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list of the league episodes | https://en.wikipedia.org/wiki/List_of_The_League_episodes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-28348757-3.html.csv | majority | the majority of episodes had a numbers rating of at least one million total households . | {'scope': 'all', 'col': '8', 'most_or_all': 'most', 'criterion': 'greater_than_eq', 'value': '1.0', 'subset': None} | {'func': 'most_greater_eq', 'args': ['all_rows', 'us viewers ( million )', '1.0'], 'result': True, 'ind': 0, 'tointer': 'for the us viewers ( million ) records of all rows , most of them are greater than or equal to 1.0 .', 'tostr': 'most_greater_eq { all_rows ; us viewers ( million ) ; 1.0 } = true'} | most_greater_eq { all_rows ; us viewers ( million ) ; 1.0 } = true | for the us viewers ( million ) records of all rows , most of them are greater than or equal to 1.0 . | 1 | 1 | {'most_greater_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'us viewers (million)_3': 3, '1.0_4': 4} | {'most_greater_eq_0': 'most_greater_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'us viewers (million)_3': 'us viewers ( million )', '1.0_4': '1.0'} | {'most_greater_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'us viewers (million)_3': [0], '1.0_4': [0]} | ['no', '-', 'title', 'directed by', 'written by', 'original air date', 'production code', 'us viewers ( million )'] | [['7', '1', 'vegas draft', 'jeff schaffer', 'jeff schaffer & jackie marcus schaffer', 'september 16 , 2010', 'xle02001', '1.71'], ['8', '2', 'bro - lo el cuã ± ado', 'jeff schaffer', 'jeff schaffer & jackie marcus schaffer', 'september 23 , 2010', 'xle02002', '1.05'], ['9', '3', 'the white knuckler', 'jeff schaffer', 'jeff schaffer & jackie marcus schaffer', 'september 30 , 2010', 'xle02003', '0.89'], ['10', '4', 'the kluneberg', 'jeff schaffer', 'jeff schaffer & jackie marcus schaffer', 'october 7 , 2010', 'xle02004', '0.82'], ['11', '5', 'the marathon', 'jackie marcus schaffer', 'craig digregorio', 'october 14 , 2010', 'xle02005', '0.86'], ['12', '6', 'the anniversary party', 'jeff schaffer', 'nick kroll & paul scheer', 'october 21 , 2010', 'xle02006', '0.62'], ['13', '7', 'ghost monkey', 'jeff schaffer', 'jeff schaffer & jackie marcus schaffer', 'october 28 , 2010', 'xle02007', '0.67'], ['14', '8', 'the tie', 'jackie marcus schaffer', "dan o'keefe", 'november 4 , 2010', 'xle02008', '1.01'], ['15', '9', 'the expert witness', 'jeff schaffer', 'nick kroll & paul scheer', 'november 11 , 2010', 'xle02009', '1.00'], ['16', '10', 'high school reunion', 'jeff schaffer', 'jeff schaffer & jackie marcus schaffer', 'november 18 , 2010', 'xle02010', '1.04'], ['18', '12', 'kegel the elf', 'jeff schaffer', 'jeff schaffer & jackie marcus schaffer', 'december 9 , 2010', 'xle02012', '1.05']] |
1997 cfl draft | https://en.wikipedia.org/wiki/1997_CFL_Draft | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-28059992-1.html.csv | unique | in the 1997 cfl draft , the only player picked from north dakota was tim prinsen . | {'scope': 'all', 'row': '4', 'col': '5', 'col_other': '3', 'criterion': 'equal', 'value': 'north dakota', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'college', 'north dakota'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose college record fuzzily matches to north dakota .', 'tostr': 'filter_eq { all_rows ; college ; north dakota }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; college ; north dakota } }', 'tointer': 'select the rows whose college record fuzzily matches to north dakota . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'college', 'north dakota'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose college record fuzzily matches to north dakota .', 'tostr': 'filter_eq { all_rows ; college ; north dakota }'}, 'player'], 'result': 'tim prinsen', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; college ; north dakota } ; player }'}, 'tim prinsen'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; college ; north dakota } ; player } ; tim prinsen }', 'tointer': 'the player record of this unqiue row is tim prinsen .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; college ; north dakota } } ; eq { hop { filter_eq { all_rows ; college ; north dakota } ; player } ; tim prinsen } } = true', 'tointer': 'select the rows whose college record fuzzily matches to north dakota . there is only one such row in the table . the player record of this unqiue row is tim prinsen .'} | and { only { filter_eq { all_rows ; college ; north dakota } } ; eq { hop { filter_eq { all_rows ; college ; north dakota } ; player } ; tim prinsen } } = true | select the rows whose college record fuzzily matches to north dakota . there is only one such row in the table . the player record of this unqiue row is tim prinsen . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'college_7': 7, 'north dakota_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'player_9': 9, 'tim prinsen_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'college_7': 'college', 'north dakota_8': 'north dakota', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'player_9': 'player', 'tim prinsen_10': 'tim prinsen'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'college_7': [0], 'north dakota_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'player_9': [2], 'tim prinsen_10': [3]} | ['pick', 'cfl team', 'player', 'position', 'college'] | [['1', 'toronto argonauts', 'chad folk', 'ol', 'utah'], ['2', 'saskatchewan roughriders', 'ben fairbrother', 'ol', 'calgary'], ['3', 'edmonton eskimos', 'ian franklin', 'cb', 'weber state'], ['4', 'hamilton tiger - cats', 'tim prinsen', 'og', 'north dakota'], ['5', 'calgary stampeders', 'doug brown', 'dl', 'simon fraser'], ['6', 'montreal alouettes', 'steve charbonneau', 'dl', 'new hampshire'], ['7', 'calgary', 'jason clemett', 'lb', 'simon fraser'], ['8', 'edmonton', 'mark farraway', 'dl', 'st francis xavier']] |
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 | superlative | toni teittinenis the newest winner of the danish grand prix . | {'scope': 'all', 'col_superlative': '1', 'row_superlative': '13', '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', 'year'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; year }'}, 'driver'], 'result': 'toni teittinen', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; year } ; driver }'}, 'toni teittinen'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; year } ; driver } ; toni teittinen } = true', 'tointer': 'select the row whose year record of all rows is maximum . the driver record of this row is toni teittinen .'} | eq { hop { argmax { all_rows ; year } ; driver } ; toni teittinen } = true | select the row whose year record of all rows is maximum . the driver record of this row is toni teittinen . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'year_5': 5, 'driver_6': 6, 'toni teittinen_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'year_5': 'year', 'driver_6': 'driver', 'toni teittinen_7': 'toni teittinen'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'year_5': [0], 'driver_6': [1], 'toni teittinen_7': [2]} | ['year', 'driver', 'constructor', 'location', 'formula', 'report'] | [['1960', 'jack brabham', 'cooper - climax', 'roskilde ring', 'formula 2', 'report'], ['1961', 'stirling moss', 'lotus - climax', 'roskilde ring', 'formula 1', 'report'], ['1962', 'jack brabham', 'lotus - climax', 'roskilde ring', 'formula 1', 'report'], ['1963', 'peter revson', 'cooper - bmc', 'roskilde ring', 'formula junior', 'report'], ['1964', 'hartvig conradsen', 'cooper - bmc', 'roskilde ring', 'formula junior', 'report'], ['1965', 'kurt ahrens jr', 'brabham - ford', 'roskilde ring', 'formula 3', 'report'], ['1968', 'ingvar pettersson', 'tecno - ford', 'roskilde ring', 'formula 3', 'report'], ['1973', 'randy lewis', 'brabham - ford', 'roskilde ring', 'formula 3', 'report'], ['1974', 'jac nelleman', 'grd - ford', 'jyllandsringen', 'formula 3', 'report'], ['1975', 'jac nelleman', 'grd - ford', 'jyllandsringen', 'formula 3', 'report'], ['1976', 'jac nelleman', 'van diemen - toyota', 'jyllandsringen', 'formula 3', 'report'], ['1977', 'jac nelleman', 'chevron - toyota', 'jyllandsringen', 'formula 3', 'report'], ['1995', 'toni teittinen', 'reynard - mugen - honda', 'jyllandsringen', 'formula 3', 'report']] |
branimir subašić | https://en.wikipedia.org/wiki/Branimir_Suba%C5%A1i%C4%87 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11978803-1.html.csv | unique | branimir subašić only played in one competition that was n't a friendly one . | {'scope': 'all', 'row': '2', 'col': '5', 'col_other': 'n/a', 'criterion': 'not_equal', 'value': 'friendly', 'subset': None} | {'func': 'only', 'args': [{'func': 'filter_str_not_eq', 'args': ['all_rows', 'competition', 'friendly'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose competition record does not match to friendly .', 'tostr': 'filter_not_eq { all_rows ; competition ; friendly }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_not_eq { all_rows ; competition ; friendly } } = true', 'tointer': 'select the rows whose competition record does not match to friendly . there is only one such row in the table .'} | only { filter_not_eq { all_rows ; competition ; friendly } } = true | select the rows whose competition record does not match to friendly . there is only one such row in the table . | 2 | 2 | {'only_1': 1, 'result_2': 2, 'filter_str_not_eq_0': 0, 'all_rows_3': 3, 'competition_4': 4, 'friendly_5': 5} | {'only_1': 'only', 'result_2': 'true', 'filter_str_not_eq_0': 'filter_str_not_eq', 'all_rows_3': 'all_rows', 'competition_4': 'competition', 'friendly_5': 'friendly'} | {'only_1': [2], 'result_2': [], 'filter_str_not_eq_0': [1], 'all_rows_3': [0], 'competition_4': [0], 'friendly_5': [0]} | ['date', 'venue', 'score', 'result', 'competition'] | [['march 7 , 2007', 'shymkent , kazakhstan', '0 - 1', 'win', 'friendly'], ['june 2 , 2007', 'baku , azerbaijan', '1 - 3', 'lost', 'uefa euro 2008 qualifying'], ['august 22 , 2007', 'dushanbe , tajikistan', '2 - 3', 'win', 'friendly'], ['september 12 , 2007', 'baku , azerbaijan', '1 - 1', 'draw', 'friendly'], ['june 4 , 2008', 'andorra la vella , andorra', '1 - 2', 'win', 'friendly'], ['november 19 , 2008', 'baku , azerbaijan', '1 - 1', 'draw', 'friendly'], ['august 15 , 2012', 'baku , azerbaijan', '3 - 0', 'win', 'friendly']] |
united states presidential election in nevada , 2008 | https://en.wikipedia.org/wiki/United_States_presidential_election_in_Nevada%2C_2008 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-20424014-1.html.csv | superlative | eureka had the highest percentage of voters who choose mccain instead of obama . | {'scope': 'all', 'col_superlative': '3', 'row_superlative': '7', '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', 'mccain %'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; mccain % }'}, 'county'], 'result': 'eureka', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; mccain % } ; county }'}, 'eureka'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; mccain % } ; county } ; eureka } = true', 'tointer': 'select the row whose mccain % record of all rows is maximum . the county record of this row is eureka .'} | eq { hop { argmax { all_rows ; mccain % } ; county } ; eureka } = true | select the row whose mccain % record of all rows is maximum . the county record of this row is eureka . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'mccain %_5': 5, 'county_6': 6, 'eureka_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'mccain %_5': 'mccain %', 'county_6': 'county', 'eureka_7': 'eureka'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'mccain %_5': [0], 'county_6': [1], 'eureka_7': [2]} | ['county', 'mccain', 'mccain %', 'obama', 'obama %'] | [['carson city', '11419', '48.2 %', '11623', '49.1 %'], ['churchill', '6832', '64.4 %', '3494', '33.0 %'], ['clark', '257078', '39.5 %', '380765', '58.5 %'], ['douglas', '14648', '56.6 %', '10672', '41.2 %'], ['elko', '10969', '68.5 %', '4541', '28.4 %'], ['esmeralda', '303', '69.0 %', '104', '23.7 %'], ['eureka', '564', '75.7 %', '144', '19.3 %'], ['humboldt', '3586', '63.3 %', '1909', '33.7 %'], ['lander', '1466', '69.7 %', '577', '27.5 %'], ['lincoln', '1498', '71.1 %', '518', '24.6 %'], ['lyon', '12154', '57.6 %', '8405', '39.8 %'], ['mineral', '1131', '49.0 %', '1082', '46.9 %'], ['nye', '9537', '54.5 %', '7226', '41.3 %'], ['pershing', '1075', '58.6 %', '673', '36.7 %'], ['storey', '1247', '51.6 %', '1102', '45.6 %'], ['washoe', '76880', '42.6 %', '99671', '55.3 %']] |
michel rougerie | https://en.wikipedia.org/wiki/Michel_Rougerie | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14889717-2.html.csv | majority | most of the teams in the grand prix races have 0 wins . | {'scope': 'all', 'col': '6', 'most_or_all': 'most', 'criterion': 'equal', 'value': '0', 'subset': None} | {'func': 'most_eq', 'args': ['all_rows', 'wins', '0'], 'result': True, 'ind': 0, 'tointer': 'for the wins records of all rows , most of them are equal to 0 .', 'tostr': 'most_eq { all_rows ; wins ; 0 } = true'} | most_eq { all_rows ; wins ; 0 } = true | for the wins records of all rows , most of them are equal to 0 . | 1 | 1 | {'most_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'wins_3': 3, '0_4': 4} | {'most_eq_0': 'most_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'wins_3': 'wins', '0_4': '0'} | {'most_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'wins_3': [0], '0_4': [0]} | ['year', 'class', 'team', 'points', 'rank', 'wins'] | [['1972', '125cc', 'aermacchi', '2', '38th', '0'], ['1972', '350cc', 'aermacchi', '3', '30th', '0'], ['1973', '250cc', 'harley davidson', '45', '5th', '0'], ['1973', '350cc', 'harley davidson', '4', '34th', '0'], ['1973', '500cc', 'harley davidson', '6', '28th', '0'], ['1974', '250cc', 'harley davidson', '21', '9th', '0'], ['1974', '350cc', 'harley davidson', '25', '7th', '0'], ['1974', '500cc', 'harley davidson', '14', '16th', '0'], ['1975', '250cc', 'harley davidson', '76', '2nd', '2'], ['1975', '500cc', 'harley davidson', '4', '28th', '0'], ['1976', '500cc', 'suzuki', '16', '14th', '0'], ['1977', '250cc', 'yamaha', '5', '27th', '0'], ['1977', '350cc', 'yamaha', '50', '4th', '1'], ['1977', '500cc', 'suzuki', '21', '13th', '0'], ['1978', '350cc', 'yamaha', '47', '6th', '0'], ['1978', '500cc', 'suzuki', '23', '10th', '0'], ['1979', '350cc', 'yamaha', '10', '17th', '0'], ['1979', '500cc', 'suzuki', '16', '15th', '0'], ['1980', '500cc', 'suzuki', '4', '17th', '0'], ['1981', '350cc', 'yamaha', '1', '32nd', '0']] |
portland timbers ( 2001 - 10 ) | https://en.wikipedia.org/wiki/Portland_Timbers_%282001%E2%80%9310%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-14240688-1.html.csv | superlative | the portland timbers ' highest audience attendance was during the 2009 season . | {'scope': 'all', 'col_superlative': '7', 'row_superlative': '9', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'avg attendance'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; avg attendance }'}, 'year'], 'result': '2009', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; avg attendance } ; year }'}, '2009'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; avg attendance } ; year } ; 2009 } = true', 'tointer': 'select the row whose avg attendance record of all rows is maximum . the year record of this row is 2009 .'} | eq { hop { argmax { all_rows ; avg attendance } ; year } ; 2009 } = true | select the row whose avg attendance record of all rows is maximum . the year record of this row is 2009 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'num_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'avg attendance_5': 5, 'year_6': 6, '2009_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'num_hop_1': 'num_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'avg attendance_5': 'avg attendance', 'year_6': 'year', '2009_7': '2009'} | {'eq_2': [3], 'result_3': [], 'num_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'avg attendance_5': [0], 'year_6': [1], '2009_7': [2]} | ['year', 'division', 'league', 'regular season', 'playoffs', 'open cup', 'avg attendance'] | [['2001', '2', 'usl a - league', '4th , western', 'quarterfinals', 'did not qualify', '7169'], ['2002', '2', 'usl a - league', '2nd , pacific', '1st round', 'did not qualify', '6260'], ['2003', '2', 'usl a - league', '3rd , pacific', 'did not qualify', 'did not qualify', '5871'], ['2004', '2', 'usl a - league', '1st , western', 'quarterfinals', '4th round', '5628'], ['2005', '2', 'usl first division', '5th', 'quarterfinals', '4th round', '6028'], ['2006', '2', 'usl first division', '11th', 'did not qualify', '3rd round', '5575'], ['2007', '2', 'usl first division', '2nd', 'semifinals', '2nd round', '6851'], ['2008', '2', 'usl first division', '11th', 'did not qualify', '1st round', '8567'], ['2009', '2', 'usl first division', '1st', 'semifinals', '3rd round', '9734']] |
the rob brydon show | https://en.wikipedia.org/wiki/The_Rob_Brydon_Show | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-29135051-3.html.csv | majority | most of the rob brydon show episodes were transmitted in the month of august . | {'scope': 'all', 'col': '2', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'august', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'broadcast date', 'august'], 'result': True, 'ind': 0, 'tointer': 'for the broadcast date records of all rows , most of them fuzzily match to august .', 'tostr': 'most_eq { all_rows ; broadcast date ; august } = true'} | most_eq { all_rows ; broadcast date ; august } = true | for the broadcast date records of all rows , most of them fuzzily match to august . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'broadcast date_3': 3, 'august_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'broadcast date_3': 'broadcast date', 'august_4': 'august'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'broadcast date_3': [0], 'august_4': [0]} | ['episode', 'broadcast date', 'guest ( s )', 'singer ( s )', 'ratings'] | [['1', '14 august 2012', 'michael mcintyre and alex james', 'amy macdonald', '1.44 m'], ['2', '21 august 2012', 'barbara windsor and heston blumenthal', 'the overtones', 'under 1.39 m'], ['3', '28 august 2012', 'sarah millican and grayson perry', 'newton faulkner', 'under 1.39 m'], ['4', '4 september 2012', 'jason manford and neil morrissey', 'ronan keating', 'under 1.25 m'], ['5', '11 september 2012', 'emilia fox and steve backshall', 'tom jones', 'under 1.37 m']] |
australian cricket team in 2007 - 08 | https://en.wikipedia.org/wiki/Australian_cricket_team_in_2007%E2%80%9308 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13136868-11.html.csv | superlative | for the australian cricket team in 2007-08 , the player with the highest number of wkts was brett lee . | {'scope': 'all', 'col_superlative': '2', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'wkts'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; wkts }'}, 'player'], 'result': 'brett lee', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; wkts } ; player }'}, 'brett lee'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; wkts } ; player } ; brett lee } = true', 'tointer': 'select the row whose wkts record of all rows is maximum . the player record of this row is brett lee .'} | eq { hop { argmax { all_rows ; wkts } ; player } ; brett lee } = true | select the row whose wkts record of all rows is maximum . the player record of this row is brett lee . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'wkts_5': 5, 'player_6': 6, 'brett lee_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'wkts_5': 'wkts', 'player_6': 'player', 'brett lee_7': 'brett lee'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'wkts_5': [0], 'player_6': [1], 'brett lee_7': [2]} | ['player', 'wkts', 'runs', 'econ', 'ovrs'] | [['brett lee', '29', '703', '4.90', '143.2'], ['nathan bracken', '26', '629', '4.47', '140.3'], ['mitchell johnson', '25', '571', '4.26', '134.0'], ['brad hogg', '23', '583', '4.66', '125.0'], ['james hopes', '17', '450', '3.88', '115.5'], ['stuart clark', '9', '212', '3.95', '53.4'], ['michael clarke', '6', '204', '5.10', '40.0'], ['shaun tait', '5', '89', '4.95', '18.0'], ['ashley noffke', '1', '46', '5.11', '9.0'], ['andrew symonds', '1', '137', '5.30', '25.5'], ['brad hodge', '0', '18', '9.00', '2.0']] |
memphis grizzlies all - time roster | https://en.wikipedia.org/wiki/Memphis_Grizzlies_all-time_roster | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-16494599-3.html.csv | majority | most of the members on the memphis grizzlies all time roster are from the united states . | {'scope': 'all', 'col': '3', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'united states', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'nationality', 'united states'], 'result': True, 'ind': 0, 'tointer': 'for the nationality records of all rows , all of them fuzzily match to united states .', 'tostr': 'all_eq { all_rows ; nationality ; united states } = true'} | all_eq { all_rows ; nationality ; united states } = true | for the nationality records of all rows , all of them fuzzily match to united states . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'nationality_3': 3, 'united states_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'nationality_3': 'nationality', 'united states_4': 'united states'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'nationality_3': [0], 'united states_4': [0]} | ['player', 'no', 'nationality', 'position', 'years for grizzlies', 'school / club team'] | [['brian cardinal', '35', 'united states', 'forward', '2004 - 2008', 'purdue'], ['rodney carney', '10', 'united states', 'forward', '2011', 'memphis'], ['antoine carr', '55', 'united states', 'forward / center', '1999 - 2000', 'wichita state'], ['demarre carroll', '1', 'united states', 'forward', '2009 - 2012', 'missouri'], ['pete chilcutt', '32', 'united states', 'power forward', '1996 - 1999', 'north carolina'], ['jason collins', '34', 'united states', 'center', '2008', 'stanford'], ['mike conley , jr', '11', 'united states', 'point guard', '2007present', 'ohio state'], ['will conroy', '5', 'united states', 'guard', '2007', 'washington'], ['javaris crittenton', '3', 'united states', 'point guard', '2008', 'georgia tech']] |
1972 isle of man tt | https://en.wikipedia.org/wiki/1972_Isle_of_Man_TT | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15753390-3.html.csv | majority | the majority of riders from the united kingdom at he 1972 isle of man tt scored less than 10 points . | {'scope': 'subset', 'col': '7', 'most_or_all': 'most', 'criterion': 'less_than', 'value': '10', 'subset': {'col': '3', 'criterion': 'equal', 'value': 'united kingdom'}} | {'func': 'most_less', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'united kingdom'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; country ; united kingdom }', 'tointer': 'select the rows whose country record fuzzily matches to united kingdom .'}, 'points', '10'], 'result': True, 'ind': 1, 'tointer': 'select the rows whose country record fuzzily matches to united kingdom . for the points records of these rows , most of them are less than 10 .', 'tostr': 'most_less { filter_eq { all_rows ; country ; united kingdom } ; points ; 10 } = true'} | most_less { filter_eq { all_rows ; country ; united kingdom } ; points ; 10 } = true | select the rows whose country record fuzzily matches to united kingdom . for the points records of these rows , most of them are less than 10 . | 2 | 2 | {'most_less_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, 'country_4': 4, 'united kingdom_5': 5, 'points_6': 6, '10_7': 7} | {'most_less_1': 'most_less', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'country_4': 'country', 'united kingdom_5': 'united kingdom', 'points_6': 'points', '10_7': '10'} | {'most_less_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'country_4': [0], 'united kingdom_5': [0], 'points_6': [1], '10_7': [1]} | ['place', 'rider', 'country', 'machine', 'speed', 'time', 'points'] | [['1', 'phil read', 'united kingdom', 'yamaha', '99.68 mph', '1:30.51.2', '15'], ['2', 'rod gould', 'united kingdom', 'yamaha', '98.09 mph', '1:32.19.6', '12'], ['3', 'john williams', 'united kingdom', 'yamaha', '97.09 mph', '1:33.16.4', '10'], ['4', 'charlie williams', 'united kingdom', 'yamaha', '95.98 mph', '1:34.24.1', '8'], ['5', 'werner pfirter', 'switzerland', 'yamaha', '95.93 mph', '1:34.24.2', '6'], ['6', 'bill henderson', 'united kingdom', 'yamaha', '95.26 mph', '1:35.04.4', '5'], ['7', 'derek chatterton', 'united kingdom', 'yamaha', '95.13 mph', '1:35.12.20', '4'], ['8', 'dudley probinson', 'united kingdom', 'yamaha', '94.88 mph', '1:35.27.4', '3'], ['9', 'barry randle', 'united kingdom', 'yamaha', '94.84 mph', '1:35.29.8', '2'], ['10', 'brae', 'united kingdom', 'yamaha', '92.86 mph', '1:37.31.8', '1']] |
rear enz | https://en.wikipedia.org/wiki/Rear_Enz | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11221498-1.html.csv | unique | there was only one recording that took place in 1980 . | {'scope': 'all', 'row': '7', 'col': '4', 'col_other': 'n/a', 'criterion': 'fuzzily_match', 'value': '1980', 'subset': None} | {'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'recorded', '1980'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose recorded record fuzzily matches to 1980 .', 'tostr': 'filter_eq { all_rows ; recorded ; 1980 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; recorded ; 1980 } } = true', 'tointer': 'select the rows whose recorded record fuzzily matches to 1980 . there is only one such row in the table .'} | only { filter_eq { all_rows ; recorded ; 1980 } } = true | select the rows whose recorded record fuzzily matches to 1980 . 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, 'recorded_4': 4, '1980_5': 5} | {'only_1': 'only', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'recorded_4': 'recorded', '1980_5': '1980'} | {'only_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'recorded_4': [0], '1980_5': [0]} | ['track', 'title', 'author ( s )', 'recorded', 'length'] | [['1', 'firedrill', 'tim finn , neil finn , eddie rayner', 'may 1982', '3:55'], ['2', 'your inspiration', 'n finn', 'april 1984', '3:49'], ['3', 'parasite', 't finn', 'october 1983', '3:37'], ['4', 'next exit', 't finn', 'march 1983', '3:40'], ['5', 'over drive', 'rayner', 'september 1984', '3:43'], ['6', 'serge', 'n finn', 'aav studios , 1984', '3:35'], ['7', 'in the wars', 't finn', 'november 1980', '3:06'], ['8', 'love & success', 'n finn', 'april 1984', '3:04'], ['9', 'big heart', 't finn', 'april 1984', '3:42'], ['10', 'mr catalyst', 'rayner , t finn', 'april 1984', '3:38'], ['11', 'remember when', 't finn', 'march 1983', '3:15']] |
lella lombardi | https://en.wikipedia.org/wiki/Lella_Lombardi | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1235922-1.html.csv | unique | the only time the williams fw04 chassis was used was in 1975 by frank williams racing cars . | {'scope': 'all', 'row': '4', 'col': '3', 'col_other': '1,2', 'criterion': 'equal', 'value': 'williams fw04', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'chassis', 'williams fw04'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose chassis record fuzzily matches to williams fw04 .', 'tostr': 'filter_eq { all_rows ; chassis ; williams fw04 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; chassis ; williams fw04 } }', 'tointer': 'select the rows whose chassis record fuzzily matches to williams fw04 . there is only one such row in the table .'}, {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'chassis', 'williams fw04'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose chassis record fuzzily matches to williams fw04 .', 'tostr': 'filter_eq { all_rows ; chassis ; williams fw04 }'}, 'year'], 'result': '1975', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; chassis ; williams fw04 } ; year }'}, '1975'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; chassis ; williams fw04 } ; year } ; 1975 }', 'tointer': 'the year record of this unqiue row is 1975 .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'chassis', 'williams fw04'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose chassis record fuzzily matches to williams fw04 .', 'tostr': 'filter_eq { all_rows ; chassis ; williams fw04 }'}, 'entrant'], 'result': 'frank williams racing cars', 'ind': 4, 'tostr': 'hop { filter_eq { all_rows ; chassis ; williams fw04 } ; entrant }'}, 'frank williams racing cars'], 'result': True, 'ind': 5, 'tostr': 'eq { hop { filter_eq { all_rows ; chassis ; williams fw04 } ; entrant } ; frank williams racing cars }', 'tointer': 'the entrant record of this unqiue row is frank williams racing cars .'}], 'result': True, 'ind': 6, 'tostr': 'and { eq { hop { filter_eq { all_rows ; chassis ; williams fw04 } ; year } ; 1975 } ; eq { hop { filter_eq { all_rows ; chassis ; williams fw04 } ; entrant } ; frank williams racing cars } }', 'tointer': 'the year record of this unqiue row is 1975 . the entrant record of this unqiue row is frank williams racing cars .'}], 'result': True, 'ind': 7, 'tostr': 'and { only { filter_eq { all_rows ; chassis ; williams fw04 } } ; and { eq { hop { filter_eq { all_rows ; chassis ; williams fw04 } ; year } ; 1975 } ; eq { hop { filter_eq { all_rows ; chassis ; williams fw04 } ; entrant } ; frank williams racing cars } } } = true', 'tointer': 'select the rows whose chassis record fuzzily matches to williams fw04 . there is only one such row in the table . the year record of this unqiue row is 1975 . the entrant record of this unqiue row is frank williams racing cars .'} | and { only { filter_eq { all_rows ; chassis ; williams fw04 } } ; and { eq { hop { filter_eq { all_rows ; chassis ; williams fw04 } ; year } ; 1975 } ; eq { hop { filter_eq { all_rows ; chassis ; williams fw04 } ; entrant } ; frank williams racing cars } } } = true | select the rows whose chassis record fuzzily matches to williams fw04 . there is only one such row in the table . the year record of this unqiue row is 1975 . the entrant record of this unqiue row is frank williams racing cars . | 10 | 8 | {'and_7': 7, 'result_8': 8, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_9': 9, 'chassis_10': 10, 'williams fw04_11': 11, 'and_6': 6, 'eq_3': 3, 'num_hop_2': 2, 'year_12': 12, '1975_13': 13, 'str_eq_5': 5, 'str_hop_4': 4, 'entrant_14': 14, 'frank williams racing cars_15': 15} | {'and_7': 'and', 'result_8': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_9': 'all_rows', 'chassis_10': 'chassis', 'williams fw04_11': 'williams fw04', 'and_6': 'and', 'eq_3': 'eq', 'num_hop_2': 'num_hop', 'year_12': 'year', '1975_13': '1975', 'str_eq_5': 'str_eq', 'str_hop_4': 'str_hop', 'entrant_14': 'entrant', 'frank williams racing cars_15': 'frank williams racing cars'} | {'and_7': [8], 'result_8': [], 'only_1': [7], 'filter_str_eq_0': [1, 2, 4], 'all_rows_9': [0], 'chassis_10': [0], 'williams fw04_11': [0], 'and_6': [7], 'eq_3': [6], 'num_hop_2': [3], 'year_12': [2], '1975_13': [3], 'str_eq_5': [6], 'str_hop_4': [5], 'entrant_14': [4], 'frank williams racing cars_15': [5]} | ['year', 'entrant', 'chassis', 'engine', 'points'] | [['1974', 'allied polymer group', 'brabham bt42', 'cosworth v8', '0'], ['1975', 'march engineering', 'march 741', 'cosworth v8', '0.5'], ['1975', 'lavazza march', 'march 751', 'cosworth v8', '0.5'], ['1975', 'frank williams racing cars', 'williams fw04', 'cosworth v8', '0.5'], ['1976', 'lavazza march', 'march 761', 'cosworth v8', '0'], ['1976', 'ram racing with lavazza', 'brabham bt44b', 'cosworth v8', '0']] |
dalymount park | https://en.wikipedia.org/wiki/Dalymount_Park | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1711684-2.html.csv | count | cliftonville fc won the irish cup two different times at dalymount park . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'cliftonville fc', 'result': '2', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'winners', 'cliftonville fc'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose winners record fuzzily matches to cliftonville fc .', 'tostr': 'filter_eq { all_rows ; winners ; cliftonville fc }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; winners ; cliftonville fc } }', 'tointer': 'select the rows whose winners record fuzzily matches to cliftonville fc . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; winners ; cliftonville fc } } ; 2 } = true', 'tointer': 'select the rows whose winners record fuzzily matches to cliftonville fc . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; winners ; cliftonville fc } } ; 2 } = true | select the rows whose winners record fuzzily matches to cliftonville fc . 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, 'winners_5': 5, 'cliftonville fc_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', 'winners_5': 'winners', 'cliftonville fc_6': 'cliftonville fc', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'winners_5': [0], 'cliftonville fc_6': [0], '2_7': [2]} | ['date', 'competition', 'winners', 'score', 'runners - up'] | [['13 / 3 / 1903', 'irish cup', 'distillery', '1 - 1', 'bohemians'], ['28 / 04 / 1906', 'irish cup', 'shelbourne fc', '2 - 0', 'belfast celtic'], ['20 / 04 / 1907', 'irish cup', 'cliftonville fc', '1 - 0', 'shelbourne fc'], ['21 / 03 / 1908', 'irish cup', 'bohemians', '1 - 1', 'shelbourne fc'], ['28 / 03 / 1908', 'irish cup ( replay )', 'bohemians', '3 - 1', 'shelbourne fc'], ['10 / 04 / 1909', 'irish cup', 'cliftonville fc', '2 - 1', 'bohemians'], ['25 / 03 / 1911', 'irish cup', 'shelbourne fc', '0 - 0', 'bohemians'], ['15 / 04 / 1911', 'irish cup ( replay )', 'shelbourne fc', '2 - 1', 'bohemians'], ['17 / 03 / 1922', 'irish free state cup final', "st james 's gate fc", '1 - 1', 'shamrock rovers fc'], ['8 / 04 / 1922', 'irish free state cup final replay', "st james 's gate", '1 - 0', 'shamrock rovers'], ['17 / 03 / 1923', 'irish free state cup final', 'alton united fc', '1 - 0', 'shelbourne fc'], ['17 / 03 / 1924', 'irish free state cup final', 'athlone town afc', '1 - 0', 'fordsons fc'], ['17 / 03 / 1925', 'irish free state cup final', 'shamrock rovers fc', '1 - 0', 'shelbourne fc'], ['22 / 05 / 1968', 'blaxnit cup final ( 2nd leg )', 'shamrock rovers fc', '1 - 2', 'crusaders fc'], ['00 / 00 / 1969', 'blaxnit cup final ( 2nd leg )', 'shamrock rovers fc', '2 - 2', 'coleraine fc'], ['22 / 05 / 1970', 'blaxnit cup final ( 2nd leg )', 'sligo rovers fc', '1 - 4', 'crusaders fc'], ['01 / 05 / 1996', 'fai cup ( replay )', 'shelbourne fc', '2 - 1', "st patrick 's athletic fc"], ['04 / 05 / 1997', 'fai cup', 'shelbourne fc', '2 - 0', 'derry city fc'], ['10 / 05 / 1998', 'fai cup', 'cork city fc', '0 - 0', 'shelbourne fc'], ['16 / 05 / 1998', 'fai cup ( replay )', 'cork city fc', '1 - 0', 'shelbourne fc']] |
2007 pga championship | https://en.wikipedia.org/wiki/2007_PGA_Championship | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12333215-2.html.csv | count | of the past champions in the 2007 pga championship , three finished at 6 over par . | {'scope': 'all', 'criterion': 'equal', 'value': '+ 6', 'result': '3', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'to par', '+ 6'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose to par record fuzzily matches to + 6 .', 'tostr': 'filter_eq { all_rows ; to par ; + 6 }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; to par ; + 6 } }', 'tointer': 'select the rows whose to par record fuzzily matches to + 6 . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; to par ; + 6 } } ; 3 } = true', 'tointer': 'select the rows whose to par record fuzzily matches to + 6 . the number of such rows is 3 .'} | eq { count { filter_eq { all_rows ; to par ; + 6 } } ; 3 } = true | select the rows whose to par record fuzzily matches to + 6 . the number of such rows is 3 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'to par_5': 5, '+ 6_6': 6, '3_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'to par_5': 'to par', '+ 6_6': '+ 6', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'to par_5': [0], '+ 6_6': [0], '3_7': [2]} | ['player', 'country', 'year ( s ) won', 'total', 'to par', 'finish'] | [['tiger woods', 'united states', '1999 , 2000 , 2006', '272', '8', '1'], ['john daly', 'united states', '1991', '286', '+ 6', 't32'], ['shaun micheel', 'united states', '2003', '286', '+ 6', 't32'], ['phil mickelson', 'united states', '2005', '286', '+ 6', 't32'], ['david toms', 'united states', '2001', '288', '+ 8', 't42'], ['bob tway', 'united states', '1986', '289', '+ 9', 't50']] |
georgia collegiate athletic association | https://en.wikipedia.org/wiki/Georgia_Collegiate_Athletic_Association | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-16734640-1.html.csv | unique | abraham baldwin agricultural college is the only institution located in tifton . | {'scope': 'all', 'row': '1', 'col': '2', 'col_other': '1', 'criterion': 'equal', 'value': 'tifton', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location', 'tifton'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose location record fuzzily matches to tifton .', 'tostr': 'filter_eq { all_rows ; location ; tifton }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; location ; tifton } }', 'tointer': 'select the rows whose location record fuzzily matches to tifton . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location', 'tifton'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose location record fuzzily matches to tifton .', 'tostr': 'filter_eq { all_rows ; location ; tifton }'}, 'institution'], 'result': 'abraham baldwin agricultural college', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; location ; tifton } ; institution }'}, 'abraham baldwin agricultural college'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; location ; tifton } ; institution } ; abraham baldwin agricultural college }', 'tointer': 'the institution record of this unqiue row is abraham baldwin agricultural college .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; location ; tifton } } ; eq { hop { filter_eq { all_rows ; location ; tifton } ; institution } ; abraham baldwin agricultural college } } = true', 'tointer': 'select the rows whose location record fuzzily matches to tifton . there is only one such row in the table . the institution record of this unqiue row is abraham baldwin agricultural college .'} | and { only { filter_eq { all_rows ; location ; tifton } } ; eq { hop { filter_eq { all_rows ; location ; tifton } ; institution } ; abraham baldwin agricultural college } } = true | select the rows whose location record fuzzily matches to tifton . there is only one such row in the table . the institution record of this unqiue row is abraham baldwin agricultural college . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'location_7': 7, 'tifton_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'institution_9': 9, 'abraham baldwin agricultural college_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', 'tifton_8': 'tifton', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'institution_9': 'institution', 'abraham baldwin agricultural college_10': 'abraham baldwin agricultural college'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'location_7': [0], 'tifton_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'institution_9': [2], 'abraham baldwin agricultural college_10': [3]} | ['institution', 'location', 'nickname', 'founded', 'enrollment', 'joined'] | [['abraham baldwin agricultural college', 'tifton', 'stallions', '1908', '3284', '2010'], ['albany technical college', 'albany', 'titans', '1961', '4000', '2010'], ['andrew college', 'cuthbert', 'fighting tigers', '1854', '350', '2010'], ['atlanta metropolitan state college', 'atlanta', 'trailblazers', '1965', '2001', '2010'], ['central georgia technical college', 'macon', 'titans', '1962', '3896', '2010'], ['chattahoochee technical college', 'marietta', 'eagles', '2003', '6264', '2010'], ['darton state college', 'albany', 'cavaliers', '1963', '6000', '2010'], ['east georgia state college', 'swainsboro', 'bobcats', '1973', '2384', '2010'], ['georgia highlands college', 'rome', 'chargers', '1970', '5529', '2011'], ['georgia military college', 'milledgeville', 'bulldogs', '1879', '1200', '2010'], ['georgia northwestern technical college', 'rome', 'bobcats', '1962', '6000', '2010'], ['georgia perimeter college', 'decatur', 'jaguars', '1964', '24000', '2010'], ['gordon state college', 'barnesville', 'highlanders', '1872', '4555', '2010'], ['middle georgia state college', 'cochran', 'knights', '1884', '2960', '2010'], ['north georgia technical college', 'clarkesville', 'wolves', '1944', '500', '2011'], ['oxford college of emory university', 'oxford', 'eagles', '1836', '753', '2010'], ['south georgia state college', 'douglas', 'hawks', '1906', '1959', '2010'], ['south georgia technical college', 'americus', 'jets', '1948', '1972', '2010'], ['southern crescent technical college', 'griffin', 'tigers', '1961', '501', '2010']] |
maryland public television | https://en.wikipedia.org/wiki/Maryland_Public_Television | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1381064-1.html.csv | aggregation | the maryland public television channels have an average haat of 261 meters . | {'scope': 'all', 'col': '5', 'type': 'average', 'result': '261', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'haat'], 'result': '261', 'ind': 0, 'tostr': 'avg { all_rows ; haat }'}, '261'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; haat } ; 261 } = true', 'tointer': 'the average of the haat record of all rows is 261 .'} | round_eq { avg { all_rows ; haat } ; 261 } = true | the average of the haat record of all rows is 261 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'haat_4': 4, '261_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'haat_4': 'haat', '261_5': '261'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'haat_4': [0], '261_5': [1]} | ['station', 'city of license', 'channels tv / rf', 'first air date', 'haat', 'facility id', 'public license information'] | [['wmpb', 'baltimore', '67 ( psip ) 29 ( uhf )', 'october 5 , 1969', '309 m', '65944', 'profile cdbs'], ['wmpt 1', 'annapolis', '22 ( psip ) 42 ( uhf )', 'september 22 , 1975', '289 m', '65942', 'profile cdbs'], ['wcpb', 'salisbury', '28 ( psip ) 28 ( uhf )', 'march 18 , 1971', '155 m', '40618', 'profile cdbs'], ['wwpb', 'hagerstown', '31 ( psip ) 44 ( uhf )', 'october 5 , 1974', '369 m', '65943', 'profile cdbs'], ['wgpt', 'oakland', '36 ( psip ) 36 ( uhf )', 'july 4 , 1987', '285 m', '40619', 'profile cdbs'], ['wfpt', 'frederick', '62 ( psip ) 28 ( uhf )', 'july 4 , 1987', '158 m', '40626', 'profile cdbs']] |
indiana high school athletics conferences : allen county - metropolitan | https://en.wikipedia.org/wiki/Indiana_High_School_Athletics_Conferences%3A_Allen_County_%E2%80%93_Metropolitan | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13986492-13.html.csv | count | the ihsaa football class for six of the schools was aaaa . | {'scope': 'all', 'criterion': 'equal', 'value': 'aaaa', 'result': '6', 'col': '6', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'ihsaa football class', 'aaaa'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose ihsaa football class record fuzzily matches to aaaa .', 'tostr': 'filter_eq { all_rows ; ihsaa football class ; aaaa }'}], 'result': '6', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; ihsaa football class ; aaaa } }', 'tointer': 'select the rows whose ihsaa football class record fuzzily matches to aaaa . the number of such rows is 6 .'}, '6'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; ihsaa football class ; aaaa } } ; 6 } = true', 'tointer': 'select the rows whose ihsaa football class record fuzzily matches to aaaa . the number of such rows is 6 .'} | eq { count { filter_eq { all_rows ; ihsaa football class ; aaaa } } ; 6 } = true | select the rows whose ihsaa football class record fuzzily matches to aaaa . 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, 'ihsaa football class_5': 5, 'aaaa_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', 'ihsaa football class_5': 'ihsaa football class', 'aaaa_6': 'aaaa', '6_7': '6'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'ihsaa football class_5': [0], 'aaaa_6': [0], '6_7': [2]} | ['school', 'location', 'mascot', 'enrollment', 'ihsaa class', 'ihsaa football class', 'county'] | [['muncie delta', 'muncie', 'eagles', '863', 'aaa', 'aaaa', '18 delaware'], ['greenfield central', 'greenfield', 'cougars', '1410', 'aaaa', 'aaaa', '30 hancock'], ['mount vernon fortville', 'fortville', 'marauders', '1077', 'aaa', 'aaaa', '30 hancock'], ['new palestine', 'new palestine', 'dragons', '1092', 'aaaa', 'aaaa', '30 hancock'], ['pendleton heights', 'pendleton', 'arabians', '1235', 'aaaa', 'aaaa', '48 madison'], ['rushville consolidated', 'rushville', 'lions', '815', 'aaa', 'aaa', '70 rush'], ['shelbyville', 'shelbyville', 'golden bears', '1153', 'aaaa', 'aaaa', '73 shelby'], ['yorktown', 'yorktown', 'tigers', '755', 'aaa', 'aaa', '18 delaware']] |
united states house of representatives elections , 1996 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1996 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1341472-20.html.csv | majority | the majority of winners in the louisiana house of representatives elections in 96 were republicans . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'republican', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'party', 'republican'], 'result': True, 'ind': 0, 'tointer': 'for the party records of all rows , most of them fuzzily match to republican .', 'tostr': 'most_eq { all_rows ; party ; republican } = true'} | most_eq { all_rows ; party ; republican } = true | for the party records of all rows , most of them fuzzily match to republican . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'party_3': 3, 'republican_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'party_3': 'party', 'republican_4': 'republican'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'party_3': [0], 'republican_4': [0]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['louisiana 1', 'robert livingston', 'republican', '1977', 're - elected', 'robert livingston ( r ) ( unopposed )'], ['louisiana 2', 'william j jefferson', 'democratic', '1990', 're - elected', 'william j jefferson ( d ) ( unopposed )'], ['louisiana 3', 'billy tauzin', 'republican', '1980', 're - elected', 'billy tauzin ( r ) ( unopposed )'], ['louisiana 4', 'jim mccrery', 'republican', '1988', 're - elected', 'jim mccrery ( r ) 71.38 % paul chachere ( d ) 28.62 %'], ['louisiana 6', 'richard baker', 'republican', '1986', 're - elected', 'richard baker ( r ) 69.30 % steve myers ( d ) 30.70 %']] |
1945 vfl season | https://en.wikipedia.org/wiki/1945_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10809271-3.html.csv | count | in the 1945 vfl season , among the games where home team scored above 14.00 , 2 of them had attendance above 9,999 . | {'scope': 'subset', 'criterion': 'greater_than', 'value': '9999', 'result': '2', 'col': '6', 'subset': {'col': '2', 'criterion': 'greater_than', 'value': '14'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'home team score', '14'], 'result': None, 'ind': 0, 'tostr': 'filter_greater { all_rows ; home team score ; 14 }', 'tointer': 'select the rows whose home team score record is greater than 14 .'}, 'crowd', '9999'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose home team score record is greater than 14 . among these rows , select the rows whose crowd record is greater than 9999 .', 'tostr': 'filter_greater { filter_greater { all_rows ; home team score ; 14 } ; crowd ; 9999 }'}], 'result': '2', 'ind': 2, 'tostr': 'count { filter_greater { filter_greater { all_rows ; home team score ; 14 } ; crowd ; 9999 } }', 'tointer': 'select the rows whose home team score record is greater than 14 . among these rows , select the rows whose crowd record is greater than 9999 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_greater { filter_greater { all_rows ; home team score ; 14 } ; crowd ; 9999 } } ; 2 } = true', 'tointer': 'select the rows whose home team score record is greater than 14 . among these rows , select the rows whose crowd record is greater than 9999 . the number of such rows is 2 .'} | eq { count { filter_greater { filter_greater { all_rows ; home team score ; 14 } ; crowd ; 9999 } } ; 2 } = true | select the rows whose home team score record is greater than 14 . among these rows , select the rows whose crowd record is greater than 9999 . the number of such rows is 2 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_greater_1': 1, 'filter_greater_0': 0, 'all_rows_5': 5, 'home team score_6': 6, '14_7': 7, 'crowd_8': 8, '9999_9': 9, '2_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_greater_1': 'filter_greater', 'filter_greater_0': 'filter_greater', 'all_rows_5': 'all_rows', 'home team score_6': 'home team score', '14_7': '14', 'crowd_8': 'crowd', '9999_9': '9999', '2_10': '2'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_greater_1': [2], 'filter_greater_0': [1], 'all_rows_5': [0], 'home team score_6': [0], '14_7': [0], 'crowd_8': [1], '9999_9': [1], '2_10': [3]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['richmond', '13.11 ( 89 )', 'south melbourne', '15.19 ( 109 )', 'punt road oval', '27000', '5 may 1945'], ['fitzroy', '12.9 ( 81 )', 'footscray', '14.14 ( 98 )', 'brunswick street oval', '20000', '5 may 1945'], ['collingwood', '10.21 ( 81 )', 'melbourne', '11.12 ( 78 )', 'victoria park', '12000', '5 may 1945'], ['st kilda', '15.10 ( 100 )', 'hawthorn', '11.13 ( 79 )', 'junction oval', '10000', '5 may 1945'], ['north melbourne', '14.15 ( 99 )', 'geelong', '10.15 ( 75 )', 'arden street oval', '6000', '5 may 1945'], ['essendon', '22.18 ( 150 )', 'carlton', '7.8 ( 50 )', 'windy hill', '16000', '5 may 1945']] |
women 's british open | https://en.wikipedia.org/wiki/Women%27s_British_Open | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1520559-1.html.csv | superlative | jiyai shin had the largest margin of victory in the women 's british open . | {'scope': 'all', 'col_superlative': '8', 'row_superlative': '2', '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', 'margin of victory'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; margin of victory }'}, 'champion'], 'result': 'jiyai shin', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; margin of victory } ; champion }'}, 'jiyai shin'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; margin of victory } ; champion } ; jiyai shin } = true', 'tointer': 'select the row whose margin of victory record of all rows is maximum . the champion record of this row is jiyai shin .'} | eq { hop { argmax { all_rows ; margin of victory } ; champion } ; jiyai shin } = true | select the row whose margin of victory record of all rows is maximum . the champion record of this row is jiyai shin . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'margin of victory_5': 5, 'champion_6': 6, 'jiyai shin_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'margin of victory_5': 'margin of victory', 'champion_6': 'champion', 'jiyai shin_7': 'jiyai shin'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'margin of victory_5': [0], 'champion_6': [1], 'jiyai shin_7': [2]} | ['year', 'dates', 'venue', 'champion', 'country', 'score', 'to par', 'margin of victory', 'runner ( s ) - up', 'purse', "winner 's share"] | [['2013', 'aug 1 - 4', 'old course at st andrews', 'stacy lewis', 'united states', '280', '- 8', '2 strokes', 'na yeon choi hee young park', '2750000', '402583'], ['2012', 'sep 13 - 16', 'royal liverpool golf club', 'jiyai shin', 'south korea', '279', '- 9', '9 strokes', 'inbee park', '2750000', '428650'], ['2011', 'july 28 - 31', 'carnoustie golf links', 'yani tseng', 'taiwan', '272', '- 16', '4 strokes', 'brittany lang', '2500000', '392133'], ['2010', 'july 29 - aug 1', 'royal birkdale golf club', 'yani tseng', 'taiwan', '277', '- 11', '1 stroke', 'katherine hull', '2500000', '408714'], ['2009', 'july 30 - aug 2', 'royal lytham & st annes golf club', 'catriona matthew', 'scotland', '285', '- 3', '3 strokes', 'karrie webb', '2200000', '335000'], ['2008', 'july 31 - aug 3', 'sunningdale golf club', 'jiyai shin', 'south korea', '270', '- 18', '3 strokes', 'yani tseng', '2100000', '314464'], ['2007', 'aug 2 - 5', 'old course at st andrews', 'lorena ochoa', 'mexico', '287', '- 5', '4 strokes', 'maria hjorth jee young lee', '2000000', '320512'], ['2006', 'aug 3 - 6', 'royal lytham & st annes golf club', 'sherri steinhauer', 'united states', '281', '- 7', '3 strokes', 'sophie gustafson cristie kerr', '1800000', '305440'], ['2005', 'july 28 - 31', 'royal birkdale golf club', 'jeong jang', 'south korea', '272', '- 16', '4 strokes', 'sophie gustafson', '1800000', '280208'], ['2004', 'july 29 - aug 1', 'sunningdale golf club', 'karen stupples', 'england', '269', '- 19', '5 strokes', 'rachel hetherington', '1600000', '290880'], ['2003', 'july 31 - aug 3', 'royal lytham & st annes golf club', 'annika sörenstam', 'sweden', '278', '- 10', '1 stroke', 'se ri pak', '1600000', '254880'], ['2002', 'aug 8 - 11', 'turnberry - ailsa course', 'karrie webb', 'australia', '273', '- 15', '2 strokes', 'michelle ellis paula martí', '1500000', '236383'], ['2001', 'aug 2 - 5', 'sunningdale golf club', 'se ri pak', 'south korea', '277', '- 11', '2 strokes', 'mi hyun kim', '1500000', '221650']] |
sébastien bourdais | https://en.wikipedia.org/wiki/S%C3%A9bastien_Bourdais | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1019053-2.html.csv | aggregation | the average number of points sebastian bourdais scored was approximately 325.4 . | {'scope': 'all', 'col': '6', 'type': 'average', 'result': '325.4', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'points'], 'result': '325.4', 'ind': 0, 'tostr': 'avg { all_rows ; points }'}, '325.4'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; points } ; 325.4 } = true', 'tointer': 'the average of the points record of all rows is 325.4 .'} | round_eq { avg { all_rows ; points } ; 325.4 } = true | the average of the points record of all rows is 325.4 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'points_4': 4, '325.4_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'points_4': 'points', '325.4_5': '325.4'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'points_4': [0], '325.4_5': [1]} | ['year', 'team', 'chassis', 'engine', 'rank', 'points'] | [['2003', 'newman / haas racing', 'lola b02 / 00', 'ford xfe', '4th', '159'], ['2004', 'newman / haas racing', 'lola b02 / 00', 'ford xfe', '1st', '369'], ['2005', 'newman / haas racing', 'lola b02 / 00', 'ford xfe', '1st', '348'], ['2006', 'newman / haas racing', 'lola b02 / 00', 'ford xfe', '1st', '387'], ['2007', 'newman / haas / lanigan racing', 'panoz dp01', 'cosworth xfe', '1st', '364']] |
canadian interuniversity sport men 's soccer | https://en.wikipedia.org/wiki/Canadian_Interuniversity_Sport_men%27s_soccer | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27369069-4.html.csv | comparative | for canadian interuniversity sport men 's soccer , mcgill university was founded 22 years before université de sherbrooke . | {'row_1': '3', 'row_2': '5', 'col': '5', 'col_other': '1', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'university', 'mcgill university'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose university record fuzzily matches to mcgill university .', 'tostr': 'filter_eq { all_rows ; university ; mcgill university }'}, 'founded'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; university ; mcgill university } ; founded }', 'tointer': 'select the rows whose university record fuzzily matches to mcgill university . take the founded record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'university', 'université de sherbrooke'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose university record fuzzily matches to université de sherbrooke .', 'tostr': 'filter_eq { all_rows ; university ; université de sherbrooke }'}, 'founded'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; university ; université de sherbrooke } ; founded }', 'tointer': 'select the rows whose university record fuzzily matches to université de sherbrooke . take the founded record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; university ; mcgill university } ; founded } ; hop { filter_eq { all_rows ; university ; université de sherbrooke } ; founded } } = true', 'tointer': 'select the rows whose university record fuzzily matches to mcgill university . take the founded record of this row . select the rows whose university record fuzzily matches to université de sherbrooke . take the founded record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; university ; mcgill university } ; founded } ; hop { filter_eq { all_rows ; university ; université de sherbrooke } ; founded } } = true | select the rows whose university record fuzzily matches to mcgill university . take the founded record of this row . select the rows whose university record fuzzily matches to université de sherbrooke . take the founded record of this row . the first record is less than the second record . | 5 | 5 | {'less_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'university_7': 7, 'mcgill university_8': 8, 'founded_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'university_11': 11, 'université de sherbrooke_12': 12, 'founded_13': 13} | {'less_4': 'less', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'university_7': 'university', 'mcgill university_8': 'mcgill university', 'founded_9': 'founded', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'university_11': 'university', 'université de sherbrooke_12': 'université de sherbrooke', 'founded_13': 'founded'} | {'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'university_7': [0], 'mcgill university_8': [0], 'founded_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'university_11': [1], 'université de sherbrooke_12': [1], 'founded_13': [3]} | ['university', 'varsity name', 'city', 'province', 'founded', 'soccer stadium', 'stadium capacity'] | [['concordia university', 'stingers', 'montreal', 'qc', '1896', 'concordia stadium', '4000'], ['université laval', 'rouge et or', 'quebec city', 'qc', '1663', 'peps stadium', '12257'], ['mcgill university', 'redmen', 'montreal', 'qc', '1821', 'percival molson memorial stadium', '25012'], ['université de montréal', 'carabins', 'montreal', 'qc', '1821', 'cepsum stadium', '5100'], ['université de sherbrooke', 'vert et or', 'sherbrooke', 'qc', '1843', "stade de l'université de sherbrooke", '3359'], ['université du québec à montréal', 'citadins', 'montreal', 'qc', '1969', 'terrain 2 of complexe sportif claude - robillard', '1000']] |
1973 nhl amateur draft | https://en.wikipedia.org/wiki/1973_NHL_Amateur_Draft | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1965650-6.html.csv | count | there were 16 players who participated in the 1973 nhl amateur draft . | {'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', 'player'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose player record is arbitrary .', 'tostr': 'filter_all { all_rows ; player }'}], 'result': '16', 'ind': 1, 'tostr': 'count { filter_all { all_rows ; player } }', 'tointer': 'select the rows whose player record is arbitrary . the number of such rows is 16 .'}, '16'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_all { all_rows ; player } } ; 16 } = true', 'tointer': 'select the rows whose player record is arbitrary . the number of such rows is 16 .'} | eq { count { filter_all { all_rows ; player } } ; 16 } = true | select the rows whose player 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, 'player_5': 5, '16_6': 6} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_all_0': 'filter_all', 'all_rows_4': 'all_rows', 'player_5': 'player', '16_6': '16'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_all_0': [1], 'all_rows_4': [0], 'player_5': [0], '16_6': [2]} | ['pick', 'player', 'position', 'nationality', 'nhl team', 'college / junior / club team'] | [['81', 'keith smith', 'defence', 'canada', 'new york islanders', 'brown university ( ecac )'], ['82', 'willie trognitz', 'left wing', 'canada', 'california golden seals', 'thunder bay vulcans ( tbjhl )'], ['83', 'jim cowell', 'centre', 'canada', 'vancouver canucks', "ottawa 67 's ( oha )"], ['84', 'doug marit', 'defence', 'canada', 'toronto maple leafs', 'regina pats ( wchl )'], ['85', 'ken houston', 'defence', 'canada', 'atlanta flames', 'chatham maroons sojhl'], ['86', 'blair macdonald', 'right wing', 'canada', 'los angeles kings', 'cornwall royals ( qmjhl )'], ['87', 'don seiling', 'left wing', 'canada', 'pittsburgh penguins', 'oshawa generals ( oha )'], ['88', 'randy smith', 'left wing', 'canada', 'st louis blues', 'edmonton oil kings ( wchl )'], ['89', 'david lee', 'left wing', 'united kingdom canada', 'minnesota north stars', "ottawa 67 's ( oha )"], ['90', 'doug ferguson', 'defence', 'canada', 'philadelphia flyers', 'hamilton red wings ( oha )'], ['91', 'glenn cickello', 'defence', 'canada', 'detroit red wings', 'hamilton red wings ( oha )'], ['92', 'neil korzack', 'left wing', 'canada', 'buffalo sabres', 'peterborough petes ( oha )'], ['93', 'garry doerksen', 'centre', 'canada', 'chicago black hawks', 'winnipeg jets ( wchl )'], ['94', 'dwayne pentland', 'defence', 'canada', 'new york rangers', 'brandon wheat kings ( wchl )'], ['95', 'jp burgoyne', 'defence', 'canada', 'boston bruins', 'shawinigan dynamos ( qmjhl )'], ['96', 'denis patry', 'right wing', 'canada', 'montreal canadiens', 'drummondville rangers ( qmjhl )']] |
eurovision dance contest 2008 | https://en.wikipedia.org/wiki/Eurovision_Dance_Contest_2008 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13053979-1.html.csv | majority | the majority of the competing dancers of the eurovision dance contest 2008 , chose rumba as one of their dancing styles . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'rumba', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'dance styles', 'rumba'], 'result': True, 'ind': 0, 'tointer': 'for the dance styles records of all rows , most of them fuzzily match to rumba .', 'tostr': 'most_eq { all_rows ; dance styles ; rumba } = true'} | most_eq { all_rows ; dance styles ; rumba } = true | for the dance styles records of all rows , most of them fuzzily match to rumba . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'dance styles_3': 3, 'rumba_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'dance styles_3': 'dance styles', 'rumba_4': 'rumba'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'dance styles_3': [0], 'rumba_4': [0]} | ['draw', 'competing dancers', 'dance styles', 'rank', 'points'] | [['01', 'danny saucedo & jeanette carlsson', 'cha - cha', '12', '38'], ['02', 'dorian steidl & nicole kuntner', 'slowfox / jive / hip - hop', '13', '29'], ['03', 'patrick spiegelberg & katja svensson', 'samba / tango / paso doble / jazz dance', '6', '102'], ['04', 'eldar dzhafarov & anna sazhina', 'paso doble / rumba / tango / azeri folk dance', '5', '106'], ['05', 'gavin ó fearraigh & dearbhla lennon', 'paso doble / rumba / hard shoe irish dance', '11', '40'], ['06', 'maria lund & mikko ahti', 'tango', '10', '44'], ['07', 'thomas berge & roemjana de haan', 'rumba / show dance', '14', '1'], ['08', 'karina krysko & saulius skambinas', 'rumba / cha - cha / acrobatic elements', '4', '110'], ['09', 'louisa lytton & vincent simone', 'paso doble / jive / tango', '9', '47'], ['10', 'tatiana navka & alexander litvinenko', 'cha - cha / samba / rumba / paso doble / russian folk dance', '2', '121'], ['11', 'jason roditis & tonia kosovich', 'latin dances', '7', '72'], ['12', 'raquel tavares & joão tiago', 'rumba / tango', '8', '61'], ['13', 'edyta herbuś & marcin mroczek', 'rumba / cha - cha / jazz dance', '1', '154'], ['14', 'lilia podkopayeva & sergey kostetskiy', "jive / ukrainian folk dance / rock 'n' roll", '3', '119']] |
1950 green bay packers season | https://en.wikipedia.org/wiki/1950_Green_Bay_Packers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-14877831-2.html.csv | aggregation | the average crowd attendance in the 1950 green bay packers season was 23036 . | {'scope': 'all', 'col': '11', 'type': 'average', 'result': '23036', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'attendance'], 'result': '23036', 'ind': 0, 'tostr': 'avg { all_rows ; attendance }'}, '23036'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; attendance } ; 23036 } = true', 'tointer': 'the average of the attendance record of all rows is 23036 .'} | round_eq { avg { all_rows ; attendance } ; 23036 } = true | the average of the attendance record of all rows is 23036 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'attendance_4': 4, '23036_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'attendance_4': 'attendance', '23036_5': '23036'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'attendance_4': [0], '23036_5': [1]} | ['game', 'date', 'opponent', 'result', 'packers points', 'opponents', 'first downs', 'record', 'streak', 'venue', 'attendance'] | [['1', 'september 17', 'detroit lions', 'loss', '7', '45', '11', '0 - 1', 'lost 1', 'city stadium', '22096'], ['2', 'september 24', 'washington redskins', 'win', '35', '21', '21', '1 - 1', 'won 1', 'state fair park', '14109'], ['3', 'oct 1', 'chicago bears', 'win', '31', '21', '8', '2 - 1', 'won 2', 'city stadium', '24893'], ['4', 'oct 8', 'new york yanks', 'loss', '31', '44', '23', '2 - 2', 'lost 1', 'city stadium', '23871'], ['5', 'oct 15', 'chicago bears', 'loss', '14', '28', '11', '2 - 3', 'lost 2', 'wrigley field', '51065'], ['6', 'oct 19', 'new york yanks', 'loss', '17', '35', '14', '2 - 4', 'lost 3', 'yankee stadium', '13661'], ['7', 'nov 5', 'baltimore colts', 'loss', '21', '41', '13', '2 - 5', 'lost 4', 'memorial stadium', '12971'], ['8', 'nov 12', 'los angeles rams', 'loss', '14', '45', '17', '2 - 6', 'lost 5', 'state fair park', '20456'], ['9', 'nov 19', 'detroit lions', 'loss', '21', '24', '16', '2 - 7', 'lost 6', 'briggs stadium', '17752'], ['10', 'nov 26', 'san francisco 49ers', 'win', '25', '21', '13', '3 - 7', 'won 1', 'city stadium', '13196'], ['11', 'dec 3', 'los angeles rams', 'loss', '14', '51', '13', '3 - 8', 'lost 1', 'los angeles memorial coliseum', '39323']] |
world series of poker europe | https://en.wikipedia.org/wiki/World_Series_of_Poker_Europe | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12454156-1.html.csv | aggregation | the world series of poker europe had an average of approximately 399 entrants each year . | {'scope': 'all', 'col': '5', 'type': 'average', 'result': '399', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'entrants'], 'result': '399', 'ind': 0, 'tostr': 'avg { all_rows ; entrants }'}, '399'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; entrants } ; 399 } = true', 'tointer': 'the average of the entrants record of all rows is 399 .'} | round_eq { avg { all_rows ; entrants } ; 399 } = true | the average of the entrants record of all rows is 399 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'entrants_4': 4, '399_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'entrants_4': 'entrants', '399_5': '399'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'entrants_4': [0], '399_5': [1]} | ['year', 'winner', 'winning hand', 'prize money', 'entrants', 'runner - up', 'losing hand'] | [['2007', 'annette obrestad', '7h 7s', '1000000', '362', 'john tabatabai', '5s 6d'], ['2008', 'john juanda', 'ks 6c', '868800', '362', 'stanislav alekhin', 'ac 9s'], ['2009', 'barry shulman', '10s 10c', '801603', '334', 'daniel negreanu', '4s 4d'], ['2010', 'james bord', '10d 10h', '830401', '346', 'fabrizio baldassari', '5s 5h'], ['2011', 'elio fox', 'ad 10s', '1400000', '593', 'chris moorman', 'ah 7s'], ['2012', 'phil hellmuth', 'ah 10d', '1058403', '420', 'sergii baranov', 'as 4c'], ['2013', 'adrián mateos', 'as kc', '1000000', '375', 'fabrice soulier', '9d 8d']] |
vanity ( performer ) | https://en.wikipedia.org/wiki/Vanity_%28performer%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1023439-2.html.csv | ordinal | pretty mess was the second highest charting us r & b single for vanity . | {'row': '1', 'col': '4', 'order': '2', 'col_other': '2', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'us r & b', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; us r & b ; 2 }'}, 'title'], 'result': 'pretty mess', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; us r & b ; 2 } ; title }'}, 'pretty mess'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; us r & b ; 2 } ; title } ; pretty mess } = true', 'tointer': 'select the row whose us r & b record of all rows is 2nd maximum . the title record of this row is pretty mess .'} | eq { hop { nth_argmax { all_rows ; us r & b ; 2 } ; title } ; pretty mess } = true | select the row whose us r & b record of all rows is 2nd maximum . the title record of this row is pretty mess . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'us r&b_5': 5, '2_6': 6, 'title_7': 7, 'pretty mess_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', 'us r&b_5': 'us r & b', '2_6': '2', 'title_7': 'title', 'pretty mess_8': 'pretty mess'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'us r&b_5': [0], '2_6': [0], 'title_7': [1], 'pretty mess_8': [2]} | ['year', 'title', 'us', 'us r & b', 'us dance'] | [['1984', 'pretty mess', '75', '15', '13'], ['1985', 'mechanical emotion', '107', '23', '-'], ['1986', 'under the influence', '56', '9', '6'], ['1986', 'animals', '-', '-', '-'], ['1988', 'undress', '-', '-', '-']] |
kingsport mets | https://en.wikipedia.org/wiki/Kingsport_Mets | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1196050-1.html.csv | ordinal | the kingsport mets had their second highest number of wins in the year 1979 . | {'row': '6', 'col': '2', 'order': '2', 'col_other': '1', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'record', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; record ; 2 }'}, 'year'], 'result': '1979', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; record ; 2 } ; year }'}, '1979'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; record ; 2 } ; year } ; 1979 } = true', 'tointer': 'select the row whose record record of all rows is 2nd maximum . the year record of this row is 1979 .'} | eq { hop { nth_argmax { all_rows ; record ; 2 } ; year } ; 1979 } = true | select the row whose record record of all rows is 2nd maximum . the year record of this row is 1979 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'num_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'record_5': 5, '2_6': 6, 'year_7': 7, '1979_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'num_hop_1': 'num_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'record_5': 'record', '2_6': '2', 'year_7': 'year', '1979_8': '1979'} | {'eq_2': [3], 'result_3': [], 'num_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'record_5': [0], '2_6': [0], 'year_7': [1], '1979_8': [2]} | ['year', 'record', 'finish', 'manager', 'playoffs'] | [['1974', '31 - 39', '7th', 'hoyt wilhelm', 'none'], ['1975', '33 - 33', '6th', 'gene hassell', 'none'], ['1976', '25 - 42', '8th', 'bobby dews', 'none'], ['1977', '43 - 27', '2nd', 'bob didier', 'none'], ['1978', '33 - 37', '5th', 'eddie haas', 'none'], ['1979', '39 - 31', '2nd', 'gene hassell', 'none']] |
2008 indiana fever season | https://en.wikipedia.org/wiki/2008_Indiana_Fever_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-17104539-10.html.csv | aggregation | the average number of high assists per game during the 2008 indiana fever season is 4.5 . | {'scope': 'all', 'col': '7', 'type': 'average', 'result': '4.5', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'high assists'], 'result': '4.5', 'ind': 0, 'tostr': 'avg { all_rows ; high assists }'}, '4.5'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; high assists } ; 4.5 } = true', 'tointer': 'the average of the high assists record of all rows is 4.5 .'} | round_eq { avg { all_rows ; high assists } ; 4.5 } = true | the average of the high assists record of all rows is 4.5 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'high assists_4': 4, '4.5_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'high assists_4': 'high assists', '4.5_5': '4.5'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'high assists_4': [0], '4.5_5': [1]} | ['game', 'date', 'opponent', 'score', 'high points', 'high rebounds', 'high assists', 'location / attendance', 'record'] | [['16', 'july 2', 'chicago', 'w 74 - 67', 'catchings ( 18 )', 'sutton - brown ( 12 )', 'catchings , douglas ( 3 )', 'conseco fieldhouse 6196', '8 - 8'], ['17', 'july 5', 'connecticut', 'w 81 - 74', 'douglas , sutton - brown ( 18 )', 'sutton - brown ( 9 )', 'douglas ( 5 )', 'conseco fieldhouse 6329', '9 - 8'], ['18', 'july 8', 'washington', 'l 50 - 48', 'hoffman ( 16 )', 'hoffman ( 9 )', 'bevilaqua ( 4 )', 'verizon center 7587', '9 - 9'], ['19', 'july 12', 'chicago', 'w 66 - 57', 'douglas ( 25 )', 'catchings ( 8 )', 'catchings ( 4 )', 'conseco fieldhouse 7134', '10 - 9'], ['20', 'july 16', 'atlanta', 'l 81 - 77', 'catchings ( 18 )', 'catchings ( 12 )', 'catchings ( 5 )', 'conseco fieldhouse 9303', '10 - 10'], ['21', 'july 18', 'seattle', 'l 65 - 59', 'sutton - brown ( 12 )', 'sutton - brown ( 7 )', 'bevilaqua , bond ( 3 )', 'conseco fieldhouse 7450', '10 - 11'], ['22', 'july 19', 'new york liberty outdoor classic', 'w 71 - 55', 'douglas ( 20 )', 'catchings , sutton - brown ( 9 )', 'catchings , douglas ( 4 )', 'arthur ashe stadium 19393', '11 - 11'], ['23', 'july 22', 'chicago', 'l 68 - 60', 'douglas , sutton - brown ( 14 )', 'sutton - brown ( 10 )', 'catchings ( 4 )', 'uic pavilion 3035', '11 - 12'], ['24', 'july 24', 'minnesota', 'l 84 - 80', 'catchings , hoffman ( 17 )', 'sutton - brown ( 9 )', 'catchings ( 9 )', 'conseco fieldhouse 6010', '11 - 13'], ['25', 'july 26', 'sacramento', 'l 70 - 62', 'douglas ( 23 )', 'hoffman ( 8 )', 'catchings , white ( 4 )', 'arco arena 7082', '11 - 14']] |
2004 - 05 san antonio spurs season | https://en.wikipedia.org/wiki/2004%E2%80%9305_San_Antonio_Spurs_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13759275-4.html.csv | count | in the 2004 - 05 san antonio spurs season , when the spurs were the home team , there were 3 times when tim duncan was the leading scorer . | {'scope': 'subset', 'criterion': 'fuzzily_match', 'value': 'tim duncan', 'result': '3', 'col': '5', 'subset': {'col': '4', 'criterion': 'equal', 'value': 'spurs'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'home', 'spurs'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; home ; spurs }', 'tointer': 'select the rows whose home record fuzzily matches to spurs .'}, 'leading scorer', 'tim duncan'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose home record fuzzily matches to spurs . among these rows , select the rows whose leading scorer record fuzzily matches to tim duncan .', 'tostr': 'filter_eq { filter_eq { all_rows ; home ; spurs } ; leading scorer ; tim duncan }'}], 'result': '3', 'ind': 2, 'tostr': 'count { filter_eq { filter_eq { all_rows ; home ; spurs } ; leading scorer ; tim duncan } }', 'tointer': 'select the rows whose home record fuzzily matches to spurs . among these rows , select the rows whose leading scorer record fuzzily matches to tim duncan . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_eq { filter_eq { all_rows ; home ; spurs } ; leading scorer ; tim duncan } } ; 3 } = true', 'tointer': 'select the rows whose home record fuzzily matches to spurs . among these rows , select the rows whose leading scorer record fuzzily matches to tim duncan . the number of such rows is 3 .'} | eq { count { filter_eq { filter_eq { all_rows ; home ; spurs } ; leading scorer ; tim duncan } } ; 3 } = true | select the rows whose home record fuzzily matches to spurs . among these rows , select the rows whose leading scorer record fuzzily matches to tim duncan . the number of such rows is 3 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_str_eq_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'home_6': 6, 'spurs_7': 7, 'leading scorer_8': 8, 'tim duncan_9': 9, '3_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_str_eq_1': 'filter_str_eq', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'home_6': 'home', 'spurs_7': 'spurs', 'leading scorer_8': 'leading scorer', 'tim duncan_9': 'tim duncan', '3_10': '3'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_str_eq_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'home_6': [0], 'spurs_7': [0], 'leading scorer_8': [1], 'tim duncan_9': [1], '3_10': [3]} | ['date', 'visitor', 'score', 'home', 'leading scorer', 'record'] | [['1 december 2004', '76ers', '72 - 105', 'spurs', 'two - way tie ( 24 )', '13 - 3'], ['3 december 2004', 'pistons', '77 - 80', 'spurs', 'tony parker ( 20 )', '14 - 3'], ['4 december 2004', 'spurs', '104 - 83', 'bucks', 'tim duncan ( 20 )', '15 - 3'], ['6 december 2004', 'spurs', '91 - 75', 'bulls', 'tony parker ( 17 )', '16 - 3'], ['8 december 2004', 'supersonics', '102 - 96', 'spurs', 'tim duncan ( 39 )', '16 - 4'], ['9 december 2004', 'spurs', '80 - 81', 'rockets', 'tim duncan ( 26 )', '16 - 5'], ['11 december 2004', 'cavaliers', '97 - 116', 'spurs', 'tim duncan ( 34 )', '17 - 5'], ['15 december 2004', 'magic', '91 - 94', 'spurs', 'tim duncan ( 24 )', '18 - 5'], ['17 december 2004', 'spurs', '83 - 67', 'hornets', 'tim duncan ( 19 )', '19 - 5'], ['18 december 2004', 'warriors', '85 - 104', 'spurs', 'two - way tie ( 21 )', '20 - 5'], ['22 december 2004', 'spurs', '87 - 93', 'magic', 'tim duncan ( 24 )', '20 - 6'], ['23 december 2004', 'timberwolves', '79 - 94', 'spurs', 'manu ginóbili ( 22 )', '21 - 6'], ['26 december 2004', 'celtics', '90 - 107', 'spurs', 'tony parker ( 27 )', '22 - 6'], ['28 december 2004', 'suns', '94 - 115', 'spurs', 'tony parker ( 29 )', '23 - 6'], ['30 december 2004', 'spurs', '114 - 80', 'trail blazers', 'tim duncan ( 19 )', '24 - 6'], ['31 december 2004', 'spurs', '98 - 79', 'clippers', 'tim duncan ( 23 )', '25 - 6']] |
united states house of representatives elections , 2000 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_2000 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1341423-21.html.csv | aggregation | the average winning percentage of the massachusetts districts incumbents who did not run unopposed in the 2000 united states house of representatives elections was just over 72 % . | {'scope': 'subset', 'col': '6', 'type': 'average', 'result': '72', 'subset': {'col': '6', 'criterion': 'not_equal', 'value': 'unopposed'}} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': [{'func': 'filter_str_not_eq', 'args': ['all_rows', 'candidates', 'unopposed'], 'result': None, 'ind': 0, 'tostr': 'filter_not_eq { all_rows ; candidates ; unopposed }', 'tointer': 'select the rows whose candidates record does not match to unopposed .'}, 'candidates'], 'result': '72', 'ind': 1, 'tostr': 'avg { filter_not_eq { all_rows ; candidates ; unopposed } ; candidates }'}, '72'], 'result': True, 'ind': 2, 'tostr': 'round_eq { avg { filter_not_eq { all_rows ; candidates ; unopposed } ; candidates } ; 72 } = true', 'tointer': 'select the rows whose candidates record does not match to unopposed . the average of the candidates record of these rows is 72 .'} | round_eq { avg { filter_not_eq { all_rows ; candidates ; unopposed } ; candidates } ; 72 } = true | select the rows whose candidates record does not match to unopposed . the average of the candidates record of these rows is 72 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'avg_1': 1, 'filter_str_not_eq_0': 0, 'all_rows_4': 4, 'candidates_5': 5, 'unopposed_6': 6, 'candidates_7': 7, '72_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'avg_1': 'avg', 'filter_str_not_eq_0': 'filter_str_not_eq', 'all_rows_4': 'all_rows', 'candidates_5': 'candidates', 'unopposed_6': 'unopposed', 'candidates_7': 'candidates', '72_8': '72'} | {'eq_2': [3], 'result_3': [], 'avg_1': [2], 'filter_str_not_eq_0': [1], 'all_rows_4': [0], 'candidates_5': [0], 'unopposed_6': [0], 'candidates_7': [1], '72_8': [2]} | ['district', 'incumbent', 'party', 'first elected', 'results', 'candidates'] | [['massachusetts 1', 'john olver', 'democratic', '1991', 're - elected', 'john olver ( d ) 69 % peter abair ( r ) 30 %'], ['massachusetts 2', 'richard neal', 'democratic', '1988', 're - elected', 'richard neal ( d ) unopposed'], ['massachusetts 3', 'jim mcgovern', 'democratic', '1996', 're - elected', 'jim mcgovern ( d ) unopposed'], ['massachusetts 4', 'barney frank', 'democratic', '1980', 're - elected', 'barney frank ( d ) 71 % martin travis ( r ) 21 %'], ['massachusetts 5', 'marty meehan', 'democratic', '1992', 're - elected', 'marty meehan ( d ) unopposed'], ['massachusetts 6', 'john f tierney', 'democratic', '1996', 're - elected', 'john f tierney ( d ) 71 % paul mccarthy ( r ) 29 %'], ['massachusetts 7', 'ed markey', 'democratic', '1976', 're - elected', 'ed markey ( d ) unopposed'], ['massachusetts 8', 'mike capuano', 'democratic', '1998', 're - elected', 'mike capuano ( d ) unopposed'], ['massachusetts 9', 'joe moakley', 'democratic', '1972', 're - elected', 'joe moakley ( d ) 78 % janet jeghelian ( r ) 20 %']] |
2008 vanderbilt commodores baseball team | https://en.wikipedia.org/wiki/2008_Vanderbilt_Commodores_baseball_team | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15925327-6.html.csv | aggregation | in week 11 of the season , the 2008 vanderbilt commodores baseball team 's average rank was 15.4 . | {'scope': 'all', 'col': '11', 'type': 'average', 'result': '15.4', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'wk 11'], 'result': '15.4', 'ind': 0, 'tostr': 'avg { all_rows ; wk 11 }'}, '15.4'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; wk 11 } ; 15.4 } = true', 'tointer': 'the average of the wk 11 record of all rows is 15.4 .'} | round_eq { avg { all_rows ; wk 11 } ; 15.4 } = true | the average of the wk 11 record of all rows is 15.4 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'wk 11_4': 4, '15.4_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'wk 11_4': 'wk 11', '15.4_5': '15.4'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'wk 11_4': [0], '15.4_5': [1]} | ['poll', 'wk 2', 'wk 3', 'wk 4', 'wk 5', 'wk 6', 'wk 7', 'wk 8', 'wk 9', 'wk 10', 'wk 11', 'wk 12', 'wk 13', 'wk 14', 'final'] | [["usa today / espn coaches ' poll ( top 25 )", '11', '12', '8', '13', '8', '17', '14', '13', '17', '14', '13', '21', '22', 'n / r'], ['baseball america ( top 25 )', '7', '6', '5', '9', '8', '19', '17', '17', '22', '18', '19', 'n / r', 'n / r', 'n / r'], ['collegiate baseball ( top 30 )', '10', '12', '9', '14', '13', '23', '22', '20', '20', '16', '17', 'n / r', '24', '27'], ['ncbwa ( top 30 )', '10', '9', '6', '11', '6', '13', '11', '10', '13', '11', '13', '21', '21', '25'], ['rivalscom ( top 25 )', '5', '4', '4', '9', '9', '17', '18', '18', '22', '18', '19', 'n / r', 'n / r', 'n / r']] |
martina hingis | https://en.wikipedia.org/wiki/Martina_Hingis | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-19047-2.html.csv | majority | most of martina hingis 's tournament wins came on a hard surface . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'hard', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'surface', 'hard'], 'result': True, 'ind': 0, 'tointer': 'for the surface records of all rows , most of them fuzzily match to hard .', 'tostr': 'most_eq { all_rows ; surface ; hard } = true'} | most_eq { all_rows ; surface ; hard } = true | for the surface records of all rows , most of them fuzzily match to hard . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'surface_3': 3, 'hard_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'surface_3': 'surface', 'hard_4': 'hard'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'surface_3': [0], 'hard_4': [0]} | ['outcome', 'year', 'championship', 'surface', 'opponent in the final', 'score in the final'] | [['winner', '1997', 'australian open', 'hard', 'mary pierce', '6 - 2 , 6 - 2'], ['runner - up', '1997', 'french open', 'clay', 'iva majoli', '6 - 4 , 6 - 2'], ['winner', '1997', 'wimbledon', 'grass', 'jana novotná', '2 - 6 , 6 - 3 , 6 - 3'], ['winner', '1997', 'us open', 'hard', 'venus williams', '6 - 0 , 6 - 4'], ['winner', '1998', 'australian open ( 2 )', 'hard', 'conchita martínez', '6 - 3 , 6 - 3'], ['runner - up', '1998', 'us open', 'hard', 'lindsay davenport', '6 - 3 , 7 - 5'], ['winner', '1999', 'australian open ( 3 )', 'hard', 'amélie mauresmo', '6 - 2 , 6 - 3'], ['runner - up', '1999', 'french open ( 2 )', 'clay', 'steffi graf', '4 - 6 , 7 - 5 , 6 - 2'], ['runner - up', '1999', 'us open ( 2 )', 'hard', 'serena williams', '6 - 3 , 7 - 6 ( 4 )'], ['runner - up', '2000', 'australian open', 'hard', 'lindsay davenport', '6 - 1 , 7 - 5'], ['runner - up', '2001', 'australian open ( 2 )', 'hard', 'jennifer capriati', '6 - 4 , 6 - 3']] |
ludovico scarfiotti | https://en.wikipedia.org/wiki/Ludovico_Scarfiotti | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1235774-1.html.csv | aggregation | ludovico scarfiotti scored a total of 2 points in 1967 . | {'scope': 'subset', 'col': '5', 'type': 'sum', 'result': '2', 'subset': {'col': '1', 'criterion': 'equal', 'value': '1967'}} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'year', '1967'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; year ; 1967 }', 'tointer': 'select the rows whose year record is equal to 1967 .'}, 'points'], 'result': '2', 'ind': 1, 'tostr': 'sum { filter_eq { all_rows ; year ; 1967 } ; points }'}, '2'], 'result': True, 'ind': 2, 'tostr': 'round_eq { sum { filter_eq { all_rows ; year ; 1967 } ; points } ; 2 } = true', 'tointer': 'select the rows whose year record is equal to 1967 . the sum of the points record of these rows is 2 .'} | round_eq { sum { filter_eq { all_rows ; year ; 1967 } ; points } ; 2 } = true | select the rows whose year record is equal to 1967 . the sum of the points record of these rows is 2 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'sum_1': 1, 'filter_eq_0': 0, 'all_rows_4': 4, 'year_5': 5, '1967_6': 6, 'points_7': 7, '2_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'sum_1': 'sum', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'year_5': 'year', '1967_6': '1967', 'points_7': 'points', '2_8': '2'} | {'eq_2': [3], 'result_3': [], 'sum_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'year_5': [0], '1967_6': [0], 'points_7': [1], '2_8': [2]} | ['year', 'team', 'chassis', 'engine', 'points'] | [['1963', 'scuderia ferrari', 'ferrari 156', 'ferrari v6', '1'], ['1964', 'scuderia ferrari', 'ferrari 156', 'ferrari v6', '0'], ['1965', 'scuderia ferrari', 'ferrari 1512', 'ferrari v12', '0'], ['1966', 'scuderia ferrari', 'ferrari 246', 'ferrari v6', '9'], ['1966', 'scuderia ferrari', 'ferrari 312 / 66', 'ferrari v12', '9'], ['1967', 'scuderia ferrari', 'ferrari 312 / 67', 'ferrari v12', '1'], ['1967', 'anglo american racers', 'eagle t1 g', 'weslake v12', '1'], ['1968', 'cooper car company', 'cooper t86', 'maserati v12', '6'], ['1968', 'cooper car company', 'cooper t86b', 'brm v12', '6']] |
1997 open championship | https://en.wikipedia.org/wiki/1997_Open_Championship | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18060467-2.html.csv | majority | in the 1997 open championship , most of the players were from the united states . | {'scope': 'all', 'col': '2', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'united states', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'country', 'united states'], 'result': True, 'ind': 0, 'tointer': 'for the country records of all rows , most of them fuzzily match to united states .', 'tostr': 'most_eq { all_rows ; country ; united states } = true'} | most_eq { all_rows ; country ; united states } = true | for the country records of all rows , most of them fuzzily match to united states . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'country_3': 3, 'united states_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'country_3': 'country', 'united states_4': 'united states'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'country_3': [0], 'united states_4': [0]} | ['player', 'country', 'year ( s ) won', 'total', 'to par', 'finish'] | [['mark calcavecchia', 'united states', '1989', '282', '- 2', 't10'], ['tom watson', 'united states', '1975 , 1977 , 1980 , 1982 , 1983', '282', '- 2', 't10'], ['tom lehman', 'united states', '1996', '284', 'e', 't24'], ['greg norman', 'australia', '1986 , 1993', '287', '+ 3', 't37'], ['nick faldo', 'england', '1987 , 1990 , 1992', '291', '+ 7', 't50'], ['jack nicklaus', 'united states', '1966 , 1970 , 1978', '293', '+ 9', 't60']] |
1998 u.s. open ( golf ) | https://en.wikipedia.org/wiki/1998_U.S._Open_%28golf%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17162166-4.html.csv | count | twelve of the players are from the united states . | {'scope': 'all', 'criterion': 'equal', 'value': 'united states', 'result': '12', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'united states'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose country record fuzzily matches to united states .', 'tostr': 'filter_eq { all_rows ; country ; united states }'}], 'result': '12', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; country ; united states } }', 'tointer': 'select the rows whose country record fuzzily matches to united states . the number of such rows is 12 .'}, '12'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; country ; united states } } ; 12 } = true', 'tointer': 'select the rows whose country record fuzzily matches to united states . the number of such rows is 12 .'} | eq { count { filter_eq { all_rows ; country ; united states } } ; 12 } = true | select the rows whose country record fuzzily matches to united states . the number of such rows is 12 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'country_5': 5, 'united states_6': 6, '12_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'country_5': 'country', 'united states_6': 'united states', '12_7': '12'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'country_5': [0], 'united states_6': [0], '12_7': [2]} | ['place', 'player', 'country', 'score', 'to par'] | [['1', 'payne stewart', 'united states', '66', '- 4'], ['2', 'mark carnevale', 'united states', '67', '- 3'], ['t3', 'joe durant', 'united states', '68', '- 2'], ['t3', 'tom lehman', 'united states', '68', '- 2'], ['t3', 'josé maría olazábal', 'spain', '68', '- 2'], ['t3', 'bob tway', 'united states', '68', '- 2'], ['t7', 'john daly', 'united states', '69', '- 1'], ['t7', 'jeff maggert', 'united states', '69', '- 1'], ['t7', 'jesper parnevik', 'sweden', '69', '- 1'], ['t10', 'tom kite', 'united states', '70', 'e'], ['t10', 'matt kuchar ( a )', 'united states', '70', 'e'], ['t10', 'colin montgomerie', 'scotland', '70', 'e'], ['t10', 'andrew magee', 'united states', '70', 'e'], ['t10', 'david ogrin', 'united states', '70', 'e'], ['t10', "mark o'meara", 'united states', '70', 'e']] |
banking and insurance in iran | https://en.wikipedia.org/wiki/Banking_and_insurance_in_Iran | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16254980-5.html.csv | superlative | the bank of industry and mine has the highest assets score . | {'scope': 'all', 'col_superlative': '7', 'row_superlative': '3', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'total assets ( score )'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; total assets ( score ) }'}, 'bank'], 'result': 'bank of industry and mine', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; total assets ( score ) } ; bank }'}, 'bank of industry and mine'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; total assets ( score ) } ; bank } ; bank of industry and mine } = true', 'tointer': 'select the row whose total assets ( score ) record of all rows is maximum . the bank record of this row is bank of industry and mine .'} | eq { hop { argmax { all_rows ; total assets ( score ) } ; bank } ; bank of industry and mine } = true | select the row whose total assets ( score ) record of all rows is maximum . the bank record of this row is bank of industry and mine . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'total assets (score)_5': 5, 'bank_6': 6, 'bank of industry and mine_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'total assets (score)_5': 'total assets ( score )', 'bank_6': 'bank', 'bank of industry and mine_7': 'bank of industry and mine'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'total assets (score)_5': [0], 'bank_6': [1], 'bank of industry and mine_7': [2]} | ['bank', 'score ( iran )', 'score ( global )', 'banking power / capital base ( million )', 'banking power / capital base ( % change )', 'total assets ( million )', 'total assets ( score )', 'total assets ( % change )', 'credibility / capital to assets ratio ( % )', 'credibility / capital to assets ratio ( score )', 'performance / return on capital ( % )', 'performance / return on capital ( score )', 'return on assets ( % )', 'return on assets ( score )'] | [['bank saderat iran', '1', '259', '3109', '4.46', '54877', '3', '14.22', '5.66', '7', '25.63', '8', '1.45', '7'], ['pasargad bank', '2', '266', '3057', '147.7', '18057', '8', '47.41', '16.93', '3', '20.69', '9', '3.5', '2'], ['bank of industry and mine', '3', '310', '2550', '- 2.16', '9432', '10', '12.1', '27.04', '2', '3.2', '13', '0.87', '10'], ['mellat bank', '4', '320', '2402', 'nm', '68370', '2', 'nm', '3.51', '12', '32.59', '15', '1.14', '9'], ['tejarat bank', '5', '350', '2103', '13.6', '68370', '4', '18.65', '4.66', '9', '27.14', '7', '1.26', '8']] |
b ' z discography | https://en.wikipedia.org/wiki/B%27z_discography | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13619558-1.html.csv | majority | most of the album releases by b ' z occurred prior to ' 00 . | {'scope': 'all', 'col': '1', 'most_or_all': 'most', 'criterion': 'less_than', 'value': '2000', 'subset': None} | {'func': 'most_less', 'args': ['all_rows', 'year', '2000'], 'result': True, 'ind': 0, 'tointer': 'for the year records of all rows , most of them are less than 2000 .', 'tostr': 'most_less { all_rows ; year ; 2000 } = true'} | most_less { all_rows ; year ; 2000 } = true | for the year records of all rows , most of them are less than 2000 . | 1 | 1 | {'most_less_0': 0, 'result_1': 1, 'all_rows_2': 2, 'year_3': 3, '2000_4': 4} | {'most_less_0': 'most_less', 'result_1': 'true', 'all_rows_2': 'all_rows', 'year_3': 'year', '2000_4': '2000'} | {'most_less_0': [1], 'result_1': [], 'all_rows_2': [0], 'year_3': [0], '2000_4': [0]} | ['year', 'album', 'oricon position', '1st week sales', 'copies sold'] | [['1988', "b ' z release date : september 21 , 1988", '47', '3790 +', '338360 +'], ['1989', 'off the lock release date : may 21 , 1989', '33', '4590 +', '604700 +'], ['1990', 'break through release date : february 21 , 1990', '3', '41700 +', '724640 +'], ['1990', 'risky release date : november 7 , 1990', '1', '314770 +', '1695900 +'], ['1991', 'in the life release date : november 27 , 1991', '1', '1043070 +', '2402970 +'], ['1992', 'run release date : october 28 , 1992', '1', '1190380 +', '2196660 +'], ['1994', 'the 7th blues release date : march 2 , 1994', '1', '1049900 +', '1630450 +'], ['1995', 'loose release date : november 22 , 1995', '1', '1336150 +', '3003210 +'], ['1997', 'survive release date : november 19 , 1997', '1', '1040160 +', '1723030 +'], ['1999', 'brotherhood release date : july 14 , 1999', '1', '1019270 +', '1391850 +'], ['2000', 'eleven release date : december 6 , 2000', '1', '756910 +', '1132180 +'], ['2002', 'green release date : july 3 , 2002', '1', '800120 +', '1131788 +'], ['2003', 'big machine release date : september 17 , 2003', '1', '500237 +', '746451 +'], ['2005', 'the circle release date : april 6 , 2005', '1', '345041 +', '557783 +'], ['2006', 'monster release date : june 28 , 2006', '1', '401000 +', '539708 +'], ['2007', 'action release date : december 5 , 2007', '1', '292987 +', '440108 +'], ['2009', 'magic release date : november 18 , 2009', '1', '340630 +', '488468 +'], ['2011', "c'mon release date : july 27 , 2011", '1', '272397', '383428 +']] |
2007 amsterdam admirals season | https://en.wikipedia.org/wiki/2007_Amsterdam_Admirals_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-10392906-2.html.csv | aggregation | the average attendance for a game during the 2007 amsterdam admirals season was 16119 . | {'scope': 'all', 'col': '8', 'type': 'average', 'result': '16119', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'attendance'], 'result': '16119', 'ind': 0, 'tostr': 'avg { all_rows ; attendance }'}, '16119'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; attendance } ; 16119 } = true', 'tointer': 'the average of the attendance record of all rows is 16119 .'} | round_eq { avg { all_rows ; attendance } ; 16119 } = true | the average of the attendance record of all rows is 16119 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'attendance_4': 4, '16119_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'attendance_4': 'attendance', '16119_5': '16119'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'attendance_4': [0], '16119_5': [1]} | ['week', 'date', 'kickoff', 'opponent', 'final score', 'team record', 'game site', 'attendance'] | [['1', 'saturday , april 14', '7:00 pm', 'frankfurt galaxy', 'l 14 - 30', '0 - 1', 'commerzbank - arena', '38125'], ['2', 'friday , april 20', '8:00 pm', 'rhein fire', 'l 10 - 16', '0 - 2', 'amsterdam arena', '14611'], ['3', 'saturday , april 28', '6:00 pm', 'berlin thunder', 'w 14 - 10', '1 - 2', 'olympic stadium', '11942'], ['4', 'sunday , may 6', '3:00 pm', 'frankfurt galaxy', 'w 19 - 17', '2 - 2', 'amsterdam arena', '10788'], ['5', 'saturday , may 12', '6:00 pm', 'hamburg sea devils', 'l 17 - 24', '2 - 3', 'aol arena', '15271'], ['6', 'friday , may 18', '8:00 pm', 'hamburg sea devils', 'w 41 - 31', '3 - 3', 'amsterdam arena', '9384'], ['7', 'friday , may 25', '8:00 pm', 'cologne centurions', 'l 7 - 30', '3 - 4', 'amsterdam arena', '11714'], ['8', 'sunday , june 3', '4:00 pm', 'rhein fire', 'l 38 - 41', '3 - 5', 'ltu arena', '20355'], ['9', 'saturday , june 9', '6:00 pm', 'cologne centurions', 'l 13 - 31', '3 - 6', 'rheinenergiestadion', '12878']] |
list of formula one driver records | https://en.wikipedia.org/wiki/List_of_Formula_One_driver_records | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-13599687-46.html.csv | count | there are 9 drivers listed in the formula one driver records . | {'scope': 'all', 'criterion': 'all', 'value': 'n/a', 'result': '9', 'col': '1', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_all', 'args': ['all_rows', ''], 'result': None, 'ind': 0, 'tointer': 'select the rows whose record is arbitrary .', 'tostr': 'filter_all { all_rows ; }'}], 'result': '9', 'ind': 1, 'tostr': 'count { filter_all { all_rows ; } }', 'tointer': 'select the rows whose record is arbitrary . the number of such rows is 9 .'}, '9'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_all { all_rows ; } } ; 9 } = true', 'tointer': 'select the rows whose record is arbitrary . the number of such rows is 9 .'} | eq { count { filter_all { all_rows ; } } ; 9 } = true | select the rows whose record is arbitrary . the number of such rows is 9 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_all_0': 0, 'all_rows_4': 4, '_5': 5, '9_6': 6} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_all_0': 'filter_all', 'all_rows_4': 'all_rows', '_5': '', '9_6': '9'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_all_0': [1], 'all_rows_4': [0], '_5': [0], '9_6': [2]} | ['', 'driver', 'seasons', 'entries', 'podiums', 'percentage'] | [['1', 'michael schumacher', '1991 - 2006 , 2010 - 2012', '308', '155', '50.32 %'], ['2', 'alain prost', '1980 - 1991 , 1993', '202', '106', '52.47 %'], ['3', 'fernando alonso', '2001 , 2003 - 2013', '215', '94', '43.72 %'], ['4', 'ayrton senna', '1984 - 1994', '162', '80', '49.38 %'], ['5', 'kimi räikkönen', '2001 - 2009 , 2012 - 2013', '194', '77', '39.69 %'], ['6', 'rubens barrichello', '1993 - 2011', '326', '68', '20.85 %'], ['7', 'david coulthard', '1994 - 2008', '247', '62', '25.10 %'], ['8', 'nelson piquet', '1978 - 1991', '207', '60', '28.98 %'], ['8', 'sebastian vettel', '2007 - 2013', '118', '60', '50.85 %']] |
2003 cricket world cup statistics | https://en.wikipedia.org/wiki/2003_Cricket_World_Cup_statistics | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11611293-7.html.csv | majority | for the 2003 cricket world cup , when the venue is johannesburg , most of the time there were over 140 runs . | {'scope': 'subset', 'col': '1', 'most_or_all': 'most', 'criterion': 'greater_than', 'value': '140', 'subset': {'col': '5', 'criterion': 'equal', 'value': 'johannesburg'}} | {'func': 'most_greater', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'venue', 'johannesburg'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; venue ; johannesburg }', 'tointer': 'select the rows whose venue record fuzzily matches to johannesburg .'}, 'runs', '140'], 'result': True, 'ind': 1, 'tointer': 'select the rows whose venue record fuzzily matches to johannesburg . for the runs records of these rows , most of them are greater than 140 .', 'tostr': 'most_greater { filter_eq { all_rows ; venue ; johannesburg } ; runs ; 140 } = true'} | most_greater { filter_eq { all_rows ; venue ; johannesburg } ; runs ; 140 } = true | select the rows whose venue record fuzzily matches to johannesburg . for the runs records of these rows , most of them are greater than 140 . | 2 | 2 | {'most_greater_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, 'venue_4': 4, 'johannesburg_5': 5, 'runs_6': 6, '140_7': 7} | {'most_greater_1': 'most_greater', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'venue_4': 'venue', 'johannesburg_5': 'johannesburg', 'runs_6': 'runs', '140_7': '140'} | {'most_greater_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'venue_4': [0], 'johannesburg_5': [0], 'runs_6': [1], '140_7': [1]} | ['runs', 'balls', 'batsman', 'versus', 'venue', 'date', 'strike rate'] | [['172', '151', 'cb wishart', 'namibia', 'harare', '10 - 02 - 2003', '113.91'], ['152', '151', 'sr tendulkar', 'namibia', 'pietermaritzburg', '23 - 02 - 2003', '100.66'], ['143', '125', 'a symonds', 'pakistan', 'johannesburg', '11 - 02 - 2003', '114.40'], ['143', '141', 'hh gibbs', 'new zealand', 'johannesburg', '16 - 02 - 2003', '101.42'], ['141', '125', 'sb styris', 'sri lanka', 'bloemfontein', '10 - 02 - 2003', '112.80'], ['146', '121', 'rt ponting', 'india', 'johannesburg', '23 - 03 - 2003', '115.70'], ['134', '132', 'sp fleming', 'south africa', 'johannesburg', '16 - 02 - 2003', '101.52'], ['134', '129', 'kjj van noortwijk', 'namibia', 'bloemfontein', '03 - 03 - 2003', '103.88'], ['124', '129', 'ms atapattu', 'south africa', 'durban', '03 - 03 - 2003', '96.12'], ['121', '142', 'jf kloppenburg', 'namibia', 'bloemfontein', '03 - 03 - 2003', '85.21']] |
1982 pga tour | https://en.wikipedia.org/wiki/1982_PGA_Tour | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14640525-4.html.csv | ordinal | tom watson had the 2nd highest number of wins in the 1982 pga tour . | {'row': '2', 'col': '5', 'order': '2', 'col_other': '2', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'wins', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; wins ; 2 }'}, 'player'], 'result': 'tom watson', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; wins ; 2 } ; player }'}, 'tom watson'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; wins ; 2 } ; player } ; tom watson } = true', 'tointer': 'select the row whose wins record of all rows is 2nd maximum . the player record of this row is tom watson .'} | eq { hop { nth_argmax { all_rows ; wins ; 2 } ; player } ; tom watson } = true | select the row whose wins record of all rows is 2nd maximum . the player record of this row is tom watson . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'wins_5': 5, '2_6': 6, 'player_7': 7, 'tom watson_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', 'wins_5': 'wins', '2_6': '2', 'player_7': 'player', 'tom watson_8': 'tom watson'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'wins_5': [0], '2_6': [0], 'player_7': [1], 'tom watson_8': [2]} | ['rank', 'player', 'country', 'earnings', 'wins'] | [['1', 'jack nicklaus', 'united states', '3992070', '71'], ['2', 'tom watson', 'united states', '2866383', '32'], ['3', 'lee trevino', 'united states', '2643085', '28'], ['4', 'raymond floyd', 'united states', '2178796', '18'], ['5', 'tom weiskopf', 'united states', '2158631', '16']] |
1960 vfl season | https://en.wikipedia.org/wiki/1960_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10775890-9.html.csv | aggregation | the total crowd in all vfl games on 18th june 1960 was 123128 . | {'scope': 'all', 'col': '6', 'type': 'sum', 'result': '123128', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'crowd'], 'result': '123128', 'ind': 0, 'tostr': 'sum { all_rows ; crowd }'}, '123128'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; crowd } ; 123128 } = true', 'tointer': 'the sum of the crowd record of all rows is 123128 .'} | round_eq { sum { all_rows ; crowd } ; 123128 } = true | the sum of the crowd record of all rows is 123128 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'crowd_4': 4, '123128_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'crowd_4': 'crowd', '123128_5': '123128'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'crowd_4': [0], '123128_5': [1]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['fitzroy', '10.8 ( 68 )', 'melbourne', '16.14 ( 110 )', 'brunswick street oval', '23233', '18 june 1960'], ['essendon', '13.10 ( 88 )', 'south melbourne', '12.15 ( 87 )', 'windy hill', '21000', '18 june 1960'], ['carlton', '18.12 ( 120 )', 'north melbourne', '8.15 ( 63 )', 'princes park', '13897', '18 june 1960'], ['st kilda', '7.13 ( 55 )', 'hawthorn', '8.19 ( 67 )', 'junction oval', '23900', '18 june 1960'], ['richmond', '11.17 ( 83 )', 'geelong', '12.11 ( 83 )', 'punt road oval', '13000', '18 june 1960'], ['footscray', '8.19 ( 67 )', 'collingwood', '10.14 ( 74 )', 'western oval', '28098', '18 june 1960']] |
new york city mayoral elections | https://en.wikipedia.org/wiki/New_York_City_mayoral_elections | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1108394-24.html.csv | comparative | mario biaggi received more votes in brooklyn than albert h blumenthal . | {'row_1': '7', 'row_2': '5', 'col': '4', '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', '1973 democratic initial primary', 'mario biaggi'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose 1973 democratic initial primary record fuzzily matches to mario biaggi .', 'tostr': 'filter_eq { all_rows ; 1973 democratic initial primary ; mario biaggi }'}, 'brooklyn'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; 1973 democratic initial primary ; mario biaggi } ; brooklyn }', 'tointer': 'select the rows whose 1973 democratic initial primary record fuzzily matches to mario biaggi . take the brooklyn record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', '1973 democratic initial primary', 'albert h blumenthal'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose 1973 democratic initial primary record fuzzily matches to albert h blumenthal .', 'tostr': 'filter_eq { all_rows ; 1973 democratic initial primary ; albert h blumenthal }'}, 'brooklyn'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; 1973 democratic initial primary ; albert h blumenthal } ; brooklyn }', 'tointer': 'select the rows whose 1973 democratic initial primary record fuzzily matches to albert h blumenthal . take the brooklyn record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; 1973 democratic initial primary ; mario biaggi } ; brooklyn } ; hop { filter_eq { all_rows ; 1973 democratic initial primary ; albert h blumenthal } ; brooklyn } } = true', 'tointer': 'select the rows whose 1973 democratic initial primary record fuzzily matches to mario biaggi . take the brooklyn record of this row . select the rows whose 1973 democratic initial primary record fuzzily matches to albert h blumenthal . take the brooklyn record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; 1973 democratic initial primary ; mario biaggi } ; brooklyn } ; hop { filter_eq { all_rows ; 1973 democratic initial primary ; albert h blumenthal } ; brooklyn } } = true | select the rows whose 1973 democratic initial primary record fuzzily matches to mario biaggi . take the brooklyn record of this row . select the rows whose 1973 democratic initial primary record fuzzily matches to albert h blumenthal . take the brooklyn 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, '1973 democratic initial primary_7': 7, 'mario biaggi_8': 8, 'brooklyn_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, '1973 democratic initial primary_11': 11, 'albert h blumenthal_12': 12, 'brooklyn_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', '1973 democratic initial primary_7': '1973 democratic initial primary', 'mario biaggi_8': 'mario biaggi', 'brooklyn_9': 'brooklyn', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', '1973 democratic initial primary_11': '1973 democratic initial primary', 'albert h blumenthal_12': 'albert h blumenthal', 'brooklyn_13': 'brooklyn'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], '1973 democratic initial primary_7': [0], 'mario biaggi_8': [0], 'brooklyn_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], '1973 democratic initial primary_11': [1], 'albert h blumenthal_12': [1], 'brooklyn_13': [3]} | ['1973 democratic initial primary', 'manhattan', 'the bronx', 'brooklyn', 'queens', 'richmond', 'total', '%'] | [['abraham beame', '45901', '41508', '96621', '73520', '8912', '266462', '34 %'], ['abraham beame', '26 %', '27 %', '41 %', '40 %', '42 %', '266462', '34 %'], ['herman badillo', '73676', '55432', '57836', '33990', '2902', '223836', '29 %'], ['herman badillo', '41 %', '36 %', '25 %', '19 %', '14 %', '223836', '29 %'], ['albert h blumenthal', '41906', '18400', '31913', '28960', '2062', '123241', '16 %'], ['albert h blumenthal', '23 %', '12 %', '14 %', '16 %', '10 %', '123241', '16 %'], ['mario biaggi', '17830', '39462', '48352', '45992', '7524', '159160', '21 %'], ['mario biaggi', '10 %', '25 %', '21 %', '25 %', '35 %', '159160', '21 %']] |
fairuz fauzy | https://en.wikipedia.org/wiki/Fairuz_Fauzy | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1628093-1.html.csv | superlative | in the 2011 season the most number of races was 18 . | {'scope': 'subset', 'col_superlative': '4', 'row_superlative': '13', 'value_mentioned': 'yes', 'max_or_min': 'max', 'other_col': '1', 'subset': {'col': '1', 'criterion': 'equal', 'value': '2011'}} | {'func': 'eq', 'args': [{'func': 'max', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'season', '2011'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; season ; 2011 }', 'tointer': 'select the rows whose season record is equal to 2011 .'}, 'races'], 'result': '18', 'ind': 1, 'tostr': 'max { filter_eq { all_rows ; season ; 2011 } ; races }', 'tointer': 'select the rows whose season record is equal to 2011 . the maximum races record of these rows is 18 .'}, '18'], 'result': True, 'ind': 2, 'tostr': 'eq { max { filter_eq { all_rows ; season ; 2011 } ; races } ; 18 } = true', 'tointer': 'select the rows whose season record is equal to 2011 . the maximum races record of these rows is 18 .'} | eq { max { filter_eq { all_rows ; season ; 2011 } ; races } ; 18 } = true | select the rows whose season record is equal to 2011 . the maximum races record of these rows is 18 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'max_1': 1, 'filter_eq_0': 0, 'all_rows_4': 4, 'season_5': 5, '2011_6': 6, 'races_7': 7, '18_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'max_1': 'max', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'season_5': 'season', '2011_6': '2011', 'races_7': 'races', '18_8': '18'} | {'eq_2': [3], 'result_3': [], 'max_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'season_5': [0], '2011_6': [0], 'races_7': [1], '18_8': [2]} | ['season', 'series', 'team', 'races', 'wins', 'poles', 'f / laps', 'podiums', 'points', 'pos'] | [['2003', 'british formula three season', 'promatecme uk / team syr', '24', '0', '0', '0', '0', '30.5', '16th'], ['2004', 'british formula three season', 'menu f3 motorsport / p1 racing', '24', '0', '0', '0', '1', '49', '12th'], ['2005', 'gp2 series', 'dams', '23', '0', '0', '0', '0', '0', '24th'], ['2005 - 06', 'a1 grand prix', 'a1 team malaysia', '4', '0', '0', '0', '0', '8', '5th ( 1 )'], ['2006', 'gp2 series', 'super nova racing', '21', '0', '0', '0', '0', '0', '25th'], ['2007', 'formula one', 'spyker f1', 'test driver', 'test driver', 'test driver', 'test driver', 'test driver', 'test driver', 'test driver'], ['2007 - 08', 'a1 grand prix', 'a1 team malaysia', '6', '0', '0', '0', '0', '7', '15th ( 1 )'], ['2008', 'gp2 asia series', 'super nova racing', '10', '1', '0', '1', '3', '24', '4th'], ['2008 - 09', 'a1 grand prix', 'a1 team malaysia', '12', '1', '1', '1', '3', '43', '6th ( 1 )'], ['2009', 'formula renault 3.5 series', 'mofaz racing', '17', '1', '1', '1', '5', '98', '2nd'], ['2010', 'formula one', 'lotus racing', 'test driver', 'test driver', 'test driver', 'test driver', 'test driver', 'test driver', 'test driver'], ['2011', 'gp2 asia series', 'super nova racing', '4', '0', '0', '0', '0', '1', '14th'], ['2011', 'gp2 series', 'super nova racing', '18', '0', '0', '0', '0', '5', '18th'], ['2011', 'formula one', 'lotus renault gp', 'test driver', 'test driver', 'test driver', 'test driver', 'test driver', 'test driver', 'test driver'], ['2011', 'formula renault 3.5 series', 'mofaz racing', '4', '0', '0', '0', '1', '15', '16th']] |
united states house of representatives elections , 1888 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1888 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1431459-6.html.csv | comparative | both william h. perry and william elliot , who ran in the 1888 united states house of representatives elections were first seated in the year 1884 . | {'row_1': '4', 'row_2': '7', 'col': '4', 'col_other': '2', 'relation': 'equal', 'record_mentioned': 'yes', 'diff_result': None} | {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'incumbent', 'william h perry'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose incumbent record fuzzily matches to william h perry .', 'tostr': 'filter_eq { all_rows ; incumbent ; william h perry }'}, 'first elected'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; incumbent ; william h perry } ; first elected }', 'tointer': 'select the rows whose incumbent record fuzzily matches to william h perry . take the first elected record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'incumbent', 'william elliott'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose incumbent record fuzzily matches to william elliott .', 'tostr': 'filter_eq { all_rows ; incumbent ; william elliott }'}, 'first elected'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; incumbent ; william elliott } ; first elected }', 'tointer': 'select the rows whose incumbent record fuzzily matches to william elliott . take the first elected record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'eq { hop { filter_eq { all_rows ; incumbent ; william h perry } ; first elected } ; hop { filter_eq { all_rows ; incumbent ; william elliott } ; first elected } }', 'tointer': 'select the rows whose incumbent record fuzzily matches to william h perry . take the first elected record of this row . select the rows whose incumbent record fuzzily matches to william elliott . take the first elected record of this row . the first record is equal to the second record .'}, {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'incumbent', 'william h perry'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose incumbent record fuzzily matches to william h perry .', 'tostr': 'filter_eq { all_rows ; incumbent ; william h perry }'}, 'first elected'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; incumbent ; william h perry } ; first elected }', 'tointer': 'select the rows whose incumbent record fuzzily matches to william h perry . take the first elected record of this row .'}, '1884'], 'result': True, 'ind': 5, 'tostr': 'eq { hop { filter_eq { all_rows ; incumbent ; william h perry } ; first elected } ; 1884 }', 'tointer': 'the first elected record of the first row is 1884 .'}, {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'incumbent', 'william elliott'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose incumbent record fuzzily matches to william elliott .', 'tostr': 'filter_eq { all_rows ; incumbent ; william elliott }'}, 'first elected'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; incumbent ; william elliott } ; first elected }', 'tointer': 'select the rows whose incumbent record fuzzily matches to william elliott . take the first elected record of this row .'}, '1884'], 'result': True, 'ind': 6, 'tostr': 'eq { hop { filter_eq { all_rows ; incumbent ; william elliott } ; first elected } ; 1884 }', 'tointer': 'the first elected record of the second row is 1884 .'}], 'result': True, 'ind': 7, 'tostr': 'and { eq { hop { filter_eq { all_rows ; incumbent ; william h perry } ; first elected } ; 1884 } ; eq { hop { filter_eq { all_rows ; incumbent ; william elliott } ; first elected } ; 1884 } }', 'tointer': 'the first elected record of the first row is 1884 . the first elected record of the second row is 1884 .'}], 'result': True, 'ind': 8, 'tostr': 'and { eq { hop { filter_eq { all_rows ; incumbent ; william h perry } ; first elected } ; hop { filter_eq { all_rows ; incumbent ; william elliott } ; first elected } } ; and { eq { hop { filter_eq { all_rows ; incumbent ; william h perry } ; first elected } ; 1884 } ; eq { hop { filter_eq { all_rows ; incumbent ; william elliott } ; first elected } ; 1884 } } } = true', 'tointer': 'select the rows whose incumbent record fuzzily matches to william h perry . take the first elected record of this row . select the rows whose incumbent record fuzzily matches to william elliott . take the first elected record of this row . the first record is equal to the second record . the first elected record of the first row is 1884 . the first elected record of the second row is 1884 .'} | and { eq { hop { filter_eq { all_rows ; incumbent ; william h perry } ; first elected } ; hop { filter_eq { all_rows ; incumbent ; william elliott } ; first elected } } ; and { eq { hop { filter_eq { all_rows ; incumbent ; william h perry } ; first elected } ; 1884 } ; eq { hop { filter_eq { all_rows ; incumbent ; william elliott } ; first elected } ; 1884 } } } = true | select the rows whose incumbent record fuzzily matches to william h perry . take the first elected record of this row . select the rows whose incumbent record fuzzily matches to william elliott . take the first elected record of this row . the first record is equal to the second record . the first elected record of the first row is 1884 . the first elected record of the second row is 1884 . | 13 | 9 | {'and_8': 8, 'result_9': 9, 'eq_4': 4, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_10': 10, 'incumbent_11': 11, 'william h perry_12': 12, 'first elected_13': 13, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_14': 14, 'incumbent_15': 15, 'william elliott_16': 16, 'first elected_17': 17, 'and_7': 7, 'eq_5': 5, '1884_18': 18, 'eq_6': 6, '1884_19': 19} | {'and_8': 'and', 'result_9': 'true', 'eq_4': 'eq', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_10': 'all_rows', 'incumbent_11': 'incumbent', 'william h perry_12': 'william h perry', 'first elected_13': 'first elected', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_14': 'all_rows', 'incumbent_15': 'incumbent', 'william elliott_16': 'william elliott', 'first elected_17': 'first elected', 'and_7': 'and', 'eq_5': 'eq', '1884_18': '1884', 'eq_6': 'eq', '1884_19': '1884'} | {'and_8': [9], 'result_9': [], 'eq_4': [8], 'num_hop_2': [4, 5], 'filter_str_eq_0': [2], 'all_rows_10': [0], 'incumbent_11': [0], 'william h perry_12': [0], 'first elected_13': [2], 'num_hop_3': [4, 6], 'filter_str_eq_1': [3], 'all_rows_14': [1], 'incumbent_15': [1], 'william elliott_16': [1], 'first elected_17': [3], 'and_7': [8], 'eq_5': [7], '1884_18': [5], 'eq_6': [7], '1884_19': [6]} | ['district', 'incumbent', 'party', 'first elected', 'result'] | [['south carolina 1', 'samuel dibble', 'democratic', '1882', 're - elected'], ['south carolina 2', 'george d tillman', 'democratic', '1878', 're - elected'], ['south carolina 3', 'james s cothran', 'democratic', '1886', 're - elected'], ['south carolina 4', 'william h perry', 'democratic', '1884', 're - elected'], ['south carolina 5', 'john j hemphill', 'democratic', '1882', 're - elected'], ['south carolina 6', 'george w dargan', 'democratic', '1882', 're - elected'], ['south carolina 7', 'william elliott', 'democratic', '1884', 're - elected']] |
1958 formula one season | https://en.wikipedia.org/wiki/1958_Formula_One_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1140110-6.html.csv | superlative | in the 1958 formula one season , the vi glover trophy race is ranked the earliest . | {'scope': 'all', 'col_superlative': '3', 'row_superlative': '1', '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', 'date'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; date }'}, 'race name'], 'result': 'vi glover trophy', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; date } ; race name }'}, 'vi glover trophy'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmin { all_rows ; date } ; race name } ; vi glover trophy } = true', 'tointer': 'select the row whose date record of all rows is minimum . the race name record of this row is vi glover trophy .'} | eq { hop { argmin { all_rows ; date } ; race name } ; vi glover trophy } = true | select the row whose date record of all rows is minimum . the race name record of this row is vi glover trophy . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'date_5': 5, 'race name_6': 6, 'vi glover trophy_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'date_5': 'date', 'race name_6': 'race name', 'vi glover trophy_7': 'vi glover trophy'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'date_5': [0], 'race name_6': [1], 'vi glover trophy_7': [2]} | ['race name', 'circuit', 'date', 'winning driver', 'constructor', 'report'] | [['vi glover trophy', 'goodwood', '7 april', 'mike hawthorn', 'ferrari', 'report'], ['viii gran premio di siracusa', 'syracuse', '13 april', 'luigi musso', 'ferrari', 'report'], ['xiii barc aintree 200', 'aintree', '19 april', 'stirling moss', 'cooper - climax', 'report'], ['x brdc international trophy', 'silverstone', '3 may', 'peter collins', 'ferrari', 'report'], ['vi grand prix de caen', 'caen', '20 july', 'stirling moss', 'cooper - climax', 'report']] |
list of benedictine colleges and universities | https://en.wikipedia.org/wiki/List_of_Benedictine_colleges_and_universities | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14014822-1.html.csv | majority | of the benedictine colleges and universities , most of the schools have an enrollment of over 1000 . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'greater_than', 'value': '1000', 'subset': None} | {'func': 'most_greater', 'args': ['all_rows', 'enrollment', '1000'], 'result': True, 'ind': 0, 'tointer': 'for the enrollment records of all rows , most of them are greater than 1000 .', 'tostr': 'most_greater { all_rows ; enrollment ; 1000 } = true'} | most_greater { all_rows ; enrollment ; 1000 } = true | for the enrollment records of all rows , most of them are greater than 1000 . | 1 | 1 | {'most_greater_0': 0, 'result_1': 1, 'all_rows_2': 2, 'enrollment_3': 3, '1000_4': 4} | {'most_greater_0': 'most_greater', 'result_1': 'true', 'all_rows_2': 'all_rows', 'enrollment_3': 'enrollment', '1000_4': '1000'} | {'most_greater_0': [1], 'result_1': [], 'all_rows_2': [0], 'enrollment_3': [0], '1000_4': [0]} | ['school', 'city', 'state', 'enrollment', 'founded'] | [['belmont abbey college', 'belmont', 'north carolina', '1320', '1876'], ['benedictine college', 'atchison', 'kansas', '1855', '1858'], ['benedictine university', 'lisle', 'illinois', '6857', '1887'], ['benedictine university at springfield', 'springfield', 'illinois', '981', '1929'], ['college of saint benedict', 'st joseph', 'minnesota', '2042', '1913'], ['college of saint scholastica', 'duluth', 'minnesota', '3309', '1912'], ['conception seminary college', 'conception', 'missouri', '108', '1886'], ['mount marty college', 'yankton', 'south dakota', '1100', '1936'], ['saint anselm college', 'goffstown', 'new hampshire', '2000', '1889'], ["saint gregory 's university", 'shawnee', 'oklahoma', '800', '1875'], ["saint john 's university", 'collegeville', 'minnesota', '1886', '1857'], ['saint joseph seminary college', 'covington', 'louisiana', '171', '1889'], ['saint leo university', 'saint leo', 'florida', '1628', '1889'], ["saint martin 's university", 'lacey', 'washington', '1650', '1895'], ['saint vincent college', 'latrobe', 'pennsylvania', '1848', '1846'], ['thomas more college ( kentucky )', 'crestview hills', 'kentucky', '1500', '1921'], ['university of mary', 'bismarck', 'north dakota', '2900', '1959'], ['colegio san carlos', 'bogotã ¡', 'colombia', '1400', '1960']] |
united states house of representatives elections , 2006 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_2006 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1805191-2.html.csv | majority | most of the incumbents to the united states house of representatives were from the republican party . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'republican', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'party', 'republican'], 'result': True, 'ind': 0, 'tointer': 'for the party records of all rows , most of them fuzzily match to republican .', 'tostr': 'most_eq { all_rows ; party ; republican } = true'} | most_eq { all_rows ; party ; republican } = true | for the party records of all rows , most of them fuzzily match to republican . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'party_3': 3, 'republican_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'party_3': 'party', 'republican_4': 'republican'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'party_3': [0], 'republican_4': [0]} | ['district', 'incumbent', 'party', 'first elected', 'results', 'candidates'] | [['alabama 1', 'jo bonner', 'republican', '2002', 're - elected', 'jo bonner ( r ) 68.1 % vivian beckerle ( d ) 31.8 %'], ['alabama 2', 'terry everett', 'republican', '1992', 're - elected', 'terry everett ( r ) 69.5 % chuck james ( d ) 30.4 %'], ['alabama 4', 'robert aderholt', 'republican', '1996', 're - elected', 'robert aderholt ( r ) 70.2 % barbara bobo ( d ) 29.7 %'], ['alabama 5', 'robert cramer', 'democratic', '1990', 're - elected', 'robert cramer ( d ) unopposed'], ['alabama 6', 'spencer bachus', 'republican', '1992', 're - elected', 'spencer bachus ( r ) unopposed']] |
weightlifting at the 1999 pan american games | https://en.wikipedia.org/wiki/Weightlifting_at_the_1999_Pan_American_Games | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11279593-11.html.csv | comparative | patricia sosa scored a lower total than nancy niro in the women 's weightlifting competition of the 1999 pan american games . | {'row_1': '5', 'row_2': '2', 'col': '5', 'col_other': '1', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'name', 'patricia sosa ( esa )'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose name record fuzzily matches to patricia sosa ( esa ) .', 'tostr': 'filter_eq { all_rows ; name ; patricia sosa ( esa ) }'}, 'total ( kg )'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; name ; patricia sosa ( esa ) } ; total ( kg ) }', 'tointer': 'select the rows whose name record fuzzily matches to patricia sosa ( esa ) . take the total ( kg ) record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'name', 'nancy niro ( can )'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose name record fuzzily matches to nancy niro ( can ) .', 'tostr': 'filter_eq { all_rows ; name ; nancy niro ( can ) }'}, 'total ( kg )'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; name ; nancy niro ( can ) } ; total ( kg ) }', 'tointer': 'select the rows whose name record fuzzily matches to nancy niro ( can ) . take the total ( kg ) record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; name ; patricia sosa ( esa ) } ; total ( kg ) } ; hop { filter_eq { all_rows ; name ; nancy niro ( can ) } ; total ( kg ) } } = true', 'tointer': 'select the rows whose name record fuzzily matches to patricia sosa ( esa ) . take the total ( kg ) record of this row . select the rows whose name record fuzzily matches to nancy niro ( can ) . take the total ( kg ) record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; name ; patricia sosa ( esa ) } ; total ( kg ) } ; hop { filter_eq { all_rows ; name ; nancy niro ( can ) } ; total ( kg ) } } = true | select the rows whose name record fuzzily matches to patricia sosa ( esa ) . take the total ( kg ) record of this row . select the rows whose name record fuzzily matches to nancy niro ( can ) . take the total ( kg ) record of this row . the first record is less than the second record . | 5 | 5 | {'less_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'name_7': 7, 'patricia sosa ( esa )_8': 8, 'total (kg)_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'name_11': 11, 'nancy niro ( can )_12': 12, 'total (kg)_13': 13} | {'less_4': 'less', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'name_7': 'name', 'patricia sosa ( esa )_8': 'patricia sosa ( esa )', 'total (kg)_9': 'total ( kg )', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'name_11': 'name', 'nancy niro ( can )_12': 'nancy niro ( can )', 'total (kg)_13': 'total ( kg )'} | {'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'name_7': [0], 'patricia sosa ( esa )_8': [0], 'total (kg)_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'name_11': [1], 'nancy niro ( can )_12': [1], 'total (kg)_13': [3]} | ['name', 'bodyweight', 'snatch', 'clean & jerk', 'total ( kg )'] | [['maryse turcotte ( can )', '57.56', '87.5', '112.5', '200.0'], ['nancy niro ( can )', '57.92', '87.5', '105.0', '192.5'], ['soraya jiménez ( mex )', '57.19', '85.0', '105.0', '190.0'], ['ruth rivera ( pur )', '57.56', '67.5', '95.0', '162.5'], ['patricia sosa ( esa )', '57.41', '67.5', '92.5', '160.0'], ['liliana garcía ( ven )', '57.32', '80.0', '105.0', '-']] |
brad gumm | https://en.wikipedia.org/wiki/Brad_Gumm | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17445678-2.html.csv | unique | only the match against cj fernandes was resolved as a draw . | {'scope': 'all', 'row': '15', 'col': '4', 'col_other': '3', 'criterion': 'equal', 'value': 'draw', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'method', 'draw'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose method record fuzzily matches to draw .', 'tostr': 'filter_eq { all_rows ; method ; draw }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; method ; draw } }', 'tointer': 'select the rows whose method record fuzzily matches to draw . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'method', 'draw'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose method record fuzzily matches to draw .', 'tostr': 'filter_eq { all_rows ; method ; draw }'}, 'opponent'], 'result': 'cj fernandes', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; method ; draw } ; opponent }'}, 'cj fernandes'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; method ; draw } ; opponent } ; cj fernandes }', 'tointer': 'the opponent record of this unqiue row is cj fernandes .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; method ; draw } } ; eq { hop { filter_eq { all_rows ; method ; draw } ; opponent } ; cj fernandes } } = true', 'tointer': 'select the rows whose method record fuzzily matches to draw . there is only one such row in the table . the opponent record of this unqiue row is cj fernandes .'} | and { only { filter_eq { all_rows ; method ; draw } } ; eq { hop { filter_eq { all_rows ; method ; draw } ; opponent } ; cj fernandes } } = true | select the rows whose method record fuzzily matches to draw . there is only one such row in the table . the opponent record of this unqiue row is cj fernandes . | 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, 'opponent_9': 9, 'cj fernandes_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', 'opponent_9': 'opponent', 'cj fernandes_10': 'cj fernandes'} | {'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], 'opponent_9': [2], 'cj fernandes_10': [3]} | ['res', 'record', 'opponent', 'method', 'event', 'round', 'location'] | [['loss', '10 - 6 - 1', 'hank weis', 'submission ( guillotine choke )', 'kickdown - sturgis', '1', 'south dakota , united states'], ['loss', '10 - 5 - 1', 'don ortega', 'decision', 'pnrf - explosion', '2', 'mexico'], ['loss', '10 - 4 - 1', 'heath sims', 'submission ( strikes )', 'sf 2 - on the move', '2', 'oregon , united states'], ['loss', '10 - 3 - 1', 'carlos condit', 'tko', 'rof 11 - bring it on', '1', 'colorado , united states'], ['nc', '10 - 2 - 1', 'doug evans', 'no contest - evans kicking in groin', 'ifc - global domination', '1', 'colorado , united states'], ['win', '10 - 2 - 1', 'antoine skinner', 'submission ( omo plata )', 'battleground 1 - war cry', '2', 'illinois , united states'], ['win', '9 - 2 - 1', 'michael buell', 'tko', 'samp - showdown at mcgee park', '2', 'mexico'], ['win', '8 - 2 - 1', 'eric davila', 'decision', 'rof 5 - predators', '3', 'colorado , united states'], ['win', '7 - 2 - 1', 'brad blackburn', 'decision', 'mfc 4 - new groundz', '3', 'alberta , canada'], ['loss', '6 - 2 - 1', 'joe stevenson', 'decision', 'up 1 - ultimate pankration 1', '3', 'california , united states'], ['win', '6 - 1 - 1', 'joe stevenson', 'decision', 'gc 5 - rumble in the rockies', '3', 'colorado , united states'], ['win', '5 - 1 - 1', 'brian dunn', 'submission ( rear naked choke )', 'msf - total destruction', '2', 'south dakota , united states'], ['win', '4 - 1 - 1', 'jeff lindsay', 'decision', 'rof 3 - ring of fire 3', '3', 'colorado , united states'], ['win', '3 - 1 - 1', 'clint rather', 'submission ( rear naked choke )', 'msf - night of thunder', '1', 'colorado , united states'], ['draw', '2 - 1 - 1', 'cj fernandes', 'draw', 'ufc 27', '2', 'louisiana , united states'], ['loss', '2 - 1', 'shonie carter', 'decision', 'ufc 24', '2', 'louisiana , united states'], ['win', '2 - 0', 'dario valdez', 'submission', 'bri 5 - bas rutten invitational 5', '1', 'colorado , united states'], ['win', '1 - 0', 'jason mckeever', 'submission ( arm bar )', 'bri 1 - bas rutten invitational 1', '1', 'united states']] |
w.d. & h.o. wills tournament | https://en.wikipedia.org/wiki/W.D._%26_H.O._Wills_Tournament | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15942377-1.html.csv | majority | the majority of winners of the w.d. & h.o. wills tournament are from england . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'england', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'country', 'england'], 'result': True, 'ind': 0, 'tointer': 'for the country records of all rows , most of them fuzzily match to england .', 'tostr': 'most_eq { all_rows ; country ; england } = true'} | most_eq { all_rows ; country ; england } = true | for the country records of all rows , most of them fuzzily match to england . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'country_3': 3, 'england_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'country_3': 'country', 'england_4': 'england'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'country_3': [0], 'england_4': [0]} | ['year', 'venue', 'winner', 'country', 'score'] | [['1974', 'kings norton golf club', 'neil coles', 'england', '283 ( - 5 )'], ['1973', 'kings norton golf club', 'charles coody', 'united states', '281 ( - 7 )'], ['1972', 'dalmahoy golf club', 'peter thomson', 'australia', '270 ( - 14 )'], ['1971', 'dalmahoy golf club', 'bernard hunt', 'england', '276 ( - 8 )'], ['1970', 'dalmahoy golf club', 'tony jacklin', 'england', '267 ( - 17 )'], ['1969', 'moor park golf club', 'bernard gallacher', 'scotland', '275'], ['1968', 'pannal golf club', 'peter butler', 'england', '281']] |
1985 - 86 philadelphia flyers season | https://en.wikipedia.org/wiki/1985%E2%80%9386_Philadelphia_Flyers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14320222-6.html.csv | comparative | the 1985-86 philadelphia flyers had more points after game 63 than after game 57 . | {'row_1': '12', 'row_2': '6', 'col': '6', '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', 'game', '63'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose game record fuzzily matches to 63 .', 'tostr': 'filter_eq { all_rows ; game ; 63 }'}, 'points'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; game ; 63 } ; points }', 'tointer': 'select the rows whose game record fuzzily matches to 63 . take the points record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'game', '57'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose game record fuzzily matches to 57 .', 'tostr': 'filter_eq { all_rows ; game ; 57 }'}, 'points'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; game ; 57 } ; points }', 'tointer': 'select the rows whose game record fuzzily matches to 57 . take the points record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; game ; 63 } ; points } ; hop { filter_eq { all_rows ; game ; 57 } ; points } } = true', 'tointer': 'select the rows whose game record fuzzily matches to 63 . take the points record of this row . select the rows whose game record fuzzily matches to 57 . take the points record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; game ; 63 } ; points } ; hop { filter_eq { all_rows ; game ; 57 } ; points } } = true | select the rows whose game record fuzzily matches to 63 . take the points record of this row . select the rows whose game record fuzzily matches to 57 . take the points 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, 'game_7': 7, '63_8': 8, 'points_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'game_11': 11, '57_12': 12, 'points_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', 'game_7': 'game', '63_8': '63', 'points_9': 'points', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'game_11': 'game', '57_12': '57', 'points_13': 'points'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'game_7': [0], '63_8': [0], 'points_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'game_11': [1], '57_12': [1], 'points_13': [3]} | ['game', 'february', 'opponent', 'score', 'record', 'points'] | [['52', '1', 'quebec nordiques', '2 - 2 ot', '35 - 15 - 2', '72'], ['53', '6', 'st louis blues', '4 - 3', '36 - 15 - 2', '74'], ['54', '8', 'minnesota north stars', '3 - 3 ot', '36 - 15 - 3', '75'], ['55', '9', 'chicago black hawks', '2 - 2 ot', '36 - 15 - 4', '76'], ['56', '12', 'buffalo sabres', '4 - 0', '37 - 15 - 4', '78'], ['57', '13', 'new york islanders', '6 - 3', '38 - 15 - 4', '80'], ['58', '15', 'montreal canadiens', '3 - 5', '38 - 16 - 4', '80'], ['59', '17', 'winnipeg jets', '8 - 4', '39 - 16 - 4', '82'], ['60', '20', 'los angeles kings', '5 - 3', '40 - 16 - 4', '84'], ['61', '22', 'washington capitals', '3 - 1', '41 - 16 - 4', '86'], ['62', '27', 'calgary flames', '4 - 7', '41 - 17 - 4', '86'], ['63', '28', 'vancouver canucks', '1 - 3', '41 - 18 - 4', '86']] |
1983 world ice hockey championships | https://en.wikipedia.org/wiki/1983_World_Ice_Hockey_Championships | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14148130-1.html.csv | majority | the largest number of games were won by fewer than 10 points . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'less_than', 'value': '10', 'subset': None} | {'func': 'most_less', 'args': ['all_rows', 'points', '10'], 'result': True, 'ind': 0, 'tointer': 'for the points records of all rows , most of them are less than 10 .', 'tostr': 'most_less { all_rows ; points ; 10 } = true'} | most_less { all_rows ; points ; 10 } = true | for the points records of all rows , most of them are less than 10 . | 1 | 1 | {'most_less_0': 0, 'result_1': 1, 'all_rows_2': 2, 'points_3': 3, '10_4': 4} | {'most_less_0': 'most_less', 'result_1': 'true', 'all_rows_2': 'all_rows', 'points_3': 'points', '10_4': '10'} | {'most_less_0': [1], 'result_1': [], 'all_rows_2': [0], 'points_3': [0], '10_4': [0]} | ['games', 'drawn', 'lost', 'points difference', 'points'] | [['7', '0', '0', '41 - 07', '14'], ['7', '0', '2', '26 - 16', '10'], ['7', '1', '2', '30 - 15', '9'], ['7', '1', '2', '26 - 21', '9'], ['7', '1', '3', '17 - 23', '7'], ['7', '0', '5', '19 - 28', '4'], ['7', '1', '5', '20 - 28', '3'], ['7', '0', '7', '05 - 46', '0']] |
mountain peaks of the rocky mountains | https://en.wikipedia.org/wiki/Mountain_peaks_of_the_Rocky_Mountains | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12069382-4.html.csv | comparative | pikes peak is located further north than blanca peak is . | {'row_1': '4', 'row_2': '5', 'col': '5', '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', 'mountain peak', 'pikes peak'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose mountain peak record fuzzily matches to pikes peak .', 'tostr': 'filter_eq { all_rows ; mountain peak ; pikes peak }'}, 'location'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; mountain peak ; pikes peak } ; location }', 'tointer': 'select the rows whose mountain peak record fuzzily matches to pikes peak . take the location record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'mountain peak', 'blanca peak'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose mountain peak record fuzzily matches to blanca peak .', 'tostr': 'filter_eq { all_rows ; mountain peak ; blanca peak }'}, 'location'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; mountain peak ; blanca peak } ; location }', 'tointer': 'select the rows whose mountain peak record fuzzily matches to blanca peak . take the location record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; mountain peak ; pikes peak } ; location } ; hop { filter_eq { all_rows ; mountain peak ; blanca peak } ; location } } = true', 'tointer': 'select the rows whose mountain peak record fuzzily matches to pikes peak . take the location record of this row . select the rows whose mountain peak record fuzzily matches to blanca peak . take the location record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; mountain peak ; pikes peak } ; location } ; hop { filter_eq { all_rows ; mountain peak ; blanca peak } ; location } } = true | select the rows whose mountain peak record fuzzily matches to pikes peak . take the location record of this row . select the rows whose mountain peak record fuzzily matches to blanca peak . take the location 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, 'mountain peak_7': 7, 'pikes peak_8': 8, 'location_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'mountain peak_11': 11, 'blanca peak_12': 12, 'location_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', 'mountain peak_7': 'mountain peak', 'pikes peak_8': 'pikes peak', 'location_9': 'location', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'mountain peak_11': 'mountain peak', 'blanca peak_12': 'blanca peak', 'location_13': 'location'} | {'greater_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'mountain peak_7': [0], 'pikes peak_8': [0], 'location_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'mountain peak_11': [1], 'blanca peak_12': [1], 'location_13': [3]} | ['rank', 'mountain peak', 'region', 'mountain range', 'location'] | [['1', 'fishers peak', 'colorado', 'raton mesa', '37.0982 degreen 104.4628 degreew'], ['2', 'east spanish peak', 'colorado', 'spanish peaks', '37.3934 degreen 104.9201 degreew'], ['3', 'west spanish peak', 'colorado', 'spanish peaks', '37.3756 degreen 104.9934 degreew'], ['4', 'pikes peak', 'colorado', 'front range', '38.8405 degreen 105.0442 degreew'], ['5', 'blanca peak', 'colorado', 'sangre de cristo mountains', '37.5775 degreen 105.4856 degreew'], ['6', 'mount harvard', 'colorado', 'sawatch range', '38.9244 degreen 106.3207 degreew'], ['7', 'mount elbert', 'colorado', 'sawatch range', '39.1178 degreen 106.4454 degreew']] |
central indiana athletic conference | https://en.wikipedia.org/wiki/Central_Indiana_Athletic_Conference | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18765652-2.html.csv | count | eight of the schools joined the conference in 1932 . | {'scope': 'all', 'criterion': 'equal', 'value': '1932', 'result': '7', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'year joined', '1932'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose year joined record is equal to 1932 .', 'tostr': 'filter_eq { all_rows ; year joined ; 1932 }'}], 'result': '7', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; year joined ; 1932 } }', 'tointer': 'select the rows whose year joined record is equal to 1932 . the number of such rows is 7 .'}, '7'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; year joined ; 1932 } } ; 7 } = true', 'tointer': 'select the rows whose year joined record is equal to 1932 . the number of such rows is 7 .'} | eq { count { filter_eq { all_rows ; year joined ; 1932 } } ; 7 } = true | select the rows whose year joined record is equal to 1932 . the number of such rows is 7 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_eq_0': 0, 'all_rows_4': 4, 'year joined_5': 5, '1932_6': 6, '7_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'year joined_5': 'year joined', '1932_6': '1932', '7_7': '7'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'year joined_5': [0], '1932_6': [0], '7_7': [2]} | ['school', 'location', 'mascot', 'county', 'year joined', 'previous conference', 'year left'] | [['huntington north', 'huntington', 'vikings', '35 huntington', '1932', 'independents', '1974'], ['noblesville', 'noblesville', 'millers', '29 hamilton', '1932', 'hamilton county', '1938'], ['peru', 'peru', 'tigers', '52 miami', '1932', 'independents', '1998'], ['rochester', 'rochester', 'zebras', '25 fulton', '1932', 'north central', '1964'], ['tipton', 'tipton', 'blue devils', '80 tipton', '1932', 'independents', '1998'], ['wabash', 'wabash', 'apaches', '85 wabash', '1932', 'independents', '2006'], ['windfall', 'windfall', 'dragons', '80 tipton', '1932', 'independents', '1936'], ['warsaw', 'warsaw', 'tigers', '43 kosciusko', '1933 1953', 'independents northeastern in', '1946 1964'], ['plymouth', 'plymouth', 'pilgrims', '50 marshall', '1935', 'independents', '1964'], ['muncie burris', 'muncie', 'owls', '18 delaware', '1938', 'independents', '1976'], ['hartford city', 'hartford city', 'airedales', '05 blackford', '1945', 'independents', '1968'], ['monticello', 'monticello', 'tioga indians', '91 white', '1945', 'independents', '1963'], ['south side', 'fort wayne', 'archers', '02 allen', '1945', 'fort wayne', '1947']] |
supernatural ( season 6 ) | https://en.wikipedia.org/wiki/Supernatural_%28season_6%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27892955-1.html.csv | ordinal | in season 6 of supernatural , the 2nd highest number of viewers was for the episode titled weekend at bobby 's . | {'row': '4', 'col': '8', 'order': '2', 'col_other': '3', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'us viewers ( million )', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; us viewers ( million ) ; 2 }'}, 'title'], 'result': "weekend at bobby 's", 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; us viewers ( million ) ; 2 } ; title }'}, "weekend at bobby 's"], 'result': True, 'ind': 2, 'tostr': "eq { hop { nth_argmax { all_rows ; us viewers ( million ) ; 2 } ; title } ; weekend at bobby 's } = true", 'tointer': "select the row whose us viewers ( million ) record of all rows is 2nd maximum . the title record of this row is weekend at bobby 's ."} | eq { hop { nth_argmax { all_rows ; us viewers ( million ) ; 2 } ; title } ; weekend at bobby 's } = true | select the row whose us viewers ( million ) record of all rows is 2nd maximum . the title record of this row is weekend at bobby 's . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'us viewers (million)_5': 5, '2_6': 6, 'title_7': 7, "weekend at bobby 's_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', 'us viewers (million)_5': 'us viewers ( million )', '2_6': '2', 'title_7': 'title', "weekend at bobby 's_8": "weekend at bobby 's"} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'us viewers (million)_5': [0], '2_6': [0], 'title_7': [1], "weekend at bobby 's_8": [2]} | ['no in series', 'no in season', 'title', 'directed by', 'written by', 'original air date', 'production code', 'us viewers ( million )'] | [['105', '1', 'exile on main st', 'phil sgriccia', 'sera gamble', 'september 24 , 2010', '3x6052', '2.90'], ['106', '2', 'two and a half men', 'john showalter', 'adam glass', 'october 1 , 2010', '3x6053', '2.33'], ['107', '3', 'the third man', 'robert singer', 'ben edlund', 'october 8 , 2010', '3x6054', '2.16'], ['108', '4', "weekend at bobby 's", 'jensen ackles', 'andrew dabb & daniel loflin', 'october 15 , 2010', '3x6051', '2.84'], ['109', '5', 'live free or twihard', 'rod hardy', 'brett matthews', 'october 22 , 2010', '3x6056', '2.47'], ['111', '7', 'family matters', 'guy bee', 'andrew dabb & daniel loflin', 'november 5 , 2010', '3x6057', '2.46'], ['112', '8', 'all dogs go to heaven', 'phil sgriccia', 'adam glass', 'november 12 , 2010', '3x6058', '2.09'], ['113', '9', 'clap your hands if you believe', 'john showalter', 'ben edlund', 'november 19 , 2010', '3x6059', '1.94'], ['114', '10', 'caged heat', 'robert singer', 'brett matthews & jenny klein', 'december 3 , 2010', '3x6060', '2.15'], ['115', '11', 'appointment in samarra', 'mike rohl', 'sera gamble & robert singer', 'december 10 , 2010', '3x6061', '2.27'], ['116', '12', 'like a virgin', 'phil sgriccia', 'adam glass', 'february 4 , 2011', '3x6062', '2.25'], ['117', '13', 'unforgiven', 'david barrett', 'andrew dabb & daniel loflin', 'february 11 , 2011', '3x6063', '1.97'], ['118', '14', 'mannequin 3 : the reckoning', 'jeannot szwarc', 'eric charmelo & nicole snyder', 'february 18 , 2011', '3x6064', '2.25'], ['119', '15', 'the french mistake', 'charles beeson', 'ben edlund', 'february 25 , 2011', '3x6065', '2.18'], ['120', '16', 'and then there were none', 'mike rohl', 'brett matthews', 'march 4 , 2011', '3x6066', '2.14'], ['121', '17', 'my heart will go on', 'phil sgriccia', 'eric charmelo & nicole snyder', 'april 15 , 2011', '3x6068', '2.26'], ['123', '19', 'mommy dearest', 'john showalter', 'adam glass', 'april 29 , 2011', '3x6069', '2.01'], ['124', '20', 'the man who would be king', 'ben edlund', 'ben edlund', 'may 6 , 2011', '3x6070', '2.11'], ['125', '21', 'let it bleed', 'john showalter', 'sera gamble', 'may 20 , 2011', '3x6071', '2.02']] |
cruizer - class brig - sloop | https://en.wikipedia.org/wiki/Cruizer-class_brig-sloop | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16304334-5.html.csv | majority | all of the cruizer-class brig-sloops were ordered on the date of 1 october 1806 . | {'scope': 'all', 'col': '2', 'most_or_all': 'all', 'criterion': 'equal', 'value': '1 october 1806', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'ordered', '1 october 1806'], 'result': True, 'ind': 0, 'tointer': 'for the ordered records of all rows , all of them fuzzily match to 1 october 1806 .', 'tostr': 'all_eq { all_rows ; ordered ; 1 october 1806 } = true'} | all_eq { all_rows ; ordered ; 1 october 1806 } = true | for the ordered records of all rows , all of them fuzzily match to 1 october 1806 . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'ordered_3': 3, '1 october 1806_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'ordered_3': 'ordered', '1 october 1806_4': '1 october 1806'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'ordered_3': [0], '1 october 1806_4': [0]} | ['name', 'ordered', 'builder', 'launched', 'fate'] | [['derwent', '1 october 1806', 'isaac blackburn , turnchapel , plymouth', '23 may 1807', 'sold 1817'], ['eclair', '1 october 1806', 'matthew warren , brightlingsea , essex', '8 july 1807', 'broken up 1831'], ['eclipse', '1 october 1806', 'john king , dover', '4 august 1807', 'sold for mercantile use 1815'], ['barracouta', '1 october 1806', 'jabez bailey , ipswich', '6 july 1807', 'sold 1815'], ['nautilus', '1 october 1806', 'james betts , mistleythorn', '5 august 1807', 'broken up 1823'], ['pilot', '1 october 1806', 'robert guillaume , northam , southampton', '6 august 1807', 'sold 1828'], ['sparrowhawk', '1 october 1806', 'matthew warren , brightlingsea , essex', '20 august 1807', 'sold 1841'], ['zenobia', '1 october 1806', "josiah & thomas brindley , king 's lynn", '7 october 1807', 'sold 1835'], ['magnet', '1 october 1806', 'robert guillaume , northam , southampton', '19 october 1807', 'wrecked 1809'], ['peruvian', '1 october 1806', 'george parsons , warsash', '26 april 1808', 'broken up 1830']] |
rajgarh ( lok sabha constituency ) | https://en.wikipedia.org/wiki/Rajgarh_%28Lok_Sabha_constituency%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18517323-1.html.csv | count | there are two constituents representing the guna district in the rajgarh ( lok sabha constituency ) . | {'scope': 'all', 'criterion': 'equal', 'value': 'guna', 'result': '2', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'district', 'guna'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose district record fuzzily matches to guna .', 'tostr': 'filter_eq { all_rows ; district ; guna }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; district ; guna } }', 'tointer': 'select the rows whose district record fuzzily matches to guna . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; district ; guna } } ; 2 } = true', 'tointer': 'select the rows whose district record fuzzily matches to guna . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; district ; guna } } ; 2 } = true | select the rows whose district record fuzzily matches to guna . 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, 'district_5': 5, 'guna_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', 'district_5': 'district', 'guna_6': 'guna', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'district_5': [0], 'guna_6': [0], '2_7': [2]} | ['constituency number', 'name', 'reserved for ( sc / st / none )', 'district', 'number of electorates ( 2009 )'] | [['30', 'chachoura', 'none', 'guna', '149857'], ['31', 'raghogarh', 'none', 'guna', '146874'], ['160', 'narsinghgarh', 'none', 'rajgarh', '162429'], ['161', 'biaora', 'none', 'rajgarh', '162340'], ['162', 'rajgarh', 'none', 'rajgarh', '161219'], ['163', 'khilchipur', 'none', 'rajgarh', '169412'], ['164', 'sarangpur', 'sc', 'rajgarh', '140001'], ['165', 'susner', 'none', 'shajapur', '169378']] |
yoji anjo | https://en.wikipedia.org/wiki/Yoji_Anjo | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17445522-3.html.csv | aggregation | yoji anjo 's matches lasted an average of 1.5 rounds . | {'scope': 'all', 'col': '6', 'type': 'average', 'result': '1.5', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'round'], 'result': '1.5', 'ind': 0, 'tostr': 'avg { all_rows ; round }'}, '1.5'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; round } ; 1.5 } = true', 'tointer': 'the average of the round record of all rows is 1.5 .'} | round_eq { avg { all_rows ; round } ; 1.5 } = true | the average of the round record of all rows is 1.5 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'round_4': 4, '1.5_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'round_4': 'round', '1.5_5': '1.5'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'round_4': [0], '1.5_5': [1]} | ['res', 'record', 'opponent', 'method', 'event', 'round', 'time', 'location'] | [['loss', '0 - 5 - 1', 'ryan gracie', 'submission ( armbar )', 'pride shockwave 2004', '1', '8:33', 'saitama , japan'], ['draw', '0 - 4 - 1', 'gia chirragishvili', 'draw', 'deep - 1st impact', '3', '5:00', 'nagoya , japan'], ['loss', '0 - 4', 'matt lindland', 'tko ( strikes )', 'ufc 29', '1', '2:58', 'tokyo , japan'], ['loss', '0 - 3', 'murilo bustamante', 'submission ( arm triangle choke )', 'ufc 25', '2', '0:31', 'tokyo , japan'], ['loss', '0 - 2', 'david abbott', 'decision', 'ufc japan', '1', '15:00', 'yokohama , japan'], ['loss', '0 - 1', 'sean alvarez', 'submission ( punches )', 'u - japan', '1', '34:26', 'japan']] |
1967 boston red sox season | https://en.wikipedia.org/wiki/1967_Boston_Red_Sox_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12195635-2.html.csv | unique | the only game played by the boston red sox in april 1967 that had less than 1500 in attendance was the game played on april 18th . | {'scope': 'all', 'row': '6', 'col': '5', 'col_other': '1', 'criterion': 'less_than', 'value': '1500', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'attendance', '1500'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose attendance record is less than 1500 .', 'tostr': 'filter_less { all_rows ; attendance ; 1500 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_less { all_rows ; attendance ; 1500 } }', 'tointer': 'select the rows whose attendance record is less than 1500 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'attendance', '1500'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose attendance record is less than 1500 .', 'tostr': 'filter_less { all_rows ; attendance ; 1500 }'}, 'date'], 'result': 'april 18', 'ind': 2, 'tostr': 'hop { filter_less { all_rows ; attendance ; 1500 } ; date }'}, 'april 18'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_less { all_rows ; attendance ; 1500 } ; date } ; april 18 }', 'tointer': 'the date record of this unqiue row is april 18 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_less { all_rows ; attendance ; 1500 } } ; eq { hop { filter_less { all_rows ; attendance ; 1500 } ; date } ; april 18 } } = true', 'tointer': 'select the rows whose attendance record is less than 1500 . there is only one such row in the table . the date record of this unqiue row is april 18 .'} | and { only { filter_less { all_rows ; attendance ; 1500 } } ; eq { hop { filter_less { all_rows ; attendance ; 1500 } ; date } ; april 18 } } = true | select the rows whose attendance record is less than 1500 . there is only one such row in the table . the date record of this unqiue row is april 18 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_less_0': 0, 'all_rows_6': 6, 'attendance_7': 7, '1500_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'date_9': 9, 'april 18_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_less_0': 'filter_less', 'all_rows_6': 'all_rows', 'attendance_7': 'attendance', '1500_8': '1500', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'date_9': 'date', 'april 18_10': 'april 18'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_less_0': [1, 2], 'all_rows_6': [0], 'attendance_7': [0], '1500_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'date_9': [2], 'april 18_10': [3]} | ['date', 'opponent', 'score', 'loss', 'attendance', 'record'] | [['april 12', 'white sox', '5 - 4', 'buzhardt ( 0 - 1 )', '8324', '1 - 0'], ['april 13', 'white sox', '8 - 5', 'fischer ( 0 - 1 )', '3607', '1 - 1'], ['april 14', 'yankees', '3 - 0', 'ford ( 0 - 1 )', '14375', '2 - 1'], ['april 15', 'yankees', '1 - 0', 'bennett ( 0 - 1 )', '12035', '2 - 2'], ['april 16', 'yankees', '7 - 6 ( 18 )', 'stange ( 0 - 1 )', '19290', '2 - 3'], ['april 18', 'white sox', '5 - 2', 'brandon ( 0 - 1 )', '1313', '2 - 4'], ['april 21', 'yankees', '6 - 1', 'stottlemyre ( 2 - 1 )', '25603', '3 - 4'], ['april 22', 'yankees', '5 - 4', 'womack ( 0 - 1 )', '8189', '4 - 4'], ['april 23', 'yankees', '7 - 5', 'santiago ( 1 - 1 )', '18041', '4 - 5'], ['april 24', 'senators', '7 - 4', 'lines ( 0 - 1 )', '2235', '5 - 5'], ['april 25', 'senators', '9 - 3', 'richert ( 0 - 3 )', '3367', '6 - 5'], ['april 28', 'athletics', '3 - 0', 'hunter ( 2 - 1 )', '9026', '7 - 5'], ['april 29', 'athletics', '11 - 10 ( 15 )', 'aker ( 2 - 1 )', '9724', '8 - 5'], ['april 30', 'athletics', '1 - 0', 'brandon ( 0 - 2 )', '31450', '8 - 6']] |
stefan johansson | https://en.wikipedia.org/wiki/Stefan_Johansson | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1226329-2.html.csv | ordinal | 1986 was the year in which stefan johansson scored the fourth highest amount of points in his career . | {'row': '7', 'col': '5', 'order': '4', 'col_other': '1', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'pts', '4'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; pts ; 4 }'}, 'year'], 'result': '1986', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; pts ; 4 } ; year }'}, '1986'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; pts ; 4 } ; year } ; 1986 } = true', 'tointer': 'select the row whose pts record of all rows is 4th maximum . the year record of this row is 1986 .'} | eq { hop { nth_argmax { all_rows ; pts ; 4 } ; year } ; 1986 } = true | select the row whose pts record of all rows is 4th maximum . the year record of this row is 1986 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'num_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'pts_5': 5, '4_6': 6, 'year_7': 7, '1986_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'num_hop_1': 'num_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'pts_5': 'pts', '4_6': '4', 'year_7': 'year', '1986_8': '1986'} | {'eq_2': [3], 'result_3': [], 'num_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'pts_5': [0], '4_6': [0], 'year_7': [1], '1986_8': [2]} | ['year', 'entrant', 'chassis', 'engine', 'pts'] | [['1980', 'shadow cars', 'shadow dn11', 'ford cosworth dfv v8', '0'], ['1983', 'spirit racing', 'spirit 201c', 'honda v6 ( t / c )', '0'], ['1984', 'tyrrell racing organisation', 'tyrrell 012', 'ford cosworth dfy v8', '3'], ['1984', 'toleman group motorsport', 'toleman tg184', 'hart straight - 4 ( t / c )', '3'], ['1985', 'tyrrell racing organisation', 'tyrrell 012', 'ford cosworth dfy v8', '26'], ['1985', 'scuderia ferrari', 'ferrari 156 / 85', 'ferrari v6 ( t / c )', '26'], ['1986', 'scuderia ferrari', 'ferrari f1 / 86', 'ferrari v6 ( t / c )', '23'], ['1987', 'marlboro mclaren international', 'mclaren mp4 / 3', 'tag v6 ( t / c )', '30'], ['1988', 'ligier loto', 'ligier js31', 'judd v8', '0'], ['1989', 'moneytron onyx', 'onyx ore - 1', 'ford cosworth dfr v8', '6'], ['1990', 'moneytron onyx', 'onyx ore - 1', 'ford cosworth dfr v8', '0'], ['1991', 'automobiles gonfaronnaises sportives', 'ags jh25b', 'ford cosworth dfr v8', '0'], ['1991', 'footwork grand prix international', 'footwork fa12', 'porsche v12', '0'], ['1991', 'footwork grand prix international', 'footwork fa12c', 'ford cosworth dfr v8', '0']] |
2010 - 11 pittsburgh panthers men 's basketball team | https://en.wikipedia.org/wiki/2010%E2%80%9311_Pittsburgh_Panthers_men%27s_basketball_team | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-29050051-3.html.csv | superlative | gary mcghee is the heaviest man on the panther 's men 's basketball team . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '4', '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', 'weight ( lb )'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; weight ( lb ) }'}, 'name'], 'result': 'gary mcghee', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; weight ( lb ) } ; name }'}, 'gary mcghee'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; weight ( lb ) } ; name } ; gary mcghee } = true', 'tointer': 'select the row whose weight ( lb ) record of all rows is maximum . the name record of this row is gary mcghee .'} | eq { hop { argmax { all_rows ; weight ( lb ) } ; name } ; gary mcghee } = true | select the row whose weight ( lb ) record of all rows is maximum . the name record of this row is gary mcghee . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'weight ( lb )_5': 5, 'name_6': 6, 'gary mcghee_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'weight ( lb )_5': 'weight ( lb )', 'name_6': 'name', 'gary mcghee_7': 'gary mcghee'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'weight ( lb )_5': [0], 'name_6': [1], 'gary mcghee_7': [2]} | ['name', '-', 'position', 'height', 'weight ( lb )', 'year', 'hometown', 'previous school'] | [['gilbert brown', '5', 'forward', 'ft6in ( m )', '215', '2 senior ( rs )', 'harrisburg , pa', 'south kent school'], ['isaiah epps', '2', 'guard', 'ft2in ( m )', '175', '2 freshman', 'plainfield , nj', 'hargrave military academy / plainfield hs'], ['ashton gibbs', '12', 'guard', 'ft2in ( m )', '190', '1 junior', 'scotch plains , nj', 'seton hall prep'], ['gary mcghee', '52', 'center', 'ft11in ( m )', '250', '2 senior', 'anderson , in', 'highland hs'], ['jj moore', '44', 'forward', 'ft6in ( m )', '200', '2 freshman', 'brentwood , ny', 'south kent school / brentwood hs'], ['aron nwankwo', '15', 'forward', 'ft7in ( m )', '200', '2 freshman', 'baltimore , md', 'baltimore city college'], ['lamar patterson', '21', 'guard / forward', 'ft5in ( m )', '220', '1 freshman ( rs )', 'lancaster , pa', "st benedict 's prep / jp mccaskey hs"], ['jj richardson', '55', 'forward / center', 'ft7in ( m )', '235', '1 sophomore', 'missouri city , tx', 'fort bend hightower hs'], ['nick rivers', '14', 'guard', 'ft0in ( m )', '180', '1 senior', 'phoenix , az', 'brophy college prep'], ['nasir robinson', '35', 'forward', 'ft5in ( m )', '220', '1 junior', 'chester , pa', 'chester hs'], ['dante taylor', '11', 'forward', 'ft9in ( m )', '240', '1 sophomore', 'greenburgh , ny', 'national christian academy ( md )'], ['brad wanamaker', '22', 'guard', 'ft4in ( m )', '210', '2 senior', 'philadelphia , pa', 'roman catholic hs'], ['travon woodall', '1', 'guard', 'ft11in ( m )', '190', '1 sophomore ( rs )', 'brooklyn , ny - paterson , nj', 'st anthony hs'], ['cameron wright', '3', 'guard', 'ft4in ( m )', '200', '1 freshman', 'cleveland , oh', 'benedictine hs']] |
my love : essential collection | https://en.wikipedia.org/wiki/My_Love%3A_Essential_Collection | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18969843-5.html.csv | majority | most releases of my love were done on a 2 cd set . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'equal', 'value': '2cd', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'format', '2cd'], 'result': True, 'ind': 0, 'tointer': 'for the format records of all rows , most of them fuzzily match to 2cd .', 'tostr': 'most_eq { all_rows ; format ; 2cd } = true'} | most_eq { all_rows ; format ; 2cd } = true | for the format records of all rows , most of them fuzzily match to 2cd . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'format_3': 3, '2cd_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'format_3': 'format', '2cd_4': '2cd'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'format_3': [0], '2cd_4': [0]} | ['region', 'date', 'label', 'format', 'catalog'] | [['europe', 'october 24 , 2008', 'columbia', 'cd', '88697400492'], ['europe', 'october 24 , 2008', 'columbia', '2cd', '88697400502'], ['australia', 'october 27 , 2008', 'columbia', '2cd', '88697374522'], ['north america', 'october 28 , 2008', 'columbia', 'cd', '88697411432'], ['north america', 'october 28 , 2008', 'columbia', '2cd', '88697374522'], ['australia', 'july 11 , 2011', 'legacy recordings', '2cd', '88697936772'], ['europe', 'july 15 , 2011', 'legacy recordings', '2cd', '88697936772'], ['north america', 'august 29 , 2011', 'legacy recordings', '3cd', '886979487321'], ['north america', 'september 13 , 2011', 'legacy recordings', '2cd', '886979487222']] |
2007 - 08 new jersey devils season | https://en.wikipedia.org/wiki/2007%E2%80%9308_New_Jersey_Devils_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11902366-5.html.csv | superlative | the game on december 23 had a larger crowd attendance than any other game . | {'scope': 'all', 'col_superlative': '6', 'row_superlative': '11', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'attendance'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; attendance }'}, 'date'], 'result': 'december 23', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; attendance } ; date }'}, 'december 23'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; attendance } ; date } ; december 23 } = true', 'tointer': 'select the row whose attendance record of all rows is maximum . the date record of this row is december 23 .'} | eq { hop { argmax { all_rows ; attendance } ; date } ; december 23 } = true | select the row whose attendance record of all rows is maximum . the date record of this row is december 23 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'attendance_5': 5, 'date_6': 6, 'december 23_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'attendance_5': 'attendance', 'date_6': 'date', 'december 23_7': 'december 23'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'attendance_5': [0], 'date_6': [1], 'december 23_7': [2]} | ['date', 'visitor', 'score', 'home', 'decision', 'attendance', 'record'] | [['december 2', 'atlanta', '2 - 3', 'new jersey', 'brodeur', '14978', '14 - 10 - 2'], ['december 5', 'boston', '3 - 4', 'new jersey', 'brodeur', '14012', '15 - 10 - 2'], ['december 7', 'washington', '2 - 3', 'new jersey', 'brodeur', '16265', '16 - 10 - 2'], ['december 9', 'new jersey', '0 - 1', 'ny rangers', 'brodeur', '18200', '16 - 10 - 3'], ['december 10', 'new jersey', '2 - 3', 'washington', 'weekes', '10719', '16 - 11 - 3'], ['december 13', 'new jersey', '3 - 1', 'boston', 'brodeur', '12064', '17 - 11 - 3'], ['december 15', 'phoenix', '4 - 1', 'new jersey', 'brodeur', '16636', '17 - 12 - 3'], ['december 16', 'philadelphia', '2 - 4', 'new jersey', 'brodeur', '16687', '18 - 12 - 3'], ['december 18', 'new jersey', '0 - 5', 'vancouver', 'brodeur', '18630', '18 - 13 - 3'], ['december 21', 'new jersey', '3 - 1', 'edmonton', 'brodeur', '16839', '19 - 13 - 3'], ['december 23', 'new jersey', '1 - 0', 'calgary', 'brodeur', '19289', '20 - 13 - 3'], ['december 28', 'buffalo', '1 - 2', 'new jersey', 'brodeur', '17625', '21 - 13 - 3'], ['december 29', 'new jersey', '2 - 5', 'ny islanders', 'brodeur', '16234', '21 - 14 - 3']] |
1940 in brazilian football | https://en.wikipedia.org/wiki/1940_in_Brazilian_football | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15349635-2.html.csv | superlative | the highest number of points was when palestra itália - sp was the team . | {'scope': 'all', 'col_superlative': '3', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '2', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'points'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; points }'}, 'team'], 'result': 'palestra itália - sp', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; points } ; team }'}, 'palestra itália - sp'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; points } ; team } ; palestra itália - sp } = true', 'tointer': 'select the row whose points record of all rows is maximum . the team record of this row is palestra itália - sp .'} | eq { hop { argmax { all_rows ; points } ; team } ; palestra itália - sp } = true | select the row whose points record of all rows is maximum . the team record of this row is palestra itália - sp . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'points_5': 5, 'team_6': 6, 'palestra itália - sp_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'points_5': 'points', 'team_6': 'team', 'palestra itália - sp_7': 'palestra itália - sp'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'points_5': [0], 'team_6': [1], 'palestra itália - sp_7': [2]} | ['position', 'team', 'points', 'played', 'drawn', 'lost', 'against', 'difference'] | [['1', 'palestra itália - sp', '33', '20', '3', '2', '19', '34'], ['2', 'portuguesa', '30', '20', '4', '3', '24', '22'], ['3', 'ypiranga - sp', '27', '20', '1', '6', '37', '19'], ['4', 'corinthians', '26', '20', '2', '6', '31', '23'], ['5', 'portuguesa santista', '25', '20', '3', '6', '40', '13'], ['6', 'são paulo', '19', '20', '1', '10', '41', '1'], ['7', 'santos', '18', '20', '4', '9', '49', '2'], ['8', 'são paulo railway', '16', '20', '6', '9', '50', '- 6'], ['9', 'hespanha', '10', '20', '0', '15', '47', '- 22'], ['10', 'comercial - sp', '9', '20', '3', '14', '72', '- 47'], ['11', 'juventus', '7', '20', '1', '16', '68', '- 39']] |
2007 icc world twenty20 statistics | https://en.wikipedia.org/wiki/2007_ICC_World_Twenty20_statistics | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13219504-10.html.csv | majority | the majority of 2007 icc world twenty20 game statistics were taken in the johannesburg venue . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'johannesburg', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'venue', 'johannesburg'], 'result': True, 'ind': 0, 'tointer': 'for the venue records of all rows , most of them fuzzily match to johannesburg .', 'tostr': 'most_eq { all_rows ; venue ; johannesburg } = true'} | most_eq { all_rows ; venue ; johannesburg } = true | for the venue records of all rows , most of them fuzzily match to johannesburg . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'venue_3': 3, 'Johannesburg_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'venue_3': 'venue', 'Johannesburg_4': 'johannesburg'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'venue_3': [0], 'Johannesburg_4': [0]} | ['wicket', 'runs', 'partnerships', 'venue', 'date'] | [['1st', '145', 'chris gayle / devon smith', 'johannesburg', '2007 - 09 - 11'], ['2nd', '95', 'devon smith / shivnarine chanderpaul', 'johannesburg', '2007 - 09 - 13'], ['3rd', '120', 'herschelle gibbs / justin kemp', 'johannesburg', '2007 - 09 - 11'], ['4th', '101', 'younis khan / shoaib malik', 'johannesburg', '2007 - 09 - 17'], ['5th', '119', 'shoaib malik / misbah - ul - haq', 'johannesburg', '2007 - 09 - 18'], ['6th', '73', 'craig mcmillan / jacob oram', 'johannesburg', '2007 - 09 - 16'], ['7th', '45', 'jehan mubarak / gayan wijekoon', 'johannesburg', '2007 - 09 - 14'], ['8th', '40', 'jehan mubarak / chaminda vaas', 'newlands , cape town', '2007 - 09 - 17'], ['9th', '27', 'jimmy kamande / rajesh bhudia', 'durban', '2007 - 09 - 12'], ['10th', '18', 'majid haq / dewald nel', 'durban', '2007 - 09 - 12']] |
qf 4 inch mk v naval gun | https://en.wikipedia.org/wiki/QF_4_inch_Mk_V_naval_gun | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-16439764-1.html.csv | count | for the qf 4 inch mk v naval gun , when the max height ( ft ) is at least 20000 , there are 3 times when the m / v ft / s is at least 2200 . | {'scope': 'subset', 'criterion': 'greater_than_eq', 'value': '2200', 'result': '3', 'col': '2', 'subset': {'col': '7', 'criterion': 'greater_than_eq', 'value': '20000'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater_eq', 'args': [{'func': 'filter_greater_eq', 'args': ['all_rows', 'max height ( ft )', '20000'], 'result': None, 'ind': 0, 'tostr': 'filter_greater_eq { all_rows ; max height ( ft ) ; 20000 }', 'tointer': 'select the rows whose max height ( ft ) record is greater than or equal to 20000 .'}, 'm / v ft / s', '2200'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose max height ( ft ) record is greater than or equal to 20000 . among these rows , select the rows whose m / v ft / s record is greater than or equal to 2200 .', 'tostr': 'filter_greater_eq { filter_greater_eq { all_rows ; max height ( ft ) ; 20000 } ; m / v ft / s ; 2200 }'}], 'result': '3', 'ind': 2, 'tostr': 'count { filter_greater_eq { filter_greater_eq { all_rows ; max height ( ft ) ; 20000 } ; m / v ft / s ; 2200 } }', 'tointer': 'select the rows whose max height ( ft ) record is greater than or equal to 20000 . among these rows , select the rows whose m / v ft / s record is greater than or equal to 2200 . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_greater_eq { filter_greater_eq { all_rows ; max height ( ft ) ; 20000 } ; m / v ft / s ; 2200 } } ; 3 } = true', 'tointer': 'select the rows whose max height ( ft ) record is greater than or equal to 20000 . among these rows , select the rows whose m / v ft / s record is greater than or equal to 2200 . the number of such rows is 3 .'} | eq { count { filter_greater_eq { filter_greater_eq { all_rows ; max height ( ft ) ; 20000 } ; m / v ft / s ; 2200 } } ; 3 } = true | select the rows whose max height ( ft ) record is greater than or equal to 20000 . among these rows , select the rows whose m / v ft / s record is greater than or equal to 2200 . the number of such rows is 3 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_greater_eq_1': 1, 'filter_greater_eq_0': 0, 'all_rows_5': 5, 'max height (ft)_6': 6, '20000_7': 7, 'm / v ft / s_8': 8, '2200_9': 9, '3_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_greater_eq_1': 'filter_greater_eq', 'filter_greater_eq_0': 'filter_greater_eq', 'all_rows_5': 'all_rows', 'max height (ft)_6': 'max height ( ft )', '20000_7': '20000', 'm / v ft / s_8': 'm / v ft / s', '2200_9': '2200', '3_10': '3'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_greater_eq_1': [2], 'filter_greater_eq_0': [1], 'all_rows_5': [0], 'max height (ft)_6': [0], '20000_7': [0], 'm / v ft / s_8': [1], '2200_9': [1], '3_10': [3]} | ['gun', 'm / v ft / s', 'shell ( lb )', 'time to ft ( m ) at 25 degree ( seconds )', 'time to ft ( m ) at 40 degree ( seconds )', 'time to ft ( m ) at 55 degree ( seconds )', 'max height ( ft )'] | [['qf 13 pdr 9 cwt', '1990', '12.5', '10.1', '15.5', '22.1', '19000'], ['qf 12 pdr 12 cwt', '2200', '12.5', '9.1', '14.1', '19.1', '20000'], ['qf 3 inch 20 cwt 1914', '2500', '12.5', '8.3', '12.6', '16.3', '23500'], ['qf 3 inch 20 cwt 1916', '2000', '16', '9.2', '13.7', '18.8', '22000'], ['qf 4inch mk v world war i', '2350', '31 ( 3 crh )', '4.4', '9.6', '12.3', '28750']] |
anthony thomas ( american football ) | https://en.wikipedia.org/wiki/Anthony_Thomas_%28American_football%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14013061-2.html.csv | ordinal | anthony thomas has the second highest rushing attempts of the top 5 michigan wolverines runningback single season performances . | {'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', 'attempts', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; attempts ; 2 }'}, 'name'], 'result': 'anthony thomas', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; attempts ; 2 } ; name }'}, 'anthony thomas'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; attempts ; 2 } ; name } ; anthony thomas } = true', 'tointer': 'select the row whose attempts record of all rows is 2nd maximum . the name record of this row is anthony thomas .'} | eq { hop { nth_argmax { all_rows ; attempts ; 2 } ; name } ; anthony thomas } = true | select the row whose attempts record of all rows is 2nd maximum . the name record of this row is anthony thomas . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'attempts_5': 5, '2_6': 6, 'name_7': 7, 'anthony thomas_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', 'attempts_5': 'attempts', '2_6': '2', 'name_7': 'name', 'anthony thomas_8': 'anthony thomas'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'attempts_5': [0], '2_6': [0], 'name_7': [1], 'anthony thomas_8': [2]} | ['rank', 'name', 'attempts', 'net yds', 'yds / att', 'year'] | [['1', 'tim biakabutuka', '303', '1818', '6.0', '1995'], ['2', 'anthony thomas', '319', '1733', '5.4', '2000'], ['3', 'jamie morris', '282', '1703', '6.0', '1987'], ['4', 'denard robinson', '256', '1702', '6.6', '2010'], ['5', 'chris perry', '338', '1674', '5.0', '2003']] |
ídolos brazil ( season 5 ) | https://en.wikipedia.org/wiki/%C3%8Ddolos_Brazil_%28season_5%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27615445-1.html.csv | unique | peninha was the only guest judge whose episode 's audition was held in.sao paolo . | {'scope': 'all', 'row': '7', 'col': '2', 'col_other': '5', 'criterion': 'equal', 'value': 'são paulo', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'audition city', 'são paulo'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose audition city record fuzzily matches to são paulo .', 'tostr': 'filter_eq { all_rows ; audition city ; são paulo }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; audition city ; são paulo } }', 'tointer': 'select the rows whose audition city record fuzzily matches to são paulo . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'audition city', 'são paulo'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose audition city record fuzzily matches to são paulo .', 'tostr': 'filter_eq { all_rows ; audition city ; são paulo }'}, 'guest fourth judge'], 'result': 'peninha', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; audition city ; são paulo } ; guest fourth judge }'}, 'peninha'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; audition city ; são paulo } ; guest fourth judge } ; peninha }', 'tointer': 'the guest fourth judge record of this unqiue row is peninha .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; audition city ; são paulo } } ; eq { hop { filter_eq { all_rows ; audition city ; são paulo } ; guest fourth judge } ; peninha } } = true', 'tointer': 'select the rows whose audition city record fuzzily matches to são paulo . there is only one such row in the table . the guest fourth judge record of this unqiue row is peninha .'} | and { only { filter_eq { all_rows ; audition city ; são paulo } } ; eq { hop { filter_eq { all_rows ; audition city ; são paulo } ; guest fourth judge } ; peninha } } = true | select the rows whose audition city record fuzzily matches to são paulo . there is only one such row in the table . the guest fourth judge record of this unqiue row is peninha . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'audition city_7': 7, 'são paulo_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'guest fourth judge_9': 9, 'peninha_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'audition city_7': 'audition city', 'são paulo_8': 'são paulo', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'guest fourth judge_9': 'guest fourth judge', 'peninha_10': 'peninha'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'audition city_7': [0], 'são paulo_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'guest fourth judge_9': [2], 'peninha_10': [3]} | ['episode air date', 'audition city', 'audition date', 'audition venue', 'guest fourth judge'] | [['june 10 , 2010', 'florianópolis', 'april 10 , 2010', 'nego quirido sambadrome', 'luiza possi'], ['june 15 , 2010', 'florianópolis', 'april 10 , 2010', 'nego quirido sambadrome', 'luiza possi'], ['june 15 , 2010', 'rio de janeiro', 'april 17 , 2010', 'joão havelange olympic stadium', 'marcelo d2'], ['june 17 , 2010', 'rio de janeiro', 'april 17 , 2010', 'joão havelange olympic stadium', 'marcelo d2'], ['june 22 , 2010', 'fortaleza', 'march 27 , 2010', 'paulo sarasate gymnasium', 'reginaldo rossi'], ['june 24 , 2010', 'fortaleza', 'march 27 , 2010', 'paulo sarasate gymnasium', 'reginaldo rossi'], ['june 29 , 2010', 'são paulo', 'april 24 , 2010', 'anhembi sambadrome', 'peninha']] |
2007 - 08 commonwealth bank series statistics | https://en.wikipedia.org/wiki/2007%E2%80%9308_Commonwealth_Bank_Series_statistics | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15700367-3.html.csv | comparative | adam gilchrist played more innings than matthew hayden played . | {'row_1': '1', 'row_2': '2', 'col': '2', 'col_other': '1', 'relation': 'greater', 'record_mentioned': 'yes', 'diff_result': None} | {'func': 'and', 'args': [{'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'name', 'adam gilchrist ( wk )'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose name record fuzzily matches to adam gilchrist ( wk ) .', 'tostr': 'filter_eq { all_rows ; name ; adam gilchrist ( wk ) }'}, 'innings'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; name ; adam gilchrist ( wk ) } ; innings }', 'tointer': 'select the rows whose name record fuzzily matches to adam gilchrist ( wk ) . take the innings record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'name', 'matthew hayden'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose name record fuzzily matches to matthew hayden .', 'tostr': 'filter_eq { all_rows ; name ; matthew hayden }'}, 'innings'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; name ; matthew hayden } ; innings }', 'tointer': 'select the rows whose name record fuzzily matches to matthew hayden . take the innings record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; name ; adam gilchrist ( wk ) } ; innings } ; hop { filter_eq { all_rows ; name ; matthew hayden } ; innings } }', 'tointer': 'select the rows whose name record fuzzily matches to adam gilchrist ( wk ) . take the innings record of this row . select the rows whose name record fuzzily matches to matthew hayden . take the innings record of this row . the first record is greater than the second record .'}, {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'name', 'adam gilchrist ( wk )'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose name record fuzzily matches to adam gilchrist ( wk ) .', 'tostr': 'filter_eq { all_rows ; name ; adam gilchrist ( wk ) }'}, 'innings'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; name ; adam gilchrist ( wk ) } ; innings }', 'tointer': 'select the rows whose name record fuzzily matches to adam gilchrist ( wk ) . take the innings record of this row .'}, '8'], 'result': True, 'ind': 5, 'tostr': 'eq { hop { filter_eq { all_rows ; name ; adam gilchrist ( wk ) } ; innings } ; 8 }', 'tointer': 'the innings record of the first row is 8 .'}, {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'name', 'matthew hayden'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose name record fuzzily matches to matthew hayden .', 'tostr': 'filter_eq { all_rows ; name ; matthew hayden }'}, 'innings'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; name ; matthew hayden } ; innings }', 'tointer': 'select the rows whose name record fuzzily matches to matthew hayden . take the innings record of this row .'}, '6'], 'result': True, 'ind': 6, 'tostr': 'eq { hop { filter_eq { all_rows ; name ; matthew hayden } ; innings } ; 6 }', 'tointer': 'the innings record of the second row is 6 .'}], 'result': True, 'ind': 7, 'tostr': 'and { eq { hop { filter_eq { all_rows ; name ; adam gilchrist ( wk ) } ; innings } ; 8 } ; eq { hop { filter_eq { all_rows ; name ; matthew hayden } ; innings } ; 6 } }', 'tointer': 'the innings record of the first row is 8 . the innings record of the second row is 6 .'}], 'result': True, 'ind': 8, 'tostr': 'and { greater { hop { filter_eq { all_rows ; name ; adam gilchrist ( wk ) } ; innings } ; hop { filter_eq { all_rows ; name ; matthew hayden } ; innings } } ; and { eq { hop { filter_eq { all_rows ; name ; adam gilchrist ( wk ) } ; innings } ; 8 } ; eq { hop { filter_eq { all_rows ; name ; matthew hayden } ; innings } ; 6 } } } = true', 'tointer': 'select the rows whose name record fuzzily matches to adam gilchrist ( wk ) . take the innings record of this row . select the rows whose name record fuzzily matches to matthew hayden . take the innings record of this row . the first record is greater than the second record . the innings record of the first row is 8 . the innings record of the second row is 6 .'} | and { greater { hop { filter_eq { all_rows ; name ; adam gilchrist ( wk ) } ; innings } ; hop { filter_eq { all_rows ; name ; matthew hayden } ; innings } } ; and { eq { hop { filter_eq { all_rows ; name ; adam gilchrist ( wk ) } ; innings } ; 8 } ; eq { hop { filter_eq { all_rows ; name ; matthew hayden } ; innings } ; 6 } } } = true | select the rows whose name record fuzzily matches to adam gilchrist ( wk ) . take the innings record of this row . select the rows whose name record fuzzily matches to matthew hayden . take the innings record of this row . the first record is greater than the second record . the innings record of the first row is 8 . the innings record of the second row is 6 . | 13 | 9 | {'and_8': 8, 'result_9': 9, 'greater_4': 4, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_10': 10, 'name_11': 11, 'adam gilchrist (wk)_12': 12, 'innings_13': 13, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_14': 14, 'name_15': 15, 'matthew hayden_16': 16, 'innings_17': 17, 'and_7': 7, 'eq_5': 5, '8_18': 18, 'eq_6': 6, '6_19': 19} | {'and_8': 'and', 'result_9': 'true', 'greater_4': 'greater', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_10': 'all_rows', 'name_11': 'name', 'adam gilchrist (wk)_12': 'adam gilchrist ( wk )', 'innings_13': 'innings', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_14': 'all_rows', 'name_15': 'name', 'matthew hayden_16': 'matthew hayden', 'innings_17': 'innings', 'and_7': 'and', 'eq_5': 'eq', '8_18': '8', 'eq_6': 'eq', '6_19': '6'} | {'and_8': [9], 'result_9': [], 'greater_4': [8], 'num_hop_2': [4, 5], 'filter_str_eq_0': [2], 'all_rows_10': [0], 'name_11': [0], 'adam gilchrist (wk)_12': [0], 'innings_13': [2], 'num_hop_3': [4, 6], 'filter_str_eq_1': [3], 'all_rows_14': [1], 'name_15': [1], 'matthew hayden_16': [1], 'innings_17': [3], 'and_7': [8], 'eq_5': [7], '8_18': [5], 'eq_6': [7], '6_19': [6]} | ['name', 'innings', 'runs scored', 'balls faced', 'average', 'sr'] | [['adam gilchrist ( wk )', '8', '313', '318', '39.13', '98.43'], ['matthew hayden', '6', '161', '231', '26.83', '69.70'], ['ricky ponting ( c )', '8', '189', '256', '23.63', '73.83'], ['michael clarke', '7', '293', '416', '48.83', '70.43'], ['andrew symonds', '8', '100', '125', '14.29', '80.00'], ['michael hussey', '7', '189', '283', '47.25', '66.78'], ['james hopes', '7', '115', '125', '16.43', '92.00'], ['brett lee', '5', '49', '102', '12.25', '48.04'], ['mitchell johnson', '5', '21', '44', '7.00', '47.73'], ['nathan bracken', '4', '16', '43', '5.33', '37.21'], ['stuart clark', '2', '8', '10', '8.00', '80.00'], ['brad haddin', '2', '12', '44', '6.00', '27.27'], ['brad hogg', '4', '62', '100', '15.50', '62.00']] |
1957 vfl season | https://en.wikipedia.org/wiki/1957_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10774891-14.html.csv | aggregation | the average crowd attendance for the vfl games was 20188 . | {'scope': 'all', 'col': '6', 'type': 'average', 'result': '20188', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'crowd'], 'result': '20188', 'ind': 0, 'tostr': 'avg { all_rows ; crowd }'}, '20188'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; crowd } ; 20188 } = true', 'tointer': 'the average of the crowd record of all rows is 20188 .'} | round_eq { avg { all_rows ; crowd } ; 20188 } = true | the average of the crowd record of all rows is 20188 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'crowd_4': 4, '20188_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'crowd_4': 'crowd', '20188_5': '20188'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'crowd_4': [0], '20188_5': [1]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['richmond', '10.13 ( 73 )', 'south melbourne', '11.12 ( 78 )', 'punt road oval', '21000', '27 july 1957'], ['hawthorn', '7.13 ( 55 )', 'north melbourne', '5.4 ( 34 )', 'glenferrie oval', '10000', '27 july 1957'], ['essendon', '9.18 ( 72 )', 'melbourne', '11.7 ( 73 )', 'windy hill', '22500', '27 july 1957'], ['collingwood', '13.14 ( 92 )', 'geelong', '6.8 ( 44 )', 'victoria park', '21316', '27 july 1957'], ['carlton', '11.13 ( 79 )', 'footscray', '7.10 ( 52 )', 'princes park', '31810', '27 july 1957'], ['st kilda', '15.18 ( 108 )', 'fitzroy', '8.8 ( 56 )', 'junction oval', '14500', '27 july 1957']] |
karen kavaleryan | https://en.wikipedia.org/wiki/Karen_Kavaleryan | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17632536-1.html.csv | comparative | the song shady lady received more points than the song peace will come . | {'row_1': '5', 'row_2': '6', 'col': '5', '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', 'song', 'shady lady'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose song record fuzzily matches to shady lady .', 'tostr': 'filter_eq { all_rows ; song ; shady lady }'}, 'points'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; song ; shady lady } ; points }', 'tointer': 'select the rows whose song record fuzzily matches to shady lady . take the points record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'song', 'peace will come'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose song record fuzzily matches to peace will come .', 'tostr': 'filter_eq { all_rows ; song ; peace will come }'}, 'points'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; song ; peace will come } ; points }', 'tointer': 'select the rows whose song record fuzzily matches to peace will come . take the points record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; song ; shady lady } ; points } ; hop { filter_eq { all_rows ; song ; peace will come } ; points } } = true', 'tointer': 'select the rows whose song record fuzzily matches to shady lady . take the points record of this row . select the rows whose song record fuzzily matches to peace will come . take the points record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; song ; shady lady } ; points } ; hop { filter_eq { all_rows ; song ; peace will come } ; points } } = true | select the rows whose song record fuzzily matches to shady lady . take the points record of this row . select the rows whose song record fuzzily matches to peace will come . take the points 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, 'song_7': 7, 'shady lady_8': 8, 'points_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'song_11': 11, 'peace will come_12': 12, 'points_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', 'song_7': 'song', 'shady lady_8': 'shady lady', 'points_9': 'points', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'song_11': 'song', 'peace will come_12': 'peace will come', 'points_13': 'points'} | {'greater_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'song_7': [0], 'shady lady_8': [0], 'points_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'song_11': [1], 'peace will come_12': [1], 'points_13': [3]} | ['year', 'song', 'artist', 'place', 'points', 'composer'] | [['2002', 'northern girl 1', 'prime minister', '10', '55', 'kim breitburg'], ['2006', 'never let you go 2', 'dima bilan', '2 ( sf : 3rd )', '248 ( sf : 217 )', 'alexander lunyov'], ['2007', 'work your magic', 'dmitry koldun', '6 ( sf : 4th )', '145 ( sf : 176 )', 'philipp kirkorov'], ['2007', 'anytime you need 3', 'hayko', '8 ( sf : - )', '138 ( sf : - )', 'hayko'], ['2008', 'shady lady', 'ani lorak', '2 ( sf : 1 )', '230 ( sf : 152 )', 'philipp kirkorov'], ['2008', 'peace will come', 'diana gurtskaya', '11 ( sf : 5 )', '83 ( sf : 107 )', 'kim breitburg'], ['2010', 'apricot stone', 'eva rivas', '7 ( sf :6 )', '141 ( sf :83 )', 'armen martirosyan'], ['2013', 'gravity', 'zlata ognevich', '3 ( sf :3 )', '214 ( sf :140 )', 'm nekrosov']] |
central indiana athletic conference | https://en.wikipedia.org/wiki/Central_Indiana_Athletic_Conference | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18765652-2.html.csv | majority | the previous conference for most of the schools was independents . | {'scope': 'all', 'col': '6', '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', 'year joined', 'previous conference', 'year left'] | [['huntington north', 'huntington', 'vikings', '35 huntington', '1932', 'independents', '1974'], ['noblesville', 'noblesville', 'millers', '29 hamilton', '1932', 'hamilton county', '1938'], ['peru', 'peru', 'tigers', '52 miami', '1932', 'independents', '1998'], ['rochester', 'rochester', 'zebras', '25 fulton', '1932', 'north central', '1964'], ['tipton', 'tipton', 'blue devils', '80 tipton', '1932', 'independents', '1998'], ['wabash', 'wabash', 'apaches', '85 wabash', '1932', 'independents', '2006'], ['windfall', 'windfall', 'dragons', '80 tipton', '1932', 'independents', '1936'], ['warsaw', 'warsaw', 'tigers', '43 kosciusko', '1933 1953', 'independents northeastern in', '1946 1964'], ['plymouth', 'plymouth', 'pilgrims', '50 marshall', '1935', 'independents', '1964'], ['muncie burris', 'muncie', 'owls', '18 delaware', '1938', 'independents', '1976'], ['hartford city', 'hartford city', 'airedales', '05 blackford', '1945', 'independents', '1968'], ['monticello', 'monticello', 'tioga indians', '91 white', '1945', 'independents', '1963'], ['south side', 'fort wayne', 'archers', '02 allen', '1945', 'fort wayne', '1947']] |
rafael barreto ( singer ) | https://en.wikipedia.org/wiki/Rafael_Barreto_%28singer%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27614571-1.html.csv | unique | the only time rafael barreto was not safe from elimination was the week he performed country pop . | {'scope': 'all', 'row': '7', 'col': '6', 'col_other': '2', 'criterion': 'equal', 'value': 'bottom', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'result', 'bottom'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose result record fuzzily matches to bottom .', 'tostr': 'filter_eq { all_rows ; result ; bottom }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; result ; bottom } }', 'tointer': 'select the rows whose result record fuzzily matches to bottom . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'result', 'bottom'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose result record fuzzily matches to bottom .', 'tostr': 'filter_eq { all_rows ; result ; bottom }'}, 'theme'], 'result': 'country pop', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; result ; bottom } ; theme }'}, 'country pop'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; result ; bottom } ; theme } ; country pop }', 'tointer': 'the theme record of this unqiue row is country pop .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; result ; bottom } } ; eq { hop { filter_eq { all_rows ; result ; bottom } ; theme } ; country pop } } = true', 'tointer': 'select the rows whose result record fuzzily matches to bottom . there is only one such row in the table . the theme record of this unqiue row is country pop .'} | and { only { filter_eq { all_rows ; result ; bottom } } ; eq { hop { filter_eq { all_rows ; result ; bottom } ; theme } ; country pop } } = true | select the rows whose result record fuzzily matches to bottom . there is only one such row in the table . the theme record of this unqiue row is country pop . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'result_7': 7, 'bottom_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'theme_9': 9, 'country pop_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', 'bottom_8': 'bottom', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'theme_9': 'theme', 'country pop_10': 'country pop'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'result_7': [0], 'bottom_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'theme_9': [2], 'country pop_10': [3]} | ['week', 'theme', 'song choice', 'original artist', 'order', 'result'] | [['audition', "auditioner 's choice", 'quando chove', 'patricia marx', 'n / a', 'advanced'], ['theater', 'first solo', 'você chegou', 'ls jack', 'n / a', 'advanced'], ['top 30', 'semi - final / group 2', 'uma carta', 'ls jack', '9', 'advanced'], ['top 10', 'my idol', 'pra rua me levar', 'ana carolina', '6', 'safe'], ['top 9', 'female singers', 'nada por mim', 'leila pinheiro', '8', 'safe'], ['top 8', 'love songs', 'anjo', 'roupa nova', '4', 'safe'], ['top 7', 'country pop', 'como um anjo', 'césar menotti & fabiano', '7', 'bottom 2'], ['top 6', 'samba', 'tarde em itapuã', 'vinicius de moraes / toquinho', '5', 'safe'], ['top 5', 'birth year songs', 'olhar 43', 'rpm', '5', 'safe'], ['top 5', 'birth year songs', 'dona', 'roupa nova', '10', 'safe'], ['top 4', 'roberto carlos & elis regina', 'é preciso saber viver', 'roberto carlos', '2', 'safe'], ['top 4', 'roberto carlos & elis regina', 'romaria', 'elis regina', '6', 'safe'], ['top 3', 'jovem pan number 1 hits', 'o sol', 'jota quest', '2', 'safe'], ['top 3', 'jovem pan number 1 hits', 'tem que ser você', 'victor & leo', '5', 'safe'], ['top 3', 'jovem pan number 1 hits', 'por mais que eu tente', 'marjorie estiano', '8', 'safe'], ['top 2', "winner 's single 1", 'ficou no ar', 'rafael barreto', '2', 'winner'], ['top 2', "contestant 's choice", "you 'll be in my heart", 'phil collins / ed motta', '4', 'winner']] |
selima sfar | https://en.wikipedia.org/wiki/Selima_Sfar | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13604859-2.html.csv | majority | selima sfar won most of her tournaments on a clay surface . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'clay', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'surface', 'clay'], 'result': True, 'ind': 0, 'tointer': 'for the surface records of all rows , most of them fuzzily match to clay .', 'tostr': 'most_eq { all_rows ; surface ; clay } = true'} | most_eq { all_rows ; surface ; clay } = true | for the surface records of all rows , most of them fuzzily match to clay . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'surface_3': 3, 'clay_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'surface_3': 'surface', 'clay_4': 'clay'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'surface_3': [0], 'clay_4': [0]} | ['date', 'tournament', 'surface', 'opponent in the final', 'score'] | [['august 14 , 1994', 'carthage', 'clay', 'anne - gaëlle sidot', '5 - 7 6 - 3 6 - 4'], ['march 26 , 1995', 'moulins', 'hard indoors', 'linda sentis', '3 - 6 6 - 3 6 - 2'], ['november 26 , 1995', 'le havre', 'clay indoors', 'émilie loit', '0 - 6 6 - 3 6 - 4'], ['february 4 , 1996', 'dinan', 'clay indoors', 'virginie massart', '6 - 4 7 - 6'], ['august 11 , 1996', 'carthage', 'clay', 'marielle bruens', '7 - 5 6 - 4'], ['december 14 , 1997', 'ismailia', 'clay', 'tzipora obziler', '5 - 7 7 - 5 6 - 4'], ['april 30 , 2000', 'bournemouth', 'clay', 'dragana zarić', '7 - 5 6 - 2'], ['september 22 , 2002', 'glasgow', 'hard indoors', 'anne keothavong', '7 - 6 2 - 6 7 - 6'], ['november 3 , 2002', 'nottingham', 'hard indoors', 'lilia osterloh', '6 - 2 6 - 2'], ['may 14 , 2006', 'jounieh', 'clay', 'anastasiya yakimova', '6 - 4 7 - 5'], ['may 13 , 2007', 'jounieh', 'clay', 'mariya koryttseva', '6 - 2 4 - 6 7 - 6']] |
list of actors who played president of the united states | https://en.wikipedia.org/wiki/List_of_actors_who_played_President_of_the_United_States | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1673723-9.html.csv | unique | daniel day-lewis was the only person to win best actor . | {'scope': 'all', 'row': '6', 'col': '6', 'col_other': '4', 'criterion': 'equal', 'value': 'won', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'result', 'won'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose result record fuzzily matches to won .', 'tostr': 'filter_eq { all_rows ; result ; won }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; result ; won } }', 'tointer': 'select the rows whose result record fuzzily matches to won . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'result', 'won'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose result record fuzzily matches to won .', 'tostr': 'filter_eq { all_rows ; result ; won }'}, 'nominee'], 'result': 'daniel day - lewis', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; result ; won } ; nominee }'}, 'daniel day - lewis'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; result ; won } ; nominee } ; daniel day - lewis }', 'tointer': 'the nominee record of this unqiue row is daniel day - lewis .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; result ; won } } ; eq { hop { filter_eq { all_rows ; result ; won } ; nominee } ; daniel day - lewis } } = true', 'tointer': 'select the rows whose result record fuzzily matches to won . there is only one such row in the table . the nominee record of this unqiue row is daniel day - lewis .'} | and { only { filter_eq { all_rows ; result ; won } } ; eq { hop { filter_eq { all_rows ; result ; won } ; nominee } ; daniel day - lewis } } = true | select the rows whose result record fuzzily matches to won . there is only one such row in the table . the nominee record of this unqiue row is daniel day - lewis . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'result_7': 7, 'won_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'nominee_9': 9, 'daniel day - lewis_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', 'won_8': 'won', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'nominee_9': 'nominee', 'daniel day - lewis_10': 'daniel day - lewis'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'result_7': [0], 'won_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'nominee_9': [2], 'daniel day - lewis_10': [3]} | ['year', 'category', 'president', 'nominee', 'film', 'result'] | [['1941', 'best actor', 'abraham lincoln', 'raymond massey', 'abe lincoln in illinois', 'nominated'], ['1976', 'best actor', 'harry s truman', 'james whitmore', "give 'em hell , harry !", 'nominated'], ['1996', 'best actor', 'richard nixon', 'anthony hopkins', 'nixon', 'nominated'], ['1998', 'best supporting actor', 'john quincy adams', 'anthony hopkins', 'amistad', 'nominated'], ['2009', 'best actor', 'richard nixon', 'frank langella', 'frost / nixon', 'nominated'], ['2013', 'best actor', 'abraham lincoln', 'daniel day - lewis', 'lincoln', 'won']] |
intel | https://en.wikipedia.org/wiki/Intel | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14617-1.html.csv | unique | stpmesoft is the only company from finland that was acquired by intel corporation . | {'scope': 'all', 'row': '6', 'col': '4', 'col_other': '2', 'criterion': 'equal', 'value': 'finland', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'finland'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose country record fuzzily matches to finland .', 'tostr': 'filter_eq { all_rows ; country ; finland }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; country ; finland } }', 'tointer': 'select the rows whose country record fuzzily matches to finland . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'finland'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose country record fuzzily matches to finland .', 'tostr': 'filter_eq { all_rows ; country ; finland }'}, 'company'], 'result': 'stonesoft', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; country ; finland } ; company }'}, 'stonesoft'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; country ; finland } ; company } ; stonesoft }', 'tointer': 'the company record of this unqiue row is stonesoft .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; country ; finland } } ; eq { hop { filter_eq { all_rows ; country ; finland } ; company } ; stonesoft } } = true', 'tointer': 'select the rows whose country record fuzzily matches to finland . there is only one such row in the table . the company record of this unqiue row is stonesoft .'} | and { only { filter_eq { all_rows ; country ; finland } } ; eq { hop { filter_eq { all_rows ; country ; finland } ; company } ; stonesoft } } = true | select the rows whose country record fuzzily matches to finland . there is only one such row in the table . the company record of this unqiue row is stonesoft . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'country_7': 7, 'finland_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'company_9': 9, 'stonesoft_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', 'finland_8': 'finland', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'company_9': 'company', 'stonesoft_10': 'stonesoft'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'country_7': [0], 'finland_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'company_9': [2], 'stonesoft_10': [3]} | ['number', 'company', 'business', 'country', 'price', 'used as or integrated with'] | [['1', 'mcafee', 'security', 'usa', '7.6 b', 'software'], ['2', 'infineon', 'wireless', 'germany', '1.4 b', 'mobile cpus'], ['3', 'telmap', 'software', 'israel', 'n / a', 'location services'], ['4', 'mashery', 'cloud software', 'usa', '180 m', 'software'], ['5', 'aepona', 'sdn', 'ireland', 'n / a', 'software'], ['6', 'stonesoft', 'security', 'finland', '389 m', 'software'], ['7', 'omek interactive', 'gesture', 'israel', 'n / a', 'software'], ['7', 'indysis', 'natural language processing', 'spain', 'n / a', 'software']] |
1977 vfl season | https://en.wikipedia.org/wiki/1977_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10887379-17.html.csv | unique | only the game between footscray and essendon took place in the western oval . | {'scope': 'all', 'row': '5', 'col': '5', 'col_other': '1,3', 'criterion': 'equal', 'value': 'western oval', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'venue', 'western oval'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose venue record fuzzily matches to western oval .', 'tostr': 'filter_eq { all_rows ; venue ; western oval }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; venue ; western oval } }', 'tointer': 'select the rows whose venue record fuzzily matches to western oval . there is only one such row in the table .'}, {'func': 'and', 'args': [{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'venue', 'western oval'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose venue record fuzzily matches to western oval .', 'tostr': 'filter_eq { all_rows ; venue ; western oval }'}, 'home team'], 'result': 'footscray', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; venue ; western oval } ; home team }'}, 'footscray'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; venue ; western oval } ; home team } ; footscray }', 'tointer': 'the home team record of this unqiue row is footscray .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'venue', 'western oval'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose venue record fuzzily matches to western oval .', 'tostr': 'filter_eq { all_rows ; venue ; western oval }'}, 'away team'], 'result': 'essendon', 'ind': 4, 'tostr': 'hop { filter_eq { all_rows ; venue ; western oval } ; away team }'}, 'essendon'], 'result': True, 'ind': 5, 'tostr': 'eq { hop { filter_eq { all_rows ; venue ; western oval } ; away team } ; essendon }', 'tointer': 'the away team record of this unqiue row is essendon .'}], 'result': True, 'ind': 6, 'tostr': 'and { eq { hop { filter_eq { all_rows ; venue ; western oval } ; home team } ; footscray } ; eq { hop { filter_eq { all_rows ; venue ; western oval } ; away team } ; essendon } }', 'tointer': 'the home team record of this unqiue row is footscray . the away team record of this unqiue row is essendon .'}], 'result': True, 'ind': 7, 'tostr': 'and { only { filter_eq { all_rows ; venue ; western oval } } ; and { eq { hop { filter_eq { all_rows ; venue ; western oval } ; home team } ; footscray } ; eq { hop { filter_eq { all_rows ; venue ; western oval } ; away team } ; essendon } } } = true', 'tointer': 'select the rows whose venue record fuzzily matches to western oval . there is only one such row in the table . the home team record of this unqiue row is footscray . the away team record of this unqiue row is essendon .'} | and { only { filter_eq { all_rows ; venue ; western oval } } ; and { eq { hop { filter_eq { all_rows ; venue ; western oval } ; home team } ; footscray } ; eq { hop { filter_eq { all_rows ; venue ; western oval } ; away team } ; essendon } } } = true | select the rows whose venue record fuzzily matches to western oval . there is only one such row in the table . the home team record of this unqiue row is footscray . the away team record of this unqiue row is essendon . | 10 | 8 | {'and_7': 7, 'result_8': 8, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_9': 9, 'venue_10': 10, 'western oval_11': 11, 'and_6': 6, 'str_eq_3': 3, 'str_hop_2': 2, 'home team_12': 12, 'footscray_13': 13, 'str_eq_5': 5, 'str_hop_4': 4, 'away team_14': 14, 'essendon_15': 15} | {'and_7': 'and', 'result_8': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_9': 'all_rows', 'venue_10': 'venue', 'western oval_11': 'western oval', 'and_6': 'and', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'home team_12': 'home team', 'footscray_13': 'footscray', 'str_eq_5': 'str_eq', 'str_hop_4': 'str_hop', 'away team_14': 'away team', 'essendon_15': 'essendon'} | {'and_7': [8], 'result_8': [], 'only_1': [7], 'filter_str_eq_0': [1, 2, 4], 'all_rows_9': [0], 'venue_10': [0], 'western oval_11': [0], 'and_6': [7], 'str_eq_3': [6], 'str_hop_2': [3], 'home team_12': [2], 'footscray_13': [3], 'str_eq_5': [6], 'str_hop_4': [5], 'away team_14': [4], 'essendon_15': [5]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['north melbourne', '15.11 ( 101 )', 'richmond', '14.14 ( 98 )', 'arden street oval', '15359', '23 july 1977'], ['fitzroy', '7.13 ( 55 )', 'south melbourne', '16.21 ( 117 )', 'junction oval', '10220', '23 july 1977'], ['carlton', '11.8 ( 74 )', 'collingwood', '15.16 ( 106 )', 'princes park', '38220', '23 july 1977'], ['melbourne', '15.18 ( 108 )', 'geelong', '20.14 ( 134 )', 'mcg', '15890', '23 july 1977'], ['footscray', '12.21 ( 93 )', 'essendon', '11.10 ( 76 )', 'western oval', '17834', '23 july 1977'], ['hawthorn', '24.19 ( 163 )', 'st kilda', '11.11 ( 77 )', 'vfl park', '20469', '23 july 1977']] |
1942 vfl season | https://en.wikipedia.org/wiki/1942_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10807990-7.html.csv | ordinal | the footscray game had the second most people attending on june 20 1942 . | {'row': '5', 'col': '6', 'order': '2', 'col_other': '1,7', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'and', 'args': [{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'crowd', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; crowd ; 2 }'}, 'home team'], 'result': 'footscray', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; crowd ; 2 } ; home team }'}, 'footscray'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; crowd ; 2 } ; home team } ; footscray }', 'tointer': 'select the row whose crowd record of all rows is 2nd maximum . the home team record of this row is footscray .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'crowd', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; crowd ; 2 }'}, 'date'], 'result': '20 june 1942', 'ind': 3, 'tostr': 'hop { nth_argmax { all_rows ; crowd ; 2 } ; date }'}, '20 june 1942'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { nth_argmax { all_rows ; crowd ; 2 } ; date } ; 20 june 1942 }', 'tointer': 'the date record of this row is 20 june 1942 .'}], 'result': True, 'ind': 5, 'tostr': 'and { eq { hop { nth_argmax { all_rows ; crowd ; 2 } ; home team } ; footscray } ; eq { hop { nth_argmax { all_rows ; crowd ; 2 } ; date } ; 20 june 1942 } } = true', 'tointer': 'select the row whose crowd record of all rows is 2nd maximum . the home team record of this row is footscray . the date record of this row is 20 june 1942 .'} | and { eq { hop { nth_argmax { all_rows ; crowd ; 2 } ; home team } ; footscray } ; eq { hop { nth_argmax { all_rows ; crowd ; 2 } ; date } ; 20 june 1942 } } = true | select the row whose crowd record of all rows is 2nd maximum . the home team record of this row is footscray . the date record of this row is 20 june 1942 . | 7 | 6 | {'and_5': 5, 'result_6': 6, 'str_eq_2': 2, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_7': 7, 'crowd_8': 8, '2_9': 9, 'home team_10': 10, 'footscray_11': 11, 'str_eq_4': 4, 'str_hop_3': 3, 'date_12': 12, '20 june 1942_13': 13} | {'and_5': 'and', 'result_6': 'true', 'str_eq_2': 'str_eq', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_7': 'all_rows', 'crowd_8': 'crowd', '2_9': '2', 'home team_10': 'home team', 'footscray_11': 'footscray', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'date_12': 'date', '20 june 1942_13': '20 june 1942'} | {'and_5': [6], 'result_6': [], 'str_eq_2': [5], 'str_hop_1': [2], 'nth_argmax_0': [1, 3], 'all_rows_7': [0], 'crowd_8': [0], '2_9': [0], 'home team_10': [1], 'footscray_11': [2], 'str_eq_4': [5], 'str_hop_3': [4], 'date_12': [3], '20 june 1942_13': [4]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['richmond', '10.9 ( 69 )', 'south melbourne', '11.20 ( 86 )', 'punt road oval', '18000', '20 june 1942'], ['fitzroy', '16.14 ( 110 )', 'hawthorn', '14.10 ( 94 )', 'brunswick street oval', '5000', '20 june 1942'], ['north melbourne', '11.10 ( 76 )', 'melbourne', '12.11 ( 83 )', 'arden street oval', '4000', '20 june 1942'], ['st kilda', '11.14 ( 80 )', 'collingwood', '9.14 ( 68 )', 'toorak park', '5000', '20 june 1942'], ['footscray', '12.19 ( 91 )', 'carlton', '10.12 ( 72 )', 'yarraville oval', '8500', '20 june 1942']] |
1982 vfl season | https://en.wikipedia.org/wiki/1982_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10824095-15.html.csv | superlative | the richmond game had the most people in attendance there . | {'scope': 'all', 'col_superlative': '6', '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', 'crowd'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; crowd }'}, 'home team'], 'result': 'richmond', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; crowd } ; home team }'}, 'richmond'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; crowd } ; home team } ; richmond } = true', 'tointer': 'select the row whose crowd record of all rows is maximum . the home team record of this row is richmond .'} | eq { hop { argmax { all_rows ; crowd } ; home team } ; richmond } = true | select the row whose crowd record of all rows is maximum . the home team record of this row is richmond . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'crowd_5': 5, 'home team_6': 6, 'richmond_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'crowd_5': 'crowd', 'home team_6': 'home team', 'richmond_7': 'richmond'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'crowd_5': [0], 'home team_6': [1], 'richmond_7': [2]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['essendon', '21.13 ( 139 )', 'fitzroy', '7.12 ( 54 )', 'windy hill', '20059', '3 july 1982'], ['carlton', '18.20 ( 128 )', 'melbourne', '16.15 ( 111 )', 'princes park', '21871', '3 july 1982'], ['richmond', '17.14 ( 116 )', 'hawthorn', '22.14 ( 146 )', 'mcg', '48338', '3 july 1982'], ['swans', '18.18 ( 126 )', 'geelong', '12.15 ( 87 )', 'scg', '12221', '3 july 1982'], ['st kilda', '20.11 ( 131 )', 'footscray', '18.12 ( 120 )', 'moorabbin oval', '15958', '3 july 1982'], ['north melbourne', '16.13 ( 109 )', 'collingwood', '13.11 ( 89 )', 'vfl park', '32812', '3 july 1982']] |
united states house of representatives elections , 1942 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1942 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1342256-10.html.csv | ordinal | pat cannon recorded the highest percentage ratio among all candidates of the 1942 house of representatives elections . | {'row': '4', 'col': '6', 'order': '1', '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', 'candidates', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; candidates ; 1 }'}, 'incumbent'], 'result': 'pat cannon', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; candidates ; 1 } ; incumbent }'}, 'pat cannon'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; candidates ; 1 } ; incumbent } ; pat cannon } = true', 'tointer': 'select the row whose candidates record of all rows is 1st maximum . the incumbent record of this row is pat cannon .'} | eq { hop { nth_argmax { all_rows ; candidates ; 1 } ; incumbent } ; pat cannon } = true | select the row whose candidates record of all rows is 1st maximum . the incumbent record of this row is pat cannon . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'candidates_5': 5, '1_6': 6, 'incumbent_7': 7, 'pat cannon_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', 'candidates_5': 'candidates', '1_6': '1', 'incumbent_7': 'incumbent', 'pat cannon_8': 'pat cannon'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'candidates_5': [0], '1_6': [0], 'incumbent_7': [1], 'pat cannon_8': [2]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['florida 1', 'j hardin peterson', 'democratic', '1932', 're - elected', 'j hardin peterson ( d ) unopposed'], ['florida 2', 'robert a green', 'democratic', '1932', 'ran in at - large district democratic hold', 'emory h price ( d ) unopposed'], ['florida 3', 'robert l f sikes', 'democratic', '1940', 're - elected', 'robert l f sikes ( d ) unopposed'], ['florida 4', 'pat cannon', 'democratic', '1938', 're - elected', 'pat cannon ( d ) 81.4 % bert leigh acker ( r ) 18.6 %'], ['florida 5', 'joe hendricks', 'democratic', '1936', 're - elected', 'joe hendricks ( d ) 70.9 % emory akerman ( r ) 29.1 %']] |
2002 pba draft | https://en.wikipedia.org/wiki/2002_PBA_draft | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10810530-2.html.csv | count | two of the top 10 draft picks from the 2002 pba draft were from the united states . | {'scope': 'all', 'criterion': 'equal', 'value': 'united states', 'result': '2', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country of origin', 'united states'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose country of origin record fuzzily matches to united states .', 'tostr': 'filter_eq { all_rows ; country of origin ; united states }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; country of origin ; united states } }', 'tointer': 'select the rows whose country of origin record fuzzily matches to united states . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; country of origin ; united states } } ; 2 } = true', 'tointer': 'select the rows whose country of origin record fuzzily matches to united states . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; country of origin ; united states } } ; 2 } = true | select the rows whose country of origin record fuzzily matches to united states . the number of such rows is 2 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'country of origin_5': 5, 'united states_6': 6, '2_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'country of origin_5': 'country of origin', 'united states_6': 'united states', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'country of origin_5': [0], 'united states_6': [0], '2_7': [2]} | ['pick', 'player', 'country of origin', 'pba team', 'college'] | [['1', 'yancy de ocampo', 'philippines', 'fedex express', 'st francis'], ['2', 'rafi reavis', 'united states', 'coca - cola tigers', 'coppin state'], ['3', 'omanzie rodriguez', 'philippines', 'sta lucia realtors', 'mapua'], ['4', 'chris calaguio', 'philippines', 'shell turbo chargers', 'letran'], ['5', 'homer se', 'philippines', 'red bull thunder', 'san sebastian'], ['6', 'migs noble', 'united states', 'alaska aces', 'utica'], ['7', 'eric canlas', 'philippines', 'shell turbo chargers', 'st francis'], ['8', 'ren - ren ritualo', 'philippines', 'fedex express', 'la salle - manila'], ['9', 'chester tolomia', 'philippines', 'barangay ginebra kings', 'perpetual help'], ['10', 'leo avenido', 'philippines', 'coca - cola tigers', 'far eastern']] |
2007 gran premio tecate | https://en.wikipedia.org/wiki/2007_Gran_Premio_Tecate | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14171191-1.html.csv | count | the number of drivers in the 2007 gran premio tecate with the best lap time being greater than 1:25.000 is 6 . | {'scope': 'all', 'criterion': 'greater_than', 'value': '1:25.000', 'result': '6', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'best', '1:25.000'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose best record is greater than 1:25.000 .', 'tostr': 'filter_greater { all_rows ; best ; 1:25.000 }'}], 'result': '6', 'ind': 1, 'tostr': 'count { filter_greater { all_rows ; best ; 1:25.000 } }', 'tointer': 'select the rows whose best record is greater than 1:25.000 . the number of such rows is 6 .'}, '6'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_greater { all_rows ; best ; 1:25.000 } } ; 6 } = true', 'tointer': 'select the rows whose best record is greater than 1:25.000 . the number of such rows is 6 .'} | eq { count { filter_greater { all_rows ; best ; 1:25.000 } } ; 6 } = true | select the rows whose best record is greater than 1:25.000 . the number of such rows is 6 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_greater_0': 0, 'all_rows_4': 4, 'best_5': 5, '1:25.000_6': 6, '6_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_greater_0': 'filter_greater', 'all_rows_4': 'all_rows', 'best_5': 'best', '1:25.000_6': '1:25.000', '6_7': '6'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_greater_0': [1], 'all_rows_4': [0], 'best_5': [0], '1:25.000_6': [0], '6_7': [2]} | ['name', 'team', 'qual 1', 'qual 2', 'best'] | [['will power', 'team australia', '1:25.199', '1:23.558', '1:23.558'], ['sébastien bourdais', 'n / h / l racing', '1:24.698', '1:24.901', '1:24.698'], ['robert doornbos', 'minardi team usa', '1:26.220', '1:24.152', '1:24.152'], ['oriol servià', 'pkv racing', '1:25.436', '1:24.324', '1:24.324'], ['justin wilson', 'rusport', '1:24.825', '1:24.365', '1:24.365'], ['simon pagenaud', 'team australia', '1:25.952', '1:24.394', '1:24.394'], ['graham rahal', 'n / h / l racing', '1:25.889', '1:24.515', '1:24.515'], ['paul tracy', 'forsythe racing', '1:26.130', '1:24.608', '1:24.608'], ['dan clarke', 'minardi team usa', '1:26.617', '1:24.764', '1:24.764'], ['david martínez', 'forsythe racing', '1:26.056', '1:24.888', '1:24.888'], ['neel jani', 'pkv racing', '1:26.156', '1:24.929', '1:24.929'], ['bruno junqueira', 'dale coyne racing', '1:26.190', '1:25.361', '1:25.361'], ['nelson philippe', 'conquest racing', '1:26.952', '1:25.405', '1:25.405'], ['alex tagliani', 'rocketsports racing', '1:27.277', '1:25.446', '1:25.446'], ['mario domínguez', 'pacific coast motorsports', '1:26.181', '1:25.602', '1:25.602'], ['katherine legge', 'dale coyne racing', '1:28.069', '1:26.277', '1:26.277'], ['alex figge', 'pacific coast motorsports', '1:27.230', '1:26.582', '1:26.582']] |
1982 indycar season | https://en.wikipedia.org/wiki/1982_IndyCar_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10706907-2.html.csv | majority | rick mears had the majority of pole positions in the 1982 indycar season . | {'scope': 'all', 'col': '2', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'rick mears', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'pole position', 'rick mears'], 'result': True, 'ind': 0, 'tointer': 'for the pole position records of all rows , most of them fuzzily match to rick mears .', 'tostr': 'most_eq { all_rows ; pole position ; rick mears } = true'} | most_eq { all_rows ; pole position ; rick mears } = true | for the pole position records of all rows , most of them fuzzily match to rick mears . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'pole position_3': 3, 'rick mears_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'pole position_3': 'pole position', 'rick mears_4': 'rick mears'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'pole position_3': [0], 'rick mears_4': [0]} | ['name', 'pole position', 'fastest lap', 'winning driver', 'report'] | [['kraco car stereo 150', 'rick mears', 'unknown', 'rick mears', 'report'], ["stoh 's 200", 'rick mears', 'unknown', 'rick mears', 'report'], ['gould - rex mays 150', 'gordon johncock', 'unknown', 'gordon johncock', 'report'], ['budweiser cleveland 500', 'kevin cogan', 'unknown', 'bobby rahal', 'report'], ['norton - michigan 500', 'rick mears', 'unknown', 'gordon johncock', 'report'], ['tony bettenhausen 200', 'rick mears', 'unknown', 'tom sneva', 'report'], ["domino 's pizza pocono 500", 'rick mears', 'unknown', 'rick mears', 'report'], ['aircal 500', 'kevin cogan', 'unknown', 'rick mears', 'report'], ['road america 200', 'rick mears', 'unknown', 'hector rebaque', 'report'], ['detroit news grand prix', 'rick mears', 'unknown', 'bobby rahal', 'report'], ['miller high life 150', 'rick mears', 'unknown', 'tom sneva', 'report']] |
chak ting fung | https://en.wikipedia.org/wiki/Chak_Ting_Fung | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18699027-2.html.csv | unique | only the competition in prince mohamed bin fahd stadium took place in 2014 . | {'scope': 'all', 'row': '5', 'col': '5', 'col_other': '2', 'criterion': 'equal', 'value': '2014', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'competition', '2014'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose competition record is equal to 2014 .', 'tostr': 'filter_eq { all_rows ; competition ; 2014 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; competition ; 2014 } }', 'tointer': 'select the rows whose competition record is equal to 2014 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'competition', '2014'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose competition record is equal to 2014 .', 'tostr': 'filter_eq { all_rows ; competition ; 2014 }'}, 'venue'], 'result': 'prince mohamed bin fahd stadium , dammam', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; competition ; 2014 } ; venue }'}, 'prince mohamed bin fahd stadium , dammam'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; competition ; 2014 } ; venue } ; prince mohamed bin fahd stadium , dammam }', 'tointer': 'the venue record of this unqiue row is prince mohamed bin fahd stadium , dammam .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; competition ; 2014 } } ; eq { hop { filter_eq { all_rows ; competition ; 2014 } ; venue } ; prince mohamed bin fahd stadium , dammam } } = true', 'tointer': 'select the rows whose competition record is equal to 2014 . there is only one such row in the table . the venue record of this unqiue row is prince mohamed bin fahd stadium , dammam .'} | and { only { filter_eq { all_rows ; competition ; 2014 } } ; eq { hop { filter_eq { all_rows ; competition ; 2014 } ; venue } ; prince mohamed bin fahd stadium , dammam } } = true | select the rows whose competition record is equal to 2014 . there is only one such row in the table . the venue record of this unqiue row is prince mohamed bin fahd stadium , dammam . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'competition_7': 7, '2014_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'venue_9': 9, 'prince mohamed bin fahd stadium , dammam_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'competition_7': 'competition', '2014_8': '2014', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'venue_9': 'venue', 'prince mohamed bin fahd stadium , dammam_10': 'prince mohamed bin fahd stadium , dammam'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'competition_7': [0], '2014_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'venue_9': [2], 'prince mohamed bin fahd stadium , dammam_10': [3]} | ['date', 'venue', 'result', 'scored', 'competition'] | [['3 march 2010', 'hong kong stadium , hong kong', '0 - 0', '0', '2011 afc asian cup qualification'], ['9 october 2010', 'kaohsiung national stadium , kaohsiung', '4 - 2', '0', '2010 long teng cup'], ['10 october 2010', 'kaohsiung national stadium , kaohsiung', '4 - 0', '0', '2010 long teng cup'], ['12 october 2010', 'kaohsiung national stadium , kaohsiung', '1 - 1', '0', '2010 long teng cup'], ['23 july 2011', 'prince mohamed bin fahd stadium , dammam', '0 - 3', '0', '2014 fifa world cup qualification'], ['30 september 2011', 'kaohsiung national stadium , kaohsiung', '3 - 3', '0', '2011 long teng cup'], ['2 october 2011', 'kaohsiung national stadium , kaohsiung', '5 - 1', '0', '2011 long teng cup'], ['4 october 2011', 'kaohsiung national stadium , kaohsiung', '6 - 0', '0', '2011 long teng cup'], ['29 february 2012', 'mong kok stadium , hong kong', '5 - 1', '0', 'friendly'], ['1 june 2012', 'hong kong stadium , hong kong', '1 - 0', '0', 'friendly'], ['10 june 2012', 'mong kok stadium , hong kong', '1 - 2', '0', 'friendly'], ['15 august 2012', 'jurong west stadium , singapore', '0 - 2', '0', 'friendly']] |
wru division one west | https://en.wikipedia.org/wiki/WRU_Division_One_West | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12792876-5.html.csv | aggregation | there was a total of 44 try bonus points at the wru division one west . | {'scope': 'all', 'col': '9', 'type': 'sum', 'result': '44', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'try bonus'], 'result': '44', 'ind': 0, 'tostr': 'sum { all_rows ; try bonus }'}, '44'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; try bonus } ; 44 } = true', 'tointer': 'the sum of the try bonus record of all rows is 44 .'} | round_eq { sum { all_rows ; try bonus } ; 44 } = true | the sum of the try bonus record of all rows is 44 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'try bonus_4': 4, '44_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'try bonus_4': 'try bonus', '44_5': '44'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'try bonus_4': [0], '44_5': [1]} | ['club', 'played', 'drawn', 'lost', 'points for', 'points against', 'tries for', 'tries against', 'try bonus'] | [['club', 'played', 'drawn', 'lost', 'points for', 'points against', 'tries for', 'tries against', 'try bonus'], ['tonmawr rfc', '22', '1', '3', '538', '245', '79', '21', '9'], ['carmarthen rfc', '22', '2', '3', '553', '265', '69', '28', '9'], ['narberth rfc', '22', '1', '4', '566', '369', '67', '41', '7'], ['merthyr rfc', '22', '0', '10', '411', '378', '57', '46', '5'], ['llangennech rfc', '22', '1', '11', '382', '344', '42', '36', '4'], ['whitland rfc', '22', '0', '12', '395', '357', '39', '40', '4'], ['cwmllynfell rfc', '22', '0', '11', '335', '425', '37', '48', '1'], ['bonymaen rfc', '22', '0', '13', '338', '360', '31', '42', '0'], ['corus ( port talbot ) rfc', '22', '1', '14', '319', '466', '37', '52', '2'], ['dunvant rfc', '22', '0', '14', '288', '437', '25', '53', '1'], ['bridgend athletic rfc', '22', '1', '16', '349', '482', '32', '59', '2'], ['waunarlwydd rfc', '22', '1', '17', '278', '624', '31', '80', '0']] |
fred astaire chronology of performances | https://en.wikipedia.org/wiki/Fred_Astaire_chronology_of_performances | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15186990-4.html.csv | unique | june 3rd , 1931 is the only time the director for fred astaire 's performance was hassard short . | {'scope': 'all', 'row': '1', 'col': '5', 'col_other': '1', 'criterion': 'equal', 'value': 'hassard short', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'director', 'hassard short'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose director record fuzzily matches to hassard short .', 'tostr': 'filter_eq { all_rows ; director ; hassard short }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; director ; hassard short } }', 'tointer': 'select the rows whose director record fuzzily matches to hassard short . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'director', 'hassard short'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose director record fuzzily matches to hassard short .', 'tostr': 'filter_eq { all_rows ; director ; hassard short }'}, 'date'], 'result': 'june 3 , 1931', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; director ; hassard short } ; date }'}, 'june 3 , 1931'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; director ; hassard short } ; date } ; june 3 , 1931 }', 'tointer': 'the date record of this unqiue row is june 3 , 1931 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; director ; hassard short } } ; eq { hop { filter_eq { all_rows ; director ; hassard short } ; date } ; june 3 , 1931 } } = true', 'tointer': 'select the rows whose director record fuzzily matches to hassard short . there is only one such row in the table . the date record of this unqiue row is june 3 , 1931 .'} | and { only { filter_eq { all_rows ; director ; hassard short } } ; eq { hop { filter_eq { all_rows ; director ; hassard short } ; date } ; june 3 , 1931 } } = true | select the rows whose director record fuzzily matches to hassard short . there is only one such row in the table . the date record of this unqiue row is june 3 , 1931 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'director_7': 7, 'hassard short_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'date_9': 9, 'june 3 , 1931_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', 'hassard short_8': 'hassard short', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'date_9': 'date', 'june 3 , 1931_10': 'june 3 , 1931'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'director_7': [0], 'hassard short_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'date_9': [2], 'june 3 , 1931_10': [3]} | ['date', 'theatre , studio , or network', 'role', 'dance partner', 'director'] | [['june 3 , 1931', 'new amsterdam', 'himself', 'adele astaire tilly losch', 'hassard short'], ['nov 29 1932', 'ethel barrymore', 'guy holden', 'claire luce', 'howard lindsay'], ['nov 2 1933', 'palace', 'guy holden', 'claire luce', 'felix edwardes'], ['dec 2 , 1933', 'mgm', 'himself', 'joan crawford', 'robert z leonard'], ['dec 20 , 1933', 'rko', 'fred ayres', 'dolores del río ginger rogers', 'thornton freeland'], ['oct 3 , 1934', 'rko', 'guy holden', 'ginger rogers', 'mark sandrich'], ['feb 12 , 1935', 'rko', 'huckleberry haines', 'ginger rogers', 'william a seiter'], ['aug 12 1935', 'nbc', 'himself', '-', '-'], ['aug 16 , 1935', 'rko', 'jerry travers', 'ginger rogers', 'mark sandrich'], ['feb 19 , 1936', 'rko', 'bake baker', 'ginger rogers', 'mark sandrich'], ['aug 26 , 1936', 'rko', 'lucky garnett', 'ginger rogers', 'george stevens'], ['sept 15 1936', 'nbc', 'himself ( host )', '-', '-'], ['apr 30 , 1937', 'rko', 'peter p peters', 'ginger rogers', 'mark sandrich'], ['nov 20 , 1937', 'rko', 'jerry halliday', 'george burns & gracie allen joan fontaine', 'george stevens'], ['aug 30 , 1938', 'rko', 'tony flagg', 'ginger rogers', 'mark sandrich'], ['jan 15 1939', 'nbc', '-', '-', '-'], ['mar 31 , 1939', 'rko', 'vernon castle', 'ginger rogers', 'hc potter'], ['feb 14 , 1940', 'mgm', 'johnny brett', 'eleanor powell george murphy', 'norman taurog'], ['dec 3 , 1940', 'paramount', "danny o'neill", 'paulette goddard', 'hc potter']] |
united states house of representatives elections , 1942 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1942 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1342256-6.html.csv | ordinal | harry lane englebright is the incumbent of the 1942 house of representatives elections with the earliest first elected year . | {'row': '1', 'col': '4', 'order': '1', 'col_other': '2', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'first elected', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; first elected ; 1 }'}, 'incumbent'], 'result': 'harry lane englebright', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; first elected ; 1 } ; incumbent }'}, 'harry lane englebright'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; first elected ; 1 } ; incumbent } ; harry lane englebright } = true', 'tointer': 'select the row whose first elected record of all rows is 1st minimum . the incumbent record of this row is harry lane englebright .'} | eq { hop { nth_argmin { all_rows ; first elected ; 1 } ; incumbent } ; harry lane englebright } = true | select the row whose first elected record of all rows is 1st minimum . the incumbent record of this row is harry lane englebright . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'first elected_5': 5, '1_6': 6, 'incumbent_7': 7, 'harry lane englebright_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmin_0': 'nth_argmin', 'all_rows_4': 'all_rows', 'first elected_5': 'first elected', '1_6': '1', 'incumbent_7': 'incumbent', 'harry lane englebright_8': 'harry lane englebright'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'first elected_5': [0], '1_6': [0], 'incumbent_7': [1], 'harry lane englebright_8': [2]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['california 2', 'harry lane englebright', 'republican', '1926', 're - elected', 'harry lane englebright ( r ) unopposed'], ['california 4', 'thomas rolph', 'republican', '1940', 're - elected', 'thomas rolph ( r ) 98.3 % archie brown ( w / i ) 1.7 %'], ['california 7', 'john h tolan', 'democratic', '1934', 're - elected', 'john h tolan ( d ) unopposed'], ['california 9', 'bertrand w gearhart', 'republican', '1934', 're - elected', 'bertrand w gearhart ( r ) unopposed'], ['california 10', 'alfred j elliott', 'democratic', '1937', 're - elected', 'alfred j elliott ( d ) unopposed'], ['california 17', 'cecil r king', 'democratic', 'august 25 , 1942', 're - elected', 'cecil r king ( d ) unopposed'], ['california 22', 'none ( district created )', 'none ( district created )', 'none ( district created )', 'new seat republican gain', 'john j phillips ( r ) 57.6 % n e west ( d ) 42.4 %']] |
virginia wade | https://en.wikipedia.org/wiki/Virginia_Wade | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-177273-2.html.csv | majority | the majority of virginia wade 's tournaments took place on a grass surface . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'grass', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'surface', 'grass'], 'result': True, 'ind': 0, 'tointer': 'for the surface records of all rows , most of them fuzzily match to grass .', 'tostr': 'most_eq { all_rows ; surface ; grass } = true'} | most_eq { all_rows ; surface ; grass } = true | for the surface records of all rows , most of them fuzzily match to grass . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'surface_3': 3, 'grass_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'surface_3': 'surface', 'grass_4': 'grass'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'surface_3': [0], 'grass_4': [0]} | ['outcome', 'year', 'championship', 'surface', 'partner', 'opponents', 'score'] | [['runner - up', '1969', 'us open', 'grass', 'margaret court', 'françoise dürr darlene hard', '0 - 6 , 6 - 4 , 6 - 4'], ['runner - up', '1970', 'wimbledon', 'grass', 'françoise dürr', 'rosie casals billie jean king', '6 - 2 , 6 - 3'], ['runner - up', '1970', 'us open', 'grass', 'rosie casals', 'margaret court judy tegart dalton', '6 - 3 , 6 - 4'], ['runner - up', '1972', 'us open', 'grass', 'margaret court', 'françoise dürr betty stöve', '6 - 3 , 1 - 6 , 6 - 3'], ['winner', '1973', 'australian open', 'grass', 'margaret court', 'kerry harris kerry melville', '6 - 4 , 6 - 4'], ['winner', '1973', 'french open', 'clay', 'margaret court', 'françoise dürr betty stöve', '6 - 2 , 6 - 3'], ['winner', '1973', 'us open', 'grass', 'margaret court', 'rosie casals billie jean king', '2 - 6 , 6 - 3 , 7 - 5'], ['winner', '1975', 'us open', 'clay', 'margaret court', 'rosie casals billie jean king', '7 - 5 , 2 - 6 , 7 - 6 ( 5 )'], ['runner - up', '1976', 'us open', 'clay', 'olga morozova', 'linky boshoff ilana kloss', '6 - 1 , 6 - 4']] |
1999 masters tournament | https://en.wikipedia.org/wiki/1999_Masters_Tournament | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16514575-3.html.csv | majority | most of the players in the 1999 masters tournament were from the united states . | {'scope': 'all', 'col': '2', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'united states', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'country', 'united states'], 'result': True, 'ind': 0, 'tointer': 'for the country records of all rows , most of them fuzzily match to united states .', 'tostr': 'most_eq { all_rows ; country ; united states } = true'} | most_eq { all_rows ; country ; united states } = true | for the country records of all rows , most of them fuzzily match to united states . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'country_3': 3, 'united states_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'country_3': 'country', 'united states_4': 'united states'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'country_3': [0], 'united states_4': [0]} | ['player', 'country', 'year ( s ) won', 'total', 'to par'] | [['fuzzy zoeller', 'united states', '1979', '149', '+ 5'], ['charles coody', 'united states', '1971', '151', '+ 7'], ['tom watson', 'united states', '1977 , 1981', '151', '+ 7'], ['ben crenshaw', 'united states', '1984 , 1995', '153', '+ 9'], ['nick faldo', 'england', '1989 , 1990 , 1996', '153', '+ 9'], ['seve ballesteros', 'spain', '1980 , 1983', '156', '+ 12'], ['gary player', 'south africa', '1961 , 1974 , 1978', '158', '+ 14'], ['tommy aaron', 'united states', '1973', '159', '+ 14'], ['arnold palmer', 'united states', '1958 , 1960 , 1962 , 1962', '161', '+ 17'], ['gay brewer', 'united states', '1967', 'wd', '+ 8'], ['billy casper', 'united states', '1970', 'wd', '+ 14'], ['doug ford', 'united states', '1957', 'wd', '+ 16']] |
2008 ford world women 's curling championship | https://en.wikipedia.org/wiki/2008_Ford_World_Women%27s_Curling_Championship | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1644876-2.html.csv | count | in the 2008 ford world women 's curling championship , among the skips that had more than 50 ends won , 2 of them had less than 50 ends lost . | {'scope': 'subset', 'criterion': 'less_than', 'value': '50', 'result': '2', 'col': '4', 'subset': {'col': '3', 'criterion': 'greater_than', 'value': '50'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_less', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'ends won', '50'], 'result': None, 'ind': 0, 'tostr': 'filter_greater { all_rows ; ends won ; 50 }', 'tointer': 'select the rows whose ends won record is greater than 50 .'}, 'ends lost', '50'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose ends won record is greater than 50 . among these rows , select the rows whose ends lost record is less than 50 .', 'tostr': 'filter_less { filter_greater { all_rows ; ends won ; 50 } ; ends lost ; 50 }'}], 'result': '2', 'ind': 2, 'tostr': 'count { filter_less { filter_greater { all_rows ; ends won ; 50 } ; ends lost ; 50 } }', 'tointer': 'select the rows whose ends won record is greater than 50 . among these rows , select the rows whose ends lost record is less than 50 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_less { filter_greater { all_rows ; ends won ; 50 } ; ends lost ; 50 } } ; 2 } = true', 'tointer': 'select the rows whose ends won record is greater than 50 . among these rows , select the rows whose ends lost record is less than 50 . the number of such rows is 2 .'} | eq { count { filter_less { filter_greater { all_rows ; ends won ; 50 } ; ends lost ; 50 } } ; 2 } = true | select the rows whose ends won record is greater than 50 . among these rows , select the rows whose ends lost record is less than 50 . the number of such rows is 2 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_less_1': 1, 'filter_greater_0': 0, 'all_rows_5': 5, 'ends won_6': 6, '50_7': 7, 'ends lost_8': 8, '50_9': 9, '2_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_less_1': 'filter_less', 'filter_greater_0': 'filter_greater', 'all_rows_5': 'all_rows', 'ends won_6': 'ends won', '50_7': '50', 'ends lost_8': 'ends lost', '50_9': '50', '2_10': '2'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_less_1': [2], 'filter_greater_0': [1], 'all_rows_5': [0], 'ends won_6': [0], '50_7': [0], 'ends lost_8': [1], '50_9': [1], '2_10': [3]} | ['locale', 'skip', 'ends won', 'ends lost', 'blank ends', 'stolen ends', 'shot %'] | [['china', 'wang bingyu', '57', '43', '6', '18', '80 %'], ['canada', 'jennifer jones', '46', '43', '13', '9', '84 %'], ['switzerland', 'mirjam ott', '51', '46', '7', '11', '81 %'], ['japan', 'moe meguro', '49', '45', '17', '13', '77 %'], ['denmark', 'angelina jensen', '44', '51', '16', '7', '79 %'], ['sweden', 'stina viktorsson', '45', '51', '10', '7', '80 %'], ['united states', 'debbie mccormick', '51', '52', '6', '13', '78 %'], ['russia', 'ludmila privivkova', '45', '48', '11', '12', '78 %'], ['germany', 'andrea schöpp', '49', '45', '17', '14', '77 %'], ['scotland', 'gail munro', '43', '48', '17', '8', '77 %'], ['italy', 'diana gaspari', '45', '47', '14', '10', '74 %'], ['czech republic', 'kateřina urbanová', '40', '46', '16', '10', '72 %']] |
motori moderni | https://en.wikipedia.org/wiki/Motori_Moderni | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1226710-1.html.csv | majority | all entrants with motori moderni used the same engine motori moderni tipo 615 - 90 1.5 v6 t. | {'scope': 'all', 'col': '4', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'motori moderni tipo 615 - 90 1.5 v6 t', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'engine', 'motori moderni tipo 615 - 90 1.5 v6 t'], 'result': True, 'ind': 0, 'tointer': 'for the engine records of all rows , all of them fuzzily match to motori moderni tipo 615 - 90 1.5 v6 t .', 'tostr': 'all_eq { all_rows ; engine ; motori moderni tipo 615 - 90 1.5 v6 t } = true'} | all_eq { all_rows ; engine ; motori moderni tipo 615 - 90 1.5 v6 t } = true | for the engine records of all rows , all of them fuzzily match to motori moderni tipo 615 - 90 1.5 v6 t . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'engine_3': 3, 'motori moderni tipo 615 - 90 1.5 v6 t_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'engine_3': 'engine', 'motori moderni tipo 615 - 90 1.5 v6 t_4': 'motori moderni tipo 615 - 90 1.5 v6 t'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'engine_3': [0], 'motori moderni tipo 615 - 90 1.5 v6 t_4': [0]} | ['year', 'entrant', 'chassis', 'engine', 'tyres', 'points'] | [['1985', 'minardi team spa', 'minardi m185', 'motori moderni tipo 615 - 90 1.5 v6 t', 'p', '0'], ['1985', 'minardi team spa', 'minardi m185', 'motori moderni tipo 615 - 90 1.5 v6 t', 'p', '0'], ['1986', 'minardi team spa', 'minardi m185b m186', 'motori moderni tipo 615 - 90 1.5 v6 t', 'p', '0'], ['1986', 'minardi team spa', 'minardi m185b m186', 'motori moderni tipo 615 - 90 1.5 v6 t', 'p', '0'], ['1986', 'minardi team spa', 'minardi m185b m186', 'motori moderni tipo 615 - 90 1.5 v6 t', 'p', '0'], ['1986', 'jolly club spa', 'ags jh21c', 'motori moderni tipo 615 - 90 1.5 v6 t', 'g', '0'], ['1987', 'minardi team spa', 'minardi m187', 'motori moderni tipo 615 - 90 1.5 v6 t', 'g', '0'], ['1987', 'minardi team spa', 'minardi m187', 'motori moderni tipo 615 - 90 1.5 v6 t', 'g', '0'], ['1987', 'minardi team spa', 'minardi m187', 'motori moderni tipo 615 - 90 1.5 v6 t', 'g', '0']] |
sc 122 | https://en.wikipedia.org/wiki/Convoys_HX_229/SC_122 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12018899-2.html.csv | aggregation | for sc 122 , the average tonnage when the flag is the united kingdom is 5983.8 . | {'scope': 'subset', 'col': '4', 'type': 'average', 'result': '5983.8', 'subset': {'col': '3', 'criterion': 'equal', 'value': 'united kingdom'}} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'flag', 'united kingdom'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; flag ; united kingdom }', 'tointer': 'select the rows whose flag record fuzzily matches to united kingdom .'}, 'tonnage ( grt )'], 'result': '5983.8', 'ind': 1, 'tostr': 'avg { filter_eq { all_rows ; flag ; united kingdom } ; tonnage ( grt ) }'}, '5983.8'], 'result': True, 'ind': 2, 'tostr': 'round_eq { avg { filter_eq { all_rows ; flag ; united kingdom } ; tonnage ( grt ) } ; 5983.8 } = true', 'tointer': 'select the rows whose flag record fuzzily matches to united kingdom . the average of the tonnage ( grt ) record of these rows is 5983.8 .'} | round_eq { avg { filter_eq { all_rows ; flag ; united kingdom } ; tonnage ( grt ) } ; 5983.8 } = true | select the rows whose flag record fuzzily matches to united kingdom . the average of the tonnage ( grt ) record of these rows is 5983.8 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'avg_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'flag_5': 5, 'united kingdom_6': 6, 'tonnage (grt)_7': 7, '5983.8_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'avg_1': 'avg', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'flag_5': 'flag', 'united kingdom_6': 'united kingdom', 'tonnage (grt)_7': 'tonnage ( grt )', '5983.8_8': '5983.8'} | {'eq_2': [3], 'result_3': [], 'avg_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'flag_5': [0], 'united kingdom_6': [0], 'tonnage (grt)_7': [1], '5983.8_8': [2]} | ['date', 'name', 'flag', 'tonnage ( grt )', 'sunk by'] | [['16 / 17 march 1943', 'kingsbury', 'united kingdom', '4898', 'u - 338'], ['16 / 17 march 1943', 'king gruffydd', 'united kingdom', '5072', 'u - 338'], ['16 / 17 march 1943', 'alderamin', 'netherlands', '7886', 'u - 338'], ['17 march 1943', 'fort cedar lake', 'united kingdom', '7134', 'u - 338 , u - 665'], ['17 march 1943', 'port auckland', 'united kingdom', '8789', 'u - 305'], ['18 march 1943', 'zouave', 'united kingdom', '4256', 'u - 305'], ['18 march 1943', 'granville', 'panama', '4071', 'u - 338'], ['18 / 19 march 1943', 'carras', 'greece', '5234', 'u - 333 , u - 666'], ['19 march 1943', 'clarissa radcliffe', 'united kingdom', '5754', 'u - 663']] |
thunder live | https://en.wikipedia.org/wiki/Thunder_Live | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12702752-1.html.csv | majority | most of the japanese releases of casiopea 's thunder live have been on alfa records . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'alfa records', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'label', 'alfa records'], 'result': True, 'ind': 0, 'tointer': 'for the label records of all rows , most of them fuzzily match to alfa records .', 'tostr': 'most_eq { all_rows ; label ; alfa records } = true'} | most_eq { all_rows ; label ; alfa records } = true | for the label records of all rows , most of them fuzzily match to alfa records . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'label_3': 3, 'alfa records_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'label_3': 'label', 'alfa records_4': 'alfa records'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'label_3': [0], 'alfa records_4': [0]} | ['region', 'date', 'label', 'format', 'catalog', 'note'] | [['japan', 'april 21 , 1980', 'alfa records', 'stereo lp', 'alr - 6037', '30 cm'], ['japan', 'december 21 , 1986', 'alfa records', 'cd', '32xa - 106', '12 cm'], ['japan', 'march 21 , 1992', 'alfa records', 'cd', 'alca - 273', '12 cm'], ['japan', 'june 29 , 1994', 'alfa records', 'cd', 'alca - 9003', '12 cm'], ['japan', 'july 23 , 1998', 'alfa records', 'cd', 'alca - 9198', '12 cm'], ['japan', 'december 19 , 2001', 'village records', 'ed remaster cd', 'vrcl - 2203', '12 cm , dsd , lp paper jacket'], ['japan', 'january 17 , 2002', 'village records', 'ed remaster cd', 'vrcl - 2223', '12 cm , dsd'], ['japan', 'may 27 , 2009', 'sony music direct', 'ed remaster cd', 'mhcl - 20005', '12 cm , dsd , blu - spec cd , lp paper jacket']] |
83rd united states congress | https://en.wikipedia.org/wiki/83rd_United_States_Congress | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1652224-5.html.csv | majority | the majority of these seats were vacated because the previous congressman died . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'died', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'reason for change', 'died'], 'result': True, 'ind': 0, 'tointer': 'for the reason for change records of all rows , most of them fuzzily match to died .', 'tostr': 'most_eq { all_rows ; reason for change ; died } = true'} | most_eq { all_rows ; reason for change ; died } = true | for the reason for change records of all rows , most of them fuzzily match to died . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'reason for change_3': 3, 'died_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'reason for change_3': 'reason for change', 'died_4': 'died'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'reason for change_3': [0], 'died_4': [0]} | ['district', 'vacator', 'reason for change', 'successor', 'date successor seated'] | [['georgia 2nd', 'vacant', 'rep edward e cox died during previous congress', 'j l pilcher ( d )', 'february 4 , 1953'], ['south carolina 4th', 'joseph r bryson ( d )', 'died march 10 , 1953', 'robert t ashmore ( d )', 'june 2 , 1953'], ['kentucky 2nd', 'garrett l withers ( d )', 'died april 30 , 1953', 'william h natcher ( d )', 'august 1 , 1953'], ['wisconsin 9th', 'merlin hull ( r )', 'died may 17 , 1953', 'lester johnson ( d )', 'october 13 , 1953'], ['new jersey 6th', 'clifford p case ( r )', 'resigned august 16 , 1953', 'harrison a williams ( d )', 'november 3 , 1953'], ['hawaii territory at - large', 'joseph r farrington ( r )', 'resigned june 19 , 1954', 'elizabeth p farrington ( r )', 'july 31 , 1954'], ['georgia 4th', 'a sidney camp ( d )', 'died july 24 , 1954', 'john j flynt , jr ( d )', 'november 2 , 1954'], ['michigan 3rd', 'paul w shafer ( r )', 'died august 17 , 1954', 'vacant', 'not filled this term'], ['ohio 15th', 'robert t secrest ( d )', 'resigned september 26 , 1954', 'vacant', 'not filled this term']] |
united states house of representatives elections in georgia , 2000 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections_in_Georgia%2C_2000 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-26336739-1.html.csv | ordinal | john lewis recorded the highest percentage ratio among all candidates of the 2000 house of representatives elections . | {'row': '5', 'col': '6', 'order': '1', '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', 'result', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; result ; 1 }'}, 'incumbent'], 'result': 'john lewis', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; result ; 1 } ; incumbent }'}, 'john lewis'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; result ; 1 } ; incumbent } ; john lewis } = true', 'tointer': 'select the row whose result record of all rows is 1st maximum . the incumbent record of this row is john lewis .'} | eq { hop { nth_argmax { all_rows ; result ; 1 } ; incumbent } ; john lewis } = true | select the row whose result record of all rows is 1st maximum . the incumbent record of this row is john lewis . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'result_5': 5, '1_6': 6, 'incumbent_7': 7, 'john lewis_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'result_5': 'result', '1_6': '1', 'incumbent_7': 'incumbent', 'john lewis_8': 'john lewis'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'result_5': [0], '1_6': [0], 'incumbent_7': [1], 'john lewis_8': [2]} | ['district', 'incumbent', 'party', 'elected', 'status', 'result'] | [["georgia 's 1st", 'jack kingston', 'republican', '1992', 're - elected', 'jack kingston ( r ) 69 % joyce marie griggs ( d ) 31 %'], ["georgia 's 2nd", 'sanford bishop', 'democratic', '1992', 're - elected', 'sanford bishop ( d ) 53 % dylan glenn ( r ) 47 %'], ["georgia 's 3rd", 'mac collins', 'republican', '1992', 're - elected', 'mac collins ( r ) 63 % gail notti ( d ) 37 %'], ["georgia 's 4th", 'cynthia mckinney', 'democratic', '1992', 're - elected', 'cynthia mckinney ( d ) 60 % sunny warren ( r ) 40 %'], ["georgia 's 5th", 'john lewis', 'democratic', '1986', 're - elected', 'john lewis ( d ) 77 % hank schwab ( r ) 23 %'], ["georgia 's 6th", 'johnny isakson', 'republican', '1999', 're - elected', 'johnny isakson ( r ) 75 % brett dehart ( d ) 25 %'], ["georgia 's 7th", 'bob barr', 'republican', '1994', 're - elected', 'bob barr ( r ) 54 % roger kahn ( d ) 46 %'], ["georgia 's 8th", 'saxby chambliss', 'republican', '1994', 're - elected', 'saxby chambliss ( r ) 59 % jim marshall ( d ) 41 %'], ["georgia 's 9th", 'nathan deal', 'republican', '1992', 're - elected', 'nathan deal ( r ) 75 % james harrington ( d ) 25 %'], ["georgia 's 10th", 'charlie norwood', 'republican', '1994', 're - elected', 'charlie norwood ( r ) 63 % marion freeman ( d ) 37 %']] |
charlotte county , new brunswick | https://en.wikipedia.org/wiki/Charlotte_County%2C_New_Brunswick | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-170969-2.html.csv | comparative | there are more people in saint george than there are in saint andrews . | {'row_1': '1', 'row_2': '11', 'col': '4', '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', 'official name', 'saint george'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose official name record fuzzily matches to saint george .', 'tostr': 'filter_eq { all_rows ; official name ; saint george }'}, 'population'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; official name ; saint george } ; population }', 'tointer': 'select the rows whose official name record fuzzily matches to saint george . take the population record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'official name', 'saint andrews'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose official name record fuzzily matches to saint andrews .', 'tostr': 'filter_eq { all_rows ; official name ; saint andrews }'}, 'population'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; official name ; saint andrews } ; population }', 'tointer': 'select the rows whose official name record fuzzily matches to saint andrews . take the population record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; official name ; saint george } ; population } ; hop { filter_eq { all_rows ; official name ; saint andrews } ; population } } = true', 'tointer': 'select the rows whose official name record fuzzily matches to saint george . take the population record of this row . select the rows whose official name record fuzzily matches to saint andrews . take the population record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; official name ; saint george } ; population } ; hop { filter_eq { all_rows ; official name ; saint andrews } ; population } } = true | select the rows whose official name record fuzzily matches to saint george . take the population record of this row . select the rows whose official name record fuzzily matches to saint andrews . take the population 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, 'official name_7': 7, 'saint george_8': 8, 'population_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'official name_11': 11, 'saint andrews_12': 12, 'population_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', 'official name_7': 'official name', 'saint george_8': 'saint george', 'population_9': 'population', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'official name_11': 'official name', 'saint andrews_12': 'saint andrews', 'population_13': 'population'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'official name_7': [0], 'saint george_8': [0], 'population_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'official name_11': [1], 'saint andrews_12': [1], 'population_13': [3]} | ['official name', 'status', 'area km 2', 'population', 'census ranking'] | [['saint george', 'parish', '499.51', '2476', '1146 of 5008'], ['pennfield', 'parish', '363.88', '2322', '1206 of 5008'], ['saint stephen', 'parish', '104.41', '2113', '1268 of 5008'], ['saint david', 'parish', '189.91', '1499', '1592 of 5008'], ['saint james', 'parish', '555.99', '1350', '1706 of 5008'], ['campobello', 'parish', '39.59', '1056', '1986 of 5008'], ['lepreau', 'parish', '209.40', '824', '2319 of 5008'], ['west isles', 'parish', '37.93', '824', '2319 of 5008'], ['saint patrick', 'parish', '236.76', '721', '2525 of 5008'], ['saint croix', 'parish', '78.67', '670', '2630 of 5008'], ['saint andrews', 'parish', '24.38', '592', '2797 of 5008'], ['dufferin', 'parish', '12.40', '535', '2919 of 5008'], ['dumbarton', 'parish', '375.06', '356', '3474 of 5008'], ['grand manan', 'parish', '6.20', '190', '4057 of 5008'], ['clarendon', 'parish', '492.84', '71', '4565 of 5008']] |
cyprus in the eurovision song contest 1999 | https://en.wikipedia.org/wiki/Cyprus_in_the_Eurovision_Song_Contest_1999 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11522647-1.html.csv | superlative | marlen angelidou got the most points in the cypriot final of the eurovision song contest 1999 . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '2', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'points'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; points }'}, 'artist'], 'result': 'marlen angelidou', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; points } ; artist }'}, 'marlen angelidou'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; points } ; artist } ; marlen angelidou } = true', 'tointer': 'select the row whose points record of all rows is maximum . the artist record of this row is marlen angelidou .'} | eq { hop { argmax { all_rows ; points } ; artist } ; marlen angelidou } = true | select the row whose points record of all rows is maximum . the artist record of this row is marlen angelidou . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'points_5': 5, 'artist_6': 6, 'marlen angelidou_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'points_5': 'points', 'artist_6': 'artist', 'marlen angelidou_7': 'marlen angelidou'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'points_5': [0], 'artist_6': [1], 'marlen angelidou_7': [2]} | ['draw', 'artist', 'song', 'points', 'place'] | [['1', 'marlen angelidou', "tha ' ne erotas", '225', '1'], ['2', 'riana athanasiou', 'moni', '107', '7'], ['3', 'elena tsolaki', 'aspro feggari', '116', '5'], ['4', 'christina saranti', 'adeio feggari', '102', '8'], ['5', 'stelios constantas', 'methysmeno feggari', '125', '4'], ['6', 'giorgos stamataris', 'maria', '143', '3'], ['7', 'lucas christodolou', 'an gyriseis', '113', '6'], ['8', 'giorgos gavriel', 'pios erotas glykos', '88', '9'], ['9', 'demos beke', 'tha sou edina oli mou ti zoi', '178', '2']] |
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