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fiba eurobasket 2007 squads | https://en.wikipedia.org/wiki/FIBA_EuroBasket_2007_squads | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12962773-14.html.csv | aggregation | the average height of players for the fiba eurobasket 2007 squads is 1.99 . | {'scope': 'all', 'col': '2', 'type': 'average', 'result': '1.99', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'height'], 'result': '1.99', 'ind': 0, 'tostr': 'avg { all_rows ; height }'}, '1.99'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; height } ; 1.99 } = true', 'tointer': 'the average of the height record of all rows is 1.99 .'} | round_eq { avg { all_rows ; height } ; 1.99 } = true | the average of the height record of all rows is 1.99 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'height_4': 4, '1.99_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'height_4': 'height', '1.99_5': '1.99'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'height_4': [0], '1.99_5': [1]} | ['player', 'height', 'position', 'year born', 'current club'] | [['sandi čebular', '1.94', 'guard', '1986', 'unattached'], ['jaka lakovič', '1.86', 'guard', '1978', 'axa fc barcelona'], ['aleksandar ćapin', '1.86', 'guard', '1982', 'whirlpool varese'], ['goran dragić', '1.88', 'guard', '1986', 'tau cerámica'], ['rasho nesterovič', '2.14', 'center', '1976', 'toronto raptors'], ['matjaž smodiš', '2.05', 'forward', '1979', 'cska moscow'], ['uroš slokar', '2.09', 'center', '1983', 'triumph lyubertsy'], ['jaka klobučar', '1.94', 'guard', '1987', 'geoplin slovan'], ['goran jagodnik', '2.02', 'forward', '1974', 'hemofarm'], ['domen lorbek', '1.96', 'guard', '1985', 'mmt estudiantes'], ['gašper vidmar', '2.08', 'center', '1987', 'fenerbahçe ülker'], ['erazem lorbek', '2.09', 'center', '1984', 'lottomatica roma']] |
list of presidents of india by longevity | https://en.wikipedia.org/wiki/List_of_Presidents_of_India_by_longevity | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18596194-1.html.csv | superlative | ramaswamy venkataraman was the longest serving president of india , serving 6030 days . | {'scope': 'all', 'col_superlative': '6', 'row_superlative': '8', 'value_mentioned': 'yes', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'max', 'args': ['all_rows', 'length of retirement'], 'result': '6030 days', 'ind': 0, 'tostr': 'max { all_rows ; length of retirement }', 'tointer': 'the maximum length of retirement record of all rows is 6030 days .'}, '6030 days'], 'result': True, 'ind': 1, 'tostr': 'eq { max { all_rows ; length of retirement } ; 6030 days }', 'tointer': 'the maximum length of retirement record of all rows is 6030 days .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'length of retirement'], 'result': None, 'ind': 2, 'tostr': 'argmax { all_rows ; length of retirement }'}, 'president'], 'result': 'venkataraman , ramaswamy ramaswamy venkataraman', 'ind': 3, 'tostr': 'hop { argmax { all_rows ; length of retirement } ; president }'}, 'venkataraman , ramaswamy ramaswamy venkataraman'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { argmax { all_rows ; length of retirement } ; president } ; venkataraman , ramaswamy ramaswamy venkataraman }', 'tointer': 'the president record of the row with superlative length of retirement record is venkataraman , ramaswamy ramaswamy venkataraman .'}], 'result': True, 'ind': 5, 'tostr': 'and { eq { max { all_rows ; length of retirement } ; 6030 days } ; eq { hop { argmax { all_rows ; length of retirement } ; president } ; venkataraman , ramaswamy ramaswamy venkataraman } } = true', 'tointer': 'the maximum length of retirement record of all rows is 6030 days . the president record of the row with superlative length of retirement record is venkataraman , ramaswamy ramaswamy venkataraman .'} | and { eq { max { all_rows ; length of retirement } ; 6030 days } ; eq { hop { argmax { all_rows ; length of retirement } ; president } ; venkataraman , ramaswamy ramaswamy venkataraman } } = true | the maximum length of retirement record of all rows is 6030 days . the president record of the row with superlative length of retirement record is venkataraman , ramaswamy ramaswamy venkataraman . | 6 | 6 | {'and_5': 5, 'result_6': 6, 'eq_1': 1, 'max_0': 0, 'all_rows_7': 7, 'length of retirement_8': 8, '6030 days_9': 9, 'str_eq_4': 4, 'str_hop_3': 3, 'argmax_2': 2, 'all_rows_10': 10, 'length of retirement_11': 11, 'president_12': 12, 'venkataraman , ramaswamy ramaswamy venkataraman_13': 13} | {'and_5': 'and', 'result_6': 'true', 'eq_1': 'eq', 'max_0': 'max', 'all_rows_7': 'all_rows', 'length of retirement_8': 'length of retirement', '6030 days_9': '6030 days', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'argmax_2': 'argmax', 'all_rows_10': 'all_rows', 'length of retirement_11': 'length of retirement', 'president_12': 'president', 'venkataraman , ramaswamy ramaswamy venkataraman_13': 'venkataraman , ramaswamy ramaswamy venkataraman'} | {'and_5': [6], 'result_6': [], 'eq_1': [5], 'max_0': [1], 'all_rows_7': [0], 'length of retirement_8': [0], '6030 days_9': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'argmax_2': [3], 'all_rows_10': [2], 'length of retirement_11': [2], 'president_12': [3], 'venkataraman , ramaswamy ramaswamy venkataraman_13': [4]} | ['president', 'date of birth', 'date of inauguration', 'age at inauguration', 'end of term', 'length of retirement', 'date of death', 'lifespan'] | [['prasad , rajendra rajendra prasad', '1884 - 12 - 03 3 december 1884', '26 january 1950', '65 - 054 65years , 54days', '13 may 1962', '0291 days', '1963 - 02 - 28 28 february 1963', 'days ( 78years , 87days )'], ['radhakrishnan , sarvepalli sarvepalli radhakrishnan', '1888 - 09 - 05 5 september 1888', '13 may 1962', '73 - 250 73years , 250days', '13 may 1967', '2896 days', '1975 - 04 - 17 17 april 1975', 'days ( 86years , 224days )'], ['hussain , zakir zakir hussain', '1897 - 02 - 08 8 february 1897', '13 may 1967', '70 - 094 70years , 94days', '3 may 1969', '0000 n / a', '1969 - 05 - 03 3 may 1969', 'days ( 72years , 84days )'], ['giri , v v vv giri', '1894 - 08 - 10 10 august 1894', '24 august 1969', '75 - 014 75years , 14days', '24 august 1974', '2130 days', '1980 - 06 - 23 23 june 1980', 'days ( 85years , 318days )'], ['ahmed , fakhruddin fakhruddin ahmed', '1905 - 05 - 13 13 may 1905', '24 august 1974', '69 - 103 69years , 103days', '11 february 1977', '0000 n / a', '1977 - 02 - 11 11 february 1977', 'days ( 71years , 274days )'], ['reddy , neelam neelam reddy', '1913 - 05 - 19 19 may 1913', '25 july 1977', '64 - 067 64years , 67days', '25 july 1982', '5060 days', '1996 - 06 - 01 1 june 1996', 'days ( 83years , 13days )'], ['singh , zail zail singh', '1916 - 05 - 05 5 may 1916', '25 july 1982', '66 - 081 66years , 81days', '25 july 1987', '2710 days', '1994 - 12 - 25 25 december 1994', 'days ( 78years , 234days )'], ['venkataraman , ramaswamy ramaswamy venkataraman', '1910 - 12 - 04 4 december 1910', '25 july 1987', '76 - 233 76years , 233days', '25 july 1992', '6030 days', '2009 - 01 - 27 27 january 2009', 'days ( 98years , 54days )'], ['sharma , shankar shankar dayal sharma', '1918 - 08 - 19 19 august 1918', '25 july 1992', '73 - 341 73years , 341days', '25 july 1997', '0884 days', '1999 - 12 - 26 26 december 1999', 'days ( 81years , 129days )'], ['narayanan , k r kr narayanan', '1920 - 10 - 27 27 october 1920', '25 july 1997', '76 - 271 76years , 271days', '25 july 2002', '1203 days', '2005 - 11 - 09 9 november 2005', 'days ( 85years , 13days )'], ['kalam , a p j apjabdul kalam', '1931 - 10 - 15 15 october 1931', '25 july 2002', '70 - 283 70years , 283days', '25 july 2007', '0 , 2383 days', '2014 - 02 - 1', 'days ( 82years , 109days )'], ['patil , pratibha pratibha patil', '1934 - 12 - 19 19 december 1934', '25 july 2007', '72 - 218 72years , 218days', '25 july 2012', '0 , 556 days', '2014 - 02 - 1', 'days ( 79years , 44days )'], ['mukherjee , pranab pranab mukherjee', '1934 - 12 - 19 11 december 1935', '25 july 2012', '76years , 227days', 'incumbent', '0000 incumbent', '2014 - 02 - 1', 'days ( 78years , 52days )'], ['president', 'date of birth', 'date of inauguration', 'age at inauguration', 'end of term', 'length of retirement', 'date of death 25 - 7 - 2012', 'lifespan']] |
hugo duarte | https://en.wikipedia.org/wiki/Hugo_Duarte | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17446996-2.html.csv | superlative | the highest duration of a combat that hugo duarte had in his carrer was against bob schrijber . | {'scope': 'all', 'col_superlative': '7', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '3', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'time'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; time }'}, 'opponent'], 'result': 'bob schrijber', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; time } ; opponent }'}, 'bob schrijber'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; time } ; opponent } ; bob schrijber } = true', 'tointer': 'select the row whose time record of all rows is maximum . the opponent record of this row is bob schrijber .'} | eq { hop { argmax { all_rows ; time } ; opponent } ; bob schrijber } = true | select the row whose time record of all rows is maximum . the opponent record of this row is bob schrijber . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'time_5': 5, 'opponent_6': 6, 'bob schrijber_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'time_5': 'time', 'opponent_6': 'opponent', 'bob schrijber_7': 'bob schrijber'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'time_5': [0], 'opponent_6': [1], 'bob schrijber_7': [2]} | ['res', 'record', 'opponent', 'method', 'event', 'round', 'time', 'location'] | [['loss', '6 - 3', 'bob schrijber', 'tko ( punches )', '2h2h 1 - 2 hot 2 handle', '1', '3:34', 'netherlands'], ['win', '6 - 2', 'mikhail avetisyan', 'dq ( eye gouging )', 'wvc 8 - world vale tudo championship 8', '1', '1:51', 'havana beach club , aruba'], ['loss', '5 - 2', 'mark kerr', 'tko', 'pride 4', '3', '2:32', 'tokyo , japan'], ['loss', '5 - 1', 'tank abbott', 'tko ( strikes )', 'ufc 17', '1', '0:43', 'alabama , united states'], ['win', '5 - 0', 'steve seddon', 'submission ( rear naked choke )', 'wff - world fighting federation', '1', '0:31', 'alabama , united states'], ['win', '4 - 0', 'harold howard', 'submission ( punches )', 'uvf 3 - universal vale tudo fighting 3', '1', '0:29', 'tokyo , japan'], ['win', '3 - 0', 'gerry harris', 'submission ( punches )', 'uvf 2 - universal vale tudo fighting 2', '1', '0:08', 'brazil'], ['win', '2 - 0', 'dieusel berto', 'submission ( kimura )', 'uvf 1 - universal vale tudo fighting 1', '1', '1:28', 'japan'], ['win', '1 - 0', 'marcelo raul', 'submission ( strikes )', 'gcvt 2 - gaisei challenge vale tudo 2', '1', '0:20', 'brazil']] |
cyprus in the eurovision song contest 1999 | https://en.wikipedia.org/wiki/Cyprus_in_the_Eurovision_Song_Contest_1999 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11522647-1.html.csv | unique | giorgos gavriel was the only artist in the cypriot final of the eurovision song contest 1999 to get less than 100 points . | {'scope': 'all', 'row': '8', 'col': '4', 'col_other': '2', 'criterion': 'less_than', 'value': '100', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'points', '100'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose points record is less than 100 .', 'tostr': 'filter_less { all_rows ; points ; 100 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_less { all_rows ; points ; 100 } }', 'tointer': 'select the rows whose points record is less than 100 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'points', '100'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose points record is less than 100 .', 'tostr': 'filter_less { all_rows ; points ; 100 }'}, 'artist'], 'result': 'giorgos gavriel', 'ind': 2, 'tostr': 'hop { filter_less { all_rows ; points ; 100 } ; artist }'}, 'giorgos gavriel'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_less { all_rows ; points ; 100 } ; artist } ; giorgos gavriel }', 'tointer': 'the artist record of this unqiue row is giorgos gavriel .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_less { all_rows ; points ; 100 } } ; eq { hop { filter_less { all_rows ; points ; 100 } ; artist } ; giorgos gavriel } } = true', 'tointer': 'select the rows whose points record is less than 100 . there is only one such row in the table . the artist record of this unqiue row is giorgos gavriel .'} | and { only { filter_less { all_rows ; points ; 100 } } ; eq { hop { filter_less { all_rows ; points ; 100 } ; artist } ; giorgos gavriel } } = true | select the rows whose points record is less than 100 . there is only one such row in the table . the artist record of this unqiue row is giorgos gavriel . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_less_0': 0, 'all_rows_6': 6, 'points_7': 7, '100_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'artist_9': 9, 'giorgos gavriel_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_less_0': 'filter_less', 'all_rows_6': 'all_rows', 'points_7': 'points', '100_8': '100', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'artist_9': 'artist', 'giorgos gavriel_10': 'giorgos gavriel'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_less_0': [1, 2], 'all_rows_6': [0], 'points_7': [0], '100_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'artist_9': [2], 'giorgos gavriel_10': [3]} | ['draw', 'artist', 'song', 'points', 'place'] | [['1', 'marlen angelidou', "tha ' ne erotas", '225', '1'], ['2', 'riana athanasiou', 'moni', '107', '7'], ['3', 'elena tsolaki', 'aspro feggari', '116', '5'], ['4', 'christina saranti', 'adeio feggari', '102', '8'], ['5', 'stelios constantas', 'methysmeno feggari', '125', '4'], ['6', 'giorgos stamataris', 'maria', '143', '3'], ['7', 'lucas christodolou', 'an gyriseis', '113', '6'], ['8', 'giorgos gavriel', 'pios erotas glykos', '88', '9'], ['9', 'demos beke', 'tha sou edina oli mou ti zoi', '178', '2']] |
1996 in brazilian football | https://en.wikipedia.org/wiki/1996_in_Brazilian_football | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14979855-9.html.csv | unique | of the teams that did not qualify at the copa libertadores 1996 , the only one to reach the copa semifinals in copa conmebol 1996 was vasco . | {'scope': 'subset', 'row': '11', 'col': '4', 'col_other': '1,2', 'criterion': 'equal', 'value': 'semifinals', 'subset': {'col': '3', 'criterion': 'equal', 'value': 'did not qualify'}} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'supercopa sudamericana 1996', 'did not qualify'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; supercopa sudamericana 1996 ; did not qualify }', 'tointer': 'select the rows whose supercopa sudamericana 1996 record fuzzily matches to did not qualify .'}, 'copa conmebol 1996', 'semifinals'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose supercopa sudamericana 1996 record fuzzily matches to did not qualify . among these rows , select the rows whose copa conmebol 1996 record fuzzily matches to semifinals .', 'tostr': 'filter_eq { filter_eq { all_rows ; supercopa sudamericana 1996 ; did not qualify } ; copa conmebol 1996 ; semifinals }'}], 'result': True, 'ind': 2, 'tostr': 'only { filter_eq { filter_eq { all_rows ; supercopa sudamericana 1996 ; did not qualify } ; copa conmebol 1996 ; semifinals } }', 'tointer': 'select the rows whose supercopa sudamericana 1996 record fuzzily matches to did not qualify . among these rows , select the rows whose copa conmebol 1996 record fuzzily matches to semifinals . there is only one such row in the table .'}, {'func': 'and', 'args': [{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'supercopa sudamericana 1996', 'did not qualify'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; supercopa sudamericana 1996 ; did not qualify }', 'tointer': 'select the rows whose supercopa sudamericana 1996 record fuzzily matches to did not qualify .'}, 'copa conmebol 1996', 'semifinals'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose supercopa sudamericana 1996 record fuzzily matches to did not qualify . among these rows , select the rows whose copa conmebol 1996 record fuzzily matches to semifinals .', 'tostr': 'filter_eq { filter_eq { all_rows ; supercopa sudamericana 1996 ; did not qualify } ; copa conmebol 1996 ; semifinals }'}, 'team'], 'result': 'vasco', 'ind': 3, 'tostr': 'hop { filter_eq { filter_eq { all_rows ; supercopa sudamericana 1996 ; did not qualify } ; copa conmebol 1996 ; semifinals } ; team }'}, 'vasco'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { filter_eq { filter_eq { all_rows ; supercopa sudamericana 1996 ; did not qualify } ; copa conmebol 1996 ; semifinals } ; team } ; vasco }', 'tointer': 'the team record of this unqiue row is vasco .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'supercopa sudamericana 1996', 'did not qualify'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; supercopa sudamericana 1996 ; did not qualify }', 'tointer': 'select the rows whose supercopa sudamericana 1996 record fuzzily matches to did not qualify .'}, 'copa conmebol 1996', 'semifinals'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose supercopa sudamericana 1996 record fuzzily matches to did not qualify . among these rows , select the rows whose copa conmebol 1996 record fuzzily matches to semifinals .', 'tostr': 'filter_eq { filter_eq { all_rows ; supercopa sudamericana 1996 ; did not qualify } ; copa conmebol 1996 ; semifinals }'}, 'copa libertadores 1996'], 'result': 'did not qualify', 'ind': 5, 'tostr': 'hop { filter_eq { filter_eq { all_rows ; supercopa sudamericana 1996 ; did not qualify } ; copa conmebol 1996 ; semifinals } ; copa libertadores 1996 }'}, 'did not qualify'], 'result': True, 'ind': 6, 'tostr': 'eq { hop { filter_eq { filter_eq { all_rows ; supercopa sudamericana 1996 ; did not qualify } ; copa conmebol 1996 ; semifinals } ; copa libertadores 1996 } ; did not qualify }', 'tointer': 'the copa libertadores 1996 record of this unqiue row is did not qualify .'}], 'result': True, 'ind': 7, 'tostr': 'and { eq { hop { filter_eq { filter_eq { all_rows ; supercopa sudamericana 1996 ; did not qualify } ; copa conmebol 1996 ; semifinals } ; team } ; vasco } ; eq { hop { filter_eq { filter_eq { all_rows ; supercopa sudamericana 1996 ; did not qualify } ; copa conmebol 1996 ; semifinals } ; copa libertadores 1996 } ; did not qualify } }', 'tointer': 'the team record of this unqiue row is vasco . the copa libertadores 1996 record of this unqiue row is did not qualify .'}], 'result': True, 'ind': 8, 'tostr': 'and { only { filter_eq { filter_eq { all_rows ; supercopa sudamericana 1996 ; did not qualify } ; copa conmebol 1996 ; semifinals } } ; and { eq { hop { filter_eq { filter_eq { all_rows ; supercopa sudamericana 1996 ; did not qualify } ; copa conmebol 1996 ; semifinals } ; team } ; vasco } ; eq { hop { filter_eq { filter_eq { all_rows ; supercopa sudamericana 1996 ; did not qualify } ; copa conmebol 1996 ; semifinals } ; copa libertadores 1996 } ; did not qualify } } } = true', 'tointer': 'select the rows whose supercopa sudamericana 1996 record fuzzily matches to did not qualify . among these rows , select the rows whose copa conmebol 1996 record fuzzily matches to semifinals . there is only one such row in the table . the team record of this unqiue row is vasco . the copa libertadores 1996 record of this unqiue row is did not qualify .'} | and { only { filter_eq { filter_eq { all_rows ; supercopa sudamericana 1996 ; did not qualify } ; copa conmebol 1996 ; semifinals } } ; and { eq { hop { filter_eq { filter_eq { all_rows ; supercopa sudamericana 1996 ; did not qualify } ; copa conmebol 1996 ; semifinals } ; team } ; vasco } ; eq { hop { filter_eq { filter_eq { all_rows ; supercopa sudamericana 1996 ; did not qualify } ; copa conmebol 1996 ; semifinals } ; copa libertadores 1996 } ; did not qualify } } } = true | select the rows whose supercopa sudamericana 1996 record fuzzily matches to did not qualify . among these rows , select the rows whose copa conmebol 1996 record fuzzily matches to semifinals . there is only one such row in the table . the team record of this unqiue row is vasco . the copa libertadores 1996 record of this unqiue row is did not qualify . | 13 | 9 | {'and_8': 8, 'result_9': 9, 'only_2': 2, 'filter_str_eq_1': 1, 'filter_str_eq_0': 0, 'all_rows_10': 10, 'supercopa sudamericana 1996_11': 11, 'did not qualify_12': 12, 'copa conmebol 1996_13': 13, 'semifinals_14': 14, 'and_7': 7, 'str_eq_4': 4, 'str_hop_3': 3, 'team_15': 15, 'vasco_16': 16, 'str_eq_6': 6, 'str_hop_5': 5, 'copa libertadores 1996_17': 17, 'did not qualify_18': 18} | {'and_8': 'and', 'result_9': 'true', 'only_2': 'only', 'filter_str_eq_1': 'filter_str_eq', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_10': 'all_rows', 'supercopa sudamericana 1996_11': 'supercopa sudamericana 1996', 'did not qualify_12': 'did not qualify', 'copa conmebol 1996_13': 'copa conmebol 1996', 'semifinals_14': 'semifinals', 'and_7': 'and', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'team_15': 'team', 'vasco_16': 'vasco', 'str_eq_6': 'str_eq', 'str_hop_5': 'str_hop', 'copa libertadores 1996_17': 'copa libertadores 1996', 'did not qualify_18': 'did not qualify'} | {'and_8': [9], 'result_9': [], 'only_2': [8], 'filter_str_eq_1': [2, 3, 5], 'filter_str_eq_0': [1], 'all_rows_10': [0], 'supercopa sudamericana 1996_11': [0], 'did not qualify_12': [0], 'copa conmebol 1996_13': [1], 'semifinals_14': [1], 'and_7': [8], 'str_eq_4': [7], 'str_hop_3': [4], 'team_15': [3], 'vasco_16': [4], 'str_eq_6': [7], 'str_hop_5': [6], 'copa libertadores 1996_17': [5], 'did not qualify_18': [6]} | ['team', 'copa libertadores 1996', 'supercopa sudamericana 1996', 'copa conmebol 1996', 'recopa sudamericana 1996'] | [['botafogo', 'round of 16', 'did not qualify', 'did not qualify', 'n / a'], ['bragantino', 'did not qualify', 'did not qualify', 'quarterfinals', 'n / a'], ['corinthians', 'quarterfinals', 'did not qualify', 'did not qualify', 'n / a'], ['cruzeiro', 'did not qualify', 'runner - up', 'did not qualify', 'n / a'], ['flamengo', 'did not qualify', 'quarterfinals', 'did not qualify', 'n / a'], ['fluminense', 'did not qualify', 'did not qualify', 'round of 16', 'n / a'], ['grêmio', 'semifinals', 'round of 16', 'did not qualify', 'champions'], ['palmeiras', 'did not qualify', 'did not qualify', 'round of 16', 'n / a'], ['santos', 'did not qualify', 'semifinals', 'did not qualify', 'n / a'], ['são paulo', 'did not qualify', 'round of 16', 'did not qualify', 'n / a'], ['vasco', 'did not qualify', 'did not qualify', 'semifinals', 'n / a']] |
west lancashire light railway | https://en.wikipedia.org/wiki/West_Lancashire_Light_Railway | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1179778-1.html.csv | unique | no 45 is the only model in the west lancashire light railway that is a static display . | {'scope': 'all', 'row': '5', 'col': '4', 'col_other': '1', 'criterion': 'equal', 'value': 'static display', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'status', 'static display'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose status record fuzzily matches to static display .', 'tostr': 'filter_eq { all_rows ; status ; static display }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; status ; static display } }', 'tointer': 'select the rows whose status record fuzzily matches to static display . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'status', 'static display'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose status record fuzzily matches to static display .', 'tostr': 'filter_eq { all_rows ; status ; static display }'}, 'name / number'], 'result': 'no 45', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; status ; static display } ; name / number }'}, 'no 45'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; status ; static display } ; name / number } ; no 45 }', 'tointer': 'the name / number record of this unqiue row is no 45 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; status ; static display } } ; eq { hop { filter_eq { all_rows ; status ; static display } ; name / number } ; no 45 } } = true', 'tointer': 'select the rows whose status record fuzzily matches to static display . there is only one such row in the table . the name / number record of this unqiue row is no 45 .'} | and { only { filter_eq { all_rows ; status ; static display } } ; eq { hop { filter_eq { all_rows ; status ; static display } ; name / number } ; no 45 } } = true | select the rows whose status record fuzzily matches to static display . there is only one such row in the table . the name / number record of this unqiue row is no 45 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'status_7': 7, 'static display_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'name / number_9': 9, 'no 45_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'status_7': 'status', 'static display_8': 'static display', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'name / number_9': 'name / number', 'no 45_10': 'no 45'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'status_7': [0], 'static display_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'name / number_9': [2], 'no 45_10': [3]} | ['name / number', 'builder', 'type', 'status', 'notes'] | [['irish mail', 'hunslet', "0 - 4 - 0st ' alice ' class", 'operational', 'ex dinorwic slate quarry , wales'], ['joffre', 'kerr stuart', "0 - 6 - 0t + wt ' joffre ' class", 'operational', 'ex ww1 french artillery railways'], ['montalban ( 22 )', 'orenstein and koppel', '0 - 4 - 0t + wt', 'operational', 'ex minas y ferrocarril de utrillas , aragon , spain'], ['utrillas ( 21 )', 'orenstein and koppel', '0 - 4 - 0t + wt', 'operational', 'ex minas y ferrocarril de utrillas , aragon , spain'], ['no 45', 'chrzanow', "0 - 6 - 0t + wt ' las ' class", 'static display', 'ex polish 2ft gauge'], ['no47', 'henschel', '0 - 8 - 0t', 'awaiting restoration', 'ex ww1 german feldbahn'], ['no48', 'fowler', '0 - 4 - 2t', 'awaiting restoration', 'ex sena sugar estates , mozambique'], ['sybil', 'bagnall', '0 - 4 - 0st', 'awaiting restoration', 'ex dinorwic slate quarry , wales']] |
eastern states collegiate hockey league | https://en.wikipedia.org/wiki/Eastern_States_Collegiate_Hockey_League | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16382861-1.html.csv | ordinal | in the eastern states collegiate hockey league , the school that has the 2nd highest enrollment is stony brook university . | {'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', 'enrollment', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; enrollment ; 2 }'}, 'school'], 'result': 'stony brook university', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; enrollment ; 2 } ; school }'}, 'stony brook university'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; enrollment ; 2 } ; school } ; stony brook university } = true', 'tointer': 'select the row whose enrollment record of all rows is 2nd maximum . the school record of this row is stony brook university .'} | eq { hop { nth_argmax { all_rows ; enrollment ; 2 } ; school } ; stony brook university } = true | select the row whose enrollment record of all rows is 2nd maximum . the school record of this row is stony brook university . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'enrollment_5': 5, '2_6': 6, 'school_7': 7, 'stony brook university_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'enrollment_5': 'enrollment', '2_6': '2', 'school_7': 'school', 'stony brook university_8': 'stony brook university'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'enrollment_5': [0], '2_6': [0], 'school_7': [1], 'stony brook university_8': [2]} | ['school', 'location', 'founded', 'affiliation', 'enrollment', 'nickname', 'primary conference'] | [['university of delaware', 'newark , de', '1743', 'public', '19067', "fightin ' blue hens", 'colonial athletic association ( d - i )'], ['lebanon valley college', 'annville , pa', '1866', 'private / methodist', '2100', 'flying dutchmen', 'mac commonwealth conference ( d - iii )'], ['university of rhode island', 'kingston , ri', '1892', 'public', '19095', 'rams', 'atlantic 10 conference ( d - i )'], ['rutgers university', 'new brunswick , nj', '1766', 'public', '56868', 'scarlet knights', 'american athletic conference ( d - i )'], ['stony brook university', 'stony brook , ny', '1957', 'public', '23997', 'seawolves', 'america east conference ( d - i )'], ['west chester university', 'west chester , pa', '1871', 'public', '12800', 'golden rams', 'psac ( d - ii )']] |
2012 fina world swimming championships ( 25 m ) | https://en.wikipedia.org/wiki/2012_FINA_World_Swimming_Championships_%2825_m%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16913465-7.html.csv | majority | the majority of the championship records broken were in the final round of the respective events . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'final', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'round', 'final'], 'result': True, 'ind': 0, 'tointer': 'for the round records of all rows , most of them fuzzily match to final .', 'tostr': 'most_eq { all_rows ; round ; final } = true'} | most_eq { all_rows ; round ; final } = true | for the round records of all rows , most of them fuzzily match to final . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'round_3': 3, 'final_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'round_3': 'round', 'final_4': 'final'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'round_3': [0], 'final_4': [0]} | ['event', 'date', 'round', 'name', 'nationality', 'time', 'record'] | [["women 's 50 m breaststroke", '12 december', 'heats', 'rūta meilutytė', 'lithuania', '29.56', 'cr'], ["women 's 50 m breaststroke", '12 december', 'semifinal', 'rūta meilutytė', 'lithuania', '29.51', 'cr'], ["women 's 200 m butterfly", '12 december', 'final', 'katinka hosszú', 'hungary', '2:02.20', 'cr'], ["women 's 400 m medley", '12 december', 'final', 'hannah miley', 'great britain', '4:23.14', 'cr'], ["women 's 50 m breaststroke", '13 december', 'final', 'rūta meilutytė', 'lithuania', '29.44', 'cr'], ["women 's 100 m medley", '14 december', 'final', 'katinka hosszú', 'hungary', '58.49', 'cr'], ["women 's 100 m breaststroke", '15 december', 'final', 'rūta meilutytė', 'lithuania', '1:03.52', 'cr'], ["women 's 50 m backstroke", '15 december', 'semifinal', 'zhao jing', 'china', '26.11', 'cr'], ["women 's 200 m medley", '15 december', 'final', 'ye shiwen', 'china', '2:04.64', 'cr'], ["women 's 50 m backstroke", '16 december', 'final', 'zhao jing', 'china', '25.95', 'cr'], ["women 's 200 m breaststroke", '16 december', 'final', 'rikke møller pedersen', 'denmark', '2:16.08', 'cr']] |
european orienteering championships | https://en.wikipedia.org/wiki/European_Orienteering_Championships | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17760670-5.html.csv | unique | 2006 is the only year that minna kauppi won a gold medal at the european orienteering championships . | {'scope': 'all', 'row': '3', 'col': '2', 'col_other': '1', 'criterion': 'equal', 'value': 'minna kauppi', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'gold', 'minna kauppi'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose gold record fuzzily matches to minna kauppi .', 'tostr': 'filter_eq { all_rows ; gold ; minna kauppi }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; gold ; minna kauppi } }', 'tointer': 'select the rows whose gold record fuzzily matches to minna kauppi . there is only one such row in the table .'}, {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'gold', 'minna kauppi'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose gold record fuzzily matches to minna kauppi .', 'tostr': 'filter_eq { all_rows ; gold ; minna kauppi }'}, 'year'], 'result': '2006', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; gold ; minna kauppi } ; year }'}, '2006'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; gold ; minna kauppi } ; year } ; 2006 }', 'tointer': 'the year record of this unqiue row is 2006 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; gold ; minna kauppi } } ; eq { hop { filter_eq { all_rows ; gold ; minna kauppi } ; year } ; 2006 } } = true', 'tointer': 'select the rows whose gold record fuzzily matches to minna kauppi . there is only one such row in the table . the year record of this unqiue row is 2006 .'} | and { only { filter_eq { all_rows ; gold ; minna kauppi } } ; eq { hop { filter_eq { all_rows ; gold ; minna kauppi } ; year } ; 2006 } } = true | select the rows whose gold record fuzzily matches to minna kauppi . there is only one such row in the table . the year record of this unqiue row is 2006 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'gold_7': 7, 'minna kauppi_8': 8, 'eq_3': 3, 'num_hop_2': 2, 'year_9': 9, '2006_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'gold_7': 'gold', 'minna kauppi_8': 'minna kauppi', 'eq_3': 'eq', 'num_hop_2': 'num_hop', 'year_9': 'year', '2006_10': '2006'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'gold_7': [0], 'minna kauppi_8': [0], 'eq_3': [4], 'num_hop_2': [3], 'year_9': [2], '2006_10': [3]} | ['year', 'gold', 'silver', 'bronze', 'notes'] | [['2002', 'gunilla svärd', 'brigitte wolf', 'birgitte husebye', '4.5 km , 13controls'], ['2004', 'hanne staff', 'dainora alšauskaitė', 'tatiana ryabkina', '5.3 km , 21controls'], ['2006', 'minna kauppi', 'marianne andersen', 'heli jukkola', '5.679 km , 15controls'], ['2008', 'heli jukkola', 'merja rantanen', 'minna kauppi', '5.2 km , 16controls'], ['2010', 'simone niggli - luder', 'signe soes', 'lena eliasson', '5.4 km , 22controls'], ['2012', 'simone niggli - luder', 'minna kauppi', 'tatiana ryabkina', '5.19 km , 18controls']] |
david brabham | https://en.wikipedia.org/wiki/David_Brabham | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1148454-4.html.csv | unique | david brabham 's race in 1992 was the only race where he participated in the c1 class . | {'scope': 'all', 'row': '1', 'col': '4', 'col_other': '1', 'criterion': 'equal', 'value': 'c1', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'class', 'c1'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose class record fuzzily matches to c1 .', 'tostr': 'filter_eq { all_rows ; class ; c1 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; class ; c1 } }', 'tointer': 'select the rows whose class record fuzzily matches to c1 . there is only one such row in the table .'}, {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'class', 'c1'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose class record fuzzily matches to c1 .', 'tostr': 'filter_eq { all_rows ; class ; c1 }'}, 'year'], 'result': '1992', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; class ; c1 } ; year }'}, '1992'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; class ; c1 } ; year } ; 1992 }', 'tointer': 'the year record of this unqiue row is 1992 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; class ; c1 } } ; eq { hop { filter_eq { all_rows ; class ; c1 } ; year } ; 1992 } } = true', 'tointer': 'select the rows whose class record fuzzily matches to c1 . there is only one such row in the table . the year record of this unqiue row is 1992 .'} | and { only { filter_eq { all_rows ; class ; c1 } } ; eq { hop { filter_eq { all_rows ; class ; c1 } ; year } ; 1992 } } = true | select the rows whose class record fuzzily matches to c1 . there is only one such row in the table . the year record of this unqiue row is 1992 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'class_7': 7, 'c1_8': 8, 'eq_3': 3, 'num_hop_2': 2, 'year_9': 9, '1992_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'class_7': 'class', 'c1_8': 'c1', 'eq_3': 'eq', 'num_hop_2': 'num_hop', 'year_9': 'year', '1992_10': '1992'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'class_7': [0], 'c1_8': [0], 'eq_3': [4], 'num_hop_2': [3], 'year_9': [2], '1992_10': [3]} | ['year', 'team', 'co - drivers', 'class', 'laps', 'pos', 'class pos'] | [['1992', "toyota team tom 's", 'geoff lees ukyo katayama', 'c1', '192', 'dnf', 'dnf'], ['1993', 'twr jaguar racing', 'john nielsen david coulthard', 'gt', '306', 'dsq', 'dsq'], ['1996', 'gulf racing gtc racing', 'pierre - henri raphanel lindsay owen - jones', 'gt1', '335', '5th', '4th'], ['1997', 'david price racing', 'perry mccarthy doc bundy', 'gt1', '145', 'dnf', 'dnf'], ['1998', 'panoz motorsports', 'andy wallace jamie davies', 'gt1', '335', '7th', '7th'], ['1999', 'panoz motorsports', 'éric bernard butch leitzinger', 'lmp', '336', '7th', '6th'], ['2000', 'panoz motorsports', 'jan magnussen mario andretti', 'lmp900', '315', '15th', '8th'], ['2001', 'panoz motorsports', 'jan magnussen franck lagorce', 'lmp900', '85', 'dnf', 'dnf'], ['2002', 'panoz motor sports', 'jan magnussen bryan herta', 'lmp900', '90', 'dnf', 'dnf'], ['2003', 'team bentley', 'mark blundell johnny herbert', 'lmgtp', '375', '2nd', '2nd'], ['2004', 'zytek engineering , ltd', 'andy wallace hayanari shimoda', 'lmp1', '167', 'dnf', 'dnf'], ['2005', 'aston martin racing', 'stéphane sarrazin darren turner', 'gt1', '333', '9th', '3rd'], ['2006', 'russian age racing team modena', 'antonio garcía nelson piquet , jr', 'gt1', '343', '9th', '4th'], ['2007', 'aston martin racing', 'darren turner rickard rydell', 'gt1', '343', '5th', '1st'], ['2008', 'aston martin racing', 'antonio garcía darren turner', 'gt1', '344', '13th', '1st'], ['2009', 'peugeot sport total', 'marc gené alexander wurz', 'lmp1', '382', '1st', '1st'], ['2010', 'highcroft racing', 'marino franchitti marco werner', 'lmp2', '296', '25th', '9th'], ['2012', 'jrm', 'peter dumbreck karun chandhok', 'lmp1', '357', '6th', '6th']] |
luke adams | https://en.wikipedia.org/wiki/Luke_Adams | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12955561-1.html.csv | aggregation | from 1999 to 2012 , racewalker luke adams average placement in the races was 13.56 . | {'scope': 'all', 'col': '4', 'type': 'average', 'result': '13.56', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'position'], 'result': '13.56', 'ind': 0, 'tostr': 'avg { all_rows ; position }'}, '13.56'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; position } ; 13.56 } = true', 'tointer': 'the average of the position record of all rows is 13.56 .'} | round_eq { avg { all_rows ; position } ; 13.56 } = true | the average of the position record of all rows is 13.56 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'position_4': 4, '13.56_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'position_4': 'position', '13.56_5': '13.56'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'position_4': [0], '13.56_5': [1]} | ['year', 'competition', 'venue', 'position', 'notes'] | [['1999', 'world race walking cup', 'mézidon - canon , france', '55th', '20 km'], ['2002', 'world race walking cup', 'turin , italy', '29th', '50 km'], ['2002', 'commonwealth games', 'manchester , england', '2nd', '20 km'], ['2003', 'world championships', 'paris , france', '5th', '20 km'], ['2004', 'olympic games', 'athens , greece', '16th', '20 km'], ['2004', 'world race walking cup', 'naumburg , germany', '14th', '20 km'], ['2005', 'world championships', 'helsinki , finland', '10th', '20 km'], ['2006', 'commonwealth games', 'melbourne , australia', '2nd', '20 km'], ['2006', 'world race walking cup', 'la coruña , spain', '18th', '20 km'], ['2007', 'world championships', 'osaka , japan', '7th', '20 km'], ['2008', 'olympic games', 'beijing , pr china', '6th', '20 km'], ['2009', 'world championships', 'berlin , germany', '18th', '20 km'], ['2009', 'world championships', 'berlin , germany', '6th', '50 km'], ['2010', 'world race walking cup', 'chihuahua , mexico', 'dnf', '50 km'], ['2010', 'commonwealth games', 'delhi , india', '2nd', '20 km'], ['2012', 'olympic games', 'london , united kingdom', '27th', '50 km']] |
galatasaray s.k. ( superleague formula team ) | https://en.wikipedia.org/wiki/Galatasaray_S.K._%28Superleague_Formula_team%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-23293785-2.html.csv | aggregation | the galatasaray s.k. superleague formula team scored a total of 128 of their points in race 1 . | {'scope': 'all', 'col': '6', 'type': 'sum', 'result': '128', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'race 1 ( pts )'], 'result': '128', 'ind': 0, 'tostr': 'sum { all_rows ; race 1 ( pts ) }'}, '128'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; race 1 ( pts ) } ; 128 } = true', 'tointer': 'the sum of the race 1 ( pts ) record of all rows is 128 .'} | round_eq { sum { all_rows ; race 1 ( pts ) } ; 128 } = true | the sum of the race 1 ( pts ) record of all rows is 128 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'race 1 (pts)_4': 4, '128_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'race 1 (pts)_4': 'race 1 ( pts )', '128_5': '128'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'race 1 (pts)_4': [0], '128_5': [1]} | ['sf round', 'country', 'location', 'date', 'driver', 'race 1 ( pts )', 'race 2 ( pts )', 'race total ( pts )'] | [['1', 'england', 'donington park', '30 - 31 august 2008', 'alessandro pier guidi', '12', '12', '24'], ['2', 'germany', 'nürburgring', '20 - 21 september 2008', 'alessandro pier guidi', '40', '26', '90'], ['3', 'belgium', 'zolder', '4 - 5 october 2008', 'alessandro pier guidi', '10', '14', '114'], ['4', 'portugal', 'estoril circuit', '18 - 19 october 2008', 'alessandro pier guidi', '26', '40', '180'], ['5', 'italy', 'vallelunga circuit', '1 - 2 november 2008', 'alessandro pier guidi', '40', '16', '236']] |
eastern kentucky colonels basketball | https://en.wikipedia.org/wiki/Eastern_Kentucky_Colonels_basketball | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14565148-5.html.csv | comparative | the colonels basketball team won more games in 1965 than they won in 1959 . | {'row_1': '4', 'row_2': '2', 'col': '3', 'col_other': '1', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'year', '1965'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose year record fuzzily matches to 1965 .', 'tostr': 'filter_eq { all_rows ; year ; 1965 }'}, 'overall record'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; year ; 1965 } ; overall record }', 'tointer': 'select the rows whose year record fuzzily matches to 1965 . take the overall record record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'year', '1959'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose year record fuzzily matches to 1959 .', 'tostr': 'filter_eq { all_rows ; year ; 1959 }'}, 'overall record'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; year ; 1959 } ; overall record }', 'tointer': 'select the rows whose year record fuzzily matches to 1959 . take the overall record record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; year ; 1965 } ; overall record } ; hop { filter_eq { all_rows ; year ; 1959 } ; overall record } } = true', 'tointer': 'select the rows whose year record fuzzily matches to 1965 . take the overall record record of this row . select the rows whose year record fuzzily matches to 1959 . take the overall record record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; year ; 1965 } ; overall record } ; hop { filter_eq { all_rows ; year ; 1959 } ; overall record } } = true | select the rows whose year record fuzzily matches to 1965 . take the overall record record of this row . select the rows whose year record fuzzily matches to 1959 . take the overall record record of this row . the first record is greater than the second record . | 5 | 5 | {'greater_4': 4, 'result_5': 5, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'year_7': 7, '1965_8': 8, 'overall record_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'year_11': 11, '1959_12': 12, 'overall record_13': 13} | {'greater_4': 'greater', 'result_5': 'true', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'year_7': 'year', '1965_8': '1965', 'overall record_9': 'overall record', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'year_11': 'year', '1959_12': '1959', 'overall record_13': 'overall record'} | {'greater_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'year_7': [0], '1965_8': [0], 'overall record_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'year_11': [1], '1959_12': [1], 'overall record_13': [3]} | ['year', 'conference', 'overall record', 'conference record', 'coach'] | [['1953', 'ohio valley', '16 - 9', '9 - 1', 'paul s mcbrayer'], ['1959', 'ohio valley', '16 - 6', '10 - 2', 'paul s mcbrayer'], ['1961', 'ohio valley', '15 - 9', '9 - 3', 'paul s mcbrayer'], ['1965', 'ohio valley', '19 - 6', '13 - 1', 'james e baechtold'], ['1972', 'ohio valley', '15 - 11', '9 - 5', 'guy r strong'], ['1979', 'ohio valley', '21 - 8', '9 - 3', 'ed byhre'], ['total', 'total', '6', '6', '6']] |
xxl ( mylène farmer song ) | https://en.wikipedia.org/wiki/XXL_%28Myl%C3%A8ne_Farmer_song%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14562754-1.html.csv | aggregation | the average length of all the different versions of the mylène farmer song " xxl " is 5:04 . | {'scope': 'all', 'col': '2', 'type': 'average', 'result': '5:04', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'length'], 'result': '5:04', 'ind': 0, 'tostr': 'avg { all_rows ; length }'}, '5:04'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; length } ; 5:04 } = true', 'tointer': 'the average of the length record of all rows is 5:04 .'} | round_eq { avg { all_rows ; length } ; 5:04 } = true | the average of the length record of all rows is 5:04 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'length_4': 4, '5:04_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'length_4': 'length', '5:04_5': '5:04'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'length_4': [0], '5:04_5': [1]} | ['version', 'length', 'album', 'remixed by', 'year'] | [['album version', '4:45', 'anamorphosée , les mots', '-', '1995'], ['single version', '4:23', '-', 'laurent boutonnat', '1995'], ['no voice remix edit', '4:20', '-', 'laurent boutonnat , bertrand chtenet', '1995'], ['extra large remix', '5:02', '-', 'laurent boutonnat , bertrand chtenet', '1995'], ['distorded dance mix', '5:20', '-', 'laurent boutonnat , bertrand chtenet', '1995'], ['new remix edit', '4:25', '-', 'laurent boutonnat , bertrand chtenet', '1995'], ['single dance mix', '4:25', '-', 'laurent boutonnat , bertrand chtenet', '1995'], ['new remix edit ( germany )', '4:43', '-', 'laurent boutonnat , bertrand chtenet', '1995'], ['german radio edit', '3:54', '-', 'laurent boutonnat , bertrand chtenet', '1995'], ['music video', '4:22', 'music videos ii , music videos ii & iii', '-', '1995'], ['uk remix', '9:00', '-', 'richard dekkard', '1996'], ['live version ( recorded in 1996 )', '7:25', 'live à bercy', '-', '1996'], ['jxl remix', '6:06', 'remixes', 'junkie xl', '2003'], ['live version ( recorded in 2006 )', '5:28', "avant que l'ombre", '-', '2006'], ['live version ( recorded in 2009 )', '4:30', 'n degree5 on tour', '-', '2009']] |
1989 - 90 illinois fighting illini men 's basketball team | https://en.wikipedia.org/wiki/1989%E2%80%9390_Illinois_Fighting_Illini_men%27s_basketball_team | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-22824324-2.html.csv | superlative | in the 1989 - 90 illinois fighting illini men 's basketball team , kendall gill ranks the highest . | {'scope': 'all', 'col_superlative': '10', 'row_superlative': '1', 'value_mentioned': 'yes', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'max', 'args': ['all_rows', 'points'], 'result': '581', 'ind': 0, 'tostr': 'max { all_rows ; points }', 'tointer': 'the maximum points record of all rows is 581 .'}, '581'], 'result': True, 'ind': 1, 'tostr': 'eq { max { all_rows ; points } ; 581 }', 'tointer': 'the maximum points record of all rows is 581 .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'points'], 'result': None, 'ind': 2, 'tostr': 'argmax { all_rows ; points }'}, 'player'], 'result': 'kendall gill', 'ind': 3, 'tostr': 'hop { argmax { all_rows ; points } ; player }'}, 'kendall gill'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { argmax { all_rows ; points } ; player } ; kendall gill }', 'tointer': 'the player record of the row with superlative points record is kendall gill .'}], 'result': True, 'ind': 5, 'tostr': 'and { eq { max { all_rows ; points } ; 581 } ; eq { hop { argmax { all_rows ; points } ; player } ; kendall gill } } = true', 'tointer': 'the maximum points record of all rows is 581 . the player record of the row with superlative points record is kendall gill .'} | and { eq { max { all_rows ; points } ; 581 } ; eq { hop { argmax { all_rows ; points } ; player } ; kendall gill } } = true | the maximum points record of all rows is 581 . the player record of the row with superlative points record is kendall gill . | 6 | 6 | {'and_5': 5, 'result_6': 6, 'eq_1': 1, 'max_0': 0, 'all_rows_7': 7, 'points_8': 8, '581_9': 9, 'str_eq_4': 4, 'str_hop_3': 3, 'argmax_2': 2, 'all_rows_10': 10, 'points_11': 11, 'player_12': 12, 'kendall gill_13': 13} | {'and_5': 'and', 'result_6': 'true', 'eq_1': 'eq', 'max_0': 'max', 'all_rows_7': 'all_rows', 'points_8': 'points', '581_9': '581', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'argmax_2': 'argmax', 'all_rows_10': 'all_rows', 'points_11': 'points', 'player_12': 'player', 'kendall gill_13': 'kendall gill'} | {'and_5': [6], 'result_6': [], 'eq_1': [5], 'max_0': [1], 'all_rows_7': [0], 'points_8': [0], '581_9': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'argmax_2': [3], 'all_rows_10': [2], 'points_11': [2], 'player_12': [3], 'kendall gill_13': [4]} | ['player', 'games played', 'field goals', 'three pointers', 'free throws', 'rebounds', 'assists', 'blocks', 'steals', 'points'] | [['kendall gill', '29', '211', '23', '136', '143', '96', '16', '63', '581'], ['andy kaufmann', '29', '91', '22', '81', '93', '54', '5', '27', '285'], ['steve bardo', '29', '99', '28', '55', '178', '137', '14', '37', '281'], ['rodney jones', '29', '88', '0', '40', '126', '9', '18', '17', '216'], ['ervin small', '29', '75', '1', '49', '151', '12', '5', '23', '200']] |
2007 - 08 perth glory season | https://en.wikipedia.org/wiki/2007%E2%80%9308_Perth_Glory_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10866507-1.html.csv | ordinal | on 12 august 2007 , perth glory recorded the highest crowd participation of their 2007 - 08 season . | {'row': '5', 'col': '6', 'order': '1', 'col_other': '2', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'crowd', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; crowd ; 1 }'}, 'date'], 'result': '12 august 2007', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; crowd ; 1 } ; date }'}, '12 august 2007'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; crowd ; 1 } ; date } ; 12 august 2007 } = true', 'tointer': 'select the row whose crowd record of all rows is 1st maximum . the date record of this row is 12 august 2007 .'} | eq { hop { nth_argmax { all_rows ; crowd ; 1 } ; date } ; 12 august 2007 } = true | select the row whose crowd record of all rows is 1st maximum . the date record of this row is 12 august 2007 . | 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, 'date_7': 7, '12 august 2007_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', 'date_7': 'date', '12 august 2007_8': '12 august 2007'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'crowd_5': [0], '1_6': [0], 'date_7': [1], '12 august 2007_8': [2]} | ['round', 'date', 'home team', 'score', 'away team', 'crowd', 'stadium'] | [['1', '14 july 2007', 'newcastle jets', '0 - 1', 'perth glory', '2700', 'port macquarie regional stadium'], ['2', '20 july 2007', 'adelaide united', '1 - 1', 'perth glory', '3513', 'hindmarsh stadium'], ['3', '28 july 2007', 'perth glory', '2 - 1', 'melbourne victory', '2700', 'darwin football stadium'], ['sf', '4 august 2007', 'central coast mariners', '2 - 3', 'perth glory', '5967', 'bluetongue central coast stadium'], ['gf', '12 august 2007', 'adelaide united', '2 - 1', 'perth glory', '9606', 'hindmarsh stadium']] |
34th united states congress | https://en.wikipedia.org/wiki/34th_United_States_Congress | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2417308-4.html.csv | unique | josã m gallegos ( d ) was the only vacator whose change was due to a contested election on july 23 , 1856 . | {'scope': 'all', 'row': '3', 'col': '3', 'col_other': '2', 'criterion': 'equal', 'value': 'contested election', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'reason for change', 'contested election'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose reason for change record fuzzily matches to contested election .', 'tostr': 'filter_eq { all_rows ; reason for change ; contested election }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; reason for change ; contested election } }', 'tointer': 'select the rows whose reason for change record fuzzily matches to contested election . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'reason for change', 'contested election'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose reason for change record fuzzily matches to contested election .', 'tostr': 'filter_eq { all_rows ; reason for change ; contested election }'}, 'vacator'], 'result': 'josã m gallegos ( d )', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; reason for change ; contested election } ; vacator }'}, 'josã m gallegos ( d )'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; reason for change ; contested election } ; vacator } ; josã m gallegos ( d ) }', 'tointer': 'the vacator record of this unqiue row is josã m gallegos ( d ) .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; reason for change ; contested election } } ; eq { hop { filter_eq { all_rows ; reason for change ; contested election } ; vacator } ; josã m gallegos ( d ) } } = true', 'tointer': 'select the rows whose reason for change record fuzzily matches to contested election . there is only one such row in the table . the vacator record of this unqiue row is josã m gallegos ( d ) .'} | and { only { filter_eq { all_rows ; reason for change ; contested election } } ; eq { hop { filter_eq { all_rows ; reason for change ; contested election } ; vacator } ; josã m gallegos ( d ) } } = true | select the rows whose reason for change record fuzzily matches to contested election . there is only one such row in the table . the vacator record of this unqiue row is josã m gallegos ( d ) . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'reason for change_7': 7, 'contested election_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'vacator_9': 9, 'josã m gallegos ( d )_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'reason for change_7': 'reason for change', 'contested election_8': 'contested election', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'vacator_9': 'vacator', 'josã m gallegos ( d )_10': 'josã m gallegos ( d )'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'reason for change_7': [0], 'contested election_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'vacator_9': [2], 'josã m gallegos ( d )_10': [3]} | ['district', 'vacator', 'reason for change', 'successor', 'date successor seated'] | [['missouri 5th', 'john g miller ( o )', 'died may 11 , 1856', 'thomas p akers ( kn )', 'seated august 18 , 1856'], ['virginia 1st', 'thomas h bayly ( d )', 'died june 23 , 1856', 'muscoe r h garnett ( d )', 'seated december 1 , 1856'], ['new mexico territory at - large', 'josã m gallegos ( d )', 'contested election july 23 , 1856', 'miguel a otero ( d )', 'seated july 23 , 1856'], ['vermont 1st', 'james meacham ( o )', 'died august 23 , 1856', 'george t hodges ( r )', 'seated december 1 , 1856'], ['illinois 5th', 'william a richardson ( d )', 'resigned august 25 , 1856', 'jacob c davis ( d )', 'seated november 4 , 1856'], ['south carolina 4th', 'preston brooks ( d )', 'died january 28 , 1857', 'vacant', 'not filled this term'], ['new york 20th', 'orsamus b matteson ( o )', 'resigned february 27 , 1857', 'vacant', 'not filled this term'], ['new york 23rd', 'william a gilbert ( o )', 'resigned february 27 , 1857', 'vacant', 'not filled this term']] |
vern schuppan | https://en.wikipedia.org/wiki/Vern_Schuppan | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1235700-2.html.csv | count | for vern schuppan , there were two occasions where his chassis was wildcat . | {'scope': 'all', 'criterion': 'equal', 'value': 'wildcat', 'result': '2', 'col': '2', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'chassis', 'wildcat'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose chassis record fuzzily matches to wildcat .', 'tostr': 'filter_eq { all_rows ; chassis ; wildcat }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; chassis ; wildcat } }', 'tointer': 'select the rows whose chassis record fuzzily matches to wildcat . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; chassis ; wildcat } } ; 2 } = true', 'tointer': 'select the rows whose chassis record fuzzily matches to wildcat . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; chassis ; wildcat } } ; 2 } = true | select the rows whose chassis record fuzzily matches to wildcat . 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, 'chassis_5': 5, 'wildcat_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', 'chassis_5': 'chassis', 'wildcat_6': 'wildcat', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'chassis_5': [0], 'wildcat_6': [0], '2_7': [2]} | ['year', 'chassis', 'engine', 'start', 'finish'] | [['1976', 'eagle', 'offy', '17th', '18th'], ['1977', 'wildcat', 'offy', 'dnq', 'dnq'], ['1979', 'wildcat', 'dgs', '22nd', '21st'], ['1981', 'mclaren', 'cosworth', '18th', '3rd'], ['1982', 'penske', 'cosworth', 'dnq', 'dnq']] |
list of ngc objects ( 5001 - 6000 ) | https://en.wikipedia.org/wiki/List_of_NGC_objects_%285001%E2%80%936000%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11051845-5.html.csv | count | ursa major has a total of 3 ngc objects . | {'scope': 'all', 'criterion': 'equal', 'value': 'ursa major', 'result': '3', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'constellation', 'ursa major'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose constellation record fuzzily matches to ursa major .', 'tostr': 'filter_eq { all_rows ; constellation ; ursa major }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; constellation ; ursa major } }', 'tointer': 'select the rows whose constellation record fuzzily matches to ursa major . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; constellation ; ursa major } } ; 3 } = true', 'tointer': 'select the rows whose constellation record fuzzily matches to ursa major . the number of such rows is 3 .'} | eq { count { filter_eq { all_rows ; constellation ; ursa major } } ; 3 } = true | select the rows whose constellation record fuzzily matches to ursa major . 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, 'constellation_5': 5, 'ursa major_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', 'constellation_5': 'constellation', 'ursa major_6': 'ursa major', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'constellation_5': [0], 'ursa major_6': [0], '3_7': [2]} | ['ngc number', 'object type', 'constellation', 'right ascension ( j2000 )', 'declination ( j2000 )', 'apparent magnitude'] | [['5408', 'irregular galaxy', 'centaurus', '14h03 m21 .0 s', 'degree22 ′ 44 ″', '14.0'], ['5457', 'spiral galaxy', 'ursa major', '14h03 m12 .5 s', 'degree20 ′ 53 ″', '8.7'], ['5466', 'globular cluster', 'boötes', '14h05 m27 .4 s', 'degree32 ′ 04 ″', '10.5'], ['5474', 'spiral galaxy', 'ursa major', '14h05 m01 .5 s', 'degree39 ′ 45 ″', '11.9'], ['5477', 'irregular galaxy', 'ursa major', '14h05 m33 .1 s', 'degree27 ′ 40 ″', '14.5']] |
international wrestling association | https://en.wikipedia.org/wiki/International_Wrestling_Association | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1272033-1.html.csv | majority | the majority of international wrestling association championships were won in bayamón , puerto rico . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'bayamón , puerto rico', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'location', 'bayamón , puerto rico'], 'result': True, 'ind': 0, 'tointer': 'for the location records of all rows , most of them fuzzily match to bayamón , puerto rico .', 'tostr': 'most_eq { all_rows ; location ; bayamón , puerto rico } = true'} | most_eq { all_rows ; location ; bayamón , puerto rico } = true | for the location records of all rows , most of them fuzzily match to bayamón , puerto rico . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'location_3': 3, 'bayamón , puerto rico_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'location_3': 'location', 'bayamón , puerto rico_4': 'bayamón , puerto rico'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'location_3': [0], 'bayamón , puerto rico_4': [0]} | ['championship', 'champion ( s )', 'previous champion ( s )', 'date won', 'location'] | [['iwa undisputed world heavyweight championship', 'bonecrusher', 'jay - cobs', 'january 29 , 2012', 'bayamón , puerto rico'], ['iwa intercontinental heavyweight championship', 'chris angel', 'diabólico', 'december 5 , 2010', 'bayamón , puerto rico'], ['iwa caribbean heavyweight championship', 'xix xavant', 'vacant', 'october 16 , 2010', 'aguas buenas , puerto rico'], ['iwa puerto rico heavyweight championship', 'noel rodríguez', 'vacant', 'december 5 , 2010', 'bayamón , puerto rico'], ['iwa world tag team championship', 'atomo & sonico', 'rick stanley & dennis rivera', 'november 20 , 2010', 'bayamón , puerto rico'], ["iwa world women 's championship", 'vacant', 'genesis', 'july 7 , 2010', 'bayamón , puerto rico'], ['iwa xtreme combat division championship', 'havok', 'lash', 'october 16 , 2010', 'bayamón , puerto rico']] |
thomaz bellucci | https://en.wikipedia.org/wiki/Thomaz_Bellucci | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17436425-8.html.csv | majority | of the tournaments thomaz bellucci played in , all of the them were on a clay surface . | {'scope': 'all', 'col': '4', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'clay', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'surface', 'clay'], 'result': True, 'ind': 0, 'tointer': 'for the surface records of all rows , all of them fuzzily match to clay .', 'tostr': 'all_eq { all_rows ; surface ; clay } = true'} | all_eq { all_rows ; surface ; clay } = true | for the surface records of all rows , all of them fuzzily match to clay . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'surface_3': 3, 'clay_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'surface_3': 'surface', 'clay_4': 'clay'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'surface_3': [0], 'clay_4': [0]} | ['outcome', 'date', 'tournament', 'surface', 'opponent', 'score'] | [['runner - up', '15 july 2007', 'bogotá , colombia', 'clay', 'carlos salamanca', '6 - 4 , 3 - 6 , 2 - 6'], ['runner - up', '22 july 2007', 'cuenca , ecuador', 'clay', 'leonardo mayer', '3 - 6 , 2 - 6'], ['winner', '2 march 2008', 'santiago , chile', 'clay', 'eduardo schwank', '6 - 4 , 7 - 6 ( 7 - 3 )'], ['winner', '14 april 2008', 'florianapolis , brazil', 'clay', 'franco ferreiro', '4 - 6 , 6 - 4 , 6 - 2'], ['winner', '4 may 2008', 'tunis , tunisia', 'clay', 'dušan vemić', '6 - 2 , 6 - 4'], ['winner', '11 may 2008', 'rabat , morocco', 'clay', 'martín vassallo argüello', '6 - 2 , 6 - 2'], ['winner', '19 july 2009', 'rimini , italy', 'clay', 'juan pablo brzezicki', '3 - 6 , 6 - 3 , 6 - 1'], ['winner', '1 november 2009', 'são paulo , brazil', 'clay', 'nicolás lapentti', '6 - 4 , 6 - 4'], ['runner - up', '30 october 2010', 'são paulo , brazil', 'clay', 'marcos daniel', '1 - 6 , 6 - 3 , 3 - 6'], ['winner', '7 july 2012', 'braunschweig , germany', 'clay', 'tobias kamke', '7 - 6 ( 7 - 4 ) , 6 - 3'], ['winner', '3 november 2013', 'montevideo , uruguay', 'clay', 'diego sebastián schwartzman', '6 - 4 , 6 - 4']] |
swimming at the 2008 summer olympics - women 's 100 metre backstroke | https://en.wikipedia.org/wiki/Swimming_at_the_2008_Summer_Olympics_%E2%80%93_Women%27s_100_metre_backstroke | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18625437-5.html.csv | aggregation | in the women 's 100 metre backstroke swimming competition at the 2008 summer olympics , contenders averaged a time of 1:00.25 . | {'scope': 'all', 'col': '5', 'type': 'average', 'result': '1:00.25', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'time'], 'result': '1:00.25', 'ind': 0, 'tostr': 'avg { all_rows ; time }'}, '1:00.25'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; time } ; 1:00.25 } = true', 'tointer': 'the average of the time record of all rows is 1:00.25 .'} | round_eq { avg { all_rows ; time } ; 1:00.25 } = true | the average of the time record of all rows is 1:00.25 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'time_4': 4, '1:00.25_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'time_4': 'time', '1:00.25_5': '1:00.25'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'time_4': [0], '1:00.25_5': [1]} | ['rank', 'lane', 'name', 'nationality', 'time'] | [['1', '4', 'kirsty coventry', 'zimbabwe', '58.77'], ['2', '5', 'anastasia zuyeva', 'russia', '59.77'], ['3', '6', 'margaret hoelzer', 'united states', '59.84'], ['4', '3', 'laure manaudou', 'france', '1:00.19'], ['5', '2', 'emily seebohm', 'australia', '1:00.31'], ['6', '1', 'nina zhivanevskaya', 'spain', '1:00.50'], ['7', '7', 'antje buschschulte', 'germany', '1:01.15'], ['8', '8', 'elizabeth coster', 'new zealand', '1:01.45']] |
walter martínez ( footballer ) | https://en.wikipedia.org/wiki/Walter_Mart%C3%ADnez_%28footballer%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11982701-1.html.csv | aggregation | walter martinez scored an average of about 3.9 goals during these games . | {'scope': 'all', 'col': '6', 'type': 'average', 'result': '3.9', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'goals'], 'result': '3.9', 'ind': 0, 'tostr': 'avg { all_rows ; goals }'}, '3.9'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; goals } ; 3.9 } = true', 'tointer': 'the average of the goals record of all rows is 3.9 .'} | round_eq { avg { all_rows ; goals } ; 3.9 } = true | the average of the goals record of all rows is 3.9 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'goals_4': 4, '3.9_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'goals_4': 'goals', '3.9_5': '3.9'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'goals_4': [0], '3.9_5': [1]} | ['season', 'team', 'country', 'division', 'apps', 'goals'] | [['00 / 01', 'club deportivo victoria', 'honduras', '1', '19', '1'], ['01 / 02', 'club deportivo victoria', 'honduras', '1', '14', '2'], ['02 / 03', 'club deportivo victoria', 'honduras', '1', '10', '4'], ['03 / 04', 'club deportivo victoria', 'honduras', '1', '10', '2'], ['03 / 04', 'club deportivo marathón', 'honduras', '1', '10', '2'], ['04 / 05', 'club deportivo marathón', 'honduras', '1', '10', '1'], ['05 / 06', 'club deportivo y social vida', 'honduras', '1', '8', '3'], ['06 / 07', 'club deportivo marathón', 'honduras', '1', '18', '9'], ['2007', 'beijing guoan', 'china', '1', '28', '7'], ['2008', 'beijing guoan', 'china', '1', '16', '7'], ['08 / 09', 'deportivo alavés', 'spain', '2', '3', '0'], ['09 / 10', 'club deportivo marathón', 'honduras', '1', '23', '7'], ['2010', 'beijing guoan', 'china', '1', '12', '4'], ['2011', 'beijing guoan', 'china', '1', '25', '9'], ['2012', 'chongqing fc', 'china', '2', '29', '3'], ['2013', 'san jose earthquakes', 'usa', '1', '11', '2']] |
2008 - 09 leeds united a.f.c. season | https://en.wikipedia.org/wiki/2008%E2%80%9309_Leeds_United_A.F.C._season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17634290-7.html.csv | ordinal | snodgrass has the second highest transfer fee of all listed players . | {'row': '4', 'col': '7', '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', 'transfer fee', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; transfer fee ; 2 }'}, 'name'], 'result': 'snodgrass', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; transfer fee ; 2 } ; name }'}, 'snodgrass'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; transfer fee ; 2 } ; name } ; snodgrass } = true', 'tointer': 'select the row whose transfer fee record of all rows is 2nd maximum . the name record of this row is snodgrass .'} | eq { hop { nth_argmax { all_rows ; transfer fee ; 2 } ; name } ; snodgrass } = true | select the row whose transfer fee record of all rows is 2nd maximum . the name record of this row is snodgrass . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'transfer fee_5': 5, '2_6': 6, 'name_7': 7, 'snodgrass_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', 'transfer fee_5': 'transfer fee', '2_6': '2', 'name_7': 'name', 'snodgrass_8': 'snodgrass'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'transfer fee_5': [0], '2_6': [0], 'name_7': [1], 'snodgrass_8': [2]} | ['name', 'country', 'type', 'moving from', 'transfer window', 'ends', 'transfer fee', 'source'] | [['robinson', 'eng', 'free agent', 'swansea city', 'summer', '2011', 'free', 'leeds united yorkshire evening post'], ['sheehan', 'ire', 'transferred 1', 'leicester city', 'summer', '2011', 'undisclosed', 'leeds united'], ['showunmi', 'ngr eng', 'free agent', 'bristol city', 'summer', '2010', 'free', 'leeds united'], ['snodgrass', 'sco', 'free agent 1', 'livingston', 'summer', '2011', '35k 2', 'leeds united'], ['becchio', 'arg', 'transferred', 'mérida ud', 'summer', '2011', '300k 3', 'leeds united'], ['telfer', 'sco', 'free agent', 'bournemouth', 'summer', '2009 4', 'free', 'leeds united'], ['christie', 'eng', 'free agent', 'middlesbrough', 'summer', 'n / a 5', 'free', 'leeds united'], ['assoumani', 'mli fra', 'free agent', 'sportfreunde siegen', 'summer', '2009', 'free', 'leeds united'], ['grella', 'usa', 'free agent', 'cary clarets', 'winter', '2010', 'free', 'leeds united'], ['naylor', 'eng', 'transferred', 'ipswich town', 'winter', '2011', 'free', 'leeds united']] |
kansas jayhawk community college conference | https://en.wikipedia.org/wiki/Kansas_Jayhawk_Community_College_Conference | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12434380-1.html.csv | count | two colleges have orange & black as their school colors . | {'scope': 'all', 'criterion': 'equal', 'value': 'orange & black', 'result': '2', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'school colors', 'orange & black'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose school colors record fuzzily matches to orange & black .', 'tostr': 'filter_eq { all_rows ; school colors ; orange & black }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; school colors ; orange & black } }', 'tointer': 'select the rows whose school colors record fuzzily matches to orange & black . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; school colors ; orange & black } } ; 2 } = true', 'tointer': 'select the rows whose school colors record fuzzily matches to orange & black . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; school colors ; orange & black } } ; 2 } = true | select the rows whose school colors record fuzzily matches to orange & black . 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, 'school colors_5': 5, 'orange & black_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', 'school colors_5': 'school colors', 'orange & black_6': 'orange & black', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'school colors_5': [0], 'orange & black_6': [0], '2_7': [2]} | ['institution', 'main campus location', 'founded', 'mascot', 'school colors'] | [['allen community college', 'iola', '1923', 'red devils', 'scarlet & black'], ['coffeyville community college', 'coffeyville', '1923', 'red ravens', 'red & white'], ['cowley college', 'arkansas city', '1922', 'tigers', 'orange & black'], ['fort scott community college', 'fort scott', '1919', 'greyhounds', 'maroon & grey'], ['highland community college', 'highland', '1858', 'scotties', 'navy & gold'], ['independence community college', 'independence', '1925', 'pirates', 'navy blue & vegas gold'], ['johnson county community college', 'overland park', '1967', 'cavaliers', 'maroon & gold'], ['kansas city kansas community college', 'kansas city', '1923', 'blue devils', 'blue , red & white'], ['labette community college', 'parsons', '1923', 'cardinals', 'red & white'], ['neosho county community college', 'chanute', '1936', 'panthers', 'orange & black']] |
list of awards and nominations received by renée zellweger | https://en.wikipedia.org/wiki/List_of_awards_and_nominations_received_by_Ren%C3%A9e_Zellweger | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18747538-7.html.csv | count | two of renée zellweger 's nominations and awards , were for the film chicago . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'chicago', 'result': '2', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'film', 'chicago'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose film record fuzzily matches to chicago .', 'tostr': 'filter_eq { all_rows ; film ; chicago }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; film ; chicago } }', 'tointer': 'select the rows whose film record fuzzily matches to chicago . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; film ; chicago } } ; 2 } = true', 'tointer': 'select the rows whose film record fuzzily matches to chicago . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; film ; chicago } } ; 2 } = true | select the rows whose film record fuzzily matches to chicago . 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, 'film_5': 5, 'chicago_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', 'film_5': 'film', 'chicago_6': 'chicago', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'film_5': [0], 'chicago_6': [0], '2_7': [2]} | ['year', 'category', 'film', 'result', 'lost to'] | [['1996', 'outstanding supporting actress', 'jerry maguire', 'nominated', 'lauren bacall ( the mirror has two faces )'], ['2001', 'outstanding actress', "bridget jones 's diary", 'nominated', 'halle berry ( monsters ball )'], ['2002', 'outstanding cast', 'chicago', 'won', '-'], ['2002', 'outstanding actress', 'chicago', 'won', '-'], ['2003', 'outstanding supporting actress', 'cold mountain', 'won', '-']] |
1965 philadelphia eagles season | https://en.wikipedia.org/wiki/1965_Philadelphia_Eagles_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18843092-2.html.csv | count | in the 1965 philadelphia eagles season , when the month was december , there were two occasions when the eagles lost . | {'scope': 'subset', 'criterion': 'fuzzily_match', 'value': 'l', 'result': '2', 'col': '4', 'subset': {'col': '2', 'criterion': 'fuzzily_match', 'value': 'december'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', 'december'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; date ; december }', 'tointer': 'select the rows whose date record fuzzily matches to december .'}, 'result', 'l'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose date record fuzzily matches to december . among these rows , select the rows whose result record fuzzily matches to l .', 'tostr': 'filter_eq { filter_eq { all_rows ; date ; december } ; result ; l }'}], 'result': '2', 'ind': 2, 'tostr': 'count { filter_eq { filter_eq { all_rows ; date ; december } ; result ; l } }', 'tointer': 'select the rows whose date record fuzzily matches to december . among these rows , select the rows whose result record fuzzily matches to l . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_eq { filter_eq { all_rows ; date ; december } ; result ; l } } ; 2 } = true', 'tointer': 'select the rows whose date record fuzzily matches to december . among these rows , select the rows whose result record fuzzily matches to l . the number of such rows is 2 .'} | eq { count { filter_eq { filter_eq { all_rows ; date ; december } ; result ; l } } ; 2 } = true | select the rows whose date record fuzzily matches to december . among these rows , select the rows whose result record fuzzily matches to l . 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, 'date_6': 6, 'december_7': 7, 'result_8': 8, 'l_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', 'date_6': 'date', 'december_7': 'december', 'result_8': 'result', 'l_9': 'l', '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], 'date_6': [0], 'december_7': [0], 'result_8': [1], 'l_9': [1], '2_10': [3]} | ['week', 'date', 'opponent', 'result', 'attendance'] | [['1', 'september 19 , 1965', 'st louis cardinals', 'w 34 - 27', '54260'], ['2', 'september 26 , 1965', 'new york giants', 'l 16 - 14', '57154'], ['3', 'october 3 , 1965', 'cleveland browns', 'l 35 - 17', '60759'], ['4', 'october 10 , 1965', 'dallas cowboys', 'w 35 - 24', '56249'], ['5', 'october 17 , 1965', 'new york giants', 'l 35 - 27', '62815'], ['6', 'october 24 , 1965', 'pittsburgh steelers', 'l 20 - 14', '56515'], ['7', 'october 31 , 1965', 'washington redskins', 'l 23 - 21', '50301'], ['8', 'november 7 , 1965', 'cleveland browns', 'l 38 - 34', '72807'], ['9', 'november 14 , 1965', 'washington redskins', 'w 21 - 14', '60444'], ['10', 'november 21 , 1965', 'baltimore colts', 'l 34 - 24', '60238'], ['11', 'november 28 , 1965', 'st louis cardinals', 'w 28 - 24', '28706'], ['12', 'december 5 , 1965', 'dallas cowboys', 'l 21 - 19', '54714'], ['13', 'december 12 , 1965', 'pittsburgh steelers', 'w 47 - 13', '22002'], ['14', 'december 19 , 1965', 'detroit lions', 'l 35 - 28', '56718']] |
2010 southeastern conference football season | https://en.wikipedia.org/wiki/2010_Southeastern_Conference_football_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-26842217-10.html.csv | ordinal | the ben hill griffin stadium recorded the 2nd highest attendance during the 2010 southeastern conference . | {'row': '3', 'col': '8', 'order': '2', 'col_other': '5', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'attendance', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; attendance ; 2 }'}, 'site'], 'result': 'ben hill griffin stadium gainesville , fl', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; attendance ; 2 } ; site }'}, 'ben hill griffin stadium gainesville , fl'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; attendance ; 2 } ; site } ; ben hill griffin stadium gainesville , fl } = true', 'tointer': 'select the row whose attendance record of all rows is 2nd maximum . the site record of this row is ben hill griffin stadium gainesville , fl .'} | eq { hop { nth_argmax { all_rows ; attendance ; 2 } ; site } ; ben hill griffin stadium gainesville , fl } = true | select the row whose attendance record of all rows is 2nd maximum . the site record of this row is ben hill griffin stadium gainesville , fl . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'attendance_5': 5, '2_6': 6, 'site_7': 7, 'ben hill griffin stadium gainesville , fl_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'attendance_5': 'attendance', '2_6': '2', 'site_7': 'site', 'ben hill griffin stadium gainesville , fl_8': 'ben hill griffin stadium gainesville , fl'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'attendance_5': [0], '2_6': [0], 'site_7': [1], 'ben hill griffin stadium gainesville , fl_8': [2]} | ['date', 'time', 'visiting team', 'home team', 'site', 'broadcast', 'result', 'attendance'] | [['september 25', '12:21 pm', 'uab', 'tennessee', 'neyland stadium knoxville , tn', 'sec network', 'w 32 - 29 2ot', '95183'], ['september 25', '3:30 pm', '1 alabama', '10 arkansas', 'razorback stadium fayetteville , ar', 'cbs', 'ala 24 - 20', '76808'], ['september 25', '7:00 pm', 'kentucky', '9 florida', 'ben hill griffin stadium gainesville , fl', 'espnu', 'fla 48 - 14', '90547'], ['september 25', '7:00 pm', 'georgia', 'mississippi state', 'davis wade stadium starkville , ms', 'fsn', 'msst 24 - 12', '56721'], ['september 25', '7:30 pm', 'fresno state', 'ole miss', 'vaught - hemingway stadium oxford , ms', 'css', 'w 55 - 38', '55267'], ['september 25', '7:45 pm', '12 south carolina', '17 auburn', 'jordan - hare stadium auburn , al', 'espn', 'aub 35 - 27', '87237']] |
v - league 5th season 1st conference | https://en.wikipedia.org/wiki/V-League_5th_Season_1st_Conference | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16348031-4.html.csv | ordinal | far eastern university had the 2nd most sets lost in the v-league 1st conference 5th season . | {'row': '5', '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', 'sets lost', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; sets lost ; 2 }'}, 'team'], 'result': 'far eastern university', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; sets lost ; 2 } ; team }'}, 'far eastern university'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; sets lost ; 2 } ; team } ; far eastern university } = true', 'tointer': 'select the row whose sets lost record of all rows is 2nd maximum . the team record of this row is far eastern university .'} | eq { hop { nth_argmax { all_rows ; sets lost ; 2 } ; team } ; far eastern university } = true | select the row whose sets lost record of all rows is 2nd maximum . the team record of this row is far eastern university . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'sets lost_5': 5, '2_6': 6, 'team_7': 7, 'far eastern university_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', 'sets lost_5': 'sets lost', '2_6': '2', 'team_7': 'team', 'far eastern university_8': 'far eastern university'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'sets lost_5': [0], '2_6': [0], 'team_7': [1], 'far eastern university_8': [2]} | ['rank', 'team', 'loss', 'sets won', 'sets lost', 'percentage'] | [['1', 'san sebastian college - recoletos', '1', '27', '3', '90 %'], ['2', 'adamson university', '1', '27', '6', '81 %'], ['3', 'lyceum of the philippines university', '3', '16', '22', '42 %'], ['4', 'ateneo de manila university', '4', '16', '23', '41 %'], ['5', 'far eastern university', '6', '15', '25', '38 %'], ['6', 'college of saint benilde', '10', '4', '30', '12 %']] |
nfl europe | https://en.wikipedia.org/wiki/NFL_Europe | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-160994-4.html.csv | aggregation | the three stadiums used by rhein fire ( an nfl europe team ) had an average capacity of 56,308 . | {'scope': 'subset', 'col': '3', 'type': 'average', 'result': '56308', 'subset': {'col': '1', 'criterion': 'equal', 'value': 'rhein fire'}} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'team', 'rhein fire'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; team ; rhein fire }', 'tointer': 'select the rows whose team record fuzzily matches to rhein fire .'}, 'capacity'], 'result': '56308', 'ind': 1, 'tostr': 'avg { filter_eq { all_rows ; team ; rhein fire } ; capacity }'}, '56308'], 'result': True, 'ind': 2, 'tostr': 'round_eq { avg { filter_eq { all_rows ; team ; rhein fire } ; capacity } ; 56308 } = true', 'tointer': 'select the rows whose team record fuzzily matches to rhein fire . the average of the capacity record of these rows is 56308 .'} | round_eq { avg { filter_eq { all_rows ; team ; rhein fire } ; capacity } ; 56308 } = true | select the rows whose team record fuzzily matches to rhein fire . the average of the capacity record of these rows is 56308 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'avg_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'team_5': 5, 'rhein fire_6': 6, 'capacity_7': 7, '56308_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'avg_1': 'avg', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'team_5': 'team', 'rhein fire_6': 'rhein fire', 'capacity_7': 'capacity', '56308_8': '56308'} | {'eq_2': [3], 'result_3': [], 'avg_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'team_5': [0], 'rhein fire_6': [0], 'capacity_7': [1], '56308_8': [2]} | ['team', 'stadium', 'capacity', 'opened', 'city'] | [['amsterdam admirals', 'amsterdam arena', '51859', '1996', 'amsterdam , the netherlands'], ['amsterdam admirals', 'olympisch stadion', '31600', '1928', 'amsterdam , the netherlands'], ['barcelona dragons', 'mini estadi', '15276', '1982', 'barcelona , spain'], ['barcelona dragons', 'estadi olímpic lluís companys', '56000', '1929', 'barcelona , spain'], ['berlin thunder', 'olympiastadion', '76000', '1936', 'berlin , germany'], ['berlin thunder', 'f l jahn sportpark', '19500', '1951', 'berlin , germany'], ['cologne centurions', 'rheinenergiestadion', '50374', '1923', 'cologne , germany'], ['frankfurt galaxy', 'commerzbank - arena waldstadion ( 1925 - 2005 )', '52000', '1925', 'frankfurt , germany'], ['hamburg sea devils', 'aol arena', '55989', '2000', 'hamburg , germany'], ['london / england monarchs', 'ashton gate', '21500', '1900', 'bristol , england'], ['london / england monarchs', 'alexander stadium', '7600', '1976', 'birmingham , england'], ['london / england monarchs', 'crystal palace national sports centre', '15500', '1964', 'london , england'], ['london / england monarchs', 'stamford bridge', '42449', '1877', 'london , england'], ['london / england monarchs', 'white hart lane', '36240', '1899', 'london , england'], ['london / england monarchs', 'wembley stadium', '80000', '1923', 'london , england'], ['rhein fire', 'ltu arena', '51500', '2004', 'düsseldorf , germany'], ['rhein fire', 'arena aufschalke', '61524', '2001', 'gelsenkirchen , germany'], ['rhein fire', 'rheinstadion', '55900', '1926', 'düsseldorf , germany'], ['scottish claymores', 'hampden park', '52500', '1903', 'glasgow , scotland'], ['scottish claymores', 'murrayfield stadium', '67500', '1925', 'edinburgh , scotland']] |
volleyball at the 2006 asian games | https://en.wikipedia.org/wiki/Volleyball_at_the_2006_Asian_Games | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17877429-1.html.csv | unique | at the 2006 asian games , the only team to win 3 gold medals in volleyball was china . | {'scope': 'all', 'row': '1', 'col': '3', 'col_other': '2', 'criterion': 'equal', 'value': '3', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'gold', '3'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose gold record is equal to 3 .', 'tostr': 'filter_eq { all_rows ; gold ; 3 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; gold ; 3 } }', 'tointer': 'select the rows whose gold record is equal to 3 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'gold', '3'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose gold record is equal to 3 .', 'tostr': 'filter_eq { all_rows ; gold ; 3 }'}, 'nation'], 'result': 'china ( chn )', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; gold ; 3 } ; nation }'}, 'china ( chn )'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; gold ; 3 } ; nation } ; china ( chn ) }', 'tointer': 'the nation record of this unqiue row is china ( chn ) .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; gold ; 3 } } ; eq { hop { filter_eq { all_rows ; gold ; 3 } ; nation } ; china ( chn ) } } = true', 'tointer': 'select the rows whose gold record is equal to 3 . there is only one such row in the table . the nation record of this unqiue row is china ( chn ) .'} | and { only { filter_eq { all_rows ; gold ; 3 } } ; eq { hop { filter_eq { all_rows ; gold ; 3 } ; nation } ; china ( chn ) } } = true | select the rows whose gold record is equal to 3 . there is only one such row in the table . the nation record of this unqiue row is china ( chn ) . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'gold_7': 7, '3_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'nation_9': 9, 'china (chn)_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'gold_7': 'gold', '3_8': '3', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'nation_9': 'nation', 'china (chn)_10': 'china ( chn )'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'gold_7': [0], '3_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'nation_9': [2], 'china (chn)_10': [3]} | ['rank', 'nation', 'gold', 'silver', 'bronze', 'total'] | [['1', 'china ( chn )', '3', '2', '1', '6'], ['2', 'south korea ( kor )', '1', '0', '0', '1'], ['3', 'japan ( jpn )', '0', '2', '0', '2'], ['4', 'chinese taipei ( tpe )', '0', '0', '1', '1'], ['4', 'indonesia ( ina )', '0', '0', '1', '1'], ['4', 'saudi arabia ( ksa )', '0', '0', '1', '1'], ['total', 'total', '4', '4', '4', '12']] |
supernatural ( season 6 ) | https://en.wikipedia.org/wiki/Supernatural_%28season_6%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27892955-1.html.csv | superlative | in season 6 of supernatural , highest number of viewers was for the episode titled exile on main st. | {'scope': 'all', 'col_superlative': '8', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '3', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'us viewers ( million )'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; us viewers ( million ) }'}, 'title'], 'result': 'exile on main st', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; us viewers ( million ) } ; title }'}, 'exile on main st'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; us viewers ( million ) } ; title } ; exile on main st } = true', 'tointer': 'select the row whose us viewers ( million ) record of all rows is maximum . the title record of this row is exile on main st .'} | eq { hop { argmax { all_rows ; us viewers ( million ) } ; title } ; exile on main st } = true | select the row whose us viewers ( million ) record of all rows is maximum . the title record of this row is exile on main st . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'us viewers (million)_5': 5, 'title_6': 6, 'exile on main st_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'us viewers (million)_5': 'us viewers ( million )', 'title_6': 'title', 'exile on main st_7': 'exile on main st'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'us viewers (million)_5': [0], 'title_6': [1], 'exile on main st_7': [2]} | ['no in series', 'no in season', 'title', 'directed by', 'written by', 'original air date', 'production code', 'us viewers ( million )'] | [['105', '1', 'exile on main st', 'phil sgriccia', 'sera gamble', 'september 24 , 2010', '3x6052', '2.90'], ['106', '2', 'two and a half men', 'john showalter', 'adam glass', 'october 1 , 2010', '3x6053', '2.33'], ['107', '3', 'the third man', 'robert singer', 'ben edlund', 'october 8 , 2010', '3x6054', '2.16'], ['108', '4', "weekend at bobby 's", 'jensen ackles', 'andrew dabb & daniel loflin', 'october 15 , 2010', '3x6051', '2.84'], ['109', '5', 'live free or twihard', 'rod hardy', 'brett matthews', 'october 22 , 2010', '3x6056', '2.47'], ['111', '7', 'family matters', 'guy bee', 'andrew dabb & daniel loflin', 'november 5 , 2010', '3x6057', '2.46'], ['112', '8', 'all dogs go to heaven', 'phil sgriccia', 'adam glass', 'november 12 , 2010', '3x6058', '2.09'], ['113', '9', 'clap your hands if you believe', 'john showalter', 'ben edlund', 'november 19 , 2010', '3x6059', '1.94'], ['114', '10', 'caged heat', 'robert singer', 'brett matthews & jenny klein', 'december 3 , 2010', '3x6060', '2.15'], ['115', '11', 'appointment in samarra', 'mike rohl', 'sera gamble & robert singer', 'december 10 , 2010', '3x6061', '2.27'], ['116', '12', 'like a virgin', 'phil sgriccia', 'adam glass', 'february 4 , 2011', '3x6062', '2.25'], ['117', '13', 'unforgiven', 'david barrett', 'andrew dabb & daniel loflin', 'february 11 , 2011', '3x6063', '1.97'], ['118', '14', 'mannequin 3 : the reckoning', 'jeannot szwarc', 'eric charmelo & nicole snyder', 'february 18 , 2011', '3x6064', '2.25'], ['119', '15', 'the french mistake', 'charles beeson', 'ben edlund', 'february 25 , 2011', '3x6065', '2.18'], ['120', '16', 'and then there were none', 'mike rohl', 'brett matthews', 'march 4 , 2011', '3x6066', '2.14'], ['121', '17', 'my heart will go on', 'phil sgriccia', 'eric charmelo & nicole snyder', 'april 15 , 2011', '3x6068', '2.26'], ['123', '19', 'mommy dearest', 'john showalter', 'adam glass', 'april 29 , 2011', '3x6069', '2.01'], ['124', '20', 'the man who would be king', 'ben edlund', 'ben edlund', 'may 6 , 2011', '3x6070', '2.11'], ['125', '21', 'let it bleed', 'john showalter', 'sera gamble', 'may 20 , 2011', '3x6071', '2.02']] |
united states house of representatives elections , 1974 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1974 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1341690-20.html.csv | unique | clarence long was the only maryland incumbent in the 1974 united states house of representatives elections that was first elected in the 1960s . | {'scope': 'all', 'row': '2', 'col': '4', 'col_other': '2', 'criterion': 'fuzzily_match', 'value': '196', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'first elected', '196'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose first elected record fuzzily matches to 196 .', 'tostr': 'filter_eq { all_rows ; first elected ; 196 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; first elected ; 196 } }', 'tointer': 'select the rows whose first elected record fuzzily matches to 196 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'first elected', '196'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose first elected record fuzzily matches to 196 .', 'tostr': 'filter_eq { all_rows ; first elected ; 196 }'}, 'incumbent'], 'result': 'clarence long', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; first elected ; 196 } ; incumbent }'}, 'clarence long'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; first elected ; 196 } ; incumbent } ; clarence long }', 'tointer': 'the incumbent record of this unqiue row is clarence long .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; first elected ; 196 } } ; eq { hop { filter_eq { all_rows ; first elected ; 196 } ; incumbent } ; clarence long } } = true', 'tointer': 'select the rows whose first elected record fuzzily matches to 196 . there is only one such row in the table . the incumbent record of this unqiue row is clarence long .'} | and { only { filter_eq { all_rows ; first elected ; 196 } } ; eq { hop { filter_eq { all_rows ; first elected ; 196 } ; incumbent } ; clarence long } } = true | select the rows whose first elected record fuzzily matches to 196 . there is only one such row in the table . the incumbent record of this unqiue row is clarence long . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'first elected_7': 7, '196_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'incumbent_9': 9, 'clarence long_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'first elected_7': 'first elected', '196_8': '196', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'incumbent_9': 'incumbent', 'clarence long_10': 'clarence long'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'first elected_7': [0], '196_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'incumbent_9': [2], 'clarence long_10': [3]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['maryland 1', 'robert bauman', 'republican', '1973', 're - elected', 'robert bauman ( r ) 53.0 % thomas j hatem ( d ) 47.0 %'], ['maryland 2', 'clarence long', 'democratic', '1962', 're - elected', 'clarence long ( d ) 77.1 % john m seney ( r ) 22.9 %'], ['maryland 4', 'marjorie holt', 'republican', '1972', 're - elected', 'marjorie holt ( r ) 58.1 % fred l wineland ( d ) 41.9 %'], ['maryland 6', 'goodloe byron', 'democratic', '1970', 're - elected', 'goodloe byron ( d ) 73.7 % elton r wampler ( r ) 26.3 %'], ['maryland 7', 'parren mitchell', 'democratic', '1970', 're - elected', 'parren mitchell ( d ) unopposed']] |
dessine - moi un mouton | https://en.wikipedia.org/wiki/Dessine-moi_un_mouton | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14857820-1.html.csv | majority | the majority of the versions of dessine - moi un mouton are longer than 4:00 in length . | {'scope': 'all', 'col': '2', 'most_or_all': 'most', 'criterion': 'greater_than', 'value': '4:00', 'subset': None} | {'func': 'most_greater', 'args': ['all_rows', 'length', '4:00'], 'result': True, 'ind': 0, 'tointer': 'for the length records of all rows , most of them are greater than 4:00 .', 'tostr': 'most_greater { all_rows ; length ; 4:00 } = true'} | most_greater { all_rows ; length ; 4:00 } = true | for the length records of all rows , most of them are greater than 4:00 . | 1 | 1 | {'most_greater_0': 0, 'result_1': 1, 'all_rows_2': 2, 'length_3': 3, '4:00_4': 4} | {'most_greater_0': 'most_greater', 'result_1': 'true', 'all_rows_2': 'all_rows', 'length_3': 'length', '4:00_4': '4:00'} | {'most_greater_0': [1], 'result_1': [], 'all_rows_2': [0], 'length_3': [0], '4:00_4': [0]} | ['version', 'length', 'album', 'remixed by', 'year'] | [['album version', '4:34', 'innamoramento', '-', '1999'], ['live version ( recorded in 2000 )', '4:50 ( cd ) 6:40 ( dvd / vhs ) 4:16 ( cassette )', 'mylenium tour', '-', '2000'], ['single live version', '4:34', '-', 'laurent boutonnat', '2000'], ['live radio edit', '4:05', '-', 'laurent boutonnat', '2000'], ['world is mine remix', '4:53', '-', 'quentin and visa', '2000'], ['snakebite beat mix', '4:42', '-', 'osman and visa', '2000'], ['draw me a sheep remix', '3:53', '-', 'hot sly and visa', '2000'], ['music video', '4:56', '-', '-', '2000']] |
eurovision song contest 1970 | https://en.wikipedia.org/wiki/Eurovision_Song_Contest_1970 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-184813-1.html.csv | comparative | the song " retour " placed higher than the song " waterman . " . | {'row_1': '2', 'row_2': '1', 'col': '4', 'col_other': '3', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'song', 'retour'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose song record fuzzily matches to retour .', 'tostr': 'filter_eq { all_rows ; song ; retour }'}, 'place'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; song ; retour } ; place }', 'tointer': 'select the rows whose song record fuzzily matches to retour . take the place record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'song', 'waterman'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose song record fuzzily matches to waterman .', 'tostr': 'filter_eq { all_rows ; song ; waterman }'}, 'place'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; song ; waterman } ; place }', 'tointer': 'select the rows whose song record fuzzily matches to waterman . take the place record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; song ; retour } ; place } ; hop { filter_eq { all_rows ; song ; waterman } ; place } } = true', 'tointer': 'select the rows whose song record fuzzily matches to retour . take the place record of this row . select the rows whose song record fuzzily matches to waterman . take the place record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; song ; retour } ; place } ; hop { filter_eq { all_rows ; song ; waterman } ; place } } = true | select the rows whose song record fuzzily matches to retour . take the place record of this row . select the rows whose song record fuzzily matches to waterman . take the place 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, 'song_7': 7, 'retour_8': 8, 'place_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'song_11': 11, 'waterman_12': 12, 'place_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', 'song_7': 'song', 'retour_8': 'retour', 'place_9': 'place', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'song_11': 'song', 'waterman_12': 'waterman', 'place_13': 'place'} | {'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'song_7': [0], 'retour_8': [0], 'place_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'song_11': [1], 'waterman_12': [1], 'place_13': [3]} | ['language', 'artist', 'song', 'place', 'points'] | [['dutch', 'hearts of soul', 'waterman', '7', '7'], ['french', 'henri dès', 'retour', '4', '8'], ['italian', 'gianni morandi', 'occhi di ragazza', '8', '5'], ['slovene', 'eva sršen', 'pridi , dala ti bom cvet', '11', '4'], ['french', 'jean vallée', "viens l'oublier", '8', '5'], ['french', 'guy bonnet', 'marie - blanche', '4', '8'], ['english', 'mary hopkin', "knock , knock who 's there", '2', '26'], ['french', 'david alexandre winter', 'je suis tombé du ciel', '12', '0'], ['spanish', 'julio iglesias', 'gwendolyne', '4', '8'], ['french', 'dominique dussault', 'marlène', '8', '5'], ['german', 'katja ebstein', 'wunder gibt es immer wieder', '3', '12'], ['english', 'dana', 'all kinds of everything', '1', '32']] |
intel core | https://en.wikipedia.org/wiki/Intel_Core | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-24538587-11.html.csv | ordinal | the core i3 - 32xx brand name processor has the second highest tdp of intel core processors . | {'row': '4', 'col': '6', 'order': '2', 'col_other': '2', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'tdp', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; tdp ; 2 }'}, 'brand name ( list )'], 'result': 'core i3 - 32xx', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; tdp ; 2 } ; brand name ( list ) }'}, 'core i3 - 32xx'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; tdp ; 2 } ; brand name ( list ) } ; core i3 - 32xx } = true', 'tointer': 'select the row whose tdp record of all rows is 2nd maximum . the brand name ( list ) record of this row is core i3 - 32xx .'} | eq { hop { nth_argmax { all_rows ; tdp ; 2 } ; brand name ( list ) } ; core i3 - 32xx } = true | select the row whose tdp record of all rows is 2nd maximum . the brand name ( list ) record of this row is core i3 - 32xx . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'tdp_5': 5, '2_6': 6, 'brand name (list)_7': 7, 'core i3 - 32xx_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', 'tdp_5': 'tdp', '2_6': '2', 'brand name (list)_7': 'brand name ( list )', 'core i3 - 32xx_8': 'core i3 - 32xx'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'tdp_5': [0], '2_6': [0], 'brand name (list)_7': [1], 'core i3 - 32xx_8': [2]} | ['codename ( main article )', 'brand name ( list )', 'cores', 'l3 cache', 'socket', 'tdp', 'i / o bus'] | [['sandy bridge ( desktop )', 'core i3 - 21xx', '2', '3 mb', 'lga 1155', '65 w', 'direct media interface , integrated gpu'], ['sandy bridge ( desktop )', 'core i3 - 21xxt', '2', '3 mb', 'lga 1155', '35 w', 'direct media interface , integrated gpu'], ['ivy bridge ( desktop )', 'core i3 - 32xxt', '2', '3 mb', 'lga 1155', '35 w', 'direct media interface , integrated gpu'], ['ivy bridge ( desktop )', 'core i3 - 32xx', '2', '3 mb', 'lga 1155', '55 w', 'direct media interface , integrated gpu'], ['sandy bridge ( mobile )', 'core i3 - 2xx0 m', '2', '3 mb', 'rpga - 988b bga - 1023', '35 w', 'direct media interface , integrated gpu'], ['sandy bridge ( mobile )', 'core i3 - 2xx7 m', '2', '3 mb', 'bga - 1023', '17 w', 'direct media interface , integrated gpu'], ['ivy bridge ( mobile )', 'core i3 - 3xx0 m', '2', '3 mb', 'rpga - 988b bga - 1023', '35 w', 'direct media interface , integrated gpu'], ['ivy bridge ( mobile )', 'core i3 - 3xx7u', '2', '3 mb', 'bga - 1023', '17 w', 'direct media interface , integrated gpu']] |
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 | aggregation | the average crowd size for the 1945 vfl season was 14,000 people . | {'scope': 'all', 'col': '6', 'type': 'average', 'result': '14000', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'crowd'], 'result': '14000', 'ind': 0, 'tostr': 'avg { all_rows ; crowd }'}, '14000'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; crowd } ; 14000 } = true', 'tointer': 'the average of the crowd record of all rows is 14000 .'} | round_eq { avg { all_rows ; crowd } ; 14000 } = true | the average of the crowd record of all rows is 14000 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'crowd_4': 4, '14000_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'crowd_4': 'crowd', '14000_5': '14000'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'crowd_4': [0], '14000_5': [1]} | ['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']] |
100 metres | https://en.wikipedia.org/wiki/100_metres | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1231316-7.html.csv | aggregation | in the 100 meters race , united states recorded a total of 66.98 s. | {'scope': 'subset', 'col': '2', 'type': 'sum', 'result': '66.98 s', 'subset': {'col': '5', 'criterion': 'equal', 'value': 'united states'}} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'nation', 'united states'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; nation ; united states }', 'tointer': 'select the rows whose nation record fuzzily matches to united states .'}, 'fastest time ( s )'], 'result': '66.98 s', 'ind': 1, 'tostr': 'sum { filter_eq { all_rows ; nation ; united states } ; fastest time ( s ) }'}, '66.98 s'], 'result': True, 'ind': 2, 'tostr': 'round_eq { sum { filter_eq { all_rows ; nation ; united states } ; fastest time ( s ) } ; 66.98 s } = true', 'tointer': 'select the rows whose nation record fuzzily matches to united states . the sum of the fastest time ( s ) record of these rows is 66.98 s .'} | round_eq { sum { filter_eq { all_rows ; nation ; united states } ; fastest time ( s ) } ; 66.98 s } = true | select the rows whose nation record fuzzily matches to united states . the sum of the fastest time ( s ) record of these rows is 66.98 s . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'sum_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'nation_5': 5, 'united states_6': 6, 'fastest time (s)_7': 7, '66.98s_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'sum_1': 'sum', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'nation_5': 'nation', 'united states_6': 'united states', 'fastest time (s)_7': 'fastest time ( s )', '66.98s_8': '66.98 s'} | {'eq_2': [3], 'result_3': [], 'sum_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'nation_5': [0], 'united states_6': [0], 'fastest time (s)_7': [1], '66.98s_8': [2]} | ['rank', 'fastest time ( s )', 'wind ( m / s )', 'athlete', 'nation', 'date', 'location'] | [['1', '11.13', '+ 2.0', 'chandra cheeseborough', 'united states', '21 june 1976', 'eugene'], ['2', '11.14', '+ 1.7', 'marion jones', 'united states', '6 june 1992', 'norwalk'], ['2', '11.14', '0.5', 'angela williams', 'united states', '21 june 1997', 'edwardsville'], ['4', '11.16', '+ 1.2', 'gabrielle mayo', 'united states', '22 june 2006', 'indianapolis'], ['5', '11.17 a', '+ 0.6', 'wendy vereen', 'united states', '3 july 1983', 'colorado springs'], ['6', '11.20 a', '+ 1.2', 'raelene boyle', 'australia', '15 june 1968', 'mexico city'], ['7', '11.24', '+ 1.2', 'jeneba tarmoh', 'united states', '22 june 2006', 'indianapolis'], ['7', '11.24', '+ 0.8', 'jodie williams', 'great britain', '31 may 2010', 'bedford'], ['9', '11.26', '+ 1.4', 'grit breuer', 'east germany', '30 june 1989', 'dresden']] |
dave penney | https://en.wikipedia.org/wiki/Dave_Penney | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1175663-1.html.csv | superlative | the highest win percentage was from when there were 6 matches . | {'scope': 'all', 'col_superlative': '7', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'win %'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; win % }'}, 'matches'], 'result': '6', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; win % } ; matches }'}, '6'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; win % } ; matches } ; 6 } = true', 'tointer': 'select the row whose win % record of all rows is maximum . the matches record of this row is 6 .'} | eq { hop { argmax { all_rows ; win % } ; matches } ; 6 } = true | select the row whose win % record of all rows is maximum . the matches record of this row is 6 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'num_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'win %_5': 5, 'matches_6': 6, '6_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'num_hop_1': 'num_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'win %_5': 'win %', 'matches_6': 'matches', '6_7': '6'} | {'eq_2': [3], 'result_3': [], 'num_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'win %_5': [0], 'matches_6': [1], '6_7': [2]} | ['team', 'nation', 'from', 'matches', 'drawn', 'lost', 'win %'] | [['doncaster rovers', 'england', '22 april 2000', '6', '1', '1', '66.7'], ['doncaster rovers', 'england', '27 december 2001', '241', '62', '65', '47.3'], ['darlington', 'england', '30 october 2006', '139', '35', '44', '43.2'], ['oldham athletic', 'england', '30 april 2009', '48', '13', '22', '27.1'], ['bristol rovers', 'england', '10 january 2011', '13', '2', '9', '15.38']] |
albert county , new brunswick | https://en.wikipedia.org/wiki/Albert_County%2C_New_Brunswick | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-170958-2.html.csv | majority | most of the parishes in albert county new brunswick have a population under 1000 . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'less_than', 'value': '1000', 'subset': None} | {'func': 'most_less', 'args': ['all_rows', 'population', '1000'], 'result': True, 'ind': 0, 'tointer': 'for the population records of all rows , most of them are less than 1000 .', 'tostr': 'most_less { all_rows ; population ; 1000 } = true'} | most_less { all_rows ; population ; 1000 } = true | for the population records of all rows , most of them are less than 1000 . | 1 | 1 | {'most_less_0': 0, 'result_1': 1, 'all_rows_2': 2, 'population_3': 3, '1000_4': 4} | {'most_less_0': 'most_less', 'result_1': 'true', 'all_rows_2': 'all_rows', 'population_3': 'population', '1000_4': '1000'} | {'most_less_0': [1], 'result_1': [], 'all_rows_2': [0], 'population_3': [0], '1000_4': [0]} | ['official name', 'status', 'area km 2', 'population', 'census ranking'] | [['coverdale', 'parish', '236.15', '4401', '769 of 5008'], ['hillsborough', 'parish', '303.73', '1395', '1684 of 5008'], ['elgin', 'parish', '519.38', '968', '2124 of 5008'], ['hopewell', 'parish', '149.32', '643', '2689 of 5008'], ['harvey', 'parish', '276.84', '376', '3372 of 5008'], ['alma', 'parish', '222.79', '0', '4932 of 5008']] |
documentary film festivals | https://en.wikipedia.org/wiki/Documentary_film_festivals | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12757263-2.html.csv | superlative | the yamagata international documentary film festival was established prior to any of the other festivals . | {'scope': 'all', 'col_superlative': '2', 'row_superlative': '7', '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', 'est'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; est }'}, 'name'], 'result': 'yamagata international documentary film festival', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; est } ; name }'}, 'yamagata international documentary film festival'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmin { all_rows ; est } ; name } ; yamagata international documentary film festival } = true', 'tointer': 'select the row whose est record of all rows is minimum . the name record of this row is yamagata international documentary film festival .'} | eq { hop { argmin { all_rows ; est } ; name } ; yamagata international documentary film festival } = true | select the row whose est record of all rows is minimum . the name record of this row is yamagata international documentary film festival . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'est_5': 5, 'name_6': 6, 'yamagata international documentary film festival_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'est_5': 'est', 'name_6': 'name', 'yamagata international documentary film festival_7': 'yamagata international documentary film festival'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'est_5': [0], 'name_6': [1], 'yamagata international documentary film festival_7': [2]} | ['name', 'est', 'city', 'country', 'website'] | [['development film festival', '2005', 'chennai', 'india', 'wwwdhanorg / dff'], ['culture unplugged film festival', '2007', 'india', 'india', 'wwwcultureunpluggedcom'], ['dox box - ayyam cinema al waqe', '2008', 'damascus', 'syria', 'wwwdox - boxorg'], ['freedom film fest', '2003', 'malaysia', 'malaysia', 'freedomfilmfestkomasorg'], ['vibgyor international film festival', '2006', 'thrissur', 'india', '2009 . vibgyorfilmcom'], ['yogyakarta documentary film festival', '2002', 'yogyakarta', 'indonesia', 'wwwfestivalfilmdokumenterorg'], ['yamagata international documentary film festival', '1989', 'yamagata', 'japan', 'wwwyidffjp'], ['jeevika : asia livelihood documentary festival', '2003', 'new delhi', 'india', 'wwwjeevikaorg']] |
1926 - 27 new york rangers season | https://en.wikipedia.org/wiki/1926%E2%80%9327_New_York_Rangers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15950317-3.html.csv | count | the rangers played against the bruins two times in the 1926-27 season . | {'scope': 'all', 'criterion': 'equal', 'value': 'boston bruins', 'result': '2', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', 'boston bruins'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose opponent record fuzzily matches to boston bruins .', 'tostr': 'filter_eq { all_rows ; opponent ; boston bruins }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; opponent ; boston bruins } }', 'tointer': 'select the rows whose opponent record fuzzily matches to boston bruins . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; opponent ; boston bruins } } ; 2 } = true', 'tointer': 'select the rows whose opponent record fuzzily matches to boston bruins . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; opponent ; boston bruins } } ; 2 } = true | select the rows whose opponent record fuzzily matches to boston bruins . the number of such rows is 2 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'opponent_5': 5, 'boston bruins_6': 6, '2_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'opponent_5': 'opponent', 'boston bruins_6': 'boston bruins', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'opponent_5': [0], 'boston bruins_6': [0], '2_7': [2]} | ['game', 'december', 'opponent', 'score', 'record'] | [['6', '4', 'detroit cougars', '1 - 0', '4 - 2 - 0'], ['7', '7', 'boston bruins', '1 - 0', '5 - 2 - 0'], ['8', '12', 'boston bruins', '2 - 1 ot', '6 - 2 - 0'], ['9', '15', 'chicago black hawks', '6 - 2', '6 - 3 - 0'], ['10', '19', 'detroit cougars', '1 - 1 ot', '6 - 3 - 1'], ['11', '21', 'pittsburgh pirates', '1 - 0', '7 - 3 - 1'], ['12', '23', 'ottawa senators', '1 - 0', '7 - 4 - 1'], ['13', '26', 'new york americans', '5 - 2', '7 - 5 - 1'], ['14', '28', 'ottawa senators', '3 - 2 ot', '7 - 6 - 1']] |
2001 masters tournament | https://en.wikipedia.org/wiki/2001_Masters_Tournament | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16514667-3.html.csv | aggregation | all the players of the 2001 masters tournament had an average score of around 137 . | {'scope': 'all', 'col': '4', 'type': 'average', 'result': '136.82', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'score'], 'result': '136.82', 'ind': 0, 'tostr': 'avg { all_rows ; score }'}, '136.82'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; score } ; 136.82 } = true', 'tointer': 'the average of the score record of all rows is 136.82 .'} | round_eq { avg { all_rows ; score } ; 136.82 } = true | the average of the score record of all rows is 136.82 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'score_4': 4, '136.82_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'score_4': 'score', '136.82_5': '136.82'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'score_4': [0], '136.82_5': [1]} | ['place', 'player', 'country', 'score', 'to par'] | [['1', 'chris dimarco', 'united states', '65 + 69 = 134', '- 10'], ['t2', 'phil mickelson', 'united states', '67 + 69 = 136', '- 8'], ['t2', 'tiger woods', 'united states', '70 + 66 = 136', '- 8'], ['t4', 'ángel cabrera', 'argentina', '66 + 71 = 137', '- 7'], ['t4', 'david duval', 'united states', '71 + 66 = 137', '- 7'], ['t4', 'toshimitsu izawa', 'japan', '71 + 66 = 137', '- 7'], ['t4', 'lee janzen', 'united states', '67 + 70 = 137', '- 7'], ['t4', 'steve stricker', 'united states', '66 + 71 = 137', '- 7'], ['t9', 'mark calcavecchia', 'united states', '72 + 66 = 138', '- 6'], ['t9', 'josé maría olazábal', 'spain', '70 + 68 = 138', '- 6'], ['t9', 'kirk triplett', 'united states', '68 + 70 = 138', '- 6']] |
list of amd turion microprocessors | https://en.wikipedia.org/wiki/List_of_AMD_Turion_microprocessors | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1604940-9.html.csv | superlative | the amd turion microprocessor with the highest frequency is the turion 64 x2 tl - 68 . | {'scope': 'all', 'col_superlative': '2', 'row_superlative': '12', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'frequency'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; frequency }'}, 'model number'], 'result': 'turion 64 x2 tl - 68', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; frequency } ; model number }'}, 'turion 64 x2 tl - 68'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; frequency } ; model number } ; turion 64 x2 tl - 68 } = true', 'tointer': 'select the row whose frequency record of all rows is maximum . the model number record of this row is turion 64 x2 tl - 68 .'} | eq { hop { argmax { all_rows ; frequency } ; model number } ; turion 64 x2 tl - 68 } = true | select the row whose frequency record of all rows is maximum . the model number record of this row is turion 64 x2 tl - 68 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'frequency_5': 5, 'model number_6': 6, 'turion 64 x2 tl - 68_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'frequency_5': 'frequency', 'model number_6': 'model number', 'turion 64 x2 tl - 68_7': 'turion 64 x2 tl - 68'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'frequency_5': [0], 'model number_6': [1], 'turion 64 x2 tl - 68_7': [2]} | ['model number', 'frequency', 'l2 - cache', 'multiplier 1', 'voltage', 'socket', 'release date', 'order part number'] | [['turion 64 x2 tl - 56', '1800 mhz', '2 x 512 kb', '9x', '1.075 / 1.10 / 1.125 v', 'g socket s1 1', 'may 7 , 2007', 'tmdtl56hax5dc'], ['turion 64 x2 tl - 56', '1800 mhz', '2 x 512 kb', '9x', '1.075 / 1.10 / 1.125 v', 'socket s1 g1', 'may 7 , 2007', 'tmdtl56hax5dm'], ['turion 64 x2 tl - 58', '1900 mhz', '2 x 512 kb', '9.5 x', '1.075 / 1.10 / 1.125 v', 'socket s1 g1', 'may 7 , 2007', 'tmdtl58hax5dc'], ['turion 64 x2 tl - 58', '1900 mhz', '2 x 512 kb', '9.5 x', '1.075 / 1.10 / 1.125 v', 'socket s1 g1', 'may 7 , 2007', 'tmdtl58hax5dm'], ['turion 64 x2 tl - 60', '2000 mhz', '2 x 512 kb', '10x', '1.075 / 1.10 / 1.125 v', 'socket s1 g1', 'may 7 , 2007', 'tmdtl60hax5dc'], ['turion 64 x2 tl - 60', '2000 mhz', '2 x 512 kb', '10x', '1.075 / 1.10 / 1.125 v', 'socket s1 g1', 'may 7 , 2007', 'tmdtl60hax5dm'], ['turion 64 x2 tl - 62', '2100 mhz', '2 x 512 kb', '10.5 x', '1.075 / 1.10 / 1.125 v', 'socket s1 g1', 'may 7 , 2007', 'tmdtl62hax5dm'], ['turion 64 x2 tl - 64', '2200 mhz', '2 x 512 kb', '11x', '1.075 / 1.10 / 1.125 v', 'socket s1 g1', 'may 7 , 2007', 'tmdtl64hax5dc'], ['turion 64 x2 tl - 64', '2200 mhz', '2 x 512 kb', '11x', '1.075 / 1.10 / 1.125 v', 'socket s1 g1', 'may 7 , 2007', 'tmdtl64hax5dm'], ['turion 64 x2 tl - 66', '2300 mhz', '2 x 512 kb', '11.5 x', '1.075 / 1.10 / 1.125 v', 'socket s1 g1', 'may 7 , 2007', 'tmdtl66hax5dc'], ['turion 64 x2 tl - 66', '2300 mhz', '2 x 512 kb', '11.5 x', '1.075 / 1.10 / 1.125 v', 'socket s1 g1', 'may 7 , 2007', 'tmdtl66hax5dm'], ['turion 64 x2 tl - 68', '2400 mhz', '2 x 512 kb', '12x', '1.075 / 1.10 / 1.125 v', 'socket s1 g1', 'dec 19 , 2007', 'tmdtl68hax5dm']] |
george eaton | https://en.wikipedia.org/wiki/George_Eaton | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1228395-1.html.csv | aggregation | the engines driven by george eaton scored a total of 0 points . | {'scope': 'all', 'col': '5', 'type': 'sum', 'result': '0', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'points'], 'result': '0', 'ind': 0, 'tostr': 'sum { all_rows ; points }'}, '0'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; points } ; 0 } = true', 'tointer': 'the sum of the points record of all rows is 0 .'} | round_eq { sum { all_rows ; points } ; 0 } = true | the sum of the points record of all rows is 0 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'points_4': 4, '0_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'points_4': 'points', '0_5': '0'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'points_4': [0], '0_5': [1]} | ['year', 'entrant', 'chassis', 'engine', 'points'] | [['1969', 'owen racing organisation', 'brm p138', 'brm', '0'], ['1970', 'owen racing organisation', 'brm p139', 'brm', '0'], ['1970', 'owen racing organisation', 'brm p153', 'brm', '0'], ['1970', 'yardley team brm', 'brm p153', 'brm', '0'], ['1971', 'yardley team brm', 'brm p160', 'brm', '0']] |
united states army air forces | https://en.wikipedia.org/wiki/United_States_Army_Air_Forces | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-23508196-5.html.csv | superlative | the heavy bombardment group had the highest total personnel in the united states army air forces . | {'scope': 'all', 'col_superlative': '6', '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', 'total personnel'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; total personnel }'}, 'type of unit'], 'result': 'heavy bombardment group', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; total personnel } ; type of unit }'}, 'heavy bombardment group'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; total personnel } ; type of unit } ; heavy bombardment group } = true', 'tointer': 'select the row whose total personnel record of all rows is maximum . the type of unit record of this row is heavy bombardment group .'} | eq { hop { argmax { all_rows ; total personnel } ; type of unit } ; heavy bombardment group } = true | select the row whose total personnel record of all rows is maximum . the type of unit record of this row is heavy bombardment group . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'total personnel_5': 5, 'type of unit_6': 6, 'heavy bombardment group_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'total personnel_5': 'total personnel', 'type of unit_6': 'type of unit', 'heavy bombardment group_7': 'heavy bombardment group'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'total personnel_5': [0], 'type of unit_6': [1], 'heavy bombardment group_7': [2]} | ['type of unit', 'type of aircraft', 'number of aircraft', 'number of crews', 'men per crew', 'total personnel', 'officers', 'enlisted'] | [['very heavy bombardment group', 'b - 29', '45', '60', '11', '2078', '462', '1816'], ['heavy bombardment group', 'b - 17 , b - 24', '72', '96', '9 to 11', '2261', '465', '1796'], ['medium bombardment group', 'b - 25 , b - 26', '96', '96', '5 or 6', '1759', '393', '1386'], ['light bombardment group', 'a - 20 , a - 26', '96', '96', '3 or 4', '1304', '211', '1093'], ['single - engine fighter group', 'p - 40 , p - 47 p - 51', '111 to 126', '108 to 126', '1', '994', '183', '811'], ['twin - engine fighter group', 'p - 38', '111 to 126', '108 to 126', '1', '1081', '183', '838'], ['troop carrier group', 'c - 47', '80 - 110', '128', '4 or 5', '1837', '514', '1323'], ['combat cargo group', 'c - 46 , c - 47', '125', '150', '4', '883', '350', '533'], ['night fighter squadron', 'p - 61 , p - 70', '18', '16', '2 or 3', '288', '50', '238'], ['tactical reconnaissance squadron', 'f - 6 , p - 40 l - 4 , l - 5', '27', '23', '1', '233', '39', '194'], ['photo reconnaissance squadron', 'f - 5', '24', '21', '1', '347', '50', '297']] |
atlanta falcons draft history | https://en.wikipedia.org/wiki/Atlanta_Falcons_draft_history | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15198842-18.html.csv | aggregation | the average pick for the atlanta falcons draft history is 16.6 . | {'scope': 'all', 'col': '2', 'type': 'average', 'result': '16.6', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'pick'], 'result': '16.6', 'ind': 0, 'tostr': 'avg { all_rows ; pick }'}, '16.6'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; pick } ; 16.6 } = true', 'tointer': 'the average of the pick record of all rows is 16.6 .'} | round_eq { avg { all_rows ; pick } ; 16.6 } = true | the average of the pick record of all rows is 16.6 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'pick_4': 4, '16.6_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'pick_4': 'pick', '16.6_5': '16.6'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'pick_4': [0], '16.6_5': [1]} | ['round', 'pick', 'overall', 'name', 'position', 'college'] | [['1', '16', '16', 'mike pitts', 'defensive end', 'alabama'], ['2', '15', '43', 'james britt', 'defensive back', 'lsu'], ['3', '19', '75', 'andrew provence', 'defensive tackle', 'south carolina'], ['4', '18', '102', 'john harper', 'linebacker', 'southern illinois'], ['5', '17', '129', 'brett miller', 'offensive tackle', 'iowa'], ['6', '16', '156', 'anthony allen', 'wide receiver', 'washington'], ['7', '15', '183', 'jeff turk', 'defensive back', 'boise state'], ['8', '19', '215', 'john rade', 'linebacker', 'boise state'], ['10', '17', '268', 'ralph giacomarro', 'punter', 'penn state'], ['11', '16', '295', 'john salley', 'defensive back', 'wyoming'], ['12', '15', '322', 'allama matthews', 'tight end', 'vanderbilt']] |
1968 vfl season | https://en.wikipedia.org/wiki/1968_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10808933-2.html.csv | superlative | south melbourne had the highest recorded score of any away team in the 1968 vfl season . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '3', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'away team score'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; away team score }'}, 'away team'], 'result': 'south melbourne', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; away team score } ; away team }'}, 'south melbourne'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; away team score } ; away team } ; south melbourne } = true', 'tointer': 'select the row whose away team score record of all rows is maximum . the away team record of this row is south melbourne .'} | eq { hop { argmax { all_rows ; away team score } ; away team } ; south melbourne } = true | select the row whose away team score record of all rows is maximum . the away team record of this row is south melbourne . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'away team score_5': 5, 'away team_6': 6, 'south melbourne_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'away team score_5': 'away team score', 'away team_6': 'away team', 'south melbourne_7': 'south melbourne'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'away team score_5': [0], 'away team_6': [1], 'south melbourne_7': [2]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['hawthorn', '17.24 ( 126 )', 'south melbourne', '19.12 ( 126 )', 'glenferrie oval', '13536', '20 april 1968'], ['st kilda', '16.22 ( 118 )', 'melbourne', '9.8 ( 62 )', 'moorabbin oval', '21758', '20 april 1968'], ['geelong', '9.17 ( 71 )', 'footscray', '6.11 ( 47 )', 'kardinia park', '14589', '20 april 1968'], ['north melbourne', '9.9 ( 63 )', 'essendon', '10.22 ( 82 )', 'arden street oval', '14810', '20 april 1968'], ['fitzroy', '14.16 ( 100 )', 'collingwood', '10.11 ( 71 )', 'princes park', '17149', '20 april 1968'], ['richmond', '17.16 ( 118 )', 'carlton', '10.12 ( 72 )', 'mcg', '51889', '20 april 1968']] |
euroleague 2007 - 08 individual statistics | https://en.wikipedia.org/wiki/Euroleague_2007%E2%80%9308_Individual_Statistics | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16050349-9.html.csv | aggregation | the average number of assists for all players in the euroleague is 12.8 . | {'scope': 'all', 'col': '5', 'type': 'average', 'result': '12.8', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'assists'], 'result': '12.8', 'ind': 0, 'tostr': 'avg { all_rows ; assists }'}, '12.8'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; assists } ; 12.8 } = true', 'tointer': 'the average of the assists record of all rows is 12.8 .'} | round_eq { avg { all_rows ; assists } ; 12.8 } = true | the average of the assists record of all rows is 12.8 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'assists_4': 4, '12.8_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'assists_4': 'assists', '12.8_5': '12.8'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'assists_4': [0], '12.8_5': [1]} | ['rank', 'name', 'team', 'games', 'assists'] | [['1', 'yotam halperin', 'maccabi tel aviv', '3', '16'], ['2', 'theodoros papaloukas', 'cska moscow', '3', '15'], ['2', 'lynn greer', 'olympiacos', '3', '15'], ['4', 'terrell mcintyre', 'montepaschi siena', '2', '10'], ['5', 'bootsy thornton', 'montepaschi siena', '2', '8']] |
gymnastics at the 2008 summer olympics - women 's uneven bars | https://en.wikipedia.org/wiki/Gymnastics_at_the_2008_Summer_Olympics_%E2%80%93_Women%27s_uneven_bars | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18662048-4.html.csv | ordinal | ksenia semenova recorded the highest b score in gymnastics at the 2008 summer olympics - women 's uneven bars . | {'row': '2', 'col': '4', 'order': '1', 'col_other': '2', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'b score', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; b score ; 1 }'}, 'gymnast'], 'result': 'ksenia semenova ( rus )', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; b score ; 1 } ; gymnast }'}, 'ksenia semenova ( rus )'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; b score ; 1 } ; gymnast } ; ksenia semenova ( rus ) } = true', 'tointer': 'select the row whose b score record of all rows is 1st maximum . the gymnast record of this row is ksenia semenova ( rus ) .'} | eq { hop { nth_argmax { all_rows ; b score ; 1 } ; gymnast } ; ksenia semenova ( rus ) } = true | select the row whose b score record of all rows is 1st maximum . the gymnast record of this row is ksenia semenova ( rus ) . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'b score_5': 5, '1_6': 6, 'gymnast_7': 7, 'ksenia semenova ( rus )_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', 'b score_5': 'b score', '1_6': '1', 'gymnast_7': 'gymnast', 'ksenia semenova ( rus )_8': 'ksenia semenova ( rus )'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'b score_5': [0], '1_6': [0], 'gymnast_7': [1], 'ksenia semenova ( rus )_8': [2]} | ['position', 'gymnast', 'a score', 'b score', 'total'] | [['1', 'yang yilin ( chn )', '7.700', '8.950', '16.650'], ['2', 'ksenia semenova ( rus )', '7.400', '9.075', '16.475'], ['3', 'anastasia koval ( ukr )', '7.300', '9.025', '16.325'], ['4', 'steliana nistor ( rou )', '7.300', '8.675', '15.975'], ['5', 'nastia liukin ( usa )', '7.700', '8.250', '15.950'], ['6', 'he kexin ( chn )', '7.500', '8.225', '15.725'], ['7', 'dariya zgoba ( ukr )', '6.900', '8.875', '15.675'], ['8', 'beth tweddle ( gbr )', '7.600', '8.050', '15.650']] |
1958 green bay packers season | https://en.wikipedia.org/wiki/1958_Green_Bay_Packers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14656268-2.html.csv | unique | the game on october 19th , 1958 was the only game that took place at griffith stadium . | {'scope': 'all', 'row': '4', 'col': '5', 'col_other': '2', 'criterion': 'equal', 'value': 'griffith stadium', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'venue', 'griffith stadium'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose venue record fuzzily matches to griffith stadium .', 'tostr': 'filter_eq { all_rows ; venue ; griffith stadium }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; venue ; griffith stadium } }', 'tointer': 'select the rows whose venue record fuzzily matches to griffith stadium . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'venue', 'griffith stadium'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose venue record fuzzily matches to griffith stadium .', 'tostr': 'filter_eq { all_rows ; venue ; griffith stadium }'}, 'date'], 'result': 'october 19 , 1958', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; venue ; griffith stadium } ; date }'}, 'october 19 , 1958'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; venue ; griffith stadium } ; date } ; october 19 , 1958 }', 'tointer': 'the date record of this unqiue row is october 19 , 1958 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; venue ; griffith stadium } } ; eq { hop { filter_eq { all_rows ; venue ; griffith stadium } ; date } ; october 19 , 1958 } } = true', 'tointer': 'select the rows whose venue record fuzzily matches to griffith stadium . there is only one such row in the table . the date record of this unqiue row is october 19 , 1958 .'} | and { only { filter_eq { all_rows ; venue ; griffith stadium } } ; eq { hop { filter_eq { all_rows ; venue ; griffith stadium } ; date } ; october 19 , 1958 } } = true | select the rows whose venue record fuzzily matches to griffith stadium . there is only one such row in the table . the date record of this unqiue row is october 19 , 1958 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'venue_7': 7, 'griffith stadium_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'date_9': 9, 'october 19 , 1958_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'venue_7': 'venue', 'griffith stadium_8': 'griffith stadium', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'date_9': 'date', 'october 19 , 1958_10': 'october 19 , 1958'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'venue_7': [0], 'griffith stadium_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'date_9': [2], 'october 19 , 1958_10': [3]} | ['week', 'date', 'opponent', 'result', 'venue', 'attendance'] | [['1', 'september 28 , 1958', 'chicago bears', 'l 34 - 20', 'city stadium', '32150'], ['2', 'october 5 , 1958', 'detroit lions', 't 13 - 13', 'city stadium', '32053'], ['3', 'october 12 , 1958', 'baltimore colts', 'l 24 - 17', 'milwaukee county stadium', '24553'], ['4', 'october 19 , 1958', 'washington redskins', 'l 37 - 21', 'griffith stadium', '25228'], ['5', 'october 26 , 1958', 'philadelphia eagles', 'w 38 - 35', 'city stadium', '31043'], ['6', 'november 2 , 1958', 'baltimore colts', 'l 56 - 0', 'memorial stadium', '51333'], ['7', 'november 9 , 1958', 'chicago bears', 'l 24 - 10', 'wrigley field', '48424'], ['8', 'november 16 , 1958', 'los angeles rams', 'l 20 - 7', 'city stadium', '28051'], ['9', 'november 23 , 1958', 'san francisco 49ers', 'l 33 - 12', 'milwaukee county stadium', '19786'], ['10', 'november 27 , 1958', 'detroit lions', 'l 24 - 14', 'briggs stadium', '50971'], ['11', 'december 7 , 1958', 'san francisco 49ers', 'l 48 - 21', 'kezar stadium', '50793'], ['12', 'december 14 , 1958', 'los angeles rams', 'l 34 - 20', 'los angeles memorial coliseum', '54634']] |
miguel malvar - class corvette | https://en.wikipedia.org/wiki/Miguel_Malvar-class_corvette | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17849650-1.html.csv | superlative | the brp pangasinan had the earliest launch date of all the others in its class . | {'scope': 'all', 'col_superlative': '3', 'row_superlative': '9', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '2', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmin', 'args': ['all_rows', 'launched'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; launched }'}, 'ship name'], 'result': 'brp pangasinan', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; launched } ; ship name }'}, 'brp pangasinan'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmin { all_rows ; launched } ; ship name } ; brp pangasinan } = true', 'tointer': 'select the row whose launched record of all rows is minimum . the ship name record of this row is brp pangasinan .'} | eq { hop { argmin { all_rows ; launched } ; ship name } ; brp pangasinan } = true | select the row whose launched record of all rows is minimum . the ship name record of this row is brp pangasinan . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'launched_5': 5, 'ship name_6': 6, 'brp pangasinan_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'launched_5': 'launched', 'ship name_6': 'ship name', 'brp pangasinan_7': 'brp pangasinan'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'launched_5': [0], 'ship name_6': [1], 'brp pangasinan_7': [2]} | ['bow number', 'ship name', 'launched', 'commissioned', 'service'] | [['ps - 18', 'brp datu tupas', '14 november 1943', 'november 1975', 'philippine navy patrol force'], ['ps - 19', 'brp miguel malvar', '1 march 1944', 'november 1975', 'philippine navy patrol force'], ['ps - 20', 'brp magat salamat', '19 march 1944', 'november 1975', 'philippine navy patrol force'], ['ps - 22', 'brp sultan kudarat', '18 may 1943', 'november 1975', 'philippine navy patrol force'], ['ps - 23', 'brp datu marikudo', '18 march 1944', '5 april 1976', 'philippine navy patrol force'], ['ps - 28', 'brp cebu', '10 november 1943', 'july 1948', 'philippine navy patrol force'], ['ps - 29', 'brp negros occidental', '24 february 1944', 'july 1948', 'philippine navy patrol force'], ['ps - 30', 'rps leyte', '20 june 1944', 'july 1948', 'philippine navy patrol force'], ['ps - 31', 'brp pangasinan', '24 april 1943', 'july 1948', 'philippine navy patrol force'], ['ps - 32', 'brp iloilo', '3 august 1943', 'july 1948', 'philippine navy patrol force'], ['ps - 33', 'rps samar', '20 november 1943', '24 may 1948', 'philippine navy patrol force']] |
list of superfund sites in alaska | https://en.wikipedia.org/wiki/List_of_Superfund_sites_in_Alaska | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10834634-1.html.csv | unique | adak naval air station is the only superfund site in aleutians west . | {'scope': 'all', 'row': '1', 'col': '3', 'col_other': '2', 'criterion': 'equal', 'value': 'aleutians west', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'borough or census area', 'aleutians west'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose borough or census area record fuzzily matches to aleutians west .', 'tostr': 'filter_eq { all_rows ; borough or census area ; aleutians west }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; borough or census area ; aleutians west } }', 'tointer': 'select the rows whose borough or census area record fuzzily matches to aleutians west . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'borough or census area', 'aleutians west'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose borough or census area record fuzzily matches to aleutians west .', 'tostr': 'filter_eq { all_rows ; borough or census area ; aleutians west }'}, 'name'], 'result': 'adak naval air station', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; borough or census area ; aleutians west } ; name }'}, 'adak naval air station'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; borough or census area ; aleutians west } ; name } ; adak naval air station }', 'tointer': 'the name record of this unqiue row is adak naval air station .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; borough or census area ; aleutians west } } ; eq { hop { filter_eq { all_rows ; borough or census area ; aleutians west } ; name } ; adak naval air station } } = true', 'tointer': 'select the rows whose borough or census area record fuzzily matches to aleutians west . there is only one such row in the table . the name record of this unqiue row is adak naval air station .'} | and { only { filter_eq { all_rows ; borough or census area ; aleutians west } } ; eq { hop { filter_eq { all_rows ; borough or census area ; aleutians west } ; name } ; adak naval air station } } = true | select the rows whose borough or census area record fuzzily matches to aleutians west . there is only one such row in the table . the name record of this unqiue row is adak naval air station . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'borough or census area_7': 7, 'aleutians west_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'name_9': 9, 'adak naval air station_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'borough or census area_7': 'borough or census area', 'aleutians west_8': 'aleutians west', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'name_9': 'name', 'adak naval air station_10': 'adak naval air station'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'borough or census area_7': [0], 'aleutians west_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'name_9': [2], 'adak naval air station_10': [3]} | ['cerclis id', 'name', 'borough or census area', 'proposed', 'listed', 'construction completed', 'partially deleted', 'deleted'] | [['ak4170024323', 'adak naval air station', 'aleutians west', '10 / 14 / 1992', '05 / 31 / 1994', '-', '-', '-'], ['ak8570028649', 'elmendorf air force base', 'anchorage', '07 / 14 / 1989', '08 / 30 / 1990', '-', '-', '-'], ['ak6214522157', 'fort richardson ( usarmy )', 'anchorage', '06 / 23 / 1993', '05 / 31 / 1994', '09 / 28 / 2006', '-', '-'], ['akd980978787', 'standard steel & metals salvage yard ( usdot )', 'anchorage', '07 / 14 / 1989', '08 / 30 / 1990', '09 / 16 / 1999', '-', '09 / 30 / 2002'], ['akd004904215', 'alaska battery enterprises', 'fairbanks north star', '06 / 24 / 1988', '03 / 31 / 1989', '03 / 02 / 1993', '-', '07 / 26 / 1996'], ['akd980988158', 'arctic surplus', 'fairbanks north star', '10 / 26 / 1989', '08 / 30 / 1990', '04 / 18 / 2005', '-', '09 / 25 / 2006'], ['ak1570028646', 'eielson air force base', 'fairbanks north star', '07 / 14 / 1989', '11 / 21 / 1989', '09 / 30 / 1998', '-', '-'], ['ak6210022426', 'fort wainwright', 'fairbanks north star', '07 / 14 / 1989', '08 / 30 / 1990', '09 / 27 / 2002', '-', '-'], ['ak0001897602', 'salt chuck mine', 'outer ketchikan', '09 / 23 / 2009', '03 / 04 / 2010', '-', '-', '-']] |
1994 fei world equestrian games | https://en.wikipedia.org/wiki/1994_FEI_World_Equestrian_Games | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11871998-2.html.csv | ordinal | netherlands recorded the 2nd highest number of bronze in the fei world equestrian games of 1994 . | {'row': '4', 'col': '4', 'order': '2', 'col_other': '1', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'bronze', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; bronze ; 2 }'}, 'nation'], 'result': 'netherlands', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; bronze ; 2 } ; nation }'}, 'netherlands'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; bronze ; 2 } ; nation } ; netherlands } = true', 'tointer': 'select the row whose bronze record of all rows is 2nd maximum . the nation record of this row is netherlands .'} | eq { hop { nth_argmax { all_rows ; bronze ; 2 } ; nation } ; netherlands } = true | select the row whose bronze record of all rows is 2nd maximum . the nation record of this row is netherlands . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'bronze_5': 5, '2_6': 6, 'nation_7': 7, 'netherlands_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', 'bronze_5': 'bronze', '2_6': '2', 'nation_7': 'nation', 'netherlands_8': 'netherlands'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'bronze_5': [0], '2_6': [0], 'nation_7': [1], 'netherlands_8': [2]} | ['nation', 'gold', 'silver', 'bronze', 'total'] | [['germany', '7', '4', '5', '16'], ['france', '1', '4', '1', '6'], ['united states', '1', '2', '1', '4'], ['netherlands', '1', '1', '3', '5'], ['united kingdom', '1', '1', '1', '3'], ['switzerland', '1', '-', '1', '2'], ['denmark', '1', '-', '-', '1'], ['new zealand', '1', '-', '-', '1'], ['belgium', '-', '1', '-', '1'], ['spain', '-', '1', '-', '1'], ['australia', '-', '-', '1', '1'], ['sweden', '-', '-', '1', '1']] |
united states house of representatives elections , 2006 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_2006 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1805191-47.html.csv | comparative | frank wolf has a first elected year which is earlier than that of rick boucher . | {'row_1': '10', 'row_2': '9', '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', 'frank wolf'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose incumbent record fuzzily matches to frank wolf .', 'tostr': 'filter_eq { all_rows ; incumbent ; frank wolf }'}, 'first elected'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; incumbent ; frank wolf } ; first elected }', 'tointer': 'select the rows whose incumbent record fuzzily matches to frank wolf . take the first elected record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'incumbent', 'rick boucher'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose incumbent record fuzzily matches to rick boucher .', 'tostr': 'filter_eq { all_rows ; incumbent ; rick boucher }'}, 'first elected'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; incumbent ; rick boucher } ; first elected }', 'tointer': 'select the rows whose incumbent record fuzzily matches to rick boucher . take the first elected record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; incumbent ; frank wolf } ; first elected } ; hop { filter_eq { all_rows ; incumbent ; rick boucher } ; first elected } } = true', 'tointer': 'select the rows whose incumbent record fuzzily matches to frank wolf . take the first elected record of this row . select the rows whose incumbent record fuzzily matches to rick boucher . take the first elected record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; incumbent ; frank wolf } ; first elected } ; hop { filter_eq { all_rows ; incumbent ; rick boucher } ; first elected } } = true | select the rows whose incumbent record fuzzily matches to frank wolf . take the first elected record of this row . select the rows whose incumbent record fuzzily matches to rick boucher . 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, 'frank wolf_8': 8, 'first elected_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'incumbent_11': 11, 'rick boucher_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', 'frank wolf_8': 'frank wolf', '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', 'rick boucher_12': 'rick boucher', '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], 'frank wolf_8': [0], 'first elected_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'incumbent_11': [1], 'rick boucher_12': [1], 'first elected_13': [3]} | ['district', 'incumbent', 'party', 'first elected', 'results'] | [['virginia 1', 'jo ann davis', 'republican', '2000', 're - elected'], ['virginia 2', 'thelma drake', 'republican', '2004', 're - elected'], ['virginia 3', 'bobby scott', 'democratic', '1992', 're - elected'], ['virginia 4', 'randy forbes', 'republican', '2001', 're - elected'], ['virginia 5', 'virgil goode', 'republican', '1996', 're - elected'], ['virginia 6', 'bob goodlatte', 'republican', '1992', 're - elected'], ['virginia 7', 'eric cantor', 'republican', '2000', 're - elected'], ['virginia 8', 'jim moran', 'democratic', '1990', 're - elected'], ['virginia 9', 'rick boucher', 'democratic', '1982', 're - elected'], ['virginia 10', 'frank wolf', 'republican', '1980', 're - elected'], ['virginia 11', 'tom davis', 'republican', '1994', 're - elected']] |
dave penney | https://en.wikipedia.org/wiki/Dave_Penney | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1175663-1.html.csv | unique | darlington was the only team to play 139 matches . | {'scope': 'all', 'row': '3', 'col': '4', 'col_other': '1', 'criterion': 'equal', 'value': '139', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'matches', '139'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose matches record is equal to 139 .', 'tostr': 'filter_eq { all_rows ; matches ; 139 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; matches ; 139 } }', 'tointer': 'select the rows whose matches record is equal to 139 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'matches', '139'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose matches record is equal to 139 .', 'tostr': 'filter_eq { all_rows ; matches ; 139 }'}, 'team'], 'result': 'darlington', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; matches ; 139 } ; team }'}, 'darlington'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; matches ; 139 } ; team } ; darlington }', 'tointer': 'the team record of this unqiue row is darlington .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; matches ; 139 } } ; eq { hop { filter_eq { all_rows ; matches ; 139 } ; team } ; darlington } } = true', 'tointer': 'select the rows whose matches record is equal to 139 . there is only one such row in the table . the team record of this unqiue row is darlington .'} | and { only { filter_eq { all_rows ; matches ; 139 } } ; eq { hop { filter_eq { all_rows ; matches ; 139 } ; team } ; darlington } } = true | select the rows whose matches record is equal to 139 . there is only one such row in the table . the team record of this unqiue row is darlington . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'matches_7': 7, '139_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'team_9': 9, 'darlington_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'matches_7': 'matches', '139_8': '139', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'team_9': 'team', 'darlington_10': 'darlington'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'matches_7': [0], '139_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'team_9': [2], 'darlington_10': [3]} | ['team', 'nation', 'from', 'matches', 'drawn', 'lost', 'win %'] | [['doncaster rovers', 'england', '22 april 2000', '6', '1', '1', '66.7'], ['doncaster rovers', 'england', '27 december 2001', '241', '62', '65', '47.3'], ['darlington', 'england', '30 october 2006', '139', '35', '44', '43.2'], ['oldham athletic', 'england', '30 april 2009', '48', '13', '22', '27.1'], ['bristol rovers', 'england', '10 january 2011', '13', '2', '9', '15.38']] |
2008 - 09 milwaukee bucks season | https://en.wikipedia.org/wiki/2008%E2%80%9309_Milwaukee_Bucks_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17058116-8.html.csv | unique | the bucks only played in the izod center one time . | {'scope': 'all', 'row': '1', 'col': '7', 'col_other': 'n/a', 'criterion': 'fuzzily_match', 'value': 'izod center', 'subset': None} | {'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location attendance', 'izod center'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose location attendance record fuzzily matches to izod center .', 'tostr': 'filter_eq { all_rows ; location attendance ; izod center }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; location attendance ; izod center } } = true', 'tointer': 'select the rows whose location attendance record fuzzily matches to izod center . there is only one such row in the table .'} | only { filter_eq { all_rows ; location attendance ; izod center } } = true | select the rows whose location attendance record fuzzily matches to izod center . there is only one such row in the table . | 2 | 2 | {'only_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, 'location attendance_4': 4, 'izod center_5': 5} | {'only_1': 'only', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'location attendance_4': 'location attendance', 'izod center_5': 'izod center'} | {'only_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'location attendance_4': [0], 'izod center_5': [0]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'location attendance', 'record'] | [['52', 'february 3', 'new jersey', 'l 85 - 99 ( ot )', 'richard jefferson ( 27 )', 'dan gadzuric ( 9 )', 'izod center 10102', '24 - 28'], ['53', 'february 7', 'detroit', 'l 121 - 126 ( ot )', 'ramon sessions ( 44 )', 'francisco elson ( 8 )', 'bradley center 17297', '24 - 29'], ['54', 'february 9', 'houston', 'w 124 - 112 ( ot )', 'ramon sessions ( 26 )', 'charlie villanueva ( 8 )', 'bradley center 13904', '25 - 29'], ['55', 'february 11', 'indiana', 'w 122 - 110 ( ot )', 'richard jefferson ( 32 )', 'luc mbah a moute ( 11 )', 'bradley center 13486', '26 - 29'], ['56', 'february 17', 'detroit', 'w 92 - 86 ( ot )', 'richard jefferson ( 29 )', 'ramon sessions ( 9 )', 'the palace of auburn hills 20217', '27 - 29'], ['57', 'february 18', 'chicago', 'l 104 - 113 ( ot )', 'richard jefferson ( 32 )', 'charlie villanueva ( 12 )', 'bradley center 15309', '27 - 30'], ['58', 'february 20', 'cleveland', 'l 103 - 111 ( ot )', 'charlie villanueva ( 26 )', 'charlie villanueva ( 13 )', 'bradley center 18076', '27 - 31'], ['59', 'february 22', 'denver', 'w 120 - 117 ( ot )', 'charlie villanueva ( 36 )', 'francisco elson ( 7 )', 'bradley center 14891', '28 - 31'], ['60', 'february 25', 'dallas', 'l 96 - 116 ( ot )', 'charlie villanueva ( 25 )', 'charlie villanueva ( 7 )', 'american airlines center 19558', '28 - 32'], ['61', 'february 27', 'new orleans', 'l 94 - 95 ( ot )', 'richard jefferson ( 22 )', 'charlie villanueva ( 7 )', 'new orleans arena 17621', '28 - 33'], ['62', 'february 28', 'washington', 'w 109 - 93 ( ot )', 'charlie villanueva ( 25 )', 'dan gadzuric ( 11 )', 'bradley center 15970', '29 - 33']] |
statistics relating to enlargement of the european union | https://en.wikipedia.org/wiki/Statistics_relating_to_enlargement_of_the_European_Union | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1307842-2.html.csv | count | 2 of the countries with population less than 60000000 has gdp ( billion us ) less than 100 . | {'scope': 'subset', 'criterion': 'less_than', 'value': '100', 'result': '2', 'col': '4', 'subset': {'col': '2', 'criterion': 'less_than', 'value': '60000000'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_less', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'population', '60000000'], 'result': None, 'ind': 0, 'tostr': 'filter_less { all_rows ; population ; 60000000 }', 'tointer': 'select the rows whose population record is less than 60000000 .'}, 'gdp ( billion us )', '100'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose population record is less than 60000000 . among these rows , select the rows whose gdp ( billion us ) record is less than 100 .', 'tostr': 'filter_less { filter_less { all_rows ; population ; 60000000 } ; gdp ( billion us ) ; 100 }'}], 'result': '2', 'ind': 2, 'tostr': 'count { filter_less { filter_less { all_rows ; population ; 60000000 } ; gdp ( billion us ) ; 100 } }', 'tointer': 'select the rows whose population record is less than 60000000 . among these rows , select the rows whose gdp ( billion us ) record is less than 100 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_less { filter_less { all_rows ; population ; 60000000 } ; gdp ( billion us ) ; 100 } } ; 2 } = true', 'tointer': 'select the rows whose population record is less than 60000000 . among these rows , select the rows whose gdp ( billion us ) record is less than 100 . the number of such rows is 2 .'} | eq { count { filter_less { filter_less { all_rows ; population ; 60000000 } ; gdp ( billion us ) ; 100 } } ; 2 } = true | select the rows whose population record is less than 60000000 . among these rows , select the rows whose gdp ( billion us ) record is less than 100 . the number of such rows is 2 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_less_1': 1, 'filter_less_0': 0, 'all_rows_5': 5, 'population_6': 6, '60000000_7': 7, 'gdp (billion us)_8': 8, '100_9': 9, '2_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_less_1': 'filter_less', 'filter_less_0': 'filter_less', 'all_rows_5': 'all_rows', 'population_6': 'population', '60000000_7': '60000000', 'gdp (billion us)_8': 'gdp ( billion us )', '100_9': '100', '2_10': '2'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_less_1': [2], 'filter_less_0': [1], 'all_rows_5': [0], 'population_6': [0], '60000000_7': [0], 'gdp (billion us)_8': [1], '100_9': [1], '2_10': [3]} | ['member countries', 'population', 'area ( km square )', 'gdp ( billion us )', 'gdp per capita ( us )'] | [['denmark', '5021861', '43094', '70.032', '59928'], ['ireland', '3073200', '70273', '21.103', '39638'], ['united kingdom', '56210000', '244820', '675.941', '36728'], ['accession countries', '64305061', '358187', '767.076', '11929'], ['existing members ( 1973 )', '192457106', '1299536', '2381396', '12374'], ['ec9 ( 1973 )', '256762167 ( + 33.41 % )', '1657723 ( + 25.44 % )', '3148.472 ( + 32.21 % )', '12262 ( 0.91 % )']] |
list of georgian submissions for the academy award for best foreign language film | https://en.wikipedia.org/wiki/List_of_Georgian_submissions_for_the_Academy_Award_for_Best_Foreign_Language_Film | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-18069789-1.html.csv | majority | the majority of georgian submissions for best foreign language film were not nominated for the academy award . | {'scope': 'all', 'col': '6', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'not nominated', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'result', 'not nominated'], 'result': True, 'ind': 0, 'tointer': 'for the result records of all rows , most of them fuzzily match to not nominated .', 'tostr': 'most_eq { all_rows ; result ; not nominated } = true'} | most_eq { all_rows ; result ; not nominated } = true | for the result records of all rows , most of them fuzzily match to not nominated . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'result_3': 3, 'not nominated_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'result_3': 'result', 'not nominated_4': 'not nominated'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'result_3': [0], 'not nominated_4': [0]} | ['year ( ceremony )', 'film title used in nomination', 'original title', 'director', 'main language ( s )', 'result'] | [['1996 ( 69th )', 'a chef in love', 'შეყვარებული მზარეულის 1001 რეცეპტი', 'nana dzhordzhadze', 'french , georgian', 'nominee'], ['1999 ( 72nd )', 'here comes the dawn', 'აქ თენდება', 'zaza urushadze', 'georgian', 'not nominated'], ['2000 ( 73rd )', '27 missing kisses', 'ზაფხული , ანუ 27 მოპარული კოცნა', 'nana dzhordzhadze', 'georgian , russian', 'not nominated'], ['2001 ( 74th )', 'migration of the angel', 'ანგელოზის გადაფრენა', 'nodar managadze', 'georgian', 'not nominated'], ['2005 ( 78th )', 'tbilisi , tbilisi', 'თბილისი - თბილისი', 'levan zaqareishvili', 'georgian', 'not nominated'], ['2007 ( 80th )', 'russian triangle', 'რუსული სამკუთხედი', 'aleko tsabadze', 'russian', 'not nominated'], ['2008 ( 81st )', 'mediator', 'მედიატორი', 'dito tsintsadze', 'english , german , russian', 'not nominated'], ['2009 ( 82nd )', 'the other bank', 'გაღმა ნაპირი', 'george ovashvili', 'georgian , abkhaz , russian', 'not nominated'], ['2010 ( 83rd )', 'street days', 'ქუჩის დღეები', 'levan koguashvili', 'georgian', 'not nominated'], ['2011 ( 84th )', 'chantrapas', 'შანტრაპა', 'otar iosseliani', 'french , georgian', 'not nominated'], ['2012 ( 85th )', 'keep smiling', 'გაიღიმეთ', 'rusudan chkonia', 'georgian', 'not nominated']] |
fiba africa clubs champions cup | https://en.wikipedia.org/wiki/FIBA_Africa_Clubs_Champions_Cup | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12965873-1.html.csv | ordinal | primeiro de agosto has the second most runners-up in the fiba africa clubs champions cup . | {'row': '1', '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', 'runners - up', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; runners - up ; 2 }'}, 'clubs'], 'result': 'primeiro de agosto', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; runners - up ; 2 } ; clubs }'}, 'primeiro de agosto'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; runners - up ; 2 } ; clubs } ; primeiro de agosto } = true', 'tointer': 'select the row whose runners - up record of all rows is 2nd maximum . the clubs record of this row is primeiro de agosto .'} | eq { hop { nth_argmax { all_rows ; runners - up ; 2 } ; clubs } ; primeiro de agosto } = true | select the row whose runners - up record of all rows is 2nd maximum . the clubs record of this row is primeiro de agosto . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'runners - up_5': 5, '2_6': 6, 'clubs_7': 7, 'primeiro de agosto_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', 'runners - up_5': 'runners - up', '2_6': '2', 'clubs_7': 'clubs', 'primeiro de agosto_8': 'primeiro de agosto'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'runners - up_5': [0], '2_6': [0], 'clubs_7': [1], 'primeiro de agosto_8': [2]} | ['clubs', 'winners', 'runners - up', 'total finals', 'winnig years'] | [['primeiro de agosto', '7', '3', '10', '2002 , 2004 , 2007 , 2008 , 2009 , 2010 , 2012'], ['as forces armées', '3', '1', '4', '1975 , 1979 , 1981'], ['asec mimosas', '2', '2', '4', '1989 , 2000'], ['gezira sc', '2', '0', '2', '1994 , 1996'], ['hit trésor', '2', '0', '2', '1973 , 1976'], ['petro atlético', '1', '5', '6', '2006'], ['zamalek sc', '1', '3', '4', '1992'], ['es sahel', '1', '1', '2', '2011'], ['abidjan basket club', '1', '1', '2', '2005'], ["asc jeanne d'arc", '1', '1', '2', '1991'], ['as police', '1', '1', '2', '1983'], ['mas fez', '1', '0', '1', '1998'], ['al - ittihad alexandria', '1', '0', '1', '1987'], ['cd maxaquene', '1', '0', '1', '1985'], ['red star', '1', '0', '1', '1972']] |
2007 - 08 euroleague women | https://en.wikipedia.org/wiki/2007%E2%80%9308_EuroLeague_Women | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14121260-9.html.csv | comparative | jelena skerovic had more assists than kathy wambe in the women 's 2007 - 08 euroleague . | {'row_1': '5', 'row_2': '3', 'col': '5', 'col_other': '2', 'relation': 'greater', 'record_mentioned': 'yes', 'diff_result': None} | {'func': 'and', 'args': [{'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'name', 'jelena skerovic'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose name record fuzzily matches to jelena skerovic .', 'tostr': 'filter_eq { all_rows ; name ; jelena skerovic }'}, 'assists'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; name ; jelena skerovic } ; assists }', 'tointer': 'select the rows whose name record fuzzily matches to jelena skerovic . take the assists record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'name', 'kathy wambe'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose name record fuzzily matches to kathy wambe .', 'tostr': 'filter_eq { all_rows ; name ; kathy wambe }'}, 'assists'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; name ; kathy wambe } ; assists }', 'tointer': 'select the rows whose name record fuzzily matches to kathy wambe . take the assists record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; name ; jelena skerovic } ; assists } ; hop { filter_eq { all_rows ; name ; kathy wambe } ; assists } }', 'tointer': 'select the rows whose name record fuzzily matches to jelena skerovic . take the assists record of this row . select the rows whose name record fuzzily matches to kathy wambe . take the assists record of this row . the first record is greater than the second record .'}, {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'name', 'jelena skerovic'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose name record fuzzily matches to jelena skerovic .', 'tostr': 'filter_eq { all_rows ; name ; jelena skerovic }'}, 'assists'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; name ; jelena skerovic } ; assists }', 'tointer': 'select the rows whose name record fuzzily matches to jelena skerovic . take the assists record of this row .'}, '54'], 'result': True, 'ind': 5, 'tostr': 'eq { hop { filter_eq { all_rows ; name ; jelena skerovic } ; assists } ; 54 }', 'tointer': 'the assists record of the first row is 54 .'}, {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'name', 'kathy wambe'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose name record fuzzily matches to kathy wambe .', 'tostr': 'filter_eq { all_rows ; name ; kathy wambe }'}, 'assists'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; name ; kathy wambe } ; assists }', 'tointer': 'select the rows whose name record fuzzily matches to kathy wambe . take the assists record of this row .'}, '48'], 'result': True, 'ind': 6, 'tostr': 'eq { hop { filter_eq { all_rows ; name ; kathy wambe } ; assists } ; 48 }', 'tointer': 'the assists record of the second row is 48 .'}], 'result': True, 'ind': 7, 'tostr': 'and { eq { hop { filter_eq { all_rows ; name ; jelena skerovic } ; assists } ; 54 } ; eq { hop { filter_eq { all_rows ; name ; kathy wambe } ; assists } ; 48 } }', 'tointer': 'the assists record of the first row is 54 . the assists record of the second row is 48 .'}], 'result': True, 'ind': 8, 'tostr': 'and { greater { hop { filter_eq { all_rows ; name ; jelena skerovic } ; assists } ; hop { filter_eq { all_rows ; name ; kathy wambe } ; assists } } ; and { eq { hop { filter_eq { all_rows ; name ; jelena skerovic } ; assists } ; 54 } ; eq { hop { filter_eq { all_rows ; name ; kathy wambe } ; assists } ; 48 } } } = true', 'tointer': 'select the rows whose name record fuzzily matches to jelena skerovic . take the assists record of this row . select the rows whose name record fuzzily matches to kathy wambe . take the assists record of this row . the first record is greater than the second record . the assists record of the first row is 54 . the assists record of the second row is 48 .'} | and { greater { hop { filter_eq { all_rows ; name ; jelena skerovic } ; assists } ; hop { filter_eq { all_rows ; name ; kathy wambe } ; assists } } ; and { eq { hop { filter_eq { all_rows ; name ; jelena skerovic } ; assists } ; 54 } ; eq { hop { filter_eq { all_rows ; name ; kathy wambe } ; assists } ; 48 } } } = true | select the rows whose name record fuzzily matches to jelena skerovic . take the assists record of this row . select the rows whose name record fuzzily matches to kathy wambe . take the assists record of this row . the first record is greater than the second record . the assists record of the first row is 54 . the assists record of the second row is 48 . | 13 | 9 | {'and_8': 8, 'result_9': 9, 'greater_4': 4, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_10': 10, 'name_11': 11, 'jelena skerovic_12': 12, 'assists_13': 13, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_14': 14, 'name_15': 15, 'kathy wambe_16': 16, 'assists_17': 17, 'and_7': 7, 'eq_5': 5, '54_18': 18, 'eq_6': 6, '48_19': 19} | {'and_8': 'and', 'result_9': 'true', 'greater_4': 'greater', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_10': 'all_rows', 'name_11': 'name', 'jelena skerovic_12': 'jelena skerovic', 'assists_13': 'assists', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_14': 'all_rows', 'name_15': 'name', 'kathy wambe_16': 'kathy wambe', 'assists_17': 'assists', 'and_7': 'and', 'eq_5': 'eq', '54_18': '54', 'eq_6': 'eq', '48_19': '48'} | {'and_8': [9], 'result_9': [], 'greater_4': [8], 'num_hop_2': [4, 5], 'filter_str_eq_0': [2], 'all_rows_10': [0], 'name_11': [0], 'jelena skerovic_12': [0], 'assists_13': [2], 'num_hop_3': [4, 6], 'filter_str_eq_1': [3], 'all_rows_14': [1], 'name_15': [1], 'kathy wambe_16': [1], 'assists_17': [3], 'and_7': [8], 'eq_5': [7], '54_18': [5], 'eq_6': [7], '48_19': [6]} | ['rank', 'name', 'team', 'games', 'assists'] | [['1', 'dalma iványi', 'mizo pécs 2010', '13', '74'], ['2', 'caroline aubert', 'uso mondeville basket ummc ekaterinburg', '16', '80'], ['3', 'kathy wambe', 'esb lille metropole', '10', '48'], ['4', 'sue bird', 'spartak moscow region', '14', '65'], ['5', 'jelena skerovic', 'wisła can - pack kraków', '12', '54']] |
soo line locomotives | https://en.wikipedia.org/wiki/Soo_Line_locomotives | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17248696-6.html.csv | majority | the majorityof soo line locomotive models did not have any quantity of models preserved . | {'scope': 'all', 'col': '7', 'most_or_all': 'most', 'criterion': 'equal', 'value': '0', 'subset': None} | {'func': 'most_eq', 'args': ['all_rows', 'quantity preserved', '0'], 'result': True, 'ind': 0, 'tointer': 'for the quantity preserved records of all rows , most of them are equal to 0 .', 'tostr': 'most_eq { all_rows ; quantity preserved ; 0 } = true'} | most_eq { all_rows ; quantity preserved ; 0 } = true | for the quantity preserved records of all rows , most of them are equal to 0 . | 1 | 1 | {'most_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'quantity preserved_3': 3, '0_4': 4} | {'most_eq_0': 'most_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'quantity preserved_3': 'quantity preserved', '0_4': '0'} | {'most_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'quantity preserved_3': [0], '0_4': [0]} | ['class', 'wheel arrangement', 'fleet number ( s )', 'manufacturer', 'year made', 'quantity made', 'quantity preserved'] | [['2 - 8 - 0 - ooooo - consolidation', '2 - 8 - 0 - ooooo - consolidation', '2 - 8 - 0 - ooooo - consolidation', '2 - 8 - 0 - ooooo - consolidation', '2 - 8 - 0 - ooooo - consolidation', '2 - 8 - 0 - ooooo - consolidation', '2 - 8 - 0 - ooooo - consolidation'], ['f - 1', '2 - 8 - 0', '403 - 405 , 407 - 412', 'schenectady', '1893', '9', '0'], ['f - 2', '2 - 8 - 0', '406', 'schenectady', '1893', '1', '0'], ['f - 3', '2 - 8 - 0', '413 - 416', 'schenectady', '1893', '4', '0'], ['f - 4', '2 - 8 - 0', '417', 'schenectady', '1893', '1', '0'], ['f - 6', '2 - 8 - 0', '400 - 402 , 418 - 427', 'rhode island', '1893', '13', '0'], ['f - 7', '2 - 8 - 0', '428 - 430', 'schenectady', '1900', '3', '0'], ['f - 8', '2 - 8 - 0', '431 - 444', 'alco - schenectady', '1902 - 1903', '14', '1'], ['f - 9', '2 - 8 - 0', '445 - 472', 'alco - schenectady', '1905 - 1906', '28', '1'], ['f - 10', '2 - 8 - 0', '473 - 474', 'alco - schenectady', '1909', '2', '0'], ['f - 11', '2 - 8 - 0', '475 - 484', 'alco - schenectady', '1910', '10', '0'], ['f - 12', '2 - 8 - 0', '485 - 499', 'alco - schenectady', '1912 - 1913', '15', '0'], ['f - 20', '2 - 8 - 0', '2400 - 2424', 'alco - schenectady', '1903 - 1907', '25', '1'], ['f - 21', '2 - 8 - 0', '2425 - 2428', 'alco - schenectady', '1909', '4', '1'], ['f - 22', '2 - 8 - 0', '2429 - 2443', 'alco - schenectady', '1911', '15', '1'], ['f - 23', '2 - 8 - 0', '2444 - 2450', 'alco - schenectady', '1914', '7', '0']] |
list of abs - cbn corporation channels and stations | https://en.wikipedia.org/wiki/List_of_ABS-CBN_Corporation_channels_and_stations | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2610582-7.html.csv | count | for the abs - cbn corporation channels and stations , when the power is 10 kw , there are two stations where the frequency is over 100.0 . | {'scope': 'subset', 'criterion': 'greater_than', 'value': '100.0', 'result': '2', 'col': '3', 'subset': {'col': '4', 'criterion': 'equal', 'value': '10 kw'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'power ( kw )', '10 kw'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; power ( kw ) ; 10 kw }', 'tointer': 'select the rows whose power ( kw ) record fuzzily matches to 10 kw .'}, 'frequency', '100.0'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose power ( kw ) record fuzzily matches to 10 kw . among these rows , select the rows whose frequency record is greater than 100.0 .', 'tostr': 'filter_greater { filter_eq { all_rows ; power ( kw ) ; 10 kw } ; frequency ; 100.0 }'}], 'result': '2', 'ind': 2, 'tostr': 'count { filter_greater { filter_eq { all_rows ; power ( kw ) ; 10 kw } ; frequency ; 100.0 } }', 'tointer': 'select the rows whose power ( kw ) record fuzzily matches to 10 kw . among these rows , select the rows whose frequency record is greater than 100.0 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_greater { filter_eq { all_rows ; power ( kw ) ; 10 kw } ; frequency ; 100.0 } } ; 2 } = true', 'tointer': 'select the rows whose power ( kw ) record fuzzily matches to 10 kw . among these rows , select the rows whose frequency record is greater than 100.0 . the number of such rows is 2 .'} | eq { count { filter_greater { filter_eq { all_rows ; power ( kw ) ; 10 kw } ; frequency ; 100.0 } } ; 2 } = true | select the rows whose power ( kw ) record fuzzily matches to 10 kw . among these rows , select the rows whose frequency record is greater than 100.0 . the number of such rows is 2 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_greater_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'power (kw)_6': 6, '10 kw_7': 7, 'frequency_8': 8, '100.0_9': 9, '2_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_greater_1': 'filter_greater', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'power (kw)_6': 'power ( kw )', '10 kw_7': '10 kw', 'frequency_8': 'frequency', '100.0_9': '100.0', '2_10': '2'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_greater_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'power (kw)_6': [0], '10 kw_7': [0], 'frequency_8': [1], '100.0_9': [1], '2_10': [3]} | ['branding', 'callsign', 'frequency', 'power ( kw )', 'location'] | [['mor 103.1 baguio for life !', 'dzrr - fm', '103.1 mhz', '10 kw', 'baguio'], ['mor 95.5 laoag for life !', 'dwel - fm', '95.5 mhz', '10 kw', 'laoag'], ['mor 94.3 dagupan for life !', 'dwec - fm', '94.3 mhz', '10 kw', 'dagupan'], ['mor 99.9 puerto princesa for life !', 'dycu - fm', '99.9 mhz', '5 kw', 'puerto princesa'], ['mor 99.7 española for life !', 'dyea - fm', '99.7 mhz', '5 kw', 'sofronio española'], ['mor 93.5 naga for life !', 'dwac - fm', '93.5 mhz', '10 kw', 'naga'], ['mor 93.9 legazpi for life !', 'dwrd - fm', '93.9 mhz', '10 kw', 'legazpi'], ['mor 91.1 iloilo for life !', 'dymc - fm', '91.1 mhz', '10 kw', 'iloilo'], ['mor 101.5 bacolod for life !', 'dyoo - fm', '101.5 mhz', '10 kw', 'bacolod'], ['mor 97.1 cebu for life !', 'dyls - fm', '97.1 mhz', '20 kw', 'cebu'], ['mor 94.3 tacloban for life !', 'dytc - fm', '94.3 mhz', '10 kw', 'tacloban'], ['mor 98.7 zamboanga for life !', 'dxfh - fm', '98.7 mhz', '10 kw', 'zamboanga'], ['mor 91.9 cagayan de oro for life !', 'dxec - fm', '91.9 mhz', '10 kw', 'cagayan de oro'], ['mor 101.1 davao for life !', 'dxrr - fm', '101.1 mhz', '20 kw', 'davao'], ['mor 92.7 general santos for life !', 'dxbc - fm', '92.7 mhz', '10 kw', 'general santos']] |
2008 - 09 phoenix suns season | https://en.wikipedia.org/wiki/2008%E2%80%9309_Phoenix_Suns_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17340355-8.html.csv | count | during this period of the 2008-09 phoenix suns season , the phoenix suns played golden state two times . | {'scope': 'all', 'criterion': 'equal', 'value': 'golden state', 'result': '2', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'team', 'golden state'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose team record fuzzily matches to golden state .', 'tostr': 'filter_eq { all_rows ; team ; golden state }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; team ; golden state } }', 'tointer': 'select the rows whose team record fuzzily matches to golden state . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; team ; golden state } } ; 2 } = true', 'tointer': 'select the rows whose team record fuzzily matches to golden state . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; team ; golden state } } ; 2 } = true | select the rows whose team record fuzzily matches to golden state . 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, 'team_5': 5, 'golden state_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', 'team_5': 'team', 'golden state_6': 'golden state', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'team_5': [0], 'golden state_6': [0], '2_7': [2]} | ['game', 'date', 'team', 'score', 'high points', 'high assists', 'location attendance', 'record'] | [['46', 'february 2', 'sacramento', 'w 129 - 81 ( ot )', "amar ' e stoudemire ( 25 )", 'steve nash ( 9 )', 'us airways center 18422', '26 - 20'], ['47', 'february 4', 'golden state', 'l 112 - 124 ( ot )', 'jason richardson ( 24 )', 'steve nash ( 9 )', 'oracle arena 19596', '26 - 21'], ['48', 'february 6', 'golden state', 'w 115 - 105 ( ot )', 'grant hill ( 27 )', 'steve nash ( 8 )', 'us airways center 18422', '27 - 21'], ['49', 'february 8', 'detroit', 'w 107 - 97 ( ot )', 'jason richardson ( 21 )', 'steve nash ( 21 )', 'the palace of auburn hills 22076', '28 - 21'], ['50', 'february 9', 'philadelphia', 'l 91 - 108 ( ot )', "amar ' e stoudemire ( 19 )", 'steve nash ( 8 )', 'wachovia center 16797', '28 - 22'], ['51', 'february 11', 'cleveland', 'l 92 - 109 ( ot )', "amar ' e stoudemire ( 27 )", 'leandro barbosa ( 7 )', 'quicken loans arena 20562', '28 - 23'], ['52', 'february 17', 'la clippers', 'w 140 - 100 ( ot )', 'leandro barbosa ( 24 )', 'steve nash ( 10 )', 'us airways center 18422', '29 - 23'], ['53', 'february 18', 'la clippers', 'w 142 - 119 ( ot )', "amar ' e stoudemire ( 42 )", 'steve nash ( 12 )', 'staples center 18169', '30 - 23'], ['54', 'february 20', 'oklahoma city', 'w 140 - 118 ( ot )', 'leandro barbosa ( 41 )', 'matt barnes ( 9 )', 'us airways center 18422', '31 - 23'], ['55', 'february 22', 'boston', 'l 108 - 128 ( ot )', 'jason richardson ( 21 )', 'steve nash ( 11 )', 'us airways center 18422', '31 - 24'], ['56', 'february 24', 'charlotte', 'w 112 - 102 ( ot )', 'steve nash ( 22 )', 'steve nash ( 5 )', 'us airways center 18422', '32 - 24'], ['57', 'february 26', 'la lakers', 'l 106 - 132 ( ot )', 'leandro barbosa ( 18 )', 'leandro barbosa ( 7 )', 'staples center 18997', '32 - 25'], ['58', 'february 27', 'toronto', 'w 133 - 113 ( ot )', "shaquille o'neal ( 45 )", 'grant hill ( 12 )', 'us airways center 18422', '33 - 25']] |
2008 - 09 denver nuggets season | https://en.wikipedia.org/wiki/2008%E2%80%9309_Denver_Nuggets_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17355408-5.html.csv | majority | all games of the 2008 - 09 denver nuggets ' season were scheduled for the month of december . | {'scope': 'all', 'col': '2', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'december', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'date', 'december'], 'result': True, 'ind': 0, 'tointer': 'for the date records of all rows , all of them fuzzily match to december .', 'tostr': 'all_eq { all_rows ; date ; december } = true'} | all_eq { all_rows ; date ; december } = true | for the date records of all rows , all of them fuzzily match to december . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'date_3': 3, 'december_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'date_3': 'date', 'december_4': 'december'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'date_3': [0], 'december_4': [0]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record'] | [['19', 'december 2', 'toronto', 'w 132 - 93 ( ot )', 'chauncey billups ( 24 )', 'nenê ( 11 )', 'chauncey billups ( 14 )', 'pepsi center 14243', '13 - 6'], ['20', 'december 4', 'san antonio', 'l 91 - 108 ( ot )', 'carmelo anthony ( 16 )', 'j r smith ( 10 )', 'j r smith , chauncey billups ( 4 )', 'pepsi center 15866', '13 - 7'], ['21', 'december 6', 'sacramento', 'w 118 - 85 ( ot )', 'chauncey billups ( 24 )', 'nenê , carmelo anthony ( 7 )', 'chauncey billups ( 4 )', 'arco arena 12322', '14 - 7'], ['22', 'december 10', 'minnesota', 'w 116 - 105 ( ot )', 'carmelo anthony ( 45 )', 'carmelo anthony ( 11 )', 'chauncey billups ( 6 )', 'pepsi center 14007', '15 - 7'], ['23', 'december 13', 'golden state', 'w 123 - 105 ( ot )', 'carmelo anthony ( 27 )', 'carmelo anthony ( 9 )', 'chauncey billups ( 11 )', 'pepsi center 15322', '16 - 7'], ['24', 'december 15', 'dallas', 'w 98 - 88 ( ot )', 'j r smith ( 25 )', 'kenyon martin ( 10 )', 'chauncey billups ( 8 )', 'american airlines center 19969', '17 - 7'], ['25', 'december 16', 'houston', 'l 96 - 108 ( ot )', 'carmelo anthony ( 22 )', 'kenyon martin ( 8 )', 'chauncey billups ( 6 )', 'toyota center 17737', '17 - 8'], ['26', 'december 19', 'cleveland', 'l 88 - 105 ( ot )', 'chauncey billups ( 16 )', 'chris andersen ( 10 )', 'anthony carter , j r smith ( 4 )', 'pepsi center 19155', '17 - 9'], ['27', 'december 20', 'phoenix', 'l 101 - 108 ( ot )', 'j r smith ( 23 )', 'nenê ( 15 )', 'chauncey billups ( 8 )', 'us airways center 18422', '17 - 10'], ['28', 'december 22', 'portland', 'w 97 - 89 ( ot )', 'chauncey billups , nenê ( 19 )', 'kenyon martin ( 12 )', 'chauncey billups ( 10 )', 'pepsi center 18611', '18 - 10'], ['29', 'december 23', 'portland', 'l 92 - 101 ( ot )', 'linas kleiza ( 20 )', 'nenê ( 13 )', 'chucky atkins ( 4 )', 'rose garden 20007', '18 - 11'], ['30', 'december 26', 'philadelphia', 'w 105 - 101 ( ot )', 'j r smith ( 27 )', 'nenê ( 12 )', 'chauncey billups ( 10 )', 'pepsi center 19155', '19 - 11'], ['31', 'december 28', 'new york', 'w 117 - 110 ( ot )', 'carmelo anthony ( 32 )', 'carmelo anthony , nenê ( 9 )', 'chauncey billups ( 5 )', 'madison square garden 19763', '20 - 11'], ['32', 'december 29', 'atlanta', 'l 91 - 109 ( ot )', 'kenyon martin ( 19 )', 'chris andersen ( 6 )', 'anthony carter ( 7 )', 'philips arena 17131', '20 - 12'], ['33', 'december 31', 'toronto', 'w 114 - 107 ( ot )', 'nenê ( 21 )', 'chris andersen ( 10 )', 'chauncey billups ( 7 )', 'air canada centre 18879', '21 - 12']] |
1984 pga championship | https://en.wikipedia.org/wiki/1984_PGA_Championship | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18155811-3.html.csv | majority | in the 1984 pga championship , most of the players in the top 10 finishers were from the united states . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'united states', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'country', 'united states'], 'result': True, 'ind': 0, 'tointer': 'for the country records of all rows , most of them fuzzily match to united states .', 'tostr': 'most_eq { all_rows ; country ; united states } = true'} | most_eq { all_rows ; country ; united states } = true | for the country records of all rows , most of them fuzzily match to united states . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'country_3': 3, 'united states_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'country_3': 'country', 'united states_4': 'united states'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'country_3': [0], 'united states_4': [0]} | ['place', 'player', 'country', 'score', 'to par', 'money'] | [['1', 'lee trevino', 'united states', '69 + 68 + 67 + 69 = 273', '- 15', '125000'], ['t2', 'gary player', 'south africa', '74 + 63 + 69 + 71 = 277', '- 11', '62500'], ['t2', 'lanny wadkins', 'united states', '68 + 69 + 68 + 72 = 277', '- 11', '62500'], ['4', 'calvin peete', 'united states', '71 + 70 + 69 + 68 = 278', '- 10', '35000'], ['5', 'seve ballesteros', 'spain', '70 + 69 + 70 + 70 = 279', '- 9', '25000'], ['t6', 'gary hallberg', 'united states', '69 + 71 + 68 + 72 = 280', '- 8', '17125'], ['t6', 'larry mize', 'united states', '71 + 69 + 67 + 73 = 280', '- 8', '17125'], ['t6', 'scott simpson', 'united states', '69 + 69 + 72 + 70 = 280', '- 8', '17125'], ['t6', 'hal sutton', 'united states', '74 + 73 + 64 + 69 = 280', '- 8', '17125'], ['t10', 'russ cochran', 'united states', '73 + 68 + 73 + 67 = 281', '- 7', '12083'], ['t10', 'tsuneyuki nakajima', 'japan', '72 + 68 + 67 + 74 = 281', '- 7', '12083'], ['t10', 'victor regalado', 'mexico', '69 + 69 + 73 + 70 = 281', '- 7', '12083']] |
1944 vfl season | https://en.wikipedia.org/wiki/1944_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10809142-14.html.csv | aggregation | the average score of the guest teams in the matches is approximately 12.00 . | {'scope': 'all', 'col': '4', 'type': 'average', 'result': '11.94', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'away team score'], 'result': '11.94', 'ind': 0, 'tostr': 'avg { all_rows ; away team score }'}, '11.94'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; away team score } ; 11.94 } = true', 'tointer': 'the average of the away team score record of all rows is 11.94 .'} | round_eq { avg { all_rows ; away team score } ; 11.94 } = true | the average of the away team score record of all rows is 11.94 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'away team score_4': 4, '11.94_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'away team score_4': 'away team score', '11.94_5': '11.94'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'away team score_4': [0], '11.94_5': [1]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['st kilda', '7.12 ( 54 )', 'south melbourne', '10.19 ( 79 )', 'junction oval', '8000', '5 august 1944'], ['geelong', '11.20 ( 86 )', 'hawthorn', '9.7 ( 61 )', 'kardinia park', '7000', '5 august 1944'], ['collingwood', '8.12 ( 60 )', 'footscray', '15.9 ( 99 )', 'victoria park', '9000', '5 august 1944'], ['carlton', '4.14 ( 38 )', 'melbourne', '8.6 ( 54 )', 'princes park', '10000', '5 august 1944'], ['north melbourne', '11.12 ( 78 )', 'fitzroy', '15.11 ( 101 )', 'arden street oval', '14000', '5 august 1944'], ['richmond', '11.17 ( 83 )', 'essendon', '12.15 ( 87 )', 'punt road oval', '26000', '5 august 1944']] |
1978 san diego chargers season | https://en.wikipedia.org/wiki/1978_San_Diego_Chargers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15385921-2.html.csv | aggregation | a total of 791,469 fans attended games during the 1978 san diego chargers season . | {'scope': 'all', 'col': '5', 'type': 'sum', 'result': '791,469', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'attendance'], 'result': '791,469', 'ind': 0, 'tostr': 'sum { all_rows ; attendance }'}, '791,469'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; attendance } ; 791,469 } = true', 'tointer': 'the sum of the attendance record of all rows is 791,469 .'} | round_eq { sum { all_rows ; attendance } ; 791,469 } = true | the sum of the attendance record of all rows is 791,469 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'attendance_4': 4, '791,469_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'attendance_4': 'attendance', '791,469_5': '791,469'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'attendance_4': [0], '791,469_5': [1]} | ['week', 'date', 'opponent', 'result', 'attendance'] | [['1', 'september 3 , 1978', 'seattle seahawks', 'w 24 - 20', '55778'], ['2', 'september 10 , 1978', 'oakland raiders', 'l 21 - 20', '51653'], ['3', 'september 17 , 1978', 'denver broncos', 'l 27 - 14', '74983'], ['4', 'september 24 , 1978', 'green bay packers', 'l 24 - 3', '42755'], ['5', 'october 1 , 1978', 'new england patriots', 'l 28 - 23', '60781'], ['6', 'october 8 , 1978', 'denver broncos', 'w 23 - 0', '50077'], ['7', 'october 15 , 1978', 'miami dolphins', 'l 28 - 21', '50637'], ['8', 'october 22 , 1978', 'detroit lions', 'l 31 - 14', '54031'], ['9', 'october 29 , 1978', 'oakland raiders', 'w 27 - 23', '52612'], ['10', 'november 5 , 1978', 'cincinnati bengals', 'w 22 - 13', '43639'], ['11', 'november 12 , 1978', 'kansas city chiefs', 'w 29 - 23', '41395'], ['12', 'november 19 , 1978', 'minnesota vikings', 'w 13 - 7', '38859'], ['13', 'november 26 , 1978', 'kansas city chiefs', 'l 23 - 0', '26248'], ['14', 'december 4 , 1978', 'chicago bears', 'w 40 - 7', '48492'], ['15', 'december 10 , 1978', 'seattle seahawks', 'w 37 - 10', '49975'], ['16', 'december 17 , 1978', 'houston oilers', 'w 45 - 24', '49554']] |
daren kagasoff | https://en.wikipedia.org/wiki/Daren_Kagasoff | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18381900-1.html.csv | count | daren kagasoff had a result of nominated five times . | {'scope': 'all', 'criterion': 'equal', 'value': 'nominated', 'result': '5', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'result', 'nominated'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose result record fuzzily matches to nominated .', 'tostr': 'filter_eq { all_rows ; result ; nominated }'}], 'result': '5', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; result ; nominated } }', 'tointer': 'select the rows whose result record fuzzily matches to nominated . the number of such rows is 5 .'}, '5'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; result ; nominated } } ; 5 } = true', 'tointer': 'select the rows whose result record fuzzily matches to nominated . the number of such rows is 5 .'} | eq { count { filter_eq { all_rows ; result ; nominated } } ; 5 } = true | select the rows whose result record fuzzily matches to nominated . the number of such rows is 5 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'result_5': 5, 'nominated_6': 6, '5_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'result_5': 'result', 'nominated_6': 'nominated', '5_7': '5'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'result_5': [0], 'nominated_6': [0], '5_7': [2]} | ['year', 'award', 'work', 'category', 'result'] | [['2009', 'teen choice awards', 'the secret life of the american teenager', 'choice summer tv star : male', 'won'], ['2009', 'teen choice awards', 'the secret life of the american teenager', 'choice tv breakout star : male', 'nominated'], ['2010', 'teen choice awards', 'the secret life of the american teenager', 'choice tv actor : drama', 'nominated'], ['2010', 'teen choice awards', 'the secret life of the american teenager', 'choice summer tv star : male', 'nominated'], ['2011', 'teen choice awards', 'the secret life of the american teenager', 'choice tv actor : drama', 'nominated'], ['2012', 'teen choice awards', 'the secret life of the american teenager', 'choice summer tv star : male', 'nominated']] |
mahendra singh dhoni | https://en.wikipedia.org/wiki/Mahendra_Singh_Dhoni | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1695229-6.html.csv | count | mahendra singh dhoni played matches in eden gardens twice . | {'scope': 'all', 'criterion': 'equal', 'value': 'eden gardens', 'result': '2', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'stadium', 'eden gardens'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose stadium record fuzzily matches to eden gardens .', 'tostr': 'filter_eq { all_rows ; stadium ; eden gardens }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; stadium ; eden gardens } }', 'tointer': 'select the rows whose stadium record fuzzily matches to eden gardens . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; stadium ; eden gardens } } ; 2 } = true', 'tointer': 'select the rows whose stadium record fuzzily matches to eden gardens . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; stadium ; eden gardens } } ; 2 } = true | select the rows whose stadium record fuzzily matches to eden gardens . 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, 'stadium_5': 5, 'eden gardens_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', 'stadium_5': 'stadium', 'eden gardens_6': 'eden gardens', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'stadium_5': [0], 'eden gardens_6': [0], '2_7': [2]} | ['runs', 'match', 'stadium', 'city / country', 'year'] | [['runs', 'match', 'stadium', 'city / country', 'year'], ['148', '5', 'iqbal stadium', 'faisalabad , pakistan', '2006'], ['110', '38', 'sardar patel stadium', 'ahmedabad , india', '2009'], ['100', '40', 'brabourne stadium', 'mumbai , india', '2009'], ['132', '42', 'eden gardens', 'kolkata , india', '2010'], ['144', '63', 'eden gardens', 'kolkata , india', '2011'], ['224', '74', 'ma chidambaram stadium', 'chennai , india', '2013']] |
venezuela at the olympics | https://en.wikipedia.org/wiki/Venezuela_at_the_Olympics | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14778294-1.html.csv | ordinal | the 2nd gold medal won by venezuela at the olympics was won in men 's épée . | {'scope': 'subset', 'row': '12', 'col': '3', 'order': '2', 'col_other': '5', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'subset': {'col': '1', 'criterion': 'equal', 'value': 'gold'}} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'medal', 'gold'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; medal ; gold }', 'tointer': 'select the rows whose medal record fuzzily matches to gold .'}, 'games', '2'], 'result': None, 'ind': 1, 'tostr': 'nth_argmin { filter_eq { all_rows ; medal ; gold } ; games ; 2 }'}, 'event'], 'result': "men 's épée", 'ind': 2, 'tostr': 'hop { nth_argmin { filter_eq { all_rows ; medal ; gold } ; games ; 2 } ; event }'}, "men 's épée"], 'result': True, 'ind': 3, 'tostr': "eq { hop { nth_argmin { filter_eq { all_rows ; medal ; gold } ; games ; 2 } ; event } ; men 's épée } = true", 'tointer': "select the rows whose medal record fuzzily matches to gold . select the row whose games record of these rows is 2nd minimum . the event record of this row is men 's épée ."} | eq { hop { nth_argmin { filter_eq { all_rows ; medal ; gold } ; games ; 2 } ; event } ; men 's épée } = true | select the rows whose medal record fuzzily matches to gold . select the row whose games record of these rows is 2nd minimum . the event record of this row is men 's épée . | 4 | 4 | {'str_eq_3': 3, 'result_4': 4, 'str_hop_2': 2, 'nth_argmin_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'medal_6': 6, 'gold_7': 7, 'games_8': 8, '2_9': 9, 'event_10': 10, "men 's épée_11": 11} | {'str_eq_3': 'str_eq', 'result_4': 'true', 'str_hop_2': 'str_hop', 'nth_argmin_1': 'nth_argmin', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'medal_6': 'medal', 'gold_7': 'gold', 'games_8': 'games', '2_9': '2', 'event_10': 'event', "men 's épée_11": "men 's épée"} | {'str_eq_3': [4], 'result_4': [], 'str_hop_2': [3], 'nth_argmin_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'medal_6': [0], 'gold_7': [0], 'games_8': [1], '2_9': [1], 'event_10': [2], "men 's épée_11": [3]} | ['medal', 'name', 'games', 'sport', 'event'] | [['bronze', 'arnoldo devonish', '1952 helsinki', 'athletics', "men 's triple jump"], ['bronze', 'enrico forcella', '1960 rome', 'shooting', "men 's 50 metre rifle prone"], ['gold', 'francisco rodriguez', '1968 mexico city', 'boxing', "men 's light flyweight"], ['silver', 'pedro gamarro', '1976 montreal', 'boxing', "men 's welterweight"], ['silver', 'bernardo piñango', '1980 moscow', 'boxing', "men 's bantamweight"], ['bronze', 'marcelino bolivar', '1984 los angeles', 'boxing', "men 's light flyweight"], ['bronze', 'omar catari', '1984 los angeles', 'boxing', "men 's featherweight"], ['bronze', 'rafael vidal', '1984 los angeles', 'swimming', "men 's 200 m butterfly"], ['bronze', 'adriana carmona', '2004 athens', 'taekwondo', 'women + 67 kg'], ['bronze', 'israel jose rubio', '2004 athens', 'weightlifting', "men 's featherweight"], ['bronze', 'dalia contreras', '2008 beijing', 'taekwondo', 'women 49 kg'], ['gold', 'rubén limardo', '2012 london', 'fencing', "men 's épée"]] |
united states house of representatives elections , 1956 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1956 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1341973-3.html.csv | ordinal | george m grant was the second earliest incumbent representative to first get elected in the alabama election . | {'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': 'george m grant', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; first elected ; 2 } ; incumbent }'}, 'george m grant'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; first elected ; 2 } ; incumbent } ; george m grant } = true', 'tointer': 'select the row whose first elected record of all rows is 2nd minimum . the incumbent record of this row is george m grant .'} | eq { hop { nth_argmin { all_rows ; first elected ; 2 } ; incumbent } ; george m grant } = true | select the row whose first elected record of all rows is 2nd minimum . the incumbent record of this row is george m grant . | 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, 'george m grant_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', 'george m grant_8': 'george m grant'} | {'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], 'george m grant_8': [2]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['alabama 1', 'frank w boykin', 'democratic', '1935', 're - elected', 'frank w boykin ( d ) unopposed'], ['alabama 2', 'george m grant', 'democratic', '1938', 're - elected', 'george m grant ( d ) unopposed'], ['alabama 3', 'george w andrews', 'democratic', '1944', 're - elected', 'george w andrews ( d ) unopposed'], ['alabama 4', 'kenneth a roberts', 'democratic', '1950', 're - elected', 'kenneth a roberts ( d ) 73.4 % roy banks ( r ) 26.6 %'], ['alabama 5', 'albert rains', 'democratic', '1944', 're - elected', 'albert rains ( d ) unopposed'], ['alabama 6', 'armistead i selden , jr', 'democratic', '1952', 're - elected', 'armistead i selden , jr ( d ) unopposed']] |
1971 - 72 philadelphia flyers season | https://en.wikipedia.org/wiki/1971%E2%80%9372_Philadelphia_Flyers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14293527-13.html.csv | ordinal | glen irwin was drafted third of all players by the flyers in the 1971 draft . | {'row': '3', 'col': '1', 'order': '3', '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', 'round', '3'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; round ; 3 }'}, 'player'], 'result': 'glen irwin', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; round ; 3 } ; player }'}, 'glen irwin'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; round ; 3 } ; player } ; glen irwin } = true', 'tointer': 'select the row whose round record of all rows is 3rd minimum . the player record of this row is glen irwin .'} | eq { hop { nth_argmin { all_rows ; round ; 3 } ; player } ; glen irwin } = true | select the row whose round record of all rows is 3rd minimum . the player record of this row is glen irwin . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'round_5': 5, '3_6': 6, 'player_7': 7, 'glen irwin_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', 'round_5': 'round', '3_6': '3', 'player_7': 'player', 'glen irwin_8': 'glen irwin'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'round_5': [0], '3_6': [0], 'player_7': [1], 'glen irwin_8': [2]} | ['round', 'player', 'position', 'nationality', 'college / junior / club team ( league )'] | [['1', 'larry wright', 'center', 'canada', 'regina pats ( wchl )'], ['1', 'pierre plante', 'right wing', 'canada', 'drummondville rangers ( qmjhl )'], ['3', 'glen irwin', 'defense', 'canada', 'estevan bruins ( wchl )'], ['4', 'ted scharf', 'right wing', 'canada', 'kitchener rangers ( oha )'], ['5', 'don mcculloch', 'defense', 'canada', 'niagara falls flyers ( oha )'], ['6', 'yvon bilodeau', 'defense', 'canada', 'estevan bruins ( wchl )'], ['7', 'bobby gerard', 'right wing', 'canada', 'regina pats ( wchl )'], ['8', 'jerome mrazek', 'goaltender', 'canada', 'minnesota - duluth bulldogs ( wcha )']] |
southern league cup ( scotland ) | https://en.wikipedia.org/wiki/Southern_League_Cup_%28Scotland%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16880170-1.html.csv | superlative | the latest season the rangers won scotland southern league cup was 1944-45 . | {'scope': 'subset', 'col_superlative': '1', 'row_superlative': '5', 'value_mentioned': 'yes', 'max_or_min': 'max', 'other_col': '2', 'subset': {'col': '2', 'criterion': 'equal', 'value': 'rangers'}} | {'func': 'eq', 'args': [{'func': 'max', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'winner', 'rangers'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; winner ; rangers }', 'tointer': 'select the rows whose winner record fuzzily matches to rangers .'}, 'season'], 'result': '1944 - 45', 'ind': 1, 'tostr': 'max { filter_eq { all_rows ; winner ; rangers } ; season }', 'tointer': 'select the rows whose winner record fuzzily matches to rangers . the maximum season record of these rows is 1944 - 45 .'}, '1944 - 45'], 'result': True, 'ind': 2, 'tostr': 'eq { max { filter_eq { all_rows ; winner ; rangers } ; season } ; 1944 - 45 } = true', 'tointer': 'select the rows whose winner record fuzzily matches to rangers . the maximum season record of these rows is 1944 - 45 .'} | eq { max { filter_eq { all_rows ; winner ; rangers } ; season } ; 1944 - 45 } = true | select the rows whose winner record fuzzily matches to rangers . the maximum season record of these rows is 1944 - 45 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'max_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'winner_5': 5, 'rangers_6': 6, 'season_7': 7, '1944 - 45_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'max_1': 'max', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'winner_5': 'winner', 'rangers_6': 'rangers', 'season_7': 'season', '1944 - 45_8': '1944 - 45'} | {'eq_2': [3], 'result_3': [], 'max_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'winner_5': [0], 'rangers_6': [0], 'season_7': [1], '1944 - 45_8': [2]} | ['season', 'winner', 'score', 'runner - up', 'venue'] | [['1940 - 41', 'rangers', '4 - 2 ( rep )', 'heart of midlothian', 'hampden park'], ['1941 - 42', 'rangers', '2 - 0', 'morton', 'hampden park'], ['1942 - 43', 'rangers', '1 - 1 ( 11 - 3 corners )', 'falkirk', 'hampden park'], ['1943 - 44', 'hibernian', '0 - 0 ( 6 - 5 corners )', 'rangers', 'hampden park'], ['1944 - 45', 'rangers', '2 - 1', 'motherwell', 'hampden park'], ['1945 - 46', 'aberdeen', '3 - 2', 'rangers', 'hampden park']] |
1982 vfl season | https://en.wikipedia.org/wiki/1982_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10824095-9.html.csv | aggregation | 134,131 people attended games played during the 1982 vfl season . | {'scope': 'all', 'col': '6', 'type': 'sum', 'result': '134,131', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'crowd'], 'result': '134,131', 'ind': 0, 'tostr': 'sum { all_rows ; crowd }'}, '134,131'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; crowd } ; 134,131 } = true', 'tointer': 'the sum of the crowd record of all rows is 134,131 .'} | round_eq { sum { all_rows ; crowd } ; 134,131 } = true | the sum of the crowd record of all rows is 134,131 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'crowd_4': 4, '134,131_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'crowd_4': 'crowd', '134,131_5': '134,131'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'crowd_4': [0], '134,131_5': [1]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['essendon', '19.19 ( 133 )', 'melbourne', '12.13 ( 85 )', 'windy hill', '22403', '22 may 1982'], ['collingwood', '13.14 ( 92 )', 'hawthorn', '17.12 ( 114 )', 'victoria park', '24904', '22 may 1982'], ['carlton', '27.23 ( 185 )', 'swans', '12.11 ( 83 )', 'princes park', '23954', '22 may 1982'], ['richmond', '21.13 ( 139 )', 'footscray', '14.14 ( 98 )', 'mcg', '22493', '22 may 1982'], ['st kilda', '16.19 ( 115 )', 'fitzroy', '25.12 ( 162 )', 'moorabbin oval', '15140', '22 may 1982'], ['geelong', '15.19 ( 109 )', 'north melbourne', '9.9 ( 63 )', 'vfl park', '25237', '22 may 1982']] |
mondo film | https://en.wikipedia.org/wiki/Mondo_film | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1176486-1.html.csv | ordinal | addio zio tom is the mondo film movie that has the second highest uncut run time . | {'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', 'uncut run time', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; uncut run time ; 2 }'}, 'title'], 'result': 'addio zio tom', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; uncut run time ; 2 } ; title }'}, 'addio zio tom'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; uncut run time ; 2 } ; title } ; addio zio tom } = true', 'tointer': 'select the row whose uncut run time record of all rows is 2nd maximum . the title record of this row is addio zio tom .'} | eq { hop { nth_argmax { all_rows ; uncut run time ; 2 } ; title } ; addio zio tom } = true | select the row whose uncut run time record of all rows is 2nd maximum . the title record of this row is addio zio tom . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'uncut run time_5': 5, '2_6': 6, 'title_7': 7, 'addio zio tom_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', 'uncut run time_5': 'uncut run time', '2_6': '2', 'title_7': 'title', 'addio zio tom_8': 'addio zio tom'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'uncut run time_5': [0], '2_6': [0], 'title_7': [1], 'addio zio tom_8': [2]} | ['title', 'year', 'country', 'music', 'uncut run time'] | [['mondo cane', '1962', 'italy', 'riz ortolani', '108 minutes'], ['la donna nel mondo', '1963', 'italy', 'riz ortolani nino oliviero', '107 minutes'], ['mondo cane 2', '1963', 'italy', 'nino oliviero', '95 minutes'], ['africa addio', '1966', 'italy', 'riz ortolani', '139 minutes'], ['addio zio tom', '1971', 'italy', 'riz ortolani', '136 minutes']] |
united states house of representatives elections , 1950 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1950 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1342198-33.html.csv | ordinal | in the united states house of representatives elections in 1950 , of the candidates who ran unopposed , john h kerr had been in office the longest . | {'scope': 'subset', 'row': '1', 'col': '4', 'order': '1', 'col_other': '2', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'subset': {'col': '6', 'criterion': 'fuzzily_match', 'value': 'unopposed'}} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'candidates', 'unopposed'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; candidates ; unopposed }', 'tointer': 'select the rows whose candidates record fuzzily matches to unopposed .'}, 'first elected', '1'], 'result': None, 'ind': 1, 'tostr': 'nth_argmin { filter_eq { all_rows ; candidates ; unopposed } ; first elected ; 1 }'}, 'incumbent'], 'result': 'john h kerr', 'ind': 2, 'tostr': 'hop { nth_argmin { filter_eq { all_rows ; candidates ; unopposed } ; first elected ; 1 } ; incumbent }'}, 'john h kerr'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { nth_argmin { filter_eq { all_rows ; candidates ; unopposed } ; first elected ; 1 } ; incumbent } ; john h kerr } = true', 'tointer': 'select the rows whose candidates record fuzzily matches to unopposed . select the row whose first elected record of these rows is 1st minimum . the incumbent record of this row is john h kerr .'} | eq { hop { nth_argmin { filter_eq { all_rows ; candidates ; unopposed } ; first elected ; 1 } ; incumbent } ; john h kerr } = true | select the rows whose candidates record fuzzily matches to unopposed . select the row whose first elected record of these rows is 1st minimum . the incumbent record of this row is john h kerr . | 4 | 4 | {'str_eq_3': 3, 'result_4': 4, 'str_hop_2': 2, 'nth_argmin_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'candidates_6': 6, 'unopposed_7': 7, 'first elected_8': 8, '1_9': 9, 'incumbent_10': 10, 'john h kerr_11': 11} | {'str_eq_3': 'str_eq', 'result_4': 'true', 'str_hop_2': 'str_hop', 'nth_argmin_1': 'nth_argmin', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'candidates_6': 'candidates', 'unopposed_7': 'unopposed', 'first elected_8': 'first elected', '1_9': '1', 'incumbent_10': 'incumbent', 'john h kerr_11': 'john h kerr'} | {'str_eq_3': [4], 'result_4': [], 'str_hop_2': [3], 'nth_argmin_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'candidates_6': [0], 'unopposed_7': [0], 'first elected_8': [1], '1_9': [1], 'incumbent_10': [2], 'john h kerr_11': [3]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['north carolina 2', 'john h kerr', 'democratic', '1923', 're - elected', 'john h kerr ( d ) unopposed'], ['north carolina 3', 'graham arthur barden', 'democratic', '1934', 're - elected', 'graham arthur barden ( d ) unopposed'], ['north carolina 4', 'harold d cooley', 'democratic', '1934', 're - elected', 'harold d cooley ( d ) 72.8 % ray f swain ( r ) 27.2 %'], ['north carolina 5', 'richard thurmond chatham', 'democratic', '1948', 're - elected', 'richard thurmond chatham ( d ) unopposed'], ['north carolina 6', 'carl t durham', 'democratic', '1938', 're - elected', 'carl t durham ( d ) 75.4 % a a mcdonald ( r ) 24.6 %']] |
water polo at the 2004 summer olympics - women 's team rosters | https://en.wikipedia.org/wiki/Water_polo_at_the_2004_Summer_Olympics_%E2%80%93_Women%27s_team_rosters | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17774593-2.html.csv | count | in water polo at the 2004 summer olympics , 2 of the participants from the kfc breakers club were born in 1974 . | {'scope': 'subset', 'criterion': 'fuzzily_match', 'value': '1974', 'result': '2', 'col': '5', 'subset': {'col': '6', 'criterion': 'equal', 'value': 'kfc breakers'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'club', 'kfc breakers'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; club ; kfc breakers }', 'tointer': 'select the rows whose club record fuzzily matches to kfc breakers .'}, 'date of birth', '1974'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose club record fuzzily matches to kfc breakers . among these rows , select the rows whose date of birth record fuzzily matches to 1974 .', 'tostr': 'filter_eq { filter_eq { all_rows ; club ; kfc breakers } ; date of birth ; 1974 }'}], 'result': '2', 'ind': 2, 'tostr': 'count { filter_eq { filter_eq { all_rows ; club ; kfc breakers } ; date of birth ; 1974 } }', 'tointer': 'select the rows whose club record fuzzily matches to kfc breakers . among these rows , select the rows whose date of birth record fuzzily matches to 1974 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_eq { filter_eq { all_rows ; club ; kfc breakers } ; date of birth ; 1974 } } ; 2 } = true', 'tointer': 'select the rows whose club record fuzzily matches to kfc breakers . among these rows , select the rows whose date of birth record fuzzily matches to 1974 . the number of such rows is 2 .'} | eq { count { filter_eq { filter_eq { all_rows ; club ; kfc breakers } ; date of birth ; 1974 } } ; 2 } = true | select the rows whose club record fuzzily matches to kfc breakers . among these rows , select the rows whose date of birth record fuzzily matches to 1974 . 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, 'club_6': 6, 'kfc breakers_7': 7, 'date of birth_8': 8, '1974_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', 'club_6': 'club', 'kfc breakers_7': 'kfc breakers', 'date of birth_8': 'date of birth', '1974_9': '1974', '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], 'club_6': [0], 'kfc breakers_7': [0], 'date of birth_8': [1], '1974_9': [1], '2_10': [3]} | ['name', 'pos', 'height', 'weight', 'date of birth', 'club'] | [['emma knox', 'gk', 'm ( ft 8in )', '-', '1978 - 03 - 02', 'uwa comets'], ['rebecca rippon', 'd', 'm ( ft 5in )', '-', '1978 - 12 - 26', 'balmain tigers'], ['nikita cuffe', 'cf', 'm ( ft 10in )', '-', '1979 - 09 - 26', 'kfc breakers'], ['naomi castle', 'cb', 'm ( ft 11in )', '-', '1974 - 05 - 29', 'kfc breakers'], ['bronwyn smith', 'd', 'm ( ft 9in )', '-', '1974 - 07 - 03', 'kfc breakers'], ['belinda brooks', 'cb', 'm ( ft 9in )', '-', '1977 - 02 - 03', 'fremantle marlins'], ['jodie stuhmcke', 'cf', 'm ( ft 11in )', '-', '1980 - 11 - 21', 'kfc breakers'], ['kate gynther', 'd', 'm ( ft 9in )', '-', '1982 - 07 - 05', 'brisbane barracudas'], ['elise norwood', 'd', 'm ( ft 8in )', '-', '1981 - 06 - 18', 'sydney university lions'], ['kelly heuchan', 'd', 'm ( ft 9in )', '-', '1980 - 01 - 30', 'fremantle marlins'], ['jemma brownlow', 'gk', 'm ( ft 6in )', '-', '1979 - 11 - 14', 'balmain tigers'], ['joanne fox', 'cb', 'm ( ft 0in )', '-', '1979 - 06 - 12', 'balmain tigers'], ['melissa rippon', 'd', 'm ( ft 7in )', '-', '1981 - 01 - 20', 'brisbane barracudas']] |
high - speed rail in europe | https://en.wikipedia.org/wiki/High-speed_rail_in_Europe | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14227171-10.html.csv | comparative | the sofia dragoman line is shorter than the vidin sofia line . | {'row_1': '6', 'row_2': '7', 'col': '3', 'col_other': '1', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'line', 'sofia - dragoman'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose line record fuzzily matches to sofia - dragoman .', 'tostr': 'filter_eq { all_rows ; line ; sofia - dragoman }'}, 'length'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; line ; sofia - dragoman } ; length }', 'tointer': 'select the rows whose line record fuzzily matches to sofia - dragoman . take the length record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'line', 'vidin - sofia'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose line record fuzzily matches to vidin - sofia .', 'tostr': 'filter_eq { all_rows ; line ; vidin - sofia }'}, 'length'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; line ; vidin - sofia } ; length }', 'tointer': 'select the rows whose line record fuzzily matches to vidin - sofia . take the length record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; line ; sofia - dragoman } ; length } ; hop { filter_eq { all_rows ; line ; vidin - sofia } ; length } } = true', 'tointer': 'select the rows whose line record fuzzily matches to sofia - dragoman . take the length record of this row . select the rows whose line record fuzzily matches to vidin - sofia . take the length record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; line ; sofia - dragoman } ; length } ; hop { filter_eq { all_rows ; line ; vidin - sofia } ; length } } = true | select the rows whose line record fuzzily matches to sofia - dragoman . take the length record of this row . select the rows whose line record fuzzily matches to vidin - sofia . take the length 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, 'line_7': 7, 'sofia - dragoman_8': 8, 'length_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'line_11': 11, 'vidin - sofia_12': 12, 'length_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', 'line_7': 'line', 'sofia - dragoman_8': 'sofia - dragoman', 'length_9': 'length', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'line_11': 'line', 'vidin - sofia_12': 'vidin - sofia', 'length_13': 'length'} | {'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'line_7': [0], 'sofia - dragoman_8': [0], 'length_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'line_11': [1], 'vidin - sofia_12': [1], 'length_13': [3]} | ['line', 'speed', 'length', 'construction begun', 'expected start of revenue services'] | [['svilengrad - turkish border', '200 km / h', '19 km', '2010', '2012'], ['dimitrovgrad - svilengrad', '200 km / h', '70 km', '2012', '2013'], ['plovdiv - burgas', '200 km / h', '291 km', '2010', '2013'], ['sofia - plovdiv', '200 km / h', '156 km', '2010', '2015'], ['sofia - radomir', '200 km / h', '53 km', '2014', '2017'], ['sofia - dragoman', '200 km / h', '44 km', '2014', '2017'], ['vidin - sofia', '200 km / h', '222 km', 'unknown', '2020']] |
octagonal | https://en.wikipedia.org/wiki/Octagonal | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1284347-2.html.csv | superlative | the cox plate race was the only race where the average jockey weight was under 50 kg . | {'scope': 'all', 'col_superlative': '7', 'row_superlative': '5', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '3', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmin', 'args': ['all_rows', 'weight ( kg )'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; weight ( kg ) }'}, 'race'], 'result': 'cox plate', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; weight ( kg ) } ; race }'}, 'cox plate'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmin { all_rows ; weight ( kg ) } ; race } ; cox plate } = true', 'tointer': 'select the row whose weight ( kg ) record of all rows is minimum . the race record of this row is cox plate .'} | eq { hop { argmin { all_rows ; weight ( kg ) } ; race } ; cox plate } = true | select the row whose weight ( kg ) record of all rows is minimum . the race record of this row is cox plate . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'weight (kg)_5': 5, 'race_6': 6, 'cox plate_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'weight (kg)_5': 'weight ( kg )', 'race_6': 'race', 'cox plate_7': 'cox plate'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'weight (kg)_5': [0], 'race_6': [1], 'cox plate_7': [2]} | ['result', 'date', 'race', 'venue', 'group', 'distance', 'weight ( kg )', 'jockey', 'winner / 2nd'] | [['2nd', '2 sep 1995', 'roman consul stakes', 'randwick', 'g3', '1200 m', '55', 'g cooksley', '1st - our maizcay'], ['won', '16 sep 1995', 'heritage stakes', 'rosehill', 'lr', '1300 m', '55.5', 'g cooksley', '2nd - mi modest'], ['won', '2 oct 1995', 'stan fox stakes', 'randwick', 'g3', '1400 m', '55', 'g cooksley', '2nd - encores'], ['3rd', '14 oct 1995', 'caulfield guineas', 'caulfield', 'g1', '1600 m', '55.5', 'd gauci', '1st - our maizcay'], ['won', '28 oct 1995', 'cox plate', 'moonee valley', 'g1', '2040 m', '48.5', 's dye', '2nd - mahogany'], ['2nd', '4 nov 1995', 'victoria derby', 'flemington', 'g1', '2500 m', '55.5', 's scriven', "1st - nothin ' leica dane"], ['2nd', '24 feb 1996', 'hobartville stakes', 'warwick farm', 'g2', '1400 m', '55.5', 'g cooksley', "1st - nothin ' leica dane"], ['won', '9 mar 1996', 'canterbury guineas', 'canterbury', 'g1', '1900 m', '55.5', 'd beadman', '2nd - filante'], ['won', '23 mar 1996', 'rosehill guineas', 'rosehill', 'g1', '2000 m', '55.5', 'd beadman', '2nd - saintly'], ['won', '30 mar 1996', 'mercedes classic', 'rosehill', 'g1', '2400 m', '52', 'd beadman', '2nd - count chivas']] |
wru division five south east | https://en.wikipedia.org/wiki/WRU_Division_Five_South_East | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17625749-2.html.csv | ordinal | cilfynydd rfc was the team with the 2nd most points among the wru division five south east . | {'row': '3', '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', 'points for', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; points for ; 2 }'}, 'club'], 'result': 'cilfynydd rfc', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; points for ; 2 } ; club }'}, 'cilfynydd rfc'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; points for ; 2 } ; club } ; cilfynydd rfc } = true', 'tointer': 'select the row whose points for record of all rows is 2nd maximum . the club record of this row is cilfynydd rfc .'} | eq { hop { nth_argmax { all_rows ; points for ; 2 } ; club } ; cilfynydd rfc } = true | select the row whose points for record of all rows is 2nd maximum . the club record of this row is cilfynydd rfc . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'points for_5': 5, '2_6': 6, 'club_7': 7, 'cilfynydd rfc_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'points for_5': 'points for', '2_6': '2', 'club_7': 'club', 'cilfynydd rfc_8': 'cilfynydd rfc'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'points for_5': [0], '2_6': [0], 'club_7': [1], 'cilfynydd rfc_8': [2]} | ['club', 'played', 'drawn', 'lost', 'points for', 'points against', 'tries for', 'tries against', 'try bonus', 'losing bonus', 'points'] | [['club', 'played', 'drawn', 'lost', 'points for', 'points against', 'tries for', 'tries against', 'try bonus', 'losing bonus', 'points'], ['pontyclun rfc', '20', '0', '2', '694', '191', '104', '21', '12', '2', '86'], ['cilfynydd rfc', '20', '1', '4', '635', '330', '90', '37', '10', '2', '74'], ['barry rfc', '20', '2', '5', '515', '247', '64', '30', '5', '2', '63'], ['st albans rfc', '20', '0', '9', '504', '347', '68', '40', '7', '4', '55'], ['deri rfc', '20', '0', '9', '409', '349', '55', '45', '5', '3', '52'], ['hirwaun rfc', '20', '1', '8', '476', '421', '59', '57', '7', '2', '51'], ['penygraig rfc', '20', '1', '10', '283', '405', '41', '51', '4', '1', '43'], ['cowbridge rfc', '20', '1', '12', '337', '369', '33', '46', '3', '4', '37'], ['old penarthians rfc', '20', '0', '13', '318', '431', '39', '61', '2', '3', '33'], ['dinas powys rfc', '20', '0', '17', '291', '701', '44', '105', '4', '3', '19'], ['canton rfc', '20', '0', '18', '157', '828', '19', '123', '1', '1', '10']] |
list of kent first - class cricket records | https://en.wikipedia.org/wiki/List_of_Kent_first-class_cricket_records | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11204543-17.html.csv | unique | colin blythe bowling of 17-48 was the best of all the seasons . | {'scope': 'all', 'row': '1', 'col': '1', 'col_other': '2', 'criterion': 'equal', 'value': '17 - 48', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'bowling', '17 - 48'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose bowling record fuzzily matches to 17 - 48 .', 'tostr': 'filter_eq { all_rows ; bowling ; 17 - 48 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; bowling ; 17 - 48 } }', 'tointer': 'select the rows whose bowling record fuzzily matches to 17 - 48 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'bowling', '17 - 48'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose bowling record fuzzily matches to 17 - 48 .', 'tostr': 'filter_eq { all_rows ; bowling ; 17 - 48 }'}, 'player'], 'result': 'colin blythe', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; bowling ; 17 - 48 } ; player }'}, 'colin blythe'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; bowling ; 17 - 48 } ; player } ; colin blythe }', 'tointer': 'the player record of this unqiue row is colin blythe .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; bowling ; 17 - 48 } } ; eq { hop { filter_eq { all_rows ; bowling ; 17 - 48 } ; player } ; colin blythe } } = true', 'tointer': 'select the rows whose bowling record fuzzily matches to 17 - 48 . there is only one such row in the table . the player record of this unqiue row is colin blythe .'} | and { only { filter_eq { all_rows ; bowling ; 17 - 48 } } ; eq { hop { filter_eq { all_rows ; bowling ; 17 - 48 } ; player } ; colin blythe } } = true | select the rows whose bowling record fuzzily matches to 17 - 48 . there is only one such row in the table . the player record of this unqiue row is colin blythe . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'bowling_7': 7, '17 - 48_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'player_9': 9, 'colin blythe_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'bowling_7': 'bowling', '17 - 48_8': '17 - 48', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'player_9': 'player', 'colin blythe_10': 'colin blythe'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'bowling_7': [0], '17 - 48_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'player_9': [2], 'colin blythe_10': [3]} | ['bowling', 'player', 'opponent', 'venue', 'season'] | [['17 - 48', 'colin blythe', 'v northamptonshire', 'county ground , northampton', '1907'], ['17 - 67', 'tich freeman', 'v sussex', 'county ground , hove', '1922'], ['17 - 92', 'tich freeman', 'v warwickshire', 'cheriton road , folkestone', '1932'], ['16 - 80', 'doug wright', 'v somerset', 'recreation ground , bath', '1939'], ['16 - 82', 'tich freeman', 'v northamptonshire', 'nevill ground , tunbridge wells', '1932']] |
1940 vfl season | https://en.wikipedia.org/wiki/1940_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10807253-16.html.csv | majority | all games of the 1940 vfl season was played on the 17th of august . | {'scope': 'all', 'col': '7', 'most_or_all': 'all', 'criterion': 'equal', 'value': '17 august 1940', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'date', '17 august 1940'], 'result': True, 'ind': 0, 'tointer': 'for the date records of all rows , all of them fuzzily match to 17 august 1940 .', 'tostr': 'all_eq { all_rows ; date ; 17 august 1940 } = true'} | all_eq { all_rows ; date ; 17 august 1940 } = true | for the date records of all rows , all of them fuzzily match to 17 august 1940 . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'date_3': 3, '17 august 1940_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'date_3': 'date', '17 august 1940_4': '17 august 1940'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'date_3': [0], '17 august 1940_4': [0]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['footscray', '17.22 ( 124 )', 'north melbourne', '8.13 ( 61 )', 'western oval', '8000', '17 august 1940'], ['collingwood', '12.18 ( 90 )', 'melbourne', '16.8 ( 104 )', 'victoria park', '8000', '17 august 1940'], ['carlton', '13.14 ( 92 )', 'st kilda', '6.16 ( 52 )', 'princes park', '6000', '17 august 1940'], ['south melbourne', '12.19 ( 91 )', 'geelong', '13.9 ( 87 )', 'lake oval', '7000', '17 august 1940'], ['richmond', '14.15 ( 99 )', 'fitzroy', '10.11 ( 71 )', 'punt road oval', '22000', '17 august 1940'], ['hawthorn', '11.18 ( 84 )', 'essendon', '18.12 ( 120 )', 'glenferrie oval', '9000', '17 august 1940']] |
chala kelele | https://en.wikipedia.org/wiki/Chala_Kelele | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12736407-1.html.csv | majority | most of the events in which chala kelele competed in were team competitions . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'team competition', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'extra', 'team competition'], 'result': True, 'ind': 0, 'tointer': 'for the extra records of all rows , most of them fuzzily match to team competition .', 'tostr': 'most_eq { all_rows ; extra ; team competition } = true'} | most_eq { all_rows ; extra ; team competition } = true | for the extra records of all rows , most of them fuzzily match to team competition . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'extra_3': 3, 'team competition_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'extra_3': 'extra', 'team competition_4': 'team competition'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'extra_3': [0], 'team competition_4': [0]} | ['year', 'tournament', 'venue', 'result', 'extra'] | [['1988', 'world cross country championships', 'auckland , new zealand', '2nd', 'team competition'], ['1991', 'world cross country championships', 'antwerp , belgium', '7th', 'long race'], ['1991', 'world cross country championships', 'antwerp , belgium', '2nd', 'team competition'], ['1995', 'world cross country championships', 'durham , england', '27th', 'long race'], ['1995', 'world cross country championships', 'durham , england', '5th', 'team competition'], ['1996', 'world cross country championships', 'stellenbosch , south africa', '3rd', 'team competition']] |
fiji national rugby union team | https://en.wikipedia.org/wiki/Fiji_national_rugby_union_team | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1074616-5.html.csv | ordinal | nicky little had the most starts of any player in the fiji national rugby union team . | {'row': '1', 'col': '3', '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', 'start', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; start ; 1 }'}, 'player'], 'result': 'nicky little', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; start ; 1 } ; player }'}, 'nicky little'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; start ; 1 } ; player } ; nicky little } = true', 'tointer': 'select the row whose start record of all rows is 1st maximum . the player record of this row is nicky little .'} | eq { hop { nth_argmax { all_rows ; start ; 1 } ; player } ; nicky little } = true | select the row whose start record of all rows is 1st maximum . the player record of this row is nicky little . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'start_5': 5, '1_6': 6, 'player_7': 7, 'nicky little_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', 'start_5': 'start', '1_6': '1', 'player_7': 'player', 'nicky little_8': 'nicky little'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'start_5': [0], '1_6': [0], 'player_7': [1], 'nicky little_8': [2]} | ['player', 'span', 'start', 'tries', 'conv', 'pens', 'drop', 'lost', 'draw'] | [['nicky little', '1996 - 2011', '60', '2', '117', '140', '2', '34', '0'], ['jacob rauluni', '1995 - 2006', '40', '6', '0', '0', '0', '23', '0'], ['joeli veitayaki', '1994 - 2003', '45', '3', '0', '0', '0', '23', '0'], ['emori katalau', '1995 - 2003', '39', '4', '0', '0', '0', '23', '0'], ['norman ligairi', '2000 - 2010', '39', '16', '0', '0', '0', '22', '0'], ['seremaia bai', '2000 -', '44', '4', '47', '51', '1', '22', '1'], ['sisa koyamaibole', '2001 - 2011', '35', '3', '0', '0', '0', '25', '1'], ['ifereimi tawake', '1986 - 1999', '38', '4', '0', '2', '0', '29', '1'], ['mosese rauluni', '1996 - 2009', '36', '4', '0', '0', '0', '21', '0'], ['greg smith', '1995 - 2003', '44', '1', '0', '0', '0', '20', '0']] |
1964 american football league draft | https://en.wikipedia.org/wiki/1964_American_Football_League_Draft | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18652117-1.html.csv | comparative | bob brown was picked earlier in the 1964 american football league draft than ted davis . | {'row_1': '4', 'row_2': '8', 'col': '1', 'col_other': '3', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', 'bob brown'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose player record fuzzily matches to bob brown .', 'tostr': 'filter_eq { all_rows ; player ; bob brown }'}, 'pick'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; player ; bob brown } ; pick }', 'tointer': 'select the rows whose player record fuzzily matches to bob brown . take the pick record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', 'ted davis'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose player record fuzzily matches to ted davis .', 'tostr': 'filter_eq { all_rows ; player ; ted davis }'}, 'pick'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; player ; ted davis } ; pick }', 'tointer': 'select the rows whose player record fuzzily matches to ted davis . take the pick record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; player ; bob brown } ; pick } ; hop { filter_eq { all_rows ; player ; ted davis } ; pick } } = true', 'tointer': 'select the rows whose player record fuzzily matches to bob brown . take the pick record of this row . select the rows whose player record fuzzily matches to ted davis . take the pick record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; player ; bob brown } ; pick } ; hop { filter_eq { all_rows ; player ; ted davis } ; pick } } = true | select the rows whose player record fuzzily matches to bob brown . take the pick record of this row . select the rows whose player record fuzzily matches to ted davis . take the pick record of this row . the first record is less than the second record . | 5 | 5 | {'less_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'player_7': 7, 'bob brown_8': 8, 'pick_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'player_11': 11, 'ted davis_12': 12, 'pick_13': 13} | {'less_4': 'less', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'player_7': 'player', 'bob brown_8': 'bob brown', 'pick_9': 'pick', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'player_11': 'player', 'ted davis_12': 'ted davis', 'pick_13': 'pick'} | {'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'player_7': [0], 'bob brown_8': [0], 'pick_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'player_11': [1], 'ted davis_12': [1], 'pick_13': [3]} | ['pick', 'team', 'player', 'position', 'college'] | [['1', 'boston', 'jack concannon', 'qb', 'boston college'], ['2', 'kansas city', 'pete beathard', 'qb', 'usc'], ['3', 'new york', 'matt snell', 'rb', 'ohio state'], ['4', 'denver', 'bob brown', 'ot', 'nebraska'], ['5', 'buffalo', 'carl eller', 'de', 'minnesota'], ['6', 'houston', 'scott appleton', 'dt', 'texas'], ['7', 'oakland', 'tony lorick', 'rb', 'arizona state'], ['8', 'san diego', 'ted davis', 'lb', 'georgia tech']] |
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/2-11872185-11.html.csv | unique | chennai express is the only movie on the list of highest - grossing bollywood films that was produced by red chillies entertainment . | {'scope': 'all', 'row': '3', 'col': '4', 'col_other': '2', 'criterion': 'equal', 'value': 'red chillies entertainment', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'studio ( s )', 'red chillies entertainment'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose studio ( s ) record fuzzily matches to red chillies entertainment .', 'tostr': 'filter_eq { all_rows ; studio ( s ) ; red chillies entertainment }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; studio ( s ) ; red chillies entertainment } }', 'tointer': 'select the rows whose studio ( s ) record fuzzily matches to red chillies entertainment . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'studio ( s )', 'red chillies entertainment'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose studio ( s ) record fuzzily matches to red chillies entertainment .', 'tostr': 'filter_eq { all_rows ; studio ( s ) ; red chillies entertainment }'}, 'movie'], 'result': 'chennai express', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; studio ( s ) ; red chillies entertainment } ; movie }'}, 'chennai express'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; studio ( s ) ; red chillies entertainment } ; movie } ; chennai express }', 'tointer': 'the movie record of this unqiue row is chennai express .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; studio ( s ) ; red chillies entertainment } } ; eq { hop { filter_eq { all_rows ; studio ( s ) ; red chillies entertainment } ; movie } ; chennai express } } = true', 'tointer': 'select the rows whose studio ( s ) record fuzzily matches to red chillies entertainment . there is only one such row in the table . the movie record of this unqiue row is chennai express .'} | and { only { filter_eq { all_rows ; studio ( s ) ; red chillies entertainment } } ; eq { hop { filter_eq { all_rows ; studio ( s ) ; red chillies entertainment } ; movie } ; chennai express } } = true | select the rows whose studio ( s ) record fuzzily matches to red chillies entertainment . there is only one such row in the table . the movie record of this unqiue row is chennai express . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'studio (s)_7': 7, 'red chillies entertainment_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'movie_9': 9, 'chennai express_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'studio (s)_7': 'studio ( s )', 'red chillies entertainment_8': 'red chillies entertainment', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'movie_9': 'movie', 'chennai express_10': 'chennai express'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'studio (s)_7': [0], 'red chillies entertainment_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'movie_9': [2], 'chennai express_10': [3]} | ['rank', 'movie', 'year', 'studio ( s )', 'third week nett gross'] | [['1', '3 idiots', '2009', 'vinod chopra productions', '30 , 30 , 00000'], ['2', 'yeh jawaani hai deewani', '2013', 'dharma productions', '19 , 60 , 00000'], ['3', 'chennai express', '2013', 'red chillies entertainment', '18 , 31 , 00000'], ['4', 'dabangg', '2010', 'arbaaz khan productions', '17 , 21 , 00000'], ['5', 'barfi', '2012', 'utv motion pictures', '15 , 70 , 00000'], ['6', 'bhaag milkha bhaag', '2013', 'viacom 18', '15 , 49 , 00000'], ['7', 'rowdy rathore', '2012', 'utv motion pictures', '15 , 16 , 00000'], ['8', 'ghajini', '2008', 'reliance entertainment', '14 , 13 , 00000'], ['9', 'ready', '2010', 't - series', '13 , 61 , 00000'], ['10', 'omg ! oh my god', '2012', 'paresh rawal', '13 , 44 , 00000']] |
statistics relating to enlargement of the european union | https://en.wikipedia.org/wiki/Statistics_relating_to_enlargement_of_the_European_Union | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1307842-6.html.csv | unique | of the entries in the statistics relating to enlargement of the european union only finland has a gdp per capita less than 16000 . | {'scope': 'all', 'row': '2', 'col': '5', 'col_other': '1', 'criterion': 'less_than', 'value': '16000', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'gdp per capita ( us )', '16000'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose gdp per capita ( us ) record is less than 16000 .', 'tostr': 'filter_less { all_rows ; gdp per capita ( us ) ; 16000 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_less { all_rows ; gdp per capita ( us ) ; 16000 } }', 'tointer': 'select the rows whose gdp per capita ( us ) record is less than 16000 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'gdp per capita ( us )', '16000'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose gdp per capita ( us ) record is less than 16000 .', 'tostr': 'filter_less { all_rows ; gdp per capita ( us ) ; 16000 }'}, 'member countries'], 'result': 'finland', 'ind': 2, 'tostr': 'hop { filter_less { all_rows ; gdp per capita ( us ) ; 16000 } ; member countries }'}, 'finland'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_less { all_rows ; gdp per capita ( us ) ; 16000 } ; member countries } ; finland }', 'tointer': 'the member countries record of this unqiue row is finland .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_less { all_rows ; gdp per capita ( us ) ; 16000 } } ; eq { hop { filter_less { all_rows ; gdp per capita ( us ) ; 16000 } ; member countries } ; finland } } = true', 'tointer': 'select the rows whose gdp per capita ( us ) record is less than 16000 . there is only one such row in the table . the member countries record of this unqiue row is finland .'} | and { only { filter_less { all_rows ; gdp per capita ( us ) ; 16000 } } ; eq { hop { filter_less { all_rows ; gdp per capita ( us ) ; 16000 } ; member countries } ; finland } } = true | select the rows whose gdp per capita ( us ) record is less than 16000 . there is only one such row in the table . the member countries record of this unqiue row is finland . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_less_0': 0, 'all_rows_6': 6, 'gdp per capita (us)_7': 7, '16000_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'member countries_9': 9, 'finland_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_less_0': 'filter_less', 'all_rows_6': 'all_rows', 'gdp per capita (us)_7': 'gdp per capita ( us )', '16000_8': '16000', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'member countries_9': 'member countries', 'finland_10': 'finland'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_less_0': [1, 2], 'all_rows_6': [0], 'gdp per capita (us)_7': [0], '16000_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'member countries_9': [2], 'finland_10': [3]} | ['member countries', 'population', 'area ( km square )', 'gdp ( billion us )', 'gdp per capita ( us )'] | [['austria', '8206524', '83871', '145.238', '18048'], ['finland', '5261008', '338145', '80.955', '15859'], ['sweden', '9047752', '449964', '156.640', '17644'], ['accession countries', '22029977', '871980', '382.833', '17378'], ['existing members ( 1995 )', '350909402', '2495174', '5894.232', '16797']] |
comparison of amd chipsets | https://en.wikipedia.org/wiki/Comparison_of_AMD_chipsets | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12341355-5.html.csv | comparative | the sb850 amd chipset series has a higher tdp wattage than the sb710 amd chipset series . | {'row_1': '7', 'row_2': '4', 'col': '12', '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', 'model', 'amd 800 chipset series'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose model record fuzzily matches to amd 800 chipset series .', 'tostr': 'filter_eq { all_rows ; model ; amd 800 chipset series }'}, 'tdp ( w )'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; model ; amd 800 chipset series } ; tdp ( w ) }', 'tointer': 'select the rows whose model record fuzzily matches to amd 800 chipset series . take the tdp ( w ) record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'model', 'amd 700 chipset series'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose model record fuzzily matches to amd 700 chipset series .', 'tostr': 'filter_eq { all_rows ; model ; amd 700 chipset series }'}, 'tdp ( w )'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; model ; amd 700 chipset series } ; tdp ( w ) }', 'tointer': 'select the rows whose model record fuzzily matches to amd 700 chipset series . take the tdp ( w ) record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; model ; amd 800 chipset series } ; tdp ( w ) } ; hop { filter_eq { all_rows ; model ; amd 700 chipset series } ; tdp ( w ) } } = true', 'tointer': 'select the rows whose model record fuzzily matches to amd 800 chipset series . take the tdp ( w ) record of this row . select the rows whose model record fuzzily matches to amd 700 chipset series . take the tdp ( w ) record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; model ; amd 800 chipset series } ; tdp ( w ) } ; hop { filter_eq { all_rows ; model ; amd 700 chipset series } ; tdp ( w ) } } = true | select the rows whose model record fuzzily matches to amd 800 chipset series . take the tdp ( w ) record of this row . select the rows whose model record fuzzily matches to amd 700 chipset series . take the tdp ( w ) 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, 'model_7': 7, 'amd 800 chipset series_8': 8, 'tdp ( w )_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'model_11': 11, 'amd 700 chipset series_12': 12, 'tdp ( w )_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', 'model_7': 'model', 'amd 800 chipset series_8': 'amd 800 chipset series', 'tdp ( w )_9': 'tdp ( w )', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'model_11': 'model', 'amd 700 chipset series_12': 'amd 700 chipset series', 'tdp ( w )_13': 'tdp ( w )'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'model_7': [0], 'amd 800 chipset series_8': [0], 'tdp ( w )_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'model_11': [1], 'amd 700 chipset series_12': [1], 'tdp ( w )_13': [3]} | ['model', 'codename', 'released', 'fab ( nm )', 'sata', 'usb 2.0 + 1.1', 'usb 3.0', 'parallel ata 1', 'raid', 'gb ethernet mac', 'package', 'tdp ( w )'] | [['amd 480 / 570 / 580 / 690 crossfire chipset', 'sb600', '2006', '130', '43 gbit / s ahci 1.1 sata revision 2.0', '10 + 0', 'no', '1 ata / 133', '0 , 1 , 10', 'no', '548 - pin fc - bga', '4.0'], ['amd 700 chipset series', 'sb700', 'q1 2008', '130', '63 gbit / s ahci1 .1 sata revision 2.0', '12 + 2', 'no', '1 ata / 133', '0 , 1 , 10', 'no', '548 - pin fc - bga', '4.5'], ['amd 700s chipset series', 'sb700s', 'q1 2008', '130', '63 gbit / s ahci1 .1 sata revision 2.0', '12 + 2', 'no', '1 ata / 133', '0 , 1 , 10', 'no', '548 - pin fc - bga', '4.5'], ['amd 700 chipset series', 'sb710', 'q4 2008', '130', '63 gbit / s ahci1 .1 sata revision 2.0', '12 + 2', 'no', '1 ata / 133', '0 , 1 , 10', 'no', '548 - pin fc - bga', '4.5'], ['amd 700 chipset series', 'sb750', 'q4 2008', '130', '63 gbit / s ahci1 .1 sata revision 2.0', '12 + 2', 'no', '1 ata / 133', '0 , 1 , 5 , 10', 'no', '548 - pin fc - bga', '4.5'], ['amd 800 chipset series', 'sb810', 'q1 2010', '65', '63 gbit / s ahci1 .2 sata revision 2.0', '14 + 2', 'no', 'no', '0 , 1 , 10', '10 / 100 / 1000', '605 - pin fc - bga', '6.0'], ['amd 800 chipset series', 'sb850', 'q1 2010', '65', '66 gbps ahci1 .2 sata revision 3.0', '14 + 2', 'no', 'no', '0 , 1 , 5 , 10', '10 / 100 / 1000', '605 - pin fc - bga', '6.0'], ['amd 900 chipset series', 'sb920', 'may 30 , 2011', '65', '66 gbps ahci1 .2 sata revision 3.0', '14 + 2', 'no', 'no', '0 , 1 , 10', '10 / 100 / 1000', '605 - pin fc - bga', '6.0'], ['amd 900 chipset series', 'sb950', 'may 30 , 2011', '65', '66 gbps ahci1 .2 sata revision 3.0', '14 + 2', 'no', 'no', '0 , 1 , 5 , 10', '10 / 100 / 1000', '605 - pin fc - bga', '6.0']] |
salyut 6 | https://en.wikipedia.org/wiki/Salyut_6 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-245800-2.html.csv | aggregation | the average amount of days the salyut 6 was in orbit for was 56 days . | {'scope': 'all', 'col': '7', 'type': 'average', 'result': '56.37', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'duration ( days )'], 'result': '56.37', 'ind': 0, 'tostr': 'avg { all_rows ; duration ( days ) }'}, '56.37'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; duration ( days ) } ; 56.37 } = true', 'tointer': 'the average of the duration ( days ) record of all rows is 56.37 .'} | round_eq { avg { all_rows ; duration ( days ) } ; 56.37 } = true | the average of the duration ( days ) record of all rows is 56.37 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'duration (days)_4': 4, '56.37_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'duration (days)_4': 'duration ( days )', '56.37_5': '56.37'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'duration (days)_4': [0], '56.37_5': [1]} | ['expedition', 'crew', 'launch date', 'flight up', 'landing date', 'flight down', 'duration ( days )'] | [['salyut 6 - eo - 1', 'yuri romanenko , georgi grechko', '10 december 1977 01:18:40', 'soyuz 26', '16 march 1978 11:18:47', 'soyuz 27', '96.42'], ['salyut 6 - ep - 1', 'vladimir dzhanibekov , oleg makarov', '10 january 1978 12:26:00', 'soyuz 27', '16 january 1978 11:24:58', 'soyuz 26', '5.96'], ['salyut 6 - ep - 2', 'aleksei gubarev , vladimír remek - czechoslovakia', '2 march 1978 15:28:00', 'soyuz 28', '10 march 1978 13:44:00', 'soyuz 28', '7.93'], ['salyut 6 - eo - 2', 'vladimir kovalyonok , aleksandr ivanchenkov', '15 june 1978 20:16:45', 'soyuz 29', '2 november 1978 11:04:17', 'soyuz 31', '139.62'], ['salyut 6 - ep - 3', 'pyotr klimuk , miroslaw hermaszewski - poland', '27 june 1978 15:27:21', 'soyuz 30', '5 july 1978 13:30:20', 'soyuz 30', '7.92'], ['salyut 6 - eo - 3', 'vladimir lyakhov , valery ryumin', '25 february 1979 11:53:49', 'soyuz 32', '19 august 1979 12:29:26', 'soyuz 34', '175.02'], ['salyut 6 - eo - 4', 'leonid popov , valery ryumin', '9 april 1980 13:38:22', 'soyuz 35', '11 october 1980 09:49:57', 'soyuz 37', '184.84'], ['salyut 6 - ep - 5', 'valery kubasov , bertalan farkas - hungary', '26 may 1980 18:20:39', 'soyuz 36', '3 june 1980 15:06:23', 'soyuz 35', '7.87'], ['salyut 6 - ep - 6', 'yuri malyshev , vladimir aksyonov', '5 june 1980 14:19:30', 'soyuz t - 2', '9 june 1980 12:39:00', 'soyuz t - 2', '3.93'], ['salyut 6 - ep - 7', 'viktor gorbatko , pham tuan - vietnam', '23 july 1980 18:33:03', 'soyuz 37', '31 july 1980 15:15:02', 'soyuz 36', '7.86'], ['salyut 6 - ep - 8', 'yuri romanenko , arnaldo tamayo méndez - cuba', '18 september 1980 19:11:03', 'soyuz 38', '26 september 1980 15:54:27', 'soyuz 38', '7.86'], ['salyut 6 - eo - 5', 'leonid kizim , oleg makarov gennady strekalov', '27 november 1980 14:18:28', 'soyuz t - 3', '10 december 1980 09:26:10', 'soyuz t - 3', '12.80'], ['salyut 6 - eo - 6', 'vladimir kovalyonok , viktor savinykh', '12 march 1981 19:00:11', 'soyuz t - 4', '26 may 1981 12:37:34', 'soyuz t - 4', '74.73']] |
skid row ( american band ) | https://en.wikipedia.org/wiki/Skid_Row_%28American_band%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1690020-1.html.csv | aggregation | the average oricon peak of skid row ( american brand ) is 78.2 . | {'scope': 'all', 'col': '4', 'type': 'average', 'result': '78.2', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'oricon peak'], 'result': '78.2', 'ind': 0, 'tostr': 'avg { all_rows ; oricon peak }'}, '78.2'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; oricon peak } ; 78.2 } = true', 'tointer': 'the average of the oricon peak record of all rows is 78.2 .'} | round_eq { avg { all_rows ; oricon peak } ; 78.2 } = true | the average of the oricon peak record of all rows is 78.2 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'oricon peak_4': 4, '78.2_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'oricon peak_4': 'oricon peak', '78.2_5': '78.2'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'oricon peak_4': [0], '78.2_5': [1]} | ['date of release', 'title', 'label', 'oricon peak', 'riaa cert'] | [['1989', 'skid row', 'atlantic', '5', '5x platinum'], ['1991', 'slave to the grind', 'atlantic', '3', '2x platinum'], ['1995', 'subhuman race', 'atlantic', '6', 'gold'], ['2003', 'thickskin', 'skid row recs', '111', 'none'], ['2006', 'revolutions per minute', 'spv', '266', 'none']] |
saltwood miniature railway | https://en.wikipedia.org/wiki/Saltwood_Miniature_Railway | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11658983-1.html.csv | ordinal | in saltwood miniature railway , number1 was the earliest one to be withdrawn of the steam locomotive type . | {'scope': 'subset', 'row': '1', 'col': '6', 'order': '1', 'col_other': '1', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'subset': {'col': '2', 'criterion': 'equal', 'value': 'steam'}} | {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'nth_argmin', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'locomotive type', 'steam'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; locomotive type ; steam }', 'tointer': 'select the rows whose locomotive type record fuzzily matches to steam .'}, 'withdrawn', '1'], 'result': None, 'ind': 1, 'tostr': 'nth_argmin { filter_eq { all_rows ; locomotive type ; steam } ; withdrawn ; 1 }'}, 'number'], 'result': '1', 'ind': 2, 'tostr': 'hop { nth_argmin { filter_eq { all_rows ; locomotive type ; steam } ; withdrawn ; 1 } ; number }'}, '1'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { nth_argmin { filter_eq { all_rows ; locomotive type ; steam } ; withdrawn ; 1 } ; number } ; 1 } = true', 'tointer': 'select the rows whose locomotive type record fuzzily matches to steam . select the row whose withdrawn record of these rows is 1st minimum . the number record of this row is 1 .'} | eq { hop { nth_argmin { filter_eq { all_rows ; locomotive type ; steam } ; withdrawn ; 1 } ; number } ; 1 } = true | select the rows whose locomotive type record fuzzily matches to steam . select the row whose withdrawn record of these rows is 1st minimum . the number record of this row is 1 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'num_hop_2': 2, 'nth_argmin_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'locomotive type_6': 6, 'steam_7': 7, 'withdrawn_8': 8, '1_9': 9, 'number_10': 10, '1_11': 11} | {'eq_3': 'eq', 'result_4': 'true', 'num_hop_2': 'num_hop', 'nth_argmin_1': 'nth_argmin', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'locomotive type_6': 'locomotive type', 'steam_7': 'steam', 'withdrawn_8': 'withdrawn', '1_9': '1', 'number_10': 'number', '1_11': '1'} | {'eq_3': [4], 'result_4': [], 'num_hop_2': [3], 'nth_argmin_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'locomotive type_6': [0], 'steam_7': [0], 'withdrawn_8': [1], '1_9': [1], 'number_10': [2], '1_11': [3]} | ['number', 'locomotive type', 'wheel arrangement', 'builder', 'entered service', 'withdrawn'] | [['1', 'steam', '0 - 4 - 2 tank', 'jubb engineering', '1922', '1928'], ['471', 'steam', '4 - 4 - 2 atlantic', 'f & a schwab', '1928', '1970'], ['260', 'steam', '2 - 6 - 0 mogul', 'f & a schwab & henry greenly', '1939', '1975'], ['5060', 'battery electric', "bo ' 2 '", 'tom smith', '1974', '1987'], ['7007', 'battery electric', "bo ' 2 '", 'tom smith', '1976', '1987']] |
tadese tola | https://en.wikipedia.org/wiki/Tadese_Tola | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11035487-1.html.csv | ordinal | the second highest placing that tadese tola received was in osaka , japan . | {'row': '8', 'col': '4', 'order': '2', 'col_other': '3', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'position', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; position ; 2 }'}, 'venue'], 'result': 'osaka , japan', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; position ; 2 } ; venue }'}, 'osaka , japan'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; position ; 2 } ; venue } ; osaka , japan } = true', 'tointer': 'select the row whose position record of all rows is 2nd maximum . the venue record of this row is osaka , japan .'} | eq { hop { nth_argmax { all_rows ; position ; 2 } ; venue } ; osaka , japan } = true | select the row whose position record of all rows is 2nd maximum . the venue record of this row is osaka , japan . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'position_5': 5, '2_6': 6, 'venue_7': 7, 'osaka , japan_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', 'position_5': 'position', '2_6': '2', 'venue_7': 'venue', 'osaka , japan_8': 'osaka , japan'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'position_5': [0], '2_6': [0], 'venue_7': [1], 'osaka , japan_8': [2]} | ['year', 'competition', 'venue', 'position', 'event'] | [['2006', 'world cross country championships', 'fukuoka , japan', '10th', 'individual junior race'], ['2006', 'world cross country championships', 'fukuoka , japan', '3rd', 'team junior race'], ['2006', 'african championships in athletics', 'bambous , mauritius', '5th', '10000 m'], ['2006', 'world road running championships', 'debrecen , hungary', '7th', 'individual 20 km'], ['2006', 'world road running championships', 'debrecen , hungary', '3rd', 'team 20 km'], ['2007', 'world cross country championships', 'mombasa , kenya', '7th', 'individual'], ['2007', 'all - africa games', 'algiers , algeria', '2nd', '10000 m'], ['2007', 'world championships in athletics', 'osaka , japan', '13th', '10000 m'], ['2009', 'world cross country championships', 'amman , jordan', '17th', 'individual'], ['2013', 'world championships', 'moscow , russia', '3rd', 'marathon']] |
miss asia pageant | https://en.wikipedia.org/wiki/Miss_Asia_Pageant | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2876467-3.html.csv | count | there are three countries that have never placed first in the miss asia pageant . | {'scope': 'all', 'criterion': 'equal', 'value': '0', 'result': '3', 'col': '2', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'first place', '0'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose first place record is equal to 0 .', 'tostr': 'filter_eq { all_rows ; first place ; 0 }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; first place ; 0 } }', 'tointer': 'select the rows whose first place record is equal to 0 . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; first place ; 0 } } ; 3 } = true', 'tointer': 'select the rows whose first place record is equal to 0 . the number of such rows is 3 .'} | eq { count { filter_eq { all_rows ; first place ; 0 } } ; 3 } = true | select the rows whose first place record is equal to 0 . the number of such rows is 3 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_eq_0': 0, 'all_rows_4': 4, 'first place_5': 5, '0_6': 6, '3_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'first place_5': 'first place', '0_6': '0', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'first place_5': [0], '0_6': [0], '3_7': [2]} | ['region represented', 'first place', 'second place', 'third place', 'total top 3 placements', 'first place winning year ( s ) ( if applicable )'] | [['china', '5', '0', '4', '9', '2004 , 2005 , 2009 , 2010 , 2011'], ['hong kong', '2', '5', '1', '8', '2007 , 2008'], ['kazakhstan', '1', '0', '0', '1', '2006'], ['korea', '0', '2', '1', '3', 'n / a'], ['canada', '0', '1', '0', '1', 'n / a'], ['tajikistan', '0', '1', '0', '1', 'n / a'], ['taiwan', '1', '0', '2', '3', '2012']] |
australian technology network | https://en.wikipedia.org/wiki/Australian_Technology_Network | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1187124-1.html.csv | count | three of the austrlian technology network universities were not ranked by academic ranking of world universities 2012 . | {'scope': 'all', 'criterion': 'equal', 'value': 'not ranked', 'result': '3', 'col': '6', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'academic ranking of world universities 2012', 'not ranked'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose academic ranking of world universities 2012 record fuzzily matches to not ranked .', 'tostr': 'filter_eq { all_rows ; academic ranking of world universities 2012 ; not ranked }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; academic ranking of world universities 2012 ; not ranked } }', 'tointer': 'select the rows whose academic ranking of world universities 2012 record fuzzily matches to not ranked . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; academic ranking of world universities 2012 ; not ranked } } ; 3 } = true', 'tointer': 'select the rows whose academic ranking of world universities 2012 record fuzzily matches to not ranked . the number of such rows is 3 .'} | eq { count { filter_eq { all_rows ; academic ranking of world universities 2012 ; not ranked } } ; 3 } = true | select the rows whose academic ranking of world universities 2012 record fuzzily matches to not ranked . 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, 'academic ranking of world universities 2012_5': 5, 'not ranked_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', 'academic ranking of world universities 2012_5': 'academic ranking of world universities 2012', 'not ranked_6': 'not ranked', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'academic ranking of world universities 2012_5': [0], 'not ranked_6': [0], '3_7': [2]} | ['university', 'location', 'year of foundation', 'university status', 'the world university rankings 2012 - 13', 'academic ranking of world universities 2012', 'qs world university rankings 2012'] | [['curtin university', 'perth , wa', '1902', '1986', 'not ranked', '401 - 500', '258'], ['queensland university of technology', 'brisbane , qld', '1908', '1989', '251 - 275', 'not ranked', '281'], ['royal melbourne institute of technology', 'melbourne , vic', '1887', '1992', 'not ranked', 'not ranked', '246'], ['university of south australia', 'adelaide , sa', '1856', '1991', '301 - 350', 'not ranked', '293'], ['university of technology , sydney', 'sydney , nsw', '1843', '1988', '351 - 400', '401 - 500', '284']] |
list of new zealand warriors records | https://en.wikipedia.org/wiki/List_of_New_Zealand_Warriors_records | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13274816-9.html.csv | ordinal | the largest margin of victory was against south sydney a total of 66 points . | {'row': '1', 'col': '1', 'order': '1', 'col_other': '3', 'max_or_min': 'max_to_min', 'value_mentioned': 'yes', 'scope': 'all', 'subset': None} | {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'nth_max', 'args': ['all_rows', 'margin', '1'], 'result': '66', 'ind': 0, 'tostr': 'nth_max { all_rows ; margin ; 1 }', 'tointer': 'the 1st maximum margin record of all rows is 66 .'}, '66'], 'result': True, 'ind': 1, 'tostr': 'eq { nth_max { all_rows ; margin ; 1 } ; 66 }', 'tointer': 'the 1st maximum margin record of all rows is 66 .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'margin', '1'], 'result': None, 'ind': 2, 'tostr': 'nth_argmax { all_rows ; margin ; 1 }'}, 'opponent'], 'result': 'south sydney rabbitohs', 'ind': 3, 'tostr': 'hop { nth_argmax { all_rows ; margin ; 1 } ; opponent }'}, 'south sydney rabbitohs'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { nth_argmax { all_rows ; margin ; 1 } ; opponent } ; south sydney rabbitohs }', 'tointer': 'the opponent record of the row with 1st maximum margin record is south sydney rabbitohs .'}], 'result': True, 'ind': 5, 'tostr': 'and { eq { nth_max { all_rows ; margin ; 1 } ; 66 } ; eq { hop { nth_argmax { all_rows ; margin ; 1 } ; opponent } ; south sydney rabbitohs } } = true', 'tointer': 'the 1st maximum margin record of all rows is 66 . the opponent record of the row with 1st maximum margin record is south sydney rabbitohs .'} | and { eq { nth_max { all_rows ; margin ; 1 } ; 66 } ; eq { hop { nth_argmax { all_rows ; margin ; 1 } ; opponent } ; south sydney rabbitohs } } = true | the 1st maximum margin record of all rows is 66 . the opponent record of the row with 1st maximum margin record is south sydney rabbitohs . | 6 | 6 | {'and_5': 5, 'result_6': 6, 'eq_1': 1, 'nth_max_0': 0, 'all_rows_7': 7, 'margin_8': 8, '1_9': 9, '66_10': 10, 'str_eq_4': 4, 'str_hop_3': 3, 'nth_argmax_2': 2, 'all_rows_11': 11, 'margin_12': 12, '1_13': 13, 'opponent_14': 14, 'south sydney rabbitohs_15': 15} | {'and_5': 'and', 'result_6': 'true', 'eq_1': 'eq', 'nth_max_0': 'nth_max', 'all_rows_7': 'all_rows', 'margin_8': 'margin', '1_9': '1', '66_10': '66', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'nth_argmax_2': 'nth_argmax', 'all_rows_11': 'all_rows', 'margin_12': 'margin', '1_13': '1', 'opponent_14': 'opponent', 'south sydney rabbitohs_15': 'south sydney rabbitohs'} | {'and_5': [6], 'result_6': [], 'eq_1': [5], 'nth_max_0': [1], 'all_rows_7': [0], 'margin_8': [0], '1_9': [0], '66_10': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'nth_argmax_2': [3], 'all_rows_11': [2], 'margin_12': [2], '1_13': [2], 'opponent_14': [3], 'south sydney rabbitohs_15': [4]} | ['margin', 'score', 'opponent', 'venue', 'year'] | [['66', '66 - 0', 'south sydney rabbitohs', 'sydney football stadium', '2006'], ['58', '68 - 10', 'northern eagles', 'mt smart stadium', '2002'], ['46', '52 - 6', 'north queensland cowboys', 'mt smart stadium', '1996'], ['44', '60 - 16', 'western suburbs', 'campbelltown', '1999'], ['44', '52 - 8', 'penrith panthers', 'mt smart stadium', '2001']] |
2006 geelong football club season | https://en.wikipedia.org/wiki/2006_Geelong_Football_Club_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12886301-2.html.csv | superlative | in the 2006 geelong football season will slade made the most goals . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '5', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'goals'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; goals }'}, 'player'], 'result': 'will slade', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; goals } ; player }'}, 'will slade'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; goals } ; player } ; will slade } = true', 'tointer': 'select the row whose goals record of all rows is maximum . the player record of this row is will slade .'} | eq { hop { argmax { all_rows ; goals } ; player } ; will slade } = true | select the row whose goals record of all rows is maximum . the player record of this row is will slade . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'goals_5': 5, 'player_6': 6, 'will slade_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'goals_5': 'goals', 'player_6': 'player', 'will slade_7': 'will slade'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'goals_5': [0], 'player_6': [1], 'will slade_7': [2]} | ['player', 'afl debut', 'games', 'goals', 'kicks', 'handballs', 'disposals', 'marks', 'tackles'] | [['nick batchelor', '-', '-', '-', '-', '-', '-', '-', '-'], ['todd grima', '-', '-', '-', '-', '-', '-', '-', '-'], ['sam hunt', '2002', '-', '-', '-', '-', '-', '-', '-'], ['tim sheringham', '-', '-', '-', '-', '-', '-', '-', '-'], ['will slade', '2002', '6', '1', '32', '31', '63', '21', '7']] |
memphis grizzlies all - time roster | https://en.wikipedia.org/wiki/Memphis_Grizzlies_all-time_roster | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-16494599-10.html.csv | superlative | chris johnson was the last of these players to be recruited for the memphis grizzlies . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '4', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'years for grizzlies'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; years for grizzlies }'}, 'player'], 'result': 'chris johnson', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; years for grizzlies } ; player }'}, 'chris johnson'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; years for grizzlies } ; player } ; chris johnson } = true', 'tointer': 'select the row whose years for grizzlies record of all rows is maximum . the player record of this row is chris johnson .'} | eq { hop { argmax { all_rows ; years for grizzlies } ; player } ; chris johnson } = true | select the row whose years for grizzlies record of all rows is maximum . the player record of this row is chris johnson . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'years for grizzlies_5': 5, 'player_6': 6, 'chris johnson_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'years for grizzlies_5': 'years for grizzlies', 'player_6': 'player', 'chris johnson_7': 'chris johnson'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'years for grizzlies_5': [0], 'player_6': [1], 'chris johnson_7': [2]} | ['player', 'no', 'nationality', 'position', 'years for grizzlies', 'school / club team'] | [['bobby jackson', '24', 'united states', 'guard', '2005 - 2006', 'minnesota'], ['casey jacobsen', '23', 'united states', 'guard - forward', '2007 - 2008', 'stanford'], ['alexander johnson', '32', 'united states', 'power forward', '2006 - 2007', 'florida state'], ['chris johnson', '4', 'united states', 'small forward', '2013', 'dayton'], ['bobby jones', '8', 'united states', 'forward', '2008', 'washington'], ['dahntay jones', '30', 'united states', 'guard - forward', '2003 - 2007', 'duke'], ['damon jones', '11', 'united states', 'shooting guard', '2000 - 2001', 'houston']] |
united states house of representatives elections , 1984 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1984 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1341598-36.html.csv | unique | tony p hall was the only unopposed incumbent of the 1984 house of representatives elections . | {'scope': 'all', 'row': '2', 'col': '6', 'col_other': '2', 'criterion': 'fuzzily_match', 'value': 'unopposed', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'candidates', 'unopposed'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose candidates record fuzzily matches to unopposed .', 'tostr': 'filter_eq { all_rows ; candidates ; unopposed }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; candidates ; unopposed } }', 'tointer': 'select the rows whose candidates record fuzzily matches to unopposed . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'candidates', 'unopposed'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose candidates record fuzzily matches to unopposed .', 'tostr': 'filter_eq { all_rows ; candidates ; unopposed }'}, 'incumbent'], 'result': 'tony p hall', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; candidates ; unopposed } ; incumbent }'}, 'tony p hall'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; candidates ; unopposed } ; incumbent } ; tony p hall }', 'tointer': 'the incumbent record of this unqiue row is tony p hall .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; candidates ; unopposed } } ; eq { hop { filter_eq { all_rows ; candidates ; unopposed } ; incumbent } ; tony p hall } } = true', 'tointer': 'select the rows whose candidates record fuzzily matches to unopposed . there is only one such row in the table . the incumbent record of this unqiue row is tony p hall .'} | and { only { filter_eq { all_rows ; candidates ; unopposed } } ; eq { hop { filter_eq { all_rows ; candidates ; unopposed } ; incumbent } ; tony p hall } } = true | select the rows whose candidates record fuzzily matches to unopposed . there is only one such row in the table . the incumbent record of this unqiue row is tony p hall . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'candidates_7': 7, 'unopposed_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'incumbent_9': 9, 'tony p hall_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'candidates_7': 'candidates', 'unopposed_8': 'unopposed', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'incumbent_9': 'incumbent', 'tony p hall_10': 'tony p hall'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'candidates_7': [0], 'unopposed_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'incumbent_9': [2], 'tony p hall_10': [3]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['ohio 2', 'bill gradison', 'republican', '1974', 're - elected', 'bill gradison ( r ) 68.6 % thomas j porter ( d ) 31.4 %'], ['ohio 3', 'tony p hall', 'democratic', '1978', 're - elected', 'tony p hall ( d ) unopposed'], ['ohio 4', 'mike oxley', 'republican', '1972', 're - elected', 'mike oxley ( r ) 77.5 % william o sutton ( d ) 22.5 %'], ['ohio 5', 'del latta', 'republican', '1958', 're - elected', 'del latta ( r ) 62.7 % james r sherck ( d ) 37.3 %'], ['ohio 6', 'bob mcewen', 'republican', '1980', 're - elected', 'bob mcewen ( r ) 74.0 % bob smith ( d ) 26.0 %'], ['ohio 8', 'tom kindness', 'republican', '1974', 're - elected', 'tom kindness ( r ) 76.9 % john t francis ( d ) 23.1 %'], ['ohio 11', 'dennis e eckart', 'democratic', '1980', 're - elected', 'dennis e eckart ( d ) 66.8 % dean beagle ( r ) 33.2 %'], ['ohio 12', 'john kasich', 'republican', '1982', 're - elected', 'john kasich ( r ) 69.5 % richard s sloan ( d ) 30.5 %'], ['ohio 15', 'chalmers p wylie', 'republican', '1966', 're - elected', 'chalmers p wylie ( r ) 71.6 % duane jager ( d ) 28.4 %'], ['ohio 16', 'ralph regula', 'republican', '1972', 're - elected', 'ralph regula ( r ) 72.4 % james gwin ( d ) 27.6 %']] |
lessons to be learned | https://en.wikipedia.org/wiki/Lessons_to_Be_Learned | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15038728-5.html.csv | unique | the only location where the album was released in 2009 was the united states . | {'scope': 'all', 'row': '8', 'col': '1', 'col_other': '2', 'criterion': 'equal', 'value': 'united states', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'region', 'united states'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose region record fuzzily matches to united states .', 'tostr': 'filter_eq { all_rows ; region ; united states }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; region ; united states } }', 'tointer': 'select the rows whose region record fuzzily matches to united states . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'region', 'united states'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose region record fuzzily matches to united states .', 'tostr': 'filter_eq { all_rows ; region ; united states }'}, 'date'], 'result': '17 march 2009', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; region ; united states } ; date }'}, '17 march 2009'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; region ; united states } ; date } ; 17 march 2009 }', 'tointer': 'the date record of this unqiue row is 17 march 2009 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; region ; united states } } ; eq { hop { filter_eq { all_rows ; region ; united states } ; date } ; 17 march 2009 } } = true', 'tointer': 'select the rows whose region record fuzzily matches to united states . there is only one such row in the table . the date record of this unqiue row is 17 march 2009 .'} | and { only { filter_eq { all_rows ; region ; united states } } ; eq { hop { filter_eq { all_rows ; region ; united states } ; date } ; 17 march 2009 } } = true | select the rows whose region record fuzzily matches to united states . there is only one such row in the table . the date record of this unqiue row is 17 march 2009 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'region_7': 7, 'united states_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'date_9': 9, '17 march 2009_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'region_7': 'region', 'united states_8': 'united states', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'date_9': 'date', '17 march 2009_10': '17 march 2009'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'region_7': [0], 'united states_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'date_9': [2], '17 march 2009_10': [3]} | ['region', 'date', 'label', 'format', 'catalogue'] | [['united kingdom', '31 march 2008', 'island', 'cd , digital download', '1763307'], ['australia', '10 may 2008', 'mushroom', 'cd , digital download', '5144275002'], ['new zealand', '12 may 2008', 'warner bros', 'cd , digital download', '5144275002'], ['europe', '20 june 2008', 'island', 'cd , digital download', '060251773945'], ['brazil', '10 september 2008', 'universal', 'cd', '602517739468'], ['australia ( deluxe edition )', '11 october 2008', 'mushroom', 'cd', '5186504315'], ['poland', '28 october 2008', 'universal', 'cd', '1785089'], ['united states', '17 march 2009', 'universal republic', 'cd', 'b0012720 - 02']] |
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