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.38 special | https://en.wikipedia.org/wiki/.38_Special | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-173103-1.html.csv | comparative | the .357 sig has a higher maximum pressure psi than the .380 acp cartridge . | {'row_1': '13', 'row_2': '7', 'col': '5', 'col_other': '1', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'cartridge', '.357 sig'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose cartridge record fuzzily matches to .357 sig .', 'tostr': 'filter_eq { all_rows ; cartridge ; .357 sig }'}, 'max pressure'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; cartridge ; .357 sig } ; max pressure }', 'tointer': 'select the rows whose cartridge record fuzzily matches to .357 sig . take the max pressure record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'cartridge', '.380 acp'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose cartridge record fuzzily matches to .380 acp .', 'tostr': 'filter_eq { all_rows ; cartridge ; .380 acp }'}, 'max pressure'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; cartridge ; .380 acp } ; max pressure }', 'tointer': 'select the rows whose cartridge record fuzzily matches to .380 acp . take the max pressure record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; cartridge ; .357 sig } ; max pressure } ; hop { filter_eq { all_rows ; cartridge ; .380 acp } ; max pressure } } = true', 'tointer': 'select the rows whose cartridge record fuzzily matches to .357 sig . take the max pressure record of this row . select the rows whose cartridge record fuzzily matches to .380 acp . take the max pressure record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; cartridge ; .357 sig } ; max pressure } ; hop { filter_eq { all_rows ; cartridge ; .380 acp } ; max pressure } } = true | select the rows whose cartridge record fuzzily matches to .357 sig . take the max pressure record of this row . select the rows whose cartridge record fuzzily matches to .380 acp . take the max pressure 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, 'cartridge_7': 7, '.357 sig_8': 8, 'max pressure_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'cartridge_11': 11, '.380 acp_12': 12, 'max pressure_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', 'cartridge_7': 'cartridge', '.357 sig_8': '.357 sig', 'max pressure_9': 'max pressure', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'cartridge_11': 'cartridge', '.380 acp_12': '.380 acp', 'max pressure_13': 'max pressure'} | {'greater_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'cartridge_7': [0], '.357 sig_8': [0], 'max pressure_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'cartridge_11': [1], '.380 acp_12': [1], 'max pressure_13': [3]} | ['cartridge', 'bullet weight', 'muzzle velocity', 'muzzle energy', 'max pressure'] | [['.38 short colt', 'gr ( g )', 'ft / s ( m / s )', '181ft lbf ( 245 j )', '7500 cup'], ['.38 long colt', 'gr ( g )', 'ft / s ( m / s )', '201ft lbf ( 273 j )', '12000 cup'], ['.38 s & w', 'gr ( g )', 'ft / s ( m / s )', '206ft lbf ( 279 j )', '14500 psi'], ['.38 s & w special', 'gr ( g )', 'ft / s ( m / s )', '310ft lbf ( 420 j )', '17000 psi'], ['.38 special + p', 'gr ( g )', 'ft / s ( m / s )', '351ft lbf ( 476 j )', '20000 psi'], ['.38 special + p +', 'gr ( g )', 'ft / s ( m / s )', '295ft lbf ( 400 j )', '> 20000 psi'], ['.380 acp', 'gr ( g )', 'ft / s ( m / s )', '178ft lbf ( 241 j )', '21500 psi'], ['9x19 mm parabellum', 'gr ( g )', 'ft / s ( m / s )', '420ft lbf ( 570 j )', '39200 psi'], ['9x19 mm parabellum', 'gr ( g )', 'ft / s ( m / s )', '383ft lbf ( 520 j )', '39200 psi'], ['9x18 mm makarov', 'gr ( g )', 'ft / s ( m / s )', '231ft lbf ( 313 j )', '23206 psi'], ['.38 super', 'grains ( g )', 'ft / s ( m / s )', '468ft lbf ( 634 j )', '36500 psi'], ['.357 magnum', 'grains ( g )', 'ft / s ( m / s )', '639ft lbf ( 866 j )', '35000 psi'], ['.357 sig', 'grains ( g )', 'ft / s ( m / s )', '506ft lbf ( 686 j )', '40000 psi']] |
1973 u.s. open ( golf ) | https://en.wikipedia.org/wiki/1973_U.S._Open_%28golf%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17245540-2.html.csv | majority | of the players in the 1973 us open , most had a total under 300 . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'less_than', 'value': '300', 'subset': None} | {'func': 'most_less', 'args': ['all_rows', 'total', '300'], 'result': True, 'ind': 0, 'tointer': 'for the total records of all rows , most of them are less than 300 .', 'tostr': 'most_less { all_rows ; total ; 300 } = true'} | most_less { all_rows ; total ; 300 } = true | for the total records of all rows , most of them are less than 300 . | 1 | 1 | {'most_less_0': 0, 'result_1': 1, 'all_rows_2': 2, 'total_3': 3, '300_4': 4} | {'most_less_0': 'most_less', 'result_1': 'true', 'all_rows_2': 'all_rows', 'total_3': 'total', '300_4': '300'} | {'most_less_0': [1], 'result_1': [], 'all_rows_2': [0], 'total_3': [0], '300_4': [0]} | ['player', 'country', 'year ( s ) won', 'total', 'to par', 'finish'] | [['jack nicklaus', 'united states', '1962 , 1967 , 1972', '282', '- 2', 't4'], ['arnold palmer', 'united states', '1960', '282', '- 2', 't4'], ['lee trevino', 'united states', '1968 , 1971', '282', '- 2', 't4'], ['julius boros', 'united states', '1952 , 1963', '283', '- 1', 't7'], ['gary player', 'south africa', '1965', '287', '+ 3', '12'], ['gene littler', 'united states', '1961', '291', '+ 7', 't18'], ['tony jacklin', 'england', '1970', '300', '+ 16', 't52']] |
list of geological features on venus | https://en.wikipedia.org/wiki/List_of_geological_features_on_Venus | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16799784-15.html.csv | aggregation | the average diameter of a named geological feature on venus is 512.6 kilometers . | {'scope': 'all', 'col': '4', 'type': 'average', 'result': '512.6', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'diameter ( km )'], 'result': '512.6', 'ind': 0, 'tostr': 'avg { all_rows ; diameter ( km ) }'}, '512.6'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; diameter ( km ) } ; 512.6 } = true', 'tointer': 'the average of the diameter ( km ) record of all rows is 512.6 .'} | round_eq { avg { all_rows ; diameter ( km ) } ; 512.6 } = true | the average of the diameter ( km ) record of all rows is 512.6 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'diameter (km)_4': 4, '512.6_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'diameter (km)_4': 'diameter ( km )', '512.6_5': '512.6'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'diameter (km)_4': [0], '512.6_5': [1]} | ['name', 'latitude', 'longitude', 'diameter ( km )', 'year named'] | [['akkruva colles', '46.1 n', '115.5 e', '1059.0', '1985'], ['asherat colles', '12.0 n', '162.0 e', '500.0', '2003'], ['chernava colles', '10.5 s', '335.5 e', '1000.0', '1997'], ['jurate colles', '56.8 n', '153.5 e', '418.0', '1985'], ['marake colles', '55.7 n', '217.8 e', '150.0', '1997'], ['mena colles', '52.5 s', '160.0 e', '850.0', '1994'], ['migazesh colles', '49.0 s', '198.0 e', '230.0', '2000'], ['molpe colles', '76.0 n', '192.0 e', '548.0', '1991'], ['nahete colles', '38.0 n', '241.0 e', '400.0', '1997'], ['nuliayoq colles', '48.0 n', '224.0 e', '350.0', '1997'], ['olosa colles', '18.0 n', '353.3 e', '200.0', '1997'], ['ran colles', '1.0 n', '163.0 e', '400.0', '2003'], ['ruad colles', '68.0 s', '118.0 e', '400.0', '1997'], ['salofa colles', '63.0 s', '167.0 e', '250.0', '1997'], ["t ' ien hu colles", '30.7 n', '15.1 e', '947.0', '1991'], ['urutonga colles', '10.0 n', '154.0 e', '500.0', '2003']] |
2010 - 11 indiana pacers season | https://en.wikipedia.org/wiki/2010%E2%80%9311_Indiana_Pacers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27756164-7.html.csv | majority | all games of the indiana pacers ' in the 2010 - 11 season were scheduled for the month of december . | {'scope': 'all', 'col': '2', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'december', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'date', 'december'], 'result': True, 'ind': 0, 'tointer': 'for the date records of all rows , all of them fuzzily match to december .', 'tostr': 'all_eq { all_rows ; date ; december } = true'} | all_eq { all_rows ; date ; december } = true | for the date records of all rows , all of them fuzzily match to december . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'date_3': 3, 'december_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'date_3': 'date', 'december_4': 'december'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'date_3': [0], 'december_4': [0]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record'] | [['17', 'december 1', 'utah', 'l 88 - 110 ( ot )', 'darren collison ( 16 )', 'danny granger ( 7 )', 'darren collison , josh mcroberts ( 5 )', 'energysolutions arena 18732', '9 - 8'], ['18', 'december 3', 'phoenix', 'l 97 - 105 ( ot )', 'brandon rush ( 21 )', 'josh mcroberts ( 9 )', 't j ford ( 9 )', 'us airways center 16991', '9 - 9'], ['19', 'december 6', 'toronto', 'w 124 - 100 ( ot )', 'brandon rush ( 26 )', 'danny granger ( 9 )', 't j ford , roy hibbert , josh mcroberts ( 6 )', 'conseco fieldhouse 11930', '10 - 9'], ['20', 'december 8', 'milwaukee', 'l 95 - 97 ( ot )', 'danny granger ( 26 )', 'josh mcroberts ( 7 )', 'josh mcroberts ( 5 )', 'bradley center 12789', '10 - 10'], ['21', 'december 10', 'charlotte', 'w 100 - 92 ( ot )', 'danny granger ( 18 )', 'roy hibbert ( 14 )', 'darren collison ( 7 )', 'conseco fieldhouse 13128', '11 - 10'], ['22', 'december 11', 'atlanta', 'l 83 - 97 ( ot )', 'mike dunleavy ( 16 )', 'mike dunleavy ( 9 )', 'darren collison ( 5 )', 'philips arena 14131', '11 - 11'], ['23', 'december 13', 'chicago', 'l 73 - 92 ( ot )', 't j ford , brandon rush ( 13 )', 'mike dunleavy ( 8 )', 't j ford ( 4 )', 'united center 21287', '11 - 12'], ['24', 'december 15', 'la lakers', 'l 94 - 109 ( ot )', 'darren collison ( 17 )', 'james posey ( 7 )', 'darren collison , t j ford ( 6 )', 'conseco fieldhouse 18165', '11 - 13'], ['25', 'december 17', 'cleveland', 'w 108 - 99 ( ot )', 'danny granger ( 30 )', 'danny granger ( 12 )', 'darren collison ( 5 )', 'conseco fieldhouse 12021', '12 - 13'], ['26', 'december 19', 'boston', 'l 88 - 99 ( ot )', 'danny granger ( 19 )', 'roy hibbert ( 14 )', 't j ford , james posey ( 3 )', 'td garden 18624', '12 - 14'], ['27', 'december 20', 'new orleans', 'w 94 - 93 ( ot )', 'danny granger ( 27 )', 'jeff foster ( 11 )', 'darren collison , t j ford ( 5 )', 'conseco fieldhouse 12271', '13 - 14'], ['28', 'december 26', 'memphis', 'l 90 - 104 ( ot )', 'danny granger ( 29 )', 'roy hibbert ( 10 )', 'darren collison , t j ford ( 4 )', 'conseco fieldhouse 12630', '13 - 15'], ['29', 'december 28', 'boston', 'l 83 - 95 ( ot )', 'brandon rush ( 17 )', 'roy hibbert ( 8 )', 'danny granger ( 4 )', 'conseco fieldhouse 18165', '13 - 16'], ['30', 'december 29', 'washington', 'l 90 - 104 ( ot )', 'mike dunleavy ( 20 )', 'danny granger ( 9 )', 'darren collison ( 5 )', 'verizon center 16108', '13 - 17']] |
united states house of representatives elections , 1952 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1952 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1342149-24.html.csv | ordinal | jamie l whitten was the second incumbent to be first elected before the 1952 united states house of representatives elections . | {'row': '3', 'col': '4', 'order': '2', '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', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; first elected ; 2 }'}, 'incumbent'], 'result': 'jamie l whitten', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; first elected ; 2 } ; incumbent }'}, 'jamie l whitten'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; first elected ; 2 } ; incumbent } ; jamie l whitten } = true', 'tointer': 'select the row whose first elected record of all rows is 2nd minimum . the incumbent record of this row is jamie l whitten .'} | eq { hop { nth_argmin { all_rows ; first elected ; 2 } ; incumbent } ; jamie l whitten } = true | select the row whose first elected record of all rows is 2nd minimum . the incumbent record of this row is jamie l whitten . | 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, '2_6': 6, 'incumbent_7': 7, 'jamie l whitten_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', '2_6': '2', 'incumbent_7': 'incumbent', 'jamie l whitten_8': 'jamie l whitten'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'first elected_5': [0], '2_6': [0], 'incumbent_7': [1], 'jamie l whitten_8': [2]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['mississippi 1', 'thomas abernethy redistricted from 4th', 'democratic', '1942', 're - elected', 'thomas abernethy ( d ) unopposed'], ['mississippi 1', 'john e rankin', 'democratic', '1920', 'lost renomination democratic loss', 'thomas abernethy ( d ) unopposed'], ['mississippi 2', 'jamie l whitten', 'democratic', '1941', 're - elected', 'jamie l whitten ( d ) unopposed'], ['mississippi 3', 'frank e smith', 'democratic', '1950', 're - elected', 'frank e smith ( d ) 87.2 % paul clark ( r ) 12.8 %'], ['mississippi 4', 'john bell williams redistricted from 7th', 'democratic', '1946', 're - elected', 'john bell williams ( d ) unopposed']] |
wnba finals | https://en.wikipedia.org/wiki/WNBA_Finals | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1164512-3.html.csv | ordinal | the new york liberty team recorded the highest number of losses in the wnba finals . | {'row': '3', 'col': '4', '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', 'losses', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; losses ; 1 }'}, 'team'], 'result': 'new york liberty', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; losses ; 1 } ; team }'}, 'new york liberty'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; losses ; 1 } ; team } ; new york liberty } = true', 'tointer': 'select the row whose losses record of all rows is 1st maximum . the team record of this row is new york liberty .'} | eq { hop { nth_argmax { all_rows ; losses ; 1 } ; team } ; new york liberty } = true | select the row whose losses record of all rows is 1st maximum . the team record of this row is new york liberty . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'losses_5': 5, '1_6': 6, 'team_7': 7, 'new york liberty_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', 'losses_5': 'losses', '1_6': '1', 'team_7': 'team', 'new york liberty_8': 'new york liberty'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'losses_5': [0], '1_6': [0], 'team_7': [1], 'new york liberty_8': [2]} | ['finals', 'team', 'wins', 'losses', 'pct'] | [['4', 'houston comets 2', '4', '0', '1.000'], ['4', 'detroit shock 3', '3', '1', '750'], ['4', 'new york liberty', '0', '4', '000'], ['3', 'los angeles sparks', '2', '1', '667'], ['3', 'phoenix mercury', '2', '1', '667'], ['3', 'atlanta dream', '0', '3', '000'], ['3', 'minnesota lynx', '2', '1', '667'], ['2', 'seattle storm', '2', '0', '1.000'], ['2', 'sacramento monarchs 4', '1', '1', '500'], ['2', 'connecticut sun', '0', '2', '000'], ['2', 'indiana fever', '1', '1', '500'], ['1', 'san antonio silver stars', '0', '1', '000'], ['1', 'charlotte sting 1', '0', '1', '000']] |
list of dr. floyd episodes | https://en.wikipedia.org/wiki/List_of_Dr._Floyd_episodes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10621888-3.html.csv | superlative | for dr. floyd episodes , the one with the longest run time , is episode 313 . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '13', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'run time'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; run time }'}, 'episode number'], 'result': '313', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; run time } ; episode number }'}, '313'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; run time } ; episode number } ; 313 } = true', 'tointer': 'select the row whose run time record of all rows is maximum . the episode number record of this row is 313 .'} | eq { hop { argmax { all_rows ; run time } ; episode number } ; 313 } = true | select the row whose run time record of all rows is maximum . the episode number record of this row is 313 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'num_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'run time_5': 5, 'episode number_6': 6, '313_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'num_hop_1': 'num_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'run time_5': 'run time', 'episode number_6': 'episode number', '313_7': '313'} | {'eq_2': [3], 'result_3': [], 'num_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'run time_5': [0], 'episode number_6': [1], '313_7': [2]} | ['episode number', 'title', 'podcast date', 'run time', 'historical references'] | [['301', 'home sweet home !', 'august 1 , 2005', '6:07', 'none'], ['302', 'the adventures of lewis & clark !', 'august 8 , 2005', '4:16', 'meriwether lewis & william clark'], ['303', 'call of the wild !', 'august 14 , 2005', '4:49', 'meriwether lewis & william clark'], ['304', 'the greatest show on earth !', 'august 21 , 2005', '5:16', 'pt barnum'], ['305', 'hitting the bricks !', 'august 28 , 2005', '5:48', 'pt barnum'], ['306', 'fiji queasy !', 'september 4 , 2005', '4:59', 'pt barnum'], ['307', 'accident in time !', 'september 11 , 2005', '5:04', 'none'], ['308', "all 's wells that ends welles !", 'september 18 , 2005', '5:51', 'hg wells & orson welles'], ['309', 'jump the shark !', 'september 25 , 2005', '5:04', 'jumping the shark'], ['310', 'jump the shark ! part ii !', 'october 2 , 2005', '4:36', 'jumping the shark'], ['311', 'annie are you oakley are you oakley , annie !', 'october 9 , 2005', '6:13', 'annie oakley & buffalo bill cody'], ['312', 'reach for the sky !', 'october 16 , 2005', '5:52', 'annie oakley & buffalo bill cody'], ['313', 'as the worm turns !', 'october 23 , 2005', '6:31', 'none']] |
sébastien bourdais | https://en.wikipedia.org/wiki/S%C3%A9bastien_Bourdais | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1019053-15.html.csv | superlative | the best ranking that sébastien bourdais had in his participations on the grand-am rolex sports car series was in the 2012 year . | {'scope': 'all', 'col_superlative': '6', 'row_superlative': '4', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '1', 'subset': None} | {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'argmin', 'args': ['all_rows', 'rank'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; rank }'}, 'year'], 'result': '2012', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; rank } ; year }'}, '2012'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmin { all_rows ; rank } ; year } ; 2012 } = true', 'tointer': 'select the row whose rank record of all rows is minimum . the year record of this row is 2012 .'} | eq { hop { argmin { all_rows ; rank } ; year } ; 2012 } = true | select the row whose rank record of all rows is minimum . the year record of this row is 2012 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'num_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'rank_5': 5, 'year_6': 6, '2012_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'num_hop_1': 'num_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'rank_5': 'rank', 'year_6': 'year', '2012_7': '2012'} | {'eq_2': [3], 'result_3': [], 'num_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'rank_5': [0], 'year_6': [1], '2012_7': [2]} | ['year', 'team', 'make', 'engine', 'class', 'rank', 'points'] | [['2005', 'newman racing / silverstone racing', 'crawford dp03', 'ford', 'dp', '89th', '6'], ['2006', 'doran racing', 'doran je4', 'ford', 'dp', '108th', '3'], ['2010', 'crown royal / npn racing', 'riley mk xi', 'bmw 5.0 l v8', 'dp', 'nc', '0'], ['2012', 'starworks motorsport', 'riley mk xxvi', 'ford', 'dp', '17th', '97'], ['2013', 'starworks motorsport', 'riley mk xxvi', 'ford', 'dp', '18th', '160']] |
2006 masters tournament | https://en.wikipedia.org/wiki/2006_Masters_Tournament | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12626983-7.html.csv | aggregation | the players in the 2006 masters tournament won an average money amount of 420350 . | {'scope': 'all', 'col': '6', 'type': 'average', 'result': '420350', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'money'], 'result': '420350', 'ind': 0, 'tostr': 'avg { all_rows ; money }'}, '420350'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; money } ; 420350 } = true', 'tointer': 'the average of the money record of all rows is 420350 .'} | round_eq { avg { all_rows ; money } ; 420350 } = true | the average of the money record of all rows is 420350 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'money_4': 4, '420350_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'money_4': 'money', '420350_5': '420350'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'money_4': [0], '420350_5': [1]} | ['place', 'player', 'country', 'score', 'to par', 'money'] | [['1', 'phil mickelson', 'united states', '70 + 72 + 70 + 69 = 281', '- 7', '1260000'], ['2', 'tim clark', 'south africa', '70 + 72 + 72 + 69 = 283', '- 5', '756000'], ['t3', 'chad campbell', 'united states', '71 + 67 + 75 + 71 = 284', '- 4', '315700'], ['t3', 'fred couples', 'united states', '71 + 70 + 72 + 71 = 284', '- 4', '315700'], ['t3', 'retief goosen', 'south africa', '70 + 73 + 72 + 69 = 284', '- 4', '315700'], ['t3', 'josé maría olazábal', 'spain', '76 + 71 + 71 + 66 = 284', '- 4', '315700'], ['t3', 'tiger woods', 'united states', '72 + 71 + 71 + 70 = 284', '- 4', '315700'], ['t8', 'ángel cabrera', 'argentina', '73 + 74 + 70 + 68 = 285', '- 3', '210000'], ['t8', 'vijay singh', 'fiji', '67 + 74 + 73 + 71 = 285', '- 3', '210000'], ['10', 'stewart cink', 'united states', '72 + 73 + 71 + 70 = 286', '- 2', '189000']] |
1990 fei world equestrian games | https://en.wikipedia.org/wiki/1990_FEI_World_Equestrian_Games | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11871903-2.html.csv | superlative | west germany won the most total medals in the 1990 fei world equestrian games . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'total'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; total }'}, 'nation'], 'result': 'west germany', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; total } ; nation }'}, 'west germany'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; total } ; nation } ; west germany } = true', 'tointer': 'select the row whose total record of all rows is maximum . the nation record of this row is west germany .'} | eq { hop { argmax { all_rows ; total } ; nation } ; west germany } = true | select the row whose total record of all rows is maximum . the nation record of this row is west germany . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'total_5': 5, 'nation_6': 6, 'west germany_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'total_5': 'total', 'nation_6': 'nation', 'west germany_7': 'west germany'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'total_5': [0], 'nation_6': [1], 'west germany_7': [2]} | ['nation', 'gold', 'silver', 'bronze', 'total'] | [['west germany', '4', '4', '4', '12'], ['france', '2', '-', '1', '3'], ['new zealand', '2', '-', '-', '2'], ['sweden', '2', '-', '-', '2'], ['united kingdom', '1', '4', '1', '6'], ['united states', '1', '-', '2', '3'], ['switzerland', '1', '-', '1', '2'], ['hungary', '-', '1', '1', '2'], ['netherlands', '-', '1', '1', '2'], ['belgium', '-', '1', '-', '1'], ['finland', '-', '1', '-', '1'], ['soviet union', '-', '1', '-', '1'], ['australia', '-', '-', '1', '1'], ['spain', '-', '-', '1', '1']] |
dessine - moi un mouton | https://en.wikipedia.org/wiki/Dessine-moi_un_mouton | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14857820-1.html.csv | unique | the album version of dessine - moi un mouton was the only one released in the year 1999 . | {'scope': 'all', 'row': '1', 'col': '5', 'col_other': '1', 'criterion': 'equal', 'value': '1999', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'year', '1999'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose year record is equal to 1999 .', 'tostr': 'filter_eq { all_rows ; year ; 1999 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; year ; 1999 } }', 'tointer': 'select the rows whose year record is equal to 1999 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'year', '1999'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose year record is equal to 1999 .', 'tostr': 'filter_eq { all_rows ; year ; 1999 }'}, 'version'], 'result': 'album version', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; year ; 1999 } ; version }'}, 'album version'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; year ; 1999 } ; version } ; album version }', 'tointer': 'the version record of this unqiue row is album version .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; year ; 1999 } } ; eq { hop { filter_eq { all_rows ; year ; 1999 } ; version } ; album version } } = true', 'tointer': 'select the rows whose year record is equal to 1999 . there is only one such row in the table . the version record of this unqiue row is album version .'} | and { only { filter_eq { all_rows ; year ; 1999 } } ; eq { hop { filter_eq { all_rows ; year ; 1999 } ; version } ; album version } } = true | select the rows whose year record is equal to 1999 . there is only one such row in the table . the version record of this unqiue row is album version . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'year_7': 7, '1999_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'version_9': 9, 'album version_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'year_7': 'year', '1999_8': '1999', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'version_9': 'version', 'album version_10': 'album version'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'year_7': [0], '1999_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'version_9': [2], 'album version_10': [3]} | ['version', 'length', 'album', 'remixed by', 'year'] | [['album version', '4:34', 'innamoramento', '-', '1999'], ['live version ( recorded in 2000 )', '4:50 ( cd ) 6:40 ( dvd / vhs ) 4:16 ( cassette )', 'mylenium tour', '-', '2000'], ['single live version', '4:34', '-', 'laurent boutonnat', '2000'], ['live radio edit', '4:05', '-', 'laurent boutonnat', '2000'], ['world is mine remix', '4:53', '-', 'quentin and visa', '2000'], ['snakebite beat mix', '4:42', '-', 'osman and visa', '2000'], ['draw me a sheep remix', '3:53', '-', 'hot sly and visa', '2000'], ['music video', '4:56', '-', '-', '2000']] |
greg pursley | https://en.wikipedia.org/wiki/Greg_Pursley | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15544826-1.html.csv | superlative | from 1999 to 2012 , greg pursley 's greatest number of wins was in 2011 . | {'scope': 'all', 'col_superlative': '3', 'row_superlative': '7', 'value_mentioned': 'yes', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'max', 'args': ['all_rows', 'wins'], 'result': '6', 'ind': 0, 'tostr': 'max { all_rows ; wins }', 'tointer': 'the maximum wins record of all rows is 6 .'}, '6'], 'result': True, 'ind': 1, 'tostr': 'eq { max { all_rows ; wins } ; 6 }', 'tointer': 'the maximum wins record of all rows is 6 .'}, {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'wins'], 'result': None, 'ind': 2, 'tostr': 'argmax { all_rows ; wins }'}, 'year'], 'result': '2011', 'ind': 3, 'tostr': 'hop { argmax { all_rows ; wins } ; year }'}, '2011'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { argmax { all_rows ; wins } ; year } ; 2011 }', 'tointer': 'the year record of the row with superlative wins record is 2011 .'}], 'result': True, 'ind': 5, 'tostr': 'and { eq { max { all_rows ; wins } ; 6 } ; eq { hop { argmax { all_rows ; wins } ; year } ; 2011 } } = true', 'tointer': 'the maximum wins record of all rows is 6 . the year record of the row with superlative wins record is 2011 .'} | and { eq { max { all_rows ; wins } ; 6 } ; eq { hop { argmax { all_rows ; wins } ; year } ; 2011 } } = true | the maximum wins record of all rows is 6 . the year record of the row with superlative wins record is 2011 . | 6 | 6 | {'and_5': 5, 'result_6': 6, 'eq_1': 1, 'max_0': 0, 'all_rows_7': 7, 'wins_8': 8, '6_9': 9, 'eq_4': 4, 'num_hop_3': 3, 'argmax_2': 2, 'all_rows_10': 10, 'wins_11': 11, 'year_12': 12, '2011_13': 13} | {'and_5': 'and', 'result_6': 'true', 'eq_1': 'eq', 'max_0': 'max', 'all_rows_7': 'all_rows', 'wins_8': 'wins', '6_9': '6', 'eq_4': 'eq', 'num_hop_3': 'num_hop', 'argmax_2': 'argmax', 'all_rows_10': 'all_rows', 'wins_11': 'wins', 'year_12': 'year', '2011_13': '2011'} | {'and_5': [6], 'result_6': [], 'eq_1': [5], 'max_0': [1], 'all_rows_7': [0], 'wins_8': [0], '6_9': [1], 'eq_4': [5], 'num_hop_3': [4], 'argmax_2': [3], 'all_rows_10': [2], 'wins_11': [2], 'year_12': [3], '2011_13': [4]} | ['year', 'races', 'wins', 'top 5', 'top 10', 'poles', 'avg start', 'avg finish', 'season rank'] | [['1999', '1', '0', '0', '0', '0', '16.0', '11.0', '64th'], ['2002', '10', '0', '2', '5', '0', '9.2', '10.2', '9th'], ['2007', '1', '0', '0', '0', '0', '22.0', '29.0', '69th'], ['2008', '4', '0', '0', '0', '0', '12.8', '25.2', '32nd'], ['2009', '13', '1', '8', '11', '2', '6.5', '6.3', '3rd'], ['2010', '12', '2', '4', '7', '3', '4.7', '11.6', '5th'], ['2011', '14', '6', '12', '12', '6', '3.3', '5.2', '1st'], ['2012', '9', '2', '7', '9', '3', '3.2', '3.8', '2nd']] |
list of little house on the prairie episodes | https://en.wikipedia.org/wiki/List_of_Little_House_on_the_Prairie_episodes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1854728-2.html.csv | superlative | the first episode of little house on the prairie to originally air in 1975 was entitled family quarrel . | {'scope': 'subset', 'col_superlative': '5', 'row_superlative': '15', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '2', 'subset': {'col': '5', 'criterion': 'fuzzily_match', 'value': '1975'}} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmin', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'air date', '1975'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; air date ; 1975 }', 'tointer': 'select the rows whose air date record fuzzily matches to 1975 .'}, 'air date'], 'result': None, 'ind': 1, 'tostr': 'argmin { filter_eq { all_rows ; air date ; 1975 } ; air date }'}, 'title'], 'result': 'family quarrel', 'ind': 2, 'tostr': 'hop { argmin { filter_eq { all_rows ; air date ; 1975 } ; air date } ; title }'}, 'family quarrel'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { argmin { filter_eq { all_rows ; air date ; 1975 } ; air date } ; title } ; family quarrel } = true', 'tointer': 'select the rows whose air date record fuzzily matches to 1975 . select the row whose air date record of these rows is minimum . the title record of this row is family quarrel .'} | eq { hop { argmin { filter_eq { all_rows ; air date ; 1975 } ; air date } ; title } ; family quarrel } = true | select the rows whose air date record fuzzily matches to 1975 . select the row whose air date record of these rows is minimum . the title record of this row is family quarrel . | 4 | 4 | {'str_eq_3': 3, 'result_4': 4, 'str_hop_2': 2, 'argmin_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'air date_6': 6, '1975_7': 7, 'air date_8': 8, 'title_9': 9, 'family quarrel_10': 10} | {'str_eq_3': 'str_eq', 'result_4': 'true', 'str_hop_2': 'str_hop', 'argmin_1': 'argmin', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'air date_6': 'air date', '1975_7': '1975', 'air date_8': 'air date', 'title_9': 'title', 'family quarrel_10': 'family quarrel'} | {'str_eq_3': [4], 'result_4': [], 'str_hop_2': [3], 'argmin_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'air date_6': [0], '1975_7': [0], 'air date_8': [1], 'title_9': [2], 'family quarrel_10': [3]} | ['no in series', 'title', 'directed by', 'written by', 'air date', 'production code'] | [['1', 'a harvest of friends', 'michael landon', 'blanche hanalis , john hawkins & william putman', 'september 11 , 1974', '1002'], ['2', 'country girls', 'william f claxton', 'blanche hanalis & juanita bartlett', 'september 18 , 1974', '1001'], ['3', '100 mile walk', 'william f claxton', 'blanche hanalis & ward hawkins', 'september 25 , 1974', '1003'], ['4', "mr edwards ' homecoming", 'michael landon', 'blanche hanalis & joel murcott', 'october 2 , 1974', '1004'], ['5', 'the love of johnny johnson', 'william f claxton', 'blanche hanalis & gerry day', 'october 9 , 1974', '1005'], ['6', 'if i should wake before i die', 'victor french', 'blanche hanalis & harold swanton', 'october 23 , 1974', '1006'], ['7', 'town party , country party', 'alf kjellin', 'blanche hanalis & juanita bartlett', 'october 30 , 1974', '1007'], ['8', "ma 's holiday", 'leo penn', 'blanche hanalis & dale eunson', 'november 6 , 1974', '1010'], ['9', 'school mom', 'william f claxton', 'blanche hanalis , ward hawkins & jean rouverol', 'november 13 , 1974', '1011'], ['10', 'the raccoon', 'william f claxton', 'blanche hanalis & joseph bonaduce', 'november 20 , 1974', '1013'], ['11', 'the voice of tinker jones', 'leo penn', 'tony kayden & michael russnow', 'december 4 , 1974', '1012'], ['12', 'the award', 'william f claxton', 'michael landon', 'december 11 , 1974', '1014'], ['13 / 14', 'the lord is my shepherd', 'michael landon', 'michael landon', 'december 18 , 1974', '1008 / 1009'], ['15', 'christmas at plum creek', 'william f claxton', 'arthur heinemann', 'december 25 , 1974', '1015'], ['16', 'family quarrel', 'william f claxton', 'ward hawkins', 'january 8 , 1975', '1016'], ['20', 'child of pain', 'victor french', 'john meston', 'february 12 , 1975', '1020'], ['21', 'money crop', 'leo penn', 'teleplay by : ward hawkins story by : john meston', 'february 19 , 1975', '1021']] |
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/2-15753390-1.html.csv | ordinal | mick grant had the third most points among competitors at the 1972 isle of man tt . | {'row': '3', 'col': '7', 'order': '3', 'col_other': '2', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'points', '3'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; points ; 3 }'}, 'rider'], 'result': 'mick grant', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; points ; 3 } ; rider }'}, 'mick grant'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; points ; 3 } ; rider } ; mick grant } = true', 'tointer': 'select the row whose points record of all rows is 3rd maximum . the rider record of this row is mick grant .'} | eq { hop { nth_argmax { all_rows ; points ; 3 } ; rider } ; mick grant } = true | select the row whose points record of all rows is 3rd maximum . the rider record of this row is mick grant . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'points_5': 5, '3_6': 6, 'rider_7': 7, 'mick grant_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', 'points_5': 'points', '3_6': '3', 'rider_7': 'rider', 'mick grant_8': 'mick grant'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'points_5': [0], '3_6': [0], 'rider_7': [1], 'mick grant_8': [2]} | ['place', 'rider', 'country', 'machine', 'speed', 'time', 'points'] | [['1', 'giacomo agostini', 'italy', 'mv agusta', '102.03 mph', '1:50.56.8', '15'], ['2', 'tony rutter', 'united kingdom', 'yamaha', '98.13 mph', '1:55.21.4', '12'], ['3', 'mick grant', 'united kingdom', 'yamaha', '97.57 mph', '1:56.01.0', '10'], ['4', 'jack findlay', 'australia', 'yamaha', '97.41 mph', '1:53.13.0', '8'], ['5', 'derek chatterton', 'united kingdom', 'yamaha', '95.65 mph', '1:58.21.4', '6'], ['6', 'selwyn griffiths', 'united kingdom', 'yamaha', '94.16 mph', '2:00.13.8', '5'], ['7', 'mick chatterton', 'united kingdom', 'yamaha', '92.98 mph', '2:01.45.2', '4'], ['8', 'lászló szabó', 'hungary', 'yamaha', '90.52 mph', '2:05.03.80', '3'], ['9', 'bill rae', 'united kingdom', 'yamaha', '90.51 mph', '2:05.04.80', '2'], ['10', 'blee', 'united kingdom', 'yamaha', '89.85 mph', '2:05.59.6', '1']] |
list of great central railway locomotives and rolling stock | https://en.wikipedia.org/wiki/List_of_Great_Central_Railway_locomotives_and_rolling_stock | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11913905-3.html.csv | superlative | the no 07005 great central railway locomotive is the newest one . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '10', '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', 'date'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; date }'}, 'number & name'], 'result': 'no 07005', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; date } ; number & name }'}, 'no 07005'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; date } ; number & name } ; no 07005 } = true', 'tointer': 'select the row whose date record of all rows is maximum . the number & name record of this row is no 07005 .'} | eq { hop { argmax { all_rows ; date } ; number & name } ; no 07005 } = true | select the row whose date record of all rows is maximum . the number & name record of this row is no 07005 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'date_5': 5, 'number & name_6': 6, 'no 07005_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'date_5': 'date', 'number & name_6': 'number & name', 'no 07005_7': 'no 07005'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'date_5': [0], 'number & name_6': [1], 'no 07005_7': [2]} | ['number & name', 'description', 'livery', 'owner ( s )', 'date'] | [['operational', 'operational', 'operational', 'operational', 'operational'], ['no d2158 margaret - ann', 'british rail class 03 0 - 6 - 0dm', 'br blue with the late crest', 'great central railway plc', '1960'], ['no d3101', 'british rail class 08 0 - 6 - 0de', 'br green with wasp stripes and the early crest', 'private owner', '1955'], ['no 13180', 'british rail class 08 0 - 6 - 0de', 'br green with the early crest', 'private owner', '1955'], ['no 08220', 'british rail class 08 0 - 6 - 0de', 'br rail blue', 'english electric preservation', '1956'], ['no 08694', 'british rail class 08 0 - 6 - 0de', 'ews red & gold', 'private owner', '1959'], ['no 10119 margaret ethel - thomas alfred naylor', 'british rail class 10 0 - 6 - 0de', 'br rail blue', 'private owner', '1961'], ['undergoing overhaul , restoration or repairs', 'undergoing overhaul , restoration or repairs', 'undergoing overhaul , restoration or repairs', 'undergoing overhaul , restoration or repairs', 'undergoing overhaul , restoration or repairs'], ['no d2118', 'british rail class 03 0 - 6 - 0dm', 'br rail blue', 'private owner', '1959'], ['no 07005', 'british rail class 07 0 - 6 - 0de', 'br rail blue', 'private owner', '1962']] |
2005 - 06 liverpool f.c. season | https://en.wikipedia.org/wiki/2005%E2%80%9306_Liverpool_F.C._season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-19764939-1.html.csv | ordinal | djibril cisse had the 2nd highest total in the 2005 - 06 liverpool f.c. season . | {'row': '2', 'col': '10', 'order': '2', 'col_other': '4', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'total', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; total ; 2 }'}, 'player'], 'result': 'djibril cisse', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; total ; 2 } ; player }'}, 'djibril cisse'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; total ; 2 } ; player } ; djibril cisse } = true', 'tointer': 'select the row whose total record of all rows is 2nd maximum . the player record of this row is djibril cisse .'} | eq { hop { nth_argmax { all_rows ; total ; 2 } ; player } ; djibril cisse } = true | select the row whose total record of all rows is 2nd maximum . the player record of this row is djibril cisse . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'total_5': 5, '2_6': 6, 'player_7': 7, 'djibril cisse_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'total_5': 'total', '2_6': '2', 'player_7': 'player', 'djibril cisse_8': 'djibril cisse'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'total_5': [0], '2_6': [0], 'player_7': [1], 'djibril cisse_8': [2]} | ['rank', 'no', 'pos', 'player', 'premier league', 'fa cup', 'league cup', 'champions league', 'club world cup', 'total'] | [['1', '8', 'mf', 'steven gerrard', '10', '4', '1', '7', '1', '23'], ['2', '9', 'fw', 'djibril cisse', '9', '2', '0', '6', '0', '19'], ['3', '15', 'fw', 'peter crouch', '8', '3', '0', '0', '2', '13'], ['4', '10', 'mf', 'luis garcã\xada', '7', '1', '0', '2', '0', '11'], ['5', '19', 'fw', 'fernando morientes', '5', '1', '0', '3', '0', '9'], ['6', '11', 'fw', 'robbie fowler', '5', '0', '0', '0', '0', '5'], ['6', '14', 'mf', 'xabi alonso', '3', '2', '0', '0', '0', '5'], ['8', '6', 'df', 'john arne riise', '1', '3', '0', '0', '0', '4'], ['9', '7', 'mf', 'harry kewell', '3', '0', '0', '0', '0', '3'], ['9', '24', 'fw', 'florent sinama - pongolle', '0', '2', '0', '1', '0', '3'], ['11', '4', 'df', 'sami hyypia', '1', '1', '0', '0', '0', '2'], ['11', '30', 'mf', 'boudewijn zenden', '2', '0', '0', '0', '0', '2'], ['13', '23', 'df', 'jamie carragher', '0', '0', '0', '1', '0', '1'], ['13', '28', 'df', 'stephen warnock', '1', '0', '0', '0', '0', '1']] |
2005 spanish grand prix | https://en.wikipedia.org/wiki/2005_Spanish_Grand_Prix | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1790368-3.html.csv | count | minardi - cosworth constructed 3 cars at the 2005 spanish grand prix . | {'scope': 'all', 'criterion': 'equal', 'value': 'minardi - cosworth', 'result': '2', 'col': '2', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'constructor', 'minardi - cosworth'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose constructor record fuzzily matches to minardi - cosworth .', 'tostr': 'filter_eq { all_rows ; constructor ; minardi - cosworth }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; constructor ; minardi - cosworth } }', 'tointer': 'select the rows whose constructor record fuzzily matches to minardi - cosworth . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; constructor ; minardi - cosworth } } ; 2 } = true', 'tointer': 'select the rows whose constructor record fuzzily matches to minardi - cosworth . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; constructor ; minardi - cosworth } } ; 2 } = true | select the rows whose constructor record fuzzily matches to minardi - cosworth . 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, 'constructor_5': 5, 'minardi - cosworth_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', 'constructor_5': 'constructor', 'minardi - cosworth_6': 'minardi - cosworth', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'constructor_5': [0], 'minardi - cosworth_6': [0], '2_7': [2]} | ['driver', 'constructor', 'laps', 'time / retired', 'grid'] | [['kimi räikkönen', 'mclaren - mercedes', '66', '1:27:16.830', '1'], ['fernando alonso', 'renault', '66', '+ 27.652', '3'], ['jarno trulli', 'toyota', '66', '+ 45.947', '5'], ['ralf schumacher', 'toyota', '66', '+ 46.719', '4'], ['giancarlo fisichella', 'renault', '66', '+ 57.936', '6'], ['mark webber', 'williams - bmw', '66', '+ 1:08.542', '2'], ['juan pablo montoya', 'mclaren - mercedes', '65', '+ 1 lap', '7'], ['david coulthard', 'red bull - cosworth', '65', '+ 1 lap', '9'], ['rubens barrichello', 'ferrari', '65', '+ 1 lap', '16'], ['nick heidfeld', 'williams - bmw', '65', '+ 1 lap', '17'], ['felipe massa', 'sauber - petronas', '63', 'wheel rim', '10'], ['tiago monteiro', 'jordan - toyota', '63', '+ 3 laps', '18'], ['narain karthikeyan', 'jordan - toyota', '63', '+ 3 laps', '13'], ['jacques villeneuve', 'sauber - petronas', '51', 'engine', '12'], ['michael schumacher', 'ferrari', '46', 'puncture', '8'], ['christijan albers', 'minardi - cosworth', '19', 'gearbox', '14'], ['patrick friesacher', 'minardi - cosworth', '11', 'spun off', '15'], ['vitantonio liuzzi', 'red bull - cosworth', '9', 'spun off', '11']] |
1953 - 54 segunda división | https://en.wikipedia.org/wiki/1953%E2%80%9354_Segunda_Divisi%C3%B3n | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17416195-2.html.csv | majority | all of the teams in the 1953 -54 segunda division played a total of 30 matches . | {'scope': 'all', 'col': '2', 'most_or_all': 'all', 'criterion': 'equal', 'value': '30', 'subset': None} | {'func': 'all_eq', 'args': ['all_rows', 'played', '30'], 'result': True, 'ind': 0, 'tointer': 'for the played records of all rows , all of them are equal to 30 .', 'tostr': 'all_eq { all_rows ; played ; 30 } = true'} | all_eq { all_rows ; played ; 30 } = true | for the played records of all rows , all of them are equal to 30 . | 1 | 1 | {'all_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'played_3': 3, '30_4': 4} | {'all_eq_0': 'all_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'played_3': 'played', '30_4': '30'} | {'all_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'played_3': [0], '30_4': [0]} | ['position', 'played', 'points', 'wins', 'draws', 'losses', 'goals for', 'goals against', 'goal difference'] | [['1', '30', '41', '17', '7', '6', '65', '42', '+ 23'], ['2', '30', '38', '17', '4', '9', '56', '36', '+ 20'], ['3', '30', '38', '16', '6', '8', '62', '44', '+ 18'], ['4', '30', '34', '15', '4', '11', '63', '46', '+ 17'], ['5', '30', '33', '12', '9', '9', '62', '48', '+ 14'], ['6', '30', '32', '14', '4', '12', '52', '53', '- 1'], ['7', '30', '29', '10', '9', '11', '56', '54', '+ 2'], ['8', '30', '29', '12', '5', '13', '44', '58', '- 14'], ['9', '30', '29', '11', '7', '12', '76', '59', '+ 17'], ['10', '30', '28', '12', '4', '14', '65', '55', '+ 10'], ['11', '30', '28', '9', '10', '11', '45', '61', '- 16'], ['12', '30', '28', '11', '6', '13', '38', '46', '- 8'], ['13', '30', '25', '10', '5', '15', '49', '63', '- 14'], ['14', '30', '25', '11', '3', '16', '35', '64', '- 29'], ['15', '30', '22', '8', '6', '16', '44', '56', '- 12'], ['16', '30', '21', '8', '5', '17', '42', '69', '- 27']] |
2008 women 's british open | https://en.wikipedia.org/wiki/2008_Women%27s_British_Open | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18594233-5.html.csv | unique | at the 2008 women 's british open , lorena ochoa was the only golfer that finished in the top 12 that was from mexico . | {'scope': 'all', 'row': '8', 'col': '3', 'col_other': '2', 'criterion': 'equal', 'value': 'mexico', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'mexico'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose country record fuzzily matches to mexico .', 'tostr': 'filter_eq { all_rows ; country ; mexico }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; country ; mexico } }', 'tointer': 'select the rows whose country record fuzzily matches to mexico . 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', 'mexico'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose country record fuzzily matches to mexico .', 'tostr': 'filter_eq { all_rows ; country ; mexico }'}, 'player'], 'result': 'lorena ochoa', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; country ; mexico } ; player }'}, 'lorena ochoa'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; country ; mexico } ; player } ; lorena ochoa }', 'tointer': 'the player record of this unqiue row is lorena ochoa .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; country ; mexico } } ; eq { hop { filter_eq { all_rows ; country ; mexico } ; player } ; lorena ochoa } } = true', 'tointer': 'select the rows whose country record fuzzily matches to mexico . there is only one such row in the table . the player record of this unqiue row is lorena ochoa .'} | and { only { filter_eq { all_rows ; country ; mexico } } ; eq { hop { filter_eq { all_rows ; country ; mexico } ; player } ; lorena ochoa } } = true | select the rows whose country record fuzzily matches to mexico . there is only one such row in the table . the player record of this unqiue row is lorena ochoa . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'country_7': 7, 'mexico_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'player_9': 9, 'lorena ochoa_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', 'mexico_8': 'mexico', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'player_9': 'player', 'lorena ochoa_10': 'lorena ochoa'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'country_7': [0], 'mexico_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'player_9': [2], 'lorena ochoa_10': [3]} | ['place', 'player', 'country', 'score', 'to par'] | [['t1', 'yuri fudoh', 'japan', '66 + 68 = 134', '10'], ['t1', 'jiyai shin', 'south korea', '66 + 68 = 134', '10'], ['3', 'juli inkster', 'united states', '65 + 70 = 135', '9'], ['t4', 'cristie kerr', 'united states', '71 + 65 = 136', '8'], ['t4', 'bo bae song', 'south korea', '68 + 68 = 136', '8'], ['t6', 'natalie gulbis', 'united states', '69 + 68 = 137', '7'], ['t6', 'ai miyazato', 'japan', '73 + 69 = 137', '7'], ['t6', 'lorena ochoa', 'mexico', '69 + 68 = 137', '7'], ['t9', 'laura diaz', 'united states', '66 + 72 = 138', '6'], ['t9', 'momoko ueda', 'japan', '66 + 72 = 138', '6'], ['t9', 'sophie gustafson', 'sweden', '69 + 69 = 138', '6'], ['t9', 'eun - hee ji', 'south korea', '68 + 70 = 138', '6']] |
claudio suárez | https://en.wikipedia.org/wiki/Claudio_Su%C3%A1rez | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1007636-2.html.csv | unique | the game on december 14th , 1994 was the only game where the score was 3-1 . | {'scope': 'all', 'row': '3', 'col': '3', 'col_other': '2', 'criterion': 'equal', 'value': '3 - 1', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'score', '3 - 1'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose score record fuzzily matches to 3 - 1 .', 'tostr': 'filter_eq { all_rows ; score ; 3 - 1 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; score ; 3 - 1 } }', 'tointer': 'select the rows whose score record fuzzily matches to 3 - 1 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'score', '3 - 1'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose score record fuzzily matches to 3 - 1 .', 'tostr': 'filter_eq { all_rows ; score ; 3 - 1 }'}, 'date'], 'result': 'december 14 , 1994', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; score ; 3 - 1 } ; date }'}, 'december 14 , 1994'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; score ; 3 - 1 } ; date } ; december 14 , 1994 }', 'tointer': 'the date record of this unqiue row is december 14 , 1994 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; score ; 3 - 1 } } ; eq { hop { filter_eq { all_rows ; score ; 3 - 1 } ; date } ; december 14 , 1994 } } = true', 'tointer': 'select the rows whose score record fuzzily matches to 3 - 1 . there is only one such row in the table . the date record of this unqiue row is december 14 , 1994 .'} | and { only { filter_eq { all_rows ; score ; 3 - 1 } } ; eq { hop { filter_eq { all_rows ; score ; 3 - 1 } ; date } ; december 14 , 1994 } } = true | select the rows whose score record fuzzily matches to 3 - 1 . there is only one such row in the table . the date record of this unqiue row is december 14 , 1994 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'score_7': 7, '3 - 1_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'date_9': 9, 'december 14 , 1994_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'score_7': 'score', '3 - 1_8': '3 - 1', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'date_9': 'date', 'december 14 , 1994_10': 'december 14 , 1994'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'score_7': [0], '3 - 1_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'date_9': [2], 'december 14 , 1994_10': [3]} | ['goal', 'date', 'score', 'result', 'competition'] | [['1', 'november 8 , 1992', '2 - 0', '4 - 0', '1994 fifa world cup qualification'], ['2', 'november 22 , 1992', '2 - 0', '4 - 0', '1994 fifa world cup qualification'], ['3', 'december 14 , 1994', '3 - 1', '5 - 1', 'friendly'], ['4', 'october 11 , 1995', '1 - 1', '2 - 1', 'friendly'], ['5', 'january 31 , 2001', '1 - 0', '2 - 3', 'friendly'], ['6', 'may 1 , 2001', '1 - 0', '3 - 3', 'friendly']] |
2007 - 08 atlanta hawks season | https://en.wikipedia.org/wiki/2007%E2%80%9308_Atlanta_Hawks_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-11961582-4.html.csv | superlative | in the 2007 - 08 atlanta hawks season , when a horford had the high rebounds , the highest attendance was on december 8th . | {'scope': 'subset', 'col_superlative': '8', 'row_superlative': '4', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '2,6', 'subset': {'col': '6', 'criterion': 'fuzzily_match', 'value': 'a horford'}} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'high rebounds', 'a horford'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; high rebounds ; a horford }', 'tointer': 'select the rows whose high rebounds record fuzzily matches to a horford .'}, 'location attendance'], 'result': None, 'ind': 1, 'tostr': 'argmax { filter_eq { all_rows ; high rebounds ; a horford } ; location attendance }'}, 'date'], 'result': 'december 8', 'ind': 2, 'tostr': 'hop { argmax { filter_eq { all_rows ; high rebounds ; a horford } ; location attendance } ; date }'}, 'december 8'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { argmax { filter_eq { all_rows ; high rebounds ; a horford } ; location attendance } ; date } ; december 8 } = true', 'tointer': 'select the rows whose high rebounds record fuzzily matches to a horford . select the row whose location attendance record of these rows is maximum . the date record of this row is december 8 .'} | eq { hop { argmax { filter_eq { all_rows ; high rebounds ; a horford } ; location attendance } ; date } ; december 8 } = true | select the rows whose high rebounds record fuzzily matches to a horford . select the row whose location attendance record of these rows is maximum . the date record of this row is december 8 . | 4 | 4 | {'str_eq_3': 3, 'result_4': 4, 'str_hop_2': 2, 'argmax_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'high rebounds_6': 6, 'a horford_7': 7, 'location attendance_8': 8, 'date_9': 9, 'december 8_10': 10} | {'str_eq_3': 'str_eq', 'result_4': 'true', 'str_hop_2': 'str_hop', 'argmax_1': 'argmax', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'high rebounds_6': 'high rebounds', 'a horford_7': 'a horford', 'location attendance_8': 'location attendance', 'date_9': 'date', 'december 8_10': 'december 8'} | {'str_eq_3': [4], 'result_4': [], 'str_hop_2': [3], 'argmax_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'high rebounds_6': [0], 'a horford_7': [0], 'location attendance_8': [1], 'date_9': [2], 'december 8_10': [3]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record'] | [['16', 'december 3', 'philadelphia', 'w 88 - 79', 'j smtih ( 22 )', 'a horford ( 13 )', 'j johnson ( 7 )', 'wachovia center 11465', '7 - 9'], ['17', 'december 4', 'detroit', 'l 95 - 106', 'j childress ( 18 )', 'a horford ( 10 )', 'a johnson , s stoudamire ( 3 )', 'philips arena 12754', '7 - 10'], ['18', 'december 6', 'minnesota', 'w 90 - 89', 'j smith ( 28 )', 'a horford ( 15 )', 'a johnson ( 6 )', 'philips arena 12232', '8 - 10'], ['19', 'december 8', 'memphis', 'w 86 - 78', 'j smith ( 25 )', 'a horford ( 14 )', 'a johnson ( 8 )', 'philips arena 15658', '9 - 10'], ['20', 'december 10', 'orlando', 'w 98 - 87', 'j smith ( 25 )', 'j smith ( 15 )', 'j smith , a johnson ( 5 )', 'amway arena 16821', '10 - 10'], ['21', 'december 11', 'toronto', 'l 88 - 100', 'j johnson , m williams ( 23 )', 'a horford ( 10 )', 'a law ( 6 )', 'philips arena 13173', '10 - 11'], ['22', 'december 14', 'detroit', 'l 81 - 91', 'j johnson ( 23 )', 'l wright ( 12 )', 'a johnson , j smith ( 3 )', 'the palace of auburn hills 22076', '10 - 12'], ['23', 'december 15', 'charlotte', 'w 93 - 84', 'j johnson ( 31 )', 'j smith ( 10 )', 'a johnson ( 7 )', 'philips arena 14040', '11 - 12'], ['24', 'december 17', 'utah', 'w 116 - 111', 'j johnson ( 26 )', 'j smith ( 12 )', 'a johnson ( 14 )', 'philips arena 15263', '12 - 12'], ['25', 'december 19', 'miami', 'w 114 - 111 ( ot )', 'mwilliams ( 26 )', 'mwilliams ( 9 )', 'ajohnson , jjohnson ( 9 )', 'philips arena 17069', '13 - 12'], ['26', 'december 21', 'washington', 'w 97 - 92', 'j johnson ( 32 )', 'j smith ( 14 )', 'j johnson , a johnson ( 8 )', 'verizon center 16472', '14 - 12'], ['27', 'december 26', 'indiana', 'w 107 - 95', 'j johnson ( 26 )', 's williams ( 10 )', 'j johnson ( 11 )', 'philips arena 16070', '15 - 12']] |
solomon islands national football team results | https://en.wikipedia.org/wiki/Solomon_Islands_national_football_team_results | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12276713-1.html.csv | count | the solomon islands national football team played a total of three friendly competitions . | {'scope': 'all', 'criterion': 'equal', 'value': 'friendly', 'result': '3', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'competition', 'friendly'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose competition record fuzzily matches to friendly .', 'tostr': 'filter_eq { all_rows ; competition ; friendly }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; competition ; friendly } }', 'tointer': 'select the rows whose competition record fuzzily matches to friendly . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; competition ; friendly } } ; 3 } = true', 'tointer': 'select the rows whose competition record fuzzily matches to friendly . the number of such rows is 3 .'} | eq { count { filter_eq { all_rows ; competition ; friendly } } ; 3 } = true | select the rows whose competition record fuzzily matches to friendly . the number of such rows is 3 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'competition_5': 5, 'friendly_6': 6, '3_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'competition_5': 'competition', 'friendly_6': 'friendly', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'competition_5': [0], 'friendly_6': [0], '3_7': [2]} | ['date', 'venue', 'score', 'competition', 'att'] | [['17 november 1995', 'solomon islands ( h )', '0 - 1', '1996 ofc nations cup', '-'], ['11 may 1996', 'tahiti ( a )', '1 - 2', '1996 ofc nations cup', '-'], ['16 september 1996', 'papua new guinea ( a )', '1 - 1', '1998 fifa world cup qualification', '-'], ['18 september 1996', 'papua new guinea ( n )', '1 - 1', '1998 fifa world cup qualification', '-'], ['15 february 1997', 'tonga ( a )', '4 - 0', '1998 fifa world cup qualification', '-'], ['17 february 1997', 'fiji ( a )', '2 - 1', 'friendly', '-'], ['21 february 1997', 'fiji ( a )', '2 - 3', 'friendly', '-'], ['1 march 1997', 'solomon islands ( h )', '9 - 0', '1998 fifa world cup qualification', '-'], ['11 june 1997', 'australia ( n )', '0 - 13', '1998 fifa world cup qualification', '-'], ['15 june 1997', 'australia ( n )', '4 - 1', '1998 fifa world cup qualification', '-'], ['17 june 1997', 'australia ( a )', '2 - 6', '1998 fifa world cup qualification', '-'], ['21 june 1997', 'australia ( n )', '1 - 1', '1998 fifa world cup qualification', '-'], ['5 september 1998', 'vanuatu ( n )', '3 - 1', 'melanesia cup 1998', '-'], ['8 september 1998', 'vanuatu ( n )', '3 - 2', 'melanesia cup 1998', '-'], ['10 september 1998', 'vanuatu ( a )', '1 - 3', 'melanesia cup 1998', '-'], ['12 september 1998', 'vanuatu ( n )', '1 - 1', 'melanesia cup 1998', '-'], ['19 september 1998', 'solomon islands ( h )', '2 - 1', 'friendly', '-']] |
1992 open championship | https://en.wikipedia.org/wiki/1992_Open_Championship | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18122130-2.html.csv | unique | sandy lyle was the only player in the 1992 open championship golf tournament from scotland . | {'scope': 'all', 'row': '2', 'col': '2', 'col_other': '1', 'criterion': 'equal', 'value': 'scotland', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'scotland'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose country record fuzzily matches to scotland .', 'tostr': 'filter_eq { all_rows ; country ; scotland }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; country ; scotland } }', 'tointer': 'select the rows whose country record fuzzily matches to scotland . 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', 'scotland'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose country record fuzzily matches to scotland .', 'tostr': 'filter_eq { all_rows ; country ; scotland }'}, 'player'], 'result': 'sandy lyle', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; country ; scotland } ; player }'}, 'sandy lyle'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; country ; scotland } ; player } ; sandy lyle }', 'tointer': 'the player record of this unqiue row is sandy lyle .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; country ; scotland } } ; eq { hop { filter_eq { all_rows ; country ; scotland } ; player } ; sandy lyle } } = true', 'tointer': 'select the rows whose country record fuzzily matches to scotland . there is only one such row in the table . the player record of this unqiue row is sandy lyle .'} | and { only { filter_eq { all_rows ; country ; scotland } } ; eq { hop { filter_eq { all_rows ; country ; scotland } ; player } ; sandy lyle } } = true | select the rows whose country record fuzzily matches to scotland . there is only one such row in the table . the player record of this unqiue row is sandy lyle . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'country_7': 7, 'scotland_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'player_9': 9, 'sandy lyle_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', 'scotland_8': 'scotland', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'player_9': 'player', 'sandy lyle_10': 'sandy lyle'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'country_7': [0], 'scotland_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'player_9': [2], 'sandy lyle_10': [3]} | ['player', 'country', 'year ( s ) won', 'total', 'to par', 'finish'] | [['nick faldo', 'england', '1987 , 1990', '272', '- 12', '1'], ['sandy lyle', 'scotland', '1985', '280', '- 4', 't12'], ['greg norman', 'australia', '1986', '281', '- 3', '18'], ['ian baker - finch', 'australia', '1991', '282', '- 2', 't19'], ['mark calcavecchia', 'united states', '1989', '285', '+ 1', 't28'], ['lee trevino', 'united states', '1971 , 1972', '287', '+ 3', 't39']] |
three rivers conference ( indiana ) | https://en.wikipedia.org/wiki/Three_Rivers_Conference_%28Indiana%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15176211-1.html.csv | ordinal | whitko has the second highest enrollment amongst all schools in the three rivers conference . | {'row': '8', 'col': '4', 'order': '2', 'col_other': '1', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'enrollment', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; enrollment ; 2 }'}, 'school'], 'result': 'whitko', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; enrollment ; 2 } ; school }'}, 'whitko'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; enrollment ; 2 } ; school } ; whitko } = true', 'tointer': 'select the row whose enrollment record of all rows is 2nd maximum . the school record of this row is whitko .'} | eq { hop { nth_argmax { all_rows ; enrollment ; 2 } ; school } ; whitko } = true | select the row whose enrollment record of all rows is 2nd maximum . the school record of this row is whitko . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'enrollment_5': 5, '2_6': 6, 'school_7': 7, 'whitko_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', 'enrollment_5': 'enrollment', '2_6': '2', 'school_7': 'school', 'whitko_8': 'whitko'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'enrollment_5': [0], '2_6': [0], 'school_7': [1], 'whitko_8': [2]} | ['school', 'location', 'mascot', 'enrollment', 'ihsaa class', 'county', 'year joined', 'previous conference'] | [['manchester', 'north manchester', 'squires', '434', 'aa', '85 wabash', '1976', 'northern lakes'], ['northfield', 'wabash', 'norsemen', '380', 'aa', '85 wabash', '1971', 'none ( new school )'], ['north miami', 'denver', 'warriors', '348', 'a', '52 miami', '1971', 'mid - indiana'], ['rochester community', 'rochester', 'zebras', '615', 'aaa', '25 fulton', '1987', 'northern lakes'], ['southwood', 'wabash', 'knights', '427', 'aa', '85 wabash', '1976', 'mid - indiana'], ['tippecanoe valley', 'akron', 'vikings', '600', 'aaa', '43 kosciusko', '1976', 'independents'], ['wabash', 'wabash', 'apaches', '455', 'aa', '85 wabash', '2006', 'central indiana'], ['whitko', 'south whitley', 'wildcats', '613', 'aa', '92 whitley', '1976', 'independents']] |
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 | aggregation | the average purse for the women 's british open is 2046154 . | {'scope': 'all', 'col': '10', 'type': 'average', 'result': '2046154', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'purse'], 'result': '2046154', 'ind': 0, 'tostr': 'avg { all_rows ; purse }'}, '2046154'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; purse } ; 2046154 } = true', 'tointer': 'the average of the purse record of all rows is 2046154 .'} | round_eq { avg { all_rows ; purse } ; 2046154 } = true | the average of the purse record of all rows is 2046154 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'purse_4': 4, '2046154_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'purse_4': 'purse', '2046154_5': '2046154'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'purse_4': [0], '2046154_5': [1]} | ['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']] |
list of sports teams in nebraska | https://en.wikipedia.org/wiki/List_of_sports_teams_in_Nebraska | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14115168-4.html.csv | unique | of the college sports teams in nebraska that are part of the national association of intercollegiate athletics , the college of saint mary is the only one that does not have a national title . | {'scope': 'all', 'row': '2', 'col': '4', 'col_other': '1', 'criterion': 'equal', 'value': '0', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'national titles', '0'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose national titles record is equal to 0 .', 'tostr': 'filter_eq { all_rows ; national titles ; 0 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; national titles ; 0 } }', 'tointer': 'select the rows whose national titles record is equal to 0 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'national titles', '0'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose national titles record is equal to 0 .', 'tostr': 'filter_eq { all_rows ; national titles ; 0 }'}, 'school'], 'result': 'college of saint mary', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; national titles ; 0 } ; school }'}, 'college of saint mary'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; national titles ; 0 } ; school } ; college of saint mary }', 'tointer': 'the school record of this unqiue row is college of saint mary .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; national titles ; 0 } } ; eq { hop { filter_eq { all_rows ; national titles ; 0 } ; school } ; college of saint mary } } = true', 'tointer': 'select the rows whose national titles record is equal to 0 . there is only one such row in the table . the school record of this unqiue row is college of saint mary .'} | and { only { filter_eq { all_rows ; national titles ; 0 } } ; eq { hop { filter_eq { all_rows ; national titles ; 0 } ; school } ; college of saint mary } } = true | select the rows whose national titles record is equal to 0 . there is only one such row in the table . the school record of this unqiue row is college of saint mary . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'national titles_7': 7, '0_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'school_9': 9, 'college of saint mary_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'national titles_7': 'national titles', '0_8': '0', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'school_9': 'school', 'college of saint mary_10': 'college of saint mary'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'national titles_7': [0], '0_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'school_9': [2], 'college of saint mary_10': [3]} | ['school', 'mascot', 'conference', 'national titles', 'founded'] | [['bellevue university', 'bellevue bruins', 'midlands', '14', '1966'], ['college of saint mary', 'saint mary flames', 'midlands', '0', '1923'], ['concordia university', 'concordia bulldogs', 'great plains', '1', '1894'], ['doane college', 'doane tigers', 'great plains', '10', '1872'], ['hastings college', 'hastings broncos', 'great plains', '3', '1882'], ['midland university', 'midland warriors', 'great plains', '2', '1883'], ['nebraska wesleyan university', 'nw prairie wolves', 'great plains', '19', '1887'], ['peru state college', 'peru state bobcats', 'midlands', '2', '1865'], ['york college', 'york panthers', 'midlands', '28', '1890']] |
water polo at the pan american games | https://en.wikipedia.org/wiki/Water_polo_at_the_Pan_American_Games | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12420066-2.html.csv | count | in water polo at the pan american games , for those that won more than 1 total medal , two of them won 0 bronze medals . | {'scope': 'subset', 'criterion': 'equal', 'value': '0', 'result': '2', 'col': '4', 'subset': {'col': '5', 'criterion': 'greater_than', 'value': '1'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'total', '1'], 'result': None, 'ind': 0, 'tostr': 'filter_greater { all_rows ; total ; 1 }', 'tointer': 'select the rows whose total record is greater than 1 .'}, 'bronze', '0'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose total record is greater than 1 . among these rows , select the rows whose bronze record is equal to 0 .', 'tostr': 'filter_eq { filter_greater { all_rows ; total ; 1 } ; bronze ; 0 }'}], 'result': '2', 'ind': 2, 'tostr': 'count { filter_eq { filter_greater { all_rows ; total ; 1 } ; bronze ; 0 } }', 'tointer': 'select the rows whose total record is greater than 1 . among these rows , select the rows whose bronze record is equal to 0 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_eq { filter_greater { all_rows ; total ; 1 } ; bronze ; 0 } } ; 2 } = true', 'tointer': 'select the rows whose total record is greater than 1 . among these rows , select the rows whose bronze record is equal to 0 . the number of such rows is 2 .'} | eq { count { filter_eq { filter_greater { all_rows ; total ; 1 } ; bronze ; 0 } } ; 2 } = true | select the rows whose total record is greater than 1 . among these rows , select the rows whose bronze record is equal to 0 . the number of such rows is 2 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_eq_1': 1, 'filter_greater_0': 0, 'all_rows_5': 5, 'total_6': 6, '1_7': 7, 'bronze_8': 8, '0_9': 9, '2_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_eq_1': 'filter_eq', 'filter_greater_0': 'filter_greater', 'all_rows_5': 'all_rows', 'total_6': 'total', '1_7': '1', 'bronze_8': 'bronze', '0_9': '0', '2_10': '2'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_eq_1': [2], 'filter_greater_0': [1], 'all_rows_5': [0], 'total_6': [0], '1_7': [0], 'bronze_8': [1], '0_9': [1], '2_10': [3]} | ['rank', 'gold', 'silver', 'bronze', 'total'] | [['1', '3', '1', '0', '4'], ['2', '1', '3', '0', '4'], ['3', '0', '0', '3', '3'], ['4', '0', '0', '1', '1'], ['total', '4', '4', '4', '12']] |
2008 - 09 detroit red wings season | https://en.wikipedia.org/wiki/2008%E2%80%9309_Detroit_Red_Wings_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17371135-30.html.csv | unique | in the 2008-09 detroit red wings season , when the player 's position is center , the only player from canada is julien cayer . | {'scope': 'subset', 'row': '4', 'col': '5', 'col_other': '3', 'criterion': 'equal', 'value': 'canada', 'subset': {'col': '4', 'criterion': 'equal', 'value': 'center'}} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'position', 'center'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; position ; center }', 'tointer': 'select the rows whose position record fuzzily matches to center .'}, 'nationality', 'canada'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose position record fuzzily matches to center . among these rows , select the rows whose nationality record fuzzily matches to canada .', 'tostr': 'filter_eq { filter_eq { all_rows ; position ; center } ; nationality ; canada }'}], 'result': True, 'ind': 2, 'tostr': 'only { filter_eq { filter_eq { all_rows ; position ; center } ; nationality ; canada } }', 'tointer': 'select the rows whose position record fuzzily matches to center . among these rows , select the rows whose nationality record fuzzily matches to canada . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'position', 'center'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; position ; center }', 'tointer': 'select the rows whose position record fuzzily matches to center .'}, 'nationality', 'canada'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose position record fuzzily matches to center . among these rows , select the rows whose nationality record fuzzily matches to canada .', 'tostr': 'filter_eq { filter_eq { all_rows ; position ; center } ; nationality ; canada }'}, 'player'], 'result': 'julien cayer', 'ind': 3, 'tostr': 'hop { filter_eq { filter_eq { all_rows ; position ; center } ; nationality ; canada } ; player }'}, 'julien cayer'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { filter_eq { filter_eq { all_rows ; position ; center } ; nationality ; canada } ; player } ; julien cayer }', 'tointer': 'the player record of this unqiue row is julien cayer .'}], 'result': True, 'ind': 5, 'tostr': 'and { only { filter_eq { filter_eq { all_rows ; position ; center } ; nationality ; canada } } ; eq { hop { filter_eq { filter_eq { all_rows ; position ; center } ; nationality ; canada } ; player } ; julien cayer } } = true', 'tointer': 'select the rows whose position record fuzzily matches to center . among these rows , select the rows whose nationality record fuzzily matches to canada . there is only one such row in the table . the player record of this unqiue row is julien cayer .'} | and { only { filter_eq { filter_eq { all_rows ; position ; center } ; nationality ; canada } } ; eq { hop { filter_eq { filter_eq { all_rows ; position ; center } ; nationality ; canada } ; player } ; julien cayer } } = true | select the rows whose position record fuzzily matches to center . among these rows , select the rows whose nationality record fuzzily matches to canada . there is only one such row in the table . the player record of this unqiue row is julien cayer . | 8 | 6 | {'and_5': 5, 'result_6': 6, 'only_2': 2, 'filter_str_eq_1': 1, 'filter_str_eq_0': 0, 'all_rows_7': 7, 'position_8': 8, 'center_9': 9, 'nationality_10': 10, 'canada_11': 11, 'str_eq_4': 4, 'str_hop_3': 3, 'player_12': 12, 'julien cayer_13': 13} | {'and_5': 'and', 'result_6': 'true', 'only_2': 'only', 'filter_str_eq_1': 'filter_str_eq', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_7': 'all_rows', 'position_8': 'position', 'center_9': 'center', 'nationality_10': 'nationality', 'canada_11': 'canada', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'player_12': 'player', 'julien cayer_13': 'julien cayer'} | {'and_5': [6], 'result_6': [], 'only_2': [5], 'filter_str_eq_1': [2, 3], 'filter_str_eq_0': [1], 'all_rows_7': [0], 'position_8': [0], 'center_9': [0], 'nationality_10': [1], 'canada_11': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'player_12': [3], 'julien cayer_13': [4]} | ['round', 'overall pick', 'player', 'position', 'nationality', 'college / junior / club team ( league )'] | [['1', '30', 'thomas mccollum', 'goaltender', 'united states', 'guelph storm ( ohl )'], ['3', '91', 'max nicastro', 'defenseman', 'united states', 'chicago steel ( ushl )'], ['4', '121', 'gustav nyquist', 'center', 'sweden', 'malmö redhawks ( sweden jr )'], ['5', '151', 'julien cayer', 'center', 'canada', 'northwood school ( hs - new york )'], ['6', '181', 'stephen johnston', 'left wing', 'canada', 'belleville bulls ( ohl )'], ['7', '211', 'jesper samuelsson', 'center', 'sweden', 'hc vita hästen ( swe - 3 )']] |
the superinvestors of graham - and - doddsville | https://en.wikipedia.org/wiki/The_Superinvestors_of_Graham-and-Doddsville | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11886885-1.html.csv | count | among the the funds - superinvestors of graham - and - doddsvill managed not by warren buffett , 3 of them are ltd . | {'scope': 'subset', 'criterion': 'equal', 'value': 'ltd', 'result': '3', 'col': '1', 'subset': {'col': '2', 'criterion': 'not_equal', 'value': 'warren buffett'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_not_eq', 'args': ['all_rows', 'manager', 'warren buffett'], 'result': None, 'ind': 0, 'tostr': 'filter_not_eq { all_rows ; manager ; warren buffett }', 'tointer': 'select the rows whose manager record does not match to warren buffett .'}, 'fund', 'ltd'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose manager record does not match to warren buffett . among these rows , select the rows whose fund record fuzzily matches to ltd .', 'tostr': 'filter_eq { filter_not_eq { all_rows ; manager ; warren buffett } ; fund ; ltd }'}], 'result': '3', 'ind': 2, 'tostr': 'count { filter_eq { filter_not_eq { all_rows ; manager ; warren buffett } ; fund ; ltd } }', 'tointer': 'select the rows whose manager record does not match to warren buffett . among these rows , select the rows whose fund record fuzzily matches to ltd . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_eq { filter_not_eq { all_rows ; manager ; warren buffett } ; fund ; ltd } } ; 3 } = true', 'tointer': 'select the rows whose manager record does not match to warren buffett . among these rows , select the rows whose fund record fuzzily matches to ltd . the number of such rows is 3 .'} | eq { count { filter_eq { filter_not_eq { all_rows ; manager ; warren buffett } ; fund ; ltd } } ; 3 } = true | select the rows whose manager record does not match to warren buffett . among these rows , select the rows whose fund record fuzzily matches to ltd . 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_not_eq_0': 0, 'all_rows_5': 5, 'manager_6': 6, 'warren buffett_7': 7, 'fund_8': 8, 'ltd_9': 9, '3_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_str_eq_1': 'filter_str_eq', 'filter_str_not_eq_0': 'filter_str_not_eq', 'all_rows_5': 'all_rows', 'manager_6': 'manager', 'warren buffett_7': 'warren buffett', 'fund_8': 'fund', 'ltd_9': 'ltd', '3_10': '3'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_str_eq_1': [2], 'filter_str_not_eq_0': [1], 'all_rows_5': [0], 'manager_6': [0], 'warren buffett_7': [0], 'fund_8': [1], 'ltd_9': [1], '3_10': [3]} | ['fund', 'manager', 'fund period', 'fund return', 'market return'] | [['wjs limited partners', 'walter j schloss', '1956 - 1984', '21.3 % / 16.1 %', '8.4 % ( s & p )'], ['tbk limited partners', 'tom knapp', '1968 - 1983', '20.0 % / 16.0 %', '7.0 % ( djia )'], ['buffett partnership , ltd', 'warren buffett', '1957 - 1969', '29.5 % / 23.8 %', '7.4 % ( djia )'], ['sequoia fund , inc', 'william j ruane', '1970 - 1984', '18.2 %', '10.0 %'], ['charles munger , ltd', 'charles munger', '1962 - 1975', '19.8 % / 13.7 %', '5.0 % ( djia )'], ['pacific partners , ltd', 'rick guerin', '1965 - 1983', '32.9 % / 23.6 %', '7.8 % ( s & p )'], ['perlmeter investments , ltd', 'stan perlmeter', '1965 - 1983', '23.0 % / 19.0 %', '7.0 % ( djia )'], ['washington post master trust', '3 different managers', '1978 - 1983', '21.8 %', '7.0 % ( djia )'], ['fmc corporation pension fund', '8 different managers', '1975 - 1983', '17.1 %', '12.6 % ( becker avg )']] |
royal canadian mint ice hockey coins | https://en.wikipedia.org/wiki/Royal_Canadian_Mint_ice_hockey_coins | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12991375-7.html.csv | majority | the issue price of all royal canadian mint ice hockey coins is 24.95 . | {'scope': 'all', 'col': '5', 'most_or_all': 'all', 'criterion': 'equal', 'value': '24.95', 'subset': None} | {'func': 'all_eq', 'args': ['all_rows', 'issue price', '24.95'], 'result': True, 'ind': 0, 'tointer': 'for the issue price records of all rows , all of them are equal to 24.95 .', 'tostr': 'all_eq { all_rows ; issue price ; 24.95 } = true'} | all_eq { all_rows ; issue price ; 24.95 } = true | for the issue price records of all rows , all of them are equal to 24.95 . | 1 | 1 | {'all_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'issue price_3': 3, '24.95_4': 4} | {'all_eq_0': 'all_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'issue price_3': 'issue price', '24.95_4': '24.95'} | {'all_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'issue price_3': [0], '24.95_4': [0]} | ['year', 'theme', 'artist', 'mintage', 'issue price', 'special notes'] | [['2006', 'montreal canadiens', 'n / a', 'n / a', '24.95', 'from montreal canadiens gift set'], ['2006', 'ottawa senators', 'n / a', 'n / a', '24.95', 'from ottawa senators gift set'], ['2006', 'toronto maple leafs', 'n / a', 'n / a', '24.95', 'from toronto maple leafs gift set'], ['2007', 'calgary flames', 'n / a', '832', '24.95', 'from calgary flames gift set'], ['2007', 'edmonton oilers', 'n / a', '2213', '24.95', 'from edmonton oilers gift set'], ['2007', 'montreal canadiens', 'n / a', '2952', '24.95', 'from montreal canadiens gift set'], ['2007', 'ottawa senators', 'n / a', '1634', '24.95', 'from ottawa senators gift set'], ['2007', 'toronto maple leafs', 'n / a', '3527', '24.95', 'from toronto maple leafs gift set'], ['2007', 'vancouver canucks', 'n / a', '1264', '24.95', 'from vancouver canucks gift set']] |
swimming at the 2000 summer olympics - women 's 200 metre individual medley | https://en.wikipedia.org/wiki/Swimming_at_the_2000_Summer_Olympics_%E2%80%93_Women%27s_200_metre_individual_medley | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12446647-5.html.csv | unique | germany was the only country with a swimmer in the 2:18 time range . | {'scope': 'all', 'row': '8', 'col': '5', 'col_other': '4', 'criterion': 'equal', 'value': '2:18', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'time', '2:18'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose time record fuzzily matches to 2:18 .', 'tostr': 'filter_eq { all_rows ; time ; 2:18 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; time ; 2:18 } }', 'tointer': 'select the rows whose time record fuzzily matches to 2:18 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'time', '2:18'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose time record fuzzily matches to 2:18 .', 'tostr': 'filter_eq { all_rows ; time ; 2:18 }'}, 'nationality'], 'result': 'germany', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; time ; 2:18 } ; nationality }'}, 'germany'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; time ; 2:18 } ; nationality } ; germany }', 'tointer': 'the nationality record of this unqiue row is germany .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; time ; 2:18 } } ; eq { hop { filter_eq { all_rows ; time ; 2:18 } ; nationality } ; germany } } = true', 'tointer': 'select the rows whose time record fuzzily matches to 2:18 . there is only one such row in the table . the nationality record of this unqiue row is germany .'} | and { only { filter_eq { all_rows ; time ; 2:18 } } ; eq { hop { filter_eq { all_rows ; time ; 2:18 } ; nationality } ; germany } } = true | select the rows whose time record fuzzily matches to 2:18 . there is only one such row in the table . the nationality record of this unqiue row is germany . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'time_7': 7, '2:18_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'nationality_9': 9, 'germany_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'time_7': 'time', '2:18_8': '2:18', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'nationality_9': 'nationality', 'germany_10': 'germany'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'time_7': [0], '2:18_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'nationality_9': [2], 'germany_10': [3]} | ['rank', 'lane', 'name', 'nationality', 'time'] | [['1', '5', 'yana klochkova', 'ukraine', '2:13.08'], ['2', '3', 'cristina teuscher', 'united states', '2:13.47'], ['3', '4', 'oxana verevka', 'russia', '2:14.04'], ['4', '6', 'tomoko hagiwara', 'japan', '2:15.09'], ['5', '2', 'chen yan', 'china', '2:15.27'], ['6', '7', 'sue rolph', 'great britain', '2:15.98'], ['7', '1', 'zhan shu', 'china', '2:16.58'], ['8', '8', 'nicole hetzer', 'germany', '2:18.08']] |
1987 masters tournament | https://en.wikipedia.org/wiki/1987_Masters_Tournament | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16490473-1.html.csv | majority | most players who participated in the 1987 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', 'finish'] | [['seve ballesteros', 'spain', '1980 , 1983', '285', '3', 't2'], ['ben crenshaw', 'united states', '1984', '286', '2', 't4'], ['bernhard langer', 'west germany', '1985', '289', '+ 1', 't7'], ['jack nicklaus', 'united states', '1963 , 1965 , 1966 , 1972 , 1975 , 1986', '289', '+ 1', 't7'], ['tom watson', 'united states', '1977 , 1981', '289', '+ 1', 't7'], ['craig stadler', 'united states', '1982', '291', '+ 3', 't17'], ['fuzzy zoeller', 'united states', '1979', '295', '+ 7', 't27'], ['gary player', 'south africa', '1961 , 1974 , 1978', '297', '+ 9', 't35'], ['tommy aaron', 'united states', '1973', '305', '+ 17', 't50'], ['billy casper', 'united states', '1970', '305', '+ 17', 't50']] |
1985 - 86 argentine primera división | https://en.wikipedia.org/wiki/1985%E2%80%9386_Argentine_Primera_Divisi%C3%B3n | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17968244-2.html.csv | count | in the 1985 - 86 argentine primera división , among the teams that had their 3rd season , 4 of them had an average score above 40.00 . | {'scope': 'subset', 'criterion': 'greater_than', 'value': '40', 'result': '4', 'col': '7', 'subset': {'col': '6', 'criterion': 'equal', 'value': '3'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'seasons', '3'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; seasons ; 3 }', 'tointer': 'select the rows whose seasons record is equal to 3 .'}, 'points average', '40'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose seasons record is equal to 3 . among these rows , select the rows whose points average record is greater than 40 .', 'tostr': 'filter_greater { filter_eq { all_rows ; seasons ; 3 } ; points average ; 40 }'}], 'result': '4', 'ind': 2, 'tostr': 'count { filter_greater { filter_eq { all_rows ; seasons ; 3 } ; points average ; 40 } }', 'tointer': 'select the rows whose seasons record is equal to 3 . among these rows , select the rows whose points average record is greater than 40 . the number of such rows is 4 .'}, '4'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_greater { filter_eq { all_rows ; seasons ; 3 } ; points average ; 40 } } ; 4 } = true', 'tointer': 'select the rows whose seasons record is equal to 3 . among these rows , select the rows whose points average record is greater than 40 . the number of such rows is 4 .'} | eq { count { filter_greater { filter_eq { all_rows ; seasons ; 3 } ; points average ; 40 } } ; 4 } = true | select the rows whose seasons record is equal to 3 . among these rows , select the rows whose points average record is greater than 40 . the number of such rows is 4 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_greater_1': 1, 'filter_eq_0': 0, 'all_rows_5': 5, 'seasons_6': 6, '3_7': 7, 'points average_8': 8, '40_9': 9, '4_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_greater_1': 'filter_greater', 'filter_eq_0': 'filter_eq', 'all_rows_5': 'all_rows', 'seasons_6': 'seasons', '3_7': '3', 'points average_8': 'points average', '40_9': '40', '4_10': '4'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_greater_1': [2], 'filter_eq_0': [1], 'all_rows_5': [0], 'seasons_6': [0], '3_7': [0], 'points average_8': [1], '40_9': [1], '4_10': [3]} | ['team', '1983', '1984', '1985 - 1986', 'total points', 'seasons', 'points average'] | [['deportivo español', 'n / a', 'n / a', '46', '46', '1', '46.00'], ['ferro carril oeste', '46', '50', '40', '136', '3', '45.33'], ['argentinos juniors', '36', '51', '44', '131', '3', '43.66'], ['river plate', '29', '43', '56', '128', '3', '42.33'], ['san lorenzo', '47', '37', '40', '124', '3', '41.33'], ['vélez sársfield', '44', '42', '34', '120', '3', '40.00'], ["newell 's old boys", '35', '38', '46', '119', '3', '39.67'], ['independiente', '48', '31', '36', '115', '3', '38.33'], ['estudiantes de la plata', '38', '48', '27', '113', '3', '37.67'], ['boca juniors', '37', '30', '41', '108', '3', '36.00'], ['gimnasia de la plata', 'n / a', 'n / a', '36', '36', '1', '36.00'], ['talleres de córdoba', '33', '34', '37', '104', '3', '34.67'], ['instituto de córdoba', '35', '33', '35', '103', '3', '34.33'], ['unión de santa fe', '38', '30', '31', '99', '3', '33.00'], ['racing de córdoba', '27', '43', '26', '96', '3', '32.00'], ['platense', '34', '33', '27', '94', '3', '31.33'], ['temperley', '33', '31', '29', '93', '3', '31.00'], ['huracán', '32', '27', '32', '91', '3', '30.33'], ['chacarita juniors', 'n / a', '34', '21', '55', '2', '27.50']] |
2006 - 07 macedonian cup | https://en.wikipedia.org/wiki/2006%E2%80%9307_Macedonian_Cup | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17065288-2.html.csv | majority | most of the agg game scores in the 2006 -- 2007 macedonian cup do not have a team scoring 0 . | {'scope': 'all', 'col': '2', 'most_or_all': 'most', 'criterion': 'not_equal', 'value': '0', 'subset': None} | {'func': 'most_not_eq', 'args': ['all_rows', 'agg', '0'], 'result': True, 'ind': 0, 'tointer': 'for the agg records of all rows , most of them are not equal to 0 .', 'tostr': 'most_not_eq { all_rows ; agg ; 0 } = true'} | most_not_eq { all_rows ; agg ; 0 } = true | for the agg records of all rows , most of them are not equal to 0 . | 1 | 1 | {'most_not_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'agg_3': 3, '0_4': 4} | {'most_not_eq_0': 'most_not_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'agg_3': 'agg', '0_4': '0'} | {'most_not_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'agg_3': [0], '0_4': [0]} | ['team 1', 'agg', 'team 2', '1st leg', '2nd leg'] | [['pobeda', '3 - 0', 'shkëndija 79', '2 - 0', '1 - 0'], ['vardar', '5 - 1', 'metalurg', '4 - 1', '1 - 0'], ['drita', '4 - 2', 'bregalnica kraun', '3 - 0', '1 - 2'], ['gostivar', '3 - 6', 'renova', '1 - 4', '2 - 2'], ['milano', '4 - 3', 'baškimi', '2 - 1', '2 - 2'], ['rabotnički', '5 - 4', 'ilinden', '4 - 0', '1 - 4'], ['makedonija', '0 - 2', 'meridian fcu', '0 - 2', '0 - 0'], ['madžari solidarnost', '2 - 4', 'pelister', '2 - 2', '0 - 2']] |
list of great central railway locomotives and rolling stock | https://en.wikipedia.org/wiki/List_of_Great_Central_Railway_locomotives_and_rolling_stock | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11913905-3.html.csv | count | four great central railway locomotives and rolling stock had the br rail blue livery type . | {'scope': 'all', 'criterion': 'equal', 'value': 'br rail blue', 'result': '4', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'livery', 'br rail blue'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose livery record fuzzily matches to br rail blue .', 'tostr': 'filter_eq { all_rows ; livery ; br rail blue }'}], 'result': '4', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; livery ; br rail blue } }', 'tointer': 'select the rows whose livery record fuzzily matches to br rail blue . the number of such rows is 4 .'}, '4'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; livery ; br rail blue } } ; 4 } = true', 'tointer': 'select the rows whose livery record fuzzily matches to br rail blue . the number of such rows is 4 .'} | eq { count { filter_eq { all_rows ; livery ; br rail blue } } ; 4 } = true | select the rows whose livery record fuzzily matches to br rail blue . the number of such rows is 4 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'livery_5': 5, 'br rail blue_6': 6, '4_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'livery_5': 'livery', 'br rail blue_6': 'br rail blue', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'livery_5': [0], 'br rail blue_6': [0], '4_7': [2]} | ['number & name', 'description', 'livery', 'owner ( s )', 'date'] | [['operational', 'operational', 'operational', 'operational', 'operational'], ['no d2158 margaret - ann', 'british rail class 03 0 - 6 - 0dm', 'br blue with the late crest', 'great central railway plc', '1960'], ['no d3101', 'british rail class 08 0 - 6 - 0de', 'br green with wasp stripes and the early crest', 'private owner', '1955'], ['no 13180', 'british rail class 08 0 - 6 - 0de', 'br green with the early crest', 'private owner', '1955'], ['no 08220', 'british rail class 08 0 - 6 - 0de', 'br rail blue', 'english electric preservation', '1956'], ['no 08694', 'british rail class 08 0 - 6 - 0de', 'ews red & gold', 'private owner', '1959'], ['no 10119 margaret ethel - thomas alfred naylor', 'british rail class 10 0 - 6 - 0de', 'br rail blue', 'private owner', '1961'], ['undergoing overhaul , restoration or repairs', 'undergoing overhaul , restoration or repairs', 'undergoing overhaul , restoration or repairs', 'undergoing overhaul , restoration or repairs', 'undergoing overhaul , restoration or repairs'], ['no d2118', 'british rail class 03 0 - 6 - 0dm', 'br rail blue', 'private owner', '1959'], ['no 07005', 'british rail class 07 0 - 6 - 0de', 'br rail blue', 'private owner', '1962']] |
houston rockets all - time roster | https://en.wikipedia.org/wiki/Houston_Rockets_all-time_roster | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11734041-7.html.csv | unique | on the houston rockets all time roster , for those players in the guard position , the only one who is 6 ft 2 inches tall is winston garland . | {'scope': 'subset', 'row': '3', 'col': '3', 'col_other': '1', 'criterion': 'equal', 'value': '6 - 2', 'subset': {'col': '4', 'criterion': 'fuzzily_match', 'value': 'guard'}} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'position', 'guard'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; position ; guard }', 'tointer': 'select the rows whose position record fuzzily matches to guard .'}, 'height in ft', '6 - 2'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose position record fuzzily matches to guard . among these rows , select the rows whose height in ft record fuzzily matches to 6 - 2 .', 'tostr': 'filter_eq { filter_eq { all_rows ; position ; guard } ; height in ft ; 6 - 2 }'}], 'result': True, 'ind': 2, 'tostr': 'only { filter_eq { filter_eq { all_rows ; position ; guard } ; height in ft ; 6 - 2 } }', 'tointer': 'select the rows whose position record fuzzily matches to guard . among these rows , select the rows whose height in ft record fuzzily matches to 6 - 2 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'position', 'guard'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; position ; guard }', 'tointer': 'select the rows whose position record fuzzily matches to guard .'}, 'height in ft', '6 - 2'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose position record fuzzily matches to guard . among these rows , select the rows whose height in ft record fuzzily matches to 6 - 2 .', 'tostr': 'filter_eq { filter_eq { all_rows ; position ; guard } ; height in ft ; 6 - 2 }'}, 'player'], 'result': 'garland , winston winston garland', 'ind': 3, 'tostr': 'hop { filter_eq { filter_eq { all_rows ; position ; guard } ; height in ft ; 6 - 2 } ; player }'}, 'garland , winston winston garland'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { filter_eq { filter_eq { all_rows ; position ; guard } ; height in ft ; 6 - 2 } ; player } ; garland , winston winston garland }', 'tointer': 'the player record of this unqiue row is garland , winston winston garland .'}], 'result': True, 'ind': 5, 'tostr': 'and { only { filter_eq { filter_eq { all_rows ; position ; guard } ; height in ft ; 6 - 2 } } ; eq { hop { filter_eq { filter_eq { all_rows ; position ; guard } ; height in ft ; 6 - 2 } ; player } ; garland , winston winston garland } } = true', 'tointer': 'select the rows whose position record fuzzily matches to guard . among these rows , select the rows whose height in ft record fuzzily matches to 6 - 2 . there is only one such row in the table . the player record of this unqiue row is garland , winston winston garland .'} | and { only { filter_eq { filter_eq { all_rows ; position ; guard } ; height in ft ; 6 - 2 } } ; eq { hop { filter_eq { filter_eq { all_rows ; position ; guard } ; height in ft ; 6 - 2 } ; player } ; garland , winston winston garland } } = true | select the rows whose position record fuzzily matches to guard . among these rows , select the rows whose height in ft record fuzzily matches to 6 - 2 . there is only one such row in the table . the player record of this unqiue row is garland , winston winston garland . | 8 | 6 | {'and_5': 5, 'result_6': 6, 'only_2': 2, 'filter_str_eq_1': 1, 'filter_str_eq_0': 0, 'all_rows_7': 7, 'position_8': 8, 'guard_9': 9, 'height in ft_10': 10, '6 - 2_11': 11, 'str_eq_4': 4, 'str_hop_3': 3, 'player_12': 12, 'garland , winston winston garland_13': 13} | {'and_5': 'and', 'result_6': 'true', 'only_2': 'only', 'filter_str_eq_1': 'filter_str_eq', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_7': 'all_rows', 'position_8': 'position', 'guard_9': 'guard', 'height in ft_10': 'height in ft', '6 - 2_11': '6 - 2', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'player_12': 'player', 'garland , winston winston garland_13': 'garland , winston winston garland'} | {'and_5': [6], 'result_6': [], 'only_2': [5], 'filter_str_eq_1': [2, 3], 'filter_str_eq_0': [1], 'all_rows_7': [0], 'position_8': [0], 'guard_9': [0], 'height in ft_10': [1], '6 - 2_11': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'player_12': [3], 'garland , winston winston garland_13': [4]} | ['player', 'no ( s )', 'height in ft', 'position', 'years for rockets', 'school / club team / country'] | [['gaines , reece reece gaines', '4', '6 - 6', 'guard', '2004 - 05', 'louisville'], ['gambee , dave dave gambee', '20', '6 - 6', 'forward', '1967 - 68', 'oregon state'], ['garland , winston winston garland', '22', '6 - 2', 'guard', '1992 - 93', 'southwest missouri state'], ['garrett , calvin calvin garrett', '00', '6 - 7', 'forward', '1980 - 83', 'austin peay , oral roberts'], ['gibbs , dick dick gibbs', '40', '6 - 5', 'forward', '1971 - 73', 'texas - el paso'], ['godfread , dan dan godfread', '35', '6 - 9', 'forward / center', '1991 - 92', 'evansville'], ['graham , stephen stephen graham', '9', '6 - 6', 'guard / forward', '2005', 'oklahoma state'], ['gray , devin devin gray', '9', '6 - 6', 'guard / forward', '1999 - 2000', 'clemson'], ['green , gerald gerald green', '25', '6 - 8', 'guard / forward', '2008', 'gulf shores academy ( tx )'], ['green , johnny johnny green', '24', '6 - 5', 'forward', '1967 - 68', 'michigan state'], ['griffin , adrian adrian griffin', '7', '6 - 5', 'guard / forward', '2003 - 04', 'seton hall'], ['griffin , eddie eddie griffin', '33', '6 - 10', 'forward', '2001 - 03', 'seton hall'], ['guokas , matt matt guokas', '11', '6 - 6', 'guard', '1973 - 74', "st joseph 's"]] |
2008 - 09 dallas mavericks season | https://en.wikipedia.org/wiki/2008%E2%80%9309_Dallas_Mavericks_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17288869-9.html.csv | superlative | the american airlines center was the first location used by the dallas mavericks in the 2008 - 09 season . | {'scope': 'all', 'col_superlative': '2', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '8', '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 }'}, 'location attendance'], 'result': 'american airlines center 19688', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; date } ; location attendance }'}, 'american airlines center 19688'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmin { all_rows ; date } ; location attendance } ; american airlines center 19688 } = true', 'tointer': 'select the row whose date record of all rows is minimum . the location attendance record of this row is american airlines center 19688 .'} | eq { hop { argmin { all_rows ; date } ; location attendance } ; american airlines center 19688 } = true | select the row whose date record of all rows is minimum . the location attendance record of this row is american airlines center 19688 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'date_5': 5, 'location attendance_6': 6, 'american airlines center 19688_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', 'location attendance_6': 'location attendance', 'american airlines center 19688_7': 'american airlines center 19688'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'date_5': [0], 'location attendance_6': [1], 'american airlines center 19688_7': [2]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record'] | [['59', 'march 1', 'toronto', 'w 109 - 98 ( ot )', 'dirk nowitzki ( 24 )', 'james singleton ( 16 )', 'jason kidd ( 15 )', 'american airlines center 19688', '36 - 23'], ['60', 'march 2', 'oklahoma city', 'l 87 - 96 ( ot )', 'dirk nowitzki ( 28 )', 'james singleton ( 6 )', 'dirk nowitzki ( 6 )', 'ford center 18527', '36 - 24'], ['61', 'march 4', 'san antonio', 'w 107 - 102 ( ot )', 'josh howard ( 29 )', 'dirk nowitzki ( 12 )', 'jason kidd ( 9 )', 'american airlines center 20316', '37 - 24'], ['62', 'march 5', 'new orleans', 'l 88 - 104 ( ot )', 'dirk nowitzki ( 27 )', 'erick dampier ( 9 )', 'jason terry ( 4 )', 'new orleans arena 17230', '37 - 25'], ['63', 'march 7', 'washington', 'w 119 - 103 ( ot )', 'dirk nowitzki ( 34 )', 'dirk nowitzki ( 9 )', 'jason kidd ( 11 )', 'american airlines center 20150', '38 - 25'], ['64', 'march 10', 'phoenix', 'w 122 - 117 ( ot )', 'dirk nowitzki ( 34 )', 'dirk nowitzki ( 13 )', 'dirk nowitzki , josé juan barea ( 4 )', 'us airways center 18422', '39 - 25'], ['65', 'march 11', 'portland', 'w 93 - 89 ( ot )', 'dirk nowitzki ( 29 )', 'dirk nowitzki , jason kidd ( 10 )', 'jason kidd ( 10 )', 'rose garden 20286', '40 - 25'], ['66', 'march 13', 'golden state', 'l 110 - 119 ( ot )', 'dirk nowitzki ( 27 )', 'james singleton ( 11 )', 'jason kidd ( 11 )', 'oracle arena 18751', '40 - 26'], ['67', 'march 15', 'la lakers', 'l 100 - 107 ( ot )', 'jason terry ( 29 )', 'james singleton ( 10 )', 'jason kidd ( 9 )', 'staples center 18997', '40 - 27'], ['68', 'march 17', 'detroit', 'w 103 - 101 ( ot )', 'dirk nowitzki ( 30 )', 'erick dampier ( 13 )', 'josé juan barea ( 8 )', 'american airlines center 20427', '41 - 27'], ['69', 'march 19', 'atlanta', 'l 87 - 95 ( ot )', 'dirk nowitzki ( 23 )', 'dirk nowitzki ( 12 )', 'jason kidd ( 6 )', 'philips arena 17499', '41 - 28'], ['70', 'march 20', 'indiana', 'w 94 - 92 ( ot )', 'dirk nowitzki ( 23 )', 'james singleton ( 11 )', 'josé juan barea ( 6 )', 'conseco fieldhouse 17232', '42 - 28'], ['71', 'march 25', 'golden state', 'w 128 - 106 ( ot )', 'jason terry , dirk nowitzki ( 26 )', 'erick dampier ( 10 )', 'josé juan barea , jason kidd ( 7 )', 'american airlines center 19862', '43 - 28'], ['72', 'march 27', 'denver', 'l 101 - 103 ( ot )', 'dirk nowitzki ( 26 )', 'dirk nowitzki ( 11 )', 'josé juan barea , jason terry ( 4 )', 'american airlines center 20310', '43 - 29'], ['73', 'march 29', 'cleveland', 'l 74 - 102 ( ot )', 'dirk nowitzki ( 20 )', 'ryan hollins ( 12 )', 'jason kidd ( 8 )', 'quicken loans arena 20562', '43 - 30'], ['74', 'march 31', 'minnesota', 'w 108 - 88 ( ot )', 'dirk nowitzki ( 23 )', 'dirk nowitzki ( 12 )', 'jason kidd ( 13 )', 'target center 12111', '44 - 30']] |
wu liufang | https://en.wikipedia.org/wiki/Wu_Liufang | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-26681728-1.html.csv | count | wu liufang ranked 1 in the qualifiers in two of the competitions in her competitive history . | {'scope': 'all', 'criterion': 'equal', 'value': '1', 'result': '2', 'col': '7', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'rank - qualifying', '1'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose rank - qualifying record is equal to 1 .', 'tostr': 'filter_eq { all_rows ; rank - qualifying ; 1 }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; rank - qualifying ; 1 } }', 'tointer': 'select the rows whose rank - qualifying record is equal to 1 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; rank - qualifying ; 1 } } ; 2 } = true', 'tointer': 'select the rows whose rank - qualifying record is equal to 1 . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; rank - qualifying ; 1 } } ; 2 } = true | select the rows whose rank - qualifying record is equal to 1 . the number of such rows is 2 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_eq_0': 0, 'all_rows_4': 4, 'rank - qualifying_5': 5, '1_6': 6, '2_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'rank - qualifying_5': 'rank - qualifying', '1_6': '1', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'rank - qualifying_5': [0], '1_6': [0], '2_7': [2]} | ['year', 'competition', 'location', 'apparatus', 'rank - final', 'score - final', 'rank - qualifying', 'score - qualifying'] | [['2011', 'world cup', 'ghent', 'uneven bars', '3', '15.350', '1', '15.350'], ['2011', 'world cup', 'ghent', 'balance beam', '1', '14.975', '2', '14.850'], ['2011', 'world cup', 'ghent', 'floor exercise', '2', '13.650', '3', '13.475'], ['2010', 'world cup', 'ghent', 'uneven bars', '1', '15.050', '2', '14.775'], ['2010', 'world cup', 'ghent', 'balance beam', '3', '13.650', '2', '14.700'], ['2010', 'world cup', 'ghent', 'floor', '6', '12.700', '5', '13.450'], ['2010', 'world cup', 'doha', 'uneven bars', '2', '13.850', '2', '15.025'], ['2010', 'world cup', 'doha', 'balance beam', '1', '14.700', '1', '14.525'], ['2010', 'world cup', 'doha', 'floor', '1', '13.975', '6', '12.950']] |
arantxa rus | https://en.wikipedia.org/wiki/Arantxa_Rus | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18586543-6.html.csv | majority | through 2013 , arantxa rus lost a majority of her doubles matches played on clay . | {'scope': 'subset', 'col': '1', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': 'runner - up', 'subset': {'col': '4', 'criterion': 'equal', 'value': 'clay'}} | {'func': 'most_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'surface', 'clay'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; surface ; clay }', 'tointer': 'select the rows whose surface record fuzzily matches to clay .'}, 'outcome', 'runner - up'], 'result': True, 'ind': 1, 'tointer': 'select the rows whose surface record fuzzily matches to clay . for the outcome records of these rows , most of them fuzzily match to runner - up .', 'tostr': 'most_eq { filter_eq { all_rows ; surface ; clay } ; outcome ; runner - up } = true'} | most_eq { filter_eq { all_rows ; surface ; clay } ; outcome ; runner - up } = true | select the rows whose surface record fuzzily matches to clay . for the outcome records of these rows , most of them fuzzily match to runner - up . | 2 | 2 | {'most_str_eq_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, 'surface_4': 4, 'clay_5': 5, 'outcome_6': 6, 'runner - up_7': 7} | {'most_str_eq_1': 'most_str_eq', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'surface_4': 'surface', 'clay_5': 'clay', 'outcome_6': 'outcome', 'runner - up_7': 'runner - up'} | {'most_str_eq_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'surface_4': [0], 'clay_5': [0], 'outcome_6': [1], 'runner - up_7': [1]} | ['outcome', 'date', 'tournament', 'surface', 'partner', 'opponents', 'score'] | [['winner', '27 . october 2007', 'mexico city', 'hard', 'nicole thijssen', 'ivana abramović maria abramović', '6 - 0 , 6 - 1'], ['runner - up', '19 november 2008', 'opole', 'carpet', 'katarzyna piter', 'karolina kosińska aleksandra rosolska', '6 - 2 , 6 - 7 ( 6 ) ,'], ['runner - up', '31 may 2010', 'rome', 'clay', 'iryna bremond', 'christina mchale olivia rogowska', '4 - 6 , 1 - 6'], ['winner', '11 . february 2011', 'stockholm', 'hard ( i )', 'anastasiya yakimova', 'claire feuerstein ksenia lykina', '6 - 3 , 2 - 6 ,'], ['winner', '12 . may 2013', 'cagnes - sur - mer', 'clay', 'vania king', 'catalina castaño teliana pereira', '4 - 6 , 7 - 5 ,'], ['runner - up', '6 october 2013', 'vallduxo', 'clay', 'cindy burger', 'florencia molinero laura thorpe', '1 - 6 , 4 - 6']] |
2008 - 09 new york knicks season | https://en.wikipedia.org/wiki/2008%E2%80%9309_New_York_Knicks_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-17060277-10.html.csv | majority | all games of the new york knicks ' in the 2008 - 09 season were scheduled for the month of april . | {'scope': 'all', 'col': '2', 'most_or_all': 'all', 'criterion': 'fuzzily_match', 'value': 'april', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'date', 'april'], 'result': True, 'ind': 0, 'tointer': 'for the date records of all rows , all of them fuzzily match to april .', 'tostr': 'all_eq { all_rows ; date ; april } = true'} | all_eq { all_rows ; date ; april } = true | for the date records of all rows , all of them fuzzily match to april . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'date_3': 3, 'april_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'date_3': 'date', 'april_4': 'april'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'date_3': [0], 'april_4': [0]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record'] | [['76', 'april 4', 'toronto', 'l 95 - 102 ( ot )', 'al harrington , chris duhon ( 22 )', 'al harrington , david lee ( 7 )', 'david lee ( 6 )', 'madison square garden 19763', '29 - 47'], ['77', 'april 5', 'toronto', 'w 112 - 103 ( ot )', 'wilson chandler ( 17 )', 'david lee , al harrington ( 10 )', 'nate robinson ( 7 )', 'air canada centre 18879', '30 - 47'], ['78', 'april 7', 'chicago', 'l 103 - 110 ( ot )', 'wilson chandler ( 26 )', 'david lee ( 13 )', 'david lee , chris duhon ( 6 )', 'united center 20764', '30 - 48'], ['79', 'april 8', 'detroit', 'l 86 - 113 ( ot )', 'al harrington ( 26 )', 'wilson chandler ( 8 )', 'nate robinson , chris duhon ( 4 )', 'madison square garden 19763', '30 - 49'], ['80', 'april 10', 'orlando', 'w 105 - 95 ( ot )', 'al harrington ( 27 )', 'david lee ( 16 )', 'chris duhon , al harrington , david lee ( 4 )', 'amway arena 17461', '31 - 49'], ['81', 'april 12', 'miami', 'l 105 - 122 ( ot )', 'wilson chandler , al harrington ( 21 )', 'david lee ( 11 )', 'larry hughes , nate robinson ( 4 )', 'american airlines arena 19600', '31 - 50']] |
canada women 's national soccer team | https://en.wikipedia.org/wiki/Canada_women%27s_national_soccer_team | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1818918-3.html.csv | comparative | canada women 's national soccer team were champions in 1998 and 2010 . | {'row_1': '3', 'row_2': '6', 'col': '2', 'col_other': '1', 'relation': 'equal', 'record_mentioned': 'yes', 'diff_result': None} | {'func': 'and', 'args': [{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'year', '1998'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose year record fuzzily matches to 1998 .', 'tostr': 'filter_eq { all_rows ; year ; 1998 }'}, 'result'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; year ; 1998 } ; result }', 'tointer': 'select the rows whose year record fuzzily matches to 1998 . take the result record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'year', '2010'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose year record fuzzily matches to 2010 .', 'tostr': 'filter_eq { all_rows ; year ; 2010 }'}, 'result'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; year ; 2010 } ; result }', 'tointer': 'select the rows whose year record fuzzily matches to 2010 . take the result record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'eq { hop { filter_eq { all_rows ; year ; 1998 } ; result } ; hop { filter_eq { all_rows ; year ; 2010 } ; result } }', 'tointer': 'select the rows whose year record fuzzily matches to 1998 . take the result record of this row . select the rows whose year record fuzzily matches to 2010 . take the result record of this row . the first record fuzzily matches to the second record .'}, {'func': 'and', 'args': [{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'year', '1998'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose year record fuzzily matches to 1998 .', 'tostr': 'filter_eq { all_rows ; year ; 1998 }'}, 'result'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; year ; 1998 } ; result }', 'tointer': 'select the rows whose year record fuzzily matches to 1998 . take the result record of this row .'}, 'champions'], 'result': True, 'ind': 5, 'tostr': 'eq { hop { filter_eq { all_rows ; year ; 1998 } ; result } ; champions }', 'tointer': 'the result record of the first row is champions .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'year', '2010'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose year record fuzzily matches to 2010 .', 'tostr': 'filter_eq { all_rows ; year ; 2010 }'}, 'result'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; year ; 2010 } ; result }', 'tointer': 'select the rows whose year record fuzzily matches to 2010 . take the result record of this row .'}, 'champions'], 'result': True, 'ind': 6, 'tostr': 'eq { hop { filter_eq { all_rows ; year ; 2010 } ; result } ; champions }', 'tointer': 'the result record of the second row is champions .'}], 'result': True, 'ind': 7, 'tostr': 'and { eq { hop { filter_eq { all_rows ; year ; 1998 } ; result } ; champions } ; eq { hop { filter_eq { all_rows ; year ; 2010 } ; result } ; champions } }', 'tointer': 'the result record of the first row is champions . the result record of the second row is champions .'}], 'result': True, 'ind': 8, 'tostr': 'and { eq { hop { filter_eq { all_rows ; year ; 1998 } ; result } ; hop { filter_eq { all_rows ; year ; 2010 } ; result } } ; and { eq { hop { filter_eq { all_rows ; year ; 1998 } ; result } ; champions } ; eq { hop { filter_eq { all_rows ; year ; 2010 } ; result } ; champions } } } = true', 'tointer': 'select the rows whose year record fuzzily matches to 1998 . take the result record of this row . select the rows whose year record fuzzily matches to 2010 . take the result record of this row . the first record fuzzily matches to the second record . the result record of the first row is champions . the result record of the second row is champions .'} | and { eq { hop { filter_eq { all_rows ; year ; 1998 } ; result } ; hop { filter_eq { all_rows ; year ; 2010 } ; result } } ; and { eq { hop { filter_eq { all_rows ; year ; 1998 } ; result } ; champions } ; eq { hop { filter_eq { all_rows ; year ; 2010 } ; result } ; champions } } } = true | select the rows whose year record fuzzily matches to 1998 . take the result record of this row . select the rows whose year record fuzzily matches to 2010 . take the result record of this row . the first record fuzzily matches to the second record . the result record of the first row is champions . the result record of the second row is champions . | 13 | 9 | {'and_8': 8, 'result_9': 9, 'str_eq_4': 4, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_10': 10, 'year_11': 11, '1998_12': 12, 'result_13': 13, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_14': 14, 'year_15': 15, '2010_16': 16, 'result_17': 17, 'and_7': 7, 'str_eq_5': 5, 'champions_18': 18, 'str_eq_6': 6, 'champions_19': 19} | {'and_8': 'and', 'result_9': 'true', 'str_eq_4': 'str_eq', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_10': 'all_rows', 'year_11': 'year', '1998_12': '1998', 'result_13': 'result', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_14': 'all_rows', 'year_15': 'year', '2010_16': '2010', 'result_17': 'result', 'and_7': 'and', 'str_eq_5': 'str_eq', 'champions_18': 'champions', 'str_eq_6': 'str_eq', 'champions_19': 'champions'} | {'and_8': [9], 'result_9': [], 'str_eq_4': [8], 'str_hop_2': [4, 5], 'filter_str_eq_0': [2], 'all_rows_10': [0], 'year_11': [0], '1998_12': [0], 'result_13': [2], 'str_hop_3': [4, 6], 'filter_str_eq_1': [3], 'all_rows_14': [1], 'year_15': [1], '2010_16': [1], 'result_17': [3], 'and_7': [8], 'str_eq_5': [7], 'champions_18': [5], 'str_eq_6': [7], 'champions_19': [6]} | ['year', 'result', 'matches', 'wins', 'draws', 'losses'] | [['1991', 'runner - up', '5', '4', '0', '1'], ['1994', 'runner - up', '4', '3', '0', '1'], ['1998', 'champions', '5', '5', '0', '0'], ['2002', 'runner - up', '5', '4', '0', '1'], ['2006', 'runner - up', '2', '1', '0', '1'], ['2010', 'champions', '5', '5', '0', '0']] |
2007 grand rapids rampage season | https://en.wikipedia.org/wiki/2007_Grand_Rapids_Rampage_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11786440-4.html.csv | comparative | in the 2007 grand rapids rampage 's season , kenny solomon had 2 more touchdowns than chris ryan . | {'row_1': '9', 'row_2': '10', 'col': '5', 'col_other': '1', 'relation': 'diff', 'record_mentioned': 'no', 'diff_result': {'diff_value': '2', 'bigger': 'row1'}} | {'func': 'eq', 'args': [{'func': 'diff', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', 'kenny solomon'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose player record fuzzily matches to kenny solomon .', 'tostr': 'filter_eq { all_rows ; player ; kenny solomon }'}, "td 's"], 'result': None, 'ind': 2, 'tostr': "hop { filter_eq { all_rows ; player ; kenny solomon } ; td 's }", 'tointer': "select the rows whose player record fuzzily matches to kenny solomon . take the td 's record of this row ."}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', 'chris ryan'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose player record fuzzily matches to chris ryan .', 'tostr': 'filter_eq { all_rows ; player ; chris ryan }'}, "td 's"], 'result': None, 'ind': 3, 'tostr': "hop { filter_eq { all_rows ; player ; chris ryan } ; td 's }", 'tointer': "select the rows whose player record fuzzily matches to chris ryan . take the td 's record of this row ."}], 'result': '2', 'ind': 4, 'tostr': "diff { hop { filter_eq { all_rows ; player ; kenny solomon } ; td 's } ; hop { filter_eq { all_rows ; player ; chris ryan } ; td 's } }"}, '2'], 'result': True, 'ind': 5, 'tostr': "eq { diff { hop { filter_eq { all_rows ; player ; kenny solomon } ; td 's } ; hop { filter_eq { all_rows ; player ; chris ryan } ; td 's } } ; 2 } = true", 'tointer': "select the rows whose player record fuzzily matches to kenny solomon . take the td 's record of this row . select the rows whose player record fuzzily matches to chris ryan . take the td 's record of this row . the first record is 2 larger than the second record ."} | eq { diff { hop { filter_eq { all_rows ; player ; kenny solomon } ; td 's } ; hop { filter_eq { all_rows ; player ; chris ryan } ; td 's } } ; 2 } = true | select the rows whose player record fuzzily matches to kenny solomon . take the td 's record of this row . select the rows whose player record fuzzily matches to chris ryan . take the td 's record of this row . the first record is 2 larger than the second record . | 6 | 6 | {'eq_5': 5, 'result_6': 6, 'diff_4': 4, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_7': 7, 'player_8': 8, 'kenny solomon_9': 9, "td 's_10": 10, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_11': 11, 'player_12': 12, 'chris ryan_13': 13, "td 's_14": 14, '2_15': 15} | {'eq_5': 'eq', 'result_6': 'true', 'diff_4': 'diff', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_7': 'all_rows', 'player_8': 'player', 'kenny solomon_9': 'kenny solomon', "td 's_10": "td 's", 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_11': 'all_rows', 'player_12': 'player', 'chris ryan_13': 'chris ryan', "td 's_14": "td 's", '2_15': '2'} | {'eq_5': [6], 'result_6': [], 'diff_4': [5], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_7': [0], 'player_8': [0], 'kenny solomon_9': [0], "td 's_10": [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_11': [1], 'player_12': [1], 'chris ryan_13': [1], "td 's_14": [3], '2_15': [5]} | ['player', 'rec', 'yards', 'avg', "td 's", 'long'] | [['cornelius bonner', '102', '1436', '14.1', '29', '49'], ['timon marshall', '102', '1134', '11.1', '27', '34'], ['jerome riley', '78', '845', '10.8', '12', '43'], ['scotty anderson', '31', '323', '10.4', '6', '33'], ['clarence coleman', '23', '253', '11', '3', '28'], ['ronney daniels', '23', '243', '10.6', '6', '30'], ['jermaine lewis', '23', '234', '10.2', '2', '30'], ['troy edwards', '27', '220', '8.1', '2', '24'], ['kenny solomon', '18', '201', '11.2', '3', '46'], ['chris ryan', '9', '70', '7.8', '1', '24'], ['winfield garnett', '1', '2', '2', '0', '2']] |
2008 - 09 nbl season | https://en.wikipedia.org/wiki/2008%E2%80%9309_NBL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16653153-23.html.csv | count | in the 2008 - 09 nbl season , among the games played in january , three of them had attendance below 4,000 . | {'scope': 'subset', 'criterion': 'less_than', 'value': '4000', 'result': '3', 'col': '6', 'subset': {'col': '1', 'criterion': 'fuzzily_match', 'value': 'january'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_less', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', 'january'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; date ; january }', 'tointer': 'select the rows whose date record fuzzily matches to january .'}, 'crowd', '4000'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose date record fuzzily matches to january . among these rows , select the rows whose crowd record is less than 4000 .', 'tostr': 'filter_less { filter_eq { all_rows ; date ; january } ; crowd ; 4000 }'}], 'result': '3', 'ind': 2, 'tostr': 'count { filter_less { filter_eq { all_rows ; date ; january } ; crowd ; 4000 } }', 'tointer': 'select the rows whose date record fuzzily matches to january . among these rows , select the rows whose crowd record is less than 4000 . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_less { filter_eq { all_rows ; date ; january } ; crowd ; 4000 } } ; 3 } = true', 'tointer': 'select the rows whose date record fuzzily matches to january . among these rows , select the rows whose crowd record is less than 4000 . the number of such rows is 3 .'} | eq { count { filter_less { filter_eq { all_rows ; date ; january } ; crowd ; 4000 } } ; 3 } = true | select the rows whose date record fuzzily matches to january . among these rows , select the rows whose crowd record is less than 4000 . the number of such rows is 3 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_less_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'date_6': 6, 'january_7': 7, 'crowd_8': 8, '4000_9': 9, '3_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_less_1': 'filter_less', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'date_6': 'date', 'january_7': 'january', 'crowd_8': 'crowd', '4000_9': '4000', '3_10': '3'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_less_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'date_6': [0], 'january_7': [0], 'crowd_8': [1], '4000_9': [1], '3_10': [3]} | ['date', 'home team', 'score', 'away team', 'venue', 'crowd', 'box score', 'report'] | [['31 december', 'cairns taipans', '105 - 112', 'wollongong hawks', 'cairns convention centre', '3853', 'box score', '-'], ['31 december', 'gold coast blaze', '103 - 94', 'adelaide 36ers', 'gold coast convention centre', '2233', 'box score', '-'], ['31 december', 'townsville crocodiles', '105 - 95', 'south dragons', 'townsville entertainment centre', '4644', 'box score', '-'], ['2 january', 'wollongong hawks', '111 - 94', 'new zealand breakers', 'win entertainment centre', '2175', 'box score', '-'], ['3 january', 'south dragons', '90 - 99', 'perth wildcats', 'hisense arena', '4069', 'box score', '-'], ['3 january', 'sydney spirit', '86 - 85', 'new zealand breakers', 'whitlam centre', '920', 'box score', '-'], ['4 january', 'gold coast blaze', '88 - 105', 'townsville crocodiles', 'gold coast convention centre', '2374', 'box score', '-']] |
united states house of representatives elections , 1922 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1922 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1342426-18.html.csv | superlative | in the 1922 for the united states house of representatives , the incumbent with the earliest date of first election is henry garland dupré . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '2', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '2', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmin', 'args': ['all_rows', 'first elected'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; first elected }'}, 'incumbent'], 'result': 'henry garland dupré', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; first elected } ; incumbent }'}, 'henry garland dupré'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmin { all_rows ; first elected } ; incumbent } ; henry garland dupré } = true', 'tointer': 'select the row whose first elected record of all rows is minimum . the incumbent record of this row is henry garland dupré .'} | eq { hop { argmin { all_rows ; first elected } ; incumbent } ; henry garland dupré } = true | select the row whose first elected record of all rows is minimum . the incumbent record of this row is henry garland dupré . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'first elected_5': 5, 'incumbent_6': 6, 'henry garland dupré_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'first elected_5': 'first elected', 'incumbent_6': 'incumbent', 'henry garland dupré_7': 'henry garland dupré'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'first elected_5': [0], 'incumbent_6': [1], 'henry garland dupré_7': [2]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['louisiana 1', "james o'connor", 'democratic', '1918', 're - elected', "james o'connor ( d ) unopposed"], ['louisiana 2', 'henry garland dupré', 'democratic', '1908', 're - elected', 'henry garland dupré ( d ) unopposed'], ['louisiana 3', 'whitmell p martin', 'democratic', '1914', 're - elected', 'whitmell p martin ( d ) unopposed'], ['louisiana 4', 'john n sandlin', 'democratic', '1920', 're - elected', 'john n sandlin ( d ) unopposed'], ['louisiana 5', 'riley joseph wilson', 'democratic', '1914', 're - elected', 'riley joseph wilson ( d ) unopposed'], ['louisiana 6', 'george k favrot', 'democratic', '1920', 're - elected', 'george k favrot ( d ) unopposed'], ['louisiana 7', 'ladislas lazaro', 'democratic', '1912', 're - elected', 'ladislas lazaro ( d ) unopposed']] |
1972 miami dolphins season | https://en.wikipedia.org/wiki/1972_Miami_Dolphins_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14202514-1.html.csv | comparative | the miami dolphins had a game against washington redskins earlier than the minnesota vikings . | {'row_1': '5', 'row_2': '6', 'col': '2', 'col_other': '3', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', 'washington redskins'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose opponent record fuzzily matches to washington redskins .', 'tostr': 'filter_eq { all_rows ; opponent ; washington redskins }'}, 'date'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; opponent ; washington redskins } ; date }', 'tointer': 'select the rows whose opponent record fuzzily matches to washington redskins . take the date record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', 'minnesota vikings'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose opponent record fuzzily matches to minnesota vikings .', 'tostr': 'filter_eq { all_rows ; opponent ; minnesota vikings }'}, 'date'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; opponent ; minnesota vikings } ; date }', 'tointer': 'select the rows whose opponent record fuzzily matches to minnesota vikings . take the date record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; opponent ; washington redskins } ; date } ; hop { filter_eq { all_rows ; opponent ; minnesota vikings } ; date } } = true', 'tointer': 'select the rows whose opponent record fuzzily matches to washington redskins . take the date record of this row . select the rows whose opponent record fuzzily matches to minnesota vikings . take the date record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; opponent ; washington redskins } ; date } ; hop { filter_eq { all_rows ; opponent ; minnesota vikings } ; date } } = true | select the rows whose opponent record fuzzily matches to washington redskins . take the date record of this row . select the rows whose opponent record fuzzily matches to minnesota vikings . take the date record of this row . the first record is less than the second record . | 5 | 5 | {'less_4': 4, 'result_5': 5, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'opponent_7': 7, 'washington redskins_8': 8, 'date_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'opponent_11': 11, 'minnesota vikings_12': 12, 'date_13': 13} | {'less_4': 'less', 'result_5': 'true', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'opponent_7': 'opponent', 'washington redskins_8': 'washington redskins', 'date_9': 'date', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'opponent_11': 'opponent', 'minnesota vikings_12': 'minnesota vikings', 'date_13': 'date'} | {'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'opponent_7': [0], 'washington redskins_8': [0], 'date_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'opponent_11': [1], 'minnesota vikings_12': [1], 'date_13': [3]} | ['week', 'date', 'opponent', 'result', 'record'] | [['1', 'august 5 , 1972', 'detroit lions', 'l 23 - 31', '0 - 1'], ['2', 'august 12 , 1972', 'green bay packers', 'l 13 - 14', '0 - 2'], ['3', 'august 19 , 1972', 'cincinnati bengals', 'w 35 - 17', '1 - 2'], ['4', 'august 25 , 1972', 'atlanta falcons', 'w 24 - 10', '2 - 2'], ['5', 'august 31 , 1972', 'washington redskins', 'l 24 - 27', '2 - 3'], ['6', 'september 10 , 1972', 'minnesota vikings', 'w 21 - 19', '3 - 3']] |
1990 dallas cowboys season | https://en.wikipedia.org/wiki/1990_Dallas_Cowboys_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11281728-2.html.csv | ordinal | the dallas cowboys ' game against the new york giants recorded their highest attendance of the 1990 season . | {'row': '4', 'col': '6', 'order': '1', 'col_other': '3', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'attendance', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; attendance ; 1 }'}, 'opponent'], 'result': 'new york giants', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; attendance ; 1 } ; opponent }'}, 'new york giants'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; attendance ; 1 } ; opponent } ; new york giants } = true', 'tointer': 'select the row whose attendance record of all rows is 1st maximum . the opponent record of this row is new york giants .'} | eq { hop { nth_argmax { all_rows ; attendance ; 1 } ; opponent } ; new york giants } = true | select the row whose attendance record of all rows is 1st maximum . the opponent record of this row is new york giants . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'attendance_5': 5, '1_6': 6, 'opponent_7': 7, 'new york giants_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'attendance_5': 'attendance', '1_6': '1', 'opponent_7': 'opponent', 'new york giants_8': 'new york giants'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'attendance_5': [0], '1_6': [0], 'opponent_7': [1], 'new york giants_8': [2]} | ['week', 'date', 'opponent', 'result', 'venue', 'attendance'] | [['1', '1990 - 09 - 09', 'san diego chargers', 'w 17 - 14', 'texas stadium', '48063'], ['2', '1990 - 09 - 16', 'new york giants', 'l 28 - 7', 'texas stadium', '61090'], ['3', '1990 - 09 - 23', 'washington redskins', 'l 19 - 15', 'robert f kennedy memorial stadium', '53804'], ['4', '1990 - 09 - 30', 'new york giants', 'l 31 - 17', 'giants stadium', '75923'], ['5', '1990 - 10 - 07', 'tampa bay buccaneers', 'w 14 - 10', 'texas stadium', '60076'], ['6', '1990 - 10 - 14', 'phoenix cardinals', 'l 20 - 3', 'sun devil stadium', '45235'], ['7', '1990 - 10 - 21', 'tampa bay buccaneers', 'w 17 - 13', 'tampa stadium', '68315'], ['8', '1990 - 10 - 28', 'philadelphia eagles', 'l 21 - 20', 'texas stadium', '62605'], ['9', '1990 - 11 - 04', 'new york jets', 'l 24 - 9', 'the meadowlands', '68086'], ['10', '1990 - 11 - 11', 'san francisco 49ers', 'l 24 - 6', 'texas stadium', '62966'], ['11', '1990 - 11 - 18', 'los angeles rams', 'w 24 - 21', 'anaheim stadium', '58589'], ['12', '1990 - 11 - 22', 'washington redskins', 'w 27 - 17', 'texas stadium', '60355'], ['13', '1990 - 12 - 02', 'new orleans saints', 'w 17 - 13', 'texas stadium', '60087'], ['14', '-', '-', '-', '-', ''], ['15', '1990 - 12 - 16', 'phoenix cardinals', 'w 41 - 10', 'texas stadium', '60190'], ['16', '1990 - 12 - 23', 'philadelphia eagles', 'l 17 - 3', 'veterans stadium', '63895'], ['17', '1990 - 12 - 30', 'atlanta falcons', 'l 26 - 7', 'atlanta - fulton county stadium', '50097']] |
césar cielo | https://en.wikipedia.org/wiki/C%C3%A9sar_Cielo | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12627202-1.html.csv | comparative | césar cielo competed in an event in rome the year after he competed in an event in beijing . | {'row_1': '6', 'row_2': '3', 'col': '4', 'col_other': '3', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'venue', 'rome'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose venue record fuzzily matches to rome .', 'tostr': 'filter_eq { all_rows ; venue ; rome }'}, 'date'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; venue ; rome } ; date }', 'tointer': 'select the rows whose venue record fuzzily matches to rome . take the date record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'venue', 'beijing'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose venue record fuzzily matches to beijing .', 'tostr': 'filter_eq { all_rows ; venue ; beijing }'}, 'date'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; venue ; beijing } ; date }', 'tointer': 'select the rows whose venue record fuzzily matches to beijing . take the date record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; venue ; rome } ; date } ; hop { filter_eq { all_rows ; venue ; beijing } ; date } } = true', 'tointer': 'select the rows whose venue record fuzzily matches to rome . take the date record of this row . select the rows whose venue record fuzzily matches to beijing . take the date record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; venue ; rome } ; date } ; hop { filter_eq { all_rows ; venue ; beijing } ; date } } = true | select the rows whose venue record fuzzily matches to rome . take the date record of this row . select the rows whose venue record fuzzily matches to beijing . take the date record of this row . the first record is greater than the second record . | 5 | 5 | {'greater_4': 4, 'result_5': 5, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'venue_7': 7, 'rome_8': 8, 'date_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'venue_11': 11, 'beijing_12': 12, 'date_13': 13} | {'greater_4': 'greater', 'result_5': 'true', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'venue_7': 'venue', 'rome_8': 'rome', 'date_9': 'date', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'venue_11': 'venue', 'beijing_12': 'beijing', 'date_13': 'date'} | {'greater_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'venue_7': [0], 'rome_8': [0], 'date_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'venue_11': [1], 'beijing_12': [1], 'date_13': [3]} | ['event', 'time', 'venue', 'date', 'notes'] | [['50 m freestyle', '20.91', 'são paulo', 'december 18 , 2009', 'wr'], ['100 m freestyle', '46.91', 'rome', 'july 30 , 2009', 'wr'], ['50 m freestyle', '21.30', 'beijing', 'august 16 , 2008', 'or'], ['50 m butterfly', '22.76', 'rio de janeiro', 'april 26 , 2012', 'am'], ['450 m freestyle', '1:26.12', 'são paulo', 'december 19 , 2009', 'sa'], ['4100 m freestyle', '3:10.80', 'rome', 'july 26 , 2009', 'sa'], ['4100 m medley', '3:29.16', 'rome', 'august 2 , 2009', 'sa']] |
1908 vfl season | https://en.wikipedia.org/wiki/1908_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1204658-15.html.csv | count | there were 5 game venues used during the 1908 vfl season . | {'scope': 'all', 'criterion': 'all', 'value': 'venue', 'result': '5', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_all', 'args': ['all_rows', 'venue'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose venue record is arbitrary .', 'tostr': 'filter_all { all_rows ; venue }'}], 'result': '5', 'ind': 1, 'tostr': 'count { filter_all { all_rows ; venue } }', 'tointer': 'select the rows whose venue record is arbitrary . the number of such rows is 5 .'}, '5'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_all { all_rows ; venue } } ; 5 } = true', 'tointer': 'select the rows whose venue record is arbitrary . the number of such rows is 5 .'} | eq { count { filter_all { all_rows ; venue } } ; 5 } = true | select the rows whose venue record is arbitrary . the number of such rows is 5 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_all_0': 0, 'all_rows_4': 4, 'venue_5': 5, '5_6': 6} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_all_0': 'filter_all', 'all_rows_4': 'all_rows', 'venue_5': 'venue', '5_6': '5'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_all_0': [1], 'all_rows_4': [0], 'venue_5': [0], '5_6': [2]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'date'] | [['melbourne', '7.12 ( 54 )', 'university', '8.10 ( 58 )', 'mcg', '1 august 1908'], ['essendon', '8.13 ( 61 )', 'fitzroy', '7.8 ( 50 )', 'emcg', '1 august 1908'], ['carlton', '8.19 ( 67 )', 'south melbourne', '6.5 ( 41 )', 'princes park', '1 august 1908'], ['st kilda', '17.5 ( 107 )', 'geelong', '5.8 ( 38 )', 'junction oval', '1 august 1908'], ['richmond', '11.8 ( 74 )', 'collingwood', '10.9 ( 69 )', 'punt road oval', '1 august 1908']] |
porphyrin | https://en.wikipedia.org/wiki/Porphyrin | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-182499-1.html.csv | comparative | uroporphyrinogen iii synthase has a higher omim than protoporphyrinogen oxidase . | {'row_1': '4', 'row_2': '7', 'col': '7', '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', 'enzyme', 'uroporphyrinogen iii synthase'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose enzyme record fuzzily matches to uroporphyrinogen iii synthase .', 'tostr': 'filter_eq { all_rows ; enzyme ; uroporphyrinogen iii synthase }'}, 'omim'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; enzyme ; uroporphyrinogen iii synthase } ; omim }', 'tointer': 'select the rows whose enzyme record fuzzily matches to uroporphyrinogen iii synthase . take the omim record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'enzyme', 'protoporphyrinogen oxidase'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose enzyme record fuzzily matches to protoporphyrinogen oxidase .', 'tostr': 'filter_eq { all_rows ; enzyme ; protoporphyrinogen oxidase }'}, 'omim'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; enzyme ; protoporphyrinogen oxidase } ; omim }', 'tointer': 'select the rows whose enzyme record fuzzily matches to protoporphyrinogen oxidase . take the omim record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; enzyme ; uroporphyrinogen iii synthase } ; omim } ; hop { filter_eq { all_rows ; enzyme ; protoporphyrinogen oxidase } ; omim } } = true', 'tointer': 'select the rows whose enzyme record fuzzily matches to uroporphyrinogen iii synthase . take the omim record of this row . select the rows whose enzyme record fuzzily matches to protoporphyrinogen oxidase . take the omim record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; enzyme ; uroporphyrinogen iii synthase } ; omim } ; hop { filter_eq { all_rows ; enzyme ; protoporphyrinogen oxidase } ; omim } } = true | select the rows whose enzyme record fuzzily matches to uroporphyrinogen iii synthase . take the omim record of this row . select the rows whose enzyme record fuzzily matches to protoporphyrinogen oxidase . take the omim 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, 'enzyme_7': 7, 'uroporphyrinogen iii synthase_8': 8, 'omim_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'enzyme_11': 11, 'protoporphyrinogen oxidase_12': 12, 'omim_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', 'enzyme_7': 'enzyme', 'uroporphyrinogen iii synthase_8': 'uroporphyrinogen iii synthase', 'omim_9': 'omim', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'enzyme_11': 'enzyme', 'protoporphyrinogen oxidase_12': 'protoporphyrinogen oxidase', 'omim_13': 'omim'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'enzyme_7': [0], 'uroporphyrinogen iii synthase_8': [0], 'omim_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'enzyme_11': [1], 'protoporphyrinogen oxidase_12': [1], 'omim_13': [3]} | ['enzyme', 'location', 'substrate', 'product', 'chromosome', 'ec', 'omim', 'porphyria'] | [['ala synthase', 'mitochondrion', 'glycine , succinyl coa', 'δ - aminolevulinic acid', '3p21 .1', '2.3.1.37', '125290', 'none'], ['ala dehydratase', 'cytosol', 'δ - aminolevulinic acid', 'porphobilinogen', '9q34', '4.2.1.24', '125270', 'ala - dehydratase deficiency'], ['pbg deaminase', 'cytosol', 'porphobilinogen', 'hydroxymethyl bilane', '11q23 .3', '2.5.1.61', '176000', 'acute intermittent porphyria'], ['uroporphyrinogen iii synthase', 'cytosol', 'hydroxymethyl bilane', 'uroporphyrinogen iii', '10q25 .2 - q26 .3', '4.2.1.75', '606938', 'congenital erythropoietic porphyria'], ['uroporphyrinogen iii decarboxylase', 'cytosol', 'uroporphyrinogen iii', 'coproporphyrinogen iii', '1p34', '4.1.1.37', '176100', 'porphyria cutanea tarda'], ['coproporphyrinogen iii oxidase', 'mitochondrion', 'coproporphyrinogen iii', 'protoporphyrinogen ix', '3q12', '1.3.3.3', '121300', 'coproporphyria'], ['protoporphyrinogen oxidase', 'mitochondrion', 'protoporphyrinogen ix', 'protoporphyrin ix', '1q22', '1.3.3.4', '600923', 'variegate porphyria']] |
miss namibia 2009 | https://en.wikipedia.org/wiki/Miss_Namibia_2009 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-23576576-2.html.csv | ordinal | daniella filipovic is the second oldest contestant in the miss namibia 2009 pageant . | {'row': '9', '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', 'age', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; age ; 2 }'}, 'contestant'], 'result': 'daniella filipovic', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; age ; 2 } ; contestant }'}, 'daniella filipovic'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; age ; 2 } ; contestant } ; daniella filipovic } = true', 'tointer': 'select the row whose age record of all rows is 2nd maximum . the contestant record of this row is daniella filipovic .'} | eq { hop { nth_argmax { all_rows ; age ; 2 } ; contestant } ; daniella filipovic } = true | select the row whose age record of all rows is 2nd maximum . the contestant record of this row is daniella filipovic . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'age_5': 5, '2_6': 6, 'contestant_7': 7, 'daniella filipovic_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', 'age_5': 'age', '2_6': '2', 'contestant_7': 'contestant', 'daniella filipovic_8': 'daniella filipovic'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'age_5': [0], '2_6': [0], 'contestant_7': [1], 'daniella filipovic_8': [2]} | ['represented', 'contestant', 'age', 'height ( in )', 'height ( cm )', 'hometown'] | [['caprivi', 'happie ntelamo', '21', "6 ' 1", '185', 'katima mulilo'], ['erongo', 'theodora amutjira', '18', "5 ' 8", '176', 'walvis bay'], ['karas', 'mari venter', '23', "5 ' 10", '179', 'swakopmund'], ['kavango', 'albertina shigwedha', '26', "5 ' 9", '177', 'rundu'], ['khomas', 'tanya schemmer', '19', "6 ' 0", '183', 'windhoek'], ['ohangwena', 'jayne david', '24', "5 ' 5", '166', 'eenhana'], ['omusati', 'susan van zyl', '20', "5 ' 11", '182', 'oshakati'], ['oshikoto', 'selma usiku', '22', "6 ' 0", '184', 'omuthiya'], ['swakopmund', 'daniella filipovic', '25', "5 ' 7", '172', 'swakopmund']] |
united states house of representatives elections , 1918 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1918 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1346118-5.html.csv | majority | the majority of the representatives in this election were indeed re-elected . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'equal', 'value': 're - elected', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'result', 're - elected'], 'result': True, 'ind': 0, 'tointer': 'for the result records of all rows , most of them fuzzily match to re - elected .', 'tostr': 'most_eq { all_rows ; result ; re - elected } = true'} | most_eq { all_rows ; result ; re - elected } = true | for the result records of all rows , most of them fuzzily match to re - elected . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'result_3': 3, 're - elected_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'result_3': 'result', 're - elected_4': 're - elected'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'result_3': [0], 're - elected_4': [0]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['california 1', 'clarence f lea', 'democratic', '1916', 're - elected', 'clarence f lea ( d ) ( unopposed )'], ['california 2', 'john e raker', 'democratic', '1910', 're - elected', 'john e raker ( d ) ( unopposed )'], ['california 4', 'julius kahn', 'republican', '1898', 're - elected', 'julius kahn ( r ) 86.6 % william short ( s ) 13.4 %'], ['california 5', 'john i nolan', 'republican', '1912', 're - elected', 'john i nolan ( r ) 87 % thomas f feeley ( s ) 13 %'], ['california 6', 'john a elston', 'progressive', '1912', 're - elected as republican republican gain', 'john a elston ( r ) 88.4 % luella twining ( s ) 11.6 %'], ['california 7', 'denver s church', 'democratic', '1912', 'retired republican gain', 'henry e barbour ( r ) 52.1 % henry hawson ( d ) 47.9 %']] |
brl v6 | https://en.wikipedia.org/wiki/BRL_V6 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15216339-1.html.csv | unique | of these drivers , only donny creveis drove for the waytech team . | {'scope': 'all', 'row': '1', 'col': '3', 'col_other': '2', 'criterion': 'equal', 'value': 'weytech', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'team', 'weytech'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose team record fuzzily matches to weytech .', 'tostr': 'filter_eq { all_rows ; team ; weytech }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; team ; weytech } }', 'tointer': 'select the rows whose team record fuzzily matches to weytech . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'team', 'weytech'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose team record fuzzily matches to weytech .', 'tostr': 'filter_eq { all_rows ; team ; weytech }'}, 'driver'], 'result': 'donny crevels', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; team ; weytech } ; driver }'}, 'donny crevels'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; team ; weytech } ; driver } ; donny crevels }', 'tointer': 'the driver record of this unqiue row is donny crevels .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; team ; weytech } } ; eq { hop { filter_eq { all_rows ; team ; weytech } ; driver } ; donny crevels } } = true', 'tointer': 'select the rows whose team record fuzzily matches to weytech . there is only one such row in the table . the driver record of this unqiue row is donny crevels .'} | and { only { filter_eq { all_rows ; team ; weytech } } ; eq { hop { filter_eq { all_rows ; team ; weytech } ; driver } ; donny crevels } } = true | select the rows whose team record fuzzily matches to weytech . there is only one such row in the table . the driver record of this unqiue row is donny crevels . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'team_7': 7, 'weytech_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'driver_9': 9, 'donny crevels_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'team_7': 'team', 'weytech_8': 'weytech', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'driver_9': 'driver', 'donny crevels_10': 'donny crevels'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'team_7': [0], 'weytech_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'driver_9': [2], 'donny crevels_10': [3]} | ['season', 'driver', 'team', 'tyre', 'points'] | [['2004', 'donny crevels', 'weytech', 'h', '86'], ['2005', 'jeroen bleekemolen', 'us carworld racing', 'h', '262'], ['2006', 'sandor van es', 'collé racing', 'h', '203'], ['2007', 'donald molenaar', 'collé racing', 'h', '206'], ['2008', 'donald molenaar', 'collé racing', 'h', '230'], ['2009', 'donald molenaar', 'collé racing', 'h', '210']] |
list of los angeles lakers broadcasters | https://en.wikipedia.org/wiki/List_of_Los_Angeles_Lakers_broadcasters | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16701360-6.html.csv | majority | all of the channels have stu lantz as the color commentator for the los angeles lakers . | {'scope': 'all', 'col': '3', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'stu lantz', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'color commentator ( s )', 'stu lantz'], 'result': True, 'ind': 0, 'tointer': 'for the color commentator ( s ) records of all rows , all of them fuzzily match to stu lantz .', 'tostr': 'all_eq { all_rows ; color commentator ( s ) ; stu lantz } = true'} | all_eq { all_rows ; color commentator ( s ) ; stu lantz } = true | for the color commentator ( s ) records of all rows , all of them fuzzily match to stu lantz . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'color commentator (s)_3': 3, 'stu lantz_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'color commentator (s)_3': 'color commentator ( s )', 'stu lantz_4': 'stu lantz'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'color commentator (s)_3': [0], 'stu lantz_4': [0]} | ['channel', 'play - by - play', 'color commentator ( s )', 'studio host', 'studio analysts'] | [['kcal - tv', 'chick hearn', 'stu lantz', 'alan massengale', 'james worthy'], ['fox sports net west', 'chick hearn', 'stu lantz', 'paul sunderland', 'jack haley'], ['kcal - tv', 'paul sunderland', 'stu lantz', 'alan massengale', 'james worthy'], ['fox sports net west', 'paul sunderland', 'stu lantz', 'bill macdonald', 'jack haley or reggie theus'], ['fsn west', 'paul sunderland', 'stu lantz', 'bill macdonald', 'jack haley'], ['kcal - tv', 'joel meyers', 'stu lantz', 'alan massengale', 'james worthy'], ['fsn west', 'joel meyers', 'stu lantz', 'bill macdonald', 'jack haley'], ['fsn west', 'joel meyers', 'stu lantz', 'bill macdonald', 'jack haley or paul westphal'], ['kcal - tv', 'joel meyers', 'stu lantz', 'jim hill', 'james worthy'], ['fox sports west', 'joel meyers', 'stu lantz', 'bill macdonald', 'norm nixon or paul westphal'], ['fox sports west', 'joel meyers', 'stu lantz', 'bill macdonald', 'norm nixon']] |
merlin ( series 2 ) | https://en.wikipedia.org/wiki/Merlin_%28series_2%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-29063233-1.html.csv | ordinal | the curse of cornelius sigan was the first episode to air for merlin ( series 2 ) . | {'row': '1', 'col': '2', 'order': '1', 'col_other': '3', 'max_or_min': 'min_to_max', 'value_mentioned': 'yes', 'scope': 'all', 'subset': None} | {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'nth_min', 'args': ['all_rows', 'no for series', '1'], 'result': '1', 'ind': 0, 'tostr': 'nth_min { all_rows ; no for series ; 1 }', 'tointer': 'the 1st minimum no for series record of all rows is 1 .'}, '1'], 'result': True, 'ind': 1, 'tostr': 'eq { nth_min { all_rows ; no for series ; 1 } ; 1 }', 'tointer': 'the 1st minimum no for series record of all rows is 1 .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'no for series', '1'], 'result': None, 'ind': 2, 'tostr': 'nth_argmin { all_rows ; no for series ; 1 }'}, 'title'], 'result': 'the curse of cornelius sigan', 'ind': 3, 'tostr': 'hop { nth_argmin { all_rows ; no for series ; 1 } ; title }'}, 'the curse of cornelius sigan'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { nth_argmin { all_rows ; no for series ; 1 } ; title } ; the curse of cornelius sigan }', 'tointer': 'the title record of the row with 1st minimum no for series record is the curse of cornelius sigan .'}], 'result': True, 'ind': 5, 'tostr': 'and { eq { nth_min { all_rows ; no for series ; 1 } ; 1 } ; eq { hop { nth_argmin { all_rows ; no for series ; 1 } ; title } ; the curse of cornelius sigan } } = true', 'tointer': 'the 1st minimum no for series record of all rows is 1 . the title record of the row with 1st minimum no for series record is the curse of cornelius sigan .'} | and { eq { nth_min { all_rows ; no for series ; 1 } ; 1 } ; eq { hop { nth_argmin { all_rows ; no for series ; 1 } ; title } ; the curse of cornelius sigan } } = true | the 1st minimum no for series record of all rows is 1 . the title record of the row with 1st minimum no for series record is the curse of cornelius sigan . | 6 | 6 | {'and_5': 5, 'result_6': 6, 'eq_1': 1, 'nth_min_0': 0, 'all_rows_7': 7, 'no for series_8': 8, '1_9': 9, '1_10': 10, 'str_eq_4': 4, 'str_hop_3': 3, 'nth_argmin_2': 2, 'all_rows_11': 11, 'no for series_12': 12, '1_13': 13, 'title_14': 14, 'the curse of cornelius sigan_15': 15} | {'and_5': 'and', 'result_6': 'true', 'eq_1': 'eq', 'nth_min_0': 'nth_min', 'all_rows_7': 'all_rows', 'no for series_8': 'no for series', '1_9': '1', '1_10': '1', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'nth_argmin_2': 'nth_argmin', 'all_rows_11': 'all_rows', 'no for series_12': 'no for series', '1_13': '1', 'title_14': 'title', 'the curse of cornelius sigan_15': 'the curse of cornelius sigan'} | {'and_5': [6], 'result_6': [], 'eq_1': [5], 'nth_min_0': [1], 'all_rows_7': [0], 'no for series_8': [0], '1_9': [0], '1_10': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'nth_argmin_2': [3], 'all_rows_11': [2], 'no for series_12': [2], '1_13': [2], 'title_14': [3], 'the curse of cornelius sigan_15': [4]} | ['no overall', 'no for series', 'title', 'directed by', 'written by', 'original air date', 'uk viewers ( million )'] | [['14', '1', 'the curse of cornelius sigan', 'david moore', 'julian jones', '19 september 2009', '5.77'], ['15', '2', 'the once and future queen', 'jeremy webb', 'howard overman', '26 september 2009', '5.94'], ['16', '3', 'the nightmare begins', 'jeremy webb', 'ben vanstone', '3 october 2009', '6.09'], ['17', '4', 'lancelot and guinevere', 'david moore', 'howard overman', '10 october 2009', '5.69'], ['18', '5', 'beauty and the beast ( part 1 )', 'david moore', 'jake michie', '24 october 2009', '5.53'], ['19', '6', 'beauty and the beast ( part 2 )', 'metin huseyin', 'ben vanstone', '31 october 2009', '6.14'], ['20', '7', 'the witchfinder', 'jeremy webb', 'jake michie', '7 november 2009', '5.62'], ['21', '8', 'the sins of the father', 'metin huseyin', 'howard overman', '14 november 2009', '6.16'], ['22', '9', 'the lady of the lake', 'metin huseyin', 'julian jones', '21 november 2009', '6.30'], ['23', '10', 'sweet dreams', 'alice troughton', 'lucy watkins', '28 november 2009', '6.02'], ['24', '11', "the witch 's quickening", 'alice troughton', 'jake michie', '5 december 2009', '6.01'], ['25', '12', 'the fires of idirsholas', 'jeremy webb', 'julian jones', '12 december 2009', '6.01']] |
matt baker ( television presenter ) | https://en.wikipedia.org/wiki/Matt_Baker_%28television_presenter%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1014319-1.html.csv | aggregation | the average score that matt baker received on his dances from horwood was 8 . | {'scope': 'all', 'col': '3', 'type': 'average', 'result': '8', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'horwood'], 'result': '8', 'ind': 0, 'tostr': 'avg { all_rows ; horwood }'}, '8'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; horwood } ; 8 } = true', 'tointer': 'the average of the horwood record of all rows is 8 .'} | round_eq { avg { all_rows ; horwood } ; 8 } = true | the average of the horwood record of all rows is 8 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'horwood_4': 4, '8_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'horwood_4': 'horwood', '8_5': '8'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'horwood_4': [0], '8_5': [1]} | ['week', 'dance / song', 'horwood', 'goodman', 'dixon', 'tonioli', 'total', 'result'] | [['1', "cha - cha - cha / ai n't no mountain high enough", '7', '8', '8', '8', '31', 'n / a'], ['2', 'foxtrot / she said', '7', '8', '8', '8', '31', 'safe'], ['3', 'quickstep / dreaming of you', '8', '7', '8', '8', '31', 'safe'], ['4', 'charleston / forty - second street', '9', '9', '9', '8', '35', 'safe'], ['5', 'argentine tango / bat out of hell', '8', '8', '9', '9', '34', 'safe'], ['6', 'viennese waltz / where the wild roses grow', '8', '9', '9', '9', '35', 'safe'], ['7', 'rumba / too lost in you', '8', '9', '9', '9', '35', 'safe'], ['8', 'samba / young hearts run free', '9', '9', '10', '10', '38', 'safe'], ['10', 'jive / soul bossa nova', '8', '9', '9', '9', '35', 'safe'], ['11', 'salsa / spinning around', '7', '7', '7', '7', '28', 'safe'], ['11', 'swing / in the mood', 'n / a', 'n / a', 'n / a', 'n / a', '2nd / 4 points', 'safe'], ['11', 'tango / hung up', '9', '10', '10', '9', '38', 'safe'], ['12', 'samba / young hearts run free', '9', '9', '10', '10', '38', 'second place'], ['12', 'showdance / i like the way ( you move )', '7', '9', '9', '9', '34', 'second place'], ['12', "paso doble / do n't let me be misunderstood", '9', '8', '9', '9', '35', 'second place']] |
heikki kovalainen | https://en.wikipedia.org/wiki/Heikki_Kovalainen | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1527343-1.html.csv | superlative | heikki kovalainen had the most points at the british formula three in 2002 . | {'scope': 'subset', 'col_superlative': '9', 'row_superlative': '4', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '2', 'subset': {'col': '1', 'criterion': 'equal', 'value': '2002'}} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'season', '2002'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; season ; 2002 }', 'tointer': 'select the rows whose season record is equal to 2002 .'}, 'points'], 'result': None, 'ind': 1, 'tostr': 'argmax { filter_eq { all_rows ; season ; 2002 } ; points }'}, 'series'], 'result': 'british formula three', 'ind': 2, 'tostr': 'hop { argmax { filter_eq { all_rows ; season ; 2002 } ; points } ; series }'}, 'british formula three'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { argmax { filter_eq { all_rows ; season ; 2002 } ; points } ; series } ; british formula three } = true', 'tointer': 'select the rows whose season record is equal to 2002 . select the row whose points record of these rows is maximum . the series record of this row is british formula three .'} | eq { hop { argmax { filter_eq { all_rows ; season ; 2002 } ; points } ; series } ; british formula three } = true | select the rows whose season record is equal to 2002 . select the row whose points record of these rows is maximum . the series record of this row is british formula three . | 4 | 4 | {'str_eq_3': 3, 'result_4': 4, 'str_hop_2': 2, 'argmax_1': 1, 'filter_eq_0': 0, 'all_rows_5': 5, 'season_6': 6, '2002_7': 7, 'points_8': 8, 'series_9': 9, 'british formula three_10': 10} | {'str_eq_3': 'str_eq', 'result_4': 'true', 'str_hop_2': 'str_hop', 'argmax_1': 'argmax', 'filter_eq_0': 'filter_eq', 'all_rows_5': 'all_rows', 'season_6': 'season', '2002_7': '2002', 'points_8': 'points', 'series_9': 'series', 'british formula three_10': 'british formula three'} | {'str_eq_3': [4], 'result_4': [], 'str_hop_2': [3], 'argmax_1': [2], 'filter_eq_0': [1], 'all_rows_5': [0], 'season_6': [0], '2002_7': [0], 'points_8': [1], 'series_9': [2], 'british formula three_10': [3]} | ['season', 'series', 'team', 'races', 'wins', 'poles', 'f / laps', 'podiums', 'points', 'position'] | [['2001', 'formula renault 2000 uk', 'fortec motorsport', '13', '2', '2', '3', '5', '243', '4th'], ['2001', 'macau grand prix', 'fortec motorsport', '1', '0', '0', '0', '0', 'n / a', '8th'], ['2001', 'korea super prix', 'fortec motorsport', '1', '0', '0', '0', '0', 'n / a', '25th'], ['2002', 'british formula three', 'fortec motorsport', '26', '5', '2', '3', '12', '257', '3rd'], ['2002', 'macau grand prix', 'fortec motorsport', '1', '0', '0', '0', '1', 'n / a', '2nd'], ['2002', 'korea super prix', 'fortec motorsport', '1', '0', '0', '0', '0', 'n / a', '14th'], ['2002', 'masters of formula 3', 'fortec motorsport', '1', '0', '0', '0', '0', 'n / a', '4th'], ['2003', 'world series by nissan', 'gabord competiciã cubicn', '18', '1', '3', '1', '4', '134', '2nd'], ['2004', 'world series by nissan', 'pons racing', '18', '6', '10', '8', '11', '176', '1st'], ['2005', 'gp2 series', 'arden international', '23', '5', '2', '1', '12', '105', '2nd'], ['2006', 'formula one', 'mild seven renault f1 team', 'test driver', 'test driver', 'test driver', 'test driver', 'test driver', 'test driver', 'test driver'], ['2007', 'formula one', 'ing renault f1 team', '17', '0', '0', '0', '1', '30', '7th'], ['2008', 'formula one', 'vodafone mclaren mercedes', '18', '1', '1', '2', '3', '53', '7th'], ['2009', 'formula one', 'vodafone mclaren mercedes', '17', '0', '0', '0', '0', '22', '12th'], ['2010', 'formula one', 'lotus racing', '19', '0', '0', '0', '0', '0', '20th'], ['2011', 'formula one', 'team lotus', '19', '0', '0', '0', '0', '0', '22nd'], ['2012', 'formula one', 'caterham f1 team', '20', '0', '0', '0', '0', '0', '22nd'], ['2013', 'formula one', 'caterham f1 team', 'test driver', 'test driver', 'test driver', 'test driver', 'test driver', 'test driver', 'test driver']] |
1952 vfl season | https://en.wikipedia.org/wiki/1952_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10750694-2.html.csv | ordinal | in the 1952 vfl season , when the away team has under 10 points , the 2nd highest crowd was when the venue was victoria park . | {'scope': 'subset', 'row': '2', 'col': '6', 'order': '2', 'col_other': '5', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'subset': {'col': '4', 'criterion': 'less_than', 'value': '10'}} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'away team score', '10'], 'result': None, 'ind': 0, 'tostr': 'filter_less { all_rows ; away team score ; 10 }', 'tointer': 'select the rows whose away team score record is less than 10 .'}, 'crowd', '2'], 'result': None, 'ind': 1, 'tostr': 'nth_argmax { filter_less { all_rows ; away team score ; 10 } ; crowd ; 2 }'}, 'venue'], 'result': 'victoria park', 'ind': 2, 'tostr': 'hop { nth_argmax { filter_less { all_rows ; away team score ; 10 } ; crowd ; 2 } ; venue }'}, 'victoria park'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { nth_argmax { filter_less { all_rows ; away team score ; 10 } ; crowd ; 2 } ; venue } ; victoria park } = true', 'tointer': 'select the rows whose away team score record is less than 10 . select the row whose crowd record of these rows is 2nd maximum . the venue record of this row is victoria park .'} | eq { hop { nth_argmax { filter_less { all_rows ; away team score ; 10 } ; crowd ; 2 } ; venue } ; victoria park } = true | select the rows whose away team score record is less than 10 . select the row whose crowd record of these rows is 2nd maximum . the venue record of this row is victoria park . | 4 | 4 | {'str_eq_3': 3, 'result_4': 4, 'str_hop_2': 2, 'nth_argmax_1': 1, 'filter_less_0': 0, 'all_rows_5': 5, 'away team score_6': 6, '10_7': 7, 'crowd_8': 8, '2_9': 9, 'venue_10': 10, 'victoria park_11': 11} | {'str_eq_3': 'str_eq', 'result_4': 'true', 'str_hop_2': 'str_hop', 'nth_argmax_1': 'nth_argmax', 'filter_less_0': 'filter_less', 'all_rows_5': 'all_rows', 'away team score_6': 'away team score', '10_7': '10', 'crowd_8': 'crowd', '2_9': '2', 'venue_10': 'venue', 'victoria park_11': 'victoria park'} | {'str_eq_3': [4], 'result_4': [], 'str_hop_2': [3], 'nth_argmax_1': [2], 'filter_less_0': [1], 'all_rows_5': [0], 'away team score_6': [0], '10_7': [0], 'crowd_8': [1], '2_9': [1], 'venue_10': [2], 'victoria park_11': [3]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['essendon', '14.12 ( 96 )', 'north melbourne', '13.11 ( 89 )', 'windy hill', '21000', '26 april 1952'], ['collingwood', '13.17 ( 95 )', 'fitzroy', '8.14 ( 62 )', 'victoria park', '26000', '26 april 1952'], ['carlton', '12.12 ( 84 )', 'south melbourne', '13.11 ( 89 )', 'princes park', '31500', '26 april 1952'], ['st kilda', '13.11 ( 89 )', 'melbourne', '12.19 ( 91 )', 'junction oval', '19000', '26 april 1952'], ['richmond', '12.10 ( 82 )', 'hawthorn', '8.14 ( 62 )', 'punt road oval', '13000', '26 april 1952'], ['geelong', '10.4 ( 64 )', 'footscray', '7.15 ( 57 )', 'kardinia park', '30000', '26 april 1952']] |
communication with extraterrestrial intelligence | https://en.wikipedia.org/wiki/Communication_with_extraterrestrial_intelligence | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1446835-2.html.csv | unique | the cosmic call designated " hd 245409 " is the only communication with extraterrestrial intelligence that was sent to the orion constellation . | {'scope': 'all', 'row': '6', 'col': '2', 'col_other': '1', 'criterion': 'equal', 'value': 'orion', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'constellation', 'orion'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose constellation record fuzzily matches to orion .', 'tostr': 'filter_eq { all_rows ; constellation ; orion }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; constellation ; orion } }', 'tointer': 'select the rows whose constellation record fuzzily matches to orion . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'constellation', 'orion'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose constellation record fuzzily matches to orion .', 'tostr': 'filter_eq { all_rows ; constellation ; orion }'}, 'designation hd'], 'result': 'hd 245409', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; constellation ; orion } ; designation hd }'}, 'hd 245409'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; constellation ; orion } ; designation hd } ; hd 245409 }', 'tointer': 'the designation hd record of this unqiue row is hd 245409 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; constellation ; orion } } ; eq { hop { filter_eq { all_rows ; constellation ; orion } ; designation hd } ; hd 245409 } } = true', 'tointer': 'select the rows whose constellation record fuzzily matches to orion . there is only one such row in the table . the designation hd record of this unqiue row is hd 245409 .'} | and { only { filter_eq { all_rows ; constellation ; orion } } ; eq { hop { filter_eq { all_rows ; constellation ; orion } ; designation hd } ; hd 245409 } } = true | select the rows whose constellation record fuzzily matches to orion . there is only one such row in the table . the designation hd record of this unqiue row is hd 245409 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'constellation_7': 7, 'orion_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'designation hd_9': 9, 'hd 245409_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'constellation_7': 'constellation', 'orion_8': 'orion', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'designation hd_9': 'designation hd', 'hd 245409_10': 'hd 245409'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'constellation_7': [0], 'orion_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'designation hd_9': [2], 'hd 245409_10': [3]} | ['designation hd', 'constellation', 'date sent', 'arrival date', 'message'] | [['hd 186408', 'cygnus', 'may 24 , 1999', 'november 2069', 'cosmic call 1'], ['hd 190406', 'sagitta', 'june 30 , 1999', 'february 2057', 'cosmic call 1'], ['hd 178428', 'sagitta', 'june 30 , 1999', 'october 2067', 'cosmic call 1'], ['hd 190360', 'cygnus', 'july 1 , 1999', 'april 2051', 'cosmic call 1'], ['hip 4872', 'cassiopeia', 'july 6 , 2003', 'april 2036', 'cosmic call 2'], ['hd 245409', 'orion', 'july 6 , 2003', 'august 2040', 'cosmic call 2'], ['hd 75732', 'cancer', 'july 6 , 2003', 'may 2044', 'cosmic call 2'], ['hd 10307', 'andromeda', 'july 6 , 2003', 'september 2044', 'cosmic call 2'], ['hd 95128', 'ursa major', 'july 6 , 2003', 'may 2049', 'cosmic call 2']] |
irrigation in bolivia | https://en.wikipedia.org/wiki/Irrigation_in_Bolivia | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17118006-1.html.csv | unique | of the departments , only la paz has exactly 35994 units of irrigation . | {'scope': 'all', 'row': '3', 'col': '6', 'col_other': '1', 'criterion': 'equal', 'value': '35994', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'total', '35994'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose total record is equal to 35994 .', 'tostr': 'filter_eq { all_rows ; total ; 35994 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; total ; 35994 } }', 'tointer': 'select the rows whose total record is equal to 35994 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'total', '35994'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose total record is equal to 35994 .', 'tostr': 'filter_eq { all_rows ; total ; 35994 }'}, 'department'], 'result': 'la paz', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; total ; 35994 } ; department }'}, 'la paz'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; total ; 35994 } ; department } ; la paz }', 'tointer': 'the department record of this unqiue row is la paz .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; total ; 35994 } } ; eq { hop { filter_eq { all_rows ; total ; 35994 } ; department } ; la paz } } = true', 'tointer': 'select the rows whose total record is equal to 35994 . there is only one such row in the table . the department record of this unqiue row is la paz .'} | and { only { filter_eq { all_rows ; total ; 35994 } } ; eq { hop { filter_eq { all_rows ; total ; 35994 } ; department } ; la paz } } = true | select the rows whose total record is equal to 35994 . there is only one such row in the table . the department record of this unqiue row is la paz . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'total_7': 7, '35994_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'department_9': 9, 'la paz_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'total_7': 'total', '35994_8': '35994', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'department_9': 'department', 'la paz_10': 'la paz'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'total_7': [0], '35994_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'department_9': [2], 'la paz_10': [3]} | ['department', 'micro ( 10ha )', 'small ( 100ha )', 'medium ( 500ha )', 'big ( > 500ha )', 'total'] | [['chuquisaca', '1653', '11370', '4261', '3884', '21168'], ['cochabamba', '1938', '22225', '27403', '35968', '81925'], ['la paz', '1703', '21047', '6052', '7192', '35994'], ['oruro', '940', '3638', '440', '9021', '14039'], ['potosã\xad', '3240', '10146', '2254', '600', '16240'], ['santa cruz', '269', '5456', '8434', '1080', '15239'], ['tarija', '785', '12755', '17101', '5710', '36351'], ['total', '10528', '86638', '65944', '63454', '226564']] |
bolt thrust | https://en.wikipedia.org/wiki/Bolt_thrust | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-26967904-1.html.csv | count | two different gun chambering types have the same p1 diameter of 10.77 mm . | {'scope': 'all', 'criterion': 'equal', 'value': '10.77', 'result': '2', 'col': '2', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'p1 diameter ( mm )', '10.77'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose p1 diameter ( mm ) record is equal to 10.77 .', 'tostr': 'filter_eq { all_rows ; p1 diameter ( mm ) ; 10.77 }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; p1 diameter ( mm ) ; 10.77 } }', 'tointer': 'select the rows whose p1 diameter ( mm ) record is equal to 10.77 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; p1 diameter ( mm ) ; 10.77 } } ; 2 } = true', 'tointer': 'select the rows whose p1 diameter ( mm ) record is equal to 10.77 . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; p1 diameter ( mm ) ; 10.77 } } ; 2 } = true | select the rows whose p1 diameter ( mm ) record is equal to 10.77 . the number of such rows is 2 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_eq_0': 0, 'all_rows_4': 4, 'p1 diameter (mm)_5': 5, '10.77_6': 6, '2_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'p1 diameter (mm)_5': 'p1 diameter ( mm )', '10.77_6': '10.77', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'p1 diameter (mm)_5': [0], '10.77_6': [0], '2_7': [2]} | ['chambering', 'p1 diameter ( mm )', 'a external ( cm 2 )', 'p max ( bar )', 'f bolt ( kgf )', 'f bolt'] | [['.22 long rifle', '5.74', '0.2587', '1650', '435', 'n ( lbf )'], ['9x19 mm parabellum', '9.93', '0.7744', '2350', '1820', 'n ( lbf )'], ['.357 sig', '10.77', '0.9110', '3050', '2779', 'n ( lbf )'], ['.380 acp', '9.70', '0.7390', '1500', '1130', 'n ( lbf )'], ['.40 s & w', '10.77', '0.9110', '2250', '2050', 'n ( lbf )'], ['10 mm auto', '10.81', '0.9178', '2300', '2111', 'n ( lbf )'], ['.45 acp', '12.09', '1.1671', '1300', '1517', 'n ( lbf )'], ['.454 casull', '12.13', '1.1556', '3900', '4507', 'n ( lbf )']] |
nuevo laredo | https://en.wikipedia.org/wiki/Nuevo_Laredo | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1436627-6.html.csv | aggregation | the average of nuevo laredo radio station frequencies with webcasts is 958 . | {'scope': 'subset', 'col': '1', 'type': 'average', 'result': '958', 'subset': {'col': '6', 'criterion': 'not_equal', 'value': '-'}} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': [{'func': 'filter_not_eq', 'args': ['all_rows', 'webcast', '-'], 'result': None, 'ind': 0, 'tostr': 'filter_not_eq { all_rows ; webcast ; - }', 'tointer': 'select the rows whose webcast record is not equal to - .'}, 'frequency'], 'result': '958', 'ind': 1, 'tostr': 'avg { filter_not_eq { all_rows ; webcast ; - } ; frequency }'}, '958'], 'result': True, 'ind': 2, 'tostr': 'round_eq { avg { filter_not_eq { all_rows ; webcast ; - } ; frequency } ; 958 } = true', 'tointer': 'select the rows whose webcast record is not equal to - . the average of the frequency record of these rows is 958 .'} | round_eq { avg { filter_not_eq { all_rows ; webcast ; - } ; frequency } ; 958 } = true | select the rows whose webcast record is not equal to - . the average of the frequency record of these rows is 958 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'avg_1': 1, 'filter_not_eq_0': 0, 'all_rows_4': 4, 'webcast_5': 5, '-_6': 6, 'frequency_7': 7, '958_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'avg_1': 'avg', 'filter_not_eq_0': 'filter_not_eq', 'all_rows_4': 'all_rows', 'webcast_5': 'webcast', '-_6': '-', 'frequency_7': 'frequency', '958_8': '958'} | {'eq_2': [3], 'result_3': [], 'avg_1': [2], 'filter_not_eq_0': [1], 'all_rows_4': [0], 'webcast_5': [0], '-_6': [0], 'frequency_7': [1], '958_8': [2]} | ['frequency', 'callsign', 'brand', 'city of license', 'website', 'webcast'] | [['680', 'kkyx', 'country legends 680', 'san antonio', 'kkyxcom', 'listen live'], ['720', 'ksah', 'norteño 720', 'san antonio', '-', '-'], ['740', 'ktrh', 'newsradio 740 ktrh', 'houston', 'ktrhcom', 'listen live'], ['760', 'ktkr', 'ticket 760 am', 'san antonio', 'ticket760.com', 'listen live'], ['990', 'xet', 'la t grande', 'monterrey', '-', 'listen live'], ['1030', 'kcta', 'kcta 1030 am', 'corpus christi', 'kctaradiocom', 'listen live'], ['1050', 'xeg', 'ranchera de monterrey', 'monterrey', 'rancherademonterreycom', 'listen live'], ['1140', 'xemr', 'mr deportes', 'monterrey', '-', '-'], ['1200', 'woai', 'news radio 1200', 'san antonio', 'radiowoaicom', 'listen live'], ['1210', 'kubr', 'radio cristiana', 'san juan', '-', 'listen live'], ['1530', 'kgbt', 'la tremenda 1530', 'harlingen', 'latremenda1530.com', '-']] |
list of number - one singles of 1981 ( canada ) | https://en.wikipedia.org/wiki/List_of_number-one_singles_of_1981_%28Canada%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15476957-1.html.csv | comparative | the song ' endless love ' spent more weeks on top of the 1981 canadian chart than ' morning train ' . | {'row_1': '13', 'row_2': '7', 'col': '3', 'col_other': '4', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'song', 'endless love'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose song record fuzzily matches to endless love .', 'tostr': 'filter_eq { all_rows ; song ; endless love }'}, 'weeks on top'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; song ; endless love } ; weeks on top }', 'tointer': 'select the rows whose song record fuzzily matches to endless love . take the weeks on top record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'song', 'morning train'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose song record fuzzily matches to morning train .', 'tostr': 'filter_eq { all_rows ; song ; morning train }'}, 'weeks on top'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; song ; morning train } ; weeks on top }', 'tointer': 'select the rows whose song record fuzzily matches to morning train . take the weeks on top record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; song ; endless love } ; weeks on top } ; hop { filter_eq { all_rows ; song ; morning train } ; weeks on top } } = true', 'tointer': 'select the rows whose song record fuzzily matches to endless love . take the weeks on top record of this row . select the rows whose song record fuzzily matches to morning train . take the weeks on top record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; song ; endless love } ; weeks on top } ; hop { filter_eq { all_rows ; song ; morning train } ; weeks on top } } = true | select the rows whose song record fuzzily matches to endless love . take the weeks on top record of this row . select the rows whose song record fuzzily matches to morning train . take the weeks on top 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, 'song_7': 7, 'endless love_8': 8, 'weeks on top_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'song_11': 11, 'morning train_12': 12, 'weeks on top_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', 'song_7': 'song', 'endless love_8': 'endless love', 'weeks on top_9': 'weeks on top', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'song_11': 'song', 'morning train_12': 'morning train', 'weeks on top_13': 'weeks on top'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'song_7': [0], 'endless love_8': [0], 'weeks on top_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'song_11': [1], 'morning train_12': [1], 'weeks on top_13': [3]} | ['volume : issue', 'issue date ( s )', 'weeks on top', 'song', 'artist'] | [['34:6 - 8', '20 december 1980 - 31 january 1981', '7', '( just like ) starting over', 'john lennon'], ['34:9 - 12', '7 - 28 february', '4', 'the tide is high', 'blondie'], ['34:13', '7 march', '1', 'the best of times', 'styx'], ['34:14 - 15', '14 - 21 march', '2', 'woman', 'john lennon'], ['34:16 - 18', '28 march - 11 april', '3', 'celebration', 'kool & the gang'], ['34:19 - 20', '18 - 25 april', '2', '9 to 5', 'dolly parton'], ['34:21 - 22', '2 - 9 may', '2', 'morning train', 'sheena easton'], ['34:23 - 25', '16 - 30 may', '3', 'angel of the morning', 'juice newton'], ['34:26 - 35:4', '6 june - 22 august', '12', 'stars on 45 medley', 'stars on 45'], ['35:5 §', '29 august', '1', 'gemini dream', 'moody blues'], ['35:6', '5 september', '1', 'sausalito summernight', 'diesel'], ['35:7 - 8', '12 - 19 september', '2', 'urgent', 'foreigner'], ['35:9 - 14', '26 september - 31 october', '6', 'endless love', 'diana ross and lionel richie'], ['35:15', '7 november', '1', 'every little thing she does is magic', 'the police'], ['35:16 - 20', '14 november - 12 december', '5', 'the friends of mr cairo', 'jon & vangelis'], ['35:21 - 24', '19 december - 23 january 1982', '6', 'physical', 'olivia newton - john']] |
1957 vfl season | https://en.wikipedia.org/wiki/1957_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10774891-12.html.csv | majority | all of the matches of the 1957 vfl season took place on 6 july 1957 . | {'scope': 'all', 'col': '7', 'most_or_all': 'all', 'criterion': 'equal', 'value': '6 july 1957', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'date', '6 july 1957'], 'result': True, 'ind': 0, 'tointer': 'for the date records of all rows , all of them fuzzily match to 6 july 1957 .', 'tostr': 'all_eq { all_rows ; date ; 6 july 1957 } = true'} | all_eq { all_rows ; date ; 6 july 1957 } = true | for the date records of all rows , all of them fuzzily match to 6 july 1957 . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'date_3': 3, '6 July 1957_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'date_3': 'date', '6 July 1957_4': '6 july 1957'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'date_3': [0], '6 July 1957_4': [0]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['north melbourne', '17.15 ( 117 )', 'richmond', '10.13 ( 73 )', 'arden street oval', '21000', '6 july 1957'], ['footscray', '9.11 ( 65 )', 'geelong', '9.10 ( 64 )', 'western oval', '23578', '6 july 1957'], ['south melbourne', '11.15 ( 81 )', 'st kilda', '9.17 ( 71 )', 'lake oval', '18000', '6 july 1957'], ['melbourne', '24.14 ( 158 )', 'fitzroy', '10.14 ( 74 )', 'mcg', '21370', '6 july 1957'], ['essendon', '12.16 ( 88 )', 'collingwood', '10.13 ( 73 )', 'windy hill', '26500', '6 july 1957'], ['hawthorn', '7.10 ( 52 )', 'carlton', '8.13 ( 61 )', 'glenferrie oval', '26000', '6 july 1957']] |
minnesota golden gophers football under fritz crisler | https://en.wikipedia.org/wiki/Minnesota_Golden_Gophers_football_under_Fritz_Crisler | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14725662-2.html.csv | count | two of these golden gophers games had an attendance of 15000 people . | {'scope': 'all', 'criterion': 'equal', 'value': '15000', 'result': '2', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'attendance', '15000'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose attendance record is equal to 15000 .', 'tostr': 'filter_eq { all_rows ; attendance ; 15000 }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; attendance ; 15000 } }', 'tointer': 'select the rows whose attendance record is equal to 15000 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; attendance ; 15000 } } ; 2 } = true', 'tointer': 'select the rows whose attendance record is equal to 15000 . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; attendance ; 15000 } } ; 2 } = true | select the rows whose attendance record is equal to 15000 . the number of such rows is 2 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_eq_0': 0, 'all_rows_4': 4, 'attendance_5': 5, '15000_6': 6, '2_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'attendance_5': 'attendance', '15000_6': '15000', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'attendance_5': [0], '15000_6': [0], '2_7': [2]} | ['date', 'opponent', 'site', 'result', 'attendance'] | [['09 / 26 / 1931', 'north dakota state', 'memorial stadium minneapolis , mn', 'w13 - 7', '15000'], ['09 / 26 / 1931', 'ripon', 'memorial stadium minneapolis , mn', 'w30 - 0', '15000'], ['10 / 03 / 1931', 'oklahoma a & m', 'memorial stadium minneapolis , mn', 'w20 - 0', '20000'], ['10 / 10 / 1931', 'stanford', 'stanford stadium palo alto , ca', 'l13 - 7', '54787'], ['10 / 24 / 1931', 'iowa', 'memorial stadium minneapolis , mn', 'w34 - 0', '25000'], ['10 / 31 / 1931', 'wisconsin', 'memorial stadium minneapolis , mn', 'w14 - 0', '52000'], ['11 / 07 / 1931', 'northwestern', 'dyche stadium evanston , il', 'l14 - 32', '42000'], ['11 / 14 / 1931', 'cornell ( ia )', 'memorial stadium minneapolis , mn', 'w47 - 7', '10000'], ['11 / 21 / 1931', 'michigan', 'michigan stadium ann arbor , mi', 'l0 - 6', '37251'], ['11 / 28 / 1931', 'ohio state', 'memorial stadium minneapolis , mn', 'w19 - 7', '25000']] |
big day out lineups by year | https://en.wikipedia.org/wiki/Big_Day_Out_lineups_by_year | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12230393-5.html.csv | count | 13 out of 15 performers performed at the sydney big day out music festival . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'yes', 'result': '13', 'col': '1', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'sydney', 'yes'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose sydney record fuzzily matches to yes .', 'tostr': 'filter_eq { all_rows ; sydney ; yes }'}], 'result': '13', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; sydney ; yes } }', 'tointer': 'select the rows whose sydney record fuzzily matches to yes . the number of such rows is 13 .'}, '13'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; sydney ; yes } } ; 13 } = true', 'tointer': 'select the rows whose sydney record fuzzily matches to yes . the number of such rows is 13 .'} | eq { count { filter_eq { all_rows ; sydney ; yes } } ; 13 } = true | select the rows whose sydney record fuzzily matches to yes . the number of such rows is 13 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'sydney_5': 5, 'yes_6': 6, '13_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'sydney_5': 'sydney', 'yes_6': 'yes', '13_7': '13'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'sydney_5': [0], 'yes_6': [0], '13_7': [2]} | ['sydney', 'melbourne', 'perth', 'adelaide', 'gold coast', 'auckland'] | [['yes', 'yes', 'yes', 'yes', 'yes', 'yes'], ['yes', 'yes', 'yes', 'yes', 'yes', 'no'], ['yes', 'yes', 'no', 'no', 'yes', 'yes'], ['yes', 'yes', 'no', 'no', 'yes', 'no'], ['yes', 'yes', 'yes', 'yes', 'no', 'yes'], ['yes', 'yes', 'yes', 'no', 'yes', 'no'], ['yes', 'yes', 'no', 'yes', 'no', 'no'], ['yes', 'yes', 'no', 'yes', 'yes', 'no'], ['yes', 'no', 'yes', 'yes', 'yes', 'no'], ['yes', 'no', 'no', 'no', 'yes', 'no'], ['yes', 'no', 'no', 'yes', 'no', 'no'], ['yes', 'yes', 'no', 'no', 'no', 'no'], ['no', 'yes', 'yes', 'no', 'noound : ccc , | no', 's'], ['yes', 'no', 'no', 'no', 'no', 'no'], ['no', 'no', 'no', 'no', 'no', 'yes']] |
list of t.u.f.f. puppy episodes | https://en.wikipedia.org/wiki/List_of_T.U.F.F._Puppy_episodes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-28787871-3.html.csv | superlative | the earliest original air date was for the episode titled a doomed christmas . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '3', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmin', 'args': ['all_rows', 'original air date'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; original air date }'}, 'title'], 'result': 'a doomed christmas', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; original air date } ; title }'}, 'a doomed christmas'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmin { all_rows ; original air date } ; title } ; a doomed christmas } = true', 'tointer': 'select the row whose original air date record of all rows is minimum . the title record of this row is a doomed christmas .'} | eq { hop { argmin { all_rows ; original air date } ; title } ; a doomed christmas } = true | select the row whose original air date record of all rows is minimum . the title record of this row is a doomed christmas . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'original air date_5': 5, 'title_6': 6, 'a doomed christmas_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'original air date_5': 'original air date', 'title_6': 'title', 'a doomed christmas_7': 'a doomed christmas'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'original air date_5': [0], 'title_6': [1], 'a doomed christmas_7': [2]} | ['no in series', 'no in season', 'title', 'original air date', 'production code', 'us viewers ( millions )'] | [['21', '1', 'a doomed christmas', 'december 10 , 2011', '121', 'n / a'], ['22', '2', "big dog on campus / dog 's best friend", 'january 16 , 2012', '122', 'n / a'], ['23', '3', 'monkey business / diary of a mad cat', 'april 21 , 2012', '125', 'n / a'], ['24', '4', 'dudley do - wrong / puppy unplugged', 'may 6 , 2012', '123', 'n / a'], ['25', '5', 'freaky spy day / dog tired', 'may 13 , 2012', '202', 'n / a'], ['26', '6', 'top dog / quack in the box', 'may 20 , 2012', '124', 'n / a'], ['27', '7', 'lie like a dog / cold fish', 'may 27 , 2012', '126', '2.3'], ['28', '8', 'pup daddy / candy cane - ine', 'june 3 , 2012', '201', 'n / a'], ['29', '9', 'bark to the future / lights , camera , quacktion', 'october 13 , 2012', '205', '1.8'], ['30', '10', 'happy howl - o - ween', 'october 27 , 2012', '210', '1.6'], ['31', '11', 'bark to nature / mutts and bolts', 'august 5 , 2013', '213', '1.9'], ['32', '12', 'dog house / time waits for no mutt', 'august 6 , 2013', '203', '1.6'], ['33', '13', 'hush puppy / quacky birthday', 'august 8 , 2013', '209', '1.8'], ['34', '14', 'love bird / bluff puppy', 'october 20 , 2013 ( nicktoons )', '204', 'n / a'], ['35', '15', 'rat trap / agent of the year', 'october 27 , 2013 ( nicktoons )', '207', 'n / a'], ['36', '16', 'barking tall / bad eggs', 'november 3 , 2013 ( nicktoons )', '212', 'n / a'], ['37', '17', 'carbon copies / tuff cookies', 'november 10 , 2013 ( nicktoons )', '214', 'n / a'], ['39', '19', 'tuff choices / sob story', 'tba ( nicktoons )', '208', 'n / a']] |
list of australia one day international cricket records | https://en.wikipedia.org/wiki/List_of_Australia_One_Day_International_cricket_records | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-21100348-15.html.csv | comparative | adam gilchrist has played more matches in a day than steve rixon has . | {'row_1': '1', 'row_2': '10', 'col': '4', 'col_other': '3', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', 'adam gilchrist'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose player record fuzzily matches to adam gilchrist .', 'tostr': 'filter_eq { all_rows ; player ; adam gilchrist }'}, 'matches'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; player ; adam gilchrist } ; matches }', 'tointer': 'select the rows whose player record fuzzily matches to adam gilchrist . take the matches record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', 'steve rixon'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose player record fuzzily matches to steve rixon .', 'tostr': 'filter_eq { all_rows ; player ; steve rixon }'}, 'matches'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; player ; steve rixon } ; matches }', 'tointer': 'select the rows whose player record fuzzily matches to steve rixon . take the matches record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; player ; adam gilchrist } ; matches } ; hop { filter_eq { all_rows ; player ; steve rixon } ; matches } } = true', 'tointer': 'select the rows whose player record fuzzily matches to adam gilchrist . take the matches record of this row . select the rows whose player record fuzzily matches to steve rixon . take the matches record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; player ; adam gilchrist } ; matches } ; hop { filter_eq { all_rows ; player ; steve rixon } ; matches } } = true | select the rows whose player record fuzzily matches to adam gilchrist . take the matches record of this row . select the rows whose player record fuzzily matches to steve rixon . take the matches record of this row . the first record is greater than the second record . | 5 | 5 | {'greater_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'player_7': 7, 'adam gilchrist_8': 8, 'matches_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'player_11': 11, 'steve rixon_12': 12, 'matches_13': 13} | {'greater_4': 'greater', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'player_7': 'player', 'adam gilchrist_8': 'adam gilchrist', 'matches_9': 'matches', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'player_11': 'player', 'steve rixon_12': 'steve rixon', 'matches_13': 'matches'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'player_7': [0], 'adam gilchrist_8': [0], 'matches_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'player_11': [1], 'steve rixon_12': [1], 'matches_13': [3]} | ['rank', 'dismissals', 'player', 'matches', 'caught', 'stumped'] | [['1', '470', 'adam gilchrist', '287', '416', '54'], ['2', '233', 'ian healy', '168', '194', '39'], ['3', '142', 'brad haddin', '96', '133', '9'], ['4', '124', 'rodney marsh', '92', '120', '4'], ['5', '49', 'wayne b phillips', '48', '42', '7'], ['6', '44', 'mathew wade', '35', '39', '5'], ['7', '39', 'tim paine', '26', '35', '4'], ['8', '28', 'greg dyer', '23', '24', '4'], ['9', '23', 'tim zoehrer', '22', '21', '2'], ['10', '11', 'steve rixon', '6', '9', '2']] |
salyut 7 | https://en.wikipedia.org/wiki/Salyut_7 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-245801-1.html.csv | count | three of the launch dates were in the month of june . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'june', 'result': '3', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'launch date', 'june'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose launch date record fuzzily matches to june .', 'tostr': 'filter_eq { all_rows ; launch date ; june }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; launch date ; june } }', 'tointer': 'select the rows whose launch date record fuzzily matches to june . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; launch date ; june } } ; 3 } = true', 'tointer': 'select the rows whose launch date record fuzzily matches to june . the number of such rows is 3 .'} | eq { count { filter_eq { all_rows ; launch date ; june } } ; 3 } = true | select the rows whose launch date record fuzzily matches to june . 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, 'launch date_5': 5, 'june_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', 'launch date_5': 'launch date', 'june_6': 'june', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'launch date_5': [0], 'june_6': [0], '3_7': [2]} | ['expedition', 'crew', 'launch date', 'flight up', 'landing date', 'flight down', 'duration ( days )'] | [['salyut 7 - eo - 1', 'anatoli berezovoy , valentin lebedev', '13 may 1982 09:58:05 utc', 'soyuz t - 5', '10 december 1982 19:02:36 utc', 'soyuz t - 7', '211.38'], ['salyut 7 - eo - 2', 'vladimir lyakhov , aleksandr pavlovich aleksandrov', '27 june 1983 09:12:00 utc', 'soyuz t - 9', '23 november 1983 19:58:00 utc', 'soyuz t - 9', '149.45'], ['salyut 7 - eo - 3', 'leonid kizim , vladimir solovyov , oleg atkov', '8 february 1984 12:07:26 utc', 'soyuz t - 10', '2 october 1984 10:57:00 utc', 'soyuz t - 11', '236.95'], ['salyut 7 - eo - 4 - 1a', 'viktor savinykh', '6 june 1985 06:39:52 utc', 'soyuz t - 13', '21 november 1985 10:31:00 utc', 'soyuz t - 14', '168.16'], ['salyut 7 - eo - 4 - 1b', 'vladimir dzhanibekov', '6 june 1985 06:39:52 utc', 'soyuz t - 13', '26 september 1985 09:51:58 utc', 'soyuz t - 13', '112.13'], ['salyut 7 - ep - 5', 'georgi grechko', '17 september 1985 12:38:52 utc', 'soyuz t - 14', '26 september 1985 09:51:58 utc', 'soyuz t - 13', '8.88'], ['salyut 7 - eo - 4 - 2', 'vladimir vasyutin , alexander volkov', '17 september 1985 12:38:52 utc', 'soyuz t - 14', '21 november 1985 10:31:00 utc', 'soyuz t - 14', '64.91']] |
2003 - 04 toronto raptors season | https://en.wikipedia.org/wiki/2003%E2%80%9304_Toronto_Raptors_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-15869204-9.html.csv | aggregation | the average crowd attendance for 2003 - 04 toronto raptors season games was 18627 . | {'scope': 'all', 'col': '8', 'type': 'average', 'result': '18627', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'location attendance'], 'result': '18627', 'ind': 0, 'tostr': 'avg { all_rows ; location attendance }'}, '18627'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; location attendance } ; 18627 } = true', 'tointer': 'the average of the location attendance record of all rows is 18627 .'} | round_eq { avg { all_rows ; location attendance } ; 18627 } = true | the average of the location attendance record of all rows is 18627 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'location attendance_4': 4, '18627_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'location attendance_4': 'location attendance', '18627_5': '18627'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'location attendance_4': [0], '18627_5': [1]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record'] | [['75', 'april 2', 'indiana', 'l 64 - 84 ( ot )', 'jalen rose ( 22 )', 'chris bosh ( 7 )', 'rod strickland ( 4 )', 'conseco fieldhouse 17775', '30 - 45'], ['76', 'april 4', 'milwaukee', 'l 83 - 90 ( ot )', 'jalen rose ( 21 )', 'donyell marshall ( 16 )', 'jalen rose ( 7 )', 'air canada centre 17276', '30 - 46'], ['77', 'april 6', 'cleveland', 'w 87 - 86 ( ot )', 'vince carter ( 32 )', 'donyell marshall ( 11 )', 'jalen rose ( 6 )', 'gund arena 20071', '31 - 46'], ['78', 'april 7', 'indiana', 'l 90 - 94 ( ot )', 'donyell marshall ( 26 )', 'donyell marshall ( 10 )', 'jalen rose ( 8 )', 'air canada centre 17554', '31 - 47'], ['79', 'april 9', 'detroit', 'l 66 - 74 ( ot )', 'chris bosh , vince carter ( 18 )', 'donyell marshall ( 11 )', 'vince carter ( 5 )', 'the palace of auburn hills 22076', '31 - 48'], ['80', 'april 11', 'chicago', 'l 108 - 114 ( ot )', 'jalen rose ( 32 )', 'donyell marshall ( 16 )', 'jalen rose ( 6 )', 'air canada centre 17362', '31 - 49'], ['81', 'april 13', 'detroit', 'w 87 - 78 ( ot )', 'donyell marshall ( 27 )', 'donyell marshall ( 16 )', 'morris peterson , jalen rose ( 5 )', 'air canada centre 18273', '32 - 49']] |
sabyrkhan ibraev | https://en.wikipedia.org/wiki/Sabyrkhan_Ibraev | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18119901-1.html.csv | aggregation | sabyrkhan ibraev recorded a total of 106 appearances in the premier league . | {'scope': 'all', 'col': '6', 'type': 'sum', 'result': '106', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'apps'], 'result': '106', 'ind': 0, 'tostr': 'sum { all_rows ; apps }'}, '106'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; apps } ; 106 } = true', 'tointer': 'the sum of the apps record of all rows is 106 .'} | round_eq { sum { all_rows ; apps } ; 106 } = true | the sum of the apps record of all rows is 106 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'apps_4': 4, '106_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'apps_4': 'apps', '106_5': '106'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'apps_4': [0], '106_5': [1]} | ['season', 'team', 'country', 'league', 'level', 'apps', 'goals'] | [['2006', 'irtysh', 'kazakhstan', 'premier league', '1', '27', '2'], ['2007', 'irtysh', 'kazakhstan', 'premier league', '1', '17', '1'], ['2008', 'tobol', 'kazakhstan', 'premier league', '1', '25', '3'], ['2009', 'tobol', 'kazakhstan', 'premier league', '1', '22', '1'], ['2010', 'kairat', 'kazakhstan', 'premier league', '1', '15', '0']] |
boston university terriers men 's ice hockey | https://en.wikipedia.org/wiki/Boston_University_Terriers_men%27s_ice_hockey | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12453414-5.html.csv | majority | for boston university terriers men 's ice hockey , most of the players had under 100 goals . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'less_than', 'value': '100', 'subset': None} | {'func': 'most_less', 'args': ['all_rows', 'goals', '100'], 'result': True, 'ind': 0, 'tointer': 'for the goals records of all rows , most of them are less than 100 .', 'tostr': 'most_less { all_rows ; goals ; 100 } = true'} | most_less { all_rows ; goals ; 100 } = true | for the goals records of all rows , most of them are less than 100 . | 1 | 1 | {'most_less_0': 0, 'result_1': 1, 'all_rows_2': 2, 'goals_3': 3, '100_4': 4} | {'most_less_0': 'most_less', 'result_1': 'true', 'all_rows_2': 'all_rows', 'goals_3': 'goals', '100_4': '100'} | {'most_less_0': [1], 'result_1': [], 'all_rows_2': [0], 'goals_3': [0], '100_4': [0]} | ['player', 'years', 'goals', 'assists', 'points'] | [['john cullen', '1983 - 87', '98', '143', '241'], ['david sacco', '1989 - 93', '74', '143', '217'], ['chris drury', '1994 - 98', '113', '101', '214'], ['rick meagher', '1973 - 77', '90', '120', '210'], ['mike eruzione', '1973 - 77', '92', '116', '208'], ['shawn mceachern', '1988 - 91', '79', '107', '186'], ['david tomlinson', '1987 - 91', '77', '102', '179'], ['mark fidler', '1977 - 81', '77', '101', '178'], ['mike kelfer', '1985 - 89', '83', '89', '172'], ['mike hyndman', '1967 - 70', '52', '119', '171']] |
high jump | https://en.wikipedia.org/wiki/High_jump | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13791-3.html.csv | count | two of the athletes have a nationality of bulgaria . | {'scope': 'all', 'criterion': 'equal', 'value': 'bulgaria', 'result': '2', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'nationality', 'bulgaria'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose nationality record fuzzily matches to bulgaria .', 'tostr': 'filter_eq { all_rows ; nationality ; bulgaria }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; nationality ; bulgaria } }', 'tointer': 'select the rows whose nationality record fuzzily matches to bulgaria . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; nationality ; bulgaria } } ; 2 } = true', 'tointer': 'select the rows whose nationality record fuzzily matches to bulgaria . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; nationality ; bulgaria } } ; 2 } = true | select the rows whose nationality record fuzzily matches to bulgaria . the number of such rows is 2 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'nationality_5': 5, 'bulgaria_6': 6, '2_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'nationality_5': 'nationality', 'bulgaria_6': 'bulgaria', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'nationality_5': [0], 'bulgaria_6': [0], '2_7': [2]} | ['pos', 'mark', 'athlete', 'nationality', 'venue', 'date'] | [['1', '2.09 m ( 6ft10 ¼ in )', 'stefka kostadinova', 'bulgaria', 'rome', '30 august 1987'], ['2', '2.08 m ( 6ft9 ¾ in )', 'blanka vlašić', 'croatia', 'zagreb', '31 august 2009'], ['3', '2.07 m ( 6ft9 ¼ in )', 'lyudmila andonova', 'bulgaria', 'berlin', '20 july 1984'], ['3', '2.07 m ( 6ft9 ¼ in )', 'anna chicherova', 'russia', 'cheboksary', '22 july 2011'], ['5', '2.06 m ( 6ft9in )', 'kajsa bergqvist', 'sweden', 'eberstadt', '26 july 2003'], ['5', '2.06 m ( 6ft9in )', 'hestrie cloete', 'south africa', 'paris', '31 august 2003'], ['5', '2.06 m ( 6ft9in )', 'yelena slesarenko', 'russia', 'athens', '28 august 2004'], ['5', '2.06 m ( 6ft9in )', 'ariane friedrich', 'germany', 'berlin', '14 june 2009'], ['9', '2.05 m ( 6ft8 ½ in )', 'tamara bykova', 'soviet union', 'kiev', '22 june 1984'], ['9', '2.05 m ( 6ft8 ½ in )', 'heike henkel', 'germany', 'tokyo', '31 august 1991'], ['9', '2.05 m ( 6ft8 ½ in )', 'inha babakova', 'ukraine', 'tokyo', '15 september 1995'], ['9', '2.05 m ( 6ft8 ½ in )', 'tia hellebaut', 'belgium', 'beijing', '23 august 2008'], ['9', '2.05 m ( 6ft8 ½ in )', 'chaunté lowe', 'usa', 'des moines', '26 june 2010']] |
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 | majority | rafael barreto was safe from elimination in most weeks that he performed . | {'scope': 'all', 'col': '6', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'safe', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'result', 'safe'], 'result': True, 'ind': 0, 'tointer': 'for the result records of all rows , most of them fuzzily match to safe .', 'tostr': 'most_eq { all_rows ; result ; safe } = true'} | most_eq { all_rows ; result ; safe } = true | for the result records of all rows , most of them fuzzily match to safe . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'result_3': 3, 'safe_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'result_3': 'result', 'safe_4': 'safe'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'result_3': [0], 'safe_4': [0]} | ['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']] |
list of the amanda show episodes | https://en.wikipedia.org/wiki/List_of_The_Amanda_Show_episodes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-17152787-3.html.csv | superlative | episode 27 was the last of these episodes of the amanda show to air . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '13', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '3', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'original air date'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; original air date }'}, 'title'], 'result': 'episode 27', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; original air date } ; title }'}, 'episode 27'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; original air date } ; title } ; episode 27 } = true', 'tointer': 'select the row whose original air date record of all rows is maximum . the title record of this row is episode 27 .'} | eq { hop { argmax { all_rows ; original air date } ; title } ; episode 27 } = true | select the row whose original air date record of all rows is maximum . the title record of this row is episode 27 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'original air date_5': 5, 'title_6': 6, 'episode 27_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'original air date_5': 'original air date', 'title_6': 'title', 'episode 27_7': 'episode 27'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'original air date_5': [0], 'title_6': [1], 'episode 27_7': [2]} | ['series', 'season', 'title', 'directed by', 'original air date', 'prod code'] | [['14', '1', 'episode 14', 'rich correll , virgil l fabian & ken whittingham', 'july 15 , 2000', '214'], ['16', '3', 'episode 16', 'virgil l fabian & ken whittingham', 'august 12 , 2000', '216'], ['17', '4', 'episode 17', 'virgil l fabian & ken whittingham', 'august 26 , 2000', '217'], ['18', '5', 'episode 18', "tim o'donnell , rich correll & virgil l fabian", 'september 9 , 2000', '218'], ['19', '6', 'episode 19', 'rich correll & virgil l fabian', 'september 23 , 2000', '219'], ['20', '7', 'episode 20', 'rich correll , virgil l fabian & ken whittingham', 'october 7 , 2000', '220'], ['21', '8', 'episode 21', "rich correll , virgil l fabian & tim o'donnell", 'october 21 , 2000', '221'], ['22', '9', 'episode 22', 'rich correll , virgil l fabian & ken whittingham', 'october 28 , 2000', '222'], ['23', '10', 'episode 23', 'rich correll , virgil l fabian & ken whittingham', 'november 18 , 2000', '223'], ['24', '11', 'episode 24', "rich correll , virgil l fabian & tim o'donnell", 'december 9 , 2000', '224'], ['25', '12', 'episode 25', 'rich correll & virgil l fabian', 'december 23 , 2000', '225'], ['26', '13', 'episode 26', 'virgil l fabian & ken whittingham', 'january 27 , 2001', '226'], ['27', '14', 'episode 27', 'rich correll & virgil l fabian', 'february 17 , 2001', '227']] |
walter martínez ( footballer ) | https://en.wikipedia.org/wiki/Walter_Mart%C3%ADnez_%28footballer%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11982701-1.html.csv | superlative | walter martinez scored the fewest goals during the 08/09 season . | {'scope': 'all', 'col_superlative': '6', 'row_superlative': '11', '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', 'goals'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; goals }'}, 'season'], 'result': '08 / 09', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; goals } ; season }'}, '08 / 09'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmin { all_rows ; goals } ; season } ; 08 / 09 } = true', 'tointer': 'select the row whose goals record of all rows is minimum . the season record of this row is 08 / 09 .'} | eq { hop { argmin { all_rows ; goals } ; season } ; 08 / 09 } = true | select the row whose goals record of all rows is minimum . the season record of this row is 08 / 09 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'goals_5': 5, 'season_6': 6, '08 / 09_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'goals_5': 'goals', 'season_6': 'season', '08 / 09_7': '08 / 09'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'goals_5': [0], 'season_6': [1], '08 / 09_7': [2]} | ['season', 'team', 'country', 'division', 'apps', 'goals'] | [['00 / 01', 'club deportivo victoria', 'honduras', '1', '19', '1'], ['01 / 02', 'club deportivo victoria', 'honduras', '1', '14', '2'], ['02 / 03', 'club deportivo victoria', 'honduras', '1', '10', '4'], ['03 / 04', 'club deportivo victoria', 'honduras', '1', '10', '2'], ['03 / 04', 'club deportivo marathón', 'honduras', '1', '10', '2'], ['04 / 05', 'club deportivo marathón', 'honduras', '1', '10', '1'], ['05 / 06', 'club deportivo y social vida', 'honduras', '1', '8', '3'], ['06 / 07', 'club deportivo marathón', 'honduras', '1', '18', '9'], ['2007', 'beijing guoan', 'china', '1', '28', '7'], ['2008', 'beijing guoan', 'china', '1', '16', '7'], ['08 / 09', 'deportivo alavés', 'spain', '2', '3', '0'], ['09 / 10', 'club deportivo marathón', 'honduras', '1', '23', '7'], ['2010', 'beijing guoan', 'china', '1', '12', '4'], ['2011', 'beijing guoan', 'china', '1', '25', '9'], ['2012', 'chongqing fc', 'china', '2', '29', '3'], ['2013', 'san jose earthquakes', 'usa', '1', '11', '2']] |
presidents ' athletic conference | https://en.wikipedia.org/wiki/Presidents%27_Athletic_Conference | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-262476-1.html.csv | count | there are two institutions in the presidents ' athletic conference that joined in 2007 . | {'scope': 'all', 'criterion': 'equal', 'value': '2007', 'result': '2', 'col': '6', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'joined', '2007'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose joined record is equal to 2007 .', 'tostr': 'filter_eq { all_rows ; joined ; 2007 }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; joined ; 2007 } }', 'tointer': 'select the rows whose joined record is equal to 2007 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; joined ; 2007 } } ; 2 } = true', 'tointer': 'select the rows whose joined record is equal to 2007 . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; joined ; 2007 } } ; 2 } = true | select the rows whose joined record is equal to 2007 . the number of such rows is 2 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_eq_0': 0, 'all_rows_4': 4, 'joined_5': 5, '2007_6': 6, '2_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'joined_5': 'joined', '2007_6': '2007', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'joined_5': [0], '2007_6': [0], '2_7': [2]} | ['institution', 'location', 'nickname', 'founded', 'enrollment', 'joined'] | [['bethany college', 'bethany , west virginia', 'bison', '1840', '1030', '1958'], ['chatham university', 'pittsburgh , pennsylvania', 'cougars', '1869', '2300', '2007'], ['geneva college', 'beaver falls , pennsylvania', 'golden tornadoes', '1848', '1791', '2007'], ['grove city college', 'grove city , pennsylvania', 'wolverines', '1876', '2500', '1984'], ['saint vincent college', 'latrobe , pennsylvania', 'bearcats', '1846', '1652', '2006'], ['thiel college', 'greenville , pennsylvania', 'tomcats', '1866', '1066', '1958'], ['thomas more college', 'crestview hills , kentucky', 'saints', '1921', '1900', '2005'], ['washington & jefferson college', 'washington , pennsylvania', 'presidents', '1781', '1519', '1958'], ['waynesburg university', 'waynesburg , pennsylvania', 'yellow jackets', '1849', '1500', '1990']] |
1940 vfl season | https://en.wikipedia.org/wiki/1940_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10807253-16.html.csv | count | there were 6 game venues used during the 1940 vfl season . | {'scope': 'all', 'criterion': 'all', 'value': 'n/a', 'result': '6', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_all', 'args': ['all_rows', 'venue'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose venue record is arbitrary .', 'tostr': 'filter_all { all_rows ; venue }'}], 'result': '6', 'ind': 1, 'tostr': 'count { filter_all { all_rows ; venue } }', 'tointer': 'select the rows whose venue record is arbitrary . the number of such rows is 6 .'}, '6'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_all { all_rows ; venue } } ; 6 } = true', 'tointer': 'select the rows whose venue record is arbitrary . the number of such rows is 6 .'} | eq { count { filter_all { all_rows ; venue } } ; 6 } = true | select the rows whose venue record is arbitrary . the number of such rows is 6 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_all_0': 0, 'all_rows_4': 4, 'venue_5': 5, '6_6': 6} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_all_0': 'filter_all', 'all_rows_4': 'all_rows', 'venue_5': 'venue', '6_6': '6'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_all_0': [1], 'all_rows_4': [0], 'venue_5': [0], '6_6': [2]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['footscray', '17.22 ( 124 )', 'north melbourne', '8.13 ( 61 )', 'western oval', '8000', '17 august 1940'], ['collingwood', '12.18 ( 90 )', 'melbourne', '16.8 ( 104 )', 'victoria park', '8000', '17 august 1940'], ['carlton', '13.14 ( 92 )', 'st kilda', '6.16 ( 52 )', 'princes park', '6000', '17 august 1940'], ['south melbourne', '12.19 ( 91 )', 'geelong', '13.9 ( 87 )', 'lake oval', '7000', '17 august 1940'], ['richmond', '14.15 ( 99 )', 'fitzroy', '10.11 ( 71 )', 'punt road oval', '22000', '17 august 1940'], ['hawthorn', '11.18 ( 84 )', 'essendon', '18.12 ( 120 )', 'glenferrie oval', '9000', '17 august 1940']] |
1995 wta tour | https://en.wikipedia.org/wiki/1995_WTA_Tour | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15866312-10.html.csv | unique | shi - ting wang was the only player to win matches with scores of 6 - 1 , 6 - 1 . | {'scope': 'all', 'row': '1', 'col': '3', 'col_other': 'n/a', 'criterion': 'equal', 'value': '6 - 1 , 6 - 1', 'subset': None} | {'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'winner', '6 - 1 , 6 - 1'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose winner record fuzzily matches to 6 - 1 , 6 - 1 .', 'tostr': 'filter_eq { all_rows ; winner ; 6 - 1 , 6 - 1 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; winner ; 6 - 1 , 6 - 1 } } = true', 'tointer': 'select the rows whose winner record fuzzily matches to 6 - 1 , 6 - 1 . there is only one such row in the table .'} | only { filter_eq { all_rows ; winner ; 6 - 1 , 6 - 1 } } = true | select the rows whose winner record fuzzily matches to 6 - 1 , 6 - 1 . 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, 'winner_4': 4, '6 - 1 , 6 - 1_5': 5} | {'only_1': 'only', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'winner_4': 'winner', '6 - 1 , 6 - 1_5': '6 - 1 , 6 - 1'} | {'only_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'winner_4': [0], '6 - 1 , 6 - 1_5': [0]} | ['week of', 'tier', 'winner', 'runner - up', 'semi finalists'] | [['2 october', 'tier iv', 'shi - ting wang 6 - 1 , 6 - 1', 'jing - qian yi', 'tina križan annabel ellwood'], ['2 october', 'tier iv', 'petra kamstra tina križan 2 - 6 , 6 - 4 , 6 - 1', 'nana miyagi stephanie reece', 'tina križan annabel ellwood'], ['2 october', 'tier i', 'iva majoli 6 - 4 , 6 - 4', 'mary pierce', 'chanda rubin mariaan de swardt'], ['2 october', 'tier i', 'nicole arendt manon bollegraf 6 - 4 , 6 - 7 , 6 - 4', 'chanda rubin caroline vis', 'chanda rubin mariaan de swardt'], ['9 october', 'tier ii', 'iva majoli 6 - 4 , 7 - 6', 'gabriela sabatini', 'anke huber chanda rubin'], ['9 october', 'tier ii', 'gigi fernández natalia zvereva 5 - 7 , 6 - 1 , 6 - 4', 'meredith mcgrath larisa savchenko', 'anke huber chanda rubin'], ['17 october', 'tier ii', 'mary joe fernández 6 - 4 , 7 - 5', 'amanda coetzer', 'kristie boogert magdalena maleeva'], ['17 october', 'tier ii', 'meredith mcgrath larisa savchenko 7 - 5 , 6 - 1', 'lori mcneil helena suková', 'kristie boogert magdalena maleeva'], ['30 october', 'tier iii', 'brenda schultz - mccarthy 7 - 6 , 6 - 2', 'dominique monami', 'lindsay lee rennae stubbs'], ['30 october', 'tier iii', 'nicole arendt manon bollegraf 7 - 6 , 4 - 6 , 6 - 2', 'lisa raymond rennae stubbs', 'lindsay lee rennae stubbs'], ['30 october', 'tier ii', 'magdalena maleeva 6 - 3 , 6 - 4', 'ai sugiyama', 'lindsay davenport mary joe fernández'], ['30 october', 'tier ii', 'lori mcneil helena suková 3 - 6 , 6 - 4 , 6 - 3', 'katrina adams zina garrison - jackson', 'lindsay davenport mary joe fernández']] |
aaron kelly ( singer ) | https://en.wikipedia.org/wiki/Aaron_Kelly_%28singer%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27075510-1.html.csv | count | aaron kelly was in the bottom three for two weeks after his performance . | {'scope': 'all', 'criterion': 'equal', 'value': 'bottom 3', 'result': '2', 'col': '6', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'result', 'bottom 3'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose result record fuzzily matches to bottom 3 .', 'tostr': 'filter_eq { all_rows ; result ; bottom 3 }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; result ; bottom 3 } }', 'tointer': 'select the rows whose result record fuzzily matches to bottom 3 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; result ; bottom 3 } } ; 2 } = true', 'tointer': 'select the rows whose result record fuzzily matches to bottom 3 . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; result ; bottom 3 } } ; 2 } = true | select the rows whose result record fuzzily matches to bottom 3 . the number of such rows is 2 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'result_5': 5, 'bottom 3_6': 6, '2_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'result_5': 'result', 'bottom 3_6': 'bottom 3', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'result_5': [0], 'bottom 3_6': [0], '2_7': [2]} | ['week', 'theme', 'song choice', 'original artist', 'order', 'result'] | [['audition', 'n / a', 'the climb', 'miley cyrus', 'n / a', 'advanced'], ['hollywood', 'group round', 'get ready', 'the temptations', 'n / a', 'advanced'], ['hollywood', 'second solo', 'angel', 'sarah mclachlan', 'n / a', 'advanced'], ['top 24 ( 12 men )', 'billboard hot 100 hits', 'here comes goodbye', 'rascal flatts', '2', 'safe'], ['top 20 ( 10 men )', 'billboard hot 100 hits', 'my girl', 'the temptations', '8', 'safe'], ['top 16 ( 8 men )', 'billboard hot 100 hits', "i 'm already there", 'lonestar', '6', 'safe'], ['top 12', 'the rolling stones', 'angie', 'the rolling stones', '11', 'safe'], ['top 11', 'billboard number 1 hits', "i do n't want to miss a thing", 'aerosmith', '4', 'safe'], ['top 10', 'r & b / soul', "ai n't no sunshine", 'bill withers', '10', 'safe'], ['top 9', 'lennonmccartney', 'the long and winding road', 'the beatles', '1', 'bottom 3'], ['top 9', 'elvis presley', 'blue suede shoes', 'carl perkins', '5', 'safe'], ['top 7', 'inspirational', 'i believe i can fly', 'r kelly', '4', 'bottom 3'], ['top 6', 'shania twain', "you 've got a way", 'shania twain', '5', 'safe']] |
list of new york undercover episodes | https://en.wikipedia.org/wiki/List_of_New_York_Undercover_episodes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-11951237-2.html.csv | superlative | the last episode of new york undercover was titled the enforcers . | {'scope': 'all', 'col_superlative': '7', 'row_superlative': '17', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '3', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'original air date'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; original air date }'}, 'title'], 'result': 'the enforcers', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; original air date } ; title }'}, 'the enforcers'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; original air date } ; title } ; the enforcers } = true', 'tointer': 'select the row whose original air date record of all rows is maximum . the title record of this row is the enforcers .'} | eq { hop { argmax { all_rows ; original air date } ; title } ; the enforcers } = true | select the row whose original air date record of all rows is maximum . the title record of this row is the enforcers . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'original air date_5': 5, 'title_6': 6, 'the enforcers_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'original air date_5': 'original air date', 'title_6': 'title', 'the enforcers_7': 'the enforcers'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'original air date_5': [0], 'title_6': [1], 'the enforcers_7': [2]} | ['series', 'season', 'title', 'directed by', 'written by', 'musical guest and song', 'original air date', 'production code'] | [['27', '1', 'high on the hog', 'frederick k keller', 'larry moskowitz', "al jarreau we 're in this love together", 'august 31 , 1995', 'k0503'], ['29', '3', "man 's best friend", 'frederick k keller', 'natalie chaidez', 'guy tell me what you like', 'september 14 , 1995', 'k0504'], ['32', '6', 'buster and claudia', 'don kurt', 'michael mahern', 'bb king the thrill is gone', 'october 5 , 1995', 'k0510'], ['33', '7', 'student affairs', 'michael lange', 'larry moskowitz', 'jon b my cherie amour', 'october 12 , 1995', 'k0511'], ['34', '8', 'the highest bidder', 'frederick k keller', 'judith mccreary', "d'angelo brown sugar", 'october 19 , 1995', 'k0513'], ['35', '9', 'young , beautiful and dead', 'michael lange', 'natalie chaidez', 'silk wildflower', 'november 2 , 1995', 'k0512'], ['36', '10', 'color lines', 'frederick k keller', 'shane salerno', 'marnell kenan run to you', 'november 9 , 1995', 'k0514'], ['37', '11', 'the finals', 'don kurt', 'reggie rock bythewood', 'al green love and happiness', 'november 16 , 1995', 'k0515'], ['39', '13', 'bad girls', 'peter r mcintosh', 'michael mahern', 'dionne farris food for thought', 'december 14 , 1995', 'k0517'], ['40', '14', 'a time to kill', 'frederick k keller', 'judith mccreary', 'monifah i miss you ( come back home )', 'january 4 , 1996', 'k0519'], ['41', '15', 'bad blood', 'matthew penn', 'reggie rock bythewood & jamal joseph', "brownstone do n't ask my neighbor", 'january 18 , 1996', 'k0501'], ['42', '16', 'fire show', 'jace alexander', 'natalie chaidez', 'tito nieves lo prometido es deuda', 'february 1 , 1996', 'k0518'], ['43', '17', 'toy soldiers', 'melanie mayron', 'larry moskowitz', 'luther vandross a house is not a home', 'february 8 , 1996', 'k0502'], ['44', '18', 'sympathy for the devil', 'martha mitchell', 'shane salerno', 'xscape all this love', 'february 15 , 1996', 'k0520'], ['45', '19', 'checkmate', 'oscar l costo', 'judith mccreary', 'roberta flack killing me softly with his song', 'february 22 , 1996', 'k0521'], ['47', '21', 'the reckoning', 'jesús treviño', 'judith mccreary', 'aaron neville use me', 'march 14 , 1996', 'k0509'], ['48', '22', 'the enforcers', 'matthew penn', 'michael mahern', 'koko taylor wang dang doodle', 'april 4 , 1996', 'k0523']] |
list of greek episodes | https://en.wikipedia.org/wiki/List_of_Greek_episodes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-12419515-4.html.csv | count | 9 episodes of the greek series were directed by michael lange . | {'scope': 'all', 'criterion': 'equal', 'value': 'michael lange', 'result': '9', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'directed by', 'michael lange'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose directed by record fuzzily matches to michael lange .', 'tostr': 'filter_eq { all_rows ; directed by ; michael lange }'}], 'result': '9', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; directed by ; michael lange } }', 'tointer': 'select the rows whose directed by record fuzzily matches to michael lange . the number of such rows is 9 .'}, '9'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; directed by ; michael lange } } ; 9 } = true', 'tointer': 'select the rows whose directed by record fuzzily matches to michael lange . the number of such rows is 9 .'} | eq { count { filter_eq { all_rows ; directed by ; michael lange } } ; 9 } = true | select the rows whose directed by record fuzzily matches to michael lange . the number of such rows is 9 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'directed by_5': 5, 'michael lange_6': 6, '9_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'directed by_5': 'directed by', 'michael lange_6': 'michael lange', '9_7': '9'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'directed by_5': [0], 'michael lange_6': [0], '9_7': [2]} | ['series', 'season', 'title', 'directed by', 'written by', 'original air date', 'total viewers ( in millions )'] | [['45', '1', 'the day after', 'michael lange', 'patrick sean smith', 'august 31 , 2009', '1.211'], ['46', '2', 'our fathers', 'patrick norris', 'jessica otoole & amy rardin', 'september 7 , 2009', '1.313'], ['47', '3', 'the half - naked gun', 'michael lange', 'roger grant', 'september 14 , 2009', 'n / a'], ['48', '4', 'high and dry', 'shawn piller', 'casey johnson', 'september 21 , 2009', 'n / a'], ['49', '5', 'down on your luck', 'michael lange', 'matt whitney', 'september 28 , 2009', 'n / a'], ['50', '6', 'lost and founders', 'fred gerber', 'michael berns', 'october 5 , 2009', 'n / a'], ['51', '7', 'the dork knight', 'rick rosenthal', 'adam milch', 'october 12 , 2009', 'n / a'], ['52', '8', 'fight the power', 'michael lange', 'jessica otoole & amy rardin', 'october 19 , 2009', 'n / a'], ['53', '9', 'the wish - pretzel', 'melanie mayron', 'lana cho & matt whitney', 'october 26 , 2009', 'n / a'], ['54', '10', 'friend or foe', 'michael lange', 'roger grant', 'november 2 , 2009', 'n / a'], ['55', '11', 'i know what you did last semester', 'michael lange', 'casey johnson & david windsor', 'january 25 , 2010', 'n / a'], ['56', '12', 'pride & punishment', 'john t kretchmer', 'jessica otoole & amy rardin', 'february 1 , 2010', 'n / a'], ['57', '13', 'take me out', 'lee rose', 'matt whitney', 'february 8 , 2010', 'n / a'], ['58', '14', 'the tortoise and the hair', 'michael lange', 'rob bragin', 'february 15 , 2010', 'n / a'], ['59', '15', 'love , actually , possibly , maybe or not', 'mark rosman', 'roger grant', 'february 22 , 2010', '0.872'], ['60', '16', 'your friends and neighbors', 'michael lange', 'dana greenblatt', 'march 1 , 2010', '0.937'], ['61', '17', 'the big easy does it', 'fred savage', 'casey johnson & david windsor', 'march 8 , 2010', '1.031'], ['62', '18', 'camp buy me love', 'michael lange', 'jessica otoole & amy rardin', 'march 15 , 2010', '0.820'], ['63', '19', 'the first last', 'patrick norris', 'roger grant & matt whitney', 'march 22 , 2010', 'n / a']] |
marinne giraud | https://en.wikipedia.org/wiki/Marinne_Giraud | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15508602-2.html.csv | unique | the tournament in trivandrum was marinne giraud 's only tournament on a clay surface . | {'scope': 'all', 'row': '4', 'col': '4', 'col_other': '3', 'criterion': 'equal', 'value': 'clay', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'surface', 'clay'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose surface record fuzzily matches to clay .', 'tostr': 'filter_eq { all_rows ; surface ; clay }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; surface ; clay } }', 'tointer': 'select the rows whose surface record fuzzily matches to clay . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'surface', 'clay'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose surface record fuzzily matches to clay .', 'tostr': 'filter_eq { all_rows ; surface ; clay }'}, 'tournament'], 'result': 'trivandrum', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; surface ; clay } ; tournament }'}, 'trivandrum'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; surface ; clay } ; tournament } ; trivandrum }', 'tointer': 'the tournament record of this unqiue row is trivandrum .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; surface ; clay } } ; eq { hop { filter_eq { all_rows ; surface ; clay } ; tournament } ; trivandrum } } = true', 'tointer': 'select the rows whose surface record fuzzily matches to clay . there is only one such row in the table . the tournament record of this unqiue row is trivandrum .'} | and { only { filter_eq { all_rows ; surface ; clay } } ; eq { hop { filter_eq { all_rows ; surface ; clay } ; tournament } ; trivandrum } } = true | select the rows whose surface record fuzzily matches to clay . there is only one such row in the table . the tournament record of this unqiue row is trivandrum . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'surface_7': 7, 'clay_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'tournament_9': 9, 'trivandrum_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'surface_7': 'surface', 'clay_8': 'clay', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'tournament_9': 'tournament', 'trivandrum_10': 'trivandrum'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'surface_7': [0], 'clay_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'tournament_9': [2], 'trivandrum_10': [3]} | ['outcome', 'date', 'tournament', 'surface', 'opponent in the final', 'score'] | [['winner', '24 - oct - 2005', 'pretoria', 'hard', 'alicia pillay', '6 - 4 6 - 2'], ['runner - up', '09 - oct - 2006', 'braga', 'carpet', 'eloisa compostizo de andres', '4 - 6 , 7 - 5 , 3 - 6'], ['winner', '14 april 2007', 'dubai', 'hard', 'çağla büyükakçay', '6 - 2 6 - 2'], ['winner', '14 - may - 2007', 'trivandrum', 'clay', 'agnes szatmari', '7 - 5 6 - 3'], ['winner', '20 - may - 2007', 'mumbai', 'hard', 'rushmi chakravarthi', '7 - 6 ( 7 ) 6 - 2']] |
1967 south african grand prix | https://en.wikipedia.org/wiki/1967_South_African_Grand_Prix | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1122362-1.html.csv | comparative | at the 1967 south african grand prix , mike spence completed one more lap than jo bonnier . | {'row_1': '14', 'row_2': '15', 'col': '3', 'col_other': '1', 'relation': 'diff', 'record_mentioned': 'no', 'diff_result': {'diff_value': '1', 'bigger': 'row1'}} | {'func': 'eq', 'args': [{'func': 'diff', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'driver', 'mike spence'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose driver record fuzzily matches to mike spence .', 'tostr': 'filter_eq { all_rows ; driver ; mike spence }'}, 'laps'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; driver ; mike spence } ; laps }', 'tointer': 'select the rows whose driver record fuzzily matches to mike spence . take the laps record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'driver', 'jo bonnier'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose driver record fuzzily matches to jo bonnier .', 'tostr': 'filter_eq { all_rows ; driver ; jo bonnier }'}, 'laps'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; driver ; jo bonnier } ; laps }', 'tointer': 'select the rows whose driver record fuzzily matches to jo bonnier . take the laps record of this row .'}], 'result': '1', 'ind': 4, 'tostr': 'diff { hop { filter_eq { all_rows ; driver ; mike spence } ; laps } ; hop { filter_eq { all_rows ; driver ; jo bonnier } ; laps } }'}, '1'], 'result': True, 'ind': 5, 'tostr': 'eq { diff { hop { filter_eq { all_rows ; driver ; mike spence } ; laps } ; hop { filter_eq { all_rows ; driver ; jo bonnier } ; laps } } ; 1 } = true', 'tointer': 'select the rows whose driver record fuzzily matches to mike spence . take the laps record of this row . select the rows whose driver record fuzzily matches to jo bonnier . take the laps record of this row . the first record is 1 larger than the second record .'} | eq { diff { hop { filter_eq { all_rows ; driver ; mike spence } ; laps } ; hop { filter_eq { all_rows ; driver ; jo bonnier } ; laps } } ; 1 } = true | select the rows whose driver record fuzzily matches to mike spence . take the laps record of this row . select the rows whose driver record fuzzily matches to jo bonnier . take the laps record of this row . the first record is 1 larger than the second record . | 6 | 6 | {'eq_5': 5, 'result_6': 6, 'diff_4': 4, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_7': 7, 'driver_8': 8, 'mike spence_9': 9, 'laps_10': 10, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_11': 11, 'driver_12': 12, 'jo bonnier_13': 13, 'laps_14': 14, '1_15': 15} | {'eq_5': 'eq', 'result_6': 'true', 'diff_4': 'diff', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_7': 'all_rows', 'driver_8': 'driver', 'mike spence_9': 'mike spence', 'laps_10': 'laps', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_11': 'all_rows', 'driver_12': 'driver', 'jo bonnier_13': 'jo bonnier', 'laps_14': 'laps', '1_15': '1'} | {'eq_5': [6], 'result_6': [], 'diff_4': [5], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_7': [0], 'driver_8': [0], 'mike spence_9': [0], 'laps_10': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_11': [1], 'driver_12': [1], 'jo bonnier_13': [1], 'laps_14': [3], '1_15': [5]} | ['driver', 'constructor', 'laps', 'time / retired', 'grid'] | [['pedro rodrã\xadguez', 'cooper - maserati', '80', '2:05:45.9', '4'], ['john love', 'cooper - climax', '80', '+ 26.4', '5'], ['john surtees', 'honda', '79', '+ 1 lap', '6'], ['denny hulme', 'brabham - repco', '78', '+ 2 laps', '2'], ['bob anderson', 'brabham - climax', '78', '+ 2 laps', '10'], ['jack brabham', 'brabham - repco', '76', '+ 4 laps', '1'], ['dave charlton', 'brabham - climax', '63', 'not classified', '8'], ['luki botha', 'brabham - climax', '60', 'not classified', '17'], ['sam tingle', 'lds - climax', '56', 'accident', '14'], ['piers courage', 'lotus - brm', '51', 'fuel system', '18'], ['dan gurney', 'eagle - climax', '44', 'suspension', '11'], ['jo siffert', 'cooper - maserati', '41', 'engine', '16'], ['jochen rindt', 'cooper - maserati', '38', 'engine', '7'], ['mike spence', 'brm', '31', 'oil leak', '13'], ['jo bonnier', 'cooper - maserati', '30', 'engine', '12'], ['jim clark', 'lotus - brm', '22', 'engine', '3'], ['graham hill', 'lotus - brm', '6', 'accident', '15'], ['jackie stewart', 'brm', '2', 'engine', '9']] |
1998 pga tour | https://en.wikipedia.org/wiki/1998_PGA_Tour | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14611466-4.html.csv | count | 4 players from the united states participated in the 1998 pga tour . | {'scope': 'all', 'criterion': 'equal', 'value': 'united states', 'result': '4', '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': '4', '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 4 .'}, '4'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; country ; united states } } ; 4 } = true', 'tointer': 'select the rows whose country record fuzzily matches to united states . the number of such rows is 4 .'} | eq { count { filter_eq { all_rows ; country ; united states } } ; 4 } = true | select the rows whose country record fuzzily matches to united states . the number of such rows is 4 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'country_5': 5, 'united states_6': 6, '4_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'country_5': 'country', 'united states_6': 'united states', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'country_5': [0], 'united states_6': [0], '4_7': [2]} | ['rank', 'player', 'country', 'earnings', 'wins'] | [['1', 'greg norman', 'australia', '11936443', '20'], ['2', 'fred couples', 'united states', '10535876', '14'], ['3', 'tom kite', 'united states', '10447472', '19'], ['4', "mark o'meara", 'united states', '10293473', '16'], ['5', 'davis love iii', 'united states', '10012134', '13']] |
2008 - 09 philadelphia flyers season | https://en.wikipedia.org/wiki/2008%E2%80%9309_Philadelphia_Flyers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17511295-3.html.csv | aggregation | the average attendance for games in the 2008 - 09 philadelphia flyers season was 17706 . | {'scope': 'all', 'col': '6', 'type': 'average', 'result': '17706', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'attendance'], 'result': '17706', 'ind': 0, 'tostr': 'avg { all_rows ; attendance }'}, '17706'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; attendance } ; 17706 } = true', 'tointer': 'the average of the attendance record of all rows is 17706 .'} | round_eq { avg { all_rows ; attendance } ; 17706 } = true | the average of the attendance record of all rows is 17706 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'attendance_4': 4, '17706_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'attendance_4': 'attendance', '17706_5': '17706'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'attendance_4': [0], '17706_5': [1]} | ['date', 'visitor', 'score', 'home', 'decision', 'attendance', 'record'] | [['october 11', 'ny rangers', '4 - 3', 'philadelphia', 'biron', '19623', '0 - 1 - 0'], ['october 13', 'montreal', '5 - 3', 'philadelphia', 'biron', '19323', '0 - 2 - 0'], ['october 14', 'philadelphia', '2 - 3', 'pittsburgh', 'niittymaki', '16965', '0 - 2 - 1'], ['october 16', 'philadelphia', '2 - 5', 'colorado', 'biron', '18007', '0 - 3 - 1'], ['october 18', 'philadelphia', '4 - 5', 'san jose', 'niittymaki', '17496', '0 - 3 - 2'], ['october 22', 'san jose', '7 - 6', 'philadelphia', 'biron', '19072', '0 - 3 - 3'], ['october 24', 'philadelphia', '6 - 3', 'new jersey', 'biron', '15529', '1 - 3 - 3'], ['october 25', 'new jersey', '2 - 3', 'philadelphia', 'biron', '19611', '2 - 3 - 3'], ['october 28', 'philadelphia', '7 - 0', 'atlanta', 'niittymaki', '13207', '3 - 3 - 3'], ['october 30', 'ny islanders', '2 - 3', 'philadelphia', 'biron', '18227', '4 - 3 - 3']] |
komlavi loglo | https://en.wikipedia.org/wiki/Komlavi_Loglo | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14008546-2.html.csv | superlative | in the latest tournament in dakar komlavi loglo had rudy coco for the opponent in the field . | {'scope': 'subset', 'col_superlative': '1', 'row_superlative': '6', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '2,4', 'subset': {'col': '2', 'criterion': 'equal', 'value': 'dakar'}} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'tournament', 'dakar'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; tournament ; dakar }', 'tointer': 'select the rows whose tournament record fuzzily matches to dakar .'}, 'date'], 'result': None, 'ind': 1, 'tostr': 'argmax { filter_eq { all_rows ; tournament ; dakar } ; date }'}, 'opponent in the final'], 'result': 'rudy coco', 'ind': 2, 'tostr': 'hop { argmax { filter_eq { all_rows ; tournament ; dakar } ; date } ; opponent in the final }'}, 'rudy coco'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { argmax { filter_eq { all_rows ; tournament ; dakar } ; date } ; opponent in the final } ; rudy coco } = true', 'tointer': 'select the rows whose tournament record fuzzily matches to dakar . select the row whose date record of these rows is maximum . the opponent in the final record of this row is rudy coco .'} | eq { hop { argmax { filter_eq { all_rows ; tournament ; dakar } ; date } ; opponent in the final } ; rudy coco } = true | select the rows whose tournament record fuzzily matches to dakar . select the row whose date record of these rows is maximum . the opponent in the final record of this row is rudy coco . | 4 | 4 | {'str_eq_3': 3, 'result_4': 4, 'str_hop_2': 2, 'argmax_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'tournament_6': 6, 'dakar_7': 7, 'date_8': 8, 'opponent in the final_9': 9, 'rudy coco_10': 10} | {'str_eq_3': 'str_eq', 'result_4': 'true', 'str_hop_2': 'str_hop', 'argmax_1': 'argmax', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'tournament_6': 'tournament', 'dakar_7': 'dakar', 'date_8': 'date', 'opponent in the final_9': 'opponent in the final', 'rudy coco_10': 'rudy coco'} | {'str_eq_3': [4], 'result_4': [], 'str_hop_2': [3], 'argmax_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'tournament_6': [0], 'dakar_7': [0], 'date_8': [1], 'opponent in the final_9': [2], 'rudy coco_10': [3]} | ['date', 'tournament', 'surface', 'opponent in the final', 'score'] | [['may 31 , 2004', 'tenerife', 'hard', 'jaymon crabb', '4 - 6 , 6 - 4 , 6 - 4'], ['july 26 , 2004', 'lomé', 'hard', 'adam thompson', '6 - 0 , 6 - 4'], ['october 17 , 2005', 'lagos', 'hard', 'arnaud segodo', '6 - 4 , 3 - 6 , 6 - 3'], ['july 31 , 2006', 'dakar', 'hard', 'valentin sanon', '6 - 1 , 1 - 6 , 6 - 1'], ['february 26 , 2007', 'benin city', 'hard', 'valentin sanon', '6 - 4 , 6 - 4'], ['july 30 , 2007', 'dakar', 'hard', 'rudy coco', '6 - 2 , 6 - 3'], ['august 6 , 2007', 'yaoundé', 'hard', 'bogdan leonte', '6 - 4 , 6 - 4']] |
list of australia one day international cricket records | https://en.wikipedia.org/wiki/List_of_Australia_One_Day_International_cricket_records | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-21100348-15.html.csv | superlative | adam gilchrist has played the most amount of matches of cricket in one day . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '3', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'matches'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; matches }'}, 'player'], 'result': 'adam gilchrist', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; matches } ; player }'}, 'adam gilchrist'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; matches } ; player } ; adam gilchrist } = true', 'tointer': 'select the row whose matches record of all rows is maximum . the player record of this row is adam gilchrist .'} | eq { hop { argmax { all_rows ; matches } ; player } ; adam gilchrist } = true | select the row whose matches record of all rows is maximum . the player record of this row is adam gilchrist . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'matches_5': 5, 'player_6': 6, 'adam gilchrist_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'matches_5': 'matches', 'player_6': 'player', 'adam gilchrist_7': 'adam gilchrist'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'matches_5': [0], 'player_6': [1], 'adam gilchrist_7': [2]} | ['rank', 'dismissals', 'player', 'matches', 'caught', 'stumped'] | [['1', '470', 'adam gilchrist', '287', '416', '54'], ['2', '233', 'ian healy', '168', '194', '39'], ['3', '142', 'brad haddin', '96', '133', '9'], ['4', '124', 'rodney marsh', '92', '120', '4'], ['5', '49', 'wayne b phillips', '48', '42', '7'], ['6', '44', 'mathew wade', '35', '39', '5'], ['7', '39', 'tim paine', '26', '35', '4'], ['8', '28', 'greg dyer', '23', '24', '4'], ['9', '23', 'tim zoehrer', '22', '21', '2'], ['10', '11', 'steve rixon', '6', '9', '2']] |
football records in spain | https://en.wikipedia.org/wiki/Football_records_in_Spain | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17937080-1.html.csv | unique | for the football records in spain , of the clubs 38 apps , the only one with 91 points is barcelona . | {'scope': 'subset', 'row': '8', 'col': '4', 'col_other': '2,5', 'criterion': 'equal', 'value': '91', 'subset': {'col': '5', 'criterion': 'equal', 'value': '38'}} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'apps', '38'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; apps ; 38 }', 'tointer': 'select the rows whose apps record is equal to 38 .'}, 'points', '91'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose apps record is equal to 38 . among these rows , select the rows whose points record is equal to 91 .', 'tostr': 'filter_eq { filter_eq { all_rows ; apps ; 38 } ; points ; 91 }'}], 'result': True, 'ind': 2, 'tostr': 'only { filter_eq { filter_eq { all_rows ; apps ; 38 } ; points ; 91 } }', 'tointer': 'select the rows whose apps record is equal to 38 . among these rows , select the rows whose points record is equal to 91 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_eq', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'apps', '38'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; apps ; 38 }', 'tointer': 'select the rows whose apps record is equal to 38 .'}, 'points', '91'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose apps record is equal to 38 . among these rows , select the rows whose points record is equal to 91 .', 'tostr': 'filter_eq { filter_eq { all_rows ; apps ; 38 } ; points ; 91 }'}, 'club'], 'result': 'barcelona', 'ind': 3, 'tostr': 'hop { filter_eq { filter_eq { all_rows ; apps ; 38 } ; points ; 91 } ; club }'}, 'barcelona'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { filter_eq { filter_eq { all_rows ; apps ; 38 } ; points ; 91 } ; club } ; barcelona }', 'tointer': 'the club record of this unqiue row is barcelona .'}], 'result': True, 'ind': 5, 'tostr': 'and { only { filter_eq { filter_eq { all_rows ; apps ; 38 } ; points ; 91 } } ; eq { hop { filter_eq { filter_eq { all_rows ; apps ; 38 } ; points ; 91 } ; club } ; barcelona } } = true', 'tointer': 'select the rows whose apps record is equal to 38 . among these rows , select the rows whose points record is equal to 91 . there is only one such row in the table . the club record of this unqiue row is barcelona .'} | and { only { filter_eq { filter_eq { all_rows ; apps ; 38 } ; points ; 91 } } ; eq { hop { filter_eq { filter_eq { all_rows ; apps ; 38 } ; points ; 91 } ; club } ; barcelona } } = true | select the rows whose apps record is equal to 38 . among these rows , select the rows whose points record is equal to 91 . there is only one such row in the table . the club record of this unqiue row is barcelona . | 8 | 6 | {'and_5': 5, 'result_6': 6, 'only_2': 2, 'filter_eq_1': 1, 'filter_eq_0': 0, 'all_rows_7': 7, 'apps_8': 8, '38_9': 9, 'points_10': 10, '91_11': 11, 'str_eq_4': 4, 'str_hop_3': 3, 'club_12': 12, 'barcelona_13': 13} | {'and_5': 'and', 'result_6': 'true', 'only_2': 'only', 'filter_eq_1': 'filter_eq', 'filter_eq_0': 'filter_eq', 'all_rows_7': 'all_rows', 'apps_8': 'apps', '38_9': '38', 'points_10': 'points', '91_11': '91', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'club_12': 'club', 'barcelona_13': 'barcelona'} | {'and_5': [6], 'result_6': [], 'only_2': [5], 'filter_eq_1': [2, 3], 'filter_eq_0': [1], 'all_rows_7': [0], 'apps_8': [0], '38_9': [0], 'points_10': [1], '91_11': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'club_12': [3], 'barcelona_13': [4]} | ['rank', 'club', 'season', 'points', 'apps'] | [['1', 'real madrid', '2011 / 12', '100', '38'], ['1', 'barcelona', '2012 / 13', '100', '38'], ['3', 'barcelona', '2009 / 10', '99', '38'], ['4', 'real madrid', '2009 / 10', '96', '38'], ['4', 'barcelona', '2010 / 11', '96', '38'], ['6', 'real madrid', '2010 / 11', '92', '38'], ['7', 'real madrid', '1996 / 97', '92', '42'], ['8', 'barcelona', '2011 / 12', '91', '38'], ['9', 'barcelona', '1996 / 97', '90', '42']] |
1994 arizona cardinals season | https://en.wikipedia.org/wiki/1994_Arizona_Cardinals_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16714815-1.html.csv | count | the arizona cardinals won 8 games in 1994 . | {'scope': 'all', 'criterion': 'equal', 'value': 'w', 'result': '8', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'result', 'w'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose result record fuzzily matches to w .', 'tostr': 'filter_eq { all_rows ; result ; w }'}], 'result': '8', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; result ; w } }', 'tointer': 'select the rows whose result record fuzzily matches to w . the number of such rows is 8 .'}, '8'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; result ; w } } ; 8 } = true', 'tointer': 'select the rows whose result record fuzzily matches to w . the number of such rows is 8 .'} | eq { count { filter_eq { all_rows ; result ; w } } ; 8 } = true | select the rows whose result record fuzzily matches to w . the number of such rows is 8 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'result_5': 5, 'w_6': 6, '8_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'result_5': 'result', 'w_6': 'w', '8_7': '8'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'result_5': [0], 'w_6': [0], '8_7': [2]} | ['week', 'date', 'opponent', 'result', 'attendance'] | [['1', 'september 4 , 1994', 'los angeles rams', 'l 14 - 12', '32969'], ['2', 'september 11 , 1994', 'new york giants', 'l 20 - 17', '60066'], ['3', 'september 18 , 1994', 'cleveland browns', 'l 32 - 0', '62818'], ['5', 'october 2 , 1994', 'minnesota vikings', 'w 17 - 7', '67950'], ['6', 'october 9 , 1994', 'dallas cowboys', 'l 38 - 3', '64518'], ['7', 'october 16 , 1994', 'washington redskins', 'w 19 - 16', '50019'], ['8', 'october 23 , 1994', 'dallas cowboys', 'l 28 - 21', '71023'], ['9', 'october 30 , 1994', 'pittsburgh steelers', 'w 20 - 17', '65690'], ['10', 'november 6 , 1994', 'philadelphia eagles', 'l 17 - 7', '64952'], ['11', 'november 13 , 1994', 'new york giants', 'w 10 - 9', '71719'], ['12', 'november 20 , 1994', 'philadelphia eagles', 'w 12 - 6', '62779'], ['13', 'november 27 , 1994', 'chicago bears', 'l 19 - 16', '65922'], ['14', 'december 4 , 1994', 'houston oilers', 'w 30 - 12', '39821'], ['15', 'december 11 , 1994', 'washington redskins', 'w 17 - 15', '53790'], ['16', 'december 18 , 1994', 'cincinnati bengals', 'w 28 - 7', '50110'], ['17', 'december 24 , 1994', 'atlanta falcons', 'l 10 - 6', '35311']] |
aguaclara | https://en.wikipedia.org/wiki/AguaClara | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-18268930-1.html.csv | superlative | the plant located at marcala , hon serves the largest population among plants designed by aguaclara . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '3', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'population served'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; population served }'}, 'location'], 'result': 'marcala , hon', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; population served } ; location }'}, 'marcala , hon'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; population served } ; location } ; marcala , hon } = true', 'tointer': 'select the row whose population served record of all rows is maximum . the location record of this row is marcala , hon .'} | eq { hop { argmax { all_rows ; population served } ; location } ; marcala , hon } = true | select the row whose population served record of all rows is maximum . the location record of this row is marcala , hon . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'population served_5': 5, 'location_6': 6, 'marcala , hon_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'population served_5': 'population served', 'location_6': 'location', 'marcala , hon_7': 'marcala , hon'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'population served_5': [0], 'location_6': [1], 'marcala , hon_7': [2]} | ['location', 'partner', 'construction start', 'inauguration date', 'population served', 'design flow ( lpm )'] | [['ojojona , hon', 'app', '2006 june', '2007 july', '2000', '375'], ['tamara , hon', 'app', '2008 january', '2008 june', '3500', '720'], ['marcala , hon', 'irwa', '2007 october', '2008 july', '9000', '1900'], ['4 comunidades , hon', 'app', '2008 october', '2009 march', '2000', '375'], ['agalteca , hon', 'app', '2009 october', '2010 june', '2200', '375'], ['marcala , hon expansion', 'app / acra', '2010 november', '2011 may', '6000', '1300'], ['alauca , el paraiso , hon', 'app', '2011 may', '2012 february', '3600', '720']] |
mont ventoux | https://en.wikipedia.org/wiki/Mont_Ventoux | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-162439-2.html.csv | majority | the mont ventoux race was in category 1 for the majority of years . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': '1', 'subset': None} | {'func': 'most_eq', 'args': ['all_rows', 'category', '1'], 'result': True, 'ind': 0, 'tointer': 'for the category records of all rows , most of them are equal to 1 .', 'tostr': 'most_eq { all_rows ; category ; 1 } = true'} | most_eq { all_rows ; category ; 1 } = true | for the category records of all rows , most of them are equal to 1 . | 1 | 1 | {'most_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'category_3': 3, '1_4': 4} | {'most_eq_0': 'most_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'category_3': 'category', '1_4': '1'} | {'most_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'category_3': [0], '1_4': [0]} | ['year', 'stage', 'category', 'start', 'finish', 'leader at the summit'] | [['1994', '15', 'hc', 'montpellier', 'carpentras', 'eros poli ( ita )'], ['1974', '12', '1', 'savines - le - lac', 'orange', 'gonzalo aja ( esp )'], ['1967', '13', '1', 'marseille', 'carpentras', 'julio jimãnez ( esp )'], ['1955', '11', '1', 'marseille', 'avignon', 'louison bobet ( fra )'], ['1952', '14', '1', 'aix - en - provence', 'avignon', 'jean robic ( fra )'], ['1951', '18', '1', 'montpellier', 'avignon', 'lucien lazarides ( fra )']] |
1960 los angeles rams season | https://en.wikipedia.org/wiki/1960_Los_Angeles_Rams_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11171998-1.html.csv | superlative | of the games played during the 1960 los angeles rams season , the lowest attendance against the baltimore colts was 57808 . | {'scope': 'subset', 'col_superlative': '5', 'row_superlative': '4', 'value_mentioned': 'yes', 'max_or_min': 'min', 'other_col': '3', 'subset': {'col': '3', 'criterion': 'equal', 'value': 'baltimore colts'}} | {'func': 'eq', 'args': [{'func': 'min', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', 'baltimore colts'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; opponent ; baltimore colts }', 'tointer': 'select the rows whose opponent record fuzzily matches to baltimore colts .'}, 'attendance'], 'result': '57808', 'ind': 1, 'tostr': 'min { filter_eq { all_rows ; opponent ; baltimore colts } ; attendance }', 'tointer': 'select the rows whose opponent record fuzzily matches to baltimore colts . the minimum attendance record of these rows is 57808 .'}, '57808'], 'result': True, 'ind': 2, 'tostr': 'eq { min { filter_eq { all_rows ; opponent ; baltimore colts } ; attendance } ; 57808 } = true', 'tointer': 'select the rows whose opponent record fuzzily matches to baltimore colts . the minimum attendance record of these rows is 57808 .'} | eq { min { filter_eq { all_rows ; opponent ; baltimore colts } ; attendance } ; 57808 } = true | select the rows whose opponent record fuzzily matches to baltimore colts . the minimum attendance record of these rows is 57808 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'min_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'opponent_5': 5, 'baltimore colts_6': 6, 'attendance_7': 7, '57808_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'min_1': 'min', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'opponent_5': 'opponent', 'baltimore colts_6': 'baltimore colts', 'attendance_7': 'attendance', '57808_8': '57808'} | {'eq_2': [3], 'result_3': [], 'min_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'opponent_5': [0], 'baltimore colts_6': [0], 'attendance_7': [1], '57808_8': [2]} | ['week', 'date', 'opponent', 'result', 'attendance'] | [['1', 'september 23 , 1960', 'st louis cardinals', 'l 43 - 21', '47448'], ['2', 'october 2 , 1960', 'san francisco 49ers', 'l 13 - 9', '53633'], ['3', 'october 9 , 1960', 'chicago bears', 'l 34 - 27', '47776'], ['4', 'october 16 , 1960', 'baltimore colts', 'l 31 - 17', '57808'], ['5', 'october 23 , 1960', 'chicago bears', 't 24 - 24', '63438'], ['6', 'october 30 , 1960', 'detroit lions', 'w 48 - 35', '53295'], ['7', 'november 6 , 1960', 'dallas cowboys', 'w 38 - 13', '16000'], ['8', 'november 13 , 1960', 'detroit lions', 'l 12 - 10', '54019'], ['9', 'november 20 , 1960', 'green bay packers', 'w 33 - 31', '35763'], ['11', 'december 4 , 1960', 'san francisco 49ers', 'l 23 - 7', '77254'], ['12', 'december 11 , 1960', 'baltimore colts', 'w 10 - 3', '75461'], ['13', 'december 17 , 1960', 'green bay packers', 'l 35 - 21', '53445']] |
rowing at the 2008 summer olympics - women 's coxless pair | https://en.wikipedia.org/wiki/Rowing_at_the_2008_Summer_Olympics_%E2%80%93_Women%27s_coxless_pair | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18662697-3.html.csv | ordinal | china had the 2nd longest rowing time at the 2008 summer olympics women 's coxless pair competition . | {'row': '3', 'col': '4', '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', 'time', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; time ; 2 }'}, 'country'], 'result': 'china', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; time ; 2 } ; country }'}, 'china'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; time ; 2 } ; country } ; china } = true', 'tointer': 'select the row whose time record of all rows is 2nd maximum . the country record of this row is china .'} | eq { hop { nth_argmax { all_rows ; time ; 2 } ; country } ; china } = true | select the row whose time record of all rows is 2nd maximum . the country record of this row is china . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'time_5': 5, '2_6': 6, 'country_7': 7, 'china_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', 'time_5': 'time', '2_6': '2', 'country_7': 'country', 'china_8': 'china'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'time_5': [0], '2_6': [0], 'country_7': [1], 'china_8': [2]} | ['rank', 'rowers', 'country', 'time', 'notes'] | [['1', 'yuliya bichyk , natallia helakh', 'belarus', '7:24.47', 'fa'], ['2', 'juliette haigh , nicola coles', 'new zealand', '7:31.45', 'r'], ['3', 'wu you , gao yulan', 'china', '7:32.50', 'r'], ['4', 'kim crow , sarah cook', 'australia', '7:44.04', 'r'], ['5', 'zoe hoskins , sabrina kolker', 'canada', 'boat under weight', 'r']] |
asymmetric digital subscriber line | https://en.wikipedia.org/wiki/Asymmetric_digital_subscriber_line | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18934536-1.html.csv | superlative | the adsl2 + + version of the asymmetric digital subscriber line has the highest upstream rate . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '12', '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', 'upstream rate'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; upstream rate }'}, 'version'], 'result': 'adsl2 + +', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; upstream rate } ; version }'}, 'adsl2 + +'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; upstream rate } ; version } ; adsl2 + + } = true', 'tointer': 'select the row whose upstream rate record of all rows is maximum . the version record of this row is adsl2 + + .'} | eq { hop { argmax { all_rows ; upstream rate } ; version } ; adsl2 + + } = true | select the row whose upstream rate record of all rows is maximum . the version record of this row is adsl2 + + . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'upstream rate_5': 5, 'version_6': 6, 'adsl2 + +_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'upstream rate_5': 'upstream rate', 'version_6': 'version', 'adsl2 + +_7': 'adsl2 + +'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'upstream rate_5': [0], 'version_6': [1], 'adsl2 + +_7': [2]} | ['version', 'standard name', 'common name', 'downstream rate', 'upstream rate'] | [['adsl', 'ansi t1 .413 - 1998 issue 2', 'adsl', '08.0 8.0 mbit / s', '1.0 mbit / s'], ['adsl', 'itu g992 .1', 'adsl ( gdmt )', '8.0 mbit / s', '1.3 mbit / s'], ['adsl', 'itu g992 .1 annex a', 'adsl over pots', '12.0 mbit / s', '1.3 mbit / s'], ['adsl', 'itu g992 .1 annex b', 'adsl over isdn', '12.0 mbit / s', '1.8 mbit / s'], ['adsl', 'itu g992 .2', 'adsl lite ( glite )', '01.5 1.5 mbit / s', '0.5 mbit / s'], ['adsl2', 'itu g992 .3', 'adsl2', '12.0 mbit / s', '1.3 mbit / s'], ['adsl2', 'itu g992 .3 annex j', 'adsl2', '12.0 mbit / s', '3.5 mbit / s'], ['adsl2', 'itu g992 .3 annex l', 're - adsl2', '05.0 5.0 mbit / s', '0.8 mbit / s'], ['adsl2', 'itu g992 .4', 'splitterless adsl2', '01.5 1.5 mbit / s', '0.5 mbit / s'], ['adsl2 +', 'itu g992 .5', 'adsl2 +', '20.0 mbit / s', '1.1 mbit / s'], ['adsl2 +', 'itu g992 .5 annex m', 'adsl2 + m', '24.0 mbit / s', '3.3 mbit / s'], ['adsl2 + +', '( up to 3.75 mhz )', 'adsl4', '52.0 mbit / s', '5.0 mbit / s']] |
alun jones ( tennis ) | https://en.wikipedia.org/wiki/Alun_Jones_%28tennis%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12762499-2.html.csv | count | alun jones played a total of four tournaments on a hard surface . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'hard', 'result': '4', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'surface', 'hard'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose surface record fuzzily matches to hard .', 'tostr': 'filter_eq { all_rows ; surface ; hard }'}], 'result': '4', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; surface ; hard } }', 'tointer': 'select the rows whose surface record fuzzily matches to hard . the number of such rows is 4 .'}, '4'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; surface ; hard } } ; 4 } = true', 'tointer': 'select the rows whose surface record fuzzily matches to hard . the number of such rows is 4 .'} | eq { count { filter_eq { all_rows ; surface ; hard } } ; 4 } = true | select the rows whose surface record fuzzily matches to hard . the number of such rows is 4 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'surface_5': 5, 'hard_6': 6, '4_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'surface_5': 'surface', 'hard_6': 'hard', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'surface_5': [0], 'hard_6': [0], '4_7': [2]} | ['date', 'tournament', 'surface', 'opponent in the final', 'score'] | [['19 november 2002', 'berri', 'grass', 'paul baccanello', '6 - 2 , 6 - 2'], ['2 may 2005', 'phuket', 'hard', 'patrick schmolzer', '6 - 1 , 6 - 1'], ['16 may 2005', 'phuket', 'hard', 'phillip king', '6 - 3 , 6 - 1'], ['30 may 2005', 'maspalomas', 'clay', 'ignasi villacampa', '6 - 1 , 6 - 2'], ['12 september 2006', 'hope island', 'hard', 'robert smeets', '6 - 3 , 7 - 6'], ['24 october 2006', 'mildura', 'grass', 'samuel groth', '3 - 6 , 7 - 5 , 6 - 4'], ['31 october 2006', 'berri', 'grass', 'shannon nettle', '6 - 4 , 6 - 3'], ['20 march 2007', 'lyneham', 'clay', 'vasilis mazarakis', '3 - 6 , 6 - 1 , 6 - 3'], ['10 july 2007', 'felixstowe', 'grass', 'nicolas tourte', '6 - 3 , 6 - 4'], ['23 july 2007', 'nottingham', 'grass', 'aisam - ul - haq qureshi', '6 - 3 , 4 - 6 , 6 - 4'], ['9 december 2007', 'burnie', 'hard', 'rameez junaid', '6 - 0 , 6 - 1']] |
xxl ( mylène farmer song ) | https://en.wikipedia.org/wiki/XXL_%28Myl%C3%A8ne_Farmer_song%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14562754-1.html.csv | superlative | the uk remix of the mylène farmer song " xxl " is the longest version of the song at 9:00 . | {'scope': 'all', 'col_superlative': '2', 'row_superlative': '11', 'value_mentioned': 'yes', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'max', 'args': ['all_rows', 'length'], 'result': '9:00', 'ind': 0, 'tostr': 'max { all_rows ; length }', 'tointer': 'the maximum length record of all rows is 9:00 .'}, '9:00'], 'result': True, 'ind': 1, 'tostr': 'eq { max { all_rows ; length } ; 9:00 }', 'tointer': 'the maximum length record of all rows is 9:00 .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'length'], 'result': None, 'ind': 2, 'tostr': 'argmax { all_rows ; length }'}, 'version'], 'result': 'uk remix', 'ind': 3, 'tostr': 'hop { argmax { all_rows ; length } ; version }'}, 'uk remix'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { argmax { all_rows ; length } ; version } ; uk remix }', 'tointer': 'the version record of the row with superlative length record is uk remix .'}], 'result': True, 'ind': 5, 'tostr': 'and { eq { max { all_rows ; length } ; 9:00 } ; eq { hop { argmax { all_rows ; length } ; version } ; uk remix } } = true', 'tointer': 'the maximum length record of all rows is 9:00 . the version record of the row with superlative length record is uk remix .'} | and { eq { max { all_rows ; length } ; 9:00 } ; eq { hop { argmax { all_rows ; length } ; version } ; uk remix } } = true | the maximum length record of all rows is 9:00 . the version record of the row with superlative length record is uk remix . | 6 | 6 | {'and_5': 5, 'result_6': 6, 'eq_1': 1, 'max_0': 0, 'all_rows_7': 7, 'length_8': 8, '9:00_9': 9, 'str_eq_4': 4, 'str_hop_3': 3, 'argmax_2': 2, 'all_rows_10': 10, 'length_11': 11, 'version_12': 12, 'uk remix_13': 13} | {'and_5': 'and', 'result_6': 'true', 'eq_1': 'eq', 'max_0': 'max', 'all_rows_7': 'all_rows', 'length_8': 'length', '9:00_9': '9:00', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'argmax_2': 'argmax', 'all_rows_10': 'all_rows', 'length_11': 'length', 'version_12': 'version', 'uk remix_13': 'uk remix'} | {'and_5': [6], 'result_6': [], 'eq_1': [5], 'max_0': [1], 'all_rows_7': [0], 'length_8': [0], '9:00_9': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'argmax_2': [3], 'all_rows_10': [2], 'length_11': [2], 'version_12': [3], 'uk remix_13': [4]} | ['version', 'length', 'album', 'remixed by', 'year'] | [['album version', '4:45', 'anamorphosée , les mots', '-', '1995'], ['single version', '4:23', '-', 'laurent boutonnat', '1995'], ['no voice remix edit', '4:20', '-', 'laurent boutonnat , bertrand chtenet', '1995'], ['extra large remix', '5:02', '-', 'laurent boutonnat , bertrand chtenet', '1995'], ['distorded dance mix', '5:20', '-', 'laurent boutonnat , bertrand chtenet', '1995'], ['new remix edit', '4:25', '-', 'laurent boutonnat , bertrand chtenet', '1995'], ['single dance mix', '4:25', '-', 'laurent boutonnat , bertrand chtenet', '1995'], ['new remix edit ( germany )', '4:43', '-', 'laurent boutonnat , bertrand chtenet', '1995'], ['german radio edit', '3:54', '-', 'laurent boutonnat , bertrand chtenet', '1995'], ['music video', '4:22', 'music videos ii , music videos ii & iii', '-', '1995'], ['uk remix', '9:00', '-', 'richard dekkard', '1996'], ['live version ( recorded in 1996 )', '7:25', 'live à bercy', '-', '1996'], ['jxl remix', '6:06', 'remixes', 'junkie xl', '2003'], ['live version ( recorded in 2006 )', '5:28', "avant que l'ombre", '-', '2006'], ['live version ( recorded in 2009 )', '4:30', 'n degree5 on tour', '-', '2009']] |
bmw 3 series compact | https://en.wikipedia.org/wiki/BMW_3_Series_Compact | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1180976-2.html.csv | ordinal | the 320td ( diesel ) bmw 3 series compact model has the second lowest torque . | {'row': '5', 'col': '5', 'order': '2', 'col_other': '1', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'torque', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; torque ; 2 }'}, 'model'], 'result': '320td ( diesel )', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; torque ; 2 } ; model }'}, '320td ( diesel )'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; torque ; 2 } ; model } ; 320td ( diesel ) } = true', 'tointer': 'select the row whose torque record of all rows is 2nd minimum . the model record of this row is 320td ( diesel ) .'} | eq { hop { nth_argmin { all_rows ; torque ; 2 } ; model } ; 320td ( diesel ) } = true | select the row whose torque record of all rows is 2nd minimum . the model record of this row is 320td ( diesel ) . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'torque_5': 5, '2_6': 6, 'model_7': 7, '320td (diesel)_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', 'torque_5': 'torque', '2_6': '2', 'model_7': 'model', '320td (diesel)_8': '320td ( diesel )'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'torque_5': [0], '2_6': [0], 'model_7': [1], '320td (diesel)_8': [2]} | ['model', 'years', 'engine code', 'power', 'torque'] | [['316ti', '2001 - 2004', 'n42b18 / n46b18', '5500', '3750'], ['318ti', '2001 - 2004', 'n42b20 / n46b20', '6000', '3750'], ['325ti', '2001 - 2004', 'm54b25', '6000', '3500'], ['318td ( diesel )', '2003 - 2004', 'm47d20', '4000', '1750'], ['320td ( diesel )', '2001 - 2004', 'm47d20', '4000', '2000']] |
1971 u.s. open ( golf ) | https://en.wikipedia.org/wiki/1971_U.S._Open_%28golf%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17245565-8.html.csv | count | 4 players in the 1971 us open shot 5 over par . | {'scope': 'all', 'criterion': 'equal', 'value': '+5', 'result': '4', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'to par', '+5'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose to par record fuzzily matches to +5 .', 'tostr': 'filter_eq { all_rows ; to par ; +5 }'}], 'result': '4', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; to par ; +5 } }', 'tointer': 'select the rows whose to par record fuzzily matches to +5 . the number of such rows is 4 .'}, '4'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; to par ; +5 } } ; 4 } = true', 'tointer': 'select the rows whose to par record fuzzily matches to +5 . the number of such rows is 4 .'} | eq { count { filter_eq { all_rows ; to par ; +5 } } ; 4 } = true | select the rows whose to par record fuzzily matches to +5 . the number of such rows is 4 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'to par_5': 5, '+5_6': 6, '4_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'to par_5': 'to par', '+5_6': '+5', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'to par_5': [0], '+5_6': [0], '4_7': [2]} | ['place', 'player', 'country', 'score', 'to par', 'money'] | [['t1', 'lee trevino', 'united states', '70 + 72 + 69 + 69 = 280', 'e', 'playoff'], ['t1', 'jack nicklaus', 'united states', '69 + 72 + 68 + 71 = 280', 'e', 'playoff'], ['t3', 'jim colbert', 'united states', '69 + 69 + 73 + 71 = 282', '+ 2', '9000'], ['t3', 'bob rosburg', 'united states', '71 + 72 + 70 + 69 = 282', '+ 2', '9000'], ['t5', 'george archer', 'united states', '71 + 70 + 70 + 72 = 283', '+ 3', '6500'], ['t5', 'johnny miller', 'united states', '70 + 73 + 70 + 70 = 283', '+ 3', '6500'], ['t5', 'jim simons ( a )', 'united states', '71 + 71 + 65 + 76 = 283', '+ 3', '0'], ['8', 'raymond floyd', 'united states', '71 + 75 + 67 + 71 = 284', '+ 4', '5000'], ['t9', 'gay brewer', 'united states', '70 + 70 + 73 + 72 = 285', '+ 5', '3325'], ['t9', 'larry hinson', 'united states', '71 + 71 + 70 + 73 = 285', '+ 5', '3325'], ['t9', 'bobby nichols', 'united states', '69 + 72 + 69 + 75 = 285', '+ 5', '3325'], ['t9', 'bert yancey', 'united states', '75 + 69 + 69 + 72 = 285', '+ 5', '3325']] |
2008 - 09 cardiff city f.c. season | https://en.wikipedia.org/wiki/2008%E2%80%9309_Cardiff_City_F.C._season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17596418-4.html.csv | majority | for cardiff city f.c. , the majority of the transfers acquired in the 2008 - 09 season had contracts that ended in 2010 . | {'scope': 'all', 'col': '6', 'most_or_all': 'most', 'criterion': 'equal', 'value': '2010', 'subset': None} | {'func': 'most_eq', 'args': ['all_rows', 'ends', '2010'], 'result': True, 'ind': 0, 'tointer': 'for the ends records of all rows , most of them are equal to 2010 .', 'tostr': 'most_eq { all_rows ; ends ; 2010 } = true'} | most_eq { all_rows ; ends ; 2010 } = true | for the ends records of all rows , most of them are equal to 2010 . | 1 | 1 | {'most_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'ends_3': 3, '2010_4': 4} | {'most_eq_0': 'most_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'ends_3': 'ends', '2010_4': '2010'} | {'most_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'ends_3': [0], '2010_4': [0]} | ['name', 'country', 'type', 'moving from', 'transfer window', 'ends', 'transfer fee', 'source'] | [['comminges', 'gpe', 'free transfer', 'swindon town', 'summer', '2010', 'free', 'bbc sport'], ['kennedy', 'irl', 'free transfer', 'crystal palace', 'summer', '2010', 'free', 'bbc sport'], ['enckelman', 'fin', 'free transfer', 'blackburn rovers', 'summer', '2010', 'free', 'bbc sport'], ['dennehy', 'irl', 'free transfer', 'everton', 'summer', '2010', 'free', 'bbc sport'], ['mccormack', 'sco', 'transfer', 'motherwell', 'summer', '2010', '120000', 'bbc sport'], ['bothroyd', 'eng', 'transfer', 'wolverhampton wanderers', 'summer', '2011', '350000', 'bbc sport'], ['gyepes', 'hun', 'transfer', 'northampton town', 'summer', '2010', '200000', 'bbc sport'], ['burke', 'sco', 'free transfer', 'rangers', 'winter', '2011', 'free', 'bbc sport']] |
ireland in the eurovision song contest 1990 | https://en.wikipedia.org/wiki/Ireland_in_the_Eurovision_Song_Contest_1990 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16729685-1.html.csv | superlative | liam reilly 's " somewhere in europe " won the 1990 ireland in the eurovision song contest . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '8', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '2,3', 'subset': None} | {'func': 'and', 'args': [{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmin', 'args': ['all_rows', 'place'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; place }'}, 'artist'], 'result': 'liam reilly', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; place } ; artist }'}, 'liam reilly'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmin { all_rows ; place } ; artist } ; liam reilly }', 'tointer': 'select the row whose place record of all rows is minimum . the artist record of this row is liam reilly .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmin', 'args': ['all_rows', 'place'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; place }'}, 'song'], 'result': 'somewhere in europe', 'ind': 3, 'tostr': 'hop { argmin { all_rows ; place } ; song }'}, 'somewhere in europe'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { argmin { all_rows ; place } ; song } ; somewhere in europe }', 'tointer': 'the song record of this row is somewhere in europe .'}], 'result': True, 'ind': 5, 'tostr': 'and { eq { hop { argmin { all_rows ; place } ; artist } ; liam reilly } ; eq { hop { argmin { all_rows ; place } ; song } ; somewhere in europe } } = true', 'tointer': 'select the row whose place record of all rows is minimum . the artist record of this row is liam reilly . the song record of this row is somewhere in europe .'} | and { eq { hop { argmin { all_rows ; place } ; artist } ; liam reilly } ; eq { hop { argmin { all_rows ; place } ; song } ; somewhere in europe } } = true | select the row whose place record of all rows is minimum . the artist record of this row is liam reilly . the song record of this row is somewhere in europe . | 7 | 6 | {'and_5': 5, 'result_6': 6, 'str_eq_2': 2, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_7': 7, 'place_8': 8, 'artist_9': 9, 'liam reilly_10': 10, 'str_eq_4': 4, 'str_hop_3': 3, 'song_11': 11, 'somewhere in europe_12': 12} | {'and_5': 'and', 'result_6': 'true', 'str_eq_2': 'str_eq', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_7': 'all_rows', 'place_8': 'place', 'artist_9': 'artist', 'liam reilly_10': 'liam reilly', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'song_11': 'song', 'somewhere in europe_12': 'somewhere in europe'} | {'and_5': [6], 'result_6': [], 'str_eq_2': [5], 'str_hop_1': [2], 'argmin_0': [1, 3], 'all_rows_7': [0], 'place_8': [0], 'artist_9': [1], 'liam reilly_10': [2], 'str_eq_4': [5], 'str_hop_3': [4], 'song_11': [3], 'somewhere in europe_12': [4]} | ['draw', 'artist', 'song', 'points', 'place'] | [['1', 'the memories', 'if it means losing you', '57', '8th'], ['2', 'ann breen', 'oh , darling', '80', '4th'], ['3', 'fran meen', 'say that you love me', '66', '6th'], ['4', 'dreams', "sin sin ( that 's that )", '73', '5th'], ['5', 'connor stevens', 'count on me', '88', '3rd'], ['6', 'linda martin and friends', 'all the people in the world', '105', '2nd'], ['7', 'maggie toal', 'feed him with love', '61', '7th'], ['8', 'liam reilly', 'somewhere in europe', '130', '1st']] |
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