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leonardo de souza
https://en.wikipedia.org/wiki/Leonardo_de_Souza
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27582888-1.html.csv
majority
for the majority of his seasons racing , leonardo de souza 's was with team kemba racing .
{'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'kemba racing', 'subset': None}
{'func': 'most_str_eq', 'args': ['all_rows', 'team name', 'kemba racing'], 'result': True, 'ind': 0, 'tointer': 'for the team name records of all rows , most of them fuzzily match to kemba racing .', 'tostr': 'most_eq { all_rows ; team name ; kemba racing } = true'}
most_eq { all_rows ; team name ; kemba racing } = true
for the team name records of all rows , most of them fuzzily match to kemba racing .
1
1
{'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'team name_3': 3, 'kemba racing_4': 4}
{'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'team name_3': 'team name', 'kemba racing_4': 'kemba racing'}
{'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'team name_3': [0], 'kemba racing_4': [0]}
['season', 'series', 'team name', 'races', 'poles', 'wins', 'podiums', 'f / laps', 'points', 'final placing']
[['2005', 'formula renault brasil', 'kemba racing', '14', '0', '0', '0', '0', '18', '21st'], ['2006', 'formula renault brasil', 'eng makers', '10', '0', '0', '0', '0', '8', '18th'], ['2008', 'formula three sudamericana', 'kemba racing', '14', '0', '0', '0', '0', '24', '8th'], ['2009', 'formula three sudamericana', 'kem...
mattia pasini
https://en.wikipedia.org/wiki/Mattia_Pasini
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13985563-1.html.csv
unique
2008 was the only year that mattia pasini reached exactly 4 podiums .
{'scope': 'all', 'row': '5', 'col': '3', 'col_other': '1', 'criterion': 'equal', 'value': '4', 'subset': None}
{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'podiums', '4'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose podiums record is equal to 4 .', 'tostr': 'filter_eq { all_rows ; podiums ; 4 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ;...
and { only { filter_eq { all_rows ; podiums ; 4 } } ; eq { hop { filter_eq { all_rows ; podiums ; 4 } ; season } ; 2008 } } = true
select the rows whose podiums record is equal to 4 . there is only one such row in the table . the season record of this unqiue row is 2008 .
6
5
{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'podiums_7': 7, '4_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'season_9': 9, '2008_10': 10}
{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'podiums_7': 'podiums', '4_8': '4', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'season_9': 'season', '2008_10': '2008'}
{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'podiums_7': [0], '4_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'season_9': [2], '2008_10': [3]}
['season', 'races', 'podiums', 'pole', 'flap']
[['2004', '16', '0', '0', '0'], ['2005', '15', '6', '0', '0'], ['2006', '16', '6', '2', '2'], ['2007', '17', '5', '9', '2'], ['2008', '16', '4', '0', '0'], ['2009', '16', '5', '0', '0'], ['2010', '8', '0', '0', '0'], ['2011', '17', '0', '0', '0'], ['2012', '14', '0', '0', '0'], ['2012', '1', '0', '0', '0'], ['2013', '1...
2009 - 10 english premiership ( rugby union )
https://en.wikipedia.org/wiki/2009%E2%80%9310_English_Premiership_%28rugby_union%29
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-23909238-2.html.csv
count
only two of the eleven clubs amassed more than 70 points in the 2009-2010 season .
{'scope': 'all', 'criterion': 'greater_than', 'value': '70', 'result': '2', 'col': '14', 'subset': None}
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'points', '70'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose points record is greater than 70 .', 'tostr': 'filter_greater { all_rows ; points ; 70 }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_g...
eq { count { filter_greater { all_rows ; points ; 70 } } ; 2 } = true
select the rows whose points record is greater than 70 . the number of such rows is 2 .
3
3
{'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_greater_0': 0, 'all_rows_4': 4, 'points_5': 5, '70_6': 6, '2_7': 7}
{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_greater_0': 'filter_greater', 'all_rows_4': 'all_rows', 'points_5': 'points', '70_6': '70', '2_7': '2'}
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_greater_0': [1], 'all_rows_4': [0], 'points_5': [0], '70_6': [0], '2_7': [2]}
['', 'club', 'played', 'won', 'drawn', 'lost', 'points for', 'points against', 'points difference', 'tries for', 'tries against', 'try bonus', 'losing bonus', 'points']
[['1', 'leicester tigers ( c )', '22', '15', '1', '6', '541', '325', '216', '46', '18', '7', '4', '73'], ['2', 'northampton saints ( sf )', '22', '16', '0', '6', '472', '322', '150', '44', '26', '2', '5', '71'], ['3', 'saracens ( f )', '22', '15', '1', '6', '480', '367', '113', '39', '22', '2', '5', '69'], ['4', 'bath ...
1945 - 46 huddersfield town f.c. season
https://en.wikipedia.org/wiki/1945%E2%80%9346_Huddersfield_Town_F.C._season
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-19730892-1.html.csv
superlative
billy price had the most total goals in the 1945 - 46 huddersfield town f.c. season .
{'scope': 'all', 'col_superlative': '7', 'row_superlative': '12', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None}
{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'total goals'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; total goals }'}, 'name'], 'result': 'billy price', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; total goals } ; name }'}, 'billy price'], 'result': Tr...
eq { hop { argmax { all_rows ; total goals } ; name } ; billy price } = true
select the row whose total goals record of all rows is maximum . the name record of this row is billy price .
3
3
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'total goals_5': 5, 'name_6': 6, 'billy price_7': 7}
{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'total goals_5': 'total goals', 'name_6': 'name', 'billy price_7': 'billy price'}
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'total goals_5': [0], 'name_6': [1], 'billy price_7': [2]}
['name', 'nation', 'position', 'fa cup apps', 'fa cup goals', 'total apps', 'total goals']
[['graham bailey', 'england', 'df', '2', '0', '2', '0'], ['jeff barker', 'england', 'df', '2', '0', '2', '0'], ['albert bateman', 'england', 'mf', '2', '0', '2', '0'], ['eddie carr', 'england', 'mf', '1', '0', '1', '0'], ['don clegg', 'england', 'gk', '2', '0', '2', '0'], ['jimmy glazzard', 'england', 'fw', '2', '0', '...
brian watts
https://en.wikipedia.org/wiki/Brian_Watts
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10167122-1.html.csv
majority
in the majority of tournaments brian makes at least 1 cut .
{'scope': 'all', 'col': '6', 'most_or_all': 'all', 'criterion': 'greater_than_eq', 'value': '1', 'subset': None}
{'func': 'all_greater_eq', 'args': ['all_rows', 'cuts made', '1'], 'result': True, 'ind': 0, 'tointer': 'for the cuts made records of all rows , all of them are greater than or equal to 1 .', 'tostr': 'all_greater_eq { all_rows ; cuts made ; 1 } = true'}
all_greater_eq { all_rows ; cuts made ; 1 } = true
for the cuts made records of all rows , all of them are greater than or equal to 1 .
1
1
{'all_greater_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'cuts made_3': 3, '1_4': 4}
{'all_greater_eq_0': 'all_greater_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'cuts made_3': 'cuts made', '1_4': '1'}
{'all_greater_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'cuts made_3': [0], '1_4': [0]}
['tournament', 'wins', 'top - 5', 'top - 25', 'events', 'cuts made']
[['masters tournament', '0', '0', '0', '2', '1'], ['us open', '0', '0', '1', '2', '1'], ['the open championship', '0', '1', '2', '7', '4'], ['pga championship', '0', '0', '0', '6', '4'], ['totals', '0', '1', '3', '17', '10']]
1980 winter olympics
https://en.wikipedia.org/wiki/1980_Winter_Olympics
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-113360-1.html.csv
unique
at the 1980 winter olympics , the only country to win 6 gold medals was the united states .
{'scope': 'all', 'row': '3', 'col': '3', 'col_other': '2', 'criterion': 'equal', 'value': '6', 'subset': None}
{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'gold', '6'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose gold record is equal to 6 .', 'tostr': 'filter_eq { all_rows ; gold ; 6 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; gold ; 6...
and { only { filter_eq { all_rows ; gold ; 6 } } ; eq { hop { filter_eq { all_rows ; gold ; 6 } ; nation } ; united states } } = true
select the rows whose gold record is equal to 6 . there is only one such row in the table . the nation record of this unqiue row is united states .
6
5
{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'gold_7': 7, '6_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'nation_9': 9, 'united states_10': 10}
{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'gold_7': 'gold', '6_8': '6', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'nation_9': 'nation', 'united states_10': 'united states'}
{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'gold_7': [0], '6_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'nation_9': [2], 'united states_10': [3]}
['rank', 'nation', 'gold', 'silver', 'bronze', 'total']
[['1', 'soviet union', '10', '6', '6', '22'], ['2', 'east germany ( gdr )', '9', '7', '7', '23'], ['3', 'united states', '6', '4', '2', '12'], ['4', 'austria', '3', '2', '2', '7'], ['5', 'sweden', '3', '0', '1', '4'], ['6', 'liechtenstein', '2', '2', '0', '4'], ['7', 'finland', '1', '5', '3', '9'], ['8', 'norway', '1',...
edmonton radial railway society
https://en.wikipedia.org/wiki/Edmonton_Radial_Railway_Society
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-22481967-1.html.csv
count
a total of five edmonton radial railway society models were withdrawn in the year 1951 .
{'scope': 'all', 'criterion': 'equal', 'value': '1951', 'result': '5', 'col': '6', 'subset': None}
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'withdrawn', '1951'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose withdrawn record is equal to 1951 .', 'tostr': 'filter_eq { all_rows ; withdrawn ; 1951 }'}], 'result': '5', 'ind': 1, 'tostr': 'count { filter_...
eq { count { filter_eq { all_rows ; withdrawn ; 1951 } } ; 5 } = true
select the rows whose withdrawn record is equal to 1951 . the number of such rows is 5 .
3
3
{'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_eq_0': 0, 'all_rows_4': 4, 'withdrawn_5': 5, '1951_6': 6, '5_7': 7}
{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'withdrawn_5': 'withdrawn', '1951_6': '1951', '5_7': '5'}
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'withdrawn_5': [0], '1951_6': [0], '5_7': [2]}
['date', 'builder', 'type', 'operator', 'number', 'withdrawn', 'status']
[['1907', 'occ', 'combination sweeper / overhead line car', 'saskatoon municipal railway', '200', '1951', 'stored'], ['1908', 'occ', 'streetcar', 'edmonton radial railway', '1', '1951', 'display only'], ['1912', 'stl', 'streetcar', 'edmonton radial railway', '33', '1951', 'stored'], ['1912', 'stl', 'streetcar', 'edmont...
shane hall
https://en.wikipedia.org/wiki/Shane_Hall
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2649597-1.html.csv
count
shane hall drove with the stegell motorsports team for a total of four years .
{'scope': 'all', 'criterion': 'equal', 'value': 'stegell motorsports', 'result': '4', 'col': '12', 'subset': None}
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'team ( s )', 'stegell motorsports'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose team ( s ) record fuzzily matches to stegell motorsports .', 'tostr': 'filter_eq { all_rows ; team ( s ) ; stegell motorspor...
eq { count { filter_eq { all_rows ; team ( s ) ; stegell motorsports } } ; 4 } = true
select the rows whose team ( s ) record fuzzily matches to stegell motorsports . 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, 'team (s)_5': 5, 'stegell motorsports_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', 'team (s)_5': 'team ( s )', 'stegell motorsports_6': 'stegell motorsports', '4_7': '4'}
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'team (s)_5': [0], 'stegell motorsports_6': [0], '4_7': [2]}
['year', 'races', 'wins', 'poles', 'top 5', 'top 10', 'dnf', 'finish', 'start', 'winnings', 'season rank', 'team ( s )']
[['1995', '2', '0', '0', '0', '0', '0', '24.0', '37.0', '5225', '75th', 'stegell motorsports'], ['1996', '14', '0', '0', '0', '0', '6', '26.4', '25.1', '63865', '42nd', 'stegell motorsports'], ['1997', '28', '0', '1', '0', '1', '10', '27.1', '21.6', '196656', '23rd', 'stegell motorsports'], ['1998', '31', '0', '1', '0'...
list of number - one singles of 1999 ( canada )
https://en.wikipedia.org/wiki/List_of_number-one_singles_of_1999_%28Canada%29
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17481317-1.html.csv
comparative
the song kiss me was the number one song in canada in 1999 for more weeks than the song smooth .
{'row_1': '11', 'row_2': '16', 'col': '3', 'col_other': '4', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None}
{'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'song', 'kiss me'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose song record fuzzily matches to kiss me .', 'tostr': 'filter_eq { all_rows ; song ; kiss me }'}, 'weeks on top'], 'result': None, 'ind':...
greater { hop { filter_eq { all_rows ; song ; kiss me } ; weeks on top } ; hop { filter_eq { all_rows ; song ; smooth } ; weeks on top } } = true
select the rows whose song record fuzzily matches to kiss me . take the weeks on top record of this row . select the rows whose song record fuzzily matches to smooth . take the weeks on top 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, 'song_7': 7, 'kiss me_8': 8, 'weeks on top_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'song_11': 11, 'smooth_12': 12, 'weeks on top_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', 'song_7': 'song', 'kiss me_8': 'kiss me', 'weeks on top_9': 'weeks on top', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'song_11': 'song', 'smooth...
{'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'song_7': [0], 'kiss me_8': [0], 'weeks on top_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'song_11': [1], 'smooth_12': [1], 'weeks on top_13': [3]}
['volume : issue', 'issue date ( s )', 'weeks on top', 'song', 'artist']
[['68:10 - 12', '30 november - 4 january 1999 §', '6 §', 'thank u', 'alanis morissette'], ['68:13', '11 january - 18 january ≠', '2 ≠', "it 's all been done", 'barenaked ladies'], ['68:14', '25 january', '1', 'hands', 'jewel'], ['68:15', '1 february', '1', 'you get what you give', 'new radicals'], ['68:16', '8 february...
statues of the liberators
https://en.wikipedia.org/wiki/Statues_of_the_Liberators
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13846706-1.html.csv
ordinal
the statue of benito juarez was the third statue of liberator to be erected on virginia avenue .
{'row': '5', 'col': '4', 'order': '3', 'col_other': '1', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None}
{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'year erected', '3'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; year erected ; 3 }'}, 'statue'], 'result': 'benito juarez', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; year erected ; 3 } ; statue...
eq { hop { nth_argmin { all_rows ; year erected ; 3 } ; statue } ; benito juarez } = true
select the row whose year erected record of all rows is 3rd minimum . the statue record of this row is benito juarez .
3
3
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'year erected_5': 5, '3_6': 6, 'statue_7': 7, 'benito juarez_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', 'year erected_5': 'year erected', '3_6': '3', 'statue_7': 'statue', 'benito juarez_8': 'benito juarez'}
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'year erected_5': [0], '3_6': [0], 'statue_7': [1], 'benito juarez_8': [2]}
['statue', 'liberator', 'country', 'year erected', 'artist']
[['general josé gervasio artigas', 'josé gervasio artigas', 'uruguay', '1950', 'juan manuel blanes ( 1830 - 1901 )'], ['equestrian of simón bolívar', 'simón bolívar', 'venezuela', '1958', 'felix de weldon ( 1907 - 2003 )'], ['general jose de san martin memorial', 'josé de san martín', 'argentina', '1970s', 'augustin - ...
locomotives of the glasgow and south western railway
https://en.wikipedia.org/wiki/Locomotives_of_the_Glasgow_and_South_Western_Railway
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15412381-5.html.csv
comparative
north british built a locomotive in an earlier year than g & swr kilmarnock .
{'row_1': '1', 'row_2': '2', 'col': '3', 'col_other': '4', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None}
{'func': 'less', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'builder', 'north british'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose builder record fuzzily matches to north british .', 'tostr': 'filter_eq { all_rows ; builder ; north british }'}, 'date'], 'resul...
less { hop { filter_eq { all_rows ; builder ; north british } ; date } ; hop { filter_eq { all_rows ; builder ; g & swr kilmarnock } ; date } } = true
select the rows whose builder record fuzzily matches to north british . take the date record of this row . select the rows whose builder record fuzzily matches to g & swr kilmarnock . take the date 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, 'builder_7': 7, 'north british_8': 8, 'date_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'builder_11': 11, 'g&swr kilmarnock_12': 12, 'date_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', 'builder_7': 'builder', 'north british_8': 'north british', 'date_9': 'date', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'builder_11': 'builder', 'g&sw...
{'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'builder_7': [0], 'north british_8': [0], 'date_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'builder_11': [1], 'g&swr kilmarnock_12': [1], 'date_13': [3]}
['class', 'wheels', 'date', 'builder', 'no built', '1919 nos', 'lms class', 'lms nos']
[['4 - 4 - 0', '131', '1913', 'north british', '6', '331 - 336', '3p', '14510 - 5'], ['4 - 4 - 0', '137', '1915', 'g & swr kilmarnock', '6', '325 - 330', '3p', '14516 - 21'], ['0 - 6 - 0t', '5', '1917', 'north british', '3', '322 - 324', '2f', '16377 - 9'], ['0 - 6 - 2t', '45', '1915 - 17', 'north british', '18', '11 -...
2009 - 10 washington capitals season
https://en.wikipedia.org/wiki/2009%E2%80%9310_Washington_Capitals_season
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-23308178-9.html.csv
count
six games were played at the verizon center .
{'scope': 'all', 'criterion': 'equal', 'value': 'verizon center', 'result': '7', 'col': '5', 'subset': None}
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location', 'verizon center'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose location record fuzzily matches to verizon center .', 'tostr': 'filter_eq { all_rows ; location ; verizon center }'}], 'result': '7...
eq { count { filter_eq { all_rows ; location ; verizon center } } ; 7 } = true
select the rows whose location record fuzzily matches to verizon center . the number of such rows is 7 .
3
3
{'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'location_5': 5, 'verizon center_6': 6, '7_7': 7}
{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'location_5': 'location', 'verizon center_6': 'verizon center', '7_7': '7'}
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'location_5': [0], 'verizon center_6': [0], '7_7': [2]}
['game', 'date', 'opponent', 'score', 'location', 'attendance', 'record', 'points']
[['63', 'march 3', 'buffalo sabres', '3 - 1', 'hsbc arena', '18690', '42 - 13 - 8', '92'], ['64', 'march 4', 'tampa bay lightning', '5 - 4', 'verizon center', '18277', '43 - 13 - 8', '94'], ['65', 'march 6', 'new york rangers', '2 - 0', 'verizon center', '18277', '44 - 13 - 8', '96'], ['66', 'march 8', 'dallas stars', ...
1975 dallas cowboys season
https://en.wikipedia.org/wiki/1975_Dallas_Cowboys_season
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16767061-2.html.csv
count
the dallas cowboys played against the st louis cardinals 2 times during the 1975 season .
{'scope': 'all', 'criterion': 'equal', 'value': 'st louis cardinals', 'result': '2', 'col': '3', 'subset': None}
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', 'st louis cardinals'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose opponent record fuzzily matches to st louis cardinals .', 'tostr': 'filter_eq { all_rows ; opponent ; st louis cardinals }'}], ...
eq { count { filter_eq { all_rows ; opponent ; st louis cardinals } } ; 2 } = true
select the rows whose opponent record fuzzily matches to st louis cardinals . 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, 'st louis cardinals_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', 'st louis cardinals_6': 'st louis cardinals', '2_7': '2'}
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'opponent_5': [0], 'st louis cardinals_6': [0], '2_7': [2]}
['week', 'date', 'opponent', 'result', 'attendance']
[['1', 'september 21 , 1975', 'los angeles rams', 'w 18 - 7', '49091'], ['2', 'september 28 , 1975', 'st louis cardinals', 'w 37 - 31', '52417'], ['3', 'october 6 , 1975', 'detroit lions', 'w 36 - 10', '79384'], ['4', 'october 12 , 1975', 'new york giants', 'w 13 - 7', '56511'], ['5', 'october 19 , 1975', 'green bay pa...
2007 amsterdam admirals season
https://en.wikipedia.org/wiki/2007_Amsterdam_Admirals_season
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-10392906-2.html.csv
superlative
the amsterdam admirals received their highest score during the 2007 season against the hamburg devils with 41 points .
{'scope': 'all', 'col_superlative': '5', 'row_superlative': '6', 'value_mentioned': 'yes', 'max_or_min': 'max', 'other_col': '4', 'subset': None}
{'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'max', 'args': ['all_rows', 'final score'], 'result': 'w 41 - 31', 'ind': 0, 'tostr': 'max { all_rows ; final score }', 'tointer': 'the maximum final score record of all rows is w 41 - 31 .'}, 'w 41 - 31'], 'result': True, 'ind': 1, 'tostr': 'eq { max { all_rows...
and { eq { max { all_rows ; final score } ; w 41 - 31 } ; eq { hop { argmax { all_rows ; final score } ; opponent } ; hamburg sea devils } } = true
the maximum final score record of all rows is w 41 - 31 . the opponent record of the row with superlative final score record is hamburg sea devils .
6
6
{'and_5': 5, 'result_6': 6, 'eq_1': 1, 'max_0': 0, 'all_rows_7': 7, 'final score_8': 8, 'w 41 - 31_9': 9, 'str_eq_4': 4, 'str_hop_3': 3, 'argmax_2': 2, 'all_rows_10': 10, 'final score_11': 11, 'opponent_12': 12, 'hamburg sea devils_13': 13}
{'and_5': 'and', 'result_6': 'true', 'eq_1': 'eq', 'max_0': 'max', 'all_rows_7': 'all_rows', 'final score_8': 'final score', 'w 41 - 31_9': 'w 41 - 31', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'argmax_2': 'argmax', 'all_rows_10': 'all_rows', 'final score_11': 'final score', 'opponent_12': 'opponent', 'hamburg sea...
{'and_5': [6], 'result_6': [], 'eq_1': [5], 'max_0': [1], 'all_rows_7': [0], 'final score_8': [0], 'w 41 - 31_9': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'argmax_2': [3], 'all_rows_10': [2], 'final score_11': [2], 'opponent_12': [3], 'hamburg sea devils_13': [4]}
['week', 'date', 'kickoff', 'opponent', 'final score', 'team record', 'game site', 'attendance']
[['1', 'saturday , april 14', '7:00 pm', 'frankfurt galaxy', 'l 14 - 30', '0 - 1', 'commerzbank - arena', '38125'], ['2', 'friday , april 20', '8:00 pm', 'rhein fire', 'l 10 - 16', '0 - 2', 'amsterdam arena', '14611'], ['3', 'saturday , april 28', '6:00 pm', 'berlin thunder', 'w 14 - 10', '1 - 2', 'olympic stadium', '1...
fabiano iha
https://en.wikipedia.org/wiki/Fabiano_Iha
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17445451-2.html.csv
majority
the majority of fabiano iha 's fights ended in the 1st round of the fight .
{'scope': 'all', 'col': '6', 'most_or_all': 'most', 'criterion': 'equal', 'value': '1', 'subset': None}
{'func': 'most_eq', 'args': ['all_rows', 'round', '1'], 'result': True, 'ind': 0, 'tointer': 'for the round records of all rows , most of them are equal to 1 .', 'tostr': 'most_eq { all_rows ; round ; 1 } = true'}
most_eq { all_rows ; round ; 1 } = true
for the round records of all rows , most of them are equal to 1 .
1
1
{'most_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'round_3': 3, '1_4': 4}
{'most_eq_0': 'most_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'round_3': 'round', '1_4': '1'}
{'most_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'round_3': [0], '1_4': [0]}
['res', 'record', 'opponent', 'method', 'event', 'round', 'time']
[['win', '9 - 5', 'john cox', 'ko', 'lip 1 - lockdown in paradise 1', '1', '0:30'], ['win', '8 - 5', 'flavio troccoli', 'submission ( armbar )', 'hfp 2 - hitman fighting productions 2', '1', '0:53'], ['loss', '7 - 5', 'din thomas', 'decision ( unanimous )', 'ufc 33', '3', '5:00'], ['loss', '7 - 4', 'caol uno', 'ko ( pu...
list of england national rugby union team results 1980 - 89
https://en.wikipedia.org/wiki/List_of_England_national_rugby_union_team_results_1980%E2%80%9389
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18178608-3.html.csv
majority
in regards to the england national rugby union team , the status of most of the matches was five nations .
{'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'five nations', 'subset': None}
{'func': 'most_str_eq', 'args': ['all_rows', 'status', 'five nations'], 'result': True, 'ind': 0, 'tointer': 'for the status records of all rows , most of them fuzzily match to five nations .', 'tostr': 'most_eq { all_rows ; status ; five nations } = true'}
most_eq { all_rows ; status ; five nations } = true
for the status records of all rows , most of them fuzzily match to five nations .
1
1
{'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'status_3': 3, 'five nations_4': 4}
{'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'status_3': 'status', 'five nations_4': 'five nations'}
{'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'status_3': [0], 'five nations_4': [0]}
['opposing teams', 'against', 'date', 'venue', 'status']
[['australia', '11', '02 / 01 / 1982', 'twickenham , london', 'test match'], ['scotland', '9', '16 / 01 / 1982', 'murrayfield , edinburgh', 'five nations'], ['ireland', '16', '06 / 02 / 1982', 'twickenham , london', 'five nations'], ['france', '15', '20 / 02 / 1982', 'parc des princes , paris', 'five nations'], ['wales...
new zealand open ( badminton )
https://en.wikipedia.org/wiki/New_Zealand_Open_%28badminton%29
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12275551-1.html.csv
comparative
nicholas hall participated in the men 's singles event before andrew smith did .
{'row_1': '1', 'row_2': '13', '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', "men 's singles", 'nicholas hall'], 'result': None, 'ind': 0, 'tointer': "select the rows whose men 's singles record fuzzily matches to nicholas hall .", 'tostr': "filter_eq { all_rows ; men 's singles ; nicholas hall...
less { hop { filter_eq { all_rows ; men 's singles ; nicholas hall } ; year } ; hop { filter_eq { all_rows ; men 's singles ; andrew smith } ; year } } = true
select the rows whose men 's singles record fuzzily matches to nicholas hall . take the year record of this row . select the rows whose men 's singles record fuzzily matches to andrew smith . 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, "men 's singles_7": 7, 'nicholas hall_8': 8, 'year_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, "men 's singles_11": 11, 'andrew smith_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', "men 's singles_7": "men 's singles", 'nicholas hall_8': 'nicholas hall', 'year_9': 'year', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', "men 's singles_...
{'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], "men 's singles_7": [0], 'nicholas hall_8': [0], 'year_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], "men 's singles_11": [1], 'andrew smith_12': [1], 'year_13': [3]}
['year', "men 's singles", "women 's singles", "men 's doubles", "women 's doubles", 'mixed doubles']
[['1990', 'nicholas hall', 'stephanie spicer', 'nicholas hall dean galt', 'rhona robertson lynne scutt', 'brent chapman tammy jenkins'], ['1991', 'wei yan', 'anna oi chan lao', 'peter blackburn darren mcdonald', 'rhonda cator anna oi chan lao', 'peter blackburn lisa campbell'], ['1992', 'dean galt', 'julie still', 'dea...
radiopharmacology
https://en.wikipedia.org/wiki/Radiopharmacology
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1035507-12.html.csv
unique
in111 - s leukocyte is the only one with infection / inflammation imaging among those with iv route of administration .
{'scope': 'subset', 'row': '3', 'col': '2', 'col_other': '1', 'criterion': 'equal', 'value': 'infection / inflammation imaging', 'subset': {'col': '3', 'criterion': 'equal', 'value': 'iv'}}
{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'route of administration', 'iv'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; route of administration ; iv }', 'tointer': 'select the rows whose route of administration rec...
and { only { filter_eq { filter_eq { all_rows ; route of administration ; iv } ; investigation ; infection / inflammation imaging } } ; eq { hop { filter_eq { filter_eq { all_rows ; route of administration ; iv } ; investigation ; infection / inflammation imaging } ; name } ; in111 - s leukocyte } } = true
select the rows whose route of administration record fuzzily matches to iv . among these rows , select the rows whose investigation record fuzzily matches to infection / inflammation imaging . there is only one such row in the table . the name record of this unqiue row is in111 - s leukocyte .
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, 'route of administration_8': 8, 'iv_9': 9, 'investigation_10': 10, 'infection / inflammation imaging_11': 11, 'str_eq_4': 4, 'str_hop_3': 3, 'name_12': 12, 'in111 - s leukocyte_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', 'route of administration_8': 'route of administration', 'iv_9': 'iv', 'investigation_10': 'investigation', 'infection / inflammation imaging_11': 'infection / inflamma...
{'and_5': [6], 'result_6': [], 'only_2': [5], 'filter_str_eq_1': [2, 3], 'filter_str_eq_0': [1], 'all_rows_7': [0], 'route of administration_8': [0], 'iv_9': [0], 'investigation_10': [1], 'infection / inflammation imaging_11': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'name_12': [3], 'in111 - s leukocyte_13': [4]}
['name', 'investigation', 'route of administration', 'in - vitro / in - vivo', 'imaging / non - imaging']
[['in111 - dtpa ( diethylenetriaminepenta - acetic acid )', 'ventriculo - peritoneal shunt ( laveen shunt )', 'intraperitoneal injection', 'in - vivo', 'imaging'], ['in111 - dtpa ( diethylenetriaminepenta - acetic acid )', 'cisternography', 'intra - cisternal', 'in - vivo', 'imaging'], ['in111 - s leukocyte', 'infectio...
1981 all - ireland senior hurling championship
https://en.wikipedia.org/wiki/1981_All-Ireland_Senior_Hurling_Championship
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18937093-2.html.csv
aggregation
in the 1981 all-ireland senior hurling championship all 17 players combined achieved an average total of 9.29 .
{'scope': 'all', 'col': '5', 'type': 'average', 'result': '9.29', 'subset': None}
{'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'total'], 'result': '9.29', 'ind': 0, 'tostr': 'avg { all_rows ; total }'}, '9.29'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; total } ; 9.29 } = true', 'tointer': 'the average of the total record of all rows is 9.29 .'}
round_eq { avg { all_rows ; total } ; 9.29 } = true
the average of the total record of all rows is 9.29 .
2
2
{'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'total_4': 4, '9.29_5': 5}
{'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'total_4': 'total', '9.29_5': '9.29'}
{'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'total_4': [0], '9.29_5': [1]}
['rank', 'player', 'county', 'tally', 'total', 'opposition']
[['1', 'joe connolly', 'galway', '2 - 7', '13', 'limerick'], ['2', 'joe mckenna', 'limerick', '3 - 3', '12', 'clare'], ['2', 'john grogan', 'tipperary', '2 - 6', '12', 'limerick'], ['4', 'bernie forde', 'galway', '2 - 5', '11', 'antrim'], ['5', 'joe mckenna', 'limerick', '3 - 1', '10', 'tipperary'], ['6', 'billy bohane...
2001 - 02 philadelphia flyers season
https://en.wikipedia.org/wiki/2001%E2%80%9302_Philadelphia_Flyers_season
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14347256-5.html.csv
superlative
the philadelphia flyers ' game against vancouver canucks recorded the most points in the 2001 - 02 season .
{'scope': 'all', 'col_superlative': '6', 'row_superlative': '15', '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', 'points'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; points }'}, 'opponent'], 'result': 'vancouver canucks', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; points } ; opponent }'}, 'vancouver canucks'], 'result...
eq { hop { argmax { all_rows ; points } ; opponent } ; vancouver canucks } = true
select the row whose points record of all rows is maximum . the opponent record of this row is vancouver canucks .
3
3
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'points_5': 5, 'opponent_6': 6, 'vancouver canucks_7': 7}
{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'points_5': 'points', 'opponent_6': 'opponent', 'vancouver canucks_7': 'vancouver canucks'}
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'points_5': [0], 'opponent_6': [1], 'vancouver canucks_7': [2]}
['game', 'december', 'opponent', 'score', 'record', 'points']
[['24', '1', 'tampa bay lightning', '2 - 0', '11 - 7 - 5 - 1', '28'], ['25', '4', 'new york islanders', '3 - 2', '12 - 7 - 5 - 1', '30'], ['26', '6', 'new york islanders', '0 - 2', '12 - 8 - 5 - 1', '30'], ['27', '8', 'minnesota wild', '5 - 1', '13 - 8 - 5 - 1', '32'], ['28', '10', 'atlanta thrashers', '3 - 1', '14 - 8...
saulo roston
https://en.wikipedia.org/wiki/Saulo_Roston
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27614707-1.html.csv
count
there are three episodes of ídolos brazil where the theme of the songs were the judge 's choice .
{'scope': 'all', 'criterion': 'equal', 'value': "judge 's choice", 'result': '3', 'col': '2', 'subset': None}
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'theme', "judge 's choice"], 'result': None, 'ind': 0, 'tointer': "select the rows whose theme record fuzzily matches to judge 's choice .", 'tostr': "filter_eq { all_rows ; theme ; judge 's choice }"}], 'result': '3', 'in...
eq { count { filter_eq { all_rows ; theme ; judge 's choice } } ; 3 } = true
select the rows whose theme record fuzzily matches to judge 's choice . 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, 'theme_5': 5, "judge's choice_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', 'theme_5': 'theme', "judge's choice_6": "judge 's choice", '3_7': '3'}
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'theme_5': [0], "judge's choice_6": [0], '3_7': [2]}
['week', 'theme', 'song choice', 'original artist', 'order', 'result']
[['audition', "auditioner 's choice", 'bem que se quis', 'marisa monte', 'n / a', 'advanced'], ['theater', 'first solo', 'n / a', 'n / a', 'n / a', 'advanced'], ['top 24', 'top 12 men', 'como vai você', 'roberto carlos', '7', 'advanced'], ['top 12', 'sing your idol', 'beija eu', 'marisa monte', '4', 'safe'], ['top 11',...
2008 tour de suisse
https://en.wikipedia.org/wiki/2008_Tour_de_Suisse
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17672470-19.html.csv
majority
rene weissinger had the majority of sprints classification in the 2008 tour de suisse .
{'scope': 'all', 'col': '6', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'rené weissinger', 'subset': None}
{'func': 'most_str_eq', 'args': ['all_rows', 'sprints classification', 'rené weissinger'], 'result': True, 'ind': 0, 'tointer': 'for the sprints classification records of all rows , most of them fuzzily match to rené weissinger .', 'tostr': 'most_eq { all_rows ; sprints classification ; rené weissinger } = true'}
most_eq { all_rows ; sprints classification ; rené weissinger } = true
for the sprints classification records of all rows , most of them fuzzily match to rené weissinger .
1
1
{'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'sprints classification_3': 3, 'rené weissinger_4': 4}
{'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'sprints classification_3': 'sprints classification', 'rené weissinger_4': 'rené weissinger'}
{'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'sprints classification_3': [0], 'rené weissinger_4': [0]}
['stage', 'winner', 'general classification', 'mountains classification', 'points classification', 'sprints classification', 'team classification']
[['1', 'óscar freire', 'óscar freire', 'no award', 'óscar freire', 'no award', "caisse d'epargne"], ['2', 'igor antón', 'igor antón', 'david loosli', 'kim kirchen', 'david loosli', 'team csc'], ['3', 'robbie mcewen', 'igor antón', 'david loosli', 'óscar freire', 'rené weissinger', 'team csc'], ['4', 'robbie mcewen', 'i...
greg norman
https://en.wikipedia.org/wiki/Greg_Norman
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-157447-7.html.csv
aggregation
the professional golfer greg norman had an added total of 48 top 25 placements .
{'scope': 'all', 'col': '5', 'type': 'sum', 'result': '48', 'subset': None}
{'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'top - 25'], 'result': '48', 'ind': 0, 'tostr': 'sum { all_rows ; top - 25 }'}, '48'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; top - 25 } ; 48 } = true', 'tointer': 'the sum of the top - 25 record of all rows is 48 .'}
round_eq { sum { all_rows ; top - 25 } ; 48 } = true
the sum of the top - 25 record of all rows is 48 .
2
2
{'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'top - 25_4': 4, '48_5': 5}
{'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'top - 25_4': 'top - 25', '48_5': '48'}
{'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'top - 25_4': [0], '48_5': [1]}
['tournament', 'wins', 'top - 5', 'top - 10', 'top - 25', 'events', 'cuts made']
[['masters tournament', '0', '8', '9', '12', '23', '17'], ['us open', '0', '3', '5', '7', '19', '13'], ['the open championship', '2', '4', '10', '17', '27', '23'], ['pga championship', '0', '5', '6', '12', '22', '18'], ['totals', '2', '20', '30', '48', '91', '71']]
1986 u.s. open ( golf )
https://en.wikipedia.org/wiki/1986_U.S._Open_%28golf%29
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17231232-7.html.csv
unique
bernhard langer was the only non-american who won a share of the prize money .
{'scope': 'all', 'row': '8', 'col': '3', 'col_other': '2', 'criterion': 'not_equal', 'value': 'united states', 'subset': None}
{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_not_eq', 'args': ['all_rows', 'country', 'united states'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose country record does not match to united states .', 'tostr': 'filter_not_eq { all_rows ; country ; united states }'}], 'result': T...
and { only { filter_not_eq { all_rows ; country ; united states } } ; eq { hop { filter_not_eq { all_rows ; country ; united states } ; player } ; bernhard langer } } = true
select the rows whose country record does not match to united states . there is only one such row in the table . the player record of this unqiue row is bernhard langer .
6
5
{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_not_eq_0': 0, 'all_rows_6': 6, 'country_7': 7, 'united states_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'player_9': 9, 'bernhard langer_10': 10}
{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_not_eq_0': 'filter_str_not_eq', 'all_rows_6': 'all_rows', 'country_7': 'country', 'united states_8': 'united states', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'player_9': 'player', 'bernhard langer_10': 'bernhard langer'}
{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_not_eq_0': [1, 2], 'all_rows_6': [0], 'country_7': [0], 'united states_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'player_9': [2], 'bernhard langer_10': [3]}
['place', 'player', 'country', 'score', 'to par', 'money']
[['1', 'raymond floyd', 'united states', '75 + 68 + 70 + 66 = 279', '1', '115000'], ['t2', 'chip beck', 'united states', '75 + 73 + 68 + 65 = 281', '+ 1', '47646'], ['t2', 'lanny wadkins', 'united states', '74 + 70 + 72 + 65 = 281', '+ 1', '47646'], ['t4', 'hal sutton', 'united states', '75 + 70 + 66 + 71 = 282', '+ 2'...
laser quest
https://en.wikipedia.org/wiki/Laser_Quest
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2011349-2.html.csv
count
paragon denver co was the first runner up for laser quest a total of three times .
{'scope': 'all', 'criterion': 'equal', 'value': 'paragon denver co', 'result': '3', 'col': '3', 'subset': None}
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'first runner up', 'paragon denver co'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose first runner up record fuzzily matches to paragon denver co .', 'tostr': 'filter_eq { all_rows ; first runner up ; parago...
eq { count { filter_eq { all_rows ; first runner up ; paragon denver co } } ; 3 } = true
select the rows whose first runner up record fuzzily matches to paragon denver co . 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, 'first runner up_5': 5, 'paragon denver co_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', 'first runner up_5': 'first runner up', 'paragon denver co_6': 'paragon denver co', '3_7': '3'}
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'first runner up_5': [0], 'paragon denver co_6': [0], '3_7': [2]}
['year', 'winner', 'first runner up', 'third place', 'consolation winner / 4th', 'finals location']
[['2012 details', 'tsa toronto on', 'nrh north richland hills tx', 'mesa mesa az', 'denver denver co', 'las vegas nv'], ['2011 details', 'nrh north richland hills tx', 'tsa toronto on', 'mesa mesa az', 'federal way seattle wa', 'las vegas nv'], ['2010 details', 'tsa toronto on', 'nrh north richland hills tx', 'mesa mes...
cho jae - jin
https://en.wikipedia.org/wiki/Cho_Jae-Jin
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1385081-3.html.csv
aggregation
from 2003 - 2007 , cho jae-jin scored a total of 10 goals in international games .
{'scope': 'all', 'col': '3', 'type': 'sum', 'result': '10', 'subset': None}
{'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'score'], 'result': '10', 'ind': 0, 'tostr': 'sum { all_rows ; score }'}, '10'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; score } ; 10 } = true', 'tointer': 'the sum of the score record of all rows is 10 .'}
round_eq { sum { all_rows ; score } ; 10 } = true
the sum of the score record of all rows is 10 .
2
2
{'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'score_4': 4, '10_5': 5}
{'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'score_4': 'score', '10_5': '10'}
{'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'score_4': [0], '10_5': [1]}
['date', 'venue', 'score', 'result', 'competition']
[['25 september 2003', 'incheon', '1 goal', '5 - 0', '2004 afc asian cup qualification'], ['24 october 2003', 'muscat', '1 goal', '7 - 0', '2004 afc asian cup qualification'], ['19 december 2004', 'busan', '1 goal', '3 - 1', 'friendly match'], ['1 february 2006', 'hong kong', '1 goal', '1 - 3', '2006 carlsberg cup'], [...
1996 senior pga tour
https://en.wikipedia.org/wiki/1996_Senior_PGA_Tour
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11621873-3.html.csv
count
three of the top-ranked players in the 1996 senior pga tour came from the united states .
{'scope': 'all', 'criterion': 'equal', 'value': 'united states', 'result': '3', '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': '3', 'in...
eq { count { filter_eq { all_rows ; country ; united states } } ; 3 } = true
select the rows whose country record fuzzily matches to united states . the number of such rows is 3 .
3
3
{'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'country_5': 5, 'united states_6': 6, '3_7': 7}
{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'country_5': 'country', 'united states_6': 'united states', '3_7': '3'}
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'country_5': [0], 'united states_6': [0], '3_7': [2]}
['rank', 'player', 'country', 'earnings', 'events', 'wins']
[['1', 'jim colbert', 'united states', '1627890', '32', '5'], ['2', 'hale irwin', 'united states', '1615769', '23', '2'], ['3', 'john bland', 'south africa', '1357987', '35', '4'], ['4', 'isao aoki', 'japan', '1162581', '26', '2'], ['5', 'dave stockton', 'united states', '1117685', '29', '2']]
list of prime ministers of albania
https://en.wikipedia.org/wiki/List_of_Prime_Ministers_of_Albania
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-167235-2.html.csv
majority
the majority of prime ministers in albania ere not members of a party .
{'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': 'non - party', 'subset': None}
{'func': 'most_str_eq', 'args': ['all_rows', 'political party', 'non - party'], 'result': True, 'ind': 0, 'tointer': 'for the political party records of all rows , most of them fuzzily match to non - party .', 'tostr': 'most_eq { all_rows ; political party ; non - party } = true'}
most_eq { all_rows ; political party ; non - party } = true
for the political party records of all rows , most of them fuzzily match to non - party .
1
1
{'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'political party_3': 3, 'non - party_4': 4}
{'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'political party_3': 'political party', 'non - party_4': 'non - party'}
{'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'political party_3': [0], 'non - party_4': [0]}
['name', 'born - died', 'term start', 'term end', 'political party']
[['prime ministers 1914 - 1925', 'prime ministers 1914 - 1925', 'prime ministers 1914 - 1925', 'prime ministers 1914 - 1925', 'prime ministers 1914 - 1925'], ['turhan pasha përmeti ( 1st time )', '1846 - 1927', '7 march 1914', '3 september 1914', 'non - party'], ['essad pasha toptani', '1863 - 1920', '5 october 1914', ...
list of earthquakes in iran
https://en.wikipedia.org/wiki/List_of_earthquakes_in_Iran
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10677198-1.html.csv
superlative
the biggest earthquake in iran during 2002-2013 happened in saravan .
{'scope': 'all', 'col_superlative': '4', 'row_superlative': '1', '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', 'magnitude'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; magnitude }'}, 'epicenter'], 'result': 'saravan , iran', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; magnitude } ; epicenter }'}, 'saravan , iran'], 'r...
eq { hop { argmax { all_rows ; magnitude } ; epicenter } ; saravan , iran } = true
select the row whose magnitude record of all rows is maximum . the epicenter record of this row is saravan , iran .
3
3
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'magnitude_5': 5, 'epicenter_6': 6, 'saravan , iran_7': 7}
{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'magnitude_5': 'magnitude', 'epicenter_6': 'epicenter', 'saravan , iran_7': 'saravan , iran'}
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'magnitude_5': [0], 'epicenter_6': [1], 'saravan , iran_7': [2]}
['date', 'time', 'epicenter', 'magnitude', 'fatalities', 'name']
[['apr 16 , 2013', '10:44:13', 'saravan , iran', '7.8', '1 ( non - residential area , due to landslide )', '2013 sistan and baluchestan earthquake'], ['apr 9 , 2013', '16:22:50', 'bushehr', '6.3', '30 ( early estimate )', '2013 bushehr earthquake'], ['aug 11 , 2012', '12:23:18', 'tabriz', '6.4 and 6.3', '306', '2012 ta...
lukoil
https://en.wikipedia.org/wiki/Lukoil
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1027881-2.html.csv
majority
all lukoil that was launched in 1958 has a capacity , mln tpa of 12 ,0 or more .
{'scope': 'subset', 'col': '5', 'most_or_all': 'all', 'criterion': 'greater_than_eq', 'value': '12,0', 'subset': {'col': '3', 'criterion': 'equal', 'value': '1958'}}
{'func': 'all_greater_eq', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'launched', '1958'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; launched ; 1958 }', 'tointer': 'select the rows whose launched record is equal to 1958 .'}, 'capacity , mln tpa', '12,0'], 'result': True, 'ind': 1, 'tointer': '...
all_greater_eq { filter_eq { all_rows ; launched ; 1958 } ; capacity , mln tpa ; 12,0 } = true
select the rows whose launched record is equal to 1958 . for the capacity , mln tpa records of these rows , all of them are greater than or equal to 12,0 .
2
2
{'all_greater_eq_1': 1, 'result_2': 2, 'filter_eq_0': 0, 'all_rows_3': 3, 'launched_4': 4, '1958_5': 5, 'capacity , mln tpa_6': 6, '12,0_7': 7}
{'all_greater_eq_1': 'all_greater_eq', 'result_2': 'true', 'filter_eq_0': 'filter_eq', 'all_rows_3': 'all_rows', 'launched_4': 'launched', '1958_5': '1958', 'capacity , mln tpa_6': 'capacity , mln tpa', '12,0_7': '12,0'}
{'all_greater_eq_1': [2], 'result_2': [], 'filter_eq_0': [1], 'all_rows_3': [0], 'launched_4': [0], '1958_5': [0], 'capacity , mln tpa_6': [1], '12,0_7': [1]}
['name', 'location', 'launched', 'acquired', 'capacity , mln tpa']
[['lukoil - nizhegorodnefteorgsintez', 'kstovo', '1958', '2000', '15 , 0'], ['lukoil - permnefteorgsintez', 'perm', '1958', '1991', '12 , 0'], ['lukoil - volgogradneftepererabotka', 'volgograd', '1957', '1991', '9 , 9'], ['lukoil - ukhtaneftepererabotka', 'ukhta', '1934', '2000', '3 , 7'], ['lukoil - odessky nefteperer...
utah jazz all - time roster
https://en.wikipedia.org/wiki/Utah_Jazz_all-time_roster
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11545282-10.html.csv
unique
mark jackson is the only player on the utah jazz all - time roster from the st john 's school .
{'scope': 'all', 'row': '1', 'col': '5', 'col_other': '1', 'criterion': 'equal', 'value': "st john 's", 'subset': None}
{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'school / club team', "st john 's"], 'result': None, 'ind': 0, 'tointer': "select the rows whose school / club team record fuzzily matches to st john 's .", 'tostr': "filter_eq { all_rows ; school / club team ; st john 's ...
and { only { filter_eq { all_rows ; school / club team ; st john 's } } ; eq { hop { filter_eq { all_rows ; school / club team ; st john 's } ; player } ; mark jackson } } = true
select the rows whose school / club team record fuzzily matches to st john 's . there is only one such row in the table . the player record of this unqiue row is mark jackson .
6
5
{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'school / club team_7': 7, "st john 's_8": 8, 'str_eq_3': 3, 'str_hop_2': 2, 'player_9': 9, 'mark jackson_10': 10}
{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'school / club team_7': 'school / club team', "st john 's_8": "st john 's", 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'player_9': 'player', 'mark jackson_10': 'mark jackson'}
{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'school / club team_7': [0], "st john 's_8": [0], 'str_eq_3': [4], 'str_hop_2': [3], 'player_9': [2], 'mark jackson_10': [3]}
['player', 'nationality', 'position', 'years for jazz', 'school / club team']
[['mark jackson', 'united states', 'point guard', '2002 - 03', "st john 's"], ['dave jamerson', 'united states', 'guard - forward', '1993', 'ohio'], ['aaron james', 'united states', 'forward', '1974 - 79', 'grambling state'], ['henry james', 'united states', 'forward', '1993', "st mary 's ( tx )"], ['al jefferson', 'un...
toronto , grey and bruce railway
https://en.wikipedia.org/wiki/Toronto%2C_Grey_and_Bruce_Railway
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15339223-1.html.csv
majority
most of the railways were built by avonside engine company .
{'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'avonside engine company', 'subset': None}
{'func': 'most_str_eq', 'args': ['all_rows', 'builder', 'avonside engine company'], 'result': True, 'ind': 0, 'tointer': 'for the builder records of all rows , most of them fuzzily match to avonside engine company .', 'tostr': 'most_eq { all_rows ; builder ; avonside engine company } = true'}
most_eq { all_rows ; builder ; avonside engine company } = true
for the builder records of all rows , most of them fuzzily match to avonside engine company .
1
1
{'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'builder_3': 3, 'avonside engine company_4': 4}
{'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'builder_3': 'builder', 'avonside engine company_4': 'avonside engine company'}
{'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'builder_3': [0], 'avonside engine company_4': [0]}
['number', 'name', 'builder', 'type', 'date', 'works number']
[['1', 'gordon', 'avonside engine company', '4 - 6 - 0', 'aug 1870', '799'], ['2', 'ar mcmaster', 'avonside engine company', '4 - 4 - 0', 'aug 1870', '800'], ['3', 'kincardine', 'avonside engine company', '4 - 4 - 0', 'september 1870', '809'], ['4', 'r walker & sons', 'avonside engine company', '4 - 4 - 0', 'may 1871',...
nathan ablett
https://en.wikipedia.org/wiki/Nathan_Ablett
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1756688-1.html.csv
superlative
nathan ablett played in the most games in the year of 2007 .
{'scope': 'all', 'col_superlative': '3', 'row_superlative': '3', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None}
{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'games'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; games }'}, 'season'], 'result': '2007', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; games } ; season }'}, '2007'], 'result': True, 'ind': 2, 'tostr': 'eq {...
eq { hop { argmax { all_rows ; games } ; season } ; 2007 } = true
select the row whose games record of all rows is maximum . the season record of this row is 2007 .
3
3
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'games_5': 5, 'season_6': 6, '2007_7': 7}
{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'games_5': 'games', 'season_6': 'season', '2007_7': '2007'}
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'games_5': [0], 'season_6': [1], '2007_7': [2]}
['season', 'team', 'games', 'disposals', 'kicks', 'handballs', 'marks', 'tackles', 'goals', 'behinds']
[['2005', 'geelong', '4', '27 ( 6.8 )', '19 ( 4.8 )', '8 ( 2.0 )', '13 ( 3.2 )', '5 ( 1.2 )', '8 ( 2.0 )', '2 ( 0.5 )'], ['2006', 'geelong', '7', '56 ( 8.0 )', '33 ( 4.7 )', '23 ( 3.3 )', '27 ( 3.9 )', '5 ( 0.7 )', '4 ( 0.6 )', '3 ( 0.4 )'], ['2007', 'geelong', '21', '191 ( 9.1 )', '117 ( 5.6 )', '74 ( 3.5 )', '86 ( 4....
1973 u.s. open ( golf )
https://en.wikipedia.org/wiki/1973_U.S._Open_%28golf%29
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17245540-2.html.csv
unique
only one player in the 1973 us open came from england .
{'scope': 'all', 'row': '7', 'col': '2', 'col_other': 'n/a', 'criterion': 'equal', 'value': 'england', 'subset': None}
{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'england'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose country record fuzzily matches to england .', 'tostr': 'filter_eq { all_rows ; country ; england }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_ro...
only { filter_eq { all_rows ; country ; england } } = true
select the rows whose country record fuzzily matches to england . there is only one such row in the table .
2
2
{'only_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, 'country_4': 4, 'england_5': 5}
{'only_1': 'only', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'country_4': 'country', 'england_5': 'england'}
{'only_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'country_4': [0], 'england_5': [0]}
['player', 'country', 'year ( s ) won', 'total', 'to par', 'finish']
[['jack nicklaus', 'united states', '1962 , 1967 , 1972', '282', '- 2', 't4'], ['arnold palmer', 'united states', '1960', '282', '- 2', 't4'], ['lee trevino', 'united states', '1968 , 1971', '282', '- 2', 't4'], ['julius boros', 'united states', '1952 , 1963', '283', '- 1', 't7'], ['gary player', 'south africa', '1965'...
oldest football competitions
https://en.wikipedia.org/wiki/Oldest_football_competitions
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18050568-2.html.csv
ordinal
the first football competition that took place in launceston , tasmania had victorian rules .
{'scope': 'subset', 'row': '4', 'col': '1', 'order': '1', 'col_other': '3', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'subset': {'col': '5', 'criterion': 'equal', 'value': 'launceston , tasmania'}}
{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location', 'launceston , tasmania'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; location ; launceston , tasmania }', 'tointer': 'select the rows whose location record ...
eq { hop { nth_argmin { filter_eq { all_rows ; location ; launceston , tasmania } ; years ; 1 } ; original code } ; victorian rules } = true
select the rows whose location record fuzzily matches to launceston , tasmania . select the row whose years record of these rows is 1st minimum . the original code record of this row is victorian rules .
4
4
{'str_eq_3': 3, 'result_4': 4, 'str_hop_2': 2, 'nth_argmin_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'location_6': 6, 'launceston , tasmania_7': 7, 'years_8': 8, '1_9': 9, 'original code_10': 10, 'victorian rules_11': 11}
{'str_eq_3': 'str_eq', 'result_4': 'true', 'str_hop_2': 'str_hop', 'nth_argmin_1': 'nth_argmin', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'location_6': 'location', 'launceston , tasmania_7': 'launceston , tasmania', 'years_8': 'years', '1_9': '1', 'original code_10': 'original code', 'victorian rul...
{'str_eq_3': [4], 'result_4': [], 'str_hop_2': [3], 'nth_argmin_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'location_6': [0], 'launceston , tasmania_7': [0], 'years_8': [1], '1_9': [1], 'original code_10': [2], 'victorian rules_11': [3]}
['years', 'type', 'original code', 'current code', 'location']
[['1860 -', 'interclub fixture', 'sheffield rules', 'defunct', 'sheffield , england'], ['1867 only', 'club trophy', 'sheffield rules', 'defunct', 'sheffield , england'], ['1868 only', 'club trophy', 'sheffield rules', 'defunct', 'sheffield , england'], ['1882 - 1883', 'club league', 'victorian rules', 'defunct', 'launc...
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
unique
the k297au call sign of family life radio is the only one with an fcc info .
{'scope': 'all', 'row': '5', 'col': '5', 'col_other': '1', 'criterion': 'equal', 'value': 'fcc', 'subset': None}
{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'fcc info', 'fcc'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose fcc info record fuzzily matches to fcc .', 'tostr': 'filter_eq { all_rows ; fcc info ; fcc }'}], 'result': True, 'ind': 1, 'tostr': 'only { fi...
and { only { filter_eq { all_rows ; fcc info ; fcc } } ; eq { hop { filter_eq { all_rows ; fcc info ; fcc } ; call sign } ; k297au } } = true
select the rows whose fcc info record fuzzily matches to fcc . there is only one such row in the table . the call sign record of this unqiue row is k297au .
6
5
{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'fcc info_7': 7, 'fcc_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'call sign_9': 9, 'k297au_10': 10}
{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'fcc info_7': 'fcc info', 'fcc_8': 'fcc', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'call sign_9': 'call sign', 'k297au_10': 'k297au'}
{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'fcc info_7': [0], 'fcc_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'call sign_9': [2], 'k297au_10': [3]}
['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']]
anaprof 2006
https://en.wikipedia.org/wiki/ANAPROF_2006
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11442591-4.html.csv
unique
the tauro fc is the only team with a single lost ( pp ) in the 2006 season of anaprof .
{'scope': 'all', 'row': '1', 'col': '6', 'col_other': '2', 'criterion': 'equal', 'value': '1', 'subset': None}
{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'lost ( pp )', '1'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose lost ( pp ) record is equal to 1 .', 'tostr': 'filter_eq { all_rows ; lost ( pp ) ; 1 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq ...
and { only { filter_eq { all_rows ; lost ( pp ) ; 1 } } ; eq { hop { filter_eq { all_rows ; lost ( pp ) ; 1 } ; team ( equipo ) } ; tauro fc } } = true
select the rows whose lost ( pp ) record is equal to 1 . there is only one such row in the table . the team ( equipo ) record of this unqiue row is tauro fc .
6
5
{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'lost (pp)_7': 7, '1_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'team (equipo)_9': 9, 'tauro fc_10': 10}
{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'lost (pp)_7': 'lost ( pp )', '1_8': '1', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'team (equipo)_9': 'team ( equipo )', 'tauro fc_10': 'tauro fc'}
{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'lost (pp)_7': [0], '1_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'team (equipo)_9': [2], 'tauro fc_10': [3]}
['place ( posición )', 'team ( equipo )', 'played ( pj )', 'won ( pg )', 'draw ( pe )', 'lost ( pp )', 'goals scored ( gf )', 'goals conceded ( gc )', '+ / - ( dif )', 'points ( pts )']
[['1', 'tauro fc', '18', '10', '7', '1', '31', '17', '+ 14', '37'], ['2', 'san francisco fc', '18', '11', '2', '5', '40', '25', '+ 15', '35'], ['3', 'arabe unido', '18', '10', '3', '5', '30', '20', '+ 10', '33'], ['4', 'atlético veragüense', '18', '9', '6', '3', '22', '16', '+ 6', '33'], ['5', 'plaza amador', '18', '9'...
wvtf
https://en.wikipedia.org/wiki/WVTF
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12155786-3.html.csv
ordinal
the 2nd highest frequency for wvtf was when the license was for the city of pound .
{'row': '5', 'col': '2', 'order': '2', 'col_other': '3', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None}
{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'frequency mhz', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; frequency mhz ; 2 }'}, 'city of license'], 'result': 'pound , virginia', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; frequency mhz...
eq { hop { nth_argmax { all_rows ; frequency mhz ; 2 } ; city of license } ; pound , virginia } = true
select the row whose frequency mhz record of all rows is 2nd maximum . the city of license record of this row is pound , virginia .
3
3
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'frequency mhz_5': 5, '2_6': 6, 'city of license_7': 7, 'pound , virginia_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', 'frequency mhz_5': 'frequency mhz', '2_6': '2', 'city of license_7': 'city of license', 'pound , virginia_8': 'pound , virginia'}
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'frequency mhz_5': [0], '2_6': [0], 'city of license_7': [1], 'pound , virginia_8': [2]}
['call sign', 'frequency mhz', 'city of license', 'erp w', 'fcc info']
[['w211bf', '90.1', 'big stone gap , virginia', '8', 'fcc'], ['w212bp', '90.3', 'clintwood , virginia', '1', 'fcc'], ['w211be', '90.1', 'lebanon , virginia', '8.5', 'fcc'], ['w219cj', '91.7', 'norton , virginia', '50', 'fcc'], ['w217bf', '91.3', 'pound , virginia', '1', 'fcc'], ['w215bj', '90.9', 'saint paul , virginia...
2009 open championship
https://en.wikipedia.org/wiki/2009_Open_Championship
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18811509-7.html.csv
comparative
in the 2009 open championship , mathew goggin earned 66600 more than justin leonard .
{'row_1': '6', 'row_2': '12', 'col': '6', 'col_other': '2', 'relation': 'diff', 'record_mentioned': 'no', 'diff_result': {'diff_value': '66600', 'bigger': 'row1'}}
{'func': 'eq', 'args': [{'func': 'diff', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', 'mathew goggin'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose player record fuzzily matches to mathew goggin .', 'tostr': 'filter_eq { all_rows ; player ; mathew goggin...
eq { diff { hop { filter_eq { all_rows ; player ; mathew goggin } ; money } ; hop { filter_eq { all_rows ; player ; justin leonard } ; money } } ; 66600 } = true
select the rows whose player record fuzzily matches to mathew goggin . take the money record of this row . select the rows whose player record fuzzily matches to justin leonard . take the money record of this row . the first record is 66600 larger than the second record .
6
6
{'eq_5': 5, 'result_6': 6, 'diff_4': 4, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_7': 7, 'player_8': 8, 'mathew goggin_9': 9, 'money_10': 10, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_11': 11, 'player_12': 12, 'justin leonard_13': 13, 'money_14': 14, '66600_15': 15}
{'eq_5': 'eq', 'result_6': 'true', 'diff_4': 'diff', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_7': 'all_rows', 'player_8': 'player', 'mathew goggin_9': 'mathew goggin', 'money_10': 'money', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_11': 'all_rows', 'player_12': 'p...
{'eq_5': [6], 'result_6': [], 'diff_4': [5], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_7': [0], 'player_8': [0], 'mathew goggin_9': [0], 'money_10': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_11': [1], 'player_12': [1], 'justin leonard_13': [1], 'money_14': [3], '66600_15': [5]}
['place', 'player', 'country', 'score', 'to par', 'money']
[['t1', 'stewart cink', 'united states', '66 + 72 + 71 + 69 = 278', '2', 'playoff'], ['t1', 'tom watson', 'united states', '65 + 70 + 71 + 72 = 278', '2', 'playoff'], ['t3', 'lee westwood', 'england', '68 + 70 + 70 + 71 = 279', '1', '255000'], ['t3', 'chris wood', 'england', '70 + 70 + 72 + 67 = 279', '1', '255000'], [...
dominik meffert
https://en.wikipedia.org/wiki/Dominik_Meffert
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13141391-4.html.csv
majority
in most of the tournaments that dominik meffert participated in , the clay surface was used .
{'scope': 'all', 'col': '2', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'clay', 'subset': None}
{'func': 'most_str_eq', 'args': ['all_rows', 'surface', 'clay'], 'result': True, 'ind': 0, 'tointer': 'for the surface records of all rows , most of them fuzzily match to clay .', 'tostr': 'most_eq { all_rows ; surface ; clay } = true'}
most_eq { all_rows ; surface ; clay } = true
for the surface records of all rows , most of them fuzzily match to clay .
1
1
{'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'surface_3': 3, 'clay_4': 4}
{'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'surface_3': 'surface', 'clay_4': 'clay'}
{'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'surface_3': [0], 'clay_4': [0]}
['tournament', 'surface', 'partner', 'opponents in the final', 'score in the final']
[['freudenstadt', 'clay', 'tomas behrend', 'alexandre sidorenko mischa zverev', '7 - 5 , 7 - 6 5'], ['durban', 'hard', 'rik de voest', 'stéphane bohli noam okun', '6 - 4 , 6 - 2'], ['tanger', 'clay', 'steve darcis', 'uladzimir ignatik martin kližan', '5 - 7 , 7 - 5 ,'], ['pereira', 'clay', 'philipp oswald', 'gero krets...
1979 buffalo bills season
https://en.wikipedia.org/wiki/1979_Buffalo_Bills_season
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17386076-3.html.csv
superlative
on october 7th against the chicaco bears , the bills had their highest attended game of the season .
{'scope': 'all', 'col_superlative': '5', 'row_superlative': '6', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '2,3', 'subset': None}
{'func': 'and', 'args': [{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'attendance'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; attendance }'}, 'date'], 'result': 'october 7 , 1979', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; attendance } ; date }'}, '...
and { eq { hop { argmax { all_rows ; attendance } ; date } ; october 7 , 1979 } ; eq { hop { argmax { all_rows ; attendance } ; opponent } ; chicago bears } } = true
select the row whose attendance record of all rows is maximum . the date record of this row is october 7 , 1979 . the opponent record of this row is chicago bears .
7
6
{'and_5': 5, 'result_6': 6, 'str_eq_2': 2, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_7': 7, 'attendance_8': 8, 'date_9': 9, 'october 7 , 1979_10': 10, 'str_eq_4': 4, 'str_hop_3': 3, 'opponent_11': 11, 'chicago bears_12': 12}
{'and_5': 'and', 'result_6': 'true', 'str_eq_2': 'str_eq', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_7': 'all_rows', 'attendance_8': 'attendance', 'date_9': 'date', 'october 7 , 1979_10': 'october 7 , 1979', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'opponent_11': 'opponent', 'chicago bears_12': 'chic...
{'and_5': [6], 'result_6': [], 'str_eq_2': [5], 'str_hop_1': [2], 'argmax_0': [1, 3], 'all_rows_7': [0], 'attendance_8': [0], 'date_9': [1], 'october 7 , 1979_10': [2], 'str_eq_4': [5], 'str_hop_3': [4], 'opponent_11': [3], 'chicago bears_12': [4]}
['week', 'date', 'opponent', 'result', 'attendance']
[['1', 'september 2 , 1979', 'miami dolphins', 'l 9 - 7', '69441'], ['2', 'september 9 , 1979', 'cincinnati bengals', 'w 51 - 24', '43504'], ['3', 'september 16 , 1979', 'san diego chargers', 'l 27 - 19', '50709'], ['4', 'september 23 , 1979', 'new york jets', 'w 46 - 31', '68731'], ['5', 'september 30 , 1979', 'baltim...
1977 washington redskins season
https://en.wikipedia.org/wiki/1977_Washington_Redskins_season
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15085862-2.html.csv
superlative
the buffalo bills were the opponent of the game of the '77 season of the washington redskins with the lowest attendance count .
{'scope': 'all', 'col_superlative': '5', 'row_superlative': '12', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '3', 'subset': None}
{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmin', 'args': ['all_rows', 'attendance'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; attendance }'}, 'opponent'], 'result': 'buffalo bills', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; attendance } ; opponent }'}, 'buffalo bills'], 're...
eq { hop { argmin { all_rows ; attendance } ; opponent } ; buffalo bills } = true
select the row whose attendance record of all rows is minimum . the opponent record of this row is buffalo bills .
3
3
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'attendance_5': 5, 'opponent_6': 6, 'buffalo bills_7': 7}
{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'attendance_5': 'attendance', 'opponent_6': 'opponent', 'buffalo bills_7': 'buffalo bills'}
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'attendance_5': [0], 'opponent_6': [1], 'buffalo bills_7': [2]}
['week', 'date', 'opponent', 'result', 'attendance']
[['1', 'september 18 , 1977', 'new york giants', 'l 20 - 17', '76086'], ['2', 'september 25 , 1977', 'atlanta falcons', 'w 10 - 6', '55031'], ['3', 'october 2 , 1977', 'st louis cardinals', 'w 24 - 14', '55031'], ['4', 'october 9 , 1977', 'tampa bay buccaneers', 'w 10 - 0', '58571'], ['5', 'october 16 , 1977', 'dallas ...
vc zenit - kazan
https://en.wikipedia.org/wiki/VC_Zenit-Kazan
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-14363116-1.html.csv
unique
matthew anderson is the only player on the vc zenit - kazan team from the united states .
{'scope': 'all', 'row': '1', 'col': '2', '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 }'}], 'resul...
and { only { filter_eq { all_rows ; nationality ; united states } } ; eq { hop { filter_eq { all_rows ; nationality ; united states } ; player } ; matthew anderson } } = true
select the rows whose nationality record fuzzily matches to united states . there is only one such row in the table . the player record of this unqiue row is matthew anderson .
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, 'player_9': 9, 'matthew anderson_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', 'player_9': 'player', 'matthew anderson_10': 'matthew anderson'}
{'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], 'player_9': [2], 'matthew anderson_10': [3]}
['shirt no', 'nationality', 'player', 'birth date', 'height', 'position']
[['1', 'united states', 'matthew anderson', 'april 18 , 1987 ( age26 )', '204', 'outside hitter'], ['3', 'russia', 'nikolay apalikov', 'august 26 , 1982 ( age31 )', '203', 'middle blocker'], ['4', 'russia', 'ivan demakov', 'june 1 , 1993 ( age20 )', '209', 'middle blocker'], ['5', 'italy', 'valerio vermiglio', 'march 1...
1994 u.s. open ( golf )
https://en.wikipedia.org/wiki/1994_U.S._Open_%28golf%29
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17162228-2.html.csv
count
7 players participated in the 1994 u.s. open ( golf ) .
{'scope': 'all', 'criterion': 'all', 'value': 'n/a', 'result': '7', 'col': '1', 'subset': None}
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_all', 'args': ['all_rows', 'player'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose player record is arbitrary .', 'tostr': 'filter_all { all_rows ; player }'}], 'result': '7', 'ind': 1, 'tostr': 'count { filter_all { all_rows ; player } ...
eq { count { filter_all { all_rows ; player } } ; 7 } = true
select the rows whose player record is arbitrary . the number of such rows is 7 .
3
3
{'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_all_0': 0, 'all_rows_4': 4, 'player_5': 5, '7_6': 6}
{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_all_0': 'filter_all', 'all_rows_4': 'all_rows', 'player_5': 'player', '7_6': '7'}
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_all_0': [1], 'all_rows_4': [0], 'player_5': [0], '7_6': [2]}
['player', 'country', 'year ( s ) won', 'total', 'to par', 'finish']
[['curtis strange', 'united states', '1988 , 1989', '280', '- 4', '4'], ['tom watson', 'united states', '1982', '283', '- 1', 't6'], ['hale irwin', 'united states', '1974 , 1979 , 1990', '287', '+ 3', 't18'], ['jack nicklaus', 'united states', '1962 , 1967 , 1972 , 1980', '292', '+ 8', 't28'], ['tom kite', 'united stat...
kim hyun - joong
https://en.wikipedia.org/wiki/Kim_Hyun-joong
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18629727-2.html.csv
count
kim hyun-joong has appeared in only 2 sitcoms .
{'scope': 'all', 'criterion': 'equal', 'value': 'sitcom', 'result': '2', 'col': '6', 'subset': None}
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'genre', 'sitcom'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose genre record fuzzily matches to sitcom .', 'tostr': 'filter_eq { all_rows ; genre ; sitcom }'}], 'result': '2', 'ind': 1, 'tostr': 'count { fi...
eq { count { filter_eq { all_rows ; genre ; sitcom } } ; 2 } = true
select the rows whose genre record fuzzily matches to sitcom . 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, 'genre_5': 5, 'sitcom_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', 'genre_5': 'genre', 'sitcom_6': 'sitcom', '2_7': '2'}
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'genre_5': [0], 'sitcom_6': [0], '2_7': [2]}
['year', 'title', 'hangul / japanese', 'role', 'network', 'genre']
[['2005', 'nonstop 5', '논스톱 5', 'guest ep208', 'mbc', 'sitcom'], ['2005', 'can love be refilled', '사랑도 리필이 되나요', 'william', 'kbs2', 'sitcom'], ['2007', 'hotelier', 'ホテリアー', 'cameo ep7 ( with ss501 )', 'tv asahi', 'drama'], ['2008', 'spotlight', '스포트라이트', 'cameo ( with ss501 )', 'mbc', 'drama'], ['2009', 'boys over flow...
1930 british empire games
https://en.wikipedia.org/wiki/1930_British_Empire_Games
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-177520-1.html.csv
majority
all of the ranks at the 1930 british empire games had at east one silver medal .
{'scope': 'all', 'col': '3', 'most_or_all': 'all', 'criterion': 'greater_than_eq', 'value': '1', 'subset': None}
{'func': 'all_greater_eq', 'args': ['all_rows', 'silver', '1'], 'result': True, 'ind': 0, 'tointer': 'for the silver records of all rows , all of them are greater than or equal to 1 .', 'tostr': 'all_greater_eq { all_rows ; silver ; 1 } = true'}
all_greater_eq { all_rows ; silver ; 1 } = true
for the silver records of all rows , all of them are greater than or equal to 1 .
1
1
{'all_greater_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'silver_3': 3, '1_4': 4}
{'all_greater_eq_0': 'all_greater_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'silver_3': 'silver', '1_4': '1'}
{'all_greater_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'silver_3': [0], '1_4': [0]}
['rank', 'gold', 'silver', 'bronze', 'total']
[['1', '25', '22', '13', '60'], ['2', '20', '16', '18', '54'], ['3', '6', '4', '8', '18'], ['4', '3', '4', '2', '9'], ['5', '3', '4', '1', '8'], ['6', '2', '3', '5', '10'], ['7', '0', '2', '1', '3'], ['8', '0', '1', '1', '2'], ['9', '0', '1', '0', '1'], ['total', '59', '57', '49', '165']]
jimmy davies
https://en.wikipedia.org/wiki/Jimmy_Davies
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1236195-3.html.csv
majority
jimmy davies drove a majority of years with the offenhauser l4 engine .
{'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'offenhauser l4', 'subset': None}
{'func': 'most_str_eq', 'args': ['all_rows', 'engine', 'offenhauser l4'], 'result': True, 'ind': 0, 'tointer': 'for the engine records of all rows , most of them fuzzily match to offenhauser l4 .', 'tostr': 'most_eq { all_rows ; engine ; offenhauser l4 } = true'}
most_eq { all_rows ; engine ; offenhauser l4 } = true
for the engine records of all rows , most of them fuzzily match to offenhauser l4 .
1
1
{'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'engine_3': 3, 'offenhauser l4_4': 4}
{'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'engine_3': 'engine', 'offenhauser l4_4': 'offenhauser l4'}
{'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'engine_3': [0], 'offenhauser l4_4': [0]}
['year', 'entrant', 'chassis', 'engine', 'points']
[['1950', 'pat clancy', 'ewing', 'offenhauser l4', '0'], ['1951', 'parks offenhauser / le parks', 'pawl', 'offenhauser l4', '0'], ['1953', 'pat clancy', 'kurtis kraft 500b', 'offenhauser l4', '0'], ['1954', 'bardahl / ed walsh', 'kurtis kraft 4000', 'offenhauser l4', '0'], ['1955', 'bardahl / pat clancy', 'kurtis kraft...
lexington legends
https://en.wikipedia.org/wiki/Lexington_Legends
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1031852-2.html.csv
unique
the 2013 season was the only year where kansas city was the mlb affiliate for the lexington legends .
{'scope': 'all', 'row': '13', 'col': '7', 'col_other': '1', 'criterion': 'equal', 'value': 'kansas city', 'subset': None}
{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'mlb affiliate', 'kansas city'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose mlb affiliate record fuzzily matches to kansas city .', 'tostr': 'filter_eq { all_rows ; mlb affiliate ; kansas city }'}], 'resul...
and { only { filter_eq { all_rows ; mlb affiliate ; kansas city } } ; eq { hop { filter_eq { all_rows ; mlb affiliate ; kansas city } ; season } ; 2013 } } = true
select the rows whose mlb affiliate record fuzzily matches to kansas city . there is only one such row in the table . the season record of this unqiue row is 2013 .
6
5
{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'mlb affiliate_7': 7, 'kansas city_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'season_9': 9, '2013_10': 10}
{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'mlb affiliate_7': 'mlb affiliate', 'kansas city_8': 'kansas city', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'season_9': 'season', '2013_10': '2013'}
{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'mlb affiliate_7': [0], 'kansas city_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'season_9': [2], '2013_10': [3]}
['season', 'manager', 'record', 'win %', 'post - season record', 'post - season win %', 'mlb affiliate']
[['2001', 'joe cannon', '92 - 48', '657', '4 - 0', '1.000', 'houston'], ['2002', 'joe cannon', '81 - 59', '579', '-', '-', 'houston'], ['2003 ♦', 'russ nixon', '75 - 63', '543', '0 - 2', '000', 'houston'], ['2004', 'iván dejesús', '68 - 72', '486', '-', '-', 'houston'], ['2005', 'tim bogar', '81 - 58', '583', '-', '-',...
clear lake ( oregon )
https://en.wikipedia.org/wiki/Clear_Lake_%28Oregon%29
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12484336-1.html.csv
majority
the majority of clear lake bodies of water in oregon are of the lake type .
{'scope': 'all', 'col': '2', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'lake', 'subset': None}
{'func': 'most_str_eq', 'args': ['all_rows', 'type', 'lake'], 'result': True, 'ind': 0, 'tointer': 'for the type records of all rows , most of them fuzzily match to lake .', 'tostr': 'most_eq { all_rows ; type ; lake } = true'}
most_eq { all_rows ; type ; lake } = true
for the type records of all rows , most of them fuzzily match to lake .
1
1
{'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'type_3': 3, 'lake_4': 4}
{'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'type_3': 'type', 'lake_4': 'lake'}
{'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'type_3': [0], 'lake_4': [0]}
['name', 'type', 'elevation', 'usgs map', 'gnis id']
[['clear lake ( douglas county , oregon )', 'lake', 'feet ( m )', 'winchester bay', '1139800'], ['clear lake ( wasco county , oregon )', 'reservoir', 'feet ( m )', 'wapinitia pass', '1139803'], ['clear lake ( amazon creek , oregon )', 'lake', 'feet ( m )', 'eugene west', '1119000'], ['clear lake ( marion county , orego...
list of tallest buildings in kansas city , missouri
https://en.wikipedia.org/wiki/List_of_tallest_buildings_in_Kansas_City%2C_Missouri
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12815540-4.html.csv
comparative
the historic federal reserve bank has less floors than the kansas city power and light building .
{'row_1': '3', 'row_2': '5', 'col': '5', 'col_other': '1', 'relation': 'less', 'record_mentioned': 'yes', 'diff_result': None}
{'func': 'and', 'args': [{'func': 'less', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'name', 'historic federal reserve bank'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose name record fuzzily matches to historic federal reserve bank .', 'tostr': 'filter_eq { all_...
and { less { hop { filter_eq { all_rows ; name ; historic federal reserve bank } ; floors } ; hop { filter_eq { all_rows ; name ; kansas city power and light building } ; floors } } ; and { eq { hop { filter_eq { all_rows ; name ; historic federal reserve bank } ; floors } ; 16 } ; eq { hop { filter_eq { all_rows ; nam...
select the rows whose name record fuzzily matches to historic federal reserve bank . take the floors record of this row . select the rows whose name record fuzzily matches to kansas city power and light building . take the floors record of this row . the first record is less than the second record . the floors record o...
13
9
{'and_8': 8, 'result_9': 9, 'less_4': 4, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_10': 10, 'name_11': 11, 'historic federal reserve bank_12': 12, 'floors_13': 13, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_14': 14, 'name_15': 15, 'kansas city power and light building_16': 16, 'floors_17': 17, 'and_7': 7, 'e...
{'and_8': 'and', 'result_9': 'true', 'less_4': 'less', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_10': 'all_rows', 'name_11': 'name', 'historic federal reserve bank_12': 'historic federal reserve bank', 'floors_13': 'floors', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_ro...
{'and_8': [9], 'result_9': [], 'less_4': [8], 'num_hop_2': [4, 5], 'filter_str_eq_0': [2], 'all_rows_10': [0], 'name_11': [0], 'historic federal reserve bank_12': [0], 'floors_13': [2], 'num_hop_3': [4, 6], 'filter_str_eq_1': [3], 'all_rows_14': [1], 'name_15': [1], 'kansas city power and light building_16': [1], 'floo...
['name', 'street address', 'years as tallest', 'height feet / m', 'floors']
[['new york life insurance building', '20 w ninth street', '1890 - 1906', '180 / 55', '12'], ['commerce trust building', '922 walnut street', '1906 - 1921', '258 / 79', '17'], ['historic federal reserve bank', '925 grand avenue', '1921 - 1929', '298 / 91', '16'], ['oak tower', '324 e 11th street', '1929 - 1931', '379 /...
new york film critics circle award for best foreign language film
https://en.wikipedia.org/wiki/New_York_Film_Critics_Circle_Award_for_Best_Foreign_Language_Film
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12788276-5.html.csv
comparative
bad education won an award after city of god did .
{'row_1': '5', 'row_2': '4', 'col': '1', 'col_other': '2', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None}
{'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'english title', 'bad education'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose english title record fuzzily matches to bad education .', 'tostr': 'filter_eq { all_rows ; english title ; bad education...
greater { hop { filter_eq { all_rows ; english title ; bad education } ; year } ; hop { filter_eq { all_rows ; english title ; city of god } ; year } } = true
select the rows whose english title record fuzzily matches to bad education . take the year record of this row . select the rows whose english title record fuzzily matches to city of god . take the year record of this row . the first record is greater than the second record .
5
5
{'greater_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'english title_7': 7, 'bad education_8': 8, 'year_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'english title_11': 11, 'city of god_12': 12, 'year_13': 13}
{'greater_4': 'greater', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'english title_7': 'english title', 'bad education_8': 'bad education', 'year_9': 'year', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'english tit...
{'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'english title_7': [0], 'bad education_8': [0], 'year_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'english title_11': [1], 'city of god_12': [1], 'year_13': [3]}
['year', 'english title', 'original title', 'country', 'director ( s )']
[['2000', 'yi yi : a one and a two', 'yi yi', 'japan / taiwan', 'edward yang'], ['2001', 'in the mood for love', 'fa yeung nin wa', 'france / hong kong', 'wong kar - wai'], ['2002', 'and your mother too', 'y tu mamá también', 'mexico', 'alfonso cuarón'], ['2003', 'city of god', 'cidade de deus', 'brazil', 'fernando mei...
united states house of representatives elections , 2006
https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_2006
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1805191-37.html.csv
unique
ernest istook was the only representative who retired that year .
{'scope': 'all', 'row': '5', 'col': '5', 'col_other': '2', 'criterion': 'equal', 'value': 'retired', 'subset': None}
{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'results', 'retired'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose results record fuzzily matches to retired .', 'tostr': 'filter_eq { all_rows ; results ; retired }'}], 'result': True, 'ind': 1, 'tostr': '...
and { only { filter_eq { all_rows ; results ; retired } } ; eq { hop { filter_eq { all_rows ; results ; retired } ; incumbent } ; ernest istook } } = true
select the rows whose results record fuzzily matches to retired . there is only one such row in the table . the incumbent record of this unqiue row is ernest istook .
6
5
{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'results_7': 7, 'retired_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'incumbent_9': 9, 'ernest istook_10': 10}
{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'results_7': 'results', 'retired_8': 'retired', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'incumbent_9': 'incumbent', 'ernest istook_10': 'ernest istook'}
{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'results_7': [0], 'retired_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'incumbent_9': [2], 'ernest istook_10': [3]}
['district', 'incumbent', 'party', 'first elected', 'results']
[['oklahoma 1', 'john sullivan', 'republican', '2002', 're - elected'], ['oklahoma 2', 'dan boren', 'democratic', '2004', 're - elected'], ['oklahoma 3', 'frank lucas', 'republican', '1994', 're - elected'], ['oklahoma 4', 'tom cole', 'republican', '2002', 're - elected'], ['oklahoma 5', 'ernest istook', 'republican', ...
sparc enterprise
https://en.wikipedia.org/wiki/SPARC_Enterprise
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-10818465-1.html.csv
count
in sparc enterprise , 2 of the ones with max memory 128 gb its max processors is 1 ultrasparc t2 .
{'scope': 'subset', 'criterion': 'equal', 'value': '1 ultrasparc t2', 'result': '2', 'col': '3', 'subset': {'col': '5', 'criterion': 'equal', 'value': '128 gb'}}
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'max memory', '128 gb'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; max memory ; 128 gb }', 'tointer': 'select the rows whose max memory record fuzzily matches to 128 gb ....
eq { count { filter_eq { filter_eq { all_rows ; max memory ; 128 gb } ; max processors ; 1 ultrasparc t2 } } ; 2 } = true
select the rows whose max memory record fuzzily matches to 128 gb . among these rows , select the rows whose max processors record fuzzily matches to 1 ultrasparc t2 . the number of such rows is 2 .
4
4
{'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_str_eq_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'max memory_6': 6, '128 gb_7': 7, 'max processors_8': 8, '1 ultrasparc t2_9': 9, '2_10': 10}
{'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_str_eq_1': 'filter_str_eq', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'max memory_6': 'max memory', '128 gb_7': '128 gb', 'max processors_8': 'max processors', '1 ultrasparc t2_9': '1 ultrasparc t2', '2_10': '2'}
{'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_str_eq_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'max memory_6': [0], '128 gb_7': [0], 'max processors_8': [1], '1 ultrasparc t2_9': [1], '2_10': [3]}
['model', 'ru', 'max processors', 'processor frequency', 'max memory', 'max disk capacity', 'ga date']
[['m3000', '2', '1 sparc64 vii or vii +', '2.52 , 2.75 ghz ( vii ) or 2.86 ghz ( vii + )', '64 gb', '4 2.5 sas', 'october 2008 ( vii ) , april 2011 ( vii + )'], ['t1000', '1', '1 ultrasparc t1', '1.0 ghz', '32 gb', 'one 3.5 sata or two 2.5 sas', 'march 2006'], ['t2000', '2', '1 ultrasparc t1', '1.0 , 1.2 , 1.4 ghz', '6...
2007 kansas lottery indy 300
https://en.wikipedia.org/wiki/2007_Kansas_Lottery_Indy_300
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-17693171-1.html.csv
ordinal
driver dan wheldon had the highest number of points in the 2007 kansas lottery indy 300 .
{'row': '1', 'col': '9', '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', 'points', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; points ; 1 }'}, 'driver'], 'result': 'dan wheldon', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; points ; 1 } ; driver }'}, 'dan wheldon']...
eq { hop { nth_argmax { all_rows ; points ; 1 } ; driver } ; dan wheldon } = true
select the row whose points record of all rows is 1st maximum . the driver record of this row is dan wheldon .
3
3
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'points_5': 5, '1_6': 6, 'driver_7': 7, 'dan wheldon_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', '1_6': '1', 'driver_7': 'driver', 'dan wheldon_8': 'dan wheldon'}
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'points_5': [0], '1_6': [0], 'driver_7': [1], 'dan wheldon_8': [2]}
['fin pos', 'car no', 'driver', 'team', 'laps', 'time / retired', 'grid', 'laps led', 'points']
[['1', '10', 'dan wheldon', 'target chip ganassi', '200', '1:36:56.0586', '4', '177', '50 + 3'], ['2', '27', 'dario franchitti', 'andretti green', '200', '+ 18.4830', '6', '0', '40'], ['3', '3', 'hãlio castroneves', 'team penske', '200', '+ 33.2280', '3', '0', '35'], ['4', '9', 'scott dixon', 'target chip ganassi', '20...
2000 san diego chargers season
https://en.wikipedia.org/wiki/2000_San_Diego_Chargers_season
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15331726-1.html.csv
aggregation
in the 2000 san diego chargers season the total attendance at the two games with the oakland raiders was 123,032 .
{'scope': 'subset', 'col': '7', 'type': 'sum', 'result': '123032', 'subset': {'col': '3', 'criterion': 'equal', 'value': 'oakland raiders'}}
{'func': 'round_eq', 'args': [{'func': 'sum', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', 'oakland raiders'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; opponent ; oakland raiders }', 'tointer': 'select the rows whose opponent record fuzzily matches to oakland raiders .'}, 'atten...
round_eq { sum { filter_eq { all_rows ; opponent ; oakland raiders } ; attendance } ; 123032 } = true
select the rows whose opponent record fuzzily matches to oakland raiders . the sum of the attendance record of these rows is 123032 .
3
3
{'eq_2': 2, 'result_3': 3, 'sum_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'opponent_5': 5, 'oakland raiders_6': 6, 'attendance_7': 7, '123032_8': 8}
{'eq_2': 'eq', 'result_3': 'true', 'sum_1': 'sum', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'opponent_5': 'opponent', 'oakland raiders_6': 'oakland raiders', 'attendance_7': 'attendance', '123032_8': '123032'}
{'eq_2': [3], 'result_3': [], 'sum_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'opponent_5': [0], 'oakland raiders_6': [0], 'attendance_7': [1], '123032_8': [2]}
['week', 'date', 'opponent', 'result', 'game site', 'record', 'attendance']
[['1', 'september 3 , 2000', 'oakland raiders', 'l 6 - 9', 'network associates coliseum', '0 - 1', '56373'], ['2', 'september 10 , 2000', 'new orleans saints', 'l 27 - 28', 'qualcomm stadium', '0 - 2', '51300'], ['3', 'september 17 , 2000', 'kansas city chiefs', 'l 10 - 42', 'arrowhead stadium', '0 - 3', '77604'], ['4'...
records of members of parliament of the united kingdom
https://en.wikipedia.org/wiki/Records_of_members_of_parliament_of_the_United_Kingdom
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11921877-1.html.csv
majority
the majority of members of parliament of the united kingdom belong to the labour party .
{'scope': 'all', 'col': '6', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'labour party', 'subset': None}
{'func': 'most_str_eq', 'args': ['all_rows', 'political party', 'labour party'], 'result': True, 'ind': 0, 'tointer': 'for the political party records of all rows , most of them fuzzily match to labour party .', 'tostr': 'most_eq { all_rows ; political party ; labour party } = true'}
most_eq { all_rows ; political party ; labour party } = true
for the political party records of all rows , most of them fuzzily match to labour party .
1
1
{'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'political party_3': 3, 'labour party_4': 4}
{'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'political party_3': 'political party', 'labour party_4': 'labour party'}
{'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'political party_3': [0], 'labour party_4': [0]}
['born', 'became oldest mp', 'left house', 'age on leaving', 'died', 'political party']
[['6 may 1866', '1945', '1950', '83 2', '24 april 1957', 'liberal party'], ['22 november 1871', '1950', 'feb 1964', '92 1', '25 february 1964', 'labour party'], ['30 november 1874', 'feb 1964', 'sep 1964', '89 2', '24 january 1965', 'conservative'], ['18 october 1884', 'sep 1964', '1970', '85 2', '8 may 1986', 'labour ...
joão barbosa
https://en.wikipedia.org/wiki/Jo%C3%A3o_Barbosa
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18864385-1.html.csv
unique
2004 was the only year that that joão barbosa had a dnf position .
{'scope': 'all', 'row': '1', 'col': '6', 'col_other': '1', 'criterion': 'equal', 'value': 'dnf', 'subset': None}
{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'pos', 'dnf'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose pos record fuzzily matches to dnf .', 'tostr': 'filter_eq { all_rows ; pos ; dnf }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_r...
and { only { filter_eq { all_rows ; pos ; dnf } } ; eq { hop { filter_eq { all_rows ; pos ; dnf } ; year } ; 2004 } } = true
select the rows whose pos record fuzzily matches to dnf . there is only one such row in the table . the year record of this unqiue row is 2004 .
6
5
{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'pos_7': 7, 'dnf_8': 8, 'eq_3': 3, 'num_hop_2': 2, 'year_9': 9, '2004_10': 10}
{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'pos_7': 'pos', 'dnf_8': 'dnf', 'eq_3': 'eq', 'num_hop_2': 'num_hop', 'year_9': 'year', '2004_10': '2004'}
{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'pos_7': [0], 'dnf_8': [0], 'eq_3': [4], 'num_hop_2': [3], 'year_9': [2], '2004_10': [3]}
['year', 'team', 'co - drivers', 'class', 'laps', 'pos', 'class pos']
[['2004', 'rollcentre racing', 'martin short rob barff', 'lmp1', '230', 'dnf', 'dnf'], ['2005', 'rollcentre racing', 'martin short vanina ickx', 'lmp1', '318', '16th', '8th'], ['2006', 'rollcentre racing', 'martin short stuart moseley', 'lmp2', '294', '20th', '5th'], ['2007', 'rollcentre racing', 'stuart hall martin sh...
1973 ohio state buckeyes football team
https://en.wikipedia.org/wiki/1973_Ohio_State_Buckeyes_football_team
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17824926-1.html.csv
ordinal
the ohio state buckeyes ' game against usc recorded their highest attendance of the 1973 football season .
{'row': '11', 'col': '6', 'order': '1', 'col_other': '2', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None}
{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'attendance', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; attendance ; 1 }'}, 'opponent'], 'result': '7 usc', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; attendance ; 1 } ; opponent }'}, '7 u...
eq { hop { nth_argmax { all_rows ; attendance ; 1 } ; opponent } ; 7 usc } = true
select the row whose attendance record of all rows is 1st maximum . the opponent record of this row is 7 usc .
3
3
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'attendance_5': 5, '1_6': 6, 'opponent_7': 7, '7 usc_8': 8}
{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'attendance_5': 'attendance', '1_6': '1', 'opponent_7': 'opponent', '7 usc_8': '7 usc'}
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'attendance_5': [0], '1_6': [0], 'opponent_7': [1], '7 usc_8': [2]}
['date', 'opponent', 'rank', 'site', 'result', 'attendance']
[['september 15', 'minnesota', '3', 'ohio stadium columbus , oh', 'w56 - 7', '86005'], ['september 29', 'tcu', '3', 'ohio stadium columbus , oh', 'w37 - 3', '87439'], ['october 6', 'washington state', '1', 'ohio stadium columbus , oh', 'w27 - 3', '87425'], ['october 13', 'wisconsin', '1', 'camp randall stadium madison ...
list of number - one singles of 1999 ( canada )
https://en.wikipedia.org/wiki/List_of_number-one_singles_of_1999_%28Canada%29
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17481317-1.html.csv
ordinal
livin ' la vida loca spent the 2nd highest number of weeks on top among all number one singles of 1999 in canada .
{'row': '12', 'col': '3', 'order': '2', 'col_other': '4', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None}
{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'weeks on top', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; weeks on top ; 2 }'}, 'song'], 'result': "livin ' la vida loca", 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; weeks on top ; 2 } ; s...
eq { hop { nth_argmax { all_rows ; weeks on top ; 2 } ; song } ; livin ' la vida loca } = true
select the row whose weeks on top record of all rows is 2nd maximum . the song record of this row is livin ' la vida loca .
3
3
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'weeks on top_5': 5, '2_6': 6, 'song_7': 7, "livin' la vida loca_8": 8}
{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'weeks on top_5': 'weeks on top', '2_6': '2', 'song_7': 'song', "livin' la vida loca_8": "livin ' la vida loca"}
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'weeks on top_5': [0], '2_6': [0], 'song_7': [1], "livin' la vida loca_8": [2]}
['volume : issue', 'issue date ( s )', 'weeks on top', 'song', 'artist']
[['68:10 - 12', '30 november - 4 january 1999 §', '6 §', 'thank u', 'alanis morissette'], ['68:13', '11 january - 18 january ≠', '2 ≠', "it 's all been done", 'barenaked ladies'], ['68:14', '25 january', '1', 'hands', 'jewel'], ['68:15', '1 february', '1', 'you get what you give', 'new radicals'], ['68:16', '8 february...
fabiano iha
https://en.wikipedia.org/wiki/Fabiano_Iha
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17445451-2.html.csv
comparative
fabiano iha 's fight against clever luciano lasted a longer time than his fight against john borsos .
{'row_1': '12', 'row_2': '14', 'col': '7', 'col_other': '3', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None}
{'func': 'greater', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', 'cleber luciano'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose opponent record fuzzily matches to cleber luciano .', 'tostr': 'filter_eq { all_rows ; opponent ; cleber luciano }'}, 'time'...
greater { hop { filter_eq { all_rows ; opponent ; cleber luciano } ; time } ; hop { filter_eq { all_rows ; opponent ; john borsos } ; time } } = true
select the rows whose opponent record fuzzily matches to cleber luciano . take the time record of this row . select the rows whose opponent record fuzzily matches to john borsos . take the time record of this row . the first record is greater than the second record .
5
5
{'greater_4': 4, 'result_5': 5, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'opponent_7': 7, 'cleber luciano_8': 8, 'time_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'opponent_11': 11, 'john borsos_12': 12, 'time_13': 13}
{'greater_4': 'greater', 'result_5': 'true', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'opponent_7': 'opponent', 'cleber luciano_8': 'cleber luciano', 'time_9': 'time', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'opponent_11': 'oppo...
{'greater_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'opponent_7': [0], 'cleber luciano_8': [0], 'time_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'opponent_11': [1], 'john borsos_12': [1], 'time_13': [3]}
['res', 'record', 'opponent', 'method', 'event', 'round', 'time']
[['win', '9 - 5', 'john cox', 'ko', 'lip 1 - lockdown in paradise 1', '1', '0:30'], ['win', '8 - 5', 'flavio troccoli', 'submission ( armbar )', 'hfp 2 - hitman fighting productions 2', '1', '0:53'], ['loss', '7 - 5', 'din thomas', 'decision ( unanimous )', 'ufc 33', '3', '5:00'], ['loss', '7 - 4', 'caol uno', 'ko ( pu...
2008 - 09 segunda división
https://en.wikipedia.org/wiki/2008%E2%80%9309_Segunda_Divisi%C3%B3n
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12951990-4.html.csv
superlative
chema was the goalkeeper who played the most matches in the 2008 - 09 segunda división .
{'scope': 'all', 'col_superlative': '3', 'row_superlative': '3', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None}
{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'matches'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; matches }'}, 'goalkeeper'], 'result': 'chema', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; matches } ; goalkeeper }'}, 'chema'], 'result': True, 'ind': 2...
eq { hop { argmax { all_rows ; matches } ; goalkeeper } ; chema } = true
select the row whose matches record of all rows is maximum . the goalkeeper record of this row is chema .
3
3
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'matches_5': 5, 'goalkeeper_6': 6, 'chema_7': 7}
{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'matches_5': 'matches', 'goalkeeper_6': 'goalkeeper', 'chema_7': 'chema'}
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'matches_5': [0], 'goalkeeper_6': [1], 'chema_7': [2]}
['goalkeeper', 'goals', 'matches', 'average', 'team']
[['david cobeño', '35', '40', '0.88', 'rayo vallecano'], ['claudio bravo', '28', '32', '0.88', 'real sociedad'], ['chema', '41', '41', '1', 'xerez cd'], ['carlos sánchez', '34', '34', '1', 'cd castellón'], ['alberto cifuentes', '34', '33', '1.03', 'ud salamanca'], ['juan calatayud', '42', '40', '1.05', 'hércules cf'], ...
1993 minnesota vikings season
https://en.wikipedia.org/wiki/1993_Minnesota_Vikings_season
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10362162-2.html.csv
superlative
the minnesota vikings ' game against the denver broncos had the most attendance in the 1993 season .
{'scope': 'all', 'col_superlative': '5', 'row_superlative': '9', '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', 'attendance'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; attendance }'}, 'opponent'], 'result': 'denver broncos', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; attendance } ; opponent }'}, 'denver broncos'], '...
eq { hop { argmax { all_rows ; attendance } ; opponent } ; denver broncos } = true
select the row whose attendance record of all rows is maximum . the opponent record of this row is denver broncos .
3
3
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'attendance_5': 5, 'opponent_6': 6, 'denver broncos_7': 7}
{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'attendance_5': 'attendance', 'opponent_6': 'opponent', 'denver broncos_7': 'denver broncos'}
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'attendance_5': [0], 'opponent_6': [1], 'denver broncos_7': [2]}
['week', 'date', 'opponent', 'result', 'attendance']
[['1', 'september 5 , 1993', 'los angeles raiders', 'l 24 - 7', '44120'], ['2', 'september 12 , 1993', 'chicago bears', 'w 10 - 7', '57921'], ['4', 'september 26 , 1993', 'green bay packers', 'w 15 - 13', '61746'], ['5', 'october 3 , 1993', 'san francisco 49ers', 'l 38 - 19', '63071'], ['6', 'october 10 , 1993', 'tampa...
athletics at the 1956 summer olympics - men 's long jump
https://en.wikipedia.org/wiki/Athletics_at_the_1956_Summer_Olympics_%E2%80%93_Men%27s_long_jump
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10676139-2.html.csv
superlative
gregory bell had the highest jump 3 score in the 1956 summer olympics - men 's long jump .
{'scope': 'all', 'col_superlative': '4', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None}
{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'jump 3'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; jump 3 }'}, 'athlete name'], 'result': 'gregory bell ( usa )', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; jump 3 } ; athlete name }'}, 'gregory bell ( us...
eq { hop { argmax { all_rows ; jump 3 } ; athlete name } ; gregory bell ( usa ) } = true
select the row whose jump 3 record of all rows is maximum . the athlete name record of this row is gregory bell ( usa ) .
3
3
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'jump 3_5': 5, 'athlete name_6': 6, 'gregory bell ( usa )_7': 7}
{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'jump 3_5': 'jump 3', 'athlete name_6': 'athlete name', 'gregory bell ( usa )_7': 'gregory bell ( usa )'}
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'jump 3_5': [0], 'athlete name_6': [1], 'gregory bell ( usa )_7': [2]}
['athlete name', 'jump 1', 'jump 2', 'jump 3', 'best jump']
[['gregory bell ( usa )', '6.98', '7.83', '7.77', '7.83 m'], ['john bennett ( usa )', '7.68', '7.61', 'x', '7.68 m'], ['jorma valkama ( fin )', '7.11', 'x', '7.48', '7.48 m'], ['dmitriy bondarenko ( urs )', '7.44', 'x', '7.13', '7.44 m'], ['karim olowu ( ngr )', '7.28', '6.77', '7.36', '7.36 m'], ['kazimierz kropidlows...
gilmour racing
https://en.wikipedia.org/wiki/Gilmour_Racing
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16351380-1.html.csv
aggregation
gilmour racing averaged 160.5 points in the australian formula 3 championship - national class .
{'scope': 'subset', 'col': '3', 'type': 'average', 'result': '160.5', 'subset': {'col': '2', 'criterion': 'equal', 'value': 'australian formula 3 championship - national class'}}
{'func': 'round_eq', 'args': [{'func': 'avg', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'series', 'australian formula 3 championship - national class'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; series ; australian formula 3 championship - national class }', 'tointer': 'select the rows wh...
round_eq { avg { filter_eq { all_rows ; series ; australian formula 3 championship - national class } ; points } ; 160.5 } = true
select the rows whose series record fuzzily matches to australian formula 3 championship - national class . the average of the points record of these rows is 160.5 .
3
3
{'eq_2': 2, 'result_3': 3, 'avg_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'series_5': 5, 'australian formula 3 championship - national class_6': 6, 'points_7': 7, '160.5_8': 8}
{'eq_2': 'eq', 'result_3': 'true', 'avg_1': 'avg', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'series_5': 'series', 'australian formula 3 championship - national class_6': 'australian formula 3 championship - national class', 'points_7': 'points', '160.5_8': '160.5'}
{'eq_2': [3], 'result_3': [], 'avg_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'series_5': [0], 'australian formula 3 championship - national class_6': [0], 'points_7': [1], '160.5_8': [2]}
['season', 'series', 'points', 'position', 'driver']
[['2001', 'queensland formula ford championship', '216', '2nd', 'chris gilmour'], ['2002', 'queensland formula ford championship', '234', '2nd', 'chris gilmour'], ['2003', 'queensland formula ford championship', '222', '1st', 'chris gilmour'], ['2004', 'australian formula 3 championship', '235', '2nd', 'chris gilmour']...
2008 in british television
https://en.wikipedia.org/wiki/2008_in_British_television
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-13549921-18.html.csv
majority
most of the programmes had itv as the original channel .
{'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'itv', 'subset': None}
{'func': 'most_str_eq', 'args': ['all_rows', 'original channel', 'itv'], 'result': True, 'ind': 0, 'tointer': 'for the original channel records of all rows , most of them fuzzily match to itv .', 'tostr': 'most_eq { all_rows ; original channel ; itv } = true'}
most_eq { all_rows ; original channel ; itv } = true
for the original channel records of all rows , most of them fuzzily match to itv .
1
1
{'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'original channel_3': 3, 'itv_4': 4}
{'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'original channel_3': 'original channel', 'itv_4': 'itv'}
{'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'original channel_3': [0], 'itv_4': [0]}
['programme', 'date ( s ) of original removal', 'original channel', 'date ( s ) of return', 'new channel ( s )']
[['mr and mrs as all star mr & mrs', '1999', 'itv', '12 april 2008', 'n / a ( same channel as original )'], ['itv news at ten', '5 march 1999 30 january 2004', 'itv', '22 january 2001 14 january 2008', 'n / a ( same channel as original )'], ['gladiators', '1 january 2000', 'itv', '11 may 2008', 'sky1'], ['superstars', ...
2008 - 09 croatian cup
https://en.wikipedia.org/wiki/2008%E2%80%9309_Croatian_Cup
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18828647-1.html.csv
majority
most of the rounds did n't have any new entries in the round .
{'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': 'none', 'subset': None}
{'func': 'most_str_eq', 'args': ['all_rows', 'new entries this round', 'none'], 'result': True, 'ind': 0, 'tointer': 'for the new entries this round records of all rows , most of them fuzzily match to none .', 'tostr': 'most_eq { all_rows ; new entries this round ; none } = true'}
most_eq { all_rows ; new entries this round ; none } = true
for the new entries this round 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, 'new entries this round_3': 3, 'none_4': 4}
{'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'new entries this round_3': 'new entries this round', 'none_4': 'none'}
{'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'new entries this round_3': [0], 'none_4': [0]}
['round', 'main date', 'number of fixtures', 'clubs', 'new entries this round']
[['preliminary round', '27 august 2008', '16', '48 → 32', 'none'], ['first round', '23 and 24 september 2008', '16', '32 → 16', '16'], ['second round', '29 october 2008', '8', '16 → 8', 'none'], ['quarter - finals', '12 and 26 november 2008', '8', '8 → 4', 'none'], ['semi - finals', '4 and 18 march 2009', '4', '4 → 2',...
1983 tampa bay buccaneers season
https://en.wikipedia.org/wiki/1983_Tampa_Bay_Buccaneers_season
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11440693-2.html.csv
superlative
the largest attendance of the 1983 tampa bay buccaneers season was at the last game of the season .
{'scope': 'all', 'col_superlative': '7', 'row_superlative': '17', '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', 'attendance'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; attendance }'}, 'week'], 'result': '16', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; attendance } ; week }'}, '16'], 'result': True, 'ind': 2, 'tostr'...
eq { hop { argmax { all_rows ; attendance } ; week } ; 16 } = true
select the row whose attendance record of all rows is maximum . the week record of this row is 16 .
3
3
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'attendance_5': 5, 'week_6': 6, '16_7': 7}
{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'attendance_5': 'attendance', 'week_6': 'week', '16_7': '16'}
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'attendance_5': [0], 'week_6': [1], '16_7': [2]}
['week', 'date', 'opponent', 'result', 'kickoff', 'game site', 'attendance', 'record']
[['week', 'date', 'opponent', 'result', 'kickoff', 'game site', 'attendance', 'record'], ['1', 'september 4 , 1983', 'detroit lions', 'l 11 - 0', '1:00', 'tampa stadium', '62154', '0 - 1'], ['2', 'september 11 , 1983', 'chicago bears', 'l 17 - 10', '1:00', 'soldier field', '58156', '0 - 2'], ['3', 'september 18 , 1983'...
2007 - 08 four hills tournament
https://en.wikipedia.org/wiki/2007%E2%80%9308_Four_Hills_Tournament
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14948647-3.html.csv
count
in the 2007 - 08 four hills tournament , among the players not from germany ( ger ) , 2 of them earned more than 257.0 points .
{'scope': 'subset', 'criterion': 'greater_than', 'value': '257.0', 'result': '2', 'col': '6', 'subset': {'col': '3', 'criterion': 'not_equal', 'value': 'ger'}}
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater', 'args': [{'func': 'filter_str_not_eq', 'args': ['all_rows', 'nationality', 'ger'], 'result': None, 'ind': 0, 'tostr': 'filter_not_eq { all_rows ; nationality ; ger }', 'tointer': 'select the rows whose nationality record does not match to ger...
eq { count { filter_greater { filter_not_eq { all_rows ; nationality ; ger } ; points ; 257.0 } } ; 2 } = true
select the rows whose nationality record does not match to ger . among these rows , select the rows whose points record is greater than 257.0 . the number of such rows is 2 .
4
4
{'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_greater_1': 1, 'filter_str_not_eq_0': 0, 'all_rows_5': 5, 'nationality_6': 6, 'ger_7': 7, 'points_8': 8, '257.0_9': 9, '2_10': 10}
{'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_greater_1': 'filter_greater', 'filter_str_not_eq_0': 'filter_str_not_eq', 'all_rows_5': 'all_rows', 'nationality_6': 'nationality', 'ger_7': 'ger', 'points_8': 'points', '257.0_9': '257.0', '2_10': '2'}
{'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_greater_1': [2], 'filter_str_not_eq_0': [1], 'all_rows_5': [0], 'nationality_6': [0], 'ger_7': [0], 'points_8': [1], '257.0_9': [1], '2_10': [3]}
['rank', 'name', 'nationality', '1st ( m )', '2nd ( m )', 'points', 'overall fht points', 'overall wc points ( rank )']
[['1', 'gregor schlierenzauer', 'aut', '132.0', '141.0', '274.4', '555.1 ( 1 )', '609 ( 2 )'], ['2', 'janne ahonen', 'fin', '139.0', '135.0', '272.7', '551.7 ( 3 )', '415 ( 3 )'], ['3', 'michael neumayer', 'ger', '131.5', '135.5', '258.6', '518.1 ( 5 )', '240 ( 10 )'], ['4', 'roman koudelka', 'cze', '132.0', '132.0', '...
harlem rocker
https://en.wikipedia.org/wiki/Harlem_Rocker
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17644295-1.html.csv
superlative
hallandale beach was the first site location on which harlem rocker participated in a race .
{'scope': 'all', 'col_superlative': '1', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '4', 'subset': None}
{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmin', 'args': ['all_rows', 'date'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; date }'}, 'location'], 'result': 'hallandale beach , florida', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; date } ; location }'}, 'hallandale beach , florid...
eq { hop { argmin { all_rows ; date } ; location } ; hallandale beach , florida } = true
select the row whose date record of all rows is minimum . the location record of this row is hallandale beach , florida .
3
3
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'date_5': 5, 'location_6': 6, 'hallandale beach , florida_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_6': 'location', 'hallandale beach , florida_7': 'hallandale beach , florida'}
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'date_5': [0], 'location_6': [1], 'hallandale beach , florida_7': [2]}
['date', 'race', 'track', 'location', 'distance', 'surface', 'purse', 'finish']
[['february 14 , 2008', 'maiden special weight', 'gulfstream park', 'hallandale beach , florida', '7 fur', 'dirt', '40000', '1st'], ['march 30 , 2008', 'allowance', 'gulfstream park', 'hallandale beach , florida', '1 mi', 'dirt', '42500', '1st'], ['april 26 , 2008', 'withers stakes', 'aqueduct racetrack', 'new york cit...
list of mountains in norway by prominence
https://en.wikipedia.org/wiki/List_of_mountains_in_Norway_by_prominence
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12280396-1.html.csv
count
two of the mountains in norway are located in oppland county .
{'scope': 'all', 'criterion': 'equal', 'value': 'oppland', 'result': '2', 'col': '6', 'subset': None}
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'county', 'oppland'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose county record fuzzily matches to oppland .', 'tostr': 'filter_eq { all_rows ; county ; oppland }'}], 'result': '2', 'ind': 1, 'tostr': 'coun...
eq { count { filter_eq { all_rows ; county ; oppland } } ; 2 } = true
select the rows whose county record fuzzily matches to oppland . 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, 'county_5': 5, 'oppland_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', 'county_5': 'county', 'oppland_6': 'oppland', '2_7': '2'}
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'county_5': [0], 'oppland_6': [0], '2_7': [2]}
['peak', 'elevation ( m )', 'prominence ( m )', 'isolation ( km )', 'municipality', 'county']
[['galdhøpiggen', '2469', '2372', '1570', 'lom', 'oppland'], ['jiehkkevárri', '1833', '1741', '140', 'lyngen , tromsø', 'troms'], ['snøhetta', '2286', '1675', '83', 'dovre', 'oppland'], ['store lenangstind', '1625', '1576', '47', 'lyngen', 'troms'], ['gjegnen / blånibba', '1670', '1460', '47', 'bremanger', 'sogn og fjo...
1960 philadelphia eagles season
https://en.wikipedia.org/wiki/1960_Philadelphia_Eagles_season
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16678519-2.html.csv
aggregation
the 1960 philadelphia eagles scored an average of 24.69 points a game .
{'scope': 'all', 'col': '4', 'type': 'average', 'result': '24.69', 'subset': None}
{'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'result'], 'result': '24.69', 'ind': 0, 'tostr': 'avg { all_rows ; result }'}, '24.69'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; result } ; 24.69 } = true', 'tointer': 'the average of the result record of all rows is 24.69 .'}
round_eq { avg { all_rows ; result } ; 24.69 } = true
the average of the result record of all rows is 24.69 .
2
2
{'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'result_4': 4, '24.69_5': 5}
{'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'result_4': 'result', '24.69_5': '24.69'}
{'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'result_4': [0], '24.69_5': [1]}
['week', 'date', 'opponent', 'result', 'attendance']
[['1', 'september 25 , 1960', 'cleveland browns', 'l 24 - 41', '56303'], ['2', 'september 30 , 1960', 'dallas cowboys', 'w 27 - 25', '18500'], ['3', 'october 9 , 1960', 'st louis cardinals', 'w 31 - 27', '33701'], ['4', 'october 16 , 1960', 'detroit lions', 'w 28 - 10', '38065'], ['5', 'october 23 , 1960', 'cleveland b...
media in sherbrooke
https://en.wikipedia.org/wiki/Media_in_Sherbrooke
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18409243-1.html.csv
unique
of the media in sherbrooke , only the station with the format campus radio is cfak - fm .
{'scope': 'all', 'row': '2', 'col': '3', 'col_other': '2', 'criterion': 'equal', 'value': 'campus radio', 'subset': None}
{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'format', 'campus radio'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose format record fuzzily matches to campus radio .', 'tostr': 'filter_eq { all_rows ; format ; campus radio }'}], 'result': True, 'ind': 1...
and { only { filter_eq { all_rows ; format ; campus radio } } ; eq { hop { filter_eq { all_rows ; format ; campus radio } ; call sign } ; cfak - fm } } = true
select the rows whose format record fuzzily matches to campus radio . there is only one such row in the table . the call sign record of this unqiue row is cfak - fm .
6
5
{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'format_7': 7, 'campus radio_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'call sign_9': 9, 'cfak - fm_10': 10}
{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'format_7': 'format', 'campus radio_8': 'campus radio', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'call sign_9': 'call sign', 'cfak - fm_10': 'cfak - fm'}
{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'format_7': [0], 'campus radio_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'call sign_9': [2], 'cfak - fm_10': [3]}
['frequency', 'call sign', 'format', 'owner', 'notes']
[['fm 88.1', 'cfpp - fm', 'christian radio', 'fabrique notre - dame du perpétuel - secours', 'french'], ['fm 88.3', 'cfak - fm', 'campus radio', 'université de sherbrooke', 'french'], ['fm 88.9', 'cjmq - fm', 'community radio', "bishop 's university", 'english'], ['fm 89.7', 'cbm - fm - 1', 'public music', 'canadian br...
1938 vfl season
https://en.wikipedia.org/wiki/1938_VFL_season
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10806592-9.html.csv
majority
a majority of the time the crowd was over 10,000 people .
{'scope': 'all', 'col': '6', 'most_or_all': 'most', 'criterion': 'greater_than', 'value': '10,000', 'subset': None}
{'func': 'most_greater', 'args': ['all_rows', 'crowd', '10,000'], 'result': True, 'ind': 0, 'tointer': 'for the crowd records of all rows , most of them are greater than 10,000 .', 'tostr': 'most_greater { all_rows ; crowd ; 10,000 } = true'}
most_greater { all_rows ; crowd ; 10,000 } = true
for the crowd records of all rows , most of them are greater than 10,000 .
1
1
{'most_greater_0': 0, 'result_1': 1, 'all_rows_2': 2, 'crowd_3': 3, '10,000_4': 4}
{'most_greater_0': 'most_greater', 'result_1': 'true', 'all_rows_2': 'all_rows', 'crowd_3': 'crowd', '10,000_4': '10,000'}
{'most_greater_0': [1], 'result_1': [], 'all_rows_2': [0], 'crowd_3': [0], '10,000_4': [0]}
['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date']
[['geelong', '11.23 ( 89 )', 'hawthorn', '6.13 ( 49 )', 'corio oval', '7000', '18 june 1938'], ['fitzroy', '16.12 ( 108 )', 'south melbourne', '8.8 ( 56 )', 'brunswick street oval', '12000', '18 june 1938'], ['st kilda', '14.12 ( 96 )', 'melbourne', '16.16 ( 112 )', 'junction oval', '14000', '18 june 1938'], ['richmond...
1973 - 74 football league cup
https://en.wikipedia.org/wiki/1973%E2%80%9374_Football_League_Cup
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-24887326-8.html.csv
majority
most of the 1973-74 football league cup matches that had over 10000 people were played on 21-11-1973 .
{'scope': 'subset', 'col': '6', 'most_or_all': 'most', 'criterion': 'equal', 'value': '21 - 11 - 1973', 'subset': {'col': '5', 'criterion': 'greater_than', 'value': '10000'}}
{'func': 'most_str_eq', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'attendance', '10000'], 'result': None, 'ind': 0, 'tostr': 'filter_greater { all_rows ; attendance ; 10000 }', 'tointer': 'select the rows whose attendance record is greater than 10000 .'}, 'date', '21 - 11 - 1973'], 'result': True, 'ind':...
most_eq { filter_greater { all_rows ; attendance ; 10000 } ; date ; 21 - 11 - 1973 } = true
select the rows whose attendance record is greater than 10000 . for the date records of these rows , most of them fuzzily match to 21 - 11 - 1973 .
2
2
{'most_str_eq_1': 1, 'result_2': 2, 'filter_greater_0': 0, 'all_rows_3': 3, 'attendance_4': 4, '10000_5': 5, 'date_6': 6, '21 - 11 - 1973_7': 7}
{'most_str_eq_1': 'most_str_eq', 'result_2': 'true', 'filter_greater_0': 'filter_greater', 'all_rows_3': 'all_rows', 'attendance_4': 'attendance', '10000_5': '10000', 'date_6': 'date', '21 - 11 - 1973_7': '21 - 11 - 1973'}
{'most_str_eq_1': [2], 'result_2': [], 'filter_greater_0': [1], 'all_rows_3': [0], 'attendance_4': [0], '10000_5': [0], 'date_6': [1], '21 - 11 - 1973_7': [1]}
['tie no', 'home team', 'score 1', 'away team', 'attendance', 'date']
[['1', 'york city', '0 - 0', 'manchester city', '15360', '21 - 11 - 1973'], ['2', 'queens park rangers', '0 - 3', 'plymouth argyle', '19072', '20 - 11 - 1973'], ['3', 'southampton', '0 - 2', 'norwich city', '14415', '21 - 11 - 1973'], ['4', 'ipswich town', '1 - 3', 'birmingham city', '12241', '21 - 11 - 1973'], ['5', '...
will & grace ( season 5 )
https://en.wikipedia.org/wiki/Will_%26_Grace_%28season_5%29
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27833469-1.html.csv
majority
the majority of episodes had over 15 million viewers .
{'scope': 'all', 'col': '7', 'most_or_all': 'most', 'criterion': 'greater_than_eq', 'value': '15', 'subset': None}
{'func': 'most_greater_eq', 'args': ['all_rows', 'us viewers ( millions )', '15'], 'result': True, 'ind': 0, 'tointer': 'for the us viewers ( millions ) records of all rows , most of them are greater than or equal to 15 .', 'tostr': 'most_greater_eq { all_rows ; us viewers ( millions ) ; 15 } = true'}
most_greater_eq { all_rows ; us viewers ( millions ) ; 15 } = true
for the us viewers ( millions ) records of all rows , most of them are greater than or equal to 15 .
1
1
{'most_greater_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'us viewers (millions)_3': 3, '15_4': 4}
{'most_greater_eq_0': 'most_greater_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'us viewers (millions)_3': 'us viewers ( millions )', '15_4': '15'}
{'most_greater_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'us viewers (millions)_3': [0], '15_4': [0]}
['series', 'season', 'title', 'directed by', 'written by', 'original air date', 'us viewers ( millions )']
[['93', '1', 'and the horse he rode in on', 'james burrows', 'adam barr', 'september 26 , 2002', '21.5'], ['94', '2', 'bacon and eggs', 'james burrows', 'alex herschlag', 'october 3 , 2002', '20.6'], ['95', '3', 'the kid stays out of the picture', 'james burrows', 'jhoni marchinko', 'october 10 , 2002', '20.2'], ['96',...
1981 vfl season
https://en.wikipedia.org/wiki/1981_VFL_season
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10823950-14.html.csv
ordinal
vfl park venue recorded the highest crowd participation during the 1981 vfl season .
{'row': '5', 'col': '6', 'order': '1', 'col_other': '5', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None}
{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'crowd', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; crowd ; 1 }'}, 'venue'], 'result': 'vfl park', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; crowd ; 1 } ; venue }'}, 'vfl park'], 'result':...
eq { hop { nth_argmax { all_rows ; crowd ; 1 } ; venue } ; vfl park } = true
select the row whose crowd record of all rows is 1st maximum . the venue record of this row is vfl park .
3
3
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'crowd_5': 5, '1_6': 6, 'venue_7': 7, 'vfl park_8': 8}
{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'crowd_5': 'crowd', '1_6': '1', 'venue_7': 'venue', 'vfl park_8': 'vfl park'}
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'crowd_5': [0], '1_6': [0], 'venue_7': [1], 'vfl park_8': [2]}
['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date']
[['carlton', '15.25 ( 115 )', 'footscray', '5.4 ( 34 )', 'princes park', '17419', '27 june 1981'], ['richmond', '21.23 ( 149 )', 'north melbourne', '15.16 ( 106 )', 'mcg', '31212', '27 june 1981'], ['st kilda', '18.19 ( 127 )', 'melbourne', '8.7 ( 55 )', 'moorabbin oval', '14058', '27 june 1981'], ['south melbourne', '...
minnesota golden gophers football under bernie bierman
https://en.wikipedia.org/wiki/Minnesota_Golden_Gophers_football_under_Bernie_Bierman
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16518708-2.html.csv
comparative
more points were scored in the golden gopher 's game on september 30 , 1993 than the game on november 4 .
{'row_1': '1', 'row_2': '6', 'col': '4', 'col_other': '1', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None}
{'func': 'greater', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', '09 / 30 / 1933'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose date record fuzzily matches to 09 / 30 / 1933 .', 'tostr': 'filter_eq { all_rows ; date ; 09 / 30 / 1933 }'}, 'result'], 'result...
greater { hop { filter_eq { all_rows ; date ; 09 / 30 / 1933 } ; result } ; hop { filter_eq { all_rows ; date ; 11 / 04 / 1933 } ; result } } = true
select the rows whose date record fuzzily matches to 09 / 30 / 1933 . take the result record of this row . select the rows whose date record fuzzily matches to 11 / 04 / 1933 . take the result record of this row . the first record is greater than the second record .
5
5
{'greater_4': 4, 'result_5': 5, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'date_7': 7, '09 / 30 / 1933_8': 8, 'result_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'date_11': 11, '11 / 04 / 1933_12': 12, 'result_13': 13}
{'greater_4': 'greater', 'result_5': 'true', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'date_7': 'date', '09 / 30 / 1933_8': '09 / 30 / 1933', 'result_9': 'result', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'date_11': 'date', '11 /...
{'greater_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'date_7': [0], '09 / 30 / 1933_8': [0], 'result_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'date_11': [1], '11 / 04 / 1933_12': [1], 'result_13': [3]}
['date', 'opponent', 'site', 'result', 'attendance']
[['09 / 30 / 1933', 'south dakota state', 'memorial stadium minneapolis , mn', 'w19 - 6', '25000'], ['10 / 07 / 1933', 'indiana', 'memorial stadium minneapolis , mn', 't6 - 6', '20000'], ['10 / 14 / 1933', 'purdue', 'memorial stadium minneapolis , mn', 't7 - 7', '26497'], ['10 / 21 / 1933', 'pittsburgh', 'memorial stad...
1991 san diego chargers season
https://en.wikipedia.org/wiki/1991_San_Diego_Chargers_season
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15345678-1.html.csv
count
in the 1991 san diego chargers season , two of the players went to school at tennessee .
{'scope': 'all', 'criterion': 'equal', 'value': 'tennessee', 'result': '2', 'col': '5', 'subset': None}
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'school / club team', 'tennessee'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose school / club team record fuzzily matches to tennessee .', 'tostr': 'filter_eq { all_rows ; school / club team ; tennessee }'}...
eq { count { filter_eq { all_rows ; school / club team ; tennessee } } ; 2 } = true
select the rows whose school / club team record fuzzily matches to tennessee . 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, 'school / club team_5': 5, 'tennessee_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', 'school / club team_5': 'school / club team', 'tennessee_6': 'tennessee', '2_7': '2'}
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'school / club team_5': [0], 'tennessee_6': [0], '2_7': [2]}
['round', 'pick', 'player', 'position', 'school / club team']
[['1', '9', 'stanley richard', 'defensive back', 'texas'], ['2', '36', 'george thornton', 'defensive tackle', 'alabama'], ['2', '39', 'eric bieniemy', 'running back', 'colorado'], ['2', '47', 'eric moten', 'guard', 'michigan state'], ['4', '90', 'yancey thigpen', 'wide receiver', 'winston - salem state'], ['5', '123', ...
list of dams and reservoirs in asturias
https://en.wikipedia.org/wiki/List_of_dams_and_reservoirs_in_Asturias
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-28702208-1.html.csv
unique
in the list of dams and reservoirs in asturias , the only one of gravity type that has drainage basin 0.0 km square its location is morcín .
{'scope': 'subset', 'row': '9', 'col': '7', 'col_other': '3', 'criterion': 'equal', 'value': '0.0', 'subset': {'col': '4', 'criterion': 'equal', 'value': 'gravity'}}
{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'type', 'gravity'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; type ; gravity }', 'tointer': 'select the rows whose type record fuzzily matches to gravity .'}, 'drainage basin...
and { only { filter_eq { filter_eq { all_rows ; type ; gravity } ; drainage basin ( km square ) ; 0.0 } } ; eq { hop { filter_eq { filter_eq { all_rows ; type ; gravity } ; drainage basin ( km square ) ; 0.0 } ; location } ; morcín } } = true
select the rows whose type record fuzzily matches to gravity . among these rows , select the rows whose drainage basin ( km square ) record is equal to 0.0 . there is only one such row in the table . the location record of this unqiue row is morcín .
8
6
{'and_5': 5, 'result_6': 6, 'only_2': 2, 'filter_eq_1': 1, 'filter_str_eq_0': 0, 'all_rows_7': 7, 'type_8': 8, 'gravity_9': 9, 'drainage basin (km square)_10': 10, '0.0_11': 11, 'str_eq_4': 4, 'str_hop_3': 3, 'location_12': 12, 'morcín_13': 13}
{'and_5': 'and', 'result_6': 'true', 'only_2': 'only', 'filter_eq_1': 'filter_eq', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_7': 'all_rows', 'type_8': 'type', 'gravity_9': 'gravity', 'drainage basin (km square)_10': 'drainage basin ( km square )', '0.0_11': '0.0', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'loca...
{'and_5': [6], 'result_6': [], 'only_2': [5], 'filter_eq_1': [2, 3], 'filter_str_eq_0': [1], 'all_rows_7': [0], 'type_8': [0], 'gravity_9': [0], 'drainage basin (km square)_10': [1], '0.0_11': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'location_12': [3], 'morcín_13': [4]}
['reservoir', 'basin', 'location', 'type', 'height ( m )', 'length along the top ( m )', 'drainage basin ( km square )', 'reservoir surface ( ha )', 'volume ( hm cubic )']
[['alfilorios', 'barrea', 'ribera de arriba', 'embankment', '67.0', '171.7', '4.09', '52.0', '9.140'], ['arbón', 'navia', 'coaña , villayón', 'embankment', '35.0', '180.0', '2443.0', '270.0', '38.20'], ['barca , la', 'narcea', 'belmonte , tineo', 'arch', '73.5', '178.0', '1216.0', '194.0', '31.10'], ['doiras', 'navia',...
amy alcott
https://en.wikipedia.org/wiki/Amy_Alcott
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1629086-4.html.csv
majority
amy alcott won the nabisco dinah shore major championship more often than any other major competition she was in .
{'scope': 'all', 'col': '2', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'nabisco dinah shore', 'subset': None}
{'func': 'most_str_eq', 'args': ['all_rows', 'championship', 'nabisco dinah shore'], 'result': True, 'ind': 0, 'tointer': 'for the championship records of all rows , most of them fuzzily match to nabisco dinah shore .', 'tostr': 'most_eq { all_rows ; championship ; nabisco dinah shore } = true'}
most_eq { all_rows ; championship ; nabisco dinah shore } = true
for the championship records of all rows , most of them fuzzily match to nabisco dinah shore .
1
1
{'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'championship_3': 3, 'nabisco dinah shore_4': 4}
{'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'championship_3': 'championship', 'nabisco dinah shore_4': 'nabisco dinah shore'}
{'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'championship_3': [0], 'nabisco dinah shore_4': [0]}
['year', 'championship', 'winning score', 'margin', 'runner ( s ) - up']
[['1979', 'peter jackson classic', '7 ( 75 + 70 + 70 + 70 = 285 )', '3 strokes', 'nancy lopez'], ['1980', "us women 's open", '4 ( 70 + 70 + 68 + 72 = 280 )', '9 strokes', 'hollis stacy'], ['1983', 'nabisco dinah shore', '6 ( 70 + 70 + 70 + 72 = 282 )', '2 strokes', 'beth daniel , kathy whitworth'], ['1988', 'nabisco d...
katie taylor
https://en.wikipedia.org/wiki/Katie_Taylor
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12426364-1.html.csv
ordinal
the second tournament that katie taylor played in was in warsaw , poland .
{'row': '2', 'col': '1', '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', 'year', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; year ; 2 }'}, 'venue'], 'result': 'warsaw , poland', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; year ; 2 } ; venue }'}, 'warsaw , poland']...
eq { hop { nth_argmin { all_rows ; year ; 2 } ; venue } ; warsaw , poland } = true
select the row whose year record of all rows is 2nd minimum . the venue record of this row is warsaw , poland .
3
3
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'year_5': 5, '2_6': 6, 'venue_7': 7, 'warsaw , poland_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', 'year_5': 'year', '2_6': '2', 'venue_7': 'venue', 'warsaw , poland_8': 'warsaw , poland'}
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'year_5': [0], '2_6': [0], 'venue_7': [1], 'warsaw , poland_8': [2]}
['year', 'tournament', 'venue', 'result', 'event']
[['2005', 'european amateur championships', 'tãnsberg , norway', '1st', '60 kg'], ['2006', 'european amateur championships', 'warsaw , poland', '1st', '60 kg'], ['2006', 'world amateur championship', 'new delhi , india', '1st', '60 kg'], ['2007', 'european amateur championships', 'vejle , denmark', '1st', '60 kg'], ['2...
fred astaire chronology of performances
https://en.wikipedia.org/wiki/Fred_Astaire_chronology_of_performances
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15186990-4.html.csv
count
in three of fred astaire 's performances , he played the role of guy holden .
{'scope': 'all', 'criterion': 'equal', 'value': 'guy holden', 'result': '3', 'col': '3', 'subset': None}
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'role', 'guy holden'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose role record fuzzily matches to guy holden .', 'tostr': 'filter_eq { all_rows ; role ; guy holden }'}], 'result': '3', 'ind': 1, 'tostr': 'c...
eq { count { filter_eq { all_rows ; role ; guy holden } } ; 3 } = true
select the rows whose role record fuzzily matches to guy holden . 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, 'role_5': 5, 'guy holden_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', 'role_5': 'role', 'guy holden_6': 'guy holden', '3_7': '3'}
{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'role_5': [0], 'guy holden_6': [0], '3_7': [2]}
['date', 'theatre , studio , or network', 'role', 'dance partner', 'director']
[['june 3 , 1931', 'new amsterdam', 'himself', 'adele astaire tilly losch', 'hassard short'], ['nov 29 1932', 'ethel barrymore', 'guy holden', 'claire luce', 'howard lindsay'], ['nov 2 1933', 'palace', 'guy holden', 'claire luce', 'felix edwardes'], ['dec 2 , 1933', 'mgm', 'himself', 'joan crawford', 'robert z leonard'...
three rivers conference ( indiana )
https://en.wikipedia.org/wiki/Three_Rivers_Conference_%28Indiana%29
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15176211-1.html.csv
majority
the majority of schools in the three rivers conference have an aa ihsaa class .
{'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'aa', 'subset': None}
{'func': 'most_str_eq', 'args': ['all_rows', 'ihsaa class', 'aa'], 'result': True, 'ind': 0, 'tointer': 'for the ihsaa class records of all rows , most of them fuzzily match to aa .', 'tostr': 'most_eq { all_rows ; ihsaa class ; aa } = true'}
most_eq { all_rows ; ihsaa class ; aa } = true
for the ihsaa class records of all rows , most of them fuzzily match to aa .
1
1
{'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'ihsaa class_3': 3, 'aa_4': 4}
{'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'ihsaa class_3': 'ihsaa class', 'aa_4': 'aa'}
{'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'ihsaa class_3': [0], 'aa_4': [0]}
['school', 'location', 'mascot', 'enrollment', 'ihsaa class', 'county', 'year joined', 'previous conference']
[['manchester', 'north manchester', 'squires', '434', 'aa', '85 wabash', '1976', 'northern lakes'], ['northfield', 'wabash', 'norsemen', '380', 'aa', '85 wabash', '1971', 'none ( new school )'], ['north miami', 'denver', 'warriors', '348', 'a', '52 miami', '1971', 'mid - indiana'], ['rochester community', 'rochester', ...
mikael pernfors
https://en.wikipedia.org/wiki/Mikael_Pernfors
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1828774-4.html.csv
majority
in almost all of the matches mikael perfors played on a had surface , he was the winner of the match .
{'scope': 'subset', 'col': '1', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'winner', 'subset': {'col': '4', 'criterion': 'fuzzily_match', 'value': 'hard'}}
{'func': 'most_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'surface', 'hard'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; surface ; hard }', 'tointer': 'select the rows whose surface record fuzzily matches to hard .'}, 'outcome', 'winner'], 'result': True, 'ind': 1, 'tointer': 'sele...
most_eq { filter_eq { all_rows ; surface ; hard } ; outcome ; winner } = true
select the rows whose surface record fuzzily matches to hard . for the outcome records of these rows , most of them fuzzily match to winner .
2
2
{'most_str_eq_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, 'surface_4': 4, 'hard_5': 5, 'outcome_6': 6, 'winner_7': 7}
{'most_str_eq_1': 'most_str_eq', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'surface_4': 'surface', 'hard_5': 'hard', 'outcome_6': 'outcome', 'winner_7': 'winner'}
{'most_str_eq_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'surface_4': [0], 'hard_5': [0], 'outcome_6': [1], 'winner_7': [1]}
['outcome', 'date', 'championship', 'surface', 'opponent in the final', 'score in the final']
[['runner - up', '26 may 1986', 'french open , paris , france', 'clay', 'ivan lendl', '3 - 6 , 2 - 6 , 4 - 6'], ['runner - up', '15 february 1988', 'memphis , usa', 'hard ( i )', 'andre agassi', '4 - 6 , 4 - 6 , 5 - 7'], ['winner', '19 september 1988', 'los angeles , usa', 'hard', 'andre agassi', '6 - 2 , 7 - 5'], ['wi...
1983 formula one season
https://en.wikipedia.org/wiki/1983_Formula_One_season
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1140074-2.html.csv
comparative
in the 1983 formula one season , the italian grand prix took place 14 days before the european grand prix .
{'row_1': '13', 'row_2': '14', 'col': '3', 'col_other': '2', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None}
{'func': 'less', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'race', 'italian grand prix'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose race record fuzzily matches to italian grand prix .', 'tostr': 'filter_eq { all_rows ; race ; italian grand prix }'}, 'date'], ...
less { hop { filter_eq { all_rows ; race ; italian grand prix } ; date } ; hop { filter_eq { all_rows ; race ; european grand prix } ; date } } = true
select the rows whose race record fuzzily matches to italian grand prix . take the date record of this row . select the rows whose race record fuzzily matches to european grand prix . take the date record of this row . the first record is less than the second record .
5
5
{'less_4': 4, 'result_5': 5, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'race_7': 7, 'italian grand prix_8': 8, 'date_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'race_11': 11, 'european grand prix_12': 12, 'date_13': 13}
{'less_4': 'less', 'result_5': 'true', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'race_7': 'race', 'italian grand prix_8': 'italian grand prix', 'date_9': 'date', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'race_11': 'race', 'europe...
{'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'race_7': [0], 'italian grand prix_8': [0], 'date_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'race_11': [1], 'european grand prix_12': [1], 'date_13': [3]}
['rnd', 'race', 'date', 'location', 'pole position', 'fastest lap', 'race winner', 'constructor', 'report']
[['1', 'brazilian grand prix', '13 march', 'jacarepaguá', 'keke rosberg', 'nelson piquet', 'nelson piquet', 'brabham - bmw', 'report'], ['2', 'united states grand prix west', '27 march', 'long beach', 'patrick tambay', 'niki lauda', 'john watson', 'mclaren - ford', 'report'], ['3', 'french grand prix', '17 april', 'pau...
budjak
https://en.wikipedia.org/wiki/Budjak
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1138646-1.html.csv
ordinal
in budjak , more people live in the city of izmayil ( 85100 ) than any other district or city .
{'row': '10', 'col': '2', 'order': '1', 'col_other': '1', 'max_or_min': 'max_to_min', 'value_mentioned': 'yes', 'scope': 'all', 'subset': None}
{'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'nth_max', 'args': ['all_rows', 'total', '1'], 'result': '85100', 'ind': 0, 'tostr': 'nth_max { all_rows ; total ; 1 }', 'tointer': 'the 1st maximum total record of all rows is 85100 .'}, '85100'], 'result': True, 'ind': 1, 'tostr': 'eq { nth_max { all_rows ; to...
and { eq { nth_max { all_rows ; total ; 1 } ; 85100 } ; eq { hop { nth_argmax { all_rows ; total ; 1 } ; raion ( district ) or city } ; city of izmayil } } = true
the 1st maximum total record of all rows is 85100 . the raion ( district ) or city record of the row with 1st maximum total record is city of izmayil .
6
6
{'and_5': 5, 'result_6': 6, 'eq_1': 1, 'nth_max_0': 0, 'all_rows_7': 7, 'total_8': 8, '1_9': 9, '85100_10': 10, 'str_eq_4': 4, 'str_hop_3': 3, 'nth_argmax_2': 2, 'all_rows_11': 11, 'total_12': 12, '1_13': 13, 'raion (district) or city_14': 14, 'city of izmayil_15': 15}
{'and_5': 'and', 'result_6': 'true', 'eq_1': 'eq', 'nth_max_0': 'nth_max', 'all_rows_7': 'all_rows', 'total_8': 'total', '1_9': '1', '85100_10': '85100', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'nth_argmax_2': 'nth_argmax', 'all_rows_11': 'all_rows', 'total_12': 'total', '1_13': '1', 'raion (district) or city_14'...
{'and_5': [6], 'result_6': [], 'eq_1': [5], 'nth_max_0': [1], 'all_rows_7': [0], 'total_8': [0], '1_9': [0], '85100_10': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'nth_argmax_2': [3], 'all_rows_11': [2], 'total_12': [2], '1_13': [2], 'raion (district) or city_14': [3], 'city of izmayil_15': [4]}
['raion ( district ) or city', 'total', 'ukrainians', 'moldovans', 'bessarabian bulgarians', 'russians', 'gagauzians', 'other ethnic groups square']
[['artsyzskyi raion', '51700', '14200', '3300', '20200', '11500', '900', '1600'], ['bilhorod - dnistrovskyi raion', '62300', '51000', '3900', '800', '5500', '200', '900'], ['bolhradskyi raion', '75000', '5700', '1200', '45600', '6000', '14000', '2500'], ['izmayilskyi raion', '54700', '15800', '15100', '14100', '8900', ...
fantasy black channel
https://en.wikipedia.org/wiki/Fantasy_Black_Channel
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17637041-2.html.csv
superlative
the last time that fantasy black channel was released in 2008 was on september 4 , 2008 .
{'scope': 'subset', 'col_superlative': '2', 'row_superlative': '4', 'value_mentioned': 'yes', 'max_or_min': 'max', 'other_col': 'n/a', 'subset': {'col': '2', 'criterion': 'fuzzily_match', 'value': '2008'}}
{'func': 'eq', 'args': [{'func': 'max', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', '2008'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; date ; 2008 }', 'tointer': 'select the rows whose date record fuzzily matches to 2008 .'}, 'date'], 'result': '4 september 2008', 'ind': 1, 'tostr':...
eq { max { filter_eq { all_rows ; date ; 2008 } ; date } ; 4 september 2008 } = true
select the rows whose date record fuzzily matches to 2008 . the maximum date record of these rows is 4 september 2008 .
3
3
{'eq_2': 2, 'result_3': 3, 'max_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'date_5': 5, '2008_6': 6, 'date_7': 7, '4 september 2008_8': 8}
{'eq_2': 'eq', 'result_3': 'true', 'max_1': 'max', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'date_5': 'date', '2008_6': '2008', 'date_7': 'date', '4 september 2008_8': '4 september 2008'}
{'eq_2': [3], 'result_3': [], 'max_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'date_5': [0], '2008_6': [0], 'date_7': [1], '4 september 2008_8': [2]}
['region', 'date', 'label', 'format ( s )', 'catalog']
[['japan', '30 july 2008', 'toshiba emi', 'cd', 'tocp - 66797'], ['united kingdom and ireland', '4 august 2008', 'parlophone', 'lp', '228 0331'], ['united kingdom and ireland', '11 august 2008', 'parlophone', 'cd , digital download', '228 0342'], ['france', '4 september 2008', 'because music', 'cd', 'bec 5772361'], ['u...
kslt
https://en.wikipedia.org/wiki/KSLT
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10044708-2.html.csv
majority
all of the kslt radio channels belong to the d broadcast station class .
{'scope': 'all', 'col': '5', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'd', 'subset': None}
{'func': 'all_str_eq', 'args': ['all_rows', 'class', 'd'], 'result': True, 'ind': 0, 'tointer': 'for the class records of all rows , all of them fuzzily match to d .', 'tostr': 'all_eq { all_rows ; class ; d } = true'}
all_eq { all_rows ; class ; d } = true
for the class records of all rows , all of them fuzzily match to d .
1
1
{'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'class_3': 3, 'd_4': 4}
{'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'class_3': 'class', 'd_4': 'd'}
{'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'class_3': [0], 'd_4': [0]}
['call sign', 'frequency mhz', 'city of license', 'erp w', 'class', 'fcc info']
[['k276dl', '103.1', 'hemingford , nebraska', '80', 'd', 'fcc'], ['k276dm', '103.1', 'chadron , nebraska', '5', 'd', 'fcc'], ['k292ec', '106.3', 'hot springs , south dakota', '68', 'd', 'fcc'], ['k292dn', '106.3', 'newcastle , wyoming', '31', 'd', 'fcc'], ['k292dz', '106.3', 'sheridan , wyoming', '135', 'd', 'fcc'], ['...
the midlands , england
https://en.wikipedia.org/wiki/The_Midlands%2C_England
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-184077-2.html.csv
majority
most of the clubs in the midlands , england play in the aviva premiership league .
{'scope': 'all', 'col': '2', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'aviva premiership', 'subset': None}
{'func': 'most_str_eq', 'args': ['all_rows', 'league', 'aviva premiership'], 'result': True, 'ind': 0, 'tointer': 'for the league records of all rows , most of them fuzzily match to aviva premiership .', 'tostr': 'most_eq { all_rows ; league ; aviva premiership } = true'}
most_eq { all_rows ; league ; aviva premiership } = true
for the league records of all rows , most of them fuzzily match to aviva premiership .
1
1
{'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'league_3': 3, 'aviva premiership_4': 4}
{'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'league_3': 'league', 'aviva premiership_4': 'aviva premiership'}
{'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'league_3': [0], 'aviva premiership_4': [0]}
['club', 'league', 'city / town', 'stadium', 'capacity']
[['leicester tigers', 'aviva premiership', 'leicester', 'welford road', '24000'], ['northampton saints', 'aviva premiership', 'northampton', "franklin 's gardens", '13600'], ['worcester warriors', 'aviva premiership', 'worcester', 'sixways stadium', '12068'], ['moseley', 'rfu championship', 'birmingham', 'billesley com...
anna thompson ( athlete )
https://en.wikipedia.org/wiki/Anna_Thompson_%28athlete%29
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17218317-1.html.csv
aggregation
anna thompson averaged at 10.15 th place across all the given tournaments .
{'scope': 'all', 'col': '4', 'type': 'average', 'result': '10.15 th', 'subset': None}
{'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'result'], 'result': '10.15 th', 'ind': 0, 'tostr': 'avg { all_rows ; result }'}, '10.15 th'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; result } ; 10.15 th } = true', 'tointer': 'the average of the result record of all rows is 10....
round_eq { avg { all_rows ; result } ; 10.15 th } = true
the average of the result record of all rows is 10.15 th .
2
2
{'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'result_4': 4, '10.15th_5': 5}
{'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'result_4': 'result', '10.15th_5': '10.15 th'}
{'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'result_4': [0], '10.15th_5': [1]}
['year', 'tournament', 'venue', 'result', 'extra']
[['2002', 'commonwealth games', 'manchester , england', '9th', '5000 m'], ['2002', 'world cross country championships', 'dublin , ireland', '15th', 'short race'], ['2002', 'world cross country championships', 'dublin , ireland', '5th', 'team competition'], ['2005', 'world cross country championships', 'st etienne , fra...
1939 vfl season
https://en.wikipedia.org/wiki/1939_VFL_season
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10806852-6.html.csv
superlative
the game played between carlton and richmond in round 6 of the 1939 vfl season had the highest attendance of all the games played in that round .
{'scope': 'all', 'col_superlative': '6', 'row_superlative': '3', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1,3', 'subset': None}
{'func': 'and', 'args': [{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'crowd'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; crowd }'}, 'home team'], 'result': 'carlton', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; crowd } ; home team }'}, 'carlton'], 're...
and { eq { hop { argmax { all_rows ; crowd } ; home team } ; carlton } ; eq { hop { argmax { all_rows ; crowd } ; away team } ; richmond } } = true
select the row whose crowd record of all rows is maximum . the home team record of this row is carlton . the away team record of this row is richmond .
7
6
{'and_5': 5, 'result_6': 6, 'str_eq_2': 2, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_7': 7, 'crowd_8': 8, 'home team_9': 9, 'carlton_10': 10, 'str_eq_4': 4, 'str_hop_3': 3, 'away team_11': 11, 'richmond_12': 12}
{'and_5': 'and', 'result_6': 'true', 'str_eq_2': 'str_eq', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_7': 'all_rows', 'crowd_8': 'crowd', 'home team_9': 'home team', 'carlton_10': 'carlton', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'away team_11': 'away team', 'richmond_12': 'richmond'}
{'and_5': [6], 'result_6': [], 'str_eq_2': [5], 'str_hop_1': [2], 'argmax_0': [1, 3], 'all_rows_7': [0], 'crowd_8': [0], 'home team_9': [1], 'carlton_10': [2], 'str_eq_4': [5], 'str_hop_3': [4], 'away team_11': [3], 'richmond_12': [4]}
['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date']
[['melbourne', '19.23 ( 137 )', 'south melbourne', '3.12 ( 30 )', 'mcg', '16523', '27 may 1939'], ['collingwood', '14.14 ( 98 )', 'hawthorn', '12.7 ( 79 )', 'victoria park', '15000', '27 may 1939'], ['carlton', '8.13 ( 61 )', 'richmond', '9.14 ( 68 )', 'princes park', '34000', '27 may 1939'], ['st kilda', '16.18 ( 114 ...
world tourism rankings
https://en.wikipedia.org/wiki/World_Tourism_rankings
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14752049-4.html.csv
superlative
of the ten top-ranked countries in world tourism , uruguay saw the highest percentage growth of tourist arrivals from 2010 to 2011 .
{'scope': 'all', 'col_superlative': '6', 'row_superlative': '10', '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', 'change ( 2010 to 2011 )'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; change ( 2010 to 2011 ) }'}, 'country'], 'result': 'uruguay', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; change ( 2010 to 2011 ) } ; cou...
eq { hop { argmax { all_rows ; change ( 2010 to 2011 ) } ; country } ; uruguay } = true
select the row whose change ( 2010 to 2011 ) record of all rows is maximum . the country record of this row is uruguay .
3
3
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'change (2010 to 2011)_5': 5, 'country_6': 6, 'uruguay_7': 7}
{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'change (2010 to 2011)_5': 'change ( 2010 to 2011 )', 'country_6': 'country', 'uruguay_7': 'uruguay'}
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'change (2010 to 2011)_5': [0], 'country_6': [1], 'uruguay_7': [2]}
['rank', 'country', 'international tourist arrivals ( 2012 )', 'international tourist arrivals ( 2011 )', 'change ( 2011 to 2012 )', 'change ( 2010 to 2011 )']
[['1', 'united states', '67.0 million', '62.7 million', '+ 6.8 %', '+ 4.9 %'], ['2', 'mexico', '23.4 million', '23.4 million', '+ 0.0 %', '+ 0.5 %'], ['3', 'canada', '16.3 million', '16.0 million', '+ 1.8 %', '- 1.3 %'], ['4', 'brazil', '5.6 million', '5.4 million', '+ 4.5 %', '+ 5.3 %'], ['5', 'argentina', '5.5 millio...
ken schrader
https://en.wikipedia.org/wiki/Ken_Schrader
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1671401-2.html.csv
superlative
the highest amount of earnings for ken schrader came in the year 2006 .
{'scope': 'all', 'col_superlative': '9', 'row_superlative': '15', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None}
{'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'winnings'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; winnings }'}, 'year'], 'result': '2006', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; winnings } ; year }'}, '2006'], 'result': True, 'ind': 2, 'tostr': 'eq ...
eq { hop { argmax { all_rows ; winnings } ; year } ; 2006 } = true
select the row whose winnings record of all rows is maximum . the year record of this row is 2006 .
3
3
{'eq_2': 2, 'result_3': 3, 'num_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'winnings_5': 5, 'year_6': 6, '2006_7': 7}
{'eq_2': 'eq', 'result_3': 'true', 'num_hop_1': 'num_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'winnings_5': 'winnings', 'year_6': 'year', '2006_7': '2006'}
{'eq_2': [3], 'result_3': [], 'num_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'winnings_5': [0], 'year_6': [1], '2006_7': [2]}
['year', 'starts', 'wins', 'top 5', 'top 10', 'poles', 'avg start', 'avg finish', 'winnings', 'position', 'team ( s )']
[['1987', '1', '0', '1', '1', '0', '21.0', '5.0', '1825', '83rd', 'ken schrader racing'], ['1988', '10', '0', '2', '3', '0', '16.3', '20.1', '45175', '33rd', 'ken schrader racing'], ['1989', '11', '1', '1', '6', '1', '14.3', '17.6', '27577', '32nd', 'ken schrader racing hendrick motorsports'], ['1990', '11', '0', '1', ...
northern indiana athletic conference
https://en.wikipedia.org/wiki/Northern_Indiana_Athletic_Conference
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12264570-1.html.csv
ordinal
the third to last team to join the northern indiana athletic conference was south bend clay .
{'row': '6', 'col': '6', 'order': '3', 'col_other': '1', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None}
{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'joined', '3'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; joined ; 3 }'}, 'school'], 'result': 'south bend clay', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; joined ; 3 } ; school }'}, 'south ben...
eq { hop { nth_argmax { all_rows ; joined ; 3 } ; school } ; south bend clay } = true
select the row whose joined record of all rows is 3rd maximum . the school record of this row is south bend clay .
3
3
{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'joined_5': 5, '3_6': 6, 'school_7': 7, 'south bend clay_8': 8}
{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'joined_5': 'joined', '3_6': '3', 'school_7': 'school', 'south bend clay_8': 'south bend clay'}
{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'joined_5': [0], '3_6': [0], 'school_7': [1], 'south bend clay_8': [2]}
['school', 'location', 'mascot', 'county', 'enrollment ihsaa class', 'joined', 'previous conference']
[['elkhart central', 'elkhart', 'blue blazers', '20 elkhart', '1747 aaaa', '1927', 'independents'], ['mishawaka', 'mishawaka', 'cavemen', '71 st joseph', '1761 aaaa', '1927', 'independents'], ['mishawaka marian', 'mishawaka', 'knights', '71 st joseph', '768 aaa', '2005', 'independents'], ['penn', 'mishawaka', 'kingsmen...
international rankings of iran
https://en.wikipedia.org/wiki/International_rankings_of_Iran
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15733308-7.html.csv
comparative
the happy planet index ranked three points higher than the environmental performance index in the international rankings of iran .
{'row_1': '4', 'row_2': '5', 'col': '2', 'col_other': '1', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None}
{'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'name', 'happy planet index'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose name record fuzzily matches to happy planet index .', 'tostr': 'filter_eq { all_rows ; name ; happy planet index }'}, 'rank'...
greater { hop { filter_eq { all_rows ; name ; happy planet index } ; rank } ; hop { filter_eq { all_rows ; name ; environmental performance index } ; rank } } = true
select the rows whose name record fuzzily matches to happy planet index . take the rank record of this row . select the rows whose name record fuzzily matches to environmental performance index . take the rank record of this row . the first record is greater than the second record .
5
5
{'greater_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'name_7': 7, 'happy planet index_8': 8, 'rank_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'name_11': 11, 'environmental performance index_12': 12, 'rank_13': 13}
{'greater_4': 'greater', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'name_7': 'name', 'happy planet index_8': 'happy planet index', 'rank_9': 'rank', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'name_11': 'name', '...
{'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'name_7': [0], 'happy planet index_8': [0], 'rank_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'name_11': [1], 'environmental performance index_12': [1], 'rank_13': [3]}
['name', 'rank', 'out of', 'source', 'year']
[['environmental sustainability index', '132', '146', 'yale university', '2005'], ['greenhouse emissions per capita', '74', 'world', 'world resources institute', '2000'], ['number of species under threat of extinction', '37', '158', 'united nations', '1999'], ['happy planet index', '81', '178', 'new economics foundatio...
national technical university of athens
https://en.wikipedia.org/wiki/National_Technical_University_of_Athens
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1064216-1.html.csv
ordinal
the school that has 18 lecturers has the 2nd highest number of total professors .
{'row': '5', 'col': '5', 'order': '2', 'col_other': '1', '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', 'total', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; total ; 2 }'}, 'lecturers'], 'result': '18', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; total ; 2 } ; lecturers }'}, '18'], 'result': True, '...
eq { hop { nth_argmax { all_rows ; total ; 2 } ; lecturers } ; 18 } = true
select the row whose total record of all rows is 2nd maximum . the lecturers record of this row is 18 .
3
3
{'eq_2': 2, 'result_3': 3, 'num_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'total_5': 5, '2_6': 6, 'lecturers_7': 7, '18_8': 8}
{'eq_2': 'eq', 'result_3': 'true', 'num_hop_1': 'num_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'total_5': 'total', '2_6': '2', 'lecturers_7': 'lecturers', '18_8': '18'}
{'eq_2': [3], 'result_3': [], 'num_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'total_5': [0], '2_6': [0], 'lecturers_7': [1], '18_8': [2]}
['lecturers', 'associate professors', 'assistant professors', 'professors', 'total']
[['5', '35', '27', '40', '120'], ['9', '10', '8', '58', '96'], ['12', '16', '17', '23', '81'], ['5', '12', '8', '20', '55'], ['18', '20', '9', '34', '119'], ['6', '13', '10', '48', '78'], ['7', '14', '5', '15', '49'], ['4', '10', '9', '14', '51'], ['2', '4', '8', '14', '28']]
fiat albea
https://en.wikipedia.org/wiki/Fiat_Albea
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1415652-1.html.csv
majority
all fiat albea with 16 v engine has a power of at4000 rpm at least .
{'scope': 'subset', 'col': '4', 'most_or_all': 'all', 'criterion': 'greater_than_eq', 'value': 'at4000 rpm', 'subset': {'col': '1', 'criterion': 'equal', 'value': '16 v'}}
{'func': 'all_greater_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'engine', '16 v'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; engine ; 16 v }', 'tointer': 'select the rows whose engine record fuzzily matches to 16 v .'}, 'power', 'at4000 rpm'], 'result': True, 'ind': 1, 'tointer': 'se...
all_greater_eq { filter_eq { all_rows ; engine ; 16 v } ; power ; at4000 rpm } = true
select the rows whose engine record fuzzily matches to 16 v . for the power records of these rows , all of them are greater than or equal to at4000 rpm .
2
2
{'all_greater_eq_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, 'engine_4': 4, '16 v_5': 5, 'power_6': 6, 'at4000 rpm_7': 7}
{'all_greater_eq_1': 'all_greater_eq', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'engine_4': 'engine', '16 v_5': '16 v', 'power_6': 'power', 'at4000 rpm_7': 'at4000 rpm'}
{'all_greater_eq_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'engine_4': [0], '16 v_5': [0], 'power_6': [1], 'at4000 rpm_7': [1]}
['engine', 'type', 'displacement', 'power', 'torque']
[['1.2 8v sohc', 'i4', '1242 cc', 'at5000 rpm', 'at2500 rpm'], ['1.2 16v dohc', 'i4', '1242 cc', 'at5000 rpm', 'at4000 rpm'], ['1.4 8v sohc', 'i4', '1368 cc', 'at6000 rpm', 'at3000 rpm'], ['1.6 16v dohc', 'i4', '1596 cc', 'at5750 rpm', 'at4000 rpm'], ['1.3 16v multijet', 'i4', '1248 cc', 'at4000 rpm', 'at1500 rpm']]
harry hinton
https://en.wikipedia.org/wiki/Harry_Hinton
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16877441-3.html.csv
aggregation
the average number of points for harry hinton was two .
{'scope': 'all', 'col': '4', 'type': 'average', 'result': '2', 'subset': None}
{'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'points'], 'result': '2', 'ind': 0, 'tostr': 'avg { all_rows ; points }'}, '2'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; points } ; 2 } = true', 'tointer': 'the average of the points record of all rows is 2 .'}
round_eq { avg { all_rows ; points } ; 2 } = true
the average of the points record of all rows is 2 .
2
2
{'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'points_4': 4, '2_5': 5}
{'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'points_4': 'points', '2_5': '2'}
{'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'points_4': [0], '2_5': [1]}
['year', 'class', 'team', 'points', 'wins']
[['1949', '350cc', 'norton', '0', '0'], ['1949', '500cc', 'norton', '0', '0'], ['1950', '350cc', 'norton', '9', '0'], ['1950', '500cc', 'norton', '5', '0'], ['1951', '350cc', 'norton', '0', '0'], ['1958', '350cc', 'velocette', '0', '0'], ['1958', '500cc', 'norton', '0', '0']]
henri leconte
https://en.wikipedia.org/wiki/Henri_Leconte
https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1171445-5.html.csv
unique
the only time henri leconte played in the us was in memphis .
{'scope': 'all', 'row': '4', 'col': '3', 'col_other': 'n/a', 'criterion': 'equal', 'value': 'memphis , us', 'subset': None}
{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'championship', 'memphis , us'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose championship record fuzzily matches to memphis , us .', 'tostr': 'filter_eq { all_rows ; championship ; memphis , us }'}], 'result': True, 'ind': 1, 'tost...
only { filter_eq { all_rows ; championship ; memphis , us } } = true
select the rows whose championship record fuzzily matches to memphis , us . there is only one such row in the table .
2
2
{'only_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, 'championship_4': 4, 'memphis, us_5': 5}
{'only_1': 'only', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'championship_4': 'championship', 'memphis, us_5': 'memphis , us'}
{'only_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'championship_4': [0], 'memphis, us_5': [0]}
['outcome', 'date', 'championship', 'surface', 'opponent in the final', 'score in the final']
[['winner', '1982', 'stockholm , sweden', 'hard ( i )', 'mats wilander', '7 - 6 ( 4 ) , 6 - 3'], ['runner - up', '1983', 'kitzbühel , austria', 'clay', 'guillermo vilas', '6 - 7 , 6 - 4 , 4 - 6'], ['runner - up', '1983', 'sydney indoor , australia', 'hard ( i )', 'john mcenroe', '1 - 6 , 4 - 6 , 5 - 7'], ['runner - up'...
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
unique
game number 10 was the only game where the location was the wachovia center .
{'scope': 'all', 'row': '9', 'col': '7', 'col_other': '1', 'criterion': 'equal', 'value': 'wachovia center', 'subset': None}
{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location attendance', 'wachovia center'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose location attendance record fuzzily matches to wachovia center .', 'tostr': 'filter_eq { all_rows ; location attendance ...
and { only { filter_eq { all_rows ; location attendance ; wachovia center } } ; eq { hop { filter_eq { all_rows ; location attendance ; wachovia center } ; game } ; 10 } } = true
select the rows whose location attendance record fuzzily matches to wachovia center . there is only one such row in the table . the game record of this unqiue row is 10 .
6
5
{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'location attendance_7': 7, 'wachovia center_8': 8, 'eq_3': 3, 'num_hop_2': 2, 'game_9': 9, '10_10': 10}
{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'location attendance_7': 'location attendance', 'wachovia center_8': 'wachovia center', 'eq_3': 'eq', 'num_hop_2': 'num_hop', 'game_9': 'game', '10_10': '10'}
{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'location attendance_7': [0], 'wachovia center_8': [0], 'eq_3': [4], 'num_hop_2': [3], 'game_9': [2], '10_10': [3]}
['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...