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aguaclara | https://en.wikipedia.org/wiki/AguaClara | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18268930-1.html.csv | aggregation | the average population served by locations in aguaclara is 4038 . | {'scope': 'all', 'col': '5', 'type': 'average', 'result': '4038', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'population served'], 'result': '4038', 'ind': 0, 'tostr': 'avg { all_rows ; population served }'}, '4038'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; population served } ; 4038 } = true', 'tointer': 'the average of the population served record of all rows is 4038 .'} | round_eq { avg { all_rows ; population served } ; 4038 } = true | the average of the population served record of all rows is 4038 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'population served_4': 4, '4038_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'population served_4': 'population served', '4038_5': '4038'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'population served_4': [0], '4038_5': [1]} | ['location', 'partner', 'construction start', 'inauguration date', 'population served', 'design flow ( lpm )'] | [['ojojona , hon', 'app', '2006 june', '2007 july', '2000', '375'], ['tamara , hon', 'app', '2008 january', '2008 june', '3500', '720'], ['marcala , hon', 'irwa', '2007 october', '2008 july', '9000', '1900'], ['4 comunidades , hon', 'app', '2008 october', '2009 march', '2000', '375'], ['agalteca , hon', 'app', '2009 october', '2010 june', '2200', '375'], ['marcala , hon expansion', 'app / acra', '2010 november', '2011 may', '6000', '1300'], ['alauca , el paraiso , hon', 'app', '2011 may', '2012 february', '3600', '720'], ['atima , santa barbara , hon', 'app', '2011 december', '2012 may', '4000', '960']] |
1961 vfl season | https://en.wikipedia.org/wiki/1961_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10776330-15.html.csv | majority | most of the away vfl teams scored under 70 points on august 5 . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'less_than', 'value': '70', 'subset': None} | {'func': 'most_less', 'args': ['all_rows', 'away team score', '70'], 'result': True, 'ind': 0, 'tointer': 'for the away team score records of all rows , most of them are less than 70 .', 'tostr': 'most_less { all_rows ; away team score ; 70 } = true'} | most_less { all_rows ; away team score ; 70 } = true | for the away team score records of all rows , most of them are less than 70 . | 1 | 1 | {'most_less_0': 0, 'result_1': 1, 'all_rows_2': 2, 'away team score_3': 3, '70_4': 4} | {'most_less_0': 'most_less', 'result_1': 'true', 'all_rows_2': 'all_rows', 'away team score_3': 'away team score', '70_4': '70'} | {'most_less_0': [1], 'result_1': [], 'all_rows_2': [0], 'away team score_3': [0], '70_4': [0]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['hawthorn', '15.10 ( 100 )', 'north melbourne', '6.11 ( 47 )', 'glenferrie oval', '14000', '5 august 1961'], ['essendon', '13.16 ( 94 )', 'geelong', '7.14 ( 56 )', 'windy hill', '27500', '5 august 1961'], ['collingwood', '5.10 ( 40 )', 'footscray', '11.12 ( 78 )', 'victoria park', '22324', '5 august 1961'], ['carlton', '17.9 ( 111 )', 'south melbourne', '7.10 ( 52 )', 'princes park', '16889', '5 august 1961'], ['st kilda', '9.12 ( 66 )', 'melbourne', '7.13 ( 55 )', 'junction oval', '33100', '5 august 1961'], ['richmond', '9.9 ( 63 )', 'fitzroy', '9.14 ( 68 )', 'punt road oval', '15547', '5 august 1961']] |
minnesota golden gophers football under fritz crisler | https://en.wikipedia.org/wiki/Minnesota_Golden_Gophers_football_under_Fritz_Crisler | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14725662-2.html.csv | superlative | the game against stanford had the highest attendance of any of these golden gophers games . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '4', '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', 'attendance'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; attendance }'}, 'opponent'], 'result': 'stanford', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; attendance } ; opponent }'}, 'stanford'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; attendance } ; opponent } ; stanford } = true', 'tointer': 'select the row whose attendance record of all rows is maximum . the opponent record of this row is stanford .'} | eq { hop { argmax { all_rows ; attendance } ; opponent } ; stanford } = true | select the row whose attendance record of all rows is maximum . the opponent record of this row is stanford . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'attendance_5': 5, 'opponent_6': 6, 'stanford_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', 'opponent_6': 'opponent', 'stanford_7': 'stanford'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'attendance_5': [0], 'opponent_6': [1], 'stanford_7': [2]} | ['date', 'opponent', 'site', 'result', 'attendance'] | [['09 / 26 / 1931', 'north dakota state', 'memorial stadium minneapolis , mn', 'w13 - 7', '15000'], ['09 / 26 / 1931', 'ripon', 'memorial stadium minneapolis , mn', 'w30 - 0', '15000'], ['10 / 03 / 1931', 'oklahoma a & m', 'memorial stadium minneapolis , mn', 'w20 - 0', '20000'], ['10 / 10 / 1931', 'stanford', 'stanford stadium palo alto , ca', 'l13 - 7', '54787'], ['10 / 24 / 1931', 'iowa', 'memorial stadium minneapolis , mn', 'w34 - 0', '25000'], ['10 / 31 / 1931', 'wisconsin', 'memorial stadium minneapolis , mn', 'w14 - 0', '52000'], ['11 / 07 / 1931', 'northwestern', 'dyche stadium evanston , il', 'l14 - 32', '42000'], ['11 / 14 / 1931', 'cornell ( ia )', 'memorial stadium minneapolis , mn', 'w47 - 7', '10000'], ['11 / 21 / 1931', 'michigan', 'michigan stadium ann arbor , mi', 'l0 - 6', '37251'], ['11 / 28 / 1931', 'ohio state', 'memorial stadium minneapolis , mn', 'w19 - 7', '25000']] |
1991 - 92 seattle supersonics season | https://en.wikipedia.org/wiki/1991%E2%80%9392_Seattle_SuperSonics_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27902171-8.html.csv | comparative | the supersonics lost to the portland trailblazers before they lost to the detroit pistons . | {'row_1': '5', 'row_2': '6', 'col': '2', 'col_other': '3', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'team', 'portland trail blazers'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose team record fuzzily matches to portland trail blazers .', 'tostr': 'filter_eq { all_rows ; team ; portland trail blazers }'}, 'date'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; team ; portland trail blazers } ; date }', 'tointer': 'select the rows whose team record fuzzily matches to portland trail blazers . take the date record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'team', 'detroit pistons'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose team record fuzzily matches to detroit pistons .', 'tostr': 'filter_eq { all_rows ; team ; detroit pistons }'}, 'date'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; team ; detroit pistons } ; date }', 'tointer': 'select the rows whose team record fuzzily matches to detroit pistons . take the date record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; team ; portland trail blazers } ; date } ; hop { filter_eq { all_rows ; team ; detroit pistons } ; date } } = true', 'tointer': 'select the rows whose team record fuzzily matches to portland trail blazers . take the date record of this row . select the rows whose team record fuzzily matches to detroit pistons . take the date record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; team ; portland trail blazers } ; date } ; hop { filter_eq { all_rows ; team ; detroit pistons } ; date } } = true | select the rows whose team record fuzzily matches to portland trail blazers . take the date record of this row . select the rows whose team record fuzzily matches to detroit pistons . 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, 'team_7': 7, 'portland trail blazers_8': 8, 'date_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'team_11': 11, 'detroit pistons_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', 'team_7': 'team', 'portland trail blazers_8': 'portland trail blazers', 'date_9': 'date', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'team_11': 'team', 'detroit pistons_12': 'detroit pistons', 'date_13': 'date'} | {'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'team_7': [0], 'portland trail blazers_8': [0], 'date_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'team_11': [1], 'detroit pistons_12': [1], 'date_13': [3]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record'] | [['58', 'march 1', 'cleveland cavaliers', 'w 113 - 107', 'e johnson , r pierce ( 22 )', 'b benjamin , m cage ( 14 )', 'r pierce ( 6 )', 'seattle center coliseum 13647', '32 - 26'], ['59', 'march 3', 'denver nuggets', 'w 111 - 92', 's kemp ( 21 )', 's kemp ( 13 )', 'g payton ( 9 )', 'seattle center coliseum 9865', '33 - 26'], ['60', 'march 5', 'phoenix suns', 'l 105 - 118', 'r pierce ( 23 )', 's kemp ( 19 )', 'g payton ( 12 )', 'arizona veterans memorial coliseum 14496', '33 - 27'], ['61', 'march 7', 'new jersey nets', 'w 109 - 98', 'r pierce ( 27 )', 'm cage ( 13 )', 'n mcmillan ( 7 )', 'seattle center coliseum 13419', '34 - 27'], ['62', 'march 8', 'portland trail blazers', 'l 97 - 109', 'r pierce ( 28 )', 'r pierce ( 10 )', 'g payton ( 7 )', 'memorial coliseum 12888', '34 - 28'], ['63', 'march 10', 'detroit pistons', 'l 92 - 98', 'g payton ( 19 )', 's kemp ( 9 )', 'n mcmillan ( 5 )', 'seattle center coliseum 13098', '34 - 29'], ['64', 'march 11', 'los angeles clippers', 'w 104 - 96', 'r pierce ( 19 )', 'b benjamin , m cage ( 6 )', 'g payton ( 9 )', 'los angeles memorial sports arena 10912', '35 - 29'], ['65', 'march 15', 'dallas mavericks', 'w 109 - 100', 'r pierce ( 23 )', 's kemp ( 15 )', 'g payton ( 8 )', 'seattle center coliseum 12163', '36 - 29'], ['66', 'march 17', 'golden state warriors', 'l 107 - 119', 'r pierce ( 24 )', 's kemp ( 15 )', 'r pierce ( 5 )', 'seattle center coliseum 13163', '36 - 30'], ['67', 'march 19', 'houston rockets', 'w 112 - 91', 'r pierce ( 22 )', 'm cage , s kemp ( 14 )', 'g payton ( 11 )', 'the summit 15122', '37 - 30'], ['68', 'march 21', 'san antonio spurs', 'l 96 - 101', 'e johnson ( 23 )', 's kemp ( 13 )', 'd barros , m cage , n mcmillan ( 4 )', 'hemisfair arena 16057', '37 - 31'], ['69', 'march 22', 'dallas mavericks', 'w 113 - 105', 'e johnson ( 31 )', 's kemp ( 17 )', 'n mcmillan ( 8 )', 'reunion arena 14345', '38 - 31'], ['70', 'march 24', 'houston rockets', 'w 128 - 106', 'd mckey ( 23 )', 'm cage , s kemp ( 11 )', 'n mcmillan , g payton ( 7 )', 'seattle center coliseum 11377', '39 - 31'], ['71', 'march 27', 'milwaukee bucks', 'w 96 - 95', 'e johnson ( 21 )', 'n mcmillan ( 7 )', 'n mcmillan ( 6 )', 'seattle center coliseum 11450', '40 - 31'], ['72', 'march 28', 'new york knicks', 'l 87 - 92', 's kemp ( 27 )', 's kemp ( 12 )', 'n mcmillan ( 6 )', 'seattle center coliseum 14812', '40 - 32']] |
2008 - 09 milwaukee bucks season | https://en.wikipedia.org/wiki/2008%E2%80%9309_Milwaukee_Bucks_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17058116-8.html.csv | count | richard jefferson had the high point 5 times . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'richard jefferson', 'result': '5', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'high points', 'richard jefferson'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose high points record fuzzily matches to richard jefferson .', 'tostr': 'filter_eq { all_rows ; high points ; richard jefferson }'}], 'result': '5', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; high points ; richard jefferson } }', 'tointer': 'select the rows whose high points record fuzzily matches to richard jefferson . the number of such rows is 5 .'}, '5'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; high points ; richard jefferson } } ; 5 } = true', 'tointer': 'select the rows whose high points record fuzzily matches to richard jefferson . the number of such rows is 5 .'} | eq { count { filter_eq { all_rows ; high points ; richard jefferson } } ; 5 } = true | select the rows whose high points record fuzzily matches to richard jefferson . 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, 'high points_5': 5, 'richard jefferson_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', 'high points_5': 'high points', 'richard jefferson_6': 'richard jefferson', '5_7': '5'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'high points_5': [0], 'richard jefferson_6': [0], '5_7': [2]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'location attendance', 'record'] | [['52', 'february 3', 'new jersey', 'l 85 - 99 ( ot )', 'richard jefferson ( 27 )', 'dan gadzuric ( 9 )', 'izod center 10102', '24 - 28'], ['53', 'february 7', 'detroit', 'l 121 - 126 ( ot )', 'ramon sessions ( 44 )', 'francisco elson ( 8 )', 'bradley center 17297', '24 - 29'], ['54', 'february 9', 'houston', 'w 124 - 112 ( ot )', 'ramon sessions ( 26 )', 'charlie villanueva ( 8 )', 'bradley center 13904', '25 - 29'], ['55', 'february 11', 'indiana', 'w 122 - 110 ( ot )', 'richard jefferson ( 32 )', 'luc mbah a moute ( 11 )', 'bradley center 13486', '26 - 29'], ['56', 'february 17', 'detroit', 'w 92 - 86 ( ot )', 'richard jefferson ( 29 )', 'ramon sessions ( 9 )', 'the palace of auburn hills 20217', '27 - 29'], ['57', 'february 18', 'chicago', 'l 104 - 113 ( ot )', 'richard jefferson ( 32 )', 'charlie villanueva ( 12 )', 'bradley center 15309', '27 - 30'], ['58', 'february 20', 'cleveland', 'l 103 - 111 ( ot )', 'charlie villanueva ( 26 )', 'charlie villanueva ( 13 )', 'bradley center 18076', '27 - 31'], ['59', 'february 22', 'denver', 'w 120 - 117 ( ot )', 'charlie villanueva ( 36 )', 'francisco elson ( 7 )', 'bradley center 14891', '28 - 31'], ['60', 'february 25', 'dallas', 'l 96 - 116 ( ot )', 'charlie villanueva ( 25 )', 'charlie villanueva ( 7 )', 'american airlines center 19558', '28 - 32'], ['61', 'february 27', 'new orleans', 'l 94 - 95 ( ot )', 'richard jefferson ( 22 )', 'charlie villanueva ( 7 )', 'new orleans arena 17621', '28 - 33'], ['62', 'february 28', 'washington', 'w 109 - 93 ( ot )', 'charlie villanueva ( 25 )', 'dan gadzuric ( 11 )', 'bradley center 15970', '29 - 33']] |
2008 - 09 f.c. copenhagen season | https://en.wikipedia.org/wiki/2008%E2%80%9309_F.C._Copenhagen_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17637370-3.html.csv | unique | in the 2008 - 09 season , bertolt was the only player that came to f.c. copenhagen via the end of a loan . | {'scope': 'all', 'row': '3', 'col': '4', 'col_other': '2', 'criterion': 'equal', 'value': 'end of loan', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'type', 'end of loan'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose type record fuzzily matches to end of loan .', 'tostr': 'filter_eq { all_rows ; type ; end of loan }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; type ; end of loan } }', 'tointer': 'select the rows whose type record fuzzily matches to end of loan . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'type', 'end of loan'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose type record fuzzily matches to end of loan .', 'tostr': 'filter_eq { all_rows ; type ; end of loan }'}, 'name'], 'result': 'bertolt', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; type ; end of loan } ; name }'}, 'bertolt'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; type ; end of loan } ; name } ; bertolt }', 'tointer': 'the name record of this unqiue row is bertolt .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; type ; end of loan } } ; eq { hop { filter_eq { all_rows ; type ; end of loan } ; name } ; bertolt } } = true', 'tointer': 'select the rows whose type record fuzzily matches to end of loan . there is only one such row in the table . the name record of this unqiue row is bertolt .'} | and { only { filter_eq { all_rows ; type ; end of loan } } ; eq { hop { filter_eq { all_rows ; type ; end of loan } ; name } ; bertolt } } = true | select the rows whose type record fuzzily matches to end of loan . there is only one such row in the table . the name record of this unqiue row is bertolt . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'type_7': 7, 'end of loan_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'name_9': 9, 'bertolt_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'type_7': 'type', 'end of loan_8': 'end of loan', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'name_9': 'name', 'bertolt_10': 'bertolt'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'type_7': [0], 'end of loan_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'name_9': [2], 'bertolt_10': [3]} | ['nat', 'name', 'moving from', 'type', 'transfer window', 'ends', 'transfer fee', 'source'] | [['dnk', 'd jensen', 'youth system', 'promoted', 'summer', '2011', 'youth system', 'fckdk'], ['dnk', 'albrechtsen', 'youth system', 'promoted', 'summer', '2010', 'youth system', 'fckdk'], ['dnk', 'bertolt', 'viborg', 'end of loan', 'summer', '2009', 'n / a', 'fckdk'], ['dnk', 'kristensen', 'nordsjãlland', 'transfer', 'summer', '2012', 'undisclosed', 'fckdk'], ['bra', 'santin', 'kalmar ff', 'transfer', 'summer', '2013', 'dkk 15000000', 'fckdk'], ['swe', 'larsson', 'halmstads bk', 'transfer', 'summer', '2013', 'dkk 15000000', 'fckdk'], ['swe', 'wiland', 'if elfsborg', 'transfer', 'winter', '2013', 'dkk 8000000', 'fckdk'], ['dnk', 'vingaard', 'esbjerg', 'transfer', 'winter', '2012', 'dkk 8000000', 'fckdk'], ['sen', "n'doye", 'ofi', 'transfer', 'winter', '2013', 'dkk 15000000', 'fckdk']] |
hairuddin omar | https://en.wikipedia.org/wiki/Hairuddin_Omar | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10358163-1.html.csv | majority | hairuddin omar won the majority of matches he played in from 2000 to 2008 . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'won', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'result', 'won'], 'result': True, 'ind': 0, 'tointer': 'for the result records of all rows , most of them fuzzily match to won .', 'tostr': 'most_eq { all_rows ; result ; won } = true'} | most_eq { all_rows ; result ; won } = true | for the result records of all rows , most of them fuzzily match to won . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'result_3': 3, 'won_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'result_3': 'result', 'won_4': 'won'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'result_3': [0], 'won_4': [0]} | ['date', 'venue', 'score', 'result', 'competition'] | [['7 november 2000', 'bangkok , thailand', '5 - 0', 'won', '2000 tiger cup group stage'], ['9 november 2000', 'bangkok , thailand', '3 - 2', 'won', '2000 tiger cup group stage'], ['9 may 2001', 'ba , fiji', '1 - 2', 'won', 'friendly'], ['23 march 2001', 'doha , qatar', '2 - 1', 'lost', '2002 fifa world cup qualification ( afc )'], ['25 march 2001', 'doha , qatar', '4 - 3', 'won', '2002 fifa world cup qualification ( afc )'], ['11 december 2002', 'kuala lumpur , malaysia', '5 - 0', 'won', 'friendly'], ['20 october 2003', 'manama , bahrain', '5 - 1', 'lost', '2004 afc asian cup qualification'], ['24 october 2003', 'manama , bahrain', '2 - 1', 'lost', '2004 afc asian cup qualification'], ['12 january 2007', 'bangkok , thailand', '4 - 0', 'won', '2007 asean football championship'], ['18 june 2007', 'shah alam , malaysia', '6 - 0', 'won', 'friendly'], ['10 october 2008', 'kuala lumpur , malaysia', '4 - 1', 'won', 'friendly'], ['20 october 2008', 'kuala lumpur , malaysia', '6 - 0', 'won', '2008 merdeka tournament']] |
2008 - 09 portland trail blazers season | https://en.wikipedia.org/wiki/2008%E2%80%9309_Portland_Trail_Blazers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17058178-12.html.csv | majority | during the 2008-09 portland trail blazers seasons most of the high points were scored by brandon roy . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'brandon roy', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'high points', 'brandon roy'], 'result': True, 'ind': 0, 'tointer': 'for the high points records of all rows , most of them fuzzily match to brandon roy .', 'tostr': 'most_eq { all_rows ; high points ; brandon roy } = true'} | most_eq { all_rows ; high points ; brandon roy } = true | for the high points records of all rows , most of them fuzzily match to brandon roy . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'high points_3': 3, 'brandon roy_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'high points_3': 'high points', 'brandon roy_4': 'brandon roy'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'high points_3': [0], 'brandon roy_4': [0]} | ['game', 'date', 'team', 'score', 'high points', 'high assists', 'location attendance', 'record'] | [['1', 'april 18', 'houston', 'l 81 - 108 ( ot )', 'brandon roy ( 21 )', 'steve blake ( 6 )', 'rose garden 20329', '0 - 1'], ['2', 'april 21', 'houston', 'w 107 - 103 ( ot )', 'brandon roy ( 42 )', 'steve blake ( 5 )', 'rose garden 20408', '1 - 1'], ['3', 'april 24', 'houston', 'l 83 - 86 ( ot )', 'brandon roy ( 19 )', 'steve blake ( 10 )', 'toyota center 18371', '1 - 2'], ['4', 'april 26', 'houston', 'l 88 - 89 ( ot )', 'brandon roy ( 31 )', 'steve blake ( 8 )', 'toyota center 18271', '1 - 3'], ['5', 'april 28', 'houston', 'w 88 - 77 ( ot )', 'brandon roy , lamarcus aldridge ( 25 )', 'joel przybilla ( 4 )', 'rose garden 20462', '2 - 3'], ['6', 'april 30', 'houston', 'l 76 - 92 ( ot )', 'lamarcus aldridge ( 25 )', 'steve blake ( 5 )', 'toyota center', '2 - 4']] |
the soundgraphy | https://en.wikipedia.org/wiki/The_Soundgraphy | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12703884-2.html.csv | majority | most of the soundgraphy 's records were released by alfa records . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'alfa records', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'label', 'alfa records'], 'result': True, 'ind': 0, 'tointer': 'for the label records of all rows , most of them fuzzily match to alfa records .', 'tostr': 'most_eq { all_rows ; label ; alfa records } = true'} | most_eq { all_rows ; label ; alfa records } = true | for the label records of all rows , most of them fuzzily match to alfa records . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'label_3': 3, 'alfa records_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'label_3': 'label', 'alfa records_4': 'alfa records'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'label_3': [0], 'alfa records_4': [0]} | ['region', 'date', 'label', 'format', 'catalog'] | [['japan', 'april 25 , 1984', 'alfa records', 'stereo lp', 'alr - 28055'], ['japan', 'may 25 , 1984', 'alfa records', 'cd', '38xa - 12'], ['japan', 'january 25 , 1987', 'alfa records', 'cd', '32xa - 116'], ['japan', 'march 21 , 1992', 'alfa records', 'cd', 'alca - 281'], ['japan', 'august 31 , 1994', 'alfa records', 'cd', 'alca - 9011'], ['japan', 'august 29 , 1998', 'alfa records', 'cd', 'alca - 9206'], ['japan', 'december 6 , 2000', 'toshiba emi', 'cd', 'toct - 10752'], ['japan', 'january 23 , 2002', 'village records', 'ed remaster cd', 'vrcl - 2211'], ['japan', 'february 14 , 2002', 'village records', 'ed remaster cd', 'vrcl - 2231'], ['japan', 'may 27 , 2009', 'sony music direct', 'ed remaster cd', 'mhcl - 20013']] |
cities of the underworld | https://en.wikipedia.org/wiki/Cities_of_the_Underworld | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10926568-2.html.csv | unique | secret soviet bases is the only episode in the cities of the underworld series that was aired in the month of may . | {'scope': 'all', 'row': '13', 'col': '3', 'col_other': '4', 'criterion': 'equal', 'value': 'may', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'original airdate', 'may'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose original airdate record fuzzily matches to may .', 'tostr': 'filter_eq { all_rows ; original airdate ; may }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; original airdate ; may } }', 'tointer': 'select the rows whose original airdate record fuzzily matches to may . 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 airdate', 'may'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose original airdate record fuzzily matches to may .', 'tostr': 'filter_eq { all_rows ; original airdate ; may }'}, 'episode title'], 'result': 'secret soviet bases', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; original airdate ; may } ; episode title }'}, 'secret soviet bases'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; original airdate ; may } ; episode title } ; secret soviet bases }', 'tointer': 'the episode title record of this unqiue row is secret soviet bases .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; original airdate ; may } } ; eq { hop { filter_eq { all_rows ; original airdate ; may } ; episode title } ; secret soviet bases } } = true', 'tointer': 'select the rows whose original airdate record fuzzily matches to may . there is only one such row in the table . the episode title record of this unqiue row is secret soviet bases .'} | and { only { filter_eq { all_rows ; original airdate ; may } } ; eq { hop { filter_eq { all_rows ; original airdate ; may } ; episode title } ; secret soviet bases } } = true | select the rows whose original airdate record fuzzily matches to may . there is only one such row in the table . the episode title record of this unqiue row is secret soviet bases . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'original airdate_7': 7, 'may_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'episode title_9': 9, 'secret soviet bases_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'original airdate_7': 'original airdate', 'may_8': 'may', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'episode title_9': 'episode title', 'secret soviet bases_10': 'secret soviet bases'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'original airdate_7': [0], 'may_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'episode title_9': [2], 'secret soviet bases_10': [3]} | ['production no', 'episode no', 'original airdate', 'episode title', 'host'] | [['15', '201', 'january 28 , 2008', 'underground apocalypse', 'don wildman'], ['16', '202', 'february 4 , 2008', 'vietnam', 'don wildman'], ['17', '203', 'february 11 , 2008', 'a - bomb underground', 'don wildman'], ['18', '204', 'february 25 , 2008', 'viking underground', 'don wildman'], ['19', '205', 'march 3 , 2008', "hitler 's last secret", 'don wildman'], ['20', '206', 'march 10 , 2008', 'maya underground', 'don wildman'], ['21', '207', 'march 17 , 2008', 'mob underground', 'don wildman'], ['22', '208', 'march 24 , 2008', 'prophecies from below', 'don wildman'], ['23', '209', 'march 31 , 2008', 'new york : secret societies', 'don wildman'], ['24', '210', 'april 14 , 2008', 'washington , dc : seat of power', 'don wildman'], ['25', '211', 'april 21 , 2008', "stalin 's secret lair", 'don wildman'], ['26', '212', 'april 28 , 2008', 'katrina underground', 'don wildman'], ['27', '213', 'may 5 , 2008', 'secret soviet bases', 'don wildman']] |
swimming at the 2000 summer olympics - men 's 100 metre butterfly | https://en.wikipedia.org/wiki/Swimming_at_the_2000_Summer_Olympics_%E2%80%93_Men%27s_100_metre_butterfly | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12446342-5.html.csv | unique | michael klim is the only competitor in the men 's 100 metre butterfly that is from australia . | {'scope': 'all', 'row': '1', 'col': '4', 'col_other': '3', 'criterion': 'equal', 'value': 'australia', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'nationality', 'australia'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose nationality record fuzzily matches to australia .', 'tostr': 'filter_eq { all_rows ; nationality ; australia }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; nationality ; australia } }', 'tointer': 'select the rows whose nationality record fuzzily matches to australia . 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', 'australia'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose nationality record fuzzily matches to australia .', 'tostr': 'filter_eq { all_rows ; nationality ; australia }'}, 'name'], 'result': 'michael klim', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; nationality ; australia } ; name }'}, 'michael klim'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; nationality ; australia } ; name } ; michael klim }', 'tointer': 'the name record of this unqiue row is michael klim .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; nationality ; australia } } ; eq { hop { filter_eq { all_rows ; nationality ; australia } ; name } ; michael klim } } = true', 'tointer': 'select the rows whose nationality record fuzzily matches to australia . there is only one such row in the table . the name record of this unqiue row is michael klim .'} | and { only { filter_eq { all_rows ; nationality ; australia } } ; eq { hop { filter_eq { all_rows ; nationality ; australia } ; name } ; michael klim } } = true | select the rows whose nationality record fuzzily matches to australia . there is only one such row in the table . the name record of this unqiue row is michael klim . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'nationality_7': 7, 'australia_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'name_9': 9, 'michael klim_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', 'australia_8': 'australia', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'name_9': 'name', 'michael klim_10': 'michael klim'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'nationality_7': [0], 'australia_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'name_9': [2], 'michael klim_10': [3]} | ['rank', 'lane', 'name', 'nationality', 'time'] | [['1', '4', 'michael klim', 'australia', '52.63'], ['2', '2', 'ian crocker', 'united states', '52.82'], ['3', '3', 'lars frölander', 'sweden', '52.84'], ['4', '5', 'mike mintenko', 'canada', '53.00'], ['5', '1', 'thomas rupprath', 'germany', '53.18'], ['6', '6', 'anatoly polyakov', 'russia', '53.32'], ['7', '7', 'franck esposito', 'france', '53.38'], ['8', '8', 'jere hård', 'finland', '53.65']] |
2001 ansett australia cup | https://en.wikipedia.org/wiki/2001_Ansett_Australia_Cup | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-16388439-2.html.csv | aggregation | the games played on february 16 , 2001 had a crowd of over 46,000 . | {'scope': 'subset', 'col': '7', 'type': 'sum', 'result': '46,000', 'subset': {'col': '6', 'criterion': 'equal', 'value': 'friday , 16 february'}} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', 'friday , 16 february'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; date ; friday , 16 february }', 'tointer': 'select the rows whose date record fuzzily matches to friday , 16 february .'}, 'crowd'], 'result': '46,000', 'ind': 1, 'tostr': 'sum { filter_eq { all_rows ; date ; friday , 16 february } ; crowd }'}, '46,000'], 'result': True, 'ind': 2, 'tostr': 'round_eq { sum { filter_eq { all_rows ; date ; friday , 16 february } ; crowd } ; 46,000 } = true', 'tointer': 'select the rows whose date record fuzzily matches to friday , 16 february . the sum of the crowd record of these rows is 46,000 .'} | round_eq { sum { filter_eq { all_rows ; date ; friday , 16 february } ; crowd } ; 46,000 } = true | select the rows whose date record fuzzily matches to friday , 16 february . the sum of the crowd record of these rows is 46,000 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'sum_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'date_5': 5, 'friday , 16 february_6': 6, 'crowd_7': 7, '46,000_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'sum_1': 'sum', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'date_5': 'date', 'friday , 16 february_6': 'friday , 16 february', 'crowd_7': 'crowd', '46,000_8': '46,000'} | {'eq_2': [3], 'result_3': [], 'sum_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'date_5': [0], 'friday , 16 february_6': [0], 'crowd_7': [1], '46,000_8': [2]} | ['home team', 'home team score', 'away team', 'away team score', 'ground', 'date', 'crowd'] | [['collingwood', '12.14 ( 86 )', 'st kilda', '10.8 ( 68 )', 'colonial stadium', 'friday , 16 february', '30072'], ['west coast', '6.11 ( 47 )', 'kangaroos', '14.12 ( 96 )', 'subiaco oval', 'friday , 16 february', '16905'], ['kangaroos', '14.12 ( 96 )', 'st kilda', '12.9 ( 81 )', 'manuka oval', 'saturday , 24 february', '8157'], ['west coast', '12.6 ( 78 )', 'collingwood', '12.8 ( 80 )', 'subiaco oval', 'saturday , 24 february', '16090'], ['st kilda', '19.9 ( 123 )', 'west coast', '15.7 ( 97 )', 'colonial stadium', 'friday , 2 march', '8642']] |
1970 boston patriots season | https://en.wikipedia.org/wiki/1970_Boston_Patriots_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10646877-1.html.csv | ordinal | the boston patriots ' game against the miami dolphins was the earliest in the 1970 season . | {'row': '1', 'col': '2', 'order': '1', 'col_other': '3', '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', 'date', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; date ; 1 }'}, 'opponent'], 'result': 'miami dolphins', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; date ; 1 } ; opponent }'}, 'miami dolphins'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; date ; 1 } ; opponent } ; miami dolphins } = true', 'tointer': 'select the row whose date record of all rows is 1st minimum . the opponent record of this row is miami dolphins .'} | eq { hop { nth_argmin { all_rows ; date ; 1 } ; opponent } ; miami dolphins } = true | select the row whose date record of all rows is 1st minimum . the opponent record of this row is miami dolphins . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'date_5': 5, '1_6': 6, 'opponent_7': 7, 'miami dolphins_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', 'date_5': 'date', '1_6': '1', 'opponent_7': 'opponent', 'miami dolphins_8': 'miami dolphins'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'date_5': [0], '1_6': [0], 'opponent_7': [1], 'miami dolphins_8': [2]} | ['week', 'date', 'opponent', 'result', 'attendance'] | [['1', 'september 20 , 1970', 'miami dolphins', 'w 27 - 14', '32607'], ['2', 'september 27 , 1970', 'new york jets', 'l 31 - 21', '36040'], ['3', 'october 4 , 1970', 'baltimore colts', 'l 14 - 6', '38235'], ['4', 'october 11 , 1970', 'kansas city chiefs', 'l 23 - 10', '50698'], ['5', 'october 18 , 1970', 'new york giants', 'l 16 - 0', '39091'], ['6', 'october 25 , 1970', 'baltimore colts', 'l 27 - 3', '60240'], ['7', 'november 1 , 1970', 'buffalo bills', 'l 45 - 10', '31148'], ['8', 'november 8 , 1970', 'st louis cardinals', 'l 31 - 0', '46466'], ['9', 'november 15 , 1970', 'san diego chargers', 'l 16 - 14', '30597'], ['10', 'november 22 , 1970', 'new york jets', 'l 17 - 3', '61822'], ['11', 'november 29 , 1970', 'buffalo bills', 'w 14 - 10', '31427'], ['12', 'december 6 , 1970', 'miami dolphins', 'l 37 - 20', '51032'], ['13', 'december 13 , 1970', 'minnesota vikings', 'l 35 - 14', '37819'], ['14', 'december 20 , 1970', 'cincinnati bengals', 'l 45 - 7', '60157']] |
memphis grizzlies all - time roster | https://en.wikipedia.org/wiki/Memphis_Grizzlies_all-time_roster | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-16494599-4.html.csv | majority | all of the players on the memphis grizzlies all - time roster are from the united states . | {'scope': 'all', 'col': '3', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'united states', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'nationality', 'united states'], 'result': True, 'ind': 0, 'tointer': 'for the nationality records of all rows , all of them fuzzily match to united states .', 'tostr': 'all_eq { all_rows ; nationality ; united states } = true'} | all_eq { all_rows ; nationality ; united states } = true | for the nationality records of all rows , all of them fuzzily match to united states . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'nationality_3': 3, 'united states_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'nationality_3': 'nationality', 'united states_4': 'united states'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'nationality_3': [0], 'united states_4': [0]} | ['player', 'no', 'nationality', 'position', 'years for grizzlies', 'school / club team'] | [['antonio daniels', '33', 'united states', 'point guard', '1997 - 1998', 'bowling green'], ['ed davis', '32', 'united states', 'forward', '2013 - present', 'north carolina'], ['josh davis', '18', 'united states', 'forward', '2011 - 2012', 'wyoming'], ['austin daye', '5', 'united states', 'small forward', '2013 - present', 'gonzaga'], ['terry dehere', '24', 'united states', 'guard', '1999', 'seton hall'], ['michael dickerson', '8', 'united states', 'guard - forward', '1999 - 2003', 'arizona']] |
2008 issf world cup final ( shotgun ) | https://en.wikipedia.org/wiki/2008_ISSF_World_Cup_Final_%28shotgun%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18351792-6.html.csv | superlative | of the players that were n't medalists , ariel mauricio flores had the highest total . | {'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', 'total'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; total }'}, 'shooter'], 'result': 'ariel mauricio flores ( mex )', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; total } ; shooter }'}, 'ariel mauricio flores ( mex )'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; total } ; shooter } ; ariel mauricio flores ( mex ) } = true', 'tointer': 'select the row whose total record of all rows is maximum . the shooter record of this row is ariel mauricio flores ( mex ) .'} | eq { hop { argmax { all_rows ; total } ; shooter } ; ariel mauricio flores ( mex ) } = true | select the row whose total record of all rows is maximum . the shooter record of this row is ariel mauricio flores ( mex ) . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'total_5': 5, 'shooter_6': 6, 'ariel mauricio flores ( mex )_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'total_5': 'total', 'shooter_6': 'shooter', 'ariel mauricio flores ( mex )_7': 'ariel mauricio flores ( mex )'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'total_5': [0], 'shooter_6': [1], 'ariel mauricio flores ( mex )_7': [2]} | ['shooter', 'event', 'rank points', 'score points', 'total'] | [['georgios achilleos ( cyp )', 'wcf 2007', 'defending champion', 'defending champion', 'defending champion'], ['vincent hancock ( usa )', 'og beijing', 'olympic gold medalist', 'olympic gold medalist', 'olympic gold medalist'], ['tore brovold ( nor )', 'og beijing', 'olympic silver medalist', 'olympic silver medalist', 'olympic silver medalist'], ['anthony terras ( fra )', 'og beijing', 'olympic bronze medalist', 'olympic bronze medalist', 'olympic bronze medalist'], ['ariel mauricio flores ( mex )', 'wc kerrville', '15', '12', '27'], ['qu ridong ( chn )', 'wc beijing', '15', '10', '25'], ['andrea benelli ( ita )', 'wc belgrade', '10', '13', '23'], ['konstantin tsuranov ( rus )', 'wc beijing', '10', '10', '20'], ['jan sychra ( cze )', 'wc belgrade', '5', '13', '18'], ['valerio luchini ( ita )', 'wc kerrville', '8', '10', '18'], ['leos hlavacek ( cze )', 'wc suhl', '5', '11', '16'], ['abdullah alrashidi ( kuw )', 'wc belgrade', '3', '12', '15']] |
2008 - 09 montreal canadiens season | https://en.wikipedia.org/wiki/2008%E2%80%9309_Montreal_Canadiens_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17206737-5.html.csv | aggregation | the average attendance at the montreal canadiens home games during the 2008-09 season was 21273 . | {'scope': 'all', 'col': '6', 'type': 'average', 'result': '21273', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'attendance'], 'result': '21273', 'ind': 0, 'tostr': 'avg { all_rows ; attendance }'}, '21273'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; attendance } ; 21273 } = true', 'tointer': 'the average of the attendance record of all rows is 21273 .'} | round_eq { avg { all_rows ; attendance } ; 21273 } = true | the average of the attendance record of all rows is 21273 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'attendance_4': 4, '21273_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'attendance_4': 'attendance', '21273_5': '21273'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'attendance_4': [0], '21273_5': [1]} | ['date', 'visitor', 'score', 'home', 'decision', 'attendance', 'record', 'points'] | [['november 1', 'montreal canadiens', '5 - 4', 'new york islanders', 'price', '14429', '8 - 1 - 1', '17'], ['november 7', 'montreal canadiens', '3 - 4 so', 'columbus blue jackets', 'halak', '14603', '8 - 1 - 2', '18'], ['november 8', 'montreal canadiens', '3 - 6', 'toronto maple leafs', 'price', '19512', '8 - 2 - 2', '18'], ['november 11', 'ottawa senators', '0 - 4', 'montreal canadiens', 'price', '21273', '9 - 2 - 2', '20'], ['november 13', 'montreal canadiens', '1 - 6', 'boston bruins', 'price', '16816', '9 - 3 - 2', '20'], ['november 15', 'philadelphia flyers', '2 - 1', 'montreal canadiens', 'halak', '21273', '9 - 4 - 2', '20'], ['november 16', 'montreal canadiens', '3 - 2 so', 'st louis blues', 'price', '19150', '10 - 4 - 2', '22'], ['november 18', 'montreal canadiens', '1 - 2', 'carolina hurricanes', 'price', '12164', '10 - 5 - 2', '22'], ['november 20', 'montreal canadiens', '3 - 2 so', 'ottawa senators', 'price', '20475', '11 - 5 - 2', '24'], ['november 22', 'boston bruins', '3 - 2 so', 'montreal canadiens', 'price', '21273', '11 - 5 - 3', '25'], ['november 24', 'new york islanders', '4 - 3 so', 'montreal canadiens', 'price', '21273', '11 - 5 - 4', '26'], ['november 26', 'montreal canadiens', '3 - 1', 'detroit red wings', 'price', '20066', '12 - 5 - 4', '28'], ['november 28', 'montreal canadiens', '0 - 3', 'washington capitals', 'halak', '18277', '12 - 6 - 4', '28'], ['november 29', 'buffalo sabres', '2 - 3', 'montreal canadiens', 'price', '21273', '13 - 6 - 4', '30']] |
csi ( franchise ) | https://en.wikipedia.org/wiki/CSI_%28franchise%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-10819266-8.html.csv | unique | season 8 of csi was the only season in which there was 18 episodes . | {'scope': 'all', 'row': '8', 'col': '2', 'col_other': '1', 'criterion': 'equal', 'value': '18', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'episodes', '18'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose episodes record is equal to 18 .', 'tostr': 'filter_eq { all_rows ; episodes ; 18 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; episodes ; 18 } }', 'tointer': 'select the rows whose episodes record is equal to 18 . there is only one such row in the table .'}, {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'episodes', '18'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose episodes record is equal to 18 .', 'tostr': 'filter_eq { all_rows ; episodes ; 18 }'}, 'season'], 'result': '8', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; episodes ; 18 } ; season }'}, '8'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; episodes ; 18 } ; season } ; 8 }', 'tointer': 'the season record of this unqiue row is 8 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; episodes ; 18 } } ; eq { hop { filter_eq { all_rows ; episodes ; 18 } ; season } ; 8 } } = true', 'tointer': 'select the rows whose episodes record is equal to 18 . there is only one such row in the table . the season record of this unqiue row is 8 .'} | and { only { filter_eq { all_rows ; episodes ; 18 } } ; eq { hop { filter_eq { all_rows ; episodes ; 18 } ; season } ; 8 } } = true | select the rows whose episodes record is equal to 18 . there is only one such row in the table . the season record of this unqiue row is 8 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'episodes_7': 7, '18_8': 8, 'eq_3': 3, 'num_hop_2': 2, 'season_9': 9, '8_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'episodes_7': 'episodes', '18_8': '18', 'eq_3': 'eq', 'num_hop_2': 'num_hop', 'season_9': 'season', '8_10': '8'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'episodes_7': [0], '18_8': [0], 'eq_3': [4], 'num_hop_2': [3], 'season_9': [2], '8_10': [3]} | ['season', 'episodes', 'time slot ( est )', 'season premiere', 'season finale', 'tv season', 'rank', 'viewers ( in millions )'] | [['1', '23', 'wednesday 10 pm / 9c', 'september 22 , 2004', 'may 18 , 2005', '2004 - 2005', '21', '13.59'], ['2', '24', 'wednesday 10 pm / 9c', 'september 28 , 2005', 'may 17 , 2006', '2005 - 2006', '22', '14.04'], ['3', '24', 'wednesday 10 pm / 9c', 'september 20 , 2006', 'may 16 , 2007', '2006 - 2007', '25', '13.92'], ['4', '21', 'wednesday 10 pm / 9c', 'september 26 , 2007', 'may 21 , 2008', '2007 - 2008', '28', '11.71'], ['5', '25', 'wednesday 10 pm / 9c', 'september 24 , 2008', 'may 14 , 2009', '2008 - 2009', '17', '13.50'], ['6', '23', 'wednesday 10 pm / 9c', 'september 23 , 2009', 'may 26 , 2010', '2009 - 2010', '23', '12.66'], ['7', '22', 'friday 9 pm / 8c', 'september 24 , 2010', 'may 13 , 2011', '2010 - 2011', '37', '10.73'], ['8', '18', 'friday 9 pm / 8c', 'september 23 , 2011', 'may 11 , 2012', '2011 - 2012', '38', '10.34']] |
spain men 's national volleyball team | https://en.wikipedia.org/wiki/Spain_men%27s_national_volleyball_team | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-13312864-1.html.csv | aggregation | the average weight of players on the spain men 's national volleyball team is 90 kg . | {'scope': 'all', 'col': '4', 'type': 'average', 'result': '90', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'weight'], 'result': '90', 'ind': 0, 'tostr': 'avg { all_rows ; weight }'}, '90'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; weight } ; 90 } = true', 'tointer': 'the average of the weight record of all rows is 90 .'} | round_eq { avg { all_rows ; weight } ; 90 } = true | the average of the weight record of all rows is 90 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'weight_4': 4, '90_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'weight_4': 'weight', '90_5': '90'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'weight_4': [0], '90_5': [1]} | ['shirt no', 'player', 'birth date', 'weight', 'height'] | [['1', 'rafael pascual', '16 march 1970', '94', '194'], ['2', 'ibán pérez', '13 november 1983', '89', '198'], ['3', 'josé luis lobato', '19 february 1977', '81', '186'], ['4', 'manuel sevillano', '2 july 1981', '90', '194'], ['7', 'guillermo hernán', '25 july 1982', '68', '181'], ['10', 'miguel ángel falasca', '29 april 1973', '92', '195'], ['11', 'javier subiela', '22 march 1984', '88', '198'], ['12', 'guillermo falasca', '24 october 1977', '104', '200'], ['14', 'josé luis moltó', '29 june 1975', '95', '207'], ['16', 'julián garcía - torres', '8 november 1980', '93', '202'], ['17', 'enrique de la fuente', '11 august 1975', '95', '195']] |
1966 u.s. open ( golf ) | https://en.wikipedia.org/wiki/1966_U.S._Open_%28golf%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17277136-4.html.csv | majority | most of the players which participated in the 1966 u.s. open ( golf ) were from the united states . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'united states', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'country', 'united states'], 'result': True, 'ind': 0, 'tointer': 'for the country records of all rows , most of them fuzzily match to united states .', 'tostr': 'most_eq { all_rows ; country ; united states } = true'} | most_eq { all_rows ; country ; united states } = true | for the country records of all rows , most of them fuzzily match to united states . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'country_3': 3, 'united states_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'country_3': 'country', 'united states_4': 'united states'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'country_3': [0], 'united states_4': [0]} | ['place', 'player', 'country', 'score', 'to par'] | [['t1', 'billy casper', 'united states', '69 + 68 = 137', '- 3'], ['t1', 'arnold palmer', 'united states', '71 + 66 = 137', '- 3'], ['t3', 'phil rodgers', 'united states', '70 + 70 = 140', 'e'], ['t3', 'rives mcbee', 'united states', '76 + 64 = 140', 'e'], ['t5', 'jack nicklaus', 'united states', '71 + 71 = 142', '+ 2'], ['t5', 'johnny miller ( a )', 'united states', '70 + 72 = 142', '+ 2'], ['t7', 'julius boros', 'united states', '74 + 69 = 143', '+ 3'], ['t7', 'dave hill', 'united states', '72 + 71 = 143', '+ 3'], ['t7', 'kel nagle', 'australia', '70 + 73 = 143', '+ 3'], ['t10', 'bob goalby', 'united states', '71 + 73 = 144', '+ 4'], ['t10', 'al mengert', 'united states', '67 + 77 = 144', '+ 4']] |
10 ka dum | https://en.wikipedia.org/wiki/10_Ka_Dum | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-18513028-3.html.csv | majority | most of the contestants won the amount of rupees 10,00,000 . ` . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'rs 10 , 00000', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'winning amount', 'rs 10 , 00000'], 'result': True, 'ind': 0, 'tointer': 'for the winning amount records of all rows , most of them fuzzily match to rs 10 , 00000 .', 'tostr': 'most_eq { all_rows ; winning amount ; rs 10 , 00000 } = true'} | most_eq { all_rows ; winning amount ; rs 10 , 00000 } = true | for the winning amount records of all rows , most of them fuzzily match to rs 10 , 00000 . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'winning amount_3': 3, 'rs 10 , 00000_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'winning amount_3': 'winning amount', 'rs 10 , 00000_4': 'rs 10 , 00000'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'winning amount_3': [0], 'rs 10 , 00000_4': [0]} | ['contestant name', 'episode', 'date premiered ( 2009 )', 'winning amount', 'eliminated contestant'] | [['kareena kapoor', '1', 'may 30', 'rs10 , 00000', 'karishma kapoor'], ['daler mehndi', '2', 'june 6', 'rs10 , 00000', 'mika singh'], ['darsheel safary', '3', 'june 13', 'rs1 , 00000', 'tanay chheda'], ['katrina kaif', '4', 'june 20', 'rs10 , 00000', 'neil nitin mukesh'], ['vijendra kumar', '5', 'june 27', 'rs 1 , 00000', 'malika sherawat'], ['sunny deol', '6', 'july 4', 'rs 1 , 00000', 'dharmendra'], ['kangana ranaut', '7', 'july 11', 'rs 1 , 00000', 'pandit janardan'], ['shilpa shetty', '8', 'july 18', 'rs 1 , 00000', 'irfan pathan'], ['sunil mishra', '9', 'july 25', 'rs 10000', 'priyanka shukla'], ['farah khan', '10', 'august 1', 'rs 10 , 00000', 'deepika padukone'], ['sanjay dutt', '11', 'august 8', 'rs 10 , 00000', 'jackie shroff'], ['dutta pangare ( dabba wala )', '12', 'august 15', 'rs 10 , 00000', 'meena bhoir ( macchi wali )'], ['kapil dev', '13', 'august 22', 'rs 1 , 00000', 'navjot singh sidhu'], ['ragini khanna & ratan rajput', '14', 'august 29', 'rs 10 , 00000', 'sara khan & tina dutta'], ['sunil shetty', '15', 'september 5', 'rs10 , 00000', 'javed jaffrey & aftab shivdasani'], ['rani mukerjee', '16', 'september 12', 'rs 1 , 00000', 'shahid kapoor'], ['boney kapoor & sri devi', '17', 'september 19', 'rs 1 , 00000', 'prabhu deva & ayesha takia azmi'], ['ritesh deshmukh', '18', 'september 26', 'rs 10 , 00000', 'govinda & david dhawan'], ['shatrughan sinha', '19', 'october 3', 'rs 10000', 'hema malini'], ['himesh reshammiya', '20', 'october 10', 'rs 1 , 00000', 'sonal sehgal & shenaz treasurywala']] |
caroline wozniacki career statistics | https://en.wikipedia.org/wiki/Caroline_Wozniacki_career_statistics | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-26958265-17.html.csv | count | two of caroline wozniacki 's gi round robin fed cup doubles matches were played on a clay surface . | {'scope': 'all', 'criterion': 'equal', 'value': 'clay', 'result': '3', 'col': '7', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'surface', 'clay'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose surface record fuzzily matches to clay .', 'tostr': 'filter_eq { all_rows ; surface ; clay }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; surface ; clay } }', 'tointer': 'select the rows whose surface record fuzzily matches to clay . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; surface ; clay } } ; 3 } = true', 'tointer': 'select the rows whose surface record fuzzily matches to clay . the number of such rows is 3 .'} | eq { count { filter_eq { all_rows ; surface ; clay } } ; 3 } = true | select the rows whose surface record fuzzily matches to clay . 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, 'surface_5': 5, 'clay_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', 'surface_5': 'surface', 'clay_6': 'clay', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'surface_5': [0], 'clay_6': [0], '3_7': [2]} | ['edition', 'round', 'date', 'venue', 'partering', 'against', 'surface', 'opponents', 'w / l', 'result', 'team result'] | [['2005 fed cup', 'gi relegation play - offs', '23 april 2005', 'antalya', 'hanne skak jensen', 'greece', 'clay', 'asimina kaplani anna koumantou', 'win', '7 - 6 ( 7 - 5 ) , 6 - 4', 'win ( 2 - 1 )'], ['2007 fed cup', 'gi round robin', '19 april 2007', 'plovdiv', 'eva dyrberg', 'netherlands', 'clay', 'elise tamaëla nicole thyssen', 'win', '4 - 6 , 6 - 3 , 6 - 4', 'win ( 2 - 1 )'], ['2007 fed cup', 'gi round robin', '20 april 2007', 'plovdiv', 'eva dyrberg', 'romania', 'clay', 'mădălina gojnea monica niculescu', 'lose', '4 - 6 , 5 - 7', 'lose ( 1 - 2 )'], ['2008 fed cup', 'gi round robin', '1 february 2008', 'budapest', 'eva dyrberg', 'great britain', 'carpet ( i )', 'elena baltacha anne keothavong', 'win', '6 - 3 , 6 - 2', 'win ( 2 - 1 )'], ['2009 fed cup', 'gi round robin', '4 february 2009', 'tallinn', 'eva dyrberg', 'belarus', 'hard ( i )', 'victoria azarenka olga govortsova', 'lose', '0 - 6 , 4 - 6', 'lose ( 1 - 2 )'], ['2010 fed cup', 'gi round robin', '3 february 2010', 'lisbon', 'karina - ildor jacobsgaard', 'sweden', 'hard ( i )', 'sofia arvidsson johanna larsson', 'lose', '0 - 6 , 0 - 6', 'lose ( 1 - 2 )'], ['2011 fed cup', 'gi round robin', '3 february 2011', 'eilat', 'mai grage', 'switzerland', 'hard', 'timea bacsinszky patty schnyder', 'lose', '3 - 6 , 2 - 6', 'lose ( 1 - 2 )'], ['2011 fed cup', 'gi round robin', '4 february 2011', 'eilat', 'mai grage', 'great britain', 'hard', 'jocelyn rae heather watson', 'lose', '7 - 5 , 5 - 7 , 5 - 7', 'lose ( 1 - 2 )']] |
who dares wins ( uk game show ) | https://en.wikipedia.org/wiki/Who_Dares_Wins_%28UK_game_show%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-14523485-9.html.csv | superlative | in who dares wins , when the year aired begins in 2007 , the highest top prize is 250000 . | {'scope': 'subset', 'col_superlative': '6', 'row_superlative': '1', 'value_mentioned': 'yes', 'max_or_min': 'max', 'other_col': '5', 'subset': {'col': '5', 'criterion': 'fuzzily_match', 'value': '2007'}} | {'func': 'eq', 'args': [{'func': 'max', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'year aired', '2007'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; year aired ; 2007 }', 'tointer': 'select the rows whose year aired record fuzzily matches to 2007 .'}, 'top prize'], 'result': '250000', 'ind': 1, 'tostr': 'max { filter_eq { all_rows ; year aired ; 2007 } ; top prize }', 'tointer': 'select the rows whose year aired record fuzzily matches to 2007 . the maximum top prize record of these rows is 250000 .'}, '250000'], 'result': True, 'ind': 2, 'tostr': 'eq { max { filter_eq { all_rows ; year aired ; 2007 } ; top prize } ; 250000 } = true', 'tointer': 'select the rows whose year aired record fuzzily matches to 2007 . the maximum top prize record of these rows is 250000 .'} | eq { max { filter_eq { all_rows ; year aired ; 2007 } ; top prize } ; 250000 } = true | select the rows whose year aired record fuzzily matches to 2007 . the maximum top prize record of these rows is 250000 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'max_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'year aired_5': 5, '2007_6': 6, 'top prize_7': 7, '250000_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'max_1': 'max', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'year aired_5': 'year aired', '2007_6': '2007', 'top prize_7': 'top prize', '250000_8': '250000'} | {'eq_2': [3], 'result_3': [], 'max_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'year aired_5': [0], '2007_6': [0], 'top prize_7': [1], '250000_8': [2]} | ['country', 'local name', 'host', 'channel', 'year aired', 'top prize'] | [['australia', 'the rich list', "andrew o'keefe", 'seven network', '2007 - 2009', '250000'], ['france', 'la liste gagnante', 'patrice laffont', 'france 3', '2009', '5000'], ['germany', 'rich list', 'kai pflaume', 'sat1', '2007 - present', '100000'], ['new zealand', 'the rich list', 'jason gunn', 'tvnz', '2007 - present', '50000'], ['united kingdom', 'who dares wins', 'nick knowles', 'bbc one', '2007 - present', '50000'], ['united states', 'the rich list', 'eamonn holmes', 'fox', '2006', '250000']] |
the mole ( tv series ) | https://en.wikipedia.org/wiki/The_Mole_%28TV_series%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-178242-2.html.csv | superlative | season 5 of the mole had the highest potential prize money among all seasons . | {'scope': 'all', 'col_superlative': '7', 'row_superlative': '5', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'potential prize money'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; potential prize money }'}, 'season'], 'result': '5', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; potential prize money } ; season }'}, '5'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; potential prize money } ; season } ; 5 } = true', 'tointer': 'select the row whose potential prize money record of all rows is maximum . the season record of this row is 5 .'} | eq { hop { argmax { all_rows ; potential prize money } ; season } ; 5 } = true | select the row whose potential prize money record of all rows is maximum . the season record of this row is 5 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'num_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'potential prize money_5': 5, 'season_6': 6, '5_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'num_hop_1': 'num_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'potential prize money_5': 'potential prize money', 'season_6': 'season', '5_7': '5'} | {'eq_2': [3], 'result_3': [], 'num_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'potential prize money_5': [0], 'season_6': [1], '5_7': [2]} | ['season', 'year', 'mole', 'winner', 'runner - up', 'total prize money', 'potential prize money', 'destination'] | [['1', '2000', 'alan mason', 'jan moody', 'abby coleman', '115000', '200000', 'australia ( tasmania )'], ['2', '2001', 'michael laffy', 'brooke marshall', 'hal pritchard', '100000', '255000', 'australia ( victoria )'], ['3', '2002', 'alaina taylor', 'crystal - rose cluff', 'marc jongebloed', '108000', '416000', 'australia ( gold coast )'], ['4', '2003', 'petrina edge', 'shaun faulkner', 'nathan beves', '104000', '531000', 'new caledonia'], ['5', '2005', 'john whitehall', 'liz cantor', 'craig murell', '203000', '539000', 'new zealand'], ['6', '2013', 'erin dooley', 'hillal kara - ali', 'aisha jefcoate', '180000', '250000', 'australia']] |
1951 - 52 segunda división | https://en.wikipedia.org/wiki/1951%E2%80%9352_Segunda_Divisi%C3%B3n | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17298923-4.html.csv | aggregation | the 1951-1952 segunda division had an average of 30 points . | {'scope': 'all', 'col': '3', 'type': 'average', 'result': '30', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'points'], 'result': '30', 'ind': 0, 'tostr': 'avg { all_rows ; points }'}, '30'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; points } ; 30 } = true', 'tointer': 'the average of the points record of all rows is 30 .'} | round_eq { avg { all_rows ; points } ; 30 } = true | the average of the points record of all rows is 30 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'points_4': 4, '30_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'points_4': 'points', '30_5': '30'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'points_4': [0], '30_5': [1]} | ['position', 'played', 'points', 'wins', 'draws', 'losses', 'goals for', 'goals against', 'goal difference'] | [['1', '30', '42', '18', '6', '6', '83', '37', '+ 46'], ['2', '30', '40', '18', '4', '8', '63', '32', '+ 31'], ['3', '30', '36', '16', '4', '10', '55', '39', '+ 16'], ['4', '30', '36', '15', '6', '9', '41', '37', '+ 4'], ['5', '30', '33', '13', '7', '10', '44', '39', '+ 5'], ['6', '30', '32', '15', '2', '13', '60', '39', '+ 21'], ['7', '30', '32', '14', '4', '12', '45', '44', '+ 1'], ['8', '30', '30', '13', '4', '13', '59', '51', '+ 8'], ['9', '30', '29', '13', '3', '14', '52', '64', '- 12'], ['10', '30', '28', '13', '2', '15', '52', '56', '- 4'], ['11', '30', '26', '9', '8', '13', '46', '69', '- 23'], ['12', '30', '25', '10', '5', '15', '38', '53', '- 15'], ['13', '30', '24', '9', '6', '15', '32', '53', '- 21'], ['14', '30', '24', '10', '4', '16', '33', '50', '- 17'], ['15', '30', '24', '10', '4', '16', '35', '49', '- 14'], ['16', '30', '19', '6', '7', '17', '34', '60', '- 26']] |
south africa | https://en.wikipedia.org/wiki/South_Africa | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17416221-1.html.csv | unique | the only place that has less than 2,000,000 living in it is the northern cape . | {'scope': 'all', 'row': '8', 'col': '5', 'col_other': '1', 'criterion': 'less_than', 'value': '2,000,000', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'population ( 2013 )', '2,000,000'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose population ( 2013 ) record is less than 2,000,000 .', 'tostr': 'filter_less { all_rows ; population ( 2013 ) ; 2,000,000 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_less { all_rows ; population ( 2013 ) ; 2,000,000 } }', 'tointer': 'select the rows whose population ( 2013 ) record is less than 2,000,000 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'population ( 2013 )', '2,000,000'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose population ( 2013 ) record is less than 2,000,000 .', 'tostr': 'filter_less { all_rows ; population ( 2013 ) ; 2,000,000 }'}, 'province'], 'result': 'northern cape', 'ind': 2, 'tostr': 'hop { filter_less { all_rows ; population ( 2013 ) ; 2,000,000 } ; province }'}, 'northern cape'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_less { all_rows ; population ( 2013 ) ; 2,000,000 } ; province } ; northern cape }', 'tointer': 'the province record of this unqiue row is northern cape .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_less { all_rows ; population ( 2013 ) ; 2,000,000 } } ; eq { hop { filter_less { all_rows ; population ( 2013 ) ; 2,000,000 } ; province } ; northern cape } } = true', 'tointer': 'select the rows whose population ( 2013 ) record is less than 2,000,000 . there is only one such row in the table . the province record of this unqiue row is northern cape .'} | and { only { filter_less { all_rows ; population ( 2013 ) ; 2,000,000 } } ; eq { hop { filter_less { all_rows ; population ( 2013 ) ; 2,000,000 } ; province } ; northern cape } } = true | select the rows whose population ( 2013 ) record is less than 2,000,000 . there is only one such row in the table . the province record of this unqiue row is northern cape . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_less_0': 0, 'all_rows_6': 6, 'population (2013)_7': 7, '2,000,000_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'province_9': 9, 'northern cape_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_less_0': 'filter_less', 'all_rows_6': 'all_rows', 'population (2013)_7': 'population ( 2013 )', '2,000,000_8': '2,000,000', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'province_9': 'province', 'northern cape_10': 'northern cape'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_less_0': [1, 2], 'all_rows_6': [0], 'population (2013)_7': [0], '2,000,000_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'province_9': [2], 'northern cape_10': [3]} | ['province', 'provincial capital', 'largest city', 'area ( km 2 )', 'population ( 2013 )'] | [['eastern cape', 'bhisho', 'port elizabeth', '168966', '6620100'], ['free state', 'bloemfontein', 'bloemfontein', '129825', '2753200'], ['gauteng', 'johannesburg', 'johannesburg', '18178', '12728400'], ['kwazulu - natal', 'pietermaritzburg', 'durban', '94361', '10456900'], ['limpopo', 'polokwane', 'polokwane', '125754', '5518000'], ['mpumalanga', 'nelspruit', 'nelspruit', '76495', '4128000'], ['north west', 'mahikeng', 'rustenburg', '104882', '3597600'], ['northern cape', 'kimberley', 'kimberley', '372889', '1162900'], ['western cape', 'cape town', 'cape town', '129462', '6016900']] |
2008 qatar motorcycle grand prix | https://en.wikipedia.org/wiki/2008_Qatar_motorcycle_Grand_Prix | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16175675-1.html.csv | aggregation | in the 2008 qatar motorcycle grand prix , when the manufacturer is suzuki , the average number of laps is 21.5 . | {'scope': 'subset', 'col': '3', 'type': 'average', 'result': '21.5', 'subset': {'col': '2', 'criterion': 'equal', 'value': 'suzuki'}} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'manufacturer', 'suzuki'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; manufacturer ; suzuki }', 'tointer': 'select the rows whose manufacturer record fuzzily matches to suzuki .'}, 'laps'], 'result': '21.5', 'ind': 1, 'tostr': 'avg { filter_eq { all_rows ; manufacturer ; suzuki } ; laps }'}, '21.5'], 'result': True, 'ind': 2, 'tostr': 'round_eq { avg { filter_eq { all_rows ; manufacturer ; suzuki } ; laps } ; 21.5 } = true', 'tointer': 'select the rows whose manufacturer record fuzzily matches to suzuki . the average of the laps record of these rows is 21.5 .'} | round_eq { avg { filter_eq { all_rows ; manufacturer ; suzuki } ; laps } ; 21.5 } = true | select the rows whose manufacturer record fuzzily matches to suzuki . the average of the laps record of these rows is 21.5 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'avg_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'manufacturer_5': 5, 'suzuki_6': 6, 'laps_7': 7, '21.5_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'avg_1': 'avg', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'manufacturer_5': 'manufacturer', 'suzuki_6': 'suzuki', 'laps_7': 'laps', '21.5_8': '21.5'} | {'eq_2': [3], 'result_3': [], 'avg_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'manufacturer_5': [0], 'suzuki_6': [0], 'laps_7': [1], '21.5_8': [2]} | ['rider', 'manufacturer', 'laps', 'time / retired', 'grid'] | [['casey stoner', 'ducati', '22', '42:36.587', '4'], ['jorge lorenzo', 'yamaha', '22', '+ 5.323', '1'], ['dani pedrosa', 'honda', '22', '+ 10.600', '8'], ['andrea dovizioso', 'honda', '22', '+ 13.288', '9'], ['valentino rossi', 'yamaha', '22', '+ 13.305', '7'], ['james toseland', 'yamaha', '22', '+ 14.040', '2'], ['colin edwards', 'yamaha', '22', '+ 15.150', '3'], ['loris capirossi', 'suzuki', '22', '+ 32.505', '13'], ['randy de puniet', 'honda', '22', '+ 33.003', '5'], ['nicky hayden', 'honda', '22', '+ 38.354', '6'], ['marco melandri', 'ducati', '22', '+ 44.284', '16'], ['john hopkins', 'kawasaki', '22', '+ 49.857', '10'], ['shinya nakano', 'honda', '22', '+ 49.871', '15'], ['toni elias', 'ducati', '22', '+ 58.532', '14'], ['sylvain guintoli', 'ducati', '22', '+ 58.930', '17'], ['anthony west', 'kawasaki', '22', '+ 1:05.643', '18'], ['chris vermeulen', 'suzuki', '21', '+ 1 lap', '11'], ['alex de angelis', 'honda', '16', 'accident', '12']] |
the soundgraphy | https://en.wikipedia.org/wiki/The_Soundgraphy | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12703884-2.html.csv | unique | only one album from the soundgraphy was released on sony music direct . | {'scope': 'all', 'row': '10', 'col': '3', 'col_other': 'n/a', 'criterion': 'equal', 'value': 'sony music direct', 'subset': None} | {'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'label', 'sony music direct'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose label record fuzzily matches to sony music direct .', 'tostr': 'filter_eq { all_rows ; label ; sony music direct }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; label ; sony music direct } } = true', 'tointer': 'select the rows whose label record fuzzily matches to sony music direct . there is only one such row in the table .'} | only { filter_eq { all_rows ; label ; sony music direct } } = true | select the rows whose label record fuzzily matches to sony music direct . there is only one such row in the table . | 2 | 2 | {'only_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, 'label_4': 4, 'sony music direct_5': 5} | {'only_1': 'only', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'label_4': 'label', 'sony music direct_5': 'sony music direct'} | {'only_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'label_4': [0], 'sony music direct_5': [0]} | ['region', 'date', 'label', 'format', 'catalog'] | [['japan', 'april 25 , 1984', 'alfa records', 'stereo lp', 'alr - 28055'], ['japan', 'may 25 , 1984', 'alfa records', 'cd', '38xa - 12'], ['japan', 'january 25 , 1987', 'alfa records', 'cd', '32xa - 116'], ['japan', 'march 21 , 1992', 'alfa records', 'cd', 'alca - 281'], ['japan', 'august 31 , 1994', 'alfa records', 'cd', 'alca - 9011'], ['japan', 'august 29 , 1998', 'alfa records', 'cd', 'alca - 9206'], ['japan', 'december 6 , 2000', 'toshiba emi', 'cd', 'toct - 10752'], ['japan', 'january 23 , 2002', 'village records', 'ed remaster cd', 'vrcl - 2211'], ['japan', 'february 14 , 2002', 'village records', 'ed remaster cd', 'vrcl - 2231'], ['japan', 'may 27 , 2009', 'sony music direct', 'ed remaster cd', 'mhcl - 20013']] |
religion in eritrea | https://en.wikipedia.org/wiki/Religion_in_Eritrea | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16806446-2.html.csv | comparative | the tigrigna ehtnic group has a larger percentage of christians than the saho ethnic group . | {'row_1': '1', 'row_2': '3', 'col': '5', 'col_other': '1', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'ethnic group', 'tigrigna'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose ethnic group record fuzzily matches to tigrigna .', 'tostr': 'filter_eq { all_rows ; ethnic group ; tigrigna }'}, 'christians'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; ethnic group ; tigrigna } ; christians }', 'tointer': 'select the rows whose ethnic group record fuzzily matches to tigrigna . take the christians record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'ethnic group', 'saho'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose ethnic group record fuzzily matches to saho .', 'tostr': 'filter_eq { all_rows ; ethnic group ; saho }'}, 'christians'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; ethnic group ; saho } ; christians }', 'tointer': 'select the rows whose ethnic group record fuzzily matches to saho . take the christians record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; ethnic group ; tigrigna } ; christians } ; hop { filter_eq { all_rows ; ethnic group ; saho } ; christians } } = true', 'tointer': 'select the rows whose ethnic group record fuzzily matches to tigrigna . take the christians record of this row . select the rows whose ethnic group record fuzzily matches to saho . take the christians record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; ethnic group ; tigrigna } ; christians } ; hop { filter_eq { all_rows ; ethnic group ; saho } ; christians } } = true | select the rows whose ethnic group record fuzzily matches to tigrigna . take the christians record of this row . select the rows whose ethnic group record fuzzily matches to saho . take the christians 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, 'ethnic group_7': 7, 'tigrigna_8': 8, 'christians_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'ethnic group_11': 11, 'saho_12': 12, 'christians_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', 'ethnic group_7': 'ethnic group', 'tigrigna_8': 'tigrigna', 'christians_9': 'christians', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'ethnic group_11': 'ethnic group', 'saho_12': 'saho', 'christians_13': 'christians'} | {'greater_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'ethnic group_7': [0], 'tigrigna_8': [0], 'christians_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'ethnic group_11': [1], 'saho_12': [1], 'christians_13': [3]} | ['ethnic group', 'main regions', 'population', 'percentage of total population', 'christians', 'muslims', 'other'] | [['tigrigna', 'maekel region , debub region', '3319680', '57 %', '53 %', '44 %', '1 %'], ['tigre', 'gash - barka region , anseba region , maekel region', '1630720', '28 %', '6 %', '90 %', '4 %'], ['saho', 'northern red sea region , debub region', '232960', '4 %', '7 %', '93 %', 'n / a'], ['kunama', 'gash - barka region', '174720', '3 %', '41 %', '23 %', '36 %'], ['afar', 'southern red sea region', '174720', '3 %', '2 %', '98 %', 'n / a'], ['bilen', 'anseba region', '116480', '2 %', '48 %', '47 %', '5 %'], ['nara', 'gash - barka region', '58240', '1 %', '14 %', '85 %', '1 %'], ['beja', 'gash - barka region , anseba region', '58240', '1 %', '1 %', '98 %', '1 %'], ['rashaida', 'northern red sea region', '58.240', '1 %', 'n / a', '99 %', 'na']] |
list of kim possible episodes | https://en.wikipedia.org/wiki/List_of_Kim_Possible_episodes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2623498-4.html.csv | comparative | the episode dimension twist originally aired before the episode entitled team possible . | {'row_1': '6', 'row_2': '10', 'col': '6', 'col_other': '3', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'title', 'dimension twist'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose title record fuzzily matches to dimension twist .', 'tostr': 'filter_eq { all_rows ; title ; dimension twist }'}, 'original air date'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; title ; dimension twist } ; original air date }', 'tointer': 'select the rows whose title record fuzzily matches to dimension twist . take the original air date record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'title', 'team impossible'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose title record fuzzily matches to team impossible .', 'tostr': 'filter_eq { all_rows ; title ; team impossible }'}, 'original air date'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; title ; team impossible } ; original air date }', 'tointer': 'select the rows whose title record fuzzily matches to team impossible . take the original air date record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; title ; dimension twist } ; original air date } ; hop { filter_eq { all_rows ; title ; team impossible } ; original air date } } = true', 'tointer': 'select the rows whose title record fuzzily matches to dimension twist . take the original air date record of this row . select the rows whose title record fuzzily matches to team impossible . take the original air date record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; title ; dimension twist } ; original air date } ; hop { filter_eq { all_rows ; title ; team impossible } ; original air date } } = true | select the rows whose title record fuzzily matches to dimension twist . take the original air date record of this row . select the rows whose title record fuzzily matches to team impossible . take the original air 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, 'title_7': 7, 'dimension twist_8': 8, 'original air date_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'title_11': 11, 'team impossible_12': 12, 'original air 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', 'title_7': 'title', 'dimension twist_8': 'dimension twist', 'original air date_9': 'original air date', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'title_11': 'title', 'team impossible_12': 'team impossible', 'original air date_13': 'original air date'} | {'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'title_7': [0], 'dimension twist_8': [0], 'original air date_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'title_11': [1], 'team impossible_12': [1], 'original air date_13': [3]} | ['episode', 'season episode', 'title', 'directed by', 'written by', 'original air date', 'prod code'] | [['52', '1', 'steal wheels', 'steve loter', 'brian swenlin', 'september 25 , 2004', '301'], ['53', '2', 'emotion sickness', 'steve loter', 'brian swenlin', 'october 15 , 2004', '302'], ['54', '3', 'bonding', 'steve loter', 'john behnke & rob humphrey', 'october 22 , 2004', '303'], ['55', '4', 'bad boy', 'steve loter', 'nicole dubuc', 'january 14 , 2005', '304'], ['56', '5', 'showdown at the crooked d', 'steve loter', 'mark palmer', 'march 25 , 2005', '229'], ['57', '6', 'dimension twist', 'steve loter', 'tracy berna', 'april 1 , 2005', '308'], ['58a', '7a', 'overdue', 'steve loter', 'jim peterson & brian swenlin', 'april 15 , 2005', '309a'], ['58b', '7b', 'roachie', 'steve loter', 'jim peterson & brian swenlin', 'april 15 , 2005', '309b'], ['59', '8', 'rappin ™ drakken', 'steve loter', 'mark mccorkle & bob schooley', 'june 25 , 2005', '311'], ['60', '9', 'team impossible', 'steve loter', 'john behnke & rob humphrey', 'august 26 , 2005', '313'], ['61', '10', 'gorilla fist', 'steve loter', 'mark mccorkle & bob schooley', 'november 18 , 2005', '312'], ['62', '11', 'and the mole rat will be cgi', 'steve loter', 'mark drop', 'june 10 , 2006', '310']] |
greg sacks | https://en.wikipedia.org/wiki/Greg_Sacks | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2308381-1.html.csv | superlative | greg sacks had his highest ever total winnings in the year 1994 . | {'scope': 'all', 'col_superlative': '9', 'row_superlative': '9', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'winnings'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; winnings }'}, 'year'], 'result': '1994', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; winnings } ; year }'}, '1994'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; winnings } ; year } ; 1994 } = true', 'tointer': 'select the row whose winnings record of all rows is maximum . the year record of this row is 1994 .'} | eq { hop { argmax { all_rows ; winnings } ; year } ; 1994 } = true | select the row whose winnings record of all rows is maximum . the year record of this row is 1994 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'num_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'winnings_5': 5, 'year_6': 6, '1994_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'num_hop_1': 'num_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'winnings_5': 'winnings', 'year_6': 'year', '1994_7': '1994'} | {'eq_2': [3], 'result_3': [], 'num_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'winnings_5': [0], 'year_6': [1], '1994_7': [2]} | ['year', 'starts', 'wins', 'top 5', 'top 10', 'poles', 'avg start', 'avg finish', 'winnings', 'position', 'team ( s )'] | [['1983', '5', '0', '0', '0', '0', '25.6', '30.4', '8060', '47th', '5 sacks & sons'], ['1984', '29', '0', '0', '1', '0', '24.3', '25.1', '75183', '19th', '51 sacks & sons'], ['1986', '8', '0', '0', '1', '0', '22.4', '30.4', '64810', '41st', '10 digard motorsports'], ['1987', '16', '0', '0', '0', '0', '23.6', '29.8', '54815', '33rd', '50 dingman brothers racing'], ['1990', '16', '0', '2', '4', '1', '18.6', '20.8', '216148', '32nd', '17 / 18 / 46 hendrick motorsports'], ['1991', '11', '0', '0', '0', '0', '27.5', '30.4', '84215', '39th', '18 daytona speed inc 47 close racing'], ['1992', '20', '0', '0', '0', '0', '23.5', '25.1', '178120', '30th', '41 larry hedrick motorsports'], ['1993', '19', '0', '0', '1', '0', '24.3', '24.2', '168055', '35th', '9 melling racing 68 tristar motorsports'], ['1994', '31', '0', '0', '3', '1', '19.7', '27.0', '411728', '31st', '77 us motorsports inc'], ['1998', '7', '0', '0', '0', '0', '23.6', '35.3', '296880', '53rd', '98 yarborough - burdette motorsports'], ['2004', '3', '0', '0', '0', '0', '36.3', '41.7', '154100', '71st', '13 daytona speed inc']] |
list of gary unmarried episodes | https://en.wikipedia.org/wiki/List_of_Gary_Unmarried_episodes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-24781886-3.html.csv | aggregation | from 2009 to 2010,111.2 million viewers saw gary unmarried episodes . | {'scope': 'all', 'col': '6', 'type': 'sum', 'result': '111.2', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'viewers'], 'result': '111.2', 'ind': 0, 'tostr': 'sum { all_rows ; viewers }'}, '111.2'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; viewers } ; 111.2 } = true', 'tointer': 'the sum of the viewers record of all rows is 111.2 .'} | round_eq { sum { all_rows ; viewers } ; 111.2 } = true | the sum of the viewers record of all rows is 111.2 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'viewers_4': 4, '111.2_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'viewers_4': 'viewers', '111.2_5': '111.2'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'viewers_4': [0], '111.2_5': [1]} | ['total', '-', 'title', 'director', 'writer ( s )', 'viewers', 'air date', 'production code'] | [['21', '1', 'gary has a dream', 'james burrows', 'mark gross', '7.37', 'september 23 , 2009', '201'], ['22', '2', 'gary promises too much', 'james burrows', 'sally bradford', '7.08', 'september 30 , 2009', '203'], ['23', '3', "gary 's demo", 'james burrows', 'wil calhoun', '7.17', 'october 7 , 2009', '202'], ['24', '4', 'gary shoots fish in a barrel', 'james burrows', 'ira ungerleider', '7.38', 'october 14 , 2009', '204'], ['25', '5', 'gary on the air', 'james burrows', 'rob deshotel', '7.12', 'october 21 , 2009', '205'], ['26', '6', 'gary tries to do it all', 'james burrows', 'bill daly', '6.29', 'november 4 , 2009', '206'], ['27', '7', "gary and allison 's friend", 'james burrows', 'julie bean', '7.70', 'november 11 , 2009', '207'], ['28', '8', 'gary apologizes', 'james burrows', 'jill cargerman', '7.17', 'november 18 , 2009', '208'], ['29', '9', 'gary keeps a secret', 'james burrows', 'brian keith etheridge', '6.80', 'november 25 , 2009', '209'], ['30', '10', 'gary gives sasha his full attention', 'james burrows', 'mark gross', '7.16', 'december 9 , 2009', '210'], ['31', '11', 'gary is a boat guy', 'james burrows', 'wil calhoun', '7.92', 'december 16 , 2009', '211'], ['32', '12', 'gary feels tom slipping away', 'james burrows', 'kevin lappin', '5.80', 'january 13 , 2010', '212'], ['33', '13', 'gary has to choose', 'james burrows', 'sally bradford', '5.89', 'january 20 , 2010', '213'], ['34', '14', 'gary lowers the bar', 'james burrows', 'jill cargerman', '7.50', 'february 10 , 2010', '214'], ['35', '15', "gary 's big mouth", 'james burrows', 'bill daly', '6.02', 'march 3 , 2010', '215'], ['36', '16', 'gary tries to find something for mitch', 'james burrows', 'sam johnson', '6.83', 'march 10 , 2010', '216']] |
1966 mexican grand prix | https://en.wikipedia.org/wiki/1966_Mexican_Grand_Prix | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1122361-1.html.csv | count | there were 3 drivers with a +1 lap completion time during the 1966 mexican grand prix . | {'scope': 'all', 'criterion': 'equal', 'value': '+1 lap', 'result': '3', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'time / retired', '+1 lap'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose time / retired record fuzzily matches to +1 lap .', 'tostr': 'filter_eq { all_rows ; time / retired ; +1 lap }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; time / retired ; +1 lap } }', 'tointer': 'select the rows whose time / retired record fuzzily matches to +1 lap . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; time / retired ; +1 lap } } ; 3 } = true', 'tointer': 'select the rows whose time / retired record fuzzily matches to +1 lap . the number of such rows is 3 .'} | eq { count { filter_eq { all_rows ; time / retired ; +1 lap } } ; 3 } = true | select the rows whose time / retired record fuzzily matches to +1 lap . 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, 'time / retired_5': 5, '+1 lap_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', 'time / retired_5': 'time / retired', '+1 lap_6': '+1 lap', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'time / retired_5': [0], '+1 lap_6': [0], '3_7': [2]} | ['driver', 'constructor', 'laps', 'time / retired', 'grid'] | [['john surtees', 'cooper - maserati', '65', '2:06:35.34', '1'], ['jack brabham', 'brabham - repco', '65', '+ 7.88', '4'], ['denny hulme', 'brabham - repco', '64', '+ 1 lap', '6'], ['richie ginther', 'honda', '64', '+ 1 lap', '3'], ['dan gurney', 'eagle - climax', '64', '+ 1 lap', '9'], ['jo bonnier', 'cooper - maserati', '63', '+ 2 laps', '12'], ['peter arundell', 'lotus - brm', '61', '+ 4 laps', '17'], ['ronnie bucknum', 'honda', '60', '+ 5 laps', '13'], ['pedro rodríguez', 'lotus - brm', '49', 'differential', '8'], ['bruce mclaren', 'mclaren - ford', '40', 'engine', '14'], ['jo siffert', 'cooper - maserati', '33', 'suspension', '11'], ['jochen rindt', 'cooper - maserati', '32', 'suspension', '5'], ['innes ireland', 'brm', '28', 'transmission', '16'], ['jackie stewart', 'brm', '26', 'oil leak', '10'], ['bob bondurant', 'eagle - weslake', '24', 'fuel system', '18'], ['graham hill', 'brm', '18', 'engine', '7'], ['jim clark', 'lotus - brm', '9', 'gearbox', '2'], ['moisés solana', 'cooper - maserati', '9', 'overheating', '15']] |
michigan wolverines men 's ice hockey | https://en.wikipedia.org/wiki/Michigan_Wolverines_men%27s_ice_hockey | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-22165661-3.html.csv | superlative | the michigan wolverine 's men 's ice hockey team experienced the highest goal differential in a championship game in 1999 's championship game . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '4', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'score'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; score }'}, 'tournament'], 'result': '1999', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; score } ; tournament }'}, '1999'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; score } ; tournament } ; 1999 } = true', 'tointer': 'select the row whose score record of all rows is maximum . the tournament record of this row is 1999 .'} | eq { hop { argmax { all_rows ; score } ; tournament } ; 1999 } = true | select the row whose score record of all rows is maximum . the tournament record of this row is 1999 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'num_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'score_5': 5, 'tournament_6': 6, '1999_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'num_hop_1': 'num_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'score_5': 'score', 'tournament_6': 'tournament', '1999_7': '1999'} | {'eq_2': [3], 'result_3': [], 'num_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'score_5': [0], 'tournament_6': [1], '1999_7': [2]} | ['tournament', 'conference', 'championship game opponent', 'score', 'location', 'head coach'] | [['1994', 'ccha', 'lake superior state', '3 - 0', 'joe louis arena detroit , mi', 'red berenson'], ['1996', 'ccha', 'lake superior state', '4 - 3', 'joe louis arena detroit , mi', 'red berenson'], ['1997', 'ccha', 'michigan state', '3 - 1', 'joe louis arena detroit , mi', 'red berenson'], ['1999', 'ccha', 'northern michigan', '5 - 1', 'joe louis arena detroit , mi', 'red berenson'], ['2002', 'ccha', 'michigan state', '3 - 2', 'joe louis arena detroit , mi', 'red berenson'], ['2003', 'ccha', 'ferris state', '5 - 3', 'joe louis arena detroit , mi', 'red berenson'], ['2005', 'ccha', 'ohio state', '4 - 2', 'joe louis arena detroit , mi', 'red berenson'], ['2008', 'ccha', 'miami university', '2 - 1', 'joe louis arena detroit , mi', 'red berenson']] |
1910 in brazilian football | https://en.wikipedia.org/wiki/1910_in_Brazilian_football | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15419242-1.html.csv | ordinal | americano - sp recorded the 2nd highest difference during the 1910 brazilian football season . | {'row': '2', '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': 'americano - sp', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; difference ; 2 } ; team }'}, 'americano - sp'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; difference ; 2 } ; team } ; americano - sp } = true', 'tointer': 'select the row whose difference record of all rows is 2nd maximum . the team record of this row is americano - sp .'} | eq { hop { nth_argmax { all_rows ; difference ; 2 } ; team } ; americano - sp } = true | select the row whose difference record of all rows is 2nd maximum . the team record of this row is americano - sp . | 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, 'americano - sp_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', 'americano - sp_8': 'americano - sp'} | {'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], 'americano - sp_8': [2]} | ['position', 'team', 'points', 'played', 'drawn', 'lost', 'against', 'difference'] | [['1', 'aa das palmeiras', '18', '10', '0', '1', '12', '31'], ['2', 'americano - sp', '16', '10', '0', '2', '18', '7'], ['3', 'são paulo athletic', '11', '10', '1', '4', '26', '- 2'], ['4', 'paulistano', '8', '10', '2', '5', '17', '2'], ['5', 'ypiranga - sp', '4', '10', '2', '7', '32', '- 21'], ['6', 'germnia', '3', '10', '1', '8', '31', '- 17']] |
2007 - 08 crewe alexandra f.c. season | https://en.wikipedia.org/wiki/2007%E2%80%9308_Crewe_Alexandra_F.C._season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12964478-4.html.csv | unique | bopp was the only club to win an award from germany . | {'scope': 'all', 'row': '3', 'col': '2', 'col_other': '3', 'criterion': 'equal', 'value': 'ger', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'ger'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose country record fuzzily matches to ger .', 'tostr': 'filter_eq { all_rows ; country ; ger }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; country ; ger } }', 'tointer': 'select the rows whose country record fuzzily matches to ger . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'ger'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose country record fuzzily matches to ger .', 'tostr': 'filter_eq { all_rows ; country ; ger }'}, 'name'], 'result': 'bopp', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; country ; ger } ; name }'}, 'bopp'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; country ; ger } ; name } ; bopp }', 'tointer': 'the name record of this unqiue row is bopp .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; country ; ger } } ; eq { hop { filter_eq { all_rows ; country ; ger } ; name } ; bopp } } = true', 'tointer': 'select the rows whose country record fuzzily matches to ger . there is only one such row in the table . the name record of this unqiue row is bopp .'} | and { only { filter_eq { all_rows ; country ; ger } } ; eq { hop { filter_eq { all_rows ; country ; ger } ; name } ; bopp } } = true | select the rows whose country record fuzzily matches to ger . there is only one such row in the table . the name record of this unqiue row is bopp . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'country_7': 7, 'ger_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'name_9': 9, 'bopp_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'country_7': 'country', 'ger_8': 'ger', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'name_9': 'name', 'bopp_10': 'bopp'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'country_7': [0], 'ger_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'name_9': [2], 'bopp_10': [3]} | ['date', 'country', 'name', 'award', 'notes'] | [['13 aug 2007', 'eng', 'g s roberts', 'team of the week', 'source'], ['20 aug 2007', 'eng', 'woodards', 'team of the week', 'source'], ['10 sep 2007', 'ger', 'bopp', 'team of the week', 'source'], ['24 sep 2007', 'eng', 'williams', 'team of the week', 'source'], ['1 oct 2007', 'eng', 'jones', 'team of the week', 'source'], ['22 oct 2007', 'eng', 'lowe', 'team of the week', 'source'], ['5 nov 2007', 'eng', 'moore', 'team of the week', 'source'], ['19 nov 2007', 'eng', 'woodards', 'team of the week ( 2 )', 'source'], ['10 dec 2007', 'eng', 'woodards', 'team of the week ( 3 )', 'source'], ['28 jan 2008', 'eng', 'williams', 'team of the week ( 2 )', 'source'], ['3 mar 2008', 'eng', 'williams', 'team of the week ( 3 )', 'source'], ['17 mar 2008', 'eng', "o'connor", 'team of the week', 'source']] |
maxus ( rocket ) | https://en.wikipedia.org/wiki/Maxus_%28rocket%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16003024-1.html.csv | aggregation | on average the rockets from maxus missions had an apogee at 645km . | {'scope': 'all', 'col': '5', 'type': 'average', 'result': '645', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'apogee'], 'result': '645', 'ind': 0, 'tostr': 'avg { all_rows ; apogee }'}, '645'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; apogee } ; 645 } = true', 'tointer': 'the average of the apogee record of all rows is 645 .'} | round_eq { avg { all_rows ; apogee } ; 645 } = true | the average of the apogee record of all rows is 645 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'apogee_4': 4, '645_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'apogee_4': 'apogee', '645_5': '645'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'apogee_4': [0], '645_5': [1]} | ['mission', 'date', 'launch site', 'motor', 'apogee'] | [['maxus 1', '1991 may 8', 'esrange', 'castor 4b', '154 km'], ['maxus 1b', '1992 nov 8', 'esrange', 'castor 4b', '717 km'], ['maxus 2', '1995 nov 29', 'esrange', 'castor 4b', '706 km'], ['maxus 3', '1998 nov 24', 'esrange', 'castor 4b', '713 km'], ['maxus 4', '2001 apr 29', 'esrange', 'castor 4b', '704 km'], ['maxus 5', '2003 apr 1', 'esrange', 'castor 4b', '703 km'], ['maxus 6', '2004 nov 22', 'esrange', 'castor 4b', '707 km'], ['maxus 7', '2006 may 2', 'esrange', 'castor 4b', '705 km'], ['maxus 8', '2010 march 26', 'esrange', 'castor 4b', '703 km']] |
list of sumo record holders | https://en.wikipedia.org/wiki/List_of_sumo_record_holders | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17634218-19.html.csv | aggregation | the average totals for the sumo record holders is 27.42 . | {'scope': 'all', 'col': '2', 'type': 'average', 'result': '27.42', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'total'], 'result': '27.42', 'ind': 0, 'tostr': 'avg { all_rows ; total }'}, '27.42'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; total } ; 27.42 } = true', 'tointer': 'the average of the total record of all rows is 27.42 .'} | round_eq { avg { all_rows ; total } ; 27.42 } = true | the average of the total record of all rows is 27.42 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'total_4': 4, '27.42_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'total_4': 'total', '27.42_5': '27.42'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'total_4': [0], '27.42_5': [1]} | ['name', 'total', 'first', 'last', 'highest rank'] | [['kotonishiki', '34', 'september 1990', 'september 1999', 'sekiwake'], ['kaiō', '32', 'may 1994', 'july 2000', 'ōzeki'], ['musōyama', '31', 'march 1994', 'september 2000', 'ōzeki'], ['hasegawa', '30', 'november 1965', 'september 1974', 'sekiwake'], ['kotomitsuki', '30', 'january 2001', 'july 2007', 'ōzeki'], ['akinoshima', '27', 'november 1988', 'september 2000', 'sekiwake'], ['takamiyama', '27', 'november 1969', 'september 1982', 'sekiwake'], ['takatōriki', '26', 'may 1991', 'may 2000', 'sekiwake'], ['wakanosato', '26', 'november 2000', 'september 2005', 'sekiwake'], ['daikirin', '22', 'november 1966', 'september 1970', 'ōzeki'], ['tochiazuma ii', '22', 'july 1997', 'january 2005', 'ōzeki'], ['kisenosato', '22', 'july 2006', 'september 2011', 'ōzeki']] |
list of united states national ice hockey team rosters | https://en.wikipedia.org/wiki/List_of_United_States_national_ice_hockey_team_rosters | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15715109-14.html.csv | ordinal | al iafrate was the second tallest player on the united states ice hockey rosters . | {'row': '6', 'col': '4', 'order': '2', 'col_other': '3', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'height ( cm )', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; height ( cm ) ; 2 }'}, 'name'], 'result': 'al iafrate', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; height ( cm ) ; 2 } ; name }'}, 'al iafrate'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; height ( cm ) ; 2 } ; name } ; al iafrate } = true', 'tointer': 'select the row whose height ( cm ) record of all rows is 2nd maximum . the name record of this row is al iafrate .'} | eq { hop { nth_argmax { all_rows ; height ( cm ) ; 2 } ; name } ; al iafrate } = true | select the row whose height ( cm ) record of all rows is 2nd maximum . the name record of this row is al iafrate . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'height (cm)_5': 5, '2_6': 6, 'name_7': 7, 'al iafrate_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'height (cm)_5': 'height ( cm )', '2_6': '2', 'name_7': 'name', 'al iafrate_8': 'al iafrate'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'height (cm)_5': [0], '2_6': [0], 'name_7': [1], 'al iafrate_8': [2]} | ['position', 'jersey', 'name', 'height ( cm )', 'weight ( kg )', 'birthdate', 'birthplace', 'previous club / team'] | [['g', '29', 'marc behrend', '185', '84', '11 january 1961', 'madison , wisconsin', 'university of wisconsin'], ['g', '1', 'bob mason', '185', '82', '22 april 1961', 'international falls , minnesota', 'university of minnesota - duluth'], ['d', '21', 'chris chelios', '185', '86', '25 january 1962', 'evergreen park , illinois', 'university of wisconsin'], ['d', '6', 'mark fusco', '175', '82', '12 march 1961', 'woburn , massachusetts', 'harvard university'], ['d', '22', 'tom hirsch', '193', '95', '27 january 1963', 'minneapolis , minnesota', 'university of minnesota'], ['d', '18', 'al iafrate', '190', '86', '21 march 1966', 'dearborn , michigan', 'belleville bulls ( ohl )'], ['d', '28', 'david h jensen', '185', '86', '3 may 1961', 'minneapolis , minnesota', 'birmingham south stars ( chl )'], ['f', '17', 'scott bjugstad', '185', '84', '2 june 1961', 'minneapolis , minnesota', 'university of minnesota'], ['f', '13', 'bob brooke', '188', '94', '18 december 1960', 'melrose , massachusetts', 'yale university'], ['f', '9', 'scott fusco', '175', '79', '21 january 1963', 'woburn , massachusetts', 'harvard university'], ['f', '10', 'steve griffith', '178', '84', '12 march 1961', 'saint paul , minnesota', 'university of minnesota'], ['f', '19', 'paul guay', '183', '88', '2 september 1963', 'woonsocket , rhode island', 'providence college'], ['f', '23', 'john harrington', '178', '82', '24 may 1957', 'virginia , minnesota', 'university of minnesota - duluth'], ['f', '7', 'david a jensen', '185', '79', '19 august 1965', 'newton , massachusetts', 'belmont hill academy ( isl )'], ['f', '25', 'mark kumpel', '183', '86', 'march 7 , 1961 in', 'wakefield , massachusetts', 'university of lowell'], ['f', '16', 'pat lafontaine', '178', '83', '22 february 1965', 'st louis , missouri', 'verdun juniors ( qmjhl )'], ['f', '26', 'corey millen', '170', '75', '30 march 1964', 'duluth , minnesota', 'university of minnesota'], ['f', '12', 'ed olczyk', '185', '89', '16 august 1966', 'chicago , illinois', 'stratford cullitons ( gojhl )'], ['f', '27', 'gary sampson', '183', '86', '24 august 1959', 'atikokan , ontario', 'boston college'], ['f', '8', 'phil verchota', '188', '89', '28 december 1956', 'preston , minnesota', 'university of minnesota']] |
2001 arizona cardinals season | https://en.wikipedia.org/wiki/2001_Arizona_Cardinals_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16434134-1.html.csv | unique | tevita ofahengaue was the only player that was drafted by the cardinals from brigham young university . | {'scope': 'all', 'row': '10', 'col': '5', 'col_other': '3', 'criterion': 'equal', 'value': 'brigham young university', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'school / club team', 'brigham young university'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose school / club team record fuzzily matches to brigham young university .', 'tostr': 'filter_eq { all_rows ; school / club team ; brigham young university }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; school / club team ; brigham young university } }', 'tointer': 'select the rows whose school / club team record fuzzily matches to brigham young university . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'school / club team', 'brigham young university'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose school / club team record fuzzily matches to brigham young university .', 'tostr': 'filter_eq { all_rows ; school / club team ; brigham young university }'}, 'player'], 'result': 'tevita ofahengaue', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; school / club team ; brigham young university } ; player }'}, 'tevita ofahengaue'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; school / club team ; brigham young university } ; player } ; tevita ofahengaue }', 'tointer': 'the player record of this unqiue row is tevita ofahengaue .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; school / club team ; brigham young university } } ; eq { hop { filter_eq { all_rows ; school / club team ; brigham young university } ; player } ; tevita ofahengaue } } = true', 'tointer': 'select the rows whose school / club team record fuzzily matches to brigham young university . there is only one such row in the table . the player record of this unqiue row is tevita ofahengaue .'} | and { only { filter_eq { all_rows ; school / club team ; brigham young university } } ; eq { hop { filter_eq { all_rows ; school / club team ; brigham young university } ; player } ; tevita ofahengaue } } = true | select the rows whose school / club team record fuzzily matches to brigham young university . there is only one such row in the table . the player record of this unqiue row is tevita ofahengaue . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'school / club team_7': 7, 'brigham young university_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'player_9': 9, 'tevita ofahengaue_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'school / club team_7': 'school / club team', 'brigham young university_8': 'brigham young university', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'player_9': 'player', 'tevita ofahengaue_10': 'tevita ofahengaue'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'school / club team_7': [0], 'brigham young university_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'player_9': [2], 'tevita ofahengaue_10': [3]} | ['round', 'pick', 'player', 'position', 'school / club team'] | [['1', '2', 'leonard davis', 'tackle', 'texas'], ['2', '34', 'kyle vanden bosch', 'defensive end', 'nebraska'], ['2', '54', 'michael stone', 'defensive back', 'memphis'], ['3', '64', 'adrian wilson ( american football )', 'defensive back', 'north carolina state'], ['4', '98', 'bill gramatica', 'kicker', 'south florida'], ['4', '123', 'marcus bell', 'defensive tackle', 'memphis'], ['5', '133', 'mario fatafehi', 'defensive tackle', 'kansas state'], ['6', '166', 'bobby newcombe', 'wide receiver', 'nebraska'], ['7', '202', 'renaldo hill', 'defensive back', 'michigan state'], ['7', '246', 'tevita ofahengaue', 'tight end', 'brigham young university']] |
list of cities , towns and villages in vojvodina | https://en.wikipedia.org/wiki/List_of_cities%2C_towns_and_villages_in_Vojvodina | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2562572-12.html.csv | majority | the majorty of cities , towns , and villages in vojvodina have orthodox christianity as the dominant religion . | {'scope': 'all', 'col': '6', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'orthodox christianity', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'dominant religion ( 2002 )', 'orthodox christianity'], 'result': True, 'ind': 0, 'tointer': 'for the dominant religion ( 2002 ) records of all rows , most of them fuzzily match to orthodox christianity .', 'tostr': 'most_eq { all_rows ; dominant religion ( 2002 ) ; orthodox christianity } = true'} | most_eq { all_rows ; dominant religion ( 2002 ) ; orthodox christianity } = true | for the dominant religion ( 2002 ) records of all rows , most of them fuzzily match to orthodox christianity . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'dominant religion (2002)_3': 3, 'orthodox christianity_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'dominant religion (2002)_3': 'dominant religion ( 2002 )', 'orthodox christianity_4': 'orthodox christianity'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'dominant religion (2002)_3': [0], 'orthodox christianity_4': [0]} | ['settlement', 'cyrillic name other names', 'type', 'population ( 2011 )', 'largest ethnic group ( 2002 )', 'dominant religion ( 2002 )'] | [['bačka palanka', 'бачка паланка', 'town', '28239', 'serbs', 'orthodox christianity'], ['čelarevo', 'челарево', 'village', '4831', 'serbs', 'orthodox christianity'], ['despotovo', 'деспотово', 'village', '1853', 'serbs', 'orthodox christianity'], ['gajdobra', 'гајдобра', 'village', '2578', 'serbs', 'orthodox christianity'], ['karađorđevo', 'карађорђево', 'village', '738', 'serbs', 'orthodox christianity'], ['mladenovo', 'младеново', 'village', '2679', 'serbs', 'orthodox christianity'], ['neštin', 'нештин', 'village', '794', 'serbs', 'orthodox christianity'], ['nova gajdobra', 'нова гајдобра', 'village', '1220', 'serbs', 'orthodox christianity'], ['obrovac', 'обровац', 'village', '2944', 'serbs', 'orthodox christianity'], ['parage', 'параге', 'village', '921', 'serbs', 'orthodox christianity'], ['pivnice', 'пивнице ( slovak : pivnice )', 'village', '3337', 'slovaks', 'protestantism'], ['silbaš', 'силбаш', 'village', '2467', 'serbs', 'orthodox christianity'], ['tovariševo', 'товаришево', 'village', '2657', 'serbs', 'orthodox christianity']] |
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 | comparative | the prize money in 1982 was 60,000 higher than the prize money for 1983 . | {'row_1': '9', 'row_2': '8', 'col': '4', 'col_other': '1', 'relation': 'diff', 'record_mentioned': 'no', 'diff_result': {'diff_value': '60000', 'bigger': 'row1'}} | {'func': 'eq', 'args': [{'func': 'diff', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'year', '1982'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose year record fuzzily matches to 1982 .', 'tostr': 'filter_eq { all_rows ; year ; 1982 }'}, 'prize money'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; year ; 1982 } ; prize money }', 'tointer': 'select the rows whose year record fuzzily matches to 1982 . take the prize money record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'year', '1983'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose year record fuzzily matches to 1983 .', 'tostr': 'filter_eq { all_rows ; year ; 1983 }'}, 'prize money'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; year ; 1983 } ; prize money }', 'tointer': 'select the rows whose year record fuzzily matches to 1983 . take the prize money record of this row .'}], 'result': '60000', 'ind': 4, 'tostr': 'diff { hop { filter_eq { all_rows ; year ; 1982 } ; prize money } ; hop { filter_eq { all_rows ; year ; 1983 } ; prize money } }'}, '60000'], 'result': True, 'ind': 5, 'tostr': 'eq { diff { hop { filter_eq { all_rows ; year ; 1982 } ; prize money } ; hop { filter_eq { all_rows ; year ; 1983 } ; prize money } } ; 60000 } = true', 'tointer': 'select the rows whose year record fuzzily matches to 1982 . take the prize money record of this row . select the rows whose year record fuzzily matches to 1983 . take the prize money record of this row . the first record is 60000 larger than the second record .'} | eq { diff { hop { filter_eq { all_rows ; year ; 1982 } ; prize money } ; hop { filter_eq { all_rows ; year ; 1983 } ; prize money } } ; 60000 } = true | select the rows whose year record fuzzily matches to 1982 . take the prize money record of this row . select the rows whose year record fuzzily matches to 1983 . take the prize money record of this row . the first record is 60000 larger than the second record . | 6 | 6 | {'eq_5': 5, 'result_6': 6, 'diff_4': 4, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_7': 7, 'year_8': 8, '1982_9': 9, 'prize money_10': 10, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_11': 11, 'year_12': 12, '1983_13': 13, 'prize money_14': 14, '60000_15': 15} | {'eq_5': 'eq', 'result_6': 'true', 'diff_4': 'diff', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_7': 'all_rows', 'year_8': 'year', '1982_9': '1982', 'prize money_10': 'prize money', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_11': 'all_rows', 'year_12': 'year', '1983_13': '1983', 'prize money_14': 'prize money', '60000_15': '60000'} | {'eq_5': [6], 'result_6': [], 'diff_4': [5], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_7': [0], 'year_8': [0], '1982_9': [0], 'prize money_10': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_11': [1], 'year_12': [1], '1983_13': [1], 'prize money_14': [3], '60000_15': [5]} | ['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']] |
2009 masters tournament | https://en.wikipedia.org/wiki/2009_Masters_Tournament | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18812411-7.html.csv | aggregation | at the 2009 masters tournament , the average number of strokes to par was -5.94 . | {'scope': 'all', 'col': '5', 'type': 'average', 'result': '-5.94', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'to par'], 'result': '-5.94', 'ind': 0, 'tostr': 'avg { all_rows ; to par }'}, '-5.94'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; to par } ; -5.94 } = true', 'tointer': 'the average of the to par record of all rows is -5.94 .'} | round_eq { avg { all_rows ; to par } ; -5.94 } = true | the average of the to par record of all rows is -5.94 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'to par_4': 4, '-5.94_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'to par_4': 'to par', '-5.94_5': '-5.94'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'to par_4': [0], '-5.94_5': [1]} | ['place', 'player', 'country', 'score', 'to par'] | [['t1', 'ángel cabrera', 'argentina', '68 + 68 + 69 = 205', '- 11'], ['t1', 'kenny perry', 'united states', '68 + 67 + 70 = 205', '- 11'], ['3', 'chad campbell', 'united states', '65 + 70 + 72 = 207', '- 9'], ['4', 'jim furyk', 'united states', '66 + 74 + 68 = 208', '- 8'], ['5', 'steve stricker', 'united states', '72 + 69 + 68 = 209', '- 7'], ['t6', 'todd hamilton', 'united states', '68 + 70 + 72 = 210', '- 6'], ['t6', 'shingo katayama', 'japan', '67 + 73 + 70 = 210', '- 6'], ['t6', 'rory sabbatini', 'south africa', '73 + 67 + 70 = 210', '- 6'], ['9', 'tim clark', 'south africa', '68 + 71 + 72 = 211', '- 5'], ['t10', 'stephen ames', 'canada', '73 + 68 + 71 = 212', '- 4'], ['t10', 'anthony kim', 'united states', '75 + 65 + 72 = 212', '- 4'], ['t10', 'hunter mahan', 'united states', '66 + 75 + 71 = 212', '- 4'], ['t10', 'phil mickelson', 'united states', '73 + 68 + 71 = 212', '- 4'], ['t10', "sean o'hair", 'united states', '68 + 76 + 68 = 212', '- 4'], ['t10', 'ian poulter', 'england', '71 + 73 + 68 = 212', '- 4'], ['t10', 'lee westwood', 'england', '70 + 72 + 70 = 212', '- 4'], ['t10', 'tiger woods', 'united states', '70 + 72 + 70 = 212', '- 4']] |
mark mccumber | https://en.wikipedia.org/wiki/Mark_McCumber | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1598242-1.html.csv | unique | the anheuser - busch golf classic is the only tournament where the margin of victory was 3 strokes . | {'scope': 'all', 'row': '8', 'col': '4', 'col_other': '2', 'criterion': 'equal', 'value': '3 strokes', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'margin of victory', '3 strokes'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose margin of victory record fuzzily matches to 3 strokes .', 'tostr': 'filter_eq { all_rows ; margin of victory ; 3 strokes }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; margin of victory ; 3 strokes } }', 'tointer': 'select the rows whose margin of victory record fuzzily matches to 3 strokes . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'margin of victory', '3 strokes'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose margin of victory record fuzzily matches to 3 strokes .', 'tostr': 'filter_eq { all_rows ; margin of victory ; 3 strokes }'}, 'tournament'], 'result': 'anheuser - busch golf classic', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; margin of victory ; 3 strokes } ; tournament }'}, 'anheuser - busch golf classic'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; margin of victory ; 3 strokes } ; tournament } ; anheuser - busch golf classic }', 'tointer': 'the tournament record of this unqiue row is anheuser - busch golf classic .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; margin of victory ; 3 strokes } } ; eq { hop { filter_eq { all_rows ; margin of victory ; 3 strokes } ; tournament } ; anheuser - busch golf classic } } = true', 'tointer': 'select the rows whose margin of victory record fuzzily matches to 3 strokes . there is only one such row in the table . the tournament record of this unqiue row is anheuser - busch golf classic .'} | and { only { filter_eq { all_rows ; margin of victory ; 3 strokes } } ; eq { hop { filter_eq { all_rows ; margin of victory ; 3 strokes } ; tournament } ; anheuser - busch golf classic } } = true | select the rows whose margin of victory record fuzzily matches to 3 strokes . there is only one such row in the table . the tournament record of this unqiue row is anheuser - busch golf classic . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'margin of victory_7': 7, '3 strokes_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'tournament_9': 9, 'anheuser - busch golf classic_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'margin of victory_7': 'margin of victory', '3 strokes_8': '3 strokes', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'tournament_9': 'tournament', 'anheuser - busch golf classic_10': 'anheuser - busch golf classic'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'margin of victory_7': [0], '3 strokes_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'tournament_9': [2], 'anheuser - busch golf classic_10': [3]} | ['date', 'tournament', 'winning score', 'margin of victory', 'runner - up'] | [['mar 18 , 1979', 'doral - eastern open', '- 9 ( 67 + 71 + 69 + 72 = 279 )', '1 stroke', 'bill rogers'], ['jul 3 , 1983', 'western open', '- 4 ( 74 + 71 + 68 + 71 = 284 )', '1 stroke', 'tom watson'], ['oct 30 , 1983', 'pensacola open', '- 18 ( 68 + 68 + 65 + 65 = 266 )', '4 strokes', 'lon hinkle'], ['feb 24 , 1985', 'doral - eastern open', '- 4 ( 70 + 71 + 72 + 71 = 284 )', '1 stroke', 'tom kite'], ['jul 12 , 1987', 'anheuser - busch golf classic', '- 17 ( 65 + 69 + 67 + 66 = 267 )', '1 stroke', 'bobby clampett'], ['mar 27 , 1988', 'the players championship', '- 15 ( 65 + 72 + 67 + 69 = 273 )', '4 strokes', 'mike reid'], ['jul 3 , 1989', 'beatrice western open', '- 13 ( 68 + 67 + 71 + 69 = 275 )', 'playoff', 'peter jacobsen'], ['jul 10 , 1994', 'anheuser - busch golf classic', '- 17 ( 67 + 69 + 65 + 66 = 267 )', '3 strokes', 'glen day'], ['sep 25 , 1994', "hardee 's golf classic", '- 15 ( 66 + 67 + 65 + 67 = 265 )', '1 stroke', 'kenny perry'], ['oct 30 , 1994', 'the tour championship', '- 10 ( 66 + 71 + 69 + 68 = 274 )', 'playoff', 'fuzzy zoeller']] |
2008 cfl draft | https://en.wikipedia.org/wiki/2008_CFL_Draft | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16575609-5.html.csv | comparative | jon gott was picked sooner than paul woldu in the 2008 cfl draft . | {'row_1': '3', 'row_2': '4', 'col': '1', 'col_other': '3', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', 'jon gott'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose player record fuzzily matches to jon gott .', 'tostr': 'filter_eq { all_rows ; player ; jon gott }'}, 'pick'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; player ; jon gott } ; pick }', 'tointer': 'select the rows whose player record fuzzily matches to jon gott . take the pick record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', 'paul woldu'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose player record fuzzily matches to paul woldu .', 'tostr': 'filter_eq { all_rows ; player ; paul woldu }'}, 'pick'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; player ; paul woldu } ; pick }', 'tointer': 'select the rows whose player record fuzzily matches to paul woldu . take the pick record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; player ; jon gott } ; pick } ; hop { filter_eq { all_rows ; player ; paul woldu } ; pick } } = true', 'tointer': 'select the rows whose player record fuzzily matches to jon gott . take the pick record of this row . select the rows whose player record fuzzily matches to paul woldu . take the pick record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; player ; jon gott } ; pick } ; hop { filter_eq { all_rows ; player ; paul woldu } ; pick } } = true | select the rows whose player record fuzzily matches to jon gott . take the pick record of this row . select the rows whose player record fuzzily matches to paul woldu . take the pick 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, 'player_7': 7, 'jon gott_8': 8, 'pick_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'player_11': 11, 'paul woldu_12': 12, 'pick_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', 'player_7': 'player', 'jon gott_8': 'jon gott', 'pick_9': 'pick', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'player_11': 'player', 'paul woldu_12': 'paul woldu', 'pick_13': 'pick'} | {'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'player_7': [0], 'jon gott_8': [0], 'pick_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'player_11': [1], 'paul woldu_12': [1], 'pick_13': [3]} | ['pick', 'cfl team', 'player', 'position', 'college'] | [['33', 'hamilton tiger - cats', 'laurent lavigne masse', 'rec', 'laval'], ['34', 'edmonton eskimos', 'dante luciani', 'rec', 'laurier'], ['35', 'calgary stampeders', 'jon gott', 'ol', 'boise state'], ['36', 'montreal alouettes', 'paul woldu', 'db', 'saskatchewan'], ['37', 'toronto argonauts', 'richard zulys', 'ol', 'western'], ['38', 'bc lions', 'brady browne', 'db', 'manitoba'], ['39', 'winnipeg blue bombers', 'don oramasionwu', 'dl', 'manitoba'], ['40', 'saskatchewan roughriders', 'jeff zelinski', 'db', "saint mary 's"]] |
bombay jayashri | https://en.wikipedia.org/wiki/Bombay_Jayashri | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11203591-2.html.csv | unique | anti pettukundhuna is the only song by bombay jayashri to be directed by dharan . | {'scope': 'all', 'row': '10', 'col': '4', 'col_other': '2', 'criterion': 'equal', 'value': 'dharan', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'music director', 'dharan'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose music director record fuzzily matches to dharan .', 'tostr': 'filter_eq { all_rows ; music director ; dharan }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; music director ; dharan } }', 'tointer': 'select the rows whose music director record fuzzily matches to dharan . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'music director', 'dharan'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose music director record fuzzily matches to dharan .', 'tostr': 'filter_eq { all_rows ; music director ; dharan }'}, 'song title'], 'result': 'anti pettukundhuna', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; music director ; dharan } ; song title }'}, 'anti pettukundhuna'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; music director ; dharan } ; song title } ; anti pettukundhuna }', 'tointer': 'the song title record of this unqiue row is anti pettukundhuna .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; music director ; dharan } } ; eq { hop { filter_eq { all_rows ; music director ; dharan } ; song title } ; anti pettukundhuna } } = true', 'tointer': 'select the rows whose music director record fuzzily matches to dharan . there is only one such row in the table . the song title record of this unqiue row is anti pettukundhuna .'} | and { only { filter_eq { all_rows ; music director ; dharan } } ; eq { hop { filter_eq { all_rows ; music director ; dharan } ; song title } ; anti pettukundhuna } } = true | select the rows whose music director record fuzzily matches to dharan . there is only one such row in the table . the song title record of this unqiue row is anti pettukundhuna . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'music director_7': 7, 'dharan_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'song title_9': 9, 'anti pettukundhuna_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'music director_7': 'music director', 'dharan_8': 'dharan', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'song title_9': 'song title', 'anti pettukundhuna_10': 'anti pettukundhuna'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'music director_7': [0], 'dharan_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'song title_9': [2], 'anti pettukundhuna_10': [3]} | ['year', 'song title', 'movie', 'music director', 'co - singers'] | [['1997', 'sasivadane', 'iddaru', 'a r rahman', 'unni krishnan'], ['2001', 'manohara', 'cheli', 'harris jayaraj', 'solo'], ['2002', 'tiya tiyani kalalanu', 'sreeram', 'r p patnaik', 'solo'], ['2005', 'hrudayam ekkadunnadi', 'ghajini', 'harris jayaraj', 'harish raghavendra'], ['2005', 'aamani koyilanai', 'premikulu', 'sajan madhav', 'solo'], ['2006', 'vere maina anani', 'amma cheppindi', 'm m keeravani', 'solo'], ['2006', 'yentho dooram', 'amma cheppindi', 'm m keeravani', 'solo'], ['2006', 'ulike o chilake', 'jalakanta', 'harris jayaraj', 'karthik'], ['2007', 'banam', 'raghavan', 'harris jayaraj', 'harish raghavendra'], ['2008', 'anti pettukundhuna', '16 days', 'dharan', 'haricharan'], ['2008', 'enduko madi', 'nenu meeku telusa', 'achu', 'hemachandra'], ['2008', 'muddula muddula', 'salute', 'harris jayaraj', 'balram , sunitha sarathy'], ['2009', 'eenaadu ee samaram', 'eeenadu', 'shruthi hassan', 'kamal haasan'], ['2011', 'ee manchullo', 'rangam', 'harris jayaraj', 'sriram parthasarathy'], ['2012', 'vennelave', 'thuppakki', 'harris jayaraj', 'hariharan'], ['2013', 'kamalaasana', 'intinta annamaya', 'm m keeravani', 'solo']] |
dock jumping | https://en.wikipedia.org/wiki/Dock_jumping | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17371890-2.html.csv | unique | the only event that took place in feb was at the indianapolis boat , sport & travel show . | {'scope': 'all', 'row': '3', 'col': '1', 'col_other': '4', 'criterion': 'fuzzily_match', 'value': 'february', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', 'february'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose date record fuzzily matches to february .', 'tostr': 'filter_eq { all_rows ; date ; february }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; date ; february } }', 'tointer': 'select the rows whose date record fuzzily matches to february . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', 'february'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose date record fuzzily matches to february .', 'tostr': 'filter_eq { all_rows ; date ; february }'}, 'event'], 'result': 'indianapolis boat , sport & travel show', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; date ; february } ; event }'}, 'indianapolis boat , sport & travel show'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; date ; february } ; event } ; indianapolis boat , sport & travel show }', 'tointer': 'the event record of this unqiue row is indianapolis boat , sport & travel show .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; date ; february } } ; eq { hop { filter_eq { all_rows ; date ; february } ; event } ; indianapolis boat , sport & travel show } } = true', 'tointer': 'select the rows whose date record fuzzily matches to february . there is only one such row in the table . the event record of this unqiue row is indianapolis boat , sport & travel show .'} | and { only { filter_eq { all_rows ; date ; february } } ; eq { hop { filter_eq { all_rows ; date ; february } ; event } ; indianapolis boat , sport & travel show } } = true | select the rows whose date record fuzzily matches to february . there is only one such row in the table . the event record of this unqiue row is indianapolis boat , sport & travel show . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'date_7': 7, 'february_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'event_9': 9, 'indianapolis boat , sport & travel show_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'date_7': 'date', 'february_8': 'february', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'event_9': 'event', 'indianapolis boat , sport & travel show_10': 'indianapolis boat , sport & travel show'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'date_7': [0], 'february_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'event_9': [2], 'indianapolis boat , sport & travel show_10': [3]} | ['date', 'distance', 'handler', 'event', 'location'] | [['7 july 2000', 'ft4in ( m )', 'beth gutteridge', 'espn great outdoor games', 'lake placid , ny'], ['8 july 2001', 'ft1in ( m )', 'mike wallace', 'espn great outdoor games', 'lake placid , ny'], ['20 february 2002', 'ft3in ( m )', 'mike jackson', 'indianapolis boat , sport & travel show', 'indianapolis , in'], ['1 may 2002', 'ft4in ( m )', 'john kline', 'espn2 super retriever series', 'northfield , mn'], ['6 july 2002', 'ft6in ( m )', 'mike jackson', 'espn great outdoor games', 'lake placid , ny'], ['7 august 2005', 'ft5in ( m )', 'kevin meese', 'bass pro shops', 'baltimore , md'], ['21 august 2005', 'ft7in ( m )', 'kevin meese', "big nickle time cabela 's", 'hamburg , pa'], ['9 october 2005', 'ft10in ( m )', 'kevin meese', 'bass pro shops', 'baltimore , md'], ['30 may 2010', 'ft11 .59 in ( m )', 'rande murphy', 'super retriever series crown championship', 'little rock , ar'], ['11 july 2010', 'ft1in ( m )', 'melissa ness', '2010 ukc premier', 'richmond , in'], ['29 may 2011', 'ft7in ( m )', 'tony lampert', 'super retriever series crown championship', 'little rock , ar'], ['07 oct 2011', 'ft11in ( m )', 'tony lampert', 'david letterman show , october 7 2011', 'new york , ny']] |
independent school league ( boston area ) | https://en.wikipedia.org/wiki/Independent_School_League_%28Boston_Area%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2439728-1.html.csv | count | there are 2 schools of the independent school league ( boston area ) are not located in massachusetts . | {'scope': 'all', 'criterion': 'not_equal', 'value': 'ma', 'result': '2', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_not_eq', 'args': ['all_rows', 'location', 'ma'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose location record does not match to ma .', 'tostr': 'filter_not_eq { all_rows ; location ; ma }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_not_eq { all_rows ; location ; ma } }', 'tointer': 'select the rows whose location record does not match to ma . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_not_eq { all_rows ; location ; ma } } ; 2 } = true', 'tointer': 'select the rows whose location record does not match to ma . the number of such rows is 2 .'} | eq { count { filter_not_eq { all_rows ; location ; ma } } ; 2 } = true | select the rows whose location record does not match to ma . the number of such rows is 2 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_not_eq_0': 0, 'all_rows_4': 4, 'location_5': 5, 'ma_6': 6, '2_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_not_eq_0': 'filter_str_not_eq', 'all_rows_4': 'all_rows', 'location_5': 'location', 'ma_6': 'ma', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_not_eq_0': [1], 'all_rows_4': [0], 'location_5': [0], 'ma_6': [0], '2_7': [2]} | ['school', 'mascot', 'location', 'founded', 'entered isl', 'grades', 'number of students', 'varsity teams'] | [['belmont hill school', 'no mascot ( sextant is school symbol )', 'belmont , ma', '1923', '1948', '7 - 12', '420 boys', '16'], ['brooks school', 'bishops', 'north andover , ma', '1926', '1948', '9 - 12', '368', '22'], ['buckingham browne & nichols', 'knights', 'cambridge , ma', '1883', '1948', 'pre - k - 12', '997', '16'], ["governor 's academy", 'red dogs', 'byfield , ma', '1763', '1948', '9 - 12', '376', '20'], ['groton school', 'zebras', 'groton , ma', '1884', '1972', '8 - 12', '352', '19'], ['lawrence academy at groton', 'spartans', 'groton , ma', '1793', '1973', '9 - 12', '375', '22'], ['middlesex school', 'zebras', 'concord , ma', '1901', '1968', '9 - 12', '350', '24'], ['milton academy', 'mustangs', 'milton , ma', '1798', '1948', 'k - 12', '680', '25'], ['noble and greenough school', 'bulldogs', 'dedham , ma', '1866', '1948', '7 - 12', '525', '25'], ['rivers school', 'red wings', 'weston , ma', '1915', '1973', '6 - 12', '450', '16'], ['roxbury latin school', 'foxes', 'west roxbury , ma', '1645', '1974', '7 - 12', '290 boys', '10'], ["st george 's school", 'dragons', 'middletown , ri', '1896', '1981', '9 - 12', '345', '24'], ["st mark 's school", 'lions', 'southborough , ma', '1865', '1948', '9 - 12', '325', '22'], ["st paul 's school", 'pelicans ( teams are cheered for as big red )', 'concord , nh', '1856', '1973', '9 - 12', '533', '17'], ["st sebastian 's school", 'arrows', 'needham , ma', '1941', '1973', '7 - 12', '350 boys', '14']] |
2003 bradford bulls season | https://en.wikipedia.org/wiki/2003_Bradford_Bulls_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10814478-6.html.csv | superlative | the bradford bulls had their highest recorded score when they played at the south leeds stadium . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '2', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '3', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'score'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; score }'}, 'venue'], 'result': 'south leeds stadium', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; score } ; venue }'}, 'south leeds stadium'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; score } ; venue } ; south leeds stadium } = true', 'tointer': 'select the row whose score record of all rows is maximum . the venue record of this row is south leeds stadium .'} | eq { hop { argmax { all_rows ; score } ; venue } ; south leeds stadium } = true | select the row whose score record of all rows is maximum . the venue record of this row is south leeds stadium . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'score_5': 5, 'venue_6': 6, 'south leeds stadium_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'score_5': 'score', 'venue_6': 'venue', 'south leeds stadium_7': 'south leeds stadium'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'score_5': [0], 'venue_6': [1], 'south leeds stadium_7': [2]} | ['date', 'competition', 'venue', 'result', 'score', 'goals'] | [['8 / 2 / 03', 'cup', 'wilderspool', 'w', '38 - 12', 'deacon 7 / 7'], ['2 / 3 / 03', 'cup', 'south leeds stadium', 'w', '82 - 0', 'deacon 11 / 15'], ['15 / 3 / 03', 'cup', 'halton stadium', 'w', '38 - 28', 'deacon 7 / 7'], ['13 / 4 / 03', 'cup', 'mcalpine stadium', 'w', '36 - 22', 'deacon 6 / 6'], ['26 / 4 / 03', 'cup', 'millennium stadium', 'w', '22 - 20', 'deacon 5 / 5']] |
2008 iaaf world indoor championships - men 's 800 metres | https://en.wikipedia.org/wiki/2008_IAAF_World_Indoor_Championships_%E2%80%93_Men%27s_800_metres | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16195179-3.html.csv | aggregation | in the 2008 iaaf world indoor championships , the average time for contenders running in lane 1 for the men 's 800 metres was 1:48.84 . | {'scope': 'subset', 'col': '5', 'type': 'average', 'result': '1:48.84', 'subset': {'col': '2', 'criterion': 'equal', 'value': '1'}} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'lane', '1'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; lane ; 1 }', 'tointer': 'select the rows whose lane record is equal to 1 .'}, 'mark'], 'result': '1:48.84', 'ind': 1, 'tostr': 'avg { filter_eq { all_rows ; lane ; 1 } ; mark }'}, '1:48.84'], 'result': True, 'ind': 2, 'tostr': 'round_eq { avg { filter_eq { all_rows ; lane ; 1 } ; mark } ; 1:48.84 } = true', 'tointer': 'select the rows whose lane record is equal to 1 . the average of the mark record of these rows is 1:48.84 .'} | round_eq { avg { filter_eq { all_rows ; lane ; 1 } ; mark } ; 1:48.84 } = true | select the rows whose lane record is equal to 1 . the average of the mark record of these rows is 1:48.84 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'avg_1': 1, 'filter_eq_0': 0, 'all_rows_4': 4, 'lane_5': 5, '1_6': 6, 'mark_7': 7, '1:48.84_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'avg_1': 'avg', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'lane_5': 'lane', '1_6': '1', 'mark_7': 'mark', '1:48.84_8': '1:48.84'} | {'eq_2': [3], 'result_3': [], 'avg_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'lane_5': [0], '1_6': [0], 'mark_7': [1], '1:48.84_8': [2]} | ['heat', 'lane', 'name', 'country', 'mark'] | [['1', '5', 'dmitriy bogdanov', 'russia', '1:46.83'], ['1', '2', 'yusuf saad kamel', 'bahrain', '1:46.88 pb'], ['1', '4', 'khadevis robinson', 'united states', '1:47.57'], ['1', '3', 'richard hill', 'united kingdom', '1:47.82'], ['1', '6', 'manuel olmedo', 'spain', '1:48.90'], ['1', '1', 'fabiano peã § anha', 'brazil', '1:49.63'], ['2', '1', 'mbulaeni mulaudzi', 'south africa', '1:47.39 sb'], ['2', '5', 'abubaker kaki khamis', 'sudan', '1:47.41'], ['2', '2', 'robert lathouwers', 'netherlands', '1:48.27 pb'], ['2', '4', 'abraham chepkirwok', 'uganda', '1:48.30'], ['2', '6', 'mattias claesson', 'sweden', '1:48.50'], ['2', '3', 'jozef repcik', 'slovakia', '1:48.61'], ['3', '5', 'nick symmonds', 'united states', '1:48.43'], ['3', '4', 'dmitrijs milkevics', 'latvia', '1:48.80'], ['3', '3', 'eugenio barrios', 'spain', '1:49.02'], ['3', '6', 'ehsan mohajer shojaei', 'iran', '1:49.32'], ['3', '1', 'abdoulaye wagne', 'senegal', '1:49.49'], ['3', '2', 'lukas rifeser', 'italy', '1:51.20']] |
list of widows and widowers | https://en.wikipedia.org/wiki/List_of_widows_and_widowers | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-24143253-4.html.csv | comparative | on the list of widows and widowers jessica mitford was married longer than helen palmer geisel . | {'row_1': '9', 'row_2': '8', 'col': '5', 'col_other': '2', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'deceased spouse', 'jessica mitford'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose deceased spouse record fuzzily matches to jessica mitford .', 'tostr': 'filter_eq { all_rows ; deceased spouse ; jessica mitford }'}, 'length of marriage'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; deceased spouse ; jessica mitford } ; length of marriage }', 'tointer': 'select the rows whose deceased spouse record fuzzily matches to jessica mitford . take the length of marriage record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'deceased spouse', 'helen palmer geisel'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose deceased spouse record fuzzily matches to helen palmer geisel .', 'tostr': 'filter_eq { all_rows ; deceased spouse ; helen palmer geisel }'}, 'length of marriage'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; deceased spouse ; helen palmer geisel } ; length of marriage }', 'tointer': 'select the rows whose deceased spouse record fuzzily matches to helen palmer geisel . take the length of marriage record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; deceased spouse ; jessica mitford } ; length of marriage } ; hop { filter_eq { all_rows ; deceased spouse ; helen palmer geisel } ; length of marriage } } = true', 'tointer': 'select the rows whose deceased spouse record fuzzily matches to jessica mitford . take the length of marriage record of this row . select the rows whose deceased spouse record fuzzily matches to helen palmer geisel . take the length of marriage record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; deceased spouse ; jessica mitford } ; length of marriage } ; hop { filter_eq { all_rows ; deceased spouse ; helen palmer geisel } ; length of marriage } } = true | select the rows whose deceased spouse record fuzzily matches to jessica mitford . take the length of marriage record of this row . select the rows whose deceased spouse record fuzzily matches to helen palmer geisel . take the length of marriage 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, 'deceased spouse_7': 7, 'jessica mitford_8': 8, 'length of marriage_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'deceased spouse_11': 11, 'helen palmer geisel_12': 12, 'length of marriage_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', 'deceased spouse_7': 'deceased spouse', 'jessica mitford_8': 'jessica mitford', 'length of marriage_9': 'length of marriage', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'deceased spouse_11': 'deceased spouse', 'helen palmer geisel_12': 'helen palmer geisel', 'length of marriage_13': 'length of marriage'} | {'greater_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'deceased spouse_7': [0], 'jessica mitford_8': [0], 'length of marriage_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'deceased spouse_11': [1], 'helen palmer geisel_12': [1], 'length of marriage_13': [3]} | ['name', 'deceased spouse', 'cause of death', 'date of spouses death', 'length of marriage', 'children together', 'current marital status'] | [['samuel beckett', 'suzanne dãchevaux - dumesnil', 'unknown', 'july 17 , 1989 ( aged89 )', '28 years', 'none', 'deceased ( 1989 )'], ['jan berenstain', 'stan berenstain', 'unknown', 'november 26 , 2005 ( aged82 )', '59 years', '2 sons ( leo , michael )', 'deceased ( 2012 )'], ['ray bradbury', 'marguerite mcclure', 'not known', 'november 24 , 2003 ( aged81 )', '56 years', '4 daughters ( susan , ramona , bettina , alexandra )', 'deceased ( 2012 )'], ['mary welsh hemingway', 'ernest hemingway', 'suicide', 'july 2 , 1961 ( aged61 )', '15 years', 'none ( miscarriage )', 'deceased ( 1986 )'], ['norris church mailer', 'norman mailer', 'acute renal failure', 'november 10 , 2007 ( aged84 )', '27 years', '1 son ( john )', 'deceased ( 2010 )'], ['frederica sagor maas', 'ernest maas', 'natural causes', 'july 21 , 1986 ( aged94 )', '59 years', 'none', 'deceased ( 2012 )'], ['edgar allan poe', 'virginia eliza clemm poe', 'tuberculosis', 'january 30 , 1847 ( aged24 )', '11 years', 'none', 'deceased ( 1849 )'], ['dr seuss', 'helen palmer geisel', 'overdose of barbiturates', 'october 23 , 1967 ( aged68 )', '40 years', 'none', 'deceased ( 1991 )'], ['robert treuhaft', 'jessica mitford', 'lung cancer', 'july 22 , 1996 ( aged78 )', '53 years', '2 sons ( nicholas , benjamin )', 'deceased ( 2001 )']] |
2007 eneco tour | https://en.wikipedia.org/wiki/2007_Eneco_Tour | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12608303-1.html.csv | count | two of the stages took place on wednesdays . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'wednesday', 'result': '2', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', 'wednesday'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose date record fuzzily matches to wednesday .', 'tostr': 'filter_eq { all_rows ; date ; wednesday }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; date ; wednesday } }', 'tointer': 'select the rows whose date record fuzzily matches to wednesday . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; date ; wednesday } } ; 2 } = true', 'tointer': 'select the rows whose date record fuzzily matches to wednesday . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; date ; wednesday } } ; 2 } = true | select the rows whose date record fuzzily matches to wednesday . 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, 'date_5': 5, 'wednesday_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', 'date_5': 'date', 'wednesday_6': 'wednesday', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'date_5': [0], 'wednesday_6': [0], '2_7': [2]} | ['stage', 'route', 'distance', 'date', 'winner'] | [['p', 'hasselt - hasselt', '5.1 km', 'wednesday , august 22', 'michiel elijzen'], ['1', 'waremme - eupen', '189.5 km', 'thursday , august 23', 'nick nuyens'], ['2', 'antwerp - knokke - heist', '199.1 km', 'friday , august 24', 'mark cavendish'], ['3', 'knokke - heist - putte', '170.8 km', 'saturday , august 25', 'robbie mcewen'], ['4', 'maldegem - terneuzen', '182.7 km', 'sunday , august 26', 'wouter weylandt'], ['5', 'terneuzen - nieuwegein', '179.9 km', 'monday , august 27', 'luciano pagliarini'], ['6', 'beek - landgraaf', '177.4 km', 'tuesday , august 28', 'pablo lastras'], ['7 ( itt )', 'sittard - geleen', '29.6 km', 'wednesday , august 29', 'sébastien rosseler']] |
list of essex list a cricket records | https://en.wikipedia.org/wiki/List_of_Essex_List_A_cricket_records | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11337751-4.html.csv | ordinal | mark pettini and jason gallian were 2nd in runs scored for their record wicket parthership . | {'row': '1', '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', 'runs', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; runs ; 2 }'}, 'batsmen'], 'result': 'mark pettini jason gallian', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; runs ; 2 } ; batsmen }'}, 'mark pettini jason gallian'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; runs ; 2 } ; batsmen } ; mark pettini jason gallian } = true', 'tointer': 'select the row whose runs record of all rows is 2nd maximum . the batsmen record of this row is mark pettini jason gallian .'} | eq { hop { nth_argmax { all_rows ; runs ; 2 } ; batsmen } ; mark pettini jason gallian } = true | select the row whose runs record of all rows is 2nd maximum . the batsmen record of this row is mark pettini jason gallian . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'runs_5': 5, '2_6': 6, 'batsmen_7': 7, 'mark pettini jason gallian_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', 'runs_5': 'runs', '2_6': '2', 'batsmen_7': 'batsmen', 'mark pettini jason gallian_8': 'mark pettini jason gallian'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'runs_5': [0], '2_6': [0], 'batsmen_7': [1], 'mark pettini jason gallian_8': [2]} | ['wicket partnership', 'runs', 'batsmen', 'opponents', 'venue', 'season'] | [['1st', '269', 'mark pettini jason gallian', 'v surrey', 'the oval', '2008'], ['2nd', '273', 'graham gooch ken mcewan', 'v nottinghamshire', 'nottingham', '1983'], ['3rd', '268', 'graham gooch keith fletcher', 'v sussex', 'hove', '1982'], ['4th', '151', 'ronnie irani paul grayson', 'v northamptonshire', 'northampton', '1999'], ['5th', '190', 'ravi bopara james foster', 'v leicestershire', 'leicester', '2008'], ['6th', '127', 'stuart law robert rollins', 'v hampshire', 'southampton', '1996'], ['7th', '92', 'brian edmeades stuart turner', 'v nottinghamshire', 'chelmsford', '1969'], ['8th', '109', 'ray east neil smith', 'v northamptonshire', 'chelmsford', '1977'], ['9th', '67', 'unknown ray east', 'v gloucestershire', 'chelmsford', '1973'], ['10th', '81', 'stuart turner ray east', 'v yorkshire', 'leeds', '1982']] |
list of corporations by market capitalization | https://en.wikipedia.org/wiki/List_of_corporations_by_market_capitalization | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14094649-14.html.csv | unique | among the corporations with the greatest market capitalization , only toyota motor corporation is headquartered in japan . | {'scope': 'all', 'row': '9', 'col': '3', 'col_other': '2', 'criterion': 'equal', 'value': 'japan', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'headquarters', 'japan'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose headquarters record fuzzily matches to japan .', 'tostr': 'filter_eq { all_rows ; headquarters ; japan }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; headquarters ; japan } }', 'tointer': 'select the rows whose headquarters record fuzzily matches to japan . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'headquarters', 'japan'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose headquarters record fuzzily matches to japan .', 'tostr': 'filter_eq { all_rows ; headquarters ; japan }'}, 'name'], 'result': 'toyota motor corporation', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; headquarters ; japan } ; name }'}, 'toyota motor corporation'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; headquarters ; japan } ; name } ; toyota motor corporation }', 'tointer': 'the name record of this unqiue row is toyota motor corporation .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; headquarters ; japan } } ; eq { hop { filter_eq { all_rows ; headquarters ; japan } ; name } ; toyota motor corporation } } = true', 'tointer': 'select the rows whose headquarters record fuzzily matches to japan . there is only one such row in the table . the name record of this unqiue row is toyota motor corporation .'} | and { only { filter_eq { all_rows ; headquarters ; japan } } ; eq { hop { filter_eq { all_rows ; headquarters ; japan } ; name } ; toyota motor corporation } } = true | select the rows whose headquarters record fuzzily matches to japan . there is only one such row in the table . the name record of this unqiue row is toyota motor corporation . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'headquarters_7': 7, 'Japan_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'name_9': 9, 'toyota motor corporation_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'headquarters_7': 'headquarters', 'Japan_8': 'japan', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'name_9': 'name', 'toyota motor corporation_10': 'toyota motor corporation'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'headquarters_7': [0], 'Japan_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'name_9': [2], 'toyota motor corporation_10': [3]} | ['rank', 'name', 'headquarters', 'industry', 'market value ( usd million )'] | [['1', 'exxon mobil', 'united states', 'oil and gas', '371631'], ['2', 'general electric', 'united states', 'conglomerate', '362527'], ['3', 'microsoft', 'united states', 'software industry', '281171'], ['4', 'citigroup', 'united states', 'banking', '238935'], ['5', 'bp', 'united kingdom', 'oil and gas', '233260'], ['6', 'bank of america', 'united states', 'banking', '211706'], ['7', 'royal dutch shell', 'the netherlands', 'oil and gas', '211280'], ['8', 'wal - mart', 'united states', 'retail', '196860'], ['9', 'toyota motor corporation', 'japan', 'automotive', '196731'], ['10', 'gazprom', 'russia', 'oil and gas', '196339']] |
2006 sydney roosters season | https://en.wikipedia.org/wiki/2006_Sydney_Roosters_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18838673-1.html.csv | count | sfs was the venue on three occasions in the 2006 sydney roosters season . | {'scope': 'all', 'criterion': 'equal', 'value': 'sfs', 'result': '3', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'venue', 'sfs'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose venue record fuzzily matches to sfs .', 'tostr': 'filter_eq { all_rows ; venue ; sfs }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; venue ; sfs } }', 'tointer': 'select the rows whose venue record fuzzily matches to sfs . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; venue ; sfs } } ; 3 } = true', 'tointer': 'select the rows whose venue record fuzzily matches to sfs . the number of such rows is 3 .'} | eq { count { filter_eq { all_rows ; venue ; sfs } } ; 3 } = true | select the rows whose venue record fuzzily matches to sfs . 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, 'venue_5': 5, 'sfs_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', 'venue_5': 'venue', 'sfs_6': 'sfs', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'venue_5': [0], 'sfs_6': [0], '3_7': [2]} | ['round', 'opponent', 'result', 'opp', 'venue'] | [['1', 'south sydney rabbitohs', 'win', '22', 'aussie stadium'], ['2', 'melbourne storm', 'loss', '16', 'sfs'], ['3', 'canberra raiders', 'win', '26', 'sfs'], ['4', 'manly sea eagles', 'loss', '30', 'brookvale oval'], ['5', 'cronulla sharks', 'win', '24', 'toyota park'], ['6', 'brisbane broncos', 'loss', '24', 'sfs'], ['7', 'st george - illawarra dragons', 'loss', '22', 'aussie stadium'], ['8', 'north queensland cowboys', 'win', '18', 'dairy farmers stadium']] |
b " missouri tigers men 's basketball " | https://en.wikipedia.org/wiki/Missouri_Tigers_men%27s_basketball | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-16201038-4.html.csv | count | the missouri tigers basketball team has a current losing streak against two different teams . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'l', 'result': '2', 'col': '8', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'current streak', 'l'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose current streak record fuzzily matches to l .', 'tostr': 'filter_eq { all_rows ; current streak ; l }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; current streak ; l } }', 'tointer': 'select the rows whose current streak record fuzzily matches to l . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; current streak ; l } } ; 2 } = true', 'tointer': 'select the rows whose current streak record fuzzily matches to l . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; current streak ; l } } ; 2 } = true | select the rows whose current streak record fuzzily matches to l . 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, 'current streak_5': 5, 'l_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', 'current streak_5': 'current streak', 'l_6': 'l', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'current streak_5': [0], 'l_6': [0], '2_7': [2]} | ['missouri vs', 'overall record', 'columbia', 'opponents venue', 'neutral site', 'last 5 meetings', 'last 10 meetings', 'current streak'] | [['colorado', 'mu , 99 - 53', 'mu , 57 - 11', 'cu , 34 - 30', 'mu , 12 - 8', 'mu , 4 - 1', 'mu , 9 - 1', 'w 1'], ['creighton', 'mu , 9 - 7', 'mu , 3 - 2', 'tied , 4 - 4', 'mu , 2 - 1', 'mu , 3 - 2', 'cu , 6 - 4', 'l 1'], ['drake', 'mu , 27 - 7', 'mu , 17 - 3', 'mu , 10 - 4', 'tied , 0 - 0', 'mu , 4 - 1', 'mu , 8 - 2', 'w 4'], ['illinois', 'ui , 27 - 16', 'ui , 3 - 2', 'ui , 4 - 1', 'ui , 20 - 13', 'mu , 4 - 1', 'ui , 6 - 4', 'w 4'], ['indiana', 'tied , 9 - 9', 'mu , 5 - 3', 'iu , 6 - 3', 'mu , 1 - 0', 'mu , 4 - 1', 'tied , 5 - 5', 'w 3'], ['iowa', 'ui , 10 - 7', 'mu , 4 - 2', 'ui , 7 - 2', 'tied , 1 - 1', 'mu , 3 - 2', 'tied , 5 - 5', 'w 2'], ['nebraska', 'mu , 126 - 93', 'mu , 70 - 25', 'nu , 56 - 42', 'mu , 14 - 12', 'mu , 3 - 2', 'tied , 5 - 5', 'l 1'], ['saint louis', 'mu , 21 - 19', 'slu , 12 - 10', 'mu , 11 - 7', 'tied , 0 - 0', 'mu , 3 - 2', 'tied , 5 - 5', 'w 2'], ['washington u of stl', 'mu , 71 - 29', 'mu , 42 - 8', 'mu , 29 - 21', 'tied , 0 - 0', 'mu , 5 - 0', 'mu , 8 - 2', 'w 7']] |
1926 vfl season | https://en.wikipedia.org/wiki/1926_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10746808-5.html.csv | unique | only the match between essendon and st. kilda took place in windy hill . | {'scope': 'all', 'row': '2', 'col': '5', 'col_other': '1,3', 'criterion': 'equal', 'value': 'windy hill', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'venue', 'windy hill'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose venue record fuzzily matches to windy hill .', 'tostr': 'filter_eq { all_rows ; venue ; windy hill }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; venue ; windy hill } }', 'tointer': 'select the rows whose venue record fuzzily matches to windy hill . there is only one such row in the table .'}, {'func': 'and', 'args': [{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'venue', 'windy hill'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose venue record fuzzily matches to windy hill .', 'tostr': 'filter_eq { all_rows ; venue ; windy hill }'}, 'home team'], 'result': 'essendon', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; venue ; windy hill } ; home team }'}, 'essendon'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; venue ; windy hill } ; home team } ; essendon }', 'tointer': 'the home team record of this unqiue row is essendon .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'venue', 'windy hill'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose venue record fuzzily matches to windy hill .', 'tostr': 'filter_eq { all_rows ; venue ; windy hill }'}, 'away team'], 'result': 'st kilda', 'ind': 4, 'tostr': 'hop { filter_eq { all_rows ; venue ; windy hill } ; away team }'}, 'st kilda'], 'result': True, 'ind': 5, 'tostr': 'eq { hop { filter_eq { all_rows ; venue ; windy hill } ; away team } ; st kilda }', 'tointer': 'the away team record of this unqiue row is st kilda .'}], 'result': True, 'ind': 6, 'tostr': 'and { eq { hop { filter_eq { all_rows ; venue ; windy hill } ; home team } ; essendon } ; eq { hop { filter_eq { all_rows ; venue ; windy hill } ; away team } ; st kilda } }', 'tointer': 'the home team record of this unqiue row is essendon . the away team record of this unqiue row is st kilda .'}], 'result': True, 'ind': 7, 'tostr': 'and { only { filter_eq { all_rows ; venue ; windy hill } } ; and { eq { hop { filter_eq { all_rows ; venue ; windy hill } ; home team } ; essendon } ; eq { hop { filter_eq { all_rows ; venue ; windy hill } ; away team } ; st kilda } } } = true', 'tointer': 'select the rows whose venue record fuzzily matches to windy hill . there is only one such row in the table . the home team record of this unqiue row is essendon . the away team record of this unqiue row is st kilda .'} | and { only { filter_eq { all_rows ; venue ; windy hill } } ; and { eq { hop { filter_eq { all_rows ; venue ; windy hill } ; home team } ; essendon } ; eq { hop { filter_eq { all_rows ; venue ; windy hill } ; away team } ; st kilda } } } = true | select the rows whose venue record fuzzily matches to windy hill . there is only one such row in the table . the home team record of this unqiue row is essendon . the away team record of this unqiue row is st kilda . | 10 | 8 | {'and_7': 7, 'result_8': 8, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_9': 9, 'venue_10': 10, 'windy hill_11': 11, 'and_6': 6, 'str_eq_3': 3, 'str_hop_2': 2, 'home team_12': 12, 'essendon_13': 13, 'str_eq_5': 5, 'str_hop_4': 4, 'away team_14': 14, 'st kilda_15': 15} | {'and_7': 'and', 'result_8': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_9': 'all_rows', 'venue_10': 'venue', 'windy hill_11': 'windy hill', 'and_6': 'and', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'home team_12': 'home team', 'essendon_13': 'essendon', 'str_eq_5': 'str_eq', 'str_hop_4': 'str_hop', 'away team_14': 'away team', 'st kilda_15': 'st kilda'} | {'and_7': [8], 'result_8': [], 'only_1': [7], 'filter_str_eq_0': [1, 2, 4], 'all_rows_9': [0], 'venue_10': [0], 'windy hill_11': [0], 'and_6': [7], 'str_eq_3': [6], 'str_hop_2': [3], 'home team_12': [2], 'essendon_13': [3], 'str_eq_5': [6], 'str_hop_4': [5], 'away team_14': [4], 'st kilda_15': [5]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['melbourne', '19.8 ( 122 )', 'richmond', '12.17 ( 89 )', 'mcg', '28628', '29 may 1926'], ['essendon', '13.7 ( 85 )', 'st kilda', '5.8 ( 38 )', 'windy hill', '20000', '29 may 1926'], ['south melbourne', '10.15 ( 75 )', 'north melbourne', '11.7 ( 73 )', 'lake oval', '15000', '29 may 1926'], ['hawthorn', '9.13 ( 67 )', 'footscray', '14.16 ( 100 )', 'glenferrie oval', '10000', '29 may 1926'], ['geelong', '9.14 ( 68 )', 'collingwood', '10.15 ( 75 )', 'corio oval', '19500', '29 may 1926'], ['fitzroy', '7.16 ( 58 )', 'carlton', '7.6 ( 48 )', 'brunswick street oval', '25000', '29 may 1926']] |
list of covert affairs episodes | https://en.wikipedia.org/wiki/List_of_Covert_Affairs_episodes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-25740548-2.html.csv | unique | for covert affairs episodes , of the episodes that originally aired in august , the only one written by dana calvo was the one titled houses of the holy . | {'scope': 'subset', 'row': '6', 'col': '4', 'col_other': '2', 'criterion': 'equal', 'value': 'dana calvo', 'subset': {'col': '5', 'criterion': 'fuzzily_match', 'value': 'august'}} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'original air date', 'august'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; original air date ; august }', 'tointer': 'select the rows whose original air date record fuzzily matches to august .'}, 'written by', 'dana calvo'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose original air date record fuzzily matches to august . among these rows , select the rows whose written by record fuzzily matches to dana calvo .', 'tostr': 'filter_eq { filter_eq { all_rows ; original air date ; august } ; written by ; dana calvo }'}], 'result': True, 'ind': 2, 'tostr': 'only { filter_eq { filter_eq { all_rows ; original air date ; august } ; written by ; dana calvo } }', 'tointer': 'select the rows whose original air date record fuzzily matches to august . among these rows , select the rows whose written by record fuzzily matches to dana calvo . 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', 'original air date', 'august'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; original air date ; august }', 'tointer': 'select the rows whose original air date record fuzzily matches to august .'}, 'written by', 'dana calvo'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose original air date record fuzzily matches to august . among these rows , select the rows whose written by record fuzzily matches to dana calvo .', 'tostr': 'filter_eq { filter_eq { all_rows ; original air date ; august } ; written by ; dana calvo }'}, 'title'], 'result': 'houses of the holy', 'ind': 3, 'tostr': 'hop { filter_eq { filter_eq { all_rows ; original air date ; august } ; written by ; dana calvo } ; title }'}, 'houses of the holy'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { filter_eq { filter_eq { all_rows ; original air date ; august } ; written by ; dana calvo } ; title } ; houses of the holy }', 'tointer': 'the title record of this unqiue row is houses of the holy .'}], 'result': True, 'ind': 5, 'tostr': 'and { only { filter_eq { filter_eq { all_rows ; original air date ; august } ; written by ; dana calvo } } ; eq { hop { filter_eq { filter_eq { all_rows ; original air date ; august } ; written by ; dana calvo } ; title } ; houses of the holy } } = true', 'tointer': 'select the rows whose original air date record fuzzily matches to august . among these rows , select the rows whose written by record fuzzily matches to dana calvo . there is only one such row in the table . the title record of this unqiue row is houses of the holy .'} | and { only { filter_eq { filter_eq { all_rows ; original air date ; august } ; written by ; dana calvo } } ; eq { hop { filter_eq { filter_eq { all_rows ; original air date ; august } ; written by ; dana calvo } ; title } ; houses of the holy } } = true | select the rows whose original air date record fuzzily matches to august . among these rows , select the rows whose written by record fuzzily matches to dana calvo . there is only one such row in the table . the title record of this unqiue row is houses of the holy . | 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, 'original air date_8': 8, 'august_9': 9, 'written by_10': 10, 'dana calvo_11': 11, 'str_eq_4': 4, 'str_hop_3': 3, 'title_12': 12, 'houses of the holy_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', 'original air date_8': 'original air date', 'august_9': 'august', 'written by_10': 'written by', 'dana calvo_11': 'dana calvo', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'title_12': 'title', 'houses of the holy_13': 'houses of the holy'} | {'and_5': [6], 'result_6': [], 'only_2': [5], 'filter_str_eq_1': [2, 3], 'filter_str_eq_0': [1], 'all_rows_7': [0], 'original air date_8': [0], 'august_9': [0], 'written by_10': [1], 'dana calvo_11': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'title_12': [3], 'houses of the holy_13': [4]} | ['series', 'title', 'directed by', 'written by', 'original air date', 'production code', 'us viewers ( million )'] | [['1', 'pilot welcome to the cia', 'tim matheson', 'matt corman & chris ord', 'july 13 , 2010', 'ca101', '4.88'], ['2', "walter 's walk", 'félix alcalá', 'matt corman & chris ord', 'july 20 , 2010', 'ca102', '5.21'], ['3', 'south bound suarez', 'john kretchmer', 'james parriott', 'july 27 , 2010', 'ca103', '4.83'], ['4', 'no quarter', 'allan kroeker', 'stephen hootstein', 'august 3 , 2010', 'ca104', '5.30'], ['5', 'in the light', 'jonathan glassner', 'meredith lavender & marcie ulin', 'august 10 , 2010', 'ca105', '5.17'], ['6', 'houses of the holy', 'alex chapple', 'dana calvo', 'august 17 , 2010', 'ca106', '5.36'], ['7', 'communication breakdown', 'kate woods', 'matthew lau', 'august 24 , 2010', 'ca107', '5.87'], ['8', 'what is and what should never be', 'rod hardy', 'brett conrad', 'august 31 , 2010', 'ca108', '5.26'], ['9', 'fool in the rain', 'vincent misiano', 'stephen hootstein', 'september 7 , 2010', 'ca109', '5.40'], ['10', "i ca n't quit you baby", 'ken girotti', 'james parriott', 'september 14 , 2010', 'ca110', '4.59']] |
28th united states congress | https://en.wikipedia.org/wiki/28th_United_States_Congress | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-225206-3.html.csv | unique | the tennessee ( 2 ) seat in the 28th united states congress was the only seat that had failure to elect as a reason for change . | {'scope': 'all', 'row': '1', 'col': '3', 'col_other': '1', 'criterion': 'equal', 'value': 'failure to elect', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'reason for change', 'failure to elect'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose reason for change record fuzzily matches to failure to elect .', 'tostr': 'filter_eq { all_rows ; reason for change ; failure to elect }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; reason for change ; failure to elect } }', 'tointer': 'select the rows whose reason for change record fuzzily matches to failure to elect . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'reason for change', 'failure to elect'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose reason for change record fuzzily matches to failure to elect .', 'tostr': 'filter_eq { all_rows ; reason for change ; failure to elect }'}, 'state ( class )'], 'result': 'tennessee ( 2 )', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; reason for change ; failure to elect } ; state ( class ) }'}, 'tennessee ( 2 )'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; reason for change ; failure to elect } ; state ( class ) } ; tennessee ( 2 ) }', 'tointer': 'the state ( class ) record of this unqiue row is tennessee ( 2 ) .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; reason for change ; failure to elect } } ; eq { hop { filter_eq { all_rows ; reason for change ; failure to elect } ; state ( class ) } ; tennessee ( 2 ) } } = true', 'tointer': 'select the rows whose reason for change record fuzzily matches to failure to elect . there is only one such row in the table . the state ( class ) record of this unqiue row is tennessee ( 2 ) .'} | and { only { filter_eq { all_rows ; reason for change ; failure to elect } } ; eq { hop { filter_eq { all_rows ; reason for change ; failure to elect } ; state ( class ) } ; tennessee ( 2 ) } } = true | select the rows whose reason for change record fuzzily matches to failure to elect . there is only one such row in the table . the state ( class ) record of this unqiue row is tennessee ( 2 ) . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'reason for change_7': 7, 'failure to elect_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'state (class)_9': 9, 'tennessee (2)_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'reason for change_7': 'reason for change', 'failure to elect_8': 'failure to elect', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'state (class)_9': 'state ( class )', 'tennessee (2)_10': 'tennessee ( 2 )'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'reason for change_7': [0], 'failure to elect_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'state (class)_9': [2], 'tennessee (2)_10': [3]} | ['state ( class )', 'vacator', 'reason for change', 'successor', 'date of successors formal installation'] | [['tennessee ( 2 )', 'vacant', 'failure to elect', 'spencer jarnagin ( w )', 'elected october 17 , 1843'], ['maine ( 1 )', 'vacant', 'rep reuel williams resigned in previous congress', 'john fairfield ( d )', 'elected december 4 , 1843'], ['illinois ( 2 )', 'samuel mcroberts ( d )', 'died march 27 , 1843', 'james semple ( d )', 'elected december 4 , 1843'], ['missouri ( 3 )', 'lewis f linn ( d )', 'died october 3 , 1843', 'david r atchison ( d )', 'elected december 14 , 1843'], ['rhode island ( 1 )', 'william sprague ( d )', 'resigned january 17 , 1844', 'john b francis ( lo )', 'elected january 25 , 1844'], ['arkansas ( 2 )', 'william s fulton ( d )', 'died august 15 , 1844', 'chester ashley ( d )', 'elected november 8 , 1844'], ['new york ( 3 )', 'henry a foster ( d )', 'successor elected january 27 , 1845', 'john a dix ( d )', 'elected january 27 , 1845'], ['south carolina ( 2 )', 'daniel e huger ( d )', 'resigned march 3 , 1845', 'vacant', 'not filled this term'], ['florida ( 1 )', 'vacant', 'florida admitted to the union march 3 , 1845', 'vacant', 'not filled this term']] |
2002 new york jets season | https://en.wikipedia.org/wiki/2002_New_York_Jets_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10769447-1.html.csv | aggregation | the average pick for the 2002 new york jets season is 88.4 . | {'scope': 'all', 'col': '2', 'type': 'average', 'result': '88.4', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'pick'], 'result': '88.4', 'ind': 0, 'tostr': 'avg { all_rows ; pick }'}, '88.4'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; pick } ; 88.4 } = true', 'tointer': 'the average of the pick record of all rows is 88.4 .'} | round_eq { avg { all_rows ; pick } ; 88.4 } = true | the average of the pick record of all rows is 88.4 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'pick_4': 4, '88.4_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'pick_4': 'pick', '88.4_5': '88.4'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'pick_4': [0], '88.4_5': [1]} | ['round', 'pick', 'player', 'position', 'college'] | [['1', '22', 'bryan thomas', 'defensive end', 'uab'], ['2', '57', 'jon mcgraw', 'safety', 'kansas state'], ['3', '88', 'chris baker', 'tight end', 'michigan state'], ['4', '121', 'alan harper', 'defensive tackle', 'fresno state'], ['5', '154', 'jonathan goodwin', 'guard', 'michigan']] |
1971 washington redskins season | https://en.wikipedia.org/wiki/1971_Washington_Redskins_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15093626-2.html.csv | majority | the washington redskins won most of their games in the 1971 season . | {'scope': 'all', 'col': '4', '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', 'opponent', 'result', 'attendance'] | [['1', 'september 19 , 1971', 'st louis cardinals', 'w 24 - 17', '46805'], ['2', 'september 26 , 1971', 'new york giants', 'w 30 - 3', '62795'], ['3', 'october 3 , 1971', 'dallas cowboys', 'w 20 - 16', '61554'], ['4', 'october 10 , 1971', 'houston oilers', 'w 22 - 13', '53041'], ['5', 'october 17 , 1971', 'st louis cardinals', 'w 20 - 0', '53041'], ['6', 'october 24 , 1971', 'kansas city chiefs', 'l 27 - 20', '51989'], ['7', 'october 31 , 1971', 'new orleans saints', 'w 24 - 14', '53041'], ['8', 'november 7 , 1971', 'philadelphia eagles', 't 7 - 7', '53041'], ['9', 'november 14 , 1971', 'chicago bears', 'l 16 - 15', '55049'], ['10', 'november 21 , 1971', 'dallas cowboys', 'l 13 - 0', '53041'], ['11', 'november 28 , 1971', 'philadelphia eagles', 'w 20 - 13', '65358'], ['12', 'december 5 , 1971', 'new york giants', 'w 23 - 7', '53041'], ['13', 'december 13 , 1971', 'los angeles rams', 'w 38 - 24', '80402'], ['14', 'december 19 , 1971', 'cleveland browns', 'l 20 - 13', '53041']] |
landskrona bois | https://en.wikipedia.org/wiki/Landskrona_BoIS | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1816947-2.html.csv | majority | the majority of the average home attendance is under 3200 people . | {'scope': 'all', 'col': '2', 'most_or_all': 'most', 'criterion': 'less_than', 'value': '3200', 'subset': None} | {'func': 'most_less', 'args': ['all_rows', 'average attendance home', '3200'], 'result': True, 'ind': 0, 'tointer': 'for the average attendance home records of all rows , most of them are less than 3200 .', 'tostr': 'most_less { all_rows ; average attendance home ; 3200 } = true'} | most_less { all_rows ; average attendance home ; 3200 } = true | for the average attendance home records of all rows , most of them are less than 3200 . | 1 | 1 | {'most_less_0': 0, 'result_1': 1, 'all_rows_2': 2, 'average attendance home_3': 3, '3200_4': 4} | {'most_less_0': 'most_less', 'result_1': 'true', 'all_rows_2': 'all_rows', 'average attendance home_3': 'average attendance home', '3200_4': '3200'} | {'most_less_0': [1], 'result_1': [], 'all_rows_2': [0], 'average attendance home_3': [0], '3200_4': [0]} | ['season', 'average attendance home', 'highest attendance home', 'average attendance away', 'highest attendance away', 'division / section', 'level', 'average attendance league'] | [['2002', '7.546', '11.902 vs helsingborgs if', '9.924', '24.570 vs malmö ff', 'allsvenskan', 'tier 1', '10.180'], ['2003', '6.436', '11.375 vs malmö ff', '8.728', '23.081 vs malmö ff', 'allsvenskan', 'tier 1', '10.208'], ['2004', '5.881', '11.036 vs helsingborg', '8.526', '18.824 vs malmö ff', 'allsvenskan', 'tier 1', '9.768'], ['2005', '5.660', '9.649 vs malmö ff', '6.762', '15.047 vs helsingborg', 'allsvenskan', 'tier 1', '8.691'], ['2006', '3.192', '4.290 vs jönköpings s if', '2.027', '4.517 vs ifk norrköping', 'superettan', 'tier 2', '2.105'], ['2007', '2.972', '4.199 vs enköpings sk', '2.579', '7.193 vs ifk norrköping', 'superettan', 'tier 2', '2.450'], ['2008', '2.752', '3.873 vs enköpings sk', '1.846', '4.569 vs lb07', 'superettan', 'tier 2', '1.557'], ['2009', '2.307', '3.036 vs ängelholms ff', '1.889', '3.596 vs gif sundsvall', 'superettan', 'tier 2', '1.880'], ['2010', '3.123', '4.467 vs degerfors if', '2.251', '5.239 vs hammarby if', 'superettan', 'tier 2', '2.572'], ['2011', '2.929', '4.040 vs ifk värnamo', '2.664', '12.081 vs hammarby if', 'superettan', 'tier 2', '2.423'], ['2012', '2.459', '3.450 vs hammarby if', '2.119', '6.802 vs hammarby if', 'superettan', 'tier 2', '2.456']] |
2009 pga championship | https://en.wikipedia.org/wiki/2009_PGA_Championship | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18786347-3.html.csv | unique | in the 2009 pga championship , of the players whose score was 70 , the only one from denmark was søren kjeldsen . | {'scope': 'subset', 'row': '13', 'col': '3', 'col_other': '2', 'criterion': 'equal', 'value': 'denmark', 'subset': {'col': '4', 'criterion': 'equal', 'value': '70'}} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'score', '70'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; score ; 70 }', 'tointer': 'select the rows whose score record is equal to 70 .'}, 'country', 'denmark'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose score record is equal to 70 . among these rows , select the rows whose country record fuzzily matches to denmark .', 'tostr': 'filter_eq { filter_eq { all_rows ; score ; 70 } ; country ; denmark }'}], 'result': True, 'ind': 2, 'tostr': 'only { filter_eq { filter_eq { all_rows ; score ; 70 } ; country ; denmark } }', 'tointer': 'select the rows whose score record is equal to 70 . among these rows , select the rows whose country record fuzzily matches to denmark . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'score', '70'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; score ; 70 }', 'tointer': 'select the rows whose score record is equal to 70 .'}, 'country', 'denmark'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose score record is equal to 70 . among these rows , select the rows whose country record fuzzily matches to denmark .', 'tostr': 'filter_eq { filter_eq { all_rows ; score ; 70 } ; country ; denmark }'}, 'player'], 'result': 'søren kjeldsen', 'ind': 3, 'tostr': 'hop { filter_eq { filter_eq { all_rows ; score ; 70 } ; country ; denmark } ; player }'}, 'søren kjeldsen'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { filter_eq { filter_eq { all_rows ; score ; 70 } ; country ; denmark } ; player } ; søren kjeldsen }', 'tointer': 'the player record of this unqiue row is søren kjeldsen .'}], 'result': True, 'ind': 5, 'tostr': 'and { only { filter_eq { filter_eq { all_rows ; score ; 70 } ; country ; denmark } } ; eq { hop { filter_eq { filter_eq { all_rows ; score ; 70 } ; country ; denmark } ; player } ; søren kjeldsen } } = true', 'tointer': 'select the rows whose score record is equal to 70 . among these rows , select the rows whose country record fuzzily matches to denmark . there is only one such row in the table . the player record of this unqiue row is søren kjeldsen .'} | and { only { filter_eq { filter_eq { all_rows ; score ; 70 } ; country ; denmark } } ; eq { hop { filter_eq { filter_eq { all_rows ; score ; 70 } ; country ; denmark } ; player } ; søren kjeldsen } } = true | select the rows whose score record is equal to 70 . among these rows , select the rows whose country record fuzzily matches to denmark . there is only one such row in the table . the player record of this unqiue row is søren kjeldsen . | 8 | 6 | {'and_5': 5, 'result_6': 6, 'only_2': 2, 'filter_str_eq_1': 1, 'filter_eq_0': 0, 'all_rows_7': 7, 'score_8': 8, '70_9': 9, 'country_10': 10, 'denmark_11': 11, 'str_eq_4': 4, 'str_hop_3': 3, 'player_12': 12, 'søren kjeldsen_13': 13} | {'and_5': 'and', 'result_6': 'true', 'only_2': 'only', 'filter_str_eq_1': 'filter_str_eq', 'filter_eq_0': 'filter_eq', 'all_rows_7': 'all_rows', 'score_8': 'score', '70_9': '70', 'country_10': 'country', 'denmark_11': 'denmark', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'player_12': 'player', 'søren kjeldsen_13': 'søren kjeldsen'} | {'and_5': [6], 'result_6': [], 'only_2': [5], 'filter_str_eq_1': [2, 3], 'filter_eq_0': [1], 'all_rows_7': [0], 'score_8': [0], '70_9': [0], 'country_10': [1], 'denmark_11': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'player_12': [3], 'søren kjeldsen_13': [4]} | ['place', 'player', 'country', 'score', 'to par'] | [['1', 'tiger woods', 'united states', '67', '5'], ['2', 'pádraig harrington', 'ireland', '68', '4'], ['t3', 'robert allenby', 'australia', '69', '3'], ['t3', 'mathew goggin', 'australia', '69', '3'], ['t3', 'hunter mahan', 'united states', '69', '3'], ['t3', 'álvaro quirós', 'spain', '69', '3'], ['t3', 'vijay singh', 'fiji', '69', '3'], ['t3', 'david toms', 'united states', '69', '3'], ['t9', 'michael bradley', 'united states', '70', '2'], ['t9', 'ben crane', 'united states', '70', '2'], ['t9', 'gonzalo fernández - castaño', 'spain', '70', '2'], ['t9', 'paul goydos', 'united states', '70', '2'], ['t9', 'søren kjeldsen', 'denmark', '70', '2'], ['t9', 'graeme mcdowell', 'northern ireland', '70', '2'], ['t9', 'thongchai jaidee', 'thailand', '70', '2'], ['t9', 'lee westwood', 'england', '70', '2']] |
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 | comparative | the population of palash upazila in 2001 was lower than the population of narsingdi district . | {'row_1': '13', 'row_2': '11', 'col': '3', 'col_other': '1', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'administrative division', 'palash upazila'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose administrative division record fuzzily matches to palash upazila .', 'tostr': 'filter_eq { all_rows ; administrative division ; palash upazila }'}, 'population 2001 census ( adjusted )'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; administrative division ; palash upazila } ; population 2001 census ( adjusted ) }', 'tointer': 'select the rows whose administrative division record fuzzily matches to palash upazila . take the population 2001 census ( adjusted ) record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'administrative division', 'narsingdi district'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose administrative division record fuzzily matches to narsingdi district .', 'tostr': 'filter_eq { all_rows ; administrative division ; narsingdi district }'}, 'population 2001 census ( adjusted )'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; administrative division ; narsingdi district } ; population 2001 census ( adjusted ) }', 'tointer': 'select the rows whose administrative division record fuzzily matches to narsingdi district . take the population 2001 census ( adjusted ) record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; administrative division ; palash upazila } ; population 2001 census ( adjusted ) } ; hop { filter_eq { all_rows ; administrative division ; narsingdi district } ; population 2001 census ( adjusted ) } } = true', 'tointer': 'select the rows whose administrative division record fuzzily matches to palash upazila . take the population 2001 census ( adjusted ) record of this row . select the rows whose administrative division record fuzzily matches to narsingdi district . take the population 2001 census ( adjusted ) record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; administrative division ; palash upazila } ; population 2001 census ( adjusted ) } ; hop { filter_eq { all_rows ; administrative division ; narsingdi district } ; population 2001 census ( adjusted ) } } = true | select the rows whose administrative division record fuzzily matches to palash upazila . take the population 2001 census ( adjusted ) record of this row . select the rows whose administrative division record fuzzily matches to narsingdi district . take the population 2001 census ( adjusted ) 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, 'administrative division_7': 7, 'palash upazila_8': 8, 'population 2001 census (adjusted)_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'administrative division_11': 11, 'narsingdi district_12': 12, 'population 2001 census (adjusted)_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', 'administrative division_7': 'administrative division', 'palash upazila_8': 'palash upazila', 'population 2001 census (adjusted)_9': 'population 2001 census ( adjusted )', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'administrative division_11': 'administrative division', 'narsingdi district_12': 'narsingdi district', 'population 2001 census (adjusted)_13': 'population 2001 census ( adjusted )'} | {'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'administrative division_7': [0], 'palash upazila_8': [0], 'population 2001 census (adjusted)_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'administrative division_11': [1], 'narsingdi district_12': [1], 'population 2001 census (adjusted)_13': [3]} | ['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']] |
1941 vfl season | https://en.wikipedia.org/wiki/1941_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10807673-13.html.csv | aggregation | the average crowd size in the 1941 vfl season across all stadiums is 13000 . | {'scope': 'all', 'col': '6', 'type': 'average', 'result': '13000', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'crowd'], 'result': '13000', 'ind': 0, 'tostr': 'avg { all_rows ; crowd }'}, '13000'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; crowd } ; 13000 } = true', 'tointer': 'the average of the crowd record of all rows is 13000 .'} | round_eq { avg { all_rows ; crowd } ; 13000 } = true | the average of the crowd record of all rows is 13000 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'crowd_4': 4, '13000_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'crowd_4': 'crowd', '13000_5': '13000'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'crowd_4': [0], '13000_5': [1]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['melbourne', '18.16 ( 124 )', 'south melbourne', '10.13 ( 73 )', 'mcg', '23000', '26 july 1941'], ['collingwood', '22.20 ( 152 )', 'hawthorn', '12.13 ( 85 )', 'victoria park', '4000', '26 july 1941'], ['carlton', '12.11 ( 83 )', 'richmond', '11.18 ( 84 )', 'princes park', '27000', '26 july 1941'], ['st kilda', '18.14 ( 122 )', 'geelong', '11.15 ( 81 )', 'junction oval', '4000', '26 july 1941'], ['footscray', '15.20 ( 110 )', 'fitzroy', '9.4 ( 58 )', 'western oval', '10000', '26 july 1941'], ['north melbourne', '12.14 ( 86 )', 'essendon', '17.8 ( 110 )', 'arden street oval', '10000', '26 july 1941']] |
g.d. estoril praia | https://en.wikipedia.org/wiki/G.D._Estoril_Praia | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1629175-1.html.csv | count | g.d. estoril had three group h rounds in 2013-14 . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'group h', 'result': '3', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'round', 'group h'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose round record fuzzily matches to group h .', 'tostr': 'filter_eq { all_rows ; round ; group h }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; round ; group h } }', 'tointer': 'select the rows whose round record fuzzily matches to group h . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; round ; group h } } ; 3 } = true', 'tointer': 'select the rows whose round record fuzzily matches to group h . the number of such rows is 3 .'} | eq { count { filter_eq { all_rows ; round ; group h } } ; 3 } = true | select the rows whose round record fuzzily matches to group h . 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, 'round_5': 5, 'group h_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', 'round_5': 'round', 'group h_6': 'group h', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'round_5': [0], 'group h_6': [0], '3_7': [2]} | ['season', 'competition', 'round', 'opponent', 'home', 'away'] | [['2013 - 14', 'uefa europa league', '3q', 'hapoel ramat gan', '0 - 0', '1 - 0'], ['2013 - 14', 'uefa europa league', 'play - off', 'pasching', '2 - 0', '2 - 1'], ['2013 - 14', 'uefa europa league', 'group h', 'sevilla', '1 - 2', '-'], ['2013 - 14', 'uefa europa league', 'group h', 'slovan liberec', '-', '1 - 2'], ['2013 - 14', 'uefa europa league', 'group h', 'freiburg', '-', '1 - 1']] |
east surrey ( uk parliament constituency ) | https://en.wikipedia.org/wiki/East_Surrey_%28UK_Parliament_constituency%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1809923-1.html.csv | count | the position of first member for east surrey went to the liberal party four times . | {'scope': 'all', 'criterion': 'equal', 'value': 'liberal', 'result': '4', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', '1st party', 'liberal'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose 1st party record fuzzily matches to liberal .', 'tostr': 'filter_eq { all_rows ; 1st party ; liberal }'}], 'result': '4', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; 1st party ; liberal } }', 'tointer': 'select the rows whose 1st party record fuzzily matches to liberal . the number of such rows is 4 .'}, '4'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; 1st party ; liberal } } ; 4 } = true', 'tointer': 'select the rows whose 1st party record fuzzily matches to liberal . the number of such rows is 4 .'} | eq { count { filter_eq { all_rows ; 1st party ; liberal } } ; 4 } = true | select the rows whose 1st party record fuzzily matches to liberal . the number of such rows is 4 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, '1st party_5': 5, 'liberal_6': 6, '4_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', '1st party_5': '1st party', 'liberal_6': 'liberal', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], '1st party_5': [0], 'liberal_6': [0], '4_7': [2]} | ['election', 'first member', '1st party', 'second member', '2nd party'] | [['1832', 'john ivatt briscoe', 'liberal', 'aubrey beauclerk', 'liberal'], ['1835', 'richard alsager', 'conservative', 'aubrey beauclerk', 'liberal'], ['1837', 'richard alsager', 'conservative', 'henry kemble', 'conservative'], ['1841 by - election', 'edmund antrobus', 'conservative', 'henry kemble', 'conservative'], ['1847', 'peter john locke king', 'liberal', 'thomas alcock', 'liberal'], ['1865', 'peter john locke king', 'liberal', 'charles buxton', 'liberal'], ['1871 by - election', 'peter john locke king', 'liberal', 'james watney', 'conservative'], ['1874', 'william grantham', 'conservative', 'james watney', 'conservative'], ['1885', 'constituency abolished', 'constituency abolished', 'constituency abolished', 'constituency abolished']] |
pilibhit ( lok sabha constituency ) | https://en.wikipedia.org/wiki/Pilibhit_%28Lok_Sabha_constituency%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18106841-1.html.csv | ordinal | for pilibhit , when the trailing party was bahujan samaj party , the 2nd highest % of votes for the trailing party was in 1998 . | {'scope': 'subset', 'row': '12', 'col': '7', 'order': '2', 'col_other': '1', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'subset': {'col': '6', 'criterion': 'equal', 'value': 'bahujan samaj party'}} | {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'nth_argmax', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'trailing party', 'bahujan samaj party'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; trailing party ; bahujan samaj party }', 'tointer': 'select the rows whose trailing party record fuzzily matches to bahujan samaj party .'}, 'trailing party % votes', '2'], 'result': None, 'ind': 1, 'tostr': 'nth_argmax { filter_eq { all_rows ; trailing party ; bahujan samaj party } ; trailing party % votes ; 2 }'}, 'year'], 'result': '1998', 'ind': 2, 'tostr': 'hop { nth_argmax { filter_eq { all_rows ; trailing party ; bahujan samaj party } ; trailing party % votes ; 2 } ; year }'}, '1998'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { nth_argmax { filter_eq { all_rows ; trailing party ; bahujan samaj party } ; trailing party % votes ; 2 } ; year } ; 1998 } = true', 'tointer': 'select the rows whose trailing party record fuzzily matches to bahujan samaj party . select the row whose trailing party % votes record of these rows is 2nd maximum . the year record of this row is 1998 .'} | eq { hop { nth_argmax { filter_eq { all_rows ; trailing party ; bahujan samaj party } ; trailing party % votes ; 2 } ; year } ; 1998 } = true | select the rows whose trailing party record fuzzily matches to bahujan samaj party . select the row whose trailing party % votes record of these rows is 2nd maximum . the year record of this row is 1998 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'num_hop_2': 2, 'nth_argmax_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'trailing party_6': 6, 'bahujan samaj party_7': 7, 'trailing party % votes_8': 8, '2_9': 9, 'year_10': 10, '1998_11': 11} | {'eq_3': 'eq', 'result_4': 'true', 'num_hop_2': 'num_hop', 'nth_argmax_1': 'nth_argmax', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'trailing party_6': 'trailing party', 'bahujan samaj party_7': 'bahujan samaj party', 'trailing party % votes_8': 'trailing party % votes', '2_9': '2', 'year_10': 'year', '1998_11': '1998'} | {'eq_3': [4], 'result_4': [], 'num_hop_2': [3], 'nth_argmax_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'trailing party_6': [0], 'bahujan samaj party_7': [0], 'trailing party % votes_8': [1], '2_9': [1], 'year_10': [2], '1998_11': [3]} | ['year', 'lok sabha', 'members of parliament', 'party won', "winner 's % votes", 'trailing party', 'trailing party % votes'] | [['1951', '1st lok sabha', 'mukund lal agrawal', 'indian national congress', '43.11 %', 'socialist party', '22.58 %'], ['1957', '2nd lok sabha', 'mohan swarup', 'praja socialist party', '50.54 %', 'indian national congress', '34.86 %'], ['1962', '3rd lok sabha', 'mohan swarup', 'praja socialist party', '29.62 %', 'indian national congress', '27.42 %'], ['1967', '4th lok sabha', 'mohan swarup', 'praja socialist party', '28.24 %', 'indian national congress', '24.26 %'], ['1971', '5th lok sabha', 'mohan swarup', 'indian national congress', '38.96 %', 'indian national organization', '24.74 %'], ['1977', '6th lok sabha', 'md shamsul hasan khan', 'bharatiya lok dal', '71.32 %', 'indian national congress', '19.73 %'], ['1980', '7th lok sabha', 'harish kumar gangawar', 'indian national congress', '40.42 %', 'janata party', '25.34 %'], ['1984', '8th lok sabha', 'bhanu pratap singh', 'indian national congress', '63.84 %', 'bharatiya lok dal', '23.39 %'], ['1989', '9th lok sabha', 'maneka gandhi', 'janata dal', '57.34 %', 'indian national congress', '29.37 %'], ['1991', '10th lok sabha', 'parshuram gangwar', 'bharatiya janta party', '30.86 %', 'janata dal', '29.40 %'], ['1996', '11th lok sabha', 'maneka gandhi', 'janata dal', '59.83 %', 'bharatiya janta party', '17.01 %'], ['1998', '12th lok sabha', 'maneka gandhi', 'independent', '55.99 %', 'bahujan samaj party', '22.60 %'], ['1999', '13th lok sabha', 'maneka gandhi', 'independent', '57.94 %', 'bahujan samaj party', '25.88 %'], ['2004', '14th lok sabha', 'maneka gandhi', 'bharatiya janta party', '37.75 %', 'samajwadi party', '22.58 %'], ['2009', '15th lok sabha', 'feroze varun gandhi', 'bharatiya janta party', '49.79 %', 'indian national congress', '16.38 %']] |
2008 - 09 minnesota timberwolves season | https://en.wikipedia.org/wiki/2008%E2%80%9309_Minnesota_Timberwolves_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-17058226-10.html.csv | superlative | in games played at the target center , sebastian telfair 's best score was 21 points . | {'scope': 'subset', 'col_superlative': '5', 'row_superlative': '5', 'value_mentioned': 'yes', 'max_or_min': 'max', 'other_col': '8', 'subset': {'col': '8', 'criterion': 'fuzzily_match', 'value': 'target center'}} | {'func': 'eq', 'args': [{'func': 'max', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location attendance', 'target center'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; location attendance ; target center }', 'tointer': 'select the rows whose location attendance record fuzzily matches to target center .'}, 'high points'], 'result': 'sebastian telfair ( 21 )', 'ind': 1, 'tostr': 'max { filter_eq { all_rows ; location attendance ; target center } ; high points }', 'tointer': 'select the rows whose location attendance record fuzzily matches to target center . the maximum high points record of these rows is sebastian telfair ( 21 ) .'}, 'sebastian telfair ( 21 )'], 'result': True, 'ind': 2, 'tostr': 'eq { max { filter_eq { all_rows ; location attendance ; target center } ; high points } ; sebastian telfair ( 21 ) } = true', 'tointer': 'select the rows whose location attendance record fuzzily matches to target center . the maximum high points record of these rows is sebastian telfair ( 21 ) .'} | eq { max { filter_eq { all_rows ; location attendance ; target center } ; high points } ; sebastian telfair ( 21 ) } = true | select the rows whose location attendance record fuzzily matches to target center . the maximum high points record of these rows is sebastian telfair ( 21 ) . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'max_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'location attendance_5': 5, 'target center_6': 6, 'high points_7': 7, 'sebastian telfair (21)_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'max_1': 'max', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'location attendance_5': 'location attendance', 'target center_6': 'target center', 'high points_7': 'high points', 'sebastian telfair (21)_8': 'sebastian telfair ( 21 )'} | {'eq_2': [3], 'result_3': [], 'max_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'location attendance_5': [0], 'target center_6': [0], 'high points_7': [1], 'sebastian telfair (21)_8': [2]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record'] | [['76', 'april 3', 'utah', 'w 103 - 102 ( ot )', 'ryan gomes , rodney carney ( 25 )', 'mike miller ( 9 )', 'mike miller ( 8 )', 'energysolutions arena 19911', '22 - 54'], ['77', 'april 5', 'denver', 'l 87 - 110 ( ot )', 'sebastian telfair ( 18 )', 'shelden williams ( 12 )', 'mike miller ( 6 )', 'target center 16839', '22 - 55'], ['78', 'april 7', 'la clippers', 'w 87 - 77 ( ot )', 'ryan gomes ( 24 )', 'kevin love ( 15 )', 'sebastian telfair , mike miller ( 6 )', 'staples center 16757', '23 - 55'], ['79', 'april 8', 'golden state', 'w 105 - 97 ( ot )', 'sebastian telfair ( 21 )', 'kevin love ( 12 )', 'mike miller ( 6 )', 'oracle arena 18808', '24 - 55'], ['80', 'april 11', 'phoenix', 'l 97 - 110 ( ot )', 'sebastian telfair ( 21 )', 'mike miller ( 9 )', 'mike miller ( 9 )', 'target center 18478', '24 - 56'], ['81', 'april 13', 'dallas', 'l 94 - 96 ( ot )', 'craig smith ( 24 )', 'kevin love ( 11 )', 'sebastian telfair ( 12 )', 'american airlines center 19900', '24 - 57']] |
2008 indiana fever season | https://en.wikipedia.org/wiki/2008_Indiana_Fever_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17104539-10.html.csv | majority | all games of the 2008 indiana fever 's season were scheduled for the month of july . | {'scope': 'all', 'col': '2', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'july', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'date', 'july'], 'result': True, 'ind': 0, 'tointer': 'for the date records of all rows , all of them fuzzily match to july .', 'tostr': 'all_eq { all_rows ; date ; july } = true'} | all_eq { all_rows ; date ; july } = true | for the date records of all rows , all of them fuzzily match to july . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'date_3': 3, 'july_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'date_3': 'date', 'july_4': 'july'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'date_3': [0], 'july_4': [0]} | ['game', 'date', 'opponent', 'score', 'high points', 'high rebounds', 'high assists', 'location / attendance', 'record'] | [['16', 'july 2', 'chicago', 'w 74 - 67', 'catchings ( 18 )', 'sutton - brown ( 12 )', 'catchings , douglas ( 3 )', 'conseco fieldhouse 6196', '8 - 8'], ['17', 'july 5', 'connecticut', 'w 81 - 74', 'douglas , sutton - brown ( 18 )', 'sutton - brown ( 9 )', 'douglas ( 5 )', 'conseco fieldhouse 6329', '9 - 8'], ['18', 'july 8', 'washington', 'l 50 - 48', 'hoffman ( 16 )', 'hoffman ( 9 )', 'bevilaqua ( 4 )', 'verizon center 7587', '9 - 9'], ['19', 'july 12', 'chicago', 'w 66 - 57', 'douglas ( 25 )', 'catchings ( 8 )', 'catchings ( 4 )', 'conseco fieldhouse 7134', '10 - 9'], ['20', 'july 16', 'atlanta', 'l 81 - 77', 'catchings ( 18 )', 'catchings ( 12 )', 'catchings ( 5 )', 'conseco fieldhouse 9303', '10 - 10'], ['21', 'july 18', 'seattle', 'l 65 - 59', 'sutton - brown ( 12 )', 'sutton - brown ( 7 )', 'bevilaqua , bond ( 3 )', 'conseco fieldhouse 7450', '10 - 11'], ['22', 'july 19', 'new york liberty outdoor classic', 'w 71 - 55', 'douglas ( 20 )', 'catchings , sutton - brown ( 9 )', 'catchings , douglas ( 4 )', 'arthur ashe stadium 19393', '11 - 11'], ['23', 'july 22', 'chicago', 'l 68 - 60', 'douglas , sutton - brown ( 14 )', 'sutton - brown ( 10 )', 'catchings ( 4 )', 'uic pavilion 3035', '11 - 12'], ['24', 'july 24', 'minnesota', 'l 84 - 80', 'catchings , hoffman ( 17 )', 'sutton - brown ( 9 )', 'catchings ( 9 )', 'conseco fieldhouse 6010', '11 - 13'], ['25', 'july 26', 'sacramento', 'l 70 - 62', 'douglas ( 23 )', 'hoffman ( 8 )', 'catchings , white ( 4 )', 'arco arena 7082', '11 - 14'], ['26', 'july 27', 'phoenix', 'w 84 - 80', 'catchings ( 25 )', 'hoffman ( 7 )', 'catchings ( 6 )', 'us airways center 7924', '12 - 14']] |
wru division five south west | https://en.wikipedia.org/wiki/WRU_Division_Five_South_West | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17675675-2.html.csv | comparative | swansea uplands rfc had a lower number of tries for than trebanos rfc . | {'row_1': '11', 'row_2': '7', 'col': '7', 'col_other': '1', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'club', 'swansea uplands rfc'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose club record fuzzily matches to swansea uplands rfc .', 'tostr': 'filter_eq { all_rows ; club ; swansea uplands rfc }'}, 'tries for'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; club ; swansea uplands rfc } ; tries for }', 'tointer': 'select the rows whose club record fuzzily matches to swansea uplands rfc . take the tries for record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'club', 'trebanos rfc'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose club record fuzzily matches to trebanos rfc .', 'tostr': 'filter_eq { all_rows ; club ; trebanos rfc }'}, 'tries for'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; club ; trebanos rfc } ; tries for }', 'tointer': 'select the rows whose club record fuzzily matches to trebanos rfc . take the tries for record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; club ; swansea uplands rfc } ; tries for } ; hop { filter_eq { all_rows ; club ; trebanos rfc } ; tries for } } = true', 'tointer': 'select the rows whose club record fuzzily matches to swansea uplands rfc . take the tries for record of this row . select the rows whose club record fuzzily matches to trebanos rfc . take the tries for record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; club ; swansea uplands rfc } ; tries for } ; hop { filter_eq { all_rows ; club ; trebanos rfc } ; tries for } } = true | select the rows whose club record fuzzily matches to swansea uplands rfc . take the tries for record of this row . select the rows whose club record fuzzily matches to trebanos rfc . take the tries for 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, 'club_7': 7, 'swansea uplands rfc_8': 8, 'tries for_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'club_11': 11, 'trebanos rfc_12': 12, 'tries for_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', 'club_7': 'club', 'swansea uplands rfc_8': 'swansea uplands rfc', 'tries for_9': 'tries for', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'club_11': 'club', 'trebanos rfc_12': 'trebanos rfc', 'tries for_13': 'tries for'} | {'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'club_7': [0], 'swansea uplands rfc_8': [0], 'tries for_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'club_11': [1], 'trebanos rfc_12': [1], 'tries for_13': [3]} | ['club', 'played', 'drawn', 'lost', 'points for', 'points against', 'tries for', 'tries against', 'try bonus'] | [['club', 'played', 'drawn', 'lost', 'points for', 'points against', 'tries for', 'tries against', 'try bonus'], ['betws rfc', '20', '0', '2', '727', '243', '111', '29', '14'], ['ystradgynlais rfc', '20', '0', '2', '667', '200', '107', '24', '15'], ['alltwen rfc', '20', '1', '4', '434', '237', '55', '21', '7'], ['new dock stars rfc', '20', '1', '8', '367', '318', '51', '38', '5'], ['pontardawe rfc', '20', '0', '10', '441', '381', '64', '51', '9'], ['trebanos rfc', '20', '1', '9', '441', '404', '51', '58', '5'], ['glais rfc', '20', '0', '11', '293', '325', '36', '42', '4'], ['gowerton rfc', '20', '0', '13', '313', '468', '38', '69', '2'], ['cwmtwrch rfc', '20', '2', '13', '261', '406', '28', '58', '0'], ['swansea uplands rfc', '20', '1', '17', '197', '574', '28', '89', '1'], ['bynea rfc', '20', '0', '18', '139', '724', '21', '111', '1']] |
psych ( season 4 ) | https://en.wikipedia.org/wiki/Psych_%28season_4%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-26429771-1.html.csv | count | mel damski directed a total of four episodes of psych in season 4 . | {'scope': 'all', 'criterion': 'equal', 'value': 'mel damski', 'result': '4', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'directed by', 'mel damski'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose directed by record fuzzily matches to mel damski .', 'tostr': 'filter_eq { all_rows ; directed by ; mel damski }'}], 'result': '4', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; directed by ; mel damski } }', 'tointer': 'select the rows whose directed by record fuzzily matches to mel damski . the number of such rows is 4 .'}, '4'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; directed by ; mel damski } } ; 4 } = true', 'tointer': 'select the rows whose directed by record fuzzily matches to mel damski . the number of such rows is 4 .'} | eq { count { filter_eq { all_rows ; directed by ; mel damski } } ; 4 } = true | select the rows whose directed by record fuzzily matches to mel damski . the number of such rows is 4 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'directed by_5': 5, 'mel damski_6': 6, '4_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'directed by_5': 'directed by', 'mel damski_6': 'mel damski', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'directed by_5': [0], 'mel damski_6': [0], '4_7': [2]} | ['no in series', 'no in season', 'title', 'directed by', 'written by', 'original air date', 'production code', 'us viewers ( million )'] | [['48', '1', 'extradition : british columbia', 'steve franks', 'steve franks', 'august 7 , 2009', '4001', 'n / a'], ['49', '2', 'he dead', 'michael mcmurray', 'saladin k patterson', 'august 14 , 2009', '4002', 'n / a'], ['50', '3', 'high noon - ish', 'mel damski', 'kell cahoon', 'august 21 , 2009', '4003', 'n / a'], ['52', '5', 'shawn gets the yips', 'tawnia mckiernan', 'kell cahoon & bill callahan', 'september 11 , 2009', '4005', 'n / a'], ['53', '6', 'bollywood homicide', 'jay chandrasekhar', 'steve franks & anupam nigam', 'september 18 , 2009', '4006', 'n / a'], ['54', '7', 'high top fade - out', 'stephen surjik', 'saladin k patterson & james roday', 'september 25 , 2009', '4007', 'n / a'], ['55', '8', "let 's get hairy", 'andrew bernstein', 'todd harthan & james roday', 'october 9 , 2009', '4008', 'n / a'], ['56', '9', 'shawn takes a shot in the dark', 'mel damski', 'andy berman', 'october 16 , 2009', '4009', '3.68'], ['57', '10', "you ca n't handle this episode", 'mel damski', 'andy berman', 'january 27 , 2010', '4010', '4.37'], ['58', '11', 'thrill seekers and hell - raisers', 'mel damski', 'kell cahoon & saladin k patterson', 'february 3 , 2010', '4011', '2.86'], ['59', '12', 'a very juliet episode', 'steve franks', 'steve franks & tim meltreger', 'february 10 , 2010', '4012', '3.57'], ['60', '13', 'death is in the air', 'stephen surjik', 'bill callahan & anupam nigam', 'february 17 , 2010', '4013', '2.94'], ['61', '14', 'think tank', 'stephen surjik', 'steve franks & andy berman', 'february 24 , 2010', '4014', '3.57'], ['62', '15', 'the head , the tail , the whole damn episode', 'matt shakman', 'steve franks & tim meltreger', 'march 3 , 2010', '4015', '2.87']] |
sheffield and hallamshire association cup | https://en.wikipedia.org/wiki/Sheffield_and_Hallamshire_Association_Cup | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14909105-1.html.csv | count | kiveton park had two wines in the sheffield and hallamshire association cup from 2002-2013 . | {'scope': 'all', 'criterion': 'equal', 'value': 'kiveton park', 'result': '2', 'col': '2', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'winner', 'kiveton park'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose winner record fuzzily matches to kiveton park .', 'tostr': 'filter_eq { all_rows ; winner ; kiveton park }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; winner ; kiveton park } }', 'tointer': 'select the rows whose winner record fuzzily matches to kiveton park . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; winner ; kiveton park } } ; 2 } = true', 'tointer': 'select the rows whose winner record fuzzily matches to kiveton park . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; winner ; kiveton park } } ; 2 } = true | select the rows whose winner record fuzzily matches to kiveton park . the number of such rows is 2 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'winner_5': 5, 'kiveton park_6': 6, '2_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'winner_5': 'winner', 'kiveton park_6': 'kiveton park', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'winner_5': [0], 'kiveton park_6': [0], '2_7': [2]} | ['season', 'winner', 'result', 'runner - up', 'final venue'] | [['2002 - 03', 'elm tree', '1 - 0', 'stocksbridge park steels reserves', 'belle vue'], ['2003 - 04', 'hsbc', '3 - 2', 'athersley recreation', 'belle vue'], ['2004 - 05', 'kiveton park', '2 - 2', 'athersley recreation', 'sandy lane'], ['2005 - 06', 'kiveton park', '5 - 0', 'sheffield lane top', 'belle vue'], ['2006 - 07', 'stocksbridge park steels reserves', '3 - 1', 'hemsworth miners welfare', 'millmoor'], ['2007 - 08', 'athersley recreation', '1 - 0', 'hollinsend amateurs', 'oakwell'], ['2008 - 09', 'hall green united', '2 - 1', 'kirkburton', 'keepmoat stadium ( pitch 2 )'], ['2009 - 10', 'sheffield reserves', '2 - 1', 'dearne colliery miners welfare', 'inkersall road'], ['2010 - 11', 'stocksbridge park steels reserves', '3 - 0', 'kirkburton', 'green lane'], ['2012 - 13', 'swinton athletic', '3 - 0', 'kirkburton', 'sandy lane']] |
2010 nba all - star game | https://en.wikipedia.org/wiki/2010_NBA_All-Star_Game | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15753220-9.html.csv | superlative | texas won the shooting stars competition in the 2010 nba all-star game , completing the final round in the least amount of time . | {'scope': 'all', 'col_superlative': '5', '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', 'final round'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; final round }'}, 'city / state'], 'result': 'texas', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; final round } ; city / state }'}, 'texas'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmin { all_rows ; final round } ; city / state } ; texas } = true', 'tointer': 'select the row whose final round record of all rows is minimum . the city / state record of this row is texas .'} | eq { hop { argmin { all_rows ; final round } ; city / state } ; texas } = true | select the row whose final round record of all rows is minimum . the city / state record of this row is texas . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'final round_5': 5, 'city / state_6': 6, 'texas_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'final round_5': 'final round', 'city / state_6': 'city / state', 'texas_7': 'texas'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'final round_5': [0], 'city / state_6': [1], 'texas_7': [2]} | ['city / state', 'members', 'team', 'first round', 'final round'] | [['texas', 'dirk nowitzki', 'dallas mavericks', '1:28', '34.3'], ['texas', 'becky hammon', 'san antonio silver stars', '1:28', '34.3'], ['texas', 'kenny smith', 'houston rockets ( retired )', '1:28', '34.3'], ['los angeles', 'pau gasol', 'los angeles lakers', '1:00', '55.2'], ['los angeles', 'marie ferdinand - harris', 'los angeles sparks', '1:00', '55.2'], ['los angeles', 'brent barry', 'los angeles clippers ( retired )', '1:00', '55.2'], ['sacramento', 'tyreke evans', 'sacramento kings', '1:46', '-'], ['sacramento', 'nicole powell', 'sacramento monarchs', '1:46', '-'], ['sacramento', 'chris webber', 'sacramento kings ( retired )', '1:46', '-'], ['atlanta', 'joe johnson', 'atlanta hawks', '1:47', '-'], ['atlanta', 'angel mccoughtry', 'atlanta dream', '1:47', '-'], ['atlanta', 'steve smith', 'atlanta hawks ( retired )', '1:47', '-']] |
united states house of representatives elections , 1980 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1980 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1341640-26.html.csv | superlative | the candidate receiving the highest percentage of the votes in their perspective election was bill clay . | {'scope': 'all', 'col_superlative': '6', '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', 'candidates'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; candidates }'}, 'incumbent'], 'result': 'bill clay', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; candidates } ; incumbent }'}, 'bill clay'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; candidates } ; incumbent } ; bill clay } = true', 'tointer': 'select the row whose candidates record of all rows is maximum . the incumbent record of this row is bill clay .'} | eq { hop { argmax { all_rows ; candidates } ; incumbent } ; bill clay } = true | select the row whose candidates record of all rows is maximum . the incumbent record of this row is bill clay . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'candidates_5': 5, 'incumbent_6': 6, 'bill clay_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'candidates_5': 'candidates', 'incumbent_6': 'incumbent', 'bill clay_7': 'bill clay'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'candidates_5': [0], 'incumbent_6': [1], 'bill clay_7': [2]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['missouri 1', 'bill clay', 'democratic', '1968', 're - elected', 'bill clay ( d ) 70.2 % bill white ( r ) 29.8 %'], ['missouri 4', 'ike skelton', 'democratic', '1976', 're - elected', 'ike skelton ( d ) 67.8 % bill baker ( r ) 32.2 %'], ['missouri 7', 'gene taylor', 'republican', '1972', 're - elected', 'gene taylor ( r ) 67.8 % ken young ( d ) 32.2 %'], ['missouri 8', 'richard howard ichord , jr', 'democratic', '1960', 'retired republican gain', 'wendell bailey ( r ) 57.1 % steve gardner ( d ) 42.9 %'], ['missouri 9', 'harold volkmer', 'democratic', '1976', 're - elected', 'harold volkmer ( d ) 56.5 % john w turner ( r ) 43.5 %']] |
law & order : special victims unit | https://en.wikipedia.org/wiki/Law_%26_Order%3A_Special_Victims_Unit | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-197060-1.html.csv | unique | the only season where law & order : special victims unit was ranked 33rd was season 1 . | {'scope': 'all', 'row': '1', 'col': '7', 'col_other': '1', 'criterion': 'equal', 'value': '33rd', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'ranking', '33rd'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose ranking record fuzzily matches to 33rd .', 'tostr': 'filter_eq { all_rows ; ranking ; 33rd }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; ranking ; 33rd } }', 'tointer': 'select the rows whose ranking record fuzzily matches to 33rd . there is only one such row in the table .'}, {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'ranking', '33rd'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose ranking record fuzzily matches to 33rd .', 'tostr': 'filter_eq { all_rows ; ranking ; 33rd }'}, 'season'], 'result': '1', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; ranking ; 33rd } ; season }'}, '1'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; ranking ; 33rd } ; season } ; 1 }', 'tointer': 'the season record of this unqiue row is 1 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; ranking ; 33rd } } ; eq { hop { filter_eq { all_rows ; ranking ; 33rd } ; season } ; 1 } } = true', 'tointer': 'select the rows whose ranking record fuzzily matches to 33rd . there is only one such row in the table . the season record of this unqiue row is 1 .'} | and { only { filter_eq { all_rows ; ranking ; 33rd } } ; eq { hop { filter_eq { all_rows ; ranking ; 33rd } ; season } ; 1 } } = true | select the rows whose ranking record fuzzily matches to 33rd . there is only one such row in the table . the season record of this unqiue row is 1 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'ranking_7': 7, '33rd_8': 8, 'eq_3': 3, 'num_hop_2': 2, 'season_9': 9, '1_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'ranking_7': 'ranking', '33rd_8': '33rd', 'eq_3': 'eq', 'num_hop_2': 'num_hop', 'season_9': 'season', '1_10': '1'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'ranking_7': [0], '33rd_8': [0], 'eq_3': [4], 'num_hop_2': [3], 'season_9': [2], '1_10': [3]} | ['season', 'episodes', 'timeslot ( est )', 'season premiere', 'season finale', 'tv season', 'ranking', 'viewers ( in millions )'] | [['1', '22', 'monday 9:00 pm ( 1999 ) friday 10:00 pm ( 2000 )', 'september 20 , 1999', 'may 19 , 2000', '1999 - 2000', '33rd', '12.18'], ['2', '21', 'friday 10:00 pm', 'october 20 , 2000', 'may 11 , 2001', '2000 - 01', '29th', '13.1'], ['3', '23', 'friday 10:00 pm', 'september 28 , 2001', 'may 17 , 2002', '2001 - 02', '14th', '15.2'], ['4', '25', 'friday 10:00 pm', 'september 27 , 2002', 'may 16 , 2003', '2002 - 03', '16th', '14.83'], ['5', '25', 'tuesday 10:00 pm', 'september 23 , 2003', 'may 18 , 2004', '2003 - 04', '21st', '12.72'], ['6', '23', 'tuesday 10:00 pm', 'september 21 , 2004', 'may 24 , 2005', '2004 - 05', '23rd', '13.46'], ['7', '22', 'tuesday 10:00 pm', 'september 20 , 2005', 'may 16 , 2006', '2005 - 06', '24th', '13.78'], ['8', '22', 'tuesday 10:00 pm', 'september 19 , 2006', 'may 22 , 2007', '2006 - 07', '38th', '11.94'], ['9', '19', 'tuesday 10:00 pm', 'september 25 , 2007', 'may 13 , 2008', '2007 - 08', '30th', '11.33'], ['10', '22', 'tuesday 10:00 pm', 'september 23 , 2008', 'june 2 , 2009', '2008 - 09', '39th', '10.11'], ['11', '24', 'wednesday 9:00 pm wednesday 10:00 pm', 'september 23 , 2009', 'may 19 , 2010', '2009 - 10', '44th', '8.81'], ['13', '23', 'wednesday 10:00 pm', 'september 21 , 2011', 'may 23 , 2012', '2011 - 12', '67th', '7.59'], ['14', '24', 'wednesday 9:00 pm', 'september 26 , 2012', 'may 22 , 2013', '2012 - 13', '56th', '7.30']] |
justin lee collins : good times | https://en.wikipedia.org/wiki/Justin_Lee_Collins%3A_Good_Times | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-26733129-1.html.csv | ordinal | justin lee collins first appeared in good times on april 5 , 2010 . | {'row': '1', 'col': '1', 'order': '1', 'col_other': '2', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'episode number', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; episode number ; 1 }'}, 'air date'], 'result': '5 april 2010', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; episode number ; 1 } ; air date }'}, '5 april 2010'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; episode number ; 1 } ; air date } ; 5 april 2010 } = true', 'tointer': 'select the row whose episode number record of all rows is 1st minimum . the air date record of this row is 5 april 2010 .'} | eq { hop { nth_argmin { all_rows ; episode number ; 1 } ; air date } ; 5 april 2010 } = true | select the row whose episode number record of all rows is 1st minimum . the air date record of this row is 5 april 2010 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'episode number_5': 5, '1_6': 6, 'air date_7': 7, '5 april 2010_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', 'episode number_5': 'episode number', '1_6': '1', 'air date_7': 'air date', '5 april 2010_8': '5 april 2010'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'episode number_5': [0], '1_6': [0], 'air date_7': [1], '5 april 2010_8': [2]} | ['episode number', 'air date', 'guests', 'three darts challenge', 'musical performance'] | [['2', '5 april 2010', 'aaron johnson , patsy palmer , sharleen spiteri', 'joanna lumley', 'sharleen spiteri - xandu'], ['3', '12 april 2010', 'katy brand , james corden , paloma faith', 'ewan mcgregor', 'paloma faith - upside down'], ['7', '10 may 2010', 'gok wan , yvette fielding , alphabeat', 'sharon osbourne', 'alphabeat - dj ( i could be dancing )'], ['8', '17 may 2010', 'matthew horne , rihanna , the cast of jersey boys', 'meat loaf', 'the cast of jersey boys'], ['9', '7 june 2010', 'joe swash , arlene phillips , mary j blige', 'jermaine jackson', 'mary j blige - each tear']] |
houston rockets all - time roster | https://en.wikipedia.org/wiki/Houston_Rockets_all-time_roster | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11734041-7.html.csv | superlative | within the houson rockets all-time roster , the tallest player in the guard position was 6-8 . | {'scope': 'subset', 'col_superlative': '3', 'row_superlative': '9', 'value_mentioned': 'yes', 'max_or_min': 'max', 'other_col': '4', 'subset': {'col': '4', 'criterion': 'fuzzily_match', 'value': 'guard'}} | {'func': 'eq', 'args': [{'func': 'max', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'position', 'guard'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; position ; guard }', 'tointer': 'select the rows whose position record fuzzily matches to guard .'}, 'height in ft'], 'result': '6 - 8', 'ind': 1, 'tostr': 'max { filter_eq { all_rows ; position ; guard } ; height in ft }', 'tointer': 'select the rows whose position record fuzzily matches to guard . the maximum height in ft record of these rows is 6 - 8 .'}, '6 - 8'], 'result': True, 'ind': 2, 'tostr': 'eq { max { filter_eq { all_rows ; position ; guard } ; height in ft } ; 6 - 8 } = true', 'tointer': 'select the rows whose position record fuzzily matches to guard . the maximum height in ft record of these rows is 6 - 8 .'} | eq { max { filter_eq { all_rows ; position ; guard } ; height in ft } ; 6 - 8 } = true | select the rows whose position record fuzzily matches to guard . the maximum height in ft record of these rows is 6 - 8 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'max_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'position_5': 5, 'guard_6': 6, 'height in ft_7': 7, '6 - 8_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'max_1': 'max', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'position_5': 'position', 'guard_6': 'guard', 'height in ft_7': 'height in ft', '6 - 8_8': '6 - 8'} | {'eq_2': [3], 'result_3': [], 'max_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'position_5': [0], 'guard_6': [0], 'height in ft_7': [1], '6 - 8_8': [2]} | ['player', 'no ( s )', 'height in ft', 'position', 'years for rockets', 'school / club team / country'] | [['gaines , reece reece gaines', '4', '6 - 6', 'guard', '2004 - 05', 'louisville'], ['gambee , dave dave gambee', '20', '6 - 6', 'forward', '1967 - 68', 'oregon state'], ['garland , winston winston garland', '22', '6 - 2', 'guard', '1992 - 93', 'southwest missouri state'], ['garrett , calvin calvin garrett', '00', '6 - 7', 'forward', '1980 - 83', 'austin peay , oral roberts'], ['gibbs , dick dick gibbs', '40', '6 - 5', 'forward', '1971 - 73', 'texas - el paso'], ['godfread , dan dan godfread', '35', '6 - 9', 'forward / center', '1991 - 92', 'evansville'], ['graham , stephen stephen graham', '9', '6 - 6', 'guard / forward', '2005', 'oklahoma state'], ['gray , devin devin gray', '9', '6 - 6', 'guard / forward', '1999 - 2000', 'clemson'], ['green , gerald gerald green', '25', '6 - 8', 'guard / forward', '2008', 'gulf shores academy ( tx )'], ['green , johnny johnny green', '24', '6 - 5', 'forward', '1967 - 68', 'michigan state'], ['griffin , adrian adrian griffin', '7', '6 - 5', 'guard / forward', '2003 - 04', 'seton hall'], ['griffin , eddie eddie griffin', '33', '6 - 10', 'forward', '2001 - 03', 'seton hall'], ['guokas , matt matt guokas', '11', '6 - 6', 'guard', '1973 - 74', "st joseph 's"]] |
fiba eurobasket 2007 squads | https://en.wikipedia.org/wiki/FIBA_EuroBasket_2007_squads | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-12962773-14.html.csv | majority | most of the players listed in the fiba eurobasket 2007 squad had the guard position . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'guard', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'position', 'guard'], 'result': True, 'ind': 0, 'tointer': 'for the position records of all rows , most of them fuzzily match to guard .', 'tostr': 'most_eq { all_rows ; position ; guard } = true'} | most_eq { all_rows ; position ; guard } = true | for the position records of all rows , most of them fuzzily match to guard . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'position_3': 3, 'guard_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'position_3': 'position', 'guard_4': 'guard'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'position_3': [0], 'guard_4': [0]} | ['no', 'player', 'height', 'position', 'year born', 'current club'] | [['4', 'sandi čebular', '1.94', 'guard', '1986', 'unattached'], ['5', 'jaka lakovič', '1.86', 'guard', '1978', 'axa fc barcelona'], ['6', 'aleksandar ćapin', '1.86', 'guard', '1982', 'whirlpool varese'], ['7', 'goran dragić', '1.88', 'guard', '1986', 'tau cerámica'], ['8', 'rasho nesterovič', '2.14', 'center', '1976', 'toronto raptors'], ['9', 'matjaž smodiš', '2.05', 'forward', '1979', 'cska moscow'], ['10', 'uroš slokar', '2.09', 'center', '1983', 'triumph lyubertsy'], ['11', 'jaka klobučar', '1.94', 'guard', '1987', 'geoplin slovan'], ['12', 'goran jagodnik', '2.02', 'forward', '1974', 'hemofarm'], ['13', 'domen lorbek', '1.96', 'guard', '1985', 'mmt estudiantes'], ['14', 'gašper vidmar', '2.08', 'center', '1987', 'fenerbahçe ülker']] |
1989 australian touring car championship | https://en.wikipedia.org/wiki/1989_Australian_Touring_Car_Championship | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16512496-2.html.csv | majority | the majority of races in the 1989 australian touring car championship were won by dick johnson racing team . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'dick johnson', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'winner', 'dick johnson'], 'result': True, 'ind': 0, 'tointer': 'for the winner records of all rows , most of them fuzzily match to dick johnson .', 'tostr': 'most_eq { all_rows ; winner ; dick johnson } = true'} | most_eq { all_rows ; winner ; dick johnson } = true | for the winner records of all rows , most of them fuzzily match to dick johnson . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'winner_3': 3, 'dick johnson_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'winner_3': 'winner', 'dick johnson_4': 'dick johnson'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'winner_3': [0], 'dick johnson_4': [0]} | ['race title', 'circuit', 'city / state', 'date', 'winner', 'team'] | [['amaroo', 'amaroo park', 'sydney , new south wales', '5 march', 'john bowe', 'dick johnson racing'], ['launceston', 'symmons plains raceway', 'launceston , tasmania', '12 march', 'dick johnson', 'dick johnson racing'], ['lakeside', 'lakeside international raceway', 'brisbane , queensland', '16 april', 'dick johnson', 'dick johnson racing'], ['perth', 'barbagallo raceway', 'perth , western australia', '30 april', 'john bowe', 'dick johnson racing'], ['mallala', 'mallala motor sport park', 'mallala , south australia', '7 may', 'dick johnson', 'dick johnson racing'], ['sandown', 'sandown raceway', 'melbourne , victoria', '21 may', 'dick johnson', 'dick johnson racing'], ['winton', 'winton motor raceway', 'benalla , victoria', '4 june', 'george fury', 'nissan motorsport australia'], ['oran park', 'oran park raceway', 'sydney , new south wales', '9 july', 'peter brock', 'mobil 1 racing']] |
swimming at the 2007 world aquatics championships - men 's 50 metre butterfly | https://en.wikipedia.org/wiki/Swimming_at_the_2007_World_Aquatics_Championships_%E2%80%93_Men%27s_50_metre_butterfly | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10289926-15.html.csv | aggregation | jorge arturo arce aita and goksu bicer came in at an average rank of 72 in the 2007 championships . | {'scope': 'all', 'col': '6', 'type': 'average', 'result': '72', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'overall rank'], 'result': '72', 'ind': 0, 'tostr': 'avg { all_rows ; overall rank }'}, '72'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; overall rank } ; 72 } = true', 'tointer': 'the average of the overall rank record of all rows is 72 .'} | round_eq { avg { all_rows ; overall rank } ; 72 } = true | the average of the overall rank record of all rows is 72 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'overall rank_4': 4, '72_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'overall rank_4': 'overall rank', '72_5': '72'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'overall rank_4': [0], '72_5': [1]} | ['heat rank', 'lane', 'swimmer', 'country', 'time', 'overall rank'] | [['1', '1', 'jacinto ayala', 'dominican republic', '24.81', '45'], ['2', '7', 'gabriel melconian', 'uruguay', '25.43', '61'], ['3', '5', 'georgi palazov', 'bulgaria', '25.44', '62'], ['4', '2', 'martin liivamã ¤ gi', 'estonia', '25.47', '63'], ['5', '3', 'daniel william bego', 'malaysia', '25.82', '70'], ['6', '6', 'martin kutscher belgeri', 'uruguay', '25.83', '71'], ['7', '4', 'jorge arturo arce aita', 'costa rica', '25.98', '72'], ['7', '8', 'goksu bicer', 'turkey', '25.98', '72']] |
list of entertainment events in greater moncton | https://en.wikipedia.org/wiki/List_of_entertainment_events_in_Greater_Moncton | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11758927-2.html.csv | majority | most of the events were established in the year 2000 or later . | {'scope': 'all', 'col': '2', 'most_or_all': 'most', 'criterion': 'greater_than_eq', 'value': '2000', 'subset': None} | {'func': 'most_greater_eq', 'args': ['all_rows', 'established', '2000'], 'result': True, 'ind': 0, 'tointer': 'for the established records of all rows , most of them are greater than or equal to 2000 .', 'tostr': 'most_greater_eq { all_rows ; established ; 2000 } = true'} | most_greater_eq { all_rows ; established ; 2000 } = true | for the established records of all rows , most of them are greater than or equal to 2000 . | 1 | 1 | {'most_greater_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'established_3': 3, '2000_4': 4} | {'most_greater_eq_0': 'most_greater_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'established_3': 'established', '2000_4': '2000'} | {'most_greater_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'established_3': [0], '2000_4': [0]} | ['event name', 'established', 'category', 'sub category', 'main venue'] | [['dieppe kite international', '2001', 'sporting', 'kite flying', 'dover park'], ['the frye festival', '2000', 'arts', 'literary', 'university of moncton'], ['hubcap comedy festival', '2000', 'arts', 'comedy', 'various'], ['touchdown atlantic', '2010', 'sporting', 'football', 'moncton stadium'], ['atlantic nationals automotive extravaganza', '2000', 'transportation', 'automotive', 'moncton coliseum'], ['world wine & food expo', '1990', 'arts', 'food & drink', 'moncton coliseum'], ['shediac lobster festival', '1950', 'arts', 'food & drink', 'shediac festival grounds'], ['mosaã ¯ q multicultural festival', '2004', 'festival', 'multicultural', 'moncton city hall plaza']] |
katie o'brien | https://en.wikipedia.org/wiki/Katie_O%27Brien | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11961200-6.html.csv | unique | katie o'brien 's only match that ended with a w/o was against sorena cirstea . | {'scope': 'all', 'row': '8', 'col': '5', 'col_other': '4', 'criterion': 'equal', 'value': 'w / o', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'score in the final', 'w / o'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose score in the final record fuzzily matches to w / o .', 'tostr': 'filter_eq { all_rows ; score in the final ; w / o }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; score in the final ; w / o } }', 'tointer': 'select the rows whose score in the final record fuzzily matches to w / o . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'score in the final', 'w / o'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose score in the final record fuzzily matches to w / o .', 'tostr': 'filter_eq { all_rows ; score in the final ; w / o }'}, 'partnering'], 'result': 'sorana cîrstea', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; score in the final ; w / o } ; partnering }'}, 'sorana cîrstea'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; score in the final ; w / o } ; partnering } ; sorana cîrstea }', 'tointer': 'the partnering record of this unqiue row is sorana cîrstea .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; score in the final ; w / o } } ; eq { hop { filter_eq { all_rows ; score in the final ; w / o } ; partnering } ; sorana cîrstea } } = true', 'tointer': 'select the rows whose score in the final record fuzzily matches to w / o . there is only one such row in the table . the partnering record of this unqiue row is sorana cîrstea .'} | and { only { filter_eq { all_rows ; score in the final ; w / o } } ; eq { hop { filter_eq { all_rows ; score in the final ; w / o } ; partnering } ; sorana cîrstea } } = true | select the rows whose score in the final record fuzzily matches to w / o . there is only one such row in the table . the partnering record of this unqiue row is sorana cîrstea . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'score in the final_7': 7, 'w / o_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'partnering_9': 9, 'sorana cîrstea_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'score in the final_7': 'score in the final', 'w / o_8': 'w / o', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'partnering_9': 'partnering', 'sorana cîrstea_10': 'sorana cîrstea'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'score in the final_7': [0], 'w / o_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'partnering_9': [2], 'sorana cîrstea_10': [3]} | ['outcome', 'tournament', 'surface', 'partnering', 'score in the final'] | [['runner - up', '10000 tipton , great britain', 'hard ( i )', 'melanie south', '4 - 6 , 2 - 6'], ['runner - up', '10000 hull , great britain', 'hard ( i )', 'melanie south', '6 - 4 , 3 - 6 , 5 - 7'], ['runner - up', '25000 jersey , great britain', 'hard ( i )', 'melanie south', '3 - 6 , 1 - 6'], ['winner', '25000 madrid , spain', 'hard', 'sorana cîrstea', '6 - 4 , 6 - 4'], ['runner - up', '25000 nottingham , great britain', 'hard', 'margit rüütel', '2 - 6 , 6 - 2 , 6 - 7 ( 1 - 7 )'], ['winner', '25000 jersey , great britain', 'hard ( i )', 'margit rüütel', '7 - 5 , 6 - 4'], ['runner - up', '25000 glasgow , great britain', 'hard ( i )', 'margit rüütel', '4 - 6 , 3 - 6'], ['runner - up', '25000 istanbul , turkey', 'hard ( i )', 'sorana cîrstea', 'w / o'], ['runner - up', '25000 jersey , great britain', 'hard ( i )', 'georgie stoop', '0 - 6 , 4 - 6'], ['runner - up', '25000 sutton , great britain', 'hard ( i )', 'rebecca marino', '3 - 6 , 3 - 6'], ['runner - up', '50000 nottingham , great britain', 'grass', 'naomi broady', '3 - 6 , 6 - 2 ,']] |
2008 - 09 philadelphia 76ers season | https://en.wikipedia.org/wiki/2008%E2%80%9309_Philadelphia_76ers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17323042-7.html.csv | ordinal | the philadelphia 76ers ' game on january 17 recorded their 2nd highest attendance of the 2008 - 09 season . | {'row': '9', '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', 'location attendance', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; location attendance ; 2 }'}, 'date'], 'result': 'january 17', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; location attendance ; 2 } ; date }'}, 'january 17'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; location attendance ; 2 } ; date } ; january 17 } = true', 'tointer': 'select the row whose location attendance record of all rows is 2nd maximum . the date record of this row is january 17 .'} | eq { hop { nth_argmax { all_rows ; location attendance ; 2 } ; date } ; january 17 } = true | select the row whose location attendance record of all rows is 2nd maximum . the date record of this row is january 17 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'location attendance_5': 5, '2_6': 6, 'date_7': 7, 'january 17_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', 'location attendance_5': 'location attendance', '2_6': '2', 'date_7': 'date', 'january 17_8': 'january 17'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'location attendance_5': [0], '2_6': [0], 'date_7': [1], 'january 17_8': [2]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record'] | [['32', 'january 2', 'dallas', 'l 86 - 96 ( ot )', 'andre iguodala ( 22 )', 'andre miller ( 11 )', 'andre iguodala ( 5 )', 'american airlines center 20327', '13 - 19'], ['33', 'january 3', 'san antonio', 'l 106 - 108 ( ot )', 'andre miller ( 28 )', 'andre iguodala ( 8 )', 'andre iguodala ( 8 )', 'at & t center 18797', '13 - 20'], ['34', 'january 6', 'houston', 'w 104 - 96 ( ot )', 'andre iguodala ( 28 )', 'marreese speights ( 8 )', 'andre miller , louis williams ( 8 )', 'wachovia center 14858', '14 - 20'], ['35', 'january 7', 'milwaukee', 'w 110 - 105 ( ot )', 'andre miller ( 28 )', 'andre miller ( 9 )', 'andre iguodala ( 7 )', 'bradley center 13381', '15 - 20'], ['36', 'january 9', 'charlotte', 'w 93 - 87 ( ot )', 'andre miller ( 22 )', 'samuel dalembert ( 9 )', 'andre iguodala ( 7 )', 'wachovia center 14235', '16 - 20'], ['37', 'january 11', 'atlanta', 'w 109 - 94 ( ot )', 'andre iguodala ( 27 )', 'thaddeus young ( 9 )', 'andre iguodala ( 9 )', 'philips arena 15079', '17 - 20'], ['38', 'january 14', 'portland', 'w 100 - 79 ( ot )', 'andre iguodala ( 29 )', 'samuel dalembert ( 9 )', 'louis williams , andre iguodala , andre miller ( 6 )', 'wachovia center 14561', '18 - 20'], ['39', 'january 16', 'san antonio', 'w 109 - 87 ( ot )', 'thaddeus young ( 27 )', 'samuel dalembert ( 12 )', 'andre iguodala ( 8 )', 'wachovia center 18739', '19 - 20'], ['40', 'january 17', 'new york', 'w 107 - 97 ( ot )', 'andre iguodala ( 28 )', 'andre iguodala , thaddeus young ( 10 )', 'andre miller ( 8 )', 'madison square garden 19408', '20 - 20'], ['41', 'january 19', 'dallas', 'l 93 - 95 ( ot )', 'louis williams ( 25 )', 'andre iguodala ( 12 )', 'andre miller ( 7 )', 'wachovia center 14503', '20 - 21'], ['42', 'january 24', 'new york', 'w 116 - 110 ( ot )', 'andre iguodala ( 24 )', 'samuel dalembert ( 17 )', 'andre iguodala ( 6 )', 'wachovia center 19239', '21 - 21'], ['43', 'january 26', 'new orleans', 'l 86 - 101 ( ot )', 'thaddeus young ( 22 )', 'samuel dalembert ( 12 )', 'andre iguodala ( 7 )', 'new orleans arena 16131', '21 - 22'], ['44', 'january 28', 'houston', 'w 95 - 93 ( ot )', 'andre iguodala ( 20 )', 'samuel dalembert ( 13 )', 'andre miller ( 7 )', 'toyota center 15544', '22 - 22'], ['45', 'january 30', 'washington', 'w 104 - 94 ( ot )', 'andre iguodala , willie green ( 20 )', 'thaddeus young ( 9 )', 'andre miller ( 9 )', 'wachovia center 15528', '23 - 22'], ['46', 'january 31', 'new jersey', 'l 83 - 85 ( ot )', 'andre miller ( 19 )', 'elton brand ( 9 )', 'andre miller ( 7 )', 'wachovia center 17783', '23 - 23']] |
91st united states congress | https://en.wikipedia.org/wiki/91st_United_States_Congress | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1204065-2.html.csv | ordinal | michael j harrington was the second earliest appointed successor in the 91st united states congress . | {'row': '2', 'col': '5', 'order': '2', 'col_other': '4', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'date successor seated', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; date successor seated ; 2 }'}, 'successor'], 'result': 'michael j harrington ( d )', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; date successor seated ; 2 } ; successor }'}, 'michael j harrington ( d )'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; date successor seated ; 2 } ; successor } ; michael j harrington ( d ) } = true', 'tointer': 'select the row whose date successor seated record of all rows is 2nd minimum . the successor record of this row is michael j harrington ( d ) .'} | eq { hop { nth_argmin { all_rows ; date successor seated ; 2 } ; successor } ; michael j harrington ( d ) } = true | select the row whose date successor seated record of all rows is 2nd minimum . the successor record of this row is michael j harrington ( d ) . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'date successor seated_5': 5, '2_6': 6, 'successor_7': 7, 'michael j harrington (d)_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', 'date successor seated_5': 'date successor seated', '2_6': '2', 'successor_7': 'successor', 'michael j harrington (d)_8': 'michael j harrington ( d )'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'date successor seated_5': [0], '2_6': [0], 'successor_7': [1], 'michael j harrington (d)_8': [2]} | ['district', 'vacator', 'reason for change', 'successor', 'date successor seated'] | [['tennessee 8th', 'robert a everett ( d )', 'died january 26 , 1969', 'ed jones ( d )', 'march 25 , 1969'], ['massachusetts 6th', 'william h bates ( r )', 'died june 22 , 1969', 'michael j harrington ( d )', 'september 30 , 1969'], ['illinois 6th', 'daniel j ronan ( d )', 'died august 13 , 1969', 'george w collins ( d )', 'november 3 , 1970'], ['california 24th', 'glenard p lipscomb ( r )', 'died february 1 , 1970', 'john h rousselot ( r )', 'june 30 , 1970'], ['california 35th', 'james b utt ( r )', 'died march 1 , 1970', 'john g schmitz ( r )', 'june 30 , 1970'], ['connecticut 2nd', 'william st onge ( d )', 'died may 1 , 1970', 'robert h steele ( r )', 'november 3 , 1970'], ['ohio 19th', 'michael j kirwan ( d )', 'died july 27 , 1970', 'charles j carney ( d )', 'november 3 , 1970'], ['pennsylvania 9th', 'george watkins ( r )', 'died august 7 , 1970', 'john h ware iii ( r )', 'november 3 , 1970'], ['illinois 1st', 'william l dawson ( d )', 'died november 9 , 1970', 'vacant', 'not filled this term']] |
jet engine | https://en.wikipedia.org/wiki/Jet_engine | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15944-5.html.csv | count | four jet engines had exhaust velocities of over 10,000 m/s . | {'scope': 'all', 'criterion': 'greater_than', 'value': '10000', 'result': '4', 'col': '6', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'effective exhaust velocity ( m / s )', '10000'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose effective exhaust velocity ( m / s ) record is greater than 10000 .', 'tostr': 'filter_greater { all_rows ; effective exhaust velocity ( m / s ) ; 10000 }'}], 'result': '4', 'ind': 1, 'tostr': 'count { filter_greater { all_rows ; effective exhaust velocity ( m / s ) ; 10000 } }', 'tointer': 'select the rows whose effective exhaust velocity ( m / s ) record is greater than 10000 . the number of such rows is 4 .'}, '4'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_greater { all_rows ; effective exhaust velocity ( m / s ) ; 10000 } } ; 4 } = true', 'tointer': 'select the rows whose effective exhaust velocity ( m / s ) record is greater than 10000 . the number of such rows is 4 .'} | eq { count { filter_greater { all_rows ; effective exhaust velocity ( m / s ) ; 10000 } } ; 4 } = true | select the rows whose effective exhaust velocity ( m / s ) record is greater than 10000 . 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, 'effective exhaust velocity (m / s)_5': 5, '10000_6': 6, '4_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_greater_0': 'filter_greater', 'all_rows_4': 'all_rows', 'effective exhaust velocity (m / s)_5': 'effective exhaust velocity ( m / s )', '10000_6': '10000', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_greater_0': [1], 'all_rows_4': [0], 'effective exhaust velocity (m / s)_5': [0], '10000_6': [0], '4_7': [2]} | ['engine type', 'scenario', 'sfc in lb / ( lbf h )', 'sfc in g / ( kn s )', 'specific impulse ( s )', 'effective exhaust velocity ( m / s )'] | [['nk - 33 rocket engine', 'vacuum', '10.9', '309', '331', '3240'], ['ssme rocket engine', 'space shuttle vacuum', '7.95', '225', '453', '4423'], ['ramjet', 'mach 1', '4.5', '127', '800', '7877'], ['j - 58 turbojet', 'sr - 71 at mach 3.2 ( wet )', '1.9', '53.8', '1900', '18587'], ['rolls - royce / snecma olympus 593', 'concorde mach 2 cruise ( dry )', '1.195', '33.8', '3012', '29553'], ['cf6 - 80c2b1f turbofan', 'boeing 747 - 400 cruise', '0.605', '17.1', '5950', '58400'], ['general electric cf6 turbofan', 'sea level', '0.307', '8.696', '11700', '115000']] |
2008 - 09 nbl season | https://en.wikipedia.org/wiki/2008%E2%80%9309_NBL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16653153-9.html.csv | majority | all of the games of the 2008-09 nbl season were played in september . | {'scope': 'all', 'col': '1', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'september', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'date', 'september'], 'result': True, 'ind': 0, 'tointer': 'for the date records of all rows , all of them fuzzily match to september .', 'tostr': 'all_eq { all_rows ; date ; september } = true'} | all_eq { all_rows ; date ; september } = true | for the date records of all rows , all of them fuzzily match to september . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'date_3': 3, 'september_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'date_3': 'date', 'september_4': 'september'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'date_3': [0], 'september_4': [0]} | ['date', 'home team', 'score', 'away team', 'venue', 'box score', 'report'] | [['24 september', 'adelaide 36ers', '99 - 89', 'sydney spirit', 'distinctive homes dome', 'box score', '-'], ['25 september', 'new zealand breakers', '120 - 111', 'melbourne tigers', 'north shore events centre', 'box score', '-'], ['25 september', 'south dragons', '89 - 91', 'townsville crocodiles', 'hisense arena', 'box score', '-'], ['26 september', 'perth wildcats', '94 - 80', 'gold coast blaze', 'challenge stadium', 'box score', '-'], ['27 september', 'townsville crocodiles', '100 - 96', 'cairns taipans', 'townsville entertainment centre', 'box score', '-'], ['27 september', 'sydney spirit', '112 - 105', 'adelaide 36ers', 'ais arena', 'box score', '-']] |
1965 buffalo bills season | https://en.wikipedia.org/wiki/1965_Buffalo_Bills_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16008156-2.html.csv | superlative | the game played on week 15 of the 1965 buffalo bills season drew the highest crowd attendance . | {'scope': 'all', 'col_superlative': '5', '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', 'attendance'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; attendance }'}, 'week'], 'result': '15', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; attendance } ; week }'}, '15'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; attendance } ; week } ; 15 } = true', 'tointer': 'select the row whose attendance record of all rows is maximum . the week record of this row is 15 .'} | eq { hop { argmax { all_rows ; attendance } ; week } ; 15 } = true | select the row whose attendance record of all rows is maximum . the week record of this row is 15 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'num_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'attendance_5': 5, 'week_6': 6, '15_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'num_hop_1': 'num_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'attendance_5': 'attendance', 'week_6': 'week', '15_7': '15'} | {'eq_2': [3], 'result_3': [], 'num_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'attendance_5': [0], 'week_6': [1], '15_7': [2]} | ['week', 'date', 'opponent', 'result', 'attendance'] | [['1', 'september 11 , 1965', 'boston patriots', 'w 24 - 7', '45502'], ['2', 'september 19 , 1965', 'denver broncos', 'w 30 - 15', '30682'], ['3', 'september 26 , 1965', 'new york jets', 'w 33 - 21', '45056'], ['4', 'october 3 , 1965', 'oakland raiders', 'w 17 - 12', '41256'], ['5', 'october 10 , 1965', 'san diego chargers', 'l 34 - 3', '45260'], ['6', 'october 17 , 1965', 'kansas city chiefs', 'w 23 - 7', '26941'], ['7', 'october 24 , 1965', 'denver broncos', 'w 31 - 13', '45046'], ['8', 'october 31 , 1965', 'houston oilers', 'l 19 - 17', '44267'], ['9', 'november 7 , 1965', 'boston patriots', 'w 23 - 7', '24415'], ['10', 'november 14 , 1965', 'oakland raiders', 'w 17 - 14', '19352'], ['12', 'november 25 , 1965', 'san diego chargers', 't 20 - 20', '27473'], ['13', 'december 5 , 1965', 'houston oilers', 'w 29 - 18', '23087'], ['14', 'december 12 , 1965', 'kansas city chiefs', 'w 34 - 25', '40298'], ['15', 'december 19 , 1965', 'new york jets', 'l 14 - 12', '57396']] |
1972 san francisco 49ers season | https://en.wikipedia.org/wiki/1972_San_Francisco_49ers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16714074-2.html.csv | majority | in the 1972 san francisco 49ers season , the 49ers won most of their games in november . | {'scope': 'subset', 'col': '4', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': 'w', 'subset': {'col': '2', 'criterion': 'fuzzily_match', 'value': 'november'}} | {'func': 'most_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', 'november'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; date ; november }', 'tointer': 'select the rows whose date record fuzzily matches to november .'}, 'result', 'w'], 'result': True, 'ind': 1, 'tointer': 'select the rows whose date record fuzzily matches to november . for the result records of these rows , most of them fuzzily match to w .', 'tostr': 'most_eq { filter_eq { all_rows ; date ; november } ; result ; w } = true'} | most_eq { filter_eq { all_rows ; date ; november } ; result ; w } = true | select the rows whose date record fuzzily matches to november . for the result records of these rows , most of them fuzzily match to w . | 2 | 2 | {'most_str_eq_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, 'date_4': 4, 'november_5': 5, 'result_6': 6, 'w_7': 7} | {'most_str_eq_1': 'most_str_eq', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'date_4': 'date', 'november_5': 'november', 'result_6': 'result', 'w_7': 'w'} | {'most_str_eq_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'date_4': [0], 'november_5': [0], 'result_6': [1], 'w_7': [1]} | ['week', 'date', 'opponent', 'result', 'attendance'] | [['1', 'september 17 , 1972', 'san diego chargers', 'w 34 - 3', '59438'], ['2', 'september 24 , 1972', 'buffalo bills', 'l 27 - 20', '45845'], ['3', 'october 1 , 1972', 'new orleans saints', 'w 37 - 2', '69840'], ['4', 'october 8 , 1972', 'los angeles rams', 'l 31 - 7', '77382'], ['5', 'october 15 , 1972', 'new york giants', 'l 23 - 17', '58606'], ['6', 'october 22 , 1972', 'new orleans saints', 't 20 - 20', '59167'], ['7', 'october 29 , 1972', 'atlanta falcons', 'w 49 - 14', '58850'], ['8', 'november 5 , 1972', 'green bay packers', 'l 34 - 24', '47897'], ['9', 'november 12 , 1972', 'baltimore colts', 'w 24 - 21', '61214'], ['10', 'november 19 , 1972', 'chicago bears', 'w 34 - 21', '55701'], ['11', 'november 23 , 1972', 'dallas cowboys', 'w 31 - 10', '65124'], ['12', 'december 4 , 1972', 'los angeles rams', 'l 26 - 16', '61214'], ['13', 'december 10 , 1972', 'atlanta falcons', 'w 20 - 0', '61214'], ['14', 'december 16 , 1972', 'minnesota vikings', 'w 20 - 17', '61214']] |
1945 vfl season | https://en.wikipedia.org/wiki/1945_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10809271-4.html.csv | superlative | the largest crowd size was when the venue was punt road oval . | {'scope': 'all', 'col_superlative': '6', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '5', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'crowd'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; crowd }'}, 'venue'], 'result': 'punt road oval', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; crowd } ; venue }'}, 'punt road oval'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; crowd } ; venue } ; punt road oval } = true', 'tointer': 'select the row whose crowd record of all rows is maximum . the venue record of this row is punt road oval .'} | eq { hop { argmax { all_rows ; crowd } ; venue } ; punt road oval } = true | select the row whose crowd record of all rows is maximum . the venue record of this row is punt road oval . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'crowd_5': 5, 'venue_6': 6, 'punt road oval_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'crowd_5': 'crowd', 'venue_6': 'venue', 'punt road oval_7': 'punt road oval'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'crowd_5': [0], 'venue_6': [1], 'punt road oval_7': [2]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['melbourne', '9.11 ( 65 )', 'richmond', '13.7 ( 85 )', 'punt road oval', '23000', '12 may 1945'], ['geelong', '9.13 ( 67 )', 'south melbourne', '10.23 ( 83 )', 'kardinia park', '10500', '12 may 1945'], ['footscray', '11.13 ( 79 )', 'north melbourne', '14.8 ( 92 )', 'western oval', '15000', '12 may 1945'], ['collingwood', '13.23 ( 101 )', 'hawthorn', '9.9 ( 63 )', 'victoria park', '11000', '12 may 1945'], ['carlton', '12.12 ( 84 )', 'fitzroy', '11.11 ( 77 )', 'princes park', '12000', '12 may 1945'], ['st kilda', '14.17 ( 101 )', 'essendon', '23.18 ( 156 )', 'junction oval', '12000', '12 may 1945']] |
coins of the republic of ireland | https://en.wikipedia.org/wiki/Coins_of_the_Republic_of_Ireland | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1682865-1.html.csv | superlative | of the coins of the republic of ireland , the last one withdrawn was the florin . | {'scope': 'all', 'col_superlative': '6', 'row_superlative': '7', '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', 'withdrawal'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; withdrawal }'}, 'irish name'], 'result': 'flóirín', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; withdrawal } ; irish name }'}, 'flóirín'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; withdrawal } ; irish name } ; flóirín } = true', 'tointer': 'select the row whose withdrawal record of all rows is maximum . the irish name record of this row is flóirín .'} | eq { hop { argmax { all_rows ; withdrawal } ; irish name } ; flóirín } = true | select the row whose withdrawal record of all rows is maximum . the irish name record of this row is flóirín . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'withdrawal_5': 5, 'irish name_6': 6, 'flóirín_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'withdrawal_5': 'withdrawal', 'irish name_6': 'irish name', 'flóirín_7': 'flóirín'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'withdrawal_5': [0], 'irish name_6': [1], 'flóirín_7': [2]} | ['english name', 'irish name', 'numeral', 'reverse', 'introduction', 'withdrawal', '1 fraction'] | [['farthing', 'feoirling', '¼ d', 'woodcock', '12 december 1928', '1 january 1962', '1 / 960'], ['halfpenny', 'leath phingin', '½ d', 'sow and litter', '12 december 1928', '1 august 1969', '1 / 480'], ['penny', 'pingin', '1d', 'hen and chickens', '12 december 1928', '1 january 1972', '1 / 240'], ['threepence', 'leath reul', '3d', 'hare', '12 december 1928', '1 january 1972', '1 / 80'], ['sixpence', 'reul', '6d', 'wolfhound', '12 december 1928', '1 january 1972', '1 / 40'], ['shilling', 'scilling', '1s', 'bull', '12 december 1928', '1 january 1993', '1 / 20'], ['florin', 'flóirín', '2s', 'salmon', '12 december 1928', '1 june 1994', '1 / 10'], ['half - crown', 'leath choróin', '2s6d', 'horse', '12 december 1928', '1 january 1970', '1 / 8']] |
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 | unique | heath lane is the only primary school in dacorum of the nursery type . | {'scope': 'all', 'row': '6', 'col': '3', 'col_other': '1', 'criterion': 'equal', 'value': 'nursery', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'type', 'nursery'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose type record fuzzily matches to nursery .', 'tostr': 'filter_eq { all_rows ; type ; nursery }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; type ; nursery } }', 'tointer': 'select the rows whose type record fuzzily matches to nursery . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'type', 'nursery'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose type record fuzzily matches to nursery .', 'tostr': 'filter_eq { all_rows ; type ; nursery }'}, 'name'], 'result': 'heath lane', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; type ; nursery } ; name }'}, 'heath lane'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; type ; nursery } ; name } ; heath lane }', 'tointer': 'the name record of this unqiue row is heath lane .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; type ; nursery } } ; eq { hop { filter_eq { all_rows ; type ; nursery } ; name } ; heath lane } } = true', 'tointer': 'select the rows whose type record fuzzily matches to nursery . there is only one such row in the table . the name record of this unqiue row is heath lane .'} | and { only { filter_eq { all_rows ; type ; nursery } } ; eq { hop { filter_eq { all_rows ; type ; nursery } ; name } ; heath lane } } = true | select the rows whose type record fuzzily matches to nursery . there is only one such row in the table . the name record of this unqiue row is heath lane . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'type_7': 7, 'nursery_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'name_9': 9, 'heath lane_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'type_7': 'type', 'nursery_8': 'nursery', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'name_9': 'name', 'heath lane_10': 'heath lane'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'type_7': [0], 'nursery_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'name_9': [2], 'heath lane_10': [3]} | ['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']] |
colonial turf cup | https://en.wikipedia.org/wiki/Colonial_Turf_Cup | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11237859-1.html.csv | superlative | showing up had the lowest time of all these horses . | {'scope': 'all', 'col_superlative': '7', 'row_superlative': '6', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '1', 'subset': None} | {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'argmin', 'args': ['all_rows', 'time'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; time }'}, 'year'], 'result': '2006', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; time } ; year }'}, '2006'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmin { all_rows ; time } ; year } ; 2006 } = true', 'tointer': 'select the row whose time record of all rows is minimum . the year record of this row is 2006 .'} | eq { hop { argmin { all_rows ; time } ; year } ; 2006 } = true | select the row whose time record of all rows is minimum . the year record of this row is 2006 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'num_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'time_5': 5, 'year_6': 6, '2006_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'num_hop_1': 'num_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'time_5': 'time', 'year_6': 'year', '2006_7': '2006'} | {'eq_2': [3], 'result_3': [], 'num_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'time_5': [0], 'year_6': [1], '2006_7': [2]} | ['year', 'winner', 'jockey', 'trainer', 'owner', 'distance ( miles )', 'time'] | [['2011', 'rahystrada', 'sheldon russell', 'byron hughes', 'robert courtney', '1 - 3 / 16', '1:54.68'], ['2010', "paddy o'prado", 'kent desormeaux', 'dale romans', 'donegal racing', '1 - 3 / 16', '1:54.20'], ['2009', 'battle of hastings', 'tyler baze', 'jeff mullins', 'michael house', '1 - 3 / 16', '1:57.79'], ['2008', "sailor 's cap", 'alan garcia', 'james j toner', 'team valor international', '1 - 3 / 16', '2:04.42'], ['2007', 'summer doldrums', 'jose lezcano', 'richard a violette , jr', 'klaravich stables', '1 - 3 / 16', '1:55.68'], ['2006', 'showing up', 'cornelio velã ¡ squez', 'barclay tagg', 'lael stables', '1 - 3 / 16', '1:52.98'], ['2005', 'english channel', 'john velazquez', 'todd pletcher', 'james t scatuorchio', '1 - 3 / 16', '1:56:37']] |
sébastien bourdais | https://en.wikipedia.org/wiki/S%C3%A9bastien_Bourdais | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1019053-15.html.csv | aggregation | the participations of sébastien bourdais on the grand-am rolex sports car series have averaged around 53 points for each race . | {'scope': 'all', 'col': '7', 'type': 'average', 'result': '53', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'points'], 'result': '53', 'ind': 0, 'tostr': 'avg { all_rows ; points }'}, '53'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; points } ; 53 } = true', 'tointer': 'the average of the points record of all rows is 53 .'} | round_eq { avg { all_rows ; points } ; 53 } = true | the average of the points record of all rows is 53 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'points_4': 4, '53_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'points_4': 'points', '53_5': '53'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'points_4': [0], '53_5': [1]} | ['year', 'team', 'make', 'engine', 'class', 'rank', 'points'] | [['2005', 'newman racing / silverstone racing', 'crawford dp03', 'ford', 'dp', '89th', '6'], ['2006', 'doran racing', 'doran je4', 'ford', 'dp', '108th', '3'], ['2010', 'crown royal / npn racing', 'riley mk xi', 'bmw 5.0 l v8', 'dp', 'nc', '0'], ['2012', 'starworks motorsport', 'riley mk xxvi', 'ford', 'dp', '17th', '97'], ['2013', 'starworks motorsport', 'riley mk xxvi', 'ford', 'dp', '18th', '160']] |
international speedway corporation | https://en.wikipedia.org/wiki/International_Speedway_Corporation | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1245148-1.html.csv | majority | of the tracks under the international speedway corporation , most of them have a seating capacity under 100000 . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'less_than', 'value': '100000', 'subset': None} | {'func': 'most_less', 'args': ['all_rows', 'seating', '100000'], 'result': True, 'ind': 0, 'tointer': 'for the seating records of all rows , most of them are less than 100000 .', 'tostr': 'most_less { all_rows ; seating ; 100000 } = true'} | most_less { all_rows ; seating ; 100000 } = true | for the seating records of all rows , most of them are less than 100000 . | 1 | 1 | {'most_less_0': 0, 'result_1': 1, 'all_rows_2': 2, 'seating_3': 3, '100000_4': 4} | {'most_less_0': 'most_less', 'result_1': 'true', 'all_rows_2': 'all_rows', 'seating_3': 'seating', '100000_4': '100000'} | {'most_less_0': [1], 'result_1': [], 'all_rows_2': [0], 'seating_3': [0], '100000_4': [0]} | ['track name', 'location', 'length', 'seating', 'year opened', 'year acquired'] | [['auto club speedway', 'fontana , ca', '-', '92000', '1997', '1999'], ['chicagoland speedway', 'joliet , il', '-', '75000', '2001', '2007'], ['darlington raceway', 'darlington , sc', '-', '63000', '1950', '1982'], ['daytona international speedway', 'daytona beach , fl', '-', '168000', '1959', '1959'], ['homestead - miami speedway', 'homestead , fl', '-', '65000', '1995', '1999'], ['kansas speedway', 'kansas city , ks', '-', '81687', '2001', '2001'], ['martinsville speedway', 'ridgeway , va', '-', '65000', '1947', '2004'], ['michigan international speedway', 'brooklyn , mi', '-', '137243', '1968', '1999'], ['phoenix international raceway', 'avondale , az', '-', '76812', '1964', '1997'], ['richmond international raceway', 'richmond , va', '-', '107097', '1946', '1999'], ['route 66 raceway', 'joliet , il', 'miles ( km ) dragstrip', '30000', '1998', '2007'], ['talladega superspeedway', 'talladega , al', '-', '175000', '1969', '1969']] |
martin kaymer | https://en.wikipedia.org/wiki/Martin_Kaymer | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12821159-8.html.csv | superlative | martin kaymer had the highest margin of victory on june 22 , 2006 . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '3', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'margin of victory'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; margin of victory }'}, 'date'], 'result': '22 jun 2006', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; margin of victory } ; date }'}, '22 jun 2006'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; margin of victory } ; date } ; 22 jun 2006 } = true', 'tointer': 'select the row whose margin of victory record of all rows is maximum . the date record of this row is 22 jun 2006 .'} | eq { hop { argmax { all_rows ; margin of victory } ; date } ; 22 jun 2006 } = true | select the row whose margin of victory record of all rows is maximum . the date record of this row is 22 jun 2006 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'margin of victory_5': 5, 'date_6': 6, '22 jun 2006_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'margin of victory_5': 'margin of victory', 'date_6': 'date', '22 jun 2006_7': '22 jun 2006'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'margin of victory_5': [0], 'date_6': [1], '22 jun 2006_7': [2]} | ['date', 'tournament', 'winning score', 'margin of victory', 'runner - up'] | [['14 jun 2005', 'central german classic ( as an amateur )', '- 19 ( 67 + 64 + 66 = 197 )', '5 strokes', 'wolfgang huget'], ['1 jun 2006', 'friedberg classic', '- 13 ( 70 + 64 + 69 = 203 )', '7 strokes', 'mark grabow schytter'], ['22 jun 2006', 'habsburg classic', '- 27 ( 68 + 59 + 62 = 189 )', '10 strokes', 'rick huiskamp'], ['4 jul 2006', 'coburg brose open', '- 12 ( 68 + 68 + 68 = 204 )', '4 strokes', 'lasse jensen'], ['12 jul 2006', 'winterbrock classic', '- 17 ( 68 + 60 + 71 = 199 )', '1 stroke', 'richard treis'], ['17 aug 2006', 'hockenberg classic', '- 17 ( 72 + 64 + 63 = 199 )', '7 strokes', 'christoph günther']] |
1958 san francisco 49ers season | https://en.wikipedia.org/wiki/1958_San_Francisco_49ers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18589208-1.html.csv | majority | the san francisco 49ers lost most games in the month of november during the 1958 season . | {'scope': 'subset', 'col': '4', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': 'l', 'subset': {'col': '2', 'criterion': 'fuzzily_match', 'value': 'november'}} | {'func': 'most_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', 'november'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; date ; november }', 'tointer': 'select the rows whose date record fuzzily matches to november .'}, 'result', 'l'], 'result': True, 'ind': 1, 'tointer': 'select the rows whose date record fuzzily matches to november . for the result records of these rows , most of them fuzzily match to l .', 'tostr': 'most_eq { filter_eq { all_rows ; date ; november } ; result ; l } = true'} | most_eq { filter_eq { all_rows ; date ; november } ; result ; l } = true | select the rows whose date record fuzzily matches to november . for the result records of these rows , most of them fuzzily match to l . | 2 | 2 | {'most_str_eq_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, 'date_4': 4, 'november_5': 5, 'result_6': 6, 'l_7': 7} | {'most_str_eq_1': 'most_str_eq', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'date_4': 'date', 'november_5': 'november', 'result_6': 'result', 'l_7': 'l'} | {'most_str_eq_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'date_4': [0], 'november_5': [0], 'result_6': [1], 'l_7': [1]} | ['week', 'date', 'opponent', 'result', 'attendance'] | [['1', 'september 28 , 1958', 'pittsburgh steelers', 'w 23 - 20', '51856'], ['2', 'october 5 , 1958', 'los angeles rams', 'l 33 - 3', '59826'], ['3', 'october 12 , 1958', 'chicago bears', 'l 28 - 6', '45310'], ['4', 'october 19 , 1958', 'philadelphia eagles', 'w 30 - 24', '33110'], ['5', 'october 26 , 1958', 'chicago bears', 'l 27 - 14', '59441'], ['6', 'november 2 , 1958', 'detroit lions', 'w 24 - 21', '59350'], ['7', 'november 9 , 1958', 'los angeles rams', 'l 56 - 7', '95082'], ['8', 'november 16 , 1958', 'detroit lions', 'l 35 - 21', '54523'], ['9', 'november 23 , 1958', 'green bay packers', 'w 33 - 12', '43819'], ['10', 'november 30 , 1958', 'baltimore colts', 'l 35 - 27', '57557'], ['11', 'december 7 , 1958', 'green bay packers', 'w 48 - 21', '50793'], ['12', 'december 14 , 1958', 'baltimore colts', 'w 21 - 12', '58334']] |
2008 - 09 süper lig | https://en.wikipedia.org/wiki/2008%E2%80%9309_S%C3%BCper_Lig | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-17356873-1.html.csv | unique | antalyaspor is the only team where mardan is the shirt sponsor . | {'scope': 'all', 'row': '3', 'col': '7', 'col_other': '1', 'criterion': 'equal', 'value': 'mardan', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'shirt sponsor', 'mardan'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose shirt sponsor record fuzzily matches to mardan .', 'tostr': 'filter_eq { all_rows ; shirt sponsor ; mardan }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; shirt sponsor ; mardan } }', 'tointer': 'select the rows whose shirt sponsor record fuzzily matches to mardan . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'shirt sponsor', 'mardan'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose shirt sponsor record fuzzily matches to mardan .', 'tostr': 'filter_eq { all_rows ; shirt sponsor ; mardan }'}, 'team'], 'result': 'antalyaspor', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; shirt sponsor ; mardan } ; team }'}, 'antalyaspor'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; shirt sponsor ; mardan } ; team } ; antalyaspor }', 'tointer': 'the team record of this unqiue row is antalyaspor .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; shirt sponsor ; mardan } } ; eq { hop { filter_eq { all_rows ; shirt sponsor ; mardan } ; team } ; antalyaspor } } = true', 'tointer': 'select the rows whose shirt sponsor record fuzzily matches to mardan . there is only one such row in the table . the team record of this unqiue row is antalyaspor .'} | and { only { filter_eq { all_rows ; shirt sponsor ; mardan } } ; eq { hop { filter_eq { all_rows ; shirt sponsor ; mardan } ; team } ; antalyaspor } } = true | select the rows whose shirt sponsor record fuzzily matches to mardan . there is only one such row in the table . the team record of this unqiue row is antalyaspor . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'shirt sponsor_7': 7, 'mardan_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'team_9': 9, 'antalyaspor_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'shirt sponsor_7': 'shirt sponsor', 'mardan_8': 'mardan', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'team_9': 'team', 'antalyaspor_10': 'antalyaspor'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'shirt sponsor_7': [0], 'mardan_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'team_9': [2], 'antalyaspor_10': [3]} | ['team', 'head coach', 'team captain', 'venue', 'capacity', 'kitmaker', 'shirt sponsor', 'club chairman'] | [['ankaragücü', 'hakan kutlu', 'murat erdoğan', 'ankara 19 mayıs stadium', '19209', 'lotto', 'turkcell', 'cemal azmi aydın'], ['ankaraspor', 'aykut kocaman', 'hürriyet güçer', 'yenikent asaş stadium', '19626', 'nike', 'turkcell', 'ruhi kurnaz'], ['antalyaspor', 'mehmet özdilek', 'uğur kavuk', 'antalya atatürk stadium', '11137', 'nike', 'mardan', 'hasan y akıncıoğlu'], ['beşiktaş', 'mustafa denizli', 'matías delgado', 'bjk inönü stadium', '32086', 'umbro', 'cola turka', 'yıldırım demirören'], ['bursaspor', 'ertuğrul sağlam', 'ömer erdoğan', 'bursa atatürk stadium', '18587', 'kappa', 'turkcell', 'ibrahim yazıcı'], ['denizlispor', 'mesut bakkal', 'roman kratochvil', 'denizli atatürk stadium', '15427', 'lescon', 'turkcell', 'ali ipek'], ['eskişehirspor', 'rıza çalımbay', 'emre toraman', 'eskişehir atatürk stadium', '18880', 'nike', 'eti', 'halil ünal'], ['fenerbahçe', 'luis aragonés', 'alex', 'şükrü saracoğlu stadium', '53586', 'adidas', 'avea', 'aziz yıldırım'], ['galatasaray', 'bülent korkmaz', 'ayhan akman', 'ali sami yen stadium', '22800', 'adidas', 'avea', 'adnan polat'], ['gaziantepspor', 'josé couceiro', 'bekir irtegün', 'gaziantep kamil ocak stadium', '16981', 'lescon', 'turkcell', 'ibrahim halil kızıl'], ['gençlerbirliği', 'samet aybaba', 'abdel zaher el saka', 'ankara 19 mayıs stadium', '19209', 'lotto', 'turkcell', 'ilhan cavcav'], ['hacettepe', 'erdoğan arıca', 'orhan şam', 'ankara 19 mayıs stadium', '19209', 'lotto', 'turkcell', 'turgay kalemci'], ['istanbul bb', 'abdullah avcı', 'efe inanç', 'atatürk olympic stadium', '76092', 'lescon', 'kalpen', 'göksel gümüşdağ'], ['kayserispor', 'tolunay kafkas', 'mehmet topuz', 'kadir has stadium 1', '32864', 'adidas', 'turkcell', 'recep mamur'], ['kocaelispor', 'erhan altın', 'serdar topraktepe', 'ismet pasa stadium', '12710', 'umbro', 'erciyas', 'serhan gürkan'], ['konyaspor', 'ünal karaman', 'ömer gündostu', 'konya atatürk stadium', '21968', 'lotto', 'turkcell', 'mehmet ali kuntoğlu'], ['sivasspor', 'bülent uygun', 'mehmet yildiz', 'sivas 4 eylül stadium', '14998', 'adidas', 'turkcell', 'mecnun otyakmaz']] |
so you think you can dance ( u.s. season 4 ) | https://en.wikipedia.org/wiki/So_You_Think_You_Can_Dance_%28U.S._season_4%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15918328-9.html.csv | unique | kherington payne and mark kanemura were the only couple to dance in a country-western two-step style . | {'scope': 'all', 'row': '3', 'col': '2', 'col_other': '1', 'criterion': 'equal', 'value': 'country - western two - step', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'style', 'country - western two - step'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose style record fuzzily matches to country - western two - step .', 'tostr': 'filter_eq { all_rows ; style ; country - western two - step }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; style ; country - western two - step } }', 'tointer': 'select the rows whose style record fuzzily matches to country - western two - step . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'style', 'country - western two - step'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose style record fuzzily matches to country - western two - step .', 'tostr': 'filter_eq { all_rows ; style ; country - western two - step }'}, 'couple'], 'result': 'kherington payne mark kanemura', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; style ; country - western two - step } ; couple }'}, 'kherington payne mark kanemura'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; style ; country - western two - step } ; couple } ; kherington payne mark kanemura }', 'tointer': 'the couple record of this unqiue row is kherington payne mark kanemura .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; style ; country - western two - step } } ; eq { hop { filter_eq { all_rows ; style ; country - western two - step } ; couple } ; kherington payne mark kanemura } } = true', 'tointer': 'select the rows whose style record fuzzily matches to country - western two - step . there is only one such row in the table . the couple record of this unqiue row is kherington payne mark kanemura .'} | and { only { filter_eq { all_rows ; style ; country - western two - step } } ; eq { hop { filter_eq { all_rows ; style ; country - western two - step } ; couple } ; kherington payne mark kanemura } } = true | select the rows whose style record fuzzily matches to country - western two - step . there is only one such row in the table . the couple record of this unqiue row is kherington payne mark kanemura . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'style_7': 7, 'country - western two - step_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'couple_9': 9, 'kherington payne mark kanemura_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'style_7': 'style', 'country - western two - step_8': 'country - western two - step', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'couple_9': 'couple', 'kherington payne mark kanemura_10': 'kherington payne mark kanemura'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'style_7': [0], 'country - western two - step_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'couple_9': [2], 'kherington payne mark kanemura_10': [3]} | ['couple', 'style', 'music', 'choreographer ( s )', 'results'] | [['courtney galiano joshua allen', 'hip - hop', "skippin ' - mario", 'dave scott', 'safe'], ['courtney galiano joshua allen', 'rumba', 'hero - enrique iglesias', 'jean - marc généreux france mousseau', 'safe'], ['kherington payne mark kanemura', 'country - western two - step', 'kick back - ty england', 'ronnie debenedetta brandi tobais', 'payne eliminated kanemura in bottom 4'], ['kherington payne mark kanemura', 'jazz', 'canned heat - jamiroquai', 'tyce diorio', 'payne eliminated kanemura in bottom 4'], ['comfort fedoke stephen twitch boss', 'smooth waltz', 'open arms - journey', 'hunter johnson', 'fedoke in bottom 4'], ['comfort fedoke stephen twitch boss', 'hip - hop', 'forever - chris brown', 'dave scott', 'fedoke in bottom 4'], ['katee shean william wingfield', 'broadway', "sit down you 're rocking the boat - sam harris", 'tyce diorio', 'safe'], ['katee shean william wingfield', 'pas de deux', 'imagine - david archuleta', 'dwight rhoden desmond richardson', 'safe'], ['chelsie hightower gev manoukian', 'contemporary', 'these arms of mine - otis redding', 'sonya tayeh', 'manoukian eliminated'], ['chelsie hightower gev manoukian', 'jive', "the house is rockin ' - brian setzer", 'jean - marc généreux france mousseau assisting', 'manoukian eliminated']] |
list of californication episodes | https://en.wikipedia.org/wiki/List_of_Californication_episodes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-13336122-3.html.csv | majority | the majority of californication 's episodes were written by tom kapinos . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'tom kapinos', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'written by', 'tom kapinos'], 'result': True, 'ind': 0, 'tointer': 'for the written by records of all rows , most of them fuzzily match to tom kapinos .', 'tostr': 'most_eq { all_rows ; written by ; tom kapinos } = true'} | most_eq { all_rows ; written by ; tom kapinos } = true | for the written by records of all rows , most of them fuzzily match to tom kapinos . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'written by_3': 3, 'tom kapinos_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'written by_3': 'written by', 'tom kapinos_4': 'tom kapinos'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'written by_3': [0], 'tom kapinos_4': [0]} | ['no in series', 'no in season', 'title', 'directed by', 'written by', 'original air date'] | [['13', '1', 'slip of the tongue', 'david duchovny', 'tom kapinos', 'september 28 , 2008'], ['14', '2', 'the great ashby', 'david von ancken', 'tom kapinos', 'october 5 , 2008'], ['15', '3', 'no way to treat a lady', 'john dahl', 'gina fattore', 'october 12 , 2008'], ['16', '4', 'the raw & the cooked', 'david von ancken', 'tom kapinos', 'october 19 , 2008'], ['17', '5', 'vaginatown', 'ken whittingham', 'jay dyer', 'october 26 , 2008'], ['18', '6', 'coke dick & first kick', 'michael lehmann', 'gina fattore & gabriel roth', 'november 2 , 2008'], ['19', '7', 'in a lonely place', 'jake kasdan', 'tom kapinos', 'november 9 , 2008'], ['20', '8', 'going down and out in beverly hills', 'danny ducovny', 'daisy gardner', 'november 16 , 2008'], ['21', '9', 'la ronde', 'adam bernstein', 'gina fattore', 'november 23 , 2008'], ['22', '10', 'in utero', 'david von ancken', 'tom kapinos', 'november 30 , 2008'], ['23', '11', 'blues from laurel canyon', 'michael lehmann', 'gina fattore', 'december 7 , 2008']] |
sunshine state conference | https://en.wikipedia.org/wiki/Sunshine_State_Conference | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1183842-1.html.csv | count | there are 9 member institutions in the sunshine state conference . | {'scope': 'all', 'criterion': 'all', 'value': 'n/a', 'result': '9', 'col': '1', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_all', 'args': ['all_rows', 'institution'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose institution record is arbitrary .', 'tostr': 'filter_all { all_rows ; institution }'}], 'result': '9', 'ind': 1, 'tostr': 'count { filter_all { all_rows ; institution } }', 'tointer': 'select the rows whose institution record is arbitrary . the number of such rows is 9 .'}, '9'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_all { all_rows ; institution } } ; 9 } = true', 'tointer': 'select the rows whose institution record is arbitrary . the number of such rows is 9 .'} | eq { count { filter_all { all_rows ; institution } } ; 9 } = true | select the rows whose institution record is arbitrary . the number of such rows is 9 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_all_0': 0, 'all_rows_4': 4, 'institution_5': 5, '9_6': 6} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_all_0': 'filter_all', 'all_rows_4': 'all_rows', 'institution_5': 'institution', '9_6': '9'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_all_0': [1], 'all_rows_4': [0], 'institution_5': [0], '9_6': [2]} | ['institution', 'location', 'founded', 'type', 'enrollment', 'nickname', 'joined'] | [['barry university', 'miami shores , florida', '1940', 'private', '9300', 'buccaneers', '1988'], ['eckerd college', 'st petersburg , florida', '1958', 'private', '3584', 'tritons', '1975'], ['florida southern college', 'lakeland , florida', '1883', 'private', '3488', 'moccasins', '1975'], ['florida institute of technology', 'melbourne , florida', '1958', 'private', '7626', 'panthers', '1981'], ['lynn university', 'boca raton , florida', '1962', 'private', '4660', 'fighting knights', '1997'], ['nova southeastern university', 'davie , florida', '1964', 'private', '33135', 'sharks', '2002'], ['rollins college', 'winter park , florida', '1885', 'private', '4320', 'tars', '1975'], ['saint leo university', 'saint leo , florida', '1889', 'private', '15120', 'lions', '1975'], ['the university of tampa', 'tampa , florida', '1931', 'private', '10515', 'spartans', '1981']] |
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