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stringclasses 15
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1961 vfl season
|
https://en.wikipedia.org/wiki/1961_VFL_season
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10776330-15.html.csv
|
superlative
|
the game between st kilda and melbourne had the highest crowd turnout .
|
{'scope': 'all', 'col_superlative': '6', 'row_superlative': '5', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1,3', 'subset': None}
|
{'func': 'and', 'args': [{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'crowd'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; crowd }'}, 'home team'], 'result': 'st kilda', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; crowd } ; home team }'}, 'st kilda'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; crowd } ; home team } ; st kilda }', 'tointer': 'select the row whose crowd record of all rows is maximum . the home team record of this row is st kilda .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'crowd'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; crowd }'}, 'away team'], 'result': 'melbourne', 'ind': 3, 'tostr': 'hop { argmax { all_rows ; crowd } ; away team }'}, 'melbourne'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { argmax { all_rows ; crowd } ; away team } ; melbourne }', 'tointer': 'the away team record of this row is melbourne .'}], 'result': True, 'ind': 5, 'tostr': 'and { eq { hop { argmax { all_rows ; crowd } ; home team } ; st kilda } ; eq { hop { argmax { all_rows ; crowd } ; away team } ; melbourne } } = true', 'tointer': 'select the row whose crowd record of all rows is maximum . the home team record of this row is st kilda . the away team record of this row is melbourne .'}
|
and { eq { hop { argmax { all_rows ; crowd } ; home team } ; st kilda } ; eq { hop { argmax { all_rows ; crowd } ; away team } ; melbourne } } = true
|
select the row whose crowd record of all rows is maximum . the home team record of this row is st kilda . the away team record of this row is melbourne .
|
7
|
6
|
{'and_5': 5, 'result_6': 6, 'str_eq_2': 2, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_7': 7, 'crowd_8': 8, 'home team_9': 9, 'st kilda_10': 10, 'str_eq_4': 4, 'str_hop_3': 3, 'away team_11': 11, 'melbourne_12': 12}
|
{'and_5': 'and', 'result_6': 'true', 'str_eq_2': 'str_eq', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_7': 'all_rows', 'crowd_8': 'crowd', 'home team_9': 'home team', 'st kilda_10': 'st kilda', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'away team_11': 'away team', 'melbourne_12': 'melbourne'}
|
{'and_5': [6], 'result_6': [], 'str_eq_2': [5], 'str_hop_1': [2], 'argmax_0': [1, 3], 'all_rows_7': [0], 'crowd_8': [0], 'home team_9': [1], 'st kilda_10': [2], 'str_eq_4': [5], 'str_hop_3': [4], 'away team_11': [3], 'melbourne_12': [4]}
|
['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date']
|
[['hawthorn', '15.10 ( 100 )', 'north melbourne', '6.11 ( 47 )', 'glenferrie oval', '14000', '5 august 1961'], ['essendon', '13.16 ( 94 )', 'geelong', '7.14 ( 56 )', 'windy hill', '27500', '5 august 1961'], ['collingwood', '5.10 ( 40 )', 'footscray', '11.12 ( 78 )', 'victoria park', '22324', '5 august 1961'], ['carlton', '17.9 ( 111 )', 'south melbourne', '7.10 ( 52 )', 'princes park', '16889', '5 august 1961'], ['st kilda', '9.12 ( 66 )', 'melbourne', '7.13 ( 55 )', 'junction oval', '33100', '5 august 1961'], ['richmond', '9.9 ( 63 )', 'fitzroy', '9.14 ( 68 )', 'punt road oval', '15547', '5 august 1961']]
|
melbourne victory records and statistics
|
https://en.wikipedia.org/wiki/Melbourne_Victory_records_and_statistics
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18639024-11.html.csv
|
unique
|
among melbourne victory fc 's all-time appearance records , kevin muscat is the only one whom has no substitute appearances in the a-league .
|
{'scope': 'all', 'row': '5', 'col': '3', 'col_other': '1', 'criterion': 'fuzzily_match', 'value': '( 0 )', 'subset': None}
|
{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'a - league', '( 0 )'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose a - league record fuzzily matches to ( 0 ) .', 'tostr': 'filter_eq { all_rows ; a - league ; ( 0 ) }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; a - league ; ( 0 ) } }', 'tointer': 'select the rows whose a - league record fuzzily matches to ( 0 ) . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'a - league', '( 0 )'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose a - league record fuzzily matches to ( 0 ) .', 'tostr': 'filter_eq { all_rows ; a - league ; ( 0 ) }'}, 'name'], 'result': 'kevin muscat', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; a - league ; ( 0 ) } ; name }'}, 'kevin muscat'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; a - league ; ( 0 ) } ; name } ; kevin muscat }', 'tointer': 'the name record of this unqiue row is kevin muscat .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; a - league ; ( 0 ) } } ; eq { hop { filter_eq { all_rows ; a - league ; ( 0 ) } ; name } ; kevin muscat } } = true', 'tointer': 'select the rows whose a - league record fuzzily matches to ( 0 ) . there is only one such row in the table . the name record of this unqiue row is kevin muscat .'}
|
and { only { filter_eq { all_rows ; a - league ; ( 0 ) } } ; eq { hop { filter_eq { all_rows ; a - league ; ( 0 ) } ; name } ; kevin muscat } } = true
|
select the rows whose a - league record fuzzily matches to ( 0 ) . there is only one such row in the table . the name record of this unqiue row is kevin muscat .
|
6
|
5
|
{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'a - league_7': 7, '(0)_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'name_9': 9, 'kevin muscat_10': 10}
|
{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'a - league_7': 'a - league', '(0)_8': '( 0 )', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'name_9': 'name', 'kevin muscat_10': 'kevin muscat'}
|
{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'a - league_7': [0], '(0)_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'name_9': [2], 'kevin muscat_10': [3]}
|
['name', 'years', 'a - league', 'finals', 'total']
|
[['archie thompson', '2005 / 06 -', '149 ( 5 )', '11 ( 2 )', '170 ( 9 )'], ['adrian leijer', '2006 / 07 - 2007 / 08 , 2009 / 10 -', '133 ( 1 )', '9 ( 0 )', '153 ( 1 )'], ['rodrigo vargas', '2006 / 07 - 2011 / 2012', '129 ( 1 )', '10 ( 0 )', '153 ( 1 )'], ['leigh broxham', '2006 / 2007 -', '124 ( 37 )', '6 ( 1 )', '143 ( 39 )'], ['kevin muscat', '2005 / 06 - 2010 / 2011', '113 ( 0 )', '9 ( 0 )', '138 ( 0 )'], ['carlos hernã ¡ ndez', '2007 / 08 - 2011 / 2012', '114 ( 11 )', '7 ( 1 )', '134 ( 16 )'], ['danny allsopp', '2005 / 06 - 2009 , 2009 / 2010 -', '111 ( 17 )', '7 ( 0 )', '129 ( 17 )'], ['grant brebner', '2006 / 07 - 2011 / 2012', '110 ( 22 )', '9 ( 3 )', '126 ( 25 )'], ['billy celeski', '2009 / 10 - 2012 / 13', '86 ( 12 )', '6 ( 1 )', '101 ( 16 )'], ['matthew kemp', '2006 / 07 - 2011 / 2012', '76 ( 7 )', '3 ( 0 )', '89 ( 7 )']]
|
united states house of representatives elections , 1824
|
https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1824
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2668264-8.html.csv
|
ordinal
|
henry clay recorded the highest percentage ratio among the candidates of the 1824 house of representatives elections .
|
{'row': '2', 'col': '6', 'order': '1', 'col_other': '2', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None}
|
{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'candidates', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; candidates ; 1 }'}, 'incumbent'], 'result': 'henry clay', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; candidates ; 1 } ; incumbent }'}, 'henry clay'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; candidates ; 1 } ; incumbent } ; henry clay } = true', 'tointer': 'select the row whose candidates record of all rows is 1st maximum . the incumbent record of this row is henry clay .'}
|
eq { hop { nth_argmax { all_rows ; candidates ; 1 } ; incumbent } ; henry clay } = true
|
select the row whose candidates record of all rows is 1st maximum . the incumbent record of this row is henry clay .
|
3
|
3
|
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'candidates_5': 5, '1_6': 6, 'incumbent_7': 7, 'henry clay_8': 8}
|
{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'candidates_5': 'candidates', '1_6': '1', 'incumbent_7': 'incumbent', 'henry clay_8': 'henry clay'}
|
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'candidates_5': [0], '1_6': [0], 'incumbent_7': [1], 'henry clay_8': [2]}
|
['district', 'incumbent', 'party', 'first elected', 'result', 'candidates']
|
[['kentucky 1', 'david trimble', 'adams - clay republican', '1816', 're - elected', 'david trimble ( a )'], ['kentucky 3', 'henry clay', 'adams - clay republican', '1810 1822', 're - elected', 'henry clay ( a ) 100 %'], ['kentucky 4', 'robert p letcher', 'adams - clay republican', '1822', 're - elected', 'robert p letcher ( a ) 60.1 % john speed smith 39.9 %'], ['kentucky 6', 'david white', 'adams - clay republican', '1822', 'retired jacksonian gain', 'joseph lecompte ( j ) john logan'], ['kentucky 7', 'thomas p moore', 'jacksonian republican', '1822', 're - elected', 'thomas p moore ( j ) samuel woodson']]
|
aguaclara
|
https://en.wikipedia.org/wiki/AguaClara
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18268930-1.html.csv
|
majority
|
the majority of aguaclara locations were constructed with app as their partner .
|
{'scope': 'all', 'col': '2', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'app', 'subset': None}
|
{'func': 'most_str_eq', 'args': ['all_rows', 'partner', 'app'], 'result': True, 'ind': 0, 'tointer': 'for the partner records of all rows , most of them fuzzily match to app .', 'tostr': 'most_eq { all_rows ; partner ; app } = true'}
|
most_eq { all_rows ; partner ; app } = true
|
for the partner records of all rows , most of them fuzzily match to app .
|
1
|
1
|
{'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'partner_3': 3, 'app_4': 4}
|
{'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'partner_3': 'partner', 'app_4': 'app'}
|
{'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'partner_3': [0], 'app_4': [0]}
|
['location', 'partner', 'construction start', 'inauguration date', 'population served', 'design flow ( lpm )']
|
[['ojojona , hon', 'app', '2006 june', '2007 july', '2000', '375'], ['tamara , hon', 'app', '2008 january', '2008 june', '3500', '720'], ['marcala , hon', 'irwa', '2007 october', '2008 july', '9000', '1900'], ['4 comunidades , hon', 'app', '2008 october', '2009 march', '2000', '375'], ['agalteca , hon', 'app', '2009 october', '2010 june', '2200', '375'], ['marcala , hon expansion', 'app / acra', '2010 november', '2011 may', '6000', '1300'], ['alauca , el paraiso , hon', 'app', '2011 may', '2012 february', '3600', '720'], ['atima , santa barbara , hon', 'app', '2011 december', '2012 may', '4000', '960']]
|
list of england national rugby union team results 1980 - 89
|
https://en.wikipedia.org/wiki/List_of_England_national_rugby_union_team_results_1980%E2%80%9389
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18178608-10.html.csv
|
aggregation
|
in 1980-89 , the england national rugby union team scored a total of 53 against opposing teams .
|
{'scope': 'all', 'col': '2', 'type': 'sum', 'result': '53', 'subset': None}
|
{'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'against'], 'result': '53', 'ind': 0, 'tostr': 'sum { all_rows ; against }'}, '53'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; against } ; 53 } = true', 'tointer': 'the sum of the against record of all rows is 53 .'}
|
round_eq { sum { all_rows ; against } ; 53 } = true
|
the sum of the against record of all rows is 53 .
|
2
|
2
|
{'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'against_4': 4, '53_5': 5}
|
{'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'against_4': 'against', '53_5': '53'}
|
{'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'against_4': [0], '53_5': [1]}
|
['opposing teams', 'against', 'date', 'venue', 'status']
|
[['scotland', '12', '04 / 02 / 1989', 'twickenham , london', 'five nations'], ['ireland', '3', '18 / 02 / 1989', 'lansdowne road , dublin', 'five nations'], ['france', '0', '04 / 03 / 1989', 'twickenham , london', 'five nations'], ['wales', '12', '18 / 03 / 1989', 'cardiff arms park , cardiff', 'five nations'], ['romania', '3', '13 / 05 / 1989', 'dinamo stadium , bucharest', 'test match'], ['fiji', '23', '04 / 11 / 1989', 'twickenham , london', 'test match']]
|
shinji nakano
|
https://en.wikipedia.org/wiki/Shinji_Nakano
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1226567-5.html.csv
|
superlative
|
the highest number of laps shinji nakano completed in a race was 325 .
|
{'scope': 'all', 'col_superlative': '5', 'row_superlative': '6', 'value_mentioned': 'yes', 'max_or_min': 'max', 'other_col': 'n/a', 'subset': None}
|
{'func': 'eq', 'args': [{'func': 'max', 'args': ['all_rows', 'laps'], 'result': '325', 'ind': 0, 'tostr': 'max { all_rows ; laps }', 'tointer': 'the maximum laps record of all rows is 325 .'}, '325'], 'result': True, 'ind': 1, 'tostr': 'eq { max { all_rows ; laps } ; 325 } = true', 'tointer': 'the maximum laps record of all rows is 325 .'}
|
eq { max { all_rows ; laps } ; 325 } = true
|
the maximum laps record of all rows is 325 .
|
2
|
2
|
{'eq_1': 1, 'result_2': 2, 'max_0': 0, 'all_rows_3': 3, 'laps_4': 4, '325_5': 5}
|
{'eq_1': 'eq', 'result_2': 'true', 'max_0': 'max', 'all_rows_3': 'all_rows', 'laps_4': 'laps', '325_5': '325'}
|
{'eq_1': [2], 'result_2': [], 'max_0': [1], 'all_rows_3': [0], 'laps_4': [0], '325_5': [1]}
|
['year', 'team', 'co - drivers', 'class', 'laps', 'pos', 'class pos']
|
[['2005', 'courage compétition', 'jonathan cochet bruce jouanny', 'lmp1', '52', 'dnf', 'dnf'], ['2006', 'courage compétition', 'jean - marc gounon haruki kurosawa', 'lmp1', '35', 'dnf', 'dnf'], ['2007', 'creation autosportif ltd', 'jamie campbell - walter felipe ortiz', 'lmp1', '55', 'dnf', 'dnf'], ['2008', 'epsilon euskadi', 'stefan johansson jean - marc gounon', 'lmp1', '158', 'dnf', 'dnf'], ['2011', 'oak racing', 'nicolas de crem jan charouz', 'lmp2', '313', '14th', '5th'], ['2012', 'boutsen ginion racing', 'bastien brière jens petersen', 'lmp2', '325', '24th', '10th']]
|
2010 fei world equestrian games
|
https://en.wikipedia.org/wiki/2010_FEI_World_Equestrian_Games
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11661065-10.html.csv
|
ordinal
|
germany recorded the highest number of bronze in the fei world equestrian games of 2010 .
|
{'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': 'germany', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; bronze ; 1 } ; nation }'}, 'germany'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; bronze ; 1 } ; nation } ; germany } = true', 'tointer': 'select the row whose bronze record of all rows is 1st maximum . the nation record of this row is germany .'}
|
eq { hop { nth_argmax { all_rows ; bronze ; 1 } ; nation } ; germany } = true
|
select the row whose bronze record of all rows is 1st maximum . the nation record of this row is germany .
|
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, 'germany_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', 'germany_8': 'germany'}
|
{'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], 'germany_8': [2]}
|
['rank', 'nation', 'gold', 'silver', 'bronze', 'total']
|
[['1', 'great britain', '9', '7', '3', '19'], ['2', 'germany', '5', '5', '4', '14'], ['3', 'netherlands', '5', '3', '1', '9'], ['4', 'united states of america', '3', '2', '3', '8'], ['5', 'belgium', '1', '2', '1', '4'], ['6', 'united arab emirates', '1', '1', '1', '3'], ['7', 'australia', '1', '0', '2', '3'], ['8', 'spain', '1', '0', '0', '1'], ['8', 'switzerland', '1', '0', '0', '1'], ['10', 'denmark', '0', '3', '3', '6'], ['11', 'france', '0', '2', '1', '3'], ['12', 'canada', '0', '1', '2', '3'], ['13', 'saudi arabia', '0', '1', '0', '1'], ['14', 'new zealand', '0', '0', '2', '2'], ['15', 'austria', '0', '0', '1', '1'], ['15', 'finland', '0', '0', '1', '1'], ['15', 'italy', '0', '0', '1', '1'], ['15', 'norway', '0', '0', '1', '1'], ['total', 'total', '27', '27', '27', '81']]
|
list of australian test bowlers who have taken over 200 test wickets
|
https://en.wikipedia.org/wiki/List_of_Australian_Test_bowlers_who_have_taken_over_200_Test_wickets
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18914438-1.html.csv
|
comparative
|
of the australian test bowlers who have taken over 200 test wickets had under 100 matches , jeff thomason had one more match than mitchell johnson .
|
{'row_1': '14', 'row_2': '13', 'col': '3', 'col_other': '1', 'relation': 'diff', 'record_mentioned': 'no', 'diff_result': {'diff_value': '1', 'bigger': 'row1'}}
|
{'func': 'eq', 'args': [{'func': 'diff', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'name', 'jeff thomson'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose name record fuzzily matches to jeff thomson .', 'tostr': 'filter_eq { all_rows ; name ; jeff thomson }'}, 'matches'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; name ; jeff thomson } ; matches }', 'tointer': 'select the rows whose name record fuzzily matches to jeff thomson . take the matches record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'name', 'mitchell johnson'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose name record fuzzily matches to mitchell johnson .', 'tostr': 'filter_eq { all_rows ; name ; mitchell johnson }'}, 'matches'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; name ; mitchell johnson } ; matches }', 'tointer': 'select the rows whose name record fuzzily matches to mitchell johnson . take the matches record of this row .'}], 'result': '1', 'ind': 4, 'tostr': 'diff { hop { filter_eq { all_rows ; name ; jeff thomson } ; matches } ; hop { filter_eq { all_rows ; name ; mitchell johnson } ; matches } }'}, '1'], 'result': True, 'ind': 5, 'tostr': 'eq { diff { hop { filter_eq { all_rows ; name ; jeff thomson } ; matches } ; hop { filter_eq { all_rows ; name ; mitchell johnson } ; matches } } ; 1 } = true', 'tointer': 'select the rows whose name record fuzzily matches to jeff thomson . take the matches record of this row . select the rows whose name record fuzzily matches to mitchell johnson . take the matches record of this row . the first record is 1 larger than the second record .'}
|
eq { diff { hop { filter_eq { all_rows ; name ; jeff thomson } ; matches } ; hop { filter_eq { all_rows ; name ; mitchell johnson } ; matches } } ; 1 } = true
|
select the rows whose name record fuzzily matches to jeff thomson . take the matches record of this row . select the rows whose name record fuzzily matches to mitchell johnson . take the matches record of this row . the first record is 1 larger than the second record .
|
6
|
6
|
{'eq_5': 5, 'result_6': 6, 'diff_4': 4, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_7': 7, 'name_8': 8, 'jeff thomson_9': 9, 'matches_10': 10, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_11': 11, 'name_12': 12, 'mitchell johnson_13': 13, 'matches_14': 14, '1_15': 15}
|
{'eq_5': 'eq', 'result_6': 'true', 'diff_4': 'diff', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_7': 'all_rows', 'name_8': 'name', 'jeff thomson_9': 'jeff thomson', 'matches_10': 'matches', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_11': 'all_rows', 'name_12': 'name', 'mitchell johnson_13': 'mitchell johnson', 'matches_14': 'matches', '1_15': '1'}
|
{'eq_5': [6], 'result_6': [], 'diff_4': [5], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_7': [0], 'name_8': [0], 'jeff thomson_9': [0], 'matches_10': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_11': [1], 'name_12': [1], 'mitchell johnson_13': [1], 'matches_14': [3], '1_15': [5]}
|
['name', 'career', 'matches', 'overs', 'maidens', 'runs', 'wickets', 'average', 'best']
|
[['shane warne', '1992 - 2007', '145', '6784.1', '1762', '17995', '708', '25.42', '8 / 71'], ['glenn mcgrath', '1993 - 2007', '124', '4874.4', '1470', '12186', '563', '21.64', '8 / 24'], ['dennis lillee', '1971 - 1984', '70', '2834.1', '652', '8493', '355', '23.92', '7 / 83'], ['brett lee', '1999 - 2010', '76', '2755.1', '547', '9555', '310', '30.82', '5 / 30'], ['craig mcdermott', '1984 - 1996', '71', '2764.2', '583', '8332', '291', '28.63', '8 / 97'], ['jason gillespie', '1996 - 2006', '71', '2372.2', '630', '6770', '259', '26.14', '7 / 37'], ['richie benaud', '1952 - 1964', '63', '2727.2', '805', '6704', '248', '27.03', '7 / 72'], ['graham mckenzie', '1961 - 1971', '60', '2629.5', '547', '7328', '246', '29.79', '8 / 71'], ['ray lindwall', '1946 - 1960', '61', '1970.2', '419', '5251', '228', '23.03', '7 / 38'], ['clarrie grimmett', '1925 - 1936', '37', '2408.3', '736', '5231', '216', '24.22', '7 / 40'], ['merv hughes', '1985 - 1994', '53', '2047.3', '499', '6017', '212', '28.38', '8 / 87'], ['stuart macgill', '1998 - 2008', '44', '1872.5', '365', '6037', '208', '29.02', '8 / 108'], ['mitchell johnson', '2007 -', '50', '1870', '331', '6281', '205', '30.64', '8 / 61'], ['jeff thomson', '1972 - 1985', '51', '1589.3', '300', '5601', '200', '29.01', '6 / 46']]
|
list of artificial radiation belts
|
https://en.wikipedia.org/wiki/List_of_artificial_radiation_belts
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-148578-1.html.csv
|
aggregation
|
the average altitude of the artificial radiation belts is 244.35 km .
|
{'scope': 'all', 'col': '5', 'type': 'average', 'result': '244.35', 'subset': None}
|
{'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'altitude ( km )'], 'result': '244.35', 'ind': 0, 'tostr': 'avg { all_rows ; altitude ( km ) }'}, '244.35'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; altitude ( km ) } ; 244.35 } = true', 'tointer': 'the average of the altitude ( km ) record of all rows is 244.35 .'}
|
round_eq { avg { all_rows ; altitude ( km ) } ; 244.35 } = true
|
the average of the altitude ( km ) record of all rows is 244.35 .
|
2
|
2
|
{'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'altitude (km)_4': 4, '244.35_5': 5}
|
{'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'altitude (km)_4': 'altitude ( km )', '244.35_5': '244.35'}
|
{'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'altitude (km)_4': [0], '244.35_5': [1]}
|
['explosion', 'location', 'date', 'yield ( approximate )', 'altitude ( km )', 'nation of origin']
|
[['hardtack teak', 'johnston island ( pacific )', '1958 - 08 - 01', '3.8 megatons', '76.8', 'united states'], ['hardtack orange', 'johnston island ( pacific )', '1958 - 08 - 12', '3.8 megatons', '43', 'united states'], ['argus i', 'south atlantic', '1958 - 08 - 27', '1 - 2 kilotons', '200', 'united states'], ['argus ii', 'south atlantic', '1958 - 08 - 30', '1 - 2 kilotons', '256', 'united states'], ['argus iii', 'south atlantic', '1958 - 09 - 06', '1 - 2 kilotons', '539', 'united states'], ['starfish prime', 'johnston island ( pacific )', '1962 - 07 - 09', '1.4 megatons', '400', 'united states'], ['k - 3', 'kazakhstan', '1962 - 10 - 22', '300 s kiloton', '290', 'ussr'], ['k - 4', 'kazakhstan', '1962 - 10 - 28', '300 s kiloton', '150', 'ussr']]
|
galicia , spain
|
https://en.wikipedia.org/wiki/Galicia%2C_Spain
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-12837-1.html.csv
|
aggregation
|
cities in galicia , spain , have an average of 18.4 days with frost per year .
|
{'scope': 'all', 'col': '5', 'type': 'average', 'result': '18.4', 'subset': None}
|
{'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'days with frost'], 'result': '18.4', 'ind': 0, 'tostr': 'avg { all_rows ; days with frost }'}, '18.4'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; days with frost } ; 18.4 } = true', 'tointer': 'the average of the days with frost record of all rows is 18.4 .'}
|
round_eq { avg { all_rows ; days with frost } ; 18.4 } = true
|
the average of the days with frost record of all rows is 18.4 .
|
2
|
2
|
{'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'days with frost_4': 4, '18.4_5': 5}
|
{'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'days with frost_4': 'days with frost', '18.4_5': '18.4'}
|
{'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'days with frost_4': [0], '18.4_5': [1]}
|
['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']]
|
lists of oldest cricketers
|
https://en.wikipedia.org/wiki/Lists_of_oldest_cricketers
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16388723-6.html.csv
|
aggregation
|
the average age of the 5 oldest cricketers is 103 years 28 days .
|
{'scope': 'subset', 'col': '6', 'type': 'average', 'result': '103 years 28 days', 'subset': {'col': '6', 'criterion': 'greater_than_eq', 'value': '102 years 242 days'}}
|
{'func': 'round_eq', 'args': [{'func': 'avg', 'args': [{'func': 'filter_greater_eq', 'args': ['all_rows', 'age ( as of 1 february 2014 )', '102 years 242 days'], 'result': None, 'ind': 0, 'tostr': 'filter_greater_eq { all_rows ; age ( as of 1 february 2014 ) ; 102 years 242 days }', 'tointer': 'select the rows whose age ( as of 1 february 2014 ) record is greater than or equal to 102 years 242 days .'}, 'age ( as of 1 february 2014 )'], 'result': '103 years 28 days', 'ind': 1, 'tostr': 'avg { filter_greater_eq { all_rows ; age ( as of 1 february 2014 ) ; 102 years 242 days } ; age ( as of 1 february 2014 ) }'}, '103 years 28 days'], 'result': True, 'ind': 2, 'tostr': 'round_eq { avg { filter_greater_eq { all_rows ; age ( as of 1 february 2014 ) ; 102 years 242 days } ; age ( as of 1 february 2014 ) } ; 103 years 28 days } = true', 'tointer': 'select the rows whose age ( as of 1 february 2014 ) record is greater than or equal to 102 years 242 days . the average of the age ( as of 1 february 2014 ) record of these rows is 103 years 28 days .'}
|
round_eq { avg { filter_greater_eq { all_rows ; age ( as of 1 february 2014 ) ; 102 years 242 days } ; age ( as of 1 february 2014 ) } ; 103 years 28 days } = true
|
select the rows whose age ( as of 1 february 2014 ) record is greater than or equal to 102 years 242 days . the average of the age ( as of 1 february 2014 ) record of these rows is 103 years 28 days .
|
3
|
3
|
{'eq_2': 2, 'result_3': 3, 'avg_1': 1, 'filter_greater_eq_0': 0, 'all_rows_4': 4, 'age (as of 1 february 2014)_5': 5, '102 years 242 days_6': 6, 'age (as of 1 february 2014)_7': 7, '103 years 28 days_8': 8}
|
{'eq_2': 'eq', 'result_3': 'true', 'avg_1': 'avg', 'filter_greater_eq_0': 'filter_greater_eq', 'all_rows_4': 'all_rows', 'age (as of 1 february 2014)_5': 'age ( as of 1 february 2014 )', '102 years 242 days_6': '102 years 242 days', 'age (as of 1 february 2014)_7': 'age ( as of 1 february 2014 )', '103 years 28 days_8': '103 years 28 days'}
|
{'eq_2': [3], 'result_3': [], 'avg_1': [2], 'filter_greater_eq_0': [1], 'all_rows_4': [0], 'age (as of 1 february 2014)_5': [0], '102 years 242 days_6': [0], 'age (as of 1 february 2014)_7': [1], '103 years 28 days_8': [2]}
|
['rank', 'name', 'team ( s )', 'birth date', 'death date', 'age ( as of 1 february 2014 )', 'nationality']
|
[['1', 'jim hutchinson', 'derbyshire', '29 november 1896', '7 november 2000', '103 years , 344 days', 'england'], ['2', 'syd ward', 'wellington', '5 august 1907', '31 december 2010', '103 years , 148 days', 'new zealand'], ['3', 'rupert de smidt', 'western province', '23 november 1883', '3 august 1986', '102 years , 253 days', 'south africa'], ['4', 'edward english', 'hampshire', '1 january 1864', '5 september 1966', '102 years , 247 days', 'england'], ['5', 'cyril perkins', 'northamptonshire , minor counties', '4 june 1911', 'living', '102years , 242days', 'living in england'], ['6', 'john wheatley', 'canterbury', '8 january 1860', '19 april 1962', '102 years , 101 days', 'new zealand'], ['7', 'norman gordon', 'south africa , transvaal', '6 august 1911', 'living', '102years , 179days', 'living in south africa'], ['8', 'ted martin', 'western australia', '30 september 1902', '9 june 2004', '101 years , 253 days', 'australia'], ['9', 'd b deodhar', 'hindus , maharashtra', '14 january 1892', '24 august 1993', '101 years , 222 days', 'india'], ['10', 'george harman', 'dublin university', '6 june 1874', '14 december 1975', '101 years , 191 days', 'ireland'], ['11', 'fred gibson', 'leicestershire', '13 february 1912', '28 june 2013', '101 years , 135 days', 'jamaica ( lived in england )'], ['12', 'alan finlayson', 'eastern province', '1 september 1900', '28 october 2001', '101 years , 57 days', 'south africa'], ['13', 'neil mccorkell', 'hampshire , players', '23 march 1912', '28 february 2013', '100 years , 342 days', 'england'], ['14', 'charles braithwaite', 'english residents , players of usa', '10 september 1845', '15 april 1946', '100 years , 217 days', 'united states'], ['15', 'harry forsyth', 'dublin university', '18 december 1903', '19 july 2004', '100 years , 214 days', 'ireland'], ['16', 'george deane', 'hampshire', '11 december 1828', '26 february 1929', '100 years , 77 days', 'england']]
|
list of high schools in indiana
|
https://en.wikipedia.org/wiki/List_of_high_schools_in_Indiana
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1984697-85.html.csv
|
aggregation
|
504 is the average size of the listed high schools in indiana .
|
{'scope': 'all', 'col': '4', 'type': 'average', 'result': '504', 'subset': None}
|
{'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'size'], 'result': '504', 'ind': 0, 'tostr': 'avg { all_rows ; size }'}, '504'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; size } ; 504 } = true', 'tointer': 'the average of the size record of all rows is 504 .'}
|
round_eq { avg { all_rows ; size } ; 504 } = true
|
the average of the size record of all rows is 504 .
|
2
|
2
|
{'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'size_4': 4, '504_5': 5}
|
{'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'size_4': 'size', '504_5': '504'}
|
{'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'size_4': [0], '504_5': [1]}
|
['school', 'city / town', 'website', 'size', 'principal', 'grades', 'idoe profile']
|
[['emmanuel christian school', 'wabash', '-', '105', 'doug phillips', 'pk - 12', 'snapshot'], ['manchester junior - senior high school', 'north manchester', 'website', '715', 'ms nancy alspaugh', '07 - 12', 'snapshot'], ['northfield junior - senior high school', 'wabash', 'website', '604', 'mike keaffaber', '07 - 12', 'snapshot'], ['southwood junior - senior high school', 'wabash', 'website', '634', 'tim drake', '07 - 12', 'snapshot'], ['wabash high school', 'wabash', 'website', '462', 'josh blossom', '09 - 12', 'snapshot']]
|
nello pagani
|
https://en.wikipedia.org/wiki/Nello_Pagani
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1235127-3.html.csv
|
majority
|
nello pagani finished with at least 10 points the majority of years he raced .
|
{'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'greater_than_eq', 'value': '10', 'subset': None}
|
{'func': 'most_greater_eq', 'args': ['all_rows', 'points', '10'], 'result': True, 'ind': 0, 'tointer': 'for the points records of all rows , most of them are greater than or equal to 10 .', 'tostr': 'most_greater_eq { all_rows ; points ; 10 } = true'}
|
most_greater_eq { all_rows ; points ; 10 } = true
|
for the points records of all rows , most of them are greater than or equal to 10 .
|
1
|
1
|
{'most_greater_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'points_3': 3, '10_4': 4}
|
{'most_greater_eq_0': 'most_greater_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'points_3': 'points', '10_4': '10'}
|
{'most_greater_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'points_3': [0], '10_4': [0]}
|
['year', 'class', 'team', 'points', 'rank', 'wins']
|
[['1949', '125cc', 'mondial', '27', '1st', '2'], ['1949', '500cc', 'gilera', '28', '2nd', '2'], ['1950', '500cc', 'gilera', '12', '4th', '0'], ['1951', '125cc', 'mondial', '3', '10th', '0'], ['1951', '500cc', 'gilera', '10', '5th', '0'], ['1952', '500cc', 'gilera', '12', '8th', '0'], ['1953', '500cc', 'gilera', '2', '15th', '0'], ['1954', '500cc', 'mv agusta', '4', '13th', '0'], ['1955', '500cc', 'mv agusta', '2', '20th', '0']]
|
list of bored to death episodes
|
https://en.wikipedia.org/wiki/List_of_Bored_to_Death_episodes
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-26136228-3.html.csv
|
aggregation
|
for the show bored to death , the average number of us viewers ( in millions ) is .94 .
|
{'scope': 'all', 'col': '7', 'type': 'average', 'result': '0.944', 'subset': None}
|
{'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'us viewers ( millions )'], 'result': '0.944', 'ind': 0, 'tostr': 'avg { all_rows ; us viewers ( millions ) }'}, '0.944'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; us viewers ( millions ) } ; 0.944 } = true', 'tointer': 'the average of the us viewers ( millions ) record of all rows is 0.944 .'}
|
round_eq { avg { all_rows ; us viewers ( millions ) } ; 0.944 } = true
|
the average of the us viewers ( millions ) record of all rows is 0.944 .
|
2
|
2
|
{'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'us viewers (millions)_4': 4, '0.944_5': 5}
|
{'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'us viewers (millions)_4': 'us viewers ( millions )', '0.944_5': '0.944'}
|
{'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'us viewers (millions)_4': [0], '0.944_5': [1]}
|
['series no', 'episode no', 'title', 'directed by', 'written by', 'original air date', 'us viewers ( millions )']
|
[['9', '1', 'escape from the dungeon !', 'alan taylor', 'jonathan ames', 'september 26 , 2010', '1.05'], ['10', '2', 'make it quick , fitzgerald !', 'alan taylor', 'jonathan ames', 'october 3 , 2010', '1.08'], ['11', '3', 'the gowanus canal has gonorrhea !', 'michael lehmann', 'martin gero & jonathan ames', 'october 10 , 2010', '0.86'], ['12', '4', "i 've been living like a demented god !", 'michael lehmann', 'donick cary & jonathan ames', 'october 17 , 2010', '0.82'], ['13', '5', 'forty - two down !', 'troy miller', 'tami sagher & jonathan ames', 'october 24 , 2010', '1.01'], ['14', '6', 'the case of the grievous clerical error !', 'tristram shapeero', 'sam sklaver & jonathan ames', 'october 31 , 2010', '0.69'], ['15', '7', 'escape from the castle !', 'adam bernstein', 'donick cary & jonathan ames', 'november 7 , 2010', '1.10']]
|
hairuddin omar
|
https://en.wikipedia.org/wiki/Hairuddin_Omar
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10358163-1.html.csv
|
count
|
hairuddin omar lost three events from 2000 to 2008 .
|
{'scope': 'all', 'criterion': 'equal', 'value': 'lost', 'result': '3', 'col': '4', 'subset': None}
|
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'result', 'lost'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose result record fuzzily matches to lost .', 'tostr': 'filter_eq { all_rows ; result ; lost }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; result ; lost } }', 'tointer': 'select the rows whose result record fuzzily matches to lost . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; result ; lost } } ; 3 } = true', 'tointer': 'select the rows whose result record fuzzily matches to lost . the number of such rows is 3 .'}
|
eq { count { filter_eq { all_rows ; result ; lost } } ; 3 } = true
|
select the rows whose result record fuzzily matches to lost . 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, 'result_5': 5, 'lost_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', 'result_5': 'result', 'lost_6': 'lost', '3_7': '3'}
|
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'result_5': [0], 'lost_6': [0], '3_7': [2]}
|
['date', 'venue', 'score', 'result', 'competition']
|
[['7 november 2000', 'bangkok , thailand', '5 - 0', 'won', '2000 tiger cup group stage'], ['9 november 2000', 'bangkok , thailand', '3 - 2', 'won', '2000 tiger cup group stage'], ['9 may 2001', 'ba , fiji', '1 - 2', 'won', 'friendly'], ['23 march 2001', 'doha , qatar', '2 - 1', 'lost', '2002 fifa world cup qualification ( afc )'], ['25 march 2001', 'doha , qatar', '4 - 3', 'won', '2002 fifa world cup qualification ( afc )'], ['11 december 2002', 'kuala lumpur , malaysia', '5 - 0', 'won', 'friendly'], ['20 october 2003', 'manama , bahrain', '5 - 1', 'lost', '2004 afc asian cup qualification'], ['24 october 2003', 'manama , bahrain', '2 - 1', 'lost', '2004 afc asian cup qualification'], ['12 january 2007', 'bangkok , thailand', '4 - 0', 'won', '2007 asean football championship'], ['18 june 2007', 'shah alam , malaysia', '6 - 0', 'won', 'friendly'], ['10 october 2008', 'kuala lumpur , malaysia', '4 - 1', 'won', 'friendly'], ['20 october 2008', 'kuala lumpur , malaysia', '6 - 0', 'won', '2008 merdeka tournament']]
|
1975 minnesota vikings season
|
https://en.wikipedia.org/wiki/1975_Minnesota_Vikings_season
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10361480-2.html.csv
|
aggregation
|
the average attendance for vikings games in the 1975 nfl season is just over 50,000 .
|
{'scope': 'all', 'col': '5', 'type': 'average', 'result': '52,519.93', 'subset': None}
|
{'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'attendance'], 'result': '52,519.93', 'ind': 0, 'tostr': 'avg { all_rows ; attendance }'}, '52,519.93'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; attendance } ; 52,519.93 } = true', 'tointer': 'the average of the attendance record of all rows is 52,519.93 .'}
|
round_eq { avg { all_rows ; attendance } ; 52,519.93 } = true
|
the average of the attendance record of all rows is 52,519.93 .
|
2
|
2
|
{'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'attendance_4': 4, '52,519.93_5': 5}
|
{'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'attendance_4': 'attendance', '52,519.93_5': '52,519.93'}
|
{'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'attendance_4': [0], '52,519.93_5': [1]}
|
['week', 'date', 'opponent', 'result', 'attendance']
|
[['1', 'september 21 , 1975', 'san francisco 49ers', 'w 27 - 17', '46479'], ['2', 'september 28 , 1975', 'cleveland browns', 'w 42 - 10', '68064'], ['3', 'october 5 , 1975', 'chicago bears', 'w 28 - 3', '47578'], ['4', 'october 12 , 1975', 'new york jets', 'w 29 - 21', '47739'], ['5', 'october 19 , 1975', 'detroit lions', 'w 25 - 19', '47872'], ['6', 'october 27 , 1975', 'chicago bears', 'w 13 - 9', '51259'], ['7', 'november 2 , 1975', 'green bay packers', 'w 28 - 17', '57267'], ['8', 'november 9 , 1975', 'atlanta falcons', 'w 38 - 0', '43751'], ['9', 'november 16 , 1975', 'new orleans saints', 'w 20 - 7', '52765'], ['10', 'november 23 , 1975', 'san diego chargers', 'w 28 - 13', '43737'], ['11', 'november 30 , 1975', 'washington redskins', 'l 30 - 31', '54498'], ['12', 'december 7 , 1975', 'green bay packers', 'w 24 - 3', '46147'], ['13', 'december 14 , 1975', 'detroit lions', 'l 10 - 17', '73130'], ['14', 'december 20 , 1975', 'buffalo bills', 'w 35 - 13', '54993']]
|
list of how it 's made episodes
|
https://en.wikipedia.org/wiki/List_of_How_It%27s_Made_episodes
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15187735-14.html.csv
|
count
|
in the " how it 's made " episodes with numbers in the range 170-175 , sporting equipment was featured in six segments .
|
{'scope': 'subset', 'criterion': 'all', 'value': 'n/a', 'result': '6', 'col': '4', 'subset': {'col': '2', 'criterion': 'less_than_eq', 'value': '175'}}
|
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_all', 'args': [{'func': 'filter_less_eq', 'args': ['all_rows', 'episode', '175'], 'result': None, 'ind': 0, 'tostr': 'filter_less_eq { all_rows ; episode ; 175 }', 'tointer': 'select the rows whose episode record is less than or equal to 175 .'}, 'segment a'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose episode record is less than or equal to 175 . among these rows , select the rows whose segment a record is arbitrary .', 'tostr': 'filter_all { filter_less_eq { all_rows ; episode ; 175 } ; segment a }'}], 'result': '6', 'ind': 2, 'tostr': 'count { filter_all { filter_less_eq { all_rows ; episode ; 175 } ; segment a } }', 'tointer': 'select the rows whose episode record is less than or equal to 175 . among these rows , select the rows whose segment a record is arbitrary . the number of such rows is 6 .'}, '6'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_all { filter_less_eq { all_rows ; episode ; 175 } ; segment a } } ; 6 } = true', 'tointer': 'select the rows whose episode record is less than or equal to 175 . among these rows , select the rows whose segment a record is arbitrary . the number of such rows is 6 .'}
|
eq { count { filter_all { filter_less_eq { all_rows ; episode ; 175 } ; segment a } } ; 6 } = true
|
select the rows whose episode record is less than or equal to 175 . among these rows , select the rows whose segment a record is arbitrary . the number of such rows is 6 .
|
4
|
4
|
{'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_all_1': 1, 'filter_less_eq_0': 0, 'all_rows_5': 5, 'episode_6': 6, '175_7': 7, 'segment a_8': 8, '6_9': 9}
|
{'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_all_1': 'filter_all', 'filter_less_eq_0': 'filter_less_eq', 'all_rows_5': 'all_rows', 'episode_6': 'episode', '175_7': '175', 'segment a_8': 'segment a', '6_9': '6'}
|
{'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_all_1': [2], 'filter_less_eq_0': [1], 'all_rows_5': [0], 'episode_6': [0], '175_7': [0], 'segment a_8': [1], '6_9': [3]}
|
['series ep', 'episode', 'netflix', 'segment a', 'segment b', 'segment c', 'segment d']
|
[['14 - 01', '170', 's07e01', 'mini gp motorcycles', 'fig cookies', 'tool boxes', 'pipe bends'], ['14 - 02', '171', 's07e02', 'western revolver s replica', 'arc trainers', 'used - oil furnaces', 'vegetable peelers and s pizza cutter'], ['14 - 03', '172', 's07e03', 'metal s golf club', 's waffle', 'custom wires and s cable', 'train s wheel'], ['14 - 04', '173', 's07e04', 's sail', 's walnut', 'wheel immobilizers', 'honeycomb structural panels'], ['14 - 05', '174', 's07e05', 's surfboard', 's sticker', 'sandwich s cookie', 'concrete roofing s tile'], ['14 - 06', '175', 's07e06', 'ski goggles', 'tower cranes', 'porcelain s figurine', 's diesel engine'], ['14 - 07', '176', 's07e07', 'stuffed s olive', 's astrolabe', 's western saddle ( part 1 )', 's western saddle ( part 2 )'], ['14 - 08', '177', 's07e08', 'custom running shoes', 's axe', 'racing s kart', 's animatronic'], ['14 - 09', '178', 's07e09', 's headphone', 's diving regulator', 'reflector light bulbs ( part 1 )', 'reflector light bulbs ( part 2 )'], ['14 - 10', '179', 's07e10', 's fly fishing reel', 'house paint', 's weaving loom', 's ice maker'], ['14 - 11', '180', 's07e11', 's graphite pencil lead', 's clarinet', 's special effect ( part 1 )', 's special effect ( part 2 )'], ['14 - 12', '181', 's07e12', 's air boat', 's onion', '3d metal printing', 's curved cabinet door'], ['14 - 13', '182', 's07e13', 's retractable ballpoint pen', 'solar salt', 's tuba ( part 1 )', 's tuba ( part 2 )']]
|
77th united states congress
|
https://en.wikipedia.org/wiki/77th_United_States_Congress
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1958768-3.html.csv
|
majority
|
out of the 77th . united states congress 's vacancy instances , most are democrat .
|
{'scope': 'all', 'col': '2', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': 'd', 'subset': None}
|
{'func': 'most_str_eq', 'args': ['all_rows', 'vacator', 'd'], 'result': True, 'ind': 0, 'tointer': 'for the vacator records of all rows , most of them fuzzily match to d .', 'tostr': 'most_eq { all_rows ; vacator ; d } = true'}
|
most_eq { all_rows ; vacator ; d } = true
|
for the vacator records of all rows , most of them fuzzily match to d .
|
1
|
1
|
{'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'vacator_3': 3, 'd_4': 4}
|
{'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'vacator_3': 'vacator', 'd_4': 'd'}
|
{'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'vacator_3': [0], 'd_4': [0]}
|
['district', 'vacator', 'reason for change', 'successor', 'date successor seated']
|
[['oklahoma 7th', 'sam c massingale ( d )', 'died january 17 , 1941', 'victor wickersham ( d )', 'april 1 , 1941'], ['new york 17th', 'kenneth f simpson ( r )', 'died january 25 , 1941', 'joseph c baldwin ( r )', 'march 11 , 1941'], ['alabama 7th', 'walter w bankhead ( d )', 'resigned february 1 , 1941', 'carter manasco ( d )', 'june 24 , 1941'], ['maryland 6th', 'william d byron ( d )', 'died february 27 , 1941', 'katharine byron ( d )', 'may 27 , 1941'], ['new york 42nd', 'pius l schwert ( d )', 'died march 11 , 1941', 'john c butler ( r )', 'april 22 , 1941'], ['north carolina 5th', 'alonzo d folger ( d )', 'died april 30 , 1941', 'john h folger ( d )', 'june 14 , 1941'], ['new york 14th', 'morris m edelstein ( d )', 'died june 4 , 1941', 'arthur g klein ( d )', 'july 29 , 1941'], ['wisconsin 1st', 'stephen bolles ( r )', 'died july 8 , 1941', 'lawrence h smith ( r )', 'august 29 , 1941'], ['pennsylvania 15th', 'albert g rutherford ( r )', 'died august 10 , 1941', 'wilson d gillette ( r )', 'november 4 , 1941'], ['colorado 4th', 'edward t taylor ( d )', 'died september 3 , 1941', 'robert f rockwell ( r )', 'december 9 , 1941'], ['california 17th', 'lee e geyer ( d )', 'died october 11 , 1941', 'cecil r king ( d )', 'august 25 , 1942'], ['massachusetts 7th', 'lawrence j connery ( d )', 'died october 19 , 1941', 'thomas j lane ( d )', 'december 30 , 1941'], ['pennsylvania 11th', 'patrick j boland ( d )', 'died may 18 , 1942', 'veronica g boland ( d )', 'november 3 , 1942'], ['california 3rd', 'frank h buck ( d )', 'died september 17 , 1942', 'vacant until the next congress', 'vacant until the next congress'], ['pennsylvania 25th', 'charles i faddis ( d )', 'resigned december 4 , 1942 to enter the us army', 'vacant until the next congress', 'vacant until the next congress'], ['illinois 6th', 'a f maciejewski ( d )', 'resigned december 6 , 1942', 'vacant until the next congress', 'vacant until the next congress']]
|
peter arundell
|
https://en.wikipedia.org/wiki/Peter_Arundell
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1235866-1.html.csv
|
superlative
|
from 1963 - 1966 , peter arundell 's highest number of points for team lotus was 11 .
|
{'scope': 'all', 'col_superlative': '5', 'row_superlative': '2', 'value_mentioned': 'yes', 'max_or_min': 'max', 'other_col': '2', 'subset': None}
|
{'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'max', 'args': ['all_rows', 'points'], 'result': '11', 'ind': 0, 'tostr': 'max { all_rows ; points }', 'tointer': 'the maximum points record of all rows is 11 .'}, '11'], 'result': True, 'ind': 1, 'tostr': 'eq { max { all_rows ; points } ; 11 }', 'tointer': 'the maximum points record of all rows is 11 .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'points'], 'result': None, 'ind': 2, 'tostr': 'argmax { all_rows ; points }'}, 'entrant'], 'result': 'team lotus', 'ind': 3, 'tostr': 'hop { argmax { all_rows ; points } ; entrant }'}, 'team lotus'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { argmax { all_rows ; points } ; entrant } ; team lotus }', 'tointer': 'the entrant record of the row with superlative points record is team lotus .'}], 'result': True, 'ind': 5, 'tostr': 'and { eq { max { all_rows ; points } ; 11 } ; eq { hop { argmax { all_rows ; points } ; entrant } ; team lotus } } = true', 'tointer': 'the maximum points record of all rows is 11 . the entrant record of the row with superlative points record is team lotus .'}
|
and { eq { max { all_rows ; points } ; 11 } ; eq { hop { argmax { all_rows ; points } ; entrant } ; team lotus } } = true
|
the maximum points record of all rows is 11 . the entrant record of the row with superlative points record is team lotus .
|
6
|
6
|
{'and_5': 5, 'result_6': 6, 'eq_1': 1, 'max_0': 0, 'all_rows_7': 7, 'points_8': 8, '11_9': 9, 'str_eq_4': 4, 'str_hop_3': 3, 'argmax_2': 2, 'all_rows_10': 10, 'points_11': 11, 'entrant_12': 12, 'team lotus_13': 13}
|
{'and_5': 'and', 'result_6': 'true', 'eq_1': 'eq', 'max_0': 'max', 'all_rows_7': 'all_rows', 'points_8': 'points', '11_9': '11', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'argmax_2': 'argmax', 'all_rows_10': 'all_rows', 'points_11': 'points', 'entrant_12': 'entrant', 'team lotus_13': 'team lotus'}
|
{'and_5': [6], 'result_6': [], 'eq_1': [5], 'max_0': [1], 'all_rows_7': [0], 'points_8': [0], '11_9': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'argmax_2': [3], 'all_rows_10': [2], 'points_11': [2], 'entrant_12': [3], 'team lotus_13': [4]}
|
['year', 'entrant', 'chassis', 'engine', 'points']
|
[['1963', 'team lotus', 'lotus 25', 'climax v8', '0'], ['1964', 'team lotus', 'lotus 25', 'climax v8', '11'], ['1966', 'team lotus', 'lotus 43', 'brm h16', '1'], ['1966', 'team lotus', 'lotus 33', 'brm v8', '1'], ['1966', 'team lotus', 'lotus 33', 'climax v8', '1']]
|
2005 world weightlifting championships
|
https://en.wikipedia.org/wiki/2005_World_Weightlifting_Championships
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10929638-3.html.csv
|
count
|
six nations ranked 12th in the 2005 world weightlifting championships-bulgaria , dominican republic , france , slovakia , united states and vietnam .
|
{'scope': 'all', 'criterion': 'equal', 'value': '12', 'result': '6', 'col': '1', 'subset': None}
|
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'rank', '12'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose rank record is equal to 12 .', 'tostr': 'filter_eq { all_rows ; rank ; 12 }'}], 'result': '6', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; rank ; 12 } }', 'tointer': 'select the rows whose rank record is equal to 12 . the number of such rows is 6 .'}, '6'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; rank ; 12 } } ; 6 } = true', 'tointer': 'select the rows whose rank record is equal to 12 . the number of such rows is 6 .'}
|
eq { count { filter_eq { all_rows ; rank ; 12 } } ; 6 } = true
|
select the rows whose rank record is equal to 12 . the number of such rows is 6 .
|
3
|
3
|
{'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_eq_0': 0, 'all_rows_4': 4, 'rank_5': 5, '12_6': 6, '6_7': 7}
|
{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'rank_5': 'rank', '12_6': '12', '6_7': '6'}
|
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'rank_5': [0], '12_6': [0], '6_7': [2]}
|
['rank', 'nation', 'gold', 'silver', 'bronze', 'total']
|
[['1', 'china', '7', '4', '1', '12'], ['2', 'russia', '2', '4', '4', '10'], ['3', 'thailand', '1', '3', '1', '5'], ['4', 'south korea', '1', '2', '0', '2'], ['5', 'azerbaijan', '1', '0', '0', '1'], ['5', 'chinese taipei', '1', '0', '0', '1'], ['5', 'iran', '1', '0', '0', '1'], ['5', 'kazakhstan', '1', '0', '0', '1'], ['9', 'romania', '0', '1', '1', '2'], ['10', 'moldova', '0', '1', '0', '1'], ['11', 'qatar', '0', '0', '2', '2'], ['12', 'bulgaria', '0', '0', '1', '1'], ['12', 'dominican republic', '0', '0', '1', '1'], ['12', 'france', '0', '0', '1', '1'], ['12', 'slovakia', '0', '0', '1', '1'], ['12', 'united states', '0', '0', '1', '1'], ['12', 'vietnam', '0', '0', '1', '1'], ['total', 'total', '15', '15', '15', '45']]
|
fiba eurobasket 2007 squads
|
https://en.wikipedia.org/wiki/FIBA_EuroBasket_2007_squads
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12962773-14.html.csv
|
superlative
|
player goran jagodnik was born before all other players on the fiba eurobasket 2007 squads .
|
{'scope': 'all', 'col_superlative': '4', 'row_superlative': '9', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '1', 'subset': None}
|
{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmin', 'args': ['all_rows', 'year born'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; year born }'}, 'player'], 'result': 'goran jagodnik', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; year born } ; player }'}, 'goran jagodnik'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmin { all_rows ; year born } ; player } ; goran jagodnik } = true', 'tointer': 'select the row whose year born record of all rows is minimum . the player record of this row is goran jagodnik .'}
|
eq { hop { argmin { all_rows ; year born } ; player } ; goran jagodnik } = true
|
select the row whose year born record of all rows is minimum . the player record of this row is goran jagodnik .
|
3
|
3
|
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'year born_5': 5, 'player_6': 6, 'goran jagodnik_7': 7}
|
{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'year born_5': 'year born', 'player_6': 'player', 'goran jagodnik_7': 'goran jagodnik'}
|
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'year born_5': [0], 'player_6': [1], 'goran jagodnik_7': [2]}
|
['player', 'height', 'position', 'year born', 'current club']
|
[['sandi čebular', '1.94', 'guard', '1986', 'unattached'], ['jaka lakovič', '1.86', 'guard', '1978', 'axa fc barcelona'], ['aleksandar ćapin', '1.86', 'guard', '1982', 'whirlpool varese'], ['goran dragić', '1.88', 'guard', '1986', 'tau cerámica'], ['rasho nesterovič', '2.14', 'center', '1976', 'toronto raptors'], ['matjaž smodiš', '2.05', 'forward', '1979', 'cska moscow'], ['uroš slokar', '2.09', 'center', '1983', 'triumph lyubertsy'], ['jaka klobučar', '1.94', 'guard', '1987', 'geoplin slovan'], ['goran jagodnik', '2.02', 'forward', '1974', 'hemofarm'], ['domen lorbek', '1.96', 'guard', '1985', 'mmt estudiantes'], ['gašper vidmar', '2.08', 'center', '1987', 'fenerbahçe ülker'], ['erazem lorbek', '2.09', 'center', '1984', 'lottomatica roma']]
|
iran at the asian games
|
https://en.wikipedia.org/wiki/Iran_at_the_Asian_Games
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10882501-12.html.csv
|
majority
|
most of the participants from iran at the asian games won at least one silver medal .
|
{'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'greater_than_eq', 'value': '1', 'subset': None}
|
{'func': 'most_greater_eq', 'args': ['all_rows', 'silver', '1'], 'result': True, 'ind': 0, 'tointer': 'for the silver records of all rows , most of them are greater than or equal to 1 .', 'tostr': 'most_greater_eq { all_rows ; silver ; 1 } = true'}
|
most_greater_eq { all_rows ; silver ; 1 } = true
|
for the silver records of all rows , most of them are greater than or equal to 1 .
|
1
|
1
|
{'most_greater_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'silver_3': 3, '1_4': 4}
|
{'most_greater_eq_0': 'most_greater_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'silver_3': 'silver', '1_4': '1'}
|
{'most_greater_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'silver_3': [0], '1_4': [0]}
|
['athlete', 'sport', 'asian games', 'gold', 'silver', 'bronze', 'total']
|
[['mohammad nassiri', 'weightlifting', '1966 - 1974', '4', '1', '0', '5'], ['moslem eskandar - filabi', 'wrestling', '1966 - 1974', '4', '0', '0', '4'], ['reza soukhteh - saraei', 'wrestling', '1974 - 1990', '3', '1', '0', '4'], ['houshang kargarnejad', 'weightlifting', '1970 - 1974', '3', '0', '1', '4'], ['alireza heidari', 'wrestling', '1998 - 2006', '3', '0', '0', '3'], ['jalal keshmiri', 'athletics', '1966 - 1974', '2', '3', '1', '6'], ['hassan arianfard', 'cycling', '1970 - 1974', '2', '1', '0', '3'], ['jasem vishgahi', 'karate', '2002 - 2010', '2', '1', '0', '3'], ['akbar shokrollahi', 'weightlifting', '1974', '2', '1', '0', '3'], ['ali vali', 'weightlifting', '1974', '2', '1', '0', '3'], ['teymour ghiasi', 'athletics', '1966 - 1974', '2', '0', '1', '3'], ['hossein rezazadeh', 'weightlifting', '1998 - 2006', '2', '0', '1', '3']]
|
wmbj
|
https://en.wikipedia.org/wiki/WMBJ
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14996829-1.html.csv
|
superlative
|
the frequency 105.1 fm has the highest erp of all the wmbj frequencies .
|
{'scope': 'all', 'col_superlative': '4', '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', 'erp w'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; erp w }'}, 'frequency mhz'], 'result': '105.1 fm', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; erp w } ; frequency mhz }'}, '105.1 fm'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; erp w } ; frequency mhz } ; 105.1 fm } = true', 'tointer': 'select the row whose erp w record of all rows is maximum . the frequency mhz record of this row is 105.1 fm .'}
|
eq { hop { argmax { all_rows ; erp w } ; frequency mhz } ; 105.1 fm } = true
|
select the row whose erp w record of all rows is maximum . the frequency mhz record of this row is 105.1 fm .
|
3
|
3
|
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'erp w_5': 5, 'frequency mhz_6': 6, '105.1 fm_7': 7}
|
{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'erp w_5': 'erp w', 'frequency mhz_6': 'frequency mhz', '105.1 fm_7': '105.1 fm'}
|
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'erp w_5': [0], 'frequency mhz_6': [1], '105.1 fm_7': [2]}
|
['call sign', 'frequency mhz', 'city of license', 'erp w', 'class', 'fcc info']
|
[['w203bq', '88.5 fm', 'walterboro , sc', '30', 'd', 'fcc'], ['w298aj', '107.5 fm', 'boone , nc', '10', 'd', 'fcc'], ['w227bk', '93.3 fm', 'surfside beach , sc', '27', 'd', 'fcc'], ['w238bi', '95.5 fm', 'georgetown , sc', '10', 'd', 'fcc'], ['w283av', '104.5 fm', 'little river , sc', '5', 'd', 'fcc'], ['w286ay', '105.1 fm', 'charleston , sc', '117', 'd', 'fcc']]
|
2008 - 09 chicago bulls season
|
https://en.wikipedia.org/wiki/2008%E2%80%9309_Chicago_Bulls_season
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17058151-11.html.csv
|
majority
|
most of the games took place in the month of april .
|
{'scope': 'all', 'col': '2', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': 'april', 'subset': None}
|
{'func': 'most_str_eq', 'args': ['all_rows', 'date', 'april'], 'result': True, 'ind': 0, 'tointer': 'for the date records of all rows , most of them fuzzily match to april .', 'tostr': 'most_eq { all_rows ; date ; april } = true'}
|
most_eq { all_rows ; date ; april } = true
|
for the date records of all rows , most of them fuzzily match to april .
|
1
|
1
|
{'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'date_3': 3, 'april_4': 4}
|
{'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'date_3': 'date', 'april_4': 'april'}
|
{'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'date_3': [0], 'april_4': [0]}
|
['game', 'date', 'team', 'score', 'location attendance', 'series']
|
[['1', 'april 18', 'boston', 'w 105 - 103 ( ot )', 'td banknorth garden 18624', '1 - 0'], ['2', 'april 20', 'boston', 'l 115 - 118 ( ot )', 'td banknorth garden 18624', '1 - 1'], ['3', 'april 23', 'boston', 'l 86 - 107 ( ot )', 'united center 23072', '1 - 2'], ['4', 'april 26', 'boston', 'w 121 - 118 ( 2ot )', 'united center 23067', '2 - 2'], ['5', 'april 28', 'boston', 'l 104 - 106 ( ot )', 'td banknorth garden 18624', '2 - 3'], ['6', 'april 30', 'boston', 'w 128 - 127 ( 3ot )', 'united center 23430', '3 - 3'], ['7', 'may 2', 'boston', 'l 99 - 109 ( ot )', 'td banknorth garden 18624', '3 - 4']]
|
dragon zakura ( tv series )
|
https://en.wikipedia.org/wiki/Dragon_Zakura_%28TV_series%29
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-25847911-1.html.csv
|
aggregation
|
the average ratings among episodes 2 through 10 of dragon zakura is 15.7 % .
|
{'scope': 'all', 'col': '6', 'type': 'average', 'result': '15.7 %', 'subset': None}
|
{'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'ratings'], 'result': '15.7 %', 'ind': 0, 'tostr': 'avg { all_rows ; ratings }'}, '15.7 %'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; ratings } ; 15.7 % } = true', 'tointer': 'the average of the ratings record of all rows is 15.7 % .'}
|
round_eq { avg { all_rows ; ratings } ; 15.7 % } = true
|
the average of the ratings record of all rows is 15.7 % .
|
2
|
2
|
{'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'ratings_4': 4, '15.7%_5': 5}
|
{'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'ratings_4': 'ratings', '15.7%_5': '15.7 %'}
|
{'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'ratings_4': [0], '15.7%_5': [1]}
|
['', 'episode title', 'romanized title', 'translation of title', 'broadcast date', 'ratings']
|
[['ep 2', '自分の弱さを知れ !', 'jibun no yowasa wo shire !', 'know your weaknesses !', 'july 15 , 2005', '16.5 %'], ['ep 3', '遊べ!受験はスポーツだ !', 'asobe ! juken wa supootsu da !', 'entrance exams are sports , so play !', 'july 22 , 2005', '13.8 %'], ['ep 4', '壁にぶつかるまで我慢しろ', 'kabe ni butsukaru made gaman shiro', 'hold out until you hit the wall', 'july 29 , 2005', '16.1 %'], ['ep 5', '泣くな!お前の人生だ !', 'nakuna ! omae no jinsei da !', "do n't cry ! it 's your life !", 'august 5 , 2005', '16.8 %'], ['ep 6', '英語対決!勝負だバカ6人', 'eigo taiketsu ! shoubu da baka rokunin', 'english showdown ! fight for stupid 6', 'august 12 , 2005', '17.9 %'], ['ep 7', '見返してやる!東大模試', 'mikaeshite yaru ! toudai moshi', 'vengeance ! mock exam for tokyo university', 'august 19 , 2005', '15.6 %'], ['ep 9', '信じろ!成績は必ず上がる', 'shinjiro ! seiseki wa kanarazu agaru', 'trust yourself ! your marks will surely improve', 'september 2 , 2005', '14.5 %'], ['ep 10', '友情か受験か最後の決断', 'yuujou ka juken ka saigo no ketsudan', 'friendship or entrance exam final decision', 'september 9 , 2005', '14.5 %']]
|
wru division five west
|
https://en.wikipedia.org/wiki/WRU_Division_Five_West
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17941032-3.html.csv
|
aggregation
|
the total tries scored in wru division five west was 475 .
|
{'scope': 'all', 'col': '7', 'type': 'sum', 'result': '475', 'subset': None}
|
{'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'tries for'], 'result': '475', 'ind': 0, 'tostr': 'sum { all_rows ; tries for }'}, '475'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; tries for } ; 475 } = true', 'tointer': 'the sum of the tries for record of all rows is 475 .'}
|
round_eq { sum { all_rows ; tries for } ; 475 } = true
|
the sum of the tries for record of all rows is 475 .
|
2
|
2
|
{'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'tries for_4': 4, '475_5': 5}
|
{'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'tries for_4': 'tries for', '475_5': '475'}
|
{'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'tries for_4': [0], '475_5': [1]}
|
['club', 'played', 'drawn', 'lost', 'points for', 'points against', 'tries for', 'tries against', 'try bonus', 'losing bonus', 'points']
|
[['club', 'played', 'drawn', 'lost', 'points for', 'points against', 'tries for', 'tries against', 'try bonus', 'losing bonus', 'points'], ['burry port rfc', '20', '0', '2', '438', '180', '64', '23', '8', '0', '80'], ['cefneithin rfc', '20', '0', '5', '379', '206', '55', '25', '6', '3', '69'], ['aberaeron rfc', '20', '0', '7', '369', '232', '49', '28', '6', '5', '63'], ['penygroes rfc', '20', '0', '10', '355', '307', '46', '42', '4', '5', '49'], ['llandybie rfc', '20', '0', '11', '377', '376', '48', '52', '5', '6', '47'], ['furnace united rfc', '20', '0', '11', '312', '295', '46', '36', '4', '7', '47'], ['fishguard and goodwick rfc', '20', '0', '11', '261', '321', '31', '41', '2', '5', '43'], ['llangwm rfc', '20', '1', '12', '325', '357', '45', '49', '4', '9', '43'], ['st davids rfc', '20', '0', '11', '256', '494', '32', '69', '1', '2', '39'], ['st clears rfc', '20', '1', '12', '235', '316', '30', '48', '3', '4', '37'], ['pontyates rfc', '20', '0', '17', '230', '453', '29', '62', '2', '6', '20']]
|
communist league ( new zealand )
|
https://en.wikipedia.org/wiki/Communist_League_%28New_Zealand%29
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1110530-1.html.csv
|
superlative
|
the communist league won their highest amount of votes in the 1990 election .
|
{'scope': 'all', 'col_superlative': '4', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None}
|
{'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'votes'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; votes }'}, 'election'], 'result': '1990', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; votes } ; election }'}, '1990'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; votes } ; election } ; 1990 } = true', 'tointer': 'select the row whose votes record of all rows is maximum . the election record of this row is 1990 .'}
|
eq { hop { argmax { all_rows ; votes } ; election } ; 1990 } = true
|
select the row whose votes record of all rows is maximum . the election record of this row is 1990 .
|
3
|
3
|
{'eq_2': 2, 'result_3': 3, 'num_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'votes_5': 5, 'election_6': 6, '1990_7': 7}
|
{'eq_2': 'eq', 'result_3': 'true', 'num_hop_1': 'num_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'votes_5': 'votes', 'election_6': 'election', '1990_7': '1990'}
|
{'eq_2': [3], 'result_3': [], 'num_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'votes_5': [0], 'election_6': [1], '1990_7': [2]}
|
['election', 'candidates', 'seats won', 'votes', '% of vote']
|
[['1990', '9', '0', '210', '0.01'], ['1993', '2', '0', '84', '0.00'], ['1996', '2', '0', '99', '0.00'], ['1999', '2', '0', '89', '0.00'], ['2002', '2', '0', '171', '0.01'], ['2005', '2', '0', '107', '0.00'], ['2008', '2', '0', '74', '0.00']]
|
1961 washington redskins season
|
https://en.wikipedia.org/wiki/1961_Washington_Redskins_season
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15122858-2.html.csv
|
majority
|
the 1961 washington redskins lost all of their games that were played in the month of october .
|
{'scope': 'subset', 'col': '4', 'most_or_all': 'all', 'criterion': 'fuzzily_match', 'value': 'l', 'subset': {'col': '2', 'criterion': 'fuzzily_match', 'value': 'october'}}
|
{'func': 'all_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', 'october'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; date ; october }', 'tointer': 'select the rows whose date record fuzzily matches to october .'}, 'result', 'l'], 'result': True, 'ind': 1, 'tointer': 'select the rows whose date record fuzzily matches to october . for the result records of these rows , all of them fuzzily match to l .', 'tostr': 'all_eq { filter_eq { all_rows ; date ; october } ; result ; l } = true'}
|
all_eq { filter_eq { all_rows ; date ; october } ; result ; l } = true
|
select the rows whose date record fuzzily matches to october . for the result records of these rows , all of them fuzzily match to l .
|
2
|
2
|
{'all_str_eq_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, 'date_4': 4, 'october_5': 5, 'result_6': 6, 'l_7': 7}
|
{'all_str_eq_1': 'all_str_eq', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'date_4': 'date', 'october_5': 'october', 'result_6': 'result', 'l_7': 'l'}
|
{'all_str_eq_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'date_4': [0], 'october_5': [0], 'result_6': [1], 'l_7': [1]}
|
['week', 'date', 'opponent', 'result', 'attendance']
|
[['1', 'september 17 , 1961', 'san francisco 49ers', 'l 35 - 3', '43142'], ['2', 'september 24 , 1961', 'philadelphia eagles', 'l 14 - 7', '50108'], ['3', 'october 1 , 1961', 'new york giants', 'l 24 - 21', '36767'], ['4', 'october 8 , 1961', 'cleveland browns', 'l 31 - 7', '46186'], ['5', 'october 15 , 1961', 'pittsburgh steelers', 'l 20 - 0', '15072'], ['6', 'october 22 , 1961', 'st louis cardinals', 'l 24 - 0', '28037'], ['7', 'october 29 , 1961', 'philadelphia eagles', 'l 27 - 24', '31066'], ['8', 'november 5 , 1961', 'new york giants', 'l 53 - 0', '56077'], ['9', 'november 12 , 1961', 'cleveland browns', 'l 17 - 6', '28975'], ['10', 'november 19 , 1961', 'dallas cowboys', 't 28 - 28', '17500'], ['11', 'november 26 , 1961', 'baltimore colts', 'l 27 - 6', '41062'], ['12', 'december 3 , 1961', 'st louis cardinals', 'l 38 - 24', '16204'], ['13', 'december 10 , 1961', 'pittsburgh steelers', 'l 30 - 14', '21134'], ['14', 'december 17 , 1961', 'dallas cowboys', 'w 34 - 24', '21451']]
|
list of highest - grossing bollywood films
|
https://en.wikipedia.org/wiki/List_of_highest-grossing_Bollywood_films
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11872185-8.html.csv
|
superlative
|
the bollywood movie chennai express has had the highest net gross figures of the first week .
|
{'scope': 'all', 'col_superlative': '5', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '2', 'subset': None}
|
{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'opening week nett gross'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; opening week nett gross }'}, 'movie'], 'result': 'chennai express', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; opening week nett gross } ; movie }'}, 'chennai express'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; opening week nett gross } ; movie } ; chennai express } = true', 'tointer': 'select the row whose opening week nett gross record of all rows is maximum . the movie record of this row is chennai express .'}
|
eq { hop { argmax { all_rows ; opening week nett gross } ; movie } ; chennai express } = true
|
select the row whose opening week nett gross record of all rows is maximum . the movie record of this row is chennai express .
|
3
|
3
|
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'opening week nett gross_5': 5, 'movie_6': 6, 'chennai express_7': 7}
|
{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'opening week nett gross_5': 'opening week nett gross', 'movie_6': 'movie', 'chennai express_7': 'chennai express'}
|
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'opening week nett gross_5': [0], 'movie_6': [1], 'chennai express_7': [2]}
|
['rank', 'movie', 'year', 'studio ( s )', 'opening week nett gross']
|
[['1', 'chennai express', '2013', 'red chillies entertainment', '156 , 70 , 00000'], ['2', 'ek tha tiger', '2012', 'yash raj films', '133 , 22 , 00000'], ['3', 'yeh jawaani hai deewani', '2013', 'dharma productions', '106 , 00 , 00000'], ['4', 'bodyguard', '2011', 'reliance entertainment', '100 , 15 , 00000'], ['5', 'dabangg 2', '2012', 'arbaaz khan productions', '99 , 00 , 00000'], ['6', 'raone', '2011', 'red chillies entertainment', '91 , 27 , 00000'], ['7', 'agneepath', '2012', 'dharma productions', '81 , 77 , 00000'], ['8', 'dabangg', '2010', 'arbaaz khan productions', '80 , 87 , 00000'], ['9', 'jab tak hai jaan', '2012', 'yash raj films', '78 , 00 , 00000'], ['10', 'rowdy rathore', '2012', 'utv motion pictures', '77 , 00 , 00000']]
|
coins of the republic of ireland
|
https://en.wikipedia.org/wiki/Coins_of_the_Republic_of_Ireland
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1682865-1.html.csv
|
majority
|
of the coins of the republic of ireland , all of them were introduced on december 12 , 1928 .
|
{'scope': 'all', 'col': '5', 'most_or_all': 'all', 'criterion': 'equal', 'value': '12 december 1928', 'subset': None}
|
{'func': 'all_str_eq', 'args': ['all_rows', 'introduction', '12 december 1928'], 'result': True, 'ind': 0, 'tointer': 'for the introduction records of all rows , all of them fuzzily match to 12 december 1928 .', 'tostr': 'all_eq { all_rows ; introduction ; 12 december 1928 } = true'}
|
all_eq { all_rows ; introduction ; 12 december 1928 } = true
|
for the introduction records of all rows , all of them fuzzily match to 12 december 1928 .
|
1
|
1
|
{'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'introduction_3': 3, '12 december 1928_4': 4}
|
{'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'introduction_3': 'introduction', '12 december 1928_4': '12 december 1928'}
|
{'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'introduction_3': [0], '12 december 1928_4': [0]}
|
['english name', 'irish name', 'numeral', 'reverse', 'introduction', 'withdrawal', '1 fraction']
|
[['farthing', 'feoirling', '¼ d', 'woodcock', '12 december 1928', '1 january 1962', '1 / 960'], ['halfpenny', 'leath phingin', '½ d', 'sow and litter', '12 december 1928', '1 august 1969', '1 / 480'], ['penny', 'pingin', '1d', 'hen and chickens', '12 december 1928', '1 january 1972', '1 / 240'], ['threepence', 'leath reul', '3d', 'hare', '12 december 1928', '1 january 1972', '1 / 80'], ['sixpence', 'reul', '6d', 'wolfhound', '12 december 1928', '1 january 1972', '1 / 40'], ['shilling', 'scilling', '1s', 'bull', '12 december 1928', '1 january 1993', '1 / 20'], ['florin', 'flóirín', '2s', 'salmon', '12 december 1928', '1 june 1994', '1 / 10'], ['half - crown', 'leath choróin', '2s6d', 'horse', '12 december 1928', '1 january 1970', '1 / 8']]
|
1966 british grand prix
|
https://en.wikipedia.org/wiki/1966_British_Grand_Prix
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1122355-1.html.csv
|
ordinal
|
dan gurney drove the second lowest amount of laps in the 1966 british grand prix .
|
{'row': '19', 'col': '3', 'order': '2', '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', 'laps', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; laps ; 2 }'}, 'driver'], 'result': 'dan gurney', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; laps ; 2 } ; driver }'}, 'dan gurney'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; laps ; 2 } ; driver } ; dan gurney } = true', 'tointer': 'select the row whose laps record of all rows is 2nd minimum . the driver record of this row is dan gurney .'}
|
eq { hop { nth_argmin { all_rows ; laps ; 2 } ; driver } ; dan gurney } = true
|
select the row whose laps record of all rows is 2nd minimum . the driver record of this row is dan gurney .
|
3
|
3
|
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'laps_5': 5, '2_6': 6, 'driver_7': 7, 'dan gurney_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', 'laps_5': 'laps', '2_6': '2', 'driver_7': 'driver', 'dan gurney_8': 'dan gurney'}
|
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'laps_5': [0], '2_6': [0], 'driver_7': [1], 'dan gurney_8': [2]}
|
['driver', 'constructor', 'laps', 'time / retired', 'grid']
|
[['jack brabham', 'brabham - repco', '80', '2:13:13.4', '1'], ['denny hulme', 'brabham - repco', '80', '+ 9.6', '2'], ['graham hill', 'brm', '79', '+ 1 lap', '4'], ['jim clark', 'lotus - climax', '79', '+ 1 lap', '5'], ['jochen rindt', 'cooper - maserati', '79', '+ 1 lap', '7'], ['bruce mclaren', 'mclaren - serenissima', '78', '+ 2 laps', '13'], ['chris irwin', 'brabham - climax', '78', '+ 2 laps', '12'], ['john taylor', 'brabham - brm', '76', '+ 4 laps', '16'], ['bob bondurant', 'brm', '76', '+ 4 laps', '14'], ['guy ligier', 'cooper - maserati', '75', '+ 5 laps', '17'], ['chris lawrence', 'cooper - ferrari', '73', '+ 7 laps', '19'], ['bob anderson', 'brabham - climax', '70', 'not classified', '10'], ['jo siffert', 'cooper - maserati', '70', 'not classified', '11'], ['john surtees', 'cooper - maserati', '67', 'transmission', '6'], ['jo bonnier', 'brabham - climax', '42', 'clutch', '15'], ['peter arundell', 'lotus - brm', '32', 'gearbox', '20'], ['jackie stewart', 'brm', '17', 'engine', '8'], ['mike spence', 'lotus - brm', '15', 'oil leak', '9'], ['dan gurney', 'eagle - climax', '9', 'engine', '3'], ['trevor taylor', 'shannon - climax', '0', 'engine', '18']]
|
1981 vfl season
|
https://en.wikipedia.org/wiki/1981_VFL_season
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10823950-14.html.csv
|
count
|
there were 6 game venues used during the 1981 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 } }', 'tointer': 'select the rows whose venue record is arbitrary . the number of such rows is 6 .'}, '6'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_all { all_rows ; venue } } ; 6 } = true', 'tointer': 'select the rows whose venue record is arbitrary . the number of such rows is 6 .'}
|
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']
|
[['carlton', '15.25 ( 115 )', 'footscray', '5.4 ( 34 )', 'princes park', '17419', '27 june 1981'], ['richmond', '21.23 ( 149 )', 'north melbourne', '15.16 ( 106 )', 'mcg', '31212', '27 june 1981'], ['st kilda', '18.19 ( 127 )', 'melbourne', '8.7 ( 55 )', 'moorabbin oval', '14058', '27 june 1981'], ['south melbourne', '9.16 ( 70 )', 'fitzroy', '14.9 ( 93 )', 'lake oval', '11756', '27 june 1981'], ['collingwood', '13.8 ( 86 )', 'geelong', '9.14 ( 68 )', 'vfl park', '50441', '27 june 1981'], ['hawthorn', '20.13 ( 133 )', 'essendon', '22.19 ( 151 )', 'the gabba', '20351', '28 june 1981']]
|
2008 - 09 milwaukee bucks season
|
https://en.wikipedia.org/wiki/2008%E2%80%9309_Milwaukee_Bucks_season
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17058116-8.html.csv
|
majority
|
the majority of the time milwaukee lost the game .
|
{'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': 'l', 'subset': None}
|
{'func': 'most_str_eq', 'args': ['all_rows', 'score', 'l'], 'result': True, 'ind': 0, 'tointer': 'for the score records of all rows , most of them fuzzily match to l .', 'tostr': 'most_eq { all_rows ; score ; l } = true'}
|
most_eq { all_rows ; score ; l } = true
|
for the score records of all rows , most of them fuzzily match to l .
|
1
|
1
|
{'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'score_3': 3, 'l_4': 4}
|
{'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'score_3': 'score', 'l_4': 'l'}
|
{'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'score_3': [0], 'l_4': [0]}
|
['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'location attendance', 'record']
|
[['52', 'february 3', 'new jersey', 'l 85 - 99 ( ot )', 'richard jefferson ( 27 )', 'dan gadzuric ( 9 )', 'izod center 10102', '24 - 28'], ['53', 'february 7', 'detroit', 'l 121 - 126 ( ot )', 'ramon sessions ( 44 )', 'francisco elson ( 8 )', 'bradley center 17297', '24 - 29'], ['54', 'february 9', 'houston', 'w 124 - 112 ( ot )', 'ramon sessions ( 26 )', 'charlie villanueva ( 8 )', 'bradley center 13904', '25 - 29'], ['55', 'february 11', 'indiana', 'w 122 - 110 ( ot )', 'richard jefferson ( 32 )', 'luc mbah a moute ( 11 )', 'bradley center 13486', '26 - 29'], ['56', 'february 17', 'detroit', 'w 92 - 86 ( ot )', 'richard jefferson ( 29 )', 'ramon sessions ( 9 )', 'the palace of auburn hills 20217', '27 - 29'], ['57', 'february 18', 'chicago', 'l 104 - 113 ( ot )', 'richard jefferson ( 32 )', 'charlie villanueva ( 12 )', 'bradley center 15309', '27 - 30'], ['58', 'february 20', 'cleveland', 'l 103 - 111 ( ot )', 'charlie villanueva ( 26 )', 'charlie villanueva ( 13 )', 'bradley center 18076', '27 - 31'], ['59', 'february 22', 'denver', 'w 120 - 117 ( ot )', 'charlie villanueva ( 36 )', 'francisco elson ( 7 )', 'bradley center 14891', '28 - 31'], ['60', 'february 25', 'dallas', 'l 96 - 116 ( ot )', 'charlie villanueva ( 25 )', 'charlie villanueva ( 7 )', 'american airlines center 19558', '28 - 32'], ['61', 'february 27', 'new orleans', 'l 94 - 95 ( ot )', 'richard jefferson ( 22 )', 'charlie villanueva ( 7 )', 'new orleans arena 17621', '28 - 33'], ['62', 'february 28', 'washington', 'w 109 - 93 ( ot )', 'charlie villanueva ( 25 )', 'dan gadzuric ( 11 )', 'bradley center 15970', '29 - 33']]
|
2007 - 08 fis ski jumping world cup
|
https://en.wikipedia.org/wiki/2007%E2%80%9308_FIS_Ski_Jumping_World_Cup
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14407512-6.html.csv
|
comparative
|
andreas kofler scored more total points than tom hilde in the 2007 - 08 fis ski jumping world cup .
|
{'row_1': '2', 'row_2': '3', 'col': '6', 'col_other': '2', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None}
|
{'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'name', 'andreas kofler'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose name record fuzzily matches to andreas kofler .', 'tostr': 'filter_eq { all_rows ; name ; andreas kofler }'}, 'points'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; name ; andreas kofler } ; points }', 'tointer': 'select the rows whose name record fuzzily matches to andreas kofler . take the points record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'name', 'tom hilde'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose name record fuzzily matches to tom hilde .', 'tostr': 'filter_eq { all_rows ; name ; tom hilde }'}, 'points'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; name ; tom hilde } ; points }', 'tointer': 'select the rows whose name record fuzzily matches to tom hilde . take the points record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; name ; andreas kofler } ; points } ; hop { filter_eq { all_rows ; name ; tom hilde } ; points } } = true', 'tointer': 'select the rows whose name record fuzzily matches to andreas kofler . take the points record of this row . select the rows whose name record fuzzily matches to tom hilde . take the points record of this row . the first record is greater than the second record .'}
|
greater { hop { filter_eq { all_rows ; name ; andreas kofler } ; points } ; hop { filter_eq { all_rows ; name ; tom hilde } ; points } } = true
|
select the rows whose name record fuzzily matches to andreas kofler . take the points record of this row . select the rows whose name record fuzzily matches to tom hilde . take the points 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, 'name_7': 7, 'andreas kofler_8': 8, 'points_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'name_11': 11, 'tom hilde_12': 12, 'points_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', 'name_7': 'name', 'andreas kofler_8': 'andreas kofler', 'points_9': 'points', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'name_11': 'name', 'tom hilde_12': 'tom hilde', 'points_13': 'points'}
|
{'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'name_7': [0], 'andreas kofler_8': [0], 'points_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'name_11': [1], 'tom hilde_12': [1], 'points_13': [3]}
|
['rank', 'name', 'nationality', '1st ( m )', '2nd ( m )', 'points', 'overall wc points ( rank )']
|
[['1', 'thomas morgenstern', 'aut', '132.5', '133.0', '260.4', '600 ( 1 )'], ['2', 'andreas kofler', 'aut', '134.5', '128.5', '254.4', '248 ( 6 )'], ['3', 'tom hilde', 'nor', '133.5', '129.5', '252.9', '256 ( 4 )'], ['4', 'gregor schlierenzauer', 'aut', '126.5', '134.5', '249.8', '349 ( 2 )'], ['5', 'wolfgang loitzl', 'aut', '130.5', '126.5', '242.6', '250 ( 5 )']]
|
50 metre rifle prone
|
https://en.wikipedia.org/wiki/50_metre_rifle_prone
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18656178-1.html.csv
|
ordinal
|
in the 50 metre rifle prone , cairo was the place of the earliest one between 1962 and 1978 .
|
{'scope': 'subset', 'row': '1', 'col': '1', 'order': '1', 'col_other': '2', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'subset': {'col': '1', 'criterion': 'less_than_eq', 'value': '1978'}}
|
{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': [{'func': 'filter_less_eq', 'args': ['all_rows', 'year', '1978'], 'result': None, 'ind': 0, 'tostr': 'filter_less_eq { all_rows ; year ; 1978 }', 'tointer': 'select the rows whose year record is less than or equal to 1978 .'}, 'year', '1'], 'result': None, 'ind': 1, 'tostr': 'nth_argmin { filter_less_eq { all_rows ; year ; 1978 } ; year ; 1 }'}, 'place'], 'result': 'cairo', 'ind': 2, 'tostr': 'hop { nth_argmin { filter_less_eq { all_rows ; year ; 1978 } ; year ; 1 } ; place }'}, 'cairo'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { nth_argmin { filter_less_eq { all_rows ; year ; 1978 } ; year ; 1 } ; place } ; cairo } = true', 'tointer': 'select the rows whose year record is less than or equal to 1978 . select the row whose year record of these rows is 1st minimum . the place record of this row is cairo .'}
|
eq { hop { nth_argmin { filter_less_eq { all_rows ; year ; 1978 } ; year ; 1 } ; place } ; cairo } = true
|
select the rows whose year record is less than or equal to 1978 . select the row whose year record of these rows is 1st minimum . the place record of this row is cairo .
|
4
|
4
|
{'str_eq_3': 3, 'result_4': 4, 'str_hop_2': 2, 'nth_argmin_1': 1, 'filter_less_eq_0': 0, 'all_rows_5': 5, 'year_6': 6, '1978_7': 7, 'year_8': 8, '1_9': 9, 'place_10': 10, 'cairo_11': 11}
|
{'str_eq_3': 'str_eq', 'result_4': 'true', 'str_hop_2': 'str_hop', 'nth_argmin_1': 'nth_argmin', 'filter_less_eq_0': 'filter_less_eq', 'all_rows_5': 'all_rows', 'year_6': 'year', '1978_7': '1978', 'year_8': 'year', '1_9': '1', 'place_10': 'place', 'cairo_11': 'cairo'}
|
{'str_eq_3': [4], 'result_4': [], 'str_hop_2': [3], 'nth_argmin_1': [2], 'filter_less_eq_0': [1], 'all_rows_5': [0], 'year_6': [0], '1978_7': [0], 'year_8': [1], '1_9': [1], 'place_10': [2], 'cairo_11': [3]}
|
['year', 'place', 'gold', 'silver', 'bronze']
|
[['1962', 'cairo', 'karl wenk ( frg )', 'vladimir chuian ( urs )', 'james enoch hill ( usa )'], ['1966', 'wiesbaden', 'david boyd ( usa )', 'jerzy nowicki ( pol )', 'bill krilling ( usa )'], ['1970', 'phoenix', 'manfred fiess ( rsa )', 'esa einari kervinen ( fin )', 'klaus zaehringer ( frg )'], ['1974', 'thun', 'karel bulan ( tch )', 'helge edvin anshushaug ( nor )', 'wolfram waibel sr ( aut )'], ['1978', 'seoul', 'alister allan ( gbr )', 'lones wigger ( usa )', 'lanny bassham ( usa )'], ['1982', 'caracas', 'victor daniltchenko ( urs )', 'william beard ( usa )', 'viktor vlasov ( urs )'], ['1986', 'suhl', 'sandor bereczky ( hun )', 'gale stewart ( can )', 'michael heine ( frg )'], ['1990', 'moscow', 'viatcheslav botchkarev ( urs )', 'harald stenvaag ( nor )', 'tadeusz czerwinski ( pol )'], ['1994', 'milan', 'wenjie li ( chn )', 'stevan pletikosic ( iop )', 'michel bury ( fra )'], ['1998', 'barcelona', 'thomas tamas ( usa )', 'juha hirvi ( fin )', 'sergei kovalenko ( rus )'], ['2002', 'lahti', 'matthew emmons ( usa )', 'rajmond debevec ( slo )', 'espen berg - knutsen ( nor )'], ['2006', 'zagreb', 'sergei martynov ( blr )', 'jury sukhorukov ( ukr )', 'marco de nicolo ( ita )']]
|
1982 - 83 atlanta hawks season
|
https://en.wikipedia.org/wiki/1982%E2%80%9383_Atlanta_Hawks_season
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18409079-1.html.csv
|
majority
|
all of the players that the atlanta hawks drafted were from the united states .
|
{'scope': 'all', 'col': '4', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'united states', 'subset': None}
|
{'func': 'all_str_eq', 'args': ['all_rows', 'nationality', 'united states'], 'result': True, 'ind': 0, 'tointer': 'for the nationality records of all rows , all of them fuzzily match to united states .', 'tostr': 'all_eq { all_rows ; nationality ; united states } = true'}
|
all_eq { all_rows ; nationality ; united states } = true
|
for the nationality records of all rows , all of them fuzzily match to united states .
|
1
|
1
|
{'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'nationality_3': 3, 'united states_4': 4}
|
{'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'nationality_3': 'nationality', 'united states_4': 'united states'}
|
{'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'nationality_3': [0], 'united states_4': [0]}
|
['round', 'pick', 'player', 'nationality', 'college']
|
[['1', '10', 'keith edmonson', 'united states', 'purdue'], ['3', '56', 'joe kopicki', 'united states', 'detroit mercy'], ['5', '102', 'mark hall', 'united states', 'minnesota'], ['6', '126', 'jay bruchak', 'united states', "mount st mary 's"], ['7', '148', 'horace wyatt', 'united states', 'clemson'], ['8', '172', 'james ratiff', 'united states', 'howard'], ['9', '194', 'pierre bland', 'united states', 'elizabeth city state'], ['10', '216', 'ronnie mcadoo', 'united states', 'old dominion']]
|
1975 vfl season
|
https://en.wikipedia.org/wiki/1975_VFL_season
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10883333-3.html.csv
|
majority
|
all games of the 1975 vfl season were played on the 19th of april .
|
{'scope': 'all', 'col': '7', 'most_or_all': 'all', 'criterion': 'equal', 'value': '19 april 1975', 'subset': None}
|
{'func': 'all_str_eq', 'args': ['all_rows', 'date', '19 april 1975'], 'result': True, 'ind': 0, 'tointer': 'for the date records of all rows , all of them fuzzily match to 19 april 1975 .', 'tostr': 'all_eq { all_rows ; date ; 19 april 1975 } = true'}
|
all_eq { all_rows ; date ; 19 april 1975 } = true
|
for the date records of all rows , all of them fuzzily match to 19 april 1975 .
|
1
|
1
|
{'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'date_3': 3, '19 april 1975_4': 4}
|
{'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'date_3': 'date', '19 april 1975_4': '19 april 1975'}
|
{'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'date_3': [0], '19 april 1975_4': [0]}
|
['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date']
|
[['st kilda', '11.21 ( 87 )', 'south melbourne', '9.17 ( 71 )', 'moorabbin oval', '15736', '19 april 1975'], ['essendon', '16.21 ( 117 )', 'melbourne', '15.10 ( 100 )', 'windy hill', '22824', '19 april 1975'], ['carlton', '14.18 ( 102 )', 'north melbourne', '9.12 ( 66 )', 'princes park', '23824', '19 april 1975'], ['geelong', '13.12 ( 90 )', 'footscray', '14.14 ( 98 )', 'kardinia park', '17158', '19 april 1975'], ['fitzroy', '12.13 ( 85 )', 'collingwood', '12.15 ( 87 )', 'junction oval', '17626', '19 april 1975'], ['hawthorn', '17.14 ( 116 )', 'richmond', '12.15 ( 87 )', 'vfl park', '39496', '19 april 1975']]
|
the women 's ashes
|
https://en.wikipedia.org/wiki/The_Women%27s_Ashes
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2554479-2.html.csv
|
aggregation
|
the average number of tests won by england during all series is 0.47 .
|
{'scope': 'all', 'col': '7', 'type': 'average', 'result': '0.47', 'subset': None}
|
{'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'tests won by england'], 'result': '0.47', 'ind': 0, 'tostr': 'avg { all_rows ; tests won by england }'}, '0.47'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; tests won by england } ; 0.47 } = true', 'tointer': 'the average of the tests won by england record of all rows is 0.47 .'}
|
round_eq { avg { all_rows ; tests won by england } ; 0.47 } = true
|
the average of the tests won by england record of all rows is 0.47 .
|
2
|
2
|
{'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'tests won by england_4': 4, '0.47_5': 5}
|
{'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'tests won by england_4': 'tests won by england', '0.47_5': '0.47'}
|
{'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'tests won by england_4': [0], '0.47_5': [1]}
|
['series', 'season', 'played in', 'first match', 'tests played ( sched )', 'tests won by australia', 'tests won by england', 'tests drawn', 'series result', 'holder at series end']
|
[['1', '1934 - 35', 'australia', '28 december 1934', '3', '0', '2', '1', 'england', 'england'], ['2', '1937', 'england', '12 june 1937', '3', '1', '1', '1', 'drawn', 'england'], ['3', '1949 - 50', 'australia', '15 january 1949', '3', '1', '0', '2', 'australia', 'australia'], ['4', '1951', 'england', '16 june 1951', '3', '1', '1', '1', 'drawn', 'australia'], ['5', '1957 - 58', 'australia', '7 february 1958', '3 ( 4 )', '0', '0', '3', 'drawn', 'australia'], ['6', '1963', 'england', '15 june 1961', '3', '0', '1', '2', 'england', 'england'], ['7', '1968 - 69', 'australia', '27 december 1968', '3', '0', '0', '3', 'drawn', 'england'], ['8', '1976', 'england', '19 june 1976', '3', '0', '0', '3', 'drawn', 'england'], ['9', '1984 - 85', 'australia', '13 december 1984', '5', '2', '1', '2', 'australia', 'australia'], ['10', '1987', 'england', '1 august 1987', '3', '1', '0', '2', 'australia', 'australia'], ['11', '1991 - 92', 'australia', '19 february 1992', '1', '1', '0', '0', 'australia', 'australia'], ['12', '1998', 'england', '6 august 1998', '3', '0', '0', '3', 'drawn', 'australia'], ['13', '2001', 'england', '24 june 2001', '2', '2', '0', '0', 'australia', 'australia'], ['14', '2002 - 2003', 'australia', '15 february 2003', '2', '1', '0', '1', 'australia', 'australia'], ['15', '2005', 'england', '9 august 2005', '2', '0', '1', '1', 'england', 'england'], ['16', '2007 - 2008', 'australia', '15 february 2008', '1', '0', '1', '0', 'england', 'england'], ['17', '2009', 'england', '10 july 2009', '1', '0', '0', '1', 'drawn', 'england']]
|
united states house of representatives elections , 1988
|
https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1988
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1341577-47.html.csv
|
ordinal
|
out of the us virginia house of representatives voted in 1988 , thomas j. billey , jr. was the first originally elected to serve .
|
{'row': '1', 'col': '4', 'order': '1', 'col_other': '2', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None}
|
{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'first elected', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; first elected ; 1 }'}, 'incumbent'], 'result': 'thomas j bliley , jr', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; first elected ; 1 } ; incumbent }'}, 'thomas j bliley , jr'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; first elected ; 1 } ; incumbent } ; thomas j bliley , jr } = true', 'tointer': 'select the row whose first elected record of all rows is 1st minimum . the incumbent record of this row is thomas j bliley , jr .'}
|
eq { hop { nth_argmin { all_rows ; first elected ; 1 } ; incumbent } ; thomas j bliley , jr } = true
|
select the row whose first elected record of all rows is 1st minimum . the incumbent record of this row is thomas j bliley , jr .
|
3
|
3
|
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'first elected_5': 5, '1_6': 6, 'incumbent_7': 7, 'thomas j bliley , jr_8': 8}
|
{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmin_0': 'nth_argmin', 'all_rows_4': 'all_rows', 'first elected_5': 'first elected', '1_6': '1', 'incumbent_7': 'incumbent', 'thomas j bliley , jr_8': 'thomas j bliley , jr'}
|
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'first elected_5': [0], '1_6': [0], 'incumbent_7': [1], 'thomas j bliley , jr_8': [2]}
|
['district', 'incumbent', 'party', 'first elected', 'result', 'candidates']
|
[['virginia 3', 'thomas j bliley , jr', 'republican', '1980', 're - elected', 'thomas j bliley , jr ( r ) unopposed'], ['virginia 4', 'norman sisisky', 'democratic', '1982', 're - elected', 'norman sisisky ( d ) unopposed'], ['virginia 6', 'jim olin', 'democratic', '1982', 're - elected', 'jim olin ( d ) 63.9 % charles e judd ( r ) 36.1 %'], ['virginia 7', 'd french slaughter , jr', 'republican', '1984', 're - elected', 'd french slaughter , jr ( r ) unopposed'], ['virginia 9', 'rick boucher', 'democratic', '1982', 're - elected', 'rick boucher ( d ) 63.4 % john c brown ( r ) 36.6 %']]
|
2009 - 14 icc world cricket league
|
https://en.wikipedia.org/wiki/2009%E2%80%9314_ICC_World_Cricket_League
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-22577693-1.html.csv
|
superlative
|
2011 division seven had the most number of runs scored with 72 by kuwait .
|
{'scope': 'all', 'col_superlative': '5', 'row_superlative': '8', 'value_mentioned': 'yes', 'max_or_min': 'max', 'other_col': '1', 'subset': None}
|
{'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'max', 'args': ['all_rows', 'result'], 'result': 'kuwait won by 72 runs scorecard', 'ind': 0, 'tostr': 'max { all_rows ; result }', 'tointer': 'the maximum result record of all rows is kuwait won by 72 runs scorecard .'}, 'kuwait won by 72 runs scorecard'], 'result': True, 'ind': 1, 'tostr': 'eq { max { all_rows ; result } ; kuwait won by 72 runs scorecard }', 'tointer': 'the maximum result record of all rows is kuwait won by 72 runs scorecard .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'result'], 'result': None, 'ind': 2, 'tostr': 'argmax { all_rows ; result }'}, 'details'], 'result': '2011 division seven', 'ind': 3, 'tostr': 'hop { argmax { all_rows ; result } ; details }'}, '2011 division seven'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { argmax { all_rows ; result } ; details } ; 2011 division seven }', 'tointer': 'the details record of the row with superlative result record is 2011 division seven .'}], 'result': True, 'ind': 5, 'tostr': 'and { eq { max { all_rows ; result } ; kuwait won by 72 runs scorecard } ; eq { hop { argmax { all_rows ; result } ; details } ; 2011 division seven } } = true', 'tointer': 'the maximum result record of all rows is kuwait won by 72 runs scorecard . the details record of the row with superlative result record is 2011 division seven .'}
|
and { eq { max { all_rows ; result } ; kuwait won by 72 runs scorecard } ; eq { hop { argmax { all_rows ; result } ; details } ; 2011 division seven } } = true
|
the maximum result record of all rows is kuwait won by 72 runs scorecard . the details record of the row with superlative result record is 2011 division seven .
|
6
|
6
|
{'and_5': 5, 'result_6': 6, 'eq_1': 1, 'max_0': 0, 'all_rows_7': 7, 'result_8': 8, 'kuwait won by 72 runs scorecard_9': 9, 'str_eq_4': 4, 'str_hop_3': 3, 'argmax_2': 2, 'all_rows_10': 10, 'result_11': 11, 'details_12': 12, '2011 division seven_13': 13}
|
{'and_5': 'and', 'result_6': 'true', 'eq_1': 'eq', 'max_0': 'max', 'all_rows_7': 'all_rows', 'result_8': 'result', 'kuwait won by 72 runs scorecard_9': 'kuwait won by 72 runs scorecard', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'argmax_2': 'argmax', 'all_rows_10': 'all_rows', 'result_11': 'result', 'details_12': 'details', '2011 division seven_13': '2011 division seven'}
|
{'and_5': [6], 'result_6': [], 'eq_1': [5], 'max_0': [1], 'all_rows_7': [0], 'result_8': [0], 'kuwait won by 72 runs scorecard_9': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'argmax_2': [3], 'all_rows_10': [2], 'result_11': [2], 'details_12': [3], '2011 division seven_13': [4]}
|
['details', 'host nation ( s )', 'final venue', 'winner', 'result', 'runner - up']
|
[['2009 division seven', 'guernsey', 'king george v sports ground , castel', '207 / 7 ( 46.1 overs )', 'bahrain won by 3 wickets scorecard', 'guernsey 204 / 9 ( 50.0 overs )'], ['2009 division six', 'singapore', 'kallang cricket ground , singapore', '242 / 8 ( 50.0 overs )', 'singapore won by 68 runs scorecard', '174 all out ( 48.4 overs )'], ['2010 division one', 'netherlands', 'vra ground , amstelveen', 'ireland 233 / 4 ( 44.5 overs )', 'ireland won by 6 wickets scorecard', '232 all out ( 48.5 overs )'], ['2010 division four', 'italy', 'ovale di rastignano , pianoro', 'united states 188 / 2 ( 21.4 overs )', 'united states won by 8 wickets scorecard', 'italy 185 / 9 ( 50 overs )'], ['2010 division eight', 'kuwait', 'kuwait oil company hubara ground , ahmadi city', '164 / 4 ( 33.1 overs )', 'kuwait won by 6 wickets scorecard', '163 / 8 ( 50 overs )'], ['2011 division three', 'hong kong', 'kowloon cricket club', 'hong kong 207 / 6 ( 47.1 overs )', 'hong kong won by 4 wickets scorecard', '202 ( 50 overs )'], ['2011 division two', 'united arab emirates', 'dsc cricket stadium , dubai', '201 / 5 ( 45.3 overs )', 'united arab emirates won by 5 wickets scorecard', 'namibia 200 ( 49.3 overs )'], ['2011 division seven', 'botswana', 'botswana cricket association oval 1 , gaborone', '219 / 9 ( 50 overs )', 'kuwait won by 72 runs scorecard', '147 ( 36.5 overs )'], ['2011 division six', 'malaysia', 'kinrara academy oval , kuala lumpur', 'guernsey 211 / 8 ( 49.3 overs )', 'guernsey won by 2 wickets scorecard', '208 / 9 ( 50 overs )'], ['2012 division five', 'singapore', 'kallang ground , singapore', '164 / 1 ( 26.4 overs )', 'singapore won by 9 wickets scorecard', '159 ( 47 overs )'], ['2012 division four', 'malaysia', 'kinrara academy oval , kuala lumpur', '147 / 2 ( 28 overs )', 'nepal won by 8 wickets scorecard', 'united states 145 ( 48.1 overs )'], ['2012 division eight', 'samoa', 'faleata oval no 1 , apia', '222 / 9 ( 50 overs )', 'vanuatu won by 39 runs scorecard', '183 ( 42.5 overs )'], ['2013 division seven', 'botswana', 'botswana cricket association oval 1 , gaborone', '134 / 4 ( 32.1 overs )', 'nigeria won by 6 wickets ( d / l ) scorecard', '133 ( 38 , 4 overs )'], ['2013 division three', 'bermuda', 'national stadium , hamilton', '153 / 5 ( 39.2 overs )', 'nepal won by 5 wickets scorecard', '151 / 8 ( 50.0 overs )'], ['2013 division six', 'jersey', 'grainville cricket ground , st saviour', 'jersey 10 points', 'jersey won on points table', '8 points']]
|
i am ... ( ayumi hamasaki album )
|
https://en.wikipedia.org/wiki/I_Am..._%28Ayumi_Hamasaki_album%29
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1754908-3.html.csv
|
superlative
|
the 'm ' track of the i am ... ( ayumi hamasaki album ) had the most sales .
|
{'scope': 'all', 'col_superlative': '5', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '2', 'subset': None}
|
{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'sales'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; sales }'}, 'title'], 'result': 'm', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; sales } ; title }'}, 'm'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; sales } ; title } ; m } = true', 'tointer': 'select the row whose sales record of all rows is maximum . the title record of this row is m .'}
|
eq { hop { argmax { all_rows ; sales } ; title } ; m } = true
|
select the row whose sales record of all rows is maximum . the title record of this row is m .
|
3
|
3
|
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'sales_5': 5, 'title_6': 6, 'm_7': 7}
|
{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'sales_5': 'sales', 'title_6': 'title', 'm_7': 'm'}
|
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'sales_5': [0], 'title_6': [1], 'm_7': [2]}
|
['date', 'title', 'peak position', 'weeks', 'sales']
|
[['december 13 , 2000', 'm', '1', '18 weeks', '1319070'], ['january 31 , 2001', 'evolution', '1', '17 weeks', '955250'], ['march 7 , 2001', 'never ever', '1', '12 weeks', '756980'], ['may 16 , 2001', 'endless sorrow', '1', '11 weeks', '768510'], ['july 11 , 2001', 'unite !', '1', '17 weeks', '571110'], ['september 27 , 2001', 'dearest', '1', '16 weeks', '750420'], ['december 12 , 2001', 'a song is born', '1', '10 weeks', '441410'], ['march 6 , 2002', 'daybreak ( re - cut single )', '2', '9 weeks', '197140']]
|
intel core
|
https://en.wikipedia.org/wiki/Intel_Core
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-24538587-11.html.csv
|
majority
|
all of the intel core processors have an l3 cache of 3 mb .
|
{'scope': 'all', 'col': '4', 'most_or_all': 'all', 'criterion': 'equal', 'value': '3 mb', 'subset': None}
|
{'func': 'all_str_eq', 'args': ['all_rows', 'l3 cache', '3 mb'], 'result': True, 'ind': 0, 'tointer': 'for the l3 cache records of all rows , all of them fuzzily match to 3 mb .', 'tostr': 'all_eq { all_rows ; l3 cache ; 3 mb } = true'}
|
all_eq { all_rows ; l3 cache ; 3 mb } = true
|
for the l3 cache records of all rows , all of them fuzzily match to 3 mb .
|
1
|
1
|
{'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'l3 cache_3': 3, '3 mb_4': 4}
|
{'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'l3 cache_3': 'l3 cache', '3 mb_4': '3 mb'}
|
{'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'l3 cache_3': [0], '3 mb_4': [0]}
|
['codename ( main article )', 'brand name ( list )', 'cores', 'l3 cache', 'socket', 'tdp', 'i / o bus']
|
[['sandy bridge ( desktop )', 'core i3 - 21xx', '2', '3 mb', 'lga 1155', '65 w', 'direct media interface , integrated gpu'], ['sandy bridge ( desktop )', 'core i3 - 21xxt', '2', '3 mb', 'lga 1155', '35 w', 'direct media interface , integrated gpu'], ['ivy bridge ( desktop )', 'core i3 - 32xxt', '2', '3 mb', 'lga 1155', '35 w', 'direct media interface , integrated gpu'], ['ivy bridge ( desktop )', 'core i3 - 32xx', '2', '3 mb', 'lga 1155', '55 w', 'direct media interface , integrated gpu'], ['sandy bridge ( mobile )', 'core i3 - 2xx0 m', '2', '3 mb', 'rpga - 988b bga - 1023', '35 w', 'direct media interface , integrated gpu'], ['sandy bridge ( mobile )', 'core i3 - 2xx7 m', '2', '3 mb', 'bga - 1023', '17 w', 'direct media interface , integrated gpu'], ['ivy bridge ( mobile )', 'core i3 - 3xx0 m', '2', '3 mb', 'rpga - 988b bga - 1023', '35 w', 'direct media interface , integrated gpu'], ['ivy bridge ( mobile )', 'core i3 - 3xx7u', '2', '3 mb', 'bga - 1023', '17 w', 'direct media interface , integrated gpu']]
|
1960 st. louis cardinals ( nfl ) season
|
https://en.wikipedia.org/wiki/1960_St._Louis_Cardinals_%28NFL%29_season
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16642141-1.html.csv
|
unique
|
in the 1960 st. louis cardinals ( nfl ) season , when the game was in december , the only game that was a loss was when the opponent was the philadelphia eagles .
|
{'scope': 'subset', 'row': '11', 'col': '4', 'col_other': '3', 'criterion': 'fuzzily_match', 'value': 'l', 'subset': {'col': '2', 'criterion': 'fuzzily_match', 'value': 'december'}}
|
{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', 'december'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; date ; december }', 'tointer': 'select the rows whose date record fuzzily matches to december .'}, 'result', 'l'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose date record fuzzily matches to december . among these rows , select the rows whose result record fuzzily matches to l .', 'tostr': 'filter_eq { filter_eq { all_rows ; date ; december } ; result ; l }'}], 'result': True, 'ind': 2, 'tostr': 'only { filter_eq { filter_eq { all_rows ; date ; december } ; result ; l } }', 'tointer': 'select the rows whose date record fuzzily matches to december . among these rows , select the rows whose result record fuzzily matches to l . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', 'december'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; date ; december }', 'tointer': 'select the rows whose date record fuzzily matches to december .'}, 'result', 'l'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose date record fuzzily matches to december . among these rows , select the rows whose result record fuzzily matches to l .', 'tostr': 'filter_eq { filter_eq { all_rows ; date ; december } ; result ; l }'}, 'opponent'], 'result': 'philadelphia eagles', 'ind': 3, 'tostr': 'hop { filter_eq { filter_eq { all_rows ; date ; december } ; result ; l } ; opponent }'}, 'philadelphia eagles'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { filter_eq { filter_eq { all_rows ; date ; december } ; result ; l } ; opponent } ; philadelphia eagles }', 'tointer': 'the opponent record of this unqiue row is philadelphia eagles .'}], 'result': True, 'ind': 5, 'tostr': 'and { only { filter_eq { filter_eq { all_rows ; date ; december } ; result ; l } } ; eq { hop { filter_eq { filter_eq { all_rows ; date ; december } ; result ; l } ; opponent } ; philadelphia eagles } } = true', 'tointer': 'select the rows whose date record fuzzily matches to december . among these rows , select the rows whose result record fuzzily matches to l . there is only one such row in the table . the opponent record of this unqiue row is philadelphia eagles .'}
|
and { only { filter_eq { filter_eq { all_rows ; date ; december } ; result ; l } } ; eq { hop { filter_eq { filter_eq { all_rows ; date ; december } ; result ; l } ; opponent } ; philadelphia eagles } } = true
|
select the rows whose date record fuzzily matches to december . among these rows , select the rows whose result record fuzzily matches to l . there is only one such row in the table . the opponent record of this unqiue row is philadelphia eagles .
|
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, 'date_8': 8, 'december_9': 9, 'result_10': 10, 'l_11': 11, 'str_eq_4': 4, 'str_hop_3': 3, 'opponent_12': 12, 'philadelphia eagles_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', 'date_8': 'date', 'december_9': 'december', 'result_10': 'result', 'l_11': 'l', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'opponent_12': 'opponent', 'philadelphia eagles_13': 'philadelphia eagles'}
|
{'and_5': [6], 'result_6': [], 'only_2': [5], 'filter_str_eq_1': [2, 3], 'filter_str_eq_0': [1], 'all_rows_7': [0], 'date_8': [0], 'december_9': [0], 'result_10': [1], 'l_11': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'opponent_12': [3], 'philadelphia eagles_13': [4]}
|
['week', 'date', 'opponent', 'result', 'attendance']
|
[['1', 'september 23 , 1960', 'los angeles rams', 'w 43 - 21', '47448'], ['2', 'october 2 , 1960', 'new york giants', 'l 35 - 14', '26089'], ['3', 'october 9 , 1960', 'philadelphia eagles', 'l 31 - 27', '33701'], ['4', 'october 16 , 1960', 'pittsburgh steelers', 'l 27 - 14', '22971'], ['5', 'october 23 , 1960', 'dallas cowboys', 'w 12 - 10', '23128'], ['6', 'october 30 , 1960', 'new york giants', 'w 20 - 13', '58516'], ['7', 'november 6 , 1960', 'washington redskins', 'w 44 - 7', '22458'], ['8', 'november 13 , 1960', 'cleveland browns', 'l 28 - 27', '49192'], ['9', 'november 20 , 1960', 'washington redskins', 'w 26 - 14', '23848'], ['10', 'november 27 , 1960', 'cleveland browns', 't 17 - 17', '26146'], ['11', 'december 4 , 1960', 'philadelphia eagles', 'l 20 - 6', '21358'], ['13', 'december 18 , 1960', 'pittsburgh steelers', 'w 38 - 7', '20840']]
|
list of number - one singles of 1981 ( canada )
|
https://en.wikipedia.org/wiki/List_of_number-one_singles_of_1981_%28Canada%29
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15476957-1.html.csv
|
ordinal
|
the song ' ( just like ) starting over ' spent the second highest amount of weeks on top of the 1981 canadian chart .
|
{'row': '1', 'col': '3', 'order': '2', 'col_other': '4', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None}
|
{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'weeks on top', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; weeks on top ; 2 }'}, 'song'], 'result': '( just like ) starting over', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; weeks on top ; 2 } ; song }'}, '( just like ) starting over'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; weeks on top ; 2 } ; song } ; ( just like ) starting over } = true', 'tointer': 'select the row whose weeks on top record of all rows is 2nd maximum . the song record of this row is ( just like ) starting over .'}
|
eq { hop { nth_argmax { all_rows ; weeks on top ; 2 } ; song } ; ( just like ) starting over } = true
|
select the row whose weeks on top record of all rows is 2nd maximum . the song record of this row is ( just like ) starting over .
|
3
|
3
|
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'weeks on top_5': 5, '2_6': 6, 'song_7': 7, '(just like) starting over_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', 'weeks on top_5': 'weeks on top', '2_6': '2', 'song_7': 'song', '(just like) starting over_8': '( just like ) starting over'}
|
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'weeks on top_5': [0], '2_6': [0], 'song_7': [1], '(just like) starting over_8': [2]}
|
['volume : issue', 'issue date ( s )', 'weeks on top', 'song', 'artist']
|
[['34:6 - 8', '20 december 1980 - 31 january 1981', '7', '( just like ) starting over', 'john lennon'], ['34:9 - 12', '7 - 28 february', '4', 'the tide is high', 'blondie'], ['34:13', '7 march', '1', 'the best of times', 'styx'], ['34:14 - 15', '14 - 21 march', '2', 'woman', 'john lennon'], ['34:16 - 18', '28 march - 11 april', '3', 'celebration', 'kool & the gang'], ['34:19 - 20', '18 - 25 april', '2', '9 to 5', 'dolly parton'], ['34:21 - 22', '2 - 9 may', '2', 'morning train', 'sheena easton'], ['34:23 - 25', '16 - 30 may', '3', 'angel of the morning', 'juice newton'], ['34:26 - 35:4', '6 june - 22 august', '12', 'stars on 45 medley', 'stars on 45'], ['35:5 §', '29 august', '1', 'gemini dream', 'moody blues'], ['35:6', '5 september', '1', 'sausalito summernight', 'diesel'], ['35:7 - 8', '12 - 19 september', '2', 'urgent', 'foreigner'], ['35:9 - 14', '26 september - 31 october', '6', 'endless love', 'diana ross and lionel richie'], ['35:15', '7 november', '1', 'every little thing she does is magic', 'the police'], ['35:16 - 20', '14 november - 12 december', '5', 'the friends of mr cairo', 'jon & vangelis'], ['35:21 - 24', '19 december - 23 january 1982', '6', 'physical', 'olivia newton - john']]
|
socialist destourian party
|
https://en.wikipedia.org/wiki/Socialist_Destourian_Party
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-13746866-2.html.csv
|
unique
|
1981 was the only year that the socialist destourian party did not receive 100 % of the votes .
|
{'scope': 'all', 'row': '5', 'col': '4', 'col_other': '1', 'criterion': 'not_equal', 'value': '100 %', 'subset': None}
|
{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_not_eq', 'args': ['all_rows', 'percentage of votes', '100 %'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose percentage of votes record does not match to 100 % .', 'tostr': 'filter_not_eq { all_rows ; percentage of votes ; 100 % }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_not_eq { all_rows ; percentage of votes ; 100 % } }', 'tointer': 'select the rows whose percentage of votes record does not match to 100 % . there is only one such row in the table .'}, {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_not_eq', 'args': ['all_rows', 'percentage of votes', '100 %'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose percentage of votes record does not match to 100 % .', 'tostr': 'filter_not_eq { all_rows ; percentage of votes ; 100 % }'}, 'election date'], 'result': '1981', 'ind': 2, 'tostr': 'hop { filter_not_eq { all_rows ; percentage of votes ; 100 % } ; election date }'}, '1981'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_not_eq { all_rows ; percentage of votes ; 100 % } ; election date } ; 1981 }', 'tointer': 'the election date record of this unqiue row is 1981 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_not_eq { all_rows ; percentage of votes ; 100 % } } ; eq { hop { filter_not_eq { all_rows ; percentage of votes ; 100 % } ; election date } ; 1981 } } = true', 'tointer': 'select the rows whose percentage of votes record does not match to 100 % . there is only one such row in the table . the election date record of this unqiue row is 1981 .'}
|
and { only { filter_not_eq { all_rows ; percentage of votes ; 100 % } } ; eq { hop { filter_not_eq { all_rows ; percentage of votes ; 100 % } ; election date } ; 1981 } } = true
|
select the rows whose percentage of votes record does not match to 100 % . there is only one such row in the table . the election date record of this unqiue row is 1981 .
|
6
|
5
|
{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_not_eq_0': 0, 'all_rows_6': 6, 'percentage of votes_7': 7, '100%_8': 8, 'eq_3': 3, 'num_hop_2': 2, 'election date_9': 9, '1981_10': 10}
|
{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_not_eq_0': 'filter_str_not_eq', 'all_rows_6': 'all_rows', 'percentage of votes_7': 'percentage of votes', '100%_8': '100 %', 'eq_3': 'eq', 'num_hop_2': 'num_hop', 'election date_9': 'election date', '1981_10': '1981'}
|
{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_not_eq_0': [1, 2], 'all_rows_6': [0], 'percentage of votes_7': [0], '100%_8': [0], 'eq_3': [4], 'num_hop_2': [3], 'election date_9': [2], '1981_10': [3]}
|
['election date', 'party leader', 'number of votes received', 'percentage of votes', 'number of deputies']
|
[['1964', 'habib bourguiba', '1255153', '100 %', '101'], ['1969', 'habib bourguiba', '1363939', '100 %', '101'], ['1974', 'habib bourguiba', '1570954', '100 %', '112'], ['1979', 'habib bourguiba', '1560753', '100 %', '121'], ['1981', 'habib bourguiba', '1828363', '94.2 %', '136']]
|
fai world grand prix 2008
|
https://en.wikipedia.org/wiki/FAI_World_Grand_Prix_2008
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17277703-7.html.csv
|
superlative
|
in the 2008 fai world grand prix , mario kiessling 's position ranks the highest .
|
{'scope': 'all', 'col_superlative': '1', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '2', 'subset': None}
|
{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmin', 'args': ['all_rows', 'position'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; position }'}, 'pilot'], 'result': 'mario kiessling', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; position } ; pilot }'}, 'mario kiessling'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmin { all_rows ; position } ; pilot } ; mario kiessling } = true', 'tointer': 'select the row whose position record of all rows is minimum . the pilot record of this row is mario kiessling .'}
|
eq { hop { argmin { all_rows ; position } ; pilot } ; mario kiessling } = true
|
select the row whose position record of all rows is minimum . the pilot record of this row is mario kiessling .
|
3
|
3
|
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'position_5': 5, 'pilot_6': 6, 'mario kiessling_7': 7}
|
{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'position_5': 'position', 'pilot_6': 'pilot', 'mario kiessling_7': 'mario kiessling'}
|
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'position_5': [0], 'pilot_6': [1], 'mario kiessling_7': [2]}
|
['position', 'pilot', 'glider', 'speed', 'distance']
|
[['1', 'mario kiessling', 'ventus 2ax', '128.8 km / h', '240.5 km'], ['2', 'uli schwenk', 'ventus 2ax', '128.1 km / h', '240.5 km'], ['3', 'carlos rocca vidal', 'ventus 2b', '127.6 km / h', '240.5 km'], ['4', 'sebastian kawa', 'diana 2', '127.1 km / h', '240.5 km'], ['5', 'thomas gostner', 'diana 2', '126.3 km / h', '240.5 km'], ['6', 'graham parker', 'asg 29', '125.7 km / h', '240.5 km'], ['7', 'tilo holighaus', 'ventus 2ax', '125.3 km / h', '240.5 km'], ['8', 'wolfgang janowitsch', 'ventus 2cax', '124.2 km / h', '240.5 km'], ['9', 'heimo demmerer', 'ventus 2b', '124.1 km / h', '240.5 km'], ['10', 'eduard supersperger', 'ventus 2b', '124.0 km / h', '240.5 km'], ['10', 'stanislaw wujczak', 'asg 29', '123.9 km / h', '240.5 km'], ['10', 'petr krejcirik', 'ventus 2ax', '121.4 km / h', '240.5 km'], ['10', 'rene vidal', 'ventus 2c', '117.1 km / h', '240.5 km'], ['10', 'patrick puskeiler', 'discus 2ax', '111.1 km / h', '240.5 km'], ['10', 'olli teronen', 'asg 29', '95 km / h', '240.5 km']]
|
1997 tennessee oilers season
|
https://en.wikipedia.org/wiki/1997_Tennessee_Oilers_season
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15986484-2.html.csv
|
count
|
in 1997 , the tennessee oilers played the jacksonville jaguars twice .
|
{'scope': 'all', 'criterion': 'equal', 'value': 'jacksonville jaguars', 'result': '2', 'col': '3', 'subset': None}
|
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', 'jacksonville jaguars'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose opponent record fuzzily matches to jacksonville jaguars .', 'tostr': 'filter_eq { all_rows ; opponent ; jacksonville jaguars }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; opponent ; jacksonville jaguars } }', 'tointer': 'select the rows whose opponent record fuzzily matches to jacksonville jaguars . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; opponent ; jacksonville jaguars } } ; 2 } = true', 'tointer': 'select the rows whose opponent record fuzzily matches to jacksonville jaguars . the number of such rows is 2 .'}
|
eq { count { filter_eq { all_rows ; opponent ; jacksonville jaguars } } ; 2 } = true
|
select the rows whose opponent record fuzzily matches to jacksonville jaguars . the number of such rows is 2 .
|
3
|
3
|
{'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'opponent_5': 5, 'jacksonville jaguars_6': 6, '2_7': 7}
|
{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'opponent_5': 'opponent', 'jacksonville jaguars_6': 'jacksonville jaguars', '2_7': '2'}
|
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'opponent_5': [0], 'jacksonville jaguars_6': [0], '2_7': [2]}
|
['week', 'date', 'opponent', 'result', 'record', 'location', 'attendance']
|
[['1', 'august 31 , 1997', 'oakland raiders', 'w 24 - 21', '1 - 0', 'liberty bowl memorial stadium', '30171'], ['2', 'september 7 , 1997', 'miami dolphins', 'l 16 - 13', '1 - 1', 'pro player stadium', '64439'], ['3', '-', '-', '-', '-', '-', ''], ['4', 'september 21 , 1997', 'baltimore ravens', 'l 36 - 10', '1 - 2', 'liberty bowl memorial stadium', '17737'], ['5', 'september 28 , 1997', 'pittsburgh steelers', 'l 37 - 24', '1 - 3', 'three rivers stadium', '57507'], ['6', 'october 5 , 1997', 'seattle seahawks', 'l 16 - 13', '1 - 4', 'kingdome', '49897'], ['7', 'october 12 , 1997', 'cincinnati bengals', 'w 30 - 7', '2 - 4', 'liberty bowl memorial stadium', '17071'], ['8', 'october 19 , 1997', 'washington redskins', 'w 28 - 14', '3 - 4', 'liberty bowl memorial stadium', '31042'], ['9', 'october 26 , 1997', 'arizona cardinals', 'w 41 - 14', '4 - 4', 'sun devil stadium', '44030'], ['10', 'november 2 , 1997', 'jacksonville jaguars', 'l 30 - 24', '4 - 5', 'liberty bowl memorial stadium', '27208'], ['11', 'november 9 , 1997', 'new york giants', 'w 10 - 6', '5 - 5', 'liberty bowl memorial stadium', '26744'], ['12', 'november 16 , 1997', 'jacksonville jaguars', 'l 17 - 9', '5 - 6', 'alltel stadium', '70070'], ['13', 'november 23 , 1997', 'buffalo bills', 'w 31 - 14', '6 - 6', 'liberty bowl memorial stadium', '23571'], ['14', 'november 27 , 1997', 'dallas cowboys', 'w 27 - 14', '7 - 6', 'texas stadium', '63421'], ['15', 'december 4 , 1997', 'cincinnati bengals', 'l 41 - 14', '7 - 7', 'cinergy field', '49086'], ['16', 'december 14 , 1997', 'baltimore ravens', 'l 21 - 19', '7 - 8', 'memorial stadium', '60558'], ['17', 'december 21 , 1997', 'pittsburgh steelers', 'w 16 - 6', '8 - 8', 'liberty bowl memorial stadium', '50677']]
|
washington redskins draft history
|
https://en.wikipedia.org/wiki/Washington_Redskins_draft_history
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17100961-11.html.csv
|
count
|
two players were drafted by the washington redskins out of duquesne college .
|
{'scope': 'all', 'criterion': 'equal', 'value': 'duquesne', 'result': '2', 'col': '6', 'subset': None}
|
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'college', 'duquesne'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose college record fuzzily matches to duquesne .', 'tostr': 'filter_eq { all_rows ; college ; duquesne }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; college ; duquesne } }', 'tointer': 'select the rows whose college record fuzzily matches to duquesne . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; college ; duquesne } } ; 2 } = true', 'tointer': 'select the rows whose college record fuzzily matches to duquesne . the number of such rows is 2 .'}
|
eq { count { filter_eq { all_rows ; college ; duquesne } } ; 2 } = true
|
select the rows whose college record fuzzily matches to duquesne . the number of such rows is 2 .
|
3
|
3
|
{'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'college_5': 5, 'duquesne_6': 6, '2_7': 7}
|
{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'college_5': 'college', 'duquesne_6': 'duquesne', '2_7': '2'}
|
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'college_5': [0], 'duquesne_6': [0], '2_7': [2]}
|
['round', 'pick', 'overall', 'name', 'position', 'college']
|
[['1', '6', '6', 'spec sanders', 'hb', 'texas'], ['3', '6', '21', 'rufus deal', 'rb', 'auburn'], ['5', '6', '36', 'joe zeno', 'g', 'holy cross'], ['6', '6', '46', 'harley mccollum', 'ot', 'tulane'], ['7', '6', '56', 'bob fitch', 'e', 'minnesota'], ['8', '6', '66', 'george peters', 'rb', 'oregon state'], ['9', '6', '76', 'frank swiger', 'rb', 'duke'], ['10', '6', '86', 'john goodyear', 'rb', 'marquette'], ['11', '6', '96', 'al demao', 'c', 'duquesne'], ['12', '6', '106', 'phil ahwesh', 'rb', 'duquesne'], ['13', '6', '116', 'john kovatch', 'e', 'notre dame'], ['14', '6', '126', 'bill decorrevont', 'rb', 'northwestern'], ['15', '6', '136', 'marvin whited', 'g', 'oklahoma'], ['16', '6', '146', 'dee chipman', 'rb', 'brigham young'], ['17', '6', '156', 'george watts', 'ot', 'appalachian state'], ['18', '6', '166', 'gene stewart', 'rb', 'willamette'], ['19', '6', '176', 'charlie timmons', 'fb', 'clemson'], ['20', '6', '186', 'tiny croft', 'ot', 'ripon'], ['21', '1', '191', 'steve juzwik', 'hb', 'notre dame'], ['22', '1', '196', 'al couppee', 'g', 'iowa']]
|
papal election , 1280 - 81
|
https://en.wikipedia.org/wiki/Papal_election%2C_1280%E2%80%9381
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18924985-1.html.csv
|
majority
|
the majority of the electors had rome as their nationality .
|
{'scope': 'all', 'col': '2', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'rome', 'subset': None}
|
{'func': 'most_str_eq', 'args': ['all_rows', 'nationality', 'rome'], 'result': True, 'ind': 0, 'tointer': 'for the nationality records of all rows , most of them fuzzily match to rome .', 'tostr': 'most_eq { all_rows ; nationality ; rome } = true'}
|
most_eq { all_rows ; nationality ; rome } = true
|
for the nationality records of all rows , most of them fuzzily match to rome .
|
1
|
1
|
{'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'nationality_3': 3, 'rome_4': 4}
|
{'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'nationality_3': 'nationality', 'rome_4': 'rome'}
|
{'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'nationality_3': [0], 'rome_4': [0]}
|
['elector', 'nationality', 'cardinalatial order and title', 'elevated', 'elevator']
|
[['ordonho alvares', 'portuguese', 'cardinal - bishop of frascati', '1278 , march 12', 'nicholas iii'], ['latino malabranca orsini , op', 'rome', 'cardinal - bishop of ostia e velletri', '1278 , march 12', 'nicholas iii'], ['bentivenga da bentivengi , ofm', 'acquasparta', 'cardinal - bishop of albano', '1278 , march 12', 'nicholas iii'], ['anchero pantalãone', 'french', 'cardinal - priest of s prassede', '1262 , may 22', 'urban iv'], ['simon de brion', 'french', 'cardinal - priest of s cecilia', '1261 , december 17', 'urban iv'], ['guillaume de bray', 'french', 'cardinal - priest of s marco', '1262 , may 22', 'urban iv'], ['gerardo bianchi', 'parma', 'cardinal - priest of ss xii apostoli', '1278 , march 12', 'nicholas iii'], ['girolamo masci , ofm', 'lisciano', 'cardinal - priest of s pudenziana', '1278 , march 12', 'nicholas iii'], ['giacomo savelli', 'rome', 'cardinal - deacon of s maria in cosmedin', '1261 , december 17', 'urban iv'], ['goffredo da alatri', 'alatri', 'cardinal - deacon of s giorgio in velabro', '1261 , december 17', 'urban iv'], ['matteo orsini', 'rome', 'cardinal - deacon of s maria in portico', '1262 , may 22', 'urban iv'], ['giordano orsini', 'rome', 'cardinal - deacon of s eustachio', '1278 , march 12', 'nicholas iii'], ['giacomo colonna', 'rome', 'cardinal - deacon of s maria in via lata', '1278 , march 12', 'nicholas iii']]
|
1951 vfl season
|
https://en.wikipedia.org/wiki/1951_VFL_season
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10701914-14.html.csv
|
superlative
|
in the 1951 vfl season the home team with biggest crowd was 26500 on 4 august 1951 .
|
{'scope': 'all', 'col_superlative': '6', 'row_superlative': '5', 'value_mentioned': 'yes', 'max_or_min': 'max', 'other_col': '7', 'subset': None}
|
{'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'max', 'args': ['all_rows', 'crowd'], 'result': '26500', 'ind': 0, 'tostr': 'max { all_rows ; crowd }', 'tointer': 'the maximum crowd record of all rows is 26500 .'}, '26500'], 'result': True, 'ind': 1, 'tostr': 'eq { max { all_rows ; crowd } ; 26500 }', 'tointer': 'the maximum crowd record of all rows is 26500 .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'crowd'], 'result': None, 'ind': 2, 'tostr': 'argmax { all_rows ; crowd }'}, 'date'], 'result': '4 august 1951', 'ind': 3, 'tostr': 'hop { argmax { all_rows ; crowd } ; date }'}, '4 august 1951'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { argmax { all_rows ; crowd } ; date } ; 4 august 1951 }', 'tointer': 'the date record of the row with superlative crowd record is 4 august 1951 .'}], 'result': True, 'ind': 5, 'tostr': 'and { eq { max { all_rows ; crowd } ; 26500 } ; eq { hop { argmax { all_rows ; crowd } ; date } ; 4 august 1951 } } = true', 'tointer': 'the maximum crowd record of all rows is 26500 . the date record of the row with superlative crowd record is 4 august 1951 .'}
|
and { eq { max { all_rows ; crowd } ; 26500 } ; eq { hop { argmax { all_rows ; crowd } ; date } ; 4 august 1951 } } = true
|
the maximum crowd record of all rows is 26500 . the date record of the row with superlative crowd record is 4 august 1951 .
|
6
|
6
|
{'and_5': 5, 'result_6': 6, 'eq_1': 1, 'max_0': 0, 'all_rows_7': 7, 'crowd_8': 8, '26500_9': 9, 'str_eq_4': 4, 'str_hop_3': 3, 'argmax_2': 2, 'all_rows_10': 10, 'crowd_11': 11, 'date_12': 12, '4 august 1951_13': 13}
|
{'and_5': 'and', 'result_6': 'true', 'eq_1': 'eq', 'max_0': 'max', 'all_rows_7': 'all_rows', 'crowd_8': 'crowd', '26500_9': '26500', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'argmax_2': 'argmax', 'all_rows_10': 'all_rows', 'crowd_11': 'crowd', 'date_12': 'date', '4 august 1951_13': '4 august 1951'}
|
{'and_5': [6], 'result_6': [], 'eq_1': [5], 'max_0': [1], 'all_rows_7': [0], 'crowd_8': [0], '26500_9': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'argmax_2': [3], 'all_rows_10': [2], 'crowd_11': [2], 'date_12': [3], '4 august 1951_13': [4]}
|
['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date']
|
[['fitzroy', '8.21 ( 69 )', 'melbourne', '6.9 ( 45 )', 'brunswick street oval', '9000', '4 august 1951'], ['essendon', '16.10 ( 106 )', 'south melbourne', '8.12 ( 60 )', 'windy hill', '20000', '4 august 1951'], ['st kilda', '11.8 ( 74 )', 'hawthorn', '9.14 ( 68 )', 'junction oval', '6000', '4 august 1951'], ['north melbourne', '10.10 ( 70 )', 'footscray', '11.15 ( 81 )', 'arden street oval', '14000', '4 august 1951'], ['geelong', '3.11 ( 29 )', 'collingwood', '4.7 ( 31 )', 'kardinia park', '26500', '4 august 1951'], ['richmond', '9.12 ( 66 )', 'carlton', '4.9 ( 33 )', 'punt road oval', '17000', '4 august 1951']]
|
atlantic hurricane season
|
https://en.wikipedia.org/wiki/Atlantic_hurricane_season
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2930244-3.html.csv
|
aggregation
|
on average , there were about 4.3 hurricanes across all atlantic hurricane seasons .
|
{'scope': 'all', 'col': '3', 'type': 'average', 'result': '4.3', 'subset': None}
|
{'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'number of hurricanes'], 'result': '4.3', 'ind': 0, 'tostr': 'avg { all_rows ; number of hurricanes }'}, '4.3'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; number of hurricanes } ; 4.3 } = true', 'tointer': 'the average of the number of hurricanes record of all rows is 4.3 .'}
|
round_eq { avg { all_rows ; number of hurricanes } ; 4.3 } = true
|
the average of the number of hurricanes record of all rows is 4.3 .
|
2
|
2
|
{'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'number of hurricanes_4': 4, '4.3_5': 5}
|
{'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'number of hurricanes_4': 'number of hurricanes', '4.3_5': '4.3'}
|
{'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'number of hurricanes_4': [0], '4.3_5': [1]}
|
['year', 'number of tropical storms', 'number of hurricanes', 'number of major hurricanes', 'deaths', 'strongest storm']
|
[['1860', '1', '5', '1', '60 +', 'one'], ['1861', '2', '6', '0', '22 +', 'one and three'], ['1862', '3', '3', '0', '3', 'two and three'], ['1863', '4', '5', '0', '90', 'one , two , three & four'], ['1864', '2', '3', '0', 'none', 'one , three & five'], ['1865', '4', '3', '0', '326', 'four & seven'], ['1866', '1', '5', '1', '383', 'six'], ['1867', '2', '6', '0', '811', "' san narciso '"], ['1868', '1', '3', '0', '2', 'one , two & four']]
|
united states house of representatives elections , 1948
|
https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1948
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1342218-43.html.csv
|
count
|
of the incumbents from texas districts that were re-elected in the 1948 united states house of representative elections , two of them were first elected in the year 1944 .
|
{'scope': 'subset', 'criterion': 'equal', 'value': '1944', 'result': '2', 'col': '4', 'subset': {'col': '5', 'criterion': 'equal', 'value': 're - elected'}}
|
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'result', 're - elected'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; result ; re - elected }', 'tointer': 'select the rows whose result record fuzzily matches to re - elected .'}, 'first elected', '1944'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose result record fuzzily matches to re - elected . among these rows , select the rows whose first elected record is equal to 1944 .', 'tostr': 'filter_eq { filter_eq { all_rows ; result ; re - elected } ; first elected ; 1944 }'}], 'result': '2', 'ind': 2, 'tostr': 'count { filter_eq { filter_eq { all_rows ; result ; re - elected } ; first elected ; 1944 } }', 'tointer': 'select the rows whose result record fuzzily matches to re - elected . among these rows , select the rows whose first elected record is equal to 1944 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_eq { filter_eq { all_rows ; result ; re - elected } ; first elected ; 1944 } } ; 2 } = true', 'tointer': 'select the rows whose result record fuzzily matches to re - elected . among these rows , select the rows whose first elected record is equal to 1944 . the number of such rows is 2 .'}
|
eq { count { filter_eq { filter_eq { all_rows ; result ; re - elected } ; first elected ; 1944 } } ; 2 } = true
|
select the rows whose result record fuzzily matches to re - elected . among these rows , select the rows whose first elected record is equal to 1944 . the number of such rows is 2 .
|
4
|
4
|
{'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_eq_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'result_6': 6, 're - elected_7': 7, 'first elected_8': 8, '1944_9': 9, '2_10': 10}
|
{'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_eq_1': 'filter_eq', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'result_6': 'result', 're - elected_7': 're - elected', 'first elected_8': 'first elected', '1944_9': '1944', '2_10': '2'}
|
{'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_eq_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'result_6': [0], 're - elected_7': [0], 'first elected_8': [1], '1944_9': [1], '2_10': [3]}
|
['district', 'incumbent', 'party', 'first elected', 'result', 'candidates']
|
[['texas 1', 'wright patman', 'democratic', '1928', 're - elected', 'wright patman ( d ) unopposed'], ['texas 2', 'jesse m combs', 'democratic', '1944', 're - elected', 'jesse m combs ( d ) 93.3 % don parker ( r ) 6.7 %'], ['texas 4', 'sam rayburn', 'democratic', '1912', 're - elected', 'sam rayburn ( d ) unopposed'], ['texas 7', 'tom pickett', 'democratic', '1944', 're - elected', 'tom pickett ( d ) unopposed'], ['texas 9', 'clark w thompson', 'democratic', '1947', 're - elected', 'clark w thompson ( d ) unopposed'], ['texas 10', 'lyndon b johnson', 'democratic', '1937', 'retired to run for us senate democratic hold', 'homer thornberry ( d ) unopposed'], ['texas 13', 'ed gossett', 'democratic', '1938', 're - elected', 'ed gossett ( d ) unopposed'], ['texas 15', 'milton h west', 'democratic', '1933', 'retired democratic hold', 'lloyd bentsen ( d ) unopposed'], ['texas 17', 'omar burleson', 'democratic', '1946', 're - elected', 'omar burleson ( d ) unopposed'], ['texas 18', 'eugene worley', 'democratic', '1940', 're - elected', 'eugene worley ( d ) 88.7 % j evetts haley ( r ) 11.3 %'], ['texas 20', 'paul j kilday', 'democratic', '1938', 're - elected', 'paul j kilday ( d ) 75.3 % j p ledvina ( r ) 24.7 %']]
|
1972 - 73 new york rangers season
|
https://en.wikipedia.org/wiki/1972%E2%80%9373_New_York_Rangers_season
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17324893-6.html.csv
|
count
|
the new york rangers played new york islanders three times .
|
{'scope': 'all', 'criterion': 'equal', 'value': 'new york islanders', 'result': '3', 'col': '3', 'subset': None}
|
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', 'new york islanders'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose opponent record fuzzily matches to new york islanders .', 'tostr': 'filter_eq { all_rows ; opponent ; new york islanders }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; opponent ; new york islanders } }', 'tointer': 'select the rows whose opponent record fuzzily matches to new york islanders . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; opponent ; new york islanders } } ; 3 } = true', 'tointer': 'select the rows whose opponent record fuzzily matches to new york islanders . the number of such rows is 3 .'}
|
eq { count { filter_eq { all_rows ; opponent ; new york islanders } } ; 3 } = true
|
select the rows whose opponent record fuzzily matches to new york islanders . 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, 'opponent_5': 5, 'new york islanders_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', 'opponent_5': 'opponent', 'new york islanders_6': 'new york islanders', '3_7': '3'}
|
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'opponent_5': [0], 'new york islanders_6': [0], '3_7': [2]}
|
['game', 'february', 'opponent', 'score', 'record']
|
[['52', '3', 'boston bruins', '7 - 3', '35 - 13 - 4'], ['53', '4', 'atlanta flames', '6 - 0', '36 - 13 - 4'], ['54', '7', 'new york islanders', '6 - 0', '37 - 13 - 4'], ['55', '10', 'new york islanders', '6 - 0', '38 - 13 - 4'], ['56', '11', 'montreal canadiens', '2 - 2', '38 - 13 - 5'], ['57', '14', 'montreal canadiens', '6 - 3', '38 - 14 - 5'], ['58', '15', 'buffalo sabres', '4 - 1', '38 - 15 - 5'], ['59', '18', 'new york islanders', '3 - 2', '39 - 15 - 5'], ['60', '21', 'los angeles kings', '4 - 3', '40 - 15 - 5'], ['61', '23', 'california golden seals', '5 - 3', '40 - 16 - 5'], ['62', '25', 'minnesota north stars', '6 - 5', '41 - 16 - 5'], ['63', '28', 'chicago black hawks', '3 - 3', '41 - 16 - 6']]
|
hy - vee triathlon
|
https://en.wikipedia.org/wiki/Hy-Vee_Triathlon
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12014430-2.html.csv
|
count
|
australia won the hy-vee triathlon 4 times between 2007 and 2013 .
|
{'scope': 'all', 'criterion': 'equal', 'value': 'australia', 'result': '4', 'col': '3', 'subset': None}
|
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'nation', 'australia'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose nation record fuzzily matches to australia .', 'tostr': 'filter_eq { all_rows ; nation ; australia }'}], 'result': '4', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; nation ; australia } }', 'tointer': 'select the rows whose nation record fuzzily matches to australia . the number of such rows is 4 .'}, '4'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; nation ; australia } } ; 4 } = true', 'tointer': 'select the rows whose nation record fuzzily matches to australia . the number of such rows is 4 .'}
|
eq { count { filter_eq { all_rows ; nation ; australia } } ; 4 } = true
|
select the rows whose nation record fuzzily matches to australia . 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, 'nation_5': 5, 'australia_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', 'nation_5': 'nation', 'australia_6': 'australia', '4_7': '4'}
|
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'nation_5': [0], 'australia_6': [0], '4_7': [2]}
|
['year', 'athlete', 'nation', 'time', 'location']
|
[['2007', 'bennett , laura laura bennett', 'united states', '2:04:3', 'des moines'], ['2008', 'snowsill , emma emma snowsill', 'australia', '2:03:15', 'west des moines'], ['2009', 'moffat , emma emma moffatt', 'australia', '1:59:46', 'west des moines'], ['2010', 'snowsill , emma emma snowsill ( 2 )', 'australia', '1:59.34', 'west des moines'], ['2011', 'nordén , lisa lisa nordén', 'sweden', '1:59:12', 'des moines'], ['2012', 'nordén , lisa lisa nordén ( 2 )', 'sweden', '2:01:59', 'des moines'], ['2013', 'moffat , emma emma moffatt ( 2 )', 'australia', '1:57:04', 'des moines']]
|
300 metre rifle prone
|
https://en.wikipedia.org/wiki/300_metre_rifle_prone
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18938143-1.html.csv
|
comparative
|
norbert sturny earned his second medal much more recently than malcolm cooper between the years of 1982 and 2006 .
|
{'row_1': '6', 'row_2': '2', 'col': '1', 'col_other': '3', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None}
|
{'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'gold', 'norbert sturny ( sui )'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose gold record fuzzily matches to norbert sturny ( sui ) .', 'tostr': 'filter_eq { all_rows ; gold ; norbert sturny ( sui ) }'}, 'year'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; gold ; norbert sturny ( sui ) } ; year }', 'tointer': 'select the rows whose gold record fuzzily matches to norbert sturny ( sui ) . take the year record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'gold', 'malcolm cooper ( gbr )'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose gold record fuzzily matches to malcolm cooper ( gbr ) .', 'tostr': 'filter_eq { all_rows ; gold ; malcolm cooper ( gbr ) }'}, 'year'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; gold ; malcolm cooper ( gbr ) } ; year }', 'tointer': 'select the rows whose gold record fuzzily matches to malcolm cooper ( gbr ) . take the year record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; gold ; norbert sturny ( sui ) } ; year } ; hop { filter_eq { all_rows ; gold ; malcolm cooper ( gbr ) } ; year } } = true', 'tointer': 'select the rows whose gold record fuzzily matches to norbert sturny ( sui ) . take the year record of this row . select the rows whose gold record fuzzily matches to malcolm cooper ( gbr ) . take the year record of this row . the first record is greater than the second record .'}
|
greater { hop { filter_eq { all_rows ; gold ; norbert sturny ( sui ) } ; year } ; hop { filter_eq { all_rows ; gold ; malcolm cooper ( gbr ) } ; year } } = true
|
select the rows whose gold record fuzzily matches to norbert sturny ( sui ) . take the year record of this row . select the rows whose gold record fuzzily matches to malcolm cooper ( gbr ) . take the year 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, 'gold_7': 7, 'norbert sturny ( sui )_8': 8, 'year_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'gold_11': 11, 'malcolm cooper ( gbr )_12': 12, 'year_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', 'gold_7': 'gold', 'norbert sturny ( sui )_8': 'norbert sturny ( sui )', 'year_9': 'year', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'gold_11': 'gold', 'malcolm cooper ( gbr )_12': 'malcolm cooper ( gbr )', 'year_13': 'year'}
|
{'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'gold_7': [0], 'norbert sturny ( sui )_8': [0], 'year_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'gold_11': [1], 'malcolm cooper ( gbr )_12': [1], 'year_13': [3]}
|
['year', 'place', 'gold', 'silver', 'bronze']
|
[['1982', 'caracas', 'victor daniltchenko ( urs )', 'malcolm cooper ( gbr )', 'ernest van de zande ( usa )'], ['1986', 'skoevde', 'malcolm cooper ( gbr )', 'pekka roeppaenen ( fin )', 'glenn dubis ( usa )'], ['1990', 'moscow', 'harald stenvaag ( nor )', 'norbert sturny ( sui )', 'thomas tamas ( usa )'], ['1994', 'tolmezzo', 'bernd ruecker ( ger )', 'petr kurka ( cze )', 'roger chassat ( fra )'], ['1998', 'zaragoza', 'bengt andersson ( swe )', 'tapio saynevirta ( fin )', 'glenn dubis ( usa )'], ['2002', 'lahti', 'norbert sturny ( sui )', 'thomas jerabek ( cze )', 'michael larsson ( swe )'], ['2006', 'zagreb', 'lubos opelka ( cze )', 'peter sidi ( hun )', 'rajmond debevec ( slo )']]
|
1971 isle of man tt
|
https://en.wikipedia.org/wiki/1971_Isle_of_Man_TT
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10638654-8.html.csv
|
comparative
|
dwood and dcoomber recorded a faster speed than dhawes and jpmann in the 1971 isle of man tt .
|
{'row_1': '5', 'row_2': '9', 'col': '4', 'col_other': '2', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None}
|
{'func': 'greater', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'rider', 'dwood / dcoomber'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose rider record fuzzily matches to dwood / dcoomber .', 'tostr': 'filter_eq { all_rows ; rider ; dwood / dcoomber }'}, 'speed'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; rider ; dwood / dcoomber } ; speed }', 'tointer': 'select the rows whose rider record fuzzily matches to dwood / dcoomber . take the speed record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'rider', 'dhawes / jpmann'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose rider record fuzzily matches to dhawes / jpmann .', 'tostr': 'filter_eq { all_rows ; rider ; dhawes / jpmann }'}, 'speed'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; rider ; dhawes / jpmann } ; speed }', 'tointer': 'select the rows whose rider record fuzzily matches to dhawes / jpmann . take the speed record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; rider ; dwood / dcoomber } ; speed } ; hop { filter_eq { all_rows ; rider ; dhawes / jpmann } ; speed } } = true', 'tointer': 'select the rows whose rider record fuzzily matches to dwood / dcoomber . take the speed record of this row . select the rows whose rider record fuzzily matches to dhawes / jpmann . take the speed record of this row . the first record is greater than the second record .'}
|
greater { hop { filter_eq { all_rows ; rider ; dwood / dcoomber } ; speed } ; hop { filter_eq { all_rows ; rider ; dhawes / jpmann } ; speed } } = true
|
select the rows whose rider record fuzzily matches to dwood / dcoomber . take the speed record of this row . select the rows whose rider record fuzzily matches to dhawes / jpmann . take the speed 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, 'rider_7': 7, 'dwood / dcoomber_8': 8, 'speed_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'rider_11': 11, 'dhawes / jpmann_12': 12, 'speed_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', 'rider_7': 'rider', 'dwood / dcoomber_8': 'dwood / dcoomber', 'speed_9': 'speed', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'rider_11': 'rider', 'dhawes / jpmann_12': 'dhawes / jpmann', 'speed_13': 'speed'}
|
{'greater_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'rider_7': [0], 'dwood / dcoomber_8': [0], 'speed_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'rider_11': [1], 'dhawes / jpmann_12': [1], 'speed_13': [3]}
|
['rank', 'rider', 'team', 'speed', 'time']
|
[['1', 'georg auerbacher / hhahn', 'bmw', '86.86 mph', '1.18.12.0'], ['2', 'ajsamson / dajose', 'triumph', '82.50 mph', '1.22.20.2'], ['3', 'rwilliamson / jmcpherson', 'weslake', '82.25 mph', '1.23.50.0'], ['4', 'rwoodhouse / dwoodhouse', 'honda', '81.91 mph', '1.22.55.0'], ['5', 'dwood / dcoomber', 'norton', '81.19 mph', '1.23.39.8'], ['6', 'dplummer / mbrett', 'triumph', '80.77 mph', '1.24.05.6'], ['7', 'bcurrie / mscott', 'triumph', '80.60 mph', '1.24.16.2'], ['8', 'mpotter / pjburleigh', 'bsa', '80.18 mph', '1.24.43.4'], ['9', 'dhawes / jpmann', 'seeley', '80.09 mph', '1.24.48.6'], ['10', 'amethersill / mmitchinson', 'ams', '79.52 mph', '1.25.24.8']]
|
atlanta falcons draft history
|
https://en.wikipedia.org/wiki/Atlanta_Falcons_draft_history
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15198842-48.html.csv
|
majority
|
most of the atlanta falcons ' draft picks had an overall score over 100 .
|
{'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'greater_than', 'value': '100', 'subset': None}
|
{'func': 'most_greater', 'args': ['all_rows', 'overall', '100'], 'result': True, 'ind': 0, 'tointer': 'for the overall records of all rows , most of them are greater than 100 .', 'tostr': 'most_greater { all_rows ; overall ; 100 } = true'}
|
most_greater { all_rows ; overall ; 100 } = true
|
for the overall records of all rows , most of them are greater than 100 .
|
1
|
1
|
{'most_greater_0': 0, 'result_1': 1, 'all_rows_2': 2, 'overall_3': 3, '100_4': 4}
|
{'most_greater_0': 'most_greater', 'result_1': 'true', 'all_rows_2': 'all_rows', 'overall_3': 'overall', '100_4': '100'}
|
{'most_greater_0': [1], 'result_1': [], 'all_rows_2': [0], 'overall_3': [0], '100_4': [0]}
|
['round', 'pick', 'overall', 'name', 'position', 'college']
|
[['1', '22', '22', 'desmond trufant', 'cornerback', 'washington'], ['2', '28', '60', 'robert alford', 'cornerback', 'southeastern louisiana'], ['4', '30', '127', 'malliciah goodman', 'defensive end', 'clemson'], ['4', '36', '133', 'levine toilolo', 'tight end', 'stanford'], ['5', '20', '153', 'stansly maponga', 'defensive end', 'tcu'], ['7', '37', '243', 'kemal ishmael', 'safety', 'central florida'], ['7', '38', '244', 'zeke motta', 'safety', 'notre dame'], ['7', '43', '249', 'sean renfree', 'quarterback', 'duke']]
|
fiba eurobasket 2007 squads
|
https://en.wikipedia.org/wiki/FIBA_EuroBasket_2007_squads
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-12962773-1.html.csv
|
majority
|
the majority of the players were born in the 1980 's .
|
{'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'greater_than_eq', 'value': '1980', 'subset': None}
|
{'func': 'most_greater_eq', 'args': ['all_rows', 'year born', '1980'], 'result': True, 'ind': 0, 'tointer': 'for the year born records of all rows , most of them are greater than or equal to 1980 .', 'tostr': 'most_greater_eq { all_rows ; year born ; 1980 } = true'}
|
most_greater_eq { all_rows ; year born ; 1980 } = true
|
for the year born records of all rows , most of them are greater than or equal to 1980 .
|
1
|
1
|
{'most_greater_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'year born_3': 3, '1980_4': 4}
|
{'most_greater_eq_0': 'most_greater_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'year born_3': 'year born', '1980_4': '1980'}
|
{'most_greater_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'year born_3': [0], '1980_4': [0]}
|
['no', 'player', 'height', 'position', 'year born', 'current club']
|
[['4', 'theodoros papaloukas', '2.00', 'guard', '1977', 'cska moscow'], ['5', 'ioannis bourousis', '2.13', 'center', '1983', 'olympiacos'], ['6', 'nikolaos zisis', '1.95', 'guard', '1983', 'cska moscow'], ['7', 'vasileios spanoulis', '1.92', 'guard', '1982', 'panathinaikos'], ['8', 'panagiotis vasilopoulos', '2.01', 'forward', '1984', 'olympiacos'], ['9', 'michalis pelekanos', '1.98', 'forward', '1981', 'real madrid'], ['10', 'nikolaos chatzivrettas', '1.95', 'guard', '1977', 'panathinaikos'], ['11', 'dimosthenis dikoudis', '2.06', 'forward', '1977', 'panathinaikos'], ['12', 'konstantinos tsartsaris', '2.09', 'center', '1979', 'panathinaikos'], ['13', 'dimitris diamantidis', '1.96', 'guard', '1980', 'panathinaikos'], ['14', 'lazaros papadopoulos', '2.10', 'center', '1980', 'real madrid']]
|
swatch fivb world tour 2007
|
https://en.wikipedia.org/wiki/Swatch_FIVB_World_Tour_2007
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18314203-3.html.csv
|
comparative
|
in the swatch fivb world tour 2007 germany won more silver medals than the united states .
|
{'row_1': '7', 'row_2': '2', 'col': '4', 'col_other': '2', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None}
|
{'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'nation', 'germany'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose nation record fuzzily matches to germany .', 'tostr': 'filter_eq { all_rows ; nation ; germany }'}, 'silver'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; nation ; germany } ; silver }', 'tointer': 'select the rows whose nation record fuzzily matches to germany . take the silver record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'nation', 'united states'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose nation record fuzzily matches to united states .', 'tostr': 'filter_eq { all_rows ; nation ; united states }'}, 'silver'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; nation ; united states } ; silver }', 'tointer': 'select the rows whose nation record fuzzily matches to united states . take the silver record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; nation ; germany } ; silver } ; hop { filter_eq { all_rows ; nation ; united states } ; silver } } = true', 'tointer': 'select the rows whose nation record fuzzily matches to germany . take the silver record of this row . select the rows whose nation record fuzzily matches to united states . take the silver record of this row . the first record is greater than the second record .'}
|
greater { hop { filter_eq { all_rows ; nation ; germany } ; silver } ; hop { filter_eq { all_rows ; nation ; united states } ; silver } } = true
|
select the rows whose nation record fuzzily matches to germany . take the silver record of this row . select the rows whose nation record fuzzily matches to united states . take the silver 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, 'nation_7': 7, 'germany_8': 8, 'silver_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'nation_11': 11, 'united states_12': 12, 'silver_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', 'nation_7': 'nation', 'germany_8': 'germany', 'silver_9': 'silver', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'nation_11': 'nation', 'united states_12': 'united states', 'silver_13': 'silver'}
|
{'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'nation_7': [0], 'germany_8': [0], 'silver_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'nation_11': [1], 'united states_12': [1], 'silver_13': [3]}
|
['rank', 'nation', 'gold', 'silver', 'bronze', 'total']
|
[['1', 'brazil', '21', '9', '12', '42'], ['2', 'united states', '9', '3', '6', '18'], ['3', 'china', '1', '9', '8', '18'], ['4', 'australia', '1', '1', '1', '3'], ['4', 'netherlands', '1', '1', '1', '3'], ['6', 'estonia', '1', '0', '0', '1'], ['7', 'germany', '0', '5', '1', '6'], ['8', 'russia', '0', '2', '3', '5'], ['9', 'argentina', '0', '2', '0', '2'], ['10', 'switzerland', '0', '1', '1', '2'], ['11', 'norway', '0', '1', '0', '1'], ['12', 'austria', '0', '0', '1', '1']]
|
berlusconi ii cabinet
|
https://en.wikipedia.org/wiki/Berlusconi_II_Cabinet
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16824962-2.html.csv
|
comparative
|
rocco buttiglione took office in the berlusconi ii cabinet earlier than mario baccini .
|
{'row_1': '1', 'row_2': '10', 'col': '3', 'col_other': '2', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None}
|
{'func': 'less', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'minister', 'rocco buttiglione'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose minister record fuzzily matches to rocco buttiglione .', 'tostr': 'filter_eq { all_rows ; minister ; rocco buttiglione }'}, 'took office'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; minister ; rocco buttiglione } ; took office }', 'tointer': 'select the rows whose minister record fuzzily matches to rocco buttiglione . take the took office record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'minister', 'mario baccini'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose minister record fuzzily matches to mario baccini .', 'tostr': 'filter_eq { all_rows ; minister ; mario baccini }'}, 'took office'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; minister ; mario baccini } ; took office }', 'tointer': 'select the rows whose minister record fuzzily matches to mario baccini . take the took office record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; minister ; rocco buttiglione } ; took office } ; hop { filter_eq { all_rows ; minister ; mario baccini } ; took office } } = true', 'tointer': 'select the rows whose minister record fuzzily matches to rocco buttiglione . take the took office record of this row . select the rows whose minister record fuzzily matches to mario baccini . take the took office record of this row . the first record is less than the second record .'}
|
less { hop { filter_eq { all_rows ; minister ; rocco buttiglione } ; took office } ; hop { filter_eq { all_rows ; minister ; mario baccini } ; took office } } = true
|
select the rows whose minister record fuzzily matches to rocco buttiglione . take the took office record of this row . select the rows whose minister record fuzzily matches to mario baccini . take the took office record of this row . the first record is less than the second record .
|
5
|
5
|
{'less_4': 4, 'result_5': 5, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'minister_7': 7, 'rocco buttiglione_8': 8, 'took office_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'minister_11': 11, 'mario baccini_12': 12, 'took office_13': 13}
|
{'less_4': 'less', 'result_5': 'true', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'minister_7': 'minister', 'rocco buttiglione_8': 'rocco buttiglione', 'took office_9': 'took office', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'minister_11': 'minister', 'mario baccini_12': 'mario baccini', 'took office_13': 'took office'}
|
{'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'minister_7': [0], 'rocco buttiglione_8': [0], 'took office_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'minister_11': [1], 'mario baccini_12': [1], 'took office_13': [3]}
|
['portfolio', 'minister', 'took office', 'left office', 'party']
|
[['minister european affairs', 'rocco buttiglione', '11 june 2001', '23 april 2005', 'udc'], ['minister of reforms and devolutions', 'umberto bossi', '11 june 2001', '16 july 2004', 'lega nord'], ['minister of reforms and devolutions', 'roberto calderoli', '16 july 2004', '23 april 2005', 'lega nord'], ['minister of innovations', 'lucio stanca', '11 june 2001', '23 april 2005', 'forza italia'], ['minister for regional affairs', 'enrico la loggia', '11 june 2001', '23 april 2005', 'forza italia'], ['minister for platform accomplishment', 'claudio scajola', '28 august 2003', '23 april 2005', 'forza italia'], ['minister of equal opportunities', 'stefania prestigiacomo', '11 june 2001', '23 april 2005', 'forza italia'], ['minister of pubblic administration', 'franco frattini', '11 june 2001', '14 november 2002', 'forza italia'], ['minister of pubblic administration', 'luigi mazzella', '14 november 2002', '3 december 2004', 'independent'], ['minister of pubblic administration', 'mario baccini', '3 december 2004', '23 april 2005', 'udc'], ['minister of italians in the world', 'mirko tremaglia', '11 june 2001', '23 april 2005', 'an']]
|
1973 u.s. open ( golf )
|
https://en.wikipedia.org/wiki/1973_U.S._Open_%28golf%29
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17245540-2.html.csv
|
count
|
of the players in the 1973 us open , five came from the united states .
|
{'scope': 'all', 'criterion': 'equal', 'value': 'united states', 'result': '5', 'col': '2', 'subset': None}
|
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'united states'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose country record fuzzily matches to united states .', 'tostr': 'filter_eq { all_rows ; country ; united states }'}], 'result': '5', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; country ; united states } }', 'tointer': 'select the rows whose country record fuzzily matches to united states . the number of such rows is 5 .'}, '5'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; country ; united states } } ; 5 } = true', 'tointer': 'select the rows whose country record fuzzily matches to united states . the number of such rows is 5 .'}
|
eq { count { filter_eq { all_rows ; country ; united states } } ; 5 } = true
|
select the rows whose country record fuzzily matches to united states . the number of such rows is 5 .
|
3
|
3
|
{'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'country_5': 5, 'united states_6': 6, '5_7': 7}
|
{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'country_5': 'country', 'united states_6': 'united states', '5_7': '5'}
|
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'country_5': [0], 'united states_6': [0], '5_7': [2]}
|
['player', 'country', 'year ( s ) won', 'total', 'to par', 'finish']
|
[['jack nicklaus', 'united states', '1962 , 1967 , 1972', '282', '- 2', 't4'], ['arnold palmer', 'united states', '1960', '282', '- 2', 't4'], ['lee trevino', 'united states', '1968 , 1971', '282', '- 2', 't4'], ['julius boros', 'united states', '1952 , 1963', '283', '- 1', 't7'], ['gary player', 'south africa', '1965', '287', '+ 3', '12'], ['gene littler', 'united states', '1961', '291', '+ 7', 't18'], ['tony jacklin', 'england', '1970', '300', '+ 16', 't52']]
|
duchess of nemours
|
https://en.wikipedia.org/wiki/Duchess_of_Nemours
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1825009-5.html.csv
|
unique
|
louise marie adelaide de bourbon was the only duchess who lost her title due to her husbands execution .
|
{'scope': 'all', 'row': '5', 'col': '5', 'col_other': '1', 'criterion': 'equal', 'value': "husband 's execution", 'subset': None}
|
{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'ceased to be duchess', "husband 's execution"], 'result': None, 'ind': 0, 'tointer': "select the rows whose ceased to be duchess record fuzzily matches to husband 's execution .", 'tostr': "filter_eq { all_rows ; ceased to be duchess ; husband 's execution }"}], 'result': True, 'ind': 1, 'tostr': "only { filter_eq { all_rows ; ceased to be duchess ; husband 's execution } }", 'tointer': "select the rows whose ceased to be duchess record fuzzily matches to husband 's execution . there is only one such row in the table ."}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'ceased to be duchess', "husband 's execution"], 'result': None, 'ind': 0, 'tointer': "select the rows whose ceased to be duchess record fuzzily matches to husband 's execution .", 'tostr': "filter_eq { all_rows ; ceased to be duchess ; husband 's execution }"}, 'name'], 'result': 'louise marie adélaïde de bourbon', 'ind': 2, 'tostr': "hop { filter_eq { all_rows ; ceased to be duchess ; husband 's execution } ; name }"}, 'louise marie adélaïde de bourbon'], 'result': True, 'ind': 3, 'tostr': "eq { hop { filter_eq { all_rows ; ceased to be duchess ; husband 's execution } ; name } ; louise marie adélaïde de bourbon }", 'tointer': 'the name record of this unqiue row is louise marie adélaïde de bourbon .'}], 'result': True, 'ind': 4, 'tostr': "and { only { filter_eq { all_rows ; ceased to be duchess ; husband 's execution } } ; eq { hop { filter_eq { all_rows ; ceased to be duchess ; husband 's execution } ; name } ; louise marie adélaïde de bourbon } } = true", 'tointer': "select the rows whose ceased to be duchess record fuzzily matches to husband 's execution . there is only one such row in the table . the name record of this unqiue row is louise marie adélaïde de bourbon ."}
|
and { only { filter_eq { all_rows ; ceased to be duchess ; husband 's execution } } ; eq { hop { filter_eq { all_rows ; ceased to be duchess ; husband 's execution } ; name } ; louise marie adélaïde de bourbon } } = true
|
select the rows whose ceased to be duchess record fuzzily matches to husband 's execution . there is only one such row in the table . the name record of this unqiue row is louise marie adélaïde de bourbon .
|
6
|
5
|
{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'ceased to be duchess_7': 7, "husband 's execution_8": 8, 'str_eq_3': 3, 'str_hop_2': 2, 'name_9': 9, 'louise marie adélaïde de bourbon_10': 10}
|
{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'ceased to be duchess_7': 'ceased to be duchess', "husband 's execution_8": "husband 's execution", 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'name_9': 'name', 'louise marie adélaïde de bourbon_10': 'louise marie adélaïde de bourbon'}
|
{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'ceased to be duchess_7': [0], "husband 's execution_8": [0], 'str_eq_3': [4], 'str_hop_2': [3], 'name_9': [2], 'louise marie adélaïde de bourbon_10': [3]}
|
['name', 'birth', 'marriage', 'became duchess', 'ceased to be duchess', 'death', 'spouse']
|
[['elizabeth charlotte of the palatinate', '27 may 1652', '16 november 1671', '1672 peerage awarded to husband', "9 june 1701 husband 's death", '9 december 1722', 'philippe , duke of orléans'], ['françoise marie de bourbon , légitimée de france', '25 may 1677', '18 february 1692', "9 june 1701 husband 's accession", "2 december 1723 husband 's death", '1 february 1749', 'philippe , duke of orléans'], ['margravine johanna of baden - baden', '10 november 1704', '13 july 1724', '13 july 1724', '8 july 1726', '8 july 1726', 'louis , duke of orléans'], ['louise henriette de bourbon', '20 june 1726', '17 december 1743', "4 february 1752 husband 's accession", '9 february 1759', '9 february 1759', 'louis philippe , duke of orléans'], ['louise marie adélaïde de bourbon', '13 march 1753', '8 may 1768', "18 november 1785 husband 's accession", "6 november 1793 husband 's execution", '23 june 1821', 'philippe , duke of orléans'], ['maria amalia of naples and sicily', '26 april 1782', '25 november 1809', '25 november 1809', '9 august 1830 became queen consort', '24 march 1866', 'louis philippe i'], ['victoria of saxe - coburg and gotha', '14 february 1822', '27 april 1840', '27 april 1840', '10 december 1857', '10 december 1857', 'prince louis'], ['name', 'birth', 'marriage', 'became duchess', 'ceased to be duchess', 'death', 'spouse']]
|
list of artists who reached number one on the french singles chart
|
https://en.wikipedia.org/wiki/List_of_artists_who_reached_number_one_on_the_French_Singles_Chart
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27441210-17.html.csv
|
unique
|
for artists who reached number one on the french singles chart , when the country is france , the only single that spent 8 weeks at number 1 is n'importe quoi .
|
{'scope': 'subset', 'row': '2', 'col': '5', 'col_other': '3', 'criterion': 'equal', 'value': '8', 'subset': {'col': '2', 'criterion': 'equal', 'value': 'france'}}
|
{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'france'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; country ; france }', 'tointer': 'select the rows whose country record fuzzily matches to france .'}, 'weeks at 1', '8'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose country record fuzzily matches to france . among these rows , select the rows whose weeks at 1 record is equal to 8 .', 'tostr': 'filter_eq { filter_eq { all_rows ; country ; france } ; weeks at 1 ; 8 }'}], 'result': True, 'ind': 2, 'tostr': 'only { filter_eq { filter_eq { all_rows ; country ; france } ; weeks at 1 ; 8 } }', 'tointer': 'select the rows whose country record fuzzily matches to france . among these rows , select the rows whose weeks at 1 record is equal to 8 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'france'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; country ; france }', 'tointer': 'select the rows whose country record fuzzily matches to france .'}, 'weeks at 1', '8'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose country record fuzzily matches to france . among these rows , select the rows whose weeks at 1 record is equal to 8 .', 'tostr': 'filter_eq { filter_eq { all_rows ; country ; france } ; weeks at 1 ; 8 }'}, 'number - one single ( s )'], 'result': "n'importe quoi", 'ind': 3, 'tostr': 'hop { filter_eq { filter_eq { all_rows ; country ; france } ; weeks at 1 ; 8 } ; number - one single ( s ) }'}, "n'importe quoi"], 'result': True, 'ind': 4, 'tostr': "eq { hop { filter_eq { filter_eq { all_rows ; country ; france } ; weeks at 1 ; 8 } ; number - one single ( s ) } ; n'importe quoi }", 'tointer': "the number - one single ( s ) record of this unqiue row is n'importe quoi ."}], 'result': True, 'ind': 5, 'tostr': "and { only { filter_eq { filter_eq { all_rows ; country ; france } ; weeks at 1 ; 8 } } ; eq { hop { filter_eq { filter_eq { all_rows ; country ; france } ; weeks at 1 ; 8 } ; number - one single ( s ) } ; n'importe quoi } } = true", 'tointer': "select the rows whose country record fuzzily matches to france . among these rows , select the rows whose weeks at 1 record is equal to 8 . there is only one such row in the table . the number - one single ( s ) record of this unqiue row is n'importe quoi ."}
|
and { only { filter_eq { filter_eq { all_rows ; country ; france } ; weeks at 1 ; 8 } } ; eq { hop { filter_eq { filter_eq { all_rows ; country ; france } ; weeks at 1 ; 8 } ; number - one single ( s ) } ; n'importe quoi } } = true
|
select the rows whose country record fuzzily matches to france . among these rows , select the rows whose weeks at 1 record is equal to 8 . there is only one such row in the table . the number - one single ( s ) record of this unqiue row is n'importe quoi .
|
8
|
6
|
{'and_5': 5, 'result_6': 6, 'only_2': 2, 'filter_eq_1': 1, 'filter_str_eq_0': 0, 'all_rows_7': 7, 'country_8': 8, 'france_9': 9, 'weeks at 1_10': 10, '8_11': 11, 'str_eq_4': 4, 'str_hop_3': 3, 'number - one single (s)_12': 12, "n'importe quoi_13": 13}
|
{'and_5': 'and', 'result_6': 'true', 'only_2': 'only', 'filter_eq_1': 'filter_eq', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_7': 'all_rows', 'country_8': 'country', 'france_9': 'france', 'weeks at 1_10': 'weeks at 1', '8_11': '8', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'number - one single (s)_12': 'number - one single ( s )', "n'importe quoi_13": "n'importe quoi"}
|
{'and_5': [6], 'result_6': [], 'only_2': [5], 'filter_eq_1': [2, 3], 'filter_str_eq_0': [1], 'all_rows_7': [0], 'country_8': [0], 'france_9': [0], 'weeks at 1_10': [1], '8_11': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'number - one single (s)_12': [3], "n'importe quoi_13": [4]}
|
['artist', 'country', 'number - one single ( s )', 'year', 'weeks at 1', 'straight to 1']
|
[['paco', 'viet nam', 'amor de mis amores', '1988', '5', 'no'], ['pagny , florent', 'france', "n'importe quoi", '1988', '8', 'no'], ['pagny , florent', 'france', 'savoir aimer', '1997', '9', 'no'], ['pagny , florent', 'france', 'ma liberté de penser', '2003', '6', 'no'], ['pakito', 'france', 'living on video', '2004', '4', 'no'], ['paradis , vanessa', 'france', 'joe le taxi', '1987', '11', 'no'], ['parker jr , ray', 'united states', 'ghostbusters', '1984', '5', 'no'], ['parker , tony', 'france', 'balance - toi', '2007', '1', 'yes'], ['passi', 'france', 'laisse parler les gens 1', '2003', '3', 'no'], ['patti , guesch', 'france', 'étienne', '1987', '5', 'no'], ["pep 's", 'france', 'liberta', '2009', '2', 'yes'], ['peter & sloane', 'france', 'besoin de rien , envie de toi', '1984', '9', 'no'], ['pietri , julie', 'france', 'ève lève - toi', '1986', '1', 'no'], ['pigloo', 'france', 'le papa pingouin', '2006', '3', 'no'], ['pitbull', 'united states', 'i know you want me ( calle ocho )', '2009', '8', 'no'], ['plage , la', 'france', 'coup de boule', '2006', '3', 'no'], ['m pokora', 'france', 'dangerous', '2008', '1', 'yes'], ['pow wow', 'france', 'le chat', '1992', '7', 'no'], ['product g & b , the', 'united states', 'maria maria 1', '2000', '4', 'no']]
|
weltklang
|
https://en.wikipedia.org/wiki/Weltklang
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18948956-2.html.csv
|
comparative
|
of weltklang 's tracks , mono 45upm - romance adieu ( weltklang remix ) was released earlier than kinder aus asbest - hey engel ( weltklang remix ) .
|
{'row_1': '1', 'row_2': '6', 'col': '5', 'col_other': '2', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None}
|
{'func': 'less', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'track', 'mono 45upm - romance adieu ( weltklang remix )'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose track record fuzzily matches to mono 45upm - romance adieu ( weltklang remix ) .', 'tostr': 'filter_eq { all_rows ; track ; mono 45upm - romance adieu ( weltklang remix ) }'}, 'year'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; track ; mono 45upm - romance adieu ( weltklang remix ) } ; year }', 'tointer': 'select the rows whose track record fuzzily matches to mono 45upm - romance adieu ( weltklang remix ) . take the year record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'track', 'kinder aus asbest - hey engel ( weltklang remix )'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose track record fuzzily matches to kinder aus asbest - hey engel ( weltklang remix ) .', 'tostr': 'filter_eq { all_rows ; track ; kinder aus asbest - hey engel ( weltklang remix ) }'}, 'year'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; track ; kinder aus asbest - hey engel ( weltklang remix ) } ; year }', 'tointer': 'select the rows whose track record fuzzily matches to kinder aus asbest - hey engel ( weltklang remix ) . take the year record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; track ; mono 45upm - romance adieu ( weltklang remix ) } ; year } ; hop { filter_eq { all_rows ; track ; kinder aus asbest - hey engel ( weltklang remix ) } ; year } } = true', 'tointer': 'select the rows whose track record fuzzily matches to mono 45upm - romance adieu ( weltklang remix ) . take the year record of this row . select the rows whose track record fuzzily matches to kinder aus asbest - hey engel ( weltklang remix ) . take the year record of this row . the first record is less than the second record .'}
|
less { hop { filter_eq { all_rows ; track ; mono 45upm - romance adieu ( weltklang remix ) } ; year } ; hop { filter_eq { all_rows ; track ; kinder aus asbest - hey engel ( weltklang remix ) } ; year } } = true
|
select the rows whose track record fuzzily matches to mono 45upm - romance adieu ( weltklang remix ) . take the year record of this row . select the rows whose track record fuzzily matches to kinder aus asbest - hey engel ( weltklang remix ) . take the year record of this row . the first record is less than the second record .
|
5
|
5
|
{'less_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'track_7': 7, 'mono 45upm - romance adieu (weltklang remix)_8': 8, 'year_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'track_11': 11, 'kinder aus asbest - hey engel (weltklang remix)_12': 12, 'year_13': 13}
|
{'less_4': 'less', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'track_7': 'track', 'mono 45upm - romance adieu (weltklang remix)_8': 'mono 45upm - romance adieu ( weltklang remix )', 'year_9': 'year', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'track_11': 'track', 'kinder aus asbest - hey engel (weltklang remix)_12': 'kinder aus asbest - hey engel ( weltklang remix )', 'year_13': 'year'}
|
{'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'track_7': [0], 'mono 45upm - romance adieu (weltklang remix)_8': [0], 'year_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'track_11': [1], 'kinder aus asbest - hey engel (weltklang remix)_12': [1], 'year_13': [3]}
|
['release', 'track', 'format', 'label', 'year']
|
[['liebesgrüsse aus ost - berlin', 'mono 45upm - romance adieu ( weltklang remix )', '12', 'exil - system', '2006'], ['a dark wave from the black sea', 'aeronautica - rocket bomb ( weltklang remix )', 'cd', 'exil - system', '2007'], ['the greater key', 'asmodeus x - typhoon ( weltklang remix )', 'cd', 'latex records', '2008'], ['classic electro', 'p1 / e - 49 second dance ( weltklang remix )', 'cd', 'electro emotions', '2008'], ['classic electro', 'mono 45upm - romance adieu ( weltklang remix )', 'cd', 'electro emotions', '2008'], ['classic electro', 'kinder aus asbest - hey engel ( weltklang remix )', 'cd', 'electro emotions', '2008'], ['classic electro', 'sonnenbrandt - entweder / oder ( weltklang remix )', 'cd', 'electro emotions', '2008']]
|
1957 argentine grand prix
|
https://en.wikipedia.org/wiki/1957_Argentine_Grand_Prix
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1122148-1.html.csv
|
superlative
|
in the 1957 argentine grand prix , when the constructor was a maserati , the highest grid is luigi piotti .
|
{'scope': 'subset', 'col_superlative': '5', 'row_superlative': '10', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1,2', 'subset': {'col': '2', 'criterion': 'equal', 'value': 'maserati'}}
|
{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'constructor', 'maserati'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; constructor ; maserati }', 'tointer': 'select the rows whose constructor record fuzzily matches to maserati .'}, 'grid'], 'result': None, 'ind': 1, 'tostr': 'argmax { filter_eq { all_rows ; constructor ; maserati } ; grid }'}, 'driver'], 'result': 'luigi piotti', 'ind': 2, 'tostr': 'hop { argmax { filter_eq { all_rows ; constructor ; maserati } ; grid } ; driver }'}, 'luigi piotti'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { argmax { filter_eq { all_rows ; constructor ; maserati } ; grid } ; driver } ; luigi piotti } = true', 'tointer': 'select the rows whose constructor record fuzzily matches to maserati . select the row whose grid record of these rows is maximum . the driver record of this row is luigi piotti .'}
|
eq { hop { argmax { filter_eq { all_rows ; constructor ; maserati } ; grid } ; driver } ; luigi piotti } = true
|
select the rows whose constructor record fuzzily matches to maserati . select the row whose grid record of these rows is maximum . the driver record of this row is luigi piotti .
|
4
|
4
|
{'str_eq_3': 3, 'result_4': 4, 'str_hop_2': 2, 'argmax_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'constructor_6': 6, 'maserati_7': 7, 'grid_8': 8, 'driver_9': 9, 'luigi piotti_10': 10}
|
{'str_eq_3': 'str_eq', 'result_4': 'true', 'str_hop_2': 'str_hop', 'argmax_1': 'argmax', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'constructor_6': 'constructor', 'maserati_7': 'maserati', 'grid_8': 'grid', 'driver_9': 'driver', 'luigi piotti_10': 'luigi piotti'}
|
{'str_eq_3': [4], 'result_4': [], 'str_hop_2': [3], 'argmax_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'constructor_6': [0], 'maserati_7': [0], 'grid_8': [1], 'driver_9': [2], 'luigi piotti_10': [3]}
|
['driver', 'constructor', 'laps', 'time / retired', 'grid']
|
[['juan manuel fangio', 'maserati', '100', '3:00:55.9', '2'], ['jean behra', 'maserati', '100', '+ 18.3 secs', '3'], ['carlos menditeguy', 'maserati', '99', '+ 1 lap', '8'], ['harry schell', 'maserati', '98', '+ 2 laps', '9'], ['alfonso de portago josé froilán gonzález', 'ferrari', '98', '+ 2 laps', '10'], ['cesare perdisa peter collins wolfgang von trips', 'ferrari', '98', '+ 2 laps', '11'], ['jo bonnier', 'maserati', '95', '+ 5 laps', '13'], ['stirling moss', 'maserati', '93', '+ 7 laps', '1'], ['alessandro de tomaso', 'ferrari', '91', '+ 9 laps', '12'], ['luigi piotti', 'maserati', '90', '+ 10 laps', '14'], ['eugenio castellotti', 'ferrari', '75', 'wheel', '4'], ['mike hawthorn', 'ferrari', '35', 'clutch', '7'], ['luigi musso', 'ferrari', '31', 'clutch', '6'], ['peter collins', 'ferrari', '26', 'clutch', '5']]
|
karrie webb
|
https://en.wikipedia.org/wiki/Karrie_Webb
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1036386-2.html.csv
|
unique
|
of the championships played by karrie webb , only the us women 's open had a margin of 8 strokes .
|
{'scope': 'all', 'row': '5', 'col': '4', 'col_other': '2', 'criterion': 'equal', 'value': '8 strokes', 'subset': None}
|
{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'margin', '8 strokes'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose margin record fuzzily matches to 8 strokes .', 'tostr': 'filter_eq { all_rows ; margin ; 8 strokes }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; margin ; 8 strokes } }', 'tointer': 'select the rows whose margin record fuzzily matches to 8 strokes . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'margin', '8 strokes'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose margin record fuzzily matches to 8 strokes .', 'tostr': 'filter_eq { all_rows ; margin ; 8 strokes }'}, 'championship'], 'result': "us women 's open", 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; margin ; 8 strokes } ; championship }'}, "us women 's open"], 'result': True, 'ind': 3, 'tostr': "eq { hop { filter_eq { all_rows ; margin ; 8 strokes } ; championship } ; us women 's open }", 'tointer': "the championship record of this unqiue row is us women 's open ."}], 'result': True, 'ind': 4, 'tostr': "and { only { filter_eq { all_rows ; margin ; 8 strokes } } ; eq { hop { filter_eq { all_rows ; margin ; 8 strokes } ; championship } ; us women 's open } } = true", 'tointer': "select the rows whose margin record fuzzily matches to 8 strokes . there is only one such row in the table . the championship record of this unqiue row is us women 's open ."}
|
and { only { filter_eq { all_rows ; margin ; 8 strokes } } ; eq { hop { filter_eq { all_rows ; margin ; 8 strokes } ; championship } ; us women 's open } } = true
|
select the rows whose margin record fuzzily matches to 8 strokes . there is only one such row in the table . the championship record of this unqiue row is us women 's open .
|
6
|
5
|
{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'margin_7': 7, '8 strokes_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'championship_9': 9, "us women 's open_10": 10}
|
{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'margin_7': 'margin', '8 strokes_8': '8 strokes', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'championship_9': 'championship', "us women 's open_10": "us women 's open"}
|
{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'margin_7': [0], '8 strokes_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'championship_9': [2], "us women 's open_10": [3]}
|
['year', 'championship', 'winning score', 'margin', 'runner ( s ) - up']
|
[['1999', 'du maurier classic', '11 ( 73 + 72 + 66 + 66 = 277 )', '2 strokes', 'laura davies'], ['2000', 'nabisco championship', '14 ( 67 + 70 + 67 + 70 = 274 )', '10 strokes', 'dottie pepper'], ['2000', "us women 's open", '6 ( 69 + 72 + 68 + 73 = 282 )', '5 strokes', 'cristie kerr , meg mallon'], ['2001', "mcdonald 's lpga championship", '14 ( 67 + 64 + 70 + 69 = 270 )', '2 strokes', 'laura diaz'], ['2001', "us women 's open", '7 ( 70 + 65 + 69 + 69 = 273 )', '8 strokes', 'se ri pak'], ['2002', "weetabix women 's british open", '15 ( 66 + 71 + 70 + 66 = 273 )', '2 strokes', 'michelle ellis , paula martí'], ['2006', 'kraft nabisco championship', '9 ( 70 + 68 + 76 + 65 = 279 )', 'playoff 1', 'lorena ochoa']]
|
2007 icc world twenty20 statistics
|
https://en.wikipedia.org/wiki/2007_ICC_World_Twenty20_statistics
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13219504-9.html.csv
|
ordinal
|
herschelle gibbs / justin kemp had the 3rd highest number of runs during the 2007 icc world twenty20 championship .
|
{'row': '3', 'col': '1', 'order': '3', 'col_other': '3', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None}
|
{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'runs ( balls )', '3'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; runs ( balls ) ; 3 }'}, 'partnerships'], 'result': 'herschelle gibbs / justin kemp', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; runs ( balls ) ; 3 } ; partnerships }'}, 'herschelle gibbs / justin kemp'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; runs ( balls ) ; 3 } ; partnerships } ; herschelle gibbs / justin kemp } = true', 'tointer': 'select the row whose runs ( balls ) record of all rows is 3rd maximum . the partnerships record of this row is herschelle gibbs / justin kemp .'}
|
eq { hop { nth_argmax { all_rows ; runs ( balls ) ; 3 } ; partnerships } ; herschelle gibbs / justin kemp } = true
|
select the row whose runs ( balls ) record of all rows is 3rd maximum . the partnerships record of this row is herschelle gibbs / justin kemp .
|
3
|
3
|
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'runs (balls)_5': 5, '3_6': 6, 'partnerships_7': 7, 'herschelle gibbs / justin kemp_8': 8}
|
{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'runs (balls)_5': 'runs ( balls )', '3_6': '3', 'partnerships_7': 'partnerships', 'herschelle gibbs / justin kemp_8': 'herschelle gibbs / justin kemp'}
|
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'runs (balls)_5': [0], '3_6': [0], 'partnerships_7': [1], 'herschelle gibbs / justin kemp_8': [2]}
|
['runs ( balls )', 'wicket', 'partnerships', 'venue', 'date']
|
[['145 ( 81 )', '1st', 'chris gayle / devon smith', 'johannesburg', '2007 - 09 - 11'], ['136 ( 88 )', '1st', 'gautam gambhir / virender sehwag', 'durban', '2007 - 09 - 19'], ['120 ( 57 )', '3rd', 'herschelle gibbs / justin kemp', 'johannesburg', '2007 - 09 - 11'], ['119 ( 75 )', '5th', 'shoaib malik / misbah - ul - haq', 'johannesburg', '2007 - 09 - 18'], ['109 ( 62 )', '3rd', 'aftab ahmed / mohammad ashraful', 'johannesburg', '2007 - 09 - 13'], ['104 ( 69 )', '1st', 'adam gilchrist / matthew hayden', 'cape town', '2007 - 09 - 16'], ['102 ( 62 )', '1st', 'adam gilchrist / matthew hayden', 'cape town', '2007 - 09 - 22'], ['101 ( 55 )', '4th', 'younis khan / shoaib malik', 'johannesburg', '2007 - 09 - 17'], ['100 ( 45 )', '4th', 'kevin pietersen / paul collingwood', 'cape town', '2007 - 09 - 13'], ['95 ( 79 )', '2nd', 'devon smith / shivnarine chanderpaul', 'johannesburg', '2007 - 09 - 13']]
|
avc club volleyball championship
|
https://en.wikipedia.org/wiki/AVC_Club_Volleyball_Championship
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14841421-2.html.csv
|
ordinal
|
kazakhstan won the 2nd most silver medals at the avc club volleyball championship .
|
{'row': '3', 'col': '4', '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', 'silver', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; silver ; 2 }'}, 'nation'], 'result': 'kazakhstan', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; silver ; 2 } ; nation }'}, 'kazakhstan'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; silver ; 2 } ; nation } ; kazakhstan } = true', 'tointer': 'select the row whose silver record of all rows is 2nd maximum . the nation record of this row is kazakhstan .'}
|
eq { hop { nth_argmax { all_rows ; silver ; 2 } ; nation } ; kazakhstan } = true
|
select the row whose silver record of all rows is 2nd maximum . the nation record of this row is kazakhstan .
|
3
|
3
|
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'silver_5': 5, '2_6': 6, 'nation_7': 7, 'kazakhstan_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', 'silver_5': 'silver', '2_6': '2', 'nation_7': 'nation', 'kazakhstan_8': 'kazakhstan'}
|
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'silver_5': [0], '2_6': [0], 'nation_7': [1], 'kazakhstan_8': [2]}
|
['rank', 'nation', 'gold', 'silver', 'bronze', 'total']
|
[['1', 'iran', '9', '4', '2', '15'], ['2', 'south korea', '2', '1', '0', '3'], ['3', 'kazakhstan', '1', '3', '2', '6'], ['4', 'qatar', '1', '2', '2', '5'], ['5', 'china', '1', '1', '4', '6'], ['6', 'saudi arabia', '0', '2', '0', '2'], ['7', 'japan', '0', '1', '2', '3'], ['8', 'chinese taipei', '0', '0', '1', '1'], ['8', 'indonesia', '0', '0', '1', '1'], ['total', 'total', '14', '14', '14', '42']]
|
soccer - specific stadium
|
https://en.wikipedia.org/wiki/Soccer-specific_stadium
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1034291-6.html.csv
|
aggregation
|
the average seating capacity for the soccer-specific stadiums is 4736 .
|
{'scope': 'all', 'col': '5', 'type': 'average', 'result': '4736', 'subset': None}
|
{'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'capacity'], 'result': '4736', 'ind': 0, 'tostr': 'avg { all_rows ; capacity }'}, '4736'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; capacity } ; 4736 } = true', 'tointer': 'the average of the capacity record of all rows is 4736 .'}
|
round_eq { avg { all_rows ; capacity } ; 4736 } = true
|
the average of the capacity record of all rows is 4736 .
|
2
|
2
|
{'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'capacity_4': 4, '4736_5': 5}
|
{'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'capacity_4': 'capacity', '4736_5': '4736'}
|
{'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'capacity_4': [0], '4736_5': [1]}
|
['stadium', 'club ( s )', 'division', 'city', 'capacity', 'opened']
|
[['blackbaud stadium', 'charleston battery', 'usl pro', 'charleston , sc', '5113', '1999'], ['city park stadium', 'westchester flames', 'pdl', 'new rochelle , ny', '1845', '1970s'], ['seminole soccer complex ( sanford )', 'central florida kraze', 'pdl', 'lake mary , fl', '3666', '1995'], ['ezell park', 'nashville metros', 'pdl', 'nashville , tn', '1317', '1950s'], ['highmark stadium', 'pittsburgh riverhounds', 'usl pro', 'pittsburgh , pa', '3500', '2013'], ['indiana invaders soccer complex', 'indiana invaders', 'pdl', 'south bend , in', '4985', '2004'], ['legion stadium', 'wilmington hammerheads', 'usl pro', 'wilmington , nc', '5300', '1930s'], ['lusitano stadium', 'western mass pioneers', 'pdl', 'ludlow , ma', '3000', '1918'], ['macpherson stadium', 'carolina dynamo', 'pdl', 'browns summit , nc', '1600', '2002'], ['patriot stadium', 'chivas el paso patriots', 'pdl', 'el paso , tx', '3000', '2005'], ["sahlen 's stadium", 'rochester rhinos western new york flash', 'usl pro nwsl', 'rochester , ny', '13500', '2006'], ['virginia beach sportsplex', 'hampton roads piranhas', 'pdl', 'virginia beach , va', '10000', '1999']]
|
athletics at the 2008 summer olympics - men 's 200 metres
|
https://en.wikipedia.org/wiki/Athletics_at_the_2008_Summer_Olympics_%E2%80%93_Men%27s_200_metres
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18569011-12.html.csv
|
superlative
|
the athlete that represented zimbabwe scored the fastest time in the 200 meters competition .
|
{'scope': 'all', 'col_superlative': '5', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '4', 'subset': None}
|
{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmin', 'args': ['all_rows', 'time'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; time }'}, 'nationality'], 'result': 'zimbabwe', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; time } ; nationality }'}, 'zimbabwe'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmin { all_rows ; time } ; nationality } ; zimbabwe } = true', 'tointer': 'select the row whose time record of all rows is minimum . the nationality record of this row is zimbabwe .'}
|
eq { hop { argmin { all_rows ; time } ; nationality } ; zimbabwe } = true
|
select the row whose time record of all rows is minimum . the nationality record of this row is zimbabwe .
|
3
|
3
|
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'time_5': 5, 'nationality_6': 6, 'zimbabwe_7': 7}
|
{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'time_5': 'time', 'nationality_6': 'nationality', 'zimbabwe_7': 'zimbabwe'}
|
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'time_5': [0], 'nationality_6': [1], 'zimbabwe_7': [2]}
|
['rank', 'lane', 'athlete', 'nationality', 'time', 'react']
|
[['1', '4', 'brian dzingai', 'zimbabwe', '20.23', '0.182'], ['2', '7', 'walter dix', 'united states', '20.27', '0.162'], ['3', '8', 'christopher williams', 'jamaica', '20.28', '0.159'], ['4', '6', 'christian malcolm', 'great britain', '20.30', '0.188'], ['5', '9', 'stephan buckland', 'mauritius', '20.37', '0.188'], ['6', '5', 'roman smirnov', 'russia', '20.62', '0.161'], ['7', '3', 'shinji takahira', 'japan', '20.63', '0.185'], ['8', '2', 'matic osovnikar', 'slovenia', '20.95', '0.171']]
|
1966 dutch grand prix
|
https://en.wikipedia.org/wiki/1966_Dutch_Grand_Prix
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1122356-1.html.csv
|
comparative
|
in the 1966 dutch grand prix , graham hill finished faster than jim clark .
|
{'row_1': '2', 'row_2': '3', 'col': '4', 'col_other': '1', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None}
|
{'func': 'less', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'driver', 'graham hill'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose driver record fuzzily matches to graham hill .', 'tostr': 'filter_eq { all_rows ; driver ; graham hill }'}, 'time / retired'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; driver ; graham hill } ; time / retired }', 'tointer': 'select the rows whose driver record fuzzily matches to graham hill . take the time / retired record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'driver', 'jim clark'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose driver record fuzzily matches to jim clark .', 'tostr': 'filter_eq { all_rows ; driver ; jim clark }'}, 'time / retired'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; driver ; jim clark } ; time / retired }', 'tointer': 'select the rows whose driver record fuzzily matches to jim clark . take the time / retired record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; driver ; graham hill } ; time / retired } ; hop { filter_eq { all_rows ; driver ; jim clark } ; time / retired } } = true', 'tointer': 'select the rows whose driver record fuzzily matches to graham hill . take the time / retired record of this row . select the rows whose driver record fuzzily matches to jim clark . take the time / retired record of this row . the first record is less than the second record .'}
|
less { hop { filter_eq { all_rows ; driver ; graham hill } ; time / retired } ; hop { filter_eq { all_rows ; driver ; jim clark } ; time / retired } } = true
|
select the rows whose driver record fuzzily matches to graham hill . take the time / retired record of this row . select the rows whose driver record fuzzily matches to jim clark . take the time / retired record of this row . the first record is less than the second record .
|
5
|
5
|
{'less_4': 4, 'result_5': 5, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'driver_7': 7, 'graham hill_8': 8, 'time / retired_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'driver_11': 11, 'jim clark_12': 12, 'time / retired_13': 13}
|
{'less_4': 'less', 'result_5': 'true', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'driver_7': 'driver', 'graham hill_8': 'graham hill', 'time / retired_9': 'time / retired', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'driver_11': 'driver', 'jim clark_12': 'jim clark', 'time / retired_13': 'time / retired'}
|
{'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'driver_7': [0], 'graham hill_8': [0], 'time / retired_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'driver_11': [1], 'jim clark_12': [1], 'time / retired_13': [3]}
|
['driver', 'constructor', 'laps', 'time / retired', 'grid']
|
[['jack brabham', 'brabham - repco', '90', '2:20:32.5', '1'], ['graham hill', 'brm', '89', '+ 1 lap', '7'], ['jim clark', 'lotus - climax', '88', '+ 2 laps', '3'], ['jackie stewart', 'brm', '88', '+ 2 laps', '8'], ['mike spence', 'lotus - brm', '87', '+ 3 laps', '12'], ['lorenzo bandini', 'ferrari', '87', '+ 3 laps', '9'], ['jo bonnier', 'cooper - maserati', '84', '+ 6 laps', '13'], ['john taylor', 'brabham - brm', '84', '+ 6 laps', '17'], ['guy ligier', 'cooper - maserati', '84', '+ 6 laps', '16'], ['jo siffert', 'cooper - maserati', '79', 'engine', '11'], ['bob anderson', 'brabham - climax', '73', 'suspension', '14'], ['john surtees', 'cooper - maserati', '44', 'electrical', '10'], ['denny hulme', 'brabham - repco', '37', 'ignition', '2'], ['peter arundell', 'lotus - brm', '28', 'ignition', '15'], ['dan gurney', 'eagle - climax', '26', 'oil leak', '4'], ['mike parkes', 'ferrari', '10', 'accident', '5'], ['jochen rindt', 'cooper - maserati', '2', 'accident', '6']]
|
2008 - 09 in argentine football
|
https://en.wikipedia.org/wiki/2008%E2%80%9309_in_Argentine_football
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-18027411-1.html.csv
|
count
|
three of the teams did not play in the 2008 recopa sudamericana .
|
{'scope': 'all', 'criterion': 'equal', 'value': 'did not play', 'result': '3', 'col': '3', 'subset': None}
|
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', '2008 recopa sudamericana', 'did not play'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose 2008 recopa sudamericana record fuzzily matches to did not play .', 'tostr': 'filter_eq { all_rows ; 2008 recopa sudamericana ; did not play }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; 2008 recopa sudamericana ; did not play } }', 'tointer': 'select the rows whose 2008 recopa sudamericana record fuzzily matches to did not play . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; 2008 recopa sudamericana ; did not play } } ; 3 } = true', 'tointer': 'select the rows whose 2008 recopa sudamericana record fuzzily matches to did not play . the number of such rows is 3 .'}
|
eq { count { filter_eq { all_rows ; 2008 recopa sudamericana ; did not play } } ; 3 } = true
|
select the rows whose 2008 recopa sudamericana record fuzzily matches to did not play . 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, '2008 recopa sudamericana_5': 5, 'did not play_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', '2008 recopa sudamericana_5': '2008 recopa sudamericana', 'did not play_6': 'did not play', '3_7': '3'}
|
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], '2008 recopa sudamericana_5': [0], 'did not play_6': [0], '3_7': [2]}
|
['team / competition', '2008 suruga bank championship', '2008 recopa sudamericana', '2008 copa sudamericana', '2009 copa libertadores']
|
[['argentinos juniors', 'did not play', 'did not play', 'semifinals eliminated by estudiantes', 'did not qualify'], ['arsenal de sarandí', 'champions defeated gamba osaka', 'runner up lost to boca juniors', 'round of 16 eliminated by estudiantes', 'did not qualify'], ['boca juniors', 'did not play', 'champions defeated arsenal de sarandí', 'quarterfinals eliminated by internacional', 'round of 16 eliminated by defensor sporting'], ['estudiantes de la plata', 'did not play', 'did not play', 'runner up lost to internacional', 'champions defeated cruzeiro'], ['independiente', 'did not play', 'did not play', 'first round eliminated by estudiantes', 'did not qualify']]
|
2008 - 09 serie a
|
https://en.wikipedia.org/wiki/2008%E2%80%9309_Serie_A
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17043360-1.html.csv
|
count
|
for the 2008 - 09 serie a , when the capacity is over 30000 , there were two times that the stadium was stadio giuseppe meazza .
|
{'scope': 'subset', 'criterion': 'equal', 'value': 'stadio giuseppe meazza', 'result': '2', 'col': '3', 'subset': {'col': '4', 'criterion': 'greater_than', 'value': '30000'}}
|
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'capacity', '30000'], 'result': None, 'ind': 0, 'tostr': 'filter_greater { all_rows ; capacity ; 30000 }', 'tointer': 'select the rows whose capacity record is greater than 30000 .'}, 'stadium', 'stadio giuseppe meazza'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose capacity record is greater than 30000 . among these rows , select the rows whose stadium record fuzzily matches to stadio giuseppe meazza .', 'tostr': 'filter_eq { filter_greater { all_rows ; capacity ; 30000 } ; stadium ; stadio giuseppe meazza }'}], 'result': '2', 'ind': 2, 'tostr': 'count { filter_eq { filter_greater { all_rows ; capacity ; 30000 } ; stadium ; stadio giuseppe meazza } }', 'tointer': 'select the rows whose capacity record is greater than 30000 . among these rows , select the rows whose stadium record fuzzily matches to stadio giuseppe meazza . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_eq { filter_greater { all_rows ; capacity ; 30000 } ; stadium ; stadio giuseppe meazza } } ; 2 } = true', 'tointer': 'select the rows whose capacity record is greater than 30000 . among these rows , select the rows whose stadium record fuzzily matches to stadio giuseppe meazza . the number of such rows is 2 .'}
|
eq { count { filter_eq { filter_greater { all_rows ; capacity ; 30000 } ; stadium ; stadio giuseppe meazza } } ; 2 } = true
|
select the rows whose capacity record is greater than 30000 . among these rows , select the rows whose stadium record fuzzily matches to stadio giuseppe meazza . the number of such rows is 2 .
|
4
|
4
|
{'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_str_eq_1': 1, 'filter_greater_0': 0, 'all_rows_5': 5, 'capacity_6': 6, '30000_7': 7, 'stadium_8': 8, 'stadio giuseppe meazza_9': 9, '2_10': 10}
|
{'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_str_eq_1': 'filter_str_eq', 'filter_greater_0': 'filter_greater', 'all_rows_5': 'all_rows', 'capacity_6': 'capacity', '30000_7': '30000', 'stadium_8': 'stadium', 'stadio giuseppe meazza_9': 'stadio giuseppe meazza', '2_10': '2'}
|
{'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_str_eq_1': [2], 'filter_greater_0': [1], 'all_rows_5': [0], 'capacity_6': [0], '30000_7': [0], 'stadium_8': [1], 'stadio giuseppe meazza_9': [1], '2_10': [3]}
|
['club', 'city', 'stadium', 'capacity', '2007 - 08 season']
|
[['atalanta bc', 'bergamo', "stadio atleti azzurri d'italia", '26393', '9th in serie a'], ['bologna fc 1909', 'bologna', "stadio renato dall ' ara", '39444', '2nd in serie b'], ['cagliari calcio', 'cagliari', "stadio sant ' elia", '23486', '14th in serie a'], ['calcio catania', 'catania', 'stadio angelo massimino', '23420', '17th in serie a'], ['ac chievoverona', 'verona', 'stadio marcantonio bentegodi', '39211', 'serie b champions'], ['acf fiorentina', 'florence', 'stadio artemio franchi , florence', '47282', '4th in serie a'], ['genoa cfc', 'genoa', 'stadio luigi ferraris', '36685', '10th in serie a'], ['fc internazionale milano', 'milan', 'stadio giuseppe meazza', '80074', 'serie a champions'], ['juventus fc', 'turin', 'stadio olimpico di torino', '27500', '3rd in serie a'], ['ss lazio', 'rome', 'stadio olimpico', '72700', '12th in serie a'], ['us lecce', 'lecce', 'stadio via del mare', '33876', 'serie b playoff winners'], ['ac milan', 'milan', 'stadio giuseppe meazza', '80074', '5th in serie a'], ['ssc napoli', 'naples', 'stadio san paolo', '60240', '8th in serie a'], ['us città di palermo', 'palermo', 'stadio renzo barbera', '37242', '11th in serie a'], ['reggina calcio', 'reggio calabria', 'stadio oreste granillo', '27454', '16th in serie a'], ['as roma', 'rome', 'stadio olimpico', '72700', '2nd in serie a'], ['uc sampdoria', 'genoa', 'stadio luigi ferraris', '36685', '6th in serie a'], ['ac siena', 'siena', 'stadio artemio franchi , siena', '15373', '13th in serie a'], ['torino fc', 'turin', 'stadio olimpico di torino', '27500', '15th in serie a'], ['udinese calcio', 'udine', 'stadio friuli', '41652', '7th in serie a']]
|
thiago alves ( tennis )
|
https://en.wikipedia.org/wiki/Thiago_Alves_%28tennis%29
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14924949-12.html.csv
|
superlative
|
the highest score for thiago alves tennis tournaments was on march 5 , 2007 .
|
{'scope': 'all', 'col_superlative': '6', 'row_superlative': '2', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None}
|
{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'score'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; score }'}, 'date'], 'result': 'march 5 , 2007', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; score } ; date }'}, 'march 5 , 2007'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; score } ; date } ; march 5 , 2007 } = true', 'tointer': 'select the row whose score record of all rows is maximum . the date record of this row is march 5 , 2007 .'}
|
eq { hop { argmax { all_rows ; score } ; date } ; march 5 , 2007 } = true
|
select the row whose score record of all rows is maximum . the date record of this row is march 5 , 2007 .
|
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, 'march 5 , 2007_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', 'march 5 , 2007_7': 'march 5 , 2007'}
|
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'score_5': [0], 'date_6': [1], 'march 5 , 2007_7': [2]}
|
['date', 'tournament', 'surface', 'partnering', 'opponents', 'score']
|
[['april 10 , 2006', 'florianópolis , brazil', 'clay', 'júlio silva', 'máximo gonzález sergio roitman', '6 - 2 , 3 - 6 ,'], ['march 5 , 2007', 'salinas , ecuador', 'hard', 'franco ferreiro', 'scott lipsky david martin', '7 - 5 , 7 - 6 ( 11 - 9 )'], ['september 29 , 2008', 'aracaju , brazil', 'clay', 'joão souza', 'juan martín aranguren franco ferreiro', '6 - 4 , 6 - 4'], ['november 3 , 2008', 'guayaquil , ecuador', 'clay', 'ricardo hocevar', 'sebastián decoud santiago giraldo', '6 - 4 , 6 - 4'], ['may 12 , 2012', 'rio quente , brazil', 'hard', 'augusto laranja', 'guido andreozzi marcel felder', '6 - 3 , 6 - 3']]
|
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
|
superlative
|
the player from scotland had the lowest score of all players in the 2006 u.s. open .
|
{'scope': 'all', 'col_superlative': '4', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '3', 'subset': None}
|
{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmin', 'args': ['all_rows', 'score'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; score }'}, 'country'], 'result': 'scotland', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; score } ; country }'}, 'scotland'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmin { all_rows ; score } ; country } ; scotland } = true', 'tointer': 'select the row whose score record of all rows is minimum . the country record of this row is scotland .'}
|
eq { hop { argmin { all_rows ; score } ; country } ; scotland } = true
|
select the row whose score record of all rows is minimum . the country record of this row is scotland .
|
3
|
3
|
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'score_5': 5, 'country_6': 6, 'scotland_7': 7}
|
{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'score_5': 'score', 'country_6': 'country', 'scotland_7': 'scotland'}
|
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'score_5': [0], 'country_6': [1], 'scotland_7': [2]}
|
['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', 'john cook', 'united states', '71', '+ 1'], ['t7', 'kenneth ferrie', 'england', '71', '+ 1'], ['t7', 'fred funk', 'united states', '71', '+ 1'], ['t7', 'graeme mcdowell', 'northern ireland', '71', '+ 1'], ['t7', 'geoff ogilvy', 'australia', '71', '+ 1'], ['t7', 'vijay singh', 'fiji', '71', '+ 1'], ['t7', 'mike weir', 'canada', '71', '+ 1']]
|
1956 vfl season
|
https://en.wikipedia.org/wiki/1956_VFL_season
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10640687-7.html.csv
|
ordinal
|
mcg venue recorded the highest crowd participation during the 1956 vfl season .
|
{'row': '5', 'col': '6', 'order': '1', 'col_other': '5', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None}
|
{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'crowd', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; crowd ; 1 }'}, 'venue'], 'result': 'mcg', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; crowd ; 1 } ; venue }'}, 'mcg'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; crowd ; 1 } ; venue } ; mcg } = true', 'tointer': 'select the row whose crowd record of all rows is 1st maximum . the venue record of this row is mcg .'}
|
eq { hop { nth_argmax { all_rows ; crowd ; 1 } ; venue } ; mcg } = true
|
select the row whose crowd record of all rows is 1st maximum . the venue record of this row is mcg .
|
3
|
3
|
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'crowd_5': 5, '1_6': 6, 'venue_7': 7, 'mcg_8': 8}
|
{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'crowd_5': 'crowd', '1_6': '1', 'venue_7': 'venue', 'mcg_8': 'mcg'}
|
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'crowd_5': [0], '1_6': [0], 'venue_7': [1], 'mcg_8': [2]}
|
['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date']
|
[['north melbourne', '15.7 ( 97 )', 'south melbourne', '7.16 ( 58 )', 'arden street oval', '13000', '26 may 1956'], ['st kilda', '9.10 ( 64 )', 'richmond', '6.8 ( 44 )', 'junction oval', '15800', '26 may 1956'], ['hawthorn', '8.10 ( 58 )', 'fitzroy', '9.13 ( 67 )', 'glenferrie oval', '18000', '26 may 1956'], ['geelong', '15.17 ( 107 )', 'essendon', '8.9 ( 57 )', 'kardinia park', '21758', '26 may 1956'], ['melbourne', '11.13 ( 79 )', 'collingwood', '9.7 ( 61 )', 'mcg', '46868', '26 may 1956'], ['footscray', '7.13 ( 55 )', 'carlton', '8.8 ( 56 )', 'western oval', '33089', '26 may 1956']]
|
2009 nhl winter classic
|
https://en.wikipedia.org/wiki/2009_NHL_Winter_Classic
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18463659-1.html.csv
|
count
|
in the 2009 nhl winter classic , when the team is detroit , there were 2 times when jiri hudler scored a goal .
|
{'scope': 'subset', 'criterion': 'fuzzily_match', 'value': 'jiri hudler', 'result': '2', 'col': '3', 'subset': {'col': '2', 'criterion': 'equal', 'value': 'det'}}
|
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'team', 'det'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; team ; det }', 'tointer': 'select the rows whose team record fuzzily matches to det .'}, 'goal', 'jiri hudler'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose team record fuzzily matches to det . among these rows , select the rows whose goal record fuzzily matches to jiri hudler .', 'tostr': 'filter_eq { filter_eq { all_rows ; team ; det } ; goal ; jiri hudler }'}], 'result': '2', 'ind': 2, 'tostr': 'count { filter_eq { filter_eq { all_rows ; team ; det } ; goal ; jiri hudler } }', 'tointer': 'select the rows whose team record fuzzily matches to det . among these rows , select the rows whose goal record fuzzily matches to jiri hudler . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_eq { filter_eq { all_rows ; team ; det } ; goal ; jiri hudler } } ; 2 } = true', 'tointer': 'select the rows whose team record fuzzily matches to det . among these rows , select the rows whose goal record fuzzily matches to jiri hudler . the number of such rows is 2 .'}
|
eq { count { filter_eq { filter_eq { all_rows ; team ; det } ; goal ; jiri hudler } } ; 2 } = true
|
select the rows whose team record fuzzily matches to det . among these rows , select the rows whose goal record fuzzily matches to jiri hudler . 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, 'team_6': 6, 'det_7': 7, 'goal_8': 8, 'jiri hudler_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', 'team_6': 'team', 'det_7': 'det', 'goal_8': 'goal', 'jiri hudler_9': 'jiri hudler', '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], 'team_6': [0], 'det_7': [0], 'goal_8': [1], 'jiri hudler_9': [1], '2_10': [3]}
|
['period', 'team', 'goal', 'assist ( s )', 'time', 'score']
|
[['1st', 'chi', 'kris versteeg ( 11 ) ( pp )', 'martin havlat ( 18 ) , brent seabrook ( 7 )', '3:24', '1 - 0 chi'], ['1st', 'det', 'mikael samuelsson ( 8 ) ( pp )', 'henrik zetterberg ( 18 ) , marian hossa ( 18 )', '9:50', '1 - 1'], ['1st', 'chi', 'martin havlat ( 10 ) ( pp )', 'kris versteeg ( 20 ) , brian campbell ( 21 )', '12:37', '2 - 1 chi'], ['1st', 'chi', 'ben eager ( 7 )', 'martin havlat ( 19 )', '19:18', '3 - 1 chi'], ['2nd', 'det', 'jiri hudler ( 14 )', 'marian hossa ( 19 ) , henrik zetterberg ( 19 )', '1:14', '3 - 2 chi'], ['2nd', 'det', 'jiri hudler ( 15 )', 'brian rafalski ( 24 ) , nicklas lidstrom ( 20 )', '12:43', '3 - 3'], ['2nd', 'det', 'pavel datsyuk ( 16 )', 'johan franzen ( 10 ) , brian rafalski ( 25 )', '17:17', '4 - 3 det'], ['3rd', 'det', 'brian rafalski ( 5 ) ( pp )', 'jiri hudler ( 17 ) , tomas holmstrom ( 13 )', '3:07', '5 - 3 det'], ['3rd', 'det', 'brett lebda ( 3 )', 'henrik zetterberg ( 20 ) , marian hossa ( 20 )', '3:24', '6 - 3 det'], ['3rd', 'chi', 'duncan keith ( 5 ) ( pp )', 'patrick sharp ( 12 ) , jonathan toews ( 20 )', '19:50', '6 - 4 det']]
|
1949 giro d'italia
|
https://en.wikipedia.org/wiki/1949_Giro_d%27Italia
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12582434-1.html.csv
|
majority
|
all the winners of the 1949 giro d'italia were italian .
|
{'scope': 'all', 'col': '5', 'most_or_all': 'all', 'criterion': 'fuzzily_match', 'value': '( ita )', 'subset': None}
|
{'func': 'all_str_eq', 'args': ['all_rows', 'winner', '( ita )'], 'result': True, 'ind': 0, 'tointer': 'for the winner records of all rows , all of them fuzzily match to ( ita ) .', 'tostr': 'all_eq { all_rows ; winner ; ( ita ) } = true'}
|
all_eq { all_rows ; winner ; ( ita ) } = true
|
for the winner records of all rows , all of them fuzzily match to ( ita ) .
|
1
|
1
|
{'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'winner_3': 3, '( ita )_4': 4}
|
{'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'winner_3': 'winner', '( ita )_4': '( ita )'}
|
{'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'winner_3': [0], '( ita )_4': [0]}
|
['date', 'course', 'distance', 'type', 'winner']
|
[['21 may', 'palermo to catania', '100 km', 'stage with mountain ( s )', 'mario fazio ( ita )'], ['22 may', 'catania to messina', '100 km', 'plain stage', 'sergio maggini ( ita )'], ['23 may', 'villa san giovanni to cosenza', '100 km', 'stage with mountain ( s )', 'guido de santi ( ita )'], ['24 may', 'cosenza to salerno', '100 km', 'plain stage', 'fausto coppi ( ita )'], ['26 may', 'salerno to naples', '100 km', 'plain stage', 'serafino biagioni ( ita )'], ['27 may', 'naples to rome', '100 km', 'plain stage', 'mario ricci ( ita )'], ['28 may', 'rome to pesaro', '100 km', 'plain stage', 'adolfo leoni ( ita )'], ['29 may', 'pesaro to venezia', '100 km', 'plain stage', 'luigi casola ( ita )'], ['31 may', 'venezia to udine', '100 km', 'plain stage', 'adolfo leoni ( ita )'], ['1 june', 'udine to bassano del grappa', '100 km', 'plain stage', 'giovanni corrieri ( ita )'], ['2 june', 'bassano del grappa to bolzano', '100 km', 'stage with mountain ( s )', 'fausto coppi ( ita )'], ['4 june', 'bolzano to modena', '100 km', 'plain stage', 'oreste conte ( ita )'], ['5 june', 'modena to montecatini terme', '100 km', 'stage with mountain ( s )', 'adolfo leoni ( ita )'], ['6 june', 'montecatini terme to genoa', '100 km', 'stage with mountain ( s )', 'vincenzo rossello ( ita )'], ['7 june', 'genoa to sanremo', '100 km', 'plain stage', 'luciano maggini ( ita )'], ['9 june', 'sanremo to cuneo', '100 km', 'stage with mountain ( s )', 'oreste conte ( ita )'], ['10 june', 'cuneo to pinerolo', '100 km', 'stage with mountain ( s )', 'fausto coppi ( ita )'], ['11 june', 'pinerolo to turin', '100 km', 'individual time trial', 'antonio bevilacqua ( ita )'], ['12 june', 'turin to monza', '100 km', 'stage with mountain ( s )', 'giovanni corrieri ( ita )']]
|
list of pittsburgh penguins general managers
|
https://en.wikipedia.org/wiki/List_of_Pittsburgh_Penguins_general_managers
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13834044-2.html.csv
|
aggregation
|
the pittsburgh penguins played 375 games with jack riley as general manager .
|
{'scope': 'subset', 'col': '3', 'type': 'sum', 'result': '375', 'subset': {'col': '1', 'criterion': 'equal', 'value': 'jack riley'}}
|
{'func': 'round_eq', 'args': [{'func': 'sum', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'name', 'jack riley'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; name ; jack riley }', 'tointer': 'select the rows whose name record fuzzily matches to jack riley .'}, 'games'], 'result': '375', 'ind': 1, 'tostr': 'sum { filter_eq { all_rows ; name ; jack riley } ; games }'}, '375'], 'result': True, 'ind': 2, 'tostr': 'round_eq { sum { filter_eq { all_rows ; name ; jack riley } ; games } ; 375 } = true', 'tointer': 'select the rows whose name record fuzzily matches to jack riley . the sum of the games record of these rows is 375 .'}
|
round_eq { sum { filter_eq { all_rows ; name ; jack riley } ; games } ; 375 } = true
|
select the rows whose name record fuzzily matches to jack riley . the sum of the games record of these rows is 375 .
|
3
|
3
|
{'eq_2': 2, 'result_3': 3, 'sum_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'name_5': 5, 'jack riley_6': 6, 'games_7': 7, '375_8': 8}
|
{'eq_2': 'eq', 'result_3': 'true', 'sum_1': 'sum', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'name_5': 'name', 'jack riley_6': 'jack riley', 'games_7': 'games', '375_8': '375'}
|
{'eq_2': [3], 'result_3': [], 'sum_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'name_5': [0], 'jack riley_6': [0], 'games_7': [1], '375_8': [2]}
|
['name', 'term', 'games', 'record ( w - l - t / otl )', 'points', 'win percentage']
|
[['jack riley', 'june 6 , 1967 - may 1 , 1970', '226', '73 - 117 - 36', '182', '403'], ['red kelly', 'may 1 , 1970 - january 29 , 1972', '126', '33 - 64 - 29', '95', '377'], ['jack riley', 'january 29 , 1972 - january 13 , 1974', '149', '57 - 73 - 19', '133', '446'], ['jack button', 'january 13 , 1974 - july 1 , 1975', '117', '54 - 44 - 19', '127', '543'], ['wren blair', 'july 1 , 1975 - december 3 , 1976', '105', '44 - 44 - 17', '105', '500'], ['baz bastien', 'december 3 , 1976 - march 15 , 1983', '527', '193 - 248 - 86', '472', '447'], ['-', 'march 16 , 1983 - april 3 , 1983', '8', '2 - 5 - 1', '5', '313'], ['eddie johnston', 'may 27 , 1983 - april 14 , 1988', '400', '140 - 220 - 40', '320', '400'], ['tony esposito', 'april 14 , 1988 - december 5 , 1989', '106', '50 - 47 - 9', '109', '514'], ['craig patrick', 'december 5 , 1989 - may 20 , 2006', '1250', '575 - 511 - 127 - 37', '1314', '526'], ['ray shero', 'may 20 , 2006 - present', '164', '94 - 51 - 19', '207', '573']]
|
1983 - 84 north west counties football league
|
https://en.wikipedia.org/wiki/1983%E2%80%9384_North_West_Counties_Football_League
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-17718005-2.html.csv
|
superlative
|
in the 1983 - 84 north west counties football league , of teams that lost at least 10 games , the highest number of goals against was for rosendale united .
|
{'scope': 'subset', 'col_superlative': '8', 'row_superlative': '15', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '2,4', 'subset': {'col': '6', 'criterion': 'greater_than_eq', 'value': '10'}}
|
{'func': 'and', 'args': [{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': [{'func': 'filter_greater_eq', 'args': ['all_rows', 'lost', '10'], 'result': None, 'ind': 0, 'tostr': 'filter_greater_eq { all_rows ; lost ; 10 }', 'tointer': 'select the rows whose lost record is greater than or equal to 10 .'}, 'goals against'], 'result': None, 'ind': 1, 'tostr': 'argmax { filter_greater_eq { all_rows ; lost ; 10 } ; goals against }'}, 'team'], 'result': 'rossendale united', 'ind': 2, 'tostr': 'hop { argmax { filter_greater_eq { all_rows ; lost ; 10 } ; goals against } ; team }'}, 'rossendale united'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { argmax { filter_greater_eq { all_rows ; lost ; 10 } ; goals against } ; team } ; rossendale united }', 'tointer': 'select the rows whose lost record is greater than or equal to 10 . select the row whose goals against record of these rows is maximum . the team record of this row is rossendale united .'}, {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'argmax', 'args': [{'func': 'filter_greater_eq', 'args': ['all_rows', 'lost', '10'], 'result': None, 'ind': 0, 'tostr': 'filter_greater_eq { all_rows ; lost ; 10 }', 'tointer': 'select the rows whose lost record is greater than or equal to 10 .'}, 'goals against'], 'result': None, 'ind': 1, 'tostr': 'argmax { filter_greater_eq { all_rows ; lost ; 10 } ; goals against }'}, 'won'], 'result': '10', 'ind': 4, 'tostr': 'hop { argmax { filter_greater_eq { all_rows ; lost ; 10 } ; goals against } ; won }'}, '10'], 'result': True, 'ind': 5, 'tostr': 'eq { hop { argmax { filter_greater_eq { all_rows ; lost ; 10 } ; goals against } ; won } ; 10 }', 'tointer': 'the won record of this row is 10 .'}], 'result': True, 'ind': 6, 'tostr': 'and { eq { hop { argmax { filter_greater_eq { all_rows ; lost ; 10 } ; goals against } ; team } ; rossendale united } ; eq { hop { argmax { filter_greater_eq { all_rows ; lost ; 10 } ; goals against } ; won } ; 10 } } = true', 'tointer': 'select the rows whose lost record is greater than or equal to 10 . select the row whose goals against record of these rows is maximum . the team record of this row is rossendale united . the won record of this row is 10 .'}
|
and { eq { hop { argmax { filter_greater_eq { all_rows ; lost ; 10 } ; goals against } ; team } ; rossendale united } ; eq { hop { argmax { filter_greater_eq { all_rows ; lost ; 10 } ; goals against } ; won } ; 10 } } = true
|
select the rows whose lost record is greater than or equal to 10 . select the row whose goals against record of these rows is maximum . the team record of this row is rossendale united . the won record of this row is 10 .
|
9
|
7
|
{'and_6': 6, 'result_7': 7, 'str_eq_3': 3, 'str_hop_2': 2, 'argmax_1': 1, 'filter_greater_eq_0': 0, 'all_rows_8': 8, 'lost_9': 9, '10_10': 10, 'goals against_11': 11, 'team_12': 12, 'rossendale united_13': 13, 'eq_5': 5, 'num_hop_4': 4, 'won_14': 14, '10_15': 15}
|
{'and_6': 'and', 'result_7': 'true', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'argmax_1': 'argmax', 'filter_greater_eq_0': 'filter_greater_eq', 'all_rows_8': 'all_rows', 'lost_9': 'lost', '10_10': '10', 'goals against_11': 'goals against', 'team_12': 'team', 'rossendale united_13': 'rossendale united', 'eq_5': 'eq', 'num_hop_4': 'num_hop', 'won_14': 'won', '10_15': '10'}
|
{'and_6': [7], 'result_7': [], 'str_eq_3': [6], 'str_hop_2': [3], 'argmax_1': [2, 4], 'filter_greater_eq_0': [1], 'all_rows_8': [0], 'lost_9': [0], '10_10': [0], 'goals against_11': [1], 'team_12': [2], 'rossendale united_13': [3], 'eq_5': [6], 'num_hop_4': [5], 'won_14': [4], '10_15': [5]}
|
['position', 'team', 'played', 'won', 'drawn', 'lost', 'goals for', 'goals against', 'goal difference', 'points 1']
|
[['1', 'fleetwood town', '34', '24', '8', '2', '73', '24', '+ 49', '56'], ['2', 'eastwood hanley', '34', '21', '6', '7', '69', '35', '+ 34', '48'], ['3', 'irlam town', '34', '19', '8', '7', '67', '41', '+ 26', '46'], ['4', 'warrington town', '34', '18', '7', '9', '65', '45', '+ 20', '43'], ['5', 'droylsden', '34', '19', '5', '10', '59', '42', '+ 17', '43'], ['6', 'colne dynamoes', '34', '16', '9', '9', '55', '37', '+ 18', '41'], ['7', 'ellesmere port & neston', '34', '12', '10', '12', '49', '38', '+ 11', '34'], ['8', 'chadderton', '34', '14', '6', '14', '56', '46', '+ 10', '34'], ['9', 'atherton laburnum rovers', '34', '11', '11', '12', '37', '41', '4', '33'], ['10', 'wren rovers', '34', '11', '10', '13', '45', '47', '2', '33'], ['11', 'skelmersdale united', '34', '13', '6', '15', '60', '63', '3', '32'], ['12', 'ford motors', '34', '9', '9', '16', '38', '53', '15', '27'], ['13', 'prescot bi', '34', '9', '9', '16', '50', '66', '16', '27'], ['14', 'lytham', '34', '13', '3', '18', '56', '81', '25', '27 2'], ['15', 'rossendale united', '34', '10', '6', '18', '53', '84', '31', '26'], ['16', 'great harwood town', '34', '5', '12', '17', '36', '60', '24', '22'], ['17', 'salford', '34', '5', '11', '18', '24', '60', '36', '21']]
|
1989 all - ireland senior hurling championship
|
https://en.wikipedia.org/wiki/1989_All-Ireland_Senior_Hurling_Championship
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12296897-3.html.csv
|
majority
|
in the 1989 all - ireland senior hurling championship , of the players who had at least 3 matches , most of them had an average of at least 8 .
|
{'scope': 'subset', 'col': '7', 'most_or_all': 'most', 'criterion': 'greater_than_eq', 'value': '8', 'subset': {'col': '6', 'criterion': 'greater_than_eq', 'value': '3'}}
|
{'func': 'most_greater_eq', 'args': [{'func': 'filter_greater_eq', 'args': ['all_rows', 'matches', '3'], 'result': None, 'ind': 0, 'tostr': 'filter_greater_eq { all_rows ; matches ; 3 }', 'tointer': 'select the rows whose matches record is greater than or equal to 3 .'}, 'average', '8'], 'result': True, 'ind': 1, 'tointer': 'select the rows whose matches record is greater than or equal to 3 . for the average records of these rows , most of them are greater than or equal to 8 .', 'tostr': 'most_greater_eq { filter_greater_eq { all_rows ; matches ; 3 } ; average ; 8 } = true'}
|
most_greater_eq { filter_greater_eq { all_rows ; matches ; 3 } ; average ; 8 } = true
|
select the rows whose matches record is greater than or equal to 3 . for the average records of these rows , most of them are greater than or equal to 8 .
|
2
|
2
|
{'most_greater_eq_1': 1, 'result_2': 2, 'filter_greater_eq_0': 0, 'all_rows_3': 3, 'matches_4': 4, '3_5': 5, 'average_6': 6, '8_7': 7}
|
{'most_greater_eq_1': 'most_greater_eq', 'result_2': 'true', 'filter_greater_eq_0': 'filter_greater_eq', 'all_rows_3': 'all_rows', 'matches_4': 'matches', '3_5': '3', 'average_6': 'average', '8_7': '8'}
|
{'most_greater_eq_1': [2], 'result_2': [], 'filter_greater_eq_0': [1], 'all_rows_3': [0], 'matches_4': [0], '3_5': [0], 'average_6': [1], '8_7': [1]}
|
['rank', 'player', 'county', 'tally', 'total', 'matches', 'average']
|
[['1', 'nicky english', 'tipperary', '4 - 38', '50', '4', '12.50'], ['2', 'adrian ronan', 'kilkenny', '1 - 21', '24', '3', '8.00'], ['2', 'mark corrigan', 'offaly', '4 - 12', '24', '3', '8.00'], ['4', 'finbarr delaney', 'cork', '1 - 19', '23', '2', '8.00'], ['5', 'pat fox', 'tipperary', '3 - 11', '20', '4', '5.00']]
|
mitsuo itoh
|
https://en.wikipedia.org/wiki/Mitsuo_Itoh
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15250161-2.html.csv
|
aggregation
|
between the years of 1966 and 1967 , mitsuo itoh scored 15 points .
|
{'scope': 'subset', 'col': '4', 'type': 'sum', 'result': '15', 'subset': {'col': '1', 'criterion': 'greater_than_eq', 'value': '1966'}}
|
{'func': 'round_eq', 'args': [{'func': 'sum', 'args': [{'func': 'filter_greater_eq', 'args': ['all_rows', 'year', '1966'], 'result': None, 'ind': 0, 'tostr': 'filter_greater_eq { all_rows ; year ; 1966 }', 'tointer': 'select the rows whose year record is greater than or equal to 1966 .'}, 'points'], 'result': '15', 'ind': 1, 'tostr': 'sum { filter_greater_eq { all_rows ; year ; 1966 } ; points }'}, '15'], 'result': True, 'ind': 2, 'tostr': 'round_eq { sum { filter_greater_eq { all_rows ; year ; 1966 } ; points } ; 15 } = true', 'tointer': 'select the rows whose year record is greater than or equal to 1966 . the sum of the points record of these rows is 15 .'}
|
round_eq { sum { filter_greater_eq { all_rows ; year ; 1966 } ; points } ; 15 } = true
|
select the rows whose year record is greater than or equal to 1966 . the sum of the points record of these rows is 15 .
|
3
|
3
|
{'eq_2': 2, 'result_3': 3, 'sum_1': 1, 'filter_greater_eq_0': 0, 'all_rows_4': 4, 'year_5': 5, '1966_6': 6, 'points_7': 7, '15_8': 8}
|
{'eq_2': 'eq', 'result_3': 'true', 'sum_1': 'sum', 'filter_greater_eq_0': 'filter_greater_eq', 'all_rows_4': 'all_rows', 'year_5': 'year', '1966_6': '1966', 'points_7': 'points', '15_8': '15'}
|
{'eq_2': [3], 'result_3': [], 'sum_1': [2], 'filter_greater_eq_0': [1], 'all_rows_4': [0], 'year_5': [0], '1966_6': [0], 'points_7': [1], '15_8': [2]}
|
['year', 'class', 'team', 'points', 'wins']
|
[['1961', '125cc', 'suzuki', '0', '0'], ['1961', '250cc', 'suzuki', '0', '0'], ['1962', '50cc', 'suzuki', '23', '0'], ['1962', '125cc', 'suzuki', '4', '0'], ['1963', '50cc', 'suzuki', '20', '1'], ['1963', '125cc', 'suzuki', '1', '0'], ['1964', '50cc', 'suzuki', '19', '0'], ['1964', '125cc', 'suzuki', '6', '0'], ['1965', '50cc', 'suzuki', '16', '0'], ['1966', '50cc', 'suzuki', '3', '0'], ['1966', '125cc', 'suzuki', '4', '0'], ['1967', '50cc', 'suzuki', '8', '1']]
|
werner pfirter
|
https://en.wikipedia.org/wiki/Werner_Pfirter
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16431762-2.html.csv
|
superlative
|
werner pfirter had the highest number of points with a 350cc in 1971 .
|
{'scope': 'all', 'col_superlative': '4', 'row_superlative': '4', 'value_mentioned': 'yes', 'max_or_min': 'max', 'other_col': '1', 'subset': None}
|
{'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'max', 'args': ['all_rows', 'points'], 'result': '33', 'ind': 0, 'tostr': 'max { all_rows ; points }', 'tointer': 'the maximum points record of all rows is 33 .'}, '33'], 'result': True, 'ind': 1, 'tostr': 'eq { max { all_rows ; points } ; 33 }', 'tointer': 'the maximum points record of all rows is 33 .'}, {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'points'], 'result': None, 'ind': 2, 'tostr': 'argmax { all_rows ; points }'}, 'year'], 'result': '1971', 'ind': 3, 'tostr': 'hop { argmax { all_rows ; points } ; year }'}, '1971'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { argmax { all_rows ; points } ; year } ; 1971 }', 'tointer': 'the year record of the row with superlative points record is 1971 .'}], 'result': True, 'ind': 5, 'tostr': 'and { eq { max { all_rows ; points } ; 33 } ; eq { hop { argmax { all_rows ; points } ; year } ; 1971 } } = true', 'tointer': 'the maximum points record of all rows is 33 . the year record of the row with superlative points record is 1971 .'}
|
and { eq { max { all_rows ; points } ; 33 } ; eq { hop { argmax { all_rows ; points } ; year } ; 1971 } } = true
|
the maximum points record of all rows is 33 . the year record of the row with superlative points record is 1971 .
|
6
|
6
|
{'and_5': 5, 'result_6': 6, 'eq_1': 1, 'max_0': 0, 'all_rows_7': 7, 'points_8': 8, '33_9': 9, 'eq_4': 4, 'num_hop_3': 3, 'argmax_2': 2, 'all_rows_10': 10, 'points_11': 11, 'year_12': 12, '1971_13': 13}
|
{'and_5': 'and', 'result_6': 'true', 'eq_1': 'eq', 'max_0': 'max', 'all_rows_7': 'all_rows', 'points_8': 'points', '33_9': '33', 'eq_4': 'eq', 'num_hop_3': 'num_hop', 'argmax_2': 'argmax', 'all_rows_10': 'all_rows', 'points_11': 'points', 'year_12': 'year', '1971_13': '1971'}
|
{'and_5': [6], 'result_6': [], 'eq_1': [5], 'max_0': [1], 'all_rows_7': [0], 'points_8': [0], '33_9': [1], 'eq_4': [5], 'num_hop_3': [4], 'argmax_2': [3], 'all_rows_10': [2], 'points_11': [2], 'year_12': [3], '1971_13': [4]}
|
['year', 'class', 'team', 'points', 'wins']
|
[['1970', '250cc', 'yamaha', '0', '0'], ['1970', '350cc', 'yamaha', '0', '0'], ['1971', '250cc', 'yamaha', '9', '0'], ['1971', '350cc', 'yamaha', '33', '0'], ['1972', '250cc', 'yamaha', '28', '0'], ['1972', '350cc', 'yamaha', '17', '0'], ['1973', '250cc', 'yamaha', '20', '0'], ['1973', '350cc', 'yamaha', '17', '0']]
|
list of birds on stamps of bhutan
|
https://en.wikipedia.org/wiki/List_of_birds_on_stamps_of_Bhutan
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2006661-1.html.csv
|
majority
|
the majority of the time yvert had a value of zero .
|
{'scope': 'all', 'col': '8', 'most_or_all': 'most', 'criterion': 'equal', 'value': '0', 'subset': None}
|
{'func': 'most_eq', 'args': ['all_rows', 'yvert', '0'], 'result': True, 'ind': 0, 'tointer': 'for the yvert records of all rows , most of them are equal to 0 .', 'tostr': 'most_eq { all_rows ; yvert ; 0 } = true'}
|
most_eq { all_rows ; yvert ; 0 } = true
|
for the yvert records of all rows , most of them are equal to 0 .
|
1
|
1
|
{'most_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'yvert_3': 3, '0_4': 4}
|
{'most_eq_0': 'most_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'yvert_3': 'yvert', '0_4': '0'}
|
{'most_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'yvert_3': [0], '0_4': [0]}
|
['year', 'date', 'type', 'species', 'author species', 'value', 'scott', 'yvert', 'mitchell', 'sta & gib', 'order', 'family']
|
[['1968', '( 20.01 )', 'nor', 'tragopan satyra', '( linnaeus , 1758 )', '1c', '92', '143', '179', '0', 'galliformes', 'phasianidae'], ['1968', '( 23.04 )', 'nor', 'lophophorus sclateri', 'jerdon , 1870', '4n', '92 g', '150', '186', '0', 'galliformes', 'phasianidae'], ['1968', '( 07.12 )', 'nor', 'liocichla phoenicea', '( gould , 1837 )', '2c', '99', '198', '248', '187', 'passeriformes', 'timaliidae'], ['1968', '( 28.12 )', 'nor', 'liocichla phoenicea', '( gould , 1837 )', '20c', '0', '0', '0', '0', 'passeriformes', 'timaliidae'], ['1969', '( 20.01 )', 'nor', 'liocichla phoenicea', '( gould , 1837 )', '1.50 n', '0', '0', '0', '0', 'passeriformes', 'timaliidae'], ['1969', '( 05.08 )', 'nor', 'strix aluco', 'linnaeus , 1758', '15c', '0', '0', '0', '0', 'strigiformes', 'strigidae'], ['1970', '( 19.06 )', 'nor', 'lophophorus sclateri', 'jerdon , 1870', '20c', '0', '0', '0', '0', 'galliformes', 'phasianidae'], ['1970', '( 20.09 )', 'nor', 'tragopan satyra', '( linnaeus , 1758 )', '85c', '0', '0', '0', '0', 'galliformes', 'phasianidae'], ['1970', '( 02.11 )', 'nor', 'tragopan satyra', '( linnaeus , 1758 )', '20c', '0', '0', '0', '0', 'galliformes', 'phasianidae'], ['1971', '( 01.07 )', 'nor', 'lophophorus impejanus', '( latham , 1790 )', '55c', '0', '0', '0', '0', 'galliformes', 'phasianidae'], ['1982', '( 19.04 )', 'nor', 'chloropsis hardwickii', 'jardine & selby , 1830', '2n', '0', '0', '0', '0', 'passeriformes', 'irenidae'], ['1985', '( 29.11 )', 'nor', 'lagopus lagopus', '( linnaeus , 1758 )', '1n', '0', '0', '0', '0', 'galliformes', 'tetraonidae'], ['1985', '( 06.12 )', 'nor', 'anas platyrhynchos', 'linnaeus , 1758', '50c', '0', '0', '0', '0', 'anseriformes', 'anatidae'], ['1987', '( 25.05 )', 'nor', 'phoenicopterus ruber', 'linnaeus , 1758', '1n', '0', '0', '0', '0', 'phoenicopteriformes', 'phoenicopteridae'], ['1989', '( 22.11 )', 'nor', 'chrysocolaptes lucidus', '( scopoli , 1786 )', '50c', '0', '0', '0', '0', 'piciformes', 'picidae'], ['1990', '( 21.05 )', 'nor', 'grus japonensis', '( muller , 1776 )', '25n', '0', '0', '0', '0', 'gruiformes', 'gruidae'], ['1993', '( 01.07 )', 'nor', 'grus nigricollis', 'przewalski , 1876', '15n', '0', '0', '0', '0', 'gruiformes', 'gruidae'], ['1995', '( 01.09 )', 'nor', 'megaceryle lugubris', '( temminck , 1834 )', '1n', '0', '0', '0', '0', 'coraciiformes', 'alcedinidae']]
|
1977 baltimore colts season
|
https://en.wikipedia.org/wiki/1977_Baltimore_Colts_season
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-14945608-1.html.csv
|
aggregation
|
the 1977 baltimore colts scored an average of 20.38 points per game .
|
{'scope': 'all', 'col': '4', 'type': 'average', 'result': '20.38', 'subset': None}
|
{'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'result'], 'result': '20.38', 'ind': 0, 'tostr': 'avg { all_rows ; result }'}, '20.38'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; result } ; 20.38 } = true', 'tointer': 'the average of the result record of all rows is 20.38 .'}
|
round_eq { avg { all_rows ; result } ; 20.38 } = true
|
the average of the result record of all rows is 20.38 .
|
2
|
2
|
{'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'result_4': 4, '20.38_5': 5}
|
{'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'result_4': 'result', '20.38_5': '20.38'}
|
{'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'result_4': [0], '20.38_5': [1]}
|
['week', 'date', 'opponent', 'result', 'record', 'game site', 'attendance']
|
[['1', 'september 18 , 1977', 'seattle seahawks', 'w 29 - 14', '1 - 0', 'kingdome', '58991'], ['2', 'september 25 , 1977', 'new york jets', 'w 20 - 12', '2 - 0', 'shea stadium', '43439'], ['3', 'october 2 , 1977', 'buffalo bills', 'w 17 - 14', '3 - 0', 'memorial stadium', '49247'], ['4', 'october 9 , 1977', 'miami dolphins', 'w 45 - 28', '4 - 0', 'memorial stadium', '57829'], ['5', 'october 16 , 1977', 'kansas city chiefs', 'w 17 - 6', '5 - 0', 'arrowhead stadium', '63076'], ['6', 'october 23 , 1977', 'new england patriots', 'l 3 - 17', '5 - 1', 'schaeffer stadium', '60958'], ['7', 'october 30 , 1977', 'pittsburgh steelers', 'w 31 - 21', '6 - 1', 'memorial stadium', '60225'], ['8', 'november 7 , 1977', 'washington redskins', 'w 10 - 3', '7 - 1', 'memorial stadium', '57740'], ['9', 'november 13 , 1977', 'buffalo bills', 'w 31 - 13', '8 - 1', 'rich stadium', '39444'], ['10', 'november 20 , 1977', 'new york jets', 'w 33 - 12', '9 - 1', 'memorial stadium', '50957'], ['11', 'november 27 , 1977', 'denver broncos', 'l 13 - 27', '9 - 2', 'mile high stadium', '74939'], ['12', 'december 5 , 1977', 'miami dolphins', 'l 6 - 17', '9 - 3', 'miami orange bowl', '68977'], ['13', 'december 11 , 1977', 'detroit lions', 'l 10 - 13', '9 - 4', 'memorial stadium', '45124']]
|
1990 fei world equestrian games
|
https://en.wikipedia.org/wiki/1990_FEI_World_Equestrian_Games
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11871903-2.html.csv
|
comparative
|
in the 1990 fei world equestrian games , the united kingdom won more silver medals than finland .
|
{'row_1': '5', 'row_2': '11', 'col': '3', 'col_other': '1', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None}
|
{'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'nation', 'united kingdom'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose nation record fuzzily matches to united kingdom .', 'tostr': 'filter_eq { all_rows ; nation ; united kingdom }'}, 'silver'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; nation ; united kingdom } ; silver }', 'tointer': 'select the rows whose nation record fuzzily matches to united kingdom . take the silver record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'nation', 'finland'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose nation record fuzzily matches to finland .', 'tostr': 'filter_eq { all_rows ; nation ; finland }'}, 'silver'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; nation ; finland } ; silver }', 'tointer': 'select the rows whose nation record fuzzily matches to finland . take the silver record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; nation ; united kingdom } ; silver } ; hop { filter_eq { all_rows ; nation ; finland } ; silver } } = true', 'tointer': 'select the rows whose nation record fuzzily matches to united kingdom . take the silver record of this row . select the rows whose nation record fuzzily matches to finland . take the silver record of this row . the first record is greater than the second record .'}
|
greater { hop { filter_eq { all_rows ; nation ; united kingdom } ; silver } ; hop { filter_eq { all_rows ; nation ; finland } ; silver } } = true
|
select the rows whose nation record fuzzily matches to united kingdom . take the silver record of this row . select the rows whose nation record fuzzily matches to finland . take the silver 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, 'nation_7': 7, 'united kingdom_8': 8, 'silver_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'nation_11': 11, 'finland_12': 12, 'silver_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', 'nation_7': 'nation', 'united kingdom_8': 'united kingdom', 'silver_9': 'silver', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'nation_11': 'nation', 'finland_12': 'finland', 'silver_13': 'silver'}
|
{'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'nation_7': [0], 'united kingdom_8': [0], 'silver_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'nation_11': [1], 'finland_12': [1], 'silver_13': [3]}
|
['nation', 'gold', 'silver', 'bronze', 'total']
|
[['west germany', '4', '4', '4', '12'], ['france', '2', '-', '1', '3'], ['new zealand', '2', '-', '-', '2'], ['sweden', '2', '-', '-', '2'], ['united kingdom', '1', '4', '1', '6'], ['united states', '1', '-', '2', '3'], ['switzerland', '1', '-', '1', '2'], ['hungary', '-', '1', '1', '2'], ['netherlands', '-', '1', '1', '2'], ['belgium', '-', '1', '-', '1'], ['finland', '-', '1', '-', '1'], ['soviet union', '-', '1', '-', '1'], ['australia', '-', '-', '1', '1'], ['spain', '-', '-', '1', '1']]
|
2008 - 09 toronto raptors season
|
https://en.wikipedia.org/wiki/2008%E2%80%9309_Toronto_Raptors_season
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-17323092-7.html.csv
|
majority
|
the 2008 - 09 toronto raptors lost most of their games in february .
|
{'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': 'l', 'subset': None}
|
{'func': 'most_str_eq', 'args': ['all_rows', 'score', 'l'], 'result': True, 'ind': 0, 'tointer': 'for the score records of all rows , most of them fuzzily match to l .', 'tostr': 'most_eq { all_rows ; score ; l } = true'}
|
most_eq { all_rows ; score ; l } = true
|
for the score records of all rows , most of them fuzzily match to l .
|
1
|
1
|
{'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'score_3': 3, 'l_4': 4}
|
{'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'score_3': 'score', 'l_4': 'l'}
|
{'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'score_3': [0], 'l_4': [0]}
|
['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record']
|
[['49', 'february 1', 'orlando', 'l 90 - 113 ( ot )', 'josé calderón ( 16 )', 'joey graham ( 12 )', 'josé calderón , will solomon ( 5 )', 'air canada centre 19800', '19 - 30'], ['50', 'february 3', 'cleveland', 'l 83 - 101 ( ot )', 'chris bosh ( 29 )', 'andrea bargnani ( 10 )', 'anthony parker ( 8 )', 'quicken loans arena 20562', '19 - 31'], ['51', 'february 4', 'la lakers', 'l 107 - 115 ( ot )', 'joey graham ( 24 )', "andrea bargnani , jermaine o'neal ( 9 )", 'anthony parker ( 9 )', 'air canada centre 19800', '19 - 32'], ['52', 'february 6', 'new orleans', 'l 92 - 101 ( ot )', "jermaine o'neal ( 24 )", 'jamario moon ( 7 )', 'josé calderón ( 9 )', 'new orleans arena 17319', '19 - 33'], ['53', 'february 7', 'memphis', 'l 70 - 78 ( ot )', 'josé calderón ( 18 )', 'andrea bargnani , jamario moon ( 9 )', 'josé calderón ( 5 )', 'fedexforum 11498', '19 - 34'], ['54', 'february 10', 'minnesota', 'w 110 - 102 ( ot )', 'joey graham ( 24 )', 'jamario moon ( 9 )', 'josé calderón ( 9 )', 'target center 12722', '20 - 34'], ['55', 'february 11', 'san antonio', 'w 91 - 89 ( ot )', 'andrea bargnani ( 23 )', "jermaine o'neal ( 10 )", 'anthony parker ( 4 )', 'air canada centre 18909', '21 - 34'], ['56', 'february 18', 'cleveland', 'l 76 - 93 ( ot )', 'joey graham ( 15 )', 'anthony parker ( 7 )', 'shawn marion ( 6 )', 'air canada centre 19800', '21 - 35'], ['57', 'february 20', 'new york', 'l 97 - 127 ( ot )', 'joey graham ( 19 )', 'shawn marion ( 12 )', 'josé calderón ( 10 )', 'madison square garden 19763', '21 - 36'], ['58', 'february 22', 'new york', 'w 111 - 100 ( ot )', 'andrea bargnani ( 28 )', 'shawn marion ( 15 )', 'josé calderón ( 11 )', 'air canada centre 19800', '22 - 36'], ['59', 'february 24', 'minnesota', 'w 118 - 110 ( ot )', 'andrea bargnani , chris bosh ( 26 )', 'shawn marion ( 8 )', 'josé calderón ( 13 )', 'air canada centre 17457', '23 - 36']]
|
1998 - 99 european challenge cup pool stage
|
https://en.wikipedia.org/wiki/1998%E2%80%9399_European_Challenge_Cup_pool_stage
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-28204447-3.html.csv
|
aggregation
|
the six teams that competed in the 1998-99 european challenge , cup pool stage , got a total of 21 wins between them .
|
{'scope': 'all', 'col': '3', 'type': 'sum', 'result': '21', 'subset': None}
|
{'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'w'], 'result': '21', 'ind': 0, 'tostr': 'sum { all_rows ; w }'}, '21'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; w } ; 21 } = true', 'tointer': 'the sum of the w record of all rows is 21 .'}
|
round_eq { sum { all_rows ; w } ; 21 } = true
|
the sum of the w record of all rows is 21 .
|
2
|
2
|
{'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'w_4': 4, '21_5': 5}
|
{'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'w_4': 'w', '21_5': '21'}
|
{'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'w_4': [0], '21_5': [1]}
|
['team', 'p', 'w', 'd', 'l', 'tries for', 'tries against', 'try diff', 'points for', 'points against', 'points diff', 'pts']
|
[['brive', '6', '5', '0', '1', '35', '14', '+ 21', '241', '102', '+ 139', '10'], ['agen', '6', '4', '0', '2', '30', '11', '+ 19', '231', '93', '+ 138', '8'], ['pau', '6', '4', '0', '2', '25', '8', '+ 17', '211', '87', '+ 124', '8'], ['biarritz', '6', '4', '0', '2', '30', '14', '+ 16', '187', '124', '+ 63', '8'], ['bridgend rfc', '6', '2', '0', '4', '19', '28', '9', '158', '206', '48', '4'], ['dinamo bucureşti', '6', '2', '0', '4', '19', '31', '12', '131', '246', '115', '4']]
|
atlanta falcons draft history
|
https://en.wikipedia.org/wiki/Atlanta_Falcons_draft_history
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15198842-8.html.csv
|
aggregation
|
the average pick for the atlanta falcons draft history is about 13.14 .
|
{'scope': 'all', 'col': '2', 'type': 'average', 'result': '13.14', 'subset': None}
|
{'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'pick'], 'result': '13.14', 'ind': 0, 'tostr': 'avg { all_rows ; pick }'}, '13.14'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; pick } ; 13.14 } = true', 'tointer': 'the average of the pick record of all rows is 13.14 .'}
|
round_eq { avg { all_rows ; pick } ; 13.14 } = true
|
the average of the pick record of all rows is 13.14 .
|
2
|
2
|
{'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'pick_4': 4, '13.14_5': 5}
|
{'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'pick_4': 'pick', '13.14_5': '13.14'}
|
{'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'pick_4': [0], '13.14_5': [1]}
|
['round', 'pick', 'overall', 'name', 'position', 'college']
|
[['2', '13', '39', 'greg marx', 'defensive end', 'notre dame'], ['4', '16', '94', 'tom geredine', 'wide receiver', 'northeast missouri state'], ['6', '12', '142', 'nick bebout', 'offensive tackle', 'wyoming'], ['7', '14', '170', 'george campbell', 'defensive back', 'iowa state'], ['8', '13', '195', 'tom reed', 'guard', 'arkansas'], ['9', '12', '220', 'russ ingram', 'center', 'texas tech'], ['10', '14', '248', 'nick mike - mayer', 'kicker', 'temple'], ['11', '13', '273', 'byron buelow', 'defensive back', 'wisconsinla crosse'], ['12', '12', '298', 'mike samples', 'linebacker', 'drake'], ['13', '14', '326', 'chris stecher', 'offensive tackle', 'claremont mckenna'], ['14', '13', '351', 'john madeya', 'quarterback', 'louisville'], ['15', '12', '376', 'thomas gage', 'defensive back', 'lamar'], ['16', '14', '404', 'rufus ferguson', 'running back', 'wisconsin'], ['17', '12', '428', 'jim hedge', 'wide receiver', 'arkansas']]
|
2004 belarusian premier league
|
https://en.wikipedia.org/wiki/2004_Belarusian_Premier_League
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14749151-1.html.csv
|
aggregation
|
the average capacity of the venues for the 2004 belarusian premier league is under 10300 .
|
{'scope': 'all', 'col': '4', 'type': 'average', 'result': '10300', 'subset': None}
|
{'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'capacity'], 'result': '10300', 'ind': 0, 'tostr': 'avg { all_rows ; capacity }'}, '10300'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; capacity } ; 10300 } = true', 'tointer': 'the average of the capacity record of all rows is 10300 .'}
|
round_eq { avg { all_rows ; capacity } ; 10300 } = true
|
the average of the capacity record of all rows is 10300 .
|
2
|
2
|
{'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'capacity_4': 4, '10300_5': 5}
|
{'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'capacity_4': 'capacity', '10300_5': '10300'}
|
{'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'capacity_4': [0], '10300_5': [1]}
|
['team', 'location', 'venue', 'capacity', 'position in 2003']
|
[['gomel', 'gomel', 'central , gomel', '11800', '1'], ['bate', 'borisov', 'city stadium , borisov', '5500', '2'], ['dinamo minsk', 'minsk', 'dinamo , minsk', '41040', '3'], ['torpedo - ska', 'minsk', 'torpedo , minsk', '5200', '4'], ['shakhtyor', 'soligorsk', 'stroitel', '5000', '5'], ['torpedo', 'zhodino', 'torpedo , zhodino', '3020', '6'], ['neman', 'grodno', 'neman', '6300', '7'], ['naftan', 'novopolotsk', 'atlant', '6500', '8'], ['dnepr - transmash', 'mogilev', 'spartak , mogilev', '11200', '9'], ['belshina', 'bobruisk', 'spartak , bobruisk', '3550', '10'], ['dinamo brest', 'brest', 'osk brestskiy', '10080', '11'], ['zvezda - va - bgu', 'minsk', 'traktor', '17600', '12'], ['darida', 'minsk raion', 'darida', '6000', '13'], ['slavia', 'mozyr', 'yunost', '5500', '14'], ['lokomotiv', 'vitebsk', 'central , vitebsk', '8300', 'first league , 1'], ['mtz - ripo', 'minsk', 'traktor', '17600', 'first league , 2']]
|
1939 vfl season
|
https://en.wikipedia.org/wiki/1939_VFL_season
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10806852-7.html.csv
|
aggregation
|
the average crowd attendance for the 1939 vfl season was 17,750 .
|
{'scope': 'all', 'col': '6', 'type': 'average', 'result': '17750', 'subset': None}
|
{'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'crowd'], 'result': '17750', 'ind': 0, 'tostr': 'avg { all_rows ; crowd }'}, '17750'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; crowd } ; 17750 } = true', 'tointer': 'the average of the crowd record of all rows is 17750 .'}
|
round_eq { avg { all_rows ; crowd } ; 17750 } = true
|
the average of the crowd record of all rows is 17750 .
|
2
|
2
|
{'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'crowd_4': 4, '17750_5': 5}
|
{'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'crowd_4': 'crowd', '17750_5': '17750'}
|
{'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'crowd_4': [0], '17750_5': [1]}
|
['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date']
|
[['geelong', '17.13 ( 115 )', 'north melbourne', '14.13 ( 97 )', 'corio oval', '8000', '3 june 1939'], ['fitzroy', '14.15 ( 99 )', 'melbourne', '18.14 ( 122 )', 'brunswick street oval', '11000', '3 june 1939'], ['south melbourne', '8.14 ( 62 )', 'st kilda', '13.17 ( 95 )', 'lake oval', '15000', '3 june 1939'], ['hawthorn', '12.15 ( 87 )', 'footscray', '7.23 ( 65 )', 'glenferrie oval', '12500', '3 june 1939'], ['richmond', '6.17 ( 53 )', 'collingwood', '12.17 ( 89 )', 'punt road oval', '40000', '3 june 1939'], ['essendon', '10.12 ( 72 )', 'carlton', '10.18 ( 78 )', 'windy hill', '20000', '3 june 1939']]
|
18 to life
|
https://en.wikipedia.org/wiki/18_to_Life
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-25304789-1.html.csv
|
aggregation
|
the sitcom 18 to life had on average a rating around 0.6 among its five first episodes .
|
{'scope': 'all', 'col': '4', 'type': 'average', 'result': '0.6', 'subset': None}
|
{'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'rating'], 'result': '0.6', 'ind': 0, 'tostr': 'avg { all_rows ; rating }'}, '0.6'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; rating } ; 0.6 } = true', 'tointer': 'the average of the rating record of all rows is 0.6 .'}
|
round_eq { avg { all_rows ; rating } ; 0.6 } = true
|
the average of the rating record of all rows is 0.6 .
|
2
|
2
|
{'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'rating_4': 4, '0.6_5': 5}
|
{'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'rating_4': 'rating', '0.6_5': '0.6'}
|
{'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'rating_4': [0], '0.6_5': [1]}
|
['order', 'episode', 'us air date', 'rating', 'share', 'rating / share ( 1849 )', 'viewers ( millions )', 'rank ( timeslot )']
|
[['1', 'a modest proposal', 'august 3 , 2010', '0.7', '1', '0.4 / 1', '1.010', '5'], ['2', 'no strings attached', 'august 3 , 2010', '0.6', '1', '0.3 / 1', '0.862', '5'], ['3', "it 's my party", 'august 10 , 2010', '0.6', '1', '0.3 / 1', '0.747', '5'], ['4', 'detour', 'august 10 , 2010', '0.5', '1', '0.3 / 1', '0.776', '5'], ['5', 'baby got bank', 'august 17 , 2010', '0.5', '1', '0.3 / 1', '0.802', '5']]
|
2007 - 08 portland trail blazers season
|
https://en.wikipedia.org/wiki/2007%E2%80%9308_Portland_Trail_Blazers_season
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-11964047-8.html.csv
|
aggregation
|
during the 2007-2008 season , the portland trail blazers ' total attendance at the rose garden was 121,570 .
|
{'scope': 'subset', 'col': '7', 'type': 'sum', 'result': '121570', 'subset': {'col': '7', 'criterion': 'fuzzily_match', 'value': 'rose garden'}}
|
{'func': 'round_eq', 'args': [{'func': 'sum', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'attendance', 'rose garden'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; attendance ; rose garden }', 'tointer': 'select the rows whose attendance record fuzzily matches to rose garden .'}, 'attendance'], 'result': '121570', 'ind': 1, 'tostr': 'sum { filter_eq { all_rows ; attendance ; rose garden } ; attendance }'}, '121570'], 'result': True, 'ind': 2, 'tostr': 'round_eq { sum { filter_eq { all_rows ; attendance ; rose garden } ; attendance } ; 121570 } = true', 'tointer': 'select the rows whose attendance record fuzzily matches to rose garden . the sum of the attendance record of these rows is 121570 .'}
|
round_eq { sum { filter_eq { all_rows ; attendance ; rose garden } ; attendance } ; 121570 } = true
|
select the rows whose attendance record fuzzily matches to rose garden . the sum of the attendance record of these rows is 121570 .
|
3
|
3
|
{'eq_2': 2, 'result_3': 3, 'sum_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'attendance_5': 5, 'rose garden_6': 6, 'attendance_7': 7, '121570_8': 8}
|
{'eq_2': 'eq', 'result_3': 'true', 'sum_1': 'sum', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'attendance_5': 'attendance', 'rose garden_6': 'rose garden', 'attendance_7': 'attendance', '121570_8': '121570'}
|
{'eq_2': [3], 'result_3': [], 'sum_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'attendance_5': [0], 'rose garden_6': [0], 'attendance_7': [1], '121570_8': [2]}
|
['', 'date', 'visitor', 'score', 'home', 'leading scorer', 'attendance', 'record', 'streak']
|
[['46', 'february 1', 'new york knicks', 'w 94 - 88 ot', 'portland trail blazers', 'randolph : 25', 'rose garden 20422', '27 - 19', 'w1'], ['47', 'february 4', 'denver nuggets', 'l 105 - 103 ot', 'portland trail blazers', 'anthony : 28', 'rose garden 20320', '27 - 20', 'l1'], ['48', 'february 6', 'chicago bulls', 'w 97 - 100', 'portland trail blazers', 'roy : 28', 'rose garden 20126', '28 - 20', 'w1'], ['49', 'february 8', 'portland trail blazers', 'l 82 - 91', 'detroit pistons', 'aldridge : 22', 'the palace of auburn hills 22076', '28 - 21', 'l1'], ['50', 'february 9', 'portland trail blazers', 'l 93 - 101', 'indiana pacers', 'granger : 29', 'conseco fieldhouse 14130', '28 - 22', 'l2'], ['51', 'february 11', 'portland trail blazers', 'l 83 - 95', 'houston rockets', 'yao : 25', 'toyota center 14710', '28 - 23', 'l3'], ['52', 'february 13', 'portland trail blazers', 'l 76 - 96', 'dallas mavericks', 'nowitzki : 37', 'american airlines center 20159', '28 - 24', 'l4'], ['53', 'february 19', 'sacramento kings', 'l 105 - 94', 'portland trail blazers', 'artest : 24', 'rose garden 19980', '28 - 25', 'l5'], ['54', 'february 21', 'seattle supersonics', 'w 88 - 92', 'portland trail blazers', 'durant : 20', 'rose garden 20168', '29 - 25', 'w1'], ['55', 'february 22', 'portland trail blazers', 'l 87 - 99', 'seattle supersonics', 'outlaw : 26', 'keyarena 16640', '29 - 26', 'l1'], ['56', 'february 24', 'boston celtics', 'l 112 - 102', 'portland trail blazers', 'pierce : 30', 'rose garden 20554', '29 - 27', 'l2'], ['57', 'february 26', 'portland trail blazers', 'l 83 - 96', 'los angeles lakers', 'bryant : 30', 'staples center 18997', '29 - 28', 'l3'], ['58', 'february 27', 'portland trail blazers', 'w 82 - 80', 'los angeles clippers', 'maggette : 32', 'staples center 16494', '30 - 28', 'w1']]
|
1971 vfl season
|
https://en.wikipedia.org/wiki/1971_VFL_season
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10826072-3.html.csv
|
majority
|
the majority of the games in the 1971 season had over 10,000 attendees in the crowd .
|
{'scope': 'all', 'col': '6', 'most_or_all': 'most', 'criterion': 'greater_than', 'value': '10000', 'subset': None}
|
{'func': 'most_greater', 'args': ['all_rows', 'crowd', '10000'], 'result': True, 'ind': 0, 'tointer': 'for the crowd records of all rows , most of them are greater than 10000 .', 'tostr': 'most_greater { all_rows ; crowd ; 10000 } = true'}
|
most_greater { all_rows ; crowd ; 10000 } = true
|
for the crowd records of all rows , most of them are greater than 10000 .
|
1
|
1
|
{'most_greater_0': 0, 'result_1': 1, 'all_rows_2': 2, 'crowd_3': 3, '10000_4': 4}
|
{'most_greater_0': 'most_greater', 'result_1': 'true', 'all_rows_2': 'all_rows', 'crowd_3': 'crowd', '10000_4': '10000'}
|
{'most_greater_0': [1], 'result_1': [], 'all_rows_2': [0], 'crowd_3': [0], '10000_4': [0]}
|
['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date']
|
[['footscray', '14.15 ( 99 )', 'south melbourne', '14.9 ( 93 )', 'western oval', '15003', '17 april 1971'], ['fitzroy', '17.26 ( 128 )', 'north melbourne', '14.10 ( 94 )', 'junction oval', '8917', '17 april 1971'], ['hawthorn', '16.19 ( 115 )', 'geelong', '16.11 ( 107 )', 'glenferrie oval', '14090', '17 april 1971'], ['essendon', '9.12 ( 66 )', 'collingwood', '9.12 ( 66 )', 'windy hill', '22421', '17 april 1971'], ['melbourne', '19.13 ( 127 )', 'carlton', '15.10 ( 100 )', 'mcg', '42885', '17 april 1971'], ['richmond', '10.8 ( 68 )', 'st kilda', '6.13 ( 49 )', 'vfl park', '33489', '17 april 1971']]
|
1986 seattle seahawks season
|
https://en.wikipedia.org/wiki/1986_Seattle_Seahawks_season
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13258818-2.html.csv
|
count
|
during the 1986 seattle seahawks season , 3 of the games played at the kingdome were attended by less than 62000 people .
|
{'scope': 'subset', 'criterion': 'less_than', 'value': '62000', 'result': '3', 'col': '7', 'subset': {'col': '5', 'criterion': 'equal', 'value': 'kingdome'}}
|
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_less', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'game site', 'kingdome'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; game site ; kingdome }', 'tointer': 'select the rows whose game site record fuzzily matches to kingdome .'}, 'attendance', '62000'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose game site record fuzzily matches to kingdome . among these rows , select the rows whose attendance record is less than 62000 .', 'tostr': 'filter_less { filter_eq { all_rows ; game site ; kingdome } ; attendance ; 62000 }'}], 'result': '3', 'ind': 2, 'tostr': 'count { filter_less { filter_eq { all_rows ; game site ; kingdome } ; attendance ; 62000 } }', 'tointer': 'select the rows whose game site record fuzzily matches to kingdome . among these rows , select the rows whose attendance record is less than 62000 . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_less { filter_eq { all_rows ; game site ; kingdome } ; attendance ; 62000 } } ; 3 } = true', 'tointer': 'select the rows whose game site record fuzzily matches to kingdome . among these rows , select the rows whose attendance record is less than 62000 . the number of such rows is 3 .'}
|
eq { count { filter_less { filter_eq { all_rows ; game site ; kingdome } ; attendance ; 62000 } } ; 3 } = true
|
select the rows whose game site record fuzzily matches to kingdome . among these rows , select the rows whose attendance record is less than 62000 . the number of such rows is 3 .
|
4
|
4
|
{'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_less_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'game site_6': 6, 'kingdome_7': 7, 'attendance_8': 8, '62000_9': 9, '3_10': 10}
|
{'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_less_1': 'filter_less', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'game site_6': 'game site', 'kingdome_7': 'kingdome', 'attendance_8': 'attendance', '62000_9': '62000', '3_10': '3'}
|
{'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_less_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'game site_6': [0], 'kingdome_7': [0], 'attendance_8': [1], '62000_9': [1], '3_10': [3]}
|
['week', 'date', 'opponent', 'result', 'game site', 'record', 'attendance']
|
[['1', 'september 7 , 1986', 'pittsburgh steelers', 'w 30 - 0', 'kingdome', '1 - 0', '61461'], ['2', 'september 14 , 1986', 'kansas city chiefs', 'w 23 - 17', 'kingdome', '2 - 0', '61068'], ['3', 'september 21 , 1986', 'new england patriots', 'w 38 - 31', 'sullivan stadium', '3 - 0', '58977'], ['4', 'september 28 , 1986', 'washington redskins', 'l 14 - 19', 'robert f kennedy memorial stadium', '3 - 1', '54157'], ['5', 'october 6 , 1986', 'san diego chargers', 'w 33 - 7', 'kingdome', '4 - 1', '63207'], ['6', 'october 12 , 1986', 'los angeles raiders', 'l 10 - 14', 'los angeles memorial coliseum', '4 - 2', '70635'], ['7', 'october 19 , 1986', 'new york giants', 'w 17 - 12', 'kingdome', '5 - 2', '62282'], ['8', 'october 26 , 1986', 'denver broncos', 'l 13 - 20', 'mile high stadium', '5 - 3', '76089'], ['9', 'november 2 , 1986', 'new york jets', 'l 7 - 38', 'kingdome', '5 - 4', '62497'], ['10', 'november 9 , 1986', 'kansas city chiefs', 'l 7 - 27', 'arrowhead stadium', '5 - 5', '53268'], ['11', 'november 16 , 1986', 'cincinnati bengals', 'l 7 - 34', 'riverfront stadium', '5 - 6', '54410'], ['12', 'november 23 , 1986', 'philadelphia eagles', 'w 24 - 20', 'kingdome', '6 - 6', '55786'], ['13', 'november 27 , 1986', 'dallas cowboys', 'w 31 - 14', 'texas stadium', '7 - 6', '58020'], ['14', 'december 8 , 1986', 'los angeles raiders', 'w 37 - 0', 'kingdome', '8 - 6', '62923'], ['15', 'december 14 , 1986', 'san diego chargers', 'w 34 - 24', 'jack murphy stadium', '9 - 6', '47096'], ['16', 'december 20 , 1986', 'denver broncos', 'w 41 - 16', 'kingdome', '10 - 6', '63697']]
|
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
|
count
|
one member-elect of the house of representatives was from the whig party .
|
{'scope': 'all', 'criterion': 'equal', 'value': 'whig', 'result': '1', 'col': '2', 'subset': None}
|
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'party', 'whig'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose party record fuzzily matches to whig .', 'tostr': 'filter_eq { all_rows ; party ; whig }'}], 'result': '1', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; party ; whig } }', 'tointer': 'select the rows whose party record fuzzily matches to whig . the number of such rows is 1 .'}, '1'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; party ; whig } } ; 1 } = true', 'tointer': 'select the rows whose party record fuzzily matches to whig . the number of such rows is 1 .'}
|
eq { count { filter_eq { all_rows ; party ; whig } } ; 1 } = true
|
select the rows whose party record fuzzily matches to whig . the number of such rows is 1 .
|
3
|
3
|
{'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'party_5': 5, 'whig_6': 6, '1_7': 7}
|
{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'party_5': 'party', 'whig_6': 'whig', '1_7': '1'}
|
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'party_5': [0], 'whig_6': [0], '1_7': [2]}
|
['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 take office'], ['william dowse', 'federalist', 'ny - 15', 'december 15 to 17 , 1812', '13th', 'died on february 18 , 1813'], ['richard p giles', 'democratic', 'mo - 1', 'november 3 , 1896', '55th', 'died november 17 , 1896'], ['samuel marx', 'democratic', 'ny - 19', 'november 7 , 1922', '68th', 'died november 30 , 1922'], ['washington poe', 'whig', 'ga - 3', 'november 5 , 1844', '29th', 'resigned before taking office'], ['jack swigert', 'republican', 'co - 6', 'november 2 , 1982', '98th', 'died before taking office']]
|
flavio cipolla
|
https://en.wikipedia.org/wiki/Flavio_Cipolla
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16474033-3.html.csv
|
unique
|
for flavio cipolla 's tournaments , of the ones in italy , the only time his opponent was marcel granollers was on may 30 , 2006 .
|
{'scope': 'subset', 'row': '1', 'col': '4', 'col_other': '1,2', 'criterion': 'equal', 'value': 'marcel granollers', 'subset': {'col': '2', 'criterion': 'fuzzily_match', 'value': 'italy'}}
|
{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'tournament', 'italy'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; tournament ; italy }', 'tointer': 'select the rows whose tournament record fuzzily matches to italy .'}, 'opponent', 'marcel granollers'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose tournament record fuzzily matches to italy . among these rows , select the rows whose opponent record fuzzily matches to marcel granollers .', 'tostr': 'filter_eq { filter_eq { all_rows ; tournament ; italy } ; opponent ; marcel granollers }'}], 'result': True, 'ind': 2, 'tostr': 'only { filter_eq { filter_eq { all_rows ; tournament ; italy } ; opponent ; marcel granollers } }', 'tointer': 'select the rows whose tournament record fuzzily matches to italy . among these rows , select the rows whose opponent record fuzzily matches to marcel granollers . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'tournament', 'italy'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; tournament ; italy }', 'tointer': 'select the rows whose tournament record fuzzily matches to italy .'}, 'opponent', 'marcel granollers'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose tournament record fuzzily matches to italy . among these rows , select the rows whose opponent record fuzzily matches to marcel granollers .', 'tostr': 'filter_eq { filter_eq { all_rows ; tournament ; italy } ; opponent ; marcel granollers }'}, 'date'], 'result': '30 may 2006', 'ind': 3, 'tostr': 'hop { filter_eq { filter_eq { all_rows ; tournament ; italy } ; opponent ; marcel granollers } ; date }'}, '30 may 2006'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { filter_eq { filter_eq { all_rows ; tournament ; italy } ; opponent ; marcel granollers } ; date } ; 30 may 2006 }', 'tointer': 'the date record of this unqiue row is 30 may 2006 .'}], 'result': True, 'ind': 5, 'tostr': 'and { only { filter_eq { filter_eq { all_rows ; tournament ; italy } ; opponent ; marcel granollers } } ; eq { hop { filter_eq { filter_eq { all_rows ; tournament ; italy } ; opponent ; marcel granollers } ; date } ; 30 may 2006 } } = true', 'tointer': 'select the rows whose tournament record fuzzily matches to italy . among these rows , select the rows whose opponent record fuzzily matches to marcel granollers . there is only one such row in the table . the date record of this unqiue row is 30 may 2006 .'}
|
and { only { filter_eq { filter_eq { all_rows ; tournament ; italy } ; opponent ; marcel granollers } } ; eq { hop { filter_eq { filter_eq { all_rows ; tournament ; italy } ; opponent ; marcel granollers } ; date } ; 30 may 2006 } } = true
|
select the rows whose tournament record fuzzily matches to italy . among these rows , select the rows whose opponent record fuzzily matches to marcel granollers . there is only one such row in the table . the date record of this unqiue row is 30 may 2006 .
|
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, 'tournament_8': 8, 'italy_9': 9, 'opponent_10': 10, 'marcel granollers_11': 11, 'str_eq_4': 4, 'str_hop_3': 3, 'date_12': 12, '30 may 2006_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', 'tournament_8': 'tournament', 'italy_9': 'italy', 'opponent_10': 'opponent', 'marcel granollers_11': 'marcel granollers', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'date_12': 'date', '30 may 2006_13': '30 may 2006'}
|
{'and_5': [6], 'result_6': [], 'only_2': [5], 'filter_str_eq_1': [2, 3], 'filter_str_eq_0': [1], 'all_rows_7': [0], 'tournament_8': [0], 'italy_9': [0], 'opponent_10': [1], 'marcel granollers_11': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'date_12': [3], '30 may 2006_13': [4]}
|
['date', 'tournament', 'surface', 'opponent', 'score']
|
[['30 may 2006', 'turin , italy', 'clay', 'marcel granollers', '6 - 3 , 6 - 3'], ['31 july 2007', 'trani , italy', 'clay', 'pablo andújar', '4 - 6 , 6 - 2 , 6 - 4'], ['4 september 2007', 'genoa , italy', 'clay', 'gianluca naso', '6 - 2 , 6 - 7 ( 4 - 7 ) , 7 - 5'], ['1 january 2008', 'nouméa , new caledonia', 'hard', 'stéphane bohli', '6 - 4 , 7 - 5'], ['6 february 2011', 'burnie , australia', 'hard', 'chris guccione', 'w / o']]
|
2008 - 09 copa del rey
|
https://en.wikipedia.org/wiki/2008%E2%80%9309_Copa_del_Rey
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17074170-4.html.csv
|
comparative
|
elche and numancia scored the same amount of points , zero , during the second leg at the 2008-2009 copa del rey .
|
{'row_1': '15', 'row_2': '16', 'col': '5', 'col_other': '1', 'relation': 'equal', 'record_mentioned': 'yes', 'diff_result': None}
|
{'func': 'and', 'args': [{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'team 1', 'elche'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose team 1 record fuzzily matches to elche .', 'tostr': 'filter_eq { all_rows ; team 1 ; elche }'}, '2nd leg'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; team 1 ; elche } ; 2nd leg }', 'tointer': 'select the rows whose team 1 record fuzzily matches to elche . take the 2nd leg record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'team 1', 'numancia'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose team 1 record fuzzily matches to numancia .', 'tostr': 'filter_eq { all_rows ; team 1 ; numancia }'}, '2nd leg'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; team 1 ; numancia } ; 2nd leg }', 'tointer': 'select the rows whose team 1 record fuzzily matches to numancia . take the 2nd leg record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'eq { hop { filter_eq { all_rows ; team 1 ; elche } ; 2nd leg } ; hop { filter_eq { all_rows ; team 1 ; numancia } ; 2nd leg } }', 'tointer': 'select the rows whose team 1 record fuzzily matches to elche . take the 2nd leg record of this row . select the rows whose team 1 record fuzzily matches to numancia . take the 2nd leg record of this row . the first record fuzzily matches to the second record .'}, {'func': 'and', 'args': [{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'team 1', 'elche'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose team 1 record fuzzily matches to elche .', 'tostr': 'filter_eq { all_rows ; team 1 ; elche }'}, '2nd leg'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; team 1 ; elche } ; 2nd leg }', 'tointer': 'select the rows whose team 1 record fuzzily matches to elche . take the 2nd leg record of this row .'}, '0 - 2'], 'result': True, 'ind': 5, 'tostr': 'eq { hop { filter_eq { all_rows ; team 1 ; elche } ; 2nd leg } ; 0 - 2 }', 'tointer': 'the 2nd leg record of the first row is 0 - 2 .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'team 1', 'numancia'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose team 1 record fuzzily matches to numancia .', 'tostr': 'filter_eq { all_rows ; team 1 ; numancia }'}, '2nd leg'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; team 1 ; numancia } ; 2nd leg }', 'tointer': 'select the rows whose team 1 record fuzzily matches to numancia . take the 2nd leg record of this row .'}, '0 - 2'], 'result': True, 'ind': 6, 'tostr': 'eq { hop { filter_eq { all_rows ; team 1 ; numancia } ; 2nd leg } ; 0 - 2 }', 'tointer': 'the 2nd leg record of the second row is 0 - 2 .'}], 'result': True, 'ind': 7, 'tostr': 'and { eq { hop { filter_eq { all_rows ; team 1 ; elche } ; 2nd leg } ; 0 - 2 } ; eq { hop { filter_eq { all_rows ; team 1 ; numancia } ; 2nd leg } ; 0 - 2 } }', 'tointer': 'the 2nd leg record of the first row is 0 - 2 . the 2nd leg record of the second row is 0 - 2 .'}], 'result': True, 'ind': 8, 'tostr': 'and { eq { hop { filter_eq { all_rows ; team 1 ; elche } ; 2nd leg } ; hop { filter_eq { all_rows ; team 1 ; numancia } ; 2nd leg } } ; and { eq { hop { filter_eq { all_rows ; team 1 ; elche } ; 2nd leg } ; 0 - 2 } ; eq { hop { filter_eq { all_rows ; team 1 ; numancia } ; 2nd leg } ; 0 - 2 } } } = true', 'tointer': 'select the rows whose team 1 record fuzzily matches to elche . take the 2nd leg record of this row . select the rows whose team 1 record fuzzily matches to numancia . take the 2nd leg record of this row . the first record fuzzily matches to the second record . the 2nd leg record of the first row is 0 - 2 . the 2nd leg record of the second row is 0 - 2 .'}
|
and { eq { hop { filter_eq { all_rows ; team 1 ; elche } ; 2nd leg } ; hop { filter_eq { all_rows ; team 1 ; numancia } ; 2nd leg } } ; and { eq { hop { filter_eq { all_rows ; team 1 ; elche } ; 2nd leg } ; 0 - 2 } ; eq { hop { filter_eq { all_rows ; team 1 ; numancia } ; 2nd leg } ; 0 - 2 } } } = true
|
select the rows whose team 1 record fuzzily matches to elche . take the 2nd leg record of this row . select the rows whose team 1 record fuzzily matches to numancia . take the 2nd leg record of this row . the first record fuzzily matches to the second record . the 2nd leg record of the first row is 0 - 2 . the 2nd leg record of the second row is 0 - 2 .
|
13
|
9
|
{'and_8': 8, 'result_9': 9, 'str_eq_4': 4, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_10': 10, 'team 1_11': 11, 'elche_12': 12, '2nd leg_13': 13, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_14': 14, 'team 1_15': 15, 'numancia_16': 16, '2nd leg_17': 17, 'and_7': 7, 'str_eq_5': 5, '0 - 2_18': 18, 'str_eq_6': 6, '0 - 2_19': 19}
|
{'and_8': 'and', 'result_9': 'true', 'str_eq_4': 'str_eq', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_10': 'all_rows', 'team 1_11': 'team 1', 'elche_12': 'elche', '2nd leg_13': '2nd leg', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_14': 'all_rows', 'team 1_15': 'team 1', 'numancia_16': 'numancia', '2nd leg_17': '2nd leg', 'and_7': 'and', 'str_eq_5': 'str_eq', '0 - 2_18': '0 - 2', 'str_eq_6': 'str_eq', '0 - 2_19': '0 - 2'}
|
{'and_8': [9], 'result_9': [], 'str_eq_4': [8], 'str_hop_2': [4, 5], 'filter_str_eq_0': [2], 'all_rows_10': [0], 'team 1_11': [0], 'elche_12': [0], '2nd leg_13': [2], 'str_hop_3': [4, 6], 'filter_str_eq_1': [3], 'all_rows_14': [1], 'team 1_15': [1], 'numancia_16': [1], '2nd leg_17': [3], 'and_7': [8], 'str_eq_5': [7], '0 - 2_18': [5], 'str_eq_6': [7], '0 - 2_19': [6]}
|
['team 1', 'agg', 'team 2', '1st leg', '2nd leg']
|
[['real unión', '( a ) 6 - 6', 'real madrid', '3 - 2', '3 - 4'], ['portugalete', '1 - 7', 'valencia', '1 - 4', '0 - 3'], ['ponferradina', '1 - 4', 'sevilla', '1 - 0', '0 - 4'], ['orihuela', '0 - 1', 'atlético', '0 - 1', '0 - 0'], ['poli ejido', '6 - 1', 'villarreal', '5 - 0', '1 - 1'], ['hércules', '3 - 7', 'valladolid', '1 - 5', '2 - 2'], ['rayo vallecano', '1 - 5', 'almería', '1 - 2', '0 - 3'], ['celta', '2 - 5', 'espanyol', '2 - 2', '0 - 3'], ['castellón', '0 - 4', 'betis', '0 - 2', '0 - 2'], ['real murcia', '2 - 3', 'racing', '2 - 1', '0 - 2'], ['málaga', '1 - 3', 'mallorca', '1 - 1', '0 - 2'], ['athletic', '3 - 2', 'recreativo', '2 - 0', '1 - 2'], ['getafe', '0 - 1', 'osasuna', '0 - 0', '0 - 1'], ['benidorm', '0 - 2', 'barcelona', '0 - 1', '0 - 1'], ['elche', '0 - 4', 'deportivo', '0 - 2', '0 - 2'], ['numancia', '0 - 3', 'sporting', '0 - 1', '0 - 2']]
|
2010 - 11 uae pro - league
|
https://en.wikipedia.org/wiki/2010%E2%80%9311_UAE_Pro-League
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27631756-2.html.csv
|
count
|
adidas was the kitmaker for three teams in the 2010 - 11 uae pro - league .
|
{'scope': 'all', 'criterion': 'equal', 'value': 'adidas', 'result': '3', 'col': '5', 'subset': None}
|
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'kitmaker', 'adidas'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose kitmaker record fuzzily matches to adidas .', 'tostr': 'filter_eq { all_rows ; kitmaker ; adidas }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; kitmaker ; adidas } }', 'tointer': 'select the rows whose kitmaker record fuzzily matches to adidas . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; kitmaker ; adidas } } ; 3 } = true', 'tointer': 'select the rows whose kitmaker record fuzzily matches to adidas . the number of such rows is 3 .'}
|
eq { count { filter_eq { all_rows ; kitmaker ; adidas } } ; 3 } = true
|
select the rows whose kitmaker record fuzzily matches to adidas . 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, 'kitmaker_5': 5, 'adidas_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', 'kitmaker_5': 'kitmaker', 'adidas_6': 'adidas', '3_7': '3'}
|
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'kitmaker_5': [0], 'adidas_6': [0], '3_7': [2]}
|
['team', 'chairman', 'head coach', 'captain', 'kitmaker', 'shirt sponsor']
|
[['al ahli', 'abdullah saeed al naboodah', 'abdul hamid al mistaki', 'fabio cannavaro', 'adidas', 'toshiba'], ['al jazira', 'mansour bin zayed al nahyan', 'abel braga', 'ibrahim diaky', 'adidas', 'ipic'], ['al wahda', 'sheikh saeed bin zayed al nahyan', 'josef hickersberger', 'bashir saeed', 'nike', 'emal'], ['al ain', 'hazza bin zayed al nahyan', 'alexandre gallo', 'ali al wehaibi', 'macron', 'first gulf bank'], ['al sharjah', 'abdullah bin mohammed al thani', 'abdul majid', 'abdullah suhail', 'n / a', 'saif - zone'], ['al nasr', 'maktoum bin hasher bin maktoum al maktoum', 'walter zenga', 'abdallah mousa', 'erreà', 'emirates nbd'], ['ittihad kalba', 'saeed bin saqr al qasimi', 'jorvan vieira', 'gregory dufrennes', 'adidas', 'gillett group'], ['dubai', 'sheikh ahmed bin rashed al maktoum', 'junior dos santos', 'ali hassan', 'umbro', 'n / a'], ['bani yas', 'saif bin zayed al nahyan', 'mahdi ali', 'fawzi bashir', 'erreà', 'secure project management'], ['al wasl', 'sheikh ahmed bin rashed al maktoum', 'khalifa mobarak', 'khalid darwish', 'nike', 'saif belhasa group of companies'], ['al shabab', 'hh sh saeed bin maktoum al maktoum', 'paulo bonamigo', 'adeel abdullah', 'erreà', 'emaratech']]
|
washington redskins draft history
|
https://en.wikipedia.org/wiki/Washington_Redskins_draft_history
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17100961-80.html.csv
|
superlative
|
first lb picked in the 2009 washington redsins draft was cody glenn .
|
{'scope': 'subset', 'col_superlative': '3', 'row_superlative': '3', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '4,5', 'subset': {'col': '5', 'criterion': 'equal', 'value': 'lb'}}
|
{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmin', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'position', 'lb'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; position ; lb }', 'tointer': 'select the rows whose position record fuzzily matches to lb .'}, 'overall'], 'result': None, 'ind': 1, 'tostr': 'argmin { filter_eq { all_rows ; position ; lb } ; overall }'}, 'name'], 'result': 'cody glenn', 'ind': 2, 'tostr': 'hop { argmin { filter_eq { all_rows ; position ; lb } ; overall } ; name }'}, 'cody glenn'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { argmin { filter_eq { all_rows ; position ; lb } ; overall } ; name } ; cody glenn } = true', 'tointer': 'select the rows whose position record fuzzily matches to lb . select the row whose overall record of these rows is minimum . the name record of this row is cody glenn .'}
|
eq { hop { argmin { filter_eq { all_rows ; position ; lb } ; overall } ; name } ; cody glenn } = true
|
select the rows whose position record fuzzily matches to lb . select the row whose overall record of these rows is minimum . the name record of this row is cody glenn .
|
4
|
4
|
{'str_eq_3': 3, 'result_4': 4, 'str_hop_2': 2, 'argmin_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'position_6': 6, 'lb_7': 7, 'overall_8': 8, 'name_9': 9, 'cody glenn_10': 10}
|
{'str_eq_3': 'str_eq', 'result_4': 'true', 'str_hop_2': 'str_hop', 'argmin_1': 'argmin', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'position_6': 'position', 'lb_7': 'lb', 'overall_8': 'overall', 'name_9': 'name', 'cody glenn_10': 'cody glenn'}
|
{'str_eq_3': [4], 'result_4': [], 'str_hop_2': [3], 'argmin_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'position_6': [0], 'lb_7': [0], 'overall_8': [1], 'name_9': [2], 'cody glenn_10': [3]}
|
['round', 'pick', 'overall', 'name', 'position', 'college']
|
[['1', '13', '13', 'brian orakpo', 'de', 'texas'], ['3', '16', '80', 'kevin barnes', 'cb', 'maryland'], ['5', '22', '158', 'cody glenn', 'lb', 'nebraska'], ['6', '13', '186', 'robert henson', 'lb', 'texas christian'], ['7', '12', '221', 'eddie williams', 'te', 'idaho'], ['7', '34', '243', 'marko mitchell', 'wr', 'nevada']]
|
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