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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 netw...
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 matche...
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 ...
{'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...
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'...
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 ...
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'...
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...
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':...
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...
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 } ...
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 fo...
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...
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', 'champion...
{'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', ...
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 { fi...
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'], [...
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': '...
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', '...
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 ...
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'], ['t...
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...
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', 'h...
{'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 -...
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', 't...
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...
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 -...
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':...
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', 'janu...
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'], ['le6...
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 }'}, 'phili...
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 ...
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 ...
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', '1...
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'...
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 , ...
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 } }', 'toin...
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'...
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 ( anj...
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 ( ...
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 %'],...
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 ; re...
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': 'n...
{'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', 'democrati...
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', ...
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', 'formul...
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 mat...
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'...
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', ...
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 { filt...
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...
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, 'in...
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_1...
{'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', 'detro...
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', ...
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', 'm...
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 o...
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...
{'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 , ...
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
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 - ...
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 j...
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 {...
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 }'}, 'avera...
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'...
{'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 ...
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_...
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'],...
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':...
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': 'se...
{'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...
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 ...
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...
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 g...
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': ...
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_...
{'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',...
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'], 'r...
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', 'l...
{'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', '1...
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 { fi...
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', '19...
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 seati...
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'], ['quadric...
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 }...
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', 'j...
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_e...
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 , migue...
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']...
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...
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':...
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 receive...
{'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 new...
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_row...
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', '...
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': '26,6...
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', 'arrowh...
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 surt...
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'],...
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'],...
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 %'...
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': 'av...
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', '...
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 ; athlet...
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...
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': Tr...
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...
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 ...
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', 'iry...
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 point...
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'], ['199...
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...
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'...
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 .'}, 'atten...
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...
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 seri...
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 formu...
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', 'mineswe...
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, 'tos...
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', '19...
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', ...
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...
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 { al...
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 ( ...
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 { filt...
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....
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...
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', '...
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 }'},...
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', '...
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': ...
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 str...
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 } ; gr...
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...
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 { al...
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...
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': '...
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 ...
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', 'toi...
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',...
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 ) ; ...
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'], ['...
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'], 'resu...
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 )', '8.76...
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 ...
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, 'i...
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', ...
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'...
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'],...
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'], ['fo...
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'...
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',...
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 }'}, ...
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': 'nat...
{'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'...
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 fo...
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', 'novembe...
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':...
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...
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 }'}...
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...
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',...
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 }'}], ...
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', 'm...
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, 'to...
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', '197...
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'], 're...
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',...
{'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', 'un...
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'...
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': 'coun...
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', ...
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, 't...
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 ...
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, ...
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 e...
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 bea...
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':...
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', 'defens...
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 { filte...
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', 'q...
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', ...
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', ...
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 {...
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 mei...
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 commu...
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', 'w...