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list of cities , towns and villages in vojvodina | https://en.wikipedia.org/wiki/List_of_cities%2C_towns_and_villages_in_Vojvodina | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2562572-2.html.csv | aggregation | the average population in 2011 of urban settlements in vojvodina was 29547 . | {'scope': 'all', 'col': '7', 'type': 'average', 'result': '29547', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'population ( 2011 )'], 'result': '29547', 'ind': 0, 'tostr': 'avg { all_rows ; population ( 2011 ) }'}, '29547'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; population ( 2011 ) } ; 29547 } = true', 'tointer': 'the average of the population ( 2011 ) record of all rows is 29547 .'} | round_eq { avg { all_rows ; population ( 2011 ) } ; 29547 } = true | the average of the population ( 2011 ) record of all rows is 29547 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'population (2011)_4': 4, '29547_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'population (2011)_4': 'population ( 2011 )', '29547_5': '29547'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'population (2011)_4': [0], '29547_5': [1]} | ['urban settlement', 'cyrillic name', 'city / municipality', 'district', 'population ( 1991 )', 'population ( 2002 )', 'population ( 2011 )'] | [['bač', 'бач', 'bač', 'south bačka', '6046', '6087', '5399'], ['bačka palanka', 'бачка паланка', 'bačka palanka', 'south bačka', '26780', '29449', '28239'], ['bački jarak', 'бачки јарак', 'temerin', 'south bačka', '5426', '6049', '5687'], ['bački petrovac', 'бачки петровац', 'bački petrovac', 'south bačka', '7236', '6727', '6155'], ['bečej', 'бечеј', 'bečej', 'south bačka', '26634', '25774', '23895'], ['beočin', 'беочин', 'beočin', 'south bačka', '7873', '8058', '7839'], ['futog', 'футог', 'novi sad', 'south bačka', '16048', '18582', '18641'], ['novi sad', 'нови сад', 'novi sad', 'south bačka', '179626', '191405', '250439'], ['petrovaradin', 'петроварадин', 'petrovaradin , novi sad', 'south bačka', '11285', '13973', '14810'], ['srbobran', 'србобран', 'srbobran', 'south bačka', '12798', '13091', '12009'], ['sremska kamenica', 'сремска каменица', 'petrovaradin , novi sad', 'south bačka', '7955', '11205', '12273'], ['sremski karlovci', 'сремски карловци', 'sremski karlovci', 'south bačka', '7534', '8839', '8750'], ['temerin', 'темерин', 'temerin', 'south bačka', '16971', '19216', '19661'], ['titel', 'тител', 'titel', 'south bačka', '6007', '5894', '5294'], ['vrbas', 'врбас', 'vrbas', 'south bačka', '25858', '25907', '24112']] |
2008 - 09 fiba eurochallenge | https://en.wikipedia.org/wiki/2008%E2%80%9309_FIBA_EuroChallenge | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18842999-2.html.csv | comparative | energy invest rustavi scored more total points in the 2008 - 09 fiba eurochallenge than spartak pleven . | {'row_1': '7', 'row_2': '8', 'col': '2', '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', 'team 1', 'energy invest rustavi'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose team 1 record fuzzily matches to energy invest rustavi .', 'tostr': 'filter_eq { all_rows ; team 1 ; energy invest rustavi }'}, 'agg'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; team 1 ; energy invest rustavi } ; agg }', 'tointer': 'select the rows whose team 1 record fuzzily matches to energy invest rustavi . take the agg record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'team 1', 'spartak pleven'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose team 1 record fuzzily matches to spartak pleven .', 'tostr': 'filter_eq { all_rows ; team 1 ; spartak pleven }'}, 'agg'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; team 1 ; spartak pleven } ; agg }', 'tointer': 'select the rows whose team 1 record fuzzily matches to spartak pleven . take the agg record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; team 1 ; energy invest rustavi } ; agg } ; hop { filter_eq { all_rows ; team 1 ; spartak pleven } ; agg } } = true', 'tointer': 'select the rows whose team 1 record fuzzily matches to energy invest rustavi . take the agg record of this row . select the rows whose team 1 record fuzzily matches to spartak pleven . take the agg record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; team 1 ; energy invest rustavi } ; agg } ; hop { filter_eq { all_rows ; team 1 ; spartak pleven } ; agg } } = true | select the rows whose team 1 record fuzzily matches to energy invest rustavi . take the agg record of this row . select the rows whose team 1 record fuzzily matches to spartak pleven . take the agg record of this row . the first record is greater than the second record . | 5 | 5 | {'greater_4': 4, 'result_5': 5, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'team 1_7': 7, 'energy invest rustavi_8': 8, 'agg_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'team 1_11': 11, 'spartak pleven_12': 12, 'agg_13': 13} | {'greater_4': 'greater', 'result_5': 'true', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'team 1_7': 'team 1', 'energy invest rustavi_8': 'energy invest rustavi', 'agg_9': 'agg', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'team 1_11': 'team 1', 'spartak pleven_12': 'spartak pleven', 'agg_13': 'agg'} | {'greater_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'team 1_7': [0], 'energy invest rustavi_8': [0], 'agg_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'team 1_11': [1], 'spartak pleven_12': [1], 'agg_13': [3]} | ['team 1', 'agg', 'team 2', '1st leg', '2nd leg'] | [['bk prostějov', '134 - 148', 'kk zagreb', '61 - 69', '73 - 79'], ['kk amak', '148 - 145', 'zlatorog laško', '70 - 76', '78 - 69'], ['csu asesoft', '147 - 145', 'spartak', '79 - 76', '68 - 69'], ['u mobitelco cluj', '132 - 163', 'ewe baskets', '60 - 86', '72 - 77'], ['svendborg rabbits', '168 - 180', 'hkk široki', '92 - 100', '76 - 80'], ['mbc mykolaiv', '138 - 151', 'db skyliners', '68 - 75', '70 - 76'], ['energy invest rustavi', '160 - 200', 'sumykhimprom', '81 - 110', '79 - 90'], ['spartak pleven', '153 - 176', 'antalya bb bk', '83 - 87', '70 - 89'], ['apoel', '113 - 135', 'ja vichy', '52 - 66', '61 - 69'], ['csu sibiu', '144 - 186', 'banvit bandırma', '67 - 74', '77 - 112'], ['cedevita zagreb', '150 - 157', 'hyères - toulon', '92 - 82', '58 - 75'], ['körmend', '171 - 201', 'eiffeltowers den bosch', '71 - 88', '100 - 113'], ['bc donetsk', '120 - 134', 'ael', '65 - 65', '55 - 79'], ['bakken bears', '119 - 164', 'liege basket', '55 - 67', '64 - 97']] |
list of manchester city f.c. records and statistics | https://en.wikipedia.org/wiki/List_of_Manchester_City_F.C._records_and_statistics | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-14962287-1.html.csv | unique | in manchester city f.c. records and statistics , for players that started playing in the 1960s , the only one with a total over 600 is joe corrigan . | {'scope': 'subset', 'row': '2', 'col': '8', 'col_other': '1,2', 'criterion': 'greater_than', 'value': '600', 'subset': {'col': '2', 'criterion': 'fuzzily_match', 'value': '196'}} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_greater', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'years', '196'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; years ; 196 }', 'tointer': 'select the rows whose years record fuzzily matches to 196 .'}, 'total', '600'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose years record fuzzily matches to 196 . among these rows , select the rows whose total record is greater than 600 .', 'tostr': 'filter_greater { filter_eq { all_rows ; years ; 196 } ; total ; 600 }'}], 'result': True, 'ind': 2, 'tostr': 'only { filter_greater { filter_eq { all_rows ; years ; 196 } ; total ; 600 } }', 'tointer': 'select the rows whose years record fuzzily matches to 196 . among these rows , select the rows whose total record is greater than 600 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_greater', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'years', '196'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; years ; 196 }', 'tointer': 'select the rows whose years record fuzzily matches to 196 .'}, 'total', '600'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose years record fuzzily matches to 196 . among these rows , select the rows whose total record is greater than 600 .', 'tostr': 'filter_greater { filter_eq { all_rows ; years ; 196 } ; total ; 600 }'}, 'name'], 'result': 'joe corrigan', 'ind': 3, 'tostr': 'hop { filter_greater { filter_eq { all_rows ; years ; 196 } ; total ; 600 } ; name }'}, 'joe corrigan'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { filter_greater { filter_eq { all_rows ; years ; 196 } ; total ; 600 } ; name } ; joe corrigan }', 'tointer': 'the name record of this unqiue row is joe corrigan .'}], 'result': True, 'ind': 5, 'tostr': 'and { only { filter_greater { filter_eq { all_rows ; years ; 196 } ; total ; 600 } } ; eq { hop { filter_greater { filter_eq { all_rows ; years ; 196 } ; total ; 600 } ; name } ; joe corrigan } } = true', 'tointer': 'select the rows whose years record fuzzily matches to 196 . among these rows , select the rows whose total record is greater than 600 . there is only one such row in the table . the name record of this unqiue row is joe corrigan .'} | and { only { filter_greater { filter_eq { all_rows ; years ; 196 } ; total ; 600 } } ; eq { hop { filter_greater { filter_eq { all_rows ; years ; 196 } ; total ; 600 } ; name } ; joe corrigan } } = true | select the rows whose years record fuzzily matches to 196 . among these rows , select the rows whose total record is greater than 600 . there is only one such row in the table . the name record of this unqiue row is joe corrigan . | 8 | 6 | {'and_5': 5, 'result_6': 6, 'only_2': 2, 'filter_greater_1': 1, 'filter_str_eq_0': 0, 'all_rows_7': 7, 'years_8': 8, '196_9': 9, 'total_10': 10, '600_11': 11, 'str_eq_4': 4, 'str_hop_3': 3, 'name_12': 12, 'joe corrigan_13': 13} | {'and_5': 'and', 'result_6': 'true', 'only_2': 'only', 'filter_greater_1': 'filter_greater', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_7': 'all_rows', 'years_8': 'years', '196_9': '196', 'total_10': 'total', '600_11': '600', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'name_12': 'name', 'joe corrigan_13': 'joe corrigan'} | {'and_5': [6], 'result_6': [], 'only_2': [5], 'filter_greater_1': [2, 3], 'filter_str_eq_0': [1], 'all_rows_7': [0], 'years_8': [0], '196_9': [0], 'total_10': [1], '600_11': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'name_12': [3], 'joe corrigan_13': [4]} | ['name', 'years', 'league', 'fa cup', 'league cup', 'europe', 'other a', 'total'] | [['alan oakes', '1959 - 1976', '561 ( 3 )', '41 ( 0 )', '46 ( 1 )', '17 ( 0 )', '11 ( 0 )', '676 ( 4 )'], ['joe corrigan', '1967 - 1983', '476 ( 0 )', '37 ( 0 )', '52 ( 0 )', '27 ( 0 )', '12 ( 1 )', '604 ( 1 )'], ['mike doyle', '1967 - 1978', '441 ( 7 )', '44 ( 0 )', '23 ( 0 )', '20 ( 0 )', '37 ( 0 )', '565 ( 7 )'], ['bert trautmann', '1949 - 1964', '508 ( 0 )', '33 ( 0 )', '4 ( 0 )', '00 ( 0 )', '0 ( 0 )', '545 ( 0 )'], ['colin bell', '1966 - 1979', '393 ( 1 )', '33 ( 1 )', '40 ( 0 )', '23 ( 1 )', '9 ( 0 )', '498 ( 3 )'], ['eric brook', '1928 - 1939', '450 ( 0 )', '41 ( 0 )', '0 ( 0 )', '0 ( 0 )', '2 ( 0 )', '493 ( 0 ) b'], ['tommy booth', '1968 - 1981', '380 ( 2 )', '27 ( 0 )', '44 ( 2 )', '26 ( 0 )', '11 ( 0 )', '487 ( 4 )'], ['mike summerbee', '1965 - 1975', '355 ( 2 )', '34 ( 0 )', '36 ( 0 )', '16 ( 0 )', '8 ( 1 )', '449 ( 3 )'], ['paul power', '1975 - 1986', '358 ( 7 )', '28 ( 0 )', '37 ( 1 )', '7 ( 1 )', '7 ( 1 )', '437 ( 10 )']] |
women 's british open | https://en.wikipedia.org/wiki/Women%27s_British_Open | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1520559-2.html.csv | aggregation | the average margin of victory for the women 's british open was 4 strokes . | {'scope': 'all', 'col': '8', 'type': 'average', 'result': '4', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'margin of victory'], 'result': '4', 'ind': 0, 'tostr': 'avg { all_rows ; margin of victory }'}, '4'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; margin of victory } ; 4 } = true', 'tointer': 'the average of the margin of victory record of all rows is 4 .'} | round_eq { avg { all_rows ; margin of victory } ; 4 } = true | the average of the margin of victory record of all rows is 4 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'margin of victory_4': 4, '4_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'margin of victory_4': 'margin of victory', '4_5': '4'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'margin of victory_4': [0], '4_5': [1]} | ['year', 'date', 'venue', 'champion', 'country', 'score', 'to par', 'margin of victory', 'purse', "winner 's share"] | [['2000', 'aug 17 - 20', 'royal birkdale golf club', 'sophie gustafson', 'sweden', '282', '- 6', '2 strokes', '1250000', '178000'], ['1999', 'aug 12 - 15', 'woburn golf and country club', 'sherri steinhauer', 'united states', '283', '- 5', '1 stroke', '1000000', '160000'], ['1998', 'aug 13 - 16', 'royal lytham & st annes golf club', 'sherri steinhauer', 'united states', '292', '+ 4', '1 stroke', '1000000', '162000'], ['1997', 'aug 14 - 17', 'sunningdale golf club', 'karrie webb', 'australia', '269', '- 19', '8 strokes', '900000', '129938'], ['1996', 'aug 15 - 18', 'woburn golf and country club', 'emilee klein', 'united states', '277', '- 11', '7 strokes', '850000', '124000'], ['1995', 'aug 17 - 20', 'woburn golf and country club', 'karrie webb', 'australia', '278', '- 10', '6 strokes', '600000', '92400'], ['1994', 'aug 11 - 14', 'woburn golf and country club', 'liselotte neumann', 'sweden', '280', '- 8', '3 strokes', '500000', '80325']] |
1993 washington redskins season | https://en.wikipedia.org/wiki/1993_Washington_Redskins_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14610099-1.html.csv | majority | the majority of games in the 1993 washington redskins ended in losses for the redskins . | {'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 6 , 1993', 'dallas cowboys', 'w 35 - 16', '56345'], ['2', 'september 12 , 1993', 'phoenix cardinals', 'l 17 - 10', '53525'], ['3', 'september 19 , 1993', 'philadelphia eagles', 'l 34 - 31', '65435'], ['5', 'october 4 , 1993', 'miami dolphins', 'l 17 - 10', '68568'], ['6', 'october 10 , 1993', 'new york giants', 'l 41 - 7', '53715'], ['7', 'october 17 , 1993', 'phoenix cardinals', 'l 36 - 6', '48143'], ['9', 'november 1 , 1993', 'buffalo bills', 'l 24 - 10', '79106'], ['10', 'november 7 , 1993', 'indianapolis colts', 'w 30 - 24', '50523'], ['11', 'november 14 , 1993', 'new york giants', 'l 20 - 6', '76606'], ['12', 'november 21 , 1993', 'los angeles rams', 'l 10 - 6', '45546'], ['13', 'november 28 , 1993', 'philadelphia eagles', 'l 17 - 14', '46663'], ['14', 'december 5 , 1993', 'tampa bay buccaneers', 'w 23 - 17', '49035'], ['15', 'december 11 , 1993', 'new york jets', 'l 3 - 0', '47970'], ['16', 'december 19 , 1993', 'atlanta falcons', 'w 30 - 17', '50192'], ['17', 'december 26 , 1993', 'dallas cowboys', 'l 38 - 3', '64497'], ['18', 'december 31 , 1993', 'minnesota vikings', 'l 14 - 9', '42836']] |
within these walls | https://en.wikipedia.org/wiki/Within_These_Walls | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2582519-5.html.csv | superlative | silent night was the last of these episodes to air in 1976 . | {'scope': 'all', 'col_superlative': '6', 'row_superlative': '17', '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', 'original airdate'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; original airdate }'}, 'title'], 'result': 'silent night', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; original airdate } ; title }'}, 'silent night'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; original airdate } ; title } ; silent night } = true', 'tointer': 'select the row whose original airdate record of all rows is maximum . the title record of this row is silent night .'} | eq { hop { argmax { all_rows ; original airdate } ; title } ; silent night } = true | select the row whose original airdate record of all rows is maximum . the title record of this row is silent night . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'original airdate_5': 5, 'title_6': 6, 'silent night_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'original airdate_5': 'original airdate', 'title_6': 'title', 'silent night_7': 'silent night'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'original airdate_5': [0], 'title_6': [1], 'silent night_7': [2]} | ['total', 'series', 'title', 'director', 'writer ( s )', 'original airdate'] | [['43', '1', 'catalyst', 'christopher hodson', 'david butler', '4 september 1976'], ['44', '2', 'the man with the magic touch', 'christopher hodson', 'terence feely', '11 september 1976'], ['45', '3', 'the complaint', 'paul annett', 'tony hoare', '18 september 1976'], ['46', '4', 'the line of duty', 'paddy russell', 'david butler', '25 september 1976'], ['47', '5', 'k block', 'bryan izzard', 'david butler', '2 october 1976'], ['48', '6', 'a way of loving', 'john gorrie', 'john gorrie', '9 october 1976'], ['49', '7', 'love and the chaplain', 'paddy russell', 'kathleen j smith', '16 october 1976'], ['50', '8', 'the mystery', 'bryan izzard', 'tony hoare', '23 october 1976'], ['51', '9', 'a sentence of death', 'bryan izzard', 'peter wildeblood', '30 october 1976'], ['52', '10', 'vacuum', 'paul annett', 'pj hammond', '6 november 1976'], ['53', '11', 'on trial', 'marek kanievska', 'susan pleat', '13 november 1976'], ['54', '12', 'visitors', 'peter moffatt', 'terence feely', '20 november 1976'], ['55', '13', 'transfer', 'christopher hodson', 'tony parker', '27 november 1976'], ['56', '14', "someone 's got to do it", 'mike gibbon', 'mona bruce and robert james', '4 december 1976'], ['57', '15', 'islands in the heartline', 'marek kanievska', 'susan pleat', '11 december 1976'], ['58', '16', 'invasion of privacy', 'bill bain', 'david butler', '18 december 1976'], ['59', '17', 'silent night', 'phillip casson', 'david butler', '24 december 1976']] |
united states house of representatives elections , 1888 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1888 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1431459-6.html.csv | count | the year 1882 was the year that three of the incumbents in the 1888 united states house of representatives elections from the districts of south carolina were first seated . | {'scope': 'all', 'criterion': 'equal', 'value': '1882', 'result': '3', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'first elected', '1882'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose first elected record is equal to 1882 .', 'tostr': 'filter_eq { all_rows ; first elected ; 1882 }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; first elected ; 1882 } }', 'tointer': 'select the rows whose first elected record is equal to 1882 . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; first elected ; 1882 } } ; 3 } = true', 'tointer': 'select the rows whose first elected record is equal to 1882 . the number of such rows is 3 .'} | eq { count { filter_eq { all_rows ; first elected ; 1882 } } ; 3 } = true | select the rows whose first elected record is equal to 1882 . 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, 'first elected_5': 5, '1882_6': 6, '3_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'first elected_5': 'first elected', '1882_6': '1882', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'first elected_5': [0], '1882_6': [0], '3_7': [2]} | ['district', 'incumbent', 'party', 'first elected', 'result'] | [['south carolina 1', 'samuel dibble', 'democratic', '1882', 're - elected'], ['south carolina 2', 'george d tillman', 'democratic', '1878', 're - elected'], ['south carolina 3', 'james s cothran', 'democratic', '1886', 're - elected'], ['south carolina 4', 'william h perry', 'democratic', '1884', 're - elected'], ['south carolina 5', 'john j hemphill', 'democratic', '1882', 're - elected'], ['south carolina 6', 'george w dargan', 'democratic', '1882', 're - elected'], ['south carolina 7', 'william elliott', 'democratic', '1884', 're - elected']] |
chalid arrab | https://en.wikipedia.org/wiki/Chalid_Arrab | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10363239-3.html.csv | unique | the hero ’s 2005 event was the only one help in seoul korea . | {'scope': 'all', 'row': '1', 'col': '6', 'col_other': '5', 'criterion': 'equal', 'value': 'seoul , south korea', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location', 'seoul , south korea'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose location record fuzzily matches to seoul , south korea .', 'tostr': 'filter_eq { all_rows ; location ; seoul , south korea }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; location ; seoul , south korea } }', 'tointer': 'select the rows whose location record fuzzily matches to seoul , south korea . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location', 'seoul , south korea'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose location record fuzzily matches to seoul , south korea .', 'tostr': 'filter_eq { all_rows ; location ; seoul , south korea }'}, 'event'], 'result': "hero 's 2005 in seoul", 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; location ; seoul , south korea } ; event }'}, "hero 's 2005 in seoul"], 'result': True, 'ind': 3, 'tostr': "eq { hop { filter_eq { all_rows ; location ; seoul , south korea } ; event } ; hero 's 2005 in seoul }", 'tointer': "the event record of this unqiue row is hero 's 2005 in seoul ."}], 'result': True, 'ind': 4, 'tostr': "and { only { filter_eq { all_rows ; location ; seoul , south korea } } ; eq { hop { filter_eq { all_rows ; location ; seoul , south korea } ; event } ; hero 's 2005 in seoul } } = true", 'tointer': "select the rows whose location record fuzzily matches to seoul , south korea . there is only one such row in the table . the event record of this unqiue row is hero 's 2005 in seoul ."} | and { only { filter_eq { all_rows ; location ; seoul , south korea } } ; eq { hop { filter_eq { all_rows ; location ; seoul , south korea } ; event } ; hero 's 2005 in seoul } } = true | select the rows whose location record fuzzily matches to seoul , south korea . there is only one such row in the table . the event record of this unqiue row is hero 's 2005 in seoul . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'location_7': 7, 'seoul , south korea_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'event_9': 9, "hero 's 2005 in seoul_10": 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'location_7': 'location', 'seoul , south korea_8': 'seoul , south korea', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'event_9': 'event', "hero 's 2005 in seoul_10": "hero 's 2005 in seoul"} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'location_7': [0], 'seoul , south korea_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'event_9': [2], "hero 's 2005 in seoul_10": [3]} | ['res', 'record', 'opponent', 'method', 'event', 'location'] | [['win', '7 - 3', 'hiromitsu kanehara', 'decision ( majority )', "hero 's 2005 in seoul", 'seoul , south korea'], ['win', '6 - 3', 'yukiya naito', 'decision ( unanimous )', "hero 's 1", 'saitama , saitama , japan'], ['loss', '5 - 3', 'kazuhiro nakamura', 'submission ( armbar )', 'pride bushido 3', 'yokohama , japan'], ['win', '5 - 2', 'rodney glunder', 'decision ( unanimous )', 'pride bushido 1', 'saitama , saitama , japan'], ['loss', '4 - 2', 'jeremy horn', 'decision ( unanimous )', '2h2h 6 - simply the best 6', 'rotterdam , netherlands'], ['win', '4 - 1', 'stanislav nuschik', 'ko ( punches )', 'm - 1 mfc - european championship 2002', 'saint petersburg , russia'], ['win', '3 - 1', 'roman zentsov', 'ko', 'm - 1 mfc - russia vs the world 2', 'saint petersburg , russia'], ['win', '2 - 1', 'peter varga', 'submission ( arm lock )', 'millenniumsports - veni vidi vici', 'veenendaal , netherlands'], ['loss', '1 - 1', 'ramazan mezhidov', 'submission ( rear naked choke )', 'iafc - pankration world championship 2000', 'moscow , russia'], ['win', '1 - 0', 'spartak kochnev', 'tko ( strikes )', 'iafc - pankration world championship 2000', 'moscow , russia']] |
2010 tim hortons brier | https://en.wikipedia.org/wiki/2010_Tim_Hortons_Brier | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-25381437-2.html.csv | aggregation | the average number of blank ends for tim hortons brier in 2010 is 7.64 . | {'scope': 'all', 'col': '9', 'type': 'average', 'result': '7.64', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'blank ends'], 'result': '7.64', 'ind': 0, 'tostr': 'avg { all_rows ; blank ends }'}, '7.64'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; blank ends } ; 7.64 } = true', 'tointer': 'the average of the blank ends record of all rows is 7.64 .'} | round_eq { avg { all_rows ; blank ends } ; 7.64 } = true | the average of the blank ends record of all rows is 7.64 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'blank ends_4': 4, '7.64_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'blank ends_4': 'blank ends', '7.64_5': '7.64'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'blank ends_4': [0], '7.64_5': [1]} | ['locale', 'skip', 'w', 'l', 'pf', 'pa', 'ends won', 'ends lost', 'blank ends', 'stolen ends', 'shot pct'] | [['ontario', 'glenn howard', '11', '0', '90', '45', '50', '35', '8', '15', '88'], ['northern ontario', 'brad jacobs', '9', '2', '80', '54', '49', '39', '6', '17', '84'], ['alberta', 'kevin koe', '8', '3', '81', '62', '45', '42', '9', '11', '85'], ['newfoundland and labrador', 'brad gushue', '8', '3', '79', '53', '45', '35', '9', '11', '84'], ['manitoba', 'jeff stoughton', '7', '4', '71', '58', '45', '41', '9', '12', '83'], ['quebec', 'serge reid', '5', '6', '60', '71', '41', '42', '8', '9', '76'], ['saskatchewan', 'darrell mckee', '4', '7', '70', '79', '44', '44', '5', '7', '80'], ['british columbia', 'jeff richard', '4', '7', '68', '71', '43', '45', '9', '6', '79'], ['new brunswick', 'james grattan', '3', '8', '56', '71', '38', '47', '11', '6', '79'], ['nova scotia', 'ian fitzner - leblanc', '3', '8', '62', '90', '38', '54', '2', '5', '76'], ['prince edward island', 'rod macdonald', '3', '8', '64', '75', '44', '47', '8', '7', '80']] |
harlem rocker | https://en.wikipedia.org/wiki/Harlem_Rocker | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17644295-1.html.csv | majority | most of the surface on which harlem rocker performed its races was dirt . | {'scope': 'all', 'col': '6', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'dirt', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'surface', 'dirt'], 'result': True, 'ind': 0, 'tointer': 'for the surface records of all rows , most of them fuzzily match to dirt .', 'tostr': 'most_eq { all_rows ; surface ; dirt } = true'} | most_eq { all_rows ; surface ; dirt } = true | for the surface records of all rows , most of them fuzzily match to dirt . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'surface_3': 3, 'dirt_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'surface_3': 'surface', 'dirt_4': 'dirt'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'surface_3': [0], 'dirt_4': [0]} | ['date', 'race', 'track', 'location', 'distance', 'surface', 'purse', 'finish'] | [['february 14 , 2008', 'maiden special weight', 'gulfstream park', 'hallandale beach , florida', '7 fur', 'dirt', '40000', '1st'], ['march 30 , 2008', 'allowance', 'gulfstream park', 'hallandale beach , florida', '1 mi', 'dirt', '42500', '1st'], ['april 26 , 2008', 'withers stakes', 'aqueduct racetrack', 'new york city , new york', '1 mi', 'dirt', '142500', '1st'], ['june 1 , 2008', 'plate trial stakes', 'woodbine racetrack', 'toronto , ontario', '1 ⅛ mi', 'polytrack', '151781', '4th'], ['july 13 , 2008', 'prince of wales stakes', 'fort erie racetrack', 'fort erie , ontario', '1 1 / 16 mi', 'dirt', '495400', '1st'], ['august 23 , 2008', 'travers stakes', 'saratoga race course', 'saratoga springs , new york', '1 ¼ mi', 'dirt', '1000000', '4th'], ['october 5 , 2008', 'jerome handicap', 'belmont park', 'elmont , new york', '1 mi', 'dirt', '150000', '3rd'], ['november 29 , 2008', 'cigar mile handicap', 'aqueduct racetrack', 'new york city , new york', '1 mi', 'dirt', '300000', '2nd'], ['november 14 , 2009', 'allowance optional claiming', 'churchill downs', 'louisville , kentucky', '7 fur', 'dirt', '56000', '2nd'], ['january 3 , 2010', "hal 's hope handicap", 'gulfstream park', 'hallandale beach , florida', '1 mi', 'dirt', '100000', '4th']] |
elena reid | https://en.wikipedia.org/wiki/Elena_Reid | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1433370-2.html.csv | unique | tko ( liver punch ) is the only method used once by elena reid . | {'scope': 'all', 'row': '4', 'col': '4', 'col_other': 'n/a', 'criterion': 'equal', 'value': 'tko ( liver punch )', 'subset': None} | {'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'method', 'tko ( liver punch )'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose method record fuzzily matches to tko ( liver punch ) .', 'tostr': 'filter_eq { all_rows ; method ; tko ( liver punch ) }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; method ; tko ( liver punch ) } } = true', 'tointer': 'select the rows whose method record fuzzily matches to tko ( liver punch ) . there is only one such row in the table .'} | only { filter_eq { all_rows ; method ; tko ( liver punch ) } } = true | select the rows whose method record fuzzily matches to tko ( liver punch ) . 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, 'method_4': 4, 'tko (liver punch)_5': 5} | {'only_1': 'only', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'method_4': 'method', 'tko (liver punch)_5': 'tko ( liver punch )'} | {'only_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'method_4': [0], 'tko (liver punch)_5': [0]} | ['res', 'record', 'opponent', 'method', 'event', 'round', 'time', 'location'] | [['loss', '4 - 1', 'catia vitoria', 'tko ( punches )', 'playboy fight night 4', '3', '3:59', 'new town , north dakota , united states'], ['win', '4 - 0', 'masako yoshida', 'tko ( punches )', 'eb - beatdown at 4 bears 5', '3', '2:35', 'new town , north dakota , united states'], ['win', '3 - 0', 'michelle waterson', 'tko ( punches )', 'apache gold : extreme beatdown', '2', '1:50', 'phoenix , arizona , united states'], ['win', '2 - 0', 'stephanie palmer', 'tko ( liver punch )', 'superfights mma - night of combat 2', '1', '0:53', 'las vegas , nevada , united states'], ['win', '1 - 0', 'tammie schneider', 'tko ( punches )', 'ifo - fireworks in the cage iv', '2', '2:05', 'las vegas , nevada , united states']] |
primera división de fútbol profesional apertura 2008 | https://en.wikipedia.org/wiki/Primera_Divisi%C3%B3n_de_F%C3%BAtbol_Profesional_Apertura_2008 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18522916-5.html.csv | ordinal | carlos jurado was appointed the 4th soonest in the primera division de futbol . | {'row': '4', 'col': '6', 'order': '4', 'col_other': '5', '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 of appointment', '4'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; date of appointment ; 4 }'}, 'replaced by'], 'result': 'carlos jurado', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; date of appointment ; 4 } ; replaced by }'}, 'carlos jurado'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; date of appointment ; 4 } ; replaced by } ; carlos jurado } = true', 'tointer': 'select the row whose date of appointment record of all rows is 4th minimum . the replaced by record of this row is carlos jurado .'} | eq { hop { nth_argmin { all_rows ; date of appointment ; 4 } ; replaced by } ; carlos jurado } = true | select the row whose date of appointment record of all rows is 4th minimum . the replaced by record of this row is carlos jurado . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'date of appointment_5': 5, '4_6': 6, 'replaced by_7': 7, 'carlos jurado_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 of appointment_5': 'date of appointment', '4_6': '4', 'replaced by_7': 'replaced by', 'carlos jurado_8': 'carlos jurado'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'date of appointment_5': [0], '4_6': [0], 'replaced by_7': [1], 'carlos jurado_8': [2]} | ['team', 'outgoing manager', 'manner of departure', 'date of vacancy', 'replaced by', 'date of appointment', 'position in table'] | [['nejapa', 'mauricio cienfuegos', 'mutual consent', '14 august 2008', 'daniel uberti', '5 september 2008', '10th'], ['firpo', 'gerardo reinoso', 'sacked', '25 august 2008', 'oscar benitez', '2 september 2008', '7th'], ['balboa', 'gustavo de simone', 'sacked', '30 august 2008', 'roberto gamarra', '5 september 2008', '10th'], ['alianza', 'pablo centrone', 'sacked', '14 september 2008', 'carlos jurado', '16 september 2008', '5th'], ['firpo', 'oscar benítez', 'sacked', '9 december 2008', 'agustín castillo', '23 december 2008', 'post - season ( 6th )'], ['águila', 'agustín castillo', 'sacked', '15 december 2008', 'pablo centrone', '24 december 2008', 'post - season ( semifinals )'], ['fas', 'nelson ancheta', 'sacked', '27 december 2008', 'roberto gamarra', '1 january 2009', 'post - season ( semifinals )'], ['nejapa', 'daniel uberti', 'sacked', '29 december 2008', 'nelson ancheta', '29 december 2008', 'post - season ( 10th )'], ['balboa', 'roberto gamarra', 'mutual consent', '1 january 2009', 'carlos de toro', '16 january 2009', 'post - season ( 7th )'], ['independiente', 'jorge abrego', 'sacked', 'december 2008', 'ramón sánchez', 'december 2009', 'post - season ( 8th )']] |
2008 - 09 detroit red wings season | https://en.wikipedia.org/wiki/2008%E2%80%9309_Detroit_Red_Wings_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17371135-30.html.csv | superlative | in the 2008-09 detroit red wings season , the last overall pick for a player from the united states , was max nicastro . | {'scope': 'subset', 'col_superlative': '2', 'row_superlative': '2', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '3', 'subset': {'col': '5', 'criterion': 'equal', 'value': 'united states'}} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'nationality', 'united states'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; nationality ; united states }', 'tointer': 'select the rows whose nationality record fuzzily matches to united states .'}, 'overall pick'], 'result': None, 'ind': 1, 'tostr': 'argmax { filter_eq { all_rows ; nationality ; united states } ; overall pick }'}, 'player'], 'result': 'max nicastro', 'ind': 2, 'tostr': 'hop { argmax { filter_eq { all_rows ; nationality ; united states } ; overall pick } ; player }'}, 'max nicastro'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { argmax { filter_eq { all_rows ; nationality ; united states } ; overall pick } ; player } ; max nicastro } = true', 'tointer': 'select the rows whose nationality record fuzzily matches to united states . select the row whose overall pick record of these rows is maximum . the player record of this row is max nicastro .'} | eq { hop { argmax { filter_eq { all_rows ; nationality ; united states } ; overall pick } ; player } ; max nicastro } = true | select the rows whose nationality record fuzzily matches to united states . select the row whose overall pick record of these rows is maximum . the player record of this row is max nicastro . | 4 | 4 | {'str_eq_3': 3, 'result_4': 4, 'str_hop_2': 2, 'argmax_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'nationality_6': 6, 'united states_7': 7, 'overall pick_8': 8, 'player_9': 9, 'max nicastro_10': 10} | {'str_eq_3': 'str_eq', 'result_4': 'true', 'str_hop_2': 'str_hop', 'argmax_1': 'argmax', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'nationality_6': 'nationality', 'united states_7': 'united states', 'overall pick_8': 'overall pick', 'player_9': 'player', 'max nicastro_10': 'max nicastro'} | {'str_eq_3': [4], 'result_4': [], 'str_hop_2': [3], 'argmax_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'nationality_6': [0], 'united states_7': [0], 'overall pick_8': [1], 'player_9': [2], 'max nicastro_10': [3]} | ['round', 'overall pick', 'player', 'position', 'nationality', 'college / junior / club team ( league )'] | [['1', '30', 'thomas mccollum', 'goaltender', 'united states', 'guelph storm ( ohl )'], ['3', '91', 'max nicastro', 'defenseman', 'united states', 'chicago steel ( ushl )'], ['4', '121', 'gustav nyquist', 'center', 'sweden', 'malmö redhawks ( sweden jr )'], ['5', '151', 'julien cayer', 'center', 'canada', 'northwood school ( hs - new york )'], ['6', '181', 'stephen johnston', 'left wing', 'canada', 'belleville bulls ( ohl )'], ['7', '211', 'jesper samuelsson', 'center', 'sweden', 'hc vita hästen ( swe - 3 )']] |
jacksonville jaguars draft history | https://en.wikipedia.org/wiki/Jacksonville_Jaguars_draft_history | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15100419-11.html.csv | unique | alvin pearman is the only player in the running back position drafted by the jacksonville jaguars . | {'scope': 'all', 'row': '4', 'col': '5', 'col_other': '4', 'criterion': 'equal', 'value': 'running back', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'position', 'running back'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose position record fuzzily matches to running back .', 'tostr': 'filter_eq { all_rows ; position ; running back }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; position ; running back } }', 'tointer': 'select the rows whose position record fuzzily matches to running back . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'position', 'running back'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose position record fuzzily matches to running back .', 'tostr': 'filter_eq { all_rows ; position ; running back }'}, 'name'], 'result': 'alvin pearman', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; position ; running back } ; name }'}, 'alvin pearman'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; position ; running back } ; name } ; alvin pearman }', 'tointer': 'the name record of this unqiue row is alvin pearman .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; position ; running back } } ; eq { hop { filter_eq { all_rows ; position ; running back } ; name } ; alvin pearman } } = true', 'tointer': 'select the rows whose position record fuzzily matches to running back . there is only one such row in the table . the name record of this unqiue row is alvin pearman .'} | and { only { filter_eq { all_rows ; position ; running back } } ; eq { hop { filter_eq { all_rows ; position ; running back } ; name } ; alvin pearman } } = true | select the rows whose position record fuzzily matches to running back . there is only one such row in the table . the name record of this unqiue row is alvin pearman . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'position_7': 7, 'running back_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'name_9': 9, 'alvin pearman_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'position_7': 'position', 'running back_8': 'running back', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'name_9': 'name', 'alvin pearman_10': 'alvin pearman'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'position_7': [0], 'running back_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'name_9': [2], 'alvin pearman_10': [3]} | ['round', 'pick', 'overall', 'name', 'position', 'college'] | [['1', '21', '21', 'matt jones', 'wide receiver', 'arkansas'], ['2', '20', '52', 'khalif barnes', 'offensive tackle', 'washington'], ['3', '23', '87', 'scott starks', 'cornerback', 'wisconsin'], ['4', '26', '127', 'alvin pearman', 'running back', 'virginia'], ['5', '21', '157', 'gerald sensabaugh', 'safety', 'north carolina'], ['6', '11', '185', 'chad owens', 'wide receiver', 'hawaii'], ['6', '20', '194', 'pat thomas', 'linebacker', 'north carolina state'], ['7', '23', '237', 'chris roberson', 'cornerback', 'eastern michigan']] |
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 | ordinal | the fourth game of the detroit lions 2007 season was against the chicago bears . | {'row': '4', 'col': '1', 'order': '4', 'col_other': '3', 'max_or_min': 'min_to_max', 'value_mentioned': 'yes', 'scope': 'all', 'subset': None} | {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'nth_min', 'args': ['all_rows', 'week', '4'], 'result': '4', 'ind': 0, 'tostr': 'nth_min { all_rows ; week ; 4 }', 'tointer': 'the 4th minimum week record of all rows is 4 .'}, '4'], 'result': True, 'ind': 1, 'tostr': 'eq { nth_min { all_rows ; week ; 4 } ; 4 }', 'tointer': 'the 4th minimum week record of all rows is 4 .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'week', '4'], 'result': None, 'ind': 2, 'tostr': 'nth_argmin { all_rows ; week ; 4 }'}, 'opponent'], 'result': 'chicago bears', 'ind': 3, 'tostr': 'hop { nth_argmin { all_rows ; week ; 4 } ; opponent }'}, 'chicago bears'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { nth_argmin { all_rows ; week ; 4 } ; opponent } ; chicago bears }', 'tointer': 'the opponent record of the row with 4th minimum week record is chicago bears .'}], 'result': True, 'ind': 5, 'tostr': 'and { eq { nth_min { all_rows ; week ; 4 } ; 4 } ; eq { hop { nth_argmin { all_rows ; week ; 4 } ; opponent } ; chicago bears } } = true', 'tointer': 'the 4th minimum week record of all rows is 4 . the opponent record of the row with 4th minimum week record is chicago bears .'} | and { eq { nth_min { all_rows ; week ; 4 } ; 4 } ; eq { hop { nth_argmin { all_rows ; week ; 4 } ; opponent } ; chicago bears } } = true | the 4th minimum week record of all rows is 4 . the opponent record of the row with 4th minimum week record is chicago bears . | 6 | 6 | {'and_5': 5, 'result_6': 6, 'eq_1': 1, 'nth_min_0': 0, 'all_rows_7': 7, 'week_8': 8, '4_9': 9, '4_10': 10, 'str_eq_4': 4, 'str_hop_3': 3, 'nth_argmin_2': 2, 'all_rows_11': 11, 'week_12': 12, '4_13': 13, 'opponent_14': 14, 'chicago bears_15': 15} | {'and_5': 'and', 'result_6': 'true', 'eq_1': 'eq', 'nth_min_0': 'nth_min', 'all_rows_7': 'all_rows', 'week_8': 'week', '4_9': '4', '4_10': '4', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'nth_argmin_2': 'nth_argmin', 'all_rows_11': 'all_rows', 'week_12': 'week', '4_13': '4', 'opponent_14': 'opponent', 'chicago bears_15': 'chicago bears'} | {'and_5': [6], 'result_6': [], 'eq_1': [5], 'nth_min_0': [1], 'all_rows_7': [0], 'week_8': [0], '4_9': [0], '4_10': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'nth_argmin_2': [3], 'all_rows_11': [2], 'week_12': [2], '4_13': [2], 'opponent_14': [3], 'chicago bears_15': [4]} | ['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']] |
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 | count | there are 11 institutions which participated in the kentucky intercollegiate athletic conference . | {'scope': 'all', 'criterion': 'all', 'value': 'n/a', 'result': '11', 'col': '1', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_all', 'args': ['all_rows', 'institution'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose institution record is arbitrary .', 'tostr': 'filter_all { all_rows ; institution }'}], 'result': '11', 'ind': 1, 'tostr': 'count { filter_all { all_rows ; institution } }', 'tointer': 'select the rows whose institution record is arbitrary . the number of such rows is 11 .'}, '11'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_all { all_rows ; institution } } ; 11 } = true', 'tointer': 'select the rows whose institution record is arbitrary . the number of such rows is 11 .'} | eq { count { filter_all { all_rows ; institution } } ; 11 } = true | select the rows whose institution record is arbitrary . the number of such rows is 11 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_all_0': 0, 'all_rows_4': 4, 'institution_5': 5, '11_6': 6} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_all_0': 'filter_all', 'all_rows_4': 'all_rows', 'institution_5': 'institution', '11_6': '11'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_all_0': [1], 'all_rows_4': [0], 'institution_5': [0], '11_6': [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']] |
urea cycle disorder | https://en.wikipedia.org/wiki/Urea_cycle_disorder | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1089254-1.html.csv | unique | arginase deficiency or argininemia is the only urea cycle disorder that is measured with arginine . | {'scope': 'all', 'row': '6', 'col': '5', 'col_other': '4', 'criterion': 'equal', 'value': 'arginine', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'measurements', 'arginine'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose measurements record fuzzily matches to arginine .', 'tostr': 'filter_eq { all_rows ; measurements ; arginine }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; measurements ; arginine } }', 'tointer': 'select the rows whose measurements record fuzzily matches to arginine . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'measurements', 'arginine'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose measurements record fuzzily matches to arginine .', 'tostr': 'filter_eq { all_rows ; measurements ; arginine }'}, 'disorder'], 'result': 'arginase deficiency or argininemia', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; measurements ; arginine } ; disorder }'}, 'arginase deficiency or argininemia'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; measurements ; arginine } ; disorder } ; arginase deficiency or argininemia }', 'tointer': 'the disorder record of this unqiue row is arginase deficiency or argininemia .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; measurements ; arginine } } ; eq { hop { filter_eq { all_rows ; measurements ; arginine } ; disorder } ; arginase deficiency or argininemia } } = true', 'tointer': 'select the rows whose measurements record fuzzily matches to arginine . there is only one such row in the table . the disorder record of this unqiue row is arginase deficiency or argininemia .'} | and { only { filter_eq { all_rows ; measurements ; arginine } } ; eq { hop { filter_eq { all_rows ; measurements ; arginine } ; disorder } ; arginase deficiency or argininemia } } = true | select the rows whose measurements record fuzzily matches to arginine . there is only one such row in the table . the disorder record of this unqiue row is arginase deficiency or argininemia . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'measurements_7': 7, 'arginine_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'disorder_9': 9, 'arginase deficiency or argininemia_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'measurements_7': 'measurements', 'arginine_8': 'arginine', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'disorder_9': 'disorder', 'arginase deficiency or argininemia_10': 'arginase deficiency or argininemia'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'measurements_7': [0], 'arginine_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'disorder_9': [2], 'arginase deficiency or argininemia_10': [3]} | ['location', 'abb', 'enzyme', 'disorder', 'measurements'] | [['mitochondria', 'nags', 'n - acetylglutamate synthetase', 'n - acetylglutamate synthase deficiency', '+ ammonia'], ['mitochondria', 'cps1', 'carbamoyl phosphate synthetase i', 'carbamoyl phosphate synthetase i deficiency', '+ ammonia'], ['mitochondria', 'otc', 'ornithine transcarbamylase', 'ornithine transcarbamylase deficiency', '+ ornithine , + uracil , + orotic acid'], ['cytosol', 'ass', 'argininosuccinic acid synthetase', 'as deficiency or citrullinemia', '+ citrulline'], ['cytosol', 'asl', 'argininosuccinase acid lyase', 'al deficiency or argininosuccinic aciduria ( asa )', '+ citrulline , + argininosuccinic acid'], ['cytosol', 'arg', 'arginase', 'arginase deficiency or argininemia', '+ arginine']] |
1965 wyoming cowboys football team | https://en.wikipedia.org/wiki/1965_Wyoming_Cowboys_football_team | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-22801331-1.html.csv | aggregation | in their 1965 season , wyoming cowboys scored a total of 154 points between the games they won . | {'scope': 'subset', 'col': '5', 'type': 'sum', 'result': '154', 'subset': {'col': '4', 'criterion': 'equal', 'value': 'win'}} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'result', 'win'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; result ; win }', 'tointer': 'select the rows whose result record fuzzily matches to win .'}, 'cowboys points'], 'result': '154', 'ind': 1, 'tostr': 'sum { filter_eq { all_rows ; result ; win } ; cowboys points }'}, '154'], 'result': True, 'ind': 2, 'tostr': 'round_eq { sum { filter_eq { all_rows ; result ; win } ; cowboys points } ; 154 } = true', 'tointer': 'select the rows whose result record fuzzily matches to win . the sum of the cowboys points record of these rows is 154 .'} | round_eq { sum { filter_eq { all_rows ; result ; win } ; cowboys points } ; 154 } = true | select the rows whose result record fuzzily matches to win . the sum of the cowboys points record of these rows is 154 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'sum_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'result_5': 5, 'win_6': 6, 'cowboys points_7': 7, '154_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'sum_1': 'sum', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'result_5': 'result', 'win_6': 'win', 'cowboys points_7': 'cowboys points', '154_8': '154'} | {'eq_2': [3], 'result_3': [], 'sum_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'result_5': [0], 'win_6': [0], 'cowboys points_7': [1], '154_8': [2]} | ['game', 'date', 'opponent', 'result', 'cowboys points', 'opponents', 'record'] | [['1', 'sept 18', 'air force', 'win', '13', '0', '1 - 0'], ['2', 'sept 25', 'colorado state', 'win', '23', '6', '2 - 0'], ['3', 'oct 2', 'arizona', 'win', '36', '6', '3 - 0'], ['4', 'oct 9', 'utah', 'loss', '3', '42', '3 - 1'], ['5', 'oct 16', 'texas el - paso', 'win', '37', '7', '4 - 1'], ['6', 'oct 23', 'brigham young', 'win', '35', '10', '5 - 1'], ['7', 'nov 6', 'new mexico', 'win', '10', '12', '6 - 1'], ['8', 'nov 13', 'army', 'loss', '0', '13', '6 - 2'], ['9', 'nov 20', 'arizona state', 'loss', '31', '7', '6 - 3']] |
inbee park | https://en.wikipedia.org/wiki/Inbee_Park | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18198579-2.html.csv | aggregation | inbee park won an average amount of 363889 in winnings per tournament . | {'scope': 'all', 'col': '7', 'type': 'average', 'result': '363889', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', "winner 's share"], 'result': '363889', 'ind': 0, 'tostr': "avg { all_rows ; winner 's share }"}, '363889'], 'result': True, 'ind': 1, 'tostr': "round_eq { avg { all_rows ; winner 's share } ; 363889 } = true", 'tointer': "the average of the winner 's share record of all rows is 363889 ."} | round_eq { avg { all_rows ; winner 's share } ; 363889 } = true | the average of the winner 's share record of all rows is 363889 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, "winner 's share_4": 4, '363889_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', "winner 's share_4": "winner 's share", '363889_5': '363889'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], "winner 's share_4": [0], '363889_5': [1]} | ['date', 'tournament', 'winning score', 'to par', 'margin of victory', 'runner ( s ) - up', "winner 's share"] | [['29 jun 2008', "us women 's open", '72 + 69 + 71 + 71 = 283', '- 9', '4 strokes', 'helen alfredsson', '560000'], ['29 jul 2012', 'evian masters', '71 + 64 + 70 + 66 = 271', '- 17', '2 strokes', 'karrie webb stacy lewis', '487500'], ['14 oct 2012', 'sime darby lpga malaysia', '69 + 68 + 65 + 67 = 269', '- 15', '2 strokes', 'choi na - yeon', '285000'], ['24 feb 2013', 'honda lpga thailand', '67 + 71 + 71 + 67 = 276', '- 12', '1 stroke', 'ariya jutanugarn', '225000'], ['7 apr 2013', 'kraft nabisco championship', '70 + 67 + 67 + 69 = 273', '- 15', '4 strokes', 'ryu so - yeon', '300000'], ['28 apr 2013', 'north texas lpga shootout', '67 + 70 + 67 + 67 = 271', '- 13', '1 stroke', 'carlota ciganda', '195000'], ['9 jun 2013', 'lpga championship', '72 + 68 + 68 + 75 = 283', '- 5', 'playoff', 'catriona matthew', '337500'], ['23 jun 2013', 'walmart nw arkansas championship', '69 + 65 + 67 = 201', '- 12', 'playoff', 'ryu so - yeon', '300000'], ['30 jun 2013', "us women 's open", '67 + 68 + 71 + 74 = 280', '- 8', '4 strokes', 'in - kyung kim', '585000']] |
united states house of representatives elections , 1956 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1956 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1341973-3.html.csv | count | six of the incumbent representatives in the 1956 election are from the democratic party . | {'scope': 'all', 'criterion': 'all', 'value': 'n/a', 'result': '6', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_all', 'args': ['all_rows', 'party'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose party record is arbitrary .', 'tostr': 'filter_all { all_rows ; party }'}], 'result': '6', 'ind': 1, 'tostr': 'count { filter_all { all_rows ; party } }', 'tointer': 'select the rows whose party record is arbitrary . the number of such rows is 6 .'}, '6'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_all { all_rows ; party } } ; 6 } = true', 'tointer': 'select the rows whose party record is arbitrary . the number of such rows is 6 .'} | eq { count { filter_all { all_rows ; party } } ; 6 } = true | select the rows whose party record is arbitrary . the number of such rows is 6 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_all_0': 0, 'all_rows_4': 4, 'party_5': 5, '6_6': 6} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_all_0': 'filter_all', 'all_rows_4': 'all_rows', 'party_5': 'party', '6_6': '6'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_all_0': [1], 'all_rows_4': [0], 'party_5': [0], '6_6': [2]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['alabama 1', 'frank w boykin', 'democratic', '1935', 're - elected', 'frank w boykin ( d ) unopposed'], ['alabama 2', 'george m grant', 'democratic', '1938', 're - elected', 'george m grant ( d ) unopposed'], ['alabama 3', 'george w andrews', 'democratic', '1944', 're - elected', 'george w andrews ( d ) unopposed'], ['alabama 4', 'kenneth a roberts', 'democratic', '1950', 're - elected', 'kenneth a roberts ( d ) 73.4 % roy banks ( r ) 26.6 %'], ['alabama 5', 'albert rains', 'democratic', '1944', 're - elected', 'albert rains ( d ) unopposed'], ['alabama 6', 'armistead i selden , jr', 'democratic', '1952', 're - elected', 'armistead i selden , jr ( d ) unopposed']] |
rural community | https://en.wikipedia.org/wiki/Rural_community | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-26321719-1.html.csv | superlative | of the rural communities located in new brunswick , beaubassin east has the highest population in 2011 . | {'scope': 'all', 'col_superlative': '2', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'population ( 2011 )'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; population ( 2011 ) }'}, 'name'], 'result': 'beaubassin east', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; population ( 2011 ) } ; name }'}, 'beaubassin east'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; population ( 2011 ) } ; name } ; beaubassin east } = true', 'tointer': 'select the row whose population ( 2011 ) record of all rows is maximum . the name record of this row is beaubassin east .'} | eq { hop { argmax { all_rows ; population ( 2011 ) } ; name } ; beaubassin east } = true | select the row whose population ( 2011 ) record of all rows is maximum . the name record of this row is beaubassin east . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'population (2011)_5': 5, 'name_6': 6, 'beaubassin east_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'population (2011)_5': 'population ( 2011 )', 'name_6': 'name', 'beaubassin east_7': 'beaubassin east'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'population (2011)_5': [0], 'name_6': [1], 'beaubassin east_7': [2]} | ['name', 'population ( 2011 )', 'population ( 2006 )', 'change ( % )', 'area ( km square )', 'population density'] | [['beaubassin east', '6200', '6429', '- 3.6', '291.12', '21.3'], ['campobello island', '925', '1056', '- 12.4', '39.67', '23.3'], ['kedgwick', '993', '1146', '- 13.4', '4.28', '232.2'], ['saint - andré', '819', '868', '- 5.6', '8.12', '100.8'], ['upper miramichi', '2373', '2414', '- 1.7', '1835.01', '1.3']] |
6th united states congress | https://en.wikipedia.org/wiki/6th_United_States_Congress | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-224840-4.html.csv | unique | jonathan havens was the only 6th us congress vacator from a new york district . | {'scope': 'all', 'row': '1', 'col': '1', 'col_other': '2', 'criterion': 'equal', 'value': 'new york', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'district', 'new york'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose district record fuzzily matches to new york .', 'tostr': 'filter_eq { all_rows ; district ; new york }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; district ; new york } }', 'tointer': 'select the rows whose district record fuzzily matches to new york . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'district', 'new york'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose district record fuzzily matches to new york .', 'tostr': 'filter_eq { all_rows ; district ; new york }'}, 'vacator'], 'result': 'jonathan havens ( dr )', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; district ; new york } ; vacator }'}, 'jonathan havens ( dr )'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; district ; new york } ; vacator } ; jonathan havens ( dr ) }', 'tointer': 'the vacator record of this unqiue row is jonathan havens ( dr ) .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; district ; new york } } ; eq { hop { filter_eq { all_rows ; district ; new york } ; vacator } ; jonathan havens ( dr ) } } = true', 'tointer': 'select the rows whose district record fuzzily matches to new york . there is only one such row in the table . the vacator record of this unqiue row is jonathan havens ( dr ) .'} | and { only { filter_eq { all_rows ; district ; new york } } ; eq { hop { filter_eq { all_rows ; district ; new york } ; vacator } ; jonathan havens ( dr ) } } = true | select the rows whose district record fuzzily matches to new york . there is only one such row in the table . the vacator record of this unqiue row is jonathan havens ( dr ) . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'district_7': 7, 'new york_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'vacator_9': 9, 'jonathan havens (dr)_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'district_7': 'district', 'new york_8': 'new york', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'vacator_9': 'vacator', 'jonathan havens (dr)_10': 'jonathan havens ( dr )'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'district_7': [0], 'new york_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'vacator_9': [2], 'jonathan havens (dr)_10': [3]} | ['district', 'vacator', 'reason for change', 'successor', 'date successor seated'] | [['new york 1st', 'jonathan havens ( dr )', 'died october 25 , 1799', 'john smith ( dr )', 'february 27 , 1800'], ['connecticut at - large', 'jonathan brace ( f )', 'resigned sometime in 1800', 'john cotton smith ( f )', 'november 17 , 1800'], ['virginia 13th', 'john marshall ( f )', 'resigned june 7 , 1800 to become secretary of state', 'littleton w tazewell ( dr )', 'november 26 , 1800'], ['massachusetts 3rd', 'samuel lyman ( f )', 'resigned november 6 , 1800', 'ebenezer mattoon ( f )', 'february 2 , 1801'], ['pennsylvania 8th', 'thomas hartley ( f )', 'died december 21 , 1800', 'john stewart ( dr )', 'february 3 , 1801']] |
1965 buffalo bills season | https://en.wikipedia.org/wiki/1965_Buffalo_Bills_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16008156-2.html.csv | aggregation | the average crowd attendance for games in the 1965 buffalo bills season was 36859 . | {'scope': 'all', 'col': '5', 'type': 'average', 'result': '36859', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'attendance'], 'result': '36859', 'ind': 0, 'tostr': 'avg { all_rows ; attendance }'}, '36859'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; attendance } ; 36859 } = true', 'tointer': 'the average of the attendance record of all rows is 36859 .'} | round_eq { avg { all_rows ; attendance } ; 36859 } = true | the average of the attendance record of all rows is 36859 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'attendance_4': 4, '36859_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'attendance_4': 'attendance', '36859_5': '36859'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'attendance_4': [0], '36859_5': [1]} | ['week', 'date', 'opponent', 'result', 'attendance'] | [['1', 'september 11 , 1965', 'boston patriots', 'w 24 - 7', '45502'], ['2', 'september 19 , 1965', 'denver broncos', 'w 30 - 15', '30682'], ['3', 'september 26 , 1965', 'new york jets', 'w 33 - 21', '45056'], ['4', 'october 3 , 1965', 'oakland raiders', 'w 17 - 12', '41256'], ['5', 'october 10 , 1965', 'san diego chargers', 'l 34 - 3', '45260'], ['6', 'october 17 , 1965', 'kansas city chiefs', 'w 23 - 7', '26941'], ['7', 'october 24 , 1965', 'denver broncos', 'w 31 - 13', '45046'], ['8', 'october 31 , 1965', 'houston oilers', 'l 19 - 17', '44267'], ['9', 'november 7 , 1965', 'boston patriots', 'w 23 - 7', '24415'], ['10', 'november 14 , 1965', 'oakland raiders', 'w 17 - 14', '19352'], ['12', 'november 25 , 1965', 'san diego chargers', 't 20 - 20', '27473'], ['13', 'december 5 , 1965', 'houston oilers', 'w 29 - 18', '23087'], ['14', 'december 12 , 1965', 'kansas city chiefs', 'w 34 - 25', '40298'], ['15', 'december 19 , 1965', 'new york jets', 'l 14 - 12', '57396']] |
cyrille diabaté | https://en.wikipedia.org/wiki/Cyrille_Diabat%C3%A9 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18722380-1.html.csv | comparative | cyrille diabaté 's fight against alexey ignashov went more rounds than his fight against lee hasdell . | {'row_1': '3', 'row_2': '6', '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', 'opponent', 'alexey ignashov'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose opponent record fuzzily matches to alexey ignashov .', 'tostr': 'filter_eq { all_rows ; opponent ; alexey ignashov }'}, 'round'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; opponent ; alexey ignashov } ; round }', 'tointer': 'select the rows whose opponent record fuzzily matches to alexey ignashov . take the round record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', 'lee hasdell'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose opponent record fuzzily matches to lee hasdell .', 'tostr': 'filter_eq { all_rows ; opponent ; lee hasdell }'}, 'round'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; opponent ; lee hasdell } ; round }', 'tointer': 'select the rows whose opponent record fuzzily matches to lee hasdell . take the round record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; opponent ; alexey ignashov } ; round } ; hop { filter_eq { all_rows ; opponent ; lee hasdell } ; round } } = true', 'tointer': 'select the rows whose opponent record fuzzily matches to alexey ignashov . take the round record of this row . select the rows whose opponent record fuzzily matches to lee hasdell . take the round record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; opponent ; alexey ignashov } ; round } ; hop { filter_eq { all_rows ; opponent ; lee hasdell } ; round } } = true | select the rows whose opponent record fuzzily matches to alexey ignashov . take the round record of this row . select the rows whose opponent record fuzzily matches to lee hasdell . take the round 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, 'opponent_7': 7, 'alexey ignashov_8': 8, 'round_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'opponent_11': 11, 'lee hasdell_12': 12, 'round_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', 'opponent_7': 'opponent', 'alexey ignashov_8': 'alexey ignashov', 'round_9': 'round', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'opponent_11': 'opponent', 'lee hasdell_12': 'lee hasdell', 'round_13': 'round'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'opponent_7': [0], 'alexey ignashov_8': [0], 'round_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'opponent_11': [1], 'lee hasdell_12': [1], 'round_13': [3]} | ['result', 'opponent', 'method', 'event', 'round', 'location'] | [['win', 'michael bisping', 'decision ( unanimous )', 'cwfc : strike force 1', '4', 'coventry , west midlands , england'], ['loss', 'aleksandr pitchkounov', 'decision ( unanimous )', 'ichigeki paris 2005', '5', 'paris , france'], ['loss', 'alexey ignashov', 'decision', 'mt one', '5', 'saint - pierre , réunion'], ['loss', 'petar majstorović', 'decision ( unanimous )', 'k - 1 spain grand prix 2003 in barcelona', '3', 'barcelona , spain'], ['win', 'damián garcía', 'ko', 'k - 1 spain grand prix 2003 in barcelona', '1', 'barcelona , spain'], ['win', 'lee hasdell', 'tko ( doctor stoppage )', 'shoot boxing : s volume 1', '4', 'tokyo , japan'], ['win', 'rick roufus', 'tko ( doctor stoppage )', 'iska championship', '3', 'las vegas , nevada , united states']] |
xavier malisse | https://en.wikipedia.org/wiki/Xavier_Malisse | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1551805-6.html.csv | count | 7 games that xavier malisse competed in were played on a hard surface . | {'scope': 'all', 'criterion': 'equal', 'value': 'hard', 'result': '7', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'surface', 'hard'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose surface record fuzzily matches to hard .', 'tostr': 'filter_eq { all_rows ; surface ; hard }'}], 'result': '7', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; surface ; hard } }', 'tointer': 'select the rows whose surface record fuzzily matches to hard . the number of such rows is 7 .'}, '7'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; surface ; hard } } ; 7 } = true', 'tointer': 'select the rows whose surface record fuzzily matches to hard . the number of such rows is 7 .'} | eq { count { filter_eq { all_rows ; surface ; hard } } ; 7 } = true | select the rows whose surface record fuzzily matches to hard . the number of such rows is 7 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'surface_5': 5, 'hard_6': 6, '7_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'surface_5': 'surface', 'hard_6': 'hard', '7_7': '7'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'surface_5': [0], 'hard_6': [0], '7_7': [2]} | ['outcome', 'year', 'surface', 'opponent', 'score'] | [['runner - up', '2 november 1998', 'clay', 'jiří novák', '3 - 6 , 3 - 6'], ['runner - up', '10 may 1999', 'clay', 'lleyton hewitt', '4 - 6 , 7 - 6 ( 7 - 2 ) , 1 - 6'], ['runner - up', '12 march 2001', 'hard', 'jan - michael gambill', '5 - 7 , 4 - 6'], ['runner - up', '30 april 2001', 'clay', 'andy roddick', '2 - 6 , 4 - 6'], ['runner - up', '24 may 2004', 'clay', 'filippo volandri', '1 - 6 , 4 - 6'], ['runner - up', '11 october 2004', 'carpet', 'robin söderling', '2 - 6 , 6 - 3 , 4 - 6'], ['winner', '31 january 2005', 'hard', 'jiří novák', '7 - 6 ( 8 - 6 ) , 6 - 2'], ['runner - up', '9 january 2006', 'hard', 'florent serra', '3 - 6 , 4 - 6'], ['runner - up', '6 february 2006', 'hard', 'tommy haas', '3 - 6 , 6 - 3 , 6 - 7 ( 5 - 7 )'], ['winner', '1 january 2007', 'hard', 'stefan koubek', '6 - 1 , 6 - 3'], ['winner', '28 january 2007', 'hard', 'james blake', '5 - 7 , 6 - 4 , 6 - 4'], ['runner - up', '11 january 2011', 'hard', 'stanislas wawrinka', '5 - 7 , 6 - 4 , 1 - 6']] |
2007 - 08 new orleans hornets season | https://en.wikipedia.org/wiki/2007%E2%80%9308_New_Orleans_Hornets_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11963536-8.html.csv | superlative | the match on 16 march 2008 had the highest attendance of all the matches . | {'scope': 'all', 'col_superlative': '6', 'row_superlative': '8', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'attendance'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; attendance }'}, 'date'], 'result': '16 march 2008', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; attendance } ; date }'}, '16 march 2008'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; attendance } ; date } ; 16 march 2008 } = true', 'tointer': 'select the row whose attendance record of all rows is maximum . the date record of this row is 16 march 2008 .'} | eq { hop { argmax { all_rows ; attendance } ; date } ; 16 march 2008 } = true | select the row whose attendance record of all rows is maximum . the date record of this row is 16 march 2008 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'attendance_5': 5, 'date_6': 6, '16 march 2008_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'attendance_5': 'attendance', 'date_6': 'date', '16 march 2008_7': '16 march 2008'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'attendance_5': [0], 'date_6': [1], '16 march 2008_7': [2]} | ['date', 'visitor', 'score', 'home', 'leading scorer', 'attendance', 'record'] | [['2 march 2008', 'hornets', 'l 84 - 101 ( ot )', 'wizards', 'peja stojakovic ( 17 )', '20173', '39 - 19'], ['3 march 2008', 'hornets', 'w 100 - 88 ( ot )', 'knicks', 'chris paul ( 27 )', '18467', '40 - 19'], ['5 march 2008', 'hawks', 'w 116 - 101 ( ot )', 'hornets', 'peja stojakovic ( 29 )', '17430', '41 - 19'], ['7 march 2008', 'nets', 'w 107 - 96 ( ot )', 'hornets', 'chris paul ( 25 )', '17225', '42 - 19'], ['8 march 2008', 'hornets', 'l 96 - 106 ( ot )', 'rockets', 'chris paul ( 37 )', '18279', '42 - 20'], ['12 march 2008', 'spurs', 'w 100 - 75 ( ot )', 'hornets', 'david west ( 29 )', '17419', '43 - 20'], ['14 march 2008', 'lakers', 'w 108 - 98 ( ot )', 'hornets', 'chris paul ( 27 )', '18299', '44 - 20'], ['16 march 2008', 'hornets', 'l 84 - 105 ( ot )', 'pistons', 'peja stojakovic ( 21 )', '22076', '44 - 21'], ['17 march 2008', 'bulls', 'w 108 - 97 ( ot )', 'hornets', 'chris paul ( 37 )', '17337', '45 - 21'], ['19 march 2008', 'rockets', 'w 90 - 69 ( ot )', 'hornets', 'bonzi wells ( 25 )', '18056', '46 - 21'], ['22 march 2008', 'celtics', 'w 113 - 106 ( ot )', 'hornets', 'david west ( 37 )', '18380', '47 - 21'], ['25 march 2008', 'hornets', 'w 114 - 106 ( ot )', 'pacers', 'david west ( 35 )', '10829', '48 - 21'], ['26 march 2008', 'hornets', 'w 100 - 99 ( ot )', 'cavaliers', 'peja stojakovic ( 25 )', '20562', '49 - 21'], ['28 march 2008', 'hornets', 'l 92 - 112 ( ot )', 'celtics', 'chris paul ( 22 )', '18624', '49 - 22'], ['30 march 2008', 'hornets', 'w 118 - 111 ( ot )', 'raptors', 'david west ( 32 )', '19800', '50 - 22']] |
list of indycar series teams | https://en.wikipedia.org/wiki/List_of_IndyCar_Series_teams | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2503102-2.html.csv | ordinal | rahal letterman lanigan racing is the team with the second lowest team number in the indycar series . | {'row': '6', 'col': '2', 'order': '2', 'col_other': '1', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', '-', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; - ; 2 }'}, 'team'], 'result': 'rahal letterman lanigan racing', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; - ; 2 } ; team }'}, 'rahal letterman lanigan racing'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; - ; 2 } ; team } ; rahal letterman lanigan racing } = true', 'tointer': 'select the row whose - record of all rows is 2nd minimum . the team record of this row is rahal letterman lanigan racing .'} | eq { hop { nth_argmin { all_rows ; - ; 2 } ; team } ; rahal letterman lanigan racing } = true | select the row whose - record of all rows is 2nd minimum . the team record of this row is rahal letterman lanigan racing . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, '-_5': 5, '2_6': 6, 'team_7': 7, 'rahal letterman lanigan racing_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', '-_5': '-', '2_6': '2', 'team_7': 'team', 'rahal letterman lanigan racing_8': 'rahal letterman lanigan racing'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], '-_5': [0], '2_6': [0], 'team_7': [1], 'rahal letterman lanigan racing_8': [2]} | ['team', '-', 'primary sponsor', 'driver ( s )', 'listed owner ( s )', 'engine', 'chassis'] | [['a j foyt enterprises', '41', 'abc supply', 'conor daly', 'a j foyt', 'honda', 'dallara'], ['andretti autosport', '26', 'electric energy straws', 'carlos muã ± oz', 'michael andretti', 'chevrolet', 'dallara'], ['chip ganassi racing', '8', 'ntt data', 'ryan briscoe', 'chip ganassi', 'honda', 'dallara'], ['dale coyne racing', '63', 'cyclops gear', 'pippa mann', 'dale coyne', 'honda', 'dallara'], ['lazier partners racing', '91', 'advance auto parts', 'buddy lazier', 'bob lazier corbet krause', 'chevrolet', 'dallara'], ['rahal letterman lanigan racing', '17', 'blu e - cigs', 'mike conway', 'mike lanigan david letterman bobby rahal', 'honda', 'dallara'], ['sam schmidt motorsports', '81', "angie 's list", 'katherine legge', 'sam schmidt ric peterson', 'honda', 'dallara'], ['sarah fisher hartman racing', '97', 'rotondo weirich / muscle milk', 'lucas luhr', "sarah fisher andy o'gara steve weirich", 'honda', 'dallara']] |
the bachelorette | https://en.wikipedia.org/wiki/The_Bachelorette | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-174953-1.html.csv | comparative | ryan sutter won the bachelorette before jesse csincsak won the show . | {'row_1': '1', 'row_2': '4', 'col': '2', 'col_other': '5', 'relation': 'less', 'record_mentioned': 'yes', 'diff_result': None} | {'func': 'and', 'args': [{'func': 'less', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'winner', 'ryan sutter'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose winner record fuzzily matches to ryan sutter .', 'tostr': 'filter_eq { all_rows ; winner ; ryan sutter }'}, 'premiered'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; winner ; ryan sutter } ; premiered }', 'tointer': 'select the rows whose winner record fuzzily matches to ryan sutter . take the premiered record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'winner', 'jesse csincsak'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose winner record fuzzily matches to jesse csincsak .', 'tostr': 'filter_eq { all_rows ; winner ; jesse csincsak }'}, 'premiered'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; winner ; jesse csincsak } ; premiered }', 'tointer': 'select the rows whose winner record fuzzily matches to jesse csincsak . take the premiered record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; winner ; ryan sutter } ; premiered } ; hop { filter_eq { all_rows ; winner ; jesse csincsak } ; premiered } }', 'tointer': 'select the rows whose winner record fuzzily matches to ryan sutter . take the premiered record of this row . select the rows whose winner record fuzzily matches to jesse csincsak . take the premiered record of this row . the first record is less than the second record .'}, {'func': 'and', 'args': [{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'winner', 'ryan sutter'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose winner record fuzzily matches to ryan sutter .', 'tostr': 'filter_eq { all_rows ; winner ; ryan sutter }'}, 'premiered'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; winner ; ryan sutter } ; premiered }', 'tointer': 'select the rows whose winner record fuzzily matches to ryan sutter . take the premiered record of this row .'}, 'january 8 , 2003'], 'result': True, 'ind': 5, 'tostr': 'eq { hop { filter_eq { all_rows ; winner ; ryan sutter } ; premiered } ; january 8 , 2003 }', 'tointer': 'the premiered record of the first row is january 8 , 2003 .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'winner', 'jesse csincsak'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose winner record fuzzily matches to jesse csincsak .', 'tostr': 'filter_eq { all_rows ; winner ; jesse csincsak }'}, 'premiered'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; winner ; jesse csincsak } ; premiered }', 'tointer': 'select the rows whose winner record fuzzily matches to jesse csincsak . take the premiered record of this row .'}, 'may 19 , 2008'], 'result': True, 'ind': 6, 'tostr': 'eq { hop { filter_eq { all_rows ; winner ; jesse csincsak } ; premiered } ; may 19 , 2008 }', 'tointer': 'the premiered record of the second row is may 19 , 2008 .'}], 'result': True, 'ind': 7, 'tostr': 'and { eq { hop { filter_eq { all_rows ; winner ; ryan sutter } ; premiered } ; january 8 , 2003 } ; eq { hop { filter_eq { all_rows ; winner ; jesse csincsak } ; premiered } ; may 19 , 2008 } }', 'tointer': 'the premiered record of the first row is january 8 , 2003 . the premiered record of the second row is may 19 , 2008 .'}], 'result': True, 'ind': 8, 'tostr': 'and { less { hop { filter_eq { all_rows ; winner ; ryan sutter } ; premiered } ; hop { filter_eq { all_rows ; winner ; jesse csincsak } ; premiered } } ; and { eq { hop { filter_eq { all_rows ; winner ; ryan sutter } ; premiered } ; january 8 , 2003 } ; eq { hop { filter_eq { all_rows ; winner ; jesse csincsak } ; premiered } ; may 19 , 2008 } } } = true', 'tointer': 'select the rows whose winner record fuzzily matches to ryan sutter . take the premiered record of this row . select the rows whose winner record fuzzily matches to jesse csincsak . take the premiered record of this row . the first record is less than the second record . the premiered record of the first row is january 8 , 2003 . the premiered record of the second row is may 19 , 2008 .'} | and { less { hop { filter_eq { all_rows ; winner ; ryan sutter } ; premiered } ; hop { filter_eq { all_rows ; winner ; jesse csincsak } ; premiered } } ; and { eq { hop { filter_eq { all_rows ; winner ; ryan sutter } ; premiered } ; january 8 , 2003 } ; eq { hop { filter_eq { all_rows ; winner ; jesse csincsak } ; premiered } ; may 19 , 2008 } } } = true | select the rows whose winner record fuzzily matches to ryan sutter . take the premiered record of this row . select the rows whose winner record fuzzily matches to jesse csincsak . take the premiered record of this row . the first record is less than the second record . the premiered record of the first row is january 8 , 2003 . the premiered record of the second row is may 19 , 2008 . | 13 | 9 | {'and_8': 8, 'result_9': 9, 'less_4': 4, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_10': 10, 'winner_11': 11, 'ryan sutter_12': 12, 'premiered_13': 13, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_14': 14, 'winner_15': 15, 'jesse csincsak_16': 16, 'premiered_17': 17, 'and_7': 7, 'str_eq_5': 5, 'january 8 , 2003_18': 18, 'str_eq_6': 6, 'may 19 , 2008_19': 19} | {'and_8': 'and', 'result_9': 'true', 'less_4': 'less', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_10': 'all_rows', 'winner_11': 'winner', 'ryan sutter_12': 'ryan sutter', 'premiered_13': 'premiered', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_14': 'all_rows', 'winner_15': 'winner', 'jesse csincsak_16': 'jesse csincsak', 'premiered_17': 'premiered', 'and_7': 'and', 'str_eq_5': 'str_eq', 'january 8 , 2003_18': 'january 8 , 2003', 'str_eq_6': 'str_eq', 'may 19 , 2008_19': 'may 19 , 2008'} | {'and_8': [9], 'result_9': [], 'less_4': [8], 'str_hop_2': [4, 5], 'filter_str_eq_0': [2], 'all_rows_10': [0], 'winner_11': [0], 'ryan sutter_12': [0], 'premiered_13': [2], 'str_hop_3': [4, 6], 'filter_str_eq_1': [3], 'all_rows_14': [1], 'winner_15': [1], 'jesse csincsak_16': [1], 'premiered_17': [3], 'and_7': [8], 'str_eq_5': [7], 'january 8 , 2003_18': [5], 'str_eq_6': [7], 'may 19 , 2008_19': [6]} | ['season', 'premiered', 'bachelorette', 'profile', 'winner', 'runner ( s ) - up', 'proposal'] | [['1', 'january 8 , 2003', 'trista rehn', 'physical therapist', 'ryan sutter', 'charlie maher', 'yes'], ['2', 'january 14 , 2004', 'meredith phillips', 'makeup artist', 'ian mckee', 'matthew hickl', 'yes'], ['3', 'january 10 , 2005', 'jennifer schefft', 'publicist', 'none', 'jerry ferris and john paul merritt', 'no'], ['4', 'may 19 , 2008', 'deanna pappas', 'real estate agent', 'jesse csincsak', 'jason mesnick', 'yes'], ['5', 'may 18 , 2009', 'jillian harris', 'interior designer', 'ed swiderski', 'kiptyn locke', 'yes'], ['6', 'may 24 , 2010', 'ali fedotowsky', 'advertising account manager', 'roberto martinez', 'chris lambton', 'yes'], ['7', 'may 23 , 2011', 'ashley hebert', 'dental student', 'jp rosenbaum', 'ben flajnik', 'yes'], ['8', 'may 14 , 2012', 'emily maynard', "children 's hospital event planner", 'jef holm', 'arie luyendyk , jr', 'yes'], ['9', 'may 27 , 2013', 'desiree hartsock', 'bridal stylist', 'chris siegfried', 'drew kenney', 'yes']] |
2006 - 07 macedonian cup | https://en.wikipedia.org/wiki/2006%E2%80%9307_Macedonian_Cup | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17065288-2.html.csv | count | in the ' 06 - '07 macedonian cup , 2 of the games have a 2nd . leg score of 0 - 1 or 1 - 0 . | {'scope': 'all', 'criterion': 'equal', 'value': '1 - 0', 'result': '2', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', '2nd leg', '1 - 0'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose 2nd leg record fuzzily matches to 1 - 0 .', 'tostr': 'filter_eq { all_rows ; 2nd leg ; 1 - 0 }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; 2nd leg ; 1 - 0 } }', 'tointer': 'select the rows whose 2nd leg record fuzzily matches to 1 - 0 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; 2nd leg ; 1 - 0 } } ; 2 } = true', 'tointer': 'select the rows whose 2nd leg record fuzzily matches to 1 - 0 . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; 2nd leg ; 1 - 0 } } ; 2 } = true | select the rows whose 2nd leg record fuzzily matches to 1 - 0 . the number of such rows is 2 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, '2nd leg_5': 5, '1 - 0_6': 6, '2_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', '2nd leg_5': '2nd leg', '1 - 0_6': '1 - 0', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], '2nd leg_5': [0], '1 - 0_6': [0], '2_7': [2]} | ['team 1', 'agg', 'team 2', '1st leg', '2nd leg'] | [['pobeda', '3 - 0', 'shkëndija 79', '2 - 0', '1 - 0'], ['vardar', '5 - 1', 'metalurg', '4 - 1', '1 - 0'], ['drita', '4 - 2', 'bregalnica kraun', '3 - 0', '1 - 2'], ['gostivar', '3 - 6', 'renova', '1 - 4', '2 - 2'], ['milano', '4 - 3', 'baškimi', '2 - 1', '2 - 2'], ['rabotnički', '5 - 4', 'ilinden', '4 - 0', '1 - 4'], ['makedonija', '0 - 2', 'meridian fcu', '0 - 2', '0 - 0'], ['madžari solidarnost', '2 - 4', 'pelister', '2 - 2', '0 - 2']] |
luke donald | https://en.wikipedia.org/wiki/Luke_Donald | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1590652-7.html.csv | superlative | luke donald places in the top - 10 more times in the masters tournament than any other tournament . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'top - 10'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; top - 10 }'}, 'tournament'], 'result': 'masters tournament', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; top - 10 } ; tournament }'}, 'masters tournament'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; top - 10 } ; tournament } ; masters tournament } = true', 'tointer': 'select the row whose top - 10 record of all rows is maximum . the tournament record of this row is masters tournament .'} | eq { hop { argmax { all_rows ; top - 10 } ; tournament } ; masters tournament } = true | select the row whose top - 10 record of all rows is maximum . the tournament record of this row is masters tournament . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'top - 10_5': 5, 'tournament_6': 6, 'masters tournament_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'top - 10_5': 'top - 10', 'tournament_6': 'tournament', 'masters tournament_7': 'masters tournament'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'top - 10_5': [0], 'tournament_6': [1], 'masters tournament_7': [2]} | ['tournament', 'wins', 'top - 5', 'top - 10', 'top - 25', 'events', 'cuts made'] | [['masters tournament', '0', '2', '3', '4', '9', '7'], ['us open', '0', '0', '1', '3', '9', '6'], ['the open championship', '0', '2', '2', '3', '13', '6'], ['pga championship', '0', '1', '2', '5', '10', '8'], ['totals', '0', '5', '8', '15', '41', '27']] |
european parliament election , 1984 ( ireland ) | https://en.wikipedia.org/wiki/European_Parliament_election%2C_1984_%28Ireland%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13564562-2.html.csv | ordinal | the connachtulster constituency recorded the 2nd highest quota during the 1984 european parliament election ( ireland ) . | {'row': '1', 'col': '6', 'order': '2', 'col_other': '1', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'quota', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; quota ; 2 }'}, 'constituency'], 'result': 'connachtulster', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; quota ; 2 } ; constituency }'}, 'connachtulster'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; quota ; 2 } ; constituency } ; connachtulster } = true', 'tointer': 'select the row whose quota record of all rows is 2nd maximum . the constituency record of this row is connachtulster .'} | eq { hop { nth_argmax { all_rows ; quota ; 2 } ; constituency } ; connachtulster } = true | select the row whose quota record of all rows is 2nd maximum . the constituency record of this row is connachtulster . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'quota_5': 5, '2_6': 6, 'constituency_7': 7, 'connachtulster_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', 'quota_5': 'quota', '2_6': '2', 'constituency_7': 'constituency', 'connachtulster_8': 'connachtulster'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'quota_5': [0], '2_6': [0], 'constituency_7': [1], 'connachtulster_8': [2]} | ['constituency', 'electorate', 'turnout', 'spoilt', 'valid poll', 'quota', 'seats', 'candidates'] | [['connachtulster', '471577', '241244 ( 51.2 % )', '5763 ( 2.4 % )', '235481', '58871', '3', '11'], ['dublin', '704873', '288831 ( 40.9 % )', '6153 ( 2.1 % )', '282678', '56536', '4', '12'], ['leinster', '545878', '268491 ( 49.2 % )', '9197 ( 3.4 % )', '259294', '64824', '3', '9'], ['munster', '691076', '349179 ( 50.5 % )', '6216 ( 1.8 % )', '342963', '57161', '5', '9'], ['total', '2413404', '1147745 ( 47.6 % )', '27329 ( 2.4 % )', '1120416', 'n / a', '15', '41']] |
canton railroad | https://en.wikipedia.org/wiki/Canton_Railroad | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15441362-1.html.csv | majority | a majority of trains on the canton railroad were switchers . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'switcher', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'type', 'switcher'], 'result': True, 'ind': 0, 'tointer': 'for the type records of all rows , most of them fuzzily match to switcher .', 'tostr': 'most_eq { all_rows ; type ; switcher } = true'} | most_eq { all_rows ; type ; switcher } = true | for the type records of all rows , most of them fuzzily match to switcher . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'type_3': 3, 'switcher_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'type_3': 'type', 'switcher_4': 'switcher'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'type_3': [0], 'switcher_4': [0]} | ['locomotive number', 'model', 'type', 'propulsion', 'manufacturer'] | [['ctn 32', 'vo - 1000', 'switcher', 'diesel - electric', 'baldwin locomotive works'], ['ctn 46', 'emd sw900', 'switcher', 'diesel - electric', 'gm electro - motive div'], ['ctn 50', 'emd sw9', 'switcher', 'diesel - electric', 'gm electro - motive div'], ['ctn 51', 'emd sw9', 'switcher', 'diesel - electric', 'gm electro - motive div'], ['ctn 1201', 'emd sw1200', 'switcher', 'diesel - electric', 'gm electro - motive div'], ['ctn 1203', 'emd sw1200', 'switcher', 'diesel - electric', 'gm electro - motive div'], ['ctn 1204', 'emd sw1200rs', 'switcher', 'diesel - electric', 'gm electro - motive div'], ['ctn 1307', 'emd gp7 u', 'four - axle roadswitcher', 'diesel - electric', 'gm electro - motive div'], ['ctn 1364', 'emd gp7u', 'four - axle roadswitcher', 'diesel - electric', 'gm electro - motive div'], ['ctn 1501', 'emd sw1500', 'switcher', 'diesel - electric', 'gm electro - motive div'], ['ctn 1502', 'emd sw1500', 'switcher', 'diesel - electric', 'gm electro - motive div']] |
yuriko kobayashi | https://en.wikipedia.org/wiki/Yuriko_Kobayashi | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17889598-1.html.csv | count | yuriko kobayashi participated in a total of four race competitions that were 1500 meters long . | {'scope': 'all', 'criterion': 'equal', 'value': '1500 m', 'result': '4', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'notes', '1500 m'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose notes record fuzzily matches to 1500 m .', 'tostr': 'filter_eq { all_rows ; notes ; 1500 m }'}], 'result': '4', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; notes ; 1500 m } }', 'tointer': 'select the rows whose notes record fuzzily matches to 1500 m . the number of such rows is 4 .'}, '4'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; notes ; 1500 m } } ; 4 } = true', 'tointer': 'select the rows whose notes record fuzzily matches to 1500 m . the number of such rows is 4 .'} | eq { count { filter_eq { all_rows ; notes ; 1500 m } } ; 4 } = true | select the rows whose notes record fuzzily matches to 1500 m . 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, 'notes_5': 5, '1500 m_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', 'notes_5': 'notes', '1500 m_6': '1500 m', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'notes_5': [0], '1500 m_6': [0], '4_7': [2]} | ['year', 'competition', 'venue', 'position', 'notes'] | [['2004', 'world junior championships', 'grosseto , italy', '4th ( heats )', '800 m'], ['2005', 'world youth championships', 'marrakech , morocco', '2nd', '1500 m'], ['2005', 'asian championships', 'incheon , south korea', '3rd', '1500 m'], ['2006', 'world cross country championships', 'fukuoka , japan', '11th', 'team competition'], ['2006', 'world junior championships', 'beijing , china', '3rd', '1500 m'], ['2006', 'asian games', 'doha , qatar', '2nd', '1500 m'], ['2008', 'summer olympics', 'beijing , china', '7th ( heats )', '5000 m'], ['2009', 'world championships', 'berlin , germany', '11th', '5000 m'], ['2009', 'east asian games', 'hong kong , china', '1st', '5000 m']] |
1979 detroit lions season | https://en.wikipedia.org/wiki/1979_Detroit_Lions_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18733329-2.html.csv | aggregation | the average crowd attendance during the 1979 detroit lions season was 60644 . | {'scope': 'all', 'col': '5', 'type': 'average', 'result': '60644', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'attendance'], 'result': '60644', 'ind': 0, 'tostr': 'avg { all_rows ; attendance }'}, '60644'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; attendance } ; 60644 } = true', 'tointer': 'the average of the attendance record of all rows is 60644 .'} | round_eq { avg { all_rows ; attendance } ; 60644 } = true | the average of the attendance record of all rows is 60644 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'attendance_4': 4, '60644_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'attendance_4': 'attendance', '60644_5': '60644'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'attendance_4': [0], '60644_5': [1]} | ['week', 'date', 'opponent', 'result', 'attendance'] | [['1', 'september 1 , 1979', 'tampa bay buccaneers', 'l 31 - 16', '68225'], ['2', 'september 9 , 1979', 'washington redskins', 'l 27 - 24', '54991'], ['3', 'september 16 , 1979', 'new york jets', 'l 31 - 10', '49612'], ['4', 'september 23 , 1979', 'atlanta falcons', 'w 24 - 23', '56249'], ['5', 'september 30 , 1979', 'minnesota vikings', 'l 13 - 10', '75295'], ['6', 'october 7 , 1979', 'new england patriots', 'l 24 - 17', '60629'], ['7', 'october 14 , 1979', 'green bay packers', 'l 24 - 16', '53930'], ['8', 'october 21 , 1979', 'new orleans saints', 'l 17 - 7', '57428'], ['9', 'october 28 , 1979', 'buffalo bills', 'l 20 - 17', '61911'], ['10', 'november 4 , 1979', 'chicago bears', 'l 35 - 7', '50108'], ['11', 'november 11 , 1979', 'tampa bay buccaneers', 'l 16 - 14', '70461'], ['12', 'november 18 , 1979', 'minnesota vikings', 'l 14 - 7', '43650'], ['13', 'november 22 , 1979', 'chicago bears', 'w 20 - 0', '66219'], ['14', 'december 2 , 1979', 'philadelphia eagles', 'l 44 - 7', '66128'], ['15', 'december 9 , 1979', 'miami dolphins', 'l 28 - 10', '78087'], ['16', 'december 15 , 1979', 'green bay packers', 'l 18 - 13', '57376']] |
longyan | https://en.wikipedia.org/wiki/Longyan | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1204998-2.html.csv | superlative | zhangping city has the lowest population density with 81 people per square km . | {'scope': 'all', 'col_superlative': '7', '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', 'population'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; population }'}, 'english name'], 'result': 'zhangping city', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; population } ; english name }'}, 'zhangping city'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmin { all_rows ; population } ; english name } ; zhangping city } = true', 'tointer': 'select the row whose population record of all rows is minimum . the english name record of this row is zhangping city .'} | eq { hop { argmin { all_rows ; population } ; english name } ; zhangping city } = true | select the row whose population record of all rows is minimum . the english name record of this row is zhangping city . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'population_5': 5, 'english name_6': 6, 'zhangping city_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'population_5': 'population', 'english name_6': 'english name', 'zhangping city_7': 'zhangping city'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'population_5': [0], 'english name_6': [1], 'zhangping city_7': [2]} | ['english name', 'simplified', 'traditional', 'pinyin', 'hakka', 'area', 'population', 'density'] | [['xinluo district', '新罗区', '新羅區', 'xīnluó qū', 'sîn - lò - khî', '2685', '662429', '247'], ['zhangping city', '漳平市', '漳平市', 'zhāngpíng shì', 'chông - phìn - sṳ', '2975', '240194', '81'], ['changting county', '长汀县', '長汀縣', 'chángtīng xiàn', 'tshòng - tin - yen', '3099', '393390', '127'], ['yongding county', '永定县', '永定縣', 'yǒngdìng xiàn', 'yún - thin - yen', '2216', '362658', '164'], ['shanghang county', '上杭县', '上杭縣', 'shàngháng xiàn', 'sông - hông - yen', '2879', '374047', '130'], ['wuping county', '武平县', '武平縣', 'wǔpíng xiàn', 'vú - phìn - yen', '2630', '278182', '106']] |
avc club volleyball championship | https://en.wikipedia.org/wiki/AVC_Club_Volleyball_Championship | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14841421-2.html.csv | majority | all of the countries competing in the avc club volleyball championship won at least one medal . | {'scope': 'all', 'col': '6', 'most_or_all': 'all', 'criterion': 'greater_than_eq', 'value': '1', 'subset': None} | {'func': 'all_greater_eq', 'args': ['all_rows', 'total', '1'], 'result': True, 'ind': 0, 'tointer': 'for the total records of all rows , all of them are greater than or equal to 1 .', 'tostr': 'all_greater_eq { all_rows ; total ; 1 } = true'} | all_greater_eq { all_rows ; total ; 1 } = true | for the total records of all rows , all of them are greater than or equal to 1 . | 1 | 1 | {'all_greater_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'total_3': 3, '1_4': 4} | {'all_greater_eq_0': 'all_greater_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'total_3': 'total', '1_4': '1'} | {'all_greater_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'total_3': [0], '1_4': [0]} | ['rank', 'nation', 'gold', 'silver', 'bronze', 'total'] | [['1', 'iran', '9', '4', '2', '15'], ['2', 'south korea', '2', '1', '0', '3'], ['3', 'kazakhstan', '1', '3', '2', '6'], ['4', 'qatar', '1', '2', '2', '5'], ['5', 'china', '1', '1', '4', '6'], ['6', 'saudi arabia', '0', '2', '0', '2'], ['7', 'japan', '0', '1', '2', '3'], ['8', 'chinese taipei', '0', '0', '1', '1'], ['8', 'indonesia', '0', '0', '1', '1'], ['total', 'total', '14', '14', '14', '42']] |
massachusetts route 139 | https://en.wikipedia.org/wiki/Massachusetts_Route_139 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-10568553-1.html.csv | ordinal | the western terminus rockland location has the third highest milepost value of these locations . | {'row': '3', 'col': '4', 'order': '3', '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', 'milepost', '3'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; milepost ; 3 }'}, 'location'], 'result': 'rockland', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; milepost ; 3 } ; location }'}, 'rockland'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; milepost ; 3 } ; location } ; rockland } = true', 'tointer': 'select the row whose milepost record of all rows is 3rd maximum . the location record of this row is rockland .'} | eq { hop { nth_argmax { all_rows ; milepost ; 3 } ; location } ; rockland } = true | select the row whose milepost record of all rows is 3rd maximum . the location record of this row is rockland . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'milepost_5': 5, '3_6': 6, 'location_7': 7, 'rockland_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', 'milepost_5': 'milepost', '3_6': '3', 'location_7': 'location', 'rockland_8': 'rockland'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'milepost_5': [0], '3_6': [0], 'location_7': [1], 'rockland_8': [2]} | ['county', 'location', 'street names', 'milepost', 'roads intersected', 'notes'] | [['norfolk', 'stoughton', 'pleasant street turnpike street lindelof avenue', '3.0', 'route 24', 'route 24 exit 20'], ['norfolk', 'weymouth', 'anne street', '( no major junctions )', '( no major junctions )', '( no major junctions )'], ['plymouth', 'rockland', 'north avenue plain street market street', '12.2', 'route 123', 'western terminus of route 123 / 139 concurrency'], ['plymouth', 'rockland', 'north avenue plain street market street', '12.8', 'route 123', 'eastern terminus of route 123 / 139 concurrency'], ['plymouth', 'hanover', 'hanover street rockland street columbia road', '17.9', 'route 53', 'northern terminus of route 53 / 139 concurrency']] |
canoeing at the 2008 summer olympics - men 's k - 1 500 metres | https://en.wikipedia.org/wiki/Canoeing_at_the_2008_Summer_Olympics_%E2%80%93_Men%27s_K-1_500_metres | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18646681-3.html.csv | unique | for canoeing at the 2008 summer olympics , in the men 's k - 1 500 metres , when the time is under 1:40 , the only athlete from canada is adam van koeverden . | {'scope': 'subset', 'row': '1', 'col': '3', 'col_other': '2', 'criterion': 'equal', 'value': 'canada', 'subset': {'col': '4', 'criterion': 'less_than', 'value': '1:40'}} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'time', '1:40'], 'result': None, 'ind': 0, 'tostr': 'filter_less { all_rows ; time ; 1:40 }', 'tointer': 'select the rows whose time record is less than 1:40 .'}, 'country', 'canada'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose time record is less than 1:40 . among these rows , select the rows whose country record fuzzily matches to canada .', 'tostr': 'filter_eq { filter_less { all_rows ; time ; 1:40 } ; country ; canada }'}], 'result': True, 'ind': 2, 'tostr': 'only { filter_eq { filter_less { all_rows ; time ; 1:40 } ; country ; canada } }', 'tointer': 'select the rows whose time record is less than 1:40 . among these rows , select the rows whose country record fuzzily matches to canada . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'time', '1:40'], 'result': None, 'ind': 0, 'tostr': 'filter_less { all_rows ; time ; 1:40 }', 'tointer': 'select the rows whose time record is less than 1:40 .'}, 'country', 'canada'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose time record is less than 1:40 . among these rows , select the rows whose country record fuzzily matches to canada .', 'tostr': 'filter_eq { filter_less { all_rows ; time ; 1:40 } ; country ; canada }'}, 'athletes'], 'result': 'adam van koeverden', 'ind': 3, 'tostr': 'hop { filter_eq { filter_less { all_rows ; time ; 1:40 } ; country ; canada } ; athletes }'}, 'adam van koeverden'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { filter_eq { filter_less { all_rows ; time ; 1:40 } ; country ; canada } ; athletes } ; adam van koeverden }', 'tointer': 'the athletes record of this unqiue row is adam van koeverden .'}], 'result': True, 'ind': 5, 'tostr': 'and { only { filter_eq { filter_less { all_rows ; time ; 1:40 } ; country ; canada } } ; eq { hop { filter_eq { filter_less { all_rows ; time ; 1:40 } ; country ; canada } ; athletes } ; adam van koeverden } } = true', 'tointer': 'select the rows whose time record is less than 1:40 . among these rows , select the rows whose country record fuzzily matches to canada . there is only one such row in the table . the athletes record of this unqiue row is adam van koeverden .'} | and { only { filter_eq { filter_less { all_rows ; time ; 1:40 } ; country ; canada } } ; eq { hop { filter_eq { filter_less { all_rows ; time ; 1:40 } ; country ; canada } ; athletes } ; adam van koeverden } } = true | select the rows whose time record is less than 1:40 . among these rows , select the rows whose country record fuzzily matches to canada . there is only one such row in the table . the athletes record of this unqiue row is adam van koeverden . | 8 | 6 | {'and_5': 5, 'result_6': 6, 'only_2': 2, 'filter_str_eq_1': 1, 'filter_less_0': 0, 'all_rows_7': 7, 'time_8': 8, '1:40_9': 9, 'country_10': 10, 'canada_11': 11, 'str_eq_4': 4, 'str_hop_3': 3, 'athletes_12': 12, 'adam van koeverden_13': 13} | {'and_5': 'and', 'result_6': 'true', 'only_2': 'only', 'filter_str_eq_1': 'filter_str_eq', 'filter_less_0': 'filter_less', 'all_rows_7': 'all_rows', 'time_8': 'time', '1:40_9': '1:40', 'country_10': 'country', 'canada_11': 'canada', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'athletes_12': 'athletes', 'adam van koeverden_13': 'adam van koeverden'} | {'and_5': [6], 'result_6': [], 'only_2': [5], 'filter_str_eq_1': [2, 3], 'filter_less_0': [1], 'all_rows_7': [0], 'time_8': [0], '1:40_9': [0], 'country_10': [1], 'canada_11': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'athletes_12': [3], 'adam van koeverden_13': [4]} | ['rank', 'athletes', 'country', 'time', 'notes'] | [['1', 'adam van koeverden', 'canada', '1:35.554 wb', 'qs'], ['2', 'eirik verãs larsen', 'norway', '1:36.439', 'qs'], ['3', 'michele zerial', 'italy', '1:36.950', 'qs'], ['4', 'steven ferguson', 'new zealand', '1:37.538', 'qs'], ['5', 'shaun rubenstein', 'south africa', '1:37.687', 'qs'], ['6', 'dmitriy torlopov', 'kazakhstan', '1:39.892', 'qs'], ['7', 'jorge garcia', 'cuba', '1:42.803', 'qs'], ['8', 'rudolph berking - williams', 'samoa', '1:47.839', 'qs']] |
eisbären berlin | https://en.wikipedia.org/wiki/Eisb%C3%A4ren_Berlin | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1790061-7.html.csv | ordinal | for eisbären berlin , when the season is in the 1990s , the 2nd highest number of games was for thomas graul . | {'scope': 'subset', 'row': '5', 'col': '3', 'order': '2', 'col_other': '1', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'subset': {'col': '2', 'criterion': 'fuzzily_match', 'value': '199'}} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'season', '199'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; season ; 199 }', 'tointer': 'select the rows whose season record fuzzily matches to 199 .'}, 'games', '2'], 'result': None, 'ind': 1, 'tostr': 'nth_argmax { filter_eq { all_rows ; season ; 199 } ; games ; 2 }'}, 'name'], 'result': 'thomas graul', 'ind': 2, 'tostr': 'hop { nth_argmax { filter_eq { all_rows ; season ; 199 } ; games ; 2 } ; name }'}, 'thomas graul'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { nth_argmax { filter_eq { all_rows ; season ; 199 } ; games ; 2 } ; name } ; thomas graul } = true', 'tointer': 'select the rows whose season record fuzzily matches to 199 . select the row whose games record of these rows is 2nd maximum . the name record of this row is thomas graul .'} | eq { hop { nth_argmax { filter_eq { all_rows ; season ; 199 } ; games ; 2 } ; name } ; thomas graul } = true | select the rows whose season record fuzzily matches to 199 . select the row whose games record of these rows is 2nd maximum . the name record of this row is thomas graul . | 4 | 4 | {'str_eq_3': 3, 'result_4': 4, 'str_hop_2': 2, 'nth_argmax_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'season_6': 6, '199_7': 7, 'games_8': 8, '2_9': 9, 'name_10': 10, 'thomas graul_11': 11} | {'str_eq_3': 'str_eq', 'result_4': 'true', 'str_hop_2': 'str_hop', 'nth_argmax_1': 'nth_argmax', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'season_6': 'season', '199_7': '199', 'games_8': 'games', '2_9': '2', 'name_10': 'name', 'thomas graul_11': 'thomas graul'} | {'str_eq_3': [4], 'result_4': [], 'str_hop_2': [3], 'nth_argmax_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'season_6': [0], '199_7': [0], 'games_8': [1], '2_9': [1], 'name_10': [2], 'thomas graul_11': [3]} | ['name', 'season', 'games', 'goals', 'assists', 'points'] | [['name', 'season', 'games', 'goals', 'assists', 'points'], ['mark jooris', '1991 - 1992', '50', '54', '69', '123'], ['steve walker', '2007 - 2008', '53', '27', '58', '85'], ['jiří dopita', '1994 - 1995', '42', '28', '40', '68'], ['thomas graul', '1991 - 1992', '47', '28', '32', '60'], ['alex hicks', '2000 - 2001', '56', '27', '31', '58']] |
1930 vfl season | https://en.wikipedia.org/wiki/1930_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10767641-15.html.csv | ordinal | mcg venue recorded the highest crowd participation during the 1930 vfl season . | {'row': '6', 'col': '6', 'order': '1', 'col_other': '5', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'crowd', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; crowd ; 1 }'}, 'venue'], 'result': 'mcg', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; crowd ; 1 } ; venue }'}, 'mcg'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; crowd ; 1 } ; venue } ; mcg } = true', 'tointer': 'select the row whose crowd record of all rows is 1st maximum . the venue record of this row is mcg .'} | eq { hop { nth_argmax { all_rows ; crowd ; 1 } ; venue } ; mcg } = true | select the row whose crowd record of all rows is 1st maximum . the venue record of this row is mcg . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'crowd_5': 5, '1_6': 6, 'venue_7': 7, 'mcg_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'crowd_5': 'crowd', '1_6': '1', 'venue_7': 'venue', 'mcg_8': 'mcg'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'crowd_5': [0], '1_6': [0], 'venue_7': [1], 'mcg_8': [2]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['geelong', '18.17 ( 125 )', 'hawthorn', '6.7 ( 43 )', 'corio oval', '9000', '23 august 1930'], ['footscray', '8.18 ( 66 )', 'south melbourne', '11.18 ( 84 )', 'western oval', '12500', '23 august 1930'], ['fitzroy', '11.5 ( 71 )', 'richmond', '8.12 ( 60 )', 'brunswick street oval', '14000', '23 august 1930'], ['north melbourne', '6.12 ( 48 )', 'essendon', '14.11 ( 95 )', 'arden street oval', '8000', '23 august 1930'], ['st kilda', '14.7 ( 91 )', 'collingwood', '17.13 ( 115 )', 'junction oval', '16000', '23 august 1930'], ['melbourne', '12.11 ( 83 )', 'carlton', '11.11 ( 77 )', 'mcg', '31481', '23 august 1930']] |
2006 latvian first league | https://en.wikipedia.org/wiki/2006_Latvian_First_League | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18017936-2.html.csv | aggregation | on average , the number of losses that teams playing in the 2006 latvian first league had was around 13 losses . | {'scope': 'all', 'col': '6', 'type': 'average', 'result': '13', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'losses'], 'result': '13', 'ind': 0, 'tostr': 'avg { all_rows ; losses }'}, '13'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; losses } ; 13 } = true', 'tointer': 'the average of the losses record of all rows is 13 .'} | round_eq { avg { all_rows ; losses } ; 13 } = true | the average of the losses record of all rows is 13 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'losses_4': 4, '13_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'losses_4': 'losses', '13_5': '13'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'losses_4': [0], '13_5': [1]} | ['position', 'club', 'played', 'wins', 'draws', 'losses', 'goals for', 'goals against', 'points', 'goal difference'] | [['1', 'jfk olimps r카ga', '30', '26', '2', '2', '111', '15', '80', '+ 96'], ['2', 'fc ditton - 2 daugavpils', '30', '21', '7', '2', '88', '24', '70', '+ 64'], ['3', 'skonto - 2 riga', '30', '20', '5', '5', '78', '23', '65', '+ 55'], ['4', 'ventspils - 2', '30', '20', '4', '6', '108', '25', '64', '+ 83'], ['5', 'r카ga - 2', '30', '17', '3', '10', '74', '44', '54', '+ 30'], ['6', 'dinaburg - zemessardze daugavpils', '30', '16', '3', '17', '60', '51', '51', '+ 9'], ['7', 'fk valmiera', '30', '13', '7', '10', '50', '53', '46', '- 3'], ['8', 'liepajas metalurgs - 2', '30', '13', '6', '11', '68', '47', '45', '+ 21'], ['9', 'fk jelgava', '30', '12', '6', '12', '53', '49', '42', '+ 4'], ['10', 'eirobaltija riga', '30', '11', '7', '12', '50', '40', '40', '+ 10'], ['11', 'j큰rmala - 2', '30', '10', '5', '15', '86', '74', '35', '+ 12'], ['12', 'tranz카ts ventspils', '30', '8', '4', '18', '37', '88', '28', '- 51'], ['13', 'multibanka riga', '30', '7', '6', '17', '34', '58', '27', '- 24'], ['14', 'fk auda kekava', '30', '5', '2', '23', '28', '79', '17', '- 51'], ['15', 'alberts riga', '30', '4', '4', '22', '32', '114', '16', '- 82'], ['16', 'abuls smiltene', '30', '1', '1', '28', '18', '191', '4', '- 173']] |
2008 - 09 los angeles clippers season | https://en.wikipedia.org/wiki/2008%E2%80%9309_Los_Angeles_Clippers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17323529-7.html.csv | superlative | the game played by the los angeles clippers on january 30 drew the highest attendance number . | {'scope': 'all', 'col_superlative': '8', 'row_superlative': '15', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '2', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'location attendance'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; location attendance }'}, 'date'], 'result': 'january 30', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; location attendance } ; date }'}, 'january 30'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; location attendance } ; date } ; january 30 } = true', 'tointer': 'select the row whose location attendance record of all rows is maximum . the date record of this row is january 30 .'} | eq { hop { argmax { all_rows ; location attendance } ; date } ; january 30 } = true | select the row whose location attendance record of all rows is maximum . the date record of this row is january 30 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'location attendance_5': 5, 'date_6': 6, 'january 30_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'location attendance_5': 'location attendance', 'date_6': 'date', 'january 30_7': 'january 30'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'location attendance_5': [0], 'date_6': [1], 'january 30_7': [2]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record'] | [['32', 'january 2', 'phoenix', 'l 98 - 106 ( ot )', 'eric gordon ( 21 )', 'marcus camby ( 23 )', 'fred jones , marcus camby ( 4 )', 'us airways center 18422', '8 - 24'], ['33', 'january 4', 'detroit', 'l 87 - 88 ( ot )', 'eric gordon ( 31 )', 'marcus camby ( 20 )', 'mardy collins ( 12 )', 'staples center 17968', '8 - 25'], ['34', 'january 6', 'dallas', 'l 102 - 107 ( ot )', 'eric gordon ( 32 )', 'marcus camby ( 19 )', 'eric gordon ( 6 )', 'american airlines center 19794', '8 - 26'], ['35', 'january 8', 'san antonio', 'l 84 - 106 ( ot )', 'al thornton , eric gordon ( 21 )', 'marcus camby ( 9 )', 'jason hart ( 4 )', 'at & t center 17873', '8 - 27'], ['36', 'january 9', 'new orleans', 'l 80 - 107 ( ot )', 'eric gordon , mardy collins ( 15 )', 'marcus camby ( 17 )', 'mardy collins ( 6 )', 'new orleans arena 17815', '8 - 28'], ['37', 'january 11', 'phoenix', 'l 103 - 109 ( ot )', 'al thornton ( 23 )', 'marcus camby ( 18 )', 'fred jones ( 10 )', 'staples center 17307', '8 - 29'], ['38', 'january 14', 'atlanta', 'l 80 - 97 ( ot )', 'al thornton ( 25 )', 'marcus camby ( 18 )', 'mardy collins ( 8 )', 'staples center 15901', '8 - 30'], ['39', 'january 17', 'milwaukee', 'w 101 - 92 ( ot )', 'brian skinner , marcus camby ( 18 )', 'marcus camby ( 11 )', 'mardy collins ( 11 )', 'staples center 16448', '9 - 30'], ['40', 'january 19', 'minnesota', 'l 86 - 94 ( ot )', 'eric gordon ( 25 )', 'deandre jordan ( 10 )', 'mardy collins ( 8 )', 'staples center 14399', '9 - 31'], ['41', 'january 21', 'la lakers', 'l 97 - 108 ( ot )', 'deandre jordan ( 23 )', 'deandre jordan ( 12 )', 'eric gordon ( 6 )', 'staples center 19627', '9 - 32'], ['42', 'january 23', 'oklahoma city', 'w 107 - 104 ( ot )', 'eric gordon ( 41 )', 'cheikh samb ( 8 )', 'ricky davis ( 11 )', 'staples center 14913', '10 - 32'], ['43', 'january 25', 'golden state', 'l 92 - 107 ( ot )', 'eric gordon ( 21 )', 'deandre jordan ( 20 )', 'ricky davis ( 7 )', 'oracle arena 17746', '10 - 33'], ['44', 'january 26', 'portland', 'l 88 - 113 ( ot )', 'al thornton ( 23 )', 'brian skinner ( 10 )', 'fred jones , eric gordon ( 7 )', 'staples center 16570', '10 - 34'], ['45', 'january 28', 'chicago', 'l 75 - 95 ( ot )', 'eric gordon ( 19 )', 'al thornton , deandre jordan , marcus camby ( 6 )', 'eric gordon ( 7 )', 'staples center 15637', '10 - 35'], ['46', 'january 30', 'cleveland', 'l 95 - 112 ( ot )', 'eric gordon ( 27 )', 'eric gordon , baron davis ( 7 )', 'fred jones ( 9 )', 'quicken loans arena 20562', '10 - 36'], ['47', 'january 31', 'washington', 'l 94 - 106 ( ot )', 'eric gordon ( 25 )', 'brian skinner ( 10 )', 'baron davis , fred jones ( 6 )', 'verizon center 18227', '10 - 37']] |
who do you think you are ? ( canadian tv series ) | https://en.wikipedia.org/wiki/Who_Do_You_Think_You_Are%3F_%28Canadian_TV_series%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-11642945-1.html.csv | comparative | out of who do you think you are ? episodes , the one directed by david langer has an air date that 's earlier than that of the one directed by matt gallagher . | {'row_1': '3', 'row_2': '7', 'col': '4', 'col_other': '3', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'director', 'david langer'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose director record fuzzily matches to david langer .', 'tostr': 'filter_eq { all_rows ; director ; david langer }'}, 'original air date'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; director ; david langer } ; original air date }', 'tointer': 'select the rows whose director record fuzzily matches to david langer . take the original air date record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'director', 'matt gallagher'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose director record fuzzily matches to matt gallagher .', 'tostr': 'filter_eq { all_rows ; director ; matt gallagher }'}, 'original air date'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; director ; matt gallagher } ; original air date }', 'tointer': 'select the rows whose director record fuzzily matches to matt gallagher . take the original air date record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; director ; david langer } ; original air date } ; hop { filter_eq { all_rows ; director ; matt gallagher } ; original air date } } = true', 'tointer': 'select the rows whose director record fuzzily matches to david langer . take the original air date record of this row . select the rows whose director record fuzzily matches to matt gallagher . take the original air date record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; director ; david langer } ; original air date } ; hop { filter_eq { all_rows ; director ; matt gallagher } ; original air date } } = true | select the rows whose director record fuzzily matches to david langer . take the original air date record of this row . select the rows whose director record fuzzily matches to matt gallagher . take the original air date record of this row . the first record is less than the second record . | 5 | 5 | {'less_4': 4, 'result_5': 5, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'director_7': 7, 'david langer_8': 8, 'original air date_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'director_11': 11, 'matt gallagher_12': 12, 'original air date_13': 13} | {'less_4': 'less', 'result_5': 'true', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'director_7': 'director', 'david langer_8': 'david langer', 'original air date_9': 'original air date', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'director_11': 'director', 'matt gallagher_12': 'matt gallagher', 'original air date_13': 'original air date'} | {'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'director_7': [0], 'david langer_8': [0], 'original air date_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'director_11': [1], 'matt gallagher_12': [1], 'original air date_13': [3]} | ['total no', 'celebrity', 'director', 'original air date', 'viewers'] | [['1', 'shaun majumder', 'scott harper', '11 october 2007', 'n / a'], ['2', 'margot kidder', 'margaret slaght', '18 october 2007', 'n / a'], ['3', 'steven page', 'david langer', '25 october 2007', 'n / a'], ['4', 'sonja smits', 'karen pinker', '1 november 2007', 'n / a'], ['5', 'chantal kreviazuk', 'nadine schwartz', '8 november 2007', 'n / a'], ['6', 'major - general lewis mackenzie', 'richard martyn', '15 november 2007', 'n / a'], ['7', 'mary walsh', 'matt gallagher', '22 november 2007', 'n / a'], ['8', 'randy bachman', 'margaret slaght', '29 november 2007', 'n / a'], ['9', 'scott thompson', 'scott harper', '6 december 2007', 'n / a'], ['10', 'don cherry', 'richard martyn', '10 january 2008', 'n / a'], ['11', 'measha brueggergosman', 'karen pinker', '17 january 2008', 'n / a'], ['12', 'margaret trudeau', 'peter findlay', '24 january 2008', 'n / a']] |
statistics relating to enlargement of the european union | https://en.wikipedia.org/wiki/Statistics_relating_to_enlargement_of_the_European_Union | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1307842-7.html.csv | superlative | existing members ( 2004 ) of the european union account for the most gdp ( billion us ) . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '13', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'gdp ( billion us )'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; gdp ( billion us ) }'}, 'member countries'], 'result': 'eu25 ( 2004 )', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; gdp ( billion us ) } ; member countries }'}, 'eu25 ( 2004 )'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; gdp ( billion us ) } ; member countries } ; eu25 ( 2004 ) } = true', 'tointer': 'select the row whose gdp ( billion us ) record of all rows is maximum . the member countries record of this row is eu25 ( 2004 ) .'} | eq { hop { argmax { all_rows ; gdp ( billion us ) } ; member countries } ; eu25 ( 2004 ) } = true | select the row whose gdp ( billion us ) record of all rows is maximum . the member countries record of this row is eu25 ( 2004 ) . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'gdp (billion us)_5': 5, 'member countries_6': 6, 'eu25 (2004)_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'gdp (billion us)_5': 'gdp ( billion us )', 'member countries_6': 'member countries', 'eu25 (2004)_7': 'eu25 ( 2004 )'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'gdp (billion us)_5': [0], 'member countries_6': [1], 'eu25 (2004)_7': [2]} | ['member countries', 'population', 'area ( km square )', 'gdp ( billion us )', 'gdp per capita ( us )'] | [['cyprus', '775927', '9250', '11.681', '15054'], ['czech republic', '10246178', '78866', '105.248', '10272'], ['estonia', '1341664', '45226', '22.384', '16684'], ['hungary', '10032375', '93030', '102183', '10185'], ['latvia', '2306306', '64589', '24.826', '10764'], ['lithuania', '3607899', '65200', '31.971', '8861'], ['malta', '396851', '316', '5.097', '12843'], ['poland', '38580445', '311904', '316.438', '8202'], ['slovakia', '5423567', '49036', '42.800', '7810'], ['slovenia', '2011473', '20273', '29.633', '14732'], ['accession countries', '74722685', '737690', '685.123', '9169'], ['existing members ( 2004 )', '381781620', '3367154', '7711.871', '20200'], ['eu25 ( 2004 )', '456504305 ( + 19.57 % )', '4104844 ( + 17.97 % )', '8396994 ( + 8.88 % )', '18394 ( 8.94 % )']] |
2002 belarusian premier league | https://en.wikipedia.org/wiki/2002_Belarusian_Premier_League | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14747981-1.html.csv | aggregation | the average capacity for all venues in the 2002 belarusian premier league is just over 9900 . | {'scope': 'all', 'col': '4', 'type': 'average', 'result': '9900', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'capacity'], 'result': '9900', 'ind': 0, 'tostr': 'avg { all_rows ; capacity }'}, '9900'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; capacity } ; 9900 } = true', 'tointer': 'the average of the capacity record of all rows is 9900 .'} | round_eq { avg { all_rows ; capacity } ; 9900 } = true | the average of the capacity record of all rows is 9900 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'capacity_4': 4, '9900_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'capacity_4': 'capacity', '9900_5': '9900'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'capacity_4': [0], '9900_5': [1]} | ['team', 'location', 'venue', 'capacity', 'position in 2001'] | [['belshina', 'bobruisk', 'spartak , bobruisk', '3550', '1'], ['dinamo minsk', 'minsk', 'dinamo , minsk', '41040', '2'], ['bate', 'borisov', 'city stadium , borisov', '5500', '3'], ['neman', 'grodno', 'neman', '6300', '4'], ['shakhtyor', 'soligorsk', 'stroitel', '5000', '5'], ['gomel', 'gomel', 'central , gomel', '11800', '6'], ['slavia', 'mozyr', 'yunost', '5500', '7'], ['torpedo - maz', 'minsk', 'torpedo , minsk', '5200', '8'], ['dnepr - transmash', 'mogilev', 'spartak , mogilev', '11200', '9'], ['molodechno - 2000', 'molodechno', 'city stadium , molodechno', '5500', '10'], ['dinamo brest', 'brest', 'osk brestskiy', '10080', '11'], ['lokomotiv - 96', 'vitebsk', 'central , vitebsk', '8300', '12'], ['torpedo', 'zhodino', 'torpedo , zhodino', '3020', 'first league , 1'], ['zvezda - va - bgu', 'minsk', 'traktor', '17600', 'first league , 2']] |
sterling marlin | https://en.wikipedia.org/wiki/Sterling_Marlin | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1708014-2.html.csv | aggregation | of the races sterling martin participated in , his average number of wins was .12 . | {'scope': 'all', 'col': '3', 'type': 'average', 'result': '.12', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'wins'], 'result': '.12', 'ind': 0, 'tostr': 'avg { all_rows ; wins }'}, '.12'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; wins } ; .12 } = true', 'tointer': 'the average of the wins record of all rows is .12 .'} | round_eq { avg { all_rows ; wins } ; .12 } = true | the average of the wins record of all rows is .12 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'wins_4': 4, '.12_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'wins_4': 'wins', '.12_5': '.12'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'wins_4': [0], '.12_5': [1]} | ['year', 'starts', 'wins', 'top 5', 'top 10', 'poles', 'avg start', 'avg finish', 'winnings', 'position', 'team ( s )'] | [['1986', '1', '0', '0', '0', '0', '29.0', '29.0', '830', '133rd', '69 hagan racing'], ['1988', '4', '0', '0', '0', '0', '19.2', '17.2', '6406', '46th', '44 hagan racing'], ['1989', '2', '0', '0', '0', '0', '17.5', '32.0', '12475', '77th', '48 hagan racing'], ['1990', '5', '1', '2', '2', '0', '16.8', '14.6', '81690', '48th', '48 fred turner racing'], ['1992', '2', '0', '1', '1', '0', '15.0', '21.5', '13169', '73rd', '10 fred turner racing'], ['1993', '8', '0', '1', '2', '0', '28.1', '18.8', '36493', '41st', '48 fred turner racing'], ['1994', '9', '0', '1', '3', '0', '21.9', '25.0', '49680', '44th', '4 fred turner racing'], ['1995', '1', '0', '0', '0', '0', '7.0', '36.0', '2085', '106th', '22 fred turner racing'], ['1996', '2', '0', '1', '1', '1', '8.5', '12.5', '31285', '60th', '22 fred turner racing 92 martin racing'], ['1997', '3', '0', '0', '0', '0', '27.0', '22.7', '17020', '69th', '92 martin racing 4 phoenix racing'], ['1998', '5', '0', '0', '2', '0', '25.0', '22.0', '35649', '58th', '1 sterling marlin racing'], ['1999', '7', '0', '1', '3', '0', '9.4', '18.7', '67565', '54th', '42 joe gibbs racing 14 sterling marlin racing'], ['2000', '4', '1', '2', '3', '0', '15.0', '14.0', '56575', '62nd', '82 / 01 team sabco'], ['2004', '2', '0', '0', '0', '0', '28.5', '29.0', '36458', '102nd', '1 phoenix racing'], ['2005', '19', '0', '3', '5', '0', '23.6', '20.5', '408295', '29th', '40 / 12 fitzbradshaw racing'], ['2007', '2', '0', '0', '0', '0', '13.5', '20.5', '39605', '106th', '1 phoenix racing'], ['2008', '1', '0', '0', '0', '0', '20.0', '22.0', '25284', '118th', '1 phoenix racing']] |
matthew shepard and james byrd , jr. hate crimes prevention act | https://en.wikipedia.org/wiki/Matthew_Shepard_and_James_Byrd%2C_Jr._Hate_Crimes_Prevention_Act | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11045469-1.html.csv | count | for the matthew shepard and james byrd , jr. hate crimes prevention act , during the 111th congress , there were two times it was introduced in april . | {'scope': 'subset', 'criterion': 'fuzzily_match', 'value': 'april', 'result': '2', 'col': '3', 'subset': {'col': '1', 'criterion': 'equal', 'value': '111th congress'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'congress', '111th congress'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; congress ; 111th congress }', 'tointer': 'select the rows whose congress record fuzzily matches to 111th congress .'}, 'date introduced', 'april'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose congress record fuzzily matches to 111th congress . among these rows , select the rows whose date introduced record fuzzily matches to april .', 'tostr': 'filter_eq { filter_eq { all_rows ; congress ; 111th congress } ; date introduced ; april }'}], 'result': '2', 'ind': 2, 'tostr': 'count { filter_eq { filter_eq { all_rows ; congress ; 111th congress } ; date introduced ; april } }', 'tointer': 'select the rows whose congress record fuzzily matches to 111th congress . among these rows , select the rows whose date introduced record fuzzily matches to april . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_eq { filter_eq { all_rows ; congress ; 111th congress } ; date introduced ; april } } ; 2 } = true', 'tointer': 'select the rows whose congress record fuzzily matches to 111th congress . among these rows , select the rows whose date introduced record fuzzily matches to april . the number of such rows is 2 .'} | eq { count { filter_eq { filter_eq { all_rows ; congress ; 111th congress } ; date introduced ; april } } ; 2 } = true | select the rows whose congress record fuzzily matches to 111th congress . among these rows , select the rows whose date introduced record fuzzily matches to april . 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, 'congress_6': 6, '111th congress_7': 7, 'date introduced_8': 8, 'april_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', 'congress_6': 'congress', '111th congress_7': '111th congress', 'date introduced_8': 'date introduced', 'april_9': 'april', '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], 'congress_6': [0], '111th congress_7': [0], 'date introduced_8': [1], 'april_9': [1], '2_10': [3]} | ['congress', 'bill number', 'date introduced', 'sponsor', 'of cosponsors'] | [['107th congress', 'hr 1343', 'april 3 , 2001', 'rep john conyers ( d - mi )', '208'], ['107th congress', 's 625', 'march 27 , 2001', 'sen ted kennedy ( d - ma )', '50'], ['108th congress', 'hr 4204', 'april 22 , 2004', 'rep john conyers ( d - mi )', '178'], ['108th congress', 'samdt 3183 to s 2400', 'june 14 , 2004', 'sen gordon h smith ( r - or )', '4'], ['109th congress', 'hr 2662', 'may 26 , 2005', 'rep john conyers ( d - mi )', '159'], ['109th congress', 's 1145', 'may 26 , 2005', 'sen ted kennedy ( d - ma )', '45'], ['110th congress', 'hr 1592', 'march 30 , 2007', 'rep john conyers ( d - mi )', '171'], ['110th congress', 's 1105', 'april 12 , 2007', 'sen ted kennedy ( d - ma )', '44'], ['111th congress', 'hr 1913', 'april 2 , 2009', 'rep john conyers ( d - mi )', '120'], ['111th congress', 's 909', 'april 28 , 2009', 'sen ted kennedy ( d - ma )', '45'], ['111th congress', 'samdt 1511 to s 1390', 'july 15 , 2009', 'sen patrick leahy ( d - vt )', '37']] |
2004 baltimore ravens season | https://en.wikipedia.org/wiki/2004_Baltimore_Ravens_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18731638-1.html.csv | superlative | during the 2004 baltimore ravens season , the game with the highest attendance against a team from pennsylvania was on september 19th . | {'scope': 'subset', 'col_superlative': '7', 'row_superlative': '2', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '2', 'subset': {'col': '3', 'criterion': 'equal', 'value': 'pittsburgh steelers'}} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', 'pittsburgh steelers'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; opponent ; pittsburgh steelers }', 'tointer': 'select the rows whose opponent record fuzzily matches to pittsburgh steelers .'}, 'attendance'], 'result': None, 'ind': 1, 'tostr': 'argmax { filter_eq { all_rows ; opponent ; pittsburgh steelers } ; attendance }'}, 'date'], 'result': 'september 19 , 2004', 'ind': 2, 'tostr': 'hop { argmax { filter_eq { all_rows ; opponent ; pittsburgh steelers } ; attendance } ; date }'}, 'september 19 , 2004'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { argmax { filter_eq { all_rows ; opponent ; pittsburgh steelers } ; attendance } ; date } ; september 19 , 2004 } = true', 'tointer': 'select the rows whose opponent record fuzzily matches to pittsburgh steelers . select the row whose attendance record of these rows is maximum . the date record of this row is september 19 , 2004 .'} | eq { hop { argmax { filter_eq { all_rows ; opponent ; pittsburgh steelers } ; attendance } ; date } ; september 19 , 2004 } = true | select the rows whose opponent record fuzzily matches to pittsburgh steelers . select the row whose attendance record of these rows is maximum . the date record of this row is september 19 , 2004 . | 4 | 4 | {'str_eq_3': 3, 'result_4': 4, 'str_hop_2': 2, 'argmax_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'opponent_6': 6, 'pittsburgh steelers_7': 7, 'attendance_8': 8, 'date_9': 9, 'september 19 , 2004_10': 10} | {'str_eq_3': 'str_eq', 'result_4': 'true', 'str_hop_2': 'str_hop', 'argmax_1': 'argmax', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'opponent_6': 'opponent', 'pittsburgh steelers_7': 'pittsburgh steelers', 'attendance_8': 'attendance', 'date_9': 'date', 'september 19 , 2004_10': 'september 19 , 2004'} | {'str_eq_3': [4], 'result_4': [], 'str_hop_2': [3], 'argmax_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'opponent_6': [0], 'pittsburgh steelers_7': [0], 'attendance_8': [1], 'date_9': [2], 'september 19 , 2004_10': [3]} | ['week', 'date', 'opponent', 'result', 'record', 'tv time', 'attendance'] | [['1', 'september 12 , 2004', 'cleveland browns', 'l 20 - 3', '0 - 1 - 0', 'cbs 1:00 pm', '73068'], ['2', 'september 19 , 2004', 'pittsburgh steelers', 'w 30 - 13', '1 - 1 - 0', 'cbs 1:00 pm', '69859'], ['3', 'september 26 , 2004', 'cincinnati bengals', 'w 23 - 9', '2 - 1 - 0', 'cbs 1:00 pm', '65575'], ['4', 'october 4 , 2004', 'kansas city chiefs', 'l 27 - 24', '2 - 2 - 0', 'abc 9:00 pm', '69827'], ['5', 'october 10 , 2004', 'washington redskins', 'w 17 - 10', '3 - 2 - 0', 'espn 8:30 pm', '90287'], ['6', '-', '-', '-', '-', '-', ''], ['7', 'october 24 , 2004', 'buffalo bills', 'w 20 - 6', '4 - 2 - 0', 'cbs 1:00 pm', '69809'], ['8', 'october 31 , 2004', 'philadelphia eagles', 'l 15 - 10', '4 - 3 - 0', 'cbs 1:00 pm', '67715'], ['9', 'november 7 , 2004', 'cleveland browns', 'w 27 - 13', '5 - 3 - 0', 'espn 8:30 pm', '69781'], ['10', 'november 14 , 2004', 'new york jets', 'w 20 - 17 ot', '6 - 3 - 0', 'cbs 1:00 pm', '77826'], ['11', 'november 21 , 2004', 'dallas cowboys', 'w 30 - 10', '7 - 3 - 0', 'fox 1:00 pm', '69924'], ['12', 'november 28 , 2004', 'new england patriots', 'l 24 - 3', '7 - 4 - 0', 'cbs 4:15 pm', '68756'], ['13', 'december 5 , 2004', 'cincinnati bengals', 'l 27 - 26', '7 - 5 - 0', 'cbs 1:00 pm', '69695'], ['14', 'december 12 , 2004', 'new york giants', 'w 37 - 14', '8 - 5 - 0', 'fox 1:00 pm', '69856'], ['15', 'december 19 , 2004', 'indianapolis colts', 'l 20 - 10', '8 - 6 - 0', 'espn 8:30 pm', '57240'], ['16', 'december 26 , 2004', 'pittsburgh steelers', 'l 20 - 7', '8 - 7 - 0', 'cbs 1:00 pm', '64227'], ['17', 'january 2 , 2005', 'miami dolphins', 'w 30 - 23', '9 - 7 - 0', 'cbs 1:00 pm', '69843']] |
2008 - 09 toronto raptors season | https://en.wikipedia.org/wiki/2008%E2%80%9309_Toronto_Raptors_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-17323092-7.html.csv | unique | in february of the 2008 - 09 toronto raptors season , their game against new orleans was the only one in which jermaine o'neal was the highest point scorer . | {'scope': 'all', 'row': '4', 'col': '5', 'col_other': '3', 'criterion': 'fuzzily_match', 'value': "jermaine o'neal", 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'high points', "jermaine o'neal"], 'result': None, 'ind': 0, 'tointer': "select the rows whose high points record fuzzily matches to jermaine o'neal .", 'tostr': "filter_eq { all_rows ; high points ; jermaine o'neal }"}], 'result': True, 'ind': 1, 'tostr': "only { filter_eq { all_rows ; high points ; jermaine o'neal } }", 'tointer': "select the rows whose high points record fuzzily matches to jermaine o'neal . there is only one such row in the table ."}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'high points', "jermaine o'neal"], 'result': None, 'ind': 0, 'tointer': "select the rows whose high points record fuzzily matches to jermaine o'neal .", 'tostr': "filter_eq { all_rows ; high points ; jermaine o'neal }"}, 'team'], 'result': 'new orleans', 'ind': 2, 'tostr': "hop { filter_eq { all_rows ; high points ; jermaine o'neal } ; team }"}, 'new orleans'], 'result': True, 'ind': 3, 'tostr': "eq { hop { filter_eq { all_rows ; high points ; jermaine o'neal } ; team } ; new orleans }", 'tointer': 'the team record of this unqiue row is new orleans .'}], 'result': True, 'ind': 4, 'tostr': "and { only { filter_eq { all_rows ; high points ; jermaine o'neal } } ; eq { hop { filter_eq { all_rows ; high points ; jermaine o'neal } ; team } ; new orleans } } = true", 'tointer': "select the rows whose high points record fuzzily matches to jermaine o'neal . there is only one such row in the table . the team record of this unqiue row is new orleans ."} | and { only { filter_eq { all_rows ; high points ; jermaine o'neal } } ; eq { hop { filter_eq { all_rows ; high points ; jermaine o'neal } ; team } ; new orleans } } = true | select the rows whose high points record fuzzily matches to jermaine o'neal . there is only one such row in the table . the team record of this unqiue row is new orleans . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'high points_7': 7, "jermaine o'neal_8": 8, 'str_eq_3': 3, 'str_hop_2': 2, 'team_9': 9, 'new orleans_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'high points_7': 'high points', "jermaine o'neal_8": "jermaine o'neal", 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'team_9': 'team', 'new orleans_10': 'new orleans'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'high points_7': [0], "jermaine o'neal_8": [0], 'str_eq_3': [4], 'str_hop_2': [3], 'team_9': [2], 'new orleans_10': [3]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record'] | [['49', 'february 1', 'orlando', 'l 90 - 113 ( ot )', 'josé calderón ( 16 )', 'joey graham ( 12 )', 'josé calderón , will solomon ( 5 )', 'air canada centre 19800', '19 - 30'], ['50', 'february 3', 'cleveland', 'l 83 - 101 ( ot )', 'chris bosh ( 29 )', 'andrea bargnani ( 10 )', 'anthony parker ( 8 )', 'quicken loans arena 20562', '19 - 31'], ['51', 'february 4', 'la lakers', 'l 107 - 115 ( ot )', 'joey graham ( 24 )', "andrea bargnani , jermaine o'neal ( 9 )", 'anthony parker ( 9 )', 'air canada centre 19800', '19 - 32'], ['52', 'february 6', 'new orleans', 'l 92 - 101 ( ot )', "jermaine o'neal ( 24 )", 'jamario moon ( 7 )', 'josé calderón ( 9 )', 'new orleans arena 17319', '19 - 33'], ['53', 'february 7', 'memphis', 'l 70 - 78 ( ot )', 'josé calderón ( 18 )', 'andrea bargnani , jamario moon ( 9 )', 'josé calderón ( 5 )', 'fedexforum 11498', '19 - 34'], ['54', 'february 10', 'minnesota', 'w 110 - 102 ( ot )', 'joey graham ( 24 )', 'jamario moon ( 9 )', 'josé calderón ( 9 )', 'target center 12722', '20 - 34'], ['55', 'february 11', 'san antonio', 'w 91 - 89 ( ot )', 'andrea bargnani ( 23 )', "jermaine o'neal ( 10 )", 'anthony parker ( 4 )', 'air canada centre 18909', '21 - 34'], ['56', 'february 18', 'cleveland', 'l 76 - 93 ( ot )', 'joey graham ( 15 )', 'anthony parker ( 7 )', 'shawn marion ( 6 )', 'air canada centre 19800', '21 - 35'], ['57', 'february 20', 'new york', 'l 97 - 127 ( ot )', 'joey graham ( 19 )', 'shawn marion ( 12 )', 'josé calderón ( 10 )', 'madison square garden 19763', '21 - 36'], ['58', 'february 22', 'new york', 'w 111 - 100 ( ot )', 'andrea bargnani ( 28 )', 'shawn marion ( 15 )', 'josé calderón ( 11 )', 'air canada centre 19800', '22 - 36'], ['59', 'february 24', 'minnesota', 'w 118 - 110 ( ot )', 'andrea bargnani , chris bosh ( 26 )', 'shawn marion ( 8 )', 'josé calderón ( 13 )', 'air canada centre 17457', '23 - 36']] |
2009 grand prix motorcycle racing season | https://en.wikipedia.org/wiki/2009_Grand_Prix_motorcycle_racing_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-15299235-1.html.csv | unique | the only race andrea dovizioso won in the 2009 season was in round 10 . | {'scope': 'all', 'row': '10', 'col': '7', 'col_other': '1', 'criterion': 'equal', 'value': 'andrea dovizioso', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'motogp winner', 'andrea dovizioso'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose motogp winner record fuzzily matches to andrea dovizioso .', 'tostr': 'filter_eq { all_rows ; motogp winner ; andrea dovizioso }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; motogp winner ; andrea dovizioso } }', 'tointer': 'select the rows whose motogp winner record fuzzily matches to andrea dovizioso . there is only one such row in the table .'}, {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'motogp winner', 'andrea dovizioso'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose motogp winner record fuzzily matches to andrea dovizioso .', 'tostr': 'filter_eq { all_rows ; motogp winner ; andrea dovizioso }'}, 'round'], 'result': '10', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; motogp winner ; andrea dovizioso } ; round }'}, '10'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; motogp winner ; andrea dovizioso } ; round } ; 10 }', 'tointer': 'the round record of this unqiue row is 10 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; motogp winner ; andrea dovizioso } } ; eq { hop { filter_eq { all_rows ; motogp winner ; andrea dovizioso } ; round } ; 10 } } = true', 'tointer': 'select the rows whose motogp winner record fuzzily matches to andrea dovizioso . there is only one such row in the table . the round record of this unqiue row is 10 .'} | and { only { filter_eq { all_rows ; motogp winner ; andrea dovizioso } } ; eq { hop { filter_eq { all_rows ; motogp winner ; andrea dovizioso } ; round } ; 10 } } = true | select the rows whose motogp winner record fuzzily matches to andrea dovizioso . there is only one such row in the table . the round record of this unqiue row is 10 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'motogp winner_7': 7, 'andrea dovizioso_8': 8, 'eq_3': 3, 'num_hop_2': 2, 'round_9': 9, '10_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'motogp winner_7': 'motogp winner', 'andrea dovizioso_8': 'andrea dovizioso', 'eq_3': 'eq', 'num_hop_2': 'num_hop', 'round_9': 'round', '10_10': '10'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'motogp winner_7': [0], 'andrea dovizioso_8': [0], 'eq_3': [4], 'num_hop_2': [3], 'round_9': [2], '10_10': [3]} | ['round', 'date', 'grand prix', 'circuit', '125cc winner', '250cc winner', 'motogp winner', 'report'] | [['1', '12 - 13 april', 'qatar grand prix', 'losail', 'andrea iannone', 'héctor barberá', 'casey stoner', 'report'], ['2', '26 april', 'japanese grand prix', 'motegi', 'andrea iannone', 'álvaro bautista', 'jorge lorenzo', 'report'], ['3', '3 may', 'spanish grand prix', 'jerez', 'bradley smith', 'hiroshi aoyama', 'valentino rossi', 'report'], ['4', '17 may', 'french grand prix', 'le mans', 'julián simón', 'marco simoncelli', 'jorge lorenzo', 'report'], ['5', '31 may', 'italian grand prix', 'mugello', 'bradley smith', 'mattia pasini', 'casey stoner', 'report'], ['6', '14 june', 'catalan grand prix', 'catalunya', 'andrea iannone', 'álvaro bautista', 'valentino rossi', 'report'], ['7', '27 june', 'dutch tt', 'assen', 'sergio gadea', 'hiroshi aoyama', 'valentino rossi', 'report'], ['8', '5 july', 'united states grand prix', 'laguna seca', 'no 125cc and 250cc race', 'no 125cc and 250cc race', 'dani pedrosa', 'report'], ['9', '19 july', 'german grand prix', 'sachsenring', 'julián simón', 'marco simoncelli', 'valentino rossi', 'report'], ['10', '26 july', 'british grand prix', 'donington', 'julián simón', 'hiroshi aoyama', 'andrea dovizioso', 'report'], ['11', '16 august', 'czech republic grand prix', 'brno', 'nicolás terol', 'marco simoncelli', 'valentino rossi', 'report'], ['12', '30 august', 'indianapolis grand prix', 'indianapolis', 'pol espargaró', 'marco simoncelli', 'jorge lorenzo', 'report'], ['13', '6 september', 'san marino grand prix', 'misano', 'julián simón', 'héctor barberá', 'valentino rossi', 'report'], ['14', '4 october', 'portuguese grand prix', 'estoril', 'pol espargaró', 'marco simoncelli', 'jorge lorenzo', 'report'], ['15', '18 october', 'australian grand prix', 'phillip island', 'julián simón', 'marco simoncelli', 'casey stoner', 'report'], ['16', '25 october', 'malaysian grand prix', 'sepang', 'julián simón', 'hiroshi aoyama', 'casey stoner', 'report']] |
1990 - 91 segunda división | https://en.wikipedia.org/wiki/1990%E2%80%9391_Segunda_Divisi%C3%B3n | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12103836-2.html.csv | ordinal | in the 1990-91 segunda división , the real murica club had the third highest goal difference . | {'row': '3', 'col': '10', 'order': '3', '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', 'goal difference', '3'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; goal difference ; 3 }'}, 'club'], 'result': 'real murcia', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; goal difference ; 3 } ; club }'}, 'real murcia'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; goal difference ; 3 } ; club } ; real murcia } = true', 'tointer': 'select the row whose goal difference record of all rows is 3rd maximum . the club record of this row is real murcia .'} | eq { hop { nth_argmax { all_rows ; goal difference ; 3 } ; club } ; real murcia } = true | select the row whose goal difference record of all rows is 3rd maximum . the club record of this row is real murcia . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'goal difference_5': 5, '3_6': 6, 'club_7': 7, 'real murcia_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', 'goal difference_5': 'goal difference', '3_6': '3', 'club_7': 'club', 'real murcia_8': 'real murcia'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'goal difference_5': [0], '3_6': [0], 'club_7': [1], 'real murcia_8': [2]} | ['position', 'club', 'played', 'points', 'wins', 'draws', 'losses', 'goals for', 'goals against', 'goal difference'] | [['1', 'albacete bp', '38', '49 + 11', '18', '13', '7', '56', '31', '+ 25'], ['2', 'deportivo de la coruña', '38', '48 + 10', '20', '8', '10', '60', '32', '+ 28'], ['3', 'real murcia', '38', '48 + 10', '18', '12', '8', '56', '36', '+ 20'], ['4', 'cd málaga', '38', '46 + 8', '16', '14', '8', '52', '35', '+ 17'], ['5', 'orihuela deportiva 1', '38', '43 + 5', '12', '19', '7', '46', '39', '+ 7'], ['6', 'ue lleida', '38', '43 + 5', '16', '11', '11', '41', '36', '+ 5'], ['7', 'ue figueres', '38', '39 + 1', '14', '11', '13', '44', '42', '+ 2'], ['8', 'sestao', '38', '38', '9', '20', '9', '29', '27', '+ 2'], ['9', 'real avilés', '38', '38', '10', '18', '10', '35', '37', '- 2'], ['10', 'sd eibar', '38', '37 - 1', '9', '19', '10', '35', '34', '+ 1'], ['11', 'rayo vallecano', '38', '36 - 2', '8', '20', '10', '44', '50', '- 6'], ['12', 'ce sabadell fc', '38', '36 - 2', '11', '14', '13', '32', '45', '- 13'], ['13', 'bilbao athletic', '38', '36 - 2', '11', '14', '13', '35', '43', '- 8'], ['14', 'celta de vigo', '38', '36 - 2', '8', '20', '10', '31', '38', '- 7'], ['15', 'ud las palmas', '38', '36 - 2', '10', '16', '12', '38', '43', '- 5'], ['16', 'palamós cf', '38', '35 - 3', '9', '17', '12', '33', '46', '- 13'], ['17', 'elche cf', '38', '34 - 4', '12', '10', '16', '39', '45', '- 9'], ['18', 'ud salamanca', '38', '31 - 7', '9', '13', '16', '41', '40', '+ 1'], ['19', 'levante ud', '38', '27 - 11', '6', '15', '17', '27', '51', '- 24'], ['20', 'xerez cd', '38', '24 - 14', '6', '12', '20', '37', '61', '- 24']] |
wayne gardner | https://en.wikipedia.org/wiki/Wayne_Gardner | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1861430-3.html.csv | aggregation | wayne gardner 's total number of wins from the years 1983-1992 is 18 . | {'scope': 'all', 'col': '6', 'type': 'sum', 'result': '18', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'wins'], 'result': '18', 'ind': 0, 'tostr': 'sum { all_rows ; wins }'}, '18'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; wins } ; 18 } = true', 'tointer': 'the sum of the wins record of all rows is 18 .'} | round_eq { sum { all_rows ; wins } ; 18 } = true | the sum of the wins record of all rows is 18 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'wins_4': 4, '18_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'wins_4': 'wins', '18_5': '18'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'wins_4': [0], '18_5': [1]} | ['year', 'class', 'team', 'machine', 'points', 'wins'] | [['1983', '500cc', 'honda britain', 'ns500', '0', '0'], ['1984', '500cc', 'honda britain', 'ns500', '33', '0'], ['1985', '500cc', 'rothmans honda', 'nsr500', '73', '0'], ['1986', '500cc', 'rothmans honda', 'nsr500', '117', '3'], ['1987', '500cc', 'rothmans honda', 'nsr500', '178', '7'], ['1988', '500cc', 'rothmans honda', 'nsr500', '229', '4'], ['1989', '500cc', 'rothmans honda', 'nsr500', '67', '1'], ['1990', '500cc', 'rothmans honda', 'nsr500', '138', '2'], ['1991', '500cc', 'rothmans honda', 'nsr500', '161', '0'], ['1992', '500cc', 'rothmans honda', 'nsr500', '78', '1']] |
chung kyung - ho | https://en.wikipedia.org/wiki/Chung_Kyung-Ho | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1385043-2.html.csv | count | chung kyung - ho competed three times in the 2004 afc asian cup qualification . | {'scope': 'all', 'criterion': 'equal', 'value': '2004 afc asian cup qualification', 'result': '3', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'competition', '2004 afc asian cup qualification'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose competition record fuzzily matches to 2004 afc asian cup qualification .', 'tostr': 'filter_eq { all_rows ; competition ; 2004 afc asian cup qualification }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; competition ; 2004 afc asian cup qualification } }', 'tointer': 'select the rows whose competition record fuzzily matches to 2004 afc asian cup qualification . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; competition ; 2004 afc asian cup qualification } } ; 3 } = true', 'tointer': 'select the rows whose competition record fuzzily matches to 2004 afc asian cup qualification . the number of such rows is 3 .'} | eq { count { filter_eq { all_rows ; competition ; 2004 afc asian cup qualification } } ; 3 } = true | select the rows whose competition record fuzzily matches to 2004 afc asian cup qualification . 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, 'competition_5': 5, '2004 afc asian cup qualification_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', 'competition_5': 'competition', '2004 afc asian cup qualification_6': '2004 afc asian cup qualification', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'competition_5': [0], '2004 afc asian cup qualification_6': [0], '3_7': [2]} | ['date', 'venue', 'score', 'result', 'competition'] | [['september 29 , 2003', 'incheon', '1 goal', '16 - 0', '2004 afc asian cup qualification'], ['october 21 , 2003', 'muscat', '1 goal', '1 - 3', '2004 afc asian cup qualification'], ['october 24 , 2003', 'muscat', '1 goal', '7 - 0', '2004 afc asian cup qualification'], ['january 15 , 2005', 'los angeles', '1 goal', '1 - 2', 'friendly match'], ['january 22 , 2005', 'carson', '1 goal', '1 - 1', 'friendly match'], ['june 8 , 2005', 'kuwait city', '1 goal', '4 - 0', '2006 fifa world cup qualification']] |
salyut 7 | https://en.wikipedia.org/wiki/Salyut_7 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-245801-1.html.csv | superlative | the expedition with the highest duration of days is salyut 7 - eo - 3 . | {'scope': 'all', 'col_superlative': '7', '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', 'duration ( days )'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; duration ( days ) }'}, 'expedition'], 'result': 'salyut 7 - eo - 3', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; duration ( days ) } ; expedition }'}, 'salyut 7 - eo - 3'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; duration ( days ) } ; expedition } ; salyut 7 - eo - 3 } = true', 'tointer': 'select the row whose duration ( days ) record of all rows is maximum . the expedition record of this row is salyut 7 - eo - 3 .'} | eq { hop { argmax { all_rows ; duration ( days ) } ; expedition } ; salyut 7 - eo - 3 } = true | select the row whose duration ( days ) record of all rows is maximum . the expedition record of this row is salyut 7 - eo - 3 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'duration (days)_5': 5, 'expedition_6': 6, 'salyut 7 - eo - 3_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'duration (days)_5': 'duration ( days )', 'expedition_6': 'expedition', 'salyut 7 - eo - 3_7': 'salyut 7 - eo - 3'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'duration (days)_5': [0], 'expedition_6': [1], 'salyut 7 - eo - 3_7': [2]} | ['expedition', 'crew', 'launch date', 'flight up', 'landing date', 'flight down', 'duration ( days )'] | [['salyut 7 - eo - 1', 'anatoli berezovoy , valentin lebedev', '13 may 1982 09:58:05 utc', 'soyuz t - 5', '10 december 1982 19:02:36 utc', 'soyuz t - 7', '211.38'], ['salyut 7 - eo - 2', 'vladimir lyakhov , aleksandr pavlovich aleksandrov', '27 june 1983 09:12:00 utc', 'soyuz t - 9', '23 november 1983 19:58:00 utc', 'soyuz t - 9', '149.45'], ['salyut 7 - eo - 3', 'leonid kizim , vladimir solovyov , oleg atkov', '8 february 1984 12:07:26 utc', 'soyuz t - 10', '2 october 1984 10:57:00 utc', 'soyuz t - 11', '236.95'], ['salyut 7 - eo - 4 - 1a', 'viktor savinykh', '6 june 1985 06:39:52 utc', 'soyuz t - 13', '21 november 1985 10:31:00 utc', 'soyuz t - 14', '168.16'], ['salyut 7 - eo - 4 - 1b', 'vladimir dzhanibekov', '6 june 1985 06:39:52 utc', 'soyuz t - 13', '26 september 1985 09:51:58 utc', 'soyuz t - 13', '112.13'], ['salyut 7 - ep - 5', 'georgi grechko', '17 september 1985 12:38:52 utc', 'soyuz t - 14', '26 september 1985 09:51:58 utc', 'soyuz t - 13', '8.88'], ['salyut 7 - eo - 4 - 2', 'vladimir vasyutin , alexander volkov', '17 september 1985 12:38:52 utc', 'soyuz t - 14', '21 november 1985 10:31:00 utc', 'soyuz t - 14', '64.91']] |
list of world records in canoeing | https://en.wikipedia.org/wiki/List_of_world_records_in_canoeing | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14884844-1.html.csv | count | german nationals hold a total of two world records in canoeing . | {'scope': 'all', 'criterion': 'equal', 'value': 'germany', 'result': '2', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'nationality', 'germany'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose nationality record fuzzily matches to germany .', 'tostr': 'filter_eq { all_rows ; nationality ; germany }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; nationality ; germany } }', 'tointer': 'select the rows whose nationality record fuzzily matches to germany . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; nationality ; germany } } ; 2 } = true', 'tointer': 'select the rows whose nationality record fuzzily matches to germany . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; nationality ; germany } } ; 2 } = true | select the rows whose nationality record fuzzily matches to germany . the number of such rows is 2 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'nationality_5': 5, 'germany_6': 6, '2_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'nationality_5': 'nationality', 'germany_6': 'germany', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'nationality_5': [0], 'germany_6': [0], '2_7': [2]} | ['distance', 'event', 'record', 'nationality', 'year', 'location'] | [['200 m', 'k1', '33.8 s', 'canada', '2012', 'montreal , canada'], ['200 m', 'k2', '30.962 s', 'russia', '2012', 'duisburg , germany'], ['200 m', 'k4', '29.023 s', 'hungary', '1997', 'plovdiv , bulgaria'], ['500 m', 'k1', '1:35.554 s', 'canada', '2008', 'beijing , china'], ['500 m', 'k2', '1:26.873 s', 'belarus', '2008', 'poznan , poland'], ['500 m', 'k4', '1:19.650 s', 'slovakia', '2002', 'szeged , hungary'], ['1000 m', 'k1', '3:22.485 s', 'germany', '2011', 'belgrade , serbia'], ['1000 m', 'k2', '3:09.190 s', 'italy', '1996', 'atlanta , usa'], ['1000 m', 'k4', '2:47.734 s', 'germany', '2011', 'szeged , hungary']] |
edmonton radial railway society | https://en.wikipedia.org/wiki/Edmonton_Radial_Railway_Society | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-22481967-1.html.csv | majority | the majority of models in the edmonton radial railway society are of the streetcar type . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'streetcar', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'type', 'streetcar'], 'result': True, 'ind': 0, 'tointer': 'for the type records of all rows , most of them fuzzily match to streetcar .', 'tostr': 'most_eq { all_rows ; type ; streetcar } = true'} | most_eq { all_rows ; type ; streetcar } = true | for the type records of all rows , most of them fuzzily match to streetcar . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'type_3': 3, 'streetcar_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'type_3': 'type', 'streetcar_4': 'streetcar'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'type_3': [0], 'streetcar_4': [0]} | ['date', 'builder', 'type', 'operator', 'number', 'withdrawn', 'status'] | [['1907', 'occ', 'combination sweeper / overhead line car', 'saskatoon municipal railway', '200', '1951', 'stored'], ['1908', 'occ', 'streetcar', 'edmonton radial railway', '1', '1951', 'display only'], ['1912', 'stl', 'streetcar', 'edmonton radial railway', '33', '1951', 'stored'], ['1912', 'stl', 'streetcar', 'edmonton radial railway', '42', '1951', 'fort edmonton park line'], ['1914', 'preston', 'streetcar', 'toronto suburban railway', '24 , ( later cnr 15702 )', '1960s', 'fort edmonton park line'], ['1921', 'u / s', 'tram', 'nankai electric railway ( osaka , japan )', '247', '1990', 'high level bridge line'], ['ca 1920s', 'cc & f', 'streetcar', 'regina municipal railway', '42', '1950', 'closed to viewing'], ['1930', 'occ', 'streetcar', 'edmonton radial railway', '80', '1951', 'fort edmonton park line'], ['1947', 'ptc', 'w6 class tram', 'melbourne and metropolitan tramways board', '930', '1997', 'high level bridge line'], ['1951', 'cc & f', 'pcc streetcar', 'toronto transit commission', '4612', '1995', 'fort edmonton park line']] |
united states house of representatives elections , 1926 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1926 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1342379-41.html.csv | ordinal | finis j. garrett was the first person in the house of representatives in 1926 to have served a term . | {'row': '8', 'col': '4', 'order': '1', 'col_other': '2', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'first elected', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; first elected ; 1 }'}, 'incumbent'], 'result': 'finis j garrett', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; first elected ; 1 } ; incumbent }'}, 'finis j garrett'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; first elected ; 1 } ; incumbent } ; finis j garrett } = true', 'tointer': 'select the row whose first elected record of all rows is 1st minimum . the incumbent record of this row is finis j garrett .'} | eq { hop { nth_argmin { all_rows ; first elected ; 1 } ; incumbent } ; finis j garrett } = true | select the row whose first elected record of all rows is 1st minimum . the incumbent record of this row is finis j garrett . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'first elected_5': 5, '1_6': 6, 'incumbent_7': 7, 'finis j garrett_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmin_0': 'nth_argmin', 'all_rows_4': 'all_rows', 'first elected_5': 'first elected', '1_6': '1', 'incumbent_7': 'incumbent', 'finis j garrett_8': 'finis j garrett'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'first elected_5': [0], '1_6': [0], 'incumbent_7': [1], 'finis j garrett_8': [2]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['tennessee 1', 'b carroll reece', 'republican', '1920', 're - elected', 'b carroll reece ( r ) 88.0 % w i giles ( d ) 12.0 %'], ['tennessee 2', 'j will taylor', 'republican', '1918', 're - elected', 'j will taylor ( r ) 99.8 % r l swann ( d ) 0.2 %'], ['tennessee 4', 'cordell hull', 'democratic', '1922', 're - elected', 'cordell hull ( d ) 71.4 % w thompson ( r ) 28.6 %'], ['tennessee 5', 'ewin l davis', 'democratic', '1918', 're - elected', 'ewin l davis ( d ) unopposed'], ['tennessee 6', 'joseph w byrns , sr', 'democratic', '1908', 're - elected', 'joseph w byrns , sr ( d ) unopposed'], ['tennessee 7', 'edward everett eslick', 'democratic', '1924', 're - elected', 'edward everett eslick ( d ) unopposed'], ['tennessee 8', 'gordon browning', 'democratic', '1922', 're - elected', 'gordon browning ( d ) unopposed'], ['tennessee 9', 'finis j garrett', 'democratic', '1904', 're - elected', 'finis j garrett ( d ) unopposed']] |
1984 - 85 fa cup | https://en.wikipedia.org/wiki/1984%E2%80%9385_FA_Cup | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17438338-4.html.csv | count | there were a total of two replays in the 1984 - 85 fa cup . | {'scope': 'all', 'criterion': 'equal', 'value': 'replay', 'result': '2', 'col': '1', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'tie no', 'replay'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose tie no record fuzzily matches to replay .', 'tostr': 'filter_eq { all_rows ; tie no ; replay }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; tie no ; replay } }', 'tointer': 'select the rows whose tie no record fuzzily matches to replay . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; tie no ; replay } } ; 2 } = true', 'tointer': 'select the rows whose tie no record fuzzily matches to replay . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; tie no ; replay } } ; 2 } = true | select the rows whose tie no record fuzzily matches to replay . 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, 'tie no_5': 5, 'replay_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', 'tie no_5': 'tie no', 'replay_6': 'replay', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'tie no_5': [0], 'replay_6': [0], '2_7': [2]} | ['tie no', 'home team', 'score', 'away team', 'date'] | [['1', 'darlington', '1 - 1', 'telford united', '29 january 1985'], ['replay', 'telford united', '3 - 0', 'darlington', '4 february 1985'], ['2', 'liverpool', '1 - 0', 'tottenham hotspur', '27 january 1985'], ['3', 'leicester city', '1 - 0', 'carlisle united', '26 january 1985'], ['4', 'nottingham forest', '0 - 0', 'wimbledon', '26 january 1985'], ['replay', 'wimbledon', '1 - 0', 'nottingham forest', '30 january 1985'], ['5', 'sheffield wednesday', '5 - 1', 'oldham athletic', '26 january 1985'], ['6', 'grimsby town', '1 - 3', 'watford', '26 january 1985'], ['7', 'luton town', '2 - 0', 'huddersfield town', '26 january 1985'], ['8', 'everton', '2 - 0', 'doncaster rovers', '26 january 1985'], ['9', 'ipswich town', '3 - 2', 'gillingham', '26 january 1985'], ['10', 'barnsley', '2 - 1', 'brighton & hove albion', '26 january 1985'], ['11', 'west ham united', '2 - 1', 'norwich city', '4 february 1985'], ['12', 'manchester united', '2 - 1', 'coventry city', '26 january 1985'], ['13', 'chelsea', '2 - 3', 'millwall', '4 february 1985'], ['14', 'york city', '1 - 0', 'arsenal', '26 january 1985'], ['15', 'oxford united', '0 - 1', 'blackburn rovers', '30 january 1985'], ['16', 'orient', '0 - 2', 'southampton', '26 january 1985']] |
2008 - 09 football league two | https://en.wikipedia.org/wiki/2008%E2%80%9309_Football_League_Two | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-18795125-6.html.csv | unique | lee sinnott is the only manager who left due to mutual consent . | {'scope': 'all', 'row': '3', 'col': '3', 'col_other': '2', 'criterion': 'equal', 'value': 'mutual consent', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'manner of departure', 'mutual consent'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose manner of departure record fuzzily matches to mutual consent .', 'tostr': 'filter_eq { all_rows ; manner of departure ; mutual consent }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; manner of departure ; mutual consent } }', 'tointer': 'select the rows whose manner of departure record fuzzily matches to mutual consent . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'manner of departure', 'mutual consent'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose manner of departure record fuzzily matches to mutual consent .', 'tostr': 'filter_eq { all_rows ; manner of departure ; mutual consent }'}, 'outgoing manager'], 'result': 'lee sinnott', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; manner of departure ; mutual consent } ; outgoing manager }'}, 'lee sinnott'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; manner of departure ; mutual consent } ; outgoing manager } ; lee sinnott }', 'tointer': 'the outgoing manager record of this unqiue row is lee sinnott .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; manner of departure ; mutual consent } } ; eq { hop { filter_eq { all_rows ; manner of departure ; mutual consent } ; outgoing manager } ; lee sinnott } } = true', 'tointer': 'select the rows whose manner of departure record fuzzily matches to mutual consent . there is only one such row in the table . the outgoing manager record of this unqiue row is lee sinnott .'} | and { only { filter_eq { all_rows ; manner of departure ; mutual consent } } ; eq { hop { filter_eq { all_rows ; manner of departure ; mutual consent } ; outgoing manager } ; lee sinnott } } = true | select the rows whose manner of departure record fuzzily matches to mutual consent . there is only one such row in the table . the outgoing manager record of this unqiue row is lee sinnott . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'manner of departure_7': 7, 'mutual consent_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'outgoing manager_9': 9, 'lee sinnott_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'manner of departure_7': 'manner of departure', 'mutual consent_8': 'mutual consent', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'outgoing manager_9': 'outgoing manager', 'lee sinnott_10': 'lee sinnott'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'manner of departure_7': [0], 'mutual consent_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'outgoing manager_9': [2], 'lee sinnott_10': [3]} | ['team', 'outgoing manager', 'manner of departure', 'date of vacancy', 'replaced by', 'date of appointment', 'position in table'] | [['bournemouth', 'kevin bond', 'contract terminated', '1 september 2008', 'jimmy quinn', '2 september 2008', '23rd'], ['grimsby town', 'alan buckley', 'contract terminated', '15 september 2008', 'mike newell', '6 october 2008', '20th'], ['port vale', 'lee sinnott', 'mutual consent', '22 september 2008', 'dean glover', '6 october 2008', '16th'], ['chester city', 'simon davies', 'contract terminated', '11 november 2008', 'mark wright', '14 november 2008', '19th'], ['barnet', 'paul fairclough', 'resigned', '28 december 2008', 'ian hendon', '21 april 2009', '16th']] |
1991 - 92 seattle supersonics season | https://en.wikipedia.org/wiki/1991%E2%80%9392_Seattle_SuperSonics_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27902171-5.html.csv | majority | all games of 1991 - 92 seattle supersonics season was scheduled for december . | {'scope': 'all', 'col': '2', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'december', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'date', 'december'], 'result': True, 'ind': 0, 'tointer': 'for the date records of all rows , all of them fuzzily match to december .', 'tostr': 'all_eq { all_rows ; date ; december } = true'} | all_eq { all_rows ; date ; december } = true | for the date records of all rows , all of them fuzzily match to december . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'date_3': 3, 'december_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'date_3': 'date', 'december_4': 'december'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'date_3': [0], 'december_4': [0]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record'] | [['16', 'december 3', 'washington bullets', 'w 91 - 90', 'r pierce ( 26 )', 's kemp ( 12 )', 'g payton ( 5 )', 'seattle center coliseum 10957', '9 - 7'], ['17', 'december 6', 'minnesota timberwolves', 'w 96 - 94', 'r pierce ( 29 )', 'm cage ( 23 )', 'g payton , r pierce ( 5 )', 'seattle center coliseum 9796', '10 - 7'], ['18', 'december 7', 'dallas mavericks', 'w 104 - 101', 'r pierce ( 27 )', 'm cage ( 14 )', 'n mcmillan ( 6 )', 'seattle center coliseum 12313', '11 - 7'], ['19', 'december 10', 'chicago bulls', 'l 103 - 108', 'r pierce ( 30 )', 'm cage ( 13 )', 's kemp , g payton ( 5 )', 'chicago stadium 18061', '11 - 8'], ['20', 'december 11', 'new york knicks', 'l 87 - 96', 'r pierce ( 25 )', 'b benjamin , s kemp ( 9 )', 'r pierce ( 7 )', 'madison square garden 14934', '11 - 9'], ['21', 'december 13', 'boston celtics', 'l 97 - 117', 'r pierce ( 21 )', 'b benjamin ( 8 )', 'n mcmillan ( 8 )', 'boston garden 14890', '11 - 10'], ['22', 'december 14', 'philadelphia 76ers', 'l 95 - 104', 'b benjamin ( 23 )', 'b benjamin ( 9 )', 'n mcmillan ( 8 )', 'the spectrum 12395', '11 - 11'], ['23', 'december 17', 'los angeles clippers', 'w 116 - 99', 'b benjamin ( 20 )', 'm cage ( 13 )', 'n mcmillan ( 6 )', 'seattle center coliseum 10357', '12 - 11'], ['24', 'december 19', 'denver nuggets', 'w 119 - 106', 'r pierce ( 29 )', 'm cage ( 15 )', 'd mckey , n mcmillan , g payton ( 4 )', 'seattle center coliseum 10663', '13 - 11'], ['25', 'december 21', 'golden state warriors', 'w 120 - 112', 'r pierce ( 34 )', 'g payton ( 11 )', 'g payton ( 12 )', 'seattle center coliseum 14180', '14 - 11'], ['26', 'december 22', 'portland trail blazers', 'l 87 - 96', 'b benjamin ( 18 )', 'm cage ( 9 )', 'b kofoed , g payton ( 5 )', 'memorial coliseum 12888', '14 - 12'], ['27', 'december 26', 'sacramento kings', 'w 115 - 106 ( ot )', 'r pierce ( 27 )', 'b benjamin ( 13 )', 'g payton ( 5 )', 'arco arena 17014', '15 - 12']] |
2005 open championship | https://en.wikipedia.org/wiki/2005_Open_Championship | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16225902-7.html.csv | count | six of the players earned 122100 dollars in money . | {'scope': 'all', 'criterion': 'equal', 'value': '122100', 'result': '6', 'col': '6', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'money', '122100'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose money record is equal to 122100 .', 'tostr': 'filter_eq { all_rows ; money ; 122100 }'}], 'result': '6', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; money ; 122100 } }', 'tointer': 'select the rows whose money record is equal to 122100 . the number of such rows is 6 .'}, '6'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; money ; 122100 } } ; 6 } = true', 'tointer': 'select the rows whose money record is equal to 122100 . the number of such rows is 6 .'} | eq { count { filter_eq { all_rows ; money ; 122100 } } ; 6 } = true | select the rows whose money record is equal to 122100 . the number of such rows is 6 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_eq_0': 0, 'all_rows_4': 4, 'money_5': 5, '122100_6': 6, '6_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'money_5': 'money', '122100_6': '122100', '6_7': '6'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'money_5': [0], '122100_6': [0], '6_7': [2]} | ['place', 'player', 'country', 'score', 'to par', 'money'] | [['1', 'tiger woods', 'united states', '66 + 67 + 71 + 70 = 274', '14', '720000'], ['2', 'colin montgomerie', 'scotland', '71 + 66 + 70 + 72 = 279', '9', '430000'], ['t3', 'fred couples', 'united states', '68 + 71 + 73 + 68 = 280', '8', '242350'], ['t3', 'josé maría olazábal', 'spain', '68 + 70 + 68 + 74 = 280', '8', '242350'], ['t5', 'michael campbell', 'new zealand', '69 + 72 + 68 + 72 = 281', '7', '122100'], ['t5', 'sergio garcía', 'spain', '70 + 69 + 69 + 73 = 281', '7', '122100'], ['t5', 'retief goosen', 'south africa', '68 + 73 + 66 + 74 = 281', '7', '122100'], ['t5', 'bernhard langer', 'germany', '71 + 69 + 70 + 71 = 281', '7', '122100'], ['t5', 'geoff ogilvy', 'australia', '71 + 74 + 67 + 69 = 281', '7', '122100'], ['t5', 'vijay singh', 'fiji', '69 + 69 + 71 + 72 = 281', '7', '122100']] |
weightlifting at the 1999 pan american games | https://en.wikipedia.org/wiki/Weightlifting_at_the_1999_Pan_American_Games | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11279593-14.html.csv | majority | at the 1999 pan american games , most of the people had a bodyweight of at least 70 . | {'scope': 'all', 'col': '2', 'most_or_all': 'most', 'criterion': 'greater_than_eq', 'value': '70', 'subset': None} | {'func': 'most_greater_eq', 'args': ['all_rows', 'bodyweight', '70'], 'result': True, 'ind': 0, 'tointer': 'for the bodyweight records of all rows , most of them are greater than or equal to 70 .', 'tostr': 'most_greater_eq { all_rows ; bodyweight ; 70 } = true'} | most_greater_eq { all_rows ; bodyweight ; 70 } = true | for the bodyweight records of all rows , most of them are greater than or equal to 70 . | 1 | 1 | {'most_greater_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'bodyweight_3': 3, '70_4': 4} | {'most_greater_eq_0': 'most_greater_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'bodyweight_3': 'bodyweight', '70_4': '70'} | {'most_greater_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'bodyweight_3': [0], '70_4': [0]} | ['name', 'bodyweight', 'snatch', 'clean & jerk', 'total ( kg )'] | [['wanda rijo ( dom )', '73.68', '100.0', '120.0', '220.0'], ['cara heads ( usa )', '73.26', '97.5', '120.0', '217.5'], ['jean lassen ( can )', '73.73', '92.5', '117.5', '210.0'], ['theresa brick ( can )', '74.80', '95.0', '115.0', '210.0'], ['mayra martínez ( ven )', '73.60', '87.5', '112.5', '200.0'], ['maría ruiz obando ( nca )', '73.28', '75.0', '107.5', '182.5'], ['nelly rivera ( dom )', '69.73', '70.0', '82.5', '152.5']] |
united states house of representatives elections in georgia , 1996 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections_in_Georgia%2C_1996 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27487712-1.html.csv | ordinal | in the 1996 elections for united states house of representatives in georgia , the republican candidate who received the second highest percentage of votes was mac collins . | {'row': '2', 'col': '6', 'order': '2', 'col_other': '6', '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', 'result', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; result ; 2 }'}, 'result'], 'result': 'mac collins ( r ) 61.11 % jim chafin ( d ) 38.89 %', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; result ; 2 } ; result }'}, 'mac collins ( r ) 61.11 % jim chafin ( d ) 38.89 %'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; result ; 2 } ; result } ; mac collins ( r ) 61.11 % jim chafin ( d ) 38.89 % } = true', 'tointer': 'select the row whose result record of all rows is 2nd maximum . the result record of this row is mac collins ( r ) 61.11 % jim chafin ( d ) 38.89 % .'} | eq { hop { nth_argmax { all_rows ; result ; 2 } ; result } ; mac collins ( r ) 61.11 % jim chafin ( d ) 38.89 % } = true | select the row whose result record of all rows is 2nd maximum . the result record of this row is mac collins ( r ) 61.11 % jim chafin ( d ) 38.89 % . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'result_5': 5, '2_6': 6, 'result_7': 7, 'mac collins (r) 61.11% jim chafin (d) 38.89%_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', 'result_5': 'result', '2_6': '2', 'result_7': 'result', 'mac collins (r) 61.11% jim chafin (d) 38.89%_8': 'mac collins ( r ) 61.11 % jim chafin ( d ) 38.89 %'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'result_5': [0], '2_6': [0], 'result_7': [1], 'mac collins (r) 61.11% jim chafin (d) 38.89%_8': [2]} | ['district', 'incumbent', 'party', 'elected', 'status', 'result'] | [["georgia 's 2nd", 'sanford bishop', 'democratic', '1992', 're - elected', 'sanford bishop ( d ) 53.97 % darrel ealum ( r ) 46.03 %'], ["georgia 's 3rd", 'mac collins', 'republican', '1992', 're - elected', 'mac collins ( r ) 61.11 % jim chafin ( d ) 38.89 %'], ["georgia 's 5th", 'john lewis', 'democratic', '1986', 're - elected', 'john lewis ( d ) unopposed'], ["georgia 's 6th", 'newt gingrich', 'republican', '1978', 're - elected', 'newt gingrich ( r ) 57.80 % michael coles ( d ) 42.20 %'], ["georgia 's 7th", 'bob barr', 'republican', '1994', 're - elected', 'bob barr ( r ) 57.80 % charlie watts ( d ) 42.20 %'], ["georgia 's 8th", 'saxby chambliss', 'republican', '1994', 're - elected', 'saxby chambliss ( r ) 52.56 % jim wiggins ( d ) 47.44 %'], ["georgia 's 9th", 'nathan deal', 'republican', '1992', 're - elected', 'nathan deal ( r ) 65.55 % ken poston ( d ) 34.45 %'], ["georgia 's 10th", 'charlie norwood', 'republican', '1994', 're - elected', 'charlie norwood ( r ) 52.34 % david bell ( d ) 47.65 %']] |
1989 senior pga tour | https://en.wikipedia.org/wiki/1989_Senior_PGA_Tour | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11622496-4.html.csv | count | 2 players in the 1989 senior pga tour were from the united states . | {'scope': 'all', 'criterion': 'equal', 'value': 'united states', 'result': '2', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'united states'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose country record fuzzily matches to united states .', 'tostr': 'filter_eq { all_rows ; country ; united states }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; country ; united states } }', 'tointer': 'select the rows whose country record fuzzily matches to united states . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; country ; united states } } ; 2 } = true', 'tointer': 'select the rows whose country record fuzzily matches to united states . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; country ; united states } } ; 2 } = true | select the rows whose country record fuzzily matches to united states . 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, 'country_5': 5, 'united states_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', 'country_5': 'country', 'united states_6': 'united states', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'country_5': [0], 'united states_6': [0], '2_7': [2]} | ['rank', 'player', 'country', 'earnings', 'wins'] | [['1', 'miller barber', 'united states', '2214603', '24'], ['2', 'bob charles', 'new zealand', '1910413', '13'], ['3', 'orville moody', 'united states', '1862956', '9'], ['4', 'bruce crampton', 'australia', '1682961', '15'], ['5', 'gary player', 'south africa', '1604659', '14']] |
1997 european judo championships | https://en.wikipedia.org/wiki/1997_European_Judo_Championships | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11755180-3.html.csv | superlative | france had the highest amount of total medals out of all the nations at the championship . | {'scope': 'all', 'col_superlative': '6', 'row_superlative': '5', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '2', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'total'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; total }'}, 'nation'], 'result': 'france', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; total } ; nation }'}, 'france'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; total } ; nation } ; france } = true', 'tointer': 'select the row whose total record of all rows is maximum . the nation record of this row is france .'} | eq { hop { argmax { all_rows ; total } ; nation } ; france } = true | select the row whose total record of all rows is maximum . the nation record of this row is france . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'total_5': 5, 'nation_6': 6, 'france_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'total_5': 'total', 'nation_6': 'nation', 'france_7': 'france'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'total_5': [0], 'nation_6': [1], 'france_7': [2]} | ['rank', 'nation', 'gold', 'silver', 'bronze', 'total'] | [['1', 'belgium', '6', '0', '3', '9'], ['2 =', 'germany', '2', '2', '2', '7'], ['2 =', 'netherlands', '2', '2', '2', '6'], ['4', 'turkey', '2', '0', '1', '3'], ['5', 'france', '1', '3', '6', '10'], ['6', 'belarus', '1', '2', '1', '4'], ['7', 'georgia', '1', '1', '0', '2'], ['8', 'poland', '1', '0', '4', '5'], ['9', 'great britain', '0', '2', '3', '5'], ['10', 'spain', '0', '2', '1', '3'], ['11', 'austria', '0', '1', '1', '2'], ['12', 'czech republic', '0', '1', '0', '1'], ['13', 'russia', '0', '0', '2', '2'], ['14 =', 'estonia', '0', '0', '1', '1'], ['14 =', 'italy', '0', '0', '1', '1'], ['14 =', 'lithuania', '0', '0', '1', '1'], ['14 =', 'romania', '0', '0', '1', '1'], ['14 =', 'portugal', '0', '0', '1', '1'], ['14 =', 'yugoslavia', '0', '0', '1', '1']] |
2008 in paleontology | https://en.wikipedia.org/wiki/2008_in_paleontology | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15688561-8.html.csv | majority | in 2008 in paleontology , all the ones whose location is china have valid status . | {'scope': 'subset', 'col': '2', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'valid', 'subset': {'col': '4', 'criterion': 'equal', 'value': 'china'}} | {'func': 'all_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location', 'china'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; location ; china }', 'tointer': 'select the rows whose location record fuzzily matches to china .'}, 'status', 'valid'], 'result': True, 'ind': 1, 'tointer': 'select the rows whose location record fuzzily matches to china . for the status records of these rows , all of them fuzzily match to valid .', 'tostr': 'all_eq { filter_eq { all_rows ; location ; china } ; status ; valid } = true'} | all_eq { filter_eq { all_rows ; location ; china } ; status ; valid } = true | select the rows whose location record fuzzily matches to china . for the status records of these rows , all of them fuzzily match to valid . | 2 | 2 | {'all_str_eq_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, 'location_4': 4, 'china_5': 5, 'status_6': 6, 'valid_7': 7} | {'all_str_eq_1': 'all_str_eq', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'location_4': 'location', 'china_5': 'china', 'status_6': 'status', 'valid_7': 'valid'} | {'all_str_eq_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'location_4': [0], 'china_5': [0], 'status_6': [1], 'valid_7': [1]} | ['name', 'status', 'authors', 'location', 'notes'] | [['caracara tellustris', 'valid', 'olson', 'jamaica', 'a species of caracara'], ['didactylornis', 'valid', 'yuan', 'china', 'basal n pygostylia'], ['enantiophoenix', 'valid', 'cau arduini', 'lebanon', 'an enantiornithine'], ['eoconfuciusornis', 'valid', 'zhang zhou benton', 'china', 'primitive confuciusornithid'], ['pengornis', 'valid', 'zhou clarke zhang', 'china', 'an enantiornithine'], ['zhongornis', 'valid', "gao chiappe meng o'connor wang cheng liu", 'china', 'basal bird']] |
awards and decorations of the united states coast guard | https://en.wikipedia.org/wiki/Awards_and_decorations_of_the_United_States_Coast_Guard | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2104176-1.html.csv | count | there are 2 awards or decorations for coast guard members that are lifesaving medals . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'lifesaving medal', 'result': '2', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'air force cross', 'lifesaving medal'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose air force cross record fuzzily matches to lifesaving medal .', 'tostr': 'filter_eq { all_rows ; air force cross ; lifesaving medal }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; air force cross ; lifesaving medal } }', 'tointer': 'select the rows whose air force cross record fuzzily matches to lifesaving medal . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; air force cross ; lifesaving medal } } ; 2 } = true', 'tointer': 'select the rows whose air force cross record fuzzily matches to lifesaving medal . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; air force cross ; lifesaving medal } } ; 2 } = true | select the rows whose air force cross record fuzzily matches to lifesaving medal . 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, 'air force cross_5': 5, 'lifesaving medal_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', 'air force cross_5': 'air force cross', 'lifesaving medal_6': 'lifesaving medal', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'air force cross_5': [0], 'lifesaving medal_6': [0], '2_7': [2]} | ['medal of honor', 'coast guard cross', 'navy cross', 'distinguished service cross', 'air force cross', 'homeland security distinguished service medal'] | [['transportation distinguished service medal', 'defense distinguished service medal', 'coast guard distinguished service medal', 'navy distinguished service medal', 'army distinguished service medal', 'air force distinguished service medal'], ['silver star', "dot 's secretary award for outstanding achievement", 'defense superior service medal', 'guardian medal', 'legion of merit', 'distinguished flying cross'], ['coast guard medal', 'navy and marine corps medal', "soldier 's medal", "airman 's medal", 'gold lifesaving medal', 'bronze star'], ['purple heart', 'defense meritorious service medal', 'meritorious service medal', 'air medal', 'silver lifesaving medal', 'aerial achievement medal'], ["dot 's secretary award for meritorious achievement", 'joint service commendation medal', 'coast guard commendation medal', 'navy and marine corps commendation medal', 'army commendation medal', 'air force commendation medal'], ["dot 's secretary award for superior achievement", 'joint service achievement medal', 'transportation 9 - 11 medal', 'coast guard achievement medal', 'navy and marine corps achievement medal', 'army achievement medal']] |
supernatural ( season 4 ) | https://en.wikipedia.org/wiki/Supernatural_%28season_4%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-19396259-1.html.csv | ordinal | the second episode in the fourth season of supernatural was written by jeremy carver . | {'row': '2', 'col': '2', 'order': '2', 'col_other': '5', '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', 'no in season', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; no in season ; 2 }'}, 'written by'], 'result': 'jeremy carver', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; no in season ; 2 } ; written by }'}, 'jeremy carver'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; no in season ; 2 } ; written by } ; jeremy carver } = true', 'tointer': 'select the row whose no in season record of all rows is 2nd minimum . the written by record of this row is jeremy carver .'} | eq { hop { nth_argmin { all_rows ; no in season ; 2 } ; written by } ; jeremy carver } = true | select the row whose no in season record of all rows is 2nd minimum . the written by record of this row is jeremy carver . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'no in season_5': 5, '2_6': 6, 'written by_7': 7, 'jeremy carver_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', 'no in season_5': 'no in season', '2_6': '2', 'written by_7': 'written by', 'jeremy carver_8': 'jeremy carver'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'no in season_5': [0], '2_6': [0], 'written by_7': [1], 'jeremy carver_8': [2]} | ['no in series', 'no in season', 'title', 'directed by', 'written by', 'original air date', 'production code', 'us viewers ( million )'] | [['61', '1', 'lazarus rising', 'kim manners', 'eric kripke', 'september 18 , 2008', '3t7501', '3.96'], ['63', '3', 'in the beginning', 'steve boyum', 'jeremy carver', 'october 2 , 2008', '3t7504', '3.51'], ['64', '4', 'metamorphosis', 'kim manners', 'cathryn humphris', 'october 9 , 2008', '3t7505', '3.15'], ['65', '5', 'monster movie', 'robert singer', 'ben edlund', 'october 16 , 2008', '3t7503', '3.06'], ['66', '6', 'yellow fever', 'phil sgriccia', 'andrew dabb & daniel loflin', 'october 23 , 2008', '3t7506', '3.25'], ['67', '7', "it 's the great pumpkin , sam winchester", 'charles beeson', 'julie siege', 'october 30 , 2008', '3t7507', '3.55'], ['69', '9', 'i know what you did last summer', 'charles beeson', 'sera gamble', 'november 13 , 2008', '3t7509', '2.94'], ['70', '10', 'heaven and hell', 'j miller tobin', 'story by : trevor sands teleplay by : eric kripke', 'november 20 , 2008', '3t7510', '3.34'], ['71', '11', 'family remains', 'phil sgriccia', 'jeremy carver', 'january 15 , 2009', '3t7511', '2.98'], ['72', '12', 'criss angel is a douchebag', 'robert singer', 'julie siege', 'january 22 , 2009', '3t7512', '3.06'], ['73', '13', 'after school special', 'adam kane', 'andrew dabb & daniel loflin', 'january 29 , 2009', '3t7513', '3.56'], ['74', '14', 'sex and violence', 'charles beeson', 'cathryn humphris', 'february 5 , 2009', '3t7514', '3.37'], ['75', '15', 'death takes a holiday', 'steve boyum', 'jeremy carver', 'march 12 , 2009', '3t7515', '2.84'], ['76', '16', 'on the head of a pin', 'mike rohl', 'ben edlund', 'march 19 , 2009', '3t7516', '3.37'], ['77', '17', "it 's a terrible life", 'james l conway', 'sera gamble', 'march 26 , 2009', '3t7517', '3.13'], ['79', '19', 'jump the shark', 'phil sgriccia', 'andrew dabb & daniel loflin', 'april 23 , 2009', '3t7519', '2.70'], ['80', '20', 'the rapture', 'charles beeson', 'jeremy carver', 'april 30 , 2009', '3t7520', '2.95'], ['81', '21', 'when the levee breaks', 'robert singer', 'sera gamble', 'may 7 , 2009', '3t7521', '2.79']] |
northern pacific railway locomotives | https://en.wikipedia.org/wiki/Northern_Pacific_Railway_locomotives | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18620528-14.html.csv | superlative | the oldest nothern pacific railway locomotive made is class a. | {'scope': 'all', 'col_superlative': '9', 'row_superlative': '2', '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', 'year ( s ) retired'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; year ( s ) retired }'}, 'class'], 'result': 'a', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; year ( s ) retired } ; class }'}, 'a'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; year ( s ) retired } ; class } ; a } = true', 'tointer': 'select the row whose year ( s ) retired record of all rows is maximum . the class record of this row is a .'} | eq { hop { argmax { all_rows ; year ( s ) retired } ; class } ; a } = true | select the row whose year ( s ) retired record of all rows is maximum . the class record of this row is a . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'year (s) retired_5': 5, 'class_6': 6, 'a_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'year (s) retired_5': 'year ( s ) retired', 'class_6': 'class', 'a_7': 'a'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'year (s) retired_5': [0], 'class_6': [1], 'a_7': [2]} | ['class', 'wheel arrangement', 'fleet number ( s )', 'manufacturer', 'serial numbers', 'year made', 'quantity made', 'quantity preserved', 'year ( s ) retired'] | [['4 - 8 - 4 - oooooooo - northern', '4 - 8 - 4 - oooooooo - northern', '4 - 8 - 4 - oooooooo - northern', '4 - 8 - 4 - oooooooo - northern', '4 - 8 - 4 - oooooooo - northern', '4 - 8 - 4 - oooooooo - northern', '4 - 8 - 4 - oooooooo - northern', '4 - 8 - 4 - oooooooo - northern', '4 - 8 - 4 - oooooooo - northern'], ['a', '4 - 8 - 4', '2600 - 2611', 'alco', '67010 - 67021', '1926', '12', '0', '1949 - 1959'], ['a - 1', '4 - 8 - 4', '2626', 'alco', '68056', '1930', '1', '0', '1955'], ['a - 2', '4 - 8 - 4', '2650 - 2659', 'baldwin', '61771 - 61780', '1934 - 1935', '10', '0', '1953 - 1958'], ['a - 3', '4 - 8 - 4', '2660 - 2667', 'baldwin', '62163 - 62170', '1938', '8', '0', '1954 - 1958'], ['a - 4', '4 - 8 - 4', '2670 - 2677', 'baldwin', '64155 - 64162', '1941', '8', '0', '1954 - 1958'], ['a - 5', '4 - 8 - 4', '2680 - 2689', 'baldwin', '64667 - 64676', '1943', '10', '0', '1957 - 1959']] |
usa today all - usa high school football team | https://en.wikipedia.org/wiki/USA_Today_All-USA_high_school_football_team | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-11677691-3.html.csv | count | two of the players on the usa today all - usa high school football team play the wide receiver position . | {'scope': 'all', 'criterion': 'equal', 'value': 'wide receiver', 'result': '2', 'col': '2', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'position', 'wide receiver'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose position record fuzzily matches to wide receiver .', 'tostr': 'filter_eq { all_rows ; position ; wide receiver }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; position ; wide receiver } }', 'tointer': 'select the rows whose position record fuzzily matches to wide receiver . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; position ; wide receiver } } ; 2 } = true', 'tointer': 'select the rows whose position record fuzzily matches to wide receiver . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; position ; wide receiver } } ; 2 } = true | select the rows whose position record fuzzily matches to wide receiver . 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, 'position_5': 5, 'wide receiver_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', 'position_5': 'position', 'wide receiver_6': 'wide receiver', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'position_5': [0], 'wide receiver_6': [0], '2_7': [2]} | ['player', 'position', 'school', 'hometown', 'college'] | [['cody kessler', 'quarterback', 'centennial high school', 'bakersfield , california', 'southern california'], ['mike bellamy', 'running back', 'charlotte high school', 'punta gorda , florida', 'clemson'], ['aaron green', 'running back', 'madison high school', 'san antonio , texas', 'nebraska'], ["nick o'leary", 'tight end', 'dwyer high school', 'west palm beach , florida', 'florida state'], ['trey metoyer', 'wide receiver', 'whitehouse high school', 'whitehouse , texas', 'oklahoma'], ['charone peake', 'wide receiver', 'dorman high school', 'roebuck , south carolina', 'clemson'], ['matt freeman', 'offensive line', 'cooper high school', 'abilene , texas', 'texas state'], ['ryne reeves', 'offensive line', 'crete high school', 'crete , nebraska', 'nebraska'], ['kiaro holts', 'offensive line', 'warren central high school', 'indianapolis , indiana', 'north carolina'], ['brey cook', 'offensive line', 'har - ber high school', 'springdale , arkansas', 'arkansas'], ['michael bennett', 'offensive line', 'centerville high school', 'centerville , ohio', 'ohio state']] |
lee janzen | https://en.wikipedia.org/wiki/Lee_Janzen | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1507431-4.html.csv | superlative | the highest number of top 10s for lee janzen was at the us open . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '2', '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', 'top - 10'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; top - 10 }'}, 'tournament'], 'result': 'us open', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; top - 10 } ; tournament }'}, 'us open'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; top - 10 } ; tournament } ; us open } = true', 'tointer': 'select the row whose top - 10 record of all rows is maximum . the tournament record of this row is us open .'} | eq { hop { argmax { all_rows ; top - 10 } ; tournament } ; us open } = true | select the row whose top - 10 record of all rows is maximum . the tournament record of this row is us open . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'top - 10_5': 5, 'tournament_6': 6, 'us open_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'top - 10_5': 'top - 10', 'tournament_6': 'tournament', 'us open_7': 'us open'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'top - 10_5': [0], 'tournament_6': [1], 'us open_7': [2]} | ['tournament', 'wins', 'top - 5', 'top - 10', 'top - 25', 'events', 'cuts made'] | [['masters tournament', '0', '0', '0', '3', '12', '9'], ['us open', '2', '2', '3', '6', '19', '11'], ['the open championship', '0', '0', '0', '4', '11', '7'], ['pga championship', '0', '1', '2', '6', '13', '9'], ['totals', '2', '2', '5', '19', '55', '36']] |
sagarika ghatge | https://en.wikipedia.org/wiki/Sagarika_Ghatge | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12807043-1.html.csv | majority | most of the roles that sagarika ghatge had were in the hindi language . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'hindi', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'language', 'hindi'], 'result': True, 'ind': 0, 'tointer': 'for the language records of all rows , most of them fuzzily match to hindi .', 'tostr': 'most_eq { all_rows ; language ; hindi } = true'} | most_eq { all_rows ; language ; hindi } = true | for the language records of all rows , most of them fuzzily match to hindi . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'language_3': 3, 'hindi_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'language_3': 'language', 'hindi_4': 'hindi'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'language_3': [0], 'hindi_4': [0]} | ['year', 'title', 'role', 'language', 'notes'] | [['2007', 'chak de ! india', 'preeti sabarwal', 'hindi', 'supporting role'], ['2009', 'fox', 'urvashi mathur', 'hindi', 'small role'], ['2011', 'miley naa miley hum', 'kamiah', 'hindi', 'supporting role'], ['2012', 'rush', 'ahana sharma', 'hindi', 'released on october 24 , 2012'], ['2013', 'premachi goshta', 'sonal', 'marathi', 'lead role , movie directed by satish rajwade']] |
2008 - 09 supersport series | https://en.wikipedia.org/wiki/2008%E2%80%9309_Supersport_Series | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-19662262-6.html.csv | aggregation | the five cricketers from the 2008 - 09 supersport series took a total of 90 wickets . | {'scope': 'all', 'col': '5', 'type': 'sum', 'result': '90', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'wickets'], 'result': '90', 'ind': 0, 'tostr': 'sum { all_rows ; wickets }'}, '90'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; wickets } ; 90 } = true', 'tointer': 'the sum of the wickets record of all rows is 90 .'} | round_eq { sum { all_rows ; wickets } ; 90 } = true | the sum of the wickets record of all rows is 90 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'wickets_4': 4, '90_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'wickets_4': 'wickets', '90_5': '90'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'wickets_4': [0], '90_5': [1]} | ['player', 'team', 'matches', 'overs', 'wickets', 'economy rate', 'average', 'strike rate', 'bbi', 'bbm'] | [['makhaya ntini', 'warriors', '4', '152.4', '24', '2.18', '13.91', '38.1', '6 / 85', '9 / 109'], ['lonwabo tsotsobe', 'warriors', '4', '127.5', '16', '2.26', '18.12', '47.9', '4 / 3', '5 / 98'], ['juan theron', 'warriors', '4', '133.4', '19', '2.71', '19.10', '42.2', '7 / 46', '7 / 56'], ['mornã morkel', 'titans', '3', '92.2', '17', '3.51', '19.17', '32.7', '6 / 47', '11 / 56'], ['paul harris', 'titans', '3', '126.0', '14', '2.74', '22.28', '54.0', '7 / 94', '12 / 180']] |
1990 indianapolis colts season | https://en.wikipedia.org/wiki/1990_Indianapolis_Colts_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14876127-2.html.csv | count | in the 1990 indianapolis colts season , for games in december , there were two games at the hoosier dome . | {'scope': 'subset', 'criterion': 'fuzzily_match', 'value': 'hoosier dome', 'result': '2', 'col': '6', 'subset': {'col': '2', 'criterion': 'fuzzily_match', 'value': 'december'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', 'december'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; date ; december }', 'tointer': 'select the rows whose date record fuzzily matches to december .'}, 'game site', 'hoosier dome'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose date record fuzzily matches to december . among these rows , select the rows whose game site record fuzzily matches to hoosier dome .', 'tostr': 'filter_eq { filter_eq { all_rows ; date ; december } ; game site ; hoosier dome }'}], 'result': '2', 'ind': 2, 'tostr': 'count { filter_eq { filter_eq { all_rows ; date ; december } ; game site ; hoosier dome } }', 'tointer': 'select the rows whose date record fuzzily matches to december . among these rows , select the rows whose game site record fuzzily matches to hoosier dome . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_eq { filter_eq { all_rows ; date ; december } ; game site ; hoosier dome } } ; 2 } = true', 'tointer': 'select the rows whose date record fuzzily matches to december . among these rows , select the rows whose game site record fuzzily matches to hoosier dome . the number of such rows is 2 .'} | eq { count { filter_eq { filter_eq { all_rows ; date ; december } ; game site ; hoosier dome } } ; 2 } = true | select the rows whose date record fuzzily matches to december . among these rows , select the rows whose game site record fuzzily matches to hoosier dome . 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, 'date_6': 6, 'december_7': 7, 'game site_8': 8, 'hoosier dome_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', 'date_6': 'date', 'december_7': 'december', 'game site_8': 'game site', 'hoosier dome_9': 'hoosier dome', '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], 'date_6': [0], 'december_7': [0], 'game site_8': [1], 'hoosier dome_9': [1], '2_10': [3]} | ['week', 'date', 'opponent', 'result', 'record', 'game site', 'attendance'] | [['1', 'september 9 , 1990', 'buffalo bills', 'l 10 - 26', '0 - 1', 'ralph wilson stadium', '78899'], ['2', 'september 16 , 1990', 'new england patriots', 'l 14 - 16', '0 - 2', 'hoosier dome', '49256'], ['3', 'september 23 , 1990', 'houston oilers', 'l 10 - 24', '0 - 3', 'astrodome', '50093'], ['4', 'september 30 , 1990', 'philadelphia eagles', 'w 24 - 23', '1 - 3', 'veterans stadium', '62067'], ['5', 'october 7 , 1990', 'kansas city chiefs', 'w 23 - 19', '2 - 3', 'hoosier dome', '54950'], ['6', '-', '-', '-', '-', '-', ''], ['7', 'october 21 , 1990', 'denver broncos', 'l 17 - 24', '2 - 4', 'hoosier dome', '59850'], ['8', 'october 28 , 1990', 'miami dolphins', 'l 7 - 27', '2 - 5', 'hoosier dome', '59213'], ['9', 'november 5 , 1990', 'new york giants', 'l 7 - 24', '2 - 6', 'hoosier dome', '58688'], ['10', 'november 11 , 1990', 'new england patriots', 'w 13 - 10', '3 - 6', 'foxboro stadium', '28924'], ['11', 'november 18 , 1990', 'new york jets', 'w 17 - 14', '4 - 6', 'hoosier dome', '47283'], ['12', 'november 25 , 1990', 'cincinnati bengals', 'w 34 - 20', '5 - 6', 'riverfront stadium', '60051'], ['13', 'december 2 , 1990', 'phoenix cardinals', 'l 17 - 20', '5 - 7', 'sun devil stadium', '38043'], ['14', 'december 9 , 1990', 'buffalo bills', 'l 7 - 31', '5 - 8', 'hoosier dome', '53268'], ['15', 'december 16 , 1990', 'new york jets', 'w 29 - 21', '6 - 8', 'giants stadium', '41423'], ['16', 'december 22 , 1990', 'washington redskins', 'w 35 - 28', '7 - 8', 'hoosier dome', '58173'], ['17', 'december 30 , 1990', 'miami dolphins', 'l 17 - 23', '7 - 9', 'joe robbie stadium', '59547']] |
imvic | https://en.wikipedia.org/wiki/IMViC | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16083989-1.html.csv | majority | the majority of the bacteria species show negative results on the indole test . | {'scope': 'all', 'col': '2', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'negative', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'indole', 'negative'], 'result': True, 'ind': 0, 'tointer': 'for the indole records of all rows , most of them fuzzily match to negative .', 'tostr': 'most_eq { all_rows ; indole ; negative } = true'} | most_eq { all_rows ; indole ; negative } = true | for the indole records of all rows , most of them fuzzily match to negative . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'indole_3': 3, 'negative_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'indole_3': 'indole', 'negative_4': 'negative'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'indole_3': [0], 'negative_4': [0]} | ['species', 'indole', 'methyl red', 'voges - proskauer', 'citrate'] | [['escherichia coli', 'positive', 'positive', 'negative', 'negative'], ['shigella spp', 'negative', 'positive', 'negative', 'negative'], ['salmonella spp', 'negative', 'positive', 'negative', 'positive'], ['klebsiella spp', 'negative', 'negative', 'positive', 'positive'], ['proteus vulgaris', 'positive', 'positive', 'negative', 'negative'], ['proteus mirabilis', 'negative', 'positive', 'negative', 'positive'], ['enterobacter aerogenes', 'negative', 'negative', 'positive', 'positive']] |
chris van der drift | https://en.wikipedia.org/wiki/Chris_van_der_Drift | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16864452-1.html.csv | superlative | the highest number of points chris van der drift had was when he was with the olympiacos cfp team . | {'scope': 'all', 'col_superlative': '9', 'row_superlative': '10', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '3', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'points'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; points }'}, 'team'], 'result': 'olympiacos cfp', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; points } ; team }'}, 'olympiacos cfp'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; points } ; team } ; olympiacos cfp } = true', 'tointer': 'select the row whose points record of all rows is maximum . the team record of this row is olympiacos cfp .'} | eq { hop { argmax { all_rows ; points } ; team } ; olympiacos cfp } = true | select the row whose points record of all rows is maximum . the team record of this row is olympiacos cfp . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'points_5': 5, 'team_6': 6, 'olympiacos cfp_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'points_5': 'points', 'team_6': 'team', 'olympiacos cfp_7': 'olympiacos cfp'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'points_5': [0], 'team_6': [1], 'olympiacos cfp_7': [2]} | ['season', 'series', 'team', 'races', 'wins', 'poles', 'f / laps', 'podiums', 'points', 'position'] | [['2004', 'formula bmw adac', 'team rosberg', '20', '0', '0', '0', '8', '168', '4th'], ['2005', 'formula bmw adac', 'team rosberg', '20', '1', '0', '1', '5', '149', '4th'], ['2006', 'formula renault 2.0 eurocup', 'jd motorsport', '14', '2', '2', '1', '6', '91', '2nd'], ['2006', 'formula renault 2.0 nec', 'jd motorsport', '14', '4', '7', '4', '7', '267', '2nd'], ['2007', 'international formula master', 'jd motorsport', '16', '2', '1', '2', '7', '65', '2nd'], ['2008', 'international formula master', 'jd motorsport', '16', '6', '6', '8', '10', '101', '1st'], ['2008 - 09', 'gp2 asia series', 'trident racing', '3', '0', '0', '0', '0', '5', '18th'], ['2008 - 09', 'a1 grand prix', 'new zealand', '4', '0', '0', '0', '0', '36', '7th'], ['2009', 'formula renault 3.5 series', 'epsilon euskadi', '17', '0', '0', '0', '1', '41', '11th'], ['2010', 'superleague formula', 'olympiacos cfp', '18', '4', '2', '3', '10', '653', '4th'], ['2010', 'superleague formula', 'galatasaray', '3', '0', '0', '0', '0', '358', '13th'], ['2011', 'superleague formula', 'new zealand', '3', '0', '0', '0', '0', '116', '7th'], ['2011', 'formula renault 3.5 series', 'mofaz racing', '7', '0', '0', '0', '1', '43', '12th'], ['2012', 'auto gp world series', 'manor mp motorsport', '12', '1', '0', '0', '4', '127', '4th']] |
salvatore bettiol | https://en.wikipedia.org/wiki/Salvatore_Bettiol | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15671752-1.html.csv | majority | most of salvatore bettiol 's competitions took place in the 1990 's . | {'scope': 'all', 'col': '1', 'most_or_all': 'most', 'criterion': 'greater_than_eq', 'value': '1990', 'subset': None} | {'func': 'most_greater_eq', 'args': ['all_rows', 'year', '1990'], 'result': True, 'ind': 0, 'tointer': 'for the year records of all rows , most of them are greater than or equal to 1990 .', 'tostr': 'most_greater_eq { all_rows ; year ; 1990 } = true'} | most_greater_eq { all_rows ; year ; 1990 } = true | for the year records of all rows , most of them are greater than or equal to 1990 . | 1 | 1 | {'most_greater_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'year_3': 3, '1990_4': 4} | {'most_greater_eq_0': 'most_greater_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'year_3': 'year', '1990_4': '1990'} | {'most_greater_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'year_3': [0], '1990_4': [0]} | ['year', 'competition', 'venue', 'position', 'event', 'notes'] | [['1986', 'venice marathon', 'venice , italy', '1st', 'marathon', '2:18:44'], ['1987', 'world championships', 'rome , italy', '13th', 'marathon', '2:17:45'], ['1987', 'venice marathon', 'venice , italy', '1st', 'marathon', '2:10:01'], ['1990', 'european championships', 'split , fr yugoslavia', '4th', 'marathon', '2:17:45'], ['1991', 'world championships', 'tokyo , japan', '6th', 'marathon', '2:15:58'], ['1992', 'olympic games', 'barcelona , spain', '5th', 'marathon', '2:14:15'], ['1993', 'world championships', 'stuttgart , germany', 'n / a', 'marathon', 'dnf'], ['1996', 'olympic games', 'atlanta , united states', '20th', 'marathon', '2:17:27']] |
thai solar calendar | https://en.wikipedia.org/wiki/Thai_solar_calendar | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-180802-2.html.csv | unique | the thai transcription of the equivalent month to january is the only one with two distinct transcriptions . | {'scope': 'all', 'row': '1', 'col': '4', 'col_other': '1', 'criterion': 'fuzzily_match', 'value': ',', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'transcription', ','], 'result': None, 'ind': 0, 'tointer': 'select the rows whose transcription record fuzzily matches to , .', 'tostr': 'filter_eq { all_rows ; transcription ; , }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; transcription ; , } }', 'tointer': 'select the rows whose transcription record fuzzily matches to , . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'transcription', ','], 'result': None, 'ind': 0, 'tointer': 'select the rows whose transcription record fuzzily matches to , .', 'tostr': 'filter_eq { all_rows ; transcription ; , }'}, 'english name'], 'result': 'january', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; transcription ; , } ; english name }'}, 'january'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; transcription ; , } ; english name } ; january }', 'tointer': 'the english name record of this unqiue row is january .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; transcription ; , } } ; eq { hop { filter_eq { all_rows ; transcription ; , } ; english name } ; january } } = true', 'tointer': 'select the rows whose transcription record fuzzily matches to , . there is only one such row in the table . the english name record of this unqiue row is january .'} | and { only { filter_eq { all_rows ; transcription ; , } } ; eq { hop { filter_eq { all_rows ; transcription ; , } ; english name } ; january } } = true | select the rows whose transcription record fuzzily matches to , . there is only one such row in the table . the english name record of this unqiue row is january . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'transcription_7': 7, ',_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'english name_9': 9, 'january_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'transcription_7': 'transcription', ',_8': ',', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'english name_9': 'english name', 'january_10': 'january'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'transcription_7': [0], ',_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'english name_9': [2], 'january_10': [3]} | ['english name', 'thai name', 'abbr', 'transcription', 'sanskrit word', 'zodiac sign'] | [['january', 'มกราคม', 'มค', 'makarakhom , mokkarakhom', 'makara sea - monster', 'capricorn'], ['february', 'กุมภาพันธ์', 'กพ', 'kumphaphan', 'kumbha pitcher , water - pot', 'aquarius'], ['march', 'มีนาคม', 'มีค', 'minakhom', 'mīna ( a specific kind of ) fish', 'pisces'], ['april', 'เมษายน', 'เมย', 'mesayon', 'meṣa ram', 'aries'], ['may', 'พฤษภาคม', 'พค', 'phruetsaphakhom', 'vṛṣabha bull', 'taurus'], ['june', 'มิถุนายน', 'มิย', 'mithunayon', 'mithuna a pair', 'gemini'], ['july', 'กรกฎาคม', 'กค', 'karakadakhom', 'karkaṭa crab', 'cancer'], ['august', 'สิงหาคม', 'สค', 'singhakhom', 'sinha lion', 'leo'], ['september', 'กันยายน', 'กย', 'kanyayon', 'kanyā girl', 'virgo'], ['october', 'ตุลาคม', 'ตค', 'tulakhom', 'tulā balance', 'libra'], ['november', 'พฤศจิกายน', 'พย', 'phruetsachikayon', 'vṛścika scorpion', 'scorpio'], ['december', 'ธันวาคม', 'ธค', 'thanwakhom', 'dhanu bow , arc', 'sagittarius']] |
muhsin corbbrey | https://en.wikipedia.org/wiki/Muhsin_Corbbrey | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17624865-1.html.csv | comparative | muhsin corbbrey 's fight against troy nelson lasted more rounds than his fight against shelton barnes . | {'row_1': '1', 'row_2': '4', 'col': '7', 'col_other': '3', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', 'troy nelson'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose opponent record fuzzily matches to troy nelson .', 'tostr': 'filter_eq { all_rows ; opponent ; troy nelson }'}, 'round'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; opponent ; troy nelson } ; round }', 'tointer': 'select the rows whose opponent record fuzzily matches to troy nelson . take the round record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', 'shelton barnes'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose opponent record fuzzily matches to shelton barnes .', 'tostr': 'filter_eq { all_rows ; opponent ; shelton barnes }'}, 'round'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; opponent ; shelton barnes } ; round }', 'tointer': 'select the rows whose opponent record fuzzily matches to shelton barnes . take the round record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; opponent ; troy nelson } ; round } ; hop { filter_eq { all_rows ; opponent ; shelton barnes } ; round } } = true', 'tointer': 'select the rows whose opponent record fuzzily matches to troy nelson . take the round record of this row . select the rows whose opponent record fuzzily matches to shelton barnes . take the round record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; opponent ; troy nelson } ; round } ; hop { filter_eq { all_rows ; opponent ; shelton barnes } ; round } } = true | select the rows whose opponent record fuzzily matches to troy nelson . take the round record of this row . select the rows whose opponent record fuzzily matches to shelton barnes . take the round 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, 'opponent_7': 7, 'troy nelson_8': 8, 'round_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'opponent_11': 11, 'shelton barnes_12': 12, 'round_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', 'opponent_7': 'opponent', 'troy nelson_8': 'troy nelson', 'round_9': 'round', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'opponent_11': 'opponent', 'shelton barnes_12': 'shelton barnes', 'round_13': 'round'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'opponent_7': [0], 'troy nelson_8': [0], 'round_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'opponent_11': [1], 'shelton barnes_12': [1], 'round_13': [3]} | ['date', 'result', 'opponent', 'venue', 'location', 'method', 'round', 'time', 'record'] | [['2009 - 02 - 28', 'win', 'troy nelson', 'shoreline ball room', 'hilton head , south carolina , usa', 'decision', '6', '3:00', '6 - 2 - 1'], ['2006 - 09 - 15', 'win', 'ryan rayonec', 'omar shrine temple', 'mount pleasant , south carolina , usa', 'tko', '4', '0:54', '5 - 2 - 1'], ['2006 - 06 - 15', 'loss', 'tim coleman', "michael 's eighth avenue", 'glen burnie , maryland , usa', 'decision ( unanimous )', '6', '3:00', '4 - 2 - 1'], ['2006 - 04 - 21', 'win', 'shelton barnes', 'omar shrine temple', 'mount pleasant , south carolina , usa', 'tko', '1', '2:43', '4 - 1 - 1'], ['2006 - 03 - 09', 'win', 'kareem robinson', "michael 's eighth avenue", 'glen burnie , maryland , usa', 'decision ( unanimous )', '4', '3:00', '3 - 1 - 1'], ['2006 - 01 - 26', 'win', 'anthony abrams', "michael 's eighth avenue", 'glen burnie , maryland , usa', 'decision ( unanimous )', '4', '3:00', '2 - 1 - 1'], ['2005 - 11 - 26', 'win', 'ben lock', 'show place arena', 'upper marlboro , maryland , usa', 'decision ( unanimous )', '4', '3:00', '1 - 1 - 1'], ['2005 - 04 - 26', 'loss', 'emanuel gonzã ¡ lez', 'radisson hotel', 'miami , florida , usa', 'decision ( unanimous )', '4', '3:00', '0 - 1 - 1'], ['2005 - 04 - 08', 'draw', 'ricardo planter', 'club med sandpiper', 'port st lucie , florida , usa', 'draw ( majority )', '4', '3:00', '0 - 0 - 1']] |
royal canadian mint numismatic coins ( 2000s ) | https://en.wikipedia.org/wiki/Royal_Canadian_Mint_numismatic_coins_%282000s%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11916083-40.html.csv | count | two of the designs of the royal canadian mint numismatic coins had an issue price of 79.95 . | {'scope': 'all', 'criterion': 'equal', 'value': '79.95', 'result': '2', 'col': '6', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'issue price', '79.95'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose issue price record is equal to 79.95 .', 'tostr': 'filter_eq { all_rows ; issue price ; 79.95 }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; issue price ; 79.95 } }', 'tointer': 'select the rows whose issue price record is equal to 79.95 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; issue price ; 79.95 } } ; 2 } = true', 'tointer': 'select the rows whose issue price record is equal to 79.95 . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; issue price ; 79.95 } } ; 2 } = true | select the rows whose issue price record is equal to 79.95 . the number of such rows is 2 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_eq_0': 0, 'all_rows_4': 4, 'issue price_5': 5, '79.95_6': 6, '2_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'issue price_5': 'issue price', '79.95_6': '79.95', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'issue price_5': [0], '79.95_6': [0], '2_7': [2]} | ['year', 'design', 'issue', 'artist', 'mintage', 'issue price'] | [['2003', 'niagara falls', 'hologram', 'gary corcoran', '29967', '79.95'], ['2003', 'rocky mountains', 'colorized', 'josé osio', '28793', '69.95'], ['2004', 'iceberg', 'hologram', 'josé osio', '24879', '69.95'], ['2004', 'northern lights', 'double image hologram', 'gary corcoran', '34135', '79.95'], ['2004', 'hopewell rocks', 'selectively gold plated', 'josé osio', '16918', '69.95'], ['2005', 'diamonds', 'double image hologram', 'josé osio', '35000', '69.95']] |
list of star wars : the clone wars episodes | https://en.wikipedia.org/wiki/List_of_Star_Wars%3A_The_Clone_Wars_episodes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-19229713-6.html.csv | superlative | of the star wars : the clone wars episodes , the one with the highest number of viewers was titled " to catch a jedi " . | {'scope': 'all', 'col_superlative': '8', 'row_superlative': '19', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '3', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'us viewers ( million )'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; us viewers ( million ) }'}, 'title'], 'result': 'to catch a jedi', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; us viewers ( million ) } ; title }'}, 'to catch a jedi'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; us viewers ( million ) } ; title } ; to catch a jedi } = true', 'tointer': 'select the row whose us viewers ( million ) record of all rows is maximum . the title record of this row is to catch a jedi .'} | eq { hop { argmax { all_rows ; us viewers ( million ) } ; title } ; to catch a jedi } = true | select the row whose us viewers ( million ) record of all rows is maximum . the title record of this row is to catch a jedi . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'us viewers (million)_5': 5, 'title_6': 6, 'to catch a jedi_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'us viewers (million)_5': 'us viewers ( million )', 'title_6': 'title', 'to catch a jedi_7': 'to catch a jedi'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'us viewers (million)_5': [0], 'title_6': [1], 'to catch a jedi_7': [2]} | ['no', '-', 'title', 'directed by', 'written by', 'original air date', 'production code', 'us viewers ( million )'] | [['89', '1', 'revival', 'steward lee', 'chris collins', 'september 29 , 2012', '4.26', '1.94'], ['90', '2', 'a war on two fronts', 'dave filoni', 'chris collins', 'october 6 , 2012', '4.15', '1.71'], ['91', '3', 'front runners', 'steward lee', 'chris collins', 'october 13 , 2012', '4.16', '1.75'], ['92', '4', 'the soft war', 'kyle dunlevy', 'chris collins', 'october 20 , 2012', '4.17', '1.57'], ['93', '5', 'tipping points', 'bosco ng', 'chris collins', 'october 27 , 2012', '4.18', '1.42'], ['94', '6', 'the gathering', 'kyle dunlevy', 'christian taylor', 'november 3 , 2012', '4.22', '1.66'], ['95', '7', 'a test of strength', 'bosco ng', 'christian taylor', 'november 10 , 2012', '4.23', '1.74'], ['96', '8', 'bound for rescue', "brian kalin o'connell", 'christian taylor', 'november 17 , 2012', '4.24', '1.96'], ['97', '9', 'a necessary bond', 'danny keller', 'christian taylor', 'november 24 , 2012', '4.25', '1.39'], ['98', '10', 'secret weapons', 'danny keller', 'brent friedman', 'december 1 , 2012', '5.04', '1.46'], ['99', '11', 'a sunny day in the void', 'kyle dunlevy', 'brent friedman', 'december 8 , 2012', '5.05', '1.43'], ['100', '12', 'missing in action', 'steward lee', 'brent friedman', 'january 5 , 2013', '5.06', '1.74'], ['101', '13', 'point of no return', 'bosco ng', 'brent friedman', 'january 12 , 2013', '5.07', '1.47'], ['102', '14', 'eminence', 'kyle dunlevy', 'chris collins', 'january 19 , 2013', '5.01', '1.85'], ['103', '15', 'shades of reason', 'bosco ng', 'chris collins', 'january 26 , 2013', '5.02', '1.83'], ['104', '16', 'the lawless', "brian kalin o'connell", 'chris collins', 'february 2 , 2013', '5.03', '1.86'], ['105', '17', 'sabotage', "brian kalin o'connell", 'charles murray', 'february 9 , 2013', '5.08', '2.02'], ['106', '18', 'the jedi who knew too much', 'danny keller', 'charles murray', 'february 16 , 2013', '5.09', '1.64'], ['107', '19', 'to catch a jedi', 'kyle dunlevy', 'charles murray', 'february 23 , 2013', '5.10', '2.06']] |
art competitions at the 1924 summer olympics | https://en.wikipedia.org/wiki/Art_competitions_at_the_1924_Summer_Olympics | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16581439-2.html.csv | superlative | france ( fra ) had the most bronze in art competitions at the 1924 summer olympics . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '2', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '2', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'bronze'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; bronze }'}, 'nation'], 'result': 'france ( fra )', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; bronze } ; nation }'}, 'france ( fra )'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; bronze } ; nation } ; france ( fra ) } = true', 'tointer': 'select the row whose bronze record of all rows is maximum . the nation record of this row is france ( fra ) .'} | eq { hop { argmax { all_rows ; bronze } ; nation } ; france ( fra ) } = true | select the row whose bronze record of all rows is maximum . the nation record of this row is france ( fra ) . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'bronze_5': 5, 'nation_6': 6, 'france (fra)_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'bronze_5': 'bronze', 'nation_6': 'nation', 'france (fra)_7': 'france ( fra )'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'bronze_5': [0], 'nation_6': [1], 'france (fra)_7': [2]} | ['rank', 'nation', 'gold', 'silver', 'bronze', 'total'] | [['1', 'luxembourg ( lux )', '1', '1', '0', '2'], ['2', 'france ( fra )', '1', '0', '2', '3'], ['3', 'greece ( gre )', '1', '0', '0', '1'], ['4', 'denmark ( den )', '0', '1', '1', '2'], ['4', 'ireland ( irl )', '0', '1', '1', '2'], ['6', 'great britain ( gbr )', '0', '1', '0', '1'], ['6', 'hungary ( hun )', '0', '1', '0', '1'], ['8', 'monaco ( mon )', '0', '0', '1', '1'], ['8', 'netherlands ( ned )', '0', '0', '1', '1']] |
european film award for best short film | https://en.wikipedia.org/wiki/European_Film_Award_for_Best_Short_Film | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12152327-4.html.csv | majority | all of the films were nominated in the short film 2005 prix uip category . | {'scope': 'all', 'col': '1', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'short film 2005 prix uip', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'category', 'short film 2005 prix uip'], 'result': True, 'ind': 0, 'tointer': 'for the category records of all rows , all of them fuzzily match to short film 2005 prix uip .', 'tostr': 'all_eq { all_rows ; category ; short film 2005 prix uip } = true'} | all_eq { all_rows ; category ; short film 2005 prix uip } = true | for the category records of all rows , all of them fuzzily match to short film 2005 prix uip . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'category_3': 3, 'short film 2005 prix uip_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'category_3': 'category', 'short film 2005 prix uip_4': 'short film 2005 prix uip'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'category_3': [0], 'short film 2005 prix uip_4': [0]} | ['category', 'film', 'director ( s )', 'country', 'nominating festival'] | [['short film 2005 prix uip', 'undressing my mother', 'ken wardrop', 'ireland', 'prix uip tampere'], ['short film 2005 prix uip', 'little terrorist', 'ashvin kumar', 'united kingdom', 'prix uip ghent'], ['short film 2005 prix uip', 'rendevú', 'ferenc cakó', 'hungary', 'prix uip valladolid'], ['short film 2005 prix uip', 'rain is falling', 'holger ernst', 'germany', 'prix uip valladolid'], ['short film 2005 prix uip', 'flatlife', 'jonas geirnaert', 'belgium', 'prix uip angers'], ['short film 2005 prix uip', 'hoi maya', 'claudia lorenz', 'switzerland', 'prix uip berlin'], ['short film 2005 prix uip', 'toz ( dust )', 'halit fatih kizilgok', 'turkey', 'prix uip cracow'], ['short film 2005 prix uip', 'bawke', 'hisham zaman', 'norway', 'prix uip grimstad'], ['short film 2005 prix uip', 'a serpente', 'sandro aguilar', 'portugal', 'prix uip vila do conde'], ['short film 2005 prix uip', 'scen nr 6882 ur mitt liv', 'ruben östlund', 'sweden', 'prix uip edinburgh'], ['short film 2005 prix uip', 'prva plata', 'alen drljević', 'bosnia and herzegovina', 'prix uip sarajevo'], ['short film 2005 prix uip', 'butterflies', 'max jacoby', 'luxembourg', 'prix uip venezia'], ['short film 2005 prix uip', 'minotauromaquia , pablo en el laberinto', 'juan pablo etcheverry', 'spain', 'prix uip drama']] |
list of mountains of the british isles by relative height | https://en.wikipedia.org/wiki/List_of_mountains_of_the_British_Isles_by_relative_height | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1456056-1.html.csv | aggregation | there are a total of 119 mountains over 2000 ft in the british isles . | {'scope': 'all', 'col': '2', 'type': 'sum', 'result': '119', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'total'], 'result': '119', 'ind': 0, 'tostr': 'sum { all_rows ; total }'}, '119'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; total } ; 119 } = true', 'tointer': 'the sum of the total record of all rows is 119 .'} | round_eq { sum { all_rows ; total } ; 119 } = true | the sum of the total record of all rows is 119 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'total_4': 4, '119_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'total_4': 'total', '119_5': '119'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'total_4': [0], '119_5': [1]} | ['country', 'total', '4000ft +', '3500 - 4000ft', '3000 - 3500ft', '2500 - 3000ft', '2000 - 2500ft'] | [['scotland', '82', '2', '21', '31', '21', '7'], ['ireland', '24', '0', '0', '4', '8', '12'], ['wales', '7', '0', '1', '2', '4', '0'], ['england', '4', '0', '0', '3', '1', '0'], ['northern ireland', '1', '0', '0', '0', '1', '0'], ['isle of man', '1', '0', '0', '0', '0', '1']] |
2008 twenty20 cup | https://en.wikipedia.org/wiki/2008_Twenty20_Cup | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17900317-4.html.csv | comparative | joe denly scored a higher amount of runs than phil mustard in the 2008 twenty20 cup . | {'row_1': '1', 'row_2': '10', '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', 'player', 'joe denly'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose player record fuzzily matches to joe denly .', 'tostr': 'filter_eq { all_rows ; player ; joe denly }'}, 'runs'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; player ; joe denly } ; runs }', 'tointer': 'select the rows whose player record fuzzily matches to joe denly . take the runs record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', 'phil mustard'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose player record fuzzily matches to phil mustard .', 'tostr': 'filter_eq { all_rows ; player ; phil mustard }'}, 'runs'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; player ; phil mustard } ; runs }', 'tointer': 'select the rows whose player record fuzzily matches to phil mustard . take the runs record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; player ; joe denly } ; runs } ; hop { filter_eq { all_rows ; player ; phil mustard } ; runs } } = true', 'tointer': 'select the rows whose player record fuzzily matches to joe denly . take the runs record of this row . select the rows whose player record fuzzily matches to phil mustard . take the runs record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; player ; joe denly } ; runs } ; hop { filter_eq { all_rows ; player ; phil mustard } ; runs } } = true | select the rows whose player record fuzzily matches to joe denly . take the runs record of this row . select the rows whose player record fuzzily matches to phil mustard . take the runs record of this row . the first record is greater than the second record . | 5 | 5 | {'greater_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'player_7': 7, 'joe denly_8': 8, 'runs_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'player_11': 11, 'phil mustard_12': 12, 'runs_13': 13} | {'greater_4': 'greater', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'player_7': 'player', 'joe denly_8': 'joe denly', 'runs_9': 'runs', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'player_11': 'player', 'phil mustard_12': 'phil mustard', 'runs_13': 'runs'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'player_7': [0], 'joe denly_8': [0], 'runs_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'player_11': [1], 'phil mustard_12': [1], 'runs_13': [3]} | ['player', 'team', 'matches', 'inns', 'runs', 'balls', 's / rate', '100s', 'average'] | [['joe denly', 'kent spitfires', '13', '13', '451', '379', '118.99', '0', '34.69'], ['anthony mcgrath', 'yorkshire carnegie', '9', '9', '392', '296', '132.43', '0', '56.00'], ['murray goodwin', 'sussex sharks', '10', '10', '345', '273', '126.37', '0', '43.13'], ['robert key', 'kent spitfires', '13', '13', '345', '258', '133.72', '0', '26.53'], ['michael carberry', 'hampshire hawks', '10', '10', '334', '268', '124.62', '0', '37.11'], ['graham napier', 'essex eagles', '12', '11', '326', '167', '195.20', '1', '32.60'], ['michael lumb', 'hampshire hawks', '10', '10', '315', '209', '150.71', '0', '31.50'], ['marcus trescothick', 'somerset sabres', '8', '8', '306', '185', '165.40', '1', '38.25'], ['dawid malan', 'middlesex crusaders', '12', '10', '306', '220', '139.09', '1', '61.20'], ['phil mustard', 'durham dynamos', '11', '11', '303', '224', '135.26', '0', '27.54']] |
lloyd ruby | https://en.wikipedia.org/wiki/Lloyd_Ruby | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1235044-1.html.csv | count | there were six occasions where lloyd ruby finished two hundred laps . | {'scope': 'all', 'criterion': 'equal', 'value': '200', 'result': '6', 'col': '6', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'laps', '200'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose laps record is equal to 200 .', 'tostr': 'filter_eq { all_rows ; laps ; 200 }'}], 'result': '6', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; laps ; 200 } }', 'tointer': 'select the rows whose laps record is equal to 200 . the number of such rows is 6 .'}, '6'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; laps ; 200 } } ; 6 } = true', 'tointer': 'select the rows whose laps record is equal to 200 . the number of such rows is 6 .'} | eq { count { filter_eq { all_rows ; laps ; 200 } } ; 6 } = true | select the rows whose laps record is equal to 200 . the number of such rows is 6 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_eq_0': 0, 'all_rows_4': 4, 'laps_5': 5, '200_6': 6, '6_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'laps_5': 'laps', '200_6': '200', '6_7': '6'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'laps_5': [0], '200_6': [0], '6_7': [2]} | ['year', 'start', 'qual', 'rank', 'finish', 'laps'] | [['1960', '12', '144.208', '15', '7', '200'], ['1961', '25', '146.909', '2', '8', '200'], ['1962', '24', '146.520', '24', '8', '200'], ['1963', '19', '149.123', '15', '13', '200'], ['1964', '7', '153.932', '8', '3', '200'], ['1965', '9', '157.246', '9', '11', '184'], ['1966', '5', '162.433', '5', '11', '166'], ['1967', '7', '165.229', '8', '33', '3'], ['1968', '5', '167.613', '5', '5', '200'], ['1969', '20', '166.428', '20', '20', '105'], ['1970', '25', '168.895', '6', '27', '54'], ['1971', '7', '173.821', '7', '11', '174'], ['1972', '11', '181.415', '20', '6', '196'], ['1973', '15', '191.622', '18', '27', '21'], ['1974', '18', '181.699', '20', '9', '187'], ['1975', '6', '186.984', '7', '32', '7'], ['1976', '30', '186.480', '7', '11', '100'], ['1977', '19', '190.840', '11', '27', '34']] |
travis parrott | https://en.wikipedia.org/wiki/Travis_Parrott | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18149740-3.html.csv | majority | the majority of travis parrott 's tournaments were played in the united states . | {'scope': 'all', 'col': '2', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': 'us', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'tournament', 'us'], 'result': True, 'ind': 0, 'tointer': 'for the tournament records of all rows , most of them fuzzily match to us .', 'tostr': 'most_eq { all_rows ; tournament ; us } = true'} | most_eq { all_rows ; tournament ; us } = true | for the tournament records of all rows , most of them fuzzily match to us . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'tournament_3': 3, 'us_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'tournament_3': 'tournament', 'us_4': 'us'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'tournament_3': [0], 'us_4': [0]} | ['date', 'tournament', 'surface', 'partnering', 'opponent in the final', 'score'] | [['august 16 , 2004', 'washington , dc , united states', 'hard', 'dmitry tursunov', 'chris haggard robbie koenig', '7 - 6 3 , 6 - 1'], ['july 4 , 2005', 'newport , us', 'grass', 'graydon oliver', 'jordan kerr jim thomas', '7 - 6 5 , 7 - 6 5'], ['april 14 , 2008', 'valencia , spain', 'clay', 'filip polášek', 'máximo gonzález juan mónaco', '7 - 5 , 7 - 5'], ['august 4 , 2008', 'los angeles , us', 'hard', 'dušan vemić', 'rohan bopanna eric butorac', '7 - 6 5 , 7 - 6 5'], ['february 22 , 2009', 'memphis , tennessee , us', 'hard', 'filip polášek', 'mardy fish mark knowles', '7 - 6 7 , 6 - 1'], ['june 19 , 2009', 'eastbourne , united kingdom', 'grass', 'filip polášek', 'mariusz fyrstenberg marcin matkowski', '6 - 4 , 6 - 4']] |
1970 isle of man tt | https://en.wikipedia.org/wiki/1970_Isle_of_Man_TT | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10301911-3.html.csv | comparative | stan woods finished the race with a better time than tom loughridge . | {'row_1': '3', 'row_2': '7', 'col': '5', 'col_other': '2', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'rider', 'stan woods'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose rider record fuzzily matches to stan woods .', 'tostr': 'filter_eq { all_rows ; rider ; stan woods }'}, 'time'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; rider ; stan woods } ; time }', 'tointer': 'select the rows whose rider record fuzzily matches to stan woods . take the time record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'rider', 'tom loughridge'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose rider record fuzzily matches to tom loughridge .', 'tostr': 'filter_eq { all_rows ; rider ; tom loughridge }'}, 'time'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; rider ; tom loughridge } ; time }', 'tointer': 'select the rows whose rider record fuzzily matches to tom loughridge . take the time record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; rider ; stan woods } ; time } ; hop { filter_eq { all_rows ; rider ; tom loughridge } ; time } } = true', 'tointer': 'select the rows whose rider record fuzzily matches to stan woods . take the time record of this row . select the rows whose rider record fuzzily matches to tom loughridge . take the time record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; rider ; stan woods } ; time } ; hop { filter_eq { all_rows ; rider ; tom loughridge } ; time } } = true | select the rows whose rider record fuzzily matches to stan woods . take the time record of this row . select the rows whose rider record fuzzily matches to tom loughridge . take the time record of this row . the first record is less than the second record . | 5 | 5 | {'less_4': 4, 'result_5': 5, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'rider_7': 7, 'stan woods_8': 8, 'time_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'rider_11': 11, 'tom loughridge_12': 12, 'time_13': 13} | {'less_4': 'less', 'result_5': 'true', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'rider_7': 'rider', 'stan woods_8': 'stan woods', 'time_9': 'time', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'rider_11': 'rider', 'tom loughridge_12': 'tom loughridge', 'time_13': 'time'} | {'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'rider_7': [0], 'stan woods_8': [0], 'time_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'rider_11': [1], 'tom loughridge_12': [1], 'time_13': [3]} | ['rank', 'rider', 'team', 'speed', 'time'] | [['1', 'chas mortimer', 'ducati', '84.87 mph', '2:13.23.4'], ['2', 'john williams', 'honda', '84.80 mph', '2:13.29.0'], ['3', 'stan woods', 'suzuki', '84.06 mph', '2:14.40.6'], ['4', 'ghunter', 'ducati', '83.94 mph', '2:14.52.4'], ['5', 'roy boughley', 'honda', '82.26 mph', '2:17.37.6'], ['6', 'raymond ashcroft', 'suzuki', '76.59 mph', '2:27.48.8'], ['7', 'tom loughridge', 'suzuki', '76.32 mph', '2:28.19.0'], ['8', 'cluton', 'ducati', '72.50 mph', '2:36.08.0']] |
list of cities , towns and villages in vojvodina | https://en.wikipedia.org/wiki/List_of_cities%2C_towns_and_villages_in_Vojvodina | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2562572-37.html.csv | count | considering the towns and villages in vojvodina , 3 cities have the orthodox christianity as their dominant religion . | {'scope': 'all', 'criterion': 'equal', 'value': 'orthodox christianity', 'result': '3', 'col': '6', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'dominant religion ( 2002 )', 'orthodox christianity'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose dominant religion ( 2002 ) record fuzzily matches to orthodox christianity .', 'tostr': 'filter_eq { all_rows ; dominant religion ( 2002 ) ; orthodox christianity }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; dominant religion ( 2002 ) ; orthodox christianity } }', 'tointer': 'select the rows whose dominant religion ( 2002 ) record fuzzily matches to orthodox christianity . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; dominant religion ( 2002 ) ; orthodox christianity } } ; 3 } = true', 'tointer': 'select the rows whose dominant religion ( 2002 ) record fuzzily matches to orthodox christianity . the number of such rows is 3 .'} | eq { count { filter_eq { all_rows ; dominant religion ( 2002 ) ; orthodox christianity } } ; 3 } = true | select the rows whose dominant religion ( 2002 ) record fuzzily matches to orthodox christianity . 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, 'dominant religion (2002)_5': 5, 'Orthodox Christianity_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', 'dominant religion (2002)_5': 'dominant religion ( 2002 )', 'Orthodox Christianity_6': 'orthodox christianity', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'dominant religion (2002)_5': [0], 'Orthodox Christianity_6': [0], '3_7': [2]} | ['settlement', 'cyrillic name other names', 'type', 'population ( 2011 )', 'largest ethnic group ( 2002 )', 'dominant religion ( 2002 )'] | [['nova crnja', 'нова црња ( hungarian : magyarcsernye )', 'village', '1509', 'hungarians', 'catholic christianity'], ['aleksandrovo', 'александрово', 'village', '2130', 'serbs', 'orthodox christianity'], ['radojevo', 'радојево', 'village', '1056', 'serbs', 'orthodox christianity'], ['srpska crnja', 'српска црња', 'village', '3685', 'serbs', 'orthodox christianity'], ['toba', 'тоба ( hungarian : tóba )', 'village', '518', 'hungarians', 'catholic christianity']] |
roman catholic archdiocese of boston | https://en.wikipedia.org/wiki/Roman_Catholic_Archdiocese_of_Boston | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1692165-1.html.csv | count | in the roman catholic archdiocese of boston , when there are over 60 parishes , there were two regions that had under 5 high schools . | {'scope': 'subset', 'criterion': 'less_than', 'value': '5', 'result': '2', 'col': '4', 'subset': {'col': '3', 'criterion': 'greater_than', 'value': '60'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_less', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'parishes', '60'], 'result': None, 'ind': 0, 'tostr': 'filter_greater { all_rows ; parishes ; 60 }', 'tointer': 'select the rows whose parishes record is greater than 60 .'}, 'high schools', '5'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose parishes record is greater than 60 . among these rows , select the rows whose high schools record is less than 5 .', 'tostr': 'filter_less { filter_greater { all_rows ; parishes ; 60 } ; high schools ; 5 }'}], 'result': '2', 'ind': 2, 'tostr': 'count { filter_less { filter_greater { all_rows ; parishes ; 60 } ; high schools ; 5 } }', 'tointer': 'select the rows whose parishes record is greater than 60 . among these rows , select the rows whose high schools record is less than 5 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_less { filter_greater { all_rows ; parishes ; 60 } ; high schools ; 5 } } ; 2 } = true', 'tointer': 'select the rows whose parishes record is greater than 60 . among these rows , select the rows whose high schools record is less than 5 . the number of such rows is 2 .'} | eq { count { filter_less { filter_greater { all_rows ; parishes ; 60 } ; high schools ; 5 } } ; 2 } = true | select the rows whose parishes record is greater than 60 . among these rows , select the rows whose high schools record is less than 5 . the number of such rows is 2 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_less_1': 1, 'filter_greater_0': 0, 'all_rows_5': 5, 'parishes_6': 6, '60_7': 7, 'high schools_8': 8, '5_9': 9, '2_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_less_1': 'filter_less', 'filter_greater_0': 'filter_greater', 'all_rows_5': 'all_rows', 'parishes_6': 'parishes', '60_7': '60', 'high schools_8': 'high schools', '5_9': '5', '2_10': '2'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_less_1': [2], 'filter_greater_0': [1], 'all_rows_5': [0], 'parishes_6': [0], '60_7': [0], 'high schools_8': [1], '5_9': [1], '2_10': [3]} | ['pastoral region', 'episcopal vicar', 'parishes', 'high schools', 'elementary schools', 'cemeteries'] | [['central', 'robert francis hennessey', '64', '6', '29', '8'], ['merrimack', 'currently vacant', '49', '3', '( tbd )', '4'], ['north', 'peter john uglietto', '64', '4', '6', '11'], ['south', 'john anthony dooher', '59', '3', '( tbd )', '3'], ['west', 'walter james edyvean', '67', '3', '11', '7']] |
locomotives of the southern railway | https://en.wikipedia.org/wiki/Locomotives_of_the_Southern_Railway | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1169552-12.html.csv | aggregation | from 1900 to 1914 , the southern railway build a total of 910 locomotives . | {'scope': 'subset', 'col': '5', 'type': 'sum', 'result': '910', 'subset': {'col': '3', 'criterion': 'less_than', 'value': '1914'}} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'date', '1914'], 'result': None, 'ind': 0, 'tostr': 'filter_less { all_rows ; date ; 1914 }', 'tointer': 'select the rows whose date record is less than 1914 .'}, 'no built'], 'result': '910', 'ind': 1, 'tostr': 'sum { filter_less { all_rows ; date ; 1914 } ; no built }'}, '910'], 'result': True, 'ind': 2, 'tostr': 'round_eq { sum { filter_less { all_rows ; date ; 1914 } ; no built } ; 910 } = true', 'tointer': 'select the rows whose date record is less than 1914 . the sum of the no built record of these rows is 910 .'} | round_eq { sum { filter_less { all_rows ; date ; 1914 } ; no built } ; 910 } = true | select the rows whose date record is less than 1914 . the sum of the no built record of these rows is 910 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'sum_1': 1, 'filter_less_0': 0, 'all_rows_4': 4, 'date_5': 5, '1914_6': 6, 'no built_7': 7, '910_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'sum_1': 'sum', 'filter_less_0': 'filter_less', 'all_rows_4': 'all_rows', 'date_5': 'date', '1914_6': '1914', 'no built_7': 'no built', '910_8': '910'} | {'eq_2': [3], 'result_3': [], 'sum_1': [2], 'filter_less_0': [1], 'all_rows_4': [0], 'date_5': [0], '1914_6': [0], 'no built_7': [1], '910_8': [2]} | ['class', 'wheels', 'date', 'builder', 'no built'] | [['g', '4 - 4 - 0', '1900', 'neilson', '5'], ['c', '0 - 6 - 0', '1900 - 4', 'secr ashford ( 70 )', '109'], ['c', '0 - 6 - 0', '1901 - 4', 'lcdr longhedge ( 9 )', '109'], ['c', '0 - 6 - 0', '1900', 'neilson ( 15 )', '109'], ['c', '0 - 6 - 0', '1900', 'sharp stewart ( 15 )', '109'], ['r1', '0 - 4 - 4t', '1900', 'sharp stewart', '15'], ['h', '0 - 4 - 4t', '1904 - 15', 'secr ashford', '66'], ['d', '4 - 4 - 0', '1901', 'sharp stewart ( 10 )', '51'], ['d', '4 - 4 - 0', '1903', 'stephenson ( 5 )', '51'], ['d', '4 - 4 - 0', '1903', 'vulcan foundry ( 5 )', '51'], ['d', '4 - 4 - 0', '1903', 'dã ¼ bs ( 10 )', '51'], ['d', '4 - 4 - 0', '1901 - 7', 'secr ashford ( 21 )', '51'], ['terrier', '0 - 6 - 0t', '1875', 'lbscr brighton', '50'], ['e', '4 - 4 - 0', '1905 - 10', 'secr ashford', '26'], ['p', '0 - 6 - 0t', '1909 - 10', 'secr ashford', '8'], ['j', '0 - 6 - 4t', '1913', 'secr ashford', '5'], ['l', '4 - 4 - 0', '1914', 'borsig ( 10 )', '22'], ['l', '4 - 4 - 0', '1914', 'beyer - peacock ( 12 )', '22']] |
madawaska county , new brunswick | https://en.wikipedia.org/wiki/Madawaska_County%2C_New_Brunswick | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-171250-2.html.csv | majority | most of the parishes of madawaska county , new brunswick , have a population over 200 . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'greater_than', 'value': '200', 'subset': None} | {'func': 'most_greater', 'args': ['all_rows', 'population', '200'], 'result': True, 'ind': 0, 'tointer': 'for the population records of all rows , most of them are greater than 200 .', 'tostr': 'most_greater { all_rows ; population ; 200 } = true'} | most_greater { all_rows ; population ; 200 } = true | for the population records of all rows , most of them are greater than 200 . | 1 | 1 | {'most_greater_0': 0, 'result_1': 1, 'all_rows_2': 2, 'population_3': 3, '200_4': 4} | {'most_greater_0': 'most_greater', 'result_1': 'true', 'all_rows_2': 'all_rows', 'population_3': 'population', '200_4': '200'} | {'most_greater_0': [1], 'result_1': [], 'all_rows_2': [0], 'population_3': [0], '200_4': [0]} | ['official name', 'status', 'area km 2', 'population', 'census ranking'] | [['saint - joseph', 'parish', '321.87', '1696', '1472 of 5008'], ['saint - jacques', 'parish', '298.82', '1607', '1531 of 5008'], ['sainte - anne', 'parish', '369.25', '1081', '1942 of 5008'], ['saint - léonard', 'parish', '343.95', '1039', '2011 of 5008'], ['saint - basile', 'parish', '129.73', '799', '2364 of 5008'], ['rivière - verte', 'parish', '715.58', '791', '2384 of 5008'], ['saint - françois', 'parish', '344.70', '754', '2458 of 5008'], ['lac - baker', 'parish', '57.38', '566', '2847 of 5008'], ['saint - hilaire', 'parish', '41.55', '531', '2928 of 5008'], ['notre - dame - de - lourdes', 'parish', '188.63', '284', '3729 of 5008'], ['clair', 'parish', '44.29', '282', '3737 of 5008'], ['baker brook', 'parish', '125.69', '177', '4103 of 5008'], ['madawaska', 'parish', '173.32', '10', '4889 of 5008']] |
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 | majority | most of the start sources of the 2008-09 cardiff city f.c. season were bbc sport . | {'scope': 'all', 'col': '9', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'bbc sport', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'start source', 'bbc sport'], 'result': True, 'ind': 0, 'tointer': 'for the start source records of all rows , most of them fuzzily match to bbc sport .', 'tostr': 'most_eq { all_rows ; start source ; bbc sport } = true'} | most_eq { all_rows ; start source ; bbc sport } = true | for the start source records of all rows , most of them fuzzily match to bbc sport . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'start source_3': 3, 'bbc sport_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'start source_3': 'start source', 'bbc sport_4': 'bbc sport'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'start source_3': [0], 'bbc sport_4': [0]} | ['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']] |
european orienteering championships | https://en.wikipedia.org/wiki/European_Orienteering_Championships | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17760670-3.html.csv | unique | the year 2000 is the only year that brigitte wolf won the silver medal in the european orienteering championships . | {'scope': 'all', 'row': '3', 'col': '3', 'col_other': '1', 'criterion': 'equal', 'value': 'brigitte wolf', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'silver', 'brigitte wolf'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose silver record fuzzily matches to brigitte wolf .', 'tostr': 'filter_eq { all_rows ; silver ; brigitte wolf }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; silver ; brigitte wolf } }', 'tointer': 'select the rows whose silver record fuzzily matches to brigitte wolf . there is only one such row in the table .'}, {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'silver', 'brigitte wolf'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose silver record fuzzily matches to brigitte wolf .', 'tostr': 'filter_eq { all_rows ; silver ; brigitte wolf }'}, 'year'], 'result': '2000', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; silver ; brigitte wolf } ; year }'}, '2000'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; silver ; brigitte wolf } ; year } ; 2000 }', 'tointer': 'the year record of this unqiue row is 2000 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; silver ; brigitte wolf } } ; eq { hop { filter_eq { all_rows ; silver ; brigitte wolf } ; year } ; 2000 } } = true', 'tointer': 'select the rows whose silver record fuzzily matches to brigitte wolf . there is only one such row in the table . the year record of this unqiue row is 2000 .'} | and { only { filter_eq { all_rows ; silver ; brigitte wolf } } ; eq { hop { filter_eq { all_rows ; silver ; brigitte wolf } ; year } ; 2000 } } = true | select the rows whose silver record fuzzily matches to brigitte wolf . there is only one such row in the table . the year record of this unqiue row is 2000 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'silver_7': 7, 'brigitte wolf_8': 8, 'eq_3': 3, 'num_hop_2': 2, 'year_9': 9, '2000_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'silver_7': 'silver', 'brigitte wolf_8': 'brigitte wolf', 'eq_3': 'eq', 'num_hop_2': 'num_hop', 'year_9': 'year', '2000_10': '2000'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'silver_7': [0], 'brigitte wolf_8': [0], 'eq_3': [4], 'num_hop_2': [3], 'year_9': [2], '2000_10': [3]} | ['year', 'gold', 'silver', 'bronze', 'notes'] | [['1962', 'ulla lindkvist', 'marit ãkern', 'emy gauffin', '7.5 km , 7controls ( individual event )'], ['1964', 'margrit thommen', 'ann - marie wallsten', 'ulla lindkvist', '8.1 km , 10controls ( individual event )'], ['2000', 'hanne staff', 'brigitte wolf', 'yvette baker', 'classic distance'], ['2002', 'simone niggli - luder', 'hanne staff', 'birgitte husebye', '6.7 km , 17controls'], ['2004', 'simone niggli - luder', 'emma engstrand', 'tatiana ryabkina', '9.6 km , 21controls'], ['2006', 'simone niggli - luder', 'heli jukkola', 'minna kauppi', '10.93 km , 25controls'], ['2008', 'anne margrethe hausken', 'tatiana ryabkina', 'emma engstrand', '11.0 km , 24controls'], ['2010', 'simone niggli - luder', 'dana brozkova', 'helena jansson', '11.0 km , 26controls'], ['2012', 'simone niggli - luder', 'tatiana ryabkina', 'minna kauppi', '9.76 km , 24controls']] |
economy of south america | https://en.wikipedia.org/wiki/Economy_of_South_America | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1222653-10.html.csv | aggregation | the economy of south america has a total of 8429.43027 usd . | {'scope': 'all', 'col': '4', 'type': 'sum', 'result': '8429.43027', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', '1 usd ='], 'result': '8429.43027', 'ind': 0, 'tostr': 'sum { all_rows ; 1 usd = }'}, '8429.43027'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; 1 usd = } ; 8429.43027 } = true', 'tointer': 'the sum of the 1 usd = record of all rows is 8429.43027 .'} | round_eq { sum { all_rows ; 1 usd = } ; 8429.43027 } = true | the sum of the 1 usd = record of all rows is 8429.43027 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, '1 usd =_4': 4, '8429.43027_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', '1 usd =_4': '1 usd =', '8429.43027_5': '8429.43027'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], '1 usd =_4': [0], '8429.43027_5': [1]} | ['country', 'currency', '1 euro =', '1 usd =', 'central bank'] | [['argentina', 'argentine peso ( ars )', '5.72079', '4.34950', 'central bank of argentina'], ['bolivia', 'bolivian boliviano ( bob )', '9.02081', '6.86000', 'central bank of bolivia'], ['brazil', 'brazilian real ( brl )', '2.25592', '1.71577', 'central bank of brazil'], ['chile', 'chilean peso ( clp )', '635.134', '483.050', 'central bank of chile'], ['colombia', 'colombian peso ( cop )', '2353.40', '1790.00', 'bank of the republic'], ['ecuador', 'us dollar ( usd )', '1.46611', '1', 'federal reserve'], ['guyana', 'guyanese dollar ( gyd )', '264.192', '200.950', 'bank of guyana'], ['paraguay', 'paraguayan guaranã\xad ( pyg )', '4500.00', '5916.27', 'central bank of paraguay'], ['peru', 'peruvian nuevo sol ( pen )', '3.53004', '2.68500', 'central reserve bank of peru'], ['suriname', 'surinamese dollar ( srd )', '4.27296', '3.25000', 'central bank of suriname'], ['uruguay', 'uruguayan peso ( uyu )', '25.3797', '19.3000', 'central bank of uruguay']] |
robby gordon | https://en.wikipedia.org/wiki/Robby_Gordon | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1507423-4.html.csv | count | robby gordon had top five placings in ten different years . | {'scope': 'all', 'criterion': 'not_equal', 'value': '0', 'result': '10', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_not_eq', 'args': ['all_rows', 'top 5', '0'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose top 5 record is not equal to 0 .', 'tostr': 'filter_not_eq { all_rows ; top 5 ; 0 }'}], 'result': '10', 'ind': 1, 'tostr': 'count { filter_not_eq { all_rows ; top 5 ; 0 } }', 'tointer': 'select the rows whose top 5 record is not equal to 0 . the number of such rows is 10 .'}, '10'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_not_eq { all_rows ; top 5 ; 0 } } ; 10 } = true', 'tointer': 'select the rows whose top 5 record is not equal to 0 . the number of such rows is 10 .'} | eq { count { filter_not_eq { all_rows ; top 5 ; 0 } } ; 10 } = true | select the rows whose top 5 record is not equal to 0 . the number of such rows is 10 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_not_eq_0': 0, 'all_rows_4': 4, 'top 5_5': 5, '0_6': 6, '10_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_not_eq_0': 'filter_not_eq', 'all_rows_4': 'all_rows', 'top 5_5': 'top 5', '0_6': '0', '10_7': '10'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_not_eq_0': [1], 'all_rows_4': [0], 'top 5_5': [0], '0_6': [0], '10_7': [2]} | ['year', 'starts', 'wins', 'top 5', 'top 10', 'poles', 'avg start', 'avg finish', 'winnings', 'position', 'team ( s )'] | [['1991', '2', '0', '0', '0', '0', '35.0', '22.0', '27625', '55th', '90 donlavey racing'], ['1993', '1', '0', '0', '0', '0', '14.0', '42.0', '17665', '93rd', '28 robert yates racing'], ['1994', '1', '0', '0', '0', '0', '38.0', '38.0', '7965', '76th', '07 kranefuss - haas racing'], ['1996', '3', '0', '0', '0', '0', '17.3', '40.7', '33915', '57th', '14 dale earnhardt inc 40 team sabco'], ['1997', '20', '0', '1', '1', '1', '25.3', '29.6', '622439', '40th', '40 team sabco'], ['1998', '1', '0', '0', '0', '0', '18.0', '37.0', '24765', '67th', '96 american equipment racing'], ['2000', '17', '0', '1', '2', '0', '29.9', '29.2', '620781', '43rd', '13 team menard'], ['2002', '36', '0', '1', '5', '0', '18.4', '21.1', '3342703', '20th', '31 richard childress racing'], ['2003', '36', '2', '4', '10', '0', '23.1', '19.7', '4157064', '16th', '31 richard childress racing'], ['2004', '36', '0', '2', '6', '0', '23.2', '21.2', '4225719', '23rd', '31 richard childress racing'], ['2005', '29', '0', '1', '2', '0', '27.0', '30.1', '2271313', '37th', '7 robby gordon motorsports'], ['2006', '36', '0', '1', '3', '0', '27.5', '25.3', '3143787', '30th', '7 robby gordon motorsports'], ['2007', '35', '0', '1', '2', '0', '33.9', '25.8', '3090004', '26th', '7 robby gordon motorsports'], ['2008', '36', '0', '0', '3', '0', '30.9', '29.0', '3816362', '33rd', '7 robby gordon motorsports'], ['2009', '35', '0', '1', '1', '0', '30.1', '28.5', '3860582', '34th', '7 robby gordon motorsports'], ['2010', '27', '0', '1', '1', '0', '33.8', '29.1', '2913816', '34th', '7 / 07 robby gordon motorsports'], ['2011', '25', '0', '0', '0', '0', '36.5', '33.4', '2271891', '34th', '7 robby gordon motorsports']] |
2007 new orleans voodoo season | https://en.wikipedia.org/wiki/2007_New_Orleans_VooDoo_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11783481-3.html.csv | aggregation | the total combined amount of yards by players in the 2007 new orleans voodoo season was 178 . | {'scope': 'all', 'col': '3', 'type': 'sum', 'result': '178', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'yards'], 'result': '178', 'ind': 0, 'tostr': 'sum { all_rows ; yards }'}, '178'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; yards } ; 178 } = true', 'tointer': 'the sum of the yards record of all rows is 178 .'} | round_eq { sum { all_rows ; yards } ; 178 } = true | the sum of the yards record of all rows is 178 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'yards_4': 4, '178_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'yards_4': 'yards', '178_5': '178'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'yards_4': [0], '178_5': [1]} | ['player', 'car', 'yards', 'avg', "td 's", 'long'] | [['dan curran', '27', '60', '2.2', '3', '13'], ['steve bellisari', '30', '54', '1.8', '7', '20'], ['james lynch', '26', '47', '1.8', '5', '15'], ['henry bryant', '14', '8', '0.6', '1', '2'], ['kenny henderson', '5', '7', '1.4', '2', '6'], ['andy kelly', '5', '0', '0', '0', '0'], ['wendall williams', '1', '2', '2', '0', '2']] |
2008 national league 1 | https://en.wikipedia.org/wiki/2008_National_League_1 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-19179465-1.html.csv | majority | all teams which participated in the 2008 national league 1 season games each played 18 matches . | {'scope': 'all', 'col': '3', 'most_or_all': 'all', 'criterion': 'equal', 'value': '18', 'subset': None} | {'func': 'all_eq', 'args': ['all_rows', 'played', '18'], 'result': True, 'ind': 0, 'tointer': 'for the played records of all rows , all of them are equal to 18 .', 'tostr': 'all_eq { all_rows ; played ; 18 } = true'} | all_eq { all_rows ; played ; 18 } = true | for the played records of all rows , all of them are equal to 18 . | 1 | 1 | {'all_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'played_3': 3, '18_4': 4} | {'all_eq_0': 'all_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'played_3': 'played', '18_4': '18'} | {'all_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'played_3': [0], '18_4': [0]} | ['position', 'club', 'played', 'won', 'drawn', 'lost', 'pts for', 'pts agst', 'pts diff', 'bp', 'points'] | [['1', 'salford city reds', '18', '12', '3', '3', '614', '302', '312', '3', '45'], ['2', 'celtic crusaders', '18', '12', '0', '6', '511', '391', '120', '4', '40'], ['3', 'halifax', '18', '11', '1', '6', '634', '514', '120', '3', '38'], ['4', 'leigh centurions', '18', '10', '0', '8', '448', '448', '0', '4', '34'], ['5', 'whitehaven', '18', '10', '0', '8', '420', '399', '21', '2', '32'], ['6', 'widnes vikings', '18', '10', '2', '6', '453', '410', '43', '5', '30'], ['7', 'sheffield eagles', '18', '8', '1', '9', '425', '530', '- 105', '3', '29'], ['8', 'featherstone rovers', '18', '6', '1', '11', '452', '515', '- 63', '6', '26'], ['9', 'batley bulldogs', '18', '5', '0', '13', '387', '538', '- 151', '8', '23']] |
canoeing at the 2008 summer olympics - men 's c - 1 1000 metres | https://en.wikipedia.org/wiki/Canoeing_at_the_2008_Summer_Olympics_%E2%80%93_Men%27s_C-1_1000_metres | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18646220-4.html.csv | comparative | the competitor from france was faster than the one from russia in the men 's 1000 meter canoeing event in the 2008 olympics . | {'row_1': '2', 'row_2': '5', 'col': '4', 'col_other': '3', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'france'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose country record fuzzily matches to france .', 'tostr': 'filter_eq { all_rows ; country ; france }'}, 'time'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; country ; france } ; time }', 'tointer': 'select the rows whose country record fuzzily matches to france . take the time record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'russia'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose country record fuzzily matches to russia .', 'tostr': 'filter_eq { all_rows ; country ; russia }'}, 'time'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; country ; russia } ; time }', 'tointer': 'select the rows whose country record fuzzily matches to russia . take the time record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; country ; france } ; time } ; hop { filter_eq { all_rows ; country ; russia } ; time } } = true', 'tointer': 'select the rows whose country record fuzzily matches to france . take the time record of this row . select the rows whose country record fuzzily matches to russia . take the time record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; country ; france } ; time } ; hop { filter_eq { all_rows ; country ; russia } ; time } } = true | select the rows whose country record fuzzily matches to france . take the time record of this row . select the rows whose country record fuzzily matches to russia . take the time record of this row . the first record is less than the second record . | 5 | 5 | {'less_4': 4, 'result_5': 5, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'country_7': 7, 'france_8': 8, 'time_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'country_11': 11, 'russia_12': 12, 'time_13': 13} | {'less_4': 'less', 'result_5': 'true', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'country_7': 'country', 'france_8': 'france', 'time_9': 'time', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'country_11': 'country', 'russia_12': 'russia', 'time_13': 'time'} | {'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'country_7': [0], 'france_8': [0], 'time_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'country_11': [1], 'russia_12': [1], 'time_13': [3]} | ['rank', 'athletes', 'country', 'time', 'notes'] | [['1', 'vadim menkov', 'uzbekistan', '3:56.793', 'qf'], ['2', 'mathieu goubel', 'france', '3:56.972', 'qs'], ['3', 'marián ostrčil', 'slovakia', '4:00.191', 'qs'], ['4', 'aliaksandr zhukouski', 'belarus', '4:01.380', 'qs'], ['5', 'viktor melantiev', 'russia', '4:03.316', 'qs'], ['6', 'nivalter santos', 'brazil', '4:17.407', 'qs'], ['7', 'mikhail yemelyanov', 'kazakhstan', '4:19.259', 'qs']] |
1985 los angeles rams season | https://en.wikipedia.org/wiki/1985_Los_Angeles_Rams_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11157122-2.html.csv | ordinal | the attendance at the third game the los angeles rams lost was 29960 . | {'scope': 'subset', 'row': '11', 'col': '2', 'order': '3', 'col_other': '4,9', 'max_or_min': 'min_to_max', 'value_mentioned': 'yes', 'subset': {'col': '4', 'criterion': 'equal', 'value': 'l'}} | {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'nth_min', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'result', 'l'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; result ; l }', 'tointer': 'select the rows whose result record fuzzily matches to l .'}, 'date', '3'], 'result': 'november 17 , 1985', 'ind': 1, 'tostr': 'nth_min { filter_eq { all_rows ; result ; l } ; date ; 3 }', 'tointer': 'select the rows whose result record fuzzily matches to l . the 3rd minimum date record of these rows is november 17 , 1985 .'}, 'november 17 , 1985'], 'result': True, 'ind': 2, 'tostr': 'eq { nth_min { filter_eq { all_rows ; result ; l } ; date ; 3 } ; november 17 , 1985 }', 'tointer': 'select the rows whose result record fuzzily matches to l . the 3rd minimum date record of these rows is november 17 , 1985 .'}, {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'nth_argmin', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'result', 'l'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; result ; l }', 'tointer': 'select the rows whose result record fuzzily matches to l .'}, 'date', '3'], 'result': None, 'ind': 3, 'tostr': 'nth_argmin { filter_eq { all_rows ; result ; l } ; date ; 3 }'}, 'attendance'], 'result': '29960', 'ind': 4, 'tostr': 'hop { nth_argmin { filter_eq { all_rows ; result ; l } ; date ; 3 } ; attendance }'}, '29960'], 'result': True, 'ind': 5, 'tostr': 'eq { hop { nth_argmin { filter_eq { all_rows ; result ; l } ; date ; 3 } ; attendance } ; 29960 }', 'tointer': 'the attendance record of the row with 3rd minimum date record is 29960 .'}], 'result': True, 'ind': 6, 'tostr': 'and { eq { nth_min { filter_eq { all_rows ; result ; l } ; date ; 3 } ; november 17 , 1985 } ; eq { hop { nth_argmin { filter_eq { all_rows ; result ; l } ; date ; 3 } ; attendance } ; 29960 } } = true', 'tointer': 'select the rows whose result record fuzzily matches to l . the 3rd minimum date record of these rows is november 17 , 1985 . the attendance record of the row with 3rd minimum date record is 29960 .'} | and { eq { nth_min { filter_eq { all_rows ; result ; l } ; date ; 3 } ; november 17 , 1985 } ; eq { hop { nth_argmin { filter_eq { all_rows ; result ; l } ; date ; 3 } ; attendance } ; 29960 } } = true | select the rows whose result record fuzzily matches to l . the 3rd minimum date record of these rows is november 17 , 1985 . the attendance record of the row with 3rd minimum date record is 29960 . | 8 | 7 | {'and_6': 6, 'result_7': 7, 'eq_2': 2, 'nth_min_1': 1, 'filter_str_eq_0': 0, 'all_rows_8': 8, 'result_9': 9, 'l_10': 10, 'date_11': 11, '3_12': 12, 'november 17 , 1985_13': 13, 'eq_5': 5, 'num_hop_4': 4, 'nth_argmin_3': 3, 'date_14': 14, '3_15': 15, 'attendance_16': 16, '29960_17': 17} | {'and_6': 'and', 'result_7': 'true', 'eq_2': 'eq', 'nth_min_1': 'nth_min', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_8': 'all_rows', 'result_9': 'result', 'l_10': 'l', 'date_11': 'date', '3_12': '3', 'november 17 , 1985_13': 'november 17 , 1985', 'eq_5': 'eq', 'num_hop_4': 'num_hop', 'nth_argmin_3': 'nth_argmin', 'date_14': 'date', '3_15': '3', 'attendance_16': 'attendance', '29960_17': '29960'} | {'and_6': [7], 'result_7': [], 'eq_2': [6], 'nth_min_1': [2], 'filter_str_eq_0': [1, 3], 'all_rows_8': [0], 'result_9': [0], 'l_10': [0], 'date_11': [1], '3_12': [1], 'november 17 , 1985_13': [2], 'eq_5': [6], 'num_hop_4': [5], 'nth_argmin_3': [4], 'date_14': [3], '3_15': [3], 'attendance_16': [4], '29960_17': [5]} | ['game', 'date', 'opponent', 'result', 'rams points', 'opponents', 'record', 'venue', 'attendance'] | [['1', 'september 8 , 1985', 'denver broncos', 'w', '20', '16', '1 - 0', 'anaheim stadium', '52522'], ['2', 'september 15 , 1985', 'philadelphia eagles', 'w', '17', '6', '2 - 0', 'veterans stadium', '60920'], ['3', 'september 23 , 1985', 'seattle seahawks', 'w', '35', '24', '3 - 0', 'kingdome', '63292'], ['4', 'september 29 , 1985', 'atlanta falcons', 'w', '17', '6', '4 - 0', 'anaheim stadium', '49870'], ['5', 'october 6 , 1985', 'minnesota vikings', 'w', '13', '10', '5 - 0', 'anaheim stadium', '61139'], ['6', 'october 13 , 1985', 'tampa bay buccaneers', 'w', '31', '27', '6 - 0', 'tampa stadium', '39607'], ['7', 'october 20 , 1985', 'kansas city chiefs', 'w', '16', '0', '7 - 0', 'arrowhead stadium', '64474'], ['8', 'october 27 , 1985', 'san francisco 49ers', 'l', '14', '28', '7 - 1', 'anaheim stadium', '65939'], ['9', 'november 3 , 1985', 'new orleans saints', 'w', '28', '10', '8 - 1', 'anaheim stadium', '49030'], ['10', 'november 10 , 1985', 'new york giants', 'l', '19', '24', '8 - 2', 'giants stadium', '74663'], ['11', 'november 17 , 1985', 'atlanta falcons', 'l', '14', '30', '8 - 3', 'atlanta - fulton county stadium', '29960'], ['12', 'november 24 , 1985', 'green bay packers', 'w', '34', '17', '9 - 3', 'anaheim stadium', '52710'], ['13', 'december 1 , 1985', 'new orleans saints', 'l', '3', '29', '9 - 4', 'louisiana superdome', '44122'], ['14', 'december 9 , 1985', 'san francisco 49ers', 'w', '27', '20', '10 - 4', 'candlestick park', '60581'], ['15', 'december 15 , 1985', 'st louis cardinals', 'w', '46', '14', '11 - 4', 'anaheim stadium', '52052'], ['16', 'december 23 , 1985', 'los angeles raiders', 'l', '6', '16', '11 - 5', 'anaheim stadium', '66676'], ['divisional playoff', 'january 4 , 1986', 'dallas cowboys', 'w', '20', '0', '12 - 5', 'anaheim stadium', '66351'], ['conference championship', 'january 12 , 1986', 'chicago bears', 'l', '0', '24', '12 - 6', 'soldier field', '65522']] |
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