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1972 - 73 philadelphia flyers season | https://en.wikipedia.org/wiki/1972%E2%80%9373_Philadelphia_Flyers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14294324-2.html.csv | aggregation | in the 1972-78 philadelphia flyers season , the average number of points was 5.3 . | {'scope': 'all', 'col': '6', 'type': 'average', 'result': '5.3', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'points'], 'result': '5.3', 'ind': 0, 'tostr': 'avg { all_rows ; points }'}, '5.3'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; points } ; 5.3 } = true', 'tointer': 'the average of the points record of all rows is 5.3 .'} | round_eq { avg { all_rows ; points } ; 5.3 } = true | the average of the points record of all rows is 5.3 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'points_4': 4, '5.3_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'points_4': 'points', '5.3_5': '5.3'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'points_4': [0], '5.3_5': [1]} | ['game', 'october', 'opponent', 'score', 'record', 'points'] | [['1', '7', 'st louis blues', '4 - 4', '0 - 0 - 1', '1'], ['2', '12', 'vancouver canucks', '7 - 3', '1 - 0 - 1', '3'], ['3', '14', 'detroit red wings', '0 - 5', '1 - 1 - 1', '3'], ['4', '15', 'california golden seals', '1 - 4', '1 - 2 - 1', '3'], ['5', '18', 'los angeles kings', '4 - 3', '2 - 2 - 1', '5'], ['6', '20', 'california golden seals', '3 - 3', '2 - 2 - 2', '6'], ['7', '25', 'new york rangers', '1 - 6', '2 - 3 - 2', '6'], ['8', '26', 'detroit red wings', '2 - 1', '3 - 3 - 2', '8'], ['9', '28', 'minnesota north stars', '1 - 2', '3 - 4 - 2', '8'], ['10', '29', 'toronto maple leafs', '5 - 2', '4 - 4 - 2', '10']] |
united states house of representatives elections , 1824 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1824 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2668264-8.html.csv | count | 4 incumbents were re - elected during the 1824 united states house of representatives elections . | {'scope': 'all', 'criterion': 'equal', 'value': 're - elected', 'result': '4', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'result', 're - elected'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose result record fuzzily matches to re - elected .', 'tostr': 'filter_eq { all_rows ; result ; re - elected }'}], 'result': '4', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; result ; re - elected } }', 'tointer': 'select the rows whose result record fuzzily matches to re - elected . the number of such rows is 4 .'}, '4'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; result ; re - elected } } ; 4 } = true', 'tointer': 'select the rows whose result record fuzzily matches to re - elected . the number of such rows is 4 .'} | eq { count { filter_eq { all_rows ; result ; re - elected } } ; 4 } = true | select the rows whose result record fuzzily matches to re - elected . 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, 'result_5': 5, 're - elected_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', 'result_5': 'result', 're - elected_6': 're - elected', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'result_5': [0], 're - elected_6': [0], '4_7': [2]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['kentucky 1', 'david trimble', 'adams - clay republican', '1816', 're - elected', 'david trimble ( a )'], ['kentucky 3', 'henry clay', 'adams - clay republican', '1810 1822', 're - elected', 'henry clay ( a ) 100 %'], ['kentucky 4', 'robert p letcher', 'adams - clay republican', '1822', 're - elected', 'robert p letcher ( a ) 60.1 % john speed smith 39.9 %'], ['kentucky 6', 'david white', 'adams - clay republican', '1822', 'retired jacksonian gain', 'joseph lecompte ( j ) john logan'], ['kentucky 7', 'thomas p moore', 'jacksonian republican', '1822', 're - elected', 'thomas p moore ( j ) samuel woodson']] |
2007 - 08 fis ski jumping world cup | https://en.wikipedia.org/wiki/2007%E2%80%9308_FIS_Ski_Jumping_World_Cup | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14407512-6.html.csv | aggregation | the players in the 2007 - 08 fis ski jumping world cup scored an average total of 252.0 points . | {'scope': 'all', 'col': '6', 'type': 'average', 'result': '252.0', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'points'], 'result': '252.0', 'ind': 0, 'tostr': 'avg { all_rows ; points }'}, '252.0'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; points } ; 252.0 } = true', 'tointer': 'the average of the points record of all rows is 252.0 .'} | round_eq { avg { all_rows ; points } ; 252.0 } = true | the average of the points record of all rows is 252.0 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'points_4': 4, '252.0_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'points_4': 'points', '252.0_5': '252.0'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'points_4': [0], '252.0_5': [1]} | ['rank', 'name', 'nationality', '1st ( m )', '2nd ( m )', 'points', 'overall wc points ( rank )'] | [['1', 'thomas morgenstern', 'aut', '132.5', '133.0', '260.4', '600 ( 1 )'], ['2', 'andreas kofler', 'aut', '134.5', '128.5', '254.4', '248 ( 6 )'], ['3', 'tom hilde', 'nor', '133.5', '129.5', '252.9', '256 ( 4 )'], ['4', 'gregor schlierenzauer', 'aut', '126.5', '134.5', '249.8', '349 ( 2 )'], ['5', 'wolfgang loitzl', 'aut', '130.5', '126.5', '242.6', '250 ( 5 )']] |
gardline group | https://en.wikipedia.org/wiki/Gardline_group | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-28132970-5.html.csv | superlative | of the gardline group 's windfarm support vessels , the one with the shortest overall length is marianarray . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '6', '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', 'length'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; length }'}, 'vessel'], 'result': 'marianarray', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; length } ; vessel }'}, 'marianarray'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmin { all_rows ; length } ; vessel } ; marianarray } = true', 'tointer': 'select the row whose length record of all rows is minimum . the vessel record of this row is marianarray .'} | eq { hop { argmin { all_rows ; length } ; vessel } ; marianarray } = true | select the row whose length record of all rows is minimum . the vessel record of this row is marianarray . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'length_5': 5, 'vessel_6': 6, 'marianarray_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'length_5': 'length', 'vessel_6': 'vessel', 'marianarray_7': 'marianarray'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'length_5': [0], 'vessel_6': [1], 'marianarray_7': [2]} | ['vessel', 'built', 'max speed', 'length', 'breadth', 'flag', 'propulsion'] | [['gallion', '2010', '30 knots', '20 m', '6.5 m', 'united kingdom', 'prop'], ['gardian 1', '2010', '30 knots', '20 m', '6.5 m', 'united kingdom', 'prop'], ['gardian 2', '2010', '30 knots', '20 m', '6.5 m', 'united kingdom', 'prop'], ['gardian 7', '2010', '30 knots', '20 m', '6.5 m', 'united kingdom', 'prop'], ['gardian 9', '2010', '30 knots', '20 m', '6.5 m', 'united kingdom', 'prop'], ['marianarray', '2011', '26 knots', '17 m', '6 m', 'united kingdom', 'jet'], ['smeaton array', '2011', '30 knots', '20 m', '6 m', 'united kingdom', 'controllable pitch propeller']] |
zina garrison | https://en.wikipedia.org/wiki/Zina_Garrison | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1028356-3.html.csv | comparative | zina garrison 's opponents were anne hobbs and andrew castle one year before her opponents were gretchen magers and kelly jones . | {'row_1': '1', 'row_2': '2', 'col': '2', 'col_other': '6', 'relation': 'diff', 'record_mentioned': 'no', 'diff_result': {'diff_value': '1 year', 'bigger': 'row2'}} | {'func': 'eq', 'args': [{'func': 'diff', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponents', 'anne hobbs andrew castle'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose opponents record fuzzily matches to anne hobbs andrew castle .', 'tostr': 'filter_eq { all_rows ; opponents ; anne hobbs andrew castle }'}, 'year'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; opponents ; anne hobbs andrew castle } ; year }', 'tointer': 'select the rows whose opponents record fuzzily matches to anne hobbs andrew castle . take the year record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponents', 'gretchen magers kelly jones'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose opponents record fuzzily matches to gretchen magers kelly jones .', 'tostr': 'filter_eq { all_rows ; opponents ; gretchen magers kelly jones }'}, 'year'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; opponents ; gretchen magers kelly jones } ; year }', 'tointer': 'select the rows whose opponents record fuzzily matches to gretchen magers kelly jones . take the year record of this row .'}], 'result': '-1 year', 'ind': 4, 'tostr': 'diff { hop { filter_eq { all_rows ; opponents ; anne hobbs andrew castle } ; year } ; hop { filter_eq { all_rows ; opponents ; gretchen magers kelly jones } ; year } }'}, '-1 year'], 'result': True, 'ind': 5, 'tostr': 'eq { diff { hop { filter_eq { all_rows ; opponents ; anne hobbs andrew castle } ; year } ; hop { filter_eq { all_rows ; opponents ; gretchen magers kelly jones } ; year } } ; -1 year } = true', 'tointer': 'select the rows whose opponents record fuzzily matches to anne hobbs andrew castle . take the year record of this row . select the rows whose opponents record fuzzily matches to gretchen magers kelly jones . take the year record of this row . the second record is 1 year larger than the first record .'} | eq { diff { hop { filter_eq { all_rows ; opponents ; anne hobbs andrew castle } ; year } ; hop { filter_eq { all_rows ; opponents ; gretchen magers kelly jones } ; year } } ; -1 year } = true | select the rows whose opponents record fuzzily matches to anne hobbs andrew castle . take the year record of this row . select the rows whose opponents record fuzzily matches to gretchen magers kelly jones . take the year record of this row . the second record is 1 year larger than the first record . | 6 | 6 | {'str_eq_5': 5, 'result_6': 6, 'diff_4': 4, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_7': 7, 'opponents_8': 8, 'anne hobbs andrew castle_9': 9, 'year_10': 10, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_11': 11, 'opponents_12': 12, 'gretchen magers kelly jones_13': 13, 'year_14': 14, '-1 year_15': 15} | {'str_eq_5': 'str_eq', 'result_6': 'true', 'diff_4': 'diff', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_7': 'all_rows', 'opponents_8': 'opponents', 'anne hobbs andrew castle_9': 'anne hobbs andrew castle', 'year_10': 'year', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_11': 'all_rows', 'opponents_12': 'opponents', 'gretchen magers kelly jones_13': 'gretchen magers kelly jones', 'year_14': 'year', '-1 year_15': '-1 year'} | {'str_eq_5': [6], 'result_6': [], 'diff_4': [5], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_7': [0], 'opponents_8': [0], 'anne hobbs andrew castle_9': [0], 'year_10': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_11': [1], 'opponents_12': [1], 'gretchen magers kelly jones_13': [1], 'year_14': [3], '-1 year_15': [5]} | ['outcome', 'year', 'championship', 'surface', 'partner', 'opponents', 'score'] | [['winner', '1987', 'australian open', 'grass', 'sherwood stewart', 'anne hobbs andrew castle', '3 - 6 , 7 - 6 ( 5 ) , 6 - 3'], ['winner', '1988', 'wimbledon', 'grass', 'sherwood stewart', 'gretchen magers kelly jones', '6 - 1 , 7 - 6 ( 3 )'], ['runner - up', '1989', 'australian open', 'hard', 'sherwood stewart', 'jana novotná jim pugh', '6 - 3 , 6 - 4'], ['runner - up', '1990', 'australian open', 'hard', 'jim pugh', 'natasha zvereva andrew castle', '4 - 6 , 6 - 2 , 6 - 3'], ['winner', '1990', 'wimbledon ( 2 )', 'grass', 'rick leach', 'elizabeth smylie john fitzgerald', '7 - 5 , 6 - 2']] |
1980 cleveland browns season | https://en.wikipedia.org/wiki/1980_Cleveland_Browns_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10651215-2.html.csv | majority | the cleveland browns won most of their games in the 1980 nfl 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 7 , 1980', 'new england patriots', 'l 34 - 17', '49222'], ['2', 'september 15 , 1980', 'houston oilers', 'l 16 - 7', '80243'], ['3', 'september 21 , 1980', 'kansas city chiefs', 'w 20 - 13', '63614'], ['4', 'september 28 , 1980', 'tampa bay buccaneers', 'w 34 - 27', '65540'], ['5', 'october 5 , 1980', 'denver broncos', 'l 19 - 16', '81065'], ['6', 'october 12 , 1980', 'seattle seahawks', 'w 27 - 3', '61366'], ['7', 'october 19 , 1980', 'green bay packers', 'w 26 - 21', '75548'], ['8', 'october 26 , 1980', 'pittsburgh steelers', 'w 27 - 26', '79095'], ['9', 'november 3 , 1980', 'chicago bears', 'w 27 - 21', '84225'], ['10', 'november 9 , 1980', 'baltimore colts', 'w 28 - 27', '45369'], ['11', 'november 16 , 1980', 'pittsburgh steelers', 'l 16 - 13', '54563'], ['12', 'november 23 , 1980', 'cincinnati bengals', 'w 31 - 7', '79253'], ['13', 'november 30 , 1980', 'houston oilers', 'w 17 - 14', '51514'], ['14', 'december 7 , 1980', 'new york jets', 'w 17 - 14', '78454'], ['15', 'december 14 , 1980', 'minnesota vikings', 'l 28 - 23', '42202'], ['16', 'december 21 , 1980', 'cincinnati bengals', 'w 27 - 24', '50058']] |
1939 vfl season | https://en.wikipedia.org/wiki/1939_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10806852-13.html.csv | superlative | the game played at princes park in the 1939 vfl season drew the highest crowd attendance . | {'scope': 'all', 'col_superlative': '6', 'row_superlative': '3', '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': 'princes park', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; crowd } ; venue }'}, 'princes park'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; crowd } ; venue } ; princes park } = true', 'tointer': 'select the row whose crowd record of all rows is maximum . the venue record of this row is princes park .'} | eq { hop { argmax { all_rows ; crowd } ; venue } ; princes park } = true | select the row whose crowd record of all rows is maximum . the venue record of this row is princes park . | 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, 'princes park_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', 'princes park_7': 'princes park'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'crowd_5': [0], 'venue_6': [1], 'princes park_7': [2]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['footscray', '7.7 ( 49 )', 'richmond', '13.25 ( 103 )', 'western oval', '15000', '15 july 1939'], ['collingwood', '19.11 ( 125 )', 'south melbourne', '8.13 ( 61 )', 'victoria park', '10500', '15 july 1939'], ['carlton', '14.14 ( 98 )', 'geelong', '12.5 ( 77 )', 'princes park', '19000', '15 july 1939'], ['north melbourne', '18.11 ( 119 )', 'hawthorn', '11.16 ( 82 )', 'arden street oval', '8000', '15 july 1939'], ['st kilda', '16.19 ( 115 )', 'fitzroy', '13.6 ( 84 )', 'junction oval', '16500', '15 july 1939'], ['melbourne', '7.18 ( 60 )', 'essendon', '10.17 ( 77 )', 'mcg', '16247', '15 july 1939']] |
2008 - 09 ue lleida season | https://en.wikipedia.org/wiki/2008%E2%80%9309_UE_Lleida_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-19018191-5.html.csv | comparative | david giménez scored more league goals than casado in the 2008 - 09 ue lleida season . | {'row_1': '14', 'row_2': '15', 'col': '8', 'col_other': '1', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', 'david giménez'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose player record fuzzily matches to david giménez .', 'tostr': 'filter_eq { all_rows ; player ; david giménez }'}, 'total g'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; player ; david giménez } ; total g }', 'tointer': 'select the rows whose player record fuzzily matches to david giménez . take the total g record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', 'casado'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose player record fuzzily matches to casado .', 'tostr': 'filter_eq { all_rows ; player ; casado }'}, 'total g'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; player ; casado } ; total g }', 'tointer': 'select the rows whose player record fuzzily matches to casado . take the total g record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; player ; david giménez } ; total g } ; hop { filter_eq { all_rows ; player ; casado } ; total g } } = true', 'tointer': 'select the rows whose player record fuzzily matches to david giménez . take the total g record of this row . select the rows whose player record fuzzily matches to casado . take the total g record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; player ; david giménez } ; total g } ; hop { filter_eq { all_rows ; player ; casado } ; total g } } = true | select the rows whose player record fuzzily matches to david giménez . take the total g record of this row . select the rows whose player record fuzzily matches to casado . take the total g record of this row . the first record is greater than the second record . | 5 | 5 | {'greater_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'player_7': 7, 'david giménez_8': 8, 'total g_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'player_11': 11, 'casado_12': 12, 'total g_13': 13} | {'greater_4': 'greater', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'player_7': 'player', 'david giménez_8': 'david giménez', 'total g_9': 'total g', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'player_11': 'player', 'casado_12': 'casado', 'total g_13': 'total g'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'player_7': [0], 'david giménez_8': [0], 'total g_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'player_11': [1], 'casado_12': [1], 'total g_13': [3]} | ['player', 'nat', 'pos', 'l apps', 'l g', 'c apps', 'total apps', 'total g'] | [['gabernet', 'esp', 'mf', '15', '1', '0', '15', '1'], ['galán', 'esp', 'df', '32', '2', '0', '32', '2'], ['jerson', 'esp', 'df', '34', '1', '0', '34', '1'], ['urrea', 'esp', 'mf', '16', '0', '0', '16', '0'], ['dani marín', 'esp', 'df', '30', '1', '0', '30', '1'], ['campabadal', 'esp', 'mf', '32', '1', '0', '32', '1'], ['parra', 'esp', 'fw', '37', '4', '0', '37', '4'], ['figuerola', 'esp', 'mf', '25', '0', '0', '25', '0'], ['mikel álvaro', 'esp', 'mf', '36', '13', '0', '36', '13'], ['ermengol', 'esp', 'fw', '24', '0', '0', '24', '0'], ['miki', 'esp', 'mf', '36', '1', '0', '36', '1'], ['benet', 'esp', 'mf', '4', '0', '0', '4', '0'], ['moya', 'esp', 'df', '31', '5', '0', '31', '5'], ['david giménez', 'esp', 'mf', '36', '6', '0', '36', '6'], ['casado', 'esp', 'df', '27', '1', '0', '27', '1'], ['jaume', 'esp', 'mf', '35', '0', '0', '35', '0'], ['sellarés', 'esp', 'fw', '37', '8', '0', '37', '8']] |
1992 - 93 ue lleida season | https://en.wikipedia.org/wiki/1992%E2%80%9393_UE_Lleida_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12356410-6.html.csv | superlative | in the 1992 - 93 ue lleida season , their first game with palamós was served by daudén ibáñez referee . | {'scope': 'subset', 'col_superlative': '2', 'row_superlative': '3', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '3,6', 'subset': {'col': '3', 'criterion': 'equal', 'value': 'palamós'}} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmin', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponents', 'palamós'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; opponents ; palamós }', 'tointer': 'select the rows whose opponents record fuzzily matches to palamós .'}, 'kick off'], 'result': None, 'ind': 1, 'tostr': 'argmin { filter_eq { all_rows ; opponents ; palamós } ; kick off }'}, 'referee'], 'result': 'daudén ibáñez', 'ind': 2, 'tostr': 'hop { argmin { filter_eq { all_rows ; opponents ; palamós } ; kick off } ; referee }'}, 'daudén ibáñez'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { argmin { filter_eq { all_rows ; opponents ; palamós } ; kick off } ; referee } ; daudén ibáñez } = true', 'tointer': 'select the rows whose opponents record fuzzily matches to palamós . select the row whose kick off record of these rows is minimum . the referee record of this row is daudén ibáñez .'} | eq { hop { argmin { filter_eq { all_rows ; opponents ; palamós } ; kick off } ; referee } ; daudén ibáñez } = true | select the rows whose opponents record fuzzily matches to palamós . select the row whose kick off record of these rows is minimum . the referee record of this row is daudén ibáñez . | 4 | 4 | {'str_eq_3': 3, 'result_4': 4, 'str_hop_2': 2, 'argmin_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'opponents_6': 6, 'palamós_7': 7, 'kick off_8': 8, 'referee_9': 9, 'daudén ibáñez_10': 10} | {'str_eq_3': 'str_eq', 'result_4': 'true', 'str_hop_2': 'str_hop', 'argmin_1': 'argmin', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'opponents_6': 'opponents', 'palamós_7': 'palamós', 'kick off_8': 'kick off', 'referee_9': 'referee', 'daudén ibáñez_10': 'daudén ibáñez'} | {'str_eq_3': [4], 'result_4': [], 'str_hop_2': [3], 'argmin_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'opponents_6': [0], 'palamós_7': [0], 'kick off_8': [1], 'referee_9': [2], 'daudén ibáñez_10': [3]} | ['round', 'kick off', 'opponents', 'h / a', 'result', 'referee'] | [['r3', '1992 - 10 - 01 21:15', 'hércules', 'a', '1 - 1', 'panadero martínez'], ['r3', '1992 - 11 - 05 20:30', 'hércules', 'h', '1 - 0', 'garcía prieto'], ['r5', '1993 - 01 - 13 20:30', 'palamós', 'h', '0 - 0', 'daudén ibáñez'], ['r5', '1993 - 01 - 20 20:30', 'palamós', 'a', '1 - 1', 'velázquez carrillo'], ['l16', '1993 - 02 - 03 20:30', 'real sociedad', 'h', '0 - 0', 'garcía aranda'], ['l16', '1993 - 02 - 17 20:30', 'real sociedad', 'a', '0 - 3', 'lópez nieto']] |
2008 winnipeg blue bombers season | https://en.wikipedia.org/wiki/2008_Winnipeg_Blue_Bombers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16912111-3.html.csv | unique | the game on september 19 was the only game to have less than 20000 attendance in the bomber 's 2008 season . | {'scope': 'all', 'row': '13', 'col': '6', 'col_other': '2', 'criterion': 'less_than', 'value': '20000', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'attendance', '20000'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose attendance record is less than 20000 .', 'tostr': 'filter_less { all_rows ; attendance ; 20000 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_less { all_rows ; attendance ; 20000 } }', 'tointer': 'select the rows whose attendance record is less than 20000 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'attendance', '20000'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose attendance record is less than 20000 .', 'tostr': 'filter_less { all_rows ; attendance ; 20000 }'}, 'date'], 'result': 'sept 19', 'ind': 2, 'tostr': 'hop { filter_less { all_rows ; attendance ; 20000 } ; date }'}, 'sept 19'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_less { all_rows ; attendance ; 20000 } ; date } ; sept 19 }', 'tointer': 'the date record of this unqiue row is sept 19 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_less { all_rows ; attendance ; 20000 } } ; eq { hop { filter_less { all_rows ; attendance ; 20000 } ; date } ; sept 19 } } = true', 'tointer': 'select the rows whose attendance record is less than 20000 . there is only one such row in the table . the date record of this unqiue row is sept 19 .'} | and { only { filter_less { all_rows ; attendance ; 20000 } } ; eq { hop { filter_less { all_rows ; attendance ; 20000 } ; date } ; sept 19 } } = true | select the rows whose attendance record is less than 20000 . there is only one such row in the table . the date record of this unqiue row is sept 19 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_less_0': 0, 'all_rows_6': 6, 'attendance_7': 7, '20000_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'date_9': 9, 'sept 19_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_less_0': 'filter_less', 'all_rows_6': 'all_rows', 'attendance_7': 'attendance', '20000_8': '20000', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'date_9': 'date', 'sept 19_10': 'sept 19'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_less_0': [1, 2], 'all_rows_6': [0], 'attendance_7': [0], '20000_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'date_9': [2], 'sept 19_10': [3]} | ['week', 'date', 'opponent', 'score', 'result', 'attendance', 'record'] | [['1', 'june 27', 'toronto argonauts', '23 - 16', 'loss', '26155', '0 - 1'], ['2', 'july 4', 'montreal alouettes', '38 - 24', 'loss', '20202', '0 - 2'], ['3', 'july 11', 'bc lions', '42 - 24', 'loss', '26735', '0 - 3'], ['4', 'july 18', 'bc lions', '27 - 18', 'loss', '37174', '0 - 4'], ['5', 'july 24', 'calgary stampeders', '32 - 28', 'win', '26882', '1 - 4'], ['6', 'aug 1', 'toronto argonauts', '19 - 11', 'loss', '28523', '1 - 5'], ['7', 'aug 8', 'montreal alouettes', '39 - 11', 'loss', '27674', '1 - 6'], ['8', 'aug 14', 'hamilton tiger - cats', '37 - 24', 'win', '25484', '2 - 6'], ['9', '-', '-', '-', '-', '-', '2 - 6'], ['10', 'aug 31', 'saskatchewan roughriders', '19 - 6', 'loss', '30985', '2 - 7'], ['11', 'sept 7', 'saskatchewan roughriders', '34 - 31', 'loss', '29770', '2 - 8'], ['12', 'sept 12', 'toronto argonauts', '39 - 9', 'win', '28453', '3 - 8'], ['13', 'sept 19', 'hamilton tiger - cats', '25 - 23', 'win', '19102', '4 - 8'], ['14', 'sept 26', 'edmonton eskimos', '30 - 23', 'win', '29794', '5 - 8'], ['15', 'oct 4', 'edmonton eskimos', '36 - 22', 'loss', '40453', '5 - 9'], ['16', 'oct 10', 'toronto argonauts', '25 - 16', 'win', '27368', '6 - 9'], ['17', 'oct 18', 'calgary stampeders', '37 - 16', 'loss', '30110', '6 - 10'], ['18', 'oct 26', 'montreal alouettes', '24 - 23', 'win', '20202', '7 - 10'], ['19', 'nov 1', 'hamilton tiger - cats', '44 - 30', 'win', '24595', '8 - 10']] |
rugby union at the 2002 asian games | https://en.wikipedia.org/wiki/Rugby_union_at_the_2002_Asian_Games | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14335046-1.html.csv | count | of the nations that did not win a gold medal in rugby union at the 2002 asian games , two of them won a silver medal . | {'scope': 'subset', 'criterion': 'equal', 'value': '1', 'result': '2', 'col': '4', 'subset': {'col': '3', 'criterion': 'equal', 'value': '0'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'gold', '0'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; gold ; 0 }', 'tointer': 'select the rows whose gold record is equal to 0 .'}, 'silver', '1'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose gold record is equal to 0 . among these rows , select the rows whose silver record is equal to 1 .', 'tostr': 'filter_eq { filter_eq { all_rows ; gold ; 0 } ; silver ; 1 }'}], 'result': '2', 'ind': 2, 'tostr': 'count { filter_eq { filter_eq { all_rows ; gold ; 0 } ; silver ; 1 } }', 'tointer': 'select the rows whose gold record is equal to 0 . among these rows , select the rows whose silver record is equal to 1 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_eq { filter_eq { all_rows ; gold ; 0 } ; silver ; 1 } } ; 2 } = true', 'tointer': 'select the rows whose gold record is equal to 0 . among these rows , select the rows whose silver record is equal to 1 . the number of such rows is 2 .'} | eq { count { filter_eq { filter_eq { all_rows ; gold ; 0 } ; silver ; 1 } } ; 2 } = true | select the rows whose gold record is equal to 0 . among these rows , select the rows whose silver record is equal to 1 . the number of such rows is 2 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_eq_1': 1, 'filter_eq_0': 0, 'all_rows_5': 5, 'gold_6': 6, '0_7': 7, 'silver_8': 8, '1_9': 9, '2_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_eq_1': 'filter_eq', 'filter_eq_0': 'filter_eq', 'all_rows_5': 'all_rows', 'gold_6': 'gold', '0_7': '0', 'silver_8': 'silver', '1_9': '1', '2_10': '2'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_eq_1': [2], 'filter_eq_0': [1], 'all_rows_5': [0], 'gold_6': [0], '0_7': [0], 'silver_8': [1], '1_9': [1], '2_10': [3]} | ['rank', 'nation', 'gold', 'silver', 'bronze', 'total'] | [['1', 'south korea ( kor )', '2', '0', '0', '2'], ['2', 'chinese taipei ( tpe )', '0', '1', '1', '2'], ['3', 'japan ( jpn )', '0', '1', '0', '1'], ['4', 'thailand ( tha )', '0', '0', '1', '1'], ['total', 'total', '2', '2', '2', '6']] |
gold coast titans | https://en.wikipedia.org/wiki/Gold_Coast_Titans | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1613020-1.html.csv | count | greg bird and nate myles were the captains of the gold coast titans for a total of two seasons . | {'scope': 'all', 'criterion': 'equal', 'value': 'greg bird nate myles', 'result': '2', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'captain ( s )', 'greg bird nate myles'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose captain ( s ) record fuzzily matches to greg bird nate myles .', 'tostr': 'filter_eq { all_rows ; captain ( s ) ; greg bird nate myles }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; captain ( s ) ; greg bird nate myles } }', 'tointer': 'select the rows whose captain ( s ) record fuzzily matches to greg bird nate myles . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; captain ( s ) ; greg bird nate myles } } ; 2 } = true', 'tointer': 'select the rows whose captain ( s ) record fuzzily matches to greg bird nate myles . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; captain ( s ) ; greg bird nate myles } } ; 2 } = true | select the rows whose captain ( s ) record fuzzily matches to greg bird nate myles . 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, 'captain (s)_5': 5, 'greg bird nate myles_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', 'captain (s)_5': 'captain ( s )', 'greg bird nate myles_6': 'greg bird nate myles', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'captain (s)_5': [0], 'greg bird nate myles_6': [0], '2_7': [2]} | ['competition', 'ladder position', 'coach', 'captain ( s )', 'details'] | [['2007 nrl season', '12 / 16', 'john cartwright', 'luke bailey scott prince', '2007 gold coast titans season'], ['2008 nrl season', '13 / 16', 'john cartwright', 'luke bailey scott prince', '2008 gold coast titans season'], ['2009 nrl season', '3 / 16', 'john cartwright', 'luke bailey scott prince', '2009 gold coast titans season'], ['2010 nrl season', '4 / 16', 'john cartwright', 'scott prince', '2010 gold coast titans season'], ['2011 nrl season', '16 / 16', 'john cartwright', 'scott prince', '2011 gold coast titans season'], ['2012 nrl season', '11 / 16', 'john cartwright', 'scott prince', '2012 gold coast titans season'], ['2013 nrl season', '9 / 16', 'john cartwright', 'greg bird nate myles', '2013 gold coast titans season'], ['2014 nrl season', '16', 'john cartwright', 'greg bird nate myles', '2014 gold coast titans season']] |
equatorial bulge | https://en.wikipedia.org/wiki/Equatorial_bulge | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-143023-1.html.csv | ordinal | earth has the highest equatorial diameter among planets with equatorial bulge less than 100 km . | {'scope': 'subset', 'row': '1', 'col': '2', 'order': '1', 'col_other': '1', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'subset': {'col': '4', 'criterion': 'less_than', 'value': '100'}} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'equatorial bulge', '100'], 'result': None, 'ind': 0, 'tostr': 'filter_less { all_rows ; equatorial bulge ; 100 }', 'tointer': 'select the rows whose equatorial bulge record is less than 100 .'}, 'equatorial diameter', '1'], 'result': None, 'ind': 1, 'tostr': 'nth_argmax { filter_less { all_rows ; equatorial bulge ; 100 } ; equatorial diameter ; 1 }'}, 'body'], 'result': 'earth', 'ind': 2, 'tostr': 'hop { nth_argmax { filter_less { all_rows ; equatorial bulge ; 100 } ; equatorial diameter ; 1 } ; body }'}, 'earth'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { nth_argmax { filter_less { all_rows ; equatorial bulge ; 100 } ; equatorial diameter ; 1 } ; body } ; earth } = true', 'tointer': 'select the rows whose equatorial bulge record is less than 100 . select the row whose equatorial diameter record of these rows is 1st maximum . the body record of this row is earth .'} | eq { hop { nth_argmax { filter_less { all_rows ; equatorial bulge ; 100 } ; equatorial diameter ; 1 } ; body } ; earth } = true | select the rows whose equatorial bulge record is less than 100 . select the row whose equatorial diameter record of these rows is 1st maximum . the body record of this row is earth . | 4 | 4 | {'str_eq_3': 3, 'result_4': 4, 'str_hop_2': 2, 'nth_argmax_1': 1, 'filter_less_0': 0, 'all_rows_5': 5, 'equatorial bulge_6': 6, '100_7': 7, 'equatorial diameter_8': 8, '1_9': 9, 'body_10': 10, 'earth_11': 11} | {'str_eq_3': 'str_eq', 'result_4': 'true', 'str_hop_2': 'str_hop', 'nth_argmax_1': 'nth_argmax', 'filter_less_0': 'filter_less', 'all_rows_5': 'all_rows', 'equatorial bulge_6': 'equatorial bulge', '100_7': '100', 'equatorial diameter_8': 'equatorial diameter', '1_9': '1', 'body_10': 'body', 'earth_11': 'earth'} | {'str_eq_3': [4], 'result_4': [], 'str_hop_2': [3], 'nth_argmax_1': [2], 'filter_less_0': [1], 'all_rows_5': [0], 'equatorial bulge_6': [0], '100_7': [0], 'equatorial diameter_8': [1], '1_9': [1], 'body_10': [2], 'earth_11': [3]} | ['body', 'equatorial diameter', 'polar diameter', 'equatorial bulge', 'flattening ratio'] | [['earth', '12756.28 km', '12713.56 km', '42.72 km', '1:298.2575'], ['mars', '6805 km', '6754.8 km', '50.2 km', '1:135.56'], ['ceres', '975 km', '909 km', '66 km', '1:14.77'], ['jupiter', '143884 km', '133709 km', '10175 km', '1:14.14'], ['saturn', '120536 km', '108728 km', '11808 km', '1:10.21'], ['uranus', '51118 km', '49946 km', '1172 km', '1:43.62'], ['neptune', '49528 km', '48682 km', '846 km', '1:58.54']] |
1986 - 87 segunda división | https://en.wikipedia.org/wiki/1986%E2%80%9387_Segunda_Divisi%C3%B3n | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12109851-2.html.csv | majority | all clubs in the 1986 - 87 segunda división played 34 games . | {'scope': 'all', 'col': '3', 'most_or_all': 'all', 'criterion': 'equal', 'value': '34', 'subset': None} | {'func': 'all_eq', 'args': ['all_rows', 'played', '34'], 'result': True, 'ind': 0, 'tointer': 'for the played records of all rows , all of them are equal to 34 .', 'tostr': 'all_eq { all_rows ; played ; 34 } = true'} | all_eq { all_rows ; played ; 34 } = true | for the played records of all rows , all of them are equal to 34 . | 1 | 1 | {'all_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'played_3': 3, '34_4': 4} | {'all_eq_0': 'all_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'played_3': 'played', '34_4': '34'} | {'all_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'played_3': [0], '34_4': [0]} | ['position', 'club', 'played', 'points', 'wins', 'draws', 'losses', 'goals for', 'goals against', 'goal difference'] | [['1', 'valencia cf', '34', '46 + 12', '19', '8', '7', '53', '26', '+ 27'], ['2', 'deportivo de la coruña', '34', '43 + 9', '16', '11', '7', '46', '33', '+ 13'], ['3', 'cd logroñés', '34', '41 + 7', '16', '9', '9', '46', '33', '+ 13'], ['4', 'celta de vigo', '34', '40 + 6', '17', '6', '11', '56', '35', '+ 21'], ['5', 'recreativo de huelva', '34', '39 + 5', '18', '3', '13', '53', '44', '+ 9'], ['6', 'sestao', '34', '38 + 4', '13', '12', '9', '38', '23', '+ 15'], ['7', 'elche cf', '34', '36 + 2', '12', '12', '10', '31', '28', '+ 3'], ['8', 'rayo vallecano', '34', '35 + 1', '10', '15', '9', '28', '28', '0'], ['9', 'bilbao athletic', '34', '35 + 1', '12', '11', '11', '51', '54', '- 3'], ['10', 'cd castellón', '34', '34', '13', '8', '13', '38', '42', '- 4'], ['11', 'hércules cf', '34', '32 - 2', '12', '8', '14', '38', '43', '- 5'], ['12', 'cd málaga', '34', '32 - 2', '10', '12', '12', '43', '39', '+ 4'], ['13', 'barcelona atlètic', '34', '32 - 2', '11', '10', '13', '42', '46', '- 4'], ['14', 'real oviedo', '34', '30 - 4', '9', '12', '13', '33', '46', '- 13'], ['15', 'ue figueres', '34', '29 - 5', '9', '11', '14', '39', '40', '- 1'], ['16', 'cartagena fc', '34', '27 - 7', '7', '13', '14', '34', '51', '- 17'], ['17', 'castilla cf', '34', '24 - 10', '7', '10', '17', '30', '51', '- 21'], ['18', 'jerez deportivo', '34', '19 - 15', '4', '11', '19', '21', '58', '- 37']] |
2007 - 08 anaheim ducks season | https://en.wikipedia.org/wiki/2007%E2%80%9308_Anaheim_Ducks_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11801795-8.html.csv | ordinal | during the 2007 - 08 season , the anaheim ducks ' game on march 19th recorded the highest attendance . | {'row': '8', 'col': '5', 'order': '1', 'col_other': '1', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'attendance', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; attendance ; 1 }'}, 'date'], 'result': 'march 19', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; attendance ; 1 } ; date }'}, 'march 19'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; attendance ; 1 } ; date } ; march 19 } = true', 'tointer': 'select the row whose attendance record of all rows is 1st maximum . the date record of this row is march 19 .'} | eq { hop { nth_argmax { all_rows ; attendance ; 1 } ; date } ; march 19 } = true | select the row whose attendance record of all rows is 1st maximum . the date record of this row is march 19 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'attendance_5': 5, '1_6': 6, 'date_7': 7, 'march 19_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'attendance_5': 'attendance', '1_6': '1', 'date_7': 'date', 'march 19_8': 'march 19'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'attendance_5': [0], '1_6': [0], 'date_7': [1], 'march 19_8': [2]} | ['date', 'opponent', 'score', 'loss', 'attendance', 'record', 'arena', 'points'] | [['march 3', 'senators', '3 - 1', 'gerber ( 24 - 12 - 2 )', '17174', '38 - 23 - 7', 'honda center', '83'], ['march 5', 'blackhawks', '3 - 0', 'giguere ( 31 - 17 - 5 )', '16666', '38 - 24 - 7', 'united center', '83'], ['march 6', 'avalanche', '1 - 0', 'hiller ( 5 - 5 - 1 )', '18007', '38 - 25 - 7', 'pepsi center', '83'], ['march 9', 'canadiens', '3 - 1', 'price ( 16 - 11 - 3 )', '17174', '39 - 25 - 7', 'honda center', '85'], ['march 11', 'coyotes', '3 - 2', 'giguere ( 32 - 17 - 6 )', '14683', '39 - 25 - 8', 'jobingcom arena', '86'], ['march 12', 'canucks', '4 - 1', 'luongo ( 31 - 21 - 9 )', '17174', '40 - 25 - 8', 'honda center', '88'], ['march 15', 'blues', '5 - 2', 'legace ( 24 - 23 - 8 )', '17174', '41 - 25 - 8', 'honda center', '90'], ['march 19', 'stars', '2 - 1', 'turco ( 30 - 19 - 4 )', '18584', '42 - 25 - 8', 'american airlines center', '92'], ['march 21', 'sharks', '2 - 1', 'hiller ( 6 - 6 - 1 )', '17496', '42 - 26 - 8', 'hp pavilion at san jose', '92'], ['march 22', 'coyotes', '2 - 1', 'bryzgalov ( 25 - 20 - 4 )', '17645', '43 - 26 - 8', 'jobingcom arena', '94'], ['march 26', 'kings', '2 - 1', 'ersberg ( 4 - 3 - 3 )', '17331', '44 - 26 - 8', 'honda center', '96'], ['march 28', 'sharks', '3 - 1', 'hiller ( 8 - 7 - 1 )', '17334', '44 - 27 - 8', 'honda center', '96'], ['march 30', 'stars', '3 - 2', 'turco ( 31 - 20 - 6 )', '17174', '45 - 27 - 8', 'honda center', '98']] |
klm | https://en.wikipedia.org/wiki/KLM | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16882-1.html.csv | aggregation | klm 's group equity shareholding is an average of eighty-five percent . | {'scope': 'all', 'col': '5', 'type': 'average', 'result': '85 %', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', "group 's equity shareholding"], 'result': '85 %', 'ind': 0, 'tostr': "avg { all_rows ; group 's equity shareholding }"}, '85 %'], 'result': True, 'ind': 1, 'tostr': "round_eq { avg { all_rows ; group 's equity shareholding } ; 85 % } = true", 'tointer': "the average of the group 's equity shareholding record of all rows is 85 % ."} | round_eq { avg { all_rows ; group 's equity shareholding } ; 85 % } = true | the average of the group 's equity shareholding record of all rows is 85 % . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, "group 's equity shareholding_4": 4, '85%_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', "group 's equity shareholding_4": "group 's equity shareholding", '85%_5': '85 %'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], "group 's equity shareholding_4": [0], '85%_5': [1]} | ['company', 'type', 'principal activities', 'incorporated in', "group 's equity shareholding"] | [['cobalt ground solutions', 'subsidiary', 'ground handling', 'united kingdom', '60 %'], ['cygnific', 'subsidiary', 'sales and service', 'netherlands', '100 %'], ['epcor', 'subsidiary', 'maintenance', 'netherlands', '100 %'], ['high speed alliance', 'joint venture', 'high speed trains', 'netherlands', '5 % ( 10 % voting right )'], ['kenya airways', 'associate', 'airline', 'kenya', '27 %'], ['klm asia', 'subsidiary', 'airline', 'taiwan', '100 %'], ['klm catering services', 'subsidiary', 'catering services', 'netherlands', '100 %'], ['klm cityhopper', 'subsidiary', 'airline', 'netherlands', '100 %'], ['klm cityhopper uk', 'subsidiary', 'airline', 'united kingdom', '100 %'], ['klm equipment services', 'subsidiary', 'equipment support', 'netherlands', '100 %'], ['klm financial services', 'subsidiary', 'financing', 'netherlands', '100 %'], ['klm flight academy', 'subsidiary', 'flight academy', 'netherlands', '100 %'], ['klm health services', 'subsidiary', 'health services', 'netherlands', '100 %'], ['klm uk engineering', 'subsidiary', 'engineering and maintenance', 'united kingdom', '100 %'], ['martinair', 'subsidiary', 'cargo airline', 'netherlands', '100 %'], ['schiphol logistics park', 'joint controlled entity', 'logistics', 'netherlands', '53 % ( 45 % voting right )'], ['transaviacom', 'subsidiary', 'airline', 'netherlands', '100 %'], ['transaviacom france', 'associate', 'airline', 'france', '40 %']] |
peter gethin | https://en.wikipedia.org/wiki/Peter_Gethin | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1226516-1.html.csv | count | peter gethin drove for marlboro brm a total of four times . | {'scope': 'all', 'criterion': 'equal', 'value': 'marlboro brm', 'result': '4', 'col': '2', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'entrant', 'marlboro brm'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose entrant record fuzzily matches to marlboro brm .', 'tostr': 'filter_eq { all_rows ; entrant ; marlboro brm }'}], 'result': '4', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; entrant ; marlboro brm } }', 'tointer': 'select the rows whose entrant record fuzzily matches to marlboro brm . the number of such rows is 4 .'}, '4'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; entrant ; marlboro brm } } ; 4 } = true', 'tointer': 'select the rows whose entrant record fuzzily matches to marlboro brm . the number of such rows is 4 .'} | eq { count { filter_eq { all_rows ; entrant ; marlboro brm } } ; 4 } = true | select the rows whose entrant record fuzzily matches to marlboro brm . 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, 'entrant_5': 5, 'marlboro brm_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', 'entrant_5': 'entrant', 'marlboro brm_6': 'marlboro brm', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'entrant_5': [0], 'marlboro brm_6': [0], '4_7': [2]} | ['year', 'entrant', 'chassis', 'engine', 'points'] | [['1970', 'bruce mclaren motor racing', 'mclaren m14a', 'ford v8', '1'], ['1971', 'bruce mclaren motor racing', 'mclaren m14a', 'ford v8', '9'], ['1971', 'bruce mclaren motor racing', 'mclaren m19a', 'ford v8', '9'], ['1971', 'yardley team brm', 'brm p160', 'brm v12', '9'], ['1972', 'marlboro brm', 'brm p160b', 'brm v12', '1'], ['1972', 'marlboro brm', 'brm p180', 'brm v12', '1'], ['1972', 'marlboro brm', 'brm p160c', 'brm v12', '1'], ['1973', 'marlboro brm', 'brm p160e', 'brm v12', '0'], ['1974', 'embassy racing with graham hill', 'lola t370', 'ford v8', '0']] |
wide - body aircraft | https://en.wikipedia.org/wiki/Wide-body_aircraft | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-181206-1.html.csv | count | in the wide - body aircraft , 5 of the airbus model have maximum metric mtow of less than 500 . | {'scope': 'subset', 'criterion': 'less_than', 'value': '500', 'result': '5', 'col': '4', 'subset': {'col': '1', 'criterion': 'fuzzily_match', 'value': 'airbus'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_less', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'model', 'airbus'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; model ; airbus }', 'tointer': 'select the rows whose model record fuzzily matches to airbus .'}, 'maximum metric mtow', '500'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose model record fuzzily matches to airbus . among these rows , select the rows whose maximum metric mtow record is less than 500 .', 'tostr': 'filter_less { filter_eq { all_rows ; model ; airbus } ; maximum metric mtow ; 500 }'}], 'result': '5', 'ind': 2, 'tostr': 'count { filter_less { filter_eq { all_rows ; model ; airbus } ; maximum metric mtow ; 500 } }', 'tointer': 'select the rows whose model record fuzzily matches to airbus . among these rows , select the rows whose maximum metric mtow record is less than 500 . the number of such rows is 5 .'}, '5'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_less { filter_eq { all_rows ; model ; airbus } ; maximum metric mtow ; 500 } } ; 5 } = true', 'tointer': 'select the rows whose model record fuzzily matches to airbus . among these rows , select the rows whose maximum metric mtow record is less than 500 . the number of such rows is 5 .'} | eq { count { filter_less { filter_eq { all_rows ; model ; airbus } ; maximum metric mtow ; 500 } } ; 5 } = true | select the rows whose model record fuzzily matches to airbus . among these rows , select the rows whose maximum metric mtow record is less than 500 . the number of such rows is 5 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_less_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'model_6': 6, 'airbus_7': 7, 'maximum metric mtow_8': 8, '500_9': 9, '5_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_less_1': 'filter_less', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'model_6': 'model', 'airbus_7': 'airbus', 'maximum metric mtow_8': 'maximum metric mtow', '500_9': '500', '5_10': '5'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_less_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'model_6': [0], 'airbus_7': [0], 'maximum metric mtow_8': [1], '500_9': [1], '5_10': [3]} | ['model', 'eis - final prod year', 'eng', 'maximum metric mtow', 'outside diameter , main passenger deck'] | [['airbus a300', '1974 - 2007', '2', '132.0 tons 171.7 tons', 'inches ( m )'], ['airbus a310', '1982 - 2007', '2', '164.0 tons', 'inches ( m )'], ['airbus a330', '1994 -', '2', '233.0 tons', 'inches ( m )'], ['airbus a340', '1993 - 2012', '4', '380.0 tons', 'inches ( m )'], ['airbus a350 xwb', '2014 ( est )', '2', '298.0 tons', 'inches ( m )'], ['airbus a380', '2007 -', '4', '560.0 tons', 'inches ( m )'], ['boeing 747', '1970 -', '4', '412.8 tons', 'inches ( m )'], ['boeing 767', '1982 -', '2', '204.1 tons', 'inches ( m )'], ['boeing 777', '1995 -', '2', '351.5 tons', 'inches ( m )'], ['boeing 787 dreamliner', '2011', '2', '245.0 tons', 'inches ( m )'], ['ilyushin il - 86', '1980 - 1994', '4', '208.0 tons', '239inches ( 6.08 m )'], ['ilyushin il - 96', '1992 -', '4', '250.0 tons', '239inches ( 6.08 m )'], ['l - 1011 tristar', '1972 - 1985', '3', '231.3 tons', 'inches ( m )'], ['md dc - 10', '1971 - 1989', '3', '259.5 tons', 'inches ( m )'], ['md md - 11', '1990 - 2001', '3', '286.0 tons', 'inches ( m )']] |
kprd | https://en.wikipedia.org/wiki/KPRD | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14993404-1.html.csv | superlative | the highest radio frequency you can list to kprd is 107.3 in hill city , kansas . | {'scope': 'all', 'col_superlative': '2', 'row_superlative': '5', 'value_mentioned': 'yes', 'max_or_min': 'max', 'other_col': '3', 'subset': None} | {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'max', 'args': ['all_rows', 'frequency mhz'], 'result': '107.3', 'ind': 0, 'tostr': 'max { all_rows ; frequency mhz }', 'tointer': 'the maximum frequency mhz record of all rows is 107.3 .'}, '107.3'], 'result': True, 'ind': 1, 'tostr': 'eq { max { all_rows ; frequency mhz } ; 107.3 }', 'tointer': 'the maximum frequency mhz record of all rows is 107.3 .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'frequency mhz'], 'result': None, 'ind': 2, 'tostr': 'argmax { all_rows ; frequency mhz }'}, 'city of license'], 'result': 'hill city , kansas', 'ind': 3, 'tostr': 'hop { argmax { all_rows ; frequency mhz } ; city of license }'}, 'hill city , kansas'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { argmax { all_rows ; frequency mhz } ; city of license } ; hill city , kansas }', 'tointer': 'the city of license record of the row with superlative frequency mhz record is hill city , kansas .'}], 'result': True, 'ind': 5, 'tostr': 'and { eq { max { all_rows ; frequency mhz } ; 107.3 } ; eq { hop { argmax { all_rows ; frequency mhz } ; city of license } ; hill city , kansas } } = true', 'tointer': 'the maximum frequency mhz record of all rows is 107.3 . the city of license record of the row with superlative frequency mhz record is hill city , kansas .'} | and { eq { max { all_rows ; frequency mhz } ; 107.3 } ; eq { hop { argmax { all_rows ; frequency mhz } ; city of license } ; hill city , kansas } } = true | the maximum frequency mhz record of all rows is 107.3 . the city of license record of the row with superlative frequency mhz record is hill city , kansas . | 6 | 6 | {'and_5': 5, 'result_6': 6, 'eq_1': 1, 'max_0': 0, 'all_rows_7': 7, 'frequency mhz_8': 8, '107.3_9': 9, 'str_eq_4': 4, 'str_hop_3': 3, 'argmax_2': 2, 'all_rows_10': 10, 'frequency mhz_11': 11, 'city of license_12': 12, 'hill city , kansas_13': 13} | {'and_5': 'and', 'result_6': 'true', 'eq_1': 'eq', 'max_0': 'max', 'all_rows_7': 'all_rows', 'frequency mhz_8': 'frequency mhz', '107.3_9': '107.3', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'argmax_2': 'argmax', 'all_rows_10': 'all_rows', 'frequency mhz_11': 'frequency mhz', 'city of license_12': 'city of license', 'hill city , kansas_13': 'hill city , kansas'} | {'and_5': [6], 'result_6': [], 'eq_1': [5], 'max_0': [1], 'all_rows_7': [0], 'frequency mhz_8': [0], '107.3_9': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'argmax_2': [3], 'all_rows_10': [2], 'frequency mhz_11': [2], 'city of license_12': [3], 'hill city , kansas_13': [4]} | ['call sign', 'frequency mhz', 'city of license', 'erp w', 'class', 'fcc info'] | [['k202bp', '88.3', 'bellaire , smith county , kansas', '78', 'd', 'fcc'], ['k216ed', '91.1', 'phillipsburg , kansas', '222', 'd', 'fcc'], ['k241an', '96.1', 'pratt , kansas', '250', 'd', 'fcc'], ['k278ap', '103.5', 'lewis , kansas', '171', 'd', 'fcc'], ['k297ai', '107.3', 'hill city , kansas', '170', 'd', 'fcc']] |
2008 - 09 supersport series | https://en.wikipedia.org/wiki/2008%E2%80%9309_Supersport_Series | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-19662262-6.html.csv | superlative | paul harris had the highest strike rate of the players in the 2008 - 09 supersport series . | {'scope': 'all', 'col_superlative': '8', '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', 'strike rate'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; strike rate }'}, 'player'], 'result': 'paul harris', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; strike rate } ; player }'}, 'paul harris'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; strike rate } ; player } ; paul harris } = true', 'tointer': 'select the row whose strike rate record of all rows is maximum . the player record of this row is paul harris .'} | eq { hop { argmax { all_rows ; strike rate } ; player } ; paul harris } = true | select the row whose strike rate record of all rows is maximum . the player record of this row is paul harris . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'strike rate_5': 5, 'player_6': 6, 'paul harris_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'strike rate_5': 'strike rate', 'player_6': 'player', 'paul harris_7': 'paul harris'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'strike rate_5': [0], 'player_6': [1], 'paul harris_7': [2]} | ['player', 'team', 'matches', 'overs', 'wickets', 'economy rate', 'average', 'strike rate', 'bbi', 'bbm'] | [['makhaya ntini', 'warriors', '4', '152.4', '24', '2.18', '13.91', '38.1', '6 / 85', '9 / 109'], ['lonwabo tsotsobe', 'warriors', '4', '127.5', '16', '2.26', '18.12', '47.9', '4 / 3', '5 / 98'], ['juan theron', 'warriors', '4', '133.4', '19', '2.71', '19.10', '42.2', '7 / 46', '7 / 56'], ['mornã morkel', 'titans', '3', '92.2', '17', '3.51', '19.17', '32.7', '6 / 47', '11 / 56'], ['paul harris', 'titans', '3', '126.0', '14', '2.74', '22.28', '54.0', '7 / 94', '12 / 180']] |
huancayo | https://en.wikipedia.org/wiki/Huancayo | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1704094-1.html.csv | majority | all of the municipalities of the city of huancayo are over 3 msnm elevation . | {'scope': 'all', 'col': '7', 'most_or_all': 'all', 'criterion': 'greater_than', 'value': '3', 'subset': None} | {'func': 'all_greater', 'args': ['all_rows', 'elevation msnm', '3'], 'result': True, 'ind': 0, 'tointer': 'for the elevation msnm records of all rows , all of them are greater than 3 .', 'tostr': 'all_greater { all_rows ; elevation msnm ; 3 } = true'} | all_greater { all_rows ; elevation msnm ; 3 } = true | for the elevation msnm records of all rows , all of them are greater than 3 . | 1 | 1 | {'all_greater_0': 0, 'result_1': 1, 'all_rows_2': 2, 'elevation msnm_3': 3, '3_4': 4} | {'all_greater_0': 'all_greater', 'result_1': 'true', 'all_rows_2': 'all_rows', 'elevation msnm_3': 'elevation msnm', '3_4': '3'} | {'all_greater_0': [1], 'result_1': [], 'all_rows_2': [0], 'elevation msnm_3': [0], '3_4': [0]} | ['municipalities of the city', 'area km square', 'population censo 2007 ( hab )', 'population under 1 year - old censo 2007 ( hab )', 'households ( 2007 )', 'density ( hab / km square )', 'elevation msnm'] | [['chilca', '8 , 3 km square', '77.392', '1.358', '17.509', '9.324 , 33', '3.275 msnm'], ['el tambo', '73 , 56 km square', '146.847', '2.365', '36.982', '1.996 , 28', '3.260 msnm'], ['huancayo', '237 , 55 km square', '112.054', '1789', '27.552', '471 , 70', '3.249 msnm'], ['total', '319 , 41 km square', '336.293', '5.512', '82.043', '1.052 , 85', '-']] |
tax parity for health plan beneficiaries act | https://en.wikipedia.org/wiki/Tax_Parity_for_Health_Plan_Beneficiaries_Act | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13829540-1.html.csv | comparative | for the tax parity for health plan beneficiaries act , there were 3 more cosponsors in the 109th congress than in the 108th congress . | {'row_1': '7', 'row_2': '8', 'col': '5', 'col_other': '1', 'relation': 'diff', 'record_mentioned': 'no', 'diff_result': {'diff_value': '3', 'bigger': 'row1'}} | {'func': 'eq', 'args': [{'func': 'diff', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'congress', '109th congress'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose congress record fuzzily matches to 109th congress .', 'tostr': 'filter_eq { all_rows ; congress ; 109th congress }'}, 'of cosponsors'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; congress ; 109th congress } ; of cosponsors }', 'tointer': 'select the rows whose congress record fuzzily matches to 109th congress . take the of cosponsors record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'congress', '108th congress'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose congress record fuzzily matches to 108th congress .', 'tostr': 'filter_eq { all_rows ; congress ; 108th congress }'}, 'of cosponsors'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; congress ; 108th congress } ; of cosponsors }', 'tointer': 'select the rows whose congress record fuzzily matches to 108th congress . take the of cosponsors record of this row .'}], 'result': '3', 'ind': 4, 'tostr': 'diff { hop { filter_eq { all_rows ; congress ; 109th congress } ; of cosponsors } ; hop { filter_eq { all_rows ; congress ; 108th congress } ; of cosponsors } }'}, '3'], 'result': True, 'ind': 5, 'tostr': 'eq { diff { hop { filter_eq { all_rows ; congress ; 109th congress } ; of cosponsors } ; hop { filter_eq { all_rows ; congress ; 108th congress } ; of cosponsors } } ; 3 } = true', 'tointer': 'select the rows whose congress record fuzzily matches to 109th congress . take the of cosponsors record of this row . select the rows whose congress record fuzzily matches to 108th congress . take the of cosponsors record of this row . the first record is 3 larger than the second record .'} | eq { diff { hop { filter_eq { all_rows ; congress ; 109th congress } ; of cosponsors } ; hop { filter_eq { all_rows ; congress ; 108th congress } ; of cosponsors } } ; 3 } = true | select the rows whose congress record fuzzily matches to 109th congress . take the of cosponsors record of this row . select the rows whose congress record fuzzily matches to 108th congress . take the of cosponsors record of this row . the first record is 3 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, 'congress_8': 8, '109th congress_9': 9, 'of cosponsors_10': 10, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_11': 11, 'congress_12': 12, '108th congress_13': 13, 'of cosponsors_14': 14, '3_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', 'congress_8': 'congress', '109th congress_9': '109th congress', 'of cosponsors_10': 'of cosponsors', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_11': 'all_rows', 'congress_12': 'congress', '108th congress_13': '108th congress', 'of cosponsors_14': 'of cosponsors', '3_15': '3'} | {'eq_5': [6], 'result_6': [], 'diff_4': [5], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_7': [0], 'congress_8': [0], '109th congress_9': [0], 'of cosponsors_10': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_11': [1], 'congress_12': [1], '108th congress_13': [1], 'of cosponsors_14': [3], '3_15': [5]} | ['congress', 'bill number ( s )', 'date introduced', 'sponsor ( s )', 'of cosponsors', 'latest status'] | [['112th congress', 's 1171', 'june 9 , 2011', 'sen charles e schumer ( d - ny )', '19', 'referred to the senate committee on finance'], ['112th congress', 'hr 2088', 'june 2 , 2011', 'rep jim mcdermott ( d - wa )', '74', 'referred to the house committee on ways and means'], ['111th congress', 's 1153', 'may 21 , 2009', 'sen charles e schumer ( d - ny )', '23', 'died in the senate committee on finance'], ['111th congress', 'hr 2625', 'june 2 , 2009', 'rep jim mcdermott ( d - wa )', '133', 'died in the house committee on ways and means'], ['110th congress', 's 1556', 'june 6 , 2007', 'sen gordon h smith ( r - or )', '25', 'died in the senate committee on finance'], ['110th congress', 'hr 1820', 'march 29 , 2007', 'rep jim mcdermott ( d - wa )', '119', 'died in the house committee on ways and means'], ['109th congress', 's 1360', 'june 30 , 2005', 'sen gordon h smith ( r - or )', '12', 'died in the senate committee on finance'], ['108th congress', 's 1702', 'october 2 , 2003', 'sen gordon h smith ( r - or )', '9', 'died in the senate committee on finance']] |
list of state leaders in the 20th century bc | https://en.wikipedia.org/wiki/List_of_state_leaders_in_the_20th_century_BC | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17606888-8.html.csv | count | there were 3 different state leaders in the 1930s b.c. | {'scope': 'all', 'criterion': 'greater_than_eq', 'value': '1930', 'result': '3', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater_eq', 'args': ['all_rows', 'from', '1930'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose from record is greater than or equal to 1930 .', 'tostr': 'filter_greater_eq { all_rows ; from ; 1930 }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_greater_eq { all_rows ; from ; 1930 } }', 'tointer': 'select the rows whose from record is greater than or equal to 1930 . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_greater_eq { all_rows ; from ; 1930 } } ; 3 } = true', 'tointer': 'select the rows whose from record is greater than or equal to 1930 . the number of such rows is 3 .'} | eq { count { filter_greater_eq { all_rows ; from ; 1930 } } ; 3 } = true | select the rows whose from record is greater than or equal to 1930 . the number of such rows is 3 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_greater_eq_0': 0, 'all_rows_4': 4, 'from_5': 5, '1930_6': 6, '3_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_greater_eq_0': 'filter_greater_eq', 'all_rows_4': 'all_rows', 'from_5': 'from', '1930_6': '1930', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_greater_eq_0': [1], 'all_rows_4': [0], 'from_5': [0], '1930_6': [0], '3_7': [2]} | ['type', 'name', 'title', 'royal house', 'from'] | [['sovereign', 'sláine mac dela', 'high king', 'fir bolg', '1934 bc'], ['sovereign', 'rudraige mac dela', 'high king', 'fir bolg', '1933 bc'], ['sovereign', 'gann mac dela & genann', 'high king', 'fir bolg', '1931 bc'], ['sovereign', 'sengann mac dela', 'high king', 'fir bolg', '1927 bc'], ['sovereign', 'fiacha cennfinnán', 'high king', 'fir bolg', '1922 bc'], ['sovereign', 'rinnal', 'high king', 'fir bolg', '1917 bc'], ['sovereign', 'fodbgen', 'high king', 'fir bolg', '1911 bc'], ['sovereign', 'eochaid mac eirc', 'high king', 'fir bolg', '1907 bc']] |
new democratic party candidates , 2008 canadian federal election | https://en.wikipedia.org/wiki/New_Democratic_Party_candidates%2C_2008_Canadian_federal_election | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10953705-9.html.csv | majority | winnipeg is the residence of the majority of new democratic party candidates . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'winnipeg', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'residence', 'winnipeg'], 'result': True, 'ind': 0, 'tointer': 'for the residence records of all rows , most of them fuzzily match to winnipeg .', 'tostr': 'most_eq { all_rows ; residence ; winnipeg } = true'} | most_eq { all_rows ; residence ; winnipeg } = true | for the residence records of all rows , most of them fuzzily match to winnipeg . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'residence_3': 3, 'winnipeg_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'residence_3': 'residence', 'winnipeg_4': 'winnipeg'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'residence_3': [0], 'winnipeg_4': [0]} | ['riding', 'candidate', 'gender', 'residence', 'occupation', 'votes', 'rank'] | [['brandon-souris', 'jean luc bouché', 'm', 'brandon', 'locomotive engineer', '6055', '2nd'], ['charleswood-st james-assiniboia', 'fiona shiells', 'f', 'winnipeg', 'ministerial assistant', '7190', '3rd'], ['churchill', 'niki ashton', 'f', 'thompson', 'researcher', '8734', '1st'], ['dauphin-swan river-marquette', 'ron strynadka', 'm', 'birtle', 'retired', '4914', '2nd'], ['elmwood-transcona', 'jim maloway', 'm', 'winnipeg', 'small businessman', '14355', '1st'], ['kildonan-st paul', 'ross eadie', 'm', 'winnipeg', 'self employed / consultant', '12093', '2nd'], ['portage-lisgar', 'mohamed alli', 'm', 'winnipeg', 'distribution centre associate', '2353', '4th'], ['provencher', 'ross c martin', 'm', 'oakbank', 'design coordinator', '4947', '2nd'], ['saint boniface', 'matt schaubroeck', 'm', 'winnipeg', 'student', '5502', '3rd'], ['selkirk-interlake', 'patricia cordner', 'f', 'selkirk', 'retired', '9506', '2nd'], ['winnipeg centre', 'pat martin', 'm', 'winnipeg', 'parliamentarian', '12285', '1st'], ['winnipeg north', 'judy wasylycia - leis', 'f', 'winnipeg', 'parliamentarian', '14097', '1st'], ['winnipeg south', 'sean robert', 'm', 'winnipeg', 'product consultant - mlcc', '4673', '3rd'], ['winnipeg south centre', 'rachel heinrichs', 'f', 'winnipeg', 'student', '5490', '3rd']] |
india at the commonwealth games | https://en.wikipedia.org/wiki/India_at_the_Commonwealth_Games | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16792440-1.html.csv | superlative | 2010 was the year where india earned the highest amount of medals at the commonwealth games . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'total'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; total }'}, 'year'], 'result': '2010', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; total } ; year }'}, '2010'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; total } ; year } ; 2010 } = true', 'tointer': 'select the row whose total record of all rows is maximum . the year record of this row is 2010 .'} | eq { hop { argmax { all_rows ; total } ; year } ; 2010 } = true | select the row whose total record of all rows is maximum . the year record of this row is 2010 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'total_5': 5, 'year_6': 6, '2010_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', 'year_6': 'year', '2010_7': '2010'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'total_5': [0], 'year_6': [1], '2010_7': [2]} | ['year', 'gold', 'silver', 'bronze', 'total'] | [['2010', '38', '27', '36', '101'], ['2006', '22', '17', '10', '49'], ['2002', '30', '22', '13', '69'], ['1998', '7', '10', '8', '25'], ['1994', '6', '11', '7', '24'], ['1990', '13', '8', '11', '32'], ['1986', 'did not participate', 'did not participate', 'did not participate', 'did not participate'], ['1982', '5', '8', '3', '16'], ['1978', '5', '5', '5', '15'], ['1974', '4', '8', '3', '15'], ['1970', '5', '3', '4', '12'], ['1966', '3', '4', '3', '10'], ['1962', 'did not participate', 'did not participate', 'did not participate', 'did not participate'], ['1958', '2', '1', '0', '3'], ['1954', '0', '0', '0', '0'], ['1950', 'did not participate', 'did not participate', 'did not participate', 'did not participate'], ['1938', '0', '0', '0', '0'], ['1934', '0', '0', '1', '1'], ['1930', 'did not participate', 'did not participate', 'did not participate', 'did not participate'], ['total', '140', '124', '104', '372']] |
2007 cricket world cup statistics | https://en.wikipedia.org/wiki/2007_Cricket_World_Cup_statistics | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10044096-10.html.csv | count | there were 2 players with 8 sixes in the 2007 cricket world cup . | {'scope': 'all', 'criterion': 'equal', 'value': '8', 'result': '2', 'col': '1', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'sixes', '8'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose sixes record is equal to 8 .', 'tostr': 'filter_eq { all_rows ; sixes ; 8 }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; sixes ; 8 } }', 'tointer': 'select the rows whose sixes record is equal to 8 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; sixes ; 8 } } ; 2 } = true', 'tointer': 'select the rows whose sixes record is equal to 8 . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; sixes ; 8 } } ; 2 } = true | select the rows whose sixes record is equal to 8 . the number of such rows is 2 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_eq_0': 0, 'all_rows_4': 4, 'sixes_5': 5, '8_6': 6, '2_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'sixes_5': 'sixes', '8_6': '8', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'sixes_5': [0], '8_6': [0], '2_7': [2]} | ['sixes', 'player', 'opponent', 'venue', 'date'] | [['8', 'imran nazir', 'zimbabwe', 'kingston', '21 - 03 - 2007'], ['8', 'adam gilchrist', 'sri lanka', 'bridgetown', '29 - 04 - 2007'], ['7', 'herschelle gibbs', 'netherlands', 'basseterre', '16 - 03 - 2007'], ['7', 'brad hodge', 'netherlands', 'basseterre', '18 - 03 - 2007'], ['7', 'sanath jayasuriya', 'bangladesh', 'port of spain', '21 - 03 - 2007'], ['7', 'yuvraj singh', 'bermuda', 'port of spain', '19 - 03 - 2007'], ['5', 'jacques kallis', 'netherlands', 'basseterre', '16 - 03 - 2007'], ['5', 'ab de villiers', 'west indies', "st george 's", '10 - 04 - 2007'], ['5', 'mark boucher', 'west indies', "st george 's", '10 - 04 - 2007'], ['5', 'brendon mccullum', 'canada', 'gros islet', '22 - 03 - 2007'], ['5', 'craig mcmillan', 'kenya', 'gros islet', '20 - 03 - 2007'], ['5', 'ricky ponting', 'scotland', 'basseterre', '14 - 03 - 2007'], ['5', 'shivnarine chanderpaul', 'sri lanka', 'georgetown', '01 - 04 - 2007']] |
portuguese legislative election , 1995 | https://en.wikipedia.org/wiki/Portuguese_legislative_election%2C_1995 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1883027-1.html.csv | count | there are three days where there was a double digit lead . october 1st , september 23 , and october 6th . | {'scope': 'all', 'criterion': 'greater_than_eq', 'value': '10 %', 'result': '3', 'col': '7', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater_eq', 'args': ['all_rows', 'lead', '10 %'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose lead record is greater than or equal to 10 % .', 'tostr': 'filter_greater_eq { all_rows ; lead ; 10 % }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_greater_eq { all_rows ; lead ; 10 % } }', 'tointer': 'select the rows whose lead record is greater than or equal to 10 % . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_greater_eq { all_rows ; lead ; 10 % } } ; 3 } = true', 'tointer': 'select the rows whose lead record is greater than or equal to 10 % . the number of such rows is 3 .'} | eq { count { filter_greater_eq { all_rows ; lead ; 10 % } } ; 3 } = true | select the rows whose lead record is greater than or equal to 10 % . the number of such rows is 3 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_greater_eq_0': 0, 'all_rows_4': 4, 'lead_5': 5, '10%_6': 6, '3_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_greater_eq_0': 'filter_greater_eq', 'all_rows_4': 'all_rows', 'lead_5': 'lead', '10%_6': '10 %', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_greater_eq_0': [1], 'all_rows_4': [0], 'lead_5': [0], '10%_6': [0], '3_7': [2]} | ['date released', 'institute', 'social democratic', 'socialist', 'green - communist', "people 's party", 'lead'] | [['october 1 , 1995', 'election results', '34.1 % 88 seats', '43.8 % 112 seats', '8.6 % 15 seats', '9.1 % 15 seats', '9.7 %'], ['september 23 , 1995', 'metris', '32.0 %', '42.0 %', '10.0 %', '8.0 %', '10.0 %'], ['september 23 , 1995', 'euroteste', '35.0 %', '39.0 %', '9.0 %', '10.0 %', '4.0 %'], ['september 23 , 1995', 'euroexpansão', '32.7 %', '44.5 %', '11.5 %', '6.9 %', '11.8 %'], ['september 23 , 1995', 'universidade catã cubiclica', '35.0 %', '40.0 %', '9.0 %', '10.0 %', '5.0 %'], ['september 22 , 1995', 'ipsos', '35.0 %', '41.0 %', '9.0 %', '9.0 %', '6.0 %'], ['september 21 , 1995', 'marktest', '33.0 %', '42.0 %', '10.0 %', '9.0 %', '9.0 %'], ['september 16 , 1995', 'compta', '39.0 %', '40.0 %', '12.0 %', '8.0 %', '1.0 %'], ['october 6 , 1991', '1991 election', '50.6 % 135 seats', '29.1 % 72 seats', '8.8 % 17 seats', '4.4 % 5 seats', '21.5 %']] |
1945 vfl season | https://en.wikipedia.org/wiki/1945_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10809271-8.html.csv | ordinal | western oval yielded the largest crowd of 1945 vfl season . | {'scope': 'all', 'row': '4', 'col': '6', 'order': '1', 'col_other': '5', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'crowd', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; crowd ; 1 }'}, 'venue'], 'result': 'western oval', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; crowd ; 1 } ; venue }'}, 'western oval'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; crowd ; 1 } ; venue } ; western oval } = true', 'tointer': 'select the row whose crowd record of all rows is 1st maximum . the venue record of this row is western oval .'} | eq { hop { nth_argmax { all_rows ; crowd ; 1 } ; venue } ; western oval } = true | select the row whose crowd record of all rows is 1st maximum . the venue record of this row is western oval . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'crowd_5': 5, '1_6': 6, 'venue_7': 7, 'western oval_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'crowd_5': 'crowd', '1_6': '1', 'venue_7': 'venue', 'western oval_8': 'western oval'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'crowd_5': [0], '1_6': [0], 'venue_7': [1], 'western oval_8': [2]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['richmond', '16.15 ( 111 )', 'st kilda', '13.6 ( 84 )', 'punt road oval', '15000', '9 june 1945'], ['south melbourne', '12.16 ( 88 )', 'melbourne', '9.4 ( 58 )', 'junction oval', '18000', '9 june 1945'], ['north melbourne', '16.10 ( 106 )', 'hawthorn', '10.8 ( 68 )', 'arden street oval', '7000', '9 june 1945'], ['footscray', '12.15 ( 87 )', 'essendon', '7.14 ( 56 )', 'western oval', '23000', '9 june 1945'], ['fitzroy', '23.15 ( 153 )', 'collingwood', '8.10 ( 58 )', 'brunswick street oval', '20000', '9 june 1945'], ['geelong', '10.9 ( 69 )', 'carlton', '14.21 ( 105 )', 'kardinia park', '11000', '9 june 1945']] |
diezel | https://en.wikipedia.org/wiki/Diezel | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1844725-1.html.csv | comparative | of the range of diezel amplifiers , the herbert model has more tubes than the vh4s model . | {'row_1': '3', 'row_2': '2', 'col': '2', 'col_other': '1', 'relation': 'greater', 'record_mentioned': 'yes', 'diff_result': None} | {'func': 'and', 'args': [{'func': 'greater', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'model', 'herbert'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose model record fuzzily matches to herbert .', 'tostr': 'filter_eq { all_rows ; model ; herbert }'}, 'poweramp'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; model ; herbert } ; poweramp }', 'tointer': 'select the rows whose model record fuzzily matches to herbert . take the poweramp record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'model', 'vh4s'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose model record fuzzily matches to vh4s .', 'tostr': 'filter_eq { all_rows ; model ; vh4s }'}, 'poweramp'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; model ; vh4s } ; poweramp }', 'tointer': 'select the rows whose model record fuzzily matches to vh4s . take the poweramp record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; model ; herbert } ; poweramp } ; hop { filter_eq { all_rows ; model ; vh4s } ; poweramp } }', 'tointer': 'select the rows whose model record fuzzily matches to herbert . take the poweramp record of this row . select the rows whose model record fuzzily matches to vh4s . take the poweramp record of this row . the first record is greater than the second record .'}, {'func': 'and', 'args': [{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'model', 'herbert'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose model record fuzzily matches to herbert .', 'tostr': 'filter_eq { all_rows ; model ; herbert }'}, 'poweramp'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; model ; herbert } ; poweramp }', 'tointer': 'select the rows whose model record fuzzily matches to herbert . take the poweramp record of this row .'}, 'mono , 6 tubes'], 'result': True, 'ind': 5, 'tostr': 'eq { hop { filter_eq { all_rows ; model ; herbert } ; poweramp } ; mono , 6 tubes }', 'tointer': 'the poweramp record of the first row is mono , 6 tubes .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'model', 'vh4s'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose model record fuzzily matches to vh4s .', 'tostr': 'filter_eq { all_rows ; model ; vh4s }'}, 'poweramp'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; model ; vh4s } ; poweramp }', 'tointer': 'select the rows whose model record fuzzily matches to vh4s . take the poweramp record of this row .'}, 'stereo , 4 tubes'], 'result': True, 'ind': 6, 'tostr': 'eq { hop { filter_eq { all_rows ; model ; vh4s } ; poweramp } ; stereo , 4 tubes }', 'tointer': 'the poweramp record of the second row is stereo , 4 tubes .'}], 'result': True, 'ind': 7, 'tostr': 'and { eq { hop { filter_eq { all_rows ; model ; herbert } ; poweramp } ; mono , 6 tubes } ; eq { hop { filter_eq { all_rows ; model ; vh4s } ; poweramp } ; stereo , 4 tubes } }', 'tointer': 'the poweramp record of the first row is mono , 6 tubes . the poweramp record of the second row is stereo , 4 tubes .'}], 'result': True, 'ind': 8, 'tostr': 'and { greater { hop { filter_eq { all_rows ; model ; herbert } ; poweramp } ; hop { filter_eq { all_rows ; model ; vh4s } ; poweramp } } ; and { eq { hop { filter_eq { all_rows ; model ; herbert } ; poweramp } ; mono , 6 tubes } ; eq { hop { filter_eq { all_rows ; model ; vh4s } ; poweramp } ; stereo , 4 tubes } } } = true', 'tointer': 'select the rows whose model record fuzzily matches to herbert . take the poweramp record of this row . select the rows whose model record fuzzily matches to vh4s . take the poweramp record of this row . the first record is greater than the second record . the poweramp record of the first row is mono , 6 tubes . the poweramp record of the second row is stereo , 4 tubes .'} | and { greater { hop { filter_eq { all_rows ; model ; herbert } ; poweramp } ; hop { filter_eq { all_rows ; model ; vh4s } ; poweramp } } ; and { eq { hop { filter_eq { all_rows ; model ; herbert } ; poweramp } ; mono , 6 tubes } ; eq { hop { filter_eq { all_rows ; model ; vh4s } ; poweramp } ; stereo , 4 tubes } } } = true | select the rows whose model record fuzzily matches to herbert . take the poweramp record of this row . select the rows whose model record fuzzily matches to vh4s . take the poweramp record of this row . the first record is greater than the second record . the poweramp record of the first row is mono , 6 tubes . the poweramp record of the second row is stereo , 4 tubes . | 13 | 9 | {'and_8': 8, 'result_9': 9, 'greater_4': 4, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_10': 10, 'model_11': 11, 'herbert_12': 12, 'poweramp_13': 13, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_14': 14, 'model_15': 15, 'vh4s_16': 16, 'poweramp_17': 17, 'and_7': 7, 'str_eq_5': 5, 'mono , 6\u2009tubes_18': 18, 'str_eq_6': 6, 'stereo , 4\u2009tubes_19': 19} | {'and_8': 'and', 'result_9': 'true', 'greater_4': 'greater', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_10': 'all_rows', 'model_11': 'model', 'herbert_12': 'herbert', 'poweramp_13': 'poweramp', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_14': 'all_rows', 'model_15': 'model', 'vh4s_16': 'vh4s', 'poweramp_17': 'poweramp', 'and_7': 'and', 'str_eq_5': 'str_eq', 'mono , 6\u2009tubes_18': 'mono , 6 tubes', 'str_eq_6': 'str_eq', 'stereo , 4\u2009tubes_19': 'stereo , 4 tubes'} | {'and_8': [9], 'result_9': [], 'greater_4': [8], 'str_hop_2': [4, 5], 'filter_str_eq_0': [2], 'all_rows_10': [0], 'model_11': [0], 'herbert_12': [0], 'poweramp_13': [2], 'str_hop_3': [4, 6], 'filter_str_eq_1': [3], 'all_rows_14': [1], 'model_15': [1], 'vh4s_16': [1], 'poweramp_17': [3], 'and_7': [8], 'str_eq_5': [7], 'mono , 6\u2009tubes_18': [5], 'str_eq_6': [7], 'stereo , 4\u2009tubes_19': [6]} | ['model', 'poweramp', 'dimensions', 'mass', 'form factor ( s )', 'output'] | [['vh4', 'mono , 4 tubes', '29 11 11 in 74 28 28 cm', '50 lb ( 23 kg )', 'head', '90 - 160w'], ['vh4s', 'stereo , 4 tubes', '29 11 11 in 74 28 28 cm', '50 lb ( 23 kg )', 'head', '2 50w'], ['herbert', 'mono , 6 tubes', '29 11 11 in 74 28 28 cm', '60 lb ( 27 kg )', 'head', '180w'], ['hagen', 'mono , 4 tubes', '29 11 11 in 74 28 28 cm', '53 lb ( 24 kg )', 'head', '100w'], ['d - moll', 'mono , 4 tubes', '23 12 11 in 59 29 , 5 27 cm', '51 lb ( 23 kg )', 'head', '100w'], ['schmidt', 'mono , 2 tubes', '20 12 12 in 50 30 31 cm', '48 , 5 lb ( 22 kg )', 'head', '15 - 30w'], ['lucy ( bass amp )', 'up to 8 el34 500 watts rms', 'tba', 'tba', 'head', 'tba']] |
argentine primera división | https://en.wikipedia.org/wiki/Argentine_Primera_Divisi%C3%B3n | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1211728-1.html.csv | count | a total of six clubs in the argentine primera división have no title wins . | {'scope': 'all', 'criterion': 'equal', 'value': '( none )', 'result': '7', 'col': '6', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'last title', '( none )'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose last title record fuzzily matches to ( none ) .', 'tostr': 'filter_eq { all_rows ; last title ; ( none ) }'}], 'result': '7', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; last title ; ( none ) } }', 'tointer': 'select the rows whose last title record fuzzily matches to ( none ) . the number of such rows is 7 .'}, '7'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; last title ; ( none ) } } ; 7 } = true', 'tointer': 'select the rows whose last title record fuzzily matches to ( none ) . the number of such rows is 7 .'} | eq { count { filter_eq { all_rows ; last title ; ( none ) } } ; 7 } = true | select the rows whose last title record fuzzily matches to ( none ) . the number of such rows is 7 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'last title_5': 5, '(none)_6': 6, '7_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'last title_5': 'last title', '(none)_6': '( none )', '7_7': '7'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'last title_5': [0], '(none)_6': [0], '7_7': [2]} | ['club', 'district', 'area / province', 'stadium', 'first season', 'last title'] | [['all boys', 'floresta', 'buenos aires', 'islas malvinas', '1923', '( none )'], ['argentinos juniors', 'la paternal', 'buenos aires', 'diego a maradona', '1922', '2010 clausura'], ['arsenal', 'sarandí', 'greater buenos aires', 'julio h grondona', '2002 - 03', '2012 clausura'], ['atlético de rafaela', 'rafaela', 'santa fe', 'nuevo monumental', '2003 apertura', '( none )'], ['belgrano ( c )', 'córdoba', 'córdoba', 'gigante de alberdi', '1991 apertura', '( none )'], ['boca juniors', 'la boca', 'buenos aires', 'alberto j armando', '1913', '2011 apertura'], ['colón', 'santa fe', 'santa fe', 'brigadier estanislao lópez', '1966', '( none )'], ['estudiantes ( lp )', 'la plata', 'buenos aires province', 'ciudad de la plata', '1912', '2010 apertura'], ['gimnasia y esgrima ( lp )', 'la plata', 'buenos aires province', 'juan c zerillo', '1916', '1929'], ['godoy cruz', 'mendoza', 'mendoza', 'malvinas argentinas', '2006 apertura', '( none )'], ['lanús', 'lanús', 'greater buenos aires', 'ciudad de lanús', '1920', '2007 apertura'], ["newell 's old boys", 'rosario', 'santa fe', 'marcelo bielsa', '1939', '2013 final'], ['olimpo', 'bahía blanca', 'buenos aires province', 'roberto carminatti', '2002 apertura', '( none )'], ['quilmes', 'quilmes', 'greater buenos aires', 'centenario josé l meiszner', '1893', '1978 metropolitano'], ['racing', 'avellaneda', 'greater buenos aires', 'presidente juan d perón', '1911', '2001 apertura'], ['river plate', 'belgrano', 'buenos aires', 'monumental vespucio liberti', '1909', '2008 clausura'], ['rosario central', 'rosario', 'santa fe', 'gigante de arroyito', '1939', '1986 - 87'], ['san lorenzo', 'boedo', 'buenos aires', 'pedro bidegain', '1915', '2007 clausura'], ['tigre', 'victoria', 'greater buenos aires', 'coliseo de victoria', '1913', '( none )'], ['vélez sarsfield', 'liniers', 'buenos aires', 'josé amalfitani', '1919', '2013 superfinal']] |
usa today all - usa high school basketball team | https://en.wikipedia.org/wiki/USA_Today_All-USA_high_school_basketball_team | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11677760-7.html.csv | superlative | jeff lebo was the shortest player from north carolina college picked for boys ' usa high school basketball team in 1985 . | {'scope': 'subset', 'col_superlative': '2', 'row_superlative': '4', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1,5', 'subset': {'col': '5', 'criterion': 'equal', 'value': 'north carolina'}} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'college', 'north carolina'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; college ; north carolina }', 'tointer': 'select the rows whose college record fuzzily matches to north carolina .'}, 'height'], 'result': None, 'ind': 1, 'tostr': 'argmax { filter_eq { all_rows ; college ; north carolina } ; height }'}, 'player'], 'result': 'jeff lebo', 'ind': 2, 'tostr': 'hop { argmax { filter_eq { all_rows ; college ; north carolina } ; height } ; player }'}, 'jeff lebo'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { argmax { filter_eq { all_rows ; college ; north carolina } ; height } ; player } ; jeff lebo } = true', 'tointer': 'select the rows whose college record fuzzily matches to north carolina . select the row whose height record of these rows is maximum . the player record of this row is jeff lebo .'} | eq { hop { argmax { filter_eq { all_rows ; college ; north carolina } ; height } ; player } ; jeff lebo } = true | select the rows whose college record fuzzily matches to north carolina . select the row whose height record of these rows is maximum . the player record of this row is jeff lebo . | 4 | 4 | {'str_eq_3': 3, 'result_4': 4, 'str_hop_2': 2, 'argmax_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'college_6': 6, 'north carolina_7': 7, 'height_8': 8, 'player_9': 9, 'jeff lebo_10': 10} | {'str_eq_3': 'str_eq', 'result_4': 'true', 'str_hop_2': 'str_hop', 'argmax_1': 'argmax', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'college_6': 'college', 'north carolina_7': 'north carolina', 'height_8': 'height', 'player_9': 'player', 'jeff lebo_10': 'jeff lebo'} | {'str_eq_3': [4], 'result_4': [], 'str_hop_2': [3], 'argmax_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'college_6': [0], 'north carolina_7': [0], 'height_8': [1], 'player_9': [2], 'jeff lebo_10': [3]} | ['player', 'height', 'school', 'hometown', 'college', 'nba draft'] | [['danny ferry', '6 - 10', 'dematha catholic high school', 'hyattsville , md', 'duke', '1st round - 2nd pick of 1989 draft ( clippers )'], ['tito horford', '7 - 1', 'marian christian high school', 'houston , tx', 'lsu / miami ( fl )', '2nd round - 39th pick of 1988 draft ( bucks )'], ['tony kimbro', '6 - 8', 'seneca high school', 'louisville , ky', 'louisville', 'undrafted in 1989 nba draft'], ['jeff lebo', '6 - 3', 'carlisle high school', 'carlisle , pa', 'north carolina', 'undrafted in 1989 nba draft'], ['kevin madden', '6 - 6', 'robert e lee high school', 'staunton , va', 'north carolina', 'undrafted in 1990 nba draft']] |
édouard roger - vasselin | https://en.wikipedia.org/wiki/%C3%89douard_Roger-Vasselin | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11511365-4.html.csv | majority | édouard roger - vasselin partnered with nicolas mahut for the majority of tournaments . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'nicolas mahut', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'partner', 'nicolas mahut'], 'result': True, 'ind': 0, 'tointer': 'for the partner records of all rows , most of them fuzzily match to nicolas mahut .', 'tostr': 'most_eq { all_rows ; partner ; nicolas mahut } = true'} | most_eq { all_rows ; partner ; nicolas mahut } = true | for the partner records of all rows , most of them fuzzily match to nicolas mahut . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'partner_3': 3, 'nicolas mahut_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'partner_3': 'partner', 'nicolas mahut_4': 'nicolas mahut'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'partner_3': [0], 'nicolas mahut_4': [0]} | ['outcome', 'date', 'surface', 'partner', 'opponents', 'score'] | [['winner', '5 february 2012', 'hard ( i )', 'nicolas mahut', 'paul hanley jamie murray', '6 - 4 , 7 - 6 ( 7 - 4 )'], ['winner', '20 february 2012', 'hard ( i )', 'nicolas mahut', 'dustin brown jo - wilfried tsonga', '3 - 6 , 6 - 3 ,'], ['winner', '17 september 2012', 'hard ( i )', 'nicolas mahut', 'johan brunström frederik nielsen', '7 - 6 ( 7 - 3 ) , 6 - 4'], ['winner', '15 july 2013', 'grass', 'nicolas mahut', 'tim smyczek rhyne williams', '6 - 7 ( 4 - 7 ) , 6 - 2 ,'], ['runner - up', '20 july 2013', 'hard', 'igor sijsling', 'purav raja divij sharan', '6 - 7 ( 4 - 7 ) , 6 - 7 ( 3 - 7 )'], ['winner', '29 july 2013', 'hard', 'igor sijsling', 'colin fleming jonathan marray', '7 - 6 ( 8 - 6 ) , 6 - 3'], ['winner', '6 october 2013', 'hard', 'rohan bopanna', 'jamie murray john peers', '7 - 6 ( 7 - 5 ) , 6 - 4']] |
list of television stations in hong kong | https://en.wikipedia.org/wiki/List_of_television_stations_in_Hong_Kong | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-22274142-1.html.csv | majority | the majority of television stations in hong kong use analog and digital transmission . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'analog & digital', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'transmission', 'analog & digital'], 'result': True, 'ind': 0, 'tointer': 'for the transmission records of all rows , most of them fuzzily match to analog & digital .', 'tostr': 'most_eq { all_rows ; transmission ; analog & digital } = true'} | most_eq { all_rows ; transmission ; analog & digital } = true | for the transmission records of all rows , most of them fuzzily match to analog & digital . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'transmission_3': 3, 'analog & digital_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'transmission_3': 'transmission', 'analog & digital_4': 'analog & digital'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'transmission_3': [0], 'analog & digital_4': [0]} | ['ch -', 'channel', 'channel content', 'transmission', 'format', 'launch date', 'licence'] | [['1 ( a ) , 81 ( d )', 'tvb jade', "tvb 's main chinese ( cantonese ) channel", 'analog & digital', 'sdtv', '19 november 1967', 'tvb'], ['2 ( a ) , 11 ( d )', 'atv home', "atv 's main chinese ( cantonese ) channel", 'analog & digital', 'sdtv', '29 may 1957', 'atv'], ['3 ( a ) , 84 ( d )', 'tvb pearl', "tvb 's main english channel", 'analog & digital', 'hdtv', '19 november 1967', 'tvb'], ['4 ( a ) , 16 ( d )', 'atv world', "atv 's main english channel", 'analog & digital', 'sdtv', '29 may 1957', 'atv'], ['32 ( d )', 'rthk 1', "rthk 's main cantonese and english channel", 'digital', 'hdtv', '9 january 2013', 'rthk'], ['83 ( d ) , 522 ( m )', 'tvb inews', 'a 24 - hour news channel broadcasting in cantonese', 'digital & mobile', 'hdtv', '11 november 2008', 'tvb']] |
2004 kansas city chiefs season | https://en.wikipedia.org/wiki/2004_Kansas_City_Chiefs_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10996075-1.html.csv | count | during the 2004 kansas city chiefs season , the kansas city chiefs lost nine games . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'l', 'result': '9', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'result', 'l'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose result record fuzzily matches to l .', 'tostr': 'filter_eq { all_rows ; result ; l }'}], 'result': '9', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; result ; l } }', 'tointer': 'select the rows whose result record fuzzily matches to l . the number of such rows is 9 .'}, '9'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; result ; l } } ; 9 } = true', 'tointer': 'select the rows whose result record fuzzily matches to l . the number of such rows is 9 .'} | eq { count { filter_eq { all_rows ; result ; l } } ; 9 } = true | select the rows whose result record fuzzily matches to l . the number of such rows is 9 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'result_5': 5, 'l_6': 6, '9_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'result_5': 'result', 'l_6': 'l', '9_7': '9'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'result_5': [0], 'l_6': [0], '9_7': [2]} | ['week', 'date', 'opponent', 'result', 'attendance'] | [['1', 'september 12 , 2004', 'denver broncos', 'l 34 - 24', '75939'], ['2', 'september 19 , 2004', 'carolina panthers', 'l 28 - 17', '78136'], ['3', 'september 26 , 2004', 'houston texans', 'l 24 - 21', '77433'], ['4', 'october 4 , 2004', 'baltimore ravens', 'w 27 - 24', '69827'], ['6', 'october 17 , 2004', 'jacksonville jaguars', 'l 22 - 16', '66413'], ['7', 'october 24 , 2004', 'atlanta falcons', 'w 56 - 10', '78260'], ['8', 'october 31 , 2004', 'indianapolis colts', 'w 45 - 35', '78312'], ['9', 'november 7 , 2004', 'tampa bay buccaneers', 'l 34 - 31', '65495'], ['10', 'november 14 , 2004', 'new orleans saints', 'l 27 - 20', '64900'], ['11', 'november 22 , 2004', 'new england patriots', 'l 27 - 19', '78431'], ['12', 'november 28 , 2004', 'san diego chargers', 'l 34 - 31', '77447'], ['13', 'december 5 , 2004', 'oakland raiders', 'w 34 - 27', '51292'], ['14', 'december 13 , 2004', 'tennessee titans', 'w 49 - 38', '68932'], ['15', 'december 19 , 2004', 'denver broncos', 'w 45 - 17', '77702'], ['16', 'december 25 , 2004', 'oakland raiders', 'w 31 - 30', '77289'], ['17', 'january 2 , 2005', 'san diego chargers', 'l 24 - 17', '64920']] |
saturn aura | https://en.wikipedia.org/wiki/Saturn_Aura | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1373768-1.html.csv | unique | the xe ( 2007-08 ) is the only saturn aura engine that does not have a 2.4 liter engine . | {'scope': 'all', 'row': '4', 'col': '2', 'col_other': '1', 'criterion': 'not_equal', 'value': '2.4', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_not_eq', 'args': ['all_rows', 'engine', '2.4'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose engine record is not equal to 2.4 .', 'tostr': 'filter_not_eq { all_rows ; engine ; 2.4 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_not_eq { all_rows ; engine ; 2.4 } }', 'tointer': 'select the rows whose engine record is not equal to 2.4 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_not_eq', 'args': ['all_rows', 'engine', '2.4'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose engine record is not equal to 2.4 .', 'tostr': 'filter_not_eq { all_rows ; engine ; 2.4 }'}, 'trim'], 'result': 'xe ( 2007 - 08 )', 'ind': 2, 'tostr': 'hop { filter_not_eq { all_rows ; engine ; 2.4 } ; trim }'}, 'xe ( 2007 - 08 )'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_not_eq { all_rows ; engine ; 2.4 } ; trim } ; xe ( 2007 - 08 ) }', 'tointer': 'the trim record of this unqiue row is xe ( 2007 - 08 ) .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_not_eq { all_rows ; engine ; 2.4 } } ; eq { hop { filter_not_eq { all_rows ; engine ; 2.4 } ; trim } ; xe ( 2007 - 08 ) } } = true', 'tointer': 'select the rows whose engine record is not equal to 2.4 . there is only one such row in the table . the trim record of this unqiue row is xe ( 2007 - 08 ) .'} | and { only { filter_not_eq { all_rows ; engine ; 2.4 } } ; eq { hop { filter_not_eq { all_rows ; engine ; 2.4 } ; trim } ; xe ( 2007 - 08 ) } } = true | select the rows whose engine record is not equal to 2.4 . there is only one such row in the table . the trim record of this unqiue row is xe ( 2007 - 08 ) . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_not_eq_0': 0, 'all_rows_6': 6, 'engine_7': 7, '2.4_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'trim_9': 9, 'xe (2007 - 08)_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_not_eq_0': 'filter_not_eq', 'all_rows_6': 'all_rows', 'engine_7': 'engine', '2.4_8': '2.4', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'trim_9': 'trim', 'xe (2007 - 08)_10': 'xe ( 2007 - 08 )'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_not_eq_0': [1, 2], 'all_rows_6': [0], 'engine_7': [0], '2.4_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'trim_9': [2], 'xe (2007 - 08)_10': [3]} | ['trim', 'engine', 'displacement', 'power', 'torque', 'transmission', 'fuel mileage ( latest epa mpg - us )'] | [['green line', '2.4 l lat i4 ( bas hybrid )', 'cc ( cuin )', '164hp ( 124 kw )', 'n / a', '4 - speed 4t45 - e', '26 city , 34 hwy , 29 comb'], ['xe ( 2008 )', '2.4 l le5 i4', 'cc ( cuin )', '-', 'n / a', '4 - speed 4t45 - e', '22 city , 30 hwy , 25 comb'], ['xe ( 2009 )', '2.4 l le5 i4', 'cc ( cuin )', '-', 'n / a', '6 - speed 6t40', '22 city , 33 hwy , 26 comb'], ['xe ( 2007 - 08 )', '3.5 l lz4 v6', 'cc ( cuin )', '219hp ( 162 kw )', 'n / a', '4 - speed 4t45 - e', '18 city , 29 hwy , 22 comb'], ['xr ( 2009 )', '2.4 l le5 i4', 'cc ( cuin )', '-', 'n / a', '6 - speed 6t40', '22 city , 33 hwy , 26 comb']] |
kuomintang | https://en.wikipedia.org/wiki/Kuomintang | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16903-2.html.csv | unique | in the chinese elections , the one unique year when the kuomintang party got less than 3000000 votes was 2001 . | {'scope': 'all', 'row': '4', 'col': '2', 'col_other': '1', 'criterion': 'less_than', 'value': '3000000', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'total votes', '3000000'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose total votes record is less than 3000000 .', 'tostr': 'filter_less { all_rows ; total votes ; 3000000 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_less { all_rows ; total votes ; 3000000 } }', 'tointer': 'select the rows whose total votes record is less than 3000000 . there is only one such row in the table .'}, {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'total votes', '3000000'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose total votes record is less than 3000000 .', 'tostr': 'filter_less { all_rows ; total votes ; 3000000 }'}, 'election'], 'result': '2001', 'ind': 2, 'tostr': 'hop { filter_less { all_rows ; total votes ; 3000000 } ; election }'}, '2001'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_less { all_rows ; total votes ; 3000000 } ; election } ; 2001 }', 'tointer': 'the election record of this unqiue row is 2001 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_less { all_rows ; total votes ; 3000000 } } ; eq { hop { filter_less { all_rows ; total votes ; 3000000 } ; election } ; 2001 } } = true', 'tointer': 'select the rows whose total votes record is less than 3000000 . there is only one such row in the table . the election record of this unqiue row is 2001 .'} | and { only { filter_less { all_rows ; total votes ; 3000000 } } ; eq { hop { filter_less { all_rows ; total votes ; 3000000 } ; election } ; 2001 } } = true | select the rows whose total votes record is less than 3000000 . there is only one such row in the table . the election record of this unqiue row is 2001 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_less_0': 0, 'all_rows_6': 6, 'total votes_7': 7, '3000000_8': 8, 'eq_3': 3, 'num_hop_2': 2, 'election_9': 9, '2001_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_less_0': 'filter_less', 'all_rows_6': 'all_rows', 'total votes_7': 'total votes', '3000000_8': '3000000', 'eq_3': 'eq', 'num_hop_2': 'num_hop', 'election_9': 'election', '2001_10': '2001'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_less_0': [1, 2], 'all_rows_6': [0], 'total votes_7': [0], '3000000_8': [0], 'eq_3': [4], 'num_hop_2': [3], 'election_9': [2], '2001_10': [3]} | ['election', 'total votes', 'share of votes', 'outcome of election', 'election leader'] | [['1992', '5030725', '53.0 %', '1 seats , government', 'lee teng - hui'], ['1995', '4349089', '46.1 %', '10 seats , government', 'lee teng - hui'], ['1998', '4659679', '46.4 %', '38 seats , government', 'lee teng - hui'], ['2001', '2949371', '31.3 %', '46 seats , opposition coalition ( pan - blue )', 'lien chan'], ['2004', '3190081', '34.9 %', '11 seats , opposition coalition ( pan - blue )', 'lien chan'], ['2008', '5291512', '53.5 %', '2 seats , opposition coalition ( pan - blue )', 'wu po - hsiung'], ['2012', '5863379', '44.5 %', '17 seats , government ( pan - blue )', 'ma ying - jeou']] |
lithuania davis cup team | https://en.wikipedia.org/wiki/Lithuania_Davis_Cup_team | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-10295819-1.html.csv | ordinal | dovydas sakinis had the 2nd highest ties played , out of all of the players . | {'row': '5', 'col': '5', 'order': '2', 'col_other': '1', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'ties played', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; ties played ; 2 }'}, 'player'], 'result': 'dovydas šakinis', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; ties played ; 2 } ; player }'}, 'dovydas šakinis'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; ties played ; 2 } ; player } ; dovydas šakinis } = true', 'tointer': 'select the row whose ties played record of all rows is 2nd maximum . the player record of this row is dovydas šakinis .'} | eq { hop { nth_argmax { all_rows ; ties played ; 2 } ; player } ; dovydas šakinis } = true | select the row whose ties played record of all rows is 2nd maximum . the player record of this row is dovydas šakinis . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'ties played_5': 5, '2_6': 6, 'player_7': 7, 'dovydas šakinis_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', 'ties played_5': 'ties played', '2_6': '2', 'player_7': 'player', 'dovydas šakinis_8': 'dovydas šakinis'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'ties played_5': [0], '2_6': [0], 'player_7': [1], 'dovydas šakinis_8': [2]} | ['player', 'current singles ranking', 'current doubles ranking', 'first year played', 'ties played', 'total w - l', 'singles w - l', 'doubles w - l'] | [['ričardas berankis', '68', '515', '2007', '13', '17 - 9', '14 - 5', '3 - 4'], ['mantas bugailiškis', 'n / a', 'n / a', '2013', '1', '0 - 1', '0 - 0', '0 - 1'], ['laurynas grigelis', '439', '414', '2008', '9', '7 - 9', '4 - 7', '3 - 2'], ['lukas mugevičius', 'n / a', '1513', '2010', '6', '3 - 7', '2 - 4', '1 - 3'], ['dovydas šakinis', '1581', 'n / a', '2009', '10', '4 - 8', '3 - 5', '1 - 3']] |
2004 - 05 toronto raptors season | https://en.wikipedia.org/wiki/2004%E2%80%9305_Toronto_Raptors_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15872814-8.html.csv | majority | jalen rose was the high point scorer in most of the raptors april 2005 games . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'jalen rose', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'high points', 'jalen rose'], 'result': True, 'ind': 0, 'tointer': 'for the high points records of all rows , most of them fuzzily match to jalen rose .', 'tostr': 'most_eq { all_rows ; high points ; jalen rose } = true'} | most_eq { all_rows ; high points ; jalen rose } = true | for the high points records of all rows , most of them fuzzily match to jalen rose . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'high points_3': 3, 'jalen rose_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'high points_3': 'high points', 'jalen rose_4': 'jalen rose'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'high points_3': [0], 'jalen rose_4': [0]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record'] | [['72', 'april 1', 'charlotte', 'w 119 - 107 ( ot )', 'chris bosh ( 27 )', 'donyell marshall ( 12 )', 'milt palacio , morris peterson , jalen rose ( 4 )', 'charlotte coliseum 13550', '30 - 42'], ['73', 'april 3', 'detroit', 'l 103 - 113 ( ot )', 'morris peterson , jalen rose ( 22 )', 'chris bosh ( 9 )', 'jalen rose ( 5 )', 'air canada centre 19800', '30 - 43'], ['74', 'april 6', 'memphis', 'l 74 - 104 ( ot )', 'jalen rose ( 19 )', 'chris bosh ( 10 )', 'matt bonner , jalen rose ( 3 )', 'air canada centre 14964', '30 - 44'], ['75', 'april 8', 'atlanta', 'w 109 - 101 ( ot )', 'jalen rose ( 30 )', 'morris peterson ( 14 )', 'rafer alston ( 8 )', 'air canada centre 14352', '31 - 44'], ['76', 'april 9', 'chicago', 'l 97 - 110 ( ot )', 'jalen rose ( 19 )', 'chris bosh ( 9 )', 'rafer alston ( 9 )', 'united center 22281', '31 - 45'], ['77', 'april 11', 'indiana', 'l 90 - 94 ( ot )', 'jalen rose ( 26 )', 'chris bosh ( 13 )', 'rafer alston ( 9 )', 'air canada centre 15104', '31 - 46'], ['78', 'april 12', 'new york', 'w 105 - 93 ( ot )', 'chris bosh ( 29 )', 'rafer alston ( 9 )', 'rafer alston ( 7 )', 'madison square garden 18907', '32 - 46'], ['79', 'april 15', 'new jersey', 'l 90 - 101 ( ot )', 'jalen rose ( 20 )', 'morris peterson ( 8 )', 'rafer alston ( 7 )', 'air canada centre 19800', '32 - 47'], ['80', 'april 17', 'boston', 'l 98 - 103 ( ot )', 'jalen rose ( 31 )', 'chris bosh , pape sow ( 7 )', 'rafer alston ( 6 )', 'air canada centre 18797', '32 - 48'], ['81', 'april 19', 'milwaukee', 'w 127 - 109 ( ot )', 'jalen rose ( 29 )', 'pape sow ( 9 )', 'omar cook ( 10 )', 'bradley center 13947', '33 - 48'], ['82', 'april 20', 'cleveland', 'l 95 - 104 ( ot )', 'jalen rose ( 25 )', 'morris peterson ( 9 )', 'omar cook ( 9 )', 'air canada centre 19800', '33 - 49']] |
1989 masters tournament | https://en.wikipedia.org/wiki/1989_Masters_Tournament | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16514242-1.html.csv | unique | seve ballesteros was the only player to represent spain . | {'scope': 'all', 'row': '2', 'col': '2', 'col_other': '1', 'criterion': 'equal', 'value': 'spain', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'spain'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose country record fuzzily matches to spain .', 'tostr': 'filter_eq { all_rows ; country ; spain }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; country ; spain } }', 'tointer': 'select the rows whose country record fuzzily matches to spain . 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', 'spain'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose country record fuzzily matches to spain .', 'tostr': 'filter_eq { all_rows ; country ; spain }'}, 'player'], 'result': 'seve ballesteros', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; country ; spain } ; player }'}, 'seve ballesteros'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; country ; spain } ; player } ; seve ballesteros }', 'tointer': 'the player record of this unqiue row is seve ballesteros .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; country ; spain } } ; eq { hop { filter_eq { all_rows ; country ; spain } ; player } ; seve ballesteros } } = true', 'tointer': 'select the rows whose country record fuzzily matches to spain . there is only one such row in the table . the player record of this unqiue row is seve ballesteros .'} | and { only { filter_eq { all_rows ; country ; spain } } ; eq { hop { filter_eq { all_rows ; country ; spain } ; player } ; seve ballesteros } } = true | select the rows whose country record fuzzily matches to spain . there is only one such row in the table . the player record of this unqiue row is seve ballesteros . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'country_7': 7, 'spain_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'player_9': 9, 'seve ballesteros_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'country_7': 'country', 'spain_8': 'spain', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'player_9': 'player', 'seve ballesteros_10': 'seve ballesteros'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'country_7': [0], 'spain_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'player_9': [2], 'seve ballesteros_10': [3]} | ['player', 'country', 'year ( s ) won', 'total', 'to par', 'finish'] | [['ben crenshaw', 'united states', '1984', '284', '- 4', 't3'], ['seve ballesteros', 'spain', '1980 , 1983', '285', '- 3', 't5'], ['tom watson', 'united states', '1977 , 1981', '290', '+ 2', 't14'], ['jack nicklaus', 'united states', '1963 , 1965 , 1966 , 1984 , 1975 , 1986', '291', '+ 3', '18'], ['bernhard langer', 'west germany', '1985', '293', '+ 5', 't26'], ['larry mize', 'united states', '1987', '293', '+ 5', 't26'], ['fuzzy zoeller', 'united states', '1979', '293', '+ 5', 't26'], ['tommy aaron', 'united states', '1973', '298', '+ 10', 't38'], ['charles coody', 'united states', '1971', '298', '+ 10', 't38'], ['raymond floyd', 'united states', '1976', '298', '+ 10', 't38'], ['george archer', 'united states', '1969', '298', '+ 12', 't43']] |
list of 8 out of 10 cats episodes | https://en.wikipedia.org/wiki/List_of_8_Out_of_10_Cats_episodes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-23292220-3.html.csv | superlative | for episodes of cats , the episode with the most recent first broadcast date was episode 3x08 . | {'scope': 'all', 'col_superlative': '2', 'row_superlative': '8', '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', 'first broadcast'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; first broadcast }'}, 'episode'], 'result': '3x08', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; first broadcast } ; episode }'}, '3x08'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; first broadcast } ; episode } ; 3x08 } = true', 'tointer': 'select the row whose first broadcast record of all rows is maximum . the episode record of this row is 3x08 .'} | eq { hop { argmax { all_rows ; first broadcast } ; episode } ; 3x08 } = true | select the row whose first broadcast record of all rows is maximum . the episode record of this row is 3x08 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'first broadcast_5': 5, 'episode_6': 6, '3x08_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'first broadcast_5': 'first broadcast', 'episode_6': 'episode', '3x08_7': '3x08'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'first broadcast_5': [0], 'episode_6': [1], '3x08_7': [2]} | ['episode', 'first broadcast', 'seans team', 'daves team', 'scores'] | [['3x01', '26 may 2006', 'david baddiel and ruth badger', 'alan carr and ulrika jonsson', '6 - 9'], ['3x02', '2 june 2006', 'debra stephenson and david walliams', 'frankie boyle and bez', '5 - 7'], ['3x03', '9 june 2006', 'peter serafinowicz and johnny vegas', 'reginald d hunter and jayne middlemiss', '4 - 8'], ['3x04', '16 june 2006', 'edith bowman and julian clary', 'dave johns and sally lindsay', '8 - 4'], ['3x05', '23 june 2006', 'krishnan guru - murthy and vic reeves', 'david walliams and louis walsh', '3 - 6'], ['3x06', '30 june 2006', 'germaine greer and phill jupitus', 'fiona allen and jason manford', '6 - 7'], ['3x07', '7 july 2006', 'emo philips and alex zane', 'trisha goddard and justin moorhouse', '3 - 6'], ['3x08', '14 july 2006', 'eamonn holmes and vic reeves', 'joan rivers and holly willoughby', '8 - 4']] |
intel core | https://en.wikipedia.org/wiki/Intel_Core | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-24538587-13.html.csv | count | 2 intel core central processing unit models have a core count of 6 . | {'scope': 'all', 'criterion': 'equal', 'value': '6', 'result': '2', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'cores', '6'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose cores record is equal to 6 .', 'tostr': 'filter_eq { all_rows ; cores ; 6 }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; cores ; 6 } }', 'tointer': 'select the rows whose cores record is equal to 6 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; cores ; 6 } } ; 2 } = true', 'tointer': 'select the rows whose cores record is equal to 6 . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; cores ; 6 } } ; 2 } = true | select the rows whose cores record is equal to 6 . the number of such rows is 2 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_eq_0': 0, 'all_rows_4': 4, 'cores_5': 5, '6_6': 6, '2_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'cores_5': 'cores', '6_6': '6', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'cores_5': [0], '6_6': [0], '2_7': [2]} | ['codename ( main article )', 'brand name ( list )', 'cores', 'l3 cache', 'socket', 'tdp', 'process', 'i / o bus', 'release date'] | [['ivy bridge ( desktop )', 'core i7 - 37xx , i7 - 37xxk', '4', '8 mb', 'lga 1155', '77 w', '22 nm', 'direct media interface , integrated gpu', 'april 2012'], ['ivy bridge ( desktop )', 'core i7 - 37xxs', '4', '8 mb', 'lga 1155', '65 w', '22 nm', 'direct media interface , integrated gpu', 'april 2012'], ['ivy bridge ( desktop )', 'core i7 - 37xxt', '4', '8 mb', 'lga 1155', '45 w', '22 nm', 'direct media interface , integrated gpu', 'april 2012'], ['sandy bridge - e ( desktop )', 'core i7 - 39xxx', '6', '15 mb', 'lga 2011', '130 w', '32 nm', 'direct media interface', 'november 2011'], ['sandy bridge - e ( desktop )', 'core i7 - 39xxk', '6', '12 mb', 'lga 2011', '130 w', '32 nm', 'direct media interface', 'november 2011'], ['sandy bridge - e ( desktop )', 'core i7 - 38xx', '4', '10 mb', 'lga 2011', '130 w', '32 nm', 'direct media interface', 'november 2011'], ['sandy bridge ( desktop )', 'core i7 - 2xxxk , i7 - 2xxx', '4', '8 mb', 'lga 1155', '95 w', '32 nm', 'direct media interface , integrated gpu', 'january 2011'], ['sandy bridge ( desktop )', 'core i7 - 2xxxs', '4', '8 mb', 'lga 1155', '65 w', '32 nm', 'direct media interface , integrated gpu', 'january 2011'], ['ivy bridge ( mobile )', 'core i7 - 3xx9y', '2', '4 mb', 'rpga - 988b bga - 1023', '13 w', '22 nm', 'direct media interface , integrated gpu', 'january 2013'], ['ivy bridge ( mobile )', 'core i7 - 3xx7u , i7 - 3xx7ue', '2', '4 mb', 'rpga - 988b bga - 1023', '17 w', '22 nm', 'direct media interface , integrated gpu', 'april 2012'], ['ivy bridge ( mobile )', 'core i7 - 3xxxle', '2', '4 mb', 'rpga - 988b bga - 1023', '25 w', '22 nm', 'direct media interface , integrated gpu', 'april 2012'], ['ivy bridge ( mobile )', 'core i7 - 3xxxm', '2', '4 mb', 'rpga - 988b bga - 1023', '35 w', '22 nm', 'direct media interface , integrated gpu', 'april 2012'], ['ivy bridge ( mobile )', 'core i7 - 3xx2qm , i7 - 3xx2qe', '4', '6 mb', 'rpga - 988b bga - 1023', '35 w', '22 nm', 'direct media interface , integrated gpu', 'april 2012'], ['ivy bridge ( mobile )', 'core i7 - 38xxqm', '4', '8 mb', 'rpga - 988b bga - 1023', '45 w', '22 nm', 'direct media interface , integrated gpu', 'april 2012'], ['ivy bridge ( mobile )', 'core i7 - 3xxxxm', '4', '8 mb', 'rpga - 988b bga - 1023', '55 w', '22 nm', 'direct media interface , integrated gpu', 'april 2012'], ['sandy bridge ( mobile )', 'core i7 - 2xxxxm', '4', '8 mb', 'rpga - 988b bga - 1023', '55 w', '32 nm', 'direct media interface , integrated gpu', 'january 2011'], ['sandy bridge ( mobile )', 'core i7 - 28xxqm', '4', '8 mb', 'rpga - 988b bga - 1023', '45 w', '32 nm', 'direct media interface , integrated gpu', 'january 2011'], ['sandy bridge ( mobile )', 'core i7 - 2xxxqe , i7 - 26xxqm , i7 - 27xxqm', '4', '6 mb', 'rpga - 988b bga - 1023', '45 w', '32 nm', 'direct media interface , integrated gpu', 'january 2011'], ['sandy bridge ( mobile )', 'core i7 - 2xx0 m', '2', '4 mb', 'rpga - 988b bga - 1023', '35 w', '32 nm', 'direct media interface , integrated gpu', 'february 2011'], ['sandy bridge ( mobile )', 'core i7 - 2xx9 m', '2', '4 mb', 'bga - 1023', '25 w', '32 nm', 'direct media interface , integrated gpu', 'february 2011']] |
leeds united a.f.c. - manchester united f.c. rivalry | https://en.wikipedia.org/wiki/Leeds_United_A.F.C.%E2%80%93Manchester_United_F.C._rivalry | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15651485-2.html.csv | majority | the game on february 21 , 2004 was the only match between leeds united and manchester united that resulted in a draw . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': '1-1', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'score', '1-1'], 'result': True, 'ind': 0, 'tointer': 'for the score records of all rows , most of them fuzzily match to 1-1 .', 'tostr': 'most_eq { all_rows ; score ; 1-1 } = true'} | most_eq { all_rows ; score ; 1-1 } = true | for the score records of all rows , most of them fuzzily match to 1-1 . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'score_3': 3, '1-1_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'score_3': 'score', '1-1_4': '1-1'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'score_3': [0], '1-1_4': [0]} | ['date', 'home team', 'score', 'away team', 'venue', 'competition'] | [['18 october 2003', 'leeds united', '0 - 1', 'manchester united', 'elland road', 'premier league'], ['28 october 2003', 'leeds united', '2 - 3', 'manchester united', 'elland road', 'league cup'], ['21 february 2004', 'manchester united', '1 - 1', 'leeds united', 'old trafford', 'premier league'], ['3 january 2010', 'manchester united', '0 - 1', 'leeds united', 'old trafford', 'fa cup'], ['20 september 2011', 'leeds united', '0 - 3', 'manchester united', 'elland road', 'league cup']] |
1969 vfl season | https://en.wikipedia.org/wiki/1969_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10809157-6.html.csv | majority | all games of the 1969 vfl season were played on the 10th of may . | {'scope': 'all', 'col': '7', 'most_or_all': 'all', 'criterion': 'equal', 'value': '10 may 1969', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'date', '10 may 1969'], 'result': True, 'ind': 0, 'tointer': 'for the date records of all rows , all of them fuzzily match to 10 may 1969 .', 'tostr': 'all_eq { all_rows ; date ; 10 may 1969 } = true'} | all_eq { all_rows ; date ; 10 may 1969 } = true | for the date records of all rows , all of them fuzzily match to 10 may 1969 . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'date_3': 3, '10 may 1969_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'date_3': 'date', '10 may 1969_4': '10 may 1969'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'date_3': [0], '10 may 1969_4': [0]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['melbourne', '13.15 ( 93 )', 'richmond', '16.25 ( 121 )', 'mcg', '26848', '10 may 1969'], ['collingwood', '17.13 ( 115 )', 'footscray', '8.14 ( 62 )', 'victoria park', '19025', '10 may 1969'], ['south melbourne', '14.9 ( 93 )', 'st kilda', '7.14 ( 56 )', 'lake oval', '17536', '10 may 1969'], ['north melbourne', '13.9 ( 87 )', 'hawthorn', '14.12 ( 96 )', 'arden street oval', '15338', '10 may 1969'], ['fitzroy', '13.12 ( 90 )', 'essendon', '17.13 ( 115 )', 'princes park', '13028', '10 may 1969'], ['geelong', '18.16 ( 124 )', 'carlton', '13.7 ( 85 )', 'kardinia park', '32025', '10 may 1969']] |
2007 grand rapids rampage season | https://en.wikipedia.org/wiki/2007_Grand_Rapids_Rampage_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11786440-4.html.csv | aggregation | in the 2007 grand rapids rampage 's season , the average number of touchdowns is 8.27 . | {'scope': 'all', 'col': '5', 'type': 'average', 'result': '8.27', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', "td 's"], 'result': '8.27', 'ind': 0, 'tostr': "avg { all_rows ; td 's }"}, '8.27'], 'result': True, 'ind': 1, 'tostr': "round_eq { avg { all_rows ; td 's } ; 8.27 } = true", 'tointer': "the average of the td 's record of all rows is 8.27 ."} | round_eq { avg { all_rows ; td 's } ; 8.27 } = true | the average of the td 's record of all rows is 8.27 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, "td 's_4": 4, '8.27_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', "td 's_4": "td 's", '8.27_5': '8.27'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], "td 's_4": [0], '8.27_5': [1]} | ['player', 'rec', 'yards', 'avg', "td 's", 'long'] | [['cornelius bonner', '102', '1436', '14.1', '29', '49'], ['timon marshall', '102', '1134', '11.1', '27', '34'], ['jerome riley', '78', '845', '10.8', '12', '43'], ['scotty anderson', '31', '323', '10.4', '6', '33'], ['clarence coleman', '23', '253', '11', '3', '28'], ['ronney daniels', '23', '243', '10.6', '6', '30'], ['jermaine lewis', '23', '234', '10.2', '2', '30'], ['troy edwards', '27', '220', '8.1', '2', '24'], ['kenny solomon', '18', '201', '11.2', '3', '46'], ['chris ryan', '9', '70', '7.8', '1', '24'], ['winfield garnett', '1', '2', '2', '0', '2']] |
belize national football team | https://en.wikipedia.org/wiki/Belize_national_football_team | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1112597-6.html.csv | aggregation | the belize national football team scored 2 goals in the month of january 2013 . | {'scope': 'subset', 'col': '2', 'type': 'sum', 'result': '2', 'subset': {'col': '3', 'criterion': 'fuzzily_match', 'value': 'january 2013'}} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', 'january 2013'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; date ; january 2013 }', 'tointer': 'select the rows whose date record fuzzily matches to january 2013 .'}, 'result'], 'result': '2', 'ind': 1, 'tostr': 'sum { filter_eq { all_rows ; date ; january 2013 } ; result }'}, '2'], 'result': True, 'ind': 2, 'tostr': 'round_eq { sum { filter_eq { all_rows ; date ; january 2013 } ; result } ; 2 } = true', 'tointer': 'select the rows whose date record fuzzily matches to january 2013 . the sum of the result record of these rows is 2 .'} | round_eq { sum { filter_eq { all_rows ; date ; january 2013 } ; result } ; 2 } = true | select the rows whose date record fuzzily matches to january 2013 . the sum of the result record of these rows is 2 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'sum_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'date_5': 5, 'january 2013_6': 6, 'result_7': 7, '2_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', 'january 2013_6': 'january 2013', 'result_7': 'result', '2_8': '2'} | {'eq_2': [3], 'result_3': [], 'sum_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'date_5': [0], 'january 2013_6': [0], 'result_7': [1], '2_8': [2]} | ['category', 'result', 'date', 'venue', 'scorers ( belize )'] | [['cca', '0 - 1', '18 january 2013', 'estadio nacional , san josé , costa rica', 'none'], ['cca', '0 - 0', '20 january 2013', 'estadio nacional , san josé , costa rica', 'none'], ['cca', '2 - 1', '22 january 2013', 'estadio nacional , san josé , costa rica', "belize : lennen 29 ' deon mccaulay 90 + 2 '"], ['cca', '0 - 1', '25 january 2013', 'estadio nacional , san josé , costa rica', 'none'], ['cca', '0 - 1', '27 january 2013', 'estadio nacional , san josé , costa rica', 'none'], ['friendly', '0 - 0', '23 march 2013', 'ffb field , belmopan', 'none'], ['gc - gs', '1 - 6', '9 july 2013', 'jeld - wen field , portland , or', "belize : ian gaynair 40 '"], ['gc - gs', '0 - 1', '13 july 2013', 'rio tinto stadium , salt lake city , ut', 'none'], ['gc - gs', '0 - 4', '16 july 2013', 'rentschler field , hartford , ct', 'none']] |
austrian legislative election , 2008 | https://en.wikipedia.org/wiki/Austrian_legislative_election%2C_2008 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18337810-1.html.csv | aggregation | the average percentage of votes received by the grune party by austrian states in 2008 was 10.58 % . | {'scope': 'all', 'col': '2', 'type': 'average', 'result': '10.58 %', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'grüne'], 'result': '10.58 %', 'ind': 0, 'tostr': 'avg { all_rows ; grüne }'}, '10.58 %'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; grüne } ; 10.58 % } = true', 'tointer': 'the average of the grüne record of all rows is 10.58 % .'} | round_eq { avg { all_rows ; grüne } ; 10.58 % } = true | the average of the grüne record of all rows is 10.58 % . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'grüne_4': 4, '10.58%_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'grüne_4': 'grüne', '10.58%_5': '10.58 %'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'grüne_4': [0], '10.58%_5': [1]} | ['state', 'grüne', 'fritz', 'rettö', 'linke', 'stark'] | [['burgenland', '5.7 %', '1.3 %', '0.5 %', '0.1 %', '-'], ['carinthia', '6.9 %', '0.9 %', '0.7 %', '-', '0.1 %'], ['lower austria', '8.1 %', '1.1 %', '0.8 %', '-', '-'], ['salzburg', '11.8 %', '1.6 %', '0.8 %', '0.1 %', '-'], ['styria', '8.5 %', '1.4 %', '0.7 %', '-', '-'], ['tyrol', '11.1 %', '8.7 %', '0.6 %', '0.1 %', '-'], ['upper austria', '9.9 %', '1.0 %', '0.9 %', '0.0 %', '-'], ['vienna', '16.0 %', '0.8 %', '0.6 %', '0.1 %', '-'], ['vorarlberg', '17.2 %', '3.4 %', '0.4 %', '-', '-']] |
sri lanka at the commonwealth games | https://en.wikipedia.org/wiki/Sri_Lanka_at_the_Commonwealth_Games | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18916531-3.html.csv | superlative | barney henricus is the oldest medal winner for sri lanka at the commonwealth games , winning his medal in 1938 . | {'scope': 'all', 'col_superlative': '3', 'row_superlative': '1', 'value_mentioned': 'yes', 'max_or_min': 'min', 'other_col': '2', 'subset': None} | {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'min', 'args': ['all_rows', 'games'], 'result': '1938 sydney', 'ind': 0, 'tostr': 'min { all_rows ; games }', 'tointer': 'the minimum games record of all rows is 1938 sydney .'}, '1938 sydney'], 'result': True, 'ind': 1, 'tostr': 'eq { min { all_rows ; games } ; 1938 sydney }', 'tointer': 'the minimum games record of all rows is 1938 sydney .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmin', 'args': ['all_rows', 'games'], 'result': None, 'ind': 2, 'tostr': 'argmin { all_rows ; games }'}, 'name'], 'result': 'barney henricus', 'ind': 3, 'tostr': 'hop { argmin { all_rows ; games } ; name }'}, 'barney henricus'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { argmin { all_rows ; games } ; name } ; barney henricus }', 'tointer': 'the name record of the row with superlative games record is barney henricus .'}], 'result': True, 'ind': 5, 'tostr': 'and { eq { min { all_rows ; games } ; 1938 sydney } ; eq { hop { argmin { all_rows ; games } ; name } ; barney henricus } } = true', 'tointer': 'the minimum games record of all rows is 1938 sydney . the name record of the row with superlative games record is barney henricus .'} | and { eq { min { all_rows ; games } ; 1938 sydney } ; eq { hop { argmin { all_rows ; games } ; name } ; barney henricus } } = true | the minimum games record of all rows is 1938 sydney . the name record of the row with superlative games record is barney henricus . | 6 | 6 | {'and_5': 5, 'result_6': 6, 'eq_1': 1, 'min_0': 0, 'all_rows_7': 7, 'games_8': 8, '1938 sydney_9': 9, 'str_eq_4': 4, 'str_hop_3': 3, 'argmin_2': 2, 'all_rows_10': 10, 'games_11': 11, 'name_12': 12, 'barney henricus_13': 13} | {'and_5': 'and', 'result_6': 'true', 'eq_1': 'eq', 'min_0': 'min', 'all_rows_7': 'all_rows', 'games_8': 'games', '1938 sydney_9': '1938 sydney', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'argmin_2': 'argmin', 'all_rows_10': 'all_rows', 'games_11': 'games', 'name_12': 'name', 'barney henricus_13': 'barney henricus'} | {'and_5': [6], 'result_6': [], 'eq_1': [5], 'min_0': [1], 'all_rows_7': [0], 'games_8': [0], '1938 sydney_9': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'argmin_2': [3], 'all_rows_10': [2], 'games_11': [2], 'name_12': [3], 'barney henricus_13': [4]} | ['medal', 'name', 'games', 'sport', 'event'] | [['gold', 'barney henricus', '1938 sydney', 'boxing', 'featherweight ( 57 kg )'], ['gold', 'duncan white', '1950 auckland', 'athletics', "men 's 440 yards hurdles"], ['gold', 'pushpamali ramanayake malee wickremasinghe', '1994 victoria', 'shooting', "women 's air rifle - pairs"], ['gold', 'chinthana vidanage', '2006 melbourne', 'weightlifting', "men 's 62 kg"], ['silver', 'k edwin', '1950 auckland', 'boxing', 'flyweight'], ['silver', 'albert perera', '1950 auckland', 'boxing', 'bantamweight'], ['silver', 'dodangoda chandrasiri lakshman rajasinghe', '1994 victoria', 'shooting', "men 's small bore rifle , prone - pairs"], ['silver', 'malee wickremasinghe', '1994 victoria', 'shooting', "women 's air rifle"], ['silver', 'sriyani kulawansha', '1998 kuala lumpur', 'athletics', "women 's 100 m hurdles"], ['silver', 'chinthana vidanage', '2010 delhi', 'weightlifting', "men 's 69 kg"], ['bronze', 'alex obeyesekera', '1950 auckland', 'boxing', 'welterweight'], ['bronze', 'sugath thilakaratne', '1998 kuala lumpur', 'athletics', "men 's 400 m"], ['bronze', 'sudesh peiris', '2010 deilh', 'weightlifting', "men 's 62 kg"]] |
dom events | https://en.wikipedia.org/wiki/DOM_events | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1507852-1.html.csv | majority | most of the dom event categories were not cancellable . | {'scope': 'all', 'col': '6', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': 'no', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'cancelable', 'no'], 'result': True, 'ind': 0, 'tointer': 'for the cancelable records of all rows , most of them fuzzily match to no .', 'tostr': 'most_eq { all_rows ; cancelable ; no } = true'} | most_eq { all_rows ; cancelable ; no } = true | for the cancelable records of all rows , most of them fuzzily match to no . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'cancelable_3': 3, 'no_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'cancelable_3': 'cancelable', 'no_4': 'no'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'cancelable_3': [0], 'no_4': [0]} | ['category', 'type', 'attribute', 'description', 'bubbles', 'cancelable'] | [['mouse', 'dragstart', 'ondragstart', 'fired on an element when a drag is started', 'yes', 'yes'], ['keyboard', 'keyup', 'onkeyup', 'fires when a key on the keyboard is released', 'yes', 'yes'], ['html frame / object', 'resize', 'onresize', 'fires when a document view is resized', 'yes', 'no'], ['html frame / object', 'scroll', 'onscroll', 'fires when a document view is scrolled', 'yes', 'no'], ['html form', 'submit', 'onsubmit', 'fires when a form is submitted', 'yes', 'yes'], ['html form', 'reset', 'onreset', 'fires when a form is reset', 'yes', 'no'], ['mutation', 'domsubtreemodified', '( none )', 'fires when the subtree is modified', 'yes', 'no'], ['mutation', 'domnoderemoved', '( none )', 'fires when a node has been removed from a dom - tree', 'yes', 'no'], ['mutation', 'domnoderemovedfromdocument', '( none )', 'fires when a node is being removed from a document', 'no', 'no'], ['mutation', 'domattrmodified', '( none )', 'fires when an attribute has been modified', 'yes', 'no']] |
2008 mls superdraft | https://en.wikipedia.org/wiki/2008_MLS_SuperDraft | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15214004-4.html.csv | ordinal | in the 2008 mls superdraft , the 2nd to last player picked was spencer wadsworth . | {'row': '13', 'col': '1', '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', 'pick', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; pick ; 2 }'}, 'player'], 'result': 'spencer wadsworth', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; pick ; 2 } ; player }'}, 'spencer wadsworth'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; pick ; 2 } ; player } ; spencer wadsworth } = true', 'tointer': 'select the row whose pick record of all rows is 2nd maximum . the player record of this row is spencer wadsworth .'} | eq { hop { nth_argmax { all_rows ; pick ; 2 } ; player } ; spencer wadsworth } = true | select the row whose pick record of all rows is 2nd maximum . the player record of this row is spencer wadsworth . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'pick_5': 5, '2_6': 6, 'player_7': 7, 'spencer wadsworth_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', 'pick_5': 'pick', '2_6': '2', 'player_7': 'player', 'spencer wadsworth_8': 'spencer wadsworth'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'pick_5': [0], '2_6': [0], 'player_7': [1], 'spencer wadsworth_8': [2]} | ['pick', 'mls team', 'player', 'position', 'affiliation'] | [['43', 'chivas usa', 'keith savage', 'm', 'west florida central florida kraze'], ['44', 'new york red bulls', 'david roth', 'm', 'northwestern chicago fire premier'], ['45', 'fc dallas', 'jamil roberts', 'd', 'santa clara'], ['46', 'los angeles galaxy', 'brandon mcdonald', 'm', 'san francisco san jose frogs'], ['47', 'colorado rapids', 'brian grazier', 'm', 'saint louis'], ['48', 'columbus crew', 'steven lenhart', 'f', 'azusa pacific southern california seahorses'], ['49', 'colorado rapids', 'scott campbell', 'm', 'north carolina'], ['50', 'fc dallas', 'ben nason', 'm', 'virginia tech'], ['51', 'los angeles galaxy', 'matt hatzke', 'd', 'santa clara'], ['52', 'dc united', 'tony schmitz', 'm', 'creighton'], ['53', 'kansas city wizards', 'rauwshan mckenzie', 'd', 'michigan state chicago fire premier'], ['54', 'chicago fire', 'austin washington', 'd', 'gonzaga spokane spiders'], ['55', 'new england revolution', 'spencer wadsworth', 'f', 'duke'], ['56', 'houston dynamo', 'jeremy barlow', 'm', 'virginia']] |
1957 san francisco 49ers season | https://en.wikipedia.org/wiki/1957_San_Francisco_49ers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15123198-2.html.csv | aggregation | the san francisco 49ers 1957 season drew a total attendance of 658,531 . | {'scope': 'all', 'col': '6', 'type': 'sum', 'result': '658,531', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'attendance'], 'result': '658,531', 'ind': 0, 'tostr': 'sum { all_rows ; attendance }'}, '658,531'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; attendance } ; 658,531 } = true', 'tointer': 'the sum of the attendance record of all rows is 658,531 .'} | round_eq { sum { all_rows ; attendance } ; 658,531 } = true | the sum of the attendance record of all rows is 658,531 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'attendance_4': 4, '658,531_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'attendance_4': 'attendance', '658,531_5': '658,531'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'attendance_4': [0], '658,531_5': [1]} | ['date', 'visitor', 'score', 'home', 'record', 'attendance'] | [['september 29', 'chicago cardinals', '20 - 10', 'san francisco 49ers', '0 - 1 - 0', '35743'], ['october 6', 'los angeles rams', '23 - 20', 'san francisco 49ers', '1 - 1 - 0', '59637'], ['october 13', 'san francisco 49ers', '21 - 17', 'chicago bears', '2 - 1 - 0', '45310'], ['october 20', 'san francisco 49ers', '24 - 14', 'green bay packers', '3 - 1 - 0', '18919'], ['october 27', 'chicago bears', '21 - 17', 'san francisco 49ers', '4 - 1 - 0', '56693'], ['november 3', 'detroit lions', '35 - 31', 'san francisco 49ers', '5 - 1 - 0', '59702'], ['november 10', 'san francisco 49ers', '37 - 24', 'los angeles rams', '5 - 2 - 0', '102368'], ['november 17', 'san francisco 49ers', '31 - 10', 'detroit lions', '5 - 3 - 0', '56915'], ['november 24', 'san francisco 49ers', '27 - 21', 'baltimore colts', '5 - 4 - 0', '50073'], ['december 1', 'san francisco 49ers', '27 - 17', 'new york giants', '6 - 4 - 0', '54121'], ['december 8', 'baltimore colts', '17 - 13', 'san francisco 49ers', '7 - 4 - 0', '59950'], ['december 15', 'green bay packers', '27 - 20', 'san francisco 49ers', '8 - 4 - 0', '59100']] |
1969 - 70 segunda división | https://en.wikipedia.org/wiki/1969%E2%80%9370_Segunda_Divisi%C3%B3n | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17846691-2.html.csv | ordinal | the rcd español club recorded the 2nd highest number of wins in the 1969 - 70 segunda división season . | {'row': '3', 'col': '5', 'order': '2', 'col_other': '2', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'wins', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; wins ; 2 }'}, 'club'], 'result': 'rcd español', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; wins ; 2 } ; club }'}, 'rcd español'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; wins ; 2 } ; club } ; rcd español } = true', 'tointer': 'select the row whose wins record of all rows is 2nd maximum . the club record of this row is rcd español .'} | eq { hop { nth_argmax { all_rows ; wins ; 2 } ; club } ; rcd español } = true | select the row whose wins record of all rows is 2nd maximum . the club record of this row is rcd español . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'wins_5': 5, '2_6': 6, 'club_7': 7, 'rcd español_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'wins_5': 'wins', '2_6': '2', 'club_7': 'club', 'rcd español_8': 'rcd español'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'wins_5': [0], '2_6': [0], 'club_7': [1], 'rcd español_8': [2]} | ['position', 'club', 'played', 'points', 'wins', 'draws', 'losses', 'goals for', 'goals against', 'goal difference'] | [['1', 'real gijón', '38', '54', '23', '8', '7', '77', '32', '+ 45'], ['2', 'cd málaga', '38', '49', '17', '15', '6', '56', '33', '+ 23'], ['3', 'rcd español', '38', '49', '19', '11', '8', '64', '35', '+ 29'], ['4', 'real betis', '38', '47', '16', '15', '7', '44', '34', '+ 10'], ['5', 'córdoba cf', '38', '43', '17', '9', '12', '40', '40', '0'], ['6', 'rayo vallecano', '38', '41', '14', '13', '11', '41', '32', '+ 9'], ['7', 'real oviedo', '38', '40', '14', '12', '12', '39', '32', '+ 7'], ['8', 'cd san andrés', '38', '37', '13', '11', '14', '32', '34', '- 2'], ['9', 'onteniente cf', '38', '36', '15', '6', '17', '34', '33', '+ 1'], ['10', 'club ferrol', '38', '36', '14', '8', '16', '37', '50', '- 13'], ['11', 'cd castellón', '38', '35', '14', '7', '17', '36', '43', '- 7'], ['12', 'cf calvo sotelo', '38', '35', '12', '11', '15', '37', '43', '- 6'], ['13', 'bilbao athletic', '38', '35', '13', '9', '16', '33', '39', '- 6'], ['14', 'burgos cf', '38', '35', '12', '11', '15', '46', '54', '- 8'], ['15', 'ca osasuna', '38', '33', '12', '9', '17', '52', '57', '- 5'], ['16', 'cd ilicitano', '38', '32', '11', '10', '17', '46', '59', '- 13'], ['17', 'real valladolid', '38', '32', '12', '8', '18', '45', '59', '- 14'], ['18', 'real murcia', '38', '31', '9', '13', '16', '34', '46', '- 12'], ['19', 'ud salamanca', '38', '30', '11', '8', '19', '35', '54', '- 19'], ['20', 'cd orense', '38', '30', '11', '8', '19', '36', '55', '- 19']] |
andré amade | https://en.wikipedia.org/wiki/Andr%C3%A9_Amade | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16335823-2.html.csv | majority | the majority of andré amade 's fights took place in the country of japan . | {'scope': 'all', 'col': '6', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': 'japan', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'location', 'japan'], 'result': True, 'ind': 0, 'tointer': 'for the location records of all rows , most of them fuzzily match to japan .', 'tostr': 'most_eq { all_rows ; location ; japan } = true'} | most_eq { all_rows ; location ; japan } = true | for the location records of all rows , most of them fuzzily match to japan . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'location_3': 3, 'japan_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'location_3': 'location', 'japan_4': 'japan'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'location_3': [0], 'japan_4': [0]} | ['res', 'record', 'opponent', 'method', 'event', 'location'] | [['loss', '6 - 4 - 1', 'kj noons', 'decision ( unanimous )', 'dream13', 'yokohama , japan'], ['loss', '6 - 3 - 1', 'katsunori kikuno', 'tko ( punches )', 'dream10', 'saitama , saitama , japan'], ['loss', '6 - 2 - 1', 'eddie alvarez', 'tko ( punches )', 'dream1', 'saitama , saitama , japan'], ['loss', '6 - 1 - 1', 'gesias cavalcante', 'submission ( armbar )', "hero 's 10", 'yokohama , japan'], ['win', '6 - 0 - 1', 'caol uno', 'decision ( unanimous )', "hero 's 10", 'yokohama , japan'], ['win', '5 - 0 - 1', 'artur oumakhanov', 'tko ( punches )', "hero 's 9", 'yokohama , japan'], ['win', '4 - 0 - 1', 'hiroyuki takaya', 'tko ( broken nose )', "hero 's 8", 'nagoya , japan'], ['win', '3 - 0 - 1', 'felipe borges', 'tko', 'storm samurai 12', 'curitiba , brazil'], ['draw', '2 - 0 - 1', 'claudio mattos', 'draw', 'storm samurai 8', 'brasílial , brazil'], ['win', '2 - 0', 'sergio vieira', 'ko ( punch )', 'storm samurai 6', 'curitiba , brazil'], ['win', '1 - 0', 'leandro sousa', 'decision', 'storm samurai 4', 'curitiba , brazil']] |
tamil nadu legislative assembly | https://en.wikipedia.org/wiki/Tamil_Nadu_Legislative_Assembly | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-23512864-4.html.csv | ordinal | for the tamil nadu legislative assembly , the 2nd to last election year was when all india anna dravida munnetra kazhagam was the winning party . | {'row': '11', 'col': '1', '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', 'election year', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; election year ; 2 }'}, 'winning party / coalition'], 'result': 'all india anna dravida munnetra kazhagam', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; election year ; 2 } ; winning party / coalition }'}, 'all india anna dravida munnetra kazhagam'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; election year ; 2 } ; winning party / coalition } ; all india anna dravida munnetra kazhagam } = true', 'tointer': 'select the row whose election year record of all rows is 2nd maximum . the winning party / coalition record of this row is all india anna dravida munnetra kazhagam .'} | eq { hop { nth_argmax { all_rows ; election year ; 2 } ; winning party / coalition } ; all india anna dravida munnetra kazhagam } = true | select the row whose election year record of all rows is 2nd maximum . the winning party / coalition record of this row is all india anna dravida munnetra kazhagam . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'election year_5': 5, '2_6': 6, 'winning party / coalition_7': 7, 'all india anna dravida munnetra kazhagam_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', 'election year_5': 'election year', '2_6': '2', 'winning party / coalition_7': 'winning party / coalition', 'all india anna dravida munnetra kazhagam_8': 'all india anna dravida munnetra kazhagam'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'election year_5': [0], '2_6': [0], 'winning party / coalition_7': [1], 'all india anna dravida munnetra kazhagam_8': [2]} | ['election year', 'assembly', 'winning party / coalition', 'chief minister', 'speaker'] | [['1952', 'first assembly', 'indian national congress', 'c rajagopalachari k kamaraj', 'j shivashanmugam pillai ( 2 )'], ['1957', 'second assembly', 'indian national congress', 'k kamaraj ( 2 )', 'n gopala menon u krishna rao'], ['1962', 'third assembly', 'indian national congress', 'k kamaraj ( 3 ) m bakthavatsalam', 's chellapandian'], ['1967', 'fourth assembly', 'dravida munnetra kazhagam', 'cn annadurai m karunanidhi', 's p adithanar pulavar k govindan'], ['1977', 'sixth assembly', 'anna dravida munnetra kazhagam', 'mg ramachandran', 'munu adhi'], ['1980', 'seventh assembly', 'anna dravida munnetra kazhagam', 'mg ramachandran ( 2 )', 'munu adhi ( 2 ) k rajaram'], ['1984', 'eighth assembly', 'anna dravida munnetra kazhagam', 'mg ramachandran ( 3 ) janaki ramachandran', 'k rajaram ( 2 ) p h pandian'], ['1989', 'ninth assembly', 'dravida munnetra kazhagam', 'm karunanidhi ( 3 )', 'm tamilkudimagan'], ['1991', 'tenth assembly', 'all india anna dravida munnetra kazhagam', 'j jayalalithaa', 'r muthiah'], ['1996', 'eleventh assembly', 'dravida munnetra kazhagam', 'm karunanidhi ( 4 )', 'p t r palanivel rajan'], ['2001', 'twelfth assembly', 'all india anna dravida munnetra kazhagam', 'o panneerselvam j jayalalithaa ( 2 )', 'k kalimuthu a arunachalam'], ['2006', 'thirteenth assembly', 'dravida munnetra kazhagam ( dpa )', 'm karunanidhi ( 5 )', 'r avudaiappan']] |
media in fargo - moorhead | https://en.wikipedia.org/wiki/Media_in_Fargo%E2%80%93Moorhead | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11527967-4.html.csv | majority | all of the stations in fargo - moorhead are on am frequencies . | {'scope': 'all', 'col': '1', 'most_or_all': 'all', 'criterion': 'fuzzily_match', 'value': 'am', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'frequency', 'am'], 'result': True, 'ind': 0, 'tointer': 'for the frequency records of all rows , all of them fuzzily match to am .', 'tostr': 'all_eq { all_rows ; frequency ; am } = true'} | all_eq { all_rows ; frequency ; am } = true | for the frequency records of all rows , all of them fuzzily match to am . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'frequency_3': 3, 'am_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'frequency_3': 'frequency', 'am_4': 'am'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'frequency_3': [0], 'am_4': [0]} | ['frequency', 'call sign', 'name', 'format', 'owner'] | [['740 am', 'kvox', '740 the fan ( fox sports radio )', 'sports', 'radio fargo - moorhead'], ['790 am', 'kfgo', 'the mighty 790 kfgo', 'news / talk', 'radio fargo - moorhead'], ['890 am', 'kqlx', 'ag news 890', 'news / classic country', 'great plains integrated marketing'], ['970 am', 'wday', 'wday 970', 'news / talk', 'forum communications'], ['1100 am', 'wzfg', 'am 1100 the flag', 'talk', 'great plains integrated marketing'], ['1200 am', 'kfnw', 'praise 1200', 'christian', 'northwestern college'], ['1280 am', 'kvxr', 'real presence radio', 'catholic', 'real presence radio'], ['1660 am', 'kqwb', '1660 espn', 'sports', 'triad broadcasting']] |
2007 - 08 rugby - bundesliga | https://en.wikipedia.org/wiki/2007%E2%80%9308_Rugby-Bundesliga | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-20877272-4.html.csv | aggregation | the teams in the 2007 - 08 rugby - bundesliga had an average points against of 292 . | {'scope': 'all', 'col': '8', 'type': 'average', 'result': '292', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'points against'], 'result': '292', 'ind': 0, 'tostr': 'avg { all_rows ; points against }'}, '292'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; points against } ; 292 } = true', 'tointer': 'the average of the points against record of all rows is 292 .'} | round_eq { avg { all_rows ; points against } ; 292 } = true | the average of the points against record of all rows is 292 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'points against_4': 4, '292_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'points against_4': 'points against', '292_5': '292'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'points against_4': [0], '292_5': [1]} | ['', 'club', 'played', 'won', 'drawn', 'lost', 'points for', 'points against', 'difference', 'points'] | [['1', 'asv köln rugby', '16', '12', '2', '2', '484', '118', '366', '41'], ['2', 'stuttgarter rc', '16', '13', '1', '2', '339', '190', '149', '39'], ['3', 'tsv handschuhsheim ii', '16', '10', '0', '6', '377', '276', '101', '35'], ['4', 'sc 1880 frankfurt ii', '16', '8', '1', '7', '415', '245', '170', '33'], ['5', 'münchen rfc', '16', '7', '2', '7', '261', '282', '- 21', '31'], ['6', 'stusta münchen', '16', '5', '1', '10', '238', '405', '- 167', '27'], ['7', 'heidelberger tv', '16', '5', '0', '11', '253', '377', '- 124', '26'], ['8', 'rg heidelberg ii', '16', '5', '0', '11', '274', '440', '- 166', '25']] |
grasshopper club zürich | https://en.wikipedia.org/wiki/Grasshopper_Club_Z%C3%BCrich | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1573615-4.html.csv | ordinal | grasshopper club zürich had their second highest away goals scored in the match against slovan bratislava . | {'row': '13', 'col': '6', 'order': '2', 'col_other': '4', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'away', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; away ; 2 }'}, 'opponent'], 'result': 'slovan bratislava', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; away ; 2 } ; opponent }'}, 'slovan bratislava'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; away ; 2 } ; opponent } ; slovan bratislava } = true', 'tointer': 'select the row whose away record of all rows is 2nd maximum . the opponent record of this row is slovan bratislava .'} | eq { hop { nth_argmax { all_rows ; away ; 2 } ; opponent } ; slovan bratislava } = true | select the row whose away record of all rows is 2nd maximum . the opponent record of this row is slovan bratislava . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'away_5': 5, '2_6': 6, 'opponent_7': 7, 'slovan bratislava_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', 'away_5': 'away', '2_6': '2', 'opponent_7': 'opponent', 'slovan bratislava_8': 'slovan bratislava'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'away_5': [0], '2_6': [0], 'opponent_7': [1], 'slovan bratislava_8': [2]} | ['season', 'competition', 'round', 'opponent', 'home', 'away', 'series'] | [['1980 - 81', 'uefa cup', 'r1', 'kjøbenhavns boldklub', '3 - 1', '5 - 2', '8 - 3'], ['1980 - 81', 'uefa cup', 'r2', 'fc porto', '3 - 0 ( aet )', '0 - 2', '3 - 2'], ['1980 - 81', 'uefa cup', 'r3', 'torino', '2 - 1', '1 - 2', '3 - 3 ( p )'], ['1980 - 81', 'uefa cup', 'qf', 'fc sochaux', '0 - 0', '1 - 2', '1 - 2'], ['1981 - 82', 'uefa cup', 'r1', 'west bromwich albion', '1 - 1', '3 - 1', '4 - 1'], ['1981 - 82', 'uefa cup', 'r2', 'radnički niš', '2 - 0', '0 - 2', '2 - 2 ( p )'], ['1982 - 83', 'european cup', 'r1', 'dynamo kiev', '0 - 1', '0 - 3', '0 - 4'], ['1983 - 84', 'european cup', 'r1', 'dinamo minsk', '2 - 2', '0 - 1', '2 - 3'], ['1984 - 85', 'european cup', 'r1', 'budapest honvéd', '3 - 1', '1 - 2', '4 - 3'], ['1984 - 85', 'european cup', 'r2', 'juventus', '2 - 4', '0 - 2', '2 - 6'], ['1987 - 88', 'uefa cup', 'r1', 'dynamo moscow', '0 - 4', '0 - 1', '0 - 5'], ['1988 - 89', "cup winners ' cup", 'r1', 'eintracht frankfurt', '0 - 0', '0 - 1', '0 - 1'], ['1989 - 90', "cup winners ' cup", 'r1', 'slovan bratislava', '0 - 3', '4 - 0 ( aet )', '4 - 3'], ['1989 - 90', "cup winners ' cup", 'r2', 'torpedo moscow', '3 - 0', '1 - 1', '4 - 1'], ['1989 - 90', "cup winners ' cup", 'qf', 'sampdoria', '0 - 2', '1 - 2', '1 - 4']] |
drop tower : scream zone | https://en.wikipedia.org/wiki/Drop_Tower%3A_Scream_Zone | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12204442-1.html.csv | majority | most of the drop towers were opened prior to the year 2000 . | {'scope': 'all', 'col': '6', 'most_or_all': 'most', 'criterion': 'less_than', 'value': '2000', 'subset': None} | {'func': 'most_less', 'args': ['all_rows', 'opened', '2000'], 'result': True, 'ind': 0, 'tointer': 'for the opened records of all rows , most of them are less than 2000 .', 'tostr': 'most_less { all_rows ; opened ; 2000 } = true'} | most_less { all_rows ; opened ; 2000 } = true | for the opened records of all rows , most of them are less than 2000 . | 1 | 1 | {'most_less_0': 0, 'result_1': 1, 'all_rows_2': 2, 'opened_3': 3, '2000_4': 4} | {'most_less_0': 'most_less', 'result_1': 'true', 'all_rows_2': 'all_rows', 'opened_3': 'opened', '2000_4': '2000'} | {'most_less_0': [1], 'result_1': [], 'all_rows_2': [0], 'opened_3': [0], '2000_4': [0]} | ['park', 'tower height', 'drop height', 'speed', 'model', 'opened', 'height requirement'] | [["canada 's wonderland", '230feet', '200feet', '62 mph', 'giant drop', '1997', 'inches ( cm )'], ['carowinds', '174feet', '100feet', '56 mph', 'giant drop', 'march 1996', 'inches ( cm )'], ["california 's great america", '224feet', '207feet', '62 mph', 'giant drop', 'march 1996', 'inches ( cm )'], ['kings dominion', '305feet', '272feet', '72 mph', 'gyro drop', 'march 22 , 2003', 'inches ( cm )'], ['kings island', '315feet', '264feet', '67 mph', 'gyro drop', '1999', 'inches ( cm )']] |
1959 team speedway polish championship | https://en.wikipedia.org/wiki/1959_Team_Speedway_Polish_Championship | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17543955-3.html.csv | majority | a majority of the 1959 speedway polish championship teams had more than 10 points . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'greater_than', 'value': '10', 'subset': None} | {'func': 'most_greater', 'args': ['all_rows', 'points', '10'], 'result': True, 'ind': 0, 'tointer': 'for the points records of all rows , most of them are greater than 10 .', 'tostr': 'most_greater { all_rows ; points ; 10 } = true'} | most_greater { all_rows ; points ; 10 } = true | for the points records of all rows , most of them are greater than 10 . | 1 | 1 | {'most_greater_0': 0, 'result_1': 1, 'all_rows_2': 2, 'points_3': 3, '10_4': 4} | {'most_greater_0': 'most_greater', 'result_1': 'true', 'all_rows_2': 'all_rows', 'points_3': 'points', '10_4': '10'} | {'most_greater_0': [1], 'result_1': [], 'all_rows_2': [0], 'points_3': [0], '10_4': [0]} | ['team', 'match', 'points', 'draw', 'lost'] | [['stal rzeszów', '14', '27', '1', '0'], ['unia tarnów', '14', '18', '0', '5'], ['stal gorzów wlkp', '14', '16', '0', '6'], ['wanda nowa huta', '14', '14', '2', '6'], ['tramwajarz łódź', '14', '14', '0', '7'], ['skra warszawa', '14', '12', '0', '8'], ['ostrovia ostrów wlkp', '14', '11', '1', '8'], ['stal świętochłowice', '14', '0', '0', '14']] |
united states house of representatives elections , 1812 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1812 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2668367-14.html.csv | ordinal | nathaniel macon had the earliest first elected year among incumbents of the 1812 house of representatives elections . | {'row': '3', 'col': '4', 'order': '1', 'col_other': '2', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'first elected', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; first elected ; 1 }'}, 'incumbent'], 'result': 'nathaniel macon', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; first elected ; 1 } ; incumbent }'}, 'nathaniel macon'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; first elected ; 1 } ; incumbent } ; nathaniel macon } = true', 'tointer': 'select the row whose first elected record of all rows is 1st minimum . the incumbent record of this row is nathaniel macon .'} | eq { hop { nth_argmin { all_rows ; first elected ; 1 } ; incumbent } ; nathaniel macon } = true | select the row whose first elected record of all rows is 1st minimum . the incumbent record of this row is nathaniel macon . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'first elected_5': 5, '1_6': 6, 'incumbent_7': 7, 'nathaniel macon_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmin_0': 'nth_argmin', 'all_rows_4': 'all_rows', 'first elected_5': 'first elected', '1_6': '1', 'incumbent_7': 'incumbent', 'nathaniel macon_8': 'nathaniel macon'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'first elected_5': [0], '1_6': [0], 'incumbent_7': [1], 'nathaniel macon_8': [2]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['north carolina 2', 'willis alston', 'democratic - republican', '1798', 're - elected', 'willis alston ( dr ) 56.0 % daniel mason ( f ) 44.0 %'], ['north carolina 5', 'william r king', 'democratic - republican', '1810', 're - elected', 'william r king ( dr ) 100 %'], ['north carolina 6', 'nathaniel macon', 'democratic - republican', '1791', 're - elected', 'nathaniel macon ( dr )'], ['north carolina 9', 'none ( district created )', 'none ( district created )', 'none ( district created )', 'new seat democratic - republican gain', 'bartlett yancey ( dr ) 61.1 % james martin ( f ) 38.9 %'], ['north carolina 10', 'joseph pearson', 'federalist', '1808', 're - elected', 'joseph pearson ( f ) 54.1 % alexander gary ( dr ) 45.9 %']] |
papal conclave , 1378 | https://en.wikipedia.org/wiki/Papal_conclave%2C_1378 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18868987-1.html.csv | unique | simone borsano was the only milanese elector in the papal conclave of 1378 . | {'scope': 'all', 'row': '7', 'col': '2', 'col_other': '1', 'criterion': 'equal', 'value': 'milanese', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'nationality', 'milanese'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose nationality record fuzzily matches to milanese .', 'tostr': 'filter_eq { all_rows ; nationality ; milanese }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; nationality ; milanese } }', 'tointer': 'select the rows whose nationality record fuzzily matches to milanese . 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', 'milanese'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose nationality record fuzzily matches to milanese .', 'tostr': 'filter_eq { all_rows ; nationality ; milanese }'}, 'elector'], 'result': 'simone borsano', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; nationality ; milanese } ; elector }'}, 'simone borsano'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; nationality ; milanese } ; elector } ; simone borsano }', 'tointer': 'the elector record of this unqiue row is simone borsano .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; nationality ; milanese } } ; eq { hop { filter_eq { all_rows ; nationality ; milanese } ; elector } ; simone borsano } } = true', 'tointer': 'select the rows whose nationality record fuzzily matches to milanese . there is only one such row in the table . the elector record of this unqiue row is simone borsano .'} | and { only { filter_eq { all_rows ; nationality ; milanese } } ; eq { hop { filter_eq { all_rows ; nationality ; milanese } ; elector } ; simone borsano } } = true | select the rows whose nationality record fuzzily matches to milanese . there is only one such row in the table . the elector record of this unqiue row is simone borsano . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'nationality_7': 7, 'milanese_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'elector_9': 9, 'simone borsano_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', 'milanese_8': 'milanese', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'elector_9': 'elector', 'simone borsano_10': 'simone borsano'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'nationality_7': [0], 'milanese_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'elector_9': [2], 'simone borsano_10': [3]} | ['elector', 'nationality', 'cardinalatial order and title', 'elevated', 'elevator'] | [['pietro corsini', 'florentine', 'cardinal - bishop of porto e santa rufina', '1370 , june 7', 'urban v'], ['jean du cros', 'french', 'cardinal - bishop of palestrina', '1371 , may 30', 'gregory xi'], ["guillaume d'aigrefeuille , iuniore , osb", 'french', 'cardinal - priest of s stefano al monte celio', '1367 , may 12', 'urban v'], ['francesco tebaldeschi', 'roman', 'cardinal - priest of s sabina', '1368 , september 22', 'urban v'], ['bertrand lagier , ofm', 'french', 'cardinal - priest of s cecilia', '1371 , may 30', 'gregory xi'], ['robert de genève', 'french', 'cardinal - priest of ss xii apostoli', '1371 , may 30', 'gregory xi'], ['simone borsano', 'milanese', 'cardinal - priest of ss giovanni e paolo', '1375 , december 20', 'gregory xi'], ['hugues de montelais , le jeune', 'french', 'cardinal - priest of ss iv coronati', '1375 , december 20', 'gregory xi'], ['gui de maillesec', 'french', 'cardinal - priest of s croce in gerusalemme', '1375 , december 20', 'gregory xi'], ['pierre de sortenac', 'french', 'cardinal - priest of s lorenzo in lucina', '1375 , december 20', 'gregory xi'], ['gérard du puy , osb', 'french', 'cardinal - priest of s clemente', '1375 , december 20', 'gregory xi'], ['giacomo orsini', 'roman', 'cardinal - deacon of s giorgio in velabro', '1371 , may 30', 'gregory xi'], ['pierre flandrin', 'french', 'cardinal - deacon of s eustachio', '1371 , may 30', 'gregory xi'], ['guillaume noellet', 'french', 'cardinal - deacon of s angelo in pescheria', '1371 , may 30', 'gregory xi'], ['pierre de vergne', 'french', 'cardinal - deacon of s maria in via lata', '1371 , may 30', 'gregory xi'], ['pedro martínez de luna y gotor', 'aragonese', 'cardinal - deacon of s maria in cosmedin', '1375 , december 20', 'gregory xi']] |
list of schools in the hawke 's bay region | https://en.wikipedia.org/wiki/List_of_schools_in_the_Hawke%27s_Bay_Region | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12195931-4.html.csv | majority | most of the schools in the hawke 's bay region have a coed education . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'coed', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'gender', 'coed'], 'result': True, 'ind': 0, 'tointer': 'for the gender records of all rows , most of them fuzzily match to coed .', 'tostr': 'most_eq { all_rows ; gender ; coed } = true'} | most_eq { all_rows ; gender ; coed } = true | for the gender records of all rows , most of them fuzzily match to coed . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'gender_3': 3, 'coed_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'gender_3': 'gender', 'coed_4': 'coed'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'gender_3': [0], 'coed_4': [0]} | ['name', 'years', 'gender', 'area', 'authority', 'decile', 'roll'] | [['argyll east school', '1 - 8', 'coed', 'otane', 'state', '4', '51'], ["central hawke 's bay college", '9 - 15', 'coed', 'waipukurau', 'state', '4', '557'], ['elsthorpe school', '1 - 8', 'coed', 'elsthorpe', 'state', '9', '42'], ['flemington school', '1 - 8', 'coed', 'waipukurau', 'state', '8', '71'], ['mangaorapa school', '1 - 8', 'coed', 'porangahau', 'state', '3', '19'], ['omakere school', '1 - 8', 'coed', 'waipawa', 'state', '8', '30'], ['ongaonga school', '1 - 8', 'coed', 'ongaonga', 'state', '6', '111'], ['otane school', '1 - 8', 'coed', 'otane', 'state', '3', '43'], ['porangahau school', '1 - 8', 'coed', 'porangahau', 'state', '4', '31'], ['pukehou school', '1 - 8', 'coed', 'pukehou', 'state', '5', '108'], ['sherwood school', '1 - 8', 'coed', 'takapau', 'state', '6', '30'], ["st joseph 's school", '1 - 8', 'coed', 'waipukurau', 'state integrated', '5', '95'], ['takapau school', '1 - 8', 'coed', 'takapau', 'state', '5', '141'], ['te aute college', '9 - 15', 'boys', 'pukehou', 'state integrated', '3', '86'], ['the terrace school', '1 - 8', 'coed', 'waipukurau', 'state', '2', '214'], ['tikokino school', '1 - 8', 'coed', 'waipawa', 'state', '7', '42'], ['tkkm o takapau', '1 - 8', 'coed', 'takapau', 'state', '3', '37'], ['waipawa school', '1 - 8', 'coed', 'waipawa', 'state', '3', '139'], ['waipukurau school', '1 - 8', 'coed', 'waipukurau', 'state', '3', '243']] |
usage share of operating systems | https://en.wikipedia.org/wiki/Usage_share_of_operating_systems | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-11381701-3.html.csv | superlative | the highest share of ios use was reported by the wikimedia source in the list of usage share of operating systems . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '7', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'ios'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; ios }'}, 'source'], 'result': 'wikimedia', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; ios } ; source }'}, 'wikimedia'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; ios } ; source } ; wikimedia } = true', 'tointer': 'select the row whose ios record of all rows is maximum . the source record of this row is wikimedia .'} | eq { hop { argmax { all_rows ; ios } ; source } ; wikimedia } = true | select the row whose ios record of all rows is maximum . the source record of this row is wikimedia . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'ios_5': 5, 'source_6': 6, 'wikimedia_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'ios_5': 'ios', 'source_6': 'source', 'wikimedia_7': 'wikimedia'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'ios_5': [0], 'source_6': [1], 'wikimedia_7': [2]} | ['source', 'date', 'method', 'ios', 'android', 'blackberry', 'symbian / series 40', 'bada', 'windows', 'other'] | [['comscore reports ( us only )', 'may - 13', 'subscribers , us', '39.20 %', '52.40 %', '4.80 %', '0.40 %', 'n / a', '3.00 %', 'n / a'], ['gartner', 'may - 13', 'units sold', '18.2 %', '74.4 %', '3.0 %', '0.6 %', '0.7 %', '2.9 %', '0.3 %'], ['gartner', 'aug - 13', 'units sold', '14.2 %', '79.0 %', '2.7 %', '0.3 %', '0.4 %', '3.3 %', '0.2 %'], ['international data corporation', 'may - 13', 'units shipped', '17.3 %', '75.0 %', '2.9 %', '0.6', 'n / a', '3.2 %', '0.0 %'], ['net market share', 'july - 13', 'browsing', '58.26 %', '25.28 %', '3.23 %', '2.23 %', '0.05 %', '1.15 %', '0.19 %'], ['statcounter global stats', 'july - 13', 'browsing', '24.80 %', '38.34 %', '3.66 %', '20.76 %', '4.64 %', '1.52', '2.66'], ['wikimedia', 'mar - 13', 'browsing', '66.53 %', '25.93 %', '2.02 %', '3.03 %', '0.42 %', '1.85 %', '0.7 %']] |
the suite life on deck | https://en.wikipedia.org/wiki/The_Suite_Life_on_Deck | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15627191-3.html.csv | count | there were 7 total nominations for the suite life on deck in 2010 . | {'scope': 'subset', 'criterion': 'equal', 'value': 'the suite life on deck', 'result': '2', 'col': '4', 'subset': {'col': '1', 'criterion': 'equal', 'value': '2010'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'year', '2010'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; year ; 2010 }', 'tointer': 'select the rows whose year record is equal to 2010 .'}, 'recipient', 'the suite life on deck'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose year record is equal to 2010 . among these rows , select the rows whose recipient record fuzzily matches to the suite life on deck .', 'tostr': 'filter_eq { filter_eq { all_rows ; year ; 2010 } ; recipient ; the suite life on deck }'}], 'result': '2', 'ind': 2, 'tostr': 'count { filter_eq { filter_eq { all_rows ; year ; 2010 } ; recipient ; the suite life on deck } }', 'tointer': 'select the rows whose year record is equal to 2010 . among these rows , select the rows whose recipient record fuzzily matches to the suite life on deck . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_eq { filter_eq { all_rows ; year ; 2010 } ; recipient ; the suite life on deck } } ; 2 } = true', 'tointer': 'select the rows whose year record is equal to 2010 . among these rows , select the rows whose recipient record fuzzily matches to the suite life on deck . the number of such rows is 2 .'} | eq { count { filter_eq { filter_eq { all_rows ; year ; 2010 } ; recipient ; the suite life on deck } } ; 2 } = true | select the rows whose year record is equal to 2010 . among these rows , select the rows whose recipient record fuzzily matches to the suite life on deck . the number of such rows is 2 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_str_eq_1': 1, 'filter_eq_0': 0, 'all_rows_5': 5, 'year_6': 6, '2010_7': 7, 'recipient_8': 8, 'the suite life on deck_9': 9, '2_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_str_eq_1': 'filter_str_eq', 'filter_eq_0': 'filter_eq', 'all_rows_5': 'all_rows', 'year_6': 'year', '2010_7': '2010', 'recipient_8': 'recipient', 'the suite life on deck_9': 'the suite life on deck', '2_10': '2'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_str_eq_1': [2], 'filter_eq_0': [1], 'all_rows_5': [0], 'year_6': [0], '2010_7': [0], 'recipient_8': [1], 'the suite life on deck_9': [1], '2_10': [3]} | ['year', 'award', 'category', 'recipient', 'result'] | [['2010', 'green globe film awards', 'outstanding actors asians in hollywood', 'brenda song', 'nominated'], ['2010', "2010 kids ' choice awards", 'favorite tv show', 'the suite life on deck', 'nominated'], ['2010', "2010 kids ' choice awards", 'favorite tv actor', 'cole sprouse', 'nominated'], ['2010', "2010 kids ' choice awards", 'favorite tv actor', 'dylan sprouse', 'won'], ['2010', 'hollywood teen tv awards', 'teen pick show : comedy', 'the suite life on deck', 'nominated'], ['2010', 'hollywood teen tv awards', 'teen pick actress : comedy', 'debby ryan', 'nominated'], ['2010', 'hollywood teen tv awards', 'teen pick actor : comedy', 'dylan sprouse', 'nominated'], ['2011', "2011 kids ' choice awards", 'favorite tv show', 'the suite life on deck', 'nominated'], ['2011', "2011 kids ' choice awards", 'favorite tv actor', 'cole sprouse', 'nominated'], ['2011', "2011 kids ' choice awards", 'favorite tv actor', 'dylan sprouse', 'won'], ['2011', "2011 kids ' choice awards", 'favorite tv sidekick', 'brenda song', 'nominated'], ['2011', 'casting society of america', "best casting children 's series", 'dana gergely brandi brice', 'won']] |
2002 pba draft | https://en.wikipedia.org/wiki/2002_PBA_draft | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10810530-2.html.csv | majority | the majority of the players from the 2002 pba draft were from the philippines . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'philippines', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'country of origin', 'philippines'], 'result': True, 'ind': 0, 'tointer': 'for the country of origin records of all rows , most of them fuzzily match to philippines .', 'tostr': 'most_eq { all_rows ; country of origin ; philippines } = true'} | most_eq { all_rows ; country of origin ; philippines } = true | for the country of origin records of all rows , most of them fuzzily match to philippines . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'country of origin_3': 3, 'philippines_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'country of origin_3': 'country of origin', 'philippines_4': 'philippines'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'country of origin_3': [0], 'philippines_4': [0]} | ['pick', 'player', 'country of origin', 'pba team', 'college'] | [['1', 'yancy de ocampo', 'philippines', 'fedex express', 'st francis'], ['2', 'rafi reavis', 'united states', 'coca - cola tigers', 'coppin state'], ['3', 'omanzie rodriguez', 'philippines', 'sta lucia realtors', 'mapua'], ['4', 'chris calaguio', 'philippines', 'shell turbo chargers', 'letran'], ['5', 'homer se', 'philippines', 'red bull thunder', 'san sebastian'], ['6', 'migs noble', 'united states', 'alaska aces', 'utica'], ['7', 'eric canlas', 'philippines', 'shell turbo chargers', 'st francis'], ['8', 'ren - ren ritualo', 'philippines', 'fedex express', 'la salle - manila'], ['9', 'chester tolomia', 'philippines', 'barangay ginebra kings', 'perpetual help'], ['10', 'leo avenido', 'philippines', 'coca - cola tigers', 'far eastern']] |
patty schnyder | https://en.wikipedia.org/wiki/Patty_Schnyder | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1547798-2.html.csv | ordinal | patty schnyder 's second match was in germany in february of 1998 . | {'row': '2', 'col': '1', 'order': '2', 'col_other': '2', 'max_or_min': 'min_to_max', 'value_mentioned': 'yes', 'scope': 'all', 'subset': None} | {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'nth_min', 'args': ['all_rows', 'date', '2'], 'result': '22 february 1998', 'ind': 0, 'tostr': 'nth_min { all_rows ; date ; 2 }', 'tointer': 'the 2nd minimum date record of all rows is 22 february 1998 .'}, '22 february 1998'], 'result': True, 'ind': 1, 'tostr': 'eq { nth_min { all_rows ; date ; 2 } ; 22 february 1998 }', 'tointer': 'the 2nd minimum date record of all rows is 22 february 1998 .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'date', '2'], 'result': None, 'ind': 2, 'tostr': 'nth_argmin { all_rows ; date ; 2 }'}, 'tournament'], 'result': 'hannover , germany', 'ind': 3, 'tostr': 'hop { nth_argmin { all_rows ; date ; 2 } ; tournament }'}, 'hannover , germany'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { nth_argmin { all_rows ; date ; 2 } ; tournament } ; hannover , germany }', 'tointer': 'the tournament record of the row with 2nd minimum date record is hannover , germany .'}], 'result': True, 'ind': 5, 'tostr': 'and { eq { nth_min { all_rows ; date ; 2 } ; 22 february 1998 } ; eq { hop { nth_argmin { all_rows ; date ; 2 } ; tournament } ; hannover , germany } } = true', 'tointer': 'the 2nd minimum date record of all rows is 22 february 1998 . the tournament record of the row with 2nd minimum date record is hannover , germany .'} | and { eq { nth_min { all_rows ; date ; 2 } ; 22 february 1998 } ; eq { hop { nth_argmin { all_rows ; date ; 2 } ; tournament } ; hannover , germany } } = true | the 2nd minimum date record of all rows is 22 february 1998 . the tournament record of the row with 2nd minimum date record is hannover , germany . | 6 | 6 | {'and_5': 5, 'result_6': 6, 'eq_1': 1, 'nth_min_0': 0, 'all_rows_7': 7, 'date_8': 8, '2_9': 9, '22 february 1998_10': 10, 'str_eq_4': 4, 'str_hop_3': 3, 'nth_argmin_2': 2, 'all_rows_11': 11, 'date_12': 12, '2_13': 13, 'tournament_14': 14, 'hannover , germany_15': 15} | {'and_5': 'and', 'result_6': 'true', 'eq_1': 'eq', 'nth_min_0': 'nth_min', 'all_rows_7': 'all_rows', 'date_8': 'date', '2_9': '2', '22 february 1998_10': '22 february 1998', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'nth_argmin_2': 'nth_argmin', 'all_rows_11': 'all_rows', 'date_12': 'date', '2_13': '2', 'tournament_14': 'tournament', 'hannover , germany_15': 'hannover , germany'} | {'and_5': [6], 'result_6': [], 'eq_1': [5], 'nth_min_0': [1], 'all_rows_7': [0], 'date_8': [0], '2_9': [0], '22 february 1998_10': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'nth_argmin_2': [3], 'all_rows_11': [2], 'date_12': [2], '2_13': [2], 'tournament_14': [3], 'hannover , germany_15': [4]} | ['date', 'tournament', 'surface', 'opponent in the final', 'score'] | [['18 january 1998', 'hobart , australia', 'hard', 'dominique van roost', '6 - 3 , 6 - 2'], ['22 february 1998', 'hannover , germany', 'carpet ( i )', 'jana novotná', '6 - 0 , 3 - 6 , 7 - 5'], ['24 may 1998', 'madrid , spain', 'clay', 'dominique van roost', '3 - 6 , 6 - 4 , 6 - 0'], ['12 july 1998', 'maria lankowitz , austria', 'clay', 'gala león garcía', '6 - 2 , 4 - 6 , 6 - 3'], ['19 july 1998', 'palermo , italy', 'clay', 'barbara schett', '6 - 1 , 5 - 7 , 6 - 2'], ['10 january 1999', 'gold coast , australia', 'hard', 'mary pierce', '4 - 6 , 7 - 6 ( 5 ) , 6 - 2'], ['11 november 2001', 'pattaya city , thailand', 'hard', 'henrieta nagyová', '6 - 0 , 6 - 4'], ['20 october 2002', 'zürich , switzerland', 'carpet ( i )', 'lindsay davenport', '6 - 7 ( 5 ) , 7 - 6 ( 8 ) , 6 - 3'], ['8 january 2005', 'gold coast , australia', 'hard', 'samantha stosur', '1 - 6 , 6 - 3 , 7 - 5'], ['24 july 2005', 'cincinnati , usa', 'hard', 'akiko morigami', '6 - 4 , 6 - 0'], ['8 september 2008', 'bali , indonesia', 'hard', 'tamira paszek', '6 - 3 , 6 - 0']] |
1940 world series | https://en.wikipedia.org/wiki/1940_World_Series | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1332360-1.html.csv | count | three of the games were played at briggs stadium . | {'scope': 'all', 'criterion': 'equal', 'value': 'briggs stadium', 'result': '3', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location', 'briggs stadium'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose location record fuzzily matches to briggs stadium .', 'tostr': 'filter_eq { all_rows ; location ; briggs stadium }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; location ; briggs stadium } }', 'tointer': 'select the rows whose location record fuzzily matches to briggs stadium . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; location ; briggs stadium } } ; 3 } = true', 'tointer': 'select the rows whose location record fuzzily matches to briggs stadium . the number of such rows is 3 .'} | eq { count { filter_eq { all_rows ; location ; briggs stadium } } ; 3 } = true | select the rows whose location record fuzzily matches to briggs stadium . 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, 'location_5': 5, 'briggs stadium_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', 'location_5': 'location', 'briggs stadium_6': 'briggs stadium', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'location_5': [0], 'briggs stadium_6': [0], '3_7': [2]} | ['game', 'date', 'score', 'location', 'time', 'attendance'] | [['1', 'october 2', 'detroit tigers - 7 , cincinnati reds - 2', 'crosley field', '2:09', '31793'], ['2', 'october 3', 'detroit tigers - 3 , cincinnati reds - 5', 'crosley field', '1:54', '30640'], ['3', 'october 4', 'cincinnati reds - 4 , detroit tigers - 7', 'briggs stadium', '2:08', '52877'], ['4', 'october 5', 'cincinnati reds - 5 , detroit tigers - 2', 'briggs stadium', '2:06', '54093'], ['5', 'october 6', 'cincinnati reds - 0 , detroit tigers - 8', 'briggs stadium', '2:26', '55189'], ['6', 'october 7', 'detroit tigers - 0 , cincinnati reds - 4', 'crosley field', '2:01', '30481'], ['7', 'october 8', 'detroit tigers - 1 , cincinnati reds - 2', 'crosley field', '1:47', '26854']] |
mike van arsdale | https://en.wikipedia.org/wiki/Mike_van_Arsdale | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14344822-2.html.csv | majority | most of the fights involving mike van arsdale only lasted one round . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'equal', 'value': '1', 'subset': None} | {'func': 'most_eq', 'args': ['all_rows', 'round', '1'], 'result': True, 'ind': 0, 'tointer': 'for the round records of all rows , most of them are equal to 1 .', 'tostr': 'most_eq { all_rows ; round ; 1 } = true'} | most_eq { all_rows ; round ; 1 } = true | for the round records of all rows , most of them are equal to 1 . | 1 | 1 | {'most_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'round_3': 3, '1_4': 4} | {'most_eq_0': 'most_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'round_3': 'round', '1_4': '1'} | {'most_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'round_3': [0], '1_4': [0]} | ['res', 'record', 'opponent', 'method', 'round', 'time', 'location'] | [['loss', '8 - 5', 'matt lindland', 'submission ( guillotine choke )', '1', '3:38', 'california , united states'], ['loss', '8 - 4', 'jorge oliveira', 'submission ( triangle choke )', '1', '4:02', 'idaho , united states'], ['loss', '8 - 3', 'renato sobral', 'submission ( rear naked choke )', '1', '2:21', 'nevada , united states'], ['loss', '8 - 2', 'randy couture', 'submission ( anaconda choke )', '3', '0:52', 'nevada , united states'], ['win', '8 - 1', 'john marsh', 'decision ( unanimous )', '3', '5:00', 'nevada , united states'], ['win', '7 - 1', 'emanuel newton', 'submission ( kimura )', '1', '1:35', 'mexico'], ['win', '6 - 1', 'mario lopez', 'submission ( crucifix )', '1', '0:28', 'mexico'], ['win', '5 - 1', 'chris haseman', 'tko ( strikes )', '2', '3:10', 'nevada , united states'], ['loss', '4 - 1', 'wanderlei silva', 'ko ( punch and kick )', '1', '4:00', 'brazil'], ['win', '4 - 0', 'joe pardo', 'submission ( armlock )', '1', '11:01', 'alabama , united states'], ['win', '3 - 0', 'dario amorim', 'submission ( shoulder injury )', '1', '2:42', 'brazil'], ['win', '2 - 0', 'marcelo barbosa', 'submission ( punches )', '1', '3:36', 'brazil'], ['win', '1 - 0', 'francisco nonato', 'submission ( keylock )', '1', '5:42', 'brazil']] |
cain velasquez | https://en.wikipedia.org/wiki/Cain_Velasquez | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17440144-2.html.csv | count | for cain velasquez , when the result was a win , there were 8 times that it was in round 1 . | {'scope': 'subset', 'criterion': 'equal', 'value': '1', 'result': '8', 'col': '6', 'subset': {'col': '1', 'criterion': 'equal', 'value': 'win'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'res', 'win'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; res ; win }', 'tointer': 'select the rows whose res record fuzzily matches to win .'}, 'round', '1'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose res record fuzzily matches to win . among these rows , select the rows whose round record is equal to 1 .', 'tostr': 'filter_eq { filter_eq { all_rows ; res ; win } ; round ; 1 }'}], 'result': '8', 'ind': 2, 'tostr': 'count { filter_eq { filter_eq { all_rows ; res ; win } ; round ; 1 } }', 'tointer': 'select the rows whose res record fuzzily matches to win . among these rows , select the rows whose round record is equal to 1 . the number of such rows is 8 .'}, '8'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_eq { filter_eq { all_rows ; res ; win } ; round ; 1 } } ; 8 } = true', 'tointer': 'select the rows whose res record fuzzily matches to win . among these rows , select the rows whose round record is equal to 1 . the number of such rows is 8 .'} | eq { count { filter_eq { filter_eq { all_rows ; res ; win } ; round ; 1 } } ; 8 } = true | select the rows whose res record fuzzily matches to win . among these rows , select the rows whose round record is equal to 1 . the number of such rows is 8 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_eq_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'res_6': 6, 'win_7': 7, 'round_8': 8, '1_9': 9, '8_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_eq_1': 'filter_eq', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'res_6': 'res', 'win_7': 'win', 'round_8': 'round', '1_9': '1', '8_10': '8'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_eq_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'res_6': [0], 'win_7': [0], 'round_8': [1], '1_9': [1], '8_10': [3]} | ['res', 'record', 'opponent', 'method', 'event', 'round', 'time', 'location'] | [['win', '13 - 1', 'junior dos santos', 'tko ( slam and punch )', 'ufc 166', '5', '3:09', 'houston , texas , united states'], ['win', '12 - 1', 'antonio silva', 'tko ( punches )', 'ufc 160', '1', '1:21', 'las vegas , nevada , united states'], ['win', '11 - 1', 'junior dos santos', 'decision ( unanimous )', 'ufc 155', '5', '5:00', 'las vegas , nevada , united states'], ['win', '10 - 1', 'antonio silva', 'tko ( punches )', 'ufc 146', '1', '3:36', 'las vegas , nevada , united states'], ['loss', '9 - 1', 'junior dos santos', 'ko ( punches )', 'ufc on fox : velasquez vs dos santos', '1', '1:04', 'anaheim , california , united states'], ['win', '9 - 0', 'brock lesnar', 'tko ( punches )', 'ufc 121', '1', '4:12', 'anaheim , california , united states'], ['win', '8 - 0', 'antônio rodrigo nogueira', 'ko ( punches )', 'ufc 110', '1', '2:20', 'sydney , australia'], ['win', '7 - 0', 'ben rothwell', 'tko ( punches )', 'ufc 104', '2', '0:58', 'los angeles , california , united states'], ['win', '6 - 0', 'cheick kongo', 'decision ( unanimous )', 'ufc 99', '3', '5:00', 'cologne , germany'], ['win', '5 - 0', 'denis stojnić', 'tko ( punches )', 'ufc fight night : lauzon vs stephens', '2', '2:34', 'tampa , florida , united states'], ['win', '4 - 0', "jake o'brien", 'tko ( punches )', 'ufc : silva vs irvin', '1', '2:02', 'las vegas , nevada , united states'], ['win', '3 - 0', 'brad morris', 'tko ( punches )', 'ufc 83', '1', '2:10', 'montreal , quebec , canada'], ['win', '2 - 0', 'jeremiah constant', 'tko ( punches )', 'bodogfight : st petersburg', '1', '4:00', 'st petersburg , russia'], ['win', '1 - 0', 'jesse fujarczyk', 'tko ( punches )', 'strikeforce : tank vs buentello', '1', '1:58', 'fresno , california , united states']] |
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 | comparative | the crowd size at princes park was 1000 people more than when the venue was victoria park . | {'row_1': '5', 'row_2': '4', 'col': '6', 'col_other': '5', 'relation': 'diff', 'record_mentioned': 'no', 'diff_result': {'diff_value': '1000', 'bigger': 'row1'}} | {'func': 'eq', 'args': [{'func': 'diff', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'venue', 'princes park'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose venue record fuzzily matches to princes park .', 'tostr': 'filter_eq { all_rows ; venue ; princes park }'}, 'crowd'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; venue ; princes park } ; crowd }', 'tointer': 'select the rows whose venue record fuzzily matches to princes park . take the crowd record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'venue', 'victoria park'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose venue record fuzzily matches to victoria park .', 'tostr': 'filter_eq { all_rows ; venue ; victoria park }'}, 'crowd'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; venue ; victoria park } ; crowd }', 'tointer': 'select the rows whose venue record fuzzily matches to victoria park . take the crowd record of this row .'}], 'result': '1000', 'ind': 4, 'tostr': 'diff { hop { filter_eq { all_rows ; venue ; princes park } ; crowd } ; hop { filter_eq { all_rows ; venue ; victoria park } ; crowd } }'}, '1000'], 'result': True, 'ind': 5, 'tostr': 'eq { diff { hop { filter_eq { all_rows ; venue ; princes park } ; crowd } ; hop { filter_eq { all_rows ; venue ; victoria park } ; crowd } } ; 1000 } = true', 'tointer': 'select the rows whose venue record fuzzily matches to princes park . take the crowd record of this row . select the rows whose venue record fuzzily matches to victoria park . take the crowd record of this row . the first record is 1000 larger than the second record .'} | eq { diff { hop { filter_eq { all_rows ; venue ; princes park } ; crowd } ; hop { filter_eq { all_rows ; venue ; victoria park } ; crowd } } ; 1000 } = true | select the rows whose venue record fuzzily matches to princes park . take the crowd record of this row . select the rows whose venue record fuzzily matches to victoria park . take the crowd record of this row . the first record is 1000 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, 'venue_8': 8, 'princes park_9': 9, 'crowd_10': 10, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_11': 11, 'venue_12': 12, 'victoria park_13': 13, 'crowd_14': 14, '1000_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', 'venue_8': 'venue', 'princes park_9': 'princes park', 'crowd_10': 'crowd', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_11': 'all_rows', 'venue_12': 'venue', 'victoria park_13': 'victoria park', 'crowd_14': 'crowd', '1000_15': '1000'} | {'eq_5': [6], 'result_6': [], 'diff_4': [5], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_7': [0], 'venue_8': [0], 'princes park_9': [0], 'crowd_10': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_11': [1], 'venue_12': [1], 'victoria park_13': [1], 'crowd_14': [3], '1000_15': [5]} | ['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']] |
clifton webb | https://en.wikipedia.org/wiki/Clifton_Webb | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-154682-2.html.csv | majority | clifton web was nominated more times than he won . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'nominated', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'result', 'nominated'], 'result': True, 'ind': 0, 'tointer': 'for the result records of all rows , most of them fuzzily match to nominated .', 'tostr': 'most_eq { all_rows ; result ; nominated } = true'} | most_eq { all_rows ; result ; nominated } = true | for the result records of all rows , most of them fuzzily match to nominated . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'result_3': 3, 'nominated_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'result_3': 'result', 'nominated_4': 'nominated'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'result_3': [0], 'nominated_4': [0]} | ['year', 'award', 'result', 'category', 'film'] | [['1945', 'academy award', 'nominated', 'best supporting actor', 'laura'], ['1947', 'academy award', 'nominated', 'best supporting actor', "the razor 's edge"], ['1949', 'academy award', 'nominated', 'best actor in a leading role', 'sitting pretty'], ['1947', 'golden globe award', 'won', 'best supporting actor', "the razor 's edge"], ['1953', 'golden globe award', 'nominated', 'best motion picture actor - musical / comedy', 'stars and stripes forever']] |
fundraising for the 2008 united states presidential election | https://en.wikipedia.org/wiki/Fundraising_for_the_2008_United_States_presidential_election | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12030247-7.html.csv | aggregation | the total loans received in the third quarter by candidates during fundraising for the 2008 united states presidential election was 8550000 . | {'scope': 'all', 'col': '3', 'type': 'sum', 'result': '8550000', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'loans received , 3q'], 'result': '8550000', 'ind': 0, 'tostr': 'sum { all_rows ; loans received , 3q }'}, '8550000'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; loans received , 3q } ; 8550000 } = true', 'tointer': 'the sum of the loans received , 3q record of all rows is 8550000 .'} | round_eq { sum { all_rows ; loans received , 3q } ; 8550000 } = true | the sum of the loans received , 3q record of all rows is 8550000 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'loans received , 3q_4': 4, '8550000_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'loans received , 3q_4': 'loans received , 3q', '8550000_5': '8550000'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'loans received , 3q_4': [0], '8550000_5': [1]} | ['candidate', 'money raised , 3q', 'loans received , 3q', 'money spent , 3q', 'total receipts', 'cash on hand', 'total debt', 'after debt'] | [['rudy giuliani', '11624255', '-', '13300649', '47253520', '16649825', '169256', '16480569'], ['mitt romney', '9896719', '8500000', '21301755', '62829068', '9216517', '17350000', '- 8133483'], ['fred thompson', '9750820', '-', '5706366', '12828110', '7121744', '678432', '6443312'], ['ron paul', '5258455', '-', '2169644', '8268452', '5443667', '-', '5443667'], ['john mccain', '5734477', '-', '5470277', '32124785', '3488627', '1730691', '1757936'], ['mike huckabee', '1034486', '-', '819376', '2345797', '651300', '47810', '603490'], ['duncan hunter', '486356', '50000', '618117', '1890873', '132741', '50000', '82741'], ['tom tancredo', '767152', '-', '1209583', '3538244', '110079', '295603', '- 185524'], ['sam brownback', '925745', '-', '1278856', '4235333', '94653', '-', '94653']] |
national democratic congress ( ghana ) | https://en.wikipedia.org/wiki/National_Democratic_Congress_%28Ghana%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1725076-2.html.csv | superlative | the highest number of votes was received in the year 2012 . | {'scope': 'all', 'col_superlative': '3', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'number of votes'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; number of votes }'}, 'election'], 'result': '2012', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; number of votes } ; election }'}, '2012'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; number of votes } ; election } ; 2012 } = true', 'tointer': 'select the row whose number of votes record of all rows is maximum . the election record of this row is 2012 .'} | eq { hop { argmax { all_rows ; number of votes } ; election } ; 2012 } = true | select the row whose number of votes record of all rows is maximum . the election record of this row is 2012 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'number of votes_5': 5, 'election_6': 6, '2012_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'number of votes_5': 'number of votes', 'election_6': 'election', '2012_7': '2012'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'number of votes_5': [0], 'election_6': [1], '2012_7': [2]} | ['election', 'candidate', 'number of votes', 'share of votes', 'outcome of election'] | [['2012', 'john dramani mahama', '5574761', '50.7 %', 'mahama ndc government'], ['2008 ( 2 )', 'john atta mills', '4501466', '50.1 %', 'mills ndc government'], ['2008 ( 1 )', 'john atta mills', '4056634', '47.9 %', '2nd round election'], ['2004', 'john atta mills', '3850368', '44.6 %', 'ndc opposition'], ['2000 ( 2nd )', 'john atta mills', '2728241', '43.3 %', 'ndc opposition'], ['2000 ( 1st )', 'john atta mills', '2895575', '44.8 %', '2nd round election'], ['1996', 'jerry rawlings', 'n / a', '57.4 %', '2nd rawlings ndc government'], ['1992', 'jerry rawlings', '2327600', '58.4 %', 'rawlings ndc government']] |
1971 - 72 cleveland cavaliers season | https://en.wikipedia.org/wiki/1971%E2%80%9372_Cleveland_Cavaliers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16946097-3.html.csv | count | in october of the 71-72 season , the caveliers went into overtime two times . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'ot', 'result': '2', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'score', 'ot'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose score record fuzzily matches to ot .', 'tostr': 'filter_eq { all_rows ; score ; ot }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; score ; ot } }', 'tointer': 'select the rows whose score record fuzzily matches to ot . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; score ; ot } } ; 2 } = true', 'tointer': 'select the rows whose score record fuzzily matches to ot . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; score ; ot } } ; 2 } = true | select the rows whose score record fuzzily matches to ot . 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, 'score_5': 5, 'ot_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', 'score_5': 'score', 'ot_6': 'ot', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'score_5': [0], 'ot_6': [0], '2_7': [2]} | ['date', 'h / a / n', 'opponent', 'score', 'record'] | [['october 15', 'h', 'buffalo braves', '109 - 111 ( ot )', '0 - 1'], ['october 16', 'a', 'buffalo braves', '93 - 89', '1 - 1'], ['october 17', 'h', 'new york knicks', '120 - 121 ( ot )', '1 - 2'], ['october 19', 'a', 'milwaukee bucks', '82 - 116', '1 - 3'], ['october 20', 'h', 'san francisco warriors', '98 - 115', '1 - 4'], ['october 23', 'n', 'baltimore bullets', '109 - 101', '2 - 4'], ['october 24', 'h', 'philadelphia 76ers', '93 - 111', '2 - 5'], ['october 27', 'a', 'philadelphia 76ers', '106 - 120', '2 - 6'], ['october 29', 'h', 'atlanta hawks', '97 - 98', '2 - 7'], ['october 31', 'h', 'milwaukee bucks', '102 - 118', '2 - 8']] |
gotōji line | https://en.wikipedia.org/wiki/Got%C5%8Dji_Line | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11482596-1.html.csv | comparative | kami - mio railway station is further from the gotōji line than the funao railway station . | {'row_1': '5', 'row_2': '2', 'col': '3', 'col_other': '1', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'station', 'kami - mio'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose station record fuzzily matches to kami - mio .', 'tostr': 'filter_eq { all_rows ; station ; kami - mio }'}, 'distance ( km )'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; station ; kami - mio } ; distance ( km ) }', 'tointer': 'select the rows whose station record fuzzily matches to kami - mio . take the distance ( km ) record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'station', 'funao'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose station record fuzzily matches to funao .', 'tostr': 'filter_eq { all_rows ; station ; funao }'}, 'distance ( km )'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; station ; funao } ; distance ( km ) }', 'tointer': 'select the rows whose station record fuzzily matches to funao . take the distance ( km ) record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; station ; kami - mio } ; distance ( km ) } ; hop { filter_eq { all_rows ; station ; funao } ; distance ( km ) } } = true', 'tointer': 'select the rows whose station record fuzzily matches to kami - mio . take the distance ( km ) record of this row . select the rows whose station record fuzzily matches to funao . take the distance ( km ) record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; station ; kami - mio } ; distance ( km ) } ; hop { filter_eq { all_rows ; station ; funao } ; distance ( km ) } } = true | select the rows whose station record fuzzily matches to kami - mio . take the distance ( km ) record of this row . select the rows whose station record fuzzily matches to funao . take the distance ( km ) record of this row . the first record is greater than the second record . | 5 | 5 | {'greater_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'station_7': 7, 'kami - mio_8': 8, 'distance (km)_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'station_11': 11, 'funao_12': 12, 'distance (km)_13': 13} | {'greater_4': 'greater', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'station_7': 'station', 'kami - mio_8': 'kami - mio', 'distance (km)_9': 'distance ( km )', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'station_11': 'station', 'funao_12': 'funao', 'distance (km)_13': 'distance ( km )'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'station_7': [0], 'kami - mio_8': [0], 'distance (km)_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'station_11': [1], 'funao_12': [1], 'distance (km)_13': [3]} | ['station', 'japanese', 'distance ( km )', 'rapid', 'location'] | [['tagawa - gotōji', '田川後藤寺', '0.0', '●', 'tagawa'], ['funao', '船尾', '3.4', '↑', 'tagawa'], ['chikuzen - shōnai', '筑前庄内', '7.1', '↑', 'iizuka'], ['shimo - kamoo', '下鴨生', '8.3', '↑', 'kama'], ['kami - mio', '上三緒', '10.2', '↑', 'iizuka'], ['shin - iizuka', '新飯塚', '13.3', '●', 'iizuka']] |
alberta general election , 2012 | https://en.wikipedia.org/wiki/Alberta_general_election%2C_2012 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16588852-2.html.csv | superlative | in the 2012 alberta general election , the wildrose party had the single highest net gain in seats . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '2', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'gains'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; gains }'}, 'party'], 'result': 'wildrose', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; gains } ; party }'}, 'wildrose'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; gains } ; party } ; wildrose } = true', 'tointer': 'select the row whose gains record of all rows is maximum . the party record of this row is wildrose .'} | eq { hop { argmax { all_rows ; gains } ; party } ; wildrose } = true | select the row whose gains record of all rows is maximum . the party record of this row is wildrose . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'gains_5': 5, 'party_6': 6, 'wildrose_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'gains_5': 'gains', 'party_6': 'party', 'wildrose_7': 'wildrose'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'gains_5': [0], 'party_6': [1], 'wildrose_7': [2]} | ['party', 'seats ( dissol )', 'seats ( 2012 )', 'gains', 'holds', 'losses', 'net change'] | [['progressive conservative', '66', '61', '11', '50', '16', '- 5'], ['wildrose', '4', '17', '15', '2', '2', '+ 13'], ['liberal', '8', '5', '0', '5', '3', '- 3'], ['new democratic', '2', '4', '2', '2', '0', '+ 2'], ['alberta party', '1', '0', '0', '0', '1', '- 1'], ['independents', '1', '0', '0', '0', '1', '- 1'], ['total', '82', '87', '28', '59', '23', '+ 5']] |
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/1-17356873-2.html.csv | unique | osman özdemir was the only manager to leave on november 3rd , 2008 . | {'scope': 'all', 'row': '6', 'col': '6', 'col_other': '2', 'criterion': 'equal', 'value': '3 november 2008', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date of appointment', '3 november 2008'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose date of appointment record fuzzily matches to 3 november 2008 .', 'tostr': 'filter_eq { all_rows ; date of appointment ; 3 november 2008 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; date of appointment ; 3 november 2008 } }', 'tointer': 'select the rows whose date of appointment record fuzzily matches to 3 november 2008 . 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 of appointment', '3 november 2008'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose date of appointment record fuzzily matches to 3 november 2008 .', 'tostr': 'filter_eq { all_rows ; date of appointment ; 3 november 2008 }'}, 'outgoing manager'], 'result': 'osman özdemir', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; date of appointment ; 3 november 2008 } ; outgoing manager }'}, 'osman özdemir'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; date of appointment ; 3 november 2008 } ; outgoing manager } ; osman özdemir }', 'tointer': 'the outgoing manager record of this unqiue row is osman özdemir .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; date of appointment ; 3 november 2008 } } ; eq { hop { filter_eq { all_rows ; date of appointment ; 3 november 2008 } ; outgoing manager } ; osman özdemir } } = true', 'tointer': 'select the rows whose date of appointment record fuzzily matches to 3 november 2008 . there is only one such row in the table . the outgoing manager record of this unqiue row is osman özdemir .'} | and { only { filter_eq { all_rows ; date of appointment ; 3 november 2008 } } ; eq { hop { filter_eq { all_rows ; date of appointment ; 3 november 2008 } ; outgoing manager } ; osman özdemir } } = true | select the rows whose date of appointment record fuzzily matches to 3 november 2008 . there is only one such row in the table . the outgoing manager record of this unqiue row is osman özdemir . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'date of appointment_7': 7, '3 november 2008_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'outgoing manager_9': 9, 'osman özdemir_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'date of appointment_7': 'date of appointment', '3 november 2008_8': '3 november 2008', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'outgoing manager_9': 'outgoing manager', 'osman özdemir_10': 'osman özdemir'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'date of appointment_7': [0], '3 november 2008_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'outgoing manager_9': [2], 'osman özdemir_10': [3]} | ['team', 'outgoing manager', 'manner of departure', 'date of vacancy', 'replaced by', 'date of appointment'] | [['konyaspor', 'raşit çetiner', 'sacked', '17 september 2008', 'giray bulak', '24 september 2008'], ['kocaelispor', 'engin ipekoğlu', 'sacked', '25 september 2008', 'yılmaz vural', '28 september 2008'], ['beşiktaş', 'ertuğrul sağlam', 'resigned', '7 october 2008', 'mustafa denizli', '9 october 2008'], ['ankaragücü', 'hakan kutlu', 'sacked', '20 october 2008', 'ünal karaman', '24 october 2008'], ['antalyaspor', 'jozef jarabinský', 'sacked', '28 october 2008', 'mehmet özdilek', '28 october 2008'], ['hacettepe', 'osman özdemir', 'resigned', '2 november 2008', 'erdoğan arıca', '3 november 2008'], ['denizlispor', 'ali yalçın', 'resigned', '2 november 2008', 'ümit kayıhan', '10 november 2008'], ['gençlerbirliği', 'mesut bakkal', 'resigned', '3 november 2008', 'samet aybaba', '5 november 2008'], ['bursaspor', 'samet aybaba', 'resigned', '4 november 2008', 'güvenç kurtar', '4 november 2008'], ['ankaragücü', 'ünal karaman', 'resigned', '8 december 2008', 'hakan kutlu', '2 january 2009'], ['bursaspor', 'güvenç kurtar', 'resigned', '23 december 2008', 'ertuğrul sağlam', '2 january 2009'], ['kocaelispor', 'yılmaz vural', 'resigned', '29 december 2008', 'erhan altın', '17 january 2009'], ['denizlispor', 'ümit kayıhan', 'sacked', '5 february 2009', 'mesut bakkal', '6 february 2009'], ['galatasaray', 'michael skibbe', 'sacked', '23 february 2009', 'bülent korkmaz', '23 february 2009'], ['hacettepe', 'erdoğan arıca', 'resigned', '2 march 2009', 'ergün penbe', '2 march 2009'], ['gaziantepspor', 'nurullah sağlam', 'resigned', '9 march 2009', 'josé couceiro', '6 april 2009']] |
united states house of representatives elections , 1986 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1986 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1341586-39.html.csv | comparative | of the incumbents in the 1986 election for united states house of representatives , doug walgren was first elected 6 years before tom ridge . | {'row_1': '7', 'row_2': '8', 'col': '4', 'col_other': '2', 'relation': 'diff', 'record_mentioned': 'no', 'diff_result': {'diff_value': '6', 'bigger': 'row2'}} | {'func': 'eq', 'args': [{'func': 'diff', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'incumbent', 'doug walgren'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose incumbent record fuzzily matches to doug walgren .', 'tostr': 'filter_eq { all_rows ; incumbent ; doug walgren }'}, 'first elected'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; incumbent ; doug walgren } ; first elected }', 'tointer': 'select the rows whose incumbent record fuzzily matches to doug walgren . take the first elected record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'incumbent', 'tom ridge'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose incumbent record fuzzily matches to tom ridge .', 'tostr': 'filter_eq { all_rows ; incumbent ; tom ridge }'}, 'first elected'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; incumbent ; tom ridge } ; first elected }', 'tointer': 'select the rows whose incumbent record fuzzily matches to tom ridge . take the first elected record of this row .'}], 'result': '-6', 'ind': 4, 'tostr': 'diff { hop { filter_eq { all_rows ; incumbent ; doug walgren } ; first elected } ; hop { filter_eq { all_rows ; incumbent ; tom ridge } ; first elected } }'}, '-6'], 'result': True, 'ind': 5, 'tostr': 'eq { diff { hop { filter_eq { all_rows ; incumbent ; doug walgren } ; first elected } ; hop { filter_eq { all_rows ; incumbent ; tom ridge } ; first elected } } ; -6 } = true', 'tointer': 'select the rows whose incumbent record fuzzily matches to doug walgren . take the first elected record of this row . select the rows whose incumbent record fuzzily matches to tom ridge . take the first elected record of this row . the second record is 6 larger than the first record .'} | eq { diff { hop { filter_eq { all_rows ; incumbent ; doug walgren } ; first elected } ; hop { filter_eq { all_rows ; incumbent ; tom ridge } ; first elected } } ; -6 } = true | select the rows whose incumbent record fuzzily matches to doug walgren . take the first elected record of this row . select the rows whose incumbent record fuzzily matches to tom ridge . take the first elected record of this row . the second record is 6 larger than the first 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, 'incumbent_8': 8, 'doug walgren_9': 9, 'first elected_10': 10, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_11': 11, 'incumbent_12': 12, 'tom ridge_13': 13, 'first elected_14': 14, '-6_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', 'incumbent_8': 'incumbent', 'doug walgren_9': 'doug walgren', 'first elected_10': 'first elected', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_11': 'all_rows', 'incumbent_12': 'incumbent', 'tom ridge_13': 'tom ridge', 'first elected_14': 'first elected', '-6_15': '-6'} | {'eq_5': [6], 'result_6': [], 'diff_4': [5], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_7': [0], 'incumbent_8': [0], 'doug walgren_9': [0], 'first elected_10': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_11': [1], 'incumbent_12': [1], 'tom ridge_13': [1], 'first elected_14': [3], '-6_15': [5]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['pennsylvania 6', 'gus yatron', 'democratic', '1968', 're - elected', 'gus yatron ( d ) 69.1 % norm bertasavage ( r ) 30.9 %'], ['pennsylvania 7', 'robert w edgar', 'democratic', '1974', 'retired to run for u s senate republican gain', 'curt weldon ( r ) 61.3 % bill spingler ( d ) 38.7 %'], ['pennsylvania 9', 'bud shuster', 'republican', '1972', 're - elected', 'bud shuster ( r ) unopposed'], ['pennsylvania 12', 'john murtha', 'democratic', '1974', 're - elected', 'john murtha ( d ) 67.4 % kathy holtzman ( r ) 32.6 %'], ['pennsylvania 15', 'donald l ritter', 'republican', '1978', 're - elected', 'donald l ritter ( r ) 56.8 % joe simonetta ( d ) 43.2 %'], ['pennsylvania 17', 'george gekas', 'republican', '1982', 're - elected', 'george gekas ( r ) 73.6 % michael s ogden ( d ) 26.4 %'], ['pennsylvania 18', 'doug walgren', 'democratic', '1976', 're - elected', 'doug walgren ( d ) 63.0 % ernie buckman ( r ) 37.0 %'], ['pennsylvania 21', 'tom ridge', 'republican', '1982', 're - elected', 'tom ridge ( r ) 80.9 % joylyn blackwell ( d ) 19.1 %']] |
1979 - 80 philadelphia flyers season | https://en.wikipedia.org/wiki/1979%E2%80%9380_Philadelphia_Flyers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14208862-5.html.csv | comparative | the philadelphia flyers had a game against the winnipeg visitor earlier than chicago in the 1979 - 80 season . | {'row_1': '4', 'row_2': '8', 'col': '1', 'col_other': '2', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'visitor', 'winnipeg'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose visitor record fuzzily matches to winnipeg .', 'tostr': 'filter_eq { all_rows ; visitor ; winnipeg }'}, 'date'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; visitor ; winnipeg } ; date }', 'tointer': 'select the rows whose visitor record fuzzily matches to winnipeg . take the date record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'visitor', 'chicago'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose visitor record fuzzily matches to chicago .', 'tostr': 'filter_eq { all_rows ; visitor ; chicago }'}, 'date'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; visitor ; chicago } ; date }', 'tointer': 'select the rows whose visitor record fuzzily matches to chicago . take the date record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; visitor ; winnipeg } ; date } ; hop { filter_eq { all_rows ; visitor ; chicago } ; date } } = true', 'tointer': 'select the rows whose visitor record fuzzily matches to winnipeg . take the date record of this row . select the rows whose visitor record fuzzily matches to chicago . take the date record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; visitor ; winnipeg } ; date } ; hop { filter_eq { all_rows ; visitor ; chicago } ; date } } = true | select the rows whose visitor record fuzzily matches to winnipeg . take the date record of this row . select the rows whose visitor record fuzzily matches to chicago . 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, 'visitor_7': 7, 'winnipeg_8': 8, 'date_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'visitor_11': 11, 'chicago_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', 'visitor_7': 'visitor', 'winnipeg_8': 'winnipeg', 'date_9': 'date', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'visitor_11': 'visitor', 'chicago_12': 'chicago', 'date_13': 'date'} | {'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'visitor_7': [0], 'winnipeg_8': [0], 'date_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'visitor_11': [1], 'chicago_12': [1], 'date_13': [3]} | ['date', 'visitor', 'score', 'home', 'decision', 'attendance', 'record'] | [['january 4', 'philadelphia', '5 - 3', 'ny rangers', 'myre', '17398', '25 - 1 - 10'], ['january 6', 'philadelphia', '4 - 2', 'buffalo', 'peeters', '16433', '26 - 1 - 10'], ['january 7', 'philadelphia', '1 - 7', 'minnesota', 'myre', '15962', '26 - 2 - 10'], ['january 10', 'winnipeg', '4 - 5', 'philadelphia', 'peeters', '17077', '27 - 2 - 10'], ['january 12', 'philadelphia', '3 - 4', 'montreal', 'myre', '18091', '27 - 3 - 10'], ['january 13', 'st louis', '1 - 1', 'philadelphia', 'peeters', '17077', '27 - 3 - 11'], ['january 15', 'washington', '4 - 7', 'philadelphia', 'myre', '17077', '28 - 3 - 11'], ['january 17', 'chicago', '1 - 5', 'philadelphia', 'peeters', '17077', '29 - 3 - 11'], ['january 19', 'philadelphia', '4 - 4', 'washington', 'myre', '18130', '29 - 3 - 12'], ['january 22', 'philadelphia', '3 - 1', 'st louis', 'peeters', '17453', '30 - 3 - 12'], ['january 23', 'philadelphia', '4 - 1', 'chicago', 'myre', '17160', '31 - 3 - 12'], ['january 25', 'philadelphia', '5 - 4', 'winnipeg', 'peeters', '15122', '32 - 3 - 12'], ['january 27', 'philadelphia', '5 - 3', 'edmonton', 'peeters', '15423', '33 - 3 - 12'], ['january 31', 'minnesota', '2 - 4', 'philadelphia', 'st croix', '17077', '34 - 3 - 12']] |
list of game of the year awards | https://en.wikipedia.org/wiki/List_of_Game_of_the_Year_awards | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1851722-8.html.csv | count | three of the games from the game of the year awards had the xbox 360 included as one of their platforms . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'xbox 360', 'result': '3', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'platform ( s )', 'xbox 360'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose platform ( s ) record fuzzily matches to xbox 360 .', 'tostr': 'filter_eq { all_rows ; platform ( s ) ; xbox 360 }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; platform ( s ) ; xbox 360 } }', 'tointer': 'select the rows whose platform ( s ) record fuzzily matches to xbox 360 . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; platform ( s ) ; xbox 360 } } ; 3 } = true', 'tointer': 'select the rows whose platform ( s ) record fuzzily matches to xbox 360 . the number of such rows is 3 .'} | eq { count { filter_eq { all_rows ; platform ( s ) ; xbox 360 } } ; 3 } = true | select the rows whose platform ( s ) record fuzzily matches to xbox 360 . 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, 'platform (s)_5': 5, 'xbox 360_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', 'platform (s)_5': 'platform ( s )', 'xbox 360_6': 'xbox 360', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'platform (s)_5': [0], 'xbox 360_6': [0], '3_7': [2]} | ['year', 'game', 'genre', 'platform ( s )', 'developer ( s )'] | [['2005', 'resident evil 4', 'survival horror : ( third - person ) shooter', 'gamecube , playstation 2 windows', 'capcom'], ['2006', 'gears of war', 'third - person shooter', 'xbox 360', 'epic games'], ['2007', 'call of duty 4 : modern warfare', 'action', 'playstation 3 , xbox 360 , nintendo ds , pc', 'infinity ward'], ['2008', 'littlebigplanet', 'puzzle platformer', 'playstation 3', 'media molecule'], ['2009', "assassin 's creed ii", 'third - person action - adventure', 'microsoft windows , playstation 3 , xbox 360', 'ubisoft montreal']] |
tacoma public schools | https://en.wikipedia.org/wiki/Tacoma_Public_Schools | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1414702-3.html.csv | aggregation | the average enrollment in the tacoma public schools is 1357.4 . | {'scope': 'all', 'col': '4', 'type': 'average', 'result': '1077.4', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'enrollment'], 'result': '1077.4', 'ind': 0, 'tostr': 'avg { all_rows ; enrollment }'}, '1077.4'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; enrollment } ; 1077.4 } = true', 'tointer': 'the average of the enrollment record of all rows is 1077.4 .'} | round_eq { avg { all_rows ; enrollment } ; 1077.4 } = true | the average of the enrollment record of all rows is 1077.4 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'enrollment_4': 4, '1077.4_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'enrollment_4': 'enrollment', '1077.4_5': '1077.4'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'enrollment_4': [0], '1077.4_5': [1]} | ['high school', 'type', 'established', 'enrollment', 'mascot', 'wiaa classification', 'notes'] | [['henry foss', 'comprehensive', '1973', '1298', 'falcons', '3a', 'located in central tacoma'], ['lincoln', 'comprehensive', '1913', '1618', 'abes', '3a', 'located in east tacoma'], ['mount tahoma', 'comprehensive', '1961', '1865', 'thunderbirds', '3a', 'located in south tacoma'], ['oakland alternative', 'alternative', '1988', '106', 'eagles', 'n / a', 'located in central tacoma'], ['tacoma school of the arts', 'magnet', '2001', '500', 'n / a', 'n / a', 'located in downtown tacoma']] |
1950 washington redskins season | https://en.wikipedia.org/wiki/1950_Washington_Redskins_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15124563-1.html.csv | count | in the 1950 washington redskins season , among the games with attendance over 25,000 people , 3 of them were played in october . | {'scope': 'subset', 'criterion': 'fuzzily_match', 'value': 'october', 'result': '3', 'col': '2', 'subset': {'col': '5', 'criterion': 'greater_than', 'value': '25000'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'attendance', '25000'], 'result': None, 'ind': 0, 'tostr': 'filter_greater { all_rows ; attendance ; 25000 }', 'tointer': 'select the rows whose attendance record is greater than 25000 .'}, 'date', 'october'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose attendance record is greater than 25000 . among these rows , select the rows whose date record fuzzily matches to october .', 'tostr': 'filter_eq { filter_greater { all_rows ; attendance ; 25000 } ; date ; october }'}], 'result': '3', 'ind': 2, 'tostr': 'count { filter_eq { filter_greater { all_rows ; attendance ; 25000 } ; date ; october } }', 'tointer': 'select the rows whose attendance record is greater than 25000 . among these rows , select the rows whose date record fuzzily matches to october . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_eq { filter_greater { all_rows ; attendance ; 25000 } ; date ; october } } ; 3 } = true', 'tointer': 'select the rows whose attendance record is greater than 25000 . among these rows , select the rows whose date record fuzzily matches to october . the number of such rows is 3 .'} | eq { count { filter_eq { filter_greater { all_rows ; attendance ; 25000 } ; date ; october } } ; 3 } = true | select the rows whose attendance record is greater than 25000 . among these rows , select the rows whose date record fuzzily matches to october . the number of such rows is 3 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_str_eq_1': 1, 'filter_greater_0': 0, 'all_rows_5': 5, 'attendance_6': 6, '25000_7': 7, 'date_8': 8, 'october_9': 9, '3_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_str_eq_1': 'filter_str_eq', 'filter_greater_0': 'filter_greater', 'all_rows_5': 'all_rows', 'attendance_6': 'attendance', '25000_7': '25000', 'date_8': 'date', 'october_9': 'october', '3_10': '3'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_str_eq_1': [2], 'filter_greater_0': [1], 'all_rows_5': [0], 'attendance_6': [0], '25000_7': [0], 'date_8': [1], 'october_9': [1], '3_10': [3]} | ['week', 'date', 'opponent', 'result', 'attendance'] | [['1', 'september 17 , 1950', 'baltimore colts', 'w 38 - 14', '29000'], ['2', 'september 24 , 1950', 'green bay packers', 'l 35 - 21', '14109'], ['3', 'october 1 , 1950', 'pittsburgh steelers', 'l 26 - 7', '25008'], ['4', 'october 8 , 1950', 'new york giants', 'l 21 - 17', '19288'], ['6', 'october 22 , 1950', 'chicago cardinals', 'l 38 - 28', '27856'], ['7', 'october 29 , 1950', 'philadelphia eagles', 'l 35 - 3', '33707'], ['8', 'november 5 , 1950', 'new york giants', 'l 24 - 21', '23909'], ['9', 'november 12 , 1950', 'philadelphia eagles', 'l 33 - 0', '29407'], ['10', 'november 19 , 1950', 'cleveland browns', 'l 20 - 14', '21908'], ['11', 'november 26 , 1950', 'baltimore colts', 'w 38 - 28', '21275'], ['12', 'december 3 , 1950', 'pittsburgh steelers', 'w 24 - 7', '19741'], ['13', 'december 10 , 1950', 'cleveland browns', 'l 45 - 21', '30143']] |
1974 vfl season | https://en.wikipedia.org/wiki/1974_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10869646-19.html.csv | count | in the 1974 vfl season , when the away team had at least 10 points , there were 3 times that the crowd was over 15000 . | {'scope': 'subset', 'criterion': 'greater_than', 'value': '15000', 'result': '3', 'col': '6', 'subset': {'col': '4', 'criterion': 'greater_than_eq', 'value': '10'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater', 'args': [{'func': 'filter_greater_eq', 'args': ['all_rows', 'away team score', '10'], 'result': None, 'ind': 0, 'tostr': 'filter_greater_eq { all_rows ; away team score ; 10 }', 'tointer': 'select the rows whose away team score record is greater than or equal to 10 .'}, 'crowd', '15000'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose away team score record is greater than or equal to 10 . among these rows , select the rows whose crowd record is greater than 15000 .', 'tostr': 'filter_greater { filter_greater_eq { all_rows ; away team score ; 10 } ; crowd ; 15000 }'}], 'result': '3', 'ind': 2, 'tostr': 'count { filter_greater { filter_greater_eq { all_rows ; away team score ; 10 } ; crowd ; 15000 } }', 'tointer': 'select the rows whose away team score record is greater than or equal to 10 . among these rows , select the rows whose crowd record is greater than 15000 . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_greater { filter_greater_eq { all_rows ; away team score ; 10 } ; crowd ; 15000 } } ; 3 } = true', 'tointer': 'select the rows whose away team score record is greater than or equal to 10 . among these rows , select the rows whose crowd record is greater than 15000 . the number of such rows is 3 .'} | eq { count { filter_greater { filter_greater_eq { all_rows ; away team score ; 10 } ; crowd ; 15000 } } ; 3 } = true | select the rows whose away team score record is greater than or equal to 10 . among these rows , select the rows whose crowd record is greater than 15000 . the number of such rows is 3 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_greater_1': 1, 'filter_greater_eq_0': 0, 'all_rows_5': 5, 'away team score_6': 6, '10_7': 7, 'crowd_8': 8, '15000_9': 9, '3_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_greater_1': 'filter_greater', 'filter_greater_eq_0': 'filter_greater_eq', 'all_rows_5': 'all_rows', 'away team score_6': 'away team score', '10_7': '10', 'crowd_8': 'crowd', '15000_9': '15000', '3_10': '3'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_greater_1': [2], 'filter_greater_eq_0': [1], 'all_rows_5': [0], 'away team score_6': [0], '10_7': [0], 'crowd_8': [1], '15000_9': [1], '3_10': [3]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['st kilda', '9.13 ( 67 )', 'south melbourne', '13.15 ( 93 )', 'moorabbin oval', '17833', '10 august 1974'], ['hawthorn', '17.20 ( 122 )', 'melbourne', '14.13 ( 97 )', 'princes park', '8476', '10 august 1974'], ['essendon', '24.15 ( 159 )', 'fitzroy', '8.13 ( 61 )', 'windy hill', '10753', '10 august 1974'], ['geelong', '8.8 ( 56 )', 'collingwood', '10.19 ( 79 )', 'kardinia park', '22826', '10 august 1974'], ['footscray', '10.8 ( 68 )', 'carlton', '4.20 ( 44 )', 'western oval', '28151', '10 august 1974'], ['richmond', '15.12 ( 102 )', 'north melbourne', '11.11 ( 77 )', 'vfl park', '40399', '10 august 1974']] |
united states house of representatives elections , 1994 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1994 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1341522-24.html.csv | ordinal | in the 1994 united states house of representatives election , the incumbent who was first elected the 2nd earliest is barney frank . | {'row': '2', 'col': '4', 'order': '2', 'col_other': '2', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'first elected', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; first elected ; 2 }'}, 'incumbent'], 'result': 'barney frank', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; first elected ; 2 } ; incumbent }'}, 'barney frank'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; first elected ; 2 } ; incumbent } ; barney frank } = true', 'tointer': 'select the row whose first elected record of all rows is 2nd minimum . the incumbent record of this row is barney frank .'} | eq { hop { nth_argmin { all_rows ; first elected ; 2 } ; incumbent } ; barney frank } = true | select the row whose first elected record of all rows is 2nd minimum . the incumbent record of this row is barney frank . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'first elected_5': 5, '2_6': 6, 'incumbent_7': 7, 'barney frank_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmin_0': 'nth_argmin', 'all_rows_4': 'all_rows', 'first elected_5': 'first elected', '2_6': '2', 'incumbent_7': 'incumbent', 'barney frank_8': 'barney frank'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'first elected_5': [0], '2_6': [0], 'incumbent_7': [1], 'barney frank_8': [2]} | ['district', 'incumbent', 'party', 'first elected', 'status', 'opponent'] | [['massachusetts1', 'john olver', 'democratic', '1991', 're - elected', 'john olver ( d ) unopposed'], ['massachusetts4', 'barney frank', 'democratic', '1980', 're - elected', 'barney frank ( d ) unopposed'], ['massachusetts5', 'marty meehan', 'democratic', '1992', 're - elected', 'marty meehan ( d ) 69.8 % david e coleman ( r ) 30.1 %'], ['massachusetts7', 'ed markey', 'democratic', '1976', 're - elected', 'ed markey ( d ) 64.4 % brad bailey ( r ) 35.5 %'], ['massachusetts8', 'joe kennedy', 'democratic', '1986', 're - elected', 'joe kennedy ( d ) unopposed']] |
1968 vfl season | https://en.wikipedia.org/wiki/1968_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10808933-5.html.csv | aggregation | 1968 vfl season featured an average crowd of about 20000 fans per game . | {'scope': 'all', 'col': '6', 'type': 'average', 'result': '20000', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'crowd'], 'result': '20000', 'ind': 0, 'tostr': 'avg { all_rows ; crowd }'}, '20000'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; crowd } ; 20000 } = true', 'tointer': 'the average of the crowd record of all rows is 20000 .'} | round_eq { avg { all_rows ; crowd } ; 20000 } = true | the average of the crowd record of all rows is 20000 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'crowd_4': 4, '20000_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'crowd_4': 'crowd', '20000_5': '20000'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'crowd_4': [0], '20000_5': [1]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['north melbourne', '6.13 ( 49 )', 'st kilda', '9.7 ( 61 )', 'arden street oval', '14409', '11 may 1968'], ['essendon', '16.16 ( 112 )', 'fitzroy', '11.15 ( 81 )', 'windy hill', '18500', '11 may 1968'], ['collingwood', '17.11 ( 113 )', 'hawthorn', '11.16 ( 82 )', 'victoria park', '20688', '11 may 1968'], ['carlton', '16.15 ( 111 )', 'footscray', '5.9 ( 39 )', 'princes park', '14490', '11 may 1968'], ['south melbourne', '8.10 ( 58 )', 'richmond', '13.25 ( 103 )', 'lake oval', '17783', '11 may 1968'], ['melbourne', '9.9 ( 63 )', 'geelong', '10.10 ( 70 )', 'mcg', '31862', '11 may 1968']] |
united states house of representatives elections , 2000 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_2000 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1341423-49.html.csv | ordinal | tom barrett ( d ) is the candidate re-elected who gained the highest percentage of votes 75 % . | {'row': '4', 'col': '6', 'order': '1', 'col_other': '2', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'candidates', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; candidates ; 1 }'}, 'incumbent'], 'result': 'tom barrett', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; candidates ; 1 } ; incumbent }'}, 'tom barrett'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; candidates ; 1 } ; incumbent } ; tom barrett } = true', 'tointer': 'select the row whose candidates record of all rows is 1st maximum . the incumbent record of this row is tom barrett .'} | eq { hop { nth_argmax { all_rows ; candidates ; 1 } ; incumbent } ; tom barrett } = true | select the row whose candidates record of all rows is 1st maximum . the incumbent record of this row is tom barrett . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'candidates_5': 5, '1_6': 6, 'incumbent_7': 7, 'tom barrett_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'candidates_5': 'candidates', '1_6': '1', 'incumbent_7': 'incumbent', 'tom barrett_8': 'tom barrett'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'candidates_5': [0], '1_6': [0], 'incumbent_7': [1], 'tom barrett_8': [2]} | ['district', 'incumbent', 'party', 'first elected', 'results', 'candidates'] | [['wisconsin 1', 'paul ryan', 'republican', '1998', 're - elected', 'paul ryan ( r ) 66 % jeffrey thomas ( d ) 34 %'], ['wisconsin 2', 'tammy baldwin', 'democratic', '1998', 're - elected', 'tammy baldwin ( d ) 51 % john sharpless ( r ) 49 %'], ['wisconsin 3', 'ron kind', 'democratic', '1996', 're - elected', 'ron kind ( d ) 64 % susan tully ( r ) 36 %'], ['wisconsin 5', 'tom barrett', 'democratic', '1992', 're - elected', 'tom barrett ( d ) 78 % jonathan smith ( r ) 22 %'], ['wisconsin 6', 'tom petri', 'republican', '1979', 're - elected', 'tom petri ( r ) 65 % dan flaherty ( d ) 35 %'], ['wisconsin 7', 'dave obey', 'democratic', '1969', 're - elected', 'dave obey ( d ) 63 % sean cronin ( r ) 37 %'], ['wisconsin 8', 'mark green', 'republican', '1998', 're - elected', 'mark green ( r ) 75 % dean reich ( d ) 25 %']] |
norwegian european communities membership referendum , 1972 | https://en.wikipedia.org/wiki/Norwegian_European_Communities_membership_referendum%2C_1972 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1289762-1.html.csv | aggregation | the combined total electorate for constituencies in the 1972 nowegian european communities membership referendum was 2633581 . | {'scope': 'all', 'col': '2', 'type': 'sum', 'result': '2633581', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'electorate'], 'result': '2633581', 'ind': 0, 'tostr': 'sum { all_rows ; electorate }'}, '2633581'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; electorate } ; 2633581 } = true', 'tointer': 'the sum of the electorate record of all rows is 2633581 .'} | round_eq { sum { all_rows ; electorate } ; 2633581 } = true | the sum of the electorate record of all rows is 2633581 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'electorate_4': 4, '2633581_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'electorate_4': 'electorate', '2633581_5': '2633581'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'electorate_4': [0], '2633581_5': [1]} | ['constituency', 'electorate', 's spoilt vote', 'total poll ( % )', 'for ( % )', 'against ( % )'] | [['østfold', '152837', '392', '121498 ( 80 )', '58931 ( 49 )', '62567 ( 51 )'], ['akershus', '217851', '542', '180503 ( 83 )', '102521 ( 57 )', '77982 ( 43 )'], ['oslo', '356153', '619', '291654 ( 82 )', '193980 ( 67 )', '97674 ( 33 )'], ['hedmark', '124960', '519', '99508 ( 80 )', '44150 ( 44 )', '55358 ( 56 )'], ['oppland', '120082', '314', '94114 ( 79 )', '37550 ( 40 )', '56564 ( 60 )'], ['buskerud', '139999', '400', '110387 ( 79 )', '59532 ( 54 )', '50855 ( 46 )'], ['vestfold', '155338', '247', '94355 ( 79 )', '53515 ( 57 )', '40840 ( 43 )'], ['telemark', '108485', '211', '84056 ( 78 )', '32284 ( 38 )', '51772 ( 62 )'], ['aust - agder', '55276', '138', '40909 ( 74 )', '18659 ( 46 )', '22250 ( 54 )'], ['vest - agder', '81707', '177', '64100 ( 79 )', '27510 ( 43 )', '36590 ( 57 )'], ['rogaland', '174925', '309', '138601 ( 79 )', '62096 ( 45 )', '76505 ( 55 )'], ['hordaland', '248675', '511', '198095 ( 80 )', '96996 ( 49 )', '101099 ( 51 )'], ['sogn og fjordane', '67335', '153', '51705 ( 77 )', '15923 ( 31 )', '35782 ( 69 )'], ['møre og romsdal', '146917', '240', '114709 ( 78 )', '33504 ( 29 )', '81205 ( 71 )'], ['sør - trøndelag', '159730', '248', '122092 ( 77 )', '51827 ( 42 )', '70265 ( 58 )'], ['nord - trøndelag', '77954', '107', '60495 ( 78 )', '19101 ( 32 )', '41394 ( 68 )'], ['nordland', '157183', '549', '120979 ( 77 )', '33228 ( 27 )', '87751 ( 73 )'], ['troms', '88174', '385', '66499 ( 76 )', '19820 ( 30 )', '46679 ( 70 )']] |
list of highest - grossing bollywood films | https://en.wikipedia.org/wiki/List_of_highest-grossing_Bollywood_films | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11872185-1.html.csv | comparative | siddique directed a film that was designated a bollywood blockbuster before arbaaz khan did . | {'row_1': '6', 'row_2': '5', 'col': '3', 'col_other': '5', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'director', 'siddique'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose director record fuzzily matches to siddique .', 'tostr': 'filter_eq { all_rows ; director ; siddique }'}, 'year'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; director ; siddique } ; year }', 'tointer': 'select the rows whose director record fuzzily matches to siddique . take the year record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'director', 'arbaaz khan'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose director record fuzzily matches to arbaaz khan .', 'tostr': 'filter_eq { all_rows ; director ; arbaaz khan }'}, 'year'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; director ; arbaaz khan } ; year }', 'tointer': 'select the rows whose director record fuzzily matches to arbaaz khan . take the year record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; director ; siddique } ; year } ; hop { filter_eq { all_rows ; director ; arbaaz khan } ; year } } = true', 'tointer': 'select the rows whose director record fuzzily matches to siddique . take the year record of this row . select the rows whose director record fuzzily matches to arbaaz khan . take the year record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; director ; siddique } ; year } ; hop { filter_eq { all_rows ; director ; arbaaz khan } ; year } } = true | select the rows whose director record fuzzily matches to siddique . take the year record of this row . select the rows whose director record fuzzily matches to arbaaz khan . take the year 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, 'director_7': 7, 'siddique_8': 8, 'year_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'director_11': 11, 'arbaaz khan_12': 12, 'year_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', 'director_7': 'director', 'siddique_8': 'siddique', 'year_9': 'year', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'director_11': 'director', 'arbaaz khan_12': 'arbaaz khan', 'year_13': 'year'} | {'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'director_7': [0], 'siddique_8': [0], 'year_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'director_11': [1], 'arbaaz khan_12': [1], 'year_13': [3]} | ['rank', 'movie', 'year', 'worldwide gross', 'director', 'verdict'] | [['1', '3 idiots', '2009', '392 crore', 'rajkumar hirani', 'all time blockbuster'], ['2', 'chennai express', '2013', '314 crore', 'rohit shetty', 'blockbuster'], ['3', 'ek tha tiger', '2012', '310 crore', 'kabir khan', 'blockbuster'], ['4', 'yeh jawaani hai deewani', '2013', '301 crore', 'ayan mukerji', 'blockbuster'], ['5', 'dabangg 2', '2012', '251 crore', 'arbaaz khan', 'blockbuster'], ['6', 'bodyguard', '2011', '230 crore', 'siddique', 'blockbuster'], ['7', 'dabangg', '2010', '215 crore', 'abhinav singh kashyap', 'all time blockbuster'], ['8', 'jab tak hai jaan', '2012', '211 crore', 'yash chopra', 'super hit'], ['9', 'don 2', '2011', '206 crore', 'farhan akhtar', 'super hit'], ['10', 'raone', '2011', '202 crore', 'anubhav sinha', 'super hit']] |
2009 - 10 chicago bulls season | https://en.wikipedia.org/wiki/2009%E2%80%9310_Chicago_Bulls_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-22669044-7.html.csv | aggregation | the total attendance at chicago bulls games in the united center in december 2009 was 226050 . | {'scope': 'subset', 'col': '8', 'type': 'sum', 'result': '226050', 'subset': {'col': '8', 'criterion': 'equal', 'value': 'united center'}} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location attendance', 'united center'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; location attendance ; united center }', 'tointer': 'select the rows whose location attendance record fuzzily matches to united center .'}, 'location attendance'], 'result': '226050', 'ind': 1, 'tostr': 'sum { filter_eq { all_rows ; location attendance ; united center } ; location attendance }'}, '226050'], 'result': True, 'ind': 2, 'tostr': 'round_eq { sum { filter_eq { all_rows ; location attendance ; united center } ; location attendance } ; 226050 } = true', 'tointer': 'select the rows whose location attendance record fuzzily matches to united center . the sum of the location attendance record of these rows is 226050 .'} | round_eq { sum { filter_eq { all_rows ; location attendance ; united center } ; location attendance } ; 226050 } = true | select the rows whose location attendance record fuzzily matches to united center . the sum of the location attendance record of these rows is 226050 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'sum_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'location attendance_5': 5, 'united center_6': 6, 'location attendance_7': 7, '226050_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'sum_1': 'sum', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'location attendance_5': 'location attendance', 'united center_6': 'united center', 'location attendance_7': 'location attendance', '226050_8': '226050'} | {'eq_2': [3], 'result_3': [], 'sum_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'location attendance_5': [0], 'united center_6': [0], 'location attendance_7': [1], '226050_8': [2]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record'] | [['16', 'december 2', 'detroit', 'w 92 - 85 ( ot )', 'john salmons ( 22 )', 'joakim noah ( 14 )', 'derrick rose , brad miller ( 6 )', 'united center 21523', '7 - 9'], ['17', 'december 4', 'cleveland', 'l 87 - 101 ( ot )', 'taj gibson ( 14 )', 'taj gibson ( 13 )', 'derrick rose ( 7 )', 'quicken loans arena 20562', '7 - 10'], ['18', 'december 5', 'toronto', 'l 78 - 110 ( ot )', 'john salmons , jannero pargo ( 13 )', 'joakim noah ( 7 )', 'derrick rose ( 5 )', 'united center 20481', '7 - 11'], ['19', 'december 8', 'new jersey', 'l 101 - 103 ( ot )', 'luol deng , derrick rose ( 27 )', 'luol deng , joakim noah ( 9 )', 'derrick rose ( 10 )', 'united center 17872', '7 - 12'], ['20', 'december 9', 'atlanta', 'l 83 - 118 ( ot )', 'derrick rose ( 19 )', 'joakim noah ( 11 )', 'derrick rose ( 7 )', 'philips arena 16808', '7 - 13'], ['21', 'december 11', 'golden state', 'w 96 - 91 ( ot )', 'luol deng ( 21 )', 'joakim noah ( 14 )', 'luol deng ( 6 )', 'united center 18803', '8 - 13'], ['22', 'december 12', 'boston', 'l 80 - 106 ( ot )', 'derrick rose ( 19 )', 'joakim noah ( 13 )', 'john salmons ( 9 )', 'united center 21257', '8 - 14'], ['23', 'december 15', 'la lakers', 'l 87 - 96 ( ot )', 'luol deng , derrick rose ( 21 )', 'joakim noah ( 20 )', 'derrick rose , brad miller ( 6 )', 'united center 21416', '8 - 15'], ['24', 'december 17', 'new york', 'w 98 - 89 ( ot )', 'luol deng ( 24 )', 'luol deng ( 13 )', 'derrick rose ( 6 )', 'united center 19791', '9 - 15'], ['25', 'december 19', 'atlanta', 'w 101 - 98 ( ot )', 'derrick rose ( 32 )', 'luol deng ( 12 )', 'derrick rose , luol deng ( 6 )', 'united center 21381', '10 - 15'], ['26', 'december 21', 'sacramento', 'l 98 - 102 ( ot )', 'luol deng ( 26 )', 'joakim noah ( 10 )', 'derrick rose ( 7 )', 'united center 19631', '10 - 16'], ['27', 'december 22', 'new york', 'l 81 - 88 ( ot )', 'derrick rose ( 26 )', 'joakim noah ( 21 )', 'derrick rose ( 4 )', 'madison square garden 19763', '10 - 17'], ['28', 'december 26', 'new orleans', 'w 96 - 85 ( ot )', 'tyrus thomas ( 21 )', 'joakim noah ( 18 )', 'derrick rose ( 9 )', 'united center 22008', '11 - 17'], ['29', 'december 29', 'indiana', 'w 104 - 95 ( ot )', 'derrick rose ( 28 )', 'tyrus thomas ( 15 )', 'derrick rose ( 6 )', 'united center 21887', '12 - 17']] |
2008 - 09 utah jazz season | https://en.wikipedia.org/wiki/2008%E2%80%9309_Utah_Jazz_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17355716-6.html.csv | aggregation | for the 2008-09 utah jazz season the average attendance at the energy solutions arena was 19911 . | {'scope': 'subset', 'col': '8', 'type': 'average', 'result': '19911', 'subset': {'col': '8', 'criterion': 'equal', 'value': 'energy solutions arena'}} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location attendance', 'energy solutions arena'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; location attendance ; energy solutions arena }', 'tointer': 'select the rows whose location attendance record fuzzily matches to energy solutions arena .'}, 'location attendance'], 'result': '19911', 'ind': 1, 'tostr': 'avg { filter_eq { all_rows ; location attendance ; energy solutions arena } ; location attendance }'}, '19911'], 'result': True, 'ind': 2, 'tostr': 'round_eq { avg { filter_eq { all_rows ; location attendance ; energy solutions arena } ; location attendance } ; 19911 } = true', 'tointer': 'select the rows whose location attendance record fuzzily matches to energy solutions arena . the average of the location attendance record of these rows is 19911 .'} | round_eq { avg { filter_eq { all_rows ; location attendance ; energy solutions arena } ; location attendance } ; 19911 } = true | select the rows whose location attendance record fuzzily matches to energy solutions arena . the average of the location attendance record of these rows is 19911 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'avg_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'location attendance_5': 5, 'energy solutions arena_6': 6, 'location attendance_7': 7, '19911_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'avg_1': 'avg', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'location attendance_5': 'location attendance', 'energy solutions arena_6': 'energy solutions arena', 'location attendance_7': 'location attendance', '19911_8': '19911'} | {'eq_2': [3], 'result_3': [], 'avg_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'location attendance_5': [0], 'energy solutions arena_6': [0], 'location attendance_7': [1], '19911_8': [2]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record'] | [['19', 'december 2', 'sacramento', 'w 99 - 94 ( ot )', 'kyle korver ( 15 )', 'paul millsap , mehmet okur ( 11 )', 'deron williams ( 7 )', 'arco arena 10798', '12 - 7'], ['20', 'december 3', 'miami', 'l 89 - 93 ( ot )', 'paul millsap ( 20 )', 'paul millsap ( 13 )', 'deron williams ( 5 )', 'energysolutions arena 19911', '12 - 8'], ['21', 'december 5', 'toronto', 'w 114 - 87 ( ot )', 'mehmet okur ( 21 )', 'paul millsap ( 11 )', 'paul millsap ( 7 )', 'energysolutions arena 19911', '13 - 8'], ['22', 'december 6', 'phoenix', 'l 104 - 106 ( ot )', 'c j miles , paul millsap ( 20 )', 'mehmet okur ( 13 )', 'deron williams ( 15 )', 'us airways center 18422', '13 - 9'], ['23', 'december 9', 'minnesota', 'w 99 - 96 ( ot )', 'ronnie brewer ( 25 )', 'mehmet okur ( 13 )', 'deron williams ( 11 )', 'target center 10745', '14 - 9'], ['24', 'december 11', 'portland', 'w 97 - 88 ( ot )', 'mehmet okur ( 27 )', 'paul millsap ( 12 )', 'deron williams ( 11 )', 'energysolutions arena 19911', '15 - 9'], ['25', 'december 13', 'orlando', 'l 94 - 103 ( ot )', 'andrei kirilenko , deron williams ( 17 )', 'paul millsap ( 14 )', 'deron williams ( 11 )', 'energysolutions arena 19911', '15 - 10'], ['26', 'december 15', 'boston', 'l 91 - 100 ( ot )', 'paul millsap ( 32 )', 'paul millsap ( 10 )', 'deron williams ( 7 )', 'td banknorth garden 18624', '15 - 11'], ['27', 'december 17', 'new jersey', 'w 103 - 92 ( ot )', 'mehmet okur ( 23 )', 'paul millsap ( 12 )', 'deron williams ( 11 )', 'izod center 12542', '16 - 11'], ['28', 'december 19', 'detroit', 'w 120 - 114 ( 2ot )', 'deron williams ( 29 )', 'paul millsap ( 13 )', 'deron williams ( 8 )', 'the palace of auburn hills 22076', '17 - 11'], ['29', 'december 20', 'chicago', 'l 98 - 106 ( ot )', 'mehmet okur ( 23 )', 'mehmet okur ( 13 )', 'deron williams ( 6 )', 'united center 22046', '17 - 12'], ['30', 'december 23', 'milwaukee', 'l 86 - 94 ( ot )', 'andrei kirilenko ( 22 )', 'andrei kirilenko ( 11 )', 'deron williams ( 8 )', 'bradley center 14888', '17 - 13'], ['31', 'december 26', 'dallas', 'w 97 - 88 ( ot )', 'ronnie brewer ( 21 )', 'andrei kirilenko ( 14 )', 'deron williams ( 13 )', 'energysolutions arena 19911', '18 - 13'], ['32', 'december 27', 'houston', 'l 115 - 120 ( 2ot )', 'ronnie brewer ( 23 )', 'kyrylo fesenko ( 11 )', 'deron williams ( 11 )', 'toyota center 18245', '18 - 14'], ['33', 'december 29', 'philadelphia', 'w 112 - 95 ( ot )', 'deron williams ( 27 )', 'andrei kirilenko ( 13 )', 'deron williams ( 6 )', 'energysolutions arena 19911', '19 - 14']] |
emfuleni local municipality | https://en.wikipedia.org/wiki/Emfuleni_Local_Municipality | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18891012-1.html.csv | aggregation | the average population for the emfuleni local municipality in south africa is 65841 . | {'scope': 'all', 'col': '4', 'type': 'average', 'result': '65841', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'population'], 'result': '65841', 'ind': 0, 'tostr': 'avg { all_rows ; population }'}, '65841'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; population } ; 65841 } = true', 'tointer': 'the average of the population record of all rows is 65841 .'} | round_eq { avg { all_rows ; population } ; 65841 } = true | the average of the population record of all rows is 65841 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'population_4': 4, '65841_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'population_4': 'population', '65841_5': '65841'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'population_4': [0], '65841_5': [1]} | ['place', 'code', 'area ( km 2 )', 'population', 'most spoken language'] | [['boipatong', '70401', '1.62', '16867', 'sotho'], ['bophelong', '70402', '5.97', '37782', 'sotho'], ['evaton', '70404', '35.20', '143157', 'sotho'], ['orange farm', '70405', '3.79', '16720', 'zulu'], ['sebokeng', '70406', '32.80', '222045', 'sotho'], ['sharpeville', '70407', '5.04', '41032', 'sotho'], ['tshepiso', '70408', '5.26', '22952', 'sotho'], ['vanderbijlpark', '70409', '207.69', '80205', 'afrikaans'], ['vereeniging', '70410', '191.33', '73283', 'afrikaans'], ['remainder of the municipality', '70403', '498.77', '4378', 'sotho']] |
1980 toronto blue jays season | https://en.wikipedia.org/wiki/1980_Toronto_Blue_Jays_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12207900-2.html.csv | count | a total of two games in the 1980 toronto blue jays season were postponed due to rain . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'postponed ( rain )', 'result': '2', 'col': '6', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'record', 'postponed ( rain )'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose record record fuzzily matches to postponed ( rain ) .', 'tostr': 'filter_eq { all_rows ; record ; postponed ( rain ) }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; record ; postponed ( rain ) } }', 'tointer': 'select the rows whose record record fuzzily matches to postponed ( rain ) . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; record ; postponed ( rain ) } } ; 2 } = true', 'tointer': 'select the rows whose record record fuzzily matches to postponed ( rain ) . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; record ; postponed ( rain ) } } ; 2 } = true | select the rows whose record record fuzzily matches to postponed ( rain ) . 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, 'record_5': 5, 'postponed (rain)_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', 'record_5': 'record', 'postponed (rain)_6': 'postponed ( rain )', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'record_5': [0], 'postponed (rain)_6': [0], '2_7': [2]} | ['date', 'opponent', 'score', 'loss', 'attendance', 'record'] | [['april 9', 'mariners', '8 - 6', 'lemanczyk ( 0 - 1 )', '22588', '0 - 1'], ['april 11', 'mariners', '10 - 7 ( 11 )', 'dressler ( 0 - 1 )', '6104', '1 - 1'], ['april 12', 'mariners', '3 - 2 ( 10 )', 'garvin ( 0 - 1 )', '6773', '1 - 2'], ['april 13', 'mariners', '5 - 1', 'lemanczyk ( 0 - 2 )', '4567', '1 - 3'], ['april 14', 'brewers', 'postponed ( rain ) rescheduled for july 13', 'postponed ( rain ) rescheduled for july 13', 'postponed ( rain ) rescheduled for july 13', 'postponed ( rain ) rescheduled for july 13'], ['april 16', 'brewers', '11 - 2', 'slaton ( 0 - 1 )', '12688', '2 - 3'], ['april 17', 'brewers', '1 - 0', 'sorensen ( 1 - 1 )', '11235', '3 - 3'], ['april 19', 'indians', '8 - 1', 'clancy ( 0 - 1 )', '61753', '3 - 4'], ['april 20', 'indians', '5 - 3', 'denny ( 0 - 2 )', '11220', '4 - 4'], ['april 21', 'royals', '7 - 1', 'gale ( 0 - 2 )', '21117', '5 - 4'], ['april 22', 'royals', '7 - 2', 'mirabella ( 1 - 1 )', '16993', '5 - 5'], ['april 23', 'royals', '7 - 4', 'mclaughlin ( 0 - 1 )', '18855', '5 - 6'], ['april 25', 'brewers', '5 - 3', 'sorensen ( 1 - 2 )', '9902', '6 - 6'], ['april 26', 'brewers', '4 - 0', 'caldwell ( 2 - 1 )', '11038', '7 - 6'], ['april 27', 'brewers', '8 - 2', 'haas ( 1 - 3 )', '11099', '8 - 6'], ['april 28', 'royals', 'postponed ( rain ) rescheduled for august 8', 'postponed ( rain ) rescheduled for august 8', 'postponed ( rain ) rescheduled for august 8', 'postponed ( rain ) rescheduled for august 8'], ['april 29', 'royals', '3 - 1', 'leonard ( 0 - 3 )', '11553', '9 - 6'], ['april 30', 'royals', '3 - 0', 'jefferson ( 0 - 1 )', '14029', '9 - 7']] |
united states presidential election in connecticut , 2004 | https://en.wikipedia.org/wiki/United_States_presidential_election_in_Connecticut%2C_2004 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1756284-1.html.csv | ordinal | for the state of connecticut , in the 2004 presidential election , the second highest number of votes for kerry came from fairfield county . | {'row': '7', 'col': '3', 'order': '2', 'col_other': '1', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'kerry', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; kerry ; 2 }'}, 'county'], 'result': 'fairfield', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; kerry ; 2 } ; county }'}, 'fairfield'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; kerry ; 2 } ; county } ; fairfield } = true', 'tointer': 'select the row whose kerry record of all rows is 2nd maximum . the county record of this row is fairfield .'} | eq { hop { nth_argmax { all_rows ; kerry ; 2 } ; county } ; fairfield } = true | select the row whose kerry record of all rows is 2nd maximum . the county record of this row is fairfield . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'kerry_5': 5, '2_6': 6, 'county_7': 7, 'fairfield_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', 'kerry_5': 'kerry', '2_6': '2', 'county_7': 'county', 'fairfield_8': 'fairfield'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'kerry_5': [0], '2_6': [0], 'county_7': [1], 'fairfield_8': [2]} | ['county', 'kerry %', 'kerry', 'bush %', 'bush', 'others %', 'others', '2000 result'] | [['hartford', '58.7 %', '229902', '39.5 %', '154919', '1.8 %', '6987', '1.5'], ['middlesex', '56.3 %', '47292', '42.0 %', '35252', '1.7 %', '1440', '+ 1.4'], ['new london', '55.8 %', '66062', '42.2 %', '49931', '2.0 %', '2367', '+ 0.4'], ['tolland', '54.6 %', '39146', '43.6 %', '31245', '1.9 %', '1338', '+ 1.6'], ['new haven', '54.3 %', '199060', '43.8 %', '160390', '1.9 %', '6942', '- 3.7'], ['windham', '52.1 %', '25477', '45.7 %', '22324', '2.2 %', '1060', '+ 2.5'], ['fairfield', '51.4 %', '205902', '47.3 %', '189605', '1.4 %', '5460', '- 0.9']] |
1994 group | https://en.wikipedia.org/wiki/1994_Group | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-142950-1.html.csv | comparative | of the members of the 1994 group , the university of leicester was established earlier than the university of east anglia . | {'row_1': '7', 'row_2': '2', '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', 'institution', 'university of leicester'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose institution record fuzzily matches to university of leicester .', 'tostr': 'filter_eq { all_rows ; institution ; university of leicester }'}, 'established'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; institution ; university of leicester } ; established }', 'tointer': 'select the rows whose institution record fuzzily matches to university of leicester . take the established record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'institution', 'university of east anglia'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose institution record fuzzily matches to university of east anglia .', 'tostr': 'filter_eq { all_rows ; institution ; university of east anglia }'}, 'established'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; institution ; university of east anglia } ; established }', 'tointer': 'select the rows whose institution record fuzzily matches to university of east anglia . take the established record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; institution ; university of leicester } ; established } ; hop { filter_eq { all_rows ; institution ; university of east anglia } ; established } } = true', 'tointer': 'select the rows whose institution record fuzzily matches to university of leicester . take the established record of this row . select the rows whose institution record fuzzily matches to university of east anglia . take the established record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; institution ; university of leicester } ; established } ; hop { filter_eq { all_rows ; institution ; university of east anglia } ; established } } = true | select the rows whose institution record fuzzily matches to university of leicester . take the established record of this row . select the rows whose institution record fuzzily matches to university of east anglia . take the established 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, 'institution_7': 7, 'university of leicester_8': 8, 'established_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'institution_11': 11, 'university of east anglia_12': 12, 'established_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', 'institution_7': 'institution', 'university of leicester_8': 'university of leicester', 'established_9': 'established', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'institution_11': 'institution', 'university of east anglia_12': 'university of east anglia', 'established_13': 'established'} | {'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'institution_7': [0], 'university of leicester_8': [0], 'established_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'institution_11': [1], 'university of east anglia_12': [1], 'established_13': [3]} | ['institution', 'location', 'established', 'gained university status', 'vice - chancellor', 'total number of students', 'research funding ( 000 )'] | [['birkbeck , university of london', 'london', '1823', '1920', 'professor david latchman', '19020', '9985'], ['university of east anglia', 'norwich', '1963', '1963', 'professor edward acton', '19585', '16482'], ['university of essex', 'colchester', '1964', '1964', 'professor anthony forster', '11690', '9967'], ['goldsmiths , university of london', 'london', '1891', '1904', 'dr pat loughrey', '7615', '8539'], ['institute of education , university of london', 'london', '1902', '1932', 'professor chris husbands', '7215', '7734'], ['university of lancaster', 'lancaster', '1964', '1964', 'professor mark smith', '12695', '18640'], ['university of leicester', 'leicester', '1921', '1957', 'professor robert burgess', '16160', '22225'], ['loughborough university', 'loughborough', '1909', '1966', 'professor robert allison', '17825', '22398'], ['royal holloway , university of london', 'egham', '1849', '1900', 'professor paul layzell ( principal )', '7620', '13699'], ['soas , university of london', 'london', '1916', '1916', 'professor paul webley', '4525', '7238']] |
fm - and tv - mast kosztowy | https://en.wikipedia.org/wiki/FM-_and_TV-mast_Kosztowy | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1249698-1.html.csv | majority | most of the programs have an erp kw value of 60 . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': '60', 'subset': None} | {'func': 'most_eq', 'args': ['all_rows', 'erp kw', '60'], 'result': True, 'ind': 0, 'tointer': 'for the erp kw records of all rows , most of them are equal to 60 .', 'tostr': 'most_eq { all_rows ; erp kw ; 60 } = true'} | most_eq { all_rows ; erp kw ; 60 } = true | for the erp kw records of all rows , most of them are equal to 60 . | 1 | 1 | {'most_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'erp kw_3': 3, '60_4': 4} | {'most_eq_0': 'most_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'erp kw_3': 'erp kw', '60_4': '60'} | {'most_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'erp kw_3': [0], '60_4': [0]} | ['program', 'frequency mhz', 'erp kw', 'polarisation', 'antenna diagram around ( nd ) / directional ( d )'] | [['rmf fm', '93 , 00', '60', 'horizontal', 'nd'], ['94 , 5 roxy fm', '94 , 50', '0 , 50', 'horizontal', 'd'], ['eska rock', '95 , 50', '1', 'horizontal', 'd'], ['polskie radio program i', '97 , 90', '60', 'horizontal', 'nd'], ['radio rezonans', '99 , 10', '0 , 30', 'horizontal', 'd'], ['polskie radio program iii', '99 , 70', '60', 'horizontal', 'nd'], ['polskie radio katowice', '102 , 20', '60', 'horizontal', 'nd'], ['radio maryja', '103 , 70', '3', 'horizontal', 'd'], ['polskie radio program ii', '105 , 60', '60', 'horizontal', 'nd'], ['radio em', '107 , 60', '60', 'horizontal', 'nd']] |
list of songs in rock band | https://en.wikipedia.org/wiki/List_of_songs_in_Rock_Band | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14160327-3.html.csv | count | two of the songs were from the decade of the 1970s . | {'scope': 'all', 'criterion': 'equal', 'value': '1970s', 'result': '2', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'decade', '1970s'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose decade record fuzzily matches to 1970s .', 'tostr': 'filter_eq { all_rows ; decade ; 1970s }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; decade ; 1970s } }', 'tointer': 'select the rows whose decade record fuzzily matches to 1970s . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; decade ; 1970s } } ; 2 } = true', 'tointer': 'select the rows whose decade record fuzzily matches to 1970s . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; decade ; 1970s } } ; 2 } = true | select the rows whose decade record fuzzily matches to 1970s . 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, 'decade_5': 5, '1970s_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', 'decade_5': 'decade', '1970s_6': '1970s', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'decade_5': [0], '1970s_6': [0], '2_7': [2]} | ['song title', 'artist', 'decade', 'genre', 'family friendly'] | [['dirty little secret', 'all american rejects the all american rejects', '2000s', 'emo', 'yes'], ["do n't look back in anger", 'oasis', '1990s', 'rock', 'yes'], ['roam', "b - 52 's the b - 52 's", '1980s', 'pop / rock', 'yes'], ['rockaway beach', 'ramones', '1970s', 'punk', 'yes'], ['roxanne', 'police the police', '1970s', 'pop / rock', 'no']] |
2007 - 08 new orleans hornets season | https://en.wikipedia.org/wiki/2007%E2%80%9308_New_Orleans_Hornets_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-11963536-11.html.csv | comparative | the may 5th game of the 2007-08 new orleans hornet 's season had a smaller crowd size than the game played on may 8th . | {'row_1': '2', 'row_2': '3', 'col': '8', 'col_other': '2', 'relation': 'less', 'record_mentioned': 'yes', 'diff_result': None} | {'func': 'and', 'args': [{'func': 'less', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', 'may 5'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose date record fuzzily matches to may 5 .', 'tostr': 'filter_eq { all_rows ; date ; may 5 }'}, 'location attendance'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; date ; may 5 } ; location attendance }', 'tointer': 'select the rows whose date record fuzzily matches to may 5 . take the location attendance record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', 'may 8'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose date record fuzzily matches to may 8 .', 'tostr': 'filter_eq { all_rows ; date ; may 8 }'}, 'location attendance'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; date ; may 8 } ; location attendance }', 'tointer': 'select the rows whose date record fuzzily matches to may 8 . take the location attendance record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; date ; may 5 } ; location attendance } ; hop { filter_eq { all_rows ; date ; may 8 } ; location attendance } }', 'tointer': 'select the rows whose date record fuzzily matches to may 5 . take the location attendance record of this row . select the rows whose date record fuzzily matches to may 8 . take the location attendance record of this row . the first record is less than the second record .'}, {'func': 'and', 'args': [{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', 'may 5'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose date record fuzzily matches to may 5 .', 'tostr': 'filter_eq { all_rows ; date ; may 5 }'}, 'location attendance'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; date ; may 5 } ; location attendance }', 'tointer': 'select the rows whose date record fuzzily matches to may 5 . take the location attendance record of this row .'}, 'new orleans arena 17927'], 'result': True, 'ind': 5, 'tostr': 'eq { hop { filter_eq { all_rows ; date ; may 5 } ; location attendance } ; new orleans arena 17927 }', 'tointer': 'the location attendance record of the first row is new orleans arena 17927 .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', 'may 8'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose date record fuzzily matches to may 8 .', 'tostr': 'filter_eq { all_rows ; date ; may 8 }'}, 'location attendance'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; date ; may 8 } ; location attendance }', 'tointer': 'select the rows whose date record fuzzily matches to may 8 . take the location attendance record of this row .'}, 'at & t center 18797'], 'result': True, 'ind': 6, 'tostr': 'eq { hop { filter_eq { all_rows ; date ; may 8 } ; location attendance } ; at & t center 18797 }', 'tointer': 'the location attendance record of the second row is at & t center 18797 .'}], 'result': True, 'ind': 7, 'tostr': 'and { eq { hop { filter_eq { all_rows ; date ; may 5 } ; location attendance } ; new orleans arena 17927 } ; eq { hop { filter_eq { all_rows ; date ; may 8 } ; location attendance } ; at & t center 18797 } }', 'tointer': 'the location attendance record of the first row is new orleans arena 17927 . the location attendance record of the second row is at & t center 18797 .'}], 'result': True, 'ind': 8, 'tostr': 'and { less { hop { filter_eq { all_rows ; date ; may 5 } ; location attendance } ; hop { filter_eq { all_rows ; date ; may 8 } ; location attendance } } ; and { eq { hop { filter_eq { all_rows ; date ; may 5 } ; location attendance } ; new orleans arena 17927 } ; eq { hop { filter_eq { all_rows ; date ; may 8 } ; location attendance } ; at & t center 18797 } } } = true', 'tointer': 'select the rows whose date record fuzzily matches to may 5 . take the location attendance record of this row . select the rows whose date record fuzzily matches to may 8 . take the location attendance record of this row . the first record is less than the second record . the location attendance record of the first row is new orleans arena 17927 . the location attendance record of the second row is at & t center 18797 .'} | and { less { hop { filter_eq { all_rows ; date ; may 5 } ; location attendance } ; hop { filter_eq { all_rows ; date ; may 8 } ; location attendance } } ; and { eq { hop { filter_eq { all_rows ; date ; may 5 } ; location attendance } ; new orleans arena 17927 } ; eq { hop { filter_eq { all_rows ; date ; may 8 } ; location attendance } ; at & t center 18797 } } } = true | select the rows whose date record fuzzily matches to may 5 . take the location attendance record of this row . select the rows whose date record fuzzily matches to may 8 . take the location attendance record of this row . the first record is less than the second record . the location attendance record of the first row is new orleans arena 17927 . the location attendance record of the second row is at & t center 18797 . | 13 | 9 | {'and_8': 8, 'result_9': 9, 'less_4': 4, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_10': 10, 'date_11': 11, 'may 5_12': 12, 'location attendance_13': 13, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_14': 14, 'date_15': 15, 'may 8_16': 16, 'location attendance_17': 17, 'and_7': 7, 'str_eq_5': 5, 'new orleans arena 17927_18': 18, 'str_eq_6': 6, 'at&t center 18797_19': 19} | {'and_8': 'and', 'result_9': 'true', 'less_4': 'less', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_10': 'all_rows', 'date_11': 'date', 'may 5_12': 'may 5', 'location attendance_13': 'location attendance', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_14': 'all_rows', 'date_15': 'date', 'may 8_16': 'may 8', 'location attendance_17': 'location attendance', 'and_7': 'and', 'str_eq_5': 'str_eq', 'new orleans arena 17927_18': 'new orleans arena 17927', 'str_eq_6': 'str_eq', 'at&t center 18797_19': 'at & t center 18797'} | {'and_8': [9], 'result_9': [], 'less_4': [8], 'str_hop_2': [4, 5], 'filter_str_eq_0': [2], 'all_rows_10': [0], 'date_11': [0], 'may 5_12': [0], 'location attendance_13': [2], 'str_hop_3': [4, 6], 'filter_str_eq_1': [3], 'all_rows_14': [1], 'date_15': [1], 'may 8_16': [1], 'location attendance_17': [3], 'and_7': [8], 'str_eq_5': [7], 'new orleans arena 17927_18': [5], 'str_eq_6': [7], 'at&t center 18797_19': [6]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'series'] | [['1', 'may 3', 'san antonio', '101 - 82', 'west ( 30 )', 'chandler ( 15 )', 'paul ( 13 )', 'new orleans arena 18040', '1 - 0'], ['2', 'may 5', 'san antonio', '102 - 84', 'paul ( 30 )', 'chandler ( 11 )', 'paul ( 12 )', 'new orleans arena 17927', '2 - 0'], ['3', 'may 8', 'san antonio', '99 - 110', 'paul ( 35 )', 'west ( 12 )', 'paul ( 9 )', 'at & t center 18797', '2 - 1'], ['4', 'may 11', 'san antonio', '80 - 100', 'paul ( 23 )', 'armstrong , paul ( 6 )', 'paul ( 5 )', 'at & t center 18797', '2 - 2'], ['5', 'may 13', 'san antonio', '101 - 79', 'west ( 38 )', 'west ( 14 )', 'paul ( 14 )', 'new orleans arena 18246', '3 - 2'], ['6', 'may 15', 'san antonio', '80 - 99', 'paul ( 21 )', 'five - way tie ( 6 )', 'paul ( 8 )', 'at & t center 18797', '3 - 3']] |
united states house of representatives elections , 1954 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1954 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1342013-42.html.csv | comparative | homer thornberry was first elected to office before john dowdy . | {'row_1': '9', 'row_2': '7', 'col': '4', 'col_other': '2', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'incumbent', 'homer thornberry'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose incumbent record fuzzily matches to homer thornberry .', 'tostr': 'filter_eq { all_rows ; incumbent ; homer thornberry }'}, 'first elected'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; incumbent ; homer thornberry } ; first elected }', 'tointer': 'select the rows whose incumbent record fuzzily matches to homer thornberry . take the first elected record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'incumbent', 'john dowdy'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose incumbent record fuzzily matches to john dowdy .', 'tostr': 'filter_eq { all_rows ; incumbent ; john dowdy }'}, 'first elected'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; incumbent ; john dowdy } ; first elected }', 'tointer': 'select the rows whose incumbent record fuzzily matches to john dowdy . take the first elected record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; incumbent ; homer thornberry } ; first elected } ; hop { filter_eq { all_rows ; incumbent ; john dowdy } ; first elected } } = true', 'tointer': 'select the rows whose incumbent record fuzzily matches to homer thornberry . take the first elected record of this row . select the rows whose incumbent record fuzzily matches to john dowdy . take the first elected record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; incumbent ; homer thornberry } ; first elected } ; hop { filter_eq { all_rows ; incumbent ; john dowdy } ; first elected } } = true | select the rows whose incumbent record fuzzily matches to homer thornberry . take the first elected record of this row . select the rows whose incumbent record fuzzily matches to john dowdy . take the first elected 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, 'incumbent_7': 7, 'homer thornberry_8': 8, 'first elected_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'incumbent_11': 11, 'john dowdy_12': 12, 'first elected_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', 'incumbent_7': 'incumbent', 'homer thornberry_8': 'homer thornberry', 'first elected_9': 'first elected', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'incumbent_11': 'incumbent', 'john dowdy_12': 'john dowdy', 'first elected_13': 'first elected'} | {'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'incumbent_7': [0], 'homer thornberry_8': [0], 'first elected_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'incumbent_11': [1], 'john dowdy_12': [1], 'first elected_13': [3]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['texas 1', 'wright patman', 'democratic', '1928', 're - elected', 'wright patman ( d ) unopposed'], ['texas 2', 'jack brooks', 'democratic', '1952', 're - elected', 'jack brooks ( d ) unopposed'], ['texas 3', 'brady p gentry', 'democratic', '1952', 're - elected', 'brady p gentry ( d ) unopposed'], ['texas 4', 'sam rayburn', 'democratic', '1912', 're - elected', 'sam rayburn ( d ) unopposed'], ['texas 5', 'joseph franklin wilson', 'democratic', '1946', 'retired republican gain', 'bruce r alger ( r ) 52.9 % wallace savage ( d ) 47.1 %'], ['texas 6', 'olin e teague', 'democratic', '1946', 're - elected', 'olin e teague ( d ) unopposed'], ['texas 7', 'john dowdy', 'democratic', '1952', 're - elected', 'john dowdy ( d ) unopposed'], ['texas 9', 'clark w thompson', 'democratic', '1947', 're - elected', 'clark w thompson ( d ) unopposed'], ['texas 10', 'homer thornberry', 'democratic', '1948', 're - elected', 'homer thornberry ( d ) unopposed'], ['texas 11', 'william r poage', 'democratic', '1936', 're - elected', 'william r poage ( d ) unopposed'], ['texas 12', 'wingate h lucas', 'democratic', '1946', 'lost renomination democratic hold', 'jim wright ( d ) unopposed'], ['texas 13', 'frank n ikard', 'democratic', '1951', 're - elected', 'frank n ikard ( d ) unopposed'], ['texas 14', 'john e lyle , jr', 'democratic', '1944', 'retired democratic hold', 'john j bell ( d ) 93.8 % d c dewitt ( r ) 6.2 %'], ['texas 15', 'lloyd bentsen', 'democratic', '1948', 'retired democratic hold', 'joe m kilgore ( d ) unopposed'], ['texas 16', 'kenneth m regan', 'democratic', '1947', 'lost renomination democratic hold', 'j t rutherford ( d ) unopposed'], ['texas 17', 'omar burleson', 'democratic', '1946', 're - elected', 'omar burleson ( d ) unopposed'], ['texas 19', 'george h mahon', 'democratic', '1934', 're - elected', 'george h mahon ( d ) unopposed'], ['texas 20', 'paul j kilday', 'democratic', '1938', 're - elected', 'paul j kilday ( d ) unopposed'], ['texas 21', 'o c fisher', 'democratic', '1942', 're - elected', 'o c fisher ( d ) unopposed']] |
united states house of representatives elections , 1936 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1936 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1342315-4.html.csv | majority | all incumbents of the 1936 house of representatives elections were from the democratic party . | {'scope': 'all', 'col': '3', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'democratic', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'party', 'democratic'], 'result': True, 'ind': 0, 'tointer': 'for the party records of all rows , all of them fuzzily match to democratic .', 'tostr': 'all_eq { all_rows ; party ; democratic } = true'} | all_eq { all_rows ; party ; democratic } = true | for the party records of all rows , all of them fuzzily match to democratic . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'party_3': 3, 'democratic_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'party_3': 'party', 'democratic_4': 'democratic'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'party_3': [0], 'democratic_4': [0]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['arkansas 1', 'william j driver', 'democratic', '1920', 're - elected', 'william j driver ( d ) unopposed'], ['arkansas 2', 'john e miller', 'democratic', '1930', 're - elected', 'john e miller ( d ) unopposed'], ['arkansas 3', 'claude fuller', 'democratic', '1928', 're - elected', 'claude fuller ( d ) unopposed'], ['arkansas 4', 'william b cravens', 'democratic', '1932', 're - elected', 'william b cravens ( d ) unopposed'], ['arkansas 5', 'david d terry', 'democratic', '1933', 're - elected', 'david d terry ( d ) unopposed'], ['arkansas 6', 'john little mcclellan', 'democratic', '1934', 're - elected', 'john little mcclellan ( d ) unopposed']] |
royce alger | https://en.wikipedia.org/wiki/Royce_Alger | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14795931-2.html.csv | count | among the games when royce alger won , two of them were extreme challenges . | {'scope': 'subset', 'criterion': 'fuzzily_match', 'value': 'extreme challenge', 'result': '2', 'col': '5', 'subset': {'col': '1', 'criterion': 'equal', 'value': 'win'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'res', 'win'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; res ; win }', 'tointer': 'select the rows whose res record fuzzily matches to win .'}, 'event', 'extreme challenge'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose res record fuzzily matches to win . among these rows , select the rows whose event record fuzzily matches to extreme challenge .', 'tostr': 'filter_eq { filter_eq { all_rows ; res ; win } ; event ; extreme challenge }'}], 'result': '2', 'ind': 2, 'tostr': 'count { filter_eq { filter_eq { all_rows ; res ; win } ; event ; extreme challenge } }', 'tointer': 'select the rows whose res record fuzzily matches to win . among these rows , select the rows whose event record fuzzily matches to extreme challenge . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_eq { filter_eq { all_rows ; res ; win } ; event ; extreme challenge } } ; 2 } = true', 'tointer': 'select the rows whose res record fuzzily matches to win . among these rows , select the rows whose event record fuzzily matches to extreme challenge . the number of such rows is 2 .'} | eq { count { filter_eq { filter_eq { all_rows ; res ; win } ; event ; extreme challenge } } ; 2 } = true | select the rows whose res record fuzzily matches to win . among these rows , select the rows whose event record fuzzily matches to extreme challenge . the number of such rows is 2 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_str_eq_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'res_6': 6, 'win_7': 7, 'event_8': 8, 'extreme challenge_9': 9, '2_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_str_eq_1': 'filter_str_eq', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'res_6': 'res', 'win_7': 'win', 'event_8': 'event', 'extreme challenge_9': 'extreme challenge', '2_10': '2'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_str_eq_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'res_6': [0], 'win_7': [0], 'event_8': [1], 'extreme challenge_9': [1], '2_10': [3]} | ['res', 'record', 'opponent', 'method', 'event', 'round', 'time', 'location'] | [['loss', '3 - 2', 'eugene jackson', 'ko ( punch )', 'ufc 21', '2', '1:19', 'cedar rapids , iowa , united states'], ['win', '3 - 1', 'roberto ramirez', 'tko ( punches )', 'iowa cage fighting 1', '1', '4:48', 'iowa , united states'], ['win', '2 - 1', 'craig pumphrey', 'tko ( punches )', 'extreme challenge 10', '1', '4:15', 'des moines , iowa , united states'], ['win', '1 - 1', 'joe defuria', 'submission ( americana )', 'extreme challenge 9', '1', '1:24', 'davenport , iowa , united states'], ['loss', '0 - 1', 'enson inoue', 'technical submission ( armbar )', 'ufc 13', '1', '1:36', 'augusta , georgia , united states']] |
reykjavík international film festival | https://en.wikipedia.org/wiki/Reykjav%C3%ADk_International_Film_Festival | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11749830-1.html.csv | comparative | miloš forman received his lifetime achievement from reykjavík international film festival earlier than dario argento received his . | {'row_1': '6', 'row_2': '9', 'col': '2', 'col_other': '4', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'lifetime achievement', 'miloš forman'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose lifetime achievement record fuzzily matches to miloš forman .', 'tostr': 'filter_eq { all_rows ; lifetime achievement ; miloš forman }'}, 'dates'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; lifetime achievement ; miloš forman } ; dates }', 'tointer': 'select the rows whose lifetime achievement record fuzzily matches to miloš forman . take the dates record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'lifetime achievement', 'dario argento'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose lifetime achievement record fuzzily matches to dario argento .', 'tostr': 'filter_eq { all_rows ; lifetime achievement ; dario argento }'}, 'dates'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; lifetime achievement ; dario argento } ; dates }', 'tointer': 'select the rows whose lifetime achievement record fuzzily matches to dario argento . take the dates record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; lifetime achievement ; miloš forman } ; dates } ; hop { filter_eq { all_rows ; lifetime achievement ; dario argento } ; dates } } = true', 'tointer': 'select the rows whose lifetime achievement record fuzzily matches to miloš forman . take the dates record of this row . select the rows whose lifetime achievement record fuzzily matches to dario argento . take the dates record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; lifetime achievement ; miloš forman } ; dates } ; hop { filter_eq { all_rows ; lifetime achievement ; dario argento } ; dates } } = true | select the rows whose lifetime achievement record fuzzily matches to miloš forman . take the dates record of this row . select the rows whose lifetime achievement record fuzzily matches to dario argento . take the dates 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, 'lifetime achievement_7': 7, 'miloš forman_8': 8, 'dates_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'lifetime achievement_11': 11, 'dario argento_12': 12, 'dates_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', 'lifetime achievement_7': 'lifetime achievement', 'miloš forman_8': 'miloš forman', 'dates_9': 'dates', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'lifetime achievement_11': 'lifetime achievement', 'dario argento_12': 'dario argento', 'dates_13': 'dates'} | {'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'lifetime achievement_7': [0], 'miloš forman_8': [0], 'dates_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'lifetime achievement_11': [1], 'dario argento_12': [1], 'dates_13': [3]} | ['year', 'dates', 'discovery of the year ( golden puffin )', 'lifetime achievement', 'creative excellency', 'audience award', 'fipresci award', 'church of iceland award'] | [['2004', 'nov 17 - nov 25', 'n / a', 'n / a', 'n / a', 'n / a', 'n / a', 'n / a'], ['2005', 'sept 29 - oct 9', 'the death of mr lazarescu , cristi puiu', 'abbas kiarostami', 'n / a', "howl 's moving castle hayao miyazaki", 'n / a', 'n / a'], ['2006', 'sept 28 - oct 8', 'grbavica , jasmila žbanić', 'alexander sokurov', 'atom egoyan', 'we shall overcome niels arden oplev', 'red road andrea arnold', 'four minutes chris kraus'], ['2007', 'sept 27 - oct 7', "iska 's journey , csaba bollók", 'hanna schygulla', 'n / a', 'control anton corbijn', 'the art of crying peter schønau fog', 'the art of crying peter schønau fog'], ['2008', 'sept 25 - oct 5', 'tulpan , sergey dvortsevoy', 'costa - gavras', 'shirin neshat', 'electronica reykjavík arnar jónasson', 'home , ursula meier', 'snow aida begic'], ['2009', 'sept 17 - sept 27', 'i killed my mother xavier dolan', 'miloš forman', 'n / a', 'the gentlemen janus bragi jakobsson', 'the girl fredrik edfeldt', 'together matias armand jordal'], ['2010', 'sept 23 - oct 3', 'le quattro volte michelangelo frammartino', 'jim jarmusch', 'n / a', 'littlerock mike ott', 'le quattro volte michelangelo frammartino', 'morgen marian crisan'], ['2011', 'sept 22 - oct 2', 'twilight portrait angelina nikonova', 'béla tarr', 'lone scherfig', 'le havre aki kaurismäki', 'volcano rúnar rúnarsson', 'volcano rúnar rúnarsson'], ['2012', 'sept 27 - oct 7', 'beasts of the southern wild benh zeitlin', 'dario argento', 'susanne bier', 'queen of montreuil sólveig anspach', 'starlet sean baker', "god 's neighbours meni yaesh"]] |
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