrated sametime', 'yes with integrated sametime', 'no'], ['microsoft exchange server', 'yes', 'yes', 'no', 'no', 'no', 'no', 'no', 'no', 'yes', 'no'], ['microsoft lync server', 'no , integrated with exchange server', 'no', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes'], ['microsoft sharepoint', 'no , integrated with exchange server', 'no', 'no', 'no', 'no', 'no', 'no', 'no', 'yes', 'no'], ['name', 'e - mail server', 'faxing', 'instant messaging', 'telephony', 'videoconferencing', 'web conferencing', 'data conferencing', 'application sharing', 'electronic meeting system', 'synchronous conferencing']] |
list of pokémon theme songs | https://en.wikipedia.org/wiki/List_of_Pok%C3%A9mon_theme_songs | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2144389-8.html.csv | unique | kanako was a vocalist on only one pokemon theme song . | {'scope': 'all', 'row': '6', 'col': '5', 'col_other': 'n/a', 'criterion': 'equal', 'value': 'kanako', 'subset': None} | {'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'vocalist', 'kanako'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose vocalist record fuzzily matches to kanako .', 'tostr': 'filter_eq { all_rows ; vocalist ; kanako }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; vocalist ; kanako } } = true', 'tointer': 'select the rows whose vocalist record fuzzily matches to kanako . there is only one such row in the table .'} | only { filter_eq { all_rows ; vocalist ; kanako } } = true | select the rows whose vocalist record fuzzily matches to kanako . 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, 'vocalist_4': 4, 'kanako_5': 5} | {'only_1': 'only', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'vocalist_4': 'vocalist', 'kanako_5': 'kanako'} | {'only_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'vocalist_4': [0], 'kanako_5': [0]} | ['', 'japanese title', 'rōmaji', 'japanese translation', 'vocalist', 'episodes used'] | [['1', '君のそばで ～ ヒカリのテーマ ～', 'kimi no soba de ~ hikari no tēma ~', "by your side ~ hikari 's theme ~", 'grin', 'dp001 - dp024'], ['2', '君のそばで ～ ヒカリのテーマ ～ ( popupversion )', 'kimi no soba de ~ hikari no tēma ~ ( popupversion )', "by your side ~ hikari 's theme ~ ( popupversion )", 'grin', 'dp025 - dp050'], ['3', '君のそばで ～ ヒカリのテーマ ～ ( winter version )', 'kimi no soba de ~ hikari no tēma ~ ( winter version )', "by your side ~ hikari 's theme ~ ( winter version )", 'grin', 'dp051 - dp061'], ['4', '風のメッセージ', 'kaze no messēji', 'message of the wind', 'mai mizuhashi', 'dp062 - dp072 dp084 - dp095'], ['5', '風のメッセージ ( pokapoka - version )', 'kaze no messēji ( pokapoka - version )', 'message of the wind ( pokapoka - version )', 'mai mizuhashi', 'dp073 - dp083'], ['6', 'あしたはきっと', 'ashita wa kitto', 'surely tomorrow', 'kanako', 'dp096 - dp120'], ['7', 'もえよギザみみピチュー !', 'moe yo giza mimi pichū !', 'get fired up , spiky - eared pichu !', 'shoko nakagawa', 'dp121 - dp145'], ['8', 'ドッチ ～ ニョ', 'dotchi ~ nyo', 'which one ~ is it', 'moomoo milk and araki - san', 'dp146 - dp182']] |
uefa club competition records and statistics | https://en.wikipedia.org/wiki/UEFA_club_competition_records_and_statistics | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12307135-7.html.csv | unique | eusébio was the only player in the top 9 to score less than 55 goals . | {'scope': 'all', 'row': '9', 'col': '3', 'col_other': '2', 'criterion': 'less_than', 'value': '55', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'goals', '55'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose goals record is less than 55 .', 'tostr': 'filter_less { all_rows ; goals ; 55 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_less { all_rows ; goals ; 55 } }', 'tointer': 'select the rows whose goals record is less than 55 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'goals', '55'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose goals record is less than 55 .', 'tostr': 'filter_less { all_rows ; goals ; 55 }'}, 'player'], 'result': 'eusébio', 'ind': 2, 'tostr': 'hop { filter_less { all_rows ; goals ; 55 } ; player }'}, 'eusébio'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_less { all_rows ; goals ; 55 } ; player } ; eusébio }', 'tointer': 'the player record of this unqiue row is eusébio .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_less { all_rows ; goals ; 55 } } ; eq { hop { filter_less { all_rows ; goals ; 55 } ; player } ; eusébio } } = true', 'tointer': 'select the rows whose goals record is less than 55 . there is only one such row in the table . the player record of this unqiue row is eusébio .'} | and { only { filter_less { all_rows ; goals ; 55 } } ; eq { hop { filter_less { all_rows ; goals ; 55 } ; player } ; eusébio } } = true | select the rows whose goals record is less than 55 . there is only one such row in the table . the player record of this unqiue row is eusébio . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_less_0': 0, 'all_rows_6': 6, 'goals_7': 7, '55_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'player_9': 9, 'eusébio_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_less_0': 'filter_less', 'all_rows_6': 'all_rows', 'goals_7': 'goals', '55_8': '55', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'player_9': 'player', 'eusébio_10': 'eusébio'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_less_0': [1, 2], 'all_rows_6': [0], 'goals_7': [0], '55_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'player_9': [2], 'eusébio_10': [3]} | ['rank', 'player', 'goals', 'games', 'debut in europe'] | [['1', 'raúl', '75', '155', '1995'], ['2', 'filippo inzaghi', '70', '114', '1995'], ['3', 'andriy shevchenko', '67', '142', '1994'], ['4', 'lionel messi', '67', '82', '2004'], ['5', 'gerd müller', '62', '69', '1967'], ['5', 'ruud van nistelrooy', '62', '92', '1998'], ['7', 'henrik larsson', '59', '108', '1996'], ['7', 'thierry henry', '59', '140', '1996'], ['9', 'eusébio', '53', '71', '1961']] |
national democratic congress ( ghana ) | https://en.wikipedia.org/wiki/National_Democratic_Congress_%28Ghana%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1725076-2.html.csv | comparative | the share of votes in 2004 was 12.8 % lower than the share of votes in 1996 . | {'row_1': '4', 'row_2': '7', 'col': '4', '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', 'election', '2004'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose election record fuzzily matches to 2004 .', 'tostr': 'filter_eq { all_rows ; election ; 2004 }'}, 'share of votes'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; election ; 2004 } ; share of votes }', 'tointer': 'select the rows whose election record fuzzily matches to 2004 . take the share of votes record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'election', '1996'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose election record fuzzily matches to 1996 .', 'tostr': 'filter_eq { all_rows ; election ; 1996 }'}, 'share of votes'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; election ; 1996 } ; share of votes }', 'tointer': 'select the rows whose election record fuzzily matches to 1996 . take the share of votes record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; election ; 2004 } ; share of votes } ; hop { filter_eq { all_rows ; election ; 1996 } ; share of votes } } = true', 'tointer': 'select the rows whose election record fuzzily matches to 2004 . take the share of votes record of this row . select the rows whose election record fuzzily matches to 1996 . take the share of votes record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; election ; 2004 } ; share of votes } ; hop { filter_eq { all_rows ; election ; 1996 } ; share of votes } } = true | select the rows whose election record fuzzily matches to 2004 . take the share of votes record of this row . select the rows whose election record fuzzily matches to 1996 . take the share of votes 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, 'election_7': 7, '2004_8': 8, 'share of votes_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'election_11': 11, '1996_12': 12, 'share of votes_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', 'election_7': 'election', '2004_8': '2004', 'share of votes_9': 'share of votes', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'election_11': 'election', '1996_12': '1996', 'share of votes_13': 'share of votes'} | {'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'election_7': [0], '2004_8': [0], 'share of votes_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'election_11': [1], '1996_12': [1], 'share of votes_13': [3]} | ['election', 'candidate', 'number of votes', 'share of votes', 'outcome of election'] | [['2012', 'john dramani mahama', '5574761', '50.7 %', 'mahama ndc government'], ['2008 ( 2 )', 'john atta mills', '4501466', '50.1 %', 'mills ndc government'], ['2008 ( 1 )', 'john atta mills', '4056634', '47.9 %', '2nd round election'], ['2004', 'john atta mills', '3850368', '44.6 %', 'ndc opposition'], ['2000 ( 2nd )', 'john atta mills', '2728241', '43.3 %', 'ndc opposition'], ['2000 ( 1st )', 'john atta mills', '2895575', '44.8 %', '2nd round election'], ['1996', 'jerry rawlings', 'n / a', '57.4 %', '2nd rawlings ndc government'], ['1992', 'jerry rawlings', '2327600', '58.4 %', 'rawlings ndc government']] |
1991 u.s. open ( golf ) | https://en.wikipedia.org/wiki/1991_U.S._Open_%28golf%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17162268-2.html.csv | aggregation | in the 1991 u.s. open , the average number of strokes to par was 2.78 . | {'scope': 'all', 'col': '5', 'type': 'average', 'result': '2.78', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'to par'], 'result': '2.78', 'ind': 0, 'tostr': 'avg { all_rows ; to par }'}, '2.78'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; to par } ; 2.78 } = true', 'tointer': 'the average of the to par record of all rows is 2.78 .'} | round_eq { avg { all_rows ; to par } ; 2.78 } = true | the average of the to par record of all rows is 2.78 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'to par_4': 4, '2.78_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'to par_4': 'to par', '2.78_5': '2.78'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'to par_4': [0], '2.78_5': [1]} | ['player', 'country', 'year ( s ) won', 'total', 'to par', 'finish'] | [['scott simpson', 'united states', '1987', '282', '- 6', '2'], ['larry nelson', 'united states', '1983', '285', '- 3', 't3'], ['fuzzy zoeller', 'united states', '1984', '286', '- 2', '5'], ['raymond floyd', 'united states', '1986', '289', '+ 1', 't8'], ['hale irwin', 'united states', '1974 , 1979 , 1990', '290', '+ 2', 't11'], ['tom watson', 'united states', '1982', '291', '+ 3', 't16'], ['andy north', 'united states', '1978 , 1985', '295', '+ 7', 't37'], ['jack nicklaus', 'united states', '1962 , 1967 , 1972 , 1980', '297', '+ 9', 't46'], ['david graham', 'australia', '1981', '302', '+ 14', '60']] |
united states house of representatives elections , 1954 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1954 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1342013-37.html.csv | aggregation | the mean vote percentage of the republican candidates representing pennsylvania in the '54 united states house of representatives elections was 51.0 % . | {'scope': 'all', 'col': '6', 'type': 'average', 'result': '51.0', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'candidates'], 'result': '51.0', 'ind': 0, 'tostr': 'avg { all_rows ; candidates }'}, '51.0'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; candidates } ; 51.0 } = true', 'tointer': 'the average of the candidates record of all rows is 51.0 .'} | round_eq { avg { all_rows ; candidates } ; 51.0 } = true | the average of the candidates record of all rows is 51.0 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'candidates_4': 4, '51.0_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'candidates_4': 'candidates', '51.0_5': '51.0'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'candidates_4': [0], '51.0_5': [1]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['pennsylvania 6', 'hugh scott', 'republican', '1946', 're - elected', 'hugh scott ( r ) 50.6 % alexander hemphill ( d ) 49.4 %'], ['pennsylvania 8', 'karl c king', 'republican', '1951', 're - elected', 'karl c king ( r ) 51.2 % john p fullam ( d ) 48.8 %'], ['pennsylvania 9', 'paul b dague', 'republican', '1946', 're - elected', 'paul b dague ( r ) 62.7 % edward g wilson ( d ) 37.3 %'], ['pennsylvania 12', 'ivor d fenton', 'republican', '1938', 're - elected', 'ivor d fenton ( r ) 55.5 % charles e lotz ( d ) 44.5 %'], ['pennsylvania 15', 'francis e walter', 'democratic', '1932', 're - elected', 'francis e walter ( d ) 61.6 % leroy mikels ( r ) 38.4 %'], ['pennsylvania 17', 'alvin bush', 'republican', '1950', 're - elected', 'alvin bush ( r ) 56.5 % william t longe ( d ) 43.5 %'], ['pennsylvania 22', 'john p saylor', 'republican', '1949', 're - elected', 'john p saylor ( r ) 51.9 % robert s glass ( d ) 48.1 %'], ['pennsylvania 23', 'leon h gavin', 'republican', '1942', 're - elected', 'leon h gavin ( r ) 61.9 % fred c barr ( d ) 38.1 %'], ['pennsylvania 25', 'louis e graham', 'republican', '1938', 'lost re - election democratic gain', 'frank m clark ( d ) 53.5 % louis e graham ( r ) 46.5 %'], ['pennsylvania 26', 'thomas e morgan', 'democratic', '1944', 're - elected', 'thomas e morgan ( d ) 65.3 % branko stupar ( r ) 34.7 %']] |
united states house of representatives elections , 1998 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1998 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1341453-44.html.csv | count | a total of three incumbents from tennessee in the 1998 house of representatives elections were from the democratic party . | {'scope': 'all', 'criterion': 'equal', 'value': 'democratic', 'result': '3', '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': '3', '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 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; party ; democratic } } ; 3 } = true', 'tointer': 'select the rows whose party record fuzzily matches to democratic . the number of such rows is 3 .'} | eq { count { filter_eq { all_rows ; party ; democratic } } ; 3 } = true | select the rows whose party record fuzzily matches to democratic . 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, 'party_5': 5, 'democratic_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', 'party_5': 'party', 'democratic_6': 'democratic', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'party_5': [0], 'democratic_6': [0], '3_7': [2]} | ['district', 'incumbent', 'party', 'first elected', 'results', 'candidates'] | [['tennessee 1', 'william l jenkins', 'republican', '1996', 're - elected', 'william l jenkins ( r ) 69 % kay white ( d ) 31 %'], ['tennessee 2', 'jimmy duncan jr', 'republican', '1988', 're - elected', 'jimmy duncan jr ( r ) unopposed'], ['tennessee 3', 'zach wamp', 'republican', '1994', 're - elected', 'zach wamp ( r ) 67 % lewis lewis ( d ) 33 %'], ['tennessee 4', 'van hilleary', 'republican', '1994', 're - elected', 'van hilleary ( r ) 60 % jerry d cooper ( d ) 40 %'], ['tennessee 5', 'bob clement', 'democratic', '1988', 're - elected', 'bob clement ( d ) 83 %'], ['tennessee 6', 'bart gordon', 'democratic', '1984', 're - elected', 'bart gordon ( d ) 55 % walt massey ( r ) 45 %'], ['tennessee 7', 'ed bryant', 'republican', '1994', 're - elected', 'ed bryant ( r ) unopposed'], ['tennessee 8', 'john tanner', 'democratic', '1988', 're - elected', 'john tanner ( d ) unopposed']] |
list of supernanny episodes | https://en.wikipedia.org/wiki/List_of_Supernanny_episodes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-19897294-5.html.csv | count | there are 5 listed episodes in the supernanny televised series . | {'scope': 'all', 'criterion': 'all', 'value': 'n/a', 'result': '5', 'col': '2', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_all', 'args': ['all_rows', 'no in series'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose no in series record is arbitrary .', 'tostr': 'filter_all { all_rows ; no in series }'}], 'result': '5', 'ind': 1, 'tostr': 'count { filter_all { all_rows ; no in series } }', 'tointer': 'select the rows whose no in series record is arbitrary . the number of such rows is 5 .'}, '5'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_all { all_rows ; no in series } } ; 5 } = true', 'tointer': 'select the rows whose no in series record is arbitrary . the number of such rows is 5 .'} | eq { count { filter_all { all_rows ; no in series } } ; 5 } = true | select the rows whose no in series record is arbitrary . the number of such rows is 5 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_all_0': 0, 'all_rows_4': 4, 'no in series_5': 5, '5_6': 6} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_all_0': 'filter_all', 'all_rows_4': 'all_rows', 'no in series_5': 'no in series', '5_6': '5'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_all_0': [1], 'all_rows_4': [0], 'no in series_5': [0], '5_6': [2]} | ['no overall', 'no in series', 'family / families', 'location ( s )', 'original air date'] | [['uk16', '1', 'the hillhouse - docherty family', 'ayr ( scotland )', '29 august 2006'], ['uk17', '2', 'the howat family', 'shenley', '5 september 2006'], ['uk18', '3', 'the brown - smith family', 'warrington', '12 september 2006'], ['uk19', '4', 'the bates family', 'evesham', '19 september 2006'], ['uk20', '5', 'the williams family', 'birmingham', '26 september 2006']] |
list of awards and nominations received by renée zellweger | https://en.wikipedia.org/wiki/List_of_awards_and_nominations_received_by_Ren%C3%A9e_Zellweger | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18747538-7.html.csv | majority | most of renée zellweger 's nominations and awards came after the year 2000 . | {'scope': 'all', 'col': '1', 'most_or_all': 'most', 'criterion': 'greater_than', 'value': '2000', 'subset': None} | {'func': 'most_greater', 'args': ['all_rows', 'year', '2000'], 'result': True, 'ind': 0, 'tointer': 'for the year records of all rows , most of them are greater than 2000 .', 'tostr': 'most_greater { all_rows ; year ; 2000 } = true'} | most_greater { all_rows ; year ; 2000 } = true | for the year records of all rows , most of them are greater than 2000 . | 1 | 1 | {'most_greater_0': 0, 'result_1': 1, 'all_rows_2': 2, 'year_3': 3, '2000_4': 4} | {'most_greater_0': 'most_greater', 'result_1': 'true', 'all_rows_2': 'all_rows', 'year_3': 'year', '2000_4': '2000'} | {'most_greater_0': [1], 'result_1': [], 'all_rows_2': [0], 'year_3': [0], '2000_4': [0]} | ['year', 'category', 'film', 'result', 'lost to'] | [['1996', 'outstanding supporting actress', 'jerry maguire', 'nominated', 'lauren bacall ( the mirror has two faces )'], ['2001', 'outstanding actress', "bridget jones 's diary", 'nominated', 'halle berry ( monsters ball )'], ['2002', 'outstanding cast', 'chicago', 'won', '-'], ['2002', 'outstanding actress', 'chicago', 'won', '-'], ['2003', 'outstanding supporting actress', 'cold mountain', 'won', '-']] |
1970 isle of man tt | https://en.wikipedia.org/wiki/1970_Isle_of_Man_TT | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10301911-5.html.csv | majority | most of the riders had less than 10 points at the 1970 isle of man tt . | {'scope': 'all', 'col': '7', 'most_or_all': 'most', 'criterion': 'less_than', 'value': '10', 'subset': None} | {'func': 'most_less', 'args': ['all_rows', 'points', '10'], 'result': True, 'ind': 0, 'tointer': 'for the points records of all rows , most of them are less than 10 .', 'tostr': 'most_less { all_rows ; points ; 10 } = true'} | most_less { all_rows ; points ; 10 } = true | for the points records of all rows , most of them are less than 10 . | 1 | 1 | {'most_less_0': 0, 'result_1': 1, 'all_rows_2': 2, 'points_3': 3, '10_4': 4} | {'most_less_0': 'most_less', 'result_1': 'true', 'all_rows_2': 'all_rows', 'points_3': 'points', '10_4': '10'} | {'most_less_0': [1], 'result_1': [], 'all_rows_2': [0], 'points_3': [0], '10_4': [0]} | ['place', 'rider', 'country', 'machine', 'speed', 'time', 'points'] | [['1', 'kel carruthers', 'australia', 'yamaha', '96.13 mph', '2:21.19.2', '15'], ['2', 'rod gould', 'united kingdom', 'yamaha', '93.75 mph', '2:24.54.0', '12'], ['3', 'günter bartusch', 'east germany', 'mz', '93.75 mph', '2:26.58.0', '10'], ['4', 'chas mortimer', 'united kingdom', 'yamaha', '91.95 mph', '2:27.44.2', '8'], ['5', 'peter berwick', 'united kingdom', 'suzuki', '91.93 mph', '2:27.46.0', '6'], ['6', 'alex george', 'united kingdom', 'yamaha', '91.42 mph', '2:28.35.8', '5'], ['7', 'ian richardson', 'united kingdom', 'yamaha', '91.22 mph', '2:28.53.6', '4'], ['8', 'börje jansson', 'sweden', 'yamaha', '90.57 mph', '2:29.59.6', '3'], ['9', 'tony smith', 'united kingdom', 'yamaha', '90.44 mph', '2:30.12.2', '2'], ['10', 'bill smith', 'united kingdom', 'yamaha', '90.20 mph', '2:30.36.2', '1']] |
2010 cfl draft | https://en.wikipedia.org/wiki/2010_CFL_Draft | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-25017530-6.html.csv | count | three of the 2010 cfl draft picks were for the position ol . | {'scope': 'all', 'criterion': 'equal', 'value': 'ol', 'result': '3', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'position', 'ol'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose position record fuzzily matches to ol .', 'tostr': 'filter_eq { all_rows ; position ; ol }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; position ; ol } }', 'tointer': 'select the rows whose position record fuzzily matches to ol . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; position ; ol } } ; 3 } = true', 'tointer': 'select the rows whose position record fuzzily matches to ol . the number of such rows is 3 .'} | eq { count { filter_eq { all_rows ; position ; ol } } ; 3 } = true | select the rows whose position record fuzzily matches to ol . 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, 'position_5': 5, 'ol_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', 'position_5': 'position', 'ol_6': 'ol', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'position_5': [0], 'ol_6': [0], '3_7': [2]} | ['pick', 'cfl team', 'player', 'position', 'college'] | [['32', 'toronto argonauts', 'michael warner', 'ol', 'waterloo'], ['33', 'saskatchewan roughriders ( via winnipeg )', 'patrick neufeld', 'ol', 'saskatchewan'], ['34', 'bc lions', 'cauchy muamba', 'db', 'st francis xavier'], ['35', 'edmonton eskimos', 'scott ferguson', 'ol', 'st cloud state'], ['36', 'hamilton tiger - cats', 'justin palardy', 'k / p', "saint mary 's"], ['37', 'calgary stampeders', 'karl mccartney', 'lb', "saint mary 's"]] |
1992 - 93 toronto maple leafs season | https://en.wikipedia.org/wiki/1992%E2%80%9393_Toronto_Maple_Leafs_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13913477-9.html.csv | majority | all games of the toronto maple leafs in the 1992 - 93 season were scheduled for the month of april . | {'scope': 'all', 'col': '2', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'april', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'date', 'april'], 'result': True, 'ind': 0, 'tointer': 'for the date records of all rows , all of them fuzzily match to april .', 'tostr': 'all_eq { all_rows ; date ; april } = true'} | all_eq { all_rows ; date ; april } = true | for the date records of all rows , all of them fuzzily match to april . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'date_3': 3, 'april_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'date_3': 'date', 'april_4': 'april'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'date_3': [0], 'april_4': [0]} | ['game', 'date', 'visitor', 'score', 'home', 'record', 'points'] | [['78', 'april 3', 'new jersey', '1 - 0', 'toronto', '42 - 25 - 11', '95'], ['79', 'april 4', 'toronto', '0 - 4', 'philadelphia', '42 - 26 - 11', '95'], ['80', 'april 8', 'toronto', '3 - 5', 'winnipeg', '42 - 27 - 11', '95'], ['81', 'april 10', 'philadelphia', '0 - 4', 'toronto', '42 - 28 - 11', '95'], ['82', 'april 11', 'toronto', '4 - 2', 'hartford', '43 - 28 - 11', '97'], ['83', 'april 13', 'st louis', '2 - 1', 'toronto', '44 - 28 - 11', '99'], ['84', 'april 15', 'toronto', '2 - 3', 'chicago', '44 - 29 - 11', '99']] |
swimming at the 2007 world aquatics championships - men 's 200 metre freestyle | https://en.wikipedia.org/wiki/Swimming_at_the_2007_World_Aquatics_Championships_%E2%80%93_Men%27s_200_metre_freestyle | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10563642-3.html.csv | superlative | pieter van den hoogenband was the swimmer who had the fastest time overall . | {'scope': 'all', 'col_superlative': '8', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '4', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmin', 'args': ['all_rows', 'time'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; time }'}, 'name'], 'result': 'pieter van den hoogenband', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; time } ; name }'}, 'pieter van den hoogenband'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmin { all_rows ; time } ; name } ; pieter van den hoogenband } = true', 'tointer': 'select the row whose time record of all rows is minimum . the name record of this row is pieter van den hoogenband .'} | eq { hop { argmin { all_rows ; time } ; name } ; pieter van den hoogenband } = true | select the row whose time record of all rows is minimum . the name record of this row is pieter van den hoogenband . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'time_5': 5, 'name_6': 6, 'pieter van den hoogenband_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'time_5': 'time', 'name_6': 'name', 'pieter van den hoogenband_7': 'pieter van den hoogenband'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'time_5': [0], 'name_6': [1], 'pieter van den hoogenband_7': [2]} | ['rank', 'heat', 'lane', 'name', 'nationality', '100 m', '150 m', 'time'] | [['1', '2', '4', 'pieter van den hoogenband', 'netherlands', '51.16', '1:18.66', '1:46.33'], ['2', '1', '4', 'michael phelps', 'united states', '52.48', '1:20.10', '1:46.75'], ['3', '2', '2', 'massimiliano rosolino', 'italy', '52.13', '1:19.48', '1:47.44'], ['4', '1', '5', 'kenrick monk', 'australia', '52.96', '1:20.64', '1:47.45'], ['5', '2', '5', 'park tae - hwan', 'south korea', '52.91', '1:20.58', '1:47.83'], ['6', '1', '7', 'zhang lin', 'china', '53.25', '1:21.26', '1:48.29'], ['7', '2', '7', 'paul biedermann', 'germany', '53.28', '1:20.97', '1:48.43'], ['8', '2', '3', 'nicola cassio', 'italy', '53.24', '1:20.83', '1:48.47'], ['9', '2', '8', 'dominik koll', 'austria', '52.66', '1:20.50', '1:48.50'], ['10', '1', '2', 'brian johns', 'canada', '53.28', '1:21.22', '1:48.51'], ['11', '2', '6', 'dominik meichtry', 'switzerland', '52.87', '1:20.48', '1:48.54'], ['12', '1', '1', 'david carry', 'great britain', '52.87', '1:20.94', '1:48.71'], ['13', '2', '1', 'patrick murphy', 'australia', '52.92', '1:20.89', '1:48.75'], ['14', '1', '3', 'amaury leveaux', 'france', '53.28', '1:21.45', '1:48.81'], ['15', '1', '8', 'lã ¡ szlã cubic cseh', 'hungary', '52.92', '1:20.95', '1:48.89'], ['16', '1', '6', 'brent hayden', 'canada', '53.03', '1:20.99', '1:48.92']] |
northern indiana athletic conference | https://en.wikipedia.org/wiki/Northern_Indiana_Athletic_Conference | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12264570-1.html.csv | unique | south bend adams is the only school to join the northern indiana athletic conference in 1941 . | {'scope': 'all', 'row': '5', 'col': '6', 'col_other': '1', 'criterion': 'equal', 'value': '1941', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'joined', '1941'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose joined record is equal to 1941 .', 'tostr': 'filter_eq { all_rows ; joined ; 1941 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; joined ; 1941 } }', 'tointer': 'select the rows whose joined record is equal to 1941 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'joined', '1941'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose joined record is equal to 1941 .', 'tostr': 'filter_eq { all_rows ; joined ; 1941 }'}, 'school'], 'result': 'south bend adams', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; joined ; 1941 } ; school }'}, 'south bend adams'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; joined ; 1941 } ; school } ; south bend adams }', 'tointer': 'the school record of this unqiue row is south bend adams .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; joined ; 1941 } } ; eq { hop { filter_eq { all_rows ; joined ; 1941 } ; school } ; south bend adams } } = true', 'tointer': 'select the rows whose joined record is equal to 1941 . there is only one such row in the table . the school record of this unqiue row is south bend adams .'} | and { only { filter_eq { all_rows ; joined ; 1941 } } ; eq { hop { filter_eq { all_rows ; joined ; 1941 } ; school } ; south bend adams } } = true | select the rows whose joined record is equal to 1941 . there is only one such row in the table . the school record of this unqiue row is south bend adams . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'joined_7': 7, '1941_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'school_9': 9, 'south bend adams_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'joined_7': 'joined', '1941_8': '1941', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'school_9': 'school', 'south bend adams_10': 'south bend adams'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'joined_7': [0], '1941_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'school_9': [2], 'south bend adams_10': [3]} | ['school', 'location', 'mascot', 'county', 'enrollment ihsaa class', 'joined', 'previous conference'] | [['elkhart central', 'elkhart', 'blue blazers', '20 elkhart', '1747 aaaa', '1927', 'independents'], ['mishawaka', 'mishawaka', 'cavemen', '71 st joseph', '1761 aaaa', '1927', 'independents'], ['mishawaka marian', 'mishawaka', 'knights', '71 st joseph', '768 aaa', '2005', 'independents'], ['penn', 'mishawaka', 'kingsmen', '71 st joseph', '3222 aaaa', '1977', 'independents'], ['south bend adams', 'south bend', 'eagles', '71 st joseph', '1773 aaaa', '1941', 'none ( new school )'], ['south bend clay', 'south bend', 'colonials', '71 st joseph', '1466 aaaa', '1979', 'independents'], ['south bend riley', 'south bend', 'wildcats', '71 st joseph', '1511 aaaa', '1931', 'none ( new school )'], ["south bend st joseph 's", 'south bend', 'indians', '71 st joseph', '793 aaa', '2005', 'independents'], ['south bend washington', 'south bend', 'panthers', '71 st joseph', '1428 aaaa', '1938', 'none ( new school )']] |
rizal | https://en.wikipedia.org/wiki/Rizal | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-232458-1.html.csv | aggregation | the average population of cities in rizal in 2010 was 187514 . | {'scope': 'all', 'col': '4', 'type': 'average', 'result': '187514', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'population ( 2010 census )'], 'result': '187514', 'ind': 0, 'tostr': 'avg { all_rows ; population ( 2010 census ) }'}, '187514'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; population ( 2010 census ) } ; 187514 } = true', 'tointer': 'the average of the population ( 2010 census ) record of all rows is 187514 .'} | round_eq { avg { all_rows ; population ( 2010 census ) } ; 187514 } = true | the average of the population ( 2010 census ) record of all rows is 187514 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'population (2010 census)_4': 4, '187514_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'population (2010 census)_4': 'population ( 2010 census )', '187514_5': '187514'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'population (2010 census)_4': [0], '187514_5': [1]} | ['city / municipality', 'no of barangays', 'area ( km square )', 'population ( 2010 census )', 'pop density ( per km square )'] | [['angono', '10', '26.22', '102407', '3905.68'], ['antipolo', '16', '306.10', '677741', '2214.12'], ['baras', '10', '84.93', '32609', '383.95'], ['binangonan', '40', '66.34', '249872', '3766.54'], ['cainta', '7', '42.99', '311845', '7253.90'], ['cardona', '18', '28.56', '47414', '1660.15'], ['jalajala', '11', '44.12', '30074', '681.64'], ['morong', '8', '37.58', '52194', '1388.88'], ['pililla', '9', '69.95', '59527', '850.99'], ['rodriguez', '11', '312.70', '280904', '898.32'], ['san mateo', '15', '55.09', '205255', '3725.81'], ['tanay', '19', '200.00', '98879', '494.3'], ['taytay', '5', '38.80', '288956', '7447.32']] |
liberty league | https://en.wikipedia.org/wiki/Liberty_League | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1974482-1.html.csv | aggregation | the average student enrollment at institutions in the liberty league is 4067 . | {'scope': 'all', 'col': '6', 'type': 'average', 'result': '4067', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'enrollment'], 'result': '4067', 'ind': 0, 'tostr': 'avg { all_rows ; enrollment }'}, '4067'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; enrollment } ; 4067 } = true', 'tointer': 'the average of the enrollment record of all rows is 4067 .'} | round_eq { avg { all_rows ; enrollment } ; 4067 } = true | the average of the enrollment record of all rows is 4067 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'enrollment_4': 4, '4067_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'enrollment_4': 'enrollment', '4067_5': '4067'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'enrollment_4': [0], '4067_5': [1]} | ['institution', 'nickname', 'location', 'founded', 'type', 'enrollment', 'joined'] | [['bard college', 'raptors', 'annandale - on - hudson , new york', '1860', 'private', '1958', '2011'], ['clarkson university', 'golden knights', 'potsdam , new york', '1896', 'private', '2848', '1995'], ['hobart college', 'statesmen', 'geneva , new york', '1822', 'private', '905', '1995'], ['rensselaer polytechnic institute', 'engineers', 'troy , new york', '1824', 'private', '5431', '1995'], ['rochester institute of technology', 'tigers', 'henrietta , new york', '1829', 'private', '14224', '2011'], ['university of rochester', 'yellowjackets', 'rochester , new york', '1850', 'private', '5601', '1995'], ['st lawrence university', 'saints', 'canton , new york', '1856', 'private', '2327', '1995'], ['skidmore college', 'thoroughbreds', 'saratoga springs , new york', '1903', 'private', '2734', '1995'], ['union college', 'dutchmen', 'schenectady , new york', '1795', 'private', '2197', '1995'], ['vassar college', 'brewers', 'poughkeepsie , new york', '1861', 'private', '2446', '2001']] |
1969 vfl season | https://en.wikipedia.org/wiki/1969_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10809157-17.html.csv | majority | the majority of the matches were in front of a crowd of 22,000 or less . | {'scope': 'all', 'col': '6', 'most_or_all': 'most', 'criterion': 'less_than', 'value': '22,000', 'subset': None} | {'func': 'most_less', 'args': ['all_rows', 'crowd', '22,000'], 'result': True, 'ind': 0, 'tointer': 'for the crowd records of all rows , most of them are less than 22,000 .', 'tostr': 'most_less { all_rows ; crowd ; 22,000 } = true'} | most_less { all_rows ; crowd ; 22,000 } = true | for the crowd records of all rows , most of them are less than 22,000 . | 1 | 1 | {'most_less_0': 0, 'result_1': 1, 'all_rows_2': 2, 'crowd_3': 3, '22,000_4': 4} | {'most_less_0': 'most_less', 'result_1': 'true', 'all_rows_2': 'all_rows', 'crowd_3': 'crowd', '22,000_4': '22,000'} | {'most_less_0': [1], 'result_1': [], 'all_rows_2': [0], 'crowd_3': [0], '22,000_4': [0]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['st kilda', '9.14 ( 68 )', 'south melbourne', '15.10 ( 100 )', 'moorabbin oval', '13400', '9 august 1969'], ['hawthorn', '22.12 ( 144 )', 'north melbourne', '18.18 ( 126 )', 'glenferrie oval', '13504', '9 august 1969'], ['essendon', '19.18 ( 132 )', 'fitzroy', '14.11 ( 95 )', 'windy hill', '15548', '9 august 1969'], ['carlton', '14.11 ( 95 )', 'geelong', '17.8 ( 110 )', 'princes park', '27166', '9 august 1969'], ['richmond', '19.11 ( 125 )', 'melbourne', '12.13 ( 85 )', 'mcg', '23519', '9 august 1969'], ['footscray', '11.16 ( 82 )', 'collingwood', '16.8 ( 104 )', 'western oval', '21201', '9 august 1969']] |
a gift from a flower to a garden | https://en.wikipedia.org/wiki/A_Gift_from_a_Flower_to_a_Garden | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1793227-2.html.csv | count | epic was the label that released the title on six occasions . | {'scope': 'all', 'criterion': 'equal', 'value': 'epic', 'result': '6', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'label', 'epic'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose label record fuzzily matches to epic .', 'tostr': 'filter_eq { all_rows ; label ; epic }'}], 'result': '6', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; label ; epic } }', 'tointer': 'select the rows whose label record fuzzily matches to epic . the number of such rows is 6 .'}, '6'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; label ; epic } } ; 6 } = true', 'tointer': 'select the rows whose label record fuzzily matches to epic . the number of such rows is 6 .'} | eq { count { filter_eq { all_rows ; label ; epic } } ; 6 } = true | select the rows whose label record fuzzily matches to epic . the number of such rows is 6 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'label_5': 5, 'epic_6': 6, '6_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'label_5': 'label', 'epic_6': 'epic', '6_7': '6'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'label_5': [0], 'epic_6': [0], '6_7': [2]} | ['region', 'title', 'label', 'format', 'catalog - nr'] | [['usa', 'a gift from a flower to a garden', 'epic', 'mono lp', 'l2n6071'], ['usa', 'a gift from a flower to a garden', 'epic', 'stereo lp', 'b2n171'], ['uk', 'a gift from a flower to a garden', 'pye', 'mono lp', 'npl20000'], ['uk', 'a gift from a flower to a garden', 'pye', 'stereo lp', 'nspl 20000'], ['usa', 'wear your love like heaven', 'epic', 'monaural lp', 'ln 24349'], ['usa', 'wear your love like heaven', 'epic', 'stereo lp', 'bn 26349 ( stereo )'], ['usa', 'for little ones', 'epic', 'monaural lp', 'ln24350'], ['usa', 'for little ones', 'epic', 'stereo lp', 'bn26350 ( stereo )']] |
croatian bol ladies open | https://en.wikipedia.org/wiki/Croatian_Bol_Ladies_Open | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16157440-1.html.csv | unique | for just one yea , the croatian bol ladies open was in the iva category . | {'scope': 'all', 'row': '5', 'col': '2', 'col_other': 'n/a', 'criterion': 'equal', 'value': 'iva', 'subset': None} | {'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'category', 'iva'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose category record fuzzily matches to iva .', 'tostr': 'filter_eq { all_rows ; category ; iva }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; category ; iva } } = true', 'tointer': 'select the rows whose category record fuzzily matches to iva . there is only one such row in the table .'} | only { filter_eq { all_rows ; category ; iva } } = true | select the rows whose category record fuzzily matches to iva . 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, 'category_4': 4, 'iva_5': 5} | {'only_1': 'only', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'category_4': 'category', 'iva_5': 'iva'} | {'only_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'category_4': [0], 'iva_5': [0]} | ['year', 'category', 'champion', 'runner - up', 'score'] | [['1991', 'v', 'sandra cecchini', 'magdalena maleeva', '6 - 4 , 3 - 6 , 7 - 5'], ['1995', 'iii', 'sabine appelmans', 'silke meier', '6 - 4 , 6 - 3'], ['1996', 'iv', 'gloria pizzichini', 'silvija talaja', '6 - 0 , 6 - 2'], ['1997', 'iv', 'mirjana lučić', 'corina morariu', '7 - 5 , 6 - 7 , 7 - 6'], ['1998', 'iva', 'mirjana lučić', 'corina morariu', '6 - 2 , 6 - 4'], ['1999', 'iv', 'corina morariu', 'julie halard', '6 - 2 , 6 - 0'], ['2000', 'iii', 'tina pisnik', 'amélie mauresmo', '7 - 6 , 7 - 6'], ['2001', 'iii', 'ángeles montolio', 'mariana díaz - oliva', '3 - 6 , 6 - 2 , 6 - 4'], ['2002', 'iii', 'åsa svensson', 'iva majoli', '6 - 3 , 4 - 6 , 6 - 1'], ['2003', 'iii', 'vera zvonareva', 'conchita martínez g', '6 - 1 , 6 - 3']] |
kelly dullanty | https://en.wikipedia.org/wiki/Kelly_Dullanty | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17445415-2.html.csv | count | kelly dullanty had two matches in the ifc wc 13 - warriors challenge 13 . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'ifc wc 13 - warriors challenge', 'result': '2', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'event', 'ifc wc 13 - warriors challenge'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose event record fuzzily matches to ifc wc 13 - warriors challenge .', 'tostr': 'filter_eq { all_rows ; event ; ifc wc 13 - warriors challenge }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; event ; ifc wc 13 - warriors challenge } }', 'tointer': 'select the rows whose event record fuzzily matches to ifc wc 13 - warriors challenge . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; event ; ifc wc 13 - warriors challenge } } ; 2 } = true', 'tointer': 'select the rows whose event record fuzzily matches to ifc wc 13 - warriors challenge . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; event ; ifc wc 13 - warriors challenge } } ; 2 } = true | select the rows whose event record fuzzily matches to ifc wc 13 - warriors challenge . 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, 'event_5': 5, 'ifc wc 13 - warriors challenge_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', 'event_5': 'event', 'ifc wc 13 - warriors challenge_6': 'ifc wc 13 - warriors challenge', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'event_5': [0], 'ifc wc 13 - warriors challenge_6': [0], '2_7': [2]} | ['res', 'record', 'opponent', 'method', 'event', 'round', 'location'] | [['loss', '4 - 2', 'lance wipf', 'ko ( punch )', 'purecombat - bring the pain', '1', 'california , united states'], ['loss', '4 - 1', 'matt serra', 'submission ( triangle choke )', 'ufc 36', '1', 'nevada , united states'], ['win', '4 - 0', 'nuri shakir', 'decision', 'ifc wc 13 - warriors challenge 13', '4', 'california , united states'], ['win', '3 - 0', 'rudy vallederas', 'tko', 'ifc wc 13 - warriors challenge 13', 'n / a', 'california , united states'], ['win', '2 - 0', 'duane ludwig', 'decision', 'kotc 6 - road warriors', '3', 'michigan , united states'], ['win', '1 - 0', 'shad smith', 'tko ( strikes )', 'kotc 3 - knockout nightmare', '1', 'california , united states']] |
list of tvb series ( 2007 ) | https://en.wikipedia.org/wiki/List_of_TVB_series_%282007%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-11173827-1.html.csv | count | three different tvb series had an average rating of 32 in 2007 . | {'scope': 'all', 'criterion': 'equal', 'value': '32', 'result': '3', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'average', '32'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose average record is equal to 32 .', 'tostr': 'filter_eq { all_rows ; average ; 32 }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; average ; 32 } }', 'tointer': 'select the rows whose average record is equal to 32 . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; average ; 32 } } ; 3 } = true', 'tointer': 'select the rows whose average record is equal to 32 . the number of such rows is 3 .'} | eq { count { filter_eq { all_rows ; average ; 32 } } ; 3 } = true | select the rows whose average record is equal to 32 . the number of such rows is 3 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_eq_0': 0, 'all_rows_4': 4, 'average_5': 5, '32_6': 6, '3_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'average_5': 'average', '32_6': '32', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'average_5': [0], '32_6': [0], '3_7': [2]} | ['rank', 'english title', 'chinese title', 'average', 'peak', 'premiere', 'finale', 'hk viewers'] | [['1', 'the family link', '師奶兵團', '33', '42', '31', '33', '2.12 million'], ['2', 'fathers and sons', '爸爸閉翳', '32', '40', '31', '37', '2.11 million'], ['3', 'heart of greed', '溏心風暴', '32', '48', '29', '40', '2.08 million'], ['4', 'ten brothers', '十兄弟', '32', '39', '29', '36', '2.05 million'], ['5', 'on the first beat', '學警出更', '31', '38', '30', '35', '2.03 million'], ['6', 'the green grass of home', '緣來自有機', '31', '36', '29', '33', '2.01 million'], ['7', 'dicey business', '賭場風雲', '31', '37', '30', '34', '1.99 million'], ['8', 'steps', '舞動全城', '31', '36', '31', '32', '1.98 million'], ['9', 'the drive of life', '歲月風雲', '30', '39', '31', '33', '1.97 million']] |
ken schrader | https://en.wikipedia.org/wiki/Ken_Schrader | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1671401-2.html.csv | unique | the year 1995 was the only year that ken schrader had four top 10 finishes . | {'scope': 'all', 'row': '9', 'col': '5', 'col_other': '1', 'criterion': 'equal', 'value': '4', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'top 10', '4'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose top 10 record is equal to 4 .', 'tostr': 'filter_eq { all_rows ; top 10 ; 4 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; top 10 ; 4 } }', 'tointer': 'select the rows whose top 10 record is equal to 4 . there is only one such row in the table .'}, {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'top 10', '4'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose top 10 record is equal to 4 .', 'tostr': 'filter_eq { all_rows ; top 10 ; 4 }'}, 'year'], 'result': '1995', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; top 10 ; 4 } ; year }'}, '1995'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; top 10 ; 4 } ; year } ; 1995 }', 'tointer': 'the year record of this unqiue row is 1995 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; top 10 ; 4 } } ; eq { hop { filter_eq { all_rows ; top 10 ; 4 } ; year } ; 1995 } } = true', 'tointer': 'select the rows whose top 10 record is equal to 4 . there is only one such row in the table . the year record of this unqiue row is 1995 .'} | and { only { filter_eq { all_rows ; top 10 ; 4 } } ; eq { hop { filter_eq { all_rows ; top 10 ; 4 } ; year } ; 1995 } } = true | select the rows whose top 10 record is equal to 4 . there is only one such row in the table . the year record of this unqiue row is 1995 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'top 10_7': 7, '4_8': 8, 'eq_3': 3, 'num_hop_2': 2, 'year_9': 9, '1995_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'top 10_7': 'top 10', '4_8': '4', 'eq_3': 'eq', 'num_hop_2': 'num_hop', 'year_9': 'year', '1995_10': '1995'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'top 10_7': [0], '4_8': [0], 'eq_3': [4], 'num_hop_2': [3], 'year_9': [2], '1995_10': [3]} | ['year', 'starts', 'wins', 'top 5', 'top 10', 'poles', 'avg start', 'avg finish', 'winnings', 'position', 'team ( s )'] | [['1987', '1', '0', '1', '1', '0', '21.0', '5.0', '1825', '83rd', 'ken schrader racing'], ['1988', '10', '0', '2', '3', '0', '16.3', '20.1', '45175', '33rd', 'ken schrader racing'], ['1989', '11', '1', '1', '6', '1', '14.3', '17.6', '27577', '32nd', 'ken schrader racing hendrick motorsports'], ['1990', '11', '0', '1', '2', '0', '20.2', '24.1', '22860', '37th', 'ken schrader racing'], ['1991', '10', '0', '4', '5', '0', '14.0', '16.3', '57345', '35th', 'ken schrader racing darrell waltrip motorsports'], ['1992', '10', '0', '2', '6', '0', '18.8', '11.9', '48352', '29th', 'ken schrader racing ernie irvan racing'], ['1993', '9', '0', '2', '3', '1', '9.0', '15.8', '65628', '35th', 'ken schrader racing'], ['1994', '10', '1', '3', '3', '0', '20.5', '18.2', '68700', '38th', 'ken schrader racing'], ['1995', '9', '0', '2', '4', '0', '25.8', '18.8', '66605', '40th', 'ken schrader racing'], ['1998', '10', '0', '0', '3', '0', '20.7', '22.0', '68920', '46th', 'andy petree racing'], ['1999', '12', '0', '0', '3', '3', '12.1', '19.8', '148480', '42nd', 'andy petree racing'], ['2000', '1', '0', '0', '0', '0', '38.0', '43.0', '15000', '117th', 'team amick motorsports'], ['2001', '1', '0', '0', '0', '0', '11.0', '39.0', '13320', '139th', 'ken schrader racing'], ['2002', '2', '0', '0', '0', '0', '27.5', '38.0', '31000', '98th', 'ken schrader racing'], ['2006', '8', '0', '0', '0', '0', '21.5', '26.8', '197127', '59th', 'brewco motorsports']] |
indra putra mahayuddin | https://en.wikipedia.org/wiki/Indra_Putra_Mahayuddin | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11847478-2.html.csv | aggregation | indra putra mahayuddin score a total of 30 goals in the games listed . | {'scope': 'all', 'col': '3', 'type': 'sum', 'result': '30', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'score'], 'result': '30', 'ind': 0, 'tostr': 'sum { all_rows ; score }'}, '30'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; score } ; 30 } = true', 'tointer': 'the sum of the score record of all rows is 30 .'} | round_eq { sum { all_rows ; score } ; 30 } = true | the sum of the score record of all rows is 30 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'score_4': 4, '30_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'score_4': 'score', '30_5': '30'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'score_4': [0], '30_5': [1]} | ['date', 'venue', 'score', 'result', 'competition'] | [['december 11 , 2002', 'petaling jaya , malaysia', '5 - 0', 'win', 'friendly'], ['december 18 , 2002', 'singapore , singapore', '0 - 4', 'win', '2002 tiger cup group stage'], ['december 20 , 2002', 'singapore , singapore', '3 - 1', 'win', '2002 tiger cup group stage'], ['december 29 , 2002', 'singapore , singapore', '2 - 1', 'lose', '2002 tiger cup third / fourth place'], ['october 22 , 2003', 'manama , bahrain', '3 - 1', 'lose', '2004 afc asian cup qualification'], ['august 23 , 2006', 'shah alam , malaysia', '1 - 2', 'lose', '2006 merdeka tournament group stage'], ['july 10 , 2007', 'kuala lumpur , malaysia', '1 - 5', 'lose', '2007 afc asian cup group stage'], ['july 22 , 2008', 'hyderabad , india', '1 - 1', 'draw', 'friendly'], ['october 15 , 2008', 'kelana jaya , malaysia', '4 - 0', 'win', '2008 merdeka tournament'], ['october 23 , 2008', 'kuala lumpur , malaysia', '4 - 0', 'win', '2008 merdeka tournament'], ['december 6 , 2008', 'phuket , thailand', '3 - 0', 'win', '2008 aff suzuki cup'], ['december 8 , 2008', 'phuket , thailand', '2 - 3', 'lose', '2008 aff suzuki cup']] |
1967 detroit lions season | https://en.wikipedia.org/wiki/1967_Detroit_Lions_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18908350-1.html.csv | comparative | tim jones had a higher pick number than the defensive end . | {'row_1': '5', 'row_2': '4', 'col': '2', 'col_other': '3,4', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'and', 'args': [{'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', 'tim jones'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose player record fuzzily matches to tim jones .', 'tostr': 'filter_eq { all_rows ; player ; tim jones }'}, 'pick'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; player ; tim jones } ; pick }', 'tointer': 'select the rows whose player record fuzzily matches to tim jones . take the pick record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', 'lew kamanu'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose player record fuzzily matches to lew kamanu .', 'tostr': 'filter_eq { all_rows ; player ; lew kamanu }'}, 'pick'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; player ; lew kamanu } ; pick }', 'tointer': 'select the rows whose player record fuzzily matches to lew kamanu . take the pick record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; player ; tim jones } ; pick } ; hop { filter_eq { all_rows ; player ; lew kamanu } ; pick } }', 'tointer': 'select the rows whose player record fuzzily matches to tim jones . take the pick record of this row . select the rows whose player record fuzzily matches to lew kamanu . take the pick record of this row . the first record is greater than the second record .'}, {'func': 'and', 'args': [{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', 'tim jones'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose player record fuzzily matches to tim jones .', 'tostr': 'filter_eq { all_rows ; player ; tim jones }'}, 'position'], 'result': 'quarterback', 'ind': 5, 'tostr': 'hop { filter_eq { all_rows ; player ; tim jones } ; position }'}, 'quarterback'], 'result': True, 'ind': 6, 'tostr': 'eq { hop { filter_eq { all_rows ; player ; tim jones } ; position } ; quarterback }', 'tointer': 'the position record of the first row is quarterback .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', 'lew kamanu'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose player record fuzzily matches to lew kamanu .', 'tostr': 'filter_eq { all_rows ; player ; lew kamanu }'}, 'position'], 'result': 'defensive end', 'ind': 7, 'tostr': 'hop { filter_eq { all_rows ; player ; lew kamanu } ; position }'}, 'defensive end'], 'result': True, 'ind': 8, 'tostr': 'eq { hop { filter_eq { all_rows ; player ; lew kamanu } ; position } ; defensive end }', 'tointer': 'the position record of the second row is defensive end .'}], 'result': True, 'ind': 9, 'tostr': 'and { eq { hop { filter_eq { all_rows ; player ; tim jones } ; position } ; quarterback } ; eq { hop { filter_eq { all_rows ; player ; lew kamanu } ; position } ; defensive end } }', 'tointer': 'the position record of the first row is quarterback . the position record of the second row is defensive end .'}], 'result': True, 'ind': 10, 'tostr': 'and { greater { hop { filter_eq { all_rows ; player ; tim jones } ; pick } ; hop { filter_eq { all_rows ; player ; lew kamanu } ; pick } } ; and { eq { hop { filter_eq { all_rows ; player ; tim jones } ; position } ; quarterback } ; eq { hop { filter_eq { all_rows ; player ; lew kamanu } ; position } ; defensive end } } } = true', 'tointer': 'select the rows whose player record fuzzily matches to tim jones . take the pick record of this row . select the rows whose player record fuzzily matches to lew kamanu . take the pick record of this row . the first record is greater than the second record . the position record of the first row is quarterback . the position record of the second row is defensive end .'} | and { greater { hop { filter_eq { all_rows ; player ; tim jones } ; pick } ; hop { filter_eq { all_rows ; player ; lew kamanu } ; pick } } ; and { eq { hop { filter_eq { all_rows ; player ; tim jones } ; position } ; quarterback } ; eq { hop { filter_eq { all_rows ; player ; lew kamanu } ; position } ; defensive end } } } = true | select the rows whose player record fuzzily matches to tim jones . take the pick record of this row . select the rows whose player record fuzzily matches to lew kamanu . take the pick record of this row . the first record is greater than the second record . the position record of the first row is quarterback . the position record of the second row is defensive end . | 13 | 11 | {'and_10': 10, 'result_11': 11, 'greater_4': 4, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_12': 12, 'player_13': 13, 'tim jones_14': 14, 'pick_15': 15, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_16': 16, 'player_17': 17, 'lew kamanu_18': 18, 'pick_19': 19, 'and_9': 9, 'str_eq_6': 6, 'str_hop_5': 5, 'position_20': 20, 'quarterback_21': 21, 'str_eq_8': 8, 'str_hop_7': 7, 'position_22': 22, 'defensive end_23': 23} | {'and_10': 'and', 'result_11': 'true', 'greater_4': 'greater', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_12': 'all_rows', 'player_13': 'player', 'tim jones_14': 'tim jones', 'pick_15': 'pick', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_16': 'all_rows', 'player_17': 'player', 'lew kamanu_18': 'lew kamanu', 'pick_19': 'pick', 'and_9': 'and', 'str_eq_6': 'str_eq', 'str_hop_5': 'str_hop', 'position_20': 'position', 'quarterback_21': 'quarterback', 'str_eq_8': 'str_eq', 'str_hop_7': 'str_hop', 'position_22': 'position', 'defensive end_23': 'defensive end'} | {'and_10': [11], 'result_11': [], 'greater_4': [10], 'num_hop_2': [4], 'filter_str_eq_0': [2, 5], 'all_rows_12': [0], 'player_13': [0], 'tim jones_14': [0], 'pick_15': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3, 7], 'all_rows_16': [1], 'player_17': [1], 'lew kamanu_18': [1], 'pick_19': [3], 'and_9': [10], 'str_eq_6': [9], 'str_hop_5': [6], 'position_20': [5], 'quarterback_21': [6], 'str_eq_8': [9], 'str_hop_7': [8], 'position_22': [7], 'defensive end_23': [8]} | ['round', 'pick', 'player', 'position', 'school'] | [['1', '7', 'mel farr', 'running back', 'ucla'], ['2', '34', 'lem barney', 'defensive back', 'jackson state'], ['3', '60', 'paul naumoff', 'linebacker', 'tennessee'], ['4', '88', 'lew kamanu', 'defensive end', 'weber state'], ['6', '141', 'tim jones', 'quarterback', 'weber state']] |
media in sherbrooke | https://en.wikipedia.org/wiki/Media_in_Sherbrooke | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18409243-1.html.csv | comparative | of the media in sherbrooke , the station cimo - fm is at a higher frequency than the station cfak - fm . | {'row_1': '12', 'row_2': '2', 'col': '1', 'col_other': '2', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'call sign', 'cimo - fm'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose call sign record fuzzily matches to cimo - fm .', 'tostr': 'filter_eq { all_rows ; call sign ; cimo - fm }'}, 'frequency'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; call sign ; cimo - fm } ; frequency }', 'tointer': 'select the rows whose call sign record fuzzily matches to cimo - fm . take the frequency record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'call sign', 'cfak - fm'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose call sign record fuzzily matches to cfak - fm .', 'tostr': 'filter_eq { all_rows ; call sign ; cfak - fm }'}, 'frequency'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; call sign ; cfak - fm } ; frequency }', 'tointer': 'select the rows whose call sign record fuzzily matches to cfak - fm . take the frequency record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; call sign ; cimo - fm } ; frequency } ; hop { filter_eq { all_rows ; call sign ; cfak - fm } ; frequency } } = true', 'tointer': 'select the rows whose call sign record fuzzily matches to cimo - fm . take the frequency record of this row . select the rows whose call sign record fuzzily matches to cfak - fm . take the frequency record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; call sign ; cimo - fm } ; frequency } ; hop { filter_eq { all_rows ; call sign ; cfak - fm } ; frequency } } = true | select the rows whose call sign record fuzzily matches to cimo - fm . take the frequency record of this row . select the rows whose call sign record fuzzily matches to cfak - fm . take the frequency record of this row . the first record is greater than the second record . | 5 | 5 | {'greater_4': 4, 'result_5': 5, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'call sign_7': 7, 'cimo - fm_8': 8, 'frequency_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'call sign_11': 11, 'cfak - fm_12': 12, 'frequency_13': 13} | {'greater_4': 'greater', 'result_5': 'true', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'call sign_7': 'call sign', 'cimo - fm_8': 'cimo - fm', 'frequency_9': 'frequency', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'call sign_11': 'call sign', 'cfak - fm_12': 'cfak - fm', 'frequency_13': 'frequency'} | {'greater_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'call sign_7': [0], 'cimo - fm_8': [0], 'frequency_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'call sign_11': [1], 'cfak - fm_12': [1], 'frequency_13': [3]} | ['frequency', 'call sign', 'format', 'owner', 'notes'] | [['fm 88.1', 'cfpp - fm', 'christian radio', 'fabrique notre - dame du perpétuel - secours', 'french'], ['fm 88.3', 'cfak - fm', 'campus radio', 'université de sherbrooke', 'french'], ['fm 88.9', 'cjmq - fm', 'community radio', "bishop 's university", 'english'], ['fm 89.7', 'cbm - fm - 1', 'public music', 'canadian broadcasting corporation', 'english'], ['fm 90.7', 'cbfx - fm - 2', 'public music', 'société radio - canada', 'french'], ['fm 91.7', 'cbmb - fm', 'public news / talk', 'canadian broadcasting corporation', 'english'], ['fm 93.7', 'cfge - fm', 'adult contemporary', 'cogeco', 'french'], ['fm 95.5', 'cflx - fm', 'community radio', "radio communautaire de l'estrie", 'french'], ['fm 100.3', 'cira - fm - 1', 'christian radio', 'radio ville - marie', 'french'], ['fm 101.1', 'cbf - fm - 10', 'public news / talk', 'société radio - canada', 'french'], ['fm 102.7', 'cite - fm - 1', 'soft adult contemporary', 'bell media radio', 'french'], ['fm 106.1', 'cimo - fm', 'contemporary hit radio', 'bell media radio', 'french'], ['fm 107.7', 'ckoy - fm', 'talk radio', 'cogeco', 'french']] |
canada post stamp releases ( 2005 - 09 ) | https://en.wikipedia.org/wiki/Canada_Post_stamp_releases_%282005%E2%80%9309%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11900773-1.html.csv | count | there were 3 canada post stamp releases designed by hélène lheureux . | {'scope': 'all', 'criterion': 'equal', 'value': 'hélène lheureux', 'result': '3', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'design', 'hélène lheureux'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose design record fuzzily matches to hélène lheureux .', 'tostr': 'filter_eq { all_rows ; design ; hélène lheureux }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; design ; hélène lheureux } }', 'tointer': 'select the rows whose design record fuzzily matches to hélène lheureux . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; design ; hélène lheureux } } ; 3 } = true', 'tointer': 'select the rows whose design record fuzzily matches to hélène lheureux . the number of such rows is 3 .'} | eq { count { filter_eq { all_rows ; design ; hélène lheureux } } ; 3 } = true | select the rows whose design record fuzzily matches to hélène lheureux . 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, 'design_5': 5, 'hélène lheureux_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', 'design_5': 'design', 'hélène lheureux_6': 'hélène lheureux', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'design_5': [0], 'hélène lheureux_6': [0], '3_7': [2]} | ['date of issue', 'denomination', 'design', 'paper type', 'first day cover cancellation'] | [['7 january 2005', '50 cents', 'hélène lheureux', 'tullis russell coatings', 'vancouver , bc'], ['7 january 2005', '1.45', 'hélène lheureux', 'tullis russell coatings', 'vancouver , bc'], ['29 january 2005', '0.50', 'stéphane huot', 'tullis russell coatings', 'edmonton , alberta'], ['4 february 2005', '0.50', 'circle design inc', 'tullis russell coatings', 'granby , qc'], ['14 february 2005', '0.50', 'denis lallier', 'fasson', 'truro , nova scotia'], ['4 march 2005', '0.50', 'hm & e design', 'tullis russell coatings', 'vancouver , bc'], ['10 march 2005', '0.50', 'isabelle toussaint', 'fasson', 'vancouver , bc'], ['23 march 2005', '0.50', 'rolf harder', 'tullis russell coatings', 'fredericton , new brunswick'], ['2 april 2005', '0.50', 'designwerke inc , andrew perro', 'tullis russell coatings', 'montreal , qc and halifax , ns'], ['12 april 2005', '0.50', '52 pick - up inc', 'tullis russell coatings', 'toronto , on'], ['22 april 2005', '0.50', 'xerxes irani', 'tullis russell coatings', 'waterton park , ab'], ['29 april 2005', '0.50', 'derek sarty', 'tullis russell coatings', 'halifax , ns'], ['6 may 2005', '0.50', 'tilt telmet and marko barac', 'tullis russell coatings', 'ottawa , on'], ['27 may 2005', '0.50', 'hélène lheureux', 'tullis russell coatings', 'kitchener , on'], ['13 june 2005', '0.50', 'françois dallaire', 'tullis russell coatings', 'victoria , bc'], ['13 june 2005', '0.50', 'françois dallaire', 'tullis russell coatings', 'victoria , bc'], ['21 june 2005', '0.50', 'katalin kovats', 'tullis russell coatings', 'hamilton , ontario']] |
2007 amsterdam admirals season | https://en.wikipedia.org/wiki/2007_Amsterdam_Admirals_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-10392906-2.html.csv | majority | most of the games during the 2007 amsterdam admirals season were losses . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': 'l', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'final score', 'l'], 'result': True, 'ind': 0, 'tointer': 'for the final score records of all rows , most of them fuzzily match to l .', 'tostr': 'most_eq { all_rows ; final score ; l } = true'} | most_eq { all_rows ; final score ; l } = true | for the final score records of all rows , most of them fuzzily match to l . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'final score_3': 3, 'l_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'final score_3': 'final score', 'l_4': 'l'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'final score_3': [0], 'l_4': [0]} | ['week', 'date', 'kickoff', 'opponent', 'final score', 'team record', 'game site', 'attendance'] | [['1', 'saturday , april 14', '7:00 pm', 'frankfurt galaxy', 'l 14 - 30', '0 - 1', 'commerzbank - arena', '38125'], ['2', 'friday , april 20', '8:00 pm', 'rhein fire', 'l 10 - 16', '0 - 2', 'amsterdam arena', '14611'], ['3', 'saturday , april 28', '6:00 pm', 'berlin thunder', 'w 14 - 10', '1 - 2', 'olympic stadium', '11942'], ['4', 'sunday , may 6', '3:00 pm', 'frankfurt galaxy', 'w 19 - 17', '2 - 2', 'amsterdam arena', '10788'], ['5', 'saturday , may 12', '6:00 pm', 'hamburg sea devils', 'l 17 - 24', '2 - 3', 'aol arena', '15271'], ['6', 'friday , may 18', '8:00 pm', 'hamburg sea devils', 'w 41 - 31', '3 - 3', 'amsterdam arena', '9384'], ['7', 'friday , may 25', '8:00 pm', 'cologne centurions', 'l 7 - 30', '3 - 4', 'amsterdam arena', '11714'], ['8', 'sunday , june 3', '4:00 pm', 'rhein fire', 'l 38 - 41', '3 - 5', 'ltu arena', '20355'], ['9', 'saturday , june 9', '6:00 pm', 'cologne centurions', 'l 13 - 31', '3 - 6', 'rheinenergiestadion', '12878']] |
list of european cup and uefa champions league winning managers | https://en.wikipedia.org/wiki/List_of_European_Cup_and_UEFA_Champions_League_winning_managers | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15205941-2.html.csv | comparative | bob paisley won more years of the european cup and uefa champions league than brian clough . | {'row_1': '1', 'row_2': '13', 'col': '4', 'col_other': '2', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'manager', 'bob paisley'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose manager record fuzzily matches to bob paisley .', 'tostr': 'filter_eq { all_rows ; manager ; bob paisley }'}, 'years won'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; manager ; bob paisley } ; years won }', 'tointer': 'select the rows whose manager record fuzzily matches to bob paisley . take the years won record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'manager', 'brian clough'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose manager record fuzzily matches to brian clough .', 'tostr': 'filter_eq { all_rows ; manager ; brian clough }'}, 'years won'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; manager ; brian clough } ; years won }', 'tointer': 'select the rows whose manager record fuzzily matches to brian clough . take the years won record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; manager ; bob paisley } ; years won } ; hop { filter_eq { all_rows ; manager ; brian clough } ; years won } } = true', 'tointer': 'select the rows whose manager record fuzzily matches to bob paisley . take the years won record of this row . select the rows whose manager record fuzzily matches to brian clough . take the years won record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; manager ; bob paisley } ; years won } ; hop { filter_eq { all_rows ; manager ; brian clough } ; years won } } = true | select the rows whose manager record fuzzily matches to bob paisley . take the years won record of this row . select the rows whose manager record fuzzily matches to brian clough . take the years won record of this row . the first record is greater than the second record . | 5 | 5 | {'greater_4': 4, 'result_5': 5, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'manager_7': 7, 'bob paisley_8': 8, 'years won_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'manager_11': 11, 'brian clough_12': 12, 'years won_13': 13} | {'greater_4': 'greater', 'result_5': 'true', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'manager_7': 'manager', 'bob paisley_8': 'bob paisley', 'years won_9': 'years won', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'manager_11': 'manager', 'brian clough_12': 'brian clough', 'years won_13': 'years won'} | {'greater_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'manager_7': [0], 'bob paisley_8': [0], 'years won_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'manager_11': [1], 'brian clough_12': [1], 'years won_13': [3]} | ['rank', 'manager', 'runner - up', 'years won', 'clubs won'] | [['1', 'bob paisley', '0', '1977 , 1978 , 1981', 'liverpool'], ['2', 'alex ferguson', '2', '1999 , 2008', 'manchester united'], ['2', 'miguel muñoz', '2', '1960 , 1966', 'real madrid'], ['4', 'jupp heynckes', '1', '1998 , 2013', 'real madrid , bayern munich'], ['4', 'carlo ancelotti', '1', '2003 , 2007', 'milan'], ['4', 'ottmar hitzfeld', '1', '1997 , 2001', 'borussia dortmund , bayern munich'], ['4', 'ernst happel', '1', '1970 , 1983', 'feyenoord , hamburg'], ['4', 'helenio herrera', '1', '1964 , 1965', 'internazionale'], ['9', 'josep guardiola', '0', '2009 , 2011', 'barcelona'], ['9', 'josé mourinho', '0', '2004 , 2010', 'porto , internazionale'], ['9', 'vicente del bosque', '0', '2000 , 2002', 'real madrid'], ['9', 'arrigo sacchi', '0', '1989 , 1990', 'milan'], ['9', 'brian clough', '0', '1979 , 1980', 'nottingham forest'], ['9', 'dettmar cramer', '0', '1975 , 1976', 'bayern munich'], ['9', 'ștefan kovács', '0', '1972 , 1973', 'ajax'], ['9', 'nereo rocco', '0', '1963 , 1969', 'milan'], ['9', 'béla guttmann', '0', '1961 , 1962', 'benfica'], ['9', 'luis carniglia', '0', '1958 , 1959', 'real madrid'], ['9', 'josé villalonga', '0', '1956 , 1957', 'real madrid']] |
stéphane sarrazin | https://en.wikipedia.org/wiki/St%C3%A9phane_Sarrazin | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1235636-3.html.csv | aggregation | stephane sarrazin completed a total of 3670 laps between 2001 and 2013 . | {'scope': 'all', 'col': '5', 'type': 'sum', 'result': '3670', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'laps'], 'result': '3670', 'ind': 0, 'tostr': 'sum { all_rows ; laps }'}, '3670'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; laps } ; 3670 } = true', 'tointer': 'the sum of the laps record of all rows is 3670 .'} | round_eq { sum { all_rows ; laps } ; 3670 } = true | the sum of the laps record of all rows is 3670 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'laps_4': 4, '3670_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'laps_4': 'laps', '3670_5': '3670'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'laps_4': [0], '3670_5': [1]} | ['year', 'team', 'co - drivers', 'class', 'laps', 'pos', 'class pos'] | [['2001', 'viper team oreca', 'yannick dalmas franck montagny', 'lmp900', '126', 'dnf', 'dnf'], ['2002', 'playstation team oreca', 'franck montagny nicolas minassian', 'lmp900', '359', '6th', '5th'], ['2003', 'pescarolo sport', 'jean - christophe boullion franck lagorce', 'lmp900', '356', '8th', '6th'], ['2005', 'aston martin racing', 'david brabham darren turner', 'gt1', '333', '9th', '3rd'], ['2006', 'aston martin racing', 'pedro lamy stéphane ortelli', 'gt1', '342', '10th', '5th'], ['2007', 'team peugeot total', 'pedro lamy sébastien bourdais', 'lmp1', '359', '2nd', '2nd'], ['2008', 'team peugeot total', 'pedro lamy alexander wurz', 'lmp1', '368', '5th', '5th'], ['2009', 'team peugeot total', 'franck montagny sébastien bourdais', 'lmp1', '381', '2nd', '2nd'], ['2010', 'team peugeot total', 'franck montagny nicolas minassian', 'lmp1', '264', 'dnf', 'dnf'], ['2011', 'peugeot sport total', 'franck montagny nicolas minassian', 'lmp1', '353', '3rd', '3rd'], ['2012', 'toyota racing', 'anthony davidson sébastien buemi', 'lmp1', '82', 'dnf', 'dnf'], ['2013', 'toyota racing', 'anthony davidson sébastien buemi', 'lmp1', '347', '2nd', '2nd']] |
i 'm a celebrity ... get me out of here ! ( uk tv series ) | https://en.wikipedia.org/wiki/I%27m_a_Celebrity...Get_Me_Out_of_Here%21_%28UK_TV_series%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-14345690-3.html.csv | count | on i 'm a celebrity ... get me out of here ! , 3 celebrities exited on day 15 . | {'scope': 'all', 'criterion': 'equal', 'value': 'day 15', 'result': '3', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'exited', 'day 15'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose exited record fuzzily matches to day 15 .', 'tostr': 'filter_eq { all_rows ; exited ; day 15 }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; exited ; day 15 } }', 'tointer': 'select the rows whose exited record fuzzily matches to day 15 . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; exited ; day 15 } } ; 3 } = true', 'tointer': 'select the rows whose exited record fuzzily matches to day 15 . the number of such rows is 3 .'} | eq { count { filter_eq { all_rows ; exited ; day 15 } } ; 3 } = true | select the rows whose exited record fuzzily matches to day 15 . 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, 'exited_5': 5, 'day 15_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', 'exited_5': 'exited', 'day 15_6': 'day 15', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'exited_5': [0], 'day 15_6': [0], '3_7': [2]} | ['celebrity', 'famous for', 'entered', 'exited', 'finished'] | [['phil tufnell', 'ex - er cricket', 'day 1', 'day 15', '1st'], ['john fashanu', 'ex - footballer', 'day 1', 'day 15', '2nd'], ['linda barker', 'changing rooms designer', 'day 1', 'day 15', '3rd'], ['wayne sleep', 'r dance', 'day 1', 'day14', '4th'], ['antony worrall thompson', 'tv chef', 'day 1', 'day 13', '5th'], ['toyah willcox', '1980s pop star', 'day 1', 'day 12', '6th'], ['catalina guirado', 'model', 'day 1', 'day 11', '7th'], ['chris bisson', 'actor', 'day 1', 'day 10', '8th'], ['danniella westbrook', 'actress ( played sam mitchell in eastenders )', 'day 1', 'day 9', '9th']] |
1990 los angeles raiders season | https://en.wikipedia.org/wiki/1990_Los_Angeles_Raiders_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16376436-4.html.csv | count | four of the raider 's games in the 1990 season was played in november . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'november', 'result': '4', 'col': '2', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', 'november'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose date record fuzzily matches to november .', 'tostr': 'filter_eq { all_rows ; date ; november }'}], 'result': '4', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; date ; november } }', 'tointer': 'select the rows whose date record fuzzily matches to november . the number of such rows is 4 .'}, '4'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; date ; november } } ; 4 } = true', 'tointer': 'select the rows whose date record fuzzily matches to november . the number of such rows is 4 .'} | eq { count { filter_eq { all_rows ; date ; november } } ; 4 } = true | select the rows whose date record fuzzily matches to november . the number of such rows is 4 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'date_5': 5, 'november_6': 6, '4_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'date_5': 'date', 'november_6': 'november', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'date_5': [0], 'november_6': [0], '4_7': [2]} | ['week', 'date', 'opponent', 'result', 'attendance'] | [['1', 'september 9 , 1990', 'denver broncos', 'w 14 - 9', '54206'], ['2', 'september 16 , 1990', 'seattle seahawks', 'w 17 - 13', '61889'], ['3', 'september 23 , 1990', 'pittsburgh steelers', 'w 20 - 3', '50657'], ['4', 'september 30 , 1990', 'chicago bears', 'w 24 - 10', '80156'], ['5', 'october 7 , 1990', 'buffalo bills', 'l 38 - 24', '80076'], ['6', 'october 14 , 1990', 'seattle seahawks', 'w 24 - 17', '50624'], ['7', 'october 21 , 1990', 'san diego chargers', 'w 24 - 9', '60569'], ['9', 'november 4 , 1990', 'kansas city chiefs', 'l 9 - 7', '70951'], ['10', 'november 11 , 1990', 'green bay packers', 'l 29 - 16', '50855'], ['11', 'november 19 , 1990', 'miami dolphins', 'w 13 - 10', '70553'], ['12', 'november 25 , 1990', 'kansas city chiefs', 'l 27 - 24', '65710'], ['13', 'december 2 , 1990', 'denver broncos', 'w 23 - 20', '74162'], ['14', 'december 10 , 1990', 'detroit lions', 'w 38 - 31', '72190'], ['15', 'december 16 , 1990', 'cincinnati bengals', 'w 24 - 7', '54132'], ['16', 'december 22 , 1990', 'minnesota vikings', 'w 28 - 24', '53899'], ['17', 'december 30 , 1990', 'san diego chargers', 'w 17 - 12', '62593']] |
1981 senior pga tour | https://en.wikipedia.org/wiki/1981_Senior_PGA_Tour | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11622924-1.html.csv | aggregation | the total payout for all money events during the 1981 senior pga tour was $ 166,000 . | {'scope': 'all', 'col': '7', 'type': 'sum', 'result': '166,000', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', '1st prize'], 'result': '166,000', 'ind': 0, 'tostr': 'sum { all_rows ; 1st prize }'}, '166,000'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; 1st prize } ; 166,000 } = true', 'tointer': 'the sum of the 1st prize record of all rows is 166,000 .'} | round_eq { sum { all_rows ; 1st prize } ; 166,000 } = true | the sum of the 1st prize record of all rows is 166,000 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, '1st prize_4': 4, '166,000_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', '1st prize_4': '1st prize', '166,000_5': '166,000'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], '1st prize_4': [0], '166,000_5': [1]} | ['date', 'tournament', 'location', 'purse', 'winner', 'score', '1st prize'] | [['apr 5', 'michelob - egypt temple senior classic', 'florida', '125000', 'don january ( 2 )', '280 ( - 8 )', '20000'], ['jun 7', 'eureka federal savings classic', 'california', '150000', 'don january ( 3 )', '208 ( - 5 )', '25000'], ['jun 14', 'peter jackson champions', 'canada', '200000', 'miller barber ( 1 )', '204 ( - 6 )', '30000'], ['jun 28', 'marlboro classic', 'massachusetts', '150000', 'bob goalby ( 1 )', '208 ( - 2 )', '25000'], ['jul 12', 'us senior open', 'michigan', '149000', 'arnold palmer ( 2 )', '289 ( 9 )', '26000'], ['oct 18', 'suntree seniors classic', 'florida', '125000', 'miller barber ( 2 )', '204 ( - 12 )', '20000'], ['dec 6', "pga seniors ' championship", 'florida', '125000', 'miller barber ( 3 )', '281 ( - 7 )', '20000']] |
the good wife ( season 2 ) | https://en.wikipedia.org/wiki/The_Good_Wife_%28season_2%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-28561455-1.html.csv | aggregation | season 2 of the good wife episodes written by robert king & michelle king averaged 12.47 million viewers per episode . | {'scope': 'subset', 'col': '7', 'type': 'average', 'result': '12.47', 'subset': {'col': '5', 'criterion': 'equal', 'value': 'robert king & michelle king'}} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'written by', 'robert king & michelle king'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; written by ; robert king & michelle king }', 'tointer': 'select the rows whose written by record fuzzily matches to robert king & michelle king .'}, 'us viewers ( million )'], 'result': '12.47', 'ind': 1, 'tostr': 'avg { filter_eq { all_rows ; written by ; robert king & michelle king } ; us viewers ( million ) }'}, '12.47'], 'result': True, 'ind': 2, 'tostr': 'round_eq { avg { filter_eq { all_rows ; written by ; robert king & michelle king } ; us viewers ( million ) } ; 12.47 } = true', 'tointer': 'select the rows whose written by record fuzzily matches to robert king & michelle king . the average of the us viewers ( million ) record of these rows is 12.47 .'} | round_eq { avg { filter_eq { all_rows ; written by ; robert king & michelle king } ; us viewers ( million ) } ; 12.47 } = true | select the rows whose written by record fuzzily matches to robert king & michelle king . the average of the us viewers ( million ) record of these rows is 12.47 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'avg_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'written by_5': 5, 'robert king & michelle king_6': 6, 'us viewers (million)_7': 7, '12.47_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'avg_1': 'avg', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'written by_5': 'written by', 'robert king & michelle king_6': 'robert king & michelle king', 'us viewers (million)_7': 'us viewers ( million )', '12.47_8': '12.47'} | {'eq_2': [3], 'result_3': [], 'avg_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'written by_5': [0], 'robert king & michelle king_6': [0], 'us viewers (million)_7': [1], '12.47_8': [2]} | ['no in series', 'no in season', 'title', 'directed by', 'written by', 'original air date', 'us viewers ( million )'] | [['24', '1', 'taking control', 'félix alcalá', 'robert king & michelle king', 'september 28 , 2010', '12.84'], ['25', '2', 'double jeopardy', 'dean parisot', 'ted humphrey', 'october 5 , 2010', '12.76'], ['26', '3', 'breaking fast', 'james whitmore , jr', 'corinne brinkerhoff', 'october 12 , 2010', '11.82'], ['27', '4', 'cleaning house', 'rosemary rodriguez', 'robert king & michelle king', 'october 19 , 2010', '12.17'], ['28', '5', 'vip treatment', 'michael zinberg', 'robert king & michelle king', 'october 26 , 2010', '12.59'], ['29', '6', 'poisoned pill', "peter o'fallon", 'keith eisner', 'november 9 , 2010', '12.33'], ['30', '7', 'bad girls', 'jim mckay', 'courtney kemp agboh', 'november 16 , 2010', '11.74'], ['31', '8', 'on tap', 'roxann dawson', 'leonard dick', 'november 23 , 2010', '10.03'], ['32', '9', 'nine hours', 'julie hébert', 'meredith averill', 'december 14 , 2010', '11.84'], ['33', '10', 'breaking up', 'félix alcalá', 'robert king & michelle king', 'january 11 , 2011', '12.29'], ['34', '11', 'two courts', 'tom dicillo', 'ted humphrey', 'january 18 , 2011', '11.43'], ['35', '12', 'silly season', 'rosemary rodriguez', 'corinne brinkerhoff', 'february 1 , 2011', '12.14'], ['40', '17', 'ham sandwich', 'griffin dunne', 'keith eisner', 'march 22 , 2011', '11.70'], ['41', '18', 'killer song', 'james whitmore , jr', 'karen hall', 'march 29 , 2011', '10.16'], ['42', '19', 'wrongful termination', 'phil abraham', 'ted humphrey', 'april 5 , 2011', '10.82']] |
1981 open championship | https://en.wikipedia.org/wiki/1981_Open_Championship | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18169093-6.html.csv | majority | a majority of those in the top ten of the 1981 open championship 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]} | ['place', 'player', 'country', 'score', 'to par', 'money'] | [['1', 'bill rogers', 'united states', '72 + 66 + 67 + 71 = 276', '- 4', '25000'], ['2', 'bernhard langer', 'west germany', '73 + 67 + 70 + 70 = 280', 'e', '17500'], ['t3', 'raymond floyd', 'united states', '74 + 70 + 69 + 70 = 283', '+ 3', '11750'], ['t3', 'mark james', 'england', '72 + 70 + 68 + 73 = 283', '+ 3', '11750'], ['5', 'sam torrance', 'scotland', '72 + 69 + 73 + 70 = 284', '+ 4', '8500'], ['t6', 'bruce lietzke', 'united states', '76 + 69 + 71 + 69 = 285', '+ 5', '7750'], ['t6', 'manuel piñero', 'spain', '73 + 74 + 68 + 70 = 285', '+ 5', '7750'], ['t8', 'howard clark', 'england', '72 + 76 + 70 + 68 = 286', '+ 6', '6500'], ['t8', 'ben crenshaw', 'united states', '72 + 67 + 76 + 71 = 286', '+ 6', '6500'], ['t8', 'brian jones', 'australia', '73 + 76 + 66 + 71 = 286', '+ 6', '6500']] |
1995 - 96 atlanta hawks season | https://en.wikipedia.org/wiki/1995%E2%80%9396_Atlanta_Hawks_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18493036-4.html.csv | superlative | in the games played at the omni centre the highest number of points scored by any team was 124 . | {'scope': 'subset', 'col_superlative': '4', 'row_superlative': '3', 'value_mentioned': 'yes', 'max_or_min': 'max', 'other_col': '5', 'subset': {'col': '5', 'criterion': 'equal', 'value': 'the omni'}} | {'func': 'eq', 'args': [{'func': 'max', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location / attendance', 'the omni'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; location / attendance ; the omni }', 'tointer': 'select the rows whose location / attendance record fuzzily matches to the omni .'}, 'score'], 'result': 'w 124 - 91', 'ind': 1, 'tostr': 'max { filter_eq { all_rows ; location / attendance ; the omni } ; score }', 'tointer': 'select the rows whose location / attendance record fuzzily matches to the omni . the maximum score record of these rows is w 124 - 91 .'}, 'w 124 - 91'], 'result': True, 'ind': 2, 'tostr': 'eq { max { filter_eq { all_rows ; location / attendance ; the omni } ; score } ; w 124 - 91 } = true', 'tointer': 'select the rows whose location / attendance record fuzzily matches to the omni . the maximum score record of these rows is w 124 - 91 .'} | eq { max { filter_eq { all_rows ; location / attendance ; the omni } ; score } ; w 124 - 91 } = true | select the rows whose location / attendance record fuzzily matches to the omni . the maximum score record of these rows is w 124 - 91 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'max_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'location / attendance_5': 5, 'the omni_6': 6, 'score_7': 7, 'w 124 - 91_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'max_1': 'max', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'location / attendance_5': 'location / attendance', 'the omni_6': 'the omni', 'score_7': 'score', 'w 124 - 91_8': 'w 124 - 91'} | {'eq_2': [3], 'result_3': [], 'max_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'location / attendance_5': [0], 'the omni_6': [0], 'score_7': [1], 'w 124 - 91_8': [2]} | ['game', 'date', 'opponent', 'score', 'location / attendance', 'record'] | [['1', 'november 3', 'indiana pacers', 'l 106 - 111', 'the omni', '0 - 1'], ['game', 'date', 'opponent', 'score', 'location / attendance', 'record'], ['2', 'november 4', 'orlando magic', 'w 124 - 91', 'the omni', '1 - 1'], ['3', 'november 6', 'utah jazz', 'l 96 - 105', 'delta center', '1 - 2'], ['4', 'november 8', 'los angeles clippers', 'w 100 - 92', 'los angeles memorial sports arena', '2 - 2'], ['5', 'november 9', 'golden state warriors', 'w 125 - 121', 'oakland coliseum arena', '3 - 2'], ['6', 'november 11', 'dallas mavericks', 'w 113 - 100', 'reunion arena', '4 - 2'], ['7', 'november 14', 'charlotte hornets', 'w 111 - 104', 'the omni', '5 - 2'], ['8', 'november 17', 'miami heat', 'l 88 - 91', 'the omni', '5 - 3'], ['9', 'november 19', 'sacramento kings', 'w 108 - 94', 'arco arena', '6 - 3'], ['10', 'november 21', 'denver nuggets', 'l 99 - 107', 'mcnichols sports arena', '6 - 4'], ['11', 'november 22', 'phoenix suns', 'l 112 - 117', 'america west arena', '6 - 5'], ['12', 'november 25', 'toronto raptors', 'w 114 - 102', 'the omni', '7 - 5'], ['13', 'november 28', 'new york knicks', 'w 102 - 97 ( ot )', 'madison square garden', '8 - 5'], ['14', 'november 29', 'philadelphia 76ers', 'w 106 - 81', 'the omni', '9 - 5']] |
wru division five south west | https://en.wikipedia.org/wiki/WRU_Division_Five_South_West | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17675675-1.html.csv | unique | penian rfc was the only team in the division that did n't play any games at all . | {'scope': 'all', 'row': '13', 'col': '2', 'col_other': '1', 'criterion': 'equal', 'value': '0', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'played', '0'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose played record is equal to 0 .', 'tostr': 'filter_eq { all_rows ; played ; 0 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; played ; 0 } }', 'tointer': 'select the rows whose played record is equal to 0 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'played', '0'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose played record is equal to 0 .', 'tostr': 'filter_eq { all_rows ; played ; 0 }'}, 'club'], 'result': 'penlan rfc', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; played ; 0 } ; club }'}, 'penlan rfc'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; played ; 0 } ; club } ; penlan rfc }', 'tointer': 'the club record of this unqiue row is penlan rfc .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; played ; 0 } } ; eq { hop { filter_eq { all_rows ; played ; 0 } ; club } ; penlan rfc } } = true', 'tointer': 'select the rows whose played record is equal to 0 . there is only one such row in the table . the club record of this unqiue row is penlan rfc .'} | and { only { filter_eq { all_rows ; played ; 0 } } ; eq { hop { filter_eq { all_rows ; played ; 0 } ; club } ; penlan rfc } } = true | select the rows whose played record is equal to 0 . there is only one such row in the table . the club record of this unqiue row is penlan rfc . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'played_7': 7, '0_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'club_9': 9, 'penlan rfc_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'played_7': 'played', '0_8': '0', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'club_9': 'club', 'penlan rfc_10': 'penlan rfc'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'played_7': [0], '0_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'club_9': [2], 'penlan rfc_10': [3]} | ['club', 'played', 'drawn', 'lost', 'points for', 'points against', 'tries for', 'tries against', 'try bonus', 'losing bonus', 'points'] | [['club', 'played', 'drawn', 'lost', 'points for', 'points against', 'tries for', 'tries against', 'try bonus', 'losing bonus', 'points'], ['birchgrove rfc', '20', '0', '3', '538', '257', '82', '29', '13', '2', '83'], ['neath athletic rfc', '20', '0', '3', '616', '194', '89', '24', '12', '2', '82'], ['trebanos rfc', '20', '0', '3', '701', '223', '99', '27', '13', '0', '81'], ['gowerton rfc', '20', '0', '9', '439', '389', '55', '52', '5', '5', '54'], ['llandybie rfc', '20', '0', '9', '338', '374', '38', '55', '4', '3', '51'], ['alltwen rfc', '20', '1', '10', '445', '382', '50', '42', '5', '4', '47'], ['crynant rfc', '20', '0', '12', '315', '454', '43', '66', '4', '3', '39'], ['glais rfc', '20', '1', '13', '233', '444', '33', '64', '0', '1', '27'], ['tycroes rfc', '20', '0', '15', '250', '617', '32', '88', '3', '3', '26'], ['cwmtwrch rfc', '20', '2', '14', '179', '466', '25', '66', '1', '1', '22'], ['cwmgors rfc', '20', '0', '17', '206', '460', '31', '64', '3', '6', '21'], ['penlan rfc', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0']] |
spain men 's national volleyball team | https://en.wikipedia.org/wiki/Spain_men%27s_national_volleyball_team | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-13312864-1.html.csv | superlative | josé luis moltó is the tallest player on the spain men 's national volleyball team . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '9', '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', 'height'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; height }'}, 'player'], 'result': 'josé luis moltó', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; height } ; player }'}, 'josé luis moltó'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; height } ; player } ; josé luis moltó } = true', 'tointer': 'select the row whose height record of all rows is maximum . the player record of this row is josé luis moltó .'} | eq { hop { argmax { all_rows ; height } ; player } ; josé luis moltó } = true | select the row whose height record of all rows is maximum . the player record of this row is josé luis moltó . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'height_5': 5, 'player_6': 6, 'josé luis moltó_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'height_5': 'height', 'player_6': 'player', 'josé luis moltó_7': 'josé luis moltó'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'height_5': [0], 'player_6': [1], 'josé luis moltó_7': [2]} | ['shirt no', 'player', 'birth date', 'weight', 'height'] | [['1', 'rafael pascual', '16 march 1970', '94', '194'], ['2', 'ibán pérez', '13 november 1983', '89', '198'], ['3', 'josé luis lobato', '19 february 1977', '81', '186'], ['4', 'manuel sevillano', '2 july 1981', '90', '194'], ['7', 'guillermo hernán', '25 july 1982', '68', '181'], ['10', 'miguel ángel falasca', '29 april 1973', '92', '195'], ['11', 'javier subiela', '22 march 1984', '88', '198'], ['12', 'guillermo falasca', '24 october 1977', '104', '200'], ['14', 'josé luis moltó', '29 june 1975', '95', '207'], ['16', 'julián garcía - torres', '8 november 1980', '93', '202'], ['17', 'enrique de la fuente', '11 august 1975', '95', '195']] |
northeast delta dental international | https://en.wikipedia.org/wiki/Northeast_Delta_Dental_International | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15315276-1.html.csv | unique | 2011 is the only year that the northeast delta dental international tournament was won by a canadian . | {'scope': 'all', 'row': '3', 'col': '4', 'col_other': '1', 'criterion': 'equal', 'value': 'canada', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'canada'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose country record fuzzily matches to canada .', 'tostr': 'filter_eq { all_rows ; country ; canada }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; country ; canada } }', 'tointer': 'select the rows whose country record fuzzily matches to canada . there is only one such row in the table .'}, {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'canada'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose country record fuzzily matches to canada .', 'tostr': 'filter_eq { all_rows ; country ; canada }'}, 'year'], 'result': '2011', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; country ; canada } ; year }'}, '2011'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; country ; canada } ; year } ; 2011 }', 'tointer': 'the year record of this unqiue row is 2011 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; country ; canada } } ; eq { hop { filter_eq { all_rows ; country ; canada } ; year } ; 2011 } } = true', 'tointer': 'select the rows whose country record fuzzily matches to canada . there is only one such row in the table . the year record of this unqiue row is 2011 .'} | and { only { filter_eq { all_rows ; country ; canada } } ; eq { hop { filter_eq { all_rows ; country ; canada } ; year } ; 2011 } } = true | select the rows whose country record fuzzily matches to canada . there is only one such row in the table . the year record of this unqiue row is 2011 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'country_7': 7, 'canada_8': 8, 'eq_3': 3, 'num_hop_2': 2, 'year_9': 9, '2011_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'country_7': 'country', 'canada_8': 'canada', 'eq_3': 'eq', 'num_hop_2': 'num_hop', 'year_9': 'year', '2011_10': '2011'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'country_7': [0], 'canada_8': [0], 'eq_3': [4], 'num_hop_2': [3], 'year_9': [2], '2011_10': [3]} | ['year', 'dates', 'champion', 'country', 'score', 'tournament location', 'purse', "winner 's share"] | [['2013', 'jul 19 - 21', 'pk kongkraphan', 'thailand', '207 ( 9 )', 'beaver meadow golf course', '100000', '15000'], ['2012', 'jul 20 - 22', 'jenny gleason', 'united states', '211 ( 5 )', 'beaver meadow golf course', '100000', '15000'], ['2011', 'jul 22 - 24', 'jessica shepley', 'canada', '203 ( 13 )', 'beaver meadow golf course', '100000', '14000'], ['2010', 'jul 19 - 25', 'jenny shin', 'united states', '205 ( 11 )', 'beaver meadow golf course', '110000', '15400'], ['2009', 'jul 24 - 26', 'misun cho', 'south korea', '207 ( 9 )', 'beaver meadow golf course', '90000', '12600'], ['2008', 'jul 25 - 27', 'mo martin', 'united states', '204 ( 12 )', 'beaver meadow golf course', '80000', '11200'], ['2007', 'aug 3 - 5', 'ji min jeong', 'south korea', '209 ( 7 )', 'beaver meadow golf course', '75000', '10500'], ['2006', 'aug 4 - 6', 'charlotte mayorkas', 'united states', '207 ( 9 )', 'beaver meadow golf course', '70000', '9800'], ['2005', 'jul 22 - 24', 'kyeong bae', 'south korea', '209 ( 7 )', 'beaver meadow golf course', '65000', '9100'], ['2004', 'jul 16 - 18', 'erica blasberg', 'united states', '201 ( 15 )', 'canterbury woods country club', '65000', '9100']] |
list of england national rugby union team results 1990 - 99 | https://en.wikipedia.org/wiki/List_of_England_national_rugby_union_team_results_1990%E2%80%9399 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18178534-1.html.csv | comparative | france scored more points than wales against the england national rugby union team . | {'row_1': '2', 'row_2': '3', 'col': '2', 'col_other': '1', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opposing teams', 'france'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose opposing teams record fuzzily matches to france .', 'tostr': 'filter_eq { all_rows ; opposing teams ; france }'}, 'against'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; opposing teams ; france } ; against }', 'tointer': 'select the rows whose opposing teams record fuzzily matches to france . take the against record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opposing teams', 'wales'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose opposing teams record fuzzily matches to wales .', 'tostr': 'filter_eq { all_rows ; opposing teams ; wales }'}, 'against'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; opposing teams ; wales } ; against }', 'tointer': 'select the rows whose opposing teams record fuzzily matches to wales . take the against record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; opposing teams ; france } ; against } ; hop { filter_eq { all_rows ; opposing teams ; wales } ; against } } = true', 'tointer': 'select the rows whose opposing teams record fuzzily matches to france . take the against record of this row . select the rows whose opposing teams record fuzzily matches to wales . take the against record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; opposing teams ; france } ; against } ; hop { filter_eq { all_rows ; opposing teams ; wales } ; against } } = true | select the rows whose opposing teams record fuzzily matches to france . take the against record of this row . select the rows whose opposing teams record fuzzily matches to wales . take the against 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, 'opposing teams_7': 7, 'france_8': 8, 'against_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'opposing teams_11': 11, 'wales_12': 12, 'against_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', 'opposing teams_7': 'opposing teams', 'france_8': 'france', 'against_9': 'against', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'opposing teams_11': 'opposing teams', 'wales_12': 'wales', 'against_13': 'against'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'opposing teams_7': [0], 'france_8': [0], 'against_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'opposing teams_11': [1], 'wales_12': [1], 'against_13': [3]} | ['opposing teams', 'against', 'date', 'venue', 'status'] | [['ireland', '0', '20 / 01 / 1990', 'twickenham , london', 'five nations'], ['france', '7', '03 / 02 / 1990', 'parc des princes , paris', 'five nations'], ['wales', '6', '17 / 02 / 1990', 'twickenham , london', 'five nations'], ['scotland', '13', '17 / 03 / 1990', 'murrayfield , edinburgh', 'five nations'], ['argentina', '12', '28 / 07 / 1990', 'vélez sársfield , buenos aires', 'first test'], ['argentina', '15', '04 / 08 / 1990', 'vélez sársfield , buenos aires', 'second test'], ['argentina', '0', '03 / 11 / 1990', 'twickenham , london', 'test match']] |
1980 open championship | https://en.wikipedia.org/wiki/1980_Open_Championship | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18171018-5.html.csv | superlative | in the 1980 open championship , lee trevino ranks the highest . | {'scope': 'all', 'col_superlative': '1', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '2', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmin', 'args': ['all_rows', 'place'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; place }'}, 'player'], 'result': 'lee trevino', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; place } ; player }'}, 'lee trevino'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmin { all_rows ; place } ; player } ; lee trevino } = true', 'tointer': 'select the row whose place record of all rows is minimum . the player record of this row is lee trevino .'} | eq { hop { argmin { all_rows ; place } ; player } ; lee trevino } = true | select the row whose place record of all rows is minimum . the player record of this row is lee trevino . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'place_5': 5, 'player_6': 6, 'lee trevino_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'place_5': 'place', 'player_6': 'player', 'lee trevino_7': 'lee trevino'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'place_5': [0], 'player_6': [1], 'lee trevino_7': [2]} | ['place', 'player', 'country', 'score', 'to par'] | [['1', 'lee trevino', 'united states', '68 + 67 = 135', '- 7'], ['t2', 'ken brown', 'scotland', '70 + 68 = 138', '- 4'], ['t2', 'jerry pate', 'united states', '71 + 67 = 138', '- 4'], ['t2', 'tom watson', 'united states', '68 + 70 = 138', '- 4'], ['t5', 'seve ballesteros', 'spain', '72 + 68 = 140', '- 2'], ['t5', 'andy bean', 'united states', '71 + 69 = 140', '- 2'], ['t5', 'ben crenshaw', 'united states', '70 + 70 = 140', '- 2'], ['t5', 'gil morgan', 'united states', '70 + 70 = 140', '- 2'], ['t5', 'jack newton', 'australia', '69 + 71 = 140', '- 2'], ['t5', 'jack nicklaus', 'united states', '73 + 67 = 140', '- 2']] |
pol espargaró | https://en.wikipedia.org/wiki/Pol_Espargar%C3%B3 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16546257-1.html.csv | comparative | pol espargaró had more podium finishes in the 2010 season than the 2011 season . | {'row_1': '5', 'row_2': '6', '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', 'season', '2010'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose season record fuzzily matches to 2010 .', 'tostr': 'filter_eq { all_rows ; season ; 2010 }'}, 'podium'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; season ; 2010 } ; podium }', 'tointer': 'select the rows whose season record fuzzily matches to 2010 . take the podium record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'season', '2011'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose season record fuzzily matches to 2011 .', 'tostr': 'filter_eq { all_rows ; season ; 2011 }'}, 'podium'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; season ; 2011 } ; podium }', 'tointer': 'select the rows whose season record fuzzily matches to 2011 . take the podium record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; season ; 2010 } ; podium } ; hop { filter_eq { all_rows ; season ; 2011 } ; podium } } = true', 'tointer': 'select the rows whose season record fuzzily matches to 2010 . take the podium record of this row . select the rows whose season record fuzzily matches to 2011 . take the podium record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; season ; 2010 } ; podium } ; hop { filter_eq { all_rows ; season ; 2011 } ; podium } } = true | select the rows whose season record fuzzily matches to 2010 . take the podium record of this row . select the rows whose season record fuzzily matches to 2011 . take the podium 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, 'season_7': 7, '2010_8': 8, 'podium_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'season_11': 11, '2011_12': 12, 'podium_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', 'season_7': 'season', '2010_8': '2010', 'podium_9': 'podium', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'season_11': 'season', '2011_12': '2011', 'podium_13': 'podium'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'season_7': [0], '2010_8': [0], 'podium_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'season_11': [1], '2011_12': [1], 'podium_13': [3]} | ['season', 'race', 'podium', 'pole', 'flap'] | [['2006', '7', '0', '0', '0'], ['2007', '17', '1', '0', '0'], ['2008', '14', '3', '2', '1'], ['2009', '16', '5', '1', '1'], ['2010', '17', '12', '0', '3'], ['2011', '17', '2', '0', '1'], ['2012', '17', '11', '8', '5'], ['2013', '16', '10', '5', '4'], ['total', '121', '44', '16', '15']] |
thai clubs in the afc cup | https://en.wikipedia.org/wiki/Thai_clubs_in_the_AFC_Cup | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16707879-4.html.csv | count | 2 games of the thai clubs in the afc cup occurred in syria . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'syria', 'result': '2', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'venue', 'syria'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose venue record fuzzily matches to syria .', 'tostr': 'filter_eq { all_rows ; venue ; syria }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; venue ; syria } }', 'tointer': 'select the rows whose venue record fuzzily matches to syria . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; venue ; syria } } ; 2 } = true', 'tointer': 'select the rows whose venue record fuzzily matches to syria . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; venue ; syria } } ; 2 } = true | select the rows whose venue record fuzzily matches to syria . 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, 'venue_5': 5, 'syria_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', 'venue_5': 'venue', 'syria_6': 'syria', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'venue_5': [0], 'syria_6': [0], '2_7': [2]} | ['season', 'team 1', 'score', 'team 2', 'venue'] | [['2010', 'south china', '0:0', 'muangthong united', 'hong kong stadium , hong kong'], ['2010', 'muangthong united', '3:1', 'vb sports club', 'yamaha stadium ( thailand )'], ['2010', 'muangthong united', '4:1', 'persiwa wamena', 'yamaha stadium ( thailand )'], ['2010', 'vb sports club', '2:3', 'muangthong united', 'national stadium , maldives'], ['2010', 'muangthong united', '0:1', 'south china', 'surakul stadium , thailand'], ['2010', 'persiwa wamena', '2:2', 'muangthong united', 'gajayana stadium , indonesia'], ['2010', 'al - rayyan', '1:1 ( aet ) ( 2:4 p )', 'muangthong united', 'umm - affai stadium , qatar'], ['2010', 'al - karamah', '1:0', 'muangthong united', 'khaled bin walid stadium , syria'], ['2010', 'muangthong united', '2:0', 'al - karamah', 'yamaha stadium ( thailand )'], ['2010', 'muangthong united', '1:0', 'al - ittihad', 'yamaha stadium ( thailand )'], ['2010', 'al - ittihad', '2:0', 'muangthong united', 'aleppo international stadium , syria'], ['2011', 'muangthong united', '4:0', 't & t hanoi', 'scg stadium , thailand'], ['2011', 'tampines rovers', '1:1', 'muangthong united', 'jalan besar stadium , singapore'], ['2011', 'muangthong united', '1:0', 'victory sc', 'scg stadium , thailand'], ['2011', 'victory sc', '0:4', 'muangthong united', 'national stadium , maldives'], ['2011', 't & t hanoi', '0:0', 'muangthong united', 'hang day stadium , vietnam'], ['2011', 'muangthong united', '4:0', 'tampines rovers', 'scg stadium , thailand'], ['2011', 'muangthong united', '4:0', 'al ahed', 'scg stadium , thailand'], ['2011', 'kuwait sc', '1:0', 'muangthong united', 'al kuwait sports club stadium , kuwait'], ['2011', 'muangthong united', '0:0', 'kuwait sc', 'scg stadium , thailand']] |
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/2-17100961-35.html.csv | unique | bob briggs was the only fb selected in the washington redskins draft . | {'scope': 'all', 'row': '5', 'col': '5', 'col_other': '4', 'criterion': 'equal', 'value': 'fb', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'position', 'fb'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose position record fuzzily matches to fb .', 'tostr': 'filter_eq { all_rows ; position ; fb }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; position ; fb } }', 'tointer': 'select the rows whose position record fuzzily matches to fb . 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', 'fb'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose position record fuzzily matches to fb .', 'tostr': 'filter_eq { all_rows ; position ; fb }'}, 'name'], 'result': 'bob briggs', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; position ; fb } ; name }'}, 'bob briggs'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; position ; fb } ; name } ; bob briggs }', 'tointer': 'the name record of this unqiue row is bob briggs .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; position ; fb } } ; eq { hop { filter_eq { all_rows ; position ; fb } ; name } ; bob briggs } } = true', 'tointer': 'select the rows whose position record fuzzily matches to fb . there is only one such row in the table . the name record of this unqiue row is bob briggs .'} | and { only { filter_eq { all_rows ; position ; fb } } ; eq { hop { filter_eq { all_rows ; position ; fb } ; name } ; bob briggs } } = true | select the rows whose position record fuzzily matches to fb . there is only one such row in the table . the name record of this unqiue row is bob briggs . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'position_7': 7, 'fb_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'name_9': 9, 'bob briggs_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', 'fb_8': 'fb', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'name_9': 'name', 'bob briggs_10': 'bob briggs'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'position_7': [0], 'fb_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'name_9': [2], 'bob briggs_10': [3]} | ['round', 'pick', 'overall', 'name', 'position', 'college'] | [['2', '7', '21', 'bob breitenstein', 'ot', 'tulsa'], ['3', '6', '34', 'kent mccloughan', 'cb', 'nebraska'], ['8', '7', '105', 'don croftcheck', 'g', 'indiana'], ['9', '6', '118', 'jerry smith', 'te', 'arizona state'], ['10', '7', '133', 'bob briggs', 'fb', 'central state'], ['11', '6', '146', 'willie adams', 'de', 'new mexico state'], ['12', '6', '160', 'john strohmeyer', 'ot', 'michigan'], ['13', '6', '174', 'biff bracy', 'hb', 'duke'], ['14', '7', '189', 'dave estrada', 'hb', 'arizona state'], ['15', '6', '202', 'ben baldwin', 'rb', 'vanderbilt'], ['16', '7', '217', 'bob reed', 'g', 'tennessee a & i'], ['17', '6', '230', 'gary hart', 'e', 'vanderbilt'], ['18', '7', '245', 'chris hanburger', 'lb', 'north carolina'], ['19', '6', '258', 'roosevelt ellerbe', 'rb', 'iowa state']] |
united states house of representatives elections , 1998 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1998 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1341453-44.html.csv | comparative | jimmy duncan jr was first elected to the united states house of representatives earlier than zach wamp . | {'row_1': '2', 'row_2': '3', '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', 'jimmy duncan jr'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose incumbent record fuzzily matches to jimmy duncan jr .', 'tostr': 'filter_eq { all_rows ; incumbent ; jimmy duncan jr }'}, 'first elected'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; incumbent ; jimmy duncan jr } ; first elected }', 'tointer': 'select the rows whose incumbent record fuzzily matches to jimmy duncan jr . take the first elected record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'incumbent', 'zach wamp'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose incumbent record fuzzily matches to zach wamp .', 'tostr': 'filter_eq { all_rows ; incumbent ; zach wamp }'}, 'first elected'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; incumbent ; zach wamp } ; first elected }', 'tointer': 'select the rows whose incumbent record fuzzily matches to zach wamp . take the first elected record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; incumbent ; jimmy duncan jr } ; first elected } ; hop { filter_eq { all_rows ; incumbent ; zach wamp } ; first elected } } = true', 'tointer': 'select the rows whose incumbent record fuzzily matches to jimmy duncan jr . take the first elected record of this row . select the rows whose incumbent record fuzzily matches to zach wamp . take the first elected record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; incumbent ; jimmy duncan jr } ; first elected } ; hop { filter_eq { all_rows ; incumbent ; zach wamp } ; first elected } } = true | select the rows whose incumbent record fuzzily matches to jimmy duncan jr . take the first elected record of this row . select the rows whose incumbent record fuzzily matches to zach wamp . 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, 'jimmy duncan jr_8': 8, 'first elected_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'incumbent_11': 11, 'zach wamp_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', 'jimmy duncan jr_8': 'jimmy duncan jr', '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', 'zach wamp_12': 'zach wamp', '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], 'jimmy duncan jr_8': [0], 'first elected_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'incumbent_11': [1], 'zach wamp_12': [1], 'first elected_13': [3]} | ['district', 'incumbent', 'party', 'first elected', 'results', 'candidates'] | [['tennessee 1', 'william l jenkins', 'republican', '1996', 're - elected', 'william l jenkins ( r ) 69 % kay white ( d ) 31 %'], ['tennessee 2', 'jimmy duncan jr', 'republican', '1988', 're - elected', 'jimmy duncan jr ( r ) unopposed'], ['tennessee 3', 'zach wamp', 'republican', '1994', 're - elected', 'zach wamp ( r ) 67 % lewis lewis ( d ) 33 %'], ['tennessee 4', 'van hilleary', 'republican', '1994', 're - elected', 'van hilleary ( r ) 60 % jerry d cooper ( d ) 40 %'], ['tennessee 5', 'bob clement', 'democratic', '1988', 're - elected', 'bob clement ( d ) 83 %'], ['tennessee 6', 'bart gordon', 'democratic', '1984', 're - elected', 'bart gordon ( d ) 55 % walt massey ( r ) 45 %'], ['tennessee 7', 'ed bryant', 'republican', '1994', 're - elected', 'ed bryant ( r ) unopposed'], ['tennessee 8', 'john tanner', 'democratic', '1988', 're - elected', 'john tanner ( d ) unopposed']] |
roy scheider | https://en.wikipedia.org/wiki/Roy_Scheider | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-164370-1.html.csv | aggregation | roy scheider 's matches in 1948 lasted a total of 4 rounds . | {'scope': 'subset', 'col': '5', 'type': 'sum', 'result': '4', 'subset': {'col': '4', 'criterion': 'fuzzily_match', 'value': '1948'}} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', '1948'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; date ; 1948 }', 'tointer': 'select the rows whose date record fuzzily matches to 1948 .'}, 'round'], 'result': '4', 'ind': 1, 'tostr': 'sum { filter_eq { all_rows ; date ; 1948 } ; round }'}, '4'], 'result': True, 'ind': 2, 'tostr': 'round_eq { sum { filter_eq { all_rows ; date ; 1948 } ; round } ; 4 } = true', 'tointer': 'select the rows whose date record fuzzily matches to 1948 . the sum of the round record of these rows is 4 .'} | round_eq { sum { filter_eq { all_rows ; date ; 1948 } ; round } ; 4 } = true | select the rows whose date record fuzzily matches to 1948 . the sum of the round record of these rows is 4 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'sum_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'date_5': 5, '1948_6': 6, 'round_7': 7, '4_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', '1948_6': '1948', 'round_7': 'round', '4_8': '4'} | {'eq_2': [3], 'result_3': [], 'sum_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'date_5': [0], '1948_6': [0], 'round_7': [1], '4_8': [2]} | ['result', 'opponent', 'method', 'date', 'round'] | [['win', 'ted lascalza', 'ko', '1958', '1'], ['win', 'nick welling', 'ko', 'july 20 , 1953', '2'], ['win', 'earl garrett', 'ko', '1950', '1'], ['win', 'peter read', 'ko', '1950', '3'], ['win', 'phillip duncan', 'ko', 'february 17 , 1950', '1'], ['win', 'myron greenberg', 'ko', '1950', '1'], ['win', 'peter read', 'ko', 'february 21 , 1948', '2'], ['win', 'jerry gould', 'ko', '1948', '1'], ['win', "alfonse d'amore", 'ko', '1948', '1'], ['loss', 'myron greenberg', 'tko', 'march 5 , 1947', '2']] |
1992 open championship | https://en.wikipedia.org/wiki/1992_Open_Championship | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18122130-4.html.csv | majority | the majority of players came from the united states in the 1992 open championship . | {'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]} | ['place', 'player', 'country', 'score', 'to par'] | [['t1', 'raymond floyd', 'united states', '64', '- 7'], ['t1', 'steve pate', 'united states', '64', '- 7'], ['t3', 'gordon brand , jnr', 'scotland', '65', '- 6'], ['t3', 'ian woosnam', 'wales', '65', '- 6'], ['t5', 'john cook', 'united states', '66', '- 5'], ['t5', 'ernie els', 'south africa', '66', '- 5'], ['t5', 'nick faldo', 'england', '66', '- 5'], ['t5', 'lee janzen', 'united states', '66', '- 5'], ['t9', 'per - ulrik johansson', 'sweden', '67', '- 4'], ['t9', 'andrew magee', 'united states', '67', '- 4'], ['t9', 'rocco mediate', 'united states', '67', '- 4'], ['t9', 'craig parry', 'australia', '67', '- 4'], ['t9', 'costantino rocca', 'italy', '67', '- 4'], ['t9', 'orrin vincent iii', 'united states', '67', '- 4']] |
1957 world wrestling championships | https://en.wikipedia.org/wiki/1957_World_Wrestling_Championships | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16852841-1.html.csv | unique | only the soviet union won three silver medals . | {'scope': 'all', 'row': '2', 'col': '4', 'col_other': '2', 'criterion': 'equal', 'value': '3', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'silver', '3'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose silver record is equal to 3 .', 'tostr': 'filter_eq { all_rows ; silver ; 3 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; silver ; 3 } }', 'tointer': 'select the rows whose silver record is equal to 3 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'silver', '3'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose silver record is equal to 3 .', 'tostr': 'filter_eq { all_rows ; silver ; 3 }'}, 'nation'], 'result': 'soviet union', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; silver ; 3 } ; nation }'}, 'soviet union'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; silver ; 3 } ; nation } ; soviet union }', 'tointer': 'the nation record of this unqiue row is soviet union .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; silver ; 3 } } ; eq { hop { filter_eq { all_rows ; silver ; 3 } ; nation } ; soviet union } } = true', 'tointer': 'select the rows whose silver record is equal to 3 . there is only one such row in the table . the nation record of this unqiue row is soviet union .'} | and { only { filter_eq { all_rows ; silver ; 3 } } ; eq { hop { filter_eq { all_rows ; silver ; 3 } ; nation } ; soviet union } } = true | select the rows whose silver record is equal to 3 . there is only one such row in the table . the nation record of this unqiue row is soviet union . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'silver_7': 7, '3_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'nation_9': 9, 'soviet union_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'silver_7': 'silver', '3_8': '3', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'nation_9': 'nation', 'soviet union_10': 'soviet union'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'silver_7': [0], '3_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'nation_9': [2], 'soviet union_10': [3]} | ['rank', 'nation', 'gold', 'silver', 'bronze', 'total'] | [['1', 'turkey', '4', '2', '2', '8'], ['2', 'soviet union', '2', '3', '1', '6'], ['3', 'iran', '1', '1', '0', '2'], ['4', 'bulgaria', '1', '0', '2', '3'], ['5', 'finland', '0', '1', '0', '1'], ['5', 'west germany', '0', '1', '0', '1'], ['7', 'japan', '0', '0', '2', '2'], ['8', 'italy', '0', '0', '1', '1'], ['total', 'total', '8', '8', '8', '24']] |
wtbs - ld | https://en.wikipedia.org/wiki/WTBS-LD | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1097268-1.html.csv | majority | the majority of the channels have video in 480i . | {'scope': 'all', 'col': '2', 'most_or_all': 'most', 'criterion': 'equal', 'value': '480i', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'video', '480i'], 'result': True, 'ind': 0, 'tointer': 'for the video records of all rows , most of them fuzzily match to 480i .', 'tostr': 'most_eq { all_rows ; video ; 480i } = true'} | most_eq { all_rows ; video ; 480i } = true | for the video records of all rows , most of them fuzzily match to 480i . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'video_3': 3, '480i_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'video_3': 'video', '480i_4': '480i'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'video_3': [0], '480i_4': [0]} | ['channel', 'video', 'aspect', 'psip short name', 'programming'] | [['26.1', '1080i', '16:9', 'mfox', 'mundofox'], ['26.2', '480i', '4:3', 'lwn', 'live well network'], ['26.4', '480i', '4:3', 'jtv', 'jewelry tv'], ['26.5', '480i', '4:3', 'f24news', 'france 24 blank screen'], ['26.8', '480i', '4:3', 'tuff tv', 'tuff tv']] |
the general in his labyrinth | https://en.wikipedia.org/wiki/The_General_in_His_Labyrinth | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1162324-1.html.csv | majority | most of the books in the series have less that 300 pages all together . | {'scope': 'all', 'col': '6', 'most_or_all': 'most', 'criterion': 'less_than_eq', 'value': '300', 'subset': None} | {'func': 'most_less_eq', 'args': ['all_rows', 'pages', '300'], 'result': True, 'ind': 0, 'tointer': 'for the pages records of all rows , most of them are less than or equal to 300 .', 'tostr': 'most_less_eq { all_rows ; pages ; 300 } = true'} | most_less_eq { all_rows ; pages ; 300 } = true | for the pages records of all rows , most of them are less than or equal to 300 . | 1 | 1 | {'most_less_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'pages_3': 3, '300_4': 4} | {'most_less_eq_0': 'most_less_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'pages_3': 'pages', '300_4': '300'} | {'most_less_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'pages_3': [0], '300_4': [0]} | ['year', 'language', 'title', 'translator', 'company', 'pages'] | [['1989', 'arabic', 'al - jiniral fi matahatihi', 'salih ilmani', 'nicosia : ibal', '287'], ['1989', 'german', 'der general in seinem labyrinth : roman', 'dagmar ploetz', 'cologne : kiepenheuer & witsch', '359'], ['1989', 'swedish', 'generalen i sin labyrint', 'jens nordenhök', 'stockholm : wahlström & widstrand', '267'], ['1989', 'portuguese', 'o general em seu labirinto', 'moacir werneck de castro', 'rio de janeiro : editora record', '281'], ['1990', 'english', 'the general in his labyrinth', 'edith grossman', 'new york city : alfred a knopf', '285'], ['1990', 'french', 'le général dans son labyrinthe', 'annie morvan', 'paris : b grasset', '318'], ['1990', 'turkish', 'labirentindeki general', 'inci kut', 'istanbul : can yayınları', '253'], ['1990', 'basque', 'jenerala bere laberintoan', 'xabier mendiguren', 'donostia - san sebastián , spain : eikar', '279'], ['1991', 'hebrew', 'general be - mavokh', 'ritah meltser and amatsyah porat', 'tel aviv : am oved', '205'], ['1991', 'japanese', 'meikyu no shogun', 'kimura eiichi', 'tokyo : shinchosha', '323'], ['1991', 'persian', 'zhiniral dar hazar tu - yi khvad', 'hushang asadi ( based on the english version )', 'tehran : kitab - i mahnaz', '237'], ['1992', 'hungarian', 'a tábornok útvesztője', 'tomcsányi zsuzsanna', 'budapest : magvető', '254'], ['1992 , 1996', 'italian', 'il generale nel suo labirinto', 'angelo morino', 'milan : mondadori', '286'], ['1993', 'polish', 'generał w labiryncie', 'zofia wasitowa', 'warsaw : pánstwowy instytut wydawniczy', '285'], ['1995', 'chinese', 'mi gong zhong di jiang jun', 'chengdong yin', 'taipei : yun chen wen hua shi ye', '321'], ['1996', 'dutch', 'de generaal in zijn labyrint', 'mieke westra', 'amsterdam : meulenhoff , 3rd ed', '317'], ['1996', 'romanian', 'generalul în labirintul său', 'mihaela dumitrescu', 'bucharest : rao', '256'], ['1999', 'vietnamese', 'tướng qun giữa mê hồn trận', 'nguyễn trung đức', 'hanoi : hội nhà văn', '394'], ['2000', 'albanian', 'gjenerali në labirintin e vet : roman', 'nasi lera', 'tirana : mësonjëtorja e parë', '305'], ['nm', 'greek', 'ο στρατηγός μες στο λαβύρινθό του', 'klaiti sotiriadou - barajas', 'athens : livanis publications', '309']] |
2005 masters tournament | https://en.wikipedia.org/wiki/2005_Masters_Tournament | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16147528-2.html.csv | majority | the majority of players in the 2005 masters tournament are from the united states . | {'scope': 'all', 'col': '2', '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]} | ['player', 'country', 'year ( s ) won', 'total', 'to par', 'finish'] | [['tiger woods', 'united states', '1997 , 2001 , 2002', '276', '- 12', '1'], ['vijay singh', 'fiji', '2000', '284', '- 4', 't5'], ['mike weir', 'canada', '2003', '284', '- 4', 't5'], ['phil mickelson', 'united states', '2004', '285', '- 3', '10'], ['bernhard langer', 'germany', '1985 , 1993', '289', '+ 1', 't20'], ["mark o'meara", 'united states', '1998', '293', '+ 5', 't31'], ['fred couples', 'united states', '1992', '295', '+ 7', 't39'], ['craig stadler', 'united states', '1982', '306', '+ 18', '50']] |
driver deaths in motorsport | https://en.wikipedia.org/wiki/Driver_deaths_in_motorsport | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1632486-11.html.csv | count | two of the motorsport driver deaths were in qualifying sessions . | {'scope': 'all', 'criterion': 'equal', 'value': 'qualifying', 'result': '2', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'session', 'qualifying'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose session record fuzzily matches to qualifying .', 'tostr': 'filter_eq { all_rows ; session ; qualifying }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; session ; qualifying } }', 'tointer': 'select the rows whose session record fuzzily matches to qualifying . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; session ; qualifying } } ; 2 } = true', 'tointer': 'select the rows whose session record fuzzily matches to qualifying . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; session ; qualifying } } ; 2 } = true | select the rows whose session record fuzzily matches to qualifying . 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, 'session_5': 5, 'qualifying_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', 'session_5': 'session', 'qualifying_6': 'qualifying', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'session_5': [0], 'qualifying_6': [0], '2_7': [2]} | ['discipline', 'championship', 'circuit', 'event', 'session'] | [['stock car', 'sprint cup series', 'daytona international speedway', 'uno twin 125 qualifiers', 'qualifying'], ['stock car', 'whelen modified tour', 'martinsville speedway', 'winn - dixie 500', 'race'], ['drag racing', 'nhra winston drag racing series', 'indianapolis raceway park', 'mac tools us nationals', 'qualifying'], ['stock car', 'arca series', 'daytona international speedway', 'daytona arca 200', 'race'], ['open wheel', 'usac national championship', 'williams grove speedway', 'indianapolis sweepstakes', 'race']] |
united states house of representatives elections , 1936 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1936 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1342315-4.html.csv | ordinal | william j driver is the incumbent of the 1936 house of representatives elections with the earliest first elected year . | {'row': '1', 'col': '4', 'order': '1', 'col_other': '2', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'first elected', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; first elected ; 1 }'}, 'incumbent'], 'result': 'william j driver', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; first elected ; 1 } ; incumbent }'}, 'william j driver'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; first elected ; 1 } ; incumbent } ; william j driver } = true', 'tointer': 'select the row whose first elected record of all rows is 1st minimum . the incumbent record of this row is william j driver .'} | eq { hop { nth_argmin { all_rows ; first elected ; 1 } ; incumbent } ; william j driver } = true | select the row whose first elected record of all rows is 1st minimum . the incumbent record of this row is william j driver . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'first elected_5': 5, '1_6': 6, 'incumbent_7': 7, 'william j driver_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', 'first elected_5': 'first elected', '1_6': '1', 'incumbent_7': 'incumbent', 'william j driver_8': 'william j driver'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'first elected_5': [0], '1_6': [0], 'incumbent_7': [1], 'william j driver_8': [2]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['arkansas 1', 'william j driver', 'democratic', '1920', 're - elected', 'william j driver ( d ) unopposed'], ['arkansas 2', 'john e miller', 'democratic', '1930', 're - elected', 'john e miller ( d ) unopposed'], ['arkansas 3', 'claude fuller', 'democratic', '1928', 're - elected', 'claude fuller ( d ) unopposed'], ['arkansas 4', 'william b cravens', 'democratic', '1932', 're - elected', 'william b cravens ( d ) unopposed'], ['arkansas 5', 'david d terry', 'democratic', '1933', 're - elected', 'david d terry ( d ) unopposed'], ['arkansas 6', 'john little mcclellan', 'democratic', '1934', 're - elected', 'john little mcclellan ( d ) unopposed']] |
united states house of representatives elections , 1812 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1812 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2668367-14.html.csv | count | 4 incumbents were re - elected during the 1812 house of representatives elections . | {'scope': 'all', 'criterion': 'equal', 'value': 're-elected', 'result': '4', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'result', 're-elected'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose result record fuzzily matches to re-elected .', 'tostr': 'filter_eq { all_rows ; result ; re-elected }'}], 'result': '4', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; result ; re-elected } }', 'tointer': 'select the rows whose result record fuzzily matches to re-elected . the number of such rows is 4 .'}, '4'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; result ; re-elected } } ; 4 } = true', 'tointer': 'select the rows whose result record fuzzily matches to re-elected . the number of such rows is 4 .'} | eq { count { filter_eq { all_rows ; result ; re-elected } } ; 4 } = true | select the rows whose result record fuzzily matches to re-elected . 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, 'result_5': 5, 're-elected_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', 'result_5': 'result', 're-elected_6': 're-elected', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'result_5': [0], 're-elected_6': [0], '4_7': [2]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['north carolina 2', 'willis alston', 'democratic - republican', '1798', 're - elected', 'willis alston ( dr ) 56.0 % daniel mason ( f ) 44.0 %'], ['north carolina 5', 'william r king', 'democratic - republican', '1810', 're - elected', 'william r king ( dr ) 100 %'], ['north carolina 6', 'nathaniel macon', 'democratic - republican', '1791', 're - elected', 'nathaniel macon ( dr )'], ['north carolina 9', 'none ( district created )', 'none ( district created )', 'none ( district created )', 'new seat democratic - republican gain', 'bartlett yancey ( dr ) 61.1 % james martin ( f ) 38.9 %'], ['north carolina 10', 'joseph pearson', 'federalist', '1808', 're - elected', 'joseph pearson ( f ) 54.1 % alexander gary ( dr ) 45.9 %']] |
united states house of representatives elections , 2000 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_2000 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1341423-46.html.csv | count | 7 incumbents were re - elected during the 2000 united states house of representatives elections . | {'scope': 'all', 'criterion': 'equal', 'value': 're - elected', 'result': '7', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'results', 're - elected'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose results record fuzzily matches to re - elected .', 'tostr': 'filter_eq { all_rows ; results ; re - elected }'}], 'result': '7', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; results ; re - elected } }', 'tointer': 'select the rows whose results record fuzzily matches to re - elected . the number of such rows is 7 .'}, '7'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; results ; re - elected } } ; 7 } = true', 'tointer': 'select the rows whose results record fuzzily matches to re - elected . the number of such rows is 7 .'} | eq { count { filter_eq { all_rows ; results ; re - elected } } ; 7 } = true | select the rows whose results record fuzzily matches to re - elected . the number of such rows is 7 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'results_5': 5, 're - elected_6': 6, '7_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'results_5': 'results', 're - elected_6': 're - elected', '7_7': '7'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'results_5': [0], 're - elected_6': [0], '7_7': [2]} | ['district', 'incumbent', 'party', 'first elected', 'results', 'candidates'] | [['virginia 2', 'owen b pickett', 'democratic', '1986', 'retired republican gain', 'ed schrock ( r ) 52 % jody wagner ( d ) 48 %'], ['virginia 3', 'bobby scott', 'democratic', '1992', 're - elected', 'bobby scott ( d ) unopposed'], ['virginia 4', 'norman sisisky', 'democratic', '1982', 're - elected', 'norman sisisky ( d ) unopposed'], ['virginia 5', 'virgil goode', 'independent', '1996', 're - elected , independent gain', 'virgil goode ( i ) 68 % john boyd ( d ) 31 %'], ['virginia 6', 'bob goodlatte', 'republican', '1992', 're - elected', 'bob goodlatte ( r ) unopposed'], ['virginia 7', 'thomas j bliley , jr', 'republican', '1980', 'retired republican hold', 'eric cantor ( r ) 67 % warren stewart ( d ) 33 %'], ['virginia 8', 'jim moran', 'democratic', '1990', 're - elected', 'jim moran ( d ) 64 % demaris h miller ( r ) 35 %'], ['virginia 9', 'rick boucher', 'democratic', '1982', 're - elected', 'rick boucher ( d ) 70 % michael osborne ( r ) 30 %'], ['virginia 10', 'frank wolf', 'republican', '1980', 're - elected', 'frank wolf ( r ) 85 %']] |
transouth athletic conference | https://en.wikipedia.org/wiki/TranSouth_Athletic_Conference | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1715730-2.html.csv | superlative | the highest enrollment of any of the schools in the transouth athletic conference is at the school based in cleveland , tennessee . | {'scope': 'all', 'col_superlative': '4', '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 }'}, 'location'], 'result': 'cleveland , tennessee', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; enrollment } ; location }'}, 'cleveland , tennessee'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; enrollment } ; location } ; cleveland , tennessee } = true', 'tointer': 'select the row whose enrollment record of all rows is maximum . the location record of this row is cleveland , tennessee .'} | eq { hop { argmax { all_rows ; enrollment } ; location } ; cleveland , tennessee } = true | select the row whose enrollment record of all rows is maximum . the location record of this row is cleveland , tennessee . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'enrollment_5': 5, 'location_6': 6, 'cleveland , tennessee_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', 'location_6': 'location', 'cleveland , tennessee_7': 'cleveland , tennessee'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'enrollment_5': [0], 'location_6': [1], 'cleveland , tennessee_7': [2]} | ['location', 'founded', 'type', 'enrollment', 'nickname', 'joined', 'left', 'current conference'] | [['mount berry , georgia', '1902', 'private', '1937', 'vikings', '1996', '2004', 'saa ( ncaa division iii )'], ['birmingham , alabama', '1856', 'private', '1400', 'panthers', '1996', '2001', 'saa ( ncaa division iii )'], ['nashville , tennessee', '1891', 'private', '4278', 'bisons', '1996', '2001', 'atlantic sun ( a - sun ) ( ncaa division i )'], ['cleveland , tennessee', '1918', 'private', '4954', 'flames', '1996', '2004', 'ssac , gulf south in 2013'], ['nashville , tennessee', '1901', 'private', '2345', 'trojans', '1996', '2012', 'g - mac ( ncaa division ii )'], ['jackson , tennessee', '1823', 'private', '4259', 'union', '1996', '2012', 'gulf south ( gsc ) ( ncaa division ii )'], ['walnut ridge , arkansas', '1941', 'private', '700', 'eagles', '1996', '2001', 'american midwest'], ['batesville , arkansas', '1872', 'private', '600', 'scots', '1997', '2012', 'american midwest'], ['memphis , tennessee', '1941', 'private', '1970', 'eagles', '2005', '2009', 'uscaa / nccaa independent'], ['jackson , tennessee', '1843', 'private', '800', 'eagles', '2006', '2009', 'closed in 2011'], ['lebanon , tennessee', '1842', 'private', '1500', 'bulldogs', '2002', '2012', 'mid - south']] |
2008 - 09 cardiff city f.c. season | https://en.wikipedia.org/wiki/2008%E2%80%9309_Cardiff_City_F.C._season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-17596418-4.html.csv | ordinal | of the free transfers cardiff city brought in for the 2008-09 season , the second oldest was 31 years of age . | {'scope': 'subset', 'row': '3', 'col': '6', 'order': '2', 'col_other': 'n/a', 'max_or_min': 'max_to_min', 'value_mentioned': 'yes', 'subset': {'col': '7', 'criterion': 'equal', 'value': 'free transfer'}} | {'func': 'eq', 'args': [{'func': 'nth_max', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'type', 'free transfer'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; type ; free transfer }', 'tointer': 'select the rows whose type record fuzzily matches to free transfer .'}, 'age', '2'], 'result': '31', 'ind': 1, 'tostr': 'nth_max { filter_eq { all_rows ; type ; free transfer } ; age ; 2 }', 'tointer': 'select the rows whose type record fuzzily matches to free transfer . the 2nd maximum age record of these rows is 31 .'}, '31'], 'result': True, 'ind': 2, 'tostr': 'eq { nth_max { filter_eq { all_rows ; type ; free transfer } ; age ; 2 } ; 31 } = true', 'tointer': 'select the rows whose type record fuzzily matches to free transfer . the 2nd maximum age record of these rows is 31 .'} | eq { nth_max { filter_eq { all_rows ; type ; free transfer } ; age ; 2 } ; 31 } = true | select the rows whose type record fuzzily matches to free transfer . the 2nd maximum age record of these rows is 31 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'nth_max_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'type_5': 5, 'free transfer_6': 6, 'age_7': 7, '2_8': 8, '31_9': 9} | {'eq_2': 'eq', 'result_3': 'true', 'nth_max_1': 'nth_max', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'type_5': 'type', 'free transfer_6': 'free transfer', 'age_7': 'age', '2_8': '2', '31_9': '31'} | {'eq_2': [3], 'result_3': [], 'nth_max_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'type_5': [0], 'free transfer_6': [0], 'age_7': [1], '2_8': [1], '31_9': [2]} | ['n', 'p', 'name', 'eu', 'country', 'age', 'type', 'moving from', 'transfer window', 'ends', 'transfer fee', 'source'] | [['15', 'df', 'comminges', 'eu', 'gpe', '26', 'free transfer', 'swindon town', 'summer', '2010', 'free', 'bbc sport'], ['21', 'mf', 'kennedy', 'eu', 'irl', '32', 'free transfer', 'crystal palace', 'summer', '2010', 'free', 'bbc sport'], ['1', 'gk', 'enckelman', 'eu', 'fin', '31', 'free transfer', 'blackburn rovers', 'summer', '2010', 'free', 'bbc sport'], ['17', 'df', 'dennehy', 'eu', 'irl', '19', 'free transfer', 'everton', 'summer', '2010', 'free', 'bbc sport'], ['44', 'fw', 'mccormack', 'eu', 'sco', '21', 'transfer', 'motherwell', 'summer', '2010', '120000', 'bbc sport'], ['8', 'fw', 'bothroyd', 'eu', 'eng', '26', 'transfer', 'wolverhampton wanderers', 'summer', '2011', '350000', 'bbc sport'], ['6', 'df', 'gyepes', 'eu', 'hun', '27', 'transfer', 'northampton town', 'summer', '2010', '200000', 'bbc sport']] |
euro convergence criteria | https://en.wikipedia.org/wiki/Euro_convergence_criteria | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1884378-1.html.csv | aggregation | the average central rate for the currencies listed for euro convergence is 3.393 . | {'scope': 'all', 'col': '4', 'type': 'average', 'result': '3.393', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'central rate'], 'result': '3.393', 'ind': 0, 'tostr': 'avg { all_rows ; central rate }'}, '3.393'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; central rate } ; 3.393 } = true', 'tointer': 'the average of the central rate record of all rows is 3.393 .'} | round_eq { avg { all_rows ; central rate } ; 3.393 } = true | the average of the central rate record of all rows is 3.393 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'central rate_4': 4, '3.393_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'central rate_4': 'central rate', '3.393_5': '3.393'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'central rate_4': [0], '3.393_5': [1]} | ['currency', 'code', 'entry erm ii', 'central rate', 'official target date'] | [['bulgarian lev', 'bgn', '-', '1.95583', '-'], ['croatian kuna', 'hrk', '-', '-', '-'], ['czech koruna', 'czk', '-', '-', '-'], ['danish krone', 'dkk', '1 january 1999', '7.46038', 'formal opt - out'], ['hungarian forint', 'huf', '-', '-', '-'], ['latvian lats', 'lvl', '2 may 2005', '0.702804', '1 january 2014'], ['lithuanian litas', 'ltl', '28 june 2004', '3.45280', '1 january 2015'], ['polish złoty', 'pln', '-', '-', '-'], ['romanian leu', 'ron', '-', '-', '-'], ['swedish krona', 'sek', 'not considered', '-', 'de facto opt - out'], ['british pound sterling gibraltar pound', 'gbp gip', 'not considered', '-', 'formal opt - out']] |
kumar sanu | https://en.wikipedia.org/wiki/Kumar_Sanu | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1368369-1.html.csv | count | the lyricist for three of kumar sanu 's songs was sameer . | {'scope': 'all', 'criterion': 'equal', 'value': 'sameer', 'result': '3', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'lyricist', 'sameer'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose lyricist record fuzzily matches to sameer .', 'tostr': 'filter_eq { all_rows ; lyricist ; sameer }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; lyricist ; sameer } }', 'tointer': 'select the rows whose lyricist record fuzzily matches to sameer . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; lyricist ; sameer } } ; 3 } = true', 'tointer': 'select the rows whose lyricist record fuzzily matches to sameer . the number of such rows is 3 .'} | eq { count { filter_eq { all_rows ; lyricist ; sameer } } ; 3 } = true | select the rows whose lyricist record fuzzily matches to sameer . 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, 'lyricist_5': 5, 'sameer_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', 'lyricist_5': 'lyricist', 'sameer_6': 'sameer', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'lyricist_5': [0], 'sameer_6': [0], '3_7': [2]} | ['year', 'song', 'film', 'music director ( s )', 'lyricist'] | [['1991', 'ab tere bin', 'aashiqui', 'nadeem - shravan', 'sameer'], ['1992', 'mera dil bhi kitna pagal hai', 'saajan', 'nadeem - shravan', 'sameer'], ['1993', 'sochenge tumhe pyaar', 'deewana', 'nadeem - shravan', 'sameer'], ['1994', 'yeh kaali kaali aankhen', 'baazigar', 'anu malik', 'rani malik'], ['1995', 'ek ladki ko dekha', '1942 : a love story', 'rd burman', 'javed akhtar']] |
win ( tv station ) | https://en.wikipedia.org/wiki/WIN_%28TV_station%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13596926-1.html.csv | comparative | channel 59 was on air before channel 32 was on the air . | {'row_1': '4', 'row_2': '5', 'col': '3', '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', 'ch 1', '59 ( uhf )'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose ch 1 record fuzzily matches to 59 ( uhf ) .', 'tostr': 'filter_eq { all_rows ; ch 1 ; 59 ( uhf ) }'}, 'on - air date'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; ch 1 ; 59 ( uhf ) } ; on - air date }', 'tointer': 'select the rows whose ch 1 record fuzzily matches to 59 ( uhf ) . take the on - air date record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'ch 1', '32 ( uhf )'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose ch 1 record fuzzily matches to 32 ( uhf ) .', 'tostr': 'filter_eq { all_rows ; ch 1 ; 32 ( uhf ) }'}, 'on - air date'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; ch 1 ; 32 ( uhf ) } ; on - air date }', 'tointer': 'select the rows whose ch 1 record fuzzily matches to 32 ( uhf ) . take the on - air date record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; ch 1 ; 59 ( uhf ) } ; on - air date } ; hop { filter_eq { all_rows ; ch 1 ; 32 ( uhf ) } ; on - air date } } = true', 'tointer': 'select the rows whose ch 1 record fuzzily matches to 59 ( uhf ) . take the on - air date record of this row . select the rows whose ch 1 record fuzzily matches to 32 ( uhf ) . take the on - air date record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; ch 1 ; 59 ( uhf ) } ; on - air date } ; hop { filter_eq { all_rows ; ch 1 ; 32 ( uhf ) } ; on - air date } } = true | select the rows whose ch 1 record fuzzily matches to 59 ( uhf ) . take the on - air date record of this row . select the rows whose ch 1 record fuzzily matches to 32 ( uhf ) . take the on - air 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, 'ch 1_7': 7, '59 ( uhf )_8': 8, 'on - air date_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'ch 1_11': 11, '32 ( uhf )_12': 12, 'on - air 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', 'ch 1_7': 'ch 1', '59 ( uhf )_8': '59 ( uhf )', 'on - air date_9': 'on - air date', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'ch 1_11': 'ch 1', '32 ( uhf )_12': '32 ( uhf )', 'on - air date_13': 'on - air date'} | {'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'ch 1_7': [0], '59 ( uhf )_8': [0], 'on - air date_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'ch 1_11': [1], '32 ( uhf )_12': [1], 'on - air date_13': [3]} | ['region served', 'ch 1', 'on - air date', 'analogue power', 'digital power', 'analogue haat', 'digital haat', 'transmitter location'] | [['canberra', '31 ( uhf )', '31 march 1989', '600 kw', '50 kw', '362 m', '362 m', 'black mountain'], ['central tablelands', '39 ( uhf )', '30 december 1989', '2000 kw', '570 kw', '627 m', '628 m', 'mount canobolas'], ['central western slopes', '32 ( uhf )', '30 december 1989', '1000 kw', '600 kw', '648 m', '653 m', 'mount cenn cruaich'], ['illawarra & regional sydney', '59 ( uhf )', '18 march 1962', '950 kw', '250 kw', '505 m', '600 m', 'knights hill'], ['south western slopes and eastern riverina', '32 ( uhf )', '30 december 1989', '1600 kw', '600 kw', '525 m', '540 m', 'mount ulandra']] |
list of former and unopened london underground stations | https://en.wikipedia.org/wiki/List_of_former_and_unopened_London_Underground_stations | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-211615-2.html.csv | comparative | turnham green station was cancelled earlier than the crouch end station . | {'row_1': '14', 'row_2': '5', 'col': '4', 'col_other': '1', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'station', 'turnham green'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose station record fuzzily matches to turnham green .', 'tostr': 'filter_eq { all_rows ; station ; turnham green }'}, 'cancelled'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; station ; turnham green } ; cancelled }', 'tointer': 'select the rows whose station record fuzzily matches to turnham green . take the cancelled record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'station', 'crouch end'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose station record fuzzily matches to crouch end .', 'tostr': 'filter_eq { all_rows ; station ; crouch end }'}, 'cancelled'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; station ; crouch end } ; cancelled }', 'tointer': 'select the rows whose station record fuzzily matches to crouch end . take the cancelled record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; station ; turnham green } ; cancelled } ; hop { filter_eq { all_rows ; station ; crouch end } ; cancelled } } = true', 'tointer': 'select the rows whose station record fuzzily matches to turnham green . take the cancelled record of this row . select the rows whose station record fuzzily matches to crouch end . take the cancelled record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; station ; turnham green } ; cancelled } ; hop { filter_eq { all_rows ; station ; crouch end } ; cancelled } } = true | select the rows whose station record fuzzily matches to turnham green . take the cancelled record of this row . select the rows whose station record fuzzily matches to crouch end . take the cancelled 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, 'station_7': 7, 'turnham green_8': 8, 'cancelled_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'station_11': 11, 'crouch end_12': 12, 'cancelled_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', 'station_7': 'station', 'turnham green_8': 'turnham green', 'cancelled_9': 'cancelled', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'station_11': 'station', 'crouch end_12': 'crouch end', 'cancelled_13': 'cancelled'} | {'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'station_7': [0], 'turnham green_8': [0], 'cancelled_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'station_11': [1], 'crouch end_12': [1], 'cancelled_13': [3]} | ['station', 'line', 'planned', 'cancelled', 'proposal', 'details'] | [['alexandra palace', 'northern', '1935', '1954', 'transfer from lner', 'abandoned part of northern heights project'], ['bushey heath', 'northern', '1936', '1949', 'new station on new route', 'abandoned part of northern heights project'], ['camberwell', 'bakerloo', '1931', '1950', 'new station on new route', 'part of abandoned extension to camberwell'], ['cranley gardens', 'northern', '1935', '1954', 'transfer from lner', 'abandoned part of northern heights project'], ['crouch end', 'northern', '1935', '1954', 'transfer from lner', 'abandoned part of northern heights project'], ['elstree south', 'northern', '1936', '1949', 'new station on new route', 'abandoned part of northern heights project'], ['emlyn road', 'central', '1913', '1919', 'new station on new route', 'abandoned proposal for an extension to richmond'], ['heathfield terrace', 'central', '1913', '1919', 'new station on new route', 'abandoned proposal for an extension to richmond'], ['mill hill ( the hale )', 'northern', '1935', '1954', 'transfer from lner', 'abandoned part of northern heights project'], ['muswell hill', 'northern', '1935', '1954', 'transfer from lner', 'abandoned part of northern heights project'], ['paddenswick road', 'central', '1913', '1919', 'new station on new route', 'abandoned proposal for an extension to richmond'], ['rylett road', 'central', '1913', '1919', 'new station on new route', 'abandoned proposal for an extension to richmond'], ['stroud green', 'northern', '1935', '1954', 'transfer from lner', 'abandoned part of northern heights project'], ['turnham green', 'central', '1913', '1919', 'new station on new route', 'abandoned proposal for an extension to richmond']] |
black swan - class sloop | https://en.wikipedia.org/wiki/Black_Swan-class_sloop | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1220125-2.html.csv | ordinal | in black swan - class sloop , sutlej was the earliest to be laid down among those build by denny , dunbarton . | {'scope': 'subset', 'row': '1', 'col': '4', 'order': '1', 'col_other': '1', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'subset': {'col': '3', 'criterion': 'equal', 'value': 'denny , dunbarton'}} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'builder', 'denny , dunbarton'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; builder ; denny , dunbarton }', 'tointer': 'select the rows whose builder record fuzzily matches to denny , dunbarton .'}, 'laid down', '1'], 'result': None, 'ind': 1, 'tostr': 'nth_argmin { filter_eq { all_rows ; builder ; denny , dunbarton } ; laid down ; 1 }'}, 'name'], 'result': 'sutlej', 'ind': 2, 'tostr': 'hop { nth_argmin { filter_eq { all_rows ; builder ; denny , dunbarton } ; laid down ; 1 } ; name }'}, 'sutlej'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { nth_argmin { filter_eq { all_rows ; builder ; denny , dunbarton } ; laid down ; 1 } ; name } ; sutlej } = true', 'tointer': 'select the rows whose builder record fuzzily matches to denny , dunbarton . select the row whose laid down record of these rows is 1st minimum . the name record of this row is sutlej .'} | eq { hop { nth_argmin { filter_eq { all_rows ; builder ; denny , dunbarton } ; laid down ; 1 } ; name } ; sutlej } = true | select the rows whose builder record fuzzily matches to denny , dunbarton . select the row whose laid down record of these rows is 1st minimum . the name record of this row is sutlej . | 4 | 4 | {'str_eq_3': 3, 'result_4': 4, 'str_hop_2': 2, 'nth_argmin_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'builder_6': 6, 'denny , dunbarton_7': 7, 'laid down_8': 8, '1_9': 9, 'name_10': 10, 'sutlej_11': 11} | {'str_eq_3': 'str_eq', 'result_4': 'true', 'str_hop_2': 'str_hop', 'nth_argmin_1': 'nth_argmin', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'builder_6': 'builder', 'denny , dunbarton_7': 'denny , dunbarton', 'laid down_8': 'laid down', '1_9': '1', 'name_10': 'name', 'sutlej_11': 'sutlej'} | {'str_eq_3': [4], 'result_4': [], 'str_hop_2': [3], 'nth_argmin_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'builder_6': [0], 'denny , dunbarton_7': [0], 'laid down_8': [1], '1_9': [1], 'name_10': [2], 'sutlej_11': [3]} | ['name', 'pennant', 'builder', 'laid down', 'launched', 'commissioned'] | [['sutlej', 'u95', 'denny , dunbarton', '4 january 1940', '1 october 1940', '23 april 1941'], ['jumna', 'u21', 'denny , dunbarton', '28 february 1940', '16 november 1940', '13 may 1941'], ['narbada', 'u40', 'thornycroft , woolston', '30 august 1941', '21 november 1942', '29 april 1943'], ['godavari', 'u52', 'thornycroft , woolston', '30 october 1941', '21 january 1943', '28 june 1943'], ['kistna', 'u46', 'yarrow , scotstoun', '14 july 1942', '22 april 1943', '26 august 1943'], ['cauvery', 'u10', 'yarrow , scotstoun', '28 october 1942', '15 june 1943', '21 october 1943']] |
peter fleming ( tennis ) | https://en.wikipedia.org/wiki/Peter_Fleming_%28tennis%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1834797-2.html.csv | count | four of peter fleming 's tennis championship finals were played on a hard surface . | {'scope': 'all', 'criterion': 'equal', 'value': 'hard', 'result': '4', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'surface', 'hard'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose surface record fuzzily matches to hard .', 'tostr': 'filter_eq { all_rows ; surface ; hard }'}], 'result': '4', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; surface ; hard } }', 'tointer': 'select the rows whose surface record fuzzily matches to hard . the number of such rows is 4 .'}, '4'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; surface ; hard } } ; 4 } = true', 'tointer': 'select the rows whose surface record fuzzily matches to hard . the number of such rows is 4 .'} | eq { count { filter_eq { all_rows ; surface ; hard } } ; 4 } = true | select the rows whose surface record fuzzily matches to hard . 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, 'surface_5': 5, 'hard_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', 'surface_5': 'surface', 'hard_6': 'hard', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'surface_5': [0], 'hard_6': [0], '4_7': [2]} | ['outcome', 'date', 'championship', 'surface', 'opponent in the final', 'score in the final'] | [['runner - up', '1978', 'maui , us', 'hard', 'bill scanlon', '2 - 6 , 0 - 6'], ['winner', '1978', 'bologna , italy', 'carpet', 'adriano panatta', '6 - 2 , 7 - 6'], ['runner - up', '1978', 'montego bay , jamaica', 'hard', 'ilie năstase', '6 - 2 , 6 - 5 , 2 - 6 , 4 - 6 , 4 - 6'], ['runner - up', '1979', 'san jose , us', 'carpet', 'john mcenroe', '6 - 7 , 6 - 7'], ['winner', '1979', 'cincinnati , us', 'hard', 'roscoe tanner', '6 - 4 , 6 - 2'], ['winner', '1979', 'los angeles , us', 'carpet', 'john mcenroe', '6 - 4 , 6 - 4'], ['runner - up', '1979', 'san francisco , us', 'carpet', 'john mcenroe', '6 - 4 , 5 - 7 , 2 - 6'], ['runner - up', '1979', 'maui , us', 'hard', 'bill scanlon', '1 - 6 , 1 - 6']] |
kaspars stupelis | https://en.wikipedia.org/wiki/Kaspars_Stupelis | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16775140-1.html.csv | unique | kaspars stupelis only had 18 wins once , when the driver was daniel willemsen . | {'scope': 'all', 'row': '4', 'col': '4', 'col_other': '1', 'criterion': 'equal', 'value': '18', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'wins', '18'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose wins record is equal to 18 .', 'tostr': 'filter_eq { all_rows ; wins ; 18 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; wins ; 18 } }', 'tointer': 'select the rows whose wins record is equal to 18 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'wins', '18'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose wins record is equal to 18 .', 'tostr': 'filter_eq { all_rows ; wins ; 18 }'}, 'driver'], 'result': 'daniël willemsen', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; wins ; 18 } ; driver }'}, 'daniël willemsen'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; wins ; 18 } ; driver } ; daniël willemsen }', 'tointer': 'the driver record of this unqiue row is daniël willemsen .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; wins ; 18 } } ; eq { hop { filter_eq { all_rows ; wins ; 18 } ; driver } ; daniël willemsen } } = true', 'tointer': 'select the rows whose wins record is equal to 18 . there is only one such row in the table . the driver record of this unqiue row is daniël willemsen .'} | and { only { filter_eq { all_rows ; wins ; 18 } } ; eq { hop { filter_eq { all_rows ; wins ; 18 } ; driver } ; daniël willemsen } } = true | select the rows whose wins record is equal to 18 . there is only one such row in the table . the driver record of this unqiue row is daniël willemsen . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'wins_7': 7, '18_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'driver_9': 9, 'daniël willemsen_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'wins_7': 'wins', '18_8': '18', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'driver_9': 'driver', 'daniël willemsen_10': 'daniël willemsen'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'wins_7': [0], '18_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'driver_9': [2], 'daniël willemsen_10': [3]} | ['driver', 'points', 'races', 'wins', 'second', 'third'] | [['modris stelle', '14', '10', '-', '-', '-'], ['modris stelle', '69', '12', '-', '-', '-'], ['daniël willemsen', '561', '24', '13', '9', '-'], ['daniël willemsen', '572', '26', '18', '4', '1'], ['kristers serģis', '440', '22', '7', '12', '-'], ['kristers serģis', '64', '4', '-', '2', '1'], ['kristers serģis', '242', '16', '1', '8', '1'], ['kristers serģis', '434', '24', '4', '12', '2'], ['nicky pulinx', '229', '25', '-', '-', '-'], ['maris rupeiks', '423', '28', '1', '4', '2'], ['maris rupeiks', '316', '22', '1', '4', '-'], ['etienne bax', '447', '22', '9', '8', '1'], ['etienne bax', '513', '25', '14', '6', '-'], ['overall 2001 - 2013', '4224', '250', '68', '69', '8']] |
2010 - 11 uefa champions league | https://en.wikipedia.org/wiki/2010%E2%80%9311_UEFA_Champions_League | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18255941-28.html.csv | count | a total of two games in the 2010 - 11 uefa champions league 1st leg ended with a 1-1 score . | {'scope': 'all', 'criterion': 'equal', 'value': '1 - 1', 'result': '2', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', '1st leg', '1 - 1'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose 1st leg record fuzzily matches to 1 - 1 .', 'tostr': 'filter_eq { all_rows ; 1st leg ; 1 - 1 }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; 1st leg ; 1 - 1 } }', 'tointer': 'select the rows whose 1st leg record fuzzily matches to 1 - 1 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; 1st leg ; 1 - 1 } } ; 2 } = true', 'tointer': 'select the rows whose 1st leg record fuzzily matches to 1 - 1 . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; 1st leg ; 1 - 1 } } ; 2 } = true | select the rows whose 1st leg record fuzzily matches to 1 - 1 . the number of such rows is 2 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, '1st leg_5': 5, '1 - 1_6': 6, '2_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', '1st leg_5': '1st leg', '1 - 1_6': '1 - 1', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], '1st leg_5': [0], '1 - 1_6': [0], '2_7': [2]} | ['team 1', 'agg', 'team 2', '1st leg', '2nd leg'] | [['roma', '2 - 6', 'shakhtar donetsk', '2 - 3', '0 - 3'], ['milan', '0 - 1', 'tottenham hotspur', '0 - 1', '0 - 0'], ['valencia', '2 - 4', 'schalke 04', '1 - 1', '1 - 3'], ['internazionale', '( a ) 3 - 3', 'bayern munich', '0 - 1', '3 - 2'], ['lyon', '1 - 4', 'real madrid', '1 - 1', '0 - 3'], ['arsenal', '3 - 4', 'barcelona', '2 - 1', '1 - 3'], ['marseille', '1 - 2', 'manchester united', '0 - 0', '1 - 2'], ['copenhagen', '0 - 2', 'chelsea', '0 - 2', '0 - 0']] |
2008 afl season | https://en.wikipedia.org/wiki/2008_AFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-14312471-4.html.csv | ordinal | st kilda 's away team game recorded the highest crowd participation in the 2008 afl season . | {'row': '4', 'col': '6', 'order': '1', 'col_other': '3', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'crowd', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; crowd ; 1 }'}, 'away team'], 'result': 'st kilda', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; crowd ; 1 } ; away team }'}, 'st kilda'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; crowd ; 1 } ; away team } ; st kilda } = true', 'tointer': 'select the row whose crowd record of all rows is 1st maximum . the away team record of this row is st kilda .'} | eq { hop { nth_argmax { all_rows ; crowd ; 1 } ; away team } ; st kilda } = true | select the row whose crowd record of all rows is 1st maximum . the away team record of this row is st kilda . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'crowd_5': 5, '1_6': 6, 'away team_7': 7, 'st kilda_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'crowd_5': 'crowd', '1_6': '1', 'away team_7': 'away team', 'st kilda_8': 'st kilda'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'crowd_5': [0], '1_6': [0], 'away team_7': [1], 'st kilda_8': [2]} | ['home team', 'home team score', 'away team', 'away team score', 'ground', 'crowd', 'date', 'report'] | [['melbourne', '5.11 ( 41 )', 'geelong', '24.13 ( 157 )', 'mcg', '34610', 'friday , 8 august', 'aflcomau'], ['carlton', '18.24 ( 132 )', 'port adelaide', '9.12 ( 66 )', 'telstra dome', '29696', 'saturday , 9 august', 'aflcomau'], ['hawthorn', '16.14 ( 110 )', 'brisbane lions', '5.11 ( 41 )', 'aurora stadium', '19929', 'saturday , 9 august', 'aflcomau'], ['collingwood', '14.13 ( 97 )', 'st kilda', '12.11 ( 83 )', 'mcg', '52135', 'saturday , 9 august', 'aflcomau'], ['sydney', '17.10 ( 112 )', 'fremantle', '15.18 ( 108 )', 'scg', '20846', 'saturday , 9 august', 'aflcomau'], ['north melbourne', '21.10 ( 136 )', 'western bulldogs', '18.8 ( 116 )', 'telstra dome', '31957', 'sunday , 10 august', 'aflcomau'], ['adelaide', '16.12 ( 108 )', 'richmond', '6.9 ( 45 )', 'aami stadium', '37562', 'sunday , 10 august', 'aflcomau']] |
list of covert affairs episodes | https://en.wikipedia.org/wiki/List_of_Covert_Affairs_episodes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-25740548-3.html.csv | count | according to the list of covert affairs episodes , among the episodes directed by stephen kay , two of them were written by norman morrill . | {'scope': 'subset', 'criterion': 'equal', 'value': 'norman morrill', 'result': '2', 'col': '5', 'subset': {'col': '4', 'criterion': 'equal', 'value': 'stephen kay'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'directed by', 'stephen kay'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; directed by ; stephen kay }', 'tointer': 'select the rows whose directed by record fuzzily matches to stephen kay .'}, 'written by', 'norman morrill'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose directed by record fuzzily matches to stephen kay . among these rows , select the rows whose written by record fuzzily matches to norman morrill .', 'tostr': 'filter_eq { filter_eq { all_rows ; directed by ; stephen kay } ; written by ; norman morrill }'}], 'result': '2', 'ind': 2, 'tostr': 'count { filter_eq { filter_eq { all_rows ; directed by ; stephen kay } ; written by ; norman morrill } }', 'tointer': 'select the rows whose directed by record fuzzily matches to stephen kay . among these rows , select the rows whose written by record fuzzily matches to norman morrill . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_eq { filter_eq { all_rows ; directed by ; stephen kay } ; written by ; norman morrill } } ; 2 } = true', 'tointer': 'select the rows whose directed by record fuzzily matches to stephen kay . among these rows , select the rows whose written by record fuzzily matches to norman morrill . the number of such rows is 2 .'} | eq { count { filter_eq { filter_eq { all_rows ; directed by ; stephen kay } ; written by ; norman morrill } } ; 2 } = true | select the rows whose directed by record fuzzily matches to stephen kay . among these rows , select the rows whose written by record fuzzily matches to norman morrill . 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, 'directed by_6': 6, 'stephen kay_7': 7, 'written by_8': 8, 'norman morrill_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', 'directed by_6': 'directed by', 'stephen kay_7': 'stephen kay', 'written by_8': 'written by', 'norman morrill_9': 'norman morrill', '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], 'directed by_6': [0], 'stephen kay_7': [0], 'written by_8': [1], 'norman morrill_9': [1], '2_10': [3]} | ['series', 'season', 'title', 'directed by', 'written by', 'original air date', 'production code', 'us viewers ( million )'] | [['12', '1', 'begin the begin', 'kate woods', 'matt corman & chris ord', 'june 7 , 2011', 'ca201', '4.56'], ['13', '2', 'good advices', 'ken girotti', 'stephen hootstein', 'june 14 , 2011', 'ca202', '3.92'], ['14', '3', 'bang and blame', 'allan kroeker', 'erica shelton', 'june 21 , 2011', 'ca203', '4.03'], ['15', '4', 'all the right friends', 'stephen kay', 'norman morrill', 'june 28 , 2011', 'ca204', '4.01'], ['16', '5', 'around the sun', 'félix alcalá', 'dana calvo', 'july 5 , 2011', 'ca205', '4.81'], ['17', '6', 'the outsiders', 'marc roskin', 'julia ruchman', 'july 12 , 2011', 'ca206', '4.30'], ['18', '7', 'half a world away', 'félix alcalá', 'julia ruchman', 'july 19 , 2011', 'ca207', '4.55'], ['19', '8', 'welcome to the occupation', 'john fawcett', 'zak schwartz', 'july 26 , 2011', 'ca208', '4.36'], ['20', '9', 'sad professor', 'j miller tobin', 'alex berger', 'august 2 , 2011', 'ca209', '4.61'], ['21', '10', 'world leader pretend', 'kate woods', 'matt corman & chris ord', 'august 9 , 2011', 'ca210', '4.70'], ['22', '11', 'the wake - up bomb', 'stephen kay', 'stephen hootstein', 'november 1 , 2011', 'ca211', '2.70'], ['23', '12', 'uberlin', 'jonathan glassner', 'erica shelton', 'november 8 , 2011', 'ca212', '2.67'], ['24', '13', 'a girl like you', 'stephen kay', 'norman morrill', 'november 15 , 2011', 'ca213', '2.26'], ['25', '14', 'horse to water', 'rosemary rodriguez', 'alex berger', 'november 22 , 2011', 'ca214', '2.29'], ['26', '15', "what 's the frequency , kenneth", 'omar madha', 'donald joh', 'november 29 , 2011', 'ca215', '3.22']] |
nick price | https://en.wikipedia.org/wiki/Nick_Price | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1132021-7.html.csv | aggregation | nick price had an average of around 5-6 top-10 finishes across the major pga tournaments . | {'scope': 'all', 'col': '4', 'type': 'average', 'result': '5-6', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'top - 10'], 'result': '5-6', 'ind': 0, 'tostr': 'avg { all_rows ; top - 10 }'}, '5-6'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; top - 10 } ; 5-6 } = true', 'tointer': 'the average of the top - 10 record of all rows is 5-6 .'} | round_eq { avg { all_rows ; top - 10 } ; 5-6 } = true | the average of the top - 10 record of all rows is 5-6 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'top - 10_4': 4, '5-6_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'top - 10_4': 'top - 10', '5-6_5': '5-6'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'top - 10_4': [0], '5-6_5': [1]} | ['tournament', 'wins', 'top - 5', 'top - 10', 'top - 25', 'events', 'cuts made'] | [['masters tournament', '0', '1', '4', '11', '20', '13'], ['us open', '0', '3', '5', '12', '20', '15'], ['the open championship', '1', '3', '5', '8', '27', '20'], ['pga championship', '2', '5', '7', '10', '20', '16'], ['totals', '3', '12', '21', '41', '87', '64']] |
list of nurse jackie episodes | https://en.wikipedia.org/wiki/List_of_Nurse_Jackie_episodes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-26961951-4.html.csv | ordinal | game on is the title of the nurse jackie drama episode with the earliest original air date . | {'row': '1', 'col': '6', 'order': '1', 'col_other': '3', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'original air date', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; original air date ; 1 }'}, 'title'], 'result': 'game on', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; original air date ; 1 } ; title }'}, 'game on'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; original air date ; 1 } ; title } ; game on } = true', 'tointer': 'select the row whose original air date record of all rows is 1st minimum . the title record of this row is game on .'} | eq { hop { nth_argmin { all_rows ; original air date ; 1 } ; title } ; game on } = true | select the row whose original air date record of all rows is 1st minimum . the title record of this row is game on . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'original air date_5': 5, '1_6': 6, 'title_7': 7, 'game on_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', 'original air date_5': 'original air date', '1_6': '1', 'title_7': 'title', 'game on_8': 'game on'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'original air date_5': [0], '1_6': [0], 'title_7': [1], 'game on_8': [2]} | ['no in series', 'no in season', 'title', 'directed by', 'written by', 'original air date', 'us viewers ( million )'] | [['25', '1', 'game on', 'steve buscemi', 'liz brixius & linda wallem', 'march 28 , 2011', '0.61'], ['26', '2', 'enough rope', 'steve buscemi', 'liz brixius', 'april 4 , 2011', '0.49'], ['27', '3', 'play me', 'michael lehmann', 'linda wallem', 'april 11 , 2011', '0.57'], ['28', '4', 'mitten', 'michael lehmann', 'liz flahive', 'april 18 , 2011', '0.60'], ['29', '5', 'rat falls', 'tristram shapeero', 'alison mcdonald', 'april 25 , 2011', '0.65'], ['30', '6', 'when the saints go', 'tristram shapeero', 'liz brixius', 'may 2 , 2011', '0.53'], ['31', '7', 'orchids and salami', 'bob balaban', 'ellen fairey', 'may 9 , 2011', '0.47'], ['32', '8', 'the astonishing', 'bob balaban', 'rajiv joseph', 'may 16 , 2011', '0.43'], ['33', '9', 'have you met ms jones', 'daisy von scherler mayer', 'liz brixius & wyndham lewis', 'may 23 , 2011', '0.60'], ['34', '10', 'fuck the lemurs', 'daisy von scherler mayer', 'liz brixius', 'june 6 , 2011', '0.56'], ['35', '11', 'batting practice', 'linda wallem', 'liz flahive', 'june 13 , 2011', '0.58']] |
list of tallest buildings in germany | https://en.wikipedia.org/wiki/List_of_tallest_buildings_in_Germany | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11328656-3.html.csv | ordinal | the second tallest building in germany is the messeturm in frankfurt . | {'row': '2', 'col': '3', 'order': '2', 'col_other': '1', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'height ( m )', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; height ( m ) ; 2 }'}, 'name'], 'result': 'messeturm', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; height ( m ) ; 2 } ; name }'}, 'messeturm'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; height ( m ) ; 2 } ; name } ; messeturm } = true', 'tointer': 'select the row whose height ( m ) record of all rows is 2nd maximum . the name record of this row is messeturm .'} | eq { hop { nth_argmax { all_rows ; height ( m ) ; 2 } ; name } ; messeturm } = true | select the row whose height ( m ) record of all rows is 2nd maximum . the name record of this row is messeturm . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'height (m)_5': 5, '2_6': 6, 'name_7': 7, 'messeturm_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', 'height (m)_5': 'height ( m )', '2_6': '2', 'name_7': 'name', 'messeturm_8': 'messeturm'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'height (m)_5': [0], '2_6': [0], 'name_7': [1], 'messeturm_8': [2]} | ['name', 'city', 'height ( m )', 'height ( ft )', 'floors', 'years as tallest'] | [['commerzbank tower', 'frankfurt', '259', '850', '56', '1997 - present'], ['messeturm', 'frankfurt', '257', '843', '55', '1990 - 1997'], ['silberturm', 'frankfurt', '166', '545', '32', '1978 - 1990'], ['westend gate', 'frankfurt', '159', '522', '47', '1976 - 1978'], ['colonia - hochhaus', 'cologne', '147', '482', '42', '1973 - 1976'], ['city - hochhaus leipzig', 'leipzig', '143', '468', '36', '1972 - 1973'], ['bayer - hochhaus', 'leverkusen', '122', '400', '29', '1963 - 1972'], ['friedrich - engelhorn - hochhaus', 'ludwigshafen', '102', '335', '28', '1957 - 1963']] |
1970 baltimore colts season | https://en.wikipedia.org/wiki/1970_Baltimore_Colts_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-14966537-1.html.csv | comparative | the 1970 baltimore colts scored more points against the philadelphia eagles than against the chicago bears . | {'row_1': '12', 'row_2': '11', 'col': '4', 'col_other': '3', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', 'philadelphia eagles'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose opponent record fuzzily matches to philadelphia eagles .', 'tostr': 'filter_eq { all_rows ; opponent ; philadelphia eagles }'}, 'result'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; opponent ; philadelphia eagles } ; result }', 'tointer': 'select the rows whose opponent record fuzzily matches to philadelphia eagles . take the result record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', 'chicago bears'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose opponent record fuzzily matches to chicago bears .', 'tostr': 'filter_eq { all_rows ; opponent ; chicago bears }'}, 'result'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; opponent ; chicago bears } ; result }', 'tointer': 'select the rows whose opponent record fuzzily matches to chicago bears . take the result record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; opponent ; philadelphia eagles } ; result } ; hop { filter_eq { all_rows ; opponent ; chicago bears } ; result } } = true', 'tointer': 'select the rows whose opponent record fuzzily matches to philadelphia eagles . take the result record of this row . select the rows whose opponent record fuzzily matches to chicago bears . take the result record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; opponent ; philadelphia eagles } ; result } ; hop { filter_eq { all_rows ; opponent ; chicago bears } ; result } } = true | select the rows whose opponent record fuzzily matches to philadelphia eagles . take the result record of this row . select the rows whose opponent record fuzzily matches to chicago bears . take the result record of this row . the first record is greater than the second record . | 5 | 5 | {'greater_4': 4, 'result_5': 5, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'opponent_7': 7, 'philadelphia eagles_8': 8, 'result_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'opponent_11': 11, 'chicago bears_12': 12, 'result_13': 13} | {'greater_4': 'greater', 'result_5': 'true', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'opponent_7': 'opponent', 'philadelphia eagles_8': 'philadelphia eagles', 'result_9': 'result', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'opponent_11': 'opponent', 'chicago bears_12': 'chicago bears', 'result_13': 'result'} | {'greater_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'opponent_7': [0], 'philadelphia eagles_8': [0], 'result_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'opponent_11': [1], 'chicago bears_12': [1], 'result_13': [3]} | ['week', 'date', 'opponent', 'result', 'record', 'game site', 'attendance'] | [['1', 'september 20 , 1970', 'san diego chargers', 'w 16 - 14', '1 - 0', 'san diego stadium', '47782'], ['2', 'september 28 , 1970', 'kansas city chiefs', 'l 24 - 44', '1 - 1', 'memorial stadium', '53911'], ['3', 'october 4 , 1970', 'boston patriots', 'w 14 - 6', '2 - 1', 'harvard stadium', '38235'], ['4', 'october 11 , 1970', 'houston oilers', 'w 24 - 20', '3 - 1', 'astrodome', '48050'], ['5', 'october 18 , 1970', 'new york jets', 'w 29 - 22', '4 - 1', 'shea stadium', '63301'], ['6', 'october 25 , 1970', 'boston patriots', 'w 27 - 3', '5 - 1', 'memorial stadium', '60240'], ['7', 'november 1 , 1970', 'miami dolphins', 'w 35 - 0', '6 - 1', 'memorial stadium', '60240'], ['8', 'november 9 , 1970', 'green bay packers', 'w 13 - 10', '7 - 1', 'milwaukee county stadium', '48063'], ['9', 'november 15 , 1970', 'buffalo bills', 't 17 - 17', '7 - 1 - 1', 'memorial stadium', '60240'], ['10', 'november 22 , 1970', 'miami dolphins', 'l 17 - 34', '7 - 2 - 1', 'miami orange bowl', '67699'], ['11', 'november 29 , 1970', 'chicago bears', 'w 21 - 20', '8 - 2 - 1', 'memorial stadium', '60240'], ['12', 'december 6 , 1970', 'philadelphia eagles', 'w 29 - 10', '9 - 2 - 1', 'memorial stadium', '60240'], ['13', 'december 13 , 1970', 'buffalo bills', 'w 20 - 14', '10 - 2 - 1', 'war memorial stadium', '34346']] |
günter netzer | https://en.wikipedia.org/wiki/G%C3%BCnter_Netzer | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1085623-1.html.csv | majority | the majority of günter netzer 's international goals were in friendly competitions . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'friendly', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'competition', 'friendly'], 'result': True, 'ind': 0, 'tointer': 'for the competition records of all rows , most of them fuzzily match to friendly .', 'tostr': 'most_eq { all_rows ; competition ; friendly } = true'} | most_eq { all_rows ; competition ; friendly } = true | for the competition records of all rows , most of them fuzzily match to friendly . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'competition_3': 3, 'friendly_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'competition_3': 'competition', 'friendly_4': 'friendly'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'competition_3': [0], 'friendly_4': [0]} | ['date', 'venue', 'score', 'result', 'competition'] | [['22 november 1970', 'athens , greece', '1 - 0', '3 - 1', 'friendly'], ['12 june 1971', 'karlsruhe , germany', '1 - 0', '2 - 0', 'uefa euro 1972 qualifying'], ['22 june 1971', 'oslo , norway', '7 - 0', '7 - 1', 'friendly'], ['8 september 1971', 'hanover , germany', '4 - 0', '5 - 0', 'friendly'], ['29 april 1972', 'london , uk', '2 - 1', '3 - 1', 'uefa euro 1972 qualifying'], ['15 november 1972', 'düsseldorf , germany', '4 - 0', '5 - 1', 'friendly']] |
andrei pavel | https://en.wikipedia.org/wiki/Andrei_Pavel | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1723598-5.html.csv | unique | the february 14 , 1999 game was the only one to be played on a carpet surface . | {'scope': 'all', 'row': '1', 'col': '3', 'col_other': '1', 'criterion': 'equal', 'value': 'carpet', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'surface', 'carpet'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose surface record fuzzily matches to carpet .', 'tostr': 'filter_eq { all_rows ; surface ; carpet }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; surface ; carpet } }', 'tointer': 'select the rows whose surface record fuzzily matches to carpet . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'surface', 'carpet'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose surface record fuzzily matches to carpet .', 'tostr': 'filter_eq { all_rows ; surface ; carpet }'}, 'date'], 'result': 'february 14 , 1999', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; surface ; carpet } ; date }'}, 'february 14 , 1999'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; surface ; carpet } ; date } ; february 14 , 1999 }', 'tointer': 'the date record of this unqiue row is february 14 , 1999 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; surface ; carpet } } ; eq { hop { filter_eq { all_rows ; surface ; carpet } ; date } ; february 14 , 1999 } } = true', 'tointer': 'select the rows whose surface record fuzzily matches to carpet . there is only one such row in the table . the date record of this unqiue row is february 14 , 1999 .'} | and { only { filter_eq { all_rows ; surface ; carpet } } ; eq { hop { filter_eq { all_rows ; surface ; carpet } ; date } ; february 14 , 1999 } } = true | select the rows whose surface record fuzzily matches to carpet . there is only one such row in the table . the date record of this unqiue row is february 14 , 1999 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'surface_7': 7, 'carpet_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'date_9': 9, 'february 14 , 1999_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'surface_7': 'surface', 'carpet_8': 'carpet', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'date_9': 'date', 'february 14 , 1999_10': 'february 14 , 1999'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'surface_7': [0], 'carpet_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'date_9': [2], 'february 14 , 1999_10': [3]} | ['date', 'tournament', 'surface', 'partnering', 'opponents in final', 'score in final'] | [['february 14 , 1999', 'st petersburg , russia', 'carpet', 'menno oosting', 'jeff tarango daniel vacek', '3 - 6 , 6 - 3 , 7 - 5'], ['january 10 , 2005', 'doha , qatar', 'hard', 'mikhail youzhny', 'albert costa rafael nadal', '6 - 3 , 4 - 6 , 6 - 3'], ['september 18 , 2005', 'bucharest , romania', 'clay', 'victor hănescu', 'josé acasuso sebastián prieto', '6 - 3 , 4 - 6 , 6 - 3'], ['february 25 , 2007', 'rotterdam , netherlands', 'hard', 'alexander waske', 'martin damm leander paes', '6 - 3 , 6 - 7 ( 5 ) , ( 10 - 7 )'], ['may 23 , 2009', 'kitzbühel , austria', 'clay', 'horia tecău', 'marcelo melo andré sá', '6 - 7 ( 9 ) , 6 - 2 , ( 10 - 7 )']] |
grid energy storage | https://en.wikipedia.org/wiki/Grid_energy_storage | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1646838-1.html.csv | unique | the flow grid energy storage technology is the only type of technology with moving parts . | {'scope': 'all', 'row': '1', 'col': '2', 'col_other': '1', 'criterion': 'equal', 'value': 'yes', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'moving parts', 'yes'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose moving parts record fuzzily matches to yes .', 'tostr': 'filter_eq { all_rows ; moving parts ; yes }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; moving parts ; yes } }', 'tointer': 'select the rows whose moving parts record fuzzily matches to yes . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'moving parts', 'yes'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose moving parts record fuzzily matches to yes .', 'tostr': 'filter_eq { all_rows ; moving parts ; yes }'}, 'technology'], 'result': 'flow', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; moving parts ; yes } ; technology }'}, 'flow'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; moving parts ; yes } ; technology } ; flow }', 'tointer': 'the technology record of this unqiue row is flow .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; moving parts ; yes } } ; eq { hop { filter_eq { all_rows ; moving parts ; yes } ; technology } ; flow } } = true', 'tointer': 'select the rows whose moving parts record fuzzily matches to yes . there is only one such row in the table . the technology record of this unqiue row is flow .'} | and { only { filter_eq { all_rows ; moving parts ; yes } } ; eq { hop { filter_eq { all_rows ; moving parts ; yes } ; technology } ; flow } } = true | select the rows whose moving parts record fuzzily matches to yes . there is only one such row in the table . the technology record of this unqiue row is flow . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'moving parts_7': 7, 'yes_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'technology_9': 9, 'flow_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'moving parts_7': 'moving parts', 'yes_8': 'yes', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'technology_9': 'technology', 'flow_10': 'flow'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'moving parts_7': [0], 'yes_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'technology_9': [2], 'flow_10': [3]} | ['technology', 'moving parts', 'room temperature', 'flammable', 'toxic materials', 'in production', 'rare metals'] | [['flow', 'yes', 'yes', 'no', 'yes', 'no', 'no'], ['liquid metal', 'no', 'no', 'yes', 'no', 'no', 'no'], ['sodium - ion', 'no', 'no', 'yes', 'no', 'no', 'no'], ['lead - acid', 'no', 'yes', 'no', 'yes', 'yes', 'no'], ['sodium - sulfur batteries', 'no', 'no', 'no', 'yes', 'yes', 'no'], ['ni - cd', 'no', 'yes', 'no', 'yes', 'yes', 'yes'], ['lithium - ion', 'no', 'yes', 'yes', 'no', 'yes', 'no']] |
television in thailand | https://en.wikipedia.org/wiki/Television_in_Thailand | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18987481-2.html.csv | count | two of the channels in thai television are owned by the royal thai army . | {'scope': 'all', 'criterion': 'equal', 'value': 'royal thai army', 'result': '2', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'owner', 'royal thai army'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose owner record fuzzily matches to royal thai army .', 'tostr': 'filter_eq { all_rows ; owner ; royal thai army }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; owner ; royal thai army } }', 'tointer': 'select the rows whose owner record fuzzily matches to royal thai army . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; owner ; royal thai army } } ; 2 } = true', 'tointer': 'select the rows whose owner record fuzzily matches to royal thai army . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; owner ; royal thai army } } ; 2 } = true | select the rows whose owner record fuzzily matches to royal thai army . 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, 'owner_5': 5, 'royal thai army_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', 'owner_5': 'owner', 'royal thai army_6': 'royal thai army', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'owner_5': [0], 'royal thai army_6': [0], '2_7': [2]} | ['name', 'network', 'owner', 'launch date', 'channel ( bkk )', 'broadcasting area', 'transmitted area', 'broadcasting hours'] | [['channel 3', 'mcot and bangkok entertainment co , ltd', 'bec - tero', '26 march 1970', '3 / 32 ( vhf / uhf )', 'rama iv road', 'bangkok', '24 - hours'], ['rta tv - 5', 'royal thai army radio and television', 'royal thai army', '25 january 1958', '5 ( vhf )', 'sanam pao', 'bangkok', '24 - hours'], ['bbtv channel 7', 'bangkok broadcasting and tv co , ltd', 'royal thai army', '1 december 1967', '7 ( vhf )', 'mo chit', 'bangkok', '24 - hours'], ['modernine tv', 'mcot', 'mcot', '24 june 1955', '9 ( vhf )', 'mcot', 'bangkok', '24 - hours'], ['nbt', 'nbt', 'government', '11 july 1988', '11 ( vhf )', 'vibhavadi rangsit road din daeng', 'bangkok', '24 - hours'], ['thai pbs', 'thai public broadcasting service', 'government and public', '15 january 2008', '29 ( uhf )', 'vibhavadi rangsit road lak si', 'bangkok', '21 - hours ( 5:00 am - 2:00 am )']] |
list of sequenced bacterial genomes | https://en.wikipedia.org/wiki/List_of_sequenced_bacterial_genomes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11664498-16.html.csv | comparative | borella garinii has a lower amount of genes than treponema denticola . | {'row_1': '2', 'row_2': '7', 'col': '5', 'col_other': '1', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'species', 'borrelia garinii'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose species record fuzzily matches to borrelia garinii .', 'tostr': 'filter_eq { all_rows ; species ; borrelia garinii }'}, 'genes'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; species ; borrelia garinii } ; genes }', 'tointer': 'select the rows whose species record fuzzily matches to borrelia garinii . take the genes record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'species', 'treponema denticola'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose species record fuzzily matches to treponema denticola .', 'tostr': 'filter_eq { all_rows ; species ; treponema denticola }'}, 'genes'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; species ; treponema denticola } ; genes }', 'tointer': 'select the rows whose species record fuzzily matches to treponema denticola . take the genes record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; species ; borrelia garinii } ; genes } ; hop { filter_eq { all_rows ; species ; treponema denticola } ; genes } } = true', 'tointer': 'select the rows whose species record fuzzily matches to borrelia garinii . take the genes record of this row . select the rows whose species record fuzzily matches to treponema denticola . take the genes record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; species ; borrelia garinii } ; genes } ; hop { filter_eq { all_rows ; species ; treponema denticola } ; genes } } = true | select the rows whose species record fuzzily matches to borrelia garinii . take the genes record of this row . select the rows whose species record fuzzily matches to treponema denticola . take the genes 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, 'species_7': 7, 'borrelia garinii_8': 8, 'genes_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'species_11': 11, 'treponema denticola_12': 12, 'genes_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', 'species_7': 'species', 'borrelia garinii_8': 'borrelia garinii', 'genes_9': 'genes', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'species_11': 'species', 'treponema denticola_12': 'treponema denticola', 'genes_13': 'genes'} | {'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'species_7': [0], 'borrelia garinii_8': [0], 'genes_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'species_11': [1], 'treponema denticola_12': [1], 'genes_13': [3]} | ['species', 'strain', 'type', 'base pairs', 'genes'] | [['borrelia burgdorferi', 'b31', 'spirochaetes', '910724', '850'], ['borrelia garinii', 'pbi', 'spirochaetes', '904246', '832'], ['leptospira interrogans', '56601', 'spirochaetes', '4332241', '4358'], ['unspecified', 'unspecified', 'spirochaetes', '358943', '367'], ['leptospira interrogans', 'fiocruzl1130', 'spirochaetes', '4277185', '3394'], ['unspecified', 'unspecified', 'spirochaetes', '350181', '264'], ['treponema denticola', 'atcc35405', 'spirochaetes', '2843201', '2767'], ['treponema pallidum', 'nichols', 'spirochaetes', '1138011', '1031']] |
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