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2007 - 08 colorado avalanche season | https://en.wikipedia.org/wiki/2007%E2%80%9308_Colorado_Avalanche_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11786147-8.html.csv | count | in the 2007 - 08 colorado avalanche season , among the games where colorado was a visitor , 2 of them drew more than 20,000 people . | {'scope': 'subset', 'criterion': 'greater_than', 'value': '20000', 'result': '2', 'col': '6', 'subset': {'col': '2', 'criterion': 'equal', 'value': 'colorado'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'visitor', 'colorado'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; visitor ; colorado }', 'tointer': 'select the rows whose visitor record fuzzily matches to colorado .'}, 'attendance', '20000'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose visitor record fuzzily matches to colorado . among these rows , select the rows whose attendance record is greater than 20000 .', 'tostr': 'filter_greater { filter_eq { all_rows ; visitor ; colorado } ; attendance ; 20000 }'}], 'result': '2', 'ind': 2, 'tostr': 'count { filter_greater { filter_eq { all_rows ; visitor ; colorado } ; attendance ; 20000 } }', 'tointer': 'select the rows whose visitor record fuzzily matches to colorado . among these rows , select the rows whose attendance record is greater than 20000 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_greater { filter_eq { all_rows ; visitor ; colorado } ; attendance ; 20000 } } ; 2 } = true', 'tointer': 'select the rows whose visitor record fuzzily matches to colorado . among these rows , select the rows whose attendance record is greater than 20000 . the number of such rows is 2 .'} | eq { count { filter_greater { filter_eq { all_rows ; visitor ; colorado } ; attendance ; 20000 } } ; 2 } = true | select the rows whose visitor record fuzzily matches to colorado . among these rows , select the rows whose attendance record is greater than 20000 . the number of such rows is 2 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_greater_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'visitor_6': 6, 'colorado_7': 7, 'attendance_8': 8, '20000_9': 9, '2_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_greater_1': 'filter_greater', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'visitor_6': 'visitor', 'colorado_7': 'colorado', 'attendance_8': 'attendance', '20000_9': '20000', '2_10': '2'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_greater_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'visitor_6': [0], 'colorado_7': [0], 'attendance_8': [1], '20000_9': [1], '2_10': [3]} | ['date', 'visitor', 'score', 'home', 'decision', 'attendance', 'record'] | [['february 1', 'colorado', '0 - 2', 'detroit', 'budaj', '20066', '27 - 21 - 4'], ['february 2', 'colorado', '6 - 4', 'st louis', 'budaj', '19150', '28 - 21 - 4'], ['february 4', 'phoenix', '4 - 3', 'colorado', 'budaj', '14381', '28 - 21 - 5'], ['february 6', 'colorado', '3 - 1', 'san jose', 'theodore', '17087', '29 - 21 - 5'], ['february 9', 'colorado', '6 - 2', 'vancouver', 'theodore', '18630', '30 - 21 - 5'], ['february 12', 'anaheim', '2 - 1', 'colorado', 'theodore', '16257', '30 - 22 - 5'], ['february 14', 'st louis', '4 - 1', 'colorado', 'theodore', '17131', '30 - 23 - 5'], ['february 17', 'colorado', '1 - 2', 'chicago', 'theodore', '21715', '30 - 24 - 5'], ['february 18', 'detroit', '4 - 0', 'colorado', 'theodore', '18007', '30 - 25 - 5'], ['february 20', 'colorado', '2 - 3', 'anaheim', 'budaj', '17174', '30 - 25 - 6'], ['february 22', 'colorado', '3 - 2', 'phoenix', 'theodore', '15882', '31 - 25 - 6'], ['february 24', 'colorado', '2 - 3', 'edmonton', 'theodore', '16839', '31 - 26 - 6'], ['february 26', 'colorado', '3 - 2', 'calgary', 'theodore', '19289', '32 - 26 - 6'], ['february 27', 'colorado', '3 - 2', 'vancouver', 'theodore', '18630', '33 - 26 - 6']] |
best international athlete espy award | https://en.wikipedia.org/wiki/Best_International_Athlete_ESPY_Award | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10587252-1.html.csv | unique | the only baseball player to receive the best international athlete espy award was albert pujols . | {'scope': 'all', 'row': '1', 'col': '6', 'col_other': '2', 'criterion': 'equal', 'value': 'baseball', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'sport', 'baseball'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose sport record fuzzily matches to baseball .', 'tostr': 'filter_eq { all_rows ; sport ; baseball }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; sport ; baseball } }', 'tointer': 'select the rows whose sport record fuzzily matches to baseball . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'sport', 'baseball'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose sport record fuzzily matches to baseball .', 'tostr': 'filter_eq { all_rows ; sport ; baseball }'}, 'sportsperson'], 'result': 'albert pujols', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; sport ; baseball } ; sportsperson }'}, 'albert pujols'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; sport ; baseball } ; sportsperson } ; albert pujols }', 'tointer': 'the sportsperson record of this unqiue row is albert pujols .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; sport ; baseball } } ; eq { hop { filter_eq { all_rows ; sport ; baseball } ; sportsperson } ; albert pujols } } = true', 'tointer': 'select the rows whose sport record fuzzily matches to baseball . there is only one such row in the table . the sportsperson record of this unqiue row is albert pujols .'} | and { only { filter_eq { all_rows ; sport ; baseball } } ; eq { hop { filter_eq { all_rows ; sport ; baseball } ; sportsperson } ; albert pujols } } = true | select the rows whose sport record fuzzily matches to baseball . there is only one such row in the table . the sportsperson record of this unqiue row is albert pujols . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'sport_7': 7, 'baseball_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'sportsperson_9': 9, 'albert pujols_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'sport_7': 'sport', 'baseball_8': 'baseball', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'sportsperson_9': 'sportsperson', 'albert pujols_10': 'albert pujols'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'sport_7': [0], 'baseball_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'sportsperson_9': [2], 'albert pujols_10': [3]} | ['year', 'sportsperson', 'nation of birth', 'team', 'competition , federation , or league', 'sport'] | [['2006', 'albert pujols', 'dominican republic', 'st louis cardinals', 'major league baseball', 'baseball'], ['2007', 'roger federer', 'switzerland', 'not applicable', 'atp tour', 'tennis'], ['2008', 'lorena ochoa', 'mexico', 'not applicable', 'lpga tour', 'golf'], ['2009', 'usain bolt', 'jamaica', 'not applicable', 'not applicable', 'athletics'], ['2012', 'lionel messi', 'argentina', 'fc barcelona / argentina', 'la liga / fifa / uefa / afa', 'soccer']] |
longyan | https://en.wikipedia.org/wiki/Longyan | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1204998-2.html.csv | ordinal | liancheng county has the 2nd lowest population among districts and counties in longyan . | {'row': '7', 'col': '7', 'order': '2', 'col_other': '1', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'population', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; population ; 2 }'}, 'english name'], 'result': 'liancheng county', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; population ; 2 } ; english name }'}, 'liancheng county'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; population ; 2 } ; english name } ; liancheng county } = true', 'tointer': 'select the row whose population record of all rows is 2nd minimum . the english name record of this row is liancheng county .'} | eq { hop { nth_argmin { all_rows ; population ; 2 } ; english name } ; liancheng county } = true | select the row whose population record of all rows is 2nd minimum . the english name record of this row is liancheng county . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'population_5': 5, '2_6': 6, 'english name_7': 7, 'liancheng county_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', 'population_5': 'population', '2_6': '2', 'english name_7': 'english name', 'liancheng county_8': 'liancheng county'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'population_5': [0], '2_6': [0], 'english name_7': [1], 'liancheng county_8': [2]} | ['english name', 'simplified', 'traditional', 'pinyin', 'hakka', 'area', 'population', 'density'] | [['xinluo district', '新罗区', '新羅區', 'xīnluó qū', 'sîn - lò - khî', '2685', '662429', '247'], ['zhangping city', '漳平市', '漳平市', 'zhāngpíng shì', 'chông - phìn - sṳ', '2975', '240194', '81'], ['changting county', '长汀县', '長汀縣', 'chángtīng xiàn', 'tshòng - tin - yen', '3099', '393390', '127'], ['yongding county', '永定县', '永定縣', 'yǒngdìng xiàn', 'yún - thin - yen', '2216', '362658', '164'], ['shanghang county', '上杭县', '上杭縣', 'shàngháng xiàn', 'sông - hông - yen', '2879', '374047', '130'], ['wuping county', '武平县', '武平縣', 'wǔpíng xiàn', 'vú - phìn - yen', '2630', '278182', '106'], ['liancheng county', '连城县', '連城縣', 'liánchéng xiàn', 'lièn - sàng - yen', '2596', '248645', '96']] |
2008 - 09 rugby - bundesliga | https://en.wikipedia.org/wiki/2008%E2%80%9309_Rugby-Bundesliga | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-20989972-8.html.csv | majority | all of the teams in the 2008 - 09 rugby - bundesliga played a total of 18 matches . | {'scope': 'all', 'col': '3', 'most_or_all': 'all', 'criterion': 'equal', 'value': '18', 'subset': None} | {'func': 'all_eq', 'args': ['all_rows', 'played', '18'], 'result': True, 'ind': 0, 'tointer': 'for the played records of all rows , all of them are equal to 18 .', 'tostr': 'all_eq { all_rows ; played ; 18 } = true'} | all_eq { all_rows ; played ; 18 } = true | for the played records of all rows , all of them are equal to 18 . | 1 | 1 | {'all_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'played_3': 3, '18_4': 4} | {'all_eq_0': 'all_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'played_3': 'played', '18_4': '18'} | {'all_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'played_3': [0], '18_4': [0]} | ['', 'club', 'played', 'won', 'drawn', 'lost', 'points for', 'points against', 'difference', 'points'] | [['1', 'dsv 78 / 08 ricklingen', '18', '18', '0', '0', '1138', '135', '1003', '87'], ['2', 'tsv victoria linden', '18', '15', '0', '3', '720', '246', '474', '72'], ['3', 'usv potsdam', '18', '14', '0', '4', '804', '271', '533', '69'], ['4', 'fc st pauli rugby', '18', '11', '0', '7', '632', '311', '321', '56'], ['5', 'sg sv odin / vfr dãhren', '18', '11', '0', '7', '509', '328', '181', '52'], ['6', 'ru hohen neuendorf', '18', '9', '0', '9', '452', '401', '51', '45'], ['7', 'sc germania list', '18', '4', '0', '14', '250', '813', '- 563', '20'], ['8', 'hamburger rc', '18', '4', '0', '14', '235', '891', '- 656', '19'], ['9', 'berliner sv 92 rugby', '18', '3', '1', '14', '201', '857', '- 656', '15']] |
1967 - 68 pittsburgh penguins season | https://en.wikipedia.org/wiki/1967%E2%80%9368_Pittsburgh_Penguins_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13931419-3.html.csv | majority | in november of the 1967 - 68 pittsburgh penguins season , most games had an attendance under 10000 . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'less_than', 'value': '10000', 'subset': None} | {'func': 'most_less', 'args': ['all_rows', 'attendance', '10000'], 'result': True, 'ind': 0, 'tointer': 'for the attendance records of all rows , most of them are less than 10000 .', 'tostr': 'most_less { all_rows ; attendance ; 10000 } = true'} | most_less { all_rows ; attendance ; 10000 } = true | for the attendance records of all rows , most of them are less than 10000 . | 1 | 1 | {'most_less_0': 0, 'result_1': 1, 'all_rows_2': 2, 'attendance_3': 3, '10000_4': 4} | {'most_less_0': 'most_less', 'result_1': 'true', 'all_rows_2': 'all_rows', 'attendance_3': 'attendance', '10000_4': '10000'} | {'most_less_0': [1], 'result_1': [], 'all_rows_2': [0], 'attendance_3': [0], '10000_4': [0]} | ['date', 'visitor', 'score', 'home', 'attendance', 'record', 'points'] | [['november 1', 'penguins', '4 - 1', 'north stars', '7535', '4 - 6 - 1', '9'], ['november 4', 'penguins', '1 - 0', 'seals', '4549', '5 - 6 - 1', '11'], ['november 8', 'flyers', '1 - 1', 'penguins', '4719', '5 - 6 - 2', '12'], ['november 9', 'penguins', '1 - 5', 'red wings', '10683', '5 - 7 - 2', '12'], ['november 11', 'blues', '5 - 1', 'penguins', '7183', '5 - 8 - 2', '12'], ['november 15', 'flyers', '0 - 5', 'penguins', '6876', '6 - 8 - 2', '14'], ['november 18', 'penguins', '5 - 3', 'blues', '7715', '7 - 8 - 2', '16'], ['november 22', 'bruins', '1 - 4', 'penguins', '9701', '8 - 8 - 2', '18'], ['november 24', 'penguins', '3 - 5', 'kings', '6409', '8 - 9 - 2', '18'], ['november 25', 'penguins', '2 - 2', 'seals', '5977', '8 - 9 - 3', '19'], ['november 29', 'seals', '1 - 6', 'penguins', '4499', '9 - 9 - 3', '21']] |
françoise dürr | https://en.wikipedia.org/wiki/Fran%C3%A7oise_D%C3%BCrr | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2112025-3.html.csv | majority | most of the mixed doubles tournaments that françoise dürr competed in were for the french open championship . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'french open', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'championship', 'french open'], 'result': True, 'ind': 0, 'tointer': 'for the championship records of all rows , most of them fuzzily match to french open .', 'tostr': 'most_eq { all_rows ; championship ; french open } = true'} | most_eq { all_rows ; championship ; french open } = true | for the championship records of all rows , most of them fuzzily match to french open . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'championship_3': 3, 'french open_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'championship_3': 'championship', 'french open_4': 'french open'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'championship_3': [0], 'french open_4': [0]} | ['outcome', 'year', 'championship', 'surface', 'partner', 'opponents in the final', 'score in the final'] | [['winner', '1968', 'french open', 'clay', 'jean - claude barclay', 'billie jean king owen davidson', '6 - 1 , 6 - 4'], ['runner - up', '1969', 'french open', 'clay', 'jean - claude barclay', 'margaret court marty riessen', '6 - 3 , 6 - 2'], ['runner - up', '1969', 'us open', 'grass', 'dennis ralston', 'margaret court marty riessen', '6 - 4 , 7 - 5'], ['runner - up', '1970', 'french open', 'clay', 'jean - claude barclay', 'billie jean king bob hewitt', '3 - 6 , 6 - 4 , 6 - 2'], ['winner', '1971', 'french open', 'clay', 'jean - claude barclay', 'winnie shaw thomas lejus', '6 - 2 , 6 - 4'], ['runner - up', '1972', 'french open', 'clay', 'jean - claude barclay', 'evonne goolagong cawley kim warwick', '6 - 2 , 6 - 4'], ['winner', '1973', 'french open', 'clay', 'jean - claude barclay', 'betty stöve patrice dominguez', '6 - 1 , 6 - 4']] |
dick stockton ( tennis ) | https://en.wikipedia.org/wiki/Dick_Stockton_%28tennis%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11084877-1.html.csv | count | dick stockton ( tennis ) had jimmy connors as an opponent 3 times in 1977 . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'jimmy connors', 'result': '3', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', 'jimmy connors'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose opponent record fuzzily matches to jimmy connors .', 'tostr': 'filter_eq { all_rows ; opponent ; jimmy connors }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; opponent ; jimmy connors } }', 'tointer': 'select the rows whose opponent record fuzzily matches to jimmy connors . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; opponent ; jimmy connors } } ; 3 } = true', 'tointer': 'select the rows whose opponent record fuzzily matches to jimmy connors . the number of such rows is 3 .'} | eq { count { filter_eq { all_rows ; opponent ; jimmy connors } } ; 3 } = true | select the rows whose opponent record fuzzily matches to jimmy connors . the number of such rows is 3 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'opponent_5': 5, 'jimmy connors_6': 6, '3_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'opponent_5': 'opponent', 'jimmy connors_6': 'jimmy connors', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'opponent_5': [0], 'jimmy connors_6': [0], '3_7': [2]} | ['outcome', 'date', 'championship', 'surface', 'opponent', 'score'] | [['runner - up', '1971', 'merion , us', 'hard', 'clark graebner', '2 - 6 , 4 - 6 , 7 - 6 , 5 - 7'], ['runner - up', '1973', 'miami wct , us', 'hard', 'rod laver', '6 - 7 , 3 - 6 , 5 - 7'], ['winner', '1974', 'atlanta wct , us', 'clay', 'jiří hřebec', '6 - 2 , 6 - 1'], ['runner - up', '1974', 'charlotte , us', 'clay', 'jeff borowiak', '4 - 6 , 7 - 5 , 6 - 7'], ['winner', '1974', 'adelaide , australia', 'grass', 'geoff masters', '6 - 2 , 6 - 3 , 6 - 2'], ['runner - up', '1975', 'fort worth wct , us', 'hard', 'john alexander', '6 - 7 , 6 - 4 , 3 - 6'], ['winner', '1975', 'san antonio wct , us', 'hard', 'stan smith', '7 - 5 , 2 - 6 , 7 - 6'], ['runner - up', '1975', 'washington indoor wct , us', 'carpet', 'mark cox', '2 - 6 , 6 - 7'], ['winner', '1976', 'lagos wct , nigeria', 'clay', 'arthur ashe', '6 - 3 , 6 - 2'], ['runner - up', '1976', 'sydney outdoor , australia', 'grass', 'tony roche', '3 - 6 , 6 - 3 , 3 - 6 , 4 - 6'], ['winner', '1977', 'philadelphia wct , us', 'carpet', 'jimmy connors', '3 - 6 , 6 - 4 , 3 - 6 , 6 - 1 , 6 - 2'], ['winner', '1977', 'toronto indoor wct , canada', 'carpet', 'jimmy connors', '5 - 6 , ret'], ['winner', '1977', 'rotterdam , netherlands', 'carpet', 'ilie năstase', '2 - 6 , 6 - 3 , 6 - 3'], ['runner - up', '1977', 'dallas wct , us - wct finals', 'carpet', 'jimmy connors', '7 - 6 , 1 - 6 , 4 - 6 , 3 - 6'], ['runner - up', '1978', 'birmingham wct , us', 'carpet', 'björn borg', '6 - 7 , 5 - 7'], ['winner', '1978', 'little rock , us', 'carpet', 'hank pfister', '6 - 4 , 3 - 5 , ret'], ['runner - up', '1978', 'san francisco , us', 'carpet', 'john mcenroe', '6 - 2 , 6 - 7 , 2 - 6'], ['runner - up', '1981', 'south orange , us', 'clay', 'shlomo glickstein', '3 - 6 , 7 - 5 , 4 - 6']] |
2007 - 08 fis ski jumping world cup | https://en.wikipedia.org/wiki/2007%E2%80%9308_FIS_Ski_Jumping_World_Cup | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14407512-16.html.csv | comparative | simon ammann 's first jump on 27 january 2008 was longer than thomas morgenstern 's . | {'row_1': '3', 'row_2': '2', 'col': '4', 'col_other': '2', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'name', 'simon ammann'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose name record fuzzily matches to simon ammann .', 'tostr': 'filter_eq { all_rows ; name ; simon ammann }'}, '1st ( m )'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; name ; simon ammann } ; 1st ( m ) }', 'tointer': 'select the rows whose name record fuzzily matches to simon ammann . take the 1st ( m ) record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'name', 'thomas morgenstern'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose name record fuzzily matches to thomas morgenstern .', 'tostr': 'filter_eq { all_rows ; name ; thomas morgenstern }'}, '1st ( m )'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; name ; thomas morgenstern } ; 1st ( m ) }', 'tointer': 'select the rows whose name record fuzzily matches to thomas morgenstern . take the 1st ( m ) record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; name ; simon ammann } ; 1st ( m ) } ; hop { filter_eq { all_rows ; name ; thomas morgenstern } ; 1st ( m ) } } = true', 'tointer': 'select the rows whose name record fuzzily matches to simon ammann . take the 1st ( m ) record of this row . select the rows whose name record fuzzily matches to thomas morgenstern . take the 1st ( m ) record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; name ; simon ammann } ; 1st ( m ) } ; hop { filter_eq { all_rows ; name ; thomas morgenstern } ; 1st ( m ) } } = true | select the rows whose name record fuzzily matches to simon ammann . take the 1st ( m ) record of this row . select the rows whose name record fuzzily matches to thomas morgenstern . take the 1st ( m ) 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, 'name_7': 7, 'simon ammann_8': 8, '1st (m)_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'name_11': 11, 'thomas morgenstern_12': 12, '1st (m)_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', 'name_7': 'name', 'simon ammann_8': 'simon ammann', '1st (m)_9': '1st ( m )', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'name_11': 'name', 'thomas morgenstern_12': 'thomas morgenstern', '1st (m)_13': '1st ( m )'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'name_7': [0], 'simon ammann_8': [0], '1st (m)_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'name_11': [1], 'thomas morgenstern_12': [1], '1st (m)_13': [3]} | ['rank', 'name', 'nationality', '1st ( m )', 'points', 'overall wc points ( rank )'] | [['1', 'anders bardal', 'nor', '137.0', '149.1', '461 ( 6 )'], ['2', 'thomas morgenstern', 'aut', '135.0', '145.0', '1255 ( 1 )'], ['3', 'simon ammann', 'sui', '136.5', '144.2', '448 ( 8 )'], ['4', 'adam małysz', 'pol', '133.5', '141.3', '386 ( 11 )'], ['5', 'andreas küttel', 'sui', '134.0', '141.2', '459 ( 7 )']] |
w.d. & h.o. wills tournament | https://en.wikipedia.org/wiki/W.D._%26_H.O._Wills_Tournament | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15942377-1.html.csv | comparative | bernard gallacher had a lower score than peter butler in the w.d. & h.o. wills tournament . | {'row_1': '6', 'row_2': '7', 'col': '5', 'col_other': '3', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'winner', 'bernard gallacher'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose winner record fuzzily matches to bernard gallacher .', 'tostr': 'filter_eq { all_rows ; winner ; bernard gallacher }'}, 'score'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; winner ; bernard gallacher } ; score }', 'tointer': 'select the rows whose winner record fuzzily matches to bernard gallacher . take the score record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'winner', 'peter butler'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose winner record fuzzily matches to peter butler .', 'tostr': 'filter_eq { all_rows ; winner ; peter butler }'}, 'score'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; winner ; peter butler } ; score }', 'tointer': 'select the rows whose winner record fuzzily matches to peter butler . take the score record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; winner ; bernard gallacher } ; score } ; hop { filter_eq { all_rows ; winner ; peter butler } ; score } } = true', 'tointer': 'select the rows whose winner record fuzzily matches to bernard gallacher . take the score record of this row . select the rows whose winner record fuzzily matches to peter butler . take the score record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; winner ; bernard gallacher } ; score } ; hop { filter_eq { all_rows ; winner ; peter butler } ; score } } = true | select the rows whose winner record fuzzily matches to bernard gallacher . take the score record of this row . select the rows whose winner record fuzzily matches to peter butler . take the score record of this row . the first record is less than the second record . | 5 | 5 | {'less_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'winner_7': 7, 'bernard gallacher_8': 8, 'score_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'winner_11': 11, 'peter butler_12': 12, 'score_13': 13} | {'less_4': 'less', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'winner_7': 'winner', 'bernard gallacher_8': 'bernard gallacher', 'score_9': 'score', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'winner_11': 'winner', 'peter butler_12': 'peter butler', 'score_13': 'score'} | {'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'winner_7': [0], 'bernard gallacher_8': [0], 'score_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'winner_11': [1], 'peter butler_12': [1], 'score_13': [3]} | ['year', 'venue', 'winner', 'country', 'score'] | [['1974', 'kings norton golf club', 'neil coles', 'england', '283 ( - 5 )'], ['1973', 'kings norton golf club', 'charles coody', 'united states', '281 ( - 7 )'], ['1972', 'dalmahoy golf club', 'peter thomson', 'australia', '270 ( - 14 )'], ['1971', 'dalmahoy golf club', 'bernard hunt', 'england', '276 ( - 8 )'], ['1970', 'dalmahoy golf club', 'tony jacklin', 'england', '267 ( - 17 )'], ['1969', 'moor park golf club', 'bernard gallacher', 'scotland', '275'], ['1968', 'pannal golf club', 'peter butler', 'england', '281']] |
1972 vfl season | https://en.wikipedia.org/wiki/1972_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10826385-15.html.csv | aggregation | the average score of away teams in the 1972 vfl season was 11.36 . | {'scope': 'all', 'col': '4', 'type': 'average', 'result': '11.36', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'away team score'], 'result': '11.36', 'ind': 0, 'tostr': 'avg { all_rows ; away team score }'}, '11.36'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; away team score } ; 11.36 } = true', 'tointer': 'the average of the away team score record of all rows is 11.36 .'} | round_eq { avg { all_rows ; away team score } ; 11.36 } = true | the average of the away team score record of all rows is 11.36 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'away team score_4': 4, '11.36_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'away team score_4': 'away team score', '11.36_5': '11.36'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'away team score_4': [0], '11.36_5': [1]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['footscray', '14.7 ( 91 )', 'st kilda', '9.11 ( 65 )', 'western oval', '18655', '15 july 1972'], ['fitzroy', '16.14 ( 110 )', 'north melbourne', '9.12 ( 66 )', 'junction oval', '7007', '15 july 1972'], ['essendon', '13.12 ( 90 )', 'richmond', '17.9 ( 111 )', 'windy hill', '22251', '15 july 1972'], ['carlton', '20.8 ( 128 )', 'south melbourne', '8.15 ( 63 )', 'princes park', '14465', '15 july 1972'], ['hawthorn', '19.14 ( 128 )', 'geelong', '15.8 ( 98 )', 'glenferrie oval', '12425', '15 july 1972'], ['collingwood', '10.13 ( 73 )', 'melbourne', '8.10 ( 58 )', 'vfl park', '30883', '15 july 1972']] |
list of tvb series ( 2006 ) | https://en.wikipedia.org/wiki/List_of_TVB_series_%282006%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10942714-1.html.csv | comparative | the saviour of the soul drew more viewers for its finale than men in pain drew for its finale . | {'row_1': '3', 'row_2': '9', 'col': '8', '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', 'english title', 'the saviour of the soul'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose english title record fuzzily matches to the saviour of the soul .', 'tostr': 'filter_eq { all_rows ; english title ; the saviour of the soul }'}, 'hk viewers'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; english title ; the saviour of the soul } ; hk viewers }', 'tointer': 'select the rows whose english title record fuzzily matches to the saviour of the soul . take the hk viewers record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'english title', 'men in pain'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose english title record fuzzily matches to men in pain .', 'tostr': 'filter_eq { all_rows ; english title ; men in pain }'}, 'hk viewers'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; english title ; men in pain } ; hk viewers }', 'tointer': 'select the rows whose english title record fuzzily matches to men in pain . take the hk viewers record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; english title ; the saviour of the soul } ; hk viewers } ; hop { filter_eq { all_rows ; english title ; men in pain } ; hk viewers } } = true', 'tointer': 'select the rows whose english title record fuzzily matches to the saviour of the soul . take the hk viewers record of this row . select the rows whose english title record fuzzily matches to men in pain . take the hk viewers record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; english title ; the saviour of the soul } ; hk viewers } ; hop { filter_eq { all_rows ; english title ; men in pain } ; hk viewers } } = true | select the rows whose english title record fuzzily matches to the saviour of the soul . take the hk viewers record of this row . select the rows whose english title record fuzzily matches to men in pain . take the hk viewers 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, 'english title_7': 7, 'the saviour of the soul_8': 8, 'hk viewers_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'english title_11': 11, 'men in pain_12': 12, 'hk viewers_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', 'english title_7': 'english title', 'the saviour of the soul_8': 'the saviour of the soul', 'hk viewers_9': 'hk viewers', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'english title_11': 'english title', 'men in pain_12': 'men in pain', 'hk viewers_13': 'hk viewers'} | {'greater_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'english title_7': [0], 'the saviour of the soul_8': [0], 'hk viewers_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'english title_11': [1], 'men in pain_12': [1], 'hk viewers_13': [3]} | ['rank', 'english title', 'chinese title', 'average', 'peak', 'premiere', 'finale', 'hk viewers'] | [['1', 'la femme desperado', '女人唔易做', '33', '41', '31', '34', '2.14 million'], ['2', 'forensic heroes', '法證先鋒', '33', '43', '28', '37', '2.11 million'], ['3', 'the saviour of the soul', '神鵰俠侶', '32', '40', '32', '35', '2.07 million'], ['4', 'love guaranteed', '愛情全保', '32', '36', '30', '34', '2.07 million'], ['5', 'bar bender', '潮爆大狀', '32', '38', '31', '34', '2.06 million'], ['6', 'the dance of passion', '火舞黃沙', '32', '38', '34', '35', '2.05 million'], ['7', "maiden 's vow", '鳳凰四重奏', '32', '37', '32', '29', '2.05 million'], ['8', 'to grow with love', '肥田囍事', '32', '35', '32', '32', '2.04 million'], ['9', 'men in pain', '男人之苦', '32', '39', '28', '33', '2.03 million'], ['10', 'under the canopy of love', '天幕下的戀人', '31', '37', '28', '33', '2.02 million']] |
communication with extraterrestrial intelligence | https://en.wikipedia.org/wiki/Communication_with_extraterrestrial_intelligence | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1446835-2.html.csv | comparative | of the communications with extraterrestrial intelligence , cosmic call " hd 178428 " will arrive earlier than cosmic call " hd 186408 " . | {'row_1': '3', 'row_2': '1', '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', 'designation hd', 'hd 178428'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose designation hd record fuzzily matches to hd 178428 .', 'tostr': 'filter_eq { all_rows ; designation hd ; hd 178428 }'}, 'arrival date'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; designation hd ; hd 178428 } ; arrival date }', 'tointer': 'select the rows whose designation hd record fuzzily matches to hd 178428 . take the arrival date record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'designation hd', 'hd 186408'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose designation hd record fuzzily matches to hd 186408 .', 'tostr': 'filter_eq { all_rows ; designation hd ; hd 186408 }'}, 'arrival date'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; designation hd ; hd 186408 } ; arrival date }', 'tointer': 'select the rows whose designation hd record fuzzily matches to hd 186408 . take the arrival date record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; designation hd ; hd 178428 } ; arrival date } ; hop { filter_eq { all_rows ; designation hd ; hd 186408 } ; arrival date } } = true', 'tointer': 'select the rows whose designation hd record fuzzily matches to hd 178428 . take the arrival date record of this row . select the rows whose designation hd record fuzzily matches to hd 186408 . take the arrival date record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; designation hd ; hd 178428 } ; arrival date } ; hop { filter_eq { all_rows ; designation hd ; hd 186408 } ; arrival date } } = true | select the rows whose designation hd record fuzzily matches to hd 178428 . take the arrival date record of this row . select the rows whose designation hd record fuzzily matches to hd 186408 . take the arrival 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, 'designation hd_7': 7, 'hd 178428_8': 8, 'arrival date_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'designation hd_11': 11, 'hd 186408_12': 12, 'arrival 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', 'designation hd_7': 'designation hd', 'hd 178428_8': 'hd 178428', 'arrival date_9': 'arrival date', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'designation hd_11': 'designation hd', 'hd 186408_12': 'hd 186408', 'arrival date_13': 'arrival date'} | {'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'designation hd_7': [0], 'hd 178428_8': [0], 'arrival date_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'designation hd_11': [1], 'hd 186408_12': [1], 'arrival date_13': [3]} | ['designation hd', 'constellation', 'date sent', 'arrival date', 'message'] | [['hd 186408', 'cygnus', 'may 24 , 1999', 'november 2069', 'cosmic call 1'], ['hd 190406', 'sagitta', 'june 30 , 1999', 'february 2057', 'cosmic call 1'], ['hd 178428', 'sagitta', 'june 30 , 1999', 'october 2067', 'cosmic call 1'], ['hd 190360', 'cygnus', 'july 1 , 1999', 'april 2051', 'cosmic call 1'], ['hip 4872', 'cassiopeia', 'july 6 , 2003', 'april 2036', 'cosmic call 2'], ['hd 245409', 'orion', 'july 6 , 2003', 'august 2040', 'cosmic call 2'], ['hd 75732', 'cancer', 'july 6 , 2003', 'may 2044', 'cosmic call 2'], ['hd 10307', 'andromeda', 'july 6 , 2003', 'september 2044', 'cosmic call 2'], ['hd 95128', 'ursa major', 'july 6 , 2003', 'may 2049', 'cosmic call 2']] |
tourism in costa rica | https://en.wikipedia.org/wiki/Tourism_in_Costa_Rica | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17781704-3.html.csv | comparative | mexico had the most international tourists in 2011 , and barbados had the least . | {'row_1': '11', 'row_2': '2', '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', 'selected caribbean and n latin america countries', 'mexico'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose selected caribbean and n latin america countries record fuzzily matches to mexico .', 'tostr': 'filter_eq { all_rows ; selected caribbean and n latin america countries ; mexico }'}, 'internl tourist arrivals 2011 ( x1000 )'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; selected caribbean and n latin america countries ; mexico } ; internl tourist arrivals 2011 ( x1000 ) }', 'tointer': 'select the rows whose selected caribbean and n latin america countries record fuzzily matches to mexico . take the internl tourist arrivals 2011 ( x1000 ) record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'selected caribbean and n latin america countries', 'barbados'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose selected caribbean and n latin america countries record fuzzily matches to barbados .', 'tostr': 'filter_eq { all_rows ; selected caribbean and n latin america countries ; barbados }'}, 'internl tourist arrivals 2011 ( x1000 )'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; selected caribbean and n latin america countries ; barbados } ; internl tourist arrivals 2011 ( x1000 ) }', 'tointer': 'select the rows whose selected caribbean and n latin america countries record fuzzily matches to barbados . take the internl tourist arrivals 2011 ( x1000 ) record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; selected caribbean and n latin america countries ; mexico } ; internl tourist arrivals 2011 ( x1000 ) } ; hop { filter_eq { all_rows ; selected caribbean and n latin america countries ; barbados } ; internl tourist arrivals 2011 ( x1000 ) } } = true', 'tointer': 'select the rows whose selected caribbean and n latin america countries record fuzzily matches to mexico . take the internl tourist arrivals 2011 ( x1000 ) record of this row . select the rows whose selected caribbean and n latin america countries record fuzzily matches to barbados . take the internl tourist arrivals 2011 ( x1000 ) record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; selected caribbean and n latin america countries ; mexico } ; internl tourist arrivals 2011 ( x1000 ) } ; hop { filter_eq { all_rows ; selected caribbean and n latin america countries ; barbados } ; internl tourist arrivals 2011 ( x1000 ) } } = true | select the rows whose selected caribbean and n latin america countries record fuzzily matches to mexico . take the internl tourist arrivals 2011 ( x1000 ) record of this row . select the rows whose selected caribbean and n latin america countries record fuzzily matches to barbados . take the internl tourist arrivals 2011 ( x1000 ) 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, 'selected caribbean and n latin america countries_7': 7, 'mexico_8': 8, 'internl tourist arrivals 2011 (x1000)_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'selected caribbean and n latin america countries_11': 11, 'barbados_12': 12, 'internl tourist arrivals 2011 (x1000)_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', 'selected caribbean and n latin america countries_7': 'selected caribbean and n latin america countries', 'mexico_8': 'mexico', 'internl tourist arrivals 2011 (x1000)_9': 'internl tourist arrivals 2011 ( x1000 )', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'selected caribbean and n latin america countries_11': 'selected caribbean and n latin america countries', 'barbados_12': 'barbados', 'internl tourist arrivals 2011 (x1000)_13': 'internl tourist arrivals 2011 ( x1000 )'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'selected caribbean and n latin america countries_7': [0], 'mexico_8': [0], 'internl tourist arrivals 2011 (x1000)_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'selected caribbean and n latin america countries_11': [1], 'barbados_12': [1], 'internl tourist arrivals 2011 (x1000)_13': [3]} | ['selected caribbean and n latin america countries', 'internl tourist arrivals 2011 ( x1000 )', 'internl tourism receipts 2011 ( million usd )', 'receipts per arrival 2010 ( col 2 ) / ( col 1 ) ( usd )', 'receipts per capita 2005 usd', 'revenues as % of exports goods and services 2011'] | [['bahamas ( 1 )', '1368', '2059', '1505', '6288', '74.6'], ['barbados', '568', '974', '1715', '2749', '58.5'], ['brazil', '5433', '6555', '1207', '18', '3.2'], ['chile', '3070', '1831', '596', '73', '5.3'], ['costa rica', '2196', '2156', '982', '343', '17.5'], ['colombia ( 1 )', '2385', '2083', '873', '25', '6.6'], ['cuba', '2688', 'n / d', 'n / d', '169', 'n / d'], ['dominican republic', '4306', '4353', '1011', '353', '36.2'], ['guatemala', '1225', '1350', '1102', '66', '16.0'], ['jamaica', '1952', '2012', '1031', '530', '49.2'], ['mexico', '23403', '11869', '507', '103', '5.7'], ['panama', '1473', '1926', '1308', '211', '10.6'], ['peru', '2598', '2360', '908', '41', '9.0']] |
2008 - 09 cypriot first division | https://en.wikipedia.org/wiki/2008%E2%80%9309_Cypriot_First_Division | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17054062-1.html.csv | superlative | the stadium that can hold the least amount of people is the peyia municipal stadium . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '9', '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', 'capacity'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; capacity }'}, 'venue'], 'result': 'peyia municipal stadium', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; capacity } ; venue }'}, 'peyia municipal stadium'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmin { all_rows ; capacity } ; venue } ; peyia municipal stadium } = true', 'tointer': 'select the row whose capacity record of all rows is minimum . the venue record of this row is peyia municipal stadium .'} | eq { hop { argmin { all_rows ; capacity } ; venue } ; peyia municipal stadium } = true | select the row whose capacity record of all rows is minimum . the venue record of this row is peyia municipal stadium . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'capacity_5': 5, 'venue_6': 6, 'peyia municipal stadium_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'capacity_5': 'capacity', 'venue_6': 'venue', 'peyia municipal stadium_7': 'peyia municipal stadium'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'capacity_5': [0], 'venue_6': [1], 'peyia municipal stadium_7': [2]} | ['team', 'head coach', 'team captain', 'venue', 'capacity', 'kitmaker', 'shirt sponsor', 'club chairman'] | [['aek larnaca', 'savvas constantinou', 'constantinos mina', 'neo gsz stadium', '13032', 'mass', 'cytavision', 'marios ellinas'], ['ael limassol', 'mihai stoichiţă', 'simos krassas', 'tsirion stadium', '13331', 'mass', 'sinergatiko tamieftirio lemesou', 'andreas sofokleous'], ['aep paphos', 'nir klinger', 'giorgos georgiou', 'pafiako stadium', '10000', 'mass', 'eurolink investment group', 'fillippos georgiou'], ['alki larnaca', 'panikos xiourouppas', 'andrés rouga', 'ammochostos stadium', '5500', 'legea', 'team a security', 'demetris phantousis'], ['anorthosis famagusta', 'michalis pamboris', 'nikos nicolaou', 'antonis papadopoulos stadium', '10003', 'puma', 'quality group developments', 'chris georgiades'], ['apep pitsilia', 'willy scheepers', 'bruno piano', 'tsirion stadium', '13331', 'mass', 'kkcg', 'panayiotis neokleous'], ['apoel', 'ivan jovanović', 'marinos satsias', 'gsp stadium', '22859', 'lotto', 'mtn group', 'foivos erotokritou'], ['apollon limassol', 'thomas von heesen', 'christos theophilou', 'tsirion stadium', '13331', 'lotto', 'columbia ship management', 'theodoros antoniou'], ['apop kinyras peyias', 'giorgos polyviou', 'giannis sfakianakis', 'peyia municipal stadium', '3828', 'puma', 'primetel', 'michalis mitas'], ['atromitos yeroskipou', 'sofoklis sofokleous', 'argyris petrou', 'pafiako stadium', '10000', 'umbro', 'spe yeroskipou', 'vangelis genis'], ['doxa katokopia', 'charalmbos christodoulou', 'kyriacos polykarpou', 'makario stadium', '16000', 'puma', 'yiannakas real estate ltd', 'charalambos argyrou'], ['enosis neon paralimni', 'adamos adamou & antonis kleftis', 'demos goumenos', 'paralimni stadium', '5800', 'lotto', 'elian developers', 'adamos loizou'], ['ethnikos achna', 'stéphane demol', 'christos poyiatzis', 'dasaki stadium', '7000', 'nike', 'famagusta developers', 'kikis philippou'], ['omonia', 'takis lemonis', 'costas kaiafas', 'gsp stadium', '22859', 'lotto', 'ocean tankers', 'miltiadis neophytou']] |
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 | count | there are two buildings in germany that are at least 800 feet tall . | {'scope': 'all', 'criterion': 'greater_than_eq', 'value': '800', 'result': '2', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater_eq', 'args': ['all_rows', 'height ( ft )', '800'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose height ( ft ) record is greater than or equal to 800 .', 'tostr': 'filter_greater_eq { all_rows ; height ( ft ) ; 800 }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_greater_eq { all_rows ; height ( ft ) ; 800 } }', 'tointer': 'select the rows whose height ( ft ) record is greater than or equal to 800 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_greater_eq { all_rows ; height ( ft ) ; 800 } } ; 2 } = true', 'tointer': 'select the rows whose height ( ft ) record is greater than or equal to 800 . the number of such rows is 2 .'} | eq { count { filter_greater_eq { all_rows ; height ( ft ) ; 800 } } ; 2 } = true | select the rows whose height ( ft ) record is greater than or equal to 800 . the number of such rows is 2 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_greater_eq_0': 0, 'all_rows_4': 4, 'height (ft)_5': 5, '800_6': 6, '2_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_greater_eq_0': 'filter_greater_eq', 'all_rows_4': 'all_rows', 'height (ft)_5': 'height ( ft )', '800_6': '800', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_greater_eq_0': [1], 'all_rows_4': [0], 'height (ft)_5': [0], '800_6': [0], '2_7': [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']] |
2007 toronto argonauts season | https://en.wikipedia.org/wiki/2007_Toronto_Argonauts_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11916798-4.html.csv | aggregation | in the 2007 toronto argonauts season , the total attendance for the month of august was 83969 . | {'scope': 'subset', 'col': '6', 'type': 'sum', 'result': '83969', 'subset': {'col': '2', 'criterion': 'equal', 'value': 'august'}} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', 'august'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; date ; august }', 'tointer': 'select the rows whose date record fuzzily matches to august .'}, 'attendance'], 'result': '83969', 'ind': 1, 'tostr': 'sum { filter_eq { all_rows ; date ; august } ; attendance }'}, '83969'], 'result': True, 'ind': 2, 'tostr': 'round_eq { sum { filter_eq { all_rows ; date ; august } ; attendance } ; 83969 } = true', 'tointer': 'select the rows whose date record fuzzily matches to august . the sum of the attendance record of these rows is 83969 .'} | round_eq { sum { filter_eq { all_rows ; date ; august } ; attendance } ; 83969 } = true | select the rows whose date record fuzzily matches to august . the sum of the attendance record of these rows is 83969 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'sum_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'date_5': 5, 'august_6': 6, 'attendance_7': 7, '83969_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', 'august_6': 'august', 'attendance_7': 'attendance', '83969_8': '83969'} | {'eq_2': [3], 'result_3': [], 'sum_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'date_5': [0], 'august_6': [0], 'attendance_7': [1], '83969_8': [2]} | ['week', 'date', 'opponent', 'location', 'final score', 'attendance', 'record'] | [['1', 'june 28', 'lions', 'rogers centre', 'l 24 - 22', '29157', '0 - 1'], ['2', 'july 7', 'tiger - cats', 'ivor wynne stadium', 'w 30 - 5', '28198', '1 - 1'], ['3', 'july 12', 'stampeders', 'rogers centre', 'w 48 - 15', '29304', '2 - 1'], ['4', 'july 21', 'stampeders', 'mcmahon stadium', 'l 33 - 10', '28202', '2 - 2'], ['5', 'july 26', 'alouettes', 'rogers centre', 'l 26 - 13', '31097', '2 - 3'], ['6', 'august 2', 'alouettes', 'molson stadium', 'l 29 - 27 ( ot )', '20202', '2 - 4'], ['7', 'august 10', 'roughriders', 'rogers centre', 'l 24 - 13', '34234', '2 - 5'], ['9', 'august 24', 'blue bombers', 'canad inns stadium', 'l 15 - 13', '29533', '2 - 6'], ['10', 'september 3', 'tiger - cats', 'ivor wynne stadium', 'w 32 - 14', '28644', '3 - 6'], ['11', 'september 8', 'tiger - cats', 'rogers centre', 'w 35 - 22', '28279', '4 - 6'], ['12', 'september 15', 'lions', 'bc place stadium', 'l 40 - 7', '31156', '4 - 7'], ['13', 'september 23', 'blue bombers', 'rogers centre', 'w 31 - 23', '26423', '5 - 7'], ['14', 'september 28', 'eskimos', 'commonwealth stadium', 'w 18 - 11', '31056', '6 - 7'], ['15', 'october 6', 'eskimos', 'rogers centre', 'w 33 - 8', '28354', '7 - 7'], ['16', 'october 12', 'alouettes', 'rogers centre', 'w 35 - 17', '31416', '8 - 7'], ['17', 'october 20', 'alouettes', 'olympic stadium', 'w 16 - 9', '44510', '9 - 7'], ['18', 'october 27', 'blue bombers', 'rogers centre', 'w 16 - 8', '40116', '10 - 7'], ['19', 'november 3', 'roughriders', 'mosaic stadium', 'w 41 - 13', '28800', '11 - 7']] |
sports in charlotte , north carolina | https://en.wikipedia.org/wiki/Sports_in_Charlotte%2C_North_Carolina | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15720079-6.html.csv | ordinal | jim crockett park was the charlotte venue that closed the 2nd earliest . | {'row': '2', 'col': '4', 'order': '2', 'col_other': '1', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'closed', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; closed ; 2 }'}, 'venue'], 'result': 'jim crockett park', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; closed ; 2 } ; venue }'}, 'jim crockett park'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; closed ; 2 } ; venue } ; jim crockett park } = true', 'tointer': 'select the row whose closed record of all rows is 2nd minimum . the venue record of this row is jim crockett park .'} | eq { hop { nth_argmin { all_rows ; closed ; 2 } ; venue } ; jim crockett park } = true | select the row whose closed record of all rows is 2nd minimum . the venue record of this row is jim crockett park . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'closed_5': 5, '2_6': 6, 'venue_7': 7, 'jim crockett park_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', 'closed_5': 'closed', '2_6': '2', 'venue_7': 'venue', 'jim crockett park_8': 'jim crockett park'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'closed_5': [0], '2_6': [0], 'venue_7': [1], 'jim crockett park_8': [2]} | ['venue', 'location', 'environment', 'closed', 'reason'] | [['charlotte coliseum', 'eagle lake , charlotte', 'indoor arena', '2005', 'replaced'], ['jim crockett park', 'dilworth , charlotte', 'open air , natural grass', '1985', 'arson'], ['metrolina speedway', 'metrolina fairgrounds , charlotte', 'open air , dirt', '1990s', 'abandoned'], ['belk gymnasium', 'university city , charlotte', 'indoor arena', '1996', 'converted'], ['charlotte speedway', 'charlotte', 'open air , dirt', '1957', 'closed']] |
new year live | https://en.wikipedia.org/wiki/New_Year_Live | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-24212608-1.html.csv | superlative | for the show new years live , the episode with the highest number of viewers was episode 7 . | {'scope': 'all', 'col_superlative': '6', 'row_superlative': '6', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'viewers ( millions )'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; viewers ( millions ) }'}, 'episode'], 'result': '7', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; viewers ( millions ) } ; episode }'}, '7'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; viewers ( millions ) } ; episode } ; 7 } = true', 'tointer': 'select the row whose viewers ( millions ) record of all rows is maximum . the episode record of this row is 7 .'} | eq { hop { argmax { all_rows ; viewers ( millions ) } ; episode } ; 7 } = true | select the row whose viewers ( millions ) record of all rows is maximum . the episode record of this row is 7 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'num_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'viewers (millions)_5': 5, 'episode_6': 6, '7_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'num_hop_1': 'num_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'viewers (millions)_5': 'viewers ( millions )', 'episode_6': 'episode', '7_7': '7'} | {'eq_2': [3], 'result_3': [], 'num_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'viewers (millions)_5': [0], 'episode_6': [1], '7_7': [2]} | ['episode', 'broadcast date', 'bbc one presenter ( s )', 'starring', 'radio 1 presenter', 'viewers ( millions )'] | [['1', '2005', 'clare balding', 'doug segal', 'n / a', '6.43'], ['2', '2006', 'myleene klass', 'gethin jones , natasha kaplinsky & alesha dixon', 'n / a', '6.06'], ['3', '2007', 'myleene klass', 'gethin jones , natasha kaplinsky & nick knowles', 'n / a', '5.35'], ['5', '2009', 'myleene klass', 'n / a', 'nihal', '7.65'], ['6', '2010', 'jake humphrey', 'n / a', 'nihal', '9.37'], ['7', '2011', 'jake humphrey', 'n / a', 'nihal', '10.67'], ['8', '2012', 'gabby logan', 'n / a', 'nihal', '9.73']] |
list of superfund sites in connecticut | https://en.wikipedia.org/wiki/List_of_Superfund_sites_in_Connecticut | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10840672-1.html.csv | unique | in the list of superfund sites in connecticut , new london is the only county which is proposed in 1989 . | {'scope': 'subset', 'row': '13', 'col': '4', 'col_other': '3', 'criterion': 'fuzzily_match', 'value': '1989', 'subset': {'col': '4', 'criterion': 'fuzzily_match', 'value': '1989'}} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'proposed', '1989'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; proposed ; 1989 }', 'tointer': 'select the rows whose proposed record fuzzily matches to 1989 .'}, 'proposed', '1989'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose proposed record fuzzily matches to 1989 . among these rows , select the rows whose proposed record fuzzily matches to 1989 .', 'tostr': 'filter_eq { filter_eq { all_rows ; proposed ; 1989 } ; proposed ; 1989 }'}], 'result': True, 'ind': 2, 'tostr': 'only { filter_eq { filter_eq { all_rows ; proposed ; 1989 } ; proposed ; 1989 } }', 'tointer': 'select the rows whose proposed record fuzzily matches to 1989 . among these rows , select the rows whose proposed record fuzzily matches to 1989 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'proposed', '1989'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; proposed ; 1989 }', 'tointer': 'select the rows whose proposed record fuzzily matches to 1989 .'}, 'proposed', '1989'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose proposed record fuzzily matches to 1989 . among these rows , select the rows whose proposed record fuzzily matches to 1989 .', 'tostr': 'filter_eq { filter_eq { all_rows ; proposed ; 1989 } ; proposed ; 1989 }'}, 'county'], 'result': 'new london', 'ind': 3, 'tostr': 'hop { filter_eq { filter_eq { all_rows ; proposed ; 1989 } ; proposed ; 1989 } ; county }'}, 'new london'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { filter_eq { filter_eq { all_rows ; proposed ; 1989 } ; proposed ; 1989 } ; county } ; new london }', 'tointer': 'the county record of this unqiue row is new london .'}], 'result': True, 'ind': 5, 'tostr': 'and { only { filter_eq { filter_eq { all_rows ; proposed ; 1989 } ; proposed ; 1989 } } ; eq { hop { filter_eq { filter_eq { all_rows ; proposed ; 1989 } ; proposed ; 1989 } ; county } ; new london } } = true', 'tointer': 'select the rows whose proposed record fuzzily matches to 1989 . among these rows , select the rows whose proposed record fuzzily matches to 1989 . there is only one such row in the table . the county record of this unqiue row is new london .'} | and { only { filter_eq { filter_eq { all_rows ; proposed ; 1989 } ; proposed ; 1989 } } ; eq { hop { filter_eq { filter_eq { all_rows ; proposed ; 1989 } ; proposed ; 1989 } ; county } ; new london } } = true | select the rows whose proposed record fuzzily matches to 1989 . among these rows , select the rows whose proposed record fuzzily matches to 1989 . there is only one such row in the table . the county record of this unqiue row is new london . | 8 | 6 | {'and_5': 5, 'result_6': 6, 'only_2': 2, 'filter_str_eq_1': 1, 'filter_str_eq_0': 0, 'all_rows_7': 7, 'proposed_8': 8, '1989_9': 9, 'proposed_10': 10, '1989_11': 11, 'str_eq_4': 4, 'str_hop_3': 3, 'county_12': 12, 'new london_13': 13} | {'and_5': 'and', 'result_6': 'true', 'only_2': 'only', 'filter_str_eq_1': 'filter_str_eq', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_7': 'all_rows', 'proposed_8': 'proposed', '1989_9': '1989', 'proposed_10': 'proposed', '1989_11': '1989', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'county_12': 'county', 'new london_13': 'new london'} | {'and_5': [6], 'result_6': [], 'only_2': [5], 'filter_str_eq_1': [2, 3], 'filter_str_eq_0': [1], 'all_rows_7': [0], 'proposed_8': [0], '1989_9': [0], 'proposed_10': [1], '1989_11': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'county_12': [3], 'new london_13': [4]} | ['cerclis id', 'name', 'county', 'proposed', 'listed', 'construction completed', 'partially deleted', 'deleted'] | [['ctd980670814', 'kellogg - deering well field', 'fairfield', '09 / 08 / 1983', '09 / 21 / 1984', '09 / 23 / 1996', 'n / a', 'n / a'], ['ctd001186618', 'raymark industries , inc', 'fairfield', '01 / 18 / 1994', '04 / 25 / 1995', 'n / a', 'n / a', 'n / a'], ['ct0002055887', 'broad brook mill', 'hartford', '12 / 01 / 2000', 'n / a', 'n / a', 'n / a', 'n / a'], ['ctd980670806', 'old southington landfill', 'hartford', '09 / 08 / 1983', '09 / 21 / 1984', 'n / a', 'n / a', 'n / a'], ['ctd009717604', 'solvents recovery service new england', 'hartford', '12 / 30 / 1982', '09 / 08 / 1983', 'n / a', 'n / a', 'n / a'], ['ctd980732333', 'barkhamsted - new hartford landfill', 'litchfield', '06 / 24 / 1988', '10 / 04 / 1989', '09 / 28 / 2001', 'n / a', 'n / a'], ['ctd001452093', 'durham meadows', 'middlesex', '06 / 24 / 1988', '10 / 04 / 1989', 'n / a', 'n / a', 'n / a'], ['ctd072122062', 'beacon heights landfill', 'new haven', '12 / 30 / 1982', '09 / 08 / 1983', '09 / 09 / 1998', 'n / a', 'n / a'], ['ctd981067317', 'cheshire ground water contamination', 'new haven', '06 / 24 / 1988', '08 / 30 / 1990', '12 / 31 / 1996', 'n / a', '07 / 02 / 1997'], ['ctd980521165', 'laurel park incorporated', 'new haven', '12 / 30 / 1982', '09 / 08 / 1983', '09 / 11 / 1998', 'n / a', 'n / a'], ['ctd980669261', 'nutmeg valley road', 'new haven', '01 / 22 / 1987', '03 / 31 / 1989', '09 / 28 / 2004', 'n / a', '09 / 23 / 2005'], ['ct0002265551', 'scovill industrial landfill', 'new haven', '05 / 11 / 2000', '07 / 27 / 2000', 'n / a', 'n / a', 'n / a'], ['ctd980906515', 'new london submarine base', 'new london', '10 / 26 / 1989', '08 / 30 / 1990', 'n / a', 'n / a', 'n / a'], ['ctd051316313', 'precision plating corp', 'tolland', '06 / 24 / 1988', '10 / 04 / 1989', 'n / a', 'n / a', 'n / a'], ['ctd108960972', "gallup 's quarry", 'windham', '06 / 24 / 1988', '10 / 04 / 1989', '09 / 30 / 1997', 'n / a', 'n / a'], ['ctd001153923', 'linemaster switch corporation', 'windham', '06 / 24 / 1988', '02 / 21 / 1990', '03 / 29 / 2005', 'n / a', 'n / a'], ['ctd004532610', 'revere textile prints corporation', 'windham', '06 / 10 / 1986', '07 / 22 / 1987', '09 / 30 / 1992', 'n / a', '09 / 02 / 1994'], ['ctd009774969', 'yaworski waste lagoon', 'windham', '12 / 30 / 1982', '09 / 08 / 1983', '09 / 20 / 2000', 'n / a', 'n / a']] |
1980 african cup of champions clubs | https://en.wikipedia.org/wiki/1980_African_Cup_of_Champions_Clubs | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12483185-2.html.csv | comparative | mp algiers had a higher scoring game than fortior mahajanga . | {'row_1': '6', 'row_2': '8', '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', 'team 2', 'mp algiers'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose team 2 record fuzzily matches to mp algiers .', 'tostr': 'filter_eq { all_rows ; team 2 ; mp algiers }'}, '1st leg'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; team 2 ; mp algiers } ; 1st leg }', 'tointer': 'select the rows whose team 2 record fuzzily matches to mp algiers . take the 1st leg record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'team 2', 'fortior mahajanga'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose team 2 record fuzzily matches to fortior mahajanga .', 'tostr': 'filter_eq { all_rows ; team 2 ; fortior mahajanga }'}, '1st leg'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; team 2 ; fortior mahajanga } ; 1st leg }', 'tointer': 'select the rows whose team 2 record fuzzily matches to fortior mahajanga . take the 1st leg record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; team 2 ; mp algiers } ; 1st leg } ; hop { filter_eq { all_rows ; team 2 ; fortior mahajanga } ; 1st leg } } = true', 'tointer': 'select the rows whose team 2 record fuzzily matches to mp algiers . take the 1st leg record of this row . select the rows whose team 2 record fuzzily matches to fortior mahajanga . take the 1st leg record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; team 2 ; mp algiers } ; 1st leg } ; hop { filter_eq { all_rows ; team 2 ; fortior mahajanga } ; 1st leg } } = true | select the rows whose team 2 record fuzzily matches to mp algiers . take the 1st leg record of this row . select the rows whose team 2 record fuzzily matches to fortior mahajanga . take the 1st leg 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, 'team 2_7': 7, 'mp algiers_8': 8, '1st leg_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'team 2_11': 11, 'fortior mahajanga_12': 12, '1st leg_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', 'team 2_7': 'team 2', 'mp algiers_8': 'mp algiers', '1st leg_9': '1st leg', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'team 2_11': 'team 2', 'fortior mahajanga_12': 'fortior mahajanga', '1st leg_13': '1st leg'} | {'greater_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'team 2_7': [0], 'mp algiers_8': [0], '1st leg_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'team 2_11': [1], 'fortior mahajanga_12': [1], '1st leg_13': [3]} | ['team 1', 'agg', 'team 2', '1st leg', '2nd leg'] | [['djoliba ac', '1 - 2', 'hearts of oak', '1 - 1', '0 - 1'], ['etoile du congo', '1 - 1 ( 3 - 1 pen )', 'hafia fc', '0 - 1', '1 - 0'], ['simba sc', '2 - 5', 'union douala', '2 - 4', '0 - 1'], ['silures', '0 - 4', 'canon yaoundé', '0 - 1', '0 - 3'], ['ac semassi', '1 - 2', 'asf police', '1 - 1', '0 - 1'], ["stella club d'adjamé", '5 - 5', 'mp algiers', '4 - 2', '1 - 3'], ['bendel insurance', '4 - 4', 'gor mahia', '1 - 2', '3 - 2'], ['as bilima', '4 - 1', 'fortior mahajanga', '3 - 0', '1 - 1']] |
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/2-17100961-20.html.csv | superlative | jim spavital was the highest drafted player for the washington redskins . | {'scope': 'all', 'col_superlative': '2', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '2', 'subset': None} | {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'argmin', 'args': ['all_rows', 'pick'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; pick }'}, 'pick'], 'result': '5', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; pick } ; pick }'}, '5'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmin { all_rows ; pick } ; pick } ; 5 } = true', 'tointer': 'select the row whose pick record of all rows is minimum . the pick record of this row is 5 .'} | eq { hop { argmin { all_rows ; pick } ; pick } ; 5 } = true | select the row whose pick record of all rows is minimum . the pick record of this row is 5 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'num_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'pick_5': 5, 'pick_6': 6, '5_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'num_hop_1': 'num_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'pick_5': 'pick', 'pick_6': 'pick', '5_7': '5'} | {'eq_2': [3], 'result_3': [], 'num_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'pick_5': [0], 'pick_6': [1], '5_7': [2]} | ['round', 'pick', 'name', 'position', 'college', 'aafc team'] | [['1', '5', 'jim spavital', 'fb', 'oklahoma a & m', 'los angeles dons'], ['2', '18', 'chuck drazenovich', 'fb', 'penn state', 'los angeles dons'], ['3', '31', 'roland dale', 'ot', 'mississippi', 'brooklyn dodgers'], ['4', '48', 'lloyd eisenberg', 'ot', 'duke', 'los angeles dons'], ['5', '61', 'hardy brown', 'fb', 'tulsa', 'chicago hornets'], ['6', '76', 'ed hirsch', 'lb', 'northwestern', 'buffalo bills'], ['7', '89', 'ed smith', 'hb', 'texas mines', 'new york yanks'], ['9', '117', 'murray alexander', 'e', 'mississippi state', 'brooklyn dodgers'], ['10', '132', 'dewey nelson', 'hb', 'utah', 'new york bulldogs']] |
1976 - 77 philadelphia flyers season | https://en.wikipedia.org/wiki/1976%E2%80%9377_Philadelphia_Flyers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14303579-16.html.csv | ordinal | in the 1976-77 philadelphia flyers season , fourth defensive player drafted was dave hynek . | {'scope': 'subset', 'row': '4', 'col': '1', 'order': '4', 'col_other': '2', 'max_or_min': 'min_to_max', 'value_mentioned': 'yes', 'subset': {'col': '3', 'criterion': 'equal', 'value': 'defense'}} | {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'nth_min', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'position', 'defense'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; position ; defense }', 'tointer': 'select the rows whose position record fuzzily matches to defense .'}, 'round', '4'], 'result': '4', 'ind': 1, 'tostr': 'nth_min { filter_eq { all_rows ; position ; defense } ; round ; 4 }', 'tointer': 'select the rows whose position record fuzzily matches to defense . the 4th minimum round record of these rows is 4 .'}, '4'], 'result': True, 'ind': 2, 'tostr': 'eq { nth_min { filter_eq { all_rows ; position ; defense } ; round ; 4 } ; 4 }', 'tointer': 'select the rows whose position record fuzzily matches to defense . the 4th minimum round record of these rows is 4 .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'position', 'defense'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; position ; defense }', 'tointer': 'select the rows whose position record fuzzily matches to defense .'}, 'round', '4'], 'result': None, 'ind': 3, 'tostr': 'nth_argmin { filter_eq { all_rows ; position ; defense } ; round ; 4 }'}, 'player'], 'result': 'dave hynek', 'ind': 4, 'tostr': 'hop { nth_argmin { filter_eq { all_rows ; position ; defense } ; round ; 4 } ; player }'}, 'dave hynek'], 'result': True, 'ind': 5, 'tostr': 'eq { hop { nth_argmin { filter_eq { all_rows ; position ; defense } ; round ; 4 } ; player } ; dave hynek }', 'tointer': 'the player record of the row with 4th minimum round record is dave hynek .'}], 'result': True, 'ind': 6, 'tostr': 'and { eq { nth_min { filter_eq { all_rows ; position ; defense } ; round ; 4 } ; 4 } ; eq { hop { nth_argmin { filter_eq { all_rows ; position ; defense } ; round ; 4 } ; player } ; dave hynek } } = true', 'tointer': 'select the rows whose position record fuzzily matches to defense . the 4th minimum round record of these rows is 4 . the player record of the row with 4th minimum round record is dave hynek .'} | and { eq { nth_min { filter_eq { all_rows ; position ; defense } ; round ; 4 } ; 4 } ; eq { hop { nth_argmin { filter_eq { all_rows ; position ; defense } ; round ; 4 } ; player } ; dave hynek } } = true | select the rows whose position record fuzzily matches to defense . the 4th minimum round record of these rows is 4 . the player record of the row with 4th minimum round record is dave hynek . | 8 | 7 | {'and_6': 6, 'result_7': 7, 'eq_2': 2, 'nth_min_1': 1, 'filter_str_eq_0': 0, 'all_rows_8': 8, 'position_9': 9, 'defense_10': 10, 'round_11': 11, '4_12': 12, '4_13': 13, 'str_eq_5': 5, 'str_hop_4': 4, 'nth_argmin_3': 3, 'round_14': 14, '4_15': 15, 'player_16': 16, 'dave hynek_17': 17} | {'and_6': 'and', 'result_7': 'true', 'eq_2': 'eq', 'nth_min_1': 'nth_min', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_8': 'all_rows', 'position_9': 'position', 'defense_10': 'defense', 'round_11': 'round', '4_12': '4', '4_13': '4', 'str_eq_5': 'str_eq', 'str_hop_4': 'str_hop', 'nth_argmin_3': 'nth_argmin', 'round_14': 'round', '4_15': '4', 'player_16': 'player', 'dave hynek_17': 'dave hynek'} | {'and_6': [7], 'result_7': [], 'eq_2': [6], 'nth_min_1': [2], 'filter_str_eq_0': [1, 3], 'all_rows_8': [0], 'position_9': [0], 'defense_10': [0], 'round_11': [1], '4_12': [1], '4_13': [2], 'str_eq_5': [6], 'str_hop_4': [5], 'nth_argmin_3': [4], 'round_14': [3], '4_15': [3], 'player_16': [4], 'dave hynek_17': [5]} | ['round', 'player', 'position', 'nationality', 'college / junior / club team ( league )'] | [['1', 'mark suzor', 'defense', 'canada', 'kingston canadians ( oha )'], ['2', 'drew callander', 'defense', 'canada', 'regina pats ( wchl )'], ['3', 'craig hanmer', 'defense', 'united states', 'mohawk valley comets ( nahl )'], ['4', 'dave hynek', 'defense', 'canada', 'kingston canadians ( oha )'], ['5', 'robin lang', 'defense', 'canada', 'cornell big red ( ecac )'], ['6', 'paul klasinski', 'left wing', 'united states', 'st paul vulcans ( mjhl )'], ['7', 'ray kurpis', 'right wing', 'united states', 'austin mavericks ( mjhl )']] |
piercarlo ghinzani | https://en.wikipedia.org/wiki/Piercarlo_Ghinzani | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1226331-1.html.csv | unique | 1989 was the only year that the ford cosworth dfr v8 engine was used . | {'scope': 'all', 'row': '15', 'col': '4', 'col_other': '1', 'criterion': 'equal', 'value': 'ford cosworth dfr v8', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'engine', 'ford cosworth dfr v8'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose engine record fuzzily matches to ford cosworth dfr v8 .', 'tostr': 'filter_eq { all_rows ; engine ; ford cosworth dfr v8 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; engine ; ford cosworth dfr v8 } }', 'tointer': 'select the rows whose engine record fuzzily matches to ford cosworth dfr v8 . there is only one such row in the table .'}, {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'engine', 'ford cosworth dfr v8'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose engine record fuzzily matches to ford cosworth dfr v8 .', 'tostr': 'filter_eq { all_rows ; engine ; ford cosworth dfr v8 }'}, 'year'], 'result': '1989', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; engine ; ford cosworth dfr v8 } ; year }'}, '1989'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; engine ; ford cosworth dfr v8 } ; year } ; 1989 }', 'tointer': 'the year record of this unqiue row is 1989 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; engine ; ford cosworth dfr v8 } } ; eq { hop { filter_eq { all_rows ; engine ; ford cosworth dfr v8 } ; year } ; 1989 } } = true', 'tointer': 'select the rows whose engine record fuzzily matches to ford cosworth dfr v8 . there is only one such row in the table . the year record of this unqiue row is 1989 .'} | and { only { filter_eq { all_rows ; engine ; ford cosworth dfr v8 } } ; eq { hop { filter_eq { all_rows ; engine ; ford cosworth dfr v8 } ; year } ; 1989 } } = true | select the rows whose engine record fuzzily matches to ford cosworth dfr v8 . there is only one such row in the table . the year record of this unqiue row is 1989 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'engine_7': 7, 'ford cosworth dfr v8_8': 8, 'eq_3': 3, 'num_hop_2': 2, 'year_9': 9, '1989_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'engine_7': 'engine', 'ford cosworth dfr v8_8': 'ford cosworth dfr v8', 'eq_3': 'eq', 'num_hop_2': 'num_hop', 'year_9': 'year', '1989_10': '1989'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'engine_7': [0], 'ford cosworth dfr v8_8': [0], 'eq_3': [4], 'num_hop_2': [3], 'year_9': [2], '1989_10': [3]} | ['year', 'entrant', 'chassis', 'engine', 'pts'] | [['1981', 'osella squadra corse', 'osella fa1b', 'ford cosworth dfv v8', '0'], ['1983', 'osella squadra corse', 'osella fa1d', 'ford cosworth dfv v8', '0'], ['1983', 'osella squadra corse', 'osella fa1e', 'alfa romeo v12', '0'], ['1984', 'osella squadra corse', 'osella fa1f', 'alfa romeo v8 ( t / c )', '2'], ['1985', 'osella squadra corse', 'osella fa1f', 'alfa romeo v8 ( t / c )', '0'], ['1985', 'osella squadra corse', 'osella fa1 g', 'alfa romeo v8 ( t / c )', '0'], ['1985', 'toleman group motorsport', 'toleman tg185', 'hart straight - 4 ( t / c )', '0'], ['1986', 'osella squadra corse', 'osella fa1f', 'alfa romeo v8 ( t / c )', '0'], ['1986', 'osella squadra corse', 'osella fa1h', 'alfa romeo v8 ( t / c )', '0'], ['1986', 'osella squadra corse', 'osella fa1 g', 'alfa romeo v8 ( t / c )', '0'], ['1987', 'ligier loto', 'ligier js29b', 'megatron straight - 4 ( t / c )', '0'], ['1987', 'ligier loto', 'ligier js29c', 'megatron straight - 4 ( t / c )', '0'], ['1988', 'zakspeed', 'zakspeed 881', 'zakspeed straight - 4 ( t / c )', '0'], ['1988', 'zakspeed', 'zakspeed 881b', 'zakspeed straight - 4 ( t / c )', '0'], ['1989', 'osella squadra corse', 'osella fa1 m89', 'ford cosworth dfr v8', '0']] |
list of the busiest airports in africa | https://en.wikipedia.org/wiki/List_of_the_busiest_airports_in_Africa | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18600121-1.html.csv | count | four of the busiest airports in africa were in the country of south africa . | {'scope': 'all', 'criterion': 'equal', 'value': 'south africa', 'result': '4', 'col': '1', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'south africa'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose country record fuzzily matches to south africa .', 'tostr': 'filter_eq { all_rows ; country ; south africa }'}], 'result': '4', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; country ; south africa } }', 'tointer': 'select the rows whose country record fuzzily matches to south africa . the number of such rows is 4 .'}, '4'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; country ; south africa } } ; 4 } = true', 'tointer': 'select the rows whose country record fuzzily matches to south africa . the number of such rows is 4 .'} | eq { count { filter_eq { all_rows ; country ; south africa } } ; 4 } = true | select the rows whose country record fuzzily matches to south africa . 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, 'country_5': 5, 'south africa_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', 'country_5': 'country', 'south africa_6': 'south africa', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'country_5': [0], 'south africa_6': [0], '4_7': [2]} | ['country', 'airport', 'city', '2012', 'change ( 12 / 11 )'] | [['south africa', 'or tambo international airport', 'johannesburg', '18681458', '0 1.2 %'], ['spain', 'gran canaria airport', 'las palmas de gran canaria', '9892067', '0 6.1 %'], ['spain', 'tenerife sur', 'granadilla de abona', '8530729', '0 1.5 %'], ['south africa', 'cape town international airport', 'cape town', '8505563', '0 0.8 %'], ['morocco', 'mohammed v international airport', 'casablanca', '7186331', '0 1.4 %'], ['spain', 'lanzarote airport', 'san bartolomé , las palmas', '5168775', '0 6.8 %'], ['south africa', 'king shaka international airport', 'durban', '4747224', '0 5.8 %'], ['spain', 'fuerteventura airport', 'puerto del rosario', '4399023', '0 11.1 %'], ['spain', 'tenerife norte', 'san cristóbal de la laguna', '3717944', '0 9.2 %'], ['morocco', 'marrakesh menara airport', 'marrakesh', '3373475', '0 1.7 %'], ['mauritius', 'sir seewoosagur ramgoolam international airport', 'mauritius', '2490862', '0 3.7 %'], ['france', 'la réunion roland garros airport', 'saint - denis', '1997800', '0 4.2 %'], ['ghana', 'kotoka international airport', 'accra', '1726051', '0 8.9 %'], ['morocco', 'agadir - al massira airport', 'agadir', '1384931', '0 8.7 %'], ['south africa', 'port elizabeth airport', 'port elizabeth', '1316063', '0 3.7 %'], ['tunisia', 'monastir international airport', 'monastir', '1238757', '0 23.9 %']] |
comparison of microsoft windows versions | https://en.wikipedia.org/wiki/Comparison_of_Microsoft_Windows_versions | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10758793-4.html.csv | count | 12 of the versions used a closed source license . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'closed source', 'result': '12', 'col': '6', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'license', 'closed source'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose license record fuzzily matches to closed source .', 'tostr': 'filter_eq { all_rows ; license ; closed source }'}], 'result': '12', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; license ; closed source } }', 'tointer': 'select the rows whose license record fuzzily matches to closed source . the number of such rows is 12 .'}, '12'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; license ; closed source } } ; 12 } = true', 'tointer': 'select the rows whose license record fuzzily matches to closed source . the number of such rows is 12 .'} | eq { count { filter_eq { all_rows ; license ; closed source } } ; 12 } = true | select the rows whose license record fuzzily matches to closed source . the number of such rows is 12 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'license_5': 5, 'closed source_6': 6, '12_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'license_5': 'license', 'closed source_6': 'closed source', '12_7': '12'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'license_5': [0], 'closed source_6': [0], '12_7': [2]} | ['name', 'release date', 'rtm build', 'current version', 'status support', 'license', 'based on ( kernel )', 'supported architectures', 'os type'] | [['windows nt 3.1', '1993 - 07 - 27', '528', '3.10.528 sp3 ( 1994 - 11 - 10 )', 'unsupported ( 2001 - 12 - 31 )', 'closed source', 'nt 3.1', 'ia - 32 , dec alpha , mips', 'workstation , server'], ['windows nt 3.5', '1994 - 09 - 21', '807', '3.50.807 sp3 ( 1995 - 06 - 21 )', 'unsupported ( 2001 - 12 - 31 )', 'closed source', 'nt 3.5', 'ia - 32 , dec alpha , mips', 'workstation , server'], ['windows nt 3.51', '1995 - 05 - 30', '1057', '3.51.1057 sp5 ( 1996 - 09 - 19 )', 'unsupported ( 2001 - 12 - 31 )', 'closed source', 'nt 3.51', 'ia - 32 , dec alpha , mips , powerpc', 'workstation , server'], ['windows nt 4.0', '1996 - 08 - 24', '1381', '4.00.1381 sp6a ( 1999 - 11 - 30 )', 'unsupported ( 2004 - 12 - 31 )', 'closed source', 'nt 4.0', 'ia - 32 , dec alpha , mips , powerpc', 'workstation , server , embedded pcs'], ['windows 2000', '2000 - 02 - 17', '2195', '5.0 sp4 rollup 1 v2 ( 2005 - 09 - 13 )', 'unsupported ( 2010 - 07 - 13 )', 'shared source', 'nt 5.0', 'ia - 32 , ia - 64', 'desktop , workstation , server , embedded pcs'], ['windows xp', '2001 - 10 - 25', '2600', '5.1.2600 sp3 ( 2008 - 04 - 21 )', 'extended support period ( 2014 - 04 - 08 )', 'shared source', 'nt 5.1 , nt 5.2 ( 64 - bit 2003 and x64 )', 'ia - 32 , ia - 64 , x86 - 64', 'desktop , workstation , embedded pcs'], ['windows server 2003', '2003 - 04 - 24', '3790', '5.2.3790 sp2 ( 2007 - 03 - 13 )', 'supported', 'shared source', 'nt 5.2', 'ia - 32 , ia - 64 , x86 - 64', 'server , network appliance , embedded pcs , hpc'], ['windows fundamentals for legacy pcs', '2006 - 07 - 08', '2600', 'rtm ( 2006 - 07 - 08 )', 'supported', 'shared source', 'nt 5.1', 'ia - 32', 'desktop'], ['windows vista', '2006 - 11 - 08', '6000 ( sp2 : 6002 )', '6.0 sp2 ( 2009 - 04 - 28 )', 'supported', 'closed source , shared source', 'nt 6.0', 'ia - 32 , x86 - 64', 'desktop , workstation'], ['windows server 2008', '2008 - 02 - 27', '6001 ( sp2 : 6002 )', '6.0 sp2 ( 2008 - 02 - 27 )', 'supported', 'closed source , shared source', 'nt 6.0', 'ia - 32 , ia - 64 , x86 - 64', 'server'], ['windows home server', '2007 - 06 - 16', '3790', '5.2', 'supported', 'closed source', 'nt 5.2', 'ia - 32 , x86 - 64', 'server'], ['windows 7', '2009 - 10 - 22', '7600 ( sp1 : 7601 )', '6.1', 'supported', 'closed source , shared source', 'nt 6.1', 'ia - 32 , x86 - 64', 'desktop , workstation , multi - touch'], ['windows server 2008 r2', '2009 - 10 - 22', '7600 ( sp1 : 7601 )', '6.1', 'supported', 'closed source , shared source', 'nt 6.1', 'ia - 64 , x86 - 64', 'server'], ['windows home server 2011', '2011 - 04 - 05', '8400', '6.1', 'supported', 'closed source', 'nt 6.1', 'x86 - 64', 'server'], ['windows server 2012', '2012 - 9 - 4', '9200', '6.2', 'supported', 'closed source , shared source', 'nt 6.2', 'x86 - 64', 'server'], ['windows 8', '2012 - 10 - 26', '9200', '6.2', 'supported', 'closed source , shared source', 'nt 6.2', 'ia - 32 , x86 - 64 , arm architecture ( armv7 )', 'desktop , workstation , multitouch']] |
1931 vfl season | https://en.wikipedia.org/wiki/1931_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10789881-8.html.csv | comparative | north melbourne had a higher away team score than south melbourne in the 1931 vfl season . | {'row_1': '3', 'row_2': '1', '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', 'away team', 'north melbourne'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose away team record fuzzily matches to north melbourne .', 'tostr': 'filter_eq { all_rows ; away team ; north melbourne }'}, 'away team score'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; away team ; north melbourne } ; away team score }', 'tointer': 'select the rows whose away team record fuzzily matches to north melbourne . take the away team score record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'away team', 'south melbourne'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose away team record fuzzily matches to south melbourne .', 'tostr': 'filter_eq { all_rows ; away team ; south melbourne }'}, 'away team score'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; away team ; south melbourne } ; away team score }', 'tointer': 'select the rows whose away team record fuzzily matches to south melbourne . take the away team score record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; away team ; north melbourne } ; away team score } ; hop { filter_eq { all_rows ; away team ; south melbourne } ; away team score } } = true', 'tointer': 'select the rows whose away team record fuzzily matches to north melbourne . take the away team score record of this row . select the rows whose away team record fuzzily matches to south melbourne . take the away team score record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; away team ; north melbourne } ; away team score } ; hop { filter_eq { all_rows ; away team ; south melbourne } ; away team score } } = true | select the rows whose away team record fuzzily matches to north melbourne . take the away team score record of this row . select the rows whose away team record fuzzily matches to south melbourne . take the away team score record of this row . the first record is greater than the second record . | 5 | 5 | {'greater_4': 4, 'result_5': 5, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'away team_7': 7, 'north melbourne_8': 8, 'away team score_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'away team_11': 11, 'south melbourne_12': 12, 'away team score_13': 13} | {'greater_4': 'greater', 'result_5': 'true', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'away team_7': 'away team', 'north melbourne_8': 'north melbourne', 'away team score_9': 'away team score', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'away team_11': 'away team', 'south melbourne_12': 'south melbourne', 'away team score_13': 'away team score'} | {'greater_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'away team_7': [0], 'north melbourne_8': [0], 'away team score_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'away team_11': [1], 'south melbourne_12': [1], 'away team score_13': [3]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['richmond', '12.12 ( 84 )', 'south melbourne', '7.15 ( 57 )', 'punt road oval', '18000', '20 june 1931'], ['essendon', '7.13 ( 55 )', 'geelong', '13.11 ( 89 )', 'windy hill', '10000', '20 june 1931'], ['collingwood', '22.22 ( 154 )', 'north melbourne', '9.10 ( 64 )', 'victoria park', '6000', '20 june 1931'], ['carlton', '18.14 ( 122 )', 'melbourne', '9.4 ( 58 )', 'princes park', '25000', '20 june 1931'], ['st kilda', '7.10 ( 52 )', 'footscray', '11.11 ( 77 )', 'junction oval', '17000', '20 june 1931'], ['hawthorn', '12.8 ( 80 )', 'fitzroy', '7.14 ( 56 )', 'glenferrie oval', '8000', '20 june 1931']] |
list of game of the year awards | https://en.wikipedia.org/wiki/List_of_Game_of_the_Year_awards | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1851722-39.html.csv | majority | a majority of winners of the game of the year awards are from the playstation 3 . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': 'playstation 3', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'platform ( s )', 'playstation 3'], 'result': True, 'ind': 0, 'tointer': 'for the platform ( s ) records of all rows , most of them fuzzily match to playstation 3 .', 'tostr': 'most_eq { all_rows ; platform ( s ) ; playstation 3 } = true'} | most_eq { all_rows ; platform ( s ) ; playstation 3 } = true | for the platform ( s ) records of all rows , most of them fuzzily match to playstation 3 . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'platform (s)_3': 3, 'playstation 3_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'platform (s)_3': 'platform ( s )', 'playstation 3_4': 'playstation 3'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'platform (s)_3': [0], 'playstation 3_4': [0]} | ['year', 'game', 'genre', 'platform ( s )', 'developer ( s )'] | [['2007', 'super mario galaxy', 'platformer', 'wii', 'nintendo'], ['2008', 'grand theft auto iv', 'open world , action', 'xbox 360 , playstation 3 , pc', 'rockstar north'], ['2009', 'uncharted 2 : among thieves', 'third - person shooter', 'playstation 3', 'naughty dog'], ['2010', 'red dead redemption', 'open world : ( third - person ) shooter', 'playstation 3 , xbox 360', 'rockstar games'], ['2011', 'portal 2', 'puzzle , first - person shooter , science fiction', 'playstation 3 , xbox 360 , windows , mac os x', 'valve corporation'], ['2012', 'xcom : enemy unknown', 'turn - based strategy', 'windows , xbox 360 , playstation 3', 'firaxis games']] |
stephanie vogt | https://en.wikipedia.org/wiki/Stephanie_Vogt | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16306899-6.html.csv | majority | most of the tournament surfaces that stephanie vogt played on were clay . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'clay', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'surface', 'clay'], 'result': True, 'ind': 0, 'tointer': 'for the surface records of all rows , most of them fuzzily match to clay .', 'tostr': 'most_eq { all_rows ; surface ; clay } = true'} | most_eq { all_rows ; surface ; clay } = true | for the surface records of all rows , most of them fuzzily match to clay . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'surface_3': 3, 'clay_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'surface_3': 'surface', 'clay_4': 'clay'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'surface_3': [0], 'clay_4': [0]} | ['outcome', 'date', 'tournament', 'surface', 'opponent', 'score'] | [['winner', '24 june 2007', 'davos , switzerland', 'clay', 'jessica moore', '6 - 4 , 4 - 6 , 6 - 3'], ['runner - up', '19 august 2007', 'pesaro , italy', 'clay', 'polona hercog', '2 - 6 , 6 - 2 , 1 - 6'], ['runner - up', '28 october 2007', 'mexico city , mexico', 'hard', 'olivia sanchez', '6 - 2 , 2 - 6 , 2 - 6'], ['runner - up', '16 february 2008', 'majora , spain', 'clay', 'polona hercog', '6 - 4 , 1 - 6 , 3 - 6'], ['winner', '4 may 2008', 'makarska , croatia', 'clay', 'anastasia pivovarova', '6 - 2 , 6 - 3'], ['winner', '29 may 2010', 'velenje , slovenia', 'clay', 'pavla šmídová', '6 - 1 , 6 - 2'], ['winner', '31 october 2010', 'cairo , egypt', 'clay', 'maša zec peškirič', '6 - 1 , 6 - 3'], ['runner - up', '23 january 2011', 'andrézieux - bouthéon , france', 'hard', 'mona barthel', '3 - 6 , 6 - 3 , 4 - 6'], ['runner - up', '10 july 2011', 'aschaffenburg , germany', 'clay', 'florencia molinero', '6 - 7 ( 6 - 8 ) , 1 - 6'], ['winner', '11 september 2011', 'alphen aan den rijn , netherlands', 'clay', 'katarzyna piter', '6 - 2 , 6 - 4'], ['runner - up', '18 september 2011', 'rotterdam , netherlands', 'clay', 'dinah pfizenmaier', '6 - 3 , 1 - 6 , 1 - 6'], ['runner - up', '3 november 2012', 'netanya , israel', 'hard', 'anna karolína schmiedlová', '6 - 0 , 3 - 6 , 4 - 6'], ['winner', '10 march 2013', 'sutton , united kingdom', 'hard ( i )', 'carina witthöft', '3 - 6 , 6 - 4 , 6 - 3'], ['winner', '17 march 2013', 'bath , united kingdom', 'hard ( i )', 'an - sophie mestach', '7 - 6 ( 7 - 3 ) , 6 - 3'], ['winner', '13 july 2013', 'biarritz , france', 'clay', 'anna karolína schmiedlová', '1 - 6 , 6 - 3 , 6 - 2'], ['winner', '15 september 2013', 'podgorica , montenegro', 'clay', 'anett kontaveit', '6 - 4 , 6 - 3']] |
hey venus ! | https://en.wikipedia.org/wiki/Hey_Venus%21 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10647532-1.html.csv | count | hey venus ! was released two times on vinyl record . | {'scope': 'all', 'criterion': 'equal', 'value': 'vinyl record', 'result': '2', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'format', 'vinyl record'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose format record fuzzily matches to vinyl record .', 'tostr': 'filter_eq { all_rows ; format ; vinyl record }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; format ; vinyl record } }', 'tointer': 'select the rows whose format record fuzzily matches to vinyl record . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; format ; vinyl record } } ; 2 } = true', 'tointer': 'select the rows whose format record fuzzily matches to vinyl record . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; format ; vinyl record } } ; 2 } = true | select the rows whose format record fuzzily matches to vinyl record . 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, 'format_5': 5, 'vinyl record_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', 'format_5': 'format', 'vinyl record_6': 'vinyl record', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'format_5': [0], 'vinyl record_6': [0], '2_7': [2]} | ['region', 'date', 'label', 'format', 'catalogue'] | [['united kingdom', '27 august 2007', 'rough trade records', 'vinyl record', 'rtradlp 346'], ['united kingdom', '27 august 2007', 'rough trade records', 'compact disc', 'rtradcd 346'], ['united kingdom', '27 august 2007', 'rough trade records', 'download', '-'], ['united states', '28 august 2007', 'rough trade america', 'vinyl record', 'rt - 346 - 1'], ['united states', '28 august 2007', 'rough trade america', 'download', 'rt - 346 - 5'], ['united states', '22 january 2008', 'rough trade america', 'double compact disc', 'rtradcd 423'], ['japan', '12 september 2007', 'rough trade japan', 'compact disc', 'xqcy - 1003']] |
socialist destourian party | https://en.wikipedia.org/wiki/Socialist_Destourian_Party | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-13746866-2.html.csv | majority | habib bourguiba was the party leader of the socialist destourian party in all of the elections . | {'scope': 'all', 'col': '2', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'habib bourguiba', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'party leader', 'habib bourguiba'], 'result': True, 'ind': 0, 'tointer': 'for the party leader records of all rows , all of them fuzzily match to habib bourguiba .', 'tostr': 'all_eq { all_rows ; party leader ; habib bourguiba } = true'} | all_eq { all_rows ; party leader ; habib bourguiba } = true | for the party leader records of all rows , all of them fuzzily match to habib bourguiba . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'party leader_3': 3, 'habib bourguiba_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'party leader_3': 'party leader', 'habib bourguiba_4': 'habib bourguiba'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'party leader_3': [0], 'habib bourguiba_4': [0]} | ['election date', 'party leader', 'number of votes received', 'percentage of votes', 'number of deputies'] | [['1964', 'habib bourguiba', '1255153', '100 %', '101'], ['1969', 'habib bourguiba', '1363939', '100 %', '101'], ['1974', 'habib bourguiba', '1570954', '100 %', '112'], ['1979', 'habib bourguiba', '1560753', '100 %', '121'], ['1981', 'habib bourguiba', '1828363', '94.2 %', '136']] |
usa today all - usa high school basketball team | https://en.wikipedia.org/wiki/USA_Today_All-USA_high_school_basketball_team | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11677760-30.html.csv | unique | myles mack is the only usa today all - usa high school basketball team member under 6 feel tall . | {'scope': 'all', 'row': '3', 'col': '2', 'col_other': '1', 'criterion': 'less_than', 'value': '6-0', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'height', '6-0'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose height record is less than 6-0 .', 'tostr': 'filter_less { all_rows ; height ; 6-0 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_less { all_rows ; height ; 6-0 } }', 'tointer': 'select the rows whose height record is less than 6-0 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'height', '6-0'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose height record is less than 6-0 .', 'tostr': 'filter_less { all_rows ; height ; 6-0 }'}, 'player'], 'result': 'myles mack', 'ind': 2, 'tostr': 'hop { filter_less { all_rows ; height ; 6-0 } ; player }'}, 'myles mack'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_less { all_rows ; height ; 6-0 } ; player } ; myles mack }', 'tointer': 'the player record of this unqiue row is myles mack .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_less { all_rows ; height ; 6-0 } } ; eq { hop { filter_less { all_rows ; height ; 6-0 } ; player } ; myles mack } } = true', 'tointer': 'select the rows whose height record is less than 6-0 . there is only one such row in the table . the player record of this unqiue row is myles mack .'} | and { only { filter_less { all_rows ; height ; 6-0 } } ; eq { hop { filter_less { all_rows ; height ; 6-0 } ; player } ; myles mack } } = true | select the rows whose height record is less than 6-0 . there is only one such row in the table . the player record of this unqiue row is myles mack . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_less_0': 0, 'all_rows_6': 6, 'height_7': 7, '6-0_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'player_9': 9, 'myles mack_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_less_0': 'filter_less', 'all_rows_6': 'all_rows', 'height_7': 'height', '6-0_8': '6-0', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'player_9': 'player', 'myles mack_10': 'myles mack'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_less_0': [1, 2], 'all_rows_6': [0], 'height_7': [0], '6-0_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'player_9': [2], 'myles mack_10': [3]} | ['player', 'height', 'school', 'hometown', 'college'] | [['khem birch', '6 - 9', 'notre dame prep', 'montreal , qc , canada', 'pittsburgh / unlv'], ['perry ellis', '6 - 8', 'wichita heights high school', 'wichita , ks', 'kansas'], ['myles mack', '5 - 9', 'st anthony high school', 'jersey city , nj', 'rutgers'], ['shabazz muhammad', '6 - 6', 'bishop gorman high school', 'las vegas , nv', 'ucla'], ['cody zeller', '6 - 11', 'washington high school', 'washington , in', 'indiana']] |
1997 cfl draft | https://en.wikipedia.org/wiki/1997_CFL_Draft | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-28059992-1.html.csv | ordinal | in the 1997 cfl draft , the 2nd to last pick was jason clemett . | {'row': '7', 'col': '1', 'order': '2', 'col_other': '3', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'pick', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; pick ; 2 }'}, 'player'], 'result': 'jason clemett', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; pick ; 2 } ; player }'}, 'jason clemett'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; pick ; 2 } ; player } ; jason clemett } = true', 'tointer': 'select the row whose pick record of all rows is 2nd maximum . the player record of this row is jason clemett .'} | eq { hop { nth_argmax { all_rows ; pick ; 2 } ; player } ; jason clemett } = true | select the row whose pick record of all rows is 2nd maximum . the player record of this row is jason clemett . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'pick_5': 5, '2_6': 6, 'player_7': 7, 'jason clemett_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', 'pick_5': 'pick', '2_6': '2', 'player_7': 'player', 'jason clemett_8': 'jason clemett'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'pick_5': [0], '2_6': [0], 'player_7': [1], 'jason clemett_8': [2]} | ['pick', 'cfl team', 'player', 'position', 'college'] | [['1', 'toronto argonauts', 'chad folk', 'ol', 'utah'], ['2', 'saskatchewan roughriders', 'ben fairbrother', 'ol', 'calgary'], ['3', 'edmonton eskimos', 'ian franklin', 'cb', 'weber state'], ['4', 'hamilton tiger - cats', 'tim prinsen', 'og', 'north dakota'], ['5', 'calgary stampeders', 'doug brown', 'dl', 'simon fraser'], ['6', 'montreal alouettes', 'steve charbonneau', 'dl', 'new hampshire'], ['7', 'calgary', 'jason clemett', 'lb', 'simon fraser'], ['8', 'edmonton', 'mark farraway', 'dl', 'st francis xavier']] |
swimming at the 2008 summer olympics - women 's 50 metre freestyle | https://en.wikipedia.org/wiki/Swimming_at_the_2008_Summer_Olympics_%E2%80%93_Women%27s_50_metre_freestyle | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18625234-4.html.csv | ordinal | lisabeth trickett ranked 3rd among the women 's 50 metre freestyle swimmers . | {'row': '3', 'col': '1', 'order': '3', 'col_other': '3', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'rank', '3'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; rank ; 3 }'}, 'name'], 'result': 'lisbeth trickett', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; rank ; 3 } ; name }'}, 'lisbeth trickett'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; rank ; 3 } ; name } ; lisbeth trickett } = true', 'tointer': 'select the row whose rank record of all rows is 3rd minimum . the name record of this row is lisbeth trickett .'} | eq { hop { nth_argmin { all_rows ; rank ; 3 } ; name } ; lisbeth trickett } = true | select the row whose rank record of all rows is 3rd minimum . the name record of this row is lisbeth trickett . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'rank_5': 5, '3_6': 6, 'name_7': 7, 'lisbeth trickett_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmin_0': 'nth_argmin', 'all_rows_4': 'all_rows', 'rank_5': 'rank', '3_6': '3', 'name_7': 'name', 'lisbeth trickett_8': 'lisbeth trickett'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'rank_5': [0], '3_6': [0], 'name_7': [1], 'lisbeth trickett_8': [2]} | ['rank', 'lane', 'name', 'nationality', 'time'] | [['1', '3', 'britta steffen', 'germany', '24.43'], ['2', '4', 'marleen veldhuis', 'netherlands', '24.46'], ['3', '5', 'lisbeth trickett', 'australia', '24.47'], ['4', '7', 'hinkelien schreuder', 'netherlands', '24.52'], ['5', '1', 'kara lynn joyce', 'united states', '24.63'], ['6', '8', 'aliaksandra herasimenia', 'belarus', '24.72'], ['7', '6', 'francesca halsall', 'great britain', '24.80'], ['8', '2', 'malia metella', 'france', '24.89']] |
spain men 's national water polo team | https://en.wikipedia.org/wiki/Spain_men%27s_national_water_polo_team | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18985137-1.html.csv | count | there are 4 players on the team that play the d position . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'd', 'result': '4', 'col': '2', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'pos', 'd'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose pos record fuzzily matches to d .', 'tostr': 'filter_eq { all_rows ; pos ; d }'}], 'result': '4', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; pos ; d } }', 'tointer': 'select the rows whose pos record fuzzily matches to d . the number of such rows is 4 .'}, '4'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; pos ; d } } ; 4 } = true', 'tointer': 'select the rows whose pos record fuzzily matches to d . the number of such rows is 4 .'} | eq { count { filter_eq { all_rows ; pos ; d } } ; 4 } = true | select the rows whose pos record fuzzily matches to d . 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, 'pos_5': 5, 'd_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', 'pos_5': 'pos', 'd_6': 'd', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'pos_5': [0], 'd_6': [0], '4_7': [2]} | ['name', 'pos', 'height', 'weight', '2012 club'] | [['iñaki aguilar', 'gk', 'm', '-', 'cn sabadell'], ['mario josé garcía', 'd', 'm', '-', 'real canoe'], ['david martín', 'd', 'm', '-', 'cn atlètic - barceloneta'], ['balázs szirányi', 'cf', 'm', '-', 'real canoe'], ['guillermo molina', 'cf', 'm', '-', 'pro recco'], ['marc minguell', 'cf', 'm', '-', 'posillipo'], ['blai mallarach', 'cf', 'm', '-', 'havk mladost'], ['albert español', 'd', 'm', '-', 'cn atlètic - barceloneta'], ['xavier vallès', 'cf', 'm', '-', 'cn atlètic - barceloneta'], ['felipe perrone', 'd', 'm', '-', 'pro recco'], ['iván pérez', 'cf', 'm', '-', 'cn sabadell'], ['xavier garcía', 'cf', 'm', '-', 'vk primorje rijeka'], ['daniel lópez', 'gk', 'm', '-', 'cn atlètic - barceloneta']] |
list of ngc objects ( 2001 - 3000 ) | https://en.wikipedia.org/wiki/List_of_NGC_objects_%282001%E2%80%933000%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11097664-8.html.csv | unique | out of this sample of ngc objects from 2700-2799 , ngc 2787 is the only lenticular galaxy . | {'scope': 'all', 'row': '5', 'col': '2', 'col_other': '1', 'criterion': 'equal', 'value': 'lenticular galaxy', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'object type', 'lenticular galaxy'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose object type record fuzzily matches to lenticular galaxy .', 'tostr': 'filter_eq { all_rows ; object type ; lenticular galaxy }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; object type ; lenticular galaxy } }', 'tointer': 'select the rows whose object type record fuzzily matches to lenticular galaxy . there is only one such row in the table .'}, {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'object type', 'lenticular galaxy'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose object type record fuzzily matches to lenticular galaxy .', 'tostr': 'filter_eq { all_rows ; object type ; lenticular galaxy }'}, 'ngc number'], 'result': '2787', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; object type ; lenticular galaxy } ; ngc number }'}, '2787'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; object type ; lenticular galaxy } ; ngc number } ; 2787 }', 'tointer': 'the ngc number record of this unqiue row is 2787 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; object type ; lenticular galaxy } } ; eq { hop { filter_eq { all_rows ; object type ; lenticular galaxy } ; ngc number } ; 2787 } } = true', 'tointer': 'select the rows whose object type record fuzzily matches to lenticular galaxy . there is only one such row in the table . the ngc number record of this unqiue row is 2787 .'} | and { only { filter_eq { all_rows ; object type ; lenticular galaxy } } ; eq { hop { filter_eq { all_rows ; object type ; lenticular galaxy } ; ngc number } ; 2787 } } = true | select the rows whose object type record fuzzily matches to lenticular galaxy . there is only one such row in the table . the ngc number record of this unqiue row is 2787 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'object type_7': 7, 'lenticular galaxy_8': 8, 'eq_3': 3, 'num_hop_2': 2, 'ngc number_9': 9, '2787_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'object type_7': 'object type', 'lenticular galaxy_8': 'lenticular galaxy', 'eq_3': 'eq', 'num_hop_2': 'num_hop', 'ngc number_9': 'ngc number', '2787_10': '2787'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'object type_7': [0], 'lenticular galaxy_8': [0], 'eq_3': [4], 'num_hop_2': [3], 'ngc number_9': [2], '2787_10': [3]} | ['ngc number', 'object type', 'constellation', 'right ascension ( j2000 )', 'declination ( j2000 )'] | [['2715', 'spiral galaxy', 'camelopardalis', '09h08 m06 .1 s', 'degree05 ′ 07 ″'], ['2736', 'diffuse nebula', 'vela', '09h00 m', 'degree57 ′'], ['2770', 'spiral galaxy', 'lynx', '09h09 m33 .7 s', 'degree07 ′ 25 ″'], ['2775', 'spiral galaxy', 'cancer', '09h10 m20 .1 s', 'degree02 ′ 18 ″'], ['2787', 'lenticular galaxy', 'ursa major', '09h19 m18 .9 s', 'degree12 ′ 12 ″'], ['2798', 'spiral galaxy', 'lynx', '09h17 m23 .0 s', 'degree59 ′ 58 ″'], ['2799', 'irregular galaxy', 'lynx', '09h17 m31 .2 s', 'degree59 ′ 36 ″']] |
2008 japanese motorcycle grand prix | https://en.wikipedia.org/wiki/2008_Japanese_motorcycle_Grand_Prix | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16882800-1.html.csv | unique | kousuke akiyoshi is the only racer that had an accident in the entire race . | {'scope': 'all', 'row': '19', 'col': '4', 'col_other': '1', 'criterion': 'equal', 'value': 'accident', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'time', 'accident'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose time record fuzzily matches to accident .', 'tostr': 'filter_eq { all_rows ; time ; accident }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; time ; accident } }', 'tointer': 'select the rows whose time record fuzzily matches to accident . 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', 'accident'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose time record fuzzily matches to accident .', 'tostr': 'filter_eq { all_rows ; time ; accident }'}, 'rider'], 'result': 'kousuke akiyoshi', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; time ; accident } ; rider }'}, 'kousuke akiyoshi'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; time ; accident } ; rider } ; kousuke akiyoshi }', 'tointer': 'the rider record of this unqiue row is kousuke akiyoshi .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; time ; accident } } ; eq { hop { filter_eq { all_rows ; time ; accident } ; rider } ; kousuke akiyoshi } } = true', 'tointer': 'select the rows whose time record fuzzily matches to accident . there is only one such row in the table . the rider record of this unqiue row is kousuke akiyoshi .'} | and { only { filter_eq { all_rows ; time ; accident } } ; eq { hop { filter_eq { all_rows ; time ; accident } ; rider } ; kousuke akiyoshi } } = true | select the rows whose time record fuzzily matches to accident . there is only one such row in the table . the rider record of this unqiue row is kousuke akiyoshi . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'time_7': 7, 'accident_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'rider_9': 9, 'kousuke akiyoshi_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', 'accident_8': 'accident', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'rider_9': 'rider', 'kousuke akiyoshi_10': 'kousuke akiyoshi'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'time_7': [0], 'accident_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'rider_9': [2], 'kousuke akiyoshi_10': [3]} | ['rider', 'manufacturer', 'laps', 'time', 'grid'] | [['valentino rossi', 'yamaha', '24', '43:09.599', '4'], ['casey stoner', 'ducati', '24', '+ 1.943', '2'], ['dani pedrosa', 'honda', '24', '+ 4.866', '5'], ['jorge lorenzo', 'yamaha', '24', '+ 6.165', '1'], ['nicky hayden', 'honda', '24', '+ 24.593', '3'], ['loris capirossi', 'suzuki', '24', '+ 25.685', '6'], ['colin edwards', 'yamaha', '24', '+ 25.918', '7'], ['shinya nakano', 'honda', '24', '+ 26.003', '9'], ['andrea dovizioso', 'honda', '24', '+ 26.219', '13'], ['john hopkins', 'kawasaki', '24', '+ 37.131', '11'], ['james toseland', 'yamaha', '24', '+ 37.574', '10'], ['randy de puniet', 'honda', '24', '+ 38.020', '8'], ['marco melandri', 'ducati', '24', '+ 39.768', '16'], ['sylvain guintoli', 'ducati', '24', '+ 45.846', '15'], ['anthony west', 'kawasaki', '24', '+ 55.748', '17'], ['toni elias', 'ducati', '24', '+ 59.320', '14'], ['alex de angelis', 'honda', '24', '+ 1:12.398', '18'], ['chris vermeulen', 'suzuki', '16', 'retirement', '12'], ['kousuke akiyoshi', 'suzuki', '0', 'accident', '19']] |
allegheny mountain collegiate conference | https://en.wikipedia.org/wiki/Allegheny_Mountain_Collegiate_Conference | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1971074-1.html.csv | unique | only one public institution that belongs to the allegheny mountain collegiate conference have been founded before 1940 . | {'scope': 'subset', 'row': '7', 'col': '4', 'col_other': '5', 'criterion': 'less_than', 'value': '1940', 'subset': {'col': '5', 'criterion': 'equal', 'value': 'public'}} | {'func': 'only', 'args': [{'func': 'filter_less', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'type', 'public'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; type ; public }', 'tointer': 'select the rows whose type record fuzzily matches to public .'}, 'founded', '1940'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose type record fuzzily matches to public . among these rows , select the rows whose founded record is less than 1940 .', 'tostr': 'filter_less { filter_eq { all_rows ; type ; public } ; founded ; 1940 }'}], 'result': True, 'ind': 2, 'tostr': 'only { filter_less { filter_eq { all_rows ; type ; public } ; founded ; 1940 } } = true', 'tointer': 'select the rows whose type record fuzzily matches to public . among these rows , select the rows whose founded record is less than 1940 . there is only one such row in the table .'} | only { filter_less { filter_eq { all_rows ; type ; public } ; founded ; 1940 } } = true | select the rows whose type record fuzzily matches to public . among these rows , select the rows whose founded record is less than 1940 . there is only one such row in the table . | 3 | 3 | {'only_2': 2, 'result_3': 3, 'filter_less_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'type_5': 5, 'public_6': 6, 'founded_7': 7, '1940_8': 8} | {'only_2': 'only', 'result_3': 'true', 'filter_less_1': 'filter_less', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'type_5': 'type', 'public_6': 'public', 'founded_7': 'founded', '1940_8': '1940'} | {'only_2': [3], 'result_3': [], 'filter_less_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'type_5': [0], 'public_6': [0], 'founded_7': [1], '1940_8': [1]} | ['institution', 'location', 'nickname', 'founded', 'type', 'enrollment', 'joined'] | [["d'youville college", 'buffalo , new york', 'spartans', '1946', 'private / catholic', '2900', '2009'], ['franciscan university of steubenville', 'steubenville , ohio', 'barons', '1946', 'private / catholic', '2238', '2008'], ['hilbert college', 'hamburg , new york', 'hawks', '1957', 'private / catholic', '1100', '2005'], ['la roche college', 'pittsburgh , pennsylvania', 'red hawks', '1963', 'private / catholic', '1957', '1997'], ['medaille college', 'buffalo , new york', 'mavericks', '1937', 'private / non - sectarian', '3925', '2005'], ['mount aloysius college', 'cresson , pennsylvania', 'mounties', '1853', 'private / catholic', '1600', '2006'], ['penn state - altoona', 'logan township , pennsylvania', 'nittany lions', '1939', 'public', '3800', '1998'], ['penn state - erie', 'erie , pennsylvania', 'behrend lions', '1948', 'public', '4046', '1997'], ['university of pittsburgh at bradford', 'bradford , pennsylvania', 'panthers', '1963', 'public', '1250', '1997']] |
1971 - 72 philadelphia flyers season | https://en.wikipedia.org/wiki/1971%E2%80%9372_Philadelphia_Flyers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14293527-13.html.csv | majority | all of the players drafted by the flyers were canadian . | {'scope': 'all', 'col': '4', 'most_or_all': 'all', 'criterion': 'fuzzily_match', 'value': 'canada', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'nationality', 'canada'], 'result': True, 'ind': 0, 'tointer': 'for the nationality records of all rows , all of them fuzzily match to canada .', 'tostr': 'all_eq { all_rows ; nationality ; canada } = true'} | all_eq { all_rows ; nationality ; canada } = true | for the nationality records of all rows , all of them fuzzily match to canada . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'nationality_3': 3, 'canada_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'nationality_3': 'nationality', 'canada_4': 'canada'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'nationality_3': [0], 'canada_4': [0]} | ['round', 'player', 'position', 'nationality', 'college / junior / club team ( league )'] | [['1', 'larry wright', 'center', 'canada', 'regina pats ( wchl )'], ['1', 'pierre plante', 'right wing', 'canada', 'drummondville rangers ( qmjhl )'], ['3', 'glen irwin', 'defense', 'canada', 'estevan bruins ( wchl )'], ['4', 'ted scharf', 'right wing', 'canada', 'kitchener rangers ( oha )'], ['5', 'don mcculloch', 'defense', 'canada', 'niagara falls flyers ( oha )'], ['6', 'yvon bilodeau', 'defense', 'canada', 'estevan bruins ( wchl )'], ['7', 'bobby gerard', 'right wing', 'canada', 'regina pats ( wchl )'], ['8', 'jerome mrazek', 'goaltender', 'canada', 'minnesota - duluth bulldogs ( wcha )']] |
ningde | https://en.wikipedia.org/wiki/Ningde | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2013618-1.html.csv | aggregation | the average population of administrative regions in ningde is 338662 . | {'scope': 'all', 'col': '7', 'type': 'average', 'result': '338662', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'population'], 'result': '338662', 'ind': 0, 'tostr': 'avg { all_rows ; population }'}, '338662'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; population } ; 338662 } = true', 'tointer': 'the average of the population record of all rows is 338662 .'} | round_eq { avg { all_rows ; population } ; 338662 } = true | the average of the population record of all rows is 338662 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'population_4': 4, '338662_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'population_4': 'population', '338662_5': '338662'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'population_4': [0], '338662_5': [1]} | ['english name', 'simplified', 'traditional', 'pinyin', 'foochow', 'area', 'population', 'density'] | [['jiaocheng district', '蕉城区', '蕉城區', 'jiāochéng qū', 'ciĕu - siàng - kṳ̆', '1537', '429260', '279'], ["fu'an city", '福安市', '福安市', "fú ' ān shì", 'hók - ăng - chê', '1795', '563640', '314'], ['fuding city', '福鼎市', '福鼎市', 'fúdǐng shì', 'hók - tīng - chê', '1526', '529534', '347'], ['xiapu county', '霞浦县', '霞蒲縣', 'xiápǔ xiàn', 'hà - puō - ging', '1716', '461176', '269'], ['gutian county', '古田县', '古田縣', 'gǔtián xiàn', 'kŭ - chèng - ging', '2377', '323700', '136'], ['pingnan county', '屏南县', '屏南縣', 'píngnán xiàn', 'bìng - nàng - ging', '1485', '137724', '93'], ['shouning county', '寿宁县', '壽寧縣', 'shòuníng xiàn', 'sêu - nìng - ging', '1425', '175874', '123'], ['zherong county', '柘荣县', '柘榮縣', 'zhèróng xiàn', 'ciá - ìng - ging', '544', '88387', '162']] |
list of ultras of oceania | https://en.wikipedia.org/wiki/List_of_Ultras_of_Oceania | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18946749-5.html.csv | superlative | mount popomanaseu is the peak that has the highest elevation in meters of ultras in oceania . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '2', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'elevation ( m )'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; elevation ( m ) }'}, 'peak'], 'result': 'mount popomanaseu', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; elevation ( m ) } ; peak }'}, 'mount popomanaseu'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; elevation ( m ) } ; peak } ; mount popomanaseu } = true', 'tointer': 'select the row whose elevation ( m ) record of all rows is maximum . the peak record of this row is mount popomanaseu .'} | eq { hop { argmax { all_rows ; elevation ( m ) } ; peak } ; mount popomanaseu } = true | select the row whose elevation ( m ) record of all rows is maximum . the peak record of this row is mount popomanaseu . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'elevation (m)_5': 5, 'peak_6': 6, 'mount popomanaseu_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'elevation (m)_5': 'elevation ( m )', 'peak_6': 'peak', 'mount popomanaseu_7': 'mount popomanaseu'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'elevation (m)_5': [0], 'peak_6': [1], 'mount popomanaseu_7': [2]} | ['rank', 'peak', 'country', 'island', 'elevation ( m )', 'col ( m )'] | [['1', 'mount popomanaseu', 'solomon islands', 'guadalcanal', '2335', '0'], ['2', 'mont orohena', 'french polynesia', 'tahiti', '2241', '0'], ['3', 'mount tabwemasana', 'vanuatu', 'espiritu santo', '1879', '0'], ['4', 'silisili', 'samoa', "savai'i", '1858', '0'], ['5', 'mount veve', 'solomon islands', 'kolombangara', '1768', '0'], ['6', 'mont paniã', 'new caledonia', 'grande terre', '1628', '0']] |
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/1-12962773-15.html.csv | majority | the majority of players on the fiba eurobasket 2007 squad play in the guard position . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'guard', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'position', 'guard'], 'result': True, 'ind': 0, 'tointer': 'for the position records of all rows , most of them fuzzily match to guard .', 'tostr': 'most_eq { all_rows ; position ; guard } = true'} | most_eq { all_rows ; position ; guard } = true | for the position records of all rows , most of them fuzzily match to guard . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'position_3': 3, 'guard_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'position_3': 'position', 'guard_4': 'guard'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'position_3': [0], 'guard_4': [0]} | ['no', 'player', 'height', 'position', 'year born', 'current club'] | [['4', 'marco belinelli', '1.96', 'guard', '1986', 'golden state warriors'], ['5', 'gianluca basile', '1.95', 'guard', '1975', 'axa fc barcelona'], ['6', 'stefano mancinelli', '2.03', 'forward', '1983', 'climamio bologna'], ['7', 'matteo soragna', '1.97', 'guard', '1975', 'benetton treviso'], ['8', 'denis marconato', '2.12', 'center', '1975', 'axa fc barcelona'], ['9', 'marco mordente', '1.90', 'guard', '1979', 'benetton treviso'], ['10', 'andrea bargnani', '2.12', 'forward', '1985', 'toronto raptors'], ['11', 'andrea crosariol', '2.13', 'center', '1984', 'vidivici bologna'], ['12', 'massimo bulleri', '1.87', 'guard', '1977', 'armani jeans milano'], ['13', 'fabio di bella', '1.86', 'guard', '1978', 'vidivici bologna'], ['14', 'luigi datome', '2.02', 'forward', '1987', 'legea scafati']] |
2005 cologne centurions season | https://en.wikipedia.org/wiki/2005_Cologne_Centurions_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27764201-2.html.csv | aggregation | the average attendance for the 2005 cologne centurions season was around 19000-20000 fans . | {'scope': 'all', 'col': '8', 'type': 'average', 'result': '16828.89', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'attendance'], 'result': '16828.89', 'ind': 0, 'tostr': 'avg { all_rows ; attendance }'}, '16828.89'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; attendance } ; 16828.89 } = true', 'tointer': 'the average of the attendance record of all rows is 16828.89 .'} | round_eq { avg { all_rows ; attendance } ; 16828.89 } = true | the average of the attendance record of all rows is 16828.89 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'attendance_4': 4, '16828.89_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'attendance_4': 'attendance', '16828.89_5': '16828.89'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'attendance_4': [0], '16828.89_5': [1]} | ['week', 'date', 'kickoff', 'opponent', 'final score', 'team record', 'game site', 'attendance'] | [['1', 'saturday , april 2', '6:00 pm', 'hamburg sea devils', 'w 24 - 23', '1 - 0', 'rheinenergiestadion', '9468'], ['2', 'sunday , april 10', '4:00 pm', 'rhein fire', 'w 23 - 10', '2 - 0', 'ltu arena', '25304'], ['3', 'saturday , april 16', '6:00 pm', 'frankfurt galaxy', 'w 23 - 14', '3 - 0', 'rheinenergiestadion', '10821'], ['4', 'saturday , april 23', '6:00 pm', 'amsterdam admirals', 'l 24 - 37', '3 - 1', 'rheinenergiestadion', '8863'], ['5', 'saturday , april 30', '7:00 pm', 'hamburg sea devils', 'l 6 - 23', '3 - 2', 'aol arena', '15228'], ['6', 'sunday , may 8', '4:00 pm', 'berlin thunder', 'w 23 - 17', '4 - 2', 'rheinenergiestadion', '9485'], ['7', 'saturday , may 14', '7:00 pm', 'frankfurt galaxy', 'w 20 - 17 ot', '5 - 2', 'commerzbank - arena', '25347'], ['8', 'monday , may 23', '8:00 pm', 'amsterdam admirals', 'l 12 - 30', '5 - 3', 'amsterdam arena', '14423'], ['9', 'sunday , may 29', '4:00 pm', 'rhein fire', 'l 16 - 28', '5 - 4', 'rheinenergiestadion', '32521']] |
2009 - 10 washington capitals season | https://en.wikipedia.org/wiki/2009%E2%80%9310_Washington_Capitals_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-23308178-9.html.csv | majority | in most games , the capitals scored over 100 points . | {'scope': 'all', 'col': '8', 'most_or_all': 'most', 'criterion': 'greater_than', 'value': '100', 'subset': None} | {'func': 'most_greater', 'args': ['all_rows', 'points', '100'], 'result': True, 'ind': 0, 'tointer': 'for the points records of all rows , most of them are greater than 100 .', 'tostr': 'most_greater { all_rows ; points ; 100 } = true'} | most_greater { all_rows ; points ; 100 } = true | for the points records of all rows , most of them are greater than 100 . | 1 | 1 | {'most_greater_0': 0, 'result_1': 1, 'all_rows_2': 2, 'points_3': 3, '100_4': 4} | {'most_greater_0': 'most_greater', 'result_1': 'true', 'all_rows_2': 'all_rows', 'points_3': 'points', '100_4': '100'} | {'most_greater_0': [1], 'result_1': [], 'all_rows_2': [0], 'points_3': [0], '100_4': [0]} | ['game', 'date', 'opponent', 'score', 'location', 'attendance', 'record', 'points'] | [['63', 'march 3', 'buffalo sabres', '3 - 1', 'hsbc arena', '18690', '42 - 13 - 8', '92'], ['64', 'march 4', 'tampa bay lightning', '5 - 4', 'verizon center', '18277', '43 - 13 - 8', '94'], ['65', 'march 6', 'new york rangers', '2 - 0', 'verizon center', '18277', '44 - 13 - 8', '96'], ['66', 'march 8', 'dallas stars', '4 - 3 so', 'verizon center', '18277', '44 - 13 - 9', '97'], ['67', 'march 10', 'carolina hurricanes', '4 - 3 ot', 'verizon center', '18277', '45 - 13 - 9', '99'], ['68', 'march 12', 'tampa bay lightning', '2 - 3', 'verizon center', '18277', '45 - 14 - 9', '99'], ['69', 'march 14', 'chicago blackhawks', '4 - 3 ot', 'united center', '22289', '46 - 14 - 9', '101'], ['70', 'march 16', 'florida panthers', '7 - 3', 'bankatlantic center', '15123', '47 - 14 - 9', '103'], ['71', 'march 18', 'carolina hurricanes', '3 - 4 ot', 'rbc center', '18144', '47 - 14 - 10', '104'], ['72', 'march 20', 'tampa bay lightning', '3 - 1', 'st pete times forum', '19844', '48 - 14 - 10', '106'], ['73', 'march 24', 'pittsburgh penguins', '4 - 3 so', 'verizon center', '18277', '49 - 14 - 10', '108'], ['74', 'march 25', 'carolina hurricanes', '3 - 2 so', 'rbc center', '18046', '49 - 14 - 11', '109'], ['75', 'march 28', 'calgary flames', '5 - 3', 'verizon center', '18277', '49 - 15 - 11', '109']] |
ednilson | https://en.wikipedia.org/wiki/Ednilson | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17226452-1.html.csv | aggregation | ednilson made a total of 137 apps from 1999 to 2010 . | {'scope': 'all', 'col': '5', 'type': 'sum', 'result': '137', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'apps'], 'result': '137', 'ind': 0, 'tostr': 'sum { all_rows ; apps }'}, '137'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; apps } ; 137 } = true', 'tointer': 'the sum of the apps record of all rows is 137 .'} | round_eq { sum { all_rows ; apps } ; 137 } = true | the sum of the apps record of all rows is 137 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'apps_4': 4, '137_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'apps_4': 'apps', '137_5': '137'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'apps_4': [0], '137_5': [1]} | ['season', 'team', 'country', 'division', 'apps', 'goals'] | [['1999 - 00', 'roma', 'italy', '1', '1', '0'], ['2000 - 01', 'benfica', 'portugal', '1', '13', '0'], ['2001 - 02', 'benfica', 'portugal', '1', '22', '0'], ['2002 - 03', 'benfica', 'portugal', '1', '8', '0'], ['2003 - 04', 'vitória guimarães', 'portugal', '1', '8', '0'], ['2004 - 05', 'gil vicente', 'portugal', '1', '20', '0'], ['2005 - 06', 'ofi crete', 'greece', '1', '4', '0'], ['2006 - 07', 'ofi crete', 'greece', '1', '13', '0'], ['2007 - 08', 'partizan', 'serbia', '1', '14', '0'], ['2008 - 09', 'aek larnaca', 'cyprus', '1', '5', '0'], ['2009 - 10', 'dinamo tbilisi', 'georgia', '1', '29', '0']] |
2008 - 09 los angeles clippers season | https://en.wikipedia.org/wiki/2008%E2%80%9309_Los_Angeles_Clippers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17323529-6.html.csv | majority | in the 2008 - 09 los angeles clippers season , in all of the games at staples center , baron davis had the high assists . | {'scope': 'subset', 'col': '7', 'most_or_all': 'all', 'criterion': 'fuzzily_match', 'value': 'baron davis', 'subset': {'col': '8', 'criterion': 'fuzzily_match', 'value': 'staples center'}} | {'func': 'all_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location attendance', 'staples center'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; location attendance ; staples center }', 'tointer': 'select the rows whose location attendance record fuzzily matches to staples center .'}, 'high assists', 'baron davis'], 'result': True, 'ind': 1, 'tointer': 'select the rows whose location attendance record fuzzily matches to staples center . for the high assists records of these rows , all of them fuzzily match to baron davis .', 'tostr': 'all_eq { filter_eq { all_rows ; location attendance ; staples center } ; high assists ; baron davis } = true'} | all_eq { filter_eq { all_rows ; location attendance ; staples center } ; high assists ; baron davis } = true | select the rows whose location attendance record fuzzily matches to staples center . for the high assists records of these rows , all of them fuzzily match to baron davis . | 2 | 2 | {'all_str_eq_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, 'location attendance_4': 4, 'staples center_5': 5, 'high assists_6': 6, 'baron davis_7': 7} | {'all_str_eq_1': 'all_str_eq', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'location attendance_4': 'location attendance', 'staples center_5': 'staples center', 'high assists_6': 'high assists', 'baron davis_7': 'baron davis'} | {'all_str_eq_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'location attendance_4': [0], 'staples center_5': [0], 'high assists_6': [1], 'baron davis_7': [1]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record'] | [['17', 'december 2', 'dallas', 'l 98 - 100 ( ot )', 'zach randolph ( 27 )', 'marcus camby ( 15 )', 'baron davis ( 6 )', 'american airlines center 19670', '3 - 14'], ['18', 'december 3', 'houston', 'l 96 - 103 ( ot )', 'al thornton ( 24 )', 'zach randolph , marcus camby ( 11 )', 'baron davis ( 9 )', 'toyota center 15358', '3 - 15'], ['19', 'december 5', 'memphis', 'l 81 - 93 ( ot )', 'baron davis ( 23 )', 'marcus camby ( 10 )', 'baron davis ( 8 )', 'fedexforum 10484', '3 - 16'], ['20', 'december 6', 'minnesota', 'w 107 - 84 ( ot )', 'baron davis ( 27 )', 'marcus camby ( 19 )', 'baron davis ( 9 )', 'target center 10863', '4 - 16'], ['21', 'december 8', 'orlando', 'l 88 - 95 ( ot )', 'baron davis ( 27 )', 'marcus camby ( 17 )', 'baron davis ( 7 )', 'staples center 15222', '4 - 17'], ['22', 'december 12', 'portland', 'w 120 - 112 ( 2ot )', 'zach randolph ( 38 )', 'marcus camby ( 13 )', 'baron davis ( 6 )', 'rose garden 20558', '5 - 17'], ['23', 'december 13', 'houston', 'w 95 - 82 ( ot )', 'zach randolph ( 30 )', 'zach randolph , marcus camby ( 13 )', 'baron davis ( 9 )', 'staples center 16203', '6 - 17'], ['24', 'december 16', 'oklahoma city', 'w 98 - 88 ( ot )', 'eric gordon , zach randolph ( 22 )', 'marcus camby ( 15 )', 'baron davis ( 7 )', 'ford center 18275', '7 - 17'], ['25', 'december 17', 'chicago', 'l 109 - 115 ( ot )', 'zach randolph ( 30 )', 'marcus camby ( 27 )', 'baron davis ( 12 )', 'united center 20102', '7 - 18'], ['26', 'december 19', 'indiana', 'w 117 - 109 ( 2ot )', 'zach randolph ( 34 )', 'zach randolph ( 16 )', 'baron davis ( 11 )', 'conseco fieldhouse 12653', '8 - 18'], ['27', 'december 20', 'milwaukee', 'l 85 - 119 ( ot )', 'al thornton ( 20 )', 'marcus camby ( 11 )', 'jason hart ( 7 )', 'bradley center 15014', '8 - 19'], ['28', 'december 22', 'toronto', 'l 75 - 97 ( ot )', 'eric gordon , zach randolph ( 19 )', 'al thornton ( 9 )', 'baron davis ( 9 )', 'staples center 16094', '8 - 20'], ['29', 'december 28', 'dallas', 'l 76 - 98 ( ot )', 'al thornton , marcus camby ( 16 )', 'marcus camby ( 12 )', 'baron davis ( 9 )', 'staples center 16685', '8 - 21'], ['30', 'december 30', 'sacramento', 'l 90 - 92 ( ot )', 'eric gordon ( 24 )', 'marcus camby ( 24 )', 'marcus camby , baron davis ( 4 )', 'arco arena 11420', '8 - 22'], ['31', 'december 31', 'philadelphia', 'l 92 - 100 ( ot )', 'al thornton ( 24 )', 'marcus camby ( 17 )', 'baron davis ( 8 )', 'staples center 14021', '8 - 23']] |
2007 - 08 colorado avalanche season | https://en.wikipedia.org/wiki/2007%E2%80%9308_Colorado_Avalanche_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11786147-3.html.csv | unique | the game on september 20 was the only game in which the colorado avalanche decision was made for wall . | {'scope': 'all', 'row': '3', 'col': '5', 'col_other': '1', 'criterion': 'equal', 'value': 'wall', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'decision', 'wall'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose decision record fuzzily matches to wall .', 'tostr': 'filter_eq { all_rows ; decision ; wall }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; decision ; wall } }', 'tointer': 'select the rows whose decision record fuzzily matches to wall . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'decision', 'wall'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose decision record fuzzily matches to wall .', 'tostr': 'filter_eq { all_rows ; decision ; wall }'}, 'date'], 'result': 'september 20', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; decision ; wall } ; date }'}, 'september 20'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; decision ; wall } ; date } ; september 20 }', 'tointer': 'the date record of this unqiue row is september 20 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; decision ; wall } } ; eq { hop { filter_eq { all_rows ; decision ; wall } ; date } ; september 20 } } = true', 'tointer': 'select the rows whose decision record fuzzily matches to wall . there is only one such row in the table . the date record of this unqiue row is september 20 .'} | and { only { filter_eq { all_rows ; decision ; wall } } ; eq { hop { filter_eq { all_rows ; decision ; wall } ; date } ; september 20 } } = true | select the rows whose decision record fuzzily matches to wall . there is only one such row in the table . the date record of this unqiue row is september 20 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'decision_7': 7, 'wall_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'date_9': 9, 'september 20_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'decision_7': 'decision', 'wall_8': 'wall', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'date_9': 'date', 'september 20_10': 'september 20'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'decision_7': [0], 'wall_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'date_9': [2], 'september 20_10': [3]} | ['date', 'visitor', 'score', 'home', 'decision', 'record'] | [['september 17', 'colorado', '4 - 3', 'phoenix', 'weiman', '1 - 0'], ['september 19', 'los angeles', '3 - 6', 'colorado', 'budaj', '2 - 0'], ['september 20', 'colorado', '6 - 3', 'dallas', 'wall', '3 - 0'], ['september 22', 'colorado', '2 - 3', 'los angeles', 'weiman', '3 - 1'], ['september 25', 'dallas', '5 - 4', 'colorado', 'budaj', '3 - 2'], ['september 29', 'phoenix', '2 - 3', 'colorado', 'budaj', '4 - 2']] |
2005 jeux de la francophonie | https://en.wikipedia.org/wiki/2005_Jeux_de_la_Francophonie | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12402019-5.html.csv | aggregation | the nations in the 2005 jeux de la francophonie received an average of 0.4375 gold medals . | {'scope': 'all', 'col': '3', 'type': 'average', 'result': '0.4375', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'gold'], 'result': '0.4375', 'ind': 0, 'tostr': 'avg { all_rows ; gold }'}, '0.4375'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; gold } ; 0.4375 } = true', 'tointer': 'the average of the gold record of all rows is 0.4375 .'} | round_eq { avg { all_rows ; gold } ; 0.4375 } = true | the average of the gold record of all rows is 0.4375 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'gold_4': 4, '0.4375_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'gold_4': 'gold', '0.4375_5': '0.4375'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'gold_4': [0], '0.4375_5': [1]} | ['rank', 'nation', 'gold', 'silver', 'bronze', 'total'] | [['1', 'lebanon', '2', '1', '0', '3'], ['2', 'french community of belgium', '1', '0', '1', '2'], ['3', 'benin', '1', '0', '0', '1'], ['3', 'canada', '1', '0', '0', '1'], ['3', 'lithuania', '1', '0', '0', '1'], ['3', 'madagascar', '1', '0', '0', '1'], ['7', 'france', '0', '1', '1', '2'], ['7', 'niger', '0', '1', '1', '2'], ['9', 'new brunswick', '0', '1', '0', '1'], ['9', 'quebec', '0', '1', '0', '1'], ['9', 'cape verde', '0', '1', '0', '1'], ['9', 'morocco', '0', '1', '0', '1'], ['13', 'burkina faso', '0', '0', '1', '1'], ['13', 'republic of the congo', '0', '0', '1', '1'], ['13', 'ivory coast', '0', '0', '1', '1'], ['13', 'macedonia', '0', '0', '1', '1']] |
1975 masters tournament | https://en.wikipedia.org/wiki/1975_Masters_Tournament | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16456989-2.html.csv | majority | in the 1975 masters tournament all of the players come from the united states . | {'scope': 'all', 'col': '3', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'united states', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'country', 'united states'], 'result': True, 'ind': 0, 'tointer': 'for the country records of all rows , all of them fuzzily match to united states .', 'tostr': 'all_eq { all_rows ; country ; united states } = true'} | all_eq { all_rows ; country ; united states } = true | for the country records of all rows , all of them fuzzily match to united states . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'country_3': 3, 'united states_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'country_3': 'country', 'united states_4': 'united states'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'country_3': [0], 'united states_4': [0]} | ['place', 'player', 'country', 'score', 'to par'] | [['1', 'bobby nichols', 'united states', '67', '- 5'], ['t2', 'allen miller', 'united states', '68', '- 4'], ['t2', 'jack nicklaus', 'united states', '68', '- 4'], ['t4', 'arnold palmer', 'united states', '69', '- 3'], ['t4', 'j c snead', 'united states', '69', '- 3'], ['t4', 'tom weiskopf', 'united states', '69', '- 3'], ['t7', 'billy casper', 'united states', '70', '- 2'], ['t7', 'bob murphy', 'united states', '70', '- 2'], ['t7', 'tom watson', 'united states', '70', '- 2'], ['t10', 'tommy aaron', 'united states', '71', '- 1'], ['t10', 'jerry heard', 'united states', '71', '- 1'], ['t10', 'mac mclendon', 'united states', '71', '- 1'], ['t10', 'jerry pate ( a )', 'united states', '71', '- 1'], ['t10', 'sam snead', 'united states', '71', '- 1'], ['t10', 'lee trevino', 'united states', '71', '- 1'], ['t10', 'larry ziegler', 'united states', '71', '- 1']] |
bc lietuvos rytas | https://en.wikipedia.org/wiki/BC_Lietuvos_rytas | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1771141-1.html.csv | majority | bc lietuvos rytas were not champions in the lkf cup for the majority of seasons . | {'scope': 'all', 'col': '2', 'most_or_all': 'most', 'criterion': 'not_equal', 'value': 'champion', 'subset': None} | {'func': 'most_str_not_eq', 'args': ['all_rows', 'lkf cup', 'champion'], 'result': True, 'ind': 0, 'tointer': 'for the lkf cup records of all rows , most of them do not match to champion .', 'tostr': 'most_not_eq { all_rows ; lkf cup ; champion } = true'} | most_not_eq { all_rows ; lkf cup ; champion } = true | for the lkf cup records of all rows , most of them do not match to champion . | 1 | 1 | {'most_str_not_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'lkf cup_3': 3, 'champion_4': 4} | {'most_str_not_eq_0': 'most_str_not_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'lkf cup_3': 'lkf cup', 'champion_4': 'champion'} | {'most_str_not_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'lkf cup_3': [0], 'champion_4': [0]} | ['season', 'lkf cup', 'regional competitions', 'europe', 'head coach'] | [['1997 - 98', 'champion', '-', 'korać cup group stage', 'modestas paulauskas , alfredas vainauskas'], ['1998 - 99', '-', 'nebl 3rd place', 'saporta cup group stage', 'vainauskas , sakalauskas'], ['1999 - 00', '-', 'nebl finalist', 'saporta cup semifinalist', 'vainauskas , sakalauskas'], ['2000 - 01', '-', 'nebl 3rd place', 'suproleague top 16', 'šarūnas sakalauskas , alfredas vainauskas'], ['2001 - 02', '-', 'nebl champion', 'saporta cup quarterfinalist', 'jonas kazlauskas'], ['2002 - 03', '-', 'nebl finalist', 'champions cup group stage', 'jonas kazlauskas'], ['2003 - 04', '-', '-', 'uleb cup quarterfinalist', 'kazlauskas , kemzūra'], ['2004 - 05', '-', 'bbl elite division finalist', 'uleb cup champion', 'vlade djurović , tomo mahorić'], ['2005 - 06', '-', 'bbl elite division champion', 'euroleague top 16', 'neven spahija'], ['2006 - 07', 'finalist', 'bbl elite division champion', 'uleb cup finalist', 'drucker , sagadin , trifunović'], ['2007 - 08', 'finalist', 'bbl elite division finalist', 'euroleague top 16', 'aleksandar trifunović'], ['2008 - 09', 'champion', 'bbl elite division champion', 'eurocup champion', 'antanas sireika , rimas kurtinaitis'], ['2009 - 10', 'champion', 'bbl elite division finalist', 'euroleague group stage', 'rimas kurtinaitis'], ['2010 - 11', 'finalist', 'bbl elite division 3rd place', 'euroleague top 16', 'anzulović , trifunović , maskoliūnas'], ['2010 - 11', 'finalist', 'vtb group stage', 'euroleague top 16', 'anzulović , trifunović , maskoliūnas'], ['2011 - 12', '-', 'bbl elite division finalist', 'eurocup 3rd place', 'aleksandar džikić'], ['2011 - 12', '-', 'vtb 3rd place', 'eurocup 3rd place', 'aleksandar džikić'], ['2012 - 13', '-', 'vtb group stage', 'euroleague group stage', 'džikić , maskoliūnas , bauermann']] |
2005 tim hortons brier | https://en.wikipedia.org/wiki/2005_Tim_Hortons_Brier | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1505809-2.html.csv | ordinal | shawn adams had the second highest shot percentage of players in the 2005 tim hortons brier . | {'row': '3', 'col': '11', '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', 'shot pct', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; shot pct ; 2 }'}, 'skip'], 'result': 'shawn adams', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; shot pct ; 2 } ; skip }'}, 'shawn adams'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; shot pct ; 2 } ; skip } ; shawn adams } = true', 'tointer': 'select the row whose shot pct record of all rows is 2nd maximum . the skip record of this row is shawn adams .'} | eq { hop { nth_argmax { all_rows ; shot pct ; 2 } ; skip } ; shawn adams } = true | select the row whose shot pct record of all rows is 2nd maximum . the skip record of this row is shawn adams . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'shot pct_5': 5, '2_6': 6, 'skip_7': 7, 'shawn adams_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', 'shot pct_5': 'shot pct', '2_6': '2', 'skip_7': 'skip', 'shawn adams_8': 'shawn adams'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'shot pct_5': [0], '2_6': [0], 'skip_7': [1], 'shawn adams_8': [2]} | ['locale', 'skip', 'w', 'l', 'pf', 'pa', 'ends won', 'ends lost', 'blank ends', 'stolen ends', 'shot pct'] | [['alberta', 'randy ferbey', '9', '2', '90', '58', '48', '43', '7', '9', '86 %'], ['manitoba', 'randy dutiaume', '8', '3', '77', '69', '47', '44', '10', '13', '79 %'], ['nova scotia', 'shawn adams', '8', '3', '80', '60', '47', '41', '16', '13', '83 %'], ['quebec', 'jean - michel mãnard', '7', '4', '77', '69', '54', '40', '8', '15', '80 %'], ['british columbia', 'deane horning', '6', '5', '72', '65', '47', '45', '18', '12', '80 %'], ['ontario', 'wayne middaugh', '6', '5', '75', '62', '42', '46', '10', '7', '82 %'], ['newfoundland and labrador', 'brad gushue', '6', '5', '76', '69', '48', '45', '13', '10', '79 %'], ['saskatchewan', 'pat simmons', '6', '5', '66', '61', '43', '45', '12', '9', '80 %'], ['prince edward island', 'rod macdonald', '4', '7', '67', '85', '41', '51', '12', '5', '79 %'], ['northern ontario', 'mike jakubo', '3', '8', '64', '86', '41', '48', '9', '6', '79 %'], ['new brunswick', 'wade blanchard', '3', '8', '56', '83', '41', '45', '17', '8', '78 %']] |
24th united states congress | https://en.wikipedia.org/wiki/24th_United_States_Congress | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-225200-4.html.csv | unique | the virginia 2nd district seat was the only seat that was not filled during the 24th united states congress . | {'scope': 'all', 'row': '16', 'col': '5', 'col_other': '1', 'criterion': 'equal', 'value': 'not filled this congress', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date successor seated', 'not filled this congress'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose date successor seated record fuzzily matches to not filled this congress .', 'tostr': 'filter_eq { all_rows ; date successor seated ; not filled this congress }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; date successor seated ; not filled this congress } }', 'tointer': 'select the rows whose date successor seated record fuzzily matches to not filled this congress . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date successor seated', 'not filled this congress'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose date successor seated record fuzzily matches to not filled this congress .', 'tostr': 'filter_eq { all_rows ; date successor seated ; not filled this congress }'}, 'district'], 'result': 'virginia 2nd', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; date successor seated ; not filled this congress } ; district }'}, 'virginia 2nd'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; date successor seated ; not filled this congress } ; district } ; virginia 2nd }', 'tointer': 'the district record of this unqiue row is virginia 2nd .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; date successor seated ; not filled this congress } } ; eq { hop { filter_eq { all_rows ; date successor seated ; not filled this congress } ; district } ; virginia 2nd } } = true', 'tointer': 'select the rows whose date successor seated record fuzzily matches to not filled this congress . there is only one such row in the table . the district record of this unqiue row is virginia 2nd .'} | and { only { filter_eq { all_rows ; date successor seated ; not filled this congress } } ; eq { hop { filter_eq { all_rows ; date successor seated ; not filled this congress } ; district } ; virginia 2nd } } = true | select the rows whose date successor seated record fuzzily matches to not filled this congress . there is only one such row in the table . the district record of this unqiue row is virginia 2nd . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'date successor seated_7': 7, 'not filled this congress_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'district_9': 9, 'virginia 2nd_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'date successor seated_7': 'date successor seated', 'not filled this congress_8': 'not filled this congress', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'district_9': 'district', 'virginia 2nd_10': 'virginia 2nd'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'date successor seated_7': [0], 'not filled this congress_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'district_9': [2], 'virginia 2nd_10': [3]} | ['district', 'vacator', 'reason for change', 'successor', 'date successor seated'] | [['south carolina 6th', 'vacant', 'rep warren r davis died during previous congress', 'waddy thompson , jr ( aj )', 'seated september 10 , 1835'], ['georgia at - large', 'vacant', 'rep james m wayne resigned in previous congress', 'jabez y jackson ( j )', 'seated october 5 , 1835'], ['georgia at - large', 'james c terrell ( j )', 'resigned july 8 , 1835 due to ill health', 'hopkins holsey ( j )', 'seated october 5 , 1835'], ['connecticut at - large', 'zalmon wildman ( j )', 'died december 10 , 1835', 'thomas t whittlesey ( j )', 'seated april 29 , 1836'], ['pennsylvania 24th', 'john banks ( am )', 'resigned sometime in 1836', 'john j pearson ( aj )', 'seated december 5 , 1836'], ['south carolina 4th', 'james h hammond ( n )', 'resigned february 26 , 1836 because of ill health', 'franklin h elmore ( n )', 'seated december 10 , 1836'], ['new york 17th', 'samuel beardsley ( j )', 'resigned march 29 , 1836', 'rutger b miller ( j )', 'seated november 9 , 1836'], ['north carolina 12th', 'james graham ( aj )', 'seat declared vacant march 29 , 1836', 'james graham ( aj', 'seated december 5 , 1836'], ['south carolina 8th', 'richard i manning ( j )', 'died may 1 , 1836', 'john p richardson ( j )', 'seated december 19 , 1836'], ['mississippi at - large', 'david dickson ( aj )', 'died july 31 , 1836', 'samuel j gholson ( j )', 'seated december 1 , 1836'], ['georgia at - large', 'george w towns ( j )', 'resigned september 1 , 1836', 'julius c alford ( aj )', 'seated january 2 , 1837'], ['new york 30th', 'philo c fuller ( aj )', 'resigned september 2 , 1836', 'john young ( aj )', 'seated november 9 , 1836'], ['georgia at - large', 'john e coffee ( j )', 'died september 25 , 1836', 'william c dawson ( aj )', 'seated november 7 , 1836'], ['pennsylvania 13th', 'jesse miller ( j )', 'resigned october 30 , 1836', 'james black ( j )', 'seated december 5 , 1836'], ['indiana 6th', 'george l kinnard ( j )', 'died november 26 , 1836', 'william herod ( aj )', 'seated january 25 , 1837'], ['virginia 2nd', 'john y mason ( j )', 'resigned january 11 , 1837', 'vacant', 'not filled this congress']] |
2005 pga championship | https://en.wikipedia.org/wiki/2005_PGA_Championship | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12512153-2.html.csv | majority | most of the players in the 2005 pga championship were 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'] | [['steve elkington', 'australia', '1995', '277', '- 3', 't2'], ['davis love iii', 'united states', '1997', '278', '- 2', 't4'], ['tiger woods', 'united states', '1999 , 2000', '278', '- 2', 't4'], ['vijay singh', 'fiji', '1998 , 2004', '280', 'e', 't10'], ['david toms', 'united states', '2001', '280', 'e', 't10'], ['john daly', 'united states', '1991', '292', '+ 12', 't74'], ['hal sutton', 'united states', '1983', '300', '+ 20', '79']] |
narratives of empire | https://en.wikipedia.org/wiki/Narratives_of_Empire | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11251694-1.html.csv | ordinal | of the narratives of empire , the 2nd to last one published was hollywood . | {'row': '5', 'col': '4', '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', 'published', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; published ; 2 }'}, 'title'], 'result': 'hollywood', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; published ; 2 } ; title }'}, 'hollywood'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; published ; 2 } ; title } ; hollywood } = true', 'tointer': 'select the row whose published record of all rows is 2nd maximum . the title record of this row is hollywood .'} | eq { hop { nth_argmax { all_rows ; published ; 2 } ; title } ; hollywood } = true | select the row whose published record of all rows is 2nd maximum . the title record of this row is hollywood . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'published_5': 5, '2_6': 6, 'title_7': 7, 'hollywood_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', 'published_5': 'published', '2_6': '2', 'title_7': 'title', 'hollywood_8': 'hollywood'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'published_5': [0], '2_6': [0], 'title_7': [1], 'hollywood_8': [2]} | ['order', 'title', 'story timeline', 'published', 'in order of publication'] | [['1', 'burr', '1775 - 1808 , 1833 - 1836 , 1840', '1973', 'second'], ['2', 'lincoln', '1861 - 1865', '1984', 'fourth'], ['3', '1876', '1875 - 1877', '1976', 'third'], ['4', 'empire', '1898 - 1907', '1987', 'fifth'], ['5', 'hollywood', '1917 - 1923', '1990', 'sixth'], ['6', 'washington , dc', '1937 - 1952', '1967', 'first'], ['7', 'the golden age', '1939 - 1954 , 2000', '2000', 'seventh']] |
atlanta falcons draft history | https://en.wikipedia.org/wiki/Atlanta_Falcons_draft_history | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15198842-17.html.csv | unique | david tolomu was the only running back drafted by the atlanta falcons in 1982 who was taken higher than 100th overall . | {'scope': 'subset', 'row': '7', 'col': '3', 'col_other': '4', 'criterion': 'greater_than', 'value': '100th', 'subset': {'col': '5', 'criterion': 'equal', 'value': 'running back'}} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_greater', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'position', 'running back'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; position ; running back }', 'tointer': 'select the rows whose position record fuzzily matches to running back .'}, 'overall', '100th'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose position record fuzzily matches to running back . among these rows , select the rows whose overall record is greater than 100th .', 'tostr': 'filter_greater { filter_eq { all_rows ; position ; running back } ; overall ; 100th }'}], 'result': True, 'ind': 2, 'tostr': 'only { filter_greater { filter_eq { all_rows ; position ; running back } ; overall ; 100th } }', 'tointer': 'select the rows whose position record fuzzily matches to running back . among these rows , select the rows whose overall record is greater than 100th . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_greater', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'position', 'running back'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; position ; running back }', 'tointer': 'select the rows whose position record fuzzily matches to running back .'}, 'overall', '100th'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose position record fuzzily matches to running back . among these rows , select the rows whose overall record is greater than 100th .', 'tostr': 'filter_greater { filter_eq { all_rows ; position ; running back } ; overall ; 100th }'}, 'name'], 'result': 'david tolomu', 'ind': 3, 'tostr': 'hop { filter_greater { filter_eq { all_rows ; position ; running back } ; overall ; 100th } ; name }'}, 'david tolomu'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { filter_greater { filter_eq { all_rows ; position ; running back } ; overall ; 100th } ; name } ; david tolomu }', 'tointer': 'the name record of this unqiue row is david tolomu .'}], 'result': True, 'ind': 5, 'tostr': 'and { only { filter_greater { filter_eq { all_rows ; position ; running back } ; overall ; 100th } } ; eq { hop { filter_greater { filter_eq { all_rows ; position ; running back } ; overall ; 100th } ; name } ; david tolomu } } = true', 'tointer': 'select the rows whose position record fuzzily matches to running back . among these rows , select the rows whose overall record is greater than 100th . there is only one such row in the table . the name record of this unqiue row is david tolomu .'} | and { only { filter_greater { filter_eq { all_rows ; position ; running back } ; overall ; 100th } } ; eq { hop { filter_greater { filter_eq { all_rows ; position ; running back } ; overall ; 100th } ; name } ; david tolomu } } = true | select the rows whose position record fuzzily matches to running back . among these rows , select the rows whose overall record is greater than 100th . there is only one such row in the table . the name record of this unqiue row is david tolomu . | 8 | 6 | {'and_5': 5, 'result_6': 6, 'only_2': 2, 'filter_greater_1': 1, 'filter_str_eq_0': 0, 'all_rows_7': 7, 'position_8': 8, 'running back_9': 9, 'overall_10': 10, '100th_11': 11, 'str_eq_4': 4, 'str_hop_3': 3, 'name_12': 12, 'david tolomu_13': 13} | {'and_5': 'and', 'result_6': 'true', 'only_2': 'only', 'filter_greater_1': 'filter_greater', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_7': 'all_rows', 'position_8': 'position', 'running back_9': 'running back', 'overall_10': 'overall', '100th_11': '100th', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'name_12': 'name', 'david tolomu_13': 'david tolomu'} | {'and_5': [6], 'result_6': [], 'only_2': [5], 'filter_greater_1': [2, 3], 'filter_str_eq_0': [1], 'all_rows_7': [0], 'position_8': [0], 'running back_9': [0], 'overall_10': [1], '100th_11': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'name_12': [3], 'david tolomu_13': [4]} | ['round', 'pick', 'overall', 'name', 'position', 'college'] | [['1', '9', '9', 'gerald riggs', 'running back', 'arizona state'], ['2', '9', '36', 'doug rogers', 'defensive end', 'stanford'], ['3', '8', '63', 'stacey bailey', 'wide receiver', 'san jose state'], ['4', '12', '95', 'reggie brown', 'running back', 'oregon'], ['5', '11', '122', 'von mansfield', 'defensive back', 'wisconsin'], ['6', '10', '149', 'mike kelley', 'quarterback', 'georgia tech'], ['7', '9', '176', 'david tolomu', 'running back', 'hawaii'], ['8', '8', '203', 'ricky eberhart', 'defensive back', 'morris brown'], ['9', '12', '235', 'mike horan', 'punter', 'long beach state'], ['10', '11', '262', 'curtis stowers', 'linebacker', 'mississippi state'], ['11', '9', '288', 'jeff keller', 'wide receiver', 'washington state'], ['12', '9', '315', 'dave levenick', 'linebacker', 'wisconsin']] |
1981 san francisco 49ers season | https://en.wikipedia.org/wiki/1981_San_Francisco_49ers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15353865-2.html.csv | superlative | the san francisco 49ers ' game against the detroit lions recorded the most attendance in the 1981 season . | {'scope': 'all', 'col_superlative': '5', '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', 'attendance'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; attendance }'}, 'opponent'], 'result': 'detroit lions', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; attendance } ; opponent }'}, 'detroit lions'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; attendance } ; opponent } ; detroit lions } = true', 'tointer': 'select the row whose attendance record of all rows is maximum . the opponent record of this row is detroit lions .'} | eq { hop { argmax { all_rows ; attendance } ; opponent } ; detroit lions } = true | select the row whose attendance record of all rows is maximum . the opponent record of this row is detroit lions . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'attendance_5': 5, 'opponent_6': 6, 'detroit lions_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'attendance_5': 'attendance', 'opponent_6': 'opponent', 'detroit lions_7': 'detroit lions'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'attendance_5': [0], 'opponent_6': [1], 'detroit lions_7': [2]} | ['week', 'date', 'opponent', 'result', 'attendance'] | [['1', 'september 6 , 1981', 'detroit lions', 'l 17 - 24', '63710'], ['2', 'september 13 , 1981', 'chicago bears', 'w 28 - 17', '49520'], ['3', 'september 20 , 1981', 'atlanta falcons', 'l 17 - 34', '56653'], ['4', 'september 27 , 1981', 'new orleans saints', 'w 21 - 14', '44433'], ['5', 'october 4 , 1981', 'washington redskins', 'w 30 - 17', '51843'], ['6', 'october 11 , 1981', 'dallas cowboys', 'w 45 - 14', '57574'], ['7', 'october 18 , 1981', 'green bay packers', 'w 13 - 3', '50171'], ['8', 'october 25 , 1981', 'los angeles rams', 'w 20 - 17', '59190'], ['9', 'november 1 , 1981', 'pittsburgh steelers', 'w 17 - 14', '52878'], ['10', 'november 8 , 1981', 'atlanta falcons', 'w 17 - 14', '59127'], ['11', 'november 15 , 1981', 'cleveland browns', 'l 12 - 15', '52455'], ['12', 'november 22 , 1981', 'los angeles rams', 'w 33 - 31', '63456'], ['13', 'november 29 , 1981', 'new york giants', 'w 17 - 10', '57186'], ['14', 'december 6 , 1981', 'cincinnati bengals', 'w 21 - 3', '56796'], ['15', 'december 13 , 1981', 'houston oilers', 'w 28 - 6', '55707'], ['16', 'december 20 , 1981', 'new orleans saints', 'w 21 - 17', '43639']] |
primera división de fútbol profesional apertura 2008 | https://en.wikipedia.org/wiki/Primera_Divisi%C3%B3n_de_F%C3%BAtbol_Profesional_Apertura_2008 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18522916-4.html.csv | aggregation | the average attendance for matches in the primera división de fútbol profesional apertura 2008 was 6999 . | {'scope': 'all', 'col': '1', 'type': 'average', 'result': '6999', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'attendance'], 'result': '6999', 'ind': 0, 'tostr': 'avg { all_rows ; attendance }'}, '6999'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; attendance } ; 6999 } = true', 'tointer': 'the average of the attendance record of all rows is 6999 .'} | round_eq { avg { all_rows ; attendance } ; 6999 } = true | the average of the attendance record of all rows is 6999 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'attendance_4': 4, '6999_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'attendance_4': 'attendance', '6999_5': '6999'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'attendance_4': [0], '6999_5': [1]} | ['attendance', 'round', 'date', 'home', 'score', 'away', 'venue', 'weekday', 'time of day'] | [['14403', 'final', '21 december 2008', 'chalatenango', '3 - 3', 'metapán', 'estadio cuscatlán', 'sunday', 'afternoon'], ['11463', 'semifinal - 2nd leg', '13 december 2008', 'fas', '1 - 3', 'metapán', 'estadio oscar quiteño', 'saturday', 'night'], ['7690', 'round 2', '6 august 2008', 'águila', '3 - 1', 'fas', 'estadio juan francisco barraza', 'wednesday', 'night'], ['6997', 'round 16', '12 november 2008', 'fas', '1 - 0', 'águila', 'estadio oscar quiteño', 'wednesday', 'night'], ['6156', 'round 8', '20 september 2008', 'águila', '1 - 0', 'alianza', 'estadio juan francisco barraza', 'saturday', 'twilight'], ['5815', 'round 15', '15 november 2008', 'fas', '1 - 1', 'metapán', 'estadio oscar quiteño', 'saturday', 'night'], ['5307', 'round 2', '6 august 2008', 'alianza', '3 - 1', 'independiente', 'estadio cuscatlán', 'wednesday', 'afternoon'], ['5122', 'semifinal - 2nd leg', '13 december 2008', 'águila', '1 - 0', 'chalatenango', 'estadio juan francisco barraza', 'saturday', 'night'], ['4800', 'semifinal - 1st leg', '7 december 2008', 'chalatenango', '3 - 0', 'águila', 'estadio josé gregorio martínez', 'sunday', 'afternoon'], ['4722', 'round 13', '5 november 2008', 'águila', '3 - 2', 'firpo', 'estadio juan francisco barraza', 'wednesday', 'night'], ['4510', 'round 3', '9 august 2008', 'firpo', '1 - 2', 'alianza', 'estadio sergio torres', 'saturday', 'night']] |
circuit des ardennes | https://en.wikipedia.org/wiki/Circuit_des_Ardennes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18893428-1.html.csv | ordinal | the second person to have won the circuit des ardennes was pierre de crawhez . | {'row': '2', 'col': '1', 'order': '2', 'col_other': '2', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'year', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; year ; 2 }'}, 'formula'], 'result': 'grand prix', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; year ; 2 } ; formula }'}, 'grand prix'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; year ; 2 } ; formula } ; grand prix } = true', 'tointer': 'select the row whose year record of all rows is 2nd minimum . the formula record of this row is grand prix .'} | eq { hop { nth_argmin { all_rows ; year ; 2 } ; formula } ; grand prix } = true | select the row whose year record of all rows is 2nd minimum . the formula record of this row is grand prix . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'year_5': 5, '2_6': 6, 'formula_7': 7, 'grand prix_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', 'year_5': 'year', '2_6': '2', 'formula_7': 'formula', 'grand prix_8': 'grand prix'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'year_5': [0], '2_6': [0], 'formula_7': [1], 'grand prix_8': [2]} | ['year', 'formula', 'driver', 'constructor', 'location', 'report'] | [['1902', 'grand prix', 'charles jarrott', 'panhard 70', 'bastogne', 'report'], ['1903', 'grand prix', 'pierre de crawhez', 'panhard 70', 'bastogne', 'report'], ['1904', 'grand prix', 'george heath', 'panhard 70', 'bastogne', 'report'], ['1905', 'grand prix', 'victor hãmery', 'darracq', 'bastogne', 'report'], ['1906', 'grand prix', 'arthur duray', 'lorraine - dietrich', 'bastogne', 'report'], ['1907', 'grand prix', 'pierre de caters', 'mercedes - benz', 'bastogne', 'report'], ['1907', 'kaiserpreis', 'john moore - brabazon', 'minerva', 'bastogne', 'report']] |
badminton at the pan american games | https://en.wikipedia.org/wiki/Badminton_at_the_Pan_American_Games | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10371133-1.html.csv | ordinal | united states won the 2nd highest number of bronze medals in badminton at the pan american games . | {'row': '2', 'col': '5', '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', 'bronze', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; bronze ; 2 }'}, 'nation'], 'result': 'united states ( usa )', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; bronze ; 2 } ; nation }'}, 'united states ( usa )'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; bronze ; 2 } ; nation } ; united states ( usa ) } = true', 'tointer': 'select the row whose bronze record of all rows is 2nd maximum . the nation record of this row is united states ( usa ) .'} | eq { hop { nth_argmax { all_rows ; bronze ; 2 } ; nation } ; united states ( usa ) } = true | select the row whose bronze record of all rows is 2nd maximum . the nation record of this row is united states ( usa ) . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'bronze_5': 5, '2_6': 6, 'nation_7': 7, 'united states (usa)_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', 'bronze_5': 'bronze', '2_6': '2', 'nation_7': 'nation', 'united states (usa)_8': 'united states ( usa )'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'bronze_5': [0], '2_6': [0], 'nation_7': [1], 'united states (usa)_8': [2]} | ['rank', 'nation', 'gold', 'silver', 'bronze', 'total'] | [['1', 'canada ( can )', '16', '16', '11', '43'], ['2', 'united states ( usa )', '7', '6', '12', '25'], ['3', 'guatemala ( gua )', '1', '2', '3', '6'], ['4', 'jamaica ( jam )', '1', '0', '5', '6'], ['5', 'cuba ( cub )', '0', '1', '0', '1'], ['6', 'peru ( per )', '0', '0', '14', '14'], ['7', 'mexico ( mex )', '0', '0', '3', '3'], ['8', 'brazil ( bra )', '0', '0', '2', '2'], ['total', 'total', '25', '25', '50', '100']] |
south wales derby | https://en.wikipedia.org/wiki/South_Wales_derby | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15473253-4.html.csv | unique | the league competition was the only competition with 16 draws . | {'scope': 'all', 'row': '1', 'col': '4', 'col_other': '1', 'criterion': 'equal', 'value': '16', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'draw', '16'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose draw record is equal to 16 .', 'tostr': 'filter_eq { all_rows ; draw ; 16 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; draw ; 16 } }', 'tointer': 'select the rows whose draw record is equal to 16 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'draw', '16'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose draw record is equal to 16 .', 'tostr': 'filter_eq { all_rows ; draw ; 16 }'}, 'competition'], 'result': 'league', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; draw ; 16 } ; competition }'}, 'league'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; draw ; 16 } ; competition } ; league }', 'tointer': 'the competition record of this unqiue row is league .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; draw ; 16 } } ; eq { hop { filter_eq { all_rows ; draw ; 16 } ; competition } ; league } } = true', 'tointer': 'select the rows whose draw record is equal to 16 . there is only one such row in the table . the competition record of this unqiue row is league .'} | and { only { filter_eq { all_rows ; draw ; 16 } } ; eq { hop { filter_eq { all_rows ; draw ; 16 } ; competition } ; league } } = true | select the rows whose draw record is equal to 16 . there is only one such row in the table . the competition record of this unqiue row is league . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'draw_7': 7, '16_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'competition_9': 9, 'league_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'draw_7': 'draw', '16_8': '16', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'competition_9': 'competition', 'league_10': 'league'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'draw_7': [0], '16_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'competition_9': [2], 'league_10': [3]} | ['competition', 'total matches', 'cardiff win', 'draw', 'swansea win'] | [['league', '55', '19', '16', '20'], ['fa cup', '2', '0', '0', '2'], ['league cup', '5', '2', '0', '3'], ['associate members cup', '4', '1', '1', '2'], ['welsh cup / faw premier cup', '36', '21', '8', '7'], ['southern league', '4', '1', '2', '1'], ['total', '106', '44', '27', '35']] |
list of rampage killers | https://en.wikipedia.org/wiki/List_of_rampage_killers | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17794738-5.html.csv | ordinal | ernst august wagner 's rampage killing spree is the second oldest rampage . | {'row': '5', 'col': '3', 'order': '2', 'col_other': '1', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'year', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; year ; 2 }'}, 'perpetrator'], 'result': 'wagner , ernst august , 38', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; year ; 2 } ; perpetrator }'}, 'wagner , ernst august , 38'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; year ; 2 } ; perpetrator } ; wagner , ernst august , 38 } = true', 'tointer': 'select the row whose year record of all rows is 2nd minimum . the perpetrator record of this row is wagner , ernst august , 38 .'} | eq { hop { nth_argmin { all_rows ; year ; 2 } ; perpetrator } ; wagner , ernst august , 38 } = true | select the row whose year record of all rows is 2nd minimum . the perpetrator record of this row is wagner , ernst august , 38 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'year_5': 5, '2_6': 6, 'perpetrator_7': 7, 'wagner , ernst august , 38_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', 'year_5': 'year', '2_6': '2', 'perpetrator_7': 'perpetrator', 'wagner , ernst august , 38_8': 'wagner , ernst august , 38'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'year_5': [0], '2_6': [0], 'perpetrator_7': [1], 'wagner , ernst august , 38_8': [2]} | ['perpetrator', 'date', 'year', 'location', 'country', 'killed', 'injured'] | [['grachev , peter', '07.31 july 31', '1925', 'ivankovo', 'soviet union', '17', '03 3'], ['ryan , michael robert , 27', '08.19 aug 19', '1987', 'hungerford', 'united kingdom', '16', '15'], ['borel , eric , 16', '09.23 sep 23 / 24', '1995', 'solliès - pont & cuers', 'france', '15', '04 4'], ['leibacher , friedrich , 57', '09.27 sep 27', '2001', 'zug', 'switzerland', '14', '18'], ['wagner , ernst august , 38', '09.04 sep 4', '1913', 'degerloch & mühlhausen / enz', 'german empire', '14', '11'], ['hz', '06.32', '1939.9', 'kz', 'fz', '100.9', '100.9'], ['unknown', '06.10 june 10 / 11', '1945', 'rouen', 'france', '14', '09 9'], ['dornier , christian , 31', '07.12 july 12', '1989', 'luxiol', 'france', '14', '08 8'], ['dembsky , vladimir', '02.15 feb 15', '1904', 'warsaw', 'russian empire', '13', '10'], ['bogdanović , ljubiša , 60', '04.09 april 9', '2013', 'velika ivanča', 'serbia', '13', '1'], ['bird , derrick , 52', '06.02 june 2', '2010', 'copeland , cumbria', 'united kingdom', '12', '11'], ['pz', '08.32', '1989.9', 'rz', 'soz', '100.9', '100.9'], ['marimon carles , jose , 26', '05.21 may 21', '1928', 'pobla de ferran', 'spain', '10', '02 2'], ['hedin , tore , 25', '08.22 aug 22', '1952', 'saxtorp & hurva', 'sweden', '9', '10 - 20'], ['izquierdo , antonio , 53 izquierdo , emilio , 58', '08.26 aug 26', '1990', 'puerto hurraco', 'spain', '9', '06.12 6 - 12'], ['palić , vinko , 28', '01.01 jan 1', '1993', 'zrinski topolovac', 'croatia', '9', '05.7 5 - 7'], ['tranchita , rosario', '09.25 june 25', '1925', 'librizzi', 'italy', '9', '04 4']] |
2005 african judo championships | https://en.wikipedia.org/wiki/2005_African_Judo_Championships | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10642140-3.html.csv | unique | morocco is the only team to have more than 6 bronze medals in the tournament . | {'scope': 'all', 'row': '9', 'col': '5', 'col_other': '2', 'criterion': 'greater_than', 'value': '6', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'bronze', '6'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose bronze record is greater than 6 .', 'tostr': 'filter_greater { all_rows ; bronze ; 6 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_greater { all_rows ; bronze ; 6 } }', 'tointer': 'select the rows whose bronze record is greater than 6 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'bronze', '6'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose bronze record is greater than 6 .', 'tostr': 'filter_greater { all_rows ; bronze ; 6 }'}, 'nation'], 'result': 'morocco', 'ind': 2, 'tostr': 'hop { filter_greater { all_rows ; bronze ; 6 } ; nation }'}, 'morocco'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_greater { all_rows ; bronze ; 6 } ; nation } ; morocco }', 'tointer': 'the nation record of this unqiue row is morocco .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_greater { all_rows ; bronze ; 6 } } ; eq { hop { filter_greater { all_rows ; bronze ; 6 } ; nation } ; morocco } } = true', 'tointer': 'select the rows whose bronze record is greater than 6 . there is only one such row in the table . the nation record of this unqiue row is morocco .'} | and { only { filter_greater { all_rows ; bronze ; 6 } } ; eq { hop { filter_greater { all_rows ; bronze ; 6 } ; nation } ; morocco } } = true | select the rows whose bronze record is greater than 6 . there is only one such row in the table . the nation record of this unqiue row is morocco . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_greater_0': 0, 'all_rows_6': 6, 'bronze_7': 7, '6_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'nation_9': 9, 'morocco_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_greater_0': 'filter_greater', 'all_rows_6': 'all_rows', 'bronze_7': 'bronze', '6_8': '6', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'nation_9': 'nation', 'morocco_10': 'morocco'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_greater_0': [1, 2], 'all_rows_6': [0], 'bronze_7': [0], '6_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'nation_9': [2], 'morocco_10': [3]} | ['rank', 'nation', 'gold', 'silver', 'bronze', 'total'] | [['1', 'algeria', '9', '2', '5', '16'], ['2', 'tunisia', '4', '6', '6', '16'], ['3', 'egypt', '3', '3', '1', '7'], ['4', 'senegal', '1', '2', '4', '7'], ['5', 'angola', '1', '0', '0', '1'], ['6', 'south africa', '0', '3', '1', '4'], ['7', 'nigeria', '0', '1', '2', '3'], ['8', 'niger', '0', '1', '0', '1'], ['9', 'morocco', '0', '0', '7', '7'], ['10 =', 'burkina faso', '0', '0', '1', '1'], ['10 =', 'ivory coast', '0', '0', '1', '1'], ['10 =', 'gabon', '0', '0', '1', '1'], ['10 =', 'madagascar', '0', '0', '1', '1']] |
miss world | https://en.wikipedia.org/wiki/Miss_World | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-150343-3.html.csv | ordinal | the country with the 2nd highest number of miss world semi finalists is south africa . | {'row': '8', 'col': '10', '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', 'semifinalists', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; semifinalists ; 2 }'}, 'country / territory'], 'result': 'south africa', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; semifinalists ; 2 } ; country / territory }'}, 'south africa'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; semifinalists ; 2 } ; country / territory } ; south africa } = true', 'tointer': 'select the row whose semifinalists record of all rows is 2nd maximum . the country / territory record of this row is south africa .'} | eq { hop { nth_argmax { all_rows ; semifinalists ; 2 } ; country / territory } ; south africa } = true | select the row whose semifinalists record of all rows is 2nd maximum . the country / territory record of this row is south africa . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'semifinalists_5': 5, '2_6': 6, 'country / territory_7': 7, 'south africa_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', 'semifinalists_5': 'semifinalists', '2_6': '2', 'country / territory_7': 'country / territory', 'south africa_8': 'south africa'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'semifinalists_5': [0], '2_6': [0], 'country / territory_7': [1], 'south africa_8': [2]} | ['rank', 'country / territory', 'miss world', '1st runner - up', '2nd runner - up', '3rd runner - up', '4th runner - up', '5th runner - up', '6th runner - up', 'semifinalists', 'total'] | [['1', 'venezuela', '6', '2', '4', '2', '2', '0', '1', '14', '30'], ['2', 'united kingdom', '5', '6', '4', '3', '3', '1', '1', '14', '37'], ['3', 'india', '5', '1', '0', '1', '1', '0', '0', '12', '20'], ['4', 'united states', '3', '5', '2', '0', '6', '2', '1', '25', '44'], ['5', 'sweden', '3', '1', '0', '2', '2', '2', '0', '10', '20'], ['6', 'jamaica', '3', '0', '3', '1', '2', '0', '0', '14', '23'], ['7', 'iceland', '3', '0', '1', '0', '1', '0', '0', '2', '7'], ['8', 'south africa', '2', '4', '6', '1', '2', '0', '0', '17', '32'], ['9', 'australia', '2', '2', '4', '2', '0', '0', '0', '14', '24'], ['10', 'argentina', '2', '2', '0', '0', '0', '1', '0', '7', '12'], ['11', 'germany', '2', '1', '3', '1', '1', '0', '0', '10', '18'], ['12', 'peru', '2', '1', '1', '0', '0', '0', '0', '3', '7'], ['13', 'netherlands', '2', '1', '0', '1', '1', '0', '0', '9', '14'], ['14', 'austria', '2', '0', '1', '2', '0', '0', '1', '9', '15'], ['15', 'china', '2', '0', '1', '0', '3', '0', '0', '1', '7'], ['16', 'russia', '2', '0', '0', '0', '0', '0', '0', '5', '7'], ['17', 'france', '1', '3', '2', '3', '0', '2', '1', '14', '24'], ['18', 'finland', '1', '2', '1', '1', '1', '0', '0', '11', '17'], ['19', 'philippines', '1', '2', '1', '0', '3', '0', '0', '8', '15'], ['20', 'israel', '1', '1', '6', '3', '0', '1', '1', '11', '24']] |
ice hockey at the 2010 winter olympics - women 's tournament | https://en.wikipedia.org/wiki/Ice_hockey_at_the_2010_Winter_Olympics_%E2%80%93_Women%27s_tournament | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18803620-4.html.csv | aggregation | the total number of goals scored by canadian players at the 2010 winter olympics women 's ice hockey tournament is 26 . | {'scope': 'subset', 'col': '4', 'type': 'sum', 'result': '26', 'subset': {'col': '2', 'criterion': 'fuzzily_match', 'value': '( can )'}} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', '( can )'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; player ; ( can ) }', 'tointer': 'select the rows whose player record fuzzily matches to ( can ) .'}, 'goals'], 'result': '26', 'ind': 1, 'tostr': 'sum { filter_eq { all_rows ; player ; ( can ) } ; goals }'}, '26'], 'result': True, 'ind': 2, 'tostr': 'round_eq { sum { filter_eq { all_rows ; player ; ( can ) } ; goals } ; 26 } = true', 'tointer': 'select the rows whose player record fuzzily matches to ( can ) . the sum of the goals record of these rows is 26 .'} | round_eq { sum { filter_eq { all_rows ; player ; ( can ) } ; goals } ; 26 } = true | select the rows whose player record fuzzily matches to ( can ) . the sum of the goals record of these rows is 26 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'sum_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'player_5': 5, '( can )_6': 6, 'goals_7': 7, '26_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'sum_1': 'sum', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'player_5': 'player', '( can )_6': '( can )', 'goals_7': 'goals', '26_8': '26'} | {'eq_2': [3], 'result_3': [], 'sum_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'player_5': [0], '( can )_6': [0], 'goals_7': [1], '26_8': [2]} | ['rank', 'player', 'games played', 'goals', 'assists'] | [['1', 'meghan agosta ( can )', '5', '9', '6'], ['2', 'jayna hefford ( can )', '5', '5', '7'], ['3', 'stefanie marty ( sui )', '5', '9', '2'], ['4', 'jenny potter ( usa )', '5', '6', '5'], ['5', 'natalie darwitz ( usa )', '5', '4', '7'], ['6', 'caroline ouellette ( can )', '5', '2', '9'], ['6', 'hayley wickenheiser ( can )', '5', '2', '9'], ['8', 'cherie piper ( can )', '5', '5', '5'], ['9', 'monique lamoureux ( usa )', '5', '4', '6'], ['10', 'kelli stack ( usa )', '5', '3', '5'], ['10', 'sarah vaillancourt ( can )', '5', '3', '5']] |
2008 - 09 phoenix suns season | https://en.wikipedia.org/wiki/2008%E2%80%9309_Phoenix_Suns_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17340355-9.html.csv | count | in the 2008 - 09 phoenix suns season , when steve nash had the high assists , six of the games were at us airways center . | {'scope': 'subset', 'criterion': 'fuzzily_match', 'value': 'us airways center', 'result': '6', 'col': '8', 'subset': {'col': '7', 'criterion': 'fuzzily_match', 'value': 'steve nash'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'high assists', 'steve nash'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; high assists ; steve nash }', 'tointer': 'select the rows whose high assists record fuzzily matches to steve nash .'}, 'location attendance', 'us airways center'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose high assists record fuzzily matches to steve nash . among these rows , select the rows whose location attendance record fuzzily matches to us airways center .', 'tostr': 'filter_eq { filter_eq { all_rows ; high assists ; steve nash } ; location attendance ; us airways center }'}], 'result': '6', 'ind': 2, 'tostr': 'count { filter_eq { filter_eq { all_rows ; high assists ; steve nash } ; location attendance ; us airways center } }', 'tointer': 'select the rows whose high assists record fuzzily matches to steve nash . among these rows , select the rows whose location attendance record fuzzily matches to us airways center . the number of such rows is 6 .'}, '6'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_eq { filter_eq { all_rows ; high assists ; steve nash } ; location attendance ; us airways center } } ; 6 } = true', 'tointer': 'select the rows whose high assists record fuzzily matches to steve nash . among these rows , select the rows whose location attendance record fuzzily matches to us airways center . the number of such rows is 6 .'} | eq { count { filter_eq { filter_eq { all_rows ; high assists ; steve nash } ; location attendance ; us airways center } } ; 6 } = true | select the rows whose high assists record fuzzily matches to steve nash . among these rows , select the rows whose location attendance record fuzzily matches to us airways center . the number of such rows is 6 . | 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, 'high assists_6': 6, 'steve nash_7': 7, 'location attendance_8': 8, 'us airways center_9': 9, '6_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', 'high assists_6': 'high assists', 'steve nash_7': 'steve nash', 'location attendance_8': 'location attendance', 'us airways center_9': 'us airways center', '6_10': '6'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_str_eq_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'high assists_6': [0], 'steve nash_7': [0], 'location attendance_8': [1], 'us airways center_9': [1], '6_10': [3]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record'] | [['59', 'march 1', 'la lakers', 'w 118 - 111 ( ot )', "shaquille o'neal ( 33 )", 'matt barnes ( 10 )', 'matt barnes , leandro barbosa ( 7 )', 'us airways center 18422', '34 - 25'], ['60', 'march 3', 'orlando', 'l 99 - 111 ( ot )', 'jason richardson ( 27 )', "shaquille o'neal ( 11 )", 'steve nash ( 8 )', 'amway arena 17461', '34 - 26'], ['61', 'march 4', 'miami', 'l 129 - 135 ( ot )', 'steve nash ( 29 )', "shaquille o'neal ( 8 )", 'steve nash ( 10 )', 'american airlines arena 19600', '34 - 27'], ['62', 'march 6', 'houston', 'l 112 - 116 ( ot )', 'steve nash ( 32 )', 'matt barnes ( 9 )', 'steve nash ( 13 )', 'toyota center 18045', '34 - 28'], ['63', 'march 8', 'san antonio', 'l 98 - 103 ( ot )', 'steve nash ( 23 )', 'grant hill ( 8 )', 'steve nash ( 11 )', 'at & t center 18797', '34 - 29'], ['64', 'march 10', 'dallas', 'l 117 - 122 ( ot )', 'steve nash ( 23 )', 'louis amundson ( 9 )', 'steve nash ( 13 )', 'us airways center 18422', '34 - 30'], ['65', 'march 12', 'cleveland', 'l 111 - 119 ( ot )', 'matt barnes ( 21 )', "jason richardson , shaquille o'neal ( 7 )", 'steve nash ( 6 )', 'us airways center 18422', '34 - 31'], ['66', 'march 14', 'oklahoma city', 'w 106 - 95 ( ot )', 'leandro barbosa ( 22 )', 'jared dudley ( 9 )', 'steve nash ( 8 )', 'us airways center 18422', '35 - 31'], ['67', 'march 15', 'golden state', 'w 154 - 130 ( ot )', 'jason richardson ( 31 )', 'grant hill ( 8 )', 'matt barnes ( 11 )', 'oracle arena 19596', '36 - 31'], ['68', 'march 18', 'philadelphia', 'w 126 - 116 ( ot )', "shaquille o'neal ( 26 )", "shaquille o'neal ( 11 )", 'steve nash ( 10 )', 'us airways center 18422', '37 - 31'], ['69', 'march 21', 'washington', 'w 128 - 96 ( ot )', 'jason richardson ( 35 )', 'stromile swift ( 12 )', 'jared dudley ( 6 )', 'us airways center 18422', '38 - 31'], ['70', 'march 23', 'denver', 'w 118 - 115 ( ot )', 'grant hill ( 23 )', 'grant hill ( 10 )', 'steve nash ( 9 )', 'us airways center 18422', '39 - 31'], ['71', 'march 25', 'utah', 'w 118 - 114 ( ot )', 'grant hill ( 26 )', "shaquille o'neal ( 12 )", 'steve nash ( 14 )', 'us airways center 18422', '40 - 31'], ['72', 'march 26', 'portland', 'l 109 - 129 ( ot )', "shaquille o'neal ( 20 )", "shaquille o'neal ( 7 )", 'steve nash ( 5 )', 'rose garden 20650', '40 - 32'], ['73', 'march 28', 'utah', 'l 99 - 104 ( ot )', 'steve nash ( 20 )', "shaquille o'neal , matt barnes ( 10 )", 'steve nash ( 6 )', 'energysolutions arena 19911', '40 - 33'], ['74', 'march 29', 'sacramento', 'l 118 - 126 ( ot )', 'steve nash ( 31 )', 'jared dudley ( 11 )', 'steve nash ( 14 )', 'arco arena 13623', '40 - 34']] |
1986 san francisco 49ers season | https://en.wikipedia.org/wiki/1986_San_Francisco_49ers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16714751-1.html.csv | superlative | the largest crowd occurred when the date was september 28th , 1986 . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '4', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '2', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'attendance'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; attendance }'}, 'date'], 'result': 'september 28 , 1986', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; attendance } ; date }'}, 'september 28 , 1986'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; attendance } ; date } ; september 28 , 1986 } = true', 'tointer': 'select the row whose attendance record of all rows is maximum . the date record of this row is september 28 , 1986 .'} | eq { hop { argmax { all_rows ; attendance } ; date } ; september 28 , 1986 } = true | select the row whose attendance record of all rows is maximum . the date record of this row is september 28 , 1986 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'attendance_5': 5, 'date_6': 6, 'september 28 , 1986_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'attendance_5': 'attendance', 'date_6': 'date', 'september 28 , 1986_7': 'september 28 , 1986'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'attendance_5': [0], 'date_6': [1], 'september 28 , 1986_7': [2]} | ['week', 'date', 'opponent', 'result', 'attendance'] | [['1', 'september 7 , 1986', 'tampa bay buccaneers', 'w 31 - 7', '50780'], ['2', 'september 14 , 1986', 'los angeles rams', 'l 13 - 16', '65195'], ['3', 'september 21 , 1986', 'new orleans saints', 'w 26 - 17', '58297'], ['4', 'september 28 , 1986', 'miami dolphins', 'w 31 - 16', '70264'], ['5', 'october 5 , 1986', 'indianapolis colts', 'w 35 - 15', '57252'], ['6', 'october 12 , 1986', 'minnesota vikings', 'l 24 - 27 ( ot )', '58637'], ['7', 'october 19 , 1986', 'atlanta falcons', 't 10 - 10 ( ot )', '55306'], ['8', 'october 26 , 1986', 'green bay packers ( at milwaukee )', 'w 31 - 17', '50557'], ['9', 'november 2 , 1986', 'new orleans saints', 'l 10 - 23', '53234'], ['10', 'november 9 , 1986', 'st louis cardinals', 'w 43 - 17', '59172'], ['11', 'november 17 , 1986 ( mon )', 'washington redskins', 'l 6 - 14', '54774'], ['12', 'november 23 , 1986', 'atlanta falcons', 'w 20 - 0', '58747'], ['13', 'december 1 , 1986 ( mon )', 'new york giants', 'l 17 - 21', '59777'], ['14', 'december 7 , 1986', 'new york jets', 'w 24 - 10', '58091'], ['15', 'december 14 , 1986', 'new england patriots', 'w 29 - 24', '60787'], ['16', 'december 19 , 1986 ( fri )', 'los angeles rams', 'w 24 - 14', '60366']] |
calgary - edmonton corridor | https://en.wikipedia.org/wiki/Calgary%E2%80%93Edmonton_Corridor | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2134521-1.html.csv | ordinal | in the calgary - edmonton corridor , division no 11 has the highest area ( km square ) among those with pop ( 1996 ) less than 1000000 . | {'scope': 'subset', 'row': '3', 'col': '2', 'order': '1', 'col_other': '1', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'subset': {'col': '6', 'criterion': 'less_than', 'value': '1000000'}} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'pop ( 1996 )', '1000000'], 'result': None, 'ind': 0, 'tostr': 'filter_less { all_rows ; pop ( 1996 ) ; 1000000 }', 'tointer': 'select the rows whose pop ( 1996 ) record is less than 1000000 .'}, 'area ( km square )', '1'], 'result': None, 'ind': 1, 'tostr': 'nth_argmax { filter_less { all_rows ; pop ( 1996 ) ; 1000000 } ; area ( km square ) ; 1 }'}, 'census division'], 'result': 'division no 11', 'ind': 2, 'tostr': 'hop { nth_argmax { filter_less { all_rows ; pop ( 1996 ) ; 1000000 } ; area ( km square ) ; 1 } ; census division }'}, 'division no 11'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { nth_argmax { filter_less { all_rows ; pop ( 1996 ) ; 1000000 } ; area ( km square ) ; 1 } ; census division } ; division no 11 } = true', 'tointer': 'select the rows whose pop ( 1996 ) record is less than 1000000 . select the row whose area ( km square ) record of these rows is 1st maximum . the census division record of this row is division no 11 .'} | eq { hop { nth_argmax { filter_less { all_rows ; pop ( 1996 ) ; 1000000 } ; area ( km square ) ; 1 } ; census division } ; division no 11 } = true | select the rows whose pop ( 1996 ) record is less than 1000000 . select the row whose area ( km square ) record of these rows is 1st maximum . the census division record of this row is division no 11 . | 4 | 4 | {'str_eq_3': 3, 'result_4': 4, 'str_hop_2': 2, 'nth_argmax_1': 1, 'filter_less_0': 0, 'all_rows_5': 5, 'pop (1996)_6': 6, '1000000_7': 7, 'area (km square)_8': 8, '1_9': 9, 'census division_10': 10, 'division no 11_11': 11} | {'str_eq_3': 'str_eq', 'result_4': 'true', 'str_hop_2': 'str_hop', 'nth_argmax_1': 'nth_argmax', 'filter_less_0': 'filter_less', 'all_rows_5': 'all_rows', 'pop (1996)_6': 'pop ( 1996 )', '1000000_7': '1000000', 'area (km square)_8': 'area ( km square )', '1_9': '1', 'census division_10': 'census division', 'division no 11_11': 'division no 11'} | {'str_eq_3': [4], 'result_4': [], 'str_hop_2': [3], 'nth_argmax_1': [2], 'filter_less_0': [1], 'all_rows_5': [0], 'pop (1996)_6': [0], '1000000_7': [0], 'area (km square)_8': [1], '1_9': [1], 'census division_10': [2], 'division no 11_11': [3]} | ['census division', 'area ( km square )', 'pop ( 2011 )', 'pop ( 2006 )', 'pop ( 2001 )', 'pop ( 1996 )'] | [['division no 6', '12645.88', '1311022', '1160936', '1021060', '880859'], ['division no 8', '9909.31', '189243', '175337', '153049', '133592'], ['division no 11', '15767.99', '1203115', '1076103', '975477', '898888'], ['calgary - edmonton corridor', '38323.18', '2703380', '2412376', '2149586', '1913339'], ['province of alberta', '640081.87', '3645257', '3290350', '2974807', '2696826']] |
1963 in brazilian football | https://en.wikipedia.org/wiki/1963_in_Brazilian_football | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15244400-2.html.csv | majority | most of the teams with less than 10 points had a negative goal difference in 1963 season of brazilian football . | {'scope': 'subset', 'col': '8', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': '-', 'subset': {'col': '3', 'criterion': 'less_than', 'value': '10'}} | {'func': 'most_str_eq', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'points', '10'], 'result': None, 'ind': 0, 'tostr': 'filter_less { all_rows ; points ; 10 }', 'tointer': 'select the rows whose points record is less than 10 .'}, 'difference', '-'], 'result': True, 'ind': 1, 'tointer': 'select the rows whose points record is less than 10 . for the difference records of these rows , most of them fuzzily match to - .', 'tostr': 'most_eq { filter_less { all_rows ; points ; 10 } ; difference ; - } = true'} | most_eq { filter_less { all_rows ; points ; 10 } ; difference ; - } = true | select the rows whose points record is less than 10 . for the difference records of these rows , most of them fuzzily match to - . | 2 | 2 | {'most_str_eq_1': 1, 'result_2': 2, 'filter_less_0': 0, 'all_rows_3': 3, 'points_4': 4, '10_5': 5, 'difference_6': 6, '-_7': 7} | {'most_str_eq_1': 'most_str_eq', 'result_2': 'true', 'filter_less_0': 'filter_less', 'all_rows_3': 'all_rows', 'points_4': 'points', '10_5': '10', 'difference_6': 'difference', '-_7': '-'} | {'most_str_eq_1': [2], 'result_2': [], 'filter_less_0': [1], 'all_rows_3': [0], 'points_4': [0], '10_5': [0], 'difference_6': [1], '-_7': [1]} | ['position', 'team', 'points', 'played', 'drawn', 'lost', 'against', 'difference'] | [['1', 'santos', '13', '9', '1', '2', '15', '15'], ['2', 'corinthians', '12', '9', '0', '3', '9', '8'], ['3', 'fluminense', '11', '9', '3', '2', '12', '1'], ['4', 'botafogo', '10', '9', '4', '2', '14', '2'], ['5', 'palmeiras', '10', '9', '2', '3', '12', '0'], ['6', 'portuguesa', '9', '9', '3', '3', '21', '- 3'], ['7', 'portuguesa', '8', '9', '0', '5', '13', '1'], ['8', 'são paulo', '8', '9', '2', '4', '16', '- 5'], ['9', 'vasco da gama', '7', '9', '5', '3', '12', '- 3'], ['10', 'olaria', '7', '9', '2', '7', '23', '- 14']] |
1988 green bay packers season | https://en.wikipedia.org/wiki/1988_Green_Bay_Packers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-14650373-1.html.csv | comparative | patrick collins was picked by the packers after sterling sharpe had been picked . | {'row_1': '8', 'row_2': '1', 'col': '1', 'col_other': '3', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', 'patrick collins'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose player record fuzzily matches to patrick collins .', 'tostr': 'filter_eq { all_rows ; player ; patrick collins }'}, 'pick'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; player ; patrick collins } ; pick }', 'tointer': 'select the rows whose player record fuzzily matches to patrick collins . take the pick record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', 'sterling sharpe'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose player record fuzzily matches to sterling sharpe .', 'tostr': 'filter_eq { all_rows ; player ; sterling sharpe }'}, 'pick'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; player ; sterling sharpe } ; pick }', 'tointer': 'select the rows whose player record fuzzily matches to sterling sharpe . take the pick record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; player ; patrick collins } ; pick } ; hop { filter_eq { all_rows ; player ; sterling sharpe } ; pick } } = true', 'tointer': 'select the rows whose player record fuzzily matches to patrick collins . take the pick record of this row . select the rows whose player record fuzzily matches to sterling sharpe . take the pick record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; player ; patrick collins } ; pick } ; hop { filter_eq { all_rows ; player ; sterling sharpe } ; pick } } = true | select the rows whose player record fuzzily matches to patrick collins . take the pick record of this row . select the rows whose player record fuzzily matches to sterling sharpe . take the pick record of this row . the first record is greater than the second record . | 5 | 5 | {'greater_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'player_7': 7, 'patrick collins_8': 8, 'pick_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'player_11': 11, 'sterling sharpe_12': 12, 'pick_13': 13} | {'greater_4': 'greater', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'player_7': 'player', 'patrick collins_8': 'patrick collins', 'pick_9': 'pick', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'player_11': 'player', 'sterling sharpe_12': 'sterling sharpe', 'pick_13': 'pick'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'player_7': [0], 'patrick collins_8': [0], 'pick_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'player_11': [1], 'sterling sharpe_12': [1], 'pick_13': [3]} | ['pick', 'nfl team', 'player', 'position', 'college'] | [['7', 'green bay packers', 'sterling sharpe', 'wide receiver', 'south carolina'], ['34', 'green bay packers', 'shawn patterson', 'defensive end', 'arizona state'], ['61', 'green bay packers', 'keith woodside', 'running back', 'texas a & m'], ['88', 'green bay packers', 'rollin putzier', 'nose tackle', 'oregon'], ['89', 'green bay packers', 'chuck cecil', 'safety', 'arizona'], ['144', 'green bay packers', 'nate hill', 'defensive end', 'auburn'], ['173', 'green bay packers', 'gary richard', 'cornerback', 'pittsburgh'], ['200', 'green bay packers', 'patrick collins', 'running back', 'oklahoma']] |
1976 oakland raiders season | https://en.wikipedia.org/wiki/1976_Oakland_Raiders_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12293930-1.html.csv | comparative | the oakland raiders drafted dwight lewis earlier than they drafted doug hogan . | {'row_1': '9', 'row_2': '16', 'col': '1', 'col_other': '3', 'relation': 'less', 'record_mentioned': 'yes', 'diff_result': None} | {'func': 'and', 'args': [{'func': 'less', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', 'dwight lewis'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose player record fuzzily matches to dwight lewis .', 'tostr': 'filter_eq { all_rows ; player ; dwight lewis }'}, 'round'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; player ; dwight lewis } ; round }', 'tointer': 'select the rows whose player record fuzzily matches to dwight lewis . take the round record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', 'doug hogan'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose player record fuzzily matches to doug hogan .', 'tostr': 'filter_eq { all_rows ; player ; doug hogan }'}, 'round'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; player ; doug hogan } ; round }', 'tointer': 'select the rows whose player record fuzzily matches to doug hogan . take the round record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; player ; dwight lewis } ; round } ; hop { filter_eq { all_rows ; player ; doug hogan } ; round } }', 'tointer': 'select the rows whose player record fuzzily matches to dwight lewis . take the round record of this row . select the rows whose player record fuzzily matches to doug hogan . take the round record of this row . the first record is less than the second record .'}, {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', 'dwight lewis'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose player record fuzzily matches to dwight lewis .', 'tostr': 'filter_eq { all_rows ; player ; dwight lewis }'}, 'round'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; player ; dwight lewis } ; round }', 'tointer': 'select the rows whose player record fuzzily matches to dwight lewis . take the round record of this row .'}, '10'], 'result': True, 'ind': 5, 'tostr': 'eq { hop { filter_eq { all_rows ; player ; dwight lewis } ; round } ; 10 }', 'tointer': 'the round record of the first row is 10 .'}, {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', 'doug hogan'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose player record fuzzily matches to doug hogan .', 'tostr': 'filter_eq { all_rows ; player ; doug hogan }'}, 'round'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; player ; doug hogan } ; round }', 'tointer': 'select the rows whose player record fuzzily matches to doug hogan . take the round record of this row .'}, '16'], 'result': True, 'ind': 6, 'tostr': 'eq { hop { filter_eq { all_rows ; player ; doug hogan } ; round } ; 16 }', 'tointer': 'the round record of the second row is 16 .'}], 'result': True, 'ind': 7, 'tostr': 'and { eq { hop { filter_eq { all_rows ; player ; dwight lewis } ; round } ; 10 } ; eq { hop { filter_eq { all_rows ; player ; doug hogan } ; round } ; 16 } }', 'tointer': 'the round record of the first row is 10 . the round record of the second row is 16 .'}], 'result': True, 'ind': 8, 'tostr': 'and { less { hop { filter_eq { all_rows ; player ; dwight lewis } ; round } ; hop { filter_eq { all_rows ; player ; doug hogan } ; round } } ; and { eq { hop { filter_eq { all_rows ; player ; dwight lewis } ; round } ; 10 } ; eq { hop { filter_eq { all_rows ; player ; doug hogan } ; round } ; 16 } } } = true', 'tointer': 'select the rows whose player record fuzzily matches to dwight lewis . take the round record of this row . select the rows whose player record fuzzily matches to doug hogan . take the round record of this row . the first record is less than the second record . the round record of the first row is 10 . the round record of the second row is 16 .'} | and { less { hop { filter_eq { all_rows ; player ; dwight lewis } ; round } ; hop { filter_eq { all_rows ; player ; doug hogan } ; round } } ; and { eq { hop { filter_eq { all_rows ; player ; dwight lewis } ; round } ; 10 } ; eq { hop { filter_eq { all_rows ; player ; doug hogan } ; round } ; 16 } } } = true | select the rows whose player record fuzzily matches to dwight lewis . take the round record of this row . select the rows whose player record fuzzily matches to doug hogan . take the round record of this row . the first record is less than the second record . the round record of the first row is 10 . the round record of the second row is 16 . | 13 | 9 | {'and_8': 8, 'result_9': 9, 'less_4': 4, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_10': 10, 'player_11': 11, 'dwight lewis_12': 12, 'round_13': 13, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_14': 14, 'player_15': 15, 'doug hogan_16': 16, 'round_17': 17, 'and_7': 7, 'eq_5': 5, '10_18': 18, 'eq_6': 6, '16_19': 19} | {'and_8': 'and', 'result_9': 'true', 'less_4': 'less', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_10': 'all_rows', 'player_11': 'player', 'dwight lewis_12': 'dwight lewis', 'round_13': 'round', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_14': 'all_rows', 'player_15': 'player', 'doug hogan_16': 'doug hogan', 'round_17': 'round', 'and_7': 'and', 'eq_5': 'eq', '10_18': '10', 'eq_6': 'eq', '16_19': '16'} | {'and_8': [9], 'result_9': [], 'less_4': [8], 'num_hop_2': [4, 5], 'filter_str_eq_0': [2], 'all_rows_10': [0], 'player_11': [0], 'dwight lewis_12': [0], 'round_13': [2], 'num_hop_3': [4, 6], 'filter_str_eq_1': [3], 'all_rows_14': [1], 'player_15': [1], 'doug hogan_16': [1], 'round_17': [3], 'and_7': [8], 'eq_5': [7], '10_18': [5], 'eq_6': [7], '16_19': [6]} | ['round', 'overall', 'player', 'position', 'college'] | [['2', '34', 'charles philyaw', 'de', 'texas southern'], ['2', '50', 'jeb blount', 'qb', 'tulsa'], ['3', '84', 'rik bonness', 'lb', 'nebraska'], ['4', '110', 'herb mcmath', 'de', 'morningside'], ['5', '146', 'fred steinfort', 'k', 'boston college'], ['7', '204', 'clarence chapman', 'wr', 'eastern michigan'], ['8', '220', 'jerome dove', 'db', 'colorado state'], ['8', '231', 'terry kunz', 'hb', 'colorado'], ['10', '286', 'dwight lewis', 'db', 'purdue'], ['11', '313', 'rich jennings', 'hb', 'maryland'], ['12', '343', 'cedric brown', 's', 'kent state'], ['13', '367', 'craig crnick', 'de', 'idaho'], ['13', '370', 'mark young', 'g', 'washington state'], ['14', '397', 'calvin young', 'hb', 'fresno state'], ['15', '427', 'carl hargrave', 'db', 'upper iowa'], ['16', '454', 'doug hogan', 'db', 'southern california'], ['17', '478', 'buddy tate', 'db', 'tulsa'], ['17', '481', 'nate beasley', 'hb', 'delaware']] |
mike van arsdale | https://en.wikipedia.org/wiki/Mike_van_Arsdale | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14344822-2.html.csv | comparative | mike van arsdale 's fight against chris haseman lasted one more round than his fight against wanderlei silva . | {'row_1': '8', 'row_2': '9', 'col': '5', 'col_other': '3', 'relation': 'diff', 'record_mentioned': 'no', 'diff_result': {'diff_value': '1', 'bigger': 'row1'}} | {'func': 'eq', 'args': [{'func': 'diff', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', 'chris haseman'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose opponent record fuzzily matches to chris haseman .', 'tostr': 'filter_eq { all_rows ; opponent ; chris haseman }'}, 'round'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; opponent ; chris haseman } ; round }', 'tointer': 'select the rows whose opponent record fuzzily matches to chris haseman . take the round record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', 'wanderlei silva'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose opponent record fuzzily matches to wanderlei silva .', 'tostr': 'filter_eq { all_rows ; opponent ; wanderlei silva }'}, 'round'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; opponent ; wanderlei silva } ; round }', 'tointer': 'select the rows whose opponent record fuzzily matches to wanderlei silva . take the round record of this row .'}], 'result': '1', 'ind': 4, 'tostr': 'diff { hop { filter_eq { all_rows ; opponent ; chris haseman } ; round } ; hop { filter_eq { all_rows ; opponent ; wanderlei silva } ; round } }'}, '1'], 'result': True, 'ind': 5, 'tostr': 'eq { diff { hop { filter_eq { all_rows ; opponent ; chris haseman } ; round } ; hop { filter_eq { all_rows ; opponent ; wanderlei silva } ; round } } ; 1 } = true', 'tointer': 'select the rows whose opponent record fuzzily matches to chris haseman . take the round record of this row . select the rows whose opponent record fuzzily matches to wanderlei silva . take the round record of this row . the first record is 1 larger than the second record .'} | eq { diff { hop { filter_eq { all_rows ; opponent ; chris haseman } ; round } ; hop { filter_eq { all_rows ; opponent ; wanderlei silva } ; round } } ; 1 } = true | select the rows whose opponent record fuzzily matches to chris haseman . take the round record of this row . select the rows whose opponent record fuzzily matches to wanderlei silva . take the round record of this row . the first record is 1 larger than the second record . | 6 | 6 | {'eq_5': 5, 'result_6': 6, 'diff_4': 4, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_7': 7, 'opponent_8': 8, 'chris haseman_9': 9, 'round_10': 10, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_11': 11, 'opponent_12': 12, 'wanderlei silva_13': 13, 'round_14': 14, '1_15': 15} | {'eq_5': 'eq', 'result_6': 'true', 'diff_4': 'diff', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_7': 'all_rows', 'opponent_8': 'opponent', 'chris haseman_9': 'chris haseman', 'round_10': 'round', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_11': 'all_rows', 'opponent_12': 'opponent', 'wanderlei silva_13': 'wanderlei silva', 'round_14': 'round', '1_15': '1'} | {'eq_5': [6], 'result_6': [], 'diff_4': [5], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_7': [0], 'opponent_8': [0], 'chris haseman_9': [0], 'round_10': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_11': [1], 'opponent_12': [1], 'wanderlei silva_13': [1], 'round_14': [3], '1_15': [5]} | ['res', 'record', 'opponent', 'method', 'round', 'time', 'location'] | [['loss', '8 - 5', 'matt lindland', 'submission ( guillotine choke )', '1', '3:38', 'california , united states'], ['loss', '8 - 4', 'jorge oliveira', 'submission ( triangle choke )', '1', '4:02', 'idaho , united states'], ['loss', '8 - 3', 'renato sobral', 'submission ( rear naked choke )', '1', '2:21', 'nevada , united states'], ['loss', '8 - 2', 'randy couture', 'submission ( anaconda choke )', '3', '0:52', 'nevada , united states'], ['win', '8 - 1', 'john marsh', 'decision ( unanimous )', '3', '5:00', 'nevada , united states'], ['win', '7 - 1', 'emanuel newton', 'submission ( kimura )', '1', '1:35', 'mexico'], ['win', '6 - 1', 'mario lopez', 'submission ( crucifix )', '1', '0:28', 'mexico'], ['win', '5 - 1', 'chris haseman', 'tko ( strikes )', '2', '3:10', 'nevada , united states'], ['loss', '4 - 1', 'wanderlei silva', 'ko ( punch and kick )', '1', '4:00', 'brazil'], ['win', '4 - 0', 'joe pardo', 'submission ( armlock )', '1', '11:01', 'alabama , united states'], ['win', '3 - 0', 'dario amorim', 'submission ( shoulder injury )', '1', '2:42', 'brazil'], ['win', '2 - 0', 'marcelo barbosa', 'submission ( punches )', '1', '3:36', 'brazil'], ['win', '1 - 0', 'francisco nonato', 'submission ( keylock )', '1', '5:42', 'brazil']] |
fundraising for the 2008 united states presidential election | https://en.wikipedia.org/wiki/Fundraising_for_the_2008_United_States_presidential_election | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12030247-4.html.csv | aggregation | candidates in the 2008 united states presidential election averaged 12444351 in total receipts . | {'scope': 'all', 'col': '2', 'type': 'average', 'result': '12444351', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'total receipts'], 'result': '12444351', 'ind': 0, 'tostr': 'avg { all_rows ; total receipts }'}, '12444351'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; total receipts } ; 12444351 } = true', 'tointer': 'the average of the total receipts record of all rows is 12444351 .'} | round_eq { avg { all_rows ; total receipts } ; 12444351 } = true | the average of the total receipts record of all rows is 12444351 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'total receipts_4': 4, '12444351_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'total receipts_4': 'total receipts', '12444351_5': '12444351'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'total receipts_4': [0], '12444351_5': [1]} | ['candidate', 'total receipts', 'loans received', 'receipts w / o loans', 'money spent', 'cash on hand', 'total debt', 'cash on hand minus debt'] | [['hillary clinton', '27339347', '0', '26776409', '39886410', '37947874', '4987425', '32960449'], ['barack obama', '23526004', '0', '22847568', '40896076', '18626248', '792681', '17833567'], ['john edwards', '13900622', '8974714', '4834761', '18537625', '7790458', '9067278', '- 1276820'], ['joe biden', '3190122', '1132114', '2055971', '3209364', '1867392', '2073418', '- 206026'], ['bill richardson', '4971095', '1000000', '3898226', '8979217', '1813466', '374164', '1439302'], ['dennis kucinich', '1738916', '0', '1738679', '1785429', '282826', '-', '282826']] |
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/1-12962773-1.html.csv | aggregation | the average height of the players was 2.01 . | {'scope': 'all', 'col': '3', 'type': 'average', 'result': '2.01', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'height'], 'result': '2.01', 'ind': 0, 'tostr': 'avg { all_rows ; height }'}, '2.01'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; height } ; 2.01 } = true', 'tointer': 'the average of the height record of all rows is 2.01 .'} | round_eq { avg { all_rows ; height } ; 2.01 } = true | the average of the height record of all rows is 2.01 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'height_4': 4, '2.01_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'height_4': 'height', '2.01_5': '2.01'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'height_4': [0], '2.01_5': [1]} | ['no', 'player', 'height', 'position', 'year born', 'current club'] | [['4', 'theodoros papaloukas', '2.00', 'guard', '1977', 'cska moscow'], ['5', 'ioannis bourousis', '2.13', 'center', '1983', 'olympiacos'], ['6', 'nikolaos zisis', '1.95', 'guard', '1983', 'cska moscow'], ['7', 'vasileios spanoulis', '1.92', 'guard', '1982', 'panathinaikos'], ['8', 'panagiotis vasilopoulos', '2.01', 'forward', '1984', 'olympiacos'], ['9', 'michalis pelekanos', '1.98', 'forward', '1981', 'real madrid'], ['10', 'nikolaos chatzivrettas', '1.95', 'guard', '1977', 'panathinaikos'], ['11', 'dimosthenis dikoudis', '2.06', 'forward', '1977', 'panathinaikos'], ['12', 'konstantinos tsartsaris', '2.09', 'center', '1979', 'panathinaikos'], ['13', 'dimitris diamantidis', '1.96', 'guard', '1980', 'panathinaikos'], ['14', 'lazaros papadopoulos', '2.10', 'center', '1980', 'real madrid']] |
list of nuclear weapons tests | https://en.wikipedia.org/wiki/List_of_nuclear_weapons_tests | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2189647-1.html.csv | count | between 1952 and 1962 , the soviet union carried out 7 nuclear weapons tests . | {'scope': 'all', 'criterion': 'equal', 'value': 'soviet union', 'result': '7', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'soviet union'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose country record fuzzily matches to soviet union .', 'tostr': 'filter_eq { all_rows ; country ; soviet union }'}], 'result': '7', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; country ; soviet union } }', 'tointer': 'select the rows whose country record fuzzily matches to soviet union . the number of such rows is 7 .'}, '7'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; country ; soviet union } } ; 7 } = true', 'tointer': 'select the rows whose country record fuzzily matches to soviet union . the number of such rows is 7 .'} | eq { count { filter_eq { all_rows ; country ; soviet union } } ; 7 } = true | select the rows whose country record fuzzily matches to soviet union . 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, 'country_5': 5, 'soviet union_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', 'country_5': 'country', 'soviet union_6': 'soviet union', '7_7': '7'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'country_5': [0], 'soviet union_6': [0], '7_7': [2]} | ['date ( gmt )', 'yield ( megatons )', 'deployment', 'country', 'test site', 'name or number'] | [['october 30 , 1961', '50', 'parachute air drop', 'soviet union', 'novaya zemlya', 'tsar bomba , test 130'], ['december 24 , 1962', '24.2', 'air drop', 'soviet union', 'novaya zemlya', 'test 219'], ['august 5 , 1962', '21.1', 'air drop', 'soviet union', 'novaya zemlya', 'test 147'], ['september 27 , 1962', '20.0', 'air drop', 'soviet union', 'novaya zemlya', 'test 174'], ['september 25 , 1962', '19.1', 'air drop', 'soviet union', 'novaya zemlya', 'test 173'], ['february 28 , 1954', '15', 'ground', 'usa', 'bikini atoll', 'castle bravo'], ['may 4 , 1954', '13.5', 'barge', 'usa', 'bikini atoll', 'castle yankee'], ['october 23 , 1961', '12.5', 'air drop', 'soviet union', 'novaya zemlya', 'test 123'], ['march 26 , 1954', '11.0', 'barge', 'usa', 'bikini atoll', 'castle romeo'], ['october 31 , 1952', '10.4', 'ground', 'usa', 'eniwetok', 'ivy mike'], ['august 25 , 1962', '10.0', 'air drop', 'soviet union', 'novaya zemlya', 'test 158']] |
vuelta a españa records and statistics | https://en.wikipedia.org/wiki/Vuelta_a_Espa%C3%B1a_records_and_statistics | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18676973-3.html.csv | superlative | spain has more vuelta wins than any other team in the espana records . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '2', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'vuelta wins'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; vuelta wins }'}, 'country'], 'result': 'spain', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; vuelta wins } ; country }'}, 'spain'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; vuelta wins } ; country } ; spain } = true', 'tointer': 'select the row whose vuelta wins record of all rows is maximum . the country record of this row is spain .'} | eq { hop { argmax { all_rows ; vuelta wins } ; country } ; spain } = true | select the row whose vuelta wins record of all rows is maximum . the country record of this row is spain . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'vuelta wins_5': 5, 'country_6': 6, 'spain_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'vuelta wins_5': 'vuelta wins', 'country_6': 'country', 'spain_7': 'spain'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'vuelta wins_5': [0], 'country_6': [1], 'spain_7': [2]} | ['rank', 'country', 'jerseys', 'vuelta wins', 'points', "combo '", 'different holders'] | [['1', 'spain', '631', '31', '15', '12', '85'], ['2', 'france', '155', '9', '5', '2', '24'], ['3', 'belgium', '140', '7', '13', '2', '26'], ['4', 'italy', '100', '5', '4', '1', '18'], ['5', 'switzerland', '89', '5', '2', '1', '5'], ['6', 'germany', '50', '4', '7', '0', '7'], ['7', 'netherlands', '45', '2', '5', '0', '10'], ['8', 'russia', '30', '2', '0', '2', '3'], ['9', 'united kingdom', '26', '0', '1', '0', '6'], ['10', 'colombia', '23', '1', '0', '1', '4'], ['11', 'ireland', '17', '1', '4', '2', '3'], ['12', 'united states', '12', '1', '0', '1', '3'], ['13 =', 'portugal', '5', '0', '0', '0', '1'], ['13 =', 'kazakhstan', '5', '1', '0', '1', '1'], ['13 =', 'australia', '5', '0', '0', '0', '2'], ['13 =', 'denmark', '5', '0', '0', '0', '2'], ['17 =', 'norway', '3', '0', '1', '0', '1'], ['17 =', 'slovenia', '3', '0', '0', '0', '1'], ['18', 'luxembourg', '2', '0', '0', '0', '1'], ['19', 'uzbekistan', '0', '0', '1', '0', '0']] |
list of hartford whalers draft picks | https://en.wikipedia.org/wiki/List_of_Hartford_Whalers_draft_picks | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18278177-5.html.csv | count | out of all the players to be picked for nhl team hartford whalers , only 5 of them came from canada . | {'scope': 'all', 'criterion': 'equal', 'value': 'canada', 'result': '5', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'nationality', 'canada'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose nationality record fuzzily matches to canada .', 'tostr': 'filter_eq { all_rows ; nationality ; canada }'}], 'result': '5', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; nationality ; canada } }', 'tointer': 'select the rows whose nationality record fuzzily matches to canada . the number of such rows is 5 .'}, '5'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; nationality ; canada } } ; 5 } = true', 'tointer': 'select the rows whose nationality record fuzzily matches to canada . the number of such rows is 5 .'} | eq { count { filter_eq { all_rows ; nationality ; canada } } ; 5 } = true | select the rows whose nationality record fuzzily matches to canada . 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, 'nationality_5': 5, 'canada_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', 'nationality_5': 'nationality', 'canada_6': 'canada', '5_7': '5'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'nationality_5': [0], 'canada_6': [0], '5_7': [2]} | ['pick', 'player', 'position', 'nationality', 'nhl team', 'college / junior / club team'] | [['11', 'chris govedaris', 'left wing', 'canada', 'hartford whalers', 'toronto marlboros ( ohl )'], ['32', 'barry richter', 'defence', 'united states', 'hartford whalers', 'culver military academy ( ushs - in )'], ['74', 'dean dyer', 'centre', 'canada', 'hartford whalers', 'lake superior state university ( ncaa )'], ['95', 'scott morrow', 'left wing', 'united states', 'hartford whalers', 'northwood school ( ushs - ny )'], ['137', 'kerry russell', 'c', 'canada', 'hartford whalers', 'michigan state university ( ncaa )'], ['158', 'jim burke', 'd', 'united states', 'hartford whalers', 'university of maine ( ncaa )'], ['179', 'mark hirth', 'c', 'united states', 'hartford whalers', 'michigan state university ( ncaa )'], ['200', 'wayde bucsis', 'lw', 'canada', 'hartford whalers', 'prince albert raiders ( whl )'], ['221', 'rob white', 'd', 'canada', 'hartford whalers', 'st lawrence university ( ncaa )'], ['242', 'dan slatalla', 'c', 'united states', 'hartford whalers', 'deerfield academy ( ushs - ma )']] |
2008 - 09 detroit red wings season | https://en.wikipedia.org/wiki/2008%E2%80%9309_Detroit_Red_Wings_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-17371135-30.html.csv | count | two of the red wings players from the 2008-2009 season were from canada . | {'scope': 'all', 'criterion': 'equal', 'value': 'canada', 'result': '2', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'nationality', 'canada'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose nationality record fuzzily matches to canada .', 'tostr': 'filter_eq { all_rows ; nationality ; canada }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; nationality ; canada } }', 'tointer': 'select the rows whose nationality record fuzzily matches to canada . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; nationality ; canada } } ; 2 } = true', 'tointer': 'select the rows whose nationality record fuzzily matches to canada . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; nationality ; canada } } ; 2 } = true | select the rows whose nationality record fuzzily matches to canada . 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, 'nationality_5': 5, 'canada_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', 'nationality_5': 'nationality', 'canada_6': 'canada', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'nationality_5': [0], 'canada_6': [0], '2_7': [2]} | ['round', 'overall pick', 'player', 'position', 'nationality', 'college / junior / club team ( league )'] | [['1', '30', 'thomas mccollum', 'goaltender', 'united states', 'guelph storm ( ohl )'], ['3', '91', 'max nicastro', 'defenseman', 'united states', 'chicago steel ( ushl )'], ['4', '121', 'gustav nyquist', 'center', 'sweden', 'malmã redhawks ( sweden jr )'], ['5', '151', 'julien cayer', 'center', 'canada', 'northwood school ( hs - new york )'], ['6', '181', 'stephen johnston', 'left wing', 'canada', 'belleville bulls ( ohl )']] |
türk telekom arena | https://en.wikipedia.org/wiki/T%C3%BCrk_Telekom_Arena | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12243387-1.html.csv | majority | all the plans for the türk telekom arena called for at least 125 suites . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'greater_than_eq', 'value': '125', 'subset': None} | {'func': 'most_greater_eq', 'args': ['all_rows', 'suites', '125'], 'result': True, 'ind': 0, 'tointer': 'for the suites records of all rows , most of them are greater than or equal to 125 .', 'tostr': 'most_greater_eq { all_rows ; suites ; 125 } = true'} | most_greater_eq { all_rows ; suites ; 125 } = true | for the suites records of all rows , most of them are greater than or equal to 125 . | 1 | 1 | {'most_greater_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'suites_3': 3, '125_4': 4} | {'most_greater_eq_0': 'most_greater_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'suites_3': 'suites', '125_4': '125'} | {'most_greater_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'suites_3': [0], '125_4': [0]} | ['project', 'year', 'location', 'capacity', 'suites', 'architect', 'cost'] | [['faruk süren project', '1997 - 2001', 'mecidiyeköy', '40482', '125 + 72 boxes without outside seating', 'bbb architects', '118.5 million ( in 2014 dollars )'], ['mehmet cansun project', '2001', 'mecidiyeköy', '35000', '132', 'gs member architecture group', '35 million ( in 2014 dollars )'], ["özhan canaydın : back to süren 's project", '2002 - 2005', 'aslantepe', '40482', '125', 'bbb architects', '90 million ( in 2014 dollars )'], ['eren talu bidding project', '2007', 'aslantepe', '52000', '150', 'populous', 'n / a'], ['özhan canaydın project', '2007', 'aslantepe', '52652', '157', 'asp stuttgart', '250 million ( in 2014 dollars )']] |
raman vasilyuk | https://en.wikipedia.org/wiki/Raman_Vasilyuk | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17373851-1.html.csv | comparative | raman vasilyuk scored international goals in the games played on 16 august 2000 and 22 august 2007 that were both friendly competitions . | {'row_1': '1', 'row_2': '9', 'col': '5', 'col_other': '1', 'relation': 'equal', 'record_mentioned': 'yes', 'diff_result': None} | {'func': 'and', 'args': [{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', '16 august 2000'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose date record fuzzily matches to 16 august 2000 .', 'tostr': 'filter_eq { all_rows ; date ; 16 august 2000 }'}, 'competition'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; date ; 16 august 2000 } ; competition }', 'tointer': 'select the rows whose date record fuzzily matches to 16 august 2000 . take the competition record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', '22 august 2007'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose date record fuzzily matches to 22 august 2007 .', 'tostr': 'filter_eq { all_rows ; date ; 22 august 2007 }'}, 'competition'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; date ; 22 august 2007 } ; competition }', 'tointer': 'select the rows whose date record fuzzily matches to 22 august 2007 . take the competition record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'eq { hop { filter_eq { all_rows ; date ; 16 august 2000 } ; competition } ; hop { filter_eq { all_rows ; date ; 22 august 2007 } ; competition } }', 'tointer': 'select the rows whose date record fuzzily matches to 16 august 2000 . take the competition record of this row . select the rows whose date record fuzzily matches to 22 august 2007 . take the competition record of this row . the first record fuzzily matches to the second record .'}, {'func': 'and', 'args': [{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', '16 august 2000'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose date record fuzzily matches to 16 august 2000 .', 'tostr': 'filter_eq { all_rows ; date ; 16 august 2000 }'}, 'competition'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; date ; 16 august 2000 } ; competition }', 'tointer': 'select the rows whose date record fuzzily matches to 16 august 2000 . take the competition record of this row .'}, 'friendly'], 'result': True, 'ind': 5, 'tostr': 'eq { hop { filter_eq { all_rows ; date ; 16 august 2000 } ; competition } ; friendly }', 'tointer': 'the competition record of the first row is friendly .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', '22 august 2007'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose date record fuzzily matches to 22 august 2007 .', 'tostr': 'filter_eq { all_rows ; date ; 22 august 2007 }'}, 'competition'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; date ; 22 august 2007 } ; competition }', 'tointer': 'select the rows whose date record fuzzily matches to 22 august 2007 . take the competition record of this row .'}, 'friendly'], 'result': True, 'ind': 6, 'tostr': 'eq { hop { filter_eq { all_rows ; date ; 22 august 2007 } ; competition } ; friendly }', 'tointer': 'the competition record of the second row is friendly .'}], 'result': True, 'ind': 7, 'tostr': 'and { eq { hop { filter_eq { all_rows ; date ; 16 august 2000 } ; competition } ; friendly } ; eq { hop { filter_eq { all_rows ; date ; 22 august 2007 } ; competition } ; friendly } }', 'tointer': 'the competition record of the first row is friendly . the competition record of the second row is friendly .'}], 'result': True, 'ind': 8, 'tostr': 'and { eq { hop { filter_eq { all_rows ; date ; 16 august 2000 } ; competition } ; hop { filter_eq { all_rows ; date ; 22 august 2007 } ; competition } } ; and { eq { hop { filter_eq { all_rows ; date ; 16 august 2000 } ; competition } ; friendly } ; eq { hop { filter_eq { all_rows ; date ; 22 august 2007 } ; competition } ; friendly } } } = true', 'tointer': 'select the rows whose date record fuzzily matches to 16 august 2000 . take the competition record of this row . select the rows whose date record fuzzily matches to 22 august 2007 . take the competition record of this row . the first record fuzzily matches to the second record . the competition record of the first row is friendly . the competition record of the second row is friendly .'} | and { eq { hop { filter_eq { all_rows ; date ; 16 august 2000 } ; competition } ; hop { filter_eq { all_rows ; date ; 22 august 2007 } ; competition } } ; and { eq { hop { filter_eq { all_rows ; date ; 16 august 2000 } ; competition } ; friendly } ; eq { hop { filter_eq { all_rows ; date ; 22 august 2007 } ; competition } ; friendly } } } = true | select the rows whose date record fuzzily matches to 16 august 2000 . take the competition record of this row . select the rows whose date record fuzzily matches to 22 august 2007 . take the competition record of this row . the first record fuzzily matches to the second record . the competition record of the first row is friendly . the competition record of the second row is friendly . | 13 | 9 | {'and_8': 8, 'result_9': 9, 'str_eq_4': 4, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_10': 10, 'date_11': 11, '16 august 2000_12': 12, 'competition_13': 13, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_14': 14, 'date_15': 15, '22 august 2007_16': 16, 'competition_17': 17, 'and_7': 7, 'str_eq_5': 5, 'friendly_18': 18, 'str_eq_6': 6, 'friendly_19': 19} | {'and_8': 'and', 'result_9': 'true', 'str_eq_4': 'str_eq', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_10': 'all_rows', 'date_11': 'date', '16 august 2000_12': '16 august 2000', 'competition_13': 'competition', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_14': 'all_rows', 'date_15': 'date', '22 august 2007_16': '22 august 2007', 'competition_17': 'competition', 'and_7': 'and', 'str_eq_5': 'str_eq', 'friendly_18': 'friendly', 'str_eq_6': 'str_eq', 'friendly_19': 'friendly'} | {'and_8': [9], 'result_9': [], 'str_eq_4': [8], 'str_hop_2': [4, 5], 'filter_str_eq_0': [2], 'all_rows_10': [0], 'date_11': [0], '16 august 2000_12': [0], 'competition_13': [2], 'str_hop_3': [4, 6], 'filter_str_eq_1': [3], 'all_rows_14': [1], 'date_15': [1], '22 august 2007_16': [1], 'competition_17': [3], 'and_7': [8], 'str_eq_5': [7], 'friendly_18': [5], 'str_eq_6': [7], 'friendly_19': [6]} | ['date', 'venue', 'score', 'result', 'competition'] | [['16 august 2000', 'skonto stadium , riga , latvia', '1 - 0', '1 - 0', 'friendly'], ['28 march 2001', 'dynama stadium ( minsk ) , belarus', '2 - 1', '2 - 1', '2002 world cup qualifier'], ['5 september 2001', 'dynama stadium ( minsk ) , belarus', '1 - 0', '4 - 1', '2002 world cup qualifier'], ['5 september 2001', 'dynama stadium ( minsk ) , belarus', '2 - 0', '4 - 1', '2002 world cup qualifier'], ['5 september 2001', 'dynama stadium ( minsk ) , belarus', '3 - 0', '4 - 1', '2002 world cup qualifier'], ['5 september 2001', 'dynama stadium ( minsk ) , belarus', '4 - 0', '4 - 1', '2002 world cup qualifier'], ['10 september 2003', 'sheriff stadium , tiraspol , moldova', '1 - 2', '1 - 2', 'euro 2004 qualifier'], ['6 june 2007', 'vasil levski national stadium , sofia , bulgaria', '1 - 0', '1 - 2', 'euro 2008 qualifier'], ['22 august 2007', 'dynama stadium ( minsk ) , belarus', '1 - 0', '2 - 1', 'friendly'], ['2 february 2008', "ta ' qali national stadium , attard , malta", '1 - 0', '2 - 0', 'malta international football tournament']] |
list of superfund sites in connecticut | https://en.wikipedia.org/wiki/List_of_Superfund_sites_in_Connecticut | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10840672-1.html.csv | majority | most of sites in new haven county were proposed earlier than 2000 in the list of superfund sites in connecticut . | {'scope': 'subset', 'col': '4', 'most_or_all': 'most', 'criterion': 'less_than', 'value': '2000', 'subset': {'col': '3', 'criterion': 'equal', 'value': 'new haven'}} | {'func': 'most_less', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'county', 'new haven'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; county ; new haven }', 'tointer': 'select the rows whose county record fuzzily matches to new haven .'}, 'proposed', '2000'], 'result': True, 'ind': 1, 'tointer': 'select the rows whose county record fuzzily matches to new haven . for the proposed records of these rows , most of them are less than 2000 .', 'tostr': 'most_less { filter_eq { all_rows ; county ; new haven } ; proposed ; 2000 } = true'} | most_less { filter_eq { all_rows ; county ; new haven } ; proposed ; 2000 } = true | select the rows whose county record fuzzily matches to new haven . for the proposed records of these rows , most of them are less than 2000 . | 2 | 2 | {'most_less_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, 'county_4': 4, 'new haven_5': 5, 'proposed_6': 6, '2000_7': 7} | {'most_less_1': 'most_less', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'county_4': 'county', 'new haven_5': 'new haven', 'proposed_6': 'proposed', '2000_7': '2000'} | {'most_less_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'county_4': [0], 'new haven_5': [0], 'proposed_6': [1], '2000_7': [1]} | ['cerclis id', 'name', 'county', 'proposed', 'listed', 'construction completed', 'partially deleted', 'deleted'] | [['ctd980670814', 'kellogg - deering well field', 'fairfield', '09 / 08 / 1983', '09 / 21 / 1984', '09 / 23 / 1996', 'n / a', 'n / a'], ['ctd001186618', 'raymark industries , inc', 'fairfield', '01 / 18 / 1994', '04 / 25 / 1995', 'n / a', 'n / a', 'n / a'], ['ct0002055887', 'broad brook mill', 'hartford', '12 / 01 / 2000', 'n / a', 'n / a', 'n / a', 'n / a'], ['ctd980670806', 'old southington landfill', 'hartford', '09 / 08 / 1983', '09 / 21 / 1984', 'n / a', 'n / a', 'n / a'], ['ctd009717604', 'solvents recovery service new england', 'hartford', '12 / 30 / 1982', '09 / 08 / 1983', 'n / a', 'n / a', 'n / a'], ['ctd980732333', 'barkhamsted - new hartford landfill', 'litchfield', '06 / 24 / 1988', '10 / 04 / 1989', '09 / 28 / 2001', 'n / a', 'n / a'], ['ctd001452093', 'durham meadows', 'middlesex', '06 / 24 / 1988', '10 / 04 / 1989', 'n / a', 'n / a', 'n / a'], ['ctd072122062', 'beacon heights landfill', 'new haven', '12 / 30 / 1982', '09 / 08 / 1983', '09 / 09 / 1998', 'n / a', 'n / a'], ['ctd981067317', 'cheshire ground water contamination', 'new haven', '06 / 24 / 1988', '08 / 30 / 1990', '12 / 31 / 1996', 'n / a', '07 / 02 / 1997'], ['ctd980521165', 'laurel park incorporated', 'new haven', '12 / 30 / 1982', '09 / 08 / 1983', '09 / 11 / 1998', 'n / a', 'n / a'], ['ctd980669261', 'nutmeg valley road', 'new haven', '01 / 22 / 1987', '03 / 31 / 1989', '09 / 28 / 2004', 'n / a', '09 / 23 / 2005'], ['ct0002265551', 'scovill industrial landfill', 'new haven', '05 / 11 / 2000', '07 / 27 / 2000', 'n / a', 'n / a', 'n / a'], ['ctd980906515', 'new london submarine base', 'new london', '10 / 26 / 1989', '08 / 30 / 1990', 'n / a', 'n / a', 'n / a'], ['ctd051316313', 'precision plating corp', 'tolland', '06 / 24 / 1988', '10 / 04 / 1989', 'n / a', 'n / a', 'n / a'], ['ctd108960972', "gallup 's quarry", 'windham', '06 / 24 / 1988', '10 / 04 / 1989', '09 / 30 / 1997', 'n / a', 'n / a'], ['ctd001153923', 'linemaster switch corporation', 'windham', '06 / 24 / 1988', '02 / 21 / 1990', '03 / 29 / 2005', 'n / a', 'n / a'], ['ctd004532610', 'revere textile prints corporation', 'windham', '06 / 10 / 1986', '07 / 22 / 1987', '09 / 30 / 1992', 'n / a', '09 / 02 / 1994'], ['ctd009774969', 'yaworski waste lagoon', 'windham', '12 / 30 / 1982', '09 / 08 / 1983', '09 / 20 / 2000', 'n / a', 'n / a']] |
usa today all - usa high school baseball team | https://en.wikipedia.org/wiki/USA_Today_All-USA_high_school_baseball_team | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-11677100-4.html.csv | count | two of the players on the usa today all-usa team were from ca . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'ca', 'result': '2', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'hometown', 'ca'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose hometown record fuzzily matches to ca .', 'tostr': 'filter_eq { all_rows ; hometown ; ca }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; hometown ; ca } }', 'tointer': 'select the rows whose hometown record fuzzily matches to ca . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; hometown ; ca } } ; 2 } = true', 'tointer': 'select the rows whose hometown record fuzzily matches to ca . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; hometown ; ca } } ; 2 } = true | select the rows whose hometown record fuzzily matches to ca . 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, 'hometown_5': 5, 'ca_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', 'hometown_5': 'hometown', 'ca_6': 'ca', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'hometown_5': [0], 'ca_6': [0], '2_7': [2]} | ['player', 'position', 'school', 'hometown', 'mlb draft'] | [['drew henson', 'infielder', 'brighton high school', 'brighton , mi', '3rd round - 97th pick of 1998 draft ( yankees )'], ['josh beckett', 'pitcher', 'spring high school', 'spring , tx', 'beckett was a junior in the 1998 season'], ['j m gold', 'pitcher', 'toms river high school north', 'toms river , nj', '1st round - 13th pick of 1998 draft ( brewers )'], ['gerald laird', 'catcher', 'la quinta high school', 'westminster , ca', "2nd round - 45th pick of 1998 draft ( a 's )"], ['sean burroughs', 'infielder', 'wilson high school', 'long beach , ca', '1st round - 9th pick of 1998 draft ( padres )'], ['felipe lã cubicpez', 'infielder', 'lake brantley high school', 'altamonte springs , fl', '1st round - 8th pick of 1998 draft ( blue jays )'], ['mark teixeira', 'infielder', 'mount saint joseph high school', 'baltimore , md', 'attended georgia tech'], ['chip ambres', 'outfielder', 'west brook senior high school', 'beaumont , tx', '1st round - 27th pick of 1998 draft ( marlins )']] |
ace ( tennis ) | https://en.wikipedia.org/wiki/Ace_%28tennis%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1612222-1.html.csv | ordinal | of the players that served aces in wimbledon , john isner served the most . | {'scope': 'subset', 'row': '1', 'col': '1', 'order': '1', 'col_other': '2', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'subset': {'col': '4', 'criterion': 'equal', 'value': 'wimbledon'}} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'event', 'wimbledon'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; event ; wimbledon }', 'tointer': 'select the rows whose event record fuzzily matches to wimbledon .'}, 'aces', '1'], 'result': None, 'ind': 1, 'tostr': 'nth_argmax { filter_eq { all_rows ; event ; wimbledon } ; aces ; 1 }'}, 'player'], 'result': 'john isner', 'ind': 2, 'tostr': 'hop { nth_argmax { filter_eq { all_rows ; event ; wimbledon } ; aces ; 1 } ; player }'}, 'john isner'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { nth_argmax { filter_eq { all_rows ; event ; wimbledon } ; aces ; 1 } ; player } ; john isner } = true', 'tointer': 'select the rows whose event record fuzzily matches to wimbledon . select the row whose aces record of these rows is 1st maximum . the player record of this row is john isner .'} | eq { hop { nth_argmax { filter_eq { all_rows ; event ; wimbledon } ; aces ; 1 } ; player } ; john isner } = true | select the rows whose event record fuzzily matches to wimbledon . select the row whose aces record of these rows is 1st maximum . the player record of this row is john isner . | 4 | 4 | {'str_eq_3': 3, 'result_4': 4, 'str_hop_2': 2, 'nth_argmax_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'event_6': 6, 'wimbledon_7': 7, 'aces_8': 8, '1_9': 9, 'player_10': 10, 'john isner_11': 11} | {'str_eq_3': 'str_eq', 'result_4': 'true', 'str_hop_2': 'str_hop', 'nth_argmax_1': 'nth_argmax', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'event_6': 'event', 'wimbledon_7': 'wimbledon', 'aces_8': 'aces', '1_9': '1', 'player_10': 'player', 'john isner_11': 'john isner'} | {'str_eq_3': [4], 'result_4': [], 'str_hop_2': [3], 'nth_argmax_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'event_6': [0], 'wimbledon_7': [0], 'aces_8': [1], '1_9': [1], 'player_10': [2], 'john isner_11': [3]} | ['aces', 'player', 'opponent', 'event', 'sets'] | [['113', 'john isner', 'nicolas mahut', '2010 wimbledon', '5'], ['103', 'nicolas mahut', 'john isner', '2010 wimbledon', '5'], ['78', 'ivo karlović', 'radek štěpánek', '2009 davis cup', '5'], ['55', 'ivo karlović', 'lleyton hewitt', '2009 roland garros', '5'], ['54', 'gary muller', 'peter lundgren', '1993 wimbledon', '3'], ['51', 'ivo karlović', 'daniele bracciali', '2005 wimbledon', '5'], ['51', 'joachim johansson', 'andre agassi', '2005 australian open', '4'], ['50', 'roger federer', 'andy roddick', '2009 wimbledon', '5'], ['50', 'chris guccione', 'olivier patience', '2005 wimbledon', '3'], ['50', 'grégory carraz', 'tomáš zíb', '2004 andrézieux challenger', '3'], ['49', 'richard krajicek', 'yevgeny kafelnikov', '1999 us open', '5'], ['48', 'marc rosset', 'arnaud clément', '2001 davis cup', '5'], ['48', 'ivo karlović', 'ivan dodig', '2011 australian open', '5'], ['48', 'nicolás almagro', 'olivier rochus', '2012 wimbledon', '5']] |
2005 philadelphia barrage season | https://en.wikipedia.org/wiki/2005_Philadelphia_Barrage_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12075099-1.html.csv | majority | the majority of games ended in losses for the philadelphia barrage . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': 'l', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'result', 'l'], 'result': True, 'ind': 0, 'tointer': 'for the result records of all rows , most of them fuzzily match to l .', 'tostr': 'most_eq { all_rows ; result ; l } = true'} | most_eq { all_rows ; result ; l } = true | for the result records of all rows , most of them fuzzily match to l . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'result_3': 3, 'l_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'result_3': 'result', 'l_4': 'l'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'result_3': [0], 'l_4': [0]} | ['date', 'opponent', 'home / away', 'field', 'result'] | [['may 29', 'cannons', 'home', 'villanova stadium', 'l 12 - 13'], ['june 4', 'lizards', 'home', 'villanova stadium', 'l 14 - 19'], ['june 12', 'bayhawks', 'away', 'johnny unitas stadium', 'l 9 - 31'], ['june 18', 'pride', 'away', 'alumni stadium ( kean university )', 'w 11 - 10'], ['june 25', 'lizards', 'away', 'mitchel athletic complex', 'l 12 - 18'], ['june 30', 'cannons', 'away', 'nickerson field', 'w 15 - 14'], ['july 9', 'rattlers', 'away', 'bishop kearney field', 'w 26 - 15'], ['july 14', 'rattlers', 'home', 'villanova stadium', 'l 10 - 14'], ['july 23', 'cannons', 'away', 'nickerson field', 'l 10 - 11'], ['july 28', 'lizards', 'home', 'villanova stadium', 'w 16 - 14'], ['august 4', 'bayhawks', 'home', 'villanova stadium', 'l 9 - 19'], ['august 11', 'pride', 'home', 'villanova stadium', 'l 12 - 16']] |
1972 vfl season | https://en.wikipedia.org/wiki/1972_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10826385-21.html.csv | aggregation | in the 1972 vfl season , the average score for home teams was 17.67 points . | {'scope': 'all', 'col': '2', 'type': 'average', 'result': '17.67', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'home team score'], 'result': '17.67', 'ind': 0, 'tostr': 'avg { all_rows ; home team score }'}, '17.67'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; home team score } ; 17.67 } = true', 'tointer': 'the average of the home team score record of all rows is 17.67 .'} | round_eq { avg { all_rows ; home team score } ; 17.67 } = true | the average of the home team score record of all rows is 17.67 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'home team score_4': 4, '17.67_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'home team score_4': 'home team score', '17.67_5': '17.67'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'home team score_4': [0], '17.67_5': [1]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['melbourne', '17.22 ( 124 )', 'north melbourne', '14.7 ( 91 )', 'mcg', '11241', '26 august 1972'], ['footscray', '17.21 ( 123 )', 'richmond', '18.17 ( 125 )', 'western oval', '18117', '26 august 1972'], ['collingwood', '22.17 ( 149 )', 'south melbourne', '11.6 ( 72 )', 'victoria park', '19934', '26 august 1972'], ['carlton', '24.12 ( 156 )', 'hawthorn', '11.22 ( 88 )', 'princes park', '32048', '26 august 1972'], ['fitzroy', '14.20 ( 104 )', 'essendon', '18.11 ( 119 )', 'junction oval', '17252', '26 august 1972'], ['st kilda', '11.10 ( 76 )', 'geelong', '8.13 ( 61 )', 'vfl park', '25663', '26 august 1972']] |
united states house of representatives elections , 1888 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1888 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1431459-6.html.csv | ordinal | the incumbent from the third district of south carolina was the latest seated candidate in office in the 1888 united states house of representatives elections . | {'row': '3', 'col': '4', 'order': '7', 'col_other': '1', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'first elected', '7'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; first elected ; 7 }'}, 'district'], 'result': 'south carolina 3', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; first elected ; 7 } ; district }'}, 'south carolina 3'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; first elected ; 7 } ; district } ; south carolina 3 } = true', 'tointer': 'select the row whose first elected record of all rows is 7th minimum . the district record of this row is south carolina 3 .'} | eq { hop { nth_argmin { all_rows ; first elected ; 7 } ; district } ; south carolina 3 } = true | select the row whose first elected record of all rows is 7th minimum . the district record of this row is south carolina 3 . | 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, '7_6': 6, 'district_7': 7, 'south carolina 3_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', '7_6': '7', 'district_7': 'district', 'south carolina 3_8': 'south carolina 3'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'first elected_5': [0], '7_6': [0], 'district_7': [1], 'south carolina 3_8': [2]} | ['district', 'incumbent', 'party', 'first elected', 'result'] | [['south carolina 1', 'samuel dibble', 'democratic', '1882', 're - elected'], ['south carolina 2', 'george d tillman', 'democratic', '1878', 're - elected'], ['south carolina 3', 'james s cothran', 'democratic', '1886', 're - elected'], ['south carolina 4', 'william h perry', 'democratic', '1884', 're - elected'], ['south carolina 5', 'john j hemphill', 'democratic', '1882', 're - elected'], ['south carolina 6', 'george w dargan', 'democratic', '1882', 're - elected'], ['south carolina 7', 'william elliott', 'democratic', '1884', 're - elected']] |
list of the colbert report episodes ( 2010 ) | https://en.wikipedia.org/wiki/List_of_The_Colbert_Report_episodes_%282010%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-25691838-12.html.csv | unique | episode 806 of the colbert report was the only episode to have garry trudeau as a guest . | {'scope': 'all', 'row': '2', 'col': '3', 'col_other': '1', 'criterion': 'equal', 'value': 'garry trudeau', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'guest', 'garry trudeau'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose guest record fuzzily matches to garry trudeau .', 'tostr': 'filter_eq { all_rows ; guest ; garry trudeau }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; guest ; garry trudeau } }', 'tointer': 'select the rows whose guest record fuzzily matches to garry trudeau . there is only one such row in the table .'}, {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'guest', 'garry trudeau'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose guest record fuzzily matches to garry trudeau .', 'tostr': 'filter_eq { all_rows ; guest ; garry trudeau }'}, 'episode'], 'result': '806', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; guest ; garry trudeau } ; episode }'}, '806'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; guest ; garry trudeau } ; episode } ; 806 }', 'tointer': 'the episode record of this unqiue row is 806 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; guest ; garry trudeau } } ; eq { hop { filter_eq { all_rows ; guest ; garry trudeau } ; episode } ; 806 } } = true', 'tointer': 'select the rows whose guest record fuzzily matches to garry trudeau . there is only one such row in the table . the episode record of this unqiue row is 806 .'} | and { only { filter_eq { all_rows ; guest ; garry trudeau } } ; eq { hop { filter_eq { all_rows ; guest ; garry trudeau } ; episode } ; 806 } } = true | select the rows whose guest record fuzzily matches to garry trudeau . there is only one such row in the table . the episode record of this unqiue row is 806 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'guest_7': 7, 'garry trudeau_8': 8, 'eq_3': 3, 'num_hop_2': 2, 'episode_9': 9, '806_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'guest_7': 'guest', 'garry trudeau_8': 'garry trudeau', 'eq_3': 'eq', 'num_hop_2': 'num_hop', 'episode_9': 'episode', '806_10': '806'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'guest_7': [0], 'garry trudeau_8': [0], 'eq_3': [4], 'num_hop_2': [3], 'episode_9': [2], '806_10': [3]} | ['episode', 'the wãrd', 'guest', 'introductory phrase', 'original airdate', 'production code'] | [['804', 'none', 'jake tapper , michelle rhee', 'none', 'december 01', '6152'], ['806', 'unrequited gov', 'garry trudeau', 'none', 'december 06', '6154'], ['807', 'none', 'julie nixon eisenhower and david eisenhower', 'none', 'december 07', '6155'], ['809', 'none', 'daniel ellsberg , william wegman , julie taymor', 'none', 'december 09', '6157'], ['811', 'none', 'david boies , biz stone , stephen sondheim', 'none', 'december 14', '6159']] |
8th new zealand parliament | https://en.wikipedia.org/wiki/8th_New_Zealand_Parliament | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-28898974-3.html.csv | count | three incumbents of the 8th new zealand parliament vacated their seats due to death . | {'scope': 'all', 'criterion': 'equal', 'value': 'death', 'result': '3', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'reason', 'death'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose reason record fuzzily matches to death .', 'tostr': 'filter_eq { all_rows ; reason ; death }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; reason ; death } }', 'tointer': 'select the rows whose reason record fuzzily matches to death . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; reason ; death } } ; 3 } = true', 'tointer': 'select the rows whose reason record fuzzily matches to death . the number of such rows is 3 .'} | eq { count { filter_eq { all_rows ; reason ; death } } ; 3 } = true | select the rows whose reason record fuzzily matches to death . 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, 'reason_5': 5, 'death_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', 'reason_5': 'reason', 'death_6': 'death', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'reason_5': [0], 'death_6': [0], '3_7': [2]} | ['by - election', 'electorate', 'date', 'incumbent', 'reason', 'winner'] | [['1882', 'franklin north', '9 june', 'benjamin harris', 'election declared void', 'benjamin harris'], ['1882', 'wakanui', '16 june', 'cathcart wason', 'election declared void', 'joseph ivess'], ['1882', 'stanmore', '11 july', 'walter pilliet', 'election declared void', 'walter pilliet'], ['1883', 'peninsula', '22 january', 'james seaton', 'death', 'william larnach'], ['1883', 'selwyn', '6 april', 'john hall', 'resignation', 'edward james lee'], ['1883', 'inangahua', '14 may', 'thomas shailer weston', 'resignation', 'edward shaw'], ['1883', 'bruce', '29 june', 'james rutherford', 'death', 'james mcdonald'], ['1884', 'selwyn', '15 february', 'edward james lee', 'death', 'edward wakefield'], ['1884', 'thorndon', '13 may', 'william levin', 'resignation', 'alfred newman'], ['1884', 'kaiapoi', '16 may', 'isaac wilson', 'resignation', 'edward richardson']] |
1959 portuguese grand prix | https://en.wikipedia.org/wiki/1959_Portuguese_Grand_Prix | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1122212-1.html.csv | count | only three four drivers completed at least 60 laps in the 1959 portuguese grand prix . | {'scope': 'all', 'criterion': 'greater_than_eq', 'value': '60', 'result': '4', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater_eq', 'args': ['all_rows', 'laps', '60'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose laps record is greater than or equal to 60 .', 'tostr': 'filter_greater_eq { all_rows ; laps ; 60 }'}], 'result': '4', 'ind': 1, 'tostr': 'count { filter_greater_eq { all_rows ; laps ; 60 } }', 'tointer': 'select the rows whose laps record is greater than or equal to 60 . the number of such rows is 4 .'}, '4'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_greater_eq { all_rows ; laps ; 60 } } ; 4 } = true', 'tointer': 'select the rows whose laps record is greater than or equal to 60 . the number of such rows is 4 .'} | eq { count { filter_greater_eq { all_rows ; laps ; 60 } } ; 4 } = true | select the rows whose laps record is greater than or equal to 60 . the number of such rows is 4 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_greater_eq_0': 0, 'all_rows_4': 4, 'laps_5': 5, '60_6': 6, '4_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_greater_eq_0': 'filter_greater_eq', 'all_rows_4': 'all_rows', 'laps_5': 'laps', '60_6': '60', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_greater_eq_0': [1], 'all_rows_4': [0], 'laps_5': [0], '60_6': [0], '4_7': [2]} | ['driver', 'constructor', 'laps', 'time / retired', 'grid'] | [['stirling moss', 'cooper - climax', '62', '2:11:55.41', '1'], ['masten gregory', 'cooper - climax', '61', '+ 1 lap', '3'], ['dan gurney', 'ferrari', '61', '+ 1 lap', '6'], ['maurice trintignant', 'cooper - climax', '60', '+ 2 laps', '4'], ['harry schell', 'brm', '59', '+ 3 laps', '9'], ['roy salvadori', 'aston martin', '59', '+ 3 laps', '12'], ['ron flockhart', 'brm', '59', '+ 3 laps', '11'], ['carroll shelby', 'aston martin', '58', '+ 4 laps', '13'], ['tony brooks', 'ferrari', '57', '+ 5 laps', '10'], ['mário de araújo cabral', 'cooper - maserati', '56', '+ 6 laps', '14'], ['bruce mclaren', 'cooper - climax', '38', 'transmission', '8'], ['jack brabham', 'cooper - climax', '23', 'transmission', '2'], ['jo bonnier', 'brm', '10', 'engine', '5'], ['phil hill', 'ferrari', '5', 'accident', '7'], ['graham hill', 'lotus - climax', '5', 'accident', '15'], ['innes ireland', 'lotus - climax', '3', 'gearbox', '16']] |
1969 cleveland browns season | https://en.wikipedia.org/wiki/1969_Cleveland_Browns_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10652161-2.html.csv | superlative | the august 30 , 1969 game vs the packers was the only one with over 80000 people in the stands . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '4', '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', 'attendance'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; attendance }'}, 'opponent'], 'result': 'green bay packers', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; attendance } ; opponent }'}, 'green bay packers'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; attendance } ; opponent } ; green bay packers } = true', 'tointer': 'select the row whose attendance record of all rows is maximum . the opponent record of this row is green bay packers .'} | eq { hop { argmax { all_rows ; attendance } ; opponent } ; green bay packers } = true | select the row whose attendance record of all rows is maximum . the opponent record of this row is green bay packers . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'attendance_5': 5, 'opponent_6': 6, 'green bay packers_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'attendance_5': 'attendance', 'opponent_6': 'opponent', 'green bay packers_7': 'green bay packers'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'attendance_5': [0], 'opponent_6': [1], 'green bay packers_7': [2]} | ['week', 'date', 'opponent', 'result', 'attendance'] | [['1', 'august 10 , 1969', 'san francisco 49ers at seattle', 'w 24 - 19', '32219'], ['2', 'august 16 , 1969', 'los angeles rams', 'w 10 - 3', '54937'], ['3', 'august 23 , 1969', 'san diego chargers', 't 19 - 19', '36005'], ['4', 'august 30 , 1969', 'green bay packers', 'l 27 - 17', '85532'], ['5', 'september 6 , 1969', 'washington redskins', 'w 20 - 10', '45994'], ['6', 'september 13 , 1969', 'minnesota vikings at akron', 'l 23 - 16', '28561']] |
1959 - 60 segunda división | https://en.wikipedia.org/wiki/1959%E2%80%9360_Segunda_Divisi%C3%B3n | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17710217-2.html.csv | unique | rc celta de vigo was the only club to have 18 wins in the 1959 - 60 segunda división . | {'scope': 'all', 'row': '2', 'col': '5', 'col_other': '2', '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 }'}, 'club'], 'result': 'rc celta de vigo', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; wins ; 18 } ; club }'}, 'rc celta de vigo'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; wins ; 18 } ; club } ; rc celta de vigo }', 'tointer': 'the club record of this unqiue row is rc celta de vigo .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; wins ; 18 } } ; eq { hop { filter_eq { all_rows ; wins ; 18 } ; club } ; rc celta de vigo } } = true', 'tointer': 'select the rows whose wins record is equal to 18 . there is only one such row in the table . the club record of this unqiue row is rc celta de vigo .'} | and { only { filter_eq { all_rows ; wins ; 18 } } ; eq { hop { filter_eq { all_rows ; wins ; 18 } ; club } ; rc celta de vigo } } = true | select the rows whose wins record is equal to 18 . there is only one such row in the table . the club record of this unqiue row is rc celta de vigo . | 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, 'club_9': 9, 'rc celta de vigo_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', 'club_9': 'club', 'rc celta de vigo_10': 'rc celta de vigo'} | {'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], 'club_9': [2], 'rc celta de vigo_10': [3]} | ['position', 'club', 'played', 'points', 'wins', 'draws', 'losses', 'goals for', 'goals against', 'goal difference'] | [['1', 'real santander', '30', '42', '17', '8', '5', '63', '28', '+ 35'], ['2', 'rc celta de vigo', '30', '40', '18', '4', '8', '63', '37', '+ 26'], ['3', 'cd orense', '30', '37', '15', '7', '8', '56', '41', '+ 15'], ['4', 'deportivo la coruña', '30', '35', '16', '3', '11', '56', '47', '+ 9'], ['5', 'real gijón', '30', '32', '14', '4', '12', '56', '44', '+ 12'], ['6', 'cd tarrasa', '30', '31', '12', '7', '11', '47', '44', '+ 3'], ['7', 'cd sabadell cf', '30', '31', '13', '5', '12', '52', '41', '+ 11'], ['8', 'sd indautxu', '30', '29', '13', '3', '14', '56', '54', '+ 2'], ['9', 'baracaldo ah', '30', '29', '11', '7', '12', '53', '51', '+ 2'], ['10', 'cd condal', '30', '29', '11', '7', '12', '46', '45', '+ 1'], ['11', 'cd basconia', '30', '27', '11', '5', '14', '41', '57', '- 16'], ['12', 'cultural leonesa', '30', '27', '10', '7', '13', '47', '61', '- 14'], ['13', 'deportivo alavés', '30', '24', '8', '8', '14', '44', '70', '- 26'], ['14', 'club sestao', '30', '24', '9', '6', '15', '30', '47', '- 17'], ['15', 'real avilés cf', '30', '22', '6', '10', '14', '38', '52', '- 14'], ['16', 'club ferrol', '30', '21', '9', '3', '18', '50', '79', '- 29']] |
oliver marach | https://en.wikipedia.org/wiki/Oliver_Marach | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15271684-5.html.csv | comparative | oliver marach made it to the quarter final of the australian open in 2011 as compared to 2016 where he exited in the first round . | {'row_1': '2', 'row_2': '2', 'col': '15', 'col_other': '1', 'relation': 'equal', 'record_mentioned': 'yes', 'diff_result': None} | {'func': 'and', 'args': [{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'tournament', 'australian open'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose tournament record fuzzily matches to australian open .', 'tostr': 'filter_eq { all_rows ; tournament ; australian open }'}, '2011'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; tournament ; australian open } ; 2011 }', 'tointer': 'select the rows whose tournament record fuzzily matches to australian open . take the 2011 record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'tournament', 'australian open'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose tournament record fuzzily matches to australian open .', 'tostr': 'filter_eq { all_rows ; tournament ; australian open }'}, '2011'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; tournament ; australian open } ; 2011 }', 'tointer': 'select the rows whose tournament record fuzzily matches to australian open . take the 2011 record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'eq { hop { filter_eq { all_rows ; tournament ; australian open } ; 2011 } ; hop { filter_eq { all_rows ; tournament ; australian open } ; 2011 } }', 'tointer': 'select the rows whose tournament record fuzzily matches to australian open . take the 2011 record of this row . select the rows whose tournament record fuzzily matches to australian open . take the 2011 record of this row . the first record fuzzily matches to the second record .'}, {'func': 'and', 'args': [{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'tournament', 'australian open'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose tournament record fuzzily matches to australian open .', 'tostr': 'filter_eq { all_rows ; tournament ; australian open }'}, '2011'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; tournament ; australian open } ; 2011 }', 'tointer': 'select the rows whose tournament record fuzzily matches to australian open . take the 2011 record of this row .'}, 'qf'], 'result': True, 'ind': 5, 'tostr': 'eq { hop { filter_eq { all_rows ; tournament ; australian open } ; 2011 } ; qf }', 'tointer': 'the 2011 record of the first row is qf .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'tournament', 'australian open'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose tournament record fuzzily matches to australian open .', 'tostr': 'filter_eq { all_rows ; tournament ; australian open }'}, '2011'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; tournament ; australian open } ; 2011 }', 'tointer': 'select the rows whose tournament record fuzzily matches to australian open . take the 2011 record of this row .'}, 'qf'], 'result': True, 'ind': 6, 'tostr': 'eq { hop { filter_eq { all_rows ; tournament ; australian open } ; 2011 } ; qf }', 'tointer': 'the 2011 record of the second row is qf .'}], 'result': True, 'ind': 7, 'tostr': 'and { eq { hop { filter_eq { all_rows ; tournament ; australian open } ; 2011 } ; qf } ; eq { hop { filter_eq { all_rows ; tournament ; australian open } ; 2011 } ; qf } }', 'tointer': 'the 2011 record of the first row is qf . the 2011 record of the second row is qf .'}], 'result': True, 'ind': 8, 'tostr': 'and { eq { hop { filter_eq { all_rows ; tournament ; australian open } ; 2011 } ; hop { filter_eq { all_rows ; tournament ; australian open } ; 2011 } } ; and { eq { hop { filter_eq { all_rows ; tournament ; australian open } ; 2011 } ; qf } ; eq { hop { filter_eq { all_rows ; tournament ; australian open } ; 2011 } ; qf } } } = true', 'tointer': 'select the rows whose tournament record fuzzily matches to australian open . take the 2011 record of this row . select the rows whose tournament record fuzzily matches to australian open . take the 2011 record of this row . the first record fuzzily matches to the second record . the 2011 record of the first row is qf . the 2011 record of the second row is qf .'} | and { eq { hop { filter_eq { all_rows ; tournament ; australian open } ; 2011 } ; hop { filter_eq { all_rows ; tournament ; australian open } ; 2011 } } ; and { eq { hop { filter_eq { all_rows ; tournament ; australian open } ; 2011 } ; qf } ; eq { hop { filter_eq { all_rows ; tournament ; australian open } ; 2011 } ; qf } } } = true | select the rows whose tournament record fuzzily matches to australian open . take the 2011 record of this row . select the rows whose tournament record fuzzily matches to australian open . take the 2011 record of this row . the first record fuzzily matches to the second record . the 2011 record of the first row is qf . the 2011 record of the second row is qf . | 13 | 9 | {'and_8': 8, 'result_9': 9, 'str_eq_4': 4, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_10': 10, 'tournament_11': 11, 'australian open_12': 12, '2011_13': 13, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_14': 14, 'tournament_15': 15, 'australian open_16': 16, '2011_17': 17, 'and_7': 7, 'str_eq_5': 5, 'qf_18': 18, 'str_eq_6': 6, 'qf_19': 19} | {'and_8': 'and', 'result_9': 'true', 'str_eq_4': 'str_eq', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_10': 'all_rows', 'tournament_11': 'tournament', 'australian open_12': 'australian open', '2011_13': '2011', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_14': 'all_rows', 'tournament_15': 'tournament', 'australian open_16': 'australian open', '2011_17': '2011', 'and_7': 'and', 'str_eq_5': 'str_eq', 'qf_18': 'qf', 'str_eq_6': 'str_eq', 'qf_19': 'qf'} | {'and_8': [9], 'result_9': [], 'str_eq_4': [8], 'str_hop_2': [4, 5], 'filter_str_eq_0': [2], 'all_rows_10': [0], 'tournament_11': [0], 'australian open_12': [0], '2011_13': [2], 'str_hop_3': [4, 6], 'filter_str_eq_1': [3], 'all_rows_14': [1], 'tournament_15': [1], 'australian open_16': [1], '2011_17': [3], 'and_7': [8], 'str_eq_5': [7], 'qf_18': [5], 'str_eq_6': [7], 'qf_19': [6]} | ['tournament', '1998', '1999', '2000', '2001', '2002', '2003', '2004', '2005', '2006', '2007', '2008', '2009', '2010', '2011'] | [['grand slams', 'grand slams', 'grand slams', 'grand slams', 'grand slams', 'grand slams', 'grand slams', 'grand slams', 'grand slams', 'grand slams', 'grand slams', 'grand slams', 'grand slams', 'grand slams', 'grand slams'], ['australian open', 'a', 'a', 'a', 'a', 'a', 'a', 'a', 'a', '1r', '3r', '1r', 'sf', '3r', 'qf'], ['french open', 'a', 'a', 'a', 'a', 'a', 'a', 'a', 'a', '2r', '3r', 'a', '2r', 'qf', '1r'], ['wimbledon', 'a', 'a', 'a', 'a', 'a', 'a', 'a', 'a', '2r', 'a', '1r', 'qf', '1r', 'a'], ['us open', 'a', 'a', 'a', 'a', 'a', 'a', 'a', 'a', '1r', 'a', 'a', '1r', 'qf', 'a'], ['win - loss', '0 - 0', '0 - 0', '0 - 0', '0 - 0', '0 - 0', '0 - 0', '0 - 0', '0 - 0', '2 - 4', '4 - 2', '0 - 2', '8 - 4', '8 - 4', '3 - 2'], ['atp masters series', 'atp masters series', 'atp masters series', 'atp masters series', 'atp masters series', 'atp masters series', 'atp masters series', 'atp masters series', 'atp masters series', 'atp masters series', 'atp masters series', 'atp masters series', 'atp masters series', 'atp masters series', 'atp masters series'], ['indian wells', 'a', 'a', 'a', 'a', 'a', 'a', 'a', 'a', 'a', 'a', 'a', '2r', 'a', '2r'], ['miami', 'a', 'a', 'a', 'a', 'a', 'a', 'a', 'a', 'a', 'a', 'a', 'a', '1r', 'sf'], ['monte carlo', 'a', 'a', 'a', 'a', 'a', 'a', 'a', 'a', 'a', 'a', 'a', '2r', 'qf', 'qf'], ['rome', 'a', 'a', 'a', 'a', 'a', 'a', 'a', 'a', 'a', 'a', 'a', 'a', 'sf', 'qf'], ['madrid', 'a', 'a', 'a', 'a', 'a', 'a', 'a', 'a', 'a', 'a', 'a', 'a', 'qf', '2r'], ['canada', 'a', 'a', 'a', 'a', 'a', 'a', 'a', 'a', 'a', 'a', 'a', 'qf', '2r', 'a'], ['cincinnati', 'a', 'a', 'a', 'a', 'a', 'a', 'a', 'a', 'a', 'a', 'a', 'sf', 'sf', '1r'], ['shanghai', 'not held', 'not held', 'not held', 'not held', 'not held', 'not held', 'not held', 'not held', 'not held', 'not held', 'not held', 'qf', 'sf', '2r'], ['paris', 'a', 'a', 'a', 'a', 'a', 'a', 'a', 'a', 'a', 'a', 'a', '1r', 'qf', 'qf'], ['hamburg', 'a', 'a', 'a', 'a', 'a', 'a', 'a', 'a', 'a', 'a', 'a', 'nm1', 'nm1', 'nm1'], ['win - loss', '0 - 0', '0 - 0', '0 - 0', '0 - 0', '0 - 0', '0 - 0', '0 - 0', '0 - 0', '0 - 0', '0 - 0', '0 - 0', '5 - 6', '9 - 8', '8 - 8'], ['year end ranking', '793', '828', '264', '233', '169', '463', '213', '153', '40', '48', '69', '13', '11', '17']] |
chet miller | https://en.wikipedia.org/wiki/Chet_Miller | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1252058-1.html.csv | superlative | the highest start for chet miller was 3rd in 1936 . | {'scope': 'all', 'col_superlative': '2', 'row_superlative': '7', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '1', 'subset': None} | {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'argmin', 'args': ['all_rows', 'start'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; start }'}, 'year'], 'result': '1936', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; start } ; year }'}, '1936'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmin { all_rows ; start } ; year } ; 1936 } = true', 'tointer': 'select the row whose start record of all rows is minimum . the year record of this row is 1936 .'} | eq { hop { argmin { all_rows ; start } ; year } ; 1936 } = true | select the row whose start record of all rows is minimum . the year record of this row is 1936 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'num_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'start_5': 5, 'year_6': 6, '1936_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'num_hop_1': 'num_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'start_5': 'start', 'year_6': 'year', '1936_7': '1936'} | {'eq_2': [3], 'result_3': [], 'num_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'start_5': [0], 'year_6': [1], '1936_7': [2]} | ['year', 'start', 'qual', 'rank', 'finish', 'laps'] | [['1930', '15', '97.360', '23', '13', '161'], ['1931', '15', '106.185', '25', '10', '200'], ['1932', '29', '111.053', '23', '21', '125'], ['1933', '32', '112.025', '23', '20', '163'], ['1934', '32', '109.252', '29', '33', '11'], ['1935', '17', '113.552', '24', '10', '200'], ['1936', '3', '117.675', '3', '5', '200'], ['1937', '13', '119.213', '13', '30', '36'], ['1938', '5', '121.898', '9', '3', '200'], ['1939', '5', '126.318', '8', '21', '109'], ['1940', '27', '121.392', '27', '17', '189'], ['1941', '9', '121.540', '23', '6', '200'], ['1946', '17', '124.649', '8', '18', '64'], ['1948', '19', '127.249', '8', '20', '108'], ['1951', '28', '135.798', '3', '25', '56'], ['1952', '27', '139.034', '1', '30', '41']] |
lee gibson | https://en.wikipedia.org/wiki/Lee_Gibson | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17624963-2.html.csv | majority | the majority of results for lee gibson 's fights were wins for lee gibson . | {'scope': 'all', 'col': '1', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'win', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'res', 'win'], 'result': True, 'ind': 0, 'tointer': 'for the res records of all rows , most of them fuzzily match to win .', 'tostr': 'most_eq { all_rows ; res ; win } = true'} | most_eq { all_rows ; res ; win } = true | for the res records of all rows , most of them fuzzily match to win . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'res_3': 3, 'win_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'res_3': 'res', 'win_4': 'win'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'res_3': [0], 'win_4': [0]} | ['res', 'record', 'opponent', 'method', 'event', 'round', 'location'] | [['win', '12 - 3', 'joe wilk', 'tko ( strikes )', 'strikeforce challengers : woodley vs bears', '1', 'kansas , united states'], ['loss', '11 - 3', 'muhsin corbbrey', 'decision ( unanimous )', 'shoxcjuly_27 .2 c_2007_card', '3', 'california , united states'], ['win', '11 - 2', 'talon hoffman', 'tko', 'ifo - eastman vs kimmons', '2', 'nevada , united states'], ['win', '10 - 2', 'kyle olsen', 'decision ( unanimous )', 'tuff - n - uff 2', '3', 'nevada , united states'], ['win', '9 - 2', 'tj brown', 'decision ( unanimous )', 'tuff - n - uff 2', '3', 'nevada , united states'], ['win', '8 - 2', 'frank young', 'submission', 'tfc 7 - red rumble', '1', 'kansas , united states'], ['loss', '7 - 2', 'luke gwaltney', 'decision ( unanimous )', 'ggp - good guys promotions', '3', 'kansas , united states'], ['win', '7 - 1', 'billy walters', 'tko', 'tfc 6 - titan fighting championships 6', '1', 'kansas , united states'], ['win', '6 - 1', 'mike funk', 'submission ( strikes )', 'fcf - freestyle cage fighting', '1', 'oklahoma , united states'], ['loss', '5 - 1', 'justin james', 'submission ( armbar )', 'ec 70 - extreme challenge 70', '1', 'wisconsin , united states'], ['win', '5 - 0', 'robert hembree', 'submission ( strikes )', 'tfc 5 - titan fighting championship 5', '1', 'kansas , united states'], ['win', '4 - 0', 'joe davis', 'tko', 'tfc 4 - memorial mayhem', '1', 'kansas , united states'], ['win', '3 - 0', 'nathan murdock', 'decision ( unanimous )', 'tfc 3 - red river rumble', '3', 'oklahoma , united states'], ['win', '2 - 0', 'adrian olivas', 'ko', 'ndn - promotions', '2', 'oklahoma , united states'], ['win', '1 - 0', 'bobby gregg', 'tko', 'iscf - clash of the titans', '1', 'missouri , united states']] |
statistics relating to enlargement of the european union | https://en.wikipedia.org/wiki/Statistics_relating_to_enlargement_of_the_European_Union | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1307842-2.html.csv | ordinal | denmark has the highest population among the countries with area ( km square ) less than 100000 in statistics relating to enlargement of the european union . | {'scope': 'subset', 'row': '1', 'col': '2', 'order': '1', 'col_other': '1', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'subset': {'col': '3', 'criterion': 'less_than', 'value': '100000'}} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'area ( km square )', '100000'], 'result': None, 'ind': 0, 'tostr': 'filter_less { all_rows ; area ( km square ) ; 100000 }', 'tointer': 'select the rows whose area ( km square ) record is less than 100000 .'}, 'population', '1'], 'result': None, 'ind': 1, 'tostr': 'nth_argmax { filter_less { all_rows ; area ( km square ) ; 100000 } ; population ; 1 }'}, 'member countries'], 'result': 'denmark', 'ind': 2, 'tostr': 'hop { nth_argmax { filter_less { all_rows ; area ( km square ) ; 100000 } ; population ; 1 } ; member countries }'}, 'denmark'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { nth_argmax { filter_less { all_rows ; area ( km square ) ; 100000 } ; population ; 1 } ; member countries } ; denmark } = true', 'tointer': 'select the rows whose area ( km square ) record is less than 100000 . select the row whose population record of these rows is 1st maximum . the member countries record of this row is denmark .'} | eq { hop { nth_argmax { filter_less { all_rows ; area ( km square ) ; 100000 } ; population ; 1 } ; member countries } ; denmark } = true | select the rows whose area ( km square ) record is less than 100000 . select the row whose population record of these rows is 1st maximum . the member countries record of this row is denmark . | 4 | 4 | {'str_eq_3': 3, 'result_4': 4, 'str_hop_2': 2, 'nth_argmax_1': 1, 'filter_less_0': 0, 'all_rows_5': 5, 'area (km square)_6': 6, '100000_7': 7, 'population_8': 8, '1_9': 9, 'member countries_10': 10, 'denmark_11': 11} | {'str_eq_3': 'str_eq', 'result_4': 'true', 'str_hop_2': 'str_hop', 'nth_argmax_1': 'nth_argmax', 'filter_less_0': 'filter_less', 'all_rows_5': 'all_rows', 'area (km square)_6': 'area ( km square )', '100000_7': '100000', 'population_8': 'population', '1_9': '1', 'member countries_10': 'member countries', 'denmark_11': 'denmark'} | {'str_eq_3': [4], 'result_4': [], 'str_hop_2': [3], 'nth_argmax_1': [2], 'filter_less_0': [1], 'all_rows_5': [0], 'area (km square)_6': [0], '100000_7': [0], 'population_8': [1], '1_9': [1], 'member countries_10': [2], 'denmark_11': [3]} | ['member countries', 'population', 'area ( km square )', 'gdp ( billion us )', 'gdp per capita ( us )'] | [['denmark', '5021861', '43094', '70.032', '59928'], ['ireland', '3073200', '70273', '21.103', '39638'], ['united kingdom', '56210000', '244820', '675.941', '36728'], ['accession countries', '64305061', '358187', '767.076', '11929'], ['existing members ( 1973 )', '192457106', '1299536', '2381396', '12374'], ['ec9 ( 1973 )', '256762167 ( + 33.41 % )', '1657723 ( + 25.44 % )', '3148.472 ( + 32.21 % )', '12262 ( 0.91 % )']] |
1962 baltimore colts season | https://en.wikipedia.org/wiki/1962_Baltimore_Colts_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14984078-1.html.csv | unique | the game on october 21 , 1962 was the only game played at wrigley field by the baltimore colts . | {'scope': 'all', 'row': '6', 'col': '6', 'col_other': '2', 'criterion': 'equal', 'value': 'wrigley field', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'game site', 'wrigley field'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose game site record fuzzily matches to wrigley field .', 'tostr': 'filter_eq { all_rows ; game site ; wrigley field }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; game site ; wrigley field } }', 'tointer': 'select the rows whose game site record fuzzily matches to wrigley field . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'game site', 'wrigley field'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose game site record fuzzily matches to wrigley field .', 'tostr': 'filter_eq { all_rows ; game site ; wrigley field }'}, 'date'], 'result': 'october 21 , 1962', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; game site ; wrigley field } ; date }'}, 'october 21 , 1962'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; game site ; wrigley field } ; date } ; october 21 , 1962 }', 'tointer': 'the date record of this unqiue row is october 21 , 1962 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; game site ; wrigley field } } ; eq { hop { filter_eq { all_rows ; game site ; wrigley field } ; date } ; october 21 , 1962 } } = true', 'tointer': 'select the rows whose game site record fuzzily matches to wrigley field . there is only one such row in the table . the date record of this unqiue row is october 21 , 1962 .'} | and { only { filter_eq { all_rows ; game site ; wrigley field } } ; eq { hop { filter_eq { all_rows ; game site ; wrigley field } ; date } ; october 21 , 1962 } } = true | select the rows whose game site record fuzzily matches to wrigley field . there is only one such row in the table . the date record of this unqiue row is october 21 , 1962 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'game site_7': 7, 'wrigley field_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'date_9': 9, 'october 21 , 1962_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'game site_7': 'game site', 'wrigley field_8': 'wrigley field', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'date_9': 'date', 'october 21 , 1962_10': 'october 21 , 1962'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'game site_7': [0], 'wrigley field_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'date_9': [2], 'october 21 , 1962_10': [3]} | ['week', 'date', 'opponent', 'result', 'record', 'game site', 'attendance'] | [['1', 'september 16 , 1962', 'los angeles rams', 'w 30 - 27', '1 - 0', 'memorial stadium', '54796'], ['2', 'september 23 , 1962', 'minnesota vikings', 'w 34 - 7', '2 - 0', 'metropolitan stadium', '30787'], ['3', 'september 30 , 1962', 'detroit lions', 'l 20 - 29', '2 - 1', 'memorial stadium', '57966'], ['4', 'october 7 , 1962', 'san francisco 49ers', 'l 13 - 21', '2 - 2', 'memorial stadium', '54158'], ['5', 'october 14 , 1962', 'cleveland browns', 'w 36 - 14', '3 - 2', 'cleveland municipal stadium', '80132'], ['6', 'october 21 , 1962', 'chicago bears', 'l 15 - 35', '3 - 3', 'wrigley field', '49066'], ['7', 'october 28 , 1962', 'green bay packers', 'l 6 - 17', '3 - 4', 'memorial stadium', '57966'], ['8', 'november 4 , 1962', 'san francisco 49ers', 'w 22 - 3', '4 - 4', 'kezar stadium', '44875'], ['9', 'november 11 , 1962', 'los angeles rams', 'w 14 - 2', '5 - 4', 'los angeles memorial coliseum', '39502'], ['10', 'november 18 , 1962', 'green bay packers', 'l 13 - 17', '5 - 5', 'lambeau field', '38669'], ['11', 'november 25 , 1962', 'chicago bears', 'l 0 - 57', '5 - 6', 'memorial stadium', '56164'], ['12', 'december 2 , 1962', 'detroit lions', 'l 14 - 21', '5 - 7', 'tiger stadium', '53012'], ['13', 'december 8 , 1962', 'washington redskins', 'w 34 - 21', '6 - 7', 'memorial stadium', '56964'], ['14', 'december 16 , 1962', 'minnesota vikings', 'w 42 - 17', '7 - 7', 'memorial stadium', '53645']] |
2008 - 09 boston celtics season | https://en.wikipedia.org/wiki/2008%E2%80%9309_Boston_Celtics_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17140608-10.html.csv | count | paul pierce won a total of 5 high points in the 2008-09 boston celtics season . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'paul pierce', 'result': '5', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'high points', 'paul pierce'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose high points record fuzzily matches to paul pierce .', 'tostr': 'filter_eq { all_rows ; high points ; paul pierce }'}], 'result': '5', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; high points ; paul pierce } }', 'tointer': 'select the rows whose high points record fuzzily matches to paul pierce . the number of such rows is 5 .'}, '5'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; high points ; paul pierce } } ; 5 } = true', 'tointer': 'select the rows whose high points record fuzzily matches to paul pierce . the number of such rows is 5 .'} | eq { count { filter_eq { all_rows ; high points ; paul pierce } } ; 5 } = true | select the rows whose high points record fuzzily matches to paul pierce . 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, 'high points_5': 5, 'paul pierce_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', 'high points_5': 'high points', 'paul pierce_6': 'paul pierce', '5_7': '5'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'high points_5': [0], 'paul pierce_6': [0], '5_7': [2]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record'] | [['76', 'april 1', 'charlotte', 'w 111 - 109 ( 2ot )', 'paul pierce ( 32 )', 'kendrick perkins ( 12 )', 'rajon rondo ( 9 )', 'td banknorth garden 18624', '57 - 19'], ['77', 'april 3', 'atlanta', 'w 104 - 92 ( ot )', 'paul pierce ( 21 )', 'kendrick perkins ( 10 )', 'rajon rondo ( 6 )', 'td banknorth garden 18624', '58 - 19'], ['78', 'april 8', 'new jersey', 'w 106 - 104 ( ot )', 'rajon rondo ( 31 )', 'rajon rondo , kendrick perkins , mikki moore ( 9 )', 'rajon rondo , stephon marbury ( 5 )', 'td banknorth garden 18624', '59 - 19'], ['79', 'april 10', 'miami', 'w 105 - 98 ( ot )', 'paul pierce ( 28 )', 'rajon rondo ( 10 )', 'rajon rondo ( 12 )', 'td banknorth garden 18624', '60 - 19'], ['80', 'april 12', 'cleveland', 'l 76 - 107 ( ot )', 'paul pierce ( 14 )', 'kendrick perkins ( 6 )', 'rajon rondo ( 6 )', 'quicken loans arena 20562', '60 - 20'], ['81', 'april 14', 'philadelphia', 'w 100 - 98 ( ot )', 'paul pierce ( 31 )', 'kendrick perkins ( 12 )', 'tony allen , stephon marbury ( 5 )', 'wachovia center 17752', '61 - 20'], ['82', 'april 15', 'washington', 'w 115 - 107 ( ot )', 'glen davis ( 21 )', 'leon powe ( 13 )', 'stephon marbury ( 8 )', 'td banknorth garden 18624', '62 - 20']] |
2007 - 08 boston celtics season | https://en.wikipedia.org/wiki/2007%E2%80%9308_Boston_Celtics_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11959669-5.html.csv | aggregation | gannet scored 65 high rebounds in the 6 january games he was credited with high rebounds . | {'scope': 'subset', 'col': '6', 'type': 'sum', 'result': '65', 'subset': {'col': '6', 'criterion': 'fuzzily_match', 'value': 'garnett'}} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'high rebounds', 'garnett'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; high rebounds ; garnett }', 'tointer': 'select the rows whose high rebounds record fuzzily matches to garnett .'}, 'high rebounds'], 'result': '65', 'ind': 1, 'tostr': 'sum { filter_eq { all_rows ; high rebounds ; garnett } ; high rebounds }'}, '65'], 'result': True, 'ind': 2, 'tostr': 'round_eq { sum { filter_eq { all_rows ; high rebounds ; garnett } ; high rebounds } ; 65 } = true', 'tointer': 'select the rows whose high rebounds record fuzzily matches to garnett . the sum of the high rebounds record of these rows is 65 .'} | round_eq { sum { filter_eq { all_rows ; high rebounds ; garnett } ; high rebounds } ; 65 } = true | select the rows whose high rebounds record fuzzily matches to garnett . the sum of the high rebounds record of these rows is 65 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'sum_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'high rebounds_5': 5, 'garnett_6': 6, 'high rebounds_7': 7, '65_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'sum_1': 'sum', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'high rebounds_5': 'high rebounds', 'garnett_6': 'garnett', 'high rebounds_7': 'high rebounds', '65_8': '65'} | {'eq_2': [3], 'result_3': [], 'sum_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'high rebounds_5': [0], 'garnett_6': [0], 'high rebounds_7': [1], '65_8': [2]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record'] | [['30', 'january 2', 'houston', '97 - 93', 'garnett ( 26 )', 'garnett ( 9 )', 'rondo ( 9 )', 'td banknorth garden 18624', '27 - 3'], ['31', 'january 4', 'memphis', '100 - 96', 'garnett , pierce ( 23 )', 'pierce , posey ( 10 )', 'allen , garnett , pierce ( 5 )', 'td banknorth garden 18624', '28 - 3'], ['32', 'january 5', 'detroit', '92 - 85', 'davis ( 20 )', 'perkins , pierce ( 9 )', 'pierce ( 7 )', 'the palace of auburn hills 22076', '29 - 3'], ['33', 'january 9', 'charlotte', '83 - 95', 'garnett ( 24 )', 'perkins ( 10 )', 'garnett , posey ( 4 )', 'td banknorth garden 18624', '29 - 4'], ['34', 'january 11', 'new jersey', '86 - 77', 'garnett ( 20 )', 'garnett ( 11 )', 'pierce ( 5 )', 'izod center 20049', '30 - 4'], ['35', 'january 12', 'washington', '78 - 85', 'garnett ( 19 )', 'perkins ( 7 )', 'pierce ( 6 )', 'verizon center 20173', '30 - 5'], ['36', 'january 14', 'washington', '83 - 88', 'garnett ( 23 )', 'garnett ( 9 )', 'garnett ( 6 )', 'td banknorth garden 18624', '30 - 6'], ['37', 'january 16', 'portland', '100 - 90', 'allen ( 35 )', 'pierce ( 8 )', 'house , pierce ( 5 )', 'td banknorth garden 18624', '31 - 6'], ['38', 'january 18', 'philadelphia', '116 - 89', 'allen ( 23 )', 'perkins ( 7 )', 'garnett ( 8 )', 'td banknorth garden 18624', '32 - 6'], ['39', 'january 21', 'new york', '109 - 93', 'perkins ( 24 )', 'garnett ( 13 )', 'garnett , pierce ( 7 )', 'madison square garden 19763', '33 - 6'], ['40', 'january 23', 'toronto', '112 - 114', 'garnett ( 26 )', 'garnett ( 7 )', 'pierce ( 9 )', 'td banknorth garden 18624', '33 - 7'], ['41', 'january 25', 'minnesota', '87 - 86', 'perkins ( 21 )', 'garnett ( 16 )', 'pierce ( 8 )', 'td banknorth garden 18624', '34 - 7'], ['42', 'january 27', 'orlando', '93 - 96', 'pierce ( 24 )', 'pierce , powe ( 9 )', 'rondo ( 5 )', 'amway arena 17519', '34 - 8'], ['43', 'january 29', 'miami', '117 - 87', 'powe ( 25 )', 'powe ( 11 )', 'allen ( 6 )', 'american airlines arena 19600', '35 - 8'], ['44', 'january 31', 'dallas', '96 - 90', 'allen , pierce ( 26 )', 'rondo ( 12 )', 'rondo ( 4 )', 'td banknorth garden 18624', '36 - 8']] |
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/1-25740548-2.html.csv | superlative | out of the episodes that aired in august , the one with the least viewers had 5.17 million . | {'scope': 'subset', 'col_superlative': '7', 'row_superlative': '5', 'value_mentioned': 'yes', 'max_or_min': 'min', 'other_col': '5', 'subset': {'col': '5', 'criterion': 'fuzzily_match', 'value': 'august'}} | {'func': 'eq', 'args': [{'func': 'min', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'original air date', 'august'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; original air date ; august }', 'tointer': 'select the rows whose original air date record fuzzily matches to august .'}, 'us viewers ( million )'], 'result': '5.17', 'ind': 1, 'tostr': 'min { filter_eq { all_rows ; original air date ; august } ; us viewers ( million ) }', 'tointer': 'select the rows whose original air date record fuzzily matches to august . the minimum us viewers ( million ) record of these rows is 5.17 .'}, '5.17'], 'result': True, 'ind': 2, 'tostr': 'eq { min { filter_eq { all_rows ; original air date ; august } ; us viewers ( million ) } ; 5.17 } = true', 'tointer': 'select the rows whose original air date record fuzzily matches to august . the minimum us viewers ( million ) record of these rows is 5.17 .'} | eq { min { filter_eq { all_rows ; original air date ; august } ; us viewers ( million ) } ; 5.17 } = true | select the rows whose original air date record fuzzily matches to august . the minimum us viewers ( million ) record of these rows is 5.17 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'min_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'original air date_5': 5, 'august_6': 6, 'us viewers (million)_7': 7, '5.17_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'min_1': 'min', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'original air date_5': 'original air date', 'august_6': 'august', 'us viewers (million)_7': 'us viewers ( million )', '5.17_8': '5.17'} | {'eq_2': [3], 'result_3': [], 'min_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'original air date_5': [0], 'august_6': [0], 'us viewers (million)_7': [1], '5.17_8': [2]} | ['series', 'title', 'directed by', 'written by', 'original air date', 'production code', 'us viewers ( million )'] | [['1', 'pilot welcome to the cia', 'tim matheson', 'matt corman & chris ord', 'july 13 , 2010', 'ca101', '4.88'], ['2', "walter 's walk", 'félix alcalá', 'matt corman & chris ord', 'july 20 , 2010', 'ca102', '5.21'], ['3', 'south bound suarez', 'john kretchmer', 'james parriott', 'july 27 , 2010', 'ca103', '4.83'], ['4', 'no quarter', 'allan kroeker', 'stephen hootstein', 'august 3 , 2010', 'ca104', '5.30'], ['5', 'in the light', 'jonathan glassner', 'meredith lavender & marcie ulin', 'august 10 , 2010', 'ca105', '5.17'], ['6', 'houses of the holy', 'alex chapple', 'dana calvo', 'august 17 , 2010', 'ca106', '5.36'], ['7', 'communication breakdown', 'kate woods', 'matthew lau', 'august 24 , 2010', 'ca107', '5.87'], ['8', 'what is and what should never be', 'rod hardy', 'brett conrad', 'august 31 , 2010', 'ca108', '5.26'], ['9', 'fool in the rain', 'vincent misiano', 'stephen hootstein', 'september 7 , 2010', 'ca109', '5.40'], ['10', "i ca n't quit you baby", 'ken girotti', 'james parriott', 'september 14 , 2010', 'ca110', '4.59']] |
1979 masters tournament | https://en.wikipedia.org/wiki/1979_Masters_Tournament | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16458346-2.html.csv | count | in the 1979 masters tournament two of the people from the united states scored -6 to par . | {'scope': 'subset', 'criterion': 'equal', 'value': '-6', 'result': '2', 'col': '5', 'subset': {'col': '3', 'criterion': 'equal', 'value': 'united states'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'united states'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; country ; united states }', 'tointer': 'select the rows whose country record fuzzily matches to united states .'}, 'to par', '-6'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose country record fuzzily matches to united states . among these rows , select the rows whose to par record is equal to -6 .', 'tostr': 'filter_eq { filter_eq { all_rows ; country ; united states } ; to par ; -6 }'}], 'result': '2', 'ind': 2, 'tostr': 'count { filter_eq { filter_eq { all_rows ; country ; united states } ; to par ; -6 } }', 'tointer': 'select the rows whose country record fuzzily matches to united states . among these rows , select the rows whose to par record is equal to -6 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_eq { filter_eq { all_rows ; country ; united states } ; to par ; -6 } } ; 2 } = true', 'tointer': 'select the rows whose country record fuzzily matches to united states . among these rows , select the rows whose to par record is equal to -6 . the number of such rows is 2 .'} | eq { count { filter_eq { filter_eq { all_rows ; country ; united states } ; to par ; -6 } } ; 2 } = true | select the rows whose country record fuzzily matches to united states . among these rows , select the rows whose to par record is equal to -6 . the number of such rows is 2 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_eq_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'country_6': 6, 'united states_7': 7, 'to par_8': 8, '-6_9': 9, '2_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_eq_1': 'filter_eq', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'country_6': 'country', 'united states_7': 'united states', 'to par_8': 'to par', '-6_9': '-6', '2_10': '2'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_eq_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'country_6': [0], 'united states_7': [0], 'to par_8': [1], '-6_9': [1], '2_10': [3]} | ['place', 'player', 'country', 'score', 'to par'] | [['t1', 'ed sneed', 'united states', '68 + 67 = 135', '- 9'], ['t1', 'craig stadler', 'united states', '69 + 66 = 135', '- 9'], ['t3', 'raymond floyd', 'united states', '70 + 68 = 138', '- 6'], ['t3', 'leonard thompson', 'united states', '68 + 70 = 138', '- 6'], ['t5', 'miller barber', 'united states', '75 + 64 = 139', '- 5'], ['t5', 'tom watson', 'united states', '68 + 71 = 139', '- 5'], ['t5', 'joe inman', 'united states', '68 + 71 = 139', '- 5'], ['t8', 'seve ballesteros', 'spain', '72 + 68 = 140', '- 4'], ['t8', 'jack nicklaus', 'united states', '69 + 71 = 140', '- 4'], ['t8', 'lou graham', 'united states', '69 + 71 = 140', '- 4']] |
wake forest demon deacons football , 1980 - 89 | https://en.wikipedia.org/wiki/Wake_Forest_Demon_Deacons_football%2C_1980%E2%80%9389 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15531181-15.html.csv | majority | most of the games resulted in wins for the wake forest demon deacons . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': 'w', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'result', 'w'], 'result': True, 'ind': 0, 'tointer': 'for the result records of all rows , most of them fuzzily match to w .', 'tostr': 'most_eq { all_rows ; result ; w } = true'} | most_eq { all_rows ; result ; w } = true | for the result records of all rows , most of them fuzzily match to w . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'result_3': 3, 'w_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'result_3': 'result', 'w_4': 'w'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'result_3': [0], 'w_4': [0]} | ['date', 'opponent', 'location', 'result', 'attendance'] | [['09 / 12 / 1987', 'richmond', 'groves stadium winston - salem , nc', 'w 24 - 0', '14250'], ['09 / 19 / 1987', 'north carolina state', 'groves stadium winston - salem , nc', 'w 21 - 3', '23600'], ['09 / 26 / 1987', 'appalachian state', 'groves stadium winston - salem , nc', 'w 16 - 12', '33400'], ['10 / 01 / 1987', 'army', 'michie stadium west point , ny', 'w 17 - 13', '36690'], ['10 / 10 / 1987', 'north carolina', 'kenan memorial stadium chapel hill , nc', 'w 22 - 14', '50000'], ['10 / 17 / 1987', 'maryland', 'groves stadium winston - salem , nc', 'l 0 - 14', '25175'], ['10 / 24 / 1987', 'virginia', 'scott stadium charlottesville , va', 'l 21 - 35', '32500'], ['10 / 31 / 1987', '14 clemson', 'memorial stadium clemson , sc', 'l 17 - 31', '69711'], ['11 / 07 / 1987', 'duke', 'groves stadium winston - salem , nc', 'w 30 - 27', '23500'], ['11 / 14 / 1987', '14 south carolina', 'groves stadium winston - salem , nc', 'l 0 - 30', '34720'], ['11 / 21 / 1987', 'georgia tech', 'grant field atlanta , ga', 'w 33 - 6', '21114']] |
kingco athletic conference | https://en.wikipedia.org/wiki/Kingco_Athletic_Conference | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-13759592-1.html.csv | majority | the majority of the high schools in the kingco athletic conference were founded after 1950 . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'greater_than', 'value': '1950', 'subset': None} | {'func': 'most_greater', 'args': ['all_rows', 'founded', '1950'], 'result': True, 'ind': 0, 'tointer': 'for the founded records of all rows , most of them are greater than 1950 .', 'tostr': 'most_greater { all_rows ; founded ; 1950 } = true'} | most_greater { all_rows ; founded ; 1950 } = true | for the founded records of all rows , most of them are greater than 1950 . | 1 | 1 | {'most_greater_0': 0, 'result_1': 1, 'all_rows_2': 2, 'founded_3': 3, '1950_4': 4} | {'most_greater_0': 'most_greater', 'result_1': 'true', 'all_rows_2': 'all_rows', 'founded_3': 'founded', '1950_4': '1950'} | {'most_greater_0': [1], 'result_1': [], 'all_rows_2': [0], 'founded_3': [0], '1950_4': [0]} | ['high school', 'location', 'founded', 'affiliation', 'enrollment', 'nickname', 'division'] | [['ballard', 'seattle', '1903', 'public ( seattle ps )', '1649', 's beaver', 'crown'], ['bothell', 'bothell', '1959', 'public ( northshore sd )', '1800', 's cougar', 'crown'], ['eastlake', 'sammamish', '1993', 'public ( lake washington sd )', '1329', 'wolves', 'crest'], ['garfield', 'seattle', '1920', 'public ( seattle ps )', '1702', 's bulldog', 'crown'], ['inglemoor', 'kenmore', '1964', 'public ( northshore sd )', '1880', 'vikings', 'crown'], ['issaquah', 'issaquah', '1905', 'public ( issaquah sd )', '1844', 's eagle', 'crest'], ['newport', 'bellevue', '1964', 'public ( bellevue sd )', '1712', 's knight', 'crest'], ['redmond', 'redmond', '1965', 'public ( lake washington sd )', '1442', 'mustangs', 'crest'], ['roosevelt', 'seattle', '1922', 'public ( seattle ps )', '1710', 'rough riders', 'crown'], ['skyline', 'sammamish', '1997', 'public ( issaquah sd )', '1889', 'ns sparta', 'crest']] |
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