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
|
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
united states house of representatives elections , 1868
|
https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1868
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1434788-5.html.csv
|
comparative
|
james m ashley has a first elected year which is earlier than that of samuel shellabarger .
|
{'row_1': '3', 'row_2': '1', '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', 'james m ashley'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose incumbent record fuzzily matches to james m ashley .', 'tostr': 'filter_eq { all_rows ; incumbent ; james m ashley }'}, 'first elected'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; incumbent ; james m ashley } ; first elected }', 'tointer': 'select the rows whose incumbent record fuzzily matches to james m ashley . take the first elected record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'incumbent', 'samuel shellabarger'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose incumbent record fuzzily matches to samuel shellabarger .', 'tostr': 'filter_eq { all_rows ; incumbent ; samuel shellabarger }'}, 'first elected'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; incumbent ; samuel shellabarger } ; first elected }', 'tointer': 'select the rows whose incumbent record fuzzily matches to samuel shellabarger . take the first elected record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; incumbent ; james m ashley } ; first elected } ; hop { filter_eq { all_rows ; incumbent ; samuel shellabarger } ; first elected } } = true', 'tointer': 'select the rows whose incumbent record fuzzily matches to james m ashley . take the first elected record of this row . select the rows whose incumbent record fuzzily matches to samuel shellabarger . take the first elected record of this row . the first record is less than the second record .'}
|
less { hop { filter_eq { all_rows ; incumbent ; james m ashley } ; first elected } ; hop { filter_eq { all_rows ; incumbent ; samuel shellabarger } ; first elected } } = true
|
select the rows whose incumbent record fuzzily matches to james m ashley . take the first elected record of this row . select the rows whose incumbent record fuzzily matches to samuel shellabarger . 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, 'james m ashley_8': 8, 'first elected_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'incumbent_11': 11, 'samuel shellabarger_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', 'james m ashley_8': 'james m ashley', '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', 'samuel shellabarger_12': 'samuel shellabarger', '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], 'james m ashley_8': [0], 'first elected_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'incumbent_11': [1], 'samuel shellabarger_12': [1], 'first elected_13': [3]}
|
['district', 'incumbent', 'party', 'first elected', 'result', 'candidates']
|
[['ohio 7', 'samuel shellabarger', 'republican', '1864', 'retired republican hold', 'james j winans ( r ) 50.2 % john h thomas ( d ) 49.8 %'], ['ohio 8', 'john beatty', 'republican', '1868 ( s )', 're - elected', 'john beatty ( r ) 52.0 % john h benson ( d ) 48.0 %'], ['ohio 10', 'james m ashley', 'republican', '1862', 'lost re - election democratic gain', 'truman h hoag ( d ) 51.5 % james m ashley ( d ) 48.5 %'], ['ohio 11', 'john thomas wilson', 'republican', '1866', 're - elected', 'john thomas wilson ( r ) 54.2 % john sands ( d ) 45.8 %'], ['ohio 16', 'john bingham', 'republican', '1864', 're - elected', 'john bingham ( r ) 50.8 % josiah m estep ( d ) 49.2 %']]
|
united states house of representatives elections , 1794
|
https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1794
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2668420-17.html.csv
|
comparative
|
john page was first elected to office before francis walker was .
|
{'row_1': '8', 'row_2': '9', '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', 'john page'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose incumbent record fuzzily matches to john page .', 'tostr': 'filter_eq { all_rows ; incumbent ; john page }'}, 'first elected'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; incumbent ; john page } ; first elected }', 'tointer': 'select the rows whose incumbent record fuzzily matches to john page . take the first elected record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'incumbent', 'francis walker'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose incumbent record fuzzily matches to francis walker .', 'tostr': 'filter_eq { all_rows ; incumbent ; francis walker }'}, 'first elected'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; incumbent ; francis walker } ; first elected }', 'tointer': 'select the rows whose incumbent record fuzzily matches to francis walker . take the first elected record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; incumbent ; john page } ; first elected } ; hop { filter_eq { all_rows ; incumbent ; francis walker } ; first elected } } = true', 'tointer': 'select the rows whose incumbent record fuzzily matches to john page . take the first elected record of this row . select the rows whose incumbent record fuzzily matches to francis walker . take the first elected record of this row . the first record is less than the second record .'}
|
less { hop { filter_eq { all_rows ; incumbent ; john page } ; first elected } ; hop { filter_eq { all_rows ; incumbent ; francis walker } ; first elected } } = true
|
select the rows whose incumbent record fuzzily matches to john page . take the first elected record of this row . select the rows whose incumbent record fuzzily matches to francis walker . 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, 'john page_8': 8, 'first elected_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'incumbent_11': 11, 'francis walker_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', 'john page_8': 'john page', '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', 'francis walker_12': 'francis walker', '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], 'john page_8': [0], 'first elected_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'incumbent_11': [1], 'francis walker_12': [1], 'first elected_13': [3]}
|
['district', 'incumbent', 'party', 'first elected', 'result', 'candidates']
|
[['virginia 1', 'robert rutherford', 'anti - administration', '1793', 're - elected', 'robert rutherford ( dr ) daniel morgan ( f )'], ['virginia 2', 'andrew moore', 'anti - administration', '1789', 're - elected', 'andrew moore ( dr )'], ['virginia 4', 'francis preston', 'anti - administration', '1793', 're - elected', 'francis preston ( dr ) arthur campbell'], ['virginia 5', 'george hancock', 'pro - administration', '1793', 're - elected', 'george hancock ( f )'], ['virginia 9', 'william b giles', 'anti - administration', '1790', 're - elected', 'william b giles ( dr )'], ['virginia 10', 'carter b harrison', 'anti - administration', '1793', 're - elected', 'carter b harrison ( dr )'], ['virginia 11', 'josiah parker', 'pro - administration', '1789', 're - elected', 'josiah parker ( f ) robert cowper'], ['virginia 12', 'john page', 'anti - administration', '1789', 're - elected', 'john page ( dr )'], ['virginia 14', 'francis walker', 'anti - administration', '1793', 'retired democratic - republican hold', 'samuel j cabell ( dr )'], ['virginia 15', 'james madison , jr', 'anti - administration', '1789', 're - elected', 'james madison , jr ( dr )'], ['virginia 16', 'anthony new', 'anti - administration', '1793', 're - elected', 'anthony new ( dr )'], ['virginia 17', 'richard bland lee', 'pro - administration', '1789', 'lost re - election democratic - republican gain', 'richard brent ( dr ) richard bland lee ( p )'], ['virginia 18', 'john nicholas', 'anti - administration', '1793', 're - elected', 'john nicholas ( dr )']]
|
list of swat kats : the radical squadron episodes
|
https://en.wikipedia.org/wiki/List_of_SWAT_Kats%3A_The_Radical_Squadron_episodes
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-17810099-3.html.csv
|
ordinal
|
of the swat kats : the radical squadron episodes , the episode with the 2nd earliest air date is the episode titled " a bright and shiny future " .
|
{'row': '2', 'col': '6', 'order': '2', 'col_other': '3', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None}
|
{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'originalairdate', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; originalairdate ; 2 }'}, 'title'], 'result': 'a bright and shiny future', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; originalairdate ; 2 } ; title }'}, 'a bright and shiny future'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; originalairdate ; 2 } ; title } ; a bright and shiny future } = true', 'tointer': 'select the row whose originalairdate record of all rows is 2nd minimum . the title record of this row is a bright and shiny future .'}
|
eq { hop { nth_argmin { all_rows ; originalairdate ; 2 } ; title } ; a bright and shiny future } = true
|
select the row whose originalairdate record of all rows is 2nd minimum . the title record of this row is a bright and shiny future .
|
3
|
3
|
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'originalairdate_5': 5, '2_6': 6, 'title_7': 7, 'a bright and shiny future_8': 8}
|
{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmin_0': 'nth_argmin', 'all_rows_4': 'all_rows', 'originalairdate_5': 'originalairdate', '2_6': '2', 'title_7': 'title', 'a bright and shiny future_8': 'a bright and shiny future'}
|
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'originalairdate_5': [0], '2_6': [0], 'title_7': [1], 'a bright and shiny future_8': [2]}
|
['episode', 'season', 'title', 'writer ( s )', 'director', 'originalairdate']
|
[['14', '2', 'mutation city', 'glenn leopold', 'robert alvarez', 'september 10 , 1994'], ['15', '2', 'a bright and shiny future', 'glenn leopold', 'robert alvarez', 'september 17 , 1994'], ['16', '2', 'when mutilor strikes', 'lance falk', 'robert alvarez', 'september 24 , 1994'], ['17', '2', "razor 's edge", 'mark saraceni', 'robert alvarez', 'october 29 , 1994'], ['18a', '2', 'cry turmoil', 'lance falk', 'robert alvarez', 'november 5 , 1994'], ['18b', '2', 'swat kats unplugged', 'glenn leopold', 'robert alvarez', 'november 5 , 1994'], ['19', '2', 'the deadly pyramid', 'glenn leopold', 'robert alvarez', 'november 12 , 1994'], ['20', '2', 'caverns of horror', 'glenn leopold', 'robert alvarez', 'november 19 , 1994'], ['21a', '2', 'volcanus erupts !', 'glenn leopold', 'robert alvarez', 'november 26 , 1994'], ['21b', '2', 'the origin of dr viper', 'glenn leopold', 'robert alvarez', 'november 26 , 1994'], ['22', '2', 'the dark side of the swat kats', 'jim katz', 'robert alvarez', 'december 10 , 1994']]
|
1979 vfl season
|
https://en.wikipedia.org/wiki/1979_VFL_season
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10823719-21.html.csv
|
ordinal
|
in the 1979 vfl season , the 2nd largest crowd was when the home team was essendon .
|
{'row': '6', 'col': '6', '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', 'crowd', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; crowd ; 2 }'}, 'home team'], 'result': 'essendon', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; crowd ; 2 } ; home team }'}, 'essendon'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; crowd ; 2 } ; home team } ; essendon } = true', 'tointer': 'select the row whose crowd record of all rows is 2nd maximum . the home team record of this row is essendon .'}
|
eq { hop { nth_argmax { all_rows ; crowd ; 2 } ; home team } ; essendon } = true
|
select the row whose crowd record of all rows is 2nd maximum . the home team record of this row is essendon .
|
3
|
3
|
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'crowd_5': 5, '2_6': 6, 'home team_7': 7, 'essendon_8': 8}
|
{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'crowd_5': 'crowd', '2_6': '2', 'home team_7': 'home team', 'essendon_8': 'essendon'}
|
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'crowd_5': [0], '2_6': [0], 'home team_7': [1], 'essendon_8': [2]}
|
['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date']
|
[['melbourne', '24.17 ( 161 )', 'st kilda', '12.24 ( 96 )', 'mcg', '18435', '25 august 1979'], ['hawthorn', '7.18 ( 60 )', 'north melbourne', '24.21 ( 165 )', 'princes park', '18501', '25 august 1979'], ['geelong', '17.13 ( 115 )', 'richmond', '12.17 ( 89 )', 'kardinia park', '18039', '25 august 1979'], ['fitzroy', '22.19 ( 151 )', 'footscray', '14.16 ( 100 )', 'junction oval', '12076', '25 august 1979'], ['collingwood', '18.12 ( 120 )', 'carlton', '14.17 ( 101 )', 'victoria park', '36509', '25 august 1979'], ['essendon', '13.17 ( 95 )', 'south melbourne', '10.16 ( 76 )', 'vfl park', '32127', '25 august 1979']]
|
orlando magic all - time roster
|
https://en.wikipedia.org/wiki/Orlando_Magic_all-time_roster
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-15621965-10.html.csv
|
unique
|
among the players on the roster , steve kerr is the only person who plays the guard position .
|
{'scope': 'all', 'row': '5', 'col': '4', 'col_other': '1', 'criterion': 'equal', 'value': 'guard', 'subset': None}
|
{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'position', 'guard'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose position record fuzzily matches to guard .', 'tostr': 'filter_eq { all_rows ; position ; guard }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; position ; guard } }', 'tointer': 'select the rows whose position record fuzzily matches to guard . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'position', 'guard'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose position record fuzzily matches to guard .', 'tostr': 'filter_eq { all_rows ; position ; guard }'}, 'player'], 'result': 'steve kerr', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; position ; guard } ; player }'}, 'steve kerr'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; position ; guard } ; player } ; steve kerr }', 'tointer': 'the player record of this unqiue row is steve kerr .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; position ; guard } } ; eq { hop { filter_eq { all_rows ; position ; guard } ; player } ; steve kerr } } = true', 'tointer': 'select the rows whose position record fuzzily matches to guard . there is only one such row in the table . the player record of this unqiue row is steve kerr .'}
|
and { only { filter_eq { all_rows ; position ; guard } } ; eq { hop { filter_eq { all_rows ; position ; guard } ; player } ; steve kerr } } = true
|
select the rows whose position record fuzzily matches to guard . there is only one such row in the table . the player record of this unqiue row is steve kerr .
|
6
|
5
|
{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'position_7': 7, 'guard_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'player_9': 9, 'steve kerr_10': 10}
|
{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'position_7': 'position', 'guard_8': 'guard', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'player_9': 'player', 'steve kerr_10': 'steve kerr'}
|
{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'position_7': [0], 'guard_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'player_9': [2], 'steve kerr_10': [3]}
|
['player', 'no', 'nationality', 'position', 'years in orlando', 'school / club team']
|
[['mario kasun', '41', 'croatia', 'center', '2004 - 2006', 'gonzaga'], ['shawn kemp', '40', 'united states', 'forward', '2002 - 2003', 'concord hs'], ['tim kempton', '9', 'united states', 'forward - center', '2002 - 2004', 'notre dame'], ['jonathan kerner', '52', 'united states', 'center', '1998 - 1999', 'east carolina'], ['steve kerr', '2', 'united states', 'guard', '1992 - 1993', 'arizona'], ['greg kite', '34', 'united states', 'center', '1990 - 1994', 'byu'], ['jon koncak', '45', 'united states', 'center', '1995 - 1996', 'southern methodist']]
|
1985 - 86 philadelphia flyers season
|
https://en.wikipedia.org/wiki/1985%E2%80%9386_Philadelphia_Flyers_season
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14320222-6.html.csv
|
majority
|
in the majority of games played , the winner had a score of less than 5 points .
|
{'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'less_than', 'value': '5', 'subset': None}
|
{'func': 'most_less', 'args': ['all_rows', 'score', '5'], 'result': True, 'ind': 0, 'tointer': 'for the score records of all rows , most of them are less than 5 .', 'tostr': 'most_less { all_rows ; score ; 5 } = true'}
|
most_less { all_rows ; score ; 5 } = true
|
for the score records of all rows , most of them are less than 5 .
|
1
|
1
|
{'most_less_0': 0, 'result_1': 1, 'all_rows_2': 2, 'score_3': 3, '5_4': 4}
|
{'most_less_0': 'most_less', 'result_1': 'true', 'all_rows_2': 'all_rows', 'score_3': 'score', '5_4': '5'}
|
{'most_less_0': [1], 'result_1': [], 'all_rows_2': [0], 'score_3': [0], '5_4': [0]}
|
['game', 'february', 'opponent', 'score', 'record', 'points']
|
[['52', '1', 'quebec nordiques', '2 - 2 ot', '35 - 15 - 2', '72'], ['53', '6', 'st louis blues', '4 - 3', '36 - 15 - 2', '74'], ['54', '8', 'minnesota north stars', '3 - 3 ot', '36 - 15 - 3', '75'], ['55', '9', 'chicago black hawks', '2 - 2 ot', '36 - 15 - 4', '76'], ['56', '12', 'buffalo sabres', '4 - 0', '37 - 15 - 4', '78'], ['57', '13', 'new york islanders', '6 - 3', '38 - 15 - 4', '80'], ['58', '15', 'montreal canadiens', '3 - 5', '38 - 16 - 4', '80'], ['59', '17', 'winnipeg jets', '8 - 4', '39 - 16 - 4', '82'], ['60', '20', 'los angeles kings', '5 - 3', '40 - 16 - 4', '84'], ['61', '22', 'washington capitals', '3 - 1', '41 - 16 - 4', '86'], ['62', '27', 'calgary flames', '4 - 7', '41 - 17 - 4', '86'], ['63', '28', 'vancouver canucks', '1 - 3', '41 - 18 - 4', '86']]
|
baltimore city delegation
|
https://en.wikipedia.org/wiki/Baltimore_City_Delegation
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11873520-1.html.csv
|
majority
|
all of the baltimore city delegates are affiliated with the democratic party .
|
{'scope': 'all', 'col': '4', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'democratic', 'subset': None}
|
{'func': 'all_str_eq', 'args': ['all_rows', 'party', 'democratic'], 'result': True, 'ind': 0, 'tointer': 'for the party records of all rows , all of them fuzzily match to democratic .', 'tostr': 'all_eq { all_rows ; party ; democratic } = true'}
|
all_eq { all_rows ; party ; democratic } = true
|
for the party records of all rows , all of them fuzzily match to democratic .
|
1
|
1
|
{'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'party_3': 3, 'democratic_4': 4}
|
{'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'party_3': 'party', 'democratic_4': 'democratic'}
|
{'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'party_3': [0], 'democratic_4': [0]}
|
['district', 'place of birth', 'delegate', 'party', 'took office', 'committee']
|
[['40', 'baltimore city', 'frank conaway', 'democratic', '2006', 'judiciary'], ['40', 'alexandria city , alabama', 'barbara robinson', 'democratic', '2006', 'appropriations'], ['40', 'freeport , ny', 'shawn z tarrant', 'democratic', '2006', 'health and government operations'], ['41', 'baltimore city', 'jill p carter', 'democratic', '2002', 'judiciary'], ['41', 'baltimore city', 'nathaniel t oaks', 'democratic', '1982', 'health and government operations'], ['41', 'baltimore city', 'sandy rosenberg', 'democratic', '1982', 'ways and means ( vice - chair )'], ['43', 'chicago , illinois', 'curt anderson , chair', 'democratic', '1982', 'judiciary'], ['43', 'philadelphia , pennsylvania', 'mary l washington', 'democratic', '2011', 'appropriations'], ['43', 'quinter , kansas', 'maggie mcintosh', 'democratic', '1992', 'environmental matters ( chair )'], ['44', 'shelby , north carolina', 'keith e haynes', 'democratic', '2002', 'appropriations'], ['44', 'baltimore city', 'keiffer mitchell', 'democratic', '2011', 'judiciary'], ['44', 'baltimore city', 'melvin l stukes', 'democratic', '2006', 'ways and means'], ['45', 'northampton co , north carolina', 'talmadge branch', 'democratic', '1994', 'appropriations'], ['45', 'baltimore city', 'cheryl glenn', 'democratic', '2006', 'environmental matters'], ['45', 'baltimore city', 'nina r harper', 'democratic', '2013', 'ways and means'], ['46', 'baltimore city', 'peter a hammen', 'democratic', '1994', 'health and government operations ( chair )'], ['46', 'baltimore city', 'luke clippinger', 'democratic', '2011', 'judiciary'], ['46', 'baltimore city', 'brian k mchale', 'democratic', '1990', 'economic matters']]
|
list of government schools in new south wales : q - z
|
https://en.wikipedia.org/wiki/List_of_Government_schools_in_New_South_Wales%3A_Q%E2%80%93Z
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18155481-6.html.csv
|
majority
|
most of the schools in new south wales were founded before 1980 .
|
{'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'less_than', 'value': '1980', 'subset': None}
|
{'func': 'most_less', 'args': ['all_rows', 'founded', '1980'], 'result': True, 'ind': 0, 'tointer': 'for the founded records of all rows , most of them are less than 1980 .', 'tostr': 'most_less { all_rows ; founded ; 1980 } = true'}
|
most_less { all_rows ; founded ; 1980 } = true
|
for the founded records of all rows , most of them are less than 1980 .
|
1
|
1
|
{'most_less_0': 0, 'result_1': 1, 'all_rows_2': 2, 'founded_3': 3, '1980_4': 4}
|
{'most_less_0': 'most_less', 'result_1': 'true', 'all_rows_2': 'all_rows', 'founded_3': 'founded', '1980_4': '1980'}
|
{'most_less_0': [1], 'result_1': [], 'all_rows_2': [0], 'founded_3': [0], '1980_4': [0]}
|
['school', 'suburb / town', 'years', 'founded', 'website']
|
[['vacy public school', 'vacy', 'k - 6', '1859', 'website'], ['valentine public school', 'valentine', 'k - 6', '1958', 'website'], ['valley view public school', 'wyoming', 'k - 6', '1980', 'website'], ['vardys road public school', 'seven hills', 'k - 6', '1960', 'website'], ['vaucluse public school', 'vaucluse', 'k - 6', '1858', 'website'], ['verona school', 'fairfield east', 'k - 6', '1882', 'website'], ['villawood east public school', 'villawood', 'k - 6', '1955', 'website'], ['villawood north public school', 'fairfield east', 'k - 6', '1953', 'website'], ['vincentia high school', 'vincentia', '712', '1993', 'website'], ['vincentia public school', 'vincentia', 'k - 6', '1992', 'website'], ['vineyard public school', 'vineyard', 'k - 6', '1872', 'website']]
|
2002 new england patriots season
|
https://en.wikipedia.org/wiki/2002_New_England_Patriots_season
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10716117-1.html.csv
|
aggregation
|
the average overall in round 7 for the 2002 new new england patriots is 245 .
|
{'scope': 'subset', 'col': '2', 'type': 'average', 'result': '245', 'subset': {'col': '1', 'criterion': 'equal', 'value': '7'}}
|
{'func': 'round_eq', 'args': [{'func': 'avg', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'round', '7'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; round ; 7 }', 'tointer': 'select the rows whose round record is equal to 7 .'}, 'overall'], 'result': '245', 'ind': 1, 'tostr': 'avg { filter_eq { all_rows ; round ; 7 } ; overall }'}, '245'], 'result': True, 'ind': 2, 'tostr': 'round_eq { avg { filter_eq { all_rows ; round ; 7 } ; overall } ; 245 } = true', 'tointer': 'select the rows whose round record is equal to 7 . the average of the overall record of these rows is 245 .'}
|
round_eq { avg { filter_eq { all_rows ; round ; 7 } ; overall } ; 245 } = true
|
select the rows whose round record is equal to 7 . the average of the overall record of these rows is 245 .
|
3
|
3
|
{'eq_2': 2, 'result_3': 3, 'avg_1': 1, 'filter_eq_0': 0, 'all_rows_4': 4, 'round_5': 5, '7_6': 6, 'overall_7': 7, '245_8': 8}
|
{'eq_2': 'eq', 'result_3': 'true', 'avg_1': 'avg', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'round_5': 'round', '7_6': '7', 'overall_7': 'overall', '245_8': '245'}
|
{'eq_2': [3], 'result_3': [], 'avg_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'round_5': [0], '7_6': [0], 'overall_7': [1], '245_8': [2]}
|
['round', 'overall', 'player', 'position', 'college']
|
[['1', '21', 'daniel graham', 'tight end', 'colorado'], ['2', '65', 'deion branch', 'wide receiver', 'louisville'], ['4', '117', 'rohan davey', 'quarterback', 'lsu'], ['4', '126', 'jarvis green', 'defensive end', 'lsu'], ['7', '237', 'antwoine womack', 'running back', 'virginia'], ['7', '253', 'david givens', 'wide receiver', 'notre dame']]
|
mike beuttler
|
https://en.wikipedia.org/wiki/Mike_Beuttler
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1226504-1.html.csv
|
aggregation
|
mike beuttler scored a total of zero points throughout his formula one career .
|
{'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']
|
[['1971', 'clarke - mordaunt - guthrie racing', 'march 711', 'cosworth v8', '0'], ['1971', 'stp march', 'march 711', 'cosworth v8', '0'], ['1972', 'clarke - mordaunt - guthrie racing', 'march 721 g', 'cosworth v8', '0'], ['1973', 'clarke - mordaunt - guthrie - durlacher', 'march 721 g', 'cosworth v8', '0'], ['1973', 'clarke - mordaunt - guthrie - durlacher', 'march 721 g / 731', 'cosworth v8', '0']]
|
swimming at the 2000 summer olympics - men 's 200 metre individual medley
|
https://en.wikipedia.org/wiki/Swimming_at_the_2000_Summer_Olympics_%E2%80%93_Men%27s_200_metre_individual_medley
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12446479-5.html.csv
|
count
|
exactly one of the athletes was from the united states .
|
{'scope': 'all', 'criterion': 'equal', 'value': 'united states', 'result': '1', 'col': '4', 'subset': None}
|
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'nationality', 'united states'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose nationality record fuzzily matches to united states .', 'tostr': 'filter_eq { all_rows ; nationality ; united states }'}], 'result': '1', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; nationality ; united states } }', 'tointer': 'select the rows whose nationality record fuzzily matches to united states . the number of such rows is 1 .'}, '1'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; nationality ; united states } } ; 1 } = true', 'tointer': 'select the rows whose nationality record fuzzily matches to united states . the number of such rows is 1 .'}
|
eq { count { filter_eq { all_rows ; nationality ; united states } } ; 1 } = true
|
select the rows whose nationality record fuzzily matches to united states . the number of such rows is 1 .
|
3
|
3
|
{'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'nationality_5': 5, 'united states_6': 6, '1_7': 7}
|
{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'nationality_5': 'nationality', 'united states_6': 'united states', '1_7': '1'}
|
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'nationality_5': [0], 'united states_6': [0], '1_7': [2]}
|
['rank', 'lane', 'name', 'nationality', 'time']
|
[['1', '4', 'massimiliano rosolino', 'italy', '2:01.14'], ['2', '5', 'marcel wouda', 'netherlands', '2:01.40'], ['3', '3', 'jani sievinen', 'finland', '2:01.46'], ['4', '6', 'tom wilkens', 'united states', '2:01.51'], ['5', '2', 'cezar bădiţă', 'romania', '2:02.02'], ['6', '1', 'jordi carrasco', 'spain', '2:02.90'], ['7', '7', 'robert van der zant', 'australia', '2:02.91'], ['8', '8', 'brian johns', 'canada', '2:02.92']]
|
1962 world wrestling championships
|
https://en.wikipedia.org/wiki/1962_World_Wrestling_Championships
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16669292-1.html.csv
|
aggregation
|
in the 1962 world wrestling championships the total number of medals was 48 .
|
{'scope': 'all', 'col': '6', 'type': 'sum', 'result': '48', 'subset': None}
|
{'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'total'], 'result': '48', 'ind': 0, 'tostr': 'sum { all_rows ; total }'}, '48'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; total } ; 48 } = true', 'tointer': 'the sum of the total record of all rows is 48 .'}
|
round_eq { sum { all_rows ; total } ; 48 } = true
|
the sum of the total record of all rows is 48 .
|
2
|
2
|
{'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'total_4': 4, '48_5': 5}
|
{'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'total_4': 'total', '48_5': '48'}
|
{'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'total_4': [0], '48_5': [1]}
|
['rank', 'nation', 'gold', 'silver', 'bronze', 'total']
|
[['1', 'soviet union', '6', '4', '1', '11'], ['2', 'turkey', '3', '1', '5', '9'], ['3', 'japan', '2', '2', '1', '5'], ['4', 'iran', '2', '2', '0', '4'], ['5', 'hungary', '2', '0', '1', '3'], ['6', 'bulgaria', '1', '4', '0', '5'], ['7', 'italy', '0', '1', '1', '2'], ['8', 'denmark', '0', '1', '0', '1'], ['8', 'yugoslavia', '0', '1', '0', '1'], ['10', 'united states', '0', '0', '3', '3'], ['10', 'west germany', '0', '0', '3', '3'], ['12', 'united arab republic', '0', '0', '1', '1'], ['total', 'total', '16', '16', '16', '48']]
|
1975 - 76 phoenix suns season
|
https://en.wikipedia.org/wiki/1975%E2%80%9376_Phoenix_Suns_season
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-30047613-14.html.csv
|
majority
|
the phoenix suns lost most of the games that they played in .
|
{'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': 'l', 'subset': None}
|
{'func': 'most_str_eq', 'args': ['all_rows', 'score', 'l'], 'result': True, 'ind': 0, 'tointer': 'for the score records of all rows , most of them fuzzily match to l .', 'tostr': 'most_eq { all_rows ; score ; l } = true'}
|
most_eq { all_rows ; score ; l } = true
|
for the score records of all rows , most of them fuzzily match to l .
|
1
|
1
|
{'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'score_3': 3, 'l_4': 4}
|
{'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'score_3': 'score', 'l_4': 'l'}
|
{'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'score_3': [0], 'l_4': [0]}
|
['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'location attendance', 'series', 'streak']
|
[['1', 'may 23', 'boston', 'l 87 - 98', 'alvan adams ( 26 )', 'curtis perry ( 10 )', 'boston garden 15320', '0 - 1', 'l 1'], ['2', 'may 27', 'boston', 'l 90 - 105', 'paul westphal ( 28 )', 'alvan adams ( 15 )', 'boston garden 15320', '0 - 2', 'l 2'], ['3', 'may 30', 'boston', 'w 105 - 98', 'alvan adams ( 33 )', 'alvan adams ( 14 )', 'arizona veterans memorial coliseum 12884', '1 - 2', 'w 1'], ['4', 'june 2', 'boston', 'w 109 - 107', 'paul westphal ( 28 )', 'gar heard ( 15 )', 'arizona veterans memorial coliseum 13306', '2 - 2', 'w 2'], ['5', 'june 4', 'boston', 'l 126 - 128 ( 3ot )', 'ricky sobers , paul westphal ( 25 )', 'curtis perry ( 15 )', 'boston garden 15320', '2 - 3', 'l 1']]
|
united states house of representatives elections , 1954
|
https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1954
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1342013-20.html.csv
|
ordinal
|
in terms of when they were first elected , thomas j lane was the second earliest .
|
{'row': '4', 'col': '4', 'order': '2', 'col_other': '2', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None}
|
{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'first elected', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; first elected ; 2 }'}, 'incumbent'], 'result': 'thomas j lane', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; first elected ; 2 } ; incumbent }'}, 'thomas j lane'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; first elected ; 2 } ; incumbent } ; thomas j lane } = true', 'tointer': 'select the row whose first elected record of all rows is 2nd minimum . the incumbent record of this row is thomas j lane .'}
|
eq { hop { nth_argmin { all_rows ; first elected ; 2 } ; incumbent } ; thomas j lane } = true
|
select the row whose first elected record of all rows is 2nd minimum . the incumbent record of this row is thomas j lane .
|
3
|
3
|
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'first elected_5': 5, '2_6': 6, 'incumbent_7': 7, 'thomas j lane_8': 8}
|
{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmin_0': 'nth_argmin', 'all_rows_4': 'all_rows', 'first elected_5': 'first elected', '2_6': '2', 'incumbent_7': 'incumbent', 'thomas j lane_8': 'thomas j lane'}
|
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'first elected_5': [0], '2_6': [0], 'incumbent_7': [1], 'thomas j lane_8': [2]}
|
['district', 'incumbent', 'party', 'first elected', 'result', 'candidates']
|
[['massachusetts 1', 'john w heselton', 'republican', '1944', 're - elected', 'john w heselton ( r ) 55.6 % john j dwyer ( d ) 44.4 %'], ['massachusetts 3', 'philip philbin', 'democratic', '1942', 're - elected', 'philip philbin ( d ) unopposed'], ['massachusetts 5', 'edith nourse rogers', 'republican', '1925', 're - elected', 'edith nourse rogers ( r ) unopposed'], ['massachusetts 7', 'thomas j lane', 'democratic', '1941', 're - elected', 'thomas j lane ( d ) unopposed'], ['massachusetts 11', "tip o'neill", 'democratic', '1952', 're - elected', "tip o'neill ( d ) 78.2 % charles s bolster ( r ) 21.8 %"]]
|
westinghouse broadcasting
|
https://en.wikipedia.org/wiki/Westinghouse_Broadcasting
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1553485-1.html.csv
|
unique
|
kyw - tv was the only westinghouse broadcasting channel that became an nbc affiliate owned by gannett company .
|
{'scope': 'all', 'row': '5', 'col': '5', 'col_other': '2', 'criterion': 'equal', 'value': 'nbc affiliate owned by gannett company', 'subset': None}
|
{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'current affiliation', 'nbc affiliate owned by gannett company'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose current affiliation record fuzzily matches to nbc affiliate owned by gannett company .', 'tostr': 'filter_eq { all_rows ; current affiliation ; nbc affiliate owned by gannett company }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; current affiliation ; nbc affiliate owned by gannett company } }', 'tointer': 'select the rows whose current affiliation record fuzzily matches to nbc affiliate owned by gannett company . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'current affiliation', 'nbc affiliate owned by gannett company'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose current affiliation record fuzzily matches to nbc affiliate owned by gannett company .', 'tostr': 'filter_eq { all_rows ; current affiliation ; nbc affiliate owned by gannett company }'}, 'station'], 'result': 'kyw - tv ( now wkyc - tv )', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; current affiliation ; nbc affiliate owned by gannett company } ; station }'}, 'kyw - tv ( now wkyc - tv )'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; current affiliation ; nbc affiliate owned by gannett company } ; station } ; kyw - tv ( now wkyc - tv ) }', 'tointer': 'the station record of this unqiue row is kyw - tv ( now wkyc - tv ) .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; current affiliation ; nbc affiliate owned by gannett company } } ; eq { hop { filter_eq { all_rows ; current affiliation ; nbc affiliate owned by gannett company } ; station } ; kyw - tv ( now wkyc - tv ) } } = true', 'tointer': 'select the rows whose current affiliation record fuzzily matches to nbc affiliate owned by gannett company . there is only one such row in the table . the station record of this unqiue row is kyw - tv ( now wkyc - tv ) .'}
|
and { only { filter_eq { all_rows ; current affiliation ; nbc affiliate owned by gannett company } } ; eq { hop { filter_eq { all_rows ; current affiliation ; nbc affiliate owned by gannett company } ; station } ; kyw - tv ( now wkyc - tv ) } } = true
|
select the rows whose current affiliation record fuzzily matches to nbc affiliate owned by gannett company . there is only one such row in the table . the station record of this unqiue row is kyw - tv ( now wkyc - tv ) .
|
6
|
5
|
{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'current affiliation_7': 7, 'nbc affiliate owned by gannett company_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'station_9': 9, 'kyw - tv (now wkyc - tv )_10': 10}
|
{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'current affiliation_7': 'current affiliation', 'nbc affiliate owned by gannett company_8': 'nbc affiliate owned by gannett company', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'station_9': 'station', 'kyw - tv (now wkyc - tv )_10': 'kyw - tv ( now wkyc - tv )'}
|
{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'current affiliation_7': [0], 'nbc affiliate owned by gannett company_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'station_9': [2], 'kyw - tv (now wkyc - tv )_10': [3]}
|
['city of license / market', 'station', 'channel tv ( dt )', 'years owned', 'current affiliation']
|
[['san francisco - oakland - san jose', 'kpix', '5 ( 29 )', '1954 - 1995', 'cbs owned - and - operated ( o & o )'], ['baltimore', 'wjz - tv', '13 ( 13 )', '1957 - 1995', 'cbs owned - and - operated ( o & o )'], ['boston', 'wbz - tv', '4 ( 30 )', '1948 - 1995', 'cbs owned - and - operated ( o & o )'], ['charlotte', 'wpcq - tv ( now wcnc - tv )', '36 ( 22 )', '1980 - 1985', 'nbc affiliate owned by belo corporation'], ['cleveland', 'kyw - tv ( now wkyc - tv )', '3 ( 17 )', '1956 - 1965', 'nbc affiliate owned by gannett company'], ['philadelphia', 'wptz / kyw - tv', '3 ( 26 )', '1953 - 1956 1965 - 1995', 'cbs owned - and - operated ( o & o )']]
|
2005 pga championship
|
https://en.wikipedia.org/wiki/2005_PGA_Championship
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12512153-6.html.csv
|
aggregation
|
all players of the 2005 pga championship had an average score of around 206 .
|
{'scope': 'all', 'col': '4', 'type': 'average', 'result': '206', 'subset': None}
|
{'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'score'], 'result': '206', 'ind': 0, 'tostr': 'avg { all_rows ; score }'}, '206'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; score } ; 206 } = true', 'tointer': 'the average of the score record of all rows is 206 .'}
|
round_eq { avg { all_rows ; score } ; 206 } = true
|
the average of the score record of all rows is 206 .
|
2
|
2
|
{'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'score_4': 4, '206_5': 5}
|
{'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'score_4': 'score', '206_5': '206'}
|
{'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'score_4': [0], '206_5': [1]}
|
['place', 'player', 'country', 'score', 'to par']
|
[['t1', 'davis love iii', 'united states', '68 + 68 + 68 = 204', '- 6'], ['t1', 'phil mickelson', 'united states', '67 + 65 + 72 = 204', '- 6'], ['3', 'thomas bjørn', 'denmark', '71 + 71 + 63 = 205', '- 5'], ['t4', 'stuart appleby', 'australia', '67 + 70 + 69 = 206', '- 4'], ['t4', 'steve elkington', 'australia', '68 + 70 + 68 = 206', '- 4'], ['t4', 'pat perez', 'united states', '68 + 71 + 67 = 206', '- 4'], ['t4', 'vijay singh', 'fiji', '70 + 67 + 69 = 206', '- 4'], ['t8', 'jason bohn', 'united states', '71 + 68 + 68 = 207', '- 3'], ['t8', 'ben curtis', 'united states', '67 + 73 + 67 = 207', '- 3'], ['t8', 'retief goosen', 'south africa', '68 + 70 + 69 = 207', '- 3'], ['t8', 'greg owen', 'england', '68 + 69 + 70 = 207', '- 3'], ['t8', 'lee westwood', 'england', '68 + 68 + 71 = 207', '- 3']]
|
5th united states congress
|
https://en.wikipedia.org/wiki/5th_United_States_Congress
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-224839-4.html.csv
|
comparative
|
thomas tillinghast was seated a successor earlier than robert waln in the 5th united states congress .
|
{'row_1': '1', 'row_2': '9', 'col': '5', 'col_other': '4', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None}
|
{'func': 'less', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'successor', 'thomas tillinghast ( f )'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose successor record fuzzily matches to thomas tillinghast ( f ) .', 'tostr': 'filter_eq { all_rows ; successor ; thomas tillinghast ( f ) }'}, 'date successor seated'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; successor ; thomas tillinghast ( f ) } ; date successor seated }', 'tointer': 'select the rows whose successor record fuzzily matches to thomas tillinghast ( f ) . take the date successor seated record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'successor', 'robert waln ( f )'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose successor record fuzzily matches to robert waln ( f ) .', 'tostr': 'filter_eq { all_rows ; successor ; robert waln ( f ) }'}, 'date successor seated'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; successor ; robert waln ( f ) } ; date successor seated }', 'tointer': 'select the rows whose successor record fuzzily matches to robert waln ( f ) . take the date successor seated record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; successor ; thomas tillinghast ( f ) } ; date successor seated } ; hop { filter_eq { all_rows ; successor ; robert waln ( f ) } ; date successor seated } } = true', 'tointer': 'select the rows whose successor record fuzzily matches to thomas tillinghast ( f ) . take the date successor seated record of this row . select the rows whose successor record fuzzily matches to robert waln ( f ) . take the date successor seated record of this row . the first record is less than the second record .'}
|
less { hop { filter_eq { all_rows ; successor ; thomas tillinghast ( f ) } ; date successor seated } ; hop { filter_eq { all_rows ; successor ; robert waln ( f ) } ; date successor seated } } = true
|
select the rows whose successor record fuzzily matches to thomas tillinghast ( f ) . take the date successor seated record of this row . select the rows whose successor record fuzzily matches to robert waln ( f ) . take the date successor seated 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, 'successor_7': 7, 'thomas tillinghast ( f )_8': 8, 'date successor seated_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'successor_11': 11, 'robert waln ( f )_12': 12, 'date successor seated_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', 'successor_7': 'successor', 'thomas tillinghast ( f )_8': 'thomas tillinghast ( f )', 'date successor seated_9': 'date successor seated', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'successor_11': 'successor', 'robert waln ( f )_12': 'robert waln ( f )', 'date successor seated_13': 'date successor seated'}
|
{'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'successor_7': [0], 'thomas tillinghast ( f )_8': [0], 'date successor seated_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'successor_11': [1], 'robert waln ( f )_12': [1], 'date successor seated_13': [3]}
|
['district', 'vacator', 'reason for change', 'successor', 'date successor seated']
|
[['rhode island at - large', 'elisha potter ( f )', 'resigned sometime in 1797', 'thomas tillinghast ( f )', 'seated november 13 , 1797'], ['south carolina 1st', 'william l smith ( f )', 'resigned july 10 , 1797', 'thomas pinckney ( f )', 'seated november 23 , 1797'], ['massachusetts 11th', 'theophilus bradbury ( f )', 'resigned july 24 , 1797', 'bailey bartlett ( f )', 'seated november 27 , 1797'], ['new hampshire at - large', 'jeremiah smith ( f )', 'resigned july 26 , 1797', 'peleg sprague ( f )', 'seated december 15 , 1797'], ['connecticut at - large', 'james davenport ( f )', 'died august 3 , 1797', 'william edmond ( f )', 'seated november 13 , 1797'], ['pennsylvania 5th', 'george ege ( f )', 'resigned sometime in october , 1797', 'joseph hiester ( dr )', 'seated december 1 , 1797'], ['pennsylvania 4th', 'samuel sitgreaves ( f )', 'resigned sometime in 1798', 'robert brown ( dr )', 'seated december 4 , 1798'], ['north carolina 10th', 'nathan bryan ( dr )', 'died june 4 , 1798', 'richard dobbs spaight ( dr )', 'seated december 10 , 1798'], ['pennsylvania 1st', 'john swanwick ( dr )', 'died august 1 , 1798', 'robert waln ( f )', 'seated december 3 , 1798'], ['connecticut at - large', 'joshua coit ( f )', 'died september 5 , 1798', 'jonathan brace ( f )', 'seated december 3 , 1798']]
|
list of singaporean films
|
https://en.wikipedia.org/wiki/List_of_Singaporean_films
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1601229-7.html.csv
|
ordinal
|
the eye 2 was the singaporean film that had the second highest gross in 2004 .
|
{'row': '3', 'col': '5', 'order': '2', 'col_other': '2', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None}
|
{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'singapore gross', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; singapore gross ; 2 }'}, 'title'], 'result': 'the eye 2', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; singapore gross ; 2 } ; title }'}, 'the eye 2'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; singapore gross ; 2 } ; title } ; the eye 2 } = true', 'tointer': 'select the row whose singapore gross record of all rows is 2nd maximum . the title record of this row is the eye 2 .'}
|
eq { hop { nth_argmax { all_rows ; singapore gross ; 2 } ; title } ; the eye 2 } = true
|
select the row whose singapore gross record of all rows is 2nd maximum . the title record of this row is the eye 2 .
|
3
|
3
|
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'singapore gross_5': 5, '2_6': 6, 'title_7': 7, 'the eye 2_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', 'singapore gross_5': 'singapore gross', '2_6': '2', 'title_7': 'title', 'the eye 2_8': 'the eye 2'}
|
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'singapore gross_5': [0], '2_6': [0], 'title_7': [1], 'the eye 2_8': [2]}
|
['date', 'title', 'director', 'production cost', 'singapore gross']
|
[['2004', '2004', '2004', '2004', '2004'], ['february 2004', 'last life in the universe', 'pen - ek ratanaruang', 'us2000000', '65000'], ['march 2004', 'the eye 2', 'danny pang / oxide pang', 'us3000000', '1577000'], ['june 2004', 'the best bet ( 突然发财 )', 'jack neo', '1500000', '2664000'], ['august 2004', 'clouds in my coffee', 'gallen mei', 'us125000', '11000'], ['unreleased', 'zombie dogs', 'toh hai leong', 'na', 'na'], ['unreleased', 'outsiders', 'sam loh', 'na', 'na'], ['unreleased', 'tequila', 'jonathan lim', 'us13000', 'na']]
|
1966 major league baseball draft
|
https://en.wikipedia.org/wiki/1966_Major_League_Baseball_Draft
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15667202-1.html.csv
|
ordinal
|
john curtis was pick number 12 in the 1966 major league baseball draft .
|
{'row': '12', 'col': '1', 'order': '12', 'col_other': '2', 'max_or_min': 'min_to_max', 'value_mentioned': 'yes', 'scope': 'all', 'subset': None}
|
{'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'nth_min', 'args': ['all_rows', 'pick', '12'], 'result': '12', 'ind': 0, 'tostr': 'nth_min { all_rows ; pick ; 12 }', 'tointer': 'the 12th minimum pick record of all rows is 12 .'}, '12'], 'result': True, 'ind': 1, 'tostr': 'eq { nth_min { all_rows ; pick ; 12 } ; 12 }', 'tointer': 'the 12th minimum pick record of all rows is 12 .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'pick', '12'], 'result': None, 'ind': 2, 'tostr': 'nth_argmin { all_rows ; pick ; 12 }'}, 'player'], 'result': 'john curtis', 'ind': 3, 'tostr': 'hop { nth_argmin { all_rows ; pick ; 12 } ; player }'}, 'john curtis'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { nth_argmin { all_rows ; pick ; 12 } ; player } ; john curtis }', 'tointer': 'the player record of the row with 12th minimum pick record is john curtis .'}], 'result': True, 'ind': 5, 'tostr': 'and { eq { nth_min { all_rows ; pick ; 12 } ; 12 } ; eq { hop { nth_argmin { all_rows ; pick ; 12 } ; player } ; john curtis } } = true', 'tointer': 'the 12th minimum pick record of all rows is 12 . the player record of the row with 12th minimum pick record is john curtis .'}
|
and { eq { nth_min { all_rows ; pick ; 12 } ; 12 } ; eq { hop { nth_argmin { all_rows ; pick ; 12 } ; player } ; john curtis } } = true
|
the 12th minimum pick record of all rows is 12 . the player record of the row with 12th minimum pick record is john curtis .
|
6
|
6
|
{'and_5': 5, 'result_6': 6, 'eq_1': 1, 'nth_min_0': 0, 'all_rows_7': 7, 'pick_8': 8, '12_9': 9, '12_10': 10, 'str_eq_4': 4, 'str_hop_3': 3, 'nth_argmin_2': 2, 'all_rows_11': 11, 'pick_12': 12, '12_13': 13, 'player_14': 14, 'john curtis_15': 15}
|
{'and_5': 'and', 'result_6': 'true', 'eq_1': 'eq', 'nth_min_0': 'nth_min', 'all_rows_7': 'all_rows', 'pick_8': 'pick', '12_9': '12', '12_10': '12', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'nth_argmin_2': 'nth_argmin', 'all_rows_11': 'all_rows', 'pick_12': 'pick', '12_13': '12', 'player_14': 'player', 'john curtis_15': 'john curtis'}
|
{'and_5': [6], 'result_6': [], 'eq_1': [5], 'nth_min_0': [1], 'all_rows_7': [0], 'pick_8': [0], '12_9': [0], '12_10': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'nth_argmin_2': [3], 'all_rows_11': [2], 'pick_12': [2], '12_13': [2], 'player_14': [3], 'john curtis_15': [4]}
|
['pick', 'player', 'team', 'position', 'hometown / school']
|
[['1', 'steve chilcott', 'new york mets', 'c', 'lancaster , ca'], ['2', 'reggie jackson', 'kansas city athletics', 'of', 'arizona state'], ['3', 'wayne twitchell', 'houston astros', 'rhp', 'portland , or'], ['4', 'ken brett', 'boston red sox', 'lhp', 'el segundo , ca'], ['5', 'dean burk', 'chicago cubs', 'rhp', 'highland , il'], ['6', 'tom grieve', 'washington senators', 'of', 'pittsfield , ma'], ['7', 'leron lee', 'st louis cardinals', 'of', 'sacramento , ca'], ['8', 'jim deneff', 'california angels', 'ss', 'indiana university'], ['9', 'mike biko', 'philadelphia phillies', 'rhp', 'dallas , tx'], ['10', 'jim lyttle', 'new york yankees', 'of', 'florida state'], ['11', 'al santorini', 'milwaukee braves', 'rhp', 'union , nj'], ['12', 'john curtis', 'cleveland indians', 'lhp', 'smithtown , ny'], ['13', 'gary nolan', 'cincinnati reds', 'rhp', 'oroville , ca'], ['14', 'rick konik', 'detroit tigers', '1b', 'detroit , mi'], ['15', 'richie hebner', 'pittsburgh pirates', 'ss', 'norwood , ma'], ['16', 'ted parks', 'baltimore orioles', 'ss', 'university of california'], ['17', 'bob reynolds', 'san francisco giants', 'rhp', 'seattle , wa'], ['18', 'carlos may', 'chicago white sox', 'of', 'birmingham , al'], ['19', 'larry hutton', 'los angeles dodgers', 'rhp', 'greenfield , in'], ['20', 'bob jones', 'minnesota twins', '3b', 'dawson , ga']]
|
united states house of representatives elections , 1964
|
https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1964
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1341865-20.html.csv
|
comparative
|
otto passman has a first elected year which is earlier than that of t ashton thompson .
|
{'row_1': '4', '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', 'otto passman'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose incumbent record fuzzily matches to otto passman .', 'tostr': 'filter_eq { all_rows ; incumbent ; otto passman }'}, 'first elected'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; incumbent ; otto passman } ; first elected }', 'tointer': 'select the rows whose incumbent record fuzzily matches to otto passman . take the first elected record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'incumbent', 't ashton thompson'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose incumbent record fuzzily matches to t ashton thompson .', 'tostr': 'filter_eq { all_rows ; incumbent ; t ashton thompson }'}, 'first elected'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; incumbent ; t ashton thompson } ; first elected }', 'tointer': 'select the rows whose incumbent record fuzzily matches to t ashton thompson . take the first elected record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; incumbent ; otto passman } ; first elected } ; hop { filter_eq { all_rows ; incumbent ; t ashton thompson } ; first elected } } = true', 'tointer': 'select the rows whose incumbent record fuzzily matches to otto passman . take the first elected record of this row . select the rows whose incumbent record fuzzily matches to t ashton thompson . take the first elected record of this row . the first record is less than the second record .'}
|
less { hop { filter_eq { all_rows ; incumbent ; otto passman } ; first elected } ; hop { filter_eq { all_rows ; incumbent ; t ashton thompson } ; first elected } } = true
|
select the rows whose incumbent record fuzzily matches to otto passman . take the first elected record of this row . select the rows whose incumbent record fuzzily matches to t ashton thompson . 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, 'otto passman_8': 8, 'first elected_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'incumbent_11': 11, 't ashton thompson_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', 'otto passman_8': 'otto passman', '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', 't ashton thompson_12': 't ashton thompson', '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], 'otto passman_8': [0], 'first elected_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'incumbent_11': [1], 't ashton thompson_12': [1], 'first elected_13': [3]}
|
['district', 'incumbent', 'party', 'first elected', 'result', 'candidates']
|
[['louisiana 1', 'f edward hebert', 'democratic', '1940', 're - elected', 'f edward hebert ( d ) unopposed'], ['louisiana 2', 'hale boggs', 'democratic', '1946', 're - elected', 'hale boggs ( d ) 55.0 % david c treen ( r ) 45.0 %'], ['louisiana 4', 'joe waggonner', 'democratic', '1961', 're - elected', 'joe waggonner ( d ) unopposed'], ['louisiana 5', 'otto passman', 'democratic', '1946', 're - elected', 'otto passman ( d ) unopposed'], ['louisiana 7', 't ashton thompson', 'democratic', '1952', 're - elected', 't ashton thompson ( d ) unopposed']]
|
2008 washington redskins season
|
https://en.wikipedia.org/wiki/2008_Washington_Redskins_season
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10966926-8.html.csv
|
comparative
|
antwaan randle el recorded more yards than ladell betts for the 2008 washington redskins .
|
{'row_1': '3', 'row_2': '5', 'col': '3', 'col_other': '1', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None}
|
{'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', 'antwaan randle el'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose player record fuzzily matches to antwaan randle el .', 'tostr': 'filter_eq { all_rows ; player ; antwaan randle el }'}, 'yards'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; player ; antwaan randle el } ; yards }', 'tointer': 'select the rows whose player record fuzzily matches to antwaan randle el . take the yards record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', 'ladell betts'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose player record fuzzily matches to ladell betts .', 'tostr': 'filter_eq { all_rows ; player ; ladell betts }'}, 'yards'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; player ; ladell betts } ; yards }', 'tointer': 'select the rows whose player record fuzzily matches to ladell betts . take the yards record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; player ; antwaan randle el } ; yards } ; hop { filter_eq { all_rows ; player ; ladell betts } ; yards } } = true', 'tointer': 'select the rows whose player record fuzzily matches to antwaan randle el . take the yards record of this row . select the rows whose player record fuzzily matches to ladell betts . take the yards record of this row . the first record is greater than the second record .'}
|
greater { hop { filter_eq { all_rows ; player ; antwaan randle el } ; yards } ; hop { filter_eq { all_rows ; player ; ladell betts } ; yards } } = true
|
select the rows whose player record fuzzily matches to antwaan randle el . take the yards record of this row . select the rows whose player record fuzzily matches to ladell betts . take the yards 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, 'player_7': 7, 'antwaan randle el_8': 8, 'yards_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'player_11': 11, 'ladell betts_12': 12, 'yards_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', 'player_7': 'player', 'antwaan randle el_8': 'antwaan randle el', 'yards_9': 'yards', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'player_11': 'player', 'ladell betts_12': 'ladell betts', 'yards_13': 'yards'}
|
{'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'player_7': [0], 'antwaan randle el_8': [0], 'yards_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'player_11': [1], 'ladell betts_12': [1], 'yards_13': [3]}
|
['player', 'rec', 'yards', 'avg', 'long']
|
[['santana moss', '79', '1044', '13.2', '67'], ['chris cooley', '83', '849', '10.2', '28'], ['antwaan randle el', '53', '593', '11.2', '31'], ['clinton portis', '28', '218', '7.8', '29'], ['ladell betts', '22', '200', '9.1', '27'], ['devin thomas', '15', '120', '8.0', '18'], ['mike sellers', '12', '98', '8.2', '20'], ['james thrash', '9', '81', '9.0', '29'], ['todd yoder', '8', '50', '6.3', '14'], ['fred davis', '3', '27', '9.0', '15'], ['malcolm kelly', '3', '18', '6.0', '7'], ['shaun alexander', '1', '9', '9.0', '9'], ['rock cartwright', '1', '- 7', '- 7.0', '- 7'], ['pete kendall', '1', '- 9', '- 9.0', '- 9']]
|
2008 - 09 oklahoma city thunder season
|
https://en.wikipedia.org/wiki/2008%E2%80%9309_Oklahoma_City_Thunder_season
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17355628-5.html.csv
|
majority
|
kevin durant had at least a share of the high points in most of the games .
|
{'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'kevin durant', 'subset': None}
|
{'func': 'most_str_eq', 'args': ['all_rows', 'high points', 'kevin durant'], 'result': True, 'ind': 0, 'tointer': 'for the high points records of all rows , most of them fuzzily match to kevin durant .', 'tostr': 'most_eq { all_rows ; high points ; kevin durant } = true'}
|
most_eq { all_rows ; high points ; kevin durant } = true
|
for the high points records of all rows , most of them fuzzily match to kevin durant .
|
1
|
1
|
{'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'high points_3': 3, 'kevin durant_4': 4}
|
{'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'high points_3': 'high points', 'kevin durant_4': 'kevin durant'}
|
{'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'high points_3': [0], 'kevin durant_4': [0]}
|
['game', 'date', 'team', 'score', 'high points', 'high assists', 'location attendance', 'record']
|
[['2', 'november 1', 'houston', 'l 77 - 89 ( ot )', 'kevin durant ( 26 )', 'earl watson ( 8 )', 'toyota center 16996', '0 - 2'], ['3', 'november 2', 'minnesota', 'w 88 - 85 ( ot )', 'kevin durant ( 18 )', 'earl watson ( 4 )', 'ford center 18163', '1 - 2'], ['4', 'november 5', 'boston', 'l 83 - 96 ( ot )', 'kevin durant ( 17 )', 'earl watson ( 5 )', 'ford center 19136', '1 - 3'], ['5', 'november 7', 'utah', 'l 97 - 104 ( ot )', 'kevin durant ( 24 )', 'kevin durant , earl watson ( 3 )', 'energysolutions arena 19911', '1 - 4'], ['6', 'november 9', 'atlanta', 'l 85 - 89 ( ot )', 'kevin durant ( 20 )', 'earl watson ( 6 )', 'ford center 18231', '1 - 5'], ['7', 'november 10', 'indiana', 'l 99 - 107 ( ot )', 'kevin durant ( 37 )', 'earl watson ( 9 )', 'conseco fieldhouse 10165', '1 - 6'], ['8', 'november 12', 'orlando', 'l 92 - 109 ( ot )', 'jeff green ( 25 )', 'earl watson ( 8 )', 'ford center 18185', '1 - 7'], ['9', 'november 14', 'new york', 'l 106 - 116 ( ot )', 'kevin durant ( 23 )', 'earl watson ( 8 )', 'madison square garden 18008', '1 - 8'], ['10', 'november 15', 'philadelphia', 'l 85 - 110 ( ot )', 'jeff green ( 21 )', 'jeff green , russell westbrook ( 4 )', 'wachovia center 13385', '1 - 9'], ['11', 'november 17', 'houston', 'l 89 - 100 ( ot )', 'kevin durant ( 29 )', 'kevin durant , earl watson ( 4 )', 'ford center 18145', '1 - 10'], ['12', 'november 19', 'la clippers', 'l 88 - 108 ( ot )', 'kevin durant ( 18 )', 'earl watson ( 5 )', 'ford center 18312', '1 - 11'], ['13', 'november 21', 'new orleans', 'l 80 - 105 ( ot )', 'kevin durant ( 17 )', 'earl watson ( 4 )', 'ford center 19136', '1 - 12'], ['14', 'november 22', 'new orleans', 'l 97 - 109 ( ot )', 'kevin durant ( 30 )', 'russell westbrook ( 11 )', 'new orleans arena 16023', '1 - 13'], ['15', 'november 25', 'phoenix', 'l 98 - 99 ( ot )', 'kevin durant ( 29 )', 'earl watson ( 13 )', 'ford center 19136', '1 - 14'], ['16', 'november 26', 'cleveland', 'l 82 - 117 ( ot )', 'chris wilcox ( 14 )', 'russell westbrook , kyle weaver ( 5 )', 'quicken loans arena 19753', '1 - 15'], ['17', 'november 28', 'minnesota', 'l 103 - 105 ( ot )', 'kevin durant , jeff green ( 22 )', 'russell westbrook ( 8 )', 'ford center 18229', '1 - 16'], ['18', 'november 29', 'memphis', 'w 111 - 103 ( ot )', 'kevin durant ( 30 )', 'earl watson ( 7 )', 'fedexforum 11977', '2 - 16']]
|
wisconsin intercollegiate athletic conference
|
https://en.wikipedia.org/wiki/Wisconsin_Intercollegiate_Athletic_Conference
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-262495-1.html.csv
|
ordinal
|
the second largest school in the wisconsin intercollegiate conference is the university of wisconsin at oshkosh .
|
{'row': '3', 'col': '6', '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', 'undergraduate enrollment', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; undergraduate enrollment ; 2 }'}, 'institution'], 'result': 'university of wisconsin - oshkosh', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; undergraduate enrollment ; 2 } ; institution }'}, 'university of wisconsin - oshkosh'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; undergraduate enrollment ; 2 } ; institution } ; university of wisconsin - oshkosh } = true', 'tointer': 'select the row whose undergraduate enrollment record of all rows is 2nd maximum . the institution record of this row is university of wisconsin - oshkosh .'}
|
eq { hop { nth_argmax { all_rows ; undergraduate enrollment ; 2 } ; institution } ; university of wisconsin - oshkosh } = true
|
select the row whose undergraduate enrollment record of all rows is 2nd maximum . the institution record of this row is university of wisconsin - oshkosh .
|
3
|
3
|
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'undergraduate enrollment_5': 5, '2_6': 6, 'institution_7': 7, 'university of wisconsin - oshkosh_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', 'undergraduate enrollment_5': 'undergraduate enrollment', '2_6': '2', 'institution_7': 'institution', 'university of wisconsin - oshkosh_8': 'university of wisconsin - oshkosh'}
|
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'undergraduate enrollment_5': [0], '2_6': [0], 'institution_7': [1], 'university of wisconsin - oshkosh_8': [2]}
|
['institution', 'nickname', 'location ( population )', 'founded', 'type', 'undergraduate enrollment', 'joined']
|
[['university of wisconsin - eau claire', 'blugolds', 'eau claire , wisconsin ( 65883 )', '1916', 'public', '9799', '1917 - 18'], ['university of wisconsin - la crosse', 'eagles', 'la crosse , wisconsin ( 52485 )', '1909', 'public', '8324', '1913 - 14'], ['university of wisconsin - oshkosh', 'titans', 'oshkosh , wisconsin ( 66083 )', '1871', 'public', '9386', '1913 - 14'], ['university of wisconsin - platteville', 'pioneers', 'platteville , wisconsin ( 11224 )', '1866', 'public', '6498', '1913 - 14'], ['university of wisconsin - river falls', 'falcons', 'river falls , wisconsin ( 15000 )', '1874', 'public', '5801', '1913 - 14'], ['university of wisconsin - stevens point', 'pointers', 'stevens point , wisconsin ( 26717 )', '1894', 'public', '8481', '1913 - 14'], ['university of wisconsin - stout', 'blue devils', 'menomonie , wisconsin ( 16264 )', '1891', 'public', '6874', '1914 - 15'], ['university of wisconsin - superior', 'yellowjackets', 'superior , wisconsin ( 26960 )', '1893', 'public', '2114', '1913 - 14']]
|
angela stanford
|
https://en.wikipedia.org/wiki/Angela_Stanford
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-14836185-3.html.csv
|
majority
|
angela stanford finished in the top 50 of the money rank list in her tournaments played .
|
{'scope': 'all', 'col': '10', 'most_or_all': 'most', 'criterion': 'less_than', 'value': '50', 'subset': None}
|
{'func': 'most_less', 'args': ['all_rows', 'money list rank', '50'], 'result': True, 'ind': 0, 'tointer': 'for the money list rank records of all rows , most of them are less than 50 .', 'tostr': 'most_less { all_rows ; money list rank ; 50 } = true'}
|
most_less { all_rows ; money list rank ; 50 } = true
|
for the money list rank records of all rows , most of them are less than 50 .
|
1
|
1
|
{'most_less_0': 0, 'result_1': 1, 'all_rows_2': 2, 'money list rank_3': 3, '50_4': 4}
|
{'most_less_0': 'most_less', 'result_1': 'true', 'all_rows_2': 'all_rows', 'money list rank_3': 'money list rank', '50_4': '50'}
|
{'most_less_0': [1], 'result_1': [], 'all_rows_2': [0], 'money list rank_3': [0], '50_4': [0]}
|
['year', 'tournaments played', 'cuts made', 'wins', '2nd', '3rd', 'top 10s', 'best finish', 'earnings', 'money list rank', 'scoring average', 'scoring rank']
|
[['2001', '26', '12', '0', '0', '0', '0', 't15', '66956', '98', '73.24', '103'], ['2002', '19', '12', '0', '1', '0', '2', '2', '221857', '45', '72.37', '46'], ['2003', '21', '17', '1', '1', '0', '3', '1', '643192', '17', '71.94', '38'], ['2004', '24', '19', '0', '0', '0', '2', 't4', '297790', '39', '71.86', 't43'], ['2005', '25', '15', '0', '0', '1', '3', 't3', '272288', '44', '73.11', '69'], ['2006', '25', '20', '0', '2', '0', '3', '2', '473218', '23', '71.80', 't29'], ['2007', '24', '21', '0', '0', '2', '12', 't3', '713880', '19', '71.62', '11'], ['2008', '27', '23', '2', '1', '2', '10', '1', '1134753', '9', '71.22', '9'], ['2009', '21', '20', '1', '2', '2', '11', '1', '1081916', '10', '70.64', '11'], ['2010', '22', '19', '0', '1', '0', '7', '2', '596830', '18', '71.35', '19'], ['2011', '21', '20', '0', '0', '3', '9', '3', '1017196', '7', '71.42', '15'], ['2012', '26', '23', '1', '2', '1', '6', '1', '794294', '16', '71.51', '21']]
|
1965 american football league draft
|
https://en.wikipedia.org/wiki/1965_American_Football_League_Draft
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18652198-11.html.csv
|
unique
|
doug goodwin was the only running back picked between picks 81-88 .
|
{'scope': 'all', 'row': '8', 'col': '4', 'col_other': '3', 'criterion': 'equal', 'value': 'running back', 'subset': None}
|
{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'position', 'running back'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose position record fuzzily matches to running back .', 'tostr': 'filter_eq { all_rows ; position ; running back }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; position ; running back } }', 'tointer': 'select the rows whose position record fuzzily matches to running back . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'position', 'running back'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose position record fuzzily matches to running back .', 'tostr': 'filter_eq { all_rows ; position ; running back }'}, 'player'], 'result': 'doug goodwin', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; position ; running back } ; player }'}, 'doug goodwin'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; position ; running back } ; player } ; doug goodwin }', 'tointer': 'the player record of this unqiue row is doug goodwin .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; position ; running back } } ; eq { hop { filter_eq { all_rows ; position ; running back } ; player } ; doug goodwin } } = true', 'tointer': 'select the rows whose position record fuzzily matches to running back . there is only one such row in the table . the player record of this unqiue row is doug goodwin .'}
|
and { only { filter_eq { all_rows ; position ; running back } } ; eq { hop { filter_eq { all_rows ; position ; running back } ; player } ; doug goodwin } } = true
|
select the rows whose position record fuzzily matches to running back . there is only one such row in the table . the player record of this unqiue row is doug goodwin .
|
6
|
5
|
{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'position_7': 7, 'running back_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'player_9': 9, 'doug goodwin_10': 10}
|
{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'position_7': 'position', 'running back_8': 'running back', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'player_9': 'player', 'doug goodwin_10': 'doug goodwin'}
|
{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'position_7': [0], 'running back_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'player_9': [2], 'doug goodwin_10': [3]}
|
['pick', 'team', 'player', 'position', 'college']
|
[['81', 'denver broncos', 'tom vaughn', 'defensive back', 'iowa state'], ['82', 'houston oilers', 'kent mccloughan', 'cornerback', 'nebraska'], ['83', 'oakland raiders', 'bill minor', 'linebacker', 'illinois'], ['84', 'new york jets', 'jim gray', 'defensive back', 'toledo'], ['85', 'kansas city chiefs', 'al piraino', 'tackle', 'wisconsin'], ['86', 'san diego chargers', 'veran smith', 'guard', 'utah state'], ['87', 'boston patriots', 'john frechette', 'tackle', 'boston college'], ['88', 'buffalo bills', 'doug goodwin', 'running back', 'maryland eastern shore']]
|
geothermal power in new zealand
|
https://en.wikipedia.org/wiki/Geothermal_power_in_New_Zealand
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15908826-1.html.csv
|
majority
|
the majority of the geothermal power stations in new zealand listed have a capacity of over 20 mw .
|
{'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'greater_than', 'value': '20', 'subset': None}
|
{'func': 'most_greater', 'args': ['all_rows', 'capacity ( mw )', '20'], 'result': True, 'ind': 0, 'tointer': 'for the capacity ( mw ) records of all rows , most of them are greater than 20 .', 'tostr': 'most_greater { all_rows ; capacity ( mw ) ; 20 } = true'}
|
most_greater { all_rows ; capacity ( mw ) ; 20 } = true
|
for the capacity ( mw ) records of all rows , most of them are greater than 20 .
|
1
|
1
|
{'most_greater_0': 0, 'result_1': 1, 'all_rows_2': 2, 'capacity (mw)_3': 3, '20_4': 4}
|
{'most_greater_0': 'most_greater', 'result_1': 'true', 'all_rows_2': 'all_rows', 'capacity (mw)_3': 'capacity ( mw )', '20_4': '20'}
|
{'most_greater_0': [1], 'result_1': [], 'all_rows_2': [0], 'capacity (mw)_3': [0], '20_4': [0]}
|
['name', 'location', 'field', 'capacity ( mw )', 'annual generation ( average gwh )', 'commissioned']
|
[['kawerau ( bope )', 'kawerau , bay of plenty', 'kawerau', '6.3', '35', '1989 , 1993'], ['kawerau ( ka24 )', 'kawerau , bay of plenty', 'kawerau', '8.3', '70', '2008'], ['kawerau ( mrp )', 'kawerau , bay of plenty', 'kawerau', '100', '800', '2008'], ['mokai', 'northwest of taupo', 'mokai', '112', '900', '2000'], ['nga awa purua', 'north of taupo', 'rotokawa', '140', '1100', '2010'], ['ngatamariki', 'north of taupo', 'ngatamariki', '82', '600 ( approx )', '2013'], ['ngawha', 'near kaikohe , northland', 'ngawha', '25', '78', '1998'], ['ohaaki', 'between rotorua and taupo', 'ohaaki', '70', '400', '1989'], ['poihipi', 'north of taupo', 'wairakie', '55', '350', '1997'], ['rotokawa', 'north of taupo', 'rotokawa', '33', '210', '1997'], ['te huka', 'north of taupo', 'tauhara', '23', '170 ( approx )', '2010'], ['wairakei', 'north of taupo', 'wairakei', '161', '1310', '1958 , 2005']]
|
2008 - 09 minnesota timberwolves season
|
https://en.wikipedia.org/wiki/2008%E2%80%9309_Minnesota_Timberwolves_season
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17058226-7.html.csv
|
aggregation
|
during their 2008-2009 season , from games 32-45 , the minnesota timberwolves ' high rebounders combined for 175 rebounds .
|
{'scope': 'all', 'col': '6', 'type': 'sum', 'result': '175', 'subset': None}
|
{'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'high rebounds'], 'result': '175', 'ind': 0, 'tostr': 'sum { all_rows ; high rebounds }'}, '175'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; high rebounds } ; 175 } = true', 'tointer': 'the sum of the high rebounds record of all rows is 175 .'}
|
round_eq { sum { all_rows ; high rebounds } ; 175 } = true
|
the sum of the high rebounds record of all rows is 175 .
|
2
|
2
|
{'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'high rebounds_4': 4, '175_5': 5}
|
{'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'high rebounds_4': 'high rebounds', '175_5': '175'}
|
{'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'high rebounds_4': [0], '175_5': [1]}
|
['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record']
|
[['32', 'january 2', 'golden state', 'w 115 - 108 ( ot )', 'al jefferson ( 32 )', 'al jefferson , ryan gomes ( 10 )', 'randy foye ( 7 )', 'target center 11921', '7 - 25'], ['33', 'january 3', 'chicago', 'w 102 - 92 ( ot )', 'randy foye ( 21 )', 'al jefferson ( 14 )', 'sebastian telfair ( 6 )', 'united center 20516', '8 - 25'], ['34', 'january 6', 'memphis', 'w 94 - 87 ( ot )', 'randy foye ( 23 )', 'al jefferson ( 12 )', 'sebastian telfair ( 9 )', 'fedexforum 10156', '9 - 25'], ['35', 'january 7', 'oklahoma city', 'w 129 - 87 ( ot )', 'randy foye ( 32 )', 'kevin love ( 15 )', 'randy foye ( 6 )', 'target center 10272', '10 - 25'], ['36', 'january 10', 'milwaukee', 'w 106 - 104 ( ot )', 'rodney carney ( 22 )', 'kevin love ( 12 )', 'sebastian telfair ( 11 )', 'target center 15007', '11 - 25'], ['37', 'january 13', 'miami', 'l 96 - 99 ( ot )', 'randy foye ( 29 )', 'al jefferson ( 10 )', 'randy foye ( 8 )', 'target center 10856', '11 - 26'], ['38', 'january 16', 'phoenix', 'w 105 - 103 ( ot )', 'al jefferson ( 22 )', 'kevin love ( 14 )', 'mike miller ( 5 )', 'us airways center 18422', '12 - 26'], ['39', 'january 19', 'la clippers', 'w 94 - 86 ( ot )', 'al jefferson , craig smith ( 20 )', 'al jefferson ( 17 )', 'sebastian telfair ( 9 )', 'staples center 14399', '13 - 26'], ['40', 'january 20', 'utah', 'l 107 - 112 ( ot )', 'al jefferson ( 25 )', 'kevin love ( 9 )', 'sebastian telfair ( 9 )', 'energysolutions arena 19911', '13 - 27'], ['41', 'january 23', 'new orleans', 'w 116 - 108 ( ot )', 'al jefferson , randy foye ( 24 )', 'al jefferson ( 14 )', 'randy foye , sebastian telfair ( 8 )', 'target center 18224', '14 - 27'], ['42', 'january 25', 'chicago', 'w 109 - 108 ( ot )', 'al jefferson ( 39 )', 'kevin love ( 15 )', 'mike miller ( 7 )', 'target center 16009', '15 - 27'], ['43', 'january 26', 'milwaukee', 'w 90 - 83 ( ot )', 'al jefferson ( 23 )', 'al jefferson , mike miller ( 10 )', 'randy foye ( 7 )', 'bradley center 12914', '16 - 27'], ['44', 'january 28', 'detroit', 'l 89 - 98 ( ot )', 'al jefferson ( 24 )', 'kevin love ( 10 )', 'randy foye , mike miller ( 5 )', 'target center 14232', '16 - 28'], ['45', 'january 30', 'la lakers', 'l 119 - 132 ( ot )', 'al jefferson ( 34 )', 'al jefferson ( 13 )', 'sebastian telfair ( 7 )', 'target center 19111', '16 - 29']]
|
hayate usui
|
https://en.wikipedia.org/wiki/Hayate_Usui
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11221360-2.html.csv
|
aggregation
|
the matches played by hayate usui averaged two rounds each .
|
{'scope': 'all', 'col': '6', 'type': 'average', 'result': '2', 'subset': None}
|
{'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'round'], 'result': '2', 'ind': 0, 'tostr': 'avg { all_rows ; round }'}, '2'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; round } ; 2 } = true', 'tointer': 'the average of the round record of all rows is 2 .'}
|
round_eq { avg { all_rows ; round } ; 2 } = true
|
the average of the round record of all rows is 2 .
|
2
|
2
|
{'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'round_4': 4, '2_5': 5}
|
{'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'round_4': 'round', '2_5': '2'}
|
{'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'round_4': [0], '2_5': [1]}
|
['res', 'record', 'opponent', 'method', 'event', 'round', 'time']
|
[['loss', '10 - 8 - 1', 'issei tamura', 'decision ( unanimous )', 'shooto', '2', '5:00'], ['loss', '10 - 7 - 1', 'hiroshi nakamura', 'decision ( unanimous )', 'shooto', '3', '5:00'], ['win', '10 - 6 - 1', 'shinya kumazawa', 'decision ( unanimous )', 'tenkaichi fight', '2', '5:00'], ['win', '9 - 6 - 1', 'sakae kasuya', 'decision ( majority )', 'shooto', '2', '5:00'], ['win', '8 - 6 - 1', 'daisuke ishizawa', 'decision ( unanimous )', 'shooto', '2', '5:00'], ['loss', '7 - 6 - 1', 'shintaro ishiwatari', 'decision ( unanimous )', 'shooto', '2', '5:00'], ['win', '7 - 5 - 1', 'eiji murayama', 'decision ( unanimous )', 'shooto', '2', '5:00'], ['win', '6 - 5 - 1', 'hiroki kita', 'decision ( unanimous )', 'shooto', '2', '5:00'], ['draw', '5 - 5 - 1', 'ed newalu', 'draw', 'pip - east vs west', '2', '5:00'], ['win', '5 - 5', 'manabu inoue', 'decision ( majority )', 'gcm - dog 5', '2', '5:00'], ['win', '4 - 5', 'michihisa asano', 'decision ( unanimous )', 'mars', '2', '5:00'], ['loss', '3 - 5', 'akitoshi tamura', 'submission ( rear naked choke )', 'shooto', '2', '4:51'], ['win', '3 - 4', 'naosuke mizoguchi', 'submission ( armlock )', 'shooto', '2', '2:38'], ['loss', '2 - 4', 'takeshi inoue', 'ko ( punch )', 'shooto', '2', '4:58'], ['win', '2 - 3', 'seigi fujioka', 'decision ( majority )', 'shooto', '2', '5:00'], ['win', '1 - 3', 'takeshi matsushita', 'decision ( majority )', 'shooto', '2', '5:00'], ['loss', '0 - 3', 'keisuke yamada', 'decision ( majority )', 'shooto', '2', '5:00'], ['loss', '0 - 2', 'takashi inoue', 'decision ( unanimous )', 'shooto', '2', '5:00'], ['loss', '0 - 1', 'hiroyuki takaya', 'tko ( tko )', 'shooto', '2', '2:06']]
|
test matches ( 1991 - 2000 )
|
https://en.wikipedia.org/wiki/Test_matches_%281991%E2%80%932000%29
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12410929-44.html.csv
|
majority
|
mark taylor was the home captain for all of australia 's cricket test matches .
|
{'scope': 'all', 'col': '2', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'mark taylor', 'subset': None}
|
{'func': 'all_str_eq', 'args': ['all_rows', 'home captain', 'mark taylor'], 'result': True, 'ind': 0, 'tointer': 'for the home captain records of all rows , all of them fuzzily match to mark taylor .', 'tostr': 'all_eq { all_rows ; home captain ; mark taylor } = true'}
|
all_eq { all_rows ; home captain ; mark taylor } = true
|
for the home captain records of all rows , all of them fuzzily match to mark taylor .
|
1
|
1
|
{'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'home captain_3': 3, 'mark taylor_4': 4}
|
{'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'home captain_3': 'home captain', 'mark taylor_4': 'mark taylor'}
|
{'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'home captain_3': [0], 'mark taylor_4': [0]}
|
['date', 'home captain', 'away captain', 'venue', 'result']
|
[['25 , 26 , 27 , 28 , 29 november 1994', 'mark taylor', 'mike atherton', 'brisbane cricket ground', 'aus by 184 runs'], ['24 , 26 , 27 , 28 , 29 december 1994', 'mark taylor', 'mike atherton', 'melbourne cricket ground', 'aus by 295 runs'], ['1 , 2 , 3 , 4 , 5 january 1995', 'mark taylor', 'mike atherton', 'sydney cricket ground', 'draw'], ['26 , 27 , 28 , 29 , 30 january 1995', 'mark taylor', 'mike atherton', 'adelaide oval', 'eng by 106 runs'], ['3 , 4 , 5 , 6 , 7 february 1995', 'mark taylor', 'mike atherton', 'waca ground', 'aus by 329 runs']]
|
2009 - 10 cleveland cavaliers season
|
https://en.wikipedia.org/wiki/2009%E2%80%9310_Cleveland_Cavaliers_season
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-22654073-7.html.csv
|
count
|
mo williams ranked as the highest assists 2 times in the season .
|
{'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'mo williams', 'result': '2', 'col': '7', 'subset': None}
|
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'high assists', 'mo williams'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose high assists record fuzzily matches to mo williams .', 'tostr': 'filter_eq { all_rows ; high assists ; mo williams }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; high assists ; mo williams } }', 'tointer': 'select the rows whose high assists record fuzzily matches to mo williams . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; high assists ; mo williams } } ; 2 } = true', 'tointer': 'select the rows whose high assists record fuzzily matches to mo williams . the number of such rows is 2 .'}
|
eq { count { filter_eq { all_rows ; high assists ; mo williams } } ; 2 } = true
|
select the rows whose high assists record fuzzily matches to mo williams . the number of such rows is 2 .
|
3
|
3
|
{'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'high assists_5': 5, 'mo williams_6': 6, '2_7': 7}
|
{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'high assists_5': 'high assists', 'mo williams_6': 'mo williams', '2_7': '2'}
|
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'high assists_5': [0], 'mo williams_6': [0], '2_7': [2]}
|
['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record']
|
[['18', 'december 2', 'phoenix suns', 'w 107 - 90 ( ot )', 'zydrunas ilgauskas ( 14 )', "shaquille o'neal ( 9 )", 'lebron james ( 10 )', 'quicken loans arena 20562', '13 - 5'], ['19', 'december 4', 'chicago bulls', 'w 101 - 87 ( ot )', 'lebron james ( 23 )', "zydrunas ilgauskas , shaquille o'neal ( 7 )", 'lebron james ( 11 )', 'quicken loans arena 20562', '14 - 5'], ['20', 'december 6', 'milwaukee bucks', 'w 101 - 86 ( ot )', 'delonte west ( 21 )', 'anderson varejão ( 12 )', 'lebron james ( 10 )', 'bradley center 16625', '15 - 5'], ['21', 'december 8', 'memphis grizzlies', 'l 109 - 111 ( ot )', 'lebron james ( 43 )', 'lebron james ( 13 )', 'mo williams ( 8 )', 'fedex forum 16325', '15 - 6'], ['22', 'december 9', 'houston rockets', 'l 85 - 95 ( ot )', 'lebron james ( 27 )', "shaquille o'neal , j j hickson ( 10 )", 'lebron james ( 7 )', 'toyota center 18200', '15 - 7'], ['23', 'december 11', 'portland trail blazers', 'w 104 - 99 ( ot )', 'lebron james ( 33 )', "shaquille o'neal ( 11 )", 'mo williams ( 10 )', 'quicken loans arena 20562', '16 - 7'], ['24', 'december 13', 'oklahoma city thunder', 'w 102 - 89 ( ot )', 'lebron james ( 44 )', 'anderson varejão ( 10 )', 'lebron james ( 6 )', 'ford center 18203', '17 - 7'], ['25', 'december 15', 'new jersey nets', 'w 99 - 89 ( ot )', 'lebron james ( 23 )', 'mo williams , jamario moon ( 8 )', 'lebron james ( 7 )', 'quicken loans arena 20562', '18 - 7'], ['26', 'december 16', 'philadelphia 76ers', 'w 108 - 101 ( ot )', 'lebron james ( 36 )', "shaquille o'neal ( 9 )", 'lebron james ( 7 )', 'wachovia center 19517', '19 - 7'], ['27', 'december 18', 'milwaukee bucks', 'w 85 - 82 ( ot )', 'lebron james ( 26 )', 'lebron james ( 10 )', 'lebron james ( 8 )', 'quicken loans arena 20562', '20 - 7'], ['28', 'december 20', 'dallas mavericks', 'l 95 - 102 ( ot )', 'lebron james ( 25 )', "anderson varejão , shaquille o'neal ( 8 )", 'lebron james ( 6 )', 'american airlines center 20346', '20 - 8'], ['29', 'december 21', 'phoenix suns', 'w 109 - 91 ( ot )', 'lebron james ( 29 )', 'mo williams , lebron james , jj hickson ( 6 )', 'delonte west ( 6 )', 'us airways center 18221', '21 - 8'], ['30', 'december 23', 'sacramento kings', 'w 117 - 104 ( ot )', 'lebron james ( 34 )', 'lebron james ( 16 )', 'lebron james ( 10 )', 'arco arena 16407', '22 - 8'], ['31', 'december 25', 'la lakers', 'w 102 - 87 ( ot )', 'mo williams ( 28 )', 'anderson varejão , zydrunas ilgauskas ( 9 )', 'lebron james ( 9 )', 'staples center 18997', '23 - 8'], ['32', 'december 27', 'houston rockets', 'w 108 - 83 ( ot )', 'lebron james ( 29 )', "shaquille o'neal ( 11 )", 'lebron james ( 6 )', 'quicken loans arena 20562', '24 - 8']]
|
athletics at the 1982 commonwealth games
|
https://en.wikipedia.org/wiki/Athletics_at_the_1982_Commonwealth_Games
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12972743-3.html.csv
|
superlative
|
the highest number of silver medals won at the 1982 commonwealth games was by england .
|
{'scope': 'all', 'col_superlative': '4', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '2', 'subset': None}
|
{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'silver'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; silver }'}, 'nation'], 'result': 'england', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; silver } ; nation }'}, 'england'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; silver } ; nation } ; england } = true', 'tointer': 'select the row whose silver record of all rows is maximum . the nation record of this row is england .'}
|
eq { hop { argmax { all_rows ; silver } ; nation } ; england } = true
|
select the row whose silver record of all rows is maximum . the nation record of this row is england .
|
3
|
3
|
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'silver_5': 5, 'nation_6': 6, 'england_7': 7}
|
{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'silver_5': 'silver', 'nation_6': 'nation', 'england_7': 'england'}
|
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'silver_5': [0], 'nation_6': [1], 'england_7': [2]}
|
['rank', 'nation', 'gold', 'silver', 'bronze', 'total']
|
[['1', 'england', '11', '10', '11', '32'], ['2', 'australia', '9', '9', '4', '22'], ['3', 'canada', '6', '7', '8', '21'], ['4', 'scotland', '3', '1', '6', '10'], ['5', 'bahamas', '2', '2', '1', '5'], ['6', 'new zealand', '2', '1', '3', '6'], ['7', 'jamaica', '2', '1', '1', '4'], ['8', 'wales', '2', '1', '0', '3'], ['9', 'tanzania', '1', '2', '1', '4'], ['10', 'kenya', '1', '1', '3', '5'], ['11', 'nigeria', '1', '0', '0', '1'], ['12', 'uganda', '0', '2', '0', '2'], ['13', 'northern ireland', '0', '1', '0', '1'], ['14', 'bermuda', '0', '0', '1', '1'], ['total', 'total', '40', '38', '39', '117']]
|
automobiles gonfaronnaises sportives
|
https://en.wikipedia.org/wiki/Automobiles_Gonfaronnaises_Sportives
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1226665-1.html.csv
|
superlative
|
ags jh25b ags jh27 is the latest model of chasis being introduced to the market among automobiles gonfaronnaises sportives .
|
{'scope': 'all', 'col_superlative': '1', 'row_superlative': '6', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '2', 'subset': None}
|
{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'year'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; year }'}, 'chassis'], 'result': 'ags jh25b ags jh27', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; year } ; chassis }'}, 'ags jh25b ags jh27'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; year } ; chassis } ; ags jh25b ags jh27 } = true', 'tointer': 'select the row whose year record of all rows is maximum . the chassis record of this row is ags jh25b ags jh27 .'}
|
eq { hop { argmax { all_rows ; year } ; chassis } ; ags jh25b ags jh27 } = true
|
select the row whose year record of all rows is maximum . the chassis record of this row is ags jh25b ags jh27 .
|
3
|
3
|
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'year_5': 5, 'chassis_6': 6, 'ags jh25b ags jh27_7': 7}
|
{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'year_5': 'year', 'chassis_6': 'chassis', 'ags jh25b ags jh27_7': 'ags jh25b ags jh27'}
|
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'year_5': [0], 'chassis_6': [1], 'ags jh25b ags jh27_7': [2]}
|
['year', 'chassis', 'engine', 'tyres', 'points']
|
[['1986', 'ags jh21c', 'motori moderni 615 - 90 v6 ( t / c )', 'p', '0'], ['1987', 'ags jh22', 'ford dfz v8', 'g', '1'], ['1988', 'ags jh23', 'ford dfz v8', 'g', '0'], ['1989', 'ags jh23b ags jh24', 'ford dfr v8', 'g', '1'], ['1990', 'ags jh24 ags jh25', 'ford dfr v8', 'g', '0'], ['1991', 'ags jh25b ags jh27', 'ford dfr v8', 'g', '0']]
|
list of republic of doyle episodes
|
https://en.wikipedia.org/wiki/List_of_Republic_of_Doyle_episodes
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27547668-3.html.csv
|
aggregation
|
the average viewership across all republic of doyle episodes is around 880000 .
|
{'scope': 'all', 'col': '6', 'type': 'average', 'result': '880000', 'subset': None}
|
{'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'viewers'], 'result': '880000', 'ind': 0, 'tostr': 'avg { all_rows ; viewers }'}, '880000'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; viewers } ; 880000 } = true', 'tointer': 'the average of the viewers record of all rows is 880000 .'}
|
round_eq { avg { all_rows ; viewers } ; 880000 } = true
|
the average of the viewers record of all rows is 880000 .
|
2
|
2
|
{'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'viewers_4': 4, '880000_5': 5}
|
{'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'viewers_4': 'viewers', '880000_5': '880000'}
|
{'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'viewers_4': [0], '880000_5': [1]}
|
['', 'no', 'title', 'directed by', 'written by', 'viewers', 'original airdate', 'prod code']
|
[['13', '1', 'live and let doyle', 'james allodi', 'allan hawco', '1038000', 'january 12 , 2011', '201'], ['14', '2', 'popeye doyle', 'steve scaini', 'allan hawco', '944000', 'january 19 , 2011', '202'], ['15', '3', 'a stand up guy', 'steve scaini', 'perry chafe', '776000', 'january 26 , 2011', '203'], ['16', '4', 'the son also rises', 'steve dimarco', 'jesse mckeown', '899000', 'february 2 , 2011', '204'], ['17', '5', 'something old , someone blue', 'james allodi', 'adam higgs & jackie may', '854000', 'february 9 , 2011', '205'], ['18', '6', 'the ryans and the pittmans', 'steve dimarco', 'greg nelson', '843000', 'february 16 , 2011', '206'], ['19', '7', 'crashing on the couch', 'keith samples', 'jackie may', '760000', 'february 23 , 2011', '207'], ['20', '8', 'sympathy for the devil', 'stacey curtis', 'john callaghan', '834400', 'march 2 , 2011', '208'], ['21', '9', 'will the real des courtney please stand up', 'keith samples', 'greg nelson', '1026000', 'march 9 , 2011', '209'], ['22', '10', 'the special detective', 'steve scaini', 'adam higgs', '836000', 'march 16 , 2011', '210'], ['23', '11', "do n't gamble with city hall", 'john vatcher', 'jackie may', '1021000', 'march 23 , 2011', '211'], ['24', '12', "st john 's town", 'keith samples', 'perry chafe', '730000', 'march 30 , 2011', '212']]
|
1931 vfl season
|
https://en.wikipedia.org/wiki/1931_VFL_season
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10789881-9.html.csv
|
ordinal
|
the second biggest crowd on july 4 , 1931 was at the game at mcg .
|
{'row': '1', 'col': '6', 'order': '2', 'col_other': '5', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None}
|
{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'crowd', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; crowd ; 2 }'}, 'venue'], 'result': 'mcg', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; crowd ; 2 } ; venue }'}, 'mcg'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; crowd ; 2 } ; venue } ; mcg } = true', 'tointer': 'select the row whose crowd record of all rows is 2nd maximum . the venue record of this row is mcg .'}
|
eq { hop { nth_argmax { all_rows ; crowd ; 2 } ; venue } ; mcg } = true
|
select the row whose crowd record of all rows is 2nd maximum . the venue record of this row is mcg .
|
3
|
3
|
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'crowd_5': 5, '2_6': 6, 'venue_7': 7, 'mcg_8': 8}
|
{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'crowd_5': 'crowd', '2_6': '2', 'venue_7': 'venue', 'mcg_8': 'mcg'}
|
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'crowd_5': [0], '2_6': [0], 'venue_7': [1], 'mcg_8': [2]}
|
['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date']
|
[['melbourne', '4.12 ( 36 )', 'st kilda', '9.9 ( 63 )', 'mcg', '15826', '4 july 1931'], ['geelong', '13.9 ( 87 )', 'hawthorn', '9.7 ( 61 )', 'corio oval', '9500', '4 july 1931'], ['fitzroy', '8.13 ( 61 )', 'richmond', '14.17 ( 101 )', 'brunswick street oval', '15000', '4 july 1931'], ['south melbourne', '10.13 ( 73 )', 'essendon', '9.9 ( 63 )', 'lake oval', '11000', '4 july 1931'], ['footscray', '4.16 ( 40 )', 'collingwood', '6.8 ( 44 )', 'western oval', '21500', '4 july 1931'], ['north melbourne', '7.8 ( 50 )', 'carlton', '20.10 ( 130 )', 'arden street oval', '10000', '4 july 1931']]
|
family life radio
|
https://en.wikipedia.org/wiki/Family_Life_Radio
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17101015-10.html.csv
|
count
|
the family life radio has 5 different frequency mhz .
|
{'scope': 'all', 'criterion': 'all', 'value': 'n/a', 'result': '5', 'col': '2', 'subset': None}
|
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_all', 'args': ['all_rows', 'frequency mhz'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose frequency mhz record is arbitrary .', 'tostr': 'filter_all { all_rows ; frequency mhz }'}], 'result': '5', 'ind': 1, 'tostr': 'count { filter_all { all_rows ; frequency mhz } }', 'tointer': 'select the rows whose frequency mhz record is arbitrary . the number of such rows is 5 .'}, '5'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_all { all_rows ; frequency mhz } } ; 5 } = true', 'tointer': 'select the rows whose frequency mhz record is arbitrary . the number of such rows is 5 .'}
|
eq { count { filter_all { all_rows ; frequency mhz } } ; 5 } = true
|
select the rows whose frequency mhz record is arbitrary . the number of such rows is 5 .
|
3
|
3
|
{'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_all_0': 0, 'all_rows_4': 4, 'frequency mhz_5': 5, '5_6': 6}
|
{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_all_0': 'filter_all', 'all_rows_4': 'all_rows', 'frequency mhz_5': 'frequency mhz', '5_6': '5'}
|
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_all_0': [1], 'all_rows_4': [0], 'frequency mhz_5': [0], '5_6': [2]}
|
['call sign', 'frequency mhz', 'city of license', 'erp w', 'fcc info']
|
[['kamy', '90.1', 'lubbock , texas', '63000', ''], ['kflb', '88.1', 'midland , texas', '100000', ''], ['kflb', '920', 'odessa , texas', '1000 day 500 night', ''], ['krgn', '102.9', 'amarillo , texas', '100000', ''], ['k297au', '107.3', 'big spring , texas', '62', 'fcc']]
|
1967 st. louis cardinals ( nfl ) season
|
https://en.wikipedia.org/wiki/1967_St._Louis_Cardinals_%28NFL%29_season
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16678283-1.html.csv
|
ordinal
|
the earliest game the new york giants played in the 1967 st. louis cardinals ( nfl ) season was september 17 , 1967 .
|
{'scope': 'subset', 'row': '1', 'col': '2', 'order': '1', 'col_other': 'n/a', 'max_or_min': 'min_to_max', 'value_mentioned': 'yes', 'subset': {'col': '3', 'criterion': 'equal', 'value': 'new york giants'}}
|
{'func': 'eq', 'args': [{'func': 'nth_min', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', 'new york giants'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; opponent ; new york giants }', 'tointer': 'select the rows whose opponent record fuzzily matches to new york giants .'}, 'date', '1'], 'result': 'september 17 , 1967', 'ind': 1, 'tostr': 'nth_min { filter_eq { all_rows ; opponent ; new york giants } ; date ; 1 }', 'tointer': 'select the rows whose opponent record fuzzily matches to new york giants . the 1st minimum date record of these rows is september 17 , 1967 .'}, 'september 17 , 1967'], 'result': True, 'ind': 2, 'tostr': 'eq { nth_min { filter_eq { all_rows ; opponent ; new york giants } ; date ; 1 } ; september 17 , 1967 } = true', 'tointer': 'select the rows whose opponent record fuzzily matches to new york giants . the 1st minimum date record of these rows is september 17 , 1967 .'}
|
eq { nth_min { filter_eq { all_rows ; opponent ; new york giants } ; date ; 1 } ; september 17 , 1967 } = true
|
select the rows whose opponent record fuzzily matches to new york giants . the 1st minimum date record of these rows is september 17 , 1967 .
|
3
|
3
|
{'eq_2': 2, 'result_3': 3, 'nth_min_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'opponent_5': 5, 'new york giants_6': 6, 'date_7': 7, '1_8': 8, 'september 17 , 1967_9': 9}
|
{'eq_2': 'eq', 'result_3': 'true', 'nth_min_1': 'nth_min', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'opponent_5': 'opponent', 'new york giants_6': 'new york giants', 'date_7': 'date', '1_8': '1', 'september 17 , 1967_9': 'september 17 , 1967'}
|
{'eq_2': [3], 'result_3': [], 'nth_min_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'opponent_5': [0], 'new york giants_6': [0], 'date_7': [1], '1_8': [1], 'september 17 , 1967_9': [2]}
|
['week', 'date', 'opponent', 'result', 'attendance']
|
[['1', 'september 17 , 1967', 'new york giants', 'l 37 - 20', '40801'], ['2', 'september 24 , 1967', 'pittsburgh steelers', 'w 28 - 14', '45579'], ['3', 'october 1 , 1967', 'detroit lions', 'w 38 - 28', '43821'], ['4', 'october 8 , 1967', 'minnesota vikings', 'w 34 - 24', '40017'], ['5', 'october 15 , 1967', 'cleveland browns', 'l 20 - 16', '77813'], ['6', 'october 22 , 1967', 'philadelphia eagles', 'w 48 - 14', '46562'], ['7', 'october 30 , 1967', 'green bay packers', 'l 31 - 23', '49792'], ['8', 'november 5 , 1967', 'washington redskins', 'w 27 - 21', '50480'], ['9', 'november 12 , 1967', 'pittsburgh steelers', 't 14 - 14', '46994'], ['10', 'november 19 , 1967', 'chicago bears', 'l 30 - 3', '47417'], ['11', 'november 23 , 1967', 'dallas cowboys', 'l 46 - 21', '68787'], ['12', 'december 3 , 1967', 'new orleans saints', 'w 31 - 20', '41171'], ['13', 'december 10 , 1967', 'cleveland browns', 'l 20 - 16', '47782'], ['14', 'december 17 , 1967', 'new york giants', 'l 37 - 14', '62955']]
|
2008 nascar craftsman truck series
|
https://en.wikipedia.org/wiki/2008_NASCAR_Craftsman_Truck_Series
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14292964-20.html.csv
|
count
|
four cars made by toyota competed in this race .
|
{'scope': 'all', 'criterion': 'equal', 'value': 'toyota', 'result': '4', 'col': '4', 'subset': None}
|
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'make', 'toyota'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose make record fuzzily matches to toyota .', 'tostr': 'filter_eq { all_rows ; make ; toyota }'}], 'result': '4', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; make ; toyota } }', 'tointer': 'select the rows whose make record fuzzily matches to toyota . the number of such rows is 4 .'}, '4'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; make ; toyota } } ; 4 } = true', 'tointer': 'select the rows whose make record fuzzily matches to toyota . the number of such rows is 4 .'}
|
eq { count { filter_eq { all_rows ; make ; toyota } } ; 4 } = true
|
select the rows whose make record fuzzily matches to toyota . the number of such rows is 4 .
|
3
|
3
|
{'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'make_5': 5, 'toyota_6': 6, '4_7': 7}
|
{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'make_5': 'make', 'toyota_6': 'toyota', '4_7': '4'}
|
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'make_5': [0], 'toyota_6': [0], '4_7': [2]}
|
['pos', 'car', 'driver', 'make', 'team']
|
[['1', '33', 'ron hornaday', 'chevrolet', 'kevin harvick incorporated'], ['2', '18', 'dennis setzer', 'dodge', 'bobby hamilton racing - virginia'], ['3', '23', 'johnny benson', 'toyota', 'bill davis racing'], ['4', '30', 'todd bodine', 'toyota', 'germian racing'], ['5', '2', 'jack sprague', 'chevy', 'kevin harvick incorporated'], ['6', '99', 'erik darnell', 'ford', 'roush fenway racing'], ['7', '5', 'mike skinner', 'toyota', 'bill davis racing'], ['8', '14', 'rick crawford', 'ford', 'circle bar racing'], ['9', '6', 'colin braun r', 'ford', 'roush fenway racing'], ['10', '59', 'ted musgrave', 'toyota', 'ht motorsports']]
|
athletics at the 2008 summer olympics - men 's 200 metres
|
https://en.wikipedia.org/wiki/Athletics_at_the_2008_Summer_Olympics_%E2%80%93_Men%27s_200_metres
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18569011-3.html.csv
|
unique
|
shawn crawford was the only athlete from the united states .
|
{'scope': 'all', 'row': '1', 'col': '4', 'col_other': '3', 'criterion': 'equal', 'value': 'united states', 'subset': None}
|
{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'nationality', 'united states'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose nationality record fuzzily matches to united states .', 'tostr': 'filter_eq { all_rows ; nationality ; united states }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; nationality ; united states } }', 'tointer': 'select the rows whose nationality record fuzzily matches to united states . 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', 'united states'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose nationality record fuzzily matches to united states .', 'tostr': 'filter_eq { all_rows ; nationality ; united states }'}, 'athlete'], 'result': 'shawn crawford', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; nationality ; united states } ; athlete }'}, 'shawn crawford'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; nationality ; united states } ; athlete } ; shawn crawford }', 'tointer': 'the athlete record of this unqiue row is shawn crawford .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; nationality ; united states } } ; eq { hop { filter_eq { all_rows ; nationality ; united states } ; athlete } ; shawn crawford } } = true', 'tointer': 'select the rows whose nationality record fuzzily matches to united states . there is only one such row in the table . the athlete record of this unqiue row is shawn crawford .'}
|
and { only { filter_eq { all_rows ; nationality ; united states } } ; eq { hop { filter_eq { all_rows ; nationality ; united states } ; athlete } ; shawn crawford } } = true
|
select the rows whose nationality record fuzzily matches to united states . there is only one such row in the table . the athlete record of this unqiue row is shawn crawford .
|
6
|
5
|
{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'nationality_7': 7, 'united states_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'athlete_9': 9, 'shawn crawford_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', 'united states_8': 'united states', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'athlete_9': 'athlete', 'shawn crawford_10': 'shawn crawford'}
|
{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'nationality_7': [0], 'united states_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'athlete_9': [2], 'shawn crawford_10': [3]}
|
['rank', 'lane', 'athlete', 'nationality', 'time', 'react']
|
[['1', '4', 'shawn crawford', 'united states', '20.61', '0.216'], ['2', '6', 'marcin jędrusiński', 'poland', '20.64', '0.199'], ['3', '7', 'stephan buckland', 'mauritius', '20.98', '0.229'], ['4', '1', 'jiří vojtík', 'czech republic', '21.05', '0.165'], ['5', '9', 'fanuel kenosi', 'botswana', '21.09', '0.211'], ['6', '3', 'adam harris', 'guyana', '21.36', '0.163'], ['7', '5', 'khalil al - hanahneh', 'jordan', '21.55', '0.184'], ['8', '2', 'solomon bayoh', 'sierra leone', '22.16', '0.216']]
|
el tamarugal
|
https://en.wikipedia.org/wiki/El_Tamarugal
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13764346-1.html.csv
|
unique
|
in el tamarugal , the province commune is the only one that had a population of over 20,000 in 2002 .
|
{'scope': 'all', 'row': '6', 'col': '3', 'col_other': '1', 'criterion': 'greater_than', 'value': '20000', 'subset': None}
|
{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_greater', 'args': ['all_rows', '2002 population', '20000'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose 2002 population record is greater than 20000 .', 'tostr': 'filter_greater { all_rows ; 2002 population ; 20000 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_greater { all_rows ; 2002 population ; 20000 } }', 'tointer': 'select the rows whose 2002 population record is greater than 20000 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_greater', 'args': ['all_rows', '2002 population', '20000'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose 2002 population record is greater than 20000 .', 'tostr': 'filter_greater { all_rows ; 2002 population ; 20000 }'}, 'commune'], 'result': 'province', 'ind': 2, 'tostr': 'hop { filter_greater { all_rows ; 2002 population ; 20000 } ; commune }'}, 'province'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_greater { all_rows ; 2002 population ; 20000 } ; commune } ; province }', 'tointer': 'the commune record of this unqiue row is province .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_greater { all_rows ; 2002 population ; 20000 } } ; eq { hop { filter_greater { all_rows ; 2002 population ; 20000 } ; commune } ; province } } = true', 'tointer': 'select the rows whose 2002 population record is greater than 20000 . there is only one such row in the table . the commune record of this unqiue row is province .'}
|
and { only { filter_greater { all_rows ; 2002 population ; 20000 } } ; eq { hop { filter_greater { all_rows ; 2002 population ; 20000 } ; commune } ; province } } = true
|
select the rows whose 2002 population record is greater than 20000 . there is only one such row in the table . the commune record of this unqiue row is province .
|
6
|
5
|
{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_greater_0': 0, 'all_rows_6': 6, '2002 population_7': 7, '20000_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'commune_9': 9, 'province_10': 10}
|
{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_greater_0': 'filter_greater', 'all_rows_6': 'all_rows', '2002 population_7': '2002 population', '20000_8': '20000', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'commune_9': 'commune', 'province_10': 'province'}
|
{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_greater_0': [1, 2], 'all_rows_6': [0], '2002 population_7': [0], '20000_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'commune_9': [2], 'province_10': [3]}
|
['commune', 'area ( km 2 )', '2002 population', 'density ( km 2 )', 'government website']
|
[['pozo almonte ( capital )', '13765.8', '10830', '0.8', 'link'], ['pica', '8934.3', '6178', '0.7', 'link'], ['huara', '10474.6', '2599', '0.2', 'link'], ['colchane', '4015.6', '1649', '0.4', 'link'], ['camiã ± a', '2200.2', '1275', '0.6', 'none'], ['province', '39390.5', '22531', '0.6', 'link']]
|
2006 east asian judo championships
|
https://en.wikipedia.org/wiki/2006_East_Asian_Judo_Championships
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18991964-3.html.csv
|
majority
|
in the 2006 east asian judo championships most nations earned at least one gold .
|
{'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'greater_than_eq', 'value': '1', 'subset': None}
|
{'func': 'most_greater_eq', 'args': ['all_rows', 'gold', '1'], 'result': True, 'ind': 0, 'tointer': 'for the gold records of all rows , most of them are greater than or equal to 1 .', 'tostr': 'most_greater_eq { all_rows ; gold ; 1 } = true'}
|
most_greater_eq { all_rows ; gold ; 1 } = true
|
for the gold records of all rows , most of them are greater than or equal to 1 .
|
1
|
1
|
{'most_greater_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'gold_3': 3, '1_4': 4}
|
{'most_greater_eq_0': 'most_greater_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'gold_3': 'gold', '1_4': '1'}
|
{'most_greater_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'gold_3': [0], '1_4': [0]}
|
['rank', 'nation', 'gold', 'silver', 'bronze', 'total']
|
[['1', 'japan', '6', '1', '6', '13'], ['2', 'china', '3', '4', '4', '11'], ['3', 'south korea', '3', '3', '3', '9'], ['4', 'mongolia', '1', '5', '12', '18'], ['5', 'north korea', '1', '1', '2', '4'], ['6', 'chinese taipei', '0', '0', '1', '1'], ['total', 'total', '14', '14', '28', '56']]
|
2008 - 09 detroit red wings season
|
https://en.wikipedia.org/wiki/2008%E2%80%9309_Detroit_Red_Wings_season
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17371135-5.html.csv
|
comparative
|
more people went to the game on november 22 than the one on november 29 .
|
{'row_1': '8', 'row_2': '12', 'col': '6', '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', 'date', 'november 22'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose date record fuzzily matches to november 22 .', 'tostr': 'filter_eq { all_rows ; date ; november 22 }'}, 'attendance'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; date ; november 22 } ; attendance }', 'tointer': 'select the rows whose date record fuzzily matches to november 22 . take the attendance record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', 'november 29'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose date record fuzzily matches to november 29 .', 'tostr': 'filter_eq { all_rows ; date ; november 29 }'}, 'attendance'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; date ; november 29 } ; attendance }', 'tointer': 'select the rows whose date record fuzzily matches to november 29 . take the attendance record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; date ; november 22 } ; attendance } ; hop { filter_eq { all_rows ; date ; november 29 } ; attendance } } = true', 'tointer': 'select the rows whose date record fuzzily matches to november 22 . take the attendance record of this row . select the rows whose date record fuzzily matches to november 29 . take the attendance record of this row . the first record is greater than the second record .'}
|
greater { hop { filter_eq { all_rows ; date ; november 22 } ; attendance } ; hop { filter_eq { all_rows ; date ; november 29 } ; attendance } } = true
|
select the rows whose date record fuzzily matches to november 22 . take the attendance record of this row . select the rows whose date record fuzzily matches to november 29 . take the attendance 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, 'date_7': 7, 'november 22_8': 8, 'attendance_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'date_11': 11, 'november 29_12': 12, 'attendance_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', 'date_7': 'date', 'november 22_8': 'november 22', 'attendance_9': 'attendance', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'date_11': 'date', 'november 29_12': 'november 29', 'attendance_13': 'attendance'}
|
{'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'date_7': [0], 'november 22_8': [0], 'attendance_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'date_11': [1], 'november 29_12': [1], 'attendance_13': [3]}
|
['date', 'visitor', 'score', 'home', 'decision', 'attendance', 'record']
|
[['november 2', 'detroit', '3 - 2', 'vancouver', 'osgood', '18630', '8 - 2 - 2'], ['november 8', 'new jersey', '1 - 3', 'detroit', 'osgood', '20066', '9 - 2 - 2'], ['november 11', 'pittsburgh', '7 - 6', 'detroit', 'osgood', '20066', '9 - 2 - 3'], ['november 13', 'detroit', '4 - 3', 'tampa bay', 'osgood', '20544', '10 - 2 - 3'], ['november 14', 'detroit', '3 - 2', 'florida', 'conklin', '18637', '11 - 2 - 3'], ['november 17', 'edmonton', '0 - 4', 'detroit', 'conklin', '18934', '12 - 2 - 3'], ['november 20', 'detroit', '4 - 3', 'edmonton', 'osgood', '16839', '13 - 2 - 3'], ['november 22', 'detroit', '5 - 2', 'calgary', 'conklin', '19289', '14 - 2 - 3'], ['november 24', 'detroit', '2 - 3', 'vancouver', 'osgood', '18630', '14 - 2 - 4'], ['november 26', 'montreal', '3 - 1', 'detroit', 'conklin', '20066', '14 - 3 - 4'], ['november 28', 'columbus', '3 - 5', 'detroit', 'osgood', '20066', '15 - 3 - 4'], ['november 29', 'detroit', '1 - 3', 'boston', 'conklin', '17565', '15 - 4 - 4']]
|
brecht wallis
|
https://en.wikipedia.org/wiki/Brecht_Wallis
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11286695-1.html.csv
|
count
|
brecht wallis had a total of three fights in the location of las vegas , nevada , usa .
|
{'scope': 'all', 'criterion': 'equal', 'value': 'las vegas , nevada , usa', 'result': '3', 'col': '4', 'subset': None}
|
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location', 'las vegas , nevada , usa'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose location record fuzzily matches to las vegas , nevada , usa .', 'tostr': 'filter_eq { all_rows ; location ; las vegas , nevada , usa }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; location ; las vegas , nevada , usa } }', 'tointer': 'select the rows whose location record fuzzily matches to las vegas , nevada , usa . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; location ; las vegas , nevada , usa } } ; 3 } = true', 'tointer': 'select the rows whose location record fuzzily matches to las vegas , nevada , usa . the number of such rows is 3 .'}
|
eq { count { filter_eq { all_rows ; location ; las vegas , nevada , usa } } ; 3 } = true
|
select the rows whose location record fuzzily matches to las vegas , nevada , usa . the number of such rows is 3 .
|
3
|
3
|
{'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'location_5': 5, 'las vegas , nevada , usa_6': 6, '3_7': 7}
|
{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'location_5': 'location', 'las vegas , nevada , usa_6': 'las vegas , nevada , usa', '3_7': '3'}
|
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'location_5': [0], 'las vegas , nevada , usa_6': [0], '3_7': [2]}
|
['date', 'result', 'opponent', 'location', 'method']
|
[['2013 - 04 - 27', 'win', 'martinis knyzelis', 'vilnius , lithuania', 'decision'], ['2007 - 06 - 25', 'loss', 'björn bregy', 'amsterdam , netherlands', 'decision ( unanimous )'], ['2007 - 05 - 04', 'win', 'paula mataele', 'bucharest , romania', 'ko ( straight punch )'], ['2007 - 05 - 04', 'win', 'errol zimmerman', 'bucharest , romania', 'decision ( majority )'], ['2007 - 05 - 04', 'win', 'doug viney', 'bucharest , romania', 'ko ( left roundhouse kick )'], ['2007 - 04 - 07', 'loss', 'errol zimmerman', 'tilburg , netherlands', 'decision'], ['2006 - 03 - 26', 'loss', 'lloyd van dams', 'tilburg , netherlands', 'decision ( unanimous )'], ['2005 - 10 - 02', 'loss', 'alexander ustinov', 'arnhem , netherlands', 'ko'], ['2005 - 09 - 16', 'loss', 'daniel ghiță', 'cluj - napoca , romania', 'decision ( unanimous )'], ['2005 - 02 - 05', 'win', 'alexander ustinov', 'romania', 'decision'], ['2004 - 11 - 12', 'win', 'aziz khattou', '-', 'decision ( unanimous )'], ['2004 - 11 - 04', 'draw', 'cătălin zmărăndescu', 'brașov , romania', 'decision'], ['2004 - 08 - 07', 'loss', 'mighty mo', 'las vegas , nevada , usa', 'ko ( right overhand )'], ['2004 - 08 - 07', 'win', 'jörgen kruth', 'las vegas , nevada , usa', 'decision ( unanimous )'], ['2004 - 08 - 07', 'win', 'carter williams', 'las vegas , nevada , usa', 'ko ( high kick )'], ['2004 - 02 - 14', 'win', 'rickard nordstrand', 'stockholm , sweden', 'tko ( corner stoppage )'], ['2004 - 02 - 14', 'win', 'petri reima', 'stockholm , sweden', 'decision ( majority )'], ['2004 - 02 - 14', 'win', 'johan mparmpagiannis', 'stockholm , sweden', 'tko ( fighter gave up )'], ['2003 - 04 - 06', 'win', 'jörgen kruth', 'zoetermeer , netherlands', 'extr decision ( majority )']]
|
czech republic at the 2008 summer olympics
|
https://en.wikipedia.org/wiki/Czech_Republic_at_the_2008_Summer_Olympics
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-17289604-38.html.csv
|
unique
|
iveta benešová nicole vaidišová was the only person representing the czech republic in doubles in the 2008 olympics .
|
{'scope': 'all', 'row': '5', 'col': '2', 'col_other': '1', 'criterion': 'equal', 'value': 'doubles', 'subset': None}
|
{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'event', 'doubles'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose event record fuzzily matches to doubles .', 'tostr': 'filter_eq { all_rows ; event ; doubles }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; event ; doubles } }', 'tointer': 'select the rows whose event record fuzzily matches to doubles . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'event', 'doubles'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose event record fuzzily matches to doubles .', 'tostr': 'filter_eq { all_rows ; event ; doubles }'}, 'athlete'], 'result': 'iveta benešová nicole vaidišová', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; event ; doubles } ; athlete }'}, 'iveta benešová nicole vaidišová'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; event ; doubles } ; athlete } ; iveta benešová nicole vaidišová }', 'tointer': 'the athlete record of this unqiue row is iveta benešová nicole vaidišová .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; event ; doubles } } ; eq { hop { filter_eq { all_rows ; event ; doubles } ; athlete } ; iveta benešová nicole vaidišová } } = true', 'tointer': 'select the rows whose event record fuzzily matches to doubles . there is only one such row in the table . the athlete record of this unqiue row is iveta benešová nicole vaidišová .'}
|
and { only { filter_eq { all_rows ; event ; doubles } } ; eq { hop { filter_eq { all_rows ; event ; doubles } ; athlete } ; iveta benešová nicole vaidišová } } = true
|
select the rows whose event record fuzzily matches to doubles . there is only one such row in the table . the athlete record of this unqiue row is iveta benešová nicole vaidišová .
|
6
|
5
|
{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'event_7': 7, 'doubles_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'athlete_9': 9, 'iveta benešová nicole vaidišová_10': 10}
|
{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'event_7': 'event', 'doubles_8': 'doubles', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'athlete_9': 'athlete', 'iveta benešová nicole vaidišová_10': 'iveta benešová nicole vaidišová'}
|
{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'event_7': [0], 'doubles_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'athlete_9': [2], 'iveta benešová nicole vaidišová_10': [3]}
|
['athlete', 'event', 'round of 64', 'round of 32', 'round of 16', 'quarterfinals']
|
[['iveta benešová', 'singles', 'mirza ( ind ) w 6 - 2 , 2 - 1 r', 'v williams ( usa ) l 1 - 6 , 4 - 6', 'did not advance', 'did not advance'], ['lucie šafářová', 'singles', 'ani ( est ) w 6 - 4 , 6 - 2', 'koryttseva ( ukr ) w 2 - 6 , 6 - 1 , 7 - 5', 'bammer ( aut ) l 5 - 7 , 4 - 6', 'did not advance'], ['nicole vaidišová', 'singles', 'cornet ( fra ) l 6 - 4 , 1 - 6 , 4 - 6', 'did not advance', 'did not advance', 'did not advance'], ['klára zakopalová', 'singles', 'llagostera vives ( esp ) l 6 - 2 , 3 - 6 , 5 - 7', 'did not advance', 'did not advance', 'did not advance'], ['iveta benešová nicole vaidišová', 'doubles', 'n / a', 's williams / v williams ( usa ) l 6 - 4 , 5 - 7 , 1 - 6', 'did not advance', 'did not advance']]
|
list of tallest buildings in nashville
|
https://en.wikipedia.org/wiki/List_of_tallest_buildings_in_Nashville
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12169960-1.html.csv
|
superlative
|
at & t building has the most floors among the buildings in nashville .
|
{'scope': 'all', 'col_superlative': '4', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '2', 'subset': None}
|
{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'floors'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; floors }'}, 'name'], 'result': 'at & t building', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; floors } ; name }'}, 'at & t building'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; floors } ; name } ; at & t building } = true', 'tointer': 'select the row whose floors record of all rows is maximum . the name record of this row is at & t building .'}
|
eq { hop { argmax { all_rows ; floors } ; name } ; at & t building } = true
|
select the row whose floors record of all rows is maximum . the name record of this row is at & t building .
|
3
|
3
|
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'floors_5': 5, 'name_6': 6, 'at&t building_7': 7}
|
{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'floors_5': 'floors', 'name_6': 'name', 'at&t building_7': 'at & t building'}
|
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'floors_5': [0], 'name_6': [1], 'at&t building_7': [2]}
|
['rank', 'name', 'height ft ( m )', 'floors', 'year']
|
[['1', 'at & t building', '617 ( 188 )', '33', '1994'], ['2', 'fifth third center', '490 ( 149 )', '31', '1986'], ['3', 'william r snodgrass tennessee tower', '452 ( 138 )', '31', '1970'], ['4', 'pinnacle at symphony place', '417 ( 127 )', '28', '2010'], ['5', 'life and casualty tower', '409 ( 125 )', '30', '1957'], ['6', 'nashville city center', '402 ( 123 )', '27', '1988'], ['7', 'james k polk state office building', '392 ( 119 )', '24', '1981'], ['8', 'renaissance nashville hotel', '385 ( 117 )', '31', '1987'], ['9', 'viridian tower', '378 ( 115 )', '31', '2006'], ['10', 'one nashville place', '359 ( 109 )', '25', '1985'], ['11', 'regions center', '354 ( 108 )', '28', '1974'], ['12', 'sheraton nashville downtown', '300 ( 91 )', '27', '1975'], ['13', 'suntrust building', '292 ( 89 )', '20', '1967'], ['14', 'bank of america plaza', '292 ( 89 )', '20', '1977'], ['15', 'andrew jackson state office building', '286 ( 87 )', '17', '1969'], ['16', 'omni nashville hotel', '280 ( 85 )', '23', '2013'], ['17', 'palmer plaza', '269 ( 82 )', '18', '1986'], ['18', 'parkway towers', '261 ( 80 )', '21', '1968']]
|
1992 citizen cup
|
https://en.wikipedia.org/wiki/1992_Citizen_Cup
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11002159-1.html.csv
|
unique
|
in the 1992 citizen cup , when the syndicate is america 3 foundation , the only time the yacht is kanza is when the sail is usa - 28 .
|
{'scope': 'subset', 'row': '4', 'col': '2', 'col_other': '1,3', 'criterion': 'equal', 'value': 'kanza', 'subset': {'col': '3', 'criterion': 'equal', 'value': 'america 3 foundation'}}
|
{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'syndicate', 'america 3 foundation'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; syndicate ; america 3 foundation }', 'tointer': 'select the rows whose syndicate record fuzzily matches to america 3 foundation .'}, 'yacht', 'kanza'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose syndicate record fuzzily matches to america 3 foundation . among these rows , select the rows whose yacht record fuzzily matches to kanza .', 'tostr': 'filter_eq { filter_eq { all_rows ; syndicate ; america 3 foundation } ; yacht ; kanza }'}], 'result': True, 'ind': 2, 'tostr': 'only { filter_eq { filter_eq { all_rows ; syndicate ; america 3 foundation } ; yacht ; kanza } }', 'tointer': 'select the rows whose syndicate record fuzzily matches to america 3 foundation . among these rows , select the rows whose yacht record fuzzily matches to kanza . 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', 'syndicate', 'america 3 foundation'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; syndicate ; america 3 foundation }', 'tointer': 'select the rows whose syndicate record fuzzily matches to america 3 foundation .'}, 'yacht', 'kanza'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose syndicate record fuzzily matches to america 3 foundation . among these rows , select the rows whose yacht record fuzzily matches to kanza .', 'tostr': 'filter_eq { filter_eq { all_rows ; syndicate ; america 3 foundation } ; yacht ; kanza }'}, 'sail'], 'result': 'usa - 28', 'ind': 3, 'tostr': 'hop { filter_eq { filter_eq { all_rows ; syndicate ; america 3 foundation } ; yacht ; kanza } ; sail }'}, 'usa - 28'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { filter_eq { filter_eq { all_rows ; syndicate ; america 3 foundation } ; yacht ; kanza } ; sail } ; usa - 28 }', 'tointer': 'the sail record of this unqiue row is usa - 28 .'}], 'result': True, 'ind': 5, 'tostr': 'and { only { filter_eq { filter_eq { all_rows ; syndicate ; america 3 foundation } ; yacht ; kanza } } ; eq { hop { filter_eq { filter_eq { all_rows ; syndicate ; america 3 foundation } ; yacht ; kanza } ; sail } ; usa - 28 } } = true', 'tointer': 'select the rows whose syndicate record fuzzily matches to america 3 foundation . among these rows , select the rows whose yacht record fuzzily matches to kanza . there is only one such row in the table . the sail record of this unqiue row is usa - 28 .'}
|
and { only { filter_eq { filter_eq { all_rows ; syndicate ; america 3 foundation } ; yacht ; kanza } } ; eq { hop { filter_eq { filter_eq { all_rows ; syndicate ; america 3 foundation } ; yacht ; kanza } ; sail } ; usa - 28 } } = true
|
select the rows whose syndicate record fuzzily matches to america 3 foundation . among these rows , select the rows whose yacht record fuzzily matches to kanza . there is only one such row in the table . the sail record of this unqiue row is usa - 28 .
|
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, 'syndicate_8': 8, 'america 3 foundation_9': 9, 'yacht_10': 10, 'kanza_11': 11, 'str_eq_4': 4, 'str_hop_3': 3, 'sail_12': 12, 'usa - 28_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', 'syndicate_8': 'syndicate', 'america 3 foundation_9': 'america 3 foundation', 'yacht_10': 'yacht', 'kanza_11': 'kanza', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'sail_12': 'sail', 'usa - 28_13': 'usa - 28'}
|
{'and_5': [6], 'result_6': [], 'only_2': [5], 'filter_str_eq_1': [2, 3], 'filter_str_eq_0': [1], 'all_rows_7': [0], 'syndicate_8': [0], 'america 3 foundation_9': [0], 'yacht_10': [1], 'kanza_11': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'sail_12': [3], 'usa - 28_13': [4]}
|
['sail', 'yacht', 'syndicate', 'yacht club', 'nation']
|
[['usa - 9', 'jayhawk', 'america 3 foundation', 'san diego yacht club', 'united states'], ['usa - 18', 'defiant', 'america 3 foundation', 'san diego yacht club', 'united states'], ['usa - 23', 'america 3', 'america 3 foundation', 'san diego yacht club', 'united states'], ['usa - 28', 'kanza', 'america 3 foundation', 'san diego yacht club', 'united states'], ['usa - 11', 'stars & stripes', 'team dennis conner', 'san diego yacht club', 'united states']]
|
ohio river valley conference
|
https://en.wikipedia.org/wiki/Ohio_River_Valley_Conference
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18717975-2.html.csv
|
count
|
four schools joined the ohio river valley conference in 1953 .
|
{'scope': 'all', 'criterion': 'equal', 'value': '1953', 'result': '4', 'col': '5', 'subset': None}
|
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'year joined', '1953'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose year joined record is equal to 1953 .', 'tostr': 'filter_eq { all_rows ; year joined ; 1953 }'}], 'result': '4', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; year joined ; 1953 } }', 'tointer': 'select the rows whose year joined record is equal to 1953 . the number of such rows is 4 .'}, '4'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; year joined ; 1953 } } ; 4 } = true', 'tointer': 'select the rows whose year joined record is equal to 1953 . the number of such rows is 4 .'}
|
eq { count { filter_eq { all_rows ; year joined ; 1953 } } ; 4 } = true
|
select the rows whose year joined record is equal to 1953 . 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, 'year joined_5': 5, '1953_6': 6, '4_7': 7}
|
{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'year joined_5': 'year joined', '1953_6': '1953', '4_7': '4'}
|
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'year joined_5': [0], '1953_6': [0], '4_7': [2]}
|
['school', 'location', 'mascot', 'county', 'year joined', 'year left', 'conference joined']
|
[['hanover', 'hanover', 'bulldogs', '39 jefferson', '1952', '1960', 'none ( consolidated into southwestern )'], ['north ( madison )', 'madison', 'tigers', '39 jefferson', '1952', '1953', 'none ( colsolidated into madison )'], ['osgood', 'osgood', 'cowboys', '69 ripley', '1952', '1960', 'none ( consolidated into jac - cen - del )'], ['versailles', 'versailles', 'lions', '69 ripley', '1952', '1966', 'none ( consolidated into south ripley )'], ['dillsboro', 'dillsboro', 'bulldogs', '15 dearborn', '1953', '1978', 'none ( consolidated into south dearborn )'], ['moores hill', 'moores hill', 'knights', '15 dearborn', '1953', '1978', 'none ( consolidated into south dearborn )'], ['sunman', 'sunman', 'trojans', '69 ripley', '1953', '1973', 'none ( consolidated into east central )'], ['vevay', 'vevay', 'warriors', '78 switzerland', '1953', '1968', 'none ( consolidated into switzerland county )']]
|
kairat nurdauletov
|
https://en.wikipedia.org/wiki/Kairat_Nurdauletov
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12706952-1.html.csv
|
unique
|
on 8 september 2007 , kairat nurdauletov recorded the only draw result .
|
{'scope': 'all', 'row': '1', 'col': '4', 'col_other': '1', 'criterion': 'equal', 'value': 'draw', 'subset': None}
|
{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'result', 'draw'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose result record fuzzily matches to draw .', 'tostr': 'filter_eq { all_rows ; result ; draw }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; result ; draw } }', 'tointer': 'select the rows whose result record fuzzily matches to draw . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'result', 'draw'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose result record fuzzily matches to draw .', 'tostr': 'filter_eq { all_rows ; result ; draw }'}, 'date'], 'result': '8 september 2007', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; result ; draw } ; date }'}, '8 september 2007'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; result ; draw } ; date } ; 8 september 2007 }', 'tointer': 'the date record of this unqiue row is 8 september 2007 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; result ; draw } } ; eq { hop { filter_eq { all_rows ; result ; draw } ; date } ; 8 september 2007 } } = true', 'tointer': 'select the rows whose result record fuzzily matches to draw . there is only one such row in the table . the date record of this unqiue row is 8 september 2007 .'}
|
and { only { filter_eq { all_rows ; result ; draw } } ; eq { hop { filter_eq { all_rows ; result ; draw } ; date } ; 8 september 2007 } } = true
|
select the rows whose result record fuzzily matches to draw . there is only one such row in the table . the date record of this unqiue row is 8 september 2007 .
|
6
|
5
|
{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'result_7': 7, 'draw_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'date_9': 9, '8 september 2007_10': 10}
|
{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'result_7': 'result', 'draw_8': 'draw', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'date_9': 'date', '8 september 2007_10': '8 september 2007'}
|
{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'result_7': [0], 'draw_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'date_9': [2], '8 september 2007_10': [3]}
|
['date', 'venue', 'score', 'result', 'competition']
|
[['8 september 2007', 'central stadium , almaty , kazakhstan', '1 - 1', 'draw', 'friendly'], ['7 october 2011', 'king baudouin stadium , almaty , kazakhstan', '4 - 1', 'lost', 'friendly'], ['1 june 2012', 'central stadium , almaty , kazakhstan', '5 - 2', 'win', 'friendly'], ['7 september 2012', 'astana arena , astana , kazakhstan', '1 - 2', 'loss', 'world cup 2014 qualilfier'], ['6 september 2013', 'astana arena , astana , kazakhstan', '2 - 1', 'win', 'world cup 2014 qualilfier']]
|
somerset county cricket club in 2010
|
https://en.wikipedia.org/wiki/Somerset_County_Cricket_Club_in_2010
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-28846752-4.html.csv
|
aggregation
|
all somerset cricket club team members played an average of 22 innings .
|
{'scope': 'all', 'col': '3', 'type': 'average', 'result': '22', 'subset': None}
|
{'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'innings'], 'result': '22', 'ind': 0, 'tostr': 'avg { all_rows ; innings }'}, '22'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; innings } ; 22 } = true', 'tointer': 'the average of the innings record of all rows is 22 .'}
|
round_eq { avg { all_rows ; innings } ; 22 } = true
|
the average of the innings record of all rows is 22 .
|
2
|
2
|
{'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'innings_4': 4, '22_5': 5}
|
{'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'innings_4': 'innings', '22_5': '22'}
|
{'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'innings_4': [0], '22_5': [1]}
|
['player', 'matches', 'innings', 'runs', 'average', 'highest score', '100s', '50s']
|
[['james hildreth', '16', '23', '1440', '65.45', '151', '7', '5'], ['marcus trescothick', '16', '28', '1397', '58.20', '228', '4', '6'], ['zander de bruyn', '14', '21', '814', '38.76', '95', '0', '5'], ['arul suppiah', '16', '26', '771', '33.52', '125', '1', '4'], ['jos buttler', '13', '20', '569', '33.47', '144', '1', '2'], ['nick compton', '11', '17', '465', '33.21', '72', '0', '2'], ['peter trego', '16', '23', '693', '33.00', '108', '1', '5'], ['craig kieswetter', '12', '18', '467', '27.47', '84', '0', '4']]
|
list of nuclear weapons tests
|
https://en.wikipedia.org/wiki/List_of_nuclear_weapons_tests
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2189647-1.html.csv
|
superlative
|
the biggest nuclear weapons test yield between 1952 and 1962 was 50 megatons .
|
{'scope': 'all', 'col_superlative': '2', 'row_superlative': '1', 'value_mentioned': 'yes', 'max_or_min': 'max', 'other_col': '1', 'subset': None}
|
{'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'max', 'args': ['all_rows', 'yield ( megatons )'], 'result': '50', 'ind': 0, 'tostr': 'max { all_rows ; yield ( megatons ) }', 'tointer': 'the maximum yield ( megatons ) record of all rows is 50 .'}, '50'], 'result': True, 'ind': 1, 'tostr': 'eq { max { all_rows ; yield ( megatons ) } ; 50 }', 'tointer': 'the maximum yield ( megatons ) record of all rows is 50 .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'yield ( megatons )'], 'result': None, 'ind': 2, 'tostr': 'argmax { all_rows ; yield ( megatons ) }'}, 'date ( gmt )'], 'result': 'october 30 , 1961', 'ind': 3, 'tostr': 'hop { argmax { all_rows ; yield ( megatons ) } ; date ( gmt ) }'}, 'october 30 , 1961'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { argmax { all_rows ; yield ( megatons ) } ; date ( gmt ) } ; october 30 , 1961 }', 'tointer': 'the date ( gmt ) record of the row with superlative yield ( megatons ) record is october 30 , 1961 .'}], 'result': True, 'ind': 5, 'tostr': 'and { eq { max { all_rows ; yield ( megatons ) } ; 50 } ; eq { hop { argmax { all_rows ; yield ( megatons ) } ; date ( gmt ) } ; october 30 , 1961 } } = true', 'tointer': 'the maximum yield ( megatons ) record of all rows is 50 . the date ( gmt ) record of the row with superlative yield ( megatons ) record is october 30 , 1961 .'}
|
and { eq { max { all_rows ; yield ( megatons ) } ; 50 } ; eq { hop { argmax { all_rows ; yield ( megatons ) } ; date ( gmt ) } ; october 30 , 1961 } } = true
|
the maximum yield ( megatons ) record of all rows is 50 . the date ( gmt ) record of the row with superlative yield ( megatons ) record is october 30 , 1961 .
|
6
|
6
|
{'and_5': 5, 'result_6': 6, 'eq_1': 1, 'max_0': 0, 'all_rows_7': 7, 'yield (megatons)_8': 8, '50_9': 9, 'str_eq_4': 4, 'str_hop_3': 3, 'argmax_2': 2, 'all_rows_10': 10, 'yield (megatons)_11': 11, 'date (gmt)_12': 12, 'october 30 , 1961_13': 13}
|
{'and_5': 'and', 'result_6': 'true', 'eq_1': 'eq', 'max_0': 'max', 'all_rows_7': 'all_rows', 'yield (megatons)_8': 'yield ( megatons )', '50_9': '50', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'argmax_2': 'argmax', 'all_rows_10': 'all_rows', 'yield (megatons)_11': 'yield ( megatons )', 'date (gmt)_12': 'date ( gmt )', 'october 30 , 1961_13': 'october 30 , 1961'}
|
{'and_5': [6], 'result_6': [], 'eq_1': [5], 'max_0': [1], 'all_rows_7': [0], 'yield (megatons)_8': [0], '50_9': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'argmax_2': [3], 'all_rows_10': [2], 'yield (megatons)_11': [2], 'date (gmt)_12': [3], 'october 30 , 1961_13': [4]}
|
['date ( gmt )', 'yield ( megatons )', 'deployment', 'country', 'test site', 'name or number']
|
[['october 30 , 1961', '50', 'parachute air drop', 'soviet union', 'novaya zemlya', 'tsar bomba , test 130'], ['december 24 , 1962', '24.2', 'air drop', 'soviet union', 'novaya zemlya', 'test 219'], ['august 5 , 1962', '21.1', 'air drop', 'soviet union', 'novaya zemlya', 'test 147'], ['september 27 , 1962', '20.0', 'air drop', 'soviet union', 'novaya zemlya', 'test 174'], ['september 25 , 1962', '19.1', 'air drop', 'soviet union', 'novaya zemlya', 'test 173'], ['february 28 , 1954', '15', 'ground', 'usa', 'bikini atoll', 'castle bravo'], ['may 4 , 1954', '13.5', 'barge', 'usa', 'bikini atoll', 'castle yankee'], ['october 23 , 1961', '12.5', 'air drop', 'soviet union', 'novaya zemlya', 'test 123'], ['march 26 , 1954', '11.0', 'barge', 'usa', 'bikini atoll', 'castle romeo'], ['october 31 , 1952', '10.4', 'ground', 'usa', 'eniwetok', 'ivy mike'], ['august 25 , 1962', '10.0', 'air drop', 'soviet union', 'novaya zemlya', 'test 158']]
|
1952 vfl season
|
https://en.wikipedia.org/wiki/1952_VFL_season
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10750694-19.html.csv
|
count
|
a total of 6 games were played on the day of 30 august 1952 .
|
{'scope': 'all', 'criterion': 'equal', 'value': '30 august 1952', 'result': '6', 'col': '7', 'subset': None}
|
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', '30 august 1952'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose date record fuzzily matches to 30 august 1952 .', 'tostr': 'filter_eq { all_rows ; date ; 30 august 1952 }'}], 'result': '6', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; date ; 30 august 1952 } }', 'tointer': 'select the rows whose date record fuzzily matches to 30 august 1952 . the number of such rows is 6 .'}, '6'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; date ; 30 august 1952 } } ; 6 } = true', 'tointer': 'select the rows whose date record fuzzily matches to 30 august 1952 . the number of such rows is 6 .'}
|
eq { count { filter_eq { all_rows ; date ; 30 august 1952 } } ; 6 } = true
|
select the rows whose date record fuzzily matches to 30 august 1952 . 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, 'date_5': 5, '30 august 1952_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', 'date_5': 'date', '30 august 1952_6': '30 august 1952', '6_7': '6'}
|
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'date_5': [0], '30 august 1952_6': [0], '6_7': [2]}
|
['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date']
|
[['hawthorn', '8.11 ( 59 )', 'north melbourne', '12.10 ( 82 )', 'glenferrie oval', '6000', '30 august 1952'], ['footscray', '13.13 ( 91 )', 'south melbourne', '8.13 ( 61 )', 'western oval', '20723', '30 august 1952'], ['collingwood', '13.14 ( 92 )', 'melbourne', '10.11 ( 71 )', 'victoria park', '18753', '30 august 1952'], ['st kilda', '10.12 ( 72 )', 'fitzroy', '8.18 ( 66 )', 'junction oval', '9000', '30 august 1952'], ['richmond', '15.11 ( 101 )', 'essendon', '11.10 ( 76 )', 'punt road oval', '28000', '30 august 1952'], ['geelong', '10.17 ( 77 )', 'carlton', '3.14 ( 32 )', 'kardinia park', '49107', '30 august 1952']]
|
1972 u.s. open ( golf )
|
https://en.wikipedia.org/wiki/1972_U.S._Open_%28golf%29
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17245554-3.html.csv
|
count
|
11 players in the 1972 u.s. open were from the united states .
|
{'scope': 'all', 'criterion': 'equal', 'value': 'united states', 'result': '11', 'col': '3', 'subset': None}
|
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'united states'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose country record fuzzily matches to united states .', 'tostr': 'filter_eq { all_rows ; country ; united states }'}], 'result': '11', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; country ; united states } }', 'tointer': 'select the rows whose country record fuzzily matches to united states . the number of such rows is 11 .'}, '11'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; country ; united states } } ; 11 } = true', 'tointer': 'select the rows whose country record fuzzily matches to united states . the number of such rows is 11 .'}
|
eq { count { filter_eq { all_rows ; country ; united states } } ; 11 } = true
|
select the rows whose country record fuzzily matches to united states . the number of such rows is 11 .
|
3
|
3
|
{'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'country_5': 5, 'united states_6': 6, '11_7': 7}
|
{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'country_5': 'country', 'united states_6': 'united states', '11_7': '11'}
|
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'country_5': [0], 'united states_6': [0], '11_7': [2]}
|
['place', 'player', 'country', 'score', 'to par']
|
[['t1', 'jack nicklaus', 'united states', '71 + 73 = 144', 'e'], ['t1', 'bruce crampton', 'australia', '74 + 70 = 144', 'e'], ['t1', 'kermit zarley', 'united states', '71 + 73 = 144', 'e'], ['t1', 'lanny wadkins', 'united states', '76 + 68 = 144', 'e'], ['t1', 'homero blancas', 'united states', '74 + 70 = 144', 'e'], ['t1', 'cesar sanudo', 'united states', '72 + 72 = 144', 'e'], ['7', 'arnold palmer', 'united states', '77 + 68 = 145', '+ 1'], ['t8', 'lee trevino', 'united states', '74 + 72 = 146', '+ 2'], ['t8', 'lee elder', 'united states', '75 + 71 = 146', '+ 2'], ['t8', 'ralph johnston', 'united states', '74 + 72 = 146', '+ 2'], ['t8', 'rod funseth', 'united states', '73 + 73 = 146', '+ 2'], ['t8', 'gary player', 'south africa', '72 + 74 = 146', '+ 2'], ['t8', 'chi - chi rodrã\xadguez', 'united states', '71 + 75 = 146', '+ 2']]
|
1926 european aquatics championships
|
https://en.wikipedia.org/wiki/1926_European_Aquatics_Championships
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10636637-1.html.csv
|
superlative
|
germany received the most gold medals during the 1926 european aquatics championships .
|
{'scope': 'all', 'col_superlative': '3', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '2', 'subset': None}
|
{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'gold'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; gold }'}, 'nation'], 'result': 'germany', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; gold } ; nation }'}, 'germany'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; gold } ; nation } ; germany } = true', 'tointer': 'select the row whose gold record of all rows is maximum . the nation record of this row is germany .'}
|
eq { hop { argmax { all_rows ; gold } ; nation } ; germany } = true
|
select the row whose gold record of all rows is maximum . the nation record of this row is germany .
|
3
|
3
|
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'gold_5': 5, 'nation_6': 6, 'germany_7': 7}
|
{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'gold_5': 'gold', 'nation_6': 'nation', 'germany_7': 'germany'}
|
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'gold_5': [0], 'nation_6': [1], 'germany_7': [2]}
|
['rank', 'nation', 'gold', 'silver', 'bronze', 'total']
|
[['1', 'germany', '5', '3', '4', '12'], ['2', 'sweden', '2', '3', '3', '9'], ['3', 'hungary', '2', '2', '0', '4'], ['4', 'belgium', '0', '1', '0', '1'], ['5', 'czechoslovakia', '0', '0', '1', '1'], ['5', 'great britain', '0', '0', '1', '1'], ['total', 'total', '9', '9', '9', '27']]
|
heartland collegiate athletic conference
|
https://en.wikipedia.org/wiki/Heartland_Collegiate_Athletic_Conference
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-255205-1.html.csv
|
unique
|
in the heartland collegiate athletic conference , anderson university is the only institution with an enrollment of over 3000 .
|
{'scope': 'all', 'row': '1', 'col': '6', 'col_other': '1', 'criterion': 'greater_than', 'value': '3000', 'subset': None}
|
{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'enrollment', '3000'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose enrollment record is greater than 3000 .', 'tostr': 'filter_greater { all_rows ; enrollment ; 3000 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_greater { all_rows ; enrollment ; 3000 } }', 'tointer': 'select the rows whose enrollment record is greater than 3000 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'enrollment', '3000'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose enrollment record is greater than 3000 .', 'tostr': 'filter_greater { all_rows ; enrollment ; 3000 }'}, 'institution'], 'result': 'anderson university', 'ind': 2, 'tostr': 'hop { filter_greater { all_rows ; enrollment ; 3000 } ; institution }'}, 'anderson university'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_greater { all_rows ; enrollment ; 3000 } ; institution } ; anderson university }', 'tointer': 'the institution record of this unqiue row is anderson university .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_greater { all_rows ; enrollment ; 3000 } } ; eq { hop { filter_greater { all_rows ; enrollment ; 3000 } ; institution } ; anderson university } } = true', 'tointer': 'select the rows whose enrollment record is greater than 3000 . there is only one such row in the table . the institution record of this unqiue row is anderson university .'}
|
and { only { filter_greater { all_rows ; enrollment ; 3000 } } ; eq { hop { filter_greater { all_rows ; enrollment ; 3000 } ; institution } ; anderson university } } = true
|
select the rows whose enrollment record is greater than 3000 . there is only one such row in the table . the institution record of this unqiue row is anderson university .
|
6
|
5
|
{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_greater_0': 0, 'all_rows_6': 6, 'enrollment_7': 7, '3000_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'institution_9': 9, 'anderson university_10': 10}
|
{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_greater_0': 'filter_greater', 'all_rows_6': 'all_rows', 'enrollment_7': 'enrollment', '3000_8': '3000', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'institution_9': 'institution', 'anderson university_10': 'anderson university'}
|
{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_greater_0': [1, 2], 'all_rows_6': [0], 'enrollment_7': [0], '3000_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'institution_9': [2], 'anderson university_10': [3]}
|
['institution', 'location', 'nickname', 'founded', 'type', 'enrollment', 'joined']
|
[['anderson university', 'anderson , indiana', 'ravens', '1917', 'private / church of god', '3065', '1987'], ['bluffton university', 'bluffton , ohio', 'beavers', '1899', 'private / mennonite', '1191', '1998'], ['college of mount st joseph', 'cincinnati , ohio', 'lions', '1920', 'private / catholic', '2259', '1998'], ['defiance college', 'defiance , ohio', 'yellow jackets', '1850', 'private / united church of christ', '1000', '2000'], ['earlham college', 'richmond , indiana', 'quakers', '1847', 'private / quaker', '1194', '2010'], ['franklin college', 'franklin , indiana', 'grizzlies', '1834', 'private / baptist', '1000', '1987'], ['hanover college', 'hanover , indiana', 'panthers', '1827', 'private / presbyterian', '1062', '1987'], ['manchester university', 'north manchester , indiana', 'spartans', '1860', 'private / church of the brethren', '1250', '1987'], ['rose - hulman institute of technology', 'terre haute , indiana', "fightin ' engineers", '1874', 'private / non - sectarian', '1970', '1988 1']]
|
satoru nakajima
|
https://en.wikipedia.org/wiki/Satoru_Nakajima
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1226566-2.html.csv
|
unique
|
1989 was the only year that satoru nakajima drove with a judd v8 type engine .
|
{'scope': 'all', 'row': '3', 'col': '4', 'col_other': '1', 'criterion': 'equal', 'value': 'judd v8', 'subset': None}
|
{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'engine', 'judd v8'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose engine record fuzzily matches to judd v8 .', 'tostr': 'filter_eq { all_rows ; engine ; judd v8 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; engine ; judd v8 } }', 'tointer': 'select the rows whose engine record fuzzily matches to judd v8 . there is only one such row in the table .'}, {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'engine', 'judd v8'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose engine record fuzzily matches to judd v8 .', 'tostr': 'filter_eq { all_rows ; engine ; judd v8 }'}, 'year'], 'result': '1989', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; engine ; judd v8 } ; year }'}, '1989'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; engine ; judd v8 } ; year } ; 1989 }', 'tointer': 'the year record of this unqiue row is 1989 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; engine ; judd v8 } } ; eq { hop { filter_eq { all_rows ; engine ; judd v8 } ; year } ; 1989 } } = true', 'tointer': 'select the rows whose engine record fuzzily matches to judd v8 . there is only one such row in the table . the year record of this unqiue row is 1989 .'}
|
and { only { filter_eq { all_rows ; engine ; judd v8 } } ; eq { hop { filter_eq { all_rows ; engine ; judd v8 } ; year } ; 1989 } } = true
|
select the rows whose engine record fuzzily matches to judd v8 . there is only one such row in the table . the year record of this unqiue row is 1989 .
|
6
|
5
|
{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'engine_7': 7, 'judd v8_8': 8, 'eq_3': 3, 'num_hop_2': 2, 'year_9': 9, '1989_10': 10}
|
{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'engine_7': 'engine', 'judd v8_8': 'judd v8', 'eq_3': 'eq', 'num_hop_2': 'num_hop', 'year_9': 'year', '1989_10': '1989'}
|
{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'engine_7': [0], 'judd v8_8': [0], 'eq_3': [4], 'num_hop_2': [3], 'year_9': [2], '1989_10': [3]}
|
['year', 'entrant', 'chassis', 'engine', 'points']
|
[['1987', 'camel team lotus honda', 'lotus 99t', 'honda v6', '7'], ['1988', 'camel team lotus honda', 'lotus 100t', 'honda v6', '1'], ['1989', 'camel team lotus', 'lotus 101', 'judd v8', '3'], ['1990', 'tyrrell racing organisation', 'tyrrell 018', 'cosworth v8', '3'], ['1990', 'tyrrell racing organisation', 'tyrrell 019', 'cosworth v8', '3'], ['1991', 'braun tyrrell honda', 'tyrrell 020', 'honda v10', '2']]
|
2001 ansett australia cup
|
https://en.wikipedia.org/wiki/2001_Ansett_Australia_Cup
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-16388439-1.html.csv
|
count
|
during the 2001 ansett australia cup , among the games played at football park , one game had a crowd size of less than 16000 .
|
{'scope': 'subset', 'criterion': 'less_than', 'value': '16000', 'result': '1', 'col': '7', 'subset': {'col': '5', 'criterion': 'equal', 'value': 'football park'}}
|
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_less', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'ground', 'football park'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; ground ; football park }', 'tointer': 'select the rows whose ground record fuzzily matches to football park .'}, 'crowd', '16000'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose ground record fuzzily matches to football park . among these rows , select the rows whose crowd record is less than 16000 .', 'tostr': 'filter_less { filter_eq { all_rows ; ground ; football park } ; crowd ; 16000 }'}], 'result': '1', 'ind': 2, 'tostr': 'count { filter_less { filter_eq { all_rows ; ground ; football park } ; crowd ; 16000 } }', 'tointer': 'select the rows whose ground record fuzzily matches to football park . among these rows , select the rows whose crowd record is less than 16000 . the number of such rows is 1 .'}, '1'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_less { filter_eq { all_rows ; ground ; football park } ; crowd ; 16000 } } ; 1 } = true', 'tointer': 'select the rows whose ground record fuzzily matches to football park . among these rows , select the rows whose crowd record is less than 16000 . the number of such rows is 1 .'}
|
eq { count { filter_less { filter_eq { all_rows ; ground ; football park } ; crowd ; 16000 } } ; 1 } = true
|
select the rows whose ground record fuzzily matches to football park . among these rows , select the rows whose crowd record is less than 16000 . the number of such rows is 1 .
|
4
|
4
|
{'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_less_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'ground_6': 6, 'football park_7': 7, 'crowd_8': 8, '16000_9': 9, '1_10': 10}
|
{'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_less_1': 'filter_less', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'ground_6': 'ground', 'football park_7': 'football park', 'crowd_8': 'crowd', '16000_9': '16000', '1_10': '1'}
|
{'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_less_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'ground_6': [0], 'football park_7': [0], 'crowd_8': [1], '16000_9': [1], '1_10': [3]}
|
['home team', 'home team score', 'away team', 'away team score', 'ground', 'date', 'crowd']
|
[['geelong', '4.10 ( 34 )', 'sydney', '6.11 ( 47 )', 'marrara oval', 'friday , 16 february', '8500'], ['port adelaide', '16.25 ( 121 )', 'essendon', '5.12 ( 42 )', 'football park', 'saturday , 17 february', '19498'], ['port adelaide', '17.10 ( 112 )', 'sydney', '15.17 ( 107 )', 'football park', 'friday , 23 february', '15709'], ['essendon', '12.18 ( 90 )', 'geelong', '17.10 ( 112 )', 'colonial stadium', 'friday , 23 february', '22829'], ['geelong', '12.15 ( 87 )', 'port adelaide', '16.9 ( 105 )', 'colonial stadium', 'saturday , 3 march', '4474']]
|
switzerland at the 2008 summer olympics
|
https://en.wikipedia.org/wiki/Switzerland_at_the_2008_Summer_Olympics
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-17085947-32.html.csv
|
ordinal
|
olivier marceau recorded the fastest time in bike ( 40 km ) at the 2008 summer olympics .
|
{'row': '2', 'col': '5', 'order': '1', 'col_other': '1', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None}
|
{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'bike ( 40 km )', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; bike ( 40 km ) ; 1 }'}, 'athlete'], 'result': 'olivier marceau', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; bike ( 40 km ) ; 1 } ; athlete }'}, 'olivier marceau'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; bike ( 40 km ) ; 1 } ; athlete } ; olivier marceau } = true', 'tointer': 'select the row whose bike ( 40 km ) record of all rows is 1st minimum . the athlete record of this row is olivier marceau .'}
|
eq { hop { nth_argmin { all_rows ; bike ( 40 km ) ; 1 } ; athlete } ; olivier marceau } = true
|
select the row whose bike ( 40 km ) record of all rows is 1st minimum . the athlete record of this row is olivier marceau .
|
3
|
3
|
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'bike (40 km)_5': 5, '1_6': 6, 'athlete_7': 7, 'olivier marceau_8': 8}
|
{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmin_0': 'nth_argmin', 'all_rows_4': 'all_rows', 'bike (40 km)_5': 'bike ( 40 km )', '1_6': '1', 'athlete_7': 'athlete', 'olivier marceau_8': 'olivier marceau'}
|
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'bike (40 km)_5': [0], '1_6': [0], 'athlete_7': [1], 'olivier marceau_8': [2]}
|
['athlete', 'event', 'swim ( 1.5 km )', 'trans 1', 'bike ( 40 km )', 'trans 2', 'run ( 10 km )', 'total time', 'rank']
|
[['reto hug', "men 's", '18:55', '0:27', '58:20', '0:29', '33:53', '1:52:04.93', '29'], ['olivier marceau', "men 's", '18:55', '0:29', '58:18', '0:31', '32:37', '1:50:50.07', '19'], ['sven riederer', "men 's", '18:14', '0:34', '58:52', '0:28', '33:11', '1:51:19.45', '23'], ['magali chopard di marco', "women 's", '19:50', '0:30', '1:04:22', '0:29', '36:39', '2:01:50.74', '13'], ['daniela ryf', "women 's", '19:56', '0:26', '1:04:17', '0:30', '35:31', '2:00:40.20', '7']]
|
sabyrkhan ibraev
|
https://en.wikipedia.org/wiki/Sabyrkhan_Ibraev
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18119901-1.html.csv
|
unique
|
the 2010 season is the only season that sabyrkhan ibraev did not score any goals in .
|
{'scope': 'all', 'row': '5', 'col': '7', 'col_other': '1', 'criterion': 'equal', 'value': '0', 'subset': None}
|
{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'goals', '0'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose goals record is equal to 0 .', 'tostr': 'filter_eq { all_rows ; goals ; 0 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; goals ; 0 } }', 'tointer': 'select the rows whose goals record is equal to 0 . there is only one such row in the table .'}, {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'goals', '0'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose goals record is equal to 0 .', 'tostr': 'filter_eq { all_rows ; goals ; 0 }'}, 'season'], 'result': '2010', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; goals ; 0 } ; season }'}, '2010'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; goals ; 0 } ; season } ; 2010 }', 'tointer': 'the season record of this unqiue row is 2010 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; goals ; 0 } } ; eq { hop { filter_eq { all_rows ; goals ; 0 } ; season } ; 2010 } } = true', 'tointer': 'select the rows whose goals record is equal to 0 . there is only one such row in the table . the season record of this unqiue row is 2010 .'}
|
and { only { filter_eq { all_rows ; goals ; 0 } } ; eq { hop { filter_eq { all_rows ; goals ; 0 } ; season } ; 2010 } } = true
|
select the rows whose goals record is equal to 0 . there is only one such row in the table . the season record of this unqiue row is 2010 .
|
6
|
5
|
{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'goals_7': 7, '0_8': 8, 'eq_3': 3, 'num_hop_2': 2, 'season_9': 9, '2010_10': 10}
|
{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'goals_7': 'goals', '0_8': '0', 'eq_3': 'eq', 'num_hop_2': 'num_hop', 'season_9': 'season', '2010_10': '2010'}
|
{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'goals_7': [0], '0_8': [0], 'eq_3': [4], 'num_hop_2': [3], 'season_9': [2], '2010_10': [3]}
|
['season', 'team', 'country', 'league', 'level', 'apps', 'goals']
|
[['2006', 'irtysh', 'kazakhstan', 'premier league', '1', '27', '2'], ['2007', 'irtysh', 'kazakhstan', 'premier league', '1', '17', '1'], ['2008', 'tobol', 'kazakhstan', 'premier league', '1', '25', '3'], ['2009', 'tobol', 'kazakhstan', 'premier league', '1', '22', '1'], ['2010', 'kairat', 'kazakhstan', 'premier league', '1', '15', '0']]
|
list of game of the year awards
|
https://en.wikipedia.org/wiki/List_of_Game_of_the_Year_awards
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1851722-36.html.csv
|
unique
|
super smash bros melee was the only game in the fighting genre to win a game of the year award .
|
{'scope': 'all', 'row': '1', 'col': '3', 'col_other': '2', 'criterion': 'equal', 'value': 'fighting', 'subset': None}
|
{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'genre', 'fighting'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose genre record fuzzily matches to fighting .', 'tostr': 'filter_eq { all_rows ; genre ; fighting }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; genre ; fighting } }', 'tointer': 'select the rows whose genre record fuzzily matches to fighting . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'genre', 'fighting'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose genre record fuzzily matches to fighting .', 'tostr': 'filter_eq { all_rows ; genre ; fighting }'}, 'game'], 'result': 'super smash bros melee', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; genre ; fighting } ; game }'}, 'super smash bros melee'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; genre ; fighting } ; game } ; super smash bros melee }', 'tointer': 'the game record of this unqiue row is super smash bros melee .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; genre ; fighting } } ; eq { hop { filter_eq { all_rows ; genre ; fighting } ; game } ; super smash bros melee } } = true', 'tointer': 'select the rows whose genre record fuzzily matches to fighting . there is only one such row in the table . the game record of this unqiue row is super smash bros melee .'}
|
and { only { filter_eq { all_rows ; genre ; fighting } } ; eq { hop { filter_eq { all_rows ; genre ; fighting } ; game } ; super smash bros melee } } = true
|
select the rows whose genre record fuzzily matches to fighting . there is only one such row in the table . the game record of this unqiue row is super smash bros melee .
|
6
|
5
|
{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'genre_7': 7, 'fighting_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'game_9': 9, 'super smash bros melee_10': 10}
|
{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'genre_7': 'genre', 'fighting_8': 'fighting', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'game_9': 'game', 'super smash bros melee_10': 'super smash bros melee'}
|
{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'genre_7': [0], 'fighting_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'game_9': [2], 'super smash bros melee_10': [3]}
|
['year', 'game', 'genre', 'platform ( s )', 'developer ( s )']
|
[['2001', 'super smash bros melee', 'fighting', 'gamecube', 'hal laboratory , inc'], ['2002', 'metroid prime', '( first - person ) action - adventure', 'gamecube', 'retro studios , nintendo'], ['2003', 'the legend of zelda : wind waker', 'action - adventure', 'gamecube', 'nintendo ead software development group no 3'], ['2004', 'halo 2', '( first - person ) shooter', 'xbox', 'bungie'], ['2005', 'resident evil 4', 'survival horror : ( third - person ) shooter', 'gamecube', 'capcom production studio 4'], ['2006', 'the legend of zelda : twilight princess', 'action - adventure', 'wii , gamecube', 'nintendo ead software development group no 3'], ['2007', 'super mario galaxy', 'platformer', 'wii', 'nintendo ead tokyo development group'], ['2008', 'metal gear solid 4 : guns of the patriots', 'stealth action', 'playstation 3', 'kojima productions'], ['2009', 'uncharted 2 : among thieves', 'action - adventure : ( third - person ) shooter', 'playstation 3', 'naughty dog'], ['2010', 'mass effect 2', 'action rpg : ( third - person ) shooter', 'xbox 360 , windows , playstation 3', 'bioware'], ['2011', 'the legend of zelda : skyward sword', 'action - adventure', 'wii', 'nintendo ead , monolith soft'], ['2012', 'borderlands 2', 'action rpg / first - person shooter', 'xbox 360 , playstation 3 , windows', 'gearbox software']]
|
1989 indianapolis colts season
|
https://en.wikipedia.org/wiki/1989_Indianapolis_Colts_season
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14875671-1.html.csv
|
count
|
in the 1989 colts season , there were two games where the opponent was the buffalo bills .
|
{'scope': 'all', 'criterion': 'equal', 'value': 'buffalo bills', 'result': '2', 'col': '3', 'subset': None}
|
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', 'buffalo bills'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose opponent record fuzzily matches to buffalo bills .', 'tostr': 'filter_eq { all_rows ; opponent ; buffalo bills }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; opponent ; buffalo bills } }', 'tointer': 'select the rows whose opponent record fuzzily matches to buffalo bills . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; opponent ; buffalo bills } } ; 2 } = true', 'tointer': 'select the rows whose opponent record fuzzily matches to buffalo bills . the number of such rows is 2 .'}
|
eq { count { filter_eq { all_rows ; opponent ; buffalo bills } } ; 2 } = true
|
select the rows whose opponent record fuzzily matches to buffalo bills . the number of such rows is 2 .
|
3
|
3
|
{'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'opponent_5': 5, 'buffalo bills_6': 6, '2_7': 7}
|
{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'opponent_5': 'opponent', 'buffalo bills_6': 'buffalo bills', '2_7': '2'}
|
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'opponent_5': [0], 'buffalo bills_6': [0], '2_7': [2]}
|
['week', 'date', 'opponent', 'result', 'record', 'game site', 'attendance']
|
[['1', 'september 10 , 1989', 'san francisco 49ers', 'l 24 - 30', '0 - 1', 'hoosier dome', '60111'], ['2', 'september 17 , 1989', 'los angeles rams', 'l 17 - 31', '0 - 2', 'anaheim stadium', '63995'], ['3', 'september 24 , 1989', 'atlanta falcons', 'w 13 - 9', '1 - 2', 'hoosier dome', '57816'], ['4', 'october 1 , 1989', 'new york jets', 'w 17 - 10', '2 - 2', 'the meadowlands', '65542'], ['5', 'october 8 , 1989', 'buffalo bills', 'w 37 - 14', '3 - 2', 'hoosier dome', '58890'], ['6', 'october 15 , 1989', 'denver broncos', 'l 3 - 14', '3 - 3', 'mile high stadium', '74680'], ['7', 'october 22 , 1989', 'cincinnati bengals', 'w 23 - 12', '4 - 3', 'riverfront stadium', '57642'], ['8', 'october 29 , 1989', 'new england patriots', 'l 20 - 23', '4 - 4', 'hoosier dome', '59356'], ['9', 'november 5 , 1989', 'miami dolphins', 'l 13 - 19', '4 - 5', 'joe robbie stadium', '52680'], ['10', 'november 12 , 1989', 'buffalo bills', 'l 7 - 30', '4 - 6', 'rich stadium', '79256'], ['11', 'november 19 , 1989', 'new york jets', 'w 27 - 10', '5 - 6', 'hoosier dome', '58236'], ['12', 'november 26 , 1989', 'san diego chargers', 'w 10 - 6', '6 - 6', 'hoosier dome', '58822'], ['13', 'december 3 , 1989', 'new england patriots', 'l 16 - 22', '6 - 7', 'sullivan stadium', '32234'], ['14', 'december 10 , 1989', 'cleveland browns', 'w 23 - 17', '7 - 7', 'hoosier dome', '58550'], ['15', 'december 17 , 1989', 'miami dolphins', 'w 42 - 13', '8 - 7', 'hoosier dome', '55665'], ['16', 'december 24 , 1989', 'new orleans saints', 'l 6 - 41', '8 - 8', 'louisiana superdome', '49009']]
|
fiba eurobasket 2009 squads
|
https://en.wikipedia.org/wiki/FIBA_EuroBasket_2009_squads
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-23670057-5.html.csv
|
aggregation
|
the average hieght of all players on the russian fiba eurobasket 2009 squad is 2.01 meters .
|
{'scope': 'all', 'col': '3', 'type': 'average', 'result': '2.01', 'subset': None}
|
{'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'height ( m )'], 'result': '2.01', 'ind': 0, 'tostr': 'avg { all_rows ; height ( m ) }'}, '2.01'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; height ( m ) } ; 2.01 } = true', 'tointer': 'the average of the height ( m ) record of all rows is 2.01 .'}
|
round_eq { avg { all_rows ; height ( m ) } ; 2.01 } = true
|
the average of the height ( m ) record of all rows is 2.01 .
|
2
|
2
|
{'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'height (m)_4': 4, '2.01_5': 5}
|
{'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'height (m)_4': 'height ( m )', '2.01_5': '2.01'}
|
{'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'height (m)_4': [0], '2.01_5': [1]}
|
['no', 'player', 'height ( m )', 'height ( f )', 'position', 'year born', 'current club']
|
[['4', 'andrey vorontsevich', '2.07', "6 ' 09", 'forward', '1987', 'cska moscow'], ['5', 'nikita kurbanov', '2.03', "6 ' 08", 'forward', '1986', 'cska moscow'], ['6', 'sergey bykov', '1.90', "6 ' 03", 'guard', '1983', 'lokomotiv kuban'], ['7', 'vitaly fridzon', '1.95', "6 ' 05", 'guard', '1985', 'khimki'], ['8', 'kelly mccarty', '2.01', "6 ' 07", 'forward', '1975', 'unics kazan'], ['9', 'dmitri sokolov', '2.14', "7 ' 00", 'center', '1985', 'cska moscow'], ['10', 'fedor dmitriev', '2.05', "6 ' 09", 'forward', '1984', 'spartak saint petersburg'], ['11', 'egor vyaltsev', '1.94', "6 ' 04", 'guard', '1985', 'khimki'], ['12', 'sergey monya', '2.05', "6 ' 09", 'forward', '1983', 'khimki'], ['13', 'anton ponkrashov', '2.00', "6 ' 07", 'guard', '1986', 'cska moscow'], ['14', 'alexey zozulin', '2.01', "6 ' 07", 'guard', '1983', 'cska moscow']]
|
sport in saint petersburg
|
https://en.wikipedia.org/wiki/Sport_in_Saint_Petersburg
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12978801-1.html.csv
|
count
|
there is a total of three ice hockey venues in st. petersburg .
|
{'scope': 'all', 'criterion': 'equal', 'value': 'ice hockey', 'result': '3', 'col': '3', 'subset': None}
|
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'sport', 'ice hockey'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose sport record fuzzily matches to ice hockey .', 'tostr': 'filter_eq { all_rows ; sport ; ice hockey }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; sport ; ice hockey } }', 'tointer': 'select the rows whose sport record fuzzily matches to ice hockey . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; sport ; ice hockey } } ; 3 } = true', 'tointer': 'select the rows whose sport record fuzzily matches to ice hockey . the number of such rows is 3 .'}
|
eq { count { filter_eq { all_rows ; sport ; ice hockey } } ; 3 } = true
|
select the rows whose sport record fuzzily matches to ice hockey . 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, 'sport_5': 5, 'ice hockey_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', 'sport_5': 'sport', 'ice hockey_6': 'ice hockey', '3_7': '3'}
|
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'sport_5': [0], 'ice hockey_6': [0], '3_7': [2]}
|
['club', 'league', 'sport', 'venue', 'established']
|
[['zenit st petersburg', 'rfpl', 'football', 'petrovsky stadium', '1926'], ['spartak st petersburg', 'pbl', 'basketball', 'yubileyny sports palace', '1935'], ['avtomobilist st petesburg', 'vsl', 'volleyball', 'platonov volleyball academy', '1935'], ['ska st petersburg', 'khl', 'ice hockey', 'ice palace', '1946'], ['politekh st petersburg', 'mfsl', 'futsal', 'kalinin district mfok', '1995'], ['petrotrest st petersburg', 'fnl', 'football', 'msa petrovsky', '2001'], ['ska - 1946 st petersburg', 'mhl', 'ice hockey', 'msa yubileyny', '2009'], ['serebryanye lvy', 'mhl', 'ice hockey', 'spartak ice palace', '2010']]
|
list of danish consorts
|
https://en.wikipedia.org/wiki/List_of_Danish_consorts
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12418234-6.html.csv
|
count
|
three danish consort 's ceased to be consorts due to their husband 's death .
|
{'scope': 'all', 'criterion': 'fuzzily_match', 'value': "husband 's death", 'result': '3', 'col': '5', 'subset': None}
|
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'ceased to be consort', "husband 's death"], 'result': None, 'ind': 0, 'tointer': "select the rows whose ceased to be consort record fuzzily matches to husband 's death .", 'tostr': "filter_eq { all_rows ; ceased to be consort ; husband 's death }"}], 'result': '3', 'ind': 1, 'tostr': "count { filter_eq { all_rows ; ceased to be consort ; husband 's death } }", 'tointer': "select the rows whose ceased to be consort record fuzzily matches to husband 's death . the number of such rows is 3 ."}, '3'], 'result': True, 'ind': 2, 'tostr': "eq { count { filter_eq { all_rows ; ceased to be consort ; husband 's death } } ; 3 } = true", 'tointer': "select the rows whose ceased to be consort record fuzzily matches to husband 's death . the number of such rows is 3 ."}
|
eq { count { filter_eq { all_rows ; ceased to be consort ; husband 's death } } ; 3 } = true
|
select the rows whose ceased to be consort record fuzzily matches to husband 's death . 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, 'ceased to be consort_5': 5, "husband 's death_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', 'ceased to be consort_5': 'ceased to be consort', "husband 's death_6": "husband 's death", '3_7': '3'}
|
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'ceased to be consort_5': [0], "husband 's death_6": [0], '3_7': [2]}
|
['name', 'birth', 'marriage', 'became consort', 'ceased to be consort', 'spouse']
|
[['louise of hesse - kassel', '7 september 1817', '26 may 1842', "15 november 1863 husband 's ascession", '29 september 1898', 'christian ix'], ['louise of sweden', '31 october 1851', '28 july 1869', "29 january 1906 husband 's ascession", "14 may 1912 husband 's death", 'frederick viii'], ['alexandrine of mecklenburg - schwerin', '24 december 1879', '26 april 1898', "14 may 1912 husband 's ascession", "20 april 1947 husband 's death", 'christian x'], ['ingrid of sweden', '28 march 1910', '24 may 1935', "20 april 1947 husband 's ascession", "14 january 1972 husband 's death", 'frederick ix'], ['henri de laborde de monpezat', '11 june 1934', '10 june 1967', '14 january 1972', 'incumbent', 'margrethe ii']]
|
sony xperia
|
https://en.wikipedia.org/wiki/Sony_Xperia
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-23556331-4.html.csv
|
unique
|
the only sony xperia sony smartphone that has a 4.55 " screen is code-named aoba .
|
{'scope': 'all', 'row': '2', 'col': '9', 'col_other': '1', 'criterion': 'equal', 'value': '4.55', 'subset': None}
|
{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'display', '4.55'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose display record is equal to 4.55 .', 'tostr': 'filter_eq { all_rows ; display ; 4.55 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; display ; 4.55 } }', 'tointer': 'select the rows whose display record is equal to 4.55 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'display', '4.55'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose display record is equal to 4.55 .', 'tostr': 'filter_eq { all_rows ; display ; 4.55 }'}, 'code name'], 'result': 'aoba', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; display ; 4.55 } ; code name }'}, 'aoba'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; display ; 4.55 } ; code name } ; aoba }', 'tointer': 'the code name record of this unqiue row is aoba .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; display ; 4.55 } } ; eq { hop { filter_eq { all_rows ; display ; 4.55 } ; code name } ; aoba } } = true', 'tointer': 'select the rows whose display record is equal to 4.55 . there is only one such row in the table . the code name record of this unqiue row is aoba .'}
|
and { only { filter_eq { all_rows ; display ; 4.55 } } ; eq { hop { filter_eq { all_rows ; display ; 4.55 } ; code name } ; aoba } } = true
|
select the rows whose display record is equal to 4.55 . there is only one such row in the table . the code name record of this unqiue row is aoba .
|
6
|
5
|
{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'display_7': 7, '4.55_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'code name_9': 9, 'aoba_10': 10}
|
{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'display_7': 'display', '4.55_8': '4.55', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'code name_9': 'code name', 'aoba_10': 'aoba'}
|
{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'display_7': [0], '4.55_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'code name_9': [2], 'aoba_10': [3]}
|
['code name', 'market name', 'platform', 'release date', 'android version', 'system on chip', 'ram', 'rom', 'display', 'weight', 'battery ( mah )', 'bluetooth', 'wi - fi', 'nfc', 'camera', 'network']
|
[['nozomi', 'xperia s', 'fuji', '2012 - 02', '2.3 / 4.0 / 4.1', '1.5 ghz qualcomm snapdragon s3 msm8260 , dual - core', '1 gb', '32 gb', '4.3 hd', '144 g', '1750', '2.1 + edr', '802.11 b / g / n', 'yes', 'rear : 12.1 mp front : 1.3 mp', 'gsm / hspa +'], ['aoba', 'xperia ion', 'fuji', '2012 - 03', '2.3 / 4.0 / 4.1', '1.5 ghz qualcomm snapdragon s3 apq8060 , dual - core', '1 gb', '16 gb', '4.55 hd', '144 g', '1900', '2.1 + edr', '802.11 b / g / n', 'yes', 'rear : 12 mp front : 1.3 mp', 'gsm / hspa + / lte'], ['hayate', 'xperia acro hd', 'fuji', '2013 - 03', '2.3 / 4.0', '1.5 ghz qualcomm snapdragon s3 msm8660 , dual - core', '1 gb', '11 gb', '4.3 hd', '149 g', '1900', '2.1', '802.11 b / g / n', 'no', 'rear : 12.1 mp front : 1.3 mp', 'cdma / gsm / hspa +'], ['hikari', 'xperia acro hd xperia acro s', 'fuji', '2013 - 03 ( hd ) 2012 - 08 ( s )', '2.3 / 4.0 / 4.1', '1.5 ghz qualcomm snapdragon s3 msm8260 , dual - core', '1 gb', '11 gb ( hd ) 16 gb ( s )', '4.3 hd', '149 g ( hd ) 147 g ( s )', '1910', '2.1 ( hd ) 3.0 ( s )', '802.11 b / g / n', 'yes', 'rear : 12.1 mp front : 1.3 mp', 'gsm / hspa +'], ['pepper', 'xperia sola', 'riogrande', '2012 - 03', '2.3 / 4.0', '1 ghz st - ericsson novathor u8500 , dual - core', '512 mb', '8 gb', '3.7 fwvga', '107 g', '1320', '2.1 + edr', '802.11 b / g / n', 'yes', '5 mp', 'gsm / w - cdma'], ['phoenix', 'xperia neo l', 'mogami', '2012 - 03', '4.0', '1 ghz qualcomm snapdragon s2 msm8255', '512 mb', '1 gb', '4 fwvga', '131.5 g', '1500', '2.1 + edr', '802.11 b / g / n', 'no', 'rear : 5 mp front : 0.3 mp', 'gsm / hspa'], ['nypon', 'xperia p', 'riogrande', '2012 - 04', '2.3 / 4.0 / 4.1', '1 ghz st - ericsson novathor u8500 , dual - core', '1 gb', '16 gb', '4 qhd', '126 g', '1305', '2.1 + edr', '802.11 b / g / n', 'yes', 'rear : 8 mp front : 0.3 mp', 'gsm / hspa +'], ['kumquat', 'xperia u', 'riogrande', '2012 - 05', '2.3 / 4.0', '1 ghz st - ericsson novathor u8500 , dual - core', '512 mb', '4 gb', '3.5 fwvga', '110 g', '1320', '2.1 + edr', '802.11 b / g / n', 'no', 'rear : 5 mp front : 0.3 mp', 'gsm / hspa +'], ['lotus', 'xperia go', 'riogrande', '2012 - 07', '2.3 / 4.0 / 4.1', '1 ghz st - ericsson novathor u8500 , dual - core', '512 mb', '8 gb', '3.5 hvga', '110 g', '1305', '3.0', '802.11 b / g / n', 'no', '5 mp', 'gsm / hspa +'], ['tapioca', 'xperia tipo xperia tipo dual', 'tamsui', '2012 - 08', '4.0', '800 mhz qualcomm snapdragon s1 msm7225a', '512 mb', '2.9 gb', '3.2 hvga', '0 99.4 g', '1500', '2.1 + edr', '802.11 b / g / n', 'no', 'rear : 3.2 mp front : 0.3 mp', 'gsm / hspa'], ['mesona', 'xperia miro', 'tamsui', '2012 - 09', '4.0', '800 mhz qualcomm snapdragon s1 msm7225a', '512 mb', '4 gb', '3.5 hvga', '110 g', '1500', '2.1 + edr', '802.11 b / g / n', 'no', 'rear : 5 mp front : 0.3 mp', 'gsm / hspa'], ['nozomi2', 'xperia sl', 'fuji', '2012 - 09', '2.3 / 4.0 / 4.1', '1.7 ghz qualcomm snapdragon s3 msm8260 , dual - core', '1 gb', '32 gb', '4.3 hd', '144 g', '1750', '3.0', '802.11 b / g / n', 'yes', 'rear : 12.1 mp front : 1.3 mp', 'gsm / hspa +'], ['jlo', 'xperia j', 'tamsui', '2012 - 10', '4.0 / 4.1', '1 ghz qualcomm snapdragon s1 msm7227a', '512 mb', '4 gb', '4 fwvga', '124 g', '1750', '2.1 + edr', '802.11 b / g / n', 'no', 'rear : 5 mp front : 0.3 mp', 'gsm / hspa'], ['nanhu', 'xperia e xperia e dual', 'tamsui', '2013 - 03', '4.0 / 4.1', '1 ghz qualcomm snapdragon s1 msm7227a', '512 mb', '4 gb', '3.5 hvga', '115.7 g', '1530', '2.1 + edr', '802.11 b / g / n', 'no', '3.2 mp', 'gsm / hspa']]
|
1976 los angeles rams season
|
https://en.wikipedia.org/wiki/1976_Los_Angeles_Rams_season
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11159520-2.html.csv
|
majority
|
all of the games played in december 1976 by the los angeles rams were wins .
|
{'scope': 'subset', 'col': '4', 'most_or_all': 'all', 'criterion': 'fuzzily_match', 'value': 'w', 'subset': {'col': '2', 'criterion': 'fuzzily_match', 'value': 'december 1976'}}
|
{'func': 'all_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', 'december 1976'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; date ; december 1976 }', 'tointer': 'select the rows whose date record fuzzily matches to december 1976 .'}, 'result', 'w'], 'result': True, 'ind': 1, 'tointer': 'select the rows whose date record fuzzily matches to december 1976 . for the result records of these rows , all of them fuzzily match to w .', 'tostr': 'all_eq { filter_eq { all_rows ; date ; december 1976 } ; result ; w } = true'}
|
all_eq { filter_eq { all_rows ; date ; december 1976 } ; result ; w } = true
|
select the rows whose date record fuzzily matches to december 1976 . for the result records of these rows , all of them fuzzily match to w .
|
2
|
2
|
{'all_str_eq_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, 'date_4': 4, 'december 1976_5': 5, 'result_6': 6, 'w_7': 7}
|
{'all_str_eq_1': 'all_str_eq', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'date_4': 'date', 'december 1976_5': 'december 1976', 'result_6': 'result', 'w_7': 'w'}
|
{'all_str_eq_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'date_4': [0], 'december 1976_5': [0], 'result_6': [1], 'w_7': [1]}
|
['week', 'date', 'opponent', 'result', 'attendance']
|
[['1', 'september 12 , 1976', 'atlanta falcons', 'w 30 - 14', '53607'], ['2', 'september 19 , 1976', 'minnesota vikings', 't 10 - 10', '47310'], ['3', 'september 26 , 1976', 'new york giants', 'w 24 - 10', '60698'], ['4', 'october 3 , 1976', 'miami dolphins', 'w 31 - 28', '60753'], ['5', 'october 11 , 1976', 'san francisco 49ers', 'l 16 - 0', '80532'], ['6', 'october 17 , 1976', 'chicago bears', 'w 20 - 12', '71751'], ['7', 'october 24 , 1976', 'new orleans saints', 'w 16 - 10', '51984'], ['8', 'october 31 , 1976', 'seattle seahawks', 'w 45 - 6', '52035'], ['9', 'november 7 , 1976', 'cincinnati bengals', 'l 20 - 12', '52480'], ['10', 'november 14 , 1976', 'st louis cardinals', 'l 30 - 28', '64698'], ['11', 'november 21 , 1976', 'san francisco 49ers', 'w 23 - 3', '58573'], ['12', 'november 28 , 1976', 'new orleans saints', 'w 33 - 14', '54906'], ['13', 'december 4 , 1976', 'atlanta falcons', 'w 59 - 0', '57366'], ['14', 'december 11 , 1976', 'detroit lions', 'w 20 - 17', '73470']]
|
martín machón
|
https://en.wikipedia.org/wiki/Mart%C3%ADn_Mach%C3%B3n
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16525468-1.html.csv
|
superlative
|
the earliest date that martín machón played a friendly match was on november 7 , 1997 .
|
{'scope': 'subset', 'col_superlative': '1', 'row_superlative': '3', 'value_mentioned': 'yes', 'max_or_min': 'min', 'other_col': '5', 'subset': {'col': '5', 'criterion': 'equal', 'value': 'friendly match'}}
|
{'func': 'eq', 'args': [{'func': 'min', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'competition', 'friendly match'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; competition ; friendly match }', 'tointer': 'select the rows whose competition record fuzzily matches to friendly match .'}, 'date'], 'result': '7 november 1997', 'ind': 1, 'tostr': 'min { filter_eq { all_rows ; competition ; friendly match } ; date }', 'tointer': 'select the rows whose competition record fuzzily matches to friendly match . the minimum date record of these rows is 7 november 1997 .'}, '7 november 1997'], 'result': True, 'ind': 2, 'tostr': 'eq { min { filter_eq { all_rows ; competition ; friendly match } ; date } ; 7 november 1997 } = true', 'tointer': 'select the rows whose competition record fuzzily matches to friendly match . the minimum date record of these rows is 7 november 1997 .'}
|
eq { min { filter_eq { all_rows ; competition ; friendly match } ; date } ; 7 november 1997 } = true
|
select the rows whose competition record fuzzily matches to friendly match . the minimum date record of these rows is 7 november 1997 .
|
3
|
3
|
{'eq_2': 2, 'result_3': 3, 'min_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'competition_5': 5, 'friendly match_6': 6, 'date_7': 7, '7 november 1997_8': 8}
|
{'eq_2': 'eq', 'result_3': 'true', 'min_1': 'min', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'competition_5': 'competition', 'friendly match_6': 'friendly match', 'date_7': 'date', '7 november 1997_8': '7 november 1997'}
|
{'eq_2': [3], 'result_3': [], 'min_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'competition_5': [0], 'friendly match_6': [0], 'date_7': [1], '7 november 1997_8': [2]}
|
['date', 'venue', 'score', 'result', 'competition']
|
[['16 january 1996', 'edison international field , anaheim , usa', '3 - 0', '3 - 0', 'concacaf gold cup'], ['20 april 1997', 'estadio mateo flores , guatemala city , guatemala', '1 - 0', '6 - 1', 'continental qualifier'], ['7 november 1997', 'estadio regional , antofagasta , chile', '1 - 3', '1 - 4', 'friendly match'], ['17 february 1999', 'estadio mateo flores , guatemala city , guatemala', '1 - 1', '1 - 1', 'friendly match'], ['28 march 1999', 'estadio nacional , san josé , costa rica', '2 - 0', '2 - 0', 'continental qualifier']]
|
united states house of representatives elections , 1964
|
https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1964
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1341865-45.html.csv
|
aggregation
|
the winners of congressional representative seats in the texas districts reported averaged 70.31 % of the vote in each district .
|
{'scope': 'all', 'col': '6', 'type': 'average', 'result': '70.31', 'subset': None}
|
{'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'candidates'], 'result': '70.31', 'ind': 0, 'tostr': 'avg { all_rows ; candidates }'}, '70.31'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; candidates } ; 70.31 } = true', 'tointer': 'the average of the candidates record of all rows is 70.31 .'}
|
round_eq { avg { all_rows ; candidates } ; 70.31 } = true
|
the average of the candidates record of all rows is 70.31 .
|
2
|
2
|
{'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'candidates_4': 4, '70.31_5': 5}
|
{'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'candidates_4': 'candidates', '70.31_5': '70.31'}
|
{'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'candidates_4': [0], '70.31_5': [1]}
|
['district', 'incumbent', 'party', 'first elected', 'result', 'candidates']
|
[['texas 2', 'jack brooks', 'democratic', '1952', 're - elected', 'jack brooks ( d ) 62.7 % john greco ( r ) 37.3 %'], ['texas 3', 'lindley beckworth', 'democratic', '1956', 're - elected', 'lindley beckworth ( d ) 59.3 % james warren ( r ) 40.7 %'], ['texas 4', 'ray roberts', 'democratic', '1962', 're - elected', 'ray roberts ( d ) 81.4 % fred banfield ( r ) 18.6 %'], ['texas 5', 'bruce r alger', 'republican', '1954', 'lost re - election democratic gain', 'earle cabell ( d ) 57.5 % bruce r alger ( r ) 42.5 %'], ['texas 7', 'john dowdy', 'democratic', '1952', 're - elected', 'john dowdy ( d ) 83.6 % james w orr ( r ) 16.4 %'], ['texas 9', 'clark w thompson', 'democratic', '1947', 're - elected', 'clark w thompson ( d ) 75.3 % dave oakes ( r ) 24.7 %'], ['texas 10', 'j j pickle', 'democratic', '1963', 're - elected', 'j j pickle ( d ) 75.8 % billie pratt ( r ) 24.2 %'], ['texas 12', 'jim wright', 'democratic', '1954', 're - elected', 'jim wright ( d ) 68.5 % fred dielman ( r ) 31.5 %'], ['texas 14', 'john andrew young', 'democratic', '1956', 're - elected', 'john andrew young ( d ) 77.5 % w f patton ( r ) 22.5 %'], ['texas 16', 'ed foreman', 'republican', '1962', 'lost re - election democratic gain', 'richard c white ( d ) 55.7 % ed foreman ( r ) 44.3 %'], ['texas 17', 'omar burleson', 'democratic', '1946', 're - elected', 'omar burleson ( d ) 76.4 % phil bridges ( r ) 23.6 %'], ['texas 18', 'walter e rogers', 'democratic', '1950', 're - elected', 'walter e rogers ( d ) 55.0 % robert price ( r ) 45.0 %'], ['texas 19', 'george h mahon', 'democratic', '1934', 're - elected', 'george h mahon ( d ) 77.6 % joe b philips ( r ) 22.4 %'], ['texas 21', 'o c fisher', 'democratic', '1942', 're - elected', 'o c fisher ( d ) 78.1 % harry claypool ( r ) 21.9 %']]
|
1993 - 94 segunda división
|
https://en.wikipedia.org/wiki/1993%E2%80%9394_Segunda_Divisi%C3%B3n
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12092001-2.html.csv
|
count
|
20 clubs participated in the 1993 - 94 segunda división season games .
|
{'scope': 'all', 'criterion': 'all', 'value': 'n/a', 'result': '20', 'col': '2', 'subset': None}
|
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_all', 'args': ['all_rows', 'club'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose club record is arbitrary .', 'tostr': 'filter_all { all_rows ; club }'}], 'result': '20', 'ind': 1, 'tostr': 'count { filter_all { all_rows ; club } }', 'tointer': 'select the rows whose club record is arbitrary . the number of such rows is 20 .'}, '20'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_all { all_rows ; club } } ; 20 } = true', 'tointer': 'select the rows whose club record is arbitrary . the number of such rows is 20 .'}
|
eq { count { filter_all { all_rows ; club } } ; 20 } = true
|
select the rows whose club record is arbitrary . the number of such rows is 20 .
|
3
|
3
|
{'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_all_0': 0, 'all_rows_4': 4, 'club_5': 5, '20_6': 6}
|
{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_all_0': 'filter_all', 'all_rows_4': 'all_rows', 'club_5': 'club', '20_6': '20'}
|
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_all_0': [1], 'all_rows_4': [0], 'club_5': [0], '20_6': [2]}
|
['position', 'club', 'played', 'points', 'wins', 'draws', 'losses', 'goals for', 'goals against', 'goal difference']
|
[['1', 'rcd español', '38', '52', '20', '12', '6', '59', '25', '+ 34'], ['2', 'real betis', '38', '51', '22', '7', '9', '66', '38', '+ 28'], ['3', 'sd compostela', '38', '49', '21', '7', '10', '56', '36', '+ 20'], ['4', 'cd toledo', '38', '47', '18', '11', '9', '50', '32', '+ 18'], ['5', 'rcd mallorca', '38', '47', '20', '7', '11', '66', '39', '+ 27'], ['6', 'real madrid b', '38', '46', '19', '8', '11', '57', '41', '+ 16'], ['7', 'hércules cf', '38', '44', '16', '12', '10', '41', '35', '+ 6'], ['8', 'barcelona b', '38', '39', '11', '17', '10', '59', '51', '+ 8'], ['9', 'cp mérida', '38', '37', '12', '13', '13', '47', '41', '+ 6'], ['10', 'sd eibar', '38', '35', '10', '15', '13', '30', '40', '- 10'], ['11', 'cd badajoz', '38', '35', '12', '11', '15', '45', '46', '- 1'], ['12', 'atlético marbella', '38', '35', '10', '15', '13', '40', '41', '- 1'], ['13', 'palamós cf', '38', '34', '11', '12', '15', '40', '49', '- 9'], ['14', 'athletic de bilbao b', '38', '34', '10', '14', '14', '46', '52', '- 6'], ['15', 'cd leganés', '38', '34', '11', '12', '15', '53', '59', '- 6'], ['16', 'villarreal cf', '38', '34', '14', '6', '18', '29', '48', '- 19'], ['17', 'cd castellón', '38', '32', '9', '14', '15', '30', '48', '- 18'], ['18', 'real murcia', '38', '31', '10', '11', '17', '40', '64', '- 24'], ['19', 'real burgos 1', '38', '26', '10', '6', '22', '38', '68', '- 30'], ['20', 'cádiz cf', '38', '18', '4', '10', '24', '28', '67', '- 39']]
|
teo fabi
|
https://en.wikipedia.org/wiki/Teo_Fabi
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1218368-3.html.csv
|
aggregation
|
the average number of laps finished by teo fabi from 1980 to 1993 is around 200 .
|
{'scope': 'all', 'col': '6', 'type': 'average', 'result': '200', 'subset': None}
|
{'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'laps'], 'result': '200', 'ind': 0, 'tostr': 'avg { all_rows ; laps }'}, '200'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; laps } ; 200 } = true', 'tointer': 'the average of the laps record of all rows is 200 .'}
|
round_eq { avg { all_rows ; laps } ; 200 } = true
|
the average of the laps record of all rows is 200 .
|
2
|
2
|
{'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'laps_4': 4, '200_5': 5}
|
{'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'laps_4': 'laps', '200_5': '200'}
|
{'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'laps_4': [0], '200_5': [1]}
|
['year', 'class', 'tyres', 'team', 'co - drivers', 'laps', 'pos', 'class pos']
|
[['1980', 'gr5', 'p', 'scuderia lancia corse', 'hans heyer bernard darniche', '6', 'dnf', 'dnf'], ['1982', 'gr6', 'p', 'martini racing', 'michele alboreto rolf stommelen', '92', 'dnf', 'dnf'], ['1983', 'c', 'd', 'martini lancia', 'michele alboreto alessandro nannini', '27', 'dnf', 'dnf'], ['1991', 'c2', 'g', 'silk cut jaguar tom walkinshaw racing', 'bob wollek kenny acheson', '358', '3rd', '3rd'], ['1992', 'c1', 'g', "toyota team tom 's", 'jan lammers andy wallace', '331', '8th', '5th'], ['1993', 'c1', 'm', 'peugeot talbot sport', 'thierry boutsen yannick dalmas', '374', '2nd', '2nd']]
|
ross bagdasarian , jr
|
https://en.wikipedia.org/wiki/Ross_Bagdasarian%2C_Jr.
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1543453-1.html.csv
|
comparative
|
out of the alvin and the chipmunks movies that ross bagdasarian jr. worked on , " the chipmunk adventure " was released before " alvin and the chipmunks meet the wolfman " .
|
{'row_1': '1', 'row_2': '3', 'col': '1', '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', 'title', 'the chipmunk adventure'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose title record fuzzily matches to the chipmunk adventure .', 'tostr': 'filter_eq { all_rows ; title ; the chipmunk adventure }'}, 'year'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; title ; the chipmunk adventure } ; year }', 'tointer': 'select the rows whose title record fuzzily matches to the chipmunk adventure . take the year record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'title', 'alvin and the chipmunks meet the wolfman'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose title record fuzzily matches to alvin and the chipmunks meet the wolfman .', 'tostr': 'filter_eq { all_rows ; title ; alvin and the chipmunks meet the wolfman }'}, 'year'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; title ; alvin and the chipmunks meet the wolfman } ; year }', 'tointer': 'select the rows whose title record fuzzily matches to alvin and the chipmunks meet the wolfman . take the year record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; title ; the chipmunk adventure } ; year } ; hop { filter_eq { all_rows ; title ; alvin and the chipmunks meet the wolfman } ; year } } = true', 'tointer': 'select the rows whose title record fuzzily matches to the chipmunk adventure . take the year record of this row . select the rows whose title record fuzzily matches to alvin and the chipmunks meet the wolfman . take the year record of this row . the first record is less than the second record .'}
|
less { hop { filter_eq { all_rows ; title ; the chipmunk adventure } ; year } ; hop { filter_eq { all_rows ; title ; alvin and the chipmunks meet the wolfman } ; year } } = true
|
select the rows whose title record fuzzily matches to the chipmunk adventure . take the year record of this row . select the rows whose title record fuzzily matches to alvin and the chipmunks meet the wolfman . 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, 'title_7': 7, 'the chipmunk adventure_8': 8, 'year_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'title_11': 11, 'alvin and the chipmunks meet the wolfman_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', 'title_7': 'title', 'the chipmunk adventure_8': 'the chipmunk adventure', 'year_9': 'year', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'title_11': 'title', 'alvin and the chipmunks meet the wolfman_12': 'alvin and the chipmunks meet the wolfman', 'year_13': 'year'}
|
{'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'title_7': [0], 'the chipmunk adventure_8': [0], 'year_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'title_11': [1], 'alvin and the chipmunks meet the wolfman_12': [1], 'year_13': [3]}
|
['year', 'title', 'producer', 'actor', 'role']
|
[['1987', 'the chipmunk adventure', 'yes', 'yes', "alvin seville simon seville david ' dave ' seville"], ['1999', 'alvin and the chipmunks meet frankenstein', 'yes', 'yes', "alvin seville simon seville david ' dave ' seville"], ['2000', 'alvin and the chipmunks meet the wolfman', 'yes', 'yes', "alvin seville simon seville david ' dave ' seville"], ['2005', 'little alvin and the mini - munks', 'yes', 'yes', "alvin seville simon seville david ' dave ' seville"], ['2007', 'alvin and the chipmunks', 'yes', 'yes', 'alvin seville simon seville'], ['2009', 'alvin and the chipmunks : the squeakquel', 'yes', 'yes', 'alvin seville simon seville'], ['2011', 'alvin and the chipmunks : chipwrecked', 'yes', 'yes', 'alvin seville simon seville']]
|
1954 vfl season
|
https://en.wikipedia.org/wiki/1954_VFL_season
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10773616-18.html.csv
|
majority
|
all games of the 1954 vfl season was played on the 28th of august .
|
{'scope': 'all', 'col': '7', 'most_or_all': 'all', 'criterion': 'equal', 'value': '28 august 1954', 'subset': None}
|
{'func': 'all_str_eq', 'args': ['all_rows', 'date', '28 august 1954'], 'result': True, 'ind': 0, 'tointer': 'for the date records of all rows , all of them fuzzily match to 28 august 1954 .', 'tostr': 'all_eq { all_rows ; date ; 28 august 1954 } = true'}
|
all_eq { all_rows ; date ; 28 august 1954 } = true
|
for the date records of all rows , all of them fuzzily match to 28 august 1954 .
|
1
|
1
|
{'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'date_3': 3, '28 august 1954_4': 4}
|
{'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'date_3': 'date', '28 august 1954_4': '28 august 1954'}
|
{'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'date_3': [0], '28 august 1954_4': [0]}
|
['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date']
|
[['north melbourne', '19.15 ( 129 )', 'st kilda', '12.10 ( 82 )', 'arden street oval', '9500', '28 august 1954'], ['footscray', '17.15 ( 117 )', 'hawthorn', '5.4 ( 34 )', 'western oval', '22896', '28 august 1954'], ['south melbourne', '7.7 ( 49 )', 'melbourne', '14.17 ( 101 )', 'lake oval', '25000', '28 august 1954'], ['fitzroy', '14.13 ( 97 )', 'essendon', '13.13 ( 91 )', 'brunswick street oval', '20000', '28 august 1954'], ['richmond', '14.17 ( 101 )', 'collingwood', '6.12 ( 48 )', 'punt road oval', '25000', '28 august 1954'], ['geelong', '13.12 ( 90 )', 'carlton', '6.13 ( 49 )', 'kardinia park', '23119', '28 august 1954']]
|
uk film council completion fund
|
https://en.wikipedia.org/wiki/UK_Film_Council_Completion_Fund
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12181447-7.html.csv
|
unique
|
traffic warden is the only film for the uk film council completion fund that was directed by donald rice .
|
{'scope': 'all', 'row': '10', 'col': '2', 'col_other': '1', 'criterion': 'equal', 'value': 'donald rice', 'subset': None}
|
{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'director ( s )', 'donald rice'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose director ( s ) record fuzzily matches to donald rice .', 'tostr': 'filter_eq { all_rows ; director ( s ) ; donald rice }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; director ( s ) ; donald rice } }', 'tointer': 'select the rows whose director ( s ) record fuzzily matches to donald rice . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'director ( s )', 'donald rice'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose director ( s ) record fuzzily matches to donald rice .', 'tostr': 'filter_eq { all_rows ; director ( s ) ; donald rice }'}, 'film'], 'result': 'traffic warden', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; director ( s ) ; donald rice } ; film }'}, 'traffic warden'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; director ( s ) ; donald rice } ; film } ; traffic warden }', 'tointer': 'the film record of this unqiue row is traffic warden .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; director ( s ) ; donald rice } } ; eq { hop { filter_eq { all_rows ; director ( s ) ; donald rice } ; film } ; traffic warden } } = true', 'tointer': 'select the rows whose director ( s ) record fuzzily matches to donald rice . there is only one such row in the table . the film record of this unqiue row is traffic warden .'}
|
and { only { filter_eq { all_rows ; director ( s ) ; donald rice } } ; eq { hop { filter_eq { all_rows ; director ( s ) ; donald rice } ; film } ; traffic warden } } = true
|
select the rows whose director ( s ) record fuzzily matches to donald rice . there is only one such row in the table . the film record of this unqiue row is traffic warden .
|
6
|
5
|
{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'director (s)_7': 7, 'donald rice_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'film_9': 9, 'traffic warden_10': 10}
|
{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'director (s)_7': 'director ( s )', 'donald rice_8': 'donald rice', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'film_9': 'film', 'traffic warden_10': 'traffic warden'}
|
{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'director (s)_7': [0], 'donald rice_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'film_9': [2], 'traffic warden_10': [3]}
|
['film', 'director ( s )', 'writer ( s )', 'recipient', 'date', 'award']
|
[['mercy', 'candida scott knight', 'tina walker', 'maya vision international ltd', '3 / 3 / 04', '7800'], ['no deposit , no return', 'dallas campbell', 'dallas campbell , john edwards', 'rocliffe ltd', '3 / 3 / 04', '4360'], ['6.6.04', 'simon hook', 'simon hook , jayne kirkham', 'andrew wilson', '3 / 3 / 04', '1939'], ['bushido : the way of the warrior', 'susan jacobson', 'susan jacobson , anna reeves', 'pistachio pictures ltd', '3 / 3 / 04', '3386'], ['jamaica', 'martin scanlan', 'martin scanlan', 'prussia lane productions ltd', '3 / 3 / 04', '6947'], ['flowers and coins', 'joshua neale', 'neil henry , joshua neale', 'joshua neale', '3 / 3 / 04', '3740'], ['moving on', 'albert kodagolian', 'dusan tolmac', 'albert kodagolian', '3 / 3 / 04', '6504'], ['stalin , my neighbour', 'carol morley', 'carol morley', 'cannon and morley productions ltd', '3 / 3 / 04', '5750'], ['hotel infinity', 'amanda boyle', 'amanda boyle', 'picture farm ltd', '3 / 3 / 04', '9549'], ['traffic warden', 'donald rice', 'donald rice', 'clockwork pictures ltd', '3 / 3 / 04', '6947']]
|
1997 u.s. open ( golf )
|
https://en.wikipedia.org/wiki/1997_U.S._Open_%28golf%29
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17162179-6.html.csv
|
superlative
|
at the 1997 u.s. open , the highest amount of money was won by ernie els .
|
{'scope': 'all', 'col_superlative': '6', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None}
|
{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'money'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; money }'}, 'place'], 'result': '1', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; money } ; place }'}, '1'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; money } ; place } ; 1 } = true', 'tointer': 'select the row whose money record of all rows is maximum . the place record of this row is 1 .'}
|
eq { hop { argmax { all_rows ; money } ; place } ; 1 } = true
|
select the row whose money record of all rows is maximum . the place record of this row is 1 .
|
3
|
3
|
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'money_5': 5, 'place_6': 6, '1_7': 7}
|
{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'money_5': 'money', 'place_6': 'place', '1_7': '1'}
|
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'money_5': [0], 'place_6': [1], '1_7': [2]}
|
['place', 'player', 'country', 'score', 'to par', 'money']
|
[['1', 'ernie els', 'south africa', '71 + 67 + 69 + 69 = 276', '- 4', '465000'], ['2', 'colin montgomerie', 'scotland', '65 + 76 + 67 + 69 = 277', '- 3', '275000'], ['3', 'tom lehman', 'united states', '67 + 70 + 68 + 73 = 278', '- 2', '172828'], ['4', 'jeff maggert', 'united states', '73 + 66 + 68 + 74 = 281', '+ 1', '120454'], ['t5', 'olin browne', 'united states', '71 + 71 + 69 + 71 = 282', '+ 2', '79875'], ['t5', 'jim furyk', 'united states', '74 + 68 + 69 + 71 = 282', '+ 2', '79875'], ['t5', 'jay haas', 'united states', '73 + 69 + 68 + 72 = 282', '+ 2', '79875'], ['t5', 'tommy tolles', 'united states', '74 + 67 + 69 + 72 = 282', '+ 2', '79875'], ['t5', 'bob tway', 'united states', '71 + 71 + 70 + 70 = 282', '+ 2', '79875'], ['t10', 'scott hoch', 'united states', '71 + 68 + 72 + 72 = 283', '+ 3', '56949'], ['t10', 'scott mccarron', 'united states', '73 + 71 + 69 + 70 = 283', '+ 3', '56949'], ['t10', 'david ogrin', 'united states', '70 + 69 + 71 + 73 = 283', '+ 3', '56949']]
|
canadian university field lacrosse association
|
https://en.wikipedia.org/wiki/Canadian_University_Field_Lacrosse_Association
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-18042409-1.html.csv
|
majority
|
the majority of players have " none " as their major league lacrosse association .
|
{'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'none', 'subset': None}
|
{'func': 'most_str_eq', 'args': ['all_rows', 'major league lacrosse', 'none'], 'result': True, 'ind': 0, 'tointer': 'for the major league lacrosse records of all rows , most of them fuzzily match to none .', 'tostr': 'most_eq { all_rows ; major league lacrosse ; none } = true'}
|
most_eq { all_rows ; major league lacrosse ; none } = true
|
for the major league lacrosse records of all rows , most of them fuzzily match to none .
|
1
|
1
|
{'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'major league lacrosse_3': 3, 'none_4': 4}
|
{'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'major league lacrosse_3': 'major league lacrosse', 'none_4': 'none'}
|
{'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'major league lacrosse_3': [0], 'none_4': [0]}
|
['player', 'alma mater', 'national lacrosse league', 'major league lacrosse', 'international competition']
|
[['colin doyle', 'wilfrid laurier university', 'ontario raiders / toronto rock , san jose stealth', 'toronto nationals', 'team canada'], ['steve hoar', 'university of toronto', 'toronto rock', 'toronto nationals', 'team canada'], ['creighton reid', 'university of toronto ( practice squad )', 'toronto rock , colorado mammoth', 'none', 'none'], ['jay thorimbert', 'university of guelph', 'buffalo bandits , boston blazers , minnesota swarm', 'none', 'none'], ['sean thomson', 'university of guelph', 'philadelphia wings , minnesota swarm', 'none', 'none'], ['greg harnett', "bishop 's university", 'calgary roughnecks', 'none', 'none'], ['jon harnett', 'university of guelph', 'boston blazers', 'none', 'none'], ['josh wasson', 'trent university', 'chicago shamrox , toronto rock', 'none', 'none'], ['casey zaph', 'university of toronto', 'rochester knighthawks', 'none', 'none']]
|
2007 - 08 minnesota wild season
|
https://en.wikipedia.org/wiki/2007%E2%80%9308_Minnesota_Wild_season
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11739153-3.html.csv
|
count
|
in the 2007 - 08 minnesota wild season , among the games where minnesota was a visitor , 5 of them drew more than 15,000 people .
|
{'scope': 'subset', 'criterion': 'greater_than', 'value': '15000', 'result': '5', 'col': '6', 'subset': {'col': '2', 'criterion': 'equal', 'value': 'minnesota'}}
|
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'visitor', 'minnesota'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; visitor ; minnesota }', 'tointer': 'select the rows whose visitor record fuzzily matches to minnesota .'}, 'attendance', '15000'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose visitor record fuzzily matches to minnesota . among these rows , select the rows whose attendance record is greater than 15000 .', 'tostr': 'filter_greater { filter_eq { all_rows ; visitor ; minnesota } ; attendance ; 15000 }'}], 'result': '5', 'ind': 2, 'tostr': 'count { filter_greater { filter_eq { all_rows ; visitor ; minnesota } ; attendance ; 15000 } }', 'tointer': 'select the rows whose visitor record fuzzily matches to minnesota . among these rows , select the rows whose attendance record is greater than 15000 . the number of such rows is 5 .'}, '5'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_greater { filter_eq { all_rows ; visitor ; minnesota } ; attendance ; 15000 } } ; 5 } = true', 'tointer': 'select the rows whose visitor record fuzzily matches to minnesota . among these rows , select the rows whose attendance record is greater than 15000 . the number of such rows is 5 .'}
|
eq { count { filter_greater { filter_eq { all_rows ; visitor ; minnesota } ; attendance ; 15000 } } ; 5 } = true
|
select the rows whose visitor record fuzzily matches to minnesota . among these rows , select the rows whose attendance record is greater than 15000 . the number of such rows is 5 .
|
4
|
4
|
{'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_greater_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'visitor_6': 6, 'minnesota_7': 7, 'attendance_8': 8, '15000_9': 9, '5_10': 10}
|
{'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_greater_1': 'filter_greater', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'visitor_6': 'visitor', 'minnesota_7': 'minnesota', 'attendance_8': 'attendance', '15000_9': '15000', '5_10': '5'}
|
{'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_greater_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'visitor_6': [0], 'minnesota_7': [0], 'attendance_8': [1], '15000_9': [1], '5_10': [3]}
|
['date', 'visitor', 'score', 'home', 'decision', 'attendance', 'record']
|
[['october 4', 'chicago', '0 - 1', 'minnesota', 'backstrom', '18568', '1 - 0 - 0'], ['october 6', 'columbus', '2 - 3', 'minnesota', 'backstrom', '18568', '2 - 0 - 0'], ['october 10', 'edmonton', '0 - 2', 'minnesota', 'backstrom', '18568', '3 - 0 - 0'], ['october 13', 'minnesota', '3 - 2', 'phoenix', 'backstrom', '12088', '4 - 0 - 0'], ['october 14', 'minnesota', '2 - 0', 'anaheim', 'harding', '17174', '5 - 0 - 0'], ['october 16', 'minnesota', '3 - 4', 'los angeles', 'backstrom', '14239', '5 - 0 - 1'], ['october 20', 'minnesota', '3 - 1', 'st louis', 'harding', '19150', '6 - 0 - 1'], ['october 21', 'colorado', '2 - 3', 'minnesota', 'backstrom', '18568', '7 - 0 - 1'], ['october 24', 'minnesota', '3 - 5', 'calgary', 'backstrom', '19289', '7 - 1 - 1'], ['october 25', 'minnesota', '4 - 5', 'edmonton', 'harding', '16839', '7 - 1 - 2'], ['october 28', 'minnesota', '1 - 3', 'colorado', 'harding', '17041', '7 - 2 - 2'], ['october 30', 'pittsburgh', '4 - 2', 'minnesota', 'harding', '18568', '7 - 3 - 2']]
|
2008 australian carrera cup championship
|
https://en.wikipedia.org/wiki/2008_Australian_Carrera_Cup_Championship
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18333905-2.html.csv
|
ordinal
|
round 3 of the 2008 australian carrera cup championship was played at wakefield park .
|
{'scope': 'all', 'row': '3', 'col': '1', 'order': '3', 'col_other': '3', 'max_or_min': 'min_to_max', 'value_mentioned': 'yes', 'subset': None}
|
{'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'nth_min', 'args': ['all_rows', 'round', '3'], 'result': '3', 'ind': 0, 'tostr': 'nth_min { all_rows ; round ; 3 }', 'tointer': 'the 3rd minimum round record of all rows is 3 .'}, '3'], 'result': True, 'ind': 1, 'tostr': 'eq { nth_min { all_rows ; round ; 3 } ; 3 }', 'tointer': 'the 3rd minimum round record of all rows is 3 .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'round', '3'], 'result': None, 'ind': 2, 'tostr': 'nth_argmin { all_rows ; round ; 3 }'}, 'circuit'], 'result': 'wakefield park', 'ind': 3, 'tostr': 'hop { nth_argmin { all_rows ; round ; 3 } ; circuit }'}, 'wakefield park'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { nth_argmin { all_rows ; round ; 3 } ; circuit } ; wakefield park }', 'tointer': 'the circuit record of the row with 3rd minimum round record is wakefield park .'}], 'result': True, 'ind': 5, 'tostr': 'and { eq { nth_min { all_rows ; round ; 3 } ; 3 } ; eq { hop { nth_argmin { all_rows ; round ; 3 } ; circuit } ; wakefield park } } = true', 'tointer': 'the 3rd minimum round record of all rows is 3 . the circuit record of the row with 3rd minimum round record is wakefield park .'}
|
and { eq { nth_min { all_rows ; round ; 3 } ; 3 } ; eq { hop { nth_argmin { all_rows ; round ; 3 } ; circuit } ; wakefield park } } = true
|
the 3rd minimum round record of all rows is 3 . the circuit record of the row with 3rd minimum round record is wakefield park .
|
6
|
6
|
{'and_5': 5, 'result_6': 6, 'eq_1': 1, 'nth_min_0': 0, 'all_rows_7': 7, 'round_8': 8, '3_9': 9, '3_10': 10, 'str_eq_4': 4, 'str_hop_3': 3, 'nth_argmin_2': 2, 'all_rows_11': 11, 'round_12': 12, '3_13': 13, 'circuit_14': 14, 'wakefield park_15': 15}
|
{'and_5': 'and', 'result_6': 'true', 'eq_1': 'eq', 'nth_min_0': 'nth_min', 'all_rows_7': 'all_rows', 'round_8': 'round', '3_9': '3', '3_10': '3', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'nth_argmin_2': 'nth_argmin', 'all_rows_11': 'all_rows', 'round_12': 'round', '3_13': '3', 'circuit_14': 'circuit', 'wakefield park_15': 'wakefield park'}
|
{'and_5': [6], 'result_6': [], 'eq_1': [5], 'nth_min_0': [1], 'all_rows_7': [0], 'round_8': [0], '3_9': [0], '3_10': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'nth_argmin_2': [3], 'all_rows_11': [2], 'round_12': [2], '3_13': [2], 'circuit_14': [3], 'wakefield park_15': [4]}
|
['round', 'date', 'circuit', 'location', 'winning driver']
|
[['1', '21 - 24 february', 'adelaide street circuit', 'adelaide , south australia', 'craig baird'], ['2', '13 - 16 march', 'albert park street circuit', 'melbourne , victoria', 'craig baird'], ['3', '4 - 6 april', 'wakefield park', 'goulburn , new south wales', 'aaron caratti'], ['4', '9 - 11 may', 'barbagallo raceway', 'perth , western australia', 'craig baird'], ['5', '7 - 9 june', 'sandown raceway', 'melbourne , victoria', 'craig baird'], ['6', '4 - 6 july', 'queensland raceway', 'ipswich , queensland', 'craig baird'], ['7', '12 - 14 september', 'phillip island grand prix circuit', 'phillip island , victoria', 'craig baird'], ['8', '9 - 12 october', 'mount panorama circuit', 'bathurst , new south wales', 'dean fiore'], ['9', '23 - 26 october', 'surfers paradise street circuit', 'surfers paradise , queensland', 'james moffat']]
|
sheridan smith
|
https://en.wikipedia.org/wiki/Sheridan_Smith
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1644840-3.html.csv
|
comparative
|
sheridan smith won both the laurence olivier award and the theatregoers ' choice award for best actress in a musical in the year 2011 , for the same movie .
|
{'row_1': '1', 'row_2': '4', 'col': '3', 'col_other': '2', 'relation': 'equal', 'record_mentioned': 'yes', 'diff_result': None}
|
{'func': 'and', 'args': [{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'award', 'laurence olivier award'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose award record fuzzily matches to laurence olivier award .', 'tostr': 'filter_eq { all_rows ; award ; laurence olivier award }'}, 'category'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; award ; laurence olivier award } ; category }', 'tointer': 'select the rows whose award record fuzzily matches to laurence olivier award . take the category record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'award', "theatregoers ' choice award"], 'result': None, 'ind': 1, 'tointer': "select the rows whose award record fuzzily matches to theatregoers ' choice award .", 'tostr': "filter_eq { all_rows ; award ; theatregoers ' choice award }"}, 'category'], 'result': None, 'ind': 3, 'tostr': "hop { filter_eq { all_rows ; award ; theatregoers ' choice award } ; category }", 'tointer': "select the rows whose award record fuzzily matches to theatregoers ' choice award . take the category record of this row ."}], 'result': True, 'ind': 4, 'tostr': "eq { hop { filter_eq { all_rows ; award ; laurence olivier award } ; category } ; hop { filter_eq { all_rows ; award ; theatregoers ' choice award } ; category } }", 'tointer': "select the rows whose award record fuzzily matches to laurence olivier award . take the category record of this row . select the rows whose award record fuzzily matches to theatregoers ' choice award . take the category record of this row . the first record fuzzily matches to the second record ."}, {'func': 'and', 'args': [{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'award', 'laurence olivier award'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose award record fuzzily matches to laurence olivier award .', 'tostr': 'filter_eq { all_rows ; award ; laurence olivier award }'}, 'category'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; award ; laurence olivier award } ; category }', 'tointer': 'select the rows whose award record fuzzily matches to laurence olivier award . take the category record of this row .'}, 'best actress in a musical'], 'result': True, 'ind': 5, 'tostr': 'eq { hop { filter_eq { all_rows ; award ; laurence olivier award } ; category } ; best actress in a musical }', 'tointer': 'the category record of the first row is best actress in a musical .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'award', "theatregoers ' choice award"], 'result': None, 'ind': 1, 'tointer': "select the rows whose award record fuzzily matches to theatregoers ' choice award .", 'tostr': "filter_eq { all_rows ; award ; theatregoers ' choice award }"}, 'category'], 'result': None, 'ind': 3, 'tostr': "hop { filter_eq { all_rows ; award ; theatregoers ' choice award } ; category }", 'tointer': "select the rows whose award record fuzzily matches to theatregoers ' choice award . take the category record of this row ."}, 'best actress in a musical'], 'result': True, 'ind': 6, 'tostr': "eq { hop { filter_eq { all_rows ; award ; theatregoers ' choice award } ; category } ; best actress in a musical }", 'tointer': 'the category record of the second row is best actress in a musical .'}], 'result': True, 'ind': 7, 'tostr': "and { eq { hop { filter_eq { all_rows ; award ; laurence olivier award } ; category } ; best actress in a musical } ; eq { hop { filter_eq { all_rows ; award ; theatregoers ' choice award } ; category } ; best actress in a musical } }", 'tointer': 'the category record of the first row is best actress in a musical . the category record of the second row is best actress in a musical .'}], 'result': True, 'ind': 8, 'tostr': "and { eq { hop { filter_eq { all_rows ; award ; laurence olivier award } ; category } ; hop { filter_eq { all_rows ; award ; theatregoers ' choice award } ; category } } ; and { eq { hop { filter_eq { all_rows ; award ; laurence olivier award } ; category } ; best actress in a musical } ; eq { hop { filter_eq { all_rows ; award ; theatregoers ' choice award } ; category } ; best actress in a musical } } } = true", 'tointer': "select the rows whose award record fuzzily matches to laurence olivier award . take the category record of this row . select the rows whose award record fuzzily matches to theatregoers ' choice award . take the category record of this row . the first record fuzzily matches to the second record . the category record of the first row is best actress in a musical . the category record of the second row is best actress in a musical ."}
|
and { eq { hop { filter_eq { all_rows ; award ; laurence olivier award } ; category } ; hop { filter_eq { all_rows ; award ; theatregoers ' choice award } ; category } } ; and { eq { hop { filter_eq { all_rows ; award ; laurence olivier award } ; category } ; best actress in a musical } ; eq { hop { filter_eq { all_rows ; award ; theatregoers ' choice award } ; category } ; best actress in a musical } } } = true
|
select the rows whose award record fuzzily matches to laurence olivier award . take the category record of this row . select the rows whose award record fuzzily matches to theatregoers ' choice award . take the category record of this row . the first record fuzzily matches to the second record . the category record of the first row is best actress in a musical . the category record of the second row is best actress in a musical .
|
13
|
9
|
{'and_8': 8, 'result_9': 9, 'str_eq_4': 4, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_10': 10, 'award_11': 11, 'laurence olivier award_12': 12, 'category_13': 13, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_14': 14, 'award_15': 15, "theatregoers' choice award_16": 16, 'category_17': 17, 'and_7': 7, 'str_eq_5': 5, 'best actress in a musical_18': 18, 'str_eq_6': 6, 'best actress in a musical_19': 19}
|
{'and_8': 'and', 'result_9': 'true', 'str_eq_4': 'str_eq', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_10': 'all_rows', 'award_11': 'award', 'laurence olivier award_12': 'laurence olivier award', 'category_13': 'category', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_14': 'all_rows', 'award_15': 'award', "theatregoers' choice award_16": "theatregoers ' choice award", 'category_17': 'category', 'and_7': 'and', 'str_eq_5': 'str_eq', 'best actress in a musical_18': 'best actress in a musical', 'str_eq_6': 'str_eq', 'best actress in a musical_19': 'best actress in a musical'}
|
{'and_8': [9], 'result_9': [], 'str_eq_4': [8], 'str_hop_2': [4, 5], 'filter_str_eq_0': [2], 'all_rows_10': [0], 'award_11': [0], 'laurence olivier award_12': [0], 'category_13': [2], 'str_hop_3': [4, 6], 'filter_str_eq_1': [3], 'all_rows_14': [1], 'award_15': [1], "theatregoers' choice award_16": [1], 'category_17': [3], 'and_7': [8], 'str_eq_5': [7], 'best actress in a musical_18': [5], 'str_eq_6': [7], 'best actress in a musical_19': [6]}
|
['year', 'award', 'category', 'nominated work', 'result']
|
[['2009', 'laurence olivier award', 'best actress in a musical', 'little shop of horrors', 'nominated'], ['2010', 'evening standard award', 'best actress', 'legally blonde', 'nominated'], ['2011', 'laurence olivier award', 'best actress in a musical', 'legally blonde', 'won'], ['2011', "theatregoers ' choice award", 'best actress in a musical', 'legally blonde', 'won'], ['2011', 'evening standard award', 'best actress', 'flare path', 'won'], ['2011', 'broadwayworld uk award', 'best featured actress in a play', 'flare path', 'won'], ['2012', 'laurence olivier award', 'best performance in a supporting role', 'flare path', 'won'], ['2013', "theatregoers ' choice award", 'best actress in a play', 'hedda gabler', 'won'], ['2013', 'national television awards', 'outstanding drama performance ( female )', 'mrs biggs', 'nominated'], ['2013', 'royal television society awards', 'best actress', 'mrs biggs', 'nominated'], ['2013', 'british academy television award', 'best actress', 'mrs biggs', 'won'], ['2013', 'tv choice awards', 'best actress', 'mrs biggs', 'pending']]
|
anaprof 2004
|
https://en.wikipedia.org/wiki/ANAPROF_2004
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18704095-8.html.csv
|
comparative
|
at anaprof 2004 tauro scored more goals that alianza .
|
{'row_1': '2', 'row_2': '6', 'col': '6', 'col_other': '2', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None}
|
{'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'team', 'tauro'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose team record fuzzily matches to tauro .', 'tostr': 'filter_eq { all_rows ; team ; tauro }'}, 'goals scored'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; team ; tauro } ; goals scored }', 'tointer': 'select the rows whose team record fuzzily matches to tauro . take the goals scored record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'team', 'alianza'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose team record fuzzily matches to alianza .', 'tostr': 'filter_eq { all_rows ; team ; alianza }'}, 'goals scored'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; team ; alianza } ; goals scored }', 'tointer': 'select the rows whose team record fuzzily matches to alianza . take the goals scored record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; team ; tauro } ; goals scored } ; hop { filter_eq { all_rows ; team ; alianza } ; goals scored } } = true', 'tointer': 'select the rows whose team record fuzzily matches to tauro . take the goals scored record of this row . select the rows whose team record fuzzily matches to alianza . take the goals scored record of this row . the first record is greater than the second record .'}
|
greater { hop { filter_eq { all_rows ; team ; tauro } ; goals scored } ; hop { filter_eq { all_rows ; team ; alianza } ; goals scored } } = true
|
select the rows whose team record fuzzily matches to tauro . take the goals scored record of this row . select the rows whose team record fuzzily matches to alianza . take the goals scored record of this row . the first record is greater than the second record .
|
5
|
5
|
{'greater_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'team_7': 7, 'tauro_8': 8, 'goals scored_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'team_11': 11, 'alianza_12': 12, 'goals scored_13': 13}
|
{'greater_4': 'greater', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'team_7': 'team', 'tauro_8': 'tauro', 'goals scored_9': 'goals scored', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'team_11': 'team', 'alianza_12': 'alianza', 'goals scored_13': 'goals scored'}
|
{'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'team_7': [0], 'tauro_8': [0], 'goals scored_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'team_11': [1], 'alianza_12': [1], 'goals scored_13': [3]}
|
['place', 'team', 'played', 'draw', 'lost', 'goals scored', 'goals conceded', 'points']
|
[['1', 'árabe unido', '36', '5', '5', '63', '30', '83'], ['2', 'tauro', '36', '6', '9', '61', '22', '73'], ['3', 'san francisco', '36', '7', '9', '70', '31', '67'], ['4', 'el chorrillo', '36', '10', '7', '58', '51', '67'], ['5', 'plaza amador', '35', '8', '9', '59', '33', '62'], ['6', 'alianza', '36', '6', '18', '38', '53', '42'], ['7', 'atlético veragüense', '35', '7', '18', '38', '52', '37'], ['8', 'sporting coclé', '36', '9', '18', '42', '60', '36'], ['9', 'colón river', '36', '7', '22', '41', '78', '32'], ['10', 'pan de azúcar', '36', '7', '28', '22', '92', '10']]
|
1972 - 73 atlanta flames season
|
https://en.wikipedia.org/wiki/1972%E2%80%9373_Atlanta_Flames_season
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14038705-1.html.csv
|
count
|
two of the players drafted by the atlanta flames played for the regina pats previously .
|
{'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'regina pats', 'result': '2', 'col': '5', 'subset': None}
|
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'college / junior / club team', 'regina pats'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose college / junior / club team record fuzzily matches to regina pats .', 'tostr': 'filter_eq { all_rows ; college / junior / club team ; regina pats }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; college / junior / club team ; regina pats } }', 'tointer': 'select the rows whose college / junior / club team record fuzzily matches to regina pats . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; college / junior / club team ; regina pats } } ; 2 } = true', 'tointer': 'select the rows whose college / junior / club team record fuzzily matches to regina pats . the number of such rows is 2 .'}
|
eq { count { filter_eq { all_rows ; college / junior / club team ; regina pats } } ; 2 } = true
|
select the rows whose college / junior / club team record fuzzily matches to regina pats . the number of such rows is 2 .
|
3
|
3
|
{'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'college / junior / club team_5': 5, 'regina pats_6': 6, '2_7': 7}
|
{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'college / junior / club team_5': 'college / junior / club team', 'regina pats_6': 'regina pats', '2_7': '2'}
|
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'college / junior / club team_5': [0], 'regina pats_6': [0], '2_7': [2]}
|
['round', 'pick', 'player', 'nationality', 'college / junior / club team']
|
[['1', '2', 'jacques richard', 'canada', 'quebec remparts ( qmjhl )'], ['2', '18', 'dwight bialowas', 'canada', 'regina pats ( wcjhl )'], ['3', '34', 'jean lemieux', 'canada', 'sherbrooke castors ( qmjhl )'], ['4', '50', 'don martineau', 'canada', 'new westminster royals ( wcjhl )'], ['5', '78', 'john martin', 'canada', 'shawinigan bruins ( qmjhl )'], ['6', '82', 'frank blum', 'canada', 'sarnia sting ( sojhl )'], ['7', '98', 'scott smith', 'canada', 'regina pats ( wcjhl )'], ['8', '114', 'dave murphy', 'canada', 'hamilton red wings ( oha )'], ['9', '130', 'pierre roy', 'canada', 'quebec remparts ( qmjhl )']]
|
1998 pga tour
|
https://en.wikipedia.org/wiki/1998_PGA_Tour
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14611466-3.html.csv
|
majority
|
in the 1998 pga tour , for players from the united states , most of them participated in over 21 events .
|
{'scope': 'subset', 'col': '5', 'most_or_all': 'most', 'criterion': 'greater_than', 'value': '21', 'subset': {'col': '3', 'criterion': 'equal', 'value': 'united states'}}
|
{'func': 'most_greater', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'united states'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; country ; united states }', 'tointer': 'select the rows whose country record fuzzily matches to united states .'}, 'events', '21'], 'result': True, 'ind': 1, 'tointer': 'select the rows whose country record fuzzily matches to united states . for the events records of these rows , most of them are greater than 21 .', 'tostr': 'most_greater { filter_eq { all_rows ; country ; united states } ; events ; 21 } = true'}
|
most_greater { filter_eq { all_rows ; country ; united states } ; events ; 21 } = true
|
select the rows whose country record fuzzily matches to united states . for the events records of these rows , most of them are greater than 21 .
|
2
|
2
|
{'most_greater_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, 'country_4': 4, 'united states_5': 5, 'events_6': 6, '21_7': 7}
|
{'most_greater_1': 'most_greater', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'country_4': 'country', 'united states_5': 'united states', 'events_6': 'events', '21_7': '21'}
|
{'most_greater_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'country_4': [0], 'united states_5': [0], 'events_6': [1], '21_7': [1]}
|
['rank', 'player', 'country', 'earnings', 'events', 'wins']
|
[['1', 'david duval', 'united states', '2591031', '23', '4'], ['2', 'vijay singh', 'fiji', '2238998', '26', '2'], ['3', 'jim furyk', 'united states', '2054334', '28', '1'], ['4', 'tiger woods', 'united states', '1841117', '20', '1'], ['5', 'hal sutton', 'united states', '1838740', '30', '2']]
|
sat subject tests
|
https://en.wikipedia.org/wiki/SAT_subject_tests
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1637315-1.html.csv
|
superlative
|
the test with the highest mean score in the subject of mathematics is mathematics level 2 .
|
{'scope': 'subset', 'col_superlative': '3', 'row_superlative': '5', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1,2', 'subset': {'col': '2', 'criterion': 'equal', 'value': 'mathematics'}}
|
{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'subject', 'mathematics'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; subject ; mathematics }', 'tointer': 'select the rows whose subject record fuzzily matches to mathematics .'}, 'mean score'], 'result': None, 'ind': 1, 'tostr': 'argmax { filter_eq { all_rows ; subject ; mathematics } ; mean score }'}, 'test'], 'result': 'sat subject test in mathematics level 2', 'ind': 2, 'tostr': 'hop { argmax { filter_eq { all_rows ; subject ; mathematics } ; mean score } ; test }'}, 'sat subject test in mathematics level 2'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { argmax { filter_eq { all_rows ; subject ; mathematics } ; mean score } ; test } ; sat subject test in mathematics level 2 } = true', 'tointer': 'select the rows whose subject record fuzzily matches to mathematics . select the row whose mean score record of these rows is maximum . the test record of this row is sat subject test in mathematics level 2 .'}
|
eq { hop { argmax { filter_eq { all_rows ; subject ; mathematics } ; mean score } ; test } ; sat subject test in mathematics level 2 } = true
|
select the rows whose subject record fuzzily matches to mathematics . select the row whose mean score record of these rows is maximum . the test record of this row is sat subject test in mathematics level 2 .
|
4
|
4
|
{'str_eq_3': 3, 'result_4': 4, 'str_hop_2': 2, 'argmax_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'subject_6': 6, 'mathematics_7': 7, 'mean score_8': 8, 'test_9': 9, 'sat subject test in mathematics level 2_10': 10}
|
{'str_eq_3': 'str_eq', 'result_4': 'true', 'str_hop_2': 'str_hop', 'argmax_1': 'argmax', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'subject_6': 'subject', 'mathematics_7': 'mathematics', 'mean score_8': 'mean score', 'test_9': 'test', 'sat subject test in mathematics level 2_10': 'sat subject test in mathematics level 2'}
|
{'str_eq_3': [4], 'result_4': [], 'str_hop_2': [3], 'argmax_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'subject_6': [0], 'mathematics_7': [0], 'mean score_8': [1], 'test_9': [2], 'sat subject test in mathematics level 2_10': [3]}
|
['test', 'subject', 'mean score', 'standard deviation', 'number of students']
|
[['sat subject test in literature', 'literature', '576', '111', '120004'], ['sat subject test in united states history', 'us history', '608', '113', '126681'], ['sat subject test in world history', 'world history', '607', '118', '19688'], ['sat subject test in mathematics level 1', 'mathematics', '610', '100', '82827'], ['sat subject test in mathematics level 2', 'mathematics', '654', '107', '176472'], ['sat subject test in biology e / m', 'biology', 'e - 605 m - 635', '110 108', '86206 in total , 40076 ( e ) 46130 ( m )'], ['sat subject test in chemistry', 'chemistry', '648', '110', '76077'], ['sat subject test in physics', 'physics', '656', '105', '49608'], ['sat subject test in chinese with listening', 'chinese', '758', '67', '7294'], ['sat subject test in french', 'french', '622', '123', '10391'], ['sat subject test in french with listening', 'french', '646', '117', '2370'], ['sat subject test in german', 'german', '622', '135', '777'], ['sat subject test in german with listening', 'german', '611', '122', '770'], ['sat subject test in modern hebrew', 'modern hebrew', '623', '140', '491'], ['sat subject test in italian', 'italian', '666', '122', '737'], ['sat subject test in japanese with listening', 'japanese', '684', '113', '1966'], ['sat subject test in korean with listening', 'korean', '767', '57', '4273'], ['sat subject test in latin', 'latin', '611', '107', '3010'], ['sat subject test in spanish', 'spanish', '647', '117', '37762'], ['sat subject test in spanish with listening', 'spanish', '663', '107', '6399']]
|
2002 senior pga tour
|
https://en.wikipedia.org/wiki/2002_Senior_PGA_Tour
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11603116-4.html.csv
|
majority
|
all of the players in the 2002 senior pga tour were from the united states .
|
{'scope': 'all', 'col': '3', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'united states', 'subset': None}
|
{'func': 'all_str_eq', 'args': ['all_rows', 'country', 'united states'], 'result': True, 'ind': 0, 'tointer': 'for the country records of all rows , all of them fuzzily match to united states .', 'tostr': 'all_eq { all_rows ; country ; united states } = true'}
|
all_eq { all_rows ; country ; united states } = true
|
for the country records of all rows , all of them fuzzily match to united states .
|
1
|
1
|
{'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'country_3': 3, 'united states_4': 4}
|
{'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'country_3': 'country', 'united states_4': 'united states'}
|
{'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'country_3': [0], 'united states_4': [0]}
|
['rank', 'player', 'country', 'earnings', 'wins']
|
[['1', 'hale irwin', 'united states', '16950178', '36'], ['2', 'gil morgan', 'united states', '11092593', '21'], ['3', 'jim colbert', 'united states', '10840374', '20'], ['4', 'dave stockton', 'united states', '9735814', '14'], ['5', 'lee trevino', 'united states', '9616404', '29']]
|
fibt world championships 2008
|
https://en.wikipedia.org/wiki/FIBT_World_Championships_2008
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13566976-7.html.csv
|
aggregation
|
a total of 18 medals were awarded in the 2008 fibt world championships .
|
{'scope': 'all', 'col': '6', 'type': 'sum', 'result': '18', 'subset': None}
|
{'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'total'], 'result': '18', 'ind': 0, 'tostr': 'sum { all_rows ; total }'}, '18'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; total } ; 18 } = true', 'tointer': 'the sum of the total record of all rows is 18 .'}
|
round_eq { sum { all_rows ; total } ; 18 } = true
|
the sum of the total record of all rows is 18 .
|
2
|
2
|
{'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'total_4': 4, '18_5': 5}
|
{'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'total_4': 'total', '18_5': '18'}
|
{'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'total_4': [0], '18_5': [1]}
|
['rank', 'nation', 'gold', 'silver', 'bronze', 'total']
|
[['1', 'germany', '5', '2', '4', '11'], ['2', 'canada', '0', '2', '0', '2'], ['3', 'united states', '0', '1', '1', '2'], ['4', 'russia', '0', '1', '1', '2'], ['5', 'united kingdom', '1', '0', '0', '1']]
|
northwestern conference ( ihsaa )
|
https://en.wikipedia.org/wiki/Northwestern_Conference_%28IHSAA%29
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18941359-2.html.csv
|
unique
|
in the northwestern conference , when the previous conference was northern indiana , the only time the mascot was roughriders was when the school was east chicago roosevelt .
|
{'scope': 'subset', 'row': '1', 'col': '3', 'col_other': '1', 'criterion': 'equal', 'value': 'roughriders', 'subset': {'col': '6', 'criterion': 'equal', 'value': 'northern indiana'}}
|
{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'previous conference', 'northern indiana'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; previous conference ; northern indiana }', 'tointer': 'select the rows whose previous conference record fuzzily matches to northern indiana .'}, 'mascot', 'roughriders'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose previous conference record fuzzily matches to northern indiana . among these rows , select the rows whose mascot record fuzzily matches to roughriders .', 'tostr': 'filter_eq { filter_eq { all_rows ; previous conference ; northern indiana } ; mascot ; roughriders }'}], 'result': True, 'ind': 2, 'tostr': 'only { filter_eq { filter_eq { all_rows ; previous conference ; northern indiana } ; mascot ; roughriders } }', 'tointer': 'select the rows whose previous conference record fuzzily matches to northern indiana . among these rows , select the rows whose mascot record fuzzily matches to roughriders . 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', 'previous conference', 'northern indiana'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; previous conference ; northern indiana }', 'tointer': 'select the rows whose previous conference record fuzzily matches to northern indiana .'}, 'mascot', 'roughriders'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose previous conference record fuzzily matches to northern indiana . among these rows , select the rows whose mascot record fuzzily matches to roughriders .', 'tostr': 'filter_eq { filter_eq { all_rows ; previous conference ; northern indiana } ; mascot ; roughriders }'}, 'school'], 'result': 'east chicago roosevelt', 'ind': 3, 'tostr': 'hop { filter_eq { filter_eq { all_rows ; previous conference ; northern indiana } ; mascot ; roughriders } ; school }'}, 'east chicago roosevelt'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { filter_eq { filter_eq { all_rows ; previous conference ; northern indiana } ; mascot ; roughriders } ; school } ; east chicago roosevelt }', 'tointer': 'the school record of this unqiue row is east chicago roosevelt .'}], 'result': True, 'ind': 5, 'tostr': 'and { only { filter_eq { filter_eq { all_rows ; previous conference ; northern indiana } ; mascot ; roughriders } } ; eq { hop { filter_eq { filter_eq { all_rows ; previous conference ; northern indiana } ; mascot ; roughriders } ; school } ; east chicago roosevelt } } = true', 'tointer': 'select the rows whose previous conference record fuzzily matches to northern indiana . among these rows , select the rows whose mascot record fuzzily matches to roughriders . there is only one such row in the table . the school record of this unqiue row is east chicago roosevelt .'}
|
and { only { filter_eq { filter_eq { all_rows ; previous conference ; northern indiana } ; mascot ; roughriders } } ; eq { hop { filter_eq { filter_eq { all_rows ; previous conference ; northern indiana } ; mascot ; roughriders } ; school } ; east chicago roosevelt } } = true
|
select the rows whose previous conference record fuzzily matches to northern indiana . among these rows , select the rows whose mascot record fuzzily matches to roughriders . there is only one such row in the table . the school record of this unqiue row is east chicago roosevelt .
|
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, 'previous conference_8': 8, 'northern indiana_9': 9, 'mascot_10': 10, 'roughriders_11': 11, 'str_eq_4': 4, 'str_hop_3': 3, 'school_12': 12, 'east chicago roosevelt_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', 'previous conference_8': 'previous conference', 'northern indiana_9': 'northern indiana', 'mascot_10': 'mascot', 'roughriders_11': 'roughriders', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'school_12': 'school', 'east chicago roosevelt_13': 'east chicago roosevelt'}
|
{'and_5': [6], 'result_6': [], 'only_2': [5], 'filter_str_eq_1': [2, 3], 'filter_str_eq_0': [1], 'all_rows_7': [0], 'previous conference_8': [0], 'northern indiana_9': [0], 'mascot_10': [1], 'roughriders_11': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'school_12': [3], 'east chicago roosevelt_13': [4]}
|
['school', 'city', 'mascot', 'county', 'year joined', 'previous conference', 'year left', 'conference joined']
|
[['east chicago roosevelt', 'east chicago', 'roughriders', '45 lake', '1963', 'northern indiana', '1968', 'indiana lake shore'], ['east chicago washington', 'east chicago', 'senators', '45 lake', '1963', 'northern indiana', '1968', 'indiana lake shore'], ['gary emerson', 'gary', 'tornado', '45 lake', '1963', 'northern indiana', '1981', 'none ( school closed , reopened as emerson vpa )'], ['gary froebel', 'gary', 'blue devils', '45 lake', '1963', 'northern indiana', '1969', 'none ( school became ms , closed 1977 )'], ['gary mann', 'gary', 'horsemen', '45 lake', '1963', 'northern indiana', '2004', 'none ( school closed )'], ['gary tolleston', 'gary', 'blue raiders', '45 lake', '1963', 'northern indiana', '1969', 'none ( school became ms , closed 2007 )'], ['hammond', 'hammond', 'wildcats', '45 lake', '1963', 'northern indiana', '1968', 'indiana lake shore'], ['hammond clark', 'hammond', 'pioneers', '45 lake', '1963', 'northern indiana', '1968', 'indiana lake shore'], ['hammond tech', 'hammond', 'tigers', '45 lake', '1963', 'northern indiana', '1968', 'indiana lake shore'], ['valparaiso', 'valparaiso', 'vikings', '64 porter', '1963', 'northern indiana', '1968', 'independents'], ['whiting', 'whiting', 'oilers', '45 lake', '1963', 'northern indiana', '1968', 'indiana lake shore'], ['hammond gavit', 'hammond', 'gladiators', '45 lake', '1966', 'independents', '1968', 'indiana lake shore'], ['hammond morton', 'hammond', 'governors', '45 lake', '1966', 'independents', '1968', 'indiana lake shore'], ['hobart', 'hobart', 'brickies', '45 lake', '1966', 'independents', '1968', 'independents'], ['andrean', 'gary', '59ers', '45 lake', '1968', 'independents', '1975', 'independents ( school moved to merrillville )'], ['gary wirt', 'gary', 'troopers', '45 lake', '1970', 'calumet', '2009', 'school closed']]
|
1943 vfl season
|
https://en.wikipedia.org/wiki/1943_VFL_season
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10808346-8.html.csv
|
superlative
|
during the 1943 vfl season , essendon had the highest scoring game .
|
{'scope': 'all', 'col_superlative': '4', 'row_superlative': '5', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '3', 'subset': None}
|
{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'away team score'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; away team score }'}, 'away team'], 'result': 'essendon', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; away team score } ; away team }'}, 'essendon'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; away team score } ; away team } ; essendon } = true', 'tointer': 'select the row whose away team score record of all rows is maximum . the away team record of this row is essendon .'}
|
eq { hop { argmax { all_rows ; away team score } ; away team } ; essendon } = true
|
select the row whose away team score record of all rows is maximum . the away team record of this row is essendon .
|
3
|
3
|
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'away team score_5': 5, 'away team_6': 6, 'essendon_7': 7}
|
{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'away team score_5': 'away team score', 'away team_6': 'away team', 'essendon_7': 'essendon'}
|
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'away team score_5': [0], 'away team_6': [1], 'essendon_7': [2]}
|
['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date']
|
[['footscray', '10.11 ( 71 )', 'south melbourne', '6.14 ( 50 )', 'western oval', '7500', '26 june 1943'], ['collingwood', '10.21 ( 81 )', 'melbourne', '13.9 ( 87 )', 'victoria park', '5000', '26 june 1943'], ['carlton', '15.16 ( 106 )', 'fitzroy', '9.13 ( 67 )', 'princes park', '12000', '26 june 1943'], ['richmond', '15.16 ( 106 )', 'hawthorn', '8.14 ( 62 )', 'punt road oval', '16000', '26 june 1943'], ['st kilda', '15.8 ( 98 )', 'essendon', '20.19 ( 139 )', 'toorak park', '6000', '26 june 1943']]
|
list of royal pains episodes
|
https://en.wikipedia.org/wiki/List_of_Royal_Pains_episodes
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-23117208-5.html.csv
|
superlative
|
the episode entitled about face had the most viewers in that season of royal pains .
|
{'scope': 'all', 'col_superlative': '8', 'row_superlative': '6', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '3', 'subset': None}
|
{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'viewers ( millions )'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; viewers ( millions ) }'}, 'title'], 'result': 'about face', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; viewers ( millions ) } ; title }'}, 'about face'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; viewers ( millions ) } ; title } ; about face } = true', 'tointer': 'select the row whose viewers ( millions ) record of all rows is maximum . the title record of this row is about face .'}
|
eq { hop { argmax { all_rows ; viewers ( millions ) } ; title } ; about face } = true
|
select the row whose viewers ( millions ) record of all rows is maximum . the title record of this row is about face .
|
3
|
3
|
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'viewers (millions)_5': 5, 'title_6': 6, 'about face_7': 7}
|
{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'viewers (millions)_5': 'viewers ( millions )', 'title_6': 'title', 'about face_7': 'about face'}
|
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'viewers (millions)_5': [0], 'title_6': [1], 'about face_7': [2]}
|
['no in series', 'no in season', 'title', 'directed by', 'written by', 'original air date', 'prod code', 'viewers ( millions )']
|
[['47', '1', 'after the fireworks', 'emile levisetti', 'andrew lenchewski', 'june 6 , 2012', 'rp401', '3.95'], ['48', '2', 'imperfect storm', 'emile levisetti', 'michael rauch', 'june 13 , 2012', 'rp402', '4.14'], ['49', '3', 'a guesthouse divided', 'jay chandrasekhar', 'constance m burge & jack bernstein', 'june 20 , 2012', 'rp403', '3.87'], ['50', '4', 'dawn of the med', 'michael watkins', 'carol flint & jon sherman', 'june 27 , 2012', 'rp404', '4.18'], ['51', '5', 'you give love a bad name', 'michael rauch', 'michael rauch & jessica ball', 'july 11 , 2012', 'rp405', '4.15'], ['52', '6', 'about face', 'matthew penn', 'constance m burge', 'july 18 , 2012', 'rp406', '4.25'], ['53', '7', 'fools russian', 'allison liddi - brown', 'carol flint', 'july 25 , 2012', 'rp407', '3.92'], ['54', '8', 'manimal', 'mark feuerstein', 'jon sherman', 'august 1 , 2012', 'rp408', '2.96'], ['55', '9', 'business and pleasure', 'constantine makris', 'andrew lenchewski & jeff drayer', 'august 15 , 2012', 'rp409', '3.95'], ['56', '10', "who 's your daddy", 'michael watkins', 'michael rauch & jon sherman', 'august 22 , 2012', 'rp410', '3.91'], ['58', '12', 'hurts like a mother', 'tawnia mckiernan', 'jessica ball & aubrey karr', 'september 5 , 2012', 'rp412', '3.59']]
|
1964 american football league draft
|
https://en.wikipedia.org/wiki/1964_American_Football_League_Draft
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18652117-1.html.csv
|
unique
|
tony lorick was the only player picked in the 1964 american football league draft from arizona state college .
|
{'scope': 'all', 'row': '7', 'col': '5', 'col_other': '3', 'criterion': 'equal', 'value': 'arizona state', 'subset': None}
|
{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'college', 'arizona state'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose college record fuzzily matches to arizona state .', 'tostr': 'filter_eq { all_rows ; college ; arizona state }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; college ; arizona state } }', 'tointer': 'select the rows whose college record fuzzily matches to arizona state . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'college', 'arizona state'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose college record fuzzily matches to arizona state .', 'tostr': 'filter_eq { all_rows ; college ; arizona state }'}, 'player'], 'result': 'tony lorick', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; college ; arizona state } ; player }'}, 'tony lorick'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; college ; arizona state } ; player } ; tony lorick }', 'tointer': 'the player record of this unqiue row is tony lorick .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; college ; arizona state } } ; eq { hop { filter_eq { all_rows ; college ; arizona state } ; player } ; tony lorick } } = true', 'tointer': 'select the rows whose college record fuzzily matches to arizona state . there is only one such row in the table . the player record of this unqiue row is tony lorick .'}
|
and { only { filter_eq { all_rows ; college ; arizona state } } ; eq { hop { filter_eq { all_rows ; college ; arizona state } ; player } ; tony lorick } } = true
|
select the rows whose college record fuzzily matches to arizona state . there is only one such row in the table . the player record of this unqiue row is tony lorick .
|
6
|
5
|
{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'college_7': 7, 'arizona state_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'player_9': 9, 'tony lorick_10': 10}
|
{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'college_7': 'college', 'arizona state_8': 'arizona state', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'player_9': 'player', 'tony lorick_10': 'tony lorick'}
|
{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'college_7': [0], 'arizona state_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'player_9': [2], 'tony lorick_10': [3]}
|
['pick', 'team', 'player', 'position', 'college']
|
[['1', 'boston', 'jack concannon', 'qb', 'boston college'], ['2', 'kansas city', 'pete beathard', 'qb', 'usc'], ['3', 'new york', 'matt snell', 'rb', 'ohio state'], ['4', 'denver', 'bob brown', 'ot', 'nebraska'], ['5', 'buffalo', 'carl eller', 'de', 'minnesota'], ['6', 'houston', 'scott appleton', 'dt', 'texas'], ['7', 'oakland', 'tony lorick', 'rb', 'arizona state'], ['8', 'san diego', 'ted davis', 'lb', 'georgia tech']]
|
blue ridge hockey conference
|
https://en.wikipedia.org/wiki/Blue_Ridge_Hockey_Conference
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16404837-4.html.csv
|
aggregation
|
1881 is the average founding year for all the colleges in the blue ridge hockey conference .
|
{'scope': 'all', 'col': '3', 'type': 'average', 'result': '1881', 'subset': None}
|
{'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'founded'], 'result': '1881', 'ind': 0, 'tostr': 'avg { all_rows ; founded }'}, '1881'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; founded } ; 1881 } = true', 'tointer': 'the average of the founded record of all rows is 1881 .'}
|
round_eq { avg { all_rows ; founded } ; 1881 } = true
|
the average of the founded record of all rows is 1881 .
|
2
|
2
|
{'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'founded_4': 4, '1881_5': 5}
|
{'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'founded_4': 'founded', '1881_5': '1881'}
|
{'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'founded_4': [0], '1881_5': [1]}
|
['school', 'location', 'founded', 'affiliation', 'nickname']
|
[['james madison university', 'harrisonburg , va', '1908', 'public', 'dukes'], ['old dominion university', 'norfolk , va', '1930', 'public', 'monarchs'], ['radford university', 'radford , va', '1910', 'public', 'highlanders'], ['university of virginia', 'charlottesville , va', '1819', 'public flagship', 'cavaliers'], ['virginia commonwealth university', 'richmond , va', '1838', 'public', 'rams']]
|
2008 indiana fever season
|
https://en.wikipedia.org/wiki/2008_Indiana_Fever_season
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-17104539-9.html.csv
|
superlative
|
theconseco fieldhouse was the first location used by indiana fever in the 2008 season .
|
{'scope': 'all', 'col_superlative': '2', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '8', '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 }'}, 'location / attendance'], 'result': 'conseco fieldhouse 8214', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; date } ; location / attendance }'}, 'conseco fieldhouse 8214'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmin { all_rows ; date } ; location / attendance } ; conseco fieldhouse 8214 } = true', 'tointer': 'select the row whose date record of all rows is minimum . the location / attendance record of this row is conseco fieldhouse 8214 .'}
|
eq { hop { argmin { all_rows ; date } ; location / attendance } ; conseco fieldhouse 8214 } = true
|
select the row whose date record of all rows is minimum . the location / attendance record of this row is conseco fieldhouse 8214 .
|
3
|
3
|
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'date_5': 5, 'location / attendance_6': 6, 'conseco fieldhouse 8214_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', 'location / attendance_6': 'location / attendance', 'conseco fieldhouse 8214_7': 'conseco fieldhouse 8214'}
|
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'date_5': [0], 'location / attendance_6': [1], 'conseco fieldhouse 8214_7': [2]}
|
['game', 'date', 'opponent', 'score', 'high points', 'high rebounds', 'high assists', 'location / attendance', 'record']
|
[['6', 'june 7', 'houston', 'w 84 - 75', 'douglas ( 20 )', 'hoffman ( 10 )', 'douglas , hoffman ( 4 )', 'conseco fieldhouse 8214', '4 - 2'], ['7', 'june 11', 'san antonio', 'l 64 - 53', 'douglas , white ( 13 )', 'hoffman ( 9 )', 'douglas ( 4 )', 'at & t center 6262', '4 - 3'], ['8', 'june 13', 'atlanta', 'w 76 - 67', 'white ( 21 )', 'sutton - brown ( 12 )', 'douglas ( 7 )', 'philips arena 8167', '5 - 3'], ['9', 'june 15', 'san antonio', 'l 70 - 60', 'douglas ( 17 )', 'hoffman ( 10 )', 'hoffman ( 4 )', 'conseco fieldhouse 7412', '5 - 4'], ['10', 'june 18', 'new york', 'w 83 - 69', 'douglas ( 16 )', 'douglas ( 8 )', 'douglas ( 5 )', 'conseco fieldhouse 6333', '6 - 4'], ['11', 'june 20', 'seattle', 'l 78 - 70', 'sutton - brown ( 14 )', 'hoffman ( 10 )', 'catchings , white ( 4 )', 'keyarena 7393', '6 - 5'], ['12', 'june 22', 'los angeles', 'l 77 - 63', 'catchings ( 17 )', 'hoffman ( 10 )', 'catchings ( 3 )', 'staples center 9463', '6 - 6'], ['13', 'june 24', 'sacramento', 'w 78 - 73', 'hoffman ( 23 )', 'hoffman ( 13 )', 'bevilaqua , feaster , ebony hoffman ( 3 )', 'conseco fieldhouse 6020', '7 - 6'], ['14', 'june 26', 'new york', 'l 102 - 96 ( 3ot )', 'hoffman ( 26 )', 'sutton - brown ( 15 )', 'bevilaqua ( 5 )', 'madison square garden 7899', '7 - 7']]
|
1981 kansas city chiefs season
|
https://en.wikipedia.org/wiki/1981_Kansas_City_Chiefs_season
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12536490-1.html.csv
|
unique
|
bob gagliano was the only quarterback that kansas city chiefs drafted in the 1981 season .
|
{'scope': 'all', 'row': '14', 'col': '4', 'col_other': '3', 'criterion': 'equal', 'value': 'quarterback', 'subset': None}
|
{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'position', 'quarterback'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose position record fuzzily matches to quarterback .', 'tostr': 'filter_eq { all_rows ; position ; quarterback }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; position ; quarterback } }', 'tointer': 'select the rows whose position record fuzzily matches to quarterback . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'position', 'quarterback'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose position record fuzzily matches to quarterback .', 'tostr': 'filter_eq { all_rows ; position ; quarterback }'}, 'name'], 'result': 'bob gagliano', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; position ; quarterback } ; name }'}, 'bob gagliano'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; position ; quarterback } ; name } ; bob gagliano }', 'tointer': 'the name record of this unqiue row is bob gagliano .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; position ; quarterback } } ; eq { hop { filter_eq { all_rows ; position ; quarterback } ; name } ; bob gagliano } } = true', 'tointer': 'select the rows whose position record fuzzily matches to quarterback . there is only one such row in the table . the name record of this unqiue row is bob gagliano .'}
|
and { only { filter_eq { all_rows ; position ; quarterback } } ; eq { hop { filter_eq { all_rows ; position ; quarterback } ; name } ; bob gagliano } } = true
|
select the rows whose position record fuzzily matches to quarterback . there is only one such row in the table . the name record of this unqiue row is bob gagliano .
|
6
|
5
|
{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'position_7': 7, 'quarterback_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'name_9': 9, 'bob gagliano_10': 10}
|
{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'position_7': 'position', 'quarterback_8': 'quarterback', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'name_9': 'name', 'bob gagliano_10': 'bob gagliano'}
|
{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'position_7': [0], 'quarterback_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'name_9': [2], 'bob gagliano_10': [3]}
|
['round', 'pick', 'name', 'position', 'college']
|
[['1', '14', 'willie scott', 'tight end', 'south carolina'], ['2', '41', 'joe delaney', 'running back', 'northwestern state'], ['3', '70', 'marvin harvey', 'tight end', 'southern mississippi'], ['3', '75', 'roger taylor', 'tackle', 'oklahoma state'], ['3', '78', 'lloyd burruss', 'defensive back', 'maryland'], ['4', '97', 'ron washington', 'wide receiver', 'arizona state'], ['5', '124', 'todd thomas', 'center', 'north dakota'], ['6', '153', 'dock luckie', 'tackle', 'florida'], ['7', '180', 'billy jackson', 'running back', 'alabama'], ['8', '206', 'david dorn', 'wide receiver', 'rutgers'], ['9', '237', 'anthony vereen', 'defensive back', 'southeastern louisiana'], ['10', '262', 'les studdard', 'center', 'texas'], ['11', '289', 'frank case', 'defensive end', 'penn state'], ['12', '319', 'bob gagliano', 'quarterback', 'utah state']]
|
2001 masters tournament
|
https://en.wikipedia.org/wiki/2001_Masters_Tournament
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16514667-2.html.csv
|
majority
|
most of the players in the 2001 masters tournament were from the united states .
|
{'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'united states', 'subset': None}
|
{'func': 'most_str_eq', 'args': ['all_rows', 'country', 'united states'], 'result': True, 'ind': 0, 'tointer': 'for the country records of all rows , most of them fuzzily match to united states .', 'tostr': 'most_eq { all_rows ; country ; united states } = true'}
|
most_eq { all_rows ; country ; united states } = true
|
for the country records of all rows , most of them fuzzily match to united states .
|
1
|
1
|
{'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'country_3': 3, 'united states_4': 4}
|
{'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'country_3': 'country', 'united states_4': 'united states'}
|
{'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'country_3': [0], 'united states_4': [0]}
|
['place', 'player', 'country', 'score', 'to par']
|
[['1', 'chris dimarco', 'united states', '65', '- 7'], ['t2', 'ángel cabrera', 'argentina', '66', '- 6'], ['t2', 'steve stricker', 'united states', '66', '- 6'], ['t4', 'john huston', 'united states', '67', '- 5'], ['t4', 'lee janzen', 'united states', '67', '- 5'], ['t4', 'phil mickelson', 'united states', '67', '- 5'], ['t7', 'james driscoll ( a )', 'united states', '68', '- 4'], ['t7', 'miguel ángel jiménez', 'spain', '68', '- 4'], ['t7', 'chris perry', 'united states', '68', '- 4'], ['t7', 'kirk triplett', 'united states', '68', '- 4']]
|
j. l. van den heuvel orgelbouw
|
https://en.wikipedia.org/wiki/J._L._van_den_Heuvel_Orgelbouw
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11898040-1.html.csv
|
ordinal
|
the j. l. van den heuvel orgelbouw organ in the copenhagen concert hall is the second largest in size .
|
{'row': '13', 'col': '5', 'order': '2', 'col_other': '4', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None}
|
{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'size', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; size ; 2 }'}, 'building'], 'result': 'copenhagen concert hall', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; size ; 2 } ; building }'}, 'copenhagen concert hall'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; size ; 2 } ; building } ; copenhagen concert hall } = true', 'tointer': 'select the row whose size record of all rows is 2nd maximum . the building record of this row is copenhagen concert hall .'}
|
eq { hop { nth_argmax { all_rows ; size ; 2 } ; building } ; copenhagen concert hall } = true
|
select the row whose size record of all rows is 2nd maximum . the building record of this row is copenhagen concert hall .
|
3
|
3
|
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'size_5': 5, '2_6': 6, 'building_7': 7, 'copenhagen concert hall_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', 'size_5': 'size', '2_6': '2', 'building_7': 'building', 'copenhagen concert hall_8': 'copenhagen concert hall'}
|
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'size_5': [0], '2_6': [0], 'building_7': [1], 'copenhagen concert hall_8': [2]}
|
['date', 'country', 'place', 'building', 'size']
|
[['1970', 'nl', 'ridderkerk', 'singelkerk', 'iiip / 32'], ['1979', 'nl', 'katwijk aan zee', 'nieuwe kerk', 'ivp / 80'], ['1989', 'fr', 'paris', 'église saint - eustache', 'vp / 101'], ['1992', 'ch', 'geneva', 'victoria hall', 'ivp / 71'], ['1993', 'gb', 'london', "royal academy of music , duke 's hall", 'iip / 24'], ['1994', 'usa', 'new york city', 'church of the holy apostles', 'iiip / 32'], ['1995', 'se', 'stockholm', 'kungliga musikhögskolan', 'iiip / 25'], ['1995', 'nl', 'rotterdam', 'maranatha kerk', 'iiip / 25'], ['1997', 'de', 'berlin', 'st franziskus kirche', 'iiip / 51'], ['2000', 'se', 'stockholm', 'katarina kyrka', 'iiip / 62'], ['2000', 'nl', 'the hague', 'residence of ben van oosten', 'iiip / 16'], ['2000', 'fi', 'mänttä', 'church', 'iiip / 30'], ['2006', 'dk', 'copenhagen', 'copenhagen concert hall', 'ivp / 91']]
|
hadise ( album )
|
https://en.wikipedia.org/wiki/Hadise_%28album%29
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16431493-2.html.csv
|
ordinal
|
" my man and the devil on his shoulder " is the longest track on the album hadise .
|
{'row': '4', 'col': '5', 'order': '1', 'col_other': '2', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None}
|
{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'length', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; length ; 1 }'}, 'title'], 'result': 'my man and the devil on his shoulder', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; length ; 1 } ; title }'}, 'my man and the devil on his shoulder'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; length ; 1 } ; title } ; my man and the devil on his shoulder } = true', 'tointer': 'select the row whose length record of all rows is 1st maximum . the title record of this row is my man and the devil on his shoulder .'}
|
eq { hop { nth_argmax { all_rows ; length ; 1 } ; title } ; my man and the devil on his shoulder } = true
|
select the row whose length record of all rows is 1st maximum . the title record of this row is my man and the devil on his shoulder .
|
3
|
3
|
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'length_5': 5, '1_6': 6, 'title_7': 7, 'my man and the devil on his shoulder_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', 'length_5': 'length', '1_6': '1', 'title_7': 'title', 'my man and the devil on his shoulder_8': 'my man and the devil on his shoulder'}
|
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'length_5': [0], '1_6': [0], 'title_7': [1], 'my man and the devil on his shoulder_8': [2]}
|
['track', 'title', 'songwriter ( s )', 'producer ( s )', 'length']
|
[['1', 'intro', 'hadise açıkgöz', 'yves jongen', '0:52'], ['2', 'deli oğlan', 'sezen aksu', 'hadise açıkgöz , yves jongen', '3:12'], ['3', 'aşkkolik', 'deniz erten', 'özgür buldum', '4:08'], ['4', 'my man and the devil on his shoulder', 'hadise açıkgöz , yves gallard', 'hadise açıkgöz , yves gallard', '4:35'], ['5', 'my body', 'hadise açıkgöz , yves jongen', 'yves jongen', '3:06'], ['6', 'prisoner', 'hadise açıkgöz , stefaan fernande , elio deepcore', 'hadise açıkgöz , stefaan fernande , elio deepcore', '3:52'], ['7', 'a good kiss', 'hadise açıkgöz , yves jongen', 'hadise açıkgöz , yves jongen', '3:12'], ['8', 'all together', 'hadise açıkgöz , yves jongen', 'hadise açıkgöz , yves jongen', '3:07'], ['9', 'men chase women choose', 'hadise açıkgöz , yves jongen', 'hadise açıkgöz , yves jongen', '3:08'], ['10', 'creep', 'hadise açıkgöz , stefaan fernande , stano simor', 'hadise açıkgöz , stefaan fernande , stano simor', '3:44'], ['11', 'good morning baby', 'yves jongen', 'yves jongen', '4:16'], ['12', "do n't ask", 'hadise açıkgöz , yves jongen', 'hadise açıkgöz , yves jongen', '3:00'], ['13', 'intimate', 'hadise açıkgöz , stefaan fernande , luca chiaravall', 'hadise açıkgöz , stefaan fernande , luca chiaravall', '3:37'], ['14', 'busy bee', 'hadise açıkgöz , yves jongen', 'hadise açıkgöz , yves jongen', '3:32'], ['15', 'comfort zone', 'hadise açıkgöz , yves jongen', 'hadise açıkgöz , yves jongen', '4:09'], ['16', 'who am i', 'hadise açıkgöz , yves jongen', 'hadise açıkgöz , yves jongen', '3:14'], ['17', 'a song for my mother', 'hadise açıkgöz , stefaan fernande , luca chiaravall', 'hadise açıkgöz , stefaan fernande , luca chiaravall', '3:32']]
|
1968 vfl season
|
https://en.wikipedia.org/wiki/1968_VFL_season
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10808933-18.html.csv
|
aggregation
|
crowds totaling 139,789 attended games during the 1968 vfl season .
|
{'scope': 'all', 'col': '6', 'type': 'sum', 'result': '139,789', 'subset': None}
|
{'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'crowd'], 'result': '139,789', 'ind': 0, 'tostr': 'sum { all_rows ; crowd }'}, '139,789'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; crowd } ; 139,789 } = true', 'tointer': 'the sum of the crowd record of all rows is 139,789 .'}
|
round_eq { sum { all_rows ; crowd } ; 139,789 } = true
|
the sum of the crowd record of all rows is 139,789 .
|
2
|
2
|
{'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'crowd_4': 4, '139,789_5': 5}
|
{'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'crowd_4': 'crowd', '139,789_5': '139,789'}
|
{'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'crowd_4': [0], '139,789_5': [1]}
|
['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date']
|
[['hawthorn', '14.13 ( 97 )', 'melbourne', '8.11 ( 59 )', 'glenferrie oval', '14359', '17 august 1968'], ['footscray', '6.8 ( 44 )', 'st kilda', '16.13 ( 109 )', 'western oval', '15211', '17 august 1968'], ['fitzroy', '10.12 ( 72 )', 'geelong', '14.10 ( 94 )', 'princes park', '9782', '17 august 1968'], ['south melbourne', '9.14 ( 68 )', 'north melbourne', '11.13 ( 79 )', 'lake oval', '7412', '17 august 1968'], ['richmond', '10.14 ( 74 )', 'essendon', '7.12 ( 54 )', 'mcg', '68529', '17 august 1968'], ['collingwood', '10.10 ( 70 )', 'carlton', '16.11 ( 107 )', 'victoria park', '24496', '17 august 1968']]
|
2008 indiana fever season
|
https://en.wikipedia.org/wiki/2008_Indiana_Fever_season
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17104539-10.html.csv
|
ordinal
|
the indiana fever 's game against new york liberty outdoor classic recorded their highest attendance of the 2008 season .
|
{'row': '7', '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 }'}, 'opponent'], 'result': 'new york liberty outdoor classic', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; location / attendance ; 1 } ; opponent }'}, 'new york liberty outdoor classic'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; location / attendance ; 1 } ; opponent } ; new york liberty outdoor classic } = true', 'tointer': 'select the row whose location / attendance record of all rows is 1st maximum . the opponent record of this row is new york liberty outdoor classic .'}
|
eq { hop { nth_argmax { all_rows ; location / attendance ; 1 } ; opponent } ; new york liberty outdoor classic } = true
|
select the row whose location / attendance record of all rows is 1st maximum . the opponent record of this row is new york liberty outdoor classic .
|
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, 'opponent_7': 7, 'new york liberty outdoor classic_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', 'opponent_7': 'opponent', 'new york liberty outdoor classic_8': 'new york liberty outdoor classic'}
|
{'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], 'opponent_7': [1], 'new york liberty outdoor classic_8': [2]}
|
['game', 'date', 'opponent', 'score', 'high points', 'high rebounds', 'high assists', 'location / attendance', 'record']
|
[['16', 'july 2', 'chicago', 'w 74 - 67', 'catchings ( 18 )', 'sutton - brown ( 12 )', 'catchings , douglas ( 3 )', 'conseco fieldhouse 6196', '8 - 8'], ['17', 'july 5', 'connecticut', 'w 81 - 74', 'douglas , sutton - brown ( 18 )', 'sutton - brown ( 9 )', 'douglas ( 5 )', 'conseco fieldhouse 6329', '9 - 8'], ['18', 'july 8', 'washington', 'l 50 - 48', 'hoffman ( 16 )', 'hoffman ( 9 )', 'bevilaqua ( 4 )', 'verizon center 7587', '9 - 9'], ['19', 'july 12', 'chicago', 'w 66 - 57', 'douglas ( 25 )', 'catchings ( 8 )', 'catchings ( 4 )', 'conseco fieldhouse 7134', '10 - 9'], ['20', 'july 16', 'atlanta', 'l 81 - 77', 'catchings ( 18 )', 'catchings ( 12 )', 'catchings ( 5 )', 'conseco fieldhouse 9303', '10 - 10'], ['21', 'july 18', 'seattle', 'l 65 - 59', 'sutton - brown ( 12 )', 'sutton - brown ( 7 )', 'bevilaqua , bond ( 3 )', 'conseco fieldhouse 7450', '10 - 11'], ['22', 'july 19', 'new york liberty outdoor classic', 'w 71 - 55', 'douglas ( 20 )', 'catchings , sutton - brown ( 9 )', 'catchings , douglas ( 4 )', 'arthur ashe stadium 19393', '11 - 11'], ['23', 'july 22', 'chicago', 'l 68 - 60', 'douglas , sutton - brown ( 14 )', 'sutton - brown ( 10 )', 'catchings ( 4 )', 'uic pavilion 3035', '11 - 12'], ['24', 'july 24', 'minnesota', 'l 84 - 80', 'catchings , hoffman ( 17 )', 'sutton - brown ( 9 )', 'catchings ( 9 )', 'conseco fieldhouse 6010', '11 - 13'], ['25', 'july 26', 'sacramento', 'l 70 - 62', 'douglas ( 23 )', 'hoffman ( 8 )', 'catchings , white ( 4 )', 'arco arena 7082', '11 - 14'], ['26', 'july 27', 'phoenix', 'w 84 - 80', 'catchings ( 25 )', 'hoffman ( 7 )', 'catchings ( 6 )', 'us airways center 7924', '12 - 14']]
|
list of the tudors episodes
|
https://en.wikipedia.org/wiki/List_of_The_Tudors_episodes
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-10413597-4.html.csv
|
majority
|
over half of the episodes in the third season of the tv series the tudors were directed by ciaran donnelly .
|
{'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'ciaran donnelly', 'subset': None}
|
{'func': 'most_str_eq', 'args': ['all_rows', 'directed by', 'ciaran donnelly'], 'result': True, 'ind': 0, 'tointer': 'for the directed by records of all rows , most of them fuzzily match to ciaran donnelly .', 'tostr': 'most_eq { all_rows ; directed by ; ciaran donnelly } = true'}
|
most_eq { all_rows ; directed by ; ciaran donnelly } = true
|
for the directed by records of all rows , most of them fuzzily match to ciaran donnelly .
|
1
|
1
|
{'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'directed by_3': 3, 'ciaran donnelly_4': 4}
|
{'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'directed by_3': 'directed by', 'ciaran donnelly_4': 'ciaran donnelly'}
|
{'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'directed by_3': [0], 'ciaran donnelly_4': [0]}
|
['no in series', 'no in season', 'title', 'setting', 'directed by', 'written by', 'original air date']
|
[['21', '1', 'civil unrest', '30th may 1536', 'ciaran donnelly', 'michael hirst', 'april 5 , 2009'], ['22', '2', 'the northern uprising', 'winter 1536', 'ciaran donnelly', 'michael hirst', 'april 12 , 2009'], ['23', '3', 'dissension and punishment', '1536 - 1537', 'ciaran donnelly', 'michael hirst', 'april 19 , 2009'], ['24', '4', 'the death of a queen', 'july - october 1537', 'ciaran donnelly', 'michael hirst', 'april 26 , 2009'], ['25', '5', 'problems in the reformation', '1537 - 1538', 'jeremy podeswa', 'michael hirst', 'may 3 , 2009'], ['26', '6', 'search for a new queen', '1538 - 1539', 'jeremy podeswa', 'michael hirst', 'may 10 , 2009'], ['27', '7', 'protestant anne of cleves', '1539 - 1540', 'jeremy podeswa', 'michael hirst', 'may 17 , 2009']]
|
family guy ( season 7 )
|
https://en.wikipedia.org/wiki/Family_Guy_%28season_7%29
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-22261877-1.html.csv
|
majority
|
most of the family guy episodes during season seven recieved over 7 million views .
|
{'scope': 'all', 'col': '8', 'most_or_all': 'most', 'criterion': 'greater_than', 'value': '7', 'subset': None}
|
{'func': 'most_greater', 'args': ['all_rows', 'us viewers ( million )', '7'], 'result': True, 'ind': 0, 'tointer': 'for the us viewers ( million ) records of all rows , most of them are greater than 7 .', 'tostr': 'most_greater { all_rows ; us viewers ( million ) ; 7 } = true'}
|
most_greater { all_rows ; us viewers ( million ) ; 7 } = true
|
for the us viewers ( million ) records of all rows , most of them are greater than 7 .
|
1
|
1
|
{'most_greater_0': 0, 'result_1': 1, 'all_rows_2': 2, 'us viewers (million)_3': 3, '7_4': 4}
|
{'most_greater_0': 'most_greater', 'result_1': 'true', 'all_rows_2': 'all_rows', 'us viewers (million)_3': 'us viewers ( million )', '7_4': '7'}
|
{'most_greater_0': [1], 'result_1': [], 'all_rows_2': [0], 'us viewers (million)_3': [0], '7_4': [0]}
|
['no in series', 'no in season', 'title', 'directed by', 'written by', 'original air date', 'production code', 'us viewers ( million )']
|
[['111', '1', 'love , blactually', 'cyndi tang', 'mike henry', 'september 28 , 2008', '6acx03', '9.20'], ['112', '2', 'i dream of jesus', 'mike kim', 'brian scully', 'october 5 , 2008', '6acx05', '8.42'], ['113', '3', 'road to germany', 'greg colton', 'patrick meighan', 'october 19 , 2008', '6acx08', '9.07'], ['114', '4', 'baby not on board', 'julius wu', 'mark hentemann', 'november 2 , 2008', '6acx07', '9.97'], ['115', '5', 'the man with two brians', 'dominic bianchi', 'john viener', 'november 9 , 2008', '6acx09', '8.60'], ['116', '6', 'tales of a third grade nothing', 'jerry langford', 'alex carter', 'november 16 , 2008', '6acx10', '8.52'], ['117', '7', "ocean 's three and a half", 'john holmquist', 'cherry chevapravatdumrong', 'february 15 , 2009', '6acx11', '7.33'], ['118', '8', 'family gay', 'brian iles', 'richard appel', 'march 8 , 2009', '6acx12', '7.18'], ['119', '9', 'the juice is loose', 'cyndi tang', 'andrew goldberg', 'march 15 , 2009', '6acx13', '7.21'], ['120', '10', 'fox - y lady', 'pete michels', 'matt fleckenstein', 'march 22 , 2009', '6acx14', '7.45'], ['121', '11', 'not all dogs go to heaven', 'greg colton', 'danny smith', 'march 29 , 2009', '6acx17', '8.20'], ['122', '12', 'episode 420', 'julius wu', 'patrick meighan', 'april 19 , 2009', '6acx16', '7.40'], ['123', '13', 'stew - roids', 'jerry langford', 'alec sulkin', 'april 26 , 2009', '6acx18', '6.80'], ['124', '14', 'we love you , conrad', 'john holmquist', 'cherry chevapravatdumrong', 'may 3 , 2009', '6acx19', '6.67'], ['125', '15', 'three kings', 'dominic bianchi', 'alec sulkin', 'may 10 , 2009', '6acx15', '6.47']]
|
1976 - 77 segunda división
|
https://en.wikipedia.org/wiki/1976%E2%80%9377_Segunda_Divisi%C3%B3n
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12239755-2.html.csv
|
ordinal
|
the team in the 1976 - 77 segunda división with the second most points was cadiz cf.
|
{'row': '2', 'col': '4', 'order': '2', 'col_other': '2', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None}
|
{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'points', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; points ; 2 }'}, 'club'], 'result': 'cádiz cf', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; points ; 2 } ; club }'}, 'cádiz cf'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; points ; 2 } ; club } ; cádiz cf } = true', 'tointer': 'select the row whose points record of all rows is 2nd maximum . the club record of this row is cádiz cf .'}
|
eq { hop { nth_argmax { all_rows ; points ; 2 } ; club } ; cádiz cf } = true
|
select the row whose points record of all rows is 2nd maximum . the club record of this row is cádiz cf .
|
3
|
3
|
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'points_5': 5, '2_6': 6, 'club_7': 7, 'cádiz cf_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', 'points_5': 'points', '2_6': '2', 'club_7': 'club', 'cádiz cf_8': 'cádiz cf'}
|
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'points_5': [0], '2_6': [0], 'club_7': [1], 'cádiz cf_8': [2]}
|
['position', 'club', 'played', 'points', 'wins', 'draws', 'losses', 'goals for', 'goals against', 'goal difference']
|
[['1', 'sporting de gijón', '38', '47 + 9', '18', '11', '9', '62', '35', '+ 27'], ['2', 'cádiz cf', '38', '46 + 8', '17', '12', '9', '60', '42', '+ 18'], ['3', 'rayo vallecano', '38', '45 + 7', '17', '11', '10', '46', '34', '+ 12'], ['4', 'real jaén', '38', '43 + 5', '15', '13', '10', '42', '32', '+ 10'], ['5', 'real oviedo', '38', '43 + 5', '18', '7', '13', '48', '43', '+ 5'], ['6', 'cd tenerife', '38', '40 + 2', '15', '10', '13', '48', '48', '0'], ['7', 'terrassa fc', '38', '40 + 2', '13', '14', '11', '44', '34', '+ 10'], ['8', 'deportivo alavés', '38', '40 + 2', '14', '12', '12', '57', '42', '+ 15'], ['9', 'recreativo de huelva', '38', '38', '14', '10', '14', '42', '50', '- 8'], ['10', 'granada cf', '38', '36 - 2', '14', '8', '16', '42', '39', '+ 3'], ['11', 'deportivo de la coruña', '38', '36 - 2', '11', '14', '13', '40', '50', '- 10'], ['12', 'real valladolid', '38', '36 - 2', '14', '8', '16', '57', '56', '+ 1'], ['13', 'getafe deportivo', '38', '35 - 3', '12', '11', '15', '37', '48', '- 11'], ['14', 'cd castellón', '38', '35 - 3', '14', '7', '17', '46', '45', '+ 1'], ['15', 'córdoba cf', '38', '35 - 3', '10', '15', '13', '39', '45', '- 6'], ['16', 'cf calvo sotelo', '38', '34 - 4', '14', '6', '18', '39', '56', '- 17'], ['17', 'pontevedra cf', '38', '34 - 4', '10', '14', '14', '34', '44', '- 10'], ['18', 'levante ud', '38', '34 - 4', '12', '10', '16', '47', '61', '- 14'], ['19', 'ue sant andreu', '38', '33 - 5', '10', '13', '15', '39', '52', '- 13'], ['20', 'barcelona atlètic', '38', '30 - 8', '10', '10', '18', '39', '52', '- 13']]
|
jakob hlasek
|
https://en.wikipedia.org/wiki/Jakob_Hlasek
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1727962-1.html.csv
|
count
|
jakob hlasek played in a total of three tennis championship finals on clay surfaces .
|
{'scope': 'all', 'criterion': 'equal', 'value': 'clay', 'result': '3', 'col': '4', 'subset': None}
|
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'surface', 'clay'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose surface record fuzzily matches to clay .', 'tostr': 'filter_eq { all_rows ; surface ; clay }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; surface ; clay } }', 'tointer': 'select the rows whose surface record fuzzily matches to clay . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; surface ; clay } } ; 3 } = true', 'tointer': 'select the rows whose surface record fuzzily matches to clay . the number of such rows is 3 .'}
|
eq { count { filter_eq { all_rows ; surface ; clay } } ; 3 } = true
|
select the rows whose surface record fuzzily matches to clay . 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, 'surface_5': 5, 'clay_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', 'surface_5': 'surface', 'clay_6': 'clay', '3_7': '3'}
|
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'surface_5': [0], 'clay_6': [0], '3_7': [2]}
|
['outcome', 'date', 'championship', 'surface', 'opponent', 'score']
|
[['runner - up', '25 march 1985', 'rotterdam , netherlands', 'carpet', 'miloslav mečíř', '1 - 6 , 2 - 6'], ['runner - up', '4 august 1986', 'hilversum , netherlands', 'clay', 'thomas muster', '1 - 6 , 3 - 6 , 3 - 6'], ['runner - up', '11 july 1988', 'gstaad , switzerland', 'clay', 'darren cahill', '3 - 6 , 4 - 6 , 6 - 7 ( 2 - 7 )'], ['runner - up', '10 october 1988', 'basel , switzerland', 'hard ( i )', 'stefan edberg', '5 - 7 , 3 - 6 , 6 - 3 , 2 - 6'], ['winner', '14 november 1988', 'wembley , england', 'carpet', 'jonas svensson', '6 - 7 ( 4 - 7 ) , 3 - 6 , 6 - 4 , 6 - 0 , 7 - 5'], ['winner', '21 november 1988', 'johannesburg , south africa', 'hard ( i )', 'christo van rensburg', '6 - 7 , 6 - 4 , 6 - 1 , 7 - 6'], ['runner - up', '28 november 1988', 'brussels , belgium', 'carpet', 'henri leconte', '6 - 7 ( 3 - 7 ) , 6 - 7 ( 6 - 8 ) , 4 - 6'], ['winner', '13 february 1989', 'rotterdam , netherlands', 'carpet', 'anders järryd', '6 - 1 , 7 - 5'], ['runner - up', '27 february 1989', 'lyon , france', 'carpet', 'john mcenroe', '3 - 6 , 6 - 7 ( 3 - 7 )'], ['winner', '12 november 1990', 'wembley , england', 'carpet', 'michael chang', '7 - 6 ( 9 - 7 ) , 6 - 3'], ['winner', '30 september 1991', 'basel , switzerland', 'hard ( i )', 'john mcenroe', '7 - 6 ( 7 - 4 ) , 6 - 0 , 6 - 3'], ['runner - up', '11 november 1991', 'moscow , russia', 'carpet', 'andrei cherkasov', '6 - 7 ( 2 - 7 ) , 6 - 3 , 6 - 7 ( 5 - 7 )'], ['runner - up', '17 july 1995', 'gstaad , switzerland', 'clay', 'yevgeny kafelnikov', '3 - 6 , 4 - 6 , 6 - 3 , 3 - 6'], ['runner - up', '18 september 1995', 'bordeaux , france', 'hard', 'yahiya doumbia', '4 - 6 , 4 - 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
|
ordinal
|
for within these walls , the 2nd to last episode to air was titled " nemesis . " .
|
{'row': '12', 'col': '6', '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', 'original airdate', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; original airdate ; 2 }'}, 'series'], 'result': '12', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; original airdate ; 2 } ; series }'}, '12'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; original airdate ; 2 } ; series } ; 12 } = true', 'tointer': 'select the row whose original airdate record of all rows is 2nd maximum . the series record of this row is 12 .'}
|
eq { hop { nth_argmax { all_rows ; original airdate ; 2 } ; series } ; 12 } = true
|
select the row whose original airdate record of all rows is 2nd maximum . the series record of this row is 12 .
|
3
|
3
|
{'eq_2': 2, 'result_3': 3, 'num_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'original airdate_5': 5, '2_6': 6, 'series_7': 7, '12_8': 8}
|
{'eq_2': 'eq', 'result_3': 'true', 'num_hop_1': 'num_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'original airdate_5': 'original airdate', '2_6': '2', 'series_7': 'series', '12_8': '12'}
|
{'eq_2': [3], 'result_3': [], 'num_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'original airdate_5': [0], '2_6': [0], 'series_7': [1], '12_8': [2]}
|
['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']]
|
1970 isle of man tt
|
https://en.wikipedia.org/wiki/1970_Isle_of_Man_TT
|
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10301911-2.html.csv
|
aggregation
|
the average finishing time of the top 7 drivers in the 1970 isle of man tt was about 2:08.00.0 .
|
{'scope': 'all', 'col': '5', 'type': 'average', 'result': '2:08.00.0', 'subset': None}
|
{'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'time'], 'result': '2:08.00.0', 'ind': 0, 'tostr': 'avg { all_rows ; time }'}, '2:08.00.0'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; time } ; 2:08.00.0 } = true', 'tointer': 'the average of the time record of all rows is 2:08.00.0 .'}
|
round_eq { avg { all_rows ; time } ; 2:08.00.0 } = true
|
the average of the time record of all rows is 2:08.00.0 .
|
2
|
2
|
{'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'time_4': 4, '2:08.00.0_5': 5}
|
{'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'time_4': 'time', '2:08.00.0_5': '2:08.00.0'}
|
{'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'time_4': [0], '2:08.00.0_5': [1]}
|
['rank', 'rider', 'team', 'speed', 'time']
|
[['1', 'frank whiteway', 'suzuki', '89.94 mph', '2:05.52.0'], ['2', 'gordon pantall', 'triumph', '88.90 mph', '2:07.20.0'], ['3', 'ray knight', 'triumph', '88.89 mph', '2:07.20.4'], ['4', 'rbaylie', 'triumph', '87.58 mph', '2:09.15.0'], ['5', 'graham penny', 'triumph', '86.70 mph', '2:10.34.4'], ['6', 'jwade', 'suzuki', '85.31 mph', '2:12.42.0'], ['7', 'brian finch', 'velocette', '83.86 mph', '2:14.59.0']]
|
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.