topic
stringlengths 3
96
| wiki
stringlengths 33
127
| url
stringlengths 101
106
| action
stringclasses 7
values | sent
stringlengths 34
223
| annotation
stringlengths 74
227
| logic
stringlengths 207
5.45k
| logic_str
stringlengths 37
493
| interpret
stringlengths 43
471
| num_func
stringclasses 15
values | nid
stringclasses 13
values | g_ids
stringlengths 70
455
| g_ids_features
stringlengths 98
670
| g_adj
stringlengths 79
515
| table_header
stringlengths 40
458
| table_cont
large_stringlengths 135
4.41k
|
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
wu liufang
|
https://en.wikipedia.org/wiki/Wu_Liufang
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-26681728-1.html.csv
|
majority
|
wu liufang competed the most in ghent than in any other location .
|
{'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'ghent', 'subset': None}
|
{'func': 'most_str_eq', 'args': ['all_rows', 'location', 'ghent'], 'result': True, 'ind': 0, 'tointer': 'for the location records of all rows , most of them fuzzily match to ghent .', 'tostr': 'most_eq { all_rows ; location ; ghent } = true'}
|
most_eq { all_rows ; location ; ghent } = true
|
for the location records of all rows , most of them fuzzily match to ghent .
|
1
|
1
|
{'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'location_3': 3, 'ghent_4': 4}
|
{'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'location_3': 'location', 'ghent_4': 'ghent'}
|
{'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'location_3': [0], 'ghent_4': [0]}
|
['year', 'competition', 'location', 'apparatus', 'rank - final', 'score - final', 'rank - qualifying', 'score - qualifying']
|
[['2011', 'world cup', 'ghent', 'uneven bars', '3', '15.350', '1', '15.350'], ['2011', 'world cup', 'ghent', 'balance beam', '1', '14.975', '2', '14.850'], ['2011', 'world cup', 'ghent', 'floor exercise', '2', '13.650', '3', '13.475'], ['2010', 'world cup', 'ghent', 'uneven bars', '1', '15.050', '2', '14.775'], ['2010', 'world cup', 'ghent', 'balance beam', '3', '13.650', '2', '14.700'], ['2010', 'world cup', 'ghent', 'floor', '6', '12.700', '5', '13.450'], ['2010', 'world cup', 'doha', 'uneven bars', '2', '13.850', '2', '15.025'], ['2010', 'world cup', 'doha', 'balance beam', '1', '14.700', '1', '14.525'], ['2010', 'world cup', 'doha', 'floor', '1', '13.975', '6', '12.950']]
|
1986 pittsburgh steelers season
|
https://en.wikipedia.org/wiki/1986_Pittsburgh_Steelers_season
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-14520977-1.html.csv
|
majority
|
most of the games in the 1986 pittsburgh steelers season aired on nbc .
|
{'scope': 'all', 'col': '6', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'nbc', 'subset': None}
|
{'func': 'most_str_eq', 'args': ['all_rows', 'tv', 'nbc'], 'result': True, 'ind': 0, 'tointer': 'for the tv records of all rows , most of them fuzzily match to nbc .', 'tostr': 'most_eq { all_rows ; tv ; nbc } = true'}
|
most_eq { all_rows ; tv ; nbc } = true
|
for the tv records of all rows , most of them fuzzily match to nbc .
|
1
|
1
|
{'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'tv_3': 3, 'nbc_4': 4}
|
{'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'tv_3': 'tv', 'nbc_4': 'nbc'}
|
{'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'tv_3': [0], 'nbc_4': [0]}
|
['week', 'date', 'opponent', 'location', 'time ( et )', 'tv', 'result', 'record']
|
[['1', 'sun sep 7', 'seattle seahawks', 'kingdome', '4:00 pm', 'nbc', 'l 30 - 0', '0 - 1'], ['2', 'mon sep 15', 'denver broncos', 'three rivers stadium', '9:00 pm', 'abc', 'l 21 - 10', '0 - 2'], ['3', 'sun sep 21', 'minnesota vikings', 'hubert h humphrey metrodome', '1:00 pm', 'nbc', 'l 31 - 7', '0 - 3'], ['4', 'sun sep 28', 'houston oilers', 'astrodome', '1:00 pm', 'nbc', 'w 22 - 16 ot', '1 - 3'], ['5', 'sun oct 5', 'cleveland browns', 'three rivers stadium', '1:00 pm', 'nbc', 'l 27 - 24', '1 - 4'], ['6', 'mon oct 13', 'cincinnati bengals', 'riverfront stadium', '9:00 pm', 'abc', 'l 24 - 22', '1 - 5'], ['7', 'sun oct 19', 'new england patriots', 'three rivers stadium', '1:00 pm', 'nbc', 'l 34 - 0', '1 - 6'], ['8', 'sun oct 26', 'cincinnati bengals', 'three rivers stadium', '1:00 pm', 'nbc', 'w 30 - 9', '2 - 6'], ['9', 'sun nov 2', 'green bay packers', 'three rivers stadium', '1:00 pm', 'cbs', 'w 27 - 3', '3 - 6'], ['10', 'sun nov 9', 'buffalo bills', 'rich stadium', '1:00 pm', 'nbc', 'l 16 - 12', '3 - 7'], ['11', 'sun nov 16', 'houston oilers', 'three rivers stadium', '1:00 pm', 'nbc', 'w 21 - 10', '4 - 7'], ['12', 'sun nov 23', 'cleveland browns', 'cleveland municipal stadium', '1:00 pm', 'nbc', 'l 37 - 31 ot', '4 - 8'], ['13', 'sun nov 30', 'chicago bears', 'soldier field', '1:00 pm', 'nbc', 'l 13 - 10 ot', '4 - 9'], ['14', 'sun dec 7', 'detroit lions', 'three rivers stadium', '1:00 pm', 'cbs', 'w 27 - 17', '5 - 9'], ['15', 'sat dec 13', 'new york jets', 'giants stadium', '12:30 pm', 'nbc', 'w 45 - 24', '6 - 9']]
|
1995 - 96 chicago bulls season
|
https://en.wikipedia.org/wiki/1995%E2%80%9396_Chicago_Bulls_season
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-13480122-5.html.csv
|
ordinal
|
during the 1995 - 96 season , the chicago bulls ' game against toronto recorded the highest attendance .
|
{'row': '8', 'col': '8', 'order': '1', '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', 'location attendance', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; location attendance ; 1 }'}, 'team'], 'result': 'toronto', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; location attendance ; 1 } ; team }'}, 'toronto'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; location attendance ; 1 } ; team } ; toronto } = true', 'tointer': 'select the row whose location attendance record of all rows is 1st maximum . the team record of this row is toronto .'}
|
eq { hop { nth_argmax { all_rows ; location attendance ; 1 } ; team } ; toronto } = true
|
select the row whose location attendance record of all rows is 1st maximum . the team record of this row is toronto .
|
3
|
3
|
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'location attendance_5': 5, '1_6': 6, 'team_7': 7, 'toronto_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', 'location attendance_5': 'location attendance', '1_6': '1', 'team_7': 'team', 'toronto_8': 'toronto'}
|
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'location attendance_5': [0], '1_6': [0], 'team_7': [1], 'toronto_8': [2]}
|
['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record']
|
[['29', 'january 3', 'houston', 'w 100 - 86', 'michael jordan ( 38 )', 'dennis rodman ( 15 )', 'scottie pippen ( 9 )', 'united center 23854', '26 - 3'], ['30', 'january 4', 'charlotte', 'w 117 - 93', 'michael jordan ( 27 )', 'dennis rodman ( 11 )', 'ron harper ( 7 )', 'charlotte coliseum 24042', '27 - 3'], ['31', 'january 6', 'milwaukee', 'w 113 - 84', 'michael jordan ( 32 )', 'dennis rodman ( 16 )', 'scottie pippen ( 6 )', 'united center 23801', '28 - 3'], ['32', 'january 10', 'seattle', 'w 113 - 87', 'michael jordan ( 35 )', 'michael jordan ( 14 )', 'michael jordan , luc longley , scottie pippen ( 5 )', 'united center 23877', '29 - 3'], ['33', 'january 13', 'philadelphia', 'w 120 - 93', 'michael jordan ( 48 )', 'dennis rodman ( 16 )', 'scottie pippen ( 10 )', 'the spectrum 18168', '30 - 3'], ['34', 'january 15', 'washington', 'w 116 - 109', 'michael jordan ( 46 )', 'dennis rodman ( 15 )', 'scottie pippen ( 6 )', 'usair arena 18756', '31 - 3'], ['35', 'january 16', 'philadelphia', 'w 116 - 104', 'michael jordan ( 32 )', 'dennis rodman ( 21 )', 'dennis rodman ( 10 )', 'united center 23587', '32 - 3'], ['36', 'january 18', 'toronto', 'w 92 - 89', 'michael jordan ( 38 )', 'dennis rodman ( 13 )', 'scottie pippen , dennis rodman ( 4 )', 'skydome 36118', '33 - 3'], ['37', 'january 21', 'detroit', 'w 111 - 96', 'michael jordan ( 36 )', 'dennis rodman ( 9 )', 'scottie pippen ( 6 )', 'the palace of auburn hills 21454', '34 - 3'], ['38', 'january 23', 'new york', 'w 99 - 79', 'michael jordan ( 33 )', 'dennis rodman ( 13 )', 'scottie pippen ( 6 )', 'madison square garden 19763', '35 - 3'], ['39', 'january 24', 'vancouver', 'w 104 - 84', 'scottie pippen ( 30 )', 'dennis rodman ( 16 )', 'ron harper ( 7 )', 'united center 23652', '36 - 3'], ['40', 'january 26', 'miami', 'w 102 - 80', 'michael jordan ( 25 )', 'dennis rodman ( 16 )', 'scottie pippen , dennis rodman ( 5 )', 'united center 23814', '37 - 3'], ['41', 'january 28', 'phoenix', 'w 93 - 82', 'michael jordan ( 31 )', 'dennis rodman ( 20 )', 'michael jordan ( 6 )', 'united center 23927', '38 - 3']]
|
yakushiji ryōko no kaiki jikenbo
|
https://en.wikipedia.org/wiki/Yakushiji_Ry%C5%8Dko_no_Kaiki_Jikenbo
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18443854-1.html.csv
|
comparative
|
paris , the strange attractive capital was published before visitor 's fog was published .
|
{'row_1': '3', 'row_2': '7', 'col': '3', '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', 'english title', 'paris , the strange attractive capital'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose english title record fuzzily matches to paris , the strange attractive capital .', 'tostr': 'filter_eq { all_rows ; english title ; paris , the strange attractive capital }'}, 'year'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; english title ; paris , the strange attractive capital } ; year }', 'tointer': 'select the rows whose english title record fuzzily matches to paris , the strange attractive capital . take the year record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'english title', "visitor 's fog"], 'result': None, 'ind': 1, 'tointer': "select the rows whose english title record fuzzily matches to visitor 's fog .", 'tostr': "filter_eq { all_rows ; english title ; visitor 's fog }"}, 'year'], 'result': None, 'ind': 3, 'tostr': "hop { filter_eq { all_rows ; english title ; visitor 's fog } ; year }", 'tointer': "select the rows whose english title record fuzzily matches to visitor 's fog . take the year record of this row ."}], 'result': True, 'ind': 4, 'tostr': "less { hop { filter_eq { all_rows ; english title ; paris , the strange attractive capital } ; year } ; hop { filter_eq { all_rows ; english title ; visitor 's fog } ; year } } = true", 'tointer': "select the rows whose english title record fuzzily matches to paris , the strange attractive capital . take the year record of this row . select the rows whose english title record fuzzily matches to visitor 's fog . take the year record of this row . the first record is less than the second record ."}
|
less { hop { filter_eq { all_rows ; english title ; paris , the strange attractive capital } ; year } ; hop { filter_eq { all_rows ; english title ; visitor 's fog } ; year } } = true
|
select the rows whose english title record fuzzily matches to paris , the strange attractive capital . take the year record of this row . select the rows whose english title record fuzzily matches to visitor 's fog . take the year record of this row . the first record is less than the second record .
|
5
|
5
|
{'less_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'english title_7': 7, 'paris , the strange attractive capital_8': 8, 'year_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'english title_11': 11, "visitor 's fog_12": 12, 'year_13': 13}
|
{'less_4': 'less', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'english title_7': 'english title', 'paris , the strange attractive capital_8': 'paris , the strange attractive capital', 'year_9': 'year', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'english title_11': 'english title', "visitor 's fog_12": "visitor 's fog", 'year_13': 'year'}
|
{'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'english title_7': [0], 'paris , the strange attractive capital_8': [0], 'year_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'english title_11': [1], "visitor 's fog_12": [1], 'year_13': [3]}
|
['japanese title', 'english title', 'year', 'first publisher', 'isbn']
|
[['魔天楼 ( matenrō )', 'demon skyscraper', '1996', 'kodansha bunko', 'isbn 4 - 06 - 263346 - 9'], ['東京ナイトメア ( tokyo nightmare )', 'tokyo nightmare', '1999', 'kodansha novels', 'isbn 4 - 06 - 182042 - 7'], ['巴里 ・ 妖都変 ( paris yōto - hen )', 'paris , the strange attractive capital', '2000', 'kobunsha kappa novels', 'isbn 4 - 334 - 07371 - 9'], ['クレオパトラの葬送 ( cleopatra no sōsō )', 'funeral of the cleopatra', '2001', 'kodansha novels', 'isbn 4 - 06 - 182197 - 0'], ['黒蜘蛛島 ( black spider island )', 'black spider island', '2003', 'kobunsha kappa novels', 'isbn 4 - 334 - 07541 - x'], ['夜光曲 ( yakōkyoku )', 'luminous song', '2005', 'shodensha non - novels', 'isbn 4 - 396 - 20793 - x'], ['霧の訪問者 ( kiri no hōmonsha )', "visitor 's fog", '2006', 'kodansha novels', 'isbn 4 - 06 - 182499 - 6'], ['水妖日にご用心 ( suiyō - bi ni goyōjin )', 'be careful on wednesday', '2007', 'shodensha non - novels', 'isbn 4 - 396 - 20840 - 5']]
|
1998 masters tournament
|
https://en.wikipedia.org/wiki/1998_Masters_Tournament
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16514546-2.html.csv
|
count
|
there were 10 players who participated in the 1998 masters tournament .
|
{'scope': 'all', 'criterion': 'all', 'value': 'n/a', 'result': '10', 'col': '2', 'subset': None}
|
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_all', 'args': ['all_rows', 'player'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose player record is arbitrary .', 'tostr': 'filter_all { all_rows ; player }'}], 'result': '10', 'ind': 1, 'tostr': 'count { filter_all { all_rows ; player } }', 'tointer': 'select the rows whose player record is arbitrary . the number of such rows is 10 .'}, '10'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_all { all_rows ; player } } ; 10 } = true', 'tointer': 'select the rows whose player record is arbitrary . the number of such rows is 10 .'}
|
eq { count { filter_all { all_rows ; player } } ; 10 } = true
|
select the rows whose player record is arbitrary . the number of such rows is 10 .
|
3
|
3
|
{'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_all_0': 0, 'all_rows_4': 4, 'player_5': 5, '10_6': 6}
|
{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_all_0': 'filter_all', 'all_rows_4': 'all_rows', 'player_5': 'player', '10_6': '10'}
|
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_all_0': [1], 'all_rows_4': [0], 'player_5': [0], '10_6': [2]}
|
['place', 'player', 'country', 'score', 'to par']
|
[['t1', 'fred couples', 'united states', '69 + 70 = 139', '- 5'], ['t1', 'david duval', 'united states', '71 + 68 = 139', '- 5'], ['3', 'scott hoch', 'united states', '70 + 71 = 141', '- 3'], ['t4', 'paul azinger', 'united states', '71 + 72 = 143', '- 1'], ['t4', 'jay haas', 'united states', '72 + 71 = 143', '- 1'], ['t4', 'phil mickelson', 'united states', '74 + 69 = 143', '- 1'], ['t4', 'josé maría olazábal', 'spain', '70 + 73 = 143', '- 1'], ['t4', 'tiger woods', 'united states', '71 + 72 = 143', '- 1'], ['t9', 'scott mccarron', 'united states', '73 + 71 = 144', 'e'], ['t9', "mark o'meara", 'united states', '74 + 70 = 144', 'e']]
|
list of t.u.f.f. puppy episodes
|
https://en.wikipedia.org/wiki/List_of_T.U.F.F._Puppy_episodes
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-28787871-3.html.csv
|
count
|
nine of the episodes aired for the first time in the year 2012 .
|
{'scope': 'all', 'criterion': 'fuzzily_match', 'value': '2012', 'result': '9', 'col': '4', 'subset': None}
|
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'original air date', '2012'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose original air date record fuzzily matches to 2012 .', 'tostr': 'filter_eq { all_rows ; original air date ; 2012 }'}], 'result': '9', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; original air date ; 2012 } }', 'tointer': 'select the rows whose original air date record fuzzily matches to 2012 . the number of such rows is 9 .'}, '9'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; original air date ; 2012 } } ; 9 } = true', 'tointer': 'select the rows whose original air date record fuzzily matches to 2012 . the number of such rows is 9 .'}
|
eq { count { filter_eq { all_rows ; original air date ; 2012 } } ; 9 } = true
|
select the rows whose original air date record fuzzily matches to 2012 . the number of such rows is 9 .
|
3
|
3
|
{'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'original air date_5': 5, '2012_6': 6, '9_7': 7}
|
{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'original air date_5': 'original air date', '2012_6': '2012', '9_7': '9'}
|
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'original air date_5': [0], '2012_6': [0], '9_7': [2]}
|
['no in series', 'no in season', 'title', 'original air date', 'production code', 'us viewers ( millions )']
|
[['21', '1', 'a doomed christmas', 'december 10 , 2011', '121', 'n / a'], ['22', '2', "big dog on campus / dog 's best friend", 'january 16 , 2012', '122', 'n / a'], ['23', '3', 'monkey business / diary of a mad cat', 'april 21 , 2012', '125', 'n / a'], ['24', '4', 'dudley do - wrong / puppy unplugged', 'may 6 , 2012', '123', 'n / a'], ['25', '5', 'freaky spy day / dog tired', 'may 13 , 2012', '202', 'n / a'], ['26', '6', 'top dog / quack in the box', 'may 20 , 2012', '124', 'n / a'], ['27', '7', 'lie like a dog / cold fish', 'may 27 , 2012', '126', '2.3'], ['28', '8', 'pup daddy / candy cane - ine', 'june 3 , 2012', '201', 'n / a'], ['29', '9', 'bark to the future / lights , camera , quacktion', 'october 13 , 2012', '205', '1.8'], ['30', '10', 'happy howl - o - ween', 'october 27 , 2012', '210', '1.6'], ['31', '11', 'bark to nature / mutts and bolts', 'august 5 , 2013', '213', '1.9'], ['32', '12', 'dog house / time waits for no mutt', 'august 6 , 2013', '203', '1.6'], ['33', '13', 'hush puppy / quacky birthday', 'august 8 , 2013', '209', '1.8'], ['34', '14', 'love bird / bluff puppy', 'october 20 , 2013 ( nicktoons )', '204', 'n / a'], ['35', '15', 'rat trap / agent of the year', 'october 27 , 2013 ( nicktoons )', '207', 'n / a'], ['36', '16', 'barking tall / bad eggs', 'november 3 , 2013 ( nicktoons )', '212', 'n / a'], ['37', '17', 'carbon copies / tuff cookies', 'november 10 , 2013 ( nicktoons )', '214', 'n / a'], ['39', '19', 'tuff choices / sob story', 'tba ( nicktoons )', '208', 'n / a']]
|
independent girls ' schools sports association ( south australia )
|
https://en.wikipedia.org/wiki/Independent_Girls%27_Schools_Sports_Association_%28South_Australia%29
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-22043925-1.html.csv
|
superlative
|
pembroke school has the highest enrollment of schools in the independent girls ' schools sports association .
|
{'scope': 'all', 'col_superlative': '3', 'row_superlative': '4', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None}
|
{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'enrolment'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; enrolment }'}, 'school'], 'result': 'pembroke school', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; enrolment } ; school }'}, 'pembroke school'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; enrolment } ; school } ; pembroke school } = true', 'tointer': 'select the row whose enrolment record of all rows is maximum . the school record of this row is pembroke school .'}
|
eq { hop { argmax { all_rows ; enrolment } ; school } ; pembroke school } = true
|
select the row whose enrolment record of all rows is maximum . the school record of this row is pembroke school .
|
3
|
3
|
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'enrolment_5': 5, 'school_6': 6, 'pembroke school_7': 7}
|
{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'enrolment_5': 'enrolment', 'school_6': 'school', 'pembroke school_7': 'pembroke school'}
|
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'enrolment_5': [0], 'school_6': [1], 'pembroke school_7': [2]}
|
['school', 'location', 'enrolment', 'founded', 'denomination', 'boys / girls', 'day / boarding', 'school colors']
|
[['annesley college', 'wayville', '530', '1902', 'uniting church', 'girls', 'day & boarding', 'maroon & white'], ['concordia college', 'highgate', '700', '1890', 'lutheran', 'boys & girls', 'day', 'blue & gold'], ['immanuel college', 'novar gardens', '800', '1895', 'lutheran', 'boys & girls', 'day & boarding', 'blue , gold & white'], ['pembroke school', 'kensington park', '1545', '1915', 'non - denominational', 'boys & girls', 'day & boarding', 'royal blue , green & gold'], ['pulteney grammar school', 'adelaide', '820', '1847', 'anglican', 'boys & girls', 'day', 'navy blue , white & gold'], ["st peter 's collegiate girls ' school", 'stonyfell', '550', '1894', 'anglican', 'girls', 'day', 'navy blue & white'], ['scotch college', 'mitcham', '850', '1919', 'uniting church', 'boys & girls', 'day & boarding', 'blue & gold'], ['seymour college', 'glen osmond', '765', '1922', 'uniting church', 'girls', 'day & boarding', 'green , navy & white'], ['walford anglican school for girls', 'hyde park', '650', '1893', 'anglican', 'girls', 'day & boarding', 'navy blue , light blue & gold'], ['westminster school', 'marion', '1100', '1961', 'uniting church', 'boys & girls', 'day & boarding', 'green & white']]
|
list of my place episodes
|
https://en.wikipedia.org/wiki/List_of_My_Place_episodes
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-25390694-2.html.csv
|
count
|
shawn seet directed 3 episodes of the series titled ' my place ' .
|
{'scope': 'all', 'criterion': 'equal', 'value': 'shawn seet', 'result': '3', 'col': '3', 'subset': None}
|
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'director', 'shawn seet'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose director record fuzzily matches to shawn seet .', 'tostr': 'filter_eq { all_rows ; director ; shawn seet }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; director ; shawn seet } }', 'tointer': 'select the rows whose director record fuzzily matches to shawn seet . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; director ; shawn seet } } ; 3 } = true', 'tointer': 'select the rows whose director record fuzzily matches to shawn seet . the number of such rows is 3 .'}
|
eq { count { filter_eq { all_rows ; director ; shawn seet } } ; 3 } = true
|
select the rows whose director record fuzzily matches to shawn seet . 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, 'director_5': 5, 'shawn seet_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', 'director_5': 'director', 'shawn seet_6': 'shawn seet', '3_7': '3'}
|
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'director_5': [0], 'shawn seet_6': [0], '3_7': [2]}
|
['series', 'title', 'director', 'writer', 'air date', 'production code']
|
[['1', 'laura 2008', 'shawn seet', 'leah purcell', 'december 4 , 2009', '101'], ['2', 'mohammed 1998', 'shawn seet', 'brendan cowell', 'december 7 , 2009', '102'], ['3', 'lily 1988', 'shawn seet', 'greg waters', 'december 8 , 2009', '103'], ['4', 'mike 1978', 'michael james rowland', 'nicholas parsons', 'december 9 , 2009', '104'], ['5', 'sofia 1968', 'michael james rowland', 'nicholas parsons', 'december 10 , 2009', '105'], ['6', 'michaelis 1958', 'michael james rowland', 'tim pye', 'december 11 , 2009', '106'], ['7', 'jen 1948', 'catriona mckenzie', 'alice addison', 'december 14 , 2009', '107'], ['8', 'colum 1938', 'catriona mckenzie', 'greg waters', 'december 15 , 2009', '108'], ['9', 'bridie 1928', 'samantha lang', 'gina roncoli', 'december 16 , 2009', '109'], ['10', 'bertie 1918', 'samantha lang', 'nicolas parsons', 'december 17 , 2009', '110'], ['11', 'evelyn 1908', 'jessica hobbs', 'blake ayshford', 'december 18 , 2009', '111'], ['12', 'rowley 1898', 'jessica hobbs', 'tim pye', 'december 21 , 2009', '112']]
|
wind power in the republic of ireland
|
https://en.wikipedia.org/wiki/Wind_power_in_the_Republic_of_Ireland
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14101606-2.html.csv
|
count
|
there are 17 wind farms generating wind power in the republic of ireland .
|
{'scope': 'all', 'criterion': 'all', 'value': 'n/a', 'result': '17', 'col': '1', 'subset': None}
|
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_all', 'args': ['all_rows', 'wind farm'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose wind farm record is arbitrary .', 'tostr': 'filter_all { all_rows ; wind farm }'}], 'result': '17', 'ind': 1, 'tostr': 'count { filter_all { all_rows ; wind farm } }', 'tointer': 'select the rows whose wind farm record is arbitrary . the number of such rows is 17 .'}, '17'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_all { all_rows ; wind farm } } ; 17 } = true', 'tointer': 'select the rows whose wind farm record is arbitrary . the number of such rows is 17 .'}
|
eq { count { filter_all { all_rows ; wind farm } } ; 17 } = true
|
select the rows whose wind farm record is arbitrary . the number of such rows is 17 .
|
3
|
3
|
{'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_all_0': 0, 'all_rows_4': 4, 'wind farm_5': 5, '17_6': 6}
|
{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_all_0': 'filter_all', 'all_rows_4': 'all_rows', 'wind farm_5': 'wind farm', '17_6': '17'}
|
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_all_0': [1], 'all_rows_4': [0], 'wind farm_5': [0], '17_6': [2]}
|
['wind farm', 'scheduled', 'capacity ( mw )', 'turbines', 'type', 'location']
|
[['codling', 'unknown', '1100', '220', 'unknown', 'county wicklow'], ['carrowleagh', '2012', '36.8', '16', 'enercon e - 70 2.3', 'county cork'], ['dublin array', '2015', '364', '145', 'unknown', 'county dublin'], ['glenmore', '2009 summer', '30', '10', 'vestas v90', 'county clare'], ['glenough', '2010 winter', '32.5', '13', 'nordex n80 / n90', 'county tipperary'], ['gortahile', '2010 autumn', '20', '8', 'nordex n90', 'county laois'], ['grouse lodge', '2011 summer', '20', '8', 'nordex n90', 'county tipperary'], ['moneypoint', 'unknown', '22.5', '9', 'unknown', 'county clare'], ['mount callan', 'unknown', '90', '30', '3 mw', 'county clare'], ['oriel', '2013', '330', '55', 'unknown', 'county louth'], ['skerd rocks', 'unknown', '100', '20', '5 mw', 'county galway'], ['shragh', 'planning submitted oct 2011', '135', '45', 'enercon e82 3.0 mw', 'county clare'], ['garracummer', '2012', '42.5', '17', 'nordex n90 2.5 mw', 'county tipperary'], ['knockacummer', '2013', '87.5', '35', 'nordex n90 2.5 mw', 'county cork'], ['monaincha', '2013', '36', '15', 'nordex n117 2.4 mw', 'county tipperary'], ['gibbet hill', '2013', '15', '6', 'nordex n90 2.5 mw', 'county wexford'], ['glenough extension', '2013', '2.5', '1', 'nordex n90 2.5 mw', 'county tipperary']]
|
list of ireland cricket captains
|
https://en.wikipedia.org/wiki/List_of_Ireland_cricket_captains
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11783487-3.html.csv
|
superlative
|
jason mollins is the ireland cricket captain with the highest win percentage .
|
{'scope': 'all', 'col_superlative': '6', 'row_superlative': '5', 'value_mentioned': 'yes', 'max_or_min': 'max', 'other_col': '1', 'subset': None}
|
{'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'max', 'args': ['all_rows', '% win'], 'result': '100.00', 'ind': 0, 'tostr': 'max { all_rows ; % win }', 'tointer': 'the maximum % win record of all rows is 100.00 .'}, '100.00'], 'result': True, 'ind': 1, 'tostr': 'eq { max { all_rows ; % win } ; 100.00 }', 'tointer': 'the maximum % win record of all rows is 100.00 .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', '% win'], 'result': None, 'ind': 2, 'tostr': 'argmax { all_rows ; % win }'}, 'player'], 'result': 'jason molins', 'ind': 3, 'tostr': 'hop { argmax { all_rows ; % win } ; player }'}, 'jason molins'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { argmax { all_rows ; % win } ; player } ; jason molins }', 'tointer': 'the player record of the row with superlative % win record is jason molins .'}], 'result': True, 'ind': 5, 'tostr': 'and { eq { max { all_rows ; % win } ; 100.00 } ; eq { hop { argmax { all_rows ; % win } ; player } ; jason molins } } = true', 'tointer': 'the maximum % win record of all rows is 100.00 . the player record of the row with superlative % win record is jason molins .'}
|
and { eq { max { all_rows ; % win } ; 100.00 } ; eq { hop { argmax { all_rows ; % win } ; player } ; jason molins } } = true
|
the maximum % win record of all rows is 100.00 . the player record of the row with superlative % win record is jason molins .
|
6
|
6
|
{'and_5': 5, 'result_6': 6, 'eq_1': 1, 'max_0': 0, 'all_rows_7': 7, '% win_8': 8, '100.00_9': 9, 'str_eq_4': 4, 'str_hop_3': 3, 'argmax_2': 2, 'all_rows_10': 10, '% win_11': 11, 'player_12': 12, 'jason molins_13': 13}
|
{'and_5': 'and', 'result_6': 'true', 'eq_1': 'eq', 'max_0': 'max', 'all_rows_7': 'all_rows', '% win_8': '% win', '100.00_9': '100.00', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'argmax_2': 'argmax', 'all_rows_10': 'all_rows', '% win_11': '% win', 'player_12': 'player', 'jason molins_13': 'jason molins'}
|
{'and_5': [6], 'result_6': [], 'eq_1': [5], 'max_0': [1], 'all_rows_7': [0], '% win_8': [0], '100.00_9': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'argmax_2': [3], 'all_rows_10': [2], '% win_11': [2], 'player_12': [3], 'jason molins_13': [4]}
|
['player', 'dates of captaincy', 'lost', 'tied', 'no result', '% win']
|
[['alan lewis', '1993 / 94', '4', '0', '0', '42.86'], ['justin benson', '1996 / 97', '3', '0', '1', '66.66'], ['kyle mccallan', '2001 - 2005', '5', '1', '0', '44.44'], ['dekker curry', '2005', '1', '0', '0', '0.00'], ['jason molins', '2005', '0', '0', '0', '100.00'], ['william porterfield', '2009', '2', '0', '0', '80.00'], ['total', '1993 / 94 - 2005', '13', '0', '1', '58.06']]
|
liberty league
|
https://en.wikipedia.org/wiki/Liberty_League
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1974482-1.html.csv
|
majority
|
all of the institutions in the liberty league are private type institutions .
|
{'scope': 'all', 'col': '5', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'private', 'subset': None}
|
{'func': 'all_str_eq', 'args': ['all_rows', 'type', 'private'], 'result': True, 'ind': 0, 'tointer': 'for the type records of all rows , all of them fuzzily match to private .', 'tostr': 'all_eq { all_rows ; type ; private } = true'}
|
all_eq { all_rows ; type ; private } = true
|
for the type records of all rows , all of them fuzzily match to private .
|
1
|
1
|
{'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'type_3': 3, 'private_4': 4}
|
{'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'type_3': 'type', 'private_4': 'private'}
|
{'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'type_3': [0], 'private_4': [0]}
|
['institution', 'nickname', 'location', 'founded', 'type', 'enrollment', 'joined']
|
[['bard college', 'raptors', 'annandale - on - hudson , new york', '1860', 'private', '1958', '2011'], ['clarkson university', 'golden knights', 'potsdam , new york', '1896', 'private', '2848', '1995'], ['hobart college', 'statesmen', 'geneva , new york', '1822', 'private', '905', '1995'], ['rensselaer polytechnic institute', 'engineers', 'troy , new york', '1824', 'private', '5431', '1995'], ['rochester institute of technology', 'tigers', 'henrietta , new york', '1829', 'private', '14224', '2011'], ['university of rochester', 'yellowjackets', 'rochester , new york', '1850', 'private', '5601', '1995'], ['st lawrence university', 'saints', 'canton , new york', '1856', 'private', '2327', '1995'], ['skidmore college', 'thoroughbreds', 'saratoga springs , new york', '1903', 'private', '2734', '1995'], ['union college', 'dutchmen', 'schenectady , new york', '1795', 'private', '2197', '1995'], ['vassar college', 'brewers', 'poughkeepsie , new york', '1861', 'private', '2446', '2001']]
|
royal canadian mint numismatic coins ( 2000s )
|
https://en.wikipedia.org/wiki/Royal_Canadian_Mint_numismatic_coins_%282000s%29
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11916083-39.html.csv
|
aggregation
|
the average issued price of the royal canadian mint numismatic coins ( 2000s ) was 59.95 .
|
{'scope': 'all', 'col': '5', 'type': 'average', 'result': '59.95', 'subset': None}
|
{'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'issue price'], 'result': '59.95', 'ind': 0, 'tostr': 'avg { all_rows ; issue price }'}, '59.95'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; issue price } ; 59.95 } = true', 'tointer': 'the average of the issue price record of all rows is 59.95 .'}
|
round_eq { avg { all_rows ; issue price } ; 59.95 } = true
|
the average of the issue price record of all rows is 59.95 .
|
2
|
2
|
{'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'issue price_4': 4, '59.95_5': 5}
|
{'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'issue price_4': 'issue price', '59.95_5': '59.95'}
|
{'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'issue price_4': [0], '59.95_5': [1]}
|
['year', 'theme', 'artist', 'mintage', 'issue price']
|
[['2000', 'steam buggy', 'john mardon', '44367', '59.95'], ['2000', 'the bluenose', 'j franklin wright', 'included in steam buggy', '59.95'], ['2000', 'the toronto', 'john mardon', 'included in steam buggy', '59.95'], ['2001', 'the russell light four', 'john mardon', '41828', '59.95'], ['2001', 'the marco polo', 'j franklin wright', 'included in the russell', '59.95'], ['2001', 'the scotia', 'don curley', 'included in the russell', '59.95'], ['2002', 'the gray - dort', 'john mardon', '35944', '59.95'], ['2002', 'the william lawrence', 'bonnie ross', 'included in the gray - dort', '59.95'], ['2002', 'd - 10 locomotive', 'dan fell', 'included in the gray - dort', '59.95'], ['2003', 'hmcs bras dor', 'don curley', '31997', '59.95'], ['2003', 'cnr fa - 1 diesel electric', 'john mardon', 'included in hmcs bras dor', '59.95'], ['2003', 'bricklin sv - 1', 'brian hughes', 'included in hmcs bras dor', '59.95']]
|
xavier malisse
|
https://en.wikipedia.org/wiki/Xavier_Malisse
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1551805-6.html.csv
|
unique
|
the 11 october game was the only game xavier malisse competed in that was played on a carpet surface .
|
{'scope': 'all', 'row': '6', 'col': '3', 'col_other': '2', 'criterion': 'equal', 'value': 'carpet', 'subset': None}
|
{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'surface', 'carpet'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose surface record fuzzily matches to carpet .', 'tostr': 'filter_eq { all_rows ; surface ; carpet }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; surface ; carpet } }', 'tointer': 'select the rows whose surface record fuzzily matches to carpet . 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', 'carpet'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose surface record fuzzily matches to carpet .', 'tostr': 'filter_eq { all_rows ; surface ; carpet }'}, 'year'], 'result': '11 october 2004', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; surface ; carpet } ; year }'}, '11 october 2004'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; surface ; carpet } ; year } ; 11 october 2004 }', 'tointer': 'the year record of this unqiue row is 11 october 2004 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; surface ; carpet } } ; eq { hop { filter_eq { all_rows ; surface ; carpet } ; year } ; 11 october 2004 } } = true', 'tointer': 'select the rows whose surface record fuzzily matches to carpet . there is only one such row in the table . the year record of this unqiue row is 11 october 2004 .'}
|
and { only { filter_eq { all_rows ; surface ; carpet } } ; eq { hop { filter_eq { all_rows ; surface ; carpet } ; year } ; 11 october 2004 } } = true
|
select the rows whose surface record fuzzily matches to carpet . there is only one such row in the table . the year record of this unqiue row is 11 october 2004 .
|
6
|
5
|
{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'surface_7': 7, 'carpet_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'year_9': 9, '11 october 2004_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', 'carpet_8': 'carpet', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'year_9': 'year', '11 october 2004_10': '11 october 2004'}
|
{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'surface_7': [0], 'carpet_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'year_9': [2], '11 october 2004_10': [3]}
|
['outcome', 'year', 'surface', 'opponent', 'score']
|
[['runner - up', '2 november 1998', 'clay', 'jiří novák', '3 - 6 , 3 - 6'], ['runner - up', '10 may 1999', 'clay', 'lleyton hewitt', '4 - 6 , 7 - 6 ( 7 - 2 ) , 1 - 6'], ['runner - up', '12 march 2001', 'hard', 'jan - michael gambill', '5 - 7 , 4 - 6'], ['runner - up', '30 april 2001', 'clay', 'andy roddick', '2 - 6 , 4 - 6'], ['runner - up', '24 may 2004', 'clay', 'filippo volandri', '1 - 6 , 4 - 6'], ['runner - up', '11 october 2004', 'carpet', 'robin söderling', '2 - 6 , 6 - 3 , 4 - 6'], ['winner', '31 january 2005', 'hard', 'jiří novák', '7 - 6 ( 8 - 6 ) , 6 - 2'], ['runner - up', '9 january 2006', 'hard', 'florent serra', '3 - 6 , 4 - 6'], ['runner - up', '6 february 2006', 'hard', 'tommy haas', '3 - 6 , 6 - 3 , 6 - 7 ( 5 - 7 )'], ['winner', '1 january 2007', 'hard', 'stefan koubek', '6 - 1 , 6 - 3'], ['winner', '28 january 2007', 'hard', 'james blake', '5 - 7 , 6 - 4 , 6 - 4'], ['runner - up', '11 january 2011', 'hard', 'stanislas wawrinka', '5 - 7 , 6 - 4 , 1 - 6']]
|
within these walls
|
https://en.wikipedia.org/wiki/Within_These_Walls
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2582519-6.html.csv
|
comparative
|
of the episodes of within these walls , the episode titled " new girls " aired 7 days after the episode titled " freedom . " .
|
{'row_1': '10', 'row_2': '9', 'col': '6', 'col_other': '3', 'relation': 'greater', 'record_mentioned': 'yes', 'diff_result': None}
|
{'func': 'and', 'args': [{'func': 'greater', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'title', 'new girls'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose title record fuzzily matches to new girls .', 'tostr': 'filter_eq { all_rows ; title ; new girls }'}, 'original airdate'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; title ; new girls } ; original airdate }', 'tointer': 'select the rows whose title record fuzzily matches to new girls . take the original airdate record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'title', 'freedom'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose title record fuzzily matches to freedom .', 'tostr': 'filter_eq { all_rows ; title ; freedom }'}, 'original airdate'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; title ; freedom } ; original airdate }', 'tointer': 'select the rows whose title record fuzzily matches to freedom . take the original airdate record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; title ; new girls } ; original airdate } ; hop { filter_eq { all_rows ; title ; freedom } ; original airdate } }', 'tointer': 'select the rows whose title record fuzzily matches to new girls . take the original airdate record of this row . select the rows whose title record fuzzily matches to freedom . take the original airdate record of this row . the first record is greater than the second record .'}, {'func': 'and', 'args': [{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'title', 'new girls'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose title record fuzzily matches to new girls .', 'tostr': 'filter_eq { all_rows ; title ; new girls }'}, 'original airdate'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; title ; new girls } ; original airdate }', 'tointer': 'select the rows whose title record fuzzily matches to new girls . take the original airdate record of this row .'}, '25 march 1978'], 'result': True, 'ind': 5, 'tostr': 'eq { hop { filter_eq { all_rows ; title ; new girls } ; original airdate } ; 25 march 1978 }', 'tointer': 'the original airdate record of the first row is 25 march 1978 .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'title', 'freedom'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose title record fuzzily matches to freedom .', 'tostr': 'filter_eq { all_rows ; title ; freedom }'}, 'original airdate'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; title ; freedom } ; original airdate }', 'tointer': 'select the rows whose title record fuzzily matches to freedom . take the original airdate record of this row .'}, '18 march 1978'], 'result': True, 'ind': 6, 'tostr': 'eq { hop { filter_eq { all_rows ; title ; freedom } ; original airdate } ; 18 march 1978 }', 'tointer': 'the original airdate record of the second row is 18 march 1978 .'}], 'result': True, 'ind': 7, 'tostr': 'and { eq { hop { filter_eq { all_rows ; title ; new girls } ; original airdate } ; 25 march 1978 } ; eq { hop { filter_eq { all_rows ; title ; freedom } ; original airdate } ; 18 march 1978 } }', 'tointer': 'the original airdate record of the first row is 25 march 1978 . the original airdate record of the second row is 18 march 1978 .'}], 'result': True, 'ind': 8, 'tostr': 'and { greater { hop { filter_eq { all_rows ; title ; new girls } ; original airdate } ; hop { filter_eq { all_rows ; title ; freedom } ; original airdate } } ; and { eq { hop { filter_eq { all_rows ; title ; new girls } ; original airdate } ; 25 march 1978 } ; eq { hop { filter_eq { all_rows ; title ; freedom } ; original airdate } ; 18 march 1978 } } } = true', 'tointer': 'select the rows whose title record fuzzily matches to new girls . take the original airdate record of this row . select the rows whose title record fuzzily matches to freedom . take the original airdate record of this row . the first record is greater than the second record . the original airdate record of the first row is 25 march 1978 . the original airdate record of the second row is 18 march 1978 .'}
|
and { greater { hop { filter_eq { all_rows ; title ; new girls } ; original airdate } ; hop { filter_eq { all_rows ; title ; freedom } ; original airdate } } ; and { eq { hop { filter_eq { all_rows ; title ; new girls } ; original airdate } ; 25 march 1978 } ; eq { hop { filter_eq { all_rows ; title ; freedom } ; original airdate } ; 18 march 1978 } } } = true
|
select the rows whose title record fuzzily matches to new girls . take the original airdate record of this row . select the rows whose title record fuzzily matches to freedom . take the original airdate record of this row . the first record is greater than the second record . the original airdate record of the first row is 25 march 1978 . the original airdate record of the second row is 18 march 1978 .
|
13
|
9
|
{'and_8': 8, 'result_9': 9, 'greater_4': 4, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_10': 10, 'title_11': 11, 'new girls_12': 12, 'original airdate_13': 13, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_14': 14, 'title_15': 15, 'freedom_16': 16, 'original airdate_17': 17, 'and_7': 7, 'str_eq_5': 5, '25 march 1978_18': 18, 'str_eq_6': 6, '18 march 1978_19': 19}
|
{'and_8': 'and', 'result_9': 'true', 'greater_4': 'greater', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_10': 'all_rows', 'title_11': 'title', 'new girls_12': 'new girls', 'original airdate_13': 'original airdate', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_14': 'all_rows', 'title_15': 'title', 'freedom_16': 'freedom', 'original airdate_17': 'original airdate', 'and_7': 'and', 'str_eq_5': 'str_eq', '25 march 1978_18': '25 march 1978', 'str_eq_6': 'str_eq', '18 march 1978_19': '18 march 1978'}
|
{'and_8': [9], 'result_9': [], 'greater_4': [8], 'str_hop_2': [4, 5], 'filter_str_eq_0': [2], 'all_rows_10': [0], 'title_11': [0], 'new girls_12': [0], 'original airdate_13': [2], 'str_hop_3': [4, 6], 'filter_str_eq_1': [3], 'all_rows_14': [1], 'title_15': [1], 'freedom_16': [1], 'original airdate_17': [3], 'and_7': [8], 'str_eq_5': [7], '25 march 1978_18': [5], 'str_eq_6': [7], '18 march 1978_19': [6]}
|
['total', 'series', 'title', 'director', 'writer ( s )', 'original airdate']
|
[['60', '1', 'mixer', 'christopher hodson', 'david butler', '21 january 1978'], ['61', '2', 'arrivals , departures', 'paul annett', 'david butler', '28 january 1978'], ['62', '3', 'raft', 'christphoer hodson', 'pj hammond', '4 february 1978'], ['63', '4', 'public opinion', 'marek kanievska', 'mona bruce and robert james', '11 february 1978'], ['64', '5', 'sisters', 'john gorrie', 'john gorrie', '18 february 1978'], ['65', '6', 'love me , love my bear', 'bryan izzard', 'terence feely', '25 february 1978'], ['66', '7', 'the inquest', 'bryan izzard', 'tony hoare', '4 march 1978'], ['67', '8', 'the governor', 'marek kanievska', 'susan pleat', '11 march 1978'], ['68', '9', 'freedom', 'tony wharmby', 'tony parker', '18 march 1978'], ['69', '10', 'new girls', 'michael e briant', 'kathleen j smith', '25 march 1978'], ['70', '11', 'one for the road', 'peter moffatt', 'peter wildeblood', '1 april 1978'], ['71', '12', 'nemesis', 'christopher hodson', 'mona bruce and robert james', '8 april 1978'], ['72', '13', 'is there anyone there', 'john gorrie', 'david butler', '15 april 1978']]
|
1978 houston oilers season
|
https://en.wikipedia.org/wiki/1978_Houston_Oilers_season
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15984957-2.html.csv
|
majority
|
the houston oilers won the majority of games during the 1978 season .
|
{'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]}
|
['game', 'date', 'opponent', 'result', 'oilers points', 'opponents', 'oilers first downs', 'record', 'attendance']
|
[['1', 'sept 3', 'atlanta falcons', 'loss', '14', '20', '13', '0 - 1', '57328'], ['2', 'sept 10', 'kansas city chiefs', 'win', '20', '17', '15', '1 - 1', '40213'], ['3', 'sept 17', 'san francisco 49ers', 'win', '20', '19', '23', '2 - 1', '46161'], ['4', 'sept 24', 'los angeles rams', 'loss', '6', '10', '10', '2 - 2', '45749'], ['5', 'oct 1', 'cleveland browns', 'win', '16', '13', '20', '3 - 2', '72776'], ['6', 'oct 8', 'oakland raiders', 'loss', '17', '21', '20', '3 - 3', '52550'], ['7', 'oct 15', 'buffalo bills', 'win', '17', '10', '17', '4 - 3', '47727'], ['8', 'oct 23', 'pittsburgh steelers', 'win', '24', '17', '22', '5 - 3', '48021'], ['9', 'oct 29', 'cincinnati bengals', 'loss', '13', '28', '15', '5 - 4', '50532'], ['10', 'nov 5', 'cleveland browns', 'win', '14', '10', '18', '6 - 4', '45827'], ['11', 'nov 12', 'new england patriots', 'win', '26', '23', '24', '7 - 4', '60356'], ['12', 'nov 20', 'miami dolphins', 'win', '35', '30', '23', '8 - 4', '50290'], ['13', 'nov 26', 'cincinnati bengals', 'win', '17', '10', '17', '9 - 4', '43245'], ['14', 'dec 3', 'pittsburgh steelers', 'loss', '3', '13', '9', '9 - 5', '54261'], ['15', 'dec 10', 'new orleans saints', 'win', '17', '12', '16', '10 - 5', '63169'], ['16', 'dec 17', 'san diego chargers', 'loss', '24', '45', '14', '10 - 6', '49554']]
|
henlopen conference
|
https://en.wikipedia.org/wiki/Henlopen_Conference
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13054553-5.html.csv
|
majority
|
the majority of teams in the henlopen conference failed to make the playoffs .
|
{'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'failed to make playoffs', 'subset': None}
|
{'func': 'most_str_eq', 'args': ['all_rows', 'season outcome', 'failed to make playoffs'], 'result': True, 'ind': 0, 'tointer': 'for the season outcome records of all rows , most of them fuzzily match to failed to make playoffs .', 'tostr': 'most_eq { all_rows ; season outcome ; failed to make playoffs } = true'}
|
most_eq { all_rows ; season outcome ; failed to make playoffs } = true
|
for the season outcome records of all rows , most of them fuzzily match to failed to make playoffs .
|
1
|
1
|
{'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'season outcome_3': 3, 'failed to make playoffs_4': 4}
|
{'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'season outcome_3': 'season outcome', 'failed to make playoffs_4': 'failed to make playoffs'}
|
{'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'season outcome_3': [0], 'failed to make playoffs_4': [0]}
|
['school', 'team', 'division record', 'overall record', 'season outcome']
|
[['dover', 'senators', '5 - 0', '8 - 3', 'loss in first round of div i playoffs'], ['caesar rodney', 'riders', '3 - 2', '4 - 6', 'failed to make playoffs'], ['sussex central', 'golden knights', '2 - 3', '6 - 5', 'loss in first round of div i playoffs'], ['sussex tech', 'ravens', '2 - 3', '5 - 5', 'failed to make playoffs'], ['cape henlopen', 'vikings', '2 - 3', '4 - 6', 'failed to make playoffs'], ['milford', 'buccaneers', '1 - 4', '4 - 6', 'failed to make playoffs']]
|
mike di meglio
|
https://en.wikipedia.org/wiki/Mike_Di_Meglio
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16678131-2.html.csv
|
count
|
there were 4 years when mike di meglio had 16 races .
|
{'scope': 'all', 'criterion': 'equal', 'value': '16', 'result': '4', 'col': '2', 'subset': None}
|
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'races', '16'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose races record is equal to 16 .', 'tostr': 'filter_eq { all_rows ; races ; 16 }'}], 'result': '4', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; races ; 16 } }', 'tointer': 'select the rows whose races record is equal to 16 . the number of such rows is 4 .'}, '4'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; races ; 16 } } ; 4 } = true', 'tointer': 'select the rows whose races record is equal to 16 . the number of such rows is 4 .'}
|
eq { count { filter_eq { all_rows ; races ; 16 } } ; 4 } = true
|
select the rows whose races record is equal to 16 . the number of such rows is 4 .
|
3
|
3
|
{'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_eq_0': 0, 'all_rows_4': 4, 'races_5': 5, '16_6': 6, '4_7': 7}
|
{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'races_5': 'races', '16_6': '16', '4_7': '4'}
|
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'races_5': [0], '16_6': [0], '4_7': [2]}
|
['season', 'races', 'wins', 'podiums', 'poles', 'fastest laps']
|
[['2003', '10', '0', '0', '0', '0'], ['2003', '5', '0', '0', '0', '0'], ['2004', '14', '0', '0', '0', '0'], ['2005', '16', '1', '2', '0', '0'], ['2006', '14', '0', '0', '0', '0'], ['2007', '15', '0', '0', '0', '0'], ['2008', '17', '4', '9', '2', '4'], ['2009', '16', '0', '2', '1', '0'], ['2010', '16', '0', '0', '0', '0'], ['2011', '17', '0', '0', '0', '0'], ['2012', '16', '0', '0', '0', '0'], ['2013', '10', '0', '0', '0', '0'], ['total', '166', '5', '13', '3', '4']]
|
list of tallest buildings in kansas city , missouri
|
https://en.wikipedia.org/wiki/List_of_tallest_buildings_in_Kansas_City%2C_Missouri
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12815540-4.html.csv
|
ordinal
|
the building located at 1111 main street has the 3rd highest number of floors among the tallest buildings in kansas city , missouri .
|
{'row': '8', 'col': '5', 'order': '3', 'col_other': '2', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None}
|
{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'floors', '3'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; floors ; 3 }'}, 'street address'], 'result': '1111 main street', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; floors ; 3 } ; street address }'}, '1111 main street'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; floors ; 3 } ; street address } ; 1111 main street } = true', 'tointer': 'select the row whose floors record of all rows is 3rd maximum . the street address record of this row is 1111 main street .'}
|
eq { hop { nth_argmax { all_rows ; floors ; 3 } ; street address } ; 1111 main street } = true
|
select the row whose floors record of all rows is 3rd maximum . the street address record of this row is 1111 main street .
|
3
|
3
|
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'floors_5': 5, '3_6': 6, 'street address_7': 7, '1111 main street_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', 'floors_5': 'floors', '3_6': '3', 'street address_7': 'street address', '1111 main street_8': '1111 main street'}
|
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'floors_5': [0], '3_6': [0], 'street address_7': [1], '1111 main street_8': [2]}
|
['name', 'street address', 'years as tallest', 'height feet / m', 'floors']
|
[['new york life insurance building', '20 w ninth street', '1890 - 1906', '180 / 55', '12'], ['commerce trust building', '922 walnut street', '1906 - 1921', '258 / 79', '17'], ['historic federal reserve bank', '925 grand avenue', '1921 - 1929', '298 / 91', '16'], ['oak tower', '324 e 11th street', '1929 - 1931', '379 / 116', '28'], ['kansas city power and light building', '1330 baltimore street', '1931 - 1977', '476 / 145', '34'], ['2345 grand ( formerly ibm plaza )', '2345 grand avenue', '1977 - 1980', '477 / 145', '28'], ['sheraton kansas city hotel at crown center', '2345 mcgee street', '1980 - 1986', '504 / 154', '40'], ['town pavilion', '1111 main street', '1986 - 1988', '591 / 180', '38'], ['one kansas city place', '1200 main street', '1988 - present', '624 / 198', '42']]
|
2006 african swimming championships
|
https://en.wikipedia.org/wiki/2006_African_Swimming_Championships
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13023411-1.html.csv
|
aggregation
|
the total number of gold medals won by the top 5 countries in the medal table at the 2006 african swimming championships is 42 .
|
{'scope': 'subset', 'col': '3', 'type': 'sum', 'result': '42', 'subset': {'col': '1', 'criterion': 'less_than', 'value': '6'}}
|
{'func': 'round_eq', 'args': [{'func': 'sum', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'rank', '6'], 'result': None, 'ind': 0, 'tostr': 'filter_less { all_rows ; rank ; 6 }', 'tointer': 'select the rows whose rank record is less than 6 .'}, 'gold'], 'result': '42', 'ind': 1, 'tostr': 'sum { filter_less { all_rows ; rank ; 6 } ; gold }'}, '42'], 'result': True, 'ind': 2, 'tostr': 'round_eq { sum { filter_less { all_rows ; rank ; 6 } ; gold } ; 42 } = true', 'tointer': 'select the rows whose rank record is less than 6 . the sum of the gold record of these rows is 42 .'}
|
round_eq { sum { filter_less { all_rows ; rank ; 6 } ; gold } ; 42 } = true
|
select the rows whose rank record is less than 6 . the sum of the gold record of these rows is 42 .
|
3
|
3
|
{'eq_2': 2, 'result_3': 3, 'sum_1': 1, 'filter_less_0': 0, 'all_rows_4': 4, 'rank_5': 5, '6_6': 6, 'gold_7': 7, '42_8': 8}
|
{'eq_2': 'eq', 'result_3': 'true', 'sum_1': 'sum', 'filter_less_0': 'filter_less', 'all_rows_4': 'all_rows', 'rank_5': 'rank', '6_6': '6', 'gold_7': 'gold', '42_8': '42'}
|
{'eq_2': [3], 'result_3': [], 'sum_1': [2], 'filter_less_0': [1], 'all_rows_4': [0], 'rank_5': [0], '6_6': [0], 'gold_7': [1], '42_8': [2]}
|
['rank', 'nation', 'gold', 'silver', 'bronze', 'total']
|
[['1', 'south africa', '20', '10', '9', '39'], ['2', 'algeria', '8', '9', '8', '25'], ['3', 'tunisia', '5', '10', '5', '20'], ['4', 'kenya', '4', '4', '1', '9'], ['5', 'egypt', '2', '4', '7', '13'], ['6', 'seychelles', '1', '1', '3', '5'], ['7', 'senegal', '0', '1', '2', '3'], ['7', 'morocco', '0', '1', '2', '3'], ['9', 'zimbabwe', '0', '0', '3', '3'], ['total', 'total', '40', '40', '40', '120']]
|
gardline group
|
https://en.wikipedia.org/wiki/Gardline_group
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-28132970-5.html.csv
|
aggregation
|
the gardline group 's windfarm support vessels have an average max speed of 29 knots .
|
{'scope': 'all', 'col': '3', 'type': 'average', 'result': '29', 'subset': None}
|
{'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'max speed'], 'result': '29', 'ind': 0, 'tostr': 'avg { all_rows ; max speed }'}, '29'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; max speed } ; 29 } = true', 'tointer': 'the average of the max speed record of all rows is 29 .'}
|
round_eq { avg { all_rows ; max speed } ; 29 } = true
|
the average of the max speed record of all rows is 29 .
|
2
|
2
|
{'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'max speed_4': 4, '29_5': 5}
|
{'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'max speed_4': 'max speed', '29_5': '29'}
|
{'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'max speed_4': [0], '29_5': [1]}
|
['vessel', 'built', 'max speed', 'length', 'breadth', 'flag', 'propulsion']
|
[['gallion', '2010', '30 knots', '20 m', '6.5 m', 'united kingdom', 'prop'], ['gardian 1', '2010', '30 knots', '20 m', '6.5 m', 'united kingdom', 'prop'], ['gardian 2', '2010', '30 knots', '20 m', '6.5 m', 'united kingdom', 'prop'], ['gardian 7', '2010', '30 knots', '20 m', '6.5 m', 'united kingdom', 'prop'], ['gardian 9', '2010', '30 knots', '20 m', '6.5 m', 'united kingdom', 'prop'], ['marianarray', '2011', '26 knots', '17 m', '6 m', 'united kingdom', 'jet'], ['smeaton array', '2011', '30 knots', '20 m', '6 m', 'united kingdom', 'controllable pitch propeller']]
|
list of intel core i7 microprocessors
|
https://en.wikipedia.org/wiki/List_of_Intel_Core_i7_microprocessors
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18823880-15.html.csv
|
unique
|
the only intel core i7 microprocessor with a 8mb l3 cache to have a 3 ghz frequency is the core i7 - 3940xm .
|
{'scope': 'subset', 'row': '11', 'col': '4', 'col_other': '1', 'criterion': 'equal', 'value': '3 ghz', 'subset': {'col': '7', 'criterion': 'equal', 'value': '8 mb'}}
|
{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'l3 cache', '8 mb'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; l3 cache ; 8 mb }', 'tointer': 'select the rows whose l3 cache record fuzzily matches to 8 mb .'}, 'frequency', '3 ghz'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose l3 cache record fuzzily matches to 8 mb . among these rows , select the rows whose frequency record fuzzily matches to 3 ghz .', 'tostr': 'filter_eq { filter_eq { all_rows ; l3 cache ; 8 mb } ; frequency ; 3 ghz }'}], 'result': True, 'ind': 2, 'tostr': 'only { filter_eq { filter_eq { all_rows ; l3 cache ; 8 mb } ; frequency ; 3 ghz } }', 'tointer': 'select the rows whose l3 cache record fuzzily matches to 8 mb . among these rows , select the rows whose frequency record fuzzily matches to 3 ghz . 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', 'l3 cache', '8 mb'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; l3 cache ; 8 mb }', 'tointer': 'select the rows whose l3 cache record fuzzily matches to 8 mb .'}, 'frequency', '3 ghz'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose l3 cache record fuzzily matches to 8 mb . among these rows , select the rows whose frequency record fuzzily matches to 3 ghz .', 'tostr': 'filter_eq { filter_eq { all_rows ; l3 cache ; 8 mb } ; frequency ; 3 ghz }'}, 'model number'], 'result': 'core i7 - 3940xm', 'ind': 3, 'tostr': 'hop { filter_eq { filter_eq { all_rows ; l3 cache ; 8 mb } ; frequency ; 3 ghz } ; model number }'}, 'core i7 - 3940xm'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { filter_eq { filter_eq { all_rows ; l3 cache ; 8 mb } ; frequency ; 3 ghz } ; model number } ; core i7 - 3940xm }', 'tointer': 'the model number record of this unqiue row is core i7 - 3940xm .'}], 'result': True, 'ind': 5, 'tostr': 'and { only { filter_eq { filter_eq { all_rows ; l3 cache ; 8 mb } ; frequency ; 3 ghz } } ; eq { hop { filter_eq { filter_eq { all_rows ; l3 cache ; 8 mb } ; frequency ; 3 ghz } ; model number } ; core i7 - 3940xm } } = true', 'tointer': 'select the rows whose l3 cache record fuzzily matches to 8 mb . among these rows , select the rows whose frequency record fuzzily matches to 3 ghz . there is only one such row in the table . the model number record of this unqiue row is core i7 - 3940xm .'}
|
and { only { filter_eq { filter_eq { all_rows ; l3 cache ; 8 mb } ; frequency ; 3 ghz } } ; eq { hop { filter_eq { filter_eq { all_rows ; l3 cache ; 8 mb } ; frequency ; 3 ghz } ; model number } ; core i7 - 3940xm } } = true
|
select the rows whose l3 cache record fuzzily matches to 8 mb . among these rows , select the rows whose frequency record fuzzily matches to 3 ghz . there is only one such row in the table . the model number record of this unqiue row is core i7 - 3940xm .
|
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, 'l3 cache_8': 8, '8 mb_9': 9, 'frequency_10': 10, '3 ghz_11': 11, 'str_eq_4': 4, 'str_hop_3': 3, 'model number_12': 12, 'core i7 - 3940xm_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', 'l3 cache_8': 'l3 cache', '8 mb_9': '8 mb', 'frequency_10': 'frequency', '3 ghz_11': '3 ghz', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'model number_12': 'model number', 'core i7 - 3940xm_13': 'core i7 - 3940xm'}
|
{'and_5': [6], 'result_6': [], 'only_2': [5], 'filter_str_eq_1': [2, 3], 'filter_str_eq_0': [1], 'all_rows_7': [0], 'l3 cache_8': [0], '8 mb_9': [0], 'frequency_10': [1], '3 ghz_11': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'model number_12': [3], 'core i7 - 3940xm_13': [4]}
|
['model number', 'sspec number', 'cores', 'frequency', 'turbo', 'l2 cache', 'l3 cache', 'gpu model', 'gpu frequency', 'socket', 'i / o bus', 'release date', 'part number ( s )', 'release price ( usd )']
|
[['standard power', 'standard power', 'standard power', 'standard power', 'standard power', 'standard power', 'standard power', 'standard power', 'standard power', 'standard power', 'standard power', 'standard power', 'standard power', 'standard power'], ['core i7 - 3610qm', 'sr0 mn ( e1 )', '4', '2.3 ghz', '8 / 8 / 9 / 10', '4 256 kb', '6 mb', 'hd graphics 4000', '650 - 1100 mhz', 'socketg2', 'dmi 2.0', 'april 2012', 'aw8063801013511', '378'], ['core i7 - 3615qm', 'sr0 mp ( e1 )', '4', '2.3 ghz', '8 / 8 / 9 / 10', '4 256 kb', '6 mb', 'hd graphics 4000', '650 - 1200 mhz', 'bga - 1224', 'dmi 2.0', 'april 2012', 'av8063801013612', '378'], ['core i7 - 3630qm', 'sr0ux ( e1 )', '4', '2.4 ghz', '8 / 8 / 9 / 10', '4 256 kb', '6 mb', 'hd graphics 4000', '650 - 1150 mhz', 'socket g2', 'dmi 2.0', 'september 2012', 'aw8063801106200', '378'], ['core i7 - 3635qm', 'sr0uy ( e1 )', '4', '2.4 ghz', '8 / 8 / 9 / 10', '4 256 kb', '6 mb', 'hd graphics 4000', '650 - 1200 mhz', 'bga - 1224', 'dmi 2.0', 'september 2012', 'av8063801106500', '378'], ['core i7 - 3720qm', 'sr0 ml ( e1 ) sr0 mm ( e1 )', '4', '2.6 ghz', '8 / 8 / 9 / 10', '4 256 kb', '6 mb', 'hd graphics 4000', '650 - 1250 mhz', 'socket g2bga - 1224', 'dmi 2.0', 'april 2012', 'aw8063801013116av8063801013210', '378'], ['core i7 - 3740qm', 'sr0uv ( e1 ) sr0uw ( e1 )', '4', '2.7 ghz', '8 / 8 / 9 / 10', '4 256 kb', '6 mb', 'hd graphics 4000', '650 - 1300 mhz', 'socket g2bga - 1224', 'dmi 2.0', 'september 2012', 'aw8063801105000bx80638i73740qmav8063801105300', '378'], ['core i7 - 3820qm', 'sr0 mj ( e1 ) sr0 mk ( e1 )', '4', '2.7 ghz', '8 / 8 / 9 / 10', '4 256 kb', '8 mb', 'hd graphics 4000', '650 - 1250 mhz', 'socket g2bga - 1224', 'dmi 2.0', 'april 2012', 'aw8063801012708av8063801012807', '568'], ['core i7 - 3840qm', 'sr0ut ( e1 ) sr0uu ( e1 )', '4', '2.8 ghz', '8 / 8 / 9 / 10', '4 256 kb', '8 mb', 'hd graphics 4000', '650 - 1300 mhz', 'socket g2bga - 1224', 'dmi 2.0', 'september 2012', 'aw8063801103800bx80638i73840qmav8063801104100', '568'], ['core i7 - 3920xm', 'sr0 mh ( e1 ) sr0t2 ( e1 )', '4', '2.9 ghz', '7 / 7 / 8 / 9', '4 256 kb', '8 mb', 'hd graphics 4000', '650 - 1300 mhz', 'socket g2', 'dmi 2.0', 'april 2012', 'aw8063801009606aw8063801009607', '1096'], ['core i7 - 3940xm', 'sr0us ( e1 )', '4', '3 ghz', '7 / 7 / 8 / 9', '4 256 kb', '8 mb', 'hd graphics 4000', '650 - 1350 mhz', 'socket g2', 'dmi 2.0', 'september 2012', 'aw8063801103501', '1096'], ['standard power , embedded', 'standard power , embedded', 'standard power , embedded', 'standard power , embedded', 'standard power , embedded', 'standard power , embedded', 'standard power , embedded', 'standard power , embedded', 'standard power , embedded', 'standard power , embedded', 'standard power , embedded', 'standard power , embedded', 'standard power , embedded', 'standard power , embedded'], ['core i7 - 3610qe', 'sr0np ( e1 )', '4', '2.3 ghz', '8 / 8 / 9 / 10', '4 256 kb', '6 mb', 'hd graphics 4000', '650 - 1000 mhz', 'socket g2', 'dmi 2.0', 'april 2012', 'aw8063801118306', '393'], ['core i7 - 3615qe', 'sr0nc ( e1 )', '4', '2.3 ghz', '8 / 8 / 9 / 10', '4 256 kb', '6 mb', 'hd graphics 4000', '650 - 1000 mhz', 'bga - 1023', 'dmi 2.0', 'april 2012', 'av8063801117503', '393'], ['low power', 'low power', 'low power', 'low power', 'low power', 'low power', 'low power', 'low power', 'low power', 'low power', 'low power', 'low power', 'low power', 'low power'], ['core i7 - 3612qm', 'sr0 mq ( e1 ) sr0 mr ( e1 )', '4', '2.1 ghz', '7 / 7 / 9 / 10', '4 256 kb', '6 mb', 'hd graphics 4000', '650 - 1100 mhz', 'socket g2bga - 1224', 'dmi 2.0', 'april 2012', 'av8063801130504av8063801130704', '378'], ['core i7 - 3632qm', 'sr0v0 ( e1 ) sr0uz ( e1 )', '4', '2.2 ghz', '7 / 7 / 9 / 10', '4 256 kb', '6 mb', 'hd graphics 4000', '650 - 1150 mhz', 'socket g2bga - 1224', 'dmi 2.0', 'october 2012', 'aw8063801152800av8063801152700', '378'], ['low power , embedded', 'low power , embedded', 'low power , embedded', 'low power , embedded', 'low power , embedded', 'low power , embedded', 'low power , embedded', 'low power , embedded', 'low power , embedded', 'low power , embedded', 'low power , embedded', 'low power , embedded', 'low power , embedded', 'low power , embedded'], ['core i7 - 3612qe', 'sr0nd ( e1 )', '4', '2.1 ghz', '7 / 7 / 9 / 10', '4 256 kb', '6 mb', 'hd graphics 4000', '650 - 1000 mhz', 'bga - 1023', 'dmi 2.0', 'april 2012', 'av8063801149203', '426']]
|
usa today all - usa high school baseball team
|
https://en.wikipedia.org/wiki/USA_Today_All-USA_high_school_baseball_team
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-11677100-17.html.csv
|
majority
|
the majority of players on the usa today all - usa school baseball team were picked in the mlb draft .
|
{'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': 'draft', 'subset': None}
|
{'func': 'most_str_eq', 'args': ['all_rows', 'mlb draft', 'draft'], 'result': True, 'ind': 0, 'tointer': 'for the mlb draft records of all rows , most of them fuzzily match to draft .', 'tostr': 'most_eq { all_rows ; mlb draft ; draft } = true'}
|
most_eq { all_rows ; mlb draft ; draft } = true
|
for the mlb draft records of all rows , most of them fuzzily match to draft .
|
1
|
1
|
{'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'mlb draft_3': 3, 'draft_4': 4}
|
{'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'mlb draft_3': 'mlb draft', 'draft_4': 'draft'}
|
{'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'mlb draft_3': [0], 'draft_4': [0]}
|
['player', 'position', 'school', 'hometown', 'mlb draft']
|
[['dylan bundy', 'pitcher / infielder', 'owasso high school', 'owasso , ok', '1st round - 4th pick of 2010 draft ( rangers )'], ['kevin cron', 'catcher / pitcher', 'mountain pointe high school', 'phoenix , az', 'attended tcu'], ['francisco lindor', 'infielder', 'montverde academy', 'montverde , fl', '1st round - 9th pick of 2011 draft ( indians )'], ['trevor mitsui', 'infielder', 'shorewood high school', 'shoreline , wa', 'attended washington'], ['josh bell', 'outfielder', 'jesuit college preparatory school', 'dallas , tx', '2nd round - 61st pick of 2011 draft ( pirates )'], ['bubba starling', 'outfielder', 'gardner edgerton high school', 'gardner , ks', '1st round - 5th pick of 2011 draft ( royals )'], ['blake swihart', 'catcher', 'cleveland high school', 'rio rancho , nm', '1st round - 26th pick of 2011 draft ( red sox )']]
|
list of england national rugby union team results 1980 - 89
|
https://en.wikipedia.org/wiki/List_of_England_national_rugby_union_team_results_1980%E2%80%9389
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18178608-2.html.csv
|
count
|
england 's national rugby union team played against two different opposing teams in the venue of twickenham , london .
|
{'scope': 'all', 'criterion': 'equal', 'value': 'twickenham , london', 'result': '2', 'col': '4', 'subset': None}
|
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'venue', 'twickenham , london'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose venue record fuzzily matches to twickenham , london .', 'tostr': 'filter_eq { all_rows ; venue ; twickenham , london }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; venue ; twickenham , london } }', 'tointer': 'select the rows whose venue record fuzzily matches to twickenham , london . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; venue ; twickenham , london } } ; 2 } = true', 'tointer': 'select the rows whose venue record fuzzily matches to twickenham , london . the number of such rows is 2 .'}
|
eq { count { filter_eq { all_rows ; venue ; twickenham , london } } ; 2 } = true
|
select the rows whose venue record fuzzily matches to twickenham , london . 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, 'venue_5': 5, 'twickenham , london_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', 'venue_5': 'venue', 'twickenham , london_6': 'twickenham , london', '2_7': '2'}
|
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'venue_5': [0], 'twickenham , london_6': [0], '2_7': [2]}
|
['opposing teams', 'against', 'date', 'venue', 'status']
|
[['wales', '21', '17 / 01 / 1981', 'cardiff arms park , cardiff', 'five nations'], ['scotland', '17', '21 / 02 / 1981', 'twickenham , london', 'five nations'], ['ireland', '6', '07 / 03 / 1981', 'lansdowne road , dublin', 'five nations'], ['france', '16', '21 / 03 / 1981', 'twickenham , london', 'five nations'], ['argentina', '19', '30 / 05 / 1981', 'ferrocarril stadium , buenos aires', 'first test'], ['argentina', '6', '06 / 06 / 1981', 'ferrocarril stadium , buenos aires', 'second test']]
|
2008 german motorcycle grand prix
|
https://en.wikipedia.org/wiki/2008_German_motorcycle_Grand_Prix
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16878651-1.html.csv
|
majority
|
most of the competitors in the 2008 german motorcycle grand prix completed 30 laps .
|
{'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': '30', 'subset': None}
|
{'func': 'most_eq', 'args': ['all_rows', 'laps', '30'], 'result': True, 'ind': 0, 'tointer': 'for the laps records of all rows , most of them are equal to 30 .', 'tostr': 'most_eq { all_rows ; laps ; 30 } = true'}
|
most_eq { all_rows ; laps ; 30 } = true
|
for the laps records of all rows , most of them are equal to 30 .
|
1
|
1
|
{'most_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'laps_3': 3, '30_4': 4}
|
{'most_eq_0': 'most_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'laps_3': 'laps', '30_4': '30'}
|
{'most_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'laps_3': [0], '30_4': [0]}
|
['rider', 'manufacturer', 'laps', 'time', 'grid']
|
[['casey stoner', 'ducati', '30', '47:30.057', '1'], ['valentino rossi', 'yamaha', '30', '+ 3.708', '7'], ['chris vermeulen', 'suzuki', '30', '+ 14.002', '14'], ['alex de angelis', 'honda', '30', '+ 14.124', '10'], ['andrea dovizioso', 'honda', '30', '+ 42.022', '4'], ['sylvain guintoli', 'ducati', '30', '+ 46.648', '15'], ['loris capirossi', 'suzuki', '30', '+ 1:04.483', '13'], ['randy de puniet', 'honda', '30', '+ 1:04.588', '6'], ['shinya nakano', 'honda', '30', '+ 1:16.773', '9'], ['anthony west', 'kawasaki', '30', '+ 1:29.275', '17'], ['james toseland', 'yamaha', '29', '+ 1 lap', '11'], ['toni elias', 'ducati', '29', '+ 1 lap', '12'], ['nicky hayden', 'honda', '28', '+ 2 laps', '8'], ['colin edwards', 'yamaha', '20', 'accident', '3'], ['marco melandri', 'ducati', '9', 'accident', '16'], ['dani pedrosa', 'honda', '5', 'accident', '2'], ['jorge lorenzo', 'yamaha', '2', 'accident', '5']]
|
2010 - 11 oklahoma city thunder season
|
https://en.wikipedia.org/wiki/2010%E2%80%9311_Oklahoma_City_Thunder_season
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27712702-11.html.csv
|
superlative
|
in the 2010 - 11 oklahoma city thunder season , the highest attendance was on march 16th .
|
{'scope': 'all', 'col_superlative': '8', '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', 'location attendance'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; location attendance }'}, 'date'], 'result': 'march 16', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; location attendance } ; date }'}, 'march 16'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; location attendance } ; date } ; march 16 } = true', 'tointer': 'select the row whose location attendance record of all rows is maximum . the date record of this row is march 16 .'}
|
eq { hop { argmax { all_rows ; location attendance } ; date } ; march 16 } = true
|
select the row whose location attendance record of all rows is maximum . the date record of this row is march 16 .
|
3
|
3
|
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'location attendance_5': 5, 'date_6': 6, 'march 16_7': 7}
|
{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'location attendance_5': 'location attendance', 'date_6': 'date', 'march 16_7': 'march 16'}
|
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'location attendance_5': [0], 'date_6': [1], 'march 16_7': [2]}
|
['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record']
|
[['59', 'march 2', 'indiana', 'w 113 - 89 ( ot )', 'kevin durant , russell westbrook ( 21 )', 'serge ibaka ( 12 )', 'russell westbrook ( 9 )', 'oklahoma city arena 18203', '37 - 22'], ['60', 'march 4', 'atlanta', 'w 111 - 104 ( ot )', 'kevin durant ( 29 )', 'kevin durant ( 8 )', 'russell westbrook ( 9 )', 'philips arena 17916', '38 - 22'], ['61', 'march 6', 'phoenix', 'w 122 - 118 ( ot )', 'russell westbrook ( 32 )', 'nick collison , thabo sefolosha ( 9 )', 'russell westbrook ( 11 )', 'oklahoma city arena 18203', '39 - 22'], ['62', 'march 7', 'memphis', 'l 101 - 107 ( ot )', 'russell westbrook ( 27 )', 'kevin durant , james harden , serge ibaka ( 6 )', 'russell westbrook ( 7 )', 'fedexforum 13903', '39 - 23'], ['63', 'march 9', 'philadelphia', 'w 110 - 105 ( ot )', 'kevin durant ( 34 )', 'kevin durant ( 16 )', 'russell westbrook ( 12 )', 'wells fargo center 19283', '40 - 23'], ['64', 'march 11', 'detroit', 'w 104 - 94 ( ot )', 'kevin durant ( 24 )', 'kevin durant ( 9 )', 'russell westbrook ( 11 )', 'oklahoma city arena 18203', '41 - 23'], ['65', 'march 13', 'cleveland', 'w 95 - 75 ( ot )', 'russell westbrook ( 20 )', 'serge ibaka ( 14 )', 'eric maynor ( 8 )', 'quicken loans arena 19811', '42 - 23'], ['66', 'march 14', 'washington', 'w 116 - 89 ( ot )', 'kevin durant ( 32 )', 'kendrick perkins ( 9 )', 'russell westbrook ( 12 )', 'verizon center 17921', '43 - 23'], ['67', 'march 16', 'miami', 'w 96 - 85 ( ot )', 'kevin durant ( 29 )', 'serge ibaka ( 12 )', 'kevin durant ( 6 )', 'american airlines arena 20083', '44 - 23'], ['68', 'march 18', 'charlotte', 'w 99 - 82 ( ot )', 'kevin durant ( 25 )', 'serge ibaka ( 13 )', 'russell westbrook ( 7 )', 'oklahoma city arena 18203', '45 - 23'], ['70', 'march 23', 'utah', 'w 106 - 94 ( ot )', 'russell westbrook ( 31 )', 'serge ibaka ( 13 )', 'russell westbrook ( 5 )', 'oklahoma city arena 18203', '46 - 24'], ['71', 'march 25', 'minnesota', 'w 111 - 103 ( ot )', 'kevin durant ( 23 )', 'serge ibaka ( 10 )', 'russell westbrook ( 8 )', 'oklahoma city arena 18203', '47 - 24'], ['72', 'march 27', 'portland', 'w 99 - 90 ( ot )', 'russell westbrook ( 28 )', 'kendrick perkins ( 10 )', 'russell westbrook ( 7 )', 'oklahoma city arena 18203', '48 - 24'], ['73', 'march 29', 'golden state', 'w 115 - 114 ( ot )', 'kevin durant ( 39 )', 'kendrick perkins ( 13 )', 'russell westbrook ( 9 )', 'oklahoma city arena 18203', '49 - 24']]
|
new zealand national football team
|
https://en.wikipedia.org/wiki/New_Zealand_national_football_team
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1023035-3.html.csv
|
count
|
5 players in the team 's history scored 10 goals .
|
{'scope': 'all', 'criterion': 'equal', 'value': '10', 'result': '5', 'col': '3', 'subset': None}
|
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'goals', '10'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose goals record is equal to 10 .', 'tostr': 'filter_eq { all_rows ; goals ; 10 }'}], 'result': '5', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; goals ; 10 } }', 'tointer': 'select the rows whose goals record is equal to 10 . the number of such rows is 5 .'}, '5'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; goals ; 10 } } ; 5 } = true', 'tointer': 'select the rows whose goals record is equal to 10 . the number of such rows is 5 .'}
|
eq { count { filter_eq { all_rows ; goals ; 10 } } ; 5 } = true
|
select the rows whose goals record is equal to 10 . the number of such rows is 5 .
|
3
|
3
|
{'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_eq_0': 0, 'all_rows_4': 4, 'goals_5': 5, '10_6': 6, '5_7': 7}
|
{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'goals_5': 'goals', '10_6': '10', '5_7': '5'}
|
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'goals_5': [0], '10_6': [0], '5_7': [2]}
|
['name', 'career', 'goals', 'caps', 'first cap', 'most recent cap']
|
[['vaughan coveny', '1992 - 2006', '28', '64', '7 june 1992', '4 june 2006'], ['shane smeltz', '2003 -', '23', '49', 'united states 9 june 2003', 'new caledonia 21 march 2013'], ['steve sumner', '1976 - 1988', '22', '58', 'burma 13 september 1976', '23 june 1988'], ['brian turner', '1967 - 1982', '21', '59', 'australia 5 november 1967', '23 june 1982'], ['jock newall', '1951 - 1952', '17', '10', 'new caledonia 19 september 1951', 'new caledonia 28 september 1952'], ['keith nelson', '1977 - 1983', '16', '20', 'new caledonia 5 march 1977', '7 june 1983'], ['chris killen', '2000 -', '16', '48', 'tahiti 19 june 2000', '5 september 2013'], ['grant turner', '1980 - 1988', '15', '42', '20 august 1980', '27 march 1988'], ['darren mcclennan', '1986 - 1997', '12', '43', '17 september 1986', '11 june 1997'], ['michael mcgarry', '1986 - 1997', '12', '54', '17 september 1986', 'australia 6 july 1997'], ['wynton rufer', '1980 - 1997', '12', '23', '16 october 1980', 'australia 28 june 1997'], ['steve wooddin', '1980 - 1984', '11', '24', '20 august 1980', '20 october 1984'], ['roy coxon', '1951 - 1952', '10', '8', 'new caledonia 19 september 1951', 'tahiti 28 september 1952'], ['chris jackson', '1995 - 2003', '10', '60', '21 february 1995', '22 june 2003'], ['dave taylor', '1967 - 1981', '10', '47', 'south vietnam 10 november 1967', '12 september 1981'], ['colin walker', '1984 - 1988', '10', '15', '18 october 1984', '23 june 1988'], ['chris wood', '2009 -', '10', '31', '3 june 2009', '5 september 2013']]
|
fiba eurobasket 2007 squads
|
https://en.wikipedia.org/wiki/FIBA_EuroBasket_2007_squads
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12962773-16.html.csv
|
count
|
of the players in the fiba eurobasket 2007 squads , three came from the bot turów club .
|
{'scope': 'all', 'criterion': 'equal', 'value': 'bot turów', 'result': '3', 'col': '5', 'subset': None}
|
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'current club', 'bot turów'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose current club record fuzzily matches to bot turów .', 'tostr': 'filter_eq { all_rows ; current club ; bot turów }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; current club ; bot turów } }', 'tointer': 'select the rows whose current club record fuzzily matches to bot turów . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; current club ; bot turów } } ; 3 } = true', 'tointer': 'select the rows whose current club record fuzzily matches to bot turów . the number of such rows is 3 .'}
|
eq { count { filter_eq { all_rows ; current club ; bot turów } } ; 3 } = true
|
select the rows whose current club record fuzzily matches to bot turów . 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, 'current club_5': 5, 'bot turów_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', 'current club_5': 'current club', 'bot turów_6': 'bot turów', '3_7': '3'}
|
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'current club_5': [0], 'bot turów_6': [0], '3_7': [2]}
|
['player', 'height', 'position', 'year born', 'current club']
|
[['bartłomiej wołoszyn', '1.97', 'forward', '1986', 'anwil wloclawek'], ['andrzej pluta', '1.81', 'guard', '1974', 'anwil wloclawek'], ['robert skibniewski', '1.82', 'guard', '1983', 'bot turów'], ['robert witka', '2.06', 'forward', '1981', 'bot turów'], ['filip dylewicz', '2.02', 'forward', '1980', 'prokom trefl sopot'], ['radosław hyży', '2.00', 'forward', '1977', 'śląsk wrocław'], ['adam wójcik', '2.08', 'forward', '1970', "upea capo d'orlando"], ['kamil pietras', '2.04', 'forward', '1988', 'olimpija ljubljana'], ['szymon szewczyk', '2.09', 'center', '1982', 'lokomotiv rostov'], ['iwo kitzinger', '1.88', 'guard', '1985', 'bot turów'], ['przemysław frasunkiewicz', '2.01', 'forward', '1979', 'energa czarni'], ['łukasz koszarek', '1.87', 'guard', '1984', 'anwil wloclawek']]
|
e. w. scripps company
|
https://en.wikipedia.org/wiki/E._W._Scripps_Company
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1847523-2.html.csv
|
count
|
there were eight different owners of the company in the year 2011 .
|
{'scope': 'all', 'criterion': 'equal', 'value': '2011', 'result': '9', 'col': '4', 'subset': None}
|
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'owned since', '2011'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose owned since record is equal to 2011 .', 'tostr': 'filter_eq { all_rows ; owned since ; 2011 }'}], 'result': '9', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; owned since ; 2011 } }', 'tointer': 'select the rows whose owned since record is equal to 2011 . the number of such rows is 9 .'}, '9'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; owned since ; 2011 } } ; 9 } = true', 'tointer': 'select the rows whose owned since record is equal to 2011 . the number of such rows is 9 .'}
|
eq { count { filter_eq { all_rows ; owned since ; 2011 } } ; 9 } = true
|
select the rows whose owned since record is equal to 2011 . the number of such rows is 9 .
|
3
|
3
|
{'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_eq_0': 0, 'all_rows_4': 4, 'owned since_5': 5, '2011_6': 6, '9_7': 7}
|
{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'owned since_5': 'owned since', '2011_6': '2011', '9_7': '9'}
|
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'owned since_5': [0], '2011_6': [0], '9_7': [2]}
|
['city of license / market', 'station', 'channel ( tv / rf )', 'owned since', 'affiliation']
|
[['phoenix', 'knxv - tv', '15 ( 15 )', '1985', 'abc'], ['bakersfield , california', 'kero - tv', '23 ( 10 )', '2011', 'abc'], ['bakersfield , california', 'kzkc - lp', '42', '2011', 'azteca américa'], ['san diego', 'kgtv', '10 ( 10 )', '2011', 'abc'], ['san diego', 'kzsd - lp', '41', '2011', 'azteca américa'], ['colorado springs , colorado', 'kzks - lp', '23', '2011', 'azteca américa'], ['denver', 'kmgh - tv', '7 ( 7 )', '2011', 'abc'], ['denver', 'kzco - lp', '27', '2011', 'azteca américa'], ['fort collins , colorado', 'kzfc - lp', '36', '2011', 'azteca américa'], ['tampa - st petersburg', 'wfts - tv', '28 ( 29 )', '1986', 'abc'], ['west palm beach', 'wptv', '5 ( 12 )', '1961', 'nbc'], ['indianapolis', 'wrtv', '6 ( 25 )', '2011', 'abc'], ['baltimore', 'wmar - tv', '2 ( 38 )', '1991', 'abc'], ['detroit', 'wxyz - tv', '7 ( 41 )', '1986', 'abc'], ['kansas city , mo - lawrence , ks', 'kshb - tv', '41 ( 42 )', '1977', 'nbc'], ['cincinnati', 'wcpo - tv', '9 ( 22 )', '1949', 'abc'], ['cleveland - akron - canton', 'wews', '5 ( 15 )', '1947', 'abc'], ['tulsa', 'kjrh - tv', '2 ( 8 )', '1971', 'nbc']]
|
list of street railways in canada
|
https://en.wikipedia.org/wiki/List_of_street_railways_in_Canada
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16927321-1.html.csv
|
superlative
|
the edmonton radial railway is the oldest railway that serves canada .
|
{'scope': 'all', 'col_superlative': '4', 'row_superlative': '2', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '1', 'subset': None}
|
{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmin', 'args': ['all_rows', 'date ( from )'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; date ( from ) }'}, 'name of system'], 'result': 'edmonton radial railway', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; date ( from ) } ; name of system }'}, 'edmonton radial railway'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmin { all_rows ; date ( from ) } ; name of system } ; edmonton radial railway } = true', 'tointer': 'select the row whose date ( from ) record of all rows is minimum . the name of system record of this row is edmonton radial railway .'}
|
eq { hop { argmin { all_rows ; date ( from ) } ; name of system } ; edmonton radial railway } = true
|
select the row whose date ( from ) record of all rows is minimum . the name of system record of this row is edmonton radial railway .
|
3
|
3
|
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'date (from)_5': 5, 'name of system_6': 6, 'edmonton radial railway_7': 7}
|
{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'date (from)_5': 'date ( from )', 'name of system_6': 'name of system', 'edmonton radial railway_7': 'edmonton radial railway'}
|
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'date (from)_5': [0], 'name of system_6': [1], 'edmonton radial railway_7': [2]}
|
['name of system', 'location', 'traction type', 'date ( from )', 'date ( to )']
|
[['calgary municipal railway', 'calgary', 'electric', '5 jul 1909 25 may 1981', '29 dec 1950 -'], ['edmonton radial railway', 'edmonton', 'electric', '30 oct 1908 22 apr 1978', '1 sep 1951 -'], ['edmonton radial railway', 'edmonton', 'petrol ( gasoline )', '30 sep 1913', '1 apr 1914'], ['lake louise tramway', 'lake louise', 'petrol ( gasoline )', '1912', '1930'], ['lethbridge municipal railway', 'lethbridge', 'electric', 'sep 1912', '8 sep 1947']]
|
wru division one north
|
https://en.wikipedia.org/wiki/WRU_Division_One_North
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-14058433-5.html.csv
|
superlative
|
the caernarfon rfc club had the most points in the wru division one north .
|
{'scope': 'all', 'col_superlative': '12', 'row_superlative': '2', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None}
|
{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'points'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; points }'}, 'club'], 'result': 'caernarfon rfc', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; points } ; club }'}, 'caernarfon rfc'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; points } ; club } ; caernarfon rfc } = true', 'tointer': 'select the row whose points record of all rows is maximum . the club record of this row is caernarfon rfc .'}
|
eq { hop { argmax { all_rows ; points } ; club } ; caernarfon rfc } = true
|
select the row whose points record of all rows is maximum . the club record of this row is caernarfon rfc .
|
3
|
3
|
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'points_5': 5, 'club_6': 6, 'caernarfon rfc_7': 7}
|
{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'points_5': 'points', 'club_6': 'club', 'caernarfon rfc_7': 'caernarfon rfc'}
|
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'points_5': [0], 'club_6': [1], 'caernarfon rfc_7': [2]}
|
['club', 'played', 'won', 'drawn', 'lost', 'points for', 'points against', 'tries for', 'tries against', 'try bonus', 'losing bonus', 'points']
|
[['club', 'played', 'won', 'drawn', 'lost', 'points for', 'points against', 'tries for', 'tries against', 'try bonus', 'losing bonus', 'points'], ['caernarfon rfc', '22', '18', '1', '3', '643', '235', '101', '24', '14', '1', '89'], ['colwyn bay rfc', '22', '18', '0', '4', '570', '256', '79', '29', '10', '3', '85'], ['nant conwy rfc', '22', '16', '0', '6', '585', '177', '84', '21', '11', '4', '79'], ['mold rfc', '22', '16', '0', '6', '596', '239', '85', '27', '11', '3', '78'], ['ruthin rfc', '22', '15', '2', '5', '599', '198', '89', '21', '9', '3', '76'], ['llangefni rfc', '22', '13', '0', '9', '504', '311', '69', '42', '9', '5', '66'], ['llandudno rfc', '22', '9', '0', '13', '436', '498', '59', '73', '6', '3', '45'], ['denbigh rfc', '22', '7', '0', '15', '348', '467', '50', '69', '5', '5', '38'], ['bala rfc', '22', '8', '0', '14', '282', '443', '37', '61', '3', '2', '37'], ['dolgellau rfc', '22', '6', '1', '15', '250', '538', '32', '80', '3', '3', '32'], ['llanidloes rfc', '22', '2', '0', '20', '171', '835', '19', '128', '0', '2', '10'], ['newtown rfc', '22', '2', '0', '20', '109', '896', '10', '139', '0', '2', '10']]
|
royal canadian mint numismatic coins ( 2000s )
|
https://en.wikipedia.org/wiki/Royal_Canadian_Mint_numismatic_coins_%282000s%29
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11916083-28.html.csv
|
superlative
|
of all of the royal canadian mint numismatic coins from the 2000s , the one with the highest issue price was the great blue heron .
|
{'scope': 'all', 'col_superlative': '5', 'row_superlative': '7', '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', 'issue price'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; issue price }'}, 'theme'], 'result': 'great blue heron', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; issue price } ; theme }'}, 'great blue heron'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; issue price } ; theme } ; great blue heron } = true', 'tointer': 'select the row whose issue price record of all rows is maximum . the theme record of this row is great blue heron .'}
|
eq { hop { argmax { all_rows ; issue price } ; theme } ; great blue heron } = true
|
select the row whose issue price record of all rows is maximum . the theme record of this row is great blue heron .
|
3
|
3
|
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'issue price_5': 5, 'theme_6': 6, 'great blue heron_7': 7}
|
{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'issue price_5': 'issue price', 'theme_6': 'theme', 'great blue heron_7': 'great blue heron'}
|
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'issue price_5': [0], 'theme_6': [1], 'great blue heron_7': [2]}
|
['year', 'theme', 'artist', 'mintage', 'issue price']
|
[['2002', '15th anniversary loonie', 'dora de pãdery - hunt', '67672', '39.95'], ['2004', 'jack miner bird sanctuary', 'susan taylor', 'n / a', '39.95'], ['2005', 'tufted puffin', 'n / a', 'n / a', '39.95'], ['2006', 'snowy owl', 'glen loates', '20000', '39.95'], ['2007', 'trumpeter swan', 'kerri burnett', '40000', '45.95'], ['2008', 'common eider', 'mark hobson', '40000', '45.95'], ['2009', 'great blue heron', 'chris jordison', '40000', '47.95']]
|
just legal
|
https://en.wikipedia.org/wiki/Just_Legal
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2828803-1.html.csv
|
count
|
jonathan shapiro wrote who episodes of " just legal " .
|
{'scope': 'all', 'criterion': 'equal', 'value': 'jonathan shapiro', 'result': '2', 'col': '3', 'subset': None}
|
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'written by', 'jonathan shapiro'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose written by record fuzzily matches to jonathan shapiro .', 'tostr': 'filter_eq { all_rows ; written by ; jonathan shapiro }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; written by ; jonathan shapiro } }', 'tointer': 'select the rows whose written by record fuzzily matches to jonathan shapiro . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; written by ; jonathan shapiro } } ; 2 } = true', 'tointer': 'select the rows whose written by record fuzzily matches to jonathan shapiro . the number of such rows is 2 .'}
|
eq { count { filter_eq { all_rows ; written by ; jonathan shapiro } } ; 2 } = true
|
select the rows whose written by record fuzzily matches to jonathan shapiro . 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, 'written by_5': 5, 'jonathan shapiro_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', 'written by_5': 'written by', 'jonathan shapiro_6': 'jonathan shapiro', '2_7': '2'}
|
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'written by_5': [0], 'jonathan shapiro_6': [0], '2_7': [2]}
|
['series', 'title', 'written by', 'directed by', 'original air date', 'production code', 'us viewers ( millions )']
|
[['1', 'pilot', 'jonathan shapiro', 'andrew davis', 'september 19 , 2005', '475279', '3.440'], ['2', 'the runner', 'jonathan shapiro', 'dwight little', 'september 26 , 2005', '2t7001', '2.960'], ['3', 'the limit', 'rob bragin', 'john badham', 'october 3 , 2005', '2t7002', '2.880'], ['4', 'the body in the trunk', "craig o'neil & jason tracy", 'tim matheson', 'august 13 , 2006', '2t7003', 'n / a'], ['5', 'the heater', 'nick thiel', 'dennis smith', 'august 20 , 2006', '2t7004', '1.590'], ['6', 'the rainmaker', 'rama laurie stagner', 'dwight little', 'august 27 , 2006', '2t7005', '1.120'], ['7', 'the code', 'alfredo barrios jr', 'oz scott', 'september 3 , 2006', '2t7006', '1.340']]
|
spain at the paralympics
|
https://en.wikipedia.org/wiki/Spain_at_the_Paralympics
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12771081-2.html.csv
|
unique
|
the 1998 nagano games was the only time spain won 8 gold medals .
|
{'scope': 'all', 'row': '5', 'col': '2', 'col_other': '1', 'criterion': 'equal', 'value': '8', 'subset': None}
|
{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'gold', '8'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose gold record is equal to 8 .', 'tostr': 'filter_eq { all_rows ; gold ; 8 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; gold ; 8 } }', 'tointer': 'select the rows whose gold record is equal to 8 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'gold', '8'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose gold record is equal to 8 .', 'tostr': 'filter_eq { all_rows ; gold ; 8 }'}, 'games'], 'result': '1998 nagano', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; gold ; 8 } ; games }'}, '1998 nagano'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; gold ; 8 } ; games } ; 1998 nagano }', 'tointer': 'the games record of this unqiue row is 1998 nagano .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; gold ; 8 } } ; eq { hop { filter_eq { all_rows ; gold ; 8 } ; games } ; 1998 nagano } } = true', 'tointer': 'select the rows whose gold record is equal to 8 . there is only one such row in the table . the games record of this unqiue row is 1998 nagano .'}
|
and { only { filter_eq { all_rows ; gold ; 8 } } ; eq { hop { filter_eq { all_rows ; gold ; 8 } ; games } ; 1998 nagano } } = true
|
select the rows whose gold record is equal to 8 . there is only one such row in the table . the games record of this unqiue row is 1998 nagano .
|
6
|
5
|
{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'gold_7': 7, '8_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'games_9': 9, '1998 nagano_10': 10}
|
{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'gold_7': 'gold', '8_8': '8', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'games_9': 'games', '1998 nagano_10': '1998 nagano'}
|
{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'gold_7': [0], '8_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'games_9': [2], '1998 nagano_10': [3]}
|
['games', 'gold', 'silver', 'bronze', 'total', 'rank']
|
[['1984 innsbruck', '0', '0', '0', '0', '14'], ['1988 innsbruck', '1', '2', '1', '4', '11'], ['1992 tignes - albertsville', '0', '1', '3', '4', '16'], ['1994 lillehammer', '1', '6', '3', '10', '13'], ['1998 nagano', '8', '0', '0', '8', '7'], ['2002 salt lake city', '3', '3', '2', '8', '12'], ['2006 turin', '0', '1', '1', '2', '13'], ['2010 vancouver', '1', '2', '0', '3', '13']]
|
1978 u.s. open ( golf )
|
https://en.wikipedia.org/wiki/1978_U.S._Open_%28golf%29
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17245471-4.html.csv
|
superlative
|
of the players tied second after two rounds of the 1978 us open , the largest number of strikes taken , by a player , in a single round was 73 .
|
{'scope': 'subset', 'col_superlative': '4', 'row_superlative': '2', 'value_mentioned': 'yes', 'max_or_min': 'max', 'other_col': '1', 'subset': {'col': '1', 'criterion': 'equal', 'value': 't2'}}
|
{'func': 'eq', 'args': [{'func': 'max', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'place', 't2'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; place ; t2 }', 'tointer': 'select the rows whose place record fuzzily matches to t2 .'}, 'score'], 'result': '73 + 69 = 142', 'ind': 1, 'tostr': 'max { filter_eq { all_rows ; place ; t2 } ; score }', 'tointer': 'select the rows whose place record fuzzily matches to t2 . the maximum score record of these rows is 73 + 69 = 142 .'}, '73 + 69 = 142'], 'result': True, 'ind': 2, 'tostr': 'eq { max { filter_eq { all_rows ; place ; t2 } ; score } ; 73 + 69 = 142 } = true', 'tointer': 'select the rows whose place record fuzzily matches to t2 . the maximum score record of these rows is 73 + 69 = 142 .'}
|
eq { max { filter_eq { all_rows ; place ; t2 } ; score } ; 73 + 69 = 142 } = true
|
select the rows whose place record fuzzily matches to t2 . the maximum score record of these rows is 73 + 69 = 142 .
|
3
|
3
|
{'eq_2': 2, 'result_3': 3, 'max_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'place_5': 5, 't2_6': 6, 'score_7': 7, '73 + 69 = 142_8': 8}
|
{'eq_2': 'eq', 'result_3': 'true', 'max_1': 'max', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'place_5': 'place', 't2_6': 't2', 'score_7': 'score', '73 + 69 = 142_8': '73 + 69 = 142'}
|
{'eq_2': [3], 'result_3': [], 'max_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'place_5': [0], 't2_6': [0], 'score_7': [1], '73 + 69 = 142_8': [2]}
|
['place', 'player', 'country', 'score', 'to par']
|
[['1', 'andy north', 'united states', '70 + 70 = 140', '2'], ['t2', 'jack nicklaus', 'united states', '73 + 69 = 142', 'e'], ['t2', 'gary player', 'south africa', '71 + 71 = 142', 'e'], ['t2', 'j c snead', 'united states', '70 + 72 = 142', 'e'], ['t5', 'bobby clampett ( a )', 'united states', '70 + 73 = 143', '+ 1'], ['t5', 'mark hayes', 'united states', '73 + 70 = 143', '+ 1'], ['t5', 'hale irwin', 'united states', '69 + 74 = 143', '+ 1'], ['t5', 'lee trevino', 'united states', '72 + 71 = 143', '+ 1'], ['t9', 'seve ballesteros', 'spain', '75 + 69 = 144', '+ 2'], ['t9', 'andy bean', 'united states', '72 + 72 = 144', '+ 2'], ['t9', 'phil hancock', 'united states', '71 + 73 = 144', '+ 2'], ['t9', 'joe inman', 'united states', '72 + 72 = 144', '+ 2'], ['t9', 'peter oosterhuis', 'england', '72 + 72 = 144', '+ 2'], ['t9', 'dave stockton', 'united states', '71 + 73 = 144', '+ 2']]
|
2010 - 11 orlando magic season
|
https://en.wikipedia.org/wiki/2010%E2%80%9311_Orlando_Magic_season
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27700530-10.html.csv
|
count
|
in the 2010 - 11 orlando magic season , when the magic won , there were 5 times that dwight howard had at least a share of the high rebounds .
|
{'scope': 'subset', 'criterion': 'fuzzily_match', 'value': 'dwight howard', 'result': '5', 'col': '6', 'subset': {'col': '4', 'criterion': 'fuzzily_match', 'value': 'w'}}
|
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'score', 'w'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; score ; w }', 'tointer': 'select the rows whose score record fuzzily matches to w .'}, 'high rebounds', 'dwight howard'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose score record fuzzily matches to w . among these rows , select the rows whose high rebounds record fuzzily matches to dwight howard .', 'tostr': 'filter_eq { filter_eq { all_rows ; score ; w } ; high rebounds ; dwight howard }'}], 'result': '5', 'ind': 2, 'tostr': 'count { filter_eq { filter_eq { all_rows ; score ; w } ; high rebounds ; dwight howard } }', 'tointer': 'select the rows whose score record fuzzily matches to w . among these rows , select the rows whose high rebounds record fuzzily matches to dwight howard . the number of such rows is 5 .'}, '5'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_eq { filter_eq { all_rows ; score ; w } ; high rebounds ; dwight howard } } ; 5 } = true', 'tointer': 'select the rows whose score record fuzzily matches to w . among these rows , select the rows whose high rebounds record fuzzily matches to dwight howard . the number of such rows is 5 .'}
|
eq { count { filter_eq { filter_eq { all_rows ; score ; w } ; high rebounds ; dwight howard } } ; 5 } = true
|
select the rows whose score record fuzzily matches to w . among these rows , select the rows whose high rebounds record fuzzily matches to dwight howard . the number of such rows is 5 .
|
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, 'score_6': 6, 'w_7': 7, 'high rebounds_8': 8, 'dwight howard_9': 9, '5_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', 'score_6': 'score', 'w_7': 'w', 'high rebounds_8': 'high rebounds', 'dwight howard_9': 'dwight howard', '5_10': '5'}
|
{'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_str_eq_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'score_6': [0], 'w_7': [0], 'high rebounds_8': [1], 'dwight howard_9': [1], '5_10': [3]}
|
['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record']
|
[['18', 'december 1', 'chicago', 'w 107 - 78 ( ot )', 'jameer nelson ( 24 )', 'dwight howard ( 12 )', 'jameer nelson ( 9 )', 'united center 21435', '14 - 4'], ['19', 'december 3', 'detroit', 'w 104 - 91 ( ot )', 'brandon bass ( 27 )', 'marcin gortat ( 11 )', 'vince carter ( 9 )', 'the palace of auburn hills 18433', '15 - 4'], ['20', 'december 4', 'milwaukee', 'l 85 - 96 ( ot )', 'vince carter ( 20 )', 'marcin gortat ( 10 )', 'vince carter ( 6 )', 'bradley center 16218', '15 - 5'], ['21', 'december 6', 'atlanta', 'l 74 - 80 ( ot )', 'vince carter ( 18 )', 'dwight howard ( 13 )', 'vince carter ( 3 )', 'amway center 18846', '15 - 6'], ['22', 'december 9', 'portland', 'l 83 - 97 ( ot )', 'dwight howard ( 39 )', 'dwight howard ( 15 )', 'jameer nelson ( 5 )', 'rose garden 20219', '15 - 7'], ['23', 'december 10', 'utah', 'l 105 - 117 ( ot )', 'jameer nelson ( 19 )', 'dwight howard ( 12 )', 'jameer nelson ( 10 )', 'energysolutions arena 18765', '15 - 8'], ['24', 'december 12', 'la clippers', 'w 94 - 85 ( ot )', 'dwight howard ( 22 )', 'brandon bass ( 11 )', 'jameer nelson ( 9 )', 'staples center 18278', '16 - 8'], ['25', 'december 14', 'denver', 'l 94 - 111 ( ot )', 'j j redick ( 29 )', 'dwight howard ( 14 )', 'jameer nelson ( 8 )', 'pepsi center 16427', '16 - 9'], ['26', 'december 18', 'philadelphia', 'l 89 - 97 ( ot )', 'dwight howard ( 26 )', 'dwight howard ( 20 )', 'jameer nelson ( 9 )', 'amway center 18846', '16 - 10'], ['28', 'december 21', 'dallas', 'l 99 - 105 ( ot )', 'dwight howard ( 26 )', 'dwight howard ( 23 )', 'hedo türkoğlu ( 8 )', 'amway center 19057', '16 - 12'], ['29', 'december 23', 'san antonio', 'w 123 - 101 ( ot )', 'dwight howard ( 29 )', 'dwight howard ( 14 )', 'gilbert arenas ( 9 )', 'amway center 18916', '17 - 12'], ['30', 'december 25', 'boston', 'w 86 - 78 ( ot )', 'brandon bass ( 21 )', 'dwight howard ( 11 )', 'hedo türkoğlu ( 4 )', 'amway center 19013', '18 - 12'], ['31', 'december 27', 'new jersey', 'w 104 - 88 ( ot )', 'hedo türkoğlu ( 20 )', 'dwight howard ( 13 )', 'jameer nelson ( 7 )', 'prudential center 11514', '19 - 12'], ['32', 'december 28', 'cleveland', 'w 110 - 95 ( ot )', 'gilbert arenas ( 22 )', 'gilbert arenas , dwight howard , hedo türkoğlu ( 6 )', 'gilbert arenas ( 11 )', 'quicken loans arena 20562', '20 - 12']]
|
2007 icc world twenty20 statistics
|
https://en.wikipedia.org/wiki/2007_ICC_World_Twenty20_statistics
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13219504-9.html.csv
|
comparative
|
the partnership of younis khan / shoaib malik had less runs than the partnership of gautam gambhir / virender sehwag .
|
{'row_1': '8', 'row_2': '2', 'col': '1', 'col_other': '3', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None}
|
{'func': 'less', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'partnerships', 'younis khan / shoaib malik'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose partnerships record fuzzily matches to younis khan / shoaib malik .', 'tostr': 'filter_eq { all_rows ; partnerships ; younis khan / shoaib malik }'}, 'runs ( balls )'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; partnerships ; younis khan / shoaib malik } ; runs ( balls ) }', 'tointer': 'select the rows whose partnerships record fuzzily matches to younis khan / shoaib malik . take the runs ( balls ) record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'partnerships', 'gautam gambhir / virender sehwag'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose partnerships record fuzzily matches to gautam gambhir / virender sehwag .', 'tostr': 'filter_eq { all_rows ; partnerships ; gautam gambhir / virender sehwag }'}, 'runs ( balls )'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; partnerships ; gautam gambhir / virender sehwag } ; runs ( balls ) }', 'tointer': 'select the rows whose partnerships record fuzzily matches to gautam gambhir / virender sehwag . take the runs ( balls ) record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; partnerships ; younis khan / shoaib malik } ; runs ( balls ) } ; hop { filter_eq { all_rows ; partnerships ; gautam gambhir / virender sehwag } ; runs ( balls ) } } = true', 'tointer': 'select the rows whose partnerships record fuzzily matches to younis khan / shoaib malik . take the runs ( balls ) record of this row . select the rows whose partnerships record fuzzily matches to gautam gambhir / virender sehwag . take the runs ( balls ) record of this row . the first record is less than the second record .'}
|
less { hop { filter_eq { all_rows ; partnerships ; younis khan / shoaib malik } ; runs ( balls ) } ; hop { filter_eq { all_rows ; partnerships ; gautam gambhir / virender sehwag } ; runs ( balls ) } } = true
|
select the rows whose partnerships record fuzzily matches to younis khan / shoaib malik . take the runs ( balls ) record of this row . select the rows whose partnerships record fuzzily matches to gautam gambhir / virender sehwag . take the runs ( balls ) 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, 'partnerships_7': 7, 'younis khan / shoaib malik_8': 8, 'runs (balls)_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'partnerships_11': 11, 'gautam gambhir / virender sehwag_12': 12, 'runs (balls)_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', 'partnerships_7': 'partnerships', 'younis khan / shoaib malik_8': 'younis khan / shoaib malik', 'runs (balls)_9': 'runs ( balls )', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'partnerships_11': 'partnerships', 'gautam gambhir / virender sehwag_12': 'gautam gambhir / virender sehwag', 'runs (balls)_13': 'runs ( balls )'}
|
{'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'partnerships_7': [0], 'younis khan / shoaib malik_8': [0], 'runs (balls)_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'partnerships_11': [1], 'gautam gambhir / virender sehwag_12': [1], 'runs (balls)_13': [3]}
|
['runs ( balls )', 'wicket', 'partnerships', 'venue', 'date']
|
[['145 ( 81 )', '1st', 'chris gayle / devon smith', 'johannesburg', '2007 - 09 - 11'], ['136 ( 88 )', '1st', 'gautam gambhir / virender sehwag', 'durban', '2007 - 09 - 19'], ['120 ( 57 )', '3rd', 'herschelle gibbs / justin kemp', 'johannesburg', '2007 - 09 - 11'], ['119 ( 75 )', '5th', 'shoaib malik / misbah - ul - haq', 'johannesburg', '2007 - 09 - 18'], ['109 ( 62 )', '3rd', 'aftab ahmed / mohammad ashraful', 'johannesburg', '2007 - 09 - 13'], ['104 ( 69 )', '1st', 'adam gilchrist / matthew hayden', 'cape town', '2007 - 09 - 16'], ['102 ( 62 )', '1st', 'adam gilchrist / matthew hayden', 'cape town', '2007 - 09 - 22'], ['101 ( 55 )', '4th', 'younis khan / shoaib malik', 'johannesburg', '2007 - 09 - 17'], ['100 ( 45 )', '4th', 'kevin pietersen / paul collingwood', 'cape town', '2007 - 09 - 13'], ['95 ( 79 )', '2nd', 'devon smith / shivnarine chanderpaul', 'johannesburg', '2007 - 09 - 13']]
|
galicia , spain
|
https://en.wikipedia.org/wiki/Galicia%2C_Spain
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12837-1.html.csv
|
superlative
|
the highest number of sunlight hours in galicia , spain , is in the city of pontevedra .
|
{'scope': 'all', 'col_superlative': '6', 'row_superlative': '6', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None}
|
{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'sunlight hours'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; sunlight hours }'}, 'city / town'], 'result': 'pontevedra', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; sunlight hours } ; city / town }'}, 'pontevedra'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; sunlight hours } ; city / town } ; pontevedra } = true', 'tointer': 'select the row whose sunlight hours record of all rows is maximum . the city / town record of this row is pontevedra .'}
|
eq { hop { argmax { all_rows ; sunlight hours } ; city / town } ; pontevedra } = true
|
select the row whose sunlight hours record of all rows is maximum . the city / town record of this row is pontevedra .
|
3
|
3
|
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'sunlight hours_5': 5, 'city / town_6': 6, 'pontevedra_7': 7}
|
{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'sunlight hours_5': 'sunlight hours', 'city / town_6': 'city / town', 'pontevedra_7': 'pontevedra'}
|
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'sunlight hours_5': [0], 'city / town_6': [1], 'pontevedra_7': [2]}
|
['city / town', 'july av t', 'rain', 'days with rain ( year / summer )', 'days with frost', 'sunlight hours']
|
[['santiago de compostela', 'degree', 'mm ( in )', '141 / 19', '15', '1998'], ['a coruña', 'degree', 'mm ( in )', '131 / 19', '0', '1966'], ['lugo', 'degree', 'mm ( in )', '131 / 18', '42', '1821'], ['vigo', 'degree', 'mm ( in )', '130 / 18', '5', '2212'], ['ourense', 'degree', 'mm ( in )', '97 / 12', '30', '2043'], ['pontevedra', 'degree', 'mm ( in )', '133 / 18', '2', '2223']]
|
2010 - 11 atlanta thrashers season
|
https://en.wikipedia.org/wiki/2010%E2%80%9311_Atlanta_Thrashers_season
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27537518-7.html.csv
|
unique
|
in the 2010-11 atlanta thrashers season , the only time the location was the bell centre was on january 2nd .
|
{'scope': 'all', 'row': '1', 'col': '7', 'col_other': '2', 'criterion': 'equal', 'value': 'bell centre', 'subset': None}
|
{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location', 'bell centre'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose location record fuzzily matches to bell centre .', 'tostr': 'filter_eq { all_rows ; location ; bell centre }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; location ; bell centre } }', 'tointer': 'select the rows whose location record fuzzily matches to bell centre . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location', 'bell centre'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose location record fuzzily matches to bell centre .', 'tostr': 'filter_eq { all_rows ; location ; bell centre }'}, 'date'], 'result': 'january 2', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; location ; bell centre } ; date }'}, 'january 2'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; location ; bell centre } ; date } ; january 2 }', 'tointer': 'the date record of this unqiue row is january 2 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; location ; bell centre } } ; eq { hop { filter_eq { all_rows ; location ; bell centre } ; date } ; january 2 } } = true', 'tointer': 'select the rows whose location record fuzzily matches to bell centre . there is only one such row in the table . the date record of this unqiue row is january 2 .'}
|
and { only { filter_eq { all_rows ; location ; bell centre } } ; eq { hop { filter_eq { all_rows ; location ; bell centre } ; date } ; january 2 } } = true
|
select the rows whose location record fuzzily matches to bell centre . there is only one such row in the table . the date record of this unqiue row is january 2 .
|
6
|
5
|
{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'location_7': 7, 'bell centre_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'date_9': 9, 'january 2_10': 10}
|
{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'location_7': 'location', 'bell centre_8': 'bell centre', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'date_9': 'date', 'january 2_10': 'january 2'}
|
{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'location_7': [0], 'bell centre_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'date_9': [2], 'january 2_10': [3]}
|
['game', 'date', 'opponent', 'score', 'first star', 'decision', 'location', 'attendance', 'record', 'points']
|
[['42', 'january 2', 'montreal canadiens', '4 - 3 ot', 'd byfuglien', 'o pavelec', 'bell centre', '21273', '21 - 15 - 6', '48'], ['43', 'january 5', 'florida panthers', '3 - 2', 'r peverley', 'o pavelec', 'bankatlantic center', '12803', '22 - 15 - 6', '50'], ['44', 'january 7', 'toronto maple leafs', '3 - 9', 'm grabovski', 'o pavelec', 'philips arena', '14592', '22 - 16 - 6', '50'], ['45', 'january 9', 'carolina hurricanes', '3 - 4 ot', 't ruutu', 'o pavelec', 'rbc center', '17907', '22 - 16 - 7', '51'], ['46', 'january 14', 'philadelphia flyers', '2 - 5', 'd briere', 'o pavelec', 'philips arena', '15081', '22 - 17 - 7', '51'], ['47', 'january 15', 'dallas stars', '1 - 6', 't daley', 'o pavelec', 'american airlines center', '17702', '22 - 18 - 7', '51'], ['48', 'january 17', 'florida panthers', '3 - 2 so', 'a burmistrov', 'o pavelec', 'bankatlantic center', '11477', '23 - 18 - 7', '53'], ['49', 'january 20', 'tampa bay lightning', '2 - 3 so', 's stamkos', 'o pavelec', 'philips arena', '12314', '23 - 18 - 8', '54'], ['50', 'january 22', 'new york rangers', '2 - 3 so', 'm zuccarello', 'o pavelec', 'philips arena', '17061', '23 - 18 - 9', '55'], ['51', 'january 23', 'tampa bay lightning', '1 - 7', 's gagne', 'o pavelec', 'st pete times forum', '13916', '23 - 19 - 9', '55']]
|
1980 indycar season
|
https://en.wikipedia.org/wiki/1980_IndyCar_season
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10527215-2.html.csv
|
superlative
|
ontario city was the first location used in the 1980 indycar season .
|
{'scope': 'all', 'col_superlative': '5', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '4', 'subset': None}
|
{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmin', 'args': ['all_rows', 'date'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; date }'}, 'city / location'], 'result': 'ontario , california', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; date } ; city / location }'}, 'ontario , california'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmin { all_rows ; date } ; city / location } ; ontario , california } = true', 'tointer': 'select the row whose date record of all rows is minimum . the city / location record of this row is ontario , california .'}
|
eq { hop { argmin { all_rows ; date } ; city / location } ; ontario , california } = true
|
select the row whose date record of all rows is minimum . the city / location record of this row is ontario , california .
|
3
|
3
|
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'date_5': 5, 'city / location_6': 6, 'ontario , california_7': 7}
|
{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'date_5': 'date', 'city / location_6': 'city / location', 'ontario , california_7': 'ontario , california'}
|
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'date_5': [0], 'city / location_6': [1], 'ontario , california_7': [2]}
|
['sanctioning', 'race name', 'circuit', 'city / location', 'date']
|
[['joint cart / usac ( crl )', 'datsun twin 200', 'ontario motor speedway', 'ontario , california', 'april 13'], ['joint cart / usac ( crl )', 'indianapolis 500 - mile race', 'indianapolis motor speedway', 'indianapolis , indiana', 'may 26'], ['joint cart / usac ( crl )', 'gould rex mays classic 150', 'milwaukee mile', 'west allis , wisconsin', 'june 8'], ['joint cart / usac ( crl )', 'true value 500', 'pocono raceway', 'long pond , pennsylvania', 'june 22'], ['joint cart / usac ( crl )', 'red roof inns 150', 'mid - ohio sports car course', 'lexington , ohio', 'july 13'], ['cart', 'norton 200', 'michigan international speedway', 'brooklyn , michigan', 'july 20'], ['cart', 'kent oil 150', 'watkins glen international', 'watkins glen , new york', 'august 3'], ['cart', 'tony bettenhausen 200', 'milwaukee mile', 'west allis , wisconsin', 'august 10'], ['cart', 'california 500', 'ontario motor speedway', 'ontario , california', 'august 31'], ['cart', 'gould grand prix 150', 'michigan international speedway', 'brooklyn , michigan', 'september 20'], ['cart', 'i copa méxico 150', 'autódromo hermanos rodríguez', 'mexico city , mexico', 'october 26'], ['cart', 'miller high life 150', 'phoenix international raceway', 'avondale , arizona', 'november 8']]
|
grey 's anatomy ( season 4 )
|
https://en.wikipedia.org/wiki/Grey%27s_Anatomy_%28season_4%29
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-11058032-1.html.csv
|
ordinal
|
the eighth episode in the season 4 series of grey 's anatomy had the second highest number of viewers in the season .
|
{'row': '8', 'col': '7', 'order': '2', 'col_other': '2', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None}
|
{'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'us viewers ( millions )', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; us viewers ( millions ) ; 2 }'}, 'no in season'], 'result': '8', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; us viewers ( millions ) ; 2 } ; no in season }'}, '8'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; us viewers ( millions ) ; 2 } ; no in season } ; 8 } = true', 'tointer': 'select the row whose us viewers ( millions ) record of all rows is 2nd maximum . the no in season record of this row is 8 .'}
|
eq { hop { nth_argmax { all_rows ; us viewers ( millions ) ; 2 } ; no in season } ; 8 } = true
|
select the row whose us viewers ( millions ) record of all rows is 2nd maximum . the no in season record of this row is 8 .
|
3
|
3
|
{'eq_2': 2, 'result_3': 3, 'num_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'us viewers (millions)_5': 5, '2_6': 6, 'no in season_7': 7, '8_8': 8}
|
{'eq_2': 'eq', 'result_3': 'true', 'num_hop_1': 'num_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'us viewers (millions)_5': 'us viewers ( millions )', '2_6': '2', 'no in season_7': 'no in season', '8_8': '8'}
|
{'eq_2': [3], 'result_3': [], 'num_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'us viewers (millions)_5': [0], '2_6': [0], 'no in season_7': [1], '8_8': [2]}
|
['no in series', 'no in season', 'title', 'directed by', 'written by', 'original air date', 'us viewers ( millions )']
|
[['62', '1', 'a change is gon na come', 'rob corn', 'shonda rhimes', 'september 27 , 2007', '20.93'], ['63', '2', 'love / addiction', 'james frawley', 'debora cahn', 'october 4 , 2007', '18.51'], ['64', '3', 'let the truth sting', 'dan minahan', 'mark wilding', 'october 11 , 2007', '19.04'], ['65', '4', 'the heart of the matter', 'randy zisk', 'allan heinberg', 'october 18 , 2007', '18.04'], ['66', '5', 'haunt you every day', 'bethany rooney', 'krista vernoff', 'october 25 , 2007', '18.17'], ['67', '6', 'kung fu fighting', 'tom verica', 'stacy mckee', 'november 1 , 2007', '19.31'], ['68', '7', 'physical attraction , chemical reaction', 'jeff melman', 'tony phelan & joan rater', 'november 8 , 2007', '19.50'], ['69', '8', 'forever young', 'rob corn', 'mark wilding', 'november 15 , 2007', '19.61'], ['70', '9', 'crash into me ( part 1 )', 'michael grossman', 'shonda rhimes & krista vernoff', 'november 22 , 2007', '14.11'], ['71', '10', 'crash into me ( part 2 )', 'jessica yu', 'shonda rhimes & krista vernoff', 'december 6 , 2007', '17.78'], ['72', '11', 'lay your hands on me', 'john terlesky', 'allan heinberg', 'january 10 , 2008', '17.68'], ['73', '12', 'where the wild things are', 'rob corn', 'zoanne clack', 'april 24 , 2008', '16.37'], ['74', '13', 'piece of my heart', 'mark tinker', 'stacy mckee', 'may 1 , 2008', '15.31'], ['75', '14', 'the becoming', 'julie anne robinson', 'tony phelan & joan rater', 'may 8 , 2008', '16.03'], ['76', '15', 'losing my mind', 'james frawley', 'debora cahn', 'may 15 , 2008', '15.55'], ['77', '16', 'freedom ( part 1 )', 'rob corn', 'shonda rhimes', 'may 22 , 2008', '18.09']]
|
toronto raptors all - time roster
|
https://en.wikipedia.org/wiki/Toronto_Raptors_all-time_roster
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-10015132-7.html.csv
|
comparative
|
chris garner began playing for the toronto raptors seven years before dion glover .
|
{'row_1': '3', 'row_2': '5', 'col': '5', 'col_other': '1', 'relation': 'diff', 'record_mentioned': 'no', 'diff_result': {'diff_value': '7 years', 'bigger': 'row2'}}
|
{'func': 'eq', 'args': [{'func': 'diff', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', 'chris garner'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose player record fuzzily matches to chris garner .', 'tostr': 'filter_eq { all_rows ; player ; chris garner }'}, 'years in toronto'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; player ; chris garner } ; years in toronto }', 'tointer': 'select the rows whose player record fuzzily matches to chris garner . take the years in toronto record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', 'dion glover'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose player record fuzzily matches to dion glover .', 'tostr': 'filter_eq { all_rows ; player ; dion glover }'}, 'years in toronto'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; player ; dion glover } ; years in toronto }', 'tointer': 'select the rows whose player record fuzzily matches to dion glover . take the years in toronto record of this row .'}], 'result': '-7 years', 'ind': 4, 'tostr': 'diff { hop { filter_eq { all_rows ; player ; chris garner } ; years in toronto } ; hop { filter_eq { all_rows ; player ; dion glover } ; years in toronto } }'}, '-7 years'], 'result': True, 'ind': 5, 'tostr': 'eq { diff { hop { filter_eq { all_rows ; player ; chris garner } ; years in toronto } ; hop { filter_eq { all_rows ; player ; dion glover } ; years in toronto } } ; -7 years } = true', 'tointer': 'select the rows whose player record fuzzily matches to chris garner . take the years in toronto record of this row . select the rows whose player record fuzzily matches to dion glover . take the years in toronto record of this row . the second record is 7 years larger than the first record .'}
|
eq { diff { hop { filter_eq { all_rows ; player ; chris garner } ; years in toronto } ; hop { filter_eq { all_rows ; player ; dion glover } ; years in toronto } } ; -7 years } = true
|
select the rows whose player record fuzzily matches to chris garner . take the years in toronto record of this row . select the rows whose player record fuzzily matches to dion glover . take the years in toronto record of this row . the second record is 7 years 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, 'player_8': 8, 'chris garner_9': 9, 'years in toronto_10': 10, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_11': 11, 'player_12': 12, 'dion glover_13': 13, 'years in toronto_14': 14, '-7 years_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', 'player_8': 'player', 'chris garner_9': 'chris garner', 'years in toronto_10': 'years in toronto', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_11': 'all_rows', 'player_12': 'player', 'dion glover_13': 'dion glover', 'years in toronto_14': 'years in toronto', '-7 years_15': '-7 years'}
|
{'str_eq_5': [6], 'result_6': [], 'diff_4': [5], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_7': [0], 'player_8': [0], 'chris garner_9': [0], 'years in toronto_10': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_11': [1], 'player_12': [1], 'dion glover_13': [1], 'years in toronto_14': [3], '-7 years_15': [5]}
|
['player', 'no', 'nationality', 'position', 'years in toronto', 'school / club team']
|
[['sundiata gaines', '2', 'united states', 'guard', '2011', 'georgia'], ['jorge garbajosa', '15', 'spain', 'forward', '2006 - 08', 'cb mã ¡ laga ( spain )'], ['chris garner', '0', 'united states', 'guard', '1997 - 98', 'memphis'], ['rudy gay', '22', 'united states', 'forward', '2013 - present', 'connecticut'], ['dion glover', '22', 'united states', 'guard', '2004', 'georgia tech'], ['joey graham', '14', 'united states', 'guard - forward', '2005 - 09', 'oklahoma state']]
|
black swan - class sloop
|
https://en.wikipedia.org/wiki/Black_Swan-class_sloop
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1220125-3.html.csv
|
superlative
|
the chanticleer was the first sloop to be laid down in the black swan - class sloop .
|
{'scope': 'all', 'col_superlative': '4', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '1', 'subset': None}
|
{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmin', 'args': ['all_rows', 'laid down'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; laid down }'}, 'name'], 'result': 'chanticleer', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; laid down } ; name }'}, 'chanticleer'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmin { all_rows ; laid down } ; name } ; chanticleer } = true', 'tointer': 'select the row whose laid down record of all rows is minimum . the name record of this row is chanticleer .'}
|
eq { hop { argmin { all_rows ; laid down } ; name } ; chanticleer } = true
|
select the row whose laid down record of all rows is minimum . the name record of this row is chanticleer .
|
3
|
3
|
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'laid down_5': 5, 'name_6': 6, 'chanticleer_7': 7}
|
{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'laid down_5': 'laid down', 'name_6': 'name', 'chanticleer_7': 'chanticleer'}
|
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'laid down_5': [0], 'name_6': [1], 'chanticleer_7': [2]}
|
['name', 'pennant', 'builder', 'laid down', 'launched', 'commissioned']
|
[['chanticleer', 'u05', 'denny , dunbarton', '6 june 1941', '24 september 1942', '29 march 1943'], ['crane', 'u23', 'denny , dunbarton', '13 june 1941', '9 november 1942', '10 may 1943'], ['cygnet', 'u38', 'cammell laird , birkenhead', '30 august 1941', '28 july 1942', '1 december 1942'], ['kite', 'u87', 'cammell laird , birkenhead', '25 september 1941', '13 october 1942', '1 march 1943'], ['lapwing', 'u62', 'scotts , greenock', '17 december 1941', '16 july 1943', '21 march 1944'], ['lark', 'u11', 'scotts , greenock', '5 may 1942', '28 august 1943', '10 april 1944'], ['magpie', 'u82', 'thornycroft , woolston', '30 december 1941', '24 march 1943', '30 august 1943'], ['peacock', 'u96', 'thornycroft , woolston', '29 november 1942', '11 december 1943', '10 may 1944'], ['pheasant', 'u49', 'yarrow , scotstoun', '17 march 1942', '21 december 1942', '12 may 1943'], ['redpole', 'u69', 'yarrow , scotstoun', '18 may 1942', '25 february 1943', '24 june 1943'], ['snipe', 'u20', 'denny , dunbarton', '21 september 1944', '20 december 1945', '9 september 1946'], ['sparrow', 'u71', 'denny , dunbarton', '30 october 1944', '18 february 1946', '16 december 1946'], ['starling', 'u66', 'fairfield , govan', '21 october 1941', '14 october 1942', '1 april 1943'], ['woodcock', 'u90', 'fairfield , govan', '21 october 1941', '26 november 1942', '29 may 1943']]
|
nauru
|
https://en.wikipedia.org/wiki/Nauru
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-21302-1.html.csv
|
unique
|
boe is the only district that has less than 5 villages .
|
{'scope': 'all', 'row': '6', 'col': '6', 'col_other': '2', 'criterion': 'less_than', 'value': '5', 'subset': None}
|
{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'no of villages', '5'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose no of villages record is less than 5 .', 'tostr': 'filter_less { all_rows ; no of villages ; 5 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_less { all_rows ; no of villages ; 5 } }', 'tointer': 'select the rows whose no of villages record is less than 5 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'no of villages', '5'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose no of villages record is less than 5 .', 'tostr': 'filter_less { all_rows ; no of villages ; 5 }'}, 'district'], 'result': 'boe', 'ind': 2, 'tostr': 'hop { filter_less { all_rows ; no of villages ; 5 } ; district }'}, 'boe'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_less { all_rows ; no of villages ; 5 } ; district } ; boe }', 'tointer': 'the district record of this unqiue row is boe .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_less { all_rows ; no of villages ; 5 } } ; eq { hop { filter_less { all_rows ; no of villages ; 5 } ; district } ; boe } } = true', 'tointer': 'select the rows whose no of villages record is less than 5 . there is only one such row in the table . the district record of this unqiue row is boe .'}
|
and { only { filter_less { all_rows ; no of villages ; 5 } } ; eq { hop { filter_less { all_rows ; no of villages ; 5 } ; district } ; boe } } = true
|
select the rows whose no of villages record is less than 5 . there is only one such row in the table . the district record of this unqiue row is boe .
|
6
|
5
|
{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_less_0': 0, 'all_rows_6': 6, 'no of villages_7': 7, '5_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'district_9': 9, 'boe_10': 10}
|
{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_less_0': 'filter_less', 'all_rows_6': 'all_rows', 'no of villages_7': 'no of villages', '5_8': '5', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'district_9': 'district', 'boe_10': 'boe'}
|
{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_less_0': [1, 2], 'all_rows_6': [0], 'no of villages_7': [0], '5_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'district_9': [2], 'boe_10': [3]}
|
['nr', 'district', 'former name', 'area ( ha )', 'population ( 2005 )', 'no of villages', 'density persons / ha']
|
[['1', 'aiwo', 'aiue', '100', '1092', '8', '10.9'], ['2', 'anabar', 'anebwor', '143', '502', '15', '3.5'], ['3', 'anetan', 'añetañ', '100', '516', '12', '5.2'], ['4', 'anibare', 'anybody', '314', '160', '17', '0.5'], ['5', 'baiti', 'beidi', '123', '572', '15', '4.7'], ['6', 'boe', 'boi', '66', '795', '4', '12.0'], ['7', 'buada', 'arenibok', '266', '716', '14', '2.7'], ['8', 'denigomodu', 'denikomotu', '118', '2827', '17', '24.0'], ['9', 'ewa', 'eoa', '117', '318', '12', '2.7'], ['10', 'ijuw', 'ijub', '112', '303', '13', '2.7'], ['11', 'meneng', 'meneñ', '288', '1830', '18', '6.4'], ['12', 'nibok', 'ennibeck', '136', '432', '11', '3.2'], ['13', 'uaboe', 'ueboi', '97', '335', '6', '3.5'], ['14', 'yaren', 'moqua', '150', '820', '7', '5.5']]
|
kathleen horvath
|
https://en.wikipedia.org/wiki/Kathleen_Horvath
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17727652-3.html.csv
|
comparative
|
of the tournaments that kathleen horvath participated in , the one in indianapolis took place 21 days before the one in palm beach gardens .
|
{'row_1': '7', 'row_2': '8', 'col': '2', 'col_other': '3', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None}
|
{'func': 'less', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'tournament', 'indianapolis'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose tournament record fuzzily matches to indianapolis .', 'tostr': 'filter_eq { all_rows ; tournament ; indianapolis }'}, 'date'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; tournament ; indianapolis } ; date }', 'tointer': 'select the rows whose tournament record fuzzily matches to indianapolis . take the date record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'tournament', 'palm beach gardens'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose tournament record fuzzily matches to palm beach gardens .', 'tostr': 'filter_eq { all_rows ; tournament ; palm beach gardens }'}, 'date'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; tournament ; palm beach gardens } ; date }', 'tointer': 'select the rows whose tournament record fuzzily matches to palm beach gardens . take the date record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; tournament ; indianapolis } ; date } ; hop { filter_eq { all_rows ; tournament ; palm beach gardens } ; date } } = true', 'tointer': 'select the rows whose tournament record fuzzily matches to indianapolis . take the date record of this row . select the rows whose tournament record fuzzily matches to palm beach gardens . take the date record of this row . the first record is less than the second record .'}
|
less { hop { filter_eq { all_rows ; tournament ; indianapolis } ; date } ; hop { filter_eq { all_rows ; tournament ; palm beach gardens } ; date } } = true
|
select the rows whose tournament record fuzzily matches to indianapolis . take the date record of this row . select the rows whose tournament record fuzzily matches to palm beach gardens . take the date record of this row . the first record is less than the second record .
|
5
|
5
|
{'less_4': 4, 'result_5': 5, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'tournament_7': 7, 'indianapolis_8': 8, 'date_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'tournament_11': 11, 'palm beach gardens_12': 12, 'date_13': 13}
|
{'less_4': 'less', 'result_5': 'true', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'tournament_7': 'tournament', 'indianapolis_8': 'indianapolis', 'date_9': 'date', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'tournament_11': 'tournament', 'palm beach gardens_12': 'palm beach gardens', 'date_13': 'date'}
|
{'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'tournament_7': [0], 'indianapolis_8': [0], 'date_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'tournament_11': [1], 'palm beach gardens_12': [1], 'date_13': [3]}
|
['outcome', 'date', 'tournament', 'surface', 'opponent', 'score']
|
[['winner', 'january 19 , 1981', 'montreal', 'carpet ( i )', 'candy reynolds', '6 - 4 , 7 - 6'], ['winner', 'february 28 , 1983', 'nashville', 'carpet ( i )', 'marcela skuherská', '6 - 4 , 6 - 3'], ['runner - up', 'may 16 , 1983', 'berlin', 'clay', 'chris evert - lloyd', '4 - 6 , 6 - 7 ( 1 )'], ['winner', 'november 7 , 1983', 'honolulu', 'carpet ( i )', 'carling bassett', '4 - 6 , 6 - 2 , 7 - 6 ( 1 )'], ['runner - up', 'january 23 , 1984', 'marco island', 'clay', 'bonnie gadusek', '6 - 3 , 0 - 6 , 4 - 6'], ['runner - up', 'may 14 , 1984', 'berlin', 'clay', 'claudia kohde - kilsch', '6 - 7 ( 8 ) , 1 - 6'], ['winner', 'march 4 , 1985', 'indianapolis', 'carpet ( i )', 'elise burgin', '6 - 2 , 6 - 4'], ['winner', 'march 25 , 1985', 'palm beach gardens', 'clay', 'petra delhees - jauch', '3 - 6 , 6 - 3 , 6 - 3'], ['winner', 'july 6 , 1987', 'knokke', 'clay', 'bettina bunge', '6 - 1 , 7 - 6 ( 5 )']]
|
1970 vfl season
|
https://en.wikipedia.org/wiki/1970_VFL_season
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1164217-19.html.csv
|
count
|
three of the games had crowds of over 25,000 people .
|
{'scope': 'all', 'criterion': 'greater_than', 'value': '25000', 'result': '3', 'col': '6', 'subset': None}
|
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'crowd', '25000'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose crowd record is greater than 25000 .', 'tostr': 'filter_greater { all_rows ; crowd ; 25000 }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_greater { all_rows ; crowd ; 25000 } }', 'tointer': 'select the rows whose crowd record is greater than 25000 . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_greater { all_rows ; crowd ; 25000 } } ; 3 } = true', 'tointer': 'select the rows whose crowd record is greater than 25000 . the number of such rows is 3 .'}
|
eq { count { filter_greater { all_rows ; crowd ; 25000 } } ; 3 } = true
|
select the rows whose crowd record is greater than 25000 . the number of such rows is 3 .
|
3
|
3
|
{'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_greater_0': 0, 'all_rows_4': 4, 'crowd_5': 5, '25000_6': 6, '3_7': 7}
|
{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_greater_0': 'filter_greater', 'all_rows_4': 'all_rows', 'crowd_5': 'crowd', '25000_6': '25000', '3_7': '3'}
|
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_greater_0': [1], 'all_rows_4': [0], 'crowd_5': [0], '25000_6': [0], '3_7': [2]}
|
['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date']
|
[['footscray', '10.23 ( 83 )', 'north melbourne', '11.15 ( 81 )', 'western oval', '13118', '8 august 1970'], ['essendon', '12.16 ( 88 )', 'fitzroy', '14.10 ( 94 )', 'windy hill', '13572', '8 august 1970'], ['richmond', '9.10 ( 64 )', 'melbourne', '18.10 ( 118 )', 'mcg', '25158', '8 august 1970'], ['south melbourne', '16.7 ( 103 )', 'hawthorn', '13.8 ( 86 )', 'lake oval', '17437', '8 august 1970'], ['collingwood', '13.23 ( 101 )', 'carlton', '2.12 ( 24 )', 'victoria park', '39959', '8 august 1970'], ['st kilda', '12.16 ( 88 )', 'geelong', '5.7 ( 37 )', 'vfl park', '29667', '8 august 1970']]
|
gymnastics at the 2007 pan american games
|
https://en.wikipedia.org/wiki/Gymnastics_at_the_2007_Pan_American_Games
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12320552-17.html.csv
|
unique
|
brazil is the only team to win 7 gold medals in gymnastics at the 2007 pan american games .
|
{'scope': 'all', 'row': '2', 'col': '2', 'col_other': '1', 'criterion': 'equal', 'value': '7', 'subset': None}
|
{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'gold', '7'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose gold record is equal to 7 .', 'tostr': 'filter_eq { all_rows ; gold ; 7 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; gold ; 7 } }', 'tointer': 'select the rows whose gold record is equal to 7 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'gold', '7'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose gold record is equal to 7 .', 'tostr': 'filter_eq { all_rows ; gold ; 7 }'}, 'nation'], 'result': 'brazil ( bra )', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; gold ; 7 } ; nation }'}, 'brazil ( bra )'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; gold ; 7 } ; nation } ; brazil ( bra ) }', 'tointer': 'the nation record of this unqiue row is brazil ( bra ) .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; gold ; 7 } } ; eq { hop { filter_eq { all_rows ; gold ; 7 } ; nation } ; brazil ( bra ) } } = true', 'tointer': 'select the rows whose gold record is equal to 7 . there is only one such row in the table . the nation record of this unqiue row is brazil ( bra ) .'}
|
and { only { filter_eq { all_rows ; gold ; 7 } } ; eq { hop { filter_eq { all_rows ; gold ; 7 } ; nation } ; brazil ( bra ) } } = true
|
select the rows whose gold record is equal to 7 . there is only one such row in the table . the nation record of this unqiue row is brazil ( bra ) .
|
6
|
5
|
{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'gold_7': 7, '7_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'nation_9': 9, 'brazil (bra)_10': 10}
|
{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'gold_7': 'gold', '7_8': '7', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'nation_9': 'nation', 'brazil (bra)_10': 'brazil ( bra )'}
|
{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'gold_7': [0], '7_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'nation_9': [2], 'brazil (bra)_10': [3]}
|
['nation', 'gold', 'silver', 'bronze', 'total']
|
[['united states ( usa )', '9', '10', '4', '23'], ['brazil ( bra )', '7', '2', '7', '16'], ['canada ( can )', '4', '2', '3', '9'], ['venezuela ( ven )', '3', '0', '1', '4'], ['puerto rico ( pur )', '2', '0', '3', '5'], ['colombia ( col )', '0', '3', '0', '3'], ['cuba ( cub )', '0', '3', '0', '3'], ['mexico ( mex )', '0', '2', '5', '7'], ['chile ( chi )', '0', '1', '1', '2'], ['total', '25', '23', '24', '72']]
|
american idol ( season 10 )
|
https://en.wikipedia.org/wiki/American_Idol_%28season_10%29
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27455867-1.html.csv
|
unique
|
september 22 , 2010 audition is the one for that month during the first auditions of american idol ( season 10 ) .
|
{'scope': 'all', 'row': '6', 'col': '3', 'col_other': 'n/a', 'criterion': 'fuzzily_match', 'value': 'september', 'subset': None}
|
{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'first audition date', 'september'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose first audition date record fuzzily matches to september .', 'tostr': 'filter_eq { all_rows ; first audition date ; september }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; first audition date ; september } } = true', 'tointer': 'select the rows whose first audition date record fuzzily matches to september . there is only one such row in the table .'}
|
only { filter_eq { all_rows ; first audition date ; september } } = true
|
select the rows whose first audition date record fuzzily matches to september . there is only one such row in the table .
|
2
|
2
|
{'only_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, 'first audition date_4': 4, 'september_5': 5}
|
{'only_1': 'only', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'first audition date_4': 'first audition date', 'september_5': 'september'}
|
{'only_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'first audition date_4': [0], 'september_5': [0]}
|
['episode air date', 'audition city', 'first audition date', 'audition venue', 'callback audition date', 'callback venue', 'golden tickets']
|
[['january 19 , 2011', 'east rutherford , new jersey', 'august 3 , 2010', 'izod center', 'september 28 - 30 , 2010', 'liberty house restaurant', '51'], ['january 20 , 2011', 'new orleans , louisiana', 'july 26 , 2010', 'new orleans arena', 'october 17 - 18 , 2010', 'hilton riverside hotel', '37'], ['january 26 , 2011', 'milwaukee , wisconsin', 'july 21 , 2010', 'bradley center', 'october 2 - 3 , 2010', 'milwaukee art museum', '53'], ['january 27 , 2011', 'nashville , tennessee', 'july 17 , 2010', 'bridgestone arena', 'october 25 - 26 , 2010', 'ryman auditorium', '56 1'], ['february 2 , 2011', 'austin , texas', 'august 11 , 2010', 'frank erwin center', 'october 8 - 9 , 2010', 'barton creek resort & spa', '50'], ['february 3 , 2011', 'los angeles , california', 'september 22 , 2010', 'the forum', 'november 3 - 4 , 2010', 'at & t center', '30 1'], ['february 9 , 2011', 'san francisco , california', 'august 19 , 2010', 'at & t park', 'november 9 - 10 , 2010', 'westin st francis', '47 1']]
|
list of united states national ice hockey team rosters
|
https://en.wikipedia.org/wiki/List_of_United_States_national_ice_hockey_team_rosters
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15715109-14.html.csv
|
superlative
|
phil verchota was the oldest person on the united states ice hockey roster .
|
{'scope': 'all', 'col_superlative': '6', 'row_superlative': '20', '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', 'birthdate'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; birthdate }'}, 'name'], 'result': 'phil verchota', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; birthdate } ; name }'}, 'phil verchota'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmin { all_rows ; birthdate } ; name } ; phil verchota } = true', 'tointer': 'select the row whose birthdate record of all rows is minimum . the name record of this row is phil verchota .'}
|
eq { hop { argmin { all_rows ; birthdate } ; name } ; phil verchota } = true
|
select the row whose birthdate record of all rows is minimum . the name record of this row is phil verchota .
|
3
|
3
|
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'birthdate_5': 5, 'name_6': 6, 'phil verchota_7': 7}
|
{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'birthdate_5': 'birthdate', 'name_6': 'name', 'phil verchota_7': 'phil verchota'}
|
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'birthdate_5': [0], 'name_6': [1], 'phil verchota_7': [2]}
|
['position', 'jersey', 'name', 'height ( cm )', 'weight ( kg )', 'birthdate', 'birthplace', 'previous club / team']
|
[['g', '29', 'marc behrend', '185', '84', '11 january 1961', 'madison , wisconsin', 'university of wisconsin'], ['g', '1', 'bob mason', '185', '82', '22 april 1961', 'international falls , minnesota', 'university of minnesota - duluth'], ['d', '21', 'chris chelios', '185', '86', '25 january 1962', 'evergreen park , illinois', 'university of wisconsin'], ['d', '6', 'mark fusco', '175', '82', '12 march 1961', 'woburn , massachusetts', 'harvard university'], ['d', '22', 'tom hirsch', '193', '95', '27 january 1963', 'minneapolis , minnesota', 'university of minnesota'], ['d', '18', 'al iafrate', '190', '86', '21 march 1966', 'dearborn , michigan', 'belleville bulls ( ohl )'], ['d', '28', 'david h jensen', '185', '86', '3 may 1961', 'minneapolis , minnesota', 'birmingham south stars ( chl )'], ['f', '17', 'scott bjugstad', '185', '84', '2 june 1961', 'minneapolis , minnesota', 'university of minnesota'], ['f', '13', 'bob brooke', '188', '94', '18 december 1960', 'melrose , massachusetts', 'yale university'], ['f', '9', 'scott fusco', '175', '79', '21 january 1963', 'woburn , massachusetts', 'harvard university'], ['f', '10', 'steve griffith', '178', '84', '12 march 1961', 'saint paul , minnesota', 'university of minnesota'], ['f', '19', 'paul guay', '183', '88', '2 september 1963', 'woonsocket , rhode island', 'providence college'], ['f', '23', 'john harrington', '178', '82', '24 may 1957', 'virginia , minnesota', 'university of minnesota - duluth'], ['f', '7', 'david a jensen', '185', '79', '19 august 1965', 'newton , massachusetts', 'belmont hill academy ( isl )'], ['f', '25', 'mark kumpel', '183', '86', 'march 7 , 1961 in', 'wakefield , massachusetts', 'university of lowell'], ['f', '16', 'pat lafontaine', '178', '83', '22 february 1965', 'st louis , missouri', 'verdun juniors ( qmjhl )'], ['f', '26', 'corey millen', '170', '75', '30 march 1964', 'duluth , minnesota', 'university of minnesota'], ['f', '12', 'ed olczyk', '185', '89', '16 august 1966', 'chicago , illinois', 'stratford cullitons ( gojhl )'], ['f', '27', 'gary sampson', '183', '86', '24 august 1959', 'atikokan , ontario', 'boston college'], ['f', '8', 'phil verchota', '188', '89', '28 december 1956', 'preston , minnesota', 'university of minnesota']]
|
swimming at the 2008 summer olympics - women 's 100 metre backstroke
|
https://en.wikipedia.org/wiki/Swimming_at_the_2008_Summer_Olympics_%E2%80%93_Women%27s_100_metre_backstroke
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18625437-4.html.csv
|
comparative
|
kseniya moskvina had a slower time than sophie edington .
|
{'row_1': '8', 'row_2': '7', 'col': '5', 'col_other': '3', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None}
|
{'func': 'greater', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'name', 'kseniya moskvina'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose name record fuzzily matches to kseniya moskvina .', 'tostr': 'filter_eq { all_rows ; name ; kseniya moskvina }'}, 'time'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; name ; kseniya moskvina } ; time }', 'tointer': 'select the rows whose name record fuzzily matches to kseniya moskvina . take the time record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'name', 'sophie edington'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose name record fuzzily matches to sophie edington .', 'tostr': 'filter_eq { all_rows ; name ; sophie edington }'}, 'time'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; name ; sophie edington } ; time }', 'tointer': 'select the rows whose name record fuzzily matches to sophie edington . take the time record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; name ; kseniya moskvina } ; time } ; hop { filter_eq { all_rows ; name ; sophie edington } ; time } } = true', 'tointer': 'select the rows whose name record fuzzily matches to kseniya moskvina . take the time record of this row . select the rows whose name record fuzzily matches to sophie edington . take the time record of this row . the first record is greater than the second record .'}
|
greater { hop { filter_eq { all_rows ; name ; kseniya moskvina } ; time } ; hop { filter_eq { all_rows ; name ; sophie edington } ; time } } = true
|
select the rows whose name record fuzzily matches to kseniya moskvina . take the time record of this row . select the rows whose name record fuzzily matches to sophie edington . take the time record of this row . the first record is greater than the second record .
|
5
|
5
|
{'greater_4': 4, 'result_5': 5, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'name_7': 7, 'kseniya moskvina_8': 8, 'time_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'name_11': 11, 'sophie edington_12': 12, 'time_13': 13}
|
{'greater_4': 'greater', 'result_5': 'true', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'name_7': 'name', 'kseniya moskvina_8': 'kseniya moskvina', 'time_9': 'time', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'name_11': 'name', 'sophie edington_12': 'sophie edington', 'time_13': 'time'}
|
{'greater_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'name_7': [0], 'kseniya moskvina_8': [0], 'time_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'name_11': [1], 'sophie edington_12': [1], 'time_13': [3]}
|
['rank', 'lane', 'name', 'nationality', 'time']
|
[['1', '5', 'natalie coughlin', 'united states', '59.43'], ['2', '4', 'reiko nakamura', 'japan', '59.64'], ['3', '3', 'gemma spofforth', 'great britain', '59.79'], ['4', '6', 'hanae ito', 'japan', '1:00.13'], ['5', '7', 'elizabeth simmonds', 'great britain', '1:00.39'], ['6', '2', 'julia wilkinson', 'canada', '1:00.60'], ['7', '1', 'sophie edington', 'australia', '1:01.05'], ['8', '8', 'kseniya moskvina', 'russia', '1:01.06']]
|
united states house of representatives elections , 2000
|
https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_2000
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1341423-22.html.csv
|
comparative
|
dale kildee has a first elected year which is earlier than that of fred upton .
|
{'row_1': '7', 'row_2': '5', 'col': '4', 'col_other': '2', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None}
|
{'func': 'less', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'incumbent', 'dale kildee'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose incumbent record fuzzily matches to dale kildee .', 'tostr': 'filter_eq { all_rows ; incumbent ; dale kildee }'}, 'first elected'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; incumbent ; dale kildee } ; first elected }', 'tointer': 'select the rows whose incumbent record fuzzily matches to dale kildee . take the first elected record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'incumbent', 'fred upton'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose incumbent record fuzzily matches to fred upton .', 'tostr': 'filter_eq { all_rows ; incumbent ; fred upton }'}, 'first elected'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; incumbent ; fred upton } ; first elected }', 'tointer': 'select the rows whose incumbent record fuzzily matches to fred upton . take the first elected record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; incumbent ; dale kildee } ; first elected } ; hop { filter_eq { all_rows ; incumbent ; fred upton } ; first elected } } = true', 'tointer': 'select the rows whose incumbent record fuzzily matches to dale kildee . take the first elected record of this row . select the rows whose incumbent record fuzzily matches to fred upton . take the first elected record of this row . the first record is less than the second record .'}
|
less { hop { filter_eq { all_rows ; incumbent ; dale kildee } ; first elected } ; hop { filter_eq { all_rows ; incumbent ; fred upton } ; first elected } } = true
|
select the rows whose incumbent record fuzzily matches to dale kildee . take the first elected record of this row . select the rows whose incumbent record fuzzily matches to fred upton . 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, 'dale kildee_8': 8, 'first elected_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'incumbent_11': 11, 'fred upton_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', 'dale kildee_8': 'dale kildee', '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', 'fred upton_12': 'fred upton', '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], 'dale kildee_8': [0], 'first elected_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'incumbent_11': [1], 'fred upton_12': [1], 'first elected_13': [3]}
|
['district', 'incumbent', 'party', 'first elected', 'results', 'candidates']
|
[['michigan 1', 'bart stupak', 'democratic', '1992', 're - elected', 'bart stupak ( d ) 59 % chuck yob ( r ) 41 %'], ['michigan 2', 'pete hoekstra', 'republican', '1992', 're - elected', 'pete hoekstra ( r ) 65 % bob shrauger ( d ) 34 %'], ['michigan 3', 'vern ehlers', 'republican', '1993', 're - elected', 'vern ehlers ( r ) 65 % timothy steele ( d ) 34 %'], ['michigan 5', 'james barcia', 'democratic', '1992', 're - elected', 'james barcia ( d ) 75 % ronald actis ( r ) 24 %'], ['michigan 6', 'fred upton', 'republican', '1986', 're - elected', 'fred upton ( r ) 68 % james bupp ( d ) 30 %'], ['michigan 7', 'nick smith', 'republican', '1992', 're - elected', 'nick smith ( r ) 62 % jennie crittendon ( d ) 36 %'], ['michigan 9', 'dale kildee', 'democratic', '1976', 're - elected', 'dale kildee ( d ) 62 % grant garrett ( r ) 36 %'], ['michigan 10', 'david bonior', 'democratic', '1976', 're - elected', 'david bonior ( d ) 65 % tom turner ( r ) 34 %'], ['michigan 13', 'lynn rivers', 'democratic', '1994', 're - elected', 'lynn rivers ( d ) 65 % carl barry ( r ) 33 %'], ['michigan 14', 'john conyers jr', 'democratic', '1964', 're - elected', 'john conyers jr ( d ) 90 % william ashe ( r ) 10 %']]
|
united states house of representatives elections in virginia , 2008
|
https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections_in_Virginia%2C_2008
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-17503169-1.html.csv
|
majority
|
the majority of these politicians were successfully re-elected in 2008 .
|
{'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': 're - election', 'subset': None}
|
{'func': 'most_str_eq', 'args': ['all_rows', '2008 status', 're - election'], 'result': True, 'ind': 0, 'tointer': 'for the 2008 status records of all rows , most of them fuzzily match to re - election .', 'tostr': 'most_eq { all_rows ; 2008 status ; re - election } = true'}
|
most_eq { all_rows ; 2008 status ; re - election } = true
|
for the 2008 status records of all rows , most of them fuzzily match to re - election .
|
1
|
1
|
{'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, '2008 status_3': 3, 're - election_4': 4}
|
{'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', '2008 status_3': '2008 status', 're - election_4': 're - election'}
|
{'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], '2008 status_3': [0], 're - election_4': [0]}
|
['district', 'incumbent', '2008 status', 'democratic', 'republican', 'independent green', 'libertarian', 'other party']
|
[['1', 'rob wittman', 're - election', 'bill day', 'rob wittman', 'none', 'nathan larson', 'none'], ['2', 'thelma drake', 're - election', 'glenn nye', 'thelma drake', 'none', 'none', 'none'], ['3', 'robert c scott', 're - election', 'robert c scott', 'none', 'none', 'none', 'none'], ['4', 'randy forbes', 're - election', 'andrea miller', 'randy forbes', 'none', 'none', 'none'], ['5', 'virgil goode', 're - election', 'tom perriello', 'virgil goode', 'none', 'none', 'none'], ['6', 'bob goodlatte', 're - election', 'sam rasoul', 'bob goodlatte', 'none', 'none', 'janice lee allen'], ['7', 'eric cantor', 're - election', 'anita hartke', 'eric cantor', 'none', 'none', 'none'], ['8', 'jim moran', 're - election', 'jim moran', 'mark ellmore', 'j ron fisher', 'none', 'none'], ['9', 'rick boucher', 're - election', 'rick boucher', 'none', 'none', 'none', 'none'], ['10', 'frank wolf', 're - election', 'judy feder', 'frank wolf', 'none', 'none', 'neeraj nigam']]
|
1965 - 66 segunda división
|
https://en.wikipedia.org/wiki/1965%E2%80%9366_Segunda_Divisi%C3%B3n
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17832085-4.html.csv
|
aggregation
|
in the 1965 - 66 segunda división , the average number of losses was 10.94 .
|
{'scope': 'all', 'col': '7', 'type': 'average', 'result': '10.94', 'subset': None}
|
{'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'losses'], 'result': '10.94', 'ind': 0, 'tostr': 'avg { all_rows ; losses }'}, '10.94'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; losses } ; 10.94 } = true', 'tointer': 'the average of the losses record of all rows is 10.94 .'}
|
round_eq { avg { all_rows ; losses } ; 10.94 } = true
|
the average of the losses record of all rows is 10.94 .
|
2
|
2
|
{'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'losses_4': 4, '10.94_5': 5}
|
{'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'losses_4': 'losses', '10.94_5': '10.94'}
|
{'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'losses_4': [0], '10.94_5': [1]}
|
['position', 'club', 'played', 'points', 'wins', 'draws', 'losses', 'goals for', 'goals against', 'goal difference']
|
[['1', 'hércules cf', '30', '39', '16', '7', '7', '44', '24', '+ 20'], ['2', 'granada cf', '30', '37', '16', '5', '9', '40', '29', '+ 11'], ['3', 'algeciras cf', '30', '35', '14', '7', '9', '42', '29', '+ 13'], ['4', 'real valladolid', '30', '35', '13', '9', '8', '49', '32', '+ 17'], ['5', 'levante ud', '30', '34', '13', '8', '9', '42', '22', '+ 20'], ['6', 'cd mestalla', '30', '33', '10', '13', '7', '45', '44', '+ 1'], ['7', 'cf calvo sotelo', '30', '32', '13', '6', '11', '33', '36', '- 3'], ['8', 'cd tenerife', '30', '32', '13', '6', '11', '40', '34', '+ 6'], ['9', 'rayo vallecano', '30', '31', '12', '7', '11', '37', '26', '+ 11'], ['10', 'real murcia', '30', '29', '12', '5', '13', '31', '37', '- 6'], ['11', 'recreativo de huelva', '30', '29', '11', '7', '12', '31', '30', '+ 1'], ['12', 'cádiz cf', '30', '27', '10', '7', '13', '25', '28', '- 3'], ['13', 'cd constancia', '30', '26', '10', '6', '14', '34', '49', '- 15'], ['14', 'atlético ceuta', '30', '25', '11', '3', '16', '35', '47', '- 12'], ['15', 'melilla cf', '30', '20', '7', '6', '17', '26', '51', '- 25'], ['16', 'cd badajoz', '30', '16', '4', '8', '18', '22', '58', '- 36']]
|
wru division one east
|
https://en.wikipedia.org/wiki/WRU_Division_One_East
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12784856-5.html.csv
|
ordinal
|
for wru division one east , the 2nd highest number of losses was by fleur de lys rfc .
|
{'row': '11', 'col': '4', 'order': '2', 'col_other': '1', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None}
|
{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'lost', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; lost ; 2 }'}, 'club'], 'result': 'fleur de lys rfc', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; lost ; 2 } ; club }'}, 'fleur de lys rfc'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; lost ; 2 } ; club } ; fleur de lys rfc } = true', 'tointer': 'select the row whose lost record of all rows is 2nd maximum . the club record of this row is fleur de lys rfc .'}
|
eq { hop { nth_argmax { all_rows ; lost ; 2 } ; club } ; fleur de lys rfc } = true
|
select the row whose lost record of all rows is 2nd maximum . the club record of this row is fleur de lys rfc .
|
3
|
3
|
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'lost_5': 5, '2_6': 6, 'club_7': 7, 'fleur de lys rfc_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', 'lost_5': 'lost', '2_6': '2', 'club_7': 'club', 'fleur de lys rfc_8': 'fleur de lys rfc'}
|
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'lost_5': [0], '2_6': [0], 'club_7': [1], 'fleur de lys rfc_8': [2]}
|
['club', 'played', 'drawn', 'lost', 'points for', 'points against', 'tries for', 'tries against', 'try bonus', 'losing bonus', 'points']
|
[['pontypool rfc', '22', '2', '2', '648', '274', '81', '32', '12', '1', '89'], ['caerphilly rfc', '22', '2', '4', '482', '316', '56', '37', '7', '3', '78'], ['blackwood rfc', '22', '2', '6', '512', '378', '60', '42', '8', '3', '71'], ['bargoed rfc', '22', '0', '8', '538', '449', '72', '52', '10', '4', '70'], ['uwic rfc', '22', '2', '7', '554', '408', '71', '50', '6', '2', '64'], ['llanharan rfc', '22', '1', '12', '436', '442', '44', '51', '1', '7', '46'], ['newbridge rfc', '22', '2', '11', '355', '400', '36', '47', '2', '3', '45'], ['rumney rfc', '22', '2', '12', '435', '446', '56', '52', '5', '3', '44'], ['newport saracens rfc', '22', '0', '14', '344', '499', '45', '64', '2', '3', '37'], ['beddau rfc', '22', '0', '15', '310', '483', '32', '61', '2', '4', '34'], ['fleur de lys rfc', '22', '1', '16', '300', '617', '34', '77', '2', '4', '28'], ['llantrisant rfc', '22', '0', '18', '402', '592', '55', '77', '4', '6', '26']]
|
premier league of bosnia and herzegovina
|
https://en.wikipedia.org/wiki/Premier_League_of_Bosnia_and_Herzegovina
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1474099-1.html.csv
|
superlative
|
sarajevo b , c is the club of bosnia and herzegovina that has the highest number of seasons in the top division .
|
{'scope': 'all', 'col_superlative': '4', 'row_superlative': '9', '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', 'number of seasons in top division'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; number of seasons in top division }'}, 'club'], 'result': 'sarajevo b , c', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; number of seasons in top division } ; club }'}, 'sarajevo b , c'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; number of seasons in top division } ; club } ; sarajevo b , c } = true', 'tointer': 'select the row whose number of seasons in top division record of all rows is maximum . the club record of this row is sarajevo b , c .'}
|
eq { hop { argmax { all_rows ; number of seasons in top division } ; club } ; sarajevo b , c } = true
|
select the row whose number of seasons in top division record of all rows is maximum . the club record of this row is sarajevo b , c .
|
3
|
3
|
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'number of seasons in top division_5': 5, 'club_6': 6, 'sarajevo b , c_7': 7}
|
{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'number of seasons in top division_5': 'number of seasons in top division', 'club_6': 'club', 'sarajevo b , c_7': 'sarajevo b , c'}
|
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'number of seasons in top division_5': [0], 'club_6': [1], 'sarajevo b , c_7': [2]}
|
['club', 'position in 2012 - 13', 'first season in top division', 'number of seasons in top division', 'number of seasons in premier league a', 'first season of current spell in top division', 'top division titles', 'last top division title']
|
[['borac b', '003 3rd', '1961 - 62', '23', '9', '2008 - 09', '1', '2010 - 11'], ['čelik b , c', '004 4th', '1966 - 67', '30', '13', '2000 - 01', '3 d', '1996 - 97'], ['gošk ( r )', '015 15th', '2011 - 12', '2', '2', '2011 - 12', '0', 'n / a'], ['gradina ( r )', '016 16th', '2012 - 13', '1', '1', '2012 - 13', '0', 'n / a'], ['leotar b , c', '008 8th', '2002 - 03', '11', '11', '2002 - 03', '1', '2002 - 03'], ['olimpic', '005 5th', '2000 - 01', '6', '6', '2009 - 10', '0', 'n / a'], ['radnik', '012 12th', '2006 - 07', '3', '3', '2012 - 13', '1 e', '1998 - 99'], ['rudar', '011 11th', '2009 - 10', '4', '4', '2009 - 10', '0', 'n / a'], ['sarajevo b , c', '002 2nd', '1947 - 48', '55', '13', '1958 - 59', '4 f', '2006 - 07'], ['slavija', '007 7th', '1930', '17', '9', '2004 - 05', '0', 'n / a'], ['široki brijeg b , c', '006 6th', '2000 - 01', '13', '13', '2000 - 01', '6 g', '2005 - 06'], ['travnik', '014 14th', '2000 - 01', '10', '10', '2007 - 08', '0', 'n / a'], ['velež b', '013 13th', '1952 - 53', '48', '10', '2006 - 07', '0', 'n / a'], ['zrinjski b , c', '009 9th', '2000 - 01', '13', '13', '2000 - 01', '2', '2008 - 09'], ['zvijezda', '010 10th', '2008 - 09', '5', '5', '2008 - 09', '0', 'n / a']]
|
max biaggi
|
https://en.wikipedia.org/wiki/Max_Biaggi
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1694580-3.html.csv
|
count
|
there were two years where max biaggi raced 28 times .
|
{'scope': 'all', 'criterion': 'equal', 'value': '28', 'result': '2', 'col': '2', 'subset': None}
|
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'race', '28'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose race record is equal to 28 .', 'tostr': 'filter_eq { all_rows ; race ; 28 }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; race ; 28 } }', 'tointer': 'select the rows whose race record is equal to 28 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; race ; 28 } } ; 2 } = true', 'tointer': 'select the rows whose race record is equal to 28 . the number of such rows is 2 .'}
|
eq { count { filter_eq { all_rows ; race ; 28 } } ; 2 } = true
|
select the rows whose race record is equal to 28 . 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, 'race_5': 5, '28_6': 6, '2_7': 7}
|
{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'race_5': 'race', '28_6': '28', '2_7': '2'}
|
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'race_5': [0], '28_6': [0], '2_7': [2]}
|
['season', 'race', 'podium', 'pole', 'flap']
|
[['2007', '25', '17', '0', '5'], ['2008', '28', '7', '0', '1'], ['2009', '28', '9', '0', '1'], ['2010', '26', '14', '2', '2'], ['2011', '21', '12', '2', '5'], ['2012', '27', '11', '1', '5'], ['total', '155', '70', '5', '19']]
|
sophie ferguson
|
https://en.wikipedia.org/wiki/Sophie_Ferguson
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15179071-3.html.csv
|
count
|
two tournaments were played on a carpet surface by sophie ferguson .
|
{'scope': 'all', 'criterion': 'equal', 'value': 'carpet', 'result': '2', 'col': '4', 'subset': None}
|
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'surface', 'carpet'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose surface record fuzzily matches to carpet .', 'tostr': 'filter_eq { all_rows ; surface ; carpet }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; surface ; carpet } }', 'tointer': 'select the rows whose surface record fuzzily matches to carpet . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; surface ; carpet } } ; 2 } = true', 'tointer': 'select the rows whose surface record fuzzily matches to carpet . the number of such rows is 2 .'}
|
eq { count { filter_eq { all_rows ; surface ; carpet } } ; 2 } = true
|
select the rows whose surface record fuzzily matches to carpet . 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, 'surface_5': 5, 'carpet_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', 'surface_5': 'surface', 'carpet_6': 'carpet', '2_7': '2'}
|
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'surface_5': [0], 'carpet_6': [0], '2_7': [2]}
|
['outcome', 'date', 'tournament', 'surface', 'partner', 'opponents in the final', 'score']
|
[['runner - up', '14 august 2005', 'wuxi , china', 'hard', 'casey dellacqua', 'mi - ra jeon wynne prakusya', '2 - 6 6 - 7 ( 6 )'], ['runner - up', '12 november 2006', 'mount gambier , australia', 'hard', 'daniella dominikovic', 'natalie grandin christina wheeler', '4 - 6 6 - 4 4 - 6'], ['runner - up', '20 april 2007', 'bari , italy', 'clay', 'katarina kachlikova', 'veronika kapshay mariya koryttseva', '5 - 7 2 - 6'], ['winner', '19 june 2007', 'noto , japan', 'carpet', 'anne yelsey', 'natsumi hamamura maria tanaka', '7 - 6 ( 8 ) 6 - 1'], ['runner - up', '16 november 2007', 'nuriootpa , australia', 'hard', 'trudi musgrave', 'natalie grandin robin stephenson', '4 - 6 5 - 7'], ['runner - up', '23 may 2007', 'mount gambier , australia', 'hard', 'trudi musgrave', 'antonia matic monica niculescu', '7 - 5 3 - 6'], ['runner - up', '16 may 2008', 'caserta , italy', 'clay', 'christina wheeler', 'xinyun han yi - fan xu', '6 - 4 4 - 6'], ['winner', '3 may 2009', 'gifu , japan', 'carpet', 'aiko nakamura', 'misaki doi kurumi nara', '6 - 2 6 - 1'], ['winner', '6 june 2009', 'brno , czech republic', 'clay', 'trudi musgrave', 'karin morgosova romana caroline tabak', '6 - 4 6 - 1'], ['runner - up', '5 march 2010', 'sydney , australia', 'hard', 'trudi musgrave', 'casey dellacqua jessica moore', 'w / o'], ['winner', '25 june 2010', 'rome , italy', 'clay', 'trudi musgrave', 'claudia giovine valentina sulpizio', '6 - 0 6 - 3'], ['winner', '09 - may - 2011', 'reggio emilia , italy', 'clay', 'sally peers', 'claudia giovine maria irigoyen', '6 - 4 6 - 1'], ['winner', '30 - may - 2011', 'rome - tiro a volo , italy', 'clay', 'sally peers', 'magda linette liana ungur', 'w / o']]
|
tax parity for health plan beneficiaries act
|
https://en.wikipedia.org/wiki/Tax_Parity_for_Health_Plan_Beneficiaries_Act
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13829540-1.html.csv
|
count
|
for the tax parity for health plan beneficiaries act , there were 5 occasions where it was introduced in the month of june .
|
{'scope': 'all', 'criterion': 'equal', 'value': 'june', 'result': '5', 'col': '3', 'subset': None}
|
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date introduced', 'june'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose date introduced record fuzzily matches to june .', 'tostr': 'filter_eq { all_rows ; date introduced ; june }'}], 'result': '5', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; date introduced ; june } }', 'tointer': 'select the rows whose date introduced record fuzzily matches to june . the number of such rows is 5 .'}, '5'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; date introduced ; june } } ; 5 } = true', 'tointer': 'select the rows whose date introduced record fuzzily matches to june . the number of such rows is 5 .'}
|
eq { count { filter_eq { all_rows ; date introduced ; june } } ; 5 } = true
|
select the rows whose date introduced record fuzzily matches to june . 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, 'date introduced_5': 5, 'june_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', 'date introduced_5': 'date introduced', 'june_6': 'june', '5_7': '5'}
|
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'date introduced_5': [0], 'june_6': [0], '5_7': [2]}
|
['congress', 'bill number ( s )', 'date introduced', 'sponsor ( s )', 'of cosponsors', 'latest status']
|
[['112th congress', 's 1171', 'june 9 , 2011', 'sen charles e schumer ( d - ny )', '19', 'referred to the senate committee on finance'], ['112th congress', 'hr 2088', 'june 2 , 2011', 'rep jim mcdermott ( d - wa )', '74', 'referred to the house committee on ways and means'], ['111th congress', 's 1153', 'may 21 , 2009', 'sen charles e schumer ( d - ny )', '23', 'died in the senate committee on finance'], ['111th congress', 'hr 2625', 'june 2 , 2009', 'rep jim mcdermott ( d - wa )', '133', 'died in the house committee on ways and means'], ['110th congress', 's 1556', 'june 6 , 2007', 'sen gordon h smith ( r - or )', '25', 'died in the senate committee on finance'], ['110th congress', 'hr 1820', 'march 29 , 2007', 'rep jim mcdermott ( d - wa )', '119', 'died in the house committee on ways and means'], ['109th congress', 's 1360', 'june 30 , 2005', 'sen gordon h smith ( r - or )', '12', 'died in the senate committee on finance'], ['108th congress', 's 1702', 'october 2 , 2003', 'sen gordon h smith ( r - or )', '9', 'died in the senate committee on finance']]
|
list of west indies test wicket - keepers
|
https://en.wikipedia.org/wiki/List_of_West_Indies_Test_wicket-keepers
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27771406-1.html.csv
|
aggregation
|
the average number of catches for all west indies test wicket - keepers is 19.5 .
|
{'scope': 'all', 'col': '6', 'type': 'average', 'result': '19.5', 'subset': None}
|
{'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'catches'], 'result': '19.5', 'ind': 0, 'tostr': 'avg { all_rows ; catches }'}, '19.5'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; catches } ; 19.5 } = true', 'tointer': 'the average of the catches record of all rows is 19.5 .'}
|
round_eq { avg { all_rows ; catches } ; 19.5 } = true
|
the average of the catches record of all rows is 19.5 .
|
2
|
2
|
{'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'catches_4': 4, '19.5_5': 5}
|
{'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'catches_4': 'catches', '19.5_5': '19.5'}
|
{'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'catches_4': [0], '19.5_5': [1]}
|
['no', 'player', 'club', 'test career', 'tests', 'catches', 'stumpings', 'total dismissals']
|
[['2', 'errol hunte', 'trinidad and tobago', '1930', '3', '5', '0', '5'], ['3', 'ivan barrow', 'jamaica', '1930 - 1939', '11', '17', '5', '22'], ['4', 'cyril christiani', 'british guiana', '1935', '4', '6', '1', '7'], ['8', 'alfred binns', 'jamaica', '1953 - 1956', '5', '14', '3', '17'], ['9', 'ralph legall', 'trinidad and tobago', '1953', '4', '8', '1', '9'], ['10', 'clifford mcwatt', 'british guiana', '1954 - 1955', '6', '8', '1', '9'], ['11', 'clairmonte depeiaza', 'barbados', '1955 - 1956', '5', '7', '4', '11'], ['13', 'gerry alexander', 'jamaica', '1957 - 1961', '25', '85', '5', '90'], ['14', 'jackie hendriks', 'jamaica', '1962 - 1969', '20', '42', '5', '47'], ['15', 'ivor mendonca', 'guyana', '1962', '2', '8', '2', '10'], ['16', 'david allan', 'barbados', '1962 - 1966', '5', '15', '3', '18'], ['18', 'mike findlay', 'windward islands', '1969 - 1973', '10', '19', '2', '21']]
|
1962 - 63 illinois fighting illini men 's basketball team
|
https://en.wikipedia.org/wiki/1962%E2%80%9363_Illinois_Fighting_Illini_men%27s_basketball_team
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-22824297-1.html.csv
|
unique
|
tony latham is the only player on 1962 - 63 illinois fighting illini men 's basketball team that has a height of 6-10 .
|
{'scope': 'all', 'row': '8', 'col': '6', 'col_other': '2', 'criterion': 'equal', 'value': '6 - 10', 'subset': None}
|
{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'height', '6 - 10'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose height record fuzzily matches to 6 - 10 .', 'tostr': 'filter_eq { all_rows ; height ; 6 - 10 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; height ; 6 - 10 } }', 'tointer': 'select the rows whose height record fuzzily matches to 6 - 10 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'height', '6 - 10'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose height record fuzzily matches to 6 - 10 .', 'tostr': 'filter_eq { all_rows ; height ; 6 - 10 }'}, 'player'], 'result': 'tony latham', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; height ; 6 - 10 } ; player }'}, 'tony latham'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; height ; 6 - 10 } ; player } ; tony latham }', 'tointer': 'the player record of this unqiue row is tony latham .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; height ; 6 - 10 } } ; eq { hop { filter_eq { all_rows ; height ; 6 - 10 } ; player } ; tony latham } } = true', 'tointer': 'select the rows whose height record fuzzily matches to 6 - 10 . there is only one such row in the table . the player record of this unqiue row is tony latham .'}
|
and { only { filter_eq { all_rows ; height ; 6 - 10 } } ; eq { hop { filter_eq { all_rows ; height ; 6 - 10 } ; player } ; tony latham } } = true
|
select the rows whose height record fuzzily matches to 6 - 10 . there is only one such row in the table . the player record of this unqiue row is tony latham .
|
6
|
5
|
{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'height_7': 7, '6 - 10_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'player_9': 9, 'tony latham_10': 10}
|
{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'height_7': 'height', '6 - 10_8': '6 - 10', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'player_9': 'player', 'tony latham_10': 'tony latham'}
|
{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'height_7': [0], '6 - 10_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'player_9': [2], 'tony latham_10': [3]}
|
['no', 'player', 'hometown', 'class', 'position', 'height', 'weight']
|
[['10', 'larry bauer', 'springfield , illinois', 'so', 'forward', '6 - 7', '207'], ['11', 'bob meadows', 'collinsville , illinois', 'so', 'guard', '5 - 7', '157'], ['12', 'tal brody', 'trenton , new jersey / central high school', 'so', 'guard', '6 - 2', '165'], ['14', 'john love', 'ottawa , illinois', 'jr', 'forward', '6 - 3', '199'], ['22', 'jay lovelace', 'carbondale , illinois', 'sr', 'guard', '6 - 0', '164'], ['25', 'bill burwell', 'brooklyn , new york / boys high school', 'sr', 'center', '6 - 8', '227'], ['30', 'jeff ferguson', 'benton , illinois', 'sr', 'forward', '6 - 3', '195'], ['31', 'tony latham', 'waukegan , illinois', 'so', 'guard', '6 - 10', '163'], ['32', 'bill edwards', 'windsor , illinois', 'jr', 'guard', '6 - 2', '208'], ['33', 'bogie redmon', 'collinsville , illinois', 'so', 'forward', '6 - 5', '218'], ['34', 'bill mckeown', 'clinton , illinois', 'so', 'guard', '6 - 2', '185'], ['35', 'skip thoren', 'rockford , illinois / rockford east high school', 'so', 'center', '6 - 8', '201'], ['40', 'dave downey', 'canton , illinois', 'sr', 'forward', '6 - 4', '204']]
|
nevada gaming area
|
https://en.wikipedia.org/wiki/Nevada_gaming_area
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-25438110-5.html.csv
|
count
|
two of the counties in the nevada gaming area are serviced by the i-80 road .
|
{'scope': 'all', 'criterion': 'equal', 'value': 'i - 80', 'result': '2', 'col': '3', 'subset': None}
|
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'road', 'i - 80'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose road record fuzzily matches to i - 80 .', 'tostr': 'filter_eq { all_rows ; road ; i - 80 }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; road ; i - 80 } }', 'tointer': 'select the rows whose road record fuzzily matches to i - 80 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; road ; i - 80 } } ; 2 } = true', 'tointer': 'select the rows whose road record fuzzily matches to i - 80 . the number of such rows is 2 .'}
|
eq { count { filter_eq { all_rows ; road ; i - 80 } } ; 2 } = true
|
select the rows whose road record fuzzily matches to i - 80 . 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, 'road_5': 5, 'i - 80_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', 'road_5': 'road', 'i - 80_6': 'i - 80', '2_7': '2'}
|
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'road_5': [0], 'i - 80_6': [0], '2_7': [2]}
|
['casinos', 'county', 'road', '1 - jul - 08', 'fy07 millions', 'fy08 millions', 'fy09 millions']
|
[['149', 'clark', 'i - 15', '1865746', '10538', '10172', '9081'], ['32', 'washoe', 'i - 80', '410443', '1045', '977', '856'], ['17', 'elko', 'i - 80', '47071', '324', '303', '279'], ['5', 'south lake tahoe', 'route 50', '45180', '283', '307', '264'], ['14', 'carson valley', 'route 395', '54867', '120', '114', '102']]
|
yanam
|
https://en.wikipedia.org/wiki/Yanam
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1404939-5.html.csv
|
majority
|
most of the colonies in the yanam have a treaty of cession of 28 may 1956 .
|
{'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'equal', 'value': '28 may 1956', 'subset': None}
|
{'func': 'most_str_eq', 'args': ['all_rows', 'treaty of cession', '28 may 1956'], 'result': True, 'ind': 0, 'tointer': 'for the treaty of cession records of all rows , most of them fuzzily match to 28 may 1956 .', 'tostr': 'most_eq { all_rows ; treaty of cession ; 28 may 1956 } = true'}
|
most_eq { all_rows ; treaty of cession ; 28 may 1956 } = true
|
for the treaty of cession records of all rows , most of them fuzzily match to 28 may 1956 .
|
1
|
1
|
{'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'treaty of cession_3': 3, '28 may 1956_4': 4}
|
{'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'treaty of cession_3': 'treaty of cession', '28 may 1956_4': '28 may 1956'}
|
{'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'treaty of cession_3': [0], '28 may 1956_4': [0]}
|
['colony', 'liberation', 'de facto transfer', 'treaty of cession', 'de jure transfer', 'merger']
|
[['pondichéry', '-', '1 november 1954', '28 may 1956', '16 august 1963', '1 july 1963'], ['chandernagore', '-', '26 june 1949', '28 february 1951', '9 june 1952', '1 october 1954'], ['karikal', '-', '1 november 1954', '28 may 1956', '16 august 1963', '1 july 1963'], ['mahé', '16 june 1954', '1 november 1954', '28 may 1956', '16 august 1963', '1 july 1963'], ['yanaon', '13 june 1954', '1 november 1954', '28 may 1956', '16 august 1963', '1 july 1963']]
|
list of districts of west bengal
|
https://en.wikipedia.org/wiki/List_of_districts_of_West_Bengal
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2527063-3.html.csv
|
superlative
|
out of all the districts in west bengal , kolkata has the worst growth rate .
|
{'scope': 'all', 'col_superlative': '4', 'row_superlative': '10', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '2', 'subset': None}
|
{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmin', 'args': ['all_rows', 'growth rate'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; growth rate }'}, 'district'], 'result': 'kolkata', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; growth rate } ; district }'}, 'kolkata'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmin { all_rows ; growth rate } ; district } ; kolkata } = true', 'tointer': 'select the row whose growth rate record of all rows is minimum . the district record of this row is kolkata .'}
|
eq { hop { argmin { all_rows ; growth rate } ; district } ; kolkata } = true
|
select the row whose growth rate record of all rows is minimum . the district record of this row is kolkata .
|
3
|
3
|
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'growth rate_5': 5, 'district_6': 6, 'kolkata_7': 7}
|
{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'growth rate_5': 'growth rate', 'district_6': 'district', 'kolkata_7': 'kolkata'}
|
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'growth rate_5': [0], 'district_6': [1], 'kolkata_7': [2]}
|
['rank', 'district', 'population', 'growth rate', 'sex ratio', 'literacy', 'density / km']
|
[['2', 'north 24 parganas', '10082852', '12.86', '949', '84.95', '2463'], ['6', 'south 24 parganas', '8153176', '18.05', '949', '78.57', '819'], ['7', 'barddhaman', '7723663', '12.01', '943', '77.15', '1100'], ['9', 'murshidabad', '7102430', '21.07', '957', '67.53', '1334'], ['14', 'west midnapore', '5943300', '14.44', '960', '79.04', '636'], ['16', 'hooghly', '5520389', '9.49', '958', '82.55', '1753'], ['18', 'nadia', '5168488', '12.24', '947', '75.58', '1316'], ['20', 'east midnapore', '5094238', '15.32', '936', '87.66', '1076'], ['23', 'haora', '4841638', '13.31', '935', '83.85', '3300'], ['35', 'kolkata', '4486679', '- 1.88', '899', '87.14', '24252'], ['58', 'maldah', '3997970', '21.50', '939', '62.71', '1071'], ['66', 'jalpaiguri', '3869675', '13.77', '954', '73.79', '621'], ['80', 'bankura', '3596292', '12.64', '954', '70.95', '523'], ['84', 'birbhum', '3502387', '16.15', '956', '70.90', '771'], ['124', 'north dinajpur', '3000849', '22.90', '936', '60.13', '956'], ['129', 'puruliya', '2927965', '15.43', '955', '65.38', '468'], ['136', 'kochbihar', '2822780', '13.86', '942', '75.49', '833'], ['257', 'darjiling', '1842034', '14.47', '971', '79.92', '585']]
|
2004 - 05 isu junior grand prix
|
https://en.wikipedia.org/wiki/2004%E2%80%9305_ISU_Junior_Grand_Prix
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12392757-3.html.csv
|
aggregation
|
for the 2004 - 05 isu junior grand prix the total number of gold medals was 36 .
|
{'scope': 'all', 'col': '3', 'type': 'sum', 'result': '36', 'subset': None}
|
{'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'gold'], 'result': '36', 'ind': 0, 'tostr': 'sum { all_rows ; gold }'}, '36'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; gold } ; 36 } = true', 'tointer': 'the sum of the gold record of all rows is 36 .'}
|
round_eq { sum { all_rows ; gold } ; 36 } = true
|
the sum of the gold record of all rows is 36 .
|
2
|
2
|
{'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'gold_4': 4, '36_5': 5}
|
{'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'gold_4': 'gold', '36_5': '36'}
|
{'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'gold_4': [0], '36_5': [1]}
|
['rank', 'nation', 'gold', 'silver', 'bronze', 'total']
|
[['1', 'united states', '8', '13', '15', '36'], ['2', 'russia', '10', '7', '7', '24'], ['3', 'japan', '7', '4', '3', '14'], ['3', 'canada', '4', '6', '4', '14'], ['4', 'italy', '2', '1', '1', '4'], ['5', 'south korea', '1', '2', '0', '3'], ['5', 'france', '1', '0', '2', '3'], ['6', 'finland', '2', '0', '0', '2'], ['6', 'sweden', '0', '0', '2', '2'], ['6', 'switzerland', '1', '1', '0', '2'], ['6', 'israel', '0', '1', '1', '2'], ['7', 'czech republic', '0', '1', '0', '1'], ['7', 'ukraine', '0', '0', '1', '1']]
|
2007 german motorcycle grand prix
|
https://en.wikipedia.org/wiki/2007_German_motorcycle_Grand_Prix
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12262589-1.html.csv
|
majority
|
most of the drivers completed 30 laps drive during the 2007 german motorcycle grand prix .
|
{'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': '30', 'subset': None}
|
{'func': 'most_eq', 'args': ['all_rows', 'laps', '30'], 'result': True, 'ind': 0, 'tointer': 'for the laps records of all rows , most of them are equal to 30 .', 'tostr': 'most_eq { all_rows ; laps ; 30 } = true'}
|
most_eq { all_rows ; laps ; 30 } = true
|
for the laps records of all rows , most of them are equal to 30 .
|
1
|
1
|
{'most_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'laps_3': 3, '30_4': 4}
|
{'most_eq_0': 'most_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'laps_3': 'laps', '30_4': '30'}
|
{'most_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'laps_3': [0], '30_4': [0]}
|
['rider', 'manufacturer', 'laps', 'time / retired', 'grid']
|
[['dani pedrosa', 'honda', '30', '41:53.196', '2'], ['loris capirossi', 'ducati', '30', '+ 13.166', '7'], ['nicky hayden', 'honda', '30', '+ 16.771', '14'], ['colin edwards', 'yamaha', '30', '+ 18.299', '13'], ['casey stoner', 'ducati', '30', '+ 31.426', '1'], ['marco melandri', 'honda', '30', '+ 31.917', '3'], ['john hopkins', 'suzuki', '30', '+ 33.395', '5'], ['anthony west', 'kawasaki', '30', '+ 41.194', '12'], ['alex hofmann', 'ducati', '30', '+ 43.214', '16'], ['michel fabrizio', 'honda', '30', '+ 44.459', '17'], ['chris vermeulen', 'suzuki', '30', '+ 1:01.894', '11'], ['kurtis roberts', 'kr212v', '30', '+ 1:10.721', '19'], ['makoto tamada', 'yamaha', '28', '+ 2 laps', '18'], ['carlos checa', 'honda', '27', '+ 3 laps', '15'], ['randy de puniet', 'kawasaki', '29', 'retirement', '4'], ['shinya nakano', 'honda', '19', 'retirement', '10'], ['alex barros', 'ducati', '9', 'accident', '8'], ['valentino rossi', 'yamaha', '5', 'accident', '6'], ['sylvain guintoli', 'ducati', '3', 'accident', '9']]
|
kingsport mets
|
https://en.wikipedia.org/wiki/Kingsport_Mets
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1196050-1.html.csv
|
unique
|
1977 was the only year that bob didier was the manager of the kingsport mets .
|
{'scope': 'all', 'row': '4', 'col': '4', 'col_other': '1', 'criterion': 'equal', 'value': 'bob didier', 'subset': None}
|
{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'manager', 'bob didier'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose manager record fuzzily matches to bob didier .', 'tostr': 'filter_eq { all_rows ; manager ; bob didier }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; manager ; bob didier } }', 'tointer': 'select the rows whose manager record fuzzily matches to bob didier . there is only one such row in the table .'}, {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'manager', 'bob didier'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose manager record fuzzily matches to bob didier .', 'tostr': 'filter_eq { all_rows ; manager ; bob didier }'}, 'year'], 'result': '1977', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; manager ; bob didier } ; year }'}, '1977'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; manager ; bob didier } ; year } ; 1977 }', 'tointer': 'the year record of this unqiue row is 1977 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; manager ; bob didier } } ; eq { hop { filter_eq { all_rows ; manager ; bob didier } ; year } ; 1977 } } = true', 'tointer': 'select the rows whose manager record fuzzily matches to bob didier . there is only one such row in the table . the year record of this unqiue row is 1977 .'}
|
and { only { filter_eq { all_rows ; manager ; bob didier } } ; eq { hop { filter_eq { all_rows ; manager ; bob didier } ; year } ; 1977 } } = true
|
select the rows whose manager record fuzzily matches to bob didier . there is only one such row in the table . the year record of this unqiue row is 1977 .
|
6
|
5
|
{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'manager_7': 7, 'bob didier_8': 8, 'eq_3': 3, 'num_hop_2': 2, 'year_9': 9, '1977_10': 10}
|
{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'manager_7': 'manager', 'bob didier_8': 'bob didier', 'eq_3': 'eq', 'num_hop_2': 'num_hop', 'year_9': 'year', '1977_10': '1977'}
|
{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'manager_7': [0], 'bob didier_8': [0], 'eq_3': [4], 'num_hop_2': [3], 'year_9': [2], '1977_10': [3]}
|
['year', 'record', 'finish', 'manager', 'playoffs']
|
[['1974', '31 - 39', '7th', 'hoyt wilhelm', 'none'], ['1975', '33 - 33', '6th', 'gene hassell', 'none'], ['1976', '25 - 42', '8th', 'bobby dews', 'none'], ['1977', '43 - 27', '2nd', 'bob didier', 'none'], ['1978', '33 - 37', '5th', 'eddie haas', 'none'], ['1979', '39 - 31', '2nd', 'gene hassell', 'none']]
|
list of serbian submissions for the academy award for best foreign language film
|
https://en.wikipedia.org/wiki/List_of_Serbian_submissions_for_the_Academy_Award_for_Best_Foreign_Language_Film
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-22265716-1.html.csv
|
count
|
two of the serbian submissions for the academy award for best foreign language film were after the year 2000 .
|
{'scope': 'all', 'criterion': 'greater_than_eq', 'value': '2000', 'result': '2', 'col': '1', 'subset': None}
|
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater_eq', 'args': ['all_rows', 'year ( ceremony )', '2000'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose year ( ceremony ) record is greater than or equal to 2000 .', 'tostr': 'filter_greater_eq { all_rows ; year ( ceremony ) ; 2000 }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_greater_eq { all_rows ; year ( ceremony ) ; 2000 } }', 'tointer': 'select the rows whose year ( ceremony ) record is greater than or equal to 2000 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_greater_eq { all_rows ; year ( ceremony ) ; 2000 } } ; 2 } = true', 'tointer': 'select the rows whose year ( ceremony ) record is greater than or equal to 2000 . the number of such rows is 2 .'}
|
eq { count { filter_greater_eq { all_rows ; year ( ceremony ) ; 2000 } } ; 2 } = true
|
select the rows whose year ( ceremony ) record is greater than or equal to 2000 . the number of such rows is 2 .
|
3
|
3
|
{'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_greater_eq_0': 0, 'all_rows_4': 4, 'year (ceremony)_5': 5, '2000_6': 6, '2_7': 7}
|
{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_greater_eq_0': 'filter_greater_eq', 'all_rows_4': 'all_rows', 'year (ceremony)_5': 'year ( ceremony )', '2000_6': '2000', '2_7': '2'}
|
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_greater_eq_0': [1], 'all_rows_4': [0], 'year (ceremony)_5': [0], '2000_6': [0], '2_7': [2]}
|
['year ( ceremony )', 'film title used in nomination', 'original title', 'director', 'result']
|
[['1994 ( 67th )', 'vukovar poste restante', 'вуковар , једна прича', 'boro drašković', 'not nominated'], ['1995 ( 68th )', 'underground', 'подземље', 'emir kusturica', 'not nominated'], ['1996 ( 69th )', 'pretty village , pretty flame', 'лепа села лепо горе', 'srđan dragojević', 'not nominated'], ['1997 ( 70th )', 'three summer days', 'три летња дана', 'mirjana vukomanović', 'not nominated'], ['1998 ( 71st )', 'powder keg', 'буре барута', 'goran paskaljević', 'not nominated'], ['1999 ( 72nd )', 'the white suit', 'бело одело', 'lazar ristovski', 'not nominated'], ['2000 ( 73rd )', 'sky hook', 'небеска удица', 'ljubiša samardžić', 'not nominated'], ['2001 ( 74th )', 'war live', 'рат уживо', 'darko bajić', 'not nominated']]
|
1941 vfl season
|
https://en.wikipedia.org/wiki/1941_VFL_season
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10807673-13.html.csv
|
unique
|
only one home team scored over 20 in the 1941 vfl season .
|
{'scope': 'all', 'row': '2', 'col': '2', 'col_other': 'n/a', 'criterion': 'greater_than', 'value': '20', 'subset': None}
|
{'func': 'only', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'home team score', '20'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose home team score record is greater than 20 .', 'tostr': 'filter_greater { all_rows ; home team score ; 20 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_greater { all_rows ; home team score ; 20 } } = true', 'tointer': 'select the rows whose home team score record is greater than 20 . there is only one such row in the table .'}
|
only { filter_greater { all_rows ; home team score ; 20 } } = true
|
select the rows whose home team score record is greater than 20 . there is only one such row in the table .
|
2
|
2
|
{'only_1': 1, 'result_2': 2, 'filter_greater_0': 0, 'all_rows_3': 3, 'home team score_4': 4, '20_5': 5}
|
{'only_1': 'only', 'result_2': 'true', 'filter_greater_0': 'filter_greater', 'all_rows_3': 'all_rows', 'home team score_4': 'home team score', '20_5': '20'}
|
{'only_1': [2], 'result_2': [], 'filter_greater_0': [1], 'all_rows_3': [0], 'home team score_4': [0], '20_5': [0]}
|
['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date']
|
[['melbourne', '18.16 ( 124 )', 'south melbourne', '10.13 ( 73 )', 'mcg', '23000', '26 july 1941'], ['collingwood', '22.20 ( 152 )', 'hawthorn', '12.13 ( 85 )', 'victoria park', '4000', '26 july 1941'], ['carlton', '12.11 ( 83 )', 'richmond', '11.18 ( 84 )', 'princes park', '27000', '26 july 1941'], ['st kilda', '18.14 ( 122 )', 'geelong', '11.15 ( 81 )', 'junction oval', '4000', '26 july 1941'], ['footscray', '15.20 ( 110 )', 'fitzroy', '9.4 ( 58 )', 'western oval', '10000', '26 july 1941'], ['north melbourne', '12.14 ( 86 )', 'essendon', '17.8 ( 110 )', 'arden street oval', '10000', '26 july 1941']]
|
wushu tournament beijing 2008
|
https://en.wikipedia.org/wiki/Wushu_Tournament_Beijing_2008
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17660359-12.html.csv
|
count
|
in the wushu tournament beijing 2008 , among the top 3 ranked athletes , 2 of them have total score of 19.30 and higher .
|
{'scope': 'subset', 'criterion': 'greater_than_eq', 'value': '19.3', 'result': '2', 'col': '5', 'subset': {'col': '1', 'criterion': 'less_than', 'value': '4'}}
|
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater_eq', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'rank', '4'], 'result': None, 'ind': 0, 'tostr': 'filter_less { all_rows ; rank ; 4 }', 'tointer': 'select the rows whose rank record is less than 4 .'}, 'total', '19.3'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose rank record is less than 4 . among these rows , select the rows whose total record is greater than or equal to 19.3 .', 'tostr': 'filter_greater_eq { filter_less { all_rows ; rank ; 4 } ; total ; 19.3 }'}], 'result': '2', 'ind': 2, 'tostr': 'count { filter_greater_eq { filter_less { all_rows ; rank ; 4 } ; total ; 19.3 } }', 'tointer': 'select the rows whose rank record is less than 4 . among these rows , select the rows whose total record is greater than or equal to 19.3 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_greater_eq { filter_less { all_rows ; rank ; 4 } ; total ; 19.3 } } ; 2 } = true', 'tointer': 'select the rows whose rank record is less than 4 . among these rows , select the rows whose total record is greater than or equal to 19.3 . the number of such rows is 2 .'}
|
eq { count { filter_greater_eq { filter_less { all_rows ; rank ; 4 } ; total ; 19.3 } } ; 2 } = true
|
select the rows whose rank record is less than 4 . among these rows , select the rows whose total record is greater than or equal to 19.3 . the number of such rows is 2 .
|
4
|
4
|
{'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_greater_eq_1': 1, 'filter_less_0': 0, 'all_rows_5': 5, 'rank_6': 6, '4_7': 7, 'total_8': 8, '19.3_9': 9, '2_10': 10}
|
{'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_greater_eq_1': 'filter_greater_eq', 'filter_less_0': 'filter_less', 'all_rows_5': 'all_rows', 'rank_6': 'rank', '4_7': '4', 'total_8': 'total', '19.3_9': '19.3', '2_10': '2'}
|
{'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_greater_eq_1': [2], 'filter_less_0': [1], 'all_rows_5': [0], 'rank_6': [0], '4_7': [0], 'total_8': [1], '19.3_9': [1], '2_10': [3]}
|
['rank', 'athlete', 'qiangshu', 'jianshu', 'total']
|
[['1', 'ma lingjuan ( chn )', '9.85', '9.75', '19.60'], ['2', 'han jing ( mac )', '9.65', '9.65', '19.30'], ['3', 'nguyen mai phuong ( vie )', '9.55', '9.60', '19.15'], ['4', 'chen shao - chi ( tpe )', '9.50', '9.59', '19.09'], ['5', 'evgeniya ragulina ( kaz )', '9.44', '9.50', '18.94'], ['6', 'lee tenyia ( usa )', '9.41', '9.49', '18.90'], ['7', 'ng xinni ( sin )', '9.42', '9.22', '18.64']]
|
phoenix suns all - time roster
|
https://en.wikipedia.org/wiki/Phoenix_Suns_all-time_roster
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11482079-2.html.csv
|
comparative
|
alvan adams began playing for the phoenix suns 11 years before rafael addison .
|
{'row_1': '1', 'row_2': '2', 'col': '3', 'col_other': '1', 'relation': 'diff', 'record_mentioned': 'no', 'diff_result': {'diff_value': '11', 'bigger': 'row2'}}
|
{'func': 'eq', 'args': [{'func': 'diff', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', 'alvan adams'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose player record fuzzily matches to alvan adams .', 'tostr': 'filter_eq { all_rows ; player ; alvan adams }'}, 'from'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; player ; alvan adams } ; from }', 'tointer': 'select the rows whose player record fuzzily matches to alvan adams . take the from record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', 'rafael addison'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose player record fuzzily matches to rafael addison .', 'tostr': 'filter_eq { all_rows ; player ; rafael addison }'}, 'from'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; player ; rafael addison } ; from }', 'tointer': 'select the rows whose player record fuzzily matches to rafael addison . take the from record of this row .'}], 'result': '-11', 'ind': 4, 'tostr': 'diff { hop { filter_eq { all_rows ; player ; alvan adams } ; from } ; hop { filter_eq { all_rows ; player ; rafael addison } ; from } }'}, '-11'], 'result': True, 'ind': 5, 'tostr': 'eq { diff { hop { filter_eq { all_rows ; player ; alvan adams } ; from } ; hop { filter_eq { all_rows ; player ; rafael addison } ; from } } ; -11 } = true', 'tointer': 'select the rows whose player record fuzzily matches to alvan adams . take the from record of this row . select the rows whose player record fuzzily matches to rafael addison . take the from record of this row . the second record is 11 larger than the first record .'}
|
eq { diff { hop { filter_eq { all_rows ; player ; alvan adams } ; from } ; hop { filter_eq { all_rows ; player ; rafael addison } ; from } } ; -11 } = true
|
select the rows whose player record fuzzily matches to alvan adams . take the from record of this row . select the rows whose player record fuzzily matches to rafael addison . take the from record of this row . the second record is 11 larger than the first record .
|
6
|
6
|
{'eq_5': 5, 'result_6': 6, 'diff_4': 4, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_7': 7, 'player_8': 8, 'alvan adams_9': 9, 'from_10': 10, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_11': 11, 'player_12': 12, 'rafael addison_13': 13, 'from_14': 14, '-11_15': 15}
|
{'eq_5': 'eq', 'result_6': 'true', 'diff_4': 'diff', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_7': 'all_rows', 'player_8': 'player', 'alvan adams_9': 'alvan adams', 'from_10': 'from', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_11': 'all_rows', 'player_12': 'player', 'rafael addison_13': 'rafael addison', 'from_14': 'from', '-11_15': '-11'}
|
{'eq_5': [6], 'result_6': [], 'diff_4': [5], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_7': [0], 'player_8': [0], 'alvan adams_9': [0], 'from_10': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_11': [1], 'player_12': [1], 'rafael addison_13': [1], 'from_14': [3], '-11_15': [5]}
|
['player', 'pos', 'from', 'school / country', 'rebs', 'asts']
|
[['alvan adams', 'c / f', '1975', 'oklahoma', '6937', '4012'], ['rafael addison', 'g / f', '1986', 'syracuse', '106', '45'], ['danny ainge', 'sg', '1992', 'byu', '454', '650'], ['louis amundson', 'pf', '2008', 'unlv', '616', '59'], ['robert archibald', 'f / c', '2003', 'illinois', '1', '1'], ['dennis awtrey', 'c', '1974', 'santa clara', '1655', '846']]
|
list of superleague formula drivers and teams
|
https://en.wikipedia.org/wiki/List_of_Superleague_Formula_drivers_and_teams
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-19312274-2.html.csv
|
comparative
|
brazil has had more superleague formula teams than belgium has .
|
{'row_1': '3', 'row_2': '4', 'col': '2', 'col_other': '1', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None}
|
{'func': 'less', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'belgium'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose country record fuzzily matches to belgium .', 'tostr': 'filter_eq { all_rows ; country ; belgium }'}, 'total'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; country ; belgium } ; total }', 'tointer': 'select the rows whose country record fuzzily matches to belgium . take the total record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'brazil'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose country record fuzzily matches to brazil .', 'tostr': 'filter_eq { all_rows ; country ; brazil }'}, 'total'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; country ; brazil } ; total }', 'tointer': 'select the rows whose country record fuzzily matches to brazil . take the total record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; country ; belgium } ; total } ; hop { filter_eq { all_rows ; country ; brazil } ; total } } = true', 'tointer': 'select the rows whose country record fuzzily matches to belgium . take the total record of this row . select the rows whose country record fuzzily matches to brazil . take the total record of this row . the first record is less than the second record .'}
|
less { hop { filter_eq { all_rows ; country ; belgium } ; total } ; hop { filter_eq { all_rows ; country ; brazil } ; total } } = true
|
select the rows whose country record fuzzily matches to belgium . take the total record of this row . select the rows whose country record fuzzily matches to brazil . take the total 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, 'country_7': 7, 'belgium_8': 8, 'total_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'country_11': 11, 'brazil_12': 12, 'total_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', 'country_7': 'country', 'belgium_8': 'belgium', 'total_9': 'total', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'country_11': 'country', 'brazil_12': 'brazil', 'total_13': 'total'}
|
{'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'country_7': [0], 'belgium_8': [0], 'total_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'country_11': [1], 'brazil_12': [1], 'total_13': [3]}
|
['country', 'total', 'champions', 'current', 'first driver ( s )', 'last / current driver ( s )']
|
[['argentina', '1', '0', '0', 'esteban guerrieri ( 2009 )', 'esteban guerrieri ( 2010 )'], ['australia', '1', '0', '1', 'john martin ( 2009 )', 'john martin'], ['belgium', '2', '0', '1', 'bertrand baguette ( 2008 )', 'frédéric vervisch'], ['brazil', '3', '0', '1', 'tuka rocha ( 2008 )', 'antônio pizzonia'], ['china', '3', '0', '1', 'ho - pin tung ( 2009 )', 'ho - pin tung'], ['czech republic', '1', '0', '1', 'filip salaquarda ( 2011 )', 'filip salaquarda'], ['denmark', '1', '0', '0', 'kasper andersen ( 2008 )', 'kasper andersen ( 2009 )'], ['france', '7', '0', '1', 'tristan gommendy , nelson philippe ( 2008 )', 'tristan gommendy'], ['germany', '1', '0', '0', 'max wissel ( 2008 )', 'max wissel ( 2010 )'], ['greece', '1', '0', '0', 'stamatis katsimis ( 2008 )', 'stamatis katsimis ( 2008 )'], ['india', '1', '0', '0', 'narain karthikeyan ( 2010 )', 'narain karthikeyan ( 2010 )'], ['netherlands', '6', '0', '2', 'yelmer buurman , robert doornbos ( 2008 )', 'yelmer buurman , robert doornbos'], ['new zealand', '2', '0', '1', 'chris van der drift ( 2010 )', 'earl bamber'], ['portugal', '2', '0', '0', 'pedro petiz ( 2009 )', 'álvaro parente ( 2010 )'], ['switzerland', '1', '0', '1', 'neel jani ( 2010 )', 'neel jani'], ['united arab emirates', '1', '0', '0', 'andreas zuber ( 2008 )', 'andreas zuber ( 2008 )']]
|
united states house of representatives elections , 1948
|
https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1948
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1342218-13.html.csv
|
count
|
six of the incumbents from illinois districts were re-elected in the 1948 united states house of representative elections .
|
{'scope': 'all', 'criterion': 'fuzzily_match', 'value': 're-elected', 'result': '6', 'col': '5', 'subset': None}
|
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'result', 're-elected'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose result record fuzzily matches to re-elected .', 'tostr': 'filter_eq { all_rows ; result ; re-elected }'}], 'result': '6', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; result ; re-elected } }', 'tointer': 'select the rows whose result record fuzzily matches to re-elected . the number of such rows is 6 .'}, '6'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; result ; re-elected } } ; 6 } = true', 'tointer': 'select the rows whose result record fuzzily matches to re-elected . the number of such rows is 6 .'}
|
eq { count { filter_eq { all_rows ; result ; re-elected } } ; 6 } = true
|
select the rows whose result record fuzzily matches to re-elected . the number of such rows is 6 .
|
3
|
3
|
{'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'result_5': 5, 're-elected_6': 6, '6_7': 7}
|
{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'result_5': 'result', 're-elected_6': 're-elected', '6_7': '6'}
|
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'result_5': [0], 're-elected_6': [0], '6_7': [2]}
|
['district', 'incumbent', 'party', 'first elected', 'result', 'candidates']
|
[['illinois 3', 'fred e busbey', 'republican', '1946', 'lost re - election democratic gain', 'neil j linehan ( d ) 52.9 % fred e busbey ( r ) 47.1 %'], ['illinois 5', 'martin gorski redistricted from 4th', 'democratic', '1942', 're - elected', 'martin gorski ( d ) 72.4 % john l waner ( r ) 27.6 %'], ['illinois 14', 'chauncey w reed redistricted from 11th', 'republican', '1934', 're - elected', 'chauncey w reed ( r ) 68.3 % richard plum ( d ) 31.7 %'], ['illinois 15', 'noah m mason redistricted from 12th', 'republican', '1936', 're - elected', 'noah m mason ( r ) 56.4 % g m wells ( d ) 43.6 %'], ['illinois 17', 'leslie c arends', 'republican', '1934', 're - elected', 'leslie c arends ( r ) 62.8 % carl vrooman ( d ) 37.2 %'], ['illinois 18', 'everett dirksen redistricted from 16th', 'republican', '1932', 'retired republican hold', 'harold h velde ( r ) 52.1 % dale e sutton ( d ) 47.9 %'], ['illinois 20', 'sid simpson', 'republican', '1942', 're - elected', 'sid simpson ( r ) 53.1 % henry d sullivan ( d ) 46.9 %'], ['illinois 20', 'anton j johnson redistricted from 14th', 'republican', '1938', 'retired republican loss', 'sid simpson ( r ) 53.1 % henry d sullivan ( d ) 46.9 %'], ['illinois 26', 'c w bishop', 'republican', '1940', 're - elected', 'c w bishop ( r ) 51.9 % kent e keller ( d ) 48.1 %']]
|
2010 - 11 phoenix suns season
|
https://en.wikipedia.org/wiki/2010%E2%80%9311_Phoenix_Suns_season
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27733258-6.html.csv
|
majority
|
all of the games between 4 and 16 were played during the month of november .
|
{'scope': 'all', 'col': '2', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'november', 'subset': None}
|
{'func': 'all_str_eq', 'args': ['all_rows', 'date', 'november'], 'result': True, 'ind': 0, 'tointer': 'for the date records of all rows , all of them fuzzily match to november .', 'tostr': 'all_eq { all_rows ; date ; november } = true'}
|
all_eq { all_rows ; date ; november } = true
|
for the date records of all rows , all of them fuzzily match to november .
|
1
|
1
|
{'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'date_3': 3, 'November_4': 4}
|
{'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'date_3': 'date', 'November_4': 'november'}
|
{'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'date_3': [0], 'November_4': [0]}
|
['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record']
|
[['4', 'november 3', 'san antonio', 'l 110 - 112 ( ot )', 'jason richardson ( 21 )', 'grant hill ( 8 )', 'goran dragić ( 8 )', 'us airways center 17060', '1 - 3'], ['5', 'november 5', 'memphis', 'w 123 - 118 ( 2ot )', 'jason richardson ( 38 )', 'channing frye ( 11 )', 'steve nash ( 9 )', 'us airways center 16470', '2 - 3'], ['6', 'november 7', 'atlanta', 'w 118 - 114 ( ot )', 'jason richardson ( 21 )', 'jared dudley , grant hill , josh childress ( 6 )', 'steve nash ( 15 )', 'philips arena 13395', '3 - 3'], ['7', 'november 8', 'memphis', 'l 99 - 109 ( ot )', 'grant hill ( 19 )', 'grant hill ( 12 )', 'steve nash ( 11 )', 'fedexforum 10786', '3 - 4'], ['8', 'november 12', 'sacramento', 'w 103 - 89 ( ot )', 'steve nash ( 28 )', 'jason richardson ( 8 )', 'steve nash ( 14 )', 'us airways center 18029', '4 - 4'], ['9', 'november 14', 'la lakers', 'w 121 - 116 ( ot )', 'jason richardson ( 35 )', 'jason richardson ( 8 )', 'steve nash ( 13 )', 'staples center 18997', '5 - 4'], ['10', 'november 15', 'denver', 'w 100 - 94 ( ot )', 'hakim warrick ( 21 )', 'josh childress ( 8 )', 'steve nash ( 7 )', 'us airways center 17744', '6 - 4'], ['11', 'november 17', 'miami', 'l 96 - 123 ( ot )', 'steve nash ( 17 )', 'channing frye , hedo türkoğlu ( 6 )', 'hedo türkoğlu ( 4 )', 'american airlines arena 19600', '6 - 5'], ['12', 'november 18', 'orlando', 'l 89 - 105 ( ot )', 'grant hill ( 21 )', 'channing frye ( 6 )', 'goran dragić ( 4 )', 'amway center 18846', '6 - 6'], ['13', 'november 20', 'charlotte', 'l 105 - 123 ( ot )', 'grant hill ( 23 )', 'channing frye ( 6 )', 'goran dragić ( 10 )', 'time warner cable arena 16428', '6 - 7'], ['14', 'november 22', 'houston', 'w 123 - 116 ( ot )', 'jason richardson ( 26 )', 'hedo türkoğlu ( 9 )', 'steve nash ( 8 )', 'toyota center 15080', '7 - 7'], ['15', 'november 24', 'chicago', 'l 115 - 123 ( 2ot )', 'grant hill ( 27 )', 'hedo türkoğlu ( 10 )', 'steve nash ( 16 )', 'us airways center 18422', '7 - 8'], ['16', 'november 26', 'la clippers', 'w 116 - 108 ( ot )', 'jason richardson ( 29 )', 'jason richardson , hakim warrick ( 6 )', 'steve nash ( 10 )', 'us airways center 17486', '8 - 8']]
|
nino vaccarella
|
https://en.wikipedia.org/wiki/Nino_Vaccarella
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1235134-1.html.csv
|
aggregation
|
for nino vaccarella the total points scored from 1961 to 1965 was 0 .
|
{'scope': 'all', 'col': '5', 'type': 'sum', 'result': '0', 'subset': None}
|
{'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'points'], 'result': '0', 'ind': 0, 'tostr': 'sum { all_rows ; points }'}, '0'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; points } ; 0 } = true', 'tointer': 'the sum of the points record of all rows is 0 .'}
|
round_eq { sum { all_rows ; points } ; 0 } = true
|
the sum of the points record of all rows is 0 .
|
2
|
2
|
{'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'points_4': 4, '0_5': 5}
|
{'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'points_4': 'points', '0_5': '0'}
|
{'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'points_4': [0], '0_5': [1]}
|
['year', 'entrant', 'chassis', 'engine', 'points']
|
[['1961', 'scuderia serenissima', 'de tomaso f1', 'alfa romeo straight - 4', '0'], ['1962', 'scuderia sss republica di venezia', 'lotus 18 / 21', 'climax straight - 4', '0'], ['1962', 'scuderia sss republica di venezia', 'porsche 718', 'porsche flat - 4', '0'], ['1962', 'scuderia sss republica di venezia', 'lotus 24', 'climax v8', '0'], ['1965', 'scuderia ferrari spa sefac', 'ferrari 158', 'ferrari v8', '0']]
|
2009 - 10 washington wizards season
|
https://en.wikipedia.org/wiki/2009%E2%80%9310_Washington_Wizards_season
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-23274514-7.html.csv
|
ordinal
|
the washington wizards ' game against boston recorded their highest attendance of the 2009 - 10 season .
|
{'row': '1', 'col': '8', 'order': '1', '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', 'location attendance', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; location attendance ; 1 }'}, 'team'], 'result': 'boston', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; location attendance ; 1 } ; team }'}, 'boston'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; location attendance ; 1 } ; team } ; boston } = true', 'tointer': 'select the row whose location attendance record of all rows is 1st maximum . the team record of this row is boston .'}
|
eq { hop { nth_argmax { all_rows ; location attendance ; 1 } ; team } ; boston } = true
|
select the row whose location attendance record of all rows is 1st maximum . the team record of this row is boston .
|
3
|
3
|
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'location attendance_5': 5, '1_6': 6, 'team_7': 7, 'boston_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', 'location attendance_5': 'location attendance', '1_6': '1', 'team_7': 'team', 'boston_8': 'boston'}
|
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'location attendance_5': [0], '1_6': [0], 'team_7': [1], 'boston_8': [2]}
|
['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record']
|
[['47', 'february 1', 'boston', 'l 88 - 99 ( ot )', 'caron butler ( 20 )', 'caron butler ( 11 )', 'randy foye ( 4 )', 'verizon center 20173', '16 - 31'], ['48', 'february 3', 'new york', 'l 85 - 107 ( ot )', 'foye & young ( 15 )', 'brendan haywood ( 8 )', 'earl boykins ( 6 )', 'madison square garden 19225', '16 - 32'], ['49', 'february 5', 'orlando', 'w 92 - 91 ( ot )', 'caron butler ( 31 )', 'brendan haywood ( 10 )', 'randy foye ( 7 )', 'amway arena 17461', '17 - 32'], ['50', 'february 9', 'charlotte', 'l 92 - 94 ( ot )', 'caron butler ( 23 )', 'brendan haywood ( 11 )', 'caron butler ( 8 )', 'time warner cable arena 12376', '17 - 33'], ['51', 'february 17', 'minnesota', 'w 108 - 99 ( ot )', 'andray blatche ( 33 )', 'andray blatche ( 13 )', 'earl boykins ( 8 )', 'verizon center 13143', '18 - 33'], ['52', 'february 19', 'denver', 'w 107 - 97 ( ot )', 'al thornton ( 21 )', 'andray blatche ( 11 )', 'mike miller ( 7 )', 'verizon center 17212', '19 - 33'], ['53', 'february 20', 'toronto', 'l 104 - 109 ( ot )', 'andray blatche ( 24 )', 'miller & howard ( 7 )', 'earl boykins ( 6 )', 'air canada centre 19149', '19 - 34'], ['54', 'february 22', 'chicago', 'w 101 - 95 ( ot )', 'andray blatche ( 25 )', 'james singleton ( 12 )', 'randy foye ( 9 )', 'verizon center 14113', '20 - 34'], ['55', 'february 24', 'memphis', 'l 94 - 99 ( ot )', 'andray blatche ( 24 )', 'al thornton ( 11 )', 'foye & miller ( 7 )', 'verizon center 11875', '20 - 35'], ['56', 'february 26', 'new york', 'l 116 - 118 ( ot ) ot', 'andray blatche ( 26 )', 'andray blatche ( 18 )', 'randy foye ( 10 )', 'verizon center 17408', '20 - 36']]
|
jeep grand cherokee
|
https://en.wikipedia.org/wiki/Jeep_Grand_Cherokee
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1105695-9.html.csv
|
count
|
in jeep grand cherokee , the years of one of the cars with engine 4.7 l powertech v8 is 2005-2007 .
|
{'scope': 'subset', 'criterion': 'equal', 'value': '2005-2007', 'result': '1', 'col': '1', 'subset': {'col': '2', 'criterion': 'equal', 'value': '4.7 l powertech v8'}}
|
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'engine', '4.7 l powertech v8'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; engine ; 4.7 l powertech v8 }', 'tointer': 'select the rows whose engine record fuzzily matches to 4.7 l powertech v8 .'}, 'years', '2005-2007'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose engine record fuzzily matches to 4.7 l powertech v8 . among these rows , select the rows whose years record fuzzily matches to 2005-2007 .', 'tostr': 'filter_eq { filter_eq { all_rows ; engine ; 4.7 l powertech v8 } ; years ; 2005-2007 }'}], 'result': '1', 'ind': 2, 'tostr': 'count { filter_eq { filter_eq { all_rows ; engine ; 4.7 l powertech v8 } ; years ; 2005-2007 } }', 'tointer': 'select the rows whose engine record fuzzily matches to 4.7 l powertech v8 . among these rows , select the rows whose years record fuzzily matches to 2005-2007 . the number of such rows is 1 .'}, '1'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_eq { filter_eq { all_rows ; engine ; 4.7 l powertech v8 } ; years ; 2005-2007 } } ; 1 } = true', 'tointer': 'select the rows whose engine record fuzzily matches to 4.7 l powertech v8 . among these rows , select the rows whose years record fuzzily matches to 2005-2007 . the number of such rows is 1 .'}
|
eq { count { filter_eq { filter_eq { all_rows ; engine ; 4.7 l powertech v8 } ; years ; 2005-2007 } } ; 1 } = true
|
select the rows whose engine record fuzzily matches to 4.7 l powertech v8 . among these rows , select the rows whose years record fuzzily matches to 2005-2007 . the number of such rows is 1 .
|
4
|
4
|
{'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_str_eq_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'engine_6': 6, '4.7l powertech v8_7': 7, 'years_8': 8, '2005-2007_9': 9, '1_10': 10}
|
{'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_str_eq_1': 'filter_str_eq', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'engine_6': 'engine', '4.7l powertech v8_7': '4.7 l powertech v8', 'years_8': 'years', '2005-2007_9': '2005-2007', '1_10': '1'}
|
{'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_str_eq_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'engine_6': [0], '4.7l powertech v8_7': [0], 'years_8': [1], '2005-2007_9': [1], '1_10': [3]}
|
['years', 'engine', 'power', 'torque', 'notes']
|
[['2005 - 2010', '3.7 l powertech v6', '-', 'n / a', 'laredo , limited'], ['2005 - 2007', '4.7 l powertech v8', '-', 'n / a', 'laredo , limited'], ['2008 - 2009', '4.7 l powertech v8', '-', 'n / a', 'laredo , limited'], ['2005 - 2008', '5.7 l hemi v8', '-', 'n / a', 'limited , overland'], ['2009 - 2010', '5.7 l hemi v8', '-', 'n / a', 'laredo , limited , overland'], ['2006 - 2010', '6.1 l hemi v8', '-', 'n / a', 'srt - 8'], ['2005 ( 2007 - 2008 in na ) -', '3.0 l om642 diesel v6', '-', 'n / a', 'laredo , limited , overland']]
|
reinhold roth
|
https://en.wikipedia.org/wiki/Reinhold_Roth
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14860855-3.html.csv
|
aggregation
|
over his career , reinhold roth averaged over 48 points per year .
|
{'scope': 'all', 'col': '4', 'type': 'average', 'result': '48.8', 'subset': None}
|
{'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'points'], 'result': '48.8', 'ind': 0, 'tostr': 'avg { all_rows ; points }'}, '48.8'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; points } ; 48.8 } = true', 'tointer': 'the average of the points record of all rows is 48.8 .'}
|
round_eq { avg { all_rows ; points } ; 48.8 } = true
|
the average of the points record of all rows is 48.8 .
|
2
|
2
|
{'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'points_4': 4, '48.8_5': 5}
|
{'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'points_4': 'points', '48.8_5': '48.8'}
|
{'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'points_4': [0], '48.8_5': [1]}
|
['year', 'class', 'team', 'points', 'wins']
|
[['1979', '350cc', 'yamaha', '3', '0'], ['1980', '250cc', 'yamaha', '4', '0'], ['1982', '250cc', 'yamaha', '4', '0'], ['1982', '500cc', 'suzuki', '0', '0'], ['1983', '250cc', 'yamaha', '14', '0'], ['1984', '500cc', 'honda', '14', '0'], ['1985', '250cc', 'romer - juchem', '29', '0'], ['1986', '250cc', 'hb - honda', '10', '0'], ['1987', '250cc', 'hb - honda', '108', '1'], ['1988', '250cc', 'hb - honda', '158', '0'], ['1989', '250cc', 'hb - honda', '190', '2'], ['1990', '250cc', 'hb - honda', '52', '0']]
|
1990 dallas cowboys season
|
https://en.wikipedia.org/wiki/1990_Dallas_Cowboys_season
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11281728-2.html.csv
|
superlative
|
the texas stadium was the first venue used by the dallas cowboys during the 1990 season .
|
{'scope': 'all', 'col_superlative': '2', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '5', 'subset': None}
|
{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmin', 'args': ['all_rows', 'date'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; date }'}, 'venue'], 'result': 'texas stadium', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; date } ; venue }'}, 'texas stadium'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmin { all_rows ; date } ; venue } ; texas stadium } = true', 'tointer': 'select the row whose date record of all rows is minimum . the venue record of this row is texas stadium .'}
|
eq { hop { argmin { all_rows ; date } ; venue } ; texas stadium } = true
|
select the row whose date record of all rows is minimum . the venue record of this row is texas stadium .
|
3
|
3
|
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'date_5': 5, 'venue_6': 6, 'texas stadium_7': 7}
|
{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'date_5': 'date', 'venue_6': 'venue', 'texas stadium_7': 'texas stadium'}
|
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'date_5': [0], 'venue_6': [1], 'texas stadium_7': [2]}
|
['week', 'date', 'opponent', 'result', 'venue', 'attendance']
|
[['1', '1990 - 09 - 09', 'san diego chargers', 'w 17 - 14', 'texas stadium', '48063'], ['2', '1990 - 09 - 16', 'new york giants', 'l 28 - 7', 'texas stadium', '61090'], ['3', '1990 - 09 - 23', 'washington redskins', 'l 19 - 15', 'robert f kennedy memorial stadium', '53804'], ['4', '1990 - 09 - 30', 'new york giants', 'l 31 - 17', 'giants stadium', '75923'], ['5', '1990 - 10 - 07', 'tampa bay buccaneers', 'w 14 - 10', 'texas stadium', '60076'], ['6', '1990 - 10 - 14', 'phoenix cardinals', 'l 20 - 3', 'sun devil stadium', '45235'], ['7', '1990 - 10 - 21', 'tampa bay buccaneers', 'w 17 - 13', 'tampa stadium', '68315'], ['8', '1990 - 10 - 28', 'philadelphia eagles', 'l 21 - 20', 'texas stadium', '62605'], ['9', '1990 - 11 - 04', 'new york jets', 'l 24 - 9', 'the meadowlands', '68086'], ['10', '1990 - 11 - 11', 'san francisco 49ers', 'l 24 - 6', 'texas stadium', '62966'], ['11', '1990 - 11 - 18', 'los angeles rams', 'w 24 - 21', 'anaheim stadium', '58589'], ['12', '1990 - 11 - 22', 'washington redskins', 'w 27 - 17', 'texas stadium', '60355'], ['13', '1990 - 12 - 02', 'new orleans saints', 'w 17 - 13', 'texas stadium', '60087'], ['14', '-', '-', '-', '-', ''], ['15', '1990 - 12 - 16', 'phoenix cardinals', 'w 41 - 10', 'texas stadium', '60190'], ['16', '1990 - 12 - 23', 'philadelphia eagles', 'l 17 - 3', 'veterans stadium', '63895'], ['17', '1990 - 12 - 30', 'atlanta falcons', 'l 26 - 7', 'atlanta - fulton county stadium', '50097']]
|
comparison of e - book readers
|
https://en.wikipedia.org/wiki/Comparison_of_e-book_readers
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1149661-3.html.csv
|
majority
|
most of the models have a screen size of at least seven inches .
|
{'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'greater_than_eq', 'value': '7', 'subset': None}
|
{'func': 'most_greater_eq', 'args': ['all_rows', 'screen size ( inch )', '7'], 'result': True, 'ind': 0, 'tointer': 'for the screen size ( inch ) records of all rows , most of them are greater than or equal to 7 .', 'tostr': 'most_greater_eq { all_rows ; screen size ( inch ) ; 7 } = true'}
|
most_greater_eq { all_rows ; screen size ( inch ) ; 7 } = true
|
for the screen size ( inch ) records of all rows , most of them are greater than or equal to 7 .
|
1
|
1
|
{'most_greater_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'screen size (inch)_3': 3, '7_4': 4}
|
{'most_greater_eq_0': 'most_greater_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'screen size (inch)_3': 'screen size ( inch )', '7_4': '7'}
|
{'most_greater_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'screen size (inch)_3': [0], '7_4': [0]}
|
['maker', 'model', 'intro year', 'screen size ( inch )', 'screen type', 'weight', 'screen pixels', 'hours reading', 'touch screen', 'wireless network', 'internal storage', 'card reader slot']
|
[['aluratek', 'libre touch ebook reader', '2011', '7', 'lcd', 'g ( oz )', '480 800', '8', 'yes', 'yes , wi - fi', '4 gb', 'microsd'], ['aluratek', 'libre air ebook reader', '2011', '5', 'lcd', 'g ( oz )', '480 640', '20', 'no', 'yes , wi - fi', '512 mb', 'microsd'], ['aluratek', 'libre color ebook reader', '2010', '7', 'lcd', 'g ( oz )', '480 800', '24', 'no', 'no', '2 gb', 'sd'], ['aluratek', 'libre pro ebook reader', '2009', '5', 'lcd', 'g ( oz )', '480 640', '24', 'no', 'no', '256 mb', 'sd'], ['amazoncom', 'kindle fire', '2011', '7', 'lcd ( ips )', 'g ( oz )', '600 1024', '8', 'yes', 'wi - fi', '8 gb ( 6 gb )', 'no'], ['apple inc', 'ipad ( 3rd generation )', '2012', '9.7', 'lcd ( ips )', 'g ( oz ) , g ( oz )', '2048 1536', '10', 'yes', 'wi - fi , 3 g', '16 - 64 gb', 'sd via camera connection kit'], ['apple inc', 'ipad 2', '2011', '9.7', 'lcd ( ips )', 'g ( oz )', '768 1024', '10', 'yes', 'wi - fi , 3 g', '16 - 64 gb', 'sd via camera connection kit'], ['apple inc', 'ipad', '2010', '9.7', 'lcd', 'g ( oz )', '768 1024', '9', 'yes', 'wi - fi', '16 - 64 gb', 'sd via camera connection kit'], ['barnes & noble', 'nook color', '2010', '7', 'lcd', 'g ( oz )', '600 1024', '8', 'yes', 'wi - fi 802.11 b / g / n', '2 gb , 1 gb available', 'microsdhc'], ['ectaco', 'jetbook', '2008', '5', 'lcd', 'g ( oz )', '480 640', '20', 'no', 'no', '112 mb', 'sdhc'], ['elonex', '705eb', '2010', '7', 'led', 'g ( oz )', '480 800', '8', 'no', 'no', '4 gb', 'microsdhc'], ['notion ink', 'adam', '2011', '10.1', 'pixel qi', 'g ( oz )', '600 1024', '15', 'yes', 'wi - fi , 3 g', '1 gb ddr2 ram 1 gb slc', 'microsd'], ['pocketbook', 'pocketbook iq 701', '2010', '7', 'lcd', 'g ( oz )', '600 800', '8', 'yes', 'wi - fi', '2 gb', 'sdhc'], ['trekstor', 'ebook reader 3.0', '2011', '7', 'lcd', 'g ( oz )', '800 480', '8', 'no', 'no', '2 gb', 'microsdhc'], ['zzbook', 'ereader hd', '2010', '7', 'tft - lcd', 'g ( oz )', '800 480', '8', 'no', 'no', '2 gb', 'microsd'], ['maker', 'model', 'intro year', 'screen size ( inch )', 'screen type', 'weight', 'screen pixels', 'hours reading', 'touch screen', 'wireless network', 'internal storage', 'card reader slot']]
|
telecommunications in moldova
|
https://en.wikipedia.org/wiki/Telecommunications_in_Moldova
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-19246-1.html.csv
|
unique
|
among the telecommunications in moldova that were launched in 2005 the only one with connection speed 236.8 kbit/s is moldcell .
|
{'scope': 'subset', 'row': '4', 'col': '4', 'col_other': '1', 'criterion': 'equal', 'value': '236.8 kbit/s', 'subset': {'col': '5', 'criterion': 'fuzzily_match', 'value': '2005'}}
|
{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'launch date ( ddmmyyyy )', '2005'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; launch date ( ddmmyyyy ) ; 2005 }', 'tointer': 'select the rows whose launch date ( ddmmyyyy ) record fuzzily matches to 2005 .'}, 'connection speed', '236.8 kbit/s'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose launch date ( ddmmyyyy ) record fuzzily matches to 2005 . among these rows , select the rows whose connection speed record fuzzily matches to 236.8 kbit/s .', 'tostr': 'filter_eq { filter_eq { all_rows ; launch date ( ddmmyyyy ) ; 2005 } ; connection speed ; 236.8 kbit/s }'}], 'result': True, 'ind': 2, 'tostr': 'only { filter_eq { filter_eq { all_rows ; launch date ( ddmmyyyy ) ; 2005 } ; connection speed ; 236.8 kbit/s } }', 'tointer': 'select the rows whose launch date ( ddmmyyyy ) record fuzzily matches to 2005 . among these rows , select the rows whose connection speed record fuzzily matches to 236.8 kbit/s . 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', 'launch date ( ddmmyyyy )', '2005'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; launch date ( ddmmyyyy ) ; 2005 }', 'tointer': 'select the rows whose launch date ( ddmmyyyy ) record fuzzily matches to 2005 .'}, 'connection speed', '236.8 kbit/s'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose launch date ( ddmmyyyy ) record fuzzily matches to 2005 . among these rows , select the rows whose connection speed record fuzzily matches to 236.8 kbit/s .', 'tostr': 'filter_eq { filter_eq { all_rows ; launch date ( ddmmyyyy ) ; 2005 } ; connection speed ; 236.8 kbit/s }'}, 'carrier'], 'result': 'moldcell', 'ind': 3, 'tostr': 'hop { filter_eq { filter_eq { all_rows ; launch date ( ddmmyyyy ) ; 2005 } ; connection speed ; 236.8 kbit/s } ; carrier }'}, 'moldcell'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { filter_eq { filter_eq { all_rows ; launch date ( ddmmyyyy ) ; 2005 } ; connection speed ; 236.8 kbit/s } ; carrier } ; moldcell }', 'tointer': 'the carrier record of this unqiue row is moldcell .'}], 'result': True, 'ind': 5, 'tostr': 'and { only { filter_eq { filter_eq { all_rows ; launch date ( ddmmyyyy ) ; 2005 } ; connection speed ; 236.8 kbit/s } } ; eq { hop { filter_eq { filter_eq { all_rows ; launch date ( ddmmyyyy ) ; 2005 } ; connection speed ; 236.8 kbit/s } ; carrier } ; moldcell } } = true', 'tointer': 'select the rows whose launch date ( ddmmyyyy ) record fuzzily matches to 2005 . among these rows , select the rows whose connection speed record fuzzily matches to 236.8 kbit/s . there is only one such row in the table . the carrier record of this unqiue row is moldcell .'}
|
and { only { filter_eq { filter_eq { all_rows ; launch date ( ddmmyyyy ) ; 2005 } ; connection speed ; 236.8 kbit/s } } ; eq { hop { filter_eq { filter_eq { all_rows ; launch date ( ddmmyyyy ) ; 2005 } ; connection speed ; 236.8 kbit/s } ; carrier } ; moldcell } } = true
|
select the rows whose launch date ( ddmmyyyy ) record fuzzily matches to 2005 . among these rows , select the rows whose connection speed record fuzzily matches to 236.8 kbit/s . there is only one such row in the table . the carrier record of this unqiue row is moldcell .
|
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, 'launch date (ddmmyyyy)_8': 8, '2005_9': 9, 'connection speed_10': 10, '236.8kbit/s_11': 11, 'str_eq_4': 4, 'str_hop_3': 3, 'carrier_12': 12, 'moldcell_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', 'launch date (ddmmyyyy)_8': 'launch date ( ddmmyyyy )', '2005_9': '2005', 'connection speed_10': 'connection speed', '236.8kbit/s_11': '236.8 kbit/s', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'carrier_12': 'carrier', 'moldcell_13': 'moldcell'}
|
{'and_5': [6], 'result_6': [], 'only_2': [5], 'filter_str_eq_1': [2, 3], 'filter_str_eq_0': [1], 'all_rows_7': [0], 'launch date (ddmmyyyy)_8': [0], '2005_9': [0], 'connection speed_10': [1], '236.8kbit/s_11': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'carrier_12': [3], 'moldcell_13': [4]}
|
['carrier', 'standard', 'frequency', 'connection speed', 'launch date ( ddmmyyyy )']
|
[['orange', 'gsm gprs', '900 mhz and 1800 mhz', '56 kbit / s', '14.09.2005'], ['orange', 'gsm edge', '900 mhz and 1800 mhz', '236.8 kbit / s', '17.04.2006'], ['moldcell', 'gsm gprs', '900 mhz and 1800 mhz', '56 kbit / s', '31.01.2005'], ['moldcell', 'gsm edge', '900 mhz and 1800 mhz', '236.8 kbit / s', '07.06.2005'], ['unitã', 'cdma 1x', '450 mhz', '153 kbit / s', '01.03.2007'], ['idc', 'cdma 1x', '800 mhz', '153 kbit / s', '09.09.1999']]
|
1949 vfl season
|
https://en.wikipedia.org/wiki/1949_VFL_season
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10809351-5.html.csv
|
majority
|
all games of the 1949 vfl season were played on the 14th of may .
|
{'scope': 'all', 'col': '7', 'most_or_all': 'all', 'criterion': 'equal', 'value': '14 may 1949', 'subset': None}
|
{'func': 'all_str_eq', 'args': ['all_rows', 'date', '14 may 1949'], 'result': True, 'ind': 0, 'tointer': 'for the date records of all rows , all of them fuzzily match to 14 may 1949 .', 'tostr': 'all_eq { all_rows ; date ; 14 may 1949 } = true'}
|
all_eq { all_rows ; date ; 14 may 1949 } = true
|
for the date records of all rows , all of them fuzzily match to 14 may 1949 .
|
1
|
1
|
{'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'date_3': 3, '14 may 1949_4': 4}
|
{'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'date_3': 'date', '14 may 1949_4': '14 may 1949'}
|
{'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'date_3': [0], '14 may 1949_4': [0]}
|
['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date']
|
[['melbourne', '5.16 ( 46 )', 'north melbourne', '6.12 ( 48 )', 'mcg', '19000', '14 may 1949'], ['geelong', '15.13 ( 103 )', 'st kilda', '10.11 ( 71 )', 'kardinia park', '15500', '14 may 1949'], ['essendon', '11.18 ( 84 )', 'richmond', '9.15 ( 69 )', 'windy hill', '21000', '14 may 1949'], ['carlton', '16.8 ( 104 )', 'collingwood', '10.14 ( 74 )', 'princes park', '33000', '14 may 1949'], ['south melbourne', '10.8 ( 68 )', 'footscray', '6.14 ( 50 )', 'lake oval', '11000', '14 may 1949'], ['hawthorn', '9.13 ( 67 )', 'fitzroy', '14.21 ( 105 )', 'glenferrie oval', '7500', '14 may 1949']]
|
shane hall
|
https://en.wikipedia.org/wiki/Shane_Hall
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2649597-1.html.csv
|
comparative
|
shane hall drove more formula one races in the year 2001 than he did in the year 2003 .
|
{'row_1': '7', 'row_2': '9', 'col': '2', 'col_other': '1', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None}
|
{'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'year', '2001'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose year record fuzzily matches to 2001 .', 'tostr': 'filter_eq { all_rows ; year ; 2001 }'}, 'races'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; year ; 2001 } ; races }', 'tointer': 'select the rows whose year record fuzzily matches to 2001 . take the races record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'year', '2003'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose year record fuzzily matches to 2003 .', 'tostr': 'filter_eq { all_rows ; year ; 2003 }'}, 'races'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; year ; 2003 } ; races }', 'tointer': 'select the rows whose year record fuzzily matches to 2003 . take the races record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; year ; 2001 } ; races } ; hop { filter_eq { all_rows ; year ; 2003 } ; races } } = true', 'tointer': 'select the rows whose year record fuzzily matches to 2001 . take the races record of this row . select the rows whose year record fuzzily matches to 2003 . take the races record of this row . the first record is greater than the second record .'}
|
greater { hop { filter_eq { all_rows ; year ; 2001 } ; races } ; hop { filter_eq { all_rows ; year ; 2003 } ; races } } = true
|
select the rows whose year record fuzzily matches to 2001 . take the races record of this row . select the rows whose year record fuzzily matches to 2003 . take the races record of this row . the first record is greater than the second record .
|
5
|
5
|
{'greater_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'year_7': 7, '2001_8': 8, 'races_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'year_11': 11, '2003_12': 12, 'races_13': 13}
|
{'greater_4': 'greater', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'year_7': 'year', '2001_8': '2001', 'races_9': 'races', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'year_11': 'year', '2003_12': '2003', 'races_13': 'races'}
|
{'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'year_7': [0], '2001_8': [0], 'races_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'year_11': [1], '2003_12': [1], 'races_13': [3]}
|
['year', 'races', 'wins', 'poles', 'top 5', 'top 10', 'dnf', 'finish', 'start', 'winnings', 'season rank', 'team ( s )']
|
[['1995', '2', '0', '0', '0', '0', '0', '24.0', '37.0', '5225', '75th', 'stegell motorsports'], ['1996', '14', '0', '0', '0', '0', '6', '26.4', '25.1', '63865', '42nd', 'stegell motorsports'], ['1997', '28', '0', '1', '0', '1', '10', '27.1', '21.6', '196656', '23rd', 'stegell motorsports'], ['1998', '31', '0', '1', '0', '3', '5', '24.9', '25.5', '335163', '19th', 'stegell motorsports'], ['1999', '25', '0', '0', '1', '1', '9', '25.8', '18.2', '243810', '24th', 'curb - agajanian performance group'], ['2000', '2', '0', '0', '0', '0', '1', '35.0', '28.5', '15900', '90th', 'alumni motorsports'], ['2001', '33', '0', '0', '0', '0', '6', '27.9', '32.7', '491977', '23rd', 'hensley racing'], ['2002', '24', '0', '0', '0', '1', '11', '27.0', '33.0', '288325', '29th', 'hensley racing'], ['2003', '5', '0', '0', '0', '0', '4', '35.8', '25.6', '68360', '85th', 'jay robinson racing'], ['2004', '9', '0', '0', '0', '0', '6', '31.4', '37.2', '139685', '54th', 'moy racing / jay robinson racing'], ['2005', '7', '0', '0', '0', '0', '7', '40.9', '32.6', '108921', '83rd', 'jay robinson racing'], ['2006', '9', '0', '0', '0', '0', '7', '38.9', '39.1', '151184', '70th', 'jay robinson racing'], ['2008', '1', '0', '0', '0', '0', '1', '43.0', '34.0', '15674', '149th', 'jay robinson racing']]
|
red dwarf
|
https://en.wikipedia.org/wiki/Red_Dwarf
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-25721-4.html.csv
|
count
|
there were three region 2 dvd releases of the show red dwarf in the year 2004 .
|
{'scope': 'all', 'criterion': 'fuzzily_match', 'value': '2004', 'result': '3', 'col': '4', 'subset': None}
|
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'region 2', '2004'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose region 2 record fuzzily matches to 2004 .', 'tostr': 'filter_eq { all_rows ; region 2 ; 2004 }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; region 2 ; 2004 } }', 'tointer': 'select the rows whose region 2 record fuzzily matches to 2004 . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; region 2 ; 2004 } } ; 3 } = true', 'tointer': 'select the rows whose region 2 record fuzzily matches to 2004 . the number of such rows is 3 .'}
|
eq { count { filter_eq { all_rows ; region 2 ; 2004 } } ; 3 } = true
|
select the rows whose region 2 record fuzzily matches to 2004 . 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, 'region 2_5': 5, '2004_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', 'region 2_5': 'region 2', '2004_6': '2004', '3_7': '3'}
|
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'region 2_5': [0], '2004_6': [0], '3_7': [2]}
|
['release', 'of discs', 'region 1', 'region 2', 'region 4']
|
[['series i', '2', '25 february 2003', '4 november 2002', '3 december 2002'], ['series ii', '2', '25 february 2003', '10 february 2003', '1 april 2003'], ['series iii', '2', '3 february 2004', '3 november 2003', '18 november 2003'], ['series iv', '2', '3 february 2004', '16 february 2004', '9 march 2004'], ['just the shows vol 1 series 1 - 4 with no extras', '4', 'n / a', '18 october 2004', '12 november 2004'], ['series v', '2', '15 march 2005', '8 november 2004', '1 december 2004'], ['series vi', '2', '15 march 2005', '21 february 2005', '6 april 2005'], ['series vii', '3', '10 january 2006', '7 november 2005', '1 december 2005'], ['series viii', '3', '2 may 2006', '27 march 2006', '20 april 2006'], ['the complete collection series 1 - 8 with extras', '18', '5 september 2006', 'n / a', 'n / a'], ['just the shows vol 2 series 5 - 8 with no extras', '6', 'n / a', '2 october 2006', '3 november 2006'], ['beat the geek ( interactive dvd quiz game )', '1', 'n / a', '23 october 2006', '3 march 2011'], ['all the shows series 1 - 8 with no extras', '10', 'n / a', '10 november 2008', 'n / a'], ['back to earth', '2', '6 october 2009', '15 june 2009', '17 december 2009'], ['just the shows series 1 - 8 with no extras', '10', 'n / a', '9 november 2009', 'n / a']]
|
list of largest nordic companies
|
https://en.wikipedia.org/wiki/List_of_largest_Nordic_companies
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12794433-3.html.csv
|
majority
|
the majority of largest nordic companies are headquartered in sweden .
|
{'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'sweden', 'subset': None}
|
{'func': 'most_str_eq', 'args': ['all_rows', 'headquarters', 'sweden'], 'result': True, 'ind': 0, 'tointer': 'for the headquarters records of all rows , most of them fuzzily match to sweden .', 'tostr': 'most_eq { all_rows ; headquarters ; sweden } = true'}
|
most_eq { all_rows ; headquarters ; sweden } = true
|
for the headquarters records of all rows , most of them fuzzily match to sweden .
|
1
|
1
|
{'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'headquarters_3': 3, 'sweden_4': 4}
|
{'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'headquarters_3': 'headquarters', 'sweden_4': 'sweden'}
|
{'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'headquarters_3': [0], 'sweden_4': [0]}
|
['rank', 'company', 'headquarters', 'industry', 'employees', 'reference date']
|
[['1', 'iss', 'copenhagen , denmark', 'facility management', '534500', '2011'], ['2', 'securitas', 'stockholm , sweden', 'security services', '272425', '2011'], ['3', 'nokia', 'espoo , finland', 'technology', '130050', '2011'], ['4', 'ap mãller - maersk', 'copenhagen , denmark', 'transportation', '117080', '2011'], ['5', 'ericsson', 'stockholm , sweden', 'telecommunication', '104525', '2011'], ['6', 'volvo', 'gothenburg , sweden', 'automotive', '98162', '2011'], ['7', 'h & m', 'stockholm , sweden', 'retailing', '64874', '2011'], ['8', 'electrolux', 'stockholm , sweden', 'manufacturing', '52916', '2011'], ['9', 'skanska', 'stockholm , sweden', 'construction', '52557', '2011'], ['10', 'sandvik', 'sandviken , sweden', 'capital goods', '50030', '2011']]
|
list of how it 's made episodes
|
https://en.wikipedia.org/wiki/List_of_How_It%27s_Made_episodes
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15187735-12.html.csv
|
unique
|
only episode 147 of how it 's made drama series have segmented parts 1 and 2 .
|
{'scope': 'all', 'row': '4', 'col': '6', 'col_other': '2', 'criterion': 'fuzzily_match', 'value': 'part 1', 'subset': None}
|
{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'segment c', 'part 1'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose segment c record fuzzily matches to part 1 .', 'tostr': 'filter_eq { all_rows ; segment c ; part 1 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; segment c ; part 1 } }', 'tointer': 'select the rows whose segment c record fuzzily matches to part 1 . there is only one such row in the table .'}, {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'segment c', 'part 1'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose segment c record fuzzily matches to part 1 .', 'tostr': 'filter_eq { all_rows ; segment c ; part 1 }'}, 'episode'], 'result': '147', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; segment c ; part 1 } ; episode }'}, '147'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; segment c ; part 1 } ; episode } ; 147 }', 'tointer': 'the episode record of this unqiue row is 147 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; segment c ; part 1 } } ; eq { hop { filter_eq { all_rows ; segment c ; part 1 } ; episode } ; 147 } } = true', 'tointer': 'select the rows whose segment c record fuzzily matches to part 1 . there is only one such row in the table . the episode record of this unqiue row is 147 .'}
|
and { only { filter_eq { all_rows ; segment c ; part 1 } } ; eq { hop { filter_eq { all_rows ; segment c ; part 1 } ; episode } ; 147 } } = true
|
select the rows whose segment c record fuzzily matches to part 1 . there is only one such row in the table . the episode record of this unqiue row is 147 .
|
6
|
5
|
{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'segment c_7': 7, 'part 1_8': 8, 'eq_3': 3, 'num_hop_2': 2, 'episode_9': 9, '147_10': 10}
|
{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'segment c_7': 'segment c', 'part 1_8': 'part 1', 'eq_3': 'eq', 'num_hop_2': 'num_hop', 'episode_9': 'episode', '147_10': '147'}
|
{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'segment c_7': [0], 'part 1_8': [0], 'eq_3': [4], 'num_hop_2': [3], 'episode_9': [2], '147_10': [3]}
|
['series ep', 'episode', 'netflix', 'segment a', 'segment b', 'segment c', 'segment d']
|
[['12 - 01', '144', 's06e14', 'pneumatic impact wrenches', 'cultured marble sinks', 'plantain chips', 'nascar stock cars'], ['12 - 02', '145', 's06e15', 'jaws of life', 'artificial christmas trees', 'soda crackers', 'ratchets'], ['12 - 03', '146', 's06e16', 's thermometer', 'produce scales', 'aircraft painting', 'luxury s chocolate'], ['12 - 04', '147', 's06e17', 'carburetors', 'air conditioners', 'sugar ( part 1 )', 'sugar ( part 2 )'], ['12 - 05', '148', 's06e18', 'combination wrenches', 'deli meats', 'golf cars', 'airships'], ['12 - 06', '149', 's06e19', 'carbon fibre car parts', 'hand dryers', 'recycled polyester yarn', 'fleece'], ['12 - 07', '150', 's06e20', 'police badges', 'muffins', 'car washes', 'pressure gauges'], ['12 - 08', '151', 's06e21', 'metal detectors', 'rum', 'tiffany reproductions', 'aircraft engines'], ['12 - 09', '152', 's06e22', 'riding mowers', 'popcorn', 'adjustable beds', 'cultured diamonds'], ['12 - 10', '153', 's06e23', 'airstream trailers', 'horseradish', 'industrial steam s boiler', 'deodorant'], ['12 - 11', '154', 's06e24', 's screwdriver', 'compact track loaders', 'physician scales', 'carbon fibre bats'], ['12 - 12', '155', 's06e25', 's escalator', 'kevlar s canoe', 'goat cheese', 'disc music boxes'], ['12 - 13', '156', 's06e26', 'motorcycle engines', 'glass enamel sculptures', 'hand - made paper', 'vaulting poles']]
|
2008 in paraguayan football
|
https://en.wikipedia.org/wiki/2008_in_Paraguayan_football
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17334827-6.html.csv
|
superlative
|
the june 18 , 2008 game was the highest scoring game for paraguay in the year 2008 .
|
{'scope': 'all', 'col_superlative': '3', 'row_superlative': '2', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None}
|
{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'score'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; score }'}, 'date'], 'result': 'june 18 , 2008', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; score } ; date }'}, 'june 18 , 2008'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; score } ; date } ; june 18 , 2008 } = true', 'tointer': 'select the row whose score record of all rows is maximum . the date record of this row is june 18 , 2008 .'}
|
eq { hop { argmax { all_rows ; score } ; date } ; june 18 , 2008 } = true
|
select the row whose score record of all rows is maximum . the date record of this row is june 18 , 2008 .
|
3
|
3
|
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'score_5': 5, 'date_6': 6, 'june 18 , 2008_7': 7}
|
{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'score_5': 'score', 'date_6': 'date', 'june 18 , 2008_7': 'june 18 , 2008'}
|
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'score_5': [0], 'date_6': [1], 'june 18 , 2008_7': [2]}
|
['date', 'venue', 'score', 'comp', 'paraguay scorers', 'report']
|
[['june 15 , 2008', 'defensores del chaco asunción , paraguay', '2 - 0', 'wcq 2010', "santa cruz 26 ' cabañas 49 '", 'report'], ['june 18 , 2008', 'estadio hernando siles la paz , bolivia', '4 - 2', 'wcq 2010', "santa cruz 66 ' haedo valdez 82 '", 'report'], ['september 6 , 2008', 'estadio monumental buenos aires , argentina', '1 - 1', 'wcq2010', "heinze 13 ' ( og )", 'report'], ['september 9 , 2008', 'defensores del chaco asunción , paraguay', '2 - 0', 'wcq2010', "riveros 28 ' haedo valdez 45 '", 'report'], ['october 11 , 2008', 'el campín bogotá , colombia', '0 - 1', 'wcq2010', "cabañas 9 '", 'report'], ['october 15 , 2008', 'defensores del chaco asunción , paraguay', '1 - 0', 'wcq2010', "cardozo 81 '", 'report'], ['november 19 , 2008', 'sultan qaboos sports complex muscat , oman', '0 - 1', 'f', "vera 37 '", 'n / a']]
|
teen angels
|
https://en.wikipedia.org/wiki/Teen_Angels
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18073917-17.html.csv
|
unique
|
the year 2011 was the only year that teen angels was nominated in the category favorite music group .
|
{'scope': 'all', 'row': '6', 'col': '3', 'col_other': '1', 'criterion': 'equal', 'value': 'favorite music group', 'subset': None}
|
{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'category', 'favorite music group'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose category record fuzzily matches to favorite music group .', 'tostr': 'filter_eq { all_rows ; category ; favorite music group }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; category ; favorite music group } }', 'tointer': 'select the rows whose category record fuzzily matches to favorite music group . there is only one such row in the table .'}, {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'category', 'favorite music group'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose category record fuzzily matches to favorite music group .', 'tostr': 'filter_eq { all_rows ; category ; favorite music group }'}, 'year'], 'result': '2011', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; category ; favorite music group } ; year }'}, '2011'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; category ; favorite music group } ; year } ; 2011 }', 'tointer': 'the year record of this unqiue row is 2011 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; category ; favorite music group } } ; eq { hop { filter_eq { all_rows ; category ; favorite music group } ; year } ; 2011 } } = true', 'tointer': 'select the rows whose category record fuzzily matches to favorite music group . there is only one such row in the table . the year record of this unqiue row is 2011 .'}
|
and { only { filter_eq { all_rows ; category ; favorite music group } } ; eq { hop { filter_eq { all_rows ; category ; favorite music group } ; year } ; 2011 } } = true
|
select the rows whose category record fuzzily matches to favorite music group . there is only one such row in the table . the year record of this unqiue row is 2011 .
|
6
|
5
|
{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'category_7': 7, 'favorite music group_8': 8, 'eq_3': 3, 'num_hop_2': 2, 'year_9': 9, '2011_10': 10}
|
{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'category_7': 'category', 'favorite music group_8': 'favorite music group', 'eq_3': 'eq', 'num_hop_2': 'num_hop', 'year_9': 'year', '2011_10': '2011'}
|
{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'category_7': [0], 'favorite music group_8': [0], 'eq_3': [4], 'num_hop_2': [3], 'year_9': [2], '2011_10': [3]}
|
['year', 'award', 'category', 'nominated', 'result']
|
[['2009', 'capif awards', 'best album by a film / television band', 'teen angels', 'won'], ['2009', 'premios carlos gardel 2009', 'best album by a film / television band', 'teen angels', 'won'], ['2009', 'premios 40 principales', 'best argentine act', 'teen angels', 'won'], ['2010', 'premios carlos gardel 2010', 'best album by a film / television band', 'teen angels', 'won'], ['2010', 'premios 40 principales', 'best argentine act', 'teen angels', 'won'], ['2011', "kids ' choice awards argentina 2011", 'favorite music group', 'teen angels', 'won'], ['2011', 'premios carlos gardel', 'mejor álbum infantil / juvenil por teenangels 4', 'teen angels', 'pending']]
|
cass technical high school
|
https://en.wikipedia.org/wiki/Cass_Technical_High_School
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1198175-1.html.csv
|
superlative
|
at cass technical high school , the highest weight was joseph barksdale .
|
{'scope': 'all', 'col_superlative': '4', 'row_superlative': '16', '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', 'weight ( lbs )'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; weight ( lbs ) }'}, 'name'], 'result': 'joseph barksdale', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; weight ( lbs ) } ; name }'}, 'joseph barksdale'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; weight ( lbs ) } ; name } ; joseph barksdale } = true', 'tointer': 'select the row whose weight ( lbs ) record of all rows is maximum . the name record of this row is joseph barksdale .'}
|
eq { hop { argmax { all_rows ; weight ( lbs ) } ; name } ; joseph barksdale } = true
|
select the row whose weight ( lbs ) record of all rows is maximum . the name record of this row is joseph barksdale .
|
3
|
3
|
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'weight (lbs)_5': 5, 'name_6': 6, 'joseph barksdale_7': 7}
|
{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'weight (lbs)_5': 'weight ( lbs )', 'name_6': 'name', 'joseph barksdale_7': 'joseph barksdale'}
|
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'weight (lbs)_5': [0], 'name_6': [1], 'joseph barksdale_7': [2]}
|
['name', 'position', 'height', 'weight ( lbs )', 'born', 'college', 'drafted']
|
[['walter clago', 'e', "6 ' 0", '195', '6 / / 1899 detroit , mi', 'detroit', 'undrafted'], ['darris mccord', 'de / dt / oe', "6 ' 6", '250', 'january 4 , 1933 detroit , mi', 'tennessee', '1955 , r3 , p11'], ['ben john paolucci', 'dt', "6 ' 2", '240', 'march 5 , 1937 cleveland , oh', 'wayne state', 'undrafted'], ['arnie simkus', 'de / dt', "6 ' 4", '245', 'march 25 , 1943 schlava , ger', 'michigan', '1965 , r6 , p2'], ['david boone , jr', 'de', "6 ' 3", '248', 'october 30 , 1951 detroit , mi', 'eastern mich', '1974 , r11 , p11'], ['aaron kyle', 'cb / s', "5 ' 11", '185', 'april 6 , 1954 detroit , mi', 'wyoming', '1976 , r1 , p26'], ['tom seabron', 'lb', "6 ' 3", '215', 'may 24 , 1957 baltimore , md', 'michigan', '1979 , r5 , p1'], ['harlan huckleby', 'rb', "6 ' 1", '200', 'december 30 , 1957 detroit , mi', 'michigan', '1979 , r5 , p1'], ['curtis greer', 'de', "6 ' 4", '256', 'november 10 , 1957 detroit , mi', 'michigan', '1976 , r1 , p6'], ['guy frazier', 'lb', "6 ' 2", '217', 'july 20 , 1959 detroit , mi', 'wyoming', '1981 , r4 , p10'], ['thomas sidney sims', 'dt / nt', "6 ' 2", '288', 'april 18 , 1967 detroit , mi', 'pittsburgh', '1990 , r6 , p14'], ['pat ivey', 'de', "6 ' 4", '255', 'december 27 , 1972 detroit , mi', 'mizzou', 'undrafted'], ['a j ofodile', 'te', "6 ' 7", '260', 'october 9 , 1973 detroit , mi', 'mizzou', '1994 , r5 , p25'], ['clarence williams', 'rb', "5 ' 9", '193', 'may 16 , 1977 detroit , mi', 'michigan', 'undrafted'], ['vernon gholston', 'de', "6 ' 3", '264', 'june 5 , 1986 detroit , mi', 'ohio state', '2008 , r1 , p6'], ['joseph barksdale', 'ot', "6 ' 4", '325', 'january 1 , 1989 detroit , mi', 'lsu', '2011 , r3 , p12'], ['will campbell', 'og', "6 ' 4", '311', 'july 6 , 1991 detroit , mi', 'michigan', '2013 , r6 , p10']]
|
nevada gaming area
|
https://en.wikipedia.org/wiki/Nevada_gaming_area
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-25438110-5.html.csv
|
comparative
|
clark county has a higher number of casinos in the nevada gaming area than south lake tahoe .
|
{'row_1': '1', 'row_2': '4', 'col': '1', 'col_other': '2', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None}
|
{'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'county', 'clark'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose county record fuzzily matches to clark .', 'tostr': 'filter_eq { all_rows ; county ; clark }'}, 'casinos'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; county ; clark } ; casinos }', 'tointer': 'select the rows whose county record fuzzily matches to clark . take the casinos record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'county', 'south lake tahoe'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose county record fuzzily matches to south lake tahoe .', 'tostr': 'filter_eq { all_rows ; county ; south lake tahoe }'}, 'casinos'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; county ; south lake tahoe } ; casinos }', 'tointer': 'select the rows whose county record fuzzily matches to south lake tahoe . take the casinos record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; county ; clark } ; casinos } ; hop { filter_eq { all_rows ; county ; south lake tahoe } ; casinos } } = true', 'tointer': 'select the rows whose county record fuzzily matches to clark . take the casinos record of this row . select the rows whose county record fuzzily matches to south lake tahoe . take the casinos record of this row . the first record is greater than the second record .'}
|
greater { hop { filter_eq { all_rows ; county ; clark } ; casinos } ; hop { filter_eq { all_rows ; county ; south lake tahoe } ; casinos } } = true
|
select the rows whose county record fuzzily matches to clark . take the casinos record of this row . select the rows whose county record fuzzily matches to south lake tahoe . take the casinos 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, 'county_7': 7, 'clark_8': 8, 'casinos_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'county_11': 11, 'south lake tahoe_12': 12, 'casinos_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', 'county_7': 'county', 'clark_8': 'clark', 'casinos_9': 'casinos', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'county_11': 'county', 'south lake tahoe_12': 'south lake tahoe', 'casinos_13': 'casinos'}
|
{'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'county_7': [0], 'clark_8': [0], 'casinos_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'county_11': [1], 'south lake tahoe_12': [1], 'casinos_13': [3]}
|
['casinos', 'county', 'road', '1 - jul - 08', 'fy07 millions', 'fy08 millions', 'fy09 millions']
|
[['149', 'clark', 'i - 15', '1865746', '10538', '10172', '9081'], ['32', 'washoe', 'i - 80', '410443', '1045', '977', '856'], ['17', 'elko', 'i - 80', '47071', '324', '303', '279'], ['5', 'south lake tahoe', 'route 50', '45180', '283', '307', '264'], ['14', 'carson valley', 'route 395', '54867', '120', '114', '102']]
|
tri - state collegiate hockey league
|
https://en.wikipedia.org/wiki/Tri-State_Collegiate_Hockey_League
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-16384648-2.html.csv
|
comparative
|
in the tri - state collegiate hockey league , ohio university joined a year later than university of akron .
|
{'row_1': '5', 'row_2': '1', 'col': '4', 'col_other': '1', 'relation': 'diff', 'record_mentioned': 'no', 'diff_result': {'diff_value': '1 year', 'bigger': 'row1'}}
|
{'func': 'eq', 'args': [{'func': 'diff', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'institution', 'ohio university'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose institution record fuzzily matches to ohio university .', 'tostr': 'filter_eq { all_rows ; institution ; ohio university }'}, 'joined tschl'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; institution ; ohio university } ; joined tschl }', 'tointer': 'select the rows whose institution record fuzzily matches to ohio university . take the joined tschl record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'institution', 'university of akron'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose institution record fuzzily matches to university of akron .', 'tostr': 'filter_eq { all_rows ; institution ; university of akron }'}, 'joined tschl'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; institution ; university of akron } ; joined tschl }', 'tointer': 'select the rows whose institution record fuzzily matches to university of akron . take the joined tschl record of this row .'}], 'result': '1 year', 'ind': 4, 'tostr': 'diff { hop { filter_eq { all_rows ; institution ; ohio university } ; joined tschl } ; hop { filter_eq { all_rows ; institution ; university of akron } ; joined tschl } }'}, '1 year'], 'result': True, 'ind': 5, 'tostr': 'eq { diff { hop { filter_eq { all_rows ; institution ; ohio university } ; joined tschl } ; hop { filter_eq { all_rows ; institution ; university of akron } ; joined tschl } } ; 1 year } = true', 'tointer': 'select the rows whose institution record fuzzily matches to ohio university . take the joined tschl record of this row . select the rows whose institution record fuzzily matches to university of akron . take the joined tschl record of this row . the first record is 1 year larger than the second record .'}
|
eq { diff { hop { filter_eq { all_rows ; institution ; ohio university } ; joined tschl } ; hop { filter_eq { all_rows ; institution ; university of akron } ; joined tschl } } ; 1 year } = true
|
select the rows whose institution record fuzzily matches to ohio university . take the joined tschl record of this row . select the rows whose institution record fuzzily matches to university of akron . take the joined tschl record of this row . the first record is 1 year larger than the second record .
|
6
|
6
|
{'str_eq_5': 5, 'result_6': 6, 'diff_4': 4, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_7': 7, 'institution_8': 8, 'ohio university_9': 9, 'joined tschl_10': 10, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_11': 11, 'institution_12': 12, 'university of akron_13': 13, 'joined tschl_14': 14, '1 year_15': 15}
|
{'str_eq_5': 'str_eq', 'result_6': 'true', 'diff_4': 'diff', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_7': 'all_rows', 'institution_8': 'institution', 'ohio university_9': 'ohio university', 'joined tschl_10': 'joined tschl', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_11': 'all_rows', 'institution_12': 'institution', 'university of akron_13': 'university of akron', 'joined tschl_14': 'joined tschl', '1 year_15': '1 year'}
|
{'str_eq_5': [6], 'result_6': [], 'diff_4': [5], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_7': [0], 'institution_8': [0], 'ohio university_9': [0], 'joined tschl_10': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_11': [1], 'institution_12': [1], 'university of akron_13': [1], 'joined tschl_14': [3], '1 year_15': [5]}
|
['institution', 'location', 'team nickname', 'joined tschl', 'home arena', 'capacity', 'team website']
|
[['university of akron', 'akron , oh', 'zips', '2010', 'center ice sports complex', '900', 'zips hockey'], ['university of cincinnati', 'cincinnati , oh', 'bearcats', '2010', 'cincinnati gardens', '10208', 'cincinnati hockey'], ['university of dayton', 'dayton , oh', 'flyers', '2010', 'kettering rec center', '700', 'dayton hockey'], ['indiana university of pennsylvania', 'indiana , pa', 'crimson hawks', '2010', 's & t bank arena', '1000', 'iup hockey'], ['ohio university', 'athens , oh', 'bobcats', '2011', 'bird arena', '2000', 'ohio hockey'], ['university of toledo', 'toledo , oh', 'rockets', '2010', 'team toledo ice house', '1100', 'toledo hockey'], ['university of pittsburgh', 'pittsburgh , pa', 'panthers', '2010', 'bladerunners harmarville', '1200', 'pitt hockey'], ['west virginia university', 'morgantown , wv', 'mountaineers', '2010', 'morgantown municipal ice arena', '500', 'wvu hockey']]
|
leaf ( israeli company )
|
https://en.wikipedia.org/wiki/Leaf_%28Israeli_company%29
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16395908-2.html.csv
|
ordinal
|
the aptus ii 5 has the lowest iso range values at 25-400 .
|
{'row': '8', 'col': '6', 'order': '1', 'col_other': '1', 'max_or_min': 'min_to_max', 'value_mentioned': 'yes', 'scope': 'all', 'subset': None}
|
{'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'nth_min', 'args': ['all_rows', 'iso range', '1'], 'result': '25 - 400', 'ind': 0, 'tostr': 'nth_min { all_rows ; iso range ; 1 }', 'tointer': 'the 1st minimum iso range record of all rows is 25 - 400 .'}, '25 - 400'], 'result': True, 'ind': 1, 'tostr': 'eq { nth_min { all_rows ; iso range ; 1 } ; 25 - 400 }', 'tointer': 'the 1st minimum iso range record of all rows is 25 - 400 .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'iso range', '1'], 'result': None, 'ind': 2, 'tostr': 'nth_argmin { all_rows ; iso range ; 1 }'}, 'model'], 'result': 'aptus - ii 5', 'ind': 3, 'tostr': 'hop { nth_argmin { all_rows ; iso range ; 1 } ; model }'}, 'aptus - ii 5'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { nth_argmin { all_rows ; iso range ; 1 } ; model } ; aptus - ii 5 }', 'tointer': 'the model record of the row with 1st minimum iso range record is aptus - ii 5 .'}], 'result': True, 'ind': 5, 'tostr': 'and { eq { nth_min { all_rows ; iso range ; 1 } ; 25 - 400 } ; eq { hop { nth_argmin { all_rows ; iso range ; 1 } ; model } ; aptus - ii 5 } } = true', 'tointer': 'the 1st minimum iso range record of all rows is 25 - 400 . the model record of the row with 1st minimum iso range record is aptus - ii 5 .'}
|
and { eq { nth_min { all_rows ; iso range ; 1 } ; 25 - 400 } ; eq { hop { nth_argmin { all_rows ; iso range ; 1 } ; model } ; aptus - ii 5 } } = true
|
the 1st minimum iso range record of all rows is 25 - 400 . the model record of the row with 1st minimum iso range record is aptus - ii 5 .
|
6
|
6
|
{'and_5': 5, 'result_6': 6, 'eq_1': 1, 'nth_min_0': 0, 'all_rows_7': 7, 'iso range_8': 8, '1_9': 9, '25 - 400_10': 10, 'str_eq_4': 4, 'str_hop_3': 3, 'nth_argmin_2': 2, 'all_rows_11': 11, 'iso range_12': 12, '1_13': 13, 'model_14': 14, 'aptus - ii 5_15': 15}
|
{'and_5': 'and', 'result_6': 'true', 'eq_1': 'eq', 'nth_min_0': 'nth_min', 'all_rows_7': 'all_rows', 'iso range_8': 'iso range', '1_9': '1', '25 - 400_10': '25 - 400', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'nth_argmin_2': 'nth_argmin', 'all_rows_11': 'all_rows', 'iso range_12': 'iso range', '1_13': '1', 'model_14': 'model', 'aptus - ii 5_15': 'aptus - ii 5'}
|
{'and_5': [6], 'result_6': [], 'eq_1': [5], 'nth_min_0': [1], 'all_rows_7': [0], 'iso range_8': [0], '1_9': [0], '25 - 400_10': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'nth_argmin_2': [3], 'all_rows_11': [2], 'iso range_12': [2], '1_13': [2], 'model_14': [3], 'aptus - ii 5_15': [4]}
|
['model', 'released', 'sensor size', 'resolution', 'active pixels', 'iso range', 'dynamic range ( f - stops )', 'seconds / frame', 'lens conversion factor', 'display', 'storage']
|
[['aptus - ii 12r', '2010', '53.7 x40 .3 mm', '80 mp , 16 - bit', '10320 x 7752', '80 - 800', '12', '1.5', '1.0', '3.5 - inch touchscreen', 'firewire , cf'], ['aptus - ii 12', '2010', '53.7 x40 .3 mm', '80 mp , 16 - bit', '10320 x 7752', '80 - 800', '12', '1.5', '1.0', '3.5 - inch touchscreen', 'firewire , cf'], ['aptus - ii 10r', '2010', '56x36 mm', '56 mp , 16 - bit', '9288 x 6000', '80 - 800', '12', '1', '1.0', '3.5 - inch touchscreen', 'firewire , cf'], ['aptus - ii 10', '2010', '56x36 mm', '56 mp , 16 - bit', '9288 x 6000', '80 - 800', '12', '1', '1.0', '3.5 - inch touchscreen', 'firewire , cf'], ['aptus - ii 8', '2010', '44x33 mm', '40 mp , 16 - bit', '7360 x 5562', '80 - 800', '12', '8', '1.3', '3.5 - inch touchscreen', 'firewire , cf'], ['aptus - ii 7', '2009', '48x36 mm', '33 mp , 16 - bit', '6726 x 5040', '50 - 800', '12', '1.1', '1.1', '3.5 - inch touchscreen', 'firewire , cf'], ['aptus - ii 6', '2009', '44x33 mm', '28 mp , 16 - bit', '6144 x 4622', '50 - 800', '12', '1', '1.3', '3.5 - inch touchscreen', 'firewire , cf'], ['aptus - ii 5', '2009', '48x36 mm', '22 mp , 16 - bit', '5356 x 4056', '25 - 400', '12', '9', '1.1', '3.5 - inch touchscreen', 'firewire , cf']]
|
2007 - 08 los angeles clippers season
|
https://en.wikipedia.org/wiki/2007%E2%80%9308_Los_Angeles_Clippers_season
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11965402-7.html.csv
|
aggregation
|
the average crowd attendance during the 2007 - 08 los angeles clippers season was 17863 .
|
{'scope': 'all', 'col': '6', 'type': 'average', 'result': '17863', 'subset': None}
|
{'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'attendance'], 'result': '17863', 'ind': 0, 'tostr': 'avg { all_rows ; attendance }'}, '17863'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; attendance } ; 17863 } = true', 'tointer': 'the average of the attendance record of all rows is 17863 .'}
|
round_eq { avg { all_rows ; attendance } ; 17863 } = true
|
the average of the attendance record of all rows is 17863 .
|
2
|
2
|
{'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'attendance_4': 4, '17863_5': 5}
|
{'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'attendance_4': 'attendance', '17863_5': '17863'}
|
{'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'attendance_4': [0], '17863_5': [1]}
|
['date', 'visitor', 'score', 'home', 'leading scorer', 'attendance', 'record']
|
[['march 1 , 2008', 'pistons', '103 - 73', 'clippers', 'corey maggette ( 22 )', '19271', '19 - 38'], ['march 3 , 2008', 'sixers', '106 - 80', 'clippers', 'al thornton ( 20 )', '15691', '19 - 39'], ['march 5 , 2008', 'kings', '109 - 116', 'clippers', 'al thornton ( 27 )', '17030', '20 - 39'], ['march 7 , 2008', 'clippers', '82 - 119', 'lakers', 'corey maggette ( 22 )', '18997', '20 - 40'], ['march 8 , 2008', 'timberwolves', '99 - 96', 'clippers', 'corey maggette ( 29 )', '17807', '20 - 41'], ['march 10 , 2008', 'clippers', '99 - 98', 'heat', 'cuttino mobley ( 29 )', '19014', '21 - 41'], ['march 12 , 2008', 'clippers', '88 - 110', 'magic', 'corey maggette ( 22 )', '16312', '21 - 42'], ['march 14 , 2008', 'clippers', '93 - 117', 'hawks', 'two way tie ( 18 )', '16107', '21 - 43'], ['march 15 , 2008', 'clippers', '109 - 119', 'wizards', 'corey maggette ( 34 )', '20173', '21 - 44'], ['march 17 , 2008', 'clippers', '90 - 99', 'timberwolves', 'corey maggette ( 34 )', '10034', '21 - 45'], ['march 19 , 2008', 'warriors', '116 - 100', 'clippers', 'al thornton ( 24 )', '18704', '21 - 46'], ['march 21 , 2008', 'clippers', '102 - 107', 'trail blazers', 'cuttino mobley ( 24 )', '19980', '21 - 47'], ['march 22 , 2008', 'trail blazers', '83 - 72', 'clippers', 'corey maggette ( 21 )', '18248', '21 - 48'], ['march 25 , 2008', 'clippers', '90 - 103', 'mavericks', 'corey maggette ( 21 )', '20207', '21 - 49'], ['march 26 , 2008', 'clippers', '88 - 97', 'spurs', 'corey maggette ( 22 )', '18797', '21 - 50'], ['march 28 , 2008', 'clippers', '101 - 121', 'jazz', 'corey maggette ( 28 )', '19911', '21 - 51'], ['march 29 , 2008', 'grizzlies', '97 - 110', 'clippers', 'al thornton ( 39 )', '18125', '22 - 51'], ['march 31 , 2008', 'mavericks', '93 - 86', 'clippers', 'al thornton ( 26 )', '17124', '22 - 52']]
|
list of tallest buildings in montreal
|
https://en.wikipedia.org/wiki/List_of_tallest_buildings_in_Montreal
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1722194-5.html.csv
|
count
|
2 of the tallest buildings in montreal have 47 floors .
|
{'scope': 'all', 'criterion': 'equal', 'value': '47', 'result': '2', 'col': '6', 'subset': None}
|
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'floors', '47'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose floors record is equal to 47 .', 'tostr': 'filter_eq { all_rows ; floors ; 47 }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; floors ; 47 } }', 'tointer': 'select the rows whose floors record is equal to 47 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; floors ; 47 } } ; 2 } = true', 'tointer': 'select the rows whose floors record is equal to 47 . the number of such rows is 2 .'}
|
eq { count { filter_eq { all_rows ; floors ; 47 } } ; 2 } = true
|
select the rows whose floors record is equal to 47 . 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, 'floors_5': 5, '47_6': 6, '2_7': 7}
|
{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'floors_5': 'floors', '47_6': '47', '2_7': '2'}
|
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'floors_5': [0], '47_6': [0], '2_7': [2]}
|
['name', 'street address', 'years as tallest', 'of years as tallest', 'height m / ft', 'floors']
|
[['notre dame basilica', '110 notre - dame street west', '1829 - 1928', '99 years', '69 / 226', '7'], ['royal bank building', '360 saint jacques street west', '1928 - 1931', '3 years', '121 / 397', '22'], ['sun life building', '1155 metcalfe street', '1931 - 1962', '31 years', '122 / 400', '26'], ['tour cibc', '1155 rené lévesque boulevard west', '1962', '< 1 year', '187 / 614', '45'], ['place ville marie', '1 place ville - marie', '1962 - 1964', '2 years', '188 / 617', '47'], ['tour de la bourse', '800 victoria square', '1964 - 1992', '28 years', '194 / 637', '47'], ['1000 de la gauchetière', '1000 de la gauchetière street west', '1992 - present', '21 years ( current )', '205 / 673', '51']]
|
6 mm caliber
|
https://en.wikipedia.org/wiki/6_mm_caliber
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1058122-4.html.csv
|
superlative
|
the 6.5 x 68 cartilage has the longest length among all of the 6mm calibers .
|
{'scope': 'all', 'col_superlative': '3', 'row_superlative': '6', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None}
|
{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'length'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; length }'}, 'name'], 'result': '6.5 x 68', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; length } ; name }'}, '6.5 x 68'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; length } ; name } ; 6.5 x 68 } = true', 'tointer': 'select the row whose length record of all rows is maximum . the name record of this row is 6.5 x 68 .'}
|
eq { hop { argmax { all_rows ; length } ; name } ; 6.5 x 68 } = true
|
select the row whose length record of all rows is maximum . the name record of this row is 6.5 x 68 .
|
3
|
3
|
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'length_5': 5, 'name_6': 6, '6.5 x 68_7': 7}
|
{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'length_5': 'length', 'name_6': 'name', '6.5 x 68_7': '6.5 x 68'}
|
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'length_5': [0], 'name_6': [1], '6.5 x 68_7': [2]}
|
['name', 'bullet', 'length', 'base', 'shoulder', 'neck']
|
[['6.5 x 50 sr arisaka', '6.705 ( 264 )', '50.39 ( 1.984 )', '11.35 ( 447 )', '10.59 ( 417 )', '7.34 ( 289 )'], ['6.5 x 53.5 r dutch mannlicher', '6.756 ( 266 )', '53.59 ( 2.110 )', '11.48 ( 453 )', '10.75 ( 423 )', '7.55 ( 297 )'], ['6.5 x54 mm mannlicher - schãnauer', '6.705 ( 264 )', '53.65 ( 2.112 )', '11.47 ( 452 )', '10.87 ( 428 )', '7.56 ( 288 )'], ['6.5 x55 mm swedish ( aka 6.5 x55 mm krag )', '6.7 ( 264 )', '54.864 ( 2.16 )', '12.17 ( 479 )', '10.688 ( 420 )', '7.468 ( 294 )'], ['6.5 x58 mm vergueiro', '6.65 ( 262 )', '57.85 ( 2.278 )', '11.88 ( 468 )', '10.94 ( 431 )', '7.56 ( 298 )'], ['6.5 x 68', '6.70 ( 264 )', '75.02 ( 2.956 )', '13.30 ( 524 )', '12.18 ( 480 )', '7.60 ( 299 )'], ['6.5 - 284', '6.70 ( 264 )', '55.118 ( 2.170 )', '12.725 ( 501 )', '12.065 ( 475 )', '7.544 ( 297 )'], ['.260 remington', '6.70 ( 264 )', '51.7 ( 2.035 )', '11.9 ( 470 )', '11.5 ( 454 )', '7.5 ( 297 )'], ['6.5 mm creedmoor', '6.70 ( 264 )', '48.8 ( 1.924 )', '11.9 ( 470 )', '11.7 ( 459 )', '7.54 ( 297 )'], ['6.5 x47 mm lapua', '6.70 ( 264 )', '47 ( 1.9 )', '11.95 ( 470 )', '11.53 ( 454 )', '7.41 ( 292 )'], ['6.5 mm grendel', '6.70 ( 264 )', '38.7 ( 1.524 )', '11.14 ( 439 )', '10.87 ( 428 )', '7.44 ( 293 )'], ['.264 win magnum', '6.70 ( 264 )', '64 ( 2.5 )', '13.1 ( 515 )', '12.5 ( 491 )', '7.6 ( 299 )'], ['6.5 x 52 mm carcano', '6.80 ( 268 )', '52.50 ( 2.067 )', '11.42 ( 450 )', '10.85 ( 427 )', '7.52 ( 296 )']]
|
2010 fedex cup playoffs
|
https://en.wikipedia.org/wiki/2010_FedEx_Cup_Playoffs
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-28498999-4.html.csv
|
majority
|
most of the players tied for second place in the 2010 fedex cup playoffs were from australia .
|
{'scope': 'subset', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'australia', 'subset': {'col': '1', 'criterion': 'equal', 'value': 't2'}}
|
{'func': 'most_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', '', 't2'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; ; t2 }', 'tointer': 'select the rows whose record fuzzily matches to t2 .'}, 'country', 'australia'], 'result': True, 'ind': 1, 'tointer': 'select the rows whose record fuzzily matches to t2 . for the country records of these rows , most of them fuzzily match to australia .', 'tostr': 'most_eq { filter_eq { all_rows ; ; t2 } ; country ; australia } = true'}
|
most_eq { filter_eq { all_rows ; ; t2 } ; country ; australia } = true
|
select the rows whose record fuzzily matches to t2 . for the country records of these rows , most of them fuzzily match to australia .
|
2
|
2
|
{'most_str_eq_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, '_4': 4, 't2_5': 5, 'country_6': 6, 'australia_7': 7}
|
{'most_str_eq_1': 'most_str_eq', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', '_4': '', 't2_5': 't2', 'country_6': 'country', 'australia_7': 'australia'}
|
{'most_str_eq_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], '_4': [0], 't2_5': [0], 'country_6': [1], 'australia_7': [1]}
|
['', 'player', 'country', 'score', 'to par', 'winnings', 'after', 'before']
|
[['1', 'charley hoffman', 'united states', '64 + 67 + 69 + 62 = 262', '- 22', '1350000', '2', '59'], ['t2', 'jason day', 'australia', '63 + 67 + 66 + 71 = 267', '- 17', '560000', '4', '14'], ['t2', 'luke donald', 'england', '65 + 67 + 66 + 69 = 267', '- 17', '560000', '5', '17'], ['t2', 'geoff ogilvy', 'australia', '64 + 72 + 65 + 66 = 267', '- 17', '560000', '9', '52'], ['t5', 'tom gillis', 'united states', '67 + 71 + 65 + 65 = 268', '- 16', '273750', '48', '92'], ['t5', 'adam scott', 'australia', '67 + 69 + 65 + 67 = 268', '- 16', '273750', '15', '19'], ['t5', 'brandt snedeker', 'united states', '66 + 64 + 67 + 71 = 268', '- 16', '273750', '31', '53'], ['8', 'john senden', 'australia', '66 + 68 + 69 + 67 = 270', '- 14', '232500', '38', '64'], ['9', 'steve stricker', 'united states', '65 + 68 + 67 + 71 = 271', '- 13', '217500', '3', '2']]
|
iran at the 1998 asian games
|
https://en.wikipedia.org/wiki/Iran_at_the_1998_Asian_Games
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10831471-38.html.csv
|
majority
|
for iran at the 1998 asian games , of the events with competitors weight less than 65 kg , most of the atheletes did not advance to the quarterfinal .
|
{'scope': 'subset', 'col': '4', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'did not advance', 'subset': {'col': '2', 'criterion': 'less_than', 'value': '65 kg'}}
|
{'func': 'most_str_eq', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'event', '65 kg'], 'result': None, 'ind': 0, 'tostr': 'filter_less { all_rows ; event ; 65 kg }', 'tointer': 'select the rows whose event record is less than 65 kg .'}, 'quarterfinal', 'did not advance'], 'result': True, 'ind': 1, 'tointer': 'select the rows whose event record is less than 65 kg . for the quarterfinal records of these rows , most of them fuzzily match to did not advance .', 'tostr': 'most_eq { filter_less { all_rows ; event ; 65 kg } ; quarterfinal ; did not advance } = true'}
|
most_eq { filter_less { all_rows ; event ; 65 kg } ; quarterfinal ; did not advance } = true
|
select the rows whose event record is less than 65 kg . for the quarterfinal records of these rows , most of them fuzzily match to did not advance .
|
2
|
2
|
{'most_str_eq_1': 1, 'result_2': 2, 'filter_less_0': 0, 'all_rows_3': 3, 'event_4': 4, '65 kg_5': 5, 'quarterfinal_6': 6, 'did not advance_7': 7}
|
{'most_str_eq_1': 'most_str_eq', 'result_2': 'true', 'filter_less_0': 'filter_less', 'all_rows_3': 'all_rows', 'event_4': 'event', '65 kg_5': '65 kg', 'quarterfinal_6': 'quarterfinal', 'did not advance_7': 'did not advance'}
|
{'most_str_eq_1': [2], 'result_2': [], 'filter_less_0': [1], 'all_rows_3': [0], 'event_4': [0], '65 kg_5': [0], 'quarterfinal_6': [1], 'did not advance_7': [1]}
|
['athlete', 'event', 'round of 16', 'quarterfinal', 'semifinal', 'final']
|
[['alireza saadat', '52 kg', 'chulhang l 0 - 2', 'did not advance', 'did not advance', 'did not advance'], ['alireza rouzbahani', '56 kg', 'zheng l 0 - 2', 'did not advance', 'did not advance', 'did not advance'], ['ali khodaei', '60 kg', 'n / a', 'zhunuspekov l 1 - 2', 'did not advance', 'did not advance'], ['mansour norouzi', '65 kg', '-', 'zhamash l 1 - 2', 'did not advance', 'did not advance'], ['hossein ojaghi', '70 kg', 'n / a', '-', 'lumabas w 2 - 0', 'xiao l 1 - 2']]
|
royal canadian mint numismatic coins ( 2000s )
|
https://en.wikipedia.org/wiki/Royal_Canadian_Mint_numismatic_coins_%282000s%29
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11916083-49.html.csv
|
aggregation
|
the average composition of the numismatic coins was about 99 % silver .
|
{'scope': 'all', 'col': '4', 'type': 'average', 'result': '99', 'subset': None}
|
{'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'composition'], 'result': '99', 'ind': 0, 'tostr': 'avg { all_rows ; composition }'}, '99'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; composition } ; 99 } = true', 'tointer': 'the average of the composition record of all rows is 99 .'}
|
round_eq { avg { all_rows ; composition } ; 99 } = true
|
the average of the composition record of all rows is 99 .
|
2
|
2
|
{'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'composition_4': 4, '99_5': 5}
|
{'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'composition_4': 'composition', '99_5': '99'}
|
{'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'composition_4': [0], '99_5': [1]}
|
['year', 'theme', 'artist', 'composition', 'mintage', 'issue price']
|
[['2007', 'blue crystal - piedfort', 'konrad wachelko', '92.5 % silver , 7.5 % copper', '5000', '94.95'], ['2007', 'iridescent crystal - piedfort', 'konrad wachelko', '92.5 % silver , 7.5 % copper', '5000', '94.95'], ['2008', 'amethyst crystal', 'konrad wachelko', '99.99 % silver', '7500', '94.95'], ['2008', 'sapphire crystal', 'konrad wachelko', '99.99 % silver', '7500', '94.95'], ['2009', 'blue crystal', 'konrad wachelko', '99.99 % silver', '7500', '94.95'], ['2009', 'pink crystal', 'konrad wachelko', '99.99 % silver', '7500', '94.95'], ['2010', 'blue crystal', 'konrad wachelko', '99.99 % silver', '7500', '99.95'], ['2010', 'tanzanite crystal', 'konrad wachelko', '99.99 % silver', '7500', '99.95'], ['2011', 'emerald crystal', 'konrad wachelko', '99.99 % silver', '15000', '114.95'], ['2011', 'topaz crystal', 'konrad wachelko', '99.99 % silver', '15000', '114.95'], ['2011', 'hyacinth red small crystal', 'konrad wachelko', '99.99 % silver', '15000', '114.95'], ['2011', 'montana blue small crystal', 'konrad wachelko', '99.99 % silver', '15000', '114.95']]
|
swatch fivb world tour 2006
|
https://en.wikipedia.org/wiki/Swatch_FIVB_World_Tour_2006
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18395409-3.html.csv
|
unique
|
switzerland was the only nation to win only one gold medal in the 2006 swatch fivb world tour , .
|
{'scope': 'all', 'row': '5', 'col': '3', 'col_other': '2', 'criterion': 'equal', 'value': '1', 'subset': None}
|
{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'gold', '1'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose gold record is equal to 1 .', 'tostr': 'filter_eq { all_rows ; gold ; 1 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; gold ; 1 } }', 'tointer': 'select the rows whose gold record is equal to 1 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'gold', '1'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose gold record is equal to 1 .', 'tostr': 'filter_eq { all_rows ; gold ; 1 }'}, 'nation'], 'result': 'switzerland', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; gold ; 1 } ; nation }'}, 'switzerland'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; gold ; 1 } ; nation } ; switzerland }', 'tointer': 'the nation record of this unqiue row is switzerland .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; gold ; 1 } } ; eq { hop { filter_eq { all_rows ; gold ; 1 } ; nation } ; switzerland } } = true', 'tointer': 'select the rows whose gold record is equal to 1 . there is only one such row in the table . the nation record of this unqiue row is switzerland .'}
|
and { only { filter_eq { all_rows ; gold ; 1 } } ; eq { hop { filter_eq { all_rows ; gold ; 1 } ; nation } ; switzerland } } = true
|
select the rows whose gold record is equal to 1 . there is only one such row in the table . the nation record of this unqiue row is switzerland .
|
6
|
5
|
{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'gold_7': 7, '1_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'nation_9': 9, 'switzerland_10': 10}
|
{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'gold_7': 'gold', '1_8': '1', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'nation_9': 'nation', 'switzerland_10': 'switzerland'}
|
{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'gold_7': [0], '1_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'nation_9': [2], 'switzerland_10': [3]}
|
['rank', 'nation', 'gold', 'silver', 'bronze', 'total']
|
[['1', 'brazil', '17', '18', '15', '50'], ['2', 'united states', '5', '5', '4', '14'], ['3', 'china', '4', '5', '5', '14'], ['4', 'germany', '2', '1', '3', '6'], ['5', 'switzerland', '1', '0', '0', '1'], ['6', 'netherlands', '0', '0', '1', '1'], ['6', 'norway', '0', '0', '1', '1']]
|
1976 vfl season
|
https://en.wikipedia.org/wiki/1976_VFL_season
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10885968-6.html.csv
|
count
|
in the 1976 vfl season , among the games where away team scored below 11.00 , 2 of them had attendance above 15,000 .
|
{'scope': 'subset', 'criterion': 'greater_than', 'value': '15000', 'result': '2', 'col': '6', 'subset': {'col': '4', 'criterion': 'less_than', 'value': '11.0'}}
|
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'away team score', '11.0'], 'result': None, 'ind': 0, 'tostr': 'filter_less { all_rows ; away team score ; 11.0 }', 'tointer': 'select the rows whose away team score record is less than 11.0 .'}, 'crowd', '15000'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose away team score record is less than 11.0 . among these rows , select the rows whose crowd record is greater than 15000 .', 'tostr': 'filter_greater { filter_less { all_rows ; away team score ; 11.0 } ; crowd ; 15000 }'}], 'result': '2', 'ind': 2, 'tostr': 'count { filter_greater { filter_less { all_rows ; away team score ; 11.0 } ; crowd ; 15000 } }', 'tointer': 'select the rows whose away team score record is less than 11.0 . among these rows , select the rows whose crowd record is greater than 15000 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_greater { filter_less { all_rows ; away team score ; 11.0 } ; crowd ; 15000 } } ; 2 } = true', 'tointer': 'select the rows whose away team score record is less than 11.0 . among these rows , select the rows whose crowd record is greater than 15000 . the number of such rows is 2 .'}
|
eq { count { filter_greater { filter_less { all_rows ; away team score ; 11.0 } ; crowd ; 15000 } } ; 2 } = true
|
select the rows whose away team score record is less than 11.0 . among these rows , select the rows whose crowd record is greater than 15000 . the number of such rows is 2 .
|
4
|
4
|
{'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_greater_1': 1, 'filter_less_0': 0, 'all_rows_5': 5, 'away team score_6': 6, '11.0_7': 7, 'crowd_8': 8, '15000_9': 9, '2_10': 10}
|
{'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_greater_1': 'filter_greater', 'filter_less_0': 'filter_less', 'all_rows_5': 'all_rows', 'away team score_6': 'away team score', '11.0_7': '11.0', 'crowd_8': 'crowd', '15000_9': '15000', '2_10': '2'}
|
{'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_greater_1': [2], 'filter_less_0': [1], 'all_rows_5': [0], 'away team score_6': [0], '11.0_7': [0], 'crowd_8': [1], '15000_9': [1], '2_10': [3]}
|
['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date']
|
[['footscray', '11.9 ( 75 )', 'st kilda', '10.10 ( 70 )', 'western oval', '19978', '8 may 1976'], ['collingwood', '14.13 ( 97 )', 'geelong', '15.13 ( 103 )', 'victoria park', '23428', '8 may 1976'], ['south melbourne', '16.12 ( 108 )', 'melbourne', '21.10 ( 136 )', 'lake oval', '14270', '8 may 1976'], ['north melbourne', '19.21 ( 135 )', 'fitzroy', '9.9 ( 63 )', 'arden street oval', '10342', '8 may 1976'], ['hawthorn', '7.20 ( 62 )', 'carlton', '15.12 ( 102 )', 'princes park', '27055', '8 may 1976'], ['richmond', '17.17 ( 119 )', 'essendon', '9.10 ( 64 )', 'vfl park', '27631', '8 may 1976']]
|
mobile network operators of india
|
https://en.wikipedia.org/wiki/Mobile_network_operators_of_India
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-23801721-1.html.csv
|
majority
|
the majority of the mobile networks in india are privately owned .
|
{'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'not_equal', 'value': 'state - owned', 'subset': None}
|
{'func': 'most_str_not_eq', 'args': ['all_rows', 'ownership', 'state - owned'], 'result': True, 'ind': 0, 'tointer': 'for the ownership records of all rows , most of them do not match to state - owned .', 'tostr': 'most_not_eq { all_rows ; ownership ; state - owned } = true'}
|
most_not_eq { all_rows ; ownership ; state - owned } = true
|
for the ownership records of all rows , most of them do not match to state - owned .
|
1
|
1
|
{'most_str_not_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'ownership_3': 3, 'state - owned_4': 4}
|
{'most_str_not_eq_0': 'most_str_not_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'ownership_3': 'ownership', 'state - owned_4': 'state - owned'}
|
{'most_str_not_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'ownership_3': [0], 'state - owned_4': [0]}
|
['rank', 'operators name', 'technology', 'subscribers ( in millions )', 'ownership', 'market share']
|
[['2', 'reliance communications', 'cdmaone evdo gsm hspa wimax', '154.11 ( september 2012 )', 'reliance adag ( 67 % ) public ( 26 % )', 'n / a'], ['3', 'vodafone', 'gsm edge hsdpa', '155.5 ( october 2013 )', 'vodafone group ( 100 % )', '22.91 % ( october 2013 )'], ['4', 'idea cellular', 'gsm edge hspa', '127.2 ( q2 2013 )', 'aditya birla ( 49.05 % ) axiata group berhad ( 19.96 % )', '18.74 % ( october 2013 )'], ['5', 'bsnl', 'gsm edge hsdpa hspa + cdmaone evdo wimax wifi', '97.17 ( october 2013 )', 'state - owned', '14.31 % ( october 2013 )'], ['6', 'tata docomo virgin mobile india talk24 / t24', 'cdma evdo gsm edge hspa +', '90.09 ( august 2012 )', 'tata teleservices ( 74 % ) ntt docomo ( 26 % )', 'n / a'], ['7', 'aircel', 'gsm edge hsdpa', '63.20 ( october 2013 )', 'maxis communications ( 74 % ) apollo hospital ( 26 % )', '9.32 % ( october 2013 )'], ['9', 'mts india', 'cdma evdo', '14.01 ( october 2011 )', 'sistema ( 73.71 % ) shyam group ( 23.79 % )', 'n / a'], ['10', 'videocon', 'gsm gprs edge', '3.24 ( october 2013 )', 'videocon', '0.48 % ( october 2013 )'], ['11', 'mtnl', 'gsm hsdpa cdma', '3.61 ( october 2013 )', 'state - owned', '0.53 % ( october 2013 )'], ['12', 'loop mobile', 'gsm edge', '3.02 ( october 2013 )', 'khaitan holding group ( 100 % )', '0.45 % ( october 2013 )']]
|
athletics at the 2008 summer olympics - men 's 110 metres hurdles
|
https://en.wikipedia.org/wiki/Athletics_at_the_2008_Summer_Olympics_%E2%80%93_Men%27s_110_metres_hurdles
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18578891-4.html.csv
|
unique
|
konstadinos douvalidis is the only athlete from greece participating in the 110 metres men 's hurdles .
|
{'scope': 'all', 'row': '5', 'col': '4', 'col_other': '3', 'criterion': 'equal', 'value': 'greece', 'subset': None}
|
{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'nationality', 'greece'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose nationality record fuzzily matches to greece .', 'tostr': 'filter_eq { all_rows ; nationality ; greece }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; nationality ; greece } }', 'tointer': 'select the rows whose nationality record fuzzily matches to greece . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'nationality', 'greece'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose nationality record fuzzily matches to greece .', 'tostr': 'filter_eq { all_rows ; nationality ; greece }'}, 'athlete'], 'result': 'konstadinos douvalidis', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; nationality ; greece } ; athlete }'}, 'konstadinos douvalidis'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; nationality ; greece } ; athlete } ; konstadinos douvalidis }', 'tointer': 'the athlete record of this unqiue row is konstadinos douvalidis .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; nationality ; greece } } ; eq { hop { filter_eq { all_rows ; nationality ; greece } ; athlete } ; konstadinos douvalidis } } = true', 'tointer': 'select the rows whose nationality record fuzzily matches to greece . there is only one such row in the table . the athlete record of this unqiue row is konstadinos douvalidis .'}
|
and { only { filter_eq { all_rows ; nationality ; greece } } ; eq { hop { filter_eq { all_rows ; nationality ; greece } ; athlete } ; konstadinos douvalidis } } = true
|
select the rows whose nationality record fuzzily matches to greece . there is only one such row in the table . the athlete record of this unqiue row is konstadinos douvalidis .
|
6
|
5
|
{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'nationality_7': 7, 'greece_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'athlete_9': 9, 'konstadinos douvalidis_10': 10}
|
{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'nationality_7': 'nationality', 'greece_8': 'greece', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'athlete_9': 'athlete', 'konstadinos douvalidis_10': 'konstadinos douvalidis'}
|
{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'nationality_7': [0], 'greece_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'athlete_9': [2], 'konstadinos douvalidis_10': [3]}
|
['rank', 'lane', 'athlete', 'nationality', 'time', 'notes']
|
[['1', '4', 'dayron robles', 'cuba', '13.12', 'q'], ['2', '6', 'david payne', 'united states', '13.21', 'q , sb'], ['3', '5', 'ladji doucourã', 'france', '13.22', 'q , sb'], ['4', '3', 'richard phillips', 'jamaica', '13.43', 'q , sb'], ['5', '2', 'konstadinos douvalidis', 'greece', '13.55', '| | 0.157'], ['6', '8', 'gregory sedoc', 'netherlands', '13.60', '| | 0.162'], ['7', '7', 'petr svoboda', 'czech republic', '13.60', '| | 0.182'], ['8', '9', 'paulo villar', 'colombia', '13.85', '| | 0.153']]
|
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.