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stringlengths 207
5.45k
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stringlengths 37
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stringlengths 43
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stringclasses 15
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international rankings of uruguay
|
https://en.wikipedia.org/wiki/International_rankings_of_Uruguay
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-19948664-2.html.csv
|
count
|
4 of the indexes given were published in the year 2007 .
|
{'scope': 'all', 'criterion': 'fuzzily_match', 'value': '2007', 'result': '4', 'col': '3', 'subset': None}
|
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'year of publication', '2007'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose year of publication record fuzzily matches to 2007 .', 'tostr': 'filter_eq { all_rows ; year of publication ; 2007 }'}], 'result': '4', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; year of publication ; 2007 } }', 'tointer': 'select the rows whose year of publication record fuzzily matches to 2007 . the number of such rows is 4 .'}, '4'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; year of publication ; 2007 } } ; 4 } = true', 'tointer': 'select the rows whose year of publication record fuzzily matches to 2007 . the number of such rows is 4 .'}
|
eq { count { filter_eq { all_rows ; year of publication ; 2007 } } ; 4 } = true
|
select the rows whose year of publication record fuzzily matches to 2007 . 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, 'year of publication_5': 5, '2007_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', 'year of publication_5': 'year of publication', '2007_6': '2007', '4_7': '4'}
|
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'year of publication_5': [0], '2007_6': [0], '4_7': [2]}
|
['index ( year )', 'author / editor / source', 'year of publication', 'countries sampled', 'world ranking ( 1 )', 'ranking la ( 2 )']
|
[['global peace ( 2009 )', 'the economist', '2008', '140', '21st', '2nd'], ['corruption perception ( 2008 ) ( 6 )', 'transparency international', '2008', '180', '23rd', '1st'], ['democracy ( 2006 )', 'the economist', '2007', '167', '23rd', '2nd'], ['prosperity index ( 2008 )', 'legatum institute', '2008', '104', '36th', '3rd'], ['press freedom ( 2007 )', 'reporters without borders', '2007', '169', '37th', '2nd'], ['economic freedom ( 2008 )', 'the wall street journal', '2008', '157', '38th', '3rd'], ['human development ( 2005 )', 'united nations ( undp )', '2007 - 08', '177', '46th', '3rd'], ['quality - of - life ( 2005 )', 'the economist', '2007', '111', '46th', '6th'], ['travel and tourism competitiveness ( 2008 )', 'world economic forum', '2008', '130', '63rd', '7th'], ['global competitiveness ( 2009 - 2010 )', 'world economic forum', '2009 - 10', '131', '65th', '6th']]
|
2008 - 09 nbl season
|
https://en.wikipedia.org/wiki/2008%E2%80%9309_NBL_season
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16653153-21.html.csv
|
superlative
|
the melbourne tigers vs. wollongong hawks game had the highest score count of a team in the 2008 - 09 nbl season .
|
{'scope': 'all', 'col_superlative': '3', 'row_superlative': '5', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '2,4', 'subset': None}
|
{'func': 'and', 'args': [{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'score'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; score }'}, 'home team'], 'result': 'melbourne tigers', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; score } ; home team }'}, 'melbourne tigers'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; score } ; home team } ; melbourne tigers }', 'tointer': 'select the row whose score record of all rows is maximum . the home team record of this row is melbourne tigers .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'score'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; score }'}, 'away team'], 'result': 'wollongong hawks', 'ind': 3, 'tostr': 'hop { argmax { all_rows ; score } ; away team }'}, 'wollongong hawks'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { argmax { all_rows ; score } ; away team } ; wollongong hawks }', 'tointer': 'the away team record of this row is wollongong hawks .'}], 'result': True, 'ind': 5, 'tostr': 'and { eq { hop { argmax { all_rows ; score } ; home team } ; melbourne tigers } ; eq { hop { argmax { all_rows ; score } ; away team } ; wollongong hawks } } = true', 'tointer': 'select the row whose score record of all rows is maximum . the home team record of this row is melbourne tigers . the away team record of this row is wollongong hawks .'}
|
and { eq { hop { argmax { all_rows ; score } ; home team } ; melbourne tigers } ; eq { hop { argmax { all_rows ; score } ; away team } ; wollongong hawks } } = true
|
select the row whose score record of all rows is maximum . the home team record of this row is melbourne tigers . the away team record of this row is wollongong hawks .
|
7
|
6
|
{'and_5': 5, 'result_6': 6, 'str_eq_2': 2, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_7': 7, 'score_8': 8, 'home team_9': 9, 'melbourne tigers_10': 10, 'str_eq_4': 4, 'str_hop_3': 3, 'away team_11': 11, 'wollongong hawks_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', 'score_8': 'score', 'home team_9': 'home team', 'melbourne tigers_10': 'melbourne tigers', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'away team_11': 'away team', 'wollongong hawks_12': 'wollongong hawks'}
|
{'and_5': [6], 'result_6': [], 'str_eq_2': [5], 'str_hop_1': [2], 'argmax_0': [1, 3], 'all_rows_7': [0], 'score_8': [0], 'home team_9': [1], 'melbourne tigers_10': [2], 'str_eq_4': [5], 'str_hop_3': [4], 'away team_11': [3], 'wollongong hawks_12': [4]}
|
['date', 'home team', 'score', 'away team', 'venue', 'box score', 'report']
|
[['17 december', 'gold coast blaze', '91 - 88', 'wollongong hawks', 'gold coast convention centre', 'box score', '-'], ['17 december', 'cairns taipans', '63 - 69', 'melbourne tigers', 'cairns convention centre', 'box score', '-'], ['18 december', 'new zealand breakers', '114 - 70', 'sydney spirit', 'north shore events centre', 'box score', '-'], ['20 december', 'adelaide 36ers', '107 - 104', 'gold coast blaze', 'distinctive homes dome', 'box score', '-'], ['20 december', 'melbourne tigers', '128 - 101', 'wollongong hawks', 'state netball and hockey centre', 'box score', '-'], ['20 december', 'perth wildcats', '94 - 118', 'new zealand breakers', 'challenge stadium', 'box score', '-'], ['20 december', 'south dragons', '88 - 84', 'townsville crocodiles', 'hisense arena', 'box score', '-'], ['21 december', 'sydney spirit', '101 - 90', 'townsville crocodiles', 'state sports centre', 'box score', '-']]
|
franck lagorce
|
https://en.wikipedia.org/wiki/Franck_Lagorce
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1228355-3.html.csv
|
count
|
there were two pescarolo teams participating in the competitions .
|
{'scope': 'all', 'criterion': 'equal', 'value': 'pescarolo sport', 'result': '2', 'col': '2', 'subset': None}
|
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'team', 'pescarolo sport'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose team record fuzzily matches to pescarolo sport .', 'tostr': 'filter_eq { all_rows ; team ; pescarolo sport }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; team ; pescarolo sport } }', 'tointer': 'select the rows whose team record fuzzily matches to pescarolo sport . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; team ; pescarolo sport } } ; 2 } = true', 'tointer': 'select the rows whose team record fuzzily matches to pescarolo sport . the number of such rows is 2 .'}
|
eq { count { filter_eq { all_rows ; team ; pescarolo sport } } ; 2 } = true
|
select the rows whose team record fuzzily matches to pescarolo sport . the number of such rows is 2 .
|
3
|
3
|
{'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'team_5': 5, 'pescarolo sport_6': 6, '2_7': 7}
|
{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'team_5': 'team', 'pescarolo sport_6': 'pescarolo sport', '2_7': '2'}
|
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'team_5': [0], 'pescarolo sport_6': [0], '2_7': [2]}
|
['year', 'team', 'co - drivers', 'class', 'laps', 'pos', 'class pos']
|
[['1994', 'courage compétition', 'henri pescarolo alain ferté', 'lmp1 c90', '142', 'dnf', 'dnf'], ['1995', 'courage compétition', 'henri pescarolo éric bernard', 'wsc', '26', 'dnf', 'dnf'], ['1996', 'la filière elf', 'henri pescarolo emmanuel collard', 'lmp1', '327', '7th', '2nd'], ['1997', 'dams', 'éric bernard jean - christophe boullion', 'gt1', '149', 'dnf', 'dnf'], ['1998', 'nissan motorsports twr', 'john nielsen michael krumm', 'gt1', '342', '5th', '5th'], ['1999', 'amg - mercedes', 'bernd schneider pedro lamy', 'lmgtp', '76', 'dnf', 'dnf'], ['2000', 'team cadillac', 'butch leitzinger andy wallace', 'lmp900', '291', '21st', '11th'], ['2001', 'panoz motorsports', 'david brabham jan magnussen', 'lmp900', '85', 'dnf', 'dnf'], ['2002', 'pescarolo sport', 'sébastien bourdais jean - christophe boullion', 'lmp900', '343', '10th', '9th'], ['2003', 'pescarolo sport', 'stéphane sarrazin jean - christophe boullion', 'lmp900', '356', '8th', '6th']]
|
cities of east asia
|
https://en.wikipedia.org/wiki/Cities_of_East_Asia
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16489766-6.html.csv
|
aggregation
|
for the cities of east asia the total combined population in 2008 was 7062211 .
|
{'scope': 'all', 'col': '5', 'type': 'sum', 'result': '7062211', 'subset': None}
|
{'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'population ( 2008 )'], 'result': '7062211', 'ind': 0, 'tostr': 'sum { all_rows ; population ( 2008 ) }'}, '7062211'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; population ( 2008 ) } ; 7062211 } = true', 'tointer': 'the sum of the population ( 2008 ) record of all rows is 7062211 .'}
|
round_eq { sum { all_rows ; population ( 2008 ) } ; 7062211 } = true
|
the sum of the population ( 2008 ) record of all rows is 7062211 .
|
2
|
2
|
{'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'population (2008)_4': 4, '7062211_5': 5}
|
{'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'population (2008)_4': 'population ( 2008 )', '7062211_5': '7062211'}
|
{'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'population (2008)_4': [0], '7062211_5': [1]}
|
['city', 'korean', 'hancha', 'province', 'population ( 2008 )']
|
[['pyongyang', '평양', '平壤', 'direct - administered city', '3255288'], ['hamhung', '함흥', '咸興', 'south hamgyong', '768551'], ['chongjin', '청진', '清津', 'north hamgyong', '667929'], ['nampo', '남포', '南浦', 'special city', '366341'], ['wonsan', '원산', '元山', 'kangwon', '363127'], ['sinuiju', '신의주', '新義州', 'north pyongan', '359341'], ['tanchon', '단천', '端川', 'south hamgyong', '345876'], ['kaechon', '개천', '价川', 'south pyongan', '319554'], ['kaesong', '개성', '開城', 'special - level city', '308440'], ['sariwon', '사리원', '沙里院', 'north hwanghae', '307764']]
|
2009 isle of man tt
|
https://en.wikipedia.org/wiki/2009_Isle_of_Man_TT
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-21607058-1.html.csv
|
count
|
a total of eight riders in the 2009 isle of man tt recorded no time on friday , june 5th .
|
{'scope': 'all', 'criterion': 'equal', 'value': 'no time', 'result': '8', 'col': '7', 'subset': None}
|
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'fri 5 june', 'no time'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose fri 5 june record fuzzily matches to no time .', 'tostr': 'filter_eq { all_rows ; fri 5 june ; no time }'}], 'result': '8', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; fri 5 june ; no time } }', 'tointer': 'select the rows whose fri 5 june record fuzzily matches to no time . the number of such rows is 8 .'}, '8'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; fri 5 june ; no time } } ; 8 } = true', 'tointer': 'select the rows whose fri 5 june record fuzzily matches to no time . the number of such rows is 8 .'}
|
eq { count { filter_eq { all_rows ; fri 5 june ; no time } } ; 8 } = true
|
select the rows whose fri 5 june record fuzzily matches to no time . the number of such rows is 8 .
|
3
|
3
|
{'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'fri 5 june_5': 5, 'no time_6': 6, '8_7': 7}
|
{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'fri 5 june_5': 'fri 5 june', 'no time_6': 'no time', '8_7': '8'}
|
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'fri 5 june_5': [0], 'no time_6': [0], '8_7': [2]}
|
['rank', 'rider', 'mon 1 june', 'tue 2 june', 'wed 3 june', 'thurs 4 june', 'fri 5 june']
|
[['1', 'cameron donald 1000cc suzuki', "18 ' 16.16 123.912 mph", "18 ' 15.21 124.020 mph", "19 ' 31.12 115.981 mph", "17 ' 13.25 131.457 mph", '-- no time'], ['2', 'john mcguinness 1000cc honda', "17 ' 40.60 128.067 mph", "17 ' 27.56 129.661 mph", "17 ' 23.46 130.171 mph", "17 ' 52.90 126.599 mph", '-- no time'], ['3', 'bruce anstey 1000cc suzuki', "18 ' 29.06 122.471 mph", "17 ' 53.22 126.561 mph", "17 ' 42.12 127.884 mph", "17 ' 23.79 130.129 mph", '-- no time'], ['4', 'guy martin 1000cc honda', "18 ' 02.89 125.431 mph", "17 ' 38.72 128.294 mph", "17 ' 31.56 129.168 mph", "17 ' 33.86 128.886 mph", "17 ' 32.83 129.013 mph"], ['5', 'ian hutchinson 1000cc honda', '-- no time', "17 ' 47.24 127.271 mph", "17 ' 41.46 127.963 mph", "17 ' 32.71 129.027 mph", "17 ' 46.76 127.328 mph"], ['6', 'steve plater 1000cc honda', "18 ' 14.54 124.096 mph", '-- no time', "17 ' 37.42 128.453 mph", "17 ' 33.08 128.982 mph", '-- no time'], ['7', 'conor cummins 1000cc kawasaki', "17 ' 56.57 121.167 mph", '-- no time', "18 ' 10.12 124.599 mph", "17 ' 38.40 128.334 mph", "17 ' 44.59 127.588 mph"], ['8', 'gary johnson 1000cc honda', "18 ' 05.00 125.187 mph", "18 ' 09.82 124.633 mph", "18 ' 15.02 124.042 mph", "17 ' 45.04 127.533 mph", "17 ' 42.87 127.794 mph"], ['9', 'adrian archibald 1000cc suzuki', "17 ' 51.68 126.743 mph", "17 ' 51.15 126.806 mph", "19 ' 04.43 118.687 mph", "17 ' 43.13 127.762 mph", '-- no time'], ['10', 'ian lougher 1000cc yamaha', "18 ' 37.37 121.561 mph", "18 ' 09.20 124.704 mph", "17 ' 50.99 126.825 mph", "17 ' 44.25 127.628 mph", "18 ' 04.02 125.301 mph"], ['11', 'keith amor 1000cc honda', "18 ' 28.55 122.528 mph", "17 ' 58.65 125.924 mph", "17 ' 59.88 125.781 mph", "17 ' 44.48 127.600 mph", "17 ' 55.50 126.293 mph"], ['12', 'ryan farquhar 1000cc kawasaki', "18 ' 11.52 124.440 mph", "18 ' 36.60 121.644 mph", "18 ' 19.47 123.539 mph", "17 ' 58.92 125.893 mph", "17 ' 51.75 126.734 mph"], ['13', 'carl rennie 1000cc honda', "18 ' 30.86 122.273 mph", '-- no time', "18 ' 10.03 124.609 mph", "17 ' 55.85 126.252 mph", "17 ' 53.08 126.578 mph"], ['14', 'michael dunlop 1000cc yamaha', '-- no time', '-- no time', "18 ' 33.73 121.958 mph", "18 ' 22.81 123.165 mph", "18 ' 00.16 125.749 mph"], ['15', 'michael rutter 1000cc suzuki', '-- no time', "18 ' 13.25 124.243 mph", "18 ' 06.24 125.044 mph", "18 ' 02.20 125.511 mph", '-- no time'], ['16', 'dan stewart 1000cc honda', '-- no time', "18 ' 00.57 125.701 mph", "18 ' 12.45 124.333 mph", "18 ' 04.63 125.229 mph", "18 ' 06.61 125.002 mph"], ['17', 'mark miller 1000cc suzuki', "18 ' 56.90 119.743 mph", "18 ' 53.13 119.869 mph", "18 ' 40.52 121.219 mph", "18 ' 14.00 124.157 mph", '-- no time'], ['18', 'mark parrett 1000cc yamaha', "18 ' 45.30 120.704 mph", "18 ' 42.14 121.040 mph", "18 ' 30.84 122.275 mph", "18 ' 15.96 123.935 mph", '-- no time'], ['19', 'john burrows 1000cc suzuki', '-- no time', "18 ' 27.93 122.596 mph", "18 ' 22.11 123.244 mph", "18 ' 19.37 123.551 mph", "18 ' 16.78 123.843 mph"]]
|
1958 - 59 segunda división
|
https://en.wikipedia.org/wiki/1958%E2%80%9359_Segunda_Divisi%C3%B3n
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17695272-2.html.csv
|
unique
|
deportivo alavés is the only club that had 10 wins in the in the 1958 - 59 segunda división .
|
{'scope': 'all', 'row': '13', 'col': '5', 'col_other': '2', 'criterion': 'equal', 'value': '10', 'subset': None}
|
{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'wins', '10'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose wins record is equal to 10 .', 'tostr': 'filter_eq { all_rows ; wins ; 10 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; wins ; 10 } }', 'tointer': 'select the rows whose wins record is equal to 10 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'wins', '10'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose wins record is equal to 10 .', 'tostr': 'filter_eq { all_rows ; wins ; 10 }'}, 'club'], 'result': 'deportivo alavés', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; wins ; 10 } ; club }'}, 'deportivo alavés'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; wins ; 10 } ; club } ; deportivo alavés }', 'tointer': 'the club record of this unqiue row is deportivo alavés .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; wins ; 10 } } ; eq { hop { filter_eq { all_rows ; wins ; 10 } ; club } ; deportivo alavés } } = true', 'tointer': 'select the rows whose wins record is equal to 10 . there is only one such row in the table . the club record of this unqiue row is deportivo alavés .'}
|
and { only { filter_eq { all_rows ; wins ; 10 } } ; eq { hop { filter_eq { all_rows ; wins ; 10 } ; club } ; deportivo alavés } } = true
|
select the rows whose wins record is equal to 10 . there is only one such row in the table . the club record of this unqiue row is deportivo alavés .
|
6
|
5
|
{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'wins_7': 7, '10_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'club_9': 9, 'deportivo alavés_10': 10}
|
{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'wins_7': 'wins', '10_8': '10', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'club_9': 'club', 'deportivo alavés_10': 'deportivo alavés'}
|
{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'wins_7': [0], '10_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'club_9': [2], 'deportivo alavés_10': [3]}
|
['position', 'club', 'played', 'points', 'wins', 'draws', 'losses', 'goals for', 'goals against', 'goal difference']
|
[['1', 'real valladolid', '30', '40', '19', '2', '9', '70', '38', '+ 32'], ['2', 'cd sabadell cf', '30', '39', '16', '7', '7', '55', '35', '+ 20'], ['3', 'sd indautxu', '30', '35', '14', '7', '9', '46', '35', '+ 11'], ['4', 'cd condal', '30', '32', '14', '4', '12', '51', '41', '+ 10'], ['5', 'cd basconia', '30', '32', '12', '8', '10', '37', '43', '- 6'], ['6', 'baracaldo ah', '30', '31', '12', '7', '11', '38', '36', '+ 2'], ['7', 'deportivo la coruña', '30', '30', '13', '4', '13', '54', '49', '+ 5'], ['8', 'club sestao', '30', '30', '11', '8', '11', '41', '36', '+ 5'], ['9', 'real santander', '30', '30', '13', '4', '13', '39', '35', '+ 4'], ['10', 'club ferrol', '30', '27', '11', '5', '14', '43', '47', '- 4'], ['11', 'real avilés cf', '30', '27', '11', '5', '14', '40', '43', '- 3'], ['12', 'cd tarrasa', '30', '27', '12', '3', '15', '40', '56', '- 16'], ['13', 'deportivo alavés', '30', '27', '10', '7', '13', '34', '43', '- 9'], ['14', 'rayo vallecano', '30', '26', '11', '4', '15', '39', '46', '- 7'], ['15', 'gerona cf', '30', '25', '11', '3', '16', '43', '64', '- 21'], ['16', 'real unión club', '30', '22', '8', '6', '16', '34', '57', '- 23']]
|
united states presidential election in new jersey , 2008
|
https://en.wikipedia.org/wiki/United_States_presidential_election_in_New_Jersey%2C_2008
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-20278716-2.html.csv
|
superlative
|
essex county had the greatest percentage of voters voting for obama in the election .
|
{'scope': 'all', 'col_superlative': '2', 'row_superlative': '7', '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', 'obama %'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; obama % }'}, 'county'], 'result': 'essex', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; obama % } ; county }'}, 'essex'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; obama % } ; county } ; essex } = true', 'tointer': 'select the row whose obama % record of all rows is maximum . the county record of this row is essex .'}
|
eq { hop { argmax { all_rows ; obama % } ; county } ; essex } = true
|
select the row whose obama % record of all rows is maximum . the county record of this row is essex .
|
3
|
3
|
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'obama %_5': 5, 'county_6': 6, 'essex_7': 7}
|
{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'obama %_5': 'obama %', 'county_6': 'county', 'essex_7': 'essex'}
|
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'obama %_5': [0], 'county_6': [1], 'essex_7': [2]}
|
['county', 'obama %', 'obama', 'mccain %', 'mccain', 'others %', 'others']
|
[['atlantic', '56.9 %', '67830', '41.8 %', '49902', '1.3 %', '1157'], ['bergen', '54.2 %', '225367', '44.7 %', '186118', '1.1 %', '4424'], ['burlington', '58.6 %', '131219', '40.1 %', '89626', '1.3 %', '2930'], ['camden', '67.2 %', '159259', '31.2 %', '68317', '1.4 %', '3304'], ['cape may', '44.9 %', '22893', '53.5 %', '27288', '1.6 %', '802'], ['cumberland', '60.0 %', '34919', '38.4 %', '22360', '1.6 %', '915'], ['essex', '75.9 %', '240306', '23.4 %', '73975', '0.7 %', '2181'], ['gloucester', '55.2 %', '77267', '43.1 %', '60315', '1.7 %', '2364'], ['hudson', '72.8 %', '154140', '26.2 %', '52354', '1.0 %', '2116'], ['hunterdon', '42.5 %', '29776', '55.8 %', '39092', '1.6 %', '1147'], ['mercer', '67.3 %', '107926', '31.3 %', '50397', '1.4 %', '2229'], ['middlesex', '60.2 %', '193812', '38.4 %', '122586', '1.4 %', '4367'], ['monmouth', '47.5 %', '148737', '51.2 %', '160433', '1.4 %', '4244'], ['morris', '45.4 %', '112275', '53.5 %', '132331', '1.2 %', '2913'], ['ocean', '40.1 %', '110189', '58.4 %', '16067', '1.5 %', '4111'], ['passaic', '60.3 %', '113257', '38.7 %', '71850', '1.0 %', '1904'], ['salem', '50.9 %', '16044', '47.0 %', '14816', '2.1 %', '672'], ['somerset', '52.4 %', '79321', '46.3 %', '70085', '1.3 %', '2024'], ['sussex', '38.8 %', '28840', '59.4 %', '44184', '1.9 %', '1393'], ['union', '63.6 %', '141417', '35.4 %', '78768', '1.0 %', '2241']]
|
rajah broadcasting network
|
https://en.wikipedia.org/wiki/Rajah_Broadcasting_Network
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12379297-4.html.csv
|
majority
|
the majority of stations on the rajah broadcasting network operate as a relay type station .
|
{'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'relay', 'subset': None}
|
{'func': 'most_str_eq', 'args': ['all_rows', 'station type', 'relay'], 'result': True, 'ind': 0, 'tointer': 'for the station type records of all rows , most of them fuzzily match to relay .', 'tostr': 'most_eq { all_rows ; station type ; relay } = true'}
|
most_eq { all_rows ; station type ; relay } = true
|
for the station type records of all rows , most of them fuzzily match to relay .
|
1
|
1
|
{'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'station type_3': 3, 'relay_4': 4}
|
{'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'station type_3': 'station type', 'relay_4': 'relay'}
|
{'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'station type_3': [0], 'relay_4': [0]}
|
['branding', 'callsign', 'frequency', 'power ( kw )', 'station type', 'location']
|
[['rjfm 100.3', 'dzrj - fm', '100.3 mhz', '25 kw', 'originating', 'metro manila'], ['rjfm 91.1 baguio', 'dwdj - fm', '91.1 mhz', '5 kw', 'relay', 'baguio cordillera region'], ['rjfm 96.5 tuguegarao', 'dwrj - fm', '96.5 mhz', '5 kw', 'relay', 'tuguegarao northern luzon region'], ['rjfm 99.1 palawan', 'dyjr - fm', '99.1 mhz', '5 kw', 'relay', 'puerto princesa palawan'], ['rjfm 98.3 iloilo', 'dynj - fm', '98.3 mhz', '5 kw', 'relay', 'iloilo western visayas region'], ['rjfm 99.9 bacolod', 'dyfj - fm', '99.9 mhz', '5 kw', 'relay', 'bacolod western visayas region'], ['rjfm 100.3 cebu', 'dyrj - fm', '100.3 mhz', '20 kw', 'originating', 'cebu central visayas region'], ['rjfm 88.5 cagayan de oro', 'dxrj - fm', '88.5 mhz', '10 kw', 'relay', 'cagayan de oro northern mindanao region'], ['rjfm 100.3 davao', 'dxdj - fm', '100.3 mhz', '20 kw', 'originating', 'davao southern mindanao egion']]
|
2009 - 10 real madrid c.f. season
|
https://en.wikipedia.org/wiki/2009%E2%80%9310_Real_Madrid_C.F._season
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-22914245-9.html.csv
|
aggregation
|
2009 - 10 real madrid c.f. season players averaged a total of 5 goals .
|
{'scope': 'all', 'col': '7', 'type': 'average', 'result': '5', 'subset': None}
|
{'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'total'], 'result': '5', 'ind': 0, 'tostr': 'avg { all_rows ; total }'}, '5'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; total } ; 5 } = true', 'tointer': 'the average of the total record of all rows is 5 .'}
|
round_eq { avg { all_rows ; total } ; 5 } = true
|
the average of the total record of all rows is 5 .
|
2
|
2
|
{'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'total_4': 4, '5_5': 5}
|
{'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'total_4': 'total', '5_5': '5'}
|
{'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'total_4': [0], '5_5': [1]}
|
['r', 'player', 'position', 'league', 'champions league', 'copa del rey', 'total']
|
[['1', 'guti', 'am', '9', '1', '0', '10'], ['2', 'marcelo', 'lb', '9', '0', '0', '9'], ['3', 'kaká', 'am', '6', '2', '0', '8'], ['4', 'cristiano ronaldo', 'wf', '7', '0', '0', '7'], ['4', 'rafael van der vaart', 'am', '7', '0', '0', '7'], ['6', 'esteban granero', 'cm', '6', '0', '0', '6'], ['6', 'gonzalo higuaín', 'cf', '5', '1', '0', '6'], ['8', 'sergio ramos', 'rb', '5', '0', '0', '5'], ['8', 'xabi alonso', 'cm', '5', '0', '0', '5'], ['10', 'karim benzema', 'cf', '3', '1', '0', '4'], ['11', 'ezequiel garay', 'cb', '3', '0', '0', '3'], ['11', 'raúl', 'ss', '1', '2', '0', '3'], ['11', 'álvaro arbeloa', 'fb', '2', '0', '0', '2'], ['11', 'pepe', 'cb', '0', '2', '0', '2'], ['14', 'ruud van nistelrooy', 'cf', '1', '0', '0', '1'], ['14', 'lassana diarra', 'dm', '1', '0', '0', '1']]
|
1979 england rugby union tour of japan , fiji and tonga
|
https://en.wikipedia.org/wiki/1979_England_rugby_union_tour_of_Japan%2C_Fiji_and_Tonga
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18787978-1.html.csv
|
count
|
in the 1979 england rugby union tour of japan , for fiji and tonga , when the against is under 10 , there were 2 times the status was tour match .
|
{'scope': 'subset', 'criterion': 'equal', 'value': 'tour match', 'result': '2', 'col': '5', 'subset': {'col': '2', 'criterion': 'less_than', 'value': '10'}}
|
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'against', '10'], 'result': None, 'ind': 0, 'tostr': 'filter_less { all_rows ; against ; 10 }', 'tointer': 'select the rows whose against record is less than 10 .'}, 'status', 'tour match'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose against record is less than 10 . among these rows , select the rows whose status record fuzzily matches to tour match .', 'tostr': 'filter_eq { filter_less { all_rows ; against ; 10 } ; status ; tour match }'}], 'result': '2', 'ind': 2, 'tostr': 'count { filter_eq { filter_less { all_rows ; against ; 10 } ; status ; tour match } }', 'tointer': 'select the rows whose against record is less than 10 . among these rows , select the rows whose status record fuzzily matches to tour match . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_eq { filter_less { all_rows ; against ; 10 } ; status ; tour match } } ; 2 } = true', 'tointer': 'select the rows whose against record is less than 10 . among these rows , select the rows whose status record fuzzily matches to tour match . the number of such rows is 2 .'}
|
eq { count { filter_eq { filter_less { all_rows ; against ; 10 } ; status ; tour match } } ; 2 } = true
|
select the rows whose against record is less than 10 . among these rows , select the rows whose status record fuzzily matches to tour match . the number of such rows is 2 .
|
4
|
4
|
{'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_str_eq_1': 1, 'filter_less_0': 0, 'all_rows_5': 5, 'against_6': 6, '10_7': 7, 'status_8': 8, 'tour match_9': 9, '2_10': 10}
|
{'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_str_eq_1': 'filter_str_eq', 'filter_less_0': 'filter_less', 'all_rows_5': 'all_rows', 'against_6': 'against', '10_7': '10', 'status_8': 'status', 'tour match_9': 'tour match', '2_10': '2'}
|
{'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_str_eq_1': [2], 'filter_less_0': [1], 'all_rows_5': [0], 'against_6': [0], '10_7': [0], 'status_8': [1], 'tour match_9': [1], '2_10': [3]}
|
['opposing team', 'against', 'date', 'venue', 'status']
|
[["japan ' b '", '7', '10 / 05 / 1979', 'tokyo', 'tour match'], ['japan', '19', '13 / 05 / 1979', 'kintetsu hanazono stadium , osaka', "first ' test '"], ['kyūshū', '3', '16 / 05 / 1979', 'fukuoka', 'tour match'], ['japan', '18', '20 / 05 / 1979', 'olympic stadium , tokyo', "second ' test '"], ['fiji juniors', '22', '25 / 05 / 1979', 'lautoka', 'tour match'], ['fiji', '7', '29 / 05 / 1979', 'national stadium , suva', "' test ' match"], ['tonga', '17', '01 / 06 / 1979', 'teufaiva sport stadium , nuku alofa', "' test ' match"]]
|
list of people in playboy 1990 - 99
|
https://en.wikipedia.org/wiki/List_of_people_in_Playboy_1990%E2%80%9399
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1566850-3.html.csv
|
unique
|
michael jordan was the only interview subject on the 5-92 issue of playboy .
|
{'scope': 'all', 'row': '5', 'col': '4', 'col_other': '1', 'criterion': 'equal', 'value': 'michael jordan', 'subset': None}
|
{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'interview subject', 'michael jordan'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose interview subject record fuzzily matches to michael jordan .', 'tostr': 'filter_eq { all_rows ; interview subject ; michael jordan }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; interview subject ; michael jordan } }', 'tointer': 'select the rows whose interview subject record fuzzily matches to michael jordan . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'interview subject', 'michael jordan'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose interview subject record fuzzily matches to michael jordan .', 'tostr': 'filter_eq { all_rows ; interview subject ; michael jordan }'}, 'date'], 'result': '5 - 92', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; interview subject ; michael jordan } ; date }'}, '5 - 92'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; interview subject ; michael jordan } ; date } ; 5 - 92 }', 'tointer': 'the date record of this unqiue row is 5 - 92 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; interview subject ; michael jordan } } ; eq { hop { filter_eq { all_rows ; interview subject ; michael jordan } ; date } ; 5 - 92 } } = true', 'tointer': 'select the rows whose interview subject record fuzzily matches to michael jordan . there is only one such row in the table . the date record of this unqiue row is 5 - 92 .'}
|
and { only { filter_eq { all_rows ; interview subject ; michael jordan } } ; eq { hop { filter_eq { all_rows ; interview subject ; michael jordan } ; date } ; 5 - 92 } } = true
|
select the rows whose interview subject record fuzzily matches to michael jordan . there is only one such row in the table . the date record of this unqiue row is 5 - 92 .
|
6
|
5
|
{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'interview subject_7': 7, 'michael jordan_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'date_9': 9, '5 - 92_10': 10}
|
{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'interview subject_7': 'interview subject', 'michael jordan_8': 'michael jordan', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'date_9': 'date', '5 - 92_10': '5 - 92'}
|
{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'interview subject_7': [0], 'michael jordan_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'date_9': [2], '5 - 92_10': [3]}
|
['date', 'cover model', 'centerfold model', 'interview subject', '20 questions']
|
[['1 - 92', 'swedish bikini team', 'suzi simpson', 'robin williams', 'woody harrelson'], ['2 - 92', 'rachel williams', 'tanya beyer', 'liz smith', 'jennifer jason leigh'], ['3 - 92', 'anna nicole smith', 'tylyn john', 'lorne michaels', 'forest whitaker'], ['4 - 92', 'wendy kaye', 'cady cantrell', 'jonathan kozol', 'bobcat goldthwait'], ['5 - 92', 'elizabeth gracen', 'anna nicole smith', 'michael jordan', 'john leguizamo'], ['6 - 92', 'corinna harney', 'angela melini', 'ralph nader', 'patrick swayze'], ['7 - 92', 'pamela anderson', 'amanda hope', 'michael keaton', 'nicole kidman'], ['8 - 92', 'margie murphy', 'ashley allen', 'derek humphry', 'catherine crier'], ['9 - 92', 'sandra bernhard', 'morena corwin', 'betty friedan', 'dennis miller'], ['10 - 92', 'cristy thom', 'tiffany m sloan', 'sister souljah', 'tim robbins'], ['11 - 92', 'joan severance', 'stephanie adams', 'william safire', 'patrick stewart'], ['12 - 92', 'sharon stone', 'barbara moore', 'sharon stone', 'helmut newton']]
|
2007 world championships in athletics - men 's 200 metres
|
https://en.wikipedia.org/wiki/2007_World_Championships_in_Athletics_%E2%80%93_Men%27s_200_metres
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18912995-9.html.csv
|
ordinal
|
christopher williams had the fifth fastest react time of all these athletes .
|
{'row': '7', 'col': '4', 'order': '5', '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', 'react', '5'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; react ; 5 }'}, 'name'], 'result': 'christopher williams', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; react ; 5 } ; name }'}, 'christopher williams'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; react ; 5 } ; name } ; christopher williams } = true', 'tointer': 'select the row whose react record of all rows is 5th minimum . the name record of this row is christopher williams .'}
|
eq { hop { nth_argmin { all_rows ; react ; 5 } ; name } ; christopher williams } = true
|
select the row whose react record of all rows is 5th minimum . the name record of this row is christopher williams .
|
3
|
3
|
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'react_5': 5, '5_6': 6, 'name_7': 7, 'christopher williams_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', 'react_5': 'react', '5_6': '5', 'name_7': 'name', 'christopher williams_8': 'christopher williams'}
|
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'react_5': [0], '5_6': [0], 'name_7': [1], 'christopher williams_8': [2]}
|
['lane', 'name', 'nationality', 'react', 'time']
|
[['4', 'tyson gay', 'united states', '0.143', '19.76'], ['5', 'usain bolt', 'jamaica', '0.159', '19.91'], ['6', 'wallace spearmon', 'united states', '0.144', '20.05'], ['8', 'rodney martin', 'united states', '0.186', '20.06'], ['3', 'churandy martina', 'netherlands antilles', '0.144', '20.28'], ['7', 'marvin anderson', 'jamaica', '0.171', '20.28'], ['9', 'christopher williams', 'jamaica', '0.154', '20.57'], ['7', 'anastasios gousis', 'greece', '0.143', '20.75']]
|
rowing at the 2008 summer olympics - women 's single sculls
|
https://en.wikipedia.org/wiki/Rowing_at_the_2008_Summer_Olympics_%E2%80%93_Women%27s_single_sculls
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18662695-8.html.csv
|
comparative
|
julia michalska had a faster time than elana hill in the 2008 summer olympics - women 's single sculls .
|
{'row_1': '2', 'row_2': '6', 'col': '4', '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', 'athlete', 'julia michalska'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose athlete record fuzzily matches to julia michalska .', 'tostr': 'filter_eq { all_rows ; athlete ; julia michalska }'}, 'time'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; athlete ; julia michalska } ; time }', 'tointer': 'select the rows whose athlete record fuzzily matches to julia michalska . take the time record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'athlete', 'elana hill'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose athlete record fuzzily matches to elana hill .', 'tostr': 'filter_eq { all_rows ; athlete ; elana hill }'}, 'time'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; athlete ; elana hill } ; time }', 'tointer': 'select the rows whose athlete record fuzzily matches to elana hill . take the time record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; athlete ; julia michalska } ; time } ; hop { filter_eq { all_rows ; athlete ; elana hill } ; time } } = true', 'tointer': 'select the rows whose athlete record fuzzily matches to julia michalska . take the time record of this row . select the rows whose athlete record fuzzily matches to elana hill . take the time record of this row . the first record is less than the second record .'}
|
less { hop { filter_eq { all_rows ; athlete ; julia michalska } ; time } ; hop { filter_eq { all_rows ; athlete ; elana hill } ; time } } = true
|
select the rows whose athlete record fuzzily matches to julia michalska . take the time record of this row . select the rows whose athlete record fuzzily matches to elana hill . take the time record of this row . the first record is less than the second record .
|
5
|
5
|
{'less_4': 4, 'result_5': 5, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'athlete_7': 7, 'julia michalska_8': 8, 'time_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'athlete_11': 11, 'elana hill_12': 12, 'time_13': 13}
|
{'less_4': 'less', 'result_5': 'true', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'athlete_7': 'athlete', 'julia michalska_8': 'julia michalska', 'time_9': 'time', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'athlete_11': 'athlete', 'elana hill_12': 'elana hill', 'time_13': 'time'}
|
{'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'athlete_7': [0], 'julia michalska_8': [0], 'time_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'athlete_11': [1], 'elana hill_12': [1], 'time_13': [3]}
|
['rank', 'athlete', 'country', 'time', 'notes']
|
[['1', 'michelle guerette', 'united states', '7:28.91', 'sa / b'], ['2', 'julia michalska', 'poland', '7:31.90', 'sa / b'], ['3', 'gabriella bascelli', 'italy', '7:36.68', 'sa / b'], ['4', 'nuria domã\xadnguez', 'spain', '7:49.60', 'sc / d'], ['5', 'inga dudchenko', 'kazakhstan', '8:15.88', 'sc / d'], ['6', 'elana hill', 'zimbabwe', '8:20.84', 'sc / d']]
|
list of vancouver canucks draft picks
|
https://en.wikipedia.org/wiki/List_of_Vancouver_Canucks_draft_picks
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11636955-36.html.csv
|
superlative
|
alexander edler has the highest reg gp value of the players in this draft .
|
{'scope': 'all', 'col_superlative': '5', 'row_superlative': '2', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '3', 'subset': None}
|
{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'reg gp'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; reg gp }'}, 'player'], 'result': 'alexander edler', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; reg gp } ; player }'}, 'alexander edler'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; reg gp } ; player } ; alexander edler } = true', 'tointer': 'select the row whose reg gp record of all rows is maximum . the player record of this row is alexander edler .'}
|
eq { hop { argmax { all_rows ; reg gp } ; player } ; alexander edler } = true
|
select the row whose reg gp record of all rows is maximum . the player record of this row is alexander edler .
|
3
|
3
|
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'reg gp_5': 5, 'player_6': 6, 'alexander edler_7': 7}
|
{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'reg gp_5': 'reg gp', 'player_6': 'player', 'alexander edler_7': 'alexander edler'}
|
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'reg gp_5': [0], 'player_6': [1], 'alexander edler_7': [2]}
|
['rd', 'pick', 'player', 'team ( league )', 'reg gp', 'pl gp']
|
[['1', '26', 'cory schneider', 'phillips academy ( mass )', '98', '10'], ['3', '91', 'alexander edler', 'jamtland ( swe )', '431', '59'], ['4', '125', 'andrew sarauer', 'langley hornets ( bchl )', '0', '0'], ['5', '159', 'mike brown', 'university of michigan ( ncaa )', '39', '2'], ['6', '189', 'julien ellis', 'shawinigan cataractes ( qmjhl )', '0', '0'], ['8', '254', 'david schulz', 'swift current broncos ( whl )', '0', '0'], ['9', '287', 'jannik hansen', 'malmã jr ( swe2 )', '318', '58']]
|
aaron kelly ( singer )
|
https://en.wikipedia.org/wiki/Aaron_Kelly_%28singer%29
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27075510-1.html.csv
|
majority
|
aaron kelly was safe in most of the weeks they performed .
|
{'scope': 'all', 'col': '6', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'safe', 'subset': None}
|
{'func': 'most_str_eq', 'args': ['all_rows', 'result', 'safe'], 'result': True, 'ind': 0, 'tointer': 'for the result records of all rows , most of them fuzzily match to safe .', 'tostr': 'most_eq { all_rows ; result ; safe } = true'}
|
most_eq { all_rows ; result ; safe } = true
|
for the result records of all rows , most of them fuzzily match to safe .
|
1
|
1
|
{'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'result_3': 3, 'safe_4': 4}
|
{'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'result_3': 'result', 'safe_4': 'safe'}
|
{'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'result_3': [0], 'safe_4': [0]}
|
['week', 'theme', 'song choice', 'original artist', 'order', 'result']
|
[['audition', 'n / a', 'the climb', 'miley cyrus', 'n / a', 'advanced'], ['hollywood', 'group round', 'get ready', 'the temptations', 'n / a', 'advanced'], ['hollywood', 'second solo', 'angel', 'sarah mclachlan', 'n / a', 'advanced'], ['top 24 ( 12 men )', 'billboard hot 100 hits', 'here comes goodbye', 'rascal flatts', '2', 'safe'], ['top 20 ( 10 men )', 'billboard hot 100 hits', 'my girl', 'the temptations', '8', 'safe'], ['top 16 ( 8 men )', 'billboard hot 100 hits', "i 'm already there", 'lonestar', '6', 'safe'], ['top 12', 'the rolling stones', 'angie', 'the rolling stones', '11', 'safe'], ['top 11', 'billboard number 1 hits', "i do n't want to miss a thing", 'aerosmith', '4', 'safe'], ['top 10', 'r & b / soul', "ai n't no sunshine", 'bill withers', '10', 'safe'], ['top 9', 'lennonmccartney', 'the long and winding road', 'the beatles', '1', 'bottom 3'], ['top 9', 'elvis presley', 'blue suede shoes', 'carl perkins', '5', 'safe'], ['top 7', 'inspirational', 'i believe i can fly', 'r kelly', '4', 'bottom 3'], ['top 6', 'shania twain', "you 've got a way", 'shania twain', '5', 'safe']]
|
list of the league episodes
|
https://en.wikipedia.org/wiki/List_of_The_League_episodes
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-28348757-3.html.csv
|
unique
|
episode seven was the only episode with a rating number as high as 1.7 million households .
|
{'scope': 'all', 'row': '1', 'col': '8', 'col_other': '1', 'criterion': 'greater_than', 'value': '1.7', 'subset': None}
|
{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'us viewers ( million )', '1.7'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose us viewers ( million ) record is greater than 1.7 .', 'tostr': 'filter_greater { all_rows ; us viewers ( million ) ; 1.7 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_greater { all_rows ; us viewers ( million ) ; 1.7 } }', 'tointer': 'select the rows whose us viewers ( million ) record is greater than 1.7 . there is only one such row in the table .'}, {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'us viewers ( million )', '1.7'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose us viewers ( million ) record is greater than 1.7 .', 'tostr': 'filter_greater { all_rows ; us viewers ( million ) ; 1.7 }'}, 'no'], 'result': '7', 'ind': 2, 'tostr': 'hop { filter_greater { all_rows ; us viewers ( million ) ; 1.7 } ; no }'}, '7'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_greater { all_rows ; us viewers ( million ) ; 1.7 } ; no } ; 7 }', 'tointer': 'the no record of this unqiue row is 7 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_greater { all_rows ; us viewers ( million ) ; 1.7 } } ; eq { hop { filter_greater { all_rows ; us viewers ( million ) ; 1.7 } ; no } ; 7 } } = true', 'tointer': 'select the rows whose us viewers ( million ) record is greater than 1.7 . there is only one such row in the table . the no record of this unqiue row is 7 .'}
|
and { only { filter_greater { all_rows ; us viewers ( million ) ; 1.7 } } ; eq { hop { filter_greater { all_rows ; us viewers ( million ) ; 1.7 } ; no } ; 7 } } = true
|
select the rows whose us viewers ( million ) record is greater than 1.7 . there is only one such row in the table . the no record of this unqiue row is 7 .
|
6
|
5
|
{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_greater_0': 0, 'all_rows_6': 6, 'us viewers (million)_7': 7, '1.7_8': 8, 'eq_3': 3, 'num_hop_2': 2, 'no_9': 9, '7_10': 10}
|
{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_greater_0': 'filter_greater', 'all_rows_6': 'all_rows', 'us viewers (million)_7': 'us viewers ( million )', '1.7_8': '1.7', 'eq_3': 'eq', 'num_hop_2': 'num_hop', 'no_9': 'no', '7_10': '7'}
|
{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_greater_0': [1, 2], 'all_rows_6': [0], 'us viewers (million)_7': [0], '1.7_8': [0], 'eq_3': [4], 'num_hop_2': [3], 'no_9': [2], '7_10': [3]}
|
['no', '-', 'title', 'directed by', 'written by', 'original air date', 'production code', 'us viewers ( million )']
|
[['7', '1', 'vegas draft', 'jeff schaffer', 'jeff schaffer & jackie marcus schaffer', 'september 16 , 2010', 'xle02001', '1.71'], ['8', '2', 'bro - lo el cuã ± ado', 'jeff schaffer', 'jeff schaffer & jackie marcus schaffer', 'september 23 , 2010', 'xle02002', '1.05'], ['9', '3', 'the white knuckler', 'jeff schaffer', 'jeff schaffer & jackie marcus schaffer', 'september 30 , 2010', 'xle02003', '0.89'], ['10', '4', 'the kluneberg', 'jeff schaffer', 'jeff schaffer & jackie marcus schaffer', 'october 7 , 2010', 'xle02004', '0.82'], ['11', '5', 'the marathon', 'jackie marcus schaffer', 'craig digregorio', 'october 14 , 2010', 'xle02005', '0.86'], ['12', '6', 'the anniversary party', 'jeff schaffer', 'nick kroll & paul scheer', 'october 21 , 2010', 'xle02006', '0.62'], ['13', '7', 'ghost monkey', 'jeff schaffer', 'jeff schaffer & jackie marcus schaffer', 'october 28 , 2010', 'xle02007', '0.67'], ['14', '8', 'the tie', 'jackie marcus schaffer', "dan o'keefe", 'november 4 , 2010', 'xle02008', '1.01'], ['15', '9', 'the expert witness', 'jeff schaffer', 'nick kroll & paul scheer', 'november 11 , 2010', 'xle02009', '1.00'], ['16', '10', 'high school reunion', 'jeff schaffer', 'jeff schaffer & jackie marcus schaffer', 'november 18 , 2010', 'xle02010', '1.04'], ['18', '12', 'kegel the elf', 'jeff schaffer', 'jeff schaffer & jackie marcus schaffer', 'december 9 , 2010', 'xle02012', '1.05']]
|
1971 washington redskins season
|
https://en.wikipedia.org/wiki/1971_Washington_Redskins_season
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15093626-2.html.csv
|
superlative
|
the first game of the season , against the st louis cardinals , had the washington redskin 's lowest game attendance of their 1971 season .
|
{'scope': 'all', 'col_superlative': '5', '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', 'attendance'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; attendance }'}, 'opponent'], 'result': 'st louis cardinals', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; attendance } ; opponent }'}, 'st louis cardinals'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmin { all_rows ; attendance } ; opponent } ; st louis cardinals } = true', 'tointer': 'select the row whose attendance record of all rows is minimum . the opponent record of this row is st louis cardinals .'}
|
eq { hop { argmin { all_rows ; attendance } ; opponent } ; st louis cardinals } = true
|
select the row whose attendance record of all rows is minimum . the opponent record of this row is st louis cardinals .
|
3
|
3
|
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'attendance_5': 5, 'opponent_6': 6, 'st louis cardinals_7': 7}
|
{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'attendance_5': 'attendance', 'opponent_6': 'opponent', 'st louis cardinals_7': 'st louis cardinals'}
|
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'attendance_5': [0], 'opponent_6': [1], 'st louis cardinals_7': [2]}
|
['week', 'date', 'opponent', 'result', 'attendance']
|
[['1', 'september 19 , 1971', 'st louis cardinals', 'w 24 - 17', '46805'], ['2', 'september 26 , 1971', 'new york giants', 'w 30 - 3', '62795'], ['3', 'october 3 , 1971', 'dallas cowboys', 'w 20 - 16', '61554'], ['4', 'october 10 , 1971', 'houston oilers', 'w 22 - 13', '53041'], ['5', 'october 17 , 1971', 'st louis cardinals', 'w 20 - 0', '53041'], ['6', 'october 24 , 1971', 'kansas city chiefs', 'l 27 - 20', '51989'], ['7', 'october 31 , 1971', 'new orleans saints', 'w 24 - 14', '53041'], ['8', 'november 7 , 1971', 'philadelphia eagles', 't 7 - 7', '53041'], ['9', 'november 14 , 1971', 'chicago bears', 'l 16 - 15', '55049'], ['10', 'november 21 , 1971', 'dallas cowboys', 'l 13 - 0', '53041'], ['11', 'november 28 , 1971', 'philadelphia eagles', 'w 20 - 13', '65358'], ['12', 'december 5 , 1971', 'new york giants', 'w 23 - 7', '53041'], ['13', 'december 13 , 1971', 'los angeles rams', 'w 38 - 24', '80402'], ['14', 'december 19 , 1971', 'cleveland browns', 'l 20 - 13', '53041']]
|
claudio suárez
|
https://en.wikipedia.org/wiki/Claudio_Su%C3%A1rez
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1007636-2.html.csv
|
comparative
|
claudio suárez ' first goal was 14 days before his second goal .
|
{'row_1': '1', 'row_2': '2', 'col': '2', 'col_other': '2', 'relation': 'diff', 'record_mentioned': 'no', 'diff_result': {'diff_value': '14 days', 'bigger': 'row2'}}
|
{'func': 'eq', 'args': [{'func': 'diff', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', 'november 8 , 1992'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose date record fuzzily matches to november 8 , 1992 .', 'tostr': 'filter_eq { all_rows ; date ; november 8 , 1992 }'}, 'date'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; date ; november 8 , 1992 } ; date }', 'tointer': 'select the rows whose date record fuzzily matches to november 8 , 1992 . take the date record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', 'november 22 , 1992'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose date record fuzzily matches to november 22 , 1992 .', 'tostr': 'filter_eq { all_rows ; date ; november 22 , 1992 }'}, 'date'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; date ; november 22 , 1992 } ; date }', 'tointer': 'select the rows whose date record fuzzily matches to november 22 , 1992 . take the date record of this row .'}], 'result': '-14 days', 'ind': 4, 'tostr': 'diff { hop { filter_eq { all_rows ; date ; november 8 , 1992 } ; date } ; hop { filter_eq { all_rows ; date ; november 22 , 1992 } ; date } }'}, '-14 days'], 'result': True, 'ind': 5, 'tostr': 'eq { diff { hop { filter_eq { all_rows ; date ; november 8 , 1992 } ; date } ; hop { filter_eq { all_rows ; date ; november 22 , 1992 } ; date } } ; -14 days } = true', 'tointer': 'select the rows whose date record fuzzily matches to november 8 , 1992 . take the date record of this row . select the rows whose date record fuzzily matches to november 22 , 1992 . take the date record of this row . the second record is 14 days larger than the first record .'}
|
eq { diff { hop { filter_eq { all_rows ; date ; november 8 , 1992 } ; date } ; hop { filter_eq { all_rows ; date ; november 22 , 1992 } ; date } } ; -14 days } = true
|
select the rows whose date record fuzzily matches to november 8 , 1992 . take the date record of this row . select the rows whose date record fuzzily matches to november 22 , 1992 . take the date record of this row . the second record is 14 days larger than the first record .
|
6
|
6
|
{'str_eq_5': 5, 'result_6': 6, 'diff_4': 4, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_7': 7, 'date_8': 8, 'november 8 , 1992_9': 9, 'date_10': 10, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_11': 11, 'date_12': 12, 'november 22 , 1992_13': 13, 'date_14': 14, '-14 days_15': 15}
|
{'str_eq_5': 'str_eq', 'result_6': 'true', 'diff_4': 'diff', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_7': 'all_rows', 'date_8': 'date', 'november 8 , 1992_9': 'november 8 , 1992', 'date_10': 'date', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_11': 'all_rows', 'date_12': 'date', 'november 22 , 1992_13': 'november 22 , 1992', 'date_14': 'date', '-14 days_15': '-14 days'}
|
{'str_eq_5': [6], 'result_6': [], 'diff_4': [5], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_7': [0], 'date_8': [0], 'november 8 , 1992_9': [0], 'date_10': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_11': [1], 'date_12': [1], 'november 22 , 1992_13': [1], 'date_14': [3], '-14 days_15': [5]}
|
['goal', 'date', 'score', 'result', 'competition']
|
[['1', 'november 8 , 1992', '2 - 0', '4 - 0', '1994 fifa world cup qualification'], ['2', 'november 22 , 1992', '2 - 0', '4 - 0', '1994 fifa world cup qualification'], ['3', 'december 14 , 1994', '3 - 1', '5 - 1', 'friendly'], ['4', 'october 11 , 1995', '1 - 1', '2 - 1', 'friendly'], ['5', 'january 31 , 2001', '1 - 0', '2 - 3', 'friendly'], ['6', 'may 1 , 2001', '1 - 0', '3 - 3', 'friendly']]
|
mercedes - benz r230
|
https://en.wikipedia.org/wiki/Mercedes-Benz_R230
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1867831-3.html.csv
|
unique
|
the sl 63 amg is the only car to have peak power at 6800 rpm .
|
{'scope': 'all', 'row': '5', 'col': '4', 'col_other': '1', 'criterion': 'equal', 'value': '6800', 'subset': None}
|
{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'power rpm', '6800'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose power rpm record is equal to 6800 .', 'tostr': 'filter_eq { all_rows ; power rpm ; 6800 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; power rpm ; 6800 } }', 'tointer': 'select the rows whose power rpm record is equal to 6800 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'power rpm', '6800'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose power rpm record is equal to 6800 .', 'tostr': 'filter_eq { all_rows ; power rpm ; 6800 }'}, 'model'], 'result': 'sl 63 amg', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; power rpm ; 6800 } ; model }'}, 'sl 63 amg'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; power rpm ; 6800 } ; model } ; sl 63 amg }', 'tointer': 'the model record of this unqiue row is sl 63 amg .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; power rpm ; 6800 } } ; eq { hop { filter_eq { all_rows ; power rpm ; 6800 } ; model } ; sl 63 amg } } = true', 'tointer': 'select the rows whose power rpm record is equal to 6800 . there is only one such row in the table . the model record of this unqiue row is sl 63 amg .'}
|
and { only { filter_eq { all_rows ; power rpm ; 6800 } } ; eq { hop { filter_eq { all_rows ; power rpm ; 6800 } ; model } ; sl 63 amg } } = true
|
select the rows whose power rpm record is equal to 6800 . there is only one such row in the table . the model record of this unqiue row is sl 63 amg .
|
6
|
5
|
{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'power rpm_7': 7, '6800_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'model_9': 9, 'sl 63 amg_10': 10}
|
{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'power rpm_7': 'power rpm', '6800_8': '6800', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'model_9': 'model', 'sl 63 amg_10': 'sl 63 amg'}
|
{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'power rpm_7': [0], '6800_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'model_9': [2], 'sl 63 amg_10': [3]}
|
['model', 'years', 'type / code', 'power rpm', 'torque rpm']
|
[['sl 280', '2008 - 2009', 'cc ( cuin ) v6 ( m272 )', '6000', '2500 - 5000'], ['sl 300', '2009 -', 'cc ( cuin ) v6 ( m272 )', '6000', '2500 - 5000'], ['sl 350', '2008 -', 'cc ( cuin ) v6 ( m272 )', '6500', '6500'], ['sl 500 , sl 550', '2006 -', 'cc ( cuin ) v8 ( m273 )', '6000', '2800 - 4800'], ['sl 63 amg', '2008 -', 'cc ( cuin ) v8 ( m156 .984 )', '6800', '5250'], ['sl 600', '2006 - 2009', 'cc ( cuin ) v12 biturbo ( m275 )', '5000', '1900 - 3500'], ['sl 65 amg', '2004 -', 'cc ( cuin ) v12 biturbo ( m275 amg )', '4800 - 5100', '2000 - 4000'], ['sl 65 amg black series', '2008 -', 'cc ( cuin ) v12 biturbo ( m275 amg )', '5400', '2200 - 4200']]
|
1907 grand prix season
|
https://en.wikipedia.org/wiki/1907_Grand_Prix_season
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13793279-2.html.csv
|
ordinal
|
arthur duray was the 2nd earliest racing winner in the 1907 grand prix season .
|
{'row': '2', 'col': '3', 'order': '2', 'col_other': '4', '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', 'date', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; date ; 2 }'}, 'winning driver'], 'result': 'arthur duray', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; date ; 2 } ; winning driver }'}, 'arthur duray'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; date ; 2 } ; winning driver } ; arthur duray } = true', 'tointer': 'select the row whose date record of all rows is 2nd minimum . the winning driver record of this row is arthur duray .'}
|
eq { hop { nth_argmin { all_rows ; date ; 2 } ; winning driver } ; arthur duray } = true
|
select the row whose date record of all rows is 2nd minimum . the winning driver record of this row is arthur duray .
|
3
|
3
|
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'date_5': 5, '2_6': 6, 'winning driver_7': 7, 'arthur duray_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', 'date_5': 'date', '2_6': '2', 'winning driver_7': 'winning driver', 'arthur duray_8': 'arthur duray'}
|
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'date_5': [0], '2_6': [0], 'winning driver_7': [1], 'arthur duray_8': [2]}
|
['name', 'circuit', 'date', 'winning driver', 'winning constructor', 'report']
|
[['targa florio', 'madonie', '22 april', 'felice nazzaro', 'fiat', 'report'], ['moscow - st petersburg', 'public roads', '7 june', 'arthur duray', 'lorraine - dietrich', 'report'], ['kaiser preis', 'taunus', '13 - 14 june', 'felice nazzaro', 'fiat', 'report'], ['ardennes circuit ( kaiser formula )', 'bastogne', '25 july', 'john moore - brabazon', 'minerva', 'report'], ['ardennes circuit', 'bastogne', '27 july', 'pierre de caters', 'mercedes', 'report'], ['coppa florio', 'brescia', '1 september', 'ferdinando minoia', 'isotta - fraschini', 'report'], ['coppa della velocità', 'brescia', '2 september', 'alessandro cagno', 'itala', 'report']]
|
harald ertl
|
https://en.wikipedia.org/wiki/Harald_Ertl
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1226456-2.html.csv
|
majority
|
harald ertl drove a hesketh chassis most years from 1975 to 1980 .
|
{'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'hesketh', 'subset': None}
|
{'func': 'most_str_eq', 'args': ['all_rows', 'chassis', 'hesketh'], 'result': True, 'ind': 0, 'tointer': 'for the chassis records of all rows , most of them fuzzily match to hesketh .', 'tostr': 'most_eq { all_rows ; chassis ; hesketh } = true'}
|
most_eq { all_rows ; chassis ; hesketh } = true
|
for the chassis records of all rows , most of them fuzzily match to hesketh .
|
1
|
1
|
{'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'chassis_3': 3, 'hesketh_4': 4}
|
{'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'chassis_3': 'chassis', 'hesketh_4': 'hesketh'}
|
{'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'chassis_3': [0], 'hesketh_4': [0]}
|
['year', 'entrant', 'chassis', 'engine', 'points']
|
[['1975', 'warsteiner brewery', 'hesketh 308', 'cosworth v8', '0'], ['1976', 'hesketh racing', 'hesketh 308d', 'cosworth v8', '0'], ['1977', 'hesketh racing', 'hesketh 308e', 'cosworth v8', '0'], ['1978', 'sachs racing', 'ensign n177', 'cosworth v8', '0'], ['1978', 'ats engineering', 'ats hs1', 'cosworth v8', '0'], ['1980', 'team ats', 'ats d4', 'cosworth v8', '0']]
|
northumberland county , new brunswick
|
https://en.wikipedia.org/wiki/Northumberland_County%2C_New_Brunswick
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-171354-1.html.csv
|
aggregation
|
the total population among the five communities in northumberland county , new brunswick is just under 22,500 .
|
{'scope': 'all', 'col': '4', 'type': 'sum', 'result': '22,500', 'subset': None}
|
{'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'population'], 'result': '22,500', 'ind': 0, 'tostr': 'sum { all_rows ; population }'}, '22,500'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; population } ; 22,500 } = true', 'tointer': 'the sum of the population record of all rows is 22,500 .'}
|
round_eq { sum { all_rows ; population } ; 22,500 } = true
|
the sum of the population record of all rows is 22,500 .
|
2
|
2
|
{'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'population_4': 4, '22,500_5': 5}
|
{'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'population_4': 'population', '22,500_5': '22,500'}
|
{'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'population_4': [0], '22,500_5': [1]}
|
['official name', 'status', 'area km 2', 'population', 'census ranking']
|
[['miramichi', 'city', '179.84', '17811', '232 of 5008'], ['neguac', 'village', '26.69', '1678', '1500 of 5008'], ['rogersville', 'village', '7.23', '1170', '1875 of 5008'], ['blackville', 'village', '21.73', '990', '2086 of 5008'], ['doaktown', 'village', '28.74', '793', '2387 of 5008']]
|
1945 vfl season
|
https://en.wikipedia.org/wiki/1945_VFL_season
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10809271-20.html.csv
|
count
|
in the games of the 1945 vfl season shown 4 of the games had an attendance of over 10,000 .
|
{'scope': 'all', 'criterion': 'greater_than', 'value': '10000', 'result': '4', 'col': '6', 'subset': None}
|
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'crowd', '10000'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose crowd record is greater than 10000 .', 'tostr': 'filter_greater { all_rows ; crowd ; 10000 }'}], 'result': '4', 'ind': 1, 'tostr': 'count { filter_greater { all_rows ; crowd ; 10000 } }', 'tointer': 'select the rows whose crowd record is greater than 10000 . the number of such rows is 4 .'}, '4'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_greater { all_rows ; crowd ; 10000 } } ; 4 } = true', 'tointer': 'select the rows whose crowd record is greater than 10000 . the number of such rows is 4 .'}
|
eq { count { filter_greater { all_rows ; crowd ; 10000 } } ; 4 } = true
|
select the rows whose crowd record is greater than 10000 . the number of such rows is 4 .
|
3
|
3
|
{'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_greater_0': 0, 'all_rows_4': 4, 'crowd_5': 5, '10000_6': 6, '4_7': 7}
|
{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_greater_0': 'filter_greater', 'all_rows_4': 'all_rows', 'crowd_5': 'crowd', '10000_6': '10000', '4_7': '4'}
|
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_greater_0': [1], 'all_rows_4': [0], 'crowd_5': [0], '10000_6': [0], '4_7': [2]}
|
['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date']
|
[['geelong', '13.14 ( 92 )', 'st kilda', '9.11 ( 65 )', 'kardinia park', '7500', '1 september 1945'], ['fitzroy', '14.22 ( 106 )', 'melbourne', '15.11 ( 101 )', 'brunswick street oval', '5000', '1 september 1945'], ['south melbourne', '16.16 ( 112 )', 'hawthorn', '11.10 ( 76 )', 'junction oval', '12000', '1 september 1945'], ['north melbourne', '14.17 ( 101 )', 'essendon', '13.17 ( 95 )', 'arden street oval', '12000', '1 september 1945'], ['richmond', '8.19 ( 67 )', 'collingwood', '12.15 ( 87 )', 'punt road oval', '23000', '1 september 1945'], ['footscray', '8.14 ( 62 )', 'carlton', '16.19 ( 115 )', 'western oval', '30000', '1 september 1945']]
|
northern state conference ( ihsaa )
|
https://en.wikipedia.org/wiki/Northern_State_Conference_%28IHSAA%29
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18936749-1.html.csv
|
aggregation
|
the average enrollment of the members schools of the northern state conference ( ihsaa ) is about 538 students .
|
{'scope': 'all', 'col': '4', 'type': 'average', 'result': '538', 'subset': None}
|
{'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'enrollment'], 'result': '538', 'ind': 0, 'tostr': 'avg { all_rows ; enrollment }'}, '538'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; enrollment } ; 538 } = true', 'tointer': 'the average of the enrollment record of all rows is 538 .'}
|
round_eq { avg { all_rows ; enrollment } ; 538 } = true
|
the average of the enrollment record of all rows is 538 .
|
2
|
2
|
{'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'enrollment_4': 4, '538_5': 5}
|
{'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'enrollment_4': 'enrollment', '538_5': '538'}
|
{'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'enrollment_4': [0], '538_5': [1]}
|
['school ( ihsaa id )', 'location', 'mascot', 'enrollment', 'ihsaa class', 'county', 'year joined']
|
[['bremen', 'bremen', 'lions', '505', 'aa', '50 marshall', '1989'], ['culver community', 'culver', 'cavaliers', '306', 'a', '50 marshall', '1977'], ['glenn', 'walkerton', 'falcons', '613', 'aaa', '71 st joseph', '1966'], ['jimtown', 'elkhart', 'jimmies', '642', 'aaa', '20 elkhart', '1966'], ['knox community', 'knox', 'redskins', '632', 'aaa', '75 starke', '1982'], ['laville', 'lakeville', 'lancers', '413', 'a', '71 st joseph', '1966'], ['new prairie', 'new carlisle', 'cougars', '859', 'aaaa', '46 laporte 71 st joseph', '1968'], ['triton', 'bourbon', 'trojans', '333', 'a', '50 marshall', '1980']]
|
northeast delta dental international
|
https://en.wikipedia.org/wiki/Northeast_Delta_Dental_International
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-15315276-1.html.csv
|
superlative
|
2010 had the highest winners share in the northeast delta dental international .
|
{'scope': 'all', 'col_superlative': '8', 'row_superlative': '4', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None}
|
{'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'winners share'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; winners share }'}, 'year'], 'result': '2010', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; winners share } ; year }'}, '2010'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; winners share } ; year } ; 2010 } = true', 'tointer': 'select the row whose winners share record of all rows is maximum . the year record of this row is 2010 .'}
|
eq { hop { argmax { all_rows ; winners share } ; year } ; 2010 } = true
|
select the row whose winners share record of all rows is maximum . the year record of this row is 2010 .
|
3
|
3
|
{'eq_2': 2, 'result_3': 3, 'num_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'winners share_5': 5, 'year_6': 6, '2010_7': 7}
|
{'eq_2': 'eq', 'result_3': 'true', 'num_hop_1': 'num_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'winners share_5': 'winners share', 'year_6': 'year', '2010_7': '2010'}
|
{'eq_2': [3], 'result_3': [], 'num_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'winners share_5': [0], 'year_6': [1], '2010_7': [2]}
|
['year', 'dates', 'champion', 'country', 'score', 'tournament location', 'purse', 'winners share']
|
[['2013', 'jul 19 - 21', 'pk kongkraphan', 'thailand', '207 ( 9 )', 'beaver meadow golf course', '100000', '15000'], ['2012', 'jul 20 - 22', 'jenny gleason', 'united states', '211 ( 5 )', 'beaver meadow golf course', '100000', '15000'], ['2011', 'jul 22 - 24', 'jessica shepley', 'canada', '203 ( 13 )', 'beaver meadow golf course', '100000', '14000'], ['2010', 'jul 19 - 25', 'jenny shin', 'united states', '205 ( 11 )', 'beaver meadow golf course', '110000', '15400'], ['2009', 'jul 24 - 26', 'misun cho', 'south korea', '207 ( 9 )', 'beaver meadow golf course', '90000', '12600'], ['2008', 'jul 25 - 27', 'mo martin', 'united states', '204 ( 12 )', 'beaver meadow golf course', '80000', '11200'], ['2007', 'aug 3 - 5', 'ji min jeong', 'south korea', '209 ( 7 )', 'beaver meadow golf course', '75000', '10500'], ['2006', 'aug 4 - 6', 'charlotte mayorkas', 'united states', '207 ( 9 )', 'beaver meadow golf course', '70000', '9800'], ['2005', 'jul 22 - 24', 'kyeong bae', 'south korea', '209 ( 7 )', 'beaver meadow golf course', '65000', '9100']]
|
nate mohr
|
https://en.wikipedia.org/wiki/Nate_Mohr
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17440712-2.html.csv
|
count
|
seven of nate mohr 's fights ended by the method of tko .
|
{'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'tko', 'result': '7', 'col': '4', 'subset': None}
|
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'method', 'tko'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose method record fuzzily matches to tko .', 'tostr': 'filter_eq { all_rows ; method ; tko }'}], 'result': '7', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; method ; tko } }', 'tointer': 'select the rows whose method record fuzzily matches to tko . the number of such rows is 7 .'}, '7'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; method ; tko } } ; 7 } = true', 'tointer': 'select the rows whose method record fuzzily matches to tko . the number of such rows is 7 .'}
|
eq { count { filter_eq { all_rows ; method ; tko } } ; 7 } = true
|
select the rows whose method record fuzzily matches to tko . the number of such rows is 7 .
|
3
|
3
|
{'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'method_5': 5, 'tko_6': 6, '7_7': 7}
|
{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'method_5': 'method', 'tko_6': 'tko', '7_7': '7'}
|
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'method_5': [0], 'tko_6': [0], '7_7': [2]}
|
['res', 'record', 'opponent', 'method', 'event', 'round']
|
[['loss', '9 - 7', 'lenny lovato', 'decision ( unanimous )', 'gfc 2 - unstoppable', '3'], ['win', '9 - 6', 'danny rodriguez', 'tko ( punches )', 'xfo - xtreme fighting organization 28', '3'], ['loss', '8 - 6', 'dennis siver', 'tko ( spinning back kick & punches )', 'ufc 93', '3'], ['loss', '8 - 5', 'manny gamburyan', 'submission ( achilles lock )', 'ufc 79', '1'], ['win', '8 - 4', 'luke caudillo', 'decision ( unanimous )', 'ufc fight night 10', '3'], ['loss', '7 - 4', 'kurt pellegrino', 'submission ( achilles lock )', 'ufc fight night 9', '1'], ['win', '7 - 3', 'cody shipp', 'tko ( punches )', 'kotc - hard knocks', '1'], ['win', '6 - 3', 'norm alexander', 'tko ( punches )', 'xfo 13 - operation beatdown', '2'], ['win', '5 - 3', 'darren cotton', 'tko ( punches )', 'xfo 12 - outdoor war', '2'], ['win', '4 - 3', 'alex carter', 'tko ( punches )', 'xfo 11 - champions', '1'], ['loss', '3 - 3', 'donald cerrone', 'submission ( triangle choke )', 'rof 21 - full blast', '1'], ['loss', '3 - 2', 'jay ellis', 'submission ( rear naked choke )', 'xfo 9 - xtreme fighting organization 9', '1'], ['win', '3 - 1', 'enrique guzman', 'tko ( punches )', 'combat - do fighting challenge 4', '1'], ['win', '2 - 1', 'don hamilton', 'submission ( punches )', 'ic - iowa challenge', '1'], ['loss', '1 - 1', 'john strawn', 'submission ( rear naked choke )', 'ec 53 - extreme challenge 53', '2'], ['win', '1 - 0', 'cain rizzo', 'submission ( punches )', 'ec 52 - extreme challenge 52', '2']]
|
1928 in brazilian football
|
https://en.wikipedia.org/wiki/1928_in_Brazilian_football
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15384084-2.html.csv
|
superlative
|
sc internacional de são paulo earned maximum amount points during1928 season in brazilian football .
|
{'scope': 'all', 'col_superlative': '3', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '2', 'subset': None}
|
{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'points'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; points }'}, 'team'], 'result': 'sc internacional de são paulo', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; points } ; team }'}, 'sc internacional de são paulo'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; points } ; team } ; sc internacional de são paulo } = true', 'tointer': 'select the row whose points record of all rows is maximum . the team record of this row is sc internacional de são paulo .'}
|
eq { hop { argmax { all_rows ; points } ; team } ; sc internacional de são paulo } = true
|
select the row whose points record of all rows is maximum . the team record of this row is sc internacional de são paulo .
|
3
|
3
|
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'points_5': 5, 'team_6': 6, 'sc internacional de são paulo_7': 7}
|
{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'points_5': 'points', 'team_6': 'team', 'sc internacional de são paulo_7': 'sc internacional de são paulo'}
|
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'points_5': [0], 'team_6': [1], 'sc internacional de são paulo_7': [2]}
|
['position', 'team', 'points', 'played', 'drawn', 'lost', 'against', 'difference']
|
[['1', 'sc internacional de são paulo', '33', '22', '5', '3', '32', '29'], ['2', 'paulistano', '33', '22', '3', '4', '22', '39'], ['3', 'hespanha', '30', '22', '4', '5', '38', '14'], ['4', 'ponte preta', '30', '22', '4', '5', '37', '23'], ['5', 'atlético santista', '26', '22', '6', '6', '31', '26'], ['6', 'aa são bento', '23', '22', '5', '8', '40', '1'], ['7', 'independência', '18', '22', '2', '12', '58', '- 8'], ['8', 'antártica', '18', '22', '6', '10', '54', '- 14'], ['9', 'paulista', '17', '22', '3', '12', '43', '- 14'], ['10', 'germnia', '13', '22', '3', '14', '66', '- 18'], ['11', 'união lapa', '12', '22', '2', '15', '86', '- 58'], ['12', 'aa palmeiras', '11', '22', '3', '15', '55', '- 20']]
|
lella lombardi
|
https://en.wikipedia.org/wiki/Lella_Lombardi
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1235922-1.html.csv
|
majority
|
the majority of the time lella used a cosworth v8 engine .
|
{'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': 'v8', 'subset': None}
|
{'func': 'most_str_eq', 'args': ['all_rows', 'engine', 'v8'], 'result': True, 'ind': 0, 'tointer': 'for the engine records of all rows , most of them fuzzily match to v8 .', 'tostr': 'most_eq { all_rows ; engine ; v8 } = true'}
|
most_eq { all_rows ; engine ; v8 } = true
|
for the engine records of all rows , most of them fuzzily match to v8 .
|
1
|
1
|
{'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'engine_3': 3, 'v8_4': 4}
|
{'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'engine_3': 'engine', 'v8_4': 'v8'}
|
{'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'engine_3': [0], 'v8_4': [0]}
|
['year', 'entrant', 'chassis', 'engine', 'points']
|
[['1974', 'allied polymer group', 'brabham bt42', 'cosworth v8', '0'], ['1975', 'march engineering', 'march 741', 'cosworth v8', '0.5'], ['1975', 'lavazza march', 'march 751', 'cosworth v8', '0.5'], ['1975', 'frank williams racing cars', 'williams fw04', 'cosworth v8', '0.5'], ['1976', 'lavazza march', 'march 761', 'cosworth v8', '0'], ['1976', 'ram racing with lavazza', 'brabham bt44b', 'cosworth v8', '0']]
|
corey pavin
|
https://en.wikipedia.org/wiki/Corey_Pavin
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1530024-1.html.csv
|
aggregation
|
in the year 1987 , corey pavin 's average winning score was 305.5 .
|
{'scope': 'subset', 'col': '3', 'type': 'average', 'result': '305.5', 'subset': {'col': '1', 'criterion': 'fuzzily_match', 'value': '1987'}}
|
{'func': 'round_eq', 'args': [{'func': 'avg', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', '1987'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; date ; 1987 }', 'tointer': 'select the rows whose date record fuzzily matches to 1987 .'}, 'winning score'], 'result': '305.5', 'ind': 1, 'tostr': 'avg { filter_eq { all_rows ; date ; 1987 } ; winning score }'}, '305.5'], 'result': True, 'ind': 2, 'tostr': 'round_eq { avg { filter_eq { all_rows ; date ; 1987 } ; winning score } ; 305.5 } = true', 'tointer': 'select the rows whose date record fuzzily matches to 1987 . the average of the winning score record of these rows is 305.5 .'}
|
round_eq { avg { filter_eq { all_rows ; date ; 1987 } ; winning score } ; 305.5 } = true
|
select the rows whose date record fuzzily matches to 1987 . the average of the winning score record of these rows is 305.5 .
|
3
|
3
|
{'eq_2': 2, 'result_3': 3, 'avg_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'date_5': 5, '1987_6': 6, 'winning score_7': 7, '305.5_8': 8}
|
{'eq_2': 'eq', 'result_3': 'true', 'avg_1': 'avg', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'date_5': 'date', '1987_6': '1987', 'winning score_7': 'winning score', '305.5_8': '305.5'}
|
{'eq_2': [3], 'result_3': [], 'avg_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'date_5': [0], '1987_6': [0], 'winning score_7': [1], '305.5_8': [2]}
|
['date', 'tournament', 'winning score', 'margin of victory', 'runner ( s ) - up']
|
[['apr 29 , 1984', 'houston coca - cola open', '- 10 ( 70 + 68 + 68 + 68 = 274 )', '1 stroke', 'buddy gardner'], ['may 19 , 1985', 'colonial national invitation', '- 14 ( 66 + 64 + 68 + 68 = 266 )', '4 strokes', 'bob murphy'], ['feb 16 , 1986', 'hawaiian open', '- 16 ( 67 + 67 + 72 + 66 = 272 )', '2 strokes', 'paul azinger'], ['sep 21 , 1986', 'greater milwaukee open', '- 17 ( 66 + 72 + 67 + 67 = 272 )', 'playoff', 'dave barr'], ['jan 18 , 1987', 'bob hope chrysler classic', '- 19 ( 72 - 71 + 65 + 66 + 67 = 341 )', '1 stroke', 'bernhard langer'], ['feb 8 , 1987', 'hawaiian open', '- 18 ( 65 + 75 + 66 + 64 = 270 )', 'playoff', 'craig stadler'], ['oct 16 , 1988', 'texas open', '- 21 ( 64 + 63 + 66 + 66 = 259 )', '8 strokes', 'robert wrenn'], ['feb 10 , 1991', 'bob hope chrysler classic', '- 29 ( 65 - 69 + 66 + 66 + 65 = 331 )', 'playoff', "mark o'meara"], ['may 12 , 1991', 'bellsouth atlanta golf classic', '- 16 ( 68 + 67 + 67 + 70 = 272 )', 'playoff', 'steve pate'], ['mar 15 , 1992', 'honda classic', '- 15 ( 68 + 67 + 70 + 68 = 273 )', 'playoff', 'fred couples'], ['feb 13 , 1994', 'nissan los angeles open', '- 13 ( 67 + 64 + 72 + 68 = 271 )', '2 strokes', 'fred couples'], ['feb 26 , 1995', 'nissan open', '- 16 ( 67 + 66 + 68 + 67 = 268 )', '3 strokes', 'jay don blake , kenny perry'], ['jun 18 , 1995', 'us open', 'e ( 72 + 69 + 71 + 68 = 280 )', '2 strokes', 'greg norman'], ['may 19 , 1996', 'mastercard colonial', '- 8 ( 69 + 67 + 67 + 69 = 272 )', '2 strokes', 'jeff sluman'], ['jul 30 , 2006', 'us bank championship in milwaukee', '- 20 ( 61 + 64 + 68 + 67 = 260 )', '2 strokes', 'jerry kelly']]
|
sports in evansville , indiana
|
https://en.wikipedia.org/wiki/Sports_in_Evansville%2C_Indiana
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17389615-6.html.csv
|
majority
|
for sports in evansville , indiana all of the teams play football .
|
{'scope': 'all', 'col': '2', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'football', 'subset': None}
|
{'func': 'all_str_eq', 'args': ['all_rows', 'sport', 'football'], 'result': True, 'ind': 0, 'tointer': 'for the sport records of all rows , all of them fuzzily match to football .', 'tostr': 'all_eq { all_rows ; sport ; football } = true'}
|
all_eq { all_rows ; sport ; football } = true
|
for the sport records of all rows , all of them fuzzily match to football .
|
1
|
1
|
{'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'sport_3': 3, 'football_4': 4}
|
{'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'sport_3': 'sport', 'football_4': 'football'}
|
{'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'sport_3': [0], 'football_4': [0]}
|
['team', 'sport', 'played', 'venue', 'championships']
|
[['evansville crimson giants', 'football', '1921 - 1922', 'bosse field', 'none'], ['evansville vipers', 'football', '2000 - 2007', 'goebel soccer complex', 'none'], ['evansville bluecats', 'football', '2003 - 2007', 'roberts municipal stadium', 'none'], ['evansville express', 'football', '2004 - 2005', 'goebel soccer complex', 'none'], ['tri - state titans', 'football', '2008 - 2009', 'goebel soccer complex', 'none'], ['ohio river bearcats', 'football', '2008 - 2010', 'reitz bowl', 'gmfl title 2008']]
|
north american x - 15
|
https://en.wikipedia.org/wiki/North_American_X-15
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-221315-3.html.csv
|
ordinal
|
joseph a walker reached the 2nd highest max speed among all pilots of the the north american x - 15 .
|
{'row': '11', 'col': '7', 'order': '2', 'col_other': '1', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None}
|
{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'max speed ( mph )', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; max speed ( mph ) ; 2 }'}, 'pilot'], 'result': 'joseph a walker', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; max speed ( mph ) ; 2 } ; pilot }'}, 'joseph a walker'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; max speed ( mph ) ; 2 } ; pilot } ; joseph a walker } = true', 'tointer': 'select the row whose max speed ( mph ) record of all rows is 2nd maximum . the pilot record of this row is joseph a walker .'}
|
eq { hop { nth_argmax { all_rows ; max speed ( mph ) ; 2 } ; pilot } ; joseph a walker } = true
|
select the row whose max speed ( mph ) record of all rows is 2nd maximum . the pilot record of this row is joseph a walker .
|
3
|
3
|
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'max speed (mph)_5': 5, '2_6': 6, 'pilot_7': 7, 'joseph a walker_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', 'max speed (mph)_5': 'max speed ( mph )', '2_6': '2', 'pilot_7': 'pilot', 'joseph a walker_8': 'joseph a walker'}
|
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'max speed (mph)_5': [0], '2_6': [0], 'pilot_7': [1], 'joseph a walker_8': [2]}
|
['pilot', 'organization', 'total flights', 'usaf space flights', 'fai space flights', 'max mach', 'max speed ( mph )', 'max altitude ( miles )']
|
[['michael j adams', 'us air force', '7', '1', '0', '5.59', '3822', '50.3'], ['neil armstrong', 'nasa', '7', '0', '0', '5.74', '3989', '39.2'], ['scott crossfield', 'north american aviation', '14', '0', '0', '2.97', '1959', '15.3'], ['william h dana', 'nasa', '16', '2', '0', '5.53', '3897', '58.1'], ['joseph h engle', 'us air force', '16', '3', '0', '5.71', '3887', '53.1'], ['william j pete knight', 'us air force', '16', '1', '0', '6.70', '4519', '53.1'], ['john b mckay', 'nasa', '29', '1', '0', '5.65', '3863', '55.9'], ['forrest s petersen', 'us navy', '5', '0', '0', '5.3', '3600', '19.2'], ['robert a rushworth', 'us air force', '34', '1', '0', '6.06', '4017', '53.9'], ['milton o thompson', 'nasa', '14', '0', '0', '5.48', '3723', '40.5'], ['joseph a walker', 'nasa', '25', '3', '2', '5.92', '4104', '67.0']]
|
1968 kansas city chiefs season
|
https://en.wikipedia.org/wiki/1968_Kansas_City_Chiefs_season
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12535990-1.html.csv
|
superlative
|
the game the kansas city chiefs played on november 3 , 1968 had the highest attendance for the 1968 season .
|
{'scope': 'all', 'col_superlative': '5', 'row_superlative': '9', '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', 'attendance'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; attendance }'}, 'date'], 'result': 'november 3 , 1968', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; attendance } ; date }'}, 'november 3 , 1968'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; attendance } ; date } ; november 3 , 1968 } = true', 'tointer': 'select the row whose attendance record of all rows is maximum . the date record of this row is november 3 , 1968 .'}
|
eq { hop { argmax { all_rows ; attendance } ; date } ; november 3 , 1968 } = true
|
select the row whose attendance record of all rows is maximum . the date record of this row is november 3 , 1968 .
|
3
|
3
|
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'attendance_5': 5, 'date_6': 6, 'november 3 , 1968_7': 7}
|
{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'attendance_5': 'attendance', 'date_6': 'date', 'november 3 , 1968_7': 'november 3 , 1968'}
|
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'attendance_5': [0], 'date_6': [1], 'november 3 , 1968_7': [2]}
|
['week', 'date', 'opponent', 'result', 'attendance']
|
[['1', 'september 10 , 1968', 'houston oilers', 'w 26 - 21', '45083'], ['2', 'september 15 , 1968', 'new york jets', 'l 20 - 19', '48871'], ['3', 'september 22 , 1968', 'denver broncos', 'w 34 - 2', '45821'], ['4', 'september 28 , 1968', 'miami dolphins', 'w 48 - 3', '28501'], ['5', 'october 5 , 1968', 'buffalo bills', 'w 18 - 7', '40748'], ['6', 'october 13 , 1968', 'cincinnati bengals', 'w 13 - 3', '47096'], ['7', 'october 20 , 1968', 'oakland raiders', 'w 24 - 10', '50015'], ['8', 'october 27 , 1968', 'san diego chargers', 'w 27 - 20', '50344'], ['9', 'november 3 , 1968', 'oakland raiders', 'l 38 - 21', '53357'], ['10', 'november 10 , 1968', 'cincinnati bengals', 'w 16 - 9', '25537'], ['11', 'november 17 , 1968', 'boston patriots', 'w 31 - 17', '48271'], ['13', 'november 28 , 1968', 'houston oilers', 'w 24 - 10', '48493'], ['14', 'december 8 , 1968', 'san diego chargers', 'w 40 - 3', '51174'], ['15', 'december 14 , 1968', 'denver broncos', 'w 30 - 7', '38463']]
|
carla suárez navarro
|
https://en.wikipedia.org/wiki/Carla_Su%C3%A1rez_Navarro
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15551996-3.html.csv
|
majority
|
all tournaments carla suárez navarro played in were played on a clay surface .
|
{'scope': 'all', 'col': '4', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'clay', 'subset': None}
|
{'func': 'all_str_eq', 'args': ['all_rows', 'surface', 'clay'], 'result': True, 'ind': 0, 'tointer': 'for the surface records of all rows , all of them fuzzily match to clay .', 'tostr': 'all_eq { all_rows ; surface ; clay } = true'}
|
all_eq { all_rows ; surface ; clay } = true
|
for the surface records of all rows , all of them fuzzily match to clay .
|
1
|
1
|
{'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'surface_3': 3, 'clay_4': 4}
|
{'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'surface_3': 'surface', 'clay_4': 'clay'}
|
{'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'surface_3': [0], 'clay_4': [0]}
|
['outcome', 'date', 'tournament', 'surface', 'opponent', 'score']
|
[['runner - up', 'april 12 , 2009', 'andalucia tennis experience , marbella , spain', 'clay', 'jelena janković', '3 - 6 , 6 - 3 , 3 - 6'], ['runner - up', 'april 11 , 2010', 'andalucia tennis experience , marbella , spain', 'clay', 'flavia pennetta', '2 - 6 , 6 - 4 , 3 - 6'], ['runner - up', 'may 5 , 2012', 'estoril open , estoril , portugal', 'clay', 'kaia kanepi', '6 - 3 , 6 - 7 ( 6 - 8 ) , 4 - 6'], ['runner - up', 'march 2 , 2013', 'abierto mexicano telcel , acapulco , mexico', 'clay', 'sara errani', '0 - 6 , 4 - 6'], ['runner - up', 'may 4 , 2013', 'portugal open , oeiras , portugal', 'clay', 'anastasia pavlyuchenkova', '5 - 7 , 2 - 6']]
|
dragons ' den ( uk )
|
https://en.wikipedia.org/wiki/Dragons%27_Den_%28UK%29
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12617978-9.html.csv
|
superlative
|
emmie matthews and ed stevens are the entrepreneurs who requested the biggest sum of money in the dragons den .
|
{'scope': 'all', 'col_superlative': '5', 'row_superlative': '4', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '3', 'subset': None}
|
{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'money requested'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; money requested }'}, 'entrepreneur ( s )'], 'result': 'emmie matthews & ed stevens', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; money requested } ; entrepreneur ( s ) }'}, 'emmie matthews & ed stevens'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; money requested } ; entrepreneur ( s ) } ; emmie matthews & ed stevens } = true', 'tointer': 'select the row whose money requested record of all rows is maximum . the entrepreneur ( s ) record of this row is emmie matthews & ed stevens .'}
|
eq { hop { argmax { all_rows ; money requested } ; entrepreneur ( s ) } ; emmie matthews & ed stevens } = true
|
select the row whose money requested record of all rows is maximum . the entrepreneur ( s ) record of this row is emmie matthews & ed stevens .
|
3
|
3
|
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'money requested_5': 5, 'entrepreneur (s)_6': 6, 'emmie matthews & ed stevens_7': 7}
|
{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'money requested_5': 'money requested', 'entrepreneur (s)_6': 'entrepreneur ( s )', 'emmie matthews & ed stevens_7': 'emmie matthews & ed stevens'}
|
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'money requested_5': [0], 'entrepreneur (s)_6': [1], 'emmie matthews & ed stevens_7': [2]}
|
['episode', 'first aired', 'entrepreneur ( s )', 'company or product name', 'money requested', 'investing dragon ( s )']
|
[['episode 1', '15 october 2007', 'celia norowzian & ian forshew', 'beach break live', '50000', 'peter jones'], ['episode 1', '15 october 2007', 'laban roomes', 'goldgenie ( formerly midas touch )', '60000', 'james caan'], ['episode 2', '22 october 2007', 'sarah lu', 'youdoodoll', '35000', 'deborah meaden'], ['episode 2', '22 october 2007', 'emmie matthews & ed stevens', 'gaming alerts', '200000', 'theo paphitis'], ['episode 3', '29 october 2007', 'mark champkins', 'concentrate design', '100000', 'peter jones'], ['episode 4', '5 november 2007', 'max mcmurdo', 'reestore', '50000', 'deborah meaden & theo paphitis'], ['episode 4', '5 november 2007', 'jamie jenkinson', "cush 'n ' shade", '100000', 'deborah meaden & peter jones'], ['episode 5', '19 november 2007', 'shane lake and tony charles', 'hungryhousecouk', '100000', 'james caan & duncan bannatyne'], ['episode 6', '26 november 2007', 'ian helmore', 'steri spray', '145000', 'deborah meaden & theo paphitis'], ['episode 6', '26 november 2007', 'mark and eleanor davis', 'caribbean ready meals', '100000', 'james caan & duncan bannatyne'], ['episode 7', '3 december 2007', 'sammy french', 'fit fur life', '100000', 'james caan'], ['episode 7', '3 december 2007', 'jerry mantalvanos & paul merker', 'jpm eco logistics', '100000', 'deborah meaden & theo paphitis'], ['episode 8', '11 december 2007', 'peter moule', 'electroexpo , chocbox', '150000', 'duncan bannatyne & james caan'], ['episode 9', '18 december 2007', 'amanda jones & james brown', 'red button design', '50000', 'all five dragons']]
|
jets - patriots rivalry
|
https://en.wikipedia.org/wiki/Jets%E2%80%93Patriots_rivalry
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14732368-4.html.csv
|
count
|
in the jets-patriots rivalry , when the winner was the new york jets , there were 7 times the game was at shea stadium .
|
{'scope': 'subset', 'criterion': 'equal', 'value': 'shea stadium', 'result': '7', 'col': '6', 'subset': {'col': '3', 'criterion': 'equal', 'value': 'new york jets'}}
|
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'winner', 'new york jets'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; winner ; new york jets }', 'tointer': 'select the rows whose winner record fuzzily matches to new york jets .'}, 'location', 'shea stadium'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose winner record fuzzily matches to new york jets . among these rows , select the rows whose location record fuzzily matches to shea stadium .', 'tostr': 'filter_eq { filter_eq { all_rows ; winner ; new york jets } ; location ; shea stadium }'}], 'result': '7', 'ind': 2, 'tostr': 'count { filter_eq { filter_eq { all_rows ; winner ; new york jets } ; location ; shea stadium } }', 'tointer': 'select the rows whose winner record fuzzily matches to new york jets . among these rows , select the rows whose location record fuzzily matches to shea stadium . the number of such rows is 7 .'}, '7'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_eq { filter_eq { all_rows ; winner ; new york jets } ; location ; shea stadium } } ; 7 } = true', 'tointer': 'select the rows whose winner record fuzzily matches to new york jets . among these rows , select the rows whose location record fuzzily matches to shea stadium . the number of such rows is 7 .'}
|
eq { count { filter_eq { filter_eq { all_rows ; winner ; new york jets } ; location ; shea stadium } } ; 7 } = true
|
select the rows whose winner record fuzzily matches to new york jets . among these rows , select the rows whose location record fuzzily matches to shea stadium . the number of such rows is 7 .
|
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, 'winner_6': 6, 'new york jets_7': 7, 'location_8': 8, 'shea stadium_9': 9, '7_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', 'winner_6': 'winner', 'new york jets_7': 'new york jets', 'location_8': 'location', 'shea stadium_9': 'shea stadium', '7_10': '7'}
|
{'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_str_eq_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'winner_6': [0], 'new york jets_7': [0], 'location_8': [1], 'shea stadium_9': [1], '7_10': [3]}
|
['year', 'date', 'winner', 'result', 'loser', 'location']
|
[['1970', 'september 27', 'new york jets', '31 - 21', 'boston patriots', 'harvard stadium'], ['1970', 'november 22', 'new york jets', '17 - 3', 'boston patriots', 'shea stadium'], ['1971', 'october 10', 'new england patriots', '20 - 0', 'new york jets', 'schaefer stadium'], ['1971', 'december 12', 'new york jets', '13 - 6', 'new england patriots', 'shea stadium'], ['1972', 'october 15', 'new york jets', '41 - 13', 'new england patriots', 'schaefer stadium'], ['1972', 'october 29', 'new york jets', '34 - 10', 'new england patriots', 'shea stadium'], ['1973', 'october 14', 'new york jets', '9 - 7', 'new england patriots', 'schaefer stadium'], ['1973', 'november 11', 'new york jets', '33 - 13', 'new england patriots', 'shea stadium'], ['1974', 'october 13', 'new england patriots', '24 - 0', 'new york jets', 'shea stadium'], ['1974', 'november 17', 'new york jets', '21 - 16', 'new england patriots', 'schaefer stadium'], ['1975', 'october 5', 'new york jets', '36 - 7', 'new england patriots', 'shea stadium'], ['1975', 'december 7', 'new york jets', '30 - 28', 'new england patriots', 'schaefer stadium'], ['1976', 'october 18', 'new england patriots', '41 - 7', 'new york jets', 'schaefer stadium'], ['1976', 'november 21', 'new england patriots', '38 - 24', 'new york jets', 'shea stadium'], ['1977', 'october 2', 'new york jets', '30 - 27', 'new england patriots', 'shea stadium'], ['1977', 'october 30', 'new england patriots', '24 - 13', 'new york jets', 'schaefer stadium'], ['1978', 'october 29', 'new england patriots', '55 - 21', 'new york jets', 'schaefer stadium'], ['1978', 'november 19', 'new england patriots', '19 - 17', 'new york jets', 'shea stadium'], ['1979', 'september 9', 'new england patriots', '56 - 3', 'new york jets', 'schaefer stadium'], ['1979', 'december 9', 'new york jets', '27 - 26', 'new england patriots', 'shea stadium']]
|
lner thompson class b1
|
https://en.wikipedia.org/wiki/LNER_Thompson_Class_B1
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2079664-3.html.csv
|
ordinal
|
the number 18 lner thompson class b1 steam locomotive had the second lowest br number .
|
{'row': '2', 'col': '1', 'order': '2', 'col_other': 'n/a', 'max_or_min': 'min_to_max', 'value_mentioned': 'yes', 'scope': 'all', 'subset': None}
|
{'func': 'eq', 'args': [{'func': 'nth_min', 'args': ['all_rows', 'number', '2'], 'result': '18', 'ind': 0, 'tostr': 'nth_min { all_rows ; number ; 2 }', 'tointer': 'the 2nd minimum number record of all rows is 18 .'}, '18'], 'result': True, 'ind': 1, 'tostr': 'eq { nth_min { all_rows ; number ; 2 } ; 18 } = true', 'tointer': 'the 2nd minimum number record of all rows is 18 .'}
|
eq { nth_min { all_rows ; number ; 2 } ; 18 } = true
|
the 2nd minimum number record of all rows is 18 .
|
2
|
2
|
{'eq_1': 1, 'result_2': 2, 'nth_min_0': 0, 'all_rows_3': 3, 'number_4': 4, '2_5': 5, '18_6': 6}
|
{'eq_1': 'eq', 'result_2': 'true', 'nth_min_0': 'nth_min', 'all_rows_3': 'all_rows', 'number_4': 'number', '2_5': '2', '18_6': '18'}
|
{'eq_1': [2], 'result_2': [], 'nth_min_0': [1], 'all_rows_3': [0], 'number_4': [0], '2_5': [0], '18_6': [1]}
|
['number', 'previous br no', 'taken into deptal stock', 'withdrawn', 'disposal']
|
[['17', '61059', '1963', '1966', 'scrapped ( 1966 )'], ['18', '61181', '1963', '1965', 'scrapped ( 1966 )'], ['19', '61204', '1963', '1966', 'scrapped ( 1966 )'], ['20', '61205', '1963', '1965', 'scrapped ( 1966 )'], ['21', '61233', '1963', '1966', 'scrapped ( 1966 )'], ['22', '61252', '1963', '1964', 'scrapped ( 1966 )'], ['23', '61300', '1963', '1965', 'scrapped ( 1966 )'], ['24 ( 1st )', '61323', '1963', '1963', 'scrapped ( 1964 )'], ['24 ( 2nd )', '61375', '1963', '1966', 'scrapped ( 1966 )'], ['25', '61272', '1965', '1966', 'scrapped ( 1966 )'], ['26', '61138', '1965', '1967', 'scrapped ( 1968 )'], ['27', '61105', '1965', '1966', 'scrapped ( 1966 )'], ['28', '61194', '1965', '1966', 'scrapped ( 1966 )'], ['29', '61264', '1965', '1967', 'woodham brothers , later preserved'], ['30', '61050', '1966', '1968', 'scrapped ( 1968 )'], ['31 ( 2nd )', '61051', '1966', '1966', 'scrapped ( 1966 )']]
|
chevrolet hhr
|
https://en.wikipedia.org/wiki/Chevrolet_HHR
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1361602-1.html.csv
|
count
|
from 2006 to 2011 , six models of the chevrolet hhr used ecotec l61 i4 engines .
|
{'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'ecotec l61 i4', 'result': '6', 'col': '3', 'subset': None}
|
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'engine', 'ecotec l61 i4'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose engine record fuzzily matches to ecotec l61 i4 .', 'tostr': 'filter_eq { all_rows ; engine ; ecotec l61 i4 }'}], 'result': '6', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; engine ; ecotec l61 i4 } }', 'tointer': 'select the rows whose engine record fuzzily matches to ecotec l61 i4 . the number of such rows is 6 .'}, '6'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; engine ; ecotec l61 i4 } } ; 6 } = true', 'tointer': 'select the rows whose engine record fuzzily matches to ecotec l61 i4 . the number of such rows is 6 .'}
|
eq { count { filter_eq { all_rows ; engine ; ecotec l61 i4 } } ; 6 } = true
|
select the rows whose engine record fuzzily matches to ecotec l61 i4 . the number of such rows is 6 .
|
3
|
3
|
{'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'engine_5': 5, 'ecotec l61 i4_6': 6, '6_7': 7}
|
{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'engine_5': 'engine', 'ecotec l61 i4_6': 'ecotec l61 i4', '6_7': '6'}
|
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'engine_5': [0], 'ecotec l61 i4_6': [0], '6_7': [2]}
|
['year', 'trim', 'engine', 'power', 'torque', 'epa ( 2008 ) city']
|
[['2006', 'ls / lt', 'l ( cuin ) ecotec l61 i4', 'b', 'n / a', 'mpg - us ( l / 100 km , mpg - imp )'], ['2006', 'lt / 2lt', 'l ( cuin ) ecotec le5 i4', 'b', 'n / a', 'mpg - us ( l / 100 km , mpg - imp )'], ['2007', 'ls / lt', 'l ( cuin ) ecotec l61 i4', '-', 'n / a', 'mpg - us ( l / 100 km , mpg - imp )'], ['2007', 'ls / 2lt', 'l ( cuin ) ecotec le5 i4', 'b', 'n / a', 'mpg - us ( l / 100 km , mpg - imp )'], ['2008', 'ls / lt', 'l ( cuin ) ecotec l61 i4', '-', 'n / a', 'mpg - us ( l / 100 km , mpg - imp )'], ['2008', 'lt / 2lt', 'l ( cuin ) ecotec le5 i4', '-', 'n / a', 'mpg - us ( l / 100 km , mpg - imp )'], ['2008', 'ss', 'l ( cuin ) turbo ecotec lnf i4', 'b', 'n / a', 'mpg - us ( l / 100 km , mpg - imp )'], ['2009', 'ls / lt', 'l ( cuin ) ecotec l61 i4', '-', 'n / a', 'mpg - us ( l / 100 km , mpg - imp )'], ['2009', 'lt / 2lt', 'l ( cuin ) ecotec le5 i4', '-', 'n / a', 'mpg - us ( l / 100 km , mpg - imp )'], ['2009', 'ss', 'l ( cuin ) turbo ecotec lnf i4', 'b', 'n / a', 'mpg - us ( l / 100 km , mpg - imp )'], ['2010', 'ls / lt', 'l ( cuin ) ecotec l61 i4', '-', 'n / a', 'mpg - us ( l / 100 km , mpg - imp )'], ['2010', 'lt / 2lt', 'l ( cuin ) ecotec le5 i4', '-', 'n / a', 'mpg - us ( l / 100 km , mpg - imp )'], ['2010', 'ss', 'l ( cuin ) turbo ecotec lnf i4', 'b', 'n / a', 'mpg - us ( l / 100 km , mpg - imp )'], ['2011', 'ls / lt', 'l ( cuin ) ecotec l61 i4', '-', 'n / a', 'mpg - us ( l / 100 km , mpg - imp )'], ['2011', 'lt / 2lt', 'l ( cuin ) ecotec le5 i4', '-', 'n / a', 'mpg - us ( l / 100 km , mpg - imp )']]
|
nguyen tien minh
|
https://en.wikipedia.org/wiki/Nguyen_Tien_Minh
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12978997-1.html.csv
|
count
|
sho sasaki was the opponent in the final two times .
|
{'scope': 'all', 'criterion': 'equal', 'value': 'sho sasaki', 'result': '2', 'col': '4', 'subset': None}
|
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent in final', 'sho sasaki'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose opponent in final record fuzzily matches to sho sasaki .', 'tostr': 'filter_eq { all_rows ; opponent in final ; sho sasaki }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; opponent in final ; sho sasaki } }', 'tointer': 'select the rows whose opponent in final record fuzzily matches to sho sasaki . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; opponent in final ; sho sasaki } } ; 2 } = true', 'tointer': 'select the rows whose opponent in final record fuzzily matches to sho sasaki . the number of such rows is 2 .'}
|
eq { count { filter_eq { all_rows ; opponent in final ; sho sasaki } } ; 2 } = true
|
select the rows whose opponent in final record fuzzily matches to sho sasaki . 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 in final_5': 5, 'sho sasaki_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 in final_5': 'opponent in final', 'sho sasaki_6': 'sho sasaki', '2_7': '2'}
|
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'opponent in final_5': [0], 'sho sasaki_6': [0], '2_7': [2]}
|
['outcome', 'year', 'tournament', 'opponent in final', 'score']
|
[['1', '2013', 'us open grand prix gold', 'wong wing ki', '18 - 21 21 - 17 21 - 18'], ['1', '2012', 'chinese taipei open grand prix gold', 'chou tien - chen', '21 - 11 21 - 17'], ['1', '2012', 'vietnam open grand prix', 'takuma ueda', '21 - 14 21 - 19'], ['2', '2012', 'australia open grand prix gold', 'jin chen', '11 - 21 12 - 21'], ['2', '2011', 'us open grand prix gold', 'sho sasaki', '17 - 21 18 - 21'], ['1', '2011', 'vietnam open grand prix', 'sho sasaki', '21 - 13 21 - 17'], ['1', '2010', 'australia open grand prix', 'krishnan yogendran', '21 - 14 21 - 11'], ['1', '2009', 'vietnam open grand prix', 'chong wei feng', '21 - 7 , 19 - 21 , 21 - 14'], ['1', '2009', 'chinese taipei open grand prix gold', 'wong choong hann', '21 - 11 21 - 14'], ['1', '2009', 'thailand open grand prix gold', 'boonsak ponsana', '21 - 16 21 - 13'], ['1', '2008', 'vietnam open grand prix', 'chan yan kit', '24 - 22 21 - 18']]
|
1st aiba european 2008 olympic qualifying tournament
|
https://en.wikipedia.org/wiki/1st_AIBA_European_2008_Olympic_Qualifying_Tournament
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18801466-2.html.csv
|
superlative
|
germany had the most bronze medals at the 1st aiba european 2008 olympic qualifying tournament .
|
{'scope': 'all', 'col_superlative': '5', 'row_superlative': '15', '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', 'bronze'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; bronze }'}, 'nation'], 'result': 'germany ( ger )', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; bronze } ; nation }'}, 'germany ( ger )'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; bronze } ; nation } ; germany ( ger ) } = true', 'tointer': 'select the row whose bronze record of all rows is maximum . the nation record of this row is germany ( ger ) .'}
|
eq { hop { argmax { all_rows ; bronze } ; nation } ; germany ( ger ) } = true
|
select the row whose bronze record of all rows is maximum . the nation record of this row is germany ( ger ) .
|
3
|
3
|
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'bronze_5': 5, 'nation_6': 6, 'germany (ger)_7': 7}
|
{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'bronze_5': 'bronze', 'nation_6': 'nation', 'germany (ger)_7': 'germany ( ger )'}
|
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'bronze_5': [0], 'nation_6': [1], 'germany (ger)_7': [2]}
|
['rank', 'nation', 'gold', 'silver', 'bronze', 'total']
|
[['1', 'ukraine ( ukr )', '2', '2', '0', '4'], ['2', 'belarus ( blr )', '2', '1', '1', '4'], ['3', 'hungary ( hun )', '2', '0', '0', '2'], ['4', 'ireland ( irl )', '1', '0', '2', '3'], ['5', 'bulgaria ( bul )', '1', '0', '0', '1'], ['5', 'france ( fra )', '1', '0', '0', '1'], ['5', 'sweden ( swe )', '0', '0', '0', '1'], ['5', 'russia ( rus )', '1', '0', '0', '1'], ['9', 'great britain ( gbr ) eng', '0', '2', '2', '4'], ['10', 'azerbaijan ( aze )', '0', '1', '1', '2'], ['10', 'france ( fra )', '0', '1', '1', '2'], ['10', 'moldova ( mda )', '0', '1', '1', '2'], ['10', 'poland ( pol )', '0', '1', '1', '2'], ['14', 'croatia ( cro )', '0', '1', '0', '1'], ['15', 'germany ( ger )', '0', '0', '3', '3'], ['16', 'turkey ( tur )', '0', '0', '2', '2'], ['16', 'lithuania ( ltu )', '0', '0', '2', '2'], ['16', 'armenia ( arm )', '0', '0', '1', '1'], ['16', 'finland ( fin )', '0', '0', '1', '1']]
|
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/2-13219504-6.html.csv
|
count
|
a total of five bowlers in the 2007 icc world twenty20 had no wickets .
|
{'scope': 'all', 'criterion': 'equal', 'value': 'none', 'result': '5', 'col': '5', 'subset': None}
|
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'wickets', 'none'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose wickets record fuzzily matches to none .', 'tostr': 'filter_eq { all_rows ; wickets ; none }'}], 'result': '5', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; wickets ; none } }', 'tointer': 'select the rows whose wickets record fuzzily matches to none . the number of such rows is 5 .'}, '5'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; wickets ; none } } ; 5 } = true', 'tointer': 'select the rows whose wickets record fuzzily matches to none . the number of such rows is 5 .'}
|
eq { count { filter_eq { all_rows ; wickets ; none } } ; 5 } = true
|
select the rows whose wickets record fuzzily matches to none . 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, 'wickets_5': 5, 'none_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', 'wickets_5': 'wickets', 'none_6': 'none', '5_7': '5'}
|
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'wickets_5': [0], 'none_6': [0], '5_7': [2]}
|
['bowler', 'over no', 'venue', 'date', 'wickets']
|
[['shane bond', '1', 'durban', '2007 - 09 - 12', 'morris ouma bowled tanmay mishra caught oram'], ['chris martin', '9', 'durban', '2007 - 09 - 12', 'thomas odoyo caught taylor'], ['dewald nel', '2', 'durban', '2007 - 09 - 12', 'none'], ['syed rasel', '1', 'johannesburg', '2007 - 09 - 13', 'chris gayle caught kapali'], ['chaminda vaas', '1', 'johannesburg', '2007 - 09 - 14', 'morris ouma lbw'], ['irfan pathan', '9', 'durban', '2007 - 09 - 14', 'kamran akmal run out younis khan bowled'], ['shaun pollock', '1', 'cape town', '2007 - 09 - 16', 'luke wright caught de villiers'], ['dilhara fernando', '6', 'johannesburg', '2007 - 09 - 17', 'mohammad hafeez bowled'], ['shahid afridi', '9', 'johannesburg', '2007 - 09 - 18', 'andrew symonds bowled'], ['syed rasel', '2', 'johannesburg', '2007 - 09 - 18', 'none'], ['dilhara fernando', '4', 'johannesburg', '2007 - 09 - 18', 'tamim iqbal caught malinga aftab ahmed bowled'], ['mark gillespie', '4', 'durban', '2007 - 09 - 19', 'ab de villiers caught mccullum'], ['dilhara fernando', '2', 'cape town', '2007 - 09 - 20', 'none'], ['shanthakumaran sreesanth', '4', 'durban', '2007 - 09 - 22', 'none'], ['shanthakumaran sreesanth', '2', 'johannesburg', '2007 - 09 - 24', 'none']]
|
martina hingis
|
https://en.wikipedia.org/wiki/Martina_Hingis
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-19047-2.html.csv
|
unique
|
martina hingis only won a tournament played on grass once .
|
{'scope': 'all', 'row': '3', 'col': '4', 'col_other': '1', 'criterion': 'equal', 'value': 'grass', 'subset': None}
|
{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'surface', 'grass'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose surface record fuzzily matches to grass .', 'tostr': 'filter_eq { all_rows ; surface ; grass }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; surface ; grass } }', 'tointer': 'select the rows whose surface record fuzzily matches to grass . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'surface', 'grass'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose surface record fuzzily matches to grass .', 'tostr': 'filter_eq { all_rows ; surface ; grass }'}, 'outcome'], 'result': 'winner', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; surface ; grass } ; outcome }'}, 'winner'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; surface ; grass } ; outcome } ; winner }', 'tointer': 'the outcome record of this unqiue row is winner .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; surface ; grass } } ; eq { hop { filter_eq { all_rows ; surface ; grass } ; outcome } ; winner } } = true', 'tointer': 'select the rows whose surface record fuzzily matches to grass . there is only one such row in the table . the outcome record of this unqiue row is winner .'}
|
and { only { filter_eq { all_rows ; surface ; grass } } ; eq { hop { filter_eq { all_rows ; surface ; grass } ; outcome } ; winner } } = true
|
select the rows whose surface record fuzzily matches to grass . there is only one such row in the table . the outcome record of this unqiue row is winner .
|
6
|
5
|
{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'surface_7': 7, 'grass_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'outcome_9': 9, 'winner_10': 10}
|
{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'surface_7': 'surface', 'grass_8': 'grass', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'outcome_9': 'outcome', 'winner_10': 'winner'}
|
{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'surface_7': [0], 'grass_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'outcome_9': [2], 'winner_10': [3]}
|
['outcome', 'year', 'championship', 'surface', 'opponent in the final', 'score in the final']
|
[['winner', '1997', 'australian open', 'hard', 'mary pierce', '6 - 2 , 6 - 2'], ['runner - up', '1997', 'french open', 'clay', 'iva majoli', '6 - 4 , 6 - 2'], ['winner', '1997', 'wimbledon', 'grass', 'jana novotná', '2 - 6 , 6 - 3 , 6 - 3'], ['winner', '1997', 'us open', 'hard', 'venus williams', '6 - 0 , 6 - 4'], ['winner', '1998', 'australian open ( 2 )', 'hard', 'conchita martínez', '6 - 3 , 6 - 3'], ['runner - up', '1998', 'us open', 'hard', 'lindsay davenport', '6 - 3 , 7 - 5'], ['winner', '1999', 'australian open ( 3 )', 'hard', 'amélie mauresmo', '6 - 2 , 6 - 3'], ['runner - up', '1999', 'french open ( 2 )', 'clay', 'steffi graf', '4 - 6 , 7 - 5 , 6 - 2'], ['runner - up', '1999', 'us open ( 2 )', 'hard', 'serena williams', '6 - 3 , 7 - 6 ( 4 )'], ['runner - up', '2000', 'australian open', 'hard', 'lindsay davenport', '6 - 1 , 7 - 5'], ['runner - up', '2001', 'australian open ( 2 )', 'hard', 'jennifer capriati', '6 - 4 , 6 - 3']]
|
alex bogdanovic
|
https://en.wikipedia.org/wiki/Alex_Bogdanovic
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1564278-3.html.csv
|
unique
|
the tournament in oklahoma city was the only one held in 2013 .
|
{'scope': 'all', 'row': '8', 'col': '1', 'col_other': '2', 'criterion': 'fuzzily_match', 'value': '2013', 'subset': None}
|
{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', '2013'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose date record fuzzily matches to 2013 .', 'tostr': 'filter_eq { all_rows ; date ; 2013 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; date ; 2013 } }', 'tointer': 'select the rows whose date record fuzzily matches to 2013 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', '2013'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose date record fuzzily matches to 2013 .', 'tostr': 'filter_eq { all_rows ; date ; 2013 }'}, 'tournament'], 'result': 'oklahoma city , usa f9', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; date ; 2013 } ; tournament }'}, 'oklahoma city , usa f9'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; date ; 2013 } ; tournament } ; oklahoma city , usa f9 }', 'tointer': 'the tournament record of this unqiue row is oklahoma city , usa f9 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; date ; 2013 } } ; eq { hop { filter_eq { all_rows ; date ; 2013 } ; tournament } ; oklahoma city , usa f9 } } = true', 'tointer': 'select the rows whose date record fuzzily matches to 2013 . there is only one such row in the table . the tournament record of this unqiue row is oklahoma city , usa f9 .'}
|
and { only { filter_eq { all_rows ; date ; 2013 } } ; eq { hop { filter_eq { all_rows ; date ; 2013 } ; tournament } ; oklahoma city , usa f9 } } = true
|
select the rows whose date record fuzzily matches to 2013 . there is only one such row in the table . the tournament record of this unqiue row is oklahoma city , usa f9 .
|
6
|
5
|
{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'date_7': 7, '2013_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'tournament_9': 9, 'oklahoma city , usa f9_10': 10}
|
{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'date_7': 'date', '2013_8': '2013', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'tournament_9': 'tournament', 'oklahoma city , usa f9_10': 'oklahoma city , usa f9'}
|
{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'date_7': [0], '2013_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'tournament_9': [2], 'oklahoma city , usa f9_10': [3]}
|
['date', 'tournament', 'surface', 'opponent in the final', 'score']
|
[['2 june 2003', 'surbiton , great britain', 'grass', 'wesley moodie', '4 - 6 , 7 - 6 ( 2 ) , 1 - 6'], ['26 april 2004', 'glasgow , great britain f1', 'carpet', 'gaël monfils', '4 - 6 , 3 - 6'], ['5 july 2004', 'nottingham , great britain', 'grass', 'jo - wilfried tsonga', '3 - 6 , 4 - 6'], ['2 october 2006', 'mons , belgium', 'hard', 'janko tipsarević', '4 - 6 , 6 - 1 , 2 - 6'], ['16 april 2007', 'cardiff , great britain', 'hard', 'frédéric niemeyer', '4 - 6 , 5 - 7'], ['4 april 2011', 'little rock , ar , usa f9', 'hard', 'arnau brugués - davi', '3 - 6 , 1 - 6'], ['24 september 2012', 'irvine , ca , usa f26', 'hard', 'daniel nguyen', '5 - 7 , 2 - 6'], ['8 april 2013', 'oklahoma city , usa f9', 'hard', 'rik de voest', '3 - 6 , 2 - 6']]
|
weightlifting at the 2007 pan american games
|
https://en.wikipedia.org/wiki/Weightlifting_at_the_2007_Pan_American_Games
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17703223-5.html.csv
|
superlative
|
of the weightlifters who could snatch more than 150 at the 2007 pan american games , herbys márquez had the highest bodyweight .
|
{'scope': 'subset', 'col_superlative': '2', 'row_superlative': '3', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': {'col': '3', 'criterion': 'greater_than', 'value': '150'}}
|
{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'snatch', '150'], 'result': None, 'ind': 0, 'tostr': 'filter_greater { all_rows ; snatch ; 150 }', 'tointer': 'select the rows whose snatch record is greater than 150 .'}, 'bodyweight'], 'result': None, 'ind': 1, 'tostr': 'argmax { filter_greater { all_rows ; snatch ; 150 } ; bodyweight }'}, 'name'], 'result': 'herbys márquez ( ven )', 'ind': 2, 'tostr': 'hop { argmax { filter_greater { all_rows ; snatch ; 150 } ; bodyweight } ; name }'}, 'herbys márquez ( ven )'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { argmax { filter_greater { all_rows ; snatch ; 150 } ; bodyweight } ; name } ; herbys márquez ( ven ) } = true', 'tointer': 'select the rows whose snatch record is greater than 150 . select the row whose bodyweight record of these rows is maximum . the name record of this row is herbys márquez ( ven ) .'}
|
eq { hop { argmax { filter_greater { all_rows ; snatch ; 150 } ; bodyweight } ; name } ; herbys márquez ( ven ) } = true
|
select the rows whose snatch record is greater than 150 . select the row whose bodyweight record of these rows is maximum . the name record of this row is herbys márquez ( ven ) .
|
4
|
4
|
{'str_eq_3': 3, 'result_4': 4, 'str_hop_2': 2, 'argmax_1': 1, 'filter_greater_0': 0, 'all_rows_5': 5, 'snatch_6': 6, '150_7': 7, 'bodyweight_8': 8, 'name_9': 9, 'herbys márquez ( ven )_10': 10}
|
{'str_eq_3': 'str_eq', 'result_4': 'true', 'str_hop_2': 'str_hop', 'argmax_1': 'argmax', 'filter_greater_0': 'filter_greater', 'all_rows_5': 'all_rows', 'snatch_6': 'snatch', '150_7': '150', 'bodyweight_8': 'bodyweight', 'name_9': 'name', 'herbys márquez ( ven )_10': 'herbys márquez ( ven )'}
|
{'str_eq_3': [4], 'result_4': [], 'str_hop_2': [3], 'argmax_1': [2], 'filter_greater_0': [1], 'all_rows_5': [0], 'snatch_6': [0], '150_7': [0], 'bodyweight_8': [1], 'name_9': [2], 'herbys márquez ( ven )_10': [3]}
|
['name', 'bodyweight', 'snatch', 'clean & jerk', 'total ( kg )']
|
[['josé oliver ruíz ( col )', '84.45', '160.0', '203.0', '363.0'], ['jadier valladares ( cub )', '84.50', '161.0', '202.0', '363.0'], ['herbys márquez ( ven )', '84.75', '155.0', '195.0', '350.0'], ['kendrick farris ( usa )', '84.15', '158.0', '191.0', '349.0'], ['juan quiterio ( dom )', '84.35', '145.0', '185.0', '330.0'], ['buck ramsay ( can )', '84.75', '140.0', '178.0', '318.0'], ['rafael andrade ( bra )', '83.75', '140.0', '175.0', '315.0'], ['edward silva ( uru )', '84.10', '120.0', '150.0', '270.0']]
|
dexter ( season 3 )
|
https://en.wikipedia.org/wiki/Dexter_%28season_3%29
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-24132054-1.html.csv
|
count
|
john dahl directed two episdoes in the 2008 season of the series .
|
{'scope': 'all', 'criterion': 'equal', 'value': 'john dahl', 'result': '2', 'col': '4', 'subset': None}
|
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'directed by', 'john dahl'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose directed by record fuzzily matches to john dahl .', 'tostr': 'filter_eq { all_rows ; directed by ; john dahl }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; directed by ; john dahl } }', 'tointer': 'select the rows whose directed by record fuzzily matches to john dahl . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; directed by ; john dahl } } ; 2 } = true', 'tointer': 'select the rows whose directed by record fuzzily matches to john dahl . the number of such rows is 2 .'}
|
eq { count { filter_eq { all_rows ; directed by ; john dahl } } ; 2 } = true
|
select the rows whose directed by record fuzzily matches to john dahl . 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, 'directed by_5': 5, 'john dahl_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', 'directed by_5': 'directed by', 'john dahl_6': 'john dahl', '2_7': '2'}
|
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'directed by_5': [0], 'john dahl_6': [0], '2_7': [2]}
|
['no in series', 'no in season', 'title', 'directed by', 'written by', 'original air date', 'us viewers ( millions )']
|
[['25', '1', 'our father', 'keith gordon', 'clyde phillips', 'september 28 , 2008', 'n / a'], ['26', '2', 'finding freebo', 'marcos siega', 'melissa rosenberg', 'october 5 , 2008', '0.79'], ['27', '3', 'the lion sleeps tonight', 'john dahl', 'scott buck', 'october 12 , 2008', 'n / a'], ['28', '4', 'all in the family', 'keith gordon', 'adam e fierro', 'october 19 , 2008', '0.86'], ['29', '5', 'turning biminese', 'marcos siega', 'tim schlattmann', 'october 26 , 2008', 'n / a'], ['30', '6', 'sã\xad se puede', 'ernest dickerson', 'charles h eglee', 'november 2 , 2008', 'n / a'], ['31', '7', 'easy as pie', 'steve shill', 'lauren gussis', 'november 9 , 2008', 'n / a'], ['32', '8', 'the damage a man can do', 'marcos siega', 'scott buck', 'november 16 , 2008', 'n / a'], ['34', '10', 'go your own way', 'john dahl', 'tim schlattmann', 'november 30 , 2008', 'n / a'], ['35', '11', 'i had a dream', 'marcos siega', 'charles h eglee and lauren gussis', 'december 7 , 2008', 'n / a']]
|
ken schrader
|
https://en.wikipedia.org/wiki/Ken_Schrader
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1671401-3.html.csv
|
aggregation
|
ken schrader 's average winnings per year between 1995 and 2002 ( barring 1998 ) was 44881 .
|
{'scope': 'subset', 'col': '9', 'type': 'average', 'result': '44881', 'subset': {'col': '1', 'criterion': 'less_than_eq', 'value': '2002'}}
|
{'func': 'round_eq', 'args': [{'func': 'avg', 'args': [{'func': 'filter_less_eq', 'args': ['all_rows', 'year', '2002'], 'result': None, 'ind': 0, 'tostr': 'filter_less_eq { all_rows ; year ; 2002 }', 'tointer': 'select the rows whose year record is less than or equal to 2002 .'}, 'winnings'], 'result': '44881', 'ind': 1, 'tostr': 'avg { filter_less_eq { all_rows ; year ; 2002 } ; winnings }'}, '44881'], 'result': True, 'ind': 2, 'tostr': 'round_eq { avg { filter_less_eq { all_rows ; year ; 2002 } ; winnings } ; 44881 } = true', 'tointer': 'select the rows whose year record is less than or equal to 2002 . the average of the winnings record of these rows is 44881 .'}
|
round_eq { avg { filter_less_eq { all_rows ; year ; 2002 } ; winnings } ; 44881 } = true
|
select the rows whose year record is less than or equal to 2002 . the average of the winnings record of these rows is 44881 .
|
3
|
3
|
{'eq_2': 2, 'result_3': 3, 'avg_1': 1, 'filter_less_eq_0': 0, 'all_rows_4': 4, 'year_5': 5, '2002_6': 6, 'winnings_7': 7, '44881_8': 8}
|
{'eq_2': 'eq', 'result_3': 'true', 'avg_1': 'avg', 'filter_less_eq_0': 'filter_less_eq', 'all_rows_4': 'all_rows', 'year_5': 'year', '2002_6': '2002', 'winnings_7': 'winnings', '44881_8': '44881'}
|
{'eq_2': [3], 'result_3': [], 'avg_1': [2], 'filter_less_eq_0': [1], 'all_rows_4': [0], 'year_5': [0], '2002_6': [0], 'winnings_7': [1], '44881_8': [2]}
|
['year', 'starts', 'wins', 'top 5', 'top 10', 'poles', 'avg start', 'avg finish', 'winnings', 'position', 'team ( s )']
|
[['1995', '7', '1', '3', '3', '0', '8.3', '16.7', '50030', '29th', 'ken schrader racing'], ['1996', '4', '0', '0', '2', '0', '12.2', '16.0', '29250', '46th', 'ken schrader racing darrell waltrip motorsports'], ['1997', '2', '0', '0', '1', '0', '10.0', '12.0', '21125', '69th', 'ken schrader racing aj foyt enterprises'], ['1999', '1', '0', '0', '0', '0', '11.0', '36.0', '6490', '120th', 'ken schrader racing'], ['2000', '5', '0', '1', '3', '0', '10.4', '10.0', '52595', '35th', 'ken schrader racing'], ['2001', '8', '0', '1', '5', '0', '12.4', '11.5', '90670', '28th', 'ken schrader racing'], ['2002', '8', '0', '0', '3', '0', '13.9', '20.9', '64010', '27th', 'ken schrader racing'], ['2003', '11', '0', '0', '3', '0', '13.6', '15.7', '99665', '23rd', 'ken schrader racing'], ['2004', '12', '0', '1', '4', '1', '17.3', '18.6', '103797', '28th', 'ken schrader racing'], ['2005', '10', '0', '0', '1', '0', '23.5', '20.6', '82348', '31st', 'ken schrader racing darrell waltrip motorsports'], ['2007', '17', '0', '2', '3', '0', '20.6', '17.2', '245584', '19th', 'bobby hamilton racing'], ['2008', '3', '0', '1', '1', '0', '25.7', '16.7', '29530', '51st', 'ken schrader racing'], ['2009', '2', '0', '0', '1', '0', '17.5', '13.0', '18935', '60th', 'ken schrader racing']]
|
november nine
|
https://en.wikipedia.org/wiki/November_Nine
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-23696862-6.html.csv
|
aggregation
|
poker players of the november nine had an average prize purse of 3137419 .
|
{'scope': 'all', 'col': '7', 'type': 'average', 'result': '3137419', 'subset': None}
|
{'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'prize'], 'result': '3137419', 'ind': 0, 'tostr': 'avg { all_rows ; prize }'}, '3137419'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; prize } ; 3137419 } = true', 'tointer': 'the average of the prize record of all rows is 3137419 .'}
|
round_eq { avg { all_rows ; prize } ; 3137419 } = true
|
the average of the prize record of all rows is 3137419 .
|
2
|
2
|
{'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'prize_4': 4, '3137419_5': 5}
|
{'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'prize_4': 'prize', '3137419_5': '3137419'}
|
{'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'prize_4': [0], '3137419_5': [1]}
|
['name', 'starting chip count', 'wsop bracelets', 'wsop cashes', 'wsop earnings', 'final place', 'prize']
|
[['jesse sylvia', '43875000', '0', '2', '36372', '2nd', '5295149'], ['andras koroknai', '29375000', '0', '2', '39371', '6th', '1640461'], ['greg merson', '28725000', '1', '5', '1253501', '1st', '8531853'], ['russell thomas', '24800000', '0', '3', '126796', '4th', '2850494'], ['steven gee', '16860000', '1', '4', '480822', '9th', '754798'], ['michael esposito', '16260000', '0', '3', '27311', '7th', '1257790'], ['robert salaburu', '15155000', '0', '0', '0', '8th', '971252'], ['jacob balsiger', '13115000', '0', '1', '3531', '3rd', '3797558']]
|
naoki tsukahara
|
https://en.wikipedia.org/wiki/Naoki_Tsukahara
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11401861-1.html.csv
|
majority
|
all of the competitions naoki tsukahara was at were after the year 2000 .
|
{'scope': 'all', 'col': '1', 'most_or_all': 'all', 'criterion': 'greater_than', 'value': '2000', 'subset': None}
|
{'func': 'all_greater', 'args': ['all_rows', 'year', '2000'], 'result': True, 'ind': 0, 'tointer': 'for the year records of all rows , all of them are greater than 2000 .', 'tostr': 'all_greater { all_rows ; year ; 2000 } = true'}
|
all_greater { all_rows ; year ; 2000 } = true
|
for the year records of all rows , all of them are greater than 2000 .
|
1
|
1
|
{'all_greater_0': 0, 'result_1': 1, 'all_rows_2': 2, 'year_3': 3, '2000_4': 4}
|
{'all_greater_0': 'all_greater', 'result_1': 'true', 'all_rows_2': 'all_rows', 'year_3': 'year', '2000_4': '2000'}
|
{'all_greater_0': [1], 'result_1': [], 'all_rows_2': [0], 'year_3': [0], '2000_4': [0]}
|
['year', 'competition', 'venue', 'position', 'notes']
|
[['2003', '58th national sports festival of japan', 'shizuoka , japan', '7th', '100 m'], ['2004', 'japan student athletics championships', 'unknown , japan', '6th', '200 m'], ['2004', 'world junior championships', 'grosseto , italy', '3rd', '4x100 m relay'], ['2006', 'kanto students athletics championships', 'kantō , japan', '2nd', '100 m'], ['2006', 'kanto students athletics championships', 'kantō , japan', '2nd', '200 m'], ['2006', 'japan association of athletics championships', 'tokyo , japan', '1st', '100 m'], ['2006', 'japan association of athletics championships', 'tokyo , japan', '3rd', '200 m'], ['2006', 'world cup', 'athens , greece', '3rd', '4x100 m relay'], ['2006', 'asian games', 'doha , qatar', '2nd', '100 m'], ['2006', 'asian games', 'doha , qatar', '2nd', '4x100 m relay'], ['2008', 'olympic games', 'beijing , china', '3rd', '4x100 m relay']]
|
longyan
|
https://en.wikipedia.org/wiki/Longyan
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1204998-2.html.csv
|
aggregation
|
the average area of each district , city , or county is just over 2700 square km .
|
{'scope': 'all', 'col': '6', 'type': 'average', 'result': 'over 2700', 'subset': None}
|
{'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'area'], 'result': 'over 2700', 'ind': 0, 'tostr': 'avg { all_rows ; area }'}, 'over 2700'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; area } ; over 2700 } = true', 'tointer': 'the average of the area record of all rows is over 2700 .'}
|
round_eq { avg { all_rows ; area } ; over 2700 } = true
|
the average of the area record of all rows is over 2700 .
|
2
|
2
|
{'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'area_4': 4, 'over 2700_5': 5}
|
{'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'area_4': 'area', 'over 2700_5': 'over 2700'}
|
{'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'area_4': [0], 'over 2700_5': [1]}
|
['english name', 'simplified', 'traditional', 'pinyin', 'hakka', 'area', 'population', 'density']
|
[['xinluo district', '新罗区', '新羅區', 'xīnluó qū', 'sîn - lò - khî', '2685', '662429', '247'], ['zhangping city', '漳平市', '漳平市', 'zhāngpíng shì', 'chông - phìn - sṳ', '2975', '240194', '81'], ['changting county', '长汀县', '長汀縣', 'chángtīng xiàn', 'tshòng - tin - yen', '3099', '393390', '127'], ['yongding county', '永定县', '永定縣', 'yǒngdìng xiàn', 'yún - thin - yen', '2216', '362658', '164'], ['shanghang county', '上杭县', '上杭縣', 'shàngháng xiàn', 'sông - hông - yen', '2879', '374047', '130'], ['wuping county', '武平县', '武平縣', 'wǔpíng xiàn', 'vú - phìn - yen', '2630', '278182', '106']]
|
list of ultras of africa
|
https://en.wikipedia.org/wiki/List_of_Ultras_of_Africa
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18947170-11.html.csv
|
count
|
three of the ultras peaks are located in madagascar island .
|
{'scope': 'all', 'criterion': 'equal', 'value': 'madagascar', 'result': '3', 'col': '2', 'subset': None}
|
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'madagascar'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose country record fuzzily matches to madagascar .', 'tostr': 'filter_eq { all_rows ; country ; madagascar }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; country ; madagascar } }', 'tointer': 'select the rows whose country record fuzzily matches to madagascar . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; country ; madagascar } } ; 3 } = true', 'tointer': 'select the rows whose country record fuzzily matches to madagascar . the number of such rows is 3 .'}
|
eq { count { filter_eq { all_rows ; country ; madagascar } } ; 3 } = true
|
select the rows whose country record fuzzily matches to madagascar . 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, 'country_5': 5, 'madagascar_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', 'country_5': 'country', 'madagascar_6': 'madagascar', '3_7': '3'}
|
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'country_5': [0], 'madagascar_6': [0], '3_7': [2]}
|
['peak', 'country', 'elevation ( m )', 'prominence ( m )', 'col ( m )']
|
[['piton des neiges', 'france ( rãunion )', '3069', '3069', '0'], ['maromokotro', 'madagascar', '2876', '2876', '0'], ['mount karthala', 'comoros ( grande comore )', '2361', '2361', '0'], ['pic boby', 'madagascar', '2658', '1875', '783'], ['tsiafajavona', 'madagascar', '2643', '1663', '980'], ['ntingui', 'comoros ( anjouan )', '1595', '1595', '0']]
|
united states house of representatives elections , 1986
|
https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1986
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1341586-19.html.csv
|
comparative
|
jerry huckaby was in office before buddy roemer served his term .
|
{'row_1': '5', 'row_2': '4', 'col': '4', 'col_other': '2', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None}
|
{'func': 'less', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'incumbent', 'jerry huckaby'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose incumbent record fuzzily matches to jerry huckaby .', 'tostr': 'filter_eq { all_rows ; incumbent ; jerry huckaby }'}, 'first elected'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; incumbent ; jerry huckaby } ; first elected }', 'tointer': 'select the rows whose incumbent record fuzzily matches to jerry huckaby . take the first elected record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'incumbent', 'buddy roemer'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose incumbent record fuzzily matches to buddy roemer .', 'tostr': 'filter_eq { all_rows ; incumbent ; buddy roemer }'}, 'first elected'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; incumbent ; buddy roemer } ; first elected }', 'tointer': 'select the rows whose incumbent record fuzzily matches to buddy roemer . take the first elected record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; incumbent ; jerry huckaby } ; first elected } ; hop { filter_eq { all_rows ; incumbent ; buddy roemer } ; first elected } } = true', 'tointer': 'select the rows whose incumbent record fuzzily matches to jerry huckaby . take the first elected record of this row . select the rows whose incumbent record fuzzily matches to buddy roemer . take the first elected record of this row . the first record is less than the second record .'}
|
less { hop { filter_eq { all_rows ; incumbent ; jerry huckaby } ; first elected } ; hop { filter_eq { all_rows ; incumbent ; buddy roemer } ; first elected } } = true
|
select the rows whose incumbent record fuzzily matches to jerry huckaby . take the first elected record of this row . select the rows whose incumbent record fuzzily matches to buddy roemer . take the first elected record of this row . the first record is less than the second record .
|
5
|
5
|
{'less_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'incumbent_7': 7, 'jerry huckaby_8': 8, 'first elected_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'incumbent_11': 11, 'buddy roemer_12': 12, 'first elected_13': 13}
|
{'less_4': 'less', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'incumbent_7': 'incumbent', 'jerry huckaby_8': 'jerry huckaby', 'first elected_9': 'first elected', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'incumbent_11': 'incumbent', 'buddy roemer_12': 'buddy roemer', 'first elected_13': 'first elected'}
|
{'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'incumbent_7': [0], 'jerry huckaby_8': [0], 'first elected_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'incumbent_11': [1], 'buddy roemer_12': [1], 'first elected_13': [3]}
|
['district', 'incumbent', 'party', 'first elected', 'result', 'candidates']
|
[['louisiana 1', 'bob livingston', 'republican', '1977', 're - elected', 'bob livingston ( r ) unopposed'], ['louisiana 2', 'lindy boggs', 'democratic', '1973', 're - elected', 'lindy boggs ( d ) unopposed'], ['louisiana 3', 'billy tauzin', 'democratic', '1980', 're - elected', 'billy tauzin ( d ) unopposed'], ['louisiana 4', 'buddy roemer', 'democratic', '1980', 're - elected', 'buddy roemer ( d ) unopposed'], ['louisiana 5', 'jerry huckaby', 'democratic', '1976', 're - elected', 'jerry huckaby ( d ) unopposed'], ['louisiana 6', 'henson moore', 'republican', '1974', 'retired to run for u s senate republican hold', 'richard baker ( r ) unopposed']]
|
indiana high school athletics conferences : ohio river valley - western indiana
|
https://en.wikipedia.org/wiki/Indiana_High_School_Athletics_Conferences%3A_Ohio_River_Valley_%E2%80%93_Western_Indiana
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18974097-9.html.csv
|
majority
|
at the indiana high school athletics conferences : ohio river valley - western indiana , majority of schools that belong to aa ihsaa class are from 28 greene county .
|
{'scope': 'subset', 'col': '6', 'most_or_all': 'most', 'criterion': 'equal', 'value': '28 greene', 'subset': {'col': '5', 'criterion': 'equal', 'value': 'aa'}}
|
{'func': 'most_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'ihsaa class', 'aa'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; ihsaa class ; aa }', 'tointer': 'select the rows whose ihsaa class record fuzzily matches to aa .'}, 'county', '28 greene'], 'result': True, 'ind': 1, 'tointer': 'select the rows whose ihsaa class record fuzzily matches to aa . for the county records of these rows , most of them fuzzily match to 28 greene .', 'tostr': 'most_eq { filter_eq { all_rows ; ihsaa class ; aa } ; county ; 28 greene } = true'}
|
most_eq { filter_eq { all_rows ; ihsaa class ; aa } ; county ; 28 greene } = true
|
select the rows whose ihsaa class record fuzzily matches to aa . for the county records of these rows , most of them fuzzily match to 28 greene .
|
2
|
2
|
{'most_str_eq_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, 'ihsaa class_4': 4, 'aa_5': 5, 'county_6': 6, '28 greene_7': 7}
|
{'most_str_eq_1': 'most_str_eq', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'ihsaa class_4': 'ihsaa class', 'aa_5': 'aa', 'county_6': 'county', '28 greene_7': '28 greene'}
|
{'most_str_eq_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'ihsaa class_4': [0], 'aa_5': [0], 'county_6': [1], '28 greene_7': [1]}
|
['school', 'location', 'mascot', 'enrollment', 'ihsaa class', 'county']
|
[['bloomfield', 'bloomfield', 'cardinals', '337', 'aa', '28 greene'], ['clay city', 'clay city', 'eels', '272', 'a', '11 clay'], ['eastern greene', 'bloomfield', 'thunderbirds', '406', 'aa', '28 greene'], ['linton stockton', 'linton', 'miners', '344', 'aa', '28 greene'], ['north central farmersburg', 'farmersburg', 'thunderbirds', '336', 'aa', '77 sullivan'], ['north daviess', 'elnora', 'cougars', '306', 'a', '14 daviess'], ['shakamak', 'jasonville', 'lakers', '258', 'a', '28 greene'], ['union dugger', 'dugger', 'bulldogs', '117', 'a', '77 sullivan'], ['white river valley', 'switz city', 'wolverines', '253', 'a', '28 greene']]
|
2008 - 09 detroit red wings season
|
https://en.wikipedia.org/wiki/2008%E2%80%9309_Detroit_Red_Wings_season
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17371135-30.html.csv
|
majority
|
in the 2008-09 detroit red wings season , most of the centers are from sweden .
|
{'scope': 'subset', 'col': '5', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'sweden', 'subset': {'col': '4', 'criterion': 'equal', 'value': 'center'}}
|
{'func': 'most_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'position', 'center'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; position ; center }', 'tointer': 'select the rows whose position record fuzzily matches to center .'}, 'nationality', 'sweden'], 'result': True, 'ind': 1, 'tointer': 'select the rows whose position record fuzzily matches to center . for the nationality records of these rows , most of them fuzzily match to sweden .', 'tostr': 'most_eq { filter_eq { all_rows ; position ; center } ; nationality ; sweden } = true'}
|
most_eq { filter_eq { all_rows ; position ; center } ; nationality ; sweden } = true
|
select the rows whose position record fuzzily matches to center . for the nationality records of these rows , most of them fuzzily match to sweden .
|
2
|
2
|
{'most_str_eq_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, 'position_4': 4, 'center_5': 5, 'nationality_6': 6, 'sweden_7': 7}
|
{'most_str_eq_1': 'most_str_eq', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'position_4': 'position', 'center_5': 'center', 'nationality_6': 'nationality', 'sweden_7': 'sweden'}
|
{'most_str_eq_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'position_4': [0], 'center_5': [0], 'nationality_6': [1], 'sweden_7': [1]}
|
['round', 'overall pick', 'player', 'position', 'nationality', 'college / junior / club team ( league )']
|
[['1', '30', 'thomas mccollum', 'goaltender', 'united states', 'guelph storm ( ohl )'], ['3', '91', 'max nicastro', 'defenseman', 'united states', 'chicago steel ( ushl )'], ['4', '121', 'gustav nyquist', 'center', 'sweden', 'malmö redhawks ( sweden jr )'], ['5', '151', 'julien cayer', 'center', 'canada', 'northwood school ( hs - new york )'], ['6', '181', 'stephen johnston', 'left wing', 'canada', 'belleville bulls ( ohl )'], ['7', '211', 'jesper samuelsson', 'center', 'sweden', 'hc vita hästen ( swe - 3 )']]
|
aguaclara
|
https://en.wikipedia.org/wiki/AguaClara
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18268930-1.html.csv
|
superlative
|
marcala , hon is the aguaclara location that has the highest design flow in lpm .
|
{'scope': 'all', 'col_superlative': '6', 'row_superlative': '3', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None}
|
{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'design flow ( lpm )'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; design flow ( lpm ) }'}, 'location'], 'result': 'marcala , hon', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; design flow ( lpm ) } ; location }'}, 'marcala , hon'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; design flow ( lpm ) } ; location } ; marcala , hon } = true', 'tointer': 'select the row whose design flow ( lpm ) record of all rows is maximum . the location record of this row is marcala , hon .'}
|
eq { hop { argmax { all_rows ; design flow ( lpm ) } ; location } ; marcala , hon } = true
|
select the row whose design flow ( lpm ) record of all rows is maximum . the location record of this row is marcala , hon .
|
3
|
3
|
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'design flow (lpm)_5': 5, 'location_6': 6, 'marcala , hon_7': 7}
|
{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'design flow (lpm)_5': 'design flow ( lpm )', 'location_6': 'location', 'marcala , hon_7': 'marcala , hon'}
|
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'design flow (lpm)_5': [0], 'location_6': [1], 'marcala , hon_7': [2]}
|
['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']]
|
tamil nadu dr. m.g.r. medical university
|
https://en.wikipedia.org/wiki/Tamil_Nadu_Dr._M.G.R._Medical_University
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11184686-1.html.csv
|
comparative
|
government thiruvarur medical college is newer than government theni medical college .
|
{'row_1': '17', 'row_2': '14', 'col': '5', 'col_other': '1', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None}
|
{'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'college name', 'government thiruvarur medical college'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose college name record fuzzily matches to government thiruvarur medical college .', 'tostr': 'filter_eq { all_rows ; college name ; government thiruvarur medical college }'}, 'estd'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; college name ; government thiruvarur medical college } ; estd }', 'tointer': 'select the rows whose college name record fuzzily matches to government thiruvarur medical college . take the estd record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'college name', 'government theni medical college'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose college name record fuzzily matches to government theni medical college .', 'tostr': 'filter_eq { all_rows ; college name ; government theni medical college }'}, 'estd'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; college name ; government theni medical college } ; estd }', 'tointer': 'select the rows whose college name record fuzzily matches to government theni medical college . take the estd record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; college name ; government thiruvarur medical college } ; estd } ; hop { filter_eq { all_rows ; college name ; government theni medical college } ; estd } } = true', 'tointer': 'select the rows whose college name record fuzzily matches to government thiruvarur medical college . take the estd record of this row . select the rows whose college name record fuzzily matches to government theni medical college . take the estd record of this row . the first record is greater than the second record .'}
|
greater { hop { filter_eq { all_rows ; college name ; government thiruvarur medical college } ; estd } ; hop { filter_eq { all_rows ; college name ; government theni medical college } ; estd } } = true
|
select the rows whose college name record fuzzily matches to government thiruvarur medical college . take the estd record of this row . select the rows whose college name record fuzzily matches to government theni medical college . take the estd 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, 'college name_7': 7, 'government thiruvarur medical college_8': 8, 'estd_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'college name_11': 11, 'government theni medical college_12': 12, 'estd_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', 'college name_7': 'college name', 'government thiruvarur medical college_8': 'government thiruvarur medical college', 'estd_9': 'estd', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'college name_11': 'college name', 'government theni medical college_12': 'government theni medical college', 'estd_13': 'estd'}
|
{'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'college name_7': [0], 'government thiruvarur medical college_8': [0], 'estd_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'college name_11': [1], 'government theni medical college_12': [1], 'estd_13': [3]}
|
['college name', 'location', 'district', 'affiliation', 'estd']
|
[['thanjavur medical college', 'thanjavur', 'thanjavur district', 'tamil nadu dr mgr medical university', '1958'], ['madras medical college and research institute', 'park town , chennai', 'chennai district', 'tamil nadu dr mgr medical university', '1835'], ['stanley medical college', 'royapuram , chennai', 'chennai district', 'tamil nadu dr mgr medical university', '1938'], ['government kilpauk medical college', 'chetput ( chennai ) chennai', 'chennai district', 'tamil nadu dr mgr medical university', '1960'], ['chengalpattu medical college', 'chengalpattu', 'kanchipuram district', 'tamil nadu dr mgr medical university', '1965'], ['madurai medical college', 'madurai', 'madurai district', 'tamil nadu dr mgr medical university', '1954'], ['coimbatore medical college', 'coimbatore', 'coimbatore', 'tamil nadu dr mgr medical university', '1966'], ['tirunelveli medical college', 'tirunelveli', 'tirunelveli district', 'tamil nadu dr mgr medical university', 'july 1966'], ['mohan kumaramangalam medical college', 'salem , tamil nadu', 'salem district', 'tamil nadu dr mgr medical university', '1990'], ['kapviswanatham government medical college', 'tiruchirappalli tamil nadu', 'tiruchirappalli district', 'tamil nadu dr mgr medical university', '1929'], ['thoothukudi medical college', 'thoothukudi', 'thoothukudi', 'tamil nadu dr mgr medical university', '1982'], ['government vellore medical college', 'bagayam', 'vellore', 'tamil nadu dr mgr medical university', '2005'], ['kanyakumari government medical college', 'kanniyakumari', 'kanniyakumari', 'tamil nadu dr mgr medical university', '1965'], ['government theni medical college', 'theni', 'theni', 'tamil nadu dr mgr medical university', '2006'], ['government dharmapuri medical college', 'coimbatore', 'coimbatore', 'tamil nadu dr mgr medical university', '1982'], ['government villupuram medical college', 'villupuram', 'villupuram', 'tamil nadu dr mgr medical university', '1965'], ['government thiruvarur medical college', 'thiruvarur', 'thiruvarur', 'tamil nadu dr mgr medical university', '2007'], ['government sivgangai medical college', 'sivgangai', 'sivgangai', 'tamil nadu dr mgr medical university', 'proposed']]
|
athletics at the 1986 central american and caribbean games
|
https://en.wikipedia.org/wiki/Athletics_at_the_1986_Central_American_and_Caribbean_Games
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10258265-3.html.csv
|
superlative
|
cuba recorded the highest number of silver medals in athletics at the 1986 central american and caribbean games .
|
{'scope': 'all', 'col_superlative': '4', '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', 'silver'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; silver }'}, 'nation'], 'result': 'cuba', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; silver } ; nation }'}, 'cuba'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; silver } ; nation } ; cuba } = true', 'tointer': 'select the row whose silver record of all rows is maximum . the nation record of this row is cuba .'}
|
eq { hop { argmax { all_rows ; silver } ; nation } ; cuba } = true
|
select the row whose silver record of all rows is maximum . the nation record of this row is cuba .
|
3
|
3
|
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'silver_5': 5, 'nation_6': 6, 'cuba_7': 7}
|
{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'silver_5': 'silver', 'nation_6': 'nation', 'cuba_7': 'cuba'}
|
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'silver_5': [0], 'nation_6': [1], 'cuba_7': [2]}
|
['rank', 'nation', 'gold', 'silver', 'bronze', 'total']
|
[['1', 'cuba', '27', '16', '8', '51'], ['2', 'mexico', '6', '9', '6', '21'], ['3', 'colombia', '3', '1', '7', '11'], ['4', 'bahamas', '2', '4', '3', '9'], ['5', 'puerto rico', '2', '3', '6', '11'], ['6', 'jamaica', '1', '3', '3', '7'], ['7', 'us virgin islands', '1', '0', '1', '2'], ['8', 'guyana', '1', '0', '0', '1'], ['9', 'dominican republic', '0', '4', '2', '6'], ['10', 'trinidad and tobago', '0', '2', '1', '3'], ['10', 'venezuela', '0', '2', '1', '3'], ['12', 'barbados', '0', '0', '2', '2'], ['13', 'haiti', '0', '0', '1', '1'], ['13', 'panama', '0', '0', '1', '1']]
|
1999 - 2000 manchester united f.c. season
|
https://en.wikipedia.org/wiki/1999%E2%80%932000_Manchester_United_F.C._season
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12988799-9.html.csv
|
ordinal
|
the 3rd highest attendance for the 1999-2000 manchester united f.c. season was on december 8 , 1999 .
|
{'row': '2', 'col': '5', 'order': '3', 'col_other': '1', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None}
|
{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'attendance', '3'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; attendance ; 3 }'}, 'date'], 'result': '8 december 1999', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; attendance ; 3 } ; date }'}, '8 december 1999'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; date } ; 8 december 1999 } = true', 'tointer': 'select the row whose attendance record of all rows is 3rd maximum . the date record of this row is 8 december 1999 .'}
|
eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; date } ; 8 december 1999 } = true
|
select the row whose attendance record of all rows is 3rd maximum . the date record of this row is 8 december 1999 .
|
3
|
3
|
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'attendance_5': 5, '3_6': 6, 'date_7': 7, '8 december 1999_8': 8}
|
{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'attendance_5': 'attendance', '3_6': '3', 'date_7': 'date', '8 december 1999_8': '8 december 1999'}
|
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'attendance_5': [0], '3_6': [0], 'date_7': [1], '8 december 1999_8': [2]}
|
['date', 'opponents', 'h / a', 'result f - a', 'attendance', 'group position']
|
[['23 november 1999', 'fiorentina', 'a', '0 - 2', '36002', '3rd'], ['8 december 1999', 'valencia', 'h', '3 - 0', '54606', '2nd'], ['1 march 2000', 'bordeaux', 'h', '2 - 0', '59786', '2nd'], ['7 march 2000', 'bordeaux', 'a', '2 - 1', '30130', '1st'], ['15 march 2000', 'fiorentina', 'h', '3 - 1', '59926', '1st'], ['21 march 2000', 'valencia', 'a', '0 - 0', '40419', '1st']]
|
juan román riquelme
|
https://en.wikipedia.org/wiki/Juan_Rom%C3%A1n_Riquelme
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1230308-1.html.csv
|
majority
|
the majority of soccer match results were wins for juan román riquelme .
|
{'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'win', 'subset': None}
|
{'func': 'most_str_eq', 'args': ['all_rows', 'result', 'win'], 'result': True, 'ind': 0, 'tointer': 'for the result records of all rows , most of them fuzzily match to win .', 'tostr': 'most_eq { all_rows ; result ; win } = true'}
|
most_eq { all_rows ; result ; win } = true
|
for the result records of all rows , most of them fuzzily match to win .
|
1
|
1
|
{'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'result_3': 3, 'win_4': 4}
|
{'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'result_3': 'result', 'win_4': 'win'}
|
{'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'result_3': [0], 'win_4': [0]}
|
['date', 'venue', 'score', 'result', 'competition']
|
[['30 april 2003', 'june 11 stadium , tripoli , libya', '3 - 1', 'win', 'friendly'], ['17 november 2004', 'estadio monumental , buenos aires , argentina', '3 - 2', 'win', '2006 world cup qualification'], ['8 june 2005', 'estadio monumental , buenos aires , argentina', '3 - 1', 'win', '2006 world cup qualification'], ['15 june 2005', 'tetova stadium , cologne , germany', '2 - 1', 'win', '2005 fifa confederations cup'], ['18 june 2005', 'easycredit - stadion , nuremberg , germany', '4 - 2', 'win', '2005 fifa confederations cup'], ['21 june 2005', 'easycredit - stadion , nuremberg , germany', '2 - 2', 'draw', '2005 fifa confederations cup'], ['9 october 2005', 'estadio monumental , buenos aires , argentina', '2 - 0', 'win', '2006 world cup qualification'], ['16 november 2005', 'jassim bin hamad stadium , doha , qatar', '3 - 0', 'win', 'friendly'], ['2 july 2007', 'josé pachencho romero , maracaibo , venezuela', '4 - 2', 'win', '2007 copa américa'], ['8 july 2007', 'estadio metropolitano , barquisimeto , venezuela', '4 - 0', 'win', '2007 copa américa'], ['11 july 2007', 'polideportivo cachamay , puerto ordaz , venezuela', '3 - 0', 'win', '2007 copa américa'], ['13 october 2007', 'estadio monumental , buenos aires , argentina', '2 - 0', 'win', '2010 world cup qualification'], ['17 november 2007', 'estadio monumental , buenos aires , argentina', '3 - 0', 'win', '2010 world cup qualification']]
|
1996 pga championship
|
https://en.wikipedia.org/wiki/1996_PGA_Championship
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18096431-5.html.csv
|
count
|
in the 1996 pga championship , 3 players scored 138 , or 6 under par .
|
{'scope': 'all', 'criterion': 'fuzzily_match', 'value': '138', 'result': '3', 'col': '4', 'subset': None}
|
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'score', '138'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose score record fuzzily matches to 138 .', 'tostr': 'filter_eq { all_rows ; score ; 138 }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; score ; 138 } }', 'tointer': 'select the rows whose score record fuzzily matches to 138 . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; score ; 138 } } ; 3 } = true', 'tointer': 'select the rows whose score record fuzzily matches to 138 . the number of such rows is 3 .'}
|
eq { count { filter_eq { all_rows ; score ; 138 } } ; 3 } = true
|
select the rows whose score record fuzzily matches to 138 . 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, 'score_5': 5, '138_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', 'score_5': 'score', '138_6': '138', '3_7': '3'}
|
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'score_5': [0], '138_6': [0], '3_7': [2]}
|
['place', 'player', 'country', 'score', 'to par']
|
[['1', 'phil mickelson', 'united states', '67 + 67 = 134', '- 10'], ['2', 'justin leonard', 'united states', '71 + 66 = 137', '- 7'], ['t3', 'mark brooks', 'united states', '68 + 70 = 138', '- 6'], ['t3', 'kenny perry', 'united states', '66 + 72 = 138', '- 6'], ['t3', 'vijay singh', 'fiji', '69 + 69 = 138', '- 6'], ['t6', 'lee janzen', 'united states', '68 + 71 = 139', '- 5'], ['t6', 'nick price', 'zimbabwe', '68 + 72 = 139', '- 5'], ['t8', 'mike brisky', 'united states', '71 + 69 = 140', '- 4'], ['t8', 'russ cochran', 'united states', '68 + 72 = 140', '- 4'], ['t8', 'david edwards', 'united states', '69 + 71 = 140', '- 4'], ['t8', 'brad faxon', 'united states', '72 + 68 = 140', '- 4'], ['t8', 'jim furyk', 'united states', '70 + 70 = 140', '- 4'], ['t8', 'greg norman', 'australia', '68 + 72 = 140', '- 4'], ['t8', 'jesper parnevik', 'sweden', '73 + 67 = 140', '- 4'], ['t8', 'tommy tolles', 'united states', '69 + 71 = 140', '- 4'], ['t8', 'tom watson', 'united states', '69 + 71 = 140', '- 4'], ['t8', 'ian woosnam', 'wales', '68 + 72 = 140', '- 4']]
|
list of sumo record holders
|
https://en.wikipedia.org/wiki/List_of_sumo_record_holders
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17634218-20.html.csv
|
majority
|
most of the people that are sumo record holders have participated in 12 tournaments .
|
{'scope': 'all', 'col': '2', 'most_or_all': 'most', 'criterion': 'equal', 'value': '12', 'subset': None}
|
{'func': 'most_eq', 'args': ['all_rows', 'tournaments', '12'], 'result': True, 'ind': 0, 'tointer': 'for the tournaments records of all rows , most of them are equal to 12 .', 'tostr': 'most_eq { all_rows ; tournaments ; 12 } = true'}
|
most_eq { all_rows ; tournaments ; 12 } = true
|
for the tournaments records of all rows , most of them are equal to 12 .
|
1
|
1
|
{'most_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'tournaments_3': 3, '12_4': 4}
|
{'most_eq_0': 'most_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'tournaments_3': 'tournaments', '12_4': '12'}
|
{'most_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'tournaments_3': [0], '12_4': [0]}
|
['name', 'tournaments', 'pro debut', 'top division debut', 'highest rank']
|
[['jōkōryū', '9', 'may 2011', 'november 2012', 'maegashira 7'], ['ōsunaarashi', '10', 'march 2012', 'november 2013', 'maegashira 15'], ['kotoōshū', '11', 'november 2002', 'september 2004', 'ōzeki'], ['aran', '11', 'january 2007', 'november 2008', 'sekiwake'], ['itai', '12', 'september 1978', 'september 1980', 'komusubi'], ['konishiki', '12', 'july 1982', 'july 1984', 'ōzeki'], ['tochiazuma ii', '12', 'november 1994', 'november 1996', 'ōzeki'], ['asashōryū', '12', 'january 1999', 'january 2001', 'yokozuna'], ['tokitenkū', '12', 'july 2002', 'july 2004', 'komusubi'], ['yoshikaze', '12', 'january 2004', 'january 2006', 'maegashira 1'], ['baruto', '12', 'may 2004', 'may 2006', 'ōzeki'], ['sakaizawa', '12', 'march 2006', 'march 2008', 'maegashira 15'], ['yamamotoyama', '12', 'january 2007', 'january 2009', 'maegashira 9']]
|
pavlina nola
|
https://en.wikipedia.org/wiki/Pavlina_Nola
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12878201-8.html.csv
|
unique
|
of the tournaments pavlina nola participated in , when the surface was clay , the only time her partner was anna linkova was on august 7 , 1995 .
|
{'scope': 'subset', 'row': '1', 'col': '5', 'col_other': '2', 'criterion': 'equal', 'value': 'anna linkova', 'subset': {'col': '4', 'criterion': 'equal', 'value': 'clay'}}
|
{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'surface', 'clay'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; surface ; clay }', 'tointer': 'select the rows whose surface record fuzzily matches to clay .'}, 'partner', 'anna linkova'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose surface record fuzzily matches to clay . among these rows , select the rows whose partner record fuzzily matches to anna linkova .', 'tostr': 'filter_eq { filter_eq { all_rows ; surface ; clay } ; partner ; anna linkova }'}], 'result': True, 'ind': 2, 'tostr': 'only { filter_eq { filter_eq { all_rows ; surface ; clay } ; partner ; anna linkova } }', 'tointer': 'select the rows whose surface record fuzzily matches to clay . among these rows , select the rows whose partner record fuzzily matches to anna linkova . 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', 'surface', 'clay'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; surface ; clay }', 'tointer': 'select the rows whose surface record fuzzily matches to clay .'}, 'partner', 'anna linkova'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose surface record fuzzily matches to clay . among these rows , select the rows whose partner record fuzzily matches to anna linkova .', 'tostr': 'filter_eq { filter_eq { all_rows ; surface ; clay } ; partner ; anna linkova }'}, 'date'], 'result': 'august 7 , 1995', 'ind': 3, 'tostr': 'hop { filter_eq { filter_eq { all_rows ; surface ; clay } ; partner ; anna linkova } ; date }'}, 'august 7 , 1995'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { filter_eq { filter_eq { all_rows ; surface ; clay } ; partner ; anna linkova } ; date } ; august 7 , 1995 }', 'tointer': 'the date record of this unqiue row is august 7 , 1995 .'}], 'result': True, 'ind': 5, 'tostr': 'and { only { filter_eq { filter_eq { all_rows ; surface ; clay } ; partner ; anna linkova } } ; eq { hop { filter_eq { filter_eq { all_rows ; surface ; clay } ; partner ; anna linkova } ; date } ; august 7 , 1995 } } = true', 'tointer': 'select the rows whose surface record fuzzily matches to clay . among these rows , select the rows whose partner record fuzzily matches to anna linkova . there is only one such row in the table . the date record of this unqiue row is august 7 , 1995 .'}
|
and { only { filter_eq { filter_eq { all_rows ; surface ; clay } ; partner ; anna linkova } } ; eq { hop { filter_eq { filter_eq { all_rows ; surface ; clay } ; partner ; anna linkova } ; date } ; august 7 , 1995 } } = true
|
select the rows whose surface record fuzzily matches to clay . among these rows , select the rows whose partner record fuzzily matches to anna linkova . there is only one such row in the table . the date record of this unqiue row is august 7 , 1995 .
|
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, 'surface_8': 8, 'clay_9': 9, 'partner_10': 10, 'anna linkova_11': 11, 'str_eq_4': 4, 'str_hop_3': 3, 'date_12': 12, 'august 7 , 1995_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', 'surface_8': 'surface', 'clay_9': 'clay', 'partner_10': 'partner', 'anna linkova_11': 'anna linkova', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'date_12': 'date', 'august 7 , 1995_13': 'august 7 , 1995'}
|
{'and_5': [6], 'result_6': [], 'only_2': [5], 'filter_str_eq_1': [2, 3], 'filter_str_eq_0': [1], 'all_rows_7': [0], 'surface_8': [0], 'clay_9': [0], 'partner_10': [1], 'anna linkova_11': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'date_12': [3], 'august 7 , 1995_13': [4]}
|
['outcome', 'date', 'tournament', 'surface', 'partner', 'opponents in the final', 'score in the final']
|
[['runner - ups', 'august 7 , 1995', 'horb , germany itf 10000', 'clay', 'anna linkova', 'ivana havrliková monika kratochvílová', '2 - 6 , 5 - 7'], ['winners', 'september 3 , 1995', 'bad nauheim , germany itf 10000', 'clay', 'renata kochta', 'dominika górecka petra plačkova', '7 - 6 , 6 - 2'], ['winners', 'september 17 , 1995', 'varna , bulgaria itf 10000', 'clay', 'dora djilianova', 'galina dimitrova dessislava topalova', '4 - 6 , 6 - 4 , 7 - 5'], ['runner - ups', 'october 1 , 1995', 'bucharest , romania itf 25000', 'clay', 'dora djilianova', 'angela kerek maja zivec - skulj', '6 - 2 , 6 - 7 ( 5 - 7 ) , 6 - 3'], ['winners', 'august 25 , 1996', 'bad nauheim , germany itf 10000', 'clay', 'meike froehlich', 'simona galikova patrícia marková', '7 - 6 ( 7 - 4 ) , 7 - 6 ( 12 - 10 )'], ['winners', 'september 15 , 1996', 'varna , bulgaria itf 10000', 'clay', 'antoaneta pandjerova', 'galina dimitrova dessislava topalova', '6 - 4 , 6 - 2'], ['winners', 'june 1 , 1997', 'bourgas , bulgaria itf 10000', 'hard', 'teodora nedeva', 'meike froehlich kristina pojatina', '6 - 1 , 6 - 2'], ['winners', 'july 20 , 1997', 'darmstadt , germany itf 25000', 'clay', 'svetlana krivencheva', 'olga ivanova magdalena feistel', '6 - 0 , 2 - 6 , 6 - 3'], ['winners', 'july 27 , 1997', 'rostock , germany itf 25000', 'clay', 'svetlana krivencheva', 'renée reid réka vidáts', 'w / o'], ['runner - ups', 'august 17 , 1997', 'bratislava , slovakia itf 75000', 'clay', 'svetlana krivencheva', 'laurence courtois henrieta nagyová', '1 - 6 , 0 - 6'], ['winners', 'october 18 , 1998', 'indian wells , ca , usa itf 25000', 'hard', 'lindsay lee - waters', 'erika de lone katie schlukebir', '6 - 0 , 6 - 7 ( 4 - 7 ) , 6 - 1']]
|
dustley mulder
|
https://en.wikipedia.org/wiki/Dustley_Mulder
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11415108-1.html.csv
|
unique
|
the 2005 / 06 season was the only season in which dustley mulder had 24 appearances .
|
{'scope': 'all', 'row': '2', 'col': '3', 'col_other': '1', 'criterion': 'equal', 'value': '24', 'subset': None}
|
{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'apps', '24'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose apps record is equal to 24 .', 'tostr': 'filter_eq { all_rows ; apps ; 24 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; apps ; 24 } }', 'tointer': 'select the rows whose apps record is equal to 24 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'apps', '24'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose apps record is equal to 24 .', 'tostr': 'filter_eq { all_rows ; apps ; 24 }'}, 'season'], 'result': '2005 / 06', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; apps ; 24 } ; season }'}, '2005 / 06'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; apps ; 24 } ; season } ; 2005 / 06 }', 'tointer': 'the season record of this unqiue row is 2005 / 06 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; apps ; 24 } } ; eq { hop { filter_eq { all_rows ; apps ; 24 } ; season } ; 2005 / 06 } } = true', 'tointer': 'select the rows whose apps record is equal to 24 . there is only one such row in the table . the season record of this unqiue row is 2005 / 06 .'}
|
and { only { filter_eq { all_rows ; apps ; 24 } } ; eq { hop { filter_eq { all_rows ; apps ; 24 } ; season } ; 2005 / 06 } } = true
|
select the rows whose apps record is equal to 24 . there is only one such row in the table . the season record of this unqiue row is 2005 / 06 .
|
6
|
5
|
{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'apps_7': 7, '24_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'season_9': 9, '2005 / 06_10': 10}
|
{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'apps_7': 'apps', '24_8': '24', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'season_9': 'season', '2005 / 06_10': '2005 / 06'}
|
{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'apps_7': [0], '24_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'season_9': [2], '2005 / 06_10': [3]}
|
['season', 'club', 'apps', 'goals', 'division']
|
[['2004 / 05', 'excelsior', '22', '3', '2'], ['2005 / 06', 'excelsior', '24', '1', '2'], ['2005 / 06', 'rkc waalwijk', '11', '0', '1'], ['2006 / 07', 'rkc waalwijk', '25', '1', '1'], ['2007 / 08', 'rkc waalwijk', '37', '1', '2'], ['2008 / 09', 'rkc waalwijk', '37', '1', '2'], ['2009 / 10', 'rkc waalwijk', '32', '1', '1']]
|
sandra cecchini
|
https://en.wikipedia.org/wiki/Sandra_Cecchini
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14979843-3.html.csv
|
ordinal
|
the second to last tournament that sandra cecchini participated in was the moscow tournament .
|
{'row': '17', 'col': '2', 'order': '2', 'col_other': '3', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None}
|
{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'date', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; date ; 2 }'}, 'tournament'], 'result': 'moscow', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; date ; 2 } ; tournament }'}, 'moscow'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; date ; 2 } ; tournament } ; moscow } = true', 'tointer': 'select the row whose date record of all rows is 2nd maximum . the tournament record of this row is moscow .'}
|
eq { hop { nth_argmax { all_rows ; date ; 2 } ; tournament } ; moscow } = true
|
select the row whose date record of all rows is 2nd maximum . the tournament record of this row is moscow .
|
3
|
3
|
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'date_5': 5, '2_6': 6, 'tournament_7': 7, 'moscow_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', 'date_5': 'date', '2_6': '2', 'tournament_7': 'tournament', 'moscow_8': 'moscow'}
|
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'date_5': [0], '2_6': [0], 'tournament_7': [1], 'moscow_8': [2]}
|
['outcome', 'date', 'tournament', 'surface', 'opponent', 'score']
|
[['winner', '23 april 1984', 'taranto', 'clay', 'sabrina goleš', '6 - 3 , 7 - 5'], ['winner', '9 july 1984', 'rio de janeiro', 'hard', 'adriana villagran', '6 - 3 , 6 - 3'], ['winner', '6 may 1985', 'barcelona', 'clay', 'raffaella reggi', '6 - 3 , 6 - 4'], ['winner', '14 july 1986', 'bregenz', 'clay', 'mariana pérez - roldán', '6 - 4 , 6 - 0'], ['runner - up', '18 may 1987', 'strasbourg', 'clay', 'carling bassett', '3 - 6 , 4 - 6'], ['winner', '6 july 1987', 'båstad', 'clay', 'catarina lindqvist', '6 - 4 , 6 - 4'], ['winner', '2 november 1987', 'little rock', 'hard', 'natalia zvereva', '6 - 0 , 1 - 6 , 3 - 6'], ['winner', '16 may 1988', 'strasbourg', 'clay', 'judith wiesner', '6 - 3 , 6 - 0'], ['runner - up', '4 july 1988', 'båstad', 'clay', 'isabel cueto', '5 - 7 , 1 - 6'], ['winner', '11 july 1988', 'nice', 'clay', 'nathalie tauziat', '7 - 5 , 6 - 4'], ['runner - up', '17 july 1989', 'estoril', 'clay', 'isabel cueto', '6 - 7 ( 3 - 7 ) , 2 - 6'], ['winner', '18 september 1989', 'paris', 'clay', 'regina rajchrtová', '6 - 4 , 6 - 7 ( 5 - 7 ) , 6 - 1'], ['winner', '9 july 1990', 'båstad', 'clay', 'csilla bartos', '6 - 1 , 6 - 2'], ['winner', '22 april 1991', 'bol', 'clay', 'magdalena maleeva', '6 - 4 , 3 - 6 , 7 - 5'], ['runner - up', '8 july 1991', 'palermo', 'clay', 'mary pierce', '0 - 6 , 3 - 6'], ['winner', '14 september 1992', 'paris', 'clay', 'emanuela zardo', '6 - 2 , 6 - 1'], ['runner - up', '19 september 1994', 'moscow', 'carpet ( i )', 'magdalena maleeva', '5 - 7 , 1 - 6'], ['runner - up', '5 august 1996', 'maria lankowitz', 'clay', 'barbara paulus', 'w / o']]
|
robby gordon
|
https://en.wikipedia.org/wiki/Robby_Gordon
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1507423-4.html.csv
|
majority
|
in most years , robbie gordon did n't have any pole positions .
|
{'scope': 'all', 'col': '6', 'most_or_all': 'most', 'criterion': 'equal', 'value': '0', 'subset': None}
|
{'func': 'most_eq', 'args': ['all_rows', 'poles', '0'], 'result': True, 'ind': 0, 'tointer': 'for the poles records of all rows , most of them are equal to 0 .', 'tostr': 'most_eq { all_rows ; poles ; 0 } = true'}
|
most_eq { all_rows ; poles ; 0 } = true
|
for the poles records of all rows , most of them are equal to 0 .
|
1
|
1
|
{'most_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'poles_3': 3, '0_4': 4}
|
{'most_eq_0': 'most_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'poles_3': 'poles', '0_4': '0'}
|
{'most_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'poles_3': [0], '0_4': [0]}
|
['year', 'starts', 'wins', 'top 5', 'top 10', 'poles', 'avg start', 'avg finish', 'winnings', 'position']
|
[['1991', '2', '0', '0', '0', '0', '35.0', '22.0', '27625', '55th'], ['1993', '1', '0', '0', '0', '0', '14.0', '42.0', '17665', '93rd'], ['1994', '1', '0', '0', '0', '0', '38.0', '38.0', '7965', '76th'], ['1996', '3', '0', '0', '0', '0', '17.3', '40.7', '33915', '57th'], ['1997', '20', '0', '1', '1', '1', '25.3', '29.6', '622439', '40th'], ['1998', '1', '0', '0', '0', '0', '18.0', '37.0', '24765', '67th'], ['2000', '17', '0', '1', '2', '0', '29.9', '29.2', '620781', '43rd'], ['2001', '17', '1', '2', '3', '0', '32.4', '24.8', '1371900', '44th'], ['2002', '36', '0', '1', '5', '0', '18.4', '21.1', '3342703', '20th'], ['2003', '36', '2', '4', '10', '0', '23.1', '19.7', '4157064', '16th'], ['2004', '36', '0', '2', '6', '0', '23.2', '21.2', '4225719', '23rd'], ['2005', '29', '0', '1', '2', '0', '27.0', '30.1', '2271313', '37th'], ['2006', '36', '0', '1', '3', '0', '27.5', '25.3', '3143787', '30th'], ['2007', '35', '0', '1', '2', '0', '33.9', '25.8', '3090004', '26th'], ['2008', '36', '0', '0', '3', '0', '30.9', '29.0', '3816362', '33rd'], ['2009', '35', '0', '1', '1', '0', '30.1', '28.5', '3860582', '34th'], ['2010', '27', '0', '1', '1', '0', '33.8', '29.1', '2913816', '34th'], ['2011', '25', '0', '0', '0', '0', '36.5', '33.4', '2271891', '34th'], ['2012', '3', '0', '0', '0', '0', '30.0', '40.3', '405300', '52nd']]
|
1980 - 81 fa cup
|
https://en.wikipedia.org/wiki/1980%E2%80%9381_FA_Cup
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17751859-6.html.csv
|
count
|
7 games were played in march of 1981 for the fa cup .
|
{'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'march 1981', 'result': '7', 'col': '5', 'subset': None}
|
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', 'march 1981'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose date record fuzzily matches to march 1981 .', 'tostr': 'filter_eq { all_rows ; date ; march 1981 }'}], 'result': '7', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; date ; march 1981 } }', 'tointer': 'select the rows whose date record fuzzily matches to march 1981 . the number of such rows is 7 .'}, '7'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; date ; march 1981 } } ; 7 } = true', 'tointer': 'select the rows whose date record fuzzily matches to march 1981 . the number of such rows is 7 .'}
|
eq { count { filter_eq { all_rows ; date ; march 1981 } } ; 7 } = true
|
select the rows whose date record fuzzily matches to march 1981 . the number of such rows is 7 .
|
3
|
3
|
{'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'date_5': 5, 'march 1981_6': 6, '7_7': 7}
|
{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'date_5': 'date', 'march 1981_6': 'march 1981', '7_7': '7'}
|
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'date_5': [0], 'march 1981_6': [0], '7_7': [2]}
|
['tie no', 'home team', 'score', 'away team', 'date']
|
[['1', 'nottingham forest', '3 - 3', 'ipswich town', '7 march 1981'], ['replay', 'ipswich town', '1 - 0', 'nottingham forest', '10 march 1981'], ['2', 'middlesbrough', '1 - 1', 'wolverhampton wanderers', '7 march 1981'], ['replay', 'wolverhampton wanderers', '3 - 1', 'middlesbrough', '10 march 1981'], ['3', 'everton', '2 - 2', 'manchester city', '7 march 1981'], ['replay', 'manchester city', '3 - 1', 'everton', '11 march 1981'], ['4', 'tottenham hotspur', '2 - 0', 'exeter city', '7 march 1981']]
|
george mason patriots men 's basketball
|
https://en.wikipedia.org/wiki/George_Mason_Patriots_men%27s_basketball
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12661367-1.html.csv
|
majority
|
most of the george mason patriots men 's basketball players who are on the all-time scorer list scored less than 2000 total points .
|
{'scope': 'all', 'col': '6', 'most_or_all': 'most', 'criterion': 'less_than', 'value': '2000', 'subset': None}
|
{'func': 'most_less', 'args': ['all_rows', 'total points', '2000'], 'result': True, 'ind': 0, 'tointer': 'for the total points records of all rows , most of them are less than 2000 .', 'tostr': 'most_less { all_rows ; total points ; 2000 } = true'}
|
most_less { all_rows ; total points ; 2000 } = true
|
for the total points records of all rows , most of them are less than 2000 .
|
1
|
1
|
{'most_less_0': 0, 'result_1': 1, 'all_rows_2': 2, 'total points_3': 3, '2000_4': 4}
|
{'most_less_0': 'most_less', 'result_1': 'true', 'all_rows_2': 'all_rows', 'total points_3': 'total points', '2000_4': '2000'}
|
{'most_less_0': [1], 'result_1': [], 'all_rows_2': [0], 'total points_3': [0], '2000_4': [0]}
|
['rank', 'player', 'years', 'games', 'ppg avg', 'total points']
|
[['1', 'carlos yates', '1981 - 1985', '109', '22.2', '2420'], ['2', 'kenny sanders', '1985 - 1989', '107', '20.3', '2177'], ['3', 'george evans', '1997 - 2001', '116', '16.8', '1953'], ['4', 'robert dykes', '1987 - 1991', '122', '13.4', '1642'], ['5', 'ryan pearson', '2008 - 2012', '129', '12.6', '1626'], ['6', 'andre gaddy', '1977 - 1982', '98', '16.0', '1568'], ['7', 'rob rose', '1982 - 1986', '113', '13.8', '1565'], ['8', 'will thomas', '2004 - 2008', '131', '11.9', '1564'], ['9', 'folarin campbell', '2004 - 2008', '130', '11.9', '1545'], ['10', 'rudolph jones', '1971 - 1973', '59', '25.8', '1525']]
|
united states house of representatives elections , 1986
|
https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1986
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1341586-19.html.csv
|
count
|
moore was the only representative in the house of representatives to retire .
|
{'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'retire', 'result': '1', 'col': '5', 'subset': None}
|
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'result', 'retire'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose result record fuzzily matches to retire .', 'tostr': 'filter_eq { all_rows ; result ; retire }'}], 'result': '1', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; result ; retire } }', 'tointer': 'select the rows whose result record fuzzily matches to retire . the number of such rows is 1 .'}, '1'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; result ; retire } } ; 1 } = true', 'tointer': 'select the rows whose result record fuzzily matches to retire . the number of such rows is 1 .'}
|
eq { count { filter_eq { all_rows ; result ; retire } } ; 1 } = true
|
select the rows whose result record fuzzily matches to retire . 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, 'result_5': 5, 'retire_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', 'result_5': 'result', 'retire_6': 'retire', '1_7': '1'}
|
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'result_5': [0], 'retire_6': [0], '1_7': [2]}
|
['district', 'incumbent', 'party', 'first elected', 'result', 'candidates']
|
[['louisiana 1', 'bob livingston', 'republican', '1977', 're - elected', 'bob livingston ( r ) unopposed'], ['louisiana 2', 'lindy boggs', 'democratic', '1973', 're - elected', 'lindy boggs ( d ) unopposed'], ['louisiana 3', 'billy tauzin', 'democratic', '1980', 're - elected', 'billy tauzin ( d ) unopposed'], ['louisiana 4', 'buddy roemer', 'democratic', '1980', 're - elected', 'buddy roemer ( d ) unopposed'], ['louisiana 5', 'jerry huckaby', 'democratic', '1976', 're - elected', 'jerry huckaby ( d ) unopposed'], ['louisiana 6', 'henson moore', 'republican', '1974', 'retired to run for u s senate republican hold', 'richard baker ( r ) unopposed']]
|
isabel cueto
|
https://en.wikipedia.org/wiki/Isabel_Cueto
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17086086-2.html.csv
|
ordinal
|
the 2nd to last tournament for isabel cueto was when her opponent in the final was katerina maleeva .
|
{'row': '4', 'col': '1', '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', 'date', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; date ; 2 }'}, 'opponent in the final'], 'result': 'katerina maleeva', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; date ; 2 } ; opponent in the final }'}, 'katerina maleeva'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; date ; 2 } ; opponent in the final } ; katerina maleeva } = true', 'tointer': 'select the row whose date record of all rows is 2nd maximum . the opponent in the final record of this row is katerina maleeva .'}
|
eq { hop { nth_argmax { all_rows ; date ; 2 } ; opponent in the final } ; katerina maleeva } = true
|
select the row whose date record of all rows is 2nd maximum . the opponent in the final record of this row is katerina maleeva .
|
3
|
3
|
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'date_5': 5, '2_6': 6, 'opponent in the final_7': 7, 'katerina maleeva_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', 'date_5': 'date', '2_6': '2', 'opponent in the final_7': 'opponent in the final', 'katerina maleeva_8': 'katerina maleeva'}
|
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'date_5': [0], '2_6': [0], 'opponent in the final_7': [1], 'katerina maleeva_8': [2]}
|
['date', 'tournament', 'surface', 'opponent in the final', 'score']
|
[['4 july 1988', 'båstad , sweden', 'clay', 'sandra cecchini', '7 - 5 , 6 - 1'], ['1 august 1988', 'athens , greece', 'clay', 'laura golarsa', '6 - 0 , 6 - 1'], ['17 july 1989', 'estoril , portugal', 'clay', 'sandra cecchini', '7 - 6 ( 3 ) , 6 - 2'], ['31 july 1989', 'sofia , bulgaria', 'clay', 'katerina maleeva', '6 - 2 , 7 - 6 ( 3 )'], ['9 july 1990', 'palermo , italy', 'clay', 'barbara paulus', '6 - 2 , 6 - 3']]
|
three cheers for sweet revenge
|
https://en.wikipedia.org/wiki/Three_Cheers_for_Sweet_Revenge
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1148083-5.html.csv
|
majority
|
for three cheers for sweet revenge , when the region is the united states or japan , the majority of the time the format is cd .
|
{'scope': 'subset', 'col': '4', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'cd', 'subset': {'col': '1', 'criterion': 'equal', 'value': 'united states or japan'}}
|
{'func': 'most_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'region', 'united states or japan'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; region ; united states or japan }', 'tointer': 'select the rows whose region record fuzzily matches to united states or japan .'}, 'format', 'cd'], 'result': True, 'ind': 1, 'tointer': 'select the rows whose region record fuzzily matches to united states or japan . for the format records of these rows , most of them fuzzily match to cd .', 'tostr': 'most_eq { filter_eq { all_rows ; region ; united states or japan } ; format ; cd } = true'}
|
most_eq { filter_eq { all_rows ; region ; united states or japan } ; format ; cd } = true
|
select the rows whose region record fuzzily matches to united states or japan . for the format records of these rows , most of them fuzzily match to cd .
|
2
|
2
|
{'most_str_eq_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, 'region_4': 4, 'united states or japan_5': 5, 'format_6': 6, 'cd_7': 7}
|
{'most_str_eq_1': 'most_str_eq', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'region_4': 'region', 'united states or japan_5': 'united states or japan', 'format_6': 'format', 'cd_7': 'cd'}
|
{'most_str_eq_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'region_4': [0], 'united states or japan_5': [0], 'format_6': [1], 'cd_7': [1]}
|
['region', 'date', 'label', 'format', 'catalogue']
|
[['australia', 'april 11 , 2005', 'reprise', 'cd', '9362486152'], ['japan', 'july 22 , 2004', 'reprise', 'cd', 'wpcr11890'], ['japan', 'january 26 , 2005', 'reprise', 'cd + dvd', 'wpzr30075'], ['japan', 'june 24 , 2009', 'reprise', 'cd', 'wpcr13504'], ['united kingdom', 'september 3 , 2004', 'reprise', 'cd', '9362486152'], ['united states', 'june 8 , 2004', 'reprise', 'cd', '486152'], ['united states', 'december 16 , 2008', 'reprise', '12 vinyl', '148615']]
|
fabienne suter
|
https://en.wikipedia.org/wiki/Fabienne_Suter
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16403980-1.html.csv
|
comparative
|
fabienne suter had a better giant slalom standing in the 2009 season than the 2011 season .
|
{'row_1': '4', 'row_2': '6', 'col': '4', 'col_other': '1', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None}
|
{'func': 'less', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'season', '2009'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose season record fuzzily matches to 2009 .', 'tostr': 'filter_eq { all_rows ; season ; 2009 }'}, 'giant slalom'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; season ; 2009 } ; giant slalom }', 'tointer': 'select the rows whose season record fuzzily matches to 2009 . take the giant slalom record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'season', '2011'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose season record fuzzily matches to 2011 .', 'tostr': 'filter_eq { all_rows ; season ; 2011 }'}, 'giant slalom'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; season ; 2011 } ; giant slalom }', 'tointer': 'select the rows whose season record fuzzily matches to 2011 . take the giant slalom record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; season ; 2009 } ; giant slalom } ; hop { filter_eq { all_rows ; season ; 2011 } ; giant slalom } } = true', 'tointer': 'select the rows whose season record fuzzily matches to 2009 . take the giant slalom record of this row . select the rows whose season record fuzzily matches to 2011 . take the giant slalom record of this row . the first record is less than the second record .'}
|
less { hop { filter_eq { all_rows ; season ; 2009 } ; giant slalom } ; hop { filter_eq { all_rows ; season ; 2011 } ; giant slalom } } = true
|
select the rows whose season record fuzzily matches to 2009 . take the giant slalom record of this row . select the rows whose season record fuzzily matches to 2011 . take the giant slalom 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, 'season_7': 7, '2009_8': 8, 'giant slalom_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'season_11': 11, '2011_12': 12, 'giant slalom_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', 'season_7': 'season', '2009_8': '2009', 'giant slalom_9': 'giant slalom', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'season_11': 'season', '2011_12': '2011', 'giant slalom_13': 'giant slalom'}
|
{'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'season_7': [0], '2009_8': [0], 'giant slalom_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'season_11': [1], '2011_12': [1], 'giant slalom_13': [3]}
|
['season', 'overall', 'slalom', 'giant slalom', 'super g', 'downhill', 'combined']
|
[['2003', '110', '-', '48', '-', '-', '-'], ['2007', '95', '-', '46', '36', '-', '-'], ['2008', '21', '-', '35', '3', '35', '-'], ['2009', '7', '-', '20', '3', '8', '6'], ['2010', '7', '-', '27', '4', '7', '6'], ['2011', '18', '-', '31', '12', '15', '13'], ['2012', '18', '-', '36', '5', '16', '-'], ['2013', '28', '-', '44', '7', '25', '-']]
|
regions of iceland
|
https://en.wikipedia.org/wiki/Regions_of_Iceland
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2252745-1.html.csv
|
superlative
|
suðurland is the largest by area of all the regions of iceland .
|
{'scope': 'all', 'col_superlative': '5', 'row_superlative': '8', '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', 'area ( km square )'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; area ( km square ) }'}, 'name'], 'result': 'suðurland', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; area ( km square ) } ; name }'}, 'suðurland'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; area ( km square ) } ; name } ; suðurland } = true', 'tointer': 'select the row whose area ( km square ) record of all rows is maximum . the name record of this row is suðurland .'}
|
eq { hop { argmax { all_rows ; area ( km square ) } ; name } ; suðurland } = true
|
select the row whose area ( km square ) record of all rows is maximum . the name record of this row is suðurland .
|
3
|
3
|
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'area (km square)_5': 5, 'name_6': 6, 'suðurland_7': 7}
|
{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'area (km square)_5': 'area ( km square )', 'name_6': 'name', 'suðurland_7': 'suðurland'}
|
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'area (km square)_5': [0], 'name_6': [1], 'suðurland_7': [2]}
|
['', 'name', 'name ( english )', 'population 2008 - 07 - 01', 'area ( km square )', 'pop / km square', 'iso 3166 - 2', 'administrative centre']
|
[['1', 'höfuðborgarsvæði', 'capital region', '200969', '1062', '167.61', 'is - 1', 'reykjavík'], ['2', 'suðurnes', 'southern peninsula', '21431', '829', '20.18', 'is - 2', 'keflavík'], ['3', 'vesturland', 'western region', '15601', '9554', '1.51', 'is - 3', 'akranes'], ['4', 'vestfirðir', 'westfjords', '7279', '9409', '0.85', 'is - 4', 'ísafjörður'], ['5', 'norðurland vestra', 'northwestern region', '7392', '12737', '0.73', 'is - 5', 'sauðárkrókur'], ['6', 'norðurland eystra', 'northeastern region', '28925', '21968', '1.21', 'is - 6', 'akureyri'], ['7', 'austurland', 'eastern region', '13786', '22721', '0.52', 'is - 7', 'egilsstaðir'], ['8', 'suðurland', 'southern region', '23972', '24526', '0.87', 'is - 8', 'selfoss']]
|
the secret garden ( musical )
|
https://en.wikipedia.org/wiki/The_Secret_Garden_%28musical%29
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1901751-1.html.csv
|
unique
|
the only character that did n't appear in the west end production of the secret garden was ben weatherstaff .
|
{'scope': 'all', 'row': '8', 'col': '4', 'col_other': '1', 'criterion': 'equal', 'value': 'n / a', 'subset': None}
|
{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'original west end performer', 'n / a'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose original west end performer record fuzzily matches to n / a .', 'tostr': 'filter_eq { all_rows ; original west end performer ; n / a }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; original west end performer ; n / a } }', 'tointer': 'select the rows whose original west end performer record fuzzily matches to n / a . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'original west end performer', 'n / a'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose original west end performer record fuzzily matches to n / a .', 'tostr': 'filter_eq { all_rows ; original west end performer ; n / a }'}, 'character'], 'result': 'ben weatherstaff', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; original west end performer ; n / a } ; character }'}, 'ben weatherstaff'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; original west end performer ; n / a } ; character } ; ben weatherstaff }', 'tointer': 'the character record of this unqiue row is ben weatherstaff .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; original west end performer ; n / a } } ; eq { hop { filter_eq { all_rows ; original west end performer ; n / a } ; character } ; ben weatherstaff } } = true', 'tointer': 'select the rows whose original west end performer record fuzzily matches to n / a . there is only one such row in the table . the character record of this unqiue row is ben weatherstaff .'}
|
and { only { filter_eq { all_rows ; original west end performer ; n / a } } ; eq { hop { filter_eq { all_rows ; original west end performer ; n / a } ; character } ; ben weatherstaff } } = true
|
select the rows whose original west end performer record fuzzily matches to n / a . there is only one such row in the table . the character record of this unqiue row is ben weatherstaff .
|
6
|
5
|
{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'original west end performer_7': 7, 'n / a_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'character_9': 9, 'ben weatherstaff_10': 10}
|
{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'original west end performer_7': 'original west end performer', 'n / a_8': 'n / a', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'character_9': 'character', 'ben weatherstaff_10': 'ben weatherstaff'}
|
{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'original west end performer_7': [0], 'n / a_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'character_9': [2], 'ben weatherstaff_10': [3]}
|
['character', 'original broadway performer', 'original australian performer', 'original west end performer', '2005 world aids day benefit dream cast']
|
[['mary lennox', 'daisy eagan', 'samantha fiddes / sarah ogden', 'natalie morgan', 'jaclyn neidenthal'], ['archibald craven', 'mandy patinkin', 'anthony warlow', 'philip quast', 'steven pasquale'], ['lily craven', 'rebecca luker', 'marina prior', 'meredith braun', 'laura benanti'], ['neville craven', 'robert westenberg', 'philip quast', 'peter polycarpou', 'will chase'], ['martha', 'alison fraser', 'susan - ann walker', 'linzi hateley', 'celia keenan - bolger'], ['dickon', 'john cameron mitchell', 'tom blair', 'jordan dunne', 'michael arden'], ['colin craven', 'john babcock', 'bart ritchie / ross hannaford', 'luke newberry', 'struan erlenborn'], ['ben weatherstaff', 'tom toner', 'raymond duprac', 'n / a', 'david canary']]
|
1930 in brazilian football
|
https://en.wikipedia.org/wiki/1930_in_Brazilian_football
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15371152-1.html.csv
|
majority
|
of the teams who had 40 points of more in 1930 in brazilian football , all of them had a goals difference of more than 40 .
|
{'scope': 'subset', 'col': '8', 'most_or_all': 'all', 'criterion': 'greater_than', 'value': '40', 'subset': {'col': '3', 'criterion': 'greater_than_eq', 'value': '40'}}
|
{'func': 'all_greater', 'args': [{'func': 'filter_greater_eq', 'args': ['all_rows', 'points', '40'], 'result': None, 'ind': 0, 'tostr': 'filter_greater_eq { all_rows ; points ; 40 }', 'tointer': 'select the rows whose points record is greater than or equal to 40 .'}, 'difference', '40'], 'result': True, 'ind': 1, 'tointer': 'select the rows whose points record is greater than or equal to 40 . for the difference records of these rows , all of them are greater than 40 .', 'tostr': 'all_greater { filter_greater_eq { all_rows ; points ; 40 } ; difference ; 40 } = true'}
|
all_greater { filter_greater_eq { all_rows ; points ; 40 } ; difference ; 40 } = true
|
select the rows whose points record is greater than or equal to 40 . for the difference records of these rows , all of them are greater than 40 .
|
2
|
2
|
{'all_greater_1': 1, 'result_2': 2, 'filter_greater_eq_0': 0, 'all_rows_3': 3, 'points_4': 4, '40_5': 5, 'difference_6': 6, '40_7': 7}
|
{'all_greater_1': 'all_greater', 'result_2': 'true', 'filter_greater_eq_0': 'filter_greater_eq', 'all_rows_3': 'all_rows', 'points_4': 'points', '40_5': '40', 'difference_6': 'difference', '40_7': '40'}
|
{'all_greater_1': [2], 'result_2': [], 'filter_greater_eq_0': [1], 'all_rows_3': [0], 'points_4': [0], '40_5': [0], 'difference_6': [1], '40_7': [1]}
|
['position', 'team', 'points', 'played', 'drawn', 'lost', 'against', 'difference']
|
[['1', 'corinthians', '44', '26', '4', '2', '33', '61'], ['2', 'são paulo da floresta', '40', '26', '10', '1', '27', '47'], ['3', 'palestra itália - sp', '40', '26', '6', '3', '27', '58'], ['4', 'santos', '40', '26', '4', '4', '38', '42'], ['5', 'portuguesa', '30', '26', '4', '9', '56', '11'], ['6', 'guarani', '29', '26', '3', '10', '52', '14'], ['7', 'sc internacional de são paulo', '25', '26', '5', '11', '43', '2'], ['8', 'atlético santista', '22', '26', '4', '13', '65', '- 12'], ['9', 'juventus', '21', '26', '1', '15', '61', '- 22'], ['10', 'sírio', '21', '26', '3', '14', '60', '5'], ['11', 'cs américa', '16', '26', '2', '17', '73', '- 40'], ['12', 'ypiranga - sp', '11', '26', '3', '19', '100', '- 71'], ['13', 'germnia', '11', '26', '1', '20', '79', '- 35'], ['14', 'aa são bento', '11', '26', '3', '19', '94', '- 60']]
|
1926 vfl season
|
https://en.wikipedia.org/wiki/1926_VFL_season
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10746808-13.html.csv
|
aggregation
|
the average crowd at the vfl matches on 7th august 1926 was 14464 .
|
{'scope': 'all', 'col': '6', 'type': 'average', 'result': '14464', 'subset': None}
|
{'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'crowd'], 'result': '14464', 'ind': 0, 'tostr': 'avg { all_rows ; crowd }'}, '14464'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; crowd } ; 14464 } = true', 'tointer': 'the average of the crowd record of all rows is 14464 .'}
|
round_eq { avg { all_rows ; crowd } ; 14464 } = true
|
the average of the crowd record of all rows is 14464 .
|
2
|
2
|
{'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'crowd_4': 4, '14464_5': 5}
|
{'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'crowd_4': 'crowd', '14464_5': '14464'}
|
{'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'crowd_4': [0], '14464_5': [1]}
|
['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date']
|
[['hawthorn', '10.10 ( 70 )', 'north melbourne', '10.10 ( 70 )', 'glenferrie oval', '4500', '7 august 1926'], ['geelong', '12.18 ( 90 )', 'st kilda', '5.8 ( 38 )', 'corio oval', '10500', '7 august 1926'], ['fitzroy', '10.17 ( 77 )', 'richmond', '12.20 ( 92 )', 'brunswick street oval', '10000', '7 august 1926'], ['south melbourne', '15.17 ( 107 )', 'footscray', '6.12 ( 48 )', 'lake oval', '14000', '7 august 1926'], ['essendon', '6.10 ( 46 )', 'collingwood', '10.9 ( 69 )', 'windy hill', '20000', '7 august 1926'], ['melbourne', '12.18 ( 90 )', 'carlton', '8.10 ( 58 )', 'mcg', '27785', '7 august 1926']]
|
suwon samsung bluewings
|
https://en.wikipedia.org/wiki/Suwon_Samsung_Bluewings
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1054817-4.html.csv
|
unique
|
1996 was the only year the the shirt printing was bluewings .
|
{'scope': 'all', 'row': '1', 'col': '4', 'col_other': '1', 'criterion': 'equal', 'value': 'bluewings', 'subset': None}
|
{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'shirt printing', 'bluewings'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose shirt printing record fuzzily matches to bluewings .', 'tostr': 'filter_eq { all_rows ; shirt printing ; bluewings }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; shirt printing ; bluewings } }', 'tointer': 'select the rows whose shirt printing record fuzzily matches to bluewings . there is only one such row in the table .'}, {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'shirt printing', 'bluewings'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose shirt printing record fuzzily matches to bluewings .', 'tostr': 'filter_eq { all_rows ; shirt printing ; bluewings }'}, 'year'], 'result': '1996', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; shirt printing ; bluewings } ; year }'}, '1996'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; shirt printing ; bluewings } ; year } ; 1996 }', 'tointer': 'the year record of this unqiue row is 1996 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; shirt printing ; bluewings } } ; eq { hop { filter_eq { all_rows ; shirt printing ; bluewings } ; year } ; 1996 } } = true', 'tointer': 'select the rows whose shirt printing record fuzzily matches to bluewings . there is only one such row in the table . the year record of this unqiue row is 1996 .'}
|
and { only { filter_eq { all_rows ; shirt printing ; bluewings } } ; eq { hop { filter_eq { all_rows ; shirt printing ; bluewings } ; year } ; 1996 } } = true
|
select the rows whose shirt printing record fuzzily matches to bluewings . there is only one such row in the table . the year record of this unqiue row is 1996 .
|
6
|
5
|
{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'shirt printing_7': 7, 'bluewings_8': 8, 'eq_3': 3, 'num_hop_2': 2, 'year_9': 9, '1996_10': 10}
|
{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'shirt printing_7': 'shirt printing', 'bluewings_8': 'bluewings', 'eq_3': 'eq', 'num_hop_2': 'num_hop', 'year_9': 'year', '1996_10': '1996'}
|
{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'shirt printing_7': [0], 'bluewings_8': [0], 'eq_3': [4], 'num_hop_2': [3], 'year_9': [2], '1996_10': [3]}
|
['year', 'kit supplier', 'sponsor', 'shirt printing', 'notes']
|
[['1996', 'rapido', 'samsung electronics', 'bluewings', 'team name'], ['1997', 'rapido', 'samsung electronics', '名品 + 1', 'television brand'], ['1998', 'rapido', 'samsung electronics', '名品 + 1', 'television brand'], ['1999', 'rapido', 'samsung electronics', 'anycall', 'mobile phone brand'], ['2000', 'rapido', 'samsung electronics', 'anycall', 'mobile phone brand'], ['2001', 'rapido', 'samsung electronics', 'sensq bluewin', 'laptop brand air conditioner brand'], ['2002', 'adidas', 'samsung electronics', 'hauzen', 'electronics brand'], ['2003', 'adidas', 'samsung electronics', 'hauzen', 'electronics brand'], ['2004', 'adidas', 'samsung electronics', 'pavv', 'television brand'], ['2005', 'adidas', 'samsung electronics', 'pavv', 'television brand'], ['2006', 'adidas', 'samsung electronics', 'pavv', 'television brand'], ['2007', 'adidas', 'samsung electronics', 'pavv', 'television brand'], ['2008', 'adidas', 'samsung electronics', 'pavv', 'television brand'], ['2009', 'adidas', 'samsung electronics', 'samsung pavv', 'television brand'], ['2010', 'adidas', 'samsung electronics', 'samsung pavv', 'television brand'], ['2011', 'adidas', 'samsung electronics', 'samsung smart tv', 'television brand'], ['2012', 'adidas', 'samsung electronics', 'samsung smart tv', 'television brand'], ['2013', 'adidas', 'samsung electronics', 'samsung smart tv', 'television brand']]
|
1972 vfl season
|
https://en.wikipedia.org/wiki/1972_VFL_season
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10826385-15.html.csv
|
comparative
|
at the 1972 vfl season , fitzroy had a higher score as a home team than collingwood .
|
{'row_1': '2', 'row_2': '6', 'col': '2', 'col_other': '1', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None}
|
{'func': 'greater', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'home team', 'fitzroy'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose home team record fuzzily matches to fitzroy .', 'tostr': 'filter_eq { all_rows ; home team ; fitzroy }'}, 'home team score'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; home team ; fitzroy } ; home team score }', 'tointer': 'select the rows whose home team record fuzzily matches to fitzroy . take the home team score record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'home team', 'collingwood'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose home team record fuzzily matches to collingwood .', 'tostr': 'filter_eq { all_rows ; home team ; collingwood }'}, 'home team score'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; home team ; collingwood } ; home team score }', 'tointer': 'select the rows whose home team record fuzzily matches to collingwood . take the home team score record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; home team ; fitzroy } ; home team score } ; hop { filter_eq { all_rows ; home team ; collingwood } ; home team score } } = true', 'tointer': 'select the rows whose home team record fuzzily matches to fitzroy . take the home team score record of this row . select the rows whose home team record fuzzily matches to collingwood . take the home team score record of this row . the first record is greater than the second record .'}
|
greater { hop { filter_eq { all_rows ; home team ; fitzroy } ; home team score } ; hop { filter_eq { all_rows ; home team ; collingwood } ; home team score } } = true
|
select the rows whose home team record fuzzily matches to fitzroy . take the home team score record of this row . select the rows whose home team record fuzzily matches to collingwood . take the home team score record of this row . the first record is greater than the second record .
|
5
|
5
|
{'greater_4': 4, 'result_5': 5, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'home team_7': 7, 'fitzroy_8': 8, 'home team score_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'home team_11': 11, 'collingwood_12': 12, 'home team score_13': 13}
|
{'greater_4': 'greater', 'result_5': 'true', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'home team_7': 'home team', 'fitzroy_8': 'fitzroy', 'home team score_9': 'home team score', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'home team_11': 'home team', 'collingwood_12': 'collingwood', 'home team score_13': 'home team score'}
|
{'greater_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'home team_7': [0], 'fitzroy_8': [0], 'home team score_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'home team_11': [1], 'collingwood_12': [1], 'home team score_13': [3]}
|
['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date']
|
[['footscray', '14.7 ( 91 )', 'st kilda', '9.11 ( 65 )', 'western oval', '18655', '15 july 1972'], ['fitzroy', '16.14 ( 110 )', 'north melbourne', '9.12 ( 66 )', 'junction oval', '7007', '15 july 1972'], ['essendon', '13.12 ( 90 )', 'richmond', '17.9 ( 111 )', 'windy hill', '22251', '15 july 1972'], ['carlton', '20.8 ( 128 )', 'south melbourne', '8.15 ( 63 )', 'princes park', '14465', '15 july 1972'], ['hawthorn', '19.14 ( 128 )', 'geelong', '15.8 ( 98 )', 'glenferrie oval', '12425', '15 july 1972'], ['collingwood', '10.13 ( 73 )', 'melbourne', '8.10 ( 58 )', 'vfl park', '30883', '15 july 1972']]
|
list of all that episodes
|
https://en.wikipedia.org/wiki/List_of_All_That_episodes
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2655016-11.html.csv
|
superlative
|
the earliest episode of all that to air had production number 1001 .
|
{'scope': 'all', 'col_superlative': '4', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '5', 'subset': None}
|
{'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'argmin', 'args': ['all_rows', 'original air date'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; original air date }'}, 'nick prod'], 'result': '1001', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; original air date } ; nick prod }'}, '1001'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmin { all_rows ; original air date } ; nick prod } ; 1001 } = true', 'tointer': 'select the row whose original air date record of all rows is minimum . the nick prod record of this row is 1001 .'}
|
eq { hop { argmin { all_rows ; original air date } ; nick prod } ; 1001 } = true
|
select the row whose original air date record of all rows is minimum . the nick prod record of this row is 1001 .
|
3
|
3
|
{'eq_2': 2, 'result_3': 3, 'num_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'original air date_5': 5, 'nick prod_6': 6, '1001_7': 7}
|
{'eq_2': 'eq', 'result_3': 'true', 'num_hop_1': 'num_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'original air date_5': 'original air date', 'nick prod_6': 'nick prod', '1001_7': '1001'}
|
{'eq_2': [3], 'result_3': [], 'num_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'original air date_5': [0], 'nick prod_6': [1], '1001_7': [2]}
|
['season', 'series', 'episode title', 'original air date', 'nick prod']
|
[['1', '156', 'mario', 'april 30 , 2005', '1001'], ['2', '157', 'fantasia barrino', 'may 7 , 2005', '1002'], ['3', '158', 'jesse mccartney', 'may 14 , 2005', '1003'], ['4', '159', 'jojo', 'may 28 , 2005', '1009'], ['5', '160', 'tyler hilton', 'june 4 , 2005', '1004'], ['6', '161', 'drake bell', 'june 11 , 2005', '1010'], ['7', '162', 'bow wow', 'unaired', '1011'], ['8', '163', 'avril lavigne', 'june 18 , 2005', '1014'], ['9', '164', 'lil romeo / b2k', 'september 10 , 2005', '1013'], ['10', '165', 'ashlee simpson', 'september 17 , 2005', '1015'], ['11', '166', 'frankie j', 'september 24 , 2005', '1016'], ['12', '167', 'morgan smith', 'october 1 , 2005', '1005'], ['13', '168', 'brooke valentine', 'october 8 , 2005', '1006'], ['14', '169', 'american hi - fi', 'october 15 , 2005', '1007'], ['15', '170', 'brie larson', 'unaired', '1012']]
|
2009 - 10 english premiership ( rugby union )
|
https://en.wikipedia.org/wiki/2009%E2%80%9310_English_Premiership_%28rugby_union%29
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-23909238-2.html.csv
|
unique
|
the northampton saints ( sf ) were the only team with 16 wins that season .
|
{'scope': 'all', 'row': '2', 'col': '4', 'col_other': '2', 'criterion': 'equal', 'value': '16', 'subset': None}
|
{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'won', '16'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose won record is equal to 16 .', 'tostr': 'filter_eq { all_rows ; won ; 16 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; won ; 16 } }', 'tointer': 'select the rows whose won record is equal to 16 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'won', '16'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose won record is equal to 16 .', 'tostr': 'filter_eq { all_rows ; won ; 16 }'}, 'club'], 'result': 'northampton saints ( sf )', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; won ; 16 } ; club }'}, 'northampton saints ( sf )'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; won ; 16 } ; club } ; northampton saints ( sf ) }', 'tointer': 'the club record of this unqiue row is northampton saints ( sf ) .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; won ; 16 } } ; eq { hop { filter_eq { all_rows ; won ; 16 } ; club } ; northampton saints ( sf ) } } = true', 'tointer': 'select the rows whose won record is equal to 16 . there is only one such row in the table . the club record of this unqiue row is northampton saints ( sf ) .'}
|
and { only { filter_eq { all_rows ; won ; 16 } } ; eq { hop { filter_eq { all_rows ; won ; 16 } ; club } ; northampton saints ( sf ) } } = true
|
select the rows whose won record is equal to 16 . there is only one such row in the table . the club record of this unqiue row is northampton saints ( sf ) .
|
6
|
5
|
{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'won_7': 7, '16_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'club_9': 9, 'northampton saints (sf)_10': 10}
|
{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'won_7': 'won', '16_8': '16', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'club_9': 'club', 'northampton saints (sf)_10': 'northampton saints ( sf )'}
|
{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'won_7': [0], '16_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'club_9': [2], 'northampton saints (sf)_10': [3]}
|
['', 'club', 'played', 'won', 'drawn', 'lost', 'points for', 'points against', 'points difference', 'tries for', 'tries against', 'try bonus', 'losing bonus', 'points']
|
[['1', 'leicester tigers ( c )', '22', '15', '1', '6', '541', '325', '216', '46', '18', '7', '4', '73'], ['2', 'northampton saints ( sf )', '22', '16', '0', '6', '472', '322', '150', '44', '26', '2', '5', '71'], ['3', 'saracens ( f )', '22', '15', '1', '6', '480', '367', '113', '39', '22', '2', '5', '69'], ['4', 'bath ( sf )', '22', '12', '2', '8', '450', '366', '84', '49', '33', '5', '4', '61'], ['5', 'london wasps', '22', '13', '0', '9', '394', '399', '5', '35', '31', '2', '3', '57'], ['6', 'london irish', '22', '10', '3', '9', '469', '384', '85', '42', '33', '3', '3', '52'], ['7', 'gloucester', '22', '10', '1', '11', '470', '457', '13', '46', '42', '2', '4', '48'], ['8', 'harlequins', '22', '9', '2', '11', '420', '484', '64', '42', '46', '3', '3', '46'], ['9', 'newcastle falcons', '22', '6', '4', '12', '319', '431', '112', '20', '41', '1', '4', '37'], ['10', 'leeds carnegie', '22', '7', '1', '14', '283', '493', '210', '17', '48', '0', '6', '36'], ['11', 'sale sharks', '22', '6', '1', '15', '333', '495', '162', '24', '51', '0', '6', '32']]
|
georgia collegiate athletic association
|
https://en.wikipedia.org/wiki/Georgia_Collegiate_Athletic_Association
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-16734640-1.html.csv
|
count
|
there are two institutions that are located in albany georgia .
|
{'scope': 'all', 'criterion': 'equal', 'value': 'albany', 'result': '2', 'col': '2', 'subset': None}
|
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location', 'albany'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose location record fuzzily matches to albany .', 'tostr': 'filter_eq { all_rows ; location ; albany }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; location ; albany } }', 'tointer': 'select the rows whose location record fuzzily matches to albany . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; location ; albany } } ; 2 } = true', 'tointer': 'select the rows whose location record fuzzily matches to albany . the number of such rows is 2 .'}
|
eq { count { filter_eq { all_rows ; location ; albany } } ; 2 } = true
|
select the rows whose location record fuzzily matches to albany . 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, 'location_5': 5, 'albany_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', 'location_5': 'location', 'albany_6': 'albany', '2_7': '2'}
|
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'location_5': [0], 'albany_6': [0], '2_7': [2]}
|
['institution', 'location', 'nickname', 'founded', 'enrollment', 'joined']
|
[['abraham baldwin agricultural college', 'tifton', 'stallions', '1908', '3284', '2010'], ['albany technical college', 'albany', 'titans', '1961', '4000', '2010'], ['andrew college', 'cuthbert', 'fighting tigers', '1854', '350', '2010'], ['atlanta metropolitan state college', 'atlanta', 'trailblazers', '1965', '2001', '2010'], ['central georgia technical college', 'macon', 'titans', '1962', '3896', '2010'], ['chattahoochee technical college', 'marietta', 'eagles', '2003', '6264', '2010'], ['darton state college', 'albany', 'cavaliers', '1963', '6000', '2010'], ['east georgia state college', 'swainsboro', 'bobcats', '1973', '2384', '2010'], ['georgia highlands college', 'rome', 'chargers', '1970', '5529', '2011'], ['georgia military college', 'milledgeville', 'bulldogs', '1879', '1200', '2010'], ['georgia northwestern technical college', 'rome', 'bobcats', '1962', '6000', '2010'], ['georgia perimeter college', 'decatur', 'jaguars', '1964', '24000', '2010'], ['gordon state college', 'barnesville', 'highlanders', '1872', '4555', '2010'], ['middle georgia state college', 'cochran', 'knights', '1884', '2960', '2010'], ['north georgia technical college', 'clarkesville', 'wolves', '1944', '500', '2011'], ['oxford college of emory university', 'oxford', 'eagles', '1836', '753', '2010'], ['south georgia state college', 'douglas', 'hawks', '1906', '1959', '2010'], ['south georgia technical college', 'americus', 'jets', '1948', '1972', '2010'], ['southern crescent technical college', 'griffin', 'tigers', '1961', '501', '2010']]
|
hisar ( lok sabha constituency )
|
https://en.wikipedia.org/wiki/Hisar_%28Lok_Sabha_constituency%29
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17922483-1.html.csv
|
aggregation
|
the constituencies that make up the greater hisar constituency have an average of 132744 electorates .
|
{'scope': 'subset', 'col': '5', 'type': 'average', 'result': '132744', 'subset': {'col': '4', 'criterion': 'equal', 'value': 'hisar'}}
|
{'func': 'round_eq', 'args': [{'func': 'avg', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'district', 'hisar'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; district ; hisar }', 'tointer': 'select the rows whose district record fuzzily matches to hisar .'}, 'number of electorates ( 2009 )'], 'result': '132744', 'ind': 1, 'tostr': 'avg { filter_eq { all_rows ; district ; hisar } ; number of electorates ( 2009 ) }'}, '132744'], 'result': True, 'ind': 2, 'tostr': 'round_eq { avg { filter_eq { all_rows ; district ; hisar } ; number of electorates ( 2009 ) } ; 132744 } = true', 'tointer': 'select the rows whose district record fuzzily matches to hisar . the average of the number of electorates ( 2009 ) record of these rows is 132744 .'}
|
round_eq { avg { filter_eq { all_rows ; district ; hisar } ; number of electorates ( 2009 ) } ; 132744 } = true
|
select the rows whose district record fuzzily matches to hisar . the average of the number of electorates ( 2009 ) record of these rows is 132744 .
|
3
|
3
|
{'eq_2': 2, 'result_3': 3, 'avg_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'district_5': 5, 'hisar_6': 6, 'number of electorates (2009)_7': 7, '132744_8': 8}
|
{'eq_2': 'eq', 'result_3': 'true', 'avg_1': 'avg', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'district_5': 'district', 'hisar_6': 'hisar', 'number of electorates (2009)_7': 'number of electorates ( 2009 )', '132744_8': '132744'}
|
{'eq_2': [3], 'result_3': [], 'avg_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'district_5': [0], 'hisar_6': [0], 'number of electorates (2009)_7': [1], '132744_8': [2]}
|
['constituency number', 'name', 'reserved for ( sc / st / none )', 'district', 'number of electorates ( 2009 )']
|
[['37', 'uchana kalan', 'none', 'jind', '154284'], ['47', 'adampur', 'none', 'hisar', '123558'], ['48', 'uklana', 'sc', 'hisar', '147491'], ['49', 'narnaund', 'none', 'hisar', '152958'], ['50', 'hansi', 'none', 'hisar', '133581'], ['51', 'barwala', 'none', 'hisar', '119790'], ['52', 'hisar', 'none', 'hisar', '101595'], ['53', 'nalwa', 'none', 'hisar', '115472'], ['59', 'bawani khera', 'sc', 'bhiwani', '145965'], ['total :', 'total :', 'total :', 'total :', '1194694']]
|
1975 cleveland browns season
|
https://en.wikipedia.org/wiki/1975_Cleveland_Browns_season
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10651104-2.html.csv
|
ordinal
|
the cleveland browns ' game against the philadelphia eagles recorded their 2nd highest attendance of the 1975 season .
|
{'row': '2', 'col': '5', 'order': '2', 'col_other': '3', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None}
|
{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'attendance', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; attendance ; 2 }'}, 'opponent'], 'result': 'philadelphia eagles', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; attendance ; 2 } ; opponent }'}, 'philadelphia eagles'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; attendance ; 2 } ; opponent } ; philadelphia eagles } = true', 'tointer': 'select the row whose attendance record of all rows is 2nd maximum . the opponent record of this row is philadelphia eagles .'}
|
eq { hop { nth_argmax { all_rows ; attendance ; 2 } ; opponent } ; philadelphia eagles } = true
|
select the row whose attendance record of all rows is 2nd maximum . the opponent record of this row is philadelphia eagles .
|
3
|
3
|
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'attendance_5': 5, '2_6': 6, 'opponent_7': 7, 'philadelphia eagles_8': 8}
|
{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'attendance_5': 'attendance', '2_6': '2', 'opponent_7': 'opponent', 'philadelphia eagles_8': 'philadelphia eagles'}
|
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'attendance_5': [0], '2_6': [0], 'opponent_7': [1], 'philadelphia eagles_8': [2]}
|
['week', 'date', 'opponent', 'result', 'attendance']
|
[['1', 'august 10 , 1975', 'san francisco 49ers', 'l 17 - 13', '45560'], ['2', 'august 16 , 1975', 'philadelphia eagles', 'w 14 - 6', '35769'], ['3', 'august 22 , 1975', 'washington redskins', 'l 23 - 14', '15513'], ['4', 'september 1 , 1975', 'buffalo bills', 'l 34 - 20', '31155'], ['5', 'september 7 , 1975', 'new york giants at seattle', 'w 24 - 20', '20000'], ['6', 'september 13 , 1975', 'detroit lions', 'l 27 - 24', '32341']]
|
1926 european aquatics championships
|
https://en.wikipedia.org/wiki/1926_European_Aquatics_Championships
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10636637-1.html.csv
|
count
|
two nations received 3 silver medals during the 1926 european aquatics championships .
|
{'scope': 'all', 'criterion': 'equal', 'value': '3', 'result': '2', 'col': '4', 'subset': None}
|
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'silver', '3'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose silver record is equal to 3 .', 'tostr': 'filter_eq { all_rows ; silver ; 3 }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; silver ; 3 } }', 'tointer': 'select the rows whose silver record is equal to 3 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; silver ; 3 } } ; 2 } = true', 'tointer': 'select the rows whose silver record is equal to 3 . the number of such rows is 2 .'}
|
eq { count { filter_eq { all_rows ; silver ; 3 } } ; 2 } = true
|
select the rows whose silver record is equal to 3 . the number of such rows is 2 .
|
3
|
3
|
{'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_eq_0': 0, 'all_rows_4': 4, 'silver_5': 5, '3_6': 6, '2_7': 7}
|
{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'silver_5': 'silver', '3_6': '3', '2_7': '2'}
|
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'silver_5': [0], '3_6': [0], '2_7': [2]}
|
['rank', 'nation', 'gold', 'silver', 'bronze', 'total']
|
[['1', 'germany', '5', '3', '4', '12'], ['2', 'sweden', '2', '3', '3', '9'], ['3', 'hungary', '2', '2', '0', '4'], ['4', 'belgium', '0', '1', '0', '1'], ['5', 'czechoslovakia', '0', '0', '1', '1'], ['5', 'great britain', '0', '0', '1', '1'], ['total', 'total', '9', '9', '9', '27']]
|
list of grand slam related tennis records
|
https://en.wikipedia.org/wiki/List_of_Grand_Slam_related_tennis_records
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-23408094-14.html.csv
|
unique
|
the only person to have started their lead at the australian championships was roy emerson .
|
{'scope': 'all', 'row': '8', 'col': '6', 'col_other': '3', 'criterion': 'equal', 'value': 'australian championships', 'subset': None}
|
{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'tournament at which lead began', 'australian championships'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose tournament at which lead began record fuzzily matches to australian championships .', 'tostr': 'filter_eq { all_rows ; tournament at which lead began ; australian championships }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; tournament at which lead began ; australian championships } }', 'tointer': 'select the rows whose tournament at which lead began record fuzzily matches to australian championships . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'tournament at which lead began', 'australian championships'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose tournament at which lead began record fuzzily matches to australian championships .', 'tostr': 'filter_eq { all_rows ; tournament at which lead began ; australian championships }'}, 'player'], 'result': 'roy emerson', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; tournament at which lead began ; australian championships } ; player }'}, 'roy emerson'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; tournament at which lead began ; australian championships } ; player } ; roy emerson }', 'tointer': 'the player record of this unqiue row is roy emerson .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; tournament at which lead began ; australian championships } } ; eq { hop { filter_eq { all_rows ; tournament at which lead began ; australian championships } ; player } ; roy emerson } } = true', 'tointer': 'select the rows whose tournament at which lead began record fuzzily matches to australian championships . there is only one such row in the table . the player record of this unqiue row is roy emerson .'}
|
and { only { filter_eq { all_rows ; tournament at which lead began ; australian championships } } ; eq { hop { filter_eq { all_rows ; tournament at which lead began ; australian championships } ; player } ; roy emerson } } = true
|
select the rows whose tournament at which lead began record fuzzily matches to australian championships . there is only one such row in the table . the player record of this unqiue row is roy emerson .
|
6
|
5
|
{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'tournament at which lead began_7': 7, 'australian championships_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'player_9': 9, 'roy emerson_10': 10}
|
{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'tournament at which lead began_7': 'tournament at which lead began', 'australian championships_8': 'australian championships', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'player_9': 'player', 'roy emerson_10': 'roy emerson'}
|
{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'tournament at which lead began_7': [0], 'australian championships_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'player_9': [2], 'roy emerson_10': [3]}
|
['years led', 'span of years led', 'player', 'titles won at point of lead', 'total career titles', 'tournament at which lead began']
|
[['1877 - 1880', '4', 'spencer gore', '1', '1', 'wimbledon'], ['1880 - 1883', '4', 'john hartley', '2', '2', 'wimbledon'], ['1883 - 1887', '5', 'william renshaw', '3', '7', 'wimbledon'], ['1887 - 1925', '39', 'richard sears', '7', '7', 'us championships'], ['1889 - 1925', '37', 'william renshaw', '7', '7', 'wimbledon'], ['1911 - 1925', '15', 'william larned', '7', '7', 'us championships'], ['1925 - 1967', '43', 'bill tilden', '8', '10', 'us championships'], ['1967 - 2000', '34', 'roy emerson', '11', '12', 'australian championships'], ['2000 - 2009', '10', 'pete sampras', '13', '14', 'wimbledon']]
|
2008 masters tournament
|
https://en.wikipedia.org/wiki/2008_Masters_Tournament
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12531523-5.html.csv
|
majority
|
most of the participants in the 2008 masters tournament from the us scored less than -8 to par .
|
{'scope': 'subset', 'col': '5', 'most_or_all': 'most', 'criterion': 'greater_than', 'value': '-8', 'subset': {'col': '3', 'criterion': 'equal', 'value': 'united states'}}
|
{'func': 'most_greater', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'united states'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; country ; united states }', 'tointer': 'select the rows whose country record fuzzily matches to united states .'}, 'to par', '-8'], 'result': True, 'ind': 1, 'tointer': 'select the rows whose country record fuzzily matches to united states . for the to par records of these rows , most of them are greater than -8 .', 'tostr': 'most_greater { filter_eq { all_rows ; country ; united states } ; to par ; -8 } = true'}
|
most_greater { filter_eq { all_rows ; country ; united states } ; to par ; -8 } = true
|
select the rows whose country record fuzzily matches to united states . for the to par records of these rows , most of them are greater than -8 .
|
2
|
2
|
{'most_greater_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, 'country_4': 4, 'united states_5': 5, 'to par_6': 6, '-8_7': 7}
|
{'most_greater_1': 'most_greater', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'country_4': 'country', 'united states_5': 'united states', 'to par_6': 'to par', '-8_7': '-8'}
|
{'most_greater_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'country_4': [0], 'united states_5': [0], 'to par_6': [1], '-8_7': [1]}
|
['place', 'player', 'country', 'score', 'to par']
|
[['1', 'trevor immelman', 'south africa', '68 + 68 + 69 = 205', '- 11'], ['2', 'brandt snedeker', 'united states', '69 + 68 + 70 = 207', '- 9'], ['3', 'steve flesch', 'united states', '72 + 67 + 69 = 208', '- 8'], ['4', 'paul casey', 'england', '71 + 69 + 69 = 209', '- 7'], ['5', 'tiger woods', 'united states', '72 + 71 + 68 = 211', '- 5'], ['6', 'stewart cink', 'united states', '72 + 69 + 71 = 212', '- 4'], ['t7', 'retief goosen', 'south africa', '71 + 71 + 72 = 214', '- 2'], ['t7', 'pádraig harrington', 'ireland', '74 + 71 + 69 = 214', '- 2'], ['t7', 'zach johnson', 'united states', '70 + 76 + 68 = 214', '- 2'], ['t7', 'robert karlsson', 'sweden', '70 + 73 + 71 = 214', '- 2'], ['t7', 'phil mickelson', 'united states', '71 + 68 + 75 = 214', '- 2'], ['t7', "sean o'hair", 'united states', '72 + 71 + 71 = 214', '- 2'], ['t7', 'ian poulter', 'england', '70 + 69 + 75 = 214', '- 2'], ['t7', 'andrés romero', 'argentina', '72 + 72 + 70 = 214', '- 2'], ['t7', 'boo weekley', 'united states', '72 + 74 + 68 = 214', '- 2']]
|
primera división de fútbol profesional apertura 2008
|
https://en.wikipedia.org/wiki/Primera_Divisi%C3%B3n_de_F%C3%BAtbol_Profesional_Apertura_2008
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18522916-4.html.csv
|
count
|
a total of three matches in the primera división de fútbol profesional apertura 2008 took place in the afternoon .
|
{'scope': 'all', 'criterion': 'equal', 'value': 'afternoon', 'result': '3', 'col': '9', 'subset': None}
|
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'time of day', 'afternoon'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose time of day record fuzzily matches to afternoon .', 'tostr': 'filter_eq { all_rows ; time of day ; afternoon }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; time of day ; afternoon } }', 'tointer': 'select the rows whose time of day record fuzzily matches to afternoon . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; time of day ; afternoon } } ; 3 } = true', 'tointer': 'select the rows whose time of day record fuzzily matches to afternoon . the number of such rows is 3 .'}
|
eq { count { filter_eq { all_rows ; time of day ; afternoon } } ; 3 } = true
|
select the rows whose time of day record fuzzily matches to afternoon . 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, 'time of day_5': 5, 'afternoon_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', 'time of day_5': 'time of day', 'afternoon_6': 'afternoon', '3_7': '3'}
|
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'time of day_5': [0], 'afternoon_6': [0], '3_7': [2]}
|
['attendance', 'round', 'date', 'home', 'score', 'away', 'venue', 'weekday', 'time of day']
|
[['14403', 'final', '21 december 2008', 'chalatenango', '3 - 3', 'metapán', 'estadio cuscatlán', 'sunday', 'afternoon'], ['11463', 'semifinal - 2nd leg', '13 december 2008', 'fas', '1 - 3', 'metapán', 'estadio oscar quiteño', 'saturday', 'night'], ['7690', 'round 2', '6 august 2008', 'águila', '3 - 1', 'fas', 'estadio juan francisco barraza', 'wednesday', 'night'], ['6997', 'round 16', '12 november 2008', 'fas', '1 - 0', 'águila', 'estadio oscar quiteño', 'wednesday', 'night'], ['6156', 'round 8', '20 september 2008', 'águila', '1 - 0', 'alianza', 'estadio juan francisco barraza', 'saturday', 'twilight'], ['5815', 'round 15', '15 november 2008', 'fas', '1 - 1', 'metapán', 'estadio oscar quiteño', 'saturday', 'night'], ['5307', 'round 2', '6 august 2008', 'alianza', '3 - 1', 'independiente', 'estadio cuscatlán', 'wednesday', 'afternoon'], ['5122', 'semifinal - 2nd leg', '13 december 2008', 'águila', '1 - 0', 'chalatenango', 'estadio juan francisco barraza', 'saturday', 'night'], ['4800', 'semifinal - 1st leg', '7 december 2008', 'chalatenango', '3 - 0', 'águila', 'estadio josé gregorio martínez', 'sunday', 'afternoon'], ['4722', 'round 13', '5 november 2008', 'águila', '3 - 2', 'firpo', 'estadio juan francisco barraza', 'wednesday', 'night'], ['4510', 'round 3', '9 august 2008', 'firpo', '1 - 2', 'alianza', 'estadio sergio torres', 'saturday', 'night']]
|
fiba europe under - 16 championship
|
https://en.wikipedia.org/wiki/FIBA_Europe_Under-16_Championship
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17837875-2.html.csv
|
superlative
|
the rank 2 team in the fiba europe under - 16 championship won the highest amount of silver medals .
|
{'scope': 'all', 'col_superlative': '3', 'row_superlative': '2', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None}
|
{'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'silver'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; silver }'}, 'rank'], 'result': '2', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; silver } ; rank }'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; silver } ; rank } ; 2 } = true', 'tointer': 'select the row whose silver record of all rows is maximum . the rank record of this row is 2 .'}
|
eq { hop { argmax { all_rows ; silver } ; rank } ; 2 } = true
|
select the row whose silver record of all rows is maximum . the rank record of this row is 2 .
|
3
|
3
|
{'eq_2': 2, 'result_3': 3, 'num_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'silver_5': 5, 'rank_6': 6, '2_7': 7}
|
{'eq_2': 'eq', 'result_3': 'true', 'num_hop_1': 'num_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'silver_5': 'silver', 'rank_6': 'rank', '2_7': '2'}
|
{'eq_2': [3], 'result_3': [], 'num_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'silver_5': [0], 'rank_6': [1], '2_7': [2]}
|
['rank', 'gold', 'silver', 'bronze', 'total']
|
[['1', '5', '3', '3', '11'], ['2', '3', '6', '5', '14'], ['3', '3', '4', '5', '12'], ['4', '3', '1', '4', '8'], ['5', '3', '0', '0', '3'], ['6', '2', '3', '2', '7'], ['7', '1', '4', '2', '7'], ['8', '1', '2', '1', '4'], ['9', '1', '2', '0', '3'], ['10', '0', '2', '1', '3'], ['11', '0', '0', '2', '2'], ['12', '0', '0', '1', '1']]
|
novovoronezh nuclear power plant
|
https://en.wikipedia.org/wiki/Novovoronezh_Nuclear_Power_Plant
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12805568-1.html.csv
|
majority
|
most of the units of the novovoronezh nuclear power plant can produce over 300mw of gross capacity .
|
{'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'greater_than', 'value': '300 mw', 'subset': None}
|
{'func': 'most_greater', 'args': ['all_rows', 'net capacity', '300 mw'], 'result': True, 'ind': 0, 'tointer': 'for the net capacity records of all rows , most of them are greater than 300 mw .', 'tostr': 'most_greater { all_rows ; net capacity ; 300 mw } = true'}
|
most_greater { all_rows ; net capacity ; 300 mw } = true
|
for the net capacity records of all rows , most of them are greater than 300 mw .
|
1
|
1
|
{'most_greater_0': 0, 'result_1': 1, 'all_rows_2': 2, 'net capacity_3': 3, '300 mw_4': 4}
|
{'most_greater_0': 'most_greater', 'result_1': 'true', 'all_rows_2': 'all_rows', 'net capacity_3': 'net capacity', '300 mw_4': '300 mw'}
|
{'most_greater_0': [1], 'result_1': [], 'all_rows_2': [0], 'net capacity_3': [0], '300 mw_4': [0]}
|
['unit', 'reactortype', 'net capacity', 'gross capacity', 'construction started', 'electricity grid', 'commercial operation', 'shutdown']
|
[['novovoronezh - 1', 'vver - 210 ( prototype )', '197 mw', '210 mw', '01.07.1957', '30.09.1964', '31.12.1964', '16.02.1988'], ['novovoronezh - 2', 'vver - 365 ( prototype )', '336 mw', '365 mw', '01.06.1964', '27.12.1969', '14.04.1970', '29.08.1990'], ['novovoronezh - 3', 'vver - 440 / 179', '385 mw', '417 mw', '01.07.1967', '27.12.1971', '29.06.1972', '2016 planned'], ['novovoronezh - 4', 'vver - 440 / 179', '385 mw', '417 mw', '01.07.1967', '28.12.1972', '24.03.1973', '2017 planned'], ['novovoronezh - 5', 'vver - 1000 / 187 ( prototype )', '950 mw', '1000 mw', '01.03.1974', '31.05.1980', '20.02.1981', '2035 planned']]
|
parks and recreation ( season 3 )
|
https://en.wikipedia.org/wiki/Parks_and_Recreation_%28season_3%29
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-29897962-1.html.csv
|
superlative
|
the highest rated episode of the 3rd season of parks and recreation had 6.14 million viewer .
|
{'scope': 'all', 'col_superlative': '7', 'row_superlative': '1', 'value_mentioned': 'yes', 'max_or_min': 'max', 'other_col': '2', 'subset': None}
|
{'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'max', 'args': ['all_rows', 'us viewers ( million )'], 'result': '6.14', 'ind': 0, 'tostr': 'max { all_rows ; us viewers ( million ) }', 'tointer': 'the maximum us viewers ( million ) record of all rows is 6.14 .'}, '6.14'], 'result': True, 'ind': 1, 'tostr': 'eq { max { all_rows ; us viewers ( million ) } ; 6.14 }', 'tointer': 'the maximum us viewers ( million ) record of all rows is 6.14 .'}, {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'us viewers ( million )'], 'result': None, 'ind': 2, 'tostr': 'argmax { all_rows ; us viewers ( million ) }'}, 'no in season'], 'result': '1', 'ind': 3, 'tostr': 'hop { argmax { all_rows ; us viewers ( million ) } ; no in season }'}, '1'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { argmax { all_rows ; us viewers ( million ) } ; no in season } ; 1 }', 'tointer': 'the no in season record of the row with superlative us viewers ( million ) record is 1 .'}], 'result': True, 'ind': 5, 'tostr': 'and { eq { max { all_rows ; us viewers ( million ) } ; 6.14 } ; eq { hop { argmax { all_rows ; us viewers ( million ) } ; no in season } ; 1 } } = true', 'tointer': 'the maximum us viewers ( million ) record of all rows is 6.14 . the no in season record of the row with superlative us viewers ( million ) record is 1 .'}
|
and { eq { max { all_rows ; us viewers ( million ) } ; 6.14 } ; eq { hop { argmax { all_rows ; us viewers ( million ) } ; no in season } ; 1 } } = true
|
the maximum us viewers ( million ) record of all rows is 6.14 . the no in season record of the row with superlative us viewers ( million ) record is 1 .
|
6
|
6
|
{'and_5': 5, 'result_6': 6, 'eq_1': 1, 'max_0': 0, 'all_rows_7': 7, 'us viewers (million)_8': 8, '6.14_9': 9, 'eq_4': 4, 'num_hop_3': 3, 'argmax_2': 2, 'all_rows_10': 10, 'us viewers (million)_11': 11, 'no in season_12': 12, '1_13': 13}
|
{'and_5': 'and', 'result_6': 'true', 'eq_1': 'eq', 'max_0': 'max', 'all_rows_7': 'all_rows', 'us viewers (million)_8': 'us viewers ( million )', '6.14_9': '6.14', 'eq_4': 'eq', 'num_hop_3': 'num_hop', 'argmax_2': 'argmax', 'all_rows_10': 'all_rows', 'us viewers (million)_11': 'us viewers ( million )', 'no in season_12': 'no in season', '1_13': '1'}
|
{'and_5': [6], 'result_6': [], 'eq_1': [5], 'max_0': [1], 'all_rows_7': [0], 'us viewers (million)_8': [0], '6.14_9': [1], 'eq_4': [5], 'num_hop_3': [4], 'argmax_2': [3], 'all_rows_10': [2], 'us viewers (million)_11': [2], 'no in season_12': [3], '1_13': [4]}
|
['no in series', 'no in season', 'title', 'directed by', 'written by', 'original air date', 'us viewers ( million )']
|
[['31', '1', 'go big or go home', 'dean holland', 'alan yang', 'january 20 , 2011', '6.14'], ['32', '2', 'flu season', 'wendey stanzler', 'norm hiscock', 'january 27 , 2011', '5.83'], ['33', '3', 'time capsule', 'michael schur', 'michael schur', 'february 3 , 2011', '4.95'], ['34', '4', 'ron & tammy : part two', 'tucker gates', 'emily kapnek', 'february 10 , 2011', '5.03'], ['35', '5', 'media blitz', 'david rogers', 'harris wittels', 'february 17 , 2011', '4.33'], ['36', '6', 'indianapolis', 'randall einhorn', 'katie dippold', 'february 24 , 2011', '4.59'], ['37', '7', 'harvest festival', 'dean holland', 'dan goor', 'march 17 , 2011', '4.08'], ['38', '8', 'camping', 'rob schrab', 'aisha muharrar', 'march 24 , 2011', '5.15'], ['39', '9', "andy and april 's fancy party", 'michael trim', 'katie dippold', 'april 14 , 2011', '5.16'], ['40', '10', 'soulmates', 'ken whittingham', 'alan yang', 'april 21 , 2011', '4.88'], ['41', '11', "jerry 's painting", 'dean holland', 'norm hiscock', 'april 28 , 2011', '4.71'], ['42', '12', 'eagleton', 'nicole holofcener', 'emily spivey', 'may 5 , 2011', '5.06'], ['43', '13', 'the fight', 'randall einhorn', 'amy poehler', 'may 12 , 2011', '4.55'], ['44', '14', 'road trip', 'troy miller', 'harris wittels', 'may 12 , 2011', '3.55'], ['45', '15', 'the bubble', 'matt sohn', 'greg levine & brian rowe', 'may 19 , 2011', '4.27']]
|
1997 in british music
|
https://en.wikipedia.org/wiki/1997_in_British_music
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1819662-4.html.csv
|
aggregation
|
the 1997 british music bestselling albums had an average of 1236000 in sales .
|
{'scope': 'all', 'col': '4', 'type': 'average', 'result': '1236000', 'subset': None}
|
{'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'sales'], 'result': '1236000', 'ind': 0, 'tostr': 'avg { all_rows ; sales }'}, '1236000'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; sales } ; 1236000 } = true', 'tointer': 'the average of the sales record of all rows is 1236000 .'}
|
round_eq { avg { all_rows ; sales } ; 1236000 } = true
|
the average of the sales record of all rows is 1236000 .
|
2
|
2
|
{'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'sales_4': 4, '1236000_5': 5}
|
{'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'sales_4': 'sales', '1236000_5': '1236000'}
|
{'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'sales_4': [0], '1236000_5': [1]}
|
['issue date', 'album title', 'artist', 'sales', 'highest position']
|
[['1', 'be here now', 'oasis', '1740000', '1'], ['2', 'urban hymns', 'the verve', '1690000', '1'], ['3', 'spice', 'spice girls', '1320000', '1'], ['4', 'white on blonde', 'texas', '1280000', '1'], ['5', 'spiceworld', 'spice girls', '1265000', '1'], ['6', 'the fat of the land', 'the prodigy', '1100000', '1'], ['7', "let 's talk about love", 'celine dion', '1090000', '1'], ['8', 'ok computer', 'radiohead', '980000', '1'], ['9', 'greatest hits', 'eternal', '955000', '2'], ['10', 'ocean drive', 'lighthouse family', '940000', '3']]
|
1979 world figure skating championships
|
https://en.wikipedia.org/wiki/1979_World_Figure_Skating_Championships
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11312764-5.html.csv
|
superlative
|
the highest scoring skaters at the 1979 world figure skating championships were tai babilonia and randy gardner .
|
{'scope': 'all', 'col_superlative': '4', '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', 'points'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; points }'}, 'name'], 'result': 'tai babilonia / randy gardner', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; points } ; name }'}, 'tai babilonia / randy gardner'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; points } ; name } ; tai babilonia / randy gardner } = true', 'tointer': 'select the row whose points record of all rows is maximum . the name record of this row is tai babilonia / randy gardner .'}
|
eq { hop { argmax { all_rows ; points } ; name } ; tai babilonia / randy gardner } = true
|
select the row whose points record of all rows is maximum . the name record of this row is tai babilonia / randy gardner .
|
3
|
3
|
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'points_5': 5, 'name_6': 6, 'tai babilonia / randy gardner_7': 7}
|
{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'points_5': 'points', 'name_6': 'name', 'tai babilonia / randy gardner_7': 'tai babilonia / randy gardner'}
|
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'points_5': [0], 'name_6': [1], 'tai babilonia / randy gardner_7': [2]}
|
['rank', 'name', 'nation', 'points', 'places']
|
[['1', 'tai babilonia / randy gardner', 'united states', '144.54', '12'], ['2', 'marina cherkasova / sergei shakhrai', 'soviet union', '142.22', '16'], ['3', 'sabine baeãÿ / tassilo thierbach', 'east germany', '137.74', '32'], ['4', 'irina vorobieva / igor lisovski', 'soviet union', '138.72', '33'], ['5', 'marina pestova / stanislav leonovich', 'soviet union', '133.98', '46'], ['6', 'vicki heasley / robert wagenhoffer', 'united states', '132.50', '54'], ['7', 'cornelia haufe / kersten bellmann', 'east germany', '128.98', '70'], ['8', 'christina riegel / andreas nischwitz', 'west germany', '128.56', '75'], ['9', 'sheryl franks / michael botticelli', 'united states', '127.64', '77'], ['10', 'kerstin stolfig / veit kempe', 'east germany', '125.92', '84'], ['11', 'barbara underhill / paul martini', 'canada', '123.92', '94'], ['12', 'gabriele beck / jochen stahl', 'west germany', '117.62', '114'], ['13', 'elizabeth cain / peter cain', 'australia', '115.32', '117'], ['14', 'kyoko hagiwara / hisao ozaki', 'japan', '114.02', '120']]
|
geelong football league
|
https://en.wikipedia.org/wiki/Geelong_Football_League
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17982112-2.html.csv
|
majority
|
none of the former teams in the geelong football league have had a gfl premiership .
|
{'scope': 'all', 'col': '4', 'most_or_all': 'all', 'criterion': 'fuzzily_match', 'value': 'nil', 'subset': None}
|
{'func': 'all_str_eq', 'args': ['all_rows', 'gfl premierships', 'nil'], 'result': True, 'ind': 0, 'tointer': 'for the gfl premierships records of all rows , all of them fuzzily match to nil .', 'tostr': 'all_eq { all_rows ; gfl premierships ; nil } = true'}
|
all_eq { all_rows ; gfl premierships ; nil } = true
|
for the gfl premierships records of all rows , all of them fuzzily match to nil .
|
1
|
1
|
{'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'gfl premierships_3': 3, 'nil_4': 4}
|
{'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'gfl premierships_3': 'gfl premierships', 'nil_4': 'nil'}
|
{'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'gfl premierships_3': [0], 'nil_4': [0]}
|
['club', 'nickname', 'location', 'gfl premierships', 'years in gfl']
|
[['barwon', 'bulldogs', 'belmont , victoria', 'nil', '1979 - 1989'], ['east geelong', 'eagles', 'east geelong , victoria', 'nil', '1979'], ['geelong amateur', 'ammos', 'highton , victoria', 'nil', '1986 - 1988'], ['geelong west cricket & football club', 'cheetahs', 'geelong west , victoria', 'nil', '1979 - 85'], ['north geelong', 'magpies', 'north geelong , victoria', 'nil', '1979 - 1982'], ['st peters', 'saints', 'herne hill , victoria', 'nil', '1979 , 1982 - 1987'], ['thomson', 'tigers', 'thomson , victoria', 'nil', '1979 - 1981 , 1984']]
|
flora , norway
|
https://en.wikipedia.org/wiki/Flora%2C_Norway
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-178381-1.html.csv
|
superlative
|
kinnakyrkje was the earliest of these churches to have been built .
|
{'scope': 'all', 'col_superlative': '4', 'row_superlative': '6', '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', 'year built'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; year built }'}, 'church name'], 'result': 'kinnakyrkje', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; year built } ; church name }'}, 'kinnakyrkje'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmin { all_rows ; year built } ; church name } ; kinnakyrkje } = true', 'tointer': 'select the row whose year built record of all rows is minimum . the church name record of this row is kinnakyrkje .'}
|
eq { hop { argmin { all_rows ; year built } ; church name } ; kinnakyrkje } = true
|
select the row whose year built record of all rows is minimum . the church name record of this row is kinnakyrkje .
|
3
|
3
|
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'year built_5': 5, 'church name_6': 6, 'kinnakyrkje_7': 7}
|
{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'year built_5': 'year built', 'church name_6': 'church name', 'kinnakyrkje_7': 'kinnakyrkje'}
|
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'year built_5': [0], 'church name_6': [1], 'kinnakyrkje_7': [2]}
|
['parish ( prestegjeld )', 'sub - parish ( sokn )', 'church name', 'year built', 'location of the church']
|
[['kinn parish', 'bru', 'askrova bedehuskapell', '1957', 'espeset'], ['kinn parish', 'bru', 'stavang kyrkje', '1957', 'stavang'], ['kinn parish', 'eikefjord', 'eikefjord kyrkje', '1812', 'eikefjord'], ['kinn parish', 'kinn', 'batalden bedehuskapell', '1907', 'fanøya'], ['kinn parish', 'kinn', 'florø kyrkje', '1882', 'florø'], ['kinn parish', 'kinn', 'kinnakyrkje', '12th century', 'kinn'], ['kinn parish', 'nordal', 'nordal kyrkje', '1898', 'nordalen']]
|
list of sumo record holders
|
https://en.wikipedia.org/wiki/List_of_sumo_record_holders
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17634218-21.html.csv
|
comparative
|
kotokasuga made his top division debut in sumo earlier than yoshiazuma did .
|
{'row_1': '4', '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', 'name', 'kotokasuga'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose name record fuzzily matches to kotokasuga .', 'tostr': 'filter_eq { all_rows ; name ; kotokasuga }'}, 'top division debut'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; name ; kotokasuga } ; top division debut }', 'tointer': 'select the rows whose name record fuzzily matches to kotokasuga . take the top division debut record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'name', 'yoshiazuma'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose name record fuzzily matches to yoshiazuma .', 'tostr': 'filter_eq { all_rows ; name ; yoshiazuma }'}, 'top division debut'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; name ; yoshiazuma } ; top division debut }', 'tointer': 'select the rows whose name record fuzzily matches to yoshiazuma . take the top division debut record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; name ; kotokasuga } ; top division debut } ; hop { filter_eq { all_rows ; name ; yoshiazuma } ; top division debut } } = true', 'tointer': 'select the rows whose name record fuzzily matches to kotokasuga . take the top division debut record of this row . select the rows whose name record fuzzily matches to yoshiazuma . take the top division debut record of this row . the first record is less than the second record .'}
|
less { hop { filter_eq { all_rows ; name ; kotokasuga } ; top division debut } ; hop { filter_eq { all_rows ; name ; yoshiazuma } ; top division debut } } = true
|
select the rows whose name record fuzzily matches to kotokasuga . take the top division debut record of this row . select the rows whose name record fuzzily matches to yoshiazuma . take the top division debut 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, 'name_7': 7, 'kotokasuga_8': 8, 'top division debut_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'name_11': 11, 'yoshiazuma_12': 12, 'top division debut_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', 'name_7': 'name', 'kotokasuga_8': 'kotokasuga', 'top division debut_9': 'top division debut', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'name_11': 'name', 'yoshiazuma_12': 'yoshiazuma', 'top division debut_13': 'top division debut'}
|
{'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'name_7': [0], 'kotokasuga_8': [0], 'top division debut_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'name_11': [1], 'yoshiazuma_12': [1], 'top division debut_13': [3]}
|
['name', 'tournaments', 'pro debut', 'top division debut', 'highest rank']
|
[['hoshiiwato', '115', 'may 1970', 'july 1989', 'maegashira 14'], ['kyokunankai', '105', 'march 1993', 'september 2010', 'maegashira 16'], ['yoshiazuma', '93', 'january 1996', 'september 2011', 'maegashira 12'], ['kotokasuga', '91', 'march 1993', 'may 2008', 'maegashira 7'], ['kototsubaki', '89', 'march 1976', 'january 1991', 'maegashira 3'], ['toyozakura', '88', 'march 1989', 'november 2003', 'maegashira 5'], ['takanomine', '87', 'september 1974', 'march 1989', 'maegashira 12'], ['kitazakura', '86', 'march 1987', 'july 2001', 'maegashira 9'], ['daimanazuru', '85', 'may 1992', 'july 2006', 'maegashira 16'], ['ånohana', '84', 'march 1974', 'march 1988', 'maegashira 13']]
|
michael shenton
|
https://en.wikipedia.org/wiki/Michael_Shenton
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14979029-1.html.csv
|
majority
|
michael shenton scored 0 goals for all games with team castleford tigers .
|
{'scope': 'all', 'col': '5', 'most_or_all': 'all', 'criterion': 'equal', 'value': '0', 'subset': None}
|
{'func': 'all_eq', 'args': ['all_rows', 'goals', '0'], 'result': True, 'ind': 0, 'tointer': 'for the goals records of all rows , all of them are equal to 0 .', 'tostr': 'all_eq { all_rows ; goals ; 0 } = true'}
|
all_eq { all_rows ; goals ; 0 } = true
|
for the goals records of all rows , all of them are equal to 0 .
|
1
|
1
|
{'all_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'goals_3': 3, '0_4': 4}
|
{'all_eq_0': 'all_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'goals_3': 'goals', '0_4': '0'}
|
{'all_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'goals_3': [0], '0_4': [0]}
|
['year', 'team', 'apps', 'tries', 'goals', 'points']
|
[['2004', 'castleford tigers', '3', '0', '0', '0'], ['2005', 'castleford tigers', '29', '24', '0', '96'], ['2006', 'castleford tigers', '27', '8', '0', '32'], ['2007', 'castleford tigers', '20', '19', '0', '76'], ['2008', 'castleford tigers', '22', '13', '0', '52'], ['2009', 'castleford tigers', '30', '19', '0', '76'], ['2010', 'castleford tigers', '22', '10', '0', '40'], ['total', 'castleford tigers', '153', '93', '0', '372']]
|
christian danner
|
https://en.wikipedia.org/wiki/Christian_Danner
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1219722-3.html.csv
|
superlative
|
1989 is the year in which christian danner scored the most points in his career .
|
{'scope': 'all', 'col_superlative': '5', 'row_superlative': '7', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None}
|
{'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'points'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; points }'}, 'year'], 'result': '1989', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; points } ; year }'}, '1989'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; points } ; year } ; 1989 } = true', 'tointer': 'select the row whose points record of all rows is maximum . the year record of this row is 1989 .'}
|
eq { hop { argmax { all_rows ; points } ; year } ; 1989 } = true
|
select the row whose points record of all rows is maximum . the year record of this row is 1989 .
|
3
|
3
|
{'eq_2': 2, 'result_3': 3, 'num_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'points_5': 5, 'year_6': 6, '1989_7': 7}
|
{'eq_2': 'eq', 'result_3': 'true', 'num_hop_1': 'num_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'points_5': 'points', 'year_6': 'year', '1989_7': '1989'}
|
{'eq_2': [3], 'result_3': [], 'num_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'points_5': [0], 'year_6': [1], '1989_7': [2]}
|
['year', 'team', 'chassis', 'engine', 'points']
|
[['1985', 'west zakspeed racing', 'zakspeed 841', 'zakspeed 1500 / 4 1.5 l4t', '0'], ['1986', 'osella squadra corse', 'osella fa1f', 'alfa romeo 890t 1.5 v8t', '1'], ['1986', 'barclay arrows bmw', 'arrows a8', 'bmw m12 / 13 1.5 l4t', '1'], ['1986', 'barclay arrows bmw', 'arrows a9', 'bmw m12 / 13 1.5 l4t', '1'], ['1987', 'west zakspeed racing', 'zakspeed 861', 'zakspeed 1500 / 4 1.5 l4t', '0'], ['1987', 'west zakspeed racing', 'zakspeed 871', 'zakspeed 1500 / 4 1.5 l4t', '0'], ['1989', 'rial racing', 'rial arc2', 'ford cosworth dfr ( mader ) 3.5 v8', '3']]
|
disk loading
|
https://en.wikipedia.org/wiki/Disk_loading
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-10006830-1.html.csv
|
count
|
in disk loading , one of the heavy - lift helicopter has a total disk area of more than 8000 ft square .
|
{'scope': 'subset', 'criterion': 'greater_than', 'value': '8000', 'result': '1', 'col': '4', 'subset': {'col': '2', 'criterion': 'equal', 'value': 'heavy - lift helicopter'}}
|
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'description', 'heavy - lift helicopter'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; description ; heavy - lift helicopter }', 'tointer': 'select the rows whose description record fuzzily matches to heavy - lift helicopter .'}, 'total disk area', '8000'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose description record fuzzily matches to heavy - lift helicopter . among these rows , select the rows whose total disk area record is greater than 8000 .', 'tostr': 'filter_greater { filter_eq { all_rows ; description ; heavy - lift helicopter } ; total disk area ; 8000 }'}], 'result': '1', 'ind': 2, 'tostr': 'count { filter_greater { filter_eq { all_rows ; description ; heavy - lift helicopter } ; total disk area ; 8000 } }', 'tointer': 'select the rows whose description record fuzzily matches to heavy - lift helicopter . among these rows , select the rows whose total disk area record is greater than 8000 . the number of such rows is 1 .'}, '1'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_greater { filter_eq { all_rows ; description ; heavy - lift helicopter } ; total disk area ; 8000 } } ; 1 } = true', 'tointer': 'select the rows whose description record fuzzily matches to heavy - lift helicopter . among these rows , select the rows whose total disk area record is greater than 8000 . the number of such rows is 1 .'}
|
eq { count { filter_greater { filter_eq { all_rows ; description ; heavy - lift helicopter } ; total disk area ; 8000 } } ; 1 } = true
|
select the rows whose description record fuzzily matches to heavy - lift helicopter . among these rows , select the rows whose total disk area record is greater than 8000 . the number of such rows is 1 .
|
4
|
4
|
{'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_greater_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'description_6': 6, 'heavy - lift helicopter_7': 7, 'total disk area_8': 8, '8000_9': 9, '1_10': 10}
|
{'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_greater_1': 'filter_greater', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'description_6': 'description', 'heavy - lift helicopter_7': 'heavy - lift helicopter', 'total disk area_8': 'total disk area', '8000_9': '8000', '1_10': '1'}
|
{'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_greater_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'description_6': [0], 'heavy - lift helicopter_7': [0], 'total disk area_8': [1], '8000_9': [1], '1_10': [3]}
|
['aircraft', 'description', 'max gross weight', 'total disk area', 'max disk loading']
|
[['robinson r - 22', 'light utility helicopter', '1370 lb ( 635 kg )', '497 ft square ( 46.2 m square )', '2.6 lb / ft square ( 14 kg / m square )'], ['bell 206b3 jetranger', 'turboshaft utility helicopter', '3200 lb ( 1451 kg )', '872 ft square ( 81.1 m square )', '3.7 lb / ft square ( 18 kg / m square )'], ['ch - 47d chinook', 'tandem rotor helicopter', '50000 lb ( 22680 kg )', '5655 ft square ( 526 m square )', '8.8 lb / ft square ( 43 kg / m square )'], ['mil mi - 26', 'heavy - lift helicopter', '123500 lb ( 56000 kg )', '8495 ft square ( 789 m square )', '14.5 lb / ft square ( 71 kg / m square )'], ['ch - 53e super stallion', 'heavy - lift helicopter', '73500 lb ( 33300 kg )', '4900 ft square ( 460 m square )', '15 lb / ft square ( 72 kg / m square )']]
|
lori chalupny
|
https://en.wikipedia.org/wiki/Lori_Chalupny
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12265902-2.html.csv
|
count
|
four of lori chalupny 's goals took place in locations in the usa .
|
{'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'usa', 'result': '4', 'col': '2', 'subset': None}
|
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location', 'usa'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose location record fuzzily matches to usa .', 'tostr': 'filter_eq { all_rows ; location ; usa }'}], 'result': '4', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; location ; usa } }', 'tointer': 'select the rows whose location record fuzzily matches to usa . the number of such rows is 4 .'}, '4'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; location ; usa } } ; 4 } = true', 'tointer': 'select the rows whose location record fuzzily matches to usa . the number of such rows is 4 .'}
|
eq { count { filter_eq { all_rows ; location ; usa } } ; 4 } = true
|
select the rows whose location record fuzzily matches to usa . 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, 'location_5': 5, 'usa_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', 'location_5': 'location', 'usa_6': 'usa', '4_7': '4'}
|
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'location_5': [0], 'usa_6': [0], '4_7': [2]}
|
['goal', 'location', 'lineup', 'assist / pass', 'score', 'result', 'competition']
|
[['1', 'usa albuquerque nm', "on 70 ' ( off lilly )", 'tarpley', '3 - 0', '3 - 0', 'friendly'], ['2', 'usa virginia beach', '90 . start', 'unassisted', '1 - 0', '2 - 0', 'friendly'], ['3', 'chn guangzhou', '90 . start', 'unassisted', '1 - 0', '2 - 0', 'four nations tournament'], ['4', 'usa frisco tx', "off 72 ' ( on wagner )", 'tarpley', '3 - 1', '6 - 2', 'friendly'], ['5', 'chn shanghai', '90 . start', 'wambach', '1 - 0', '1 - 0', 'world cup group b'], ['6', 'chn shanghai', '90 . start', 'unassisted', '3 - 0', '4 - 1', 'world cup final - third place playoff'], ['7', 'chn beijing', '90 . start', 'rodriguez', '2 - 1', '4 - 2', 'olympics tournament'], ['8', 'usa bridgeview il', '90 . start', 'tarpley', '1 - 0', '2 - 0', 'friendly']]
|
parks and recreation ( season 3 )
|
https://en.wikipedia.org/wiki/Parks_and_Recreation_%28season_3%29
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-29897962-1.html.csv
|
count
|
in the 3rd season of parks and recreation , 3 episodes were directed by dean holland .
|
{'scope': 'all', 'criterion': 'equal', 'value': 'dean holland', 'result': '3', 'col': '4', 'subset': None}
|
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'directed by', 'dean holland'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose directed by record fuzzily matches to dean holland .', 'tostr': 'filter_eq { all_rows ; directed by ; dean holland }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; directed by ; dean holland } }', 'tointer': 'select the rows whose directed by record fuzzily matches to dean holland . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; directed by ; dean holland } } ; 3 } = true', 'tointer': 'select the rows whose directed by record fuzzily matches to dean holland . the number of such rows is 3 .'}
|
eq { count { filter_eq { all_rows ; directed by ; dean holland } } ; 3 } = true
|
select the rows whose directed by record fuzzily matches to dean holland . 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, 'directed by_5': 5, 'dean holland_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', 'directed by_5': 'directed by', 'dean holland_6': 'dean holland', '3_7': '3'}
|
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'directed by_5': [0], 'dean holland_6': [0], '3_7': [2]}
|
['no in series', 'no in season', 'title', 'directed by', 'written by', 'original air date', 'us viewers ( million )']
|
[['31', '1', 'go big or go home', 'dean holland', 'alan yang', 'january 20 , 2011', '6.14'], ['32', '2', 'flu season', 'wendey stanzler', 'norm hiscock', 'january 27 , 2011', '5.83'], ['33', '3', 'time capsule', 'michael schur', 'michael schur', 'february 3 , 2011', '4.95'], ['34', '4', 'ron & tammy : part two', 'tucker gates', 'emily kapnek', 'february 10 , 2011', '5.03'], ['35', '5', 'media blitz', 'david rogers', 'harris wittels', 'february 17 , 2011', '4.33'], ['36', '6', 'indianapolis', 'randall einhorn', 'katie dippold', 'february 24 , 2011', '4.59'], ['37', '7', 'harvest festival', 'dean holland', 'dan goor', 'march 17 , 2011', '4.08'], ['38', '8', 'camping', 'rob schrab', 'aisha muharrar', 'march 24 , 2011', '5.15'], ['39', '9', "andy and april 's fancy party", 'michael trim', 'katie dippold', 'april 14 , 2011', '5.16'], ['40', '10', 'soulmates', 'ken whittingham', 'alan yang', 'april 21 , 2011', '4.88'], ['41', '11', "jerry 's painting", 'dean holland', 'norm hiscock', 'april 28 , 2011', '4.71'], ['42', '12', 'eagleton', 'nicole holofcener', 'emily spivey', 'may 5 , 2011', '5.06'], ['43', '13', 'the fight', 'randall einhorn', 'amy poehler', 'may 12 , 2011', '4.55'], ['44', '14', 'road trip', 'troy miller', 'harris wittels', 'may 12 , 2011', '3.55'], ['45', '15', 'the bubble', 'matt sohn', 'greg levine & brian rowe', 'may 19 , 2011', '4.27']]
|
2008 - 09 coventry city f.c. season
|
https://en.wikipedia.org/wiki/2008%E2%80%9309_Coventry_City_F.C._season
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17978754-5.html.csv
|
majority
|
in the 2008 - 09 coventry city f.c. season , most people have zero league cups .
|
{'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': '0', 'subset': None}
|
{'func': 'most_eq', 'args': ['all_rows', 'league cup', '0'], 'result': True, 'ind': 0, 'tointer': 'for the league cup records of all rows , most of them are equal to 0 .', 'tostr': 'most_eq { all_rows ; league cup ; 0 } = true'}
|
most_eq { all_rows ; league cup ; 0 } = true
|
for the league cup records of all rows , most of them are equal to 0 .
|
1
|
1
|
{'most_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'league cup_3': 3, '0_4': 4}
|
{'most_eq_0': 'most_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'league cup_3': 'league cup', '0_4': '0'}
|
{'most_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'league cup_3': [0], '0_4': [0]}
|
['name', 'championship', 'league cup', 'fa cup', 'total']
|
[['aron gunnarsson', '9', '1', '2', '12'], ['daniel fox', '8', '1', '0', '9'], ['guillaume beuzelin', '7', '0', '2', '9'], ['scott dann', '8', '0', '0', '8'], ['clinton morrison', '8', '0', '0', '8'], ['stephen wright', '6', '1', '0', '7'], ['isaac osbourne', '6', '0', '0', '6'], ['jay tabb', '4', '0', '0', '4'], ['freddy eastwood', '3', '0', '1', '4'], ['keiren westwood', '3', '0', '1', '4'], ['michael doyle', '4', '0', '0', '4'], ['elliott ward', '3', '0', '1', '4'], ['leon mckenzie', '3', '0', '0', '3'], ['robbie simpson', '3', '0', '0', '3'], ['leon best', '2', '0', '0', '2'], ['jordan henderson', '2', '0', '0', '2'], ['marcus hall', '1', '1', '0', '2'], ['ben turner', '2', '0', '0', '2'], ['michael mifsud', '1', '0', '0', '1'], ['james mcpake', '1', '0', '0', '1']]
|
spartak murtazayev
|
https://en.wikipedia.org/wiki/Spartak_Murtazayev
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12418501-1.html.csv
|
aggregation
|
spartak murtazayev had an average of 1.4 goals scored per season in his career .
|
{'scope': 'all', 'col': '5', 'type': 'average', 'result': '1.4', 'subset': None}
|
{'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'goals'], 'result': '1.4', 'ind': 0, 'tostr': 'avg { all_rows ; goals }'}, '1.4'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; goals } ; 1.4 } = true', 'tointer': 'the average of the goals record of all rows is 1.4 .'}
|
round_eq { avg { all_rows ; goals } ; 1.4 } = true
|
the average of the goals record of all rows is 1.4 .
|
2
|
2
|
{'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'goals_4': 4, '1.4_5': 5}
|
{'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'goals_4': 'goals', '1.4_5': '1.4'}
|
{'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'goals_4': [0], '1.4_5': [1]}
|
['season', 'team', 'country', 'apps', 'goals']
|
[['1997', 'sogdiana jizak', 'uzbekistan', '23', '1'], ['1998', 'sogdiana jizak', 'uzbekistan', '11', '1'], ['1998', 'fc pakhtakor tashkent', 'uzbekistan', '6', '0'], ['2000', 'sogdiana jizak', 'uzbekistan', '15', '0'], ['2000', 'qyzylqum zarashfan', 'uzbekistan', '16', '6'], ['2001', 'qyzylqum zarashfan', 'uzbekistan', '27', '5'], ['2002', 'qyzylqum zarashfan', 'uzbekistan', '23', '0'], ['2003', 'fc ordabasy', 'kazakhstan', '27', '2'], ['2004', 'fc ordabasy', 'kazakhstan', '13', '2'], ['2004', 'fc yassi', 'kazakhstan', '11', '0'], ['2005', 'fc ordabasy', 'kazakhstan', '14', '0'], ['2006', 'sogdiana jizak', 'uzbekistan', '14', '2'], ['2006', 'fc atyrau', 'kazakhstan', '14', '2'], ['2007', 'fc atyrau', 'kazakhstan', '2', '0'], ['2009', 'fk samarqand - dinamo', 'uzbekistan', '0', '0']]
|
2007 bc lions season
|
https://en.wikipedia.org/wiki/2007_BC_Lions_season
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11994830-20.html.csv
|
unique
|
buck pierce was the only player with a rating of 91.7 during the 2007 bc lions season .
|
{'scope': 'all', 'row': '2', 'col': '5', 'col_other': '1', 'criterion': 'equal', 'value': '91.7', 'subset': None}
|
{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'rating', '91.7'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose rating record is equal to 91.7 .', 'tostr': 'filter_eq { all_rows ; rating ; 91.7 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; rating ; 91.7 } }', 'tointer': 'select the rows whose rating record is equal to 91.7 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'rating', '91.7'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose rating record is equal to 91.7 .', 'tostr': 'filter_eq { all_rows ; rating ; 91.7 }'}, 'player'], 'result': 'buck pierce', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; rating ; 91.7 } ; player }'}, 'buck pierce'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; rating ; 91.7 } ; player } ; buck pierce }', 'tointer': 'the player record of this unqiue row is buck pierce .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; rating ; 91.7 } } ; eq { hop { filter_eq { all_rows ; rating ; 91.7 } ; player } ; buck pierce } } = true', 'tointer': 'select the rows whose rating record is equal to 91.7 . there is only one such row in the table . the player record of this unqiue row is buck pierce .'}
|
and { only { filter_eq { all_rows ; rating ; 91.7 } } ; eq { hop { filter_eq { all_rows ; rating ; 91.7 } ; player } ; buck pierce } } = true
|
select the rows whose rating record is equal to 91.7 . there is only one such row in the table . the player record of this unqiue row is buck pierce .
|
6
|
5
|
{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'rating_7': 7, '91.7_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'player_9': 9, 'buck pierce_10': 10}
|
{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'rating_7': 'rating', '91.7_8': '91.7', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'player_9': 'player', 'buck pierce_10': 'buck pierce'}
|
{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'rating_7': [0], '91.7_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'player_9': [2], 'buck pierce_10': [3]}
|
['player', 'att', 'comp', 'yards', 'rating']
|
[['jarious jackson', '304', '167', '2553', '88.9'], ['buck pierce', '127', '81', '1013', '91.7'], ['dave dickenson', '87', '56', '740', '88.3'], ['gino guidugli', '11', '6', '138', '92.2'], ['ian smart', '1', '0', '0', '2.1']]
|
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