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1928 vfl season | https://en.wikipedia.org/wiki/1928_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10766119-9.html.csv | ordinal | victoria park venue recorded the highest crowd participation during the 1928 vfl season . | {'row': '2', 'col': '6', 'order': '1', 'col_other': '5', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'crowd', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; crowd ; 1 }'}, 'venue'], 'result': 'victoria park', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; crowd ; 1 } ; venue }'}, 'victoria park'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; crowd ; 1 } ; venue } ; victoria park } = true', 'tointer': 'select the row whose crowd record of all rows is 1st maximum . the venue record of this row is victoria park .'} | eq { hop { nth_argmax { all_rows ; crowd ; 1 } ; venue } ; victoria park } = true | select the row whose crowd record of all rows is 1st maximum . the venue record of this row is victoria park . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'crowd_5': 5, '1_6': 6, 'venue_7': 7, 'victoria park_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'crowd_5': 'crowd', '1_6': '1', 'venue_7': 'venue', 'victoria park_8': 'victoria park'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'crowd_5': [0], '1_6': [0], 'venue_7': [1], 'victoria park_8': [2]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['richmond', '21.16 ( 142 )', 'south melbourne', '9.12 ( 66 )', 'punt road oval', '21000', '9 june 1928'], ['collingwood', '13.14 ( 92 )', 'melbourne', '11.14 ( 80 )', 'victoria park', '27000', '9 june 1928'], ['carlton', '9.7 ( 61 )', 'footscray', '8.14 ( 62 )', 'princes park', '25000', '9 june 1928'], ['st kilda', '14.13 ( 97 )', 'geelong', '10.6 ( 66 )', 'junction oval', '17000', '9 june 1928'], ['hawthorn', '10.12 ( 72 )', 'fitzroy', '15.16 ( 106 )', 'glenferrie oval', '8000', '9 june 1928'], ['north melbourne', '9.5 ( 59 )', 'essendon', '10.10 ( 70 )', 'arden street oval', '13000', '9 june 1928']] |
ana timotić | https://en.wikipedia.org/wiki/Ana_Timoti%C4%87 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11326124-3.html.csv | count | for tournaments that ana timotić participated in , for the ones in 2005 , there were two times where she lost . | {'scope': 'subset', 'criterion': 'equal', 'value': 'loss', 'result': '2', 'col': '8', 'subset': {'col': '1', 'criterion': 'equal', 'value': '2005'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'edition', '2005'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; edition ; 2005 }', 'tointer': 'select the rows whose edition record is equal to 2005 .'}, 'outcome', 'loss'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose edition record is equal to 2005 . among these rows , select the rows whose outcome record fuzzily matches to loss .', 'tostr': 'filter_eq { filter_eq { all_rows ; edition ; 2005 } ; outcome ; loss }'}], 'result': '2', 'ind': 2, 'tostr': 'count { filter_eq { filter_eq { all_rows ; edition ; 2005 } ; outcome ; loss } }', 'tointer': 'select the rows whose edition record is equal to 2005 . among these rows , select the rows whose outcome record fuzzily matches to loss . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_eq { filter_eq { all_rows ; edition ; 2005 } ; outcome ; loss } } ; 2 } = true', 'tointer': 'select the rows whose edition record is equal to 2005 . among these rows , select the rows whose outcome record fuzzily matches to loss . the number of such rows is 2 .'} | eq { count { filter_eq { filter_eq { all_rows ; edition ; 2005 } ; outcome ; loss } } ; 2 } = true | select the rows whose edition record is equal to 2005 . among these rows , select the rows whose outcome record fuzzily matches to loss . the number of such rows is 2 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_str_eq_1': 1, 'filter_eq_0': 0, 'all_rows_5': 5, 'edition_6': 6, '2005_7': 7, 'outcome_8': 8, 'loss_9': 9, '2_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_str_eq_1': 'filter_str_eq', 'filter_eq_0': 'filter_eq', 'all_rows_5': 'all_rows', 'edition_6': 'edition', '2005_7': '2005', 'outcome_8': 'outcome', 'loss_9': 'loss', '2_10': '2'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_str_eq_1': [2], 'filter_eq_0': [1], 'all_rows_5': [0], 'edition_6': [0], '2005_7': [0], 'outcome_8': [1], 'loss_9': [1], '2_10': [3]} | ['edition', 'zone', 'round', 'date', 'against', 'surface', 'opponent', 'outcome', 'result'] | [['2005', 'europe / africa group i c', '1r', '21 april 2005', 'slovenia', 'clay', 'tina pisnik', 'loss', '6 - 0 , 6 - 1'], ['2005', 'europe / africa group i c', '2r', '22 april 2005', 'great britain', 'clay', 'elena baltacha', 'win', '5 - 7 , 6 - 3 , 6 - 0'], ['2005', 'europe / africa group play - off', 'semifinal', '23 april 2005', 'israel', 'clay', "shahar pe'er", 'loss', '6 - 4 , 4 - 6 , 6 - 3'], ['2006', 'europe / africa group i b', '1r', '18 april 2006', 'slovenia', 'clay', 'polona reberšak', 'loss', '6 - 3 , 6 - 2'], ['2006', 'europe / africa group i b', '3r', '20 april 2006', 'denmark', 'clay', 'eva dyrberg', 'win', '2 - 6 , 6 - 4 , 6 - 4'], ['2006', 'europe / africa group i', 'semifinal', '22 april 2006', 'israel', 'clay', 'anna smashnova', 'win', '5 - 7 , 4 - 5 ret'], ['2007', 'europe / africa group i c', '1r', '20 april 2007', 'slovenia', 'clay', 'maša zec peškirič', 'loss', '6 - 3 , 4 - 6 , 6 - 0'], ['2007', 'europe / africa group i c', 'semifinal', '21 april 2007', 'romania', 'clay', 'mădălina gojnea', 'loss', '1 - 6 , 6 - 4 , 6 - 3'], ['2007', 'world group ii play - offs', 'quarterfinal', '14 july 2007', 'slovakia', 'clay', 'daniela hantuchová', 'loss', '6 - 1 , 6 - 2']] |
1987 world rhythmic gymnastics championships | https://en.wikipedia.org/wiki/1987_World_Rhythmic_Gymnastics_Championships | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18170681-5.html.csv | aggregation | the average total score for 1987 world rhythmic gymnastics championships is 19.71 . | {'scope': 'all', 'col': '5', 'type': 'average', 'result': '19.71', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'total'], 'result': '19.71', 'ind': 0, 'tostr': 'avg { all_rows ; total }'}, '19.71'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; total } ; 19.71 } = true', 'tointer': 'the average of the total record of all rows is 19.71 .'} | round_eq { avg { all_rows ; total } ; 19.71 } = true | the average of the total record of all rows is 19.71 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'total_4': 4, '19.71_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'total_4': 'total', '19.71_5': '19.71'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'total_4': [0], '19.71_5': [1]} | ['place', 'name', 'all around', 'rope', 'total'] | [['1', 'adriana dunavska', '10.000', '10.000', '20.000'], ['1', 'bianka panova', '10.000', '10.000', '20.000'], ['3', 'anna kotchneva', '9.900', '9.900', '19.800'], ['3', 'marina lobatch', '9.900', '9.900', '19.800'], ['5', 'florentina butaru', '9.800', '9.900', '19.700'], ['6', 'milena reljin', '9.800', '9.750', '19.550'], ['7', 'andrea sinko', '9.700', '9.800', '19.500'], ['8', 'maria isabel lloret', '9.700', '9.700', '19.400']] |
1990 - 91 seattle supersonics season | https://en.wikipedia.org/wiki/1990%E2%80%9391_Seattle_SuperSonics_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17382360-6.html.csv | majority | g payton was the player with the high assists in most of the games . | {'scope': 'all', 'col': '7', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'g payton', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'high assists', 'g payton'], 'result': True, 'ind': 0, 'tointer': 'for the high assists records of all rows , most of them fuzzily match to g payton .', 'tostr': 'most_eq { all_rows ; high assists ; g payton } = true'} | most_eq { all_rows ; high assists ; g payton } = true | for the high assists records of all rows , most of them fuzzily match to g payton . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'high assists_3': 3, 'g payton_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'high assists_3': 'high assists', 'g payton_4': 'g payton'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'high assists_3': [0], 'g payton_4': [0]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record'] | [['28', 'january 3', 'philadelphia 76ers', 'w 127 - 99', 'd mckey ( 24 )', 'm cage ( 12 )', 'g payton ( 11 )', 'seattle center coliseum 13048', '13 - 15'], ['29', 'january 4', 'miami heat', 'w 112 - 86', 's threatt ( 30 )', 'm cage ( 13 )', 'g payton ( 12 )', 'seattle center coliseum 12074', '14 - 15'], ['30', 'january 6', 'portland trail blazers', 'l 111 - 114', 's kemp ( 25 )', 's kemp ( 9 )', 'g payton ( 7 )', 'memorial coliseum 12884', '14 - 16'], ['31', 'january 8', 'los angeles lakers', 'w 96 - 88', 'd mckey ( 29 )', 'o polynice ( 11 )', 'n mcmillan ( 10 )', 'seattle center coliseum 14441', '15 - 16'], ['32', 'january 10', 'golden state warriors', 'l 103 - 113', 'd mckey ( 19 )', 's kemp , o polynice ( 12 )', 'n mcmillan ( 7 )', 'seattle center coliseum 10813', '15 - 17'], ['33', 'january 12', 'sacramento kings', 'l 85 - 101', 'd mckey ( 20 )', 'o polynice ( 14 )', 'g payton ( 9 )', 'arco arena 17014', '15 - 18'], ['34', 'january 15', 'denver nuggets', 'w 146 - 99', 'd barros , d ellis ( 22 )', 's kemp ( 12 )', 'n mcmillan ( 9 )', 'seattle center coliseum 9618', '16 - 18'], ['35', 'january 18', 'los angeles lakers', 'l 96 - 105', 'd mckey ( 24 )', 's kemp ( 8 )', 'g payton ( 11 )', 'great western forum 17505', '16 - 19'], ['36', 'january 19', 'washington bullets', 'w 111 - 89', 'o polynice ( 27 )', 's kemp ( 13 )', 'n mcmillan ( 8 )', 'seattle center coliseum 13369', '17 - 19'], ['37', 'january 22', 'milwaukee bucks', 'w 132 - 101', 'e johnson ( 29 )', 'm cage ( 9 )', 'g payton ( 9 )', 'seattle center coliseum 9469', '18 - 19'], ['38', 'january 25', 'phoenix suns', 'l 113 - 128', 'e johnson ( 25 )', 's kemp ( 13 )', 'n mcmillan ( 7 )', 'arizona veterans memorial coliseum 14487', '18 - 20'], ['39', 'january 26', 'atlanta hawks', 'w 103 - 102', 'd mckey ( 23 )', 'd mckey ( 8 )', 'n mcmillan , g payton ( 9 )', 'seattle center coliseum 12792', '19 - 20'], ['40', 'january 28', 'san antonio spurs', 'l 107 - 119', 'e johnson ( 21 )', 'd mckey ( 14 )', 'g payton ( 11 )', 'hemisfair arena 15908', '19 - 21'], ['41', 'january 29', 'dallas mavericks', 'l 112 - 117', 'd mckey ( 24 )', 'o polynice ( 6 )', 'n mcmillan ( 8 )', 'reunion arena 15820', '19 - 22'], ['42', 'january 31', 'houston rockets', 'w 97 - 94', 's threatt ( 18 )', 's kemp ( 17 )', 'd mckey , d mckey ( 6 )', 'the summit 14659', '20 - 22']] |
greater dhaka area | https://en.wikipedia.org/wiki/Greater_Dhaka_Area | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-24027047-1.html.csv | aggregation | the average area in square kilometers of administrative division in the greater dhaka area is 535.74 . | {'scope': 'all', 'col': '2', 'type': 'average', 'result': '535.74', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'area ( km square ) 2011'], 'result': '535.74', 'ind': 0, 'tostr': 'avg { all_rows ; area ( km square ) 2011 }'}, '535.74'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; area ( km square ) 2011 } ; 535.74 } = true', 'tointer': 'the average of the area ( km square ) 2011 record of all rows is 535.74 .'} | round_eq { avg { all_rows ; area ( km square ) 2011 } ; 535.74 } = true | the average of the area ( km square ) 2011 record of all rows is 535.74 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'area (km square) 2011_4': 4, '535.74_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'area (km square) 2011_4': 'area ( km square ) 2011', '535.74_5': '535.74'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'area (km square) 2011_4': [0], '535.74_5': [1]} | ['administrative division', 'area ( km square ) 2011', 'population 2001 census ( adjusted )', 'population 2011 census ( adjusted )', 'population density ( / km square 2011 )'] | [['dhaka district', '1463.6', '9036647', '12517361', '8552.4'], ['savar upazila', '282.11', '629695', '1442885', '5114.6'], ['keraniganj upazila', '166.82', '649373', '824538', '4942.68'], ['narayanganj district', '684.37', '2300514', '3074078', '4491.8'], ['narayanganj sadar upazila', '100.74', '946205', '1381796', '13716.5'], ['bandar upazila', '54.39', '267021', '327149', '6014.8'], ['rupganj upazila', '176.48', '423135', '558192', '3162.9'], ['gazipur district', '1806.36', '2143200', '3548115', '1964.2'], ['gazipur sadar upazila', '457.67', '925454', '1899575', '4150.5'], ['kaliakair upazila', '314.13', '278967', '503976', '1604.3'], ['narsingdi district', '1150.14', '1983499', '2314899', '2012.7'], ['narsingdi sadar upazila', '213.43', '606474', '737362', '3454.8'], ['palash upazila', '94.43', '198106', '221979', '2350.7']] |
2007 new orleans voodoo season | https://en.wikipedia.org/wiki/2007_New_Orleans_VooDoo_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11783481-3.html.csv | unique | andy kelly was the only player in the 2007 new orleans voodoo season that recorded 0 yards . | {'scope': 'all', 'row': '6', 'col': '3', 'col_other': '1', 'criterion': 'equal', 'value': '0', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'yards', '0'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose yards record is equal to 0 .', 'tostr': 'filter_eq { all_rows ; yards ; 0 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; yards ; 0 } }', 'tointer': 'select the rows whose yards 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', 'yards', '0'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose yards record is equal to 0 .', 'tostr': 'filter_eq { all_rows ; yards ; 0 }'}, 'player'], 'result': 'andy kelly', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; yards ; 0 } ; player }'}, 'andy kelly'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; yards ; 0 } ; player } ; andy kelly }', 'tointer': 'the player record of this unqiue row is andy kelly .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; yards ; 0 } } ; eq { hop { filter_eq { all_rows ; yards ; 0 } ; player } ; andy kelly } } = true', 'tointer': 'select the rows whose yards record is equal to 0 . there is only one such row in the table . the player record of this unqiue row is andy kelly .'} | and { only { filter_eq { all_rows ; yards ; 0 } } ; eq { hop { filter_eq { all_rows ; yards ; 0 } ; player } ; andy kelly } } = true | select the rows whose yards record is equal to 0 . there is only one such row in the table . the player record of this unqiue row is andy kelly . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'yards_7': 7, '0_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'player_9': 9, 'andy kelly_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'yards_7': 'yards', '0_8': '0', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'player_9': 'player', 'andy kelly_10': 'andy kelly'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'yards_7': [0], '0_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'player_9': [2], 'andy kelly_10': [3]} | ['player', 'car', 'yards', 'avg', "td 's", 'long'] | [['dan curran', '27', '60', '2.2', '3', '13'], ['steve bellisari', '30', '54', '1.8', '7', '20'], ['james lynch', '26', '47', '1.8', '5', '15'], ['henry bryant', '14', '8', '0.6', '1', '2'], ['kenny henderson', '5', '7', '1.4', '2', '6'], ['andy kelly', '5', '0', '0', '0', '0'], ['wendall williams', '1', '2', '2', '0', '2']] |
los angeles lakers all - time roster | https://en.wikipedia.org/wiki/Los_Angeles_Lakers_all-time_roster | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10560886-8.html.csv | majority | the majority of players on the los angeles lakers all-time roster came 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', 'nationality', 'united states'], 'result': True, 'ind': 0, 'tointer': 'for the nationality records of all rows , most of them fuzzily match to united states .', 'tostr': 'most_eq { all_rows ; nationality ; united states } = true'} | most_eq { all_rows ; nationality ; united states } = true | for the nationality records of all rows , most of them fuzzily match to united states . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'nationality_3': 3, 'united states_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'nationality_3': 'nationality', 'united states_4': 'united states'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'nationality_3': [0], 'united states_4': [0]} | ['player', 'nationality', 'position', 'from', 'school / country'] | [['earl gardner', 'united states', 'forward', '1948', 'depauw'], ['dick garmaker', 'united states', 'guard / forward', '1955', 'minnesota'], ['garrett , calvin calvin garrett', 'united states', 'forward', '1983', 'oral roberts'], ['dick garrett', 'united states', 'guard', '1969', 'southern illinois'], ['pau gasol', 'spain', 'forward / center', '2008', 'spain'], ['devean george', 'united states', 'forward', '1999', 'augsburg'], ['mel gibson', 'united states', 'guard', '1963', 'western carolina'], ['norman glick', 'united states', 'forward', '1949', 'loyola marymount'], ['gail goodrich', 'united states', 'guard', '1965 1970', 'ucla'], ['andrew goudelock', 'united states', 'guard', '2011', 'charleston'], ['brian grant', 'united states', 'forward / center', '2004', 'xavier'], ['bud grant', 'united states', 'forward', '1949', 'minnesota'], ['horace grant', 'united states', 'forward / center', '2000 2003', 'clemson'], ['travis grant', 'united states', 'forward', '1950', 'kentucky state'], ['ac green', 'united states', 'forward', '1985 1999', 'oregon state'], ['jerry grote', 'united states', 'guard', '1964', 'loyola marymount'], ['pétur guðmundsson', 'iceland', 'center', '1985', 'washington']] |
1951 formula one season | https://en.wikipedia.org/wiki/1951_Formula_One_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1140117-1.html.csv | comparative | lee wallard 's win was earlier in the year than alberto ascari 's first win . | {'row_1': '2', 'row_2': '6', 'col': '3', 'col_other': '6', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'winning driver', 'lee wallard'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose winning driver record fuzzily matches to lee wallard .', 'tostr': 'filter_eq { all_rows ; winning driver ; lee wallard }'}, 'date'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; winning driver ; lee wallard } ; date }', 'tointer': 'select the rows whose winning driver record fuzzily matches to lee wallard . take the date record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'winning driver', 'alberto ascari'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose winning driver record fuzzily matches to alberto ascari .', 'tostr': 'filter_eq { all_rows ; winning driver ; alberto ascari }'}, 'date'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; winning driver ; alberto ascari } ; date }', 'tointer': 'select the rows whose winning driver record fuzzily matches to alberto ascari . take the date record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; winning driver ; lee wallard } ; date } ; hop { filter_eq { all_rows ; winning driver ; alberto ascari } ; date } } = true', 'tointer': 'select the rows whose winning driver record fuzzily matches to lee wallard . take the date record of this row . select the rows whose winning driver record fuzzily matches to alberto ascari . take the date record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; winning driver ; lee wallard } ; date } ; hop { filter_eq { all_rows ; winning driver ; alberto ascari } ; date } } = true | select the rows whose winning driver record fuzzily matches to lee wallard . take the date record of this row . select the rows whose winning driver record fuzzily matches to alberto ascari . 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, 'winning driver_7': 7, 'lee wallard_8': 8, 'date_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'winning driver_11': 11, 'alberto ascari_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', 'winning driver_7': 'winning driver', 'lee wallard_8': 'lee wallard', 'date_9': 'date', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'winning driver_11': 'winning driver', 'alberto ascari_12': 'alberto ascari', 'date_13': 'date'} | {'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'winning driver_7': [0], 'lee wallard_8': [0], 'date_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'winning driver_11': [1], 'alberto ascari_12': [1], 'date_13': [3]} | ['race', 'circuit', 'date', 'pole position', 'fastest lap', 'winning driver', 'constructor', 'tyre', 'report'] | [['swiss grand prix', 'bremgarten', '27 may', 'juan manuel fangio', 'juan manuel fangio', 'juan manuel fangio', 'alfa romeo', 'p', 'report'], ['indianapolis 500', 'indianapolis', '30 may', 'duke nalon', 'lee wallard', 'lee wallard', 'kurtis kraft - offenhauser', 'f', 'report'], ['belgian grand prix', 'spa - francorchamps', '17 june', 'juan manuel fangio', 'juan manuel fangio', 'giuseppe farina', 'alfa romeo', 'p', 'report'], ['french grand prix', 'reims - gueux', '1 july', 'juan manuel fangio', 'juan manuel fangio', 'juan manuel fangio luigi fagioli', 'alfa romeo', 'p', 'report'], ['british grand prix', 'silverstone', '14 july', 'josé froilán gonzález', 'giuseppe farina', 'josé froilán gonzález', 'ferrari', 'p', 'report'], ['german grand prix', 'nürburgring', '29 july', 'alberto ascari', 'juan manuel fangio', 'alberto ascari', 'ferrari', 'p', 'report'], ['italian grand prix', 'monza', '16 september', 'juan manuel fangio', 'giuseppe farina', 'alberto ascari', 'ferrari', 'p', 'report'], ['spanish grand prix', 'pedralbes', '28 october', 'alberto ascari', 'juan manuel fangio', 'juan manuel fangio', 'alfa romeo', 'p', 'report']] |
1984 - 85 fa cup | https://en.wikipedia.org/wiki/1984%E2%80%9385_FA_Cup | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17438338-6.html.csv | majority | most of the games after march 9 of the 1985 fa cup had at least one point scored . | {'scope': 'subset', 'col': '3', 'most_or_all': 'most', 'criterion': 'greater_than_eq', 'value': '1', 'subset': {'col': '5', 'criterion': 'greater_than', 'value': '9 march 1985'}} | {'func': 'most_greater_eq', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'date', '9 march 1985'], 'result': None, 'ind': 0, 'tostr': 'filter_greater { all_rows ; date ; 9 march 1985 }', 'tointer': 'select the rows whose date record is greater than 9 march 1985 .'}, 'score', '1'], 'result': True, 'ind': 1, 'tointer': 'select the rows whose date record is greater than 9 march 1985 . for the score records of these rows , most of them are greater than or equal to 1 .', 'tostr': 'most_greater_eq { filter_greater { all_rows ; date ; 9 march 1985 } ; score ; 1 } = true'} | most_greater_eq { filter_greater { all_rows ; date ; 9 march 1985 } ; score ; 1 } = true | select the rows whose date record is greater than 9 march 1985 . for the score records of these rows , most of them are greater than or equal to 1 . | 2 | 2 | {'most_greater_eq_1': 1, 'result_2': 2, 'filter_greater_0': 0, 'all_rows_3': 3, 'date_4': 4, '9 march 1985_5': 5, 'score_6': 6, '1_7': 7} | {'most_greater_eq_1': 'most_greater_eq', 'result_2': 'true', 'filter_greater_0': 'filter_greater', 'all_rows_3': 'all_rows', 'date_4': 'date', '9 march 1985_5': '9 march 1985', 'score_6': 'score', '1_7': '1'} | {'most_greater_eq_1': [2], 'result_2': [], 'filter_greater_0': [1], 'all_rows_3': [0], 'date_4': [0], '9 march 1985_5': [0], 'score_6': [1], '1_7': [1]} | ['tie no', 'home team', 'score', 'away team', 'date'] | [['1', 'luton town', '1 - 0', 'millwall', '13 march 1985'], ['2', 'everton', '2 - 2', 'ipswich town', '9 march 1985'], ['replay', 'ipswich town', '0 - 1', 'everton', '13 march 1985'], ['3', 'barnsley', '0 - 4', 'liverpool', '10 march 1985'], ['4', 'manchester united', '4 - 2', 'west ham united', '9 march 1985']] |
list of tallest buildings in the halifax regional municipality | https://en.wikipedia.org/wiki/List_of_tallest_buildings_in_the_Halifax_Regional_Municipality | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11339545-1.html.csv | count | in the list of tallest buildings in the halifax regional municipality four buildings are over 80 m tall . | {'scope': 'all', 'criterion': 'greater_than', 'value': '80', 'result': '4', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'height', '80'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose height record is greater than 80 .', 'tostr': 'filter_greater { all_rows ; height ; 80 }'}], 'result': '4', 'ind': 1, 'tostr': 'count { filter_greater { all_rows ; height ; 80 } }', 'tointer': 'select the rows whose height record is greater than 80 . the number of such rows is 4 .'}, '4'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_greater { all_rows ; height ; 80 } } ; 4 } = true', 'tointer': 'select the rows whose height record is greater than 80 . the number of such rows is 4 .'} | eq { count { filter_greater { all_rows ; height ; 80 } } ; 4 } = true | select the rows whose height record is greater than 80 . the number of such rows is 4 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_greater_0': 0, 'all_rows_4': 4, 'height_5': 5, '80_6': 6, '4_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_greater_0': 'filter_greater', 'all_rows_4': 'all_rows', 'height_5': 'height', '80_6': '80', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_greater_0': [1], 'all_rows_4': [0], 'height_5': [0], '80_6': [0], '4_7': [2]} | ['rank', 'building', 'height', 'floors', 'completed'] | [['1', 'fenwick tower ( residential )', '98 m ( 322ft )', '32', '1971'], ['2', "purdy 's wharf tower 2 ( office )", '88 m ( 289ft )', '22', '1990'], ['3', '1801 hollis street ( office )', '87 m ( 285ft )', '22', '1985'], ['4', 'barrington tower ( office )', '84 m ( 276ft )', '20', '1975'], ['5', 'cogswell tower ( office )', '79 m ( 259ft )', '20', '1975'], ['6', 'maritime centre ( office )', '78 m ( 256ft )', '21', '1974'], ['7', 'queen square ( office )', '75 m ( 246ft )', '19', '1975'], ['8', "purdy 's wharf tower 1 ( office )", '74 m ( 243ft )', '18', '1985'], ['9', 'bank of montreal building ( office )', '73 m ( 240ft )', '18', '1971'], ['10', 'td tower ( office )', '73 m ( 240ft )', '18', '1974'], ['11', 'duke tower ( office )', '71 m ( 233ft )', '16', '1970'], ['12', 'founders square ( office )', '71 m ( 233ft )', '15', '1970'], ['13', 'tupper building ( educational )', '70 m ( 233ft )', '16', '1967'], ['14', 'park victoria ( residential )', '70 m ( 233ft )', '21', '1969'], ['15', 'summer gardens ( residential )', '70 m ( 233ft )', '21', '1990'], ['16', 'loyola residence tower ( residential )', '67 m ( 220ft )', '22', '1971'], ['17', 'metropolitan place ( office )', '67 m ( 218ft )', '16', '1987'], ['18', 'bank of commerce ( office )', '66 m ( 217ft )', '16', '1977'], ['19', 'the trillium ( residential )', '65 m ( 213ft )', '19', '2011']] |
fil world luge championships 1978 | https://en.wikipedia.org/wiki/FIL_World_Luge_Championships_1978 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11154705-4.html.csv | count | 5 nations were represented in the fil world luge championships of 1978 . | {'scope': 'all', 'criterion': 'all', 'value': 'n/a', 'result': '5', 'col': '2', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_all', 'args': ['all_rows', 'nation'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose nation record is arbitrary .', 'tostr': 'filter_all { all_rows ; nation }'}], 'result': '5', 'ind': 1, 'tostr': 'count { filter_all { all_rows ; nation } }', 'tointer': 'select the rows whose nation record is arbitrary . the number of such rows is 5 .'}, '5'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_all { all_rows ; nation } } ; 5 } = true', 'tointer': 'select the rows whose nation record is arbitrary . the number of such rows is 5 .'} | eq { count { filter_all { all_rows ; nation } } ; 5 } = true | select the rows whose nation 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, 'nation_5': 5, '5_6': 6} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_all_0': 'filter_all', 'all_rows_4': 'all_rows', 'nation_5': 'nation', '5_6': '5'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_all_0': [1], 'all_rows_4': [0], 'nation_5': [0], '5_6': [2]} | ['rank', 'nation', 'gold', 'silver', 'bronze', 'total'] | [['1', 'soviet union', '2', '1', '0', '3'], ['2', 'west germany', '0', '2', '0', '2'], ['3', 'austria', '0', '0', '2', '2'], ['4', 'italy', '1', '0', '0', '1'], ['5', 'east germany', '0', '0', '1', '1']] |
communist league ( new zealand ) | https://en.wikipedia.org/wiki/Communist_League_%28New_Zealand%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1110530-1.html.csv | unique | 1990 was the only election in which the communist league had 9 candidates . | {'scope': 'all', 'row': '1', 'col': '2', 'col_other': '1', 'criterion': 'equal', 'value': '9', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'candidates', '9'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose candidates record is equal to 9 .', 'tostr': 'filter_eq { all_rows ; candidates ; 9 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; candidates ; 9 } }', 'tointer': 'select the rows whose candidates record is equal to 9 . there is only one such row in the table .'}, {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'candidates', '9'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose candidates record is equal to 9 .', 'tostr': 'filter_eq { all_rows ; candidates ; 9 }'}, 'election'], 'result': '1990', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; candidates ; 9 } ; election }'}, '1990'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; candidates ; 9 } ; election } ; 1990 }', 'tointer': 'the election record of this unqiue row is 1990 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; candidates ; 9 } } ; eq { hop { filter_eq { all_rows ; candidates ; 9 } ; election } ; 1990 } } = true', 'tointer': 'select the rows whose candidates record is equal to 9 . there is only one such row in the table . the election record of this unqiue row is 1990 .'} | and { only { filter_eq { all_rows ; candidates ; 9 } } ; eq { hop { filter_eq { all_rows ; candidates ; 9 } ; election } ; 1990 } } = true | select the rows whose candidates record is equal to 9 . there is only one such row in the table . the election record of this unqiue row is 1990 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'candidates_7': 7, '9_8': 8, 'eq_3': 3, 'num_hop_2': 2, 'election_9': 9, '1990_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'candidates_7': 'candidates', '9_8': '9', 'eq_3': 'eq', 'num_hop_2': 'num_hop', 'election_9': 'election', '1990_10': '1990'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'candidates_7': [0], '9_8': [0], 'eq_3': [4], 'num_hop_2': [3], 'election_9': [2], '1990_10': [3]} | ['election', 'candidates', 'seats won', 'votes', '% of vote'] | [['1990', '9', '0', '210', '0.01'], ['1993', '2', '0', '84', '0.00'], ['1996', '2', '0', '99', '0.00'], ['1999', '2', '0', '89', '0.00'], ['2002', '2', '0', '171', '0.01'], ['2005', '2', '0', '107', '0.00'], ['2008', '2', '0', '74', '0.00']] |
peter arundell | https://en.wikipedia.org/wiki/Peter_Arundell | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1235866-1.html.csv | aggregation | from 1963 - 1966 , peter arundell scored a total of 14 points for team lotus . | {'scope': 'all', 'col': '5', 'type': 'sum', 'result': '14', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'points'], 'result': '14', 'ind': 0, 'tostr': 'sum { all_rows ; points }'}, '14'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; points } ; 14 } = true', 'tointer': 'the sum of the points record of all rows is 14 .'} | round_eq { sum { all_rows ; points } ; 14 } = true | the sum of the points record of all rows is 14 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'points_4': 4, '14_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'points_4': 'points', '14_5': '14'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'points_4': [0], '14_5': [1]} | ['year', 'entrant', 'chassis', 'engine', 'points'] | [['1963', 'team lotus', 'lotus 25', 'climax v8', '0'], ['1964', 'team lotus', 'lotus 25', 'climax v8', '11'], ['1966', 'team lotus', 'lotus 43', 'brm h16', '1'], ['1966', 'team lotus', 'lotus 33', 'brm v8', '1'], ['1966', 'team lotus', 'lotus 33', 'climax v8', '1']] |
list of vehicle speed records | https://en.wikipedia.org/wiki/List_of_vehicle_speed_records | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16343705-3.html.csv | ordinal | the lockheed sr-71 blackbird achieved the second fastest speed of all the vehicles . | {'row': '2', 'col': '2', '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', 'speed ( km / h )', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; speed ( km / h ) ; 2 }'}, 'vehicle'], 'result': 'lockheed sr - 71 blackbird', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; speed ( km / h ) ; 2 } ; vehicle }'}, 'lockheed sr - 71 blackbird'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; speed ( km / h ) ; 2 } ; vehicle } ; lockheed sr - 71 blackbird } = true', 'tointer': 'select the row whose speed ( km / h ) record of all rows is 2nd maximum . the vehicle record of this row is lockheed sr - 71 blackbird .'} | eq { hop { nth_argmax { all_rows ; speed ( km / h ) ; 2 } ; vehicle } ; lockheed sr - 71 blackbird } = true | select the row whose speed ( km / h ) record of all rows is 2nd maximum . the vehicle record of this row is lockheed sr - 71 blackbird . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'speed (km / h)_5': 5, '2_6': 6, 'vehicle_7': 7, 'lockheed sr - 71 blackbird_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', 'speed (km / h)_5': 'speed ( km / h )', '2_6': '2', 'vehicle_7': 'vehicle', 'lockheed sr - 71 blackbird_8': 'lockheed sr - 71 blackbird'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'speed (km / h)_5': [0], '2_6': [0], 'vehicle_7': [1], 'lockheed sr - 71 blackbird_8': [2]} | ['category', 'speed ( km / h )', 'speed ( mph )', 'vehicle', 'pilot', 'date'] | [['rocket - powered aircraft', '7258', '4510', 'north american x - 15', 'william j knight', '3 oct 1967'], ['manned air - breathing craft', '3530', '2194', 'lockheed sr - 71 blackbird', 'eldon w joersz', '28 jul 1976'], ['propeller - driven aircraft', '870', '541', 'tupolev tu - 114', 'ivan soukhomline', '00 jan 1960'], ['piston - engined propeller - driven aircraft', '850.1', '528.33', 'grumman f8f bearcat rare bear ( n777l )', 'lyle shelton', '21 aug 1989'], ['helicopter', '401.0', '249.1', 'westland lynx 800 g - lynx', 'john egginton', '11 aug 1986'], ['glider ( sailplane )', '306.8', '190.6', 'schempp - hirth nimbus - 4dm', 'klaus ohlmann and matias garcia mazzaro', '22 dec 2006'], ['human - powered aircraft', '32', '19.8', 'mit monarch b', 'frank scarabino', '1 may 1984']] |
2003 u.s. open ( golf ) | https://en.wikipedia.org/wiki/2003_U.S._Open_%28golf%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16292316-1.html.csv | ordinal | lee janzen had the highest total during the 2003 u.s. open ( golf ) . | {'row': '5', 'col': '4', 'order': '1', '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', 'total', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; total ; 1 }'}, 'player'], 'result': 'lee janzen', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; total ; 1 } ; player }'}, 'lee janzen'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; total ; 1 } ; player } ; lee janzen } = true', 'tointer': 'select the row whose total record of all rows is 1st maximum . the player record of this row is lee janzen .'} | eq { hop { nth_argmax { all_rows ; total ; 1 } ; player } ; lee janzen } = true | select the row whose total record of all rows is 1st maximum . the player record of this row is lee janzen . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'total_5': 5, '1_6': 6, 'player_7': 7, 'lee janzen_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', '1_6': '1', 'player_7': 'player', 'lee janzen_8': 'lee janzen'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'total_5': [0], '1_6': [0], 'player_7': [1], 'lee janzen_8': [2]} | ['player', 'country', 'year ( s ) won', 'total', 'to par', 'finish'] | [['ernie els', 'south africa', '1994 , 1997', '280', 'e', 't5'], ['tiger woods', 'united states', '2000 , 2002', '283', '+ 3', 't20'], ['tom watson', 'united states', '1982', '284', '+ 4', 't28'], ['retief goosen', 'south africa', '2001', '286', '+ 6', 't42'], ['lee janzen', 'united states', '1993 , 1998', '289', '+ 9', 't55']] |
katrina adams | https://en.wikipedia.org/wiki/Katrina_Adams | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18622227-6.html.csv | unique | the only tournament that katrina adams reached the semi finals was at the 1988 wimbledon tournament . | {'scope': 'all', 'row': '4', 'col': '3', 'col_other': '1', 'criterion': 'equal', 'value': 'sf', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', '1988', 'sf'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose 1988 record fuzzily matches to sf .', 'tostr': 'filter_eq { all_rows ; 1988 ; sf }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; 1988 ; sf } }', 'tointer': 'select the rows whose 1988 record fuzzily matches to sf . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', '1988', 'sf'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose 1988 record fuzzily matches to sf .', 'tostr': 'filter_eq { all_rows ; 1988 ; sf }'}, 'tournament'], 'result': 'wimbledon', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; 1988 ; sf } ; tournament }'}, 'wimbledon'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; 1988 ; sf } ; tournament } ; wimbledon }', 'tointer': 'the tournament record of this unqiue row is wimbledon .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; 1988 ; sf } } ; eq { hop { filter_eq { all_rows ; 1988 ; sf } ; tournament } ; wimbledon } } = true', 'tointer': 'select the rows whose 1988 record fuzzily matches to sf . there is only one such row in the table . the tournament record of this unqiue row is wimbledon .'} | and { only { filter_eq { all_rows ; 1988 ; sf } } ; eq { hop { filter_eq { all_rows ; 1988 ; sf } ; tournament } ; wimbledon } } = true | select the rows whose 1988 record fuzzily matches to sf . there is only one such row in the table . the tournament record of this unqiue row is wimbledon . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, '1988_7': 7, 'sf_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'tournament_9': 9, 'wimbledon_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', '1988_7': '1988', 'sf_8': 'sf', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'tournament_9': 'tournament', 'wimbledon_10': 'wimbledon'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], '1988_7': [0], 'sf_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'tournament_9': [2], 'wimbledon_10': [3]} | ['tournament', '1986', '1988', '1989', '1990', '1991', '1992', '1993', '1994', '1995', '1996', '1997', '1998', '1999'] | [['grand slam tournaments', 'grand slam tournaments', 'grand slam tournaments', 'grand slam tournaments', 'grand slam tournaments', 'grand slam tournaments', 'grand slam tournaments', 'grand slam tournaments', 'grand slam tournaments', 'grand slam tournaments', 'grand slam tournaments', 'grand slam tournaments', 'grand slam tournaments', 'grand slam tournaments'], ['australian open', 'a', '3r', '3r', '3r', 'a', 'qf', '3r', '2r', '1r', 'a', '2r', '1r', '1r'], ['french open', 'a', 'qf', 'qf', '3r', '3r', 'qf', 'qf', '1r', 'qf', 'qf', '2r', '3r', '1r'], ['wimbledon', 'a', 'sf', 'qf', '3r', 'qf', '3r', '1r', '2r', '3r', 'qf', '3r', '3r', '1r'], ['us open', '1r', '2r', '3r', '3r', 'qf', 'a', '3r', 'qf', '3r', '2r', '3r', '2r', '1r']] |
united states district court for the northern district of iowa | https://en.wikipedia.org/wiki/United_States_District_Court_for_the_Northern_District_of_Iowa | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11088781-2.html.csv | count | two judges in the district court for the northern district of iowa are still alive today . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'present', 'result': '2', 'col': '2', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'born / died', 'present'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose born / died record fuzzily matches to present .', 'tostr': 'filter_eq { all_rows ; born / died ; present }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; born / died ; present } }', 'tointer': 'select the rows whose born / died record fuzzily matches to present . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; born / died ; present } } ; 2 } = true', 'tointer': 'select the rows whose born / died record fuzzily matches to present . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; born / died ; present } } ; 2 } = true | select the rows whose born / died record fuzzily matches to present . 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, 'born / died_5': 5, 'present_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', 'born / died_5': 'born / died', 'present_6': 'present', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'born / died_5': [0], 'present_6': [0], '2_7': [2]} | ['state', 'born / died', 'active service', 'chief judge', 'senior status', 'appointed by', 'reason for termination'] | [['ia', '1833 - 1916', '1882 - 1903', '-', '-', 'arthur', 'retirement'], ['ia', '1846 - 1924', '1904 - 1921', '-', '1921 - 1924', 't roosevelt', 'death'], ['ia', '1864 - 1948', '1922 - 1943', '-', '1943 - 1948', 'harding', 'death'], ['ia', '1893 - 1970', '1944 - 1961', '1961', '1961 - 1970', 'f roosevelt', 'death'], ['ia', '1909 - 1995', '1962 - 1977', '-', '1977 - 1995', 'kennedy', 'death'], ['ia', '1939 - present', '1986 - 1991', '-', '-', 'reagan', 'reappointment'], ['ia', '1948 - present', '1992 - 2002', '1992 - 1999', '-', 'ghw bush', 'reappointment']] |
synchronized swimming at the 2008 summer olympics - women 's duet | https://en.wikipedia.org/wiki/Synchronized_swimming_at_the_2008_Summer_Olympics_%E2%80%93_Women%27s_duet | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18789596-2.html.csv | ordinal | in the women 's duet in sychronized swimming at the 2008 summer olympics , the 2nd highest total was for andrea fuentes & gemma mengual . | {'row': '2', 'col': '5', 'order': '2', 'col_other': '2', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'total', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; total ; 2 }'}, 'athlete'], 'result': 'andrea fuentes & gemma mengual', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; total ; 2 } ; athlete }'}, 'andrea fuentes & gemma mengual'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; total ; 2 } ; athlete } ; andrea fuentes & gemma mengual } = true', 'tointer': 'select the row whose total record of all rows is 2nd maximum . the athlete record of this row is andrea fuentes & gemma mengual .'} | eq { hop { nth_argmax { all_rows ; total ; 2 } ; athlete } ; andrea fuentes & gemma mengual } = true | select the row whose total record of all rows is 2nd maximum . the athlete record of this row is andrea fuentes & gemma mengual . | 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, 'athlete_7': 7, 'andrea fuentes & gemma mengual_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', 'athlete_7': 'athlete', 'andrea fuentes & gemma mengual_8': 'andrea fuentes & gemma mengual'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'total_5': [0], '2_6': [0], 'athlete_7': [1], 'andrea fuentes & gemma mengual_8': [2]} | ['country', 'athlete', 'technical', 'free', 'total'] | [['russia', 'anastasia davydova & anastasiya yermakova', '49.334', '49.917', '99.251'], ['spain', 'andrea fuentes & gemma mengual', '48.834', '49.500', '98.334'], ['japan', 'saho harada & emiko suzuki', '48.250', '48.917', '97.167'], ['china', 'jiang tingting & jiang wenwen', '48.084', '48.250', '96.334'], ['united states', 'christina jones & andrea nott', '47.750', '47.750', '95.500'], ['canada', 'marie - pier boudreau gagnon & isabelle rampling', '47.417', '47.667', '95.084'], ['italy', 'beatrice adelizzi & giulia lapi', '46.834', '46.917', '93.751'], ['ukraine', 'darya yushko & kseniya sydorenko', '46.084', '46.584', '92.668'], ['netherlands', 'bianca van der velden & sonja van der velden', '45.584', '46.083', '91.667'], ['greece', 'evanthia makrygianni & despoina solomou', '45.834', '45.667', '91.501'], ['france', 'apolline dreyfuss & lila meesseman - bakir', '44.750', '45.583', '90.333'], ['switzerland', 'magdalena brunner & ariane schneider', '44.250', '45.000', '89.250']] |
2005 - 06 toronto raptors season | https://en.wikipedia.org/wiki/2005%E2%80%9306_Toronto_Raptors_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-15873014-5.html.csv | aggregation | the high scorer for the toronto raptors had on average about 27-28 points . | {'scope': 'all', 'col': '5', 'type': 'average', 'result': '27-28', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'high points'], 'result': '27-28', 'ind': 0, 'tostr': 'avg { all_rows ; high points }'}, '27-28'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; high points } ; 27-28 } = true', 'tointer': 'the average of the high points record of all rows is 27-28 .'} | round_eq { avg { all_rows ; high points } ; 27-28 } = true | the average of the high points record of all rows is 27-28 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'high points_4': 4, '27-28_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'high points_4': 'high points', '27-28_5': '27-28'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'high points_4': [0], '27-28_5': [1]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record'] | [['31', 'january 3', 'atlanta', 'w 108 - 97 ( ot )', 'mike james ( 28 )', 'chris bosh ( 10 )', 'mike james ( 6 )', 'philips arena 10048', '9 - 22'], ['32', 'january 4', 'orlando', 'w 121 - 97 ( ot )', 'charlie villanueva ( 24 )', 'rafael araújo ( 9 )', 'mike james ( 7 )', 'air canada centre 14085', '10 - 22'], ['33', 'january 6', 'houston', 'w 112 - 92 ( ot )', 'mike james ( 30 )', 'chris bosh ( 16 )', 'mike james ( 8 )', 'air canada centre 17460', '11 - 22'], ['34', 'january 8', 'new jersey', 'l 104 - 105 ( ot )', 'chris bosh ( 27 )', 'matt bonner ( 8 )', 'mike james ( 7 )', 'air canada centre 18935', '11 - 23'], ['35', 'january 9', 'chicago', 'l 104 - 113 ( ot )', 'chris bosh ( 26 )', 'matt bonner ( 9 )', 'mike james ( 13 )', 'united center 21103', '11 - 24'], ['36', 'january 11', 'charlotte', 'w 95 - 86 ( ot )', 'chris bosh ( 29 )', 'morris peterson ( 11 )', 'mike james ( 7 )', 'air canada centre 14098', '12 - 24'], ['37', 'january 15', 'new york', 'w 129 - 103 ( ot )', 'jalen rose ( 31 )', 'chris bosh , charlie villanueva ( 6 )', 'josé calderón ( 10 )', 'air canada centre 17393', '13 - 24'], ['38', 'january 17', 'utah', 'l 98 - 111 ( ot )', 'chris bosh ( 27 )', 'matt bonner , chris bosh ( 6 )', 'josé calderón , mike james ( 3 )', 'delta center 17831', '13 - 25'], ['39', 'january 18', 'portland', 'l 94 - 96 ( ot )', 'jalen rose ( 23 )', 'chris bosh ( 9 )', 'mike james ( 7 )', 'rose garden 12315', '13 - 26'], ['40', 'january 20', 'seattle', 'w 121 - 113 ( ot )', 'chris bosh ( 29 )', 'chris bosh ( 13 )', 'jalen rose ( 7 )', 'keyarena 15261', '14 - 26'], ['41', 'january 22', 'la lakers', 'l 104 - 122 ( ot )', 'mike james ( 26 )', 'chris bosh ( 8 )', 'mike james ( 10 )', 'staples center 18997', '14 - 27'], ['42', 'january 23', 'denver', 'l 101 - 107 ( ot )', 'mike james ( 22 )', 'matt bonner ( 9 )', 'chris bosh , mike james ( 4 )', 'pepsi center 14826', '14 - 28'], ['43', 'january 25', 'chicago', 'l 88 - 104 ( ot )', 'chris bosh ( 20 )', 'chris bosh ( 7 )', 'mike james ( 7 )', 'air canada centre 14198', '14 - 29'], ['44', 'january 27', 'milwaukee', 'l 87 - 108 ( ot )', 'chris bosh ( 21 )', 'charlie villanueva ( 6 )', 'josé calderón ( 7 )', 'bradley center 14867', '14 - 30']] |
list of paris saint - germain f.c. players | https://en.wikipedia.org/wiki/List_of_Paris_Saint-Germain_F.C._players | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-24565004-11.html.csv | superlative | philippe jeannol has the most appearances of these five players , at 219 . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '5', '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', 'appearances'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; appearances }'}, 'name'], 'result': 'philippe jeannol', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; appearances } ; name }'}, 'philippe jeannol'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; appearances } ; name } ; philippe jeannol } = true', 'tointer': 'select the row whose appearances record of all rows is maximum . the name record of this row is philippe jeannol .'} | eq { hop { argmax { all_rows ; appearances } ; name } ; philippe jeannol } = true | select the row whose appearances record of all rows is maximum . the name record of this row is philippe jeannol . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'appearances_5': 5, 'name_6': 6, 'philippe jeannol_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'appearances_5': 'appearances', 'name_6': 'name', 'philippe jeannol_7': 'philippe jeannol'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'appearances_5': [0], 'name_6': [1], 'philippe jeannol_7': [2]} | ['name', 'position', 'period', 'appearances', 'goals', 'nationality square'] | [['robert jacques', 'forward', '1985 - 1986', '28', '6', 'france'], ['christophe jallet', 'defender', '2009 -', '180', '9', 'france'], ['gérard janvion', 'defender', '1983 - 1985', '50', '0', 'france'], ['philippe jean', 'defender', '1977 - 1979', '14', '0', 'france'], ['philippe jeannol', 'defender', '1984 - 1991', '219', '15', 'france']] |
primary schools in dacorum | https://en.wikipedia.org/wiki/Primary_schools_in_Dacorum | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15089329-3.html.csv | superlative | galley hill is the primary school in dacorum that has the highest dcsf number . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '5', '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', 'dcsf number'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; dcsf number }'}, 'name'], 'result': 'galley hill', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; dcsf number } ; name }'}, 'galley hill'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; dcsf number } ; name } ; galley hill } = true', 'tointer': 'select the row whose dcsf number record of all rows is maximum . the name record of this row is galley hill .'} | eq { hop { argmax { all_rows ; dcsf number } ; name } ; galley hill } = true | select the row whose dcsf number record of all rows is maximum . the name record of this row is galley hill . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'dcsf number_5': 5, 'name_6': 6, 'galley hill_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'dcsf number_5': 'dcsf number', 'name_6': 'name', 'galley hill_7': 'galley hill'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'dcsf number_5': [0], 'name_6': [1], 'galley hill_7': [2]} | ['name', 'faith', 'type', 'intake', 'dcsf number', 'ofsted number'] | [['boxmoor', '-', 'primary', '30', '2041', '117107'], ['chaulden', '-', 'infants', '50', '2193', '117202'], ['chaulden', '-', 'junior', '60', '2185', '117198'], ['gade valley', '-', 'jmi', '30', '2274', '117249'], ['galley hill', '-', 'primary', '45', '3990', '135224'], ['heath lane', '-', 'nursery', '80', '1009', '117070'], ['micklem', '-', 'primary', '30', '2243', '117231'], ['pixies hill', '-', 'primary', '30', '2293', '117256'], ['st cuthbert mayne', 'rc', 'junior', '60', '3386', '117468'], ["st rose 's", 'rc', 'infants', '60', '3409', '117484'], ['south hill', '-', 'primary', '30', '2047', '117110']] |
list of canadian provinces and territories by population | https://en.wikipedia.org/wiki/List_of_Canadian_provinces_and_territories_by_population | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-106104-1.html.csv | count | only two of the provinces have more than 7,000,000 people , according to the 2011 census . | {'scope': 'all', 'criterion': 'greater_than', 'value': '7000000', 'result': '2', 'col': '10', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater', 'args': ['all_rows', '2013 population ( july est )', '7000000'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose 2013 population ( july est ) record is greater than 7000000 .', 'tostr': 'filter_greater { all_rows ; 2013 population ( july est ) ; 7000000 }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_greater { all_rows ; 2013 population ( july est ) ; 7000000 } }', 'tointer': 'select the rows whose 2013 population ( july est ) record is greater than 7000000 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_greater { all_rows ; 2013 population ( july est ) ; 7000000 } } ; 2 } = true', 'tointer': 'select the rows whose 2013 population ( july est ) record is greater than 7000000 . the number of such rows is 2 .'} | eq { count { filter_greater { all_rows ; 2013 population ( july est ) ; 7000000 } } ; 2 } = true | select the rows whose 2013 population ( july est ) record is greater than 7000000 . the number of such rows is 2 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_greater_0': 0, 'all_rows_4': 4, '2013 population (july est)_5': 5, '7000000_6': 6, '2_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_greater_0': 'filter_greater', 'all_rows_4': 'all_rows', '2013 population (july est)_5': '2013 population ( july est )', '7000000_6': '7000000', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_greater_0': [1], 'all_rows_4': [0], '2013 population (july est)_5': [0], '7000000_6': [0], '2_7': [2]} | ['rank', 'name', 'population ( 2011 census )', 'percent of national population', '% growth ( 2006 - 11 )', 'land area ( km square )', 'population density ( / km 2 )', 'house of commons seats', 'house of commons seats ( % )', '2013 population ( july est )'] | [['1', 'ontario', '12851821', '38.4 %', '5.7 %', '908607.67', '14.1', '106', '34.4 %', '13537994'], ['2', 'quebec', '7903001', '23.6 %', '4.7 %', '1356547.02', '5.8', '75', '24.4 %', '8155334'], ['3', 'british columbia', '4400057', '13.1 %', '7.0 %', '922509.29', '4.8', '36', '11.7 %', '4581978'], ['4', 'alberta', '3645257', '10.9 %', '10.8 %', '640081.87', '5.7', '28', '9.1 %', '4025074'], ['5', 'manitoba', '1208268', '3.6 %', '5.2 %', '552329.52', '2.2', '14', '4.5 %', '1265015']] |
1955 vfl season | https://en.wikipedia.org/wiki/1955_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10773753-5.html.csv | count | there were three total games where the attendance was exactly 15000 fans . | {'scope': 'all', 'criterion': 'equal', 'value': '15000', 'result': '3', 'col': '6', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'crowd', '15000'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose crowd record is equal to 15000 .', 'tostr': 'filter_eq { all_rows ; crowd ; 15000 }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; crowd ; 15000 } }', 'tointer': 'select the rows whose crowd record is equal to 15000 . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; crowd ; 15000 } } ; 3 } = true', 'tointer': 'select the rows whose crowd record is equal to 15000 . the number of such rows is 3 .'} | eq { count { filter_eq { all_rows ; crowd ; 15000 } } ; 3 } = true | select the rows whose crowd record is equal to 15000 . the number of such rows is 3 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_eq_0': 0, 'all_rows_4': 4, 'crowd_5': 5, '15000_6': 6, '3_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'crowd_5': 'crowd', '15000_6': '15000', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'crowd_5': [0], '15000_6': [0], '3_7': [2]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['hawthorn', '14.7 ( 91 )', 'north melbourne', '13.15 ( 93 )', 'glenferrie oval', '15000', '14 may 1955'], ['essendon', '8.11 ( 59 )', 'melbourne', '10.13 ( 73 )', 'windy hill', '25299', '14 may 1955'], ['carlton', '12.17 ( 89 )', 'collingwood', '17.12 ( 114 )', 'princes park', '37065', '14 may 1955'], ['south melbourne', '25.16 ( 166 )', 'st kilda', '4.8 ( 32 )', 'lake oval', '15000', '14 may 1955'], ['geelong', '12.12 ( 84 )', 'footscray', '10.12 ( 72 )', 'kardinia park', '28288', '14 may 1955'], ['richmond', '11.11 ( 77 )', 'fitzroy', '15.9 ( 99 )', 'punt road oval', '15000', '14 may 1955']] |
sebastian kawa | https://en.wikipedia.org/wiki/Sebastian_Kawa | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12762814-1.html.csv | ordinal | sebastian kawa 's second appearance at the world championships was in 2001 . | {'scope': 'subset', 'row': '2', 'col': '3', 'order': '2', 'col_other': 'n/a', 'max_or_min': 'min_to_max', 'value_mentioned': 'yes', 'subset': {'col': '1', 'criterion': 'equal', 'value': 'world championships'}} | {'func': 'eq', 'args': [{'func': 'nth_min', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'competition', 'world championships'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; competition ; world championships }', 'tointer': 'select the rows whose competition record fuzzily matches to world championships .'}, 'year', '2'], 'result': '2001', 'ind': 1, 'tostr': 'nth_min { filter_eq { all_rows ; competition ; world championships } ; year ; 2 }', 'tointer': 'select the rows whose competition record fuzzily matches to world championships . the 2nd minimum year record of these rows is 2001 .'}, '2001'], 'result': True, 'ind': 2, 'tostr': 'eq { nth_min { filter_eq { all_rows ; competition ; world championships } ; year ; 2 } ; 2001 } = true', 'tointer': 'select the rows whose competition record fuzzily matches to world championships . the 2nd minimum year record of these rows is 2001 .'} | eq { nth_min { filter_eq { all_rows ; competition ; world championships } ; year ; 2 } ; 2001 } = true | select the rows whose competition record fuzzily matches to world championships . the 2nd minimum year record of these rows is 2001 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'nth_min_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'competition_5': 5, 'world championships_6': 6, 'year_7': 7, '2_8': 8, '2001_9': 9} | {'eq_2': 'eq', 'result_3': 'true', 'nth_min_1': 'nth_min', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'competition_5': 'competition', 'world championships_6': 'world championships', 'year_7': 'year', '2_8': '2', '2001_9': '2001'} | {'eq_2': [3], 'result_3': [], 'nth_min_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'competition_5': [0], 'world championships_6': [0], 'year_7': [1], '2_8': [1], '2001_9': [2]} | ['competition', 'venue', 'year', 'category', 'result'] | [['world championships', 'pol leszno', '1999', 'world class', 'bronze'], ['world championships', 'esp lillo', '2001', 'world class', 'bronze'], ['world championships', 'svk nitra', '2003', 'world class', 'gold'], ['world championships', 'nor elverum', '2004', 'club class', 'gold'], ['world championships', 'fra saint - auban', '2005', 'grand prix', 'gold'], ['european championships', 'svk nitra', '2005', 'club class', 'gold'], ['world championships', 'fra vinon - sur - verdon', '2006', 'club class', 'gold'], ['european championships', 'ltu pociunai', '2007', 'club class', 'gold'], ['world championships', 'nzl omarama', '2007', 'grand prix', 'gold'], ['world air games', 'ita torino', '2009', 'grand prix', 'gold'], ['world championships', 'chl santiago de chile', '2010', 'grand prix', 'gold'], ['world championships', 'svk prievidza', '2010', 'standard class', 'gold'], ['european championships', 'svk nitra', '2011', 'standard class', 'gold'], ['world championships', 'usa uvalde', '2012', '15 m', 'gold'], ['world championships', 'argentina chavez', '2013', 'standard class', 'gold'], ['european championships', 'fra vinon - sur - verdon', '2013', '18 m', 'gold'], ['european championships', 'pol ostrã cubicw wielkopolski', '2013', 'standard class', 'gold']] |
2008 - 09 tampa bay lightning season | https://en.wikipedia.org/wiki/2008%E2%80%9309_Tampa_Bay_Lightning_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-17360840-5.html.csv | count | in the 2008 - 09 tampa bay lightning season , among the games played in st pete times forum , 5 of them had attendance greater than 16,000 . | {'scope': 'subset', 'criterion': 'greater_than', 'value': '16000', 'result': '5', 'col': '6', 'subset': {'col': '5', 'criterion': 'equal', 'value': 'st pete times forum'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location', 'st pete times forum'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; location ; st pete times forum }', 'tointer': 'select the rows whose location record fuzzily matches to st pete times forum .'}, 'attendance', '16000'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose location record fuzzily matches to st pete times forum . among these rows , select the rows whose attendance record is greater than 16000 .', 'tostr': 'filter_greater { filter_eq { all_rows ; location ; st pete times forum } ; attendance ; 16000 }'}], 'result': '5', 'ind': 2, 'tostr': 'count { filter_greater { filter_eq { all_rows ; location ; st pete times forum } ; attendance ; 16000 } }', 'tointer': 'select the rows whose location record fuzzily matches to st pete times forum . among these rows , select the rows whose attendance record is greater than 16000 . the number of such rows is 5 .'}, '5'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_greater { filter_eq { all_rows ; location ; st pete times forum } ; attendance ; 16000 } } ; 5 } = true', 'tointer': 'select the rows whose location record fuzzily matches to st pete times forum . among these rows , select the rows whose attendance record is greater than 16000 . the number of such rows is 5 .'} | eq { count { filter_greater { filter_eq { all_rows ; location ; st pete times forum } ; attendance ; 16000 } } ; 5 } = true | select the rows whose location record fuzzily matches to st pete times forum . among these rows , select the rows whose attendance record is greater than 16000 . the number of such rows is 5 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_greater_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'location_6': 6, 'st pete times forum_7': 7, 'attendance_8': 8, '16000_9': 9, '5_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_greater_1': 'filter_greater', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'location_6': 'location', 'st pete times forum_7': 'st pete times forum', 'attendance_8': 'attendance', '16000_9': '16000', '5_10': '5'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_greater_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'location_6': [0], 'st pete times forum_7': [0], 'attendance_8': [1], '16000_9': [1], '5_10': [3]} | ['game', 'date', 'opponent', 'score', 'location', 'attendance', 'record', 'points'] | [['10', 'november 1', 'ottawa senators', '3 - 2', 'st pete times forum', '16104', '4 - 3 - 3', '11'], ['11', 'november 5', 'new jersey devils', '3 - 4 so', 'prudential center', '11619', '4 - 3 - 4', '12'], ['12', 'november 6', 'new york rangers', '2 - 5', 'madison square garden', '18200', '4 - 4 - 4', '12'], ['13', 'november 8', 'philadelphia flyers', '2 - 1', 'wachovia center', '19412', '5 - 4 - 4', '14'], ['14', 'november 10', 'washington capitals', '2 - 4', 'verizon center', '17932', '5 - 5 - 4', '14'], ['15', 'november 12', 'florida panthers', '0 - 4', 'bankatlantic center', '12104', '5 - 6 - 4', '14'], ['16', 'november 13', 'detroit red wings', '3 - 4', 'st pete times forum', '20544', '5 - 7 - 4', '14'], ['17', 'november 16', 'carolina hurricanes', '2 - 3 so', 'rbc center', '13781', '5 - 7 - 5', '15'], ['18', 'november 18', 'florida panthers', '3 - 4 so', 'st pete times forum', '16176', '5 - 7 - 6', '16'], ['19', 'november 21', 'nashville predators', '4 - 1', 'st pete times forum', '16444', '6 - 7 - 6', '18'], ['20', 'november 23', 'new jersey devils', '3 - 7', 'st pete times forum', '14222', '6 - 8 - 6', '18'], ['21', 'november 26', 'new york rangers', '2 - 3 so', 'st pete times forum', '16991', '6 - 8 - 7', '19'], ['22', 'november 28', 'minnesota wild', '2 - 4', 'xcel energy center', '18568', '6 - 9 - 7', '19']] |
alice anum | https://en.wikipedia.org/wiki/Alice_Anum | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17786147-1.html.csv | majority | the majority of events that alice anum competed in were the 200 m events from 1965 to 1974 . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'equal', 'value': '200 m', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'extra', '200 m'], 'result': True, 'ind': 0, 'tointer': 'for the extra records of all rows , most of them fuzzily match to 200 m .', 'tostr': 'most_eq { all_rows ; extra ; 200 m } = true'} | most_eq { all_rows ; extra ; 200 m } = true | for the extra records of all rows , most of them fuzzily match to 200 m . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'extra_3': 3, '200 m_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'extra_3': 'extra', '200 m_4': '200 m'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'extra_3': [0], '200 m_4': [0]} | ['year', 'tournament', 'venue', 'result', 'extra'] | [['1965', 'all - africa games', 'brazzaville , congo', '1st', 'long jump'], ['1970', 'british commonwealth games', 'edinburgh , scotland', '2nd', '100 m'], ['1970', 'british commonwealth games', 'edinburgh , scotland', '2nd', '200 m'], ['1972', 'olympic games', 'munich , germany', '6th', '100 m'], ['1972', 'olympic games', 'munich , germany', '7th', '200 m'], ['1973', 'all - africa games', 'lagos , nigeria', '1st', '100 m'], ['1973', 'all - africa games', 'lagos , nigeria', '1st', '200 m'], ['1974', 'british commonwealth games', 'christchurch , new zealand', '3rd', '200 m']] |
transatlantic lines | https://en.wikipedia.org/wiki/TransAtlantic_Lines | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13580133-1.html.csv | unique | the general cargo ship is the only ship that can move over 4000 gross tons . | {'scope': 'all', 'row': '2', 'col': '5', 'col_other': '1', 'criterion': 'greater_than', 'value': '4000', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'gross tonnage', '4000'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose gross tonnage record is greater than 4000 .', 'tostr': 'filter_greater { all_rows ; gross tonnage ; 4000 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_greater { all_rows ; gross tonnage ; 4000 } }', 'tointer': 'select the rows whose gross tonnage record is greater than 4000 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'gross tonnage', '4000'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose gross tonnage record is greater than 4000 .', 'tostr': 'filter_greater { all_rows ; gross tonnage ; 4000 }'}, 'type'], 'result': 'general cargo ship / container ship', 'ind': 2, 'tostr': 'hop { filter_greater { all_rows ; gross tonnage ; 4000 } ; type }'}, 'general cargo ship / container ship'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_greater { all_rows ; gross tonnage ; 4000 } ; type } ; general cargo ship / container ship }', 'tointer': 'the type record of this unqiue row is general cargo ship / container ship .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_greater { all_rows ; gross tonnage ; 4000 } } ; eq { hop { filter_greater { all_rows ; gross tonnage ; 4000 } ; type } ; general cargo ship / container ship } } = true', 'tointer': 'select the rows whose gross tonnage record is greater than 4000 . there is only one such row in the table . the type record of this unqiue row is general cargo ship / container ship .'} | and { only { filter_greater { all_rows ; gross tonnage ; 4000 } } ; eq { hop { filter_greater { all_rows ; gross tonnage ; 4000 } ; type } ; general cargo ship / container ship } } = true | select the rows whose gross tonnage record is greater than 4000 . there is only one such row in the table . the type record of this unqiue row is general cargo ship / container ship . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_greater_0': 0, 'all_rows_6': 6, 'gross tonnage_7': 7, '4000_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'type_9': 9, 'general cargo ship / container ship_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_greater_0': 'filter_greater', 'all_rows_6': 'all_rows', 'gross tonnage_7': 'gross tonnage', '4000_8': '4000', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'type_9': 'type', 'general cargo ship / container ship_10': 'general cargo ship / container ship'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_greater_0': [1, 2], 'all_rows_6': [0], 'gross tonnage_7': [0], '4000_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'type_9': [2], 'general cargo ship / container ship_10': [3]} | ['type', 'owns', 'length', 'delivery date', 'gross tonnage'] | [['general cargo ship', 'yes', '83.5152 m ( lbp )', '1 june 1980', '2266'], ['general cargo ship / container ship', 'yes', '100.59 100.59 m ( loa )', '1997 1997', '4276'], ['petroleum tanker', 'yes', '109.1 109.1 m ( loa )', '2001 2001', '3469'], ['deck cargo barge', 'yes', '76.2 76.2 m ( lbp )', '1983 1 september 1983', '2529'], ['tugboat', 'yes', '27.7764 27.7764 m ( lbp )', '1974 1 september 1974', '189']] |
kprd | https://en.wikipedia.org/wiki/KPRD | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14993404-1.html.csv | ordinal | the station kprd at the second highest frequency is in lewis , kansas . | {'row': '4', 'col': '2', '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', 'frequency mhz', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; frequency mhz ; 2 }'}, 'city of license'], 'result': 'lewis , kansas', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; frequency mhz ; 2 } ; city of license }'}, 'lewis , kansas'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; frequency mhz ; 2 } ; city of license } ; lewis , kansas } = true', 'tointer': 'select the row whose frequency mhz record of all rows is 2nd maximum . the city of license record of this row is lewis , kansas .'} | eq { hop { nth_argmax { all_rows ; frequency mhz ; 2 } ; city of license } ; lewis , kansas } = true | select the row whose frequency mhz record of all rows is 2nd maximum . the city of license record of this row is lewis , kansas . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'frequency mhz_5': 5, '2_6': 6, 'city of license_7': 7, 'lewis , kansas_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', 'frequency mhz_5': 'frequency mhz', '2_6': '2', 'city of license_7': 'city of license', 'lewis , kansas_8': 'lewis , kansas'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'frequency mhz_5': [0], '2_6': [0], 'city of license_7': [1], 'lewis , kansas_8': [2]} | ['call sign', 'frequency mhz', 'city of license', 'erp w', 'class', 'fcc info'] | [['k202bp', '88.3', 'bellaire , smith county , kansas', '78', 'd', 'fcc'], ['k216ed', '91.1', 'phillipsburg , kansas', '222', 'd', 'fcc'], ['k241an', '96.1', 'pratt , kansas', '250', 'd', 'fcc'], ['k278ap', '103.5', 'lewis , kansas', '171', 'd', 'fcc'], ['k297ai', '107.3', 'hill city , kansas', '170', 'd', 'fcc']] |
carleton county , new brunswick | https://en.wikipedia.org/wiki/Carleton_County%2C_New_Brunswick | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-170961-2.html.csv | aggregation | the sum of all population living in carleton county , new brunswick is 17660 habitants . | {'scope': 'all', 'col': '4', 'type': 'sum', 'result': '17660', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'population'], 'result': '17660', 'ind': 0, 'tostr': 'sum { all_rows ; population }'}, '17660'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; population } ; 17660 } = true', 'tointer': 'the sum of the population record of all rows is 17660 .'} | round_eq { sum { all_rows ; population } ; 17660 } = true | the sum of the population record of all rows is 17660 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'population_4': 4, '17660_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'population_4': 'population', '17660_5': '17660'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'population_4': [0], '17660_5': [1]} | ['official name', 'status', 'area km 2', 'population', 'census ranking'] | [['wakefield', 'parish', '196.42', '2703', '1079 of 5008'], ['kent', 'parish', '839.79', '2361', '1184 of 5008'], ['woodstock', 'parish', '197.45', '2148', '1258 of 5008'], ['brighton', 'parish', '508.30', '1834', '1402 of 5008'], ['wicklow', 'parish', '195.50', '1753', '1441 of 5008'], ['northampton', 'parish', '243.31', '1599', '1537 of 5008'], ['richmond', 'parish', '258.82', '1414', '1666 of 5008'], ['peel', 'parish', '113.12', '1257', '1779 of 5008'], ['wilmot', 'parish', '191.43', '1143', '1888 of 5008'], ['aberdeen', 'parish', '447.91', '959', '2105 of 5008'], ['simonds', 'parish', '75.54', '489', '3044 of 5008']] |
volleyball at the 2002 asian games | https://en.wikipedia.org/wiki/Volleyball_at_the_2002_Asian_Games | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17978030-6.html.csv | ordinal | the first volleyball game at the 2002 asian games took place at 12pm oct 3 . | {'row': '1', 'col': '1', 'order': '1', 'col_other': '2', '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', 'date', '1'], 'result': '03 oct', 'ind': 0, 'tostr': 'nth_min { all_rows ; date ; 1 }', 'tointer': 'the 1st minimum date record of all rows is 03 oct .'}, '03 oct'], 'result': True, 'ind': 1, 'tostr': 'eq { nth_min { all_rows ; date ; 1 } ; 03 oct }', 'tointer': 'the 1st minimum date record of all rows is 03 oct .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'date', '1'], 'result': None, 'ind': 2, 'tostr': 'nth_argmin { all_rows ; date ; 1 }'}, 'time'], 'result': '12:00', 'ind': 3, 'tostr': 'hop { nth_argmin { all_rows ; date ; 1 } ; time }'}, '12:00'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { nth_argmin { all_rows ; date ; 1 } ; time } ; 12:00 }', 'tointer': 'the time record of the row with 1st minimum date record is 12:00 .'}], 'result': True, 'ind': 5, 'tostr': 'and { eq { nth_min { all_rows ; date ; 1 } ; 03 oct } ; eq { hop { nth_argmin { all_rows ; date ; 1 } ; time } ; 12:00 } } = true', 'tointer': 'the 1st minimum date record of all rows is 03 oct . the time record of the row with 1st minimum date record is 12:00 .'} | and { eq { nth_min { all_rows ; date ; 1 } ; 03 oct } ; eq { hop { nth_argmin { all_rows ; date ; 1 } ; time } ; 12:00 } } = true | the 1st minimum date record of all rows is 03 oct . the time record of the row with 1st minimum date record is 12:00 . | 6 | 6 | {'and_5': 5, 'result_6': 6, 'eq_1': 1, 'nth_min_0': 0, 'all_rows_7': 7, 'date_8': 8, '1_9': 9, '03 oct_10': 10, 'str_eq_4': 4, 'str_hop_3': 3, 'nth_argmin_2': 2, 'all_rows_11': 11, 'date_12': 12, '1_13': 13, 'time_14': 14, '12:00_15': 15} | {'and_5': 'and', 'result_6': 'true', 'eq_1': 'eq', 'nth_min_0': 'nth_min', 'all_rows_7': 'all_rows', 'date_8': 'date', '1_9': '1', '03 oct_10': '03 oct', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'nth_argmin_2': 'nth_argmin', 'all_rows_11': 'all_rows', 'date_12': 'date', '1_13': '1', 'time_14': 'time', '12:00_15': '12:00'} | {'and_5': [6], 'result_6': [], 'eq_1': [5], 'nth_min_0': [1], 'all_rows_7': [0], 'date_8': [0], '1_9': [0], '03 oct_10': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'nth_argmin_2': [3], 'all_rows_11': [2], 'date_12': [2], '1_13': [2], 'time_14': [3], '12:00_15': [4]} | ['date', 'time', 'score', 'set 1', 'set 2', 'set 3', 'total'] | [['03 oct', '12:00', '1 - 3', '25 - 21', '20 - 25', '16 - 25', '83 - 96'], ['03 oct', '14:00', '0 - 3', '18 - 25', '19 - 25', '26 - 28', '63 - 78'], ['05 oct', '12:00', '3 - 1', '29 - 27', '25 - 23', '24 - 26', '103 - 96'], ['05 oct', '14:00', '3 - 0', '25 - 16', '25 - 18', '25 - 13', '75 - 47'], ['06 oct', '10:00', '1 - 3', '16 - 25', '16 - 25', '25 - 17', '78 - 92'], ['06 oct', '12:00', '2 - 3', '21 - 25', '18 - 25', '25 - 21', '99 - 105']] |
list of the green green grass episodes | https://en.wikipedia.org/wiki/List_of_The_Green_Green_Grass_episodes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-17641206-2.html.csv | superlative | episode 1 of the green green grass had the most viewers . | {'scope': 'all', 'col_superlative': '7', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'viewership'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; viewership }'}, 'episode'], 'result': '1', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; viewership } ; episode }'}, '1'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; viewership } ; episode } ; 1 } = true', 'tointer': 'select the row whose viewership record of all rows is maximum . the episode record of this row is 1 .'} | eq { hop { argmax { all_rows ; viewership } ; episode } ; 1 } = true | select the row whose viewership record of all rows is maximum . the episode record of this row is 1 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'num_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'viewership_5': 5, 'episode_6': 6, '1_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'num_hop_1': 'num_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'viewership_5': 'viewership', 'episode_6': 'episode', '1_7': '1'} | {'eq_2': [3], 'result_3': [], 'num_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'viewership_5': [0], 'episode_6': [1], '1_7': [2]} | ['episode', 'title', 'directed by', 'written by', 'original airdate', 'duration', 'viewership'] | [['1', 'keep on running', 'tony dow', 'john sullivan', '9 september 2005', '30 minutes', '8.88 million'], ['2', 'a rocky start', 'tony dow', 'john sullivan', '16 september 2005', '30 minutes', '6.34 million'], ['3', 'the country wife', 'tony dow', 'john sullivan', '23 september 2005', '30 minutes', '5.86 million'], ['4', 'hay fever', 'tony dow', 'john sullivan', '30 september 2005', '30 minutes', '6.33 million'], ['5', 'pillow talk', 'tony dow', 'john sullivan', '7 october 2005', '30 minutes', '6.63 million']] |
1972 vfl season | https://en.wikipedia.org/wiki/1972_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10826385-6.html.csv | count | in the 1972 vfl season , when the away team 's score was under 15.0 , there were 3 times when the crowd was under 20000 . | {'scope': 'subset', 'criterion': 'less_than', 'value': '20000', 'result': '3', 'col': '6', 'subset': {'col': '4', 'criterion': 'less_than', 'value': '15.0'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_less', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'away team score', '15.0'], 'result': None, 'ind': 0, 'tostr': 'filter_less { all_rows ; away team score ; 15.0 }', 'tointer': 'select the rows whose away team score record is less than 15.0 .'}, 'crowd', '20000'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose away team score record is less than 15.0 . among these rows , select the rows whose crowd record is less than 20000 .', 'tostr': 'filter_less { filter_less { all_rows ; away team score ; 15.0 } ; crowd ; 20000 }'}], 'result': '3', 'ind': 2, 'tostr': 'count { filter_less { filter_less { all_rows ; away team score ; 15.0 } ; crowd ; 20000 } }', 'tointer': 'select the rows whose away team score record is less than 15.0 . among these rows , select the rows whose crowd record is less than 20000 . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_less { filter_less { all_rows ; away team score ; 15.0 } ; crowd ; 20000 } } ; 3 } = true', 'tointer': 'select the rows whose away team score record is less than 15.0 . among these rows , select the rows whose crowd record is less than 20000 . the number of such rows is 3 .'} | eq { count { filter_less { filter_less { all_rows ; away team score ; 15.0 } ; crowd ; 20000 } } ; 3 } = true | select the rows whose away team score record is less than 15.0 . among these rows , select the rows whose crowd record is less than 20000 . the number of such rows is 3 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_less_1': 1, 'filter_less_0': 0, 'all_rows_5': 5, 'away team score_6': 6, '15.0_7': 7, 'crowd_8': 8, '20000_9': 9, '3_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_less_1': 'filter_less', 'filter_less_0': 'filter_less', 'all_rows_5': 'all_rows', 'away team score_6': 'away team score', '15.0_7': '15.0', 'crowd_8': 'crowd', '20000_9': '20000', '3_10': '3'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_less_1': [2], 'filter_less_0': [1], 'all_rows_5': [0], 'away team score_6': [0], '15.0_7': [0], 'crowd_8': [1], '20000_9': [1], '3_10': [3]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['collingwood', '14.12 ( 96 )', 'hawthorn', '15.11 ( 101 )', 'victoria park', '29885', '6 may 1972'], ['carlton', '22.15 ( 147 )', 'geelong', '14.14 ( 98 )', 'princes park', '19073', '6 may 1972'], ['st kilda', '24.21 ( 165 )', 'richmond', '10.16 ( 76 )', 'moorabbin oval', '34055', '6 may 1972'], ['footscray', '16.16 ( 112 )', 'fitzroy', '13.12 ( 90 )', 'western oval', '18466', '6 may 1972'], ['melbourne', '16.13 ( 109 )', 'essendon', '12.13 ( 85 )', 'mcg', '41537', '6 may 1972'], ['south melbourne', '14.22 ( 106 )', 'north melbourne', '13.13 ( 91 )', 'vfl park', '9099', '6 may 1972']] |
kjil | https://en.wikipedia.org/wiki/KJIL | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14993406-2.html.csv | count | for kjil , when the class is d , there were two frequencies under 90.0 . | {'scope': 'subset', 'criterion': 'less_than', 'value': '90.0', 'result': '2', 'col': '2', 'subset': {'col': '5', 'criterion': 'equal', 'value': 'd'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_less', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'class', 'd'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; class ; d }', 'tointer': 'select the rows whose class record fuzzily matches to d .'}, 'frequency mhz', '90.0'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose class record fuzzily matches to d . among these rows , select the rows whose frequency mhz record is less than 90.0 .', 'tostr': 'filter_less { filter_eq { all_rows ; class ; d } ; frequency mhz ; 90.0 }'}], 'result': '2', 'ind': 2, 'tostr': 'count { filter_less { filter_eq { all_rows ; class ; d } ; frequency mhz ; 90.0 } }', 'tointer': 'select the rows whose class record fuzzily matches to d . among these rows , select the rows whose frequency mhz record is less than 90.0 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_less { filter_eq { all_rows ; class ; d } ; frequency mhz ; 90.0 } } ; 2 } = true', 'tointer': 'select the rows whose class record fuzzily matches to d . among these rows , select the rows whose frequency mhz record is less than 90.0 . the number of such rows is 2 .'} | eq { count { filter_less { filter_eq { all_rows ; class ; d } ; frequency mhz ; 90.0 } } ; 2 } = true | select the rows whose class record fuzzily matches to d . among these rows , select the rows whose frequency mhz record is less than 90.0 . the number of such rows is 2 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_less_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'class_6': 6, 'd_7': 7, 'frequency mhz_8': 8, '90.0_9': 9, '2_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', 'class_6': 'class', 'd_7': 'd', 'frequency mhz_8': 'frequency mhz', '90.0_9': '90.0', '2_10': '2'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_less_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'class_6': [0], 'd_7': [0], 'frequency mhz_8': [1], '90.0_9': [1], '2_10': [3]} | ['call sign', 'frequency mhz', 'city of license', 'erp w', 'class', 'fcc info'] | [['kngm', '88.9', 'guymon , oklahoma', '25000', 'c3', 'fcc'], ['kjov', '90.7', 'woodward , oklahoma', '25000', 'c2', 'fcc'], ['kjhl', '90.9', 'boise city , oklahoma', '10000', 'c3', 'fcc'], ['k229av', '93.7', 'alva , oklahoma', '170', 'd', 'fcc'], ['k204fy', '88.7', 'fairview , oklahoma', '50', 'd', 'fcc'], ['k202dc', '88.3', 'shattuck , oklahoma', '230', 'd', 'fcc']] |
united states house of representatives elections , 1926 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1926 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1342379-45.html.csv | majority | of the incumbents in the 1926 election for united states house of representatives , all of them were re-elected . | {'scope': 'all', 'col': '5', 'most_or_all': 'all', 'criterion': 'equal', 'value': 're - elected', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'result', 're - elected'], 'result': True, 'ind': 0, 'tointer': 'for the result records of all rows , all of them fuzzily match to re - elected .', 'tostr': 'all_eq { all_rows ; result ; re - elected } = true'} | all_eq { all_rows ; result ; re - elected } = true | for the result records of all rows , all of them fuzzily match to re - elected . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'result_3': 3, 're - elected_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'result_3': 'result', 're - elected_4': 're - elected'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'result_3': [0], 're - elected_4': [0]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['virginia 1', 's otis bland', 'democratic', '1918', 're - elected', 's otis bland ( d ) unopposed'], ['virginia 2', 'joseph t deal', 'democratic', '1920', 're - elected', 'joseph t deal ( d ) 65.4 % l s parsons ( r ) 34.6 %'], ['virginia 3', 'andrew jackson montague', 'democratic', '1912', 're - elected', 'andrew jackson montague ( d ) unopposed'], ['virginia 4', 'patrick h drewry', 'democratic', '1920', 're - elected', 'patrick h drewry ( d ) unopposed'], ['virginia 5', 'joseph whitehead', 'democratic', '1924', 're - elected', 'joseph whitehead ( d ) unopposed'], ['virginia 6', 'clifton a woodrum', 'democratic', '1922', 're - elected', 'clifton a woodrum ( d ) unopposed'], ['virginia 8', 'r walton moore', 'democratic', '1919', 're - elected', 'r walton moore ( d ) 95.5 % j w leedy ( r ) 4.5 %'], ['virginia 9', 'george c peery', 'democratic', '1922', 're - elected', 'george c peery ( d ) 53.4 % s r hurley ( r ) 46.6 %']] |
samantha miss | https://en.wikipedia.org/wiki/Samantha_Miss | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-20626467-1.html.csv | count | of the races that samantha miss participated in , 5 of them had randwick as the venue . | {'scope': 'all', 'criterion': 'equal', 'value': 'randwick', 'result': '5', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'venue', 'randwick'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose venue record fuzzily matches to randwick .', 'tostr': 'filter_eq { all_rows ; venue ; randwick }'}], 'result': '5', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; venue ; randwick } }', 'tointer': 'select the rows whose venue record fuzzily matches to randwick . the number of such rows is 5 .'}, '5'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; venue ; randwick } } ; 5 } = true', 'tointer': 'select the rows whose venue record fuzzily matches to randwick . the number of such rows is 5 .'} | eq { count { filter_eq { all_rows ; venue ; randwick } } ; 5 } = true | select the rows whose venue record fuzzily matches to randwick . the number of such rows is 5 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'venue_5': 5, 'randwick_6': 6, '5_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'venue_5': 'venue', 'randwick_6': 'randwick', '5_7': '5'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'venue_5': [0], 'randwick_6': [0], '5_7': [2]} | ['result', 'date', 'race', 'venue', 'distance', 'class', 'weight ( kg )', 'time', 'jockey', 'odds', 'winner / 2nd'] | [['1st', '12 / 03 / 08', 'wattle grove handicap', 'kensington', '1150 m', 'handicap', '54.5 kg', '1 - 07.95', 'hugh bowman', '1.75 f', '2nd - packing supreme'], ['3rd', '29 / 03 / 08', 'sweet embrace stakes', 'randwick', '1200 m', 'group 3', '55.5 kg', '1 - 11.03', 'hugh bowman', '3.00 f', '1st - stripper'], ['4th', '12 / 04 / 08', 'magic night stakes', 'rosehill', '1200 m', 'group 2', '55.5 kg', '1 - 11.91', 'hugh bowman', '4.40', '1st - portillo'], ['2nd', '26 / 04 / 08', 'ajc sires produce stakes', 'randwick', '1400 m', 'group 1', '54.5 kg', '1 - 25.99', 'hugh bowman', '12.00', '1st - sebring'], ['1st', '03 / 05 / 08', 'champagne stakes', 'randwick', '1600 m', 'group 1', '54.4 kg', '1 - 38.28', 'hugh bowman', '6.00', '2nd - sebring'], ['1st', '23 / 08 / 08', 'silver shadow stakes', 'wawrick farm', '1200 m', 'group 3', '58 kg', '1 - 12.44', 'hugh bowman', '6.00', '2nd - glowlamp'], ['1st', '09 / 09 / 08', 'furious stakes', 'randwick', '1400 m', 'group 2', '56 kg', '1 - 26.21', 'hugh bow man', '2.20 f', '2nd - love and kisses'], ['1st', '20 / 09 / 08', 'tea rose stakes', 'rosehill', '1500 m', 'group 2', '56 kg', '1 - 30.61', 'hugh bowman', '1.95 f', '2nd - kimillsy'], ['1st', '04 / 10 / 08', 'flight stakes', 'randwick', '1600 m', 'group 1', '56 kg', '1 - 38.49', 'hugh bowman', '1.55 f', '2nd - portillo'], ['3rd', '25 / 10 / 08', 'cox plate', 'moonee valley', '2040 m', 'group 1', '47.5 kg', '2 - 06.92', 'glen boss', '4.60 f', '1st - maldivian'], ['1st', '08 / 11 / 08', 'vrc oaks', 'flemington', '2500 m', 'group 1', '55.5 kg', '2 - 37.57', 'hugh bowman', '1.85 f', '2nd - miss scarlatti']] |
united states house of representatives elections , 2006 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_2006 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1805191-47.html.csv | aggregation | all districts in the 2006 house elections have incumbents with an average first elected year of around 1992 . | {'scope': 'all', 'col': '4', 'type': 'average', 'result': '1992', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'first elected'], 'result': '1992', 'ind': 0, 'tostr': 'avg { all_rows ; first elected }'}, '1992'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; first elected } ; 1992 } = true', 'tointer': 'the average of the first elected record of all rows is 1992 .'} | round_eq { avg { all_rows ; first elected } ; 1992 } = true | the average of the first elected record of all rows is 1992 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'first elected_4': 4, '1992_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'first elected_4': 'first elected', '1992_5': '1992'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'first elected_4': [0], '1992_5': [1]} | ['district', 'incumbent', 'party', 'first elected', 'results'] | [['virginia 1', 'jo ann davis', 'republican', '2000', 're - elected'], ['virginia 2', 'thelma drake', 'republican', '2004', 're - elected'], ['virginia 3', 'bobby scott', 'democratic', '1992', 're - elected'], ['virginia 4', 'randy forbes', 'republican', '2001', 're - elected'], ['virginia 5', 'virgil goode', 'republican', '1996', 're - elected'], ['virginia 6', 'bob goodlatte', 'republican', '1992', 're - elected'], ['virginia 7', 'eric cantor', 'republican', '2000', 're - elected'], ['virginia 8', 'jim moran', 'democratic', '1990', 're - elected'], ['virginia 9', 'rick boucher', 'democratic', '1982', 're - elected'], ['virginia 10', 'frank wolf', 'republican', '1980', 're - elected'], ['virginia 11', 'tom davis', 'republican', '1994', 're - elected']] |
1944 in brazilian football | https://en.wikipedia.org/wiki/1944_in_Brazilian_football | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15331540-1.html.csv | ordinal | the palmeiras had the second best goal differential among all teams in the 1944 brazilian football league . | {'row': '1', 'col': '8', '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', 'difference', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; difference ; 2 }'}, 'team'], 'result': 'palmeiras', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; difference ; 2 } ; team }'}, 'palmeiras'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; difference ; 2 } ; team } ; palmeiras } = true', 'tointer': 'select the row whose difference record of all rows is 2nd maximum . the team record of this row is palmeiras .'} | eq { hop { nth_argmax { all_rows ; difference ; 2 } ; team } ; palmeiras } = true | select the row whose difference record of all rows is 2nd maximum . the team record of this row is palmeiras . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'difference_5': 5, '2_6': 6, 'team_7': 7, 'palmeiras_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', 'difference_5': 'difference', '2_6': '2', 'team_7': 'team', 'palmeiras_8': 'palmeiras'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'difference_5': [0], '2_6': [0], 'team_7': [1], 'palmeiras_8': [2]} | ['position', 'team', 'points', 'played', 'drawn', 'lost', 'against', 'difference'] | [['1', 'palmeiras', '32', '20', '2', '3', '19', '31'], ['2', 'são paulo', '29', '20', '3', '4', '32', '37'], ['3', 'corinthians', '28', '20', '4', '4', '35', '20'], ['4', 'ypiranga - sp', '23', '20', '3', '7', '29', '8'], ['5', 'são paulo railway', '21', '20', '3', '8', '48', '- 7'], ['6', 'santos', '20', '20', '4', '8', '41', '- 2'], ['7', 'juventus', '18', '20', '4', '9', '49', '- 10'], ['8', 'comercial - sp', '18', '20', '2', '10', '57', '- 15'], ['9', 'portuguesa', '12', '20', '6', '11', '47', '- 18'], ['10', 'jabaquara', '10', '20', '0', '15', '50', '- 12'], ['11', 'portuguesa santista', '9', '20', '3', '14', '69', '- 32']] |
2008 - 09 orlando magic season | https://en.wikipedia.org/wiki/2008%E2%80%9309_Orlando_Magic_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-17311797-11.html.csv | majority | amway arena was the location for most of the games . | {'scope': 'all', 'col': '8', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'amway arena', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'location attendance', 'amway arena'], 'result': True, 'ind': 0, 'tointer': 'for the location attendance records of all rows , most of them fuzzily match to amway arena .', 'tostr': 'most_eq { all_rows ; location attendance ; amway arena } = true'} | most_eq { all_rows ; location attendance ; amway arena } = true | for the location attendance records of all rows , most of them fuzzily match to amway arena . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'location attendance_3': 3, 'amway arena_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'location attendance_3': 'location attendance', 'amway arena_4': 'amway arena'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'location attendance_3': [0], 'amway arena_4': [0]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'series'] | [['1', 'april 19', '76ers', 'l 98 - 100 ( ot )', 'dwight howard ( 31 )', 'dwight howard ( 16 )', 'rafer alston ( 5 )', 'amway arena 17461', '0 - 1'], ['2', 'april 22', '76ers', 'w 96 - 87 ( ot )', 'courtney lee ( 24 )', 'dwight howard ( 10 )', 'rashard lewis ( 6 )', 'amway arena 17461', '1 - 1'], ['3', 'april 24', '76ers', 'l 94 - 96 ( ot )', 'dwight howard ( 36 )', 'dwight howard ( 11 )', 'courtney lee ( 5 )', 'wachovia center 16492', '1 - 2'], ['4', 'april 26', '76ers', 'w 84 - 81 ( ot )', 'dwight howard ( 18 )', 'dwight howard ( 18 )', 'rafer alston ( 5 )', 'wachovia center 16464', '2 - 2'], ['5', 'april 28', '76ers', 'w 91 - 78 ( ot )', 'dwight howard , rashard lewis ( 24 )', 'dwight howard ( 24 )', 'rafer alston , hedo türkoğlu ( 4 )', 'amway arena 17461', '3 - 2']] |
1987 k league | https://en.wikipedia.org/wiki/1987_K_League | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14479112-3.html.csv | superlative | choi sang - kuk was the only player to score at least 15 goals in the 1987 k league . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '1', 'value_mentioned': 'yes', 'max_or_min': 'max', 'other_col': '2', 'subset': None} | {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'max', 'args': ['all_rows', 'goals'], 'result': '15', 'ind': 0, 'tostr': 'max { all_rows ; goals }', 'tointer': 'the maximum goals record of all rows is 15 .'}, '15'], 'result': True, 'ind': 1, 'tostr': 'eq { max { all_rows ; goals } ; 15 }', 'tointer': 'the maximum goals record of all rows is 15 .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'goals'], 'result': None, 'ind': 2, 'tostr': 'argmax { all_rows ; goals }'}, 'scorer'], 'result': 'choi sang - kuk', 'ind': 3, 'tostr': 'hop { argmax { all_rows ; goals } ; scorer }'}, 'choi sang - kuk'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { argmax { all_rows ; goals } ; scorer } ; choi sang - kuk }', 'tointer': 'the scorer record of the row with superlative goals record is choi sang - kuk .'}], 'result': True, 'ind': 5, 'tostr': 'and { eq { max { all_rows ; goals } ; 15 } ; eq { hop { argmax { all_rows ; goals } ; scorer } ; choi sang - kuk } } = true', 'tointer': 'the maximum goals record of all rows is 15 . the scorer record of the row with superlative goals record is choi sang - kuk .'} | and { eq { max { all_rows ; goals } ; 15 } ; eq { hop { argmax { all_rows ; goals } ; scorer } ; choi sang - kuk } } = true | the maximum goals record of all rows is 15 . the scorer record of the row with superlative goals record is choi sang - kuk . | 6 | 6 | {'and_5': 5, 'result_6': 6, 'eq_1': 1, 'max_0': 0, 'all_rows_7': 7, 'goals_8': 8, '15_9': 9, 'str_eq_4': 4, 'str_hop_3': 3, 'argmax_2': 2, 'all_rows_10': 10, 'goals_11': 11, 'scorer_12': 12, 'choi sang - kuk_13': 13} | {'and_5': 'and', 'result_6': 'true', 'eq_1': 'eq', 'max_0': 'max', 'all_rows_7': 'all_rows', 'goals_8': 'goals', '15_9': '15', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'argmax_2': 'argmax', 'all_rows_10': 'all_rows', 'goals_11': 'goals', 'scorer_12': 'scorer', 'choi sang - kuk_13': 'choi sang - kuk'} | {'and_5': [6], 'result_6': [], 'eq_1': [5], 'max_0': [1], 'all_rows_7': [0], 'goals_8': [0], '15_9': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'argmax_2': [3], 'all_rows_10': [2], 'goals_11': [2], 'scorer_12': [3], 'choi sang - kuk_13': [4]} | ['rank', 'scorer', 'club', 'goals', 'matches'] | [['1', 'choi sang - kuk', 'posco atoms', '15', '30'], ['2', 'lee heung - sil', 'posco atoms', '12', '29'], ['2', 'noh soo - jin', 'yukong elephants', '12', '30'], ['4', 'kim joo - sung', 'daewoo royals', '10', '28'], ['5', 'kim hong - woon', 'posco atoms', '9', '26'], ['6', 'lee sang - cheol', 'hyundai horang - i', '8', '28'], ['7', 'park hang - seo', 'lucky - goldstar hwangso', '7', '28'], ['8', '3 players', '3 players', '6', '-'], ['11', '2 players', '2 players', '5', '-'], ['13', '5 players', '5 players', '4', '-'], ['18', '12 players', '12 players', '3', '-'], ['30', '12 players', '12 players', '2', '-'], ['42', '15 players', '15 players', '1', '-'], ['own goals', 'own goals', 'own goals', '3', '-']] |
aalesunds fk | https://en.wikipedia.org/wiki/Aalesunds_FK | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1149273-1.html.csv | superlative | the highest score aalesunds fk has scored at an away game is two points . | {'scope': 'all', 'col_superlative': '6', 'row_superlative': '2', 'value_mentioned': 'yes', 'max_or_min': 'max', 'other_col': 'n/a', 'subset': None} | {'func': 'eq', 'args': [{'func': 'max', 'args': ['all_rows', 'away'], 'result': '2 - 0', 'ind': 0, 'tostr': 'max { all_rows ; away }', 'tointer': 'the maximum away record of all rows is 2 - 0 .'}, '2 - 0'], 'result': True, 'ind': 1, 'tostr': 'eq { max { all_rows ; away } ; 2 - 0 } = true', 'tointer': 'the maximum away record of all rows is 2 - 0 .'} | eq { max { all_rows ; away } ; 2 - 0 } = true | the maximum away record of all rows is 2 - 0 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'max_0': 0, 'all_rows_3': 3, 'away_4': 4, '2 - 0_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'max_0': 'max', 'all_rows_3': 'all_rows', 'away_4': 'away', '2 - 0_5': '2 - 0'} | {'eq_1': [2], 'result_2': [], 'max_0': [1], 'all_rows_3': [0], 'away_4': [0], '2 - 0_5': [1]} | ['season', 'competition', 'round', 'club', 'home', 'away', 'aggregate'] | [['2010 - 11', 'uefa europa league', 'q3', 'motherwell', '1 - 1', '0 - 3', '1 - 4'], ['2011 - 12', 'uefa europa league', 'q1', 'neath', '4 - 1', '2 - 0', '6 - 1'], ['2011 - 12', 'uefa europa league', 'q2', 'ferencváros', '3 - 1 ( aet )', '1 - 2', '4 - 3'], ['2011 - 12', 'uefa europa league', 'q3', 'elfsborg', '4 - 0', '1 - 1', '5 - 1'], ['2011 - 12', 'uefa europa league', 'play - off', 'az', '2 - 1', '0 - 6', '2 - 7'], ['2012 - 13', 'uefa europa league', 'q2', 'tirana', '5 - 0', '1 - 1', '6 - 1'], ['2012 - 13', 'uefa europa league', 'q3', 'apoel', '0 - 1', '1 - 2', '1 - 3']] |
paraguayan guaraní | https://en.wikipedia.org/wiki/Paraguayan_guaran%C3%AD | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1354940-2.html.csv | majority | most of the denominations of paraguayan guarani were first issued after 1980 . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'greater_than', 'value': '1980', 'subset': None} | {'func': 'most_greater', 'args': ['all_rows', 'first issued', '1980'], 'result': True, 'ind': 0, 'tointer': 'for the first issued records of all rows , most of them are greater than 1980 .', 'tostr': 'most_greater { all_rows ; first issued ; 1980 } = true'} | most_greater { all_rows ; first issued ; 1980 } = true | for the first issued records of all rows , most of them are greater than 1980 . | 1 | 1 | {'most_greater_0': 0, 'result_1': 1, 'all_rows_2': 2, 'first issued_3': 3, '1980_4': 4} | {'most_greater_0': 'most_greater', 'result_1': 'true', 'all_rows_2': 'all_rows', 'first issued_3': 'first issued', '1980_4': '1980'} | {'most_greater_0': [1], 'result_1': [], 'all_rows_2': [0], 'first issued_3': [0], '1980_4': [0]} | ['value', 'color', 'obverse', 'reverse', 'first issued'] | [['2.000', 'magenta', 'adela and celsa speratti', 'school parade', '2008'], ['5.000', 'orange', 'carlos antonio lópez', 'palace of the lopez', '1962'], ['10.000', 'brown', 'dr josé josé gaspar rodríguez de francia', 'may 15 , 1811 scene', '1962'], ['20.000', 'light blue', 'paraguayan woman', 'central bank of paraguay', '2005'], ['50.000', 'beige', 'agustín pío barrios', 'guitar of agustín pío barrios', '1981'], ['100.000', 'green', 'saint roque gonzález de santa cruz', 'itaipú dam', '1998']] |
united states house of representatives elections , 1924 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1924 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1342393-23.html.csv | unique | william y humphreys was the only congressman who did not run for re-election in 1924 . | {'scope': 'all', 'row': '3', 'col': '5', 'col_other': '2', 'criterion': 'fuzzily_match', 'value': 'retired democratic hold', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'result', 'retired democratic hold'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose result record fuzzily matches to retired democratic hold .', 'tostr': 'filter_eq { all_rows ; result ; retired democratic hold }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; result ; retired democratic hold } }', 'tointer': 'select the rows whose result record fuzzily matches to retired democratic hold . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'result', 'retired democratic hold'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose result record fuzzily matches to retired democratic hold .', 'tostr': 'filter_eq { all_rows ; result ; retired democratic hold }'}, 'incumbent'], 'result': 'william y humphreys', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; result ; retired democratic hold } ; incumbent }'}, 'william y humphreys'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; result ; retired democratic hold } ; incumbent } ; william y humphreys }', 'tointer': 'the incumbent record of this unqiue row is william y humphreys .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; result ; retired democratic hold } } ; eq { hop { filter_eq { all_rows ; result ; retired democratic hold } ; incumbent } ; william y humphreys } } = true', 'tointer': 'select the rows whose result record fuzzily matches to retired democratic hold . there is only one such row in the table . the incumbent record of this unqiue row is william y humphreys .'} | and { only { filter_eq { all_rows ; result ; retired democratic hold } } ; eq { hop { filter_eq { all_rows ; result ; retired democratic hold } ; incumbent } ; william y humphreys } } = true | select the rows whose result record fuzzily matches to retired democratic hold . there is only one such row in the table . the incumbent record of this unqiue row is william y humphreys . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'result_7': 7, 'retired democratic hold_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'incumbent_9': 9, 'william y humphreys_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'result_7': 'result', 'retired democratic hold_8': 'retired democratic hold', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'incumbent_9': 'incumbent', 'william y humphreys_10': 'william y humphreys'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'result_7': [0], 'retired democratic hold_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'incumbent_9': [2], 'william y humphreys_10': [3]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['mississippi 1', 'john e rankin', 'democratic', '1920', 're - elected', 'john e rankin ( d ) unopposed'], ['mississippi 2', 'bill g lowrey', 'democratic', '1920', 're - elected', 'bill g lowrey ( d ) unopposed'], ['mississippi 3', 'william y humphreys', 'democratic', '1923', 'retired democratic hold', 'william madison whittington ( d ) unopposed'], ['mississippi 4', 'jeff busby', 'democratic', '1922', 're - elected', 'jeff busby ( d ) 95.7 % r h dekay ( r ) 4.3 %'], ['mississippi 5', 'ross a collins', 'democratic', '1920', 're - elected', 'ross a collins ( d ) unopposed'], ['mississippi 6', 't webber wilson', 'democratic', '1922', 're - elected', 't webber wilson ( d ) unopposed'], ['mississippi 7', 'percy e quin', 'democratic', '1912', 're - elected', 'percy e quin ( d ) unopposed']] |
progressive conservative party of canada | https://en.wikipedia.org/wiki/Progressive_Conservative_Party_of_Canada | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-123462-2.html.csv | superlative | the year which was the most succesful in terms of seats won for the progressive conservative party of canada was 1984 . | {'scope': 'all', 'col_superlative': '3', 'row_superlative': '14', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'of seats won'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; of seats won }'}, 'election'], 'result': '1984', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; of seats won } ; election }'}, '1984'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; of seats won } ; election } ; 1984 } = true', 'tointer': 'select the row whose of seats won record of all rows is maximum . the election record of this row is 1984 .'} | eq { hop { argmax { all_rows ; of seats won } ; election } ; 1984 } = true | select the row whose of seats won record of all rows is maximum . the election record of this row is 1984 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'num_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'of seats won_5': 5, 'election_6': 6, '1984_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'num_hop_1': 'num_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'of seats won_5': 'of seats won', 'election_6': 'election', '1984_7': '1984'} | {'eq_2': [3], 'result_3': [], 'num_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'of seats won_5': [0], 'election_6': [1], '1984_7': [2]} | ['election', 'of candidates nominated', 'of seats won', 'of total votes', '% of popular vote'] | [['1945', '203', '65', '1448744', '27.62 %'], ['1949', '249', '41', '1734261', '29.62 %'], ['1953', '248', '50', '1749579', '31.01 %'], ['1957', '256', '109', '2564732', '38.81 %'], ['1958', '265', '208', '3908633', '53.56 %'], ['1962', '265', '114', '2865542', '37.22 %'], ['1963', '265', '93', '2582322', '32.72 %'], ['1965', '265', '95', '2500113', '32.41 %'], ['1968', '262', '72', '2548949', '31.36 %'], ['1972', '265', '107', '3388980', '35.02 %'], ['1974', '264', '95', '3371319', '35.46 %'], ['1979', '282', '136', '4111606', '35.89 %'], ['1980', '282', '103', '3552994', '32.49 %'], ['1984', '282', '211', '6278818', '50.03 %'], ['1988', '295', '169', '5667543', '43.02 %'], ['1993', '295', '2', '2178303', '16.04 %'], ['1997', '301', '20', '2446705', '18.84 %'], ['2000', '291', '12', '1566994', '12.19 %']] |
amanda overmyer | https://en.wikipedia.org/wiki/Amanda_Overmyer | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-15796072-1.html.csv | unique | " you ca n't do that " was the only beatles song that amanda overmyer sang . | {'scope': 'all', 'row': '6', 'col': '4', 'col_other': '3', 'criterion': 'equal', 'value': 'the beatles', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'original artist', 'the beatles'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose original artist record fuzzily matches to the beatles .', 'tostr': 'filter_eq { all_rows ; original artist ; the beatles }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; original artist ; the beatles } }', 'tointer': 'select the rows whose original artist record fuzzily matches to the beatles . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'original artist', 'the beatles'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose original artist record fuzzily matches to the beatles .', 'tostr': 'filter_eq { all_rows ; original artist ; the beatles }'}, 'song choice'], 'result': "you ca n't do that", 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; original artist ; the beatles } ; song choice }'}, "you ca n't do that"], 'result': True, 'ind': 3, 'tostr': "eq { hop { filter_eq { all_rows ; original artist ; the beatles } ; song choice } ; you ca n't do that }", 'tointer': "the song choice record of this unqiue row is you ca n't do that ."}], 'result': True, 'ind': 4, 'tostr': "and { only { filter_eq { all_rows ; original artist ; the beatles } } ; eq { hop { filter_eq { all_rows ; original artist ; the beatles } ; song choice } ; you ca n't do that } } = true", 'tointer': "select the rows whose original artist record fuzzily matches to the beatles . there is only one such row in the table . the song choice record of this unqiue row is you ca n't do that ."} | and { only { filter_eq { all_rows ; original artist ; the beatles } } ; eq { hop { filter_eq { all_rows ; original artist ; the beatles } ; song choice } ; you ca n't do that } } = true | select the rows whose original artist record fuzzily matches to the beatles . there is only one such row in the table . the song choice record of this unqiue row is you ca n't do that . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'original artist_7': 7, 'the beatles_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'song choice_9': 9, "you can't do that_10": 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'original artist_7': 'original artist', 'the beatles_8': 'the beatles', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'song choice_9': 'song choice', "you can't do that_10": "you ca n't do that"} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'original artist_7': [0], 'the beatles_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'song choice_9': [2], "you can't do that_10": [3]} | ['week', 'theme', 'song choice', 'original artist', 'order', 'result'] | [['hollywood', 'n / a', 'light my fire', 'the doors', 'n / a', 'advanced'], ['hollywood', 'n / a', 'piece of my heart', 'erma franklin', 'n / a', 'advanced'], ['top 24 ( 12 women )', '1960s', "baby , please do n't go", 'big joe williams', '4', 'safe'], ['top 20 ( 10 women )', '1970s', 'carry on wayward son', 'kansas', '6', 'safe'], ['top 16 ( 8 women )', '1980s', 'i hate myself for loving you', 'joan jett and the blackhearts', '3', 'safe'], ['top 12', 'lennonmccartney', "you ca n't do that", 'the beatles', '9', 'safe']] |
jack ahearn | https://en.wikipedia.org/wiki/Jack_Ahearn | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15212423-2.html.csv | aggregation | in the seasons of motorcycle racing listed for jack ahearn he managed to achieve a total of 66 points . | {'scope': 'all', 'col': '4', 'type': 'sum', 'result': '66', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'points'], 'result': '66', 'ind': 0, 'tostr': 'sum { all_rows ; points }'}, '66'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; points } ; 66 } = true', 'tointer': 'the sum of the points record of all rows is 66 .'} | round_eq { sum { all_rows ; points } ; 66 } = true | the sum of the points record of all rows is 66 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'points_4': 4, '66_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'points_4': 'points', '66_5': '66'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'points_4': [0], '66_5': [1]} | ['year', 'class', 'team', 'points', 'wins'] | [['1954', '350cc', 'norton', '0', '0'], ['1954', '500cc', 'norton', '0', '0'], ['1955', '350cc', 'norton', '0', '0'], ['1955', '500cc', 'norton', '1', '0'], ['1958', '350cc', 'ajs', '0', '0'], ['1958', '500cc', 'matchless', '0', '0'], ['1962', '350cc', 'norton', '0', '0'], ['1962', '500cc', 'norton', '0', '0'], ['1963', '125cc', 'ducati', '0', '0'], ['1963', '350cc', 'norton', '4', '0'], ['1963', '500cc', 'norton', '5', '1'], ['1964', '125cc', 'honda', '0', '0'], ['1964', '250cc', 'suzuki', '0', '0'], ['1964', '350cc', 'norton', '1', '0'], ['1964', '500cc', 'norton', '25', '1'], ['1965', '500cc', 'norton', '9', '0'], ['1966', '350cc', 'norton', '8', '0'], ['1966', '500cc', 'norton', '13', '0'], ['1974', '350cc', 'yamaha', '0', '0']] |
lukáš lacko | https://en.wikipedia.org/wiki/Luk%C3%A1%C5%A1_Lacko | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15271640-8.html.csv | majority | most of lukáš lacko 's tournaments from 2006 to 2013 were played on hard surfaces . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'hard', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'surface', 'hard'], 'result': True, 'ind': 0, 'tointer': 'for the surface records of all rows , most of them fuzzily match to hard .', 'tostr': 'most_eq { all_rows ; surface ; hard } = true'} | most_eq { all_rows ; surface ; hard } = true | for the surface records of all rows , most of them fuzzily match to hard . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'surface_3': 3, 'hard_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'surface_3': 'surface', 'hard_4': 'hard'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'surface_3': [0], 'hard_4': [0]} | ['outcome', 'date', 'tournament', 'surface', 'opponent', 'score'] | [['runner - up', '7 august 2006', 'binghamton , new york , united states', 'hard', 'scott oudsema', '6 - 7 ( 5 - 7 ) , 2 - 6'], ['runner - up', '7 may 2007', 'rijeka , croatia', 'clay', 'marin čilić', '5 - 7 , 2 - 6'], ['runner - up', '6 august 2007', 'istanbul , turkey', 'hard', 'mischa zverev', '4 - 6 , 4 - 6'], ['winner', '15 october 2007', 'kolding , denmark', 'hard ( i )', 'gilles müller', '7 - 6 ( 7 - 3 ) , 6 - 4'], ['winner', '18 may 2009', 'fergana , uzbekistan', 'hard', 'samuel groth', '4 - 6 , 7 - 5 , 7 - 6 ( 7 - 4 )'], ['winner', '26 october 2009', 'seoul , south korea', 'hard', 'dušan lojda', '6 - 4 , 6 - 2'], ['runner - up', '8 november 2010', 'urtijëi , italy', 'carpet ( i )', 'michał przysiężny', '3 - 6 , 5 - 7'], ['winner', '25 september 2011', 'izmir , turkey', 'hard', 'marsel ilhan', '6 - 4 , 6 - 3'], ['winner', '20 november 2011', 'bratislava , slovakia', 'hard', 'ričardas berankis', '7 - 6 ( 9 - 7 ) , 6 - 2'], ['runner - up', '14 october 2012', 'tashkent , uzbekistan', 'hard', 'uladzimir ignatik', '3 - 6 , 6 - 7 ( 3 - 7 )'], ['winner', '18 november 2012', 'helsinki , finland', 'hard', 'jarkko nieminen', '6 - 3 , 6 - 4'], ['runner - up', '21 july 2013', 'grandby , canada', 'hard', 'frank dancevic', '4 - 6 , 7 - 6 , 3 - 6']] |
1969 los angeles dodgers season | https://en.wikipedia.org/wiki/1969_Los_Angeles_Dodgers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12901325-10.html.csv | comparative | pat harrison was selected in an earlier round than george pugh was selected . | {'row_1': '1', 'row_2': '3', 'col': '1', 'col_other': '2', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'name', 'pat harrison'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose name record fuzzily matches to pat harrison .', 'tostr': 'filter_eq { all_rows ; name ; pat harrison }'}, 'round'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; name ; pat harrison } ; round }', 'tointer': 'select the rows whose name record fuzzily matches to pat harrison . take the round record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'name', 'george pugh'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose name record fuzzily matches to george pugh .', 'tostr': 'filter_eq { all_rows ; name ; george pugh }'}, 'round'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; name ; george pugh } ; round }', 'tointer': 'select the rows whose name record fuzzily matches to george pugh . take the round record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; name ; pat harrison } ; round } ; hop { filter_eq { all_rows ; name ; george pugh } ; round } } = true', 'tointer': 'select the rows whose name record fuzzily matches to pat harrison . take the round record of this row . select the rows whose name record fuzzily matches to george pugh . take the round record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; name ; pat harrison } ; round } ; hop { filter_eq { all_rows ; name ; george pugh } ; round } } = true | select the rows whose name record fuzzily matches to pat harrison . take the round record of this row . select the rows whose name record fuzzily matches to george pugh . take the round record of this row . the first record is less than the second record . | 5 | 5 | {'less_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'name_7': 7, 'pat harrison_8': 8, 'round_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'name_11': 11, 'george pugh_12': 12, 'round_13': 13} | {'less_4': 'less', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'name_7': 'name', 'pat harrison_8': 'pat harrison', 'round_9': 'round', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'name_11': 'name', 'george pugh_12': 'george pugh', 'round_13': 'round'} | {'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'name_7': [0], 'pat harrison_8': [0], 'round_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'name_11': [1], 'george pugh_12': [1], 'round_13': [3]} | ['round', 'name', 'position', 'school', 'signed'] | [['1', 'pat harrison', 'inf', 'university of southern california', 'no'], ['2', 'william camp', 'rhp', 'oklahoma state university', 'no cubs - 1970'], ['3', 'george pugh', 'lhp', 'mesa community college', 'no'], ['4', 'william ferguson', '1b', 'texas christian university', 'no reds - 1969 june'], ['5', 'george putz', '1b', 'springfield college', 'no cardinals - 1969 june']] |
newington college | https://en.wikipedia.org/wiki/Newington_College | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1839872-3.html.csv | ordinal | roy alfred zimmerman was the second earliest employed person by newington college . | {'row': '6', 'col': '2', 'order': '2', 'col_other': '1', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'employed', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; employed ; 2 }'}, 'name'], 'result': 'zimmerman , roy alfred', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; employed ; 2 } ; name }'}, 'zimmerman , roy alfred'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; employed ; 2 } ; name } ; zimmerman , roy alfred } = true', 'tointer': 'select the row whose employed record of all rows is 2nd minimum . the name record of this row is zimmerman , roy alfred .'} | eq { hop { nth_argmin { all_rows ; employed ; 2 } ; name } ; zimmerman , roy alfred } = true | select the row whose employed record of all rows is 2nd minimum . the name record of this row is zimmerman , roy alfred . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'employed_5': 5, '2_6': 6, 'name_7': 7, 'zimmerman , roy alfred_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', 'employed_5': 'employed', '2_6': '2', 'name_7': 'name', 'zimmerman , roy alfred_8': 'zimmerman , roy alfred'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'employed_5': [0], '2_6': [0], 'name_7': [1], 'zimmerman , roy alfred_8': [2]} | ['name', 'employed', 'position held', 'honour', 'citation'] | [['davis , phillip harris ( phil )', '1951 - 2000', 'mathematics & prefect master', 'medal of the order of australia', "it 's an honour"], ['morgan , michael dennis', '1981 - 2001', 'physical education ist viii coach', 'medal of the order of australia', "it 's an honour"], ['swain , elizabeth anne ( liz )', '1973 - 1995', 'director of music & chapel choir', 'medal of the order of australia', "it 's an honour"], ['swain , peter leonard', '1970 - 1996', 'chaplain & archivist', 'medal of the order of australia', "it 's an honour"], ['woosnam , clive thomas', '1970 - 2005', 'senior boarding master & registrar', 'medal of the order of australia', "it 's an honour"], ['zimmerman , roy alfred', '1966 - 1996', 'master - in - charge wyvern house', 'medal of the order of australia', "it 's an honour"]] |
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/2-15753390-2.html.csv | superlative | siegfried schauzu and wolfgang kalauch had the highest amounts of points scored from the race . | {'scope': 'all', 'col_superlative': '7', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '2', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'points'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; points }'}, 'rider'], 'result': 'siegfried schauzu / wolfgang kalauch', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; points } ; rider }'}, 'siegfried schauzu / wolfgang kalauch'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; points } ; rider } ; siegfried schauzu / wolfgang kalauch } = true', 'tointer': 'select the row whose points record of all rows is maximum . the rider record of this row is siegfried schauzu / wolfgang kalauch .'} | eq { hop { argmax { all_rows ; points } ; rider } ; siegfried schauzu / wolfgang kalauch } = true | select the row whose points record of all rows is maximum . the rider record of this row is siegfried schauzu / wolfgang kalauch . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'points_5': 5, 'rider_6': 6, 'siegfried schauzu / wolfgang kalauch_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'points_5': 'points', 'rider_6': 'rider', 'siegfried schauzu / wolfgang kalauch_7': 'siegfried schauzu / wolfgang kalauch'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'points_5': [0], 'rider_6': [1], 'siegfried schauzu / wolfgang kalauch_7': [2]} | ['place', 'rider', 'country', 'machine', 'speed', 'time', 'points'] | [['1', 'siegfried schauzu / wolfgang kalauch', 'west germany', 'bmw', '91.85 mph', '1:13.57.2', '15'], ['2', 'heinz luthringshauser / jcusnik', 'west germany', 'bmw', '91.70 mph', '1:14.04.6', '12'], ['3', 'gerry boret / nick boret', 'united kingdom', 'konig', '84.43 mph', '1:20.27.4', '10'], ['4', 'wklenk / nscheerer', 'west germany', 'bmw', '83.62 mph', '1:21.31.8', '8'], ['5', 'barry dungworth / rwturrington', 'united kingdom', 'bmw', '82.32 mph', '1:22.30.6', '6'], ['6', 'roy hanks / jpmann', 'united kingdom', 'bsa', '80.07 mph', '1:24.49.6', '5'], ['7', 'rwoodhouse / dwoodhouse', 'united kingdom', 'bsa', '79.83 mph', '1.25.05.40', '4'], ['8', 'roger dutton / tony wright', 'united kingdom', 'bmw', '79.63 mph', '1.25.18.0', '3'], ['9', "george o'dell / bill boldison", 'united kingdom', 'bsa', '79.60 mph', '1.25.20.2', '2'], ['10', 'jbarker / amacfadzean', 'united kingdom', 'bsa', '79.52 mph', '1.25.28.2', '1']] |
list of active sumo wrestlers | https://en.wikipedia.org/wiki/List_of_active_sumo_wrestlers | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1557974-1.html.csv | comparative | ikioi shōta made his sumo wrestling debut before tochinoshin tsuyoshi . | {'row_1': '2', 'row_2': '6', 'col': '3', 'col_other': '1', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'ring name', 'ikioi shōta'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose ring name record fuzzily matches to ikioi shōta .', 'tostr': 'filter_eq { all_rows ; ring name ; ikioi shōta }'}, 'debut'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; ring name ; ikioi shōta } ; debut }', 'tointer': 'select the rows whose ring name record fuzzily matches to ikioi shōta . take the debut record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'ring name', 'tochinoshin tsuyoshi'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose ring name record fuzzily matches to tochinoshin tsuyoshi .', 'tostr': 'filter_eq { all_rows ; ring name ; tochinoshin tsuyoshi }'}, 'debut'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; ring name ; tochinoshin tsuyoshi } ; debut }', 'tointer': 'select the rows whose ring name record fuzzily matches to tochinoshin tsuyoshi . take the debut record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; ring name ; ikioi shōta } ; debut } ; hop { filter_eq { all_rows ; ring name ; tochinoshin tsuyoshi } ; debut } } = true', 'tointer': 'select the rows whose ring name record fuzzily matches to ikioi shōta . take the debut record of this row . select the rows whose ring name record fuzzily matches to tochinoshin tsuyoshi . take the debut record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; ring name ; ikioi shōta } ; debut } ; hop { filter_eq { all_rows ; ring name ; tochinoshin tsuyoshi } ; debut } } = true | select the rows whose ring name record fuzzily matches to ikioi shōta . take the debut record of this row . select the rows whose ring name record fuzzily matches to tochinoshin tsuyoshi . take the debut 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, 'ring name_7': 7, 'ikioi shōta_8': 8, 'debut_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'ring name_11': 11, 'tochinoshin tsuyoshi_12': 12, 'debut_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', 'ring name_7': 'ring name', 'ikioi shōta_8': 'ikioi shōta', 'debut_9': 'debut', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'ring name_11': 'ring name', 'tochinoshin tsuyoshi_12': 'tochinoshin tsuyoshi', 'debut_13': 'debut'} | {'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'ring name_7': [0], 'ikioi shōta_8': [0], 'debut_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'ring name_11': [1], 'tochinoshin tsuyoshi_12': [1], 'debut_13': [3]} | ['ring name', 'current rank', 'debut', 'stable', 'birthplace', 'career and other notes'] | [['chiyonokuni toshiki', 'f0 jūryō 3 west', '2006 - 5', 'kokonoe', 'mie', 'former maegashira 8 , jūryō champion'], ['ikioi shōta', 'e0 maegashira 6 west', '2005 - 3', 'isenoumi', 'os ōsaka', 'former maegashira 1 , jūryō champion'], ['kimikaze toshiji', 'g1 makushita 13 west', '2009 - 1', 'oguruma', 'tokyo', 'former maegashira 13 , jūryō champion'], ['kyokushūhō kōki', 'e1 maegashira 14 east', '2007 - 5', 'o ōshima', 'z mongolia', 'former maegashira 12'], ['tamaasuka daisuke', 'e1 maegashira 16 west', '1998 - 3', 'kataonami', 'aichi', 'former maegashira 9 , two time jūryō winner'], ['tochinoshin tsuyoshi', 'f1 jūryō 14 west', '2006 - 3', 'kasugano', 'z mtskheta , georgia', 'many time komusubi , fellow countryman of kokkai'], ['tochiōzan yūichirō', 'c sekiwake west', '2005 - 1', 'kasugano', 'kōchi', 'many time sekiwake , longtime rival of gōeidō'], ['tokitenkū yoshiaki', 'e1 maegashira 10 east', '2002 - 7', 'tokitsukaze', 'z töv aimag , mongolia', 'former komusubi , consistent maegashira performer'], ['tokushōryū makota', 'e1 maegashira 14 west', '2009 - 1', 'kise', 'nara', 'former maegashira 10']] |
pedro nunes ( racing driver ) | https://en.wikipedia.org/wiki/Pedro_Nunes_%28racing_driver%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-25386974-1.html.csv | aggregation | the average number of races that pedro nunes participated in was 8.73 . | {'scope': 'all', 'col': '4', 'type': 'average', 'result': '8.73', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'races'], 'result': '8.73', 'ind': 0, 'tostr': 'avg { all_rows ; races }'}, '8.73'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; races } ; 8.73 } = true', 'tointer': 'the average of the races record of all rows is 8.73 .'} | round_eq { avg { all_rows ; races } ; 8.73 } = true | the average of the races record of all rows is 8.73 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'races_4': 4, '8.73_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'races_4': 'races', '8.73_5': '8.73'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'races_4': [0], '8.73_5': [1]} | ['season', 'series', 'team', 'races', 'wins', 'poles', 'f / laps', 'podiums', 'points', 'position'] | [['2006', 'formula renault 2.0 brazil', 'piquet sports', '1', '0', '0', '0', '0', '22', '17th'], ['2006', 'formula renault 2.0 brazil', 'dragão motorsport', '1', '0', '0', '0', '0', '22', '17th'], ['2006', 'formula 3 sudamericana', 'piquet sports', '14', '0', '0', '0', '0', '10', '28th'], ['2007', 'formula renault 2.0 nec', 'sl formula racing', '10', '0', '0', '0', '0', '46', '30th'], ['2007', 'eurocup formula renault 2.0', 'sl formula racing', '10', '0', '0', '0', '0', '0', 'nc'], ['2007', 'formula 3 sudamericana', 'baumer racing', '4', '0', '0', '0', '0', '1', '21st'], ['2008', 'formula 3 sudamericana', 'cesário fórmula', '17', '5', '3', '4', '11', '112', '2nd'], ['2009', 'formula 3 euro series', 'manor motorsport', '20', '0', '0', '0', '0', '0', '27th'], ['2009', 'british formula three championship', 'manor motorsport', '2', '0', '0', '0', '0', 'n / a', 'nc'], ['2009', 'masters of formula 3', 'manor motorsport', '1', '0', '0', '0', '0', 'n / a', '20th'], ['2010', 'gp3 series', 'art grand prix', '16', '0', '0', '0', '0', '4', '24th']] |
1995 st. louis rams season | https://en.wikipedia.org/wiki/1995_St._Louis_Rams_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10689293-2.html.csv | majority | the rams lost a majority of their games in the 95 season . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': 'l', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'result', 'l'], 'result': True, 'ind': 0, 'tointer': 'for the result records of all rows , most of them fuzzily match to l .', 'tostr': 'most_eq { all_rows ; result ; l } = true'} | most_eq { all_rows ; result ; l } = true | for the result records of all rows , most of them fuzzily match to l . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'result_3': 3, 'l_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'result_3': 'result', 'l_4': 'l'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'result_3': [0], 'l_4': [0]} | ['week', 'date', 'opponent', 'result', 'attendance'] | [['1', 'september 3 , 1995', 'green bay packers', 'w 17 - 14', '60104'], ['2', 'september 10 , 1995', 'new orleans saints', 'w 17 - 13', '59335'], ['3', 'september 17 , 1995', 'carolina panthers', 'w 31 - 10', '54060'], ['4', 'september 24 , 1995', 'chicago bears', 'w 34 - 28', '59679'], ['5', 'october 1 , 1995', 'indianapolis colts', 'l 21 - 18', '58616'], ['7', 'october 12 , 1995', 'atlanta falcons', 'w 21 - 19', '59700'], ['8', 'october 22 , 1995', 'san francisco 49ers', 'l 44 - 10', '59915'], ['9', 'october 29 , 1995', 'philadelphia eagles', 'l 20 - 9', '62172'], ['10', 'november 5 , 1995', 'new orleans saints', 'l 19 - 10', '43120'], ['11', 'november 12 , 1995', 'carolina panthers', 'w 28 - 17', '65598'], ['12', 'november 19 , 1995', 'atlanta falcons', 'l 31 - 6', '46309'], ['13', 'november 26 , 1995', 'san francisco 49ers', 'l 41 - 13', '66049'], ['14', 'december 3 , 1995', 'new york jets', 'w 23 - 20', '52023'], ['15', 'december 10 , 1995', 'buffalo bills', 'l 45 - 27', '64623'], ['16', 'december 17 , 1995', 'washington redskins', 'l 35 - 23', '63760'], ['17', 'december 24 , 1995', 'miami dolphins', 'l 41 - 22', '63876']] |
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 | comparative | at the 2005 spanish grand prix , mark webber had a slower time than jarno trulli . | {'row_1': '6', 'row_2': '3', 'col': '4', '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', 'driver', 'mark webber'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose driver record fuzzily matches to mark webber .', 'tostr': 'filter_eq { all_rows ; driver ; mark webber }'}, 'time / retired'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; driver ; mark webber } ; time / retired }', 'tointer': 'select the rows whose driver record fuzzily matches to mark webber . take the time / retired record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'driver', 'jarno trulli'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose driver record fuzzily matches to jarno trulli .', 'tostr': 'filter_eq { all_rows ; driver ; jarno trulli }'}, 'time / retired'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; driver ; jarno trulli } ; time / retired }', 'tointer': 'select the rows whose driver record fuzzily matches to jarno trulli . take the time / retired record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; driver ; mark webber } ; time / retired } ; hop { filter_eq { all_rows ; driver ; jarno trulli } ; time / retired } } = true', 'tointer': 'select the rows whose driver record fuzzily matches to mark webber . take the time / retired record of this row . select the rows whose driver record fuzzily matches to jarno trulli . take the time / retired record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; driver ; mark webber } ; time / retired } ; hop { filter_eq { all_rows ; driver ; jarno trulli } ; time / retired } } = true | select the rows whose driver record fuzzily matches to mark webber . take the time / retired record of this row . select the rows whose driver record fuzzily matches to jarno trulli . take the time / retired 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, 'driver_7': 7, 'mark webber_8': 8, 'time / retired_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'driver_11': 11, 'jarno trulli_12': 12, 'time / retired_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', 'driver_7': 'driver', 'mark webber_8': 'mark webber', 'time / retired_9': 'time / retired', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'driver_11': 'driver', 'jarno trulli_12': 'jarno trulli', 'time / retired_13': 'time / retired'} | {'greater_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'driver_7': [0], 'mark webber_8': [0], 'time / retired_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'driver_11': [1], 'jarno trulli_12': [1], 'time / retired_13': [3]} | ['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']] |
1907 grand prix season | https://en.wikipedia.org/wiki/1907_Grand_Prix_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13793279-2.html.csv | superlative | the targa florio was the first race of the 1907 grand prix season . | {'scope': 'all', 'col_superlative': '3', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '1', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmin', 'args': ['all_rows', 'date'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; date }'}, 'name'], 'result': 'targa florio', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; date } ; name }'}, 'targa florio'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmin { all_rows ; date } ; name } ; targa florio } = true', 'tointer': 'select the row whose date record of all rows is minimum . the name record of this row is targa florio .'} | eq { hop { argmin { all_rows ; date } ; name } ; targa florio } = true | select the row whose date record of all rows is minimum . the name record of this row is targa florio . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'date_5': 5, 'name_6': 6, 'targa florio_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', 'name_6': 'name', 'targa florio_7': 'targa florio'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'date_5': [0], 'name_6': [1], 'targa florio_7': [2]} | ['name', 'circuit', 'date', 'winning driver', 'winning constructor', 'report'] | [['targa florio', 'madonie', '22 april', 'felice nazzaro', 'fiat', 'report'], ['moscow - st petersburg', 'public roads', '7 june', 'arthur duray', 'lorraine - dietrich', 'report'], ['kaiser preis', 'taunus', '13 - 14 june', 'felice nazzaro', 'fiat', 'report'], ['ardennes circuit ( kaiser formula )', 'bastogne', '25 july', 'john moore - brabazon', 'minerva', 'report'], ['ardennes circuit', 'bastogne', '27 july', 'pierre de caters', 'mercedes', 'report'], ['coppa florio', 'brescia', '1 september', 'ferdinando minoia', 'isotta - fraschini', 'report'], ['coppa della velocità', 'brescia', '2 september', 'alessandro cagno', 'itala', 'report']] |
leonardo de souza | https://en.wikipedia.org/wiki/Leonardo_de_Souza | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27582888-1.html.csv | unique | the 2006 season was the only one in which leonardo de souza was with team eng makers . | {'scope': 'all', 'row': '2', 'col': '3', 'col_other': '1', 'criterion': 'equal', 'value': 'eng makers', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'team name', 'eng makers'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose team name record fuzzily matches to eng makers .', 'tostr': 'filter_eq { all_rows ; team name ; eng makers }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; team name ; eng makers } }', 'tointer': 'select the rows whose team name record fuzzily matches to eng makers . there is only one such row in the table .'}, {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'team name', 'eng makers'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose team name record fuzzily matches to eng makers .', 'tostr': 'filter_eq { all_rows ; team name ; eng makers }'}, 'season'], 'result': '2006', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; team name ; eng makers } ; season }'}, '2006'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; team name ; eng makers } ; season } ; 2006 }', 'tointer': 'the season record of this unqiue row is 2006 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; team name ; eng makers } } ; eq { hop { filter_eq { all_rows ; team name ; eng makers } ; season } ; 2006 } } = true', 'tointer': 'select the rows whose team name record fuzzily matches to eng makers . there is only one such row in the table . the season record of this unqiue row is 2006 .'} | and { only { filter_eq { all_rows ; team name ; eng makers } } ; eq { hop { filter_eq { all_rows ; team name ; eng makers } ; season } ; 2006 } } = true | select the rows whose team name record fuzzily matches to eng makers . there is only one such row in the table . the season record of this unqiue row is 2006 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'team name_7': 7, 'eng makers_8': 8, 'eq_3': 3, 'num_hop_2': 2, 'season_9': 9, '2006_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'team name_7': 'team name', 'eng makers_8': 'eng makers', 'eq_3': 'eq', 'num_hop_2': 'num_hop', 'season_9': 'season', '2006_10': '2006'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'team name_7': [0], 'eng makers_8': [0], 'eq_3': [4], 'num_hop_2': [3], 'season_9': [2], '2006_10': [3]} | ['season', 'series', 'team name', 'races', 'poles', 'wins', 'podiums', 'f / laps', 'points', 'final placing'] | [['2005', 'formula renault brasil', 'kemba racing', '14', '0', '0', '0', '0', '18', '21st'], ['2006', 'formula renault brasil', 'eng makers', '10', '0', '0', '0', '0', '8', '18th'], ['2008', 'formula three sudamericana', 'kemba racing', '14', '0', '0', '0', '0', '24', '8th'], ['2009', 'formula three sudamericana', 'kemba racing', '14', '0', '1', '2', '0', '33', '9th'], ['2010', 'formula three sudamericana', 'kemba racing', '20', '0', '1', '4', '1', '171', '5th']] |
southern league cup ( scotland ) | https://en.wikipedia.org/wiki/Southern_League_Cup_%28Scotland%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16880170-1.html.csv | unique | in the southern league cup , when the rangers were the winner , the only time the runner up was morton was 1941-42 . | {'scope': 'subset', 'row': '2', 'col': '4', 'col_other': '1', 'criterion': 'equal', 'value': 'morton', 'subset': {'col': '2', 'criterion': 'equal', 'value': 'rangers'}} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'winner', 'rangers'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; winner ; rangers }', 'tointer': 'select the rows whose winner record fuzzily matches to rangers .'}, 'runner - up', 'morton'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose winner record fuzzily matches to rangers . among these rows , select the rows whose runner - up record fuzzily matches to morton .', 'tostr': 'filter_eq { filter_eq { all_rows ; winner ; rangers } ; runner - up ; morton }'}], 'result': True, 'ind': 2, 'tostr': 'only { filter_eq { filter_eq { all_rows ; winner ; rangers } ; runner - up ; morton } }', 'tointer': 'select the rows whose winner record fuzzily matches to rangers . among these rows , select the rows whose runner - up record fuzzily matches to morton . 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', 'winner', 'rangers'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; winner ; rangers }', 'tointer': 'select the rows whose winner record fuzzily matches to rangers .'}, 'runner - up', 'morton'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose winner record fuzzily matches to rangers . among these rows , select the rows whose runner - up record fuzzily matches to morton .', 'tostr': 'filter_eq { filter_eq { all_rows ; winner ; rangers } ; runner - up ; morton }'}, 'season'], 'result': '1941 - 42', 'ind': 3, 'tostr': 'hop { filter_eq { filter_eq { all_rows ; winner ; rangers } ; runner - up ; morton } ; season }'}, '1941 - 42'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { filter_eq { filter_eq { all_rows ; winner ; rangers } ; runner - up ; morton } ; season } ; 1941 - 42 }', 'tointer': 'the season record of this unqiue row is 1941 - 42 .'}], 'result': True, 'ind': 5, 'tostr': 'and { only { filter_eq { filter_eq { all_rows ; winner ; rangers } ; runner - up ; morton } } ; eq { hop { filter_eq { filter_eq { all_rows ; winner ; rangers } ; runner - up ; morton } ; season } ; 1941 - 42 } } = true', 'tointer': 'select the rows whose winner record fuzzily matches to rangers . among these rows , select the rows whose runner - up record fuzzily matches to morton . there is only one such row in the table . the season record of this unqiue row is 1941 - 42 .'} | and { only { filter_eq { filter_eq { all_rows ; winner ; rangers } ; runner - up ; morton } } ; eq { hop { filter_eq { filter_eq { all_rows ; winner ; rangers } ; runner - up ; morton } ; season } ; 1941 - 42 } } = true | select the rows whose winner record fuzzily matches to rangers . among these rows , select the rows whose runner - up record fuzzily matches to morton . there is only one such row in the table . the season record of this unqiue row is 1941 - 42 . | 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, 'winner_8': 8, 'rangers_9': 9, 'runner - up_10': 10, 'morton_11': 11, 'str_eq_4': 4, 'str_hop_3': 3, 'season_12': 12, '1941 - 42_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', 'winner_8': 'winner', 'rangers_9': 'rangers', 'runner - up_10': 'runner - up', 'morton_11': 'morton', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'season_12': 'season', '1941 - 42_13': '1941 - 42'} | {'and_5': [6], 'result_6': [], 'only_2': [5], 'filter_str_eq_1': [2, 3], 'filter_str_eq_0': [1], 'all_rows_7': [0], 'winner_8': [0], 'rangers_9': [0], 'runner - up_10': [1], 'morton_11': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'season_12': [3], '1941 - 42_13': [4]} | ['season', 'winner', 'score', 'runner - up', 'venue'] | [['1940 - 41', 'rangers', '4 - 2 ( rep )', 'heart of midlothian', 'hampden park'], ['1941 - 42', 'rangers', '2 - 0', 'morton', 'hampden park'], ['1942 - 43', 'rangers', '1 - 1 ( 11 - 3 corners )', 'falkirk', 'hampden park'], ['1943 - 44', 'hibernian', '0 - 0 ( 6 - 5 corners )', 'rangers', 'hampden park'], ['1944 - 45', 'rangers', '2 - 1', 'motherwell', 'hampden park'], ['1945 - 46', 'aberdeen', '3 - 2', 'rangers', 'hampden park']] |
annika sörenstam | https://en.wikipedia.org/wiki/Annika_S%C3%B6renstam | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-102100-7.html.csv | count | there were six years where annika sörenstam played in five matches . | {'scope': 'all', 'criterion': 'equal', 'value': '5', 'result': '6', 'col': '2', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'total matches', '5'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose total matches record is equal to 5 .', 'tostr': 'filter_eq { all_rows ; total matches ; 5 }'}], 'result': '6', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; total matches ; 5 } }', 'tointer': 'select the rows whose total matches record is equal to 5 . the number of such rows is 6 .'}, '6'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; total matches ; 5 } } ; 6 } = true', 'tointer': 'select the rows whose total matches record is equal to 5 . the number of such rows is 6 .'} | eq { count { filter_eq { all_rows ; total matches ; 5 } } ; 6 } = true | select the rows whose total matches record is equal to 5 . the number of such rows is 6 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_eq_0': 0, 'all_rows_4': 4, 'total matches_5': 5, '5_6': 6, '6_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'total matches_5': 'total matches', '5_6': '5', '6_7': '6'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'total matches_5': [0], '5_6': [0], '6_7': [2]} | ['year', 'total matches', 'total w - l - h', 'singles w - l - h', 'points won', 'points %'] | [['career', '37', '22 - 11 - 4', '4 - 3 - 1', '24', '64.9'], ['1994', '3', '1 - 2 - 0', '0 - 1 - 0 lost to t green', '1', '33.3'], ['1996', '5', '3 - 0 - 2', '1 - 0 - 0 def p bradley 2 & 1', '4', '80.0'], ['1998', '5', '3 - 2 - 0', '1 - 0 - 0 def d andrews 2 & 1', '3', '60.0'], ['2000', '4', '2 - 2 - 0', '0 - 1 - 0 lost to j inkster 5 & 4', '2', '50.0'], ['2002', '5', '3 - 1 - 1', '0 - 0 - 1 halved w / w ward', '3.5', '70.0'], ['2003', '5', '4 - 1 - 0', '1 - 0 - 0 def a stanford 3 & 2', '4', '80.0'], ['2005', '5', '4 - 1 - 0', '1 - 0 - 0 def b daniel 4 & 3', '4', '80.0'], ['2007', '5', '2 - 2 - 1', '0 - 1 - 0 lost to m pressel 2 & 1', '2.5', '50.0']] |
queens county , new brunswick | https://en.wikipedia.org/wiki/Queens_County%2C_New_Brunswick | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-171356-2.html.csv | superlative | hampstead had the most census ranking in the queens county of new brunswick . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '9', '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', 'census ranking'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; census ranking }'}, 'official name'], 'result': 'hampstead', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; census ranking } ; official name }'}, 'hampstead'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; census ranking } ; official name } ; hampstead } = true', 'tointer': 'select the row whose census ranking record of all rows is maximum . the official name record of this row is hampstead .'} | eq { hop { argmax { all_rows ; census ranking } ; official name } ; hampstead } = true | select the row whose census ranking record of all rows is maximum . the official name record of this row is hampstead . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'census ranking_5': 5, 'official name_6': 6, 'hampstead_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'census ranking_5': 'census ranking', 'official name_6': 'official name', 'hampstead_7': 'hampstead'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'census ranking_5': [0], 'official name_6': [1], 'hampstead_7': [2]} | ['official name', 'status', 'area km 2', 'population', 'census ranking'] | [['chipman', 'parish', '482.81', '962', '2135 of 5008'], ['canning', 'parish', '173.40', '952', '2145 of 5008'], ['waterborough', 'parish', '444.87', '851', '2290 of 5008'], ['petersville', 'parish', '588.42', '723', '2520 of 5008'], ['johnston', 'parish', '359.18', '660', '2649 of 5008'], ['cambridge', 'parish', '113.97', '651', '2662 of 5008'], ['wickham', 'parish', '159.78', '426', '3211 of 5008'], ['gagetown', 'parish', '234.89', '316', '3574 of 5008'], ['hampstead', 'parish', '212.63', '294', '3665 of 5008']] |
list of awards and nominations received by woody allen | https://en.wikipedia.org/wiki/List_of_awards_and_nominations_received_by_Woody_Allen | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18141883-3.html.csv | count | according to the list of list of awards and nominations received by woody allen , he did n't win 2 of the nominations for the bullets over broadway . | {'scope': 'subset', 'criterion': 'equal', 'value': 'nominated', 'result': '2', 'col': '3', 'subset': {'col': '2', 'criterion': 'equal', 'value': 'bullets over broadway'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'film', 'bullets over broadway'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; film ; bullets over broadway }', 'tointer': 'select the rows whose film record fuzzily matches to bullets over broadway .'}, 'result', 'nominated'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose film record fuzzily matches to bullets over broadway . among these rows , select the rows whose result record fuzzily matches to nominated .', 'tostr': 'filter_eq { filter_eq { all_rows ; film ; bullets over broadway } ; result ; nominated }'}], 'result': '2', 'ind': 2, 'tostr': 'count { filter_eq { filter_eq { all_rows ; film ; bullets over broadway } ; result ; nominated } }', 'tointer': 'select the rows whose film record fuzzily matches to bullets over broadway . among these rows , select the rows whose result record fuzzily matches to nominated . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_eq { filter_eq { all_rows ; film ; bullets over broadway } ; result ; nominated } } ; 2 } = true', 'tointer': 'select the rows whose film record fuzzily matches to bullets over broadway . among these rows , select the rows whose result record fuzzily matches to nominated . the number of such rows is 2 .'} | eq { count { filter_eq { filter_eq { all_rows ; film ; bullets over broadway } ; result ; nominated } } ; 2 } = true | select the rows whose film record fuzzily matches to bullets over broadway . among these rows , select the rows whose result record fuzzily matches to nominated . the number of such rows is 2 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_str_eq_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'film_6': 6, 'bullets over broadway_7': 7, 'result_8': 8, 'nominated_9': 9, '2_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_str_eq_1': 'filter_str_eq', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'film_6': 'film', 'bullets over broadway_7': 'bullets over broadway', 'result_8': 'result', 'nominated_9': 'nominated', '2_10': '2'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_str_eq_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'film_6': [0], 'bullets over broadway_7': [0], 'result_8': [1], 'nominated_9': [1], '2_10': [3]} | ['year', 'film', 'result', 'category', 'actor'] | [['1977', 'annie hall', 'nominated', 'best actor', 'woody allen'], ['1977', 'annie hall', 'won', 'best actress', 'diane keaton'], ['1978', 'interiors', 'nominated', 'best actress', 'geraldine page'], ['1978', 'interiors', 'nominated', 'best supporting actress', 'maureen stapleton'], ['1979', 'manhattan', 'nominated', 'best supporting actress', 'mariel hemingway'], ['1986', 'hannah and her sisters', 'won', 'best supporting actor', 'michael caine'], ['1986', 'hannah and her sisters', 'won', 'best supporting actress', 'dianne wiest'], ['1989', 'crimes and misdemeanors', 'nominated', 'best supporting actor', 'martin landau'], ['1992', 'husbands and wives', 'nominated', 'best supporting actress', 'judy davis'], ['1994', 'bullets over broadway', 'nominated', 'best supporting actor', 'chazz palminteri'], ['1994', 'bullets over broadway', 'won', 'best supporting actress', 'dianne wiest'], ['1994', 'bullets over broadway', 'nominated', 'best supporting actress', 'jennifer tilly'], ['1995', 'mighty aphrodite', 'won', 'best supporting actress', 'mira sorvino'], ['1999', 'sweet and lowdown', 'nominated', 'best actor', 'sean penn'], ['1999', 'sweet and lowdown', 'nominated', 'best supporting actress', 'samantha morton'], ['2008', 'vicky cristina barcelona', 'won', 'best supporting actress', 'penãlope cruz']] |
list of via c3 microprocessors | https://en.wikipedia.org/wiki/List_of_VIA_C3_microprocessors | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16341329-2.html.csv | aggregation | the average frequency on the 800 models was 800 mhz . | {'scope': 'subset', 'col': '2', 'type': 'average', 'result': '800', 'subset': {'col': '1', 'criterion': 'fuzzily_match', 'value': '800'}} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'model number', '800'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; model number ; 800 }', 'tointer': 'select the rows whose model number record fuzzily matches to 800 .'}, 'frequency'], 'result': '800', 'ind': 1, 'tostr': 'avg { filter_eq { all_rows ; model number ; 800 } ; frequency }'}, '800'], 'result': True, 'ind': 2, 'tostr': 'round_eq { avg { filter_eq { all_rows ; model number ; 800 } ; frequency } ; 800 } = true', 'tointer': 'select the rows whose model number record fuzzily matches to 800 . the average of the frequency record of these rows is 800 .'} | round_eq { avg { filter_eq { all_rows ; model number ; 800 } ; frequency } ; 800 } = true | select the rows whose model number record fuzzily matches to 800 . the average of the frequency record of these rows is 800 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'avg_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'model number_5': 5, '800_6': 6, 'frequency_7': 7, '800_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'avg_1': 'avg', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'model number_5': 'model number', '800_6': '800', 'frequency_7': 'frequency', '800_8': '800'} | {'eq_2': [3], 'result_3': [], 'avg_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'model number_5': [0], '800_6': [0], 'frequency_7': [1], '800_8': [2]} | ['model number', 'frequency', 'l2 - cache', 'front side bus', 'multiplier', 'voltage', 'socket'] | [['c3 800', '800 mhz', '64 kib', '100 mhz', '8', '1.35 v', 'socket 370'], ['c3 800', '800 mhz', '64 kib', '133 mhz', '6', '1.35 v', 'socket 370'], ['c3 800t', '800 mhz', '64kib', '133 mhz', '6', '1.35 v', 'socket 370'], ['c3 850', '850 mhz', '64kib', '100 mhz', '8.5', '1.35 v', 'socket 370'], ['c3 866', '866 mhz', '64 kib', '133 mhz', '6.5', '1.35 v', 'socket 370'], ['c3 866t', '866 mhz', '64 kib', '133 mhz', '6.5', '1.35 v', 'socket 370'], ['c3 900', '900 mhz', '64kib', '100 mhz', '9', '1.35 v', 'socket 370'], ['c3 933t', '933 mhz', '64kib', '133 mhz', '7', '1.35 v', 'socket 370'], ['c3 1.0 t', '1000 mhz', '64kib', '133 mhz', '7.5', '1.35 v', 'socket 370']] |
ss prinz eitel friedrich ( 1904 ) | https://en.wikipedia.org/wiki/SS_Prinz_Eitel_Friedrich_%281904%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16644292-1.html.csv | unique | the only russian ship that was sunk by ss prinz eitel friedrich was the sailing ship isabel browne . | {'scope': 'all', 'row': '4', 'col': '4', 'col_other': '2', 'criterion': 'equal', 'value': 'russian', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'nationality', 'russian'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose nationality record fuzzily matches to russian .', 'tostr': 'filter_eq { all_rows ; nationality ; russian }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; nationality ; russian } }', 'tointer': 'select the rows whose nationality record fuzzily matches to russian . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'nationality', 'russian'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose nationality record fuzzily matches to russian .', 'tostr': 'filter_eq { all_rows ; nationality ; russian }'}, 'ship'], 'result': 'isabel browne', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; nationality ; russian } ; ship }'}, 'isabel browne'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; nationality ; russian } ; ship } ; isabel browne }', 'tointer': 'the ship record of this unqiue row is isabel browne .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; nationality ; russian } } ; eq { hop { filter_eq { all_rows ; nationality ; russian } ; ship } ; isabel browne } } = true', 'tointer': 'select the rows whose nationality record fuzzily matches to russian . there is only one such row in the table . the ship record of this unqiue row is isabel browne .'} | and { only { filter_eq { all_rows ; nationality ; russian } } ; eq { hop { filter_eq { all_rows ; nationality ; russian } ; ship } ; isabel browne } } = true | select the rows whose nationality record fuzzily matches to russian . there is only one such row in the table . the ship record of this unqiue row is isabel browne . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'nationality_7': 7, 'russian_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'ship_9': 9, 'isabel browne_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'nationality_7': 'nationality', 'russian_8': 'russian', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'ship_9': 'ship', 'isabel browne_10': 'isabel browne'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'nationality_7': [0], 'russian_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'ship_9': [2], 'isabel browne_10': [3]} | ['date', 'ship', 'type', 'nationality', 'tonnage grt', 'fate'] | [['5.12.1914', 'charcas', 'freighter', 'british', '5067', 'sunk'], ['11.12.1914', 'jean', 'sailing ship', 'french', '2207', 'retained as collier scuttled 31.12.14'], ['12.12.1914', 'kidalton', 'sailing ship', 'british', '1784', 'sunk'], ['26.1.1915', 'isabel browne', 'sailing ship', 'russian', '1315', 'sunk'], ['27.1.1915', 'pierre lott', 'sailing ship', 'french', '2196', 'sunk'], ['27.1.1915', 'william p frye', 'sailing ship', 'american', '3374', 'sunk'], ['28.1.1915', 'jacobsen', 'sailing ship', 'french', '2195', 'sunk'], ['12.2.1915', 'invercoe', 'sailing ship', 'british', '1421', 'sunk'], ['18.2.1915', 'mary ada short', 'sailing ship', 'british', '3605', 'sunk'], ['19.2.1915', 'floride', 'freighter', 'french', '6629', 'sunk'], ['20.2.1915', 'willerby', 'freighter', 'british', '3630', 'sunk']] |
forest hill railway station | https://en.wikipedia.org/wiki/Forest_Hill_railway_station | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1569516-1.html.csv | aggregation | the average frequency of trains coming through the forest hill railway station per hour is 3.11 . | {'scope': 'all', 'col': '2', 'type': 'average', 'result': '3.11', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'frequency ( per hour )'], 'result': '3.11', 'ind': 0, 'tostr': 'avg { all_rows ; frequency ( per hour ) }'}, '3.11'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; frequency ( per hour ) } ; 3.11 } = true', 'tointer': 'the average of the frequency ( per hour ) record of all rows is 3.11 .'} | round_eq { avg { all_rows ; frequency ( per hour ) } ; 3.11 } = true | the average of the frequency ( per hour ) record of all rows is 3.11 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'frequency (per hour)_4': 4, '3.11_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'frequency (per hour)_4': 'frequency ( per hour )', '3.11_5': '3.11'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'frequency (per hour)_4': [0], '3.11_5': [1]} | ['platform', 'frequency ( per hour )', 'destination', 'service pattern', 'operator', 'line'] | [['1', '4', 'highbury & islington', 'all stations via shoreditch high street', 'london overground', 'east london'], ['1', '4', 'dalston junction', 'all stations via shoreditch high street', 'london overground', 'east london'], ['1', '4', 'london bridge', 'all stations', 'southern', 'metro'], ['2', '4', 'crystal palace', 'all stations', 'london overground', 'east london'], ['2', '4', 'west croydon', 'all stations', 'london overground', 'east london'], ['2', '2', 'london victoria ( mon - sat )', 'all stations via clapham junction', 'southern', 'metro'], ['2', '2', 'caterham ( mon - sat )', 'all stations via east croydon', 'southern', 'metro'], ['2', '2', 'west croydon ( peaks & sun only )', 'sydenham then fast to norwood junction', 'southern', 'metro'], ['2', '2', 'tattenham corner ( sun only )', 'all stations via east croydon', 'southern', 'metro']] |
2007 japanese television dramas | https://en.wikipedia.org/wiki/2007_Japanese_television_dramas | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18539861-1.html.csv | aggregation | the average rating that 2007 japanese television dramas had was 14.57 . | {'scope': 'all', 'col': '5', 'type': 'average', 'result': '14.57', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'average ratings'], 'result': '14.57', 'ind': 0, 'tostr': 'avg { all_rows ; average ratings }'}, '14.57'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; average ratings } ; 14.57 } = true', 'tointer': 'the average of the average ratings record of all rows is 14.57 .'} | round_eq { avg { all_rows ; average ratings } ; 14.57 } = true | the average of the average ratings record of all rows is 14.57 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'average ratings_4': 4, '14.57_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'average ratings_4': 'average ratings', '14.57_5': '14.57'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'average ratings_4': [0], '14.57_5': [1]} | ['japanese title', 'romaji title', 'tv station', 'episodes', 'average ratings'] | [['エラいところに嫁いでしまった !', 'erai tokoro ni totsuide shimatta !', 'tv asahi', '9', '12.8 %'], ['演歌の女王', 'enka no joou', 'ntv', '10', '9.1 %'], ['華麗なる一族', 'karei - naru ichizoku', 'tbs', '10', '27.15 %'], ['きらきら研修医', 'kirakira kenshuui', 'tbs', '11', '9.38 %'], ['花より男子2 （ リターンズ ）', 'hana yori dango 2 ( returns )', 'tbs', '11', '21.7 %'], ['今週 、 妻が浮気します', 'konshu , tsuma ga uwakishimasu', 'fuji tv', '11', '10.15 %'], ['東京タワー ～ オカンとボクと 、 時々 、 オトン ～', 'tokyo tower ~ okan to boku to , tokidoki , oton ~', 'fuji tv', '11', '14.9 %'], ['拝啓 、 父上様', 'haikei , chichiue - sama', 'fuji tv', '11', '13.19 %'], ['ハケンの品格', 'haken no hinkaku', 'ntv', '10', '20.1 %'], ['ヒミツの花園', 'himitsu no hanazono', 'fuji tv', '11', '12.41 %'], ['わるいやつら', 'waruiyatsura', 'tv asahi', '8', '9.4 %']] |
1994 - 95 cleveland cavaliers season | https://en.wikipedia.org/wiki/1994%E2%80%9395_Cleveland_Cavaliers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16188254-7.html.csv | superlative | the game played on march 25 drew the highest attendance in the 1994 - 95 cleveland cavaliers season . | {'scope': 'all', 'col_superlative': '6', 'row_superlative': '13', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'attendance'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; attendance }'}, 'date'], 'result': 'march 25', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; attendance } ; date }'}, 'march 25'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; attendance } ; date } ; march 25 } = true', 'tointer': 'select the row whose attendance record of all rows is maximum . the date record of this row is march 25 .'} | eq { hop { argmax { all_rows ; attendance } ; date } ; march 25 } = true | select the row whose attendance record of all rows is maximum . the date record of this row is march 25 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'attendance_5': 5, 'date_6': 6, 'march 25_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'attendance_5': 'attendance', 'date_6': 'date', 'march 25_7': 'march 25'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'attendance_5': [0], 'date_6': [1], 'march 25_7': [2]} | ['date', 'visitor', 'score', 'home', 'leading scorer', 'attendance', 'record'] | [['march 2', 'cleveland', '84 - 90', 'dallas', 'chris mills , 16 points', 'reunion arena 12194', '33 - 23'], ['march 4', 'new york', '89 - 76', 'cleveland', 'hot rod williams , 20 points', 'gund arena 20562', '33 - 24'], ['march 7', 'detroit', '81 - 89', 'cleveland', 'chris mills , 24 points', 'gund arena 20562', '34 - 24'], ['march 9', 'san antonio', '100 - 98', 'cleveland', 'terrell brandon , 24 points', 'gund arena 20562', '34 - 25'], ['march 10', 'cleveland', '76 - 99', 'chicago', 'tyrone hill , 13 points', 'united center 22362', '34 - 26'], ['march 12', 'cleveland', '92 - 72', 'philadelphia', '3 way tie , 14 points', 'corestates spectrum 10221', '35 - 26'], ['march 16', 'utah', '85 - 93', 'cleveland', 'bobby phills , 24 points', 'gund arena 20562', '36 - 26'], ['march 17', 'cleveland', '77 - 80', 'minnesota', 'mark price , 18 points', 'target center 14222', '36 - 27'], ['march 19', 'cleveland', '90 - 96', 'washington', 'mark price , 16 points', 'usair arena 17110', '36 - 28'], ['march 20', 'dallas', '102 - 100', 'cleveland', 'tyrone hill , 29 points', 'gund arena 20562', '36 - 29'], ['march 22', 'sacramento', '89 - 101', 'cleveland', 'mark price , 23 points', 'gund arena 20562', '37 - 29'], ['march 24', 'atlanta', '74 - 75', 'cleveland', 'tyrone hill , 24 points', 'gund arena 20562', '38 - 29'], ['march 25', 'cleveland', '97 - 105', 'charlotte', 'chris mills , 26 points', 'charlotte coliseum 23698', '38 - 30'], ['march 29', 'cleveland', '96 - 107', 'indiana', 'chris mills , 22 points', 'market square arena 16619', '38 - 31'], ['march 31', 'washington', '88 - 98', 'cleveland', 'chris mills , 24 points', 'gund arena 20562', '39 - 31']] |
john isner | https://en.wikipedia.org/wiki/John_Isner | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12509095-8.html.csv | majority | john isner was the runner-up in the majority of his tournament outcomes . | {'scope': 'all', 'col': '1', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'runner - up', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'outcome', 'runner - up'], 'result': True, 'ind': 0, 'tointer': 'for the outcome records of all rows , most of them fuzzily match to runner - up .', 'tostr': 'most_eq { all_rows ; outcome ; runner - up } = true'} | most_eq { all_rows ; outcome ; runner - up } = true | for the outcome records of all rows , most of them fuzzily match to runner - up . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'outcome_3': 3, 'runner - up_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'outcome_3': 'outcome', 'runner - up_4': 'runner - up'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'outcome_3': [0], 'runner - up_4': [0]} | ['outcome', 'date', 'surface', 'opponent', 'score'] | [['runner - up', 'august 5 , 2007', 'hard', 'andy roddick', '4 - 6 , 6 - 7 ( 4 - 7 )'], ['winner', 'january 16 , 2010', 'hard', 'arnaud clément', '6 - 3 , 5 - 7 , 7 - 6 ( 7 - 2 )'], ['runner - up', 'february 21 , 2010', 'hard ( i )', 'sam querrey', '7 - 6 ( 7 - 3 ) , 6 - 7 ( 5 - 7 ) , 3 - 6'], ['runner - up', 'may 9 , 2010', 'clay', 'sam querrey', '6 - 3 , 6 - 7 ( 4 - 7 ) , 4 - 6'], ['runner - up', 'july 25 , 2010', 'hard', 'mardy fish', '6 - 4 , 4 - 6 , 6 - 7 ( 4 - 7 )'], ['winner', 'july 10 , 2011', 'grass', 'olivier rochus', '6 - 3 , 7 - 6 ( 8 - 6 )'], ['runner - up', 'july 24 , 2011', 'hard', 'mardy fish', '6 - 3 , 6 - 7 ( 6 - 8 ) , 2 - 6'], ['winner', 'august 27 , 2011', 'hard', 'julien benneteau', '4 - 6 , 6 - 3 , 6 - 4'], ['runner - up', 'march 18 , 2012', 'hard', 'roger federer', '6 - 7 ( 7 - 9 ) , 3 - 6'], ['runner - up', 'april 15 , 2012', 'clay', 'juan mónaco', '2 - 6 , 6 - 3 , 3 - 6'], ['winner', 'july 15 , 2012', 'grass', 'lleyton hewitt', '7 - 6 ( 7 - 1 ) , 6 - 4'], ['winner', 'august 25 , 2012', 'hard', 'tomáš berdych', '3 - 6 , 6 - 4 , 7 - 6 ( 11 - 9 )'], ['winner', 'april 14 , 2013', 'clay', 'nicolás almagro', '6 - 3 , 7 - 5'], ['winner', 'july 28 , 2013', 'hard', 'kevin anderson', '6 - 7 ( 3 - 7 ) , 7 - 6 ( 7 - 2 ) , 7 - 6 ( 7 - 2 )'], ['runner - up', 'august 4 , 2013', 'hard', 'juan martín del potro', '6 - 3 , 1 - 6 , 2 - 6'], ['runner - up', 'august 18 , 2013', 'hard', 'rafael nadal', '6 - 7 ( 8 - 10 ) , 6 - 7 ( 3 - 7 )']] |
2007 world championships in athletics - men 's 200 metres | https://en.wikipedia.org/wiki/2007_World_Championships_in_Athletics_%E2%80%93_Men%27s_200_metres | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18912995-9.html.csv | superlative | tyson gay has the fastest total time of all the athletes listed . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '1', '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', 'time'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; time }'}, 'name'], 'result': 'tyson gay', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; time } ; name }'}, 'tyson gay'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmin { all_rows ; time } ; name } ; tyson gay } = true', 'tointer': 'select the row whose time record of all rows is minimum . the name record of this row is tyson gay .'} | eq { hop { argmin { all_rows ; time } ; name } ; tyson gay } = true | select the row whose time record of all rows is minimum . the name record of this row is tyson gay . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'time_5': 5, 'name_6': 6, 'tyson gay_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'time_5': 'time', 'name_6': 'name', 'tyson gay_7': 'tyson gay'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'time_5': [0], 'name_6': [1], 'tyson gay_7': [2]} | ['lane', 'name', 'nationality', 'react', 'time'] | [['4', 'tyson gay', 'united states', '0.143', '19.76'], ['5', 'usain bolt', 'jamaica', '0.159', '19.91'], ['6', 'wallace spearmon', 'united states', '0.144', '20.05'], ['8', 'rodney martin', 'united states', '0.186', '20.06'], ['3', 'churandy martina', 'netherlands antilles', '0.144', '20.28'], ['7', 'marvin anderson', 'jamaica', '0.171', '20.28'], ['9', 'christopher williams', 'jamaica', '0.154', '20.57'], ['7', 'anastasios gousis', 'greece', '0.143', '20.75']] |
challenge of champions | https://en.wikipedia.org/wiki/Challenge_of_Champions | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12743706-1.html.csv | count | in five of the years , the venue for the challenge of champions was atlanta . | {'scope': 'all', 'criterion': 'equal', 'value': 'atlanta', 'result': '5', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'venue', 'atlanta'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose venue record fuzzily matches to atlanta .', 'tostr': 'filter_eq { all_rows ; venue ; atlanta }'}], 'result': '5', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; venue ; atlanta } }', 'tointer': 'select the rows whose venue record fuzzily matches to atlanta . the number of such rows is 5 .'}, '5'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; venue ; atlanta } } ; 5 } = true', 'tointer': 'select the rows whose venue record fuzzily matches to atlanta . the number of such rows is 5 .'} | eq { count { filter_eq { all_rows ; venue ; atlanta } } ; 5 } = true | select the rows whose venue record fuzzily matches to atlanta . the number of such rows is 5 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'venue_5': 5, 'atlanta_6': 6, '5_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'venue_5': 'venue', 'atlanta_6': 'atlanta', '5_7': '5'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'venue_5': [0], 'atlanta_6': [0], '5_7': [2]} | ['year', 'date final', 'venue', 'prize money', 'champion', 'runner - up', 'score in final', 'commercial name'] | [['1989', 'apr 26 - 30', 'atlanta', '500000', 'andre agassi', 'michael chang', '6 - 3 , 6 - 2', 'at & t challenge of champions'], ['1988', 'apr 28 - may 1', 'atlanta', '500000', 'ivan lendl', 'stefan edberg', '2 - 6 , 6 - 1 , 6 - 3', 'at & t challenge of champions'], ['1987', 'oct 6 - 11', 'atlanta', '500000', 'john mcenroe', 'paul annacone', '6 - 4 , 7 - 5', 'at & t challenge of champions'], ['1986', 'nov 25 - 30', 'atlanta', '500000', 'boris becker', 'john mcenroe', '3 - 6 , 6 - 3 , 7 - 5', 'at & t challenge of champions'], ['1986', 'jan 6 - 12', 'atlanta', '500000', 'ivan lendl', 'jimmy connors', '6 - 2 , 6 - 3', 'at & t challenge of champions'], ['1985', 'jan 1 - 6', 'las vegas', '1290000', 'john mcenroe', 'guillermo vilas', '7 - 5 , 6 - 0', 'at & t challenge of champions'], ['1984', 'jan 3 - 8', 'rosemont', '250000', 'jimmy connors', 'andrés gómez', '6 - 3 , 6 - 2 , 6 - 1', 'lite challenge of champions'], ['1983', 'jan 4 - 9', 'rosemont', '250000', 'ivan lendl', 'jimmy connors', '4 - 6 , 6 - 4 , 7 - 5 , 6 - 4', 'lite challenge of champions'], ['1982', 'jan 6 - 11', 'rosemont', '310000', 'jimmy connors', 'john mcenroe', '6 - 7 , 7 - 5 , 6 - 7 , 7 - 5 , 6 - 4', 'michelob light challenge of champions'], ['1981', 'jan 7 - 12', 'rosemont', '310000', 'john mcenroe', 'jimmy connors', '6 - 2 , 6 - 4 , 6 - 1', 'challenge of champions']] |
1994 foster 's cup | https://en.wikipedia.org/wiki/1994_Foster%27s_Cup | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-16387953-1.html.csv | unique | the only game in the first round of the 1994 foster 's cup that began at a time other than 8:00 pm was played at robertson oval , wagga wagga . | {'scope': 'all', 'row': '5', 'col': '8', 'col_other': '5', 'criterion': 'not_equal', 'value': '8:00 pm', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_not_eq', 'args': ['all_rows', 'time', '8:00 pm'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose time record does not match to 8:00 pm .', 'tostr': 'filter_not_eq { all_rows ; time ; 8:00 pm }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_not_eq { all_rows ; time ; 8:00 pm } }', 'tointer': 'select the rows whose time record does not match to 8:00 pm . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_not_eq', 'args': ['all_rows', 'time', '8:00 pm'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose time record does not match to 8:00 pm .', 'tostr': 'filter_not_eq { all_rows ; time ; 8:00 pm }'}, 'ground'], 'result': 'robertson oval , wagga wagga', 'ind': 2, 'tostr': 'hop { filter_not_eq { all_rows ; time ; 8:00 pm } ; ground }'}, 'robertson oval , wagga wagga'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_not_eq { all_rows ; time ; 8:00 pm } ; ground } ; robertson oval , wagga wagga }', 'tointer': 'the ground record of this unqiue row is robertson oval , wagga wagga .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_not_eq { all_rows ; time ; 8:00 pm } } ; eq { hop { filter_not_eq { all_rows ; time ; 8:00 pm } ; ground } ; robertson oval , wagga wagga } } = true', 'tointer': 'select the rows whose time record does not match to 8:00 pm . there is only one such row in the table . the ground record of this unqiue row is robertson oval , wagga wagga .'} | and { only { filter_not_eq { all_rows ; time ; 8:00 pm } } ; eq { hop { filter_not_eq { all_rows ; time ; 8:00 pm } ; ground } ; robertson oval , wagga wagga } } = true | select the rows whose time record does not match to 8:00 pm . there is only one such row in the table . the ground record of this unqiue row is robertson oval , wagga wagga . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_not_eq_0': 0, 'all_rows_6': 6, 'time_7': 7, '8:00 pm_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'ground_9': 9, 'robertson oval , wagga wagga_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_not_eq_0': 'filter_str_not_eq', 'all_rows_6': 'all_rows', 'time_7': 'time', '8:00 pm_8': '8:00 pm', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'ground_9': 'ground', 'robertson oval , wagga wagga_10': 'robertson oval , wagga wagga'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_not_eq_0': [1, 2], 'all_rows_6': [0], 'time_7': [0], '8:00 pm_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'ground_9': [2], 'robertson oval , wagga wagga_10': [3]} | ['home team', 'home team score', 'away team', 'away team score', 'ground', 'crowd', 'date', 'time'] | [['collingwood', '13.14 ( 92 )', 'north melbourne', '13.13 ( 91 )', 'waverley park', '25708', 'saturday , 19 february 1994', '8:00 pm'], ['st kilda', '14.12 ( 96 )', 'richmond', '17.14 ( 116 )', 'waverley park', '18662', 'monday , 21 february 1994', '8:00 pm'], ['adelaide', '16.17 ( 113 )', 'west coast', '14.10 ( 94 )', 'football park', '28776', 'wednesday 23 february 1994', '8:00 pm'], ['fitzroy', '12.13 ( 85 )', 'geelong', '10.11 ( 71 )', 'waverley park', '9080', 'wednesday 23 february 1994', '8:00 pm'], ['sydney', '18.11 ( 119 )', 'footscray', '16.10 ( 106 )', 'robertson oval , wagga wagga', '5525', 'saturday , 26 february 1994', '2:00 pm'], ['carlton', '11.18 ( 84 )', 'hawthorn', '14.15 ( 99 )', 'waverley park', '26117', 'saturday , 26 february 1994', '8:00 pm']] |
1982 - 83 atlanta hawks season | https://en.wikipedia.org/wiki/1982%E2%80%9383_Atlanta_Hawks_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18409079-1.html.csv | count | the 1982-83 atlanta hawks drafted a total of eight different players . | {'scope': 'all', 'criterion': 'all', 'value': 'n/a', 'result': '8', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_all', 'args': ['all_rows', 'player'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose player record is arbitrary .', 'tostr': 'filter_all { all_rows ; player }'}], 'result': '8', 'ind': 1, 'tostr': 'count { filter_all { all_rows ; player } }', 'tointer': 'select the rows whose player record is arbitrary . the number of such rows is 8 .'}, '8'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_all { all_rows ; player } } ; 8 } = true', 'tointer': 'select the rows whose player record is arbitrary . the number of such rows is 8 .'} | eq { count { filter_all { all_rows ; player } } ; 8 } = true | select the rows whose player record is arbitrary . the number of such rows is 8 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_all_0': 0, 'all_rows_4': 4, 'player_5': 5, '8_6': 6} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_all_0': 'filter_all', 'all_rows_4': 'all_rows', 'player_5': 'player', '8_6': '8'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_all_0': [1], 'all_rows_4': [0], 'player_5': [0], '8_6': [2]} | ['round', 'pick', 'player', 'nationality', 'college'] | [['1', '10', 'keith edmonson', 'united states', 'purdue'], ['3', '56', 'joe kopicki', 'united states', 'detroit mercy'], ['5', '102', 'mark hall', 'united states', 'minnesota'], ['6', '126', 'jay bruchak', 'united states', "mount st mary 's"], ['7', '148', 'horace wyatt', 'united states', 'clemson'], ['8', '172', 'james ratiff', 'united states', 'howard'], ['9', '194', 'pierre bland', 'united states', 'elizabeth city state'], ['10', '216', 'ronnie mcadoo', 'united states', 'old dominion']] |
édouard roger - vasselin | https://en.wikipedia.org/wiki/%C3%89douard_Roger-Vasselin | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11511365-4.html.csv | unique | 15 july 2013 was the only tournament that édouard roger - vasselin played on a grass surface . | {'scope': 'all', 'row': '4', 'col': '3', 'col_other': '1', 'criterion': 'equal', 'value': 'grass', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'surface', 'grass'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose surface record fuzzily matches to grass .', 'tostr': 'filter_eq { all_rows ; surface ; grass }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; surface ; grass } }', 'tointer': 'select the rows whose surface record fuzzily matches to grass . 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', 'grass'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose surface record fuzzily matches to grass .', 'tostr': 'filter_eq { all_rows ; surface ; grass }'}, 'outcome'], 'result': 'winner', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; surface ; grass } ; outcome }'}, 'winner'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; surface ; grass } ; outcome } ; winner }', 'tointer': 'the outcome record of this unqiue row is winner .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; surface ; grass } } ; eq { hop { filter_eq { all_rows ; surface ; grass } ; outcome } ; winner } } = true', 'tointer': 'select the rows whose surface record fuzzily matches to grass . there is only one such row in the table . the outcome record of this unqiue row is winner .'} | and { only { filter_eq { all_rows ; surface ; grass } } ; eq { hop { filter_eq { all_rows ; surface ; grass } ; outcome } ; winner } } = true | select the rows whose surface record fuzzily matches to grass . there is only one such row in the table . the outcome record of this unqiue row is winner . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'surface_7': 7, 'grass_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'outcome_9': 9, 'winner_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', 'grass_8': 'grass', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'outcome_9': 'outcome', 'winner_10': 'winner'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'surface_7': [0], 'grass_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'outcome_9': [2], 'winner_10': [3]} | ['outcome', 'date', 'surface', 'partner', 'opponents', 'score'] | [['winner', '5 february 2012', 'hard ( i )', 'nicolas mahut', 'paul hanley jamie murray', '6 - 4 , 7 - 6 ( 7 - 4 )'], ['winner', '20 february 2012', 'hard ( i )', 'nicolas mahut', 'dustin brown jo - wilfried tsonga', '3 - 6 , 6 - 3 ,'], ['winner', '17 september 2012', 'hard ( i )', 'nicolas mahut', 'johan brunström frederik nielsen', '7 - 6 ( 7 - 3 ) , 6 - 4'], ['winner', '15 july 2013', 'grass', 'nicolas mahut', 'tim smyczek rhyne williams', '6 - 7 ( 4 - 7 ) , 6 - 2 ,'], ['runner - up', '20 july 2013', 'hard', 'igor sijsling', 'purav raja divij sharan', '6 - 7 ( 4 - 7 ) , 6 - 7 ( 3 - 7 )'], ['winner', '29 july 2013', 'hard', 'igor sijsling', 'colin fleming jonathan marray', '7 - 6 ( 8 - 6 ) , 6 - 3'], ['winner', '6 october 2013', 'hard', 'rohan bopanna', 'jamie murray john peers', '7 - 6 ( 7 - 5 ) , 6 - 4']] |
jack turner ( racing driver ) | https://en.wikipedia.org/wiki/Jack_Turner_%28racing_driver%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1252094-1.html.csv | unique | 1958 was the only year in which jack turner started in position 10 . | {'scope': 'all', 'row': '3', 'col': '2', 'col_other': '1', 'criterion': 'equal', 'value': '10', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'start', '10'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose start record is equal to 10 .', 'tostr': 'filter_eq { all_rows ; start ; 10 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; start ; 10 } }', 'tointer': 'select the rows whose start record is equal to 10 . there is only one such row in the table .'}, {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'start', '10'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose start record is equal to 10 .', 'tostr': 'filter_eq { all_rows ; start ; 10 }'}, 'year'], 'result': '1958', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; start ; 10 } ; year }'}, '1958'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; start ; 10 } ; year } ; 1958 }', 'tointer': 'the year record of this unqiue row is 1958 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; start ; 10 } } ; eq { hop { filter_eq { all_rows ; start ; 10 } ; year } ; 1958 } } = true', 'tointer': 'select the rows whose start record is equal to 10 . there is only one such row in the table . the year record of this unqiue row is 1958 .'} | and { only { filter_eq { all_rows ; start ; 10 } } ; eq { hop { filter_eq { all_rows ; start ; 10 } ; year } ; 1958 } } = true | select the rows whose start record is equal to 10 . there is only one such row in the table . the year record of this unqiue row is 1958 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'start_7': 7, '10_8': 8, 'eq_3': 3, 'num_hop_2': 2, 'year_9': 9, '1958_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'start_7': 'start', '10_8': '10', 'eq_3': 'eq', 'num_hop_2': 'num_hop', 'year_9': 'year', '1958_10': '1958'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'start_7': [0], '10_8': [0], 'eq_3': [4], 'num_hop_2': [3], 'year_9': [2], '1958_10': [3]} | ['year', 'start', 'qual', 'rank', 'finish', 'laps'] | [['1956', '24', '142.394', '18', '25', '131'], ['1957', '19', '140.367', '25', '11', '200'], ['1958', '10', '143.438', '12', '25', '21'], ['1959', '14', '143.478', '11', '27', '47'], ['1961', '21', '144.904', '21', '25', '52'], ['1962', '25', '146.496', '25', '29', '17']] |
77th united states congress | https://en.wikipedia.org/wiki/77th_United_States_Congress | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1958768-3.html.csv | count | 3 of the vacators in the 77th . us congress resigned . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'resigned', 'result': '3', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'reason for change', 'resigned'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose reason for change record fuzzily matches to resigned .', 'tostr': 'filter_eq { all_rows ; reason for change ; resigned }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; reason for change ; resigned } }', 'tointer': 'select the rows whose reason for change record fuzzily matches to resigned . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; reason for change ; resigned } } ; 3 } = true', 'tointer': 'select the rows whose reason for change record fuzzily matches to resigned . the number of such rows is 3 .'} | eq { count { filter_eq { all_rows ; reason for change ; resigned } } ; 3 } = true | select the rows whose reason for change record fuzzily matches to resigned . 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, 'reason for change_5': 5, 'resigned_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', 'reason for change_5': 'reason for change', 'resigned_6': 'resigned', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'reason for change_5': [0], 'resigned_6': [0], '3_7': [2]} | ['district', 'vacator', 'reason for change', 'successor', 'date successor seated'] | [['oklahoma 7th', 'sam c massingale ( d )', 'died january 17 , 1941', 'victor wickersham ( d )', 'april 1 , 1941'], ['new york 17th', 'kenneth f simpson ( r )', 'died january 25 , 1941', 'joseph c baldwin ( r )', 'march 11 , 1941'], ['alabama 7th', 'walter w bankhead ( d )', 'resigned february 1 , 1941', 'carter manasco ( d )', 'june 24 , 1941'], ['maryland 6th', 'william d byron ( d )', 'died february 27 , 1941', 'katharine byron ( d )', 'may 27 , 1941'], ['new york 42nd', 'pius l schwert ( d )', 'died march 11 , 1941', 'john c butler ( r )', 'april 22 , 1941'], ['north carolina 5th', 'alonzo d folger ( d )', 'died april 30 , 1941', 'john h folger ( d )', 'june 14 , 1941'], ['new york 14th', 'morris m edelstein ( d )', 'died june 4 , 1941', 'arthur g klein ( d )', 'july 29 , 1941'], ['wisconsin 1st', 'stephen bolles ( r )', 'died july 8 , 1941', 'lawrence h smith ( r )', 'august 29 , 1941'], ['pennsylvania 15th', 'albert g rutherford ( r )', 'died august 10 , 1941', 'wilson d gillette ( r )', 'november 4 , 1941'], ['colorado 4th', 'edward t taylor ( d )', 'died september 3 , 1941', 'robert f rockwell ( r )', 'december 9 , 1941'], ['california 17th', 'lee e geyer ( d )', 'died october 11 , 1941', 'cecil r king ( d )', 'august 25 , 1942'], ['massachusetts 7th', 'lawrence j connery ( d )', 'died october 19 , 1941', 'thomas j lane ( d )', 'december 30 , 1941'], ['pennsylvania 11th', 'patrick j boland ( d )', 'died may 18 , 1942', 'veronica g boland ( d )', 'november 3 , 1942'], ['california 3rd', 'frank h buck ( d )', 'died september 17 , 1942', 'vacant until the next congress', 'vacant until the next congress'], ['pennsylvania 25th', 'charles i faddis ( d )', 'resigned december 4 , 1942 to enter the us army', 'vacant until the next congress', 'vacant until the next congress'], ['illinois 6th', 'a f maciejewski ( d )', 'resigned december 6 , 1942', 'vacant until the next congress', 'vacant until the next congress']] |
orchid stakes | https://en.wikipedia.org/wiki/Orchid_Stakes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14863959-1.html.csv | count | gerald w leigh owned two of the horses who won the orchard stakes . | {'scope': 'all', 'criterion': 'equal', 'value': 'gerald w leigh', 'result': '2', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'owner', 'gerald w leigh'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose owner record fuzzily matches to gerald w leigh .', 'tostr': 'filter_eq { all_rows ; owner ; gerald w leigh }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; owner ; gerald w leigh } }', 'tointer': 'select the rows whose owner record fuzzily matches to gerald w leigh . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; owner ; gerald w leigh } } ; 2 } = true', 'tointer': 'select the rows whose owner record fuzzily matches to gerald w leigh . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; owner ; gerald w leigh } } ; 2 } = true | select the rows whose owner record fuzzily matches to gerald w leigh . 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, 'owner_5': 5, 'gerald w leigh_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', 'owner_5': 'owner', 'gerald w leigh_6': 'gerald w leigh', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'owner_5': [0], 'gerald w leigh_6': [0], '2_7': [2]} | ['year', 'winner', 'jockey', 'trainer', 'owner', 'time'] | [['2013', 'regalo mia', 'luis contreras', 'michelle nihei', 'steven w ciccarone', '2:23.48'], ['2012', 'hit it rich', 'javier castellano', 'shug mcgaughey', 'stuart s janney iii', '2:28.06'], ['2011', 'la luna de miel', 'john velazquez', 'h graham motion', 'rashit shaykhutdinov', '2:25.76'], ['2010', 'speak easy gal', 'elvis trujillo', 'marty wolfson', 'farnsworth stables', '2:28.46'], ['2009', 'dress rehearsal', 'kent desormeaux', 'william i mott', 'swettenham stud', '2:29.77'], ['2008', 'hostess', 'john velazquez', 'h james bond', 'william clifton jr', '2:25.83'], ['2007', 'safari queen', 'chris decarlo', 'todd a pletcher', 'arindel farm', '2:25.17'], ['2006', 'honey ryder', 'john r velazquez', 'todd a pletcher', 'glencrest farm llc', '2:23.07'], ['2005', 'honey ryder', 'john r velazquez', 'todd a pletcher', 'glencrest farm llc', '2:27.15'], ['2004', 'meridiana', 'edgar prado', 'christophe clement', 'jon & sarah kelly', '2:26.99'], ['2003', 'tweedside', 'rene douglas', 'todd a pletcher', 'e & l melnyk', '2:32.36'], ['2002', 'julie jalouse', 'jose a santos', 'christophe clement', 'skymarc farm', '2:25.89'], ['2001', 'innuendo', 'jerry d bailey', 'christophe clement', 'gerald w leigh', '2:25.24'], ['2000', 'lisieux rose', 'jose a santos', 'christophe clement', 'moyglare stud farm', '2:25.64'], ['1999', 'coretta', 'jose a santos', 'christophe clement', 'gerald w leigh', '2:23.85']] |
list of bradford city a.f.c. records and statistics | https://en.wikipedia.org/wiki/List_of_Bradford_City_A.F.C._records_and_statistics | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15278857-2.html.csv | superlative | john hall is the player with the highest amount of appearances for bradford city a.f.c. | {'scope': 'all', 'col_superlative': '3', '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', 'apps'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; apps }'}, 'name'], 'result': 'john hall', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; apps } ; name }'}, 'john hall'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; apps } ; name } ; john hall } = true', 'tointer': 'select the row whose apps record of all rows is maximum . the name record of this row is john hall .'} | eq { hop { argmax { all_rows ; apps } ; name } ; john hall } = true | select the row whose apps record of all rows is maximum . the name record of this row is john hall . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'apps_5': 5, 'name_6': 6, 'john hall_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'apps_5': 'apps', 'name_6': 'name', 'john hall_7': 'john hall'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'apps_5': [0], 'name_6': [1], 'john hall_7': [2]} | ['name', 'goals', 'apps', 'avge', 'career'] | [['bobby campbell', '121', '274', '0.44', '1979 - 1983 , 1983 - 1986'], ["frank o'rourke", '88', '192', '0.46', '1907 - 1914'], ['dean windass', '76', '216', '0.35', '1999 - 2001 , 2003 - 2007'], ['john hallows', '74', '164', '0.45', '1930 - 1936'], ['joe cooke', '68', '271', '0.25', '1971 - 1979 , 1981 - 1984'], ['gerry ingram', '64', '174', '0.37', '1971 - 1977'], ['bobby ham', '64', '188', '0.34', '1967 - 1971 , 1973 - 1975'], ['david mcniven', '64', '212', '0.30', '1978 - 1983'], ['sean mccarthy', '63', '131', '0.48', '1990 - 1994'], ['john hall', '63', '430', '0.15', '1962 - 1974'], ['david jackson', '61', '250', '0.24', '1955 - 1961'], ['bruce bannister', '60', '208', '0.29', '1965 - 1971'], ['dicky bond', '60', '301', '0.20', '1909 - 1922']] |
bobsleigh at the 1932 winter olympics - four - man | https://en.wikipedia.org/wiki/Bobsleigh_at_the_1932_Winter_Olympics_%E2%80%93_Four-man | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16944107-2.html.csv | aggregation | for the four man bobsleigh 1932 winter olympics the total combined final time for both usa teams was 15:49.38 . | {'scope': 'subset', 'col': '7', 'type': 'sum', 'result': '15:49.38', 'subset': {'col': '2', 'criterion': 'fuzzily_match', 'value': 'usa'}} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'team', 'usa'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; team ; usa }', 'tointer': 'select the rows whose team record fuzzily matches to usa .'}, 'final'], 'result': '15:49.38', 'ind': 1, 'tostr': 'sum { filter_eq { all_rows ; team ; usa } ; final }'}, '15:49.38'], 'result': True, 'ind': 2, 'tostr': 'round_eq { sum { filter_eq { all_rows ; team ; usa } ; final } ; 15:49.38 } = true', 'tointer': 'select the rows whose team record fuzzily matches to usa . the sum of the final record of these rows is 15:49.38 .'} | round_eq { sum { filter_eq { all_rows ; team ; usa } ; final } ; 15:49.38 } = true | select the rows whose team record fuzzily matches to usa . the sum of the final record of these rows is 15:49.38 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'sum_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'team_5': 5, 'usa_6': 6, 'final_7': 7, '15:49.38_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'sum_1': 'sum', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'team_5': 'team', 'usa_6': 'usa', 'final_7': 'final', '15:49.38_8': '15:49.38'} | {'eq_2': [3], 'result_3': [], 'sum_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'team_5': [0], 'usa_6': [0], 'final_7': [1], '15:49.38_8': [2]} | ['rank', 'team', 'run 1', 'run 2', 'run 3', 'run 4', 'final'] | [['gold', 'united states ( usa ) usa i', '2:00.52', '1:59.16', '1:57.41', '1:56.59', '7:53.68'], ['silver', 'united states ( usa ) usa ii', '2:01.77', '2:01.09', '1:58.56', '1:54.28', '7:55.70'], ['bronze', 'germany ( ger ) germany i', '2:03.11', '2:01.34', '1:58.19', '1:57.40', '8:00.04'], ['4', 'switzerland ( sui ) switzerland ii', '2:06.81', '2:03.40', '2:01.47', '2:00.50', '8:12.18'], ['5', 'italy ( ita ) italy i', '2:07.87', '2:06.62', '2:07.94', '2:01.78', '8:24.21'], ['6', 'romania ( rou ) romania i', '2:09.09', '2:14.32', '2:02.00', '1:58.81', '8:24.21'], ['7', 'germany ( ger ) germany ii', '2:11.59', '2:11.72', '2:07.89', '2:04.25', '8:35.45']] |
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 | majority | johnson had the majority of high scores for this stretch of the atlanta hawks season . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': 'j johnson', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'high points', 'j johnson'], 'result': True, 'ind': 0, 'tointer': 'for the high points records of all rows , most of them fuzzily match to j johnson .', 'tostr': 'most_eq { all_rows ; high points ; j johnson } = true'} | most_eq { all_rows ; high points ; j johnson } = true | for the high points records of all rows , most of them fuzzily match to j johnson . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'high points_3': 3, 'j johnson_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'high points_3': 'high points', 'j johnson_4': 'j johnson'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'high points_3': [0], 'j johnson_4': [0]} | ['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']] |
1994 - 95 fa cup | https://en.wikipedia.org/wiki/1994%E2%80%9395_FA_Cup | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16222274-6.html.csv | count | in the 1994 - 95 fa cup , among the games with final score 1-0 , 2 of them were played in february . | {'scope': 'subset', 'criterion': 'fuzzily_match', 'value': 'february', 'result': '2', 'col': '5', 'subset': {'col': '3', 'criterion': 'equal', 'value': '1 - 0'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'score', '1 - 0'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; score ; 1 - 0 }', 'tointer': 'select the rows whose score record fuzzily matches to 1 - 0 .'}, 'attendance', 'february'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose score record fuzzily matches to 1 - 0 . among these rows , select the rows whose attendance record fuzzily matches to february .', 'tostr': 'filter_eq { filter_eq { all_rows ; score ; 1 - 0 } ; attendance ; february }'}], 'result': '2', 'ind': 2, 'tostr': 'count { filter_eq { filter_eq { all_rows ; score ; 1 - 0 } ; attendance ; february } }', 'tointer': 'select the rows whose score record fuzzily matches to 1 - 0 . among these rows , select the rows whose attendance record fuzzily matches to february . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_eq { filter_eq { all_rows ; score ; 1 - 0 } ; attendance ; february } } ; 2 } = true', 'tointer': 'select the rows whose score record fuzzily matches to 1 - 0 . among these rows , select the rows whose attendance record fuzzily matches to february . the number of such rows is 2 .'} | eq { count { filter_eq { filter_eq { all_rows ; score ; 1 - 0 } ; attendance ; february } } ; 2 } = true | select the rows whose score record fuzzily matches to 1 - 0 . among these rows , select the rows whose attendance record fuzzily matches to february . the number of such rows is 2 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_str_eq_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'score_6': 6, '1 - 0_7': 7, 'attendance_8': 8, 'february_9': 9, '2_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_str_eq_1': 'filter_str_eq', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'score_6': 'score', '1 - 0_7': '1 - 0', 'attendance_8': 'attendance', 'february_9': 'february', '2_10': '2'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_str_eq_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'score_6': [0], '1 - 0_7': [0], 'attendance_8': [1], 'february_9': [1], '2_10': [3]} | ['tie no', 'home team', 'score', 'away team', 'attendance'] | [['1', 'liverpool', '1 - 1', 'wimbledon', '25124'], ['replay', 'wimbledon', '0 - 2', 'liverpool', '12553'], ['2', 'watford', '0 - 0', 'crystal palace', '18 february 1995'], ['replay', 'crystal palace', '1 - 0', 'watford', '1 march 1995'], ['3', 'wolverhampton wanderers', '1 - 0', 'leicester city', '18 february 1995'], ['4', 'everton', '5 - 0', 'norwich city', '18 february 1995'], ['5', 'newcastle united', '3 - 1', 'manchester city', '19 february 1995'], ['6', 'tottenham hotspur', '1 - 1', 'southampton', '18 february 1995'], ['replay', 'southampton', '2 - 6', 'tottenham hotspur', '1 march 1995'], ['7', 'queens park rangers', '1 - 0', 'millwall', '18 february 1995'], ['8', 'manchester united', '3 - 1', 'leeds united', '19 february 1995']] |
keisuke honda | https://en.wikipedia.org/wiki/Keisuke_Honda | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14670286-4.html.csv | aggregation | keisuka honda scored an average of 2 points in all of the matches . | {'scope': 'all', 'col': '3', 'type': 'average', 'result': '2.2', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'score'], 'result': '2.2', 'ind': 0, 'tostr': 'avg { all_rows ; score }'}, '2.2'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; score } ; 2.2 } = true', 'tointer': 'the average of the score record of all rows is 2.2 .'} | round_eq { avg { all_rows ; score } ; 2.2 } = true | the average of the score record of all rows is 2.2 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'score_4': 4, '2.2_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'score_4': 'score', '2.2_5': '2.2'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'score_4': [0], '2.2_5': [1]} | ['date', 'venue', 'score', 'result', 'competition'] | [['27 may 2009', 'nagai stadium , osaka', '4 - 0', '4 - 0', '2009 kirin cup'], ['10 october 2009', 'nissan stadium , yokohama', '2 - 0', '2 - 0', 'friendly match ( 2009 kirin challenge cup )'], ['14 october 2009', 'miyagi stadium , rifu', '5 - 0', '5 - 0', 'friendly match ( 2009 kirin challenge cup )'], ['3 march 2010', 'toyota stadium , toyota', '2 - 0', '2 - 0', '2011 afc asian cup qualification'], ['14 june 2010', 'free state stadium , bloemfontein', '1 - 0', '1 - 0', '2010 fifa world cup'], ['24 june 2010', 'royal bafokeng stadium , rustenburg', '1 - 0', '3 - 1', '2010 fifa world cup'], ['13 january 2011', 'qatar sc stadium , doha', '2 - 1', '2 - 1', '2011 afc asian cup'], ['10 august 2011', 'sapporo dome , sapporo', '2 - 0', '3 - 0', 'friendly match ( 2011 kirin challenge cup )'], ['3 june 2012', 'saitama stadium 2002 , saitama', '1 - 0', '3 - 0', '2014 fifa world cup qualification'], ['8 june 2012', 'saitama stadium 2002 , saitama', '2 - 0', '6 - 0', '2014 fifa world cup qualification'], ['8 june 2012', 'saitama stadium 2002 , saitama', '3 - 0', '6 - 0', '2014 fifa world cup qualification'], ['8 june 2012', 'saitama stadium 2002 , saitama', '5 - 0', '6 - 0', '2014 fifa world cup qualification'], ['6 february 2013', "home 's stadium kobe , kobe", '2 - 0', '3 - 0', 'friendly'], ['4 june 2013', 'saitama stadium 2002 , saitama', '1 - 1', '1 - 1', '2014 fifa world cup qualification'], ['19 june 2013', 'itaipava arena pernambuco , recife', '1 - 0', '3 - 4', '2013 fifa confederations cup'], ['14 august 2013', 'miyagi stadium , rifu', '2 - 4', '2 - 4', 'friendly'], ['6 september 2013', 'nagai stadium , osaka', '1 - 0', '3 - 0', 'friendly'], ['10 september 2013', 'international stadium yokohama , kanagawa', '3 - 1', '3 - 1', 'friendly'], ['as of 6 september 2013', 'as of 6 september 2013', 'as of 6 september 2013', 'as of 6 september 2013', 'as of 6 september 2013']] |
1976 - 77 san antonio spurs season | https://en.wikipedia.org/wiki/1976%E2%80%9377_San_Antonio_Spurs_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16386910-2.html.csv | comparative | the san antonio spurs scored more points on october 26 than on october 23 . | {'row_1': '3', 'row_2': '2', 'col': '3', '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', 'date', 'october 26 , 1976'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose date record fuzzily matches to october 26 , 1976 .', 'tostr': 'filter_eq { all_rows ; date ; october 26 , 1976 }'}, 'score'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; date ; october 26 , 1976 } ; score }', 'tointer': 'select the rows whose date record fuzzily matches to october 26 , 1976 . take the score record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', 'october 23 , 1976'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose date record fuzzily matches to october 23 , 1976 .', 'tostr': 'filter_eq { all_rows ; date ; october 23 , 1976 }'}, 'score'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; date ; october 23 , 1976 } ; score }', 'tointer': 'select the rows whose date record fuzzily matches to october 23 , 1976 . take the score record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; date ; october 26 , 1976 } ; score } ; hop { filter_eq { all_rows ; date ; october 23 , 1976 } ; score } } = true', 'tointer': 'select the rows whose date record fuzzily matches to october 26 , 1976 . take the score record of this row . select the rows whose date record fuzzily matches to october 23 , 1976 . take the score record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; date ; october 26 , 1976 } ; score } ; hop { filter_eq { all_rows ; date ; october 23 , 1976 } ; score } } = true | select the rows whose date record fuzzily matches to october 26 , 1976 . take the score record of this row . select the rows whose date record fuzzily matches to october 23 , 1976 . take the score record of this row . the first record is greater than the second record . | 5 | 5 | {'greater_4': 4, 'result_5': 5, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'date_7': 7, 'october 26 , 1976_8': 8, 'score_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'date_11': 11, 'october 23 , 1976_12': 12, 'score_13': 13} | {'greater_4': 'greater', 'result_5': 'true', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'date_7': 'date', 'october 26 , 1976_8': 'october 26 , 1976', 'score_9': 'score', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'date_11': 'date', 'october 23 , 1976_12': 'october 23 , 1976', 'score_13': 'score'} | {'greater_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'date_7': [0], 'october 26 , 1976_8': [0], 'score_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'date_11': [1], 'october 23 , 1976_12': [1], 'score_13': [3]} | ['date', 'visitor', 'score', 'home', 'record'] | [['october 22 , 1976', 'san antonio spurs', '121 - 118', 'philadelphia 76ers', '1 - 0'], ['october 23 , 1976', 'san antonio spurs', '98 - 117', 'new york knicks', '1 - 1'], ['october 26 , 1976', 'san antonio spurs', '114 - 122', 'atlanta hawks', '1 - 2'], ['october 27 , 1976', 'phoenix suns', '106 - 115', 'san antonio spurs', '2 - 2'], ['october 29 , 1976', 'san antonio spurs', '102 - 130', 'kansas city kings', '2 - 3'], ['october 30 , 1976', 'boston celtics', '126 - 117', 'san antonio spurs', '2 - 4']] |
1952 vfl season | https://en.wikipedia.org/wiki/1952_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10750694-9.html.csv | unique | on june 21 , 1952 , the only game that had less than 10000 people in attendance was the st. kilda game . | {'scope': 'all', 'row': '4', 'col': '6', 'col_other': '1', 'criterion': 'less_than', 'value': '10000', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'crowd', '10000'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose crowd record is less than 10000 .', 'tostr': 'filter_less { all_rows ; crowd ; 10000 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_less { all_rows ; crowd ; 10000 } }', 'tointer': 'select the rows whose crowd record is less than 10000 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'crowd', '10000'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose crowd record is less than 10000 .', 'tostr': 'filter_less { all_rows ; crowd ; 10000 }'}, 'home team'], 'result': 'st kilda', 'ind': 2, 'tostr': 'hop { filter_less { all_rows ; crowd ; 10000 } ; home team }'}, 'st kilda'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_less { all_rows ; crowd ; 10000 } ; home team } ; st kilda }', 'tointer': 'the home team record of this unqiue row is st kilda .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_less { all_rows ; crowd ; 10000 } } ; eq { hop { filter_less { all_rows ; crowd ; 10000 } ; home team } ; st kilda } } = true', 'tointer': 'select the rows whose crowd record is less than 10000 . there is only one such row in the table . the home team record of this unqiue row is st kilda .'} | and { only { filter_less { all_rows ; crowd ; 10000 } } ; eq { hop { filter_less { all_rows ; crowd ; 10000 } ; home team } ; st kilda } } = true | select the rows whose crowd record is less than 10000 . there is only one such row in the table . the home team record of this unqiue row is st kilda . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_less_0': 0, 'all_rows_6': 6, 'crowd_7': 7, '10000_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'home team_9': 9, 'st kilda_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_less_0': 'filter_less', 'all_rows_6': 'all_rows', 'crowd_7': 'crowd', '10000_8': '10000', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'home team_9': 'home team', 'st kilda_10': 'st kilda'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_less_0': [1, 2], 'all_rows_6': [0], 'crowd_7': [0], '10000_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'home team_9': [2], 'st kilda_10': [3]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['geelong', '7.13 ( 55 )', 'south melbourne', '4.11 ( 35 )', 'kardinia park', '21513', '21 june 1952'], ['essendon', '11.8 ( 74 )', 'melbourne', '10.15 ( 75 )', 'windy hill', '16000', '21 june 1952'], ['collingwood', '6.8 ( 44 )', 'north melbourne', '8.12 ( 60 )', 'victoria park', '15500', '21 june 1952'], ['st kilda', '5.11 ( 41 )', 'hawthorn', '7.6 ( 48 )', 'junction oval', '7500', '21 june 1952'], ['footscray', '6.9 ( 45 )', 'fitzroy', '7.8 ( 50 )', 'western oval', '14085', '21 june 1952'], ['richmond', '5.3 ( 33 )', 'carlton', '5.9 ( 39 )', 'punt road oval', '21000', '21 june 1952']] |
1993 tampa bay buccaneers season | https://en.wikipedia.org/wiki/1993_Tampa_Bay_Buccaneers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11452712-1.html.csv | ordinal | for the 1993 tampa bay buccaneers season , the player picked 3rd to last was tyree davis . | {'row': '8', 'col': '2', 'order': '3', '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', 'round', '3'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; round ; 3 }'}, 'player'], 'result': 'tyree davis', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; round ; 3 } ; player }'}, 'tyree davis'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; round ; 3 } ; player } ; tyree davis } = true', 'tointer': 'select the row whose round record of all rows is 3rd maximum . the player record of this row is tyree davis .'} | eq { hop { nth_argmax { all_rows ; round ; 3 } ; player } ; tyree davis } = true | select the row whose round record of all rows is 3rd maximum . the player record of this row is tyree davis . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'round_5': 5, '3_6': 6, 'player_7': 7, 'tyree davis_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', 'round_5': 'round', '3_6': '3', 'player_7': 'player', 'tyree davis_8': 'tyree davis'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'round_5': [0], '3_6': [0], 'player_7': [1], 'tyree davis_8': [2]} | ['pick', 'round', 'player', 'position', 'school'] | [['6', 'round 1', 'eric curry', 'defensive end', 'alabama'], ['34', 'round 2', 'demetrius dubose', 'linebacker', 'notre dame'], ['60', 'round 3', 'lamar thomas', 'wide receiver', 'miami'], ['82', 'round 3', 'john lynch', 'defensive back', 'stanford'], ['91', 'round 4', 'rudy harris', 'running back', 'clemson'], ['104', 'round 4', 'horace copeland', 'wide receiver', 'miami'], ['145', 'round 6', 'chidi ahanotu', 'defensive tackle', 'california'], ['176', 'round 7', 'tyree davis', 'wide receiver', 'central arkansas'], ['220', 'round 8', 'darrick branch', 'wide receiver', 'hawaii'], ['224', 'round 8', 'daron alcorn', 'kicker', 'akron']] |
bluebird k7 | https://en.wikipedia.org/wiki/Bluebird_K7 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17829496-1.html.csv | comparative | the bluebird k7 speed run at ullswater was earlier than the one that took place at lake dumbleyung . | {'row_1': '1', 'row_2': '7', 'col': '5', 'col_other': '4', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location', 'ullswater'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose location record fuzzily matches to ullswater .', 'tostr': 'filter_eq { all_rows ; location ; ullswater }'}, 'date'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; location ; ullswater } ; date }', 'tointer': 'select the rows whose location record fuzzily matches to ullswater . take the date record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location', 'lake dumbleyung'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose location record fuzzily matches to lake dumbleyung .', 'tostr': 'filter_eq { all_rows ; location ; lake dumbleyung }'}, 'date'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; location ; lake dumbleyung } ; date }', 'tointer': 'select the rows whose location record fuzzily matches to lake dumbleyung . take the date record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; location ; ullswater } ; date } ; hop { filter_eq { all_rows ; location ; lake dumbleyung } ; date } } = true', 'tointer': 'select the rows whose location record fuzzily matches to ullswater . take the date record of this row . select the rows whose location record fuzzily matches to lake dumbleyung . take the date record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; location ; ullswater } ; date } ; hop { filter_eq { all_rows ; location ; lake dumbleyung } ; date } } = true | select the rows whose location record fuzzily matches to ullswater . take the date record of this row . select the rows whose location record fuzzily matches to lake dumbleyung . 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, 'location_7': 7, 'ullswater_8': 8, 'date_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'location_11': 11, 'lake dumbleyung_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', 'location_7': 'location', 'ullswater_8': 'ullswater', 'date_9': 'date', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'location_11': 'location', 'lake dumbleyung_12': 'lake dumbleyung', 'date_13': 'date'} | {'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'location_7': [0], 'ullswater_8': [0], 'date_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'location_11': [1], 'lake dumbleyung_12': [1], 'date_13': [3]} | ['speed', 'craft', 'pilot', 'location', 'date'] | [['-', 'bluebird k7', 'donald campbell', 'ullswater', '23 july 1955'], ['-', 'bluebird k7', 'donald campbell', 'lake mead', '16 november 1955'], ['-', 'bluebird k7', 'donald campbell', 'coniston water', '19 september 1956'], ['-', 'bluebird k7', 'donald campbell', 'coniston water', '7 november 1957'], ['-', 'bluebird k7', 'donald campbell', 'coniston water', '10 november 1958'], ['-', 'bluebird k7', 'donald campbell', 'coniston water', '14 may 1959'], ['-', 'bluebird k7', 'donald campbell', 'lake dumbleyung', '31 december 1964']] |
tampa bay rowdies ( 1975 - 1993 ) | https://en.wikipedia.org/wiki/Tampa_Bay_Rowdies_%281975%E2%80%931993%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1428018-1.html.csv | count | for the years that the tampa bay rowdies did not qualify for the playoffs , they finished 3rd in the southern division twice . | {'scope': 'subset', 'criterion': 'equal', 'value': '3rd , southern division', 'result': '2', 'col': '3', 'subset': {'col': '4', 'criterion': 'equal', 'value': 'did not qualify'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'playoffs', 'did not qualify'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; playoffs ; did not qualify }', 'tointer': 'select the rows whose playoffs record fuzzily matches to did not qualify .'}, 'regular season finish', '3rd , southern division'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose playoffs record fuzzily matches to did not qualify . among these rows , select the rows whose regular season finish record fuzzily matches to 3rd , southern division .', 'tostr': 'filter_eq { filter_eq { all_rows ; playoffs ; did not qualify } ; regular season finish ; 3rd , southern division }'}], 'result': '2', 'ind': 2, 'tostr': 'count { filter_eq { filter_eq { all_rows ; playoffs ; did not qualify } ; regular season finish ; 3rd , southern division } }', 'tointer': 'select the rows whose playoffs record fuzzily matches to did not qualify . among these rows , select the rows whose regular season finish record fuzzily matches to 3rd , southern division . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_eq { filter_eq { all_rows ; playoffs ; did not qualify } ; regular season finish ; 3rd , southern division } } ; 2 } = true', 'tointer': 'select the rows whose playoffs record fuzzily matches to did not qualify . among these rows , select the rows whose regular season finish record fuzzily matches to 3rd , southern division . the number of such rows is 2 .'} | eq { count { filter_eq { filter_eq { all_rows ; playoffs ; did not qualify } ; regular season finish ; 3rd , southern division } } ; 2 } = true | select the rows whose playoffs record fuzzily matches to did not qualify . among these rows , select the rows whose regular season finish record fuzzily matches to 3rd , southern division . the number of such rows is 2 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_str_eq_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'playoffs_6': 6, 'did not qualify_7': 7, 'regular season finish_8': 8, '3rd, southern division_9': 9, '2_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_str_eq_1': 'filter_str_eq', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'playoffs_6': 'playoffs', 'did not qualify_7': 'did not qualify', 'regular season finish_8': 'regular season finish', '3rd, southern division_9': '3rd , southern division', '2_10': '2'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_str_eq_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'playoffs_6': [0], 'did not qualify_7': [0], 'regular season finish_8': [1], '3rd, southern division_9': [1], '2_10': [3]} | ['year', 'record', 'regular season finish', 'playoffs', 'avg attend'] | [['1975', '16 - 6', '1st , eastern division', 'nasl champions', '10728'], ['1976', '18 - 6', '1st , eastern division , atlantic conference', 'atlantic conference championship', '16452'], ['1977', '14 - 12', '3rd , eastern division , atlantic conference', 'divisional playoffs', '19491'], ['1978', '18 - 12', '1st , eastern division , american conference', 'runners - up', '18123'], ['1979', '19 - 11', '1st , eastern division , american conference', 'runners - up', '27650'], ['1980', '19 - 13', '1st , eastern division , american conference', 'american conference semifinals', '28345'], ['1981', '15 - 17', '4th , southern division', 'quarterfinals', '22299'], ['1982', '12 - 20', '3rd , southern division', 'did not qualify', '22532'], ['1983', '7 - 23', '3rd , southern division', 'did not qualify', '18507'], ['1984', '9 - 15', '4th , eastern division', 'did not qualify', '10932']] |
2009 - 10 cleveland cavaliers season | https://en.wikipedia.org/wiki/2009%E2%80%9310_Cleveland_Cavaliers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-22654073-13.html.csv | aggregation | the first five games of the 2009-2010 cavalier 's conference semi-finals had a total attendance of 98,934 people . | {'scope': 'all', 'col': '8', 'type': 'sum', 'result': '98934', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'location attendance'], 'result': '98934', 'ind': 0, 'tostr': 'sum { all_rows ; location attendance }'}, '98934'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; location attendance } ; 98934 } = true', 'tointer': 'the sum of the location attendance record of all rows is 98934 .'} | round_eq { sum { all_rows ; location attendance } ; 98934 } = true | the sum of the location attendance record of all rows is 98934 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'location attendance_4': 4, '98934_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'location attendance_4': 'location attendance', '98934_5': '98934'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'location attendance_4': [0], '98934_5': [1]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'series'] | [['1', 'may 1', 'boston', 'w 101 - 93 ( ot )', 'lebron james ( 35 )', 'antawn jamison ( 9 )', 'lebron james ( 7 )', 'quicken loans arena 20562', '1 - 0'], ['2', 'may 3', 'boston', 'l 86 - 104 ( ot )', 'lebron james ( 24 )', 'lebron james ( 11 ) anderson varejão ( 11 )', 'mo williams ( 7 )', 'quicken loans arena 20562', '1 - 1'], ['3', 'may 7', 'boston', 'w 124 - 95 ( ot )', 'lebron james ( 38 )', 'antawn jamison ( 12 )', 'lebron james ( 7 ) mo williams ( 7 )', 'td garden 18624', '2 - 1'], ['4', 'may 9', 'boston', 'l 87 - 97 ( ot )', 'lebron james ( 22 )', 'lebron james ( 9 )', 'lebron james ( 8 )', 'td garden 18624', '2 - 2'], ['5', 'may 11', 'boston', 'l 88 - 120 ( ot )', "shaquille o'neal ( 21 )", 'anderson varejão ( 8 )', 'lebron james ( 7 )', 'quicken loans arena 20562', '2 - 3']] |
2007 - 08 anaheim ducks season | https://en.wikipedia.org/wiki/2007%E2%80%9308_Anaheim_Ducks_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11801795-8.html.csv | count | the jobingcom arena was used 2 times for matches against the coyotes during 2007 - 08 anaheim ducks season . | {'scope': 'all', 'criterion': 'equal', 'value': 'jobingcom arena', 'result': '2', 'col': '7', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'arena', 'jobingcom arena'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose arena record fuzzily matches to jobingcom arena .', 'tostr': 'filter_eq { all_rows ; arena ; jobingcom arena }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; arena ; jobingcom arena } }', 'tointer': 'select the rows whose arena record fuzzily matches to jobingcom arena . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; arena ; jobingcom arena } } ; 2 } = true', 'tointer': 'select the rows whose arena record fuzzily matches to jobingcom arena . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; arena ; jobingcom arena } } ; 2 } = true | select the rows whose arena record fuzzily matches to jobingcom arena . 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, 'arena_5': 5, 'jobingcom arena_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', 'arena_5': 'arena', 'jobingcom arena_6': 'jobingcom arena', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'arena_5': [0], 'jobingcom arena_6': [0], '2_7': [2]} | ['date', 'opponent', 'score', 'loss', 'attendance', 'record', 'arena', 'points'] | [['march 3', 'senators', '3 - 1', 'gerber ( 24 - 12 - 2 )', '17174', '38 - 23 - 7', 'honda center', '83'], ['march 5', 'blackhawks', '3 - 0', 'giguere ( 31 - 17 - 5 )', '16666', '38 - 24 - 7', 'united center', '83'], ['march 6', 'avalanche', '1 - 0', 'hiller ( 5 - 5 - 1 )', '18007', '38 - 25 - 7', 'pepsi center', '83'], ['march 9', 'canadiens', '3 - 1', 'price ( 16 - 11 - 3 )', '17174', '39 - 25 - 7', 'honda center', '85'], ['march 11', 'coyotes', '3 - 2', 'giguere ( 32 - 17 - 6 )', '14683', '39 - 25 - 8', 'jobingcom arena', '86'], ['march 12', 'canucks', '4 - 1', 'luongo ( 31 - 21 - 9 )', '17174', '40 - 25 - 8', 'honda center', '88'], ['march 15', 'blues', '5 - 2', 'legace ( 24 - 23 - 8 )', '17174', '41 - 25 - 8', 'honda center', '90'], ['march 19', 'stars', '2 - 1', 'turco ( 30 - 19 - 4 )', '18584', '42 - 25 - 8', 'american airlines center', '92'], ['march 21', 'sharks', '2 - 1', 'hiller ( 6 - 6 - 1 )', '17496', '42 - 26 - 8', 'hp pavilion at san jose', '92'], ['march 22', 'coyotes', '2 - 1', 'bryzgalov ( 25 - 20 - 4 )', '17645', '43 - 26 - 8', 'jobingcom arena', '94'], ['march 26', 'kings', '2 - 1', 'ersberg ( 4 - 3 - 3 )', '17331', '44 - 26 - 8', 'honda center', '96'], ['march 28', 'sharks', '3 - 1', 'hiller ( 8 - 7 - 1 )', '17334', '44 - 27 - 8', 'honda center', '96'], ['march 30', 'stars', '3 - 2', 'turco ( 31 - 20 - 6 )', '17174', '45 - 27 - 8', 'honda center', '98']] |
2008 - 09 belgian first division | https://en.wikipedia.org/wiki/2008%E2%80%9309_Belgian_First_Division | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17260623-1.html.csv | superlative | standard liège is the club with the highest capacity stadium in the belgian first division . | {'scope': 'all', 'col_superlative': '6', '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', 'capacity'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; capacity }'}, 'club'], 'result': 'standard liège', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; capacity } ; club }'}, 'standard liège'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; capacity } ; club } ; standard liège } = true', 'tointer': 'select the row whose capacity record of all rows is maximum . the club record of this row is standard liège .'} | eq { hop { argmax { all_rows ; capacity } ; club } ; standard liège } = true | select the row whose capacity record of all rows is maximum . the club record of this row is standard liège . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'capacity_5': 5, 'club_6': 6, 'standard liège_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'capacity_5': 'capacity', 'club_6': 'club', 'standard liège_7': 'standard liège'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'capacity_5': [0], 'club_6': [1], 'standard liège_7': [2]} | ['club', 'location', 'current manager', 'team captain', 'stadium', 'capacity'] | [['standard liège', 'liège', 'lászló bölöni', 'steven defour', 'stade maurice dufrasne', '30000'], ['rsc anderlecht', 'anderlecht', 'ariel jacobs', 'olivier deschacht', 'constant vanden stock stadium', '28063'], ['club brugge kv', 'bruges', 'jacky mathijssen', 'philippe clement', 'jan breydel stadium', '29415'], ['cercle brugge ksv', 'bruges', 'glen de boeck', 'denis viane', 'jan breydel stadium', '29415'], ['kfc germinal beerschot', 'antwerp', 'aimé anthuenis', 'daniel cruz', 'olympisch stadion', '12148'], ['kaa gent', 'ghent', "michel preud ' homme", 'bryan ruiz', 'jules ottenstadion', '12919'], ['sv zulte waregem', 'waregem', 'francky dury', 'ludwin van nieuwenhuyze', 'regenboogstadion', '8500'], ['r charleroi sc', 'charleroi', 'john collins', 'frank defays', 'stade du pays de charleroi', '25000'], ['kvc westerlo', 'westerlo', 'jan ceulemans', 'jef delen', 'het kuipje', '8200'], ['krc genk', 'genk', 'pierre denier and hans visser ( caretakers )', 'hans cornelis', 'cristal arena', '24900'], ['re mouscron', 'mouscron', 'enzo scifo', 'gonzague van dooren', 'stade le canonnier', '11500'], ['ksc lokeren oost - vlaanderen', 'lokeren', 'aleksandar janković', 'olivier doll', 'daknamstadion', '10000'], ['kv mechelen', 'mechelen', 'peter maes', 'jonas ivens', 'veolia - stadion', '14145'], ['ksv roeselare', 'roeselare', 'dennis van wijk', 'stefaan tanghe', 'schiervelde stadion', '9036'], ['fc verbroedering dender eh', 'denderleeuw', 'johan boskamp', 'steven de petter', 'florent beeckmanstadion', '6800'], ['raec mons', 'mons', 'christophe dessy ( caretaker )', 'roberto mirri', 'stade charles tondreau', '9504'], ['kv kortrijk', 'kortrijk', 'hein vanhaezebrouck', 'stéphane demets', 'guldensporen stadion', '8770'], ['afc tubize', 'tubize', 'albert cartier', 'gregory neels', 'stade leburton', '4000']] |
list of australian rugby league grand final records | https://en.wikipedia.org/wiki/List_of_Australian_rugby_league_grand_final_records | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16633950-2.html.csv | comparative | the eastern suburbs have a higher points record in the australian rugby league grand final than the canberra raiders . | {'row_1': '3', 'row_2': '5', 'col': '1', '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', 'premiers', 'eastern suburbs'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose premiers record fuzzily matches to eastern suburbs .', 'tostr': 'filter_eq { all_rows ; premiers ; eastern suburbs }'}, 'points'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; premiers ; eastern suburbs } ; points }', 'tointer': 'select the rows whose premiers record fuzzily matches to eastern suburbs . take the points record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'premiers', 'canberra raiders'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose premiers record fuzzily matches to canberra raiders .', 'tostr': 'filter_eq { all_rows ; premiers ; canberra raiders }'}, 'points'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; premiers ; canberra raiders } ; points }', 'tointer': 'select the rows whose premiers record fuzzily matches to canberra raiders . take the points record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; premiers ; eastern suburbs } ; points } ; hop { filter_eq { all_rows ; premiers ; canberra raiders } ; points } } = true', 'tointer': 'select the rows whose premiers record fuzzily matches to eastern suburbs . take the points record of this row . select the rows whose premiers record fuzzily matches to canberra raiders . take the points record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; premiers ; eastern suburbs } ; points } ; hop { filter_eq { all_rows ; premiers ; canberra raiders } ; points } } = true | select the rows whose premiers record fuzzily matches to eastern suburbs . take the points record of this row . select the rows whose premiers record fuzzily matches to canberra raiders . take the points record of this row . the first record is greater than the second record . | 5 | 5 | {'greater_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'premiers_7': 7, 'eastern suburbs_8': 8, 'points_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'premiers_11': 11, 'canberra raiders_12': 12, 'points_13': 13} | {'greater_4': 'greater', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'premiers_7': 'premiers', 'eastern suburbs_8': 'eastern suburbs', 'points_9': 'points', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'premiers_11': 'premiers', 'canberra raiders_12': 'canberra raiders', 'points_13': 'points'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'premiers_7': [0], 'eastern suburbs_8': [0], 'points_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'premiers_11': [1], 'canberra raiders_12': [1], 'points_13': [3]} | ['points', 'score', 'premiers', 'runners up', 'details'] | [['42', '42 - 14', 'south sydney rabbitohs', 'manly - warringah sea eagles', '1951 nswrfl grand final'], ['40', '40 - 0', 'manly - warringah sea eagles', 'melbourne storm', '2008 nrl grand final'], ['38', '38 - 0', 'eastern suburbs', 'st george dragons', '1975 nswrfl grand final'], ['38', '38 - 12', 'brisbane broncos', 'canterbury - bankstown bulldogs', '1998 nrl grand final'], ['36', '36 - 12', 'canberra raiders', 'canterbury - bankstown bulldogs', '1994 nswrl grand final']] |
volkswagen amarok | https://en.wikipedia.org/wiki/Volkswagen_Amarok | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14410430-1.html.csv | aggregation | the volkswagen amarok models of the year 2010 has an average power of 3875 rpm . | {'scope': 'subset', 'col': '5', 'type': 'average', 'result': '3875', 'subset': {'col': '2', 'criterion': 'equal', 'value': '2010'}} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'years', '2010'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; years ; 2010 }', 'tointer': 'select the rows whose years record is equal to 2010 .'}, 'power'], 'result': '3875', 'ind': 1, 'tostr': 'avg { filter_eq { all_rows ; years ; 2010 } ; power }'}, '3875'], 'result': True, 'ind': 2, 'tostr': 'round_eq { avg { filter_eq { all_rows ; years ; 2010 } ; power } ; 3875 } = true', 'tointer': 'select the rows whose years record is equal to 2010 . the average of the power record of these rows is 3875 .'} | round_eq { avg { filter_eq { all_rows ; years ; 2010 } ; power } ; 3875 } = true | select the rows whose years record is equal to 2010 . the average of the power record of these rows is 3875 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'avg_1': 1, 'filter_eq_0': 0, 'all_rows_4': 4, 'years_5': 5, '2010_6': 6, 'power_7': 7, '3875_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'avg_1': 'avg', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'years_5': 'years', '2010_6': '2010', 'power_7': 'power', '3875_8': '3875'} | {'eq_2': [3], 'result_3': [], 'avg_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'years_5': [0], '2010_6': [0], 'power_7': [1], '3875_8': [2]} | ['model', 'years', 'engine', 'displ', 'power', 'torque'] | [['2.0 tsi', '2011 -', 'i4 16v', 'cc ( cuin )', '3800 - 5500 rpm', '1600 - 3750 rpm'], ['2.0 tdi ( cr ) dpf', '2010 - 2011', 'i4 16v', 'cc ( cuin )', '3750 rpm', '1750 - 2250 rpm'], ['2.0 tdi ( cr ) dpf', '2012 -', 'i4 16v', 'cc ( cuin )', '3750 rpm', '1750 - 2250 rpm'], ['2.0 bitdi ( cr ) dpf', '2010 -', 'i4 16v', 'cc ( cuin )', '4000 rpm', '1500 - 2000 rpm'], ['2.0 bitdi ( cr ) dpf', '2012 -', 'i4 16v', 'cc ( cuin )', 'n / a', 'n / a']] |
united states house of representatives elections , 2006 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_2006 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1805191-15.html.csv | unique | chris chocola was the only us house of representatives incumbent who was first elected in 2002 . | {'scope': 'all', 'row': '2', 'col': '4', 'col_other': '2', 'criterion': 'equal', 'value': '2002', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'first elected', '2002'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose first elected record is equal to 2002 .', 'tostr': 'filter_eq { all_rows ; first elected ; 2002 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; first elected ; 2002 } }', 'tointer': 'select the rows whose first elected record is equal to 2002 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'first elected', '2002'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose first elected record is equal to 2002 .', 'tostr': 'filter_eq { all_rows ; first elected ; 2002 }'}, 'incumbent'], 'result': 'chris chocola', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; first elected ; 2002 } ; incumbent }'}, 'chris chocola'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; first elected ; 2002 } ; incumbent } ; chris chocola }', 'tointer': 'the incumbent record of this unqiue row is chris chocola .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; first elected ; 2002 } } ; eq { hop { filter_eq { all_rows ; first elected ; 2002 } ; incumbent } ; chris chocola } } = true', 'tointer': 'select the rows whose first elected record is equal to 2002 . there is only one such row in the table . the incumbent record of this unqiue row is chris chocola .'} | and { only { filter_eq { all_rows ; first elected ; 2002 } } ; eq { hop { filter_eq { all_rows ; first elected ; 2002 } ; incumbent } ; chris chocola } } = true | select the rows whose first elected record is equal to 2002 . there is only one such row in the table . the incumbent record of this unqiue row is chris chocola . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'first elected_7': 7, '2002_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'incumbent_9': 9, 'chris chocola_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'first elected_7': 'first elected', '2002_8': '2002', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'incumbent_9': 'incumbent', 'chris chocola_10': 'chris chocola'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'first elected_7': [0], '2002_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'incumbent_9': [2], 'chris chocola_10': [3]} | ['district', 'incumbent', 'party', 'first elected', 'results'] | [['indiana 1', 'pete visclosky', 'democratic', '1984', 're - elected'], ['indiana 2', 'chris chocola', 'republican', '2002', 'lost re - election democratic gain'], ['indiana 3', 'mark souder', 'republican', '1994', 're - elected'], ['indiana 4', 'steve buyer', 'republican', '1992', 're - elected'], ['indiana 5', 'dan burton', 'republican', '1982', 're - elected'], ['indiana 6', 'mike pence', 'republican', '2000', 're - elected'], ['indiana 7', 'julia carson', 'democratic', '1996', 're - elected'], ['indiana 8', 'john hostettler', 'republican', '1994', 'lost re - election democratic gain'], ['indiana 9', 'mike sodrel', 'republican', '2004', 'lost re - election democratic gain']] |
2007 - 08 dallas mavericks season | https://en.wikipedia.org/wiki/2007%E2%80%9308_Dallas_Mavericks_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11963209-7.html.csv | ordinal | the dallas mavericks ' game against the kings recorded their 2nd highest attendance of the 2007 - 08 season . | {'row': '14', 'col': '6', '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', 'attendance', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; attendance ; 2 }'}, 'visitor'], 'result': 'kings', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; attendance ; 2 } ; visitor }'}, 'kings'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; attendance ; 2 } ; visitor } ; kings } = true', 'tointer': 'select the row whose attendance record of all rows is 2nd maximum . the visitor record of this row is kings .'} | eq { hop { nth_argmax { all_rows ; attendance ; 2 } ; visitor } ; kings } = true | select the row whose attendance record of all rows is 2nd maximum . the visitor record of this row is kings . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'attendance_5': 5, '2_6': 6, 'visitor_7': 7, 'kings_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', '2_6': '2', 'visitor_7': 'visitor', 'kings_8': 'kings'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'attendance_5': [0], '2_6': [0], 'visitor_7': [1], 'kings_8': [2]} | ['date', 'visitor', 'score', 'home', 'leading scorer', 'attendance', 'record'] | [['3 february 2008', 'mavericks', '67 - 90', 'pistons', 'two - way tie ( 15 )', '22076', '31 - 15'], ['4 february 2008', 'mavericks', '107 - 98', 'magic', 'josh howard ( 28 )', '16974', '32 - 15'], ['6 february 2008', 'bucks', '96 - 107', 'mavericks', 'dirk nowitzki ( 29 )', '20079', '33 - 15'], ['8 february 2008', 'grizzlies', '81 - 92', 'mavericks', 'dirk nowitzki ( 21 )', '20315', '34 - 15'], ['10 february 2008', 'mavericks', '82 - 101', 'nets', 'dirk nowitzki ( 21 )', '16395', '34 - 16'], ['11 february 2008', 'mavericks', '76 - 84', 'sixers', 'josh howard ( 17 )', '11728', '34 - 17'], ['13 february 2008', 'trail blazers', '76 - 96', 'mavericks', 'dirk nowitzki ( 37 )', '20159', '35 - 17'], ['14 february 2008', 'mavericks', '97 - 109', 'suns', 'dirk nowitzki ( 36 )', '18422', '35 - 18'], ['20 february 2008', 'mavericks', '93 - 104', 'hornets', 'dirk nowitzki ( 31 )', '15941', '35 - 19'], ['22 february 2008', 'mavericks', '98 - 83', 'grizzlies', 'dirk nowitzki ( 27 )', '16245', '36 - 19'], ['24 february 2008', 'mavericks', '99 - 83', 'timberwolves', 'dirk nowitzki ( 29 )', '19429', '37 - 19'], ['25 february 2008', 'bulls', '94 - 102', 'mavericks', 'dirk nowitzki ( 29 )', '20340', '38 - 19'], ['28 february 2008', 'mavericks', '94 - 97', 'spurs', 'dirk nowitzki ( 28 )', '18797', '38 - 20'], ['29 february 2008', 'kings', '106 - 115', 'mavericks', 'dirk nowitzki ( 34 )', '20354', '39 - 20']] |
2008 in video gaming | https://en.wikipedia.org/wiki/2008_in_video_gaming | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10060114-4.html.csv | majority | nintendo was the publisher for most of the 2008 video game titles . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'nintendo', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'publisher', 'nintendo'], 'result': True, 'ind': 0, 'tointer': 'for the publisher records of all rows , most of them fuzzily match to nintendo .', 'tostr': 'most_eq { all_rows ; publisher ; nintendo } = true'} | most_eq { all_rows ; publisher ; nintendo } = true | for the publisher records of all rows , most of them fuzzily match to nintendo . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'publisher_3': 3, 'nintendo_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'publisher_3': 'publisher', 'nintendo_4': 'nintendo'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'publisher_3': [0], 'nintendo_4': [0]} | ['place', 'title', 'platform', 'publisher', 'units sold'] | [['1', 'monster hunter portable 2nd g', 'psp', 'capcom', '2452111'], ['2', 'pokémon platinum', 'nds', 'pokémon company', '2187337'], ['3', 'wii fit', 'wii', 'nintendo', '2149131'], ['4', 'mario kart wii', 'wii', 'nintendo', '2003315'], ['5', 'super smash bros brawl', 'wii', 'nintendo', '1747113'], ['6', 'rhythm heaven', 'nds', 'nintendo', '1350671'], ['7', 'dragon quest v : hand of the heavenly bride', 'nds', 'square enix', '1176082'], ['8', 'animal crossing : city folk', 'wii', 'nintendo', '895302'], ['9', 'kirby super star ultra', 'nds', 'nintendo', '855427'], ['10', 'wii sports', 'wii', 'nintendo', '841736']] |
1998 icc knockout trophy | https://en.wikipedia.org/wiki/1998_ICC_KnockOut_Trophy | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-11950720-8.html.csv | superlative | in the 1988 icc knockout trophy , the oldest player with right arm fast-medium bowling style was from guyana . | {'scope': 'subset', 'col_superlative': '3', 'row_superlative': '8', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '5,6', 'subset': {'col': '5', 'criterion': 'equal', 'value': 'right arm fast - medium'}} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'bowling style', 'right arm fast - medium'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; bowling style ; right arm fast - medium }', 'tointer': 'select the rows whose bowling style record fuzzily matches to right arm fast - medium .'}, 'date of birth'], 'result': None, 'ind': 1, 'tostr': 'argmax { filter_eq { all_rows ; bowling style ; right arm fast - medium } ; date of birth }'}, 'first class team'], 'result': 'guyana', 'ind': 2, 'tostr': 'hop { argmax { filter_eq { all_rows ; bowling style ; right arm fast - medium } ; date of birth } ; first class team }'}, 'guyana'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { argmax { filter_eq { all_rows ; bowling style ; right arm fast - medium } ; date of birth } ; first class team } ; guyana } = true', 'tointer': 'select the rows whose bowling style record fuzzily matches to right arm fast - medium . select the row whose date of birth record of these rows is maximum . the first class team record of this row is guyana .'} | eq { hop { argmax { filter_eq { all_rows ; bowling style ; right arm fast - medium } ; date of birth } ; first class team } ; guyana } = true | select the rows whose bowling style record fuzzily matches to right arm fast - medium . select the row whose date of birth record of these rows is maximum . the first class team record of this row is guyana . | 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, 'bowling style_6': 6, 'right arm fast - medium_7': 7, 'date of birth_8': 8, 'first class team_9': 9, 'guyana_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', 'bowling style_6': 'bowling style', 'right arm fast - medium_7': 'right arm fast - medium', 'date of birth_8': 'date of birth', 'first class team_9': 'first class team', 'guyana_10': 'guyana'} | {'str_eq_3': [4], 'result_4': [], 'str_hop_2': [3], 'argmax_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'bowling style_6': [0], 'right arm fast - medium_7': [0], 'date of birth_8': [1], 'first class team_9': [2], 'guyana_10': [3]} | ['no', 'player', 'date of birth', 'batting style', 'bowling style', 'first class team'] | [['59', 'brian lara ( captain )', '2 may 1969', 'left hand bat', 'right arm leg break googly', 'trinidad and tobago'], ['55', 'keith arthurton', '21 february 1965', 'left hand bat', 'left arm orthodox spin', 'leeward islands'], ['66', 'shivnarine chanderpaul', '16 august 1974', 'left hand bat', 'right arm leg break', 'guyana'], ['86', 'mervyn dillon', '5 june 1974', 'right hand bat', 'right arm fast - medium', 'trinidad and tobago'], ['50', 'carl hooper', '15 december 1966', 'right hand bat', 'right arm off break', 'guyana'], ['76', 'ridley jacobs ( wicket - keeper )', '26 november 1967', 'left hand bat', 'wicket - keeper', 'leeward islands'], ['89', 'reon king', '6 october 1975', 'right hand bat', 'right arm fast - medium', 'guyana'], ['58', 'clayton lambert', '10 february 1962', 'left hand bat', 'right arm off break', 'guyana'], ['85', 'rawl lewis', '5 september 1974', 'right hand bat', 'right arm leg break googly', 'windward islands'], ['78', 'nixon mclean', '20 july 1973', 'left hand bat', 'right arm fast', 'windward islands'], ['87', 'neil mcgarrell', '12 july 1972', 'right hand bat', 'left arm orthodox spin', 'guyana'], ['51', 'phil simmons', '18 april 1963', 'right hand bat', 'right arm medium', 'trinidad and tobago'], ['61', 'philo wallace', '2 august 1970', 'right hand bat', 'right arm medium', 'barbados'], ['68', 'stuart williams', '12 august 1969', 'right hand bat', 'right arm medium', 'leeward islands']] |
1967 new york giants season | https://en.wikipedia.org/wiki/1967_New_York_Giants_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16661087-1.html.csv | comparative | there were more people at the december 3rd game than at the december 17th game . | {'row_1': '12', 'row_2': '14', 'col': '5', 'col_other': '2', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', 'december 3 , 1967'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose date record fuzzily matches to december 3 , 1967 .', 'tostr': 'filter_eq { all_rows ; date ; december 3 , 1967 }'}, 'attendance'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; date ; december 3 , 1967 } ; attendance }', 'tointer': 'select the rows whose date record fuzzily matches to december 3 , 1967 . take the attendance record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', 'december 17 , 1967'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose date record fuzzily matches to december 17 , 1967 .', 'tostr': 'filter_eq { all_rows ; date ; december 17 , 1967 }'}, 'attendance'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; date ; december 17 , 1967 } ; attendance }', 'tointer': 'select the rows whose date record fuzzily matches to december 17 , 1967 . take the attendance record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; date ; december 3 , 1967 } ; attendance } ; hop { filter_eq { all_rows ; date ; december 17 , 1967 } ; attendance } } = true', 'tointer': 'select the rows whose date record fuzzily matches to december 3 , 1967 . take the attendance record of this row . select the rows whose date record fuzzily matches to december 17 , 1967 . take the attendance record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; date ; december 3 , 1967 } ; attendance } ; hop { filter_eq { all_rows ; date ; december 17 , 1967 } ; attendance } } = true | select the rows whose date record fuzzily matches to december 3 , 1967 . take the attendance record of this row . select the rows whose date record fuzzily matches to december 17 , 1967 . take the attendance 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, 'date_7': 7, 'december 3 , 1967_8': 8, 'attendance_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'date_11': 11, 'december 17 , 1967_12': 12, 'attendance_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', 'date_7': 'date', 'december 3 , 1967_8': 'december 3 , 1967', 'attendance_9': 'attendance', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'date_11': 'date', 'december 17 , 1967_12': 'december 17 , 1967', 'attendance_13': 'attendance'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'date_7': [0], 'december 3 , 1967_8': [0], 'attendance_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'date_11': [1], 'december 17 , 1967_12': [1], 'attendance_13': [3]} | ['week', 'date', 'opponent', 'result', 'attendance'] | [['1', 'september 17 , 1967', 'st louis cardinals', 'w 37 - 20', '40801'], ['2', 'september 24 , 1967', 'dallas cowboys', 'l 38 - 24', '66209'], ['3', 'october 1 , 1967', 'washington redskins', 'l 38 - 34', '50266'], ['4', 'october 8 , 1967', 'new orleans saints', 'w 27 - 21', '62670'], ['5', 'october 15 , 1967', 'pittsburgh steelers', 'w 27 - 24', '39782'], ['6', 'october 22 , 1967', 'green bay packers', 'l 48 - 21', '62585'], ['7', 'october 29 , 1967', 'cleveland browns', 'w 38 - 34', '62903'], ['8', 'november 5 , 1967', 'minnesota vikings', 'l 27 - 24', '44960'], ['9', 'november 12 , 1967', 'chicago bears', 'l 34 - 7', '46223'], ['10', 'november 19 , 1967', 'pittsburgh steelers', 'w 28 - 20', '62982'], ['11', 'november 26 , 1967', 'philadelphia eagles', 'w 44 - 7', '63027'], ['12', 'december 3 , 1967', 'cleveland browns', 'l 24 - 14', '78594'], ['13', 'december 10 , 1967', 'detroit lions', 'l 30 - 7', '63011'], ['14', 'december 17 , 1967', 'st louis cardinals', 'w 37 - 14', '62955']] |
catholic church by country | https://en.wikipedia.org/wiki/Catholic_Church_by_country | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1364343-4.html.csv | superlative | southeast asia has the most catholic members among regions in asia . | {'scope': 'all', 'col_superlative': '3', 'row_superlative': '4', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'catholic'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; catholic }'}, 'region'], 'result': 'southeast asia', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; catholic } ; region }'}, 'southeast asia'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; catholic } ; region } ; southeast asia } = true', 'tointer': 'select the row whose catholic record of all rows is maximum . the region record of this row is southeast asia .'} | eq { hop { argmax { all_rows ; catholic } ; region } ; southeast asia } = true | select the row whose catholic record of all rows is maximum . the region record of this row is southeast asia . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'catholic_5': 5, 'region_6': 6, 'southeast asia_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'catholic_5': 'catholic', 'region_6': 'region', 'southeast asia_7': 'southeast asia'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'catholic_5': [0], 'region_6': [1], 'southeast asia_7': [2]} | ['region', 'total population', 'catholic', '% catholic', '% of global catholic pop'] | [['central asia', '92019166', '199086', '1.23 %', '0.01 %'], ['east asia', '1528384440', '13853142', '0.90 %', '1.28 %'], ['south asia', '1437326682', '20107050', '1.39 %', '1.87 %'], ['southeast asia', '571337070', '86701421', '15.17 %', '8.06 %'], ['total', '3629067358', '120860699', '3.33 %', '11.24 %']] |
southwestern conference ( illinois ) | https://en.wikipedia.org/wiki/Southwestern_Conference_%28Illinois%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27653955-1.html.csv | count | white is one of the colors for 3 of the schools in the southwestern conference in illinois . | {'scope': 'all', 'criterion': 'equal', 'value': 'white', 'result': '3', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'colors', 'white'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose colors record fuzzily matches to white .', 'tostr': 'filter_eq { all_rows ; colors ; white }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; colors ; white } }', 'tointer': 'select the rows whose colors record fuzzily matches to white . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; colors ; white } } ; 3 } = true', 'tointer': 'select the rows whose colors record fuzzily matches to white . the number of such rows is 3 .'} | eq { count { filter_eq { all_rows ; colors ; white } } ; 3 } = true | select the rows whose colors record fuzzily matches to white . 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, 'colors_5': 5, 'white_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', 'colors_5': 'colors', 'white_6': 'white', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'colors_5': [0], 'white_6': [0], '3_7': [2]} | ['school', 'location', 'mascot', 'colors', 'enrollment', 'ihsa classes 2 / 3 / 4', 'ihsa music class', 'ihsa football class', 'ihsa cheerleading class'] | [['alton high school', 'alton , il', 'redbirds', 'red , gray', '2135', 'aa / 3a / 4a', 'aa', '7a', 'large squad'], ['belleville east high school', 'belleville , il', 'lancers', 'columbia blue , navy blue', '2600', 'aa / 3a / 4a', 'aa', '8a', 'large squad'], ['belleville west high school', 'belleville , il', 'maroons', 'maroon , white', '2434', 'aa / 3a / 4a', 'aa', '7a', 'large squad'], ['collinsville high school', 'collinsville , il', 'kahoks', 'purple , white', '2020', 'aa / 3a / 4a', 'aa', '7a', 'large squad'], ['east st louis senior high school', 'east st louis , il', 'flyers / flyerettes', 'orange , blue', '2146', 'aa / 3a / 4a', 'aa', '7a', 'large squad'], ['edwardsville high school', 'edwardsville , il', 'tigers', 'orange , black', '2514', 'aa / 3a / 4a', 'aa', '8a', 'large squad'], ['granite city high school', 'granite city , il', 'warriors', 'red , black , white', '2129', 'aa / 3a / 4a', 'aa', '7a', 'large squad']] |
2000 tennessee titans season | https://en.wikipedia.org/wiki/2000_Tennessee_Titans_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16025613-2.html.csv | majority | the tennessee titans won most of the games played in the 2000 nfl season . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': 'w', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'result', 'w'], 'result': True, 'ind': 0, 'tointer': 'for the result records of all rows , most of them fuzzily match to w .', 'tostr': 'most_eq { all_rows ; result ; w } = true'} | most_eq { all_rows ; result ; w } = true | for the result records of all rows , most of them fuzzily match to w . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'result_3': 3, 'w_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'result_3': 'result', 'w_4': 'w'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'result_3': [0], 'w_4': [0]} | ['week', 'date', 'tv time', 'opponent', 'result'] | [['1', 'september 3 , 2000', 'espn 7:30 pm cdt', 'buffalo bills', 'l 13 - 16'], ['2', 'september 10 , 2000', 'cbs 12:00 pm cdt', 'kansas city chiefs', 'w 17 - 14'], ['3', '-', '-', '-', 'none'], ['4', 'september 24 , 2000', 'cbs 12:00 pm cdt', 'pittsburgh steelers', 'w 23 - 20'], ['5', 'october 1 , 2000', 'fox 12:00 pm cdt', 'new york giants', 'w 28 - 14'], ['6', 'october 8 , 2000', 'cbs 12:00 pm cdt', 'cincinnati bengals', 'w 23 - 14'], ['7', 'october 16 , 2000', 'abc 8:00 pm cdt', 'jacksonville jaguars', 'w 27 - 13'], ['8', 'october 22 , 2000', 'cbs 12:00 pm cdt', 'baltimore ravens', 'w 14 - 6'], ['9', 'october 30 , 2000', 'abc 8:00 pm cdt', 'washington redskins', 'w 27 - 21'], ['10', 'november 5 , 2000', 'cbs 12:00 pm cdt', 'pittsburgh steelers', 'w 9 - 7'], ['11', 'november 12 , 2000', 'cbs 12:00 pm cdt', 'baltimore ravens', 'l 23 - 24'], ['12', 'november 19 , 2000', 'cbs 12:00 pm cdt', 'cleveland browns', 'w 24 - 10'], ['13', 'november 26 , 2000', 'cbs 3:15 pm cdt', 'jacksonville jaguars', 'l 13 - 16'], ['14', 'december 3 , 2000', 'cbs 12:00 pm cdt', 'philadelphia eagles', 'w 15 - 13'], ['15', 'december 10 , 2000', 'cbs 12:00 pm cdt', 'cincinnati bengals', 'w 35 - 3'], ['16', 'december 17 , 2000', 'cbs 12:00 pm cdt', 'cleveland browns', 'w 24 - 0'], ['17', 'december 25 , 2000', 'abc 8:00 pm cdt', 'dallas cowboys', 'w 31 - 0']] |
colts - patriots rivalry | https://en.wikipedia.org/wiki/Colts%E2%80%93Patriots_rivalry | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13342861-6.html.csv | unique | in the colts - patriots rivalry , the only time the score was 35-34 , was on november 15th . | {'scope': 'all', 'row': '14', 'col': '4', 'col_other': '2', 'criterion': 'equal', 'value': '35-34', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'result', '35-34'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose result record fuzzily matches to 35-34 .', 'tostr': 'filter_eq { all_rows ; result ; 35-34 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; result ; 35-34 } }', 'tointer': 'select the rows whose result record fuzzily matches to 35-34 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'result', '35-34'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose result record fuzzily matches to 35-34 .', 'tostr': 'filter_eq { all_rows ; result ; 35-34 }'}, 'date'], 'result': 'november 15', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; result ; 35-34 } ; date }'}, 'november 15'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; result ; 35-34 } ; date } ; november 15 }', 'tointer': 'the date record of this unqiue row is november 15 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; result ; 35-34 } } ; eq { hop { filter_eq { all_rows ; result ; 35-34 } ; date } ; november 15 } } = true', 'tointer': 'select the rows whose result record fuzzily matches to 35-34 . there is only one such row in the table . the date record of this unqiue row is november 15 .'} | and { only { filter_eq { all_rows ; result ; 35-34 } } ; eq { hop { filter_eq { all_rows ; result ; 35-34 } ; date } ; november 15 } } = true | select the rows whose result record fuzzily matches to 35-34 . there is only one such row in the table . the date record of this unqiue row is november 15 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'result_7': 7, '35-34_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'date_9': 9, 'november 15_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'result_7': 'result', '35-34_8': '35-34', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'date_9': 'date', 'november 15_10': 'november 15'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'result_7': [0], '35-34_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'date_9': [2], 'november 15_10': [3]} | ['year', 'date', 'winner', 'result', 'loser', 'location'] | [['2000', 'october 8', 'new england patriots', '24 - 16', 'indianapolis colts', 'foxboro stadium'], ['2000', 'october 22', 'indianapolis colts', '30 - 23', 'new england patriots', 'rca dome'], ['2001', 'september 30', 'new england patriots', '44 - 13', 'indianapolis colts', 'foxboro stadium'], ['2001', 'october 21', 'new england patriots', '38 - 17', 'indianapolis colts', 'rca dome'], ['2003', 'november 30', 'new england patriots', '38 - 34', 'indianapolis colts', 'rca dome'], ['2004', 'january 18', 'new england patriots', '24 - 14', 'indianapolis colts', 'gillette stadium'], ['2004', 'september 9', 'new england patriots', '27 - 24', 'indianapolis colts', 'gillette stadium'], ['2005', 'january 16', 'new england patriots', '20 - 3', 'indianapolis colts', 'gillette stadium'], ['2005', 'november 7', 'indianapolis colts', '40 - 21', 'new england patriots', 'gillette stadium'], ['2006', 'november 5', 'indianapolis colts', '27 - 20', 'new england patriots', 'gillette stadium'], ['2007', 'january 21', 'indianapolis colts', '38 - 34', 'new england patriots', 'rca dome'], ['2007', 'november 4', 'new england patriots', '24 - 20', 'indianapolis colts', 'rca dome'], ['2008', 'november 2', 'indianapolis colts', '18 - 15', 'new england patriots', 'lucas oil stadium'], ['2009', 'november 15', 'indianapolis colts', '35 - 34', 'new england patriots', 'lucas oil stadium']] |
1971 - 72 new york rangers season | https://en.wikipedia.org/wiki/1971%E2%80%9372_New_York_Rangers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17323283-6.html.csv | count | the rangers played the st louis blues two times in february in their 1971-72 season . | {'scope': 'all', 'criterion': 'equal', 'value': 'st louis blues', 'result': '2', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', 'st louis blues'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose opponent record fuzzily matches to st louis blues .', 'tostr': 'filter_eq { all_rows ; opponent ; st louis blues }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; opponent ; st louis blues } }', 'tointer': 'select the rows whose opponent record fuzzily matches to st louis blues . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; opponent ; st louis blues } } ; 2 } = true', 'tointer': 'select the rows whose opponent record fuzzily matches to st louis blues . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; opponent ; st louis blues } } ; 2 } = true | select the rows whose opponent record fuzzily matches to st louis blues . the number of such rows is 2 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'opponent_5': 5, 'st louis blues_6': 6, '2_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'opponent_5': 'opponent', 'st louis blues_6': 'st louis blues', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'opponent_5': [0], 'st louis blues_6': [0], '2_7': [2]} | ['game', 'february', 'opponent', 'score', 'record'] | [['49', '2', 'boston bruins', '2 - 0', '31 - 10 - 8'], ['50', '3', 'buffalo sabres', '4 - 2', '32 - 10 - 8'], ['51', '5', 'st louis blues', '6 - 5', '32 - 11 - 8'], ['52', '6', 'toronto maple leafs', '2 - 2', '32 - 11 - 9'], ['53', '9', 'chicago black hawks', '4 - 1', '33 - 11 - 9'], ['54', '12', 'pittsburgh penguins', '8 - 3', '34 - 11 - 9'], ['55', '13', 'los angeles kings', '4 - 2', '35 - 11 - 9'], ['56', '15', 'vancouver canucks', '5 - 1', '36 - 11 - 9'], ['57', '17', 'los angeles kings', '6 - 4', '37 - 11 - 9'], ['58', '18', 'california golden seals', '2 - 2', '37 - 11 - 10'], ['59', '20', 'detroit red wings', '4 - 3', '38 - 11 - 10'], ['60', '22', 'montreal canadiens', '7 - 3', '39 - 11 - 10'], ['61', '23', 'philadelphia flyers', '4 - 3', '40 - 11 - 10'], ['62', '27', 'st louis blues', '2 - 0', '41 - 11 - 10']] |
united states house of representatives elections , 1996 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1996 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1341472-45.html.csv | majority | most of the incumbent representatives from 1996 united states house of representatives elections belonged to the republican party . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'republican', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'party', 'republican'], 'result': True, 'ind': 0, 'tointer': 'for the party records of all rows , most of them fuzzily match to republican .', 'tostr': 'most_eq { all_rows ; party ; republican } = true'} | most_eq { all_rows ; party ; republican } = true | for the party records of all rows , most of them fuzzily match to republican . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'party_3': 3, 'republican_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'party_3': 'party', 'republican_4': 'republican'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'party_3': [0], 'republican_4': [0]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['texas 5', 'john bryant', 'democratic', '1982', 'retired to run for us senate republican gain', 'pete sessions ( r ) 53.07 % john pouland ( d ) 46.93 %'], ['texas 8', 'jack fields', 'republican', '1980', 'retired republican hold', 'kevin brady ( r ) 59.11 % gene fontenot ( d ) 40.89 %'], ['texas 9', 'steve stockman', 'republican', '1994', 'lost re - election democratic gain', 'nick lampson ( d ) 52.83 % steve stockman ( r ) 47.16 %'], ['texas 19', 'larry combest', 'republican', '1984', 're - elected', 'larry combest ( r ) 80.37 % john sawyer ( d ) 19.63 %'], ['texas 22', 'tom delay', 'republican', '1984', 're - elected', 'tom delay ( r ) 68.11 % scott cunningham ( d ) 31.89 %']] |
1964 vfl season | https://en.wikipedia.org/wiki/1964_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10784349-4.html.csv | majority | in the 1964 vfl season , when the away team 's score was under 10 , all of the crowds were over 17000 . | {'scope': 'subset', 'col': '6', 'most_or_all': 'all', 'criterion': 'greater_than', 'value': '17000', 'subset': {'col': '4', 'criterion': 'less_than', 'value': '10'}} | {'func': 'all_greater', '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', '17000'], 'result': True, 'ind': 1, 'tointer': 'select the rows whose away team score record is less than 10 . for the crowd records of these rows , all of them are greater than 17000 .', 'tostr': 'all_greater { filter_less { all_rows ; away team score ; 10 } ; crowd ; 17000 } = true'} | all_greater { filter_less { all_rows ; away team score ; 10 } ; crowd ; 17000 } = true | select the rows whose away team score record is less than 10 . for the crowd records of these rows , all of them are greater than 17000 . | 2 | 2 | {'all_greater_1': 1, 'result_2': 2, 'filter_less_0': 0, 'all_rows_3': 3, 'away team score_4': 4, '10_5': 5, 'crowd_6': 6, '17000_7': 7} | {'all_greater_1': 'all_greater', 'result_2': 'true', 'filter_less_0': 'filter_less', 'all_rows_3': 'all_rows', 'away team score_4': 'away team score', '10_5': '10', 'crowd_6': 'crowd', '17000_7': '17000'} | {'all_greater_1': [2], 'result_2': [], 'filter_less_0': [1], 'all_rows_3': [0], 'away team score_4': [0], '10_5': [0], 'crowd_6': [1], '17000_7': [1]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['collingwood', '12.13 ( 85 )', 'south melbourne', '8.9 ( 57 )', 'victoria park', '29237', '9 may 1964'], ['carlton', '12.8 ( 80 )', 'footscray', '16.15 ( 111 )', 'princes park', '21663', '9 may 1964'], ['st kilda', '13.15 ( 93 )', 'melbourne', '9.13 ( 67 )', 'junction oval', '35300', '9 may 1964'], ['north melbourne', '14.15 ( 99 )', 'hawthorn', '9.14 ( 68 )', 'arden street oval', '17431', '9 may 1964'], ['richmond', '14.20 ( 104 )', 'fitzroy', '5.10 ( 40 )', 'punt road oval', '17200', '9 may 1964'], ['geelong', '8.21 ( 69 )', 'essendon', '14.7 ( 91 )', 'kardinia park', '34083', '9 may 1964']] |
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