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tokushima vortis
https://en.wikipedia.org/wiki/Tokushima_Vortis
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1276456-1.html.csv
comparative
attendance was higher during the 2010 season than the 2009 season .
{'row_1': '6', 'row_2': '5', 'col': '5', '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', 'season', '2010'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose season record fuzzily matches to 2010 .', 'tostr': 'filter_eq { all_rows ; season ; 2010 }'}, 'attendance / g'], 'result': None, 'ind': ...
greater { hop { filter_eq { all_rows ; season ; 2010 } ; attendance / g } ; hop { filter_eq { all_rows ; season ; 2009 } ; attendance / g } } = true
select the rows whose season record fuzzily matches to 2010 . take the attendance / g record of this row . select the rows whose season record fuzzily matches to 2009 . take the attendance / g record of this row . the first record is greater than the second record .
5
5
{'greater_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'season_7': 7, '2010_8': 8, 'attendance / g_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'season_11': 11, '2009_12': 12, 'attendance / g_13': 13}
{'greater_4': 'greater', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'season_7': 'season', '2010_8': '2010', 'attendance / g_9': 'attendance / g', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'season_11': 'season', '...
{'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'season_7': [0], '2010_8': [0], 'attendance / g_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'season_11': [1], '2009_12': [1], 'attendance / g_13': [3]}
['season', 'div', 'tms', 'pos', 'attendance / g', 'j league cup', "emperor 's cup"]
[['2005', 'j2', '12', '9', '4366', '-', '4th round'], ['2006', 'j2', '13', '13', '3477', '-', '4th round'], ['2007', 'j2', '13', '13', '3289', '-', '4th round'], ['2008', 'j2', '15', '15', '3862', '-', '3rd round'], ['2009', 'j2', '18', '9', '4073', '-', '2nd round'], ['2010', 'j2', '19', '8', '4614', '-', '3rd round']...
2004 scottish claymores season
https://en.wikipedia.org/wiki/2004_Scottish_Claymores_season
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-29679510-2.html.csv
ordinal
during the 2004 scottish claymores season , the 2nd largest attendance occurred on april 10th .
{'row': '2', 'col': '8', 'order': '2', 'col_other': '2', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None}
{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'attendance', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; attendance ; 2 }'}, 'date'], 'result': 'saturday , april 10', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; attendance ; 2 } ; date }'}...
eq { hop { nth_argmax { all_rows ; attendance ; 2 } ; date } ; saturday , april 10 } = true
select the row whose attendance record of all rows is 2nd maximum . the date record of this row is saturday , april 10 .
3
3
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'attendance_5': 5, '2_6': 6, 'date_7': 7, 'saturday , april 10_8': 8}
{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'attendance_5': 'attendance', '2_6': '2', 'date_7': 'date', 'saturday , april 10_8': 'saturday , april 10'}
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'attendance_5': [0], '2_6': [0], 'date_7': [1], 'saturday , april 10_8': [2]}
['week', 'date', 'kickoff', 'opponent', 'final score', 'team record', 'game site', 'attendance']
[['1', 'sunday , april 4', '4:00 pm', 'berlin thunder', 'l 14 - 20', '0 - 1', 'olympic stadium', '14257'], ['2', 'saturday , april 10', '7:00 pm', 'rhein fire', 'l 3 - 31', '0 - 2', 'arena aufschalke', '17176'], ['3', 'sunday , april 18', '2:00 pm', 'amsterdam admirals', 'l 0 - 3', '0 - 3', 'hampden park', '10971'], ['...
mark van bommel
https://en.wikipedia.org/wiki/Mark_van_Bommel
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1886415-1.html.csv
count
there were four friendly matches played by mark van bommel .
{'scope': 'all', 'criterion': 'equal', 'value': 'friendly', 'result': '4', 'col': '5', 'subset': None}
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'competition', 'friendly'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose competition record fuzzily matches to friendly .', 'tostr': 'filter_eq { all_rows ; competition ; friendly }'}], 'result': '4', 'ind':...
eq { count { filter_eq { all_rows ; competition ; friendly } } ; 4 } = true
select the rows whose competition record fuzzily matches to friendly . 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, 'competition_5': 5, 'friendly_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', 'competition_5': 'competition', 'friendly_6': 'friendly', '4_7': '4'}
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'competition_5': [0], 'friendly_6': [0], '4_7': [2]}
['date', 'venue', 'score', 'result', 'competition']
[['14 march 2001', 'mini estadi , barcelona , spain', '0 - 5', '0 - 5', '2002 wcq'], ['15 august 2001', 'white hart lane , london , england', '0 - 1', '0 - 2', 'friendly'], ['5 september 2001', 'philips stadion , eindhoven , netherlands', '2 - 0', '5 - 0', '2002 wcq'], ['5 september 2001', 'philips stadion , eindhoven ...
russian football premier league
https://en.wikipedia.org/wiki/Russian_Football_Premier_League
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1167698-1.html.csv
ordinal
alania vladikavkaz was the third team to be runner-up in the russian football premier league .
{'row': '3', 'col': '1', 'order': '3', 'col_other': '3', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None}
{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'season', '3'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; season ; 3 }'}, 'runner - up'], 'result': 'alania vladikavkaz', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; season ; 3 } ; runner - up }'...
eq { hop { nth_argmin { all_rows ; season ; 3 } ; runner - up } ; alania vladikavkaz } = true
select the row whose season record of all rows is 3rd minimum . the runner - up record of this row is alania vladikavkaz .
3
3
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'season_5': 5, '3_6': 6, 'runner - up_7': 7, 'alania vladikavkaz_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', 'season_5': 'season', '3_6': '3', 'runner - up_7': 'runner - up', 'alania vladikavkaz_8': 'alania vladikavkaz'}
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'season_5': [0], '3_6': [0], 'runner - up_7': [1], 'alania vladikavkaz_8': [2]}
['season', 'champion', 'runner - up', 'third place', 'top scorer']
[['1994', 'spartak moscow ( 3 )', 'dynamo moscow', 'lokomotiv moscow', 'igor simutenkov ( dinamo moscow , 21 goals )'], ['1995', 'alania vladikavkaz', 'lokomotiv moscow', 'spartak moscow', 'oleg veretennikov ( rotor volgograd , 25 goals )'], ['1996', 'spartak moscow ( 4 )', 'alania vladikavkaz', 'rotor volgograd', 'ale...
city of angels ( musical )
https://en.wikipedia.org/wiki/City_of_Angels_%28musical%29
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1773562-3.html.csv
unique
city of angels ( musical ) only has the result of a win once .
{'scope': 'all', 'row': '1', 'col': '5', 'col_other': 'n/a', 'criterion': 'equal', 'value': 'won', 'subset': None}
{'func': 'only', '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': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; result ; w...
only { filter_eq { all_rows ; result ; won } } = true
select the rows whose result record fuzzily matches to won . 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, 'result_4': 4, 'won_5': 5}
{'only_1': 'only', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'result_4': 'result', 'won_5': 'won'}
{'only_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'result_4': [0], 'won_5': [0]}
['year', 'award', 'category', 'nominee', 'result']
[['1994', 'laurence olivier award', 'best new musical', 'best new musical', 'won'], ['1994', 'laurence olivier award', 'best actor in a musical', 'roger allam', 'nominated'], ['1994', 'laurence olivier award', 'best actress in a musical', 'haydn gwynne', 'nominated'], ['1994', 'laurence olivier award', 'best performanc...
1925 vfl season
https://en.wikipedia.org/wiki/1925_VFL_season
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10746200-17.html.csv
count
there were 6 game venues used during the 1925 vfl season .
{'scope': 'all', 'criterion': 'all', 'value': 'n/a', 'result': '6', 'col': '5', 'subset': None}
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_all', 'args': ['all_rows', 'venue'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose venue record is arbitrary .', 'tostr': 'filter_all { all_rows ; venue }'}], 'result': '6', 'ind': 1, 'tostr': 'count { filter_all { all_rows ; venue } }', ...
eq { count { filter_all { all_rows ; venue } } ; 6 } = true
select the rows whose venue record is arbitrary . the number of such rows is 6 .
3
3
{'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_all_0': 0, 'all_rows_4': 4, 'venue_5': 5, '6_6': 6}
{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_all_0': 'filter_all', 'all_rows_4': 'all_rows', 'venue_5': 'venue', '6_6': '6'}
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_all_0': [1], 'all_rows_4': [0], 'venue_5': [0], '6_6': [2]}
['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date']
[['melbourne', '9.9 ( 63 )', 'richmond', '2.12 ( 24 )', 'mcg', '16989', '12 september 1925'], ['hawthorn', '7.13 ( 55 )', 'north melbourne', '4.6 ( 30 )', 'glenferrie oval', '8000', '12 september 1925'], ['essendon', '10.7 ( 67 )', 'st kilda', '8.10 ( 58 )', 'windy hill', '15000', '12 september 1925'], ['geelong', '14....
comparison of java remote desktop projects
https://en.wikipedia.org/wiki/Comparison_of_Java_Remote_Desktop_projects
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18418837-1.html.csv
superlative
the last date rmi technology was used on java remote desktop projects was september 16 , 2009 .
{'scope': 'subset', 'col_superlative': '3', 'row_superlative': '5', 'value_mentioned': 'yes', 'max_or_min': 'max', 'other_col': '5', 'subset': {'col': '5', 'criterion': 'equal', 'value': 'rmi'}}
{'func': 'eq', 'args': [{'func': 'max', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'technology', 'rmi'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; technology ; rmi }', 'tointer': 'select the rows whose technology record fuzzily matches to rmi .'}, 'date'], 'result': 'september 16 , 2009', ...
eq { max { filter_eq { all_rows ; technology ; rmi } ; date } ; september 16 , 2009 } = true
select the rows whose technology record fuzzily matches to rmi . the maximum date record of these rows is september 16 , 2009 .
3
3
{'eq_2': 2, 'result_3': 3, 'max_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'technology_5': 5, 'rmi_6': 6, 'date_7': 7, 'september 16 , 2009_8': 8}
{'eq_2': 'eq', 'result_3': 'true', 'max_1': 'max', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'technology_5': 'technology', 'rmi_6': 'rmi', 'date_7': 'date', 'september 16 , 2009_8': 'september 16 , 2009'}
{'eq_2': [3], 'result_3': [], 'max_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'technology_5': [0], 'rmi_6': [0], 'date_7': [1], 'september 16 , 2009_8': [2]}
['project', 'license', 'date', 'protocol', 'technology', 'server', 'client', 'web client', 'multiple sessions', 'encryption', 'authentication', 'data compression', 'image quality', 'color quality', 'file transfer', 'clipboard transfer', 'chat', 'relay', 'http tunnel', 'proxy']
[['ajax remote desktop viewer ( ajaxrd )', 'proprietary', 'june 24 , 2006', 'proprietary', 'socket', '✓', 'x', '✓', '✓', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'x'], ['dayon !', 'gpl', 'january 3 , 2009', 'proprietary', 'socket', '✓', '✓', 'x', 'x', 'x', 'x', '✓', '✓', '✓', 'x', 'x', 'x', 'x', 'x', 'x'], ['g...
merom ( microprocessor )
https://en.wikipedia.org/wiki/Merom_%28microprocessor%29
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-24099916-1.html.csv
ordinal
of the merom microprocessors , the mobile core 2 extreme had the most tdp at 44w .
{'row': '5', 'col': '7', 'order': '1', 'col_other': '2', 'max_or_min': 'max_to_min', 'value_mentioned': 'yes', 'scope': 'all', 'subset': None}
{'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'nth_max', 'args': ['all_rows', 'tdp', '1'], 'result': '44 w', 'ind': 0, 'tostr': 'nth_max { all_rows ; tdp ; 1 }', 'tointer': 'the 1st maximum tdp record of all rows is 44 w .'}, '44 w'], 'result': True, 'ind': 1, 'tostr': 'eq { nth_max { all_rows ; tdp ; 1 } ;...
and { eq { nth_max { all_rows ; tdp ; 1 } ; 44 w } ; eq { hop { nth_argmax { all_rows ; tdp ; 1 } ; brand name } ; mobile core 2 extreme } } = true
the 1st maximum tdp record of all rows is 44 w . the brand name record of the row with 1st maximum tdp record is mobile core 2 extreme .
6
6
{'and_5': 5, 'result_6': 6, 'eq_1': 1, 'nth_max_0': 0, 'all_rows_7': 7, 'tdp_8': 8, '1_9': 9, '44 w_10': 10, 'str_eq_4': 4, 'str_hop_3': 3, 'nth_argmax_2': 2, 'all_rows_11': 11, 'tdp_12': 12, '1_13': 13, 'brand name_14': 14, 'mobile core 2 extreme_15': 15}
{'and_5': 'and', 'result_6': 'true', 'eq_1': 'eq', 'nth_max_0': 'nth_max', 'all_rows_7': 'all_rows', 'tdp_8': 'tdp', '1_9': '1', '44 w_10': '44 w', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'nth_argmax_2': 'nth_argmax', 'all_rows_11': 'all_rows', 'tdp_12': 'tdp', '1_13': '1', 'brand name_14': 'brand name', 'mobile ...
{'and_5': [6], 'result_6': [], 'eq_1': [5], 'nth_max_0': [1], 'all_rows_7': [0], 'tdp_8': [0], '1_9': [0], '44 w_10': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'nth_argmax_2': [3], 'all_rows_11': [2], 'tdp_12': [2], '1_13': [2], 'brand name_14': [3], 'mobile core 2 extreme_15': [4]}
['processor', 'brand name', 'model ( list )', 'cores', 'l2 cache', 'socket', 'tdp']
[['merom - l', 'mobile core 2 solo', 'u2xxx', '1', '2 mib', 'bga479', '5.5 w'], ['merom - 2 m', 'mobile core 2 duo', 'u7xxx', '2', '2 mib', 'bga479', '10 w'], ['merom', 'mobile core 2 duo', 'l7xxx', '2', '4 mib', 'bga479', '17 w'], ['merom merom - 2 m', 'mobile core 2 duo', 't5xxx t7xxx', '2', '2 - 4 mib', 'socket m so...
1986 - 87 segunda división
https://en.wikipedia.org/wiki/1986%E2%80%9387_Segunda_Divisi%C3%B3n
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12109851-2.html.csv
count
4 clubs in the 1986 - 87 segunda división had 13 losses .
{'scope': 'all', 'criterion': 'equal', 'value': '13', 'result': '4', 'col': '7', 'subset': None}
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'losses', '13'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose losses record is equal to 13 .', 'tostr': 'filter_eq { all_rows ; losses ; 13 }'}], 'result': '4', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ;...
eq { count { filter_eq { all_rows ; losses ; 13 } } ; 4 } = true
select the rows whose losses record is equal to 13 . 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, 'losses_5': 5, '13_6': 6, '4_7': 7}
{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'losses_5': 'losses', '13_6': '13', '4_7': '4'}
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'losses_5': [0], '13_6': [0], '4_7': [2]}
['position', 'club', 'played', 'points', 'wins', 'draws', 'losses', 'goals for', 'goals against', 'goal difference']
[['1', 'valencia cf', '34', '46 + 12', '19', '8', '7', '53', '26', '+ 27'], ['2', 'deportivo de la coruña', '34', '43 + 9', '16', '11', '7', '46', '33', '+ 13'], ['3', 'cd logroñés', '34', '41 + 7', '16', '9', '9', '46', '33', '+ 13'], ['4', 'celta de vigo', '34', '40 + 6', '17', '6', '11', '56', '35', '+ 21'], ['5', '...
28th united states congress
https://en.wikipedia.org/wiki/28th_United_States_Congress
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-225206-3.html.csv
majority
the majority of 28th united states congress seats that were vacated were filled during the term .
{'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': 'elected', 'subset': None}
{'func': 'most_str_eq', 'args': ['all_rows', 'date of successors formal installation', 'elected'], 'result': True, 'ind': 0, 'tointer': 'for the date of successors formal installation records of all rows , most of them fuzzily match to elected .', 'tostr': 'most_eq { all_rows ; date of successors formal installation ; ...
most_eq { all_rows ; date of successors formal installation ; elected } = true
for the date of successors formal installation records of all rows , most of them fuzzily match to elected .
1
1
{'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'date of successors formal installation_3': 3, 'elected_4': 4}
{'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'date of successors formal installation_3': 'date of successors formal installation', 'elected_4': 'elected'}
{'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'date of successors formal installation_3': [0], 'elected_4': [0]}
['state ( class )', 'vacator', 'reason for change', 'successor', 'date of successors formal installation']
[['tennessee ( 2 )', 'vacant', 'failure to elect', 'spencer jarnagin ( w )', 'elected october 17 , 1843'], ['maine ( 1 )', 'vacant', 'rep reuel williams resigned in previous congress', 'john fairfield ( d )', 'elected december 4 , 1843'], ['illinois ( 2 )', 'samuel mcroberts ( d )', 'died march 27 , 1843', 'james sempl...
2010 - 11 detroit pistons season
https://en.wikipedia.org/wiki/2010%E2%80%9311_Detroit_Pistons_season
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27755603-11.html.csv
count
greg monroe had the high rebounds 4 times in the 2010-11 detroit pistons season .
{'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'greg monroe', 'result': '4', 'col': '6', 'subset': None}
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'high rebounds', 'greg monroe'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose high rebounds record fuzzily matches to greg monroe .', 'tostr': 'filter_eq { all_rows ; high rebounds ; greg monroe }'}], 'resul...
eq { count { filter_eq { all_rows ; high rebounds ; greg monroe } } ; 4 } = true
select the rows whose high rebounds record fuzzily matches to greg monroe . 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, 'high rebounds_5': 5, 'greg monroe_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', 'high rebounds_5': 'high rebounds', 'greg monroe_6': 'greg monroe', '4_7': '4'}
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'high rebounds_5': [0], 'greg monroe_6': [0], '4_7': [2]}
['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record']
[['75', 'april 1', 'chicago', 'l 96 - 101 ( ot )', 'richard hamilton ( 30 )', 'greg monroe ( 9 )', 'tayshaun prince ( 6 )', 'the palace of auburn hills 22076', '26 - 49'], ['77', 'april 5', 'washington', 'l 105 - 107 ( ot )', 'greg monroe ( 22 )', 'greg monroe ( 14 )', 'tracy mcgrady ( 6 )', 'verizon center 18131', '26...
chiefs - raiders rivalry
https://en.wikipedia.org/wiki/Chiefs%E2%80%93Raiders_rivalry
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11840325-8.html.csv
majority
between 2010 and 2013 , kansas city lost most of their games against oakland .
{'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'kansas city chiefs', 'subset': None}
{'func': 'most_str_eq', 'args': ['all_rows', 'loser', 'kansas city chiefs'], 'result': True, 'ind': 0, 'tointer': 'for the loser records of all rows , most of them fuzzily match to kansas city chiefs .', 'tostr': 'most_eq { all_rows ; loser ; kansas city chiefs } = true'}
most_eq { all_rows ; loser ; kansas city chiefs } = true
for the loser records of all rows , most of them fuzzily match to kansas city chiefs .
1
1
{'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'loser_3': 3, 'kansas city chiefs_4': 4}
{'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'loser_3': 'loser', 'kansas city chiefs_4': 'kansas city chiefs'}
{'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'loser_3': [0], 'kansas city chiefs_4': [0]}
['year', 'date', 'winner', 'result', 'loser', 'location']
[['2010', 'november 7', 'oakland raiders', '23 - 20 ( ot )', 'kansas city chiefs', 'oakland - alameda county coliseum'], ['2010', 'january 2 ( 2011 )', 'oakland raiders', '31 - 10', 'kansas city chiefs', 'arrowhead stadium'], ['2011', 'october 23', 'kansas city chiefs', '28 - 0', 'oakland raiders', 'oco coliseum'], ['2...
list of sumo record holders
https://en.wikipedia.org/wiki/List_of_sumo_record_holders
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17634218-20.html.csv
aggregation
the average number of tournaments for the sumo record holders is 11.46 .
{'scope': 'all', 'col': '2', 'type': 'average', 'result': '11.46', 'subset': None}
{'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'tournaments'], 'result': '11.46', 'ind': 0, 'tostr': 'avg { all_rows ; tournaments }'}, '11.46'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; tournaments } ; 11.46 } = true', 'tointer': 'the average of the tournaments record of all ...
round_eq { avg { all_rows ; tournaments } ; 11.46 } = true
the average of the tournaments record of all rows is 11.46 .
2
2
{'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'tournaments_4': 4, '11.46_5': 5}
{'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'tournaments_4': 'tournaments', '11.46_5': '11.46'}
{'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'tournaments_4': [0], '11.46_5': [1]}
['name', 'tournaments', 'pro debut', 'top division debut', 'highest rank']
[['jōkōryū', '9', 'may 2011', 'november 2012', 'maegashira 7'], ['ōsunaarashi', '10', 'march 2012', 'november 2013', 'maegashira 15'], ['kotoōshū', '11', 'november 2002', 'september 2004', 'ōzeki'], ['aran', '11', 'january 2007', 'november 2008', 'sekiwake'], ['itai', '12', 'september 1978', 'september 1980', 'komusubi...
the whole thing 's started
https://en.wikipedia.org/wiki/The_Whole_Thing%27s_Started
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17071146-1.html.csv
superlative
the longest 7 " single release of the album the whole thing 's started is empty pages .
{'scope': 'all', 'col_superlative': '3', 'row_superlative': '6', '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', 'length'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; length }'}, 'tracks'], 'result': 'empty pages', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; length } ; tracks }'}, 'empty pages'], 'result': True, 'ind': ...
eq { hop { argmax { all_rows ; length } ; tracks } ; empty pages } = true
select the row whose length record of all rows is maximum . the tracks record of this row is empty pages .
3
3
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'length_5': 5, 'tracks_6': 6, 'empty pages_7': 7}
{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'length_5': 'length', 'tracks_6': 'tracks', 'empty pages_7': 'empty pages'}
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'length_5': [0], 'tracks_6': [1], 'empty pages_7': [2]}
['date', 'tracks', 'length', 'label', 'catalog']
[['1977', 'do what you do', '3:47', 'cbs', 'ba 222304'], ['1977', "it 's automatic", '2:57', 'cbs', 'ba 222304'], ['1977', "that 's how the whole thing started", '4:03', 'cbs', 'ba 222325'], ['1977', "there 's nothing i can do", '3:38', 'cbs', 'ba 222325'], ['1978', 'do it again', '3:35', 'columbia', 'c4 - 8217'], ['19...
list of mr. belvedere episodes
https://en.wikipedia.org/wiki/List_of_Mr._Belvedere_episodes
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-20967430-3.html.csv
majority
all of the mr. belvedere episodes were directed by noam pitlik .
{'scope': 'all', 'col': '4', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'noam pitlik', 'subset': None}
{'func': 'all_str_eq', 'args': ['all_rows', 'directed by', 'noam pitlik'], 'result': True, 'ind': 0, 'tointer': 'for the directed by records of all rows , all of them fuzzily match to noam pitlik .', 'tostr': 'all_eq { all_rows ; directed by ; noam pitlik } = true'}
all_eq { all_rows ; directed by ; noam pitlik } = true
for the directed by records of all rows , all of them fuzzily match to noam pitlik .
1
1
{'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'directed by_3': 3, 'noam pitlik_4': 4}
{'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'directed by_3': 'directed by', 'noam pitlik_4': 'noam pitlik'}
{'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'directed by_3': [0], 'noam pitlik_4': [0]}
['ep', 'season', 'title', 'directed by', 'written by', 'original air date', 'prod code']
[['30', '1', 'the thief', 'noam pitlik', 'jeffrey ferro & fredric weiss', 'september 26 , 1986', '5a03'], ['31', '2', 'grandma', 'noam pitlik', 'frank dungan & jeff stein & tony sheehan', 'october 03 , 1986', '5a04'], ['32', '3', 'debut', 'noam pitlik', 'fredric weiss & jeffrey ferro', 'october 17 , 1986', '5a05'], ['3...
1966 american football league draft
https://en.wikipedia.org/wiki/1966_American_Football_League_Draft
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17706792-1.html.csv
count
three running backs were drafted in the 1966 american football league draft .
{'scope': 'all', 'criterion': 'equal', 'value': 'running back', 'result': '3', 'col': '4', 'subset': None}
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'position', 'running back'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose position record fuzzily matches to running back .', 'tostr': 'filter_eq { all_rows ; position ; running back }'}], 'result': '3', 'in...
eq { count { filter_eq { all_rows ; position ; running back } } ; 3 } = true
select the rows whose position record fuzzily matches to running back . 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, 'position_5': 5, 'running back_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', 'position_5': 'position', 'running back_6': 'running back', '3_7': '3'}
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'position_5': [0], 'running back_6': [0], '3_7': [2]}
['pick', 'afl team', 'player', 'position', 'college']
[['1', 'miami dolphins', 'jim grabowski', 'running back', 'illinois'], ['2', 'miami dolphins', 'rick norton', 'quarterback', 'kentucky'], ['3', 'boston patriots', 'karl singer', 'offensive tackle', 'purdue'], ['4', 'denver broncos', 'jerry shay', 'offensive tackle', 'purdue'], ['5', 'houston oilers', 'tommy nobis', 'li...
usa today all - usa high school baseball team
https://en.wikipedia.org/wiki/USA_Today_All-USA_high_school_baseball_team
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-11677100-3.html.csv
count
two of the players of the usa high school baseball team were drafted on to the pirates .
{'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'pirates', 'result': '2', 'col': '5', 'subset': None}
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'mlb draft', 'pirates'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose mlb draft record fuzzily matches to pirates .', 'tostr': 'filter_eq { all_rows ; mlb draft ; pirates }'}], 'result': '2', 'ind': 1, 'tost...
eq { count { filter_eq { all_rows ; mlb draft ; pirates } } ; 2 } = true
select the rows whose mlb draft record fuzzily matches to pirates . 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, 'mlb draft_5': 5, 'pirates_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', 'mlb draft_5': 'mlb draft', 'pirates_6': 'pirates', '2_7': '2'}
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'mlb draft_5': [0], 'pirates_6': [0], '2_7': [2]}
['player', 'position', 'school', 'hometown', 'mlb draft']
[['ben davis', 'catcher', 'malvern prep', 'malvern , pa', '1st round - 2nd pick of 1995 draft ( padres )'], ['chad hutchinson', 'pitcher', 'torrey pines high school', 'san diego , ca', 'attended stanford'], ['kerry wood', 'pitcher', 'grand prairie high school', 'grand prairie , tx', '1st round - 4th pick of 1995 draft ...
united states house of representatives elections , 1950
https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1950
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1342198-33.html.csv
count
of the incumbents who were first elected to the united states house of representatives in the 1930 " s , only 1 was unopposed in the 1950 election .
{'scope': 'subset', 'criterion': 'fuzzily_match', 'value': 'unopposed', 'result': '1', 'col': '6', 'subset': {'col': '4', 'criterion': 'fuzzily_match', 'value': '193'}}
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'first elected', '193'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; first elected ; 193 }', 'tointer': 'select the rows whose first elected record fuzzily matches to 193 ....
eq { count { filter_eq { filter_eq { all_rows ; first elected ; 193 } ; candidates ; unopposed } } ; 1 } = true
select the rows whose first elected record fuzzily matches to 193 . among these rows , select the rows whose candidates record fuzzily matches to unopposed . 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, 'first elected_6': 6, '193_7': 7, 'candidates_8': 8, 'unopposed_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', 'first elected_6': 'first elected', '193_7': '193', 'candidates_8': 'candidates', 'unopposed_9': 'unopposed', '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], 'first elected_6': [0], '193_7': [0], 'candidates_8': [1], 'unopposed_9': [1], '1_10': [3]}
['district', 'incumbent', 'party', 'first elected', 'result', 'candidates']
[['north carolina 2', 'john h kerr', 'democratic', '1923', 're - elected', 'john h kerr ( d ) unopposed'], ['north carolina 3', 'graham arthur barden', 'democratic', '1934', 're - elected', 'graham arthur barden ( d ) unopposed'], ['north carolina 4', 'harold d cooley', 'democratic', '1934', 're - elected', 'harold d c...
little east conference
https://en.wikipedia.org/wiki/Little_East_Conference
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1974545-2.html.csv
unique
only salem state university has a men 's lacrosse team among the sports teams listed .
{'scope': 'all', 'row': '4', 'col': '8', 'col_other': '1', 'criterion': 'equal', 'value': "men 's lacrosse", 'subset': None}
{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'lec sport', "men 's lacrosse"], 'result': None, 'ind': 0, 'tointer': "select the rows whose lec sport record fuzzily matches to men 's lacrosse .", 'tostr': "filter_eq { all_rows ; lec sport ; men 's lacrosse }"}], 'resul...
and { only { filter_eq { all_rows ; lec sport ; men 's lacrosse } } ; eq { hop { filter_eq { all_rows ; lec sport ; men 's lacrosse } ; institution } ; salem state university } } = true
select the rows whose lec sport record fuzzily matches to men 's lacrosse . there is only one such row in the table . the institution record of this unqiue row is salem state university .
6
5
{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'lec sport_7': 7, "men's lacrosse_8": 8, 'str_eq_3': 3, 'str_hop_2': 2, 'institution_9': 9, 'salem state university_10': 10}
{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'lec sport_7': 'lec sport', "men's lacrosse_8": "men 's lacrosse", 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'institution_9': 'institution', 'salem state university_10': 'salem state university'}
{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'lec sport_7': [0], "men's lacrosse_8": [0], 'str_eq_3': [4], 'str_hop_2': [3], 'institution_9': [2], 'salem state university_10': [3]}
['institution', 'location', 'nickname', 'founded', 'type', 'enrollment', 'primary conference', 'lec sport']
[['bridgewater state university', 'bridgewater , massachusetts', 'bears', '1840', 'public', '11201', 'mascac', 'field hockey tennis'], ['fitchburg state university', 'fitchburg , massachusetts', 'falcons', '1894', 'public', '5201', 'mascac', 'field hockey'], ['framingham state university', 'framingham , massachusetts',...
dave penney
https://en.wikipedia.org/wiki/Dave_Penney
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1175663-1.html.csv
aggregation
the average number of losses for dave penney was 28.2 .
{'scope': 'all', 'col': '6', 'type': 'average', 'result': '28.2', 'subset': None}
{'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'lost'], 'result': '28.2', 'ind': 0, 'tostr': 'avg { all_rows ; lost }'}, '28.2'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; lost } ; 28.2 } = true', 'tointer': 'the average of the lost record of all rows is 28.2 .'}
round_eq { avg { all_rows ; lost } ; 28.2 } = true
the average of the lost record of all rows is 28.2 .
2
2
{'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'lost_4': 4, '28.2_5': 5}
{'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'lost_4': 'lost', '28.2_5': '28.2'}
{'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'lost_4': [0], '28.2_5': [1]}
['team', 'nation', 'from', 'matches', 'drawn', 'lost', 'win %']
[['doncaster rovers', 'england', '22 april 2000', '6', '1', '1', '66.7'], ['doncaster rovers', 'england', '27 december 2001', '241', '62', '65', '47.3'], ['darlington', 'england', '30 october 2006', '139', '35', '44', '43.2'], ['oldham athletic', 'england', '30 april 2009', '48', '13', '22', '27.1'], ['bristol rovers',...
1988 los angeles rams season
https://en.wikipedia.org/wiki/1988_Los_Angeles_Rams_season
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11157007-1.html.csv
count
in the 1988 los angeles rams season , three of the games were in the month of december .
{'scope': 'all', 'criterion': 'equal', 'value': 'december', 'result': '3', 'col': '2', 'subset': None}
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', 'december'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose date record fuzzily matches to december .', 'tostr': 'filter_eq { all_rows ; date ; december }'}], 'result': '3', 'ind': 1, 'tostr': 'count {...
eq { count { filter_eq { all_rows ; date ; december } } ; 3 } = true
select the rows whose date record fuzzily matches to december . 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, 'date_5': 5, 'december_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', 'date_5': 'date', 'december_6': 'december', '3_7': '3'}
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'date_5': [0], 'december_6': [0], '3_7': [2]}
['week', 'date', 'opponent', 'result', 'attendance']
[['1', 'september 4 , 1988', 'green bay packers', 'w 34 - 7', '53769'], ['2', 'september 11 , 1988', 'detroit lions', 'w 17 - 10', '46262'], ['3', 'september 18 , 1988', 'los angeles raiders', 'w 22 - 17', '84870'], ['4', 'september 25 , 1988', 'new york giants', 'w 45 - 31', '75617'], ['5', 'october 2 , 1988', 'phoeni...
1998 formula one season
https://en.wikipedia.org/wiki/1998_Formula_One_season
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1137694-3.html.csv
unique
in the 1998 formula one season , when mika häkkinen had the pole position , the only time damon hill was the winning driver was in round 13 .
{'scope': 'subset', 'row': '13', 'col': '5', 'col_other': '1', 'criterion': 'equal', 'value': 'damon hill', 'subset': {'col': '3', 'criterion': 'equal', 'value': 'mika häkkinen'}}
{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'pole position', 'mika häkkinen'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; pole position ; mika häkkinen }', 'tointer': 'select the rows whose pole position record fuzz...
and { only { filter_eq { filter_eq { all_rows ; pole position ; mika häkkinen } ; winning driver ; damon hill } } ; eq { hop { filter_eq { filter_eq { all_rows ; pole position ; mika häkkinen } ; winning driver ; damon hill } ; round } ; 13 } } = true
select the rows whose pole position record fuzzily matches to mika häkkinen . among these rows , select the rows whose winning driver record fuzzily matches to damon hill . there is only one such row in the table . the round record of this unqiue row is 13 .
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, 'pole position_8': 8, 'mika häkkinen_9': 9, 'winning driver_10': 10, 'damon hill_11': 11, 'eq_4': 4, 'num_hop_3': 3, 'round_12': 12, '13_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', 'pole position_8': 'pole position', 'mika häkkinen_9': 'mika häkkinen', 'winning driver_10': 'winning driver', 'damon hill_11': 'damon hill', 'eq_4': 'eq', 'num_hop_3'...
{'and_5': [6], 'result_6': [], 'only_2': [5], 'filter_str_eq_1': [2, 3], 'filter_str_eq_0': [1], 'all_rows_7': [0], 'pole position_8': [0], 'mika häkkinen_9': [0], 'winning driver_10': [1], 'damon hill_11': [1], 'eq_4': [5], 'num_hop_3': [4], 'round_12': [3], '13_13': [4]}
['round', 'grand prix', 'pole position', 'fastest lap', 'winning driver', 'winning constructor', 'report']
[['1', 'australian grand prix', 'mika häkkinen', 'mika häkkinen', 'mika häkkinen', 'mclaren - mercedes', 'report'], ['2', 'brazilian grand prix', 'mika häkkinen', 'mika häkkinen', 'mika häkkinen', 'mclaren - mercedes', 'report'], ['3', 'argentine grand prix', 'david coulthard', 'alexander wurz', 'michael schumacher', '...
solids with icosahedral symmetry
https://en.wikipedia.org/wiki/Solids_with_icosahedral_symmetry
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13727381-6.html.csv
superlative
the truncated icosidodecahedron has the highest number of edges of all dual archimedean solids .
{'scope': 'all', 'col_superlative': '4', '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', 'edges'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; edges }'}, 'dual archimedean solid'], 'result': 'truncated icosidodecahedron', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; edges } ; dual archimedean solid...
eq { hop { argmax { all_rows ; edges } ; dual archimedean solid } ; truncated icosidodecahedron } = true
select the row whose edges record of all rows is maximum . the dual archimedean solid record of this row is truncated icosidodecahedron .
3
3
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'edges_5': 5, 'dual archimedean solid_6': 6, 'truncated icosidodecahedron_7': 7}
{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'edges_5': 'edges', 'dual archimedean solid_6': 'dual archimedean solid', 'truncated icosidodecahedron_7': 'truncated icosidodecahedron'}
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'edges_5': [0], 'dual archimedean solid_6': [1], 'truncated icosidodecahedron_7': [2]}
['picture', 'dual archimedean solid', 'faces', 'edges', 'vertices', 'face polygon']
[['( video )', 'icosidodecahedron', '30', '60', '32', 'rhombus'], ['( video )', 'truncated dodecahedron', '60', '90', '32', 'isosceles triangle'], ['( video )', 'truncated icosahedron', '60', '90', '32', 'isosceles triangle'], ['( video )', 'rhombicosidodecahedron', '60', '120', '62', 'kite'], ['( video )', 'truncated ...
list of members - elect of the united states house of representatives who never took their seats
https://en.wikipedia.org/wiki/List_of_members-elect_of_the_United_States_House_of_Representatives_who_never_took_their_seats
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-14158567-1.html.csv
majority
the majority of member-elect representatives did not take their seats due to dying .
{'scope': 'all', 'col': '6', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': 'died', 'subset': None}
{'func': 'most_str_eq', 'args': ['all_rows', 'reason for non - seating', 'died'], 'result': True, 'ind': 0, 'tointer': 'for the reason for non - seating records of all rows , most of them fuzzily match to died .', 'tostr': 'most_eq { all_rows ; reason for non - seating ; died } = true'}
most_eq { all_rows ; reason for non - seating ; died } = true
for the reason for non - seating records of all rows , most of them fuzzily match to died .
1
1
{'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'reason for non - seating_3': 3, 'died_4': 4}
{'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'reason for non - seating_3': 'reason for non - seating', 'died_4': 'died'}
{'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'reason for non - seating_3': [0], 'died_4': [0]}
['member - elect', 'party', 'district', 'election date', 'congress', 'reason for non - seating']
[['augustus f allen', 'democratic', 'ny - 33', 'november 3 , 1874', '44th', 'died january 22 , 1875'], ['andrew j campbell', 'republican', 'ny - 10', 'november 5 , 1894', '54th', 'died december 6 , 1894'], ['john cantine', 'democratic - republican', 'ny - 7', 'april 27 to 29 , 1802', '8th', 'elected , but declined to t...
2006 u.s. open ( golf )
https://en.wikipedia.org/wiki/2006_U.S._Open_%28golf%29
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12523044-4.html.csv
aggregation
the average score of players in the 2006 u.s. open is 70.46 .
{'scope': 'all', 'col': '4', 'type': 'average', 'result': '70.46', 'subset': None}
{'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'score'], 'result': '70.46', 'ind': 0, 'tostr': 'avg { all_rows ; score }'}, '70.46'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; score } ; 70.46 } = true', 'tointer': 'the average of the score record of all rows is 70.46 .'}
round_eq { avg { all_rows ; score } ; 70.46 } = true
the average of the score record of all rows is 70.46 .
2
2
{'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'score_4': 4, '70.46_5': 5}
{'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'score_4': 'score', '70.46_5': '70.46'}
{'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'score_4': [0], '70.46_5': [1]}
['place', 'player', 'country', 'score', 'to par']
[['1', 'colin montgomerie', 'scotland', '69', '- 1'], ['t2', 'jim furyk', 'united states', '70', 'e'], ['t2', 'david howell', 'england', '70', 'e'], ['t2', 'miguel ángel jiménez', 'spain', '70', 'e'], ['t2', 'phil mickelson', 'united states', '70', 'e'], ['t2', 'steve stricker', 'united states', '70', 'e'], ['t7', 'joh...
1922 u.s. open ( golf )
https://en.wikipedia.org/wiki/1922_U.S._Open_%28golf%29
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18007045-1.html.csv
aggregation
in the 1922 u.s. open , the average number of strokes to par is 13.4 .
{'scope': 'all', 'col': '5', 'type': 'average', 'result': '13.4', 'subset': None}
{'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'to par'], 'result': '13.4', 'ind': 0, 'tostr': 'avg { all_rows ; to par }'}, '13.4'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; to par } ; 13.4 } = true', 'tointer': 'the average of the to par record of all rows is 13.4 .'}
round_eq { avg { all_rows ; to par } ; 13.4 } = true
the average of the to par record of all rows is 13.4 .
2
2
{'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'to par_4': 4, '13.4_5': 5}
{'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'to par_4': 'to par', '13.4_5': '13.4'}
{'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'to par_4': [0], '13.4_5': [1]}
['place', 'player', 'country', 'score', 'to par', 'money']
[['1', 'gene sarazen', 'united states', '72 + 73 + 75 + 68 = 288', '+ 8', '500'], ['t2', 'john black', 'scotland', '71 + 71 + 75 + 72 = 289', '+ 9', '300'], ['t2', 'bobby jones ( a )', 'united states', '74 + 72 + 70 + 73 = 289', '+ 9', '0'], ['4', 'bill mehlhorn', 'united states', '73 + 71 + 72 + 74 = 290', '+ 10', '20...
varvara lepchenko
https://en.wikipedia.org/wiki/Varvara_Lepchenko
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10577658-3.html.csv
majority
the majority of tennis tournaments that varvara lepchenko played in were on a hard surface .
{'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'hard', 'subset': None}
{'func': 'most_str_eq', 'args': ['all_rows', 'surface', 'hard'], 'result': True, 'ind': 0, 'tointer': 'for the surface records of all rows , most of them fuzzily match to hard .', 'tostr': 'most_eq { all_rows ; surface ; hard } = true'}
most_eq { all_rows ; surface ; hard } = true
for the surface records of all rows , most of them fuzzily match to hard .
1
1
{'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'surface_3': 3, 'hard_4': 4}
{'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'surface_3': 'surface', 'hard_4': 'hard'}
{'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'surface_3': [0], 'hard_4': [0]}
['outcome', 'date', 'surface', 'partner', 'opponents', 'score']
[['runner - up', '21 april 2003', 'clay', 'julie ditty', 'milagros sequera christina wheeler', '7 - 5 1 - 6 2 - 6'], ['winner', '31 may 2004', 'hard', 'cory - ann avants', 'tanner cochran jaslyn hewitt', '6 - 2 3 - 6 6 - 3'], ['runner - up', '7 june 2004', 'hard', 'cory - ann avants', 'angela haynes diana ospina', '0 -...
united states house of representatives elections , 1920
https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1920
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1342451-16.html.csv
majority
all of the incumbents in the 1920 united states house of representatives elections were with the democratic party .
{'scope': 'all', 'col': '3', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'democratic', 'subset': None}
{'func': 'all_str_eq', 'args': ['all_rows', 'party', 'democratic'], 'result': True, 'ind': 0, 'tointer': 'for the party records of all rows , all of them fuzzily match to democratic .', 'tostr': 'all_eq { all_rows ; party ; democratic } = true'}
all_eq { all_rows ; party ; democratic } = true
for the party records of all rows , all of them fuzzily match to democratic .
1
1
{'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'party_3': 3, 'democratic_4': 4}
{'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'party_3': 'party', 'democratic_4': 'democratic'}
{'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'party_3': [0], 'democratic_4': [0]}
['district', 'incumbent', 'party', 'first elected', 'result', 'candidates']
[['louisiana 1', "james o'connor", 'democratic', '1918', 're - elected', "james o'connor ( d ) unopposed"], ['louisiana 2', 'henry garland dupré', 'democratic', '1908', 're - elected', 'henry garland dupré ( d ) unopposed'], ['louisiana 3', 'whitmell p martin', 'democratic', '1914', 're - elected', 'whitmell p martin (...
lone star alliance
https://en.wikipedia.org/wiki/Lone_Star_Alliance
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-28243691-1.html.csv
comparative
the university of texas at austin has a larger enrollment than texas christian university .
{'row_1': '12', 'row_2': '9', 'col': '5', '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', 'institution', 'university of texas at austin'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose institution record fuzzily matches to university of texas at austin .', 'tostr': 'filter_eq { all_rows ; i...
greater { hop { filter_eq { all_rows ; institution ; university of texas at austin } ; enrollment } ; hop { filter_eq { all_rows ; institution ; texas christian university } ; enrollment } } = true
select the rows whose institution record fuzzily matches to university of texas at austin . take the enrollment record of this row . select the rows whose institution record fuzzily matches to texas christian university . take the enrollment record of this row . the first record is greater than the second record .
5
5
{'greater_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'institution_7': 7, 'university of texas at austin_8': 8, 'enrollment_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'institution_11': 11, 'texas christian university_12': 12, 'enrollment_13': 13}
{'greater_4': 'greater', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'institution_7': 'institution', 'university of texas at austin_8': 'university of texas at austin', 'enrollment_9': 'enrollment', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq',...
{'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'institution_7': [0], 'university of texas at austin_8': [0], 'enrollment_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'institution_11': [1], 'texas christian university_12': [1], 'enrollment_13': [...
['institution', 'location', 'founded', 'affiliation', 'enrollment', 'team nickname', 'primary conference']
[['baylor university', 'waco , texas', '1845', 'private , baptist', '14769', 'bears', 'big 12 ( division i )'], ['university of louisiana at lafayette', 'lafayette , louisiana', '1898', 'public', '16361', "ragin ' cajuns", 'sunbelt ( division i )'], ['louisiana state university', 'baton rouge , louisiana', '1860', 'pub...
2008 australian sports sedan series
https://en.wikipedia.org/wiki/2008_Australian_Sports_Sedan_Series
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18124534-2.html.csv
count
there were only a total of 5 races in the 2008 australian sports sedan series .
{'scope': 'all', 'criterion': 'all', 'value': 'n/a', 'result': '5', 'col': '1', 'subset': None}
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_all', 'args': ['all_rows', 'race title'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose race title record is arbitrary .', 'tostr': 'filter_all { all_rows ; race title }'}], 'result': '5', 'ind': 1, 'tostr': 'count { filter_all { all_rows...
eq { count { filter_all { all_rows ; race title } } ; 5 } = true
select the rows whose race title record is arbitrary . the number of such rows is 5 .
3
3
{'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_all_0': 0, 'all_rows_4': 4, 'race title_5': 5, '5_6': 6}
{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_all_0': 'filter_all', 'all_rows_4': 'all_rows', 'race title_5': 'race title', '5_6': '5'}
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_all_0': [1], 'all_rows_4': [0], 'race title_5': [0], '5_6': [2]}
['race title', 'circuit', 'city / state', 'date', 'winner']
[['mallala', 'mallala motor sport park', 'adelaide , south australia', '1718 may', 'luke youlden'], ['phillip island', 'phillip island grand prix circuit', 'phillip island , victoria', '14 - 15 jun', 'darren hossack'], ['eastern creek', 'eastern creek raceway', 'sydney , new south wales', '12 - 13 jul', 'darren hossack...
elvis ' gold records volume 5
https://en.wikipedia.org/wiki/Elvis%27_Gold_Records_Volume_5
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15582798-3.html.csv
unique
track number four , titled moody blue , is the only song in this album that is written by mark james .
{'scope': 'all', 'row': '4', 'col': '6', 'col_other': '1,5', 'criterion': 'equal', 'value': 'mark james', 'subset': None}
{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'writer ( s )', 'mark james'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose writer ( s ) record fuzzily matches to mark james .', 'tostr': 'filter_eq { all_rows ; writer ( s ) ; mark james }'}], 'result': Tr...
and { only { filter_eq { all_rows ; writer ( s ) ; mark james } } ; and { eq { hop { filter_eq { all_rows ; writer ( s ) ; mark james } ; track } ; 4 } ; eq { hop { filter_eq { all_rows ; writer ( s ) ; mark james } ; song title } ; moody blue } } } = true
select the rows whose writer ( s ) record fuzzily matches to mark james . there is only one such row in the table . the track record of this unqiue row is 4 . the song title record of this unqiue row is moody blue .
10
8
{'and_7': 7, 'result_8': 8, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_9': 9, 'writer (s)_10': 10, 'mark james_11': 11, 'and_6': 6, 'eq_3': 3, 'num_hop_2': 2, 'track_12': 12, '4_13': 13, 'str_eq_5': 5, 'str_hop_4': 4, 'song title_14': 14, 'moody blue_15': 15}
{'and_7': 'and', 'result_8': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_9': 'all_rows', 'writer (s)_10': 'writer ( s )', 'mark james_11': 'mark james', 'and_6': 'and', 'eq_3': 'eq', 'num_hop_2': 'num_hop', 'track_12': 'track', '4_13': '4', 'str_eq_5': 'str_eq', 'str_hop_4': 'str_hop', 'song...
{'and_7': [8], 'result_8': [], 'only_1': [7], 'filter_str_eq_0': [1, 2, 4], 'all_rows_9': [0], 'writer (s)_10': [0], 'mark james_11': [0], 'and_6': [7], 'eq_3': [6], 'num_hop_2': [3], 'track_12': [2], '4_13': [3], 'str_eq_5': [6], 'str_hop_4': [5], 'song title_14': [4], 'moody blue_15': [5]}
['track', 'recorded', 'catalogue', 'release date', 'song title', 'writer ( s )', 'time']
[['1', '3 / 28 / 72', '74 - 0769', '8 / 1 / 72', 'burning love', 'dennis linde', '2:50'], ['2', '12 / 11 / 73', 'apbo 0280', '5 / 10 / 74', 'if you talk in your sleep', 'red west and johnny christopher', '2:34'], ['3', '2 / 5 / 76', 'pb 10601b', '3 / 12 / 76', 'for the heart', 'dennis linde', '3:22'], ['4', '2 / 4 / 76...
1957 formula one season
https://en.wikipedia.org/wiki/1957_Formula_One_season
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1140111-5.html.csv
count
jean behra was the winning driver four times in the 1957 formula one season .
{'scope': 'all', 'criterion': 'equal', 'value': 'jean behra', 'result': '4', 'col': '4', 'subset': None}
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'winning driver', 'jean behra'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose winning driver record fuzzily matches to jean behra .', 'tostr': 'filter_eq { all_rows ; winning driver ; jean behra }'}], 'resul...
eq { count { filter_eq { all_rows ; winning driver ; jean behra } } ; 4 } = true
select the rows whose winning driver record fuzzily matches to jean behra . 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, 'winning driver_5': 5, 'jean behra_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', 'winning driver_5': 'winning driver', 'jean behra_6': 'jean behra', '4_7': '4'}
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'winning driver_5': [0], 'jean behra_6': [0], '4_7': [2]}
['race name', 'circuit', 'date', 'winning driver', 'constructor', 'report']
[['xi gran premio ciudad de buenos aires', 'buenos aires', '27 january', 'juan manuel fangio', 'maserati', 'report'], ['vii gran premio di siracusa', 'syracuse', '7 april', 'peter collins', 'lancia - ferrari', 'report'], ['xvii pau grand prix', 'pau', '22 april', 'jean behra', 'maserati', 'report'], ['v glover trophy',...
ian woosnam
https://en.wikipedia.org/wiki/Ian_Woosnam
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1034991-8.html.csv
superlative
ian woosnam has more top 25 finishes in the open championship than any other tournament .
{'scope': 'all', 'col_superlative': '5', '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', 'top - 25'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; top - 25 }'}, 'tournament'], 'result': 'the open championship', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; top - 25 } ; tournament }'}, 'the open champ...
eq { hop { argmax { all_rows ; top - 25 } ; tournament } ; the open championship } = true
select the row whose top - 25 record of all rows is maximum . the tournament record of this row is the open championship .
3
3
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'top - 25_5': 5, 'tournament_6': 6, 'the open championship_7': 7}
{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'top - 25_5': 'top - 25', 'tournament_6': 'tournament', 'the open championship_7': 'the open championship'}
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'top - 25_5': [0], 'tournament_6': [1], 'the open championship_7': [2]}
['tournament', 'wins', 'top - 5', 'top - 10', 'top - 25', 'events', 'cuts made']
[['masters tournament', '1', '1', '1', '7', '25', '13'], ['us open', '0', '1', '2', '4', '10', '7'], ['the open championship', '0', '4', '5', '10', '23', '17'], ['pga championship', '0', '0', '2', '3', '18', '9'], ['totals', '1', '6', '10', '24', '76', '46']]
1996 - 97 toronto raptors season
https://en.wikipedia.org/wiki/1996%E2%80%9397_Toronto_Raptors_season
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-13557843-3.html.csv
aggregation
throughout the 1996-97 toronto raptors season , damon stoudamire made 95 high assists .
{'scope': 'subset', 'col': '7', 'type': 'sum', 'result': '95', 'subset': {'col': '7', 'criterion': 'fuzzily_match', 'value': 'damon stoudamire'}}
{'func': 'round_eq', 'args': [{'func': 'sum', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'high assists', 'damon stoudamire'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; high assists ; damon stoudamire }', 'tointer': 'select the rows whose high assists record fuzzily matches to damon stoudam...
round_eq { sum { filter_eq { all_rows ; high assists ; damon stoudamire } ; high assists } ; 95 } = true
select the rows whose high assists record fuzzily matches to damon stoudamire . the sum of the high assists record of these rows is 95 .
3
3
{'eq_2': 2, 'result_3': 3, 'sum_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'high assists_5': 5, 'damon stoudamire_6': 6, 'high assists_7': 7, '95_8': 8}
{'eq_2': 'eq', 'result_3': 'true', 'sum_1': 'sum', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'high assists_5': 'high assists', 'damon stoudamire_6': 'damon stoudamire', 'high assists_7': 'high assists', '95_8': '95'}
{'eq_2': [3], 'result_3': [], 'sum_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'high assists_5': [0], 'damon stoudamire_6': [0], 'high assists_7': [1], '95_8': [2]}
['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record']
[['1', 'november 1', 'new york', 'l 99 - 107 ( ot )', 'damon stoudamire ( 28 )', 'popeye jones ( 9 )', 'damon stoudamire ( 10 )', 'skydome 28457', '0 - 1'], ['2', 'november 2', 'charlotte', 'l 98 - 109 ( ot )', 'damon stoudamire ( 19 )', 'carlos rogers ( 8 )', 'damon stoudamire ( 5 )', 'charlotte coliseum 24042', '0 - ...
central collegiate lacrosse association
https://en.wikipedia.org/wiki/Central_Collegiate_Lacrosse_Association
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-28211213-2.html.csv
comparative
the enrollment at lawrence technological university is lower than the enrollment at northern michigan university .
{'row_1': '10', 'row_2': '13', 'col': '5', 'col_other': '1', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None}
{'func': 'less', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'institution', 'lawrence technological university'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose institution record fuzzily matches to lawrence technological university .', 'tostr': 'filter_eq { all_row...
less { hop { filter_eq { all_rows ; institution ; lawrence technological university } ; enrollment } ; hop { filter_eq { all_rows ; institution ; northern michigan university } ; enrollment } } = true
select the rows whose institution record fuzzily matches to lawrence technological university . take the enrollment record of this row . select the rows whose institution record fuzzily matches to northern michigan university . take the enrollment record of this row . the first record is less than the second record .
5
5
{'less_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'institution_7': 7, 'lawrence technological university_8': 8, 'enrollment_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'institution_11': 11, 'northern michigan university_12': 12, 'enrollment_13': 13}
{'less_4': 'less', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'institution_7': 'institution', 'lawrence technological university_8': 'lawrence technological university', 'enrollment_9': 'enrollment', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq...
{'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'institution_7': [0], 'lawrence technological university_8': [0], 'enrollment_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'institution_11': [1], 'northern michigan university_12': [1], 'enrollment_13'...
['institution', 'location', 'founded', 'affiliation', 'enrollment', 'team nickname', 'primary conference']
[['aquinas college', 'grand rapids , michigan', '1886', 'private', '2159', 'saints', 'whac ( naia )'], ['butler university', 'indianapolis , indiana', '1855', 'private', '4512', 'bulldogs', 'horizon ( division i )'], ['carnegie mellon university', 'pittsburgh , pennsylvania', '1900', 'private / nonsectarian', '10875', ...
2009 world rally championship season
https://en.wikipedia.org/wiki/2009_World_Rally_Championship_season
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18811741-15.html.csv
unique
sébastien loeb had the most stage wins in the 2009 world rally championship season .
{'scope': 'all', 'row': '1', 'col': '4', 'col_other': '1', 'criterion': 'equal', 'value': '7', 'subset': None}
{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'wins', '7'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose wins record is equal to 7 .', 'tostr': 'filter_eq { all_rows ; wins ; 7 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; wins ; 7...
and { only { filter_eq { all_rows ; wins ; 7 } } ; eq { hop { filter_eq { all_rows ; wins ; 7 } ; driver } ; sébastien loeb } } = true
select the rows whose wins record is equal to 7 . there is only one such row in the table . the driver record of this unqiue row is sébastien loeb .
6
5
{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'wins_7': 7, '7_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'driver_9': 9, 'sébastien loeb_10': 10}
{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'wins_7': 'wins', '7_8': '7', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'driver_9': 'driver', 'sébastien loeb_10': 'sébastien loeb'}
{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'wins_7': [0], '7_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'driver_9': [2], 'sébastien loeb_10': [3]}
['driver', 'starts', 'finishes', 'wins', 'podiums', 'stage wins', 'points']
[['sébastien loeb', '12', '11', '7', '9', '88', '93'], ['mikko hirvonen', '12', '11', '4', '11', '51', '92'], ['daniel sordo', '12', '12', '0', '7', '18', '64'], ['jari - matti latvala', '12', '10', '1', '4', '40', '41'], ['petter solberg', '10', '7', '0', '2', '10', '35'], ['henning solberg', '12', '12', '0', '2', '8'...
inside business
https://en.wikipedia.org/wiki/Inside_Business
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10888144-1.html.csv
unique
season 1 was the only season of inside business that had less than 40 episodes .
{'scope': 'all', 'row': '1', 'col': '4', 'col_other': '1', 'criterion': 'less_than', 'value': '40', 'subset': None}
{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'episodes', '40'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose episodes record is less than 40 .', 'tostr': 'filter_less { all_rows ; episodes ; 40 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_less...
and { only { filter_less { all_rows ; episodes ; 40 } } ; eq { hop { filter_less { all_rows ; episodes ; 40 } ; season no } ; 1 } } = true
select the rows whose episodes record is less than 40 . there is only one such row in the table . the season no record of this unqiue row is 1 .
6
5
{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_less_0': 0, 'all_rows_6': 6, 'episodes_7': 7, '40_8': 8, 'eq_3': 3, 'num_hop_2': 2, 'season no_9': 9, '1_10': 10}
{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_less_0': 'filter_less', 'all_rows_6': 'all_rows', 'episodes_7': 'episodes', '40_8': '40', 'eq_3': 'eq', 'num_hop_2': 'num_hop', 'season no_9': 'season no', '1_10': '1'}
{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_less_0': [1, 2], 'all_rows_6': [0], 'episodes_7': [0], '40_8': [0], 'eq_3': [4], 'num_hop_2': [3], 'season no_9': [2], '1_10': [3]}
['season no', 'season start', 'season end', 'episodes', 'host']
[['1', '4 august 2002', '8 december 2002', '19', 'alan kohler'], ['2', '9 february 2003', '30 november 2003', '41', 'alan kohler'], ['3', '15 february 2004', '5 december 2004', '41', 'alan kohler'], ['4', '13 february 2005', '4 december 2005', '42', 'alan kohler'], ['5', '12 february 2006', '10 december 2006', '43', 'a...
list of journeyman episodes
https://en.wikipedia.org/wiki/List_of_Journeyman_episodes
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-13426649-1.html.csv
count
according to the list of journeyman episodes , among the episodes written by kevin falls , 2 of them were directed by alex graves .
{'scope': 'subset', 'criterion': 'equal', 'value': 'alex graves', 'result': '2', 'col': '3', 'subset': {'col': '4', 'criterion': 'equal', 'value': 'kevin falls'}}
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'written by', 'kevin falls'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; written by ; kevin falls }', 'tointer': 'select the rows whose written by record fuzzily matches t...
eq { count { filter_eq { filter_eq { all_rows ; written by ; kevin falls } ; directed by ; alex graves } } ; 2 } = true
select the rows whose written by record fuzzily matches to kevin falls . among these rows , select the rows whose directed by record fuzzily matches to alex graves . 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, 'written by_6': 6, 'kevin falls_7': 7, 'directed by_8': 8, 'alex graves_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', 'written by_6': 'written by', 'kevin falls_7': 'kevin falls', 'directed by_8': 'directed by', 'alex graves_9': 'alex graves', '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], 'written by_6': [0], 'kevin falls_7': [0], 'directed by_8': [1], 'alex graves_9': [1], '2_10': [3]}
['', 'title', 'directed by', 'written by', 'original air date', 'production code', 'us viewers ( millions )']
[['1', 'a love of a lifetime', 'alex graves', 'kevin falls', 'september 24 , 2007', '1anj79', '9.16'], ['2', 'friendly skies', 'alex graves', 'kevin falls', 'october 1 , 2007', '1anj01', '8.23'], ['3', 'game three', 'alex graves', 'tom szentgyorgyi', 'october 8 , 2007', '1anj02', '6.94'], ['4', 'the year of the rabbit'...
jeju international airport
https://en.wikipedia.org/wiki/Jeju_International_Airport
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1783616-4.html.csv
majority
for the majority of other airports in china that jeju airport flies to , there are over 100 aircraft movements .
{'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'greater_than', 'value': '100', 'subset': None}
{'func': 'most_greater', 'args': ['all_rows', 'aircraft movements', '100'], 'result': True, 'ind': 0, 'tointer': 'for the aircraft movements records of all rows , most of them are greater than 100 .', 'tostr': 'most_greater { all_rows ; aircraft movements ; 100 } = true'}
most_greater { all_rows ; aircraft movements ; 100 } = true
for the aircraft movements records of all rows , most of them are greater than 100 .
1
1
{'most_greater_0': 0, 'result_1': 1, 'all_rows_2': 2, 'aircraft movements_3': 3, '100_4': 4}
{'most_greater_0': 'most_greater', 'result_1': 'true', 'all_rows_2': 'all_rows', 'aircraft movements_3': 'aircraft movements', '100_4': '100'}
{'most_greater_0': [1], 'result_1': [], 'all_rows_2': [0], 'aircraft movements_3': [0], '100_4': [0]}
['rank', 'airport', 'passengers', 'aircraft movements', 'carriers']
[['1', 'shanghai , china', '192701', '1465', 'china eastern airlines , jin air'], ['2', 'osaka , japan', '131338', '1157', 'jeju air , korean air'], ['3', 'tokyo , japan', '124296', '734', 'korean air'], ['4', 'beijing , china', '97055', '768', 'china eastern airlines , korean air'], ['5', 'taipei , republic of china (...
wayne gardner
https://en.wikipedia.org/wiki/Wayne_Gardner
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1861430-3.html.csv
majority
wayne gardner drove with the team rothmans honda for the majority of years .
{'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'rothmans honda', 'subset': None}
{'func': 'most_str_eq', 'args': ['all_rows', 'team', 'rothmans honda'], 'result': True, 'ind': 0, 'tointer': 'for the team records of all rows , most of them fuzzily match to rothmans honda .', 'tostr': 'most_eq { all_rows ; team ; rothmans honda } = true'}
most_eq { all_rows ; team ; rothmans honda } = true
for the team records of all rows , most of them fuzzily match to rothmans honda .
1
1
{'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'team_3': 3, 'rothmans honda_4': 4}
{'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'team_3': 'team', 'rothmans honda_4': 'rothmans honda'}
{'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'team_3': [0], 'rothmans honda_4': [0]}
['year', 'class', 'team', 'machine', 'points', 'wins']
[['1983', '500cc', 'honda britain', 'ns500', '0', '0'], ['1984', '500cc', 'honda britain', 'ns500', '33', '0'], ['1985', '500cc', 'rothmans honda', 'nsr500', '73', '0'], ['1986', '500cc', 'rothmans honda', 'nsr500', '117', '3'], ['1987', '500cc', 'rothmans honda', 'nsr500', '178', '7'], ['1988', '500cc', 'rothmans hond...
lost souls ( doves album )
https://en.wikipedia.org/wiki/Lost_Souls_%28Doves_album%29
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1523661-2.html.csv
count
a total of two versions of the lost souls album were released by astralwerks records .
{'scope': 'all', 'criterion': 'equal', 'value': 'astralwerks records', 'result': '2', 'col': '3', 'subset': None}
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'label', 'astralwerks records'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose label record fuzzily matches to astralwerks records .', 'tostr': 'filter_eq { all_rows ; label ; astralwerks records }'}], 'resul...
eq { count { filter_eq { all_rows ; label ; astralwerks records } } ; 2 } = true
select the rows whose label record fuzzily matches to astralwerks records . 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, 'label_5': 5, 'astralwerks records_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', 'label_5': 'label', 'astralwerks records_6': 'astralwerks records', '2_7': '2'}
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'label_5': [0], 'astralwerks records_6': [0], '2_7': [2]}
['country', 'date', 'label', 'format', 'catalogue']
[['united kingdom', '3 april 2000', 'heavenly records', 'cd', 'hvnlp26cd'], ['united kingdom', '3 april 2000', 'heavenly records', 'double lp ( heavyweight vinyl , gatefold sleeve )', 'hvnlp26'], ['united states', '17 october 2000', 'astralwerks records', 'cd ( 3 bonus tracks )', 'asw 50248 ( 724385024825 )'], ['united...
2011 the dominion tankard
https://en.wikipedia.org/wiki/2011_The_Dominion_Tankard
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-29565601-2.html.csv
superlative
in the dominion tankard in 2011 , the highest number of ends won was by chris gardner .
{'scope': 'all', 'col_superlative': '6', 'row_superlative': '6', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None}
{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'ends won'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; ends won }'}, 'skip ( club )'], 'result': 'chris gardner ( renfrew )', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; ends won } ; skip ( club ) }'}, 'chri...
eq { hop { argmax { all_rows ; ends won } ; skip ( club ) } ; chris gardner ( renfrew ) } = true
select the row whose ends won record of all rows is maximum . the skip ( club ) record of this row is chris gardner ( renfrew ) .
3
3
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'ends won_5': 5, 'skip (club)_6': 6, 'chris gardner (renfrew)_7': 7}
{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'ends won_5': 'ends won', 'skip (club)_6': 'skip ( club )', 'chris gardner (renfrew)_7': 'chris gardner ( renfrew )'}
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'ends won_5': [0], 'skip (club)_6': [1], 'chris gardner (renfrew)_7': [2]}
['skip ( club )', 'w', 'l', 'pf', 'pa', 'ends won', 'ends lost', 'blank ends', 'stolen ends']
[['peter corner ( brampton )', '8', '2', '69', '54', '41', '36', '8', '11'], ['glenn howard ( coldwater )', '8', '2', '79', '35', '40', '22', '8', '11'], ['greg balsdon ( loonie )', '7', '3', '80', '57', '46', '37', '5', '12'], ['john epping ( donalda )', '7', '3', '76', '64', '43', '41', '5', '10'], ['mark bice ( sarn...
1940 vfl season
https://en.wikipedia.org/wiki/1940_VFL_season
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10807253-15.html.csv
aggregation
the average crowd size during the 1940 vfl season is 12000 .
{'scope': 'all', 'col': '6', 'type': 'average', 'result': '12000', 'subset': None}
{'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'crowd'], 'result': '12000', 'ind': 0, 'tostr': 'avg { all_rows ; crowd }'}, '12000'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; crowd } ; 12000 } = true', 'tointer': 'the average of the crowd record of all rows is 12000 .'}
round_eq { avg { all_rows ; crowd } ; 12000 } = true
the average of the crowd record of all rows is 12000 .
2
2
{'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'crowd_4': 4, '12000_5': 5}
{'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'crowd_4': 'crowd', '12000_5': '12000'}
{'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'crowd_4': [0], '12000_5': [1]}
['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date']
[['hawthorn', '10.19 ( 79 )', 'south melbourne', '10.13 ( 73 )', 'glenferrie oval', '8000', '10 august 1940'], ['geelong', '12.15 ( 87 )', 'richmond', '16.11 ( 107 )', 'corio oval', '10000', '10 august 1940'], ['essendon', '10.12 ( 72 )', 'fitzroy', '10.15 ( 75 )', 'windy hill', '18000', '10 august 1940'], ['collingwoo...
eisbären berlin
https://en.wikipedia.org/wiki/Eisb%C3%A4ren_Berlin
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1790061-7.html.csv
count
among the seasons when eisbären berlin played more than 48 games , 2 of the years they scored exactly 27 goals .
{'scope': 'subset', 'criterion': 'equal', 'value': '27', 'result': '2', 'col': '4', 'subset': {'col': '3', 'criterion': 'greater_than', 'value': '48'}}
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'games', '48'], 'result': None, 'ind': 0, 'tostr': 'filter_greater { all_rows ; games ; 48 }', 'tointer': 'select the rows whose games record is greater than 48 .'}, 'goals', '27'], 'result'...
eq { count { filter_eq { filter_greater { all_rows ; games ; 48 } ; goals ; 27 } } ; 2 } = true
select the rows whose games record is greater than 48 . among these rows , select the rows whose goals record is equal to 27 . the number of such rows is 2 .
4
4
{'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_eq_1': 1, 'filter_greater_0': 0, 'all_rows_5': 5, 'games_6': 6, '48_7': 7, 'goals_8': 8, '27_9': 9, '2_10': 10}
{'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_eq_1': 'filter_eq', 'filter_greater_0': 'filter_greater', 'all_rows_5': 'all_rows', 'games_6': 'games', '48_7': '48', 'goals_8': 'goals', '27_9': '27', '2_10': '2'}
{'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_eq_1': [2], 'filter_greater_0': [1], 'all_rows_5': [0], 'games_6': [0], '48_7': [0], 'goals_8': [1], '27_9': [1], '2_10': [3]}
['name', 'season', 'games', 'goals', 'assists', 'points']
[['name', 'season', 'games', 'goals', 'assists', 'points'], ['mark jooris', '1991 - 1992', '50', '54', '69', '123'], ['steve walker', '2007 - 2008', '53', '27', '58', '85'], ['jiří dopita', '1994 - 1995', '42', '28', '40', '68'], ['thomas graul', '1991 - 1992', '47', '28', '32', '60'], ['alex hicks', '2000 - 2001', '56...
2009 copa sudamericana
https://en.wikipedia.org/wiki/2009_Copa_Sudamericana
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-17282875-3.html.csv
superlative
san lorenzo was the team that scored the most goals in the 2009 copa sudamericana .
{'scope': 'all', 'col_superlative': '2', 'row_superlative': '6', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None}
{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'points'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; points }'}, 'team 1'], 'result': 'san lorenzo', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; points } ; team 1 }'}, 'san lorenzo'], 'result': True, 'ind': ...
eq { hop { argmax { all_rows ; points } ; team 1 } ; san lorenzo } = true
select the row whose points record of all rows is maximum . the team 1 record of this row is san lorenzo .
3
3
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'points_5': 5, 'team 1_6': 6, 'san lorenzo_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', 'team 1_6': 'team 1', 'san lorenzo_7': 'san lorenzo'}
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'points_5': [0], 'team 1_6': [1], 'san lorenzo_7': [2]}
['team 1', 'points', 'team 2', '1st leg', '2nd leg']
[['cerro porteño', '( a ) 3 - 3', 'goiás', '2 - 0', '1 - 3'], ['vélez sarsfield', '4 - 1', 'unión española', '3 - 2', '2 - 2'], ['river plate', '4 - 1', 'vitória', '4 - 1', '1 - 1'], ['internacional', '1 - 4', 'universidad de chile', '1 - 1', '0 - 1'], ['alianza atlético', '1 - 4', 'fluminense', '2 - 2', '1 - 4'], ['sa...
.38 special
https://en.wikipedia.org/wiki/.38_Special
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-173103-1.html.csv
superlative
the .357 magnum gun cartridge has the highest muzzle energy in joules .
{'scope': 'all', 'col_superlative': '4', 'row_superlative': '12', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None}
{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'muzzle energy'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; muzzle energy }'}, 'cartridge'], 'result': '.357 magnum', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; muzzle energy } ; cartridge }'}, '.357 magnum...
eq { hop { argmax { all_rows ; muzzle energy } ; cartridge } ; .357 magnum } = true
select the row whose muzzle energy record of all rows is maximum . the cartridge record of this row is .357 magnum .
3
3
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'muzzle energy_5': 5, 'cartridge_6': 6, '.357 magnum_7': 7}
{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'muzzle energy_5': 'muzzle energy', 'cartridge_6': 'cartridge', '.357 magnum_7': '.357 magnum'}
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'muzzle energy_5': [0], 'cartridge_6': [1], '.357 magnum_7': [2]}
['cartridge', 'bullet weight', 'muzzle velocity', 'muzzle energy', 'max pressure']
[['.38 short colt', 'gr ( g )', 'ft / s ( m / s )', '181ft lbf ( 245 j )', '7500 cup'], ['.38 long colt', 'gr ( g )', 'ft / s ( m / s )', '201ft lbf ( 273 j )', '12000 cup'], ['.38 s & w', 'gr ( g )', 'ft / s ( m / s )', '206ft lbf ( 279 j )', '14500 psi'], ['.38 s & w special', 'gr ( g )', 'ft / s ( m / s )', '310ft l...
primera división de fútbol profesional apertura 2002
https://en.wikipedia.org/wiki/Primera_Divisi%C3%B3n_de_F%C3%BAtbol_Profesional_Apertura_2002
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13013383-1.html.csv
ordinal
san salvador fc scored the second highest amount of goals in the primera división de fútbol profesional apertura 2002 .
{'row': '3', 'col': '6', 'order': '2', 'col_other': '2', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None}
{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'goals scored', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; goals scored ; 2 }'}, 'team'], 'result': 'san salvador fc', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; goals scored ; 2 } ; team }...
eq { hop { nth_argmax { all_rows ; goals scored ; 2 } ; team } ; san salvador fc } = true
select the row whose goals scored record of all rows is 2nd maximum . the team record of this row is san salvador fc .
3
3
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'goals scored_5': 5, '2_6': 6, 'team_7': 7, 'san salvador fc_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', 'goals scored_5': 'goals scored', '2_6': '2', 'team_7': 'team', 'san salvador fc_8': 'san salvador fc'}
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'goals scored_5': [0], '2_6': [0], 'team_7': [1], 'san salvador fc_8': [2]}
['place', 'team', 'played', 'draw', 'lost', 'goals scored', 'goals conceded', 'points']
[['1', 'cd fas', '18', '5', '3', '24', '20', '35'], ['2', 'municipal limeño', '18', '4', '5', '33', '19', '31'], ['3', 'san salvador fc', '18', '7', '4', '28', '21', '28'], ['4', 'cd águila', '18', '9', '3', '26', '20', '27'], ['5', 'cd luis ángel firpo', '18', '6', '5', '23', '24', '27'], ['6', 'ad isidro metapán', '1...
2006 - 07 golden state warriors season
https://en.wikipedia.org/wiki/2006%E2%80%9307_Golden_State_Warriors_season
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14677944-8.html.csv
majority
in april of 2007 , the warriors were the visiting team for most of their games .
{'scope': 'all', 'col': '2', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'warriors', 'subset': None}
{'func': 'most_str_eq', 'args': ['all_rows', 'visitor', 'warriors'], 'result': True, 'ind': 0, 'tointer': 'for the visitor records of all rows , most of them fuzzily match to warriors .', 'tostr': 'most_eq { all_rows ; visitor ; warriors } = true'}
most_eq { all_rows ; visitor ; warriors } = true
for the visitor records of all rows , most of them fuzzily match to warriors .
1
1
{'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'visitor_3': 3, 'warriors_4': 4}
{'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'visitor_3': 'visitor', 'warriors_4': 'warriors'}
{'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'visitor_3': [0], 'warriors_4': [0]}
['date', 'visitor', 'score', 'home', 'leading scorer', 'attendance', 'record']
[['2007 - 04 - 01', 'grizzlies', '117 - 122', 'warriors', 'jason richardson ( 26 )', '17198', '35 - 39'], ['2007 - 04 - 04', 'warriors', '110 - 99', 'rockets', 'jason richardson ( 26 )', '13929', '36 - 39'], ['2007 - 04 - 06', 'warriors', '116 - 104', 'grizzlies', 'baron davis ( 31 )', '14087', '37 - 39'], ['2007 - 04 ...
iowa corn cy - hawk series
https://en.wikipedia.org/wiki/Iowa_Corn_Cy-Hawk_Series
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14175075-5.html.csv
majority
the majority of events took place in ames .
{'scope': 'all', 'col': '2', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'ames', 'subset': None}
{'func': 'most_str_eq', 'args': ['all_rows', 'site', 'ames'], 'result': True, 'ind': 0, 'tointer': 'for the site records of all rows , most of them fuzzily match to ames .', 'tostr': 'most_eq { all_rows ; site ; ames } = true'}
most_eq { all_rows ; site ; ames } = true
for the site records of all rows , most of them fuzzily match to ames .
1
1
{'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'site_3': 3, 'ames_4': 4}
{'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'site_3': 'site', 'ames_4': 'ames'}
{'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'site_3': [0], 'ames_4': [0]}
['date', 'site', 'sport', 'winning team', 'series']
[['september 4 , 2007', 'cedar rapids', 'm golf', 'iowa state', 'iowa state 2 - 0'], ['september 8 , 2007', 'des moines', 'volleyball', 'iowa state', 'iowa state 4 - 0'], ['september 9 , 2007', 'iowa city', 'w soccer', 'tie', 'iowa state 5 - 1'], ['september 15 , 2007', 'ames', 'football', 'iowa state', 'iowa state 8 -...
chicago throwbacks
https://en.wikipedia.org/wiki/Chicago_Throwbacks
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-10595672-1.html.csv
count
james booyer had a total of two high rebounds performances for the chicago throwbacks .
{'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'james booyer', 'result': '2', 'col': '6', 'subset': None}
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'high rebounds', 'james booyer'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose high rebounds record fuzzily matches to james booyer .', 'tostr': 'filter_eq { all_rows ; high rebounds ; james booyer }'}], 're...
eq { count { filter_eq { all_rows ; high rebounds ; james booyer } } ; 2 } = true
select the rows whose high rebounds record fuzzily matches to james booyer . 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, 'high rebounds_5': 5, 'james booyer_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', 'high rebounds_5': 'high rebounds', 'james booyer_6': 'james booyer', '2_7': '2'}
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'high rebounds_5': [0], 'james booyer_6': [0], '2_7': [2]}
['date', 'opponent', 'home / away', 'score', 'high points', 'high rebounds', 'high assists', 'location / attendance', 'record']
[['january 2', 'battle creek knights', 'away', '113 - 120', 'stanley thomas ( 23 )', "michael o'neal ( 8 )", 'imari sawyer ( 7 )', 'kellogg arena ( 1257 )', '0 - 1'], ['january 4', 'detroit panthers', 'away', '110 - 106', 'stanley thomas ( 24 )', 'stanley thomas & marcus jackson ( 9 )', 'imari sawyer ( 8 )', 'groves hi...
united states house of representatives elections , 1970
https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1970
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1341718-36.html.csv
comparative
of the incumbents in the 1970 election for the united states house of representatives , the date that frank t bow was first elected was 18 years before louis stokes was first elected .
{'row_1': '6', 'row_2': '8', 'col': '4', 'col_other': '2', 'relation': 'diff', 'record_mentioned': 'no', 'diff_result': {'diff_value': '18 years', 'bigger': 'row2'}}
{'func': 'eq', 'args': [{'func': 'diff', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'incumbent', 'frank t bow'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose incumbent record fuzzily matches to frank t bow .', 'tostr': 'filter_eq { all_rows ; incumbent ; frank t ...
eq { diff { hop { filter_eq { all_rows ; incumbent ; frank t bow } ; first elected } ; hop { filter_eq { all_rows ; incumbent ; louis stokes } ; first elected } } ; -18 years } = true
select the rows whose incumbent record fuzzily matches to frank t bow . take the first elected record of this row . select the rows whose incumbent record fuzzily matches to louis stokes . take the first elected record of this row . the second record is 18 years larger than the first record .
6
6
{'str_eq_5': 5, 'result_6': 6, 'diff_4': 4, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_7': 7, 'incumbent_8': 8, 'frank t bow_9': 9, 'first elected_10': 10, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_11': 11, 'incumbent_12': 12, 'louis stokes_13': 13, 'first elected_14': 14, '-18 years_15': 15}
{'str_eq_5': 'str_eq', 'result_6': 'true', 'diff_4': 'diff', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_7': 'all_rows', 'incumbent_8': 'incumbent', 'frank t bow_9': 'frank t bow', 'first elected_10': 'first elected', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_11': '...
{'str_eq_5': [6], 'result_6': [], 'diff_4': [5], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_7': [0], 'incumbent_8': [0], 'frank t bow_9': [0], 'first elected_10': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_11': [1], 'incumbent_12': [1], 'louis stokes_13': [1], 'first elected_14': [3], '-18 years_...
['district', 'incumbent', 'party', 'first elected', 'result', 'candidates']
[['ohio 5', 'del latta', 'republican', '1958', 're - elected', 'del latta ( r ) 71.1 % carl g sherer ( d ) 28.9 %'], ['ohio 6', 'bill harsha', 'republican', '1960', 're - elected', 'bill harsha ( r ) 67.8 % raymond h stevens ( d ) 32.2 %'], ['ohio 8', 'jackson edward betts', 'republican', '1950', 're - elected', 'jacks...
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/2-18652198-7.html.csv
unique
in the 1965 american football league draft , the only player drafted from pittsburgh was marty shottenheimer .
{'scope': 'all', 'row': '8', 'col': '5', 'col_other': '3', 'criterion': 'equal', 'value': 'pittsburgh', 'subset': None}
{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'college', 'pittsburgh'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose college record fuzzily matches to pittsburgh .', 'tostr': 'filter_eq { all_rows ; college ; pittsburgh }'}], 'result': True, 'ind': 1, '...
and { only { filter_eq { all_rows ; college ; pittsburgh } } ; eq { hop { filter_eq { all_rows ; college ; pittsburgh } ; player } ; marty schottenheimer } } = true
select the rows whose college record fuzzily matches to pittsburgh . there is only one such row in the table . the player record of this unqiue row is marty schottenheimer .
6
5
{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'college_7': 7, 'pittsburgh_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'player_9': 9, 'marty schottenheimer_10': 10}
{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'college_7': 'college', 'pittsburgh_8': 'pittsburgh', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'player_9': 'player', 'marty schottenheimer_10': 'marty schottenheimer'}
{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'college_7': [0], 'pittsburgh_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'player_9': [2], 'marty schottenheimer_10': [3]}
['pick', 'team', 'player', 'position', 'college']
[['49', 'denver broncos', 'jim garcia', 'defensive end', 'purdue'], ['50', 'kansas city chiefs ( from houston oilers )', 'gloster richardson', 'wide receiver', 'jackson state'], ['51', 'new york jets ( from oakland raiders )', 'archie roberts', 'quarterback', 'columbia'], ['52', 'new york jets', 'jim harris , jr', 'def...
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
unique
the princess railway was the only railway built by kerr stuart .
{'scope': 'all', 'row': '3', 'col': '2', 'col_other': '1', 'criterion': 'equal', 'value': 'kerr stuart', 'subset': None}
{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'builder', 'kerr stuart'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose builder record fuzzily matches to kerr stuart .', 'tostr': 'filter_eq { all_rows ; builder ; kerr stuart }'}], 'result': True, 'ind': 1...
and { only { filter_eq { all_rows ; builder ; kerr stuart } } ; eq { hop { filter_eq { all_rows ; builder ; kerr stuart } ; name } ; princess } } = true
select the rows whose builder record fuzzily matches to kerr stuart . there is only one such row in the table . the name record of this unqiue row is princess .
6
5
{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'builder_7': 7, 'kerr stuart_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'name_9': 9, 'princess_10': 10}
{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'builder_7': 'builder', 'kerr stuart_8': 'kerr stuart', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'name_9': 'name', 'princess_10': 'princess'}
{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'builder_7': [0], 'kerr stuart_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'name_9': [2], 'princess_10': [3]}
['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', '19...
equatorial bulge
https://en.wikipedia.org/wiki/Equatorial_bulge
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-143023-1.html.csv
count
among the planets with equatorial bulge above 1000 km , 2 of them have polar diameter greater than 100,000 km .
{'scope': 'subset', 'criterion': 'greater_than', 'value': '100,000', 'result': '2', 'col': '3', 'subset': {'col': '4', 'criterion': 'greater_than', 'value': '1000'}}
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'equatorial bulge', '1000'], 'result': None, 'ind': 0, 'tostr': 'filter_greater { all_rows ; equatorial bulge ; 1000 }', 'tointer': 'select the rows whose equatorial bulge record is gre...
eq { count { filter_greater { filter_greater { all_rows ; equatorial bulge ; 1000 } ; polar diameter ; 100,000 } } ; 2 } = true
select the rows whose equatorial bulge record is greater than 1000 . among these rows , select the rows whose polar diameter record is greater than 100,000 . 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, 'equatorial bulge_6': 6, '1000_7': 7, 'polar diameter_8': 8, '100,000_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', 'equatorial bulge_6': 'equatorial bulge', '1000_7': '1000', 'polar diameter_8': 'polar diameter', '100,000_9': '100,000', '2_10': '2'}
{'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_greater_1': [2], 'filter_greater_0': [1], 'all_rows_5': [0], 'equatorial bulge_6': [0], '1000_7': [0], 'polar diameter_8': [1], '100,000_9': [1], '2_10': [3]}
['body', 'equatorial diameter', 'polar diameter', 'equatorial bulge', 'flattening ratio']
[['earth', '12756.28 km', '12713.56 km', '42.72 km', '1:298.2575'], ['mars', '6805 km', '6754.8 km', '50.2 km', '1:135.56'], ['ceres', '975 km', '909 km', '66 km', '1:14.77'], ['jupiter', '143884 km', '133709 km', '10175 km', '1:14.14'], ['saturn', '120536 km', '108728 km', '11808 km', '1:10.21'], ['uranus', '51118 km'...
cryengine
https://en.wikipedia.org/wiki/CryEngine
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1241866-4.html.csv
unique
star citizen was the only game made in the cryengine game engine developed by cloud imperium games corporation .
{'scope': 'all', 'row': '3', 'col': '3', 'col_other': '1', 'criterion': 'equal', 'value': 'cloud imperium games corporation', 'subset': None}
{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'developer', 'cloud imperium games corporation'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose developer record fuzzily matches to cloud imperium games corporation .', 'tostr': 'filter_eq { all_rows ; develo...
and { only { filter_eq { all_rows ; developer ; cloud imperium games corporation } } ; eq { hop { filter_eq { all_rows ; developer ; cloud imperium games corporation } ; title } ; star citizen } } = true
select the rows whose developer record fuzzily matches to cloud imperium games corporation . there is only one such row in the table . the title record of this unqiue row is star citizen .
6
5
{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'developer_7': 7, 'cloud imperium games corporation_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'title_9': 9, 'star citizen_10': 10}
{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'developer_7': 'developer', 'cloud imperium games corporation_8': 'cloud imperium games corporation', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'title_9': 'title', 'star citizen_10': 'star citizen'}
{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'developer_7': [0], 'cloud imperium games corporation_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'title_9': [2], 'star citizen_10': [3]}
['title', 'year', 'developer', 'publisher', 'platform']
[['homefront 2', '2014', 'crytek uk', 'crytek', 'tba'], ['ryse : son of rome', '2013', 'crytek gmbh', 'microsoft studios', 'xbox one'], ['star citizen', '2014', 'cloud imperium games corporation', 'cloud imperium games corporation', 'microsoft windows'], ['unannounced arkane studios title', 'tba', 'arkane studios', 'be...
maura viceconte
https://en.wikipedia.org/wiki/Maura_Viceconte
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15671631-1.html.csv
count
maura viceconte finished in 1st place of marathons a total of six times .
{'scope': 'all', 'criterion': 'equal', 'value': '1st', 'result': '6', 'col': '4', 'subset': None}
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'position', '1st'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose position record fuzzily matches to 1st .', 'tostr': 'filter_eq { all_rows ; position ; 1st }'}], 'result': '6', 'ind': 1, 'tostr': 'count { fi...
eq { count { filter_eq { all_rows ; position ; 1st } } ; 6 } = true
select the rows whose position record fuzzily matches to 1st . 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, 'position_5': 5, '1st_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', 'position_5': 'position', '1st_6': '1st', '6_7': '6'}
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'position_5': [0], '1st_6': [0], '6_7': [2]}
['year', 'competition', 'venue', 'position', 'event', 'notes']
[['1995', 'venice marathon', 'venice , italy', '1st', 'marathon', '2:29:11'], ['1996', 'olympic games', 'atlanta , united states', 'n / a', 'marathon', 'dnf'], ['1997', 'monaco marathon', 'monte carlo , monaco', '1st', 'marathon', '2:28:16'], ['1998', 'italian marathon', 'carpi , italy', '1st', 'marathon', '2:31:23'], ...
who dares wins ( uk game show )
https://en.wikipedia.org/wiki/Who_Dares_Wins_%28UK_game_show%29
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-14523485-9.html.csv
unique
in who dares wins , when the top prize was at least 10000 , the only time the host was jason gunn was when the channel was tvnz .
{'scope': 'subset', 'row': '4', 'col': '3', 'col_other': '4,6', 'criterion': 'equal', 'value': 'jason gunn', 'subset': {'col': '6', 'criterion': 'greater_than_eq', 'value': '10000'}}
{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_greater_eq', 'args': ['all_rows', 'top prize', '10000'], 'result': None, 'ind': 0, 'tostr': 'filter_greater_eq { all_rows ; top prize ; 10000 }', 'tointer': 'select the rows whose top prize record is greater than or e...
and { only { filter_eq { filter_greater_eq { all_rows ; top prize ; 10000 } ; host ; jason gunn } } ; eq { hop { filter_eq { filter_greater_eq { all_rows ; top prize ; 10000 } ; host ; jason gunn } ; channel } ; tvnz } } = true
select the rows whose top prize record is greater than or equal to 10000 . among these rows , select the rows whose host record fuzzily matches to jason gunn . there is only one such row in the table . the channel record of this unqiue row is tvnz .
8
6
{'and_5': 5, 'result_6': 6, 'only_2': 2, 'filter_str_eq_1': 1, 'filter_greater_eq_0': 0, 'all_rows_7': 7, 'top prize_8': 8, '10000_9': 9, 'host_10': 10, 'jason gunn_11': 11, 'str_eq_4': 4, 'str_hop_3': 3, 'channel_12': 12, 'tvnz_13': 13}
{'and_5': 'and', 'result_6': 'true', 'only_2': 'only', 'filter_str_eq_1': 'filter_str_eq', 'filter_greater_eq_0': 'filter_greater_eq', 'all_rows_7': 'all_rows', 'top prize_8': 'top prize', '10000_9': '10000', 'host_10': 'host', 'jason gunn_11': 'jason gunn', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'channel_12': '...
{'and_5': [6], 'result_6': [], 'only_2': [5], 'filter_str_eq_1': [2, 3], 'filter_greater_eq_0': [1], 'all_rows_7': [0], 'top prize_8': [0], '10000_9': [0], 'host_10': [1], 'jason gunn_11': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'channel_12': [3], 'tvnz_13': [4]}
['country', 'local name', 'host', 'channel', 'year aired', 'top prize']
[['australia', 'the rich list', "andrew o'keefe", 'seven network', '2007 - 2009', '250000'], ['france', 'la liste gagnante', 'patrice laffont', 'france 3', '2009', '5000'], ['germany', 'rich list', 'kai pflaume', 'sat1', '2007 - present', '100000'], ['new zealand', 'the rich list', 'jason gunn', 'tvnz', '2007 - present...
thrust specific fuel consumption
https://en.wikipedia.org/wiki/Thrust_specific_fuel_consumption
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-172348-2.html.csv
aggregation
the thrust engines have an average effective exhaust velocity of 33869 meters per second .
{'scope': 'all', 'col': '6', 'type': 'average', 'result': '33869', 'subset': None}
{'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'effective exhaust velocity ( m / s )'], 'result': '33869', 'ind': 0, 'tostr': 'avg { all_rows ; effective exhaust velocity ( m / s ) }'}, '33869'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; effective exhaust velocity ( m / s ) } ;...
round_eq { avg { all_rows ; effective exhaust velocity ( m / s ) } ; 33869 } = true
the average of the effective exhaust velocity ( m / s ) record of all rows is 33869 .
2
2
{'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'effective exhaust velocity (m / s)_4': 4, '33869_5': 5}
{'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'effective exhaust velocity (m / s)_4': 'effective exhaust velocity ( m / s )', '33869_5': '33869'}
{'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'effective exhaust velocity (m / s)_4': [0], '33869_5': [1]}
['engine type', 'scenario', 'sfc in lb / ( lbf h )', 'sfc in g / ( kn s )', 'specific impulse ( s )', 'effective exhaust velocity ( m / s )']
[['nk - 33 rocket engine', 'vacuum', '10.9', '309', '331', '3240'], ['ssme rocket engine', 'space shuttle vacuum', '7.95', '225', '453', '4423'], ['ramjet', 'mach 1', '4.5', '127', '800', '7877'], ['j - 58 turbojet', 'sr - 71 at mach 3.2 ( wet )', '1.9', '53.8', '1900', '18587'], ['rolls - royce / snecma olympus 593', ...
2008 - 09 cardiff city f.c. season
https://en.wikipedia.org/wiki/2008%E2%80%9309_Cardiff_City_F.C._season
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17596418-4.html.csv
unique
burke was the only player transfered to cardiff city f.c. during the 2008 - 09 winter trade window .
{'scope': 'all', 'row': '8', 'col': '5', 'col_other': '1', 'criterion': 'equal', 'value': 'winter', 'subset': None}
{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'transfer window', 'winter'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose transfer window record fuzzily matches to winter .', 'tostr': 'filter_eq { all_rows ; transfer window ; winter }'}], 'result': True,...
and { only { filter_eq { all_rows ; transfer window ; winter } } ; eq { hop { filter_eq { all_rows ; transfer window ; winter } ; name } ; burke } } = true
select the rows whose transfer window record fuzzily matches to winter . there is only one such row in the table . the name record of this unqiue row is burke .
6
5
{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'transfer window_7': 7, 'winter_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'name_9': 9, 'burke_10': 10}
{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'transfer window_7': 'transfer window', 'winter_8': 'winter', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'name_9': 'name', 'burke_10': 'burke'}
{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'transfer window_7': [0], 'winter_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'name_9': [2], 'burke_10': [3]}
['name', 'country', 'type', 'moving from', 'transfer window', 'ends', 'transfer fee', 'source']
[['comminges', 'gpe', 'free transfer', 'swindon town', 'summer', '2010', 'free', 'bbc sport'], ['kennedy', 'irl', 'free transfer', 'crystal palace', 'summer', '2010', 'free', 'bbc sport'], ['enckelman', 'fin', 'free transfer', 'blackburn rovers', 'summer', '2010', 'free', 'bbc sport'], ['dennehy', 'irl', 'free transfer...
darya pchelnik
https://en.wikipedia.org/wiki/Darya_Pchelnik
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12583435-1.html.csv
unique
the world athletics final was the only event that took place in greece .
{'scope': 'all', 'row': '6', 'col': '3', 'col_other': '2', 'criterion': 'equal', 'value': 'greece', 'subset': None}
{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'venue', 'greece'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose venue record fuzzily matches to greece .', 'tostr': 'filter_eq { all_rows ; venue ; greece }'}], 'result': True, 'ind': 1, 'tostr': 'only { fi...
and { only { filter_eq { all_rows ; venue ; greece } } ; eq { hop { filter_eq { all_rows ; venue ; greece } ; competition } ; world athletics final } } = true
select the rows whose venue record fuzzily matches to greece . there is only one such row in the table . the competition record of this unqiue row is world athletics final .
6
5
{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'venue_7': 7, 'greece_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'competition_9': 9, 'world athletics final_10': 10}
{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'venue_7': 'venue', 'greece_8': 'greece', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'competition_9': 'competition', 'world athletics final_10': 'world athletics final'}
{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'venue_7': [0], 'greece_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'competition_9': [2], 'world athletics final_10': [3]}
['year', 'competition', 'venue', 'position', 'notes']
[['2005', 'world championships', 'helsinki , finland', '15th ( q )', '65.54 m'], ['2005', 'universiade', 'izmir , turkey', '10th', '63.89 m'], ['2007', 'universiade', 'bangkok , thailand', '1st', '68.74 m'], ['2008', 'olympic games', 'beijing , china', '4th', '73.65 m'], ['2009', 'world championships', 'berlin , german...
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
superlative
christian dailly scored the highest number of international goals on may 23 , 2002 .
{'scope': 'all', 'col_superlative': '4', 'row_superlative': '3', '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', 'score'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; score }'}, 'date'], 'result': '23 may 2002', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; score } ; date }'}, '23 may 2002'], 'result': True, 'ind': 2, 'tos...
eq { hop { argmax { all_rows ; score } ; date } ; 23 may 2002 } = true
select the row whose score record of all rows is maximum . the date record of this row is 23 may 2002 .
3
3
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'score_5': 5, 'date_6': 6, '23 may 2002_7': 7}
{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'score_5': 'score', 'date_6': 'date', '23 may 2002_7': '23 may 2002'}
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'score_5': [0], 'date_6': [1], '23 may 2002_7': [2]}
['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'], ...
1990 major league baseball draft
https://en.wikipedia.org/wiki/1990_Major_League_Baseball_Draft
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18132662-2.html.csv
count
during the 1990 mlb draft , 6 players were selected for the rhp position .
{'scope': 'all', 'criterion': 'equal', 'value': 'rhp', 'result': '6', 'col': '4', 'subset': None}
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'position', 'rhp'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose position record fuzzily matches to rhp .', 'tostr': 'filter_eq { all_rows ; position ; rhp }'}], 'result': '6', 'ind': 1, 'tostr': 'count { fi...
eq { count { filter_eq { all_rows ; position ; rhp } } ; 6 } = true
select the rows whose position record fuzzily matches to rhp . 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, 'position_5': 5, 'rhp_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', 'position_5': 'position', 'rhp_6': 'rhp', '6_7': '6'}
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'position_5': [0], 'rhp_6': [0], '6_7': [2]}
['pick', 'player', 'team', 'position', 'hometown / school']
[['27', 'mike zimmerman', 'pittsburgh pirates', 'rhp', 'university of south alabama'], ['28', 'gabe white', 'montreal expos', 'rhp', 'sebring , florida'], ['29', 'midre cummings', 'minnesota twins', 'of', 'miami , florida'], ['30', 'paul ellis', 'st louis cardinals', 'c', 'university of california , los angeles'], ['31...
2008 - 09 denver nuggets season
https://en.wikipedia.org/wiki/2008%E2%80%9309_Denver_Nuggets_season
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17355408-6.html.csv
majority
the 2008-09 denver nuggets won most of their matches in the month of january .
{'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': 'w', 'subset': None}
{'func': 'most_str_eq', 'args': ['all_rows', 'score', 'w'], 'result': True, 'ind': 0, 'tointer': 'for the score records of all rows , most of them fuzzily match to w .', 'tostr': 'most_eq { all_rows ; score ; w } = true'}
most_eq { all_rows ; score ; w } = true
for the score 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, 'score_3': 3, 'w_4': 4}
{'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'score_3': 'score', 'w_4': 'w'}
{'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'score_3': [0], 'w_4': [0]}
['game', 'date', 'team', 'score', 'high points', 'high assists', 'location attendance', 'record']
[['34', 'january 2', 'oklahoma city', 'w 122 - 120 ( ot )', 'carmelo anthony ( 31 )', 'chauncey billups , anthony carter ( 7 )', 'ford center 18613', '22 - 12'], ['35', 'january 3', 'new orleans', 'w 105 - 100 ( ot )', 'carmelo anthony ( 22 )', 'chauncey billups ( 6 )', 'pepsi center 19614', '23 - 12'], ['36', 'january...
jhalak dikhhla jaa ( indian dance series )
https://en.wikipedia.org/wiki/Jhalak_Dikhhla_Jaa_%28Indian_Dance_Series%29
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-13133962-1.html.csv
majority
all of the seasons of the indian dance series premiered after the year 2000 .
{'scope': 'all', 'col': '2', 'most_or_all': 'all', 'criterion': 'fuzzily_match', 'value': '20', 'subset': None}
{'func': 'all_str_eq', 'args': ['all_rows', 'season premiere date', '20'], 'result': True, 'ind': 0, 'tointer': 'for the season premiere date records of all rows , all of them fuzzily match to 20 .', 'tostr': 'all_eq { all_rows ; season premiere date ; 20 } = true'}
all_eq { all_rows ; season premiere date ; 20 } = true
for the season premiere date records of all rows , all of them fuzzily match to 20 .
1
1
{'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'season premiere date_3': 3, '20_4': 4}
{'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'season premiere date_3': 'season premiere date', '20_4': '20'}
{'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'season premiere date_3': [0], '20_4': [0]}
['season', 'season premiere date', 'season finale date', 'winner', '1st runner up', '2nd runner up']
[['1', '8 september 2006', '4 november 2006', 'mona singh', 'shweta salve', 'mahesh manjrekar'], ['2', '28 september 2007', '15 december 2007', 'prachi desai', 'sandhya mridul', 'jay bhanushali'], ['3', '27 february 2009', '31 may 2009', 'baichung bhutia', 'gauhar khan', 'karan singh grover'], ['4', '12 december 2010',...
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
comparative
the eclair cruizer-class brig-sloop was launched at a later date than the derwent cruizer-class brig-sloop .
{'row_1': '2', 'row_2': '1', 'col': '4', 'col_other': '1', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None}
{'func': 'greater', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'name', 'eclair'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose name record fuzzily matches to eclair .', 'tostr': 'filter_eq { all_rows ; name ; eclair }'}, 'launched'], 'result': None, 'ind': 2, 'to...
greater { hop { filter_eq { all_rows ; name ; eclair } ; launched } ; hop { filter_eq { all_rows ; name ; derwent } ; launched } } = true
select the rows whose name record fuzzily matches to eclair . take the launched record of this row . select the rows whose name record fuzzily matches to derwent . take the launched 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, 'name_7': 7, 'eclair_8': 8, 'launched_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'name_11': 11, 'derwent_12': 12, 'launched_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', 'name_7': 'name', 'eclair_8': 'eclair', 'launched_9': 'launched', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'name_11': 'name', 'derwent_12': 'de...
{'greater_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'name_7': [0], 'eclair_8': [0], 'launched_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'name_11': [1], 'derwent_12': [1], 'launched_13': [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'], ['barracout...
1981 denver broncos season
https://en.wikipedia.org/wiki/1981_Denver_Broncos_season
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-17972136-1.html.csv
count
the denver broncos won 10 games during the 1981 season .
{'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'w', 'result': '10', 'col': '4', 'subset': None}
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'result', 'w'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose result record fuzzily matches to w .', 'tostr': 'filter_eq { all_rows ; result ; w }'}], 'result': '10', 'ind': 1, 'tostr': 'count { filter_eq { a...
eq { count { filter_eq { all_rows ; result ; w } } ; 10 } = true
select the rows whose result record fuzzily matches to w . the number of such rows is 10 .
3
3
{'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'result_5': 5, 'w_6': 6, '10_7': 7}
{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'result_5': 'result', 'w_6': 'w', '10_7': '10'}
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'result_5': [0], 'w_6': [0], '10_7': [2]}
['week', 'date', 'opponent', 'result', 'game site', 'record', 'attendance']
[['1', 'september 6', 'oakland raiders', 'w 9 - 7', 'mile high stadium', '1 - 0', '74796'], ['2', 'september 13', 'seattle seahawks', 'l 10 - 13', 'kingdome', '1 - 1', '58513'], ['3', 'september 20', 'baltimore colts', 'w 28 - 10', 'mile high stadium', '2 - 1', '74804'], ['4', 'september 27', 'san diego chargers', 'w 4...
1994 - 95 philadelphia flyers season
https://en.wikipedia.org/wiki/1994%E2%80%9395_Philadelphia_Flyers_season
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14022127-5.html.csv
ordinal
the philadelphia flyers game on april 23 had the 3rd lowest attendance of all games during the 1994 - 95 season .
{'row': '11', 'col': '6', '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', 'attendance', '3'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; attendance ; 3 }'}, 'date'], 'result': 'april 23', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; attendance ; 3 } ; date }'}, 'april 23...
eq { hop { nth_argmin { all_rows ; attendance ; 3 } ; date } ; april 23 } = true
select the row whose attendance record of all rows is 3rd minimum . the date record of this row is april 23 .
3
3
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'attendance_5': 5, '3_6': 6, 'date_7': 7, 'april 23_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', 'attendance_5': 'attendance', '3_6': '3', 'date_7': 'date', 'april 23_8': 'april 23'}
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'attendance_5': [0], '3_6': [0], 'date_7': [1], 'april 23_8': [2]}
['date', 'visitor', 'score', 'home', 'decision', 'attendance', 'record']
[['april 1', 'philadelphia', '2 - 3', 'pittsburgh', 'hextall', '17181', '17 - 13 - 4'], ['april 2', 'ny rangers', '2 - 4', 'philadelphia', 'hextall', '17380', '18 - 13 - 4'], ['april 6', 'tampa bay', '4 - 5', 'philadelphia', 'hextall', '17245', '19 - 13 - 4'], ['april 8', 'philadelphia', '3 - 1', 'washington', 'hextall...
2006 japanese television dramas
https://en.wikipedia.org/wiki/2006_Japanese_television_dramas
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18540022-2.html.csv
aggregation
2006 japanese television dramas have an average of 10.72 episodes .
{'scope': 'all', 'col': '4', 'type': 'average', 'result': '10.72', 'subset': None}
{'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'episodes'], 'result': '10.72', 'ind': 0, 'tostr': 'avg { all_rows ; episodes }'}, '10.72'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; episodes } ; 10.72 } = true', 'tointer': 'the average of the episodes record of all rows is 10.7...
round_eq { avg { all_rows ; episodes } ; 10.72 } = true
the average of the episodes record of all rows is 10.72 .
2
2
{'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'episodes_4': 4, '10.72_5': 5}
{'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'episodes_4': 'episodes', '10.72_5': '10.72'}
{'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'episodes_4': [0], '10.72_5': [1]}
['japanese title', 'romaji title', 'tv station', 'episodes', 'average ratings']
[['アテンションプリーズ', 'attention please', 'fuji tv', '11', '16.37 %'], ['医龍 - team medical dragon -', 'iryuu - team medical dragon -', 'fuji tv', '11', '14.8 %'], ['弁護士のくず', 'bengoshi no kuzu', 'tbs', '11', '12.74 %'], ['クロサギ', 'kurosagi', 'tbs', '11', '15.67 %'], ['おいしいプロポーズ', 'oishii propose', 'tbs', '10', '12.0 %'], ['トップ...
tiffany joh
https://en.wikipedia.org/wiki/Tiffany_Joh
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15870501-2.html.csv
aggregation
from 2007 - 2012 , tiffany joh played in a total of 38 tournaments .
{'scope': 'all', 'col': '2', 'type': 'sum', 'result': '38', 'subset': None}
{'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'tournaments played'], 'result': '38', 'ind': 0, 'tostr': 'sum { all_rows ; tournaments played }'}, '38'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; tournaments played } ; 38 } = true', 'tointer': 'the sum of the tournaments played...
round_eq { sum { all_rows ; tournaments played } ; 38 } = true
the sum of the tournaments played record of all rows is 38 .
2
2
{'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'tournaments played_4': 4, '38_5': 5}
{'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'tournaments played_4': 'tournaments played', '38_5': '38'}
{'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'tournaments played_4': [0], '38_5': [1]}
['year', 'tournaments played', 'cuts made', 'wins', 'best finish', 'earnings', 'scoring average']
[['2007', '1', '1', '0', 't22', 'n / a', '71.66'], ['2009', '1', '1', '0', 't21', 'n / a', '72.50'], ['2010', '2', '0', '0', 'mc', '0', '79.00'], ['2011', '14', '12', '0', '2', '237365', '72.75'], ['2012', '20', '10', '0', 't33', '48695', '74.09']]
christian heritage party of canada candidates , 2008 canadian federal election
https://en.wikipedia.org/wiki/Christian_Heritage_Party_of_Canada_candidates%2C_2008_Canadian_federal_election
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12890254-6.html.csv
ordinal
micheal mackay received the 3rd highest amount of votes out of all the candidate 's .
{'row': '1', 'col': '6', 'order': '3', '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', 'votes', '3'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; votes ; 3 }'}, "candidate 's name"], 'result': 'michael mackay', 'ind': 1, 'tostr': "hop { nth_argmax { all_rows ; votes ; 3 } ; candidate 's na...
eq { hop { nth_argmax { all_rows ; votes ; 3 } ; candidate 's name } ; michael mackay } = true
select the row whose votes record of all rows is 3rd maximum . the candidate 's name record of this row is michael mackay .
3
3
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'votes_5': 5, '3_6': 6, "candidate 's name_7": 7, 'michael mackay_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', 'votes_5': 'votes', '3_6': '3', "candidate 's name_7": "candidate 's name", 'michael mackay_8': 'michael mackay'}
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'votes_5': [0], '3_6': [0], "candidate 's name_7": [1], 'michael mackay_8': [2]}
['riding', "candidate 's name", 'gender', 'residence', 'occupation', 'votes', 'rank']
[['central nova', 'michael mackay', 'm', 'west river station', 'retail', '427', '4th'], ['dartmouth-cole harbour', 'george campbell', 'm', 'dartmouth', 'minister', '219', '5th'], ['halifax west', 'trevor ennis', 'm', 'halifax', 'swimming pool salesman', '257', '5th'], ['kings-hants', 'jim hnatiuk', 'm', 'enfield', 'com...
circuit trois - rivières
https://en.wikipedia.org/wiki/Circuit_Trois-Rivi%C3%A8res
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11095234-7.html.csv
majority
at the circuit trois - rivières , all of the drivers drove over forty laps .
{'scope': 'all', 'col': '5', 'most_or_all': 'all', 'criterion': 'greater_than', 'value': '40 laps', 'subset': None}
{'func': 'all_greater', 'args': ['all_rows', 'distance / duration', '40 laps'], 'result': True, 'ind': 0, 'tointer': 'for the distance / duration records of all rows , all of them are greater than 40 laps .', 'tostr': 'all_greater { all_rows ; distance / duration ; 40 laps } = true'}
all_greater { all_rows ; distance / duration ; 40 laps } = true
for the distance / duration records of all rows , all of them are greater than 40 laps .
1
1
{'all_greater_0': 0, 'result_1': 1, 'all_rows_2': 2, 'distance / duration_3': 3, '40 laps_4': 4}
{'all_greater_0': 'all_greater', 'result_1': 'true', 'all_rows_2': 'all_rows', 'distance / duration_3': 'distance / duration', '40 laps_4': '40 laps'}
{'all_greater_0': [1], 'result_1': [], 'all_rows_2': [0], 'distance / duration_3': [0], '40 laps_4': [0]}
['year', 'date', 'driver', 'team', 'distance / duration']
[['2007', 'sept 4', 'kerry micks', 'beyond digital imaging', '41 laps'], ['2008', 'aug 17', 'andrew ranger', 'wal - mart / tide', '46 laps'], ['2009', 'aug 17', 'andrew ranger', 'wal - mart / tide', '43 laps'], ['2010', 'aug 15', 'andrew ranger', 'dodge dealers of quebec', '42 laps'], ['2011', 'aug 7', 'robin buck', 'q...
1926 vfl season
https://en.wikipedia.org/wiki/1926_VFL_season
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10746808-7.html.csv
majority
most of the games for the vfl on 7 june 1926 had crowds of 20,000 or larger .
{'scope': 'all', 'col': '6', 'most_or_all': 'most', 'criterion': 'greater_than_eq', 'value': '20,000', 'subset': None}
{'func': 'most_greater_eq', 'args': ['all_rows', 'crowd', '20,000'], 'result': True, 'ind': 0, 'tointer': 'for the crowd records of all rows , most of them are greater than or equal to 20,000 .', 'tostr': 'most_greater_eq { all_rows ; crowd ; 20,000 } = true'}
most_greater_eq { all_rows ; crowd ; 20,000 } = true
for the crowd records of all rows , most of them are greater than or equal to 20,000 .
1
1
{'most_greater_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'crowd_3': 3, '20,000_4': 4}
{'most_greater_eq_0': 'most_greater_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'crowd_3': 'crowd', '20,000_4': '20,000'}
{'most_greater_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'crowd_3': [0], '20,000_4': [0]}
['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date']
[['north melbourne', '10.13 ( 73 )', 'richmond', '10.14 ( 74 )', 'arden street oval', '12000', '7 june 1926'], ['melbourne', '12.16 ( 88 )', 'south melbourne', '8.17 ( 65 )', 'mcg', '20974', '7 june 1926'], ['fitzroy', '11.15 ( 81 )', 'hawthorn', '14.12 ( 96 )', 'brunswick street oval', '8000', '7 june 1926'], ['geelon...
scottish parliament general election , 2007
https://en.wikipedia.org/wiki/Scottish_Parliament_general_election%2C_2007
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11105214-1.html.csv
ordinal
ayr had the 3rd largest swing to gain among constituencies in the scottish parliament general election of 2007 .
{'row': '8', 'col': '4', 'order': '3', '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', 'swing to gain', '3'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; swing to gain ; 3 }'}, 'constituency'], 'result': 'ayr', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; swing to gain ; 3 } ; constit...
eq { hop { nth_argmax { all_rows ; swing to gain ; 3 } ; constituency } ; ayr } = true
select the row whose swing to gain record of all rows is 3rd maximum . the constituency record of this row is ayr .
3
3
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'swing to gain_5': 5, '3_6': 6, 'constituency_7': 7, 'ayr_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', 'swing to gain_5': 'swing to gain', '3_6': '3', 'constituency_7': 'constituency', 'ayr_8': 'ayr'}
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'swing to gain_5': [0], '3_6': [0], 'constituency_7': [1], 'ayr_8': [2]}
['rank', 'constituency', 'winning party 2003', 'swing to gain', "labour 's place 2003", 'result']
[['1', 'dundee east', 'snp', '0.17', '2nd', 'snp hold'], ['2', 'edinburgh south', 'liberal democrats', '0.26', '2nd', 'ld hold'], ['3', 'ochil', 'snp', '0.49', '2nd', 'snp hold'], ['4', 'strathkelvin and bearsden', 'independent', '0.62', '2nd', 'lab gain'], ['5', 'aberdeen north', 'snp', '0.92', '2nd', 'snp hold'], ['6...
1951 world wrestling championships
https://en.wikipedia.org/wiki/1951_World_Wrestling_Championships
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16853558-1.html.csv
ordinal
sweden recorded the highest number of bronze in the 1951 world wrestling championships .
{'row': '2', 'col': '5', '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', 'bronze', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; bronze ; 1 }'}, 'nation'], 'result': 'sweden', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; bronze ; 1 } ; nation }'}, 'sweden'], 'result'...
eq { hop { nth_argmax { all_rows ; bronze ; 1 } ; nation } ; sweden } = true
select the row whose bronze record of all rows is 1st maximum . the nation record of this row is sweden .
3
3
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'bronze_5': 5, '1_6': 6, 'nation_7': 7, 'sweden_8': 8}
{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'bronze_5': 'bronze', '1_6': '1', 'nation_7': 'nation', 'sweden_8': 'sweden'}
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'bronze_5': [0], '1_6': [0], 'nation_7': [1], 'sweden_8': [2]}
['rank', 'nation', 'gold', 'silver', 'bronze', 'total']
[['1', 'turkey', '6', '0', '1', '7'], ['2', 'sweden', '2', '1', '3', '6'], ['3', 'finland', '0', '4', '0', '4'], ['4', 'iran', '0', '2', '2', '4'], ['5', 'italy', '0', '1', '1', '2'], ['6', 'west germany', '0', '0', '1', '1'], ['total', 'total', '8', '8', '8', '24']]
porphyrin
https://en.wikipedia.org/wiki/Porphyrin
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-182499-1.html.csv
superlative
the highest omim number of porphyrin belongs to uroporphyrinogen iii synthase .
{'scope': 'all', 'col_superlative': '7', 'row_superlative': '4', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None}
{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'omim'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; omim }'}, 'enzyme'], 'result': 'uroporphyrinogen iii synthase', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; omim } ; enzyme }'}, 'uroporphyrinogen iii synth...
eq { hop { argmax { all_rows ; omim } ; enzyme } ; uroporphyrinogen iii synthase } = true
select the row whose omim record of all rows is maximum . the enzyme record of this row is uroporphyrinogen iii synthase .
3
3
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'omim_5': 5, 'enzyme_6': 6, 'uroporphyrinogen iii synthase_7': 7}
{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'omim_5': 'omim', 'enzyme_6': 'enzyme', 'uroporphyrinogen iii synthase_7': 'uroporphyrinogen iii synthase'}
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'omim_5': [0], 'enzyme_6': [1], 'uroporphyrinogen iii synthase_7': [2]}
['enzyme', 'location', 'substrate', 'product', 'chromosome', 'ec', 'omim', 'porphyria']
[['ala synthase', 'mitochondrion', 'glycine , succinyl coa', 'δ - aminolevulinic acid', '3p21 .1', '2.3.1.37', '125290', 'none'], ['ala dehydratase', 'cytosol', 'δ - aminolevulinic acid', 'porphobilinogen', '9q34', '4.2.1.24', '125270', 'ala - dehydratase deficiency'], ['pbg deaminase', 'cytosol', 'porphobilinogen', 'h...
1954 vfl season
https://en.wikipedia.org/wiki/1954_VFL_season
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10773616-12.html.csv
majority
all games of the 1954 vfl season was played on the 10th of july .
{'scope': 'all', 'col': '7', 'most_or_all': 'all', 'criterion': 'equal', 'value': '10 july 1954', 'subset': None}
{'func': 'all_str_eq', 'args': ['all_rows', 'date', '10 july 1954'], 'result': True, 'ind': 0, 'tointer': 'for the date records of all rows , all of them fuzzily match to 10 july 1954 .', 'tostr': 'all_eq { all_rows ; date ; 10 july 1954 } = true'}
all_eq { all_rows ; date ; 10 july 1954 } = true
for the date records of all rows , all of them fuzzily match to 10 july 1954 .
1
1
{'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'date_3': 3, '10 july 1954_4': 4}
{'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'date_3': 'date', '10 july 1954_4': '10 july 1954'}
{'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'date_3': [0], '10 july 1954_4': [0]}
['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date']
[['essendon', '13.16 ( 94 )', 'hawthorn', '9.9 ( 63 )', 'windy hill', '20000', '10 july 1954'], ['collingwood', '8.6 ( 54 )', 'melbourne', '5.16 ( 46 )', 'victoria park', '29000', '10 july 1954'], ['carlton', '11.10 ( 76 )', 'south melbourne', '10.10 ( 70 )', 'princes park', '17000', '10 july 1954'], ['richmond', '14.1...
2007 gran premio tecate
https://en.wikipedia.org/wiki/2007_Gran_Premio_Tecate
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14171191-2.html.csv
unique
at the 2007 gran premio tecate the only driver to complete 64 laps and score more than 30 points was sébastien bourdais .
{'scope': 'subset', 'row': '1', 'col': '6', 'col_other': '1', 'criterion': 'greater_than', 'value': '30', 'subset': {'col': '3', 'criterion': 'equal', 'value': '64'}}
{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_greater', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'laps', '64'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; laps ; 64 }', 'tointer': 'select the rows whose laps record is equal to 64 .'}, 'points', '30'], 'result': None, 'in...
and { only { filter_greater { filter_eq { all_rows ; laps ; 64 } ; points ; 30 } } ; eq { hop { filter_greater { filter_eq { all_rows ; laps ; 64 } ; points ; 30 } ; driver } ; sébastien bourdais } } = true
select the rows whose laps record is equal to 64 . among these rows , select the rows whose points record is greater than 30 . there is only one such row in the table . the driver record of this unqiue row is sébastien bourdais .
8
6
{'and_5': 5, 'result_6': 6, 'only_2': 2, 'filter_greater_1': 1, 'filter_eq_0': 0, 'all_rows_7': 7, 'laps_8': 8, '64_9': 9, 'points_10': 10, '30_11': 11, 'str_eq_4': 4, 'str_hop_3': 3, 'driver_12': 12, 'sébastien bourdais_13': 13}
{'and_5': 'and', 'result_6': 'true', 'only_2': 'only', 'filter_greater_1': 'filter_greater', 'filter_eq_0': 'filter_eq', 'all_rows_7': 'all_rows', 'laps_8': 'laps', '64_9': '64', 'points_10': 'points', '30_11': '30', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'driver_12': 'driver', 'sébastien bourdais_13': 'sébastie...
{'and_5': [6], 'result_6': [], 'only_2': [5], 'filter_greater_1': [2, 3], 'filter_eq_0': [1], 'all_rows_7': [0], 'laps_8': [0], '64_9': [0], 'points_10': [1], '30_11': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'driver_12': [3], 'sébastien bourdais_13': [4]}
['driver', 'team', 'laps', 'time / retired', 'grid', 'points']
[['sébastien bourdais', 'n / h / l racing', '64', '1:45:02.885', '2', '32'], ['will power', 'team australia', '64', '+ 1.906', '1', '29'], ['oriol servià', 'pkv racing', '64', '+ 3.364', '4', '25'], ['graham rahal', 'n / h / l racing', '64', '+ 7.346', '7', '23'], ['paul tracy', 'forsythe racing', '64', '+ 8.593', '8',...
1978 u.s. open ( golf )
https://en.wikipedia.org/wiki/1978_U.S._Open_%28golf%29
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17245471-4.html.csv
majority
at the 1978 u.s. open golf championships most the the players from the united states scores more than 142 .
{'scope': 'subset', 'col': '4', 'most_or_all': 'most', 'criterion': 'greater_than', 'value': '142', 'subset': {'col': '3', 'criterion': 'equal', 'value': 'united states'}}
{'func': 'most_greater', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'united states'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; country ; united states }', 'tointer': 'select the rows whose country record fuzzily matches to united states .'}, 'score', '142'], 'result': True, 'in...
most_greater { filter_eq { all_rows ; country ; united states } ; score ; 142 } = true
select the rows whose country record fuzzily matches to united states . for the score records of these rows , most of them are greater than 142 .
2
2
{'most_greater_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, 'country_4': 4, 'united states_5': 5, 'score_6': 6, '142_7': 7}
{'most_greater_1': 'most_greater', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'country_4': 'country', 'united states_5': 'united states', 'score_6': 'score', '142_7': '142'}
{'most_greater_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'country_4': [0], 'united states_5': [0], 'score_6': [1], '142_7': [1]}
['place', 'player', 'country', 'score', 'to par']
[['1', 'andy north', 'united states', '70 + 70 = 140', '2'], ['t2', 'jack nicklaus', 'united states', '73 + 69 = 142', 'e'], ['t2', 'gary player', 'south africa', '71 + 71 = 142', 'e'], ['t2', 'j c snead', 'united states', '70 + 72 = 142', 'e'], ['t5', 'bobby clampett ( a )', 'united states', '70 + 73 = 143', '+ 1'], [...
sports in charlotte , north carolina
https://en.wikipedia.org/wiki/Sports_in_Charlotte%2C_North_Carolina
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15720079-4.html.csv
majority
most of the venue environments in charlotte , north carolina are open air .
{'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'open air', 'subset': None}
{'func': 'most_str_eq', 'args': ['all_rows', 'environment', 'open air'], 'result': True, 'ind': 0, 'tointer': 'for the environment records of all rows , most of them fuzzily match to open air .', 'tostr': 'most_eq { all_rows ; environment ; open air } = true'}
most_eq { all_rows ; environment ; open air } = true
for the environment records of all rows , most of them fuzzily match to open air .
1
1
{'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'environment_3': 3, 'open air_4': 4}
{'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'environment_3': 'environment', 'open air_4': 'open air'}
{'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'environment_3': [0], 'open air_4': [0]}
['venue', 'location', 'capacity', 'owner', 'environment', 'year built']
[['bank of america stadium', 'uptown charlotte', '73778', 'carolina panthers', 'open air , natural grass', '1996'], ['time warner cable arena', 'uptown charlotte', '20200', 'city of charlotte', 'indoor arena', '2005'], ['american legion memorial stadium', 'elizabeth , charlotte', '16000', 'mecklenburg parks & rec', 'op...
fiba eurobasket 2009 squads
https://en.wikipedia.org/wiki/FIBA_EuroBasket_2009_squads
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-23670057-1.html.csv
unique
ioannis kalampokis was the only player on fiba eurobasket 2009 squads that was born in the 1970s .
{'scope': 'all', 'row': '1', 'col': '6', 'col_other': '2', 'criterion': 'equal', 'value': '1978', 'subset': None}
{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'year born', '1978'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose year born record is equal to 1978 .', 'tostr': 'filter_eq { all_rows ; year born ; 1978 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_...
and { only { filter_eq { all_rows ; year born ; 1978 } } ; eq { hop { filter_eq { all_rows ; year born ; 1978 } ; player } ; ioannis kalampokis } } = true
select the rows whose year born record is equal to 1978 . there is only one such row in the table . the player record of this unqiue row is ioannis kalampokis .
6
5
{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'year born_7': 7, '1978_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'player_9': 9, 'ioannis kalampokis_10': 10}
{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'year born_7': 'year born', '1978_8': '1978', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'player_9': 'player', 'ioannis kalampokis_10': 'ioannis kalampokis'}
{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'year born_7': [0], '1978_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'player_9': [2], 'ioannis kalampokis_10': [3]}
['no', 'player', 'height ( m )', 'height ( f )', 'position', 'year born', 'current club']
[['4', 'ioannis kalampokis', '1.96', "6 ' 05 ″", 'guard', '1978', 'alba berlin'], ['5', 'ioannis bourousis', '2.13', "7 ' 00 ″", 'center', '1983', 'olimpia milano'], ['6', 'nikolaos zisis', '1.97', "6 ' 06 ″", 'guard', '1983', 'bilbao basket'], ['7', 'vasileios spanoulis', '1.93', "6 ' 04 ″", 'guard', '1982', 'olympiac...
queens county , new brunswick
https://en.wikipedia.org/wiki/Queens_County%2C_New_Brunswick
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-171356-2.html.csv
count
there are 9 official locations in the queens county of new brunswick .
{'scope': 'all', 'criterion': 'all', 'value': 'n/a', 'result': '9', 'col': '1', 'subset': None}
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_all', 'args': ['all_rows', 'official name'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose official name record is arbitrary .', 'tostr': 'filter_all { all_rows ; official name }'}], 'result': '9', 'ind': 1, 'tostr': 'count { filter_all {...
eq { count { filter_all { all_rows ; official name } } ; 9 } = true
select the rows whose official name record is arbitrary . the number of such rows is 9 .
3
3
{'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_all_0': 0, 'all_rows_4': 4, 'official name_5': 5, '9_6': 6}
{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_all_0': 'filter_all', 'all_rows_4': 'all_rows', 'official name_5': 'official name', '9_6': '9'}
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_all_0': [1], 'all_rows_4': [0], 'official name_5': [0], '9_6': [2]}
['official name', 'status', 'area km 2', 'population', 'census ranking']
[['chipman', 'parish', '482.81', '962', '2135 of 5008'], ['canning', 'parish', '173.40', '952', '2145 of 5008'], ['waterborough', 'parish', '444.87', '851', '2290 of 5008'], ['petersville', 'parish', '588.42', '723', '2520 of 5008'], ['johnston', 'parish', '359.18', '660', '2649 of 5008'], ['cambridge', 'parish', '113....
list of awards and nominations received by grey 's anatomy
https://en.wikipedia.org/wiki/List_of_awards_and_nominations_received_by_Grey%27s_Anatomy
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12372406-1.html.csv
comparative
of the awards and nominations received by grey 's anatomy , the one for outstanding actress - television series came 5 years before the one for favorite tv actress - supporting role .
{'row_1': '1', 'row_2': '5', 'col': '1', 'col_other': '4', 'relation': 'less', 'record_mentioned': 'yes', 'diff_result': None}
{'func': 'and', 'args': [{'func': 'less', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'category', 'outstanding actress - television series'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose category record fuzzily matches to outstanding actress - television series .'...
and { less { hop { filter_eq { all_rows ; category ; outstanding actress - television series } ; year } ; hop { filter_eq { all_rows ; category ; favorite tv actress - supporting role } ; year } } ; and { eq { hop { filter_eq { all_rows ; category ; outstanding actress - television series } ; year } ; 2007 } ; eq { hop...
select the rows whose category record fuzzily matches to outstanding actress - television series . take the year record of this row . select the rows whose category record fuzzily matches to favorite tv actress - supporting role . take the year record of this row . the first record is less than the second record . the ...
13
9
{'and_8': 8, 'result_9': 9, 'less_4': 4, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_10': 10, 'category_11': 11, 'outstanding actress - television series_12': 12, 'year_13': 13, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_14': 14, 'category_15': 15, 'favorite tv actress - supporting role_16': 16, 'year_17': 17,...
{'and_8': 'and', 'result_9': 'true', 'less_4': 'less', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_10': 'all_rows', 'category_11': 'category', 'outstanding actress - television series_12': 'outstanding actress - television series', 'year_13': 'year', 'num_hop_3': 'num_hop', 'filter_str_eq_1': ...
{'and_8': [9], 'result_9': [], 'less_4': [8], 'num_hop_2': [4, 5], 'filter_str_eq_0': [2], 'all_rows_10': [0], 'category_11': [0], 'outstanding actress - television series_12': [0], 'year_13': [2], 'num_hop_3': [4, 6], 'filter_str_eq_1': [3], 'all_rows_14': [1], 'category_15': [1], 'favorite tv actress - supporting rol...
['year', 'recipient', 'role', 'category', 'result']
[['2007', 'sara ramirez', 'callie torres', 'outstanding actress - television series', 'nominated'], ['2008', 'sara ramirez', 'callie torres', 'outstanding actress - drama television series', 'nominated'], ['2009', 'sara ramirez', 'callie torres', 'outstanding actress - drama television series', 'nominated'], ['2011', '...
test matches ( 1991 - 2000 )
https://en.wikipedia.org/wiki/Test_matches_%281991%E2%80%932000%29
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12410929-70.html.csv
comparative
the west indies team ( wi ) won the february 1997 test match with 4 more wickets than they did in the december 1996 match .
{'row_1': '5', 'row_2': '3', 'col': '5', 'col_other': '1', 'relation': 'diff', 'record_mentioned': 'no', 'diff_result': {'diff_value': '4', 'bigger': 'row1'}}
{'func': 'eq', 'args': [{'func': 'diff', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', '1 , 2 , 3 february 1997'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose date record fuzzily matches to 1 , 2 , 3 february 1997 .', 'tostr': 'filter_eq { all_rows ; date ;...
eq { diff { hop { filter_eq { all_rows ; date ; 1 , 2 , 3 february 1997 } ; result } ; hop { filter_eq { all_rows ; date ; 26 , 27 , 28 december 1996 } ; result } } ; 4 } = true
select the rows whose date record fuzzily matches to 1 , 2 , 3 february 1997 . take the result record of this row . select the rows whose date record fuzzily matches to 26 , 27 , 28 december 1996 . take the result record of this row . the first record is 4 larger than the second record .
6
6
{'eq_5': 5, 'result_6': 6, 'diff_4': 4, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_7': 7, 'date_8': 8, '1 , 2 , 3 february 1997_9': 9, 'result_10': 10, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_11': 11, 'date_12': 12, '26 , 27 , 28 december 1996_13': 13, 'result_14': 14, '4_15': 15}
{'eq_5': 'eq', 'result_6': 'true', 'diff_4': 'diff', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_7': 'all_rows', 'date_8': 'date', '1 , 2 , 3 february 1997_9': '1 , 2 , 3 february 1997', 'result_10': 'result', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_11': 'all_rows...
{'eq_5': [6], 'result_6': [], 'diff_4': [5], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_7': [0], 'date_8': [0], '1 , 2 , 3 february 1997_9': [0], 'result_10': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_11': [1], 'date_12': [1], '26 , 27 , 28 december 1996_13': [1], 'result_14': [3], '4_15': [5]}
['date', 'home captain', 'away captain', 'venue', 'result']
[['22 , 23 , 24 , 25 , 26 november 1996', 'mark taylor', 'courtney walsh', 'brisbane cricket ground', 'aus by 123 runs'], ['29 , 30 november , 1 , 2 , 3 december 1996', 'mark taylor', 'courtney walsh', 'sydney cricket ground', 'aus by 124 runs'], ['26 , 27 , 28 december 1996', 'mark taylor', 'courtney walsh', 'melbourn...
westinghouse broadcasting
https://en.wikipedia.org/wiki/Westinghouse_Broadcasting
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1553485-1.html.csv
ordinal
kpix was the third earliest tv channel to be owned by the westinghouse broadcasting company .
{'row': '1', 'col': '4', 'order': '3', 'col_other': '2', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None}
{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'years owned', '3'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; years owned ; 3 }'}, 'station'], 'result': 'kpix', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; years owned ; 3 } ; station }'}, 'kpi...
eq { hop { nth_argmin { all_rows ; years owned ; 3 } ; station } ; kpix } = true
select the row whose years owned record of all rows is 3rd minimum . the station record of this row is kpix .
3
3
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'years owned_5': 5, '3_6': 6, 'station_7': 7, 'kpix_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', 'years owned_5': 'years owned', '3_6': '3', 'station_7': 'station', 'kpix_8': 'kpix'}
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'years owned_5': [0], '3_6': [0], 'station_7': [1], 'kpix_8': [2]}
['city of license / market', 'station', 'channel tv ( dt )', 'years owned', 'current affiliation']
[['san francisco - oakland - san jose', 'kpix', '5 ( 29 )', '1954 - 1995', 'cbs owned - and - operated ( o & o )'], ['baltimore', 'wjz - tv', '13 ( 13 )', '1957 - 1995', 'cbs owned - and - operated ( o & o )'], ['boston', 'wbz - tv', '4 ( 30 )', '1948 - 1995', 'cbs owned - and - operated ( o & o )'], ['charlotte', 'wpc...
2008 san francisco 49ers season
https://en.wikipedia.org/wiki/2008_San_Francisco_49ers_season
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15623820-1.html.csv
aggregation
in the 2008 san francisco 49ers season , the average contract time for a quarterback was 2 years .
{'scope': 'subset', 'col': '5', 'type': 'average', 'result': '2', 'subset': {'col': '1', 'criterion': 'equal', 'value': 'qb'}}
{'func': 'round_eq', 'args': [{'func': 'avg', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'pos', 'qb'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; pos ; qb }', 'tointer': 'select the rows whose pos record fuzzily matches to qb .'}, 'contract'], 'result': '2', 'ind': 1, 'tostr': 'avg { filter...
round_eq { avg { filter_eq { all_rows ; pos ; qb } ; contract } ; 2 } = true
select the rows whose pos record fuzzily matches to qb . the average of the contract record of these rows is 2 .
3
3
{'eq_2': 2, 'result_3': 3, 'avg_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'pos_5': 5, 'qb_6': 6, 'contract_7': 7, '2_8': 8}
{'eq_2': 'eq', 'result_3': 'true', 'avg_1': 'avg', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'pos_5': 'pos', 'qb_6': 'qb', 'contract_7': 'contract', '2_8': '2'}
{'eq_2': [3], 'result_3': [], 'avg_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'pos_5': [0], 'qb_6': [0], 'contract_7': [1], '2_8': [2]}
['pos', 'player', 'free agent type', '2007 team', 'contract']
[['wr', 'isaac bruce', 'released', 'st louis rams', '2 years , 6 million'], ['rb', 'deshaun foster', 'released', 'carolina panthers', '2 years , 1.8 million'], ['lb', 'roderick green', 'ufa', 'san francisco 49ers', '1 year'], ['qb', 'shaun hill', 'ufa', 'san francisco 49ers', '3 years , 6 million'], ['wr', 'bryant john...
irrigation in bolivia
https://en.wikipedia.org/wiki/Irrigation_in_Bolivia
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17118006-1.html.csv
aggregation
these departments in bolivia have an average total amount of irrigation approximately equal to 32366 .
{'scope': 'all', 'col': '6', 'type': 'average', 'result': '32366', 'subset': None}
{'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'total'], 'result': '32366', 'ind': 0, 'tostr': 'avg { all_rows ; total }'}, '32366'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; total } ; 32366 } = true', 'tointer': 'the average of the total record of all rows is 32366 .'}
round_eq { avg { all_rows ; total } ; 32366 } = true
the average of the total record of all rows is 32366 .
2
2
{'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'total_4': 4, '32366_5': 5}
{'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'total_4': 'total', '32366_5': '32366'}
{'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'total_4': [0], '32366_5': [1]}
['department', 'micro ( 10ha )', 'small ( 100ha )', 'medium ( 500ha )', 'big ( > 500ha )', 'total']
[['chuquisaca', '1653', '11370', '4261', '3884', '21168'], ['cochabamba', '1938', '22225', '27403', '35968', '81925'], ['la paz', '1703', '21047', '6052', '7192', '35994'], ['oruro', '940', '3638', '440', '9021', '14039'], ['potosã\xad', '3240', '10146', '2254', '600', '16240'], ['santa cruz', '269', '5456', '8434', '1...
the midlands , england
https://en.wikipedia.org/wiki/The_Midlands%2C_England
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-184077-2.html.csv
ordinal
in the midlands , england , the stadium ranked the third highest capacity is franklin 's gardens .
{'row': '2', 'col': '5', 'order': '3', 'col_other': '4', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None}
{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'capacity', '3'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; capacity ; 3 }'}, 'stadium'], 'result': "franklin 's gardens", 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; capacity ; 3 } ; stadium }'}...
eq { hop { nth_argmax { all_rows ; capacity ; 3 } ; stadium } ; franklin 's gardens } = true
select the row whose capacity record of all rows is 3rd maximum . the stadium record of this row is franklin 's gardens .
3
3
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'capacity_5': 5, '3_6': 6, 'stadium_7': 7, "franklin 's gardens_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', 'capacity_5': 'capacity', '3_6': '3', 'stadium_7': 'stadium', "franklin 's gardens_8": "franklin 's gardens"}
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'capacity_5': [0], '3_6': [0], 'stadium_7': [1], "franklin 's gardens_8": [2]}
['club', 'league', 'city / town', 'stadium', 'capacity']
[['leicester tigers', 'aviva premiership', 'leicester', 'welford road', '24000'], ['northampton saints', 'aviva premiership', 'northampton', "franklin 's gardens", '13600'], ['worcester warriors', 'aviva premiership', 'worcester', 'sixways stadium', '12068'], ['moseley', 'rfu championship', 'birmingham', 'billesley com...
galicia , spain
https://en.wikipedia.org/wiki/Galicia%2C_Spain
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12837-1.html.csv
unique
in galicia , spain , the only town with 2043 hours of sunlight is ourense .
{'scope': 'all', 'row': '5', 'col': '6', 'col_other': '1', 'criterion': 'equal', 'value': '2043', 'subset': None}
{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'sunlight hours', '2043'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose sunlight hours record is equal to 2043 .', 'tostr': 'filter_eq { all_rows ; sunlight hours ; 2043 }'}], 'result': True, 'ind': 1, 'tostr': ...
and { only { filter_eq { all_rows ; sunlight hours ; 2043 } } ; eq { hop { filter_eq { all_rows ; sunlight hours ; 2043 } ; city / town } ; ourense } } = true
select the rows whose sunlight hours record is equal to 2043 . there is only one such row in the table . the city / town record of this unqiue row is ourense .
6
5
{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'sunlight hours_7': 7, '2043_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'city / town_9': 9, 'ourense_10': 10}
{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'sunlight hours_7': 'sunlight hours', '2043_8': '2043', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'city / town_9': 'city / town', 'ourense_10': 'ourense'}
{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'sunlight hours_7': [0], '2043_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'city / town_9': [2], 'ourense_10': [3]}
['city / town', 'july av t', 'rain', 'days with rain ( year / summer )', 'days with frost', 'sunlight hours']
[['santiago de compostela', 'degree', 'mm ( in )', '141 / 19', '15', '1998'], ['a coruña', 'degree', 'mm ( in )', '131 / 19', '0', '1966'], ['lugo', 'degree', 'mm ( in )', '131 / 18', '42', '1821'], ['vigo', 'degree', 'mm ( in )', '130 / 18', '5', '2212'], ['ourense', 'degree', 'mm ( in )', '97 / 12', '30', '2043'], ['...
2005 - 06 primeira liga
https://en.wikipedia.org/wiki/2005%E2%80%9306_Primeira_Liga
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17933603-1.html.csv
comparative
of the two teams bases in the city of funchal , maritimo finished in better standing overall .
{'row_1': '10', 'row_2': '11', 'col': '5', 'col_other': '1,3', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None}
{'func': 'and', 'args': [{'func': 'less', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'club', 'marítimo'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose club record fuzzily matches to marítimo .', 'tostr': 'filter_eq { all_rows ; club ; marítimo }'}, '2004 - 2005 s...
and { less { hop { filter_eq { all_rows ; club ; marítimo } ; 2004 - 2005 season } ; hop { filter_eq { all_rows ; club ; nacional } ; 2004 - 2005 season } } ; and { eq { hop { filter_eq { all_rows ; club ; marítimo } ; city } ; funchal } ; eq { hop { filter_eq { all_rows ; club ; nacional } ; city } ; funchal } } } = t...
select the rows whose club record fuzzily matches to marítimo . take the 2004 - 2005 season record of this row . select the rows whose club record fuzzily matches to nacional . take the 2004 - 2005 season record of this row . the first record is less than the second record . the city record of the first row is funchal ...
13
11
{'and_10': 10, 'result_11': 11, 'less_4': 4, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_12': 12, 'club_13': 13, 'marítimo_14': 14, '2004 - 2005 season_15': 15, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_16': 16, 'club_17': 17, 'nacional_18': 18, '2004 - 2005 season_19': 19, 'and_9': 9, 'str_eq_6': 6, 'str_hop...
{'and_10': 'and', 'result_11': 'true', 'less_4': 'less', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_12': 'all_rows', 'club_13': 'club', 'marítimo_14': 'marítimo', '2004 - 2005 season_15': '2004 - 2005 season', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_16': 'all_row...
{'and_10': [11], 'result_11': [], 'less_4': [10], 'str_hop_2': [4], 'filter_str_eq_0': [2, 5], 'all_rows_12': [0], 'club_13': [0], 'marítimo_14': [0], '2004 - 2005 season_15': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3, 7], 'all_rows_16': [1], 'club_17': [1], 'nacional_18': [1], '2004 - 2005 season_19': [3], 'and_9':...
['club', "season 's last head coach", 'city', 'stadium', '2004 - 2005 season']
[['académica de coimbra', 'nelo vingada', 'coimbra', 'estádio cidade de coimbra', '14th in the liga'], ['belenenses', 'carlos carvalhal', 'lisbon', 'estádio do restelo', '9th in the liga'], ['benfica', 'ronald koeman', 'lisbon', 'estádio da luz', '1st in the liga'], ['boavista', 'carlos brito', 'porto', 'estádio do bes...
2007 - 08 atlanta hawks season
https://en.wikipedia.org/wiki/2007%E2%80%9308_Atlanta_Hawks_season
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11961582-10.html.csv
comparative
the game with a score of 81-104 took place three days before the game with a score of 77-96 .
{'row_1': '1', 'row_2': '2', 'col': '2', 'col_other': '4', 'relation': 'diff', 'record_mentioned': 'no', 'diff_result': {'diff_value': '3 days', 'bigger': 'row2'}}
{'func': 'eq', 'args': [{'func': 'diff', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'score', '81 - 104'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose score record fuzzily matches to 81 - 104 .', 'tostr': 'filter_eq { all_rows ; score ; 81 - 104 }'}, 'date'], 're...
eq { diff { hop { filter_eq { all_rows ; score ; 81 - 104 } ; date } ; hop { filter_eq { all_rows ; score ; 77 - 96 } ; date } } ; -3 days } = true
select the rows whose score record fuzzily matches to 81 - 104 . take the date record of this row . select the rows whose score record fuzzily matches to 77 - 96 . take the date record of this row . the second record is 3 days larger than the first 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, 'score_8': 8, '81 - 104_9': 9, 'date_10': 10, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_11': 11, 'score_12': 12, '77 - 96_13': 13, 'date_14': 14, '-3 days_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', 'score_8': 'score', '81 - 104_9': '81 - 104', 'date_10': 'date', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_11': 'all_rows', 'score_12': 'score', ...
{'str_eq_5': [6], 'result_6': [], 'diff_4': [5], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_7': [0], 'score_8': [0], '81 - 104_9': [0], 'date_10': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_11': [1], 'score_12': [1], '77 - 96_13': [1], 'date_14': [3], '-3 days_15': [5]}
['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'series']
[['1', 'april 20', 'boston', '81 - 104', 'a horford ( 20 )', 'a horford ( 10 )', 'j johnson ( 7 )', 'td banknorth garden 18624', '0 - 1'], ['2', 'april 23', 'boston', '77 - 96', 'two - way tie ( 13 )', 'a horford ( 9 )', 'two - way tie ( 3 )', 'td banknorth garden 18624', '0 - 2'], ['3', 'april 26', 'boston', '102 - 93...
list of dams and reservoirs in asturias
https://en.wikipedia.org/wiki/List_of_dams_and_reservoirs_in_Asturias
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-28702208-1.html.csv
superlative
the tallest embankment type dam in asturias is 67 metres high .
{'scope': 'subset', 'col_superlative': '5', 'row_superlative': '1', 'value_mentioned': 'yes', 'max_or_min': 'max', 'other_col': '4', 'subset': {'col': '4', 'criterion': 'equal', 'value': 'embankment'}}
{'func': 'eq', 'args': [{'func': 'max', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'type', 'embankment'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; type ; embankment }', 'tointer': 'select the rows whose type record fuzzily matches to embankment .'}, 'height ( m )'], 'result': '67.0', 'ind...
eq { max { filter_eq { all_rows ; type ; embankment } ; height ( m ) } ; 67.0 } = true
select the rows whose type record fuzzily matches to embankment . the maximum height ( m ) record of these rows is 67.0 .
3
3
{'eq_2': 2, 'result_3': 3, 'max_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'type_5': 5, 'embankment_6': 6, 'height (m)_7': 7, '67.0_8': 8}
{'eq_2': 'eq', 'result_3': 'true', 'max_1': 'max', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'type_5': 'type', 'embankment_6': 'embankment', 'height (m)_7': 'height ( m )', '67.0_8': '67.0'}
{'eq_2': [3], 'result_3': [], 'max_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'type_5': [0], 'embankment_6': [0], 'height (m)_7': [1], '67.0_8': [2]}
['reservoir', 'basin', 'location', 'type', 'height ( m )', 'length along the top ( m )', 'drainage basin ( km square )', 'reservoir surface ( ha )', 'volume ( hm cubic )']
[['alfilorios', 'barrea', 'ribera de arriba', 'embankment', '67.0', '171.7', '4.09', '52.0', '9.140'], ['arbón', 'navia', 'coaña , villayón', 'embankment', '35.0', '180.0', '2443.0', '270.0', '38.20'], ['barca , la', 'narcea', 'belmonte , tineo', 'arch', '73.5', '178.0', '1216.0', '194.0', '31.10'], ['doiras', 'navia',...
reinhold roth
https://en.wikipedia.org/wiki/Reinhold_Roth
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14860855-3.html.csv
majority
reinhold roth raced 250cc motorcyles the majority of his career .
{'scope': 'all', 'col': '2', 'most_or_all': 'most', 'criterion': 'equal', 'value': '250cc', 'subset': None}
{'func': 'most_str_eq', 'args': ['all_rows', 'class', '250cc'], 'result': True, 'ind': 0, 'tointer': 'for the class records of all rows , most of them fuzzily match to 250cc .', 'tostr': 'most_eq { all_rows ; class ; 250cc } = true'}
most_eq { all_rows ; class ; 250cc } = true
for the class records of all rows , most of them fuzzily match to 250cc .
1
1
{'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'class_3': 3, '250cc_4': 4}
{'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'class_3': 'class', '250cc_4': '250cc'}
{'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'class_3': [0], '250cc_4': [0]}
['year', 'class', 'team', 'points', 'wins']
[['1979', '350cc', 'yamaha', '3', '0'], ['1980', '250cc', 'yamaha', '4', '0'], ['1982', '250cc', 'yamaha', '4', '0'], ['1982', '500cc', 'suzuki', '0', '0'], ['1983', '250cc', 'yamaha', '14', '0'], ['1984', '500cc', 'honda', '14', '0'], ['1985', '250cc', 'romer - juchem', '29', '0'], ['1986', '250cc', 'hb - honda', '10'...
1926 vfl season
https://en.wikipedia.org/wiki/1926_VFL_season
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10746808-12.html.csv
superlative
the match played at the punt road oval venue drew the largest crowd .
{'scope': 'all', 'col_superlative': '6', 'row_superlative': '1', 'value_mentioned': 'yes', 'max_or_min': 'max', 'other_col': '5', 'subset': None}
{'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'max', 'args': ['all_rows', 'crowd'], 'result': '27000', 'ind': 0, 'tostr': 'max { all_rows ; crowd }', 'tointer': 'the maximum crowd record of all rows is 27000 .'}, '27000'], 'result': True, 'ind': 1, 'tostr': 'eq { max { all_rows ; crowd } ; 27000 }', 'tointe...
and { eq { max { all_rows ; crowd } ; 27000 } ; eq { hop { argmax { all_rows ; crowd } ; venue } ; punt road oval } } = true
the maximum crowd record of all rows is 27000 . the venue record of the row with superlative crowd record is punt road oval .
6
6
{'and_5': 5, 'result_6': 6, 'eq_1': 1, 'max_0': 0, 'all_rows_7': 7, 'crowd_8': 8, '27000_9': 9, 'str_eq_4': 4, 'str_hop_3': 3, 'argmax_2': 2, 'all_rows_10': 10, 'crowd_11': 11, 'venue_12': 12, 'punt road oval_13': 13}
{'and_5': 'and', 'result_6': 'true', 'eq_1': 'eq', 'max_0': 'max', 'all_rows_7': 'all_rows', 'crowd_8': 'crowd', '27000_9': '27000', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'argmax_2': 'argmax', 'all_rows_10': 'all_rows', 'crowd_11': 'crowd', 'venue_12': 'venue', 'punt road oval_13': 'punt road oval'}
{'and_5': [6], 'result_6': [], 'eq_1': [5], 'max_0': [1], 'all_rows_7': [0], 'crowd_8': [0], '27000_9': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'argmax_2': [3], 'all_rows_10': [2], 'crowd_11': [2], 'venue_12': [3], 'punt road oval_13': [4]}
['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date']
[['richmond', '10.15 ( 75 )', 'south melbourne', '16.12 ( 108 )', 'punt road oval', '27000', '17 july 1926'], ['footscray', '7.14 ( 56 )', 'geelong', '15.17 ( 107 )', 'western oval', '17000', '17 july 1926'], ['collingwood', '18.16 ( 124 )', 'fitzroy', '11.16 ( 82 )', 'victoria park', '16000', '17 july 1926'], ['carlto...
doug lewis ( skier )
https://en.wikipedia.org/wiki/Doug_Lewis_%28skier%29
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10103807-2.html.csv
unique
doug lewis 's best downhill skiing performance was the only time he placed in the top ten in a competition in argentina .
{'scope': 'all', 'row': '5', 'col': '3', 'col_other': '4', 'criterion': 'fuzzily_match', 'value': 'argentina', 'subset': None}
{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location', 'argentina'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose location record fuzzily matches to argentina .', 'tostr': 'filter_eq { all_rows ; location ; argentina }'}], 'result': True, 'ind': 1, '...
and { only { filter_eq { all_rows ; location ; argentina } } ; eq { hop { filter_eq { all_rows ; location ; argentina } ; discipline } ; downhill } } = true
select the rows whose location record fuzzily matches to argentina . there is only one such row in the table . the discipline record of this unqiue row is downhill .
6
5
{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'location_7': 7, 'argentina_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'discipline_9': 9, 'downhill_10': 10}
{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'location_7': 'location', 'argentina_8': 'argentina', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'discipline_9': 'discipline', 'downhill_10': 'downhill'}
{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'location_7': [0], 'argentina_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'discipline_9': [2], 'downhill_10': [3]}
['season', 'date', 'location', 'discipline', 'place']
[['1984', '11 mar 1984', 'whistler , bc , canada', 'downhill', '8th'], ['1985', '15 dec 1984', 'val gardena , italy', 'downhill', '9th'], ['1985', '11 jan 1985', 'kitzbühel , austria', 'downhill', '10th'], ['1985', '1985 world championships', '1985 world championships', '1985 world championships', '1985 world champions...
1991 open championship
https://en.wikipedia.org/wiki/1991_Open_Championship
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18131508-5.html.csv
aggregation
all the players in the 1991 open championship had an average score of around 140 .
{'scope': 'all', 'col': '4', 'type': 'average', 'result': '140', 'subset': None}
{'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'score'], 'result': '140', 'ind': 0, 'tostr': 'avg { all_rows ; score }'}, '140'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; score } ; 140 } = true', 'tointer': 'the average of the score record of all rows is 140 .'}
round_eq { avg { all_rows ; score } ; 140 } = true
the average of the score record of all rows is 140 .
2
2
{'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'score_4': 4, '140_5': 5}
{'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'score_4': 'score', '140_5': '140'}
{'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'score_4': [0], '140_5': [1]}
['place', 'player', 'country', 'score', 'to par']
[['t1', 'gary hallberg', 'united states', '68 + 70 = 138', '- 2'], ['t1', 'mike harwood', 'australia', '68 + 70 = 138', '- 2'], ['t1', 'andrew oldcorn', 'scotland', '71 + 67 = 138', '- 2'], ['t4', 'seve ballesteros', 'spain', '66 + 73 = 139', '- 1'], ['t4', 'steve elkington', 'australia', '71 + 68 = 139', '- 1'], ['t4'...
list of hewitts and nuttalls in england
https://en.wikipedia.org/wiki/List_of_Hewitts_and_Nuttalls_in_England
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10814429-1.html.csv
aggregation
for hewitts and nuttalls in england , the average height when the parent is the cheviot is 642 .
{'scope': 'subset', 'col': '2', 'type': 'average', 'result': '642', 'subset': {'col': '5', 'criterion': 'equal', 'value': 'the cheviot'}}
{'func': 'round_eq', 'args': [{'func': 'avg', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'parent', 'the cheviot'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; parent ; the cheviot }', 'tointer': 'select the rows whose parent record fuzzily matches to the cheviot .'}, 'height ( m )'], 'result...
round_eq { avg { filter_eq { all_rows ; parent ; the cheviot } ; height ( m ) } ; 642 } = true
select the rows whose parent record fuzzily matches to the cheviot . the average of the height ( m ) record of these rows is 642 .
3
3
{'eq_2': 2, 'result_3': 3, 'avg_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'parent_5': 5, 'the cheviot_6': 6, 'height (m)_7': 7, '642_8': 8}
{'eq_2': 'eq', 'result_3': 'true', 'avg_1': 'avg', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'parent_5': 'parent', 'the cheviot_6': 'the cheviot', 'height (m)_7': 'height ( m )', '642_8': '642'}
{'eq_2': [3], 'result_3': [], 'avg_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'parent_5': [0], 'the cheviot_6': [0], 'height (m)_7': [1], '642_8': [2]}
['peak', 'height ( m )', 'prom ( m )', 'class', 'parent']
[['the cheviot', '815', '556', 'marilyn', 'broad law'], ['hedgehope hill', '714', '148', 'hewitt', 'the cheviot'], ['comb fell', '652', '69', 'hewitt', 'the cheviot'], ['windy gyle', '619', '113', 'hewitt', 'the cheviot'], ['cushat law', '615', '147', 'hewitt', 'the cheviot'], ['bloodybush edge', '610', '114', 'hewitt'...
hit 'n run tour
https://en.wikipedia.org/wiki/Hit_%27n_Run_Tour
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12946465-1.html.csv
ordinal
the concert on july 21st recorded the highest attendance of the hit 'n run tour .
{'row': '2', 'col': '5', 'order': '1', 'col_other': '1', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None}
{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'attendance', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; attendance ; 1 }'}, 'date'], 'result': 'july 21 , 2007', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; attendance ; 1 } ; date }'}, 'ju...
eq { hop { nth_argmax { all_rows ; attendance ; 1 } ; date } ; july 21 , 2007 } = true
select the row whose attendance record of all rows is 1st maximum . the date record of this row is july 21 , 2007 .
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, 'july 21 , 2007_8': 8}
{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'attendance_5': 'attendance', '1_6': '1', 'date_7': 'date', 'july 21 , 2007_8': 'july 21 , 2007'}
{'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], 'july 21 , 2007_8': [2]}
['date', 'city', 'country', 'venue', 'attendance']
[['july 20 , 2007', 'sault ste marie , michigan', 'united states', 'kewadin casino', '10000'], ['july 21 , 2007', 'cadott , wisconsin', 'united states', 'cadott rock fest', '35000'], ['july 25 , 2007', 'anaheim , california', 'united states', 'cisco customer appreciation event', '1000'], ['july 27 , 2007', 'san jacinto...
greater dhaka area
https://en.wikipedia.org/wiki/Greater_Dhaka_Area
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-24027047-1.html.csv
superlative
the 2011 population of dhaka district is larger than any other administrative division in the greater dhaka area .
{'scope': 'all', 'col_superlative': '4', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None}
{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'population 2011 census ( adjusted )'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; population 2011 census ( adjusted ) }'}, 'administrative division'], 'result': 'dhaka district', 'ind': 1, 'tostr': 'hop { argm...
eq { hop { argmax { all_rows ; population 2011 census ( adjusted ) } ; administrative division } ; dhaka district } = true
select the row whose population 2011 census ( adjusted ) record of all rows is maximum . the administrative division record of this row is dhaka district .
3
3
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'population 2011 census (adjusted)_5': 5, 'administrative division_6': 6, 'dhaka district_7': 7}
{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'population 2011 census (adjusted)_5': 'population 2011 census ( adjusted )', 'administrative division_6': 'administrative division', 'dhaka district_7': 'dhaka district'}
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'population 2011 census (adjusted)_5': [0], 'administrative division_6': [1], 'dhaka district_7': [2]}
['administrative division', 'area ( km square ) 2011', 'population 2001 census ( adjusted )', 'population 2011 census ( adjusted )', 'population density ( / km square 2011 )']
[['dhaka district', '1463.6', '9036647', '12517361', '8552.4'], ['savar upazila', '282.11', '629695', '1442885', '5114.6'], ['keraniganj upazila', '166.82', '649373', '824538', '4942.68'], ['narayanganj district', '684.37', '2300514', '3074078', '4491.8'], ['narayanganj sadar upazila', '100.74', '946205', '1381796', '1...
kharkov governorate
https://en.wikipedia.org/wiki/Kharkov_Governorate
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17051786-1.html.csv
ordinal
in the 1897 census of the kharkov governorate , yiddish has the third-highest number of speakers .
{'row': '3', 'col': '2', 'order': '3', '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', 'number', '3'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; number ; 3 }'}, 'language'], 'result': 'yiddish', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; number ; 3 } ; language }'}, 'yiddish'], 'r...
eq { hop { nth_argmax { all_rows ; number ; 3 } ; language } ; yiddish } = true
select the row whose number record of all rows is 3rd maximum . the language record of this row is yiddish .
3
3
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'number_5': 5, '3_6': 6, 'language_7': 7, 'yiddish_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', 'number_5': 'number', '3_6': '3', 'language_7': 'language', 'yiddish_8': 'yiddish'}
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'number_5': [0], '3_6': [0], 'language_7': [1], 'yiddish_8': [2]}
['language', 'number', 'percentage ( % )', 'males', 'females']
[['ukrainian', '2 009 411', '80.62', '1 004 372', '1 005 039'], ['russian', '440 936', '17.69', '225 803', '215 133'], ['yiddish', '12 650', '0.5', '7 007', '5 643'], ['belarusian', '10 258', '0.41', '4 936', '5 322'], ['german', '9 080', '0.36', '4 504', '4 576'], ['polish', '5 910', '0.23', '4 056', '1 854'], ['tatar...
newfoundland and labrador general election , 2011
https://en.wikipedia.org/wiki/Newfoundland_and_Labrador_general_election%2C_2011
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-24778847-2.html.csv
ordinal
the poll of the 2011 newfoundland and labrador general election taken from february 12 - march 4 , 2008 had the third highest amount of progressive conservatives .
{'row': '19', 'col': '4', 'order': '3', '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', 'progressive conservative', '3'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; progressive conservative ; 3 }'}, 'date of polling'], 'result': 'february 12 - march 4 , 2008', 'ind': 1, 'tostr': 'hop { nth...
eq { hop { nth_argmax { all_rows ; progressive conservative ; 3 } ; date of polling } ; february 12 - march 4 , 2008 } = true
select the row whose progressive conservative record of all rows is 3rd maximum . the date of polling record of this row is february 12 - march 4 , 2008 .
3
3
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'progressive conservative_5': 5, '3_6': 6, 'date of polling_7': 7, 'february 12 - march 4 , 2008_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', 'progressive conservative_5': 'progressive conservative', '3_6': '3', 'date of polling_7': 'date of polling', 'february 12 - march 4 , 2008_8': 'february 12 - march 4 , 2008'}
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'progressive conservative_5': [0], '3_6': [0], 'date of polling_7': [1], 'february 12 - march 4 , 2008_8': [2]}
['polling firm', 'date of polling', 'link', 'progressive conservative', 'liberal', 'new democratic']
[['corporate research associates', 'september 29 - october 3 , 2011', 'html', '59', '16', '25'], ['environics', 'september 29 - october 4 , 2011', 'html', '54', '13', '33'], ['marketquest omnifacts research', 'september 28 - 30 , 2011', 'html', '54', '13', '33'], ['marketquest omnifacts research', 'september 16 - 19 , ...