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ambala ( lok sabha constituency )
|
https://en.wikipedia.org/wiki/Ambala_%28Lok_Sabha_constituency%29
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17922000-1.html.csv
|
count
|
in the district of ambala , only two constituencies had a number of electorates ( 2009 ) exceeding 150000 .
|
{'scope': 'subset', 'criterion': 'greater_than', 'value': '150000', 'result': '2', 'col': '5', 'subset': {'col': '5', 'criterion': 'greater_than', 'value': '150000'}}
|
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'number of electorates ( 2009 )', '150000'], 'result': None, 'ind': 0, 'tostr': 'filter_greater { all_rows ; number of electorates ( 2009 ) ; 150000 }', 'tointer': 'select the rows whose number of electorates ( 2009 ) record is greater than 150000 .'}, 'number of electorates ( 2009 )', '150000'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose number of electorates ( 2009 ) record is greater than 150000 . among these rows , select the rows whose number of electorates ( 2009 ) record is greater than 150000 .', 'tostr': 'filter_greater { filter_greater { all_rows ; number of electorates ( 2009 ) ; 150000 } ; number of electorates ( 2009 ) ; 150000 }'}], 'result': '2', 'ind': 2, 'tostr': 'count { filter_greater { filter_greater { all_rows ; number of electorates ( 2009 ) ; 150000 } ; number of electorates ( 2009 ) ; 150000 } }', 'tointer': 'select the rows whose number of electorates ( 2009 ) record is greater than 150000 . among these rows , select the rows whose number of electorates ( 2009 ) record is greater than 150000 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_greater { filter_greater { all_rows ; number of electorates ( 2009 ) ; 150000 } ; number of electorates ( 2009 ) ; 150000 } } ; 2 } = true', 'tointer': 'select the rows whose number of electorates ( 2009 ) record is greater than 150000 . among these rows , select the rows whose number of electorates ( 2009 ) record is greater than 150000 . the number of such rows is 2 .'}
|
eq { count { filter_greater { filter_greater { all_rows ; number of electorates ( 2009 ) ; 150000 } ; number of electorates ( 2009 ) ; 150000 } } ; 2 } = true
|
select the rows whose number of electorates ( 2009 ) record is greater than 150000 . among these rows , select the rows whose number of electorates ( 2009 ) record is greater than 150000 . the number of such rows is 2 .
|
4
|
4
|
{'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_greater_1': 1, 'filter_greater_0': 0, 'all_rows_5': 5, 'number of electorates (2009)_6': 6, '150000_7': 7, 'number of electorates (2009)_8': 8, '150000_9': 9, '2_10': 10}
|
{'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_greater_1': 'filter_greater', 'filter_greater_0': 'filter_greater', 'all_rows_5': 'all_rows', 'number of electorates (2009)_6': 'number of electorates ( 2009 )', '150000_7': '150000', 'number of electorates (2009)_8': 'number of electorates ( 2009 )', '150000_9': '150000', '2_10': '2'}
|
{'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_greater_1': [2], 'filter_greater_0': [1], 'all_rows_5': [0], 'number of electorates (2009)_6': [0], '150000_7': [0], 'number of electorates (2009)_8': [1], '150000_9': [1], '2_10': [3]}
|
['constituency number', 'name', 'reserved for ( sc / st / none )', 'district', 'number of electorates ( 2009 )']
|
[['1', 'kalka', 'none', 'panchkula', '114353'], ['2', 'panchkula', 'none', 'panchkula', '130932'], ['3', 'naraingarh', 'none', 'ambala', '133850'], ['4', 'ambala cantonment', 'none', 'ambala', '134401'], ['5', 'ambala city', 'none', 'ambala', '172404'], ['6', 'mulana', 'sc', 'ambala', '157696'], ['7', 'sadhaura', 'sc', 'yamuna nagar', '149418'], ['8', 'jagadhri', 'none', 'yamuna nagar', '137791'], ['9', 'yamuna nagar', 'none', 'yamuna nagar', '128829']]
|
little league world series ( new england region )
|
https://en.wikipedia.org/wiki/Little_League_World_Series_%28New_England_Region%29
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-13011547-1.html.csv
|
majority
|
in the little league world series during the years 2001 to 2012 , lincoln ll won most often in rhode island .
|
{'scope': 'all', 'col': '6', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'lincoln ll lincoln', 'subset': None}
|
{'func': 'most_str_eq', 'args': ['all_rows', 'rhode island', 'lincoln ll lincoln'], 'result': True, 'ind': 0, 'tointer': 'for the rhode island records of all rows , most of them fuzzily match to lincoln ll lincoln .', 'tostr': 'most_eq { all_rows ; rhode island ; lincoln ll lincoln } = true'}
|
most_eq { all_rows ; rhode island ; lincoln ll lincoln } = true
|
for the rhode island records of all rows , most of them fuzzily match to lincoln ll lincoln .
|
1
|
1
|
{'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'rhode island_3': 3, 'lincoln ll lincoln_4': 4}
|
{'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'rhode island_3': 'rhode island', 'lincoln ll lincoln_4': 'lincoln ll lincoln'}
|
{'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'rhode island_3': [0], 'lincoln ll lincoln_4': [0]}
|
['year', 'connecticut', 'maine', 'massachusetts', 'new hampshire', 'rhode island', 'vermont']
|
[['2001', 'yalesville ll wallingford', 'lincoln county ll damariscotta', 'pittsfield south ll pittsfield', 'manchester east ll manchester', 'lincoln ll lincoln', 'south burlington ll south burlington'], ['2002', 'orange ll orange', 'westbrook ll westbrook', 'jesse burkett ll worcester', 'portsmouth ll portsmouth', 'portsmouth ll portsmouth', 'essex junction ll essex junction'], ['2003', 'north stamford ll stamford', 'augusta west ll augusta', 'saugus american ll saugus', 'rye ll rye', 'lincoln ll lincoln', 'south burlington ll south burlington'], ['2004', 'berlin ll berlin', 'west biddeford ll biddeford', 'jesse burkett ll worcester', 'portsmouth ll portsmouth', 'lincoln ll lincoln', 'essex junction ll essex junction'], ['2005', 'farmington ll farmington', 'westbrook ll westbrook', 'dudley ll dudley', 'bedford ll bedford', 'cranston western ll cranston', 'shelburne ll shelburne'], ['2006', 'glastonbury american ll glastonbury', 'yarmouth ll yarmouth', 'peabody western ll peabody', 'portsmouth ll portsmouth', 'lincoln ll lincoln', 'colchester ll colchester'], ['2007', 'shelton national ll shelton', 'portland north ll portland', 'walpole american ll walpole', 'portsmouth ll portsmouth', 'cranston western ll cranston', 'essex junction ll essex junction'], ['2008', 'shelton national ll shelton', 'camden - rockport ll camden', 'parkway national ll boston ( west roxbury )', 'manchester north ll manchester', 'cranston western ll cranston', 'williston ll williston'], ['2009', 'glastonbury national ll glastonbury', 'bangor east ll bangor', 'peabody western ll peabody', 'portsmouth ll portsmouth', 'lincoln ll lincoln', 'brattleboro ll brattleboro'], ['2010', 'fairfield american ll fairfield', 'bangor east ll bangor', 'southborough youth ll southborough', 'portsmouth ll portsmouth', 'cumberland national ll cumberland', 'shelburne ll shelburne'], ['2011', 'fairfield american ll fairfield', 'yarmouth ll yarmouth', 'andover national ll andover', 'goffstown ll goffstown', 'cumberland american ll cumberland', 'barre community ll barre'], ['2012', 'fairfield american ll fairfield', 'scarborough ll scarborough', 'wellesley south ll wellesley', 'bedford ll bedford', 'coventry american ll coventry', 'south burlington ll south burlington']]
|
cruizer - class brig - sloop
|
https://en.wikipedia.org/wiki/Cruizer-class_brig-sloop
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16304334-5.html.csv
|
unique
|
the magnet cruizer-class brig-sloop is the only one that had a fate of being wrecked .
|
{'scope': 'all', 'row': '9', 'col': '5', 'col_other': '1', 'criterion': 'equal', 'value': 'wrecked', 'subset': None}
|
{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'fate', 'wrecked'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose fate record fuzzily matches to wrecked .', 'tostr': 'filter_eq { all_rows ; fate ; wrecked }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; fate ; wrecked } }', 'tointer': 'select the rows whose fate record fuzzily matches to wrecked . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'fate', 'wrecked'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose fate record fuzzily matches to wrecked .', 'tostr': 'filter_eq { all_rows ; fate ; wrecked }'}, 'name'], 'result': 'magnet', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; fate ; wrecked } ; name }'}, 'magnet'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; fate ; wrecked } ; name } ; magnet }', 'tointer': 'the name record of this unqiue row is magnet .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; fate ; wrecked } } ; eq { hop { filter_eq { all_rows ; fate ; wrecked } ; name } ; magnet } } = true', 'tointer': 'select the rows whose fate record fuzzily matches to wrecked . there is only one such row in the table . the name record of this unqiue row is magnet .'}
|
and { only { filter_eq { all_rows ; fate ; wrecked } } ; eq { hop { filter_eq { all_rows ; fate ; wrecked } ; name } ; magnet } } = true
|
select the rows whose fate record fuzzily matches to wrecked . there is only one such row in the table . the name record of this unqiue row is magnet .
|
6
|
5
|
{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'fate_7': 7, 'wrecked_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'name_9': 9, 'magnet_10': 10}
|
{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'fate_7': 'fate', 'wrecked_8': 'wrecked', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'name_9': 'name', 'magnet_10': 'magnet'}
|
{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'fate_7': [0], 'wrecked_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'name_9': [2], 'magnet_10': [3]}
|
['name', 'ordered', 'builder', 'launched', 'fate']
|
[['derwent', '1 october 1806', 'isaac blackburn , turnchapel , plymouth', '23 may 1807', 'sold 1817'], ['eclair', '1 october 1806', 'matthew warren , brightlingsea , essex', '8 july 1807', 'broken up 1831'], ['eclipse', '1 october 1806', 'john king , dover', '4 august 1807', 'sold for mercantile use 1815'], ['barracouta', '1 october 1806', 'jabez bailey , ipswich', '6 july 1807', 'sold 1815'], ['nautilus', '1 october 1806', 'james betts , mistleythorn', '5 august 1807', 'broken up 1823'], ['pilot', '1 october 1806', 'robert guillaume , northam , southampton', '6 august 1807', 'sold 1828'], ['sparrowhawk', '1 october 1806', 'matthew warren , brightlingsea , essex', '20 august 1807', 'sold 1841'], ['zenobia', '1 october 1806', "josiah & thomas brindley , king 's lynn", '7 october 1807', 'sold 1835'], ['magnet', '1 october 1806', 'robert guillaume , northam , southampton', '19 october 1807', 'wrecked 1809'], ['peruvian', '1 october 1806', 'george parsons , warsash', '26 april 1808', 'broken up 1830']]
|
list of rizzoli & isles episodes
|
https://en.wikipedia.org/wiki/List_of_Rizzoli_%26_Isles_episodes
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27969432-2.html.csv
|
aggregation
|
the rizzoli & isles episodes has a total of 62.28 million viewers .
|
{'scope': 'all', 'col': '7', 'type': 'sum', 'result': '62.28', 'subset': None}
|
{'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'us viewers ( in millions )'], 'result': '62.28', 'ind': 0, 'tostr': 'sum { all_rows ; us viewers ( in millions ) }'}, '62.28'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; us viewers ( in millions ) } ; 62.28 } = true', 'tointer': 'the sum of the us viewers ( in millions ) record of all rows is 62.28 .'}
|
round_eq { sum { all_rows ; us viewers ( in millions ) } ; 62.28 } = true
|
the sum of the us viewers ( in millions ) record of all rows is 62.28 .
|
2
|
2
|
{'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'us viewers (in millions)_4': 4, '62.28_5': 5}
|
{'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'us viewers (in millions)_4': 'us viewers ( in millions )', '62.28_5': '62.28'}
|
{'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'us viewers (in millions)_4': [0], '62.28_5': [1]}
|
['no in series', 'title', 'directed by', 'written by', 'original air date', 'production', 'us viewers ( in millions )']
|
[['1', 'see one do one teach one', 'michael m robin', 'janet tamaro', 'july 12 , 2010', '296014', '7.55'], ['2', 'boston strangler redux', 'michael m robin', 'janet tamaro', 'july 19 , 2010', '2 m5451', '7.27'], ['3', 'sympathy for the devil', 'roxann dawson', 'joel fields', 'july 26 , 2010', '2 m5452', '6.55'], ['4', 'she works hard for the money', 'arvin brown', 'dave caplan', 'august 2 , 2010', '2 m5453', '6.61'], ['5', 'money for nothing', 'nelson mccormick', 'dave caplan & joel fields', 'august 9 , 2010', '2 m5456', '7.42'], ['6', 'i kissed a girl', 'michael zinberg', 'alison cross', 'august 16 , 2010', '2 m5455', '6.49'], ['7', 'born to run', 'matt penn', 'david gould', 'august 23 , 2010', '2 m5454', '6.73'], ['8', "i 'm your boogie man", 'mark haber', 'janet tamaro', 'august 30 , 2010', '2 m5457', '6.42'], ['9', 'the beast in me', 'adam arkin', 'karina csolty', 'september 6 , 2010', '2 m5458', '7.24']]
|
arkansas highway 60
|
https://en.wikipedia.org/wiki/Arkansas_Highway_60
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18506777-1.html.csv
|
ordinal
|
the aplin has the largest distance in the arkansas highway 60 location sections .
|
{'row': '9', 'col': '3', 'order': '1', 'col_other': '2', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None}
|
{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'distance', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; distance ; 1 }'}, 'location'], 'result': 'aplin', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; distance ; 1 } ; location }'}, 'aplin'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; distance ; 1 } ; location } ; aplin } = true', 'tointer': 'select the row whose distance record of all rows is 1st maximum . the location record of this row is aplin .'}
|
eq { hop { nth_argmax { all_rows ; distance ; 1 } ; location } ; aplin } = true
|
select the row whose distance record of all rows is 1st maximum . the location record of this row is aplin .
|
3
|
3
|
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'distance_5': 5, '1_6': 6, 'location_7': 7, 'aplin_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', 'distance_5': 'distance', '1_6': '1', 'location_7': 'location', 'aplin_8': 'aplin'}
|
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'distance_5': [0], '1_6': [0], 'location_7': [1], 'aplin_8': [2]}
|
['county', 'location', 'distance', 'total', 'notes']
|
[['faulkner', 'conway', '0.0', '0.0', 'eastern terminus'], ['faulkner', 'conway', '1.5', '1.5', '1.8 mile spur to office of emergency services'], ['line', 'county line', '5.5', '7.0', 'toad suck ferry lock & dam'], ['perry', 'bigelow', '7.7', '14.7', 'converge with ar 113'], ['perry', 'houston', '3.8', '18.5', 'north end terminus of ar 216'], ['perry', 'houston', '0.1', '18.6', 'diverge with ar 113'], ['perry', 'perryville', '6.5', '25.1', 'converge with ar 9 & ar 10'], ['perry', 'perryville', '0.3', '25.4', 'diverge with ar 9 & ar 10'], ['perry', 'aplin', '10.8', '36.2', 'north end terminus of ar 155'], ['perry', 'fourche junction', '10.1', '46.3', 'cross ar 7'], ['line', 'county line', '1.6', '47.9', 'county line'], ['yell', 'plainview', '7.0', '54.9', 'western terminus']]
|
phoenix suns all - time roster
|
https://en.wikipedia.org/wiki/Phoenix_Suns_all-time_roster
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11482079-8.html.csv
|
ordinal
|
lamar green was the third earliest player to join the phoenix suns .
|
{'row': '16', 'col': '3', 'order': '3', 'col_other': '1', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None}
|
{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'from', '3'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; from ; 3 }'}, 'player'], 'result': 'lamar green', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; from ; 3 } ; player }'}, 'lamar green'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; from ; 3 } ; player } ; lamar green } = true', 'tointer': 'select the row whose from record of all rows is 3rd minimum . the player record of this row is lamar green .'}
|
eq { hop { nth_argmin { all_rows ; from ; 3 } ; player } ; lamar green } = true
|
select the row whose from record of all rows is 3rd minimum . the player record of this row is lamar green .
|
3
|
3
|
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'from_5': 5, '3_6': 6, 'player_7': 7, 'lamar green_8': 8}
|
{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmin_0': 'nth_argmin', 'all_rows_4': 'all_rows', 'from_5': 'from', '3_6': '3', 'player_7': 'player', 'lamar green_8': 'lamar green'}
|
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'from_5': [0], '3_6': [0], 'player_7': [1], 'lamar green_8': [2]}
|
['player', 'pos', 'from', 'school / country', 'rebs', 'asts']
|
[['rubén garcés', 'pf', '2000', 'providence', '22', '4'], ['diante garrett', 'g', '2012', 'iowa state', '15', '31'], ['pat garrity', 'pf', '1998', 'notre dame', '75', '18'], ['kenny gattison', 'pf', '1986', 'old dominion', '271', '36'], ['armen gilliam', 'pf', '1987', 'unlv', '1045', '132'], ['gordan giriček', 'g / f', '2008', 'croatia', '51', '35'], ['georgi glouchkov', 'pf', '1985', 'bulgaria', '163', '32'], ['grant gondrezick', 'sg', '1986', 'pepperdine', '110', '81'], ['gail goodrich', 'pg', '1968', 'ucla', '777', '1123'], ['archie goodwin', 'g', '2013', 'kentucky', '1', '0'], ['marcin gortat', 'c', '2010', 'poland', '1688', '237'], ['brian grant', 'f / c', '2005', 'xavier', '57', '7'], ['greg grant', 'pg', '1989', 'trenton state', '59', '168'], ['a c green', 'f / c', '1993', 'oregon state', '2114', '353'], ['gerald green', 'g / f', '2013', 'gulf shores academy ( tx )', '2', '0'], ['lamar green', 'pf', '1969', 'morehead state', '2186', '247'], ['gary gregor', 'pf', '1968', 'south carolina', '711', '96'], ['greg griffin', 'f', '1977', 'idaho state', '103', '24'], ['taylor griffin', 'f', '2009', 'oklahoma', '2', '1'], ['tom gugliotta', 'pf', '1999', 'north carolina state', '1438', '353']]
|
2008 - 09 chicago bulls season
|
https://en.wikipedia.org/wiki/2008%E2%80%9309_Chicago_Bulls_season
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17058151-11.html.csv
|
count
|
three of the games had the united center as the location .
|
{'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'united center', 'result': '3', 'col': '5', 'subset': None}
|
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location attendance', 'united center'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose location attendance record fuzzily matches to united center .', 'tostr': 'filter_eq { all_rows ; location attendance ; united center }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; location attendance ; united center } }', 'tointer': 'select the rows whose location attendance record fuzzily matches to united center . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; location attendance ; united center } } ; 3 } = true', 'tointer': 'select the rows whose location attendance record fuzzily matches to united center . the number of such rows is 3 .'}
|
eq { count { filter_eq { all_rows ; location attendance ; united center } } ; 3 } = true
|
select the rows whose location attendance record fuzzily matches to united center . the number of such rows is 3 .
|
3
|
3
|
{'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'location attendance_5': 5, 'united center_6': 6, '3_7': 7}
|
{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'location attendance_5': 'location attendance', 'united center_6': 'united center', '3_7': '3'}
|
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'location attendance_5': [0], 'united center_6': [0], '3_7': [2]}
|
['game', 'date', 'team', 'score', 'location attendance', 'series']
|
[['1', 'april 18', 'boston', 'w 105 - 103 ( ot )', 'td banknorth garden 18624', '1 - 0'], ['2', 'april 20', 'boston', 'l 115 - 118 ( ot )', 'td banknorth garden 18624', '1 - 1'], ['3', 'april 23', 'boston', 'l 86 - 107 ( ot )', 'united center 23072', '1 - 2'], ['4', 'april 26', 'boston', 'w 121 - 118 ( 2ot )', 'united center 23067', '2 - 2'], ['5', 'april 28', 'boston', 'l 104 - 106 ( ot )', 'td banknorth garden 18624', '2 - 3'], ['6', 'april 30', 'boston', 'w 128 - 127 ( 3ot )', 'united center 23430', '3 - 3'], ['7', 'may 2', 'boston', 'l 99 - 109 ( ot )', 'td banknorth garden 18624', '3 - 4']]
|
bo ' ness and kinneil railway
|
https://en.wikipedia.org/wiki/Bo%27ness_and_Kinneil_Railway
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1174877-18.html.csv
|
comparative
|
both the naval store no. 161 and the briggs dundee no. 20 at the bo ' ness kinneil railway were built in the year 1918 .
|
{'row_1': '4', 'row_2': '5', 'col': '5', 'col_other': '1', 'relation': 'equal', 'record_mentioned': 'yes', 'diff_result': None}
|
{'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'number & name', 'naval store no 161'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose number & name record fuzzily matches to naval store no 161 .', 'tostr': 'filter_eq { all_rows ; number & name ; naval store no 161 }'}, 'date'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; number & name ; naval store no 161 } ; date }', 'tointer': 'select the rows whose number & name record fuzzily matches to naval store no 161 . take the date record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'number & name', 'briggs , dundee no 20'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose number & name record fuzzily matches to briggs , dundee no 20 .', 'tostr': 'filter_eq { all_rows ; number & name ; briggs , dundee no 20 }'}, 'date'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; number & name ; briggs , dundee no 20 } ; date }', 'tointer': 'select the rows whose number & name record fuzzily matches to briggs , dundee no 20 . take the date record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'eq { hop { filter_eq { all_rows ; number & name ; naval store no 161 } ; date } ; hop { filter_eq { all_rows ; number & name ; briggs , dundee no 20 } ; date } }', 'tointer': 'select the rows whose number & name record fuzzily matches to naval store no 161 . take the date record of this row . select the rows whose number & name record fuzzily matches to briggs , dundee no 20 . take the date record of this row . the first record is equal to the second record .'}, {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'number & name', 'naval store no 161'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose number & name record fuzzily matches to naval store no 161 .', 'tostr': 'filter_eq { all_rows ; number & name ; naval store no 161 }'}, 'date'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; number & name ; naval store no 161 } ; date }', 'tointer': 'select the rows whose number & name record fuzzily matches to naval store no 161 . take the date record of this row .'}, '1918'], 'result': True, 'ind': 5, 'tostr': 'eq { hop { filter_eq { all_rows ; number & name ; naval store no 161 } ; date } ; 1918 }', 'tointer': 'the date record of the first row is 1918 .'}, {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'number & name', 'briggs , dundee no 20'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose number & name record fuzzily matches to briggs , dundee no 20 .', 'tostr': 'filter_eq { all_rows ; number & name ; briggs , dundee no 20 }'}, 'date'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; number & name ; briggs , dundee no 20 } ; date }', 'tointer': 'select the rows whose number & name record fuzzily matches to briggs , dundee no 20 . take the date record of this row .'}, '1918'], 'result': True, 'ind': 6, 'tostr': 'eq { hop { filter_eq { all_rows ; number & name ; briggs , dundee no 20 } ; date } ; 1918 }', 'tointer': 'the date record of the second row is 1918 .'}], 'result': True, 'ind': 7, 'tostr': 'and { eq { hop { filter_eq { all_rows ; number & name ; naval store no 161 } ; date } ; 1918 } ; eq { hop { filter_eq { all_rows ; number & name ; briggs , dundee no 20 } ; date } ; 1918 } }', 'tointer': 'the date record of the first row is 1918 . the date record of the second row is 1918 .'}], 'result': True, 'ind': 8, 'tostr': 'and { eq { hop { filter_eq { all_rows ; number & name ; naval store no 161 } ; date } ; hop { filter_eq { all_rows ; number & name ; briggs , dundee no 20 } ; date } } ; and { eq { hop { filter_eq { all_rows ; number & name ; naval store no 161 } ; date } ; 1918 } ; eq { hop { filter_eq { all_rows ; number & name ; briggs , dundee no 20 } ; date } ; 1918 } } } = true', 'tointer': 'select the rows whose number & name record fuzzily matches to naval store no 161 . take the date record of this row . select the rows whose number & name record fuzzily matches to briggs , dundee no 20 . take the date record of this row . the first record is equal to the second record . the date record of the first row is 1918 . the date record of the second row is 1918 .'}
|
and { eq { hop { filter_eq { all_rows ; number & name ; naval store no 161 } ; date } ; hop { filter_eq { all_rows ; number & name ; briggs , dundee no 20 } ; date } } ; and { eq { hop { filter_eq { all_rows ; number & name ; naval store no 161 } ; date } ; 1918 } ; eq { hop { filter_eq { all_rows ; number & name ; briggs , dundee no 20 } ; date } ; 1918 } } } = true
|
select the rows whose number & name record fuzzily matches to naval store no 161 . take the date record of this row . select the rows whose number & name record fuzzily matches to briggs , dundee no 20 . take the date record of this row . the first record is equal to the second record . the date record of the first row is 1918 . the date record of the second row is 1918 .
|
13
|
9
|
{'and_8': 8, 'result_9': 9, 'eq_4': 4, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_10': 10, 'number & name_11': 11, 'naval store no 161_12': 12, 'date_13': 13, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_14': 14, 'number & name_15': 15, 'briggs , dundee no 20_16': 16, 'date_17': 17, 'and_7': 7, 'eq_5': 5, '1918_18': 18, 'eq_6': 6, '1918_19': 19}
|
{'and_8': 'and', 'result_9': 'true', 'eq_4': 'eq', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_10': 'all_rows', 'number & name_11': 'number & name', 'naval store no 161_12': 'naval store no 161', 'date_13': 'date', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_14': 'all_rows', 'number & name_15': 'number & name', 'briggs , dundee no 20_16': 'briggs , dundee no 20', 'date_17': 'date', 'and_7': 'and', 'eq_5': 'eq', '1918_18': '1918', 'eq_6': 'eq', '1918_19': '1918'}
|
{'and_8': [9], 'result_9': [], 'eq_4': [8], 'num_hop_2': [4, 5], 'filter_str_eq_0': [2], 'all_rows_10': [0], 'number & name_11': [0], 'naval store no 161_12': [0], 'date_13': [2], 'num_hop_3': [4, 6], 'filter_str_eq_1': [3], 'all_rows_14': [1], 'number & name_15': [1], 'briggs , dundee no 20_16': [1], 'date_17': [3], 'and_7': [8], 'eq_5': [7], '1918_18': [5], 'eq_6': [7], '1918_19': [6]}
|
['number & name', 'description', 'current status', 'livery', 'date']
|
[['scottish tar distillers no 78', 'rectangular tanker', 'static display in the museum', 'black', '1877'], ['oakbank oil company no 13', '10t tanker', 'static display in the museum', 'black', '1894'], ['no a43', 'shell bp tanker', 'static display in the museum', 'black', '1897'], ['naval store no 161', '14t tanker', 'static display in the museum', 'black', '1918'], ['briggs , dundee no 20', '14t tanker', 'operational', 'black', '1918'], ['briggs no 17', '14t tanker', 'stored', 'black', '1927'], ['no 206', '20t tanker', 'stored', 'silver dcl', '1930'], ['no 241', '20t tanker', 'stored', 'silver dcl', '1940'], ['no 4', '20t tanker', 'stored', 'bp chemicals', '1941'], ['no 14', '14t nitric acid tanker', 'static display in the museum', 'grey', '1941'], ['no 252', '20t tanker', 'stored', "distiller 's co ltd silver", '1951'], ['no 261', '20t tanker', 'stored', 'british hydrocarbon chemicals silver', '1956'], ['no bpo67496', '45t tta tanker', 'stored', 'bp green', '1966']]
|
1979 world figure skating championships
|
https://en.wikipedia.org/wiki/1979_World_Figure_Skating_Championships
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11312764-5.html.csv
|
unique
|
at the 1979 world figure skating championships , the only skaters from canada were barbara underhill and paul martini .
|
{'scope': 'all', 'row': '11', 'col': '3', 'col_other': '2', 'criterion': 'equal', 'value': 'canada', 'subset': None}
|
{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'nation', 'canada'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose nation record fuzzily matches to canada .', 'tostr': 'filter_eq { all_rows ; nation ; canada }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; nation ; canada } }', 'tointer': 'select the rows whose nation record fuzzily matches to canada . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'nation', 'canada'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose nation record fuzzily matches to canada .', 'tostr': 'filter_eq { all_rows ; nation ; canada }'}, 'name'], 'result': 'barbara underhill / paul martini', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; nation ; canada } ; name }'}, 'barbara underhill / paul martini'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; nation ; canada } ; name } ; barbara underhill / paul martini }', 'tointer': 'the name record of this unqiue row is barbara underhill / paul martini .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; nation ; canada } } ; eq { hop { filter_eq { all_rows ; nation ; canada } ; name } ; barbara underhill / paul martini } } = true', 'tointer': 'select the rows whose nation record fuzzily matches to canada . there is only one such row in the table . the name record of this unqiue row is barbara underhill / paul martini .'}
|
and { only { filter_eq { all_rows ; nation ; canada } } ; eq { hop { filter_eq { all_rows ; nation ; canada } ; name } ; barbara underhill / paul martini } } = true
|
select the rows whose nation record fuzzily matches to canada . there is only one such row in the table . the name record of this unqiue row is barbara underhill / paul martini .
|
6
|
5
|
{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'nation_7': 7, 'canada_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'name_9': 9, 'barbara underhill / paul martini_10': 10}
|
{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'nation_7': 'nation', 'canada_8': 'canada', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'name_9': 'name', 'barbara underhill / paul martini_10': 'barbara underhill / paul martini'}
|
{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'nation_7': [0], 'canada_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'name_9': [2], 'barbara underhill / paul martini_10': [3]}
|
['rank', 'name', 'nation', 'points', 'places']
|
[['1', 'tai babilonia / randy gardner', 'united states', '144.54', '12'], ['2', 'marina cherkasova / sergei shakhrai', 'soviet union', '142.22', '16'], ['3', 'sabine baeãÿ / tassilo thierbach', 'east germany', '137.74', '32'], ['4', 'irina vorobieva / igor lisovski', 'soviet union', '138.72', '33'], ['5', 'marina pestova / stanislav leonovich', 'soviet union', '133.98', '46'], ['6', 'vicki heasley / robert wagenhoffer', 'united states', '132.50', '54'], ['7', 'cornelia haufe / kersten bellmann', 'east germany', '128.98', '70'], ['8', 'christina riegel / andreas nischwitz', 'west germany', '128.56', '75'], ['9', 'sheryl franks / michael botticelli', 'united states', '127.64', '77'], ['10', 'kerstin stolfig / veit kempe', 'east germany', '125.92', '84'], ['11', 'barbara underhill / paul martini', 'canada', '123.92', '94'], ['12', 'gabriele beck / jochen stahl', 'west germany', '117.62', '114'], ['13', 'elizabeth cain / peter cain', 'australia', '115.32', '117'], ['14', 'kyoko hagiwara / hisao ozaki', 'japan', '114.02', '120']]
|
1965 american football league draft
|
https://en.wikipedia.org/wiki/1965_American_Football_League_Draft
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18652198-19.html.csv
|
majority
|
in the 1965 afl draft , a majority of players taken were tackles .
|
{'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'tackle', 'subset': None}
|
{'func': 'most_str_eq', 'args': ['all_rows', 'position', 'tackle'], 'result': True, 'ind': 0, 'tointer': 'for the position records of all rows , most of them fuzzily match to tackle .', 'tostr': 'most_eq { all_rows ; position ; tackle } = true'}
|
most_eq { all_rows ; position ; tackle } = true
|
for the position records of all rows , most of them fuzzily match to tackle .
|
1
|
1
|
{'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'position_3': 3, 'tackle_4': 4}
|
{'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'position_3': 'position', 'tackle_4': 'tackle'}
|
{'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'position_3': [0], 'tackle_4': [0]}
|
['pick', 'team', 'player', 'position', 'college']
|
[['145', 'denver broncos', 'ron oelschlager', 'halfback', 'kansas'], ['146', 'houston oilers', 'frank fox', 'tackle', 'sam houston state'], ['147', 'oakland raiders', 'frank mcclendon', 'tackle', 'alabama'], ['148', 'new york jets', 'mitch dudek', 'tackle', 'xavier'], ['149', 'kansas city chiefs', 'mike alford', 'center', 'auburn'], ['150', 'san diego chargers', 'braden beck', 'kicker', 'stanford'], ['151', 'boston patriots', 'jim nance', 'running back', 'syracuse'], ['152', 'buffalo bills', 'frank marchlewski', 'center', 'minnesota']]
|
bears - packers rivalry
|
https://en.wikipedia.org/wiki/Bears%E2%80%93Packers_rivalry
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11650849-7.html.csv
|
aggregation
|
the bears - packers rivalry had an average attendance of about 35000 fans per game from 1950-1959 .
|
{'scope': 'all', 'col': '6', 'type': 'average', 'result': '35000', 'subset': None}
|
{'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'attendance'], 'result': '35000', 'ind': 0, 'tostr': 'avg { all_rows ; attendance }'}, '35000'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; attendance } ; 35000 } = true', 'tointer': 'the average of the attendance record of all rows is 35000 .'}
|
round_eq { avg { all_rows ; attendance } ; 35000 } = true
|
the average of the attendance record of all rows is 35000 .
|
2
|
2
|
{'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'attendance_4': 4, '35000_5': 5}
|
{'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'attendance_4': 'attendance', '35000_5': '35000'}
|
{'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'attendance_4': [0], '35000_5': [1]}
|
['year', 'date', 'winner', 'result', 'loser', 'attendance', 'location']
|
[['1950', 'sunday , october 1', 'green bay packers', '31 - 21', 'chicago bears', '24893', 'green bay'], ['1950', 'sunday , october 15', 'chicago bears', '28 - 14', 'green bay packers', '51065', 'chicago'], ['1951', 'sunday , september 30', 'chicago bears', '31 - 20', 'green bay packers', '24666', 'green bay'], ['1951', 'sunday , november 18', 'chicago bears', '24 - 13', 'green bay packers', '36771', 'chicago'], ['1952', 'sunday , september 28', 'chicago bears', '24 - 14', 'green bay packers', '24656', 'green bay'], ['1952', 'sunday , november 9', 'green bay packers', '41 - 28', 'chicago bears', '41751', 'chicago'], ['1953', 'sunday , october 4', 'chicago bears', '17 - 13', 'green bay packers', '24835', 'green bay'], ['1953', 'sunday , november 8', 'chicago bears', '21 - 21', 'green bay packers', '39889', 'chicago'], ['1954', 'sunday , october 3', 'chicago bears', '10 - 3', 'green bay packers', '24414', 'green bay'], ['1954', 'sunday , november 7', 'chicago bears', '28 - 23', 'green bay packers', '47038', 'chicago'], ['1955', 'sunday , october 2', 'green bay packers', '24 - 3', 'chicago bears', '24662', 'green bay'], ['1955', 'sunday , november 6', 'chicago bears', '52 - 31', 'green bay packers', '48890', 'chicago'], ['1956', 'sunday , october 7', 'chicago bears', '37 - 21', 'green bay packers', '24668', 'green bay'], ['1956', 'sunday , november 11', 'chicago bears', '38 - 14', 'green bay packers', '49172', 'chicago'], ['1957', 'sunday , september 29', 'green bay packers', '21 - 17', 'chicago bears', '32132', 'green bay'], ['1957', 'sunday , november 10', 'chicago bears', '21 - 14', 'green bay packers', '47153', 'chicago'], ['1958', 'sunday , september 28', 'chicago bears', '34 - 20', 'green bay packers', '32150', 'green bay'], ['1958', 'sunday , november 9', 'chicago bears', '24 - 10', 'green bay packers', '48424', 'chicago'], ['1959', 'sunday , september 27', 'green bay packers', '9 - 6', 'chicago bears', '32150', 'green bay'], ['1959', 'sunday , november 8', 'chicago bears', '28 - 17', 'green bay packers', '46205', 'chicago']]
|
2008 french road cycling cup
|
https://en.wikipedia.org/wiki/2008_French_Road_Cycling_Cup
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15930479-1.html.csv
|
count
|
there was a total of 14 events in the 2008 cup .
|
{'scope': 'all', 'criterion': 'all', 'value': 'n/a', 'result': '14', 'col': '2', 'subset': None}
|
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_all', 'args': ['all_rows', 'event'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose event record is arbitrary .', 'tostr': 'filter_all { all_rows ; event }'}], 'result': '14', 'ind': 1, 'tostr': 'count { filter_all { all_rows ; event } }', 'tointer': 'select the rows whose event record is arbitrary . the number of such rows is 14 .'}, '14'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_all { all_rows ; event } } ; 14 } = true', 'tointer': 'select the rows whose event record is arbitrary . the number of such rows is 14 .'}
|
eq { count { filter_all { all_rows ; event } } ; 14 } = true
|
select the rows whose event record is arbitrary . the number of such rows is 14 .
|
3
|
3
|
{'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_all_0': 0, 'all_rows_4': 4, 'event_5': 5, '14_6': 6}
|
{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_all_0': 'filter_all', 'all_rows_4': 'all_rows', 'event_5': 'event', '14_6': '14'}
|
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_all_0': [1], 'all_rows_4': [0], 'event_5': [0], '14_6': [2]}
|
['date', 'event', 'winner', 'team', 'series leader']
|
[['february 24', 'tour du haut var', 'davide rebellin ( ita )', 'gerolsteiner', 'rinaldo nocentini ( ita )'], ['march 23', 'cholet - pays de loire', 'janek tombak ( est )', 'mitsubishi - jartazi', 'rinaldo nocentini ( ita )'], ['april 6', 'grand prix de rennes', 'mikhaylo khalilov ( ukr )', 'ceramica flaminia - bossini docce', 'jimmy casper ( fra )'], ['april 15', 'paris - camembert', 'alejandro valverde ( esp )', "caisse d'epargne", 'jérôme pineau ( fra )'], ['april 17', 'grand prix de denain', 'edvald boasson hagen ( nor )', 'team high road', 'jimmy casper ( fra )'], ['april 19', 'tour du finistère', 'david lelay ( fra )', 'bretagne - armor lux', 'jimmy casper ( fra )'], ['april 20', 'tro - bro léon', 'frédéric guesdon ( fra )', 'française des jeux', 'jimmy casper ( fra )'], ['may 4', 'trophée des grimpeurs', 'david lelay ( fra )', 'bretagne - armor lux', 'david lelay ( fra )'], ['may 31', 'grand prix de plumelec - morbihan', 'thomas voeckler ( fra )', 'bouygues télécom', 'david lelay ( fra )'], ['august 3', 'polynormande', 'arnaud gérard ( fra )', 'française des jeux', 'jérôme pineau ( fra )'], ['august 31', 'chteauroux classic', 'anthony ravard ( fra )', 'agritubel', 'jérôme pineau ( fra )'], ['september 21', "grand prix d'isbergues", 'william bonnet ( fra )', 'crédit agricole', 'jérôme pineau ( fra )'], ['october 5', 'tour de vendée', 'koldo fernández ( esp )', 'euskaltel - euskadi', 'jérôme pineau ( fra )'], ['october 9', 'paris - bourges', 'bernhard eisel ( aut )', 'team columbia', 'jérôme pineau ( fra )']]
|
1963 vfl season
|
https://en.wikipedia.org/wiki/1963_VFL_season
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10783853-1.html.csv
|
aggregation
|
in the 1963 vfl season , games drew 174 , 580 fans to various venues .
|
{'scope': 'all', 'col': '6', 'type': 'sum', 'result': '174 , 580', 'subset': None}
|
{'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'crowd'], 'result': '174 , 580', 'ind': 0, 'tostr': 'sum { all_rows ; crowd }'}, '174 , 580'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; crowd } ; 174 , 580 } = true', 'tointer': 'the sum of the crowd record of all rows is 174 , 580 .'}
|
round_eq { sum { all_rows ; crowd } ; 174 , 580 } = true
|
the sum of the crowd record of all rows is 174 , 580 .
|
2
|
2
|
{'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'crowd_4': 4, '174, 580_5': 5}
|
{'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'crowd_4': 'crowd', '174, 580_5': '174 , 580'}
|
{'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'crowd_4': [0], '174, 580_5': [1]}
|
['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date']
|
[['geelong', '16.26 ( 122 )', 'south melbourne', '9.9 ( 63 )', 'kardinia park', '33953', '20 april 1963'], ['st kilda', '13.5 ( 83 )', 'melbourne', '9.11 ( 65 )', 'junction oval', '31300', '20 april 1963'], ['north melbourne', '11.11 ( 77 )', 'footscray', '5.10 ( 40 )', 'arden street oval', '21960', '20 april 1963'], ['hawthorn', '8.12 ( 60 )', 'essendon', '13.7 ( 85 )', 'glenferrie oval', '30000', '20 april 1963'], ['richmond', '11.14 ( 80 )', 'collingwood', '18.16 ( 124 )', 'punt road oval', '32200', '20 april 1963'], ['fitzroy', '10.12 ( 72 )', 'carlton', '14.11 ( 95 )', 'brunswick street oval', '25167', '20 april 1963']]
|
1955 - 56 segunda división
|
https://en.wikipedia.org/wiki/1955%E2%80%9356_Segunda_Divisi%C3%B3n
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17608926-2.html.csv
|
comparative
|
real oviedo recorded more wins than ca osasuna in the 1955 - 56 segunda división .
|
{'row_1': '2', 'row_2': '1', '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', 'club', 'real oviedo'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose club record fuzzily matches to real oviedo .', 'tostr': 'filter_eq { all_rows ; club ; real oviedo }'}, 'wins'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; club ; real oviedo } ; wins }', 'tointer': 'select the rows whose club record fuzzily matches to real oviedo . take the wins record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'club', 'ca osasuna'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose club record fuzzily matches to ca osasuna .', 'tostr': 'filter_eq { all_rows ; club ; ca osasuna }'}, 'wins'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; club ; ca osasuna } ; wins }', 'tointer': 'select the rows whose club record fuzzily matches to ca osasuna . take the wins record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; club ; real oviedo } ; wins } ; hop { filter_eq { all_rows ; club ; ca osasuna } ; wins } } = true', 'tointer': 'select the rows whose club record fuzzily matches to real oviedo . take the wins record of this row . select the rows whose club record fuzzily matches to ca osasuna . take the wins record of this row . the first record is greater than the second record .'}
|
greater { hop { filter_eq { all_rows ; club ; real oviedo } ; wins } ; hop { filter_eq { all_rows ; club ; ca osasuna } ; wins } } = true
|
select the rows whose club record fuzzily matches to real oviedo . take the wins record of this row . select the rows whose club record fuzzily matches to ca osasuna . 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, 'club_7': 7, 'real oviedo_8': 8, 'wins_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'club_11': 11, 'ca osasuna_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', 'club_7': 'club', 'real oviedo_8': 'real oviedo', 'wins_9': 'wins', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'club_11': 'club', 'ca osasuna_12': 'ca osasuna', 'wins_13': 'wins'}
|
{'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'club_7': [0], 'real oviedo_8': [0], 'wins_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'club_11': [1], 'ca osasuna_12': [1], 'wins_13': [3]}
|
['position', 'club', 'played', 'points', 'wins', 'draws', 'losses', 'goals for', 'goals against', 'goal difference']
|
[['1', 'ca osasuna', '30', '42', '17', '8', '5', '76', '33', '+ 43'], ['2', 'real oviedo', '30', '41', '18', '5', '7', '78', '33', '+ 45'], ['3', 'real zaragoza', '30', '40', '18', '4', '8', '57', '27', '+ 30'], ['4', 'caudal deportivo', '30', '34', '13', '8', '9', '49', '37', '+ 12'], ['5', 'cd sabadell cf', '30', '33', '13', '7', '10', '50', '44', '+ 6'], ['6', 'club ferrol', '30', '32', '11', '10', '9', '44', '47', '- 3'], ['7', 'real gijón cf', '30', '32', '14', '4', '12', '51', '46', '+ 5'], ['8', 'sd indauchu', '30', '30', '12', '6', '12', '53', '50', '+ 3'], ['9', 'cd tarrasa', '30', '28', '10', '8', '12', '46', '59', '- 13'], ['10', 'baracaldo ah', '30', '28', '10', '8', '12', '45', '54', '- 9'], ['11', 'real santander', '30', '28', '12', '4', '14', '47', '47', '0'], ['12', 'ud lérida', '30', '26', '11', '4', '15', '53', '63', '- 10'], ['13', 'cp la felguera', '30', '26', '10', '6', '14', '35', '57', '- 22'], ['14', 'sd eibar', '30', '25', '9', '7', '14', '40', '55', '- 15'], ['15', 'club sestao', '30', '19', '6', '7', '17', '24', '58', '- 34'], ['16', 'cd logroñés', '30', '16', '4', '8', '18', '38', '76', '- 38']]
|
1933 pittsburgh pirates ( nfl ) season
|
https://en.wikipedia.org/wiki/1933_Pittsburgh_Pirates_%28NFL%29_season
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14683281-1.html.csv
|
superlative
|
in the 1933 pittsburgh pirates ( nfl ) season , the earliest game at forbes field was on sunday , september 20th .
|
{'scope': 'subset', 'col_superlative': '2', 'row_superlative': '1', 'value_mentioned': 'yes', 'max_or_min': 'min', 'other_col': '5', 'subset': {'col': '5', 'criterion': 'equal', 'value': 'forbes field'}}
|
{'func': 'eq', 'args': [{'func': 'min', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'game site', 'forbes field'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; game site ; forbes field }', 'tointer': 'select the rows whose game site record fuzzily matches to forbes field .'}, 'date'], 'result': 'sunday september 20', 'ind': 1, 'tostr': 'min { filter_eq { all_rows ; game site ; forbes field } ; date }', 'tointer': 'select the rows whose game site record fuzzily matches to forbes field . the minimum date record of these rows is sunday september 20 .'}, 'sunday september 20'], 'result': True, 'ind': 2, 'tostr': 'eq { min { filter_eq { all_rows ; game site ; forbes field } ; date } ; sunday september 20 } = true', 'tointer': 'select the rows whose game site record fuzzily matches to forbes field . the minimum date record of these rows is sunday september 20 .'}
|
eq { min { filter_eq { all_rows ; game site ; forbes field } ; date } ; sunday september 20 } = true
|
select the rows whose game site record fuzzily matches to forbes field . the minimum date record of these rows is sunday september 20 .
|
3
|
3
|
{'eq_2': 2, 'result_3': 3, 'min_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'game site_5': 5, 'forbes field_6': 6, 'date_7': 7, 'sunday september 20_8': 8}
|
{'eq_2': 'eq', 'result_3': 'true', 'min_1': 'min', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'game site_5': 'game site', 'forbes field_6': 'forbes field', 'date_7': 'date', 'sunday september 20_8': 'sunday september 20'}
|
{'eq_2': [3], 'result_3': [], 'min_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'game site_5': [0], 'forbes field_6': [0], 'date_7': [1], 'sunday september 20_8': [2]}
|
['week', 'date', 'opponent', 'result', 'game site']
|
[['1', 'sunday september 20', 'new york giants', 'l 23 - 2', 'forbes field'], ['2', 'sunday september 27', 'chicago cardinals', 'w 14 - 13', 'forbes field'], ['3', 'sunday october 4', 'boston redskins', 'l 21 - 6', 'forbes field'], ['4', 'sunday october 11', 'cincinnati reds', 'w 17 - 3', 'forbes field'], ['5', 'sunday october 15', 'green bay packers', 'l 47 - 0', 'city stadium'], ['6', 'sunday october 22', 'cincinnati reds', 't 0 - 0', 'redland field'], ['7', 'sunday october 29', 'boston redskins', 'w 16 - 14', 'fenway park'], ['8', 'sunday november 5', 'brooklyn dodgers', 't 3 - 3', 'ebbets field'], ['9', 'sunday november 12', 'brooklyn dodgers', 'l 32 - 0', 'forbes field'], ['10', 'sunday november 19', 'philadelphia eagles', 'l 25 - 6', 'baker bowl'], ['11', 'sunday december 3', 'new york giants', 'l 27 - 3', 'polo grounds']]
|
eiza gonzález
|
https://en.wikipedia.org/wiki/Eiza_Gonz%C3%A1lez
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16264878-4.html.csv
|
count
|
elza gonzalez won six awards for her participation in movies .
|
{'scope': 'all', 'criterion': 'equal', 'value': 'won', 'result': '6', 'col': '5', 'subset': None}
|
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'result', 'won'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose result record fuzzily matches to won .', 'tostr': 'filter_eq { all_rows ; result ; won }'}], 'result': '6', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; result ; won } }', 'tointer': 'select the rows whose result record fuzzily matches to won . the number of such rows is 6 .'}, '6'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; result ; won } } ; 6 } = true', 'tointer': 'select the rows whose result record fuzzily matches to won . the number of such rows is 6 .'}
|
eq { count { filter_eq { all_rows ; result ; won } } ; 6 } = true
|
select the rows whose result record fuzzily matches to won . the number of such rows is 6 .
|
3
|
3
|
{'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'result_5': 5, 'won_6': 6, '6_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', 'won_6': 'won', '6_7': '6'}
|
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'result_5': [0], 'won_6': [0], '6_7': [2]}
|
['year', 'award', 'nominated work', 'category', 'result']
|
[['2007', 'premios oye !', 'lola érase una vez ( album )', 'artista revelacion', 'nominated'], ['2008', 'premios tv y novelas', 'lola , érase una vez', 'actriz revelacion del año', 'won'], ['2009', 'premio lo nuestro', 'lola érase una vez ( álbum )', 'revelación pop del año', 'won'], ['2011', 'kids choice awards méxico', 'sueña conmigo', 'personaje femenino favorito de una serie', 'nominated'], ['2011', 'kids choice awards argentina', 'sueña conmigo', 'mejor actriz', 'nominated'], ['2011', 'kids choice awards argentina', 'sueña conmigo', 'revelacion en tv', 'won'], ['2011', 'meus premios nick', 'sueña conmigo', 'mejor actriz', 'nominated'], ['2011', 'meus premios nick', 'sueña conmigo', 'cabello maluco', 'nominated'], ['2012', 'premios juventud', 'moda ( style )', 'quiero vestir como ella', 'nominated'], ['2012', 'premios celebrity e!', 'amores verdaderos', 'celebridad del año', 'nominated'], ['2013', 'premios juventud', 'me puedes pedir lo que sea ( feat marconi )', 'mejor tema novelero', 'won'], ['2013', 'premios juventud', 'amores verdaderos', 'chica que me quita el sueño', 'nominated'], ['2013', 'mtv millennial awards', 'eiza gonzález', 'bizcocho del año', 'nominated'], ['2013', 'kids choice awards méxico', 'eiza gonzález', 'solista favorito', 'won'], ['2013', 'kids choice awards méxico', 'eiza gonzález por epp en los croods', 'doblaje favorito en película', 'won']]
|
2010 - 11 danish 1st division
|
https://en.wikipedia.org/wiki/2010%E2%80%9311_Danish_1st_Division
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27782699-3.html.csv
|
unique
|
fc hjørring is the only team whose outgoing manager left because they signed by fc fredericia .
|
{'scope': 'all', 'row': '7', 'col': '3', 'col_other': '1', 'criterion': 'equal', 'value': 'signed by fc fredericia', 'subset': None}
|
{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'manner of departure', 'signed by fc fredericia'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose manner of departure record fuzzily matches to signed by fc fredericia .', 'tostr': 'filter_eq { all_rows ; manner of departure ; signed by fc fredericia }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; manner of departure ; signed by fc fredericia } }', 'tointer': 'select the rows whose manner of departure record fuzzily matches to signed by fc fredericia . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'manner of departure', 'signed by fc fredericia'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose manner of departure record fuzzily matches to signed by fc fredericia .', 'tostr': 'filter_eq { all_rows ; manner of departure ; signed by fc fredericia }'}, 'team'], 'result': 'fc hjørring', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; manner of departure ; signed by fc fredericia } ; team }'}, 'fc hjørring'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; manner of departure ; signed by fc fredericia } ; team } ; fc hjørring }', 'tointer': 'the team record of this unqiue row is fc hjørring .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; manner of departure ; signed by fc fredericia } } ; eq { hop { filter_eq { all_rows ; manner of departure ; signed by fc fredericia } ; team } ; fc hjørring } } = true', 'tointer': 'select the rows whose manner of departure record fuzzily matches to signed by fc fredericia . there is only one such row in the table . the team record of this unqiue row is fc hjørring .'}
|
and { only { filter_eq { all_rows ; manner of departure ; signed by fc fredericia } } ; eq { hop { filter_eq { all_rows ; manner of departure ; signed by fc fredericia } ; team } ; fc hjørring } } = true
|
select the rows whose manner of departure record fuzzily matches to signed by fc fredericia . there is only one such row in the table . the team record of this unqiue row is fc hjørring .
|
6
|
5
|
{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'manner of departure_7': 7, 'signed by fc fredericia_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'team_9': 9, 'fc hjørring_10': 10}
|
{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'manner of departure_7': 'manner of departure', 'signed by fc fredericia_8': 'signed by fc fredericia', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'team_9': 'team', 'fc hjørring_10': 'fc hjørring'}
|
{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'manner of departure_7': [0], 'signed by fc fredericia_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'team_9': [2], 'fc hjørring_10': [3]}
|
['team', 'outgoing manager', 'manner of departure', 'date of vacancy', 'replaced by', 'date of appointment', 'position in table']
|
[['aarhus gf', 'erik rasmussen', 'sacked', '20 may 2010', 'peter sørensen', '1 july 2010', 'pre - season'], ['næstved bk', 'kim poulsen', 'mutual consent', '30 june 2010', 'brian flies', '1 july 2010', 'pre - season'], ['fc roskilde', 'martin jungsgaard', 'end of contract', '30 june 2010', 'carsten broe', '1 july 2010', 'pre - season'], ['hobro ik', 'søren kusk', 'end of contract', '30 june 2010', 'jan østergaard', '1 july 2010', 'pre - season'], ['ab', 'flemming christensen', 'end of contract', '30 june 2010', 'kasper kurland', '1 july 2010', 'pre - season'], ['fc fredericia', 'peter sørensen', 'signed by aarhus gf', '30 june 2010', 'thomas thomasberg', '1 july 2010', 'pre - season'], ['fc hjørring', 'thomas thomasberg', 'signed by fc fredericia', '30 june 2010', 'kim poulsen', '1 july 2010', 'pre - season'], ['hobro ik', 'jan østergaard', 'sacked', '2 november 2010', 'jens hammer sørensen', '2 november 2010', '11th'], ['viborg ff', 'lars søndergaard', 'sacked', '24 november 2010', 'steffen højer & søren frederiksen', '24 november 2010', '13th'], ['hobro ik', 'jens hammer sørensen', 'mutual consent', '26 november 2010', 'jakob michelsen', '8 january 2011', '11th'], ['hvidovre if', 'kenneth brylle larsen', 'end of contract', '31 december 2010', 'per nielsen', '1 january 2011', '14th'], ['kolding fc', 'jens letort', 'end of contract', '31 december 2010', 'kim fogh', '1 january 2011', '10th'], ['vejle bk', 'mats gren', 'sacked', '12 april 2011', 'viggo jensen', '14 april 2011', '3rd']]
|
1971 all - ireland senior hurling championship
|
https://en.wikipedia.org/wiki/1971_All-Ireland_Senior_Hurling_Championship
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13052263-3.html.csv
|
unique
|
christy kehoe is the only player who is from wexford county .
|
{'scope': 'all', 'row': '10', 'col': '3', 'col_other': '2', 'criterion': 'equal', 'value': 'wexford', 'subset': None}
|
{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'county', 'wexford'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose county record fuzzily matches to wexford .', 'tostr': 'filter_eq { all_rows ; county ; wexford }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; county ; wexford } }', 'tointer': 'select the rows whose county record fuzzily matches to wexford . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'county', 'wexford'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose county record fuzzily matches to wexford .', 'tostr': 'filter_eq { all_rows ; county ; wexford }'}, 'player'], 'result': 'christy kehoe', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; county ; wexford } ; player }'}, 'christy kehoe'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; county ; wexford } ; player } ; christy kehoe }', 'tointer': 'the player record of this unqiue row is christy kehoe .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; county ; wexford } } ; eq { hop { filter_eq { all_rows ; county ; wexford } ; player } ; christy kehoe } } = true', 'tointer': 'select the rows whose county record fuzzily matches to wexford . there is only one such row in the table . the player record of this unqiue row is christy kehoe .'}
|
and { only { filter_eq { all_rows ; county ; wexford } } ; eq { hop { filter_eq { all_rows ; county ; wexford } ; player } ; christy kehoe } } = true
|
select the rows whose county record fuzzily matches to wexford . there is only one such row in the table . the player record of this unqiue row is christy kehoe .
|
6
|
5
|
{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'county_7': 7, 'wexford_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'player_9': 9, 'christy kehoe_10': 10}
|
{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'county_7': 'county', 'wexford_8': 'wexford', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'player_9': 'player', 'christy kehoe_10': 'christy kehoe'}
|
{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'county_7': [0], 'wexford_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'player_9': [2], 'christy kehoe_10': [3]}
|
['rank', 'player', 'county', 'tally', 'total', 'opposition']
|
[['1', "michael ' babs ' keating", 'tipperary', '2 - 12', '18', 'galway'], ['2', 'eddie keher', 'kilkenny', '2 - 11', '17', 'tipperary'], ['3', 'eddie keher', 'kilkenny', '0 - 14', '14', 'london'], ['4', "michael ' babs ' keating", 'tipperary', '3 - 4', '13', 'limerick'], ['4', 'des coen', 'galway', '3 - 4', '13', 'antrim'], ['4', 'eddie keher', 'kilkenny', '2 - 7', '13', 'dublin'], ['7', 'richie bennis', 'limerick', '0 - 12', '12', 'tipperary'], ['8', 'richie bennis', 'limerick', '1 - 8', '11', 'cork'], ['8', 'eddie keher', 'kilkenny', '0 - 11', '11', 'wexford'], ['10', 'christy kehoe', 'wexford', '1 - 7', '10', 'kilkenny'], ['10', 'tom ryan', 'galway', '1 - 7', '10', 'antrim']]
|
figure skating at the asian winter games
|
https://en.wikipedia.org/wiki/Figure_skating_at_the_Asian_Winter_Games
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12573588-9.html.csv
|
superlative
|
japan won the highest number of silver medals in the asian winter games .
|
{'scope': 'all', 'col_superlative': '4', 'row_superlative': '2', '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', 'silver'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; silver }'}, 'nation'], 'result': 'japan', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; silver } ; nation }'}, 'japan'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; silver } ; nation } ; japan } = true', 'tointer': 'select the row whose silver record of all rows is maximum . the nation record of this row is japan .'}
|
eq { hop { argmax { all_rows ; silver } ; nation } ; japan } = true
|
select the row whose silver record of all rows is maximum . the nation record of this row is japan .
|
3
|
3
|
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'silver_5': 5, 'nation_6': 6, 'japan_7': 7}
|
{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'silver_5': 'silver', 'nation_6': 'nation', 'japan_7': 'japan'}
|
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'silver_5': [0], 'nation_6': [1], 'japan_7': [2]}
|
['rank', 'nation', 'gold', 'silver', 'bronze', 'total']
|
[['1', 'china', '13', '9', '13', '35'], ['2', 'japan', '7', '10', '7', '24'], ['3', 'uzbekistan', '1', '2', '3', '6'], ['4', 'kazakhstan', '2', '2', '0', '4'], ['5', 'north korea', '1', '0', '1', '2'], ['6', 'south korea', '0', '0', '2', '2'], ['total', 'total', '24', '23', '26', '73']]
|
locomotives of the great western railway
|
https://en.wikipedia.org/wiki/Locomotives_of_the_Great_Western_Railway
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1169521-12.html.csv
|
count
|
beyer peacock & co has a total of 3 types of locomotives .
|
{'scope': 'subset', 'criterion': 'equal', 'value': 'beyer , peacock & co', 'result': '3', 'col': '1', 'subset': {'col': '1', 'criterion': 'equal', 'value': 'beyer , peacock & co'}}
|
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'manufacturer', 'beyer , peacock & co'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; manufacturer ; beyer , peacock & co }', 'tointer': 'select the rows whose manufacturer record fuzzily matches to beyer , peacock & co .'}, 'manufacturer', 'beyer , peacock & co'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose manufacturer record fuzzily matches to beyer , peacock & co . among these rows , select the rows whose manufacturer record fuzzily matches to beyer , peacock & co .', 'tostr': 'filter_eq { filter_eq { all_rows ; manufacturer ; beyer , peacock & co } ; manufacturer ; beyer , peacock & co }'}], 'result': '3', 'ind': 2, 'tostr': 'count { filter_eq { filter_eq { all_rows ; manufacturer ; beyer , peacock & co } ; manufacturer ; beyer , peacock & co } }', 'tointer': 'select the rows whose manufacturer record fuzzily matches to beyer , peacock & co . among these rows , select the rows whose manufacturer record fuzzily matches to beyer , peacock & co . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_eq { filter_eq { all_rows ; manufacturer ; beyer , peacock & co } ; manufacturer ; beyer , peacock & co } } ; 3 } = true', 'tointer': 'select the rows whose manufacturer record fuzzily matches to beyer , peacock & co . among these rows , select the rows whose manufacturer record fuzzily matches to beyer , peacock & co . the number of such rows is 3 .'}
|
eq { count { filter_eq { filter_eq { all_rows ; manufacturer ; beyer , peacock & co } ; manufacturer ; beyer , peacock & co } } ; 3 } = true
|
select the rows whose manufacturer record fuzzily matches to beyer , peacock & co . among these rows , select the rows whose manufacturer record fuzzily matches to beyer , peacock & co . the number of such rows is 3 .
|
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, 'manufacturer_6': 6, 'beyer , peacock & co_7': 7, 'manufacturer_8': 8, 'beyer, peacock & co_9': 9, '3_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', 'manufacturer_6': 'manufacturer', 'beyer , peacock & co_7': 'beyer , peacock & co', 'manufacturer_8': 'manufacturer', 'beyer, peacock & co_9': 'beyer , peacock & co', '3_10': '3'}
|
{'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_str_eq_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'manufacturer_6': [0], 'beyer , peacock & co_7': [0], 'manufacturer_8': [1], 'beyer, peacock & co_9': [1], '3_10': [3]}
|
['manufacturer', 'type', 'quantity', 'm & swj nos', 'gwr nos']
|
[['beyer , peacock & co', '0 - 4 - 4t', '1', '15', '23'], ['beyer , peacock & co', '2 - 6 - 0', '1', '16', '24'], ['sharp , stewart & co', '4 - 4 - 4t', '2', '17 - 18', '25 , 27'], ['dübs & co', '0 - 6 - 0t', '2', '13 - 14', '825 , 843'], ['beyer , peacock & co', '0 - 6 - 0', '10', '19 - 28', '1003 - 1011 , 1013'], ['north british locomotive co', '4 - 4 - 0', '9', '1 - 8 , 31', '1119 - 1126 , 1128'], ['dübs & co', '4 - 4 - 0', '1', '9', '1127'], ['dübs & co', '2 - 4 - 0', '3', '10 - 12', '1334 - 1336']]
|
joão barbosa
|
https://en.wikipedia.org/wiki/Jo%C3%A3o_Barbosa
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18864385-1.html.csv
|
ordinal
|
2006 was the third year that joão barbosa drove with the rollcentre racing team .
|
{'row': '3', 'col': '1', 'order': '3', 'col_other': '2', 'max_or_min': 'min_to_max', 'value_mentioned': 'yes', 'scope': 'all', 'subset': None}
|
{'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'nth_min', 'args': ['all_rows', 'year', '3'], 'result': '2006', 'ind': 0, 'tostr': 'nth_min { all_rows ; year ; 3 }', 'tointer': 'the 3rd minimum year record of all rows is 2006 .'}, '2006'], 'result': True, 'ind': 1, 'tostr': 'eq { nth_min { all_rows ; year ; 3 } ; 2006 }', 'tointer': 'the 3rd minimum year record of all rows is 2006 .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'year', '3'], 'result': None, 'ind': 2, 'tostr': 'nth_argmin { all_rows ; year ; 3 }'}, 'team'], 'result': 'rollcentre racing', 'ind': 3, 'tostr': 'hop { nth_argmin { all_rows ; year ; 3 } ; team }'}, 'rollcentre racing'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { nth_argmin { all_rows ; year ; 3 } ; team } ; rollcentre racing }', 'tointer': 'the team record of the row with 3rd minimum year record is rollcentre racing .'}], 'result': True, 'ind': 5, 'tostr': 'and { eq { nth_min { all_rows ; year ; 3 } ; 2006 } ; eq { hop { nth_argmin { all_rows ; year ; 3 } ; team } ; rollcentre racing } } = true', 'tointer': 'the 3rd minimum year record of all rows is 2006 . the team record of the row with 3rd minimum year record is rollcentre racing .'}
|
and { eq { nth_min { all_rows ; year ; 3 } ; 2006 } ; eq { hop { nth_argmin { all_rows ; year ; 3 } ; team } ; rollcentre racing } } = true
|
the 3rd minimum year record of all rows is 2006 . the team record of the row with 3rd minimum year record is rollcentre racing .
|
6
|
6
|
{'and_5': 5, 'result_6': 6, 'eq_1': 1, 'nth_min_0': 0, 'all_rows_7': 7, 'year_8': 8, '3_9': 9, '2006_10': 10, 'str_eq_4': 4, 'str_hop_3': 3, 'nth_argmin_2': 2, 'all_rows_11': 11, 'year_12': 12, '3_13': 13, 'team_14': 14, 'rollcentre racing_15': 15}
|
{'and_5': 'and', 'result_6': 'true', 'eq_1': 'eq', 'nth_min_0': 'nth_min', 'all_rows_7': 'all_rows', 'year_8': 'year', '3_9': '3', '2006_10': '2006', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'nth_argmin_2': 'nth_argmin', 'all_rows_11': 'all_rows', 'year_12': 'year', '3_13': '3', 'team_14': 'team', 'rollcentre racing_15': 'rollcentre racing'}
|
{'and_5': [6], 'result_6': [], 'eq_1': [5], 'nth_min_0': [1], 'all_rows_7': [0], 'year_8': [0], '3_9': [0], '2006_10': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'nth_argmin_2': [3], 'all_rows_11': [2], 'year_12': [2], '3_13': [2], 'team_14': [3], 'rollcentre racing_15': [4]}
|
['year', 'team', 'co - drivers', 'class', 'laps', 'pos', 'class pos']
|
[['2004', 'rollcentre racing', 'martin short rob barff', 'lmp1', '230', 'dnf', 'dnf'], ['2005', 'rollcentre racing', 'martin short vanina ickx', 'lmp1', '318', '16th', '8th'], ['2006', 'rollcentre racing', 'martin short stuart moseley', 'lmp2', '294', '20th', '5th'], ['2007', 'rollcentre racing', 'stuart hall martin short', 'lmp1', '347', '4th', '4th'], ['2008', 'rollcentre racing', 'stéphan grégoire vanina ickx', 'lmp1', '352', '11th', '10th'], ['2009', 'pescarolo sport', 'christophe tinseau bruce jouanny', 'lmp1', '368', '8th', '8th'], ['2011', 'level 5 motorsports', 'scott tucker christophe bouchut', 'lmp2', '319', '10th', '3rd']]
|
1950 - 51 fa cup
|
https://en.wikipedia.org/wiki/1950%E2%80%9351_FA_Cup
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17520911-6.html.csv
|
aggregation
|
the 1950-1951 fa cup saw home teams during february 's fifth round scoring a combined total of 19 .
|
{'scope': 'all', 'col': '3', 'type': 'sum', 'result': '19', 'subset': None}
|
{'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'score'], 'result': '19', 'ind': 0, 'tostr': 'sum { all_rows ; score }'}, '19'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; score } ; 19 } = true', 'tointer': 'the sum of the score record of all rows is 19 .'}
|
round_eq { sum { all_rows ; score } ; 19 } = true
|
the sum of the score record of all rows is 19 .
|
2
|
2
|
{'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'score_4': 4, '19_5': 5}
|
{'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'score_4': 'score', '19_5': '19'}
|
{'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'score_4': [0], '19_5': [1]}
|
['tie no', 'home team', 'score', 'away team', 'date']
|
[['1', 'blackpool', '2 - 0', 'mansfield town', '10 february 1951'], ['2', 'wolverhampton wanderers', '2 - 0', 'huddersfield town', '10 february 1951'], ['3', 'sunderland', '3 - 1', 'norwich city', '10 february 1951'], ['4', 'bristol rovers', '3 - 0', 'hull city', '10 february 1951'], ['5', 'manchester united', '1 - 0', 'arsenal', '10 february 1951'], ['6', 'chelsea', '1 - 1', 'fulham', '10 february 1951'], ['replay', 'fulham', '3 - 0', 'chelsea', '14 february 1951'], ['7', 'stoke city', '2 - 4', 'newcastle united', '10 february 1951'], ['8', 'birmingham city', '2 - 0', 'bristol city', '10 february 1951']]
|
1978 vfl season
|
https://en.wikipedia.org/wiki/1978_VFL_season
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10887680-20.html.csv
|
count
|
three of the venues include the word " oval . " .
|
{'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'oval', 'result': '3', 'col': '5', 'subset': None}
|
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'venue', 'oval'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose venue record fuzzily matches to oval .', 'tostr': 'filter_eq { all_rows ; venue ; oval }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; venue ; oval } }', 'tointer': 'select the rows whose venue record fuzzily matches to oval . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; venue ; oval } } ; 3 } = true', 'tointer': 'select the rows whose venue record fuzzily matches to oval . the number of such rows is 3 .'}
|
eq { count { filter_eq { all_rows ; venue ; oval } } ; 3 } = true
|
select the rows whose venue record fuzzily matches to oval . the number of such rows is 3 .
|
3
|
3
|
{'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'venue_5': 5, 'oval_6': 6, '3_7': 7}
|
{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'venue_5': 'venue', 'oval_6': 'oval', '3_7': '3'}
|
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'venue_5': [0], 'oval_6': [0], '3_7': [2]}
|
['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date']
|
[['essendon', '19.16 ( 130 )', 'melbourne', '21.10 ( 136 )', 'windy hill', '11984', '19 august 1978'], ['south melbourne', '24.11 ( 155 )', 'geelong', '26.11 ( 167 )', 'lake oval', '15259', '19 august 1978'], ['footscray', '9.17 ( 71 )', 'fitzroy', '21.13 ( 139 )', 'western oval', '12525', '19 august 1978'], ['richmond', '16.13 ( 109 )', 'collingwood', '19.9 ( 123 )', 'mcg', '59580', '19 august 1978'], ['north melbourne', '9.16 ( 70 )', 'carlton', '19.17 ( 131 )', 'arden street oval', '28965', '19 august 1978'], ['st kilda', '21.13 ( 139 )', 'hawthorn', '12.11 ( 83 )', 'vfl park', '31677', '19 august 1978']]
|
1972 - 73 atlanta flames season
|
https://en.wikipedia.org/wiki/1972%E2%80%9373_Atlanta_Flames_season
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14038705-1.html.csv
|
unique
|
frank blum was the only player drafted by the atlanta flames in the 6th round .
|
{'scope': 'all', 'row': '6', 'col': '1', 'col_other': '3', 'criterion': 'equal', 'value': '6', 'subset': None}
|
{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'round', '6'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose round record is equal to 6 .', 'tostr': 'filter_eq { all_rows ; round ; 6 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; round ; 6 } }', 'tointer': 'select the rows whose round record is equal to 6 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'round', '6'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose round record is equal to 6 .', 'tostr': 'filter_eq { all_rows ; round ; 6 }'}, 'player'], 'result': 'frank blum', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; round ; 6 } ; player }'}, 'frank blum'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; round ; 6 } ; player } ; frank blum }', 'tointer': 'the player record of this unqiue row is frank blum .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; round ; 6 } } ; eq { hop { filter_eq { all_rows ; round ; 6 } ; player } ; frank blum } } = true', 'tointer': 'select the rows whose round record is equal to 6 . there is only one such row in the table . the player record of this unqiue row is frank blum .'}
|
and { only { filter_eq { all_rows ; round ; 6 } } ; eq { hop { filter_eq { all_rows ; round ; 6 } ; player } ; frank blum } } = true
|
select the rows whose round record is equal to 6 . there is only one such row in the table . the player record of this unqiue row is frank blum .
|
6
|
5
|
{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'round_7': 7, '6_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'player_9': 9, 'frank blum_10': 10}
|
{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'round_7': 'round', '6_8': '6', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'player_9': 'player', 'frank blum_10': 'frank blum'}
|
{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'round_7': [0], '6_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'player_9': [2], 'frank blum_10': [3]}
|
['round', 'pick', 'player', 'nationality', 'college / junior / club team']
|
[['1', '2', 'jacques richard', 'canada', 'quebec remparts ( qmjhl )'], ['2', '18', 'dwight bialowas', 'canada', 'regina pats ( wcjhl )'], ['3', '34', 'jean lemieux', 'canada', 'sherbrooke castors ( qmjhl )'], ['4', '50', 'don martineau', 'canada', 'new westminster royals ( wcjhl )'], ['5', '78', 'john martin', 'canada', 'shawinigan bruins ( qmjhl )'], ['6', '82', 'frank blum', 'canada', 'sarnia sting ( sojhl )'], ['7', '98', 'scott smith', 'canada', 'regina pats ( wcjhl )'], ['8', '114', 'dave murphy', 'canada', 'hamilton red wings ( oha )'], ['9', '130', 'pierre roy', 'canada', 'quebec remparts ( qmjhl )']]
|
2002 buffalo bills season
|
https://en.wikipedia.org/wiki/2002_Buffalo_Bills_season
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16352332-1.html.csv
|
unique
|
in the 2002 buffalo bill 's season , kevin thomas was the only cornerback .
|
{'scope': 'all', 'row': '6', 'col': '4', 'col_other': '3', 'criterion': 'equal', 'value': 'cornerback', 'subset': None}
|
{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'position', 'cornerback'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose position record fuzzily matches to cornerback .', 'tostr': 'filter_eq { all_rows ; position ; cornerback }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; position ; cornerback } }', 'tointer': 'select the rows whose position record fuzzily matches to cornerback . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'position', 'cornerback'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose position record fuzzily matches to cornerback .', 'tostr': 'filter_eq { all_rows ; position ; cornerback }'}, 'player'], 'result': 'kevin thomas', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; position ; cornerback } ; player }'}, 'kevin thomas'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; position ; cornerback } ; player } ; kevin thomas }', 'tointer': 'the player record of this unqiue row is kevin thomas .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; position ; cornerback } } ; eq { hop { filter_eq { all_rows ; position ; cornerback } ; player } ; kevin thomas } } = true', 'tointer': 'select the rows whose position record fuzzily matches to cornerback . there is only one such row in the table . the player record of this unqiue row is kevin thomas .'}
|
and { only { filter_eq { all_rows ; position ; cornerback } } ; eq { hop { filter_eq { all_rows ; position ; cornerback } ; player } ; kevin thomas } } = true
|
select the rows whose position record fuzzily matches to cornerback . there is only one such row in the table . the player record of this unqiue row is kevin thomas .
|
6
|
5
|
{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'position_7': 7, 'cornerback_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'player_9': 9, 'kevin thomas_10': 10}
|
{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'position_7': 'position', 'cornerback_8': 'cornerback', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'player_9': 'player', 'kevin thomas_10': 'kevin thomas'}
|
{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'position_7': [0], 'cornerback_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'player_9': [2], 'kevin thomas_10': [3]}
|
['round', 'pick', 'player', 'position', 'college']
|
[['1', '4', 'mike williams', 'tackle', 'texas'], ['2', '36', 'josh reed', 'wide receiver', 'lsu'], ['2', '61', 'ryan denney', 'defensive end', 'byu'], ['3', '97', 'coy wire', 'safety', 'stanford'], ['5', '139', 'justin bannan', 'defensive tackle', 'colorado'], ['6', '176', 'kevin thomas', 'cornerback', 'unlv'], ['7', '215', 'mike pucillo', 'center', 'auburn'], ['7', '249', 'rodney wright', 'wide receiver', 'fresno state'], ['7', '251', 'jarrett ferguson', 'running back', 'virginia tech'], ['7', '260', 'dominique stevenson', 'linebacker', 'tennessee']]
|
1979 cincinnati bengals season
|
https://en.wikipedia.org/wiki/1979_Cincinnati_Bengals_season
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17643197-2.html.csv
|
superlative
|
the game played on week 8 of the 1979 cincinnati bengals season drew the highest crowd attendance .
|
{'scope': 'all', 'col_superlative': '5', 'row_superlative': '8', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None}
|
{'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'attendance'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; attendance }'}, 'week'], 'result': '8', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; attendance } ; week }'}, '8'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; attendance } ; week } ; 8 } = true', 'tointer': 'select the row whose attendance record of all rows is maximum . the week record of this row is 8 .'}
|
eq { hop { argmax { all_rows ; attendance } ; week } ; 8 } = true
|
select the row whose attendance record of all rows is maximum . the week record of this row is 8 .
|
3
|
3
|
{'eq_2': 2, 'result_3': 3, 'num_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'attendance_5': 5, 'week_6': 6, '8_7': 7}
|
{'eq_2': 'eq', 'result_3': 'true', 'num_hop_1': 'num_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'attendance_5': 'attendance', 'week_6': 'week', '8_7': '8'}
|
{'eq_2': [3], 'result_3': [], 'num_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'attendance_5': [0], 'week_6': [1], '8_7': [2]}
|
['week', 'date', 'opponent', 'result', 'attendance']
|
[['1', 'september 2 , 1979', 'denver broncos', 'l 10 - 0', '74788'], ['2', 'september 9 , 1979', 'buffalo bills', 'l 51 - 24', '43504'], ['3', 'september 16 , 1979', 'new england patriots', 'l 20 - 14', '41805'], ['4', 'september 23 , 1979', 'houston oilers', 'l 30 - 27', '45615'], ['5', 'september 30 , 1979', 'dallas cowboys', 'l 38 - 13', '63179'], ['6', 'october 7 , 1979', 'kansas city chiefs', 'l 10 - 7', '40041'], ['7', 'october 14 , 1979', 'pittsburgh steelers', 'w 34 - 10', '52381'], ['8', 'october 21 , 1979', 'cleveland browns', 'l 28 - 27', '75119'], ['9', 'october 28 , 1979', 'philadelphia eagles', 'w 37 - 13', '42036'], ['10', 'november 4 , 1979', 'baltimore colts', 'l 38 - 28', '37740'], ['11', 'november 11 , 1979', 'san diego chargers', 'l 26 - 24', '40782'], ['12', 'november 18 , 1979', 'houston oilers', 'l 42 - 21', '49829'], ['13', 'november 25 , 1979', 'st louis cardinals', 'w 34 - 28', '25103'], ['14', 'december 2 , 1979', 'pittsburgh steelers', 'l 37 - 17', '46521'], ['15', 'december 9 , 1979', 'washington redskins', 'l 28 - 14', '52882'], ['16', 'december 16 , 1979', 'cleveland browns', 'w 16 - 12', '42183']]
|
rowing at the 2008 summer olympics - men 's double sculls
|
https://en.wikipedia.org/wiki/Rowing_at_the_2008_Summer_Olympics_%E2%80%93_Men%27s_double_sculls
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18662686-3.html.csv
|
unique
|
the iranian team was the only team that took over 7:00:00 to finish in men 's double sculls rowing at the 2008 summer olympics .
|
{'scope': 'all', 'row': '5', 'col': '4', 'col_other': '3', 'criterion': 'greater_than', 'value': '7:00:00', 'subset': None}
|
{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'time', '7:00:00'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose time record is greater than 7:00:00 .', 'tostr': 'filter_greater { all_rows ; time ; 7:00:00 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_greater { all_rows ; time ; 7:00:00 } }', 'tointer': 'select the rows whose time record is greater than 7:00:00 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'time', '7:00:00'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose time record is greater than 7:00:00 .', 'tostr': 'filter_greater { all_rows ; time ; 7:00:00 }'}, 'country'], 'result': 'iraq', 'ind': 2, 'tostr': 'hop { filter_greater { all_rows ; time ; 7:00:00 } ; country }'}, 'iraq'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_greater { all_rows ; time ; 7:00:00 } ; country } ; iraq }', 'tointer': 'the country record of this unqiue row is iraq .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_greater { all_rows ; time ; 7:00:00 } } ; eq { hop { filter_greater { all_rows ; time ; 7:00:00 } ; country } ; iraq } } = true', 'tointer': 'select the rows whose time record is greater than 7:00:00 . there is only one such row in the table . the country record of this unqiue row is iraq .'}
|
and { only { filter_greater { all_rows ; time ; 7:00:00 } } ; eq { hop { filter_greater { all_rows ; time ; 7:00:00 } ; country } ; iraq } } = true
|
select the rows whose time record is greater than 7:00:00 . there is only one such row in the table . the country record of this unqiue row is iraq .
|
6
|
5
|
{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_greater_0': 0, 'all_rows_6': 6, 'time_7': 7, '7:00:00_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'country_9': 9, 'iraq_10': 10}
|
{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_greater_0': 'filter_greater', 'all_rows_6': 'all_rows', 'time_7': 'time', '7:00:00_8': '7:00:00', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'country_9': 'country', 'iraq_10': 'iraq'}
|
{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_greater_0': [1, 2], 'all_rows_6': [0], 'time_7': [0], '7:00:00_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'country_9': [2], 'iraq_10': [3]}
|
['rank', 'rowers', 'country', 'time', 'notes']
|
[['1', 'matthew wells , stephen rowbotham', 'great britain', '6:26.33', 'sa / b'], ['2', 'ante kušurin , mario vekić', 'croatia', '6:27.38', 'sa / b'], ['3', 'tõnu endrekson , jüri jaanson', 'estonia', '6:27.95', 'sa / b'], ['4', 'alexander kornilov , alexey svirin', 'russia', '6:44.46', 'r'], ['5', 'haidar nozad , hussein jebur', 'iraq', '7:00:46', 'r']]
|
nfl starting quarterback playoff records
|
https://en.wikipedia.org/wiki/NFL_starting_quarterback_playoff_records
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17788889-4.html.csv
|
superlative
|
dave krieg with the seahawks had the highest number of losses as an nfl quarterback with 4 .
|
{'scope': 'all', 'col_superlative': '5', 'row_superlative': '7', 'value_mentioned': 'yes', 'max_or_min': 'max', 'other_col': '1', 'subset': None}
|
{'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'max', 'args': ['all_rows', 'losses'], 'result': '4', 'ind': 0, 'tostr': 'max { all_rows ; losses }', 'tointer': 'the maximum losses record of all rows is 4 .'}, '4'], 'result': True, 'ind': 1, 'tostr': 'eq { max { all_rows ; losses } ; 4 }', 'tointer': 'the maximum losses record of all rows is 4 .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'losses'], 'result': None, 'ind': 2, 'tostr': 'argmax { all_rows ; losses }'}, 'quarterback'], 'result': 'dave krieg', 'ind': 3, 'tostr': 'hop { argmax { all_rows ; losses } ; quarterback }'}, 'dave krieg'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { argmax { all_rows ; losses } ; quarterback } ; dave krieg }', 'tointer': 'the quarterback record of the row with superlative losses record is dave krieg .'}], 'result': True, 'ind': 5, 'tostr': 'and { eq { max { all_rows ; losses } ; 4 } ; eq { hop { argmax { all_rows ; losses } ; quarterback } ; dave krieg } } = true', 'tointer': 'the maximum losses record of all rows is 4 . the quarterback record of the row with superlative losses record is dave krieg .'}
|
and { eq { max { all_rows ; losses } ; 4 } ; eq { hop { argmax { all_rows ; losses } ; quarterback } ; dave krieg } } = true
|
the maximum losses record of all rows is 4 . the quarterback record of the row with superlative losses record is dave krieg .
|
6
|
6
|
{'and_5': 5, 'result_6': 6, 'eq_1': 1, 'max_0': 0, 'all_rows_7': 7, 'losses_8': 8, '4_9': 9, 'str_eq_4': 4, 'str_hop_3': 3, 'argmax_2': 2, 'all_rows_10': 10, 'losses_11': 11, 'quarterback_12': 12, 'dave krieg_13': 13}
|
{'and_5': 'and', 'result_6': 'true', 'eq_1': 'eq', 'max_0': 'max', 'all_rows_7': 'all_rows', 'losses_8': 'losses', '4_9': '4', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'argmax_2': 'argmax', 'all_rows_10': 'all_rows', 'losses_11': 'losses', 'quarterback_12': 'quarterback', 'dave krieg_13': 'dave krieg'}
|
{'and_5': [6], 'result_6': [], 'eq_1': [5], 'max_0': [1], 'all_rows_7': [0], 'losses_8': [0], '4_9': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'argmax_2': [3], 'all_rows_10': [2], 'losses_11': [2], 'quarterback_12': [3], 'dave krieg_13': [4]}
|
['quarterback', 'games', 'teams', 'wins', 'losses', 'percent']
|
[['brad johnson', '7', 'vikings', '0', '1', '571'], ['brad johnson', '7', 'redskins', '1', '1', '571'], ['brad johnson', '7', 'buccaneers', '3', '1', '571'], ['kerry collins', '7', 'panthers', '1', '1', '429'], ['kerry collins', '7', 'giants', '2', '2', '429'], ['kerry collins', '7', 'titans', '0', '1', '429'], ['dave krieg', '9', 'seahawks', '3', '4', '333'], ['dave krieg', '9', 'chiefs', '0', '1', '333'], ['dave krieg', '9', 'lions', '0', '1', '333'], ['jeff garcia', '6', '49ers', '1', '2', '333'], ['jeff garcia', '6', 'eagles', '1', '1', '333'], ['jeff garcia', '6', 'buccaneers', '0', '1', '333']]
|
2011 capital one world women 's curling championship
|
https://en.wikipedia.org/wiki/2011_Capital_One_World_Women%27s_Curling_Championship
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-26745426-2.html.csv
|
count
|
two athletes had a shot percentage of 78 % .
|
{'scope': 'all', 'criterion': 'equal', 'value': '78 %', 'result': '2', 'col': '11', 'subset': None}
|
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'shot %', '78 %'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose shot % record fuzzily matches to 78 % .', 'tostr': 'filter_eq { all_rows ; shot % ; 78 % }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; shot % ; 78 % } }', 'tointer': 'select the rows whose shot % record fuzzily matches to 78 % . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; shot % ; 78 % } } ; 2 } = true', 'tointer': 'select the rows whose shot % record fuzzily matches to 78 % . the number of such rows is 2 .'}
|
eq { count { filter_eq { all_rows ; shot % ; 78 % } } ; 2 } = true
|
select the rows whose shot % record fuzzily matches to 78 % . 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, 'shot %_5': 5, '78%_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', 'shot %_5': 'shot %', '78%_6': '78 %', '2_7': '2'}
|
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'shot %_5': [0], '78%_6': [0], '2_7': [2]}
|
['country', 'skip', 'w', 'l', 'pf', 'pa', 'ends won', 'ends lost', 'blank ends', 'stolen ends', 'shot %']
|
[['sweden', 'anette norberg', '9', '2', '67', '53', '40', '41', '12', '8', '73 %'], ['china', 'wang bingyu', '8', '3', '64', '43', '44', '30', '14', '16', '82 %'], ['denmark', 'lene nielsen', '7', '4', '77', '55', '47', '33', '15', '14', '78 %'], ['canada', 'amber holland', '7', '4', '68', '55', '42', '40', '12', '7', '82 %'], ['switzerland', 'mirjam ott', '7', '4', '68', '58', '46', '37', '15', '15', '82 %'], ['russia', 'anna sidorova', '6', '5', '70', '65', '40', '45', '8', '8', '72 %'], ['united states', 'patti lank', '6', '5', '64', '63', '48', '36', '10', '17', '72 %'], ['germany', 'andrea schöpp', '5', '6', '61', '67', '40', '49', '12', '13', '78 %'], ['scotland', 'anna sloan', '4', '7', '49', '69', '33', '43', '15', '6', '76 %'], ['norway', 'linn githmark', '3', '8', '54', '71', '42', '48', '15', '7', '77 %'], ['czech republic', 'anna kubešková', '2', '9', '40', '73', '35', '43', '11', '7', '71 %']]
|
wru division five south east
|
https://en.wikipedia.org/wiki/WRU_Division_Five_South_East
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17625749-2.html.csv
|
superlative
|
the club with the most points was the pontyclun rfc in the wru division five south east .
|
{'scope': 'all', 'col_superlative': '11', 'row_superlative': '2', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None}
|
{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'points'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; points }'}, 'club'], 'result': 'pontyclun rfc', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; points } ; club }'}, 'pontyclun rfc'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; points } ; club } ; pontyclun rfc } = true', 'tointer': 'select the row whose points record of all rows is maximum . the club record of this row is pontyclun rfc .'}
|
eq { hop { argmax { all_rows ; points } ; club } ; pontyclun rfc } = true
|
select the row whose points record of all rows is maximum . the club record of this row is pontyclun rfc .
|
3
|
3
|
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'points_5': 5, 'club_6': 6, 'pontyclun rfc_7': 7}
|
{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'points_5': 'points', 'club_6': 'club', 'pontyclun rfc_7': 'pontyclun rfc'}
|
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'points_5': [0], 'club_6': [1], 'pontyclun rfc_7': [2]}
|
['club', 'played', 'drawn', 'lost', 'points for', 'points against', 'tries for', 'tries against', 'try bonus', 'losing bonus', 'points']
|
[['club', 'played', 'drawn', 'lost', 'points for', 'points against', 'tries for', 'tries against', 'try bonus', 'losing bonus', 'points'], ['pontyclun rfc', '20', '0', '2', '694', '191', '104', '21', '12', '2', '86'], ['cilfynydd rfc', '20', '1', '4', '635', '330', '90', '37', '10', '2', '74'], ['barry rfc', '20', '2', '5', '515', '247', '64', '30', '5', '2', '63'], ['st albans rfc', '20', '0', '9', '504', '347', '68', '40', '7', '4', '55'], ['deri rfc', '20', '0', '9', '409', '349', '55', '45', '5', '3', '52'], ['hirwaun rfc', '20', '1', '8', '476', '421', '59', '57', '7', '2', '51'], ['penygraig rfc', '20', '1', '10', '283', '405', '41', '51', '4', '1', '43'], ['cowbridge rfc', '20', '1', '12', '337', '369', '33', '46', '3', '4', '37'], ['old penarthians rfc', '20', '0', '13', '318', '431', '39', '61', '2', '3', '33'], ['dinas powys rfc', '20', '0', '17', '291', '701', '44', '105', '4', '3', '19'], ['canton rfc', '20', '0', '18', '157', '828', '19', '123', '1', '1', '10']]
|
nauru
|
https://en.wikipedia.org/wiki/Nauru
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-21302-1.html.csv
|
aggregation
|
the average population of a district in nauru is 801.29 .
|
{'scope': 'all', 'col': '5', 'type': 'average', 'result': '801.29', 'subset': None}
|
{'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'population ( 2005 )'], 'result': '801.29', 'ind': 0, 'tostr': 'avg { all_rows ; population ( 2005 ) }'}, '801.29'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; population ( 2005 ) } ; 801.29 } = true', 'tointer': 'the average of the population ( 2005 ) record of all rows is 801.29 .'}
|
round_eq { avg { all_rows ; population ( 2005 ) } ; 801.29 } = true
|
the average of the population ( 2005 ) record of all rows is 801.29 .
|
2
|
2
|
{'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'population (2005)_4': 4, '801.29_5': 5}
|
{'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'population (2005)_4': 'population ( 2005 )', '801.29_5': '801.29'}
|
{'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'population (2005)_4': [0], '801.29_5': [1]}
|
['nr', 'district', 'former name', 'area ( ha )', 'population ( 2005 )', 'no of villages', 'density persons / ha']
|
[['1', 'aiwo', 'aiue', '100', '1092', '8', '10.9'], ['2', 'anabar', 'anebwor', '143', '502', '15', '3.5'], ['3', 'anetan', 'añetañ', '100', '516', '12', '5.2'], ['4', 'anibare', 'anybody', '314', '160', '17', '0.5'], ['5', 'baiti', 'beidi', '123', '572', '15', '4.7'], ['6', 'boe', 'boi', '66', '795', '4', '12.0'], ['7', 'buada', 'arenibok', '266', '716', '14', '2.7'], ['8', 'denigomodu', 'denikomotu', '118', '2827', '17', '24.0'], ['9', 'ewa', 'eoa', '117', '318', '12', '2.7'], ['10', 'ijuw', 'ijub', '112', '303', '13', '2.7'], ['11', 'meneng', 'meneñ', '288', '1830', '18', '6.4'], ['12', 'nibok', 'ennibeck', '136', '432', '11', '3.2'], ['13', 'uaboe', 'ueboi', '97', '335', '6', '3.5'], ['14', 'yaren', 'moqua', '150', '820', '7', '5.5']]
|
akapusi qera
|
https://en.wikipedia.org/wiki/Akapusi_Qera
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11470402-1.html.csv
|
superlative
|
japan was the first opponent that akapusi qera has faced off against .
|
{'scope': 'all', 'col_superlative': '1', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '3', 'subset': None}
|
{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmin', 'args': ['all_rows', 'date'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; date }'}, 'opponent'], 'result': 'japan', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; date } ; opponent }'}, 'japan'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmin { all_rows ; date } ; opponent } ; japan } = true', 'tointer': 'select the row whose date record of all rows is minimum . the opponent record of this row is japan .'}
|
eq { hop { argmin { all_rows ; date } ; opponent } ; japan } = true
|
select the row whose date record of all rows is minimum . the opponent record of this row is japan .
|
3
|
3
|
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'date_5': 5, 'opponent_6': 6, 'japan_7': 7}
|
{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'date_5': 'date', 'opponent_6': 'opponent', 'japan_7': 'japan'}
|
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'date_5': [0], 'opponent_6': [1], 'japan_7': [2]}
|
['date', 'venue', 'opponent', 'result', 'competition']
|
[['01 / 07 / 06', 'nagai stadium , osaka', 'japan', 'win - 15 - 29', 'pacific nations cup'], ['14 / 07 / 06', 'adelaide oval , adelaide', 'australia a', 'loss - 47 - 18', 'non - cap friendly'], ['26 / 05 / 07', 'churchill park , lautoka', 'japan', 'win - 30 - 15', 'pacific nations cup'], ['25 / 08 / 07', 'stade municipal , camares', 'sc albi', 'win - 24 - 47', 'non - cap friendly'], ['12 / 09 / 07', 'stadium de toulouse , toulouse', 'japan', 'win - 35 - 31', '2007 rugby world cup'], ['29 / 09 / 07', 'stade de la beaujoire , nantes', 'wales', 'win - 38 - 34', '2007 rugby world cup'], ['05 / 06 / 13', 'twin elm rugby park , nepean', 'canada', 'loss - 20 - 18', 'pacific nations cup']]
|
vitamin k deficiency
|
https://en.wikipedia.org/wiki/Vitamin_K_deficiency
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-20592988-1.html.csv
|
count
|
six of the conditions do not affect bleeding time as a response to the condition .
|
{'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'unaffected', 'result': '6', 'col': '4', 'subset': None}
|
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'bleeding time', 'unaffected'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose bleeding time record fuzzily matches to unaffected .', 'tostr': 'filter_eq { all_rows ; bleeding time ; unaffected }'}], 'result': '6', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; bleeding time ; unaffected } }', 'tointer': 'select the rows whose bleeding time record fuzzily matches to unaffected . the number of such rows is 6 .'}, '6'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; bleeding time ; unaffected } } ; 6 } = true', 'tointer': 'select the rows whose bleeding time record fuzzily matches to unaffected . the number of such rows is 6 .'}
|
eq { count { filter_eq { all_rows ; bleeding time ; unaffected } } ; 6 } = true
|
select the rows whose bleeding time record fuzzily matches to unaffected . the number of such rows is 6 .
|
3
|
3
|
{'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'bleeding time_5': 5, 'unaffected_6': 6, '6_7': 7}
|
{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'bleeding time_5': 'bleeding time', 'unaffected_6': 'unaffected', '6_7': '6'}
|
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'bleeding time_5': [0], 'unaffected_6': [0], '6_7': [2]}
|
['condition', 'prothrombin time', 'partial thromboplastin time', 'bleeding time', 'platelet count']
|
[['vitamin k deficiency or warfarin', 'prolonged', 'normal or mildly prolonged', 'unaffected', 'unaffected'], ['disseminated intravascular coagulation', 'prolonged', 'prolonged', 'prolonged', 'decreased'], ['von willebrand disease', 'unaffected', 'prolonged or unaffected', 'prolonged', 'unaffected'], ['hemophilia', 'unaffected', 'prolonged', 'unaffected', 'unaffected'], ['aspirin', 'unaffected', 'unaffected', 'prolonged', 'unaffected'], ['thrombocytopenia', 'unaffected', 'unaffected', 'prolonged', 'decreased'], ['liver failure , early', 'prolonged', 'unaffected', 'unaffected', 'unaffected'], ['liver failure , end - stage', 'prolonged', 'prolonged', 'prolonged', 'decreased'], ['uremia', 'unaffected', 'unaffected', 'prolonged', 'unaffected'], ['congenital afibrinogenemia', 'prolonged', 'prolonged', 'prolonged', 'unaffected'], ['factor v deficiency', 'prolonged', 'prolonged', 'unaffected', 'unaffected'], ['factor x deficiency as seen in amyloid purpura', 'prolonged', 'prolonged', 'unaffected', 'unaffected'], ["glanzmann 's thrombasthenia", 'unaffected', 'unaffected', 'prolonged', 'unaffected'], ['bernard - soulier syndrome', 'unaffected', 'unaffected', 'prolonged', 'decreased or unaffected'], ['factor xii deficiency', 'unaffected', 'prolonged', 'unaffected', 'unaffected']]
|
1998 cfl draft
|
https://en.wikipedia.org/wiki/1998_CFL_Draft
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16441561-6.html.csv
|
count
|
two players drafted were from the college of manitoba .
|
{'scope': 'all', 'criterion': 'equal', 'value': 'manitoba', 'result': '2', 'col': '5', 'subset': None}
|
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'college', 'manitoba'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose college record fuzzily matches to manitoba .', 'tostr': 'filter_eq { all_rows ; college ; manitoba }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; college ; manitoba } }', 'tointer': 'select the rows whose college record fuzzily matches to manitoba . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; college ; manitoba } } ; 2 } = true', 'tointer': 'select the rows whose college record fuzzily matches to manitoba . the number of such rows is 2 .'}
|
eq { count { filter_eq { all_rows ; college ; manitoba } } ; 2 } = true
|
select the rows whose college record fuzzily matches to manitoba . 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, 'college_5': 5, 'manitoba_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', 'college_5': 'college', 'manitoba_6': 'manitoba', '2_7': '2'}
|
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'college_5': [0], 'manitoba_6': [0], '2_7': [2]}
|
['pick', 'cfl team', 'player', 'position', 'college']
|
[['36', 'hamilton', 'benjie hutchison', 'dl', 'british columbia'], ['37', 'winnipeg', 'john baunemann', 'k', 'manitoba'], ['38', 'winnipeg', 'chad vath', 'lb', 'manitoba'], ['39', 'calgary', 'jodi bednarek', 'lb', 'calgary'], ['40', 'edmonton', 'adam kossack', 'ol', 'hastings college'], ['41', 'montreal', 'kelly ireland', 'ol', "saint mary 's"], ['42', 'saskatchewan', 'james rapesse', 'lb', 'saskatchewan'], ['43', 'hamilton', 'robert yelenich', 'lb', 'york'], ['44', 'toronto', 'bill mitoulas', 'lb', 'notre dame']]
|
2008 - 09 detroit red wings season
|
https://en.wikipedia.org/wiki/2008%E2%80%9309_Detroit_Red_Wings_season
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17371135-5.html.csv
|
count
|
there were red wings games in november of the 08-09 season in which over 20,000 people attended .
|
{'scope': 'all', 'criterion': 'greater_than', 'value': '20,000', 'result': '5', 'col': '6', 'subset': None}
|
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'attendance', '20,000'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose attendance record is greater than 20,000 .', 'tostr': 'filter_greater { all_rows ; attendance ; 20,000 }'}], 'result': '5', 'ind': 1, 'tostr': 'count { filter_greater { all_rows ; attendance ; 20,000 } }', 'tointer': 'select the rows whose attendance record is greater than 20,000 . the number of such rows is 5 .'}, '5'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_greater { all_rows ; attendance ; 20,000 } } ; 5 } = true', 'tointer': 'select the rows whose attendance record is greater than 20,000 . the number of such rows is 5 .'}
|
eq { count { filter_greater { all_rows ; attendance ; 20,000 } } ; 5 } = true
|
select the rows whose attendance record is greater than 20,000 . the number of such rows is 5 .
|
3
|
3
|
{'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_greater_0': 0, 'all_rows_4': 4, 'attendance_5': 5, '20,000_6': 6, '5_7': 7}
|
{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_greater_0': 'filter_greater', 'all_rows_4': 'all_rows', 'attendance_5': 'attendance', '20,000_6': '20,000', '5_7': '5'}
|
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_greater_0': [1], 'all_rows_4': [0], 'attendance_5': [0], '20,000_6': [0], '5_7': [2]}
|
['date', 'visitor', 'score', 'home', 'decision', 'attendance', 'record']
|
[['november 2', 'detroit', '3 - 2', 'vancouver', 'osgood', '18630', '8 - 2 - 2'], ['november 8', 'new jersey', '1 - 3', 'detroit', 'osgood', '20066', '9 - 2 - 2'], ['november 11', 'pittsburgh', '7 - 6', 'detroit', 'osgood', '20066', '9 - 2 - 3'], ['november 13', 'detroit', '4 - 3', 'tampa bay', 'osgood', '20544', '10 - 2 - 3'], ['november 14', 'detroit', '3 - 2', 'florida', 'conklin', '18637', '11 - 2 - 3'], ['november 17', 'edmonton', '0 - 4', 'detroit', 'conklin', '18934', '12 - 2 - 3'], ['november 20', 'detroit', '4 - 3', 'edmonton', 'osgood', '16839', '13 - 2 - 3'], ['november 22', 'detroit', '5 - 2', 'calgary', 'conklin', '19289', '14 - 2 - 3'], ['november 24', 'detroit', '2 - 3', 'vancouver', 'osgood', '18630', '14 - 2 - 4'], ['november 26', 'montreal', '3 - 1', 'detroit', 'conklin', '20066', '14 - 3 - 4'], ['november 28', 'columbus', '3 - 5', 'detroit', 'osgood', '20066', '15 - 3 - 4'], ['november 29', 'detroit', '1 - 3', 'boston', 'conklin', '17565', '15 - 4 - 4']]
|
daniel gracie
|
https://en.wikipedia.org/wiki/Daniel_Gracie
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18377709-2.html.csv
|
count
|
daniel grace finished with a time of 5:00 exactly 5 times across various events .
|
{'scope': 'all', 'criterion': 'equal', 'value': '5:00', 'result': '5', 'col': '7', 'subset': None}
|
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'time', '5:00'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose time record fuzzily matches to 5:00 .', 'tostr': 'filter_eq { all_rows ; time ; 5:00 }'}], 'result': '5', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; time ; 5:00 } }', 'tointer': 'select the rows whose time record fuzzily matches to 5:00 . the number of such rows is 5 .'}, '5'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; time ; 5:00 } } ; 5 } = true', 'tointer': 'select the rows whose time record fuzzily matches to 5:00 . the number of such rows is 5 .'}
|
eq { count { filter_eq { all_rows ; time ; 5:00 } } ; 5 } = true
|
select the rows whose time record fuzzily matches to 5:00 . the number of such rows is 5 .
|
3
|
3
|
{'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'time_5': 5, '5:00_6': 6, '5_7': 7}
|
{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'time_5': 'time', '5:00_6': '5:00', '5_7': '5'}
|
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'time_5': [0], '5:00_6': [0], '5_7': [2]}
|
['res', 'record', 'opponent', 'method', 'event', 'round', 'time', 'location']
|
[['loss', '5 - 4 - 1', 'duane bastress', 'tko ( doctor stoppage )', 'bellator 54', '2', '5:00', 'atlantic city , new jersey , united states'], ['loss', '5 - 3 - 1', 'tim carpenter', 'decision ( split )', 'bellator 38', '3', '5:00', 'tunica , mississippi , united states'], ['win', '5 - 2 - 1', 'martin wojcik', 'submission ( rear - naked choke )', 'israel fc : genesis', '1', '2:17', 'tel aviv , israel'], ['loss', '4 - 2 - 1', 'allan goes', 'tko ( punches )', 'ifl : world championship semifinals', '2', '1:03', 'portland , oregon , united states'], ['win', '4 - 1 - 1', 'wes sims', 'technical submission ( standing rear naked choke )', 'ifl : championship 2006', '1', '2:42', 'atlantic city , new jersey , united states'], ['draw', '3 - 1 - 1', 'wes sims', 'technical draw', 'gfc : team gracie vs team hammer house', '2', '5:00', 'columbus , ohio , united states'], ['win', '3 - 1', 'wataru sakata', 'submission ( armbar )', 'pride shockwave 2003', '1', '7:12', 'saitama , saitama , japan'], ['loss', '2 - 1', 'kazuhiro nakamura', 'decision ( unanimous )', 'pride bushido 1', '2', '5:00', 'saitama , saitama , japan'], ['win', '2 - 0', 'shinsuke nakamura', 'submission ( armlock )', 'inoki bom - ba - ye 2002', '2', '2:14', 'saitama , saitama , japan'], ['win', '1 - 0', 'takashi sugiura', 'decision ( split )', 'pride 21', '3', '5:00', 'saitama , saitama , japan']]
|
state assembly elections in india , 2008
|
https://en.wikipedia.org/wiki/State_Assembly_elections_in_India%2C_2008
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-15329030-1.html.csv
|
ordinal
|
the state of madhya pradesh recorded the highest number of seats ( acs ) in the 2008 india 's state assembly elections .
|
{'row': '4', 'col': '3', 'order': '1', 'col_other': '1', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None}
|
{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'seats ( acs )', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; seats ( acs ) ; 1 }'}, 'state'], 'result': 'madhya pradesh', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; seats ( acs ) ; 1 } ; state }'}, 'madhya pradesh'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; seats ( acs ) ; 1 } ; state } ; madhya pradesh } = true', 'tointer': 'select the row whose seats ( acs ) record of all rows is 1st maximum . the state record of this row is madhya pradesh .'}
|
eq { hop { nth_argmax { all_rows ; seats ( acs ) ; 1 } ; state } ; madhya pradesh } = true
|
select the row whose seats ( acs ) record of all rows is 1st maximum . the state record of this row is madhya pradesh .
|
3
|
3
|
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'seats (acs)_5': 5, '1_6': 6, 'state_7': 7, 'madhya pradesh_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', 'seats (acs)_5': 'seats ( acs )', '1_6': '1', 'state_7': 'state', 'madhya pradesh_8': 'madhya pradesh'}
|
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'seats (acs)_5': [0], '1_6': [0], 'state_7': [1], 'madhya pradesh_8': [2]}
|
['state', 'date of polls', 'seats ( acs )', 'date of counting', 'incumbent', 'election winner']
|
[['tripura', 'saturday , 23 february 2008', '60', 'friday , 7 mar 2008', 'cpi ( m )', 'cpi ( m )'], ['meghalaya', 'monday , 3 march 2008', '60', 'friday , 7 mar 2008', 'inc', 'mpa 1'], ['nagaland', 'wednesday , 5 march 2008', '60', 'saturday , 8 march 2008', 'dan', 'dan 2'], ['madhya pradesh', 'thursday , 27 november 2008', '230', 'monday , 8 december 2008', 'bjp', 'bjp'], ['delhi', 'saturday , 29 november 2008', '70', 'monday , 8 december 2008', 'inc', 'inc'], ['mizoram', 'tuesday , 2 december 2008', '40', 'monday , 08 dec 2008', 'mnf', 'inc']]
|
kashmir
|
https://en.wikipedia.org/wiki/Kashmir
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17337-1.html.csv
|
comparative
|
azad kashmir area has only 1 % more residents that practice muslim than gilgit-baltistan .
|
{'row_1': '4', 'row_2': '5', 'col': '3', 'col_other': '1', 'relation': 'diff', 'record_mentioned': 'no', 'diff_result': {'diff_value': '1 %', 'bigger': 'row1'}}
|
{'func': 'eq', 'args': [{'func': 'diff', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'area', 'azad kashmir'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose area record fuzzily matches to azad kashmir .', 'tostr': 'filter_eq { all_rows ; area ; azad kashmir }'}, '% muslim'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; area ; azad kashmir } ; % muslim }', 'tointer': 'select the rows whose area record fuzzily matches to azad kashmir . take the % muslim record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'area', 'gilgit - baltistan'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose area record fuzzily matches to gilgit - baltistan .', 'tostr': 'filter_eq { all_rows ; area ; gilgit - baltistan }'}, '% muslim'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; area ; gilgit - baltistan } ; % muslim }', 'tointer': 'select the rows whose area record fuzzily matches to gilgit - baltistan . take the % muslim record of this row .'}], 'result': '1 %', 'ind': 4, 'tostr': 'diff { hop { filter_eq { all_rows ; area ; azad kashmir } ; % muslim } ; hop { filter_eq { all_rows ; area ; gilgit - baltistan } ; % muslim } }'}, '1 %'], 'result': True, 'ind': 5, 'tostr': 'eq { diff { hop { filter_eq { all_rows ; area ; azad kashmir } ; % muslim } ; hop { filter_eq { all_rows ; area ; gilgit - baltistan } ; % muslim } } ; 1 % } = true', 'tointer': 'select the rows whose area record fuzzily matches to azad kashmir . take the % muslim record of this row . select the rows whose area record fuzzily matches to gilgit - baltistan . take the % muslim record of this row . the first record is 1 % larger than the second record .'}
|
eq { diff { hop { filter_eq { all_rows ; area ; azad kashmir } ; % muslim } ; hop { filter_eq { all_rows ; area ; gilgit - baltistan } ; % muslim } } ; 1 % } = true
|
select the rows whose area record fuzzily matches to azad kashmir . take the % muslim record of this row . select the rows whose area record fuzzily matches to gilgit - baltistan . take the % muslim record of this row . the first record is 1 % larger than the second record .
|
6
|
6
|
{'str_eq_5': 5, 'result_6': 6, 'diff_4': 4, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_7': 7, 'area_8': 8, 'azad kashmir_9': 9, '% muslim_10': 10, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_11': 11, 'area_12': 12, 'gilgit - baltistan_13': 13, '% muslim_14': 14, '1%_15': 15}
|
{'str_eq_5': 'str_eq', 'result_6': 'true', 'diff_4': 'diff', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_7': 'all_rows', 'area_8': 'area', 'azad kashmir_9': 'azad kashmir', '% muslim_10': '% muslim', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_11': 'all_rows', 'area_12': 'area', 'gilgit - baltistan_13': 'gilgit - baltistan', '% muslim_14': '% muslim', '1%_15': '1 %'}
|
{'str_eq_5': [6], 'result_6': [], 'diff_4': [5], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_7': [0], 'area_8': [0], 'azad kashmir_9': [0], '% muslim_10': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_11': [1], 'area_12': [1], 'gilgit - baltistan_13': [1], '% muslim_14': [3], '1%_15': [5]}
|
['area', 'population', '% muslim', '% hindu', '% buddhist', '% other']
|
[['kashmir valley', '~ 4 million ( 4 million )', '95 %', '4 %', '-', '-'], ['jammu', '~ 3 million ( 3 million )', '30 %', '66 %', '-', '4 %'], ['ladakh', '~ 0.25 million ( 250000 )', '46 %', '-', '50 %', '3 %'], ['azad kashmir', '~ 2.6 million ( 2.6 million )', '100 %', '-', '-', '-'], ['gilgit - baltistan', '~ 1 million ( 1 million )', '99 %', '-', '-', '-'], ['aksai chin', '-', '-', '-', '-', '-']]
|
2010 - 11 new jersey nets season
|
https://en.wikipedia.org/wiki/2010%E2%80%9311_New_Jersey_Nets_season
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27700375-8.html.csv
|
majority
|
kris humphries had the majority of the high rebounds performances for the new jersey nets .
|
{'scope': 'all', 'col': '6', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'kris humphries', 'subset': None}
|
{'func': 'most_str_eq', 'args': ['all_rows', 'high rebounds', 'kris humphries'], 'result': True, 'ind': 0, 'tointer': 'for the high rebounds records of all rows , most of them fuzzily match to kris humphries .', 'tostr': 'most_eq { all_rows ; high rebounds ; kris humphries } = true'}
|
most_eq { all_rows ; high rebounds ; kris humphries } = true
|
for the high rebounds records of all rows , most of them fuzzily match to kris humphries .
|
1
|
1
|
{'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'high rebounds_3': 3, 'kris humphries_4': 4}
|
{'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'high rebounds_3': 'high rebounds', 'kris humphries_4': 'kris humphries'}
|
{'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'high rebounds_3': [0], 'kris humphries_4': [0]}
|
['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record']
|
[['34', 'january 1', 'minnesota', 'l 88 - 103 ( ot )', 'sasha vujačić ( 22 )', 'kris humphries ( 14 )', 'devin harris ( 8 )', 'target center 12665', '9 - 25'], ['35', 'january 5', 'chicago', 'w 96 - 94 ( ot )', 'kris humphries ( 20 )', 'kris humphries ( 11 )', 'devin harris ( 11 )', 'prudential center 15025', '10 - 25'], ['36', 'january 7', 'washington', 'l 77 - 97 ( ot )', 'jordan farmar , brook lopez ( 14 )', 'stephen graham ( 9 )', 'devin harris ( 3 )', 'verizon center 16017', '10 - 26'], ['37', 'january 8', 'milwaukee', 'l 92 - 115 ( ot )', 'kris humphries ( 22 )', 'kris humphries ( 8 )', 'jordan farmar ( 10 )', 'prudential center 12898', '10 - 27'], ['38', 'january 12', 'phoenix', 'l 109 - 118 ( ot )', 'sasha vujačić ( 19 )', 'travis outlaw ( 11 )', 'devin harris ( 15 )', 'us airways center 16334', '10 - 28'], ['39', 'january 14', 'la lakers', 'l 88 - 100 ( ot )', 'brook lopez ( 35 )', 'kris humphries ( 15 )', 'devin harris ( 8 )', 'staples center 18997', '10 - 29'], ['40', 'january 15', 'portland', 'l 89 - 96 ( ot )', 'brook lopez ( 32 )', 'kris humphries ( 10 )', 'devin harris ( 6 )', 'rose garden 20441', '10 - 30'], ['41', 'january 17', 'golden state', 'l 100 - 109 ( ot )', 'brook lopez ( 20 )', 'kris humphries ( 10 )', 'devin harris ( 8 )', 'oracle arena 18563', '10 - 31'], ['42', 'january 19', 'utah', 'w 103 - 95 ( ot )', 'brook lopez ( 20 )', 'travis outlaw ( 8 )', 'devin harris ( 8 )', 'prudential center 13251', '11 - 31'], ['43', 'january 21', 'detroit', 'w 89 - 74 ( ot )', 'brook lopez ( 15 )', 'kris humphries ( 12 )', 'devin harris ( 9 )', 'prudential center 13316', '12 - 31'], ['44', 'january 22', 'dallas', 'l 86 - 87 ( ot )', 'brook lopez ( 24 )', 'kris humphries ( 15 )', 'devin harris ( 11 )', 'prudential center 14051', '12 - 32'], ['45', 'january 24', 'cleveland', 'w 103 - 101 ( ot )', 'brook lopez ( 28 )', 'kris humphries ( 11 )', 'devin harris ( 10 )', 'prudential center 10197', '13 - 32'], ['46', 'january 26', 'memphis', 'w 93 - 88 ( ot )', 'anthony morrow ( 19 )', 'derrick favors ( 9 )', 'devin harris ( 9 )', 'prudential center 8866', '14 - 32'], ['47', 'january 28', 'indiana', 'l 92 - 124 ( ot )', 'brook lopez ( 28 )', 'travis outlaw ( 6 )', 'devin harris ( 9 )', 'conseco fieldhouse 11337', '14 - 33'], ['48', 'january 29', 'milwaukee', 'l 81 - 91 ( ot )', 'brook lopez ( 26 )', 'kris humphries ( 10 )', 'devin harris ( 16 )', 'bradley center 17173', '14 - 34']]
|
thunder live
|
https://en.wikipedia.org/wiki/Thunder_Live
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12702752-1.html.csv
|
superlative
|
the april 21 , 1980 stereo lp release of thunder live was the largest size in centimeters .
|
{'scope': 'all', 'col_superlative': '6', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '2,4', 'subset': None}
|
{'func': 'and', 'args': [{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'note'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; note }'}, 'date'], 'result': 'april 21 , 1980', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; note } ; date }'}, 'april 21 , 1980'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; note } ; date } ; april 21 , 1980 }', 'tointer': 'select the row whose note record of all rows is maximum . the date record of this row is april 21 , 1980 .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'note'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; note }'}, 'format'], 'result': 'stereo lp', 'ind': 3, 'tostr': 'hop { argmax { all_rows ; note } ; format }'}, 'stereo lp'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { argmax { all_rows ; note } ; format } ; stereo lp }', 'tointer': 'the format record of this row is stereo lp .'}], 'result': True, 'ind': 5, 'tostr': 'and { eq { hop { argmax { all_rows ; note } ; date } ; april 21 , 1980 } ; eq { hop { argmax { all_rows ; note } ; format } ; stereo lp } } = true', 'tointer': 'select the row whose note record of all rows is maximum . the date record of this row is april 21 , 1980 . the format record of this row is stereo lp .'}
|
and { eq { hop { argmax { all_rows ; note } ; date } ; april 21 , 1980 } ; eq { hop { argmax { all_rows ; note } ; format } ; stereo lp } } = true
|
select the row whose note record of all rows is maximum . the date record of this row is april 21 , 1980 . the format record of this row is stereo lp .
|
7
|
6
|
{'and_5': 5, 'result_6': 6, 'str_eq_2': 2, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_7': 7, 'note_8': 8, 'date_9': 9, 'april 21 , 1980_10': 10, 'str_eq_4': 4, 'str_hop_3': 3, 'format_11': 11, 'stereo lp_12': 12}
|
{'and_5': 'and', 'result_6': 'true', 'str_eq_2': 'str_eq', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_7': 'all_rows', 'note_8': 'note', 'date_9': 'date', 'april 21 , 1980_10': 'april 21 , 1980', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'format_11': 'format', 'stereo lp_12': 'stereo lp'}
|
{'and_5': [6], 'result_6': [], 'str_eq_2': [5], 'str_hop_1': [2], 'argmax_0': [1, 3], 'all_rows_7': [0], 'note_8': [0], 'date_9': [1], 'april 21 , 1980_10': [2], 'str_eq_4': [5], 'str_hop_3': [4], 'format_11': [3], 'stereo lp_12': [4]}
|
['region', 'date', 'label', 'format', 'catalog', 'note']
|
[['japan', 'april 21 , 1980', 'alfa records', 'stereo lp', 'alr - 6037', '30 cm'], ['japan', 'december 21 , 1986', 'alfa records', 'cd', '32xa - 106', '12 cm'], ['japan', 'march 21 , 1992', 'alfa records', 'cd', 'alca - 273', '12 cm'], ['japan', 'june 29 , 1994', 'alfa records', 'cd', 'alca - 9003', '12 cm'], ['japan', 'july 23 , 1998', 'alfa records', 'cd', 'alca - 9198', '12 cm'], ['japan', 'december 19 , 2001', 'village records', 'ed remaster cd', 'vrcl - 2203', '12 cm , dsd , lp paper jacket'], ['japan', 'january 17 , 2002', 'village records', 'ed remaster cd', 'vrcl - 2223', '12 cm , dsd'], ['japan', 'may 27 , 2009', 'sony music direct', 'ed remaster cd', 'mhcl - 20005', '12 cm , dsd , blu - spec cd , lp paper jacket']]
|
dancing on ice ( series 3 )
|
https://en.wikipedia.org/wiki/Dancing_on_Ice_%28series_3%29
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-21234111-6.html.csv
|
aggregation
|
for dancing on ice ( series 3 ) teams earning a total score of over 16.0 , their average public vote % was 10.75 % .
|
{'scope': 'subset', 'col': '11', 'type': 'average', 'result': '10.75 %', 'subset': {'col': '8', 'criterion': 'greater_than', 'value': '16.0'}}
|
{'func': 'round_eq', 'args': [{'func': 'avg', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'total', '16.0'], 'result': None, 'ind': 0, 'tostr': 'filter_greater { all_rows ; total ; 16.0 }', 'tointer': 'select the rows whose total record is greater than 16.0 .'}, 'public vote %'], 'result': '10.75 %', 'ind': 1, 'tostr': 'avg { filter_greater { all_rows ; total ; 16.0 } ; public vote % }'}, '10.75 %'], 'result': True, 'ind': 2, 'tostr': 'round_eq { avg { filter_greater { all_rows ; total ; 16.0 } ; public vote % } ; 10.75 % } = true', 'tointer': 'select the rows whose total record is greater than 16.0 . the average of the public vote % record of these rows is 10.75 % .'}
|
round_eq { avg { filter_greater { all_rows ; total ; 16.0 } ; public vote % } ; 10.75 % } = true
|
select the rows whose total record is greater than 16.0 . the average of the public vote % record of these rows is 10.75 % .
|
3
|
3
|
{'eq_2': 2, 'result_3': 3, 'avg_1': 1, 'filter_greater_0': 0, 'all_rows_4': 4, 'total_5': 5, '16.0_6': 6, 'public vote %_7': 7, '10.75%_8': 8}
|
{'eq_2': 'eq', 'result_3': 'true', 'avg_1': 'avg', 'filter_greater_0': 'filter_greater', 'all_rows_4': 'all_rows', 'total_5': 'total', '16.0_6': '16.0', 'public vote %_7': 'public vote %', '10.75%_8': '10.75 %'}
|
{'eq_2': [3], 'result_3': [], 'avg_1': [2], 'filter_greater_0': [1], 'all_rows_4': [0], 'total_5': [0], '16.0_6': [0], 'public vote %_7': [1], '10.75%_8': [2]}
|
['order', 'couple', 'karen', 'nicky', 'jason', 'ruthie', 'robin', 'total', 'scoreboard', 'song', 'public vote %', 'result']
|
[['1', 'gareth & maria', '4.5', '4.0', '3.5', '3.5', '4.0', '19 , 5', '3rd', 'wake me up when september ends - green day', '6.81 %', 'safe'], ['2', 'linda & daniel', '3.5', '3.0', '3.0', '4.0', '3.0', '16.5', '5th', 'candyman - christina aguilera', '9.09 %', 'safe'], ['3', 'samantha & pavel', '3.5', '3.0', '3.0', '3.5', '3.0', '16.0', '7th', "you ca n't hurry love - the supremes", '3.30 %', 'eliminated'], ['4', 'chris & frankie', '5.0', '5.0', '4.0', '4.5', '5.0', '23.5', '1st', 'rule the world - take that', '19.20 %', 'safe'], ['5', 'aggie & sergey', '2.5', '2.0', '2.0', '3.5', '2.5', '12.5', '10th', 'total eclipse of the heart - bonnie tyler', '5.00 %', 'safe'], ['6', 'steve & susie', '3.0', '3.5', '2.0', '3.0', '3.0', '14.5', '9th', 'mony mony - billy idol', '4.68 %', 'bottom two'], ['7', 'greg & kristina', '3.5', '3.5', '2.5', '3.0', '3.0', '15.5', '8th', 'licence to kill - gladys knight', '12.90 %', 'safe'], ['8', 'zaraah & fred', '4.0', '4.5', '3.0', '3.5', '3.5', '18.5', '4th', 'take a chance on me - abba', '7.88 %', 'safe']]
|
wichita state shockers men 's basketball
|
https://en.wikipedia.org/wiki/Wichita_State_Shockers_men%27s_basketball
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16619531-2.html.csv
|
unique
|
gene wiley was the only player who played for wsu in the 50 's to be drafted to the nba .
|
{'scope': 'all', 'row': '1', 'col': '2', 'col_other': '1', 'criterion': 'equal', 'value': '1959 - 62', 'subset': None}
|
{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'wsu year ( s )', '1959 - 62'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose wsu year ( s ) record fuzzily matches to 1959 - 62 .', 'tostr': 'filter_eq { all_rows ; wsu year ( s ) ; 1959 - 62 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; wsu year ( s ) ; 1959 - 62 } }', 'tointer': 'select the rows whose wsu year ( s ) record fuzzily matches to 1959 - 62 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'wsu year ( s )', '1959 - 62'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose wsu year ( s ) record fuzzily matches to 1959 - 62 .', 'tostr': 'filter_eq { all_rows ; wsu year ( s ) ; 1959 - 62 }'}, 'name'], 'result': 'gene wiley', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; wsu year ( s ) ; 1959 - 62 } ; name }'}, 'gene wiley'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; wsu year ( s ) ; 1959 - 62 } ; name } ; gene wiley }', 'tointer': 'the name record of this unqiue row is gene wiley .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; wsu year ( s ) ; 1959 - 62 } } ; eq { hop { filter_eq { all_rows ; wsu year ( s ) ; 1959 - 62 } ; name } ; gene wiley } } = true', 'tointer': 'select the rows whose wsu year ( s ) record fuzzily matches to 1959 - 62 . there is only one such row in the table . the name record of this unqiue row is gene wiley .'}
|
and { only { filter_eq { all_rows ; wsu year ( s ) ; 1959 - 62 } } ; eq { hop { filter_eq { all_rows ; wsu year ( s ) ; 1959 - 62 } ; name } ; gene wiley } } = true
|
select the rows whose wsu year ( s ) record fuzzily matches to 1959 - 62 . there is only one such row in the table . the name record of this unqiue row is gene wiley .
|
6
|
5
|
{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'wsu year (s)_7': 7, '1959 - 62_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'name_9': 9, 'gene wiley_10': 10}
|
{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'wsu year (s)_7': 'wsu year ( s )', '1959 - 62_8': '1959 - 62', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'name_9': 'name', 'gene wiley_10': 'gene wiley'}
|
{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'wsu year (s)_7': [0], '1959 - 62_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'name_9': [2], 'gene wiley_10': [3]}
|
['name', 'wsu year ( s )', 'position', 'team', 'pro year ( s )']
|
[['gene wiley', '1959 - 62', 'c', 'los angeles lakers', '1962 - 67'], ['dave stallworth', '1962 - 65', 'pf - c', 'new york knicks', '1965 - 74'], ['nate bowman', '1962 - 65', 'c', 'cincinnati royals', '1966 - 71'], ['warren jabali', '1965 - 68', 'g - sf', 'new york knicks', '1968 - 1974'], ['bobby wilson', '1972 - 74', 'pg', 'chicago bulls', '1974 - 77'], ['lynbert cheese johnson', '1975 - 79', 'pf', 'golden state warriors', '1979 - 1979'], ['cliff levingston', '1979 - 82', 'pf', 'detroit pistons', '1982 - 94'], ['antoine carr', '1979 - 83', 'pf - c', 'detroit pistons', '1984 - 99'], ['ozell jones', '1979 - 81', 'c - pf', 'san antonio spurs', '1984 - 85'], ['xavier x - man mcdaniel', '1981 - 85', 'sf - pf', 'seattle supersonics', '1985 - 1997'], ['greg dreiling', '1981 - 82', 'c', 'indiana pacers', '1986 - 1996'], ['maurice evans', '1997 - 99', 'sg - sf', 'undrafted', '2001 - 10']]
|
1989 open championship
|
https://en.wikipedia.org/wiki/1989_Open_Championship
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18135501-6.html.csv
|
unique
|
david feherty was the only competing player representing northern ireland .
|
{'scope': 'all', 'row': '7', 'col': '3', 'col_other': '2', 'criterion': 'equal', 'value': 'northern ireland', 'subset': None}
|
{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'northern ireland'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose country record fuzzily matches to northern ireland .', 'tostr': 'filter_eq { all_rows ; country ; northern ireland }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; country ; northern ireland } }', 'tointer': 'select the rows whose country record fuzzily matches to northern ireland . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'northern ireland'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose country record fuzzily matches to northern ireland .', 'tostr': 'filter_eq { all_rows ; country ; northern ireland }'}, 'player'], 'result': 'david feherty', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; country ; northern ireland } ; player }'}, 'david feherty'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; country ; northern ireland } ; player } ; david feherty }', 'tointer': 'the player record of this unqiue row is david feherty .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; country ; northern ireland } } ; eq { hop { filter_eq { all_rows ; country ; northern ireland } ; player } ; david feherty } } = true', 'tointer': 'select the rows whose country record fuzzily matches to northern ireland . there is only one such row in the table . the player record of this unqiue row is david feherty .'}
|
and { only { filter_eq { all_rows ; country ; northern ireland } } ; eq { hop { filter_eq { all_rows ; country ; northern ireland } ; player } ; david feherty } } = true
|
select the rows whose country record fuzzily matches to northern ireland . there is only one such row in the table . the player record of this unqiue row is david feherty .
|
6
|
5
|
{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'country_7': 7, 'northern ireland_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'player_9': 9, 'david feherty_10': 10}
|
{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'country_7': 'country', 'northern ireland_8': 'northern ireland', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'player_9': 'player', 'david feherty_10': 'david feherty'}
|
{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'country_7': [0], 'northern ireland_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'player_9': [2], 'david feherty_10': [3]}
|
['place', 'player', 'country', 'score', 'to par', 'money']
|
[['t1', 'mark calcavecchia', 'united states', '71 + 68 + 68 + 68 = 275', '- 13', 'playoff'], ['t1', 'greg norman', 'australia', '69 + 70 + 72 + 64 = 275', '- 13', 'playoff'], ['t1', 'wayne grady', 'australia', '68 + 67 + 69 + 71 = 275', '- 13', 'playoff'], ['4', 'tom watson', 'united states', '69 + 68 + 68 + 72 = 277', '- 11', '40000'], ['5', 'jodie mudd', 'united states', '73 + 67 + 68 + 70 = 278', '- 10', '30000'], ['t6', 'fred couples', 'united states', '68 + 71 + 68 + 72 = 279', '- 9', '26000'], ['t6', 'david feherty', 'northern ireland', '71 + 67 + 69 + 72 = 279', '- 9', '26000'], ['t8', 'eduardo romero', 'argentina', '68 + 70 + 75 + 67 = 280', '- 8', '21000'], ['t8', 'paul azinger', 'united states', '68 + 73 + 67 + 72 = 280', '- 8', '21000'], ['t8', 'payne stewart', 'united states', '72 + 65 + 69 + 74 = 280', '- 8', '21000']]
|
forbes global 2000
|
https://en.wikipedia.org/wiki/Forbes_Global_2000
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1682026-10.html.csv
|
count
|
2 companies in the oil & gas industry are listed in the forbes global 2000 rankings .
|
{'scope': 'all', 'criterion': 'equal', 'value': 'oil & gas', 'result': '2', 'col': '4', 'subset': None}
|
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'industry', 'oil & gas'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose industry record fuzzily matches to oil & gas .', 'tostr': 'filter_eq { all_rows ; industry ; oil & gas }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; industry ; oil & gas } }', 'tointer': 'select the rows whose industry record fuzzily matches to oil & gas . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; industry ; oil & gas } } ; 2 } = true', 'tointer': 'select the rows whose industry record fuzzily matches to oil & gas . the number of such rows is 2 .'}
|
eq { count { filter_eq { all_rows ; industry ; oil & gas } } ; 2 } = true
|
select the rows whose industry record fuzzily matches to oil & gas . 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, 'industry_5': 5, 'oil & gas_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', 'industry_5': 'industry', 'oil & gas_6': 'oil & gas', '2_7': '2'}
|
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'industry_5': [0], 'oil & gas_6': [0], '2_7': [2]}
|
['rank', 'company', 'headquarters', 'industry', 'sales ( billion )', 'profits ( billion )', 'assets ( billion )', 'market value ( billion )']
|
[['1', 'citigroup', 'usa', 'banking', '94.71', '17.85', '1264.03', '255.30'], ['2', 'general electric', 'usa', 'conglomerates', '134.19', '15.59', '626.93', '328.54'], ['3', 'american international group', 'usa', 'insurance', '76.66', '6.46', '647.66', '194.87'], ['4', 'exxonmobil', 'usa', 'oil & gas', '222.88', '20.96', '166.99', '277.02'], ['5', 'bp', 'uk', 'oil & gas', '232.57', '10.27', '177.57', '173.54'], ['6', 'bank of america', 'usa', 'banking', '49.01', '10.81', '736.45', '117.55'], ['7', 'hsbc', 'uk', 'banking', '44.33', '6.66', '757.60', '177.96'], ['8', 'toyota', 'japan', 'automotive', '135.82', '7.99', '171.71', '115.40'], ['9', 'fannie mae', 'usa', 'diversified financials', '53.13', '6.48', '1019.17', '76.84'], ['10', 'walmart', 'usa', 'ing retail', '256.33', '9.05', '104.91', '243.74']]
|
reykjavík international film festival
|
https://en.wikipedia.org/wiki/Reykjav%C3%ADk_International_Film_Festival
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11749830-1.html.csv
|
unique
|
2006 was the only year that atom egoyan won the creative excellency award from reykjavík international film festival .
|
{'scope': 'all', 'row': '3', 'col': '5', 'col_other': '1', 'criterion': 'equal', 'value': 'atom egoyan', 'subset': None}
|
{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'creative excellency', 'atom egoyan'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose creative excellency record fuzzily matches to atom egoyan .', 'tostr': 'filter_eq { all_rows ; creative excellency ; atom egoyan }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; creative excellency ; atom egoyan } }', 'tointer': 'select the rows whose creative excellency record fuzzily matches to atom egoyan . there is only one such row in the table .'}, {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'creative excellency', 'atom egoyan'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose creative excellency record fuzzily matches to atom egoyan .', 'tostr': 'filter_eq { all_rows ; creative excellency ; atom egoyan }'}, 'year'], 'result': '2006', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; creative excellency ; atom egoyan } ; year }'}, '2006'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; creative excellency ; atom egoyan } ; year } ; 2006 }', 'tointer': 'the year record of this unqiue row is 2006 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; creative excellency ; atom egoyan } } ; eq { hop { filter_eq { all_rows ; creative excellency ; atom egoyan } ; year } ; 2006 } } = true', 'tointer': 'select the rows whose creative excellency record fuzzily matches to atom egoyan . there is only one such row in the table . the year record of this unqiue row is 2006 .'}
|
and { only { filter_eq { all_rows ; creative excellency ; atom egoyan } } ; eq { hop { filter_eq { all_rows ; creative excellency ; atom egoyan } ; year } ; 2006 } } = true
|
select the rows whose creative excellency record fuzzily matches to atom egoyan . there is only one such row in the table . the year record of this unqiue row is 2006 .
|
6
|
5
|
{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'creative excellency_7': 7, 'atom egoyan_8': 8, 'eq_3': 3, 'num_hop_2': 2, 'year_9': 9, '2006_10': 10}
|
{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'creative excellency_7': 'creative excellency', 'atom egoyan_8': 'atom egoyan', 'eq_3': 'eq', 'num_hop_2': 'num_hop', 'year_9': 'year', '2006_10': '2006'}
|
{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'creative excellency_7': [0], 'atom egoyan_8': [0], 'eq_3': [4], 'num_hop_2': [3], 'year_9': [2], '2006_10': [3]}
|
['year', 'dates', 'discovery of the year ( golden puffin )', 'lifetime achievement', 'creative excellency', 'audience award', 'fipresci award', 'church of iceland award']
|
[['2004', 'nov 17 - nov 25', 'n / a', 'n / a', 'n / a', 'n / a', 'n / a', 'n / a'], ['2005', 'sept 29 - oct 9', 'the death of mr lazarescu , cristi puiu', 'abbas kiarostami', 'n / a', "howl 's moving castle hayao miyazaki", 'n / a', 'n / a'], ['2006', 'sept 28 - oct 8', 'grbavica , jasmila žbanić', 'alexander sokurov', 'atom egoyan', 'we shall overcome niels arden oplev', 'red road andrea arnold', 'four minutes chris kraus'], ['2007', 'sept 27 - oct 7', "iska 's journey , csaba bollók", 'hanna schygulla', 'n / a', 'control anton corbijn', 'the art of crying peter schønau fog', 'the art of crying peter schønau fog'], ['2008', 'sept 25 - oct 5', 'tulpan , sergey dvortsevoy', 'costa - gavras', 'shirin neshat', 'electronica reykjavík arnar jónasson', 'home , ursula meier', 'snow aida begic'], ['2009', 'sept 17 - sept 27', 'i killed my mother xavier dolan', 'miloš forman', 'n / a', 'the gentlemen janus bragi jakobsson', 'the girl fredrik edfeldt', 'together matias armand jordal'], ['2010', 'sept 23 - oct 3', 'le quattro volte michelangelo frammartino', 'jim jarmusch', 'n / a', 'littlerock mike ott', 'le quattro volte michelangelo frammartino', 'morgen marian crisan'], ['2011', 'sept 22 - oct 2', 'twilight portrait angelina nikonova', 'béla tarr', 'lone scherfig', 'le havre aki kaurismäki', 'volcano rúnar rúnarsson', 'volcano rúnar rúnarsson'], ['2012', 'sept 27 - oct 7', 'beasts of the southern wild benh zeitlin', 'dario argento', 'susanne bier', 'queen of montreuil sólveig anspach', 'starlet sean baker', "god 's neighbours meni yaesh"]]
|
united states house of representatives elections , 1988
|
https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1988
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1341577-34.html.csv
|
count
|
two of the democratic party incumbents in the 1988 house of representative elections had been first elected in 1974 .
|
{'scope': 'subset', 'criterion': 'equal', 'value': '1974', 'result': '2', 'col': '4', 'subset': {'col': '3', 'criterion': 'equal', 'value': 'democratic'}}
|
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'party', 'democratic'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; party ; democratic }', 'tointer': 'select the rows whose party record fuzzily matches to democratic .'}, 'first elected', '1974'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose party record fuzzily matches to democratic . among these rows , select the rows whose first elected record is equal to 1974 .', 'tostr': 'filter_eq { filter_eq { all_rows ; party ; democratic } ; first elected ; 1974 }'}], 'result': '2', 'ind': 2, 'tostr': 'count { filter_eq { filter_eq { all_rows ; party ; democratic } ; first elected ; 1974 } }', 'tointer': 'select the rows whose party record fuzzily matches to democratic . among these rows , select the rows whose first elected record is equal to 1974 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_eq { filter_eq { all_rows ; party ; democratic } ; first elected ; 1974 } } ; 2 } = true', 'tointer': 'select the rows whose party record fuzzily matches to democratic . among these rows , select the rows whose first elected record is equal to 1974 . the number of such rows is 2 .'}
|
eq { count { filter_eq { filter_eq { all_rows ; party ; democratic } ; first elected ; 1974 } } ; 2 } = true
|
select the rows whose party record fuzzily matches to democratic . among these rows , select the rows whose first elected record is equal to 1974 . the number of such rows is 2 .
|
4
|
4
|
{'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_eq_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'party_6': 6, 'democratic_7': 7, 'first elected_8': 8, '1974_9': 9, '2_10': 10}
|
{'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_eq_1': 'filter_eq', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'party_6': 'party', 'democratic_7': 'democratic', 'first elected_8': 'first elected', '1974_9': '1974', '2_10': '2'}
|
{'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_eq_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'party_6': [0], 'democratic_7': [0], 'first elected_8': [1], '1974_9': [1], '2_10': [3]}
|
['district', 'incumbent', 'party', 'first elected', 'result', 'candidates']
|
[['north carolina 2', 'tim valentine', 'democratic', '1982', 're - elected', 'tim valentine ( d ) unopposed'], ['north carolina 3', 'martin lancaster', 'democratic', '1986', 're - elected', 'martin lancaster ( d ) unopposed'], ['north carolina 4', 'david e price', 'democratic', '1986', 're - elected', 'david e price ( d ) 58.0 % tom fetzer ( r ) 42.0 %'], ['north carolina 5', 'stephen l neal', 'democratic', '1974', 're - elected', 'stephen l neal ( d ) 52.6 % lyons gray ( r ) 47.4 %'], ['north carolina 6', 'howard coble', 'republican', '1984', 're - elected', 'howard coble ( r ) 62.5 % tom gilmore ( d ) 37.5 %'], ['north carolina 8', 'bill hefner', 'democratic', '1974', 're - elected', 'bill hefner ( d ) 51.5 % ted blanton ( r ) 48.5 %'], ['north carolina 9', 'alex mcmillan', 'republican', '1984', 're - elected', 'alex mcmillan ( r ) 65.9 % mark sholander ( d ) 34.1 %']]
|
rotores de portugal
|
https://en.wikipedia.org/wiki/Rotores_de_Portugal
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16965464-1.html.csv
|
count
|
in rotores de portugal , one of the squadron 552 squadrons dates 2006-present .
|
{'scope': 'subset', 'criterion': 'equal', 'value': '2006-present', 'result': '1', 'col': '5', 'subset': {'col': '3', 'criterion': 'equal', 'value': 'squadron 552'}}
|
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'squadron', 'squadron 552'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; squadron ; squadron 552 }', 'tointer': 'select the rows whose squadron record fuzzily matches to squadron 552 .'}, 'dates', '2006-present'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose squadron record fuzzily matches to squadron 552 . among these rows , select the rows whose dates record fuzzily matches to 2006-present .', 'tostr': 'filter_eq { filter_eq { all_rows ; squadron ; squadron 552 } ; dates ; 2006-present }'}], 'result': '1', 'ind': 2, 'tostr': 'count { filter_eq { filter_eq { all_rows ; squadron ; squadron 552 } ; dates ; 2006-present } }', 'tointer': 'select the rows whose squadron record fuzzily matches to squadron 552 . among these rows , select the rows whose dates record fuzzily matches to 2006-present . the number of such rows is 1 .'}, '1'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_eq { filter_eq { all_rows ; squadron ; squadron 552 } ; dates ; 2006-present } } ; 1 } = true', 'tointer': 'select the rows whose squadron record fuzzily matches to squadron 552 . among these rows , select the rows whose dates record fuzzily matches to 2006-present . the number of such rows is 1 .'}
|
eq { count { filter_eq { filter_eq { all_rows ; squadron ; squadron 552 } ; dates ; 2006-present } } ; 1 } = true
|
select the rows whose squadron record fuzzily matches to squadron 552 . among these rows , select the rows whose dates record fuzzily matches to 2006-present . the number of such rows is 1 .
|
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, 'squadron_6': 6, 'squadron 552_7': 7, 'dates_8': 8, '2006-present_9': 9, '1_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', 'squadron_6': 'squadron', 'squadron 552_7': 'squadron 552', 'dates_8': 'dates', '2006-present_9': '2006-present', '1_10': '1'}
|
{'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_str_eq_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'squadron_6': [0], 'squadron 552_7': [0], 'dates_8': [1], '2006-present_9': [1], '1_10': [3]}
|
['aircraft', 'origin', 'squadron', 'display aircraft', 'dates']
|
[['sud aviation alouette iii', 'france', 'squadron 33', '4', '1976-1980'], ['sud aviation alouette iii', 'france', 'squadron 102', '2', '1982-1992'], ['sud aviation alouette iii', 'france', 'squadron 111', '4', '1993-1994'], ['sud aviation alouette iii', 'france', 'squadron 552', '2', '2004-2005'], ['sud aviation alouette iii', 'france', 'squadron 552', '3', '2006-present']]
|
claire kuo
|
https://en.wikipedia.org/wiki/Claire_Kuo
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18168296-1.html.csv
|
majority
|
all of claire kuo 's albums were released under the linfiar records label .
|
{'scope': 'all', 'col': '6', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'linfair records', 'subset': None}
|
{'func': 'all_str_eq', 'args': ['all_rows', 'label', 'linfair records'], 'result': True, 'ind': 0, 'tointer': 'for the label records of all rows , all of them fuzzily match to linfair records .', 'tostr': 'all_eq { all_rows ; label ; linfair records } = true'}
|
all_eq { all_rows ; label ; linfair records } = true
|
for the label records of all rows , all of them fuzzily match to linfair records .
|
1
|
1
|
{'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'label_3': 3, 'linfair records_4': 4}
|
{'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'label_3': 'label', 'linfair records_4': 'linfair records'}
|
{'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'label_3': [0], 'linfair records_4': [0]}
|
['album', 'english title', 'chinese ( traditional )', 'chinese ( simplified )', 'release date', 'label']
|
[['1st', "i do n't want to forget you", '我不想忘記你', '我不想忘记你', 'june 29 , 2007', 'linfair records'], ['2nd', 'the next dawn', '下一個天亮', '下一个天亮', 'may 9 , 2008', 'linfair records'], ['3rd', 'singing in the tree', '在樹上唱歌', '在树上唱歌', 'may 22 , 2009', 'linfair records'], ['4th', 'your friend', '妳 朋友', '你 朋友', 'may 14 , 2010', 'linfair records'], ['5th', 'another she', '陪著我的時候想著她', '陪着我的时候想着她', 'august 25 , 2011', 'linfair records'], ['6th', 'keep loving', '我們都能幸福著', '我们都能幸福着', 'december 7 , 2012', 'linfair records']]
|
premier league of bosnia and herzegovina
|
https://en.wikipedia.org/wiki/Premier_League_of_Bosnia_and_Herzegovina
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1474099-1.html.csv
|
aggregation
|
premier league of bosnia and herzegovina clubs had an average of 16 seasons in the top division .
|
{'scope': 'all', 'col': '4', 'type': 'average', 'result': '16', 'subset': None}
|
{'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'number of seasons in top division'], 'result': '16', 'ind': 0, 'tostr': 'avg { all_rows ; number of seasons in top division }'}, '16'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; number of seasons in top division } ; 16 } = true', 'tointer': 'the average of the number of seasons in top division record of all rows is 16 .'}
|
round_eq { avg { all_rows ; number of seasons in top division } ; 16 } = true
|
the average of the number of seasons in top division record of all rows is 16 .
|
2
|
2
|
{'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'number of seasons in top division_4': 4, '16_5': 5}
|
{'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'number of seasons in top division_4': 'number of seasons in top division', '16_5': '16'}
|
{'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'number of seasons in top division_4': [0], '16_5': [1]}
|
['club', 'position in 2012 - 13', 'first season in top division', 'number of seasons in top division', 'number of seasons in premier league a', 'first season of current spell in top division', 'top division titles', 'last top division title']
|
[['borac b', '003 3rd', '1961 - 62', '23', '9', '2008 - 09', '1', '2010 - 11'], ['čelik b , c', '004 4th', '1966 - 67', '30', '13', '2000 - 01', '3 d', '1996 - 97'], ['gošk ( r )', '015 15th', '2011 - 12', '2', '2', '2011 - 12', '0', 'n / a'], ['gradina ( r )', '016 16th', '2012 - 13', '1', '1', '2012 - 13', '0', 'n / a'], ['leotar b , c', '008 8th', '2002 - 03', '11', '11', '2002 - 03', '1', '2002 - 03'], ['olimpic', '005 5th', '2000 - 01', '6', '6', '2009 - 10', '0', 'n / a'], ['radnik', '012 12th', '2006 - 07', '3', '3', '2012 - 13', '1 e', '1998 - 99'], ['rudar', '011 11th', '2009 - 10', '4', '4', '2009 - 10', '0', 'n / a'], ['sarajevo b , c', '002 2nd', '1947 - 48', '55', '13', '1958 - 59', '4 f', '2006 - 07'], ['slavija', '007 7th', '1930', '17', '9', '2004 - 05', '0', 'n / a'], ['široki brijeg b , c', '006 6th', '2000 - 01', '13', '13', '2000 - 01', '6 g', '2005 - 06'], ['travnik', '014 14th', '2000 - 01', '10', '10', '2007 - 08', '0', 'n / a'], ['velež b', '013 13th', '1952 - 53', '48', '10', '2006 - 07', '0', 'n / a'], ['zrinjski b , c', '009 9th', '2000 - 01', '13', '13', '2000 - 01', '2', '2008 - 09'], ['zvijezda', '010 10th', '2008 - 09', '5', '5', '2008 - 09', '0', 'n / a']]
|
2008 afl season
|
https://en.wikipedia.org/wiki/2008_AFL_season
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-14312471-3.html.csv
|
comparative
|
melbourne scored more points as the away team than richmond .
|
{'row_1': '2', 'row_2': '4', 'col': '4', 'col_other': '3', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None}
|
{'func': 'greater', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'away team', 'melbourne'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose away team record fuzzily matches to melbourne .', 'tostr': 'filter_eq { all_rows ; away team ; melbourne }'}, 'away team score'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; away team ; melbourne } ; away team score }', 'tointer': 'select the rows whose away team record fuzzily matches to melbourne . take the away team score record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'away team', 'richmond'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose away team record fuzzily matches to richmond .', 'tostr': 'filter_eq { all_rows ; away team ; richmond }'}, 'away team score'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; away team ; richmond } ; away team score }', 'tointer': 'select the rows whose away team record fuzzily matches to richmond . take the away team score record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; away team ; melbourne } ; away team score } ; hop { filter_eq { all_rows ; away team ; richmond } ; away team score } } = true', 'tointer': 'select the rows whose away team record fuzzily matches to melbourne . take the away team score record of this row . select the rows whose away team record fuzzily matches to richmond . take the away team score record of this row . the first record is greater than the second record .'}
|
greater { hop { filter_eq { all_rows ; away team ; melbourne } ; away team score } ; hop { filter_eq { all_rows ; away team ; richmond } ; away team score } } = true
|
select the rows whose away team record fuzzily matches to melbourne . take the away team score record of this row . select the rows whose away team record fuzzily matches to richmond . take the away team score record of this row . the first record is greater than the second record .
|
5
|
5
|
{'greater_4': 4, 'result_5': 5, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'away team_7': 7, 'melbourne_8': 8, 'away team score_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'away team_11': 11, 'richmond_12': 12, 'away team score_13': 13}
|
{'greater_4': 'greater', 'result_5': 'true', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'away team_7': 'away team', 'melbourne_8': 'melbourne', 'away team score_9': 'away team score', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'away team_11': 'away team', 'richmond_12': 'richmond', 'away team score_13': 'away team score'}
|
{'greater_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'away team_7': [0], 'melbourne_8': [0], 'away team score_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'away team_11': [1], 'richmond_12': [1], 'away team score_13': [3]}
|
['home team', 'home team score', 'away team', 'away team score', 'ground', 'crowd', 'date', 'report']
|
[['collingwood', '8.14 ( 62 )', 'hawthorn', '17.14 ( 116 )', 'mcg', '58307', 'friday , 1 august', 'aflcomau'], ['essendon', '19.10 ( 124 )', 'melbourne', '17.6 ( 108 )', 'mcg', '46334', 'saturday , 2 august', 'aflcomau'], ['adelaide', '13.16 ( 94 )', 'carlton', '12.14 ( 86 )', 'aami stadium', '40730', 'saturday , 2 august', 'aflcomau'], ['geelong', '20.14 ( 134 )', 'richmond', '10.11 ( 71 )', 'telstra dome', '42238', 'saturday , 2 august', 'aflcomau'], ['north melbourne', '13.14 ( 92 )', 'brisbane lions', '11.18 ( 84 )', 'gold coast stadium', '10037', 'saturday , 2 august', 'aflcomau'], ['western bulldogs', '17.11 ( 113 )', 'sydney', '14.13 ( 97 )', 'manuka oval', '13550', 'sunday , 3 august', 'aflcomau'], ['st kilda', '14.17 ( 101 )', 'port adelaide', '14.9 ( 93 )', 'telstra dome', '22878', 'sunday , 3 august', 'aflcomau']]
|
mutsuki - class destroyer
|
https://en.wikipedia.org/wiki/Mutsuki-class_destroyer
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18756696-1.html.csv
|
count
|
5 of the mutsuki - class destroyers had completion dates in the year 1927 .
|
{'scope': 'all', 'criterion': 'fuzzily_match', 'value': '1927', 'result': '5', 'col': '6', 'subset': None}
|
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'completed', '1927'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose completed record fuzzily matches to 1927 .', 'tostr': 'filter_eq { all_rows ; completed ; 1927 }'}], 'result': '5', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; completed ; 1927 } }', 'tointer': 'select the rows whose completed record fuzzily matches to 1927 . the number of such rows is 5 .'}, '5'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; completed ; 1927 } } ; 5 } = true', 'tointer': 'select the rows whose completed record fuzzily matches to 1927 . the number of such rows is 5 .'}
|
eq { count { filter_eq { all_rows ; completed ; 1927 } } ; 5 } = true
|
select the rows whose completed record fuzzily matches to 1927 . the number of such rows is 5 .
|
3
|
3
|
{'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'completed_5': 5, '1927_6': 6, '5_7': 7}
|
{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'completed_5': 'completed', '1927_6': '1927', '5_7': '5'}
|
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'completed_5': [0], '1927_6': [0], '5_7': [2]}
|
['kanji', 'name', 'builder', 'laid down', 'launched', 'completed']
|
[['睦月', 'mutsuki dd - 19', 'sasebo naval arsenal , japan', '21 may 1924', '23 july 1925', '25 march 1926'], ['如月', 'kisaragi dd - 21', 'maizuru naval arsenal , japan', '3 june 1924', '5 june 1925', '21 december 1925'], ['彌生', 'yayoi dd - 23', 'uraga dock company , japan', '11 january 1924', '11 july 1925', '28 august 1926'], ['卯月', 'uzuki dd - 25', 'ishikawajima shipyards , japan', '11 january 1924', '15 october 1925', '14 september 1926'], ['皐月', 'satsuki dd - 27', 'fujinagata shipyards , japan', '1 december 1924', '25 march 1925', '15 november 1925'], ['水無月', 'minazuki dd - 28', 'uraga dock company , japan', '24 march 1924', '25 march 1926', '22 march 1927'], ['文月', 'fumizuki dd - 29', 'fujinagata shipyards , japan', '20 october 1924', '16 february 1926', '3 july 1926'], ['長月', 'nagatsuki dd - 30', 'ishikawajima shipyards , japan', '16 april 1925', '6 october 1926', '30 april 1927'], ['菊月', 'kikuzuki dd - 31', 'maizuru naval arsenal , japan', '15 june 1925', '15 may 1926', '20 november 1926'], ['三日月', 'mikazuki dd - 32', 'sasebo naval arsenal , japan', '21 august 1925', '12 july 1926', '5 may 1927'], ['望月', 'mochizuki dd - 33', 'uraga dock company , japan', '23 march 1926', '28 april 1927', '31 october 1927'], ['夕月', 'yūzuki dd - 34', 'fujinagata shipyards , japan', '27 november 1926', '4 march 1927', '25 july 1927']]
|
fish leong
|
https://en.wikipedia.org/wiki/Fish_Leong
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1893815-1.html.csv
|
unique
|
the only fish leong album released by rock records in 2000 is courage .
|
{'scope': 'subset', 'row': '2', 'col': '5', 'col_other': '2,6', 'criterion': 'fuzzily_match', 'value': '2000', 'subset': {'col': '6', 'criterion': 'equal', 'value': 'rock records'}}
|
{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'label', 'rock records'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; label ; rock records }', 'tointer': 'select the rows whose label record fuzzily matches to rock records .'}, 'release date', '2000'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose label record fuzzily matches to rock records . among these rows , select the rows whose release date record fuzzily matches to 2000 .', 'tostr': 'filter_eq { filter_eq { all_rows ; label ; rock records } ; release date ; 2000 }'}], 'result': True, 'ind': 2, 'tostr': 'only { filter_eq { filter_eq { all_rows ; label ; rock records } ; release date ; 2000 } }', 'tointer': 'select the rows whose label record fuzzily matches to rock records . among these rows , select the rows whose release date record fuzzily matches to 2000 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'label', 'rock records'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; label ; rock records }', 'tointer': 'select the rows whose label record fuzzily matches to rock records .'}, 'release date', '2000'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose label record fuzzily matches to rock records . among these rows , select the rows whose release date record fuzzily matches to 2000 .', 'tostr': 'filter_eq { filter_eq { all_rows ; label ; rock records } ; release date ; 2000 }'}, 'english title'], 'result': 'courage', 'ind': 3, 'tostr': 'hop { filter_eq { filter_eq { all_rows ; label ; rock records } ; release date ; 2000 } ; english title }'}, 'courage'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { filter_eq { filter_eq { all_rows ; label ; rock records } ; release date ; 2000 } ; english title } ; courage }', 'tointer': 'the english title record of this unqiue row is courage .'}], 'result': True, 'ind': 5, 'tostr': 'and { only { filter_eq { filter_eq { all_rows ; label ; rock records } ; release date ; 2000 } } ; eq { hop { filter_eq { filter_eq { all_rows ; label ; rock records } ; release date ; 2000 } ; english title } ; courage } } = true', 'tointer': 'select the rows whose label record fuzzily matches to rock records . among these rows , select the rows whose release date record fuzzily matches to 2000 . there is only one such row in the table . the english title record of this unqiue row is courage .'}
|
and { only { filter_eq { filter_eq { all_rows ; label ; rock records } ; release date ; 2000 } } ; eq { hop { filter_eq { filter_eq { all_rows ; label ; rock records } ; release date ; 2000 } ; english title } ; courage } } = true
|
select the rows whose label record fuzzily matches to rock records . among these rows , select the rows whose release date record fuzzily matches to 2000 . there is only one such row in the table . the english title record of this unqiue row is courage .
|
8
|
6
|
{'and_5': 5, 'result_6': 6, 'only_2': 2, 'filter_str_eq_1': 1, 'filter_str_eq_0': 0, 'all_rows_7': 7, 'label_8': 8, 'rock records_9': 9, 'release date_10': 10, '2000_11': 11, 'str_eq_4': 4, 'str_hop_3': 3, 'english title_12': 12, 'courage_13': 13}
|
{'and_5': 'and', 'result_6': 'true', 'only_2': 'only', 'filter_str_eq_1': 'filter_str_eq', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_7': 'all_rows', 'label_8': 'label', 'rock records_9': 'rock records', 'release date_10': 'release date', '2000_11': '2000', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'english title_12': 'english title', 'courage_13': 'courage'}
|
{'and_5': [6], 'result_6': [], 'only_2': [5], 'filter_str_eq_1': [2, 3], 'filter_str_eq_0': [1], 'all_rows_7': [0], 'label_8': [0], 'rock records_9': [0], 'release date_10': [1], '2000_11': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'english title_12': [3], 'courage_13': [4]}
|
['album', 'english title', 'chinese ( traditional )', 'chinese ( simplified )', 'release date', 'label']
|
[['1st', 'grown up overnight', '一夜長大', '一夜长大', 'september 17 , 1999', 'rock records'], ['2nd', 'courage', '勇氣', '勇气', 'august 2 , 2000', 'rock records'], ['3rd', 'shining star', '閃亮的星', '闪亮的星', 'june 27 , 2001', 'rock records'], ['4th', 'sunrise', '我喜歡', '我喜欢', 'february 7 , 2002', 'rock records'], ['5th', 'beautiful', '美麗人生', '美丽人生', 'february 12 , 2003', 'rock records'], ['6th', 'wings of love', '燕尾蝶', '燕尾蝶', 'september 10 , 2004', 'rock records'], ['7th', 'silk road of love', '絲路', '丝路', 'september 16 , 2005', 'rock records'], ['8th', 'kissing the future of love', '親親', '亲亲', 'october 6 , 2006', "b ' in music"], ['9th', "j' adore", '崇拜', '崇拜', 'november 9 , 2007', "b ' in music"], ['10th', 'fall in love & songs', '靜茹 ＆ 情歌 - 別再為他流淚', '静茹 ＆ 情歌 - 别再为他流泪', 'january 16 , 2009', "b ' in music"], ['11th', "what love songs did n't tell you", '情歌沒有告訴你', '情歌没有告诉你', 'december 24 , 2010', 'universal music']]
|
christian dailly
|
https://en.wikipedia.org/wiki/Christian_Dailly
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1317736-1.html.csv
|
unique
|
the only game that christian dailly scored more than one international goal took place in hong kong , china .
|
{'scope': 'all', 'row': '3', 'col': '4', 'col_other': '3', 'criterion': 'greater_than', 'value': '1', 'subset': None}
|
{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'score', '1'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose score record is greater than 1 .', 'tostr': 'filter_greater { all_rows ; score ; 1 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_greater { all_rows ; score ; 1 } }', 'tointer': 'select the rows whose score record is greater than 1 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'score', '1'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose score record is greater than 1 .', 'tostr': 'filter_greater { all_rows ; score ; 1 }'}, 'venue'], 'result': 'hong kong , china', 'ind': 2, 'tostr': 'hop { filter_greater { all_rows ; score ; 1 } ; venue }'}, 'hong kong , china'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_greater { all_rows ; score ; 1 } ; venue } ; hong kong , china }', 'tointer': 'the venue record of this unqiue row is hong kong , china .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_greater { all_rows ; score ; 1 } } ; eq { hop { filter_greater { all_rows ; score ; 1 } ; venue } ; hong kong , china } } = true', 'tointer': 'select the rows whose score record is greater than 1 . there is only one such row in the table . the venue record of this unqiue row is hong kong , china .'}
|
and { only { filter_greater { all_rows ; score ; 1 } } ; eq { hop { filter_greater { all_rows ; score ; 1 } ; venue } ; hong kong , china } } = true
|
select the rows whose score record is greater than 1 . there is only one such row in the table . the venue record of this unqiue row is hong kong , china .
|
6
|
5
|
{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_greater_0': 0, 'all_rows_6': 6, 'score_7': 7, '1_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'venue_9': 9, 'hong kong , china_10': 10}
|
{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_greater_0': 'filter_greater', 'all_rows_6': 'all_rows', 'score_7': 'score', '1_8': '1', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'venue_9': 'venue', 'hong kong , china_10': 'hong kong , china'}
|
{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_greater_0': [1, 2], 'all_rows_6': [0], 'score_7': [0], '1_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'venue_9': [2], 'hong kong , china_10': [3]}
|
['goal', 'date', 'venue', 'score', 'result', 'competition']
|
[['1', '1 june 1997', "ta ' qali , malta", '1 - 0', '3 - 2', 'friendly'], ['2', '17 april 2002', 'aberdeen , scotland', '1 - 0', '1 - 2', 'friendly'], ['3', '23 may 2002', 'hong kong , china', '3 - 0', '4 - 0', 'friendly'], ['4', '12 october 2002', 'reykjavík , iceland', '1 - 0', '2 - 0', 'uefa euro 2004 qualifying'], ['5', '4 june 2005', 'glasgow , scotland', '1 - 0', '2 - 0', 'fifa world cup 2006 qualifying'], ['6', '6 september 2006', 'kaunas , lithuania', '1 - 0', '2 - 1', 'uefa euro 2008 qualifying']]
|
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/1-1341453-7.html.csv
|
comparative
|
george miller was first elected earlier than cal dooley .
|
{'row_1': '1', 'row_2': '3', 'col': '4', 'col_other': '2', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None}
|
{'func': 'less', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'incumbent', 'george miller'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose incumbent record fuzzily matches to george miller .', 'tostr': 'filter_eq { all_rows ; incumbent ; george miller }'}, 'first elected'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; incumbent ; george miller } ; first elected }', 'tointer': 'select the rows whose incumbent record fuzzily matches to george miller . take the first elected record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'incumbent', 'cal dooley'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose incumbent record fuzzily matches to cal dooley .', 'tostr': 'filter_eq { all_rows ; incumbent ; cal dooley }'}, 'first elected'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; incumbent ; cal dooley } ; first elected }', 'tointer': 'select the rows whose incumbent record fuzzily matches to cal dooley . take the first elected record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; incumbent ; george miller } ; first elected } ; hop { filter_eq { all_rows ; incumbent ; cal dooley } ; first elected } } = true', 'tointer': 'select the rows whose incumbent record fuzzily matches to george miller . take the first elected record of this row . select the rows whose incumbent record fuzzily matches to cal dooley . take the first elected record of this row . the first record is less than the second record .'}
|
less { hop { filter_eq { all_rows ; incumbent ; george miller } ; first elected } ; hop { filter_eq { all_rows ; incumbent ; cal dooley } ; first elected } } = true
|
select the rows whose incumbent record fuzzily matches to george miller . take the first elected record of this row . select the rows whose incumbent record fuzzily matches to cal dooley . take the first elected record of this row . the first record is less than the second record .
|
5
|
5
|
{'less_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'incumbent_7': 7, 'george miller_8': 8, 'first elected_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'incumbent_11': 11, 'cal dooley_12': 12, 'first elected_13': 13}
|
{'less_4': 'less', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'incumbent_7': 'incumbent', 'george miller_8': 'george miller', 'first elected_9': 'first elected', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'incumbent_11': 'incumbent', 'cal dooley_12': 'cal dooley', 'first elected_13': 'first elected'}
|
{'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'incumbent_7': [0], 'george miller_8': [0], 'first elected_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'incumbent_11': [1], 'cal dooley_12': [1], 'first elected_13': [3]}
|
['district', 'incumbent', 'party', 'first elected', 'results', 'candidates']
|
[['california 7', 'george miller', 'democratic', '1974', 're - elected', 'george miller ( d ) 77 % norman reece ( r ) 23 %'], ['california 18', 'gary condit', 'democratic', '1989', 're - elected', 'gary condit ( d ) 86.7 % linda degroat ( l ) 13.2 %'], ['california 20', 'cal dooley', 'democratic', '1990', 're - elected', 'cal dooley ( d ) 60.7 % cliff unruh ( r ) 39.3 %'], ['california 21', 'bill thomas', 'republican', '1978', 're - elected', 'bill thomas ( r ) 78.9 % john evans ( ref ) 21 %'], ['california 23', 'elton gallegly', 'republican', '1986', 're - elected', 'elton gallegly ( r ) 60 % daniel gonzalez ( d ) 39.4 %'], ['california 25', 'howard mckeon', 'republican', '1992', 're - elected', 'howard mckeon ( r ) 74.7 % bruce acker ( l ) 25.3 %'], ['california 30', 'xavier becerra', 'democratic', '1992', 're - elected', 'xavier becerra ( d ) 81.3 % patricia parker ( r ) 18.8 %'], ['california 35', 'maxine waters', 'democratic', '1990', 're - elected', 'maxine waters ( d ) 89.3 % gordon mego ( ai ) 10.7 %']]
|
united states house of representatives elections , 1828
|
https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1828
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2668243-22.html.csv
|
majority
|
all of the incumbents were from the jacksonian party .
|
{'scope': 'all', 'col': '3', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'jacksonian', 'subset': None}
|
{'func': 'all_str_eq', 'args': ['all_rows', 'party', 'jacksonian'], 'result': True, 'ind': 0, 'tointer': 'for the party records of all rows , all of them fuzzily match to jacksonian .', 'tostr': 'all_eq { all_rows ; party ; jacksonian } = true'}
|
all_eq { all_rows ; party ; jacksonian } = true
|
for the party records of all rows , all of them fuzzily match to jacksonian .
|
1
|
1
|
{'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'party_3': 3, 'jacksonian_4': 4}
|
{'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'party_3': 'party', 'jacksonian_4': 'jacksonian'}
|
{'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'party_3': [0], 'jacksonian_4': [0]}
|
['district', 'incumbent', 'party', 'first elected', 'result', 'candidates']
|
[['south carolina 1', 'william drayton', 'jacksonian', '1825 ( special )', 're - elected', 'william drayton ( j )'], ['south carolina 2', 'james hamilton , jr', 'jacksonian', '1822 ( special )', 'retired jacksonian hold', 'robert w barnwell ( j )'], ['south carolina 3', 'thomas r mitchell', 'jacksonian', '1820 1824', 'lost re - election jacksonian hold', 'john campbell ( j ) thomas r mitchell ( j )'], ['south carolina 4', 'william d martin', 'jacksonian', '1826', 're - elected', 'william d martin ( j )'], ['south carolina 5', 'george mcduffie', 'jacksonian', '1820', 're - elected', 'george mcduffie ( j )'], ['south carolina 6', 'warren r davis', 'jacksonian', '1826', 're - elected', 'warren r davis ( j ) 76.1 % cobb 23.9 %'], ['south carolina 7', 'william t nuckolls', 'jacksonian', '1826', 're - elected', 'william t nuckolls ( j )']]
|
2008 detroit lions season
|
https://en.wikipedia.org/wiki/2008_Detroit_Lions_season
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15347746-1.html.csv
|
comparative
|
there were more picks for the lions in round 3 than in round 1 .
|
{'row_1': '3', 'row_2': '2', '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', 'round', '3'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose round record fuzzily matches to 3 .', 'tostr': 'filter_eq { all_rows ; round ; 3 }'}, 'pick'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; round ; 3 } ; pick }', 'tointer': 'select the rows whose round record fuzzily matches to 3 . take the pick record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'round', '2'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose round record fuzzily matches to 2 .', 'tostr': 'filter_eq { all_rows ; round ; 2 }'}, 'pick'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; round ; 2 } ; pick }', 'tointer': 'select the rows whose round record fuzzily matches to 2 . take the pick record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; round ; 3 } ; pick } ; hop { filter_eq { all_rows ; round ; 2 } ; pick } } = true', 'tointer': 'select the rows whose round record fuzzily matches to 3 . take the pick record of this row . select the rows whose round record fuzzily matches to 2 . take the pick record of this row . the first record is greater than the second record .'}
|
greater { hop { filter_eq { all_rows ; round ; 3 } ; pick } ; hop { filter_eq { all_rows ; round ; 2 } ; pick } } = true
|
select the rows whose round record fuzzily matches to 3 . take the pick record of this row . select the rows whose round record fuzzily matches to 2 . take the pick 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, 'round_7': 7, '3_8': 8, 'pick_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'round_11': 11, '2_12': 12, 'pick_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', 'round_7': 'round', '3_8': '3', 'pick_9': 'pick', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'round_11': 'round', '2_12': '2', 'pick_13': 'pick'}
|
{'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'round_7': [0], '3_8': [0], 'pick_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'round_11': [1], '2_12': [1], 'pick_13': [3]}
|
['round', 'pick', 'player', 'position', 'team']
|
[['1', '17', 'gosder cherilus', 'offensive tackle', 'boston college'], ['2', '45', 'jordon dizon', 'linebacker', 'colorado'], ['3', '64', 'kevin smith', 'running back', 'central florida'], ['3', '87', 'andre fluellen', 'defensive tackle', 'florida state'], ['3', '92', 'cliff avril', 'linebacker', 'purdue'], ['5', '136', 'kenneth moore , jr', 'wide receiver', 'wake forest'], ['5', '146', 'jerome felton', 'fullback', 'furman'], ['7', '216', 'landon cohen', 'defensive tackle', 'ohio'], ['7', '218', 'caleb campbell', 'safety', 'army']]
|
list of protest clubs
|
https://en.wikipedia.org/wiki/List_of_protest_clubs
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-26218124-1.html.csv
|
count
|
for the protest clubs , when the sport is association football , 6 times , the country was england .
|
{'scope': 'subset', 'criterion': 'equal', 'value': 'england', 'result': '6', 'col': '5', 'subset': {'col': '6', 'criterion': 'equal', 'value': 'association football'}}
|
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'sport', 'association football'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; sport ; association football }', 'tointer': 'select the rows whose sport record fuzzily matches to association football .'}, 'country', 'england'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose sport record fuzzily matches to association football . among these rows , select the rows whose country record fuzzily matches to england .', 'tostr': 'filter_eq { filter_eq { all_rows ; sport ; association football } ; country ; england }'}], 'result': '6', 'ind': 2, 'tostr': 'count { filter_eq { filter_eq { all_rows ; sport ; association football } ; country ; england } }', 'tointer': 'select the rows whose sport record fuzzily matches to association football . among these rows , select the rows whose country record fuzzily matches to england . the number of such rows is 6 .'}, '6'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_eq { filter_eq { all_rows ; sport ; association football } ; country ; england } } ; 6 } = true', 'tointer': 'select the rows whose sport record fuzzily matches to association football . among these rows , select the rows whose country record fuzzily matches to england . the number of such rows is 6 .'}
|
eq { count { filter_eq { filter_eq { all_rows ; sport ; association football } ; country ; england } } ; 6 } = true
|
select the rows whose sport record fuzzily matches to association football . among these rows , select the rows whose country record fuzzily matches to england . the number of such rows is 6 .
|
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, 'sport_6': 6, 'association football_7': 7, 'country_8': 8, 'england_9': 9, '6_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', 'sport_6': 'sport', 'association football_7': 'association football', 'country_8': 'country', 'england_9': 'england', '6_10': '6'}
|
{'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_str_eq_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'sport_6': [0], 'association football_7': [0], 'country_8': [1], 'england_9': [1], '6_10': [3]}
|
['name', 'original club', 'stadium', 'city', 'country', 'sport', 'founded', 'reason for foundation with source']
|
[['afc liverpool', 'liverpool fc', 'valerie park', 'prescot', 'england', 'association football', '2008', 'protesting ticket prices at anfield'], ['bradford city afc', 'manningham fc', 'valley parade', 'bradford', 'england', 'association football', '1903', 'wanted to play another sport'], ['bray wanderers afc', "st kevin 's", 'carlisle grounds', 'bray', 'republic of ireland', 'association football', '1942', 'wanted to play another sport'], ['bv borussia dortmund', 'trinity youth', 'westfalenstadion', 'dortmund', 'germany', 'association football', '1909', "broke away in protest of trinity youth 's manager"], ['cruzeiro esporte clube', 'yale atlético clube', 'mineirão', 'belo horizonte', 'brazil', 'association football', '1921', "protesting yale 's administration"], ['enfield town fc', 'enfield fc', 'goldsdown road', 'london', 'england', 'association football', '2001', 'protesting the way the original club was run'], ['hapoel katamon jerusalem fc', 'hapoel jerusalem fc', 'hebrew university stadium', 'jerusalem', 'israel', 'association football', '2007', 'protesting the management of the original club'], ['liverpool fc', 'everton fc', 'anfield', 'liverpool', 'england', 'association football', '1892', 'protesting over ground usage'], ['london wasps', 'harlequin fc', 'adams park', 'high wycombe', 'england', 'rugby union', '1867', 'split in membership of hampshire rugby club'], ['newcastle falcons', 'gosforth rfc', 'kingston park', 'newcastle upon tyne', 'england', 'rugby union', '1990', 'wanted to turn professional'], ['norwich city fc', 'norwich ceyms fc', 'carrow road', 'norwich', 'england', 'association football', '1902', 'wanted to play another sport'], ['real madrid cf', 'club español de madrid', 'estadio santiago bernabéu', 'madrid', 'spain', 'association football', '1902', 'club split in membership'], ['royal ordnance factories fc', 'royal arsenal fc', 'invicta ground', 'london', 'england', 'association football', '1893', 'wanted a team for amateur factory workers'], ['sheffield eagles', 'huddersfield - sheffield giants', 'bramall lane', 'sheffield', 'england', 'rugby league', '2000', 'protesting an unsuccessful merger'], ['torino fc', 'juventus fc', 'stadio olimpico di torino', 'turin', 'italy', 'association football', '1906', 'protesting a move away from torino']]
|
list of step by step episodes
|
https://en.wikipedia.org/wiki/List_of_Step_by_Step_episodes
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2468961-8.html.csv
|
ordinal
|
of the step by step episodes , the one with the 2nd to last original air date was the one titled " the understudy . " .
|
{'row': '17', 'col': '6', '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', 'original air date', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; original air date ; 2 }'}, 'title'], 'result': 'the understudy', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; original air date ; 2 } ; title }'}, 'the understudy'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; original air date ; 2 } ; title } ; the understudy } = true', 'tointer': 'select the row whose original air date record of all rows is 2nd maximum . the title record of this row is the understudy .'}
|
eq { hop { nth_argmax { all_rows ; original air date ; 2 } ; title } ; the understudy } = true
|
select the row whose original air date record of all rows is 2nd maximum . the title record of this row is the understudy .
|
3
|
3
|
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'original air date_5': 5, '2_6': 6, 'title_7': 7, 'the understudy_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', 'original air date_5': 'original air date', '2_6': '2', 'title_7': 'title', 'the understudy_8': 'the understudy'}
|
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'original air date_5': [0], '2_6': [0], 'title_7': [1], 'the understudy_8': [2]}
|
['no in series', 'no in season', 'title', 'directed by', 'written by', 'original air date', 'production code']
|
[['142', '1', 'making the grade', 'patrick duffy', 'adam markowitz', 'september 19 , 1997', '466501'], ['143', '2', 'a star is born', 'patrick duffy', 'mindy schneider', 'september 26 , 1997', '466502'], ['144', '3', "your cheatin ' heart", 'richard correll', 'howard adler & robert griffard', 'october 3 , 1997', '466503'], ['145', '4', 'take this job and', 'patrick duffy', 'brain bird', 'october 10 , 1997', '466504'], ['146', '5', 'poetic justice', 'patrick duffy', 'fred rubin', 'october 17 , 1997', '466505'], ['147', '6', "ca n't buy me love", 'william bickley', 'robin j stein', 'october 24 , 1997', '466507'], ['148', '7', 'dream lover', 'joel zwick', 'adam markowitz', 'october 31 , 1997', '466506'], ['149', '8', 'girls just wan na have fun', 'patrick duffy', 'mindy schneider', 'november 7 , 1997', '466508'], ['150', '9', 'goodbye , mr chip', 'richard correll', 'howard adler & robert griffard', 'december 5 , 1997', '466509'], ['151', '10', 'too many santas', 'joel zwick', 'robin j stein', 'december 19 , 1997', '466512'], ['152', '11', 'phoney business', 'joel zwick', 'brian bird', 'january 9 , 1998', '466510'], ['153', '12', "goin ' to the chapel", 'joel zwick', 'fred rubin', 'january 16 , 1998', '466511'], ['154', '13', 'feet of clay', 'patrick duffy', 'garrett donovan & neil goldman', 'january 23 , 1998', '466514'], ['155', '14', 'pain in the class', 'patrick duffy', 'adam markowitz', 'january 30 , 1998', '466515'], ['156', '15', 'the half monty', 'joel zwick', 'liz sage', 'february 27 , 1998', '466513'], ['157', '16', 'and justice for some', 'patrick duffy', 'shelly landau', 'june 5 , 1998', '466519'], ['158', '17', 'the understudy', 'william bickley', 'larry kase & joel ronkin', 'june 12 , 1998', '466517'], ['159', '18', "we 're in the money", 'richard correll', 'brian bird', 'june 19 , 1998', '466516']]
|
oklahoma city hornets season
|
https://en.wikipedia.org/wiki/2005%E2%80%9306_New_Orleans/Oklahoma_City_Hornets_season
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18289217-3.html.csv
|
superlative
|
in the 2005-06 oklahoma city hornets season , their first game at the ford center took place on nov 1 .
|
{'scope': 'subset', 'col_superlative': '2', 'row_superlative': '1', 'value_mentioned': 'yes', 'max_or_min': 'min', 'other_col': '5', 'subset': {'col': '5', 'criterion': 'equal', 'value': 'ford center'}}
|
{'func': 'eq', 'args': [{'func': 'min', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location / attendance', 'ford center'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; location / attendance ; ford center }', 'tointer': 'select the rows whose location / attendance record fuzzily matches to ford center .'}, 'date'], 'result': 'nov 1', 'ind': 1, 'tostr': 'min { filter_eq { all_rows ; location / attendance ; ford center } ; date }', 'tointer': 'select the rows whose location / attendance record fuzzily matches to ford center . the minimum date record of these rows is nov 1 .'}, 'nov 1'], 'result': True, 'ind': 2, 'tostr': 'eq { min { filter_eq { all_rows ; location / attendance ; ford center } ; date } ; nov 1 } = true', 'tointer': 'select the rows whose location / attendance record fuzzily matches to ford center . the minimum date record of these rows is nov 1 .'}
|
eq { min { filter_eq { all_rows ; location / attendance ; ford center } ; date } ; nov 1 } = true
|
select the rows whose location / attendance record fuzzily matches to ford center . the minimum date record of these rows is nov 1 .
|
3
|
3
|
{'eq_2': 2, 'result_3': 3, 'min_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'location / attendance_5': 5, 'ford center_6': 6, 'date_7': 7, 'nov 1_8': 8}
|
{'eq_2': 'eq', 'result_3': 'true', 'min_1': 'min', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'location / attendance_5': 'location / attendance', 'ford center_6': 'ford center', 'date_7': 'date', 'nov 1_8': 'nov 1'}
|
{'eq_2': [3], 'result_3': [], 'min_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'location / attendance_5': [0], 'ford center_6': [0], 'date_7': [1], 'nov 1_8': [2]}
|
['game', 'date', 'opponent', 'score', 'location / attendance', 'record', 'streak']
|
[['1', 'nov 1', 'sacramento kings', '93 - 67', 'ford center', '1 - 0', 'won 1'], ['2', 'nov 2', 'cleveland cavaliers', '87 - 109', 'quicken loans arena', '1 - 1', 'lost 1'], ['3', 'nov 5', 'houston rockets', '91 - 84', 'toyota center', '2 - 1', 'won 1'], ['4', 'nov 9', 'orlando magic', '83 - 88', 'ford center', '2 - 2', 'lost 1'], ['5', 'nov 12', 'dallas mavericks', '103 - 109', 'ford center', '2 - 3', 'lost 2'], ['6', 'nov 15', 'miami heat', '102 - 109 ( ot )', 'americanairlines arena', '2 - 4', 'lost 3'], ['7', 'nov 16', 'denver nuggets', '81 - 91', 'ford center', '2 - 5', 'lost 4'], ['8', 'nov 18', 'atlanta hawks', '95 - 92', 'ford center', '3 - 5', 'won 1'], ['9', 'nov 19', 'orlando magic', '98 - 95', 'amway arena', '4 - 5', 'won 2'], ['10', 'nov 21', 'philadelphia 76ers', '91 - 103', 'wachovia center', '4 - 6', 'lost 1'], ['11', 'nov 23', 'minnesota timberwolves', '84 - 80', 'ford center', '5 - 6', 'won 1'], ['12', 'nov 26', 'seattle supersonics', '105 - 99', 'keyarena', '6 - 6', 'won 2'], ['13', 'nov 28', 'golden state warriors', '83 - 99', 'oracle arena', '6 - 7', 'lost 1'], ['14', 'nov 30', 'denver nuggets', '102 - 95', 'pepsi center', '7 - 7', 'won 1']]
|
rowing at the 2008 summer olympics - men 's coxless pair
|
https://en.wikipedia.org/wiki/Rowing_at_the_2008_Summer_Olympics_%E2%80%93_Men%27s_coxless_pair
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18662689-7.html.csv
|
comparative
|
in the 2008 summer olympic men 's coxless pairs , the australian team finished in front of the team from the united states .
|
{'row_1': '1', 'row_2': '2', 'col': '4', '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', 'country', 'australia'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose country record fuzzily matches to australia .', 'tostr': 'filter_eq { all_rows ; country ; australia }'}, 'time'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; country ; australia } ; time }', 'tointer': 'select the rows whose country record fuzzily matches to australia . take the time record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'united states'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose country record fuzzily matches to united states .', 'tostr': 'filter_eq { all_rows ; country ; united states }'}, 'time'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; country ; united states } ; time }', 'tointer': 'select the rows whose country record fuzzily matches to united states . take the time record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; country ; australia } ; time } ; hop { filter_eq { all_rows ; country ; united states } ; time } } = true', 'tointer': 'select the rows whose country record fuzzily matches to australia . take the time record of this row . select the rows whose country record fuzzily matches to united states . take the time record of this row . the first record is less than the second record .'}
|
less { hop { filter_eq { all_rows ; country ; australia } ; time } ; hop { filter_eq { all_rows ; country ; united states } ; time } } = true
|
select the rows whose country record fuzzily matches to australia . take the time record of this row . select the rows whose country record fuzzily matches to united states . take the time 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, 'country_7': 7, 'australia_8': 8, 'time_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'country_11': 11, 'united states_12': 12, 'time_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', 'country_7': 'country', 'australia_8': 'australia', 'time_9': 'time', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'country_11': 'country', 'united states_12': 'united states', 'time_13': 'time'}
|
{'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'country_7': [0], 'australia_8': [0], 'time_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'country_11': [1], 'united states_12': [1], 'time_13': [3]}
|
['rank', 'athlete', 'country', 'time', 'notes']
|
[['1', 'drew ginn , duncan free', 'australia', '6:34.29', 'fa'], ['2', 'tyler winklevoss , cameron winklevoss', 'united states', '6:36.65', 'fa'], ['3', 'tom lehmann , felix drahotta', 'germany', '6:37.26', 'fa'], ['4', 'goran jagar , nikola stojiä ‡', 'serbia', '6:38.96', 'fb'], ['5', 'giuseppe de vita , raffaello leonardo', 'italy', '6:47.30', 'fb'], ['6', 'morten nielsen , thomas larsen', 'denmark', '6:48.65', 'fb']]
|
2003 - 04 philadelphia flyers season
|
https://en.wikipedia.org/wiki/2003%E2%80%9304_Philadelphia_Flyers_season
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14347797-4.html.csv
|
aggregation
|
in the 2003 - 04 philadelphia flyers season , games against the carolina hurricanes had a total of 57 points .
|
{'scope': 'subset', 'col': '6', 'type': 'sum', 'result': '57', 'subset': {'col': '3', 'criterion': 'equal', 'value': 'carolina hurricanes'}}
|
{'func': 'round_eq', 'args': [{'func': 'sum', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', 'carolina hurricanes'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; opponent ; carolina hurricanes }', 'tointer': 'select the rows whose opponent record fuzzily matches to carolina hurricanes .'}, 'points'], 'result': '57', 'ind': 1, 'tostr': 'sum { filter_eq { all_rows ; opponent ; carolina hurricanes } ; points }'}, '57'], 'result': True, 'ind': 2, 'tostr': 'round_eq { sum { filter_eq { all_rows ; opponent ; carolina hurricanes } ; points } ; 57 } = true', 'tointer': 'select the rows whose opponent record fuzzily matches to carolina hurricanes . the sum of the points record of these rows is 57 .'}
|
round_eq { sum { filter_eq { all_rows ; opponent ; carolina hurricanes } ; points } ; 57 } = true
|
select the rows whose opponent record fuzzily matches to carolina hurricanes . the sum of the points record of these rows is 57 .
|
3
|
3
|
{'eq_2': 2, 'result_3': 3, 'sum_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'opponent_5': 5, 'carolina hurricanes_6': 6, 'points_7': 7, '57_8': 8}
|
{'eq_2': 'eq', 'result_3': 'true', 'sum_1': 'sum', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'opponent_5': 'opponent', 'carolina hurricanes_6': 'carolina hurricanes', 'points_7': 'points', '57_8': '57'}
|
{'eq_2': [3], 'result_3': [], 'sum_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'opponent_5': [0], 'carolina hurricanes_6': [0], 'points_7': [1], '57_8': [2]}
|
['game', 'november', 'opponent', 'score', 'record', 'points']
|
[['11', '1', 'toronto maple leafs', '7 - 1', '5 - 2 - 3 - 1', '14'], ['12', '6', 'washington capitals', '4 - 2', '6 - 2 - 3 - 1', '16'], ['13', '8', 'new york rangers', '2 - 1 ot', '7 - 2 - 3 - 1', '18'], ['14', '11', 'new york islanders', '2 - 1', '8 - 2 - 3 - 1', '20'], ['15', '13', 'vancouver canucks', '4 - 3 ot', '9 - 2 - 3 - 1', '22'], ['16', '15', 'atlanta thrashers', '4 - 0', '10 - 2 - 3 - 1', '24'], ['17', '18', 'carolina hurricanes', '2 - 2 ot', '10 - 2 - 4 - 1', '25'], ['18', '20', 'minnesota wild', '3 - 1', '11 - 2 - 4 - 1', '27'], ['19', '22', 'boston bruins', '3 - 2', '12 - 2 - 4 - 1', '29'], ['20', '26', 'pittsburgh penguins', '1 - 1 ot', '12 - 2 - 5 - 1', '30'], ['21', '28', 'carolina hurricanes', '4 - 2', '13 - 2 - 5 - 1', '32'], ['22', '29', 'new york islanders', '5 - 1', '14 - 2 - 5 - 1', '34']]
|
edmonton radial railway society
|
https://en.wikipedia.org/wiki/Edmonton_Radial_Railway_Society
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-22481967-1.html.csv
|
unique
|
the number 1 is the only model from the edmonton radial railway society that has a status of display only .
|
{'scope': 'all', 'row': '2', 'col': '7', 'col_other': '5', 'criterion': 'equal', 'value': 'display only', 'subset': None}
|
{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'status', 'display only'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose status record fuzzily matches to display only .', 'tostr': 'filter_eq { all_rows ; status ; display only }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; status ; display only } }', 'tointer': 'select the rows whose status record fuzzily matches to display only . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'status', 'display only'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose status record fuzzily matches to display only .', 'tostr': 'filter_eq { all_rows ; status ; display only }'}, 'number'], 'result': '1', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; status ; display only } ; number }'}, '1'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; status ; display only } ; number } ; 1 }', 'tointer': 'the number record of this unqiue row is 1 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; status ; display only } } ; eq { hop { filter_eq { all_rows ; status ; display only } ; number } ; 1 } } = true', 'tointer': 'select the rows whose status record fuzzily matches to display only . there is only one such row in the table . the number record of this unqiue row is 1 .'}
|
and { only { filter_eq { all_rows ; status ; display only } } ; eq { hop { filter_eq { all_rows ; status ; display only } ; number } ; 1 } } = true
|
select the rows whose status record fuzzily matches to display only . there is only one such row in the table . the number record of this unqiue row is 1 .
|
6
|
5
|
{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'status_7': 7, 'display only_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'number_9': 9, '1_10': 10}
|
{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'status_7': 'status', 'display only_8': 'display only', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'number_9': 'number', '1_10': '1'}
|
{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'status_7': [0], 'display only_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'number_9': [2], '1_10': [3]}
|
['date', 'builder', 'type', 'operator', 'number', 'withdrawn', 'status']
|
[['1907', 'occ', 'combination sweeper / overhead line car', 'saskatoon municipal railway', '200', '1951', 'stored'], ['1908', 'occ', 'streetcar', 'edmonton radial railway', '1', '1951', 'display only'], ['1912', 'stl', 'streetcar', 'edmonton radial railway', '33', '1951', 'stored'], ['1912', 'stl', 'streetcar', 'edmonton radial railway', '42', '1951', 'fort edmonton park line'], ['1914', 'preston', 'streetcar', 'toronto suburban railway', '24 , ( later cnr 15702 )', '1960s', 'fort edmonton park line'], ['1921', 'u / s', 'tram', 'nankai electric railway ( osaka , japan )', '247', '1990', 'high level bridge line'], ['ca 1920s', 'cc & f', 'streetcar', 'regina municipal railway', '42', '1950', 'closed to viewing'], ['1930', 'occ', 'streetcar', 'edmonton radial railway', '80', '1951', 'fort edmonton park line'], ['1947', 'ptc', 'w6 class tram', 'melbourne and metropolitan tramways board', '930', '1997', 'high level bridge line'], ['1951', 'cc & f', 'pcc streetcar', 'toronto transit commission', '4612', '1995', 'fort edmonton park line']]
|
television in china
|
https://en.wikipedia.org/wiki/Television_in_China
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15147453-3.html.csv
|
majority
|
the minority of television channel in china were launched after the year 2000 .
|
{'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'greater_than', 'value': '2000', 'subset': None}
|
{'func': 'most_greater', 'args': ['all_rows', 'launch', '2000'], 'result': True, 'ind': 0, 'tointer': 'for the launch records of all rows , most of them are greater than 2000 .', 'tostr': 'most_greater { all_rows ; launch ; 2000 } = true'}
|
most_greater { all_rows ; launch ; 2000 } = true
|
for the launch records of all rows , most of them are greater than 2000 .
|
1
|
1
|
{'most_greater_0': 0, 'result_1': 1, 'all_rows_2': 2, 'launch_3': 3, '2000_4': 4}
|
{'most_greater_0': 'most_greater', 'result_1': 'true', 'all_rows_2': 'all_rows', 'launch_3': 'launch', '2000_4': '2000'}
|
{'most_greater_0': [1], 'result_1': [], 'all_rows_2': [0], 'launch_3': [0], '2000_4': [0]}
|
['name', 'hanzi', 'language', 'launch', 'owner']
|
[['kangba satellite television', '康巴卫视', 'tibetan', '2009', 'sichuan radio and television'], ['nmtv mongolian satellite television', '内蒙古蒙语卫视', 'mongolian', '1997', 'nei mongol television ( nmtv )'], ['television southern', '南方卫视', 'cantonese', '2000', 'southern media corporation ( smc )'], ['xjtv uyghur satellite television', '新疆电视台维吾尔语新闻综合频道', 'uyghur', '1997', 'xinjiang television ( xjtv )'], ['xjtv kazakh satellite television', '新疆电视台哈萨克语新闻综合频道', 'kazakh', '1997', 'xinjiang television ( xjtv )'], ['xztv tibetan satellite television', '西藏藏语卫视', 'tibetan', '2002', 'xizang television ( xztv )'], ['yanbian satellite television', '延边卫视', 'korean', '2006', 'yanbian television ( ybtv )'], ['qinghai tibetian general channel', '青海电视台藏语综合频道', 'tibetan', '2006', 'qinghai radio and tv station']]
|
derek warwick
|
https://en.wikipedia.org/wiki/Derek_Warwick
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1158017-1.html.csv
|
count
|
there were four years in which derek warwick did n't score any points at all .
|
{'scope': 'all', 'criterion': 'equal', 'value': '0', 'result': '4', 'col': '5', 'subset': None}
|
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'points', '0'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose points record is equal to 0 .', 'tostr': 'filter_eq { all_rows ; points ; 0 }'}], 'result': '4', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; points ; 0 } }', 'tointer': 'select the rows whose points record is equal to 0 . the number of such rows is 4 .'}, '4'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; points ; 0 } } ; 4 } = true', 'tointer': 'select the rows whose points record is equal to 0 . the number of such rows is 4 .'}
|
eq { count { filter_eq { all_rows ; points ; 0 } } ; 4 } = true
|
select the rows whose points record is equal to 0 . the number of such rows is 4 .
|
3
|
3
|
{'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_eq_0': 0, 'all_rows_4': 4, 'points_5': 5, '0_6': 6, '4_7': 7}
|
{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'points_5': 'points', '0_6': '0', '4_7': '4'}
|
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'points_5': [0], '0_6': [0], '4_7': [2]}
|
['year', 'entrant', 'chassis', 'engine', 'points']
|
[['1981', 'candy toleman motorsport', 'toleman tg181', 'hart 415t 1.5 l4 t', '0'], ['1982', 'candy toleman motorsport', 'toleman tg181c', 'hart 415t 1.5 l4 t', '0'], ['1982', 'candy toleman motorsport', 'toleman tg183', 'hart 415t 1.5 l4 t', '0'], ['1983', 'candy toleman motorsport', 'toleman tg183b', 'hart 415t 1.5 l4 t', '9'], ['1984', 'equipe renault elf', 'renault re50', 'renault ef4 1.5 v6 t', '23'], ['1985', 'equipe renault elf', 'renault re60', 'renault ef4b 1.5 v6 t', '5'], ['1985', 'equipe renault elf', 'renault re60b', 'renault ef15 1.5 v6 t', '5'], ['1986', 'motor racing developments', 'brabham bt55', 'bmw m12 / 13 / 1 1.5 l4 t', '0'], ['1987', 'usf & g arrows megatron', 'arrows a10', 'megatron m12 / 13 1.5 l4 t', '3'], ['1988', 'usf & g arrows megatron', 'arrows a10b', 'megatron m12 / 13 1.5 l4 t', '17'], ['1989', 'usf & g arrows', 'arrows a11', 'ford cosworth dfr 3.5 v8', '7'], ['1990', 'camel team lotus', 'lotus 102', 'lamborghini 3512 3.5 v12', '3'], ['1993', 'footwork mugen - honda', 'footwork fa13b', 'mugen - honda mf - 351 hb 3.5 v10', '4'], ['1993', 'footwork mugen - honda', 'footwork fa14', 'mugen - honda mf - 351 hb 3.5 v10', '4']]
|
list of macintosh models grouped by cpu type
|
https://en.wikipedia.org/wiki/List_of_Macintosh_models_grouped_by_CPU_type
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18640-1.html.csv
|
majority
|
the majority of macintosh models have a processor with a clock speed of 8 mhz .
|
{'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': '8', 'subset': None}
|
{'func': 'most_eq', 'args': ['all_rows', 'clock speed ( mhz )', '8'], 'result': True, 'ind': 0, 'tointer': 'for the clock speed ( mhz ) records of all rows , most of them are equal to 8 .', 'tostr': 'most_eq { all_rows ; clock speed ( mhz ) ; 8 } = true'}
|
most_eq { all_rows ; clock speed ( mhz ) ; 8 } = true
|
for the clock speed ( mhz ) records of all rows , most of them are equal to 8 .
|
1
|
1
|
{'most_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'clock speed (mhz)_3': 3, '8_4': 4}
|
{'most_eq_0': 'most_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'clock speed (mhz)_3': 'clock speed ( mhz )', '8_4': '8'}
|
{'most_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'clock speed (mhz)_3': [0], '8_4': [0]}
|
['processor', 'model', 'clock speed ( mhz )', 'l1 cache ( bytes )', 'introduced', 'discontinued']
|
[['mc68000', 'lisa', '5', '-', 'january 1983', 'january 1984'], ['mc68000', 'lisa 2', '5', '-', 'january 1984', 'january 1985'], ['mc68000', 'macintosh', '8', '-', 'january 1984', 'october 1985'], ['mc68000', 'macintosh 512k', '8', '-', 'september 1984', 'april 1986'], ['mc68000', 'macintosh xl', '5', '-', 'january 1985', 'april 1985'], ['mc68000', 'macintosh plus', '8', '-', 'january 1986', 'october 1990'], ['mc68000', 'macintosh 512ke', '8', '-', 'april 1986', 'september 1987'], ['mc68000', 'macintosh se', '8', '-', 'march 1987', 'august 1989'], ['mc68000', 'macintosh se fdhd', '8', '-', 'august 1989', 'october 1990'], ['mc68000', 'macintosh classic', '8', '-', 'october 1990', 'september 1992'], ['mc68hc000', 'macintosh portable', '16', '-', 'september 1989', 'october 1991'], ['mc68hc000', 'powerbook 100', '16', '-', 'october 1991', 'august 1992']]
|
1998 australian super touring championship
|
https://en.wikipedia.org/wiki/1998_Australian_Super_Touring_Championship
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15394512-2.html.csv
|
unique
|
in the 1998 australian super touring championship , only one race in phillip island , victoria was won by volvo racing team .
|
{'scope': 'subset', 'row': '6', 'col': '7', 'col_other': 'n/a', 'criterion': 'equal', 'value': 'volvo racing', 'subset': {'col': '4', 'criterion': 'equal', 'value': 'phillip island , victoria'}}
|
{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'city / state', 'phillip island , victoria'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; city / state ; phillip island , victoria }', 'tointer': 'select the rows whose city / state record fuzzily matches to phillip island , victoria .'}, 'team', 'volvo racing'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose city / state record fuzzily matches to phillip island , victoria . among these rows , select the rows whose team record fuzzily matches to volvo racing .', 'tostr': 'filter_eq { filter_eq { all_rows ; city / state ; phillip island , victoria } ; team ; volvo racing }'}], 'result': True, 'ind': 2, 'tostr': 'only { filter_eq { filter_eq { all_rows ; city / state ; phillip island , victoria } ; team ; volvo racing } } = true', 'tointer': 'select the rows whose city / state record fuzzily matches to phillip island , victoria . among these rows , select the rows whose team record fuzzily matches to volvo racing . there is only one such row in the table .'}
|
only { filter_eq { filter_eq { all_rows ; city / state ; phillip island , victoria } ; team ; volvo racing } } = true
|
select the rows whose city / state record fuzzily matches to phillip island , victoria . among these rows , select the rows whose team record fuzzily matches to volvo racing . there is only one such row in the table .
|
3
|
3
|
{'only_2': 2, 'result_3': 3, 'filter_str_eq_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'city / state_5': 5, 'phillip island , victoria_6': 6, 'team_7': 7, 'volvo racing_8': 8}
|
{'only_2': 'only', 'result_3': 'true', 'filter_str_eq_1': 'filter_str_eq', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'city / state_5': 'city / state', 'phillip island , victoria_6': 'phillip island , victoria', 'team_7': 'team', 'volvo racing_8': 'volvo racing'}
|
{'only_2': [3], 'result_3': [], 'filter_str_eq_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'city / state_5': [0], 'phillip island , victoria_6': [0], 'team_7': [1], 'volvo racing_8': [1]}
|
['rd / race', 'race title', 'circuit', 'city / state', 'date', 'winner', 'team']
|
[['1 / 1', 'calder', 'calder park raceway', 'melbourne , victoria', '4 - 5 apr', 'cameron mcconville', 'brad jones racing'], ['1 / 2', 'calder', 'calder park raceway', 'melbourne , victoria', '4 - 5 apr', 'cameron mcconville', 'brad jones racing'], ['2 / 1', 'oran park', 'oran park raceway', 'sydney , new south wales', '26 - 27 apr', 'brad jones', 'brad jones racing'], ['2 / 2', 'oran park', 'oran park raceway', 'sydney , new south wales', '26 - 27 apr', 'brad jones', 'brad jones racing'], ['3 / 1', 'phillip island', 'phillip island grand prix circuit', 'phillip island , victoria', '16 - 17 may', 'cameron mcconville', 'brad jones racing'], ['3 / 2', 'phillip island', 'phillip island grand prix circuit', 'phillip island , victoria', '16 - 17 may', 'jim richards', 'volvo racing'], ['4 / 1', 'eastern creek', 'eastern creek raceway', 'sydney , new south wales', '6 - 7 jun', 'jim richards', 'volvo racing'], ['4 / 2', 'eastern creek', 'eastern creek raceway', 'sydney , new south wales', '6 - 7 jun', 'brad jones', 'brad jones racing'], ['5 / 1', 'lakeside', 'lakeside international raceway', 'brisbane , queensland', '27 - 28 jun', 'brad jones', 'brad jones racing'], ['5 / 2', 'lakeside', 'lakeside international raceway', 'brisbane , queensland', '27 - 28 jun', 'brad jones', 'brad jones racing'], ['6 / 1', 'mallala', 'mallala motorsport park', 'adelaide , south australia', '18 - 19 jul', 'brad jones', 'brad jones racing'], ['6 / 2', 'mallala', 'mallala motorsport park', 'adelaide , south australia', '18 - 19 jul', 'cameron mcconville', 'brad jones racing'], ['7 / 1', 'winton', 'winton motor raceway', 'benalla , victoria', '8 - 9 aug', 'cameron mcconville', 'brad jones racing'], ['7 / 2', 'winton', 'winton motor raceway', 'benalla , victoria', '8 - 9 aug', 'cameron mcconville', 'brad jones racing'], ['8 / 1', 'oran park', 'oran park raceway', 'sydney , new south wales', '29 - 30 aug', 'cameron mcconville', 'brad jones racing'], ['8 / 2', 'oran park', 'oran park raceway', 'sydney , new south wales', '29 - 30 aug', 'brad jones', 'brad jones racing']]
|
british records in athletics
|
https://en.wikipedia.org/wiki/British_records_in_athletics
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11070660-5.html.csv
|
unique
|
tony geal set only one british athletic record .
|
{'scope': 'all', 'row': '13', 'col': '3', 'col_other': 'n/a', 'criterion': 'equal', 'value': 'tony geal', 'subset': None}
|
{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'athlete', 'tony geal'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose athlete record fuzzily matches to tony geal .', 'tostr': 'filter_eq { all_rows ; athlete ; tony geal }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; athlete ; tony geal } } = true', 'tointer': 'select the rows whose athlete record fuzzily matches to tony geal . there is only one such row in the table .'}
|
only { filter_eq { all_rows ; athlete ; tony geal } } = true
|
select the rows whose athlete record fuzzily matches to tony geal . 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, 'athlete_4': 4, 'tony geal_5': 5}
|
{'only_1': 'only', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'athlete_4': 'athlete', 'tony geal_5': 'tony geal'}
|
{'only_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'athlete_4': [0], 'tony geal_5': [0]}
|
['event', 'data', 'athlete', 'date', 'place']
|
[['5 km', '19:29', 'andi drake', '27 may 1990', 'søfteland , norway'], ['5 miles', '32:38 +', 'ian mccombie', '23 march 1985', 'york , united kingdom'], ['10 km', '40:17', 'chris maddocks', '30 april 1989', 'burrator , united kingdom'], ['15 km', '1:01:11', 'steve barry', '24 june 1984', 'mézidon - canon , france'], ['10 miles', '1:06:15 +', 'steve barry', '26 february 1983', 'douglas , united kingdom'], ['20 km', '1:22:03', 'ian mccombie', '23 september 1988', 'seoul , south korea'], ['25 km', '1:46:16 +', 'ian mccombie', '27 april 1986', 'edinburgh , united kingdom'], ['30 km', '2:07:56', 'ian mccombie', '27 april 1986', 'edinburgh , united kingdom'], ['20 miles', '2:30:35', 'paul nihill', '12 june 1971', 'sheffield , united kingdom'], ['35 km', '2:36:19', 'chris maddocks', '29 june 1991', 'örnsköldsvik , sweden'], ['40 km', '3:02:55 +', 'chris maddocks', '28 october 1990', 'burrator , united kingdom'], ['50 km', '3:51:37', 'chris maddocks', '28 october 1990', 'burrator , united kingdom'], ['100 km', '9:34:25', 'tony geal', '2 june 1979', 'grand - quevilly , france'], ['24 hours', '219.570 km', 'derek harrison', '21 may 1978', 'rouen , france']]
|
mickey wright
|
https://en.wikipedia.org/wiki/Mickey_Wright
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1635463-1.html.csv
|
count
|
three of the championships took place in 1961 .
|
{'scope': 'all', 'criterion': 'equal', 'value': '1961', 'result': '3', 'col': '1', 'subset': None}
|
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'year', '1961'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose year record is equal to 1961 .', 'tostr': 'filter_eq { all_rows ; year ; 1961 }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; year ; 1961 } }', 'tointer': 'select the rows whose year record is equal to 1961 . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; year ; 1961 } } ; 3 } = true', 'tointer': 'select the rows whose year record is equal to 1961 . the number of such rows is 3 .'}
|
eq { count { filter_eq { all_rows ; year ; 1961 } } ; 3 } = true
|
select the rows whose year record is equal to 1961 . 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, 'year_5': 5, '1961_6': 6, '3_7': 7}
|
{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'year_5': 'year', '1961_6': '1961', '3_7': '3'}
|
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'year_5': [0], '1961_6': [0], '3_7': [2]}
|
['year', 'championship', 'winning score', 'margin', 'runner ( s ) - up']
|
[['1958', 'lpga championship', '+ 8 ( 69 + 69 + 76 + 74 = 288 )', '6 strokes', 'fay crocker'], ['1958', "us women 's open", '- 2 ( 74 + 72 + 70 + 74 = 290 )', '5 strokes', 'louise suggs'], ['1959', "us women 's open", '+ 7 ( 72 + 75 + 69 + 71 = 287 )', '2 strokes', 'louise suggs'], ['1960', 'lpga championship', '- 4 ( 71 + 76 + 74 + 71 = 292 )', '3 strokes', 'louise suggs'], ['1961', 'titleholders championship', '+ 11 ( 72 + 75 + 76 + 76 = 299 )', '1 stroke', 'patty berg , louise suggs'], ['1961', "us women 's open", '+ 5 ( 72 + 80 + 69 + 72 = 293 )', '6 strokes', 'betsy rawls'], ['1961', 'lpga championship', '+ 3 ( 67 + 77 + 72 + 71 = 287 )', '9 strokes', 'louise suggs'], ['1962', 'titleholders championship', '+ 7 ( 73 + 75 + 70 + 77 = 295 )', 'playoff 1', 'ruth jessen'], ['1962', "women 's western open", '+ 7 ( 69 + 74 + 76 + 76 = 295 )', 'playoff 2', 'mary lena faulk'], ['1963', "women 's western open", '- 4 ( 78 + 70 + 71 + 73 = 292 )', '9 strokes', 'kathy whitworth'], ['1963', 'lpga championship', '+ 10 ( 72 + 82 + 70 + 70 = 294 )', '2 strokes', 'mary lena faulk , mary mills , louise suggs'], ['1964', "us women 's open", '- 2 ( 71 + 71 + 75 + 73 = 290 )', 'playoff 3', 'ruth jessen'], ['1966', "women 's western open", '+ 2 ( 72 + 78 + 76 + 76 = 302 )', '1 stroke', 'jo ann prentice , margie masters']]
|
2008 - 09 scottish first division
|
https://en.wikipedia.org/wiki/2008%E2%80%9309_Scottish_First_Division
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14003085-5.html.csv
|
aggregation
|
the average attendance for all venues during the 2008-09 season was just over 2,500 .
|
{'scope': 'all', 'col': '6', 'type': 'average', 'result': '2530.6', 'subset': None}
|
{'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'average'], 'result': '2530.6', 'ind': 0, 'tostr': 'avg { all_rows ; average }'}, '2530.6'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; average } ; 2530.6 } = true', 'tointer': 'the average of the average record of all rows is 2530.6 .'}
|
round_eq { avg { all_rows ; average } ; 2530.6 } = true
|
the average of the average record of all rows is 2530.6 .
|
2
|
2
|
{'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'average_4': 4, '2530.6_5': 5}
|
{'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'average_4': 'average', '2530.6_5': '2530.6'}
|
{'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'average_4': [0], '2530.6_5': [1]}
|
['team', 'stadium', 'capacity', 'highest', 'lowest', 'average']
|
[['dundee', 'dens park', '11856', '6537', '2831', '3995'], ['st johnstone', 'mcdiarmid park', '10673', '7238', '2259', '3502'], ['dunfermline athletic', 'east end park', '11998', '4998', '1371', '3255'], ['partick thistle', 'firhill stadium', '10887', '3378', '2296', '2956'], ['queen of the south', 'palmerston park', '6412', '3339', '2029', '2720'], ['greenock morton', 'cappielow', '11612', '3323', '1685', '2279'], ['ross county', 'victoria park', '6310', '3444', '1625', '2279'], ['livingston', 'almondvale stadium', '10016', '2169', '1068', '1728'], ['airdrie united', 'new broomfield', '10171', '2165', '633', '1356'], ['clyde', 'broadwood stadium', '8006', '2114', '776', '1236']]
|
fencing at the 2010 summer youth olympics - mixed team
|
https://en.wikipedia.org/wiki/Fencing_at_the_2010_Summer_Youth_Olympics_%E2%80%93_Mixed_team
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-28372291-1.html.csv
|
aggregation
|
in the 2010 season the american fencer 's average rank is 6.58 .
|
{'scope': 'subset', 'col': '8', 'type': 'average', 'result': '6.58', 'subset': {'col': '1', 'criterion': 'fuzzily_match', 'value': 'america'}}
|
{'func': 'round_eq', 'args': [{'func': 'avg', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'team', 'america'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; team ; america }', 'tointer': 'select the rows whose team record fuzzily matches to america .'}, 'average fencers rank'], 'result': '6.58', 'ind': 1, 'tostr': 'avg { filter_eq { all_rows ; team ; america } ; average fencers rank }'}, '6.58'], 'result': True, 'ind': 2, 'tostr': 'round_eq { avg { filter_eq { all_rows ; team ; america } ; average fencers rank } ; 6.58 } = true', 'tointer': 'select the rows whose team record fuzzily matches to america . the average of the average fencers rank record of these rows is 6.58 .'}
|
round_eq { avg { filter_eq { all_rows ; team ; america } ; average fencers rank } ; 6.58 } = true
|
select the rows whose team record fuzzily matches to america . the average of the average fencers rank record of these rows is 6.58 .
|
3
|
3
|
{'eq_2': 2, 'result_3': 3, 'avg_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'team_5': 5, 'america_6': 6, 'average fencers rank_7': 7, '6.58_8': 8}
|
{'eq_2': 'eq', 'result_3': 'true', 'avg_1': 'avg', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'team_5': 'team', 'america_6': 'america', 'average fencers rank_7': 'average fencers rank', '6.58_8': '6.58'}
|
{'eq_2': [3], 'result_3': [], 'avg_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'team_5': [0], 'america_6': [0], 'average fencers rank_7': [1], '6.58_8': [2]}
|
['team', 'female épée', 'male épée', 'female foil', 'male foil', 'female saber', 'male saber', 'average fencers rank', 'initial team rank']
|
[['europe 1', 'santuccio alberta ( 2 ) ( ita )', 'fichera marco ( 1 ) ( ita )', 'mancini camilla ( 1 ) ( ita )', 'luperi edoardo ( 1 ) ( ita )', 'egoryan yana ( 1 ) ( rus )', 'affede leonardo ( 2 ) ( ita )', '1.33', '1'], ['europe 2', 'swatowska martyna ( 3 ) ( pol )', 'bodoczi nikolaus ( 2 ) ( ger )', 'alekseeva victoria ( 2 ) ( rus )', 'babaoglu tevfik burak ( 4 ) ( tur )', 'musch anja ( 3 ) ( ger )', 'hubers richard ( 3 ) ( ger )', '2.83', '2'], ['europe 3', 'bakhareva yulia ( 5 ) ( rus )', 'kruk tomasz ( 6 ) ( pol )', 'lupkovics dora ( 3 ) ( hun )', 'lichagin kirill ( 5 ) ( rus )', 'komaschuk alina ( 4 ) ( ukr )', 'akula mikhail ( 4 ) ( blr )', '4.5', '5'], ['europe 4', 'tataran amalia ( 7 ) ( rou )', 'ciovica lucian ( 7 ) ( rou )', 'cellerova michala ( 7 ) ( svk )', 'alexander choupenitch ( 6 ) ( cze )', 'boudad kenza ( 7 ) ( fra )', 'zatko arthur ( 5 ) ( fra )', '6.5', '6'], ['asia 1', 'lin sheng ( 1 ) ( chn )', 'na byeong hun ( 4 ) ( kor )', 'wong ye ying liane ( 6 ) ( sin )', 'lee kwang hyun ( 3 ) ( kor )', 'seo ji yeon ( 5 ) ( kor )', 'jong hun song ( 1 ) ( kor )', '4.33', '4'], ['asia 2', 'lee hye won ( 6 ) ( kor )', 'zhakupov kirill ( 5 ) ( kaz )', 'wang lianlian ( 8 ) ( chn )', 'choi nicholas edward ( 9 ) ( hkg )', 'wan yini ( 6 ) ( chn )', 'wang jackson ( 11 ) ( hkg )', '7.5', '7'], ['americas 1', 'holmes katharine ( 4 ) ( usa )', 'lyssov alexandre ( 3 ) ( can )', 'goldie allana ( 4 ) ( can )', 'massilas alexander ( 2 ) ( usa )', 'merza celina ( 2 ) ( usa )', 'spear will ( 6 ) ( usa )', '3.5', '3'], ['americas 2', 'di tella clara isabel ( 10 ) ( arg )', 'melargno guilherme ( 11 ) ( bra )', 'shaito mona ( 5 ) ( usa )', 'prades rosabal redys hanners ( 11 ) ( cub )', 'maria carreno ( 11 ) ( ven )', 'breult - mallette miguel ( 10 ) ( can )', '9.66', '8']]
|
list of tvb series ( 2009 )
|
https://en.wikipedia.org/wiki/List_of_TVB_series_%282009%29
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-19210674-1.html.csv
|
unique
|
for the tvb series in 2009 , the only episode with over 2.2 million viewers was the one titled beyond the realm of conscience .
|
{'scope': 'all', 'row': '1', 'col': '8', 'col_other': '2', 'criterion': 'greater_than', 'value': '2.20 million', 'subset': None}
|
{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'hk viewers', '2.20 million'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose hk viewers record is greater than 2.20 million .', 'tostr': 'filter_greater { all_rows ; hk viewers ; 2.20 million }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_greater { all_rows ; hk viewers ; 2.20 million } }', 'tointer': 'select the rows whose hk viewers record is greater than 2.20 million . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'hk viewers', '2.20 million'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose hk viewers record is greater than 2.20 million .', 'tostr': 'filter_greater { all_rows ; hk viewers ; 2.20 million }'}, 'english title'], 'result': 'beyond the realm of conscience', 'ind': 2, 'tostr': 'hop { filter_greater { all_rows ; hk viewers ; 2.20 million } ; english title }'}, 'beyond the realm of conscience'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_greater { all_rows ; hk viewers ; 2.20 million } ; english title } ; beyond the realm of conscience }', 'tointer': 'the english title record of this unqiue row is beyond the realm of conscience .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_greater { all_rows ; hk viewers ; 2.20 million } } ; eq { hop { filter_greater { all_rows ; hk viewers ; 2.20 million } ; english title } ; beyond the realm of conscience } } = true', 'tointer': 'select the rows whose hk viewers record is greater than 2.20 million . there is only one such row in the table . the english title record of this unqiue row is beyond the realm of conscience .'}
|
and { only { filter_greater { all_rows ; hk viewers ; 2.20 million } } ; eq { hop { filter_greater { all_rows ; hk viewers ; 2.20 million } ; english title } ; beyond the realm of conscience } } = true
|
select the rows whose hk viewers record is greater than 2.20 million . there is only one such row in the table . the english title record of this unqiue row is beyond the realm of conscience .
|
6
|
5
|
{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_greater_0': 0, 'all_rows_6': 6, 'hk viewers_7': 7, '2.20 million_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'english title_9': 9, 'beyond the realm of conscience_10': 10}
|
{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_greater_0': 'filter_greater', 'all_rows_6': 'all_rows', 'hk viewers_7': 'hk viewers', '2.20 million_8': '2.20 million', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'english title_9': 'english title', 'beyond the realm of conscience_10': 'beyond the realm of conscience'}
|
{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_greater_0': [1, 2], 'all_rows_6': [0], 'hk viewers_7': [0], '2.20 million_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'english title_9': [2], 'beyond the realm of conscience_10': [3]}
|
['rank', 'english title', 'chinese title', 'average', 'peak', 'premiere', 'finale', 'hk viewers']
|
[['1', 'beyond the realm of conscience', '宮心計', '35', '50', '33', '35', '2.26 million'], ['2', 'rosy business', '巾幗梟雄', '33', '47', '28', '39', '2.11 million'], ['3', 'burning flame iii', '烈火雄心3', '33', '38', '33', '34', '2.10 million'], ['4', "you 're hired", '絕代商驕', '32', '40', '31', '36', '2.05 million'], ['5', 'die again', '古靈精探b', '31', '38', '29', '33', '1.98 million'], ['6', 'eu', '學警狙擊', '30', '43', '29', '34', '1.92 million'], ['7', 'the threshold of a persona', 'id精英', '30', '41', '28', '32', '1.92 million'], ['8', 'a chip off the old block', '巴不得爸爸', '30', '37', '31', '28', '1.90 million'], ['9', 'a bride for a ride', '王老虎抢亲', '30', '34', '30', '31', '1.90 million']]
|
1989 san francisco 49ers season
|
https://en.wikipedia.org/wiki/1989_San_Francisco_49ers_season
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15521693-2.html.csv
|
majority
|
the 49ers won most of their games in the 1989 football season .
|
{'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': 'w', 'subset': None}
|
{'func': 'most_str_eq', 'args': ['all_rows', 'result', 'w'], 'result': True, 'ind': 0, 'tointer': 'for the result records of all rows , most of them fuzzily match to w .', 'tostr': 'most_eq { all_rows ; result ; w } = true'}
|
most_eq { all_rows ; result ; w } = true
|
for the result records of all rows , most of them fuzzily match to w .
|
1
|
1
|
{'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'result_3': 3, 'w_4': 4}
|
{'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'result_3': 'result', 'w_4': 'w'}
|
{'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'result_3': [0], 'w_4': [0]}
|
['week', 'date', 'opponent', 'result', 'tv time', 'attendance']
|
[['1', 'september 10 , 1989', 'indianapolis colts', 'w 30 - 24', 'cbs 10:00 am', '60111'], ['2', 'september 17 , 1989', 'tampa bay buccaneers', 'w 20 - 16', 'cbs 1:00 pm', '64087'], ['3', 'september 24 , 1989', 'philadelphia eagles', 'w 38 - 28', 'cbs 10:00 am', '66042'], ['4', 'october 1 , 1989', 'los angeles rams', 'l 13 - 12', 'cbs 1:00 pm', '64250'], ['5', 'october 8 , 1989', 'new orleans saints', 'w 24 - 20', 'cbs 10:00 am', '60488'], ['6', 'october 15 , 1989', 'dallas cowboys', 'w 31 - 14', 'cbs 10:00 am', '61077'], ['7', 'october 22 , 1989', 'new england patriots ( at stanford )', 'w 37 - 20', 'nbc 1:00 pm', '51781'], ['8', 'october 29 , 1989', 'new york jets', 'w 23 - 10', 'cbs 1:00 pm', '62805'], ['9', 'november 6 , 1989 ( mon )', 'new orleans saints', 'w 31 - 13', 'abc 6:00 pm', '60667'], ['10', 'november 12 , 1989', 'atlanta falcons', 'w 45 - 3', 'cbs 1:00 pm', '59914'], ['11', 'november 19 , 1989', 'green bay packers', 'l 21 - 17', 'cbs 1:00 pm', '62219'], ['12', 'november 27 , 1989 ( mon )', 'new york giants', 'w 34 - 24', 'abc 6:00 pm', '63461'], ['13', 'december 3 , 1989', 'atlanta falcons', 'w 23 - 10', 'cbs 10:00 am', '43128'], ['14', 'december 11 , 1989 ( mon )', 'los angeles rams', 'w 30 - 27', 'abc 6:00 pm', '67959'], ['15', 'december 17 , 1989', 'buffalo bills', 'w 23 - 10', 'nbc 1:00 pm', '60927'], ['16', 'december 24 , 1989', 'chicago bears', 'w 26 - 0', 'cbs 1:00 pm', '60207']]
|
1999 indianapolis colts season
|
https://en.wikipedia.org/wiki/1999_Indianapolis_Colts_season
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14901683-1.html.csv
|
count
|
in the 1999 indianapolis colts season , for games in december , there were two games at the rca dome .
|
{'scope': 'subset', 'criterion': 'equal', 'value': 'rca dome', 'result': '2', 'col': '6', 'subset': {'col': '2', 'criterion': 'fuzzily_match', 'value': 'december'}}
|
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', 'december'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; date ; december }', 'tointer': 'select the rows whose date record fuzzily matches to december .'}, 'game site', 'rca dome'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose date record fuzzily matches to december . among these rows , select the rows whose game site record fuzzily matches to rca dome .', 'tostr': 'filter_eq { filter_eq { all_rows ; date ; december } ; game site ; rca dome }'}], 'result': '2', 'ind': 2, 'tostr': 'count { filter_eq { filter_eq { all_rows ; date ; december } ; game site ; rca dome } }', 'tointer': 'select the rows whose date record fuzzily matches to december . among these rows , select the rows whose game site record fuzzily matches to rca dome . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_eq { filter_eq { all_rows ; date ; december } ; game site ; rca dome } } ; 2 } = true', 'tointer': 'select the rows whose date record fuzzily matches to december . among these rows , select the rows whose game site record fuzzily matches to rca dome . the number of such rows is 2 .'}
|
eq { count { filter_eq { filter_eq { all_rows ; date ; december } ; game site ; rca dome } } ; 2 } = true
|
select the rows whose date record fuzzily matches to december . among these rows , select the rows whose game site record fuzzily matches to rca dome . the number of such rows is 2 .
|
4
|
4
|
{'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_str_eq_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'date_6': 6, 'december_7': 7, 'game site_8': 8, 'rca dome_9': 9, '2_10': 10}
|
{'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_str_eq_1': 'filter_str_eq', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'date_6': 'date', 'december_7': 'december', 'game site_8': 'game site', 'rca dome_9': 'rca dome', '2_10': '2'}
|
{'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_str_eq_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'date_6': [0], 'december_7': [0], 'game site_8': [1], 'rca dome_9': [1], '2_10': [3]}
|
['week', 'date', 'opponent', 'result', 'record', 'game site', 'tv time', 'attendance']
|
[['1', 'september 12 , 1999', 'buffalo bills', 'w 31 - 14', '1 - 0', 'rca dome', 'cbs 1:00 pm', '56238'], ['2', 'september 19 , 1999', 'new england patriots', 'l 28 - 31', '1 - 1', 'foxboro stadium', 'cbs 1:00 pm', '59640'], ['3', 'september 26 , 1999', 'san diego chargers', 'w 27 - 19', '2 - 1', 'qualcomm stadium', 'cbs 4:15 pm', '56942'], ['4', '-', '-', '-', '-', '-', '-', ''], ['5', 'october 10 , 1999', 'miami dolphins', 'l 31 - 34', '2 - 2', 'rca dome', 'cbs 1:00 pm', '56810'], ['6', 'october 17 , 1999', 'new york jets', 'w 16 - 13', '3 - 2', 'the meadowlands', 'cbs 1:00 pm', '78112'], ['7', 'october 24 , 1999', 'cincinnati bengals', 'w 31 - 10', '4 - 2', 'rca dome', 'cbs 1:00 pm', '55996'], ['8', 'october 31 , 1999', 'dallas cowboys', 'w 34 - 24', '5 - 2', 'rca dome', 'fox 4:15 pm', '56860'], ['9', 'november 7 , 1999', 'kansas city chiefs', 'w 25 - 17', '6 - 2', 'rca dome', 'cbs 1:00 pm', '56689'], ['10', 'november 14 , 1999', 'new york giants', 'w 27 - 19', '7 - 2', 'giants stadium', 'cbs 1:00 pm', '78081'], ['11', 'november 21 , 1999', 'philadelphia eagles', 'w 44 - 17', '8 - 2', 'veterans stadium', 'cbs 1:00 pm', '65521'], ['12', 'november 28 , 1999', 'new york jets', 'w 13 - 6', '9 - 2', 'rca dome', 'cbs 4:15 pm', '56689'], ['13', 'december 5 , 1999', 'miami dolphins', 'w 37 - 34', '10 - 2', 'pro player stadium', 'cbs 1:00 pm', '74096'], ['14', 'december 12 , 1999', 'new england patriots', 'w 20 - 15', '11 - 2', 'rca dome', 'cbs 1:00 pm', '56975'], ['15', 'december 19 , 1999', 'washington redskins', 'w 24 - 21', '12 - 2', 'rca dome', 'fox 1:00 pm', '57013'], ['16', 'december 26 , 1999', 'cleveland browns', 'w 29 - 28', '13 - 2', 'cleveland browns stadium', 'cbs 1:00 pm', '72618'], ['17', 'january 2 , 2000', 'buffalo bills', 'l 6 - 31', '13 - 3', 'ralph wilson stadium', 'cbs 1:00 pm', '61959']]
|
2007 - 08 chicago bulls season
|
https://en.wikipedia.org/wiki/2007%E2%80%9308_Chicago_Bulls_season
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-11960610-10.html.csv
|
aggregation
|
during march of 2008 , hinrich averaged 7.8 assists in games in which he lead the bulls in the category .
|
{'scope': 'subset', 'col': '7', 'type': 'average', 'result': '7.8', 'subset': {'col': '7', 'criterion': 'fuzzily_match', 'value': 'hinrich'}}
|
{'func': 'round_eq', 'args': [{'func': 'avg', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'high assists', 'hinrich'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; high assists ; hinrich }', 'tointer': 'select the rows whose high assists record fuzzily matches to hinrich .'}, 'high assists'], 'result': '7.8', 'ind': 1, 'tostr': 'avg { filter_eq { all_rows ; high assists ; hinrich } ; high assists }'}, '7.8'], 'result': True, 'ind': 2, 'tostr': 'round_eq { avg { filter_eq { all_rows ; high assists ; hinrich } ; high assists } ; 7.8 } = true', 'tointer': 'select the rows whose high assists record fuzzily matches to hinrich . the average of the high assists record of these rows is 7.8 .'}
|
round_eq { avg { filter_eq { all_rows ; high assists ; hinrich } ; high assists } ; 7.8 } = true
|
select the rows whose high assists record fuzzily matches to hinrich . the average of the high assists record of these rows is 7.8 .
|
3
|
3
|
{'eq_2': 2, 'result_3': 3, 'avg_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'high assists_5': 5, 'hinrich_6': 6, 'high assists_7': 7, '7.8_8': 8}
|
{'eq_2': 'eq', 'result_3': 'true', 'avg_1': 'avg', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'high assists_5': 'high assists', 'hinrich_6': 'hinrich', 'high assists_7': 'high assists', '7.8_8': '7.8'}
|
{'eq_2': [3], 'result_3': [], 'avg_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'high assists_5': [0], 'hinrich_6': [0], 'high assists_7': [1], '7.8_8': [2]}
|
['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record']
|
[['59', 'march 2', 'cleveland', '86 - 95', 'hughes ( 23 )', 'gooden ( 10 )', 'hughes ( 4 )', 'quicken loans arena 20562', '23 - 36'], ['60', 'march 4', 'memphis', '112 - 97', 'deng , gooden ( 21 )', 'gooden ( 14 )', 'hinrich ( 12 )', 'united center 21725', '24 - 36'], ['61', 'march 6', 'cleveland', '107 - 96', 'deng , gordon ( 23 )', 'noah ( 20 )', 'hinrich ( 7 )', 'united center 22097', '25 - 36'], ['62', 'march 7', 'boston', '93 - 116', 'gordon ( 20 )', 'gray ( 8 )', 'gordon ( 4 )', 'td banknorth garden 18624', '25 - 37'], ['63', 'march 9', 'detroit', '109 - 116', 'gordon ( 27 )', 'gooden ( 8 )', 'hughes ( 5 )', 'palace of auburn hills 22076', '25 - 38'], ['64', 'march 11', 'utah', '108 - 96', 'gooden ( 24 )', 'gooden ( 10 )', 'hinrich ( 6 )', 'united center 21969', '26 - 38'], ['65', 'march 14', 'philadelphia', '106 - 110', 'deng ( 21 )', 'gooden ( 9 )', 'hinrich ( 6 )', 'united center 22069', '26 - 39'], ['66', 'march 17', 'new orleans', '97 - 108', 'gordon ( 31 )', 'gooden ( 12 )', 'hinrich ( 5 )', 'new orleans arena 14337', '26 - 40'], ['67', 'march 18', 'new jersey', '112 - 96', 'deng ( 20 )', 'gooden ( 11 )', 'hinrich ( 8 )', 'united center 22070', '27 - 40'], ['68', 'march 20', 'san antonio', '80 - 102', 'deng ( 18 )', 'gordon ( 8 )', 'gordon ( 3 )', 'united center 22353', '27 - 41'], ['69', 'march 22', 'indiana', '101 - 108', 'deng ( 28 )', 'gooden , hughes ( 10 )', 'hinrich ( 10 )', 'united center 21752', '27 - 42'], ['70', 'march 25', 'atlanta', '103 - 94', 'gooden ( 31 )', 'gooden ( 16 )', 'hinrich ( 10 )', 'united center 21806', '28 - 42'], ['71', 'march 26', 'philadelphia', '99 - 121', 'sefolosha ( 20 )', 'gooden ( 8 )', 'hinrich ( 6 )', 'wachovia center 18620', '28 - 43'], ['72', 'march 28', 'atlanta', '103 - 106', 'deng ( 19 )', 'noah ( 7 )', 'hinrich ( 8 )', 'philips arena 17223', '28 - 44']]
|
athletics at the 2008 summer olympics - men 's 400 metres
|
https://en.wikipedia.org/wiki/Athletics_at_the_2008_Summer_Olympics_%E2%80%93_Men%27s_400_metres
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18569105-7.html.csv
|
aggregation
|
the average reaction time for all athletes in the men 's 400 metres is 0.236 .
|
{'scope': 'all', 'col': '6', 'type': 'average', 'result': '0.236', 'subset': None}
|
{'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'react'], 'result': '0.236', 'ind': 0, 'tostr': 'avg { all_rows ; react }'}, '0.236'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; react } ; 0.236 } = true', 'tointer': 'the average of the react record of all rows is 0.236 .'}
|
round_eq { avg { all_rows ; react } ; 0.236 } = true
|
the average of the react record of all rows is 0.236 .
|
2
|
2
|
{'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'react_4': 4, '0.236_5': 5}
|
{'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'react_4': 'react', '0.236_5': '0.236'}
|
{'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'react_4': [0], '0.236_5': [1]}
|
['rank', 'lane', 'athlete', 'nationality', 'time', 'react']
|
[['1', '7', 'andrew steele', 'great britain', '44.94', '0.248'], ['2', '5', 'renny quow', 'trinidad and tobago', '45.13', '0.266'], ['3', '6', 'michael mathieu', 'bahamas', '45.17', '0.193'], ['4', '8', 'michael blackwood', 'jamaica', '45.56', '0.204'], ['5', '2', 'tyler christopher', 'canada', '45.67', '0.172'], ['6', '3', 'joel phillip', 'grenada', '46.30', '0.198'], ['7', '9', 'félix martinez', 'puerto rico', '46.46', '0.347'], ['8', '4', 'daniel dąbrowski', 'poland', '47.83', '0.260']]
|
campbeltown and machrihanish light railway
|
https://en.wikipedia.org/wiki/Campbeltown_and_Machrihanish_Light_Railway
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1820430-1.html.csv
|
majority
|
the majority of the railways were built by andrew barclay & co .
|
{'scope': 'all', 'col': '2', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'andrew barclay & co', 'subset': None}
|
{'func': 'most_str_eq', 'args': ['all_rows', 'builder', 'andrew barclay & co'], 'result': True, 'ind': 0, 'tointer': 'for the builder records of all rows , most of them fuzzily match to andrew barclay & co .', 'tostr': 'most_eq { all_rows ; builder ; andrew barclay & co } = true'}
|
most_eq { all_rows ; builder ; andrew barclay & co } = true
|
for the builder records of all rows , most of them fuzzily match to andrew barclay & co .
|
1
|
1
|
{'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'builder_3': 3, 'andrew barclay & co_4': 4}
|
{'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'builder_3': 'builder', 'andrew barclay & co_4': 'andrew barclay & co'}
|
{'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'builder_3': [0], 'andrew barclay & co_4': [0]}
|
['name', 'builder', 'type', 'works number', 'built']
|
[['pioneer', 'andrew barclay & co', '0 - 4 - 0 wt ( converted to 0 - 4 - 2 wt )', 'unknown', '1876'], ['chevalier', 'andrew barclay & co', '0 - 4 - 0 st ( converted to 0 - 4 - 2 st )', '269', '1885'], ['princess', 'kerr stuart', '0 - 4 - 2 t', '717', '1900'], ['argyll', 'andrew barclay & co', '0 - 6 - 2 t', '1049', '1906'], ['atlantic', 'andrew barclay & co', '0 - 6 - 2 t', '1098', '1907']]
|
united states house of representatives elections , 1824
|
https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1824
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2668264-8.html.csv
|
comparative
|
david trimble has a first elected year which is earlier than that of thomas p moore .
|
{'row_1': '1', 'row_2': '5', 'col': '4', 'col_other': '2', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None}
|
{'func': 'less', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'incumbent', 'david trimble'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose incumbent record fuzzily matches to david trimble .', 'tostr': 'filter_eq { all_rows ; incumbent ; david trimble }'}, 'first elected'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; incumbent ; david trimble } ; first elected }', 'tointer': 'select the rows whose incumbent record fuzzily matches to david trimble . take the first elected record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'incumbent', 'thomas p moore'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose incumbent record fuzzily matches to thomas p moore .', 'tostr': 'filter_eq { all_rows ; incumbent ; thomas p moore }'}, 'first elected'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; incumbent ; thomas p moore } ; first elected }', 'tointer': 'select the rows whose incumbent record fuzzily matches to thomas p moore . take the first elected record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; incumbent ; david trimble } ; first elected } ; hop { filter_eq { all_rows ; incumbent ; thomas p moore } ; first elected } } = true', 'tointer': 'select the rows whose incumbent record fuzzily matches to david trimble . take the first elected record of this row . select the rows whose incumbent record fuzzily matches to thomas p moore . take the first elected record of this row . the first record is less than the second record .'}
|
less { hop { filter_eq { all_rows ; incumbent ; david trimble } ; first elected } ; hop { filter_eq { all_rows ; incumbent ; thomas p moore } ; first elected } } = true
|
select the rows whose incumbent record fuzzily matches to david trimble . take the first elected record of this row . select the rows whose incumbent record fuzzily matches to thomas p moore . take the first elected record of this row . the first record is less than the second record .
|
5
|
5
|
{'less_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'incumbent_7': 7, 'david trimble_8': 8, 'first elected_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'incumbent_11': 11, 'thomas p moore_12': 12, 'first elected_13': 13}
|
{'less_4': 'less', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'incumbent_7': 'incumbent', 'david trimble_8': 'david trimble', 'first elected_9': 'first elected', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'incumbent_11': 'incumbent', 'thomas p moore_12': 'thomas p moore', 'first elected_13': 'first elected'}
|
{'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'incumbent_7': [0], 'david trimble_8': [0], 'first elected_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'incumbent_11': [1], 'thomas p moore_12': [1], 'first elected_13': [3]}
|
['district', 'incumbent', 'party', 'first elected', 'result', 'candidates']
|
[['kentucky 1', 'david trimble', 'adams - clay republican', '1816', 're - elected', 'david trimble ( a )'], ['kentucky 3', 'henry clay', 'adams - clay republican', '1810 1822', 're - elected', 'henry clay ( a ) 100 %'], ['kentucky 4', 'robert p letcher', 'adams - clay republican', '1822', 're - elected', 'robert p letcher ( a ) 60.1 % john speed smith 39.9 %'], ['kentucky 6', 'david white', 'adams - clay republican', '1822', 'retired jacksonian gain', 'joseph lecompte ( j ) john logan'], ['kentucky 7', 'thomas p moore', 'jacksonian republican', '1822', 're - elected', 'thomas p moore ( j ) samuel woodson']]
|
list of town tramway systems in the netherlands
|
https://en.wikipedia.org/wiki/List_of_town_tramway_systems_in_the_Netherlands
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12562214-1.html.csv
|
majority
|
the majority of town tramway systems in the netherlands had initially horse drawn systems .
|
{'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'horse', 'subset': None}
|
{'func': 'most_str_eq', 'args': ['all_rows', 'traction type', 'horse'], 'result': True, 'ind': 0, 'tointer': 'for the traction type records of all rows , most of them fuzzily match to horse .', 'tostr': 'most_eq { all_rows ; traction type ; horse } = true'}
|
most_eq { all_rows ; traction type ; horse } = true
|
for the traction type records of all rows , most of them fuzzily match to horse .
|
1
|
1
|
{'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'traction type_3': 3, 'horse_4': 4}
|
{'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'traction type_3': 'traction type', 'horse_4': 'horse'}
|
{'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'traction type_3': [0], 'horse_4': [0]}
|
['name of system', 'location', 'traction type', 'date ( from )', 'date ( to )']
|
[['atm ( 1897 - 1917 ) gta ( 1919 - 1922 )', 'apeldoorn', 'horse', '12 august 1897', '11 november 1917'], ['atm ( 1897 - 1917 ) gta ( 1919 - 1922 )', 'apeldoorn', 'petrol ( gasoline )', '5 june 1919', '8 october 1922'], ['atm ( 1880 - 1911 ) geta ( 1911 - 1944 )', 'arnhem', 'horse', '3 may 1880', '12 june 1912'], ['atm ( 1880 - 1911 ) geta ( 1911 - 1944 )', 'arnhem', 'electric', '21 may 1911', '17 september 1944'], ['hsm ( 1883 - 1910 ) gt ( 1915 - 1922 )', 'groenlo', 'steam', '29 may 1883', '31 december 1910'], ['hsm ( 1883 - 1910 ) gt ( 1915 - 1922 )', 'groenlo', 'petrol ( gasoline )', '6 august 1915', 'oct 1922'], ['hsm ( 1883 - 1910 ) gt ( 1915 - 1922 )', 'groenlo', 'horse', '1917', '1919'], ['ntm ( 1889 - 1912 ) m & w ( 1912 - 1921 ) gtn ( 1911 - 1955 )', 'nijmegen', 'horse', '1889', '1911'], ['ntm ( 1889 - 1912 ) m & w ( 1912 - 1921 ) gtn ( 1911 - 1955 )', 'nijmegen', 'steam', '30 june 1889', '31 december 1921'], ['ntm ( 1889 - 1912 ) m & w ( 1912 - 1921 ) gtn ( 1911 - 1955 )', 'nijmegen', 'electric', '4 june 1911', '20 november 1955'], ['gtz', 'zaltbommel', 'horse', '14 march 1910', '31 august 1923'], ['ztm', 'zutphen', 'horse', '16 may 1889', '29 january 1904']]
|
double trap
|
https://en.wikipedia.org/wiki/Double_trap
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1354148-3.html.csv
|
count
|
satu pusila won a total of three gold medals in the double trap events .
|
{'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'satu pusila', 'result': '3', 'col': '3', 'subset': None}
|
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'gold', 'satu pusila'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose gold record fuzzily matches to satu pusila .', 'tostr': 'filter_eq { all_rows ; gold ; satu pusila }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; gold ; satu pusila } }', 'tointer': 'select the rows whose gold record fuzzily matches to satu pusila . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; gold ; satu pusila } } ; 3 } = true', 'tointer': 'select the rows whose gold record fuzzily matches to satu pusila . the number of such rows is 3 .'}
|
eq { count { filter_eq { all_rows ; gold ; satu pusila } } ; 3 } = true
|
select the rows whose gold record fuzzily matches to satu pusila . 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, 'gold_5': 5, 'satu pusila_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', 'gold_5': 'gold', 'satu pusila_6': 'satu pusila', '3_7': '3'}
|
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'gold_5': [0], 'satu pusila_6': [0], '3_7': [2]}
|
['year', 'place', 'gold', 'silver', 'bronze']
|
[['1989', 'montecatini terme', 'roberta morara ( ita )', 'roberta pelosi ( ita )', 'anna maria bianchi ( ita )'], ['1990', 'moscow', 'satu pusila ( fin )', 'elena shishirina ( urs )', 'audrey grosch ( usa )'], ['1991', 'perth', 'satu pusila ( fin )', 'elena tkach ( urs )', 'deena julin ( usa )'], ['1993', 'barcelona', 'frances strodtman ( usa )', 'deena julin ( usa )', 'anna maria di giovanni ( ita )'], ['1994', 'fagnano', 'satu pusila ( fin )', 'elena shishirina ( rus )', 'svetlana demina ( rus )'], ['1995', 'nicosia', 'deborah gelisio ( ita )', 'gema usieto ( esp )', 'xiang xu ( chn )'], ['1997', 'lima', 'deborah gelisio ( ita )', 'cynthia meyer ( can )', 'riitta - mari murtoniemi ( fin )'], ['1998', 'barcelona', 'deborah gelisio ( ita )', 'kimberly rhode ( usa )', 'cindy gentry ( usa )'], ['1999', 'tampere', 'pia julin ( fin )', 'pia hansen ( swe )', 'yoshiko miura ( jpn )'], ['2001', 'cairo', 'yafei zhang ( chn )', 'yi chun lin ( tpe )', 'qingnian li ( chn )'], ['2002', 'lahti', 'yi chun lin ( tpe )', 'jing lin wang ( chn )', 'hye kyoung son ( kor )'], ['2003', 'nicosia', 'marã\xada quintanal ( esp )', 'fang chen ( chn )', 'jing lin wang ( chn )'], ['2005', 'lonato', 'jing lin wang ( chn )', 'qingnian li ( chn )', 'monica girotto ( ita )'], ['2006', 'zagreb', 'hye kyoung son ( kor )', 'yuxiang li ( chn )', 'bo na lee ( kor )']]
|
1965 american football league draft
|
https://en.wikipedia.org/wiki/1965_American_Football_League_Draft
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18652198-4.html.csv
|
count
|
between the 25th and 32nd picks of the 1965 afl draft , two quarterbacks were picked .
|
{'scope': 'all', 'criterion': 'equal', 'value': 'quarterback', 'result': '2', 'col': '4', 'subset': None}
|
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'position', 'quarterback'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose position record fuzzily matches to quarterback .', 'tostr': 'filter_eq { all_rows ; position ; quarterback }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; position ; quarterback } }', 'tointer': 'select the rows whose position record fuzzily matches to quarterback . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; position ; quarterback } } ; 2 } = true', 'tointer': 'select the rows whose position record fuzzily matches to quarterback . the number of such rows is 2 .'}
|
eq { count { filter_eq { all_rows ; position ; quarterback } } ; 2 } = true
|
select the rows whose position record fuzzily matches to quarterback . 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, 'position_5': 5, 'quarterback_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', 'position_5': 'position', 'quarterback_6': 'quarterback', '2_7': '2'}
|
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'position_5': [0], 'quarterback_6': [0], '2_7': [2]}
|
['pick', 'team', 'player', 'position', 'college']
|
[['25', 'denver broncos', 'george donnelly', 'defensive back', 'illinois'], ['26', 'houston oilers', 'bobby maples', 'center', 'baylor'], ['27', 'oakland raiders', 'gus otto', 'linebacker', 'missouri'], ['28', 'new york jets', 'bob schweickert', 'quarterback', 'virginia tech'], ['29', 'kansas city chiefs', 'otis taylor', 'linebacker', 'prairie view a & m'], ['30', 'san diego chargers', 'steve tensi', 'quarterback', 'florida state'], ['31', 'boston patriots', 'ellis johnson', 'halfback', 'southeastern louisiana'], ['32', 'kansas city chiefs ( from buffalo bills )', 'frank pitts', 'wide receiver', 'saginaw valley state']]
|
list of longest suspension bridge spans
|
https://en.wikipedia.org/wiki/List_of_longest_suspension_bridge_spans
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1604842-2.html.csv
|
ordinal
|
izmit bay bridge was the last bridge to open on the list of longest suspension bridge spans .
|
{'row': '1', 'col': '4', 'order': '1', 'col_other': '1', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None}
|
{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'year to open', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; year to open ; 1 }'}, 'name'], 'result': 'izmit bay bridge', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; year to open ; 1 } ; name }'}, 'izmit bay bridge'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; year to open ; 1 } ; name } ; izmit bay bridge } = true', 'tointer': 'select the row whose year to open record of all rows is 1st maximum . the name record of this row is izmit bay bridge .'}
|
eq { hop { nth_argmax { all_rows ; year to open ; 1 } ; name } ; izmit bay bridge } = true
|
select the row whose year to open record of all rows is 1st maximum . the name record of this row is izmit bay bridge .
|
3
|
3
|
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'year to open_5': 5, '1_6': 6, 'name_7': 7, 'izmit bay bridge_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', 'year to open_5': 'year to open', '1_6': '1', 'name_7': 'name', 'izmit bay bridge_8': 'izmit bay bridge'}
|
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'year to open_5': [0], '1_6': [0], 'name_7': [1], 'izmit bay bridge_8': [2]}
|
['name', 'main span metres', 'main span feet', 'year to open', 'country']
|
[['izmit bay bridge', '1550', '5085', '2017', 'turkey'], ['yavuz sultan selim bridge', '1408', '4619', '2015', 'turkey'], ['longjiang river bridge', '1196', '3924', '2015', 'china'], ['longmen bridge ( guangxi )', '1160', '3806', '2016', 'china'], ['ulsan bridge', '1150', '3773', '2014', 'south korea'], ['hålogaland bridge', '1145', '3757', '2017', 'norway'], ["ma'anshan bridge", '1080 ( x2 )', '3543 ( x2 )', '2013', 'china'], ['second namhae bridge', '890', '2920', '2016', 'south korea'], ['cuntan bridge', '880', '2887', '2016', 'china'], ['lishui bridge', '856', '2808', '2013', 'china'], ['jeokgeum bridge', '850', '2790', '2013', 'south korea'], ['yingwuzhou bridge', '850 ( x2 )', '2790 ( x2 )', '2015', 'china'], ['qincaobei bridge', '788', '2585', '2013', 'china'], ['puli bridge', '628', '2060', '2015', 'china'], ['dimuhe river bridge', '538', '1765', '2015', 'china'], ['taohuayu yellow river bridge', '406', '1332', '2013', 'china'], ['dandeung bridge', '400', '1312', '2014', 'south korea']]
|
list of big brother ( uk ) shows
|
https://en.wikipedia.org/wiki/List_of_Big_Brother_%28UK%29_shows
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-11748792-2.html.csv
|
count
|
there are 7 series of the big brother ( uk ) shows .
|
{'scope': 'all', 'criterion': 'all', 'value': 'n/a', 'result': '7', 'col': '1', 'subset': None}
|
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_all', 'args': ['all_rows', 'series'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose series record is arbitrary .', 'tostr': 'filter_all { all_rows ; series }'}], 'result': '7', 'ind': 1, 'tostr': 'count { filter_all { all_rows ; series } }', 'tointer': 'select the rows whose series record is arbitrary . the number of such rows is 7 .'}, '7'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_all { all_rows ; series } } ; 7 } = true', 'tointer': 'select the rows whose series record is arbitrary . the number of such rows is 7 .'}
|
eq { count { filter_all { all_rows ; series } } ; 7 } = true
|
select the rows whose series record is arbitrary . the number of such rows is 7 .
|
3
|
3
|
{'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_all_0': 0, 'all_rows_4': 4, 'series_5': 5, '7_6': 6}
|
{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_all_0': 'filter_all', 'all_rows_4': 'all_rows', 'series_5': 'series', '7_6': '7'}
|
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_all_0': [1], 'all_rows_4': [0], 'series_5': [0], '7_6': [2]}
|
['series', 'monday', 'tuesday', 'wednesday', 'thursday', 'friday', 'saturday', 'sunday']
|
[['celebrity big brother 8', 'emma willis jamie east', 'emma willis', 'emma willis', 'emma willis', 'emma willis jamie east', 'alice levine jamie east', 'alice levine jamie east'], ['big brother 12', 'emma willis jamie east', 'emma willis', 'emma willis', 'emma willis', 'emma willis jamie east', 'alice levine jamie east', 'alice levine jamie east'], ['celebrity big brother 9', 'emma willis jamie east', 'emma willis', 'emma willis', 'emma willis', 'emma willis jamie east', 'alice levine jamie east', 'alice levine jamie east'], ['big brother 13', 'emma willis jamie east', 'emma willis', 'emma willis', 'emma willis', 'emma willis jamie east', 'alice levine jamie east', 'alice levine jamie east'], ['celebrity big brother 10', 'emma willis jamie east', 'emma willis', 'emma willis', 'emma willis', 'emma willis jamie east', 'alice levine jamie east', 'alice levine jamie east'], ['celebrity big brother 11', 'emma willis jamie east', 'emma willis', 'emma willis', 'emma willis', 'emma willis jamie east', 'alice levine jamie east', 'alice levine jamie east'], ['big brother 14', 'aj odudu rylan clark', 'emma willis', 'emma willis', 'emma willis', 'aj odudu rylan clark', 'aj odudu iain lee', 'rylan clark']]
|
list of reality television show franchises
|
https://en.wikipedia.org/wiki/List_of_reality_television_show_franchises
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-24224647-2.html.csv
|
count
|
three clash of the choirs franchisees premiered in 2010 .
|
{'scope': 'all', 'criterion': 'equal', 'value': '2010', 'result': '3', 'col': '5', 'subset': None}
|
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'year premiered', '2010'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose year premiered record is equal to 2010 .', 'tostr': 'filter_eq { all_rows ; year premiered ; 2010 }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; year premiered ; 2010 } }', 'tointer': 'select the rows whose year premiered record is equal to 2010 . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; year premiered ; 2010 } } ; 3 } = true', 'tointer': 'select the rows whose year premiered record is equal to 2010 . the number of such rows is 3 .'}
|
eq { count { filter_eq { all_rows ; year premiered ; 2010 } } ; 3 } = true
|
select the rows whose year premiered record is equal to 2010 . 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, 'year premiered_5': 5, '2010_6': 6, '3_7': 7}
|
{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'year premiered_5': 'year premiered', '2010_6': '2010', '3_7': '3'}
|
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'year premiered_5': [0], '2010_6': [0], '3_7': [2]}
|
['region / country', 'local name', 'main presenter', 'network', 'year premiered']
|
[['china', '夢想合唱團 mengxiang hechang tuan', 'sa beining', 'cctv - 1', '2011'], ['denmark', 'allstars', 'lisbeth østergaard', 'tv2', '2008'], ['estonia', 'laululahing', 'tarmo leinatamm', 'etv', '2008'], ['finland', 'kuorosota', 'kristiina komulainen', 'nelonen', '2009'], ['france', 'la bataille des chorales', 'benjamin castaldi', 'tf1', '2009'], ['latvia', 'koru kari', 'lauris reiniks', 'tv3', '2008'], ['lithuania', 'chorų karai', 'vytautas šapranauskas & jurgita jurkutė', 'tv3', '2010'], ['norway', 'det store korslaget', 'øyvind mund', 'tv2', '2009'], ['poland', 'bitwa na glosy', 'hubert urbanski & piotr kedzierski', 'tvp 2', '2010'], ['russia', 'битва хоров', 'valery meladze', 'rossiya 1', '2012'], ['spain', 'la batalla de los coros', 'josep lobató', 'cuatro', '2008'], ['sweden', 'körslaget', 'gry forssell', 'tv4', '2008'], ['switzerland', 'kampf der chöre', 'sven epiney', 'sf 1', '2010'], ['turkey', 'korolar çarpışıyor', 'behzat uighur', 'show tv', '2009'], ['vietnam', 'hợp ca tranh tài', 'nguyên khang', 'vtv3', '2012']]
|
ministry of housing and construction
|
https://en.wikipedia.org/wiki/Ministry_of_Housing_and_Construction
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18921615-2.html.csv
|
superlative
|
eli ben - menachem is the newest member of the ministry of housing and consutrction , with his term starting in 2005 .
|
{'scope': 'all', 'col_superlative': '4', 'row_superlative': '9', 'value_mentioned': 'yes', 'max_or_min': 'max', 'other_col': '1', 'subset': None}
|
{'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'max', 'args': ['all_rows', 'term start'], 'result': '11 january 2005', 'ind': 0, 'tostr': 'max { all_rows ; term start }', 'tointer': 'the maximum term start record of all rows is 11 january 2005 .'}, '11 january 2005'], 'result': True, 'ind': 1, 'tostr': 'eq { max { all_rows ; term start } ; 11 january 2005 }', 'tointer': 'the maximum term start record of all rows is 11 january 2005 .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'term start'], 'result': None, 'ind': 2, 'tostr': 'argmax { all_rows ; term start }'}, 'minister'], 'result': 'eli ben - menachem', 'ind': 3, 'tostr': 'hop { argmax { all_rows ; term start } ; minister }'}, 'eli ben - menachem'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { argmax { all_rows ; term start } ; minister } ; eli ben - menachem }', 'tointer': 'the minister record of the row with superlative term start record is eli ben - menachem .'}], 'result': True, 'ind': 5, 'tostr': 'and { eq { max { all_rows ; term start } ; 11 january 2005 } ; eq { hop { argmax { all_rows ; term start } ; minister } ; eli ben - menachem } } = true', 'tointer': 'the maximum term start record of all rows is 11 january 2005 . the minister record of the row with superlative term start record is eli ben - menachem .'}
|
and { eq { max { all_rows ; term start } ; 11 january 2005 } ; eq { hop { argmax { all_rows ; term start } ; minister } ; eli ben - menachem } } = true
|
the maximum term start record of all rows is 11 january 2005 . the minister record of the row with superlative term start record is eli ben - menachem .
|
6
|
6
|
{'and_5': 5, 'result_6': 6, 'eq_1': 1, 'max_0': 0, 'all_rows_7': 7, 'term start_8': 8, '11 january 2005_9': 9, 'str_eq_4': 4, 'str_hop_3': 3, 'argmax_2': 2, 'all_rows_10': 10, 'term start_11': 11, 'minister_12': 12, 'eli ben - menachem_13': 13}
|
{'and_5': 'and', 'result_6': 'true', 'eq_1': 'eq', 'max_0': 'max', 'all_rows_7': 'all_rows', 'term start_8': 'term start', '11 january 2005_9': '11 january 2005', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'argmax_2': 'argmax', 'all_rows_10': 'all_rows', 'term start_11': 'term start', 'minister_12': 'minister', 'eli ben - menachem_13': 'eli ben - menachem'}
|
{'and_5': [6], 'result_6': [], 'eq_1': [5], 'max_0': [1], 'all_rows_7': [0], 'term start_8': [0], '11 january 2005_9': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'argmax_2': [3], 'all_rows_10': [2], 'term start_11': [2], 'minister_12': [3], 'eli ben - menachem_13': [4]}
|
['minister', 'party', 'governments', 'term start', 'term end']
|
[['moshe katsav', 'likud', '20', '10 october 1983', '13 september 1984'], ['avraham ravitz', 'degel hatorah', '24', '25 june 1990', '13 july 1992'], ['aryeh gamliel', 'shas', '25', '29 july 1992', '9 september 1993'], ['ran cohen', 'meretz', '25', '4 august 1992', '31 december 1992'], ['eli ben - menachem', 'labor party', '25 , 26', '8 april 1993', '18 june 1996'], ['alex goldfarb', 'yiud , atid', '25 , 26', '2 january 1995', '18 june 1996'], ['meir porush', 'united torah judaism', '27', '24 june 1996', '6 july 1999'], ['meir porush', 'united torah judaism', '29', '4 june 2001', '28 february 2003'], ['eli ben - menachem', 'labor party', '30', '11 january 2005', '23 november 2005']]
|
1944 in brazilian football
|
https://en.wikipedia.org/wiki/1944_in_Brazilian_football
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15331540-1.html.csv
|
comparative
|
juventus had a higher goals against than corinthains in the 1944 brazilian football season .
|
{'row_1': '7', 'row_2': '3', 'col': '7', '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', 'team', 'juventus'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose team record fuzzily matches to juventus .', 'tostr': 'filter_eq { all_rows ; team ; juventus }'}, 'against'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; team ; juventus } ; against }', 'tointer': 'select the rows whose team record fuzzily matches to juventus . take the against record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'team', 'corinthians'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose team record fuzzily matches to corinthians .', 'tostr': 'filter_eq { all_rows ; team ; corinthians }'}, 'against'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; team ; corinthians } ; against }', 'tointer': 'select the rows whose team record fuzzily matches to corinthians . take the against record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; team ; juventus } ; against } ; hop { filter_eq { all_rows ; team ; corinthians } ; against } } = true', 'tointer': 'select the rows whose team record fuzzily matches to juventus . take the against record of this row . select the rows whose team record fuzzily matches to corinthians . take the against record of this row . the first record is greater than the second record .'}
|
greater { hop { filter_eq { all_rows ; team ; juventus } ; against } ; hop { filter_eq { all_rows ; team ; corinthians } ; against } } = true
|
select the rows whose team record fuzzily matches to juventus . take the against record of this row . select the rows whose team record fuzzily matches to corinthians . take the against 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, 'team_7': 7, 'juventus_8': 8, 'against_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'team_11': 11, 'corinthians_12': 12, 'against_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', 'team_7': 'team', 'juventus_8': 'juventus', 'against_9': 'against', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'team_11': 'team', 'corinthians_12': 'corinthians', 'against_13': 'against'}
|
{'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'team_7': [0], 'juventus_8': [0], 'against_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'team_11': [1], 'corinthians_12': [1], 'against_13': [3]}
|
['position', 'team', 'points', 'played', 'drawn', 'lost', 'against', 'difference']
|
[['1', 'palmeiras', '32', '20', '2', '3', '19', '31'], ['2', 'são paulo', '29', '20', '3', '4', '32', '37'], ['3', 'corinthians', '28', '20', '4', '4', '35', '20'], ['4', 'ypiranga - sp', '23', '20', '3', '7', '29', '8'], ['5', 'são paulo railway', '21', '20', '3', '8', '48', '- 7'], ['6', 'santos', '20', '20', '4', '8', '41', '- 2'], ['7', 'juventus', '18', '20', '4', '9', '49', '- 10'], ['8', 'comercial - sp', '18', '20', '2', '10', '57', '- 15'], ['9', 'portuguesa', '12', '20', '6', '11', '47', '- 18'], ['10', 'jabaquara', '10', '20', '0', '15', '50', '- 12'], ['11', 'portuguesa santista', '9', '20', '3', '14', '69', '- 32']]
|
2008 - 09 detroit red wings season
|
https://en.wikipedia.org/wiki/2008%E2%80%9309_Detroit_Red_Wings_season
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17371135-5.html.csv
|
ordinal
|
the game on november 13 ranked first for the highest number in attendance for the 08-09 red wings season .
|
{'row': '4', 'col': '6', 'order': '1', 'col_other': '1', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None}
|
{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'attendance', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; attendance ; 1 }'}, 'date'], 'result': 'november 13', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; attendance ; 1 } ; date }'}, 'november 13'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; attendance ; 1 } ; date } ; november 13 } = true', 'tointer': 'select the row whose attendance record of all rows is 1st maximum . the date record of this row is november 13 .'}
|
eq { hop { nth_argmax { all_rows ; attendance ; 1 } ; date } ; november 13 } = true
|
select the row whose attendance record of all rows is 1st maximum . the date record of this row is november 13 .
|
3
|
3
|
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'attendance_5': 5, '1_6': 6, 'date_7': 7, 'november 13_8': 8}
|
{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'attendance_5': 'attendance', '1_6': '1', 'date_7': 'date', 'november 13_8': 'november 13'}
|
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'attendance_5': [0], '1_6': [0], 'date_7': [1], 'november 13_8': [2]}
|
['date', 'visitor', 'score', 'home', 'decision', 'attendance', 'record']
|
[['november 2', 'detroit', '3 - 2', 'vancouver', 'osgood', '18630', '8 - 2 - 2'], ['november 8', 'new jersey', '1 - 3', 'detroit', 'osgood', '20066', '9 - 2 - 2'], ['november 11', 'pittsburgh', '7 - 6', 'detroit', 'osgood', '20066', '9 - 2 - 3'], ['november 13', 'detroit', '4 - 3', 'tampa bay', 'osgood', '20544', '10 - 2 - 3'], ['november 14', 'detroit', '3 - 2', 'florida', 'conklin', '18637', '11 - 2 - 3'], ['november 17', 'edmonton', '0 - 4', 'detroit', 'conklin', '18934', '12 - 2 - 3'], ['november 20', 'detroit', '4 - 3', 'edmonton', 'osgood', '16839', '13 - 2 - 3'], ['november 22', 'detroit', '5 - 2', 'calgary', 'conklin', '19289', '14 - 2 - 3'], ['november 24', 'detroit', '2 - 3', 'vancouver', 'osgood', '18630', '14 - 2 - 4'], ['november 26', 'montreal', '3 - 1', 'detroit', 'conklin', '20066', '14 - 3 - 4'], ['november 28', 'columbus', '3 - 5', 'detroit', 'osgood', '20066', '15 - 3 - 4'], ['november 29', 'detroit', '1 - 3', 'boston', 'conklin', '17565', '15 - 4 - 4']]
|
puerto rico soccer league
|
https://en.wikipedia.org/wiki/Puerto_Rico_Soccer_League
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17430068-2.html.csv
|
count
|
among the clubs of puerto rico soccer league that were founded after 2000 , 3 of them played 2009 season in prsl .
|
{'scope': 'subset', 'criterion': 'fuzzily_match', 'value': '2009', 'result': '3', 'col': '5', 'subset': {'col': '4', 'criterion': 'greater_than', 'value': '2000'}}
|
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'founded', '2000'], 'result': None, 'ind': 0, 'tostr': 'filter_greater { all_rows ; founded ; 2000 }', 'tointer': 'select the rows whose founded record is greater than 2000 .'}, 'seasons in prsl', '2009'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose founded record is greater than 2000 . among these rows , select the rows whose seasons in prsl record fuzzily matches to 2009 .', 'tostr': 'filter_eq { filter_greater { all_rows ; founded ; 2000 } ; seasons in prsl ; 2009 }'}], 'result': '3', 'ind': 2, 'tostr': 'count { filter_eq { filter_greater { all_rows ; founded ; 2000 } ; seasons in prsl ; 2009 } }', 'tointer': 'select the rows whose founded record is greater than 2000 . among these rows , select the rows whose seasons in prsl record fuzzily matches to 2009 . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_eq { filter_greater { all_rows ; founded ; 2000 } ; seasons in prsl ; 2009 } } ; 3 } = true', 'tointer': 'select the rows whose founded record is greater than 2000 . among these rows , select the rows whose seasons in prsl record fuzzily matches to 2009 . the number of such rows is 3 .'}
|
eq { count { filter_eq { filter_greater { all_rows ; founded ; 2000 } ; seasons in prsl ; 2009 } } ; 3 } = true
|
select the rows whose founded record is greater than 2000 . among these rows , select the rows whose seasons in prsl record fuzzily matches to 2009 . the number of such rows is 3 .
|
4
|
4
|
{'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_str_eq_1': 1, 'filter_greater_0': 0, 'all_rows_5': 5, 'founded_6': 6, '2000_7': 7, 'seasons in prsl_8': 8, '2009_9': 9, '3_10': 10}
|
{'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_str_eq_1': 'filter_str_eq', 'filter_greater_0': 'filter_greater', 'all_rows_5': 'all_rows', 'founded_6': 'founded', '2000_7': '2000', 'seasons in prsl_8': 'seasons in prsl', '2009_9': '2009', '3_10': '3'}
|
{'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_str_eq_1': [2], 'filter_greater_0': [1], 'all_rows_5': [0], 'founded_6': [0], '2000_7': [0], 'seasons in prsl_8': [1], '2009_9': [1], '3_10': [3]}
|
['club', 'home city', 'stadium', 'founded', 'seasons in prsl']
|
[['academia quintana fc', 'san juan', 'hiram bithorn stadium', '1969', '2008 , 2009'], ['atlético de san juan fc', 'san juan', 'hiram bithorn stadium', '2008', '2008 , 2009'], ['bayamón fc', 'bayamón', 'estadio juan ramón loubriel', '2009', '2009'], ['fajardo fc', 'fajardo', 'fajardo stadium', '2010', '2010'], ['guaynabo fluminense fc', 'guaynabo', 'estadio jose pepito bonano', '2002', '2008 , 2009 , 2010'], ['gigantes de carolina fc / boca juniors carolina fc', 'carolina', 'roberto clemente stadium', '1998', '2008 , 2009'], ['puerto rico islanders fc', 'bayamón', 'estadio juan ramón loubriel', '2003', '2010'], ['cf tornados de humacao', 'humacao', 'estadio nestor morales', '1994', '2008 , 2009']]
|
2002 - 03 toronto raptors season
|
https://en.wikipedia.org/wiki/2002%E2%80%9303_Toronto_Raptors_season
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-15780718-8.html.csv
|
majority
|
all games of the 2002 - 03 toronto raptors ' season were scheduled for the month of march .
|
{'scope': 'all', 'col': '2', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'march', 'subset': None}
|
{'func': 'all_str_eq', 'args': ['all_rows', 'date', 'march'], 'result': True, 'ind': 0, 'tointer': 'for the date records of all rows , all of them fuzzily match to march .', 'tostr': 'all_eq { all_rows ; date ; march } = true'}
|
all_eq { all_rows ; date ; march } = true
|
for the date records of all rows , all of them fuzzily match to march .
|
1
|
1
|
{'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'date_3': 3, 'march_4': 4}
|
{'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'date_3': 'date', 'march_4': 'march'}
|
{'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'date_3': [0], 'march_4': [0]}
|
['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record']
|
[['56', 'march 2', 'boston', 'w 104 - 92 ( ot )', 'antonio davis ( 19 )', 'michael bradley ( 13 )', 'alvin williams ( 6 )', 'air canada centre 19800', '18 - 38'], ['57', 'march 4', 'washington', 'w 89 - 86 ( ot )', 'vince carter ( 24 )', 'michael bradley , jerome williams ( 7 )', 'antonio davis ( 5 )', 'mci center 20173', '19 - 38'], ['58', 'march 5', 'houston', 'l 95 - 97 ( ot )', 'vince carter ( 21 )', 'jerome williams ( 10 )', 'antonio davis ( 6 )', 'air canada centre 20171', '19 - 39'], ['59', 'march 8', 'atlanta', 'w 107 - 98 ( ot )', 'vince carter ( 43 )', 'jerome williams ( 15 )', 'antonio davis ( 8 )', 'philips arena 19445', '20 - 39'], ['60', 'march 9', 'memphis', 'l 106 - 119 ( ot )', 'vince carter ( 26 )', 'antonio davis ( 8 )', 'alvin williams ( 9 )', 'air canada centre 19138', '20 - 40'], ['61', 'march 11', 'denver', 'l 87 - 95 ( ot )', 'vince carter ( 21 )', 'michael bradley ( 12 )', 'alvin williams ( 6 )', 'pepsi center 13409', '20 - 41'], ['62', 'march 12', 'portland', 'l 103 - 125 ( ot )', 'vince carter ( 21 )', 'michael bradley ( 10 )', 'rafer alston ( 6 )', 'rose garden 19991', '20 - 42'], ['63', 'march 14', 'sacramento', 'l 84 - 119 ( ot )', 'vince carter , morris peterson ( 16 )', "mamadou n'diaye ( 10 )", 'rafer alston ( 7 )', 'arco arena 17317', '20 - 43'], ['64', 'march 16', 'la clippers', 'l 110 - 111 ( ot )', 'vince carter ( 28 )', 'antonio davis , jerome williams ( 8 )', 'alvin williams ( 5 )', 'staples center 18268', '20 - 44'], ['65', 'march 17', 'phoenix', 'l 91 - 95 ( ot )', 'morris peterson ( 17 )', 'antonio davis ( 15 )', 'alvin williams ( 7 )', 'america west arena 15326', '20 - 45'], ['66', 'march 19', 'atlanta', 'w 87 - 86 ( ot )', 'vince carter ( 27 )', 'jerome williams ( 10 )', 'alvin williams ( 6 )', 'air canada centre 17885', '21 - 45'], ['67', 'march 21', 'miami', 'l 98 - 107 ( ot )', 'vince carter ( 30 )', 'jerome williams ( 9 )', 'alvin williams ( 7 )', 'american airlines arena 14492', '21 - 46'], ['68', 'march 23', 'philadelphia', 'l 95 - 112 ( ot )', 'vince carter ( 22 )', 'antonio davis ( 9 )', 'vince carter ( 9 )', 'air canada centre 19800', '21 - 47'], ['69', 'march 24', 'new york', 'l 90 - 100 ( ot )', 'antonio davis ( 23 )', 'antonio davis ( 12 )', 'alvin williams ( 8 )', 'madison square garden 18824', '21 - 48'], ['70', 'march 26', 'cleveland', 'w 89 - 83 ( ot )', 'morris peterson ( 21 )', 'jelani mccoy ( 8 )', 'rafer alston ( 6 )', 'air canada centre 16832', '22 - 48'], ['71', 'march 28', 'new orleans', 'l 92 - 101 ( ot )', 'vince carter ( 21 )', 'michael bradley ( 11 )', 'alvin williams ( 5 )', 'air canada centre 18773', '22 - 49']]
|
1994 cincinnati bengals season
|
https://en.wikipedia.org/wiki/1994_Cincinnati_Bengals_season
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16779943-2.html.csv
|
aggregation
|
in the 1994 season of cincinnati bengals , games in october had a total of 245,093 people attend .
|
{'scope': 'subset', 'col': '5', 'type': 'sum', 'result': '245,093', 'subset': {'col': '2', 'criterion': 'fuzzily_match', 'value': 'october'}}
|
{'func': 'round_eq', 'args': [{'func': 'sum', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', 'october'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; date ; october }', 'tointer': 'select the rows whose date record fuzzily matches to october .'}, 'attendance'], 'result': '245,093', 'ind': 1, 'tostr': 'sum { filter_eq { all_rows ; date ; october } ; attendance }'}, '245,093'], 'result': True, 'ind': 2, 'tostr': 'round_eq { sum { filter_eq { all_rows ; date ; october } ; attendance } ; 245,093 } = true', 'tointer': 'select the rows whose date record fuzzily matches to october . the sum of the attendance record of these rows is 245,093 .'}
|
round_eq { sum { filter_eq { all_rows ; date ; october } ; attendance } ; 245,093 } = true
|
select the rows whose date record fuzzily matches to october . the sum of the attendance record of these rows is 245,093 .
|
3
|
3
|
{'eq_2': 2, 'result_3': 3, 'sum_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'date_5': 5, 'october_6': 6, 'attendance_7': 7, '245,093_8': 8}
|
{'eq_2': 'eq', 'result_3': 'true', 'sum_1': 'sum', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'date_5': 'date', 'october_6': 'october', 'attendance_7': 'attendance', '245,093_8': '245,093'}
|
{'eq_2': [3], 'result_3': [], 'sum_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'date_5': [0], 'october_6': [0], 'attendance_7': [1], '245,093_8': [2]}
|
['week', 'date', 'opponent', 'result', 'attendance']
|
[['1', 'september 4 , 1994', 'cleveland browns', 'l 20 - 28', '52778'], ['2', 'september 11 , 1994', 'san diego chargers', 'l 10 - 27', '53217'], ['3', 'september 18 , 1994', 'new england patriots', 'l 28 - 31', '46640'], ['4', 'september 25 , 1994', 'houston oilers', 'l 13 - 20', '44253'], ['5', 'october 2 , 1994', 'miami dolphins', 'l 7 - 23', '55056'], ['7', 'october 16 , 1994', 'pittsburgh steelers', 'l 10 - 14', '55353'], ['8', 'october 23 , 1994', 'cleveland browns', 'l 13 - 37', '77588'], ['9', 'october 30 , 1994', 'dallas cowboys', 'l 20 - 23', '57096'], ['10', 'november 6 , 1994', 'seattle seahawks', 'w 20 - 17', '46630'], ['11', 'november 13 , 1994', 'houston oilers', 'w 34 - 31', '54908'], ['12', 'november 20 , 1994', 'indianapolis colts', 'l 13 - 17', '55566'], ['13', 'november 27 , 1994', 'denver broncos', 'l 13 - 15', '69714'], ['14', 'december 4 , 1994', 'pittsburgh steelers', 'l 15 - 38', '53401'], ['15', 'december 11 , 1994', 'new york giants', 'l 20 - 27', '67530'], ['16', 'december 18 , 1994', 'arizona cardinals', 'l 7 - 28', '50110'], ['17', 'december 24 , 1994', 'philadelphia eagles', 'w 33 - 30', '39923']]
|
westmorland county , new brunswick
|
https://en.wikipedia.org/wiki/Westmorland_County%2C_New_Brunswick
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-176529-2.html.csv
|
superlative
|
salisbury is the parish in westmorland county , new brunswick that has the highest area .
|
{'scope': 'all', 'col_superlative': '3', 'row_superlative': '3', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None}
|
{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'area km 2'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; area km 2 }'}, 'official name'], 'result': 'salisbury', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; area km 2 } ; official name }'}, 'salisbury'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; area km 2 } ; official name } ; salisbury } = true', 'tointer': 'select the row whose area km 2 record of all rows is maximum . the official name record of this row is salisbury .'}
|
eq { hop { argmax { all_rows ; area km 2 } ; official name } ; salisbury } = true
|
select the row whose area km 2 record of all rows is maximum . the official name record of this row is salisbury .
|
3
|
3
|
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'area km 2_5': 5, 'official name_6': 6, 'salisbury_7': 7}
|
{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'area km 2_5': 'area km 2', 'official name_6': 'official name', 'salisbury_7': 'salisbury'}
|
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'area km 2_5': [0], 'official name_6': [1], 'salisbury_7': [2]}
|
['official name', 'status', 'area km 2', 'population', 'census ranking']
|
[['moncton', 'parish', '582.20', '8861', '427 of 5008'], ['shediac', 'parish', '238.47', '4801', '709 of 5008'], ['salisbury', 'parish', '873.55', '3425', '909 of 5008'], ['botsford', 'parish', '303.75', '1203', '1827 of 5008'], ['sackville', 'parish', '578.28', '1174', '1857 of 5008'], ['westmorland', 'parish', '173.48', '959', '2105 of 5008']]
|
united states house of representatives elections , 1880
|
https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1880
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1431558-4.html.csv
|
majority
|
all of the incumbents from south carolina in the united states house of representatives 1880 elections were with the democratic party .
|
{'scope': 'all', 'col': '3', 'most_or_all': 'all', 'criterion': 'fuzzily_match', 'value': 'democratic', 'subset': None}
|
{'func': 'all_str_eq', 'args': ['all_rows', 'party', 'democratic'], 'result': True, 'ind': 0, 'tointer': 'for the party records of all rows , all of them fuzzily match to democratic .', 'tostr': 'all_eq { all_rows ; party ; democratic } = true'}
|
all_eq { all_rows ; party ; democratic } = true
|
for the party records of all rows , all of them fuzzily match to democratic .
|
1
|
1
|
{'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'party_3': 3, 'democratic_4': 4}
|
{'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'party_3': 'party', 'democratic_4': 'democratic'}
|
{'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'party_3': [0], 'democratic_4': [0]}
|
['district', 'incumbent', 'party', 'first elected', 'result']
|
[['south carolina 1', 'john s richardson', 'democratic', '1878', 're - elected'], ['south carolina 2', "michael p o'connor", 'democratic', '1878', 're - elected'], ['south carolina 3', 'd wyatt aiken', 'democratic', '1876', 're - elected'], ['south carolina 4', 'john h evins', 'democratic', '1876', 're - elected'], ['south carolina 5', 'george d tillman', 'democratic', '1878', 're - elected']]
|
2005 pga championship
|
https://en.wikipedia.org/wiki/2005_PGA_Championship
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12512153-2.html.csv
|
comparative
|
john daly had won a pga championship earlier than david toms .
|
{'row_1': '6', 'row_2': '5', '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', 'player', 'john daly'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose player record fuzzily matches to john daly .', 'tostr': 'filter_eq { all_rows ; player ; john daly }'}, 'year ( s ) won'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; player ; john daly } ; year ( s ) won }', 'tointer': 'select the rows whose player record fuzzily matches to john daly . take the year ( s ) won record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', 'david toms'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose player record fuzzily matches to david toms .', 'tostr': 'filter_eq { all_rows ; player ; david toms }'}, 'year ( s ) won'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; player ; david toms } ; year ( s ) won }', 'tointer': 'select the rows whose player record fuzzily matches to david toms . take the year ( s ) won record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; player ; john daly } ; year ( s ) won } ; hop { filter_eq { all_rows ; player ; david toms } ; year ( s ) won } } = true', 'tointer': 'select the rows whose player record fuzzily matches to john daly . take the year ( s ) won record of this row . select the rows whose player record fuzzily matches to david toms . take the year ( s ) won record of this row . the first record is less than the second record .'}
|
less { hop { filter_eq { all_rows ; player ; john daly } ; year ( s ) won } ; hop { filter_eq { all_rows ; player ; david toms } ; year ( s ) won } } = true
|
select the rows whose player record fuzzily matches to john daly . take the year ( s ) won record of this row . select the rows whose player record fuzzily matches to david toms . take the year ( s ) 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, 'player_7': 7, 'john daly_8': 8, 'year (s) won_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'player_11': 11, 'david toms_12': 12, 'year (s) 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', 'player_7': 'player', 'john daly_8': 'john daly', 'year (s) won_9': 'year ( s ) won', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'player_11': 'player', 'david toms_12': 'david toms', 'year (s) won_13': 'year ( s ) won'}
|
{'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'player_7': [0], 'john daly_8': [0], 'year (s) won_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'player_11': [1], 'david toms_12': [1], 'year (s) won_13': [3]}
|
['player', 'country', 'year ( s ) won', 'total', 'to par', 'finish']
|
[['steve elkington', 'australia', '1995', '277', '- 3', 't2'], ['davis love iii', 'united states', '1997', '278', '- 2', 't4'], ['tiger woods', 'united states', '1999 , 2000', '278', '- 2', 't4'], ['vijay singh', 'fiji', '1998 , 2004', '280', 'e', 't10'], ['david toms', 'united states', '2001', '280', 'e', 't10'], ['john daly', 'united states', '1991', '292', '+ 12', 't74'], ['hal sutton', 'united states', '1983', '300', '+ 20', '79']]
|
1972 baltimore colts season
|
https://en.wikipedia.org/wiki/1972_Baltimore_Colts_season
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14959246-2.html.csv
|
comparative
|
the game against the san diego chargers was seven days before the game against the dallas cowboys .
|
{'row_1': '4', 'row_2': '5', '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', 'san diego chargers'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose opponent record fuzzily matches to san diego chargers .', 'tostr': 'filter_eq { all_rows ; opponent ; san diego chargers }'}, 'date'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; opponent ; san diego chargers } ; date }', 'tointer': 'select the rows whose opponent record fuzzily matches to san diego chargers . take the date record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', 'dallas cowboys'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose opponent record fuzzily matches to dallas cowboys .', 'tostr': 'filter_eq { all_rows ; opponent ; dallas cowboys }'}, 'date'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; opponent ; dallas cowboys } ; date }', 'tointer': 'select the rows whose opponent record fuzzily matches to dallas cowboys . take the date record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; opponent ; san diego chargers } ; date } ; hop { filter_eq { all_rows ; opponent ; dallas cowboys } ; date } } = true', 'tointer': 'select the rows whose opponent record fuzzily matches to san diego chargers . take the date record of this row . select the rows whose opponent record fuzzily matches to dallas cowboys . take the date record of this row . the first record is less than the second record .'}
|
less { hop { filter_eq { all_rows ; opponent ; san diego chargers } ; date } ; hop { filter_eq { all_rows ; opponent ; dallas cowboys } ; date } } = true
|
select the rows whose opponent record fuzzily matches to san diego chargers . take the date record of this row . select the rows whose opponent record fuzzily matches to dallas cowboys . 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, 'san diego chargers_8': 8, 'date_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'opponent_11': 11, 'dallas cowboys_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', 'san diego chargers_8': 'san diego chargers', 'date_9': 'date', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'opponent_11': 'opponent', 'dallas cowboys_12': 'dallas cowboys', 'date_13': 'date'}
|
{'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'opponent_7': [0], 'san diego chargers_8': [0], 'date_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'opponent_11': [1], 'dallas cowboys_12': [1], 'date_13': [3]}
|
['week', 'date', 'opponent', 'result', 'record', 'game site', 'attendance']
|
[['1', 'september 17 , 1972', 'st louis cardinals', 'l 3 - 10', '0 - 1', 'memorial stadium', '53562'], ['2', 'september 24 , 1972', 'new york jets', 'l 34 - 44', '0 - 2', 'memorial stadium', '56626'], ['3', 'october 1 , 1972', 'buffalo bills', 'w 17 - 0', '1 - 2', 'war memorial stadium', '46206'], ['4', 'october 8 , 1972', 'san diego chargers', 'l 20 - 23', '1 - 3', 'memorial stadium', '55459'], ['5', 'october 15 , 1972', 'dallas cowboys', 'l 0 - 21', '1 - 4', 'memorial stadium', '58992'], ['6', 'october 22 , 1972', 'new york jets', 'l 20 - 24', '1 - 5', 'shea stadium', '62948'], ['7', 'october 29 , 1972', 'miami dolphins', 'l 0 - 23', '1 - 6', 'memorial stadium', '60000'], ['8', 'november 6 , 1972', 'new england patriots', 'w 24 - 17', '2 - 6', 'schaefer stadium', '60999'], ['9', 'november 12 , 1972', 'san francisco 49ers', 'l 21 - 24', '2 - 7', 'candlestick park', '61214'], ['10', 'november 19 , 1972', 'cincinnati bengals', 'w 20 - 19', '3 - 7', 'riverfront stadium', '49512'], ['11', 'november 26 , 1972', 'new england patriots', 'w 31 - 0', '4 - 7', 'memorial stadium', '54907'], ['12', 'december 3 , 1972', 'buffalo bills', 'w 35 - 7', '5 - 7', 'memorial stadium', '55390'], ['13', 'december 10 , 1972', 'kansas city chiefs', 'l 10 - 24', '5 - 8', 'arrowhead stadium', '44175'], ['14', 'december 16 , 1972', 'miami dolphins', 'l 0 - 16', '5 - 9', 'miami orange bowl', '80010']]
|
swimming at the 2000 summer olympics - men 's 100 metre butterfly
|
https://en.wikipedia.org/wiki/Swimming_at_the_2000_Summer_Olympics_%E2%80%93_Men%27s_100_metre_butterfly
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12446342-5.html.csv
|
ordinal
|
anatoly polyakov had the 3rd longest time in the men 's 100 metre butterfly during the 2000 summer olympics .
|
{'row': '6', 'col': '5', 'order': '3', 'col_other': '3', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None}
|
{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'time', '3'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; time ; 3 }'}, 'name'], 'result': 'anatoly polyakov', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; time ; 3 } ; name }'}, 'anatoly polyakov'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; time ; 3 } ; name } ; anatoly polyakov } = true', 'tointer': 'select the row whose time record of all rows is 3rd maximum . the name record of this row is anatoly polyakov .'}
|
eq { hop { nth_argmax { all_rows ; time ; 3 } ; name } ; anatoly polyakov } = true
|
select the row whose time record of all rows is 3rd maximum . the name record of this row is anatoly polyakov .
|
3
|
3
|
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'time_5': 5, '3_6': 6, 'name_7': 7, 'anatoly polyakov_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', 'time_5': 'time', '3_6': '3', 'name_7': 'name', 'anatoly polyakov_8': 'anatoly polyakov'}
|
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'time_5': [0], '3_6': [0], 'name_7': [1], 'anatoly polyakov_8': [2]}
|
['rank', 'lane', 'name', 'nationality', 'time']
|
[['1', '4', 'michael klim', 'australia', '52.63'], ['2', '2', 'ian crocker', 'united states', '52.82'], ['3', '3', 'lars frölander', 'sweden', '52.84'], ['4', '5', 'mike mintenko', 'canada', '53.00'], ['5', '1', 'thomas rupprath', 'germany', '53.18'], ['6', '6', 'anatoly polyakov', 'russia', '53.32'], ['7', '7', 'franck esposito', 'france', '53.38'], ['8', '8', 'jere hård', 'finland', '53.65']]
|
usa today all - usa high school basketball team
|
https://en.wikipedia.org/wiki/USA_Today_All-USA_high_school_basketball_team
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11677760-10.html.csv
|
majority
|
the majority of players on the usa today all - usa high school basketball team were taken in the 1st round of the nba draft .
|
{'scope': 'all', 'col': '6', 'most_or_all': 'most', 'criterion': 'equal', 'value': '1st round', 'subset': None}
|
{'func': 'most_str_eq', 'args': ['all_rows', 'nba draft', '1st round'], 'result': True, 'ind': 0, 'tointer': 'for the nba draft records of all rows , most of them fuzzily match to 1st round .', 'tostr': 'most_eq { all_rows ; nba draft ; 1st round } = true'}
|
most_eq { all_rows ; nba draft ; 1st round } = true
|
for the nba draft records of all rows , most of them fuzzily match to 1st round .
|
1
|
1
|
{'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'nba draft_3': 3, '1st round_4': 4}
|
{'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'nba draft_3': 'nba draft', '1st round_4': '1st round'}
|
{'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'nba draft_3': [0], '1st round_4': [0]}
|
['player', 'height', 'school', 'hometown', 'college', 'nba draft']
|
[['alonzo mourning', '6 - 10', 'indian river high school', 'chesapeake , va', 'georgetown', '1st round - 2nd pick of 1992 draft ( hornets )'], ['chris jackson', '6 - 0', 'gulfport high school', 'gulfport , ms', 'lsu', '1st round - 3rd pick of 1990 draft ( nuggets )'], ['chris mills', '6 - 7', 'fairfax high school', 'los angeles , ca', 'kentucky / arizona', '1st round - 22nd pick of 1993 draft ( cavs )'], ['billy owens', '6 - 9', 'carlisle high school', 'carlisle , pa', 'syracuse', '1st round - 3rd pick of 1991 draft ( kings )'], ['kenny williams', '6 - 10', 'fork union military academy', 'elizabeth city , nc', 'barton cc / elizabeth city state', '2nd round - 46th pick of 1990 draft ( pacers )']]
|
adriano buzaid
|
https://en.wikipedia.org/wiki/Adriano_Buzaid
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-23128286-1.html.csv
|
superlative
|
adriano buzaid scored the highest amount of points in his career in the 2008 formula renault uk .
|
{'scope': 'all', 'col_superlative': '9', 'row_superlative': '5', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '2', 'subset': None}
|
{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'points'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; points }'}, 'series'], 'result': 'formula renault uk', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; points } ; series }'}, 'formula renault uk'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; points } ; series } ; formula renault uk } = true', 'tointer': 'select the row whose points record of all rows is maximum . the series record of this row is formula renault uk .'}
|
eq { hop { argmax { all_rows ; points } ; series } ; formula renault uk } = true
|
select the row whose points record of all rows is maximum . the series record of this row is formula renault uk .
|
3
|
3
|
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'points_5': 5, 'series_6': 6, 'formula renault uk_7': 7}
|
{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'points_5': 'points', 'series_6': 'series', 'formula renault uk_7': 'formula renault uk'}
|
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'points_5': [0], 'series_6': [1], 'formula renault uk_7': [2]}
|
['season', 'series', 'team name', 'races', 'wins', 'poles', 'flaps', 'podiums', 'points', 'final placing']
|
[['2006', 'formula ford uk', 'eau rouge motorsport', '17', '1', '0', '1', '1', '186', '13th'], ['2006', 'formula renault uk winter series', 'aka lemac', '4', '0', '0', '0', '1', '58', '7th'], ['2007', 'formula renault uk', 'eucatex', '20', '0', '0', '0', '2', '166', '13th'], ['2007', 'formula renault uk winter series', 'fortec motorsport', '4', '1', '1', '0', '1', '56', '7th'], ['2008', 'formula renault uk', 'fortec motorsport', '20', '5', '6', '5', '7', '418', '3rd'], ['2008', 'formula renault 2.0 italia winter cup', 'bvm minardi team', '2', '0', '0', '0', '0', '18', '10th'], ['2008', 'british formula three national class', 'carlin motorsport', '2', '0', '0', '0', '1', '22', '13th'], ['2009', 'british formula three', 't - sport', '20', '1', '1', '0', '5', '109', '6th']]
|
2001 belarusian premier league
|
https://en.wikipedia.org/wiki/2001_Belarusian_Premier_League
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14747610-1.html.csv
|
count
|
in the 2001 belarusian premier league , among the venues named central , 2 of them have capacity over 5,000 .
|
{'scope': 'subset', 'criterion': 'greater_than', 'value': '5000', 'result': '2', 'col': '4', 'subset': {'col': '3', 'criterion': 'fuzzily_match', 'value': 'central'}}
|
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'venue', 'central'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; venue ; central }', 'tointer': 'select the rows whose venue record fuzzily matches to central .'}, 'capacity', '5000'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose venue record fuzzily matches to central . among these rows , select the rows whose capacity record is greater than 5000 .', 'tostr': 'filter_greater { filter_eq { all_rows ; venue ; central } ; capacity ; 5000 }'}], 'result': '2', 'ind': 2, 'tostr': 'count { filter_greater { filter_eq { all_rows ; venue ; central } ; capacity ; 5000 } }', 'tointer': 'select the rows whose venue record fuzzily matches to central . among these rows , select the rows whose capacity record is greater than 5000 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_greater { filter_eq { all_rows ; venue ; central } ; capacity ; 5000 } } ; 2 } = true', 'tointer': 'select the rows whose venue record fuzzily matches to central . among these rows , select the rows whose capacity record is greater than 5000 . the number of such rows is 2 .'}
|
eq { count { filter_greater { filter_eq { all_rows ; venue ; central } ; capacity ; 5000 } } ; 2 } = true
|
select the rows whose venue record fuzzily matches to central . among these rows , select the rows whose capacity record is greater than 5000 . the number of such rows is 2 .
|
4
|
4
|
{'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_greater_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'venue_6': 6, 'central_7': 7, 'capacity_8': 8, '5000_9': 9, '2_10': 10}
|
{'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_greater_1': 'filter_greater', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'venue_6': 'venue', 'central_7': 'central', 'capacity_8': 'capacity', '5000_9': '5000', '2_10': '2'}
|
{'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_greater_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'venue_6': [0], 'central_7': [0], 'capacity_8': [1], '5000_9': [1], '2_10': [3]}
|
['team', 'location', 'venue', 'capacity', 'position in 2000']
|
[['slavia', 'mozyr', 'yunost', '5500', '1'], ['bate', 'borisov', 'city stadium , borisov', '5500', '2'], ['dinamo minsk', 'minsk', 'dinamo , minsk', '41040', '3'], ['neman - belcard', 'grodno', 'neman', '6300', '4'], ['shakhtyor', 'soligorsk', 'stroitel', '5000', '5'], ['gomel', 'gomel', 'central , gomel', '11800', '6'], ['dnepr - transmash', 'mogilev', 'spartak , mogilev', '11200', '7'], ['torpedo - maz', 'minsk', 'torpedo , minsk', '5200', '8'], ['belshina', 'bobruisk', 'spartak , bobruisk', '3550', '9'], ['dinamo brest', 'brest', 'osk brestskiy', '10080', '10'], ['lokomotiv - 96', 'vitebsk', 'central , vitebsk', '8300', '11'], ['vedrich - 97', 'rechytsa', 'central , rechytsa', '3550', '12'], ['naftan', 'novopolotsk', 'atlant', '6500', '13'], ['molodechno - 2000', 'molodechno', 'city stadium , molodechno', '5500', 'first league , 1']]
|
2008 italian motorcycle grand prix
|
https://en.wikipedia.org/wiki/2008_Italian_motorcycle_Grand_Prix
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16212245-1.html.csv
|
count
|
four competitors in the 2008 italian motorcycle grand prix did not complete the race due to accidents .
|
{'scope': 'all', 'criterion': 'equal', 'value': 'accident', 'result': '4', 'col': '4', 'subset': None}
|
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'time', 'accident'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose time record fuzzily matches to accident .', 'tostr': 'filter_eq { all_rows ; time ; accident }'}], 'result': '4', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; time ; accident } }', 'tointer': 'select the rows whose time record fuzzily matches to accident . the number of such rows is 4 .'}, '4'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; time ; accident } } ; 4 } = true', 'tointer': 'select the rows whose time record fuzzily matches to accident . the number of such rows is 4 .'}
|
eq { count { filter_eq { all_rows ; time ; accident } } ; 4 } = true
|
select the rows whose time record fuzzily matches to accident . 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, 'time_5': 5, 'accident_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', 'time_5': 'time', 'accident_6': 'accident', '4_7': '4'}
|
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'time_5': [0], 'accident_6': [0], '4_7': [2]}
|
['rider', 'manufacturer', 'laps', 'time', 'grid']
|
[['valentino rossi', 'yamaha', '23', '42:31.153', '1'], ['casey stoner', 'ducati', '23', '+ 2.201', '4'], ['dani pedrosa', 'honda', '23', '+ 4.867', '2'], ['alex de angelis', 'honda', '23', '+ 6.313', '10'], ['colin edwards', 'yamaha', '23', '+ 12.530', '5'], ['james toseland', 'yamaha', '23', '+ 13.806', '8'], ['loris capirossi', 'suzuki', '23', '+ 14.447', '3'], ['andrea dovizioso', 'honda', '23', '+ 15.319', '13'], ['shinya nakano', 'honda', '23', '+ 15.327', '9'], ['chris vermeulen', 'suzuki', '23', '+ 30.785', '11'], ['sylvain guintoli', 'ducati', '23', '+ 39.621', '17'], ['toni elias', 'ducati', '23', '+ 50.021', '16'], ['nicky hayden', 'honda', '23', '+ 50.440', '6'], ['tadayuki okada', 'honda', '23', '+ 58.849', '15'], ['anthony west', 'kawasaki', '23', '+ 1:00.736', '19'], ['jorge lorenzo', 'yamaha', '6', 'accident', '7'], ['john hopkins', 'kawasaki', '6', 'accident', '14'], ['randy de puniet', 'honda', '5', 'accident', '12'], ['marco melandri', 'ducati', '5', 'accident', '18']]
|
nishi - ōhira domain
|
https://en.wikipedia.org/wiki/Nishi-%C5%8Chira_Domain
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-12803263-1.html.csv
|
unique
|
ōoka tadatomo was the only daimyōs with revenues above 10000 koku .
|
{'scope': 'all', 'row': '4', 'col': '6', 'col_other': '2', 'criterion': 'greater_than', 'value': '10000 koku', 'subset': None}
|
{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'revenues', '10000 koku'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose revenues record is greater than 10000 koku .', 'tostr': 'filter_greater { all_rows ; revenues ; 10000 koku }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_greater { all_rows ; revenues ; 10000 koku } }', 'tointer': 'select the rows whose revenues record is greater than 10000 koku . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'revenues', '10000 koku'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose revenues record is greater than 10000 koku .', 'tostr': 'filter_greater { all_rows ; revenues ; 10000 koku }'}, 'name'], 'result': 'ōoka tadatomo ( 大岡忠與 )', 'ind': 2, 'tostr': 'hop { filter_greater { all_rows ; revenues ; 10000 koku } ; name }'}, 'ōoka tadatomo ( 大岡忠與 )'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_greater { all_rows ; revenues ; 10000 koku } ; name } ; ōoka tadatomo ( 大岡忠與 ) }', 'tointer': 'the name record of this unqiue row is ōoka tadatomo ( 大岡忠與 ) .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_greater { all_rows ; revenues ; 10000 koku } } ; eq { hop { filter_greater { all_rows ; revenues ; 10000 koku } ; name } ; ōoka tadatomo ( 大岡忠與 ) } } = true', 'tointer': 'select the rows whose revenues record is greater than 10000 koku . there is only one such row in the table . the name record of this unqiue row is ōoka tadatomo ( 大岡忠與 ) .'}
|
and { only { filter_greater { all_rows ; revenues ; 10000 koku } } ; eq { hop { filter_greater { all_rows ; revenues ; 10000 koku } ; name } ; ōoka tadatomo ( 大岡忠與 ) } } = true
|
select the rows whose revenues record is greater than 10000 koku . there is only one such row in the table . the name record of this unqiue row is ōoka tadatomo ( 大岡忠與 ) .
|
6
|
5
|
{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_greater_0': 0, 'all_rows_6': 6, 'revenues_7': 7, '10000 koku_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'name_9': 9, 'ōoka tadatomo (大岡忠與)_10': 10}
|
{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_greater_0': 'filter_greater', 'all_rows_6': 'all_rows', 'revenues_7': 'revenues', '10000 koku_8': '10000 koku', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'name_9': 'name', 'ōoka tadatomo (大岡忠與)_10': 'ōoka tadatomo ( 大岡忠與 )'}
|
{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_greater_0': [1, 2], 'all_rows_6': [0], 'revenues_7': [0], '10000 koku_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'name_9': [2], 'ōoka tadatomo (大岡忠與)_10': [3]}
|
['', 'name', 'tenure', 'courtesy title', 'court rank', 'revenues', 'lineage']
|
[['1', 'ōoka tadasuke ( 大岡忠相 )', '1748 - 1751', 'echizen - no - kami ( 越前守 )', 'lower 5th ( 従五位下 )', '10000 koku', '4th son of hatamoto ōoka tadataka'], ['2', 'ōoka tadayoshi ( 大岡忠宜 )', '1755 - 1766', 'echizen - no - kami ( 越前守 )', 'lower 5th ( 従五位下 )', '10000 koku', '2nd son of tadasuke'], ['3', 'ōoka tadatsune ( 大岡忠恒 )', '1766 - 1784', 'echizen - no - kami ( 越前守 )', 'lower 5th ( 従五位下 )', '10000 koku', '2nd son of tadayoshi'], ['4', 'ōoka tadatomo ( 大岡忠與 )', '1784 - 1786', 'echizen - no - kami ( 越前守 )', 'lower 5th ( 従五位下 )', '13000 koku', '3rd son of ogasawara nagamichi'], ['5', 'ōoka tadayori ( 大岡忠移 )', '1786 - 1828', 'echizen - no - kami ( 越前守 )', 'lower 5th ( 従五位下 )', '10000 koku', '3rd son of tadatsune'], ['6', 'ōoka tadayoshi ( 2nd ) ( 大岡忠愛 )', '1828 - 1857', 'echizen - no - kami ( 越前守 )', 'lower 5th ( 従五位下 )', '10000 koku', 'son of tadayori']]
|
skins ( north american tv series )
|
https://en.wikipedia.org/wiki/Skins_%28North_American_TV_series%29
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-29545336-2.html.csv
|
aggregation
|
skins had a total of 2.20 million viewers in the us in the last two episodes .
|
{'scope': 'subset', 'col': '6', 'type': 'sum', 'result': '2.20', 'subset': {'col': '1', 'criterion': 'greater_than_eq', 'value': '8'}}
|
{'func': 'round_eq', 'args': [{'func': 'sum', 'args': [{'func': 'filter_greater_eq', 'args': ['all_rows', 'no', '8'], 'result': None, 'ind': 0, 'tostr': 'filter_greater_eq { all_rows ; no ; 8 }', 'tointer': 'select the rows whose no record is greater than or equal to 8 .'}, 'us viewers ( millions )'], 'result': '2.20', 'ind': 1, 'tostr': 'sum { filter_greater_eq { all_rows ; no ; 8 } ; us viewers ( millions ) }'}, '2.20'], 'result': True, 'ind': 2, 'tostr': 'round_eq { sum { filter_greater_eq { all_rows ; no ; 8 } ; us viewers ( millions ) } ; 2.20 } = true', 'tointer': 'select the rows whose no record is greater than or equal to 8 . the sum of the us viewers ( millions ) record of these rows is 2.20 .'}
|
round_eq { sum { filter_greater_eq { all_rows ; no ; 8 } ; us viewers ( millions ) } ; 2.20 } = true
|
select the rows whose no record is greater than or equal to 8 . the sum of the us viewers ( millions ) record of these rows is 2.20 .
|
3
|
3
|
{'eq_2': 2, 'result_3': 3, 'sum_1': 1, 'filter_greater_eq_0': 0, 'all_rows_4': 4, 'no_5': 5, '8_6': 6, 'us viewers (millions)_7': 7, '2.20_8': 8}
|
{'eq_2': 'eq', 'result_3': 'true', 'sum_1': 'sum', 'filter_greater_eq_0': 'filter_greater_eq', 'all_rows_4': 'all_rows', 'no_5': 'no', '8_6': '8', 'us viewers (millions)_7': 'us viewers ( millions )', '2.20_8': '2.20'}
|
{'eq_2': [3], 'result_3': [], 'sum_1': [2], 'filter_greater_eq_0': [1], 'all_rows_4': [0], 'no_5': [0], '8_6': [0], 'us viewers (millions)_7': [1], '2.20_8': [2]}
|
['no', 'title', 'directed by', 'written by', 'featured character ( s )', 'us viewers ( millions )', 'original air date']
|
[['1', 'tony', 'scott smith', 'bryan elsley', 'tony snyder', '3.26', 'january 17 , 2011'], ['2', 'tea', 'scott smith', 'bryan elsley', 'tea marvelli', '1.58', 'january 24 , 2011'], ['3', 'chris', 'scott smith', "jack thorne and ryan o'nan", 'chris collins', '1.45', 'january 31 , 2011'], ['4', 'cadie', 'samir rehem', 'monica padrick', 'cadie campbell', '1.19', 'february 7 , 2011'], ['5', 'stanley', 'samir rehem', 'jamie brittain and mark hammer', 'stanley lucerne', '0.96', 'february 14 , 2011'], ['6', 'abbud', 'scott smith', 'matt pelfrey', 'abbud siddiqui', '0.97', 'february 21 , 2011'], ['7', 'michelle', 'samir rehem', 'maisha closson', 'michelle richardson', '1.17', 'february 28 , 2011'], ['8', 'daisy', 'samir rehem', 'jamie brittain and bryan elsley', 'daisy valero', '1.09', 'march 7 , 2011'], ['9', 'tina', 'scott smith', 'derek harvie', 'tina nolan', '1.11', 'march 14 , 2011']]
|
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