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1998 australian super touring championship | https://en.wikipedia.org/wiki/1998_Australian_Super_Touring_Championship | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15394512-2.html.csv | majority | in the 1998 australian super touring championship , when the winner was brad jones , the team was always brad jones racing . | {'scope': 'subset', 'col': '7', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'brad jones racing', 'subset': {'col': '6', 'criterion': 'equal', 'value': 'brad jones'}} | {'func': 'all_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'winner', 'brad jones'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; winner ; brad jones }', 'tointer': 'select the rows whose winner record fuzzily matches to brad jones .'}, 'team', 'brad jones racing'], 'result': True, 'ind': 1, 'tointer': 'select the rows whose winner record fuzzily matches to brad jones . for the team records of these rows , all of them fuzzily match to brad jones racing .', 'tostr': 'all_eq { filter_eq { all_rows ; winner ; brad jones } ; team ; brad jones racing } = true'} | all_eq { filter_eq { all_rows ; winner ; brad jones } ; team ; brad jones racing } = true | select the rows whose winner record fuzzily matches to brad jones . for the team records of these rows , all of them fuzzily match to brad jones racing . | 2 | 2 | {'all_str_eq_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, 'winner_4': 4, 'brad jones_5': 5, 'team_6': 6, 'brad jones racing_7': 7} | {'all_str_eq_1': 'all_str_eq', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'winner_4': 'winner', 'brad jones_5': 'brad jones', 'team_6': 'team', 'brad jones racing_7': 'brad jones racing'} | {'all_str_eq_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'winner_4': [0], 'brad jones_5': [0], 'team_6': [1], 'brad jones racing_7': [1]} | ['rd / race', 'race title', 'circuit', 'city / state', 'date', 'winner', 'team'] | [['1 / 1', 'calder', 'calder park raceway', 'melbourne , victoria', '4 - 5 apr', 'cameron mcconville', 'brad jones racing'], ['1 / 2', 'calder', 'calder park raceway', 'melbourne , victoria', '4 - 5 apr', 'cameron mcconville', 'brad jones racing'], ['2 / 1', 'oran park', 'oran park raceway', 'sydney , new south wales', '26 - 27 apr', 'brad jones', 'brad jones racing'], ['2 / 2', 'oran park', 'oran park raceway', 'sydney , new south wales', '26 - 27 apr', 'brad jones', 'brad jones racing'], ['3 / 1', 'phillip island', 'phillip island grand prix circuit', 'phillip island , victoria', '16 - 17 may', 'cameron mcconville', 'brad jones racing'], ['3 / 2', 'phillip island', 'phillip island grand prix circuit', 'phillip island , victoria', '16 - 17 may', 'jim richards', 'volvo racing'], ['4 / 1', 'eastern creek', 'eastern creek raceway', 'sydney , new south wales', '6 - 7 jun', 'jim richards', 'volvo racing'], ['4 / 2', 'eastern creek', 'eastern creek raceway', 'sydney , new south wales', '6 - 7 jun', 'brad jones', 'brad jones racing'], ['5 / 1', 'lakeside', 'lakeside international raceway', 'brisbane , queensland', '27 - 28 jun', 'brad jones', 'brad jones racing'], ['5 / 2', 'lakeside', 'lakeside international raceway', 'brisbane , queensland', '27 - 28 jun', 'brad jones', 'brad jones racing'], ['6 / 1', 'mallala', 'mallala motorsport park', 'adelaide , south australia', '18 - 19 jul', 'brad jones', 'brad jones racing'], ['6 / 2', 'mallala', 'mallala motorsport park', 'adelaide , south australia', '18 - 19 jul', 'cameron mcconville', 'brad jones racing'], ['7 / 1', 'winton', 'winton motor raceway', 'benalla , victoria', '8 - 9 aug', 'cameron mcconville', 'brad jones racing'], ['7 / 2', 'winton', 'winton motor raceway', 'benalla , victoria', '8 - 9 aug', 'cameron mcconville', 'brad jones racing'], ['8 / 1', 'oran park', 'oran park raceway', 'sydney , new south wales', '29 - 30 aug', 'cameron mcconville', 'brad jones racing'], ['8 / 2', 'oran park', 'oran park raceway', 'sydney , new south wales', '29 - 30 aug', 'brad jones', 'brad jones racing']] |
generation adidas | https://en.wikipedia.org/wiki/Generation_Adidas | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1076503-13.html.csv | count | in the generation adidas competition five players graduated from college in 2009 . | {'scope': 'all', 'criterion': 'equal', 'value': '2009', 'result': '5', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'graduated', '2009'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose graduated record is equal to 2009 .', 'tostr': 'filter_eq { all_rows ; graduated ; 2009 }'}], 'result': '5', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; graduated ; 2009 } }', 'tointer': 'select the rows whose graduated record is equal to 2009 . the number of such rows is 5 .'}, '5'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; graduated ; 2009 } } ; 5 } = true', 'tointer': 'select the rows whose graduated record is equal to 2009 . the number of such rows is 5 .'} | eq { count { filter_eq { all_rows ; graduated ; 2009 } } ; 5 } = true | select the rows whose graduated record is equal to 2009 . the number of such rows is 5 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_eq_0': 0, 'all_rows_4': 4, 'graduated_5': 5, '2009_6': 6, '5_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'graduated_5': 'graduated', '2009_6': '2009', '5_7': '5'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'graduated_5': [0], '2009_6': [0], '5_7': [2]} | ['player', 'home town', 'college / prior', 'drafting team', 'graduated'] | [['kevin alston', 'silver spring , md', 'indiana', 'new england revolution', '2009'], ['danny cruz', 'glendale , az', 'unlv', 'houston dynamo', '2011'], ['stefan frei', 'widnau , switzerland', 'california', 'toronto fc', '2010'], ['omar gonzalez', 'dallas , tx', 'maryland', 'los angeles galaxy', '2009'], ['jeremy hall', 'tampa , fl', 'maryland', 'new york red bulls', '2009'], ['baggio husidic', 'libertyville , il', 'uic', 'chicago fire', '2010'], ['peri maroå ¡ evic', 'rockford , il', 'michigan', 'fc dallas', '2011'], ['rodney wallace', 'rockville , md', 'maryland', 'dc united', '2009'], ['steve zakuani', 'london , england', 'akron', 'seattle sounders fc', '2009']] |
1983 - 84 houston rockets season | https://en.wikipedia.org/wiki/1983%E2%80%9384_Houston_Rockets_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17383465-1.html.csv | count | the united states produced 9 players in the 1983-84 houston rockets season . | {'scope': 'all', 'criterion': 'all', 'value': 'n/a', 'result': '9', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_all', 'args': ['all_rows', 'nationality'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose nationality record is arbitrary .', 'tostr': 'filter_all { all_rows ; nationality }'}], 'result': '9', 'ind': 1, 'tostr': 'count { filter_all { all_rows ; nationality } }', 'tointer': 'select the rows whose nationality record is arbitrary . the number of such rows is 9 .'}, '9'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_all { all_rows ; nationality } } ; 9 } = true', 'tointer': 'select the rows whose nationality record is arbitrary . the number of such rows is 9 .'} | eq { count { filter_all { all_rows ; nationality } } ; 9 } = true | select the rows whose nationality record is arbitrary . the number of such rows is 9 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_all_0': 0, 'all_rows_4': 4, 'nationality_5': 5, '9_6': 6} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_all_0': 'filter_all', 'all_rows_4': 'all_rows', 'nationality_5': 'nationality', '9_6': '9'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_all_0': [1], 'all_rows_4': [0], 'nationality_5': [0], '9_6': [2]} | ['round', 'pick', 'player', 'nationality', 'college'] | [['1', '1', 'ralph sampson', 'united states', 'virginia'], ['1', '3', 'rodney mccray', 'united states', 'louisville'], ['3', '48', 'craig ehlo', 'united states', 'washington state'], ['4', '71', 'darrell browder', 'united states', 'texas christian'], ['5', '94', 'chuck barnett', 'united states', 'oklahoma'], ['6', '117', 'jim stack', 'united states', 'northwestern'], ['7', '140', 'brian kellerman', 'united states', 'idaho'], ['8', '163', 'jeff bolding', 'united states', 'arkansas state'], ['9', '185', 'james campbell', 'united states', 'oklahoma city']] |
1999 denver broncos season | https://en.wikipedia.org/wiki/1999_Denver_Broncos_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17990473-1.html.csv | unique | september 26 , 1999 is the only date the denver bronces played against the tampa bay buccaneers . | {'scope': 'all', 'row': '3', 'col': '3', 'col_other': '2', 'criterion': 'equal', 'value': 'tampa bay buccaneers', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', 'tampa bay buccaneers'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose opponent record fuzzily matches to tampa bay buccaneers .', 'tostr': 'filter_eq { all_rows ; opponent ; tampa bay buccaneers }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; opponent ; tampa bay buccaneers } }', 'tointer': 'select the rows whose opponent record fuzzily matches to tampa bay buccaneers . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', 'tampa bay buccaneers'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose opponent record fuzzily matches to tampa bay buccaneers .', 'tostr': 'filter_eq { all_rows ; opponent ; tampa bay buccaneers }'}, 'date'], 'result': 'september 26 , 1999', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; opponent ; tampa bay buccaneers } ; date }'}, 'september 26 , 1999'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; opponent ; tampa bay buccaneers } ; date } ; september 26 , 1999 }', 'tointer': 'the date record of this unqiue row is september 26 , 1999 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; opponent ; tampa bay buccaneers } } ; eq { hop { filter_eq { all_rows ; opponent ; tampa bay buccaneers } ; date } ; september 26 , 1999 } } = true', 'tointer': 'select the rows whose opponent record fuzzily matches to tampa bay buccaneers . there is only one such row in the table . the date record of this unqiue row is september 26 , 1999 .'} | and { only { filter_eq { all_rows ; opponent ; tampa bay buccaneers } } ; eq { hop { filter_eq { all_rows ; opponent ; tampa bay buccaneers } ; date } ; september 26 , 1999 } } = true | select the rows whose opponent record fuzzily matches to tampa bay buccaneers . there is only one such row in the table . the date record of this unqiue row is september 26 , 1999 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'opponent_7': 7, 'tampa bay buccaneers_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'date_9': 9, 'september 26 , 1999_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'opponent_7': 'opponent', 'tampa bay buccaneers_8': 'tampa bay buccaneers', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'date_9': 'date', 'september 26 , 1999_10': 'september 26 , 1999'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'opponent_7': [0], 'tampa bay buccaneers_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'date_9': [2], 'september 26 , 1999_10': [3]} | ['week', 'date', 'opponent', 'result', 'attendance'] | [['1', 'september 13 , 1999', 'miami dolphins', 'l 38 - 21', '75623'], ['2', 'september 19 , 1999', 'kansas city chiefs', 'l 26 - 10', '78683'], ['3', 'september 26 , 1999', 'tampa bay buccaneers', 'l 13 - 10', '65297'], ['4', 'october 3 , 1999', 'new york jets', 'l 21 - 13', '74181'], ['5', 'october 10 , 1999', 'oakland raiders', 'w 16 - 13', '55704'], ['6', 'october 17 , 1999', 'green bay packers', 'w 31 - 10', '73352'], ['7', 'october 24 , 1999', 'new england patriots', 'l 24 - 23', '60011'], ['8', 'october 31 , 1999', 'minnesota vikings', 'l 23 - 20', '75021'], ['9', 'november 7 , 1999', 'san diego chargers', 'w 33 - 17', '61204'], ['10', 'november 14 , 1999', 'seattle seahawks', 'l 20 - 17', '66314'], ['11', 'november 22 , 1999', 'oakland raiders', 'w 27 - 21', '70012'], ['13', 'december 5 , 1999', 'kansas city chiefs', 'l 16 - 10', '73855'], ['14', 'december 13 , 1999', 'jacksonville jaguars', 'l 27 - 24', '71357'], ['15', 'december 19 , 1999', 'seattle seahawks', 'w 36 - 30', '65987'], ['16', 'december 25 , 1999', 'detroit lions', 'w 17 - 7', '73158'], ['17', 'january 2 , 2000', 'san diego chargers', 'l 12 - 6', '69278']] |
1949 - 50 new york rangers season | https://en.wikipedia.org/wiki/1949%E2%80%9350_New_York_Rangers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17311417-2.html.csv | unique | game 6 against the boston bruins was the only game to end in a 5-2 score in the 1949 - 50 new york rangers season . | {'scope': 'all', 'row': '6', 'col': '4', 'col_other': '3', 'criterion': 'equal', 'value': '5-2', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'score', '5-2'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose score record fuzzily matches to 5-2 .', 'tostr': 'filter_eq { all_rows ; score ; 5-2 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; score ; 5-2 } }', 'tointer': 'select the rows whose score record fuzzily matches to 5-2 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'score', '5-2'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose score record fuzzily matches to 5-2 .', 'tostr': 'filter_eq { all_rows ; score ; 5-2 }'}, 'opponent'], 'result': 'boston bruins', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; score ; 5-2 } ; opponent }'}, 'boston bruins'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; score ; 5-2 } ; opponent } ; boston bruins }', 'tointer': 'the opponent record of this unqiue row is boston bruins .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; score ; 5-2 } } ; eq { hop { filter_eq { all_rows ; score ; 5-2 } ; opponent } ; boston bruins } } = true', 'tointer': 'select the rows whose score record fuzzily matches to 5-2 . there is only one such row in the table . the opponent record of this unqiue row is boston bruins .'} | and { only { filter_eq { all_rows ; score ; 5-2 } } ; eq { hop { filter_eq { all_rows ; score ; 5-2 } ; opponent } ; boston bruins } } = true | select the rows whose score record fuzzily matches to 5-2 . there is only one such row in the table . the opponent record of this unqiue row is boston bruins . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'score_7': 7, '5-2_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'opponent_9': 9, 'boston bruins_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'score_7': 'score', '5-2_8': '5-2', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'opponent_9': 'opponent', 'boston bruins_10': 'boston bruins'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'score_7': [0], '5-2_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'opponent_9': [2], 'boston bruins_10': [3]} | ['game', 'october', 'opponent', 'score', 'record'] | [['1', '15', 'montreal canadiens', '3 - 1', '0 - 1 - 0'], ['2', '16', 'boston bruins', '2 - 2', '0 - 1 - 1'], ['3', '19', 'detroit red wings', '6 - 1', '0 - 2 - 1'], ['4', '22', 'toronto maple leafs', '2 - 2', '0 - 2 - 2'], ['5', '25', 'chicago black hawks', '2 - 1', '1 - 2 - 2'], ['6', '26', 'boston bruins', '5 - 2', '2 - 2 - 2'], ['7', '29', 'chicago black hawks', '2 - 0', '2 - 3 - 2'], ['8', '30', 'toronto maple leafs', '4 - 2', '2 - 4 - 2']] |
1951 world figure skating championships | https://en.wikipedia.org/wiki/1951_World_Figure_Skating_Championships | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11343995-1.html.csv | aggregation | the average total score for the 1951 world figure skating championships is 154.3245 . | {'scope': 'all', 'col': '7', 'type': 'average', 'result': '154.3245', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'total'], 'result': '154.3245', 'ind': 0, 'tostr': 'avg { all_rows ; total }'}, '154.3245'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; total } ; 154.3245 } = true', 'tointer': 'the average of the total record of all rows is 154.3245 .'} | round_eq { avg { all_rows ; total } ; 154.3245 } = true | the average of the total record of all rows is 154.3245 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'total_4': 4, '154.3245_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'total_4': 'total', '154.3245_5': '154.3245'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'total_4': [0], '154.3245_5': [1]} | ['rank', 'name', 'nation', 'placings', 'figures', 'free', 'total'] | [['1', 'dick button', 'united states', '7', '104.38', '79.33', '183.71'], ['2', 'james grogan', 'united states', '17', '93.11', '77.58', '170.69'], ['3', 'helmut seibt', 'austria', '22', '94.08', '74.78', '168.86'], ['4', 'hayes alan jenkins', 'united states', '25', '90.80', '77.35', '168.15'], ['5', 'dudley richards', 'united states', '38', '85.63', '70.93', '156.56'], ['6', 'carlo fassi', 'italy', '41', '84.45', '72.22', '156.67'], ['7', 'don laws', 'united states', '48', '81.92', '68.60', '150.52'], ['8', 'michael carrington', 'united kingdom', '54', '83.88', '64.05', '147.93'], ['9', 'william lewis', 'canada', '67', '76.63', '56.35', '132.98'], ['10', 'freimut stein', 'west germany', '69', '74.00', '58.10', '132.10'], ['11', 'ryusuke arisaka', 'japan', '74', '73.30', '56.10', '129.40']] |
1928 army cadets football team | https://en.wikipedia.org/wiki/1928_Army_Cadets_football_team | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-21091157-1.html.csv | majority | the majority of these games resulted in a win for the army cadets football team . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'win', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'result', 'win'], 'result': True, 'ind': 0, 'tointer': 'for the result records of all rows , most of them fuzzily match to win .', 'tostr': 'most_eq { all_rows ; result ; win } = true'} | most_eq { all_rows ; result ; win } = true | for the result records of all rows , most of them fuzzily match to win . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'result_3': 3, 'win_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'result_3': 'result', 'win_4': 'win'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'result_3': [0], 'win_4': [0]} | ['game', 'date', 'opponent', 'result', 'black knights points', 'opponents', 'record'] | [['1', 'sept 29', 'boston university', 'win', '35', '0', '1 - 0'], ['2', 'oct 6', 'southern methodist', 'win', '14', '13', '2 - 0'], ['3', 'oct 13', 'providence college', 'win', '44', '0', '3 - 0'], ['4', 'oct 20', 'harvard', 'win', '15', '0', '4 - 0'], ['5', 'oct 27', 'yale', 'win', '18', '6', '5 - 0'], ['6', 'nov 3', 'depauw', 'win', '38', '12', '6 - 0'], ['7', 'nov 10', 'notre dame', 'loss', '6', '12', '6 - 1'], ['8', 'nov 17', 'carleton', 'win', '32', '7', '7 - 1'], ['9', 'nov 24', 'nebraska', 'win', '13', '3', '8 - 1']] |
list of palatine locomotives and railbuses | https://en.wikipedia.org/wiki/List_of_Palatine_locomotives_and_railbuses | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18843924-5.html.csv | unique | railway number xi - xxii , xxviii is the only railway to have locomotives and railbuses produced before 1900 . | {'scope': 'all', 'row': '1', 'col': '5', 'col_other': '2', 'criterion': 'less_than', 'value': '1900', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'year ( s ) of manufacture', '1900'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose year ( s ) of manufacture record is less than 1900 .', 'tostr': 'filter_less { all_rows ; year ( s ) of manufacture ; 1900 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_less { all_rows ; year ( s ) of manufacture ; 1900 } }', 'tointer': 'select the rows whose year ( s ) of manufacture record is less than 1900 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'year ( s ) of manufacture', '1900'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose year ( s ) of manufacture record is less than 1900 .', 'tostr': 'filter_less { all_rows ; year ( s ) of manufacture ; 1900 }'}, 'railway number ( s )'], 'result': 'xi - xxii , xxviii', 'ind': 2, 'tostr': 'hop { filter_less { all_rows ; year ( s ) of manufacture ; 1900 } ; railway number ( s ) }'}, 'xi - xxii , xxviii'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_less { all_rows ; year ( s ) of manufacture ; 1900 } ; railway number ( s ) } ; xi - xxii , xxviii }', 'tointer': 'the railway number ( s ) record of this unqiue row is xi - xxii , xxviii .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_less { all_rows ; year ( s ) of manufacture ; 1900 } } ; eq { hop { filter_less { all_rows ; year ( s ) of manufacture ; 1900 } ; railway number ( s ) } ; xi - xxii , xxviii } } = true', 'tointer': 'select the rows whose year ( s ) of manufacture record is less than 1900 . there is only one such row in the table . the railway number ( s ) record of this unqiue row is xi - xxii , xxviii .'} | and { only { filter_less { all_rows ; year ( s ) of manufacture ; 1900 } } ; eq { hop { filter_less { all_rows ; year ( s ) of manufacture ; 1900 } ; railway number ( s ) } ; xi - xxii , xxviii } } = true | select the rows whose year ( s ) of manufacture record is less than 1900 . there is only one such row in the table . the railway number ( s ) record of this unqiue row is xi - xxii , xxviii . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_less_0': 0, 'all_rows_6': 6, 'year (s) of manufacture_7': 7, '1900_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'railway number (s)_9': 9, 'xi - xxii , xxviii_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_less_0': 'filter_less', 'all_rows_6': 'all_rows', 'year (s) of manufacture_7': 'year ( s ) of manufacture', '1900_8': '1900', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'railway number (s)_9': 'railway number ( s )', 'xi - xxii , xxviii_10': 'xi - xxii , xxviii'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_less_0': [1, 2], 'all_rows_6': [0], 'year (s) of manufacture_7': [0], '1900_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'railway number (s)_9': [2], 'xi - xxii , xxviii_10': [3]} | ['class', 'railway number ( s )', 'drg number ( s )', 'quantity', 'year ( s ) of manufacture', 'axle arrangement ( uic ) bauart'] | [['l 1', 'xi - xxii , xxviii', '99 081 - 99 092', '13', '1889 - 1907', 'c n2t'], ['l 2', 'xxiii - xxvii', '99 001 - 99 005', '5', '1903 - 1905', 'b n2t'], ['pts 2 / 2', 'xxx', '99 011', '1', '1910', 'b h2t'], ['pts 3 / 3 n', 'xxix', '99 093', '1', '1911', 'c n2t'], ['pts 3 / 3 h', 'xxxi - xxxiii', '99 101 - 99 103', '3', '1923', 'c h2t']] |
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 | ordinal | episode 809 of the colbert report had the second highest production code number . | {'row': '4', 'col': '6', 'order': '2', 'col_other': '1', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'production code', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; production code ; 2 }'}, 'episode'], 'result': '809', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; production code ; 2 } ; episode }'}, '809'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; production code ; 2 } ; episode } ; 809 } = true', 'tointer': 'select the row whose production code record of all rows is 2nd maximum . the episode record of this row is 809 .'} | eq { hop { nth_argmax { all_rows ; production code ; 2 } ; episode } ; 809 } = true | select the row whose production code record of all rows is 2nd maximum . the episode record of this row is 809 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'num_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'production code_5': 5, '2_6': 6, 'episode_7': 7, '809_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'num_hop_1': 'num_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'production code_5': 'production code', '2_6': '2', 'episode_7': 'episode', '809_8': '809'} | {'eq_2': [3], 'result_3': [], 'num_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'production code_5': [0], '2_6': [0], 'episode_7': [1], '809_8': [2]} | ['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']] |
list of danish consorts | https://en.wikipedia.org/wiki/List_of_Danish_consorts | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12418234-6.html.csv | majority | the majority of danish consorts becamse consorts due to their husband 's ascession . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'equal', 'value': "husband 's ascession", 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'became consort', "husband 's ascession"], 'result': True, 'ind': 0, 'tointer': "for the became consort records of all rows , most of them fuzzily match to husband 's ascession .", 'tostr': "most_eq { all_rows ; became consort ; husband 's ascession } = true"} | most_eq { all_rows ; became consort ; husband 's ascession } = true | for the became consort records of all rows , most of them fuzzily match to husband 's ascession . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'became consort_3': 3, "husband 's ascession_4": 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'became consort_3': 'became consort', "husband 's ascession_4": "husband 's ascession"} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'became consort_3': [0], "husband 's ascession_4": [0]} | ['name', 'birth', 'marriage', 'became consort', 'ceased to be consort', 'spouse'] | [['louise of hesse - kassel', '7 september 1817', '26 may 1842', "15 november 1863 husband 's ascession", '29 september 1898', 'christian ix'], ['louise of sweden', '31 october 1851', '28 july 1869', "29 january 1906 husband 's ascession", "14 may 1912 husband 's death", 'frederick viii'], ['alexandrine of mecklenburg - schwerin', '24 december 1879', '26 april 1898', "14 may 1912 husband 's ascession", "20 april 1947 husband 's death", 'christian x'], ['ingrid of sweden', '28 march 1910', '24 may 1935', "20 april 1947 husband 's ascession", "14 january 1972 husband 's death", 'frederick ix'], ['henri de laborde de monpezat', '11 june 1934', '10 june 1967', '14 january 1972', 'incumbent', 'margrethe ii']] |
jack fairman | https://en.wikipedia.org/wiki/Jack_Fairman | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1235888-1.html.csv | majority | jack fairman scored 0 points in the majority of years of his racing career . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'equal', 'value': '0', 'subset': None} | {'func': 'most_eq', 'args': ['all_rows', 'points', '0'], 'result': True, 'ind': 0, 'tointer': 'for the points records of all rows , most of them are equal to 0 .', 'tostr': 'most_eq { all_rows ; points ; 0 } = true'} | most_eq { all_rows ; points ; 0 } = true | for the points records of all rows , most of them are equal to 0 . | 1 | 1 | {'most_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'points_3': 3, '0_4': 4} | {'most_eq_0': 'most_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'points_3': 'points', '0_4': '0'} | {'most_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'points_3': [0], '0_4': [0]} | ['year', 'entrant', 'chassis', 'engine', 'points'] | [['1953', 'hw motors', 'hwm 53', 'alta', '0'], ['1953', 'connaught engineering', 'connaught type a', 'lea francis', '0'], ['1955', 'connaught engineering', 'connaught type b', 'alta', '0'], ['1956', 'connaught engineering', 'connaught type b', 'alta', '5'], ['1957', 'owen racing organisation', 'brm p25', 'brm', '0'], ['1958', 'bc ecclestone', 'connaught type b', 'alta', '0'], ['1958', 'cooper car company', 'cooper t45', 'coventry climax', '0'], ['1959', 'high efficiency motors', 'cooper t45', 'coventry climax', '0'], ['1959', 'high efficiency motors', 'cooper t45', 'maserati', '0'], ['1960', 'ct atkins', 'cooper t51', 'coventry climax', '0'], ['1961', 'rob walker racing', 'ferguson p99', 'coventry climax', '0'], ['1961', 'fred tuck cars', 'cooper t45', 'coventry climax', '0']] |
1965 vfl season | https://en.wikipedia.org/wiki/1965_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10788451-13.html.csv | superlative | mcg was the venue that drew the highest crowd attendance in the 1965 vfl season . | {'scope': 'all', 'col_superlative': '6', 'row_superlative': '5', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '5', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'crowd'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; crowd }'}, 'venue'], 'result': 'mcg', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; crowd } ; venue }'}, 'mcg'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; crowd } ; venue } ; mcg } = true', 'tointer': 'select the row whose crowd record of all rows is maximum . the venue record of this row is mcg .'} | eq { hop { argmax { all_rows ; crowd } ; venue } ; mcg } = true | select the row whose crowd record of all rows is maximum . the venue record of this row is mcg . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'crowd_5': 5, 'venue_6': 6, 'mcg_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'crowd_5': 'crowd', 'venue_6': 'venue', 'mcg_7': 'mcg'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'crowd_5': [0], 'venue_6': [1], 'mcg_7': [2]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['st kilda', '18.9 ( 117 )', 'south melbourne', '6.12 ( 48 )', 'moorabbin oval', '18709', '24 july 1965'], ['fitzroy', '7.13 ( 55 )', 'footscray', '6.6 ( 42 )', 'brunswick street oval', '7456', '24 july 1965'], ['north melbourne', '11.15 ( 81 )', 'melbourne', '9.6 ( 60 )', 'city of coburg oval', '8312', '24 july 1965'], ['hawthorn', '7.5 ( 47 )', 'essendon', '10.11 ( 71 )', 'glenferrie oval', '11400', '24 july 1965'], ['richmond', '8.8 ( 56 )', 'collingwood', '12.7 ( 79 )', 'mcg', '56360', '24 july 1965'], ['geelong', '5.9 ( 39 )', 'carlton', '9.12 ( 66 )', 'kardinia park', '19568', '24 july 1965']] |
1930 vfl season | https://en.wikipedia.org/wiki/1930_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10767641-4.html.csv | aggregation | the average crowd attendance for the vfl games was 17944 . | {'scope': 'all', 'col': '6', 'type': 'average', 'result': '17944', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'crowd'], 'result': '17944', 'ind': 0, 'tostr': 'avg { all_rows ; crowd }'}, '17944'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; crowd } ; 17944 } = true', 'tointer': 'the average of the crowd record of all rows is 17944 .'} | round_eq { avg { all_rows ; crowd } ; 17944 } = true | the average of the crowd record of all rows is 17944 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'crowd_4': 4, '17944_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'crowd_4': 'crowd', '17944_5': '17944'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'crowd_4': [0], '17944_5': [1]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['melbourne', '18.15 ( 123 )', 'north melbourne', '15.12 ( 102 )', 'mcg', '8662', '24 may 1930'], ['footscray', '9.10 ( 64 )', 'richmond', '14.7 ( 91 )', 'western oval', '20000', '24 may 1930'], ['essendon', '14.12 ( 96 )', 'hawthorn', '8.13 ( 61 )', 'windy hill', '15000', '24 may 1930'], ['collingwood', '10.12 ( 72 )', 'geelong', '12.18 ( 90 )', 'victoria park', '17000', '24 may 1930'], ['carlton', '20.18 ( 138 )', 'south melbourne', '11.18 ( 84 )', 'princes park', '21000', '24 may 1930'], ['st kilda', '15.18 ( 108 )', 'fitzroy', '8.10 ( 58 )', 'junction oval', '26000', '24 may 1930']] |
memphis grizzlies all - time roster | https://en.wikipedia.org/wiki/Memphis_Grizzlies_all-time_roster | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-16494599-10.html.csv | majority | the majority of memphis grizzlies players are 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', 'nationality', 'united states'], 'result': True, 'ind': 0, 'tointer': 'for the nationality records of all rows , all of them fuzzily match to united states .', 'tostr': 'all_eq { all_rows ; nationality ; united states } = true'} | all_eq { all_rows ; nationality ; united states } = true | for the nationality 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, 'nationality_3': 3, 'united states_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'nationality_3': 'nationality', 'united states_4': 'united states'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'nationality_3': [0], 'united states_4': [0]} | ['player', 'no', 'nationality', 'position', 'years for grizzlies', 'school / club team'] | [['bobby jackson', '24', 'united states', 'guard', '2005 - 2006', 'minnesota'], ['casey jacobsen', '23', 'united states', 'guard - forward', '2007 - 2008', 'stanford'], ['alexander johnson', '32', 'united states', 'power forward', '2006 - 2007', 'florida state'], ['chris johnson', '4', 'united states', 'small forward', '2013', 'dayton'], ['bobby jones', '8', 'united states', 'forward', '2008', 'washington'], ['dahntay jones', '30', 'united states', 'guard - forward', '2003 - 2007', 'duke'], ['damon jones', '11', 'united states', 'shooting guard', '2000 - 2001', 'houston']] |
list of great central railway locomotives and rolling stock | https://en.wikipedia.org/wiki/List_of_Great_Central_Railway_locomotives_and_rolling_stock | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11913905-3.html.csv | majority | most of the great central railway locomotives and rolling stock have private owners . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'private owner', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'owner ( s )', 'private owner'], 'result': True, 'ind': 0, 'tointer': 'for the owner ( s ) records of all rows , most of them fuzzily match to private owner .', 'tostr': 'most_eq { all_rows ; owner ( s ) ; private owner } = true'} | most_eq { all_rows ; owner ( s ) ; private owner } = true | for the owner ( s ) records of all rows , most of them fuzzily match to private owner . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'owner (s)_3': 3, 'private owner_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'owner (s)_3': 'owner ( s )', 'private owner_4': 'private owner'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'owner (s)_3': [0], 'private owner_4': [0]} | ['number & name', 'description', 'livery', 'owner ( s )', 'date'] | [['operational', 'operational', 'operational', 'operational', 'operational'], ['no d2158 margaret - ann', 'british rail class 03 0 - 6 - 0dm', 'br blue with the late crest', 'great central railway plc', '1960'], ['no d3101', 'british rail class 08 0 - 6 - 0de', 'br green with wasp stripes and the early crest', 'private owner', '1955'], ['no 13180', 'british rail class 08 0 - 6 - 0de', 'br green with the early crest', 'private owner', '1955'], ['no 08220', 'british rail class 08 0 - 6 - 0de', 'br rail blue', 'english electric preservation', '1956'], ['no 08694', 'british rail class 08 0 - 6 - 0de', 'ews red & gold', 'private owner', '1959'], ['no 10119 margaret ethel - thomas alfred naylor', 'british rail class 10 0 - 6 - 0de', 'br rail blue', 'private owner', '1961'], ['undergoing overhaul , restoration or repairs', 'undergoing overhaul , restoration or repairs', 'undergoing overhaul , restoration or repairs', 'undergoing overhaul , restoration or repairs', 'undergoing overhaul , restoration or repairs'], ['no d2118', 'british rail class 03 0 - 6 - 0dm', 'br rail blue', 'private owner', '1959'], ['no 07005', 'british rail class 07 0 - 6 - 0de', 'br rail blue', 'private owner', '1962']] |
1990 dallas cowboys season | https://en.wikipedia.org/wiki/1990_Dallas_Cowboys_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11281728-2.html.csv | majority | the dallas cowboys lost most of their games in the month of september during the 1990 season . | {'scope': 'subset', 'col': '4', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': 'l', 'subset': {'col': '2', 'criterion': 'fuzzily_match', 'value': '1990 - 09'}} | {'func': 'most_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', '1990 - 09'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; date ; 1990 - 09 }', 'tointer': 'select the rows whose date record fuzzily matches to 1990 - 09 .'}, 'result', 'l'], 'result': True, 'ind': 1, 'tointer': 'select the rows whose date record fuzzily matches to 1990 - 09 . for the result records of these rows , most of them fuzzily match to l .', 'tostr': 'most_eq { filter_eq { all_rows ; date ; 1990 - 09 } ; result ; l } = true'} | most_eq { filter_eq { all_rows ; date ; 1990 - 09 } ; result ; l } = true | select the rows whose date record fuzzily matches to 1990 - 09 . for the result records of these rows , most of them fuzzily match to l . | 2 | 2 | {'most_str_eq_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, 'date_4': 4, '1990 - 09_5': 5, 'result_6': 6, 'l_7': 7} | {'most_str_eq_1': 'most_str_eq', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'date_4': 'date', '1990 - 09_5': '1990 - 09', 'result_6': 'result', 'l_7': 'l'} | {'most_str_eq_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'date_4': [0], '1990 - 09_5': [0], 'result_6': [1], 'l_7': [1]} | ['week', 'date', 'opponent', 'result', 'venue', 'attendance'] | [['1', '1990 - 09 - 09', 'san diego chargers', 'w 17 - 14', 'texas stadium', '48063'], ['2', '1990 - 09 - 16', 'new york giants', 'l 28 - 7', 'texas stadium', '61090'], ['3', '1990 - 09 - 23', 'washington redskins', 'l 19 - 15', 'robert f kennedy memorial stadium', '53804'], ['4', '1990 - 09 - 30', 'new york giants', 'l 31 - 17', 'giants stadium', '75923'], ['5', '1990 - 10 - 07', 'tampa bay buccaneers', 'w 14 - 10', 'texas stadium', '60076'], ['6', '1990 - 10 - 14', 'phoenix cardinals', 'l 20 - 3', 'sun devil stadium', '45235'], ['7', '1990 - 10 - 21', 'tampa bay buccaneers', 'w 17 - 13', 'tampa stadium', '68315'], ['8', '1990 - 10 - 28', 'philadelphia eagles', 'l 21 - 20', 'texas stadium', '62605'], ['9', '1990 - 11 - 04', 'new york jets', 'l 24 - 9', 'the meadowlands', '68086'], ['10', '1990 - 11 - 11', 'san francisco 49ers', 'l 24 - 6', 'texas stadium', '62966'], ['11', '1990 - 11 - 18', 'los angeles rams', 'w 24 - 21', 'anaheim stadium', '58589'], ['12', '1990 - 11 - 22', 'washington redskins', 'w 27 - 17', 'texas stadium', '60355'], ['13', '1990 - 12 - 02', 'new orleans saints', 'w 17 - 13', 'texas stadium', '60087'], ['14', '-', '-', '-', '-', ''], ['15', '1990 - 12 - 16', 'phoenix cardinals', 'w 41 - 10', 'texas stadium', '60190'], ['16', '1990 - 12 - 23', 'philadelphia eagles', 'l 17 - 3', 'veterans stadium', '63895'], ['17', '1990 - 12 - 30', 'atlanta falcons', 'l 26 - 7', 'atlanta - fulton county stadium', '50097']] |
take me out ( uk game show ) | https://en.wikipedia.org/wiki/Take_Me_Out_%28UK_game_show%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-25664518-4.html.csv | aggregation | on take me out , episodes with 4 couples got an average viewership of 4.575 million . | {'scope': 'subset', 'col': '8', 'type': 'average', 'result': '4.575', 'subset': {'col': '3', 'criterion': 'equal', 'value': '4'}} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'no of couples', '4'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; no of couples ; 4 }', 'tointer': 'select the rows whose no of couples record is equal to 4 .'}, 'viewers ( millions )'], 'result': '4.575', 'ind': 1, 'tostr': 'avg { filter_eq { all_rows ; no of couples ; 4 } ; viewers ( millions ) }'}, '4.575'], 'result': True, 'ind': 2, 'tostr': 'round_eq { avg { filter_eq { all_rows ; no of couples ; 4 } ; viewers ( millions ) } ; 4.575 } = true', 'tointer': 'select the rows whose no of couples record is equal to 4 . the average of the viewers ( millions ) record of these rows is 4.575 .'} | round_eq { avg { filter_eq { all_rows ; no of couples ; 4 } ; viewers ( millions ) } ; 4.575 } = true | select the rows whose no of couples record is equal to 4 . the average of the viewers ( millions ) record of these rows is 4.575 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'avg_1': 1, 'filter_eq_0': 0, 'all_rows_4': 4, 'no of couples_5': 5, '4_6': 6, 'viewers (millions)_7': 7, '4.575_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'avg_1': 'avg', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'no of couples_5': 'no of couples', '4_6': '4', 'viewers (millions)_7': 'viewers ( millions )', '4.575_8': '4.575'} | {'eq_2': [3], 'result_3': [], 'avg_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'no of couples_5': [0], '4_6': [0], 'viewers (millions)_7': [1], '4.575_8': [2]} | ['', 'airdate', 'no of couples', '1st couple', '2nd couple', '3rd couple', '4th couple', 'viewers ( millions )', 'itv1 weekly ranking'] | [['1', '11 december 2010', '3', 'danny and vicky', 'adrian ( n / a )', 'alistair and alisha', 'iain and fern', '5.96', '18'], ['2', '18 december 2010', '3', 'james ( n / a )', 'dan and alice', 'samson and amy', 'silky and holly - jade', '5.10', '14'], ['3', '1 january 2011', '3', 'stuart and pegah', 'fabian and kay', 'darren and laura', 'kristen ( n / a )', 'under 3.05', 'outside top 30'], ['4', '8 january 2011', '4', 'scott and kieney', 'john and lisa', 'chi and cheryl', 'david and donna', '3.98', '29'], ['5', '15 january 2011', '3', 'harry and joanne', 'david ( n / a )', 'richie and tasha', 'gary and elle', '4.27', '23'], ['6', '22 january 2011', '4', 'brett and viv', 'ian and becky', 'james and abi - scarlett', 'rob and tanya', '4.44', '18'], ['7', '29 january 2011', '4', 'john and kerry', 'tez and kayleigh', 'dan and dawn', 'jake and sami', '4.29', '18'], ['8', '5 february 2011', '3', 'dean and maria', 'rick and megan', 'robbie ( n / a )', 'richard and jacqui', '4.28', '19'], ['9', '12 february 2011', '3', 'sam and claire', 'charles and carol', 'simon and natalie', 'stephen ( n / a )', '4.74', '18'], ['10', '19 february 2011', '3', 'ryan and luissa', 'neil ( n / a )', 'dan and krista', 'dean and jo - jo', '4.42', '19'], ['11', '26 february 2011', '4', 'frankie and nicole', 'riccardo and vikki', 'michael and julie', 'sonny and samantha h', '4.82', '18'], ['12', '5 march 2011', '4', 'dave and lucy', 'adam and katie', 'chris and kate', 'michael and adele', '5.03', '17'], ['13', '12 march 2011', '4', 'anthony and ellie', 'matt and samantha', 'andrew and peggy', 'dan and lauren', '4.89', '20']] |
pedro nunes ( racing driver ) | https://en.wikipedia.org/wiki/Pedro_Nunes_%28racing_driver%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-25386974-1.html.csv | majority | on most occasions , pedro nunes did not win the races he participated in . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'equal', 'value': '0', 'subset': None} | {'func': 'most_eq', 'args': ['all_rows', 'wins', '0'], 'result': True, 'ind': 0, 'tointer': 'for the wins records of all rows , most of them are equal to 0 .', 'tostr': 'most_eq { all_rows ; wins ; 0 } = true'} | most_eq { all_rows ; wins ; 0 } = true | for the wins records of all rows , most of them are equal to 0 . | 1 | 1 | {'most_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'wins_3': 3, '0_4': 4} | {'most_eq_0': 'most_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'wins_3': 'wins', '0_4': '0'} | {'most_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'wins_3': [0], '0_4': [0]} | ['season', 'series', 'team', 'races', 'wins', 'poles', 'f / laps', 'podiums', 'points', 'position'] | [['2006', 'formula renault 2.0 brazil', 'piquet sports', '1', '0', '0', '0', '0', '22', '17th'], ['2006', 'formula renault 2.0 brazil', 'dragão motorsport', '1', '0', '0', '0', '0', '22', '17th'], ['2006', 'formula 3 sudamericana', 'piquet sports', '14', '0', '0', '0', '0', '10', '28th'], ['2007', 'formula renault 2.0 nec', 'sl formula racing', '10', '0', '0', '0', '0', '46', '30th'], ['2007', 'eurocup formula renault 2.0', 'sl formula racing', '10', '0', '0', '0', '0', '0', 'nc'], ['2007', 'formula 3 sudamericana', 'baumer racing', '4', '0', '0', '0', '0', '1', '21st'], ['2008', 'formula 3 sudamericana', 'cesário fórmula', '17', '5', '3', '4', '11', '112', '2nd'], ['2009', 'formula 3 euro series', 'manor motorsport', '20', '0', '0', '0', '0', '0', '27th'], ['2009', 'british formula three championship', 'manor motorsport', '2', '0', '0', '0', '0', 'n / a', 'nc'], ['2009', 'masters of formula 3', 'manor motorsport', '1', '0', '0', '0', '0', 'n / a', '20th'], ['2010', 'gp3 series', 'art grand prix', '16', '0', '0', '0', '0', '4', '24th']] |
1984 u.s. open ( golf ) | https://en.wikipedia.org/wiki/1984_U.S._Open_%28golf%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17231267-6.html.csv | count | at the 1984 u.s. open , when the country is united states , there were 2 times the players ' score was 282 . | {'scope': 'subset', 'criterion': 'fuzzily_match', 'value': '282', 'result': '2', 'col': '4', 'subset': {'col': '3', 'criterion': 'equal', 'value': 'united states'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_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 .'}, 'score', '282'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose country record fuzzily matches to united states . among these rows , select the rows whose score record fuzzily matches to 282 .', 'tostr': 'filter_eq { filter_eq { all_rows ; country ; united states } ; score ; 282 }'}], 'result': '2', 'ind': 2, 'tostr': 'count { filter_eq { filter_eq { all_rows ; country ; united states } ; score ; 282 } }', 'tointer': 'select the rows whose country record fuzzily matches to united states . among these rows , select the rows whose score record fuzzily matches to 282 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_eq { filter_eq { all_rows ; country ; united states } ; score ; 282 } } ; 2 } = true', 'tointer': 'select the rows whose country record fuzzily matches to united states . among these rows , select the rows whose score record fuzzily matches to 282 . the number of such rows is 2 .'} | eq { count { filter_eq { filter_eq { all_rows ; country ; united states } ; score ; 282 } } ; 2 } = true | select the rows whose country record fuzzily matches to united states . among these rows , select the rows whose score record fuzzily matches to 282 . the number of such rows is 2 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_str_eq_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'country_6': 6, 'united states_7': 7, 'score_8': 8, '282_9': 9, '2_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_str_eq_1': 'filter_str_eq', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'country_6': 'country', 'united states_7': 'united states', 'score_8': 'score', '282_9': '282', '2_10': '2'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_str_eq_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'country_6': [0], 'united states_7': [0], 'score_8': [1], '282_9': [1], '2_10': [3]} | ['place', 'player', 'country', 'score', 'to par', 'money'] | [['t1', 'fuzzy zoeller', 'united states', '71 + 66 + 69 + 70 = 276', '- 4', 'playoff'], ['t1', 'greg norman', 'australia', '70 + 68 + 69 + 69 = 276', '- 4', 'playoff'], ['3', 'curtis strange', 'united states', '69 + 70 + 74 + 68 = 281', '+ 1', '36000'], ['t4', 'johnny miller', 'united states', '74 + 68 + 70 + 70 = 282', '+ 2', '22335'], ['t4', 'jim thorpe', 'united states', '68 + 71 + 70 + 73 = 282', '+ 2', '22335'], ['6', 'hale irwin', 'united states', '68 + 68 + 69 + 79 = 284', '+ 4', '16238'], ['t7', 'peter jacobsen', 'united states', '72 + 73 + 73 + 67 = 285', '+ 5', '14237'], ['t7', "mark o'meara", 'united states', '71 + 74 + 71 + 69 = 285', '+ 5', '14237'], ['t9', 'fred couples', 'united states', '69 + 71 + 74 + 72 = 286', '+ 6', '12122'], ['t9', 'lee trevino', 'united states', '71 + 72 + 69 + 74 = 286', '+ 6', '12122']] |
fc dacia chi \ xc8 \ x99in \ xc4 \ x83u | https://en.wikipedia.org/wiki/FC_Dacia_Chi%C8%99in%C4%83u | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2214582-1.html.csv | count | fc dacia chișinău 's has appeared in the second round of uefa cup 3 times between 2005 and 2014 . | {'scope': 'all', 'criterion': 'equal', 'value': '2', 'result': '3', 'col': '2', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'round', '2'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose round record is equal to 2 .', 'tostr': 'filter_eq { all_rows ; round ; 2 }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; round ; 2 } }', 'tointer': 'select the rows whose round record is equal to 2 . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; round ; 2 } } ; 3 } = true', 'tointer': 'select the rows whose round record is equal to 2 . the number of such rows is 3 .'} | eq { count { filter_eq { all_rows ; round ; 2 } } ; 3 } = true | select the rows whose round record is equal to 2 . the number of such rows is 3 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_eq_0': 0, 'all_rows_4': 4, 'round_5': 5, '2_6': 6, '3_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'round_5': 'round', '2_6': '2', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'round_5': [0], '2_6': [0], '3_7': [2]} | ['season', 'round', 'opponents', 'home leg', 'away leg', 'aggregate'] | [['2005 - 06', '1', 'vaduz', '0 - 2', '1 - 0', '1 - 2'], ['2008 - 09', '1', 'borac cacak', '1 - 1', '1 - 3', '2 - 4'], ['2009 - 10', '2', 'mšk žilina', '0 - 2', '0 - 1', '0 - 3'], ['2010 - 11', '1', 'fk zeta', '0 - 0', '1 - 1', '1 - 1 ( a )'], ['2010 - 11', '2', 'kalmar ff', '0 - 2', '0 - 0', '0 - 2'], ['2012 - 13', '1', 'celje', '1 - 0', '1 - 0', '2 - 0'], ['2012 - 13', '2', 'elfsborg', '1 - 0', '0 - 2', '1 - 2'], ['2013 - 14', '1', 'teuta durrës', '2 - 0', '1 - 3', '3 - 3 ( a )']] |
north melbourne football club | https://en.wikipedia.org/wiki/North_Melbourne_Football_Club | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-22106-3.html.csv | superlative | during the seasons j. brayshaw was chairman , north melbourne 's worst position was 13th . | {'scope': 'subset', 'col_superlative': '3', 'row_superlative': '10', 'value_mentioned': 'yes', 'max_or_min': 'max', 'other_col': '4', 'subset': {'col': '4', 'criterion': 'equal', 'value': 'j brayshaw'}} | {'func': 'eq', 'args': [{'func': 'max', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'chairman', 'j brayshaw'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; chairman ; j brayshaw }', 'tointer': 'select the rows whose chairman record fuzzily matches to j brayshaw .'}, 'position'], 'result': '13th', 'ind': 1, 'tostr': 'max { filter_eq { all_rows ; chairman ; j brayshaw } ; position }', 'tointer': 'select the rows whose chairman record fuzzily matches to j brayshaw . the maximum position record of these rows is 13th .'}, '13th'], 'result': True, 'ind': 2, 'tostr': 'eq { max { filter_eq { all_rows ; chairman ; j brayshaw } ; position } ; 13th } = true', 'tointer': 'select the rows whose chairman record fuzzily matches to j brayshaw . the maximum position record of these rows is 13th .'} | eq { max { filter_eq { all_rows ; chairman ; j brayshaw } ; position } ; 13th } = true | select the rows whose chairman record fuzzily matches to j brayshaw . the maximum position record of these rows is 13th . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'max_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'chairman_5': 5, 'j brayshaw_6': 6, 'position_7': 7, '13th_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'max_1': 'max', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'chairman_5': 'chairman', 'j brayshaw_6': 'j brayshaw', 'position_7': 'position', '13th_8': '13th'} | {'eq_2': [3], 'result_3': [], 'max_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'chairman_5': [0], 'j brayshaw_6': [0], 'position_7': [1], '13th_8': [2]} | ['year', 'w : l : d', 'position', 'chairman', 'ceo', 'coach', 'captain', 'vice - captain', 'best and fairest', 'leading goalkicker'] | [['2000', '15:10:0', '4th', 'r p casey / a carter', 'g miller', 'd pagan', 'w carey', 'a stevens', 'p bell', 'w carey 69'], ['2001', '9:13:0', '13th', 'a carter / a aylett', 'g miller / m easy', 'd pagan', 'w carey', 'a stevens', 's grant', 's rocca 48'], ['2002', '12:11:0', '7th', 'a aylett', 'm easy / g walsh', 'd pagan', 'a stevens', 'g archer', 'a simpson', 's rocca 50'], ['2003', '11:10:1', '10th', 'a aylett', 'g walsh', 'd laidley', 'a stevens', 'g archer', 'b harvey', 'l harding 33'], ['2004', '10:12:0', '10th', 'a aylett', 'g walsh', 'd laidley', 'a simpson', 'b harvey', 'b rawlings', 's rocca 49'], ['2005', '13:10:0', '7th', 'a aylett / g duff', 'g walsh', 'd laidley', 'a simpson', 'b harvey', 'b harvey', 'n thompson 52'], ['2006', '7:15:0', '14th', 'g duff', 'g walsh / r aylett', 'd laidley', 'a simpson', 'b harvey', 'b rawlings', 'n thompson 54'], ['2007', '15:10:0', '3rd', 'g duff / j magowan / j brayshaw', 'r aylett', 'd laidley', 'a simpson', 'b harvey', 'b harvey', 'c jones 43'], ['2008', '12:10:1', '7th', 'j brayshaw', 'e arocca', 'd laidley', 'a simpson', 'b harvey', 'b harvey', 'd hale 37'], ['2009', '7:14:1', '13th', 'j brayshaw', 'e arocca', 'd laidley / d crocker', 'b harvey', 'd petrie', 'a swallow', 'd petrie 27'], ['2010', '11:11:0', '9th', 'j brayshaw', 'e arocca', 'b scott', 'b harvey', 'd petrie', 'b harvey , b rawlings', 'l thomas 29'], ['2011', '10:12:0', '9th', 'j brayshaw', 'e arocca', 'b scott', 'b harvey', 'd petrie', 'a swallow , d wells', 'd petrie 48'], ['2012', '14:8:0', '8th', 'j brayshaw', 'earocca / cvale', 'b scott', 'a swallow', 'd petrie , j ziebell', 'aswallow', 'd petrie 57']] |
ulrikke eikeri | https://en.wikipedia.org/wiki/Ulrikke_Eikeri | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27877656-7.html.csv | comparative | ulrikke eikeri won against latvia before she won against iceland . | {'row_1': '3', 'row_2': '4', 'col': '1', 'col_other': '3', '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', 'opponent team', 'latvia'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose opponent team record fuzzily matches to latvia .', 'tostr': 'filter_eq { all_rows ; opponent team ; latvia }'}, 'outcome'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; opponent team ; latvia } ; outcome }', 'tointer': 'select the rows whose opponent team record fuzzily matches to latvia . take the outcome record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent team', 'iceland'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose opponent team record fuzzily matches to iceland .', 'tostr': 'filter_eq { all_rows ; opponent team ; iceland }'}, 'outcome'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; opponent team ; iceland } ; outcome }', 'tointer': 'select the rows whose opponent team record fuzzily matches to iceland . take the outcome record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'eq { hop { filter_eq { all_rows ; opponent team ; latvia } ; outcome } ; hop { filter_eq { all_rows ; opponent team ; iceland } ; outcome } }', 'tointer': 'select the rows whose opponent team record fuzzily matches to latvia . take the outcome record of this row . select the rows whose opponent team record fuzzily matches to iceland . take the outcome 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', 'opponent team', 'latvia'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose opponent team record fuzzily matches to latvia .', 'tostr': 'filter_eq { all_rows ; opponent team ; latvia }'}, 'outcome'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; opponent team ; latvia } ; outcome }', 'tointer': 'select the rows whose opponent team record fuzzily matches to latvia . take the outcome record of this row .'}, 'winner'], 'result': True, 'ind': 5, 'tostr': 'eq { hop { filter_eq { all_rows ; opponent team ; latvia } ; outcome } ; winner }', 'tointer': 'the outcome record of the first row is winner .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent team', 'iceland'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose opponent team record fuzzily matches to iceland .', 'tostr': 'filter_eq { all_rows ; opponent team ; iceland }'}, 'outcome'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; opponent team ; iceland } ; outcome }', 'tointer': 'select the rows whose opponent team record fuzzily matches to iceland . take the outcome record of this row .'}, 'winner'], 'result': True, 'ind': 6, 'tostr': 'eq { hop { filter_eq { all_rows ; opponent team ; iceland } ; outcome } ; winner }', 'tointer': 'the outcome record of the second row is winner .'}], 'result': True, 'ind': 7, 'tostr': 'and { eq { hop { filter_eq { all_rows ; opponent team ; latvia } ; outcome } ; winner } ; eq { hop { filter_eq { all_rows ; opponent team ; iceland } ; outcome } ; winner } }', 'tointer': 'the outcome record of the first row is winner . the outcome record of the second row is winner .'}], 'result': True, 'ind': 8, 'tostr': 'and { eq { hop { filter_eq { all_rows ; opponent team ; latvia } ; outcome } ; hop { filter_eq { all_rows ; opponent team ; iceland } ; outcome } } ; and { eq { hop { filter_eq { all_rows ; opponent team ; latvia } ; outcome } ; winner } ; eq { hop { filter_eq { all_rows ; opponent team ; iceland } ; outcome } ; winner } } } = true', 'tointer': 'select the rows whose opponent team record fuzzily matches to latvia . take the outcome record of this row . select the rows whose opponent team record fuzzily matches to iceland . take the outcome record of this row . the first record fuzzily matches to the second record . the outcome record of the first row is winner . the outcome record of the second row is winner .'} | and { eq { hop { filter_eq { all_rows ; opponent team ; latvia } ; outcome } ; hop { filter_eq { all_rows ; opponent team ; iceland } ; outcome } } ; and { eq { hop { filter_eq { all_rows ; opponent team ; latvia } ; outcome } ; winner } ; eq { hop { filter_eq { all_rows ; opponent team ; iceland } ; outcome } ; winner } } } = true | select the rows whose opponent team record fuzzily matches to latvia . take the outcome record of this row . select the rows whose opponent team record fuzzily matches to iceland . take the outcome record of this row . the first record fuzzily matches to the second record . the outcome record of the first row is winner . the outcome record of the second row is winner . | 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, 'opponent team_11': 11, 'latvia_12': 12, 'outcome_13': 13, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_14': 14, 'opponent team_15': 15, 'iceland_16': 16, 'outcome_17': 17, 'and_7': 7, 'str_eq_5': 5, 'winner_18': 18, 'str_eq_6': 6, 'winner_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', 'opponent team_11': 'opponent team', 'latvia_12': 'latvia', 'outcome_13': 'outcome', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_14': 'all_rows', 'opponent team_15': 'opponent team', 'iceland_16': 'iceland', 'outcome_17': 'outcome', 'and_7': 'and', 'str_eq_5': 'str_eq', 'winner_18': 'winner', 'str_eq_6': 'str_eq', 'winner_19': 'winner'} | {'and_8': [9], 'result_9': [], 'str_eq_4': [8], 'str_hop_2': [4, 5], 'filter_str_eq_0': [2], 'all_rows_10': [0], 'opponent team_11': [0], 'latvia_12': [0], 'outcome_13': [2], 'str_hop_3': [4, 6], 'filter_str_eq_1': [3], 'all_rows_14': [1], 'opponent team_15': [1], 'iceland_16': [1], 'outcome_17': [3], 'and_7': [8], 'str_eq_5': [7], 'winner_18': [5], 'str_eq_6': [7], 'winner_19': [6]} | ['outcome', 'edition', 'opponent team', 'surface', 'opponent', 'score'] | [['winner', '2008 europe / africa group iiia', 'mauritius', 'clay', 'astrid tixier', '6 - 1 , 6 - 2'], ['winner', '2008 europe / africa group iiia', 'zimbabwe', 'clay', 'denise atzinger', '6 - 0 , 6 - 0'], ['winner', '2008 europe / africa group iiia', 'latvia', 'clay', 'trīna šlapeka', '6 - 1 , 6 - 3'], ['winner', '2008 europe / africa group iiia', 'iceland', 'clay', 'rebekka pétursdóttir', '6 - 0 , 6 - 0'], ['winner', '2009 europe / africa group iiib', 'liechtenstein', 'hard', 'kathinka von deichmann', '6 - 1 , 6 - 4'], ['winner', '2009 europe / africa group iiib', 'iceland', 'hard', 'sandra kristjánsdóttir', '6 - 0 , 6 - 1'], ['loser', '2009 europe / africa group iiib', 'armenia', 'hard', 'anna movsisyan', '6 - 4 , 6 - 1'], ['winner', '2009 europe / africa group iiib', 'moldova', 'hard', 'olga terteac', '6 - 1 , 6 - 2'], ['winner', '2009 europe / africa group iiib', 'egypt', 'hard', 'may el wardany', '6 - 0 , 6 - 0'], ['loser', '2010 europe / africa group iib', 'armenia', 'clay', 'ani amiraghyan', '4 - 6 , 6 - 3 , 6 - 2'], ['loser', '2010 europe / africa group iib', 'finland', 'clay', 'emma laine', '6 - 1 , 6 - 2'], ['loser', '2010 europe / africa group iib', 'georgia', 'clay', 'anna tatishvili', '6 - 2 , 6 - 3'], ['loser', '2010 europe / africa group ii playoff', 'liechtenstein', 'clay', 'stephanie vogt', '6 - 4 , 7 - 5'], ['winner', '2011 europe / africa group iiib', 'ireland', 'clay', 'julia moriarty', '6 - 4 , 6 - 1'], ['winner', '2011 europe / africa group iiib', 'moldova', 'clay', 'julia helbet', '1 - 6 , 7 - 5 , 6 - 3'], ['winner', '2011 europe / africa group iiib', 'tunisia', 'clay', 'ons jabeur', '7 - 6 ( 7 - 3 ) , 6 - 4']] |
2003 bradford bulls season | https://en.wikipedia.org/wiki/2003_Bradford_Bulls_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10814478-6.html.csv | majority | all of the games resulted in wins for the bradford bulls . | {'scope': 'all', 'col': '4', 'most_or_all': 'all', 'criterion': 'fuzzily_match', 'value': 'w', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'result', 'w'], 'result': True, 'ind': 0, 'tointer': 'for the result records of all rows , all of them fuzzily match to w .', 'tostr': 'all_eq { all_rows ; result ; w } = true'} | all_eq { all_rows ; result ; w } = true | for the result records of all rows , all of them fuzzily match to w . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'result_3': 3, 'w_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'result_3': 'result', 'w_4': 'w'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'result_3': [0], 'w_4': [0]} | ['date', 'competition', 'venue', 'result', 'score', 'goals'] | [['8 / 2 / 03', 'cup', 'wilderspool', 'w', '38 - 12', 'deacon 7 / 7'], ['2 / 3 / 03', 'cup', 'south leeds stadium', 'w', '82 - 0', 'deacon 11 / 15'], ['15 / 3 / 03', 'cup', 'halton stadium', 'w', '38 - 28', 'deacon 7 / 7'], ['13 / 4 / 03', 'cup', 'mcalpine stadium', 'w', '36 - 22', 'deacon 6 / 6'], ['26 / 4 / 03', 'cup', 'millennium stadium', 'w', '22 - 20', 'deacon 5 / 5']] |
2007 - 08 english premiership ( rugby union ) | https://en.wikipedia.org/wiki/2007%E2%80%9308_English_Premiership_%28rugby_union%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10234157-2.html.csv | aggregation | looking at the top scorers from the 2007 - 08 english premiership ( rugby union ) , the average number of points they made in the season was around 158 points . | {'scope': 'all', 'col': '1', 'type': 'average', 'result': '158', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'points'], 'result': '158', 'ind': 0, 'tostr': 'avg { all_rows ; points }'}, '158'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; points } ; 158 } = true', 'tointer': 'the average of the points record of all rows is 158 .'} | round_eq { avg { all_rows ; points } ; 158 } = true | the average of the points record of all rows is 158 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'points_4': 4, '158_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'points_4': 'points', '158_5': '158'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'points_4': [0], '158_5': [1]} | ['points', 'name', 'club', 'tries', 'drop'] | [['207', 'andy goode', 'leicester tigers', '1', '4'], ['201', 'charlie hodgson', 'sale sharks', '0', '9'], ['192', 'danny cipriani', 'london wasps', '6', '0'], ['179', 'glen jackson', 'saracens', '2', '2'], ['178', 'olly barkley', 'bath rugby', '3', '0'], ['152', 'ryan lamb', 'gloucester rugby', '4', '1'], ['127', 'alberto di bernardo', 'leeds carnegie', '0', '5'], ['118', 'shane drahm', 'worcester warriors', '1', '1'], ['115', 'adrian jarvis', 'harlequins', '0', '0'], ['107', 'chris malone', 'harlequins', '2', '2']] |
2008 - 09 sacramento kings season | https://en.wikipedia.org/wiki/2008%E2%80%9309_Sacramento_Kings_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17102076-7.html.csv | count | brad miller had two high points performances for the sacramento kings . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'brad miller', 'result': '2', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'high points', 'brad miller'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose high points record fuzzily matches to brad miller .', 'tostr': 'filter_eq { all_rows ; high points ; brad miller }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; high points ; brad miller } }', 'tointer': 'select the rows whose high points record fuzzily matches to brad miller . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; high points ; brad miller } } ; 2 } = true', 'tointer': 'select the rows whose high points record fuzzily matches to brad miller . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; high points ; brad miller } } ; 2 } = true | select the rows whose high points record fuzzily matches to brad miller . 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, 'high points_5': 5, 'brad miller_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', 'high points_5': 'high points', 'brad miller_6': 'brad miller', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'high points_5': [0], 'brad miller_6': [0], '2_7': [2]} | ['game', 'date', 'team', 'score', 'high points', 'high assists', 'location attendance', 'record'] | [['33', 'january 2', 'detroit', 'l 92 - 98 ( ot )', 'brad miller ( 25 )', 'john salmons ( 4 )', 'the palace of auburn hills 22076', '8 - 25'], ['34', 'january 3', 'indiana', 'l 117 - 122 ( ot )', 'kevin martin ( 45 )', 'kevin martin , brad miller ( 6 )', 'conseco fieldhouse 12765', '8 - 26'], ['35', 'january 5', 'new jersey', 'l 90 - 98 ( ot )', 'kevin martin ( 36 )', 'brad miller ( 8 )', 'izod center 12314', '8 - 27'], ['36', 'january 6', 'chicago', 'l 94 - 99 ( ot )', 'kevin martin ( 29 )', 'beno udrih ( 5 )', 'united center 18060', '8 - 28'], ['37', 'january 9', 'miami', 'l 115 - 119 ( ot )', 'john salmons ( 29 )', 'john salmons , brad miller , bobby jackson ( 4 )', 'arco arena 12587', '8 - 29'], ['38', 'january 11', 'dallas', 'w 102 - 95 ( ot )', 'kevin martin ( 21 )', 'beno udrih ( 6 )', 'arco arena 12294', '9 - 29'], ['39', 'january 13', 'orlando', 'l 107 - 139 ( ot )', 'kevin martin ( 30 )', 'francisco garcía ( 5 )', 'arco arena 11168', '9 - 30'], ['40', 'january 14', 'golden state', 'w 135 - 133 ( 3ot )', 'brad miller ( 30 )', 'john salmons , beno udrih ( 7 )', 'oracle arena 19122', '10 - 30'], ['41', 'january 16', 'milwaukee', 'l 122 - 129 ( ot )', 'john salmons , kevin martin ( 24 )', 'john salmons ( 6 )', 'arco arena 11663', '10 - 31'], ['42', 'january 20', 'denver', 'l 99 - 118 ( ot )', 'kevin martin ( 25 )', 'john salmons , beno udrih ( 5 )', 'pepsi center 15164', '10 - 32'], ['43', 'january 21', 'washington', 'l 107 - 110 ( ot )', 'john salmons , beno udrih ( 24 )', 'john salmons ( 5 )', 'arco arena 10821', '10 - 33'], ['44', 'january 24', 'milwaukee', 'l 104 - 106 ( ot )', 'kevin martin ( 20 )', 'brad miller ( 9 )', 'bradley center 15379', '10 - 34'], ['45', 'january 25', 'toronto', 'l 97 - 113 ( ot )', 'john salmons ( 21 )', 'beno udrih ( 5 )', 'air canada centre 18127', '10 - 35'], ['46', 'january 27', 'cleveland', 'l 110 - 117 ( ot )', 'kevin martin ( 35 )', 'kevin martin ( 7 )', 'quicken loans arena 20562', '10 - 36'], ['47', 'january 28', 'boston', 'l 100 - 119 ( ot )', 'john salmons ( 22 )', 'john salmons ( 5 )', 'td banknorth garden 18624', '10 - 37'], ['48', 'january 30', 'chicago', 'l 88 - 109 ( ot )', 'kevin martin ( 27 )', 'spencer hawes , kevin martin ( 3 )', 'arco arena 13356', '10 - 38']] |
1992 pga championship | https://en.wikipedia.org/wiki/1992_PGA_Championship | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18121795-2.html.csv | aggregation | the members of the 1992 pga championship scored an average of 152.8 total points . | {'scope': 'all', 'col': '4', 'type': 'average', 'result': '152.8', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'total'], 'result': '152.8', 'ind': 0, 'tostr': 'avg { all_rows ; total }'}, '152.8'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; total } ; 152.8 } = true', 'tointer': 'the average of the total record of all rows is 152.8 .'} | round_eq { avg { all_rows ; total } ; 152.8 } = true | the average of the total record of all rows is 152.8 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'total_4': 4, '152.8_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'total_4': 'total', '152.8_5': '152.8'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'total_4': [0], '152.8_5': [1]} | ['player', 'country', 'year ( s ) won', 'total', 'to par'] | [['jack nicklaus', 'united states', '1963 , 1971 , 1973 1975 , 1980', '150', '+ 8'], ['wayne grady', 'australia', '1990', '152', '+ 10'], ['john mahaffey', 'united states', '1978', '153', '+ 11'], ['hubert green', 'united states', '1985', '154', '+ 12'], ['hal sutton', 'united states', '1983', '155', '+ 13']] |
emilio sánchez | https://en.wikipedia.org/wiki/Emilio_S%C3%A1nchez | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1800323-5.html.csv | majority | most of emilio sánchez 's tournaments were played on clay surfaces . | {'scope': 'all', 'col': '3', '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]} | ['date', 'tournament', 'surface', 'opponent in final', 'score in final'] | [['21 april 1986', 'nice , france', 'clay', 'paul mcnamee', '6 - 1 , 6 - 3'], ['12 may 1986', 'munich , west germany', 'clay', 'ricki osterthun', '6 - 1 , 6 - 3'], ['28 july 1986', 'båstad , sweden', 'clay', 'mats wilander', '7 - 6 ( 5 ) , 4 - 6 , 6 - 4'], ['13 july 1987', 'gstaad , switzerland', 'clay', 'ronald agénor', '6 - 2 , 6 - 3 , 7 - 6 ( 5 )'], ['20 july 1987', 'bordeaux , france', 'clay', 'ronald agénor', '5 - 7 , 6 - 4 , 6 - 4'], ['10 august 1987', 'kitzbühel , austria', 'clay', 'miloslav mečíř', '6 - 4 , 6 - 1 , 4 - 6 , 6 - 1'], ['21 september 1987', 'madrid , spain', 'clay', 'javier sánchez', '6 - 3 , 3 - 6 , 6 - 2'], ['1 august 1988', 'hilversum , netherlands', 'clay', 'guillermo pérez - roldán', '6 - 3 , 6 - 1 , 3 - 6 , 6 - 3'], ['7 august 1989', 'kitzbühel , austria', 'clay', 'martín jaite', '7 - 6 ( 1 ) , 6 - 1 , 2 - 6 , 6 - 2'], ['8 january 1990', 'wellington , new zealand', 'hard', 'richey reneberg', '6 - 7 ( 3 ) , 6 - 4 , 4 - 6 , 6 - 4 , 6 - 1'], ['9 april 1990', 'estoril , portugal', 'clay', 'franco davín', '6 - 3 , 6 - 1'], ['15 april 1991', 'barcelona , spain', 'clay', 'sergi bruguera', '6 - 4 , 7 - 6 ( 7 ) , 6 - 2'], ['20 may 1991', 'rome , italy', 'clay', 'alberto mancini', '6 - 3 , 6 - 1 , 3 - 0 , ret'], ['15 july 1991', 'gstaad , switzerland', 'clay', 'sergi bruguera', '6 - 1 , 6 - 4 , 6 - 4'], ['13 january 1992', 'sydney outdoor , australia', 'hard', 'guy forget', '6 - 3 , 6 - 4']] |
2009 - 10 english premiership ( rugby union ) | https://en.wikipedia.org/wiki/2009%E2%80%9310_English_Premiership_%28rugby_union%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-23909238-2.html.csv | majority | the majority of the clubs had a least one drawn game . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'greater_than_eq', 'value': '1', 'subset': None} | {'func': 'most_greater_eq', 'args': ['all_rows', 'drawn', '1'], 'result': True, 'ind': 0, 'tointer': 'for the drawn records of all rows , most of them are greater than or equal to 1 .', 'tostr': 'most_greater_eq { all_rows ; drawn ; 1 } = true'} | most_greater_eq { all_rows ; drawn ; 1 } = true | for the drawn records of all rows , most of them are greater than or equal to 1 . | 1 | 1 | {'most_greater_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'drawn_3': 3, '1_4': 4} | {'most_greater_eq_0': 'most_greater_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'drawn_3': 'drawn', '1_4': '1'} | {'most_greater_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'drawn_3': [0], '1_4': [0]} | ['', 'club', 'played', 'won', 'drawn', 'lost', 'points for', 'points against', 'points difference', 'tries for', 'tries against', 'try bonus', 'losing bonus', 'points'] | [['1', 'leicester tigers ( c )', '22', '15', '1', '6', '541', '325', '216', '46', '18', '7', '4', '73'], ['2', 'northampton saints ( sf )', '22', '16', '0', '6', '472', '322', '150', '44', '26', '2', '5', '71'], ['3', 'saracens ( f )', '22', '15', '1', '6', '480', '367', '113', '39', '22', '2', '5', '69'], ['4', 'bath ( sf )', '22', '12', '2', '8', '450', '366', '84', '49', '33', '5', '4', '61'], ['5', 'london wasps', '22', '13', '0', '9', '394', '399', '5', '35', '31', '2', '3', '57'], ['6', 'london irish', '22', '10', '3', '9', '469', '384', '85', '42', '33', '3', '3', '52'], ['7', 'gloucester', '22', '10', '1', '11', '470', '457', '13', '46', '42', '2', '4', '48'], ['8', 'harlequins', '22', '9', '2', '11', '420', '484', '64', '42', '46', '3', '3', '46'], ['9', 'newcastle falcons', '22', '6', '4', '12', '319', '431', '112', '20', '41', '1', '4', '37'], ['10', 'leeds carnegie', '22', '7', '1', '14', '283', '493', '210', '17', '48', '0', '6', '36'], ['11', 'sale sharks', '22', '6', '1', '15', '333', '495', '162', '24', '51', '0', '6', '32']] |
list of married ... with children episodes | https://en.wikipedia.org/wiki/List_of_Married..._with_Children_episodes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2226817-2.html.csv | count | 9 of the episodes of married with children were directed by linda day . | {'scope': 'all', 'criterion': 'equal', 'value': 'linda day', 'result': '9', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'directed by', 'linda day'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose directed by record fuzzily matches to linda day .', 'tostr': 'filter_eq { all_rows ; directed by ; linda day }'}], 'result': '9', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; directed by ; linda day } }', 'tointer': 'select the rows whose directed by record fuzzily matches to linda day . the number of such rows is 9 .'}, '9'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; directed by ; linda day } } ; 9 } = true', 'tointer': 'select the rows whose directed by record fuzzily matches to linda day . the number of such rows is 9 .'} | eq { count { filter_eq { all_rows ; directed by ; linda day } } ; 9 } = true | select the rows whose directed by record fuzzily matches to linda day . the number of such rows is 9 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'directed by_5': 5, 'linda day_6': 6, '9_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'directed by_5': 'directed by', 'linda day_6': 'linda day', '9_7': '9'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'directed by_5': [0], 'linda day_6': [0], '9_7': [2]} | ['no in series', 'title', 'directed by', 'written by', 'original air date', 'production code'] | [['1', 'pilot', 'linda day', 'ron leavitt & michael g moye', 'april 5 , 1987', '1.01'], ['2', 'thinergy', 'linda day', 'ron leavitt & michael g moye', 'april 12 , 1987', '1.02'], ['3', "but i did n't shoot the deputy", 'linda day', 'ron burla', 'april 19 , 1987', '1.03'], ['4', 'whose room is it anyway', 'zane buzby', 'marcy vosburgh & sandy sprung', 'april 26 , 1987', '1.04'], ['5', 'have you driven a ford lately', 'linda day', 'richard gurman & katherine green', 'may 3 , 1987', '1.05'], ['6', 'sixteen years and what do you get', 'linda day', 'katherine green & richard gurman', 'may 10 , 1987', '1.06'], ['7', 'married without children', 'linda day', 'ralph r farquhar', 'may 17 , 1987', '1.07'], ['8', 'the poker game', 'brian levant', 'ron leavitt & michael g moye', 'may 24 , 1987', '1.08'], ['9', 'peggy sue got work', 'linda day', 'ellen l fogle', 'may 31 , 1987', '1.09'], ['10', 'al loses his cherry', 'arlando smith', 'marcy vosburgh & sandy sprung', 'june 7 , 1987', '1.10'], ['11', "nightmare on al 's street", 'linda day', 'michael g moye', 'june 14 , 1987', '1.11'], ['12', "where 's the boss", 'linda day', 'marcy vosburgh & sandy sprung', 'june 21 , 1987', '1.12']] |
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/2-11677760-7.html.csv | majority | both students from north carolina were never drafted to the nba . | {'scope': 'subset', 'col': '6', 'most_or_all': 'all', 'criterion': 'fuzzily_match', 'value': 'undrafted', 'subset': {'col': '5', 'criterion': 'equal', 'value': 'north carolina'}} | {'func': 'all_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'college', 'north carolina'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; college ; north carolina }', 'tointer': 'select the rows whose college record fuzzily matches to north carolina .'}, 'nba draft', 'undrafted'], 'result': True, 'ind': 1, 'tointer': 'select the rows whose college record fuzzily matches to north carolina . for the nba draft records of these rows , all of them fuzzily match to undrafted .', 'tostr': 'all_eq { filter_eq { all_rows ; college ; north carolina } ; nba draft ; undrafted } = true'} | all_eq { filter_eq { all_rows ; college ; north carolina } ; nba draft ; undrafted } = true | select the rows whose college record fuzzily matches to north carolina . for the nba draft records of these rows , all of them fuzzily match to undrafted . | 2 | 2 | {'all_str_eq_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, 'college_4': 4, 'north carolina_5': 5, 'nba draft_6': 6, 'undrafted_7': 7} | {'all_str_eq_1': 'all_str_eq', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'college_4': 'college', 'north carolina_5': 'north carolina', 'nba draft_6': 'nba draft', 'undrafted_7': 'undrafted'} | {'all_str_eq_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'college_4': [0], 'north carolina_5': [0], 'nba draft_6': [1], 'undrafted_7': [1]} | ['player', 'height', 'school', 'hometown', 'college', 'nba draft'] | [['danny ferry', '6 - 10', 'dematha catholic high school', 'hyattsville , md', 'duke', '1st round - 2nd pick of 1989 draft ( clippers )'], ['tito horford', '7 - 1', 'marian christian high school', 'houston , tx', 'lsu / miami ( fl )', '2nd round - 39th pick of 1988 draft ( bucks )'], ['tony kimbro', '6 - 8', 'seneca high school', 'louisville , ky', 'louisville', 'undrafted in 1989 nba draft'], ['jeff lebo', '6 - 3', 'carlisle high school', 'carlisle , pa', 'north carolina', 'undrafted in 1989 nba draft'], ['kevin madden', '6 - 6', 'robert e lee high school', 'staunton , va', 'north carolina', 'undrafted in 1990 nba draft']] |
david brabham | https://en.wikipedia.org/wiki/David_Brabham | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1148454-4.html.csv | ordinal | out of the races that david brabham participated in from 1992 to 2012 , david and his team drove the second-highest total amount of laps in his race in 2003 . | {'row': '10', 'col': '5', 'order': '2', 'col_other': '1', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'laps', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; laps ; 2 }'}, 'year'], 'result': '2003', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; laps ; 2 } ; year }'}, '2003'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; laps ; 2 } ; year } ; 2003 } = true', 'tointer': 'select the row whose laps record of all rows is 2nd maximum . the year record of this row is 2003 .'} | eq { hop { nth_argmax { all_rows ; laps ; 2 } ; year } ; 2003 } = true | select the row whose laps record of all rows is 2nd maximum . the year record of this row is 2003 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'num_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'laps_5': 5, '2_6': 6, 'year_7': 7, '2003_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'num_hop_1': 'num_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'laps_5': 'laps', '2_6': '2', 'year_7': 'year', '2003_8': '2003'} | {'eq_2': [3], 'result_3': [], 'num_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'laps_5': [0], '2_6': [0], 'year_7': [1], '2003_8': [2]} | ['year', 'team', 'co - drivers', 'class', 'laps', 'pos', 'class pos'] | [['1992', "toyota team tom 's", 'geoff lees ukyo katayama', 'c1', '192', 'dnf', 'dnf'], ['1993', 'twr jaguar racing', 'john nielsen david coulthard', 'gt', '306', 'dsq', 'dsq'], ['1996', 'gulf racing gtc racing', 'pierre - henri raphanel lindsay owen - jones', 'gt1', '335', '5th', '4th'], ['1997', 'david price racing', 'perry mccarthy doc bundy', 'gt1', '145', 'dnf', 'dnf'], ['1998', 'panoz motorsports', 'andy wallace jamie davies', 'gt1', '335', '7th', '7th'], ['1999', 'panoz motorsports', 'éric bernard butch leitzinger', 'lmp', '336', '7th', '6th'], ['2000', 'panoz motorsports', 'jan magnussen mario andretti', 'lmp900', '315', '15th', '8th'], ['2001', 'panoz motorsports', 'jan magnussen franck lagorce', 'lmp900', '85', 'dnf', 'dnf'], ['2002', 'panoz motor sports', 'jan magnussen bryan herta', 'lmp900', '90', 'dnf', 'dnf'], ['2003', 'team bentley', 'mark blundell johnny herbert', 'lmgtp', '375', '2nd', '2nd'], ['2004', 'zytek engineering , ltd', 'andy wallace hayanari shimoda', 'lmp1', '167', 'dnf', 'dnf'], ['2005', 'aston martin racing', 'stéphane sarrazin darren turner', 'gt1', '333', '9th', '3rd'], ['2006', 'russian age racing team modena', 'antonio garcía nelson piquet , jr', 'gt1', '343', '9th', '4th'], ['2007', 'aston martin racing', 'darren turner rickard rydell', 'gt1', '343', '5th', '1st'], ['2008', 'aston martin racing', 'antonio garcía darren turner', 'gt1', '344', '13th', '1st'], ['2009', 'peugeot sport total', 'marc gené alexander wurz', 'lmp1', '382', '1st', '1st'], ['2010', 'highcroft racing', 'marino franchitti marco werner', 'lmp2', '296', '25th', '9th'], ['2012', 'jrm', 'peter dumbreck karun chandhok', 'lmp1', '357', '6th', '6th']] |
1983 senior pga tour | https://en.wikipedia.org/wiki/1983_Senior_PGA_Tour | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11622862-1.html.csv | count | three of the tournaments for the 1983 senior pga tour were held in florida . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'florida', 'result': '3', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location', 'florida'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose location record fuzzily matches to florida .', 'tostr': 'filter_eq { all_rows ; location ; florida }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; location ; florida } }', 'tointer': 'select the rows whose location record fuzzily matches to florida . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; location ; florida } } ; 3 } = true', 'tointer': 'select the rows whose location record fuzzily matches to florida . the number of such rows is 3 .'} | eq { count { filter_eq { all_rows ; location ; florida } } ; 3 } = true | select the rows whose location record fuzzily matches to florida . the number of such rows is 3 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'location_5': 5, 'florida_6': 6, '3_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'location_5': 'location', 'florida_6': 'florida', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'location_5': [0], 'florida_6': [0], '3_7': [2]} | ['date', 'tournament', 'location', 'purse', 'winner', 'score', '1st prize'] | [['mar 20', 'greater daytona senior classic', 'florida', '150000', 'gene littler ( 1 )', '203 ( - 13 )', '25000'], ['may 22', 'hall of fame tournament', 'north carolina', '150000', 'rod funseth ( 1 )', '198 ( - 18 )', '25000'], ['jun 5', 'gatlin brothers seniors golf classic', 'nevada', '200000', 'don january ( 6 )', '208 ( - 8 )', '33500'], ['jun 12', 'senior tournament players championship', 'ohio', '250000', 'miller barber ( 7 )', '278 ( - 10 )', '40000'], ['jun 26', 'peter jackson champions', 'canada', '200000', 'don january ( 7 )', '274 ( - 10 )', '33250'], ['jul 3', 'marlboro classic', 'massachusetts', '150000', 'don january ( 8 )', '273 ( - 11 )', '25000'], ['jul 10', "greater syracuse senior 's pro classic", 'new york', '150000', 'gene littler ( 2 )', '275 ( - 9 )', '25000'], ['jul 17', 'merrill lynch / golf digest commemorative pro - am', 'rhode island', '150000', 'miller barber ( 8 )', '200 ( - 16 )', '25000'], ['jul 25', 'us senior open', 'minnesota', '175000', 'billy casper ( 3 )', '288 ( 4 )', '30566'], ['aug 21', 'denver post champions of golf', 'colorado', '150000', 'don january ( 9 )', '271 ( - 17 )', '25000'], ['sep 4', 'citizens union senior golf classic', 'kentucky', '150000', 'don january ( 10 )', '269 ( - 19 )', '25000'], ['sep 25', 'world seniors invitational', 'north carolina', '152000', 'doug sanders ( 1 )', '283 ( - 5 )', '25000'], ['oct 2', 'united virginia bank seniors', 'virginia', '150000', 'miller barber ( 9 )', '211 ( - 5 )', '25000'], ['oct 16', 'suntree classic', 'florida', '135000', 'don january ( 11 )', '274 ( - 14 )', '22500'], ['oct 23', 'hilton head seniors international', 'south carolina', '150000', 'miller barber ( 10 )', '281 ( - 7 )', '25000'], ['dec 4', 'boca grove seniors classic', 'florida', '150000', 'arnold palmer ( 5 )', '271 ( - 17 )', '25000']] |
tony lema | https://en.wikipedia.org/wiki/Tony_Lema | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1570274-4.html.csv | comparative | tony lema finished in the top 25 more times in the masters tournament than in the pga championship . | {'row_1': '1', 'row_2': '4', 'col': '5', 'col_other': '1', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'tournament', 'masters tournament'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose tournament record fuzzily matches to masters tournament .', 'tostr': 'filter_eq { all_rows ; tournament ; masters tournament }'}, 'top - 25'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; tournament ; masters tournament } ; top - 25 }', 'tointer': 'select the rows whose tournament record fuzzily matches to masters tournament . take the top - 25 record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'tournament', 'pga championship'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose tournament record fuzzily matches to pga championship .', 'tostr': 'filter_eq { all_rows ; tournament ; pga championship }'}, 'top - 25'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; tournament ; pga championship } ; top - 25 }', 'tointer': 'select the rows whose tournament record fuzzily matches to pga championship . take the top - 25 record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; tournament ; masters tournament } ; top - 25 } ; hop { filter_eq { all_rows ; tournament ; pga championship } ; top - 25 } } = true', 'tointer': 'select the rows whose tournament record fuzzily matches to masters tournament . take the top - 25 record of this row . select the rows whose tournament record fuzzily matches to pga championship . take the top - 25 record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; tournament ; masters tournament } ; top - 25 } ; hop { filter_eq { all_rows ; tournament ; pga championship } ; top - 25 } } = true | select the rows whose tournament record fuzzily matches to masters tournament . take the top - 25 record of this row . select the rows whose tournament record fuzzily matches to pga championship . take the top - 25 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, 'tournament_7': 7, 'masters tournament_8': 8, 'top - 25_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'tournament_11': 11, 'pga championship_12': 12, 'top - 25_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', 'tournament_7': 'tournament', 'masters tournament_8': 'masters tournament', 'top - 25_9': 'top - 25', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'tournament_11': 'tournament', 'pga championship_12': 'pga championship', 'top - 25_13': 'top - 25'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'tournament_7': [0], 'masters tournament_8': [0], 'top - 25_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'tournament_11': [1], 'pga championship_12': [1], 'top - 25_13': [3]} | ['tournament', 'wins', 'top - 5', 'top - 10', 'top - 25', 'events', 'cuts made'] | [['masters tournament', '0', '1', '2', '4', '4', '4'], ['us open', '0', '2', '3', '4', '6', '5'], ['the open championship', '1', '2', '2', '2', '3', '3'], ['pga championship', '0', '0', '1', '2', '5', '4'], ['totals', '1', '5', '8', '12', '18', '16']] |
1960 vfl season | https://en.wikipedia.org/wiki/1960_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10775890-6.html.csv | comparative | the attendance at the mcg was higher than the attendance at lake oval . | {'row_1': '1', 'row_2': '5', 'col': '6', 'col_other': '5', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'venue', 'mcg'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose venue record fuzzily matches to mcg .', 'tostr': 'filter_eq { all_rows ; venue ; mcg }'}, 'crowd'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; venue ; mcg } ; crowd }', 'tointer': 'select the rows whose venue record fuzzily matches to mcg . take the crowd record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'venue', 'lake oval'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose venue record fuzzily matches to lake oval .', 'tostr': 'filter_eq { all_rows ; venue ; lake oval }'}, 'crowd'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; venue ; lake oval } ; crowd }', 'tointer': 'select the rows whose venue record fuzzily matches to lake oval . take the crowd record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; venue ; mcg } ; crowd } ; hop { filter_eq { all_rows ; venue ; lake oval } ; crowd } } = true', 'tointer': 'select the rows whose venue record fuzzily matches to mcg . take the crowd record of this row . select the rows whose venue record fuzzily matches to lake oval . take the crowd record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; venue ; mcg } ; crowd } ; hop { filter_eq { all_rows ; venue ; lake oval } ; crowd } } = true | select the rows whose venue record fuzzily matches to mcg . take the crowd record of this row . select the rows whose venue record fuzzily matches to lake oval . take the crowd 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, 'venue_7': 7, 'mcg_8': 8, 'crowd_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'venue_11': 11, 'lake oval_12': 12, 'crowd_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', 'venue_7': 'venue', 'mcg_8': 'mcg', 'crowd_9': 'crowd', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'venue_11': 'venue', 'lake oval_12': 'lake oval', 'crowd_13': 'crowd'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'venue_7': [0], 'mcg_8': [0], 'crowd_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'venue_11': [1], 'lake oval_12': [1], 'crowd_13': [3]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['melbourne', '17.22 ( 124 )', 'richmond', '4.8 ( 32 )', 'mcg', '27249', '28 may 1960'], ['footscray', '6.11 ( 47 )', 'st kilda', '10.5 ( 65 )', 'western oval', '22126', '28 may 1960'], ['north melbourne', '7.6 ( 48 )', 'hawthorn', '9.8 ( 62 )', 'arden street oval', '8600', '28 may 1960'], ['fitzroy', '8.7 ( 55 )', 'essendon', '6.14 ( 50 )', 'brunswick street oval', '25632', '28 may 1960'], ['south melbourne', '12.8 ( 80 )', 'collingwood', '11.12 ( 78 )', 'lake oval', '27000', '28 may 1960'], ['geelong', '17.17 ( 119 )', 'carlton', '10.14 ( 74 )', 'kardinia park', '16589', '28 may 1960']] |
yanina wickmayer | https://en.wikipedia.org/wiki/Yanina_Wickmayer | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15100199-8.html.csv | unique | the tournament on 28 october 2007 was yanina wickmayer 's only carpet surface tournament . | {'scope': 'all', 'row': '7', 'col': '4', 'col_other': '2', 'criterion': 'equal', 'value': 'carpet', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'surface', 'carpet'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose surface record fuzzily matches to carpet .', 'tostr': 'filter_eq { all_rows ; surface ; carpet }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; surface ; carpet } }', 'tointer': 'select the rows whose surface record fuzzily matches to carpet . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'surface', 'carpet'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose surface record fuzzily matches to carpet .', 'tostr': 'filter_eq { all_rows ; surface ; carpet }'}, 'date'], 'result': '28 october 2007', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; surface ; carpet } ; date }'}, '28 october 2007'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; surface ; carpet } ; date } ; 28 october 2007 }', 'tointer': 'the date record of this unqiue row is 28 october 2007 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; surface ; carpet } } ; eq { hop { filter_eq { all_rows ; surface ; carpet } ; date } ; 28 october 2007 } } = true', 'tointer': 'select the rows whose surface record fuzzily matches to carpet . there is only one such row in the table . the date record of this unqiue row is 28 october 2007 .'} | and { only { filter_eq { all_rows ; surface ; carpet } } ; eq { hop { filter_eq { all_rows ; surface ; carpet } ; date } ; 28 october 2007 } } = true | select the rows whose surface record fuzzily matches to carpet . there is only one such row in the table . the date record of this unqiue row is 28 october 2007 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'surface_7': 7, 'carpet_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'date_9': 9, '28 october 2007_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'surface_7': 'surface', 'carpet_8': 'carpet', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'date_9': 'date', '28 october 2007_10': '28 october 2007'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'surface_7': [0], 'carpet_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'date_9': [2], '28 october 2007_10': [3]} | ['outcome', 'date', 'tournament', 'surface', 'opponent', 'score'] | [['runner - up', '14 may 2006', 'edinburgh , united kingdom', 'clay', 'mari andersson', '6 - 0 , 1 - 6 , 3 - 6'], ['winner', '20 august 2006', 'koksijde , belgium', 'clay', 'kristina steiert', '6 - 4 , 6 - 1'], ['winner', '19 november 2006', 'florianópolis , brazil', 'clay', 'estefania craciún', '6 - 1 , 6 - 0'], ['winner', '26 november 2006', 'córdoba , argentina', 'clay', 'teliana pereira', '6 - 1 , 6 - 7 ( 4 - 7 ) , 6 - 0'], ['runner - up', '15 april 2007', 'torhout , belgium', 'hard', 'claire feuerstein', '4 - 6 , 4 - 6'], ['winner', '29 july 2007', 'les contamines , france', 'hard', 'julie coin', '6 - 2 , 7 - 6 ( 7 - 3 )'], ['winner', '28 october 2007', 'hamanako , japan', 'carpet', 'junri namigata', '4 - 6 , 6 - 4 , 6 - 2'], ['runner - up', '4 november 2007', 'taoyuan city , taiwan', 'hard', 'akiko morigami', '4 - 6 , 6 - 7 ( 5 - 7 )'], ['winner', '11 november 2007', 'taizhou , china', 'hard', 'han xinyun', '6 - 2 , 6 - 2'], ['winner', '18 november 2007', 'kunming , china', 'hard', 'urszula radwańska', '7 - 5 , 6 - 4'], ['runner - up', '15 march 2008', 'new delhi , india', 'hard', 'ekaterina dzehalevich', '6 - 2 , 3 - 6 , 2 - 6'], ['runner - up', '13 april 2008', 'monzón , spain', 'hard', 'petra kvitová', '6 - 2 , 4 - 6 , 5 - 7'], ['winner', '11 may 2008', 'indian harbour beach , usa', 'clay', 'bethanie mattek', '6 - 4 , 7 - 5'], ['winner', '22 february 2009', 'surprise , usa', 'hard', 'julia vakulenko', '6 - 7 ( 0 - 7 ) , 6 - 3 , 4 - 3 , retired'], ['runner - up', '1 march 2009', 'clearwater , united states', 'hard', 'julie coin', '6 - 3 , 1 - 1 retired'], ['runner - up', '17 march 2009', 'saint - gaudens , france', 'clay', 'anastasiya yakimova', '5 - 7 , 6 - 7 ( 0 - 7 )'], ['winner', '17 october 2010', 'torhout , belgium', 'hard', 'simona halep', '6 - 3 , 6 - 2']] |
2007 - 08 chelsea f.c. season | https://en.wikipedia.org/wiki/2007%E2%80%9308_Chelsea_F.C._season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11927320-3.html.csv | superlative | the uefa champions league had the latest last match of any of the competitions . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '3', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'last match'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; last match }'}, 'competition'], 'result': 'uefa champions league', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; last match } ; competition }'}, 'uefa champions league'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; last match } ; competition } ; uefa champions league } = true', 'tointer': 'select the row whose last match record of all rows is maximum . the competition record of this row is uefa champions league .'} | eq { hop { argmax { all_rows ; last match } ; competition } ; uefa champions league } = true | select the row whose last match record of all rows is maximum . the competition record of this row is uefa champions league . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'last match_5': 5, 'competition_6': 6, 'uefa champions league_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'last match_5': 'last match', 'competition_6': 'competition', 'uefa champions league_7': 'uefa champions league'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'last match_5': [0], 'competition_6': [1], 'uefa champions league_7': [2]} | ['competition', 'current position / round', 'final position / round', 'first match', 'last match'] | [['fa community shield', '-', 'runner - up', '5 aug 2007', '5 aug 2007'], ['premier league', '-', 'runner - up', '12 aug 2007', '11 may 2008'], ['uefa champions league', '-', 'runner - up', '18 sep 2007', '21 may 2008'], ['football league cup', '-', 'runner - up', '24 sep 2007', '24 feb 2008'], ['fa cup', '-', 'quarter - finals', '5 jan 2008', '3 mar 2008']] |
jake o'brien | https://en.wikipedia.org/wiki/Jake_O%27Brien | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15985163-2.html.csv | majority | jake o'brien has won most of his fights . | {'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'] | [['win', '15 - 4', 'miodrag petković', 'decision ( unanimous )', 'flawless fighting championship 1 : the beginning', '3'], ['win', '14 - 4', 'james shaw', 'submission ( arm - triangle choke )', 'indy mma', '1'], ['loss', '13 - 4', 'gegard mousasi', 'submission ( guillotine choke )', 'dream 15', '1'], ['win', '13 - 3', 'toni valtonen', 'decision ( unanimous )', 'fight festival 27', '3'], ['win', '12 - 3', 'dave hess', 'submission ( kimura )', 'mma big show - triple threat', '2'], ['loss', '11 - 3', 'jon jones', 'submission ( guillotine choke )', 'ufc 100', '2'], ['win', '11 - 2', 'christian wellisch', 'decision ( split )', 'ufc 94', '3'], ['loss', '10 - 2', 'cain velasquez', 'tko ( punches )', 'ufc : silva vs irvin', '1'], ['loss', '10 - 1', 'andrei arlovski', 'tko ( punches )', 'ufc 82', '2'], ['win', '10 - 0', 'heath herring', 'decision ( unanimous )', 'ufc fight night 8', '3'], ['win', '9 - 0', 'josh schockman', 'decision ( unanimous )', 'ufc 65', '3'], ['win', '8 - 0', 'kristof midoux', 'tko ( referee stoppage )', 'ufc fight night 6', '2'], ['win', '7 - 0', 'pat harmon', 'tko', 'ufl - united fight league', '1'], ['win', '6 - 0', 'antoine hayes', 'tko', 'lof - legends of fighting 6', '1'], ['win', '5 - 0', 'jay white', 'ko ( punch )', 'wec 19', '1'], ['win', '4 - 0', 'johnathan ivey', 'tko', 'lof - legends of fighting 4', '1'], ['win', '3 - 0', 'anthony ferguson', 'tko', 'lof - revolution', '1'], ['win', '2 - 0', 'paul bowers', 'tko', 'ifc - integrated fighting classic 3', '1'], ['win', '1 - 0', 'chris clark', 'tko ( referee stoppage )', 'mt - madtown throwdown 3', '1']] |
1990 los angeles raiders season | https://en.wikipedia.org/wiki/1990_Los_Angeles_Raiders_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16376436-4.html.csv | ordinal | the game against denver broncos was the raider 's third highest attended game in the 1990 season . | {'row': '12', 'col': '5', 'order': '3', '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', 'attendance', '3'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; attendance ; 3 }'}, 'opponent'], 'result': 'denver broncos', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; attendance ; 3 } ; opponent }'}, 'denver broncos'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; opponent } ; denver broncos } = true', 'tointer': 'select the row whose attendance record of all rows is 3rd maximum . the opponent record of this row is denver broncos .'} | eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; opponent } ; denver broncos } = true | select the row whose attendance record of all rows is 3rd maximum . the opponent record of this row is denver broncos . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'attendance_5': 5, '3_6': 6, 'opponent_7': 7, 'denver broncos_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'attendance_5': 'attendance', '3_6': '3', 'opponent_7': 'opponent', 'denver broncos_8': 'denver broncos'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'attendance_5': [0], '3_6': [0], 'opponent_7': [1], 'denver broncos_8': [2]} | ['week', 'date', 'opponent', 'result', 'attendance'] | [['1', 'september 9 , 1990', 'denver broncos', 'w 14 - 9', '54206'], ['2', 'september 16 , 1990', 'seattle seahawks', 'w 17 - 13', '61889'], ['3', 'september 23 , 1990', 'pittsburgh steelers', 'w 20 - 3', '50657'], ['4', 'september 30 , 1990', 'chicago bears', 'w 24 - 10', '80156'], ['5', 'october 7 , 1990', 'buffalo bills', 'l 38 - 24', '80076'], ['6', 'october 14 , 1990', 'seattle seahawks', 'w 24 - 17', '50624'], ['7', 'october 21 , 1990', 'san diego chargers', 'w 24 - 9', '60569'], ['9', 'november 4 , 1990', 'kansas city chiefs', 'l 9 - 7', '70951'], ['10', 'november 11 , 1990', 'green bay packers', 'l 29 - 16', '50855'], ['11', 'november 19 , 1990', 'miami dolphins', 'w 13 - 10', '70553'], ['12', 'november 25 , 1990', 'kansas city chiefs', 'l 27 - 24', '65710'], ['13', 'december 2 , 1990', 'denver broncos', 'w 23 - 20', '74162'], ['14', 'december 10 , 1990', 'detroit lions', 'w 38 - 31', '72190'], ['15', 'december 16 , 1990', 'cincinnati bengals', 'w 24 - 7', '54132'], ['16', 'december 22 , 1990', 'minnesota vikings', 'w 28 - 24', '53899'], ['17', 'december 30 , 1990', 'san diego chargers', 'w 17 - 12', '62593']] |
nissan yd engine | https://en.wikipedia.org/wiki/Nissan_YD_engine | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13964981-1.html.csv | superlative | the vehicle nissan y11 ad van has the least max power 77 ps ( 55 kw ) 4000 rpm . | {'scope': 'all', 'col_superlative': '8', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '2', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmin', 'args': ['all_rows', 'max power'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; max power }'}, 'vehicle'], 'result': 'nissan y11 ad van', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; max power } ; vehicle }'}, 'nissan y11 ad van'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmin { all_rows ; max power } ; vehicle } ; nissan y11 ad van } = true', 'tointer': 'select the row whose max power record of all rows is minimum . the vehicle record of this row is nissan y11 ad van .'} | eq { hop { argmin { all_rows ; max power } ; vehicle } ; nissan y11 ad van } = true | select the row whose max power record of all rows is minimum . the vehicle record of this row is nissan y11 ad van . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'max power_5': 5, 'vehicle_6': 6, 'nissan y11 ad van_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'max power_5': 'max power', 'vehicle_6': 'vehicle', 'nissan y11 ad van_7': 'nissan y11 ad van'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'max power_5': [0], 'vehicle_6': [1], 'nissan y11 ad van_7': [2]} | ['code', 'vehicle', 'year', 'displacement', 'bore', 'stroke', 'cr', 'max power'] | [['yd22dd', 'nissan y11 ad van', '2000 - 2002', '2.2 l ( 2184cc )', '86.0 mm', '94.0 mm', '18:1', '77 ps ( 55 kw ) 4000 rpm'], ['yd22ddt', 'nissan almera n16', '2000 - 2002', '2.2 l ( 2184cc )', '86.0 mm', '94.0 mm', '18:1', '110 ps ( 81 kw ) 4000 rpm'], ['yd22dti', 'nissan x - trail', '2001 - 2007', '2.2 l ( 2184cc )', '86.0 mm', '94.0 mm', '18:1', '136 ps ( 100 kw ) 4000 rpm'], ['yd22ddti', 'nissan almera n16 nissan v10 almera tino', '2003 - 2005', '2.2 l ( 2184cc )', '86.0 mm', '94.0 mm', '16.7:1', '112 ps ( 82 kw ) 4000 rpm 136 ps ( 100 kw ) 4000 rpm'], ['yd22ddti', 'nissan primera p12 nissan almera n16', '2003 - 2005', '2.2 l ( 2184cc )', '86.0 mm', '94.0 mm', '16.7:1', '139 ps ( 102 kw ) 4000 rpm'], ['yd25ddt', 'nissan d22 frontier / navara', '2001 - present', '2.5 l ( 2488cc )', '89.0 mm', '100.0 mm', '18:1', '109 ps ( 80 kw ) 4000 rpm'], ['yd25ddti', 'nissan navara / frontier ( d22 )', '2001 - present', '2.5 l ( 2488cc )', '89.0 mm', '100.0 mm', '18:1', '4000 rpm'], ['yd25ddti high power', 'nissan pathfinder ( r51 ) nissan navara ( d40 )', '2005 - 2009', '2.5 l ( 2488cc )', '89.0 mm', '100.0 mm', '16.5:1', '4000 rpm'], ['yd25ddti high power', 'nissan pathfinder ( r51 ) nissan navara ( d40 )', '2010 - present', '2.5 l ( 2488cc )', '89.0 mm', '100.0 mm', '15:1', '4000 rpm'], ['yd25ddti mid power commonrail', 'nissan navara ( d40 )', '2005 - present', '2.5 l ( 2488cc )', '89.0 mm', '100.0 mm', '16.5:1', '4000 rpm'], ['yd25ddti neo di', 'nissan u30 presage / bassara', '1998 - 2001', '2.5 l ( 2488cc )', '89.0 mm', '100.0 mm', '17.5:1', '150 ps ( 110 kw ) 4000 rpm']] |
78th united states congress | https://en.wikipedia.org/wiki/78th_United_States_Congress | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2159537-3.html.csv | count | among the seats of the 78th congress that remained vacant until the next congress , three had been held by democrats . | {'scope': 'subset', 'criterion': 'fuzzily_match', 'value': '( d )', 'result': '3', 'col': '2', 'subset': {'col': '5', 'criterion': 'equal', 'value': 'vacant until the next congress'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date successor seated', 'vacant until the next congress'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; date successor seated ; vacant until the next congress }', 'tointer': 'select the rows whose date successor seated record fuzzily matches to vacant until the next congress .'}, 'vacator', '( d )'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose date successor seated record fuzzily matches to vacant until the next congress . among these rows , select the rows whose vacator record fuzzily matches to ( d ) .', 'tostr': 'filter_eq { filter_eq { all_rows ; date successor seated ; vacant until the next congress } ; vacator ; ( d ) }'}], 'result': '3', 'ind': 2, 'tostr': 'count { filter_eq { filter_eq { all_rows ; date successor seated ; vacant until the next congress } ; vacator ; ( d ) } }', 'tointer': 'select the rows whose date successor seated record fuzzily matches to vacant until the next congress . among these rows , select the rows whose vacator record fuzzily matches to ( d ) . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_eq { filter_eq { all_rows ; date successor seated ; vacant until the next congress } ; vacator ; ( d ) } } ; 3 } = true', 'tointer': 'select the rows whose date successor seated record fuzzily matches to vacant until the next congress . among these rows , select the rows whose vacator record fuzzily matches to ( d ) . the number of such rows is 3 .'} | eq { count { filter_eq { filter_eq { all_rows ; date successor seated ; vacant until the next congress } ; vacator ; ( d ) } } ; 3 } = true | select the rows whose date successor seated record fuzzily matches to vacant until the next congress . among these rows , select the rows whose vacator record fuzzily matches to ( d ) . the number of such rows is 3 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_str_eq_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'date successor seated_6': 6, 'vacant until the next congress_7': 7, 'vacator_8': 8, '(d)_9': 9, '3_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_str_eq_1': 'filter_str_eq', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'date successor seated_6': 'date successor seated', 'vacant until the next congress_7': 'vacant until the next congress', 'vacator_8': 'vacator', '(d)_9': '( d )', '3_10': '3'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_str_eq_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'date successor seated_6': [0], 'vacant until the next congress_7': [0], 'vacator_8': [1], '(d)_9': [1], '3_10': [3]} | ['district', 'vacator', 'reason for change', 'successor', 'date successor seated'] | [['missouri 6th', 'vacant', 'rep philip a bennett died in previous congress', 'marion t bennett ( r )', 'january 12 , 1943'], ['california 2nd', 'harry l englebright ( r )', 'died may 13 , 1943', 'clair engle ( d )', 'august 31 , 1943'], ['kansas 2nd', 'ulysses s guyer ( r )', 'died june 5 , 1943', 'errett p scrivner ( r )', 'september 14 , 1943'], ['new york 32nd', 'francis d culkin ( r )', 'died august 4 , 1943', 'hadwen c fuller ( r )', 'november 2 , 1943'], ['kentucky 4th', 'edward w creal ( d )', 'died october 13 , 1943', 'chester o carrier ( r )', 'november 30 , 1943'], ['pennsylvania 17th', 'j william ditter ( r )', 'died november 21 , 1943', 'vacant until the next congress', 'vacant until the next congress'], ['alabama 3rd', 'henry b steagall ( d )', 'died november 22 , 1943', 'george w andrews ( d )', 'march 14 , 1944'], ['colorado 1st', 'lawrence lewis ( d )', 'died december 9 , 1943', 'dean m gillespie ( r )', 'march 7 , 1944'], ['illinois 19th', 'william h wheat ( r )', 'died january 16 , 1944', 'rolla c mcmillen ( r )', 'june 13 , 1944'], ['illinois 7th', 'leonard w schuetz ( d )', 'died february 13 , 1944', 'vacant until the next congress', 'vacant until the next congress'], ['new york 4th', 'thomas h cullen ( d )', 'died march 1 , 1944', 'john j rooney ( d )', 'june 6 , 1944'], ['new york 11th', "james a o'leary ( d )", 'died march 16 , 1944', 'ellsworth b buck ( r )', 'june 6 , 1944'], ['california 16th', 'will rogers , jr ( d )', 'resigned may 23 , 1944 to enter the us army', 'vacant until the next congress', 'vacant until the next congress'], ['virginia 2nd', 'winder r harris ( d )', 'resigned september 15 , 1944', 'ralph hunter daughton ( d )', 'november 7 , 1944'], ['florida 3rd', 'robert l f sikes ( d )', 'resigned october 19 , 1944 to enter the us army', 'vacant until the next congress', 'vacant until the next congress'], ['south carolina 2nd', 'hampton p fulmer ( d )', 'died october 19 , 1944', 'willa l fulmer ( r )', 'november 7 , 1944']] |
state assembly elections in india , 2008 | https://en.wikipedia.org/wiki/State_Assembly_elections_in_India%2C_2008 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-15329030-1.html.csv | unique | mizoram is the only state where the 2008 india 's state assembly election poll was conducted in december . | {'scope': 'all', 'row': '6', 'col': '2', 'col_other': '1', 'criterion': 'fuzzily_match', 'value': 'december', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date of polls', 'december'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose date of polls record fuzzily matches to december .', 'tostr': 'filter_eq { all_rows ; date of polls ; december }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; date of polls ; december } }', 'tointer': 'select the rows whose date of polls record fuzzily matches to december . 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 of polls', 'december'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose date of polls record fuzzily matches to december .', 'tostr': 'filter_eq { all_rows ; date of polls ; december }'}, 'state'], 'result': 'mizoram', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; date of polls ; december } ; state }'}, 'mizoram'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; date of polls ; december } ; state } ; mizoram }', 'tointer': 'the state record of this unqiue row is mizoram .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; date of polls ; december } } ; eq { hop { filter_eq { all_rows ; date of polls ; december } ; state } ; mizoram } } = true', 'tointer': 'select the rows whose date of polls record fuzzily matches to december . there is only one such row in the table . the state record of this unqiue row is mizoram .'} | and { only { filter_eq { all_rows ; date of polls ; december } } ; eq { hop { filter_eq { all_rows ; date of polls ; december } ; state } ; mizoram } } = true | select the rows whose date of polls record fuzzily matches to december . there is only one such row in the table . the state record of this unqiue row is mizoram . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'date of polls_7': 7, 'december_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'state_9': 9, 'mizoram_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'date of polls_7': 'date of polls', 'december_8': 'december', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'state_9': 'state', 'mizoram_10': 'mizoram'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'date of polls_7': [0], 'december_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'state_9': [2], 'mizoram_10': [3]} | ['state', 'date of polls', 'seats ( acs )', 'date of counting', 'incumbent', 'election winner'] | [['tripura', 'saturday , 23 february 2008', '60', 'friday , 7 mar 2008', 'cpi ( m )', 'cpi ( m )'], ['meghalaya', 'monday , 3 march 2008', '60', 'friday , 7 mar 2008', 'inc', 'mpa 1'], ['nagaland', 'wednesday , 5 march 2008', '60', 'saturday , 8 march 2008', 'dan', 'dan 2'], ['madhya pradesh', 'thursday , 27 november 2008', '230', 'monday , 8 december 2008', 'bjp', 'bjp'], ['delhi', 'saturday , 29 november 2008', '70', 'monday , 8 december 2008', 'inc', 'inc'], ['mizoram', 'tuesday , 2 december 2008', '40', 'monday , 08 dec 2008', 'mnf', 'inc']] |
yasuhiro yoshiura | https://en.wikipedia.org/wiki/Yasuhiro_Yoshiura | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13077577-1.html.csv | majority | prior to 2006 , yasuhiro yoshiura served as screenwriter for most of his film projects . | {'scope': 'subset', 'col': '5', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': 'screenwriter', 'subset': {'col': '1', 'criterion': 'less_than', 'value': '2006'}} | {'func': 'most_str_eq', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'year', '2006'], 'result': None, 'ind': 0, 'tostr': 'filter_less { all_rows ; year ; 2006 }', 'tointer': 'select the rows whose year record is less than 2006 .'}, 'post', 'screenwriter'], 'result': True, 'ind': 1, 'tointer': 'select the rows whose year record is less than 2006 . for the post records of these rows , most of them fuzzily match to screenwriter .', 'tostr': 'most_eq { filter_less { all_rows ; year ; 2006 } ; post ; screenwriter } = true'} | most_eq { filter_less { all_rows ; year ; 2006 } ; post ; screenwriter } = true | select the rows whose year record is less than 2006 . for the post records of these rows , most of them fuzzily match to screenwriter . | 2 | 2 | {'most_str_eq_1': 1, 'result_2': 2, 'filter_less_0': 0, 'all_rows_3': 3, 'year_4': 4, '2006_5': 5, 'post_6': 6, 'screenwriter_7': 7} | {'most_str_eq_1': 'most_str_eq', 'result_2': 'true', 'filter_less_0': 'filter_less', 'all_rows_3': 'all_rows', 'year_4': 'year', '2006_5': '2006', 'post_6': 'post', 'screenwriter_7': 'screenwriter'} | {'most_str_eq_1': [2], 'result_2': [], 'filter_less_0': [1], 'all_rows_3': [0], 'year_4': [0], '2006_5': [0], 'post_6': [1], 'screenwriter_7': [1]} | ['year', 'name', 'genre', 'status', 'post'] | [['2000', 'noisy birth', 'music', 'released', 'director'], ['2001', 'kikumana', 'dementia , psychological', 'released', 'screenwriter'], ['2002', 'mizu no kotoba', 'drama , sci - fi , psychological', 'released', 'director , screenwriter'], ['2006', 'pale cocoon', 'drama , sci - fi', 'released', 'director'], ['2009', 'eve no jikan', 'sci - fi , slice of life', 'released', 'director , screenwriter , original creator'], ['2009', 'evangelion : 2.0 you can ( not ) advance', 'action , mecha , sci - fi', 'released', 'designer'], ['2010', 'eve no jikan ( film )', 'sci - fi , slice of life', 'released', 'director , screenwriter , original creator'], ['2012', 'sakasama no patema', 'sci - fi', 'released', 'director , original creator'], ['2013', 'sakasama no patema ( film )', 'sci - fi', 'upcoming', 'director , screenwriter , original creator']] |
united states house of representatives elections , 1928 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1928 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1342370-42.html.csv | majority | most of the incumbent candidates were successfully re-elected in the 1928 elections . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'equal', 'value': 're-elected', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'result', 're-elected'], 'result': True, 'ind': 0, 'tointer': 'for the result records of all rows , most of them fuzzily match to re-elected .', 'tostr': 'most_eq { all_rows ; result ; re-elected } = true'} | most_eq { all_rows ; result ; re-elected } = true | for the result records of all rows , most of them fuzzily match to re-elected . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'result_3': 3, 're-elected_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'result_3': 'result', 're-elected_4': 're-elected'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'result_3': [0], 're-elected_4': [0]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['texas 2', 'john c box', 'democratic', '1918', 're - elected', 'john c box ( d ) unopposed'], ['texas 3', 'morgan g sanders', 'democratic', '1920', 're - elected', 'morgan g sanders ( d ) unopposed'], ['texas 4', 'sam rayburn', 'democratic', '1912', 're - elected', 'sam rayburn ( d ) 84.2 % floyd harry ( r ) 15.8 %'], ['texas 5', 'hatton w sumners', 'democratic', '1914', 're - elected', 'hatton w sumners ( d ) unopposed'], ['texas 6', 'luther a johnson', 'democratic', '1922', 're - elected', 'luther a johnson ( d ) 90.7 % h lee monroe ( r ) 9.3 %'], ['texas 7', 'clay stone briggs', 'democratic', '1918', 're - elected', 'clay stone briggs ( d ) 88.4 % a j long ( r ) 11.6 %'], ['texas 11', 'tom connally', 'democratic', '1916', 'retired to run for u s senate democratic hold', 'oliver h cross ( d ) 90.9 % r c bush ( r ) 9.1 %'], ['texas 12', 'fritz g lanham', 'democratic', '1919', 're - elected', 'fritz g lanham ( d ) 79.6 % david sutton ( r ) 20.4 %'], ['texas 13', 'guinn williams', 'democratic', '1922', 're - elected', 'guinn williams ( d ) 88.5 % p a welty ( r ) 11.5 %'], ['texas 15', 'john nance garner', 'democratic', '1902', 're - elected', 'john nance garner ( d ) 100.0 % j l burd ( i ) 0.0 %'], ['texas 16', 'claude benton hudspeth', 'democratic', '1918', 're - elected', 'claude benton hudspeth ( d ) unopposed'], ['texas 17', 'thomas l blanton', 'democratic', '1916', 'retired to run for u s senate democratic hold', 'robert quincy lee ( d ) unopposed']] |
1968 boston patriots season | https://en.wikipedia.org/wiki/1968_Boston_Patriots_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10646744-2.html.csv | ordinal | the 2nd highest attendance during the 1968 boston patriots season was on november 17th , 1968 . | {'row': '10', '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', 'attendance', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; attendance ; 2 }'}, 'date'], 'result': 'november 17 , 1968', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; attendance ; 2 } ; date }'}, 'november 17 , 1968'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; attendance ; 2 } ; date } ; november 17 , 1968 } = true', 'tointer': 'select the row whose attendance record of all rows is 2nd maximum . the date record of this row is november 17 , 1968 .'} | eq { hop { nth_argmax { all_rows ; attendance ; 2 } ; date } ; november 17 , 1968 } = true | select the row whose attendance record of all rows is 2nd maximum . the date record of this row is november 17 , 1968 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'attendance_5': 5, '2_6': 6, 'date_7': 7, 'november 17 , 1968_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'attendance_5': 'attendance', '2_6': '2', 'date_7': 'date', 'november 17 , 1968_8': 'november 17 , 1968'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'attendance_5': [0], '2_6': [0], 'date_7': [1], 'november 17 , 1968_8': [2]} | ['week', 'date', 'opponent', 'result', 'attendance'] | [['1', 'september 8 , 1968', 'buffalo bills', 'w 16 - 7', '38865'], ['3', 'september 22 , 1968', 'new york jets', 'l 47 - 31', '22002'], ['4', 'september 29 , 1968', 'denver broncos', 'w 20 - 17', '37024'], ['5', 'october 6 , 1968', 'oakland raiders', 'l 41 - 10', '44253'], ['6', 'october 13 , 1968', 'houston oilers', 'l 16 - 0', '32502'], ['7', 'october 20 , 1968', 'buffalo bills', 'w 23 - 6', '21082'], ['8', 'october 27 , 1968', 'new york jets', 'l 48 - 14', '62351'], ['9', 'november 3 , 1968', 'denver broncos', 'l 35 - 14', '18304'], ['10', 'november 10 , 1968', 'san diego chargers', 'l 27 - 17', '19278'], ['11', 'november 17 , 1968', 'kansas city chiefs', 'l 31 - 17', '48271'], ['12', 'november 24 , 1968', 'miami dolphins', 'l 34 - 10', '18305'], ['13', 'december 1 , 1968', 'cincinnati bengals', 'w 33 - 14', '17796'], ['14', 'december 8 , 1968', 'miami dolphins', 'l 38 - 7', '24242'], ['15', 'december 15 , 1968', 'houston oilers', 'l 45 - 17', '34198']] |
iowa corn cy - hawk series | https://en.wikipedia.org/wiki/Iowa_Corn_Cy-Hawk_Series | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14175075-5.html.csv | unique | the september 4 , 2007 event was the only to take place in cedar rapids . | {'scope': 'all', 'row': '1', 'col': '2', 'col_other': '1', 'criterion': 'equal', 'value': 'cedar rapids', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'site', 'cedar rapids'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose site record fuzzily matches to cedar rapids .', 'tostr': 'filter_eq { all_rows ; site ; cedar rapids }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; site ; cedar rapids } }', 'tointer': 'select the rows whose site record fuzzily matches to cedar rapids . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'site', 'cedar rapids'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose site record fuzzily matches to cedar rapids .', 'tostr': 'filter_eq { all_rows ; site ; cedar rapids }'}, 'date'], 'result': 'september 4 , 2007', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; site ; cedar rapids } ; date }'}, 'september 4 , 2007'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; site ; cedar rapids } ; date } ; september 4 , 2007 }', 'tointer': 'the date record of this unqiue row is september 4 , 2007 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; site ; cedar rapids } } ; eq { hop { filter_eq { all_rows ; site ; cedar rapids } ; date } ; september 4 , 2007 } } = true', 'tointer': 'select the rows whose site record fuzzily matches to cedar rapids . there is only one such row in the table . the date record of this unqiue row is september 4 , 2007 .'} | and { only { filter_eq { all_rows ; site ; cedar rapids } } ; eq { hop { filter_eq { all_rows ; site ; cedar rapids } ; date } ; september 4 , 2007 } } = true | select the rows whose site record fuzzily matches to cedar rapids . there is only one such row in the table . the date record of this unqiue row is september 4 , 2007 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'site_7': 7, 'cedar rapids_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'date_9': 9, 'september 4 , 2007_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'site_7': 'site', 'cedar rapids_8': 'cedar rapids', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'date_9': 'date', 'september 4 , 2007_10': 'september 4 , 2007'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'site_7': [0], 'cedar rapids_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'date_9': [2], 'september 4 , 2007_10': [3]} | ['date', 'site', 'sport', 'winning team', 'series'] | [['september 4 , 2007', 'cedar rapids', 'm golf', 'iowa state', 'iowa state 2 - 0'], ['september 8 , 2007', 'des moines', 'volleyball', 'iowa state', 'iowa state 4 - 0'], ['september 9 , 2007', 'iowa city', 'w soccer', 'tie', 'iowa state 5 - 1'], ['september 15 , 2007', 'ames', 'football', 'iowa state', 'iowa state 8 - 1'], ['november 10 , 2007', 'peoria', 'm cross country', 'iowa state', 'iowa state 10 - 1'], ['november 10 , 2007', 'peoria', 'w cross country', 'iowa', 'iowa state 10 - 3'], ['december 5 , 2007', 'ames', 'w basketball', 'iowa state', 'iowa state 12 - 3'], ['december 7 , 2007', 'ames', 'w swimming', 'iowa state', 'iowa state 14 - 3'], ['december 8 , 2007', 'ames', 'm basketball', 'iowa state', 'iowa state 16 - 3'], ['december 9 , 2007', 'ames', 'wrestling', 'iowa', 'iowa state 16 - 5'], ['february 22 , 2008', 'ames', 'w gymnastics', 'iowa state', 'iowa state 18 - 5'], ['march 7 , 2008', 'iowa city', 'w gymnastics', 'iowa', 'iowa state 18 - 7'], ['april 1 , 2008', 'ames', 'softball', 'iowa', 'iowa state 18 - 9']] |
english numerals | https://en.wikipedia.org/wiki/English_numerals | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-163873-6.html.csv | ordinal | one billion a thousand million is the short scale english numeral that has the second lowest power notation . | {'row': '2', 'col': '2', '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', 'power notation', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; power notation ; 2 }'}, 'short scale'], 'result': 'one billion a thousand million', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; power notation ; 2 } ; short scale }'}, 'one billion a thousand million'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; power notation ; 2 } ; short scale } ; one billion a thousand million } = true', 'tointer': 'select the row whose power notation record of all rows is 2nd maximum . the short scale record of this row is one billion a thousand million .'} | eq { hop { nth_argmax { all_rows ; power notation ; 2 } ; short scale } ; one billion a thousand million } = true | select the row whose power notation record of all rows is 2nd maximum . the short scale record of this row is one billion a thousand million . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'power notation_5': 5, '2_6': 6, 'short scale_7': 7, 'one billion a thousand million_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', 'power notation_5': 'power notation', '2_6': '2', 'short scale_7': 'short scale', 'one billion a thousand million_8': 'one billion a thousand million'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'power notation_5': [0], '2_6': [0], 'short scale_7': [1], 'one billion a thousand million_8': [2]} | ['number notation', 'power notation', 'short scale', 'long scale', 'indian ( or south asian ) english'] | [['1000000', '10 6', 'one million', 'one million', 'ten lakh'], ['1000000000', '10 9', 'one billion a thousand million', 'one milliard a thousand million', 'one hundred crore ( one arab )'], ['1000000000000', '10 12', 'one trillion a thousand billion', 'one billion a million million', 'one lakh crore ( ten kharab )'], ['1000000000000000', '10 15', 'one quadrillion a thousand trillion', 'one billiard a thousand billion', 'ten crore crore ( one padm )'], ['1000000000000000000', '10 18', 'one quintillion a thousand quadrillion', 'one trillion a million billion', 'ten thousand crore crore ( ten shankh )'], ['1000000000000000000000', '10 21', 'one sextillion a thousand quintillion', 'one trilliard a thousand trillion', 'one crore crore crore']] |
2006 u.s. open ( golf ) | https://en.wikipedia.org/wiki/2006_U.S._Open_%28golf%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12523044-5.html.csv | majority | the majority of players in the us open were over par . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': '+', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'to par', '+'], 'result': True, 'ind': 0, 'tointer': 'for the to par records of all rows , most of them fuzzily match to + .', 'tostr': 'most_eq { all_rows ; to par ; + } = true'} | most_eq { all_rows ; to par ; + } = true | for the to par records of all rows , most of them fuzzily match to + . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'to par_3': 3, '+_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'to par_3': 'to par', '+_4': '+'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'to par_3': [0], '+_4': [0]} | ['place', 'player', 'country', 'score', 'to par'] | [['1', 'steve stricker', 'united states', '70 + 69 = 139', '- 1'], ['2', 'colin montgomerie', 'scotland', '69 + 71 = 140', 'e'], ['t3', 'kenneth ferrie', 'england', '71 + 70 = 141', '+ 1'], ['t3', 'geoff ogilvy', 'australia', '71 + 70 = 141', '+ 1'], ['t5', 'jim furyk', 'united states', '70 + 72 = 142', '+ 2'], ['t5', 'pádraig harrington', 'ireland', '70 + 72 = 142', '+ 2'], ['t7', 'jason dufner', 'united states', '72 + 71 = 143', '+ 3'], ['t7', 'graeme mcdowell', 'northern ireland', '71 + 72 = 143', '+ 3'], ['t7', 'phil mickelson', 'united states', '70 + 73 = 143', '+ 3'], ['t7', 'arron oberholser', 'united states', '75 + 68 = 143', '+ 3']] |
boxing at the 2002 south american games | https://en.wikipedia.org/wiki/Boxing_at_the_2002_South_American_Games | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18781567-2.html.csv | ordinal | in the 2002 south american games , argentina won the second most total medals for boxing with 8 . | {'row': '4', 'col': '6', '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', 'total', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; total ; 2 }'}, 'nation'], 'result': 'argentina', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; total ; 2 } ; nation }'}, 'argentina'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; total ; 2 } ; nation } ; argentina } = true', 'tointer': 'select the row whose total record of all rows is 2nd maximum . the nation record of this row is argentina .'} | eq { hop { nth_argmax { all_rows ; total ; 2 } ; nation } ; argentina } = true | select the row whose total record of all rows is 2nd maximum . the nation record of this row is argentina . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'total_5': 5, '2_6': 6, 'nation_7': 7, 'argentina_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'total_5': 'total', '2_6': '2', 'nation_7': 'nation', 'argentina_8': 'argentina'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'total_5': [0], '2_6': [0], 'nation_7': [1], 'argentina_8': [2]} | ['rank', 'nation', 'gold', 'silver', 'bronze', 'total'] | [['1', 'brazil', '6', '2', '3', '11'], ['2', 'venezuela', '3', '3', '1', '7'], ['3', 'ecuador', '3', '1', '1', '5'], ['4', 'argentina', '0', '3', '5', '8'], ['5', 'peru', '0', '1', '1', '2'], ['6', 'aruba', '0', '1', '0', '1'], ['7', 'guyana', '0', '0', '5', '5'], ['8', 'chile', '0', '0', '2', '2'], ['9', 'paraguay', '0', '0', '0', '0']] |
politics of friuli - venezia giulia | https://en.wikipedia.org/wiki/Politics_of_Friuli-Venezia_Giulia | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18568694-2.html.csv | comparative | the municipality with the largest population in friuli-venezia giulia has over twice as many people as the second largest . | {'row_1': '1', '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', 'municipality', 'trieste'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose municipality record fuzzily matches to trieste .', 'tostr': 'filter_eq { all_rows ; municipality ; trieste }'}, 'inhabitants'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; municipality ; trieste } ; inhabitants }', 'tointer': 'select the rows whose municipality record fuzzily matches to trieste . take the inhabitants record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'municipality', 'udine'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose municipality record fuzzily matches to udine .', 'tostr': 'filter_eq { all_rows ; municipality ; udine }'}, 'inhabitants'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; municipality ; udine } ; inhabitants }', 'tointer': 'select the rows whose municipality record fuzzily matches to udine . take the inhabitants record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; municipality ; trieste } ; inhabitants } ; hop { filter_eq { all_rows ; municipality ; udine } ; inhabitants } } = true', 'tointer': 'select the rows whose municipality record fuzzily matches to trieste . take the inhabitants record of this row . select the rows whose municipality record fuzzily matches to udine . take the inhabitants record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; municipality ; trieste } ; inhabitants } ; hop { filter_eq { all_rows ; municipality ; udine } ; inhabitants } } = true | select the rows whose municipality record fuzzily matches to trieste . take the inhabitants record of this row . select the rows whose municipality record fuzzily matches to udine . take the inhabitants 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, 'municipality_7': 7, 'trieste_8': 8, 'inhabitants_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'municipality_11': 11, 'udine_12': 12, 'inhabitants_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', 'municipality_7': 'municipality', 'trieste_8': 'trieste', 'inhabitants_9': 'inhabitants', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'municipality_11': 'municipality', 'udine_12': 'udine', 'inhabitants_13': 'inhabitants'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'municipality_7': [0], 'trieste_8': [0], 'inhabitants_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'municipality_11': [1], 'udine_12': [1], 'inhabitants_13': [3]} | ['municipality', 'inhabitants', 'mayor', 'party', 'election'] | [['trieste', '205535', 'roberto cosolini', 'democratic party', '2011'], ['udine', '99627', 'furio honsell', 'democratic party', '2008'], ['pordenone', '51723', 'claudio pedrotti', 'democratic party', '2011'], ['gorizia', '35798', 'ettore romoli', 'the people of freedom', '2012'], ['monfalcone', '27877', 'silvia altran', 'democratic party', '2011'], ['sacile', '20227', 'roberto ceraolo', 'the people of freedom', '2009'], ['cordenons', '18470', 'mario ongaro', 'lega friuli - vg', '2011'], ['codroipo', '15887', 'fabio marchetti', 'the people of freedom', '2011'], ['azzano decimo', '15601', 'marco putto', 'democratic party', '2012'], ['porcia', '15443', 'stefano turchet', 'lega friuli - vg', '2009'], ['san vito al tagliamento', '15015', 'antonio di bisceglie', 'democratic party', '2011']] |
nate mohr | https://en.wikipedia.org/wiki/Nate_Mohr | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17440712-2.html.csv | majority | the majority of nate mohr 's fights ended in a win result for nate mohr . | {'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'] | [['loss', '9 - 7', 'lenny lovato', 'decision ( unanimous )', 'gfc 2 - unstoppable', '3'], ['win', '9 - 6', 'danny rodriguez', 'tko ( punches )', 'xfo - xtreme fighting organization 28', '3'], ['loss', '8 - 6', 'dennis siver', 'tko ( spinning back kick & punches )', 'ufc 93', '3'], ['loss', '8 - 5', 'manny gamburyan', 'submission ( achilles lock )', 'ufc 79', '1'], ['win', '8 - 4', 'luke caudillo', 'decision ( unanimous )', 'ufc fight night 10', '3'], ['loss', '7 - 4', 'kurt pellegrino', 'submission ( achilles lock )', 'ufc fight night 9', '1'], ['win', '7 - 3', 'cody shipp', 'tko ( punches )', 'kotc - hard knocks', '1'], ['win', '6 - 3', 'norm alexander', 'tko ( punches )', 'xfo 13 - operation beatdown', '2'], ['win', '5 - 3', 'darren cotton', 'tko ( punches )', 'xfo 12 - outdoor war', '2'], ['win', '4 - 3', 'alex carter', 'tko ( punches )', 'xfo 11 - champions', '1'], ['loss', '3 - 3', 'donald cerrone', 'submission ( triangle choke )', 'rof 21 - full blast', '1'], ['loss', '3 - 2', 'jay ellis', 'submission ( rear naked choke )', 'xfo 9 - xtreme fighting organization 9', '1'], ['win', '3 - 1', 'enrique guzman', 'tko ( punches )', 'combat - do fighting challenge 4', '1'], ['win', '2 - 1', 'don hamilton', 'submission ( punches )', 'ic - iowa challenge', '1'], ['loss', '1 - 1', 'john strawn', 'submission ( rear naked choke )', 'ec 53 - extreme challenge 53', '2'], ['win', '1 - 0', 'cain rizzo', 'submission ( punches )', 'ec 52 - extreme challenge 52', '2']] |
list of tallest buildings in houston | https://en.wikipedia.org/wiki/List_of_tallest_buildings_in_Houston | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11530524-3.html.csv | ordinal | the lomas & nettleton building is the oldest recognized structure in the list of houston 's tallest buildings . | {'row': '1', 'col': '3', 'order': '1', 'col_other': '1', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'years as tallest', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; years as tallest ; 1 }'}, 'name'], 'result': 'lomas & nettleton building', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; years as tallest ; 1 } ; name }'}, 'lomas & nettleton building'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; years as tallest ; 1 } ; name } ; lomas & nettleton building } = true', 'tointer': 'select the row whose years as tallest record of all rows is 1st minimum . the name record of this row is lomas & nettleton building .'} | eq { hop { nth_argmin { all_rows ; years as tallest ; 1 } ; name } ; lomas & nettleton building } = true | select the row whose years as tallest record of all rows is 1st minimum . the name record of this row is lomas & nettleton building . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'years as tallest_5': 5, '1_6': 6, 'name_7': 7, 'lomas & nettleton building_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', 'years as tallest_5': 'years as tallest', '1_6': '1', 'name_7': 'name', 'lomas & nettleton building_8': 'lomas & nettleton building'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'years as tallest_5': [0], '1_6': [0], 'name_7': [1], 'lomas & nettleton building_8': [2]} | ['name', 'street address', 'years as tallest', 'height ft / m', 'floors'] | [['lomas & nettleton building', '201 main street', '1904 - 1908', 'n / a', '8'], ['711 main', '711 main street', '1908 - 1910', '134 / 41', '10'], ['806 main', '806 main street', '1910 - 1926', '302 / 92', '23'], ['magnolia hotel', '1100 texas avenue', '1926 - 1927', '325 / 99', '22'], ['niels esperson building', '808 travis street', '1927 - 1929', '410 / 125', '32'], ['jpmorgan chase building', '712 main street', '1929 - 1963', '428 / 131', '36'], ['exxon building', '800 bell avenue', '1963 - 1971', '607 / 185', '44'], ['one shell plaza', '910 louisiana street', '1971 - 1980', '714 / 218', '50'], ['enterprise plaza', '1100 louisiana street', '1980 - 1982', '756 / 230', '55'], ['jpmorgan chase tower', '600 travis street', '1982 - present', '1002 / 305', '75']] |
2007 asp world tour | https://en.wikipedia.org/wiki/2007_ASP_World_Tour | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16135219-1.html.csv | unique | the only quiksilver pro event in the 2007 asp world tour to be held in australia was won by mick fanning . | {'scope': 'subset', 'row': '1', 'col': '3', 'col_other': '4', 'criterion': 'equal', 'value': 'australia', 'subset': {'col': '4', 'criterion': 'equal', 'value': 'quiksilver pro'}} | {'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'event', 'quiksilver pro'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; event ; quiksilver pro }', 'tointer': 'select the rows whose event record fuzzily matches to quiksilver pro .'}, 'country', 'australia'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose event record fuzzily matches to quiksilver pro . among these rows , select the rows whose country record fuzzily matches to australia .', 'tostr': 'filter_eq { filter_eq { all_rows ; event ; quiksilver pro } ; country ; australia }'}], 'result': True, 'ind': 2, 'tostr': 'only { filter_eq { filter_eq { all_rows ; event ; quiksilver pro } ; country ; australia } } = true', 'tointer': 'select the rows whose event record fuzzily matches to quiksilver pro . among these rows , select the rows whose country record fuzzily matches to australia . there is only one such row in the table .'} | only { filter_eq { filter_eq { all_rows ; event ; quiksilver pro } ; country ; australia } } = true | select the rows whose event record fuzzily matches to quiksilver pro . among these rows , select the rows whose country record fuzzily matches to australia . there is only one such row in the table . | 3 | 3 | {'only_2': 2, 'result_3': 3, 'filter_str_eq_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'event_5': 5, 'quiksilver pro_6': 6, 'country_7': 7, 'australia_8': 8} | {'only_2': 'only', 'result_3': 'true', 'filter_str_eq_1': 'filter_str_eq', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'event_5': 'event', 'quiksilver pro_6': 'quiksilver pro', 'country_7': 'country', 'australia_8': 'australia'} | {'only_2': [3], 'result_3': [], 'filter_str_eq_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'event_5': [0], 'quiksilver pro_6': [0], 'country_7': [1], 'australia_8': [1]} | ['date', 'location', 'country', 'event', 'winner', 'runner - up'] | [['february 27 - march 11', 'gold coast', 'australia', 'quiksilver pro', 'mick fanning ( aus )', 'bede durbidge ( aus )'], ['april 3 - april 13', 'bells beach', 'australia', 'rip curl pro', 'taj burrow ( aus )', 'andy irons ( haw )'], ['may 4 - may 14', 'teahupoo , tahiti', 'french polynesia', 'billabong pro', 'damien hobgood ( usa )', 'mick fanning ( aus )'], ['june 20 - july 1', 'arica', 'chile', 'rip curl pro search', 'andy irons ( haw )', 'damien hobgood ( usa )'], ['june 11 - july 22', 'jeffreys bay', 'south africa', 'billabong pro', 'taj burrow ( aus )', 'kelly slater ( usa )'], ['september 9 - september 15', 'trestles', 'united states', 'boost mobile pro', 'kelly slater ( usa )', 'pancho sullivan ( haw )'], ['september 20 - september 30', 'hossegor', 'france', 'quiksilver pro', 'mick fanning ( aus )', 'greg emslie ( rsa )'], ['october 1 - october 14', 'mundaka', 'spain', 'billabong pro', 'bobby martinez ( usa )', 'taj burrow ( aus )'], ['october 30 - november 7', 'santa catarina', 'brazil', 'hang loose pro', 'mick fanning ( aus )', 'kai otton ( aus )'], ['december 8 - december 20', 'pipeline , hawaii', 'united states', 'billabong pipeline masters', 'bede durbidge ( aus )', 'dean morrison ( aus )']] |
elvis ' gold records volume 5 | https://en.wikipedia.org/wiki/Elvis%27_Gold_Records_Volume_5 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15582798-4.html.csv | aggregation | each song on elvis 's gold records volume five was an average of 2 minutes and forty seconds . | {'scope': 'all', 'col': '6', 'type': 'average', 'result': '2:40', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'time'], 'result': '2:40', 'ind': 0, 'tostr': 'avg { all_rows ; time }'}, '2:40'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; time } ; 2:40 } = true', 'tointer': 'the average of the time record of all rows is 2:40 .'} | round_eq { avg { all_rows ; time } ; 2:40 } = true | the average of the time record of all rows is 2:40 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'time_4': 4, '2:40_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'time_4': 'time', '2:40_5': '2:40'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'time_4': [0], '2:40_5': [1]} | ['track', 'recorded', 'catalogue', 'release date', 'song title', 'time'] | [['1', '9 / 10 / 67', '47 - 9341', '9 / 26 / 67', 'big boss man', '2:50'], ['2', '9 / 10 / 67', '47 - 9425', '1 / 9 / 68', 'guitar man', '2:12'], ['3', '1 / 16 / 68', '47 - 9465', '2 / 28 / 68', 'us male', '2:42'], ['4', '6 / 6 / 70', '47 - 9916', '10 / 6 / 70', "you do n't have to say you love me", '2:30'], ['5', '3 / 7 / 68', '47 - 9670b', '11 / 5 / 68', 'edge of reality', '3:33'], ['6', '6 / 23 / 68', '47 - 9731', '2 / 25 / 69', 'memories', '3:06']] |
inbee park | https://en.wikipedia.org/wiki/Inbee_Park | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18198579-6.html.csv | unique | the only year that inbee park participated in 19 tournaments was 2010 . | {'scope': 'all', 'row': '7', 'col': '2', 'col_other': '1', 'criterion': 'equal', 'value': '19', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'tournaments played', '19'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose tournaments played record is equal to 19 .', 'tostr': 'filter_eq { all_rows ; tournaments played ; 19 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; tournaments played ; 19 } }', 'tointer': 'select the rows whose tournaments played record is equal to 19 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'tournaments played', '19'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose tournaments played record is equal to 19 .', 'tostr': 'filter_eq { all_rows ; tournaments played ; 19 }'}, 'year'], 'result': '2010', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; tournaments played ; 19 } ; year }'}, '2010'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; tournaments played ; 19 } ; year } ; 2010 }', 'tointer': 'the year record of this unqiue row is 2010 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; tournaments played ; 19 } } ; eq { hop { filter_eq { all_rows ; tournaments played ; 19 } ; year } ; 2010 } } = true', 'tointer': 'select the rows whose tournaments played record is equal to 19 . there is only one such row in the table . the year record of this unqiue row is 2010 .'} | and { only { filter_eq { all_rows ; tournaments played ; 19 } } ; eq { hop { filter_eq { all_rows ; tournaments played ; 19 } ; year } ; 2010 } } = true | select the rows whose tournaments played record is equal to 19 . there is only one such row in the table . the year record of this unqiue row is 2010 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'tournaments played_7': 7, '19_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'year_9': 9, '2010_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'tournaments played_7': 'tournaments played', '19_8': '19', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'year_9': 'year', '2010_10': '2010'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'tournaments played_7': [0], '19_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'year_9': [2], '2010_10': [3]} | ['year', 'tournaments played', 'cuts made', 'wins', 'top 10s', 'best finish', 'earnings', 'money list rank', 'scoring average', 'scoring rank'] | [['2004', '2', '1', '0', '1', 't8', 'n / a', 'n / a', '72.60', 'n / a'], ['2005', '2', '1', '0', '1', '5', 'n / a', 'n / a', '71.00', 'n / a'], ['2006', '2', '2', '0', '0', 't35', '5406', 'n / a', '73.86', 'n / a'], ['2007', '26', '18', '0', '2', 't2', '380263', '37', '73.19', '72'], ['2008', '26', '22', '1', '7', '1', '1138370', '8', '71.78', '26'], ['2009', '23', '16', '0', '2', 't5', '271303', '50', '72.55', '67'], ['2010', '19', '19', '0', '11', '2', '825477', '11', '70.83', '9'], ['2011', '16', '15', '0', '3', 't6', '365231', '31', '72.00', '27'], ['2012', '24', '23', '2', '12', '1', '2287080', '1', '70.21', '1'], ['2013', '21', '20', '6', '9', '1', '2335460', '1', '69.934', '3'], ['totals', '161', '137', '9', '46', 'n / a', '7603184', 'n / a', 'n / a', 'n / a']] |
northeast hoosier conference | https://en.wikipedia.org/wiki/Northeast_Hoosier_Conference | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18936832-1.html.csv | unique | the only school in the northeast hoosier conference whose mascot is the eagles , is columbia city . | {'scope': 'all', 'row': '2', 'col': '3', 'col_other': '1', 'criterion': 'equal', 'value': 'eagles', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'mascot', 'eagles'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose mascot record fuzzily matches to eagles .', 'tostr': 'filter_eq { all_rows ; mascot ; eagles }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; mascot ; eagles } }', 'tointer': 'select the rows whose mascot record fuzzily matches to eagles . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'mascot', 'eagles'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose mascot record fuzzily matches to eagles .', 'tostr': 'filter_eq { all_rows ; mascot ; eagles }'}, 'school'], 'result': 'columbia city', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; mascot ; eagles } ; school }'}, 'columbia city'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; mascot ; eagles } ; school } ; columbia city }', 'tointer': 'the school record of this unqiue row is columbia city .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; mascot ; eagles } } ; eq { hop { filter_eq { all_rows ; mascot ; eagles } ; school } ; columbia city } } = true', 'tointer': 'select the rows whose mascot record fuzzily matches to eagles . there is only one such row in the table . the school record of this unqiue row is columbia city .'} | and { only { filter_eq { all_rows ; mascot ; eagles } } ; eq { hop { filter_eq { all_rows ; mascot ; eagles } ; school } ; columbia city } } = true | select the rows whose mascot record fuzzily matches to eagles . there is only one such row in the table . the school record of this unqiue row is columbia city . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'mascot_7': 7, 'eagles_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'school_9': 9, 'columbia city_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'mascot_7': 'mascot', 'eagles_8': 'eagles', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'school_9': 'school', 'columbia city_10': 'columbia city'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'mascot_7': [0], 'eagles_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'school_9': [2], 'columbia city_10': [3]} | ['school', 'location', 'mascot', 'enrollment', 'ihsaa class', 'county'] | [['bellmont', 'decatur', 'braves', '927', 'aaa', '01 adams'], ['columbia city', 'columbia city', 'eagles', '1127', 'aaaa', '92 whitley'], ['dekalb', 'waterloo', 'barons', '1302', 'aaaa', '17 dekalb'], ['east noble', 'kendallville', 'knights', '1213', 'aaaa', '57 noble'], ['fort wayne carroll', 'fort wayne', 'chargers', '1889', 'aaaaa', '02 allen'], ['fort wayne homestead', 'fort wayne', 'spartans', '2141', 'aaaaa', '02 allen'], ['new haven', 'new haven', 'bulldogs', '985', 'aaaa', '02 allen'], ['norwell', 'ossian', 'knights', '876', 'aaaa', '90 wells']] |
1958 u.s. open ( golf ) | https://en.wikipedia.org/wiki/1958_U.S._Open_%28golf%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17290111-1.html.csv | count | in the 1958 u.s. open ( golf ) , among the players from united states , 3 of them won more 1999 prize money . | {'scope': 'subset', 'criterion': 'greater_than', 'value': '1999', 'result': '3', 'col': '6', 'subset': {'col': '3', 'criterion': 'equal', 'value': 'united states'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater', '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 .'}, 'money', '1999'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose country record fuzzily matches to united states . among these rows , select the rows whose money record is greater than 1999 .', 'tostr': 'filter_greater { filter_eq { all_rows ; country ; united states } ; money ; 1999 }'}], 'result': '3', 'ind': 2, 'tostr': 'count { filter_greater { filter_eq { all_rows ; country ; united states } ; money ; 1999 } }', 'tointer': 'select the rows whose country record fuzzily matches to united states . among these rows , select the rows whose money record is greater than 1999 . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_greater { filter_eq { all_rows ; country ; united states } ; money ; 1999 } } ; 3 } = true', 'tointer': 'select the rows whose country record fuzzily matches to united states . among these rows , select the rows whose money record is greater than 1999 . the number of such rows is 3 .'} | eq { count { filter_greater { filter_eq { all_rows ; country ; united states } ; money ; 1999 } } ; 3 } = true | select the rows whose country record fuzzily matches to united states . among these rows , select the rows whose money record is greater than 1999 . the number of such rows is 3 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_greater_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'country_6': 6, 'united states_7': 7, 'money_8': 8, '1999_9': 9, '3_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', 'country_6': 'country', 'united states_7': 'united states', 'money_8': 'money', '1999_9': '1999', '3_10': '3'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_greater_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'country_6': [0], 'united states_7': [0], 'money_8': [1], '1999_9': [1], '3_10': [3]} | ['place', 'player', 'country', 'score', 'to par', 'money'] | [['1', 'tommy bolt', 'united states', '71 + 71 + 69 + 72 = 283', '+ 3', '8000'], ['2', 'gary player', 'south africa', '75 + 68 + 73 + 71 = 287', '+ 7', '5000'], ['3', 'julius boros', 'united states', '71 + 75 + 72 + 71 = 289', '+ 9', '3000'], ['4', 'gene littler', 'united states', '74 + 73 + 67 + 76 = 290', '+ 10', '2000'], ['t5', 'walter burkemo', 'united states', '75 + 74 + 70 + 72 = 291', '+ 11', '1625'], ['t5', 'bob rosburg', 'united states', '75 + 74 + 72 + 70 = 291', '+ 11', '1625'], ['t7', 'jay hebert', 'united states', '77 + 76 + 71 + 69 = 293', '+ 13', '1016'], ['t7', 'don january', 'united states', '79 + 73 + 68 + 73 = 293', '+ 13', '1016'], ['t7', 'dick metz', 'united states', '71 + 78 + 73 + 71 = 293', '+ 13', '1016'], ['t10', 'ben hogan', 'united states', '75 + 73 + 75 + 71 = 294', '+ 14', '566'], ['t10', 'tommy jacobs', 'united states', '76 + 75 + 71 + 72 = 294', '+ 14', '566'], ['t10', 'frank stranahan', 'united states', '72 + 72 + 75 + 75 = 294', '+ 14', '566']] |
merlin ( series 3 ) | https://en.wikipedia.org/wiki/Merlin_%28series_3%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-29106680-1.html.csv | superlative | the highest number of viewers for merlin series 3 , is for the episode titled the sorcerer 's shadow . | {'scope': 'all', 'col_superlative': '7', 'row_superlative': '11', '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', 'uk viewers ( million )'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; uk viewers ( million ) }'}, 'title'], 'result': "the sorcerer 's shadow", 'ind': 1, 'tostr': 'hop { argmax { all_rows ; uk viewers ( million ) } ; title }'}, "the sorcerer 's shadow"], 'result': True, 'ind': 2, 'tostr': "eq { hop { argmax { all_rows ; uk viewers ( million ) } ; title } ; the sorcerer 's shadow } = true", 'tointer': "select the row whose uk viewers ( million ) record of all rows is maximum . the title record of this row is the sorcerer 's shadow ."} | eq { hop { argmax { all_rows ; uk viewers ( million ) } ; title } ; the sorcerer 's shadow } = true | select the row whose uk viewers ( million ) record of all rows is maximum . the title record of this row is the sorcerer 's shadow . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'uk viewers (million)_5': 5, 'title_6': 6, "the sorcerer 's shadow_7": 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'uk viewers (million)_5': 'uk viewers ( million )', 'title_6': 'title', "the sorcerer 's shadow_7": "the sorcerer 's shadow"} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'uk viewers (million)_5': [0], 'title_6': [1], "the sorcerer 's shadow_7": [2]} | ['no overall', 'no for series', 'title', 'directed by', 'written by', 'original air date', 'uk viewers ( million )'] | [['27', '1', 'the tears of uther pendragon ( part 1 )', 'jeremy webb', 'julian jones', '11 september 2010', '6.49'], ['28', '2', 'the tears of uther pendragon ( part 2 )', 'jeremy webb', 'julian jones', '18 september 2010', '6.06'], ['29', '3', "goblin 's gold", 'jeremy webb', 'howard overman', '25 september 2010', '6.22'], ['30', '4', 'gwaine', 'david moore', 'julian jones', '2 october 2010', '6.42'], ['31', '5', 'the crystal cave', 'alice troughton', 'julian jones', '9 october 2010', '6.36'], ['32', '6', 'the changeling', 'david moore', 'lucy watkins', '16 october 2010', '6.40'], ['33', '7', 'the castle of fyrien', 'david moore', 'jake michie', '23 october 2010', '6.82'], ['34', '8', 'the eye of the phoenix', 'alice troughton', 'julian jones', '30 october 2010', '6.92'], ['35', '9', 'love in the time of dragons', 'alice troughton', 'jake michie', '6 november 2010', '6.90'], ['36', '10', 'queen of hearts', 'ashley way', 'howard overman', '13 november 2010', '7.37'], ['37', '11', "the sorcerer 's shadow", 'ashley way', 'julian jones', '20 november 2010', '7.42'], ['38', '12', 'the coming of arthur ( part 1 )', 'jeremy webb', 'jake michie', '27 november 2010', '7.12']] |
sim kwon - ho | https://en.wikipedia.org/wiki/Sim_Kwon-Ho | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16680101-1.html.csv | unique | the match at the 1996 asian championships was the only match that ended in a 11:0 score for sim kwon-ho . | {'scope': 'all', 'row': '6', 'col': '4', 'col_other': '6', 'criterion': 'equal', 'value': '11:0', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'score', '11:0'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose score record fuzzily matches to 11:0 .', 'tostr': 'filter_eq { all_rows ; score ; 11:0 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; score ; 11:0 } }', 'tointer': 'select the rows whose score record fuzzily matches to 11:0 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'score', '11:0'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose score record fuzzily matches to 11:0 .', 'tostr': 'filter_eq { all_rows ; score ; 11:0 }'}, 'competition'], 'result': '1996 asian championships', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; score ; 11:0 } ; competition }'}, '1996 asian championships'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; score ; 11:0 } ; competition } ; 1996 asian championships }', 'tointer': 'the competition record of this unqiue row is 1996 asian championships .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; score ; 11:0 } } ; eq { hop { filter_eq { all_rows ; score ; 11:0 } ; competition } ; 1996 asian championships } } = true', 'tointer': 'select the rows whose score record fuzzily matches to 11:0 . there is only one such row in the table . the competition record of this unqiue row is 1996 asian championships .'} | and { only { filter_eq { all_rows ; score ; 11:0 } } ; eq { hop { filter_eq { all_rows ; score ; 11:0 } ; competition } ; 1996 asian championships } } = true | select the rows whose score record fuzzily matches to 11:0 . there is only one such row in the table . the competition record of this unqiue row is 1996 asian championships . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'score_7': 7, '11:0_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'competition_9': 9, '1996 asian championships_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'score_7': 'score', '11:0_8': '11:0', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'competition_9': 'competition', '1996 asian championships_10': '1996 asian championships'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'score_7': [0], '11:0_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'competition_9': [2], '1996 asian championships_10': [3]} | ['opponent', 'res', 'class', 'score', 'date', 'competition', 'notes'] | [['win', 'lã ¡ zaro rivas', '54 kg', '8:0', '2000 - 06 - 09', '2000 summer olympics', 'won second olympic gold medal'], ['win', 'shamseddin khudoyberdiev', '54 kg', '3:2', '1999 - 05 - 31', '1999 asian championships', 'won third asian championship gold medal'], ['win', 'kang yong - gyun', '54 kg', '5:5', '1998 - 12 - 13', '1998 asian games', 'won second asian games gold medal'], ['win', 'marian sandu', '54 kg', '5:3', '1998 - 08 - 30', '1998 world championships', 'won second world championship gold medal'], ['win', 'aleksandr pavlov', '48 kg', '4:0', '1996 - 07 - 21', '1996 summer olympics', 'won first olympic gold medal'], ['win', 'kang yong - gyun', '48 kg', '11:0', '1996 - 04 - 06', '1996 asian championships', 'won second asian championship gold medal'], ['win', 'hiroshi kado', '48 kg', '6:0', '1995 - 10 - 14', '1995 world championships', 'won first world championship gold medal'], ['win', 'dmitri korshunov', '48 kg', '12:0', '1995 - 06 - 28', '1995 asian championships', 'won first asian championship gold medal'], ['win', 'reza simkhah', '48 kg', '7:0', '1994 - 10 - 05', '1994 asian games', 'won first asian games gold medal']] |
2009 - 10 atlanta hawks season | https://en.wikipedia.org/wiki/2009%E2%80%9310_Atlanta_Hawks_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-23248910-5.html.csv | ordinal | in their second game against the trail blazers in the 2009-10 atlanta hawks season , the hawks won by 4 points . | {'scope': 'subset', 'row': '9', 'col': '2', 'order': '2', 'col_other': '3,4', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'subset': {'col': '3', 'criterion': 'equal', 'value': 'trail blazers'}} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'team', 'trail blazers'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; team ; trail blazers }', 'tointer': 'select the rows whose team record fuzzily matches to trail blazers .'}, 'date', '2'], 'result': None, 'ind': 1, 'tostr': 'nth_argmin { filter_eq { all_rows ; team ; trail blazers } ; date ; 2 }'}, 'score'], 'result': 'w 99 - 95 ( ot )', 'ind': 2, 'tostr': 'hop { nth_argmin { filter_eq { all_rows ; team ; trail blazers } ; date ; 2 } ; score }'}, 'w 99 - 95 ( ot )'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { nth_argmin { filter_eq { all_rows ; team ; trail blazers } ; date ; 2 } ; score } ; w 99 - 95 ( ot ) } = true', 'tointer': 'select the rows whose team record fuzzily matches to trail blazers . select the row whose date record of these rows is 2nd minimum . the score record of this row is w 99 - 95 ( ot ) .'} | eq { hop { nth_argmin { filter_eq { all_rows ; team ; trail blazers } ; date ; 2 } ; score } ; w 99 - 95 ( ot ) } = true | select the rows whose team record fuzzily matches to trail blazers . select the row whose date record of these rows is 2nd minimum . the score record of this row is w 99 - 95 ( ot ) . | 4 | 4 | {'str_eq_3': 3, 'result_4': 4, 'str_hop_2': 2, 'nth_argmin_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'team_6': 6, 'trail blazers_7': 7, 'date_8': 8, '2_9': 9, 'score_10': 10, 'w 99 - 95 (ot)_11': 11} | {'str_eq_3': 'str_eq', 'result_4': 'true', 'str_hop_2': 'str_hop', 'nth_argmin_1': 'nth_argmin', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'team_6': 'team', 'trail blazers_7': 'trail blazers', 'date_8': 'date', '2_9': '2', 'score_10': 'score', 'w 99 - 95 (ot)_11': 'w 99 - 95 ( ot )'} | {'str_eq_3': [4], 'result_4': [], 'str_hop_2': [3], 'nth_argmin_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'team_6': [0], 'trail blazers_7': [0], 'date_8': [1], '2_9': [1], 'score_10': [2], 'w 99 - 95 (ot)_11': [3]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record'] | [['3', 'november 1', 'lakers', 'l 110 - 118 ( ot )', 'j johnson ( 9 )', 'j johnson ( 9 ) a horford ( 9 )', 'j smith ( 7 )', 'staples center 18997', '2 - 1'], ['4', 'november 3', 'trail blazers', 'w 97 - 91 ( ot )', 'j crawford ( 27 )', 'a horford ( 13 )', 'j crawford ( 7 )', 'rose garden 20325', '3 - 1'], ['5', 'november 4', 'kings', 'w 113 - 105 ( ot )', 'j crawford ( 26 ) j johnson ( 26 )', 'j johnson ( 8 ) a horford ( 8 )', 'j crawford ( 4 ) j johnson ( 4 )', 'arco arena 11751', '4 - 1'], ['6', 'november 6', 'bobcats', 'l 83 - 103 ( ot )', 'j crawford ( 13 ) j johnson ( 13 ) j smith ( 13 )', 'j smith ( 7 )', 'j teague ( 3 ) m bibby ( 3 )', 'time warner cable arena 15874', '4 - 2'], ['7', 'november 7', 'nuggets', 'w 125 - 100 ( ot )', 'j crawford ( 25 )', 'a horford ( 12 )', 'j smith ( 7 )', 'philips arena 17801', '5 - 2'], ['8', 'november 11', 'knicks', 'w 114 - 101 ( ot )', 'a horfod ( 25 )', 'j smith ( 12 )', 'm bibby ( 9 )', 'madison square garden 19699', '6 - 2'], ['9', 'november 13', 'celtics', 'w 97 - 86 ( ot )', 'j johnson ( 24 )', 'a horford ( 13 )', 'm bibby ( 6 )', 'td garden 18624', '7 - 2'], ['10', 'november 14', 'hornets', 'w 121 - 98 ( ot )', 'j johnson ( 26 )', 'j smith ( 17 )', 'j johnson ( 7 )', 'philips arena 18572', '8 - 2'], ['11', 'november 16', 'trail blazers', 'w 99 - 95 ( ot )', 'j johnson ( 35 )', 'j smith ( 16 )', 'j johnson ( 9 )', 'philips arena 12977', '9 - 2'], ['12', 'november 18', 'heat', 'w 105 - 90 ( ot )', 'j johnson ( 30 )', 'j smith ( 14 )', 'j smith ( 7 )', 'philips arena 18729', '10 - 2'], ['13', 'november 20', 'rockets', 'w 105 - 103 ( ot )', 'm williams ( 29 )', 'm williams ( 9 )', 'j johnson ( 9 )', 'philips arena 16674', '11 - 2'], ['14', 'november 21', 'hornets', 'l 88 - 96 ( ot )', 'j crawford ( 20 )', 'a horford ( 11 )', 'j smith ( 7 )', 'new orleans arena 15933', '11 - 3'], ['15', 'november 26', 'magic', 'l 76 - 93 ( ot )', 'j johnson ( 22 )', 'j smith ( 13 )', 'm bibby ( 5 )', 'philips arena 19193', '11 - 4'], ['16', 'november 27', '76ers', 'w 100 - 86 ( ot )', 'j crawford ( 24 )', 'm williams ( 9 )', 'j crawford / m bibby ( 5 )', 'wachovia center 12984', '12 - 4']] |
triple crown ( basketball ) | https://en.wikipedia.org/wiki/Triple_Crown_%28basketball%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12072982-5.html.csv | count | the turkish basketball cup was one twice as the national cup in the triple crown . | {'scope': 'all', 'criterion': 'equal', 'value': 'turkish basketball cup', 'result': '2', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'national cup', 'turkish basketball cup'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose national cup record fuzzily matches to turkish basketball cup .', 'tostr': 'filter_eq { all_rows ; national cup ; turkish basketball cup }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; national cup ; turkish basketball cup } }', 'tointer': 'select the rows whose national cup record fuzzily matches to turkish basketball cup . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; national cup ; turkish basketball cup } } ; 2 } = true', 'tointer': 'select the rows whose national cup record fuzzily matches to turkish basketball cup . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; national cup ; turkish basketball cup } } ; 2 } = true | select the rows whose national cup record fuzzily matches to turkish basketball cup . 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, 'national cup_5': 5, 'turkish basketball cup_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', 'national cup_5': 'national cup', 'turkish basketball cup_6': 'turkish basketball cup', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'national cup_5': [0], 'turkish basketball cup_6': [0], '2_7': [2]} | ['season', 'club', 'national league', 'national cup', 'european cup'] | [['1976 - 77', 'kk split ( jugoplastika )', 'yugoslav first federal league', 'yugoslav cup', 'fiba korać cup ( 3rd tier )'], ['1978 - 79', 'kk partizan', 'yugoslav first federal league', 'yugoslav cup', 'fiba korać cup ( 3rd tier )'], ['1982 - 83', 'limoges csp', 'french nationale 1', 'french federation cup', 'fiba korać cup ( 3rd tier )'], ['1986 - 87', 'fc barcelona', 'spanish acb league', "spanish king 's cup", 'fiba korać cup ( 3rd tier )'], ['1995 - 96', 'efes pilsen', 'turkish basketball league', 'turkish basketball cup', 'fiba korać cup ( 3rd tier )'], ['1999 - 00', 'limoges csp', 'french pro a league', 'french basketball cup', 'fiba korać cup ( 3rd tier )'], ['2004 - 05', 'csu asesoft ploiesti', 'romanian divizia a', 'romanian basketball cup', 'fiba eurocup challenge ( 4th tier )'], ['2011 - 12', 'beşiktaş', 'turkish basketball league', 'turkish basketball cup', 'fiba eurochallenge ( 3rd tier )']] |
annerose fiedler | https://en.wikipedia.org/wiki/Annerose_Fiedler | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11503769-1.html.csv | count | annerose fiedler finished in second place on two different occasions . | {'scope': 'all', 'criterion': 'equal', 'value': '2nd', 'result': '2', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'result', '2nd'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose result record fuzzily matches to 2nd .', 'tostr': 'filter_eq { all_rows ; result ; 2nd }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; result ; 2nd } }', 'tointer': 'select the rows whose result record fuzzily matches to 2nd . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; result ; 2nd } } ; 2 } = true', 'tointer': 'select the rows whose result record fuzzily matches to 2nd . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; result ; 2nd } } ; 2 } = true | select the rows whose result record fuzzily matches to 2nd . 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, 'result_5': 5, '2nd_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', 'result_5': 'result', '2nd_6': '2nd', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'result_5': [0], '2nd_6': [0], '2_7': [2]} | ['year', 'tournament', 'venue', 'result', 'extra'] | [['1972', 'olympic games', 'munich , west germany', '7th', '100 m hurdles'], ['1974', 'european indoor championships', 'gothenburg , sweden', '2nd', '60 m hurdles'], ['1974', 'european championships', 'rome , italy', '2nd', '100 m hurdles'], ['1975', 'european indoor championships', 'katowice , poland', '4th', '60 m hurdles'], ['1978', 'european championships', 'prague , czechoslovakia', '6th', '100 m hurdles']] |
2008 - 09 cardiff city f.c. season | https://en.wikipedia.org/wiki/2008%E2%80%9309_Cardiff_City_F.C._season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-17596418-5.html.csv | ordinal | konstantopoulos had the 7th highest age of the names in the 2008-09 cardiff city f.c. season . | {'row': '7', 'col': '5', 'order': '7', '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', 'age', '7'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; age ; 7 }'}, 'name'], 'result': 'konstantopoulos', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; age ; 7 } ; name }'}, 'konstantopoulos'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; age ; 7 } ; name } ; konstantopoulos } = true', 'tointer': 'select the row whose age record of all rows is 7th minimum . the name record of this row is konstantopoulos .'} | eq { hop { nth_argmin { all_rows ; age ; 7 } ; name } ; konstantopoulos } = true | select the row whose age record of all rows is 7th minimum . the name record of this row is konstantopoulos . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'age_5': 5, '7_6': 6, 'name_7': 7, 'konstantopoulos_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', 'age_5': 'age', '7_6': '7', 'name_7': 'name', 'konstantopoulos_8': 'konstantopoulos'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'age_5': [0], '7_6': [0], 'name_7': [1], 'konstantopoulos_8': [2]} | ['no', 'p', 'name', 'country', 'age', 'loan club', 'started', 'ended', 'start source', 'end source'] | [['13', 'gk', 'heaton', 'eng', '23', 'manchester united', '5 may', '30 june', 'bbc sport', 'south wales echo'], ['9', 'fw', 'e johnson', 'usa', '25', 'fulham', '22 august', '30 june', 'bbc sport', 'south wales echo'], ['18', 'fw', 'chopra', 'eng', '25', 'sunderland', '6 november', '30 december', 'bbc sport', 'bbc sport'], ['14', 'mf', 'routledge', 'eng', '23', 'aston villa', '20 november', '2 january', 'cardiff city', 'bbc sport'], ['14', 'mf', 'owusu - abeyie', 'ghana', '23', 'spartak moscow', '31 january', '30 june', 'bbc sport', 'south wales echo'], ['18', 'fw', 'chopra', 'eng', '25', 'sunderland', '2 february', '30 june', 'bbc sport', 'south wales echo'], ['22', 'gk', 'konstantopoulos', 'gre', '30', 'coventry city', '9 february', '30 june', 'bbc sport', 'south wales echo']] |
2008 - 09 croatian cup | https://en.wikipedia.org/wiki/2008%E2%80%9309_Croatian_Cup | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18828647-1.html.csv | unique | the final is the only round that took place in the month of may . | {'scope': 'all', 'row': '6', 'col': '2', 'col_other': '1', 'criterion': 'fuzzily_match', 'value': 'may', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'main date', 'may'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose main date record fuzzily matches to may .', 'tostr': 'filter_eq { all_rows ; main date ; may }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; main date ; may } }', 'tointer': 'select the rows whose main date record fuzzily matches to may . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'main date', 'may'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose main date record fuzzily matches to may .', 'tostr': 'filter_eq { all_rows ; main date ; may }'}, 'round'], 'result': 'final', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; main date ; may } ; round }'}, 'final'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; main date ; may } ; round } ; final }', 'tointer': 'the round record of this unqiue row is final .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; main date ; may } } ; eq { hop { filter_eq { all_rows ; main date ; may } ; round } ; final } } = true', 'tointer': 'select the rows whose main date record fuzzily matches to may . there is only one such row in the table . the round record of this unqiue row is final .'} | and { only { filter_eq { all_rows ; main date ; may } } ; eq { hop { filter_eq { all_rows ; main date ; may } ; round } ; final } } = true | select the rows whose main date record fuzzily matches to may . there is only one such row in the table . the round record of this unqiue row is final . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'main date_7': 7, 'may_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'round_9': 9, 'final_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'main date_7': 'main date', 'may_8': 'may', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'round_9': 'round', 'final_10': 'final'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'main date_7': [0], 'may_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'round_9': [2], 'final_10': [3]} | ['round', 'main date', 'number of fixtures', 'clubs', 'new entries this round'] | [['preliminary round', '27 august 2008', '16', '48 → 32', 'none'], ['first round', '23 and 24 september 2008', '16', '32 → 16', '16'], ['second round', '29 october 2008', '8', '16 → 8', 'none'], ['quarter - finals', '12 and 26 november 2008', '8', '8 → 4', 'none'], ['semi - finals', '4 and 18 march 2009', '4', '4 → 2', 'none'], ['final', '13 and 28 may 2009', '2', '2 → 1', 'none']] |
teen age message | https://en.wikipedia.org/wiki/Teen_Age_Message | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1820752-1.html.csv | ordinal | the ursa major constellation has the shortest distance ( ly ) for which teen age messages can be sent . | {'row': '2', 'col': '3', 'order': '1', 'col_other': '2', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'distance ( ly )', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; distance ( ly ) ; 1 }'}, 'constellation'], 'result': 'ursa major', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; distance ( ly ) ; 1 } ; constellation }'}, 'ursa major'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; distance ( ly ) ; 1 } ; constellation } ; ursa major } = true', 'tointer': 'select the row whose distance ( ly ) record of all rows is 1st minimum . the constellation record of this row is ursa major .'} | eq { hop { nth_argmin { all_rows ; distance ( ly ) ; 1 } ; constellation } ; ursa major } = true | select the row whose distance ( ly ) record of all rows is 1st minimum . the constellation record of this row is ursa major . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'distance ( ly )_5': 5, '1_6': 6, 'constellation_7': 7, 'ursa major_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', 'distance ( ly )_5': 'distance ( ly )', '1_6': '1', 'constellation_7': 'constellation', 'ursa major_8': 'ursa major'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'distance ( ly )_5': [0], '1_6': [0], 'constellation_7': [1], 'ursa major_8': [2]} | ['hd designation', 'constellation', 'distance ( ly )', 'spectral type', 'signal power ( kw )', 'date sent', 'arrival date'] | [['hd197076', 'delphinus', '68.5', 'g5v', '126', 'august 29 , 2001', 'february 2070'], ['hd95128', 'ursa major', '45.9', 'g0v', '96', 'september 3 , 2001', 'july 2047'], ['hd50692', 'gemini', '56.3', 'g0v', '96', 'september 3 , 2001', 'december 2057'], ['hd126053', 'virgo', '57.4', 'g1v', '96', 'september 3 , 2001', 'january 2059'], ['hd76151', 'hydra', '55.7', 'g2v', '96', 'september 4 , 2001', 'may 2057'], ['hd193664', 'draco', '57.4', 'g3v', '96', 'september 4 , 2001', 'january 2059']] |
kentucky intercollegiate athletic conference | https://en.wikipedia.org/wiki/Kentucky_Intercollegiate_Athletic_Conference | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-10581768-2.html.csv | ordinal | midway college is the oldest established institution among those which participated in the kentucky intercollegiate athletic conference . | {'row': '10', 'col': '4', 'order': '1', 'col_other': '1', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'founded', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; founded ; 1 }'}, 'institution'], 'result': 'midway college 1', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; founded ; 1 } ; institution }'}, 'midway college 1'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; founded ; 1 } ; institution } ; midway college 1 } = true', 'tointer': 'select the row whose founded record of all rows is 1st minimum . the institution record of this row is midway college 1 .'} | eq { hop { nth_argmin { all_rows ; founded ; 1 } ; institution } ; midway college 1 } = true | select the row whose founded record of all rows is 1st minimum . the institution record of this row is midway college 1 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'founded_5': 5, '1_6': 6, 'institution_7': 7, 'midway college 1_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmin_0': 'nth_argmin', 'all_rows_4': 'all_rows', 'founded_5': 'founded', '1_6': '1', 'institution_7': 'institution', 'midway college 1_8': 'midway college 1'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'founded_5': [0], '1_6': [0], 'institution_7': [1], 'midway college 1_8': [2]} | ['institution', 'nickname', 'location', 'founded', 'type', 'enrollment'] | [['alice lloyd college', 'eagles', 'pippa passes , kentucky', '1923', 'private', '600'], ['asbury university', 'eagles', 'wilmore , kentucky', '1890', 'private', '1300'], ['berea college', 'mountaineers', 'berea , kentucky', '1855', 'private', '1514'], ['brescia university', 'bearcats', 'owensboro , kentucky', '1950', 'private', '750'], ['carlow university 1', 'celtics', 'pittsburgh , pennsylvania', '1929', 'private', '2400'], ['cincinnati christian university', 'eagles', 'cincinnati , ohio', '1924', 'private', '1100'], ['indiana university east', 'red wolves', 'richmond , indiana', '1971', 'public', '2700'], ['indiana university kokomo', 'cougars', 'kokomo , indiana', '1945', 'public', '3719'], ['indiana university southeast', 'grenadiers', 'new albany , indiana', '1941', 'public', '6840'], ['midway college 1', 'eagles', 'midway , kentucky', '1847', 'private', '1800'], ['point park university', 'pioneers', 'pittsburgh , pennsylvania', '1960', 'private', '3376']] |
2002 oakland raiders season | https://en.wikipedia.org/wiki/2002_Oakland_Raiders_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16353260-1.html.csv | majority | in the 2002 season , the majority of the oakland raiders ' games were aired on cbs . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'cbs', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'tv time', 'cbs'], 'result': True, 'ind': 0, 'tointer': 'for the tv time records of all rows , most of them fuzzily match to cbs .', 'tostr': 'most_eq { all_rows ; tv time ; cbs } = true'} | most_eq { all_rows ; tv time ; cbs } = true | for the tv time records of all rows , most of them fuzzily match to cbs . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'tv time_3': 3, 'cbs_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'tv time_3': 'tv time', 'cbs_4': 'cbs'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'tv time_3': [0], 'cbs_4': [0]} | ['week', 'date', 'opponent', 'result', 'tv time', 'record', 'attendance'] | [['1', 'september 8 , 2002', 'seattle seahawks', 'w 31 - 17', 'fox 4:15 et', '1 - 0', '53260'], ['2', 'september 15 , 2002', 'pittsburgh steelers', 'w 30 - 17', 'espn 8:30 et', '2 - 0', '62260'], ['3', '-', '-', '-', '-', '-', ''], ['4', 'september 29 , 2002', 'tennessee titans', 'w 52 - 25', 'cbs 4:15 et', '3 - 0', '58719'], ['5', 'october 6 , 2002', 'buffalo bills', 'w 49 - 31', 'cbs 1:00 et', '4 - 0', '73038'], ['6', 'october 13 , 2002', 'st louis rams', 'l 28 - 13', 'cbs 4:15 et', '4 - 1', '66070'], ['7', 'october 20 , 2002', 'san diego chargers', 'l 27 - 21 ( ot )', 'cbs 4:05 et', '4 - 2', '60974'], ['8', 'october 27 , 2002', 'kansas city chiefs', 'l 20 - 10', 'cbs 1:00 et', '4 - 3', '78685'], ['9', 'november 3 , 2002', 'san francisco 49ers', 'l 23 - 20 ( ot )', 'fox 4:15 et', '4 - 4', '62660'], ['10', 'november 11 , 2002', 'denver broncos', 'w 34 - 10', 'abc 9:00 et', '5 - 4', '76643'], ['11', 'november 17 , 2002', 'new england patriots', 'w 27 - 20', 'espn 8:30 et', '6 - 4', '62552'], ['12', 'november 24 , 2002', 'arizona cardinals', 'w 41 - 20', 'cbs 1:05 et', '7 - 4', '58814'], ['13', 'december 2 , 2002', 'new york jets', 'w 26 - 20', 'abc 9:00 et', '8 - 4', '62257'], ['14', 'december 8 , 2002', 'san diego chargers', 'w 27 - 7', 'cbs 4:15 et', '9 - 4', '67968'], ['15', 'december 15 , 2002', 'miami dolphins', 'l 23 - 17', 'cbs 1:00 et', '9 - 5', '73572'], ['16', 'december 22 , 2002', 'denver broncos', 'w 28 - 16', 'cbs 4:15 et', '10 - 5', '62592'], ['17', 'december 28 , 2002', 'kansas city chiefs', 'w 24 - 0', 'cbs 5:00 et', '11 - 5', '62078']] |
2007 - 08 nashville predators season | https://en.wikipedia.org/wiki/2007%E2%80%9308_Nashville_Predators_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11756731-14.html.csv | ordinal | ben ryan was the 2nd player from the university of notre dame drafted by nashville in the 2007-08 season . | {'scope': 'subset', 'row': '5', 'col': '1', 'order': '2', 'col_other': '2', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'subset': {'col': '5', 'criterion': 'equal', 'value': 'university of notre dame ( ccha )'}} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'college / junior / club team ( league )', 'university of notre dame ( ccha )'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; college / junior / club team ( league ) ; university of notre dame ( ccha ) }', 'tointer': 'select the rows whose college / junior / club team ( league ) record fuzzily matches to university of notre dame ( ccha ) .'}, 'round', '2'], 'result': None, 'ind': 1, 'tostr': 'nth_argmin { filter_eq { all_rows ; college / junior / club team ( league ) ; university of notre dame ( ccha ) } ; round ; 2 }'}, 'player'], 'result': 'ben ryan', 'ind': 2, 'tostr': 'hop { nth_argmin { filter_eq { all_rows ; college / junior / club team ( league ) ; university of notre dame ( ccha ) } ; round ; 2 } ; player }'}, 'ben ryan'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { nth_argmin { filter_eq { all_rows ; college / junior / club team ( league ) ; university of notre dame ( ccha ) } ; round ; 2 } ; player } ; ben ryan } = true', 'tointer': 'select the rows whose college / junior / club team ( league ) record fuzzily matches to university of notre dame ( ccha ) . select the row whose round record of these rows is 2nd minimum . the player record of this row is ben ryan .'} | eq { hop { nth_argmin { filter_eq { all_rows ; college / junior / club team ( league ) ; university of notre dame ( ccha ) } ; round ; 2 } ; player } ; ben ryan } = true | select the rows whose college / junior / club team ( league ) record fuzzily matches to university of notre dame ( ccha ) . select the row whose round record of these rows is 2nd minimum . the player record of this row is ben ryan . | 4 | 4 | {'str_eq_3': 3, 'result_4': 4, 'str_hop_2': 2, 'nth_argmin_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'college / junior / club team (league)_6': 6, 'university of notre dame ( ccha )_7': 7, 'round_8': 8, '2_9': 9, 'player_10': 10, 'ben ryan_11': 11} | {'str_eq_3': 'str_eq', 'result_4': 'true', 'str_hop_2': 'str_hop', 'nth_argmin_1': 'nth_argmin', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'college / junior / club team (league)_6': 'college / junior / club team ( league )', 'university of notre dame ( ccha )_7': 'university of notre dame ( ccha )', 'round_8': 'round', '2_9': '2', 'player_10': 'player', 'ben ryan_11': 'ben ryan'} | {'str_eq_3': [4], 'result_4': [], 'str_hop_2': [3], 'nth_argmin_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'college / junior / club team (league)_6': [0], 'university of notre dame ( ccha )_7': [0], 'round_8': [1], '2_9': [1], 'player_10': [2], 'ben ryan_11': [3]} | ['round', 'player', 'position', 'nationality', 'college / junior / club team ( league )'] | [['1', 'jonathon blum', 'd', 'united states', 'vancouver giants ( whl )'], ['2', 'jeremy smith', 'g', 'united states', 'plymouth whalers ( ohl )'], ['2', 'nick spaling', 'c', 'canada', 'kitchener rangers ( ohl )'], ['3', 'ryan thang', 'lw', 'united states', 'university of notre dame ( ccha )'], ['4', 'ben ryan', 'c', 'united states', 'university of notre dame ( ccha )'], ['4', 'mark santorelli', 'c', 'canada', 'chilliwack bruins ( whl )'], ['5', 'andreas thuresson', 'w', 'sweden', 'malmã redhawks ( sel )'], ['6', 'robert dietrich', 'd', 'germany', 'deg metro stars ( germany )'], ['7', 'atte engren', 'g', 'finland', 'lukko ( sm - liiga )']] |
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 | ordinal | italy has the fourth most jerseys of any of the countries . | {'row': '4', 'col': '3', 'order': '4', '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', 'jerseys', '4'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; jerseys ; 4 }'}, 'country'], 'result': 'italy', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; jerseys ; 4 } ; country }'}, 'italy'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; jerseys ; 4 } ; country } ; italy } = true', 'tointer': 'select the row whose jerseys record of all rows is 4th maximum . the country record of this row is italy .'} | eq { hop { nth_argmax { all_rows ; jerseys ; 4 } ; country } ; italy } = true | select the row whose jerseys record of all rows is 4th maximum . the country record of this row is italy . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'jerseys_5': 5, '4_6': 6, 'country_7': 7, 'italy_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', 'jerseys_5': 'jerseys', '4_6': '4', 'country_7': 'country', 'italy_8': 'italy'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'jerseys_5': [0], '4_6': [0], 'country_7': [1], 'italy_8': [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']] |
2006 - 07 golden state warriors season | https://en.wikipedia.org/wiki/2006%E2%80%9307_Golden_State_Warriors_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14677944-8.html.csv | aggregation | the warriors average attendance in april of 2007 was 17392 . | {'scope': 'all', 'col': '6', 'type': 'average', 'result': '17392', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'attendance'], 'result': '17392', 'ind': 0, 'tostr': 'avg { all_rows ; attendance }'}, '17392'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; attendance } ; 17392 } = true', 'tointer': 'the average of the attendance record of all rows is 17392 .'} | round_eq { avg { all_rows ; attendance } ; 17392 } = true | the average of the attendance record of all rows is 17392 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'attendance_4': 4, '17392_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'attendance_4': 'attendance', '17392_5': '17392'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'attendance_4': [0], '17392_5': [1]} | ['date', 'visitor', 'score', 'home', 'leading scorer', 'attendance', 'record'] | [['2007 - 04 - 01', 'grizzlies', '117 - 122', 'warriors', 'jason richardson ( 26 )', '17198', '35 - 39'], ['2007 - 04 - 04', 'warriors', '110 - 99', 'rockets', 'jason richardson ( 26 )', '13929', '36 - 39'], ['2007 - 04 - 06', 'warriors', '116 - 104', 'grizzlies', 'baron davis ( 31 )', '14087', '37 - 39'], ['2007 - 04 - 07', 'warriors', '99 - 112', 'spurs', 'jason richardson ( 23 )', '18797', '37 - 40'], ['2007 - 04 - 09', 'jazz', '102 - 126', 'warriors', 'stephen jackson ( 28 )', '17453', '38 - 40'], ['2007 - 04 - 13', 'warriors', '125 - 108', 'kings', 'stephen jackson ( 26 )', '17317', '39 - 40'], ['2007 - 04 - 15', 'timberwolves', '108 - 121', 'warriors', 'jason richardson ( 32 )', '18223', '40 - 40'], ['2007 - 04 - 17', 'mavericks', '82 - 111', 'warriors', 'mickaël piétrus ( 22 )', '20073', '41 - 40'], ['2007 - 04 - 18', 'warriors', '120 - 98', 'blazers', 'stephen jackson ( 31 )', '19455', '42 - 40']] |
2009 - 10 3 . liga | https://en.wikipedia.org/wiki/2009%E2%80%9310_3._Liga | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17593350-2.html.csv | count | two of the managers of 2009-2019 left the team because the contract ended . | {'scope': 'all', 'criterion': 'equal', 'value': 'end of contract', 'result': '2', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'manner of departure', 'end of contract'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose manner of departure record fuzzily matches to end of contract .', 'tostr': 'filter_eq { all_rows ; manner of departure ; end of contract }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; manner of departure ; end of contract } }', 'tointer': 'select the rows whose manner of departure record fuzzily matches to end of contract . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; manner of departure ; end of contract } } ; 2 } = true', 'tointer': 'select the rows whose manner of departure record fuzzily matches to end of contract . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; manner of departure ; end of contract } } ; 2 } = true | select the rows whose manner of departure record fuzzily matches to end of contract . 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, 'manner of departure_5': 5, 'end of contract_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', 'manner of departure_5': 'manner of departure', 'end of contract_6': 'end of contract', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'manner of departure_5': [0], 'end of contract_6': [0], '2_7': [2]} | ['team', 'outgoing manager', 'manner of departure', 'date of vacancy', 'replaced by', 'date of appointment', 'position in table'] | [['vfl osnabrück', 'claus - dieter wollitz', 'fc energie cottbus purchased rights', '30 june 2009', 'karsten baumann', '1 july 2009', 'pre - season'], ['fc carl zeiss jena', 'marc fascher', 'end of contract', '30 june 2009', 'rené van eck', '1 july 2009', 'pre - season'], ['fc rot - weiß erfurt', 'henri fuchs', 'end of tenure as caretaker', '30 june 2009', 'rainer hörgl', '1 july 2009', 'pre - season'], ['vfb stuttgart ii', 'rainer adrion', 'new coach of germany u - 21', '30 june 2009', 'reiner geyer', '1 july 2009', 'pre - season'], ['sv wacker burghausen', 'ralf santelli', 'end of contract', '30 june 2009', 'jürgen press', '1 july 2009', 'pre - season']] |
last man standing ( uk tv series ) | https://en.wikipedia.org/wiki/Last_Man_Standing_%28UK_TV_series%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12538190-1.html.csv | comparative | in the us series of last man standing , mark boban won more events than corey rennell . | {'row_1': '4', 'row_2': '2', 'col': '5', 'col_other': '1', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'name', 'mark boban'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose name record fuzzily matches to mark boban .', 'tostr': 'filter_eq { all_rows ; name ; mark boban }'}, 'events won ( us series )'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; name ; mark boban } ; events won ( us series ) }', 'tointer': 'select the rows whose name record fuzzily matches to mark boban . take the events won ( us series ) record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'name', 'corey rennell'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose name record fuzzily matches to corey rennell .', 'tostr': 'filter_eq { all_rows ; name ; corey rennell }'}, 'events won ( us series )'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; name ; corey rennell } ; events won ( us series ) }', 'tointer': 'select the rows whose name record fuzzily matches to corey rennell . take the events won ( us series ) record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; name ; mark boban } ; events won ( us series ) } ; hop { filter_eq { all_rows ; name ; corey rennell } ; events won ( us series ) } } = true', 'tointer': 'select the rows whose name record fuzzily matches to mark boban . take the events won ( us series ) record of this row . select the rows whose name record fuzzily matches to corey rennell . take the events won ( us series ) record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; name ; mark boban } ; events won ( us series ) } ; hop { filter_eq { all_rows ; name ; corey rennell } ; events won ( us series ) } } = true | select the rows whose name record fuzzily matches to mark boban . take the events won ( us series ) record of this row . select the rows whose name record fuzzily matches to corey rennell . take the events won ( us series ) 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, 'mark boban_8': 8, 'events won (us series)_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'name_11': 11, 'corey rennell_12': 12, 'events won (us series)_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', 'mark boban_8': 'mark boban', 'events won (us series)_9': 'events won ( us series )', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'name_11': 'name', 'corey rennell_12': 'corey rennell', 'events won (us series)_13': 'events won ( us series )'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'name_7': [0], 'mark boban_8': [0], 'events won (us series)_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'name_11': [1], 'corey rennell_12': [1], 'events won (us series)_13': [3]} | ['name', 'from', 'discipline', 'events won ( uk series )', 'events won ( us series )'] | [['bradley johnson', 'united states oklahoma', 'strongman', '2', '3'], ['corey rennell', 'united states alaska', 'outdoorsman', '0', '0'], ['jason bennett', 'united states florida', 'bmx racer and tree surgeon', '2', '3'], ['mark boban', 'united kingdom birmingham', 'kickboxing and salsa dance', '1', '1'], ['rajko radovic', 'united kingdom middlesex', 'fitness guru', '2', '3'], ['richard massey', 'united kingdom oxford', 'cricket and rugby', '1', '2']] |
road to ... ( family guy ) | https://en.wikipedia.org/wiki/Road_to..._%28Family_Guy%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-28210383-1.html.csv | comparative | the episode the road to the north pole aired after the road to europe . | {'row_1': '6', 'row_2': '2', 'col': '6', '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', 'title', 'road to the north pole'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose title record fuzzily matches to road to the north pole .', 'tostr': 'filter_eq { all_rows ; title ; road to the north pole }'}, 'original air date'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; title ; road to the north pole } ; original air date }', 'tointer': 'select the rows whose title record fuzzily matches to road to the north pole . take the original air date record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'title', 'road to europe'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose title record fuzzily matches to road to europe .', 'tostr': 'filter_eq { all_rows ; title ; road to europe }'}, 'original air date'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; title ; road to europe } ; original air date }', 'tointer': 'select the rows whose title record fuzzily matches to road to europe . take the original air date record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; title ; road to the north pole } ; original air date } ; hop { filter_eq { all_rows ; title ; road to europe } ; original air date } } = true', 'tointer': 'select the rows whose title record fuzzily matches to road to the north pole . take the original air date record of this row . select the rows whose title record fuzzily matches to road to europe . take the original air date record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; title ; road to the north pole } ; original air date } ; hop { filter_eq { all_rows ; title ; road to europe } ; original air date } } = true | select the rows whose title record fuzzily matches to road to the north pole . take the original air date record of this row . select the rows whose title record fuzzily matches to road to europe . take the original air date 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, 'title_7': 7, 'road to the north pole_8': 8, 'original air date_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'title_11': 11, 'road to europe_12': 12, 'original air date_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', 'title_7': 'title', 'road to the north pole_8': 'road to the north pole', 'original air date_9': 'original air date', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'title_11': 'title', 'road to europe_12': 'road to europe', 'original air date_13': 'original air date'} | {'greater_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'title_7': [0], 'road to the north pole_8': [0], 'original air date_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'title_11': [1], 'road to europe_12': [1], 'original air date_13': [3]} | ['( season )', 'no ( episode )', 'title', 'directed by', 'written by', 'original air date', 'prod code'] | [['1 ( 2 )', '20 ( 13 )', 'road to rhode island', 'dan povenmire', 'gary janetti', 'may 30 , 2000', '2acx12'], ['2 ( 3 )', '48 ( 20 )', 'road to europe', 'dan povenmire', 'daniel palladino', 'february 7 , 2002', '3acx13'], ['3 ( 5 )', '89 ( 9 )', 'road to rupert', 'dan povenmire', 'patrick meighan', 'january 28 , 2007', '5acx04'], ['4 ( 7 )', '113 ( 3 )', 'road to germany', 'greg colton', 'patrick meighan', 'october 19 , 2008', '6acx08'], ['5 ( 8 )', '127 ( 1 )', 'road to the multiverse', 'greg colton', 'wellesley wild', 'september 27 , 2009', '7acx06'], ['6 ( 9 )', '154 ( 7 / 8 )', 'road to the north pole', 'greg colton', 'danny smith & chris sheridan', 'december 12 , 2010', '8acx08 - 09']] |
2007 - 08 belgian government formation | https://en.wikipedia.org/wiki/2007%E2%80%9308_Belgian_government_formation | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12943367-1.html.csv | count | when the cd & v party was involved in the formation of the belgian government , yves leterme was their representative 2 times . | {'scope': 'subset', 'criterion': 'equal', 'value': 'yves leterme', 'result': '2', 'col': '3', 'subset': {'col': '4', 'criterion': 'equal', 'value': 'cd & v'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'party', 'cd & v'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; party ; cd & v }', 'tointer': 'select the rows whose party record fuzzily matches to cd & v .'}, 'name', 'yves leterme'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose party record fuzzily matches to cd & v . among these rows , select the rows whose name record fuzzily matches to yves leterme .', 'tostr': 'filter_eq { filter_eq { all_rows ; party ; cd & v } ; name ; yves leterme }'}], 'result': '2', 'ind': 2, 'tostr': 'count { filter_eq { filter_eq { all_rows ; party ; cd & v } ; name ; yves leterme } }', 'tointer': 'select the rows whose party record fuzzily matches to cd & v . among these rows , select the rows whose name record fuzzily matches to yves leterme . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_eq { filter_eq { all_rows ; party ; cd & v } ; name ; yves leterme } } ; 2 } = true', 'tointer': 'select the rows whose party record fuzzily matches to cd & v . among these rows , select the rows whose name record fuzzily matches to yves leterme . the number of such rows is 2 .'} | eq { count { filter_eq { filter_eq { all_rows ; party ; cd & v } ; name ; yves leterme } } ; 2 } = true | select the rows whose party record fuzzily matches to cd & v . among these rows , select the rows whose name record fuzzily matches to yves leterme . the number of such rows is 2 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_str_eq_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'party_6': 6, 'cd&v_7': 7, 'name_8': 8, 'yves leterme_9': 9, '2_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_str_eq_1': 'filter_str_eq', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'party_6': 'party', 'cd&v_7': 'cd & v', 'name_8': 'name', 'yves leterme_9': 'yves leterme', '2_10': '2'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_str_eq_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'party_6': [0], 'cd&v_7': [0], 'name_8': [1], 'yves leterme_9': [1], '2_10': [3]} | ['from', 'until', 'name', 'party', 'function'] | [['june 13 , 2007', 'july 4 , 2007', 'didier reynders', 'mr', 'informateur'], ['july 5 , 2007', 'july 15 , 2007', 'jean - luc dehaene', 'cd & v', 'mediator'], ['july 15 , 2007', 'august 23 , 2007', 'yves leterme', 'cd & v', 'formateur'], ['august 29 , 2007', 'september 29 , 2007', 'herman van rompuy', 'cd & v', 'explorator'], ['september 29 , 2007', 'december 1 , 2007', 'yves leterme', 'cd & v', 'formateur'], ['december 4 , 2007', 'december 17 , 2007', 'guy verhofstadt', 'vld', 'informateur'], ['december 17 , 2007', 'december 23 , 2007', 'guy verhofstadt', 'vld', 'formateur']] |
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/1-11677100-18.html.csv | unique | of players on the usa today all-usa high school baseball team , james kaprelian is the only one from california . | {'scope': 'all', 'row': '3', 'col': '4', 'col_other': '1', 'criterion': 'fuzzily_match', 'value': 'ca', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', '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': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; hometown ; ca } }', 'tointer': 'select the rows whose hometown record fuzzily matches to ca . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', '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 }'}, 'player'], 'result': 'james kaprelian', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; hometown ; ca } ; player }'}, 'james kaprelian'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; hometown ; ca } ; player } ; james kaprelian }', 'tointer': 'the player record of this unqiue row is james kaprelian .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; hometown ; ca } } ; eq { hop { filter_eq { all_rows ; hometown ; ca } ; player } ; james kaprelian } } = true', 'tointer': 'select the rows whose hometown record fuzzily matches to ca . there is only one such row in the table . the player record of this unqiue row is james kaprelian .'} | and { only { filter_eq { all_rows ; hometown ; ca } } ; eq { hop { filter_eq { all_rows ; hometown ; ca } ; player } ; james kaprelian } } = true | select the rows whose hometown record fuzzily matches to ca . there is only one such row in the table . the player record of this unqiue row is james kaprelian . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'hometown_7': 7, 'ca_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'player_9': 9, 'james kaprelian_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'hometown_7': 'hometown', 'ca_8': 'ca', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'player_9': 'player', 'james kaprelian_10': 'james kaprelian'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'hometown_7': [0], 'ca_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'player_9': [2], 'james kaprelian_10': [3]} | ['player', 'position', 'school', 'hometown', 'mlb draft'] | [['byron buxton', 'pitcher / outfielder', 'appling county high school', 'baxley , ga', '1st round - 2nd pick of the 2012 draft ( twins )'], ['gavin cecchini', 'infielder', 'barbe high school', 'lake charles , la', '1st round - 12th pick of the 2012 draft ( mets )'], ['james kaprelian', 'pitcher', 'beckman high school', 'irvine , ca', 'attended ucla'], ['rob kaminsky', 'pitcher', 'saint joseph regional high school', 'montvale , nj', 'kaminsky was only a junior'], ['taylor hawkins', 'infielder', 'carl albert high school', 'midwest city , ok', 'attended oklahoma']] |
wpar | https://en.wikipedia.org/wiki/WPAR | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12840409-2.html.csv | count | four of the wpar radio channels operate on an erp wattage of 10 . | {'scope': 'all', 'criterion': 'equal', 'value': '10', 'result': '4', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'erp w', '10'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose erp w record is equal to 10 .', 'tostr': 'filter_eq { all_rows ; erp w ; 10 }'}], 'result': '4', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; erp w ; 10 } }', 'tointer': 'select the rows whose erp w record is equal to 10 . the number of such rows is 4 .'}, '4'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; erp w ; 10 } } ; 4 } = true', 'tointer': 'select the rows whose erp w record is equal to 10 . the number of such rows is 4 .'} | eq { count { filter_eq { all_rows ; erp w ; 10 } } ; 4 } = true | select the rows whose erp w record is equal to 10 . the number of such rows is 4 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_eq_0': 0, 'all_rows_4': 4, 'erp w_5': 5, '10_6': 6, '4_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'erp w_5': 'erp w', '10_6': '10', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'erp w_5': [0], '10_6': [0], '4_7': [2]} | ['call sign', 'frequency mhz', 'city of license', 'erp w', 'class', 'fcc info'] | [['w294aj', '106.7', 'charlottesville , virginia', '21', 'd', 'fcc'], ['w236ad', '95.1', 'lawrenceville , virginia', '25', 'd', 'fcc'], ['w246bz', '97.1', 'crewe , virginia', '38', 'd', 'fcc'], ['w254ah', '98.7', 'farmville , virginia', '27', 'd', 'fcc'], ['w272cc', '102.3', 'smithfield , virginia', '10', 'd', 'fcc'], ['w273aa', '102.5', 'blacksburg , virginia', '10', 'd', 'fcc'], ['w274ab', '102.7', 'petersburg , virginia', '30', 'd', 'fcc'], ['w291aj', '106.1', 'waverly , virginia', '27', 'd', 'fcc'], ['w292cu', '106.3', 'christiansburg , virginia', '10', 'd', 'fcc'], ['w295ai', '106.9', 'marion , virginia', '10', 'd', 'fcc']] |
1979 world ice hockey championships | https://en.wikipedia.org/wiki/1979_World_Ice_Hockey_Championships | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14190283-9.html.csv | aggregation | the average number of points that teams earned in the 1979 world ice hockey championships were 7 . | {'scope': 'all', 'col': '5', 'type': 'average', 'result': '7', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'points'], 'result': '7', 'ind': 0, 'tostr': 'avg { all_rows ; points }'}, '7'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; points } ; 7 } = true', 'tointer': 'the average of the points record of all rows is 7 .'} | round_eq { avg { all_rows ; points } ; 7 } = true | the average of the points record of all rows is 7 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'points_4': 4, '7_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'points_4': 'points', '7_5': '7'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'points_4': [0], '7_5': [1]} | ['games', 'drawn', 'lost', 'points difference', 'points'] | [['7', '0', '0', '83 - 10', '14'], ['7', '0', '1', '64 - 17', '12'], ['7', '0', '2', '59 - 27', '10'], ['7', '0', '3', '35 - 28', '8'], ['7', '0', '5', '23 - 68', '4'], ['7', '0', '5', '25 - 48', '4'], ['7', '1', '5', '16 - 67', '3'], ['7', '1', '6', '13 - 53', '1']] |
1955 vfl season | https://en.wikipedia.org/wiki/1955_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10773753-1.html.csv | majority | most of the vfl games taking place on 16 april 1955 had at least 20000 spectators . | {'scope': 'all', 'col': '6', 'most_or_all': 'most', 'criterion': 'greater_than_eq', 'value': '20000', 'subset': None} | {'func': 'most_greater_eq', 'args': ['all_rows', 'crowd', '20000'], 'result': True, 'ind': 0, 'tointer': 'for the crowd records of all rows , most of them are greater than or equal to 20000 .', 'tostr': 'most_greater_eq { all_rows ; crowd ; 20000 } = true'} | most_greater_eq { all_rows ; crowd ; 20000 } = true | for the crowd records of all rows , most of them are greater than or equal to 20000 . | 1 | 1 | {'most_greater_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'crowd_3': 3, '20000_4': 4} | {'most_greater_eq_0': 'most_greater_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'crowd_3': 'crowd', '20000_4': '20000'} | {'most_greater_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'crowd_3': [0], '20000_4': [0]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['geelong', '15.14 ( 104 )', 'south melbourne', '9.12 ( 66 )', 'kardinia park', '20976', '16 april 1955'], ['fitzroy', '13.15 ( 93 )', 'hawthorn', '7.16 ( 58 )', 'brunswick street oval', '16000', '16 april 1955'], ['collingwood', '6.12 ( 48 )', 'footscray', '15.14 ( 104 )', 'victoria park', '33398', '16 april 1955'], ['carlton', '19.20 ( 134 )', 'north melbourne', '10.5 ( 65 )', 'princes park', '25041', '16 april 1955'], ['st kilda', '8.11 ( 59 )', 'melbourne', '17.16 ( 118 )', 'junction oval', '20000', '16 april 1955'], ['richmond', '9.23 ( 77 )', 'essendon', '13.16 ( 94 )', 'punt road oval', '30000', '16 april 1955']] |
1991 cleveland browns season | https://en.wikipedia.org/wiki/1991_Cleveland_Browns_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10650028-2.html.csv | majority | the majority of games were losses for the cleveland browns . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': 'l', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'result', 'l'], 'result': True, 'ind': 0, 'tointer': 'for the result records of all rows , most of them fuzzily match to l .', 'tostr': 'most_eq { all_rows ; result ; l } = true'} | most_eq { all_rows ; result ; l } = true | for the result records of all rows , most of them fuzzily match to l . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'result_3': 3, 'l_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'result_3': 'result', 'l_4': 'l'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'result_3': [0], 'l_4': [0]} | ['week', 'date', 'opponent', 'result', 'attendance'] | [['1', 'september 1 , 1991', 'dallas cowboys', 'l 26 - 14', '78860'], ['2', 'september 8 , 1991', 'new england patriots', 'w 20 - 0', '35377'], ['3', 'september 15 , 1991', 'cincinnati bengals', 'w 14 - 13', '78269'], ['4', 'september 22 , 1991', 'new york giants', 'l 10 - 13', '75891'], ['5', 'october 6 , 1991', 'new york jets', 'l 17 - 14', '71042'], ['6', 'october 13 , 1991', 'washington redskins', 'l 42 - 17', '54715'], ['7', 'october 20 , 1991', 'san diego chargers', 'w 30 - 24', '48440'], ['8', 'october 27 , 1991', 'pittsburgh steelers', 'w 17 - 14', '78285'], ['9', 'november 3 , 1991', 'cincinnati bengals', 'l 23 - 21', '55077'], ['10', 'november 10 , 1991', 'philadelphia eagles', 'l 32 - 30', '72086'], ['11', 'november 17 , 1991', 'houston oilers', 'l 28 - 24', '58155'], ['12', 'november 24 , 1991', 'kansas city chiefs', 'w 20 - 15', '63991'], ['13', 'december 1 , 1991', 'indianapolis colts', 'w 31 - 0', '57539'], ['14', 'december 8 , 1991', 'denver broncos', 'l 17 - 7', '73539'], ['15', 'december 15 , 1991', 'houston oilers', 'l 17 - 14', '55680'], ['16', 'december 22 , 1991', 'pittsburgh steelers', 'l 17 - 10', '47070']] |
2007 detroit lions season | https://en.wikipedia.org/wiki/2007_Detroit_Lions_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10147486-2.html.csv | comparative | more people went to the game on december 30 , than the game on december 23 . | {'row_1': '16', 'row_2': '15', 'col': '5', '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', 'date', 'december 30 , 2007'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose date record fuzzily matches to december 30 , 2007 .', 'tostr': 'filter_eq { all_rows ; date ; december 30 , 2007 }'}, 'attendance'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; date ; december 30 , 2007 } ; attendance }', 'tointer': 'select the rows whose date record fuzzily matches to december 30 , 2007 . take the attendance record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', 'december 23 , 2007'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose date record fuzzily matches to december 23 , 2007 .', 'tostr': 'filter_eq { all_rows ; date ; december 23 , 2007 }'}, 'attendance'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; date ; december 23 , 2007 } ; attendance }', 'tointer': 'select the rows whose date record fuzzily matches to december 23 , 2007 . take the attendance record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; date ; december 30 , 2007 } ; attendance } ; hop { filter_eq { all_rows ; date ; december 23 , 2007 } ; attendance } } = true', 'tointer': 'select the rows whose date record fuzzily matches to december 30 , 2007 . take the attendance record of this row . select the rows whose date record fuzzily matches to december 23 , 2007 . take the attendance record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; date ; december 30 , 2007 } ; attendance } ; hop { filter_eq { all_rows ; date ; december 23 , 2007 } ; attendance } } = true | select the rows whose date record fuzzily matches to december 30 , 2007 . take the attendance record of this row . select the rows whose date record fuzzily matches to december 23 , 2007 . take the attendance record of this row . the first record is greater than the second record . | 5 | 5 | {'greater_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'date_7': 7, 'december 30 , 2007_8': 8, 'attendance_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'date_11': 11, 'december 23 , 2007_12': 12, 'attendance_13': 13} | {'greater_4': 'greater', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'date_7': 'date', 'december 30 , 2007_8': 'december 30 , 2007', 'attendance_9': 'attendance', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'date_11': 'date', 'december 23 , 2007_12': 'december 23 , 2007', 'attendance_13': 'attendance'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'date_7': [0], 'december 30 , 2007_8': [0], 'attendance_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'date_11': [1], 'december 23 , 2007_12': [1], 'attendance_13': [3]} | ['week', 'date', 'opponent', 'result', 'attendance'] | [['1', 'september 9 , 2007', 'oakland raiders', 'w 36 - 21', '61547'], ['2', 'september 16 , 2007', 'minnesota vikings', 'w 20 - 17 ( ot )', '61771'], ['3', 'september 23 , 2007', 'philadelphia eagles', 'l 21 - 56', '67570'], ['4', 'september 30 , 2007', 'chicago bears', 'w 37 - 27', '60811'], ['5', 'october 7 , 2007', 'washington redskins', 'l 3 - 34', '88944'], ['7', 'october 21 , 2007', 'tampa bay buccaneers', 'w 23 - 16', '60442'], ['8', 'october 28 , 2007', 'chicago bears', 'w 16 - 7', '62171'], ['9', 'november 4 , 2007', 'denver broncos', 'w 44 - 7', '60783'], ['10', 'november 11 , 2007', 'arizona cardinals', 'l 21 - 31', '64753'], ['11', 'november 18 , 2007', 'new york giants', 'l 10 - 16', '60675'], ['12', 'november 22 , 2007', 'green bay packers', 'l 26 - 37', '63257'], ['13', 'december 2 , 2007', 'minnesota vikings', 'l 10 - 42', '62996'], ['14', 'december 9 , 2007', 'dallas cowboys', 'l 27 - 28', '62759'], ['15', 'december 16 , 2007', 'san diego chargers', 'l 14 - 51', '66505'], ['16', 'december 23 , 2007', 'kansas city chiefs', 'w 25 - 20', '59938'], ['17', 'december 30 , 2007', 'green bay packers', 'l 13 - 34', '70869']] |
livonia cup | https://en.wikipedia.org/wiki/Livonia_Cup | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14157023-1.html.csv | unique | skonto fc is the only club who attained the livonia cup runner - up position once . | {'scope': 'all', 'row': '1', 'col': '4', 'col_other': 'n/a', 'criterion': 'equal', 'value': 'skonto fc', 'subset': None} | {'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'runner - up', 'skonto fc'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose runner - up record fuzzily matches to skonto fc .', 'tostr': 'filter_eq { all_rows ; runner - up ; skonto fc }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; runner - up ; skonto fc } } = true', 'tointer': 'select the rows whose runner - up record fuzzily matches to skonto fc . there is only one such row in the table .'} | only { filter_eq { all_rows ; runner - up ; skonto fc } } = true | select the rows whose runner - up record fuzzily matches to skonto fc . there is only one such row in the table . | 2 | 2 | {'only_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, 'runner - up_4': 4, 'skonto fc_5': 5} | {'only_1': 'only', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'runner - up_4': 'runner - up', 'skonto fc_5': 'skonto fc'} | {'only_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'runner - up_4': [0], 'skonto fc_5': [0]} | ['season', 'winner', 'score', 'runner - up', 'venue'] | [['2011', 'fc flora tallinn', '2 - 0', 'skonto fc', 'skonto hall , riga'], ['2008', 'fk ventspils', '2 - 2 aet , 4 - 3 pen', 'fc levadia tallinn', 'skonto hall , riga'], ['2005', 'skonto fc', '4 - 3', 'fc levadia tallinn', 'skonto hall , riga'], ['2004', 'skonto fc', '3 - 3 aet , 4 - 3 pen', 'fc flora tallinn', 'skonto hall , riga'], ['2003', 'skonto fc', '2 - 2 aet , 12 - 11 pen', 'fc flora tallinn', 'skonto hall , riga']] |
fortune global 500 | https://en.wikipedia.org/wiki/Fortune_Global_500 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17581425-1.html.csv | count | 2 of the fortune global 500 companies from china are in the petroleum industry . | {'scope': 'subset', 'criterion': 'equal', 'value': 'petroleum', 'result': '2', 'col': '4', 'subset': {'col': '3', 'criterion': 'equal', 'value': 'china'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'china'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; country ; china }', 'tointer': 'select the rows whose country record fuzzily matches to china .'}, 'industry', 'petroleum'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose country record fuzzily matches to china . among these rows , select the rows whose industry record fuzzily matches to petroleum .', 'tostr': 'filter_eq { filter_eq { all_rows ; country ; china } ; industry ; petroleum }'}], 'result': '2', 'ind': 2, 'tostr': 'count { filter_eq { filter_eq { all_rows ; country ; china } ; industry ; petroleum } }', 'tointer': 'select the rows whose country record fuzzily matches to china . among these rows , select the rows whose industry record fuzzily matches to petroleum . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_eq { filter_eq { all_rows ; country ; china } ; industry ; petroleum } } ; 2 } = true', 'tointer': 'select the rows whose country record fuzzily matches to china . among these rows , select the rows whose industry record fuzzily matches to petroleum . the number of such rows is 2 .'} | eq { count { filter_eq { filter_eq { all_rows ; country ; china } ; industry ; petroleum } } ; 2 } = true | select the rows whose country record fuzzily matches to china . among these rows , select the rows whose industry record fuzzily matches to petroleum . the number of such rows is 2 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_str_eq_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'country_6': 6, 'china_7': 7, 'industry_8': 8, 'petroleum_9': 9, '2_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_str_eq_1': 'filter_str_eq', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'country_6': 'country', 'china_7': 'china', 'industry_8': 'industry', 'petroleum_9': 'petroleum', '2_10': '2'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_str_eq_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'country_6': [0], 'china_7': [0], 'industry_8': [1], 'petroleum_9': [1], '2_10': [3]} | ['rank', 'company', 'country', 'industry', 'revenue in usd'] | [['1', 'royal dutch shell', 'netherlands', 'petroleum', '481.7 billion'], ['2', 'walmart', 'united states', 'retail', '469.2 billion'], ['3', 'exxonmobil', 'united states', 'petroleum', '449.9 billion'], ['4', 'sinopec', 'china', 'petroleum', '428.2 billion'], ['5', 'china national petroleum corporation', 'china', 'petroleum', '408.6 billion'], ['6', 'bp', 'united kingdom', 'petroleum', '388.3 billion'], ['7', 'state grid corporation of china', 'china', 'power', '298.4 billion'], ['8', 'toyota', 'japan', 'automobiles', '265.7 billion'], ['9', 'volkswagen', 'germany', 'automobiles', '247.6 billion'], ['10', 'total', 'france', 'petroleum', '234.3 billion']] |
2008 - 09 miami heat season | https://en.wikipedia.org/wiki/2008%E2%80%9309_Miami_Heat_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17311783-5.html.csv | ordinal | the third game played in november was an away game against san antonio . | {'row': '3', 'col': '2', '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', 'date', '3'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; date ; 3 }'}, 'team'], 'result': 'san antonio', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; date ; 3 } ; team }'}, 'san antonio'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; date ; 3 } ; team } ; san antonio } = true', 'tointer': 'select the row whose date record of all rows is 3rd minimum . the team record of this row is san antonio .'} | eq { hop { nth_argmin { all_rows ; date ; 3 } ; team } ; san antonio } = true | select the row whose date record of all rows is 3rd minimum . the team record of this row is san antonio . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'date_5': 5, '3_6': 6, 'team_7': 7, 'san antonio_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmin_0': 'nth_argmin', 'all_rows_4': 'all_rows', 'date_5': 'date', '3_6': '3', 'team_7': 'team', 'san antonio_8': 'san antonio'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'date_5': [0], '3_6': [0], 'team_7': [1], 'san antonio_8': [2]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record'] | [['3', 'november 1', 'charlotte', 'l 87 - 100 ( ot )', 'michael beasley ( 25 )', 'shawn marion ( 8 )', 'mario chalmers ( 8 )', 'time warner cable arena 19238', '1 - 2'], ['4', 'november 5', 'philadelphia', 'w 106 - 83 ( ot )', 'dwyane wade ( 29 )', 'michael beasley ( 9 )', 'dwyane wade , mario chalmers ( 6 )', 'american airlines arena 15103', '2 - 2'], ['5', 'november 7', 'san antonio', 'w 99 - 83 ( ot )', 'dwyane wade ( 33 )', 'dwyane wade , udonis haslem ( 10 )', 'dwyane wade ( 9 )', 'at & t center 17387', '3 - 2'], ['6', 'november 8', 'new orleans', 'l 89 - 100 ( ot )', 'dwyane wade ( 30 )', 'shawn marion ( 8 )', 'dwyane wade ( 10 )', 'new orleans arena 17701', '3 - 3'], ['7', 'november 10', 'new jersey', 'w 99 - 94 ( ot )', 'dwyane wade ( 33 )', 'udonis haslem ( 8 )', 'dwyane wade ( 5 )', 'american airlines arena 15028', '4 - 3'], ['8', 'november 12', 'portland', 'l 96 - 104 ( ot )', 'dwyane wade ( 36 )', 'udonis haslem ( 11 )', 'dwyane wade ( 8 )', 'american airlines arena 15021', '4 - 4'], ['9', 'november 14', 'washington', 'w 97 - 77 ( ot )', 'dwyane wade ( 24 )', 'udonis haslem ( 13 )', 'mario chalmers ( 7 )', 'american airlines arena 15284', '5 - 4'], ['10', 'november 16', 'toronto', 'l 96 - 107 ( ot )', 'dwyane wade ( 29 )', 'udonis haslem ( 10 )', 'dwyane wade ( 8 )', 'air canada centre 19800', '5 - 5'], ['11', 'november 18', 'washington', 'w 94 - 87 ( ot )', 'dwyane wade ( 19 )', 'udonis haslem ( 11 )', 'dwyane wade ( 10 )', 'verizon center 15102', '6 - 5'], ['12', 'november 19', 'toronto', 'l 95 - 101 ( ot )', 'dwyane wade ( 40 )', 'shawn marion ( 14 )', 'dwyane wade ( 11 )', 'american airlines arena 15014', '6 - 6'], ['13', 'november 22', 'indiana', 'w 109 - 100 ( ot )', 'dwyane wade ( 38 )', 'shawn marion ( 9 )', 'dwyane wade ( 8 )', 'american airlines arena 18685', '7 - 6'], ['14', 'november 24', 'houston', 'l 98 - 107 ( ot )', 'dwyane wade , mario chalmers ( 23 )', 'joel anthony ( 8 )', 'mario chalmers ( 6 )', 'american airlines arena 18704', '7 - 7'], ['15', 'november 26', 'portland', 'l 68 - 106 ( ot )', 'michael beasley ( 14 )', 'dwyane wade , udonis haslem ( 6 )', 'dwyane wade ( 6 )', 'rose garden 20528', '7 - 8'], ['16', 'november 28', 'phoenix', 'w 107 - 92 ( ot )', 'dwyane wade ( 43 )', 'udonis haslem ( 11 )', 'dwyane wade , shawn marion ( 6 )', 'us airways center 18422', '8 - 8'], ['17', 'november 29', 'la clippers', 'l 96 - 97 ( ot )', 'dwyane wade ( 26 )', 'shawn marion ( 9 )', 'dwyane wade ( 11 )', 'staples center 16245', '8 - 9']] |
katarina srebotnik | https://en.wikipedia.org/wiki/Katarina_Srebotnik | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1729366-4.html.csv | count | katarina srebotnik had a winning outcome in her tournaments four times . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'winner', 'result': '4', 'col': '1', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'outcome', 'winner'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose outcome record fuzzily matches to winner .', 'tostr': 'filter_eq { all_rows ; outcome ; winner }'}], 'result': '4', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; outcome ; winner } }', 'tointer': 'select the rows whose outcome record fuzzily matches to winner . the number of such rows is 4 .'}, '4'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; outcome ; winner } } ; 4 } = true', 'tointer': 'select the rows whose outcome record fuzzily matches to winner . the number of such rows is 4 .'} | eq { count { filter_eq { all_rows ; outcome ; winner } } ; 4 } = true | select the rows whose outcome record fuzzily matches to winner . 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, 'outcome_5': 5, 'winner_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', 'outcome_5': 'outcome', 'winner_6': 'winner', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'outcome_5': [0], 'winner_6': [0], '4_7': [2]} | ['outcome', 'date', 'tournament', 'surface', 'opponent in final', 'score in final'] | [['winner', 'april 11 , 1999', 'estoril , portugal', 'clay', 'rita kuti - kis', '6 - 3 , 6 - 1'], ['runner - up', 'february 24 , 2002', 'bogotá , colombia', 'clay', 'fabiola zuluaga', '1 - 6 , 4 - 6'], ['winner', 'march 3 , 2002', 'acapulco , mexico', 'clay', 'paola suárez', '6 - 7 ( 1 - 7 ) , 6 - 4 , 6 - 2'], ['runner - up', 'july 13 , 2003', 'palermo , italy', 'clay', 'dinara safina', '3 - 6 , 4 - 6'], ['winner', 'january 8 , 2005', 'auckland , new zealand', 'hard', 'shinobu asagoe', '5 - 7 , 7 - 5 , 6 - 4'], ['winner', 'august 14 , 2005', 'stockholm , sweden', 'hard', 'anastasia myskina', '7 - 5 , 6 - 2'], ['runner - up', 'september 25 , 2005', 'portorož , slovenia', 'hard', 'klára koukalová', '2 - 6 , 6 - 4 , 3 - 6'], ['runner - up', 'july 25 , 2006', 'cincinnati , united states', 'hard', 'vera zvonareva', '2 - 6 , 4 - 6'], ['runner - up', 'september 23 , 2007', 'portorož , slovenia', 'hard', 'tatiana golovin', '6 - 2 , 4 - 6 , 4 - 6'], ['runner - up', 'may 25 , 2008', 'strasbourg , france', 'clay', 'anabel medina garrigues', '6 - 4 , 6 - 7 ( 4 - 7 ) , 0 - 6']] |
1981 vfl season | https://en.wikipedia.org/wiki/1981_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10823950-11.html.csv | count | three of the matches took place on june 6 1981 . | {'scope': 'all', 'criterion': 'equal', 'value': '6 june 1981', 'result': '3', 'col': '7', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', '6 june 1981'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose date record fuzzily matches to 6 june 1981 .', 'tostr': 'filter_eq { all_rows ; date ; 6 june 1981 }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; date ; 6 june 1981 } }', 'tointer': 'select the rows whose date record fuzzily matches to 6 june 1981 . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; date ; 6 june 1981 } } ; 3 } = true', 'tointer': 'select the rows whose date record fuzzily matches to 6 june 1981 . the number of such rows is 3 .'} | eq { count { filter_eq { all_rows ; date ; 6 june 1981 } } ; 3 } = true | select the rows whose date record fuzzily matches to 6 june 1981 . 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, 'date_5': 5, '6 june 1981_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', 'date_5': 'date', '6 june 1981_6': '6 june 1981', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'date_5': [0], '6 june 1981_6': [0], '3_7': [2]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['richmond', '20.16 ( 136 )', 'melbourne', '14.10 ( 94 )', 'mcg', '31025', '6 june 1981'], ['st kilda', '14.15 ( 99 )', 'fitzroy', '7.17 ( 59 )', 'moorabbin oval', '21672', '6 june 1981'], ['hawthorn', '18.19 ( 127 )', 'collingwood', '12.9 ( 81 )', 'vfl park', '92935', '6 june 1981'], ['footscray', '12.10 ( 82 )', 'geelong', '17.15 ( 117 )', 'western oval', '24974', '8 june 1981'], ['carlton', '17.13 ( 115 )', 'north melbourne', '11.18 ( 84 )', 'princes park', '31808', '8 june 1981'], ['south melbourne', '12.8 ( 80 )', 'essendon', '15.18 ( 108 )', 'lake oval', '28588', '8 june 1981']] |
norwegian international | https://en.wikipedia.org/wiki/Norwegian_International | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12121208-1.html.csv | comparative | kasperi salo raced in the men 's singles before ville land did . | {'row_1': '11', 'row_2': '5', 'col': '1', 'col_other': '2', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', "men 's singles", 'kasperi salo'], 'result': None, 'ind': 0, 'tointer': "select the rows whose men 's singles record fuzzily matches to kasperi salo .", 'tostr': "filter_eq { all_rows ; men 's singles ; kasperi salo }"}, 'year'], 'result': None, 'ind': 2, 'tostr': "hop { filter_eq { all_rows ; men 's singles ; kasperi salo } ; year }", 'tointer': "select the rows whose men 's singles record fuzzily matches to kasperi salo . take the year record of this row ."}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', "men 's singles", 'ville lang'], 'result': None, 'ind': 1, 'tointer': "select the rows whose men 's singles record fuzzily matches to ville lang .", 'tostr': "filter_eq { all_rows ; men 's singles ; ville lang }"}, 'year'], 'result': None, 'ind': 3, 'tostr': "hop { filter_eq { all_rows ; men 's singles ; ville lang } ; year }", 'tointer': "select the rows whose men 's singles record fuzzily matches to ville lang . take the year record of this row ."}], 'result': True, 'ind': 4, 'tostr': "less { hop { filter_eq { all_rows ; men 's singles ; kasperi salo } ; year } ; hop { filter_eq { all_rows ; men 's singles ; ville lang } ; year } } = true", 'tointer': "select the rows whose men 's singles record fuzzily matches to kasperi salo . take the year record of this row . select the rows whose men 's singles record fuzzily matches to ville lang . take the year record of this row . the first record is less than the second record ."} | less { hop { filter_eq { all_rows ; men 's singles ; kasperi salo } ; year } ; hop { filter_eq { all_rows ; men 's singles ; ville lang } ; year } } = true | select the rows whose men 's singles record fuzzily matches to kasperi salo . take the year record of this row . select the rows whose men 's singles record fuzzily matches to ville lang . take the year 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, "men 's singles_7": 7, 'kasperi salo_8': 8, 'year_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, "men 's singles_11": 11, 'ville lang_12': 12, 'year_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', "men 's singles_7": "men 's singles", 'kasperi salo_8': 'kasperi salo', 'year_9': 'year', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', "men 's singles_11": "men 's singles", 'ville lang_12': 'ville lang', 'year_13': 'year'} | {'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], "men 's singles_7": [0], 'kasperi salo_8': [0], 'year_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], "men 's singles_11": [1], 'ville lang_12': [1], 'year_13': [3]} | ['year', "men 's singles", "women 's singles", "men 's doubles", "women 's doubles", 'mixed doubles'] | [['2012', 'chou tien - chen', 'sashina vignes waran', 'ruud bosch koen ridder', 'samantha barning eefje muskens', 'jorrit de ruiter samantha barning'], ['2011', 'ville lang', 'linda zechiri', 'rasmus bonde anders kristiansen', 'eva lee paula lynn obanana', 'sam magee chloe magee'], ['2010', 'hans - kristian vittinghus', 'olga konon', 'ingo kindervater johannes schoettler', 'lotte jonathans paulien van dooremalen', 'michael fuchs birgit overzier'], ['2009', 'hans - kristian vittinghus', 'juliane schenk', 'rasmus bonde simon mollyhus', 'helle nielsen marie røpke', 'marcus ellis heather olver'], ['2008', 'ville lang', 'zhang xi', 'michael fuchs ingo kindervater', 'anastasia russkikh irina hlebko', 'michael fuchs annekatrin lillie'], ['2007', 'marc zwiebler', 'juliane schenk', 'howard bach bob malaythong', 'anastasia russkikh ekaterina ananina', 'kristof hopp birgit overzier'], ['2006', 'hans - kristian vittinghus', 'sara persson', 'anton nazarenko andrey ashmarin', 'imogen bankier emma mason', 'imam sodikin irawan elin bergblom'], ['2005', 'eric pang', 'juliane schenk', 'vidre wilbowo imam sodikin irawan', 'nicole grether juliane schenk', 'kristof hopp birgit overzier'], ['2004', 'björn joppien', 'petra overzier', 'kristof hopp ingo kindervater', 'liza parker suzanne rayappan', 'frederik bergström johanna persson'], ['2003', 'per - henrik croona', 'tine rasmussen', 'lee jae - jin hwang ji - man', 'ha jung - eun oh seul - ki', 'lee jae - jin lee eun - woo'], ['2002', 'kasperi salo', 'tine rasmussen', 'alexandr nikolaenko nikolaj nikolaenko', 'frida andreasson lina uhac', 'jörgen olsson frida andreasson'], ['2001', 'irwansyah', 'anu weckstrom', 'martin delfs jonas glyager jensen', 'karina sorensen julie houmann', 'tommy sorensen karina sorensen']] |
seven wonders of the ancient world | https://en.wikipedia.org/wiki/Seven_Wonders_of_the_Ancient_World | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-19342760-1.html.csv | unique | the great pyramid of giza is the only wonder of the ancient world that is still in existence . | {'scope': 'all', 'row': '1', 'col': '5', 'col_other': '1', 'criterion': 'equal', 'value': 'still in existence', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'cause of destruction', 'still in existence'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose cause of destruction record fuzzily matches to still in existence .', 'tostr': 'filter_eq { all_rows ; cause of destruction ; still in existence }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; cause of destruction ; still in existence } }', 'tointer': 'select the rows whose cause of destruction record fuzzily matches to still in existence . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'cause of destruction', 'still in existence'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose cause of destruction record fuzzily matches to still in existence .', 'tostr': 'filter_eq { all_rows ; cause of destruction ; still in existence }'}, 'name'], 'result': 'great pyramid of giza', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; cause of destruction ; still in existence } ; name }'}, 'great pyramid of giza'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; cause of destruction ; still in existence } ; name } ; great pyramid of giza }', 'tointer': 'the name record of this unqiue row is great pyramid of giza .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; cause of destruction ; still in existence } } ; eq { hop { filter_eq { all_rows ; cause of destruction ; still in existence } ; name } ; great pyramid of giza } } = true', 'tointer': 'select the rows whose cause of destruction record fuzzily matches to still in existence . there is only one such row in the table . the name record of this unqiue row is great pyramid of giza .'} | and { only { filter_eq { all_rows ; cause of destruction ; still in existence } } ; eq { hop { filter_eq { all_rows ; cause of destruction ; still in existence } ; name } ; great pyramid of giza } } = true | select the rows whose cause of destruction record fuzzily matches to still in existence . there is only one such row in the table . the name record of this unqiue row is great pyramid of giza . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'cause of destruction_7': 7, 'still in existence_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'name_9': 9, 'great pyramid of giza_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'cause of destruction_7': 'cause of destruction', 'still in existence_8': 'still in existence', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'name_9': 'name', 'great pyramid of giza_10': 'great pyramid of giza'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'cause of destruction_7': [0], 'still in existence_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'name_9': [2], 'great pyramid of giza_10': [3]} | ['name', 'date of construction', 'builder', 'date of destruction', 'cause of destruction', 'modern location'] | [['great pyramid of giza', '2584 - 2561 bc', 'egyptians', 'still in existence', 'still in existence', 'giza necropolis , egypt'], ['temple of artemis at ephesus', 'c 550 bc , and again at 323 bc', 'ns lydia , greeks', '356 bc ( by herostratus ) ad 262 ( by the goths )', 'arson by herostratus , plundering', 'near selçuk , izmir province , turkey'], ['statue of zeus at olympia', '466 - 456 bc ( temple ) 435 bc ( statue )', 'greeks', '5th - 6th centuries ad', 'disassembled , later destroyed by fire', 'olympia , greece'], ['mausoleum at halicarnassus', '351 bc', 'carians , greeks', 'by ad 1494', 'earthquakes', 'bodrum , turkey'], ['colossus of rhodes', '292 - 280 bc', 'greeks', '226 bc', '226 bc rhodes earthquake', 'rhodes , greece']] |
list of asian and pacific countries by gdp ( ppp ) | https://en.wikipedia.org/wiki/List_of_Asian_and_Pacific_countries_by_GDP_%28PPP%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2248784-4.html.csv | superlative | of the list of asian and pacific countries by gdp iran has the greatest gdp . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '4', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', '2011 gdp ( ppp ) billions of usd'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; 2011 gdp ( ppp ) billions of usd }'}, 'country'], 'result': 'iran', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; 2011 gdp ( ppp ) billions of usd } ; country }'}, 'iran'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; 2011 gdp ( ppp ) billions of usd } ; country } ; iran } = true', 'tointer': 'select the row whose 2011 gdp ( ppp ) billions of usd record of all rows is maximum . the country record of this row is iran .'} | eq { hop { argmax { all_rows ; 2011 gdp ( ppp ) billions of usd } ; country } ; iran } = true | select the row whose 2011 gdp ( ppp ) billions of usd record of all rows is maximum . the country record of this row is iran . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, '2011 gdp (ppp) billions of usd_5': 5, 'country_6': 6, 'iran_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', '2011 gdp (ppp) billions of usd_5': '2011 gdp ( ppp ) billions of usd', 'country_6': 'country', 'iran_7': 'iran'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], '2011 gdp (ppp) billions of usd_5': [0], 'country_6': [1], 'iran_7': [2]} | ['rank mideast', 'rank asia', 'rank world', 'country', '2011 gdp ( ppp ) billions of usd'] | [['1', '6', '17', 'iran', '930.236'], ['2', '9', '23', 'saudi arabia', '677.663'], ['3', '18', '48', 'united arab emirates', '261.189'], ['4', '19', '50', 'israel', '235.446'], ['5', '21', '55', 'qatar', '181.912'], ['6', '22', '58', 'kuwait', '150.002'], ['7', '23', '60', 'iraq', '127.348'], ['8', '26', '66', 'syria', '107.803'], ['9', '29', '76', 'oman', '81.005'], ['10', '30', '83', 'yemen', '63.344'], ['11', '31', '84', 'lebanon', '61.738'], ['12', '35', '97', 'jordan', '36.897'], ['13', '37', '104', 'bahrain', '30.889']] |
million dollar password | https://en.wikipedia.org/wiki/Million_Dollar_Password | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13673176-3.html.csv | aggregation | of the episodes of the million dollar password game show listed , the total number of viewers was 54.22 million . | {'scope': 'all', 'col': '6', 'type': 'sum', 'result': '54.22 million', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'viewers ( millions )'], 'result': '54.22 million', 'ind': 0, 'tostr': 'sum { all_rows ; viewers ( millions ) }'}, '54.22 million'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; viewers ( millions ) } ; 54.22 million } = true', 'tointer': 'the sum of the viewers ( millions ) record of all rows is 54.22 million .'} | round_eq { sum { all_rows ; viewers ( millions ) } ; 54.22 million } = true | the sum of the viewers ( millions ) record of all rows is 54.22 million . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'viewers (millions)_4': 4, '54.22 million_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'viewers (millions)_4': 'viewers ( millions )', '54.22 million_5': '54.22 million'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'viewers (millions)_4': [0], '54.22 million_5': [1]} | ['airdate', 'celebrities', 'rating', 'share', '1849', 'viewers ( millions )', 'weekly rank', 'prod code'] | [['sunday , june 1 , 2008', 'neil patrick harris , rachael ray', '6.8', '12', '2.2 / 7', '10.69', '3', '106'], ['sunday , june 8 , 2008', "tony hawk , rosie o'donnell", '6.3', '11', '2.1 / 6', '9.64', '5', '104'], ['thursday , june 12 , 2008', 'susie essman , betty white', '6.4', '12', '2.0 / 7', '9.52', '7', '102'], ['sunday , june 22 , 2008', 'shanna moakler , steven weber', '5.5', '10', '1.5 / 5', '8.29', '12', '105'], ['sunday , june 29 , 2008', 'sara evans , steve schirripa', '5.6', '10', '1.7 / 5', '8.55', '7', '101'], ['sunday , july 6 , 2008', 'monique coleman , damien fahey', '5.0', '9', '1.3 / 5', '7.53', '3', '103']] |
10k run | https://en.wikipedia.org/wiki/10K_run | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17370134-3.html.csv | ordinal | of the athletes from kenya who are highly ranked in 10k runs , isabella ochichi was the fastest . | {'scope': 'subset', 'row': '2', 'col': '2', 'order': '1', 'col_other': '3', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'subset': {'col': '4', 'criterion': 'equal', 'value': 'kenya'}} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'nation', 'kenya'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; nation ; kenya }', 'tointer': 'select the rows whose nation record fuzzily matches to kenya .'}, 'time', '1'], 'result': None, 'ind': 1, 'tostr': 'nth_argmin { filter_eq { all_rows ; nation ; kenya } ; time ; 1 }'}, 'athlete'], 'result': 'isabella ochichi', 'ind': 2, 'tostr': 'hop { nth_argmin { filter_eq { all_rows ; nation ; kenya } ; time ; 1 } ; athlete }'}, 'isabella ochichi'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { nth_argmin { filter_eq { all_rows ; nation ; kenya } ; time ; 1 } ; athlete } ; isabella ochichi } = true', 'tointer': 'select the rows whose nation record fuzzily matches to kenya . select the row whose time record of these rows is 1st minimum . the athlete record of this row is isabella ochichi .'} | eq { hop { nth_argmin { filter_eq { all_rows ; nation ; kenya } ; time ; 1 } ; athlete } ; isabella ochichi } = true | select the rows whose nation record fuzzily matches to kenya . select the row whose time record of these rows is 1st minimum . the athlete record of this row is isabella ochichi . | 4 | 4 | {'str_eq_3': 3, 'result_4': 4, 'str_hop_2': 2, 'nth_argmin_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'nation_6': 6, 'kenya_7': 7, 'time_8': 8, '1_9': 9, 'athlete_10': 10, 'isabella ochichi_11': 11} | {'str_eq_3': 'str_eq', 'result_4': 'true', 'str_hop_2': 'str_hop', 'nth_argmin_1': 'nth_argmin', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'nation_6': 'nation', 'kenya_7': 'kenya', 'time_8': 'time', '1_9': '1', 'athlete_10': 'athlete', 'isabella ochichi_11': 'isabella ochichi'} | {'str_eq_3': [4], 'result_4': [], 'str_hop_2': [3], 'nth_argmin_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'nation_6': [0], 'kenya_7': [0], 'time_8': [1], '1_9': [1], 'athlete_10': [2], 'isabella ochichi_11': [3]} | ['rank', 'time', 'athlete', 'nation', 'date', 'race'] | [['1', '30:21', 'paula radcliffe', 'united kingdom', '23 february 2003', "world 's best 10k"], ['2', '30:27', 'isabella ochichi', 'kenya', '26 march 2005', 'crescent city classic'], ['3', '30:29', 'asmae leghzaoui', 'morocco', '8 june 2002', 'new york mini 10k'], ['4', '30:32', 'lornah kiplagat', 'kenya', '4 july 2002', 'peachtree road race'], ['5', '30:38', 'joyce chepkirui', 'kenya', '4 september 2011', 'tilburg 10k'], ['6', '30:39', 'liz mccolgan', 'united kingdom', '11 march 1989', 'red lobster classic'], ['7 =', '30:45', 'lineth chepkurui', 'kenya', '3 april 2010', 'crescent city classic'], ['7 =', '30:45 +', 'mary jepkosgei keitany', 'kenya', '18 february 2011', 'ras al khaimah half marathon'], ['9', '30:47', 'vivian jepkemoi cheruiyot', 'kenya', '26 february 2012', "world 's best 10k"], ['10', '30:48', 'linet chepkwemoi masai', 'kenya', '12 june 2010', 'new york mini 10k']] |
1971 green bay packers season | https://en.wikipedia.org/wiki/1971_Green_Bay_Packers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-14655917-1.html.csv | ordinal | the game on november 22nd had the 2nd highest attendance of all of the games . | {'row': '10', 'col': '7', 'order': '2', 'col_other': '2', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'attendance', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; attendance ; 2 }'}, 'date'], 'result': 'november 22', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; attendance ; 2 } ; date }'}, 'november 22'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; attendance ; 2 } ; date } ; november 22 } = true', 'tointer': 'select the row whose attendance record of all rows is 2nd maximum . the date record of this row is november 22 .'} | eq { hop { nth_argmax { all_rows ; attendance ; 2 } ; date } ; november 22 } = true | select the row whose attendance record of all rows is 2nd maximum . the date record of this row is november 22 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'attendance_5': 5, '2_6': 6, 'date_7': 7, 'november 22_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'attendance_5': 'attendance', '2_6': '2', 'date_7': 'date', 'november 22_8': 'november 22'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'attendance_5': [0], '2_6': [0], 'date_7': [1], 'november 22_8': [2]} | ['week', 'date', 'opponent', 'final score', 'team record', 'game site', 'attendance'] | [['1', 'september 19', 'new york giants', 'l 40 - 42', '0 - 1', 'lambeau field', '56263'], ['2', 'september 26', 'denver broncos', 'w 34 - 13', '1 - 1', 'milwaukee county stadium', '47957'], ['3', 'october 3', 'cincinnati bengals', 'w 20 - 17', '2 - 1', 'lambeau field', '56263'], ['4', 'october 10', 'detroit lions', 'l 28 - 31', '2 - 2', 'tiger stadium', '54418'], ['5', 'october 17', 'minnesota vikings', 'l 13 - 24', '2 - 3', 'lambeau field', '56263'], ['6', 'october 24', 'los angeles rams', 'l 13 - 30', '2 - 4', 'los angeles memorial coliseum', '75531'], ['7', 'november 1', 'detroit lions', 't 14 - 14', '2 - 4 - 1', 'milwaukee county stadium', '47961'], ['8', 'november 7', 'chicago bears', 'w 17 - 14', '3 - 4 - 1', 'soldier field', '55049'], ['9', 'november 14', 'minnesota vikings', 'l 0 - 3', '3 - 5 - 1', 'metropolitan stadium', '49784'], ['10', 'november 22', 'atlanta falcons', 'l 21 - 28', '3 - 6 - 1', 'atlanta stadium', '58850'], ['11', 'november 28', 'new orleans saints', 'l 21 - 29', '3 - 7 - 1', 'milwaukee county stadium', '48035'], ['12', 'december 5', 'st louis cardinals', 't 16 - 16', '3 - 7 - 2', 'busch stadium', '50443'], ['13', 'december 12', 'chicago bears', 'w 31 - 10', '4 - 7 - 2', 'lambeau field', '56263']] |
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/1-23308178-4.html.csv | count | in the first 12 games of the washington capitals 2009 – 2010 season there were 2 games that ended in a shootout . | {'scope': 'all', 'criterion': 'equal', 'value': 'so', 'result': '2', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'score', 'so'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose score record fuzzily matches to so .', 'tostr': 'filter_eq { all_rows ; score ; so }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; score ; so } }', 'tointer': 'select the rows whose score record fuzzily matches to so . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; score ; so } } ; 2 } = true', 'tointer': 'select the rows whose score record fuzzily matches to so . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; score ; so } } ; 2 } = true | select the rows whose score record fuzzily matches to so . the number of such rows is 2 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'score_5': 5, 'so_6': 6, '2_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'score_5': 'score', 'so_6': 'so', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'score_5': [0], 'so_6': [0], '2_7': [2]} | ['game', 'date', 'opponent', 'score', 'location', 'attendance', 'record', 'points'] | [['1', 'october 1', 'boston bruins', '4 - 1', 'td garden', '17565', '1 - 0 - 0', '2'], ['2', 'october 3', 'toronto maple leafs', '6 - 4', 'verizon center', '18277', '2 - 0 - 0', '4'], ['3', 'october 6', 'philadelphia flyers', '6 - 5 ot', 'wachovia center', '19567', '2 - 0 - 1', '5'], ['4', 'october 8', 'new york rangers', '4 - 3', 'verizon center', '18277', '2 - 1 - 1', '5'], ['5', 'october 10', 'detroit red wings', '3 - 2', 'joe louis arena', '19122', '2 - 2 - 1', '5'], ['6', 'october 12', 'new jersey devils', '3 - 2 so', 'verizon center', '18277', '2 - 2 - 2', '6'], ['7', 'october 15', 'san jose sharks', '4 - 1', 'verizon center', '18277', '3 - 2 - 2', '8'], ['8', 'october 17', 'nashville predators', '3 - 2 so', 'verizon center', '18277', '4 - 2 - 2', '10'], ['9', 'october 22', 'atlanta thrashers', '5 - 4', 'philips arena', '13192', '5 - 2 - 2', '12'], ['10', 'october 24', 'new york islanders', '3 - 2 ot', 'nassau veterans memorial coliseum', '11541', '6 - 2 - 2', '14'], ['11', 'october 27', 'philadelphia flyers', '4 - 2', 'verizon center', '18277', '7 - 2 - 2', '16'], ['12', 'october 29', 'atlanta thrashers', '4 - 3', 'philips arena', '12893', '8 - 2 - 2', '18']] |
sigurd rushfeldt | https://en.wikipedia.org/wiki/Sigurd_Rushfeldt | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1207980-1.html.csv | unique | the competition on 2003-02-04 is the only one of sigurd rushfeldt 's competitions that was a uefa euro 2004 qualifying competition . | {'scope': 'all', 'row': '3', 'col': '4', 'col_other': '1', 'criterion': 'equal', 'value': 'uefa euro 2004 qualifying', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'competition', 'uefa euro 2004 qualifying'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose competition record fuzzily matches to uefa euro 2004 qualifying .', 'tostr': 'filter_eq { all_rows ; competition ; uefa euro 2004 qualifying }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; competition ; uefa euro 2004 qualifying } }', 'tointer': 'select the rows whose competition record fuzzily matches to uefa euro 2004 qualifying . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'competition', 'uefa euro 2004 qualifying'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose competition record fuzzily matches to uefa euro 2004 qualifying .', 'tostr': 'filter_eq { all_rows ; competition ; uefa euro 2004 qualifying }'}, 'date'], 'result': '2003 - 02 - 04', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; competition ; uefa euro 2004 qualifying } ; date }'}, '2003 - 02 - 04'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; competition ; uefa euro 2004 qualifying } ; date } ; 2003 - 02 - 04 }', 'tointer': 'the date record of this unqiue row is 2003 - 02 - 04 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; competition ; uefa euro 2004 qualifying } } ; eq { hop { filter_eq { all_rows ; competition ; uefa euro 2004 qualifying } ; date } ; 2003 - 02 - 04 } } = true', 'tointer': 'select the rows whose competition record fuzzily matches to uefa euro 2004 qualifying . there is only one such row in the table . the date record of this unqiue row is 2003 - 02 - 04 .'} | and { only { filter_eq { all_rows ; competition ; uefa euro 2004 qualifying } } ; eq { hop { filter_eq { all_rows ; competition ; uefa euro 2004 qualifying } ; date } ; 2003 - 02 - 04 } } = true | select the rows whose competition record fuzzily matches to uefa euro 2004 qualifying . there is only one such row in the table . the date record of this unqiue row is 2003 - 02 - 04 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'competition_7': 7, 'uefa euro 2004 qualifying_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'date_9': 9, '2003 - 02 - 04_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'competition_7': 'competition', 'uefa euro 2004 qualifying_8': 'uefa euro 2004 qualifying', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'date_9': 'date', '2003 - 02 - 04_10': '2003 - 02 - 04'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'competition_7': [0], 'uefa euro 2004 qualifying_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'date_9': [2], '2003 - 02 - 04_10': [3]} | ['date', 'venue', 'result', 'competition', 'scored'] | [['2002 - 05 - 14', 'ullevaal stadion , oslo', '3 - 0', 'friendly match', '1'], ['2003 - 01 - 28', 'bausher , muscat', '2 - 0', 'friendly match', '1'], ['2003 - 02 - 04', 'stade josy barthel , luxembourg city', '2 - 0', 'uefa euro 2004 qualifying', '1'], ['2004 - 04 - 28', 'ullevaal stadion , oslo', '3 - 2', 'friendly match', '1'], ['2005 - 02 - 09', "ta ' qali stadium , attard", '3 - 0', 'friendly match', '2'], ['2005 - 10 - 08', 'ullevaal stadion , oslo', '1 - 0', '2006 fifa world cup qualification', '1']] |
last man standing ( uk tv series ) | https://en.wikipedia.org/wiki/Last_Man_Standing_%28UK_TV_series%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12538190-1.html.csv | superlative | corey rennell won the least amount of events in the uk series . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '2', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '1', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmin', 'args': ['all_rows', 'events won ( uk series )'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; events won ( uk series ) }'}, 'name'], 'result': 'corey rennell', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; events won ( uk series ) } ; name }'}, 'corey rennell'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmin { all_rows ; events won ( uk series ) } ; name } ; corey rennell } = true', 'tointer': 'select the row whose events won ( uk series ) record of all rows is minimum . the name record of this row is corey rennell .'} | eq { hop { argmin { all_rows ; events won ( uk series ) } ; name } ; corey rennell } = true | select the row whose events won ( uk series ) record of all rows is minimum . the name record of this row is corey rennell . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'events won (uk series)_5': 5, 'name_6': 6, 'corey rennell_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'events won (uk series)_5': 'events won ( uk series )', 'name_6': 'name', 'corey rennell_7': 'corey rennell'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'events won (uk series)_5': [0], 'name_6': [1], 'corey rennell_7': [2]} | ['name', 'from', 'discipline', 'events won ( uk series )', 'events won ( us series )'] | [['bradley johnson', 'united states oklahoma', 'strongman', '2', '3'], ['corey rennell', 'united states alaska', 'outdoorsman', '0', '0'], ['jason bennett', 'united states florida', 'bmx racer and tree surgeon', '2', '3'], ['mark boban', 'united kingdom birmingham', 'kickboxing and salsa dance', '1', '1'], ['rajko radovic', 'united kingdom middlesex', 'fitness guru', '2', '3'], ['richard massey', 'united kingdom oxford', 'cricket and rugby', '1', '2']] |
2007 games of the small states of europe | https://en.wikipedia.org/wiki/2007_Games_of_the_Small_States_of_Europe | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11415043-1.html.csv | count | in the 2007 games of the small states of europe , three of the teams that had at least 10 golds had at least 20 silvers . | {'scope': 'subset', 'criterion': 'greater_than_eq', 'value': '20', 'result': '3', 'col': '4', 'subset': {'col': '3', 'criterion': 'greater_than_eq', 'value': '10'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater_eq', 'args': [{'func': 'filter_greater_eq', 'args': ['all_rows', 'gold', '10'], 'result': None, 'ind': 0, 'tostr': 'filter_greater_eq { all_rows ; gold ; 10 }', 'tointer': 'select the rows whose gold record is greater than or equal to 10 .'}, 'silver', '20'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose gold record is greater than or equal to 10 . among these rows , select the rows whose silver record is greater than or equal to 20 .', 'tostr': 'filter_greater_eq { filter_greater_eq { all_rows ; gold ; 10 } ; silver ; 20 }'}], 'result': '3', 'ind': 2, 'tostr': 'count { filter_greater_eq { filter_greater_eq { all_rows ; gold ; 10 } ; silver ; 20 } }', 'tointer': 'select the rows whose gold record is greater than or equal to 10 . among these rows , select the rows whose silver record is greater than or equal to 20 . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_greater_eq { filter_greater_eq { all_rows ; gold ; 10 } ; silver ; 20 } } ; 3 } = true', 'tointer': 'select the rows whose gold record is greater than or equal to 10 . among these rows , select the rows whose silver record is greater than or equal to 20 . the number of such rows is 3 .'} | eq { count { filter_greater_eq { filter_greater_eq { all_rows ; gold ; 10 } ; silver ; 20 } } ; 3 } = true | select the rows whose gold record is greater than or equal to 10 . among these rows , select the rows whose silver record is greater than or equal to 20 . the number of such rows is 3 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_greater_eq_1': 1, 'filter_greater_eq_0': 0, 'all_rows_5': 5, 'gold_6': 6, '10_7': 7, 'silver_8': 8, '20_9': 9, '3_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_greater_eq_1': 'filter_greater_eq', 'filter_greater_eq_0': 'filter_greater_eq', 'all_rows_5': 'all_rows', 'gold_6': 'gold', '10_7': '10', 'silver_8': 'silver', '20_9': '20', '3_10': '3'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_greater_eq_1': [2], 'filter_greater_eq_0': [1], 'all_rows_5': [0], 'gold_6': [0], '10_7': [0], 'silver_8': [1], '20_9': [1], '3_10': [3]} | ['rank', 'nation', 'gold', 'silver', 'bronze', 'total'] | [['1', 'cyprus', '36', '33', '24', '93'], ['2', 'iceland', '31', '23', '24', '78'], ['3', 'luxembourg', '20', '25', '36', '81'], ['4', 'monaco', '19', '16', '17', '52'], ['5', 'malta', '4', '9', '17', '30'], ['6', 'andorra', '4', '6', '7', '17'], ['7', 'san marino', '4', '6', '6', '16'], ['8', 'liechtenstein', '3', '5', '5', '13']] |
missouri tigers men 's basketball | https://en.wikipedia.org/wiki/Missouri_Tigers_men%27s_basketball | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-16201038-4.html.csv | comparative | washington u of stl baskbetll team has a higher current streak by missouri than saint louis basketball team . | {'row_1': '9', 'row_2': '8', 'col': '8', 'col_other': '1', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'missouri vs', 'washington u of stl'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose missouri vs record fuzzily matches to washington u of stl .', 'tostr': 'filter_eq { all_rows ; missouri vs ; washington u of stl }'}, 'current streak'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; missouri vs ; washington u of stl } ; current streak }', 'tointer': 'select the rows whose missouri vs record fuzzily matches to washington u of stl . take the current streak record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'missouri vs', 'saint louis'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose missouri vs record fuzzily matches to saint louis .', 'tostr': 'filter_eq { all_rows ; missouri vs ; saint louis }'}, 'current streak'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; missouri vs ; saint louis } ; current streak }', 'tointer': 'select the rows whose missouri vs record fuzzily matches to saint louis . take the current streak record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; missouri vs ; washington u of stl } ; current streak } ; hop { filter_eq { all_rows ; missouri vs ; saint louis } ; current streak } } = true', 'tointer': 'select the rows whose missouri vs record fuzzily matches to washington u of stl . take the current streak record of this row . select the rows whose missouri vs record fuzzily matches to saint louis . take the current streak record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; missouri vs ; washington u of stl } ; current streak } ; hop { filter_eq { all_rows ; missouri vs ; saint louis } ; current streak } } = true | select the rows whose missouri vs record fuzzily matches to washington u of stl . take the current streak record of this row . select the rows whose missouri vs record fuzzily matches to saint louis . take the current streak 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, 'missouri vs_7': 7, 'washington u of stl_8': 8, 'current streak_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'missouri vs_11': 11, 'saint louis_12': 12, 'current streak_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', 'missouri vs_7': 'missouri vs', 'washington u of stl_8': 'washington u of stl', 'current streak_9': 'current streak', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'missouri vs_11': 'missouri vs', 'saint louis_12': 'saint louis', 'current streak_13': 'current streak'} | {'greater_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'missouri vs_7': [0], 'washington u of stl_8': [0], 'current streak_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'missouri vs_11': [1], 'saint louis_12': [1], 'current streak_13': [3]} | ['missouri vs', 'overall record', 'columbia', 'opponents venue', 'neutral site', 'last 5 meetings', 'last 10 meetings', 'current streak'] | [['colorado', 'mu , 99 - 53', 'mu , 57 - 11', 'cu , 34 - 30', 'mu , 12 - 8', 'mu , 4 - 1', 'mu , 9 - 1', 'w 1'], ['creighton', 'mu , 9 - 7', 'mu , 3 - 2', 'tied , 4 - 4', 'mu , 2 - 1', 'mu , 3 - 2', 'cu , 6 - 4', 'l 1'], ['drake', 'mu , 27 - 7', 'mu , 17 - 3', 'mu , 10 - 4', 'tied , 0 - 0', 'mu , 4 - 1', 'mu , 8 - 2', 'w 4'], ['illinois', 'ui , 27 - 16', 'ui , 3 - 2', 'ui , 4 - 1', 'ui , 20 - 13', 'mu , 4 - 1', 'ui , 6 - 4', 'w 4'], ['indiana', 'tied , 9 - 9', 'mu , 5 - 3', 'iu , 6 - 3', 'mu , 1 - 0', 'mu , 4 - 1', 'tied , 5 - 5', 'w 3'], ['iowa', 'ui , 10 - 7', 'mu , 4 - 2', 'ui , 7 - 2', 'tied , 1 - 1', 'mu , 3 - 2', 'tied , 5 - 5', 'w 2'], ['nebraska', 'mu , 126 - 93', 'mu , 70 - 25', 'nu , 56 - 42', 'mu , 14 - 12', 'mu , 3 - 2', 'tied , 5 - 5', 'l 1'], ['saint louis', 'mu , 21 - 19', 'slu , 12 - 10', 'mu , 11 - 7', 'tied , 0 - 0', 'mu , 3 - 2', 'tied , 5 - 5', 'w 2'], ['washington u of stl', 'mu , 71 - 29', 'mu , 42 - 8', 'mu , 29 - 21', 'tied , 0 - 0', 'mu , 5 - 0', 'mu , 8 - 2', 'w 7']] |
delhi daredevils | https://en.wikipedia.org/wiki/Delhi_Daredevils | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15840903-14.html.csv | comparative | the delhi daredevils won by more runs on october 11th than they did on october 19th . | {'row_1': '2', 'row_2': '4', 'col': '4', 'col_other': '1', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', '11 october'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose date record fuzzily matches to 11 october .', 'tostr': 'filter_eq { all_rows ; date ; 11 october }'}, 'result'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; date ; 11 october } ; result }', 'tointer': 'select the rows whose date record fuzzily matches to 11 october . take the result record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', '19 october'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose date record fuzzily matches to 19 october .', 'tostr': 'filter_eq { all_rows ; date ; 19 october }'}, 'result'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; date ; 19 october } ; result }', 'tointer': 'select the rows whose date record fuzzily matches to 19 october . take the result record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; date ; 11 october } ; result } ; hop { filter_eq { all_rows ; date ; 19 october } ; result } } = true', 'tointer': 'select the rows whose date record fuzzily matches to 11 october . take the result record of this row . select the rows whose date record fuzzily matches to 19 october . take the result record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; date ; 11 october } ; result } ; hop { filter_eq { all_rows ; date ; 19 october } ; result } } = true | select the rows whose date record fuzzily matches to 11 october . take the result record of this row . select the rows whose date record fuzzily matches to 19 october . take the result record of this row . the first record is greater than the second record . | 5 | 5 | {'greater_4': 4, 'result_5': 5, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'date_7': 7, '11 october_8': 8, 'result_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'date_11': 11, '19 october_12': 12, 'result_13': 13} | {'greater_4': 'greater', 'result_5': 'true', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'date_7': 'date', '11 october_8': '11 october', 'result_9': 'result', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'date_11': 'date', '19 october_12': '19 october', 'result_13': 'result'} | {'greater_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'date_7': [0], '11 october_8': [0], 'result_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'date_11': [1], '19 october_12': [1], 'result_13': [3]} | ['date', 'opponent', 'venue', 'result', 'scorecard link'] | [['9 october', 'victorian bushrangers', 'delhi', 'lost by 7 wickets', 'scorecard'], ['11 october', 'wayamba elevens', 'delhi', 'won by 50 runs , mom - virender sehwag 66 ( 42 )', 'scorecard'], ['17 october', 'royal challengers bangalore', 'bangalore', 'lost by 8 wickets', 'scorecard'], ['19 october', 'cape cobras', 'delhi', 'won by 30 runs , mom - owais shah 39 ( 38 )', 'scorecard'], ['overall record of 2 - 2 failed to make semi - finals', 'overall record of 2 - 2 failed to make semi - finals', 'overall record of 2 - 2 failed to make semi - finals', 'overall record of 2 - 2 failed to make semi - finals', 'overall record of 2 - 2 failed to make semi - finals']] |
primary schools in dacorum | https://en.wikipedia.org/wiki/Primary_schools_in_Dacorum | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15089329-4.html.csv | count | among primary schools of first type in dacorum , 4 of them have intake of 30 . | {'scope': 'subset', 'criterion': 'equal', 'value': '30', 'result': '4', 'col': '5', 'subset': {'col': '3', 'criterion': 'equal', 'value': 'first'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'type', 'first'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; type ; first }', 'tointer': 'select the rows whose type record fuzzily matches to first .'}, 'intake', '30'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose type record fuzzily matches to first . among these rows , select the rows whose intake record is equal to 30 .', 'tostr': 'filter_eq { filter_eq { all_rows ; type ; first } ; intake ; 30 }'}], 'result': '4', 'ind': 2, 'tostr': 'count { filter_eq { filter_eq { all_rows ; type ; first } ; intake ; 30 } }', 'tointer': 'select the rows whose type record fuzzily matches to first . among these rows , select the rows whose intake record is equal to 30 . the number of such rows is 4 .'}, '4'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_eq { filter_eq { all_rows ; type ; first } ; intake ; 30 } } ; 4 } = true', 'tointer': 'select the rows whose type record fuzzily matches to first . among these rows , select the rows whose intake record is equal to 30 . the number of such rows is 4 .'} | eq { count { filter_eq { filter_eq { all_rows ; type ; first } ; intake ; 30 } } ; 4 } = true | select the rows whose type record fuzzily matches to first . among these rows , select the rows whose intake record is equal to 30 . the number of such rows is 4 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_eq_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'type_6': 6, 'first_7': 7, 'intake_8': 8, '30_9': 9, '4_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', 'type_6': 'type', 'first_7': 'first', 'intake_8': 'intake', '30_9': '30', '4_10': '4'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_eq_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'type_6': [0], 'first_7': [0], 'intake_8': [1], '30_9': [1], '4_10': [3]} | ['name', 'faith', 'type', 'opened', 'intake', 'dcsf number', 'ofsted number'] | [['bridgewater', '-', 'middle', '1972', '95', '4144', '117541'], ['greenway', '-', 'first', '1966', '60', '2326', '117276'], ['potten end', 'ce', 'first', '1856', '30', '3042', '117414'], ["northchurch st mary 's", 'ce', 'first', '1864', '30', '3315', '117424'], ['st thomas more', 'rc', 'primary', '1966', '30', '3402', '117479'], ['swing gate', '-', 'first', '1968', '30', '2301', '117260'], ['thomas coram', 'ce', 'middle', '1970', '95', '4627', '117559'], ['victoria', 'ce', 'first', '1897', '42', '3314', '117423'], ['westfield', '-', 'first', '1962', '30', '2288', '117254']] |
list of highest - grossing bollywood films | https://en.wikipedia.org/wiki/List_of_highest-grossing_Bollywood_films | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11872185-8.html.csv | ordinal | the movie dabangg was the first movie to be produced in the list of bollywood movies with the highest net gross . | {'row': '8', 'col': '3', 'order': '1', 'col_other': '2', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'year', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; year ; 1 }'}, 'movie'], 'result': 'dabangg', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; year ; 1 } ; movie }'}, 'dabangg'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; year ; 1 } ; movie } ; dabangg } = true', 'tointer': 'select the row whose year record of all rows is 1st minimum . the movie record of this row is dabangg .'} | eq { hop { nth_argmin { all_rows ; year ; 1 } ; movie } ; dabangg } = true | select the row whose year record of all rows is 1st minimum . the movie record of this row is dabangg . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'year_5': 5, '1_6': 6, 'movie_7': 7, 'dabangg_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', '1_6': '1', 'movie_7': 'movie', 'dabangg_8': 'dabangg'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'year_5': [0], '1_6': [0], 'movie_7': [1], 'dabangg_8': [2]} | ['rank', 'movie', 'year', 'studio ( s )', 'opening week nett gross'] | [['1', 'chennai express', '2013', 'red chillies entertainment', '156 , 70 , 00000'], ['2', 'ek tha tiger', '2012', 'yash raj films', '133 , 22 , 00000'], ['3', 'yeh jawaani hai deewani', '2013', 'dharma productions', '106 , 00 , 00000'], ['4', 'bodyguard', '2011', 'reliance entertainment', '100 , 15 , 00000'], ['5', 'dabangg 2', '2012', 'arbaaz khan productions', '99 , 00 , 00000'], ['6', 'raone', '2011', 'red chillies entertainment', '91 , 27 , 00000'], ['7', 'agneepath', '2012', 'dharma productions', '81 , 77 , 00000'], ['8', 'dabangg', '2010', 'arbaaz khan productions', '80 , 87 , 00000'], ['9', 'jab tak hai jaan', '2012', 'yash raj films', '78 , 00 , 00000'], ['10', 'rowdy rathore', '2012', 'utv motion pictures', '77 , 00 , 00000']] |
1980 winter olympics | https://en.wikipedia.org/wiki/1980_Winter_Olympics | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-113360-1.html.csv | aggregation | at the 1980 winter olympics , the average number of gold medals won , was 3.7 . | {'scope': 'all', 'col': '3', 'type': 'average', 'result': '3.7', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'gold'], 'result': '3.7', 'ind': 0, 'tostr': 'avg { all_rows ; gold }'}, '3.7'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; gold } ; 3.7 } = true', 'tointer': 'the average of the gold record of all rows is 3.7 .'} | round_eq { avg { all_rows ; gold } ; 3.7 } = true | the average of the gold record of all rows is 3.7 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'gold_4': 4, '3.7_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'gold_4': 'gold', '3.7_5': '3.7'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'gold_4': [0], '3.7_5': [1]} | ['rank', 'nation', 'gold', 'silver', 'bronze', 'total'] | [['1', 'soviet union', '10', '6', '6', '22'], ['2', 'east germany ( gdr )', '9', '7', '7', '23'], ['3', 'united states', '6', '4', '2', '12'], ['4', 'austria', '3', '2', '2', '7'], ['5', 'sweden', '3', '0', '1', '4'], ['6', 'liechtenstein', '2', '2', '0', '4'], ['7', 'finland', '1', '5', '3', '9'], ['8', 'norway', '1', '3', '6', '10'], ['9', 'netherlands', '1', '2', '1', '4'], ['10', 'switzerland', '1', '1', '3', '5']] |
swimming at the 2000 summer olympics - men 's 200 metre individual medley | https://en.wikipedia.org/wiki/Swimming_at_the_2000_Summer_Olympics_%E2%80%93_Men%27s_200_metre_individual_medley | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12446479-5.html.csv | superlative | massimiliano rosolino had the fastest time of all the athletes . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '3', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmin', 'args': ['all_rows', 'time'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; time }'}, 'name'], 'result': 'massimiliano rosolino', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; time } ; name }'}, 'massimiliano rosolino'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmin { all_rows ; time } ; name } ; massimiliano rosolino } = true', 'tointer': 'select the row whose time record of all rows is minimum . the name record of this row is massimiliano rosolino .'} | eq { hop { argmin { all_rows ; time } ; name } ; massimiliano rosolino } = true | select the row whose time record of all rows is minimum . the name record of this row is massimiliano rosolino . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'time_5': 5, 'name_6': 6, 'massimiliano rosolino_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'time_5': 'time', 'name_6': 'name', 'massimiliano rosolino_7': 'massimiliano rosolino'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'time_5': [0], 'name_6': [1], 'massimiliano rosolino_7': [2]} | ['rank', 'lane', 'name', 'nationality', 'time'] | [['1', '4', 'massimiliano rosolino', 'italy', '2:01.14'], ['2', '5', 'marcel wouda', 'netherlands', '2:01.40'], ['3', '3', 'jani sievinen', 'finland', '2:01.46'], ['4', '6', 'tom wilkens', 'united states', '2:01.51'], ['5', '2', 'cezar bădiţă', 'romania', '2:02.02'], ['6', '1', 'jordi carrasco', 'spain', '2:02.90'], ['7', '7', 'robert van der zant', 'australia', '2:02.91'], ['8', '8', 'brian johns', 'canada', '2:02.92']] |
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