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ect mainline rail | https://en.wikipedia.org/wiki/ECT_Mainline_Rail | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15805928-1.html.csv | majority | all of the rails are a class thirty one rail . | {'scope': 'all', 'col': '2', 'most_or_all': 'all', 'criterion': 'equal', 'value': '31', 'subset': None} | {'func': 'all_eq', 'args': ['all_rows', 'class', '31'], 'result': True, 'ind': 0, 'tointer': 'for the class records of all rows , all of them are equal to 31 .', 'tostr': 'all_eq { all_rows ; class ; 31 } = true'} | all_eq { all_rows ; class ; 31 } = true | for the class records of all rows , all of them are equal to 31 . | 1 | 1 | {'all_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'class_3': 3, '31_4': 4} | {'all_eq_0': 'all_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'class_3': 'class', '31_4': '31'} | {'all_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'class_3': [0], '31_4': [0]} | ['number', 'class', 'name', 'livery', 'notes'] | [['31128', '31', 'charybdis', 'fragonset black', 'now operated by nemesis rail'], ['31452', '31', 'minotaur', 'fragonset black', 'now operated by network rail'], ['31454', '31', 'the heart of wessex', 'intercity swallow', 'now operated by network rail'], ['31468', '31', 'hydra', 'fragonset black', 'now operated by network rail'], ['31601', '31', 'gauge o guild', 'wessex trains pink', 'now operated by network rail']] |
list of all that episodes | https://en.wikipedia.org/wiki/List_of_All_That_episodes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2655016-10.html.csv | unique | of the all that episodes from 2004 , the only one from season 15 was titled aaron carter . | {'scope': 'subset', 'row': '14', 'col': '1', 'col_other': '3', 'criterion': 'equal', 'value': '15', 'subset': {'col': '4', 'criterion': 'fuzzily_match', 'value': '2004'}} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'original air date', '2004'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; original air date ; 2004 }', 'tointer': 'select the rows whose original air date record fuzzily matches to 2004 .'}, 'season', '15'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose original air date record fuzzily matches to 2004 . among these rows , select the rows whose season record is equal to 15 .', 'tostr': 'filter_eq { filter_eq { all_rows ; original air date ; 2004 } ; season ; 15 }'}], 'result': True, 'ind': 2, 'tostr': 'only { filter_eq { filter_eq { all_rows ; original air date ; 2004 } ; season ; 15 } }', 'tointer': 'select the rows whose original air date record fuzzily matches to 2004 . among these rows , select the rows whose season record is equal to 15 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'original air date', '2004'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; original air date ; 2004 }', 'tointer': 'select the rows whose original air date record fuzzily matches to 2004 .'}, 'season', '15'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose original air date record fuzzily matches to 2004 . among these rows , select the rows whose season record is equal to 15 .', 'tostr': 'filter_eq { filter_eq { all_rows ; original air date ; 2004 } ; season ; 15 }'}, 'episode title'], 'result': 'aaron carter', 'ind': 3, 'tostr': 'hop { filter_eq { filter_eq { all_rows ; original air date ; 2004 } ; season ; 15 } ; episode title }'}, 'aaron carter'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { filter_eq { filter_eq { all_rows ; original air date ; 2004 } ; season ; 15 } ; episode title } ; aaron carter }', 'tointer': 'the episode title record of this unqiue row is aaron carter .'}], 'result': True, 'ind': 5, 'tostr': 'and { only { filter_eq { filter_eq { all_rows ; original air date ; 2004 } ; season ; 15 } } ; eq { hop { filter_eq { filter_eq { all_rows ; original air date ; 2004 } ; season ; 15 } ; episode title } ; aaron carter } } = true', 'tointer': 'select the rows whose original air date record fuzzily matches to 2004 . among these rows , select the rows whose season record is equal to 15 . there is only one such row in the table . the episode title record of this unqiue row is aaron carter .'} | and { only { filter_eq { filter_eq { all_rows ; original air date ; 2004 } ; season ; 15 } } ; eq { hop { filter_eq { filter_eq { all_rows ; original air date ; 2004 } ; season ; 15 } ; episode title } ; aaron carter } } = true | select the rows whose original air date record fuzzily matches to 2004 . among these rows , select the rows whose season record is equal to 15 . there is only one such row in the table . the episode title record of this unqiue row is aaron carter . | 8 | 6 | {'and_5': 5, 'result_6': 6, 'only_2': 2, 'filter_eq_1': 1, 'filter_str_eq_0': 0, 'all_rows_7': 7, 'original air date_8': 8, '2004_9': 9, 'season_10': 10, '15_11': 11, 'str_eq_4': 4, 'str_hop_3': 3, 'episode title_12': 12, 'aaron carter_13': 13} | {'and_5': 'and', 'result_6': 'true', 'only_2': 'only', 'filter_eq_1': 'filter_eq', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_7': 'all_rows', 'original air date_8': 'original air date', '2004_9': '2004', 'season_10': 'season', '15_11': '15', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'episode title_12': 'episode title', 'aaron carter_13': 'aaron carter'} | {'and_5': [6], 'result_6': [], 'only_2': [5], 'filter_eq_1': [2, 3], 'filter_str_eq_0': [1], 'all_rows_7': [0], 'original air date_8': [0], '2004_9': [0], 'season_10': [1], '15_11': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'episode title_12': [3], 'aaron carter_13': [4]} | ['season', 'series', 'episode title', 'original air date', 'nick prod'] | [['1', '139', 'lillix', 'october 11 , 2003', '941'], ['2', '140', 'nodesha', 'october 18 , 2003', '942'], ['3', '141', 'da razkalz cru', 'october 25 , 2003', '943'], ['4', '142', 'third eye blind', 'november 1 , 2003', '944'], ['5', '143', 'fefe dobson', 'november 22 , 2003', '945'], ['7', '145', 'drake bell', 'january 10 , 2004', '947'], ['8', '146', 'ok go', 'january 24 , 2004', '948'], ['9', '147', 'britney spears / nick cannon', 'january 31 , 2004', '949'], ['10', '148', 'brittany snow / wakefield', 'february 7 , 2004', '950'], ['11', '149', 'boomkat', 'february 14 , 2004', '951'], ['12', '150', 'nick lachey', 'april 17 , 2004', '952'], ['13', '151', 'avril lavigne', 'june 12 , 2004', '953'], ['14', '152', 'substitute jack', 'june 19 , 2004', '954'], ['15', '153', 'aaron carter', 'june 26 , 2004', '955']] |
suburban league | https://en.wikipedia.org/wiki/Suburban_League | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-28051859-3.html.csv | unique | of the schools in the suburban league , only mogadore has the colors green and white . | {'scope': 'all', 'row': '6', 'col': '4', 'col_other': '1', 'criterion': 'equal', 'value': 'green , white', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'colors', 'green , white'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose colors record fuzzily matches to green , white .', 'tostr': 'filter_eq { all_rows ; colors ; green , white }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; colors ; green , white } }', 'tointer': 'select the rows whose colors record fuzzily matches to green , white . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'colors', 'green , white'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose colors record fuzzily matches to green , white .', 'tostr': 'filter_eq { all_rows ; colors ; green , white }'}, 'school'], 'result': 'mogadore', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; colors ; green , white } ; school }'}, 'mogadore'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; colors ; green , white } ; school } ; mogadore }', 'tointer': 'the school record of this unqiue row is mogadore .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; colors ; green , white } } ; eq { hop { filter_eq { all_rows ; colors ; green , white } ; school } ; mogadore } } = true', 'tointer': 'select the rows whose colors record fuzzily matches to green , white . there is only one such row in the table . the school record of this unqiue row is mogadore .'} | and { only { filter_eq { all_rows ; colors ; green , white } } ; eq { hop { filter_eq { all_rows ; colors ; green , white } ; school } ; mogadore } } = true | select the rows whose colors record fuzzily matches to green , white . there is only one such row in the table . the school record of this unqiue row is mogadore . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'colors_7': 7, 'green , white_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'school_9': 9, 'mogadore_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'colors_7': 'colors', 'green , white_8': 'green , white', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'school_9': 'school', 'mogadore_10': 'mogadore'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'colors_7': [0], 'green , white_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'school_9': [2], 'mogadore_10': [3]} | ['school', 'nickname', 'location', 'colors', 'tenure'] | [['barberton', 'magics', 'barberton , summit county', 'purple , white', '2005 - 2011'], ['coventry', 'comets', 'coventry twp , summit county', 'blue , gold', '1969 - 1983'], ['field', 'falcons', 'brimfield , portage county', 'red , white , black', '1978 - 1990'], ['hudson', 'explorers', 'hudson , summit county', 'navy blue , white', '1949 - 1997'], ['manchester', 'panthers', 'new franklin , summit county', 'red , black', '1949 - 1976'], ['mogadore', 'wildcats', 'mogadore , portage county', 'green , white', '1958 - 1968'], ['norton', 'panthers', 'norton , summit county', 'red , black , white', '1972 - 2005'], ['twinsburg', 'tigers', 'twinsburg , summit county', 'blue , white', '1958 - 1964']] |
ana jovanović | https://en.wikipedia.org/wiki/Ana_Jovanovi%C4%87 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12326046-2.html.csv | unique | the opole tournament was the only one in which ana jovanović used a carpet ( i ) surface . | {'scope': 'all', 'row': '13', 'col': '4', 'col_other': '3', 'criterion': 'equal', 'value': 'carpet ( i )', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'surface', 'carpet ( i )'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose surface record fuzzily matches to carpet ( i ) .', 'tostr': 'filter_eq { all_rows ; surface ; carpet ( i ) }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; surface ; carpet ( i ) } }', 'tointer': 'select the rows whose surface record fuzzily matches to carpet ( i ) . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'surface', 'carpet ( i )'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose surface record fuzzily matches to carpet ( i ) .', 'tostr': 'filter_eq { all_rows ; surface ; carpet ( i ) }'}, 'tournament'], 'result': 'opole', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; surface ; carpet ( i ) } ; tournament }'}, 'opole'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; surface ; carpet ( i ) } ; tournament } ; opole }', 'tointer': 'the tournament record of this unqiue row is opole .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; surface ; carpet ( i ) } } ; eq { hop { filter_eq { all_rows ; surface ; carpet ( i ) } ; tournament } ; opole } } = true', 'tointer': 'select the rows whose surface record fuzzily matches to carpet ( i ) . there is only one such row in the table . the tournament record of this unqiue row is opole .'} | and { only { filter_eq { all_rows ; surface ; carpet ( i ) } } ; eq { hop { filter_eq { all_rows ; surface ; carpet ( i ) } ; tournament } ; opole } } = true | select the rows whose surface record fuzzily matches to carpet ( i ) . there is only one such row in the table . the tournament record of this unqiue row is opole . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'surface_7': 7, 'carpet (i)_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'tournament_9': 9, 'opole_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'surface_7': 'surface', 'carpet (i)_8': 'carpet ( i )', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'tournament_9': 'tournament', 'opole_10': 'opole'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'surface_7': [0], 'carpet (i)_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'tournament_9': [2], 'opole_10': [3]} | ['outcome', 'date', 'tournament', 'surface', 'opponent', 'score'] | [['winner', '13 october 2002', 'ain alsouknha', 'clay', 'aurelija miseviciute', '6 - 4 , 6 - 1'], ['winner', '27 october 2002', 'al mansoura', 'clay', 'ema janašková', '4 - 6 , 6 - 3 , 6 - 2'], ['winner', '4 july 2004', 'bibione', 'clay', 'sabrina jolk', '6 - 3 , 6 - 3'], ['ru', '27 march 2005', 'rome', 'clay', 'romina oprandi', '4 - 6 , 6 ( 4 ) - 7'], ['ru', '24 july 2005', 'palić', 'clay', 'miljana adanko', '5 - 7 , 1 - 6'], ['not played', '30 april 2006', 'herceg novi', 'clay', 'zorica petrov', 'np'], ['winner', '14 may 2006', 'mostar', 'clay', 'ani mijačika', '6 - 2 , 6 - 4'], ['winner', '25 march 2007', 'athens', 'hard', 'neuza silva', '6 - 3 , 4 - 6 , 6 - 3'], ['winner', '24 june 2007', 'sarajevo', 'clay', 'davinia lobbinger', '6 - 4 , 6 - 4'], ['winner', '5 august 2007', 'bad saulgau', 'clay', 'kathrin wörle', '7 - 5 , 4 - 6 , 7 - 5'], ['ru', '7 june 2009', 'sarajevo', 'clay', 'ivana lisjak', '0 - 6 , 6 ( 10 ) - 7'], ['ru', '2 august 2009', 'bad saulgau', 'clay', 'andrea hlaváčková', '4 - 6 , 4 - 6'], ['ru', '22 november 2009', 'opole', 'carpet ( i )', 'sandra záhlavová', '0 - 6 , 2 - 6']] |
radio iq | https://en.wikipedia.org/wiki/Radio_IQ | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12265526-1.html.csv | ordinal | wriq is the radio iq channel that broadcasts with the second highest erp wattage . | {'row': '4', 'col': '4', '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', 'erp w', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; erp w ; 2 }'}, 'call sign'], 'result': 'wriq', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; erp w ; 2 } ; call sign }'}, 'wriq'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; erp w ; 2 } ; call sign } ; wriq } = true', 'tointer': 'select the row whose erp w record of all rows is 2nd maximum . the call sign record of this row is wriq .'} | eq { hop { nth_argmax { all_rows ; erp w ; 2 } ; call sign } ; wriq } = true | select the row whose erp w record of all rows is 2nd maximum . the call sign record of this row is wriq . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'erp w_5': 5, '2_6': 6, 'call sign_7': 7, 'wriq_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', 'erp w_5': 'erp w', '2_6': '2', 'call sign_7': 'call sign', 'wriq_8': 'wriq'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'erp w_5': [0], '2_6': [0], 'call sign_7': [1], 'wriq_8': [2]} | ['call sign', 'frequency mhz', 'city of license', 'erp w', 'class', 'fcc info'] | [['wvtw', '88.5', 'charlottesville , virginia', '1000', 'b1', 'fcc'], ['wffc', '89.9', 'ferrum , virginia', '1100', 'a', 'fcc'], ['wqiq', '88.3', 'spotsylvania , virginia', '3500', 'a', 'fcc'], ['wriq', '88.7', 'lexington , virginia', '3900', 'a', 'fcc'], ['wwvt', '1260', 'christiansburg , virginia', '5000 day 25 night', 'd', 'fcc']] |
principal officials accountability system | https://en.wikipedia.org/wiki/Principal_Officials_Accountability_System | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2263674-1.html.csv | superlative | elsie leung oi - see was the oldest politician at appointment in the principal officials accountability system . | {'scope': 'all', 'col_superlative': '3', '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', 'age at appointment'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; age at appointment }'}, 'romanised name'], 'result': 'elsie leung oi - see', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; age at appointment } ; romanised name }'}, 'elsie leung oi - see'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; age at appointment } ; romanised name } ; elsie leung oi - see } = true', 'tointer': 'select the row whose age at appointment record of all rows is maximum . the romanised name record of this row is elsie leung oi - see .'} | eq { hop { argmax { all_rows ; age at appointment } ; romanised name } ; elsie leung oi - see } = true | select the row whose age at appointment record of all rows is maximum . the romanised name record of this row is elsie leung oi - see . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'age at appointment_5': 5, 'romanised name_6': 6, 'elsie leung oi - see_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'age at appointment_5': 'age at appointment', 'romanised name_6': 'romanised name', 'elsie leung oi - see_7': 'elsie leung oi - see'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'age at appointment_5': [0], 'romanised name_6': [1], 'elsie leung oi - see_7': [2]} | ['romanised name', 'chinese name', 'age at appointment', 'portfolio', 'prior occupation'] | [['donald tsang yam - kuen', '曾蔭權', '58', 'chief secretary for administration ( cs )', 'chief secretary for administration ( cs )'], ['anthony leung kam - chung', '梁錦松', '50', 'financial secretary ( fs )', 'financial secretary ( fs )'], ['elsie leung oi - see', '梁愛詩', '63', 'secretary for justice ( sj )', 'secretary for justice ( sj )'], ['joseph wong wing - ping', '王永平', '54', 'secretary for civil service', 'secretary for civil service'], ['henry tang ying - yen', '唐英年', '50', 'secretary for commerce , industry and technology', 'chairman , federation of hong kong industries'], ['stephen ip shu - kwan', '葉澍堃', '50', 'secretary for economic development and labour', 'secretary for financial services'], ['frederick ma si - hang', '馬時亨', '50', 'secretary for financial services and the treasury', 'chief financial officer , pccw'], ['sarah liao sau - tung', '廖秀冬', '51', 'secretary for the environment , transport and works', 'md of greater china , ch2 m hill'], ['dr patrick ho chi - ping', '何志平', '52', 'secretary for home affairs', 'chairman , arts development council'], ['michael suen ming - yeung', '孫明揚', '58', 'secretary for housing , planning and lands', 'secretary for constitutional affairs'], ['arthur li kwok - cheung', '李國章', '57', 'secretary for education and manpower', 'vice - chancellor , chinese university'], ['yeoh eng - kiong', '楊永強', '56', 'secretary for health , welfare and food', 'secretary for health and welfare']] |
atp bordeaux | https://en.wikipedia.org/wiki/ATP_Bordeaux | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16028631-1.html.csv | comparative | in the atp bordeaux , ivan lendl was the champion three years before andrei medvedev . | {'row_1': '11', 'row_2': '14', 'col': '1', 'col_other': '3', 'relation': 'diff', 'record_mentioned': 'no', 'diff_result': {'diff_value': '3 years', 'bigger': 'row2'}} | {'func': 'eq', 'args': [{'func': 'diff', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'champions', 'ivan lendl'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose champions record fuzzily matches to ivan lendl .', 'tostr': 'filter_eq { all_rows ; champions ; ivan lendl }'}, 'year'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; champions ; ivan lendl } ; year }', 'tointer': 'select the rows whose champions record fuzzily matches to ivan lendl . take the year record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'champions', 'andrei medvedev'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose champions record fuzzily matches to andrei medvedev .', 'tostr': 'filter_eq { all_rows ; champions ; andrei medvedev }'}, 'year'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; champions ; andrei medvedev } ; year }', 'tointer': 'select the rows whose champions record fuzzily matches to andrei medvedev . take the year record of this row .'}], 'result': '-3 years', 'ind': 4, 'tostr': 'diff { hop { filter_eq { all_rows ; champions ; ivan lendl } ; year } ; hop { filter_eq { all_rows ; champions ; andrei medvedev } ; year } }'}, '-3 years'], 'result': True, 'ind': 5, 'tostr': 'eq { diff { hop { filter_eq { all_rows ; champions ; ivan lendl } ; year } ; hop { filter_eq { all_rows ; champions ; andrei medvedev } ; year } } ; -3 years } = true', 'tointer': 'select the rows whose champions record fuzzily matches to ivan lendl . take the year record of this row . select the rows whose champions record fuzzily matches to andrei medvedev . take the year record of this row . the second record is 3 years larger than the first record .'} | eq { diff { hop { filter_eq { all_rows ; champions ; ivan lendl } ; year } ; hop { filter_eq { all_rows ; champions ; andrei medvedev } ; year } } ; -3 years } = true | select the rows whose champions record fuzzily matches to ivan lendl . take the year record of this row . select the rows whose champions record fuzzily matches to andrei medvedev . take the year record of this row . the second record is 3 years larger than the first record . | 6 | 6 | {'str_eq_5': 5, 'result_6': 6, 'diff_4': 4, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_7': 7, 'champions_8': 8, 'ivan lendl_9': 9, 'year_10': 10, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_11': 11, 'champions_12': 12, 'andrei medvedev_13': 13, 'year_14': 14, '-3 years_15': 15} | {'str_eq_5': 'str_eq', 'result_6': 'true', 'diff_4': 'diff', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_7': 'all_rows', 'champions_8': 'champions', 'ivan lendl_9': 'ivan lendl', 'year_10': 'year', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_11': 'all_rows', 'champions_12': 'champions', 'andrei medvedev_13': 'andrei medvedev', 'year_14': 'year', '-3 years_15': '-3 years'} | {'str_eq_5': [6], 'result_6': [], 'diff_4': [5], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_7': [0], 'champions_8': [0], 'ivan lendl_9': [0], 'year_10': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_11': [1], 'champions_12': [1], 'andrei medvedev_13': [1], 'year_14': [3], '-3 years_15': [5]} | ['year', 'tournament name', 'champions', 'runners - up', 'score'] | [['1979', 'grand prix passing shot', 'yannick noah', 'harold solomon', '6 - 0 , 6 - 7 , 6 - 1 , 1 - 6 , 6 - 4'], ['1980', 'grand prix de passing shot', 'mario martinez', 'gianni ocleppo', '6 - 0 , 7 - 5 , 7 - 5'], ['1981', 'grand prix passing shot', 'andrés gómez', 'thierry tulasne', '7 - 6 , 7 - 6 , 6 - 1'], ['1982', 'grand prix passing shot', 'hans gildemeister', 'pablo arraya', '7 - 5 , 6 - 1'], ['1983', 'grand prix passing shot', 'pablo arraya', 'juan aguilera', '7 - 5 , 7 - 5'], ['1984', 'grand prix passing shot', 'josé higueras', 'francesco cancellotti', '7 - 6 , 6 - 1'], ['1985', 'nabisco grand prix passing shot', 'diego pérez', 'jimmy brown', '6 - 4 , 7 - 6'], ['1986', 'nabisco grand prix passing shot', 'paolo canè', 'kent carlsson', '6 - 4 , 1 - 6 , 7 - 5'], ['1987', 'nabisco grand prix passing shot', 'emilio sánchez', 'ronald agénor', '5 - 7 , 6 - 4 , 6 - 4'], ['1988', 'ngp passing shot de bordeaux', 'thomas muster', 'ronald agénor', '6 - 3 , 6 - 3'], ['1989', 'grand prix passing shot de bordeaux', 'ivan lendl', 'emilio sánchez', '6 - 2 , 6 - 2'], ['1990', 'grand prix passing shot', 'guy forget', 'goran ivanišević', '6 - 4 , 6 - 3'], ['1991', 'grand prix passing shot', 'guy forget', 'olivier delaître', '6 - 1 , 6 - 3'], ['1992', 'grand prix passing shot', 'andrei medvedev', 'sergi bruguera', '6 - 3 , 1 - 6 , 6 - 2'], ['1993', 'grand prix passing shot bordeaux', 'sergi bruguera', 'diego nargiso', '7 - 5 , 6 - 2'], ['1994', 'grand prix passing shot', 'wayne ferreira', 'jeff tarango', '6 - 0 , 7 - 5'], ['1995', 'grand prix passing shot bordeaux', 'yahiya doumbia', 'jakob hlasek', '6 - 4 , 6 - 4']] |
bud tingelstad | https://en.wikipedia.org/wiki/Bud_Tingelstad | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1252053-1.html.csv | count | bud tingelstad started in the top 20 five times . | {'scope': 'all', 'criterion': 'less_than_eq', 'value': '20', 'result': '5', 'col': '2', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_less_eq', 'args': ['all_rows', 'start', '20'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose start record is less than or equal to 20 .', 'tostr': 'filter_less_eq { all_rows ; start ; 20 }'}], 'result': '5', 'ind': 1, 'tostr': 'count { filter_less_eq { all_rows ; start ; 20 } }', 'tointer': 'select the rows whose start record is less than or equal to 20 . the number of such rows is 5 .'}, '5'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_less_eq { all_rows ; start ; 20 } } ; 5 } = true', 'tointer': 'select the rows whose start record is less than or equal to 20 . the number of such rows is 5 .'} | eq { count { filter_less_eq { all_rows ; start ; 20 } } ; 5 } = true | select the rows whose start record is less than or equal to 20 . the number of such rows is 5 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_less_eq_0': 0, 'all_rows_4': 4, 'start_5': 5, '20_6': 6, '5_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_less_eq_0': 'filter_less_eq', 'all_rows_4': 'all_rows', 'start_5': 'start', '20_6': '20', '5_7': '5'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_less_eq_0': [1], 'all_rows_4': [0], 'start_5': [0], '20_6': [0], '5_7': [2]} | ['year', 'start', 'qual', 'rank', 'finish', 'laps'] | [['1960', '28', '142.354', '29', '9', '200'], ['1962', '10', '147.753', '10', '15', '200'], ['1963', '25', '148.227', '27', '28', '46'], ['1964', '19', '151.210', '26', '6', '198'], ['1965', '24', '154.672', '23', '16', '115'], ['1966', '27', '159.144', '26', '21', '16'], ['1967', '25', '163.228', '22', '14', '182'], ['1968', '18', '164.444', '17', '16', '158'], ['1969', '18', '166.597', '18', '15', '155'], ['1971', '17', '170.156', '24', '7', '198']] |
cascade collegiate conference | https://en.wikipedia.org/wiki/Cascade_Collegiate_Conference | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1685403-1.html.csv | aggregation | in the cascade collegiate conference , for schools with an enrollment of over 3000 , the average number of varsity sports is 10.4 . | {'scope': 'subset', 'col': '6', 'type': 'average', 'result': '10.4', 'subset': {'col': '4', 'criterion': 'greater_than', 'value': '3000'}} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'enrollment', '3000'], 'result': None, 'ind': 0, 'tostr': 'filter_greater { all_rows ; enrollment ; 3000 }', 'tointer': 'select the rows whose enrollment record is greater than 3000 .'}, 'varsity sports'], 'result': '10.4', 'ind': 1, 'tostr': 'avg { filter_greater { all_rows ; enrollment ; 3000 } ; varsity sports }'}, '10.4'], 'result': True, 'ind': 2, 'tostr': 'round_eq { avg { filter_greater { all_rows ; enrollment ; 3000 } ; varsity sports } ; 10.4 } = true', 'tointer': 'select the rows whose enrollment record is greater than 3000 . the average of the varsity sports record of these rows is 10.4 .'} | round_eq { avg { filter_greater { all_rows ; enrollment ; 3000 } ; varsity sports } ; 10.4 } = true | select the rows whose enrollment record is greater than 3000 . the average of the varsity sports record of these rows is 10.4 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'avg_1': 1, 'filter_greater_0': 0, 'all_rows_4': 4, 'enrollment_5': 5, '3000_6': 6, 'varsity sports_7': 7, '10.4_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'avg_1': 'avg', 'filter_greater_0': 'filter_greater', 'all_rows_4': 'all_rows', 'enrollment_5': 'enrollment', '3000_6': '3000', 'varsity sports_7': 'varsity sports', '10.4_8': '10.4'} | {'eq_2': [3], 'result_3': [], 'avg_1': [2], 'filter_greater_0': [1], 'all_rows_4': [0], 'enrollment_5': [0], '3000_6': [0], 'varsity sports_7': [1], '10.4_8': [2]} | ['institution', 'location', 'founded', 'enrollment', 'nickname', 'varsity sports', 'joined'] | [['college of idaho', 'caldwell , idaho ( 31041 )', '1891', '1042', 'coyotes', '17', '1988'], ['concordia university', 'portland , oregon ( 538554 )', '1905', '3111', 'cavaliers', '13', '1988'], ['corban university', 'salem , oregon ( 142914 )', '1935', '1160', 'warriors', '13', '1988'], ['eastern oregon university', 'la grande , oregon ( 12282 )', '1929', '3743', 'mountaineers', '10', '1988'], ['the evergreen state college', 'olympia , washington ( 44114 )', '1967', '4509', 'geoducks', '8', '1999'], ['northwest university', 'kirkland , washington ( 45814 )', '1934', '1280', 'eagles', '9', '1997'], ['northwest christian university', 'eugene , oregon ( 142185 )', '1895', '1290', 'beacons', '12', '2007'], ['oregon institute of technology', 'klamath falls , oregon ( 20840 )', '1947', '3927', 'owls', '9', '1988'], ['southern oregon university', 'ashland , oregon ( 20406 )', '1882', '6744', 'raiders', '12', '1988'], ['warner pacific college', 'portland , oregon ( 538554 )', '1937', '1333', 'knights', '9', '1999']] |
1950 masters tournament | https://en.wikipedia.org/wiki/1950_Masters_Tournament | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13059194-1.html.csv | unique | in the 1950 masters tournament , of those players that are from the united states , the only player who was 1 under par was in 3rd place . | {'scope': 'subset', 'row': '3', 'col': '5', 'col_other': '1', 'criterion': 'equal', 'value': '-1', 'subset': {'col': '3', 'criterion': 'equal', 'value': 'united states'}} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'united states'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; country ; united states }', 'tointer': 'select the rows whose country record fuzzily matches to united states .'}, 'to par', '-1'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose country record fuzzily matches to united states . among these rows , select the rows whose to par record is equal to -1 .', 'tostr': 'filter_eq { filter_eq { all_rows ; country ; united states } ; to par ; -1 }'}], 'result': True, 'ind': 2, 'tostr': 'only { filter_eq { filter_eq { all_rows ; country ; united states } ; to par ; -1 } }', 'tointer': 'select the rows whose country record fuzzily matches to united states . among these rows , select the rows whose to par record is equal to -1 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'united states'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; country ; united states }', 'tointer': 'select the rows whose country record fuzzily matches to united states .'}, 'to par', '-1'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose country record fuzzily matches to united states . among these rows , select the rows whose to par record is equal to -1 .', 'tostr': 'filter_eq { filter_eq { all_rows ; country ; united states } ; to par ; -1 }'}, 'place'], 'result': '3', 'ind': 3, 'tostr': 'hop { filter_eq { filter_eq { all_rows ; country ; united states } ; to par ; -1 } ; place }'}, '3'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { filter_eq { filter_eq { all_rows ; country ; united states } ; to par ; -1 } ; place } ; 3 }', 'tointer': 'the place record of this unqiue row is 3 .'}], 'result': True, 'ind': 5, 'tostr': 'and { only { filter_eq { filter_eq { all_rows ; country ; united states } ; to par ; -1 } } ; eq { hop { filter_eq { filter_eq { all_rows ; country ; united states } ; to par ; -1 } ; place } ; 3 } } = true', 'tointer': 'select the rows whose country record fuzzily matches to united states . among these rows , select the rows whose to par record is equal to -1 . there is only one such row in the table . the place record of this unqiue row is 3 .'} | and { only { filter_eq { filter_eq { all_rows ; country ; united states } ; to par ; -1 } } ; eq { hop { filter_eq { filter_eq { all_rows ; country ; united states } ; to par ; -1 } ; place } ; 3 } } = true | select the rows whose country record fuzzily matches to united states . among these rows , select the rows whose to par record is equal to -1 . there is only one such row in the table . the place record of this unqiue row is 3 . | 8 | 6 | {'and_5': 5, 'result_6': 6, 'only_2': 2, 'filter_eq_1': 1, 'filter_str_eq_0': 0, 'all_rows_7': 7, 'country_8': 8, 'united states_9': 9, 'to par_10': 10, '-1_11': 11, 'str_eq_4': 4, 'str_hop_3': 3, 'place_12': 12, '3_13': 13} | {'and_5': 'and', 'result_6': 'true', 'only_2': 'only', 'filter_eq_1': 'filter_eq', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_7': 'all_rows', 'country_8': 'country', 'united states_9': 'united states', 'to par_10': 'to par', '-1_11': '-1', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'place_12': 'place', '3_13': '3'} | {'and_5': [6], 'result_6': [], 'only_2': [5], 'filter_eq_1': [2, 3], 'filter_str_eq_0': [1], 'all_rows_7': [0], 'country_8': [0], 'united states_9': [0], 'to par_10': [1], '-1_11': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'place_12': [3], '3_13': [4]} | ['place', 'player', 'country', 'score', 'to par', 'money'] | [['1', 'jimmy demaret', 'united states', '70 + 72 + 72 + 69 = 283', '- 5', '2400'], ['2', 'jim ferrier', 'australia', '70 + 67 + 73 + 75 = 285', '- 3', '1500'], ['3', 'sam snead', 'united states', '71 + 74 + 70 + 72 = 287', '- 1', '1020'], ['t4', 'ben hogan', 'united states', '73 + 68 + 71 + 76 = 288', 'e', '725'], ['t4', 'byron nelson', 'united states', '75 + 70 + 69 + 74 = 288', 'e', '725'], ['6', 'lloyd mangrum', 'united states', '76 + 74 + 73 + 68 = 291', '+ 3', '480'], ['t7', 'clayton heafner', 'united states', '74 + 77 + 69 + 72 = 292', '+ 4', '405'], ['t7', 'cary middlecoff', 'united states', '75 + 76 + 68 + 73 = 292', '+ 4', '405'], ['9', 'lawson little', 'united states', '70 + 73 + 75 + 75 = 293', '+ 5', '360'], ['t10', 'fred haas', 'united states', '74 + 76 + 73 + 71 = 294', '+ 6', '333'], ['t10', 'gene sarazen', 'united states', '80 + 70 + 72 + 72 = 294', '+ 6', '333']] |
nfl network thursday night football results ( 2006 - present ) | https://en.wikipedia.org/wiki/NFL_Network_Thursday_Night_Football_results_%282006%E2%80%93present%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12771946-3.html.csv | comparative | there were less points scored at the chargers game than at the eagles game . | {'row_1': '5', 'row_2': '4', 'col': '3', 'col_other': '4', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'host team', 'san diego chargers'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose host team record fuzzily matches to san diego chargers .', 'tostr': 'filter_eq { all_rows ; host team ; san diego chargers }'}, 'final score'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; host team ; san diego chargers } ; final score }', 'tointer': 'select the rows whose host team record fuzzily matches to san diego chargers . take the final score record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'host team', 'philadelphia eagles'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose host team record fuzzily matches to philadelphia eagles .', 'tostr': 'filter_eq { all_rows ; host team ; philadelphia eagles }'}, 'final score'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; host team ; philadelphia eagles } ; final score }', 'tointer': 'select the rows whose host team record fuzzily matches to philadelphia eagles . take the final score record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; host team ; san diego chargers } ; final score } ; hop { filter_eq { all_rows ; host team ; philadelphia eagles } ; final score } } = true', 'tointer': 'select the rows whose host team record fuzzily matches to san diego chargers . take the final score record of this row . select the rows whose host team record fuzzily matches to philadelphia eagles . take the final score record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; host team ; san diego chargers } ; final score } ; hop { filter_eq { all_rows ; host team ; philadelphia eagles } ; final score } } = true | select the rows whose host team record fuzzily matches to san diego chargers . take the final score record of this row . select the rows whose host team record fuzzily matches to philadelphia eagles . take the final score 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, 'host team_7': 7, 'san diego chargers_8': 8, 'final score_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'host team_11': 11, 'philadelphia eagles_12': 12, 'final score_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', 'host team_7': 'host team', 'san diego chargers_8': 'san diego chargers', 'final score_9': 'final score', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'host team_11': 'host team', 'philadelphia eagles_12': 'philadelphia eagles', 'final score_13': 'final score'} | {'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'host team_7': [0], 'san diego chargers_8': [0], 'final score_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'host team_11': [1], 'philadelphia eagles_12': [1], 'final score_13': [3]} | ['date', 'visiting team', 'final score', 'host team', 'stadium'] | [['november 6', 'denver broncos', '34 - 30', 'cleveland browns', 'cleveland browns stadium'], ['november 13', 'new york jets', '34 - 31 ( ot )', 'new england patriots', 'gillette stadium'], ['november 20', 'cincinnati bengals', '10 - 27', 'pittsburgh steelers', 'heinz field'], ['november 27', 'arizona cardinals', '20 - 48', 'philadelphia eagles', 'lincoln financial field'], ['december 4', 'oakland raiders', '7 - 34', 'san diego chargers', 'qualcomm stadium'], ['december 11', 'new orleans saints', '24 - 27 ( ot )', 'chicago bears', 'soldier field'], ['december 18', 'indianapolis colts', '31 - 24', 'jacksonville jaguars', 'jacksonville municipal stadium'], ['december 20', 'baltimore ravens', '33 - 24', 'dallas cowboys', 'texas stadium']] |
1993 u.s. open ( golf ) | https://en.wikipedia.org/wiki/1993_U.S._Open_%28golf%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17162239-1.html.csv | aggregation | all of the players totaled 2548 at the 1993 u.s. open ( golf ) . | {'scope': 'all', 'col': '4', 'type': 'sum', 'result': '2548', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'total'], 'result': '2548', 'ind': 0, 'tostr': 'sum { all_rows ; total }'}, '2548'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; total } ; 2548 } = true', 'tointer': 'the sum of the total record of all rows is 2548 .'} | round_eq { sum { all_rows ; total } ; 2548 } = true | the sum of the total record of all rows is 2548 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'total_4': 4, '2548_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'total_4': 'total', '2548_5': '2548'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'total_4': [0], '2548_5': [1]} | ['player', 'country', 'year ( s ) won', 'total', 'to par', 'finish'] | [['payne stewart', 'united states', '1991', '274', '- 6', '2'], ['tom watson', 'united states', '1982', '278', '- 2', 't5'], ['raymond floyd', 'united states', '1986', '279', '- 1', 't7'], ['curtis strange', 'united states', '1988 , 1989', '283', '+ 3', 't25'], ['larry nelson', 'united states', '1983', '285', '+ 5', 't46'], ['scott simpson', 'united states', '1987', '285', '+ 5', 't46'], ['hale irwin', 'united states', '1974 , 1979 , 1990', '287', '+ 7', 't62'], ['fuzzy zoeller', 'united states', '1984', '288', '+ 8', 't68'], ['jack nicklaus', 'united states', '1962 , 1967 , 1972 , 1980', '289', '+ 9', 't72']] |
1994 miami dolphins season | https://en.wikipedia.org/wiki/1994_Miami_Dolphins_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16023821-1.html.csv | majority | the miami dolphins won most games in the month of october during the 1994 season . | {'scope': 'subset', 'col': '4', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': 'w', 'subset': {'col': '2', 'criterion': 'fuzzily_match', 'value': 'october'}} | {'func': 'most_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', 'october'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; date ; october }', 'tointer': 'select the rows whose date record fuzzily matches to october .'}, 'result', 'w'], 'result': True, 'ind': 1, 'tointer': 'select the rows whose date record fuzzily matches to october . for the result records of these rows , most of them fuzzily match to w .', 'tostr': 'most_eq { filter_eq { all_rows ; date ; october } ; result ; w } = true'} | most_eq { filter_eq { all_rows ; date ; october } ; result ; w } = true | select the rows whose date record fuzzily matches to october . for the result records of these rows , most of them fuzzily match to w . | 2 | 2 | {'most_str_eq_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, 'date_4': 4, 'october_5': 5, 'result_6': 6, 'w_7': 7} | {'most_str_eq_1': 'most_str_eq', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'date_4': 'date', 'october_5': 'october', 'result_6': 'result', 'w_7': 'w'} | {'most_str_eq_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'date_4': [0], 'october_5': [0], 'result_6': [1], 'w_7': [1]} | ['week', 'date', 'opponent', 'result', 'tv time', 'attendance'] | [['1', 'september 4 , 1994', 'new england patriots', 'w 39 - 35', 'nbc 4:15 pm', '71023'], ['2', 'september 11 , 1994', 'green bay packers', 'w 24 - 14', 'nbc 1:00 pm', '55011'], ['3', 'september 18 , 1994', 'new york jets', 'w 28 - 14', 'nbc 1:00 pm', '68977'], ['4', 'september 25 , 1994', 'minnesota vikings', 'l 38 - 35', 'nbc 1:00 pm', '64035'], ['5', 'october 2 , 1994', 'cincinnati bengals', 'w 23 - 7', 'tnt 8:15 pm', '55056'], ['6', 'october 9 , 1994', 'buffalo bills', 'l 21 - 11', 'nbc 1:00 pm', '79491'], ['7', 'october 16 , 1994', 'los angeles raiders', 'w 20 - 17', 'nbc 1:00 pm', '70112'], ['9', 'october 30 , 1994', 'new england patriots', 'w 23 - 3', 'nbc 4:15 pm', '59167'], ['10', 'november 6 , 1994', 'indianapolis colts', 'w 22 - 21', 'nbc 1:00 pm', '71158'], ['11', 'november 13 , 1994', 'chicago bears', 'l 17 - 14', 'fox 1:00 pm', '64871'], ['12', 'november 20 , 1994', 'pittsburgh steelers', 'l 16 - 13', 'nbc 1:00 pm', '59148'], ['13', 'november 27 , 1994', 'new york jets', 'w 28 - 24', 'nbc 4:15 pm', '75606'], ['14', 'december 4 , 1994', 'buffalo bills', 'l 42 - 31', 'espn 8:15 pm', '69538'], ['15', 'december 12 , 1994', 'kansas city chiefs', 'w 45 - 28', 'abc 9:00 pm', '71578'], ['16', 'december 18 , 1994', 'indianapolis colts', 'l 10 - 6', 'nbc 1:00 pm', '58867'], ['17', 'december 25 , 1994', 'detroit lions', 'w 27 - 20', 'espn 8:15 pm', '70980']] |
solar eclipse of march 29 , 2006 | https://en.wikipedia.org/wiki/Solar_eclipse_of_March_29%2C_2006 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1708610-3.html.csv | count | most of the june 10-11 of the solar eclipse of march 29,2006 have june 10 as their date . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'june 10', 'result': '2', 'col': '1', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'june 10 - 11', 'june 10'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose june 10 - 11 record fuzzily matches to june 10 .', 'tostr': 'filter_eq { all_rows ; june 10 - 11 ; june 10 }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; june 10 - 11 ; june 10 } }', 'tointer': 'select the rows whose june 10 - 11 record fuzzily matches to june 10 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; june 10 - 11 ; june 10 } } ; 2 } = true', 'tointer': 'select the rows whose june 10 - 11 record fuzzily matches to june 10 . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; june 10 - 11 ; june 10 } } ; 2 } = true | select the rows whose june 10 - 11 record fuzzily matches to june 10 . 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, 'june 10 - 11_5': 5, 'june 10_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', 'june 10 - 11_5': 'june 10 - 11', 'june 10_6': 'june 10', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'june 10 - 11_5': [0], 'june 10_6': [0], '2_7': [2]} | ['june 10 - 11', 'march 27 - 29', 'january 15 - 16', 'november 3', 'august 21 - 22'] | [['june 10 , 1964', 'march 28 , 1968', 'january 16 , 1972', 'november 3 , 1975', 'august 22 , 1979'], ['127', '129', '131', '133', '135'], ['june 11 , 1983', 'march 29 , 1987', 'january 15 , 1991', 'november 3 , 1994', 'august 22 , 1998'], ['137', '139', '141', '143', '145'], ['june 10 , 2002', 'march 29 , 2006', 'january 15 , 2010', 'november 3 , 2013', 'august 21 , 2017'], ['147', '149', '151', '153', '155']] |
ar - 15 variants | https://en.wikipedia.org/wiki/AR-15_variants | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12834315-5.html.csv | majority | among the 4th generation ar-15 variants , the m4 hand guard is the most commonly used . | {'scope': 'all', 'col': '9', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'm4', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'hand guards', 'm4'], 'result': True, 'ind': 0, 'tointer': 'for the hand guards records of all rows , most of them fuzzily match to m4 .', 'tostr': 'most_eq { all_rows ; hand guards ; m4 } = true'} | most_eq { all_rows ; hand guards ; m4 } = true | for the hand guards records of all rows , most of them fuzzily match to m4 . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'hand guards_3': 3, 'm4_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'hand guards_3': 'hand guards', 'm4_4': 'm4'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'hand guards_3': [0], 'm4_4': [0]} | ['colt model no', 'stock', 'fire control', 'rear sight', 'forward assist', 'barrel length', 'barrel profile', 'barrel twist', 'hand guards', 'bayonet lug', 'muzzle device'] | [['le1020', '4th generation', 's - 1', 'flattop', 'yes', '16 in', 'm4', '1:7', 'rail system', 'yes', 'a2'], ['le1033', '4th generation', 's - 1', 'flattop', 'yes', '11.5 in', 'a2', '1:7', 'rail system', 'yes', 'a2'], ['le6920', '4th generation', 's - 1', 'flattop', 'yes', '16 in', 'm4', '1:7', 'm4', 'yes', 'a2'], ['le6920hb', '4th generation', 's - 1', 'flattop', 'yes', '16 in', 'm4 hbar', '1:7', 'm4', 'yes', 'a2'], ['le6921', '4th generation', 's - 1', 'flattop', 'yes', '14.5 in', 'm4', '1:7', 'm4', 'yes', 'a2'], ['le6921cqb', '4th generation', 's - 1', 'flattop', 'yes', '10.5 in', 'm4 hbar', '1:7', 'm4', 'yes', 'a2'], ['le6921hb', '4th generation', 's - 1', 'flattop', 'yes', '14.5 in', 'm4 hbar', '1:7', 'm4', 'yes', 'a2'], ['le6921sp', '4th generation', 's - 1', 'flattop', 'yes', '10 in', 'm4 hbar', '1:7', 'm4', 'yes', 'a2'], ['le6933', '4th generation', 's - 1', 'flattop', 'yes', '11.5 in', 'a2', '1:7', 'short ribbed', 'yes', 'a2'], ['le6940', '4th generation', 's - 1', 'flattop', 'yes', '16 in', 'm4', '1:7', 'monolithic rail system', 'yes', 'a2'], ['le6941', '4th generation', 's - 1', 'flattop', 'yes', '16 in', 'm4', '1:7', 'rail system', 'yes', 'a2']] |
united states house of representatives elections , 1804 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1804 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2668387-18.html.csv | superlative | the member elected into the virginia house of representatives of 1804 that was first elected the earliest was phillip r. thompson . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '7', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '2', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmin', 'args': ['all_rows', 'first elected'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; first elected }'}, 'incumbent'], 'result': 'philip r thompson', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; first elected } ; incumbent }'}, 'philip r thompson'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmin { all_rows ; first elected } ; incumbent } ; philip r thompson } = true', 'tointer': 'select the row whose first elected record of all rows is minimum . the incumbent record of this row is philip r thompson .'} | eq { hop { argmin { all_rows ; first elected } ; incumbent } ; philip r thompson } = true | select the row whose first elected record of all rows is minimum . the incumbent record of this row is philip r thompson . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'first elected_5': 5, 'incumbent_6': 6, 'philip r thompson_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'first elected_5': 'first elected', 'incumbent_6': 'incumbent', 'philip r thompson_7': 'philip r thompson'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'first elected_5': [0], 'incumbent_6': [1], 'philip r thompson_7': [2]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['virginia 1', 'john g jackson', 'democratic - republican', '1803', 're - elected', 'john g jackson ( dr ) 57.2 % thomas wilson ( f ) 42.8 %'], ['virginia 2', 'james stephenson', 'federalist', '1803', 'lost re - election democratic - republican gain', 'john morrow ( dr ) james stephenson ( f )'], ['virginia 3', 'john smith', 'democratic - republican', '1801', 're - elected', 'john smith ( dr )'], ['virginia 4', 'david holmes', 'democratic - republican', '1797', 're - elected', 'david holmes ( dr )'], ['virginia 6', 'abram trigg', 'democratic - republican', '1797', 're - elected', 'abram trigg ( dr )'], ['virginia 8', 'walter jones', 'democratic - republican', '1803', 're - elected', 'walter jones ( dr ) 99.0 % henry lee ( f ) 1.0 %'], ['virginia 9', 'philip r thompson', 'democratic - republican', '1793', 're - elected', 'philip r thompson ( dr )'], ['virginia 10', 'john dawson', 'democratic - republican', '1797', 're - elected', 'john dawson ( dr ) 66.2 % james barbour ( quid ) 33.8 %'], ['virginia 13', 'christopher h clark', 'democratic - republican', '1804 ( special )', 're - elected', 'christopher h clark ( dr )'], ['virginia 14', 'matthew clay', 'democratic - republican', '1797', 're - elected', 'matthew clay ( dr ) 88.9 % william lewis ( f ) 11.1 %'], ['virginia 15', 'john randolph', 'democratic - republican', '1799', 're - elected', 'john randolph ( dr )'], ['virginia 16', 'john w eppes', 'democratic - republican', '1803', 're - elected', 'john w eppes ( dr )'], ['virginia 18', 'peterson goodwyn', 'democratic - republican', '1803', 're - elected', 'peterson goodwyn ( dr )'], ['virginia 19', 'edwin gray', 'democratic - republican', '1799', 're - elected', 'edwin gray ( dr )'], ['virginia 20', 'thomas newton , jr', 'democratic - republican', '1799', 're - elected', 'thomas newton , jr ( dr ) 100 %']] |
rovers cup | https://en.wikipedia.org/wiki/Rovers_Cup | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14645146-1.html.csv | unique | the only team in the rovers cup with 10 wins is east bengal club . | {'scope': 'all', 'row': '2', 'col': '2', 'col_other': '1', 'criterion': 'equal', 'value': '10', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'wins', '10'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose wins record is equal to 10 .', 'tostr': 'filter_eq { all_rows ; wins ; 10 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; wins ; 10 } }', 'tointer': 'select the rows whose wins record is equal to 10 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'wins', '10'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose wins record is equal to 10 .', 'tostr': 'filter_eq { all_rows ; wins ; 10 }'}, 'club'], 'result': 'east bengal club', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; wins ; 10 } ; club }'}, 'east bengal club'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; wins ; 10 } ; club } ; east bengal club }', 'tointer': 'the club record of this unqiue row is east bengal club .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; wins ; 10 } } ; eq { hop { filter_eq { all_rows ; wins ; 10 } ; club } ; east bengal club } } = true', 'tointer': 'select the rows whose wins record is equal to 10 . there is only one such row in the table . the club record of this unqiue row is east bengal club .'} | and { only { filter_eq { all_rows ; wins ; 10 } } ; eq { hop { filter_eq { all_rows ; wins ; 10 } ; club } ; east bengal club } } = true | select the rows whose wins record is equal to 10 . there is only one such row in the table . the club record of this unqiue row is east bengal club . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'wins_7': 7, '10_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'club_9': 9, 'east bengal club_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'wins_7': 'wins', '10_8': '10', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'club_9': 'club', 'east bengal club_10': 'east bengal club'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'wins_7': [0], '10_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'club_9': [2], 'east bengal club_10': [3]} | ['club', 'wins', 'last win', 'runners - up', 'last runners - up'] | [['mohun bagan ac', '14', '2000 - 01', '10', '1987'], ['east bengal club', '10', '1994', '4', '1988'], ['hyderabad police', '9', '1963', '1', '1943'], ['mohammedan sporting club', '6', '1987', '9', '1991'], ['dempo sc', '4', '1986', '1', '1989'], ['bangalore muslims', '3', '1948', '2', '1953'], ['salgaocar sc', '3', '1999', '1', '1985']] |
list of are you afraid of the dark ? episodes | https://en.wikipedia.org/wiki/List_of_Are_You_Afraid_of_the_Dark%3F_episodes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-10470082-6.html.csv | unique | season 5 , episode 11 of " are you afraid of the dark " was the only one in which gary was the storyteller . | {'scope': 'all', 'row': '11', 'col': '7', 'col_other': '2', 'criterion': 'equal', 'value': 'gary', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'storyteller', 'gary'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose storyteller record fuzzily matches to gary .', 'tostr': 'filter_eq { all_rows ; storyteller ; gary }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; storyteller ; gary } }', 'tointer': 'select the rows whose storyteller record fuzzily matches to gary . there is only one such row in the table .'}, {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'storyteller', 'gary'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose storyteller record fuzzily matches to gary .', 'tostr': 'filter_eq { all_rows ; storyteller ; gary }'}, '-'], 'result': '11', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; storyteller ; gary } ; - }'}, '11'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; storyteller ; gary } ; - } ; 11 }', 'tointer': 'the - record of this unqiue row is 11 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; storyteller ; gary } } ; eq { hop { filter_eq { all_rows ; storyteller ; gary } ; - } ; 11 } } = true', 'tointer': 'select the rows whose storyteller record fuzzily matches to gary . there is only one such row in the table . the - record of this unqiue row is 11 .'} | and { only { filter_eq { all_rows ; storyteller ; gary } } ; eq { hop { filter_eq { all_rows ; storyteller ; gary } ; - } ; 11 } } = true | select the rows whose storyteller record fuzzily matches to gary . there is only one such row in the table . the - record of this unqiue row is 11 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'storyteller_7': 7, 'gary_8': 8, 'eq_3': 3, 'num_hop_2': 2, '-_9': 9, '11_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'storyteller_7': 'storyteller', 'gary_8': 'gary', 'eq_3': 'eq', 'num_hop_2': 'num_hop', '-_9': '-', '11_10': '11'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'storyteller_7': [0], 'gary_8': [0], 'eq_3': [4], 'num_hop_2': [3], '-_9': [2], '11_10': [3]} | ['no', '-', 'title', 'director', 'writer', 'us air date', 'storyteller', 'villains'] | [['53', '1', "the tale of the dead man 's float", 'd j machale', 'will dixon', 'october 7 , 1995', 'stig', 'the pool zombie'], ['54', '2', 'the tale of the jagged sign', 'will dixon', 'susan kim', 'october 14 , 1995', 'kiki', 'none'], ['55', '3', 'the tale of station 109.1', 'ron oliver', 'scott peters', 'november 4 , 1995', 'stig', 'none'], ['56', '4', 'the tale of the mystical mirror', 'craig pryce', 'david wiechorek', 'november 11 , 1995', 'betty ann', 'ms valenti'], ['57', '5', 'the tale of the chameleons', 'iain patterson', 'mark d perry', 'november 18 , 1995', 'betty ann', 'the chameleon'], ['58', '6', "the tale of prisoner 's past", 'ron oliver', 'alan kingsberg', 'december 2 , 1995', 'tucker', 'none'], ['59', '7', 'the tale of c7', 'david winning', 'david preston', 'december 9 , 1995', 'sam', 'none'], ['60', '8', 'the tale of the manaha', 'will dixon', 'gerald wexler', 'december 30 , 1995', 'tucker', 'the shaman'], ['61', '9', 'the tale of the unexpected visitor', 'jacques laberge', 'alan kingsberg', 'january 13 , 1996', 'kiki', 'the alien kid and its mother'], ['62', '10', 'the tale of the vacant lot', 'lorette leblanc', 'gerald wexler', 'january 20 , 1996', 'kiki', 'marie'], ['63', '11', 'the tale of a door unlocked', 'ron oliver', 'scott peters', 'january 27 , 1996', 'gary', 'the toy door'], ['64', '12', 'the tale of the night shift', 'd j machale', 'chloe brown', 'february 3 , 1996', 'sam', 'the walking dead and the vampire']] |
2008 tim hortons brier | https://en.wikipedia.org/wiki/2008_Tim_Hortons_Brier | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-15597975-2.html.csv | unique | kevin martin was the only curler who had 0 losses in the 2008 tim hortons brier . | {'scope': 'all', 'row': '1', 'col': '4', 'col_other': '2', 'criterion': 'equal', 'value': '0', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'l', '0'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose l record is equal to 0 .', 'tostr': 'filter_eq { all_rows ; l ; 0 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; l ; 0 } }', 'tointer': 'select the rows whose l record is equal to 0 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'l', '0'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose l record is equal to 0 .', 'tostr': 'filter_eq { all_rows ; l ; 0 }'}, 'skip'], 'result': 'kevin martin', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; l ; 0 } ; skip }'}, 'kevin martin'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; l ; 0 } ; skip } ; kevin martin }', 'tointer': 'the skip record of this unqiue row is kevin martin .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; l ; 0 } } ; eq { hop { filter_eq { all_rows ; l ; 0 } ; skip } ; kevin martin } } = true', 'tointer': 'select the rows whose l record is equal to 0 . there is only one such row in the table . the skip record of this unqiue row is kevin martin .'} | and { only { filter_eq { all_rows ; l ; 0 } } ; eq { hop { filter_eq { all_rows ; l ; 0 } ; skip } ; kevin martin } } = true | select the rows whose l record is equal to 0 . there is only one such row in the table . the skip record of this unqiue row is kevin martin . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'l_7': 7, '0_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'skip_9': 9, 'kevin martin_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'l_7': 'l', '0_8': '0', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'skip_9': 'skip', 'kevin martin_10': 'kevin martin'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'l_7': [0], '0_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'skip_9': [2], 'kevin martin_10': [3]} | ['locale', 'skip', 'w', 'l', 'pf', 'pa', 'ends won', 'ends lost', 'blank ends', 'stolen ends', 'shot pct'] | [['alberta', 'kevin martin', '11', '0', '86', '52', '50', '40', '11', '11', '89'], ['saskatchewan', 'pat simmons', '9', '2', '80', '58', '50', '45', '9', '12', '84'], ['ontario', 'glenn howard', '9', '2', '85', '50', '54', '33', '11', '22', '88'], ['british columbia', 'bob ursel', '7', '4', '72', '66', '45', '47', '15', '11', '84'], ['newfoundland and labrador', 'brad gushue', '7', '4', '77', '69', '51', '44', '13', '14', '82'], ['manitoba', 'kerry burtnyk', '6', '5', '59', '66', '47', '40', '2', '19', '79'], ['quebec', 'jean - michel mãnard', '4', '7', '76', '69', '48', '48', '11', '15', '80'], ['northern ontario', 'eric harnden', '3', '8', '65', '80', '43', '53', '6', '6', '79'], ['prince edward island', 'peter gallant', '3', '8', '61', '78', '40', '50', '6', '7', '77'], ['nova scotia', 'brian rafuse', '3', '8', '60', '92', '42', '56', '8', '3', '77'], ['new brunswick', 'james grattan', '2', '9', '71', '86', '46', '54', '7', '5', '79']] |
list of ultras of africa | https://en.wikipedia.org/wiki/List_of_Ultras_of_Africa | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18947170-11.html.csv | majority | the majority of african ultra peaks are over 2000 m tall . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'greater_than', 'value': '2000', 'subset': None} | {'func': 'most_greater', 'args': ['all_rows', 'elevation ( m )', '2000'], 'result': True, 'ind': 0, 'tointer': 'for the elevation ( m ) records of all rows , most of them are greater than 2000 .', 'tostr': 'most_greater { all_rows ; elevation ( m ) ; 2000 } = true'} | most_greater { all_rows ; elevation ( m ) ; 2000 } = true | for the elevation ( m ) records of all rows , most of them are greater than 2000 . | 1 | 1 | {'most_greater_0': 0, 'result_1': 1, 'all_rows_2': 2, 'elevation (m)_3': 3, '2000_4': 4} | {'most_greater_0': 'most_greater', 'result_1': 'true', 'all_rows_2': 'all_rows', 'elevation (m)_3': 'elevation ( m )', '2000_4': '2000'} | {'most_greater_0': [1], 'result_1': [], 'all_rows_2': [0], 'elevation (m)_3': [0], '2000_4': [0]} | ['peak', 'country', 'elevation ( m )', 'prominence ( m )', 'col ( m )'] | [['piton des neiges', 'france ( rãunion )', '3069', '3069', '0'], ['maromokotro', 'madagascar', '2876', '2876', '0'], ['mount karthala', 'comoros ( grande comore )', '2361', '2361', '0'], ['pic boby', 'madagascar', '2658', '1875', '783'], ['tsiafajavona', 'madagascar', '2643', '1663', '980'], ['ntingui', 'comoros ( anjouan )', '1595', '1595', '0']] |
united states house of representatives elections , 1816 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1816 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2668347-14.html.csv | ordinal | caleb tompkins recorded the highest percentage ratio among all candidates of the 1816 house of representatives elections . | {'row': '1', 'col': '6', 'order': '1', 'col_other': 'n/a', 'max_or_min': 'max_to_min', 'value_mentioned': 'yes', 'scope': 'all', 'subset': None} | {'func': 'eq', 'args': [{'func': 'nth_max', 'args': ['all_rows', 'candidates', '1'], 'result': 'caleb tompkins ( dr ) 56.8 % abraham odell ( f ) 42.8 %', 'ind': 0, 'tostr': 'nth_max { all_rows ; candidates ; 1 }', 'tointer': 'the 1st maximum candidates record of all rows is caleb tompkins ( dr ) 56.8 % abraham odell ( f ) 42.8 % .'}, 'caleb tompkins ( dr ) 56.8 % abraham odell ( f ) 42.8 %'], 'result': True, 'ind': 1, 'tostr': 'eq { nth_max { all_rows ; candidates ; 1 } ; caleb tompkins ( dr ) 56.8 % abraham odell ( f ) 42.8 % } = true', 'tointer': 'the 1st maximum candidates record of all rows is caleb tompkins ( dr ) 56.8 % abraham odell ( f ) 42.8 % .'} | eq { nth_max { all_rows ; candidates ; 1 } ; caleb tompkins ( dr ) 56.8 % abraham odell ( f ) 42.8 % } = true | the 1st maximum candidates record of all rows is caleb tompkins ( dr ) 56.8 % abraham odell ( f ) 42.8 % . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'nth_max_0': 0, 'all_rows_3': 3, 'candidates_4': 4, '1_5': 5, 'caleb tompkins (dr) 56.8% abraham odell (f) 42.8%_6': 6} | {'eq_1': 'eq', 'result_2': 'true', 'nth_max_0': 'nth_max', 'all_rows_3': 'all_rows', 'candidates_4': 'candidates', '1_5': '1', 'caleb tompkins (dr) 56.8% abraham odell (f) 42.8%_6': 'caleb tompkins ( dr ) 56.8 % abraham odell ( f ) 42.8 %'} | {'eq_1': [2], 'result_2': [], 'nth_max_0': [1], 'all_rows_3': [0], 'candidates_4': [0], '1_5': [0], 'caleb tompkins (dr) 56.8% abraham odell (f) 42.8%_6': [1]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['new york 3', 'jonathan ward', 'democratic - republican', '1814', 'retired democratic - republican hold', 'caleb tompkins ( dr ) 56.8 % abraham odell ( f ) 42.8 %'], ['new york 6', 'james w wilkin', 'democratic - republican', '1815 ( special )', 're - elected', 'james w wilkin ( dr ) 55.4 % james burt ( f ) 44.6 %'], ['new york 7', 'samuel r betts', 'democratic - republican', '1814', 'retired democratic - republican hold', 'josiah hasbrouck ( dr ) 51.7 % john sudam ( f ) 48.2 %'], ['new york 10', 'hosea moffitt', 'federalist', '1812', 'retired federalist hold', 'john p cushman ( f ) 54.9 % thomas turner ( dr ) 44.9 %'], ['new york 11', 'john w taylor', 'democratic - republican', '1812', 're - elected', 'john w taylor ( dr ) 53.4 % elisha powell ( f ) 46.6 %'], ['new york 13', 'john b yates', 'democratic - republican', '1814', 'retired democratic - republican hold', 'thomas lawyer ( dr ) 54.9 % william beekman ( f ) 45.1 %'], ['new york 17', 'westel willoughby , jr', 'federalist', '1814', 'retired democratic - republican gain', 'thomas h hubbard ( dr ) 51.5 % simeon ford ( f ) 48.4 %'], ['new york 18', 'moss kent', 'federalist', '1812', 'retired federalist hold', 'david a ogden ( f ) 50.4 % ela collins ( dr ) 49.5 %']] |
united states house of representatives elections , 1812 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1812 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2668367-14.html.csv | unique | north carolina 9 was the only district of the 1812 house of representatives elections with a new seat democratic - republican gain . | {'scope': 'all', 'row': '4', 'col': '5', 'col_other': '1', 'criterion': 'equal', 'value': 'new seat democratic - republican gain', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'result', 'new seat democratic - republican gain'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose result record fuzzily matches to new seat democratic - republican gain .', 'tostr': 'filter_eq { all_rows ; result ; new seat democratic - republican gain }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; result ; new seat democratic - republican gain } }', 'tointer': 'select the rows whose result record fuzzily matches to new seat democratic - republican gain . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'result', 'new seat democratic - republican gain'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose result record fuzzily matches to new seat democratic - republican gain .', 'tostr': 'filter_eq { all_rows ; result ; new seat democratic - republican gain }'}, 'district'], 'result': 'north carolina 9', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; result ; new seat democratic - republican gain } ; district }'}, 'north carolina 9'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; result ; new seat democratic - republican gain } ; district } ; north carolina 9 }', 'tointer': 'the district record of this unqiue row is north carolina 9 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; result ; new seat democratic - republican gain } } ; eq { hop { filter_eq { all_rows ; result ; new seat democratic - republican gain } ; district } ; north carolina 9 } } = true', 'tointer': 'select the rows whose result record fuzzily matches to new seat democratic - republican gain . there is only one such row in the table . the district record of this unqiue row is north carolina 9 .'} | and { only { filter_eq { all_rows ; result ; new seat democratic - republican gain } } ; eq { hop { filter_eq { all_rows ; result ; new seat democratic - republican gain } ; district } ; north carolina 9 } } = true | select the rows whose result record fuzzily matches to new seat democratic - republican gain . there is only one such row in the table . the district record of this unqiue row is north carolina 9 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'result_7': 7, 'new seat democratic - republican gain_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'district_9': 9, 'north carolina 9_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'result_7': 'result', 'new seat democratic - republican gain_8': 'new seat democratic - republican gain', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'district_9': 'district', 'north carolina 9_10': 'north carolina 9'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'result_7': [0], 'new seat democratic - republican gain_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'district_9': [2], 'north carolina 9_10': [3]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['north carolina 2', 'willis alston', 'democratic - republican', '1798', 're - elected', 'willis alston ( dr ) 56.0 % daniel mason ( f ) 44.0 %'], ['north carolina 5', 'william r king', 'democratic - republican', '1810', 're - elected', 'william r king ( dr ) 100 %'], ['north carolina 6', 'nathaniel macon', 'democratic - republican', '1791', 're - elected', 'nathaniel macon ( dr )'], ['north carolina 9', 'none ( district created )', 'none ( district created )', 'none ( district created )', 'new seat democratic - republican gain', 'bartlett yancey ( dr ) 61.1 % james martin ( f ) 38.9 %'], ['north carolina 10', 'joseph pearson', 'federalist', '1808', 're - elected', 'joseph pearson ( f ) 54.1 % alexander gary ( dr ) 45.9 %']] |
danish grand prix | https://en.wikipedia.org/wiki/Danish_Grand_Prix | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-23548160-1.html.csv | count | 8 winners of the danish grand prix won it at roskilde ring . | {'scope': 'all', 'criterion': 'equal', 'value': 'roskilde ring', 'result': '8', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location', 'roskilde ring'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose location record fuzzily matches to roskilde ring .', 'tostr': 'filter_eq { all_rows ; location ; roskilde ring }'}], 'result': '8', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; location ; roskilde ring } }', 'tointer': 'select the rows whose location record fuzzily matches to roskilde ring . the number of such rows is 8 .'}, '8'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; location ; roskilde ring } } ; 8 } = true', 'tointer': 'select the rows whose location record fuzzily matches to roskilde ring . the number of such rows is 8 .'} | eq { count { filter_eq { all_rows ; location ; roskilde ring } } ; 8 } = true | select the rows whose location record fuzzily matches to roskilde ring . the number of such rows is 8 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'location_5': 5, 'roskilde ring_6': 6, '8_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'location_5': 'location', 'roskilde ring_6': 'roskilde ring', '8_7': '8'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'location_5': [0], 'roskilde ring_6': [0], '8_7': [2]} | ['year', 'driver', 'constructor', 'location', 'formula', 'report'] | [['1960', 'jack brabham', 'cooper - climax', 'roskilde ring', 'formula 2', 'report'], ['1961', 'stirling moss', 'lotus - climax', 'roskilde ring', 'formula 1', 'report'], ['1962', 'jack brabham', 'lotus - climax', 'roskilde ring', 'formula 1', 'report'], ['1963', 'peter revson', 'cooper - bmc', 'roskilde ring', 'formula junior', 'report'], ['1964', 'hartvig conradsen', 'cooper - bmc', 'roskilde ring', 'formula junior', 'report'], ['1965', 'kurt ahrens jr', 'brabham - ford', 'roskilde ring', 'formula 3', 'report'], ['1968', 'ingvar pettersson', 'tecno - ford', 'roskilde ring', 'formula 3', 'report'], ['1973', 'randy lewis', 'brabham - ford', 'roskilde ring', 'formula 3', 'report'], ['1974', 'jac nelleman', 'grd - ford', 'jyllandsringen', 'formula 3', 'report'], ['1975', 'jac nelleman', 'grd - ford', 'jyllandsringen', 'formula 3', 'report'], ['1976', 'jac nelleman', 'van diemen - toyota', 'jyllandsringen', 'formula 3', 'report'], ['1977', 'jac nelleman', 'chevron - toyota', 'jyllandsringen', 'formula 3', 'report'], ['1995', 'toni teittinen', 'reynard - mugen - honda', 'jyllandsringen', 'formula 3', 'report']] |
list of england national rugby union team results 1980 - 89 | https://en.wikipedia.org/wiki/List_of_England_national_rugby_union_team_results_1980%E2%80%9389 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18178608-9.html.csv | unique | ireland is the only team to play against the england national rugby team in the millennium trophy match . | {'scope': 'all', 'row': '5', 'col': '5', 'col_other': '1', 'criterion': 'equal', 'value': 'millennium trophy match', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'status', 'millennium trophy match'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose status record fuzzily matches to millennium trophy match .', 'tostr': 'filter_eq { all_rows ; status ; millennium trophy match }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; status ; millennium trophy match } }', 'tointer': 'select the rows whose status record fuzzily matches to millennium trophy match . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'status', 'millennium trophy match'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose status record fuzzily matches to millennium trophy match .', 'tostr': 'filter_eq { all_rows ; status ; millennium trophy match }'}, 'opposing teams'], 'result': 'ireland', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; status ; millennium trophy match } ; opposing teams }'}, 'ireland'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; status ; millennium trophy match } ; opposing teams } ; ireland }', 'tointer': 'the opposing teams record of this unqiue row is ireland .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; status ; millennium trophy match } } ; eq { hop { filter_eq { all_rows ; status ; millennium trophy match } ; opposing teams } ; ireland } } = true', 'tointer': 'select the rows whose status record fuzzily matches to millennium trophy match . there is only one such row in the table . the opposing teams record of this unqiue row is ireland .'} | and { only { filter_eq { all_rows ; status ; millennium trophy match } } ; eq { hop { filter_eq { all_rows ; status ; millennium trophy match } ; opposing teams } ; ireland } } = true | select the rows whose status record fuzzily matches to millennium trophy match . there is only one such row in the table . the opposing teams record of this unqiue row is ireland . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'status_7': 7, 'millennium trophy match_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'opposing teams_9': 9, 'ireland_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'status_7': 'status', 'millennium trophy match_8': 'millennium trophy match', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'opposing teams_9': 'opposing teams', 'ireland_10': 'ireland'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'status_7': [0], 'millennium trophy match_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'opposing teams_9': [2], 'ireland_10': [3]} | ['opposing teams', 'against', 'date', 'venue', 'status'] | [['france', '10', '16 / 01 / 1988', 'parc des princes , paris', 'five nations'], ['wales', '11', '06 / 02 / 1988', 'twickenham , london', 'five nations'], ['scotland', '6', '05 / 03 / 1988', 'murrayfield , edinburgh', 'five nations'], ['ireland', '3', '19 / 03 / 1988', 'twickenham , london', 'five nations'], ['ireland', '10', '23 / 04 / 1988', 'lansdowne road , dublin', 'millennium trophy match'], ['australia', '22', '29 / 05 / 1988', 'ballymore , brisbane', 'first test'], ['australia', '28', '12 / 06 / 1988', 'concord oval , sydney', 'second test'], ['fiji', '12', '16 / 06 / 1988', 'national stadium , suva', 'test match'], ['australia', '19', '05 / 11 / 1988', 'twickenham , london', 'test match']] |
sebastián gonzález | https://en.wikipedia.org/wiki/Sebasti%C3%A1n_Gonz%C3%A1lez | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1257826-1.html.csv | majority | most of the goals were scored in 2001 . | {'scope': 'all', 'col': '2', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': '2001', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'date', '2001'], 'result': True, 'ind': 0, 'tointer': 'for the date records of all rows , most of them fuzzily match to 2001 .', 'tostr': 'most_eq { all_rows ; date ; 2001 } = true'} | most_eq { all_rows ; date ; 2001 } = true | for the date records of all rows , most of them fuzzily match to 2001 . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'date_3': 3, '2001_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'date_3': 'date', '2001_4': '2001'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'date_3': [0], '2001_4': [0]} | ['goal', 'date', 'score', 'result', 'competition'] | [['1', '17 january 2001', '2 - 0', '2 - 0', 'friendly'], ['2', '20 january 2001', '1 - 0', '2 - 0', 'friendly'], ['3', '20 january 2001', '2 - 0', '2 - 0', 'friendly'], ['4', '15 march 2001', '3 - 1', '3 - 1', 'friendly'], ['5', '14 july 2004', '0 - 1', '1 - 1', '2004 copa américa'], ['6', '17 november 2004', '2 - 1', '2 - 1', 'friendly']] |
list of number - one singles of 1999 ( canada ) | https://en.wikipedia.org/wiki/List_of_number-one_singles_of_1999_%28Canada%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17481317-1.html.csv | unique | mambo no 5 is the only number one single of 1999 in canada that spent 11 weeks on top . | {'scope': 'all', 'row': '15', 'col': '3', 'col_other': '4', 'criterion': 'equal', 'value': '11', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'weeks on top', '11'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose weeks on top record is equal to 11 .', 'tostr': 'filter_eq { all_rows ; weeks on top ; 11 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; weeks on top ; 11 } }', 'tointer': 'select the rows whose weeks on top record is equal to 11 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'weeks on top', '11'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose weeks on top record is equal to 11 .', 'tostr': 'filter_eq { all_rows ; weeks on top ; 11 }'}, 'song'], 'result': 'mambo no 5', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; weeks on top ; 11 } ; song }'}, 'mambo no 5'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; weeks on top ; 11 } ; song } ; mambo no 5 }', 'tointer': 'the song record of this unqiue row is mambo no 5 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; weeks on top ; 11 } } ; eq { hop { filter_eq { all_rows ; weeks on top ; 11 } ; song } ; mambo no 5 } } = true', 'tointer': 'select the rows whose weeks on top record is equal to 11 . there is only one such row in the table . the song record of this unqiue row is mambo no 5 .'} | and { only { filter_eq { all_rows ; weeks on top ; 11 } } ; eq { hop { filter_eq { all_rows ; weeks on top ; 11 } ; song } ; mambo no 5 } } = true | select the rows whose weeks on top record is equal to 11 . there is only one such row in the table . the song record of this unqiue row is mambo no 5 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'weeks on top_7': 7, '11_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'song_9': 9, 'mambo no 5_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'weeks on top_7': 'weeks on top', '11_8': '11', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'song_9': 'song', 'mambo no 5_10': 'mambo no 5'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'weeks on top_7': [0], '11_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'song_9': [2], 'mambo no 5_10': [3]} | ['volume : issue', 'issue date ( s )', 'weeks on top', 'song', 'artist'] | [['68:10 - 12', '30 november - 4 january 1999 §', '6 §', 'thank u', 'alanis morissette'], ['68:13', '11 january - 18 january ≠', '2 ≠', "it 's all been done", 'barenaked ladies'], ['68:14', '25 january', '1', 'hands', 'jewel'], ['68:15', '1 february', '1', 'you get what you give', 'new radicals'], ['68:16', '8 february', '1', '… baby one more time', 'britney spears'], ['68:17 - 18', 'information still to be obtained for these weeks', 'information still to be obtained for these weeks', 'information still to be obtained for these weeks', 'information still to be obtained for these weeks'], ['68:19', '1 march', '1', 'believe', 'cher'], ['68:20 - 24', '8 march - 5 april', '5', 'every morning', 'sugar ray'], ['68:25 - 26', '12 april - 19 april', '2', 'love song', 'sky'], ['69:1 - 2', '26 april - 3 may', '2', 'no scrubs', 'tlc'], ['69:3 - 5', '10 may - 24 may', '3', 'kiss me', 'sixpence none the richer'], ['69:6 - 13', '31 may - 19 july', '8', "livin ' la vida loca", 'ricky martin'], ['69:14 - 15', '26 july - 2 august', '2', 'beautiful stranger', 'madonna'], ['69:16 - 21', '9 august - 13 september', '6', 'if you had my love', 'jennifer lopez'], ['69:22 - 26 , 70:1 - 6', '20 september - 29 november', '11', 'mambo no 5', 'lou bega'], ['70:7', '6 december', '1', 'smooth', 'santana featuring rob thomas'], ['70:8 - 9', '13 december - 3 january 2000 ÷', '2 ÷', 'blue', 'eiffel 65']] |
1989 pittsburgh steelers season | https://en.wikipedia.org/wiki/1989_Pittsburgh_Steelers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14563349-11.html.csv | comparative | during the 1989 pittsburgh steelers season , the steelers scored 3 more points on december 24th than they scored on december 17th . | {'row_1': '16', 'row_2': '15', 'col': '6', 'col_other': '2', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', 'sun dec 24'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose date record fuzzily matches to sun dec 24 .', 'tostr': 'filter_eq { all_rows ; date ; sun dec 24 }'}, 'result'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; date ; sun dec 24 } ; result }', 'tointer': 'select the rows whose date record fuzzily matches to sun dec 24 . take the result record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', 'sun dec 17'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose date record fuzzily matches to sun dec 17 .', 'tostr': 'filter_eq { all_rows ; date ; sun dec 17 }'}, 'result'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; date ; sun dec 17 } ; result }', 'tointer': 'select the rows whose date record fuzzily matches to sun dec 17 . take the result record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; date ; sun dec 24 } ; result } ; hop { filter_eq { all_rows ; date ; sun dec 17 } ; result } } = true', 'tointer': 'select the rows whose date record fuzzily matches to sun dec 24 . take the result record of this row . select the rows whose date record fuzzily matches to sun dec 17 . take the result record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; date ; sun dec 24 } ; result } ; hop { filter_eq { all_rows ; date ; sun dec 17 } ; result } } = true | select the rows whose date record fuzzily matches to sun dec 24 . take the result record of this row . select the rows whose date record fuzzily matches to sun dec 17 . take the result record of this row . the first record is greater than the second record . | 5 | 5 | {'greater_4': 4, 'result_5': 5, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'date_7': 7, 'sun dec 24_8': 8, 'result_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'date_11': 11, 'sun dec 17_12': 12, 'result_13': 13} | {'greater_4': 'greater', 'result_5': 'true', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'date_7': 'date', 'sun dec 24_8': 'sun dec 24', 'result_9': 'result', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'date_11': 'date', 'sun dec 17_12': 'sun dec 17', 'result_13': 'result'} | {'greater_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'date_7': [0], 'sun dec 24_8': [0], 'result_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'date_11': [1], 'sun dec 17_12': [1], 'result_13': [3]} | ['week', 'date', 'opponent', 'location', 'time ( et )', 'result', 'record'] | [['1', 'sun sep 10', 'cleveland browns', 'three rivers stadium', '4:00 pm', 'l 51 - 0', '0 - 1'], ['2', 'sun sep 17', 'cincinnati bengals', 'riverfront stadium', '1:00 pm', 'l 41 - 10', '0 - 2'], ['3', 'sun sep 24', 'minnesota vikings', 'three rivers stadium', '1:00 pm', 'w 27 - 14', '1 - 2'], ['4', 'sun oct 1', 'detroit lions', 'pontiac silverdome', '1:00 pm', 'w 23 - 3', '2 - 2'], ['5', 'sun oct 8', 'cincinnati bengals', 'three rivers stadium', '1:00 pm', 'l 26 - 16', '2 - 3'], ['6', 'sun oct 15', 'cleveland browns', 'cleveland municipal stadium', '4:00 pm', 'w 17 - 7', '3 - 3'], ['7', 'sun oct 22', 'houston oilers', 'astrodome', '1:00 pm', 'l 27 - 0', '3 - 4'], ['8', 'sun oct 29', 'kansas city chiefs', 'three rivers stadium', '1:00 pm', 'w 23 - 17', '4 - 4'], ['9', 'sun nov 5', 'denver broncos', 'mile high stadium', '4:00 pm', 'l 34 - 7', '4 - 5'], ['10', 'sun nov 12', 'chicago bears', 'three rivers stadium', '1:00 pm', 'l 20 - 0', '4 - 6'], ['11', 'sun nov 19', 'san diego chargers', 'three rivers stadium', '1:00 pm', 'w 20 - 17', '5 - 6'], ['12', 'sun nov 26', 'miami dolphins', 'joe robbie stadium', '1:00 pm', 'w 34 - 14', '6 - 6'], ['13', 'sun dec 3', 'houston oilers', 'three rivers stadium', '1:00 pm', 'l 23 - 16', '6 - 7'], ['14', 'sun dec 10', 'new york jets', 'giants stadium', '1:00 pm', 'w 13 - 0', '7 - 7'], ['15', 'sun dec 17', 'new england patriots', 'three rivers stadium', '1:00 pm', 'w 28 - 10', '8 - 7'], ['16', 'sun dec 24', 'tampa bay buccaneers', 'tampa stadium', '1:00 pm', 'w 31 - 22', '9 - 7']] |
mañana es para siempre | https://en.wikipedia.org/wiki/Ma%C3%B1ana_es_para_siempre | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18498743-1.html.csv | count | six countries countries began to show the programme mañana es para siempre in 2010 . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': '2010', 'result': '6', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'october 20 , 2008', '2010'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose october 20 , 2008 record fuzzily matches to 2010 .', 'tostr': 'filter_eq { all_rows ; october 20 , 2008 ; 2010 }'}], 'result': '6', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; october 20 , 2008 ; 2010 } }', 'tointer': 'select the rows whose october 20 , 2008 record fuzzily matches to 2010 . the number of such rows is 6 .'}, '6'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; october 20 , 2008 ; 2010 } } ; 6 } = true', 'tointer': 'select the rows whose october 20 , 2008 record fuzzily matches to 2010 . the number of such rows is 6 .'} | eq { count { filter_eq { all_rows ; october 20 , 2008 ; 2010 } } ; 6 } = true | select the rows whose october 20 , 2008 record fuzzily matches to 2010 . the number of such rows is 6 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'october 20 , 2008_5': 5, '2010_6': 6, '6_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'october 20 , 2008_5': 'october 20 , 2008', '2010_6': '2010', '6_7': '6'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'october 20 , 2008_5': [0], '2010_6': [0], '6_7': [2]} | ['mexico', 'mañana es para siempre', 'el canal de las estrellas', 'october 20 , 2008', 'june 14 , 2009', 'monday to friday'] | [['argentina', 'mañana es para siempre', 'canal 9', 'november 10 , 2011', 'march 16 , 2012', 'monday to friday'], ['bulgaria', 'утре и завинаги', 'diema family', 'january 11 , 2010', 'april 30 , 2010', 'monday to friday'], ['bosnia and herzegovina', 'ljubav je večna', 'pink bh', 'december 3 , 2009', 'may 29 , 2010', 'monday to saturday'], ['croatia', 'odavde do vječnosti', 'nova tv', 'february 1 , 2010', 'june 10 , 2010', 'monday to friday'], ['croatia', 'odavde do vječnosti', 'doma tv', 'june 16 , 2011', 'october 30 , 2011', 'monday to friday'], ['estonia', 'igavene homne', 'tv3', 'march 30 , 2010', 'november 8 , 2010', 'monday to friday'], ['hungary', 'mindörökké szerelem', 'rtl klub', 'november 15 , 2010', 'july 8 , 2011', 'monday to friday'], ['macedonia', 'љубовта е вечна', 'sitel tv', '2009', '2009', 'monday to friday'], ['lithuania', 'amžinai tavo', 'lnk', 'march , 2009', 'october 30 , 2009', 'monday to friday'], ['montenegro', 'ljubav je večna', 'pink m', 'august 10 , 2009', 'february 23 , 2010', 'monday to friday'], ['romania', 'impreuna pentru totdeauna', 'acasă', 'march 29 , 2010', 'september 4 , 2010', 'monday to friday'], ['serbia', 'ljubav je večna', 'rtv pink', 'june 5 , 2009', 'january 29 , 2010', 'monday to friday'], ['slovakia', 'love never dies', 'joj plus', 'december 21 , 2009', 'april , 2010', 'monday to friday'], ['slovenia', 'jutri je za večno', 'pop tv', 'september 25 , 2009', 'may 10 , 2010', 'monday to friday'], ['usa', 'mañana es para siempre', 'univision', 'february 23 , 2009', 'october 5 , 2009', 'monday to friday'], ['iran', 'mañana es para siempre', 'pmc', '2010', '2011', 'saturday to wednesday']] |
katarina srebotnik | https://en.wikipedia.org/wiki/Katarina_Srebotnik | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1729366-2.html.csv | comparative | katarina srebotnik finished better at the australian open than at wimbledon . | {'row_1': '10', 'row_2': '8', 'col': '7', 'col_other': '3', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'championship', 'australian open'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose championship record fuzzily matches to australian open .', 'tostr': 'filter_eq { all_rows ; championship ; australian open }'}, 'score in the final'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; championship ; australian open } ; score in the final }', 'tointer': 'select the rows whose championship record fuzzily matches to australian open . take the score in the final record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'championship', 'wimbledon'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose championship record fuzzily matches to wimbledon .', 'tostr': 'filter_eq { all_rows ; championship ; wimbledon }'}, 'score in the final'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; championship ; wimbledon } ; score in the final }', 'tointer': 'select the rows whose championship record fuzzily matches to wimbledon . take the score in the final record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; championship ; australian open } ; score in the final } ; hop { filter_eq { all_rows ; championship ; wimbledon } ; score in the final } } = true', 'tointer': 'select the rows whose championship record fuzzily matches to australian open . take the score in the final record of this row . select the rows whose championship record fuzzily matches to wimbledon . take the score in the final record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; championship ; australian open } ; score in the final } ; hop { filter_eq { all_rows ; championship ; wimbledon } ; score in the final } } = true | select the rows whose championship record fuzzily matches to australian open . take the score in the final record of this row . select the rows whose championship record fuzzily matches to wimbledon . take the score in the final 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, 'championship_7': 7, 'australian open_8': 8, 'score in the final_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'championship_11': 11, 'wimbledon_12': 12, 'score in the final_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', 'championship_7': 'championship', 'australian open_8': 'australian open', 'score in the final_9': 'score in the final', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'championship_11': 'championship', 'wimbledon_12': 'wimbledon', 'score in the final_13': 'score in the final'} | {'greater_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'championship_7': [0], 'australian open_8': [0], 'score in the final_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'championship_11': [1], 'wimbledon_12': [1], 'score in the final_13': [3]} | ['outcome', 'year', 'championship', 'surface', 'partner', 'opponents in the final', 'score in the final'] | [['winner', '1999', 'french open', 'clay', 'piet norval', 'larisa neiland rick leach', '6 - 3 , 3 - 6 , 6 - 3'], ['runner - up', '2002', 'us open', 'hard', 'bob bryan', 'lisa raymond mike bryan', '6 - 7 , 6 - 7'], ['winner', '2003', 'us open', 'hard', 'bob bryan', 'lina krasnoroutskaya daniel nestor', '5 - 7 , 7 - 5 , 7 - 6 ( 7 - 5 )'], ['runner - up', '2005', 'us open', 'hard', 'nenad zimonjić', 'daniela hantuchová mahesh bhupathi', '4 - 6 , 2 - 6'], ['winner', '2006', 'french open ( 2 )', 'clay', 'nenad zimonjić', 'elena likhovtseva daniel nestor', '6 - 3 , 6 - 4'], ['runner - up', '2007', 'french open', 'clay', 'nenad zimonjić', 'nathalie dechy andy ram', '5 - 7 , 3 - 6'], ['runner - up', '2008', 'french open', 'clay', 'nenad zimonjić', 'victoria azarenka bob bryan', '2 - 6 , 6 - 7 ( 4 - 7 )'], ['runner - up', '2008', 'wimbledon', 'grass', 'mike bryan', 'samantha stosur bob bryan', '5 - 7 , 4 - 6'], ['winner', '2010', 'french open ( 3 )', 'clay', 'nenad zimonjić', 'yaroslava shvedova julian knowle', '4 - 6 , 7 - 6 ( 7 - 5 ) ,'], ['winner', '2011', 'australian open', 'hard', 'daniel nestor', 'yung - jan chan paul hanley', '6 - 3 , 3 - 6 ,'], ['runner - up', '2011', 'french open', 'clay', 'nenad zimonjić', 'casey dellacqua scott lipsky', '6 - 7 ( 6 - 8 ) , 6 - 4 ,']] |
thor - christian ebbesvik | https://en.wikipedia.org/wiki/Thor-Christian_Ebbesvik | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-20398823-1.html.csv | superlative | the highest number of podiums that thor-christian ebbesvik had was when he had 357 points . | {'scope': 'all', 'col_superlative': '8', 'row_superlative': '3', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '9', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'podiums'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; podiums }'}, 'points'], 'result': '357', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; podiums } ; points }'}, '357'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; podiums } ; points } ; 357 } = true', 'tointer': 'select the row whose podiums record of all rows is maximum . the points record of this row is 357 .'} | eq { hop { argmax { all_rows ; podiums } ; points } ; 357 } = true | select the row whose podiums record of all rows is maximum . the points record of this row is 357 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'podiums_5': 5, 'points_6': 6, '357_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'podiums_5': 'podiums', 'points_6': 'points', '357_7': '357'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'podiums_5': [0], 'points_6': [1], '357_7': [2]} | ['season', 'series', 'team', 'races', 'wins', 'poles', 'f / laps', 'podiums', 'points', 'position'] | [['2005', 'british formula ford championship', 'team jlr', '20', '0', '0', '0', '0', '321', '6th'], ['2005', 'formula ford festival', 'team jlr', '1', '0', '0', '0', '0', 'n / a', 'nc'], ['2006', 'british formula ford championship', 'team jlr', '20', '1', '0', '2', '4', '357', '4th'], ['2006', 'formula ford festival - duratec class', 'team jlr', '1', '0', '0', '0', '0', 'n / a', 'nc'], ['2007', 'spanish formula three championship', 'team west - tec', '14', '0', '0', '0', '0', '7', '16th'], ['2008', 'spanish formula three championship', 'team west - tec', '17', '2', '1', '0', '2', '49', '10th'], ['2009', 'european f3 open championship', 'team west - tec', '16', '1', '1', '1', '3', '64', '5th'], ['2009', 'formula le mans cup', 'hope polevision racing', '2', '0', '0', '0', '0', '16', '20th'], ['2010', 'le mans series - lmp2', 'team bruichladdich', '5', '0', '0', '0', '1', '46', '5th']] |
2008 - 09 sacramento kings season | https://en.wikipedia.org/wiki/2008%E2%80%9309_Sacramento_Kings_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17102076-7.html.csv | majority | kevin martin had the majority of high points performances for the sacramento kings . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': 'kevin martin', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'high points', 'kevin martin'], 'result': True, 'ind': 0, 'tointer': 'for the high points records of all rows , most of them fuzzily match to kevin martin .', 'tostr': 'most_eq { all_rows ; high points ; kevin martin } = true'} | most_eq { all_rows ; high points ; kevin martin } = true | for the high points records of all rows , most of them fuzzily match to kevin martin . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'high points_3': 3, 'kevin martin_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'high points_3': 'high points', 'kevin martin_4': 'kevin martin'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'high points_3': [0], 'kevin martin_4': [0]} | ['game', 'date', 'team', 'score', 'high points', 'high assists', 'location attendance', 'record'] | [['33', 'january 2', 'detroit', 'l 92 - 98 ( ot )', 'brad miller ( 25 )', 'john salmons ( 4 )', 'the palace of auburn hills 22076', '8 - 25'], ['34', 'january 3', 'indiana', 'l 117 - 122 ( ot )', 'kevin martin ( 45 )', 'kevin martin , brad miller ( 6 )', 'conseco fieldhouse 12765', '8 - 26'], ['35', 'january 5', 'new jersey', 'l 90 - 98 ( ot )', 'kevin martin ( 36 )', 'brad miller ( 8 )', 'izod center 12314', '8 - 27'], ['36', 'january 6', 'chicago', 'l 94 - 99 ( ot )', 'kevin martin ( 29 )', 'beno udrih ( 5 )', 'united center 18060', '8 - 28'], ['37', 'january 9', 'miami', 'l 115 - 119 ( ot )', 'john salmons ( 29 )', 'john salmons , brad miller , bobby jackson ( 4 )', 'arco arena 12587', '8 - 29'], ['38', 'january 11', 'dallas', 'w 102 - 95 ( ot )', 'kevin martin ( 21 )', 'beno udrih ( 6 )', 'arco arena 12294', '9 - 29'], ['39', 'january 13', 'orlando', 'l 107 - 139 ( ot )', 'kevin martin ( 30 )', 'francisco garcía ( 5 )', 'arco arena 11168', '9 - 30'], ['40', 'january 14', 'golden state', 'w 135 - 133 ( 3ot )', 'brad miller ( 30 )', 'john salmons , beno udrih ( 7 )', 'oracle arena 19122', '10 - 30'], ['41', 'january 16', 'milwaukee', 'l 122 - 129 ( ot )', 'john salmons , kevin martin ( 24 )', 'john salmons ( 6 )', 'arco arena 11663', '10 - 31'], ['42', 'january 20', 'denver', 'l 99 - 118 ( ot )', 'kevin martin ( 25 )', 'john salmons , beno udrih ( 5 )', 'pepsi center 15164', '10 - 32'], ['43', 'january 21', 'washington', 'l 107 - 110 ( ot )', 'john salmons , beno udrih ( 24 )', 'john salmons ( 5 )', 'arco arena 10821', '10 - 33'], ['44', 'january 24', 'milwaukee', 'l 104 - 106 ( ot )', 'kevin martin ( 20 )', 'brad miller ( 9 )', 'bradley center 15379', '10 - 34'], ['45', 'january 25', 'toronto', 'l 97 - 113 ( ot )', 'john salmons ( 21 )', 'beno udrih ( 5 )', 'air canada centre 18127', '10 - 35'], ['46', 'january 27', 'cleveland', 'l 110 - 117 ( ot )', 'kevin martin ( 35 )', 'kevin martin ( 7 )', 'quicken loans arena 20562', '10 - 36'], ['47', 'january 28', 'boston', 'l 100 - 119 ( ot )', 'john salmons ( 22 )', 'john salmons ( 5 )', 'td banknorth garden 18624', '10 - 37'], ['48', 'january 30', 'chicago', 'l 88 - 109 ( ot )', 'kevin martin ( 27 )', 'spencer hawes , kevin martin ( 3 )', 'arco arena 13356', '10 - 38']] |
1985 senior pga tour | https://en.wikipedia.org/wiki/1985_Senior_PGA_Tour | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11622829-4.html.csv | unique | gene littler was the only player to earn less than $ 56,000 in 1985 . | {'scope': 'all', 'row': '5', 'col': '4', 'col_other': '2', 'criterion': 'less_than', 'value': '560000', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'earnings', '560000'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose earnings record is less than 560000 .', 'tostr': 'filter_less { all_rows ; earnings ; 560000 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_less { all_rows ; earnings ; 560000 } }', 'tointer': 'select the rows whose earnings record is less than 560000 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'earnings', '560000'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose earnings record is less than 560000 .', 'tostr': 'filter_less { all_rows ; earnings ; 560000 }'}, 'player'], 'result': 'gene littler', 'ind': 2, 'tostr': 'hop { filter_less { all_rows ; earnings ; 560000 } ; player }'}, 'gene littler'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_less { all_rows ; earnings ; 560000 } ; player } ; gene littler }', 'tointer': 'the player record of this unqiue row is gene littler .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_less { all_rows ; earnings ; 560000 } } ; eq { hop { filter_less { all_rows ; earnings ; 560000 } ; player } ; gene littler } } = true', 'tointer': 'select the rows whose earnings record is less than 560000 . there is only one such row in the table . the player record of this unqiue row is gene littler .'} | and { only { filter_less { all_rows ; earnings ; 560000 } } ; eq { hop { filter_less { all_rows ; earnings ; 560000 } ; player } ; gene littler } } = true | select the rows whose earnings record is less than 560000 . there is only one such row in the table . the player record of this unqiue row is gene littler . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_less_0': 0, 'all_rows_6': 6, 'earnings_7': 7, '560000_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'player_9': 9, 'gene littler_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_less_0': 'filter_less', 'all_rows_6': 'all_rows', 'earnings_7': 'earnings', '560000_8': '560000', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'player_9': 'player', 'gene littler_10': 'gene littler'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_less_0': [1, 2], 'all_rows_6': [0], 'earnings_7': [0], '560000_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'player_9': [2], 'gene littler_10': [3]} | ['rank', 'player', 'country', 'earnings', 'wins'] | [['1', 'don january', 'united states', '1038996', '18'], ['2', 'miller barber', 'united states', '962133', '17'], ['3', 'peter thomson', 'australia', '706812', '11'], ['4', 'arnold palmer', 'united states', '579998', '9'], ['5', 'gene littler', 'united states', '559751', '3']] |
taniec z gwiazdami | https://en.wikipedia.org/wiki/Taniec_z_gwiazdami | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15988037-19.html.csv | comparative | pawl stasiak had a higher average score than paolo cozza in the taniec z gwiazdami competition . | {'row_1': '5', 'row_2': '11', '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', 'celebrity', 'paweł stasiak'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose celebrity record fuzzily matches to paweł stasiak .', 'tostr': 'filter_eq { all_rows ; celebrity ; paweł stasiak }'}, 'average'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; celebrity ; paweł stasiak } ; average }', 'tointer': 'select the rows whose celebrity record fuzzily matches to paweł stasiak . take the average record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'celebrity', 'paolo cozza'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose celebrity record fuzzily matches to paolo cozza .', 'tostr': 'filter_eq { all_rows ; celebrity ; paolo cozza }'}, 'average'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; celebrity ; paolo cozza } ; average }', 'tointer': 'select the rows whose celebrity record fuzzily matches to paolo cozza . take the average record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; celebrity ; paweł stasiak } ; average } ; hop { filter_eq { all_rows ; celebrity ; paolo cozza } ; average } } = true', 'tointer': 'select the rows whose celebrity record fuzzily matches to paweł stasiak . take the average record of this row . select the rows whose celebrity record fuzzily matches to paolo cozza . take the average record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; celebrity ; paweł stasiak } ; average } ; hop { filter_eq { all_rows ; celebrity ; paolo cozza } ; average } } = true | select the rows whose celebrity record fuzzily matches to paweł stasiak . take the average record of this row . select the rows whose celebrity record fuzzily matches to paolo cozza . take the average 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, 'celebrity_7': 7, 'paweł stasiak_8': 8, 'average_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'celebrity_11': 11, 'paolo cozza_12': 12, 'average_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', 'celebrity_7': 'celebrity', 'paweł stasiak_8': 'paweł stasiak', 'average_9': 'average', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'celebrity_11': 'celebrity', 'paolo cozza_12': 'paolo cozza', 'average_13': 'average'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'celebrity_7': [0], 'paweł stasiak_8': [0], 'average_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'celebrity_11': [1], 'paolo cozza_12': [1], 'average_13': [3]} | ['rank', 'celebrity', 'professional partner', 'season', 'average'] | [['1', 'maciej jachowski', 'janja lesar', '12', '32.0'], ['2', 'stachursky', 'dominika kublik - marzec', '6', '29.0'], ['3', 'przemysław miarczyński', 'magdalena soszyńska - michno', '11', '28.5'], ['4', 'piotr adamski', 'blanka winiarska', '2', '28.0'], ['5', 'paweł stasiak', 'janja lesar', '8', '27.0'], ['5', 'marek kościkiewicz', 'agnieszka pomorska', '10', '27.0'], ['6', 'wojciech majchrzak', 'magdalena soszyńska - michno', '5', '25.5'], ['7', 'michał milowicz', 'izabela mika', '4', '25.0'], ['7', 'michał lesień', 'katarzyna krupa', '7', '25.0'], ['8', 'robert kudelski', 'agnieszka pomorska', '1', '24.0'], ['9', 'paolo cozza', 'kamila drezno', '3', '18.5'], ['10', 'zbigniew urbański', 'izabela janachowska', '13', '13.0']] |
2010 fifa world cup statistics | https://en.wikipedia.org/wiki/2010_FIFA_World_Cup_statistics | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27708484-3.html.csv | count | five of the stadiums had at least 90 % capacity filled during the 2010 world cup . | {'scope': 'all', 'criterion': 'greater_than_eq', 'value': '90', 'result': '5', 'col': '7', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater_eq', 'args': ['all_rows', 'average attendance as % of capacity', '90'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose average attendance as % of capacity record is greater than or equal to 90 .', 'tostr': 'filter_greater_eq { all_rows ; average attendance as % of capacity ; 90 }'}], 'result': '5', 'ind': 1, 'tostr': 'count { filter_greater_eq { all_rows ; average attendance as % of capacity ; 90 } }', 'tointer': 'select the rows whose average attendance as % of capacity record is greater than or equal to 90 . the number of such rows is 5 .'}, '5'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_greater_eq { all_rows ; average attendance as % of capacity ; 90 } } ; 5 } = true', 'tointer': 'select the rows whose average attendance as % of capacity record is greater than or equal to 90 . the number of such rows is 5 .'} | eq { count { filter_greater_eq { all_rows ; average attendance as % of capacity ; 90 } } ; 5 } = true | select the rows whose average attendance as % of capacity record is greater than or equal to 90 . the number of such rows is 5 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_greater_eq_0': 0, 'all_rows_4': 4, 'average attendance as % of capacity_5': 5, '90_6': 6, '5_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_greater_eq_0': 'filter_greater_eq', 'all_rows_4': 'all_rows', 'average attendance as % of capacity_5': 'average attendance as % of capacity', '90_6': '90', '5_7': '5'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_greater_eq_0': [1], 'all_rows_4': [0], 'average attendance as % of capacity_5': [0], '90_6': [0], '5_7': [2]} | ['stadium', 'city', 'capacity', 'matches played', 'overall attendance', 'average attendance per match', 'average attendance as % of capacity', 'overall goals scored', 'average goals scored per match', 'elevation'] | [['cape town stadium', 'cape town', '64100', '8', '507340', '63418', '98.9', '22', '2.75', '0 ( sea level )'], ['ellis park stadium', 'johannesburg', '55686', '7', '372843', '53263', '95.7', '19', '2.71', '1753 m'], ['free state stadium', 'bloemfontein', '40911', '6', '196823', '32804', '80.2', '14', '2.33', '1400 m'], ['loftus versfield stadium', 'pretoria', '42858', '6', '234092', '39015', '91.0', '11', '1.83', '1214 m'], ['mbombela stadium', 'nelspruit', '40929', '4', '143492', '35873', '87.6', '9', '2.25', '660 m'], ['moses mabhida stadium', 'durban', '62760', '7', '434631', '62090', '98.9', '14', '2.00', '0 ( sea level )'], ['nelson mandela bay stadium', 'port elizabeth', '42486', '8', '285643', '35705', '84.0', '16', '2.00', '0 ( sea level )'], ['peter mokaba stadium', 'polokwane', '41733', '4', '139436', '34859', '83.5', '5', '1.25', '1310 m'], ['royal bafokeng stadium', 'rustenburg', '38646', '6', '193697', '32283', '83.5', '14', '2.33', '1500 m'], ['soccer city', 'johannesburg', '84490', '8', '670809', '83851', '99.2', '21', '2.63', '1753 m']] |
tiburones rojos de veracruz | https://en.wikipedia.org/wiki/Tiburones_Rojos_de_Veracruz | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1193316-2.html.csv | comparative | the tiburones rojos placed higher in regular season 1 in 2001-02 than in regular season 1 2002-03 . | {'row_1': '1', 'row_2': '2', 'col': '3', 'col_other': '1', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'season', '2001 - 02'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose season record fuzzily matches to 2001 - 02 .', 'tostr': 'filter_eq { all_rows ; season ; 2001 - 02 }'}, 'regular season 1'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; season ; 2001 - 02 } ; regular season 1 }', 'tointer': 'select the rows whose season record fuzzily matches to 2001 - 02 . take the regular season 1 record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'season', '2002 - 03'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose season record fuzzily matches to 2002 - 03 .', 'tostr': 'filter_eq { all_rows ; season ; 2002 - 03 }'}, 'regular season 1'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; season ; 2002 - 03 } ; regular season 1 }', 'tointer': 'select the rows whose season record fuzzily matches to 2002 - 03 . take the regular season 1 record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; season ; 2001 - 02 } ; regular season 1 } ; hop { filter_eq { all_rows ; season ; 2002 - 03 } ; regular season 1 } } = true', 'tointer': 'select the rows whose season record fuzzily matches to 2001 - 02 . take the regular season 1 record of this row . select the rows whose season record fuzzily matches to 2002 - 03 . take the regular season 1 record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; season ; 2001 - 02 } ; regular season 1 } ; hop { filter_eq { all_rows ; season ; 2002 - 03 } ; regular season 1 } } = true | select the rows whose season record fuzzily matches to 2001 - 02 . take the regular season 1 record of this row . select the rows whose season record fuzzily matches to 2002 - 03 . take the regular season 1 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, 'season_7': 7, '2001 - 02_8': 8, 'regular season 1_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'season_11': 11, '2002 - 03_12': 12, 'regular season 1_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', 'season_7': 'season', '2001 - 02_8': '2001 - 02', 'regular season 1_9': 'regular season 1', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'season_11': 'season', '2002 - 03_12': '2002 - 03', 'regular season 1_13': 'regular season 1'} | {'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'season_7': [0], '2001 - 02_8': [0], 'regular season 1_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'season_11': [1], '2002 - 03_12': [1], 'regular season 1_13': [3]} | ['season', 'pyramid level', 'regular season 1', 'playoffs 1', 'regular season 2', 'playoffs 2', 'copa mãxico', 'concacaf'] | [['2001 - 02', '2 and 1', '4th', 'champions', '11th', 'did not qualify', 'no longer played', 'did not qualify'], ['2002 - 03', '1', '18th', 'did not qualify', '7th', 'quarterfinals', 'no longer played', 'did not qualify'], ['2003 - 04', '1', '12th', 'did not qualify', '20th', 'did not qualify', 'no longer played', 'did not qualify'], ['2004 - 05', '1', '1st', 'quarterfinals', '17th', 'did not qualify', 'no longer played', 'did not qualify'], ['2005 - 06', '1', '18th', 'did not qualify', '16th', 'did not qualify', 'no longer played', 'did not qualify'], ['2006 - 07', '1', '9th', 'repechaje', '18th', 'did not qualify', 'no longer played', 'did not qualify'], ['2007 - 08', '1', '13th', 'did not qualify', '16th', 'did not qualify', 'no longer played', 'did not qualify'], ['2008 - 09', '2', '11th', 'did not qualify', '3rd', 'semifinal', 'no longer played', 'did not qualify'], ['2009 - 10', '2', '4th', 'semifinal', '15th', 'did not qualify', 'no longer played', 'did not qualify'], ['2010 - 11', '2', '5th', 'second place', '5th', 'disqualified', 'no longer played', 'did not qualify'], ['2011 - 12', '2', '8th', 'did not qualify', '13th', 'did not qualify', 'no longer played', 'did not qualify'], ['2012 - 13', '2', '12th', 'did not qualify', '4th', 'quarterfinals', '4th ( dnq )', 'did not qualify']] |
1995 men 's world ice hockey championships | https://en.wikipedia.org/wiki/1995_Men%27s_World_Ice_Hockey_Championships | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13771649-3.html.csv | majority | all of the games in the 1995 men 's world ice hockey championships had a number of 5 . | {'scope': 'all', 'col': '1', 'most_or_all': 'most', 'criterion': 'equal', 'value': '5', 'subset': None} | {'func': 'most_eq', 'args': ['all_rows', 'games', '5'], 'result': True, 'ind': 0, 'tointer': 'for the games records of all rows , most of them are equal to 5 .', 'tostr': 'most_eq { all_rows ; games ; 5 } = true'} | most_eq { all_rows ; games ; 5 } = true | for the games records of all rows , most of them are equal to 5 . | 1 | 1 | {'most_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'games_3': 3, '5_4': 4} | {'most_eq_0': 'most_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'games_3': 'games', '5_4': '5'} | {'most_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'games_3': [0], '5_4': [0]} | ['games', 'drawn', 'lost', 'points difference', 'points'] | [['5', '2', '0', '17 - 11', '8'], ['5', '1', '1', '22 - 14', '7'], ['5', '1', '1', '17 - 09', '7'], ['5', '0', '2', '14 - 09', '6'], ['5', '0', '4', '09 - 18', '2'], ['5', '0', '5', '09 - 27', '0']] |
1982 all - ireland senior hurling championship | https://en.wikipedia.org/wiki/1982_All-Ireland_Senior_Hurling_Championship | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10577744-2.html.csv | superlative | the player with the highest number of points was pádraig horan . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'total'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; total }'}, 'rank'], 'result': '1', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; total } ; rank }'}, '1'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; total } ; rank } ; 1 } = true', 'tointer': 'select the row whose total record of all rows is maximum . the rank record of this row is 1 .'} | eq { hop { argmax { all_rows ; total } ; rank } ; 1 } = true | select the row whose total record of all rows is maximum . the rank record of this row is 1 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'num_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'total_5': 5, 'rank_6': 6, '1_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'num_hop_1': 'num_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'total_5': 'total', 'rank_6': 'rank', '1_7': '1'} | {'eq_2': [3], 'result_3': [], 'num_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'total_5': [0], 'rank_6': [1], '1_7': [2]} | ['rank', 'player', 'county', 'tally', 'total', 'matches', 'average'] | [['1', 'pádraig horan', 'offaly', '5 - 17', '32', '4', '8.00'], ['2', 'billy fitzpatrick', 'kilkenny', '2 - 24', '30', '4', '7.50'], ['3', "tony o ' sullivan", 'cork', '0 - 28', '28', '4', '7.00'], ['4', 'p j molloy', 'galway', '3 - 11', '20', '2', '10.00'], ['5', 'christy heffernan', 'kilkenny', '3 - 9', '18', '4', '4.50'], ['5', 'pat horgan', 'cork', '0 - 18', '18', '4', '4.50']] |
toronto raptors all - time roster | https://en.wikipedia.org/wiki/Toronto_Raptors_all-time_roster | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-10015132-7.html.csv | majority | most of the players for the toronto raptors have the nationality of united states . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'united states', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'nationality', 'united states'], 'result': True, 'ind': 0, 'tointer': 'for the nationality records of all rows , most of them fuzzily match to united states .', 'tostr': 'most_eq { all_rows ; nationality ; united states } = true'} | most_eq { all_rows ; nationality ; united states } = true | for the nationality records of all rows , most of them fuzzily match to united states . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'nationality_3': 3, 'united states_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'nationality_3': 'nationality', 'united states_4': 'united states'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'nationality_3': [0], 'united states_4': [0]} | ['player', 'no', 'nationality', 'position', 'years in toronto', 'school / club team'] | [['sundiata gaines', '2', 'united states', 'guard', '2011', 'georgia'], ['jorge garbajosa', '15', 'spain', 'forward', '2006 - 08', 'cb mã ¡ laga ( spain )'], ['chris garner', '0', 'united states', 'guard', '1997 - 98', 'memphis'], ['rudy gay', '22', 'united states', 'forward', '2013 - present', 'connecticut'], ['dion glover', '22', 'united states', 'guard', '2004', 'georgia tech'], ['joey graham', '14', 'united states', 'guard - forward', '2005 - 09', 'oklahoma state']] |
eurovision song contest 2008 | https://en.wikipedia.org/wiki/Eurovision_Song_Contest_2008 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11173692-2.html.csv | comparative | in the eurovision song contest of 2008 , hind had 5 more points than gisela . | {'row_1': '15', 'row_2': '12', 'col': '6', 'col_other': '3', 'relation': 'diff', 'record_mentioned': 'no', 'diff_result': {'diff_value': '5', 'bigger': 'row1'}} | {'func': 'eq', 'args': [{'func': 'diff', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'artist', 'hind'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose artist record fuzzily matches to hind .', 'tostr': 'filter_eq { all_rows ; artist ; hind }'}, 'points'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; artist ; hind } ; points }', 'tointer': 'select the rows whose artist record fuzzily matches to hind . take the points record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'artist', 'gisela'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose artist record fuzzily matches to gisela .', 'tostr': 'filter_eq { all_rows ; artist ; gisela }'}, 'points'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; artist ; gisela } ; points }', 'tointer': 'select the rows whose artist record fuzzily matches to gisela . take the points record of this row .'}], 'result': '5', 'ind': 4, 'tostr': 'diff { hop { filter_eq { all_rows ; artist ; hind } ; points } ; hop { filter_eq { all_rows ; artist ; gisela } ; points } }'}, '5'], 'result': True, 'ind': 5, 'tostr': 'eq { diff { hop { filter_eq { all_rows ; artist ; hind } ; points } ; hop { filter_eq { all_rows ; artist ; gisela } ; points } } ; 5 } = true', 'tointer': 'select the rows whose artist record fuzzily matches to hind . take the points record of this row . select the rows whose artist record fuzzily matches to gisela . take the points record of this row . the first record is 5 larger than the second record .'} | eq { diff { hop { filter_eq { all_rows ; artist ; hind } ; points } ; hop { filter_eq { all_rows ; artist ; gisela } ; points } } ; 5 } = true | select the rows whose artist record fuzzily matches to hind . take the points record of this row . select the rows whose artist record fuzzily matches to gisela . take the points record of this row . the first record is 5 larger than the second record . | 6 | 6 | {'eq_5': 5, 'result_6': 6, 'diff_4': 4, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_7': 7, 'artist_8': 8, 'hind_9': 9, 'points_10': 10, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_11': 11, 'artist_12': 12, 'gisela_13': 13, 'points_14': 14, '5_15': 15} | {'eq_5': 'eq', 'result_6': 'true', 'diff_4': 'diff', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_7': 'all_rows', 'artist_8': 'artist', 'hind_9': 'hind', 'points_10': 'points', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_11': 'all_rows', 'artist_12': 'artist', 'gisela_13': 'gisela', 'points_14': 'points', '5_15': '5'} | {'eq_5': [6], 'result_6': [], 'diff_4': [5], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_7': [0], 'artist_8': [0], 'hind_9': [0], 'points_10': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_11': [1], 'artist_12': [1], 'gisela_13': [1], 'points_14': [3], '5_15': [5]} | ['draw', 'language', 'artist', 'song', 'place', 'points'] | [['01', 'montenegrin', 'stefan filipović', 'zauvijek volim te', '14', '23'], ['02', 'hebrew , english', "boaz ma'uda", 'the fire in your eyes', '5', '104'], ['03', 'serbian , german , finnish', 'kreisiraadio', 'leto svet', '18', '8'], ['04', 'english', 'geta burlacu', 'a century of love', '12', '36'], ['05', 'italian', 'miodio', 'complice', '19', '5'], ['06', 'imaginary', 'ishtar', 'o julissi', '17', '16'], ['07', 'english', 'elnur and samir', 'day after day', '6', '96'], ['08', 'slovene', 'rebeka dremelj', 'vrag naj vzame', '11', '36'], ['09', 'english', 'maria haukaas storeng', 'hold on be strong', '4', '106'], ['10', 'english', 'isis gee', 'for life', '10', '42'], ['11', 'english , french', 'dustin the turkey', 'irelande douze pointe', '15', '22'], ['12', 'english , catalan', 'gisela', 'casanova', '16', '22'], ['13', 'bosnian', 'laka', 'pokušaj', '9', '72'], ['14', 'english , armenian', 'sirusho', 'qélé , qélé ( քելե քելե )', '2', '139'], ['15', 'english', 'hind', 'your heart belongs to me', '13', '27'], ['16', 'finnish', 'teräsbetoni', 'missä miehet ratsastaa', '8', '79'], ['17', 'romanian , italian', 'nico and vlad', 'pe - o margine de lume', '7', '94'], ['18', 'english', 'dima bilan', 'believe', '3', '135'], ['19', 'english', 'kalomira', 'secret combination', '1', '156']] |
tomina province | https://en.wikipedia.org/wiki/Tomina_Province | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2509350-3.html.csv | comparative | more people in padilla speak spanish than quechua . | {'row_1': '5', 'row_2': '1', 'col': '2', 'col_other': '1', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'language', 'spanish'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose language record fuzzily matches to spanish .', 'tostr': 'filter_eq { all_rows ; language ; spanish }'}, 'padilla municipality'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; language ; spanish } ; padilla municipality }', 'tointer': 'select the rows whose language record fuzzily matches to spanish . take the padilla municipality record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'language', 'quechua'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose language record fuzzily matches to quechua .', 'tostr': 'filter_eq { all_rows ; language ; quechua }'}, 'padilla municipality'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; language ; quechua } ; padilla municipality }', 'tointer': 'select the rows whose language record fuzzily matches to quechua . take the padilla municipality record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; language ; spanish } ; padilla municipality } ; hop { filter_eq { all_rows ; language ; quechua } ; padilla municipality } } = true', 'tointer': 'select the rows whose language record fuzzily matches to spanish . take the padilla municipality record of this row . select the rows whose language record fuzzily matches to quechua . take the padilla municipality record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; language ; spanish } ; padilla municipality } ; hop { filter_eq { all_rows ; language ; quechua } ; padilla municipality } } = true | select the rows whose language record fuzzily matches to spanish . take the padilla municipality record of this row . select the rows whose language record fuzzily matches to quechua . take the padilla municipality 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, 'language_7': 7, 'spanish_8': 8, 'padilla municipality_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'language_11': 11, 'quechua_12': 12, 'padilla municipality_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', 'language_7': 'language', 'spanish_8': 'spanish', 'padilla municipality_9': 'padilla municipality', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'language_11': 'language', 'quechua_12': 'quechua', 'padilla municipality_13': 'padilla municipality'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'language_7': [0], 'spanish_8': [0], 'padilla municipality_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'language_11': [1], 'quechua_12': [1], 'padilla municipality_13': [3]} | ['language', 'padilla municipality', 'tomina municipality', 'sopachuy municipality', 'villa alcalá municipality', 'el villar municipality'] | [['quechua', '2181', '7831', '6261', '1167', '1264'], ['aymara', '29', '23', '10', '7', '15'], ['guaraní', '6', '4', '3', '3', '1'], ['another native', '2', '2', '3', '1', '0'], ['spanish', '11585', '4418', '3003', '3576', '4190'], ['foreign', '27', '12', '9', '9', '4'], ['only native', '250', '4036', '3791', '176', '146'], ['native and spanish', '1951', '3803', '2478', '997', '1123']] |
list of songs in rock band | https://en.wikipedia.org/wiki/List_of_songs_in_Rock_Band | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14160327-3.html.csv | unique | dirty little secret is the only song that is from the decade of the 2000s . | {'scope': 'all', 'row': '1', 'col': '3', 'col_other': '1', 'criterion': 'equal', 'value': '2000s', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'decade', '2000s'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose decade record fuzzily matches to 2000s .', 'tostr': 'filter_eq { all_rows ; decade ; 2000s }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; decade ; 2000s } }', 'tointer': 'select the rows whose decade record fuzzily matches to 2000s . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'decade', '2000s'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose decade record fuzzily matches to 2000s .', 'tostr': 'filter_eq { all_rows ; decade ; 2000s }'}, 'song title'], 'result': 'dirty little secret', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; decade ; 2000s } ; song title }'}, 'dirty little secret'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; decade ; 2000s } ; song title } ; dirty little secret }', 'tointer': 'the song title record of this unqiue row is dirty little secret .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; decade ; 2000s } } ; eq { hop { filter_eq { all_rows ; decade ; 2000s } ; song title } ; dirty little secret } } = true', 'tointer': 'select the rows whose decade record fuzzily matches to 2000s . there is only one such row in the table . the song title record of this unqiue row is dirty little secret .'} | and { only { filter_eq { all_rows ; decade ; 2000s } } ; eq { hop { filter_eq { all_rows ; decade ; 2000s } ; song title } ; dirty little secret } } = true | select the rows whose decade record fuzzily matches to 2000s . there is only one such row in the table . the song title record of this unqiue row is dirty little secret . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'decade_7': 7, '2000s_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'song title_9': 9, 'dirty little secret_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'decade_7': 'decade', '2000s_8': '2000s', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'song title_9': 'song title', 'dirty little secret_10': 'dirty little secret'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'decade_7': [0], '2000s_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'song title_9': [2], 'dirty little secret_10': [3]} | ['song title', 'artist', 'decade', 'genre', 'family friendly'] | [['dirty little secret', 'all american rejects the all american rejects', '2000s', 'emo', 'yes'], ["do n't look back in anger", 'oasis', '1990s', 'rock', 'yes'], ['roam', "b - 52 's the b - 52 's", '1980s', 'pop / rock', 'yes'], ['rockaway beach', 'ramones', '1970s', 'punk', 'yes'], ['roxanne', 'police the police', '1970s', 'pop / rock', 'no']] |
list of indoor arenas in the philippines | https://en.wikipedia.org/wiki/List_of_indoor_arenas_in_the_Philippines | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12258195-2.html.csv | superlative | la salle coliseum has the greatest seating capacity of all these arenas . | {'scope': 'all', 'col_superlative': '5', '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', 'maximum seating capacity'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; maximum seating capacity }'}, 'arena / venue'], 'result': 'la salle coliseum', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; maximum seating capacity } ; arena / venue }'}, 'la salle coliseum'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; maximum seating capacity } ; arena / venue } ; la salle coliseum } = true', 'tointer': 'select the row whose maximum seating capacity record of all rows is maximum . the arena / venue record of this row is la salle coliseum .'} | eq { hop { argmax { all_rows ; maximum seating capacity } ; arena / venue } ; la salle coliseum } = true | select the row whose maximum seating capacity record of all rows is maximum . the arena / venue record of this row is la salle coliseum . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'maximum seating capacity_5': 5, 'arena / venue_6': 6, 'la salle coliseum_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'maximum seating capacity_5': 'maximum seating capacity', 'arena / venue_6': 'arena / venue', 'la salle coliseum_7': 'la salle coliseum'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'maximum seating capacity_5': [0], 'arena / venue_6': [1], 'la salle coliseum_7': [2]} | ['arena / venue', 'home campus', 'location', 'province / region', 'maximum seating capacity', 'year opened'] | [['blue eagle gym', 'ateneo de manila university', 'quezon city', 'metro manila', '7500', '1949'], ['la salle coliseum', 'university of st la salle', 'bacolod city', 'negros occidental', '8000', '1998'], ['olivarez sports center', 'olivarez college', 'paraã ± aque city', 'metro manila', 'unknown', 'unknown'], ['quadricentennial pavilion', 'university of sto tomas', 'manila', 'metro manila', '5792', '2009'], ['san agustin gym', 'university of san agustin', 'iloilo city', 'iloilo', 'unknown', 'unknown'], ['university of baguio gym', 'university of baguio', 'baguio city', 'benguet', '5000', 'unknown'], ['west negros university gym', 'west negros university', 'bacolod city', 'negros occidental', 'unknown', 'unknown'], ['xavier university gym', 'xavier university - ateneo de cagayan', 'cagayan de oro city', 'misamis oriental', 'unknown', 'unknown'], ['holy cross of davao college gym ( hcdc )', 'holy cross of davao college', 'davao city', 'davao del sur', '7000', '2001']] |
athletics at the 1963 pan american games | https://en.wikipedia.org/wiki/Athletics_at_the_1963_Pan_American_Games | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10648331-3.html.csv | count | 16 nations were represented in athletics at the 1963 pan american games . | {'scope': 'all', 'criterion': 'all', 'value': 'n/a', 'result': '16', 'col': '2', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_all', 'args': ['all_rows', 'nation'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose nation record is arbitrary .', 'tostr': 'filter_all { all_rows ; nation }'}], 'result': '16', 'ind': 1, 'tostr': 'count { filter_all { all_rows ; nation } }', 'tointer': 'select the rows whose nation record is arbitrary . the number of such rows is 16 .'}, '16'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_all { all_rows ; nation } } ; 16 } = true', 'tointer': 'select the rows whose nation record is arbitrary . the number of such rows is 16 .'} | eq { count { filter_all { all_rows ; nation } } ; 16 } = true | select the rows whose nation record is arbitrary . the number of such rows is 16 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_all_0': 0, 'all_rows_4': 4, 'nation_5': 5, '16_6': 6} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_all_0': 'filter_all', 'all_rows_4': 'all_rows', 'nation_5': 'nation', '16_6': '16'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_all_0': [1], 'all_rows_4': [0], 'nation_5': [0], '16_6': [2]} | ['rank', 'nation', 'gold', 'silver', 'bronze', 'total'] | [['1', 'united states', '22', '15', '10', '47'], ['2', 'canada', '5', '5', '2', '12'], ['3', 'argentina', '2', '2', '1', '5'], ['4', 'venezuela', '1', '3', '3', '7'], ['5', 'cuba', '1', '3', '1', '5'], ['6', 'mexico', '1', '1', '1', '3'], ['7', 'chile', '1', '0', '0', '1'], ['8', 'brazil', '0', '2', '6', '8'], ['9', 'jamaica', '0', '1', '1', '2'], ['10', 'guatemala', '0', '1', '0', '1'], ['11', 'trinidad and tobago', '0', '0', '2', '2'], ['11', 'barbados', '0', '0', '2', '2'], ['13', 'panama', '0', '0', '1', '1'], ['13', 'puerto rico', '0', '0', '1', '1'], ['13', 'uruguay', '0', '0', '1', '1'], ['13', 'netherlands antilles', '0', '0', '1', '1']] |
list of career achievements by tiger woods | https://en.wikipedia.org/wiki/List_of_career_achievements_by_Tiger_Woods | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11570261-1.html.csv | aggregation | in 2006 , the average margin for tiger woods was 3.5 strokes . | {'scope': 'subset', 'col': '5', 'type': 'average', 'result': '3.5', 'subset': {'col': '1', 'criterion': 'equal', 'value': '2006'}} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'year', '2006'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; year ; 2006 }', 'tointer': 'select the rows whose year record is equal to 2006 .'}, 'margin'], 'result': '3.5', 'ind': 1, 'tostr': 'avg { filter_eq { all_rows ; year ; 2006 } ; margin }'}, '3.5'], 'result': True, 'ind': 2, 'tostr': 'round_eq { avg { filter_eq { all_rows ; year ; 2006 } ; margin } ; 3.5 } = true', 'tointer': 'select the rows whose year record is equal to 2006 . the average of the margin record of these rows is 3.5 .'} | round_eq { avg { filter_eq { all_rows ; year ; 2006 } ; margin } ; 3.5 } = true | select the rows whose year record is equal to 2006 . the average of the margin record of these rows is 3.5 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'avg_1': 1, 'filter_eq_0': 0, 'all_rows_4': 4, 'year_5': 5, '2006_6': 6, 'margin_7': 7, '3.5_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'avg_1': 'avg', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'year_5': 'year', '2006_6': '2006', 'margin_7': 'margin', '3.5_8': '3.5'} | {'eq_2': [3], 'result_3': [], 'avg_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'year_5': [0], '2006_6': [0], 'margin_7': [1], '3.5_8': [2]} | ['year', 'championship', '54 holes', 'winning score', 'margin', 'runner ( s ) - up'] | [['1997', 'masters tournament', '9 shot lead', '18 ( 70 + 66 + 65 + 69 = 270 )', '12 strokes', 'tom kite'], ['1999', 'pga championship', 'tied for lead', '11 ( 70 + 67 + 68 + 72 = 277 )', '1 stroke', 'sergio garcía'], ['2000', 'us open', '10 shot lead', '12 ( 65 + 69 + 71 + 67 = 272 )', '15 strokes', 'ernie els , miguel ángel jiménez'], ['2000', 'the open championship', '6 shot lead', '19 ( 67 + 66 + 67 + 69 = 269 )', '8 strokes', 'thomas bjørn , ernie els'], ['2000', 'pga championship ( 2 )', '1 shot lead', '18 ( 66 + 67 + 70 + 67 = 270 )', 'playoff 1', 'bob may'], ['2001', 'masters tournament ( 2 )', '1 shot lead', '16 ( 70 + 66 + 68 + 68 = 272 )', '2 strokes', 'david duval'], ['2002', 'masters tournament ( 3 )', 'tied for lead', '12 ( 70 + 69 + 66 + 71 = 276 )', '3 strokes', 'retief goosen'], ['2002', 'us open ( 2 )', '4 shot lead', '3 ( 67 + 68 + 70 + 72 = 277 )', '3 strokes', 'phil mickelson'], ['2005', 'masters tournament ( 4 )', '3 shot lead', '12 ( 74 + 66 + 65 + 71 = 276 )', 'playoff 2', 'chris dimarco'], ['2005', 'the open championship ( 2 )', '2 shot lead', '14 ( 66 + 67 + 71 + 70 = 274 )', '5 strokes', 'colin montgomerie'], ['2006', 'the open championship ( 3 )', '1 shot lead', '18 ( 67 + 65 + 71 + 67 = 270 )', '2 strokes', 'chris dimarco'], ['2006', 'pga championship ( 3 )', 'tied for lead', '18 ( 69 + 68 + 65 + 68 = 270 )', '5 strokes', 'shaun micheel'], ['2007', 'pga championship ( 4 )', '3 shot lead', '8 ( 71 + 63 + 69 + 69 = 272 )', '2 strokes', 'woody austin'], ['2008', 'us open ( 3 )', '1 shot lead', '1 ( 72 + 68 + 70 + 73 = 283 )', 'playoff 3', 'rocco mediate']] |
portugal in the eurovision song contest 2008 | https://en.wikipedia.org/wiki/Portugal_in_the_Eurovision_Song_Contest_2008 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15739554-1.html.csv | count | during the 2008 portugal eurovision song contest , out of the first three draws , only 1 has votes over 5000 . | {'scope': 'subset', 'criterion': 'greater_than', 'value': '5000', 'result': '1', 'col': '5', 'subset': {'col': '1', 'criterion': 'less_than_eq', 'value': '3'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater', 'args': [{'func': 'filter_less_eq', 'args': ['all_rows', 'draw', '3'], 'result': None, 'ind': 0, 'tostr': 'filter_less_eq { all_rows ; draw ; 3 }', 'tointer': 'select the rows whose draw record is less than or equal to 3 .'}, 'votes', '5000'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose draw record is less than or equal to 3 . among these rows , select the rows whose votes record is greater than 5000 .', 'tostr': 'filter_greater { filter_less_eq { all_rows ; draw ; 3 } ; votes ; 5000 }'}], 'result': '1', 'ind': 2, 'tostr': 'count { filter_greater { filter_less_eq { all_rows ; draw ; 3 } ; votes ; 5000 } }', 'tointer': 'select the rows whose draw record is less than or equal to 3 . among these rows , select the rows whose votes record is greater than 5000 . the number of such rows is 1 .'}, '1'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_greater { filter_less_eq { all_rows ; draw ; 3 } ; votes ; 5000 } } ; 1 } = true', 'tointer': 'select the rows whose draw record is less than or equal to 3 . among these rows , select the rows whose votes record is greater than 5000 . the number of such rows is 1 .'} | eq { count { filter_greater { filter_less_eq { all_rows ; draw ; 3 } ; votes ; 5000 } } ; 1 } = true | select the rows whose draw record is less than or equal to 3 . among these rows , select the rows whose votes record is greater than 5000 . the number of such rows is 1 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_greater_1': 1, 'filter_less_eq_0': 0, 'all_rows_5': 5, 'draw_6': 6, '3_7': 7, 'votes_8': 8, '5000_9': 9, '1_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_greater_1': 'filter_greater', 'filter_less_eq_0': 'filter_less_eq', 'all_rows_5': 'all_rows', 'draw_6': 'draw', '3_7': '3', 'votes_8': 'votes', '5000_9': '5000', '1_10': '1'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_greater_1': [2], 'filter_less_eq_0': [1], 'all_rows_5': [0], 'draw_6': [0], '3_7': [0], 'votes_8': [1], '5000_9': [1], '1_10': [3]} | ['draw', 'artist', 'song', 'producer', 'votes', 'place'] | [['1', 'marco rodridgues', 'em água e sal', 'elvis veiguinha', '5944', '3'], ['2', 'carluz belo', 'cavaleiro da manhã', 'carluz belo', '2049', '8'], ['3', 'big hit', 'por ti , portugal', 'fernando martins', '2934', '6'], ['4', 'lisboa não sejas francesa', 'porto de encontro', 'miguel majer , ricardo santos', '1974', '9'], ['5', 'vnia fernandes', 'senhora do mar', 'carlos coelho', '17650', '1'], ['6', 'vanessa', 'do outro lado da vida', 'nuno feist', '2622', '7'], ['7', 'ricardo soler', 'canção pop', 'renato júnior', '4736', '4'], ['8', 'alex smith', 'obrigatório ter', 'jan van dijck', '6928', '2'], ['9', 'tucha', 'o poder da mensagem', 'ménito ramos', '626', '10'], ['10', 'blá blà blá', 'magicantasticamente', 'gimba', '4616', '5']] |
private practice ( season 1 ) | https://en.wikipedia.org/wiki/Private_Practice_%28season_1%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-24910733-1.html.csv | unique | in the first season of private practice , the only episode that was directed by tony goldwyn was the one titled " in which sam receives an unexpected visitor " . | {'scope': 'all', 'row': '1', 'col': '3', 'col_other': '2', 'criterion': 'equal', 'value': 'tony goldwyn', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'directed by', 'tony goldwyn'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose directed by record fuzzily matches to tony goldwyn .', 'tostr': 'filter_eq { all_rows ; directed by ; tony goldwyn }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; directed by ; tony goldwyn } }', 'tointer': 'select the rows whose directed by record fuzzily matches to tony goldwyn . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'directed by', 'tony goldwyn'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose directed by record fuzzily matches to tony goldwyn .', 'tostr': 'filter_eq { all_rows ; directed by ; tony goldwyn }'}, 'title'], 'result': 'in which sam receives an unexpected visitor', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; directed by ; tony goldwyn } ; title }'}, 'in which sam receives an unexpected visitor'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; directed by ; tony goldwyn } ; title } ; in which sam receives an unexpected visitor }', 'tointer': 'the title record of this unqiue row is in which sam receives an unexpected visitor .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; directed by ; tony goldwyn } } ; eq { hop { filter_eq { all_rows ; directed by ; tony goldwyn } ; title } ; in which sam receives an unexpected visitor } } = true', 'tointer': 'select the rows whose directed by record fuzzily matches to tony goldwyn . there is only one such row in the table . the title record of this unqiue row is in which sam receives an unexpected visitor .'} | and { only { filter_eq { all_rows ; directed by ; tony goldwyn } } ; eq { hop { filter_eq { all_rows ; directed by ; tony goldwyn } ; title } ; in which sam receives an unexpected visitor } } = true | select the rows whose directed by record fuzzily matches to tony goldwyn . there is only one such row in the table . the title record of this unqiue row is in which sam receives an unexpected visitor . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'directed by_7': 7, 'tony goldwyn_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'title_9': 9, 'in which sam receives an unexpected visitor_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'directed by_7': 'directed by', 'tony goldwyn_8': 'tony goldwyn', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'title_9': 'title', 'in which sam receives an unexpected visitor_10': 'in which sam receives an unexpected visitor'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'directed by_7': [0], 'tony goldwyn_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'title_9': [2], 'in which sam receives an unexpected visitor_10': [3]} | ['no in series', 'title', 'directed by', 'written by', 'original air date', 'us viewers ( millions )'] | [['2', 'in which sam receives an unexpected visitor', 'tony goldwyn', 'mike ostrowski', 'october 3 , 2007', '12.30'], ['3', 'in which addison finds the magic', 'mark tinker', 'shonda rhimes & marti noxon', 'october 10 , 2007', '12.40'], ['4', 'in which addison has a very casual get together', 'arvin brown', 'andrea newman', 'october 17 , 2007', '11.81'], ['5', 'in which addison finds a showerhead', 'julie anne robinson', 'shonda rhimes & marti noxon', 'october 24 , 2007', '11.77'], ['6', 'in which charlotte goes down the rabbit hole', 'david solomon', 'jenna bans', 'october 31 , 2007', '11.21'], ['7', 'in which sam gets taken for a ride', 'jeff melman', 'emily halpern', 'november 14 , 2007', '11.45'], ['8', 'in which cooper finds a port in his storm', 'mark tinker', 'lauren schmidt', 'november 21 , 2007', '8.44']] |
2005 - 06 greek cup | https://en.wikipedia.org/wiki/2005%E2%80%9306_Greek_Cup | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13049964-1.html.csv | unique | the 5th round in the 2005 - 06 greek cup is the only game with 8 fixtures . | {'scope': 'all', 'row': '5', 'col': '2', 'col_other': '1', 'criterion': 'equal', 'value': '8', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'fixtures', '8'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose fixtures record is equal to 8 .', 'tostr': 'filter_eq { all_rows ; fixtures ; 8 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; fixtures ; 8 } }', 'tointer': 'select the rows whose fixtures record is equal to 8 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'fixtures', '8'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose fixtures record is equal to 8 .', 'tostr': 'filter_eq { all_rows ; fixtures ; 8 }'}, 'round'], 'result': 'fifth round', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; fixtures ; 8 } ; round }'}, 'fifth round'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; fixtures ; 8 } ; round } ; fifth round }', 'tointer': 'the round record of this unqiue row is fifth round .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; fixtures ; 8 } } ; eq { hop { filter_eq { all_rows ; fixtures ; 8 } ; round } ; fifth round } } = true', 'tointer': 'select the rows whose fixtures record is equal to 8 . there is only one such row in the table . the round record of this unqiue row is fifth round .'} | and { only { filter_eq { all_rows ; fixtures ; 8 } } ; eq { hop { filter_eq { all_rows ; fixtures ; 8 } ; round } ; fifth round } } = true | select the rows whose fixtures record is equal to 8 . there is only one such row in the table . the round record of this unqiue row is fifth round . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'fixtures_7': 7, '8_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'round_9': 9, 'fifth round_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'fixtures_7': 'fixtures', '8_8': '8', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'round_9': 'round', 'fifth round_10': 'fifth round'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'fixtures_7': [0], '8_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'round_9': [2], 'fifth round_10': [3]} | ['round', 'fixtures', 'clubs', 'new entries', 'leagues entering'] | [['first round', '1', '65 → 64', '2', 'gamma ethniki'], ['second round', '16', '64 → 48', '31', 'gamma ethniki'], ['third round', '16', '48 → 32', '16', 'beta ethniki'], ['fourth round', '16', '32 → 16', '16', 'alpha ethniki'], ['fifth round', '8', '16 → 8', 'none', 'none'], ['quarter - finals', '4', '8 → 4', 'none', 'none'], ['semi - finals', '2', '4 → 2', 'none', 'none'], ['final', '1', '2 → 1', 'none', 'none']] |
2005 - 06 mighty ducks of anaheim season | https://en.wikipedia.org/wiki/2005%E2%80%9306_Mighty_Ducks_of_Anaheim_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18987966-3.html.csv | aggregation | in the 2005-06 season of mighty ducks of anaheim , their games against the coyotes had an attendance of 26,689 . | {'scope': 'subset', 'col': '5', 'type': 'sum', 'result': '26,689', 'subset': {'col': '2', 'criterion': 'equal', 'value': 'coyotes'}} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', 'coyotes'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; opponent ; coyotes }', 'tointer': 'select the rows whose opponent record fuzzily matches to coyotes .'}, 'attendance'], 'result': '26,689', 'ind': 1, 'tostr': 'sum { filter_eq { all_rows ; opponent ; coyotes } ; attendance }'}, '26,689'], 'result': True, 'ind': 2, 'tostr': 'round_eq { sum { filter_eq { all_rows ; opponent ; coyotes } ; attendance } ; 26,689 } = true', 'tointer': 'select the rows whose opponent record fuzzily matches to coyotes . the sum of the attendance record of these rows is 26,689 .'} | round_eq { sum { filter_eq { all_rows ; opponent ; coyotes } ; attendance } ; 26,689 } = true | select the rows whose opponent record fuzzily matches to coyotes . the sum of the attendance record of these rows is 26,689 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'sum_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'opponent_5': 5, 'coyotes_6': 6, 'attendance_7': 7, '26,689_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'sum_1': 'sum', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'opponent_5': 'opponent', 'coyotes_6': 'coyotes', 'attendance_7': 'attendance', '26,689_8': '26,689'} | {'eq_2': [3], 'result_3': [], 'sum_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'opponent_5': [0], 'coyotes_6': [0], 'attendance_7': [1], '26,689_8': [2]} | ['date', 'opponent', 'score', 'loss', 'attendance', 'record', 'arena', 'points'] | [['october 5', 'blackhawks', '5 - 3', 'khabibulin ( 0 - 1 - 0 )', '16533', '1 - 0 - 0', 'united center', '2'], ['october 8', 'predators', '3 - 2', 'giguere ( 1 - 0 - 1 )', '16279', '1 - 0 - 1', 'gaylord entertainment center', '3'], ['october 10', 'oilers', '4 - 2', 'giguere ( 1 - 1 - 1 )', '17174', '1 - 1 - 1', 'arrowhead pond of anaheim', '3'], ['october 14', 'blue jackets', '4 - 3', 'leclaire ( 0 - 2 - 0 )', '12930', '2 - 1 - 1', 'arrowhead pond of anaheim', '5'], ['october 16', 'wild', '4 - 1', 'giguere ( 2 - 2 - 1 )', '18568', '2 - 2 - 1', 'xcel energy center', '5'], ['october 19', 'blues', '3 - 2', 'bryzgalov ( 0 - 1 - 0 )', '10882', '2 - 3 - 1', 'savvis center', '5'], ['october 21', 'red wings', '3 - 2', 'bryzgalov ( 0 - 2 - 0 )', '20066', '2 - 4 - 1', 'joe louis arena', '5'], ['october 23', 'coyotes', '5 - 3', 'leneveu ( 0 - 3 - 1 )', '13733', '3 - 4 - 1', 'arrowhead pond of anaheim', '7'], ['october 25', 'kings', '3 - 1', 'bryzgalov ( 1 - 3 - 0 )', '18118', '3 - 5 - 1', 'staples center', '7'], ['october 26', 'flames', '4 - 1', 'kiprusoff ( 4 - 6 - 1 )', '11774', '4 - 5 - 1', 'arrowhead pond of anaheim', '9'], ['october 28', 'blues', '6 - 4', 'divis ( 0 - 1 - 0 )', '12510', '5 - 5 - 1', 'arrowhead pond of anaheim', '11'], ['october 30', 'coyotes', '3 - 2', 'leneveu ( 1 - 4 - 1 )', '12956', '6 - 5 - 1', 'arrowhead pond of anaheim', '13']] |
mike hailwood | https://en.wikipedia.org/wiki/Mike_Hailwood | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1226505-3.html.csv | majority | most of mike hailwood 's wins were won while driving a ford . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'ford', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'engine', 'ford'], 'result': True, 'ind': 0, 'tointer': 'for the engine records of all rows , most of them fuzzily match to ford .', 'tostr': 'most_eq { all_rows ; engine ; ford } = true'} | most_eq { all_rows ; engine ; ford } = true | for the engine records of all rows , most of them fuzzily match to ford . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'engine_3': 3, 'ford_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'engine_3': 'engine', 'ford_4': 'ford'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'engine_3': [0], 'ford_4': [0]} | ['year', 'entrant', 'chassis', 'engine', 'pts'] | [['1963', 'reg parnell racing', 'lotus 24', 'climax', '0'], ['1963', 'reg parnell racing', 'lola mk4', 'climax', '0'], ['1964', 'reg parnell racing', 'lotus 25', 'brm', '1'], ['1965', 'reg parnell racing', 'lotus 25', 'brm', '0'], ['1971', 'team surtees', 'surtees ts9', 'ford', '3'], ['1972', 'brooke bond oxo team surtees', 'surtees ts9b', 'ford', '13'], ['1973', 'brooke bond oxo team surtees', 'surtees ts14a', 'ford', '0'], ['1974', 'yardley team mclaren', 'mclaren m23', 'ford', '12']] |
2010 fifa world cup statistics | https://en.wikipedia.org/wiki/2010_FIFA_World_Cup_statistics | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27708484-3.html.csv | majority | the majority of stadiums for the 2010 world cup can host more than 40,000 people . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'greater_than', 'value': '40000', 'subset': None} | {'func': 'most_greater', 'args': ['all_rows', 'capacity', '40000'], 'result': True, 'ind': 0, 'tointer': 'for the capacity records of all rows , most of them are greater than 40000 .', 'tostr': 'most_greater { all_rows ; capacity ; 40000 } = true'} | most_greater { all_rows ; capacity ; 40000 } = true | for the capacity records of all rows , most of them are greater than 40000 . | 1 | 1 | {'most_greater_0': 0, 'result_1': 1, 'all_rows_2': 2, 'capacity_3': 3, '40000_4': 4} | {'most_greater_0': 'most_greater', 'result_1': 'true', 'all_rows_2': 'all_rows', 'capacity_3': 'capacity', '40000_4': '40000'} | {'most_greater_0': [1], 'result_1': [], 'all_rows_2': [0], 'capacity_3': [0], '40000_4': [0]} | ['stadium', 'city', 'capacity', 'matches played', 'overall attendance', 'average attendance per match', 'average attendance as % of capacity', 'overall goals scored', 'average goals scored per match', 'elevation'] | [['cape town stadium', 'cape town', '64100', '8', '507340', '63418', '98.9', '22', '2.75', '0 ( sea level )'], ['ellis park stadium', 'johannesburg', '55686', '7', '372843', '53263', '95.7', '19', '2.71', '1753 m'], ['free state stadium', 'bloemfontein', '40911', '6', '196823', '32804', '80.2', '14', '2.33', '1400 m'], ['loftus versfield stadium', 'pretoria', '42858', '6', '234092', '39015', '91.0', '11', '1.83', '1214 m'], ['mbombela stadium', 'nelspruit', '40929', '4', '143492', '35873', '87.6', '9', '2.25', '660 m'], ['moses mabhida stadium', 'durban', '62760', '7', '434631', '62090', '98.9', '14', '2.00', '0 ( sea level )'], ['nelson mandela bay stadium', 'port elizabeth', '42486', '8', '285643', '35705', '84.0', '16', '2.00', '0 ( sea level )'], ['peter mokaba stadium', 'polokwane', '41733', '4', '139436', '34859', '83.5', '5', '1.25', '1310 m'], ['royal bafokeng stadium', 'rustenburg', '38646', '6', '193697', '32283', '83.5', '14', '2.33', '1500 m'], ['soccer city', 'johannesburg', '84490', '8', '670809', '83851', '99.2', '21', '2.63', '1753 m']] |
v - league 5th season 1st conference | https://en.wikipedia.org/wiki/V-League_5th_Season_1st_Conference | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16348031-7.html.csv | count | in the v - league 5th season 1st conference , among the teams that were ranked in top 3 , 2 of them had at least 1 loss . | {'scope': 'subset', 'criterion': 'greater_than_eq', 'value': '1', 'result': '2', 'col': '3', 'subset': {'col': '1', 'criterion': 'less_than_eq', 'value': '3'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater_eq', 'args': [{'func': 'filter_less_eq', 'args': ['all_rows', 'rank', '3'], 'result': None, 'ind': 0, 'tostr': 'filter_less_eq { all_rows ; rank ; 3 }', 'tointer': 'select the rows whose rank record is less than or equal to 3 .'}, 'loss', '1'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose rank record is less than or equal to 3 . among these rows , select the rows whose loss record is greater than or equal to 1 .', 'tostr': 'filter_greater_eq { filter_less_eq { all_rows ; rank ; 3 } ; loss ; 1 }'}], 'result': '2', 'ind': 2, 'tostr': 'count { filter_greater_eq { filter_less_eq { all_rows ; rank ; 3 } ; loss ; 1 } }', 'tointer': 'select the rows whose rank record is less than or equal to 3 . among these rows , select the rows whose loss record is greater than or equal to 1 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_greater_eq { filter_less_eq { all_rows ; rank ; 3 } ; loss ; 1 } } ; 2 } = true', 'tointer': 'select the rows whose rank record is less than or equal to 3 . among these rows , select the rows whose loss record is greater than or equal to 1 . the number of such rows is 2 .'} | eq { count { filter_greater_eq { filter_less_eq { all_rows ; rank ; 3 } ; loss ; 1 } } ; 2 } = true | select the rows whose rank record is less than or equal to 3 . among these rows , select the rows whose loss record is greater than or equal to 1 . the number of such rows is 2 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_greater_eq_1': 1, 'filter_less_eq_0': 0, 'all_rows_5': 5, 'rank_6': 6, '3_7': 7, 'loss_8': 8, '1_9': 9, '2_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_greater_eq_1': 'filter_greater_eq', 'filter_less_eq_0': 'filter_less_eq', 'all_rows_5': 'all_rows', 'rank_6': 'rank', '3_7': '3', 'loss_8': 'loss', '1_9': '1', '2_10': '2'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_greater_eq_1': [2], 'filter_less_eq_0': [1], 'all_rows_5': [0], 'rank_6': [0], '3_7': [0], 'loss_8': [1], '1_9': [1], '2_10': [3]} | ['rank', 'team', 'loss', 'sets won', 'sets lost', 'percentage'] | [['1', 'ateneo de manila university', '0', '15', '2', '88 %'], ['2', 'lyceum of the philippines university', '1', '12', '5', '71 %'], ['3', 'university of saint la salle', '3', '9', '10', '47 %'], ['4', 'university of san jose - recoletos', '3', '9', '11', '45 %'], ['5', 'far eastern university', '4', '6', '14', '30 %'], ['6', 'college of saint benilde', '4', '3', '12', '20 %']] |
1985 european aquatics championships | https://en.wikipedia.org/wiki/1985_European_Aquatics_Championships | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13045569-1.html.csv | aggregation | the top 5 ranking countries in the 1985 european aquatics championships averaged a total of 4 bronze medals won . | {'scope': 'subset', 'col': '5', 'type': 'average', 'result': '4', 'subset': {'col': '1', 'criterion': 'less_than_eq', 'value': '5'}} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': [{'func': 'filter_less_eq', 'args': ['all_rows', 'rank', '5'], 'result': None, 'ind': 0, 'tostr': 'filter_less_eq { all_rows ; rank ; 5 }', 'tointer': 'select the rows whose rank record is less than or equal to 5 .'}, 'bronze'], 'result': '4', 'ind': 1, 'tostr': 'avg { filter_less_eq { all_rows ; rank ; 5 } ; bronze }'}, '4'], 'result': True, 'ind': 2, 'tostr': 'round_eq { avg { filter_less_eq { all_rows ; rank ; 5 } ; bronze } ; 4 } = true', 'tointer': 'select the rows whose rank record is less than or equal to 5 . the average of the bronze record of these rows is 4 .'} | round_eq { avg { filter_less_eq { all_rows ; rank ; 5 } ; bronze } ; 4 } = true | select the rows whose rank record is less than or equal to 5 . the average of the bronze record of these rows is 4 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'avg_1': 1, 'filter_less_eq_0': 0, 'all_rows_4': 4, 'rank_5': 5, '5_6': 6, 'bronze_7': 7, '4_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'avg_1': 'avg', 'filter_less_eq_0': 'filter_less_eq', 'all_rows_4': 'all_rows', 'rank_5': 'rank', '5_6': '5', 'bronze_7': 'bronze', '4_8': '4'} | {'eq_2': [3], 'result_3': [], 'avg_1': [2], 'filter_less_eq_0': [1], 'all_rows_4': [0], 'rank_5': [0], '5_6': [0], 'bronze_7': [1], '4_8': [2]} | ['rank', 'nation', 'gold', 'silver', 'bronze', 'total'] | [['1', 'east germany', '17', '17', '6', '40'], ['2', 'soviet union', '7', '4', '6', '17'], ['3', 'west germany', '6', '4', '7', '17'], ['4', 'great britain', '2', '3', '1', '6'], ['5', 'france', '2', '2', '0', '4'], ['6', 'hungary', '2', '1', '0', '3'], ['7', 'bulgaria', '1', '2', '4', '7'], ['8', 'netherlands', '1', '1', '6', '8'], ['9', 'austria', '1', '0', '1', '2'], ['10', 'sweden', '0', '1', '3', '4'], ['11', 'czechoslovakia', '0', '1', '1', '2'], ['12', 'denmark', '0', '1', '0', '1'], ['12', 'portugal', '0', '1', '0', '1'], ['12', 'yugoslavia', '0', '1', '0', '1'], ['15', 'italy', '0', '0', '2', '2'], ['15', 'switzerland', '0', '0', '2', '2'], ['total', 'total', '39', '39', '39', '117']] |
switzerland at the 2008 summer olympics | https://en.wikipedia.org/wiki/Switzerland_at_the_2008_Summer_Olympics | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-17085947-32.html.csv | count | there were 5 athletes which represented switzerland at the 2008 summer olympics . | {'scope': 'all', 'criterion': 'all', 'value': 'n/a', 'result': '5', 'col': '1', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_all', 'args': ['all_rows', 'athlete'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose athlete record is arbitrary .', 'tostr': 'filter_all { all_rows ; athlete }'}], 'result': '5', 'ind': 1, 'tostr': 'count { filter_all { all_rows ; athlete } }', 'tointer': 'select the rows whose athlete record is arbitrary . the number of such rows is 5 .'}, '5'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_all { all_rows ; athlete } } ; 5 } = true', 'tointer': 'select the rows whose athlete record is arbitrary . the number of such rows is 5 .'} | eq { count { filter_all { all_rows ; athlete } } ; 5 } = true | select the rows whose athlete record is arbitrary . the number of such rows is 5 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_all_0': 0, 'all_rows_4': 4, 'athlete_5': 5, '5_6': 6} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_all_0': 'filter_all', 'all_rows_4': 'all_rows', 'athlete_5': 'athlete', '5_6': '5'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_all_0': [1], 'all_rows_4': [0], 'athlete_5': [0], '5_6': [2]} | ['athlete', 'event', 'swim ( 1.5 km )', 'trans 1', 'bike ( 40 km )', 'trans 2', 'run ( 10 km )', 'total time', 'rank'] | [['reto hug', "men 's", '18:55', '0:27', '58:20', '0:29', '33:53', '1:52:04.93', '29'], ['olivier marceau', "men 's", '18:55', '0:29', '58:18', '0:31', '32:37', '1:50:50.07', '19'], ['sven riederer', "men 's", '18:14', '0:34', '58:52', '0:28', '33:11', '1:51:19.45', '23'], ['magali chopard di marco', "women 's", '19:50', '0:30', '1:04:22', '0:29', '36:39', '2:01:50.74', '13'], ['daniela ryf', "women 's", '19:56', '0:26', '1:04:17', '0:30', '35:31', '2:00:40.20', '7']] |
list of gilmore girls episodes | https://en.wikipedia.org/wiki/List_of_Gilmore_Girls_episodes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2602958-5.html.csv | unique | the episode that aired on october 21 , 2003 was the only episode directed by neema barnette . | {'scope': 'all', 'row': '5', 'col': '4', 'col_other': '6', 'criterion': 'equal', 'value': 'neema barnette', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'director', 'neema barnette'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose director record fuzzily matches to neema barnette .', 'tostr': 'filter_eq { all_rows ; director ; neema barnette }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; director ; neema barnette } }', 'tointer': 'select the rows whose director record fuzzily matches to neema barnette . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'director', 'neema barnette'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose director record fuzzily matches to neema barnette .', 'tostr': 'filter_eq { all_rows ; director ; neema barnette }'}, 'original air date'], 'result': 'october 21 , 2003', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; director ; neema barnette } ; original air date }'}, 'october 21 , 2003'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; director ; neema barnette } ; original air date } ; october 21 , 2003 }', 'tointer': 'the original air date record of this unqiue row is october 21 , 2003 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; director ; neema barnette } } ; eq { hop { filter_eq { all_rows ; director ; neema barnette } ; original air date } ; october 21 , 2003 } } = true', 'tointer': 'select the rows whose director record fuzzily matches to neema barnette . there is only one such row in the table . the original air date record of this unqiue row is october 21 , 2003 .'} | and { only { filter_eq { all_rows ; director ; neema barnette } } ; eq { hop { filter_eq { all_rows ; director ; neema barnette } ; original air date } ; october 21 , 2003 } } = true | select the rows whose director record fuzzily matches to neema barnette . there is only one such row in the table . the original air date record of this unqiue row is october 21 , 2003 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'director_7': 7, 'neema barnette_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'original air date_9': 9, 'october 21 , 2003_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'director_7': 'director', 'neema barnette_8': 'neema barnette', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'original air date_9': 'original air date', 'october 21 , 2003_10': 'october 21 , 2003'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'director_7': [0], 'neema barnette_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'original air date_9': [2], 'october 21 , 2003_10': [3]} | ['no', '-', 'title', 'director', 'writer ( s )', 'original air date', 'prod code', 'us viewers ( million )'] | [['66', '1', 'ballrooms and biscotti', 'amy sherman - palladino', 'amy sherman - palladino', 'september 23 , 2003', '176151', '5.2'], ['67', '2', "the lorelais ' first day at yale", 'chris long', 'daniel palladino', 'september 30 , 2003', '176152', '3.9'], ['68', '3', 'the hobbit , the sofa and digger stiles', 'matthew diamond', 'amy sherman - palladino', 'october 7 , 2003', '176153', '4.9'], ['69', '4', 'chicken or beef', 'chris long', 'jane espenson', 'october 14 , 2003', '176154', '5.5'], ['70', '5', 'the fundamental things apply', 'neema barnette', 'john stephens', 'october 21 , 2003', '176155', '5.5'], ['71', '6', 'an affair to remember', 'matthew diamond', 'amy sherman - palladino', 'october 28 , 2003', '176156', '5.2'], ['72', '7', 'the festival of living art', 'chris long', 'daniel palladino', 'november 4 , 2003', '176157', '4.7'], ['73', '8', 'die , jerk', 'tom moore', 'daniel palladino', 'november 11 , 2003', '176158', '4.9'], ['74', '9', "ted koppel 's big night out", 'jamie babbit', 'amy sherman - palladino', 'november 18 , 2003', '176159', '5.2'], ['75', '10', 'the nanny and the professor', 'peter lauer', 'scott kaufer', 'january 20 , 2004', '176160', '4.1'], ['76', '11', 'in the clamor and the clangor', 'michael grossman', 'sheila r lawrence , janet leahy', 'january 27 , 2004', '176161', '4.4'], ['77', '12', 'a family matter', 'kenny ortega', 'daniel palladino', 'february 3 , 2004', '176162', '4.9'], ['79', '14', 'the incredible sinking lorelais', 'stephen clancy', 'amy sherman - palladino , daniel palladino', 'february 17 , 2004', '176164', '4.8'], ['80', '15', 'scene in a mall', 'chris long', 'daniel palladino', 'february 24 , 2004', '176165', '4.8'], ['81', '16', 'the reigning lorelai', 'marita grabiak', 'jane espenson', 'march 2 , 2004', '176166', '5.0'], ['82', '17', "girls in bikinis , boys doin ' the twist", 'jamie babbit', 'amy sherman - palladino', 'april 13 , 2004', '176167', '4.5'], ['83', '18', 'tick , tick , tick , boom !', 'daniel palladino', 'daniel palladino', 'april 20 , 2004', '176168', '4.2'], ['84', '19', 'afterboom', 'michael zinberg', 'sheila r lawrence', 'april 27 , 2004', '176169', '4.3'], ['85', '20', 'luke can see her face', 'matthew diamond', 'amy sherman - palladino , daniel palladino', 'may 4 , 2004', '176170', '4.2'], ['86', '21', 'last week fights , this week tights', 'chris long', 'daniel palladino', 'may 11 , 2004', '176171', '4.6']] |
arantxa rus | https://en.wikipedia.org/wiki/Arantxa_Rus | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18586543-6.html.csv | unique | arantxa rus lost her only doubles match played on a carpet surface . | {'scope': 'all', 'row': '2', 'col': '4', 'col_other': 'n/a', 'criterion': 'equal', 'value': 'carpet', 'subset': None} | {'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'surface', 'carpet'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose surface record fuzzily matches to carpet .', 'tostr': 'filter_eq { all_rows ; surface ; carpet }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; surface ; carpet } } = true', 'tointer': 'select the rows whose surface record fuzzily matches to carpet . there is only one such row in the table .'} | only { filter_eq { all_rows ; surface ; carpet } } = true | select the rows whose surface record fuzzily matches to carpet . 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, 'surface_4': 4, 'carpet_5': 5} | {'only_1': 'only', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'surface_4': 'surface', 'carpet_5': 'carpet'} | {'only_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'surface_4': [0], 'carpet_5': [0]} | ['outcome', 'date', 'tournament', 'surface', 'partner', 'opponents', 'score'] | [['winner', '27 . october 2007', 'mexico city', 'hard', 'nicole thijssen', 'ivana abramović maria abramović', '6 - 0 , 6 - 1'], ['runner - up', '19 november 2008', 'opole', 'carpet', 'katarzyna piter', 'karolina kosińska aleksandra rosolska', '6 - 2 , 6 - 7 ( 6 ) ,'], ['runner - up', '31 may 2010', 'rome', 'clay', 'iryna bremond', 'christina mchale olivia rogowska', '4 - 6 , 1 - 6'], ['winner', '11 . february 2011', 'stockholm', 'hard ( i )', 'anastasiya yakimova', 'claire feuerstein ksenia lykina', '6 - 3 , 2 - 6 ,'], ['winner', '12 . may 2013', 'cagnes - sur - mer', 'clay', 'vania king', 'catalina castaño teliana pereira', '4 - 6 , 7 - 5 ,'], ['runner - up', '6 october 2013', 'vallduxo', 'clay', 'cindy burger', 'florencia molinero laura thorpe', '1 - 6 , 4 - 6']] |
shinichi ito | https://en.wikipedia.org/wiki/Shinichi_Ito | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12185077-3.html.csv | superlative | 141 points was the highest number of points that shinichi ito scored in a single year . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '7', 'value_mentioned': 'yes', 'max_or_min': 'max', 'other_col': 'n/a', 'subset': None} | {'func': 'eq', 'args': [{'func': 'max', 'args': ['all_rows', 'points'], 'result': '141', 'ind': 0, 'tostr': 'max { all_rows ; points }', 'tointer': 'the maximum points record of all rows is 141 .'}, '141'], 'result': True, 'ind': 1, 'tostr': 'eq { max { all_rows ; points } ; 141 } = true', 'tointer': 'the maximum points record of all rows is 141 .'} | eq { max { all_rows ; points } ; 141 } = true | the maximum points record of all rows is 141 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'max_0': 0, 'all_rows_3': 3, 'points_4': 4, '141_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'max_0': 'max', 'all_rows_3': 'all_rows', 'points_4': 'points', '141_5': '141'} | {'eq_1': [2], 'result_2': [], 'max_0': [1], 'all_rows_3': [0], 'points_4': [0], '141_5': [1]} | ['year', 'class', 'team', 'machine', 'points', 'rank', 'wins'] | [['1988', '500cc', 'seed - honda', 'nsr500', '0', 'nc', '0'], ['1989', '500cc', 'hrc - honda', 'nsr500', '6', '32nd', '0'], ['1990', '500cc', 'pentax - honda', 'nsr500', '7', '26th', '0'], ['1991', '500cc', 'pentax - honda', 'nsr500', '0', 'nc', '0'], ['1992', '500cc', 'hrc - honda', 'nsr500', '10', '16th', '0'], ['1993', '500cc', 'rothmans - honda', 'nsr500', '119', '7th', '0'], ['1994', '500cc', 'hrc - honda', 'nsr500', '141', '7th', '0'], ['1995', '500cc', 'repsol - honda', 'nsr500', '127', '5th', '0'], ['1996', '500cc', 'repsol - honda', 'nsr500v', '77', '12th', '0'], ['1999', '500cc', 'lucky strike - honda', 'nsr500', '9', '21st', '0'], ['2002', 'motogp', 'repsol - honda', 'rc211v', '13', '21st', '0'], ['2002', 'motogp', 'kanemoto - honda', 'nsr500', '13', '21st', '0'], ['2005', 'motogp', 'marlboro - ducati', 'gp5', '0', 'nc', '0'], ['2007', 'motogp', "pramac d'antin ducati", 'gp7', '1', '26th', '0'], ['2011', 'motogp', 'repsol - honda', 'rc212v', '3', '22nd', '0']] |
list of latvian submissions for the academy award for best foreign language film | https://en.wikipedia.org/wiki/List_of_Latvian_submissions_for_the_Academy_Award_for_Best_Foreign_Language_Film | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17822046-1.html.csv | ordinal | aigars grauba is the director of the 2nd earliest best foreign language film for the latvian submission award . | {'row': '2', 'col': '1', 'order': '2', 'col_other': '4', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'year ( ceremony )', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; year ( ceremony ) ; 2 }'}, 'director'], 'result': 'aigars grauba', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; year ( ceremony ) ; 2 } ; director }'}, 'aigars grauba'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; year ( ceremony ) ; 2 } ; director } ; aigars grauba } = true', 'tointer': 'select the row whose year ( ceremony ) record of all rows is 2nd minimum . the director record of this row is aigars grauba .'} | eq { hop { nth_argmin { all_rows ; year ( ceremony ) ; 2 } ; director } ; aigars grauba } = true | select the row whose year ( ceremony ) record of all rows is 2nd minimum . the director record of this row is aigars grauba . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'year (ceremony)_5': 5, '2_6': 6, 'director_7': 7, 'aigars grauba_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmin_0': 'nth_argmin', 'all_rows_4': 'all_rows', 'year (ceremony)_5': 'year ( ceremony )', '2_6': '2', 'director_7': 'director', 'aigars grauba_8': 'aigars grauba'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'year (ceremony)_5': [0], '2_6': [0], 'director_7': [1], 'aigars grauba_8': [2]} | ['year ( ceremony )', 'film title used in nomination', 'original title', 'director', 'result'] | [['1992 ( 65th )', 'the child of man', 'cilvēka bērns', 'jānis streičs', 'not nominated'], ['2008 ( 81st )', 'defenders of riga', 'rīgas sargi', 'aigars grauba', 'not nominated'], ['2010 ( 83rd )', 'hong kong confidential', 'amaya', 'māris martinsons', 'not nominated'], ['2012 ( 85th )', 'gulf stream under the iceberg', 'golfa straume zem ledus kalna', 'yevgeni pashkevich', 'not nominated'], ['2013 ( 86th )', 'mother , i love you', 'mammu , es tevi mīlu', 'jānis nords', 'tbd']] |
2001 philadelphia eagles season | https://en.wikipedia.org/wiki/2001_Philadelphia_Eagles_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16882018-12.html.csv | aggregation | in two games against the new york giants , the 2001 eagles attendance totaled 144706 . | {'scope': 'subset', 'col': '6', 'type': 'sum', 'result': '144706', 'subset': {'col': '3', 'criterion': 'equal', 'value': 'new york giants'}} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', 'new york giants'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; opponent ; new york giants }', 'tointer': 'select the rows whose opponent record fuzzily matches to new york giants .'}, 'attendance'], 'result': '144706', 'ind': 1, 'tostr': 'sum { filter_eq { all_rows ; opponent ; new york giants } ; attendance }'}, '144706'], 'result': True, 'ind': 2, 'tostr': 'round_eq { sum { filter_eq { all_rows ; opponent ; new york giants } ; attendance } ; 144706 } = true', 'tointer': 'select the rows whose opponent record fuzzily matches to new york giants . the sum of the attendance record of these rows is 144706 .'} | round_eq { sum { filter_eq { all_rows ; opponent ; new york giants } ; attendance } ; 144706 } = true | select the rows whose opponent record fuzzily matches to new york giants . the sum of the attendance record of these rows is 144706 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'sum_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'opponent_5': 5, 'new york giants_6': 6, 'attendance_7': 7, '144706_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'sum_1': 'sum', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'opponent_5': 'opponent', 'new york giants_6': 'new york giants', 'attendance_7': 'attendance', '144706_8': '144706'} | {'eq_2': [3], 'result_3': [], 'sum_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'opponent_5': [0], 'new york giants_6': [0], 'attendance_7': [1], '144706_8': [2]} | ['week', 'date', 'opponent', 'result', 'tv time', 'attendance'] | [['1', 'september 9 , 2001', 'st louis rams', 'l 20 - 17', 'fox 4:15 pm', '66243'], ['2', 'september 23 , 2001', 'seattle seahawks', 'w 27 - 3', 'fox 4:15 pm', '62826'], ['3', 'september 30 , 2001', 'dallas cowboys', 'w 40 - 18', 'espn 8:30 pm', '66621'], ['4', 'october 7 , 2001', 'arizona cardinals', 'l 21 - 20', 'fox 1:00 pm', '66360'], ['6', 'october 22 , 2001', 'new york giants', 'w 10 - 9', 'abc 9:00 pm', '78821'], ['7', 'october 28 , 2001', 'oakland raiders', 'l 20 - 10', 'cbs 4:15 pm', '65342'], ['8', 'november 4 , 2001', 'arizona cardinals', 'w 21 - 7', 'fox 4:05 pm', '33430'], ['9', 'november 11 , 2001', 'minnesota vikings', 'w 48 - 17', 'fox 4:15 pm', '65638'], ['10', 'november 18 , 2001', 'dallas cowboys', 'w 36 - 3', 'fox 1:00 pm', '63204'], ['11', 'november 25 , 2001', 'washington redskins', 'l 13 - 3', 'fox 1:00 pm', '65666'], ['12', 'november 29 , 2001', 'kansas city chiefs', 'w 23 - 10', 'espn 8:30 pm', '77087'], ['13', 'december 9 , 2001', 'san diego chargers', 'w 24 - 14', 'cbs 1:00 pm', '65438'], ['14', 'december 16 , 2001', 'washington redskins', 'w 20 - 6', 'fox 4:15 pm', '84036'], ['15', 'december 23 , 2001', 'san francisco 49ers', 'l 13 - 3', 'fox 4:15 pm', '68124'], ['16', 'december 30 , 2001', 'new york giants', 'w 24 - 21', 'fox 4:15 pm', '65885'], ['17', 'january 6 , 2002', 'tampa bay buccaneers', 'w 17 - 13', 'espn 8:30 pm', '65541']] |
robin frijns | https://en.wikipedia.org/wiki/Robin_Frijns | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-24405773-1.html.csv | ordinal | in the 2013 gp2 series , robin frijns had the 7th lowest position out of all his series between seasons 2009-2013 . | {'row': '7', 'col': '10', 'order': '7', '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', 'position', '7'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; position ; 7 }'}, 'series'], 'result': 'gp2 series', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; position ; 7 } ; series }'}, 'gp2 series'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; position ; 7 } ; series } ; gp2 series } = true', 'tointer': 'select the row whose position record of all rows is 7th minimum . the series record of this row is gp2 series .'} | eq { hop { nth_argmin { all_rows ; position ; 7 } ; series } ; gp2 series } = true | select the row whose position record of all rows is 7th minimum . the series record of this row is gp2 series . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'position_5': 5, '7_6': 6, 'series_7': 7, 'gp2 series_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', 'position_5': 'position', '7_6': '7', 'series_7': 'series', 'gp2 series_8': 'gp2 series'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'position_5': [0], '7_6': [0], 'series_7': [1], 'gp2 series_8': [2]} | ['season', 'series', 'team', 'races', 'wins', 'poles', 'flaps', 'podiums', 'points', 'position'] | [['2009', 'formula bmw europe', 'josef kaufmann racing', '16', '1', '1', '1', '6', '265', '3rd'], ['2010', 'formula bmw europe', 'josef kaufmann racing', '16', '6', '3', '3', '13', '383', '1st'], ['2010', 'formula renault 2.0 nec', 'josef kaufmann racing', '3', '1', '0', '1', '2', '70', '14th'], ['2011', 'eurocup formula renault 2.0', 'josef kaufmann racing', '14', '5', '1', '0', '9', '245', '1st'], ['2011', 'formula renault 2.0 nec', 'josef kaufmann racing', '12', '1', '1', '2', '7', '238', '4th'], ['2012', 'formula renault 3.5 series', 'fortec motorsport', '17', '3', '4', '1', '8', '189', '1st'], ['2013', 'gp2 series', 'hilmer motorsport', '10', '1', '0', '0', '2', '47', '15th']] |
8th coastal defence flotilla | https://en.wikipedia.org/wiki/8th_Coastal_Defence_Flotilla | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18965165-1.html.csv | aggregation | a total of 35 military vessels are still in service for the 8th coastal defence flotilla . | {'scope': 'all', 'col': '4', 'type': 'sum', 'result': '35', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'in service'], 'result': '35', 'ind': 0, 'tostr': 'sum { all_rows ; in service }'}, '35'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; in service } ; 35 } = true', 'tointer': 'the sum of the in service record of all rows is 35 .'} | round_eq { sum { all_rows ; in service } ; 35 } = true | the sum of the in service record of all rows is 35 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'in service_4': 4, '35_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'in service_4': 'in service', '35_5': '35'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'in service_4': [0], '35_5': [1]} | ['vessel', 'origin', 'type', 'in service', 'unit'] | [['xavery czernicki class', 'poland', 'logistic support', '1', '2nd minelaying and transport squadron'], ['lublin class', 'poland', 'landing craft', '5', '2nd minelaying and transport squadron'], ['deba class', 'poland', 'landing craft', '3', '2nd minelaying and transport squadron'], ['gardno class', 'poland', 'minesweeper', '12', '12th minesweeper squadron'], ['various class', 'poland', 'auxiliary vessels', '14', 'naval base swinoujscie ( auxiliary squadron )']] |
paul azinger | https://en.wikipedia.org/wiki/Paul_Azinger | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1551597-4.html.csv | majority | paul azinger did not have a win in the majority of tournaments that he participated in . | {'scope': 'all', 'col': '2', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': '0', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'wins', '0'], 'result': True, 'ind': 0, 'tointer': 'for the wins records of all rows , most of them fuzzily match to 0 .', 'tostr': 'most_eq { all_rows ; wins ; 0 } = true'} | most_eq { all_rows ; wins ; 0 } = true | for the wins records of all rows , most of them fuzzily match to 0 . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'wins_3': 3, '0_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'wins_3': 'wins', '0_4': '0'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'wins_3': [0], '0_4': [0]} | ['tournament', 'wins', 'top - 5', 'top - 10', 'top - 25', 'events', 'cuts made'] | [['masters tournament', '0', '1', '1', '6', '15', '10'], ['us open', '0', '2', '4', '8', '18', '12'], ['the open championship', '0', '1', '3', '3', '12', '7'], ['pga championship', '1', '2', '2', '5', '23', '13'], ['totals', '1', '6', '10', '22', '68', '42']] |
united kingdom general election records | https://en.wikipedia.org/wiki/United_Kingdom_general_election_records | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10107334-3.html.csv | unique | only peter law ran as an independent instead of a member of a political party . | {'scope': 'all', 'row': '13', 'col': '2', 'col_other': '1', 'criterion': 'equal', 'value': 'independent', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'party', 'independent'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose party record fuzzily matches to independent .', 'tostr': 'filter_eq { all_rows ; party ; independent }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; party ; independent } }', 'tointer': 'select the rows whose party record fuzzily matches to independent . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'party', 'independent'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose party record fuzzily matches to independent .', 'tostr': 'filter_eq { all_rows ; party ; independent }'}, 'candidate'], 'result': 'peter law', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; party ; independent } ; candidate }'}, 'peter law'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; party ; independent } ; candidate } ; peter law }', 'tointer': 'the candidate record of this unqiue row is peter law .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; party ; independent } } ; eq { hop { filter_eq { all_rows ; party ; independent } ; candidate } ; peter law } } = true', 'tointer': 'select the rows whose party record fuzzily matches to independent . there is only one such row in the table . the candidate record of this unqiue row is peter law .'} | and { only { filter_eq { all_rows ; party ; independent } } ; eq { hop { filter_eq { all_rows ; party ; independent } ; candidate } ; peter law } } = true | select the rows whose party record fuzzily matches to independent . there is only one such row in the table . the candidate record of this unqiue row is peter law . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'party_7': 7, 'independent_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'candidate_9': 9, 'peter law_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'party_7': 'party', 'independent_8': 'independent', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'candidate_9': 'candidate', 'peter law_10': 'peter law'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'party_7': [0], 'independent_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'candidate_9': [2], 'peter law_10': [3]} | ['candidate', 'party', 'constituency', 'year', 'days'] | [['alfred dobbs', 'labour', 'smethwick', '1945', '1 1'], ['john sunderland', 'labour', 'preston', '1945', '122 1'], ['john whittaker', 'labour', 'heywood and radcliffe', '1945', '137 1'], ['philip clarke', 'sinn féin', 'fermanagh and south tyrone', '1955', '152 3x'], ['thomas mitchell', 'sinn féin', 'mid - ulster', '1955', '152 3x'], ['harry west', 'ulster unionist', 'fermanagh and south tyrone', 'february 1974', '224 2'], ['michael ancram', 'conservative', 'berwick and east lothian', 'february 1974', '224 2a'], ['barry henderson', 'conservative', 'east dunbartonshire', 'february 1974', '224 2a'], ['paul tyler', 'liberal', 'bodmin', 'february 1974', '224 2a'], ['michael winstanley', 'liberal', 'hazel grove', 'february 1974', '224 2b'], ['james godfrey macmanaway', 'ulster unionist', 'belfast west', '1950', '238 3'], ['judith chaplin', 'conservative', 'newbury', '1992', '316 1'], ['peter law', 'independent', 'blaenau gwent', '2005', '355 1']] |
andrei chesnokov | https://en.wikipedia.org/wiki/Andrei_Chesnokov | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1723532-2.html.csv | count | aandrei chesnokov played tournament finals against thomas muster a total of two times . | {'scope': 'all', 'criterion': 'equal', 'value': 'thomas muster', 'result': '2', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', 'thomas muster'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose opponent record fuzzily matches to thomas muster .', 'tostr': 'filter_eq { all_rows ; opponent ; thomas muster }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; opponent ; thomas muster } }', 'tointer': 'select the rows whose opponent record fuzzily matches to thomas muster . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; opponent ; thomas muster } } ; 2 } = true', 'tointer': 'select the rows whose opponent record fuzzily matches to thomas muster . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; opponent ; thomas muster } } ; 2 } = true | select the rows whose opponent record fuzzily matches to thomas muster . 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, 'opponent_5': 5, 'thomas muster_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', 'opponent_5': 'opponent', 'thomas muster_6': 'thomas muster', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'opponent_5': [0], 'thomas muster_6': [0], '2_7': [2]} | ['outcome', 'date', 'tournament', 'surface', 'opponent', 'score'] | [['winner', '25 may 1987', 'florence', 'clay', 'alessandro de minicis', '6 - 1 , 6 - 3'], ['runner - up', '3 january 1988', 'wellington', 'hardcourt', 'ramesh krishnan', '7 - 6 , 0 - 6 , 4 - 6 , 3 - 6'], ['runner - up', '10 january 1988', 'sydney', 'grass', 'john fitzgerald', '3 - 6 , 4 - 6'], ['winner', '14 march 1988', 'orlando', 'hardcourt', 'miloslav mečíř', '7 - 6 ( 8 - 6 ) , 6 - 1'], ['runner - up', '16 october 1988', 'toulouse', 'hardcourt', 'jimmy connors', '2 - 6 , 0 - 6'], ['winner', '24 april 1989', 'nice', 'clay', 'jérôme potier', '6 - 4 , 6 - 4'], ['winner', '8 may 1989', 'munich', 'clay', 'martin střelba', '5 - 7 , 7 - 6 ( 8 - 6 ) , 6 - 2'], ['runner - up', '14 january 1990', 'auckland', 'hardcourt', 'scott davis', '6 - 4 , 3 - 6 , 3 - 6'], ['winner', '30 april 1990', 'monte carlo', 'clay', 'thomas muster', '7 - 5 , 6 - 3 , 6 - 3'], ['runner - up', '20 may 1990', 'rome', 'clay', 'thomas muster', '1 - 6 , 3 - 6 , 1 - 6'], ['winner', '15 october 1990', 'tel aviv', 'hardcourt', 'amos mansdorf', '6 - 4 , 6 - 3'], ['winner', '29 july 1991', 'montreal', 'hardcourt', 'petr korda', '3 - 6 , 6 - 4 , 6 - 3'], ['runner - up', '8 march 1992', 'indian wells', 'hardcourt', 'michael chang', '3 - 6 , 4 - 6 , 5 - 7'], ['runner - up', '9 may 1993', 'hamburg', 'clay', 'michael stich', '3 - 6 , 7 - 6 ( 7 - 1 ) , 6 - 7 ( 7 - 9 ) , 4 - 6'], ['runner - up', '8 august 1993', 'prague', 'clay', 'sergi bruguera', '5 - 7 , 4 - 6']] |
intel core | https://en.wikipedia.org/wiki/Intel_Core | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-24538587-13.html.csv | unique | of the intel core processors , core i7 - 3xx7u , i7 - 3xx7ue is the only one of a tdp rating of 17 w. | {'scope': 'all', 'row': '10', 'col': '6', 'col_other': '2', 'criterion': 'equal', 'value': '17 w', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'tdp', '17 w'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose tdp record fuzzily matches to 17 w .', 'tostr': 'filter_eq { all_rows ; tdp ; 17 w }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; tdp ; 17 w } }', 'tointer': 'select the rows whose tdp record fuzzily matches to 17 w . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'tdp', '17 w'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose tdp record fuzzily matches to 17 w .', 'tostr': 'filter_eq { all_rows ; tdp ; 17 w }'}, 'brand name ( list )'], 'result': 'core i7 - 3xx7u , i7 - 3xx7ue', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; tdp ; 17 w } ; brand name ( list ) }'}, 'core i7 - 3xx7u , i7 - 3xx7ue'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; tdp ; 17 w } ; brand name ( list ) } ; core i7 - 3xx7u , i7 - 3xx7ue }', 'tointer': 'the brand name ( list ) record of this unqiue row is core i7 - 3xx7u , i7 - 3xx7ue .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; tdp ; 17 w } } ; eq { hop { filter_eq { all_rows ; tdp ; 17 w } ; brand name ( list ) } ; core i7 - 3xx7u , i7 - 3xx7ue } } = true', 'tointer': 'select the rows whose tdp record fuzzily matches to 17 w . there is only one such row in the table . the brand name ( list ) record of this unqiue row is core i7 - 3xx7u , i7 - 3xx7ue .'} | and { only { filter_eq { all_rows ; tdp ; 17 w } } ; eq { hop { filter_eq { all_rows ; tdp ; 17 w } ; brand name ( list ) } ; core i7 - 3xx7u , i7 - 3xx7ue } } = true | select the rows whose tdp record fuzzily matches to 17 w . there is only one such row in the table . the brand name ( list ) record of this unqiue row is core i7 - 3xx7u , i7 - 3xx7ue . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'tdp_7': 7, '17 w_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'brand name (list)_9': 9, 'core i7 - 3xx7u , i7 - 3xx7ue_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'tdp_7': 'tdp', '17 w_8': '17 w', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'brand name (list)_9': 'brand name ( list )', 'core i7 - 3xx7u , i7 - 3xx7ue_10': 'core i7 - 3xx7u , i7 - 3xx7ue'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'tdp_7': [0], '17 w_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'brand name (list)_9': [2], 'core i7 - 3xx7u , i7 - 3xx7ue_10': [3]} | ['codename ( main article )', 'brand name ( list )', 'cores', 'l3 cache', 'socket', 'tdp', 'process', 'i / o bus', 'release date'] | [['ivy bridge ( desktop )', 'core i7 - 37xx , i7 - 37xxk', '4', '8 mb', 'lga 1155', '77 w', '22 nm', 'direct media interface , integrated gpu', 'april 2012'], ['ivy bridge ( desktop )', 'core i7 - 37xxs', '4', '8 mb', 'lga 1155', '65 w', '22 nm', 'direct media interface , integrated gpu', 'april 2012'], ['ivy bridge ( desktop )', 'core i7 - 37xxt', '4', '8 mb', 'lga 1155', '45 w', '22 nm', 'direct media interface , integrated gpu', 'april 2012'], ['sandy bridge - e ( desktop )', 'core i7 - 39xxx', '6', '15 mb', 'lga 2011', '130 w', '32 nm', 'direct media interface', 'november 2011'], ['sandy bridge - e ( desktop )', 'core i7 - 39xxk', '6', '12 mb', 'lga 2011', '130 w', '32 nm', 'direct media interface', 'november 2011'], ['sandy bridge - e ( desktop )', 'core i7 - 38xx', '4', '10 mb', 'lga 2011', '130 w', '32 nm', 'direct media interface', 'november 2011'], ['sandy bridge ( desktop )', 'core i7 - 2xxxk , i7 - 2xxx', '4', '8 mb', 'lga 1155', '95 w', '32 nm', 'direct media interface , integrated gpu', 'january 2011'], ['sandy bridge ( desktop )', 'core i7 - 2xxxs', '4', '8 mb', 'lga 1155', '65 w', '32 nm', 'direct media interface , integrated gpu', 'january 2011'], ['ivy bridge ( mobile )', 'core i7 - 3xx9y', '2', '4 mb', 'rpga - 988b bga - 1023', '13 w', '22 nm', 'direct media interface , integrated gpu', 'january 2013'], ['ivy bridge ( mobile )', 'core i7 - 3xx7u , i7 - 3xx7ue', '2', '4 mb', 'rpga - 988b bga - 1023', '17 w', '22 nm', 'direct media interface , integrated gpu', 'april 2012'], ['ivy bridge ( mobile )', 'core i7 - 3xxxle', '2', '4 mb', 'rpga - 988b bga - 1023', '25 w', '22 nm', 'direct media interface , integrated gpu', 'april 2012'], ['ivy bridge ( mobile )', 'core i7 - 3xxxm', '2', '4 mb', 'rpga - 988b bga - 1023', '35 w', '22 nm', 'direct media interface , integrated gpu', 'april 2012'], ['ivy bridge ( mobile )', 'core i7 - 3xx2qm , i7 - 3xx2qe', '4', '6 mb', 'rpga - 988b bga - 1023', '35 w', '22 nm', 'direct media interface , integrated gpu', 'april 2012'], ['ivy bridge ( mobile )', 'core i7 - 38xxqm', '4', '8 mb', 'rpga - 988b bga - 1023', '45 w', '22 nm', 'direct media interface , integrated gpu', 'april 2012'], ['ivy bridge ( mobile )', 'core i7 - 3xxxxm', '4', '8 mb', 'rpga - 988b bga - 1023', '55 w', '22 nm', 'direct media interface , integrated gpu', 'april 2012'], ['sandy bridge ( mobile )', 'core i7 - 2xxxxm', '4', '8 mb', 'rpga - 988b bga - 1023', '55 w', '32 nm', 'direct media interface , integrated gpu', 'january 2011'], ['sandy bridge ( mobile )', 'core i7 - 28xxqm', '4', '8 mb', 'rpga - 988b bga - 1023', '45 w', '32 nm', 'direct media interface , integrated gpu', 'january 2011'], ['sandy bridge ( mobile )', 'core i7 - 2xxxqe , i7 - 26xxqm , i7 - 27xxqm', '4', '6 mb', 'rpga - 988b bga - 1023', '45 w', '32 nm', 'direct media interface , integrated gpu', 'january 2011'], ['sandy bridge ( mobile )', 'core i7 - 2xx0 m', '2', '4 mb', 'rpga - 988b bga - 1023', '35 w', '32 nm', 'direct media interface , integrated gpu', 'february 2011'], ['sandy bridge ( mobile )', 'core i7 - 2xx9 m', '2', '4 mb', 'bga - 1023', '25 w', '32 nm', 'direct media interface , integrated gpu', 'february 2011']] |
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 | aggregation | robby gordon had less than thirty starts in the nineties . | {'scope': 'subset', 'col': '2', 'type': 'sum', 'result': '28', 'subset': {'col': '1', 'criterion': 'less_than', 'value': '2000'}} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'year', '2000'], 'result': None, 'ind': 0, 'tostr': 'filter_less { all_rows ; year ; 2000 }', 'tointer': 'select the rows whose year record is less than 2000 .'}, 'starts'], 'result': '28', 'ind': 1, 'tostr': 'sum { filter_less { all_rows ; year ; 2000 } ; starts }'}, '28'], 'result': True, 'ind': 2, 'tostr': 'round_eq { sum { filter_less { all_rows ; year ; 2000 } ; starts } ; 28 } = true', 'tointer': 'select the rows whose year record is less than 2000 . the sum of the starts record of these rows is 28 .'} | round_eq { sum { filter_less { all_rows ; year ; 2000 } ; starts } ; 28 } = true | select the rows whose year record is less than 2000 . the sum of the starts record of these rows is 28 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'sum_1': 1, 'filter_less_0': 0, 'all_rows_4': 4, 'year_5': 5, '2000_6': 6, 'starts_7': 7, '28_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'sum_1': 'sum', 'filter_less_0': 'filter_less', 'all_rows_4': 'all_rows', 'year_5': 'year', '2000_6': '2000', 'starts_7': 'starts', '28_8': '28'} | {'eq_2': [3], 'result_3': [], 'sum_1': [2], 'filter_less_0': [1], 'all_rows_4': [0], 'year_5': [0], '2000_6': [0], 'starts_7': [1], '28_8': [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 georgia force season | https://en.wikipedia.org/wiki/2007_Georgia_Force_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11710574-4.html.csv | superlative | troy bergeron averaged the highest yards per carry at 8.1 . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '2', 'value_mentioned': 'yes', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'max', 'args': ['all_rows', 'avg'], 'result': '8.1', 'ind': 0, 'tostr': 'max { all_rows ; avg }', 'tointer': 'the maximum avg record of all rows is 8.1 .'}, '8.1'], 'result': True, 'ind': 1, 'tostr': 'eq { max { all_rows ; avg } ; 8.1 }', 'tointer': 'the maximum avg record of all rows is 8.1 .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'avg'], 'result': None, 'ind': 2, 'tostr': 'argmax { all_rows ; avg }'}, 'player'], 'result': 'troy bergeron', 'ind': 3, 'tostr': 'hop { argmax { all_rows ; avg } ; player }'}, 'troy bergeron'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { argmax { all_rows ; avg } ; player } ; troy bergeron }', 'tointer': 'the player record of the row with superlative avg record is troy bergeron .'}], 'result': True, 'ind': 5, 'tostr': 'and { eq { max { all_rows ; avg } ; 8.1 } ; eq { hop { argmax { all_rows ; avg } ; player } ; troy bergeron } } = true', 'tointer': 'the maximum avg record of all rows is 8.1 . the player record of the row with superlative avg record is troy bergeron .'} | and { eq { max { all_rows ; avg } ; 8.1 } ; eq { hop { argmax { all_rows ; avg } ; player } ; troy bergeron } } = true | the maximum avg record of all rows is 8.1 . the player record of the row with superlative avg record is troy bergeron . | 6 | 6 | {'and_5': 5, 'result_6': 6, 'eq_1': 1, 'max_0': 0, 'all_rows_7': 7, 'avg_8': 8, '8.1_9': 9, 'str_eq_4': 4, 'str_hop_3': 3, 'argmax_2': 2, 'all_rows_10': 10, 'avg_11': 11, 'player_12': 12, 'troy bergeron_13': 13} | {'and_5': 'and', 'result_6': 'true', 'eq_1': 'eq', 'max_0': 'max', 'all_rows_7': 'all_rows', 'avg_8': 'avg', '8.1_9': '8.1', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'argmax_2': 'argmax', 'all_rows_10': 'all_rows', 'avg_11': 'avg', 'player_12': 'player', 'troy bergeron_13': 'troy bergeron'} | {'and_5': [6], 'result_6': [], 'eq_1': [5], 'max_0': [1], 'all_rows_7': [0], 'avg_8': [0], '8.1_9': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'argmax_2': [3], 'all_rows_10': [2], 'avg_11': [2], 'player_12': [3], 'troy bergeron_13': [4]} | ['player', 'car', 'yards', 'avg', "td 's", 'long'] | [['matt huebner', '34', '122', '3.6', '5', '24'], ['troy bergeron', '10', '81', '8.1', '0', '19'], ['john ritcher', '20', '58', '2.9', '2', '21'], ['chris greisen', '14', '25', '1.8', '6', '12'], ['chris jackson', '9', '19', '2.1', '4', '8'], ['jarrick hillery', '11', '9', '8', '3', '4'], ['derek lee', '1', '2', '2', '0', '2'], ['bruce mcclure', '1', '1', '1', '1', '1'], ['james macpherson', '1', '1', '1', '1', '1']] |
forbes global 2000 | https://en.wikipedia.org/wiki/Forbes_Global_2000 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1682026-9.html.csv | superlative | the company that made the most in profits in 2000 was exxonmobile . | {'scope': 'all', 'col_superlative': '6', 'row_superlative': '6', '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', 'profits ( billion )'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; profits ( billion ) }'}, 'company'], 'result': 'exxonmobil', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; profits ( billion ) } ; company }'}, 'exxonmobil'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; profits ( billion ) } ; company } ; exxonmobil } = true', 'tointer': 'select the row whose profits ( billion ) record of all rows is maximum . the company record of this row is exxonmobil .'} | eq { hop { argmax { all_rows ; profits ( billion ) } ; company } ; exxonmobil } = true | select the row whose profits ( billion ) record of all rows is maximum . the company record of this row is exxonmobil . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'profits (billion )_5': 5, 'company_6': 6, 'exxonmobil_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'profits (billion )_5': 'profits ( billion )', 'company_6': 'company', 'exxonmobil_7': 'exxonmobil'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'profits (billion )_5': [0], 'company_6': [1], 'exxonmobil_7': [2]} | ['rank', 'company', 'country', 'industry', 'sales ( billion )', 'profits ( billion )', 'assets ( billion )', 'market value ( billion )'] | [['1', 'citigroup', 'usa', 'banking', '108.28', '17.05', '1 , 4.10', '247.66'], ['2', 'general electric', 'usa', 'conglomerates', '152.36', '16.59', '750.33', '372.14'], ['3', 'american international group', 'usa', 'insurance', '95.04', '10.91', '776.42', '173.99'], ['4', 'bank of america', 'usa', 'banking', '65.45', '14.14', '1110.46', '188.77'], ['5', 'hsbc', 'uk', 'banking', '62.97', '9.52', '1031.29', '186.74'], ['6', 'exxonmobil', 'usa', 'oil & gas', '263.99', '25.33', '195.26', '405.25'], ['7', 'royal dutch shell', 'netherlands', 'oil & gas', '265.19', '18.54', '193.83', '221.49'], ['8', 'bp', 'uk', 'oil & gas', '285.06', '15.73', '191.11', '231.88'], ['9', 'ing group', 'netherlands', 'diversified financials', '92.01', '8.10', '1175.16', '68.04']] |
list of tallest buildings in indianapolis | https://en.wikipedia.org/wiki/List_of_tallest_buildings_in_Indianapolis | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14565330-3.html.csv | unique | one indiana square is the only building in indianapolis that is 504 feet high . | {'scope': 'all', 'row': '3', 'col': '4', 'col_other': '1', 'criterion': 'equal', 'value': '504', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'height ft ( m )', '504'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose height ft ( m ) record is equal to 504 .', 'tostr': 'filter_eq { all_rows ; height ft ( m ) ; 504 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; height ft ( m ) ; 504 } }', 'tointer': 'select the rows whose height ft ( m ) record is equal to 504 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'height ft ( m )', '504'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose height ft ( m ) record is equal to 504 .', 'tostr': 'filter_eq { all_rows ; height ft ( m ) ; 504 }'}, 'name'], 'result': 'one indiana square', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; height ft ( m ) ; 504 } ; name }'}, 'one indiana square'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; height ft ( m ) ; 504 } ; name } ; one indiana square }', 'tointer': 'the name record of this unqiue row is one indiana square .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; height ft ( m ) ; 504 } } ; eq { hop { filter_eq { all_rows ; height ft ( m ) ; 504 } ; name } ; one indiana square } } = true', 'tointer': 'select the rows whose height ft ( m ) record is equal to 504 . there is only one such row in the table . the name record of this unqiue row is one indiana square .'} | and { only { filter_eq { all_rows ; height ft ( m ) ; 504 } } ; eq { hop { filter_eq { all_rows ; height ft ( m ) ; 504 } ; name } ; one indiana square } } = true | select the rows whose height ft ( m ) record is equal to 504 . there is only one such row in the table . the name record of this unqiue row is one indiana square . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'height ft ( m )_7': 7, '504_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'name_9': 9, 'one indiana square_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'height ft ( m )_7': 'height ft ( m )', '504_8': '504', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'name_9': 'name', 'one indiana square_10': 'one indiana square'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'height ft ( m )_7': [0], '504_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'name_9': [2], 'one indiana square_10': [3]} | ['name', 'street address', 'years as tallest', 'height ft ( m )', 'floors'] | [['indiana statehouse', '04.0 200 west washington street', '1888 - 1962', '255 ( 78 )', '4'], ['city - county building', '07.0 200 east washington street', '1962 - 1970', '372 ( 113 )', '28'], ['one indiana square', '01.0 1 indiana square', '1970 - 1982', '504 ( 154 )', '36'], ['aul tower', '07.0 200 north illinois street', '1982 - 1990', '533 ( 162 )', '38'], ['bank one tower', '05.0 111 monument circle', '1990 - present', '830 ( 253 )', '48']] |
greek government - debt crisis | https://en.wikipedia.org/wiki/Greek_government-debt_crisis | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27146868-1.html.csv | ordinal | in the year of 1980 the public debt was the second lowest that it had ever been . | {'row': '8', 'col': '3', 'order': '2', 'col_other': '1', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', '1980', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; 1980 ; 2 }'}, 'greek national account'], 'result': 'public debt 8 ( billion )', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; 1980 ; 2 } ; greek national account }'}, 'public debt 8 ( billion )'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; 1980 ; 2 } ; greek national account } ; public debt 8 ( billion ) } = true', 'tointer': 'select the row whose 1980 record of all rows is 2nd minimum . the greek national account record of this row is public debt 8 ( billion ) .'} | eq { hop { nth_argmin { all_rows ; 1980 ; 2 } ; greek national account } ; public debt 8 ( billion ) } = true | select the row whose 1980 record of all rows is 2nd minimum . the greek national account record of this row is public debt 8 ( billion ) . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, '1980_5': 5, '2_6': 6, 'greek national account_7': 7, 'public debt 8 (billion )_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', '1980_5': '1980', '2_6': '2', 'greek national account_7': 'greek national account', 'public debt 8 (billion )_8': 'public debt 8 ( billion )'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], '1980_5': [0], '2_6': [0], 'greek national account_7': [1], 'public debt 8 (billion )_8': [2]} | ['greek national account', '1970', '1980', '1990', '1995', '1996', '1997', '1998', '1999', '2000', '2001 1', '2002', '2003', '2004', '2005', '2006', '2007', '2008', '2009', '2010', '2011', '2012', '2013 2', '2014 2', '2015 3'] | [['public revenue ( % of gdp )', 'n / a', 'n / a', '31.0', '37.0', '37.8', '39.3', '40.9', '41.8', '43.4', '41.3', '40.6', '39.4', '38.4', '39.0', '39.2', '40.7', '40.7', '38.3', '40.6', '42.4', '44.7', '43.5', '43.9', 'n / a'], ['public expenditure 4 ( % of gdp )', 'n / a', 'n / a', '45.2', '46.2', '44.5', '45.3', '44.7', '44.8', '47.1', '45.8', '45.4', '45.1', '46.0', '44.4', '45.0', '47.2', '50.5', '54.0', '51.3', '51.9', '54.7', '47.3', '46.5', 'n / a'], ['budget deficit 4 ( % of gdp )', 'n / a', 'n / a', '14.2', '9.1', '6.7', '5.9', '3.9', '3.1', '3.7', '4.5', '4.8', '5.7', '7.6', '5.5', '5.7', '6.5', '9.8', '15.6', '10.7', '9.5', '10.0', '3.8', '2.6', 'tba'], ['structural deficit 5 ( % of gdp )', 'n / a', 'n / a', '14.8', '9.1', '6.6', '6.1', '4.1', '3.3', '4.0', '4.6', '4.3', '5.6', '7.8', '5.3', '6.8', '7.9', '9.6', '14.8', '8.8', '5.4', '1.0', '- 2.0', '- 2.0', 'n / a'], ['hicp inflation ( annual % )', 'n / a', 'n / a', 'n / a', '8.9', '7.9', '5.4', '4.5', '2.1', '2.9', '3.7', '3.9', '3.4', '3.0', '3.5', '3.3', '3.0', '4.2', '1.3', '4.7', '3.1', '1.0', '- 0.8', '- 0.4', 'n / a'], ['gdp deflator 6 ( annual % )', '3.8', '19.3', '20.7', '9.8', '7.3', '6.8', '5.2', '3.0', '3.4', '3.1', '3.4', '3.9', '2.9', '2.8', '2.4', '3.3', '4.7', '2.3', '1.1', '1.0', '- 0.8', '- 1.1', '- 0.4', 'tba'], ['real gdp growth 7 ( % )', '8.9', '0.7', '0.0', '2.1', '2.4', '3.6', '3.4', '3.4', '4.5', '4.2', '3.4', '5.9', '4.4', '2.3', '5.5', '3.5', '0.2', '3.1', '4.9', '7.1', '6.4', '- 4.2', '0.6', 'tba'], ['public debt 8 ( billion )', '0.2', '1.5', '31.1', '86.9', '97.8', '105.2', '111.9', '118.6', '141.0', '151.9', '159.2', '168.0', '183.2', '195.4', '224.2', '239.3', '263.3', '299.7', '329.5', '355.2', '303.9', '321.5', '322.2', 'tba']] |
wmbj | https://en.wikipedia.org/wiki/WMBJ | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14996829-1.html.csv | count | two of these wmbj frequencies have a erp of 10 . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': '10', 'result': '2', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'erp w', '10'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose erp w record fuzzily matches to 10 .', 'tostr': 'filter_eq { all_rows ; erp w ; 10 }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; erp w ; 10 } }', 'tointer': 'select the rows whose erp w record fuzzily matches to 10 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; erp w ; 10 } } ; 2 } = true', 'tointer': 'select the rows whose erp w record fuzzily matches to 10 . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; erp w ; 10 } } ; 2 } = true | select the rows whose erp w record fuzzily matches to 10 . 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, 'erp w_5': 5, '10_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', 'erp w_5': 'erp w', '10_6': '10', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'erp w_5': [0], '10_6': [0], '2_7': [2]} | ['call sign', 'frequency mhz', 'city of license', 'erp w', 'class', 'fcc info'] | [['w203bq', '88.5 fm', 'walterboro , sc', '30', 'd', 'fcc'], ['w298aj', '107.5 fm', 'boone , nc', '10', 'd', 'fcc'], ['w227bk', '93.3 fm', 'surfside beach , sc', '27', 'd', 'fcc'], ['w238bi', '95.5 fm', 'georgetown , sc', '10', 'd', 'fcc'], ['w283av', '104.5 fm', 'little river , sc', '5', 'd', 'fcc'], ['w286ay', '105.1 fm', 'charleston , sc', '117', 'd', 'fcc']] |
2008 detroit shock season | https://en.wikipedia.org/wiki/2008_Detroit_Shock_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17103729-8.html.csv | aggregation | in the four games where deanna nolan was the high scorer for the detroit shock in july of 2008 , she scored an average of 25.25 points . | {'scope': 'subset', 'col': '5', 'type': 'average', 'result': '25.25', 'subset': {'col': '5', 'criterion': 'equal', 'value': 'nolan'}} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'high points', 'nolan'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; high points ; nolan }', 'tointer': 'select the rows whose high points record fuzzily matches to nolan .'}, 'high points'], 'result': '25.25', 'ind': 1, 'tostr': 'avg { filter_eq { all_rows ; high points ; nolan } ; high points }'}, '25.25'], 'result': True, 'ind': 2, 'tostr': 'round_eq { avg { filter_eq { all_rows ; high points ; nolan } ; high points } ; 25.25 } = true', 'tointer': 'select the rows whose high points record fuzzily matches to nolan . the average of the high points record of these rows is 25.25 .'} | round_eq { avg { filter_eq { all_rows ; high points ; nolan } ; high points } ; 25.25 } = true | select the rows whose high points record fuzzily matches to nolan . the average of the high points record of these rows is 25.25 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'avg_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'high points_5': 5, 'nolan_6': 6, 'high points_7': 7, '25.25_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'avg_1': 'avg', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'high points_5': 'high points', 'nolan_6': 'nolan', 'high points_7': 'high points', '25.25_8': '25.25'} | {'eq_2': [3], 'result_3': [], 'avg_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'high points_5': [0], 'nolan_6': [0], 'high points_7': [1], '25.25_8': [2]} | ['game', 'date', 'opponent', 'score', 'high points', 'high rebounds', 'high assists', 'location / attendance', 'record'] | [['18', 'july 1', 'san antonio', '72 - 79 ( ot )', 'smith ( 17 )', 'ford , sam ( 8 )', 'smith ( 9 )', 'at & t center 5656', '12 - 6'], ['19', 'july 8', 'connecticut', '88 - 82', 'pierson ( 23 )', 'braxton ( 8 )', 'nolan ( 8 )', 'palace of auburn hills 7623', '13 - 6'], ['20', 'july 11', 'washington', '79 - 66', 'smith ( 23 )', 'braxton , ford ( 7 )', 'nolan ( 4 )', 'palace of auburn hills 8596', '14 - 6'], ['21', 'july 12', 'new york', '64 - 74', 'smith , pierson ( 13 )', 'ford ( 12 )', 'nolan ( 4 )', 'madison square garden 8661', '14 - 7'], ['22', 'july 16', 'chicago', '66 - 63', 'ford ( 14 )', 'pierson ( 8 )', 'nolan , smith ( 4 )', 'palace of auburn hills 15210', '15 - 7'], ['23', 'july 18', 'washington', '99 - 62', 'nolan ( 26 )', 'braxton , hornbuckle ( 6 )', 'sam ( 8 )', 'verizon center 6834', '16 - 7'], ['24', 'july 20', 'sacramento', '85 - 88', 'nolan ( 27 )', 'ford ( 10 )', 'smith ( 6 )', 'palace of auburn hills 9138', '16 - 8'], ['25', 'july 22', 'los angeles', '81 - 84', 'smith ( 20 )', 'ford ( 9 )', 'hornbuckle , smith ( 5 )', 'palace of auburn hills 12930', '16 - 9'], ['26', 'july 24', 'houston', '61 - 79', 'nolan ( 23 )', 'nolan , sam ( 9 )', 'nolan ( 4 )', 'reliant arena 7261', '16 - 10'], ['27', 'july 27', 'san antonio', '64 - 76', 'nolan ( 25 )', 'braxton ( 9 )', 'smith ( 6 )', 'palace of auburn hills 9537', '16 - 11']] |
list of career achievements by lebron james | https://en.wikipedia.org/wiki/List_of_career_achievements_by_LeBron_James | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11012104-8.html.csv | ordinal | 48 points was the second highest amount of points that lebron james scored in a game . | {'row': '3', 'col': '4', 'order': '2', 'col_other': 'n/a', 'max_or_min': 'max_to_min', 'value_mentioned': 'yes', 'scope': 'all', 'subset': None} | {'func': 'eq', 'args': [{'func': 'nth_max', 'args': ['all_rows', 'points', '2'], 'result': '48', 'ind': 0, 'tostr': 'nth_max { all_rows ; points ; 2 }', 'tointer': 'the 2nd maximum points record of all rows is 48 .'}, '48'], 'result': True, 'ind': 1, 'tostr': 'eq { nth_max { all_rows ; points ; 2 } ; 48 } = true', 'tointer': 'the 2nd maximum points record of all rows is 48 .'} | eq { nth_max { all_rows ; points ; 2 } ; 48 } = true | the 2nd maximum points record of all rows is 48 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'nth_max_0': 0, 'all_rows_3': 3, 'points_4': 4, '2_5': 5, '48_6': 6} | {'eq_1': 'eq', 'result_2': 'true', 'nth_max_0': 'nth_max', 'all_rows_3': 'all_rows', 'points_4': 'points', '2_5': '2', '48_6': '48'} | {'eq_1': [2], 'result_2': [], 'nth_max_0': [1], 'all_rows_3': [0], 'points_4': [0], '2_5': [0], '48_6': [1]} | ['number', 'opponent', 'box score', 'points', 'fgm - fga', '3 pm - 3pa', 'ftm - fta', 'assists', 'rebounds', 'steals', 'blocks'] | [['1', 'washington wizards', 'w 97 - 96', '41', '16 - 28', '3 - 5', '6 - 9', '3', '5', '2', '0'], ['2', 'washington wizards', 'w 121 - 120', '45', '14 - 23', '0 - 1', '17 - 19', '6', '7', '2', '0'], ['3', 'detroit pistons', 'w 109 - 107', '48', '18 - 33', '2 - 3', '10 - 14', '7', '9', '2', '0'], ['4', 'boston celtics', 'l 92 - 97', '45', '14 - 29', '3 - 11', '14 - 19', '6', '5', '2', '0'], ['5', 'atlanta hawks', 'w 97 - 82', '47', '15 - 25', '5 - 10', '12 - 16', '8', '12', '1', '1'], ['6', 'orlando magic', 'l 106 - 107', '49', '20 - 30', '3 - 6', '6 - 10', '8', '6', '2', '3'], ['7', 'orlando magic', 'l 89 - 99', '41', '11 - 28', '1 - 8', '18 - 24', '9', '7', '2', '1'], ['8', 'orlando magic', 'l 114 - 116', '44', '13 - 29', '4 - 10', '14 - 18', '7', '12', '1', '1'], ['9', 'chicago bulls', 'w 112 - 102', '40', '16 - 23', '2 - 4', '6 - 6', '8', '8', '1', '2'], ['10', 'indiana pacers', 'w 101 - 93', '40', '14 - 27', '0 - 0', '12 - 16', '9', '18', '2', '2'], ['11', 'boston celtics', 'w 98 - 79', '45', '19 - 26', '2 - 4', '5 - 9', '5', '15', '0', '0']] |
list of tallest buildings in nashville | https://en.wikipedia.org/wiki/List_of_tallest_buildings_in_Nashville | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12169960-1.html.csv | ordinal | fifth third center is recorded as the 2nd tallest building in nashville . | {'row': '2', 'col': '3', 'order': '2', 'col_other': '2', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'height ft ( m )', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; height ft ( m ) ; 2 }'}, 'name'], 'result': 'fifth third center', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; height ft ( m ) ; 2 } ; name }'}, 'fifth third center'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; height ft ( m ) ; 2 } ; name } ; fifth third center } = true', 'tointer': 'select the row whose height ft ( m ) record of all rows is 2nd maximum . the name record of this row is fifth third center .'} | eq { hop { nth_argmax { all_rows ; height ft ( m ) ; 2 } ; name } ; fifth third center } = true | select the row whose height ft ( m ) record of all rows is 2nd maximum . the name record of this row is fifth third center . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'height ft (m)_5': 5, '2_6': 6, 'name_7': 7, 'fifth third center_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'height ft (m)_5': 'height ft ( m )', '2_6': '2', 'name_7': 'name', 'fifth third center_8': 'fifth third center'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'height ft (m)_5': [0], '2_6': [0], 'name_7': [1], 'fifth third center_8': [2]} | ['rank', 'name', 'height ft ( m )', 'floors', 'year'] | [['1', 'at & t building', '617 ( 188 )', '33', '1994'], ['2', 'fifth third center', '490 ( 149 )', '31', '1986'], ['3', 'william r snodgrass tennessee tower', '452 ( 138 )', '31', '1970'], ['4', 'pinnacle at symphony place', '417 ( 127 )', '28', '2010'], ['5', 'life and casualty tower', '409 ( 125 )', '30', '1957'], ['6', 'nashville city center', '402 ( 123 )', '27', '1988'], ['7', 'james k polk state office building', '392 ( 119 )', '24', '1981'], ['8', 'renaissance nashville hotel', '385 ( 117 )', '31', '1987'], ['9', 'viridian tower', '378 ( 115 )', '31', '2006'], ['10', 'one nashville place', '359 ( 109 )', '25', '1985'], ['11', 'regions center', '354 ( 108 )', '28', '1974'], ['12', 'sheraton nashville downtown', '300 ( 91 )', '27', '1975'], ['13', 'suntrust building', '292 ( 89 )', '20', '1967'], ['14', 'bank of america plaza', '292 ( 89 )', '20', '1977'], ['15', 'andrew jackson state office building', '286 ( 87 )', '17', '1969'], ['16', 'omni nashville hotel', '280 ( 85 )', '23', '2013'], ['17', 'palmer plaza', '269 ( 82 )', '18', '1986'], ['18', 'parkway towers', '261 ( 80 )', '21', '1968']] |
miss usa 1989 | https://en.wikipedia.org/wiki/Miss_USA_1989 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-16268026-3.html.csv | superlative | pennsylvania had the lowest score in the evening gown portion of the miss usa 1989 pageant . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '8', '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', 'evening gown'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; evening gown }'}, 'state'], 'result': 'pennsylvania', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; evening gown } ; state }'}, 'pennsylvania'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmin { all_rows ; evening gown } ; state } ; pennsylvania } = true', 'tointer': 'select the row whose evening gown record of all rows is minimum . the state record of this row is pennsylvania .'} | eq { hop { argmin { all_rows ; evening gown } ; state } ; pennsylvania } = true | select the row whose evening gown record of all rows is minimum . the state record of this row is pennsylvania . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'evening gown_5': 5, 'state_6': 6, 'pennsylvania_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'evening gown_5': 'evening gown', 'state_6': 'state', 'pennsylvania_7': 'pennsylvania'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'evening gown_5': [0], 'state_6': [1], 'pennsylvania_7': [2]} | ['state', 'preliminary average', 'interview', 'swimsuit', 'evening gown', 'semifinal average'] | [['new jersey', '8.510 ( 7 )', '8.626 ( 5 )', '8.712 ( 6 )', '9.165 ( 3 )', '8.834 ( 3 )'], ['colorado', '8.388 ( 10 )', '8.638 ( 4 )', '8.432 ( 9 )', '8.786 ( 5 )', '8.618 ( 7 )'], ['louisiana', '8.829 ( 2 )', '8.600 ( 6 )', '8.820 ( 4 )', '8.710 ( 7 )', '8.710 ( 5 )'], ['oklahoma', '8.662 ( 3 )', '8.880 ( 2 )', '8.762 ( 5 )', '9.214 ( 2 )', '8.952 ( 2 )'], ['california', '8.659 ( 4 )', '8.313 ( 8 )', '8.977 ( 2 )', '8.774 ( 6 )', '8.688 ( 6 )'], ['illinois', '8.501 ( 8 )', '7.988 ( 9 )', '8.432 ( 9 )', '8.681 ( 9 )', '8.367 ( 10 )'], ['texas', '9.084 ( 1 )', '9.425 ( 1 )', '9.535 ( 1 )', '9.601 ( 1 )', '9.520 ( 1 )'], ['pennsylvania', '8.580 ( 5 )', '8.534 ( 7 )', '8.467 ( 8 )', '8.613 ( 10 )', '8.538 ( 8 )'], ['arizona', '8.529 ( 6 )', '7.792 ( 10 )', '8.833 ( 3 )', '8.703 ( 8 )', '8.442 ( 9 )']] |
dusit chalermsan | https://en.wikipedia.org/wiki/Dusit_Chalermsan | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18455762-1.html.csv | majority | including friendlies dusit chalermsan won the majority of the games shown . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'won', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'result', 'won'], 'result': True, 'ind': 0, 'tointer': 'for the result records of all rows , most of them fuzzily match to won .', 'tostr': 'most_eq { all_rows ; result ; won } = true'} | most_eq { all_rows ; result ; won } = true | for the result records of all rows , most of them fuzzily match to won . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'result_3': 3, 'won_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'result_3': 'result', 'won_4': 'won'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'result_3': [0], 'won_4': [0]} | ['date', 'venue', 'score', 'result', 'competition'] | [['october 3 , 1994', 'hiroshima , japan', '1 - 2', 'lost', '1994 asian games'], ['october 5 , 1994', 'hiroshima , japan', '2 - 4', 'lost', '1994 asian games'], ['june 27 , 1996', 'bangkok , thailand', '8 - 0', 'won', '1996 asian cup qualification'], ['june 29 , 1996', 'bangkok , thailand', '5 - 1', 'won', '1996 asian cup qualification'], ['july 4 , 1996', 'singapore', '8 - 0', 'won', '1996 asian cup qualification'], ['december 11 , 1996', 'dubai , united arab emirates', '1 - 4', 'lost', '1996 asian cup'], ['march 15 , 1997', 'bangkok , thailand', '3 - 1', 'won', 'friendly'], ['march 30 , 1997', 'hong kong island , hong kong', '2 - 3', 'lost', '1998 fifa world cup qualification'], ['january 25 , 1998', 'bangkok , thailand', '1 - 1', 'drew', "king 's cup 1998"], ['december 8 , 1998', 'bangkok , thailand', '1 - 1', 'drew', '1998 asian games'], ['august 14 , 1999', 'bandar seri begawan , brunei', '2 - 0', 'won', '1999 southeast asian games'], ['september 3 , 2000', 'beijing , china', '4 - 2', 'won', 'friendly tournament'], ['november 10 , 2000', 'chiang mai , thailand', '4 - 1', 'won', '2000 tiger cup']] |
capital athletic conference | https://en.wikipedia.org/wiki/Capital_Athletic_Conference | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1973648-1.html.csv | unique | penn state - harrisburg is the only institution in the capital athletic conference that is located in pennsylvania . | {'scope': 'all', 'row': '5', 'col': '2', 'col_other': '1', 'criterion': 'fuzzily_match', 'value': 'pennsylvania', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location', 'pennsylvania'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose location record fuzzily matches to pennsylvania .', 'tostr': 'filter_eq { all_rows ; location ; pennsylvania }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; location ; pennsylvania } }', 'tointer': 'select the rows whose location record fuzzily matches to pennsylvania . 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', 'pennsylvania'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose location record fuzzily matches to pennsylvania .', 'tostr': 'filter_eq { all_rows ; location ; pennsylvania }'}, 'institution'], 'result': 'penn state - harrisburg', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; location ; pennsylvania } ; institution }'}, 'penn state - harrisburg'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; location ; pennsylvania } ; institution } ; penn state - harrisburg }', 'tointer': 'the institution record of this unqiue row is penn state - harrisburg .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; location ; pennsylvania } } ; eq { hop { filter_eq { all_rows ; location ; pennsylvania } ; institution } ; penn state - harrisburg } } = true', 'tointer': 'select the rows whose location record fuzzily matches to pennsylvania . there is only one such row in the table . the institution record of this unqiue row is penn state - harrisburg .'} | and { only { filter_eq { all_rows ; location ; pennsylvania } } ; eq { hop { filter_eq { all_rows ; location ; pennsylvania } ; institution } ; penn state - harrisburg } } = true | select the rows whose location record fuzzily matches to pennsylvania . there is only one such row in the table . the institution record of this unqiue row is penn state - harrisburg . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'location_7': 7, 'pennsylvania_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'institution_9': 9, 'penn state - harrisburg_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', 'pennsylvania_8': 'pennsylvania', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'institution_9': 'institution', 'penn state - harrisburg_10': 'penn state - harrisburg'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'location_7': [0], 'pennsylvania_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'institution_9': [2], 'penn state - harrisburg_10': [3]} | ['institution', 'location', 'nickname', 'founded', 'type', 'enrollment', 'joined'] | [['christopher newport university', 'newport news , virginia', 'captains', '1961', 'public', '5186', '2013 - 14'], ['frostburg state university', 'frostburg , maryland', 'bobcats', '1898', 'public', '5215', '2010 - 11'], ['university of mary washington', 'fredericksburg , virginia', 'eagles', '1908', 'public', '4862', '1989 - 90'], ['marymount university', 'arlington , virginia', 'saints', '1950', 'private / catholic', '3684', '1989 - 90'], ['penn state - harrisburg', 'lower swatara , pennsylvania', 'lions', '1966', 'public', '3441', '2013 - 14'], ["st mary 's college of maryland", "st mary 's city , maryland", 'seahawks', '1840', 'public', '1950', '1989 - 90'], ['salisbury university', 'salisbury , maryland', 'sea gulls', '1925', 'public', '7383', '1993 - 94'], ['southern virginia university', 'buena vista , virginia', 'knights', '1867', 'private', '804', '2013 - 14'], ['wesley college', 'dover , delaware', 'wolverines', '1873', 'private / methodist', '2400', '2007 - 08']] |
german submarine u - 404 | https://en.wikipedia.org/wiki/German_submarine_U-404 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17794265-1.html.csv | majority | most the the ships that suffered damage from the german u 404 ended up sinking . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': 'sunk', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'fate', 'sunk'], 'result': True, 'ind': 0, 'tointer': 'for the fate records of all rows , most of them fuzzily match to sunk .', 'tostr': 'most_eq { all_rows ; fate ; sunk } = true'} | most_eq { all_rows ; fate ; sunk } = true | for the fate records of all rows , most of them fuzzily match to sunk . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'fate_3': 3, 'sunk_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'fate_3': 'fate', 'sunk_4': 'sunk'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'fate_3': [0], 'sunk_4': [0]} | ['date', 'ship', 'nationality', 'tonnage', 'fate'] | [['5 march 1942', 'collamer', 'usa', '5112', 'sunk'], ['13 march 1942', 'tolten', 'chile', '1858', 'sunk'], ['14 march 1942', 'lemuel burrows', 'usa', '7610', 'sunk'], ['17 march 1942', 'san demitro', 'great britain', '8073', 'sunk'], ['30 may 1942', 'aloca shipper', 'usa', '5491', 'sunk'], ['1 june 1942', 'west notus', 'usa', '5492', 'sunk'], ['3 june 1942', 'anna', 'sweden', '1345', 'sunk'], ['24 june 1942', 'ljubica matokovic', 'yugoslavia', '3289', 'sunk'], ['25 june 1942', 'manuda', 'usa', '4772', 'sunk'], ['25 june 1942', 'nordal', 'panama', '3845', 'sunk'], ['27 june 1942', 'moldanger', 'norway', '6827', 'sunk'], ['11 september 1942', 'marit ii', 'norway', '7141', 'damaged'], ['12 september 1942', 'daghild', 'norway', '9272', 'damaged'], ['26 september 1942', 'hms veteran', 'great britain', '1120', 'sunk'], ['29 march 1943', 'nagara', 'great britain', '8791', 'sunk'], ['30 march 1943', 'empire bowman', 'great britain', '7031', 'sunk'], ['12 april 1943', 'lancastrian prince', 'great britain', '1914', 'sunk']] |
1954 vfl season | https://en.wikipedia.org/wiki/1954_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10773616-6.html.csv | ordinal | kardinia park venue recorded the highest crowd participation in the 1954 vfl season . | {'row': '5', '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': 'kardinia park', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; crowd ; 1 } ; venue }'}, 'kardinia park'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; crowd ; 1 } ; venue } ; kardinia park } = true', 'tointer': 'select the row whose crowd record of all rows is 1st maximum . the venue record of this row is kardinia park .'} | eq { hop { nth_argmax { all_rows ; crowd ; 1 } ; venue } ; kardinia park } = true | select the row whose crowd record of all rows is 1st maximum . the venue record of this row is kardinia park . | 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, 'kardinia park_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', 'kardinia park_8': 'kardinia park'} | {'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], 'kardinia park_8': [2]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['north melbourne', '8.14 ( 62 )', 'south melbourne', '12.13 ( 85 )', 'arden street oval', '15000', '22 may 1954'], ['st kilda', '14.15 ( 99 )', 'melbourne', '12.6 ( 78 )', 'junction oval', '16000', '22 may 1954'], ['richmond', '10.12 ( 72 )', 'hawthorn', '11.12 ( 78 )', 'punt road oval', '23000', '22 may 1954'], ['footscray', '12.8 ( 80 )', 'essendon', '4.7 ( 31 )', 'western oval', '30000', '22 may 1954'], ['geelong', '13.17 ( 95 )', 'collingwood', '9.8 ( 62 )', 'kardinia park', '32500', '22 may 1954'], ['fitzroy', '8.10 ( 58 )', 'carlton', '15.10 ( 100 )', 'brunswick street oval', '20000', '22 may 1954']] |
comparison of e - book readers | https://en.wikipedia.org/wiki/Comparison_of_e-book_readers | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1149661-3.html.csv | superlative | apple makes the product that has the most screen pixels on it . | {'scope': 'all', 'col_superlative': '7', 'row_superlative': '6', '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', 'screen pixels'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; screen pixels }'}, 'maker'], 'result': 'apple inc', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; screen pixels } ; maker }'}, 'apple inc'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; screen pixels } ; maker } ; apple inc } = true', 'tointer': 'select the row whose screen pixels record of all rows is maximum . the maker record of this row is apple inc .'} | eq { hop { argmax { all_rows ; screen pixels } ; maker } ; apple inc } = true | select the row whose screen pixels record of all rows is maximum . the maker record of this row is apple inc . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'screen pixels_5': 5, 'maker_6': 6, 'apple inc_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'screen pixels_5': 'screen pixels', 'maker_6': 'maker', 'apple inc_7': 'apple inc'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'screen pixels_5': [0], 'maker_6': [1], 'apple inc_7': [2]} | ['maker', 'model', 'intro year', 'screen size ( inch )', 'screen type', 'weight', 'screen pixels', 'hours reading', 'touch screen', 'wireless network', 'internal storage', 'card reader slot'] | [['aluratek', 'libre touch ebook reader', '2011', '7', 'lcd', 'g ( oz )', '480 800', '8', 'yes', 'yes , wi - fi', '4 gb', 'microsd'], ['aluratek', 'libre air ebook reader', '2011', '5', 'lcd', 'g ( oz )', '480 640', '20', 'no', 'yes , wi - fi', '512 mb', 'microsd'], ['aluratek', 'libre color ebook reader', '2010', '7', 'lcd', 'g ( oz )', '480 800', '24', 'no', 'no', '2 gb', 'sd'], ['aluratek', 'libre pro ebook reader', '2009', '5', 'lcd', 'g ( oz )', '480 640', '24', 'no', 'no', '256 mb', 'sd'], ['amazoncom', 'kindle fire', '2011', '7', 'lcd ( ips )', 'g ( oz )', '600 1024', '8', 'yes', 'wi - fi', '8 gb ( 6 gb )', 'no'], ['apple inc', 'ipad ( 3rd generation )', '2012', '9.7', 'lcd ( ips )', 'g ( oz ) , g ( oz )', '2048 1536', '10', 'yes', 'wi - fi , 3 g', '16 - 64 gb', 'sd via camera connection kit'], ['apple inc', 'ipad 2', '2011', '9.7', 'lcd ( ips )', 'g ( oz )', '768 1024', '10', 'yes', 'wi - fi , 3 g', '16 - 64 gb', 'sd via camera connection kit'], ['apple inc', 'ipad', '2010', '9.7', 'lcd', 'g ( oz )', '768 1024', '9', 'yes', 'wi - fi', '16 - 64 gb', 'sd via camera connection kit'], ['barnes & noble', 'nook color', '2010', '7', 'lcd', 'g ( oz )', '600 1024', '8', 'yes', 'wi - fi 802.11 b / g / n', '2 gb , 1 gb available', 'microsdhc'], ['ectaco', 'jetbook', '2008', '5', 'lcd', 'g ( oz )', '480 640', '20', 'no', 'no', '112 mb', 'sdhc'], ['elonex', '705eb', '2010', '7', 'led', 'g ( oz )', '480 800', '8', 'no', 'no', '4 gb', 'microsdhc'], ['notion ink', 'adam', '2011', '10.1', 'pixel qi', 'g ( oz )', '600 1024', '15', 'yes', 'wi - fi , 3 g', '1 gb ddr2 ram 1 gb slc', 'microsd'], ['pocketbook', 'pocketbook iq 701', '2010', '7', 'lcd', 'g ( oz )', '600 800', '8', 'yes', 'wi - fi', '2 gb', 'sdhc'], ['trekstor', 'ebook reader 3.0', '2011', '7', 'lcd', 'g ( oz )', '800 480', '8', 'no', 'no', '2 gb', 'microsdhc'], ['zzbook', 'ereader hd', '2010', '7', 'tft - lcd', 'g ( oz )', '800 480', '8', 'no', 'no', '2 gb', 'microsd'], ['maker', 'model', 'intro year', 'screen size ( inch )', 'screen type', 'weight', 'screen pixels', 'hours reading', 'touch screen', 'wireless network', 'internal storage', 'card reader slot']] |
athletics at the 1982 commonwealth games | https://en.wikipedia.org/wiki/Athletics_at_the_1982_Commonwealth_Games | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12972743-3.html.csv | comparative | at the 1982 commonwealth games , new zealand won 2 more bronze medals than jamaica . | {'row_1': '6', 'row_2': '7', 'col': '5', 'col_other': '2', 'relation': 'diff', 'record_mentioned': 'no', 'diff_result': {'diff_value': '2', 'bigger': 'row1'}} | {'func': 'eq', 'args': [{'func': 'diff', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'nation', 'new zealand'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose nation record fuzzily matches to new zealand .', 'tostr': 'filter_eq { all_rows ; nation ; new zealand }'}, 'bronze'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; nation ; new zealand } ; bronze }', 'tointer': 'select the rows whose nation record fuzzily matches to new zealand . take the bronze record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'nation', 'jamaica'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose nation record fuzzily matches to jamaica .', 'tostr': 'filter_eq { all_rows ; nation ; jamaica }'}, 'bronze'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; nation ; jamaica } ; bronze }', 'tointer': 'select the rows whose nation record fuzzily matches to jamaica . take the bronze record of this row .'}], 'result': '2', 'ind': 4, 'tostr': 'diff { hop { filter_eq { all_rows ; nation ; new zealand } ; bronze } ; hop { filter_eq { all_rows ; nation ; jamaica } ; bronze } }'}, '2'], 'result': True, 'ind': 5, 'tostr': 'eq { diff { hop { filter_eq { all_rows ; nation ; new zealand } ; bronze } ; hop { filter_eq { all_rows ; nation ; jamaica } ; bronze } } ; 2 } = true', 'tointer': 'select the rows whose nation record fuzzily matches to new zealand . take the bronze record of this row . select the rows whose nation record fuzzily matches to jamaica . take the bronze record of this row . the first record is 2 larger than the second record .'} | eq { diff { hop { filter_eq { all_rows ; nation ; new zealand } ; bronze } ; hop { filter_eq { all_rows ; nation ; jamaica } ; bronze } } ; 2 } = true | select the rows whose nation record fuzzily matches to new zealand . take the bronze record of this row . select the rows whose nation record fuzzily matches to jamaica . take the bronze record of this row . the first record is 2 larger than the second record . | 6 | 6 | {'eq_5': 5, 'result_6': 6, 'diff_4': 4, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_7': 7, 'nation_8': 8, 'new zealand_9': 9, 'bronze_10': 10, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_11': 11, 'nation_12': 12, 'jamaica_13': 13, 'bronze_14': 14, '2_15': 15} | {'eq_5': 'eq', 'result_6': 'true', 'diff_4': 'diff', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_7': 'all_rows', 'nation_8': 'nation', 'new zealand_9': 'new zealand', 'bronze_10': 'bronze', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_11': 'all_rows', 'nation_12': 'nation', 'jamaica_13': 'jamaica', 'bronze_14': 'bronze', '2_15': '2'} | {'eq_5': [6], 'result_6': [], 'diff_4': [5], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_7': [0], 'nation_8': [0], 'new zealand_9': [0], 'bronze_10': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_11': [1], 'nation_12': [1], 'jamaica_13': [1], 'bronze_14': [3], '2_15': [5]} | ['rank', 'nation', 'gold', 'silver', 'bronze', 'total'] | [['1', 'england', '11', '10', '11', '32'], ['2', 'australia', '9', '9', '4', '22'], ['3', 'canada', '6', '7', '8', '21'], ['4', 'scotland', '3', '1', '6', '10'], ['5', 'bahamas', '2', '2', '1', '5'], ['6', 'new zealand', '2', '1', '3', '6'], ['7', 'jamaica', '2', '1', '1', '4'], ['8', 'wales', '2', '1', '0', '3'], ['9', 'tanzania', '1', '2', '1', '4'], ['10', 'kenya', '1', '1', '3', '5'], ['11', 'nigeria', '1', '0', '0', '1'], ['12', 'uganda', '0', '2', '0', '2'], ['13', 'northern ireland', '0', '1', '0', '1'], ['14', 'bermuda', '0', '0', '1', '1'], ['total', 'total', '40', '38', '39', '117']] |
2008 - 09 minnesota timberwolves season | https://en.wikipedia.org/wiki/2008%E2%80%9309_Minnesota_Timberwolves_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17058226-5.html.csv | aggregation | the ford center games had a total attendance of over 36000 . | {'scope': 'subset', 'col': '8', 'type': 'sum', 'result': 'over 36000', 'subset': {'col': '8', 'criterion': 'fuzzily_match', 'value': 'ford center'}} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location attendance', 'ford center'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; location attendance ; ford center }', 'tointer': 'select the rows whose location attendance record fuzzily matches to ford center .'}, 'location attendance'], 'result': 'over 36000', 'ind': 1, 'tostr': 'sum { filter_eq { all_rows ; location attendance ; ford center } ; location attendance }'}, 'over 36000'], 'result': True, 'ind': 2, 'tostr': 'round_eq { sum { filter_eq { all_rows ; location attendance ; ford center } ; location attendance } ; over 36000 } = true', 'tointer': 'select the rows whose location attendance record fuzzily matches to ford center . the sum of the location attendance record of these rows is over 36000 .'} | round_eq { sum { filter_eq { all_rows ; location attendance ; ford center } ; location attendance } ; over 36000 } = true | select the rows whose location attendance record fuzzily matches to ford center . the sum of the location attendance record of these rows is over 36000 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'sum_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'location attendance_5': 5, 'Ford Center_6': 6, 'location attendance_7': 7, 'over 36000_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'sum_1': 'sum', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'location attendance_5': 'location attendance', 'Ford Center_6': 'ford center', 'location attendance_7': 'location attendance', 'over 36000_8': 'over 36000'} | {'eq_2': [3], 'result_3': [], 'sum_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'location attendance_5': [0], 'Ford Center_6': [0], 'location attendance_7': [1], 'over 36000_8': [2]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record'] | [['2', 'november 1', 'dallas', 'l 85 - 95 ( ot )', 'rashad mccants ( 18 )', 'al jefferson ( 12 )', 'randy foye ( 6 )', 'target center 16893', '1 - 1'], ['3', 'november 2', 'oklahoma city', 'l 85 - 88 ( ot )', 'al jefferson ( 24 )', 'al jefferson ( 13 )', 'randy foye ( 6 )', 'ford center 18163', '1 - 2'], ['4', 'november 5', 'san antonio', 'l 125 - 129 ( 2ot )', 'al jefferson ( 30 )', 'al jefferson ( 14 )', 'sebastian telfair ( 10 )', 'target center 11112', '1 - 3'], ['5', 'november 7', 'sacramento', 'l 109 - 121 ( ot )', 'kevin love ( 20 )', 'al jefferson ( 9 )', 'sebastian telfair ( 7 )', 'arco arena 10592', '1 - 4'], ['6', 'november 8', 'portland', 'l 93 - 97 ( ot )', 'al jefferson ( 27 )', 'kevin love ( 7 )', 'al jefferson , randy foye ( 5 )', 'rose garden 20599', '1 - 5'], ['7', 'november 11', 'golden state', 'l 110 - 113 ( ot )', 'al jefferson ( 25 )', 'al jefferson ( 12 )', 'randy foye ( 8 )', 'oracle arena 17422', '1 - 6'], ['8', 'november 15', 'portland', 'l 83 - 88 ( ot )', 'al jefferson ( 26 )', 'al jefferson ( 6 )', 'mike miller ( 5 )', 'target center 12213', '1 - 7'], ['9', 'november 16', 'denver', 'l 84 - 90 ( ot )', 'al jefferson ( 20 )', 'al jefferson ( 14 )', 'randy foye ( 6 )', 'pepsi center 16721', '1 - 8'], ['10', 'november 19', 'philadelphia', 'w 102 - 96 ( ot )', 'al jefferson ( 25 )', 'mike miller ( 10 )', 'sebastian telfair ( 8 )', 'target center 10111', '2 - 8'], ['11', 'november 21', 'boston', 'l 78 - 95 ( ot )', 'al jefferson ( 21 )', 'craig smith ( 7 )', 'craig smith ( 4 )', 'target center 19107', '2 - 9'], ['12', 'november 23', 'detroit', 'w 106 - 80 ( ot )', 'randy foye ( 23 )', 'craig smith ( 9 )', 'randy foye ( 14 )', 'the palace of auburn hills 22076', '3 - 9'], ['13', 'november 26', 'phoenix', 'l 102 - 110 ( ot )', 'al jefferson ( 28 )', 'al jefferson ( 17 )', 'mike miller ( 6 )', 'target center 11708', '3 - 10'], ['14', 'november 28', 'oklahoma city', 'w 105 - 103 ( ot )', 'craig smith ( 23 )', 'al jefferson ( 9 )', 'randy foye ( 7 )', 'ford center 18229', '4 - 10'], ['15', 'november 29', 'denver', 'l 97 - 106 ( ot )', 'randy foye ( 25 )', 'al jefferson ( 13 )', 'randy foye ( 6 )', 'target center 14197', '4 - 11']] |
2006 tampa bay storm season | https://en.wikipedia.org/wiki/2006_Tampa_Bay_Storm_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11866255-1.html.csv | count | there were eight home games in the tampa bay storm 's 2006 season . | {'scope': 'all', 'criterion': 'equal', 'value': 'home', 'result': '8', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'home / away', 'home'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose home / away record fuzzily matches to home .', 'tostr': 'filter_eq { all_rows ; home / away ; home }'}], 'result': '8', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; home / away ; home } }', 'tointer': 'select the rows whose home / away record fuzzily matches to home . the number of such rows is 8 .'}, '8'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; home / away ; home } } ; 8 } = true', 'tointer': 'select the rows whose home / away record fuzzily matches to home . the number of such rows is 8 .'} | eq { count { filter_eq { all_rows ; home / away ; home } } ; 8 } = true | select the rows whose home / away record fuzzily matches to home . the number of such rows is 8 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'home / away_5': 5, 'home_6': 6, '8_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'home / away_5': 'home / away', 'home_6': 'home', '8_7': '8'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'home / away_5': [0], 'home_6': [0], '8_7': [2]} | ['week', 'date', 'opponent', 'home / away', 'result'] | [['1', 'january 29', 'philadelphia soul', 'away', 'l 52 - 34'], ['2', 'february 3', 'grand rapids rampage', 'away', 'w 51 - 43'], ['3', 'february 10', 'georgia force', 'home', 'w 61 - 60'], ['4', 'february 19', 'orlando predators', 'home', 'l 67 - 64 ( ot )'], ['5', 'february 25', 'austin wranglers', 'home', 'w 58 - 48'], ['6', 'march 5', 'kansas city brigade', 'away', 'w 69 - 59'], ['7', 'march 12', 'dallas desperados', 'home', 'l 64 - 35'], ['8', 'march 18', 'new york dragons', 'home', 'w 60 - 44'], ['9', 'march 26', 'georgia force', 'away', 'l 61 - 51'], ['10', 'april 1', 'utah blaze', 'home', 'w 56 - 41'], ['11', 'april 7', 'san jose sabercats', 'home', 'l 52 - 43'], ['12', 'april 15', 'austin wranglers', 'away', 'l 60 - 59'], ['13', 'april 22', 'orlando predators', 'away', 'l 52 - 13'], ['14', 'april 29', 'kansas city brigade', 'home', 'w 58 - 42'], ['15', 'may 6', 'columbus destroyers', 'away', 'l 51 - 48'], ['16', 'may 13', 'nashville kats', 'away', 'l 66 - 50']] |
special representative of the secretary - general for kosovo | https://en.wikipedia.org/wiki/Special_Representative_of_the_Secretary-General_for_Kosovo | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16077854-1.html.csv | ordinal | for the special representative of the secretary - general for kosovo , the 2nd to last one to take office was lamberto zannier . | {'row': '8', 'col': '3', 'order': '2', 'col_other': '1', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'took office', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; took office ; 2 }'}, 'name'], 'result': 'lamberto zannier', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; took office ; 2 } ; name }'}, 'lamberto zannier'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; took office ; 2 } ; name } ; lamberto zannier } = true', 'tointer': 'select the row whose took office record of all rows is 2nd maximum . the name record of this row is lamberto zannier .'} | eq { hop { nth_argmax { all_rows ; took office ; 2 } ; name } ; lamberto zannier } = true | select the row whose took office record of all rows is 2nd maximum . the name record of this row is lamberto zannier . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'took office_5': 5, '2_6': 6, 'name_7': 7, 'lamberto zannier_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', 'took office_5': 'took office', '2_6': '2', 'name_7': 'name', 'lamberto zannier_8': 'lamberto zannier'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'took office_5': [0], '2_6': [0], 'name_7': [1], 'lamberto zannier_8': [2]} | ['name', 'born - died', 'took office', 'left office', 'country'] | [['sérgio vieira de mello', '1948 - 2003', 'june 1999', 'july 1999', 'brazil'], ['bernard kouchner', '1939 -', '15 july 1999', '12 january 2001', 'france'], ['hans hækkerup', '1945 -', '13 january 2001', '31 december 2001', 'denmark'], ['michael steiner', '1949 -', '14 february 2002', '8 july 2003', 'germany'], ['harri holkeri', '1937 - 2011', '25 august 2003', '11 june 2004', 'finland'], ['søren jessen - petersen', '1945 -', '16 august 2004', '30 june 2006', 'denmark'], ['joachim rücker', '1951 -', '1 september 2006', '20 june 2008', 'germany'], ['lamberto zannier', '1954 -', '20 june 2008', 'june 2011', 'italy'], ['farid zarif', '1951 -', '11 october 2011', 'incumbent', 'afghanistan']] |
1961 oakland raiders season | https://en.wikipedia.org/wiki/1961_Oakland_Raiders_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12676370-1.html.csv | majority | the majority of the oakland raiders games in the 1961 season were losses . | {'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 9 , 1961', 'houston oilers', 'l 55 - 0', '16231'], ['2', 'september 17 , 1961', 'san diego chargers', 'l 44 - 0', '20216'], ['3', 'september 24 , 1961', 'dallas texans', 'l 42 - 35', '6737'], ['4', 'october 1 , 1961', 'denver broncos', 'w 33 - 19', '8361'], ['5', 'october 15 , 1961', 'denver broncos', 'l 27 - 24', '11129'], ['6', 'october 22 , 1961', 'san diego chargers', 'l 41 - 10', '12014'], ['7', 'october 29 , 1961', 'new york titans', 'l 14 - 6', '7138'], ['8', 'november 5 , 1961', 'buffalo bills', 'w 31 - 22', '17027'], ['9', 'november 11 , 1961', 'new york titans', 'l 23 - 12', '16811'], ['10', 'november 17 , 1961', 'boston patriots', 'l 20 - 17', '18169'], ['11', 'november 26 , 1961', 'dallas texans', 'l 43 - 11', '14500'], ['12', 'december 3 , 1961', 'buffalo bills', 'l 26 - 21', '6500'], ['13', 'december 9 , 1961', 'boston patriots', 'l 35 - 21', '6500'], ['14', 'december 17 , 1961', 'houston oilers', 'l 47 - 16', '4821']] |
hunt - class mine countermeasures vessel | https://en.wikipedia.org/wiki/Hunt-class_mine_countermeasures_vessel | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1162013-1.html.csv | count | two of the hunt - class mine countermeasures vessels are with the lithuanian naval force . | {'scope': 'all', 'criterion': 'equal', 'value': 'lithuanian naval force', 'result': '2', 'col': '1', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'navy', 'lithuanian naval force'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose navy record fuzzily matches to lithuanian naval force .', 'tostr': 'filter_eq { all_rows ; navy ; lithuanian naval force }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; navy ; lithuanian naval force } }', 'tointer': 'select the rows whose navy record fuzzily matches to lithuanian naval force . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; navy ; lithuanian naval force } } ; 2 } = true', 'tointer': 'select the rows whose navy record fuzzily matches to lithuanian naval force . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; navy ; lithuanian naval force } } ; 2 } = true | select the rows whose navy record fuzzily matches to lithuanian naval force . 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, 'navy_5': 5, 'lithuanian naval force_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', 'navy_5': 'navy', 'lithuanian naval force_6': 'lithuanian naval force', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'navy_5': [0], 'lithuanian naval force_6': [0], '2_7': [2]} | ['navy', 'name', 'pennant', 'commissioned', 'home port'] | [['royal navy', 'brecon', 'm29', '1980', 'hms raleigh'], ['royal navy', 'ledbury', 'm30', '1981', 'portsmouth'], ['royal navy', 'cattistock', 'm31', '1982', 'portsmouth'], ['royal navy', 'cottesmore', 'm32', '1983', 'portsmouth'], ['royal navy', 'brocklesby', 'm33', '1982', 'portsmouth'], ['royal navy', 'middleton', 'm34', '1984', 'portsmouth'], ['royal navy', 'dulverton', 'm35', '1983', 'portsmouth'], ['royal navy', 'bicester', 'm36', '1988', 'portsmouth'], ['royal navy', 'chiddingfold', 'm37', '1984', 'portsmouth'], ['royal navy', 'atherstone', 'm38', '1986', 'portsmouth'], ['royal navy', 'hurworth', 'm39', '1985', 'portsmouth'], ['royal navy', 'berkeley', 'm40', '1986', 'portsmouth'], ['royal navy', 'quorn', 'm41', '1989', 'portsmouth'], ['hellenic navy', 'europa', 'm62', '2001', 'salamis'], ['hellenic navy', 'kallisto', 'm63', '2000', 'salamis'], ['lithuanian naval force', 'skalvis', 'm53', '2011', 'klaipėda'], ['lithuanian naval force', 'kuršis', 'm51', '2011', 'klaipėda']] |
phoenix suns all - time roster | https://en.wikipedia.org/wiki/Phoenix_Suns_all-time_roster | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11482079-2.html.csv | superlative | the highest number of rebounds for the phoenix suns was from alvan adams . | {'scope': 'all', 'col_superlative': '5', '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', 'rebs'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; rebs }'}, 'player'], 'result': 'alvan adams', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; rebs } ; player }'}, 'alvan adams'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; rebs } ; player } ; alvan adams } = true', 'tointer': 'select the row whose rebs record of all rows is maximum . the player record of this row is alvan adams .'} | eq { hop { argmax { all_rows ; rebs } ; player } ; alvan adams } = true | select the row whose rebs record of all rows is maximum . the player record of this row is alvan adams . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'rebs_5': 5, 'player_6': 6, 'alvan adams_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'rebs_5': 'rebs', 'player_6': 'player', 'alvan adams_7': 'alvan adams'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'rebs_5': [0], 'player_6': [1], 'alvan adams_7': [2]} | ['player', 'pos', 'from', 'school / country', 'rebs', 'asts'] | [['alvan adams', 'c / f', '1975', 'oklahoma', '6937', '4012'], ['rafael addison', 'g / f', '1986', 'syracuse', '106', '45'], ['danny ainge', 'sg', '1992', 'byu', '454', '650'], ['louis amundson', 'pf', '2008', 'unlv', '616', '59'], ['robert archibald', 'f / c', '2003', 'illinois', '1', '1'], ['dennis awtrey', 'c', '1974', 'santa clara', '1655', '846']] |
tomasz sikora | https://en.wikipedia.org/wiki/Tomasz_Sikora | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1269400-1.html.csv | comparative | in the individual event , tomasz sikkora did better in 2010 than in 1998 . | {'row_1': '5', 'row_2': '2', 'col': '2', 'col_other': '1', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'event', '2010 vancouver'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose event record fuzzily matches to 2010 vancouver .', 'tostr': 'filter_eq { all_rows ; event ; 2010 vancouver }'}, 'individual'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; event ; 2010 vancouver } ; individual }', 'tointer': 'select the rows whose event record fuzzily matches to 2010 vancouver . take the individual record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'event', '1998 nagano - nozawa'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose event record fuzzily matches to 1998 nagano - nozawa .', 'tostr': 'filter_eq { all_rows ; event ; 1998 nagano - nozawa }'}, 'individual'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; event ; 1998 nagano - nozawa } ; individual }', 'tointer': 'select the rows whose event record fuzzily matches to 1998 nagano - nozawa . take the individual record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; event ; 2010 vancouver } ; individual } ; hop { filter_eq { all_rows ; event ; 1998 nagano - nozawa } ; individual } } = true', 'tointer': 'select the rows whose event record fuzzily matches to 2010 vancouver . take the individual record of this row . select the rows whose event record fuzzily matches to 1998 nagano - nozawa . take the individual record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; event ; 2010 vancouver } ; individual } ; hop { filter_eq { all_rows ; event ; 1998 nagano - nozawa } ; individual } } = true | select the rows whose event record fuzzily matches to 2010 vancouver . take the individual record of this row . select the rows whose event record fuzzily matches to 1998 nagano - nozawa . take the individual 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, 'event_7': 7, '2010 vancouver_8': 8, 'individual_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'event_11': 11, '1998 nagano - nozawa_12': 12, 'individual_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', 'event_7': 'event', '2010 vancouver_8': '2010 vancouver', 'individual_9': 'individual', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'event_11': 'event', '1998 nagano - nozawa_12': '1998 nagano - nozawa', 'individual_13': 'individual'} | {'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'event_7': [0], '2010 vancouver_8': [0], 'individual_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'event_11': [1], '1998 nagano - nozawa_12': [1], 'individual_13': [3]} | ['event', 'individual', 'sprint', 'pursuit', 'mass start', 'relay'] | [['1994 lillehammer', '-', '32nd', '-', '-', '-'], ['1998 nagano - nozawa', '47th', '28th', '-', '-', '5th'], ['2002 salt lake city', '46th', '31st', '25th', '-', '9th'], ['2006 turin', '21st', '20th', '18th', '2nd', '13th'], ['2010 vancouver', '7th', '29th', '18th', '11th', '-']] |
acute liver failure | https://en.wikipedia.org/wiki/Acute_liver_failure | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1226250-1.html.csv | majority | most conditions that led to acute liver failure did not affect the platelet count . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': 'unaffected', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'platelet count', 'unaffected'], 'result': True, 'ind': 0, 'tointer': 'for the platelet count records of all rows , most of them fuzzily match to unaffected .', 'tostr': 'most_eq { all_rows ; platelet count ; unaffected } = true'} | most_eq { all_rows ; platelet count ; unaffected } = true | for the platelet count records of all rows , most of them fuzzily match to unaffected . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'platelet count_3': 3, 'unaffected_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'platelet count_3': 'platelet count', 'unaffected_4': 'unaffected'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'platelet count_3': [0], 'unaffected_4': [0]} | ['condition', 'prothrombin time', 'partial thromboplastin time', 'bleeding time', 'platelet count'] | [['vitamin k deficiency or warfarin', 'prolonged', 'normal or mildly prolonged', 'unaffected', 'unaffected'], ['disseminated intravascular coagulation', 'prolonged', 'prolonged', 'prolonged', 'decreased'], ['von willebrand disease', 'unaffected', 'prolonged or unaffected', 'prolonged', 'unaffected'], ['hemophilia', 'unaffected', 'prolonged', 'unaffected', 'unaffected'], ['aspirin', 'unaffected', 'unaffected', 'prolonged', 'unaffected'], ['thrombocytopenia', 'unaffected', 'unaffected', 'prolonged', 'decreased'], ['liver failure , early', 'prolonged', 'unaffected', 'unaffected', 'unaffected'], ['liver failure , end - stage', 'prolonged', 'prolonged', 'prolonged', 'decreased'], ['uremia', 'unaffected', 'unaffected', 'prolonged', 'unaffected'], ['congenital afibrinogenemia', 'prolonged', 'prolonged', 'prolonged', 'unaffected'], ['factor v deficiency', 'prolonged', 'prolonged', 'unaffected', 'unaffected'], ['factor x deficiency as seen in amyloid purpura', 'prolonged', 'prolonged', 'unaffected', 'unaffected'], ["glanzmann 's thrombasthenia", 'unaffected', 'unaffected', 'prolonged', 'unaffected'], ['bernard - soulier syndrome', 'unaffected', 'unaffected', 'prolonged', 'decreased or unaffected'], ['factor xii deficiency', 'unaffected', 'prolonged', 'unaffected', 'unaffected']] |
prva hnl | https://en.wikipedia.org/wiki/Prva_HNL | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1510519-1.html.csv | majority | the majority of clubs in prva hnl had 0 top division titles . | {'scope': 'all', 'col': '7', 'most_or_all': 'most', 'criterion': 'equal', 'value': '0', 'subset': None} | {'func': 'most_eq', 'args': ['all_rows', 'top division titles', '0'], 'result': True, 'ind': 0, 'tointer': 'for the top division titles records of all rows , most of them are equal to 0 .', 'tostr': 'most_eq { all_rows ; top division titles ; 0 } = true'} | most_eq { all_rows ; top division titles ; 0 } = true | for the top division titles records of all rows , most of them are equal to 0 . | 1 | 1 | {'most_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'top division titles_3': 3, '0_4': 4} | {'most_eq_0': 'most_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'top division titles_3': 'top division titles', '0_4': '0'} | {'most_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'top division titles_3': [0], '0_4': [0]} | ['club', 'position in 2012 - 13', 'first season in top division', 'number of seasons in top division', 'number of seasons in prva hnl', 'first season of current spell in top division', 'top division titles', 'last top division title'] | [['dinamo zagreb a , b', '001 1st', '1946 - 47', '68', '23', '1946 - 47', '19 c', '2012 - 13'], ['hajduk split a , b', '004 4th', '1923', '86', '23', '1923', '15 d', '2004 - 05'], ['hrvatski dragovoljac', 'zzz 1st in 2 . hnl', '1995 - 96', '9', '9', '2013 - 14', '0', 'n / a'], ['istra 1961', '006 6th', '2004 - 05', '8', '8', '2009 - 10', '0', 'n / a'], ['lokomotiva b', '002 2nd', '1946 - 47', '15', '5', '2009 - 10', '0', 'n / a'], ['osijek a , b', '007 7th', '1953 - 54', '38', '23', '1981 - 82', '0', 'n / a'], ['rijeka a , b', '003 3rd', '1946 - 47', '52', '23', '1974 - 75', '0', 'n / a'], ['slaven belupo b', '008 8th', '1997 - 98', '17', '17', '1997 - 98', '0', 'n / a'], ['rnk split b', '005 5th', '1957 - 58', '6', '4', '2010 - 11', '0', 'n / a']] |
list of agatha christie 's poirot episodes | https://en.wikipedia.org/wiki/List_of_Agatha_Christie%27s_Poirot_episodes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10831820-1.html.csv | count | 2 actors were only active from series ' 10-13 of agatha christie 's poirot . | {'scope': 'all', 'criterion': 'equal', 'value': '10 - 13', 'result': '2', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'series', '10 - 13'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose series record fuzzily matches to 10 - 13 .', 'tostr': 'filter_eq { all_rows ; series ; 10 - 13 }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; series ; 10 - 13 } }', 'tointer': 'select the rows whose series record fuzzily matches to 10 - 13 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; series ; 10 - 13 } } ; 2 } = true', 'tointer': 'select the rows whose series record fuzzily matches to 10 - 13 . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; series ; 10 - 13 } } ; 2 } = true | select the rows whose series record fuzzily matches to 10 - 13 . 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, 'series_5': 5, '10 - 13_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', 'series_5': 'series', '10 - 13_6': '10 - 13', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'series_5': [0], '10 - 13_6': [0], '2_7': [2]} | ['actor', 'character', 'title / rank', 'series', 'years'] | [['david suchet', 'hercule poirot', 'various', '1 - 13', '1989 - 2013'], ['hugh fraser', 'arthur hastings', 'captain obe', '1 - 8 , 13', '1989 - 2002 , 2013'], ['philip jackson', 'james japp', 'chief inspector', '1 - 8 , 13', '1989 - 2001 , 2013'], ['pauline moran', 'felicity lemon', 'secretary', '1 - 3 , 5 - 8 , 13', '1989 - 1991 , 1993 - 2001 , 2013'], ['zoë wanamaker', 'ariadne oliver', 'crime novelist', '10 - 13', '2006 - 2013'], ['david yelland', 'george', 'butler', '10 - 13', '2006 - 2013']] |
1981 senior pga tour | https://en.wikipedia.org/wiki/1981_Senior_PGA_Tour | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-11622924-1.html.csv | count | don january won 2 events on the 1981 senior pga tour . | {'scope': 'all', 'criterion': 'equal', 'value': 'don january', 'result': '2', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'winner', 'don january'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose winner record fuzzily matches to don january .', 'tostr': 'filter_eq { all_rows ; winner ; don january }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; winner ; don january } }', 'tointer': 'select the rows whose winner record fuzzily matches to don january . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; winner ; don january } } ; 2 } = true', 'tointer': 'select the rows whose winner record fuzzily matches to don january . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; winner ; don january } } ; 2 } = true | select the rows whose winner record fuzzily matches to don january . 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, 'winner_5': 5, 'don january_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', 'winner_5': 'winner', 'don january_6': 'don january', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'winner_5': [0], 'don january_6': [0], '2_7': [2]} | ['date', 'tournament', 'location', 'purse', 'winner', 'score', '1st prize'] | [['apr 5', 'michelob - egypt temple senior classic', 'florida', '125000', 'don january ( 2 )', '280 ( - 8 )', '20000'], ['jun 7', 'eureka federal savings classic', 'california', '150000', 'don january ( 3 )', '208 ( - 5 )', '25000'], ['jun 14', 'peter jackson champions', 'canada', '200000', 'miller barber ( 1 )', '204 ( - 6 )', '30000'], ['jun 28', 'marlboro classic', 'massachusetts', '150000', 'bob goalby ( 1 )', '208 ( - 2 )', '25000'], ['jul 12', 'us senior open', 'michigan', '149000', 'arnold palmer ( 2 )', '289 ( 9 )', '26000'], ['oct 18', 'suntree seniors classic', 'florida', '125000', 'miller barber ( 2 )', '204 ( - 12 )', '20000']] |
arkansas highway 60 | https://en.wikipedia.org/wiki/Arkansas_Highway_60 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18506777-1.html.csv | superlative | the plainview has the most total in the arkansas highway 60 location sections . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '12', '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 }'}, 'location'], 'result': 'plainview', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; total } ; location }'}, 'plainview'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; total } ; location } ; plainview } = true', 'tointer': 'select the row whose total record of all rows is maximum . the location record of this row is plainview .'} | eq { hop { argmax { all_rows ; total } ; location } ; plainview } = true | select the row whose total record of all rows is maximum . the location record of this row is plainview . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'total_5': 5, 'location_6': 6, 'plainview_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', 'location_6': 'location', 'plainview_7': 'plainview'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'total_5': [0], 'location_6': [1], 'plainview_7': [2]} | ['county', 'location', 'distance', 'total', 'notes'] | [['faulkner', 'conway', '0.0', '0.0', 'eastern terminus'], ['faulkner', 'conway', '1.5', '1.5', '1.8 mile spur to office of emergency services'], ['line', 'county line', '5.5', '7.0', 'toad suck ferry lock & dam'], ['perry', 'bigelow', '7.7', '14.7', 'converge with ar 113'], ['perry', 'houston', '3.8', '18.5', 'north end terminus of ar 216'], ['perry', 'houston', '0.1', '18.6', 'diverge with ar 113'], ['perry', 'perryville', '6.5', '25.1', 'converge with ar 9 & ar 10'], ['perry', 'perryville', '0.3', '25.4', 'diverge with ar 9 & ar 10'], ['perry', 'aplin', '10.8', '36.2', 'north end terminus of ar 155'], ['perry', 'fourche junction', '10.1', '46.3', 'cross ar 7'], ['line', 'county line', '1.6', '47.9', 'county line'], ['yell', 'plainview', '7.0', '54.9', 'western terminus']] |
1960 los angeles rams season | https://en.wikipedia.org/wiki/1960_Los_Angeles_Rams_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11171998-1.html.csv | majority | in the 1960 football season , the los angeles rams had an attendance of more than 40,000 fans in most games . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'greater_than', 'value': '40000', 'subset': None} | {'func': 'most_greater', 'args': ['all_rows', 'attendance', '40000'], 'result': True, 'ind': 0, 'tointer': 'for the attendance records of all rows , most of them are greater than 40000 .', 'tostr': 'most_greater { all_rows ; attendance ; 40000 } = true'} | most_greater { all_rows ; attendance ; 40000 } = true | for the attendance records of all rows , most of them are greater than 40000 . | 1 | 1 | {'most_greater_0': 0, 'result_1': 1, 'all_rows_2': 2, 'attendance_3': 3, '40000_4': 4} | {'most_greater_0': 'most_greater', 'result_1': 'true', 'all_rows_2': 'all_rows', 'attendance_3': 'attendance', '40000_4': '40000'} | {'most_greater_0': [1], 'result_1': [], 'all_rows_2': [0], 'attendance_3': [0], '40000_4': [0]} | ['week', 'date', 'opponent', 'result', 'attendance'] | [['1', 'september 23 , 1960', 'st louis cardinals', 'l 43 - 21', '47448'], ['2', 'october 2 , 1960', 'san francisco 49ers', 'l 13 - 9', '53633'], ['3', 'october 9 , 1960', 'chicago bears', 'l 34 - 27', '47776'], ['4', 'october 16 , 1960', 'baltimore colts', 'l 31 - 17', '57808'], ['5', 'october 23 , 1960', 'chicago bears', 't 24 - 24', '63438'], ['6', 'october 30 , 1960', 'detroit lions', 'w 48 - 35', '53295'], ['7', 'november 6 , 1960', 'dallas cowboys', 'w 38 - 13', '16000'], ['8', 'november 13 , 1960', 'detroit lions', 'l 12 - 10', '54019'], ['9', 'november 20 , 1960', 'green bay packers', 'w 33 - 31', '35763'], ['11', 'december 4 , 1960', 'san francisco 49ers', 'l 23 - 7', '77254'], ['12', 'december 11 , 1960', 'baltimore colts', 'w 10 - 3', '75461'], ['13', 'december 17 , 1960', 'green bay packers', 'l 35 - 21', '53445']] |
atlanta falcons draft history | https://en.wikipedia.org/wiki/Atlanta_Falcons_draft_history | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15198842-48.html.csv | superlative | sean renfree recieved the most overall points during the atlanta falcons ' draft pick . | {'scope': 'all', 'col_superlative': '3', 'row_superlative': '8', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '4', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'overall'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; overall }'}, 'name'], 'result': 'sean renfree', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; overall } ; name }'}, 'sean renfree'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; overall } ; name } ; sean renfree } = true', 'tointer': 'select the row whose overall record of all rows is maximum . the name record of this row is sean renfree .'} | eq { hop { argmax { all_rows ; overall } ; name } ; sean renfree } = true | select the row whose overall record of all rows is maximum . the name record of this row is sean renfree . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'overall_5': 5, 'name_6': 6, 'sean renfree_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'overall_5': 'overall', 'name_6': 'name', 'sean renfree_7': 'sean renfree'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'overall_5': [0], 'name_6': [1], 'sean renfree_7': [2]} | ['round', 'pick', 'overall', 'name', 'position', 'college'] | [['1', '22', '22', 'desmond trufant', 'cornerback', 'washington'], ['2', '28', '60', 'robert alford', 'cornerback', 'southeastern louisiana'], ['4', '30', '127', 'malliciah goodman', 'defensive end', 'clemson'], ['4', '36', '133', 'levine toilolo', 'tight end', 'stanford'], ['5', '20', '153', 'stansly maponga', 'defensive end', 'tcu'], ['7', '37', '243', 'kemal ishmael', 'safety', 'central florida'], ['7', '38', '244', 'zeke motta', 'safety', 'notre dame'], ['7', '43', '249', 'sean renfree', 'quarterback', 'duke']] |
roberto traven | https://en.wikipedia.org/wiki/Roberto_Traven | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10819986-2.html.csv | unique | roberto traven 's fight against yukiya naito was the only time a fight resulted in a draw . | {'scope': 'all', 'row': '2', 'col': '4', 'col_other': '1', 'criterion': 'equal', 'value': 'draw', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'method', 'draw'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose method record fuzzily matches to draw .', 'tostr': 'filter_eq { all_rows ; method ; draw }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; method ; draw } }', 'tointer': 'select the rows whose method record fuzzily matches to draw . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'method', 'draw'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose method record fuzzily matches to draw .', 'tostr': 'filter_eq { all_rows ; method ; draw }'}, 'res'], 'result': 'draw', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; method ; draw } ; res }'}, 'draw'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; method ; draw } ; res } ; draw }', 'tointer': 'the res record of this unqiue row is draw .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; method ; draw } } ; eq { hop { filter_eq { all_rows ; method ; draw } ; res } ; draw } } = true', 'tointer': 'select the rows whose method record fuzzily matches to draw . there is only one such row in the table . the res record of this unqiue row is draw .'} | and { only { filter_eq { all_rows ; method ; draw } } ; eq { hop { filter_eq { all_rows ; method ; draw } ; res } ; draw } } = true | select the rows whose method record fuzzily matches to draw . there is only one such row in the table . the res record of this unqiue row is draw . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'method_7': 7, 'draw_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'res_9': 9, 'draw_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'method_7': 'method', 'draw_8': 'draw', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'res_9': 'res', 'draw_10': 'draw'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'method_7': [0], 'draw_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'res_9': [2], 'draw_10': [3]} | ['res', 'record', 'opponent', 'method', 'event', 'round', 'time', 'location'] | [['loss', '6 - 4 - 1', 'john salter', 'ko ( punches )', 'adrenaline mma 3', '1', '2:15', 'birmingham , alabama , united states'], ['draw', '6 - 3 - 1', 'yukiya naito', 'draw', 'warriors realm 3', '3', '5:00', 'brisbane , australia'], ['loss', '6 - 3', 'elvis sinosic', 'ko ( punch )', 'warriors realm 1', '2', '0:35', 'queensland , australia'], ['loss', '6 - 2', 'frank mir', 'submission ( armbar )', 'ufc 34', '1', '1:05', 'las vegas , nevada'], ['win', '6 - 1', 'mikhail borissov', 'decision ( unanimous )', 'rings : king of kings 2000 block a', '2', '5:00', 'tokyo , japan'], ['loss', '5 - 1', 'dave menne', 'decision ( unanimous )', 'rings : king of kings 2000 block a', '3', '5:00', 'tokyo , japan'], ['win', '5 - 0', 'gueorguiev tzvetkov', 'decision ( majority )', 'rings : millennium combine 2', '2', '5:00', 'tokyo , japan'], ['win', '4 - 0', 'maxim tarasov', 'submission ( rear naked choke )', 'absolute fighting championship 2', '1', '2:47', 'moscow , russia'], ['win', '3 - 0', 'leonid efremov', 'submission ( punches )', 'absolute fighting championship 2', '1', '2:54', 'moscow , russia'], ['win', '2 - 0', 'artyom vilgulevsky', 'submission ( rear naked choke )', 'absolute fighting championship 2', '1', '2:28', 'moscow , russia'], ['win', '1 - 0', 'dave berry', 'submission ( strikes )', 'ufc 11', '1', '1:23', 'augusta , georgia , united states']] |
1937 in brazilian football | https://en.wikipedia.org/wiki/1937_in_Brazilian_football | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15352382-1.html.csv | majority | all teams which participated in the 1937 brazilian football season games each had 14 matches . | {'scope': 'all', 'col': '4', 'most_or_all': 'all', 'criterion': 'equal', 'value': '14', 'subset': None} | {'func': 'all_eq', 'args': ['all_rows', 'played', '14'], 'result': True, 'ind': 0, 'tointer': 'for the played records of all rows , all of them are equal to 14 .', 'tostr': 'all_eq { all_rows ; played ; 14 } = true'} | all_eq { all_rows ; played ; 14 } = true | for the played records of all rows , all of them are equal to 14 . | 1 | 1 | {'all_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'played_3': 3, '14_4': 4} | {'all_eq_0': 'all_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'played_3': 'played', '14_4': '14'} | {'all_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'played_3': [0], '14_4': [0]} | ['position', 'team', 'points', 'played', 'drawn', 'lost', 'against', 'difference'] | [['1', 'corinthians', '22', '14', '2', '2', '14', '19'], ['2', 'palestra itã ¡ lia - sp', '21', '14', '1', '3', '12', '23'], ['3', 'portuguesa santista', '19', '14', '3', '3', '18', '9'], ['4', 'estudantes paulista', '15', '14', '1', '6', '22', '11'], ['5', 'santos', '14', '14', '4', '5', '20', '7'], ['6', 'juventus', '11', '14', '3', '7', '28', '- 5']] |
wafj | https://en.wikipedia.org/wiki/WAFJ | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12499438-1.html.csv | majority | the vast majority of the of the wafj stations were class d. | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'd', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'class', 'd'], 'result': True, 'ind': 0, 'tointer': 'for the class records of all rows , most of them fuzzily match to d .', 'tostr': 'most_eq { all_rows ; class ; d } = true'} | most_eq { all_rows ; class ; d } = true | for the class records of all rows , most of them fuzzily match to d . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'class_3': 3, 'd_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'class_3': 'class', 'd_4': 'd'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'class_3': [0], 'd_4': [0]} | ['call sign', 'frequency mhz', 'city of license', 'erp w', 'class', 'fcc info'] | [['wzae', '93.3', 'wadley , georgia', '4000', 'a', 'fcc'], ['w257bg', '99.3', 'statesboro , georgia', '80', 'd', 'fcc'], ['w252bh', '98.3', 'washington , georgia', '27', 'd', 'fcc'], ['w224be', '92.7', 'sylvania , georgia', '27', 'd', 'fcc'], ['w254bn', '98.7', 'sparta , georgia', '55', 'd', 'fcc'], ['w245an', '96.9', 'milledgeville , georgia', '19', 'd', 'fcc']] |
new york film critics circle award for best foreign language film | https://en.wikipedia.org/wiki/New_York_Film_Critics_Circle_Award_for_Best_Foreign_Language_Film | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12788276-5.html.csv | unique | the only film from spain that won an award from the new york film critics for the best foreign award was bad education . | {'scope': 'all', 'row': '5', 'col': '4', 'col_other': '2', 'criterion': 'equal', 'value': 'spain', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'spain'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose country record fuzzily matches to spain .', 'tostr': 'filter_eq { all_rows ; country ; spain }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; country ; spain } }', 'tointer': 'select the rows whose country record fuzzily matches to spain . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'spain'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose country record fuzzily matches to spain .', 'tostr': 'filter_eq { all_rows ; country ; spain }'}, 'english title'], 'result': 'bad education', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; country ; spain } ; english title }'}, 'bad education'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; country ; spain } ; english title } ; bad education }', 'tointer': 'the english title record of this unqiue row is bad education .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; country ; spain } } ; eq { hop { filter_eq { all_rows ; country ; spain } ; english title } ; bad education } } = true', 'tointer': 'select the rows whose country record fuzzily matches to spain . there is only one such row in the table . the english title record of this unqiue row is bad education .'} | and { only { filter_eq { all_rows ; country ; spain } } ; eq { hop { filter_eq { all_rows ; country ; spain } ; english title } ; bad education } } = true | select the rows whose country record fuzzily matches to spain . there is only one such row in the table . the english title record of this unqiue row is bad education . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'country_7': 7, 'spain_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'english title_9': 9, 'bad education_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'country_7': 'country', 'spain_8': 'spain', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'english title_9': 'english title', 'bad education_10': 'bad education'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'country_7': [0], 'spain_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'english title_9': [2], 'bad education_10': [3]} | ['year', 'english title', 'original title', 'country', 'director ( s )'] | [['2000', 'yi yi : a one and a two', 'yi yi', 'japan / taiwan', 'edward yang'], ['2001', 'in the mood for love', 'fa yeung nin wa', 'france / hong kong', 'wong kar - wai'], ['2002', 'and your mother too', 'y tu mamá también', 'mexico', 'alfonso cuarón'], ['2003', 'city of god', 'cidade de deus', 'brazil', 'fernando meirelles'], ['2004', 'bad education', 'la mala educación', 'spain', 'pedro almodóvar'], ['2005', '2046', '2046', 'china / hong kong', 'wong kar - wai'], ['2006', 'army of shadows', "l'armée des ombres", 'france / italy', 'jean - pierre melville'], ['2007', 'the lives of others', 'das leben der anderen', 'germany', 'florian henckel von donnersmarck'], ['2008', '4 months , 3 weeks and 2 days', '4 luni , 3 săptămni şi 2 zile', 'romania', 'cristian mungiu'], ['2009', 'summer hours', "l'heure de été", 'france', 'olivier assayas']] |
north central conference ( ihsaa ) | https://en.wikipedia.org/wiki/North_Central_Conference_%28IHSAA%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18871102-1.html.csv | majority | the majority of schools in the north central conference were previously in the independents conference . | {'scope': 'all', 'col': '8', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'independents', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'previous conference', 'independents'], 'result': True, 'ind': 0, 'tointer': 'for the previous conference records of all rows , most of them fuzzily match to independents .', 'tostr': 'most_eq { all_rows ; previous conference ; independents } = true'} | most_eq { all_rows ; previous conference ; independents } = true | for the previous conference records of all rows , most of them fuzzily match to independents . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'previous conference_3': 3, 'independents_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'previous conference_3': 'previous conference', 'independents_4': 'independents'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'previous conference_3': [0], 'independents_4': [0]} | ['school', 'location', 'mascot', 'county', 'enrollment', 'ihsaa class / football / soccer', 'year joined', 'previous conference'] | [['anderson', 'anderson', 'indians', '48 madison', '1884', '4a / 5a / 2a', '1926', 'independents'], ['huntington north', 'huntington', 'vikings', '35 huntington', '1750', '4a / 5a / 2a', '2003', 'olympic'], ['kokomo', 'kokomo', 'wildkats', '34 howard', '1879', '4a / 5a / 2a', '1926', 'independents'], ['logansport community', 'logansport', 'berries', '09 cass', '1245', '4a / 4a / 2a', '1926', 'independents'], ['marion', 'marion', 'giants', '27 grant', '1159', '4a / 4a / 2a', '1933', 'independents'], ['muncie central', 'muncie', 'bearcats', '18 delaware', '915', '3a / 4a / 2a', '1926', 'independents'], ['new castle chrysler', 'new castle', 'trojans', '33 henry', '1108', '4a / 4a / 2a', '1926', 'independents'], ['richmond', 'richmond', 'red devils', '89 wayne', '1516', '4a / 5a / 2a', '1926', 'independents']] |
united states district court for the western district of washington | https://en.wikipedia.org/wiki/United_States_District_Court_for_the_Western_District_of_Washington | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1137899-2.html.csv | majority | most of the judges reason for termination from office was death . | {'scope': 'all', 'col': '8', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'death', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'reason for termination', 'death'], 'result': True, 'ind': 0, 'tointer': 'for the reason for termination records of all rows , most of them fuzzily match to death .', 'tostr': 'most_eq { all_rows ; reason for termination ; death } = true'} | most_eq { all_rows ; reason for termination ; death } = true | for the reason for termination records of all rows , most of them fuzzily match to death . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'reason for termination_3': 3, 'death_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'reason for termination_3': 'reason for termination', 'death_4': 'death'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'reason for termination_3': [0], 'death_4': [0]} | ['judge', 'state', 'born / died', 'active service', 'chief judge', 'senior status', 'appointed by', 'reason for termination'] | [['cornelius holgate hanford', 'wa', '1849 - 1926', '1890 - 1912', '-', '-', 'harrison', 'resignation'], ['george donworth', 'wa', '1861 - 1947', '1909 - 1912', '-', '-', 'taft', 'resignation'], ['edward e cushman', 'wa', '1865 - 1944', '1912 - 1939', '-', '1939 - 1944', 'taft', 'death'], ['clinton woodbury howard', 'wa', '1864 - 1937', '1912 - 1913', '-', '-', 'taft', 'not confirmed'], ['jeremiah neterer', 'wa', '1862 - 1943', '1913 - 1933', '-', '1933 - 1943', 'wilson', 'death'], ['john clyde bowen', 'wa', '1888 - 1978', '1934 - 1961', '-', '1961 - 1978', 'f roosevelt', 'death'], ['lloyd llewellyn black', 'wa', '1889 - 1950', '1939 - 1950', '-', '-', 'f roosevelt', 'death'], ['charles henry leavy', 'wa', '1884 - 1952', '1942 - 1952', '-', '1952 - 1952', 'f roosevelt', 'death'], ['william james lindberg', 'wa', '1904 - 1981', '1951 - 1971', '-', '1971 - 1981', 'truman', 'death'], ['george hugo boldt', 'wa', '1903 - 1984', '1953 - 1971', '-', '1971 - 1984', 'eisenhower', 'death'], ['william trulock beeks', 'wa', '1906 - 1988', '1961 - 1973', '-', '1973 - 1988', 'kennedy', 'death'], ['william nelson goodwin', 'wa', '1909 - 1975', '1966 - 1975', '-', '-', 'johnson', 'death'], ['morell edward sharp', 'wa', '1920 - 1980', '1971 - 1980', '-', '-', 'nixon', 'death'], ['donald s voorhees', 'wa', '1916 - 1989', '1974 - 1986', '-', '1986 - 1989', 'nixon', 'death'], ['jack edward tanner', 'wa', '1919 - 2006', '1978 - 1991', '-', '1991 - 2006', 'carter', 'death'], ['william lee dwyer', 'wa', '1929 - 2002', '1987 - 1998', '-', '1998 - 2002', 'reagan', 'death'], ['franklin d burgess', 'wa', '1935 - 2010', '1994 - 2005', '-', '2005 - 2010', 'clinton', 'death']] |
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