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naoki tsukahara | https://en.wikipedia.org/wiki/Naoki_Tsukahara | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11401861-1.html.csv | count | naoki tsukahara finished in second position at four different competitions . | {'scope': 'all', 'criterion': 'equal', 'value': '2nd', 'result': '4', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'position', '2nd'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose position record fuzzily matches to 2nd .', 'tostr': 'filter_eq { all_rows ; position ; 2nd }'}], 'result': '4', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; position ; 2nd } }', 'tointer': 'select the rows whose position record fuzzily matches to 2nd . the number of such rows is 4 .'}, '4'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; position ; 2nd } } ; 4 } = true', 'tointer': 'select the rows whose position record fuzzily matches to 2nd . the number of such rows is 4 .'} | eq { count { filter_eq { all_rows ; position ; 2nd } } ; 4 } = true | select the rows whose position record fuzzily matches to 2nd . the number of such rows is 4 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'position_5': 5, '2nd_6': 6, '4_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'position_5': 'position', '2nd_6': '2nd', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'position_5': [0], '2nd_6': [0], '4_7': [2]} | ['year', 'competition', 'venue', 'position', 'notes'] | [['2003', '58th national sports festival of japan', 'shizuoka , japan', '7th', '100 m'], ['2004', 'japan student athletics championships', 'unknown , japan', '6th', '200 m'], ['2004', 'world junior championships', 'grosseto , italy', '3rd', '4x100 m relay'], ['2006', 'kanto students athletics championships', 'kantō , japan', '2nd', '100 m'], ['2006', 'kanto students athletics championships', 'kantō , japan', '2nd', '200 m'], ['2006', 'japan association of athletics championships', 'tokyo , japan', '1st', '100 m'], ['2006', 'japan association of athletics championships', 'tokyo , japan', '3rd', '200 m'], ['2006', 'world cup', 'athens , greece', '3rd', '4x100 m relay'], ['2006', 'asian games', 'doha , qatar', '2nd', '100 m'], ['2006', 'asian games', 'doha , qatar', '2nd', '4x100 m relay'], ['2008', 'olympic games', 'beijing , china', '3rd', '4x100 m relay']] |
annika sörenstam | https://en.wikipedia.org/wiki/Annika_S%C3%B6renstam | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-102100-7.html.csv | majority | in all of her matches , annika sörenstam scored at least one point . | {'scope': 'all', 'col': '5', 'most_or_all': 'all', 'criterion': 'greater_than_eq', 'value': '1', 'subset': None} | {'func': 'all_greater_eq', 'args': ['all_rows', 'points won', '1'], 'result': True, 'ind': 0, 'tointer': 'for the points won records of all rows , all of them are greater than or equal to 1 .', 'tostr': 'all_greater_eq { all_rows ; points won ; 1 } = true'} | all_greater_eq { all_rows ; points won ; 1 } = true | for the points won records of all rows , all of them are greater than or equal to 1 . | 1 | 1 | {'all_greater_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'points won_3': 3, '1_4': 4} | {'all_greater_eq_0': 'all_greater_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'points won_3': 'points won', '1_4': '1'} | {'all_greater_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'points won_3': [0], '1_4': [0]} | ['year', 'total matches', 'total w - l - h', 'singles w - l - h', 'points won', 'points %'] | [['career', '37', '22 - 11 - 4', '4 - 3 - 1', '24', '64.9'], ['1994', '3', '1 - 2 - 0', '0 - 1 - 0 lost to t green', '1', '33.3'], ['1996', '5', '3 - 0 - 2', '1 - 0 - 0 def p bradley 2 & 1', '4', '80.0'], ['1998', '5', '3 - 2 - 0', '1 - 0 - 0 def d andrews 2 & 1', '3', '60.0'], ['2000', '4', '2 - 2 - 0', '0 - 1 - 0 lost to j inkster 5 & 4', '2', '50.0'], ['2002', '5', '3 - 1 - 1', '0 - 0 - 1 halved w / w ward', '3.5', '70.0'], ['2003', '5', '4 - 1 - 0', '1 - 0 - 0 def a stanford 3 & 2', '4', '80.0'], ['2005', '5', '4 - 1 - 0', '1 - 0 - 0 def b daniel 4 & 3', '4', '80.0'], ['2007', '5', '2 - 2 - 1', '0 - 1 - 0 lost to m pressel 2 & 1', '2.5', '50.0']] |
2007 - 08 ukrainian first league | https://en.wikipedia.org/wiki/2007%E2%80%9308_Ukrainian_First_League | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12331289-3.html.csv | count | there are 11 stadiums that can fit more than 5,000 people . | {'scope': 'all', 'criterion': 'greater_than', 'value': '5000', 'result': '11', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'capacity', '5000'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose capacity record is greater than 5000 .', 'tostr': 'filter_greater { all_rows ; capacity ; 5000 }'}], 'result': '11', 'ind': 1, 'tostr': 'count { filter_greater { all_rows ; capacity ; 5000 } }', 'tointer': 'select the rows whose capacity record is greater than 5000 . the number of such rows is 11 .'}, '11'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_greater { all_rows ; capacity ; 5000 } } ; 11 } = true', 'tointer': 'select the rows whose capacity record is greater than 5000 . the number of such rows is 11 .'} | eq { count { filter_greater { all_rows ; capacity ; 5000 } } ; 11 } = true | select the rows whose capacity record is greater than 5000 . the number of such rows is 11 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_greater_0': 0, 'all_rows_4': 4, 'capacity_5': 5, '5000_6': 6, '11_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_greater_0': 'filter_greater', 'all_rows_4': 'all_rows', 'capacity_5': 'capacity', '5000_6': '5000', '11_7': '11'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_greater_0': [1], 'all_rows_4': [0], 'capacity_5': [0], '5000_6': [0], '11_7': [2]} | ['rank', 'stadium', 'capacity', 'club', 'region'] | [['1', 'lobanovsky dynamo stadium', '16873', 'fc dynamo - 2 kyiv', 'kiev'], ['2', 'mcs rukh', '16000', 'fsc prykarpattya ivano - frankivsk', 'ivano - frankivsk'], ['3', 'illychivets', '12680', 'fc illichivets mariupol', 'donetsk'], ['4', 'youri haharyn', '12000', 'fc desna chernihiv', 'chernihiv'], ['5', 'csk zsu', '12000', 'csca kyiv', 'kiev'], ['6', 'avanhard', '11574', 'fc volyn lutsk', 'lutsk'], ['7', 'central', '10321', 'fc dnipro cherkasy', 'cherkasy'], ['8', 'stal', '9200', 'fc stal alchevsk', 'luhansk'], ['9', 'sk sevastopol', '6500', 'pfc sevastopol', 'crimea'], ['10', 'dynamo', '6000', 'fc helios kharkiv', 'kharkiv'], ['11', 'ksc nika', '5640', 'pfc oleksandria', 'kirovohrad'], ['12', 'fiolent', '5000', 'fc ihroservice simferopol', 'crimea'], ['13', 'enerhetyk stadium', '4000', 'fc enerhetyk burshtyn', 'ivano - frankivsk'], ['14', 'kniazha arena', '3220', 'fc lviv', 'lviv'], ['15', 'stc krymteplitsia', '3000', 'fc krymteplitsia molodizhne', 'crimea'], ['16', 'metalurh', '2900', 'fc stal dniprodzerzhynsk', 'dnipropetrovsk'], ['17', 'central city stadium', '1500', 'mfk mykolaiv', 'mykolaiv'], ['18', 'dukov dniester stadium', '1500', 'fc dniester ovidiopol', 'odessa'], ['19', 'obolon', '4300', 'fc obolon kyiv', 'kiev'], ['20', 'kalinino', '1050', 'fc feniks - illichovets kalinine', 'crimea']] |
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/2-1805191-24.html.csv | count | for the 2006 election for the united states house of representatives , four of the incumbents were from the democratic party . | {'scope': 'all', 'criterion': 'equal', 'value': 'democratic', 'result': '4', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'party', 'democratic'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose party record fuzzily matches to democratic .', 'tostr': 'filter_eq { all_rows ; party ; democratic }'}], 'result': '4', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; party ; democratic } }', 'tointer': 'select the rows whose party record fuzzily matches to democratic . the number of such rows is 4 .'}, '4'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; party ; democratic } } ; 4 } = true', 'tointer': 'select the rows whose party record fuzzily matches to democratic . the number of such rows is 4 .'} | eq { count { filter_eq { all_rows ; party ; democratic } } ; 4 } = true | select the rows whose party record fuzzily matches to democratic . the number of such rows is 4 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'party_5': 5, 'democratic_6': 6, '4_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'party_5': 'party', 'democratic_6': 'democratic', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'party_5': [0], 'democratic_6': [0], '4_7': [2]} | ['district', 'incumbent', 'party', 'first elected', 'results'] | [['minnesota 1', 'gil gutknecht', 'republican', '1994', 'lost re - election democratic gain'], ['minnesota 2', 'john kline', 'republican', '2002', 're - elected'], ['minnesota 3', 'jim ramstad', 'republican', '1990', 're - elected'], ['minnesota 4', 'betty mccollum', 'democratic', '2000', 're - elected'], ['minnesota 5', 'martin sabo', 'democratic', '1978', 'retired democratic hold'], ['minnesota 6', 'mark kennedy', 'republican', '2000', 'retired to run for us senate republican hold'], ['minnesota 7', 'collin peterson', 'democratic', '1990', 're - elected'], ['minnesota 8', 'jim oberstar', 'democratic', '1974', 're - elected']] |
mikhail youzhny | https://en.wikipedia.org/wiki/Mikhail_Youzhny | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1549452-2.html.csv | unique | 2010 was the only year that mikhail youzhny had 12 wins in grand slam tournaments . | {'scope': 'all', 'row': '6', 'col': '12', 'col_other': '1', 'criterion': 'fuzzily_match', 'value': '12', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', '2010', '12'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose 2010 record fuzzily matches to 12 .', 'tostr': 'filter_eq { all_rows ; 2010 ; 12 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; 2010 ; 12 } }', 'tointer': 'select the rows whose 2010 record fuzzily matches to 12 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', '2010', '12'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose 2010 record fuzzily matches to 12 .', 'tostr': 'filter_eq { all_rows ; 2010 ; 12 }'}, 'tournament'], 'result': 'win - loss', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; 2010 ; 12 } ; tournament }'}, 'win - loss'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; 2010 ; 12 } ; tournament } ; win - loss }', 'tointer': 'the tournament record of this unqiue row is win - loss .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; 2010 ; 12 } } ; eq { hop { filter_eq { all_rows ; 2010 ; 12 } ; tournament } ; win - loss } } = true', 'tointer': 'select the rows whose 2010 record fuzzily matches to 12 . there is only one such row in the table . the tournament record of this unqiue row is win - loss .'} | and { only { filter_eq { all_rows ; 2010 ; 12 } } ; eq { hop { filter_eq { all_rows ; 2010 ; 12 } ; tournament } ; win - loss } } = true | select the rows whose 2010 record fuzzily matches to 12 . there is only one such row in the table . the tournament record of this unqiue row is win - loss . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, '2010_7': 7, '12_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'tournament_9': 9, 'win - loss_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', '2010_7': '2010', '12_8': '12', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'tournament_9': 'tournament', 'win - loss_10': 'win - loss'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], '2010_7': [0], '12_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'tournament_9': [2], 'win - loss_10': [3]} | ['tournament', '2000', '2001', '2002', '2003', '2004', '2005', '2006', '2007', '2008', '2009', '2010', '2011', '2012'] | [['grand slam tournaments', 'grand slam tournaments', 'grand slam tournaments', 'grand slam tournaments', 'grand slam tournaments', 'grand slam tournaments', 'grand slam tournaments', 'grand slam tournaments', 'grand slam tournaments', 'grand slam tournaments', 'grand slam tournaments', 'grand slam tournaments', 'grand slam tournaments', 'grand slam tournaments'], ['australian open', 'a', '3r', '3r', '4r', '1r', '2r', '1r', '3r', 'qf', '1r', '3r', '3r', '1r'], ['french open', 'q1', '1r', '1r', '2r', '3r', '2r', '2r', '4r', '3r', '2r', 'qf', '3r', '3r'], ['wimbledon', 'a', '4r', '4r', '2r', '1r', '4r', '3r', '4r', '4r', '1r', '2r', '4r', 'qf'], ['us open', 'a', '3r', 'a', '1r', '3r', '3r', 'sf', '2r', 'a', '2r', 'sf', '1r', '1r'], ['win - loss', '0 - 0', '7 - 4', '5 - 3', '5 - 4', '4 - 4', '7 - 4', '8 - 4', '9 - 4', '9 - 3', '2 - 4', '12 - 3', '7 - 4', '6 - 4'], ['year - end ranking', '113', '58', '32', '43', '16', '43', '24', '19', '32', '19', '10', '35', '25']] |
1973 buffalo bills season | https://en.wikipedia.org/wiki/1973_Buffalo_Bills_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16028459-2.html.csv | ordinal | during the 1973 buffalo bills season , when the buffalo bills played against new york jets for the second time , they had scored 34 points . | {'scope': 'subset', 'row': '14', 'col': '2', 'order': '2', 'col_other': '5', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'subset': {'col': '3', 'criterion': 'equal', 'value': 'new york jets'}} | {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'nth_argmin', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', 'new york jets'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; opponent ; new york jets }', 'tointer': 'select the rows whose opponent record fuzzily matches to new york jets .'}, 'date', '2'], 'result': None, 'ind': 1, 'tostr': 'nth_argmin { filter_eq { all_rows ; opponent ; new york jets } ; date ; 2 }'}, 'bills points'], 'result': '34', 'ind': 2, 'tostr': 'hop { nth_argmin { filter_eq { all_rows ; opponent ; new york jets } ; date ; 2 } ; bills points }'}, '34'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { nth_argmin { filter_eq { all_rows ; opponent ; new york jets } ; date ; 2 } ; bills points } ; 34 } = true', 'tointer': 'select the rows whose opponent record fuzzily matches to new york jets . select the row whose date record of these rows is 2nd minimum . the bills points record of this row is 34 .'} | eq { hop { nth_argmin { filter_eq { all_rows ; opponent ; new york jets } ; date ; 2 } ; bills points } ; 34 } = true | select the rows whose opponent record fuzzily matches to new york jets . select the row whose date record of these rows is 2nd minimum . the bills points record of this row is 34 . | 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, 'opponent_6': 6, 'new york jets_7': 7, 'date_8': 8, '2_9': 9, 'bills points_10': 10, '34_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', 'opponent_6': 'opponent', 'new york jets_7': 'new york jets', 'date_8': 'date', '2_9': '2', 'bills points_10': 'bills points', '34_11': '34'} | {'eq_3': [4], 'result_4': [], 'num_hop_2': [3], 'nth_argmin_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'opponent_6': [0], 'new york jets_7': [0], 'date_8': [1], '2_9': [1], 'bills points_10': [2], '34_11': [3]} | ['game', 'date', 'opponent', 'result', 'bills points', 'opponents', 'bills first downs', 'record'] | [['1', 'sept 16', 'new england patriots', 'win', '31', '13', '23', '1 - 0'], ['2', 'sept 23', 'san diego chargers', 'loss', '7', '34', '16', '1 - 1'], ['3', 'sept 30', 'new york jets', 'win', '9', '7', '15', '2 - 1'], ['4', 'oct 7', 'philadelphia eagles', 'win', '27', '26', '16', '3 - 1'], ['5', 'oct 14', 'baltimore colts', 'win', '31', '13', '18', '4 - 1'], ['6', 'oct 21', 'miami dolphins', 'loss', '6', '27', '8', '4 - 2'], ['7', 'oct 29', 'kansas city chiefs', 'win', '23', '14', '21', '5 - 2'], ['8', 'nov 4', 'new orleans saints', 'loss', '0', '13', '10', '5 - 3'], ['9', 'nov 11', 'cincinnati bengals', 'loss', '13', '16', '10', '5 - 4'], ['10', 'nov 18', 'miami dolphins', 'loss', '0', '17', '15', '5 - 5'], ['11', 'nov 25', 'baltimore colts', 'win', '24', '17', '16', '6 - 5'], ['12', 'dec 2', 'atlanta falcons', 'win', '17', '6', '17', '7 - 5'], ['13', 'dec 9', 'new england patriots', 'win', '37', '13', '13', '8 - 5'], ['14', 'dec 16', 'new york jets', 'win', '34', '14', '21', '9 - 5']] |
angela stanford | https://en.wikipedia.org/wiki/Angela_Stanford | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-14836185-3.html.csv | unique | 2002 was the only year that angela stanford played less than 20 tournaments . | {'scope': 'all', 'row': '2', 'col': '2', 'col_other': '1', 'criterion': 'less_than', 'value': '20', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'tournaments played', '20'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose tournaments played record is less than 20 .', 'tostr': 'filter_less { all_rows ; tournaments played ; 20 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_less { all_rows ; tournaments played ; 20 } }', 'tointer': 'select the rows whose tournaments played record is less than 20 . there is only one such row in the table .'}, {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'tournaments played', '20'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose tournaments played record is less than 20 .', 'tostr': 'filter_less { all_rows ; tournaments played ; 20 }'}, 'year'], 'result': '2002', 'ind': 2, 'tostr': 'hop { filter_less { all_rows ; tournaments played ; 20 } ; year }'}, '2002'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_less { all_rows ; tournaments played ; 20 } ; year } ; 2002 }', 'tointer': 'the year record of this unqiue row is 2002 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_less { all_rows ; tournaments played ; 20 } } ; eq { hop { filter_less { all_rows ; tournaments played ; 20 } ; year } ; 2002 } } = true', 'tointer': 'select the rows whose tournaments played record is less than 20 . there is only one such row in the table . the year record of this unqiue row is 2002 .'} | and { only { filter_less { all_rows ; tournaments played ; 20 } } ; eq { hop { filter_less { all_rows ; tournaments played ; 20 } ; year } ; 2002 } } = true | select the rows whose tournaments played record is less than 20 . there is only one such row in the table . the year record of this unqiue row is 2002 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_less_0': 0, 'all_rows_6': 6, 'tournaments played_7': 7, '20_8': 8, 'eq_3': 3, 'num_hop_2': 2, 'year_9': 9, '2002_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_less_0': 'filter_less', 'all_rows_6': 'all_rows', 'tournaments played_7': 'tournaments played', '20_8': '20', 'eq_3': 'eq', 'num_hop_2': 'num_hop', 'year_9': 'year', '2002_10': '2002'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_less_0': [1, 2], 'all_rows_6': [0], 'tournaments played_7': [0], '20_8': [0], 'eq_3': [4], 'num_hop_2': [3], 'year_9': [2], '2002_10': [3]} | ['year', 'tournaments played', 'cuts made', 'wins', '2nd', '3rd', 'top 10s', 'best finish', 'earnings', 'money list rank', 'scoring average', 'scoring rank'] | [['2001', '26', '12', '0', '0', '0', '0', 't15', '66956', '98', '73.24', '103'], ['2002', '19', '12', '0', '1', '0', '2', '2', '221857', '45', '72.37', '46'], ['2003', '21', '17', '1', '1', '0', '3', '1', '643192', '17', '71.94', '38'], ['2004', '24', '19', '0', '0', '0', '2', 't4', '297790', '39', '71.86', 't43'], ['2005', '25', '15', '0', '0', '1', '3', 't3', '272288', '44', '73.11', '69'], ['2006', '25', '20', '0', '2', '0', '3', '2', '473218', '23', '71.80', 't29'], ['2007', '24', '21', '0', '0', '2', '12', 't3', '713880', '19', '71.62', '11'], ['2008', '27', '23', '2', '1', '2', '10', '1', '1134753', '9', '71.22', '9'], ['2009', '21', '20', '1', '2', '2', '11', '1', '1081916', '10', '70.64', '11'], ['2010', '22', '19', '0', '1', '0', '7', '2', '596830', '18', '71.35', '19'], ['2011', '21', '20', '0', '0', '3', '9', '3', '1017196', '7', '71.42', '15'], ['2012', '26', '23', '1', '2', '1', '6', '1', '794294', '16', '71.51', '21']] |
2009 premier league darts | https://en.wikipedia.org/wiki/2009_Premier_League_Darts | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18968744-17.html.csv | unique | terry jenkins had a 100 + of 207 in the 2009 premier league darts . | {'scope': 'all', 'row': '5', 'col': '3', 'col_other': '1', 'criterion': 'equal', 'value': '207', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', '100 +', '207'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose 100 + record is equal to 207 .', 'tostr': 'filter_eq { all_rows ; 100 + ; 207 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; 100 + ; 207 } }', 'tointer': 'select the rows whose 100 + record is equal to 207 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_eq', 'args': ['all_rows', '100 +', '207'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose 100 + record is equal to 207 .', 'tostr': 'filter_eq { all_rows ; 100 + ; 207 }'}, 'name'], 'result': 'terry jenkins', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; 100 + ; 207 } ; name }'}, 'terry jenkins'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; 100 + ; 207 } ; name } ; terry jenkins }', 'tointer': 'the name record of this unqiue row is terry jenkins .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; 100 + ; 207 } } ; eq { hop { filter_eq { all_rows ; 100 + ; 207 } ; name } ; terry jenkins } } = true', 'tointer': 'select the rows whose 100 + record is equal to 207 . there is only one such row in the table . the name record of this unqiue row is terry jenkins .'} | and { only { filter_eq { all_rows ; 100 + ; 207 } } ; eq { hop { filter_eq { all_rows ; 100 + ; 207 } ; name } ; terry jenkins } } = true | select the rows whose 100 + record is equal to 207 . there is only one such row in the table . the name record of this unqiue row is terry jenkins . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, '100 +_7': 7, '207_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'name_9': 9, 'terry jenkins_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', '100 +_7': '100 +', '207_8': '207', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'name_9': 'name', 'terry jenkins_10': 'terry jenkins'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], '100 +_7': [0], '207_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'name_9': [2], 'terry jenkins_10': [3]} | ['name', 'lwat', '100 +', '140 +', '180s'] | [['phil taylor', '29', '194', '128', '56'], ['james wade', '28', '181', '114', '43'], ['raymond van barneveld', '25', '188', '122', '43'], ['mervyn king', '28', '203', '114', '37'], ['terry jenkins', '26', '207', '129', '46'], ['john part', '18', '180', '72', '25'], ['jelle klaasen', '26', '173', '93', '33']] |
isabel cueto | https://en.wikipedia.org/wiki/Isabel_Cueto | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17086086-2.html.csv | majority | of the tournaments that isabel cueto participated in , all of them were on a clay surface . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'clay', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'surface', 'clay'], 'result': True, 'ind': 0, 'tointer': 'for the surface records of all rows , most of them fuzzily match to clay .', 'tostr': 'most_eq { all_rows ; surface ; clay } = true'} | most_eq { all_rows ; surface ; clay } = true | for the surface records of all rows , most of them fuzzily match to clay . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'surface_3': 3, 'clay_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'surface_3': 'surface', 'clay_4': 'clay'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'surface_3': [0], 'clay_4': [0]} | ['date', 'tournament', 'surface', 'opponent in the final', 'score'] | [['4 july 1988', 'båstad , sweden', 'clay', 'sandra cecchini', '7 - 5 , 6 - 1'], ['1 august 1988', 'athens , greece', 'clay', 'laura golarsa', '6 - 0 , 6 - 1'], ['17 july 1989', 'estoril , portugal', 'clay', 'sandra cecchini', '7 - 6 ( 3 ) , 6 - 2'], ['31 july 1989', 'sofia , bulgaria', 'clay', 'katerina maleeva', '6 - 2 , 7 - 6 ( 3 )'], ['9 july 1990', 'palermo , italy', 'clay', 'barbara paulus', '6 - 2 , 6 - 3']] |
marianne werdel | https://en.wikipedia.org/wiki/Marianne_Werdel | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15113825-5.html.csv | majority | marianne werdel was the runner-up in all the tournaments she participated that were played on clay surface . | {'scope': 'subset', 'col': '1', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'runner-up', 'subset': {'col': '4', 'criterion': 'equal', 'value': 'clay'}} | {'func': 'all_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'surface', 'clay'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; surface ; clay }', 'tointer': 'select the rows whose surface record fuzzily matches to clay .'}, 'outcome', 'runner-up'], 'result': True, 'ind': 1, 'tointer': 'select the rows whose surface record fuzzily matches to clay . for the outcome records of these rows , all of them fuzzily match to runner-up .', 'tostr': 'all_eq { filter_eq { all_rows ; surface ; clay } ; outcome ; runner-up } = true'} | all_eq { filter_eq { all_rows ; surface ; clay } ; outcome ; runner-up } = true | select the rows whose surface record fuzzily matches to clay . for the outcome records of these rows , all of them fuzzily match to runner-up . | 2 | 2 | {'all_str_eq_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, 'surface_4': 4, 'clay_5': 5, 'outcome_6': 6, 'runner-up_7': 7} | {'all_str_eq_1': 'all_str_eq', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'surface_4': 'surface', 'clay_5': 'clay', 'outcome_6': 'outcome', 'runner-up_7': 'runner-up'} | {'all_str_eq_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'surface_4': [0], 'clay_5': [0], 'outcome_6': [1], 'runner-up_7': [1]} | ['outcome', 'date', 'tournament', 'surface', 'partner', 'opponents', 'score'] | [['runner - up', 'may 24 , 1992', 'european open , switzerland', 'clay', 'karina habšudová', 'amy frazier elna reinach', '5 - 7 , 2 - 6'], ['runner - up', 'may 23 , 1993', 'european open , switzerland', 'clay', 'lindsay davenport', 'mary joe fernandez helena suková', '2 - 6 , 4 - 6'], ['runner - up', 'september 19 , 1993', 'hong kong', 'hard', 'debbie graham', 'karin kschwendt rachel mcquillan', '6 - 4 , 4 - 6 , 2 - 6'], ['runner - up', 'february 12 , 1995', 'chicago , illinois , usa', 'carpet', 'tami whitlinger - jones', 'gabriela sabatini brenda shultz', '7 - 5 , 6 - 7 , 4 - 6'], ['runner - up', 'may 25 , 1996', 'strasbourg , france', 'clay', 'tami whitlinger - jones', 'yayuk basuki nicole bradtke', '7 - 5 , 4 - 6 , 4 - 6'], ['runner - up', 'february 23 , 1997', 'oklahoma city , oklahoma , usa', 'hard', 'tami whitlinger - jones', 'rika hiraki nana miyagi', '4 - 6 , 1 - 6']] |
list of awards and nominations received by er | https://en.wikipedia.org/wiki/List_of_awards_and_nominations_received_by_ER | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18540176-11.html.csv | majority | john wells was the nominee for most of the awards that er was nominated for . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'john wells', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'nominee ( s )', 'john wells'], 'result': True, 'ind': 0, 'tointer': 'for the nominee ( s ) records of all rows , most of them fuzzily match to john wells .', 'tostr': 'most_eq { all_rows ; nominee ( s ) ; john wells } = true'} | most_eq { all_rows ; nominee ( s ) ; john wells } = true | for the nominee ( s ) records of all rows , most of them fuzzily match to john wells . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'nominee (s)_3': 3, 'john wells_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'nominee (s)_3': 'nominee ( s )', 'john wells_4': 'john wells'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'nominee (s)_3': [0], 'john wells_4': [0]} | ['year', 'category', 'nominee ( s )', 'episode', 'result'] | [['1996', '60 minute category', 'john wells', 'the healers', 'nominated'], ['1998', '60 minute category', 'carol flint', 'family practice', 'nominated'], ['2001', '60 minute category', 'john wells', 'a walk in the woods', 'nominated'], ['2003', '60 minute category', 'john wells', 'on the beach', 'nominated'], ['2004', '60 minute category', 'john wells', 'makemba', 'nominated'], ['2005', '60 minute category', 'dee johnson', 'alone in a crowd', 'nominated'], ['2006', '60 minute category', 'janine sherman', 'darfur', 'nominated'], ['2007', '60 minute category', 'r scott gemmill , david zabel', 'there are no angels here', 'won']] |
arizona wildcats men 's basketball | https://en.wikipedia.org/wiki/Arizona_Wildcats_men%27s_basketball | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10609116-6.html.csv | majority | most of the tournaments were played in los angeles , california . | {'scope': 'all', 'col': '6', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'los angeles , california', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'city', 'los angeles , california'], 'result': True, 'ind': 0, 'tointer': 'for the city records of all rows , most of them fuzzily match to los angeles , california .', 'tostr': 'most_eq { all_rows ; city ; los angeles , california } = true'} | most_eq { all_rows ; city ; los angeles , california } = true | for the city records of all rows , most of them fuzzily match to los angeles , california . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'city_3': 3, 'los angeles, california_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'city_3': 'city', 'los angeles, california_4': 'los angeles , california'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'city_3': [0], 'los angeles, california_4': [0]} | ['year', 'champion', 'score', 'runner - up', 'arena', 'city', 'tournament mvp'] | [['1988', 'arizona', '93 - 67', 'oregon state', 'mckale center', 'tucson , arizona', 'sean elliott , arizona'], ['1989', 'arizona', '73 - 51', 'stanford', 'great western forum', 'inglewood , california', 'sean elliott , arizona'], ['1990', 'arizona', '94 - 78', 'ucla', 'university activity center', 'tempe , arizona', 'jud buechler , arizona'], ['2002', 'arizona', '81 - 71', 'usc', 'staples center', 'los angeles , california', 'luke walton , arizona'], ['2005', 'washington', '81 - 72', 'arizona', 'staples center', 'los angeles , california', 'salim stoudamire , arizona'], ['2011', 'washington', '77 - 75 ( ot )', 'arizona', 'staples center', 'los angeles , california', 'isaiah thomas , washington'], ['2012', 'colorado', '53 - 51', 'arizona', 'staples center', 'los angeles , california', 'carlon brown , colorado']] |
2007 latvian first league | https://en.wikipedia.org/wiki/2007_Latvian_First_League | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18017970-2.html.csv | count | all teams played 30 games in the 2007 latvian first league . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': '30', 'result': '16', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'played', '30'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose played record fuzzily matches to 30 .', 'tostr': 'filter_eq { all_rows ; played ; 30 }'}], 'result': '16', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; played ; 30 } }', 'tointer': 'select the rows whose played record fuzzily matches to 30 . the number of such rows is 16 .'}, '16'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; played ; 30 } } ; 16 } = true', 'tointer': 'select the rows whose played record fuzzily matches to 30 . the number of such rows is 16 .'} | eq { count { filter_eq { all_rows ; played ; 30 } } ; 16 } = true | select the rows whose played record fuzzily matches to 30 . the number of such rows is 16 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'played_5': 5, '30_6': 6, '16_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'played_5': 'played', '30_6': '30', '16_7': '16'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'played_5': [0], '30_6': [0], '16_7': [2]} | ['position', 'club', 'played', 'wins', 'draws', 'losses', 'goals for', 'goals against', 'points', 'goal difference'] | [['1', 'fk vindava ventspils', '30', '26', '2', '2', '116', '11', '80', '+ 105'], ['2', 'sk blāzma rēzekne', '30', '25', '4', '1', '101', '11', '79', '+ 90'], ['3', 'fk auda rīga', '30', '20', '5', '5', '104', '31', '65', '+ 73'], ['4', 'fk metta / lu rīga', '30', '18', '7', '5', '67', '23', '61', '+ 44'], ['5', 'fk jelgava', '30', '16', '6', '8', '70', '43', '54', '+ 27'], ['6', 'fk jaunība - parex rīga', '30', '16', '3', '11', '71', '51', '51', '+ 20'], ['7', 'fk kauguri - pblc jūrmala', '30', '14', '4', '12', '67', '55', '46', '+ 12'], ['8', 'rfs / flaminko rīga', '30', '14', '2', '14', '60', '62', '44', '- 2'], ['9', 'fk zibens / zemessardze ilūkste', '30', '13', '3', '14', '79', '68', '42', '+ 11'], ['10', 'valmieras fk', '30', '12', '4', '14', '63', '59', '40', '+ 4'], ['11', 'fsk daugava - 90 rīga', '30', '11', '6', '13', '51', '63', '39', '- 12'], ['12', 'fk tukums - 2000 / tss', '30', '11', '3', '16', '61', '75', '36', '- 14'], ['13', 'fk multibanka rīga', '30', '6', '1', '23', '45', '96', '19', '- 51'], ['14', 'fk tranzīts ventspils', '30', '4', '4', '22', '29', '103', '17', '- 74'], ['15', 'fk abuls smiltene', '30', '3', '2', '25', '22', '163', '11', '- 141'], ['16', 'fk ilūkste / bjss', '30', '2', '2', '26', '8', '93', '8', '- 85']] |
south africa | https://en.wikipedia.org/wiki/South_Africa | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17416221-1.html.csv | majority | most of the provinces in south africa have less than 10,000,000 people living in them . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'less_than', 'value': '10000000', 'subset': None} | {'func': 'most_less', 'args': ['all_rows', 'population ( 2013 )', '10000000'], 'result': True, 'ind': 0, 'tointer': 'for the population ( 2013 ) records of all rows , most of them are less than 10000000 .', 'tostr': 'most_less { all_rows ; population ( 2013 ) ; 10000000 } = true'} | most_less { all_rows ; population ( 2013 ) ; 10000000 } = true | for the population ( 2013 ) records of all rows , most of them are less than 10000000 . | 1 | 1 | {'most_less_0': 0, 'result_1': 1, 'all_rows_2': 2, 'population (2013)_3': 3, '10000000_4': 4} | {'most_less_0': 'most_less', 'result_1': 'true', 'all_rows_2': 'all_rows', 'population (2013)_3': 'population ( 2013 )', '10000000_4': '10000000'} | {'most_less_0': [1], 'result_1': [], 'all_rows_2': [0], 'population (2013)_3': [0], '10000000_4': [0]} | ['province', 'provincial capital', 'largest city', 'area ( km 2 )', 'population ( 2013 )'] | [['eastern cape', 'bhisho', 'port elizabeth', '168966', '6620100'], ['free state', 'bloemfontein', 'bloemfontein', '129825', '2753200'], ['gauteng', 'johannesburg', 'johannesburg', '18178', '12728400'], ['kwazulu - natal', 'pietermaritzburg', 'durban', '94361', '10456900'], ['limpopo', 'polokwane', 'polokwane', '125754', '5518000'], ['mpumalanga', 'nelspruit', 'nelspruit', '76495', '4128000'], ['north west', 'mahikeng', 'rustenburg', '104882', '3597600'], ['northern cape', 'kimberley', 'kimberley', '372889', '1162900'], ['western cape', 'cape town', 'cape town', '129462', '6016900']] |
fiba eurobasket 2009 squads | https://en.wikipedia.org/wiki/FIBA_EuroBasket_2009_squads | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-23670057-1.html.csv | count | 4 players on fiba eurobasket 2009 squads played the guard position . | {'scope': 'all', 'criterion': 'equal', 'value': 'guard', 'result': '4', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'position', 'guard'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose position record fuzzily matches to guard .', 'tostr': 'filter_eq { all_rows ; position ; guard }'}], 'result': '4', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; position ; guard } }', 'tointer': 'select the rows whose position record fuzzily matches to guard . the number of such rows is 4 .'}, '4'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; position ; guard } } ; 4 } = true', 'tointer': 'select the rows whose position record fuzzily matches to guard . the number of such rows is 4 .'} | eq { count { filter_eq { all_rows ; position ; guard } } ; 4 } = true | select the rows whose position record fuzzily matches to guard . the number of such rows is 4 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'position_5': 5, 'guard_6': 6, '4_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'position_5': 'position', 'guard_6': 'guard', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'position_5': [0], 'guard_6': [0], '4_7': [2]} | ['no', 'player', 'height ( m )', 'height ( f )', 'position', 'year born', 'current club'] | [['4', 'ioannis kalampokis', '1.96', "6 ' 05 ″", 'guard', '1978', 'alba berlin'], ['5', 'ioannis bourousis', '2.13', "7 ' 00 ″", 'center', '1983', 'olimpia milano'], ['6', 'nikolaos zisis', '1.97', "6 ' 06 ″", 'guard', '1983', 'bilbao basket'], ['7', 'vasileios spanoulis', '1.93', "6 ' 04 ″", 'guard', '1982', 'olympiacos'], ['8', 'nicholas calathes', '1.98', "6 ' 06 ″", 'guard', '1989', 'lokomotiv kuban'], ['9', 'antonios fotsis', '2.09', "6 ' 10 ″", 'forward', '1981', 'olimpia milano'], ['10', 'georgios printezis', '2.06', "6 ' 09 ″", 'forward', '1985', 'olympiacos'], ['11', 'andreas glyniadakis', '2.16', "7 ' 01 ″", 'center', '1981', 'astana'], ['12', 'konstantinos kaimakoglou', '2.05', "6 ' 09 ″", 'forward', '1983', 'unics kazan'], ['13', 'konstantinos koufos', '2.13', "7 ' 00 ″", 'forward', '1989', 'denver nuggets'], ['14', 'efstratios perperoglou', '2.03', "6 ' 08 ″", 'forward', '1984', 'olympiacos']] |
hamburg state election , 2004 | https://en.wikipedia.org/wiki/Hamburg_state_election%2C_2004 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1265169-2.html.csv | ordinal | the social democratic party recorded the 2nd highest vote percentage of the 2004 hamburg state election . | {'row': '2', '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', 'vote percentage', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; vote percentage ; 2 }'}, 'party'], 'result': 'social democratic party ( spd )', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; vote percentage ; 2 } ; party }'}, 'social democratic party ( spd )'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; vote percentage ; 2 } ; party } ; social democratic party ( spd ) } = true', 'tointer': 'select the row whose vote percentage record of all rows is 2nd maximum . the party record of this row is social democratic party ( spd ) .'} | eq { hop { nth_argmax { all_rows ; vote percentage ; 2 } ; party } ; social democratic party ( spd ) } = true | select the row whose vote percentage record of all rows is 2nd maximum . the party record of this row is social democratic party ( spd ) . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'vote percentage_5': 5, '2_6': 6, 'party_7': 7, 'social democratic party (spd)_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', 'vote percentage_5': 'vote percentage', '2_6': '2', 'party_7': 'party', 'social democratic party (spd)_8': 'social democratic party ( spd )'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'vote percentage_5': [0], '2_6': [0], 'party_7': [1], 'social democratic party (spd)_8': [2]} | ['party', 'party list votes', 'vote percentage', 'total seats', 'seat percentage'] | [['christian democratic union ( cdu )', '389170', '47.2 % ( + 21.0 )', '63 ( + 30 )', '52.1 %'], ['social democratic party ( spd )', '251441', '30.5 % ( - 6.0 )', '41 ( - 5 )', '33.9 %'], ['green - alternative list ( gal )', '101227', '12.3 % ( + 3.7 )', '17 ( + 6 )', '14.0 %'], ['pro deutsche mitte ( pro dm / schill )', '25763', '3.1 % ( + 2.9 )', '0 ( + 0 )', '0.0 %'], ['free democratic party ( fdp )', '23373', '2.8 % ( - 2.2 )', '0 ( - 6 )', '0.0 %'], ['rainbow - for a new left ( regenbogen )', '9221', '1.1 % ( - 0.6 )', '0 ( + 0 )', '0.0 %'], ['grey panthers party of germany ( graue )', '8862', '1.1 % ( + 0.8 )', '0 ( + 0 )', '0.0 %'], ['law and order offensive party ( offensive )', '3041', '0.4 % ( - 19.1 )', '0 ( - 25 )', '0.0 %'], ['all others', '12030', '1.5 % ( - 0.5 )', '0', '0.0 %'], ['totals', '824128', '100.0 %', '121', '100.0 %']] |
2008 - 09 lega pro seconda divisione | https://en.wikipedia.org/wiki/2008%E2%80%9309_Lega_Pro_Seconda_Divisione | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17702363-3.html.csv | unique | in the 2008-09 lega pro seconda divisione , the only stadium with a capacity of under 2000 was scafati . | {'scope': 'all', 'row': '15', 'col': '4', 'col_other': '2', 'criterion': 'less_than', 'value': '2000', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'capacity', '2000'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose capacity record is less than 2000 .', 'tostr': 'filter_less { all_rows ; capacity ; 2000 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_less { all_rows ; capacity ; 2000 } }', 'tointer': 'select the rows whose capacity record is less than 2000 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'capacity', '2000'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose capacity record is less than 2000 .', 'tostr': 'filter_less { all_rows ; capacity ; 2000 }'}, 'city'], 'result': 'scafati', 'ind': 2, 'tostr': 'hop { filter_less { all_rows ; capacity ; 2000 } ; city }'}, 'scafati'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_less { all_rows ; capacity ; 2000 } ; city } ; scafati }', 'tointer': 'the city record of this unqiue row is scafati .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_less { all_rows ; capacity ; 2000 } } ; eq { hop { filter_less { all_rows ; capacity ; 2000 } ; city } ; scafati } } = true', 'tointer': 'select the rows whose capacity record is less than 2000 . there is only one such row in the table . the city record of this unqiue row is scafati .'} | and { only { filter_less { all_rows ; capacity ; 2000 } } ; eq { hop { filter_less { all_rows ; capacity ; 2000 } ; city } ; scafati } } = true | select the rows whose capacity record is less than 2000 . there is only one such row in the table . the city record of this unqiue row is scafati . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_less_0': 0, 'all_rows_6': 6, 'capacity_7': 7, '2000_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'city_9': 9, 'scafati_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_less_0': 'filter_less', 'all_rows_6': 'all_rows', 'capacity_7': 'capacity', '2000_8': '2000', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'city_9': 'city', 'scafati_10': 'scafati'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_less_0': [1, 2], 'all_rows_6': [0], 'capacity_7': [0], '2000_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'city_9': [2], 'scafati_10': [3]} | ['club', 'city', 'stadium', 'capacity', '200708 season'] | [['as andria bat', 'andria', 'stadio degli ulivi', '10500', '17th in serie c2 / c'], ['sf aversa normanna', 'aversa', 'stadio rinascita', '2000', '1st serie d / h'], ['ss barletta calcio', 'barletta', 'stadio cosimo puttilli', '5000', '2nd serie d / h'], ['ss cassino 1927', 'cassino', 'stadio gino salveti', '3700', '8th in serie c2 / c'], ['fc catanzaro', 'catanzaro', 'stadio nicola ceravolo', '13619', '10th in serie c2 / c'], ['cosenza calcio 1914', 'cosenza', 'stadio san vito', '24000', '1st serie d / i'], ['gela calcio', 'gela', 'stadio vincenzo presti', '4400', '7th in serie c2 / c'], ['fc igea virtus barcellona', 'barcellona pozzo di gotto', "stadio carlo d'alcontres", '5000', '11th in serie c2 / c'], ['ac isola liri', 'isola del liri', 'stadio conte a mangoni', '3400', '1st serie d / g'], ['ss manfredonia calcio', 'manfredonia', 'stadio miramare', '4076', '18th in serie c1 / a'], ['as melfi', 'melfi', 'stadio arturo valerio', '4500', '13th in serie c2 / c'], ['ac monopoli', 'monopoli', 'stadio vito simone veneziani', '6880', '6th in serie c2 / c'], ['as noicattaro calcio', 'noicattaro', 'stadio comunale', '2500', '12th in serie c2 / c'], ['as pescina valle del giovenco', 'avezzano', 'stadio dei marsi', '4500', '2nd in serie c2 / c'], ['ss scafatese calcio 1922', 'scafati', 'stadio comunale', '1950', '16th in serie c2 / c'], ['pol val di sangro', 'atessa', 'stadio montemarcone', '2000', '15th in serie c2 / c'], ['us vibonese calcio', 'vibo valentia', 'stadio luigi razza', '4500', '14th in serie c2 / c'], ['vigor lamezia', 'lamezia terme', "stadio guido d'ippolito", '4000', '4th in serie c2 / c']] |
yorkshire county cricket club in 2008 | https://en.wikipedia.org/wiki/Yorkshire_County_Cricket_Club_in_2008 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-15893020-2.html.csv | superlative | of the players in the yorkshire county cricket club in 2008 , the one with the most runs was adil rashid . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '5', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'runs'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; runs }'}, 'player'], 'result': 'adil rashid', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; runs } ; player }'}, 'adil rashid'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; runs } ; player } ; adil rashid } = true', 'tointer': 'select the row whose runs record of all rows is maximum . the player record of this row is adil rashid .'} | eq { hop { argmax { all_rows ; runs } ; player } ; adil rashid } = true | select the row whose runs record of all rows is maximum . the player record of this row is adil rashid . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'runs_5': 5, 'player_6': 6, 'adil rashid_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'runs_5': 'runs', 'player_6': 'player', 'adil rashid_7': 'adil rashid'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'runs_5': [0], 'player_6': [1], 'adil rashid_7': [2]} | ['player', 'matches', 'overs', 'maidens', 'runs', 'wickets', 'average', 'economy', '5w', '10w', 'best bowling'] | [['ajmal shahzad', '1', '24.0', '6', '64', '3', '21.33', '2.67', '0', '0', '2 / 43'], ['steven patterson', '4', '99.1', '23', '280', '12', '23.33', '2.82', '0', '0', '3 / 19'], ['matthew hoggard', '13', '342.5', '66', '1037', '42', '24.69', '3.02', '1', '0', '6 / 57'], ['tim bresnan', '14', '419.0', '726', '1267', '44', '28.80', '3.02', '1', '0', '5 / 94'], ['adil rashid', '16', '590.1', '64', '1886', '62', '30.42', '3.20', '4', '0', '7 / 107'], ['david wainwright', '4', '85.1', '18', '246', '8', '30.75', '2.89', '0', '0', '3 / 9'], ['anthony mcgrath', '14', '99.1', '16', '282', '9', '31.33', '2.84', '0', '0', '2 / 27'], ['mornã morkel', '1', '15.2', '4', '33', '1', '33.00', '2.15', '0', '0', '1 / 33'], ['rana naved - ul - hasan', '7', '153.1', '21', '604', '16', '37.75', '3.94', '0', '0', '4 / 86'], ['deon kruis', '10', '295.3', '68', '903', '22', '41.05', '3.06', '1', '0', '5 / 47'], ['darren gough', '8', '149.0', '25', '528', '9', '58.67', '3.54', '0', '0', '2 / 34'], ['jacques rudolph', '16', '21.2', '2', '74', '1', '74.00', '3.47', '0', '0', '1 / 13'], ['adam lyth', '14', '30.1', '5', '105', '1', '105.00', '3.48', '0', '0', '1 / 20'], ['oliver hannon - dalby', '1', '29.0', '5', '114', '1', '114.00', '3.93', '0', '0', '1 / 58'], ['ben sanderson', '2', '37.0', '7', '140', '1', '140.00', '3.78', '0', '0', '1 / 87'], ['richard pyrah', '5', '56.0', '11', '201', '1', '201.00', '3.59', '0', '0', '1 / 14'], ['andrew gale', '15', '1.0', '0', '3', '0', 'n / a', '3.00', '0', '0', '0 / 3'], ['michael vaughan', '6', '6.0', '0', '47', '0', 'n / a', '7.83', '0', '0', '0 / 47']] |
casey martin | https://en.wikipedia.org/wiki/Casey_Martin | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1697190-2.html.csv | comparative | casey martin played more pga tournaments in 2002 than he did in 2003 . | {'row_1': '4', 'row_2': '5', 'col': '2', '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', 'year', '2002'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose year record fuzzily matches to 2002 .', 'tostr': 'filter_eq { all_rows ; year ; 2002 }'}, 'tournaments played'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; year ; 2002 } ; tournaments played }', 'tointer': 'select the rows whose year record fuzzily matches to 2002 . take the tournaments played record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'year', '2003'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose year record fuzzily matches to 2003 .', 'tostr': 'filter_eq { all_rows ; year ; 2003 }'}, 'tournaments played'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; year ; 2003 } ; tournaments played }', 'tointer': 'select the rows whose year record fuzzily matches to 2003 . take the tournaments played record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; year ; 2002 } ; tournaments played } ; hop { filter_eq { all_rows ; year ; 2003 } ; tournaments played } } = true', 'tointer': 'select the rows whose year record fuzzily matches to 2002 . take the tournaments played record of this row . select the rows whose year record fuzzily matches to 2003 . take the tournaments played record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; year ; 2002 } ; tournaments played } ; hop { filter_eq { all_rows ; year ; 2003 } ; tournaments played } } = true | select the rows whose year record fuzzily matches to 2002 . take the tournaments played record of this row . select the rows whose year record fuzzily matches to 2003 . take the tournaments played 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, 'year_7': 7, '2002_8': 8, 'tournaments played_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'year_11': 11, '2003_12': 12, 'tournaments played_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', 'year_7': 'year', '2002_8': '2002', 'tournaments played_9': 'tournaments played', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'year_11': 'year', '2003_12': '2003', 'tournaments played_13': 'tournaments played'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'year_7': [0], '2002_8': [0], 'tournaments played_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'year_11': [1], '2003_12': [1], 'tournaments played_13': [3]} | ['year', 'tournaments played', 'cuts made', 'wins', 'best finish', 'earnings', 'money list rank'] | [['1998', '3', '2', '0', 't - 23', '37221', '221'], ['2000', '29', '14', '0', 't - 17', '143248', '179'], ['2001', '2', '0', '0', 'cut', '0', 'n / a'], ['2002', '3', '0', '0', 'cut', '0', 'n / a'], ['2003', '1', '0', '0', 'cut', '0', 'n / a'], ['2004', '2', '2', '0', 't - 69', '15858', 'n / a'], ['2005', '1', '1', '0', 't - 65', '10547', 'n / a']] |
satpura thermal power station | https://en.wikipedia.org/wiki/Satpura_Thermal_Power_Station | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-28672269-1.html.csv | aggregation | the average installed capacity of units at the satpura thermal power station is 116.56 mw . | {'scope': 'all', 'col': '3', 'type': 'average', 'result': '116.56', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'installed capacity ( mw )'], 'result': '116.56', 'ind': 0, 'tostr': 'avg { all_rows ; installed capacity ( mw ) }'}, '116.56'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; installed capacity ( mw ) } ; 116.56 } = true', 'tointer': 'the average of the installed capacity ( mw ) record of all rows is 116.56 .'} | round_eq { avg { all_rows ; installed capacity ( mw ) } ; 116.56 } = true | the average of the installed capacity ( mw ) record of all rows is 116.56 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'installed capacity ( mw )_4': 4, '116.56_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'installed capacity ( mw )_4': 'installed capacity ( mw )', '116.56_5': '116.56'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'installed capacity ( mw )_4': [0], '116.56_5': [1]} | ['stage', 'unit number', 'installed capacity ( mw )', 'date of commissioning', 'status', 'tg set provider', 'boiler provider'] | [['first', '1', '62.5', 'october , 1967', 'running', 'ge , usa', 'the babcock & wilcox company ( b & w ) , usa'], ['first', '2', '62.5', 'march , 1968', 'running', 'ge , usa', 'the babcock & wilcox company ( b & w ) , usa'], ['first', '3', '62.5', 'may , 1968', 'running', 'ge , usa', 'the babcock & wilcox company ( b & w ) , usa'], ['first', '4', '62.5', 'july , 1968', 'running', 'ge , usa', 'the babcock & wilcox company ( b & w ) , usa'], ['first', '5', '62.5', 'april , 1970', 'running', 'ge , usa', 'the babcock & wilcox company ( b & w ) , usa'], ['second', '6', '200', 'july , 1979', 'running', 'bhel , india', 'bhel , india'], ['second', '7', '210', 'september , 1980', 'running', 'bhel , india', 'bhel , india'], ['second', '8', '210', 'january , 1983', 'running', 'bhel , india', 'bhel , india']] |
1994 - 95 philadelphia flyers season | https://en.wikipedia.org/wiki/1994%E2%80%9395_Philadelphia_Flyers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14022127-5.html.csv | superlative | the philadelphia flyers on april 22 had the highest attendance of all game during the 1994 - 95 season . | {'scope': 'all', 'col_superlative': '6', 'row_superlative': '10', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'attendance'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; attendance }'}, 'date'], 'result': 'april 22', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; attendance } ; date }'}, 'april 22'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; attendance } ; date } ; april 22 } = true', 'tointer': 'select the row whose attendance record of all rows is maximum . the date record of this row is april 22 .'} | eq { hop { argmax { all_rows ; attendance } ; date } ; april 22 } = true | select the row whose attendance record of all rows is maximum . the date record of this row is april 22 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'attendance_5': 5, 'date_6': 6, 'april 22_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'attendance_5': 'attendance', 'date_6': 'date', 'april 22_7': 'april 22'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'attendance_5': [0], 'date_6': [1], 'april 22_7': [2]} | ['date', 'visitor', 'score', 'home', 'decision', 'attendance', 'record'] | [['april 1', 'philadelphia', '2 - 3', 'pittsburgh', 'hextall', '17181', '17 - 13 - 4'], ['april 2', 'ny rangers', '2 - 4', 'philadelphia', 'hextall', '17380', '18 - 13 - 4'], ['april 6', 'tampa bay', '4 - 5', 'philadelphia', 'hextall', '17245', '19 - 13 - 4'], ['april 8', 'philadelphia', '3 - 1', 'washington', 'hextall', '18130', '20 - 13 - 4'], ['april 12', 'montreal', '2 - 3', 'philadelphia', 'hextall', '17380', '21 - 13 - 4'], ['april 14', 'tampa bay', '2 - 3', 'philadelphia', 'roussel', '17380', '22 - 13 - 4'], ['april 16', 'pittsburgh', '3 - 4', 'philadelphia', 'hextall', '17380', '23 - 13 - 4'], ['april 18', 'philadelphia', '3 - 1', 'florida', 'hextall', '14703', '24 - 13 - 4'], ['april 20', 'ny islanders', '1 - 2', 'philadelphia', 'hextall', '17380', '25 - 13 - 4'], ['april 22', 'philadelphia', '4 - 3', 'new jersey', 'roussel', '19040', '26 - 13 - 4'], ['april 23', 'philadelphia', '2 - 4', 'buffalo', 'hextall', '16230', '26 - 14 - 4'], ['april 26', 'ottawa', '5 - 2', 'philadelphia', 'hextall', '17380', '26 - 15 - 4'], ['april 28', 'philadelphia', '4 - 3', 'hartford', 'hextall', '15550', '27 - 15 - 4'], ['april 30', 'ny rangers', '2 - 0', 'philadelphia', 'roussel', '17380', '27 - 16 - 4']] |
1968 cleveland browns season | https://en.wikipedia.org/wiki/1968_Cleveland_Browns_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10652150-2.html.csv | count | a total of two games resulted in wins for the browns in the 1968 cleveland browns season . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'w', 'result': '2', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'result', 'w'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose result record fuzzily matches to w .', 'tostr': 'filter_eq { all_rows ; result ; w }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; result ; w } }', 'tointer': 'select the rows whose result record fuzzily matches to w . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; result ; w } } ; 2 } = true', 'tointer': 'select the rows whose result record fuzzily matches to w . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; result ; w } } ; 2 } = true | select the rows whose result record fuzzily matches to w . the number of such rows is 2 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'result_5': 5, 'w_6': 6, '2_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'result_5': 'result', 'w_6': 'w', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'result_5': [0], 'w_6': [0], '2_7': [2]} | ['week', 'date', 'opponent', 'result', 'attendance'] | [['1', 'august 9 , 1968', 'los angeles rams', 'l 23 - 21', '64020'], ['2', 'august 18 , 1968', 'san francisco 49ers', 'w 31 - 17', '26801'], ['3', 'august 24 , 1968', 'new orleans saints', 'l 40 - 27', '70045'], ['4', 'august 30 , 1968', 'buffalo bills', 'w 22 - 12', '45448'], ['5', 'september 7 , 1968', 'green bay packers', 'l 31 - 9', '84918']] |
2002 senior pga tour | https://en.wikipedia.org/wiki/2002_Senior_PGA_Tour | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11603116-4.html.csv | comparative | gil morgan had more wins in the 2002 senior pga tour than dave stockton did . | {'row_1': '2', 'row_2': '4', 'col': '5', 'col_other': '2', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', 'gil morgan'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose player record fuzzily matches to gil morgan .', 'tostr': 'filter_eq { all_rows ; player ; gil morgan }'}, 'wins'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; player ; gil morgan } ; wins }', 'tointer': 'select the rows whose player record fuzzily matches to gil morgan . take the wins record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', 'dave stockton'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose player record fuzzily matches to dave stockton .', 'tostr': 'filter_eq { all_rows ; player ; dave stockton }'}, 'wins'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; player ; dave stockton } ; wins }', 'tointer': 'select the rows whose player record fuzzily matches to dave stockton . take the wins record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; player ; gil morgan } ; wins } ; hop { filter_eq { all_rows ; player ; dave stockton } ; wins } } = true', 'tointer': 'select the rows whose player record fuzzily matches to gil morgan . take the wins record of this row . select the rows whose player record fuzzily matches to dave stockton . take the wins record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; player ; gil morgan } ; wins } ; hop { filter_eq { all_rows ; player ; dave stockton } ; wins } } = true | select the rows whose player record fuzzily matches to gil morgan . take the wins record of this row . select the rows whose player record fuzzily matches to dave stockton . take the wins record of this row . the first record is greater than the second record . | 5 | 5 | {'greater_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'player_7': 7, 'gil morgan_8': 8, 'wins_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'player_11': 11, 'dave stockton_12': 12, 'wins_13': 13} | {'greater_4': 'greater', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'player_7': 'player', 'gil morgan_8': 'gil morgan', 'wins_9': 'wins', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'player_11': 'player', 'dave stockton_12': 'dave stockton', 'wins_13': 'wins'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'player_7': [0], 'gil morgan_8': [0], 'wins_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'player_11': [1], 'dave stockton_12': [1], 'wins_13': [3]} | ['rank', 'player', 'country', 'earnings', 'wins'] | [['1', 'hale irwin', 'united states', '16950178', '36'], ['2', 'gil morgan', 'united states', '11092593', '21'], ['3', 'jim colbert', 'united states', '10840374', '20'], ['4', 'dave stockton', 'united states', '9735814', '14'], ['5', 'lee trevino', 'united states', '9616404', '29']] |
2006 latvian first league | https://en.wikipedia.org/wiki/2006_Latvian_First_League | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18017936-2.html.csv | superlative | the abuls smiltene team had the highest number of goals against in the 2006 latvian first league . | {'scope': 'all', 'col_superlative': '8', 'row_superlative': '16', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '2', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'goals against'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; goals against }'}, 'club'], 'result': 'abuls smiltene', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; goals against } ; club }'}, 'abuls smiltene'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; goals against } ; club } ; abuls smiltene } = true', 'tointer': 'select the row whose goals against record of all rows is maximum . the club record of this row is abuls smiltene .'} | eq { hop { argmax { all_rows ; goals against } ; club } ; abuls smiltene } = true | select the row whose goals against record of all rows is maximum . the club record of this row is abuls smiltene . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'goals against_5': 5, 'club_6': 6, 'abuls smiltene_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'goals against_5': 'goals against', 'club_6': 'club', 'abuls smiltene_7': 'abuls smiltene'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'goals against_5': [0], 'club_6': [1], 'abuls smiltene_7': [2]} | ['position', 'club', 'played', 'wins', 'draws', 'losses', 'goals for', 'goals against', 'points', 'goal difference'] | [['1', 'jfk olimps r카ga', '30', '26', '2', '2', '111', '15', '80', '+ 96'], ['2', 'fc ditton - 2 daugavpils', '30', '21', '7', '2', '88', '24', '70', '+ 64'], ['3', 'skonto - 2 riga', '30', '20', '5', '5', '78', '23', '65', '+ 55'], ['4', 'ventspils - 2', '30', '20', '4', '6', '108', '25', '64', '+ 83'], ['5', 'r카ga - 2', '30', '17', '3', '10', '74', '44', '54', '+ 30'], ['6', 'dinaburg - zemessardze daugavpils', '30', '16', '3', '17', '60', '51', '51', '+ 9'], ['7', 'fk valmiera', '30', '13', '7', '10', '50', '53', '46', '- 3'], ['8', 'liepajas metalurgs - 2', '30', '13', '6', '11', '68', '47', '45', '+ 21'], ['9', 'fk jelgava', '30', '12', '6', '12', '53', '49', '42', '+ 4'], ['10', 'eirobaltija riga', '30', '11', '7', '12', '50', '40', '40', '+ 10'], ['11', 'j큰rmala - 2', '30', '10', '5', '15', '86', '74', '35', '+ 12'], ['12', 'tranz카ts ventspils', '30', '8', '4', '18', '37', '88', '28', '- 51'], ['13', 'multibanka riga', '30', '7', '6', '17', '34', '58', '27', '- 24'], ['14', 'fk auda kekava', '30', '5', '2', '23', '28', '79', '17', '- 51'], ['15', 'alberts riga', '30', '4', '4', '22', '32', '114', '16', '- 82'], ['16', 'abuls smiltene', '30', '1', '1', '28', '18', '191', '4', '- 173']] |
2007 - 08 uleb cup | https://en.wikipedia.org/wiki/2007%E2%80%9308_ULEB_Cup | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13570080-12.html.csv | superlative | the team elan chalon scored the most points in the 1st leg of the 2007 - 08 uleb cup . | {'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', '1st leg'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; 1st leg }'}, 'team 1'], 'result': 'elan chalon', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; 1st leg } ; team 1 }'}, 'elan chalon'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; 1st leg } ; team 1 } ; elan chalon } = true', 'tointer': 'select the row whose 1st leg record of all rows is maximum . the team 1 record of this row is elan chalon .'} | eq { hop { argmax { all_rows ; 1st leg } ; team 1 } ; elan chalon } = true | select the row whose 1st leg record of all rows is maximum . the team 1 record of this row is elan chalon . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, '1st leg_5': 5, 'team 1_6': 6, 'elan chalon_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', '1st leg_5': '1st leg', 'team 1_6': 'team 1', 'elan chalon_7': 'elan chalon'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], '1st leg_5': [0], 'team 1_6': [1], 'elan chalon_7': [2]} | ['team 1', 'agg', 'team 2', '1st leg', '2nd leg'] | [['asco śląsk wrocław', '161 - 177', 'dynamo moscow', '78 - 85', '83 - 92'], ['lukoil academic', '140 - 119', 'bk ventspils', '67 - 64', '73 - 55'], ['telindus bc oostende', '121 - 133', 'bc kyiv', '61 - 65', '60 - 68'], ['cez nymburk', '127 - 129', 'pge turów zgorzelec', '61 - 61', '66 - 68'], ['elan chalon', '150 - 163', 'akasvayu girona', '93 - 85', '57 - 78'], ['hemofarm', '155 - 134', 'budućnost podgorica', '82 - 56', '73 - 78'], ['unics kazan', '184 - 161', 'türk telekom', '91 - 65', '93 - 96'], ['artland dragons', '161 - 157', 'triumph lyubertsy', '81 - 75', '80 - 82'], ['allianz swans gmunden', '115 - 166', 'dkv joventut', '59 - 89', '56 - 77'], ['köln 99ers', '141 - 187', 'khimki', '72 - 91', '69 - 96'], ['azovmash mariupol', '142 - 157', 'zadar', '82 - 80', '60 - 77'], ['panionios forthnet', '131 - 141', 'pamesa valencia', '70 - 59', '61 - 82'], ['hapoel jerusalem', '141 - 146', 'beşiktaş cola turka', '88 - 73', '53 - 73'], ['red star belgrade', '164 - 153', 'benetton treviso', '81 - 71', '83 - 82'], ['adecco asvel villeurbanne', '144 - 145', 'galatasaray cafe crown', '69 - 69', '75 - 76'], ['kk bosna', '158 - 171', 'gran canaria', '89 - 82', '69 - 89']] |
südtirol | https://en.wikipedia.org/wiki/Politics_of_Trentino-Alto_Adige/S%C3%BCdtirol | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17305625-1.html.csv | superlative | the trento municipality has the most inhabitants in the südtirol region . | {'scope': 'all', 'col_superlative': '2', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'inhabitants'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; inhabitants }'}, 'municipality'], 'result': 'trento', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; inhabitants } ; municipality }'}, 'trento'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; inhabitants } ; municipality } ; trento } = true', 'tointer': 'select the row whose inhabitants record of all rows is maximum . the municipality record of this row is trento .'} | eq { hop { argmax { all_rows ; inhabitants } ; municipality } ; trento } = true | select the row whose inhabitants record of all rows is maximum . the municipality record of this row is trento . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'inhabitants_5': 5, 'municipality_6': 6, 'trento_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'inhabitants_5': 'inhabitants', 'municipality_6': 'municipality', 'trento_7': 'trento'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'inhabitants_5': [0], 'municipality_6': [1], 'trento_7': [2]} | ['municipality', 'inhabitants', 'mayor', 'party', 'election'] | [['trento', '116298', 'alessandro andreatta', 'democratic party', '2009'], ['rovereto', '38167', 'andrea miorandi', 'democratic party', '2010'], ['pergine valsugana', '20582', 'silvano corradi', 'union for trentino', '2009'], ['arco', '16901', 'paolo mattei', 'democratic party', '2010'], ['riva del garda', '16170', 'adalberto mosaner', 'democratic party', '2010']] |
list of australian football league team songs | https://en.wikipedia.org/wiki/List_of_Australian_Football_League_team_songs | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-28243323-1.html.csv | majority | most of the team songs of the australian football league were first used in the 20th . century . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'less_than', 'value': '2000', 'subset': None} | {'func': 'most_less', 'args': ['all_rows', 'first used as team song', '2000'], 'result': True, 'ind': 0, 'tointer': 'for the first used as team song records of all rows , most of them are less than 2000 .', 'tostr': 'most_less { all_rows ; first used as team song ; 2000 } = true'} | most_less { all_rows ; first used as team song ; 2000 } = true | for the first used as team song records of all rows , most of them are less than 2000 . | 1 | 1 | {'most_less_0': 0, 'result_1': 1, 'all_rows_2': 2, 'first used as team song_3': 3, '2000_4': 4} | {'most_less_0': 'most_less', 'result_1': 'true', 'all_rows_2': 'all_rows', 'first used as team song_3': 'first used as team song', '2000_4': '2000'} | {'most_less_0': [1], 'result_1': [], 'all_rows_2': [0], 'first used as team song_3': [0], '2000_4': [0]} | ['club name', 'name of team song', 'basis for team song', 'first used as team song', 'writer / composer'] | [['adelaide', 'the pride of south australia', "us marines ' hymn", '1992', 'bill sanders'], ['brisbane lions', 'the pride of brisbane town', 'la marseillaise', '1955', 'fitzroy players'], ['carlton', 'we are the navy blues', 'lily of laguna', 'c 1930', 'carlton players'], ['collingwood', 'good old collingwood forever', 'goodbye , dolly gray', '1906', 'tom nelson'], ['essendon', 'see the bombers fly up', '( keep your ) sunny side up', '1960s', 'unknown'], ['fremantle', 'freo way to go', 'original', '1995', 'ken walther'], ['geelong', 'we are geelong', 'the toreador song', '1963', 'john k watts'], ['gold coast', 'we are the suns of the gold coast sky', 'original', '2010', 'rosco elliott'], ['greater western sydney', "there 's a big big sound", 'original', '2012', 'harry angus'], ['hawthorn', 'the mighty fighting hawks', 'the yankee doodle boy', 'c 1956', 'chick lander'], ['melbourne', "it 's a grand old flag", "you 're a grand old flag", 'c 1912', 'unknown ( second verse by keith bluey truscott )'], ['north melbourne', 'join in the chorus', 'wee deoch an doris', '1920s', 'unknown'], ['port adelaide', 'power to win', 'original', '1997', 'quentin eyers and les kaczmarek'], ['richmond', "we 're from tiger land", 'row , row , row', '1962', 'jack malcolmson'], ['st kilda', 'when the saints go marching in', 'when the saints go marching in', 'c 1965', 'unknown'], ['sydney', 'the red and the white', 'notre dame victory march', '1950s', 'larry spokes'], ['west coast', "we 're flying high", 'original', '1987', 'kevin peek and ken walther']] |
german submarine u - 402 | https://en.wikipedia.org/wiki/German_submarine_U-402 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18668500-1.html.csv | count | nine of the german submarines u-402 that were sunk during a raid were from great britain . | {'scope': 'subset', 'criterion': 'equal', 'value': 'great britain', 'result': '9', 'col': '3', 'subset': {'col': '5', 'criterion': 'equal', 'value': 'sunk'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'fate', 'sunk'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; fate ; sunk }', 'tointer': 'select the rows whose fate record fuzzily matches to sunk .'}, 'nationality', 'great britain'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose fate record fuzzily matches to sunk . among these rows , select the rows whose nationality record fuzzily matches to great britain .', 'tostr': 'filter_eq { filter_eq { all_rows ; fate ; sunk } ; nationality ; great britain }'}], 'result': '9', 'ind': 2, 'tostr': 'count { filter_eq { filter_eq { all_rows ; fate ; sunk } ; nationality ; great britain } }', 'tointer': 'select the rows whose fate record fuzzily matches to sunk . among these rows , select the rows whose nationality record fuzzily matches to great britain . the number of such rows is 9 .'}, '9'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_eq { filter_eq { all_rows ; fate ; sunk } ; nationality ; great britain } } ; 9 } = true', 'tointer': 'select the rows whose fate record fuzzily matches to sunk . among these rows , select the rows whose nationality record fuzzily matches to great britain . the number of such rows is 9 .'} | eq { count { filter_eq { filter_eq { all_rows ; fate ; sunk } ; nationality ; great britain } } ; 9 } = true | select the rows whose fate record fuzzily matches to sunk . among these rows , select the rows whose nationality record fuzzily matches to great britain . the number of such rows is 9 . | 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, 'fate_6': 6, 'sunk_7': 7, 'nationality_8': 8, 'great britain_9': 9, '9_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', 'fate_6': 'fate', 'sunk_7': 'sunk', 'nationality_8': 'nationality', 'great britain_9': 'great britain', '9_10': '9'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_str_eq_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'fate_6': [0], 'sunk_7': [0], 'nationality_8': [1], 'great britain_9': [1], '9_10': [3]} | ['date', 'ship', 'nationality', 'tonnage', 'fate'] | [['16 may 1941', 'llangibby castle', 'great britain', '11951', 'damaged'], ['13 april 1942', 'empire progress', 'great britain', '5249', 'sunk'], ['30 april 1942', 'ashkhabad', 'soviet union', '5284', 'sunk'], ['2 may 1942', 'uss cythera', 'usa', '602', 'sunk'], ['2 november 1942', 'dalcroy', 'great britain', '4558', 'sunk'], ['2 november 1942', 'empire antelope', 'great britain', '4945', 'sunk'], ['2 november 1942', 'empire leopard', 'great britain', '5676', 'sunk'], ['2 november 1942', 'empire sunrise', 'great britain', '7459', 'damaged'], ['2 november 1942', 'rinos', 'greece', '4649', 'sunk'], ['7 february 1942', 'afrika', 'great britain', '8597', 'sunk'], ['7 february 1942', 'daghild', 'norway', '9272', 'damaged'], ['7 february 1942', 'henry r mallory', 'usa', '6063', 'sunk'], ['7 february 1942', 'kalliopi', 'greece', '4695', 'sunk'], ['7 february 1942', 'robert e hopkins', 'great britain', '6625', 'sunk'], ['7 february 1942', 'toward', 'great britain', '1571', 'sunk'], ['8 february 1942', 'newton ash', 'great britain', '1571', 'sunk'], ['11 may 1943', 'antigone', 'great britain', '4545', 'sunk'], ['11 may 1943', 'grado', 'norway', '3082', 'sunk']] |
australian region tropical cyclone climatology | https://en.wikipedia.org/wiki/Australian_region_tropical_cyclone_climatology | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14617522-3.html.csv | majority | the majority of seasons had more than 10 tropical lows in the australian region . | {'scope': 'all', 'col': '2', 'most_or_all': 'most', 'criterion': 'greater_than', 'value': '10', 'subset': None} | {'func': 'most_greater', 'args': ['all_rows', 'tropical lows', '10'], 'result': True, 'ind': 0, 'tointer': 'for the tropical lows records of all rows , most of them are greater than 10 .', 'tostr': 'most_greater { all_rows ; tropical lows ; 10 } = true'} | most_greater { all_rows ; tropical lows ; 10 } = true | for the tropical lows records of all rows , most of them are greater than 10 . | 1 | 1 | {'most_greater_0': 0, 'result_1': 1, 'all_rows_2': 2, 'tropical lows_3': 3, '10_4': 4} | {'most_greater_0': 'most_greater', 'result_1': 'true', 'all_rows_2': 'all_rows', 'tropical lows_3': 'tropical lows', '10_4': '10'} | {'most_greater_0': [1], 'result_1': [], 'all_rows_2': [0], 'tropical lows_3': [0], '10_4': [0]} | ['season', 'tropical lows', 'tropical cyclones', 'severe tropical cyclones', 'strongest storm'] | [['1990 - 91', '10', '10', '7', 'marian'], ['1991 - 92', '11', '10', '9', 'jane - irna'], ['1992 - 93', '6', '3', '1', 'oliver'], ['1993 - 94', '12', '11', '7', 'theodore'], ['1994 - 95', '19', '9', '6', 'chloe'], ['1995 - 96', '19', '14', '9', 'olivia'], ['1996 - 97', '15', '14', '3', 'pancho'], ['1997 - 98', '10', '9', '3', 'tiffany'], ['1998 - 99', '21', '14', '9', 'gwenda'], ['1999 - 00', '13', '12', '5', 'john / paul']] |
united states house of representatives elections , 1940 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1940 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1342270-43.html.csv | unique | clyde l garrett was the only incumbent whose result was ' lost renomination democratic hold ' . | {'scope': 'all', 'row': '15', 'col': '5', 'col_other': '2', 'criterion': 'equal', 'value': 'lost renomination democratic hold', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'result', 'lost renomination democratic hold'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose result record fuzzily matches to lost renomination democratic hold .', 'tostr': 'filter_eq { all_rows ; result ; lost renomination democratic hold }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; result ; lost renomination democratic hold } }', 'tointer': 'select the rows whose result record fuzzily matches to lost renomination democratic hold . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'result', 'lost renomination democratic hold'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose result record fuzzily matches to lost renomination democratic hold .', 'tostr': 'filter_eq { all_rows ; result ; lost renomination democratic hold }'}, 'incumbent'], 'result': 'clyde l garrett', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; result ; lost renomination democratic hold } ; incumbent }'}, 'clyde l garrett'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; result ; lost renomination democratic hold } ; incumbent } ; clyde l garrett }', 'tointer': 'the incumbent record of this unqiue row is clyde l garrett .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; result ; lost renomination democratic hold } } ; eq { hop { filter_eq { all_rows ; result ; lost renomination democratic hold } ; incumbent } ; clyde l garrett } } = true', 'tointer': 'select the rows whose result record fuzzily matches to lost renomination democratic hold . there is only one such row in the table . the incumbent record of this unqiue row is clyde l garrett .'} | and { only { filter_eq { all_rows ; result ; lost renomination democratic hold } } ; eq { hop { filter_eq { all_rows ; result ; lost renomination democratic hold } ; incumbent } ; clyde l garrett } } = true | select the rows whose result record fuzzily matches to lost renomination democratic hold . there is only one such row in the table . the incumbent record of this unqiue row is clyde l garrett . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'result_7': 7, 'lost renomination democratic hold_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'incumbent_9': 9, 'clyde l garrett_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'result_7': 'result', 'lost renomination democratic hold_8': 'lost renomination democratic hold', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'incumbent_9': 'incumbent', 'clyde l garrett_10': 'clyde l garrett'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'result_7': [0], 'lost renomination democratic hold_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'incumbent_9': [2], 'clyde l garrett_10': [3]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['texas 1', 'wright patman', 'democratic', '1928', 're - elected', 'wright patman ( d ) unopposed'], ['texas 2', 'martin dies , jr', 'democratic', '1930', 're - elected', 'martin dies , jr ( d ) unopposed'], ['texas 3', 'lindley beckworth', 'democratic', '1938', 're - elected', 'lindley beckworth ( d ) unopposed'], ['texas 4', 'sam rayburn', 'democratic', '1912', 're - elected', 'sam rayburn ( d ) unopposed'], ['texas 6', 'luther a johnson', 'democratic', '1922', 're - elected', 'luther a johnson ( d ) unopposed'], ['texas 7', 'nat patton', 'democratic', '1934', 're - elected', 'nat patton ( d ) 98.2 % dudley lawson ( r ) 1.8 %'], ['texas 9', 'joseph j mansfield', 'democratic', '1916', 're - elected', 'joseph j mansfield ( d ) unopposed'], ['texas 10', 'lyndon b johnson', 'democratic', '1937', 're - elected', 'lyndon b johnson ( d ) unopposed'], ['texas 11', 'william r poage', 'democratic', '1936', 're - elected', 'william r poage ( d ) unopposed'], ['texas 12', 'fritz g lanham', 'democratic', '1919', 're - elected', 'fritz g lanham ( d ) unopposed'], ['texas 13', 'ed gossett', 'democratic', '1938', 're - elected', 'ed gossett ( d ) 96.4 % louis n gould ( r ) 3.6 %'], ['texas 14', 'richard m kleberg', 'democratic', '1931', 're - elected', 'richard m kleberg ( d ) unopposed'], ['texas 15', 'milton h west', 'democratic', '1933', 're - elected', 'milton h west ( d ) 92.4 % j a simpson ( r ) 7.6 %'], ['texas 16', 'r ewing thomason', 'democratic', '1930', 're - elected', 'r ewing thomason ( d ) unopposed'], ['texas 17', 'clyde l garrett', 'democratic', '1936', 'lost renomination democratic hold', 'sam m russell ( d ) unopposed'], ['texas 19', 'george h mahon', 'democratic', '1934', 're - elected', 'george h mahon ( d ) unopposed']] |
tokyo indoor | https://en.wikipedia.org/wiki/Tokyo_Indoor | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17660329-1.html.csv | comparative | jimmy connors won the seiko world super tennis earlier than john mcenroe did . | {'row_1': '3', 'row_2': '5', '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', 'champions', 'jimmy connors'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose champions record fuzzily matches to jimmy connors .', 'tostr': 'filter_eq { all_rows ; champions ; jimmy connors }'}, 'year'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; champions ; jimmy connors } ; year }', 'tointer': 'select the rows whose champions record fuzzily matches to jimmy connors . take the year record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'champions', 'john mcenroe'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose champions record fuzzily matches to john mcenroe .', 'tostr': 'filter_eq { all_rows ; champions ; john mcenroe }'}, 'year'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; champions ; john mcenroe } ; year }', 'tointer': 'select the rows whose champions record fuzzily matches to john mcenroe . take the year record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; champions ; jimmy connors } ; year } ; hop { filter_eq { all_rows ; champions ; john mcenroe } ; year } } = true', 'tointer': 'select the rows whose champions record fuzzily matches to jimmy connors . take the year record of this row . select the rows whose champions record fuzzily matches to john mcenroe . take the year record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; champions ; jimmy connors } ; year } ; hop { filter_eq { all_rows ; champions ; john mcenroe } ; year } } = true | select the rows whose champions record fuzzily matches to jimmy connors . take the year record of this row . select the rows whose champions record fuzzily matches to john mcenroe . take the year record of this row . the first record is less than the second record . | 5 | 5 | {'less_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'champions_7': 7, 'jimmy connors_8': 8, 'year_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'champions_11': 11, 'john mcenroe_12': 12, 'year_13': 13} | {'less_4': 'less', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'champions_7': 'champions', 'jimmy connors_8': 'jimmy connors', 'year_9': 'year', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'champions_11': 'champions', 'john mcenroe_12': 'john mcenroe', 'year_13': 'year'} | {'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'champions_7': [0], 'jimmy connors_8': [0], 'year_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'champions_11': [1], 'john mcenroe_12': [1], 'year_13': [3]} | ['year', 'name of tournament', 'champions', 'runners - up', 'score'] | [['1978', 'seiko world super tennis', 'björn borg', 'brian teacher', '6 - 3 , 6 - 4'], ['1979', 'seiko world super tennis', 'björn borg', 'jimmy connors', '6 - 2 , 6 - 2'], ['1980', 'seiko world super tennis', 'jimmy connors', 'tom gullikson', '6 - 1 , 6 - 2'], ['1981', 'seiko world super tennis', 'vincent van patten', 'mark edmondson', '6 - 2 , 3 - 6 , 6 - 3'], ['1982', 'seiko world super tennis', 'john mcenroe', 'peter mcnamara', '7 - 6 , 7 - 5'], ['1983', 'seiko world super tennis', 'ivan lendl', 'scott davis', '3 - 6 , 6 - 3 , 6 - 4'], ['1984', 'seiko super tennis', 'jimmy connors', 'ivan lendl', '6 - 4 , 3 - 6 , 6 - 0'], ['1985', 'seiko super tennis', 'ivan lendl', 'mats wilander', '6 - 0 , 6 - 4'], ['1986', 'seiko super tennis', 'boris becker', 'stefan edberg', '7 - 6 , 6 - 1'], ['1987', 'seiko super tennis', 'stefan edberg', 'ivan lendl', '6 - 7 , 6 - 4 , 6 - 4'], ['1988', 'seiko super tennis', 'boris becker', 'john fitzgerald', '7 - 6 , 6 - 4'], ['1989', 'seiko super tennis', 'aaron krickstein', 'carl - uwe steeb', '6 - 2 , 6 - 2'], ['1990', 'seiko super tennis', 'ivan lendl', 'boris becker', '4 - 6 , 6 - 3 , 7 - 6'], ['1991', 'seiko super tennis', 'stefan edberg', 'derrick rostagno', '6 - 3 , 1 - 6 , 6 - 2'], ['1992', 'seiko super tennis', 'ivan lendl', 'henrik holm', '7 - 6 , 6 - 4'], ['1993', 'seiko super tennis', 'ivan lendl', 'todd martin', '6 - 4 , 6 - 4'], ['1994', 'seiko super tennis', 'goran ivanišević', 'michael chang', '6 - 4 , 6 - 4'], ['1995', 'seiko super tennis', 'michael chang', 'mark philippoussis', '6 - 3 , 6 - 4']] |
districts of peru | https://en.wikipedia.org/wiki/Districts_of_Peru | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2251578-4.html.csv | aggregation | the median elevation of the 19 highest districts of peru is 4390 meters . | {'scope': 'all', 'col': '6', 'type': 'average', 'result': '4390', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'elevation ( m )'], 'result': '4390', 'ind': 0, 'tostr': 'avg { all_rows ; elevation ( m ) }'}, '4390'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; elevation ( m ) } ; 4390 } = true', 'tointer': 'the average of the elevation ( m ) record of all rows is 4390 .'} | round_eq { avg { all_rows ; elevation ( m ) } ; 4390 } = true | the average of the elevation ( m ) record of all rows is 4390 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'elevation (m)_4': 4, '4390_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'elevation (m)_4': 'elevation ( m )', '4390_5': '4390'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'elevation (m)_4': [0], '4390_5': [1]} | ['', 'district', 'province', 'region', 'ubigeo', 'elevation ( m )'] | [['1', 'suykutambo', 'espinar', 'cusco', '80807', '4801'], ['2', 'condoroma', 'espinar', 'cusco', '80802', '4737'], ['3', 'san antonio', 'puno', 'puno', '210113', '4700'], ['4', 'ananea', 'san antonio de putina', 'puno', '211002', '4660'], ['5', 'morococha', 'yauli', 'junín', '120805', '4550'], ['6', 'san antonio de chuca', 'caylloma', 'arequipa', '40514', '4525'], ['7', 'santa ana', 'castrovirreyna', 'huancavelica', '90411', '4473'], ['8', 'marcapomacocha', 'yauli', 'junín', '120804', '4415'], ['9', 'capazo', 'el collao', 'puno', '210502', '4400'], ['10', 'paratia', 'lampa', 'puno', '210707', '4390'], ['11', 'cojata', 'huancané', 'puno', '210602', '4355'], ['12', 'yanacancha', 'pasco', 'pasco', '190113', '4350'], ['13', 'chaupimarca', 'pasco', 'pasco', '190101', '4338'], ['14', 'macusani', 'carabaya', 'puno', '210301', '4315'], ['15', 'huayllay', 'pasco', 'pasco', '190104', '4310'], ['16', 'caylloma', 'caylloma', 'arequipa', '40505', '4310'], ['17', 'vilavila', 'lampa', 'puno', '210710', '4300'], ['18', 'tanta', 'yauyos', 'lima', '151028', '4278'], ['19', 'tinyahuarco', 'pasco', 'pasco', '190111', '4275']] |
atherstone nature reserve | https://en.wikipedia.org/wiki/Atherstone_Nature_Reserve | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-20042805-2.html.csv | unique | the egyptian goose is the only type of goose at the atherstone nature reserve . | {'scope': 'all', 'row': '1', 'col': '1', 'col_other': 'n/a', 'criterion': 'equal', 'value': 'egyptian goose', 'subset': None} | {'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'ostrich', 'egyptian goose'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose ostrich record fuzzily matches to egyptian goose .', 'tostr': 'filter_eq { all_rows ; ostrich ; egyptian goose }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; ostrich ; egyptian goose } } = true', 'tointer': 'select the rows whose ostrich record fuzzily matches to egyptian goose . there is only one such row in the table .'} | only { filter_eq { all_rows ; ostrich ; egyptian goose } } = true | select the rows whose ostrich record fuzzily matches to egyptian goose . 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, 'ostrich_4': 4, 'egyptian goose_5': 5} | {'only_1': 'only', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'ostrich_4': 'ostrich', 'egyptian goose_5': 'egyptian goose'} | {'only_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'ostrich_4': [0], 'egyptian goose_5': [0]} | ['ostrich', 'hamerkop', 'hadeda ibis', 'african spoonbill', 'whitefaced duck', 'knobbilled duck'] | [['egyptian goose', 'secretary bird', 'cape vulture', 'lappet - faced vulture', 'white - backed vulture', 'tawny eagle'], ["wahlberg 's eagle", 'martial eagle', 'brown snake eagle', 'black - breasted snake eagle', 'bateleur', 'african fish eagle'], ['dark chanting goshawk', 'gabar goshawk', 'crested francolin', "swainson 's francolin", 'common quail', 'melba finch'], ['helmeted guineafowl', 'blue waxbill', 'violet - eared waxbill', 'white - browed sparrow weaver', 'paradise whydah', 'kori bustard'], ['lesser masked weaver', 'black korhaan', 'redcrested korhaan', 'crowned plover', 'blacksmith plover', 'spotted dikkop'], ['double - banded sandgrouse', 'rock pigeon', 'red - eyed dove', 'cape turtle dove', 'laughing dove', 'namaqua dove'], ['green - spotted dove', 'grey lourie', 'jacobin cuckoo', 'diederik cuckoo', "burchell 's coucal", 'barn owl'], ['white - faced owl', 'pearl - spotted owlet', 'flernecked nightjar', 'rufous - cheeked nightjar', 'european bee - eater', 'little bee - eater'], ['blue - cheeked bee - eater', 'european roller', 'purple roller', 'lilac - breasted roller', 'hoopoe', 'grey hornbill'], ['yellow - billed hornbill', 'red - billed hornbill', 'pied barbet', 'european swallow', 'fork - tailed drongo', 'pied crow'], ['brown - hooded kingfisher', 'titbabbler', 'puffback', 'long - billed crombec', 'wattled starling', "burchell 's starling"]] |
list of vancouver canucks draft picks | https://en.wikipedia.org/wiki/List_of_Vancouver_Canucks_draft_picks | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11636955-5.html.csv | unique | dennis ververgaert was chosen with the 3rd pick in the 1st rounds . | {'scope': 'all', 'row': '1', 'col': '2', 'col_other': '3', 'criterion': 'equal', 'value': '3', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'pick', '3'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose pick record is equal to 3 .', 'tostr': 'filter_eq { all_rows ; pick ; 3 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; pick ; 3 } }', 'tointer': 'select the rows whose pick 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', 'pick', '3'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose pick record is equal to 3 .', 'tostr': 'filter_eq { all_rows ; pick ; 3 }'}, 'player'], 'result': 'dennis ververgaert', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; pick ; 3 } ; player }'}, 'dennis ververgaert'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; pick ; 3 } ; player } ; dennis ververgaert }', 'tointer': 'the player record of this unqiue row is dennis ververgaert .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; pick ; 3 } } ; eq { hop { filter_eq { all_rows ; pick ; 3 } ; player } ; dennis ververgaert } } = true', 'tointer': 'select the rows whose pick record is equal to 3 . there is only one such row in the table . the player record of this unqiue row is dennis ververgaert .'} | and { only { filter_eq { all_rows ; pick ; 3 } } ; eq { hop { filter_eq { all_rows ; pick ; 3 } ; player } ; dennis ververgaert } } = true | select the rows whose pick record is equal to 3 . there is only one such row in the table . the player record of this unqiue row is dennis ververgaert . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'pick_7': 7, '3_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'player_9': 9, 'dennis ververgaert_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'pick_7': 'pick', '3_8': '3', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'player_9': 'player', 'dennis ververgaert_10': 'dennis ververgaert'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'pick_7': [0], '3_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'player_9': [2], 'dennis ververgaert_10': [3]} | ['rd', 'pick', 'player', 'reg gp', 'pl gp'] | [['1', '3', 'dennis ververgaert', '409', '3'], ['1', '9', 'bob dailey', '257', '7'], ['2', '19', 'paulin bordeleau', '183', '5'], ['3', '35', 'paul sheard', '0', '0'], ['4', '51', 'keith mackie', '0', '0'], ['5', '67', "paul o'neil", '5', '0'], ['6', '83', 'jim cowell', '0', '0'], ['7', '99', 'clay hebenton', '0', '0'], ['8', '115', 'john senkpiel', '0', '0'], ['9', '131', 'peter folco', '2', '0'], ['9', '146', 'terry mcdougall', '0', '0']] |
1975 - 76 fa cup | https://en.wikipedia.org/wiki/1975%E2%80%9376_FA_Cup | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18726561-4.html.csv | count | there were a total of three replays between january 27 and january 28 . | {'scope': 'all', 'criterion': 'equal', 'value': 'replay', 'result': '3', 'col': '1', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'tie no', 'replay'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose tie no record fuzzily matches to replay .', 'tostr': 'filter_eq { all_rows ; tie no ; replay }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; tie no ; replay } }', 'tointer': 'select the rows whose tie no record fuzzily matches to replay . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; tie no ; replay } } ; 3 } = true', 'tointer': 'select the rows whose tie no record fuzzily matches to replay . the number of such rows is 3 .'} | eq { count { filter_eq { all_rows ; tie no ; replay } } ; 3 } = true | select the rows whose tie no record fuzzily matches to replay . 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, 'tie no_5': 5, 'replay_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', 'tie no_5': 'tie no', 'replay_6': 'replay', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'tie no_5': [0], 'replay_6': [0], '3_7': [2]} | ['tie no', 'home team', 'score', 'away team', 'date'] | [['1', 'southampton', '3 - 1', 'blackpool', '24 january 1976'], ['2', 'leicester city', '1 - 0', 'bury', '24 january 1976'], ['3', 'west bromwich albion', '3 - 2', 'lincoln city', '24 january 1976'], ['4', 'sunderland', '1 - 0', 'hull city', '2 february 1976'], ['5', 'derby county', '1 - 0', 'liverpool', '24 january 1976'], ['6', 'ipswich town', '0 - 0', 'wolverhampton wanderers', '24 january 1976'], ['replay', 'wolverhampton wanderers', '1 - 0', 'ipswich town', '27 january 1976'], ['7', 'coventry city', '1 - 1', 'newcastle united', '24 january 1976'], ['replay', 'newcastle united', '5 - 0', 'coventry city', '28 january 1976'], ['8', 'manchester united', '3 - 1', 'peterborough united', '24 january 1976'], ['9', 'norwich city', '2 - 0', 'luton town', '24 january 1976'], ['10', 'bradford city', '3 - 1', 'tooting & mitcham united', '24 january 1976'], ['11', 'southend united', '2 - 1', 'cardiff city', '24 january 1976'], ['12', 'huddersfield town', '0 - 1', 'bolton wanderers', '24 january 1976'], ['13', 'charlton athletic', '1 - 1', 'portsmouth', '24 january 1976'], ['replay', 'portsmouth', '0 - 3', 'charlton athletic', '27 january 1976'], ['14', 'leeds united', '0 - 1', 'crystal palace', '24 january 1976'], ['15', 'york city', '0 - 2', 'chelsea', '24 january 1976'], ['16', 'stoke city', '1 - 0', 'manchester city', '28 january 1976']] |
list of amusement park rankings | https://en.wikipedia.org/wiki/List_of_amusement_park_rankings | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16578883-7.html.csv | comparative | in the rankings for amusement parks , water country usa was ranked two positions lower than siam water park . | {'row_1': '20', 'row_2': '18', 'col': '1', 'col_other': '2', 'relation': 'diff', 'record_mentioned': 'yes', 'diff_result': {'diff_value': '2', 'bigger': 'row1'}} | {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'diff', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'water park', 'water country usa'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose water park record fuzzily matches to water country usa .', 'tostr': 'filter_eq { all_rows ; water park ; water country usa }'}, 'rank'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; water park ; water country usa } ; rank }', 'tointer': 'select the rows whose water park record fuzzily matches to water country usa . take the rank record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'water park', 'siam water park'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose water park record fuzzily matches to siam water park .', 'tostr': 'filter_eq { all_rows ; water park ; siam water park }'}, 'rank'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; water park ; siam water park } ; rank }', 'tointer': 'select the rows whose water park record fuzzily matches to siam water park . take the rank record of this row .'}], 'result': '2', 'ind': 4, 'tostr': 'diff { hop { filter_eq { all_rows ; water park ; water country usa } ; rank } ; hop { filter_eq { all_rows ; water park ; siam water park } ; rank } }'}, '2'], 'result': True, 'ind': 5, 'tostr': 'eq { diff { hop { filter_eq { all_rows ; water park ; water country usa } ; rank } ; hop { filter_eq { all_rows ; water park ; siam water park } ; rank } } ; 2 }', 'tointer': 'select the rows whose water park record fuzzily matches to water country usa . take the rank record of this row . select the rows whose water park record fuzzily matches to siam water park . take the rank record of this row . the first record is 2 larger than the second record .'}, {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'water park', 'water country usa'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose water park record fuzzily matches to water country usa .', 'tostr': 'filter_eq { all_rows ; water park ; water country usa }'}, 'rank'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; water park ; water country usa } ; rank }', 'tointer': 'select the rows whose water park record fuzzily matches to water country usa . take the rank record of this row .'}, '20'], 'result': True, 'ind': 6, 'tostr': 'eq { hop { filter_eq { all_rows ; water park ; water country usa } ; rank } ; 20 }', 'tointer': 'the rank record of the first row is 20 .'}, {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'water park', 'siam water park'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose water park record fuzzily matches to siam water park .', 'tostr': 'filter_eq { all_rows ; water park ; siam water park }'}, 'rank'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; water park ; siam water park } ; rank }', 'tointer': 'select the rows whose water park record fuzzily matches to siam water park . take the rank record of this row .'}, '18'], 'result': True, 'ind': 7, 'tostr': 'eq { hop { filter_eq { all_rows ; water park ; siam water park } ; rank } ; 18 }', 'tointer': 'the rank record of the second row is 18 .'}], 'result': True, 'ind': 8, 'tostr': 'and { eq { hop { filter_eq { all_rows ; water park ; water country usa } ; rank } ; 20 } ; eq { hop { filter_eq { all_rows ; water park ; siam water park } ; rank } ; 18 } }', 'tointer': 'the rank record of the first row is 20 . the rank record of the second row is 18 .'}], 'result': True, 'ind': 9, 'tostr': 'and { eq { diff { hop { filter_eq { all_rows ; water park ; water country usa } ; rank } ; hop { filter_eq { all_rows ; water park ; siam water park } ; rank } } ; 2 } ; and { eq { hop { filter_eq { all_rows ; water park ; water country usa } ; rank } ; 20 } ; eq { hop { filter_eq { all_rows ; water park ; siam water park } ; rank } ; 18 } } } = true', 'tointer': 'select the rows whose water park record fuzzily matches to water country usa . take the rank record of this row . select the rows whose water park record fuzzily matches to siam water park . take the rank record of this row . the first record is 2 larger than the second record . the rank record of the first row is 20 . the rank record of the second row is 18 .'} | and { eq { diff { hop { filter_eq { all_rows ; water park ; water country usa } ; rank } ; hop { filter_eq { all_rows ; water park ; siam water park } ; rank } } ; 2 } ; and { eq { hop { filter_eq { all_rows ; water park ; water country usa } ; rank } ; 20 } ; eq { hop { filter_eq { all_rows ; water park ; siam water park } ; rank } ; 18 } } } = true | select the rows whose water park record fuzzily matches to water country usa . take the rank record of this row . select the rows whose water park record fuzzily matches to siam water park . take the rank record of this row . the first record is 2 larger than the second record . the rank record of the first row is 20 . the rank record of the second row is 18 . | 14 | 10 | {'and_9': 9, 'result_10': 10, 'eq_5': 5, 'diff_4': 4, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_11': 11, 'water park_12': 12, 'water country usa_13': 13, 'rank_14': 14, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_15': 15, 'water park_16': 16, 'siam water park_17': 17, 'rank_18': 18, '2_19': 19, 'and_8': 8, 'eq_6': 6, '20_20': 20, 'eq_7': 7, '18_21': 21} | {'and_9': 'and', 'result_10': 'true', 'eq_5': 'eq', 'diff_4': 'diff', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_11': 'all_rows', 'water park_12': 'water park', 'water country usa_13': 'water country usa', 'rank_14': 'rank', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_15': 'all_rows', 'water park_16': 'water park', 'siam water park_17': 'siam water park', 'rank_18': 'rank', '2_19': '2', 'and_8': 'and', 'eq_6': 'eq', '20_20': '20', 'eq_7': 'eq', '18_21': '18'} | {'and_9': [10], 'result_10': [], 'eq_5': [9], 'diff_4': [5], 'num_hop_2': [4, 6], 'filter_str_eq_0': [2], 'all_rows_11': [0], 'water park_12': [0], 'water country usa_13': [0], 'rank_14': [2], 'num_hop_3': [4, 7], 'filter_str_eq_1': [3], 'all_rows_15': [1], 'water park_16': [1], 'siam water park_17': [1], 'rank_18': [3], '2_19': [5], 'and_8': [9], 'eq_6': [8], '20_20': [6], 'eq_7': [8], '18_21': [7]} | ['rank', 'water park', 'location', '2011', '2012'] | [['1', 'typhoon lagoon at walt disney world resort', 'lake buena vista , florida , usa', '2058000', '2100000'], ['2', 'chime - long water park', 'guangzhou , china', '1900000', '2021000'], ['3', 'blizzard beach at walt disney world resort', 'lake buena vista , florida , usa', '1891000', '1929000'], ['4', 'ocean world', 'gangwon - do , south korea', '1726000', '1720000'], ['5', 'aquatica', 'orlando , florida , usa', '1500000', '1538000'], ['6', 'caribbean bay at everland resort', 'gyeonggi - do , south korea', '1497000', '1508000'], ['7', 'aquaventure', 'dubai , united arab emirates', '1200000', '1300000'], ['8', "wet 'n wild orlando", 'orlando , florida , usa', '1223000', '1247000'], ['9', "wet 'n' wild water world", 'gold coast , queensland , australia', '1200000', '1200000'], ['10', 'sunway lagoon', 'kuala lumpur , malaysia', '1040000', '1200000'], ['11', 'resom spa castle', 'chungcheongnam - do , south korea', '1034000', '1158000'], ['12', 'schlitterbahn', 'new braunfels , texas , usa', '982000', '1017000'], ['13', 'atlantis water adventure', 'jakarta , indonesia', '950000', '1000000'], ['14', 'summerland', 'tokyo , japan', '850000', '990000'], ['15', 'happy magic water cube', 'beijing , china', '768000', '968000'], ['16', 'the jungle water adventure', 'bogor , indonesia', '871000', '951000'], ['17', 'wild wadi water park', 'dubai , united arab emirates', '890000', '860000'], ['18', 'siam water park', 'tenerife , spain', '800000', '800000'], ['19', 'ocean park water adventure', 'jakarta , indonesia', '600000', '750000'], ['20', 'water country usa', 'williamsburg , virginia , usa', '723000', '748000']] |
2006 formula nippon season | https://en.wikipedia.org/wiki/2006_Formula_Nippon_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10264179-2.html.csv | majority | mobilecast impul was the winning team in the majority of these races . | {'scope': 'all', 'col': '7', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'mobilecast impul', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'winning team', 'mobilecast impul'], 'result': True, 'ind': 0, 'tointer': 'for the winning team records of all rows , most of them fuzzily match to mobilecast impul .', 'tostr': 'most_eq { all_rows ; winning team ; mobilecast impul } = true'} | most_eq { all_rows ; winning team ; mobilecast impul } = true | for the winning team records of all rows , most of them fuzzily match to mobilecast impul . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'winning team_3': 3, 'mobilecast impul_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'winning team_3': 'winning team', 'mobilecast impul_4': 'mobilecast impul'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'winning team_3': [0], 'mobilecast impul_4': [0]} | ['round', 'circuit', 'date', 'pole position', 'fastest lap', 'winning driver', 'winning team'] | [['1', 'fuji speedway', '2 april', 'benoît tréluyer', 'masataka yanagida', 'benoît tréluyer', 'mobilecast impul'], ['2', 'suzuka circuit', '16 april', 'benoît tréluyer', 'benoît tréluyer', 'loïc duval', 'piaa nakajima'], ['3', 'twin ring motegi', '28 may', 'takashi kogure', 'tsugio matsuda', 'andré lotterer', "dhg tom 's"], ['4', 'suzuka circuit', '9 july', 'benoît tréluyer', 'benoît tréluyer', 'benoît tréluyer', 'mobilecast impul'], ['5', 'autopolis', '6 august', 'takashi kogure', 'loïc duval', 'tsugio matsuda', 'mobilecast impul'], ['6', 'fuji speedway', '27 august', 'takashi kogure', 'satoshi motoyama', 'benoît tréluyer', 'mobilecast impul'], ['7', 'sportsland sugo', '17 september', 'takashi kogure', 'hideki mutoh', 'loïc duval', 'piaa nakajima'], ['8', 'twin ring motegi', '22 october', 'takashi kogure', 'satoshi motoyama', 'benoît tréluyer', 'mobilecast impul'], ['9', 'suzuka circuit', '19 november', 'tsugio matsuda', 'benoît tréluyer', 'andré lotterer', "dhg tom 's"]] |
kprd | https://en.wikipedia.org/wiki/KPRD | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14993404-1.html.csv | count | there are 3 kprd station below the 100 frequency . | {'scope': 'all', 'criterion': 'less_than', 'value': '100', 'result': '3', 'col': '2', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'frequency mhz', '100'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose frequency mhz record is less than 100 .', 'tostr': 'filter_less { all_rows ; frequency mhz ; 100 }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_less { all_rows ; frequency mhz ; 100 } }', 'tointer': 'select the rows whose frequency mhz record is less than 100 . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_less { all_rows ; frequency mhz ; 100 } } ; 3 } = true', 'tointer': 'select the rows whose frequency mhz record is less than 100 . the number of such rows is 3 .'} | eq { count { filter_less { all_rows ; frequency mhz ; 100 } } ; 3 } = true | select the rows whose frequency mhz record is less than 100 . the number of such rows is 3 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_less_0': 0, 'all_rows_4': 4, 'frequency mhz_5': 5, '100_6': 6, '3_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_less_0': 'filter_less', 'all_rows_4': 'all_rows', 'frequency mhz_5': 'frequency mhz', '100_6': '100', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_less_0': [1], 'all_rows_4': [0], 'frequency mhz_5': [0], '100_6': [0], '3_7': [2]} | ['call sign', 'frequency mhz', 'city of license', 'erp w', 'class', 'fcc info'] | [['k202bp', '88.3', 'bellaire , smith county , kansas', '78', 'd', 'fcc'], ['k216ed', '91.1', 'phillipsburg , kansas', '222', 'd', 'fcc'], ['k241an', '96.1', 'pratt , kansas', '250', 'd', 'fcc'], ['k278ap', '103.5', 'lewis , kansas', '171', 'd', 'fcc'], ['k297ai', '107.3', 'hill city , kansas', '170', 'd', 'fcc']] |
1966 in brazilian football | https://en.wikipedia.org/wiki/1966_in_Brazilian_football | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15220905-2.html.csv | majority | in 1966 brazilian football , most of the teams scored at least nine points . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'greater_than_eq', 'value': '9', 'subset': None} | {'func': 'most_greater_eq', 'args': ['all_rows', 'points', '9'], 'result': True, 'ind': 0, 'tointer': 'for the points records of all rows , most of them are greater than or equal to 9 .', 'tostr': 'most_greater_eq { all_rows ; points ; 9 } = true'} | most_greater_eq { all_rows ; points ; 9 } = true | for the points records of all rows , most of them are greater than or equal to 9 . | 1 | 1 | {'most_greater_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'points_3': 3, '9_4': 4} | {'most_greater_eq_0': 'most_greater_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'points_3': 'points', '9_4': '9'} | {'most_greater_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'points_3': [0], '9_4': [0]} | ['position', 'team', 'points', 'played', 'drawn', 'lost', 'against', 'difference'] | [['1', 'botafogo', '11', '9', '3', '2', '11', '8'], ['2', 'santos', '11', '9', '3', '2', '11', '7'], ['3', 'vasco da gama', '11', '9', '1', '3', '11', '1'], ['4', 'corinthians', '11', '9', '1', '3', '15', '0'], ['5', 'são paulo', '10', '9', '0', '4', '11', '3'], ['6', 'palmeiras', '9', '9', '1', '4', '13', '- 2'], ['7', 'flamengo', '8', '9', '2', '4', '13', '0'], ['8', 'bangu', '8', '9', '0', '5', '12', '- 3'], ['9', 'fluminense', '6', '9', '0', '6', '17', '- 9'], ['10', 'portuguesa', '5', '9', '1', '6', '16', '- 5']] |
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 | comparative | the yogyakarta documentary film festival was established before the vibgyor international film festival . | {'row_1': '6', 'row_2': '5', 'col': '2', 'col_other': '1', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'name', 'yogyakarta documentary film festival'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose name record fuzzily matches to yogyakarta documentary film festival .', 'tostr': 'filter_eq { all_rows ; name ; yogyakarta documentary film festival }'}, 'est'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; name ; yogyakarta documentary film festival } ; est }', 'tointer': 'select the rows whose name record fuzzily matches to yogyakarta documentary film festival . take the est record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'name', 'vibgyor international film festival'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose name record fuzzily matches to vibgyor international film festival .', 'tostr': 'filter_eq { all_rows ; name ; vibgyor international film festival }'}, 'est'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; name ; vibgyor international film festival } ; est }', 'tointer': 'select the rows whose name record fuzzily matches to vibgyor international film festival . take the est record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; name ; yogyakarta documentary film festival } ; est } ; hop { filter_eq { all_rows ; name ; vibgyor international film festival } ; est } } = true', 'tointer': 'select the rows whose name record fuzzily matches to yogyakarta documentary film festival . take the est record of this row . select the rows whose name record fuzzily matches to vibgyor international film festival . take the est record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; name ; yogyakarta documentary film festival } ; est } ; hop { filter_eq { all_rows ; name ; vibgyor international film festival } ; est } } = true | select the rows whose name record fuzzily matches to yogyakarta documentary film festival . take the est record of this row . select the rows whose name record fuzzily matches to vibgyor international film festival . take the est record of this row . the first record is less than the second record . | 5 | 5 | {'less_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'name_7': 7, 'yogyakarta documentary film festival_8': 8, 'est_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'name_11': 11, 'vibgyor international film festival_12': 12, 'est_13': 13} | {'less_4': 'less', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'name_7': 'name', 'yogyakarta documentary film festival_8': 'yogyakarta documentary film festival', 'est_9': 'est', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'name_11': 'name', 'vibgyor international film festival_12': 'vibgyor international film festival', 'est_13': 'est'} | {'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'name_7': [0], 'yogyakarta documentary film festival_8': [0], 'est_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'name_11': [1], 'vibgyor international film festival_12': [1], 'est_13': [3]} | ['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']] |
vk selver tallinn | https://en.wikipedia.org/wiki/VK_Selver_Tallinn | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-25058562-2.html.csv | ordinal | for vk selver tallinn , the 2nd tallest player is argo meresaar . | {'row': '5', 'col': '5', 'order': '2', 'col_other': '3', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'height', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; height ; 2 }'}, 'player'], 'result': 'argo meresaar ( c )', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; height ; 2 } ; player }'}, 'argo meresaar ( c )'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; height ; 2 } ; player } ; argo meresaar ( c ) } = true', 'tointer': 'select the row whose height record of all rows is 2nd maximum . the player record of this row is argo meresaar ( c ) .'} | eq { hop { nth_argmax { all_rows ; height ; 2 } ; player } ; argo meresaar ( c ) } = true | select the row whose height record of all rows is 2nd maximum . the player record of this row is argo meresaar ( c ) . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'height_5': 5, '2_6': 6, 'player_7': 7, 'argo meresaar (c)_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'height_5': 'height', '2_6': '2', 'player_7': 'player', 'argo meresaar (c)_8': 'argo meresaar ( c )'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'height_5': [0], '2_6': [0], 'player_7': [1], 'argo meresaar (c)_8': [2]} | ['shirt no', 'nationality', 'player', 'birth date', 'height', 'position'] | [['1', 'estonia', 'meelis kivisild', 'july 28 , 1990 ( age23 )', '199', 'middle blocker'], ['2', 'estonia', 'keiro vantsi', 'december 29 , 1993 ( age20 )', '191', 'setter'], ['3', 'estonia', 'martti keel', 'january 30 , 1992 ( age22 )', '188', 'setter'], ['4', 'estonia', 'timo tammemaa', 'november 18 , 1991 ( age22 )', '200', 'middle blocker'], ['5', 'estonia', 'argo meresaar ( c )', 'january 13 , 1980 ( age34 )', '206', 'opposite'], ['6', 'estonia', 'reimo rannar', 'january 30 , 1988 ( age26 )', '203', 'middle blocker'], ['7', 'estonia', 'kristjan ã uekallas', 'january 8 , 1981 ( age33 )', '193', 'spiker'], ['8', 'estonia', 'hindrek pulk', 'november 7 , 1990 ( age23 )', '193', 'opposite'], ['9', 'estonia', 'andri aganits', 'september 7 , 1993 ( age20 )', '207', 'middle blocker'], ['10', 'estonia', 'kaur koiduste', 'february 20 , 1994 ( age19 )', '190', 'spiker'], ['11', 'estonia', 'taavi sadam', 'july 4 , 1990 ( age23 )', '189', 'spiker'], ['12', 'latvia', 'andrejs baburovs', 'october 6 , 1987 ( age26 )', '192', 'spiker'], ['13', 'estonia', 'asko esna', 'may 1 , 1986 ( age27 )', '185', 'libero'], ['14', 'estonia', 'markus keel', 'august 18 , 1995 ( age18 )', '189', 'setter'], ['15', 'estonia', 'denis losnikov', 'february 25 , 1994 ( age19 )', '196', 'spiker']] |
transouth athletic conference | https://en.wikipedia.org/wiki/TranSouth_Athletic_Conference | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1715730-2.html.csv | comparative | more people attend the school located in cleveland than the school in birmingham . | {'row_1': '4', 'row_2': '2', 'col': '4', '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', 'location', 'cleveland , tennessee'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose location record fuzzily matches to cleveland , tennessee .', 'tostr': 'filter_eq { all_rows ; location ; cleveland , tennessee }'}, 'enrollment'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; location ; cleveland , tennessee } ; enrollment }', 'tointer': 'select the rows whose location record fuzzily matches to cleveland , tennessee . take the enrollment record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location', 'birmingham , alabama'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose location record fuzzily matches to birmingham , alabama .', 'tostr': 'filter_eq { all_rows ; location ; birmingham , alabama }'}, 'enrollment'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; location ; birmingham , alabama } ; enrollment }', 'tointer': 'select the rows whose location record fuzzily matches to birmingham , alabama . take the enrollment record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; location ; cleveland , tennessee } ; enrollment } ; hop { filter_eq { all_rows ; location ; birmingham , alabama } ; enrollment } } = true', 'tointer': 'select the rows whose location record fuzzily matches to cleveland , tennessee . take the enrollment record of this row . select the rows whose location record fuzzily matches to birmingham , alabama . take the enrollment record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; location ; cleveland , tennessee } ; enrollment } ; hop { filter_eq { all_rows ; location ; birmingham , alabama } ; enrollment } } = true | select the rows whose location record fuzzily matches to cleveland , tennessee . take the enrollment record of this row . select the rows whose location record fuzzily matches to birmingham , alabama . take the enrollment 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, 'location_7': 7, 'cleveland , tennessee_8': 8, 'enrollment_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'location_11': 11, 'birmingham , alabama_12': 12, 'enrollment_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', 'location_7': 'location', 'cleveland , tennessee_8': 'cleveland , tennessee', 'enrollment_9': 'enrollment', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'location_11': 'location', 'birmingham , alabama_12': 'birmingham , alabama', 'enrollment_13': 'enrollment'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'location_7': [0], 'cleveland , tennessee_8': [0], 'enrollment_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'location_11': [1], 'birmingham , alabama_12': [1], 'enrollment_13': [3]} | ['location', 'founded', 'type', 'enrollment', 'nickname', 'joined', 'left', 'current conference'] | [['mount berry , georgia', '1902', 'private', '1937', 'vikings', '1996', '2004', 'saa ( ncaa division iii )'], ['birmingham , alabama', '1856', 'private', '1400', 'panthers', '1996', '2001', 'saa ( ncaa division iii )'], ['nashville , tennessee', '1891', 'private', '4278', 'bisons', '1996', '2001', 'atlantic sun ( a - sun ) ( ncaa division i )'], ['cleveland , tennessee', '1918', 'private', '4954', 'flames', '1996', '2004', 'ssac , gulf south in 2013'], ['nashville , tennessee', '1901', 'private', '2345', 'trojans', '1996', '2012', 'g - mac ( ncaa division ii )'], ['jackson , tennessee', '1823', 'private', '4259', 'union', '1996', '2012', 'gulf south ( gsc ) ( ncaa division ii )'], ['walnut ridge , arkansas', '1941', 'private', '700', 'eagles', '1996', '2001', 'american midwest'], ['batesville , arkansas', '1872', 'private', '600', 'scots', '1997', '2012', 'american midwest'], ['memphis , tennessee', '1941', 'private', '1970', 'eagles', '2005', '2009', 'uscaa / nccaa independent'], ['jackson , tennessee', '1843', 'private', '800', 'eagles', '2006', '2009', 'closed in 2011'], ['lebanon , tennessee', '1842', 'private', '1500', 'bulldogs', '2002', '2012', 'mid - south']] |
maurício gugelmin | https://en.wikipedia.org/wiki/Maur%C3%ADcio_Gugelmin | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1226502-2.html.csv | aggregation | the average number of points for mauricio gugelmin is 2.33 . | {'scope': 'all', 'col': '5', 'type': 'average', 'result': '2.33', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'pts'], 'result': '2.33', 'ind': 0, 'tostr': 'avg { all_rows ; pts }'}, '2.33'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; pts } ; 2.33 } = true', 'tointer': 'the average of the pts record of all rows is 2.33 .'} | round_eq { avg { all_rows ; pts } ; 2.33 } = true | the average of the pts record of all rows is 2.33 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'pts_4': 4, '2.33_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'pts_4': 'pts', '2.33_5': '2.33'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'pts_4': [0], '2.33_5': [1]} | ['year', 'entrant', 'chassis', 'engine', 'pts'] | [['1988', 'leyton house march racing team', 'march 881', 'judd v8', '5'], ['1989', 'leyton house racing', 'march 881', 'judd v8', '4'], ['1989', 'leyton house racing', 'march cg891', 'judd v8', '4'], ['1990', 'leyton house', 'leyton house cg901', 'judd v8', '1'], ['1991', 'leyton house', 'leyton house cg911', 'ilmor v10', '0'], ['1992', 'sasol jordan yamaha', 'jordan 192', 'yamaha v12', '0']] |
2009 world rally championship season | https://en.wikipedia.org/wiki/2009_World_Rally_Championship_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18811741-15.html.csv | majority | most of the drivers scored at least 6 points or more during the 2009 world rally championship season . | {'scope': 'all', 'col': '7', 'most_or_all': 'most', 'criterion': 'greater_than_eq', 'value': '7', 'subset': None} | {'func': 'most_greater_eq', 'args': ['all_rows', 'points', '7'], 'result': True, 'ind': 0, 'tointer': 'for the points records of all rows , most of them are greater than or equal to 7 .', 'tostr': 'most_greater_eq { all_rows ; points ; 7 } = true'} | most_greater_eq { all_rows ; points ; 7 } = true | for the points records of all rows , most of them are greater than or equal to 7 . | 1 | 1 | {'most_greater_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'points_3': 3, '7_4': 4} | {'most_greater_eq_0': 'most_greater_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'points_3': 'points', '7_4': '7'} | {'most_greater_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'points_3': [0], '7_4': [0]} | ['driver', 'starts', 'finishes', 'wins', 'podiums', 'stage wins', 'points'] | [['sébastien loeb', '12', '11', '7', '9', '88', '93'], ['mikko hirvonen', '12', '11', '4', '11', '51', '92'], ['daniel sordo', '12', '12', '0', '7', '18', '64'], ['jari - matti latvala', '12', '10', '1', '4', '40', '41'], ['petter solberg', '10', '7', '0', '2', '10', '35'], ['henning solberg', '12', '12', '0', '2', '8', '33'], ['matthew wilson', '12', '11', '0', '0', '2', '28'], ['sébastien ogier', '12', '8', '0', '1', '13', '24'], ['federico villagra', '8', '7', '0', '0', '0', '16'], ['conrad rautenbach', '12', '7', '0', '0', '0', '9'], ['mads østberg', '7', '4', '0', '0', '1', '7'], ['khalid al - qassimi', '9', '9', '0', '0', '0', '6'], ['chris atkinson', '1', '1', '0', '0', '0', '4'], ['evgeny novikov', '8', '4', '0', '0', '4', '4'], ['matti rantanen', '1', '1', '0', '0', '0', '4'], ['krzysztof hołowczyc', '1', '1', '0', '0', '0', '3'], ['jari ketomaa', '1', '1', '0', '0', '0', '3'], ['nasser al - attiyah', '6', '5', '0', '0', '0', '1'], ['urmo aava', '3', '3', '0', '0', '0', '1'], ['lambros athanassoulas', '2', '2', '0', '0', '0', '1']] |
1977 san francisco 49ers season | https://en.wikipedia.org/wiki/1977_San_Francisco_49ers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18673955-1.html.csv | comparative | the san francisco 49ers had a game against the minnesota vikings earlier than green bay packers . | {'row_1': '12', 'row_2': '14', 'col': '2', 'col_other': '3', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', 'minnesota vikings'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose opponent record fuzzily matches to minnesota vikings .', 'tostr': 'filter_eq { all_rows ; opponent ; minnesota vikings }'}, 'date'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; opponent ; minnesota vikings } ; date }', 'tointer': 'select the rows whose opponent record fuzzily matches to minnesota vikings . take the date record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', 'green bay packers'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose opponent record fuzzily matches to green bay packers .', 'tostr': 'filter_eq { all_rows ; opponent ; green bay packers }'}, 'date'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; opponent ; green bay packers } ; date }', 'tointer': 'select the rows whose opponent record fuzzily matches to green bay packers . take the date record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; opponent ; minnesota vikings } ; date } ; hop { filter_eq { all_rows ; opponent ; green bay packers } ; date } } = true', 'tointer': 'select the rows whose opponent record fuzzily matches to minnesota vikings . take the date record of this row . select the rows whose opponent record fuzzily matches to green bay packers . take the date record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; opponent ; minnesota vikings } ; date } ; hop { filter_eq { all_rows ; opponent ; green bay packers } ; date } } = true | select the rows whose opponent record fuzzily matches to minnesota vikings . take the date record of this row . select the rows whose opponent record fuzzily matches to green bay packers . take the date record of this row . the first record is less than the second record . | 5 | 5 | {'less_4': 4, 'result_5': 5, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'opponent_7': 7, 'minnesota vikings_8': 8, 'date_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'opponent_11': 11, 'green bay packers_12': 12, 'date_13': 13} | {'less_4': 'less', 'result_5': 'true', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'opponent_7': 'opponent', 'minnesota vikings_8': 'minnesota vikings', 'date_9': 'date', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'opponent_11': 'opponent', 'green bay packers_12': 'green bay packers', 'date_13': 'date'} | {'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'opponent_7': [0], 'minnesota vikings_8': [0], 'date_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'opponent_11': [1], 'green bay packers_12': [1], 'date_13': [3]} | ['week', 'date', 'opponent', 'result', 'attendance'] | [['1', 'september 19 , 1977', 'pittsburgh steelers', 'l 27 - 0', '48046'], ['2', 'september 25 , 1977', 'miami dolphins', 'l 19 - 15', '40503'], ['3', 'october 2 , 1977', 'los angeles rams', 'l 34 - 14', '55466'], ['4', 'october 9 , 1977', 'atlanta falcons', 'l 7 - 0', '38009'], ['5', 'october 16 , 1977', 'new york giants', 'l 20 - 17', '70366'], ['6', 'october 23 , 1977', 'detroit lions', 'w 28 - 7', '39392'], ['7', 'october 30 , 1977', 'tampa bay buccaneers', 'w 20 - 10', '34700'], ['8', 'november 6 , 1977', 'atlanta falcons', 'w 10 - 3', '46577'], ['9', 'november 13 , 1977', 'new orleans saints', 'w 10 - 7', '41564'], ['10', 'november 20 , 1977', 'los angeles rams', 'l 23 - 10', '56779'], ['11', 'november 27 , 1977', 'new orleans saints', 'w 20 - 17', '33702'], ['12', 'december 4 , 1977', 'minnesota vikings', 'l 28 - 27', '40745'], ['13', 'december 12 , 1977', 'dallas cowboys', 'l 42 - 35', '55851'], ['14', 'december 18 , 1977', 'green bay packers', 'l 16 - 14', '44902']] |
2007 - 08 dallas mavericks season | https://en.wikipedia.org/wiki/2007%E2%80%9308_Dallas_Mavericks_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11963209-7.html.csv | majority | all games of the 2007 - 08 dallas mavericks ' season were scheduled for the month of february . | {'scope': 'all', 'col': '1', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'february', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'date', 'february'], 'result': True, 'ind': 0, 'tointer': 'for the date records of all rows , all of them fuzzily match to february .', 'tostr': 'all_eq { all_rows ; date ; february } = true'} | all_eq { all_rows ; date ; february } = true | for the date records of all rows , all of them fuzzily match to february . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'date_3': 3, 'february_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'date_3': 'date', 'february_4': 'february'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'date_3': [0], 'february_4': [0]} | ['date', 'visitor', 'score', 'home', 'leading scorer', 'attendance', 'record'] | [['3 february 2008', 'mavericks', '67 - 90', 'pistons', 'two - way tie ( 15 )', '22076', '31 - 15'], ['4 february 2008', 'mavericks', '107 - 98', 'magic', 'josh howard ( 28 )', '16974', '32 - 15'], ['6 february 2008', 'bucks', '96 - 107', 'mavericks', 'dirk nowitzki ( 29 )', '20079', '33 - 15'], ['8 february 2008', 'grizzlies', '81 - 92', 'mavericks', 'dirk nowitzki ( 21 )', '20315', '34 - 15'], ['10 february 2008', 'mavericks', '82 - 101', 'nets', 'dirk nowitzki ( 21 )', '16395', '34 - 16'], ['11 february 2008', 'mavericks', '76 - 84', 'sixers', 'josh howard ( 17 )', '11728', '34 - 17'], ['13 february 2008', 'trail blazers', '76 - 96', 'mavericks', 'dirk nowitzki ( 37 )', '20159', '35 - 17'], ['14 february 2008', 'mavericks', '97 - 109', 'suns', 'dirk nowitzki ( 36 )', '18422', '35 - 18'], ['20 february 2008', 'mavericks', '93 - 104', 'hornets', 'dirk nowitzki ( 31 )', '15941', '35 - 19'], ['22 february 2008', 'mavericks', '98 - 83', 'grizzlies', 'dirk nowitzki ( 27 )', '16245', '36 - 19'], ['24 february 2008', 'mavericks', '99 - 83', 'timberwolves', 'dirk nowitzki ( 29 )', '19429', '37 - 19'], ['25 february 2008', 'bulls', '94 - 102', 'mavericks', 'dirk nowitzki ( 29 )', '20340', '38 - 19'], ['28 february 2008', 'mavericks', '94 - 97', 'spurs', 'dirk nowitzki ( 28 )', '18797', '38 - 20'], ['29 february 2008', 'kings', '106 - 115', 'mavericks', 'dirk nowitzki ( 34 )', '20354', '39 - 20']] |
mark mcnulty | https://en.wikipedia.org/wiki/Mark_McNulty | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1601826-4.html.csv | unique | only in the charles schwab cup championship in 2004 was a winning score of less than 180 achieved . | {'scope': 'all', 'row': '3', 'col': '3', 'col_other': '2', 'criterion': 'less_than', 'value': '180', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'winning score', '180'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose winning score record is less than 180 .', 'tostr': 'filter_less { all_rows ; winning score ; 180 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_less { all_rows ; winning score ; 180 } }', 'tointer': 'select the rows whose winning score record is less than 180 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'winning score', '180'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose winning score record is less than 180 .', 'tostr': 'filter_less { all_rows ; winning score ; 180 }'}, 'tournament'], 'result': 'charles schwab cup championship', 'ind': 2, 'tostr': 'hop { filter_less { all_rows ; winning score ; 180 } ; tournament }'}, 'charles schwab cup championship'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_less { all_rows ; winning score ; 180 } ; tournament } ; charles schwab cup championship }', 'tointer': 'the tournament record of this unqiue row is charles schwab cup championship .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_less { all_rows ; winning score ; 180 } } ; eq { hop { filter_less { all_rows ; winning score ; 180 } ; tournament } ; charles schwab cup championship } } = true', 'tointer': 'select the rows whose winning score record is less than 180 . there is only one such row in the table . the tournament record of this unqiue row is charles schwab cup championship .'} | and { only { filter_less { all_rows ; winning score ; 180 } } ; eq { hop { filter_less { all_rows ; winning score ; 180 } ; tournament } ; charles schwab cup championship } } = true | select the rows whose winning score record is less than 180 . there is only one such row in the table . the tournament record of this unqiue row is charles schwab cup championship . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_less_0': 0, 'all_rows_6': 6, 'winning score_7': 7, '180_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'tournament_9': 9, 'charles schwab cup championship_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_less_0': 'filter_less', 'all_rows_6': 'all_rows', 'winning score_7': 'winning score', '180_8': '180', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'tournament_9': 'tournament', 'charles schwab cup championship_10': 'charles schwab cup championship'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_less_0': [1, 2], 'all_rows_6': [0], 'winning score_7': [0], '180_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'tournament_9': [2], 'charles schwab cup championship_10': [3]} | ['date', 'tournament', 'winning score', 'margin of victory', 'runner ( s ) - up'] | [['22 feb 2004', 'outback steakhouse pro - am', '13 ( 67 + 65 + 68 = 200 )', '1 stroke', 'larry nelson'], ['17 oct 2004', 'sbc championship', '18 ( 67 + 63 + 65 = 195 )', '8 strokes', 'gary mccord'], ['24 oct 2004', 'charles schwab cup championship', '11 ( 69 + 74 + 68 + 66 = 177 )', '1 stroke', 'tom kite'], ['26 jun 2005', 'bank of america championship', '12 ( 67 + 69 + 68 = 204 )', 'playoff', 'don pooley , tom purtzer'], ['16 oct 2005', 'administaff small business classic', '16 ( 66 + 68 + 66 = 200 )', '1 stroke', 'gil morgan'], ['19 aug 2007', 'jeld - wen tradition', '16 ( 66 + 68 + 70 + 68 = 272 )', '5 strokes', 'david edwards'], ['31 may 2009', 'principal charity classic', '10 ( 68 + 69 + 66 = 203 )', 'playoff', 'fred funk , nick price'], ['24 apr 2011', 'liberty mutual legends of golf ( with david eger )', '27 ( 64 + 64 + 61 = 189 )', 'playoff', 'scott hoch & kenny perry']] |
chad little | https://en.wikipedia.org/wiki/Chad_Little | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1875157-2.html.csv | comparative | chad little achieved a lower position in 1992 than in 1995 . | {'row_1': '1', 'row_2': '4', 'col': '10', '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', '1992'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose year record fuzzily matches to 1992 .', 'tostr': 'filter_eq { all_rows ; year ; 1992 }'}, 'position'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; year ; 1992 } ; position }', 'tointer': 'select the rows whose year record fuzzily matches to 1992 . take the position record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'year', '1995'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose year record fuzzily matches to 1995 .', 'tostr': 'filter_eq { all_rows ; year ; 1995 }'}, 'position'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; year ; 1995 } ; position }', 'tointer': 'select the rows whose year record fuzzily matches to 1995 . take the position record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; year ; 1992 } ; position } ; hop { filter_eq { all_rows ; year ; 1995 } ; position } } = true', 'tointer': 'select the rows whose year record fuzzily matches to 1992 . take the position record of this row . select the rows whose year record fuzzily matches to 1995 . take the position record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; year ; 1992 } ; position } ; hop { filter_eq { all_rows ; year ; 1995 } ; position } } = true | select the rows whose year record fuzzily matches to 1992 . take the position record of this row . select the rows whose year record fuzzily matches to 1995 . take the position 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, '1992_8': 8, 'position_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'year_11': 11, '1995_12': 12, 'position_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', '1992_8': '1992', 'position_9': 'position', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'year_11': 'year', '1995_12': '1995', 'position_13': 'position'} | {'greater_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'year_7': [0], '1992_8': [0], 'position_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'year_11': [1], '1995_12': [1], 'position_13': [3]} | ['year', 'starts', 'wins', 'top 5', 'top 10', 'poles', 'avg start', 'avg finish', 'winnings', 'position', 'team ( s )'] | [['1992', '1', '0', '0', '0', '0', '29.0', '29.0', '1400', '120th', '37 little racing'], ['1993', '12', '0', '2', '3', '0', '22.1', '22.6', '56508', '32nd', '23 mark rypien motorsports'], ['1994', '28', '0', '10', '14', '0', '21.0', '11.9', '234022', '3rd', '23 mark rypien motorsports'], ['1995', '26', '6', '11', '13', '0', '15.5', '14.5', '529056', '2nd', '23 mark rypien motorsports'], ['1996', '26', '0', '2', '7', '1', '15.3', '16.5', '317394', '5th', '23 mark rypien motorsports'], ['1998', '1', '0', '0', '0', '0', '6.0', '30.0', '4380', '108th', '9 roush racing'], ['2001', '33', '0', '2', '6', '0', '24.8', '16.0', '690321', '9th', '74 bace motorsports']] |
list of bradford city a.f.c. records and statistics | https://en.wikipedia.org/wiki/List_of_Bradford_City_A.F.C._records_and_statistics | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15278857-2.html.csv | count | a total of three different players have recorded a number of 64 goals for bradford city a.f.c. | {'scope': 'all', 'criterion': 'equal', 'value': '64', 'result': '3', 'col': '2', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'goals', '64'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose goals record is equal to 64 .', 'tostr': 'filter_eq { all_rows ; goals ; 64 }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; goals ; 64 } }', 'tointer': 'select the rows whose goals record is equal to 64 . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; goals ; 64 } } ; 3 } = true', 'tointer': 'select the rows whose goals record is equal to 64 . the number of such rows is 3 .'} | eq { count { filter_eq { all_rows ; goals ; 64 } } ; 3 } = true | select the rows whose goals record is equal to 64 . 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, 'goals_5': 5, '64_6': 6, '3_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'goals_5': 'goals', '64_6': '64', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'goals_5': [0], '64_6': [0], '3_7': [2]} | ['name', 'goals', 'apps', 'avge', 'career'] | [['bobby campbell', '121', '274', '0.44', '1979 - 1983 , 1983 - 1986'], ["frank o'rourke", '88', '192', '0.46', '1907 - 1914'], ['dean windass', '76', '216', '0.35', '1999 - 2001 , 2003 - 2007'], ['john hallows', '74', '164', '0.45', '1930 - 1936'], ['joe cooke', '68', '271', '0.25', '1971 - 1979 , 1981 - 1984'], ['gerry ingram', '64', '174', '0.37', '1971 - 1977'], ['bobby ham', '64', '188', '0.34', '1967 - 1971 , 1973 - 1975'], ['david mcniven', '64', '212', '0.30', '1978 - 1983'], ['sean mccarthy', '63', '131', '0.48', '1990 - 1994'], ['john hall', '63', '430', '0.15', '1962 - 1974'], ['david jackson', '61', '250', '0.24', '1955 - 1961'], ['bruce bannister', '60', '208', '0.29', '1965 - 1971'], ['dicky bond', '60', '301', '0.20', '1909 - 1922']] |
yanam | https://en.wikipedia.org/wiki/Yanam | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1404939-5.html.csv | comparative | chandernagore had a de facto transfer date that 's earlier than karikal . | {'row_1': '2', 'row_2': '3', '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', 'colony', 'chandernagore'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose colony record fuzzily matches to chandernagore .', 'tostr': 'filter_eq { all_rows ; colony ; chandernagore }'}, 'de facto transfer'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; colony ; chandernagore } ; de facto transfer }', 'tointer': 'select the rows whose colony record fuzzily matches to chandernagore . take the de facto transfer record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'colony', 'karikal'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose colony record fuzzily matches to karikal .', 'tostr': 'filter_eq { all_rows ; colony ; karikal }'}, 'de facto transfer'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; colony ; karikal } ; de facto transfer }', 'tointer': 'select the rows whose colony record fuzzily matches to karikal . take the de facto transfer record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; colony ; chandernagore } ; de facto transfer } ; hop { filter_eq { all_rows ; colony ; karikal } ; de facto transfer } } = true', 'tointer': 'select the rows whose colony record fuzzily matches to chandernagore . take the de facto transfer record of this row . select the rows whose colony record fuzzily matches to karikal . take the de facto transfer record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; colony ; chandernagore } ; de facto transfer } ; hop { filter_eq { all_rows ; colony ; karikal } ; de facto transfer } } = true | select the rows whose colony record fuzzily matches to chandernagore . take the de facto transfer record of this row . select the rows whose colony record fuzzily matches to karikal . take the de facto transfer 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, 'colony_7': 7, 'chandernagore_8': 8, 'de facto transfer_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'colony_11': 11, 'karikal_12': 12, 'de facto transfer_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', 'colony_7': 'colony', 'chandernagore_8': 'chandernagore', 'de facto transfer_9': 'de facto transfer', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'colony_11': 'colony', 'karikal_12': 'karikal', 'de facto transfer_13': 'de facto transfer'} | {'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'colony_7': [0], 'chandernagore_8': [0], 'de facto transfer_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'colony_11': [1], 'karikal_12': [1], 'de facto transfer_13': [3]} | ['colony', 'liberation', 'de facto transfer', 'treaty of cession', 'de jure transfer', 'merger'] | [['pondichéry', '-', '1 november 1954', '28 may 1956', '16 august 1963', '1 july 1963'], ['chandernagore', '-', '26 june 1949', '28 february 1951', '9 june 1952', '1 october 1954'], ['karikal', '-', '1 november 1954', '28 may 1956', '16 august 1963', '1 july 1963'], ['mahé', '16 june 1954', '1 november 1954', '28 may 1956', '16 august 1963', '1 july 1963'], ['yanaon', '13 june 1954', '1 november 1954', '28 may 1956', '16 august 1963', '1 july 1963']] |
jacksonville jaguars draft history | https://en.wikipedia.org/wiki/Jacksonville_Jaguars_draft_history | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15100419-7.html.csv | aggregation | the average pick for jacksonville jaguars draft history is 20.8 . | {'scope': 'all', 'col': '2', 'type': 'average', 'result': '20.8', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'pick'], 'result': '20.8', 'ind': 0, 'tostr': 'avg { all_rows ; pick }'}, '20.8'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; pick } ; 20.8 } = true', 'tointer': 'the average of the pick record of all rows is 20.8 .'} | round_eq { avg { all_rows ; pick } ; 20.8 } = true | the average of the pick record of all rows is 20.8 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'pick_4': 4, '20.8_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'pick_4': 'pick', '20.8_5': '20.8'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'pick_4': [0], '20.8_5': [1]} | ['round', 'pick', 'overall', 'name', 'position', 'college'] | [['1', '13', '13', 'marcus stroud', 'defensive tackle', 'georgia'], ['2', '12', '43', 'maurice williams', 'offensive tackle', 'michigan'], ['3', '11', '73', 'eric westmoreland', 'linebacker', 'tennessee'], ['3', '32', '94', 'james boyd', 'defensive back', 'penn state'], ['5', '11', '142', 'david leaverton', 'punter', 'tennessee'], ['6', '7', '170', 'chad ward', 'guard', 'washington'], ['7', '13', '213', 'anthony denman', 'linebacker', 'notre dame'], ['7', '33', '233', 'marlon mccree', 'safety', 'kentucky'], ['7', '35', '235', 'richmond flowers', 'wide receiver', 'tennessee - chattanooga'], ['7', '41', '241', 'randy chevrier', 'defensive tackle', 'mcgill']] |
eagles - giants rivalry | https://en.wikipedia.org/wiki/Eagles%E2%80%93Giants_rivalry | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16900662-5.html.csv | comparative | in 1968 , the new york giants scored more points against the philadelphia eagles in september than in november . | {'row_1': '16', 'row_2': '17', 'col': '4', 'col_other': '2', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', 'september 22'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose date record fuzzily matches to september 22 .', 'tostr': 'filter_eq { all_rows ; date ; september 22 }'}, 'result'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; date ; september 22 } ; result }', 'tointer': 'select the rows whose date record fuzzily matches to september 22 . take the result record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', 'november 17'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose date record fuzzily matches to november 17 .', 'tostr': 'filter_eq { all_rows ; date ; november 17 }'}, 'result'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; date ; november 17 } ; result }', 'tointer': 'select the rows whose date record fuzzily matches to november 17 . take the result record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; date ; september 22 } ; result } ; hop { filter_eq { all_rows ; date ; november 17 } ; result } } = true', 'tointer': 'select the rows whose date record fuzzily matches to september 22 . take the result record of this row . select the rows whose date record fuzzily matches to november 17 . take the result record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; date ; september 22 } ; result } ; hop { filter_eq { all_rows ; date ; november 17 } ; result } } = true | select the rows whose date record fuzzily matches to september 22 . take the result record of this row . select the rows whose date record fuzzily matches to november 17 . take the result record of this row . the first record is greater than the second record . | 5 | 5 | {'greater_4': 4, 'result_5': 5, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'date_7': 7, 'september 22_8': 8, 'result_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'date_11': 11, 'november 17_12': 12, 'result_13': 13} | {'greater_4': 'greater', 'result_5': 'true', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'date_7': 'date', 'september 22_8': 'september 22', 'result_9': 'result', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'date_11': 'date', 'november 17_12': 'november 17', 'result_13': 'result'} | {'greater_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'date_7': [0], 'september 22_8': [0], 'result_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'date_11': [1], 'november 17_12': [1], 'result_13': [3]} | ['year', 'date', 'winner', 'result', 'loser', 'location'] | [['1960', 'november 20', 'philadelphia eagles', '17 - 10', 'new york giants', 'yankee stadium'], ['1960', 'november 27', 'philadelphia eagles', '31 - 23', 'new york giants', 'franklin field'], ['1961', 'november 12', 'new york giants', '38 - 21', 'philadelphia eagles', 'yankee stadium'], ['1961', 'december 10', 'philidalphia eagles', '28 - 24', 'new york giants', 'franklin field'], ['1962', 'september 23', 'new york giants', '29 - 13', 'philadelphia eagles', 'franklin field'], ['1962', 'november 18', 'new york giants', '19 - 14', 'philadelphia eagles', 'yankee stadium'], ['1963', 'september 29', 'new york giants', '37 - 14', 'philadelphia eagles', 'franklin field'], ['1963', 'november 10', 'new york giants', '42 - 14', 'philadelphia eagles', 'yankee stadium'], ['1964', 'september 13', 'philadelphia eagles', '38 - 7', 'new york giants', 'franklin field'], ['1964', 'october 18', 'new york giants', '23 - 17', 'philadelphia eagles', 'yankee stadium'], ['1965', 'september 26', 'new york giants', '16 - 14', 'philadelphia eagles', 'franklin field'], ['1965', 'october 17', 'new york giants', '35 - 27', 'philadelphia eagles', 'yankee stadium'], ['1966', 'september 25', 'philadelphia eagles', '35 - 17', 'new york giants', 'franklin field'], ['1966', 'october 23', 'philadelphia eagles', '31 - 3', 'new york giants', 'yankee stadium'], ['1967', 'november 26', 'new york giants', '44 - 7', 'philadelphia eagles', 'yankee stadium'], ['1968', 'september 22', 'new york giants', '34 - 25', 'philadelphia eagles', 'franklin field'], ['1968', 'november 17', 'new york giants', '7 - 6', 'philadelphia eagles', 'yankee stadium'], ['1969', 'october 5', 'philadelphia eagles', '23 - 20', 'new york giants', 'yankee stadium']] |
1968 vfl season | https://en.wikipedia.org/wiki/1968_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10808933-8.html.csv | majority | most melbourne-in-name teams played as away teams during the 1968 vfl season . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'melbourne', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'away team', 'melbourne'], 'result': True, 'ind': 0, 'tointer': 'for the away team records of all rows , most of them fuzzily match to melbourne .', 'tostr': 'most_eq { all_rows ; away team ; melbourne } = true'} | most_eq { all_rows ; away team ; melbourne } = true | for the away team records of all rows , most of them fuzzily match to melbourne . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'away team_3': 3, 'melbourne_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'away team_3': 'away team', 'melbourne_4': 'melbourne'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'away team_3': [0], 'melbourne_4': [0]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['footscray', '9.8 ( 62 )', 'south melbourne', '11.9 ( 75 )', 'western oval', '14755', '8 june 1968'], ['collingwood', '11.13 ( 79 )', 'melbourne', '13.7 ( 85 )', 'victoria park', '24375', '8 june 1968'], ['north melbourne', '9.11 ( 65 )', 'geelong', '13.11 ( 89 )', 'arden street oval', '13209', '8 june 1968'], ['richmond', '11.15 ( 81 )', 'hawthorn', '11.14 ( 80 )', 'mcg', '31325', '10 june 1968'], ['st kilda', '16.17 ( 113 )', 'essendon', '8.9 ( 57 )', 'moorabbin oval', '43231', '10 june 1968'], ['fitzroy', '4.10 ( 34 )', 'carlton', '13.15 ( 93 )', 'princes park', '19306', '10 june 1968']] |
list of shortest people | https://en.wikipedia.org/wiki/List_of_shortest_people | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14229697-6.html.csv | count | only two of the athletes were in wrestling . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'wrestling', 'result': '2', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'sport', 'wrestling'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose sport record fuzzily matches to wrestling .', 'tostr': 'filter_eq { all_rows ; sport ; wrestling }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; sport ; wrestling } }', 'tointer': 'select the rows whose sport record fuzzily matches to wrestling . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; sport ; wrestling } } ; 2 } = true', 'tointer': 'select the rows whose sport record fuzzily matches to wrestling . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; sport ; wrestling } } ; 2 } = true | select the rows whose sport record fuzzily matches to wrestling . 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, 'sport_5': 5, 'wrestling_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', 'sport_5': 'sport', 'wrestling_6': 'wrestling', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'sport_5': [0], 'wrestling_6': [0], '2_7': [2]} | ['nationality', 'height', 'name', 'sport', 'lifespan'] | [['india', 'cm ( in )', 'aditya romeo dev', 'bodybuilding', '1988 - 2012'], ['canada', 'cm ( in )', 'henry franklyn', 'ice hockey', 'late 19th century'], ['united states', 'cm ( in )', 'eddie gaedel', 'baseball', '1925 - 1961'], ['canada', 'cm ( in )', 'lionel giroux', 'wrestling', '1935 - 1995'], ['united states', 'cm ( in )', 'dylan postl', 'wrestling', '1986 -'], ['united states', 'cm ( in )', 'julie krone', 'horse racing', '1963 -'], ['england', 'cm ( in )', 'tich cornford', 'cricket', '1900 - 1964'], ['australia', 'cm ( in )', 'jim bradford', 'australian rules football', '1926 - 2005'], ['united states', 'cm ( in )', 'jack shapiro', 'american football', '1907 - 2001'], ['united kingdom', 'cm ( in )', 'frederick walden', 'association football', '1888 - 1949'], ['united states', 'cm ( in )', 'shannon bobbitt', 'basketball', '1985 -'], ['united states', 'cm ( in )', 'muggsy bogues', 'basketball ( inactive )', '1965 -'], ['canada', 'cm ( in )', 'roy worters', 'ice hockey', '1900 - 1957'], ['united states', 'cm ( in )', 'earl boykins', 'basketball ( active )', '1976 -'], ['united states', 'cm ( in )', 'trindon holliday', 'american football', '1986 -']] |
thor - christian ebbesvik | https://en.wikipedia.org/wiki/Thor-Christian_Ebbesvik | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-20398823-1.html.csv | aggregation | the average number of wins that thor-christian ebbesvik had was .44 . | {'scope': 'all', 'col': '5', 'type': 'average', 'result': '.44', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'wins'], 'result': '.44', 'ind': 0, 'tostr': 'avg { all_rows ; wins }'}, '.44'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; wins } ; .44 } = true', 'tointer': 'the average of the wins record of all rows is .44 .'} | round_eq { avg { all_rows ; wins } ; .44 } = true | the average of the wins record of all rows is .44 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'wins_4': 4, '.44_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'wins_4': 'wins', '.44_5': '.44'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'wins_4': [0], '.44_5': [1]} | ['season', 'series', 'team', 'races', 'wins', 'poles', 'f / laps', 'podiums', 'points', 'position'] | [['2005', 'british formula ford championship', 'team jlr', '20', '0', '0', '0', '0', '321', '6th'], ['2005', 'formula ford festival', 'team jlr', '1', '0', '0', '0', '0', 'n / a', 'nc'], ['2006', 'british formula ford championship', 'team jlr', '20', '1', '0', '2', '4', '357', '4th'], ['2006', 'formula ford festival - duratec class', 'team jlr', '1', '0', '0', '0', '0', 'n / a', 'nc'], ['2007', 'spanish formula three championship', 'team west - tec', '14', '0', '0', '0', '0', '7', '16th'], ['2008', 'spanish formula three championship', 'team west - tec', '17', '2', '1', '0', '2', '49', '10th'], ['2009', 'european f3 open championship', 'team west - tec', '16', '1', '1', '1', '3', '64', '5th'], ['2009', 'formula le mans cup', 'hope polevision racing', '2', '0', '0', '0', '0', '16', '20th'], ['2010', 'le mans series - lmp2', 'team bruichladdich', '5', '0', '0', '0', '1', '46', '5th']] |
croatian international | https://en.wikipedia.org/wiki/Croatian_International | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-12164707-1.html.csv | count | vincent laigle and svetoslav stoyanov won the mens doubles in the croatian international a total of two times . | {'scope': 'all', 'criterion': 'equal', 'value': 'vincent laigle svetoslav stoyanov', 'result': '2', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'mens doubles', 'vincent laigle svetoslav stoyanov'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose mens doubles record fuzzily matches to vincent laigle svetoslav stoyanov .', 'tostr': 'filter_eq { all_rows ; mens doubles ; vincent laigle svetoslav stoyanov }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; mens doubles ; vincent laigle svetoslav stoyanov } }', 'tointer': 'select the rows whose mens doubles record fuzzily matches to vincent laigle svetoslav stoyanov . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; mens doubles ; vincent laigle svetoslav stoyanov } } ; 2 } = true', 'tointer': 'select the rows whose mens doubles record fuzzily matches to vincent laigle svetoslav stoyanov . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; mens doubles ; vincent laigle svetoslav stoyanov } } ; 2 } = true | select the rows whose mens doubles record fuzzily matches to vincent laigle svetoslav stoyanov . 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, 'mens doubles_5': 5, 'vincent laigle svetoslav stoyanov_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', 'mens doubles_5': 'mens doubles', 'vincent laigle svetoslav stoyanov_6': 'vincent laigle svetoslav stoyanov', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'mens doubles_5': [0], 'vincent laigle svetoslav stoyanov_6': [0], '2_7': [2]} | ['year', 'mens singles', 'womens singles', 'mens doubles', 'womens doubles', 'mixed doubles'] | [['1999', 'marvin steve', 'maja pohar', 'dmitry miznikov valery strelcov', 'natalja esipenko natalia golovkina', 'valery strelcov natalia golovkina'], ['2000', 'richard vaughan', 'anu weckstrom', 'michał łogosz robert mateusiak', 'felicity gallup joanne muggeridge', 'michael beres kara solmudson'], ['2001', 'oliver pongratz', 'karina de wit', 'kristof hopp thomas tesche', 'erica van den heuvel nicole van hooren', 'peter steffensen lene mork'], ['2002', 'przemysław wacha', 'petya nedelcheva', 'vincent laigle svetoslav stoyanov', 'tammy jenkins rhona robertson', 'russel hogg kirsteen mcewan'], ['2003', 'hendra wijaya', 'pi hongyan', 'vincent laigle svetoslav stoyanov', 'miyuki tai yoshiko iwata', 'carsten mogensen kamilla rytter juhl'], ['2004', 'hidetaka yamada', 'li li', 'daniel glaser dennis von dahn', 'jiang yanmei li li', 'svetoslav stoyanov victoria wright'], ['2005', 'holvy de pauw', 'miyo akao', 'simon mollyhus anders kristiansen', 'frances liu fan shinta mulia sari', 'hendra wijaya frances liu fan'], ['2006', 'andrew smith', 'petya nedelcheva', 'chris tonks chris langridge', 'liza parker jenny day', 'chris langridge jenny day'], ['2007', 'carl baxter', 'guo xin', 'wouter claes frederic mawet', 'cai jiani guo xin', 'wouter claes nathalie descamps'], ['2008', 'ville lång', 'kaori imabeppu', 'rupesh kumar sanave thomas', 'maria thorberg kati tolmoff', 'baptiste careme laura choinet'], ['2009', 'peter mikkelsen', 'anita raj kaur', 'mads conrad - petersen mads pieler kolding', 'ezgi epice claudia vogelsang', 'zvonimir djurkinjak stasa poznanovic'], ['2010', 'ben beckman', 'nicole grether', 'joe morgan james phillips', 'nicole grether charmaine reid', 'zvonimir djurkinjak stasa poznanovic'], ['2011', 'dieter domke', 'minatsu mitani', 'kim astrup sorensen rasmus fladberg', 'sandra - maria jensen line kjaersfeldt', 'zvonimir djurkinjak stasa poznanovic']] |
1953 masters tournament | https://en.wikipedia.org/wiki/1953_Masters_Tournament | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13073611-2.html.csv | majority | the majority of the players in the 1953 tournament were from the united states . | {'scope': 'all', 'col': '3', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'united states', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'country', 'united states'], 'result': True, 'ind': 0, 'tointer': 'for the country records of all rows , all of them fuzzily match to united states .', 'tostr': 'all_eq { all_rows ; country ; united states } = true'} | all_eq { all_rows ; country ; united states } = true | for the country records of all rows , all of them fuzzily match to united states . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'country_3': 3, 'united states_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'country_3': 'country', 'united states_4': 'united states'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'country_3': [0], 'united states_4': [0]} | ['place', 'player', 'country', 'score', 'to par'] | [['1', 'ben hogan', 'united states', '70 + 69 = 139', '- 5'], ['2', 'bob hamilton', 'united states', '71 + 69 = 140', '- 4'], ['t3', 'chick harbert', 'united states', '68 + 73 = 141', '- 3'], ['t3', 'ted kroll', 'united states', '71 + 70 = 141', '- 3'], ['t5', 'lloyd mangrum', 'united states', '74 + 68 = 142', '- 2'], ['t5', 'milan marusic', 'united states', '70 + 72 = 142', '- 2'], ['t5', 'ed oliver', 'united states', '69 + 73 = 142', '- 2'], ['t8', 'al besselink', 'united states', '69 + 75 = 144', 'e'], ['t8', 'julius boros', 'united states', '73 + 71 = 144', 'e'], ['t8', 'lew worsham', 'united states', '74 + 70 = 144', 'e']] |
alberta senate nominee election , 2004 | https://en.wikipedia.org/wiki/Alberta_Senate_nominee_election%2C_2004 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1202333-1.html.csv | aggregation | candidates in the alberta senate nominee election of 2004 received a combined total of 2176341 votes . | {'scope': 'all', 'col': '3', 'type': 'sum', 'result': '2176341', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'votes'], 'result': '2176341', 'ind': 0, 'tostr': 'sum { all_rows ; votes }'}, '2176341'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; votes } ; 2176341 } = true', 'tointer': 'the sum of the votes record of all rows is 2176341 .'} | round_eq { sum { all_rows ; votes } ; 2176341 } = true | the sum of the votes record of all rows is 2176341 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'votes_4': 4, '2176341_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'votes_4': 'votes', '2176341_5': '2176341'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'votes_4': [0], '2176341_5': [1]} | ['candidate', 'party', 'votes', 'votes %', 'ballots %', 'elected', 'appointed'] | [['bert brown', 'progressive conservative', '312041', '14.3 %', '43.7 %', 'x', 'july 10 , 2007'], ['betty unger', 'progressive conservative', '311964', '14.3 %', '43.6 %', 'x', 'january 6 , 2012'], ['cliff breitkreuz', 'progressive conservative', '241306', '11.1 %', '33.8 %', 'x', 'term ended march 26 , 2012'], ['link byfield', 'independent', '238751', '11.0 %', '33.4 %', 'x', 'resigned november 2010'], ['jim silye', 'progressive conservative', '217857', '10.0 %', '30.5 %', '30.5 %', '30.5 %'], ['david usherwood', 'progressive conservative', '193056', '8.9 %', '27.0 %', '27.0 %', '27.0 %'], ['michael roth', 'alberta alliance', '176339', '8.1 %', '24.7 %', '24.7 %', '24.7 %'], ['vance gough', 'alberta alliance', '167770', '7.7 %', '23.5 %', '23.5 %', '23.5 %'], ['tom sindlinger', 'independent', '161082', '7.4 %', '22.5 %', '22.5 %', '22.5 %'], ['gary horan', 'alberta alliance', '156175', '7.2 %', '21.9 %', '21.9 %', '21.9 %']] |
steam locomotives of ireland | https://en.wikipedia.org/wiki/Steam_locomotives_of_Ireland | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1290024-14.html.csv | majority | most of the steam locomotives of ireland were made before the 1900s . | {'scope': 'all', 'col': '6', 'most_or_all': 'most', 'criterion': 'less_than', 'value': '1900', 'subset': None} | {'func': 'most_less', 'args': ['all_rows', 'date made', '1900'], 'result': True, 'ind': 0, 'tointer': 'for the date made records of all rows , most of them are less than 1900 .', 'tostr': 'most_less { all_rows ; date made ; 1900 } = true'} | most_less { all_rows ; date made ; 1900 } = true | for the date made records of all rows , most of them are less than 1900 . | 1 | 1 | {'most_less_0': 0, 'result_1': 1, 'all_rows_2': 2, 'date made_3': 3, '1900_4': 4} | {'most_less_0': 'most_less', 'result_1': 'true', 'all_rows_2': 'all_rows', 'date made_3': 'date made', '1900_4': '1900'} | {'most_less_0': [1], 'result_1': [], 'all_rows_2': [0], 'date made_3': [0], '1900_4': [0]} | ['class', 'type', 'names', 'quantity made', 'manufacturer', 'date made'] | [['pioneer', '0 - 6 - 2t', 'pioneer sligo', '2', 'avonside engine co', '1877'], ['leitrim', '0 - 6 - 4t', 'fermanagh leitrim lurganboy lissadell hazlewood', '5', 'beyer , peacock & co', '1882 - 1899'], ['erne', '4 - 4 - 0t', 'erne', '1', 'hudswell clarke', '1883'], ['faugh - a - ballagh', '0 - 4 - 0st', 'faugh - a - ballagh', '1', 'hunslet engine co', '1878'], ['waterford', '0 - 6 - 0t', 'waterford', '1', 'hunslet engine co', '1893'], ['sir henry', '0 - 6 - 4t', 'sir henry enniskillen lough gill', '3', 'beyer , peacock & co', '1904 - 1917'], ['glencar', '4 - 4 - 0', 'blacklion glencar', '( 2 )', 'beyer , peacock & co', '1885 - 87'], ['sligo', '0 - 6 - 0', 'glencar a sligo sligo', '( 3 )', 'beyer , peacock & co', '1882 - 1890'], ['lough', '0 - 6 - 4t', 'lough melvin lough erne', '2', 'beyer , peacock & co', '1949']] |
2003 - 04 toronto raptors season | https://en.wikipedia.org/wiki/2003%E2%80%9304_Toronto_Raptors_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-15869204-7.html.csv | superlative | during this period of the 2003-04 toronto raptors season , the toronto raptors experienced their highest game attendance on february 1st in their game against the la lakers . | {'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', 'location attendance'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; location attendance }'}, 'team'], 'result': 'la lakers', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; location attendance } ; team }'}, 'la lakers'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; location attendance } ; team } ; la lakers } = true', 'tointer': 'select the row whose location attendance record of all rows is maximum . the team record of this row is la lakers .'} | eq { hop { argmax { all_rows ; location attendance } ; team } ; la lakers } = true | select the row whose location attendance record of all rows is maximum . the team record of this row is la lakers . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'location attendance_5': 5, 'team_6': 6, 'la lakers_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'location attendance_5': 'location attendance', 'team_6': 'team', 'la lakers_7': 'la lakers'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'location attendance_5': [0], 'team_6': [1], 'la lakers_7': [2]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record'] | [['45', 'february 1', 'la lakers', 'l 83 - 84 ( ot )', 'vince carter ( 27 )', 'chris bosh ( 14 )', 'morris peterson ( 4 )', 'air canada centre 20116', '21 - 24'], ['46', 'february 3', 'philadelphia', 'w 93 - 80 ( ot )', 'vince carter ( 33 )', 'donyell marshall ( 14 )', 'jalen rose ( 5 )', 'wachovia center 19049', '22 - 24'], ['47', 'february 4', 'orlando', 'w 110 - 90 ( ot )', 'donyell marshall ( 32 )', 'jérôme moïso ( 12 )', 'vince carter ( 9 )', 'air canada centre 16228', '23 - 24'], ['48', 'february 6', 'indiana', 'l 77 - 83 ( ot )', 'donyell marshall ( 24 )', 'jérôme moïso ( 11 )', 'vince carter ( 6 )', 'air canada centre 19311', '23 - 25'], ['49', 'february 8', 'golden state', 'w 84 - 81 ( ot )', 'vince carter ( 22 )', 'donyell marshall ( 13 )', 'vince carter ( 4 )', 'the arena in oakland 16873', '24 - 25'], ['50', 'february 10', 'phoenix', 'w 101 - 94 ( ot )', 'vince carter ( 29 )', 'donyell marshall ( 11 )', 'vince carter ( 6 )', 'america west arena 14138', '25 - 25'], ['51', 'february 12', 'seattle', 'l 74 - 94 ( ot )', 'alvin williams ( 20 )', 'donyell marshall ( 17 )', 'vince carter ( 7 )', 'keyarena 14239', '25 - 26'], ['52', 'february 17', 'chicago', 'l 73 - 75 ( ot )', 'vince carter ( 21 )', 'donyell marshall ( 24 )', 'alvin williams ( 6 )', 'united center 17822', '25 - 27'], ['53', 'february 18', 'san antonio', 'l 82 - 86 ( ot )', 'vince carter ( 22 )', 'donyell marshall ( 11 )', 'vince carter ( 6 )', 'air canada centre 17119', '25 - 28'], ['54', 'february 20', 'new jersey', 'l 72 - 91 ( ot )', 'donyell marshall ( 17 )', 'donyell marshall ( 13 )', 'alvin williams ( 6 )', 'air canada centre 19301', '25 - 29'], ['55', 'february 22', 'sacramento', 'l 81 - 96 ( ot )', 'chris bosh ( 20 )', 'donyell marshall ( 13 )', 'alvin williams ( 9 )', 'air canada centre 19800', '25 - 30'], ['56', 'february 24', 'new jersey', 'l 74 - 86 ( ot )', 'roger mason ( 18 )', 'jérôme moïso , morris peterson ( 6 )', 'milt palacio ( 5 )', 'continental airlines arena 12829', '25 - 31'], ['57', 'february 25', 'washington', 'l 74 - 76 ( ot )', 'donyell marshall ( 20 )', 'chris bosh ( 9 )', 'roger mason ( 6 )', 'air canada centre 17291', '25 - 32'], ['58', 'february 27', 'boston', 'l 75 - 88 ( ot )', 'donyell marshall ( 19 )', 'donyell marshall ( 13 )', 'roger mason , milt palacio ( 4 )', 'fleetcenter 16681', '25 - 33']] |
fady maalouf | https://en.wikipedia.org/wiki/Fady_Maalouf | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18490880-1.html.csv | majority | in may 2008 on deutschland sucht den superstar , yesterday was the only song by the beatles that fady maalouf performed . | {'scope': 'subset', 'col': '4', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'beatles', 'subset': {'col': '1', 'criterion': 'fuzzily_match', 'value': 'may 2008'}} | {'func': 'all_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', 'may 2008'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; date ; may 2008 }', 'tointer': 'select the rows whose date record fuzzily matches to may 2008 .'}, 'original artist', 'beatles'], 'result': True, 'ind': 1, 'tointer': 'select the rows whose date record fuzzily matches to may 2008 . for the original artist records of these rows , all of them fuzzily match to beatles .', 'tostr': 'all_eq { filter_eq { all_rows ; date ; may 2008 } ; original artist ; beatles } = true'} | all_eq { filter_eq { all_rows ; date ; may 2008 } ; original artist ; beatles } = true | select the rows whose date record fuzzily matches to may 2008 . for the original artist records of these rows , all of them fuzzily match to beatles . | 2 | 2 | {'all_str_eq_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, 'date_4': 4, 'may 2008_5': 5, 'original artist_6': 6, 'beatles_7': 7} | {'all_str_eq_1': 'all_str_eq', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'date_4': 'date', 'may 2008_5': 'may 2008', 'original artist_6': 'original artist', 'beatles_7': 'beatles'} | {'all_str_eq_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'date_4': [0], 'may 2008_5': [0], 'original artist_6': [1], 'beatles_7': [1]} | ['date', 'topic of the show', 'song', 'original artist', 'place / percentage'] | [['march 8 , 2008', 'top 15 show : jetzt oder nie', 'home', 'michael bublé', '8 , 55 % ( 2 / 15 )'], ['march 15 , 2008', 'current hits', 'helpless when she smiles', 'backstreet boys', '7 , 08 % ( 4 / 10 )'], ['march 22 , 2008', 'greatest film hits', "she 's like the wind", 'patrick swayze', '21 , 09 % ( 2 / 9 )'], ['april 5 , 2008', 'mariah carey and take that', 'back for good', 'take that', '8 , 54 % ( 3 / 8 )'], ['april 12 , 2008', 'greatest hits', 'your song', 'elton john', '13 , 91 % ( 3 / 7 )'], ['april 19 , 2008', "judges ' choice", 'we have a dream', 'pop idol', '12 , 98 % ( 3 / 6 )'], ['april 26 , 2008', 'party songs and ballads', 'never gon na give you up', 'rick astley', '16 , 69 % ( 2 / 5 )'], ['april 26 , 2008', 'party songs and ballads', 'all by myself', 'eric carmen', '16 , 69 % ( 2 / 5 )'], ['may 3 , 2008', 'germany vs england', 'und wenn ein lied', 'söhne mannheims', '19 , 22 % ( 3 / 4 )'], ['may 3 , 2008', 'germany vs england', 'breathe easy', 'blue', '19 , 22 % ( 3 / 4 )'], ['may 10 , 2008', 'no 1 hits , the beatles , dedications', 'you raise me up', 'westlife', '30 , 32 % ( 2 / 3 )'], ['may 10 , 2008', 'no 1 hits , the beatles , dedications', 'yesterday', 'the beatles', '30 , 32 % ( 2 / 3 )'], ['may 10 , 2008', 'no 1 hits , the beatles , dedications', 'feeling good', 'michael bublé', '30 , 32 % ( 2 / 3 )'], ['may 17 , 2008', 'final', 'careless whisper', 'george michael', '2 / 2 by 37 , 80 %'], ['may 17 , 2008', 'final', "she 's like the wind", 'patrick swayze', '2 / 2 by 37 , 80 %'], ['may 17 , 2008', 'final', 'blessed', 'fady maalouf', '2 / 2 by 37 , 80 %']] |
1961 ohio state buckeyes football team | https://en.wikipedia.org/wiki/1961_Ohio_State_Buckeyes_football_team | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17814506-1.html.csv | count | during the 1961 season , there were three times that the ohio state buckeyes football team was ranked 3rd . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': '3', 'result': '3', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'rank', '3'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose rank record fuzzily matches to 3 .', 'tostr': 'filter_eq { all_rows ; rank ; 3 }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; rank ; 3 } }', 'tointer': 'select the rows whose rank record fuzzily matches to 3 . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; rank ; 3 } } ; 3 } = true', 'tointer': 'select the rows whose rank record fuzzily matches to 3 . the number of such rows is 3 .'} | eq { count { filter_eq { all_rows ; rank ; 3 } } ; 3 } = true | select the rows whose rank record fuzzily matches to 3 . 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, 'rank_5': 5, '3_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', 'rank_5': 'rank', '3_6': '3', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'rank_5': [0], '3_6': [0], '3_7': [2]} | ['date', 'opponent', 'rank', 'site', 'result', 'attendance'] | [['september 30', 'texas christian', '3', 'ohio stadium columbus , oh', 't7 - 7', '82878'], ['october 7', 'ucla', '8', 'ohio stadium columbus , oh', 'w13 - 3', '82992'], ['october 14', 'illinois', '7', 'ohio stadium columbus , oh', 'w44 - 0', '82374'], ['october 21', 'northwestern', '7', 'dyche stadium evanston , il', 'w10 - 0', '43259'], ['october 28', 'wisconsin', '6', 'camp randall stadium madison , wi', 'w30 - 21', '58411'], ['november 4', '9 iowa', '5', 'ohio stadium columbus , oh', 'w29 - 13', '83795'], ['november 11', 'indiana', '3', 'memorial stadium bloomington , in', 'w16 - 7', '27108'], ['november 18', 'oregon', '3', 'ohio stadium columbus , oh', 'w22 - 12', '82073'], ['november 25', 'michigan', '2', 'michigan stadium ann arbor , mi', 'w50 - 20', '80444']] |
partnership ( cricket ) | https://en.wikipedia.org/wiki/Partnership_%28cricket%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1670921-1.html.csv | ordinal | the second most runs scored were by the players from india . | {'row': '2', 'col': '2', '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', 'runs', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; runs ; 2 }'}, 'fielding team'], 'result': 'india', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; runs ; 2 } ; fielding team }'}, 'india'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; runs ; 2 } ; fielding team } ; india } = true', 'tointer': 'select the row whose runs record of all rows is 2nd maximum . the fielding team record of this row is india .'} | eq { hop { nth_argmax { all_rows ; runs ; 2 } ; fielding team } ; india } = true | select the row whose runs record of all rows is 2nd maximum . the fielding team record of this row is india . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'runs_5': 5, '2_6': 6, 'fielding team_7': 7, 'india_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'runs_5': 'runs', '2_6': '2', 'fielding team_7': 'fielding team', 'india_8': 'india'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'runs_5': [0], '2_6': [0], 'fielding team_7': [1], 'india_8': [2]} | ['wicket', 'runs', 'battling partners', 'battling team', 'fielding team', 'venue', 'season'] | [['1st', '415', 'gc smith and neil mckenzie', 'south africa', 'bangladesh', 'chittagong', '2008'], ['2nd', '576', 'roshan mahanama and sanath jayasuriya', 'sri lanka', 'india', 'colombo', '1997'], ['3rd', '624', 'mahela jayawardene and kumar sangakkara', 'sri lanka', 'south africa', 'colombo', '2006'], ['4th', '437', 'mahela jayawardene and thilan samaraweera', 'sri lanka', 'pakistan', 'karachi', '2008 / 09'], ['5th', '405', 'donald bradman and sid barnes', 'australia', 'england', 'sydney', '1946 / 47'], ['6th', '351', 'mahela jayawardene and prasanna jayawardene', 'sri lanka', 'india', 'ahmedabad', '2009 / 10'], ['7th', '347', 'clairmonte depeiaza and denis atkinson', 'west indies', 'australia', 'bridgetown', '1954 / 55'], ['8th', '332', 'jonathan trott and stuart broad', 'england', 'pakistan', "lord 's", '2010'], ['9th', '195', 'pat symcox and mark boucher', 'south africa', 'pakistan', 'johannesburg', '1997 / 98'], ['10th', '163', 'phillip hughes and ashton agar', 'australia', 'england', 'nottingham', '2013']] |
teo fabi | https://en.wikipedia.org/wiki/Teo_Fabi | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1218368-3.html.csv | comparative | teo fabi completed more laps in the 1990s when compared to the 1980s . | {'row_1': '6', 'row_2': '2', 'col': '6', 'col_other': '1', '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', 'year', '1993'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose year record fuzzily matches to 1993 .', 'tostr': 'filter_eq { all_rows ; year ; 1993 }'}, 'laps'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; year ; 1993 } ; laps }', 'tointer': 'select the rows whose year record fuzzily matches to 1993 . take the laps record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'year', '1982'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose year record fuzzily matches to 1982 .', 'tostr': 'filter_eq { all_rows ; year ; 1982 }'}, 'laps'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; year ; 1982 } ; laps }', 'tointer': 'select the rows whose year record fuzzily matches to 1982 . take the laps record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; year ; 1993 } ; laps } ; hop { filter_eq { all_rows ; year ; 1982 } ; laps } }', 'tointer': 'select the rows whose year record fuzzily matches to 1993 . take the laps record of this row . select the rows whose year record fuzzily matches to 1982 . take the laps 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', 'year', '1993'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose year record fuzzily matches to 1993 .', 'tostr': 'filter_eq { all_rows ; year ; 1993 }'}, 'laps'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; year ; 1993 } ; laps }', 'tointer': 'select the rows whose year record fuzzily matches to 1993 . take the laps record of this row .'}, '374'], 'result': True, 'ind': 5, 'tostr': 'eq { hop { filter_eq { all_rows ; year ; 1993 } ; laps } ; 374 }', 'tointer': 'the laps record of the first row is 374 .'}, {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'year', '1982'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose year record fuzzily matches to 1982 .', 'tostr': 'filter_eq { all_rows ; year ; 1982 }'}, 'laps'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; year ; 1982 } ; laps }', 'tointer': 'select the rows whose year record fuzzily matches to 1982 . take the laps record of this row .'}, '92'], 'result': True, 'ind': 6, 'tostr': 'eq { hop { filter_eq { all_rows ; year ; 1982 } ; laps } ; 92 }', 'tointer': 'the laps record of the second row is 92 .'}], 'result': True, 'ind': 7, 'tostr': 'and { eq { hop { filter_eq { all_rows ; year ; 1993 } ; laps } ; 374 } ; eq { hop { filter_eq { all_rows ; year ; 1982 } ; laps } ; 92 } }', 'tointer': 'the laps record of the first row is 374 . the laps record of the second row is 92 .'}], 'result': True, 'ind': 8, 'tostr': 'and { greater { hop { filter_eq { all_rows ; year ; 1993 } ; laps } ; hop { filter_eq { all_rows ; year ; 1982 } ; laps } } ; and { eq { hop { filter_eq { all_rows ; year ; 1993 } ; laps } ; 374 } ; eq { hop { filter_eq { all_rows ; year ; 1982 } ; laps } ; 92 } } } = true', 'tointer': 'select the rows whose year record fuzzily matches to 1993 . take the laps record of this row . select the rows whose year record fuzzily matches to 1982 . take the laps record of this row . the first record is greater than the second record . the laps record of the first row is 374 . the laps record of the second row is 92 .'} | and { greater { hop { filter_eq { all_rows ; year ; 1993 } ; laps } ; hop { filter_eq { all_rows ; year ; 1982 } ; laps } } ; and { eq { hop { filter_eq { all_rows ; year ; 1993 } ; laps } ; 374 } ; eq { hop { filter_eq { all_rows ; year ; 1982 } ; laps } ; 92 } } } = true | select the rows whose year record fuzzily matches to 1993 . take the laps record of this row . select the rows whose year record fuzzily matches to 1982 . take the laps record of this row . the first record is greater than the second record . the laps record of the first row is 374 . the laps record of the second row is 92 . | 13 | 9 | {'and_8': 8, 'result_9': 9, 'greater_4': 4, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_10': 10, 'year_11': 11, '1993_12': 12, 'laps_13': 13, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_14': 14, 'year_15': 15, '1982_16': 16, 'laps_17': 17, 'and_7': 7, 'eq_5': 5, '374_18': 18, 'eq_6': 6, '92_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', 'year_11': 'year', '1993_12': '1993', 'laps_13': 'laps', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_14': 'all_rows', 'year_15': 'year', '1982_16': '1982', 'laps_17': 'laps', 'and_7': 'and', 'eq_5': 'eq', '374_18': '374', 'eq_6': 'eq', '92_19': '92'} | {'and_8': [9], 'result_9': [], 'greater_4': [8], 'num_hop_2': [4, 5], 'filter_str_eq_0': [2], 'all_rows_10': [0], 'year_11': [0], '1993_12': [0], 'laps_13': [2], 'num_hop_3': [4, 6], 'filter_str_eq_1': [3], 'all_rows_14': [1], 'year_15': [1], '1982_16': [1], 'laps_17': [3], 'and_7': [8], 'eq_5': [7], '374_18': [5], 'eq_6': [7], '92_19': [6]} | ['year', 'class', 'tyres', 'team', 'co - drivers', 'laps', 'pos', 'class pos'] | [['1980', 'gr5', 'p', 'scuderia lancia corse', 'hans heyer bernard darniche', '6', 'dnf', 'dnf'], ['1982', 'gr6', 'p', 'martini racing', 'michele alboreto rolf stommelen', '92', 'dnf', 'dnf'], ['1983', 'c', 'd', 'martini lancia', 'michele alboreto alessandro nannini', '27', 'dnf', 'dnf'], ['1991', 'c2', 'g', 'silk cut jaguar tom walkinshaw racing', 'bob wollek kenny acheson', '358', '3rd', '3rd'], ['1992', 'c1', 'g', "toyota team tom 's", 'jan lammers andy wallace', '331', '8th', '5th'], ['1993', 'c1', 'm', 'peugeot talbot sport', 'thierry boutsen yannick dalmas', '374', '2nd', '2nd']] |
matt baker ( television presenter ) | https://en.wikipedia.org/wiki/Matt_Baker_%28television_presenter%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1014319-1.html.csv | majority | most of matt baker 's dances scored over an 8 from goodman . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'greater_than', 'value': '8', 'subset': None} | {'func': 'most_greater', 'args': ['all_rows', 'goodman', '8'], 'result': True, 'ind': 0, 'tointer': 'for the goodman records of all rows , most of them are greater than 8 .', 'tostr': 'most_greater { all_rows ; goodman ; 8 } = true'} | most_greater { all_rows ; goodman ; 8 } = true | for the goodman records of all rows , most of them are greater than 8 . | 1 | 1 | {'most_greater_0': 0, 'result_1': 1, 'all_rows_2': 2, 'goodman_3': 3, '8_4': 4} | {'most_greater_0': 'most_greater', 'result_1': 'true', 'all_rows_2': 'all_rows', 'goodman_3': 'goodman', '8_4': '8'} | {'most_greater_0': [1], 'result_1': [], 'all_rows_2': [0], 'goodman_3': [0], '8_4': [0]} | ['week', 'dance / song', 'horwood', 'goodman', 'dixon', 'tonioli', 'total', 'result'] | [['1', "cha - cha - cha / ai n't no mountain high enough", '7', '8', '8', '8', '31', 'n / a'], ['2', 'foxtrot / she said', '7', '8', '8', '8', '31', 'safe'], ['3', 'quickstep / dreaming of you', '8', '7', '8', '8', '31', 'safe'], ['4', 'charleston / forty - second street', '9', '9', '9', '8', '35', 'safe'], ['5', 'argentine tango / bat out of hell', '8', '8', '9', '9', '34', 'safe'], ['6', 'viennese waltz / where the wild roses grow', '8', '9', '9', '9', '35', 'safe'], ['7', 'rumba / too lost in you', '8', '9', '9', '9', '35', 'safe'], ['8', 'samba / young hearts run free', '9', '9', '10', '10', '38', 'safe'], ['10', 'jive / soul bossa nova', '8', '9', '9', '9', '35', 'safe'], ['11', 'salsa / spinning around', '7', '7', '7', '7', '28', 'safe'], ['11', 'swing / in the mood', 'n / a', 'n / a', 'n / a', 'n / a', '2nd / 4 points', 'safe'], ['11', 'tango / hung up', '9', '10', '10', '9', '38', 'safe'], ['12', 'samba / young hearts run free', '9', '9', '10', '10', '38', 'second place'], ['12', 'showdance / i like the way ( you move )', '7', '9', '9', '9', '34', 'second place'], ['12', "paso doble / do n't let me be misunderstood", '9', '8', '9', '9', '35', 'second place']] |
sunshine state conference | https://en.wikipedia.org/wiki/Sunshine_State_Conference | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1183842-1.html.csv | superlative | nova southeastern university has the most enrollment among institutions in the sunshine state conference . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '6', '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', 'enrollment'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; enrollment }'}, 'institution'], 'result': 'nova southeastern university', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; enrollment } ; institution }'}, 'nova southeastern university'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; enrollment } ; institution } ; nova southeastern university } = true', 'tointer': 'select the row whose enrollment record of all rows is maximum . the institution record of this row is nova southeastern university .'} | eq { hop { argmax { all_rows ; enrollment } ; institution } ; nova southeastern university } = true | select the row whose enrollment record of all rows is maximum . the institution record of this row is nova southeastern university . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'enrollment_5': 5, 'institution_6': 6, 'nova southeastern university_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'enrollment_5': 'enrollment', 'institution_6': 'institution', 'nova southeastern university_7': 'nova southeastern university'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'enrollment_5': [0], 'institution_6': [1], 'nova southeastern university_7': [2]} | ['institution', 'location', 'founded', 'type', 'enrollment', 'nickname', 'joined'] | [['barry university', 'miami shores , florida', '1940', 'private', '9300', 'buccaneers', '1988'], ['eckerd college', 'st petersburg , florida', '1958', 'private', '3584', 'tritons', '1975'], ['florida southern college', 'lakeland , florida', '1883', 'private', '3488', 'moccasins', '1975'], ['florida institute of technology', 'melbourne , florida', '1958', 'private', '7626', 'panthers', '1981'], ['lynn university', 'boca raton , florida', '1962', 'private', '4660', 'fighting knights', '1997'], ['nova southeastern university', 'davie , florida', '1964', 'private', '33135', 'sharks', '2002'], ['rollins college', 'winter park , florida', '1885', 'private', '4320', 'tars', '1975'], ['saint leo university', 'saint leo , florida', '1889', 'private', '15120', 'lions', '1975'], ['the university of tampa', 'tampa , florida', '1931', 'private', '10515', 'spartans', '1981']] |
list of manly - warringah sea eagles honours | https://en.wikipedia.org/wiki/List_of_Manly-Warringah_Sea_Eagles_honours | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12573519-7.html.csv | count | 1978 was the only year that the manly - warringah sea eagles honours had less than 40000 people attend . | {'scope': 'all', 'criterion': 'less_than', 'value': '40000', 'result': '1', 'col': '6', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'attendance', '40000'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose attendance record is less than 40000 .', 'tostr': 'filter_less { all_rows ; attendance ; 40000 }'}], 'result': '1', 'ind': 1, 'tostr': 'count { filter_less { all_rows ; attendance ; 40000 } }', 'tointer': 'select the rows whose attendance record is less than 40000 . the number of such rows is 1 .'}, '1'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_less { all_rows ; attendance ; 40000 } } ; 1 } = true', 'tointer': 'select the rows whose attendance record is less than 40000 . the number of such rows is 1 .'} | eq { count { filter_less { all_rows ; attendance ; 40000 } } ; 1 } = true | select the rows whose attendance record is less than 40000 . the number of such rows is 1 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_less_0': 0, 'all_rows_4': 4, 'attendance_5': 5, '40000_6': 6, '1_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_less_0': 'filter_less', 'all_rows_4': 'all_rows', 'attendance_5': 'attendance', '40000_6': '40000', '1_7': '1'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_less_0': [1], 'all_rows_4': [0], 'attendance_5': [0], '40000_6': [0], '1_7': [2]} | ['year', 'opponent', 'competition', 'score', 'venue', 'attendance'] | [['1972', 'eastern suburbs roosters', 'nswrfl', '19 - 14', 'sydney cricket ground', '54537'], ['1973', 'cronulla - sutherland sharks', 'nswrfl', '10 - 7', 'sydney cricket ground', '52044'], ['1976', 'parramatta eels', 'nswrfl', '13 - 10', 'sydney cricket ground', '57343'], ['1978', 'cronulla - sutherland sharks', 'nswrfl', '16 - 0', 'sydney cricket ground', '33552'], ['1987', 'canberra raiders', 'nswrl', '18 - 8', 'sydney cricket ground', '50201'], ['1996', 'st george dragons', 'arl', '20 - 8', 'sydney football stadium', '40985'], ['2008', 'melbourne storm', 'nrl', '40 - 0', 'anz stadium', '80388'], ['2011', 'new zealand warriors', 'nrl', '24 - 10', 'anz stadium', '81988']] |
jim rathmann | https://en.wikipedia.org/wiki/Jim_Rathmann | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1252109-1.html.csv | ordinal | for jim rathmann , when there are at least 200 laps , the 2nd worst rank was in 1953 . | {'scope': 'subset', 'row': '4', 'col': '4', 'order': '2', 'col_other': '1,6', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'subset': {'col': '6', 'criterion': 'greater_than_eq', 'value': '200'}} | {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'nth_argmax', 'args': [{'func': 'filter_greater_eq', 'args': ['all_rows', 'laps', '200'], 'result': None, 'ind': 0, 'tostr': 'filter_greater_eq { all_rows ; laps ; 200 }', 'tointer': 'select the rows whose laps record is greater than or equal to 200 .'}, 'rank', '2'], 'result': None, 'ind': 1, 'tostr': 'nth_argmax { filter_greater_eq { all_rows ; laps ; 200 } ; rank ; 2 }'}, 'year'], 'result': '1953', 'ind': 2, 'tostr': 'hop { nth_argmax { filter_greater_eq { all_rows ; laps ; 200 } ; rank ; 2 } ; year }'}, '1953'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { nth_argmax { filter_greater_eq { all_rows ; laps ; 200 } ; rank ; 2 } ; year } ; 1953 } = true', 'tointer': 'select the rows whose laps record is greater than or equal to 200 . select the row whose rank record of these rows is 2nd maximum . the year record of this row is 1953 .'} | eq { hop { nth_argmax { filter_greater_eq { all_rows ; laps ; 200 } ; rank ; 2 } ; year } ; 1953 } = true | select the rows whose laps record is greater than or equal to 200 . select the row whose rank record of these rows is 2nd maximum . the year record of this row is 1953 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'num_hop_2': 2, 'nth_argmax_1': 1, 'filter_greater_eq_0': 0, 'all_rows_5': 5, 'laps_6': 6, '200_7': 7, 'rank_8': 8, '2_9': 9, 'year_10': 10, '1953_11': 11} | {'eq_3': 'eq', 'result_4': 'true', 'num_hop_2': 'num_hop', 'nth_argmax_1': 'nth_argmax', 'filter_greater_eq_0': 'filter_greater_eq', 'all_rows_5': 'all_rows', 'laps_6': 'laps', '200_7': '200', 'rank_8': 'rank', '2_9': '2', 'year_10': 'year', '1953_11': '1953'} | {'eq_3': [4], 'result_4': [], 'num_hop_2': [3], 'nth_argmax_1': [2], 'filter_greater_eq_0': [1], 'all_rows_5': [0], 'laps_6': [0], '200_7': [0], 'rank_8': [1], '2_9': [1], 'year_10': [2], '1953_11': [3]} | ['year', 'start', 'qual', 'rank', 'finish', 'laps'] | [['1949', '21', '126.516', '29', '11', '175'], ['1950', '28', '129.959', '24', '24', '122'], ['1952', '10', '136.343', '7', '2', '200'], ['1953', '25', '135.666', '28', '7', '200'], ['1954', '28', '138.228', '21', '28', '110'], ['1955', '20', '138.707', '24', '14', '191'], ['1956', '2', '145.120', '3', '20', '175'], ['1957', '32', '139.806', '31', '2', '200'], ['1958', '20', '143.147', '15', '5', '200'], ['1959', '3', '144.433', '4', '2', '200'], ['1960', '2', '146.371', '4', '1', '200'], ['1961', '11', '145.413', '13', '30', '48'], ['1962', '23', '146.610', '21', '9', '200'], ['1963', '29', '147.838', '32', '24', '99']] |
haarlem baseball week | https://en.wikipedia.org/wiki/Haarlem_Baseball_Week | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18532667-2.html.csv | superlative | the united states had the most gold in the haarlem baseball week tournament . | {'scope': 'all', 'col_superlative': '3', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '2', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'gold'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; gold }'}, 'nation'], 'result': 'united states', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; gold } ; nation }'}, 'united states'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; gold } ; nation } ; united states } = true', 'tointer': 'select the row whose gold record of all rows is maximum . the nation record of this row is united states .'} | eq { hop { argmax { all_rows ; gold } ; nation } ; united states } = true | select the row whose gold record of all rows is maximum . the nation record of this row is united states . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'gold_5': 5, 'nation_6': 6, 'united states_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'gold_5': 'gold', 'nation_6': 'nation', 'united states_7': 'united states'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'gold_5': [0], 'nation_6': [1], 'united states_7': [2]} | ['rank', 'nation', 'gold', 'silver', 'bronze', 'total'] | [['1', 'united states', '13', '7', '10', '30'], ['2', 'cuba', '5', '6', '2', '13'], ['3', 'netherlands', '3', '7', '7', '17'], ['4', 'japan', '3', '1', '2', '6'], ['5', 'canada', '1', '1', '0', '2'], ['6', 'netherlands antilles', '1', '0', '1', '2'], ['7', 'south korea', '0', '2', '0', '2'], ['8', 'germany', '0', '1', '1', '2'], ['9', 'australia', '0', '1', '0', '1'], ['9', 'puerto rico', '0', '1', '0', '1'], ['10', 'chinese taipei', '0', '0', '1', '1'], ['10', 'france', '0', '0', '1', '1'], ['10', 'italy', '0', '0', '1', '1']] |
carrefour | https://en.wikipedia.org/wiki/Carrefour | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-167638-3.html.csv | superlative | of the european countries with carrefour stores , spain has the highest number of stores classified as hard discounters . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '14', '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', 'hard discounters'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; hard discounters }'}, 'country'], 'result': 'spain', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; hard discounters } ; country }'}, 'spain'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; hard discounters } ; country } ; spain } = true', 'tointer': 'select the row whose hard discounters record of all rows is maximum . the country record of this row is spain .'} | eq { hop { argmax { all_rows ; hard discounters } ; country } ; spain } = true | select the row whose hard discounters record of all rows is maximum . the country record of this row is spain . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'hard discounters_5': 5, 'country_6': 6, 'spain_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'hard discounters_5': 'hard discounters', 'country_6': 'country', 'spain_7': 'spain'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'hard discounters_5': [0], 'country_6': [1], 'spain_7': [2]} | ['country', 'first store', 'hypermarkets', 'supermarkets', 'hard discounters'] | [['albania', '2011', '1', '-', '-'], ['belgium', '2000', '45', '370', '-'], ['bulgaria', '2009', '5', '3', '-'], ['cyprus', '2006', '7', '8', '-'], ['france', '1960', '221', '1021', '897'], ['georgia', '2012', '1', '1', '-'], ['greece', '1991', '28', '210', '397'], ['italy', '1993', '45', '485', '-'], ['macedonia', '2012', '1', '-', '-'], ['monaco', '-', '-', '1', '-'], ['poland', '1997', '84', '277', '-'], ['portugal', '1991', '-', '-', '365'], ['romania', '2001', '25', '50', '-'], ['spain', '1973', '172', '115', '2912'], ['slovakia', '1998', '4', '0', '0'], ['slovenia', '1998', '15', '12', '6'], ['turkey', '1993', '73', '99', '519'], ['united kingdom', '1972', '-', '-', '-']] |
1986 - 87 dundee united f.c. season | https://en.wikipedia.org/wiki/1986%E2%80%9387_Dundee_United_F.C._season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15640438-5.html.csv | count | in the 86-87 dundee united f. c. season only two of the games against gothenburg were played in may . | {'scope': 'subset', 'criterion': 'fuzzily_match', 'value': 'may', 'result': '2', 'col': '1', 'subset': {'col': '2', 'criterion': 'equal', 'value': 'gothenburg'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', 'gothenburg'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; opponent ; gothenburg }', 'tointer': 'select the rows whose opponent record fuzzily matches to gothenburg .'}, 'date', 'may'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose opponent record fuzzily matches to gothenburg . among these rows , select the rows whose date record fuzzily matches to may .', 'tostr': 'filter_eq { filter_eq { all_rows ; opponent ; gothenburg } ; date ; may }'}], 'result': '2', 'ind': 2, 'tostr': 'count { filter_eq { filter_eq { all_rows ; opponent ; gothenburg } ; date ; may } }', 'tointer': 'select the rows whose opponent record fuzzily matches to gothenburg . among these rows , select the rows whose date record fuzzily matches to may . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_eq { filter_eq { all_rows ; opponent ; gothenburg } ; date ; may } } ; 2 } = true', 'tointer': 'select the rows whose opponent record fuzzily matches to gothenburg . among these rows , select the rows whose date record fuzzily matches to may . the number of such rows is 2 .'} | eq { count { filter_eq { filter_eq { all_rows ; opponent ; gothenburg } ; date ; may } } ; 2 } = true | select the rows whose opponent record fuzzily matches to gothenburg . among these rows , select the rows whose date record fuzzily matches to may . 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, 'opponent_6': 6, 'gothenburg_7': 7, 'date_8': 8, 'may_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', 'opponent_6': 'opponent', 'gothenburg_7': 'gothenburg', 'date_8': 'date', 'may_9': 'may', '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], 'opponent_6': [0], 'gothenburg_7': [0], 'date_8': [1], 'may_9': [1], '2_10': [3]} | ['date', 'opponent', 'venue', 'result', 'attendance'] | [['17 september 1986', 'lens', 'a', '0 - 1', '11330'], ['1 october 1986', 'lens', 'h', '2 - 0', '11645'], ['22 october 1986', 'universitatea craiova', 'h', '3 - 0', '10728'], ['5 november 1986', 'universitatea craiova', 'a', '0 - 1', '35000'], ['26 november 1986', 'hajduk split', 'h', '2 - 0', '11569'], ['10 december 1986', 'hajduk split', 'a', '0 - 0', '26000'], ['4 march 1987', 'barcelona', 'h', '1 - 0', '21322'], ['18 march 1987', 'barcelona', 'a', '2 - 1', '42000'], ['8 april 1987', 'mönchengladbach', 'h', '0 - 0', '15789'], ['22 april 1987', 'mönchengladbach', 'a', '2 - 0', '33500'], ['6 may 1987', 'gothenburg', 'a', '0 - 1', '50053'], ['20 may 1987', 'gothenburg', 'h', '1 - 1', '20911']] |
2004 in paraguayan football | https://en.wikipedia.org/wiki/2004_in_Paraguayan_football | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-14889048-1.html.csv | count | only two of the teams in the 2004 paraguayan football league had more than 10 wins . | {'scope': 'all', 'criterion': 'greater_than', 'value': '10', 'result': '2', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'wins', '10'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose wins record is greater than 10 .', 'tostr': 'filter_greater { all_rows ; wins ; 10 }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_greater { all_rows ; wins ; 10 } }', 'tointer': 'select the rows whose wins record is greater than 10 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_greater { all_rows ; wins ; 10 } } ; 2 } = true', 'tointer': 'select the rows whose wins record is greater than 10 . the number of such rows is 2 .'} | eq { count { filter_greater { all_rows ; wins ; 10 } } ; 2 } = true | select the rows whose wins record is greater than 10 . the number of such rows is 2 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_greater_0': 0, 'all_rows_4': 4, 'wins_5': 5, '10_6': 6, '2_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_greater_0': 'filter_greater', 'all_rows_4': 'all_rows', 'wins_5': 'wins', '10_6': '10', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_greater_0': [1], 'all_rows_4': [0], 'wins_5': [0], '10_6': [0], '2_7': [2]} | ['position', 'team', 'played', 'wins', 'draws', 'losses', 'scored', 'conceded', 'points'] | [['1', 'cerro porteño', '18', '12', '5', '1', '31', '13', '41'], ['2', 'libertad', '18', '11', '5', '2', '44', '13', '38'], ['3', 'tacuary', '18', '8', '4', '6', '25', '13', '28'], ['4', 'guaraní', '18', '8', '4', '6', '20', '25', '28'], ['5', 'olimpia', '18', '6', '5', '7', '21', '28', '23'], ['6', 'nacional', '18', '5', '5', '8', '19', '24', '20'], ['7', 'sol de américa', '18', '5', '4', '9', '14', '24', '19'], ['8', '12 de octubre', '18', '5', '3', '10', '18', '28', '18'], ['9', 'sportivo luqueño', '18', '3', '8', '7', '19', '30', '17']] |
approach and landing tests | https://en.wikipedia.org/wiki/Approach_and_Landing_Tests | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16237630-3.html.csv | majority | most of the flights during the approach and landing tests were indicated as landed with 747 . | {'scope': 'all', 'col': '7', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'landed with 747', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'comment', 'landed with 747'], 'result': True, 'ind': 0, 'tointer': 'for the comment records of all rows , most of them fuzzily match to landed with 747 .', 'tostr': 'most_eq { all_rows ; comment ; landed with 747 } = true'} | most_eq { all_rows ; comment ; landed with 747 } = true | for the comment records of all rows , most of them fuzzily match to landed with 747 . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'comment_3': 3, 'landed with 747_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'comment_3': 'comment', 'landed with 747_4': 'landed with 747'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'comment_3': [0], 'landed with 747_4': [0]} | ['test flight', 'date', 'speed', 'altitude', 'crew', 'duration', 'comment'] | [['taxi test 1', 'february 15 , 1977', 'mph ( km / h )', 'taxi', 'none', 'taxi', 'concrete runway , tailcone on'], ['taxi test 2', 'february 15 , 1977', 'mph ( km / h )', 'taxi', 'none', 'taxi', 'concrete runway , tailcone on'], ['taxi test 3', 'february 15 , 1977', 'mph ( km / h )', 'taxi', 'none', 'taxi', 'concrete runway , tailcone on'], ['captive - inert flight 1', 'february 18 , 1977', 'mph ( km / h )', '16000ft 4877 m', 'none', '2 h 5 min', 'tailcone on , landed with 747'], ['captive - inert flight 2', 'february 22 , 1977', 'mph ( km / h )', '22600ft 6888 m', 'none', '3 h 13 min', 'tailcone on , landed with 747'], ['captive - inert flight 3', 'february 25 , 1977', 'mph ( km / h )', '26600ft 8108 m', 'none', '2 h 28 min', 'tailcone on , landed with 747'], ['captive - inert flight 4', 'february 28 , 1977', 'mph ( km / h )', '28565ft 8707 m', 'none', '2 h 11 min', 'tailcone on , landed with 747'], ['captive - inert flight 5', 'march 2 , 1977', 'mph ( km / h )', '30000ft 9144 m', 'none', '1 h 39 min', 'tailcone on , landed with 747'], ['captive - active flight 1', 'june 18 , 1977', 'mph ( km / h )', '14970ft 4563 m', 'haise , fullerton', '55 min 46 s', 'tailcone on , landed with 747'], ['captive - active flight 2', 'june 28 , 1977', 'mph ( km / h )', '22030ft 6715 m', 'engle , truly', '62 min 0 s', 'tailcone on , landed with 747'], ['captive - active flight 3', 'july 26 , 1977', 'mph ( km / h )', '30292ft 9233 m', 'haise , fullerton', '59 min 53 s', 'tailcone on , landed with 747'], ['free flight 1', 'august 12 , 1977', 'mph ( km / h )', '24100ft 7346 m', 'haise , fullerton', '5 min 21 s', 'tailcone on , lakebed landing'], ['free flight 2', 'september 13 , 1977', 'mph ( km / h )', '26000ft 7925 m', 'engle , truly', '5 min 28 s', 'tailcone on , lakebed landing'], ['free flight 3', 'september 23 , 1977', 'mph ( km / h )', '24700ft 7529 m', 'haise , fullerton', '5 min 34 s', 'tailcone on , lakebed landing'], ['free flight 4', 'october 12 , 1977', 'mph ( km / h )', '22400ft 6828 m', 'engle , truly', '2 min 34 s', 'tailcone off , lakebed landing'], ['free flight 5', 'october 26 , 1977', 'mph ( km / h )', '19000ft 5791 m', 'haise , fullerton', '2 min 1 s', 'tailcone off , runway landing']] |
english open ( table tennis ) | https://en.wikipedia.org/wiki/English_Open_%28table_tennis%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-28211988-1.html.csv | count | 2 seasons of the english open were hosted in kettering . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'kettering', 'result': '2', 'col': '2', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'host', 'kettering'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose host record fuzzily matches to kettering .', 'tostr': 'filter_eq { all_rows ; host ; kettering }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; host ; kettering } }', 'tointer': 'select the rows whose host record fuzzily matches to kettering . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; host ; kettering } } ; 2 } = true', 'tointer': 'select the rows whose host record fuzzily matches to kettering . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; host ; kettering } } ; 2 } = true | select the rows whose host record fuzzily matches to kettering . 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, 'host_5': 5, 'kettering_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', 'host_5': 'host', 'kettering_6': 'kettering', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'host_5': [0], 'kettering_6': [0], '2_7': [2]} | ['season', 'host', 'mens singles', 'womens singles', 'mens doubles', 'womens doubles'] | [['1995 / 96', 'kettering', 'kong linghui', 'yang ying', 'werner schlager karl jindrak', 'yang ying wang hui'], ['1996 / 97', 'kettering', 'jean - michel saive', 'chen - tong fei - ming', 'christophe legout patrick chila', 'chai po wa qiao yunping'], ['1998 / 99', 'hopton - on - sea', 'ma wenge', 'jie schoepp', 'trinko keen danny heister', 'lee eun - sil ryu ji - hae'], ['2000 / 01', 'chatham', 'wang liqin', 'yoshie takada', 'timo boll zoltan fejer - konnerth', 'kim hyang mi kim hyon hui'], ['2008 / 09', 'sheffield', 'ma long', 'guo yan', 'ma long wang liqin', 'kim kyung ah park mi young']] |
los angeles lakers all - time roster | https://en.wikipedia.org/wiki/Los_Angeles_Lakers_all-time_roster | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10560886-8.html.csv | comparative | jerry grote played at an earlier date for the los angeles lakers than andrew goudelock . | {'row_1': '16', 'row_2': '10', 'col': '4', 'col_other': '1', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', 'jerry grote'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose player record fuzzily matches to jerry grote .', 'tostr': 'filter_eq { all_rows ; player ; jerry grote }'}, 'from'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; player ; jerry grote } ; from }', 'tointer': 'select the rows whose player record fuzzily matches to jerry grote . take the from record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', 'andrew goudelock'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose player record fuzzily matches to andrew goudelock .', 'tostr': 'filter_eq { all_rows ; player ; andrew goudelock }'}, 'from'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; player ; andrew goudelock } ; from }', 'tointer': 'select the rows whose player record fuzzily matches to andrew goudelock . take the from record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; player ; jerry grote } ; from } ; hop { filter_eq { all_rows ; player ; andrew goudelock } ; from } } = true', 'tointer': 'select the rows whose player record fuzzily matches to jerry grote . take the from record of this row . select the rows whose player record fuzzily matches to andrew goudelock . take the from record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; player ; jerry grote } ; from } ; hop { filter_eq { all_rows ; player ; andrew goudelock } ; from } } = true | select the rows whose player record fuzzily matches to jerry grote . take the from record of this row . select the rows whose player record fuzzily matches to andrew goudelock . take the from 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, 'jerry grote_8': 8, 'from_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'player_11': 11, 'andrew goudelock_12': 12, 'from_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', 'jerry grote_8': 'jerry grote', 'from_9': 'from', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'player_11': 'player', 'andrew goudelock_12': 'andrew goudelock', 'from_13': 'from'} | {'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'player_7': [0], 'jerry grote_8': [0], 'from_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'player_11': [1], 'andrew goudelock_12': [1], 'from_13': [3]} | ['player', 'nationality', 'position', 'from', 'school / country'] | [['earl gardner', 'united states', 'forward', '1948', 'depauw'], ['dick garmaker', 'united states', 'guard / forward', '1955', 'minnesota'], ['garrett , calvin calvin garrett', 'united states', 'forward', '1983', 'oral roberts'], ['dick garrett', 'united states', 'guard', '1969', 'southern illinois'], ['pau gasol', 'spain', 'forward / center', '2008', 'spain'], ['devean george', 'united states', 'forward', '1999', 'augsburg'], ['mel gibson', 'united states', 'guard', '1963', 'western carolina'], ['norman glick', 'united states', 'forward', '1949', 'loyola marymount'], ['gail goodrich', 'united states', 'guard', '1965 1970', 'ucla'], ['andrew goudelock', 'united states', 'guard', '2011', 'charleston'], ['brian grant', 'united states', 'forward / center', '2004', 'xavier'], ['bud grant', 'united states', 'forward', '1949', 'minnesota'], ['horace grant', 'united states', 'forward / center', '2000 2003', 'clemson'], ['travis grant', 'united states', 'forward', '1950', 'kentucky state'], ['ac green', 'united states', 'forward', '1985 1999', 'oregon state'], ['jerry grote', 'united states', 'guard', '1964', 'loyola marymount'], ['pétur guðmundsson', 'iceland', 'center', '1985', 'washington']] |
türk telekom arena | https://en.wikipedia.org/wiki/T%C3%BCrk_Telekom_Arena | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12243387-1.html.csv | aggregation | the average capacity for the various plans for the türk telekom arena was 44,123 . | {'scope': 'all', 'col': '4', 'type': 'average', 'result': '44123', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'capacity'], 'result': '44123', 'ind': 0, 'tostr': 'avg { all_rows ; capacity }'}, '44123'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; capacity } ; 44123 } = true', 'tointer': 'the average of the capacity record of all rows is 44123 .'} | round_eq { avg { all_rows ; capacity } ; 44123 } = true | the average of the capacity record of all rows is 44123 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'capacity_4': 4, '44123_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'capacity_4': 'capacity', '44123_5': '44123'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'capacity_4': [0], '44123_5': [1]} | ['project', 'year', 'location', 'capacity', 'suites', 'architect', 'cost'] | [['faruk süren project', '1997 - 2001', 'mecidiyeköy', '40482', '125 + 72 boxes without outside seating', 'bbb architects', '118.5 million ( in 2014 dollars )'], ['mehmet cansun project', '2001', 'mecidiyeköy', '35000', '132', 'gs member architecture group', '35 million ( in 2014 dollars )'], ["özhan canaydın : back to süren 's project", '2002 - 2005', 'aslantepe', '40482', '125', 'bbb architects', '90 million ( in 2014 dollars )'], ['eren talu bidding project', '2007', 'aslantepe', '52000', '150', 'populous', 'n / a'], ['özhan canaydın project', '2007', 'aslantepe', '52652', '157', 'asp stuttgart', '250 million ( in 2014 dollars )']] |
waste management in hong kong | https://en.wikipedia.org/wiki/Waste_management_in_Hong_Kong | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16176425-2.html.csv | superlative | in 1978 , the sai kung district had the most acres for waste management . | {'scope': 'subset', 'col_superlative': '3', 'row_superlative': '8', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '2,4', 'subset': {'col': '4', 'criterion': 'equal', 'value': '1978'}} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'opened', '1978'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; opened ; 1978 }', 'tointer': 'select the rows whose opened record is equal to 1978 .'}, 'acres'], 'result': None, 'ind': 1, 'tostr': 'argmax { filter_eq { all_rows ; opened ; 1978 } ; acres }'}, 'location'], 'result': 'sai kung district', 'ind': 2, 'tostr': 'hop { argmax { filter_eq { all_rows ; opened ; 1978 } ; acres } ; location }'}, 'sai kung district'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { argmax { filter_eq { all_rows ; opened ; 1978 } ; acres } ; location } ; sai kung district } = true', 'tointer': 'select the rows whose opened record is equal to 1978 . select the row whose acres record of these rows is maximum . the location record of this row is sai kung district .'} | eq { hop { argmax { filter_eq { all_rows ; opened ; 1978 } ; acres } ; location } ; sai kung district } = true | select the rows whose opened record is equal to 1978 . select the row whose acres record of these rows is maximum . the location record of this row is sai kung district . | 4 | 4 | {'str_eq_3': 3, 'result_4': 4, 'str_hop_2': 2, 'argmax_1': 1, 'filter_eq_0': 0, 'all_rows_5': 5, 'opened_6': 6, '1978_7': 7, 'acres_8': 8, 'location_9': 9, 'sai kung district_10': 10} | {'str_eq_3': 'str_eq', 'result_4': 'true', 'str_hop_2': 'str_hop', 'argmax_1': 'argmax', 'filter_eq_0': 'filter_eq', 'all_rows_5': 'all_rows', 'opened_6': 'opened', '1978_7': '1978', 'acres_8': 'acres', 'location_9': 'location', 'sai kung district_10': 'sai kung district'} | {'str_eq_3': [4], 'result_4': [], 'str_hop_2': [3], 'argmax_1': [2], 'filter_eq_0': [1], 'all_rows_5': [0], 'opened_6': [0], '1978_7': [0], 'acres_8': [1], 'location_9': [2], 'sai kung district_10': [3]} | ['landfill', 'location', 'acres', 'opened', 'capacity', 'status', 'rehab period'] | [['gin drinkers bay', 'kwai tsing district', '29', '1960', '3.5 million tonnes', 'closed', '1999 - 2000'], ['ngau tam mei', 'yuen long district', '2', '1973', '0.15 million tonnes', 'closed', '1999 - 2000'], ['shuen wan', 'tai po district', '50', '1973', '15 million tonnes', 'closed', '1996 - 1997'], ['ma tso lung', 'north district', '2', '1976', '0.2 million tonnes', 'closed', '1999 - 2000'], ['ngau chi wan', 'wong tai sin district', '8', '1976', '0.7 million tonnes', 'closed', '1997 - 1998'], ['sai tso wan', 'kwun tong district', '9', '1978', '1.6 million tonnes', 'closed', '1997 - 1998'], ['siu lang shui', 'tuen mun district', '12', '1978', '1.2 million tonnes', 'closed', '1999 - 2000'], ['tseung kwan o stage i', 'sai kung district', '68', '1978', '15.2 million tonnes', 'closed', '1997 - 1999'], ['ma yau tong west', 'kwun tong', '6', '1979', '6 million tonnes', 'closed', '1997 - 1998'], ['ma yau tong central', 'kwun tong', '11', '1981', '1.0 million tonnes', 'closed', '1997 - 1998'], ['pillar point valley', 'tuen mun district', '38', '1983', '13 million tonnes', 'closed', '2004 - 2006'], ['jordan valley', 'kwun tong', '11', '1986', '1.5 million tonnes', 'closed', '1997 - 1998'], ['tseung kwan o stage ii - iii', 'sai kung district', '42', '1988', '12.6 million tonnes', 'closed', '1997 - 1999']] |
françoise dürr | https://en.wikipedia.org/wiki/Fran%C3%A7oise_D%C3%BCrr | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2112025-3.html.csv | comparative | both of the mixed doubles tournaments where françoise dürr competed against margaret court and marty riessen , he lost . | {'row_1': '2', 'row_2': '3', 'col': '1', 'col_other': '6', 'relation': 'equal', 'record_mentioned': 'yes', 'diff_result': None} | {'func': 'and', 'args': [{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponents in the final', 'margaret court marty riessen'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose opponents in the final record fuzzily matches to margaret court marty riessen .', 'tostr': 'filter_eq { all_rows ; opponents in the final ; margaret court marty riessen }'}, 'outcome'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; opponents in the final ; margaret court marty riessen } ; outcome }', 'tointer': 'select the rows whose opponents in the final record fuzzily matches to margaret court marty riessen . take the outcome record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponents in the final', 'margaret court marty riessen'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose opponents in the final record fuzzily matches to margaret court marty riessen .', 'tostr': 'filter_eq { all_rows ; opponents in the final ; margaret court marty riessen }'}, 'outcome'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; opponents in the final ; margaret court marty riessen } ; outcome }', 'tointer': 'select the rows whose opponents in the final record fuzzily matches to margaret court marty riessen . take the outcome record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'eq { hop { filter_eq { all_rows ; opponents in the final ; margaret court marty riessen } ; outcome } ; hop { filter_eq { all_rows ; opponents in the final ; margaret court marty riessen } ; outcome } }', 'tointer': 'select the rows whose opponents in the final record fuzzily matches to margaret court marty riessen . take the outcome record of this row . select the rows whose opponents in the final record fuzzily matches to margaret court marty riessen . take the outcome record of this row . the first record fuzzily matches to the second record .'}, {'func': 'and', 'args': [{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponents in the final', 'margaret court marty riessen'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose opponents in the final record fuzzily matches to margaret court marty riessen .', 'tostr': 'filter_eq { all_rows ; opponents in the final ; margaret court marty riessen }'}, 'outcome'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; opponents in the final ; margaret court marty riessen } ; outcome }', 'tointer': 'select the rows whose opponents in the final record fuzzily matches to margaret court marty riessen . take the outcome record of this row .'}, 'runner - up'], 'result': True, 'ind': 5, 'tostr': 'eq { hop { filter_eq { all_rows ; opponents in the final ; margaret court marty riessen } ; outcome } ; runner - up }', 'tointer': 'the outcome record of the first row is runner - up .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponents in the final', 'margaret court marty riessen'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose opponents in the final record fuzzily matches to margaret court marty riessen .', 'tostr': 'filter_eq { all_rows ; opponents in the final ; margaret court marty riessen }'}, 'outcome'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; opponents in the final ; margaret court marty riessen } ; outcome }', 'tointer': 'select the rows whose opponents in the final record fuzzily matches to margaret court marty riessen . take the outcome record of this row .'}, 'runner - up'], 'result': True, 'ind': 6, 'tostr': 'eq { hop { filter_eq { all_rows ; opponents in the final ; margaret court marty riessen } ; outcome } ; runner - up }', 'tointer': 'the outcome record of the second row is runner - up .'}], 'result': True, 'ind': 7, 'tostr': 'and { eq { hop { filter_eq { all_rows ; opponents in the final ; margaret court marty riessen } ; outcome } ; runner - up } ; eq { hop { filter_eq { all_rows ; opponents in the final ; margaret court marty riessen } ; outcome } ; runner - up } }', 'tointer': 'the outcome record of the first row is runner - up . the outcome record of the second row is runner - up .'}], 'result': True, 'ind': 8, 'tostr': 'and { eq { hop { filter_eq { all_rows ; opponents in the final ; margaret court marty riessen } ; outcome } ; hop { filter_eq { all_rows ; opponents in the final ; margaret court marty riessen } ; outcome } } ; and { eq { hop { filter_eq { all_rows ; opponents in the final ; margaret court marty riessen } ; outcome } ; runner - up } ; eq { hop { filter_eq { all_rows ; opponents in the final ; margaret court marty riessen } ; outcome } ; runner - up } } } = true', 'tointer': 'select the rows whose opponents in the final record fuzzily matches to margaret court marty riessen . take the outcome record of this row . select the rows whose opponents in the final record fuzzily matches to margaret court marty riessen . take the outcome record of this row . the first record fuzzily matches to the second record . the outcome record of the first row is runner - up . the outcome record of the second row is runner - up .'} | and { eq { hop { filter_eq { all_rows ; opponents in the final ; margaret court marty riessen } ; outcome } ; hop { filter_eq { all_rows ; opponents in the final ; margaret court marty riessen } ; outcome } } ; and { eq { hop { filter_eq { all_rows ; opponents in the final ; margaret court marty riessen } ; outcome } ; runner - up } ; eq { hop { filter_eq { all_rows ; opponents in the final ; margaret court marty riessen } ; outcome } ; runner - up } } } = true | select the rows whose opponents in the final record fuzzily matches to margaret court marty riessen . take the outcome record of this row . select the rows whose opponents in the final record fuzzily matches to margaret court marty riessen . take the outcome record of this row . the first record fuzzily matches to the second record . the outcome record of the first row is runner - up . the outcome record of the second row is runner - up . | 13 | 9 | {'and_8': 8, 'result_9': 9, 'str_eq_4': 4, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_10': 10, 'opponents in the final_11': 11, 'margaret court marty riessen_12': 12, 'outcome_13': 13, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_14': 14, 'opponents in the final_15': 15, 'margaret court marty riessen_16': 16, 'outcome_17': 17, 'and_7': 7, 'str_eq_5': 5, 'runner - up_18': 18, 'str_eq_6': 6, 'runner - up_19': 19} | {'and_8': 'and', 'result_9': 'true', 'str_eq_4': 'str_eq', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_10': 'all_rows', 'opponents in the final_11': 'opponents in the final', 'margaret court marty riessen_12': 'margaret court marty riessen', 'outcome_13': 'outcome', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_14': 'all_rows', 'opponents in the final_15': 'opponents in the final', 'margaret court marty riessen_16': 'margaret court marty riessen', 'outcome_17': 'outcome', 'and_7': 'and', 'str_eq_5': 'str_eq', 'runner - up_18': 'runner - up', 'str_eq_6': 'str_eq', 'runner - up_19': 'runner - up'} | {'and_8': [9], 'result_9': [], 'str_eq_4': [8], 'str_hop_2': [4, 5], 'filter_str_eq_0': [2], 'all_rows_10': [0], 'opponents in the final_11': [0], 'margaret court marty riessen_12': [0], 'outcome_13': [2], 'str_hop_3': [4, 6], 'filter_str_eq_1': [3], 'all_rows_14': [1], 'opponents in the final_15': [1], 'margaret court marty riessen_16': [1], 'outcome_17': [3], 'and_7': [8], 'str_eq_5': [7], 'runner - up_18': [5], 'str_eq_6': [7], 'runner - up_19': [6]} | ['outcome', 'year', 'championship', 'surface', 'partner', 'opponents in the final', 'score in the final'] | [['winner', '1968', 'french open', 'clay', 'jean - claude barclay', 'billie jean king owen davidson', '6 - 1 , 6 - 4'], ['runner - up', '1969', 'french open', 'clay', 'jean - claude barclay', 'margaret court marty riessen', '6 - 3 , 6 - 2'], ['runner - up', '1969', 'us open', 'grass', 'dennis ralston', 'margaret court marty riessen', '6 - 4 , 7 - 5'], ['runner - up', '1970', 'french open', 'clay', 'jean - claude barclay', 'billie jean king bob hewitt', '3 - 6 , 6 - 4 , 6 - 2'], ['winner', '1971', 'french open', 'clay', 'jean - claude barclay', 'winnie shaw thomas lejus', '6 - 2 , 6 - 4'], ['runner - up', '1972', 'french open', 'clay', 'jean - claude barclay', 'evonne goolagong cawley kim warwick', '6 - 2 , 6 - 4'], ['winner', '1973', 'french open', 'clay', 'jean - claude barclay', 'betty stöve patrice dominguez', '6 - 1 , 6 - 4']] |
1972 england rugby union tour of south africa | https://en.wikipedia.org/wiki/1972_England_rugby_union_tour_of_South_Africa | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17020783-1.html.csv | aggregation | in the 1972 england rugby union tour of south africa , the average against was 8.29 . | {'scope': 'all', 'col': '2', 'type': 'average', 'result': '8.29', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'against'], 'result': '8.29', 'ind': 0, 'tostr': 'avg { all_rows ; against }'}, '8.29'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; against } ; 8.29 } = true', 'tointer': 'the average of the against record of all rows is 8.29 .'} | round_eq { avg { all_rows ; against } ; 8.29 } = true | the average of the against record of all rows is 8.29 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'against_4': 4, '8.29_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'against_4': 'against', '8.29_5': '8.29'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'against_4': [0], '8.29_5': [1]} | ['opposing team', 'against', 'date', 'venue', 'status'] | [['natal', '0', 'may 17 , 1972', 'durban', 'tour match'], ['western province', '6', 'may 20 , 1972', 'cape town', 'tour match'], ['sa rugby fed xv', '6', 'may 22 , 1972', 'cape town', 'tour match'], ['sa leopards', '3', 'may 24 , 1972', 'port elizabeth', 'tour match'], ['northern transvaal', '13', 'may 27 , 1972', 'pretoria', 'tour match'], ['giqualand west', '21', 'may 30 , 1972', 'kimberley', 'tour match'], ['south africa', '9', 'june 3 , 1972', 'ellis park , johannesburg', 'test match']] |
1987 masters tournament | https://en.wikipedia.org/wiki/1987_Masters_Tournament | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16490473-1.html.csv | count | there were 10 players who participated in the 1987 masters tournament . | {'scope': 'all', 'criterion': 'all', 'value': 'n/a', 'result': '10', 'col': '1', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_all', 'args': ['all_rows', 'player'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose player record is arbitrary .', 'tostr': 'filter_all { all_rows ; player }'}], 'result': '10', 'ind': 1, 'tostr': 'count { filter_all { all_rows ; player } }', 'tointer': 'select the rows whose player record is arbitrary . the number of such rows is 10 .'}, '10'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_all { all_rows ; player } } ; 10 } = true', 'tointer': 'select the rows whose player record is arbitrary . the number of such rows is 10 .'} | eq { count { filter_all { all_rows ; player } } ; 10 } = true | select the rows whose player record is arbitrary . the number of such rows is 10 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_all_0': 0, 'all_rows_4': 4, 'player_5': 5, '10_6': 6} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_all_0': 'filter_all', 'all_rows_4': 'all_rows', 'player_5': 'player', '10_6': '10'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_all_0': [1], 'all_rows_4': [0], 'player_5': [0], '10_6': [2]} | ['player', 'country', 'year ( s ) won', 'total', 'to par', 'finish'] | [['seve ballesteros', 'spain', '1980 , 1983', '285', '3', 't2'], ['ben crenshaw', 'united states', '1984', '286', '2', 't4'], ['bernhard langer', 'west germany', '1985', '289', '+ 1', 't7'], ['jack nicklaus', 'united states', '1963 , 1965 , 1966 , 1972 , 1975 , 1986', '289', '+ 1', 't7'], ['tom watson', 'united states', '1977 , 1981', '289', '+ 1', 't7'], ['craig stadler', 'united states', '1982', '291', '+ 3', 't17'], ['fuzzy zoeller', 'united states', '1979', '295', '+ 7', 't27'], ['gary player', 'south africa', '1961 , 1974 , 1978', '297', '+ 9', 't35'], ['tommy aaron', 'united states', '1973', '305', '+ 17', 't50'], ['billy casper', 'united states', '1970', '305', '+ 17', 't50']] |
8th new zealand parliament | https://en.wikipedia.org/wiki/8th_New_Zealand_Parliament | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-28898974-3.html.csv | comparative | thomas shailer weston resigned his seat in the 8th new zealand parliament earlire than isaac wilson . | {'row_1': '6', 'row_2': '10', 'col': '3', 'col_other': '4', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'incumbent', 'thomas shailer weston'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose incumbent record fuzzily matches to thomas shailer weston .', 'tostr': 'filter_eq { all_rows ; incumbent ; thomas shailer weston }'}, 'date'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; incumbent ; thomas shailer weston } ; date }', 'tointer': 'select the rows whose incumbent record fuzzily matches to thomas shailer weston . take the date record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'incumbent', 'isaac wilson'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose incumbent record fuzzily matches to isaac wilson .', 'tostr': 'filter_eq { all_rows ; incumbent ; isaac wilson }'}, 'date'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; incumbent ; isaac wilson } ; date }', 'tointer': 'select the rows whose incumbent record fuzzily matches to isaac wilson . take the date record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; incumbent ; thomas shailer weston } ; date } ; hop { filter_eq { all_rows ; incumbent ; isaac wilson } ; date } } = true', 'tointer': 'select the rows whose incumbent record fuzzily matches to thomas shailer weston . take the date record of this row . select the rows whose incumbent record fuzzily matches to isaac wilson . take the date record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; incumbent ; thomas shailer weston } ; date } ; hop { filter_eq { all_rows ; incumbent ; isaac wilson } ; date } } = true | select the rows whose incumbent record fuzzily matches to thomas shailer weston . take the date record of this row . select the rows whose incumbent record fuzzily matches to isaac wilson . take the date record of this row . the first record is less than the second record . | 5 | 5 | {'less_4': 4, 'result_5': 5, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'incumbent_7': 7, 'thomas shailer weston_8': 8, 'date_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'incumbent_11': 11, 'isaac wilson_12': 12, 'date_13': 13} | {'less_4': 'less', 'result_5': 'true', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'incumbent_7': 'incumbent', 'thomas shailer weston_8': 'thomas shailer weston', 'date_9': 'date', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'incumbent_11': 'incumbent', 'isaac wilson_12': 'isaac wilson', 'date_13': 'date'} | {'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'incumbent_7': [0], 'thomas shailer weston_8': [0], 'date_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'incumbent_11': [1], 'isaac wilson_12': [1], 'date_13': [3]} | ['by - election', 'electorate', 'date', 'incumbent', 'reason', 'winner'] | [['1882', 'franklin north', '9 june', 'benjamin harris', 'election declared void', 'benjamin harris'], ['1882', 'wakanui', '16 june', 'cathcart wason', 'election declared void', 'joseph ivess'], ['1882', 'stanmore', '11 july', 'walter pilliet', 'election declared void', 'walter pilliet'], ['1883', 'peninsula', '22 january', 'james seaton', 'death', 'william larnach'], ['1883', 'selwyn', '6 april', 'john hall', 'resignation', 'edward james lee'], ['1883', 'inangahua', '14 may', 'thomas shailer weston', 'resignation', 'edward shaw'], ['1883', 'bruce', '29 june', 'james rutherford', 'death', 'james mcdonald'], ['1884', 'selwyn', '15 february', 'edward james lee', 'death', 'edward wakefield'], ['1884', 'thorndon', '13 may', 'william levin', 'resignation', 'alfred newman'], ['1884', 'kaiapoi', '16 may', 'isaac wilson', 'resignation', 'edward richardson']] |
ferydoon zandi | https://en.wikipedia.org/wiki/Ferydoon_Zandi | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1768182-3.html.csv | majority | most of the games played by ferydon zandi after year 2007 were friendly . | {'scope': 'subset', 'col': '5', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'friendly', 'subset': {'col': '1', 'criterion': 'greater_than', 'value': '2007'}} | {'func': 'most_str_eq', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'date', '2007'], 'result': None, 'ind': 0, 'tostr': 'filter_greater { all_rows ; date ; 2007 }', 'tointer': 'select the rows whose date record is greater than 2007 .'}, 'competition', 'friendly'], 'result': True, 'ind': 1, 'tointer': 'select the rows whose date record is greater than 2007 . for the competition records of these rows , most of them fuzzily match to friendly .', 'tostr': 'most_eq { filter_greater { all_rows ; date ; 2007 } ; competition ; friendly } = true'} | most_eq { filter_greater { all_rows ; date ; 2007 } ; competition ; friendly } = true | select the rows whose date record is greater than 2007 . for the competition records of these rows , most of them fuzzily match to friendly . | 2 | 2 | {'most_str_eq_1': 1, 'result_2': 2, 'filter_greater_0': 0, 'all_rows_3': 3, 'date_4': 4, '2007_5': 5, 'competition_6': 6, 'friendly_7': 7} | {'most_str_eq_1': 'most_str_eq', 'result_2': 'true', 'filter_greater_0': 'filter_greater', 'all_rows_3': 'all_rows', 'date_4': 'date', '2007_5': '2007', 'competition_6': 'competition', 'friendly_7': 'friendly'} | {'most_str_eq_1': [2], 'result_2': [], 'filter_greater_0': [1], 'all_rows_3': [0], 'date_4': [0], '2007_5': [0], 'competition_6': [1], 'friendly_7': [1]} | ['date', 'venue', 'score', 'result', 'competition'] | [['28 may 2005', 'azadi stadium , tehran', '1 - 0', '2 - 1', 'international match'], ['15 july 2007', 'bukit jalil stadium , kuala lumpur', '1 - 2', '2 - 2', '2007 afc asian cup'], ['7 june 2008', 'khalifa bin zayed stadium , al ain', '1 - 0', '1 - 0', '2010 fifa world cup qualification'], ['31 august 2009', 'bahrain national stadium , riffa', '1 - 2', '2 - 4', 'friendly'], ['31 august 2009', 'bahrain national stadium , riffa', '2 - 3', '2 - 4', 'friendly']] |
2005 world women 's curling championship | https://en.wikipedia.org/wiki/2005_World_Women%27s_Curling_Championship | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1554808-2.html.csv | comparative | in the 2005 world women 's curling championship scotland won more ends than canada . | {'row_1': '3', 'row_2': '6', 'col': '3', 'col_other': '1', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'locale', 'canada'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose locale record fuzzily matches to canada .', 'tostr': 'filter_eq { all_rows ; locale ; canada }'}, 'ends won'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; locale ; canada } ; ends won }', 'tointer': 'select the rows whose locale record fuzzily matches to canada . take the ends won record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'locale', 'scotland'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose locale record fuzzily matches to scotland .', 'tostr': 'filter_eq { all_rows ; locale ; scotland }'}, 'ends won'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; locale ; scotland } ; ends won }', 'tointer': 'select the rows whose locale record fuzzily matches to scotland . take the ends won record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; locale ; canada } ; ends won } ; hop { filter_eq { all_rows ; locale ; scotland } ; ends won } } = true', 'tointer': 'select the rows whose locale record fuzzily matches to canada . take the ends won record of this row . select the rows whose locale record fuzzily matches to scotland . take the ends won record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; locale ; canada } ; ends won } ; hop { filter_eq { all_rows ; locale ; scotland } ; ends won } } = true | select the rows whose locale record fuzzily matches to canada . take the ends won record of this row . select the rows whose locale record fuzzily matches to scotland . take the ends won 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, 'locale_7': 7, 'canada_8': 8, 'ends won_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'locale_11': 11, 'scotland_12': 12, 'ends won_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', 'locale_7': 'locale', 'canada_8': 'canada', 'ends won_9': 'ends won', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'locale_11': 'locale', 'scotland_12': 'scotland', 'ends won_13': 'ends won'} | {'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'locale_7': [0], 'canada_8': [0], 'ends won_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'locale_11': [1], 'scotland_12': [1], 'ends won_13': [3]} | ['locale', 'skip', 'ends won', 'ends lost', 'blank ends', 'stolen ends', 'shot pct'] | [['sweden', 'anette norberg', '56', '39', '11', '25', '75 %'], ['united states', 'cassandra johnson', '53', '38', '13', '22', '76 %'], ['canada', 'jennifer jones', '48', '45', '3', '21', '68 %'], ['norway', 'dordi nordby', '46', '40', '11', '19', '72 %'], ['russia', 'olga jarkova', '47', '45', '17', '10', '70 %'], ['scotland', 'kelly wood', '53', '40', '6', '23', '69 %'], ['china', 'wang bingyu', '42', '45', '14', '13', '68 %'], ['switzerland', 'mirjam ott', '45', '48', '11', '13', '72 %'], ['japan', 'ayumi onodera', '41', '48', '8', '12', '66 %'], ['denmark', 'madeleine dupont', '36', '50', '10', '12', '63 %'], ['italy', 'diana gaspari', '39', '46', '7', '12', '65 %'], ['finland', 'kirsi nykã ¤ nen', '32', '55', '3', '9', '58 %']] |
miguel amaral | https://en.wikipedia.org/wiki/Miguel_Amaral | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1616765-1.html.csv | ordinal | the third 24 hours of le mans race that miguel amaral was in , he completed the most laps than any other one in the same event . | {'row': '3', 'col': '4', 'order': '1', 'col_other': '1', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'laps', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; laps ; 1 }'}, 'year'], 'result': '2008', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; laps ; 1 } ; year }'}, '2008'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; laps ; 1 } ; year } ; 2008 } = true', 'tointer': 'select the row whose laps record of all rows is 1st maximum . the year record of this row is 2008 .'} | eq { hop { nth_argmax { all_rows ; laps ; 1 } ; year } ; 2008 } = true | select the row whose laps record of all rows is 1st maximum . the year record of this row is 2008 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'num_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'laps_5': 5, '1_6': 6, 'year_7': 7, '2008_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'num_hop_1': 'num_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'laps_5': 'laps', '1_6': '1', 'year_7': 'year', '2008_8': '2008'} | {'eq_2': [3], 'result_3': [], 'num_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'laps_5': [0], '1_6': [0], 'year_7': [1], '2008_8': [2]} | ['year', 'co - drivers', 'class', 'laps', 'pos', 'class pos'] | [['2006', 'warren hughes miguel ángel de castro', 'lmp2', '196', 'dnf', 'dnf'], ['2007', 'warren hughes miguel ángel de castro', 'lmp2', '137', 'dnf', 'dnf'], ['2008', 'olivier pla guy smith', 'lmp2', '325', '20th', '4th'], ['2009', 'olivier pla guy smith', 'lmp2', '46', 'dnf', 'dnf'], ['2010', 'olivier pla warren hughes', 'lmp2', '318', '20th', '7th'], ['2011', 'olivier pla warren hughes', 'lmp1', '48', 'dnf', 'dnf']] |
2007 formula nippon season | https://en.wikipedia.org/wiki/2007_Formula_Nippon_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14330477-2.html.csv | majority | team impul had the most winners in the 2007 formula nippon season . | {'scope': 'all', 'col': '7', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'team impul', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'team', 'team impul'], 'result': True, 'ind': 0, 'tointer': 'for the team records of all rows , most of them fuzzily match to team impul .', 'tostr': 'most_eq { all_rows ; team ; team impul } = true'} | most_eq { all_rows ; team ; team impul } = true | for the team records of all rows , most of them fuzzily match to team impul . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'team_3': 3, 'team impul_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'team_3': 'team', 'team impul_4': 'team impul'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'team_3': [0], 'team impul_4': [0]} | ['round', 'track', 'date', 'pole position', 'fastest race lap', 'winner', 'team'] | [['1', 'fuji', '1 april', 'benoît tréluyer', 'benoît tréluyer', 'benoît tréluyer', 'team impul'], ['2', 'suzuka', '15 april', 'tsugio matsuda', 'hiroki yoshimoto', 'satoshi motoyama', 'team impul'], ['3', 'motegi', '20 may', 'tsugio matsuda', 'takashi kogure', 'takashi kogure', 'nakajima racing'], ['4', 'okayama', '10 june', 'takashi kogure', 'tsugio matsuda', 'ronnie quintarelli', 'team boss inging'], ['5', 'suzuka', '8 july', 'tsugio matsuda', 'tsugio matsuda', 'satoshi motoyama', 'team impul'], ['6', 'fuji', '26 august', 'satoshi motoyama', 'loïc duval', 'andré lotterer', "tom 's racing"], ['7', 'sugo', '16 september', 'takashi kogure', 'naoki yokomizo', 'takashi kogure', 'nakajima racing'], ['8', 'motegi', '21 october', 'takashi kogure', 'takashi kogure', 'takashi kogure', 'nakajima racing'], ['9', 'suzuka', '18 november', 'takashi kogure', 'andré lotterer', 'satoshi motoyama', 'team impul']] |
ka commuter jabodetabek | https://en.wikipedia.org/wiki/KA_Commuter_Jabodetabek | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15039992-1.html.csv | comparative | of the train lines of the ka commuter jabodetabek , the blue line serves more stations than the pink line . | {'row_1': '4', 'row_2': '6', 'col': '4', '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', 'line color', 'blue'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose line color record fuzzily matches to blue .', 'tostr': 'filter_eq { all_rows ; line color ; blue }'}, 'stations served'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; line color ; blue } ; stations served }', 'tointer': 'select the rows whose line color record fuzzily matches to blue . take the stations served record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'line color', 'pink'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose line color record fuzzily matches to pink .', 'tostr': 'filter_eq { all_rows ; line color ; pink }'}, 'stations served'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; line color ; pink } ; stations served }', 'tointer': 'select the rows whose line color record fuzzily matches to pink . take the stations served record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; line color ; blue } ; stations served } ; hop { filter_eq { all_rows ; line color ; pink } ; stations served } } = true', 'tointer': 'select the rows whose line color record fuzzily matches to blue . take the stations served record of this row . select the rows whose line color record fuzzily matches to pink . take the stations served record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; line color ; blue } ; stations served } ; hop { filter_eq { all_rows ; line color ; pink } ; stations served } } = true | select the rows whose line color record fuzzily matches to blue . take the stations served record of this row . select the rows whose line color record fuzzily matches to pink . take the stations served 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, 'line color_7': 7, 'blue_8': 8, 'stations served_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'line color_11': 11, 'pink_12': 12, 'stations served_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', 'line color_7': 'line color', 'blue_8': 'blue', 'stations served_9': 'stations served', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'line color_11': 'line color', 'pink_12': 'pink', 'stations served_13': 'stations served'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'line color_7': [0], 'blue_8': [0], 'stations served_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'line color_11': [1], 'pink_12': [1], 'stations served_13': [3]} | ['line color', 'line', 'route', 'stations served', 'length'] | [['orange', 'jakarta loopline', 'jatinegara to depok / bogor', '30', '71.8 km'], ['red', 'jakarta - bogor', 'jakarta kota to depok / bogor', '25', '54.6 km'], ['green', 'jakarta - south tangerang', 'tanah abang to serpong / parung panjang / maja', '19', '55.7 km'], ['blue', 'jakarta - bekasi', 'jakarta kota to bekasi', '18', '27.4 km'], ['brown', 'jakarta - tangerang', 'duri to tangerang', '9', '18.9 km'], ['pink', 'tanjung priok line', 'jakarta kota to tanjung priok', '4', '7.9 km ( total ) 1.6 km ( operated )']] |
1980 world series | https://en.wikipedia.org/wiki/1980_World_Series | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1218070-1.html.csv | comparative | the third match in the 1980 world series lasted longer than the fourth match . | {'row_1': '3', 'row_2': '4', 'col': '4', 'col_other': '1', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'game', '3'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose game record fuzzily matches to 3 .', 'tostr': 'filter_eq { all_rows ; game ; 3 }'}, 'time'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; game ; 3 } ; time }', 'tointer': 'select the rows whose game record fuzzily matches to 3 . take the time record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'game', '4'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose game record fuzzily matches to 4 .', 'tostr': 'filter_eq { all_rows ; game ; 4 }'}, 'time'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; game ; 4 } ; time }', 'tointer': 'select the rows whose game record fuzzily matches to 4 . take the time record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; game ; 3 } ; time } ; hop { filter_eq { all_rows ; game ; 4 } ; time } } = true', 'tointer': 'select the rows whose game record fuzzily matches to 3 . take the time record of this row . select the rows whose game record fuzzily matches to 4 . take the time record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; game ; 3 } ; time } ; hop { filter_eq { all_rows ; game ; 4 } ; time } } = true | select the rows whose game record fuzzily matches to 3 . take the time record of this row . select the rows whose game record fuzzily matches to 4 . take the time 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, 'game_7': 7, '3_8': 8, 'time_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'game_11': 11, '4_12': 12, 'time_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', 'game_7': 'game', '3_8': '3', 'time_9': 'time', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'game_11': 'game', '4_12': '4', 'time_13': 'time'} | {'greater_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'game_7': [0], '3_8': [0], 'time_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'game_11': [1], '4_12': [1], 'time_13': [3]} | ['game', 'date', 'location', 'time', 'attendance'] | [['1', 'october 14', 'veterans stadium', '3:01', '65791'], ['2', 'october 15', 'veterans stadium', '3:01', '65775'], ['3', 'october 17', 'royals stadium', '3:19', '42380'], ['4', 'october 18', 'royals stadium', '2:37', '42363'], ['5', 'october 19', 'royals stadium', '2:51', '42369'], ['6', 'october 21', 'veterans stadium', '3:00', '65838']] |
2001 new york jets season | https://en.wikipedia.org/wiki/2001_New_York_Jets_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10768951-1.html.csv | majority | the majority of games had more than 70,000 people in attendance . | {'scope': 'all', 'col': '6', 'most_or_all': 'most', 'criterion': 'greater_than', 'value': '70000', 'subset': None} | {'func': 'most_greater', 'args': ['all_rows', 'attendance', '70000'], 'result': True, 'ind': 0, 'tointer': 'for the attendance records of all rows , most of them are greater than 70000 .', 'tostr': 'most_greater { all_rows ; attendance ; 70000 } = true'} | most_greater { all_rows ; attendance ; 70000 } = true | for the attendance records of all rows , most of them are greater than 70000 . | 1 | 1 | {'most_greater_0': 0, 'result_1': 1, 'all_rows_2': 2, 'attendance_3': 3, '70000_4': 4} | {'most_greater_0': 'most_greater', 'result_1': 'true', 'all_rows_2': 'all_rows', 'attendance_3': 'attendance', '70000_4': '70000'} | {'most_greater_0': [1], 'result_1': [], 'all_rows_2': [0], 'attendance_3': [0], '70000_4': [0]} | ['week', 'date', 'opponent', 'result', 'game site', 'attendance'] | [['1', '2001 - 09 - 09', 'indianapolis colts', 'l 45 - 24', 'the meadowlands', '78606'], ['2', '2001 - 09 - 23', 'new england patriots', 'w 10 - 3', 'foxboro stadium', '60292'], ['3', '2001 - 10 - 01', 'san francisco 49ers', 'l 19 - 17', 'the meadowlands', '78722'], ['4', '2001 - 10 - 07', 'buffalo bills', 'w 42 - 36', 'ralph wilson stadium', '72654'], ['5', '2001 - 10 - 14', 'miami dolphins', 'w 21 - 17', 'the meadowlands', '78823'], ['6', '2001 - 10 - 21', 'st louis rams', 'l 34 - 14', 'the meadowlands', '78766'], ['7', '2001 - 10 - 28', 'carolina panthers', 'w 13 - 12', 'bank of america stadium', '72642'], ['8', '2001 - 11 - 04', 'new orleans saints', 'w 16 - 9', 'louisiana superdome', '70020'], ['9', '2001 - 11 - 11', 'kansas city chiefs', 'w 27 - 7', 'the meadowlands', '78234'], ['10', '2001 - 11 - 18', 'miami dolphins', 'w 24 - 0', 'pro player stadium', '74259'], ['11', '-', '-', '-', '-', ''], ['12', '2001 - 12 - 02', 'new england patriots', 'l 17 - 16', 'the meadowlands', '78712'], ['13', '2001 - 12 - 09', 'pittsburgh steelers', 'l 18 - 7', 'heinz field', '62884'], ['14', '2001 - 12 - 16', 'cincinnati bengals', 'w 15 - 14', 'the meadowlands', '77745'], ['15', '2001 - 12 - 23', 'indianapolis colts', 'w 29 - 28', 'rca dome', '56302'], ['16', '2001 - 12 - 30', 'buffalo bills', 'l 14 - 9', 'the meadowlands', '78200'], ['17', '2002 - 01 - 06', 'oakland raiders', 'w 24 - 22', 'network associates coliseum', '62011']] |
2005 - 06 u.s. città di palermo season | https://en.wikipedia.org/wiki/2005%E2%80%9306_U.S._Citt%C3%A0_di_Palermo_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11361788-3.html.csv | comparative | round of 32 - 1st leg had a lower attendance than round of 32 - 2nd leg during the 2005 - 06 u.s. città di palermo season . | {'row_1': '7', 'row_2': '8', 'col': '6', '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', 'round', 'round of 32 - 1st leg'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose round record fuzzily matches to round of 32 - 1st leg .', 'tostr': 'filter_eq { all_rows ; round ; round of 32 - 1st leg }'}, 'attendance'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; round ; round of 32 - 1st leg } ; attendance }', 'tointer': 'select the rows whose round record fuzzily matches to round of 32 - 1st leg . take the attendance record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'round', 'round of 32 - 2nd leg'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose round record fuzzily matches to round of 32 - 2nd leg .', 'tostr': 'filter_eq { all_rows ; round ; round of 32 - 2nd leg }'}, 'attendance'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; round ; round of 32 - 2nd leg } ; attendance }', 'tointer': 'select the rows whose round record fuzzily matches to round of 32 - 2nd leg . take the attendance record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; round ; round of 32 - 1st leg } ; attendance } ; hop { filter_eq { all_rows ; round ; round of 32 - 2nd leg } ; attendance } } = true', 'tointer': 'select the rows whose round record fuzzily matches to round of 32 - 1st leg . take the attendance record of this row . select the rows whose round record fuzzily matches to round of 32 - 2nd leg . take the attendance record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; round ; round of 32 - 1st leg } ; attendance } ; hop { filter_eq { all_rows ; round ; round of 32 - 2nd leg } ; attendance } } = true | select the rows whose round record fuzzily matches to round of 32 - 1st leg . take the attendance record of this row . select the rows whose round record fuzzily matches to round of 32 - 2nd leg . take the attendance 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, 'round_7': 7, 'round of 32 - 1st leg_8': 8, 'attendance_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'round_11': 11, 'round of 32 - 2nd leg_12': 12, 'attendance_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', 'round_7': 'round', 'round of 32 - 1st leg_8': 'round of 32 - 1st leg', 'attendance_9': 'attendance', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'round_11': 'round', 'round of 32 - 2nd leg_12': 'round of 32 - 2nd leg', 'attendance_13': 'attendance'} | {'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'round_7': [0], 'round of 32 - 1st leg_8': [0], 'attendance_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'round_11': [1], 'round of 32 - 2nd leg_12': [1], 'attendance_13': [3]} | ['date and time', 'round', 'opponent', 'venue', 'result', 'attendance'] | [['september 15 , 2005 - 20.30', '1st round - 1st leg', 'anorthosis famagusta', 'home', 'won 2 - 1', '13047'], ['september 29 , 2005 - 17.00', '1st round - 2nd leg', 'anorthosis famagusta', 'away', 'won 4 - 0', '12000'], ['october 20 , 2005 - 17.00', 'group stage - group b', 'maccabi petah tikva', 'away', 'won 2 - 1', '2000'], ['november 3 , 2005 - 21.00', 'group stage - group b', 'lokomotiv moscow', 'home', 'drew 0 - 0', '15823'], ['november 24 , 2005 - 21.15', 'group stage - group b', 'espanyol', 'away', 'drew 1 - 1', '22000'], ['december 15 , 2005 - 20.45', 'group stage - group b', 'brøndby', 'home', 'won 3 - 0', '4521'], ['february 16 , 2006 - 20.45', 'round of 32 - 1st leg', 'slavia praha', 'away', 'lost 1 - 2', '6706'], ['february 23 , 2006 - 16.00', 'round of 32 - 2nd leg', 'slavia praha', 'home', 'won 1 - 0', '8063'], ['march 9 , 2006 - 18.00', 'round of 16 - 1st leg', 'schalke 04', 'home', 'won 1 - 0', '10581'], ['march 16 , 2006 - 20.30', 'round of 16 - 2nd leg', 'schalke 04', 'away', 'lost 0 - 3', '52151']] |
1931 vfl season | https://en.wikipedia.org/wiki/1931_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10789881-3.html.csv | majority | all games of the 1931 vfl season were played on the 16th of may . | {'scope': 'all', 'col': '7', 'most_or_all': 'all', 'criterion': 'equal', 'value': '16 may 1931', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'date', '16 may 1931'], 'result': True, 'ind': 0, 'tointer': 'for the date records of all rows , all of them fuzzily match to 16 may 1931 .', 'tostr': 'all_eq { all_rows ; date ; 16 may 1931 } = true'} | all_eq { all_rows ; date ; 16 may 1931 } = true | for the date records of all rows , all of them fuzzily match to 16 may 1931 . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'date_3': 3, '16 may 1931_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'date_3': 'date', '16 may 1931_4': '16 may 1931'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'date_3': [0], '16 may 1931_4': [0]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['footscray', '7.10 ( 52 )', 'richmond', '13.16 ( 94 )', 'western oval', '30000', '16 may 1931'], ['collingwood', '13.16 ( 94 )', 'south melbourne', '10.13 ( 73 )', 'victoria park', '15000', '16 may 1931'], ['carlton', '18.18 ( 126 )', 'essendon', '5.14 ( 44 )', 'princes park', '20000', '16 may 1931'], ['st kilda', '10.12 ( 72 )', 'hawthorn', '10.8 ( 68 )', 'junction oval', '14000', '16 may 1931'], ['melbourne', '12.15 ( 87 )', 'geelong', '11.17 ( 83 )', 'mcg', '19767', '16 may 1931'], ['north melbourne', '6.12 ( 48 )', 'fitzroy', '12.16 ( 88 )', 'arden street oval', '7000', '16 may 1931']] |
list of vancouver canucks draft picks | https://en.wikipedia.org/wiki/List_of_Vancouver_Canucks_draft_picks | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11636955-36.html.csv | count | for three players in one of the canucks ' drafts , the pl gp value was 0 . | {'scope': 'all', 'criterion': 'equal', 'value': '0', 'result': '3', 'col': '6', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'pl gp', '0'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose pl gp record is equal to 0 .', 'tostr': 'filter_eq { all_rows ; pl gp ; 0 }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; pl gp ; 0 } }', 'tointer': 'select the rows whose pl gp record is equal to 0 . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; pl gp ; 0 } } ; 3 } = true', 'tointer': 'select the rows whose pl gp record is equal to 0 . the number of such rows is 3 .'} | eq { count { filter_eq { all_rows ; pl gp ; 0 } } ; 3 } = true | select the rows whose pl gp 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, 'pl gp_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', 'pl gp_5': 'pl gp', '0_6': '0', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'pl gp_5': [0], '0_6': [0], '3_7': [2]} | ['rd', 'pick', 'player', 'team ( league )', 'reg gp', 'pl gp'] | [['1', '26', 'cory schneider', 'phillips academy ( mass )', '98', '10'], ['3', '91', 'alexander edler', 'jamtland ( swe )', '431', '59'], ['4', '125', 'andrew sarauer', 'langley hornets ( bchl )', '0', '0'], ['5', '159', 'mike brown', 'university of michigan ( ncaa )', '39', '2'], ['6', '189', 'julien ellis', 'shawinigan cataractes ( qmjhl )', '0', '0'], ['8', '254', 'david schulz', 'swift current broncos ( whl )', '0', '0'], ['9', '287', 'jannik hansen', 'malmã jr ( swe2 )', '318', '58']] |
united states house of representatives elections , 1998 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1998 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1341453-44.html.csv | majority | all of the results were re-elections for the incumbents in the 1998 house of representatives elections . | {'scope': 'all', 'col': '5', 'most_or_all': 'all', 'criterion': 'equal', 'value': 're - elected', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'results', 're - elected'], 'result': True, 'ind': 0, 'tointer': 'for the results records of all rows , all of them fuzzily match to re - elected .', 'tostr': 'all_eq { all_rows ; results ; re - elected } = true'} | all_eq { all_rows ; results ; re - elected } = true | for the results records of all rows , all of them fuzzily match to re - elected . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'results_3': 3, 're - elected_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'results_3': 'results', 're - elected_4': 're - elected'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'results_3': [0], 're - elected_4': [0]} | ['district', 'incumbent', 'party', 'first elected', 'results', 'candidates'] | [['tennessee 1', 'william l jenkins', 'republican', '1996', 're - elected', 'william l jenkins ( r ) 69 % kay white ( d ) 31 %'], ['tennessee 2', 'jimmy duncan jr', 'republican', '1988', 're - elected', 'jimmy duncan jr ( r ) unopposed'], ['tennessee 3', 'zach wamp', 'republican', '1994', 're - elected', 'zach wamp ( r ) 67 % lewis lewis ( d ) 33 %'], ['tennessee 4', 'van hilleary', 'republican', '1994', 're - elected', 'van hilleary ( r ) 60 % jerry d cooper ( d ) 40 %'], ['tennessee 5', 'bob clement', 'democratic', '1988', 're - elected', 'bob clement ( d ) 83 %'], ['tennessee 6', 'bart gordon', 'democratic', '1984', 're - elected', 'bart gordon ( d ) 55 % walt massey ( r ) 45 %'], ['tennessee 7', 'ed bryant', 'republican', '1994', 're - elected', 'ed bryant ( r ) unopposed'], ['tennessee 8', 'john tanner', 'democratic', '1988', 're - elected', 'john tanner ( d ) unopposed']] |
2008 wnba draft | https://en.wikipedia.org/wiki/2008_WNBA_draft | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14122892-3.html.csv | ordinal | candice wiggins , from stanford , was the 3rd person drafted to the wnba in 2008 . | {'row': '3', 'col': '1', 'order': '3', 'col_other': '2,5', 'max_or_min': 'min_to_max', 'value_mentioned': 'yes', 'scope': 'all', 'subset': None} | {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'nth_min', 'args': ['all_rows', 'pick', '3'], 'result': '3', 'ind': 0, 'tostr': 'nth_min { all_rows ; pick ; 3 }', 'tointer': 'the 3rd minimum pick record of all rows is 3 .'}, '3'], 'result': True, 'ind': 1, 'tostr': 'eq { nth_min { all_rows ; pick ; 3 } ; 3 }', 'tointer': 'the 3rd minimum pick record of all rows is 3 .'}, {'func': 'and', 'args': [{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'pick', '3'], 'result': None, 'ind': 2, 'tostr': 'nth_argmin { all_rows ; pick ; 3 }'}, 'player'], 'result': 'candice wiggins', 'ind': 3, 'tostr': 'hop { nth_argmin { all_rows ; pick ; 3 } ; player }'}, 'candice wiggins'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { nth_argmin { all_rows ; pick ; 3 } ; player } ; candice wiggins }', 'tointer': 'the player record of the row with 3rd minimum pick record is candice wiggins .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'pick', '3'], 'result': None, 'ind': 2, 'tostr': 'nth_argmin { all_rows ; pick ; 3 }'}, 'school / club team'], 'result': 'stanford', 'ind': 5, 'tostr': 'hop { nth_argmin { all_rows ; pick ; 3 } ; school / club team }'}, 'stanford'], 'result': True, 'ind': 6, 'tostr': 'eq { hop { nth_argmin { all_rows ; pick ; 3 } ; school / club team } ; stanford }', 'tointer': 'the school / club team record of the row with 3rd minimum pick record is stanford .'}], 'result': True, 'ind': 7, 'tostr': 'and { eq { hop { nth_argmin { all_rows ; pick ; 3 } ; player } ; candice wiggins } ; eq { hop { nth_argmin { all_rows ; pick ; 3 } ; school / club team } ; stanford } }', 'tointer': 'the player record of the row with 3rd minimum pick record is candice wiggins . the school / club team record of the row with 3rd minimum pick record is stanford .'}], 'result': True, 'ind': 8, 'tostr': 'and { eq { nth_min { all_rows ; pick ; 3 } ; 3 } ; and { eq { hop { nth_argmin { all_rows ; pick ; 3 } ; player } ; candice wiggins } ; eq { hop { nth_argmin { all_rows ; pick ; 3 } ; school / club team } ; stanford } } } = true', 'tointer': 'the 3rd minimum pick record of all rows is 3 . the player record of the row with 3rd minimum pick record is candice wiggins . the school / club team record of the row with 3rd minimum pick record is stanford .'} | and { eq { nth_min { all_rows ; pick ; 3 } ; 3 } ; and { eq { hop { nth_argmin { all_rows ; pick ; 3 } ; player } ; candice wiggins } ; eq { hop { nth_argmin { all_rows ; pick ; 3 } ; school / club team } ; stanford } } } = true | the 3rd minimum pick record of all rows is 3 . the player record of the row with 3rd minimum pick record is candice wiggins . the school / club team record of the row with 3rd minimum pick record is stanford . | 10 | 9 | {'and_8': 8, 'result_9': 9, 'eq_1': 1, 'nth_min_0': 0, 'all_rows_10': 10, 'pick_11': 11, '3_12': 12, '3_13': 13, 'and_7': 7, 'str_eq_4': 4, 'str_hop_3': 3, 'nth_argmin_2': 2, 'all_rows_14': 14, 'pick_15': 15, '3_16': 16, 'player_17': 17, 'candice wiggins_18': 18, 'str_eq_6': 6, 'str_hop_5': 5, 'school / club team_19': 19, 'stanford_20': 20} | {'and_8': 'and', 'result_9': 'true', 'eq_1': 'eq', 'nth_min_0': 'nth_min', 'all_rows_10': 'all_rows', 'pick_11': 'pick', '3_12': '3', '3_13': '3', 'and_7': 'and', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'nth_argmin_2': 'nth_argmin', 'all_rows_14': 'all_rows', 'pick_15': 'pick', '3_16': '3', 'player_17': 'player', 'candice wiggins_18': 'candice wiggins', 'str_eq_6': 'str_eq', 'str_hop_5': 'str_hop', 'school / club team_19': 'school / club team', 'stanford_20': 'stanford'} | {'and_8': [9], 'result_9': [], 'eq_1': [8], 'nth_min_0': [1], 'all_rows_10': [0], 'pick_11': [0], '3_12': [0], '3_13': [1], 'and_7': [8], 'str_eq_4': [7], 'str_hop_3': [4], 'nth_argmin_2': [3, 5], 'all_rows_14': [2], 'pick_15': [2], '3_16': [2], 'player_17': [3], 'candice wiggins_18': [4], 'str_eq_6': [7], 'str_hop_5': [6], 'school / club team_19': [5], 'stanford_20': [6]} | ['pick', 'player', 'nationality', 'wnba team', 'school / club team'] | [['1', 'candace parker', 'united states', 'los angeles sparks', 'tennessee'], ['2', 'sylvia fowles', 'united states', 'chicago sky', 'lsu'], ['3', 'candice wiggins', 'united states', 'minnesota lynx', 'stanford'], ['4', 'alexis hornbuckle', 'united states', 'detroit shock ( from atl , via sea )', 'tennessee'], ['5', 'matee ajavon', 'united states', 'houston comets', 'rutgers'], ['6', 'crystal langhorne', 'united states', 'washington mystics', 'maryland'], ['7', 'essence carson', 'united states', 'new york liberty', 'rutgers'], ['8', 'tamera young', 'united states', 'atlanta dream ( from sea )', 'james madison'], ['9', 'amber holt', 'united states', 'connecticut sun', 'middle tennessee'], ['10', 'laura harper', 'united states', 'sacramento monarchs', 'maryland'], ['11', 'tasha humphrey', 'united states', 'detroit shock ( from sa )', 'georgia'], ['12', 'ketia swanier', 'united states', 'connecticut sun ( from ind )', 'connecticut'], ['13', 'latoya pringle', 'united states', 'phoenix mercury', 'north carolina'], ['14', 'erlana larkins', 'united states', 'new york liberty ( from det )', 'north carolina']] |
tunisair express | https://en.wikipedia.org/wiki/TunisAir_Express | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1622736-2.html.csv | majority | tunisair express went mostly through the country of tunisia . | {'scope': 'all', 'col': '2', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'tunisia', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'country', 'tunisia'], 'result': True, 'ind': 0, 'tointer': 'for the country records of all rows , most of them fuzzily match to tunisia .', 'tostr': 'most_eq { all_rows ; country ; tunisia } = true'} | most_eq { all_rows ; country ; tunisia } = true | for the country records of all rows , most of them fuzzily match to tunisia . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'country_3': 3, 'tunisia_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'country_3': 'country', 'tunisia_4': 'tunisia'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'country_3': [0], 'tunisia_4': [0]} | ['city', 'country', 'iata', 'icao', 'airport'] | [['benghazi', 'libya', 'ben', 'hllb', 'benina international airport'], ['djerba', 'tunisia', 'dje', 'dttj', 'djerba - zarzis international airport'], ['gabès', 'tunisia', 'gae', 'dttg', 'gabès - matmata international airport'], ['gafsa', 'tunisia', 'gaf', 'dttf', 'gafsa - ksar international airport'], ['malta', 'malta', 'mla', 'lmml', 'malta international airport'], ['misrata', 'libya', 'mra', 'hlms', 'misrata airport'], ['monastir', 'tunisia', 'mir', 'dtmb', 'monastir habib bourguiba international airport'], ['naples', 'italy', 'nap', 'lirn', 'naples international airport'], ['palermo', 'italy', 'pmo', 'licj', 'falcone - borsellino airport'], ['sfax', 'tunisia', 'sfa', 'dttx', 'sfax - thyna international airport'], ['tabarka', 'tunisia', 'tbj', 'dtka', 'tabarka - ain draham international airport'], ['tozeur', 'tunisia', 'toe', 'dttz', 'tozeur - nefta international airport'], ['tripoli', 'libya', 'tip', 'hllt', 'tripoli international airport'], ['tunis', 'tunisia', 'tun', 'dtaa', 'tunis - carthage international airport']] |
eurovision song contest 1966 | https://en.wikipedia.org/wiki/Eurovision_Song_Contest_1966 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-184807-1.html.csv | majority | most of the songs in french at the 1966 eurovision song contest scored less than 10 points . | {'scope': 'subset', 'col': '7', 'most_or_all': 'most', 'criterion': 'less_than', 'value': '10', 'subset': {'col': '2', 'criterion': 'equal', 'value': 'french'}} | {'func': 'most_less', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'language', 'french'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; language ; french }', 'tointer': 'select the rows whose language record fuzzily matches to french .'}, 'points', '10'], 'result': True, 'ind': 1, 'tointer': 'select the rows whose language record fuzzily matches to french . for the points records of these rows , most of them are less than 10 .', 'tostr': 'most_less { filter_eq { all_rows ; language ; french } ; points ; 10 } = true'} | most_less { filter_eq { all_rows ; language ; french } ; points ; 10 } = true | select the rows whose language record fuzzily matches to french . for the points records of these rows , most of them are less than 10 . | 2 | 2 | {'most_less_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, 'language_4': 4, 'french_5': 5, 'points_6': 6, '10_7': 7} | {'most_less_1': 'most_less', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'language_4': 'language', 'french_5': 'french', 'points_6': 'points', '10_7': '10'} | {'most_less_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'language_4': [0], 'french_5': [0], 'points_6': [1], '10_7': [1]} | ['draw', 'language', 'artist', 'song', 'english translation', 'place', 'points'] | [['01', 'german', 'margot eskens', 'die zeiger der uhr', 'the hands of the clock', '10', '7'], ['02', 'danish', 'ulla pia', "stop - mens legen er go '", "stop while the going 's good", '14', '4'], ['03', 'french', 'tonia', 'un peu de poivre , un peu de sel', 'a bit of pepper , a bit of salt', '4', '14'], ['04', 'french', 'michèle torr', "ce soir je t ' attendais", 'tonight , i waited for you', '10', '7'], ['05', 'slovene', 'berta ambrož', 'brez besed', 'without words', '7', '9'], ['06', 'norwegian', 'åse kleveland', 'intet er nytt under solen', 'nothing is new under the sun', '3', '15'], ['07', 'finnish', 'ann christine', 'playboy', '-', '10', '7'], ['08', 'portuguese', 'madalena iglésias', 'ele e ela', 'he and she', '13', '6'], ['09', 'german', 'udo jürgens', 'merci , chérie', 'thank you , darling', '1', '31'], ['10', 'swedish', 'lill lindfors & svante thuresson', 'nygammal vals', 'new , yet familiar , waltz', '2', '16'], ['11', 'spanish', 'raphael', 'yo soy aquél', "i 'm that one", '7', '9'], ['12', 'french', 'madeleine pascal', 'ne vois - tu pas', "do n't you see", '6', '12'], ['13', 'french', 'tereza kesovija', 'bien plus fort', 'altogether stronger', '17', '0'], ['14', 'italian', 'domenico modugno', 'dio , come ti amo', 'god , how i love you', '17', '0'], ['15', 'french', 'dominique walter', 'chez nous', 'our place', '16', '1'], ['16', 'dutch', 'milly scott', 'fernando en filippo', 'fernando and filippo', '15', '2'], ['17', 'english', 'dickie rock', 'come back to stay', '-', '4', '14'], ['18', 'english', 'kenneth mckellar', 'a man without love', '-', '9', '8']] |
2008 - 09 oklahoma city thunder season | https://en.wikipedia.org/wiki/2008%E2%80%9309_Oklahoma_City_Thunder_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17355628-5.html.csv | count | carl watson had at least a share of the high assists in 13 games . | {'scope': 'all', 'criterion': 'equal', 'value': 'earl watson', 'result': '13', 'col': '6', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'high assists', 'earl watson'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose high assists record fuzzily matches to earl watson .', 'tostr': 'filter_eq { all_rows ; high assists ; earl watson }'}], 'result': '13', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; high assists ; earl watson } }', 'tointer': 'select the rows whose high assists record fuzzily matches to earl watson . the number of such rows is 13 .'}, '13'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; high assists ; earl watson } } ; 13 } = true', 'tointer': 'select the rows whose high assists record fuzzily matches to earl watson . the number of such rows is 13 .'} | eq { count { filter_eq { all_rows ; high assists ; earl watson } } ; 13 } = true | select the rows whose high assists record fuzzily matches to earl watson . the number of such rows is 13 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'high assists_5': 5, 'earl watson_6': 6, '13_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'high assists_5': 'high assists', 'earl watson_6': 'earl watson', '13_7': '13'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'high assists_5': [0], 'earl watson_6': [0], '13_7': [2]} | ['game', 'date', 'team', 'score', 'high points', 'high assists', 'location attendance', 'record'] | [['2', 'november 1', 'houston', 'l 77 - 89 ( ot )', 'kevin durant ( 26 )', 'earl watson ( 8 )', 'toyota center 16996', '0 - 2'], ['3', 'november 2', 'minnesota', 'w 88 - 85 ( ot )', 'kevin durant ( 18 )', 'earl watson ( 4 )', 'ford center 18163', '1 - 2'], ['4', 'november 5', 'boston', 'l 83 - 96 ( ot )', 'kevin durant ( 17 )', 'earl watson ( 5 )', 'ford center 19136', '1 - 3'], ['5', 'november 7', 'utah', 'l 97 - 104 ( ot )', 'kevin durant ( 24 )', 'kevin durant , earl watson ( 3 )', 'energysolutions arena 19911', '1 - 4'], ['6', 'november 9', 'atlanta', 'l 85 - 89 ( ot )', 'kevin durant ( 20 )', 'earl watson ( 6 )', 'ford center 18231', '1 - 5'], ['7', 'november 10', 'indiana', 'l 99 - 107 ( ot )', 'kevin durant ( 37 )', 'earl watson ( 9 )', 'conseco fieldhouse 10165', '1 - 6'], ['8', 'november 12', 'orlando', 'l 92 - 109 ( ot )', 'jeff green ( 25 )', 'earl watson ( 8 )', 'ford center 18185', '1 - 7'], ['9', 'november 14', 'new york', 'l 106 - 116 ( ot )', 'kevin durant ( 23 )', 'earl watson ( 8 )', 'madison square garden 18008', '1 - 8'], ['10', 'november 15', 'philadelphia', 'l 85 - 110 ( ot )', 'jeff green ( 21 )', 'jeff green , russell westbrook ( 4 )', 'wachovia center 13385', '1 - 9'], ['11', 'november 17', 'houston', 'l 89 - 100 ( ot )', 'kevin durant ( 29 )', 'kevin durant , earl watson ( 4 )', 'ford center 18145', '1 - 10'], ['12', 'november 19', 'la clippers', 'l 88 - 108 ( ot )', 'kevin durant ( 18 )', 'earl watson ( 5 )', 'ford center 18312', '1 - 11'], ['13', 'november 21', 'new orleans', 'l 80 - 105 ( ot )', 'kevin durant ( 17 )', 'earl watson ( 4 )', 'ford center 19136', '1 - 12'], ['14', 'november 22', 'new orleans', 'l 97 - 109 ( ot )', 'kevin durant ( 30 )', 'russell westbrook ( 11 )', 'new orleans arena 16023', '1 - 13'], ['15', 'november 25', 'phoenix', 'l 98 - 99 ( ot )', 'kevin durant ( 29 )', 'earl watson ( 13 )', 'ford center 19136', '1 - 14'], ['16', 'november 26', 'cleveland', 'l 82 - 117 ( ot )', 'chris wilcox ( 14 )', 'russell westbrook , kyle weaver ( 5 )', 'quicken loans arena 19753', '1 - 15'], ['17', 'november 28', 'minnesota', 'l 103 - 105 ( ot )', 'kevin durant , jeff green ( 22 )', 'russell westbrook ( 8 )', 'ford center 18229', '1 - 16'], ['18', 'november 29', 'memphis', 'w 111 - 103 ( ot )', 'kevin durant ( 30 )', 'earl watson ( 7 )', 'fedexforum 11977', '2 - 16']] |
2005 pba draft | https://en.wikipedia.org/wiki/2005_PBA_draft | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11779131-2.html.csv | unique | jay washington was the only player picked who attended eckerd college . | {'scope': 'all', 'row': '1', 'col': '5', 'col_other': '2', 'criterion': 'equal', 'value': 'eckerd', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'college', 'eckerd'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose college record fuzzily matches to eckerd .', 'tostr': 'filter_eq { all_rows ; college ; eckerd }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; college ; eckerd } }', 'tointer': 'select the rows whose college record fuzzily matches to eckerd . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'college', 'eckerd'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose college record fuzzily matches to eckerd .', 'tostr': 'filter_eq { all_rows ; college ; eckerd }'}, 'player'], 'result': 'jay washington', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; college ; eckerd } ; player }'}, 'jay washington'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; college ; eckerd } ; player } ; jay washington }', 'tointer': 'the player record of this unqiue row is jay washington .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; college ; eckerd } } ; eq { hop { filter_eq { all_rows ; college ; eckerd } ; player } ; jay washington } } = true', 'tointer': 'select the rows whose college record fuzzily matches to eckerd . there is only one such row in the table . the player record of this unqiue row is jay washington .'} | and { only { filter_eq { all_rows ; college ; eckerd } } ; eq { hop { filter_eq { all_rows ; college ; eckerd } ; player } ; jay washington } } = true | select the rows whose college record fuzzily matches to eckerd . there is only one such row in the table . the player record of this unqiue row is jay washington . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'college_7': 7, 'eckerd_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'player_9': 9, 'jay washington_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'college_7': 'college', 'eckerd_8': 'eckerd', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'player_9': 'player', 'jay washington_10': 'jay washington'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'college_7': [0], 'eckerd_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'player_9': [2], 'jay washington_10': [3]} | ['pick', 'player', 'country of origin', 'pba team', 'college'] | [['1', 'jay washington', 'united states', 'air21 express', 'eckerd'], ['2', 'alex cabagnot', 'united states', 'sta lucia realtors', 'hawaii - hilo'], ['3', 'dennis miranda', 'philippines', 'coca - cola tigers', 'feu'], ['4', 'jondan salvador', 'philippines', 'purefoods chunkee giants', 'st benilde'], ['5', 'mark cardona', 'philippines', 'air21 express', 'de la salle'], ['6', 'niã ± o canaleta', 'philippines', 'air21 express', 'ue'], ['7', 'michael holper', 'united states', 'barangay ginebra kings', 'san diego state'], ['8', 'paolo hubalde', 'philippines', 'san miguel beermen', 'ue'], ['9', 'leo najorda', 'philippines', 'red bull barako', 'san sebastian']] |
list of cities , towns and villages in vojvodina | https://en.wikipedia.org/wiki/List_of_cities%2C_towns_and_villages_in_Vojvodina | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2562572-37.html.csv | ordinal | the city of aleksandrovo has the 2nd highest population among the towns and villages in vojvodina . | {'row': '2', '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', 'population ( 2011 )', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; population ( 2011 ) ; 2 }'}, 'settlement'], 'result': 'aleksandrovo', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; population ( 2011 ) ; 2 } ; settlement }'}, 'aleksandrovo'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; population ( 2011 ) ; 2 } ; settlement } ; aleksandrovo } = true', 'tointer': 'select the row whose population ( 2011 ) record of all rows is 2nd maximum . the settlement record of this row is aleksandrovo .'} | eq { hop { nth_argmax { all_rows ; population ( 2011 ) ; 2 } ; settlement } ; aleksandrovo } = true | select the row whose population ( 2011 ) record of all rows is 2nd maximum . the settlement record of this row is aleksandrovo . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'population (2011)_5': 5, '2_6': 6, 'settlement_7': 7, 'aleksandrovo_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', 'population (2011)_5': 'population ( 2011 )', '2_6': '2', 'settlement_7': 'settlement', 'aleksandrovo_8': 'aleksandrovo'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'population (2011)_5': [0], '2_6': [0], 'settlement_7': [1], 'aleksandrovo_8': [2]} | ['settlement', 'cyrillic name other names', 'type', 'population ( 2011 )', 'largest ethnic group ( 2002 )', 'dominant religion ( 2002 )'] | [['nova crnja', 'нова црња ( hungarian : magyarcsernye )', 'village', '1509', 'hungarians', 'catholic christianity'], ['aleksandrovo', 'александрово', 'village', '2130', 'serbs', 'orthodox christianity'], ['radojevo', 'радојево', 'village', '1056', 'serbs', 'orthodox christianity'], ['srpska crnja', 'српска црња', 'village', '3685', 'serbs', 'orthodox christianity'], ['toba', 'тоба ( hungarian : tóba )', 'village', '518', 'hungarians', 'catholic christianity']] |
2010 - 11 robert morris colonials men 's basketball team | https://en.wikipedia.org/wiki/2010%E2%80%9311_Robert_Morris_Colonials_men%27s_basketball_team | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-29970488-2.html.csv | unique | karon abraham is the only player that weighed 150 pounds . | {'scope': 'all', 'row': '1', 'col': '5', 'col_other': '1', 'criterion': 'equal', 'value': '150', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'weight ( lb )', '150'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose weight ( lb ) record is equal to 150 .', 'tostr': 'filter_eq { all_rows ; weight ( lb ) ; 150 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; weight ( lb ) ; 150 } }', 'tointer': 'select the rows whose weight ( lb ) record is equal to 150 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'weight ( lb )', '150'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose weight ( lb ) record is equal to 150 .', 'tostr': 'filter_eq { all_rows ; weight ( lb ) ; 150 }'}, 'name'], 'result': 'karon abraham', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; weight ( lb ) ; 150 } ; name }'}, 'karon abraham'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; weight ( lb ) ; 150 } ; name } ; karon abraham }', 'tointer': 'the name record of this unqiue row is karon abraham .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; weight ( lb ) ; 150 } } ; eq { hop { filter_eq { all_rows ; weight ( lb ) ; 150 } ; name } ; karon abraham } } = true', 'tointer': 'select the rows whose weight ( lb ) record is equal to 150 . there is only one such row in the table . the name record of this unqiue row is karon abraham .'} | and { only { filter_eq { all_rows ; weight ( lb ) ; 150 } } ; eq { hop { filter_eq { all_rows ; weight ( lb ) ; 150 } ; name } ; karon abraham } } = true | select the rows whose weight ( lb ) record is equal to 150 . there is only one such row in the table . the name record of this unqiue row is karon abraham . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'weight ( lb )_7': 7, '150_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'name_9': 9, 'karon abraham_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'weight ( lb )_7': 'weight ( lb )', '150_8': '150', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'name_9': 'name', 'karon abraham_10': 'karon abraham'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'weight ( lb )_7': [0], '150_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'name_9': [2], 'karon abraham_10': [3]} | ['name', '-', 'position', 'height', 'weight ( lb )', 'year', 'hometown', 'previous school'] | [['karon abraham', '4', 'guard', 'ft9in ( m )', '150', '2 sophomore', 'paterson , nj', 'paterson eastside hs'], ['lawrence bridges', '24', 'forward', 'ft5in ( m )', '220', '2 junior', 'detroit , mi', 'columbus state community college'], ['yann charles', '25', 'forward', 'ft5in ( m )', '220', '2 freshman', 'longueuil , qc , canada', 'champlain saint - albert hs'], ['russell johnson', '34', 'forward', 'ft6in ( m )', '180', '2 sophomore ( rs )', 'chester , pa', 'chester hs'], ['velton jones', '2', 'guard', 'ft0in ( m )', '170', '2 sophomore ( rs )', 'philadelphia , pa', 'northeast catholic hs'], ['treadwell lewis', '10', 'guard', 'ft10in ( m )', '170', '2 sophomore', 'shelton , ct', 'christian heritage school'], ['anthony myers', '5', 'guard', 'ft11in ( m )', '170', '2 freshman', 'washington , dc', 'charis prep'], ['elton roy', '15', 'guard', 'ft2in ( m )', '195', '2 freshman', 'houston , tx', 'yates hs'], ['lijah thompson', '11', 'forward / center', 'ft7in ( m )', '200', '2 sophomore', 'philadelphia , pa', 'monsignor bonner hs'], ['deion turman', '1', 'forward / center', 'ft8in ( m )', '215', '2 freshman', 'pittsburgh , pa', 'mt lebanon hs'], ['gary wallace', '14', 'guard', 'ft3in ( m )', '200', '2 senior', 'montclair , nj', 'seton hall preparatory school']] |
fifa puskás award | https://en.wikipedia.org/wiki/FIFA_Pusk%C3%A1s_Award | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-24765815-2.html.csv | superlative | in the fifa puskás award voting shown hamit altıntop received the highest percentage of the votes . | {'scope': 'all', 'col_superlative': '8', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '2', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'vote percentage'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; vote percentage }'}, 'player'], 'result': 'hamit altıntop', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; vote percentage } ; player }'}, 'hamit altıntop'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; vote percentage } ; player } ; hamit altıntop } = true', 'tointer': 'select the row whose vote percentage record of all rows is maximum . the player record of this row is hamit altıntop .'} | eq { hop { argmax { all_rows ; vote percentage } ; player } ; hamit altıntop } = true | select the row whose vote percentage record of all rows is maximum . the player record of this row is hamit altıntop . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'vote percentage_5': 5, 'player_6': 6, 'hamit altıntop_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'vote percentage_5': 'vote percentage', 'player_6': 'player', 'hamit altıntop_7': 'hamit altıntop'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'vote percentage_5': [0], 'player_6': [1], 'hamit altıntop_7': [2]} | ['rank', 'player', 'nationality', 'team', 'opponent', 'score', 'competition', 'vote percentage'] | [['1st', 'hamit altıntop', 'turkey', 'turkey', 'kazakhstan', '0 - 2', 'uefa euro 2012 qualifying group a', '40.55 %'], ['2nd', 'linus hallenius', 'sweden', 'hammarby if', 'syrianska fc', '2 - 0', '2010 superettan', '13.23 %'], ['3rd', 'matty burrows', 'northern ireland', 'glentoran', 'portadown', '1 - 0', '2010 - 11 ifa premiership', '10.61 %'], ['unranked', 'giovanni van bronckhorst', 'netherlands', 'netherlands', 'uruguay', '1 - 0', '2010 fifa world cup semi - final', 'n / a'], ['unranked', 'lionel messi', 'argentina', 'barcelona', 'valencia', '3 - 0', '2009 - 10 la liga', 'n / a'], ['unranked', 'samir nasri', 'france', 'arsenal', 'fc porto', '5 - 0', '2009 - 10 uefa champions league knockout phase', 'n / a'], ['unranked', 'neymar', 'brazil', 'santos', 'santo andré', '2 - 1', '2010 campeonato paulista', 'n / a'], ['unranked', 'arjen robben', 'netherlands', 'bayern munich', 'schalke 04', '1 - 0', '2009 - 10 dfb - pokal semifinals', 'n / a'], ['unranked', 'siphiwe tshabalala', 'south africa', 'south africa', 'mexico', '1 - 0', '2010 fifa world cup group stage', 'n / a']] |
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